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Peer-reviewed

Research Article

Mapping Global Diversity Patterns for Migratory Birds

* E-mail: [email protected]

Affiliations Department of Zoology, University of Cambridge, Cambridge, United Kingdom, Centre d’Ecologie Fonctionnelle et Evolutive, CNRS-CEFE UMR5175, Montpellier, France

Affiliation Department of Zoology, University of Cambridge, Cambridge, United Kingdom

Affiliation BirdLife International, Wellbrook Court, Cambridge, United Kingdom

Affiliation Centre d’Ecologie Fonctionnelle et Evolutive, CNRS-CEFE UMR5175, Montpellier, France

• Marius Somveille, 
• Andrea Manica, 
• Stuart H. M. Butchart, 
• Ana S. L. Rodrigues

• Published: August 7, 2013
• https://doi.org/10.1371/journal.pone.0070907
• Reader Comments

Nearly one in five bird species has separate breeding and overwintering distributions, and the regular migrations of these species cause a substantial seasonal redistribution of avian diversity across the world. However, despite its ecological importance, bird migration has been largely ignored in studies of global avian biodiversity, with few studies having addressed it from a macroecological perspective. Here, we analyse a dataset on the global distribution of the world’s birds in order to examine global spatial patterns in the diversity of migratory species, including: the seasonal variation in overall species diversity due to migration; the contribution of migratory birds to local bird diversity; and the distribution of narrow-range and threatened migratory birds. Our analyses reveal a striking asymmetry between the Northern and Southern hemispheres, evident in all of the patterns investigated. The highest migratory bird diversity was found in the Northern Hemisphere, with high inter-continental turnover in species composition between breeding and non-breeding seasons, and extensive regions (at high latitudes) where migratory birds constitute the majority of the local avifauna. Threatened migratory birds are concentrated mainly in Central and Southern Asia, whereas narrow-range migratory species are mainly found in Central America, the Himalayas and Patagonia. Overall, global patterns in the diversity of migratory birds indicate that bird migration is mainly a Northern Hemisphere phenomenon. The asymmetry between the Northern and Southern hemispheres could not have easily been predicted from the combined results of regional scale studies, highlighting the importance of a global perspective.

Citation: Somveille M, Manica A, Butchart SHM, Rodrigues ASL (2013) Mapping Global Diversity Patterns for Migratory Birds. PLoS ONE 8(8): e70907. https://doi.org/10.1371/journal.pone.0070907

Editor: Tapio Mappes, University of Jyväskylä, Finland

Received: March 1, 2013; Accepted: June 24, 2013; Published: August 7, 2013

Copyright: © 2013 Somveille et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: The authors have no support or funding to report.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Bird migration is a phenomenon that has long fascinated scientists and other observers. An estimated 1,855 bird species (19% of extant species) are migratory, making regular cyclical movements beyond their breeding distribution, with predictable timing and destinations [1] . Much attention has been devoted to bird migration, as exemplified by the nearly 2800 references cited in a recent book on the subject [2] , and the 4539 articles in the Web of Science under the topic “bird migration”. This extensive literature has concentrated on aspects such as the behavioural adaptations of migration (e.g. [3] ), the evolution of migration (e.g. [4] ) and the conservation status of migratory species (e.g. [1] ). However, very few studies have investigated bird migration using a macroecological approach.

Macroecology, the study of broad-scale spatial patterns in biodiversity [5] , has developed considerably in recent years, and as one of the better-studied taxonomic groups, birds have had a key role in this development. From continental to global scales, bird data have been used to investigate, for example: drivers of species richness patterns [6] , [7] ; the global distributions of range sizes [8] and body sizes [9] , the spatial turnover in species [10] , and species extinction risk [11] ; and the congruence between richness and endemism [12] , [13] . However, despite this extensive body of work, most macroecological studies considered bird species only in their breeding distributions. Very few have addressed one of the most striking features of avian biogeography: the fact that, for a substantial proportion of the species, distributions vary seasonally, and accordingly so do macroecological patterns. The few previous studies that have analysed bird migration from a macroecological perspective (see Appendix S1 for a review), focus mainly on Europe and North America, and often analyse just a subset of the local bird community (e.g. only breeding species; Table S1 in Appendix S1 ). None are global in scale, and only two span the equator. Nonetheless, these studies reveal some macroecological patterns, in particular an increase in the absolute numbers and in the proportion of migratory species with latitude and increasing climatic seasonality (e.g. [14] – [19] ).

We investigated whether these regional patterns can generalise to the global scale by mapping global patterns in the diversity of migratory birds. We used a newly released dataset of digital distribution maps for the world’s birds [20] , in which breeding and non-breeding ranges are mapped separately. We mapped global spatial patterns in the seasonal variation in species richness due to migration, the diversity of migratory species, the contribution of migratory birds to local bird diversity, the distribution of narrow-range migratory birds, and of threatened migratory birds. The last two have never (to our knowledge) been investigated, and the first three had only been previously assessed through taxonomically and/or regionally restricted studies. Information on the global distribution of these features of avian communities could shed light on how avian communities are structured, and in particular how they adjust to seasonal environments in high latitudes, with many species vacating during the winter and visiting to exploit the food supply during the summer.

Materials and Methods

Spatial data.

Data on the distribution of bird species were derived from BirdLife International and NatureServe (2011) [20] , a global dataset compiled as part of the International Union for Nature Conservation (IUCN) Red List assessments for birds [21] . This dataset comprised Geographic Information System (GIS) shapefiles of the distributions of all 9783 extant bird species whose distributions are known. These distribution polygons represent moderately coarse generalizations of species’ distributions derived from the locations of known records, with interpolation by experts (see [22] for further details). Polygons were coded according to species’ presence (1– extant; 2– probably extant; 3– possibly extant; 4– possibly extinct; 5– extinct), origin (1– native; 2– reintroduced; 3– introduced; 4– vagrant; 5– origin uncertain) and seasonality (1– resident; 2– breeding season; 3– non-breeding season; 4– passage; 5– seasonal occurrence uncertain). In this analysis, only polygons coded as presence 1 or 2, origin 1 or 2, and seasonality 1, 2 or 3 were included.

For the purpose of the present study, migratory species were defined as those mapped with at least one polygon coded as breeding or non-breeding (seasonality 2 or 3; some such species also had polygons coded as seasonality 1 for resident populations). Hence, this analysis focuses on species whose annual movements result in predictable, large-scale, changes in bird diversity. It does not cover other forms of migration, such as partial migration (in which only a proportion of a population migrates while the rest remain as residents; [1] , [23] , fine-scale altitudinal migration (not captured in the maps analysed), differential migration (where migrant individuals comprise just one age-class or sex; [24] , and nomadic or irruptive species (in which the movements are not predictable seasonally or geographically; [1] , [2] . This study concentrated on geographical patterns over land and therefore marine species were excluded from the analysis (but the terrestrial part of coastal species’ distributions was included).

BirdLife International had also coded, in a separate database, the migratory status of each species. As a cross-validation analysis, we checked whether species classified in this database as “full migrants” (those for which a substantial proportion of the global or a regional population makes regular cyclical movements beyond the breeding distribution, with predictable timing and destinations) matched those that we coded as migratory based on the distribution maps. We resolved any discrepancies (either by improving the maps, or by amending the classification in the database). Our analyses were based on the corrected map dataset (which was incorporated into BirdLife International and NatureServe, 2012; available upon request from the website in reference [25] ).

To investigate the temporal variation between seasons in species distribution, while being globally consistent, we focussed on occupancy in two months, January and July, approximating to the middle of the summer season in the Southern and Northern Hemispheres, respectively. For each species, we assigned occupancy during the two focal months to each component of the distribution ( Figure 1 ). For this purpose, we considered all species whose entire distribution falls within latitudes superior to 30° N as breeding in July and non-breeding in January, and vice-versa for species at latitudes superior to 30° S. For the remaining species, we obtained information on their breeding season from the literature (in particular from the Handbook of the Birds of the World collection; [26] ). The few species for which this classification was not applicable were treated for analytical purposes as if they were resident (52 species, mainly tropical). This includes species for which the description of migratory behaviour in the literature was too vague, too conflicting or based on too few observations, as well as species that follow a more complex migration pattern (i.e. partial migrants, differential migrants, nomadic and irruptive species). The non-permanent distribution of each migratory species was defined as the area where the species only occurs seasonally ( Figure 1E ).

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This figure is illustrating: (A) the complete distribution (in brown); (B) subdivision into breeding (red), resident (green) and non-breeding (blue) components; (C) July distribution (including breeding and resident components); (D) January distribution (including non-breeding and resident components); (E) non-permanent distribution (breeding and non-breeding components). Photo by JJ Harrison/Wikimedia Commons.

https://doi.org/10.1371/journal.pone.0070907.g001

Coastline boundaries were obtained from VMAP, a vector-based collection of GIS data collated by the United States National Geospatial-Intelligence Agency ( https://www1.nga.mil/ ). Antarctica was excluded because no land species occur in this part of the world. The spatial units employed in these analyses were equal-area, equal-shape hexagons, obtained from a geodesic discrete global grid system, defined on an icosahedron and projected to the sphere using the inverse Icosahedral Snyder Equal Area (ISEA) Projection [27] . Hexagons with an area of ∼23,322 km 2 (corresponding to an ISEA Aperture 3, resolution 7 hexagon grid), were used in all analyses, for a total of 7604 land hexagons.

We produced eight maps to analyse global diversity patterns in birds:

• A) Total species richness: mapped as the number of all bird species (migratory and non-migratory) whose distributions intersect with each hexagon. This map does not correspond to the real species richness at any particular time, because migratory species are double-counted in their breeding and non-breeding distributions, but represents the variation in the total species pool across regions.
• B) Species richness in January: mapped as the number of bird species (migratory and non-migratory) whose January distributions intersect with each hexagon.
• C) Species richness in July: mapped as the number of bird species (migratory and non-migratory) whose July distributions intersect with each hexagon.
• D) Difference in species richness: mapped as the number of bird species in July (map B) minus the number of bird species in January (map C) in each hexagon. This map represents the change in species richness between the two opposite seasons due to migration.
• E) Total number of non-permanent species (referred hereinafter, for simplicity, as the total number of migratory species): mapped as the number of migratory species whose non-permanent distributions (see Figure 1E ) intersect with each hexagon. This represents the spatial variation in the number of species that are only present in each site during part of the year.
• F) Fraction of non-permanent species (referred hereinafter as the fraction of migratory species): mapped as the number of migratory species whose non-permanent distributions overlap each hexagon (map E) divided by the total number of species (map A). This represents the fraction of the total species pool that is only present during part of the year.
• G) Richness in threatened migratory species: mapped as the number of migratory bird species that are threatened (that is, classified as Vulnerable, Endangered or Critically Endangered according to the IUCN Red List; [21] ), per hexagon. As in Map A, species are counted in both their breeding and non-breeding distributions.
• H) Richness in narrow-range migratory species. Narrow-range migratory species were defined as those in the lower quartile of migratory species in terms of range size (e.g., [28] , and were identified separately for each season (July and January). Separate maps of richness in narrow-range migratory species were then obtained for January and for July, and combined into a final map representing the maximum richness in narrow-range species across seasons.

The global distribution of bird species richness (including both migratory and non-migratory species), is dominated by a concentration of species richness in the tropical regions, especially the tropical Andes in South America, the Eastern Arc mountains of East Africa, and the Himalayan slopes in Asia ( Figure 2A ). The variation in richness between January ( Figure 2B ) and July ( Figure 2C ) is most prominent in the Northern Hemisphere (North America and Eurasia), where species richness is substantially higher in July, but overall this variation is obscured by the magnitude of the latitudinal differences. The seasonal differences become much clearer when mapped directly ( Figure 3A ). The northern part of the Northern Hemisphere is richer in bird species in July than in January, but in the southern part of the Northern Hemisphere, the reverse is true. A transition zone where the difference in species richness between seasons is small or null (mapped as a pale line in Figure 3A ) is found around latitudes 30° to 40° N, crossing North America, the Mediterranean region, Central Asia, the Himalayas and Southern China. In contrast, there is no corresponding transition zone in the Southern Hemisphere. Instead, south of the Northern Hemisphere transition zone, richness is nearly always higher in January, with large seasonal differences in diversity in Central America, South Asia and South-east Asia compared with much smaller seasonal differences in the Sahara, the Arabian Peninsula, South America and Oceania.

https://doi.org/10.1371/journal.pone.0070907.g002

(A) Difference in local species richness between July and January, with positive values (in red) indicating areas that are richer in July, and negative values (in blue) indicating areas that are richer in January; (B) richness in migratory species (i.e., non permanent-species, that are only present seasonally in each area); and (C) the proportion of migratory (non-permanent) species.

https://doi.org/10.1371/journal.pone.0070907.g003

Richness in migratory species is considerably higher in the Northern Hemisphere ( Figure 3B ), with consistently high numbers outside arid regions (Sahara, Arabian Peninsula, Tibetan Plateau) and at high latitudes (Greenland, Northern Russia, Northern Canada). In contrast, richness in migratory species is generally low throughout the Southern Hemisphere. The proportion of migratory species shows a clear latitudinal gradient, increasing towards higher latitudes ( Figure 3C ). There is, however, a strong asymmetry between the two hemispheres, with higher values in the Northern Hemisphere.

The strong asymmetry between hemispheres is most striking when values in the difference in species richness, in the absolute number of migratory species, and in the proportion of migratory species are plotted against latitude ( Figure 4 ). These results are consistent across major migratory flyways (see Appendix S2 ). The difference in local species richness between January and July is rather uniform (slightly negative) at southern latitudes, whereas at northern latitudes it switches between strongly negative values (<100 species, around latitude 20°N) and strongly positive values (>150 species, around 55°N), with a transition zone around 35°N ( Figure 4A ). Richness in migratory species is uniformly lower (<100 species) at southern latitudes, whereas in the Northern Hemisphere it reaches up to 200 species between 20 and 55°N, decreasing sharply towards zero at 80°N. Finally, the proportion of migratory species is generally low south of the equator (generally <25%, with a slight increasing trend towards the south), whereas in northern latitudes there is a constant and marked increase from the equator northwards, reaching 100% around 80°N.

(A) Difference in local species richness between July and January; (B) richness in migratory (non-permanent) species; and (C) proportion of migratory (non-permanent) species.

https://doi.org/10.1371/journal.pone.0070907.g004

Among the species we defined as migratory, 132 are globally threatened ( Figure 5A ). They are mostly concentrated along two parallel bands in Asia, a northern one through Kazakhstan, Mongolia and southern Russia, and a southern band extending from Pakistan, along the Himalayan slopes into southern China and southern Japan, with a smaller concentration in Eastern Africa. Overall, 48% of all threatened migratory species are found in Eurasia, 14% in North America, 12% in South America, 17% in Africa, and 20% in Australasia (the total is larger than 100% because of shared species). Three in every four threatened migratory species also have a narrow range during at least part of the year, particularly those in the Americas and in Australia (see Table S2 in File S2 ).

(A) Richness in threatened migratory species; (B) richness in narrow-range migratory species.

https://doi.org/10.1371/journal.pone.0070907.g005

The majority (76%) of species classified as narrow-range migratory species was qualified as such in both seasons. The criteria of “narrow” was relative to all migratory bird species, rather than to all birds; in absolute terms, narrow-range migratory species (maximum range size 3.3 million km 2 in July and 3 million km 2 in January) have on average substantially wider distributions than narrow-range birds (across all birds “restricted-range species” are defined as those having a breeding distribution size less than 50,000 km 2 [29] . Richness in narrow-range migratory species is highest in Central America, the Himalayas, and also in Patagonia, and to a lesser extent in South-East Asia and North-East Asia ( Figure 5B ). In Central America, Patagonia and South-East Asia, these species are found mainly in January, while in the Himalayas and North-East Asia they occur mainly in July (see Figure S3 in File S1 ).

The results obtained in this study should be interpreted within the context of the limitations in the available data. Species were mapped as polygons that are coarse generalizations of their distribution, and may include relatively extensive areas from which the species is absent, potentially overestimating the species’ true area of occupancy [30] . For some species, finer scale distribution data are available (e.g., [31] ), but the data we used represent the best available dataset for all species globally compiled in a consistent manner, thus minimising the degree to which variations in data quality affect the spatial patterns obtained. Even so, distributions maps for species in Europe and North America are likely to be more accurate than those in other regions. However, such limitations are not expected to significantly affect the global patterns obtained, given the coarse spatial resolution of the analyses (cell area c. 23,322 km 2 ; [32] . Although lower data quality may result in an underestimation of the total number of birds in the tropics and in the Southern Hemisphere, it would be necessary for hundreds of migratory species to be unmapped for the observed asymmetrical patterns to be offset. This is highly unlikely, as birds are the best known class of organisms (with only 69 species, <1%, classified as Data Deficient, compared with 15% for mammals; [21] ). Indeed, lower data quality is likely to minimise rather than exaggerate the observed asymmetry between the northern and southern hemispheres, as coarse distribution maps may overestimate local species richness.

Classification of migratory species was based on the mapped polygons, distinguishing breeding, non-breeding, and resident areas, but this is an oversimplification of the diversity in bird migratory behaviour [33] , excluding partial, differential and nomadic or irruptive migrants. Nonetheless, we probably included nearly all species whose annual movements affect the large-scale spatial patterns of diversity of migratory species investigated here. By treating as resident 52 species with complex migratory behaviour or for which there was uncertainty about their distributions (see methods) our estimates of numbers and proportions of migratory species are conservative.

Our results confirm those of Newton and Dale (1997; [34] ) in that the difference in species richness between summer and winter is positive in the south and negative in the north of the Western Palearctic region, with a transition around 35°N. Although Newton and Dale only examined species that breed in the Western Palearctic, such species correspond to the vast majority of all migrants in the region (given that the Western Palearctic is the northernmost part of the African-Eurasian flyway, and few species occur as non-breeders in the region while breeding elsewhere). We show that this pattern generalises to the entire Palearctic and Nearctic regions as well, but that there is no corresponding pattern in the Southern Hemisphere ( Figure 4A ). Moreover, when juxtaposing the spatial pattern in the difference ( Figure 3A ) with the total number of migratory species ( Figure 3B ), it becomes clear that the transition area around 35°N (with similar numbers of migratory species in July and January) is an area rich in migratory species, corresponding therefore a region of high seasonal species turnover (in contrast, in areas such as the Sahara, Greenland and central Australia, the small differences between July and January are a consequence of the overall low richness in migratory species). This reveals that the strong migration dynamics in the Northern Hemisphere is dominated by intra-continental (rather than inter-continental) movements, with most species migrating between lower and higher latitudes within the hemisphere. In contrast, the slightly negative values observed in the Southern Hemisphere are mainly due to the relatively few long-distance migrants that cross the equator for the non-breeding season, creating a uniform low enrichment of birds in January. Our results confirm that, globally, bird migration is mainly a Northern Hemisphere phenomenon.

We found a hump-shaped relationship between the absolute number of migratory species and latitude in the Northern Hemisphere, with an increase between the equator and 50°N, followed by a decrease towards the North Pole ( Figure 4B ). This pattern is very different from that for the distribution of total avian species richness ( Figure 2A ): bird species in general are concentrated in the tropics, whereas migratory species are concentrated in the northern temperate latitudes. Somewhat unexpectedly, it also differs from the results in previous studies ( [18] , [35] ) which reported a general increase in the absolute number of migratory species with increasing latitude on North America and Europe. The discrepancy may be explained by the fact that these previous studies only looked at the breeding distributions of migratory birds. Indeed, many of the migratory species in the Northern Hemisphere winter in the southern part of this hemisphere, and so high overall numbers of migratory species are also found at relatively low latitudes.

Our study confirms previous results that the proportion of migratory species increases with latitude ( [14] , [15] ,b; Figure 3C ), and we show that this trend generalises to the global scale. Bird communities at higher latitudes are therefore more influenced by migratory species than those at lower latitudes. However, although this applies to both hemispheres, there is a strong asymmetry in the magnitude of the effect: the local percentage of migratory species reaches a maximum of 60% in the Southern Hemisphere whereas in the Northern Hemisphere percentages are often above this value. This asymmetry is not simply explained by an absence of land at high latitudes in the Southern Hemisphere, as it is found at equivalent latitudes (e.g., about 60% of species at 40°N are migratory, but just 20% at 40°S; Figure 4C ). Above 50°N, most communities are composed primarily by migratory species (>50%), which therefore have a major influence on community dynamics (e.g. intra-specific competition [36] ) and ecosystem function (e.g., long-distance dispersal of seeds [37] and of pathogens [38] ).

Global distribution patterns of threatened and narrow-range migratory species are very different from those for all migratory bird species. The latter are concentrated in the tropical Andes, Atlantic Forests of Brazil, the eastern Himalayas, eastern Madagascar, and the archipelagos of South-East Asia [39] (BirdLife International, 2008) whereas threatened migratory species are concentrated mostly in Asia and to a lesser extent in eastern Africa ( Figure 5A ). The two latitudinal bands of high diversity of threatened migratory species in Asia are mainly caused by the same species being counted in both their breeding and non-breeding distributions. The local richness in threatened migratory species is much higher in the Eastern Hemisphere than in the Western Hemisphere ( Figure 5A ), even though the total numbers of threatened migratory species by continent do not reflect this. This is explained by threatened migratory species in the Americas having generally smaller distributions (with lower degree of overlap and so lower richness per hexagon) than in the Eastern Hemisphere.

The majority of threatened migratory species are waterbirds, and these are primarily threatened by widespread degradation and destruction of wetlands [1] . In particular, industrialisation around the Yellow Sea, driven by rapid growth in the population and economy of China and South Korea, affects species on their breeding grounds (e.g., Chinese Egret), non-breeding grounds (e.g., Hooded Crane) or during their migration along the East Asian-Australasian Flyway (e.g., Great Knot, Far Eastern Curlew and Spoon-billed Sandpiper). Furthermore, the intensification of agriculture, combined with the degradation of rivers by pollution and transport in southern Asia, affects many species on their wintering grounds (e.g. Manchurian Reed Warbler, Wood Snipe, Asian Finfoot and Indian Skimmer). The region around the Black and Caspian Seas is another area with many threats to migratory species, such as the intensification of agriculture in Eastern Europe or hunting in Middle East and South-West Asia (e.g. Houbara Bustard; [40] ).

When defined across all bird species, narrow-range species are concentrated in the tropics (e.g., northern Andes, Eastern Arc of Africa, and archipelagos of South-East Asia; [13] , [29] ). In contrast, narrow-range migratory species are mostly absent from those areas and are concentrated in Central America, the Himalayas and Patagonia ( Figure 5B ). In the Americas, the concentration of migratory species in Patagonia and Central America in January may reflect the more restricted areas of land in these regions, concentrating migrants from the central/northern parts of South America and from North America, respectively. In Asia, the concentration of migrants in the Himalayas in July may reflect the availability of seasonally rich habitats at different altitudes within a narrow latitudinal band, with a large region to the south in South Asia to support migrants in the non-breeding season.

As in previous studies ( [13] for birds, [41] for mammals, and [42] for multiple taxa), we found little congruence between areas with high richness, endemism and threat for migratory bird species. The Himalayan region, however, stands out as an exception, suggesting that it is of particular importance for the conservation of migratory birds at the global scale. Other regions highlighted by at least two of these aspects of diversity include south-east Russia, Japan, southern Myanmar, Central America, eastern China, the Rift Valley, north-west India, and Mongolia. Many of these also fall within existing regions of global conservation priority [43] . However, whereas the majority of the latter occur in tropical regions, regions of importance for migratory birds are mainly found in temperate regions in the Northern Hemisphere.

Overall, we found a striking asymmetry between the Northern and Southern Hemispheres in all the patterns investigated ( Figures 3 , 4 and 5 ). This was not readily apparent from the combined results of previous regional-scale studies, highlighting the importance of a global perspective for understanding biodiversity patterns. There are a number of (non-mutually exclusive) hypotheses that might explain this asymmetry. First, the evolution of migration from the tropics towards northern areas (as proposed by the “southern-home” theory; [4] might have been favoured by the greater extent of continental mass in the Northern Hemisphere. The shape of the continental mass, with the Southern Hemisphere being dominated by the V-shaped South America and Africa, and isolated islands in Oceania, might have further enhanced this effect. Second, climate seasonality is more extreme in the Northern than in the Southern Hemisphere due to the relative amount of land versus ocean (given the buffering effect of the ocean on climate), making it more challenging for species to remain all year round. Third, differences in climatic history might have provided different opportunities for the evolution of migration in the two hemispheres. Indeed, the Northern Hemisphere has been characterised by much greater long-term climatic variability than the Southern Hemisphere (e.g. more extensive recent glaciations; [44] . Finally, present and past habitat geography could have favoured a more pronounced evolution of migration in the northern hemisphere, for example if important migration routes have evolved between tropical forests and the large temperate forests once occurring in the Northern Hemisphere [45] . Future studies explicitly testing these hypotheses, through their predictions on the spatial patterns of migratory bird diversity, will shed light on the origin and evolution of bird migration.

Supporting Information

Appendix s1. literature review. synthesis of the published literature on bird migration from a macroecological perspective. information is synthesized in a table (table s1)..

https://doi.org/10.1371/journal.pone.0070907.s001

Appendix S2. Analysis across flyways. Migratory species diversity as a function of latitude across the three major global migratory flyways. The major global flyways are described in Figure S1. Figure S2 shows the diversity in migratory species plotted against latitude and across flyways.

https://doi.org/10.1371/journal.pone.0070907.s002

File S1. Figure S3, Global patterns of species diversity for narrow-range migratory species. (A) Richness in narrow-range migratory species in July. (B) Richness in narrow-range migratory species in January.

https://doi.org/10.1371/journal.pone.0070907.s003

File S2. Table S2, Summary of geographical location, distribution and major threats for threatened migratory species.

https://doi.org/10.1371/journal.pone.0070907.s004

Author Contributions

Conceived and designed the experiments: AM AR MS. Analyzed the data: MS. Wrote the paper: MS SB AR AM. Co-coordinated the data collection: SB. Verified and corrected the data for migratory species: MS.

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Urban bird diversity: does abundance and richness vary unexpectedly with green space attributes?

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• Supplementary Data

Rebecca Thompson, Mariana Tamayo, Snorri Sigurðsson, Urban bird diversity: does abundance and richness vary unexpectedly with green space attributes?, Journal of Urban Ecology , Volume 8, Issue 1, 2022, juac017, https://doi.org/10.1093/jue/juac017

Urban bird diversity has been shown to be a useful indicator of overall biodiversity in urban green spaces. Attributes of green spaces (size, location and age) vary within a city and can influence bird diversity. To understand the relationship between bird diversity and green space attributes, we assessed bird abundance and richness in several green spaces in Reykjavik, Iceland. Fifteen green spaces were selected, representing different size categories (small: <5 ha and large: 7–41 ha) and different locations within the urban sprawl (central and suburban). Thirteen transect surveys were conducted at each park from March to September 2020. Abundance, species richness, the Shannon diversity index and evenness were compared across parks. Abundance, Shannon index and evenness were significantly higher in large, intermediate-aged parks with residential urban contexts ( P  < 0.05). Richness did not vary significantly with park size but was significantly higher in old- and intermediate-age parks that were centrally located ( P  < 0.005). Bird diversity did not vary significantly over the survey season. For abundance, our results were expected: the larger the park, the greater the abundance. However, contrary to most studies, the suburbs of Reykjavik had less richness than the city center. Furthermore, park size was not relevant for richness, which is the main factor in other cities (e.g. London, Boston). These differences in response indicate that abundance and richness should be considered simultaneously when monitoring urban bird diversity. Lastly, small urban parks (<5 ha) should not be disregarded in urban planning, especially in high latitude cities.

Most of the human population lives in cities and greatly relies on urban green spaces to maintain a connection with nature, including biodiversity ( Fragkias et al. 2013 ). Conservation of these scattered patches of natural habitat within urban areas has become increasingly important for human wellbeing as well as for the plant, animal and microbe species living within ( Faeth, Bang, and Saari 2011 ; Mexia et al. 2018 ). While biodiversity is generally much less in urbanized zones than rural and natural zones, many species can still thrive in urban green spaces ( Lepczyk et al. 2017b ). Birds are globally found to be good indicators of the status of overall urban biodiversity ( Sandström, Angelstam, and Mikusiński 2006 ; Nielsen et al. 2014 ; Peris and Montelongo 2014 ). Many studies conducted on bird diversity in urban green spaces have revolved around attributes of size, habitat structure and isolation/connectivity in relation to species richness (number of species in a given area; Ferenc et al. 2014 ; Kang et al. 2015 ; Dale 2018 ). Multiple studies have demonstrated that urban bird species richness increases with the size of the green space ( Zhou and Chu 2012 ; Peris and Montelongo 2014 ; Kang et al. 2015 ; Dale 2018 ). Larger green spaces tend to have more resources and higher habitat complexity (niche space), which can generally accommodate more species. This leads to both higher taxonomic and functional bird diversity ( Schütz and Schulze 2015 ; Jasmani, Ravn, and van den Bosch 2017 ).

Based on the island biogeography theory ( MacArthur and Wilson 1967 ), one can expect that species richness would decrease the further a green space is from the source areas and populations beyond city limits. One could then assume that parks close to highly urbanized city centers would have lower species richness ( Chamberlain et al. 2007 ) than suburban parks closer to rural source areas. While many studies do support this urban-rural gradient (Nielsen et al. 2014), there are some that do not (e.g. Dale 2018 ). Since distance may not be a strong constraint on bird distribution, this may imply that other factors (e.g. local conditions) exert a stronger effect on species richness than location ( Sandström, Angelstam, and Mikusiński 2006 ; Dale 2018 ).

Green spaces can range widely in shape (e.g. narrow strips, wide parklands), fitting into the nooks between buildings and roads or filling in gaps within the urban matrix. While it may not be the most influential factor, shape can limit diversity in some cases. Two parks with the same size may have completely different shapes which can affect the quality of habitat, where one park may have less edge habitat relative to its core habitat ( Forman 1995 ; Collinge 1996 ). The less edge habitat a fragment contains, the more species it can generally host. Species more vulnerable to disturbance may prefer core habitat, whereas some generalist species thrive in edge habitat ( Jasmani, Ravn, and van den Bosch 2017 ).

While species richness is well studied in the urban context, other measures of diversity like abundance, are less common. Because abundance measures the number of individual birds rather than species, it can provide a different picture of urban diversity trends. For example, abundance may increase with greater urbanization while species richness decreases ( Faeth, Bang, and Saari 2011 ). These abundance increases may be due to a notable rise in the numbers of a non-native bird species, as well as some native ones, which are better adapted to urban settings. Furthermore, fragmentation of urban parks may lead to other factors, such as changes in behavior, which may bring shifts in abundance ( Faeth, Bang, and Saari 2011 ). In urban forest fragments in South Korea, for example, both richness and abundance increased with patch size while habitat connectivity only influenced abundance ( Kang et al. 2015 ). Whereas, in Sacramento County, CA, USA, neither species richness nor abundance differed significantly between parks inside and outside the city of Rancho Cordova. However, species richness in Rancho Cordova was positively related to park size while abundance was instead connected to other factors such as built cover within the parks ( Haas, Kross, and Kneitel 2020 ). These discrepancies indicate the need to consider multiple measures to establish a more complete picture of the processes that affect urban bird diversity.

The City of Reykjavík, Iceland makes an interesting location for studying urban bird diversity through both species richness and abundance in relation to green space attributes. Situated in a high latitude context and in the volcanic landscape of southwest Iceland, Reykjavík is relatively small for a capital city but contains a variety of green spaces. Birds are one of the most prominent animal groups in Iceland and Reykjavík currently hosts a number of key bird habitats, including freshwater and coastal habitats, some of which are regularly monitored. These include Christmas bird counts which are conducted annually in Reykjavík and throughout the country ( IINH 2022 ). In addition, bird surveys have been conducted in southwest Iceland where 70 breeding species were recorded, many of which were seabirds, shorebirds and wading species but also included species found in urban areas ( Skarphéðinsson, Pétursson, and Hilmarsson 1994 ). Otherwise, research on bird diversity in the region is lacking and has not yet been systematically studied in Reykjavík’s urban green spaces ( Department of Environment and Planning 2016 ; IINH 2018 ).

Reykjavík contains about a third of the country’s human population (355 000 in 2018; Íslandsstofa 2021 ) and covers 273 km 2 of the 103 000 km 2 in total land area ( Vísindavefurinn 2004 ). Even though Iceland is believed to have been settled in Reykjavík around 870, the area was composed of farm and rural settlements until the mid-to-late-1700s when it began to take urban form ( Friðriksson 1991 ). With most urban development occurring in the 1900s, the city is generally considered to be around 235 years old. Outlined in The Municipal Plan 2010–2030 for Reykjavík is a shift of urban planning strategy from urban sprawl to densification, in which 90% of building projects will be in Reykjavík’s city center ( Department of Environment and Planning 2014 ). Building on land that has previously been developed reduces urban sprawl and further disturbance of natural areas. While densification has its benefits (e.g. promotes public transportation), it also puts pressure on green spaces.

Many other European cities are considerably older with more progressed urbanization. Those cities may be resigned to a purely reactionary response to balancing goals of biodiversity conservation and densification. But for Reykjavík, the city may have the opportunity to be proactive in achieving this balance while not only conserving biodiversity but increasing it through the planning and utilization of green spaces. The tension between maintaining urban green spaces (with increasing biodiversity) and a densification strategy is likely not sustainable in the long-term. While the balance between these may be successful for a time, a point will be reached when green spaces may be sacrificed for the strategy of densification ( Sandström, Angelstam, and Mikusiński 2006 ; Mexia et al. 2018 ). The decline of existing urban green spaces quality through increased urban development has accelerated species diversity loss within cities ( Chamberlain et al. 2007 ). Given the uncertainty of the long-term presence of green spaces, it is a priority to understand their value to urban bird diversity by establishing a baseline evaluation to help guide densification strategies.

In the interest of establishing such a foundation of general city-wide trends related to green space attributes and bird diversity, we investigated the following question: How do park attributes (size, location, shape and urban context) impact urban bird diversity? Along the lines of many other studies, we predicted bird richness and abundance to be higher in the larger green spaces and those located in the suburbs. We addressed this by surveying several parks of different sizes and locations in Reykjavík and determining their bird abundance and richness from spring to early fall in 2020.

Study site selection

Reykjavík (64.1355, −21.8954) is located on a peninsula surrounded by natural coastal areas (see Supplementary Data ). Outside the capital area, the landscape is dominated by mountains, heathland and moss-covered lava fields with low shrubs and sparse trees ( ME-IINH 2001 ). Most of the rural land is used for open grazing for livestock. The most urbanized sector of Reykjavík is contained within the peninsula while the suburbs sprawl inland and along the coast to the north. Study sites ( Table 1 ; Fig. 1 ) were selected within the city boundaries of Reykjavík according to the green spaces identified in the Reykjavík Municipal Plan 2014 ( Department of Environment and Planning 2014 ). Green spaces include a broad range of vegetated or partly-vegetated areas, such as public parks, cemeteries, golf courses, forest remnants and private gardens ( Haaland and van den Bosch 2015 ; Lepczyk et al. 2017a ). Of particular interest for our study were the green spaces smaller than 50 ha. Potential study sites were identified using Google Maps and the Municipal Plan 2014 that met the following criteria: non-shore areas, non-special use (e.g. athletic recreation and cemeteries) and parks currently not monitored for birds by the city (to our knowledge). An exception was made for the cemetery Gufuneskirkjugarður (Site 5) in order to include a large park (5–50 ha) in the city periphery. Fifteen green spaces were selected as a random stratified sample based on size categories (small and large) and locations within the urban sprawl (central and suburban) and included five small, central sites; five small, suburban sites; and five large sites throughout the city ( Fig. 1 ).

Map of study sites in Reykjavík. Large study sites (1–5) are located throughout the urban sprawl. Small sites are divided between the city center (6–10) and suburban districts (7–15).

Study sites surveyed in Reykjavík in 2020

Note : Coordinates are provided along with total park area, the area surveyed and the number of 100 m transect segments in each park.

Variable descriptions

Small sites were defined as any green space <5 ha in total area ( Tables 1 and 2 ). Large sites ranged between 7 and 41 ha. We used a city map web resource, Borgarvefsjá, which provides access to measurement tools and historical maps to determine the size and age of the parks ( Reykjavíkurborg 2022 ). City center (central) was defined by the boundary used in the Municipal Plan with the exclusion of Landakotstún (Site 6), which was just outside the city center boundary ( Fig. 1 ). This exception was made in order to have a suitable fifth small, central site of similar size and use to the others. Any other sites outside that boundary were considered suburban sites. Park age was used as a proxy for location: old-central (>60 years old), intermediate (40–60 years old) and young-suburban (<40 years old; Reykjavíkurborg 2022 ). Park shape was categorized into polygon or linear sites. Polygon sites were those that roughly formed a rectangular or triangular shape that had a core surrounded by relatively equal edge. Linear sites were elongated green spaces, typically along a road or walkway, which had more length than core. Due to size permitting more core area, all large sites were categorized as polygon. Urban context was categorized into residential or mixed ( Table 2 ). Residential context were sites surrounded completely by houses and apartment blocks. These buildings were often associated with open lawns and private gardens. A mixed context was a site surrounded by both residential and commercial buildings, such as businesses, restaurants and/or office buildings. These sites were often associated with more paved surfaces. Austurvöllur (Site 7) was the only survey site that could have been categorized as purely commercial and was therefore included in the mixed classification. For more site descriptions see Table 2 and Thompson (2021) .

Note : Classifications of park attributes are provided for each site.

Site 2 (Klambratún) is classified as a Suburban site when location is considered; however, when age is used as a proxy for location, it is reclassified as an old-central site.

Site 7 (Austurvöllur) is the only park qualifying as completely commercial so was included in the mixed urban context category.

Transects were selected in each green space ( Fig. 2 ) to monitor bird species presence (species richness) and abundance. Methods were chosen based on recommendations from survey manuals ( Bibby, Jones, and Marsden 2000 ; Gregory, Gibbons, and Donald 2004 ) and previous studies ( DeGraaf, Geis, and Healy 1991 ; Chamberlain et al. 2007 ; Peris and Montelongo 2014 ; Kang et al. 2015 ; Schütz and Schulze 2015 ; Haas, Kross, and Kneitel 2020 ) to achieve our goal of establishing a baseline given the time and human resources available. Established park paths were used as transects, except for Bringan (Site 10) in which the only established path was far too short. Instead, a transect was selected down the center of the park lengthwise. Birds were recorded by sight and calls separately when seen or heard within 20 m on either side of the transect. For most of the small sites, this range encompassed the entire green space. Calls were only recorded if it was certain the individual was calling within 20 m from the transect and could not be identified by sight. In cases when calls were too numerous to count accurately, only one or two individuals were recorded based on the number of directions from which the clusters of calls originated. Overflying birds (flyovers) were counted separately and were not used in diversity values. To avoid double counting, birds sighted further down the transect were not counted until reaching that point and birds flying from behind were ignored ( DeGraaf, Geis, and Healy 1991 ; Bibby, Jones, and Marsden 2000 ; Chamberlain et al. 2007 ; Peris and Montelongo 2014 ; Kang et al. 2015 ; Schütz and Schulze 2015 ). Since sunrise and daylight are extremely variable in Iceland throughout the seasons, surveys were conducted during a consistent time period between 8:00 and 11:00 am, every 2 weeks from March to September 2020 (13 surveys per site). This time period encompassed the breeding season as well as spring and fall migrations. During surveys, weather conditions were mild, with <6 m/s winds, none to little precipitation, and temperatures ranging from −2°C to 13°C. Weather was recorded from the YR mobile app ( www.yr.no/nb ) for each site location.

Selected study sites in Reykjavík. Urban green spaces have a wide range of habitat types and level of maintenance. Einarsgarður (Site 9; top-left) is a central site and a common through-way for pedestrians. Laugarás (Site 12; bottom-left), on the other hand, is a nature reserve in a suburban district. Fossvogsdalur (Site 4; top-right) has a small series of ponds and streams at the western end of the park. The green space along Suðurfell (Site 14; bottom-right) contains a paved pedestrian path and is well maintained.

Whole season diversity

Overall bird diversity was first compared across sites for the entire survey period (March–September 2020). Urban bird diversity included four diversity measures: abundance, species richness, Shannon’s diversity index and evenness ( Magurran 2013 ). Abundance and species richness were standardized per 100 m of transects and were log transformed to improve their normality for statistical analyses. Means for the Shannon and evenness indices were also log transformed; these measures were not standardized as they deal with relative abundances. The park attribute variables were size, location, age and shape. To assess collinearity between these attributes, we conducted Pearson and Spearman correlation analyses. We found that none of the attributes were highly correlated (>0.700) except location and age (Spearman rho = 0.816). For subsequent analyses, age was then used as a proxy for location. Bird diversity and park attributes were then compared between sites using t -tests and one-way analysis of variances (ANOVA) with α  < 0.05. Both Tukey HSD and Games–Howell post hoc tests were conducted to identify significant differences.

In addition, Pearson correlations were performed to assess if significant relationships occurred between the park attributes and the abundance of the most common bird species (seven species). Common species were determined by four measures: total mean abundance per 100 m, total abundance overall, total number of sightings/occurrences and the number of parks at which the species were sighted. In particular, these were species that had a total abundance >35 individuals with more than 10 occurrences in at least 5 parks. The same analysis was performed for two special interest species: golden plovers ( Pluvialis apricaria ) and whimbrels ( Numenius phaeopus ). These two species are important waders legally protected in Iceland and by international conventions (e.g. Ramsar Convention; Jóhannesdóttir et al. 2019 ). Gull species ( Larus spp.) were removed from all analyses since species were difficult to differentiate and were mostly recorded as flyovers. All analyses were performed using SPSS version 27 (IBM ® SPSS ® ).

Monthly diversity

A series of one-way repeated-measures ANOVAs were performed with α  < 0.05, to determine if urban bird diversity significantly varied across the field season (March–September) based on the total mean for each site per month. The variables compared were total mean abundance (per 100 m), total mean richness (per 100 m), mean Shannon index and mean evenness. Where sphericity could not be assumed, the Greenhouse–Geisser test was used. In addition, the Related-Samples Friedman’s Two-Way Analysis of Variance by Rank Test was used to determine if the total mean abundance of all species was significantly different during the survey season.

Over the entire survey season, 20 bird species were observed with a total of 2284 individuals recorded. Most bird species were passerines but there were some appearances of waders and waterfowls (full species list presented in Supplementary Data ). Redwings ( Turdus iliacus ) were by far the most abundant species with 798 individuals recorded and they occurred 140 times in all 15 sites. Common starlings ( Sturnus vulgaris ) were the second most abundant species (680 individuals) and were recorded 88 times at 14 sites. In contrast, common snipes ( Gallinago gallinago ) and common ringed plovers ( Charadrius hiaticula ) were the least common species and were only recorded once. Overall, the largest total abundance and species richness values were recorded in the large sites (Sites 1–5), ranging 173–489 individuals and 8–14 species (see Supplementary Data ).

Standardized total diversity

During the entire field season ( Table 3 ), mean abundance (per 100 m) was positively correlated with mean species richness (per 100 m) for all parks, so that as the abundance increased, so did richness (Pearson = 0.463, P  < 0.01). Hereafter, mean abundance and richness (per 100 m) is referred to abundance and richness. When it came to total park area, abundance was also positively correlated (Pearson = 0.353, P  < 0.01), whereas richness was not (Pearson = −0.115, P  > 0.05). Furthermore, the mean Shannon diversity index and mean evenness were positively correlated with total park size, both of which increased with park size (Shannon index: Pearson = 0.639, P  < 0.01; Evenness: Pearson = 0.274, P  < 0.01; Table 4 ).

Diversity values for each site during the whole season (March–September 2020)

Note : The means and standard errors for abundance/100 m, species richness/100 m, Shannon diversity index and evenness are shown.

Significant results of urban diversity in relation to park attributes and survey conditions for the entire survey season (March–September 2020)

Note : Diversity measures are standardized for abundance and richness (per 100 m).

Overall, abundance was significantly higher in parks that were large-sized and polygon-shaped ( Table 4 ; Fig. 3 ), but it did not vary with park location. Richness, however, was significantly higher in centrally located and polygon-shaped parks. Park size did not have a significant effect on richness. The Shannon diversity index was significantly higher in suburban locations and large polygon-shaped parks ( Table 4 ; Fig. 3 ). Evenness was also significantly higher in large, suburban parks, but there were no differences with park shape.

Urban bird diversity in Reykjavík. Shown are bird abundance/100 m, species richness/100 m, Shannon diversity index, and evenness. (A) Large study sites (1–5) are located throughout the urban sprawl, whereas small sites are divided between the city center 6–10) and suburban districts (7–15). (B) City center sites consist mostly of small sites, along with one large park (1) and a second large park (2) when the city center is defined by age.

In addition, the diversity measures varied significantly with the age of the parks ( Table 5 ). Parks of intermediate age (40–60 years old) had significantly higher abundance than old-central (>60 years old) and young-suburban parks (<40 years old; Table 5 ). Young-suburban parks had significantly less richness than the other two older park categories. Both Shannon index and evenness were significantly less in old-central parks than in intermediate-age parks (Tables 5). Furthermore, young-suburban parks had significantly higher evenness than old-central parks. In terms of urban context, all the diversity measures (except for richness which was similar in both contexts) were significantly greater in residential parks than mixed ones ( Table 5 ).

Diversity means according to age and urban context site classifications

Note : Old-central refers to parks that are >60 years old, intermediate to 40–60 years old parks and young-suburban represents parks that are <40 years old. The residential context represents sites completely surrounded by residential buildings, while mixed context describes both residential and commercial buildings surrounding the site. Abundance and richness are standardized per 100 m of transect. N is the number of surveys within each age classification conducted from March to September 2020. The means and standard errors are shown for all variables.

Most common species

Of the seven most common species ( Table 6 ), redwings and common starlings occurred in most sites. Mallard ducks were the fourth most abundant species (1.78 individuals/100 m, 213 individuals total); however, these were excluded from the most common species since they were recorded only in one location (Site 4: Fossvogsdalur). Large-sized parks had significantly greater abundance (per 100 m) of redwings, blackbirds and graylag geese compared to the small parks (redwings: t = –5.643, df  = 193, P  < 0.001; blackbirds: t = −3.278, df  = 193, P  < 0.005; graylag geese: t = −2.476, df  = 66, P  < 0.05). No significant differences in abundance were detected between large and small parks for the other common birds. Only the abundance of redwings and redpolls was significantly greater in parks located in the suburbs (redwings: t = −2.098, df  = 193, P  < 0.05; redpolls: t = −3.687, df  = 169, P  < 0.001). Both redwings and blackbirds were significantly more common in polygon-shaped parks than in linear-shaped parks (redwings: t  = 6.837, df  = 186, P  < 0.001; blackbirds: t  = 5.335, df  = 191, P  < 0.001). Parks with a residential context had significantly more (abundance/100 m) redwings and redpolls than mixed urban content parks (redwings: t  = 3.483, df  = 192, P  < 0.005; redpolls: t  = 2.411, df  = 176, P  < 0.05).

Most common bird species in Reykjavík parks for the entire survey season (March–September 2020)

Note : The mean abundance (per 100 m with standard error) and total number of individuals recorded for each species (total abundance) are shown. The total number of times each species was sighted (total occurrence), and the total number of sites at which each species was observed (total sites) are presented. For example, mallards were very abundant (213 individuals in total) and were seen 13 times (total occurrence) but were only present in one site.

In addition to the most common species, whimbrels and golden plovers were found in significantly higher abundances for some park attributes ( Table 7 ). Golden plover abundance was significantly higher in the large sites. Furthermore, abundances were higher in the suburban parks for both golden plovers and whimbrels. This was confirmed for the age categories where golden plovers were significantly more abundant in the young-suburban parks compared to both old-central and intermediate parks. In residential urban context, abundance was significantly higher for golden plovers and whimbrels when compared with mixed context, where no golden plovers nor whimbrels were recorded.

Significant results for whimbrels and golden plovers over the entire survey season (March–September 2020)

Note : Presented here is where mean abundance/100 m was significantly higher (Abundance ± SE) when comparing diversity measures with park attributes.

None of the diversity measures, on their own or in relation to park variables, were significantly different between months. Overall, bird abundance was lowest in March (1.72 ± 0.43) and highest in August (3.12 ± 3.28) ( Fig. 4 ; Supplementary Data ). March also showed the lowest richness (0.53 ± 0.13) which peaked in April instead (0.84 ± 0.11) along with the Shannon index (0.66 ± 0.10) and evenness (0.18 ± 0.03). Evenness (0.13 ± 0.02) and the Shannon index (0.43 ± 0.08) were lowest in August and September, respectively ( Fig. 4 ). Finally, no significant seasonal differences were found regarding most common species or golden plovers and whimbrels.

Mean diversity values (total for all parks) by month over the survey season (March–September 2020). Abundance and richness means are given per 100 m.

Park attributes

Urban bird diversity in Reykjavík was significantly higher in the larger parks than the smaller parks relative to abundance, Shannon diversity index and evenness, which was consistent with other studies showing the same patterns (e.g. Kang et al. 2015 ; Jasmani, Ravn, and van den Bosch 2017 ). On the other hand, species richness did not vary significantly with park size in Reykjavík. This is different from what many studies have seen in other cities around the world, where species richness significantly increased with park size ( Peris and Montelongo 2014 ; Kang et al. 2015 ; Schütz and Schulze 2015 ). This may have resulted from habitat factors or the size of our study sites (<41 ha) which could have fallen below a certain size threshold or may have been smaller compared to other studies. In London, UK, for example, it has been recommended that new urban parks should be 10 ha minimum to maximize species richness ( Chamberlain et al. 2007 ). Moreover, other researchers recommend park sizes ranging from 10 to 35 ha for greater richness, depending on the city and particular needs of the species of interest ( Fernández-Juricic and Jokimäki 2001 ). Research in Boston, USA found that having an additional 150 m 2 (0.015 ha) on average of green space will add one more species to richness observations ( Strohbach, Lerman, and Warren 2013 ). In our study in Reykjavík, 73% of the parks (11 of 15 parks) were <10 ha. Even though richness was similar between our large and small parks, the absence of the strong significant trend of higher richness in larger parks in Reykjavík suggests the importance of small parks for bird diversity. We want to explore this further in the future by increasing sample size of the parks (e.g. size and age categories) and expanding the study area to other municipalities in the Greater Reykjavík area (e.g. Kópavogur, Hafnarfjörður, Garðabær) allowing a thorough evaluation of beta diversity.

We expected to see higher diversity in the suburban parks, which the Shannon diversity and evenness indices did support. Species richness, however, was significantly higher in the centrally located parks in Reykjavík when compared with those in the suburbs. This trend is opposite of what has been found in other cities ( Sandström, Angelstam, and Mikusiński 2006 ; Lepczyk et al. 2017b ). In Sweden, more species were observed in residential and peripheral areas (most comparable to the suburban category in our study) where the habitat complexity was highest ( Sandström, Angelstam, and Mikusiński 2006 ). Interestingly, they found that abundance was also higher in the less urbanized areas when compared with the city center. A similar trend was seen in Oslo, Norway, where Dale (2018) observed that the urbanization gradient from the periphery to city-center was less influential on species richness when factoring in park size and presence of native forest. This may indicate that with adequate size and suitable habitat, an urban park could harbor high species richness, regardless of location. On the other hand, a study in California showed that although both species richness and abundance were not significantly different between urban (>50% built area) and exurban parks (5–20% built area, beyond denser suburbs), species composition did vary significantly ( Haas, Kross, and Kneitel 2020 ). Additional research on species composition along an urban gradient, expanding beyond city limits, would provide a more complete understanding of urban bird diversity both in Reykjavík and other cities in general.

Interestingly, when using the age categories, diversity was significantly higher in intermediate-age sites (40–60 years old) compared to old-central (>60 years old) and young-suburban parks (<40 years old). The exception was species richness, where intermediate and old-central sites were not significantly different, but were each significantly higher in richness than young-suburban parks. These trends may be picking up on what has been indicated elsewhere that intermediate urbanization can lead to higher species richness ( MacArthur and Wilson 1967 ; Faeth, Bang, and Saari 2011 ; Haas, Kross, and Kneitel 2020 ). In several Finnish cities, species richness increased slightly at the beginning to intermediate stages of urbanization before dropping off drastically after a certain urbanization threshold ( Jokimaki and Suhonen 1993 ).

Overall, polygon-shaped parks in Reykjavík were best for bird diversity (abundance, species richness and Shannon index) except for evenness where there was no significant difference with park shape. This may be a function of less edge effect in polygon-shaped parks than linear ones. Habitat edges are likely more prone to disturbance, such as traffic noise and pedestrians ( Fernández-Juricic and Jokimäki 2001 ). These findings are consistent with landscape ecology showing that certain shapes of small habitat patches, such as linear shapes, have greater edge habitat which influences community structure ( Forman 1995 ; Collinge 1996 ). Species accustomed to edge habitat may thrive in these locations, such as habitat generalists and others more tolerant of humans ( Fernández-Juricic and Jokimäki 2001 ; Jasmani, Ravn, and van den Bosch 2017 ). Edge effect is also related to park size, where smaller urban parks have less interior habitat than larger parks and any effects of urbanization is amplified ( Schütz and Schulze 2015 ). However, further research is warranted whether the size and shape differences between parks included in this study was substantial enough to have a significant edge effect.

Urban context and disturbance

Parks in Reykjavík embedded in a residential urban context had significantly higher abundance, Shannon index and evenness. Building density (both residential and commercial) and urban land cover are sometimes linked to decreasing bird species abundance and richness ( Jasmani, Ravn, and van den Bosch 2017 ; Lepczyk et al. 2017b ). In other cases, vegetation may be a key factor for high bird species richness and is reflected in urban context measures ( Fernández-Juricic and Jokimäki 2001 ; McCaffrey and Mannan 2012 ; Jasmani, Ravn, and van den Bosch 2017 ; Dale 2018 ). As residential areas in Reykjavík tended to have more trees in neighboring private gardens, it is unclear whether the higher bird diversity seen in these green spaces was due to habitat (within the park), urban context (surrounding the park) or disturbance. To further explore urban context, more parks with exclusively commercial surroundings should be included, as well as categories based on percentage of residential versus commercial buildings.

Comparative urbanization trends

While other studies elsewhere have found strong support for a significant size-richness relationship (e.g. Peris and Montelongo 2014 ; Dale 2018 ; Haas, Kross, and Kneitel 2020 ), this was not the case for our parks in Reykjavík. The location trend for richness (city center versus suburbs) was different than expected as well. What makes Reykjavík different from other cities in terms of species richness? Firstly, Reykjavík, a relatively young city, could be considered having a moderate level of urbanization, which may lead to different trends compared to older cities in Europe. Secondly, the landscape context in which the city is set may be a contributing factor. Compared to other cities, which are surrounded by agricultural lands and natural habitat such as forests, Reykjavík is situated in a landscape mostly composed of lava fields and heath land. These habitats are home to several native bird species, such as golden plovers and whimbrels ( Jóhannesdóttir et al. 2019 ). While there are some patches of native birch forests, which are suitable for passerines, other native trees and shrubs are sparse ( IINH 2018 ). For many cities, it may be typical for the urbanization gradient to result in diminished habitat complexity toward the city center as compared to surrounding rural and natural lands ( Strohbach, Lerman, and Warren 2013 ; Nielsen et al. 2014 ). However, this may not be true for Reykjavík, where there may be greater habitat complexity (more trees, shrubs, etc.) in the older city center than in the suburbs and surrounding landscape. Park age has been found to correlate with measures of habitat complexity, such as canopy cover and tree size, which may expand a park’s capacity for richness and abundance ( Haas, Kross, and Kneitel 2020 ). Even if this is not the case for Reykjavík, habitat composition related to preferred habitat traits (e.g. trees of a certain height or species) may be responsible for the higher species richness. Thirdly, the difference in latitude may play a role in richness patterns as food and other resources tend to diminish in a northward gradient ( Jokimaki and Suhonen 1993 ). In Finland, the number of avian breeding pairs followed this trend except in urban areas. One explanation is that towns and cities provide resources in northern regions that would otherwise be unavailable due to climatic restrictions ( Jokimaki and Suhonen 1993 ). Lastly, Reykjavík is situated on a peninsula, making much of the city close to natural coastal and marine areas. The city center of Reykjavík (as defined by the Municipal Plan 2014) is not the geographical center of the city. As the city grew, pushing out into an urban sprawl, new districts were built up along the coast and further inland. This sprawl pattern may factor into how bird diversity is impacted by urbanization. The proximity of most urban green spaces to the natural coastal areas may play a role as well, even if most of the species using the spaces are not typically coastal birds. Although we are establishing a baseline for Reykjavík, representing one year of data, long-term monitoring is needed to assess interannual variability in urban bird diversity. This database will help evaluate changes in season, climate, and urban planning (e.g. densification) as well as the consistency of urban diversity patterns found in this study.

Within urban bird communities, it is common to find three to five species that dominate abundance numbers, typically between 65% and 90% ( Jokimaki and Suhonen 1993 ; Fernández-Juricic and Jokimäki 2001 ; Peris and Montelongo 2014 ). These are often habitat generalist and relatively people-tolerant. The total abundances of the top three most common species (redwings, blackbirds, and starlings) account for 73% of the individuals recorded in this study, which falls neatly within that range. The common species in our study, with the exception of white wagtails, are at least partial year-round residents ( IINH 2018 ). It is no surprise, then, that these would be observed in greater abundances over the survey season as compared to migrants which were only present in Iceland during the summer. The presence of both common resident species and migrants in the parks support ecosystem functioning and biodiversity ( Kang et al. 2015 ) as well as further indicating the importance of green spaces and the need of managing them well.

Dale (2018) discussed a filtering process for the presence of bird species in urban green spaces in Oslo. First, sensitive ecological groups are eliminated because they do not have the tolerance for urban conditions. Then, more species are lost as park size decreases and/or native forest is lost. Finally, the last filter is location (central versus suburban) or urbanization level ( Dale 2018 ). Other studies have also shown that different ecological groups respond to different park attributes ( Fernández-Juricic and Jokimäki 2001 ; Peris and Montelongo 2014 ). A similar filtering system may be present in Reykjavík’s green spaces. Among the seven most common species, only redwings, blackbirds and redpolls showed significant differences between park attributes and followed the general abundance trends of more individuals in larger, polygon-shaped parks. Since abundance was only one factor attributing to commonality in this study, other factors such as total occurrence and total sites present may be explained by territory size or flocking behavior.

From a methods point of view, it is helpful to know that the time of year (March–September) does not significantly affect bird diversity. Further research may determine if the inclusion of winter months contributes to significant differences throughout the entire year. For example, richness and abundance may show a more significant drop while the migratory birds are not present in Iceland. Furthermore, flocking behaviors and domestic migration may increase abundance for some resident species. Ravens, in particular, tend to venture into urban areas more during the winter months in Reykjavík to forage ( IINH 2018 ).

The lack of a seasonal difference in diversity highlights the importance of maintaining a network of parks, representative of all attribute types. This network would include a mixture of small and large parks with different park features that may be more suitable to bird species during different seasons. For example, some parks may be better for nesting or roosting while others may have more food resources for foraging. These needs would not have equal importance to birds throughout the year and would likely vary based on species as well.

Recommendations

Balancing the multiple functions of urban green spaces remains a main challenge of urban planning, especially under the pressures of sustainability and urban densification ( Haaland and van den Bosch 2015 ). This not only involves ecological challenges but social ones in balancing priorities of stakeholders and encouraging public investment. For this reason, a socio-ecological approach would be advantageous for future management of small urban green spaces ( Fernández-Juricic and Jokimäki 2001 ; Jasmani, Ravn, and van den Bosch 2017 ; Lepczyk et al. 2017b ).

Developing strategies that involve communities within each district would allow more efficient management of specific urban habitats customized to that district ( Lepczyk et al. 2017b ). Public awareness and involvement are essential to managing urban green spaces and biodiversity at large. Green spaces are common through-fares for pedestrians and cyclists as well as being ideal places to enjoy good weather. Enhancing urban biodiversity makes for a good foundation of encouraging stewardship in urban biodiversity and sustainability, improving the value and success of green spaces ( Fernández-Juricic and Jokimäki 2001 ; Sandström, Angelstam, and Mikusiński 2006 ; Jasmani, Ravn, and van den Bosch 2017 ). Another important recommendation is to avoid cutting into current green spaces, as this would harm not only urban bird diversity and city-wide biodiversity but also the wellbeing of residents and community building ( Haaland and van den Bosch 2015 ).

We recommend that city planners maintain and develop a mosaic of urban parks to create a network of green spaces of different sizes, ages and habitat quality. Small parks in particular should not be disregarded because they can retain high species richness, as was the case in the old, central district of Reykjavík where most parks were <1.5 ha. In addition, small parks are the only option available for many cities and therefore may be more feasible to maintain or develop.

An assessment of the effects of connectivity and isolation in Reykjavík would be worthwhile for future management and understanding how the network of parks across the urban sprawl supports the diversity of urban birds. While the Reykjavík Municipal Plan (2014) addresses green spaces on the landscape scale, it would be beneficial to study biodiversity at multiple scales, for example at district, neighborhood and park levels.

We recognize the primary limitations of our surveys were that they did not account for bird behavior, specific factors of habitat, and were only conducted during spring and summer of 1 year. To compliment the transect surveys, it would be useful to explore and compare other methods. While our transects likely provided a useful but conservative estimate for richness and abundance, point counts (with longer observation times) and territory mapping (with more thorough habitat searches) may be better for capturing different aspects of species composition (see Bibby, Jones, and Marsden 2000 ; Gregory, Gibbons, and Donald 2004 ). These methods may provide additional insights into habitat use, territory range, habitat preferences and patterns of distribution of particular species, which are useful for urban resource managers. Ultimately, a comparison of methods warrants more research for assessing bird diversity in green spaces in Reykjavík.

All park attributes included in our study can be tied to habitat, therefore understanding the relationship between urban bird diversity and habitat complexity would improve recommendations for green space planning and management ( Sandström, Angelstam, and Mikusiński 2006 ; Faeth, Bang, and Saari 2011 ; Nielsen et al. 2014 ). Some habitat factors to explore include environmental heterogeneity, composition and structure of vegetation, and presence of private gardens in the vicinity of public green spaces ( Haas, Kross, and Kneitel 2020 ). Addressing species-specific questions may be equally important on a smaller scale, such as the role of bird species composition, territory size, habitat preferences, residents versus visitors, distribution, behavior, food availability and responses to urbanization pressures among others ( Haas, Kross, and Kneitel 2020 ).

These unexpected results, where some of the small, centrally located parks in Reykjavík had the highest species richness, support the idea that all green spaces have some biodiversity value. Furthermore, it highlights the importance of using multiple diversity measures to assess bird diversity in green spaces. Future studies may expand our knowledge of urban birds by using multiple methods that include transects, point counts, territory mapping, unlimited recording distance, conducting long-term year-round surveys and looking at beta diversity to assess species composition across various urban areas. Moreover, behavioral studies would greatly enlarge the understanding of how birds use different green spaces or respond to urban pressures, and how these factors influence diversity measures. Quantifying urbanization variables, like noise and urban context (e.g. decibel levels and percentage of residential context) would provide opportunities for deeper analysis of bird habitats in green spaces.

Stakeholders, including ecologists, residents, city planners and the birds themselves, typically have different priorities for use and enjoyment of the space ( Lepczyk et al. 2017b ). For example, design and planning often favors cultural ecosystem services such as recreation and aesthetics while neglecting others. This tension of priorities may lead to differences in use of financial and labor resources available for green space management. Limitations such as these may likely be a challenge for Reykjavík and other similar cities moving forward toward densification. Therefore, integrating biodiversity goals into sustainability and climate change actions is paramount.

Supplementary data are available at JUECOL online.

We thank the Icelandic Institute of Natural History for the availability of information as well as the City of Reykjavík for the help and collaboration. We are also grateful to Kristinn Haukur Skarphéðinsson for the great comments, information, and encouraging this submission. Finally, we would like to thank the reviewers for their valuable recommendations and feedback to further strengthen the article.

Conflict of interest statement . None declared.

The data are available upon reasonable request to the corresponding author.

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• Published: 06 June 2019

Bird diversity and waterbird habitat preferences in relation to wetland restoration at Dianchi Lake, south-west China

• Kang Luo 1 , 2 , 3 , 4 ,
• Zhaolu Wu   ORCID: orcid.org/0000-0002-8182-2086 2 ,
• Haotian Bai 2 &
• Zijiang Wang 2  

Avian Research volume  10 , Article number:  21 ( 2019 ) Cite this article

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Restoration projects have been implemented worldwide to mitigate the adverse effects of the loss and degradation of wetland habitats. Much research has been carried out on the impacts on birds of wetland restoration and management projects in China. Studies have mainly investigated central or coastal wetlands, while inland wetlands in remote areas have been much less studied. We focused on examining the response of wild birds to wetland restoration in Dianchi Lake, south-west China.

The line transect method was performed at 26 sampling plots. Three of these were in the city, and to acquire all wild bird data 23 plots were located every 2–8 km along the shore of Dianchi Lake, between December 2011 and November 2013. We collected all related bird records by searching the available literature, articles, newspapers and records of birdwatchers to compare species variation before and after implementation of wetland restoration. To measure the relationships between waterbird assemblages and habitat structures, we used canonical correspondence analysis (CCA) to pair the main matrix of bird assemblages with a second matrix of habitat variables.

We recorded 182 bird species belonging to 51 families and 17 orders. Of the species, 42 were new records for Kunming City and 20 were new records for Yunnan Province. Ten waterbird species were found to have disappeared from the shore of Dianchi Lake. CCA results indicated that waterbirds could be divided into four categories based on their habitat preference: synanthropic (wintering gulls), special habitat (shorebirds), semi-natural (wintering coots and ducks) and disturbance-tolerant (resident) species.

Conclusions

Our study is the first to consider the entire wild bird community throughout the year and discuss the species variation before and after wetland restoration projects launched for Dianchi Lake. Distinct habitat requirements of different waterbird groups were detected in our study, suggesting different types of restoration and management should be implemented.

Wetlands harbor highly diverse biological communities and provide extensive ecosystem services such as water purification, flood abatement and climate regulation (Zedler and Kercher 2005 ). However, they are frequently degraded and destroyed. It was estimated that over 50% of total wetland surface was lost during the last century (Mitsch and Gosselink 2007 ). Consequently, declines in wetland-dependent species have been some of the greatest recorded (Sievers et al. 2018 ), and wetland birds in particular are sensitive indicators of wetland conditions. Wetlands in urban settings fulfill additional environmental and social needs, which include storm-water retention of runoff from impervious surfaces, as well as removing pollutants and waste from water. Urban wetlands also provide extended recreational opportunities and visual aesthetics. The economic benefits include potentially reducing infrastructure costs, due to their ability to act as storm-water retention areas (Asomani-Boateng 2019 ). Unlike rural wetlands, urban wetlands are subject to urban development pressures, resulting in profound and extensive damage, loss, and degradation (Zedler and Leach 1998 ; Ehrenfeld 2000 ). The effects of urbanisation on bird diversity may be mitigated by the presence of wetlands, which may provide enhanced habitat and increase resource availability. Nevertheless, urbanization is one of the main driving factors in the degradation of natural wetlands (Russi et al. 2013 ). Wetland restoration projects are believed to be beneficial to storm water treatment or public amenities, but are also expected to compensate for bird habitat loss as natural wetlands decline (Zedler 2000 ; Mao et al. 2019 ). Restoration projects have been implemented worldwide to mitigate adverse effects resulting from the loss and degradation of wetland habitats (Pethick 2002 ; Nakamura et al. 2006 ). It is important, therefore, to understand the habitat requirements of birds, and to assess the suitability of habitats for birds, when restoring wetlands (Ma et al. 2010 ; Terörde and Turpie 2013 ).

In China, there has been serious wetland degradation due to urbanization and other anthropogenic threats during the last six decades. Fortunately, large numbers of wetland reserves have been established, and a wide range of management and restoration projects have been implemented in both inland and coastal areas since 1980 (Xu et al. 1999 ; An et al. 2007 ). Nevertheless, most useful research on the impacts of wetland restoration or management projects on birds in wetland reserves has considered affluent and developed areas, namely eastern or coastal China (such as Chongming Island, Ma et al. 2002 ; Yellow River Delta, Li et al. 2011 and Hua et al. 2012 ; Dongting River, Yuan et al. 2014 ; Mai Po, Wei et al. 2018 ). While coastal wetlands have been identified as important habitat for more than 230 species of waterbirds (Cao and Fox 2009 ), inland wetlands located in remote areas are much less studied (Wang et al. 2018 ). Many of these do not even appear in the Ramsar List of Wetlands of International Importance.

Wetlands and lakes in Yunnan Plateau, south-west China, are important habitats for waterbirds (Chen 1998 ; Cui et al. 2014 ). Most studies have a seasonal focus on wintering waterbirds in Lashihai (Quan et al. 2002 ), Napahai and Bitahai wetlands (Han et al. 2009 ; Li and Sun 2014 ), Luguhu Lake (Li and Yang 2015 ), Qionghai Lake (Hu et al. 2015 ) and Dianchi Lake (Wang et al. 2006 ; Wu et al. 2008 , 2009 ; Han et al. 2012 ). Few studies have documented diversity of all wild birds throughout the year (Han et al. 2014 ).

Dianchi Lake, a vital shallow lake next to Kunming City, the political and cultural center of Yunnan Province, has been greatly affected by human disturbance and has undergone severe degradation since the 1980 s. The implementation of an ambitious large-scale ecological restoration project, the “Kunming Urban Master Plan (2008‒2020)”, began along the shore of Dianchi Lake in 2008. Most researches about Dian Lake focus on the water quality recovery, while there is little information about how birds are responding to the restoration of Dianchi Lake wetlands (but see Wang et al. 2016 ). The aims of the present study were to: (1) record the entire wild bird composition; (2) identify differences in species occurrences between historical and current data; and (3) analyze waterbird habitat preference with respect to wetland restoration. Finally, we discuss waterbird response, in a general sense, to wetland restoration under conditions of urbanization.

Dianchi Lake (24°40′‒25°20′N, 102°36′‒102°47′E) is an ancient tectonic lake located in the Yunnan-Guizhou Plateau in the Yangtze River Basin (Fig.  1 a, b; Xiang 2014 ; Ma and Wang 2015 ). With an area of 308.6 km 2 , it is the sixth largest freshwater lake in China and the largest on the plateau. It is separated into two parts by a semi-artificial dam: the northern part, Caohai, has a water area of 10.7 km 2 and a mean water depth of 2.5 m; the southern part, Waihai, has a water area of 297.9 km 2 and a mean water depth of 4.3 m. The regional climate is a subtropical humid monsoon type, with a mean temperature of 14.4 °C, mean annual precipitation of 1036.1 mm and 227 frost-free days per year (Wang and Dou 1998 ). More than 20 main streams comprise the Dianchi Lake watershed, and the lake’s stable water level of 1886.9 m above sea level is maintained by an artificial floodgate in the only natural outlet south-west of Waihai. The lake is nearly semicircular: its length is 40.4 km and it has a mean width of 7.0 km. The shoreline is 150 km (Yang et al. 2010 ) in extent. Located in the southern suburbs of Kunming City, Dianchi Lake plays important roles in industrial and agricultural water supply, water storage regulation, flood control and tourism.

Location of the Dian Lake ( a , b ) and the sampling sites along the Dianchi Lake ( c )

It was known for its crystal-clear water and was once dubbed “the pearl of the Yunnan-Guizhou Plateau”. However, the lakeside was over-reclaimed in the 1970s and the water has become heavily eutrophic. The ability of the lake to self-purify has not been able to keep up with the massive discharge of municipal and industrial sewage into the water. Along with Taihu and Chaohu lakes, Dianchi is listed as one of the three most polluted lakes in China (Liu and Qiu 2007 ).

In 1988, Kunming Municipality enacted the Dianchi Protection Regulations to carry out a comprehensive ecological restoration plan. An ambitious large-scale ecological restoration project, the “Kunming urban master plan (2008–2020)”, has been implemented along the lakeside of Dianchi Lake since 2008. This is an attempt to build a green wetland belt around the lakeside, reconstructed from farmland, fishponds and residential areas, and aims to recover the wetland ecosystem function. Reed, cattail, water hyacinth, duckweed and trees were planted in the restored artificial wetlands, as these are the most conspicuous landscapes in the lakeside ecological belt.

Sampling plots

We surveyed birds at 26 sampling plots: 3 plots in Kunming City and 23 plots every 2‒8 km along Dianchi lakeside (Fig.  1 c). The plots covered multiple types of environmental gradients (urban and suburban areas, low and high human density, semi-natural wild areas and areas under construction), as well as habitats (forested, grassy, cultivated and built areas, open water, and mosaics of land and water). Land covers of sampling plots were classified into 12 types based on Google Earth images and field observation (Table  1 ). We obtained the satellite images from Google Earth for each plot and measured the amount of obvious land cover. This included areas of water, mud flood (MF), building area (BA), small pond (SP), cultivated land (CL) and wasteland (WL), as identified by Arcgis. We estimated the percentage of open water area (OA) and macrophyte cover (MC) of the water area during field surveys in April 2013. We also estimated plant cover variables: forest cover [Dry forest cover (DF) and wetland forest cover (WF)] was estimated in five randomly selected quadrats (20 m × 20 m) along each transect. Within each forest cover estimation quadrat, we randomly selected four quadrats (5 m × 5 m) to estimate shrub (SB), high grassland (HG) and low grassland (LG) coverage. A matrix of habitat variables consisting of the coverage percentages of 12 types of land cover was produced for further analysis (see details in Additional file 1 : Table S1).

Bird surveys

Field bird surveys were carried out continuously for 24 months from December 2011 to November 2013 to obtain basic bird composition data. Surveys were conducted in the mid-part or late in each month for 3‒4 days from 08:00‒12:00 to 13:30‒18:30 each day. The transect method was used to survey wild birds. As the lakeshore micro-habitats usually included open areas and areas densely filled with plants, three types of transect were used: type 1 for open habitat (300 m × 200 m), type 2 for dense habitat (300 m × 50 m) and type 3 for habitat containing a dense area next to an open area (300 m × 125 m). Between one and three transects were carried out in each plot according to plot size (details in Additional file 1 : Table S1). It usually took 15 min to count the birds in each transect (Ntongani and Andrew 2013 ). All birds heard, seen in or hovering over the plots were counted. Birds that flew over the plots quickly (usually taking less than 10 s) were not recorded. All individuals were counted, and group-counting was used in the case of large flocks (more than 500 individuals) (Bibby et al. 2000 ; Yuan et al. 2014 ). Birds were observed using telescopes (Celestron 20‒60 × 80 monocular and Sharks 8 × 42 binocular) and photographed with digital cameras (Canon 650D; EF 400 mm f/4–5.6L IS USM). Bird species were identified according to MacKinnon et al. 2000 and the IOC Checklist (v 4.4) (Gill and Donsker 2014 ). We used the maximum number of individuals counted in a single month as the species abundance for each species.

Information on bird breeding divisions and migration status was obtained from Yang and Yang ( 2004 ) and Zhao ( 2001 ). Birds were classified into waterbird (two ecological types: Grallatore and Natatores) and non-waterbird (four ecological types: Passeres, Terrestores, Raptors and Scansores) (Zhao 2001 ; Zheng 2012 ). Waterbirds were further divided into 7 sub-groups: gulls (SG1), wintering coots and ducks (SG2), shorebirds (SG3), egrets (SG4), breeding rails (SG5, dominated by the resident species Gallinula chloropus ), grebes (SG6, dominated by the resident species Tachybapus ruficollis ) and others (SG7, only containing a total of 6 individuals belonging to 5 species, excluded from further analysis) for further habitat preference analysis (Cardoni et al. 2008 ; Zhang et al. 2011 ; Yuan et al. 2014 ; Wei et al. 2018 ).

New bird records and absent species

In this paper, we define new records of birds in Kunming and Yunnan as species recorded along Dianchi Lake between 2008 and 2016, as the restoration projects mainly began in 2008.

In addition to our own field observations, new bird records were obtained by searching published papers using “new bird record”, “bird”, “Yunnan”, “Dianchi” and “Kunming” as keywords at CNKI and CQVIP, two databases of Chinese journals, and the Google Scholar for Chinese website. We also checked the references listed in the publications we collected for any potential literature we had overlooked. We also searched all articles and newspapers relating to birds in Dianchi Lake, using Baidu Search. Finally, we communicated with birdwatchers (Yunnan Bird Association) who had investigated Dianchi Lake to record birds. After acquiring the records, we first confirmed that the data from scientific publications were accurate and reliable, and reviewed the few debated records with other researchers. The related records from Baidu Search and birdwatchers were adopted only when robust evidence (e.g. photos) was available. The earliest literature related to Dianchi Lake we could reach was published in 1960 (Kuang 1960 ), which conducted field surveys during 1958 and 1959. Therefore, we categorized the records obtained from searching data collected during 1958 to 2008 as historical, and those from between 2008 and 2016 as new.

Because there was no reliable and special representative bird checklist for Dianchi Lake before 2008, we compared our current bird records (including our own field observation data and those of others) with the bird checklists of Kunming City and Yunnan Province to produce the new bird record for Kunming (hereafter NKB) and for Yunnan (NYB). We used the appendix of Wang et al. ( 2015 ) as the bird checklist of Kunming. As the appendix provided dynamic historical information for some waterbird species that were explicitly recorded along Dianchi Lake, we also detected that some species had vanished from the shore of Dianchi Lake. The bird checklist of Yunnan mainly refers to Yang and Yang ( 2004 ).

Data analysis

To test whether our sampling effort was sufficient to represent the bird species richness of Dianchi Lake, we first performed rarefaction analyses based on a Monte Carlo simulation procedure implemented with EcoSim7.0 (Gotelli and Entsminger 2006 ).

Canonical correspondence analysis (CCA) was performed to reveal the relationships between waterbird assemblages and habitat variables (Yuan et al. 2014 ; Wei et al. 2018 ). In CCA, habitat data were considered as explanatory variables and abundances of waterbirds were taken as response variables. For both the habitat and species data, no data transformation was applied. We used all 12 variables to perform the CCA analysis and produce the CCA bi-plot. We also performed a Pearson two-tailed test to determine the correlation coefficients between different habitat variables. Forward selection procedures were then applied to test the habitat variables with significant influences. Partial CCA was executed to determine the independent influence of each variable; when a significant variable was used as a definitive one, the others were used as covariables. The proportion of explained variation (net effect) was measured by using the ratio of particular canonical eigenvalues to the sum of all eigenvalues in partial CCA procedures (Lososová et al. 2004). We performed a partial CCA and a Monte Carlo permutation test with 999 permutations to evaluate the significance of variables separately. The statistical significance of each species responding to the five major environmental variables was tested by producing t -value bi-plots based on the CCA procedure. All the analyses were carried out in CANOCO 4.5 (Lepš and Šmilauer 2003 ).

Sampling adequacy and species composition

The results of sample-based rarefaction curves illustrated the completeness of survey inventories and the sufficiency of sampling efforts, because of their rapid approach to an asymptote (Fig.  2 ). In total, 25,102 records for birds belonging to 182 species, 51 families and 17 orders were recorded during the 24 continuous months from December 2011 to November 2013. Of these, 67 species were waterbirds and 115 were non-waterbirds. Many of the birds recorded are protected nationally or internationally. Of the 182 species, nine were found to be “second-class protected species” in China and 144 species appeared in the Lists of state-protected terrestrial wildlife with beneficial or important economic or scientific value in China. We found that 74 species were bi-protected between China and Japan and 38 species were bi-protected between China and Australia (see details in Additional file 2 : Table S2).

Sample-based rarefaction curves. The X -axis has been scaled to show numbers of individuals

The greatest number of registered species were from the order Passeriformes (95 species, accounting for 52.20% of total registered species), while the Charadriiformes was the order with highest number of records (14,703 records, 58.57% of total records) owing to the dominance of wintering Black-headed Gulls ( Chroicocephalus ridibundus ) (14,285 records; see details in Additional file 2 : Table S2). Of the five different categories related to migration status, residents accounted for the highest number of species, while winter visitors accounted for the largest number of individual records. With respect to the six ecological types, the suborder Passeres contained the highest number of registered species, and the Natatores accounted for the largest number of counted individuals. Birds breeding in the study site were mainly comprised by species of the Oriental realm and by widespread species (Table  2 ; see details in Additional file 2 : Table S2).

Species changes before and after 2008

Through comparisons with historical data (1958‒2008), 42 bird species recorded along the shore of Dianchi Lake were new records for Kunming City. Of these, 34 species were waterbirds, including 24 shorebird species. We found that 20 species were new records for Yunnan Province; of these, 18 were waterbirds (including 15 shorebird species) (see details in Additional file 3 : Table S3). This suggests that waterbirds, and particularly shorebirds, accounted for most new records for Dianchi Lake since 2008. The appendix of Wang et al. ( 2015 ) suggests that 10 waterbird species have disappeared from the shore of Dianchi Lake. These are Ciconia nigra , Platalea leucorodia , Anas formosa , Mergus albellus , Charadrius hiaticula , Larus crassirostris , L. canus , Sterna aurantia , S. caspia and Grus grus . Particularly, G. grus was once the dominant species along Dianchi Lake.

Waterbird habitat preference

Sixty-three waterbird species (94.30% of total registered waterbird species) representing 18,913 records (99.85% of total waterbird records) were recorded in 26 plots throughout the 24-month field investigation. All habitat variables were used to examine the relationship with the abundance of waterbirds by CCA analysis. High collinearity between habitat variables is shown in Fig.  3 , except for OA, MF and WL (see Pearson correlation of habitat variables in Additional file 1 : Table S1).

CCA ordination diagram of species distribution and environmental factors in Dianchi Lake. Black arrows represented the significant affected land-cover variables ( p MF  = 0.025; p DF  = 0.006; p LG  = 0.031; p WL  = 0.007; p SB  = 0.058), while dotted arrows were the insignificant ones. Sample sits were represented by open circles, whereas species were meant by black diamonds. See abbreviation of land-cover variables in Table  1 and species code in Additional file 2 : Table S2

The results of the CCA are shown in Table  3 . The eigenvalues of the first two canonical axes were much higher than those for the other two axes. All canonical axes explain 80.3% of the variance in species data and 99.8% of the variance in species–environment relationships. The cumulative explanation of the first two axes reached 73.2% of species data and 90.9% of species–environment relationship. Monte Carlo permutation tests for the first and all canonical axes were highly significant ( p  = 0.002, p Y  = 0.001, respectively). For species–environment relationships, approximately 41.5% and 29.3% of the variations were explained by axis 1 and axis 2, respectively. Overall, the first two canonical axes were able to explain quite well the relationship between species and the environmental variables. We found that seven habitat variables (OA, CL, WF, LG, SB, WL and MF) were positively correlated with axis 1 and the remaining five were negatively correlated with axis 1. Five habitat variables (PC, SP, HG, MF and WL) and the remaining seven variables were negatively correlated with axis 2. The bi-plot of the overall species distribution and habitat explanatory variables is shown in Fig.  3 .

Forward selection of environmental variables suggested that the effects of five habitat variables (including a marginal one)—MF, DF, LG, WL and SB—( p  = 0.058) significantly ( p  < 0.05) affected waterbird distribution (Fig.  3 ). Partial CCA suggested that, of the five main habitat variables, MF alone accounted for 40% ( p Y  = 0.001) of the variation in the bird data, and DF solely explained 40.1% ( p Y  = 0.01) of the variation. LG, WL and SB did not reach a significant level.

The statistical significance of each species’ response to the five major environmental variables was tested by producing t -value bi-plots based on the CCA procedure. The relationship between single species and a particular environmental variable is shown in Fig.  4 . DF had a significant positive correlation with gulls (SG1) and a significant negative correlation with wintering coots and ducks (SG2) (Fig.  4 a). SG2 were significantly positively related with WL, while SG1 were significantly negatively correlated with WL (Fig.  4 b). Shorebirds (SG3) were significantly positively correlated with MF (Fig.  4 c) while other habitat variables showed little relevance to this sub-group. Overall, SG4, SG5 and SG6 showed similar responses, and presented similar correlation trends to the habitat variables, but none was statistically significantly affected. SG1 responses to habitat variables were opposite those of SG4/SG5/SG6 except for response to MF (Fig.  4 a‒e).

t -value biplots of the five main environmental variables. a DF, b WL, c MF, d LG and e SB. The arrows indicated each sub species groups, and empty boxes represented environmental variables. The circles filled with gray color represented negative correlation while the transparent ones represented positive correlation

In our two-year survey, 182 species belonging to 49 families and 15 orders of birds were detected, suggesting that Dianchi Lake could provide a suitable habitat for wild birds and not just for waterbirds. Species of different migration status, ecological types and breeding fauna of bird species and individuals recorded here suggest that Dianchi Lake is an important wild bird breeding, stopover and wintering site (Table  2 ). This implies that lake restoration management should take into account the requirements of different wild birds, and especially waterbirds (breeders, migrants and winter visitors).

Species responses to wetland restoration in urbanized area

We found many new bird records for Kunming City and Yunnan Province during our fieldwork and in the observations of others (see details in Additional file 3 : Table S3). This suggests that more frequent bird surveys (that is, greater sampling effort) could lead to additional new bird records (Liu et al. 2013 ). Most of the new records are of waterbirds (34 of all 42 NKB and 18 of all 20 NYB), and this may indicate that wetland restoration projects in urban settings benefit birds, and especially waterbirds (Mander et al. 2007 ; McKinney et al. 2011 ). We also found that numerous new bird records were of shorebirds (24 NKB and 15 NYB). Most of these species were recorded in mud-flooded wetlands, showing the high dependence on this habitat by shorebirds (Murray and Fuller 2015 ). In addition, more than eight studies reported shorebirds among the new bird records for Yunnan Province (Luo 2014 ). The use of inland mud-flooded wetlands by shorebirds may also be a result of coastal wetland degradation, driving some of them to seek new habitats in inland areas (Ma et al. 2002 ). If mud-flooded habitats were to form during migration seasons in western or central China, we believe that more (new) shorebird species would be found in these regions by more researchers and birdwatchers.

Although there is no reliable and representative bird checklist of Dianchi Lake before 2008, we still found the ten of the most historically recorded waterbird species are now absent from Dianchi Lake. Little information was available on the absent species, but the Common Crane ( G. grus )—a dominant wintering visitor around Dianchi Lake in the 1960s (Kuang 1960 )—is today absent from the lake (Wang et al. 2015 ). Conspicuous and rapid increases in numbers of wintering Black-headed Gulls were apparent, from about 3000–30,000 individuals during 1985–2000 (Wang et al. 2006 ). One reason for this may be related to the growing tourism activity of feeding them in Kunming City parks (Guan et al. 2008 ). We suggest that the intensified urbanization and reclamation of the last few decades (Tan et al. 2010 ) has driven away sensitive species, while synanthropic species have increased rapidly (Blair 1996 ; Maciusik et al. 2010 ; Donaldson et al. 2016 ). An alternative reason for species disappearance may be that the historical records were of vagrant visitors or rare species in Dianchi Lake. During re-checking of specimens in 2005, a specimen collected in 1981 was confirmed to be a Caspian Tern ( Sterna caspia ). As this was the first record of this species in Yunnan (Yang 2005 ), it suggests that it was a rare species or vagrant visitor to Dianchi Lake in 1981.

The relationships between the distribution of most waterbirds and habitat characteristics, as revealed by CCA, were in agreement with the birds’ ecological requirements. For instance, the shorebirds (SG3) concentrated significantly in the mudflat (MF) wetlands (Bellio and Kingsford 2013 ; Aarif et al. 2014 ; Clemens et al. 2014 ; Murray and Fuller 2015 ). The wintering ducks and coots (SG2) clearly preferred the water area next to the waste lands cover (WL) and avoided dry forest cover (DF) (Paracuellos 2006 ; Cardoni et al. 2008 ; Ma et al. 2010 ). Along Dianchi Lake, trees have always been planted in the relatively well-managed parks for their scenic value, attracting many visitors who toss large quantities of food to gulls during the winter season (unpublished observation). The higher DF along Dianchi Lake usually suggested more human recreation activities. The habitat preference of gulls (SG1) was the complete opposite of SG2, which significantly avoided the WL and concentrated in DF (Andersson et al. 1981 ; Guan et al. 2008 ; Liordos 2010 ; Maciusik et al. 2010 ). The distributions of egrets (SG4), breeding rails (SG5) and grebes (SG6) were negatively correlated with DF and shrub cover (SB), while positively correlating with other variables, but none of these relationships was statistically significant. This situation seemed to reflect wider habitat use by resident species, which can move among patches during different seasons, searching for suitable resources, and which are more tolerant of variation in the local habitats (Chen et al. 2000 ; Rendón et al. 2008 ; Donaldson et al. 2016 ).

The partial CCA also indicated that DF and MF were the only two independent explanatory variables that can significantly explain the variation in the bird data alone, 40.1% and 40%, respectively, in our study. This may suggest the vulnerability of the bird community along Dianchi Lake, because these two variables are highly dependent on human activities. The wintering gulls concentrated significantly on DF, which means they foraged in the well-managed parks, depending on the food supply from tourists (Wu et al. 2008 ). The concentration of gulls increases their vulnerability to disease, reduces their wariness of people and favors their domestication (Ma et al. 2009 ). After avian influenza broke out in China in the early 2000s, tourists did not dare to feed the gulls, and numbers of gulls foraging in urban parks reduced by 9000 (Kunming Bird Association 2006). Most shorebirds were counted in the mudflat wetlands formed temporarily by construction-work yards. Once the construction is finished the mudflat wetlands also disappear. In the biggest mudflat wetlands with the highest shorebird numbers of our sampling sites, many fewer shorebirds were encountered after construction stopped in 2014, as the area became bare ground without any water (H. Bai, personal communication 2015). No significant correlations between most variables and species were found in our study. This does not imply, however, that those variables were of no importance in determining species community composition. We can only conclude that the correlation did not reach a significant level in this study. Hence, further work is needed to determine the effects of the variables.

Management implications

Wetland restoration projects can benefit wetland birds (Mander et al. 2007 ; Murray et al. 2013 ). Studies on managed realignment sites in the UK have shown that birds colonize and adapt quickly to new habitats (Mander et al. 2007 ). We suggest that, as the food resource of wintering gulls in our study is largely dependent on humans, food is provided appropriately to keep them wild and that attention is paid to avian influenza (Poland et al. 2007 ; Wu et al. 2008 ) and potential water contamination (Jones and Reynolds 2008 ). Several more well-managed parks should be included along the suburban lakeshore to dilute the high density of foraging gulls in the urban area (Maciusik et al. 2010 ). The use of food-supply platforms for gulls should be considered when designing the parks, rather than depending on volunteers to throw food for them during sensitive periods, such as during outbreaks of avian influenza. Our results testified that a certain number of shorebirds also use available habitats in inland China, although most of them were encountered in the mudflat wetlands formed temporarily by construction-work yards. These habitats disappear when the construction projects finish, resulting in a decrease in shorebird diversity (Ma et al. 2014 ). We strongly recommend that mudflat habitats be designed and managed for migrating shorebirds on the lakeshore to allow a more comprehensive restoration of Dianchi wetland ecosystem functions (Francesco et al. 2013 ; Clemens et al. 2014 ; Murray and Fuller 2015 ; Wang et al. 2016 ). In our study, wintering coots and ducks usually appeared in large numbers in the water area next to WL, suggesting a lower human presence there (Paracuellos 2006 ; Cardoni et al. 2008 ; Ma et al. 2010 ). This indicated to us that, when the wetlands for the entire lakeshore are designed, a certain degree of semi-natural habitat with low or no human recreation access must be reserved for these species (Cardoni et al. 2008 ; Ma et al. 2010 ). The recording of mostly resident species of waterbird in all 26 sites may be explained by the long history of adaptation to local fragmentation and disturbance (Rendón et al. 2008 ; Donaldson et al. 2016 ). Nevertheless, dense aquatic plants, excess MC and human disturbance have had a negative effect on their habitat use (Cardoni et al. 2008 ; Ma et al. 2010 and our observation). Incorporating appropriate plant density and a buffer zone (lowering human disturbance) should be taken into consideration when implementing restoration, to meet the habitat utilization requirements of resident waterbirds.

In summary, the presence of numerous migratory and resident birds recorded in our study shows that Dianchi Lake is an important habitat for wild birds, which could use it as a breeding, stopover and wintering site. We suggest that intensified urbanization and reclamation during the last few decades has driven away sensitive species, while synanthropic species have increased rapidly. Wetland restoration projects have benefited many bird species, especially waterbirds. Distribution of different waterbird species is highly dependent on human activities. Different types of restoration management should be implemented, to take into account the varied habitat requirements of different waterbird groups, and allow a more comprehensive restoration of Dianchi Lake wetland ecosystem functions.

Availability of data and materials

The datasets used in the present study are available from the corresponding author on reasonable request.

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Acknowledgements

We thank Doyle McKey from Université de Montpellier, Bo Wang from Xishuangbanna Tropical Botanical Garden, Christos Mammides from Guangxi University and Donglai Li from Liaoning University for their generous help in language editing and insightful comments about the manuscript. We thank senior schoolmates Jianyun Gao and Dongdong Su for their enormous help in this study during the pre-surveys, PhD senior schoolmate Longyuan He for his kind help in mapping, Prof. Zhiming Zhang for his great help in the data analyses, faculty of the Kunming Bird Association for their help in the field investigation and memberships in the QQ groups of Students union of Birdwatching, and Yunnan Wild Bird Association and Young Ornithologists for their help in identifying some species.

The National Natural Science Foundation of China (41471149 and 31060079) financially supported this study.

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Institute of Ecology and Geobotany, Yunnan University, Kunming, 650091, China

Kang Luo, Zhaolu Wu, Haotian Bai & Zijiang Wang

Center for Integrative Conservation, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Xishuangbanna, 666303, Yunnan, China

University of Chinese Academy of Sciences, Beijing, 100049, China

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KL and Z. Wu designed the experiments. KL and HB implemented the field surveys and collected the data. KL finished the data analysis and wrote the first draft. KL, Z. Wu and Z. Wang supervised the research and provided multiple revisions in the early stages of writing. All authors read and approved the final manuscript.

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Correspondence to Zhaolu Wu .

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The authors declare that they have no competing interests.

Additional files

Additional file 1: table s1..

Percentages of different land-covers of the 26 sampling sites around Dian Lake and the Pearson correlation of the land-cover variables.

Additional file 2: Table S2.

Bird checklist of Dianchi Lake.

Additional file 3: Table S3.

New bird records found along Dianchi Lake during 2008‒2016.

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Luo, K., Wu, Z., Bai, H. et al. Bird diversity and waterbird habitat preferences in relation to wetland restoration at Dianchi Lake, south-west China. Avian Res 10 , 21 (2019). https://doi.org/10.1186/s40657-019-0162-9

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DOI : https://doi.org/10.1186/s40657-019-0162-9

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Annual Review of Ecology, Evolution, and Systematics

Volume 51, 2020, review article, avian diversity: speciation, macroevolution, and ecological function.

• Joseph A. Tobias 1 , Jente Ottenburghs 2 , and Alex L. Pigot 3
• View Affiliations Hide Affiliations Affiliations: 1 Department of Life Sciences, Imperial College London, Silwood Park, Ascot SL5 7PY, United Kingdom; email: [email protected] 2 Department of Evolutionary Biology, Uppsala University, 752 36 Uppsala, Sweden 3 Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, London WC1E 6BT, United Kingdom
• Vol. 51:533-560 (Volume publication date November 2020) https://doi.org/10.1146/annurev-ecolsys-110218-025023
• First published as a Review in Advance on August 28, 2020
• Copyright © 2020 by Annual Reviews. All rights reserved

The origin, distribution, and function of biological diversity are fundamental themes of ecology and evolutionary biology. Research on birds has played a major role in the history and development of these ideas, yet progress was for many decades limited by a focus on patterns of current diversity, often restricted to particular clades or regions. Deeper insight is now emerging from a recent wave of integrative studies combining comprehensive phylogenetic, environmental, and functional trait data at unprecedented scales. We review these empirical advances and describe how they are reshaping our understanding of global patterns of bird diversity and the processes by which it arises, with implications for avian biogeography and functional ecology. Further expansion and integration of data sets may help to resolve longstanding debates about the evolutionary origins of biodiversity and offer a framework for understanding and predicting the response of ecosystems to environmental change.

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Diversity and abundance of wild birds species’ in two different habitats at Sharkia Governorate, Egypt

• Mohamed Abd Allah Issa   ORCID: orcid.org/0000-0002-9030-5080 1  

The Journal of Basic and Applied Zoology volume  80 , Article number:  34 ( 2019 ) Cite this article

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Birds’ survey is the best method to understand different species distribution, abundance, and diversity. The present study aimed to survey wild birds, using point count method, in two habitat types (water canals and field crops) at two districts, Zagazig and Hehia, located at Sharkia Governorate, Egypt.

Surveying birds was conducted using point count method, from a fixed raising position within a circle of 50 m radius for a specific period of time (10 min) at every point. It started early in the morning, from 6 am to 8 am, at four points in two habitat types, agriculture water canals habitat (AWCH) and field crops habitat (FCH), in (Zagazig and Hehia) at Sharkia Governorate, Egypt. Each point count was visited once every month from December 2016 to November 2017.

The total number of birds’ species recorded in the two districts was 33, belonging to 24 Families and ten Orders. Twenty-five species were resident birds and eight species were migratory. The number of birds’ species (resident and migratory) in AWCH was higher than those in FCH. Resident wild birds at AWCH had higher value of species diversity (Shannon-Weiner Diversity Index H ′ = 2.63, Simpson Diversity Index D  = 0.90, Evenness J ′ = 0.82 and Species richness r  = 25) than at FCH ( H ´ = 2.56, D  = 0.89, J ′ = 0.83, and r  = 22). In contrast, species diversity for migratory wild bird was lower in WCH ( H ′ = 1.66, D  = 0.74, J ′ = 0.80, and r  = 8) than in FCH ( H ′ = 1.81, D  = 0.78, J ′ = 0.87, and r  = 8).

Birds species (resident and migratory) numbers and abundance were higher in AWCH according to the habitat suitability than in FCH.

Egypt is located at the Northeastern corner of Africa and occupies an area of about one million kilometer. It enjoys a unique strategic location, at the crossroads between Africa, the Middle East, and Europe. Egypt is divided into four physiographical regions: Nile Valley and Delta, Western Desert, Eastern Desert, and Sinai. The country is rich in wild bird species due to its wide range of habitats. Egypt is a “centralized” zone of wild bird migration pathways from Central Asia and Europe to Eastern and Central Africa expiration in South Africa (Soliman, Saad, Elassal, Amir, Plathonoff, Bahgat, El-Badry, & Mohamed. 2012 ). About 515 birds species occurred in Egypt, 186 are resident and the rest are migratory (Tharwat, 1997 ). At Ismailia Governorate, 27 resident wild bird species, belonging to 20 families and nine orders, were recorded, while migratory birds were six species that belonged to five families and three orders (Abbasy, Mostafa, Khattab, El-Danasory, & Attia, 2011 ; Attia, 2013 ). Sharkia Governorate is a home of many wild bird species. Khattab ( 1998 ) recorded 23 resident species and eight migratory species. Attia ( 2006 ) recorded 25 resident species belonging to nine orders and 21 families, and 26 migratory species belonging to six orders and 15 families. Population density and species diversity of birds is differing, increasing or decreasing according to habitat type and richness.

This study aimed to investigate the abundant, distribution, and diversity of wild bird species, in two different habitats within two districts (Zagazig and Hehia), at Sharkia Governorate, and their probable impact on agriculture.

Materials and methods

Study areas.

Sharkia Governorate is located at the eastern site of the Nile Delta. It covers about 1,200,000 feddans (1 feddan = 4200 m 2 ), one million of them is cultivated with different field crops and fruit orchards. Desert and swampland, with their different preferred birds habitats, are located to the eastern and southern borders of this governorate.

Data was collected from two districts; Hehia (30° 67′ N, 31° 59′ E) and Zagazig (30° 60′ N, 31° 51′ E). Two main habitats were chosen in each district:

Agriculture water canal habitat (AWCH): this site was around and beside main agricultural water canals, where dense vegetation, shrubs, and high trees usually located. Different field crop lands, cultivated with wheat, alfalfa, and onion in winter, maize and rice in summer, are nearby. Very low human settlements and activities are in this habitat.

Filed crops habitat (FCH): including the main agricultural fields planted with different traditional crops (wheat, alfalfa, and onion in the winter and maize and rice in summer) with some scattered palm trees. Farmers’ houses and animal farms are adjacent to this habitat, with considerable human activities.

Field methods

Field data were obtained using the “point counts” method, which is a count from a fixed location, for a fixed time period, at any time of the year. This method is suitable for studying highly visible, and/or vocal bird species, in a wide variety of habitats (Gibbons, Hill, & Sutherland, 1996 ). In this study, birds were counted from a fixed raising position within a circle of 50 m radius for a specific period of time (10 min) at every point. After 5-min settling period, all birds seen and heard within this 50 m radius were recorded during the 10 min. Bird counts were carried out early in the morning, from 6 am to 8 am, at two points in each habitat within each district (four points at Zagazig and four points at Hehia). Each point count was visited once every month from December 2016 to November 2017 (Bibby, Burgess, Hill, & Mustoe, 2000 ; Haselmayer & Quinn, 2000 ; Lande, 1996 ). No detected windy or rainy conditions during the days of this study. A binocular (10 × 50) was used to confirm species identity. Proofs of identifications were done using Collins Bird Guide (Svensson, Mullarney, Zetterström, & Grant, 2009 ). Species were assigned to families and orders according to Clements, Schulenberg, Iliff, Roberson, Fredericks, Sullivan, and Wood ( 2018 ).

Data analysis

Data were arranged to obtain the following parameters:

The relative abundance of bird species per habitat/district was determined using:

where n is the total number of birds of a particular species and N is the total number of birds of all species.

Bird species diversity:

Species richness is the number of different species present in an area (Deitmers, Buehler, Bartlett, & Klaus, 1999 ). Species richness was estimated for each habitat.

Shannon-Weiner Index ( H ′) was calculated in order to know the species diversity (Hutcheson, 1970 ) based on species abundance using the Shannon and Weaver ( 1949 ) formula:

where H ′ is the Diversity Index, Pi is the proportion of each species in the sample, and LN (Pi) is the natural logarithm of this proportion.

Evenness of birds species compares the similarity of the population size of each species. Evenness Index ( J ′) (Kiros, Afework, & Legese, 2018 ) was calculated using the ratio of observed diversity to maximum diversity using the equation.

where H ′ is the Shannon Wiener Diversity index and H max is the natural log of total number of species.

Simpson Index ( D ) measures the probability of any two individuals drawn from noticeably large community belonging to different species (Simpson, 1949 ). It was measured by the following formula:

Results and discussion

Wild bird species records.

The structure of birds communities recorded at Sharkia Governorate was varied. The checklist in Table  1 showed wild bird species recorded in the two different habitats (AWCH and FCH) at Zagazig and Hehia districts; Sharkia Governorate, during the period from December 2016 to November 2017.

The obtained data showed that the total number of wild bird species found was 33, with 25 resident and eight migratory, belonging to 24 Families and ten Orders. Order Passeriformes was the dominant one represented by 13 families including 15 species, four migratory, and 11 residents. Order Coraciiformes was in the second rank with two families including five species, two residents, and three migratory. Order Pelecaniformes represented by one family with two resident and two migratory species. While the lowest orders in numbers were Accipitriformes, Bucerotiformes, Cuculiformes, Falconiformes, and Gruiformes, which is represented by one species for each.

Relative abundance of resident wild bird species

Resident wild bird species numbers were presented in Table  2 for both habitats. In the AWCH, the following species were recorded in a descending order: House sparrow, Hooded crow, Rock dove, Palm dove, and Cattle egret. Their numbers were the highest as follows: 1133, 575, 538, 528, and 462 individuals, respectively. Their relative abundances were 0.214, 0.108, 0.102, 0.099, and 0.087, respectively. The lowest number of birds was eight individuals with relative abundance of 0.001, for black-winged kite.

In the FCH, the highest birds number was the House sparrow followed by Palm dove, Hooded crow, Rock dove, Cattle egret, and Graceful prinia in a descending order as follows: 817, 403, 384, 318 and 193 individuals and relative abundance of: 0.230, 0.113, 0.108, 0.089, and 0.054, respectively. The Black-crowned night heron number was the lowest, with 6 individuals and 0.002 relative abundance.

Relative abundance of migratory wild bird species

The data in Table  3 demonstrated the numbers and relative abundance of migratory wild bird species in AWCH and FCH at Sharkia governorate. In the WCH, the following species were recorded in a descending order: White wagtail , Blue-cheeked bee-eater, Lesser whitethroat, Bluethroat, and Kingfisher. Their numbers were the highest as follows: 254, 88, 62, 49, and 40 individuals, respectively. Their relative abundances were 0.450, 0.156, 0.109, 0.086, and 0.071, respectively. The lowest number of birds was five individuals with relative abundance of 0.008, for chiffchaff.

In the FCH, the highest bird number was the White wagtail followed by Lesser whitethroat , Kingfisher, White throated kingfisher and Bluethroat in a descending order as follows: 175, 53, 43, 42, and 39 individuals. Their relative abundances were 0.404, 0.122, 0.099, 0.096, and 0.090, respectively. The lowest number and relative abundance was 24 individuals and 0.055 with Squacco heron.

The relative abundance of birds species in an area usually related to the availability of main life requirements (food, water and shelter) as well as suitable weather conditions. Goodman, Meininger, Bahaa El-Dine, Hoobs, and Mullie ( 1989 ) mentioned that House sparrow, Passer domesticus , Hooded crow, Corvus corone , Palm dove, Streptopelia senegalensis , and Rock dove, Columba livia were abundantly resident species in numerous portion of Egypt. White wagtail, Motacilla alba is abundant passage migrants and winter visitor to Egypt from the beginning of autumn (late September) to the end of spring (early May). Also, the Bee-eater, Merops apiaster is a common migrant throughout the country in autumn from late August to late November and spring from mid-March to late June. Attia ( 2006 ) surveyed the resident birds at Sharkia governorate in three habitats (old lands, reclaimed area, and aquatic area); he indicated that the resident birds represented in a higher value in old lands followed by aquatic area and reclaimed area while the migratory birds were highest in aquatic area followed by old lands and reclaimed area. Attia ( 2013 ) cleared that higher numbers of bird species (resident and migratory) were recorded in field crop than vegetable crop areas at Ismailia governorate. The resident wild bird species included were Crested lark, Galerida cristata , Fan tailed warbler, Cisticola juncides , Graceful warbler, Prinia gracilis , Hooded crow, Corvus corone cornix , House crow, Corvus splendens , Goldfinch, Carduelis carduelis , House sparrow, Passer domestica , Swallow, Hirundo rustica , Yellow wagtail, Motacilla flava flava , Common bulbul, Pycnonotus babatus , Rock dove, Columba livia , Palm dove, Streptopelia senegalensis , Cattle egret, Bubulcus ibis , Little egret, Egretta garzetta , Pied kingfisher, Ceryle rudis , Little green bee-eater, Merops orientalis , Black-shouldered kite, Elanus caerulus , Kestrel, Falco tinnunculus , Spur-winged plover, Hoplopterus spenosus , Moorhen, Gallinula chloropus , Senegal coucal, Centropus senegalensis , and Hoopoe, Upupa epops. While he recorded six bird species as migratory birds: White wagtail, Motacilla alba alba , Chiffchaff, Phelloscobus collybita , Stonechat, Saxicola torquata , and Kingfisher, Alcedo atthis. Noura-Barakat ( 2016 ) illustrated that the number of bird species in Tanta district at Gharbia governorate were highest in field crops, followed by trees, water canals, and building, while in Zifta district, were in water canals, trees, building, and field crops. The resident wild birds at Gharbia governorate were Senegal thick knee, Spur-winged plover, Cattle egret, Little egret, Squacco heron, Palm dove, Pied kingfisher, Senegal coucal, Kestrel, Moorhen, Crested lark, Fan tailed warbler, Graceful warbler, Hooded crow, Swallow, Yellow wagtail, House sparrow, Common bulbul, and Hoopoe, while the white wagtail was migratory. El–Danasoury, Khalifa, Omar, and Saber ( 2017 ) surveyed the resident and migratory bird species at Assiut governorate. The birds were found in a highly numbers in the fields nearby trees, while they were found in moderate numbers in fields nearby building and field crops. The resident birds were House sparrow, Hooded crow, Crested lark, Common bulbul, Fan tailed warbler, Swallow, Palm dove, Rock dove, Little green bee eater, Hoopoe, Pied kingfisher, Cattle egret, Spur winged plover, Kestrel, and Black winged kite. The migratory birds were White wagtail and chiffchaff. El–Danasoury, Omar, and Hassan ( 2018 ) surveyed wild bird species at Sohag governorate; they found that the resident wild birds were Black winged kite, cattle egret, Common bulbul, Fantailed warbler, Hoopoe , Kestrel, Spur winged plover, Swallow, Yellow wagtail, Crested lark, Hooded, House sparrow, Little green bee, Moorhen, Palm dove, Pied kingfisher, and Rock dove. The migratory bird species were chiffchaff and White wagtail.

Birds species diversity

Species diversity is the number of species and abundance of each species that live in a specific location. A diversity index is a quantitative measure of how many different species are in a community (species richness) and how individuals are distributed within those species (species abundant) (You, Vasseur, Régnière, & Zheng, 2009 ). Therefore, Diversity Index is considered as a calculation of variety, which is a useful tool to understand the profile of biodiversity across study area (Bibi & Ali, 2013 ).

Diversity indices for resident and migratory wild bird species in two different habitats

Table  4 demonstrated some parameters associated with diversity of wild bird species at two different habitats. The total number of resident bird species at AWCH was 5293 individuals, which is higher than FCH (3549 individuals). Also, species richness in AWCH was r  = 25, which is also higher than FCH ( r  = 22). At the same trend, AWCH had the highest values of Shannon-Weiner diversity index ( H ′ = 2.63) and Simpson’s Diversity ( D  = 0.90), than FCH ( H ′ = 2.56) and ( D  = 0.89). While evenness ( J ′) were higher in FCH ( J ′ = 0.83) than AWCH ( J ′ = 0.82).

The same trend existed in migratory bird species, which represented by higher numbers of individuals (564) at AWCH while at FCH was 433 individuals. Species richness was the same in AWCH and FCH ( r  = 8). But in contrast, the FCH give the higher values of Shannon-Weiner diversity index ( H ′ = 1.81), Simpson’s Diversity ( D  = 0.78), and evenness ( J ′ = 0.87), than AWCH with, Shannon-Weiner diversity index ( H ′ = 1.66), Simpson’s Diversity ( D  = 0.74), and evenness ( J ′ = 0.80).

Diversity indices for the total numbers of wild birds in two different habitats

The data in Table  5 evinced that the AWCH give the highest values of diversity index, the total number of birds species were (5857) individuals, species richness ( r  = 33), Shannon-Weiner diversity index ( H ′ = 2.85), and Simpson’s Diversity ( D  = 0.92), while in FCH, the total number were (3982) individuals, species richness ( r  = 30), Shannon-Weiner diversity index ( H ′ = 2.82), and Simpson’s Diversity ( D  = 0.91). In contrast, evenness ( J ′) were higher in FCH ( J ′ = 0.83) than in AWCH ( J ′ = 0.81).

These results were in line with Mengesha and Bekele ( 2008 ). They mentioned that the avian diversity is an indication of habitat heterogeneity and the number of species and individuals in an area implies the importance of the area. Each habitat has a specific set of microenvironment that is suitable for a species. Bibi and Ali ( 2013 ) cleared that the values of Shannon-Weiner Diversity Index usually falls between 1.5 and 3.5, only rarely it surpasses 4.5. Kiros et al. ( 2018 ) mentioned that the variation in bird species diversity, richness, and abundance associated with the vegetation composition that make changes in food sources, nesting, and protection based on birds’ habitat preference and feeding.

It is concluded from the present study that birds species varied among the study sites and between habitats. Birds species (resident and migratory) numbers and abundance were higher in AWCH according to the habitat suitability, which support free water and abundant food supply (insects, grasses, and aquatic fauna) as well as nesting and resting sites. Also, most migratory birds feed on insects. On the other hand, the FCH is an agriculture area with several seasonal and daily human activities, during the day hours and part of the night, which disturbs birds. Additionally, the structure of AWCH, which include many trees and shrubs, make it a protective cover for different bird species from predators as black-winged kite, which was recorded with a higher numbers at FCH than AWCH. The order Passeriformes was the dominant order related to its wide range of species and food types (omnivorous, insectivorous, frugivorous and granivorous). Therefore, furthermore studies of the species of this order are required in Egypt, to measure their impact on agriculture crops and to develop safe methods of crop-protection.

Recommendation

Based on the obtained results, it is clear that the majority of recorded birds species were granivorous attacking field crops. Therefore, there is an urgent need to study different species’ habitat requirements, behavior, and influence on agriculture crops. This information, from this work and from future studies, can help in the development of a successful integrated birds management program to protect affected agriculture crops from birds attack.

Abbreviations

Agriculture water canals habitat

Simpson Diversity Index

Filed crops habitat

Shannon Wiener Diversity Index

Migratory bird species

Resident bird species

Species richness

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Author acknowledge Prof. Dr. Ali H El-Sherbiny, professor of Ecology, Plant Protection Research Institute, for his helpful assistance in manuscript writing.

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Issa, M.A.A. Diversity and abundance of wild birds species’ in two different habitats at Sharkia Governorate, Egypt. JoBAZ 80 , 34 (2019). https://doi.org/10.1186/s41936-019-0103-5

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Habitat complexity has long been known to influence animal community structure by increasing the number of available habitats. Fifty years have passed since MacArthur brothers published the sem-inal paper ‘‘On bird species diversity’’, which revolutionized studies of habitat structure. This paper first evidenced and quantified the relationship between species diversity (birds) and habitat structural com-plexity (the number of stratified layers of landscape vegetation). In this article, we aim to pay homage to R. H. MacArthur’s contribution and to briefly analyze the citation history and influence of ‘‘On bird species diversity’’, focusing primarily on aquatic studies. We searched for all papers that cited ‘‘On bird species diversity’’ on Thomson Reuters (ISI—Web of Knowledge) and analyzed them for temporal citation trends. In addition, considering only aquatic papers, we explored whether and how habitat complexity was measured, as well as the ecological organization level, attributes of organisms, taxonomic groups and study design (observational or experimental). ‘‘On bird species diversity’’ citations increased over time, but this paper was less cited by limnologists compared to terrestrial and marine scientists. The majority of investigations in aquatic ecosystems quantified habitat complexity, but few used mathematical modeling. The high number of citations, which continues to increase, shows the great influence of ‘‘On bird species diversity’’ on ecological studies and typifies it as a classic in the ecological literature. However, the low citation frequency found in papers devoted to freshwater ecosystems indicates that limnologists in general neglect this original contribution in studies of habitat complexity.

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• Published: 01 July 2020

Historic changes in species composition for a globally unique bird community

• Swen C. Renner   ORCID: orcid.org/0000-0002-6893-4219 1 , 2 &
• Paul J. J. Bates   ORCID: orcid.org/0000-0003-3630-739X 2 , 3  

Scientific Reports volume  10 , Article number:  10739 ( 2020 ) Cite this article

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Significant uncertainties remain of how global change impacts on species richness, relative abundance and species composition. Recently, a discussion emerged on the importance of detecting and understanding long-term fluctuations in species composition and relative abundance and whether deterministic or non-deterministic factors can explain any temporal change. However, currently, one of the main impediments to providing answers to these questions is the relatively short time series of species diversity datasets. Many datasets are limited to 2 years and it is rare for a few decades of data to be available. In addition, long-term data typically has standardization issues from the past and/or the methods are not comparable. We address several of these uncertainties by investigating bird diversity in a globally important mountain ecosystem of the Hkakabo Razi Landscape in northern Myanmar. The study compares bird communities in two periods (pre-1940: 1900–1939 vs. post-2000: 2001–2006). Land-cover classes have been included to provide understanding of their potential role as drivers. While species richness did not change, species composition and relative abundance differed, indicating a significant species turn over and hence temporal change. Only 19.2% of bird species occurred during both periods. Land-cover model predictors explained part of the species richness variability but not relative abundance nor species composition changes. The temporal change is likely caused by minimal methodological differences and partially by land-cover.

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Introduction.

Species richness, relative abundance and species composition are dynamic phenomena and vary in space and over time 1 , 2 . Recorded fluctuations of bird species richness and species diversity are explained by deterministic changes (e.g., global change such as changes in land-cover or land-use intensification 1 ), methodological changes (different effort or sites; limited or no standardisation; and methodological and non-systematic errors 3 , 4 ), random processes (e.g., neutral dynamics 5 , 6 , 7 , 8 ), or any combination of the above.

Global change is rapidly proceeding and includes land-use intensification, changes in land-cover, climate, atmospheric composition, and invasive species, among other factors 1 . Land-cover change is probably the most important in terms of species response 9 , 10 . It is probably more important than climate change for most biodiversity 1 , 11 , particularly for many bird species 9 . Land-cover change, including land-use intensification, have been shown to affect species in a variety of direct, indirect and interacting ways, including local extinction, range shifts, changes in local abundance, or interactions with other species 12 , 13 , 14 .

Although several studies have shown the effects of global change in the form of habitat loss or land-use change, these studies typically are limited in explanatory power. In many cases, the historic (previous) baseline, which is used to estimate the diversity statistics, has a low statistical power. In others, the temporal aspect is too short to show meaningful effects 15 . Most studies use only recent baseline data and the time difference (mostly 2 years, in rare instances more than a decade) is too short for changes in species assemblage. Typically they explain only short-term fluctuations, particularly fluctuations within or between consecutive years 7 , 16 , 17 .

Only a few regions worldwide remain with a habitat cover of near pristine condition 15 . These untouched areas are embedded in a land-cover mosaic of various forms 18 . The Hkakabo Razi Landscape in the northern tip of Myanmar is largely untouched and includes large tracts (11,280 km 2 ) of pristine forests interspersed with a few, relatively small areas of degraded forests or other local land-cover forms 19 . Within this Landscape, an historic bird assemblage has been documented 20 . These baseline data were collected by British and US explorers and include specimens and letters on methods and localities. It is the quality of this historical documentation, together with the rigour of the collecting methodology (which compare favourably and complement the recent efforts), that makes the Hkakabo Razi Landscape almost unique for studying species compositional turnover. At the same time, the effects of land-cover change on birds can be analysed, because the historic samples are located in pristine forests, while our own recent samples cover both pristine and some of the relatively few degraded habitats. The historic and recent collections, when reviewed together, allow for an analysis of the historical changes to bird assemblages, covering data separated by almost 70 years. This will increase our understanding of temporal dynamics in bird communities.

Mountain ecosystems of the tropics are home to high species diversity. Those of the Himalayas, including the Hkakabo Razi Landscape are also home to a rich variety of endemic taxa. For example, the study area hosts at least one endemic bird ( Jabouilleia naungmungensis 21 ) and at least two endemic subspecies of birds 20 , 22 ( Alcippe cinereiceps hkakaboraziensis , Malacocincla abbotti kachinensis ; all species and samples are listed in Online Supporting Information Table S1 ). However, all biodiversity in mountain ecosystems is vulnerable to land-cover change 23 . Currently, the forests of the Hkakabo Razi Landscape are likely the last vast area of pristine forests in Asia or at least Southeast Asia 19 , 24 , 25 , 26 , with relatively few degraded habitats imbedded within the pristine forests. To date, 456 bird species have been recorded in the Hkakabo Razi Landscape, proving its global importance for bird conservation. While the Hkakabo Razi Landscape covers about 1% of terrestrial Myanmar, it is habitat for almost half of all bird species recorded from the country (456 vs. ~ 1,100 20 ).

Here we describe and test species turnover and temporal variation in relation to global change parameters. We predict no detectable differences in species richness, relative abundance or species composition between the two periods considered (pre-1940 vs. post-2000), because land-cover change has not yet occurred to a significant extent. In turn, any significant differences in species richness, relative abundance or species composition would indicate a high proportion of temporal variation (i.e. non-static species composition) and/or a response to deterministic reasons (e.g., environmental drivers). If we find a differences in species composition between the two periods of over 50% (natural fluctuations in bird communities of the tropics with very limited human impact exhibit up to 49% species change within or between years 27 ), or significant variation between the periods in respect to species richness and relative abundance, these fluctuations can be interpreted as a consequence of temporal change.

Since the Hkakabo Razi Landscape is one of the few remaining significantly large and natural mountain forests worldwide 24 , 25 , 26 , 28 , from which we have almost perfect historical datasets, it is an invaluable natural laboratory in which to test the impact of temporal change on species richness, relative abundance and species composition. The results of such studies are of global importance. The Hkakabo Razi Landscape is a unique constellation of largely “untouched” forests 26 with collectors in the first half of the twentieth century having labelled their specimens almost perfectly.

Material and methods

Study region and study sites.

The study sites, i.e. the localities of bird sampling, are located in the Hkakabo Razi Landscape. Distribution of the localities and consequently the area covered is defined by the historic collectors (redrawn in Fig.  1 , following Suarez-Rubio, et al. 26 ). The Hkakabo Razi Landscape is located in the northern most part of Myanmar (to many Westerners still known as “Burma”) and comprises the Hkakabo Razi National Park, the planned “Southern Extension” of the National Park and the Hponkan Razi Wildlife Sanctuary (all borders as proposed on August 15, 2015).

Map of study region in northern Kachin State, Myanmar ( red area in inset map shows the location of the protected areas and outlines the Hkakabo Razi Landscape within Myanmar). Blue and green circles are for sample sites from which data are used in the study. Grey and open circles are for sample sites whose data are excluded since they are either outside the study region or have incompatible datasets.

Within the Hkakabo Razi Landscape, two major survey programmes have been completed to assess the total number of species. The first, a series of uncoordinated ‘one-off’ studies was undertaken by British collectors in the early twentieth century, the second by S.C.R. and several colleagues in the early 2000s 20 . All samples are available, either at the Natural History Museum (Tring, UK), or at the Smithsonian Institution (Washington, DC, USA) or at the Zoological Park (Yangon, Myanmar).

In the post-2000 studies, all samples were taken in accordance with European Union, US and particularly national Myanmar laws on animal protection and conservation measures at the time of data sampling. All necessary permits have been approved by the Nature and Wildlife Conservation Division of Myanmar’s Ministry of Natural Resources and Environmental Protection (MoNREC, formerly Ministry of Forestry—MoF). The responsible officers and the permit number are listed in the acknowledgements.

Collection based data search

There is an enormous amount of data available from bird collections worldwide. However, insufficient or imprecise locality data and habitat information is an issue for analysis involving museum specimens, particularly if collected prior to the 1960’s. Nevertheless, a quite remarkable number of specimens in the collections is available for the Hkakabo Razi Landscape for further analysis. Those collected by the British forester Ronald Kaulback (sometimes written as Kaulbach) and his colleagues indicate on the labels exact locality, including coordinates and elevation (details listed in Table S1 , Online Supporting Information). They also provide simple information about the habitat types and how the birds were captured. Many were collected in the Adung Valley, which is today part of the Hkakabo Razi National Park. Kaulback was loosely associated with Lord Cranbrook, Francis Kingdon-Ward, and Bertram C. Smythies 29 , 30 , 31 , 32 , 33 , the latter used much of Hebert Cecil Smith’s information from “Notes of the birds of Burma” 34 in his field guide “Birds of Burma”. Smythies 31 and Mayr 35 provided detailed sight records of the birds found by Kaulback, and by Major John K. Stanford 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 and Garthwaite 34 . In addition, the botanist Francis Kingdon-Ward 51 , 52 , 53 , 54 , 55 , 56 , 57 provided some additional specimens to the collections (Kaulback participated in some of Kingdon-Ward’s expeditions). The specimens used for this analysis, were collected by Kaulback (96 specimens), Lord Cranbrook (34), Stanford (30), Kingdon-Ward (12), and an anonymous collector (possibly identified as Kingdon-Ward based on the collection date and locality: 1). All these records are the baseline for reconstruction of the historic bird community used herein.

All the historic specimens are held in the Ornithology Section of the BMNH in Tring, UK (collections visited during the study are listed in “Appendix A”, Online Supporting Information). They were collected between January 1, 1900 and September 20, 1939 (16 specimens are labelled without any date). However, most of the specimens were collected in 1931 and 1938, while the other years show a relatively low coverage (Fig.  2 ).

Individuals (specimens) sampled per year in the Hkakabo Razi Landscape pre-1940 and post-2000 with comparable methods and effort.

Kaulback and colleagues used mainly shotguns in the Hkakabo Razi area and also set snare traps 58 . Kaulback gives a rough indication of his shotgun collecting effort. It is apparent that there was probably two individuals shooting birds for a maximum of “half an hour” each day 58 . The effort for the snare trapping is not documented. However, from the labels written at the time of collection, ~ 5% of the specimens in the Hkakabo Razi Landscape were described as “snared in”. The specimens were collected on a total of 56 capture dates for pre-1940 (dates derived from labels in the collections). This is likely to equate to the number of days Kaulback and his colleagues sampled birds with shotguns or snare traps.

The historic collection covers an area between 27.10 North degree to 28.50 North and 96.50 East to 98.40 East (Fig.  1 ). The historic spatial extent has been chosen with a maximum overlap with the recent collection in order to maximise the comparison between the two periods. Therefore, we neglect in any analysis further localities of historic and recent collectors, particularly towards the South of the study sites (the so-called “The Triangle”) and east in Yunnan (China) (Fig.  1 ). The historic sites used in this study, sum up to 17 and have been sampled mainly in February/March (13% of the specimens pre-1940), July–September (34%), November-January (31%) in 1931 and 1938. We verified all data to the best of our knowledge to maximize accuracy and precision.

Only one historic record has been corrected based on inconclusive data (post-museum procedure), because “Adung valley” is certainly not at 97.00 East (as written on specimen label), because 97.00 East is located in India (BMNH 1938.5.5.1, Strix aluco , Female, collected by Kingdon-Ward on 7 March 1937). We corrected the locality’s coordinates in our database by using the coordinates as from other specimens’ labels with the same locality name (“Adung Valley”).

Recent collection and field data accumulation

The post-2000 data were collected between February 9, 2001 and March 20, 2006 (Fig.  1 ). This dataset comprises collections made by John H. Rappole and S.C.R., with significant support from Thein Aung, Nay Myo Shwe, Myint Kyaw, Myint Aung, and Chris M. Milensky 19 , 20 , 21 , 59 , 60 , 61 , 62 , 63 . For all recent sampling included in this study, mist nets of 12 m × 2.6 m have been used (number of capture days and mist nets detailed in Table 1 ). Typically, nets were set from 05:00 to 10:00 and from 15:00 to 18:00 local time. Recent sites were sampled for 2 days in 2001 and for 1 day each in 2004, 2005, and 2006 (details on capture days and net numbers in Table 1 ). The sampling season was mainly February to March for the recent sites and there are 65 capture days for the post-2000 period included in this analysis (Table 1 ).

The methods during historic (snares/shotguns) and current data collections (mist nets) imply differences employed in collection methods. Consequently, some difference based on the methods might explain at least part of the differing species composition (further details in the discussion). However, the datasets are very close—if not identical—for several characteristics: elevational band (between 400 and 2000 m in both periods, with an occasional locality from a higher elevation); capture localities within a small spatial margin (maximum distance between the sites is 25 km; Fig.  1 ); days of capture (56 vs. 65). The number of sites within the general study area was 17 versus 17. However, the exact localities are different (Fig.  1 ). The selection criteria for the historic sites is not documented. The recent sites were chosen randomly and are within walking distance of an existing settlement. Historic and recent sites were selected independently from each other.

We use three terms to characterize the bird communities (which are also the dependent variables in the tests as outlined below). Species richness is the number of species within the collections. We use the number of species per period (or per land-cover type or per locality) to have a measurement for comparison. With limitations, it is also possible to establish a measurement of abundance for each of the two periods, since all collections show for several species different numbers of sampled individuals per capture site (i.e. the number of samples detected for each species per site). This is described here as relative abundance . The number of individuals sampled per species and period is a measurement of abundance. The species composition comprises a list of species names per site (or locality or period).

Land-cover and habitat data

For Hkakabo Razi Landscape, land-cover and land-use classifications are available from 1989 26 , 2001 19 , and 2016 26 . Land-cover has been classified as mostly intact. The changes in land-cover types are marginal with an annual deforestation rate of ≤ 0.23% from 1989 to 2016 26 (this is indistinguishable from background noise). There has been almost no change in land-cover for the historic bird localities from 1989 to 2016. Only 47 times the land-cover form of the two classifications changed from 1989 to 2016 (Table 2 ) for the exact localities of the 173 recorded pre-1940 birds (the Landsat 30 m by 30 m pixel 26 ). Most of these land-cover changes are negligible and based on melting snow (e.g., from snow/ice/glacier to rock/bolder). Except for the Putao plains, hardly any change occurred from 1989 to 2016 19 , 26 . The pre-1940 localities have remained undeveloped 58 , 64 , 65 or are close to the same settlements as in 2016. Since most of the habitat remains pristine, all historic (pre-1940) localities are assumed to be of the same land-cover type as classified in 1989. All post-2000 localities are assigned to the land-cover classification as of 2016.

The land-cover has been classified with the same class names for 1989 and 2016 26 : pine/rhododendron, forest < 600 m, forest 600–1800 m, forest > 1,800 m, grassland/pasture, ice/glacier, clear-cut, paddy field, rock/boulder, secondary forest < 600 m, secondary forest 600–1800 m, settlement, shrub/bush/fern, and streambed.

Statistical outline

The largest issue for testing is the unknown sampling effort for pre-1940. It is not possible to assess the completeness of the pre-1940 datasets because this information is not available in the archives or from the specimen labels. This makes for some uncertainty when comparing the bird assemblages from the two periods. Nevertheless, we maximized comparability of the datasets, as far as possible with the archival and label information available. Details on methods are further published for post-2000 20 , 59 .

We performed an ANOVA for species richness and relative abundance to analyse the variance between the periods (pre-1940 vs. post-2000) and used a Kruskal–Wallis test if not normally distributed. In a second step, we added a generalized linear model (GLM) approach to test whether habitat or locality (sampling sites pooled as per nearest settlement name) have an effect on the species richness or relative abundance. Differences between periods and species richness (or relative abundance) were assessed using analysis of variance (ANOVA) after verifying for homogeneity of variances (Fligner test) and normality (Bartlett test). All analyses were performed in R version 3.5.1 66 and an α-level of 0.05. Observational data (count, species numbers) have been log-transformed (ln).

We assessed differences in bird species composition among periods, habitat types and localities using non-metric multidimensional scaling (NMS). Relative abundance was square-root transformed ( vegan -package). The NMS was run using Sørensen (Bray–Curtis) distance with an automatic stepping down resolution starting 200 runs from a random configuration.

Since the number of sample sites and the number of samples overall is relatively low for all analyses, we performed power analysis with the pwr -package in R to assess the strength of statistical outcomes. We assessed power always with a significance level of 0.05. ANOVA (variation of species numbers between periods) had a power of 1; GLM with response “species numbers” 0.137 and power for GLM with response “relative abundance” was 1.

There were a total of 708 individual bird records belonging to 193 species; 98 species (173 individuals) were only recorded pre-1940 and 132 species (535 individuals) were only recorded post-2000. Only 19.2% (37 species) occurred in both periods. This indicates a considerable discrepancy between the species assemblages. The top five most abundant species differed between the periods: Post-2000, the most abundant species was Alcippe morrisonia (42), followed by Alcippe rufogularis (25), Alophoixus flaveolus (19), Niltava grandis (19), and Ficedula monileger (18). For pre-1940, the most abundant species was Garrulax striatus (7), followed by Aethopyga saturata (6), Heterophasia pulchella (6), Arachnothera magna (4), and Cissa chinensis (4) (all samples and species included are listed in Table S1 , Online Supporting Information).

Analysing species composition with NMS yielded weak ties and hence should be considered with caution. Nevertheless, model-selection procedures in NMS showed that “period” is the best explaining factor out of “period”, “habitat (2016)” and “locality” (CCA stepwise permutation selection p for “period” = 0.02, all other p  > 0.05). Contrasting to the species composition, species richness showed no differences. Species richness did not change from pre-1940 to post-2000 (Kruskal–Wallis χ 2  = 3.774, df  = 1, p  = 0.052; Fig.  3 ). When modelling species richness with the predictors “locality”, “period”, “land-cover 1989” and “land-cover 2016”, the latter two had an effect on the species richness ( p  < 0.001, GLM models “s2” and “s3” in Table 3 ). Considering each predictor singly with species richness, only “period” predicts species richness (models “s4” to “s7” in Table 3 ).

Species numbers ( A ) and relative abundance ( B ) per collecting locality of birds in the Hkakabo Razi Landscape pre-1940 and post-2000 with comparable methods and effort. The black solid line indicates the median, circles indicate outliers, whiskers 95% CI and box margins 75% CI.

The relative abundance changed from pre-1940 to post-2000 (Kruskal–Wallis χ 2  = 26.125, df  = 1, p  ≤ 0.001; Fig.  3 ). When modelling relative abundance, neither “land-cover 1989”, “land-cover 2016”, nor “period” had an effect on the relative abundance, but only “locality” ( p  < 0.001, GLM model “a1” in Table 3 ). Considering each predictor singly with relative abundance, all but “species” predict relative abundance (models “a3” to “a7” in Table 3 ).

The community structure follows a typical species rank-abundance curve (Fig.  4 ), with few species of many individuals and many species with few individuals. The species-abundance shows a similar pattern for pre-1940 and post-2000, however, the post-2000 is about one magnitude higher (Fig.  4 ).

Species rank-abundance (i.e. number of specimens) curve of all detected individuals per period considered in the analysis of birds in the Hkakabo Razi Landscape pre-1940 and post-2000 with comparable methods and effort.

The long-term datasets of Hkakabo Razi Landscape inform us that while species richness did not change from pre-1940 to post-2000, species composition and the relative abundance changed significantly, including the five most abundant species in each period. The magnitude of change in species composition, with less than 20% of taxa shared between the two time periods, is particularly noteworthy and unexpected.

In a world where temporal patterns of biodiversity have received much less attention than spatial ones 67 , 68 , the datasets from Hkakabo Razi Landscape are important because, almost uniquely, they give us the chance to differentiate between anthropogenic impacts and background temporal changes in ecological communities in an extensive area of Old World forest biome, with a timescale of almost a century (primarily between 1931 and 2006, although a minority of specimens were collected as far back as 1900). The datasets are unusual for such studies because they are based in a subtropical rather than a temperate area and are drawn from a large tract of forest (11,280 km 2 ) that remains almost pristine. Furthermore, they are statistically valuable since, although the methodologies between the historical and more recent surveys are not the same, they are well documented and share many comparable components and are sufficiently informative to give us the opportunity to observe temporal changes not only in species diversity and species richness, but also crucially in species composition, and to a lesser extent, relative abundance within species.

The results from Hkakabo Razi Landscape, particularly the large variation in species composition, reflect earlier findings from Costa Rica, where working with more detailed data, albeit gathered over a much shorter time-scale (1985–1992) 67 , researchers noted that tropical bird communities far from being stable systems are in reality dynamic ones with a ‘complex mix of stable and variable components that produce changes in species composition and abundance over various spatial and temporal scales’. This variability in Costa Rica was observed not only, as might be expected, in secondary forest (partially as a response to vegetational succession) but also, though to a lesser extent, in mature forest. It should also be noted that rates of temporal turnover will also vary amongst ecosystem types 67 , 68 and in relation to local environmental factors, with variable responses to the same disturbance events 68 .

In contrast to the Hkakabo Razi Landscape study, which provides information on long-term temporal patterns, most others have focused more on short-term fluctuations driven by resource availability 69 , 70 . These include, for example, the movement of birds in response to the availability of fruits in a mountain biome in Costa Rica; the differential movement of insectivorous and frugivorous birds in Kenya in response to food availability; and the movement of birds in the Australian tropical forest in response to climatic variations and subsequent resource availability 71 . Other studies, both short and long-term, and over a variety of spatial scales, have focused on changes in bird diversity and composition but primarily in areas that have been significantly impacted by anthropogenic activities. These include, for example, studies of the temporal variation of taxonomic and functional diversity in the conterminous USA based on 40 years of data (1970–2011) 72 , 73 , 74 . Such studies, although extremely valuable, do not provide data that enables us to develop conservation policies that take into account purely natural cycles in diversity and abundance.

Without an understanding of natural long-term variability in essentially pristine ecosystems, it is almost impossible to differentiate between human-induced change and natural cycles in those that are anthropogenically modified. As such, the impacts of human induced environmental change may be overstated when comparing differences in species composition at any particular site over a longer time period.

That said, the results of Hkakabo Razi Landscape, should be treated with some caution. For although some of the variables in the collection methods between the pre-1940 and post 2000 datasets are (surprisingly) comparable, others are not. Those that are similar (as outlined in the Methods section) include: elevational band, primarily between 400 and 2000 m in both periods; number of collection sites, 17 versus 17; spatial distribution of capture localities, which although not the same, have a maximum distance between the sites of 25 km (Fig.  1 ); the number of capture days (56 vs. 65); period of collection 8 years (primarily from 1931 to 1938) and 6 years (from 2001 to 2006)—all of this is important since typically it has been predicted from elsewhere that there will be around twice as many species detected in a decade as in a single year 68 . However, there are also differences, the most important of which is capture method. This could be particularly important in an ecosystem, where it is predicted (based from data collected elsewhere) that high species diversity is inversely correlated to low species density—i.e. many species with fewer individuals. It is probable that some of the difference in species composition observed from the pre-1940 post 2000 data is directly attributable to differences in collecting method. Post-2000, the exclusive use of mist-nets would favour the collection of those bird species that favour niches nearer to ground level, whilst pre-1940, a hunter with a gun, will have greater success with birds, which are more visible and/or high in the canopy. This is reflected in the five most abundant species of pre-1940, which are either more colourful (e.g., brightly coloured such as some laughingtrushes), or easy to watch (such as Arachnothera magna which occurs in open forest patches and at the forest edge), or more visible through their behaviour (e.g., loud alarm calls such as from Garrulax striatus ). Contrasting, the top five post-2000 species are more secretive in behaviour and less bright coloured, hence less obvious to the hunter.

Furthermore, the by one magnitude higher, relative abundance post-2000 is probably a methodological bias. While mist nets capture, for example, the largest part of an Alcippe morrisonia flock (20 + individuals, own unpublished observations), the hunters pre-1940 shot one individual out of a flock, and the remainder of the flock certainly escaped and disappeared without trace in the forest. Moreover, mist nets, unlike hunters, do not discriminate since they catch every bird that becomes entangled in them whereas a hunter may either consciously or subconsciously eschew birds of a species for which a number of specimens have already been collected. Theoretically, the only way to compare the relative abundance between the two periods would be to collect birds today in a manner similar to that employed pre-1940. However, these methods, shooting and snares, are obviously not possible or desirable today for ethical reasons and Myanmar national laws.

In addition to variation in capture methods, there is some variation in the season of capture between the two datasets. Post-2000, all 535 individuals of the 132 species were collected in the months February–March. However, for the 173 specimens collected from pre-1940, 13% were captured in the February–March time period whilst the remainder were collected mainly in July–September and November-January. This is important since Myanmar hosts a diverse winter migrant bird fauna and since inter-seasonal fluctuations in bird composition are known to be on average higher for migratory and nomadic species than for sedentary ones 70 , 75 , 76 . However, interestingly, hardly any long-distance migrants were detected in either the pre-1940 or post-2000 datasets so that migration status alone cannot explain the large fluctuations seen in species composition between the two time periods.

An additional analysis including, for instance, the phylogenetic structure 77 of the bird community or its functional traits, could add further insights. However, for this paper we have avoided such approaches since, currently, the phylogenetic structure of the phylogenetic placement and validity of the three most important families in our data set, the Muscicapidae, Timaliidae, and Pellorneidae, are controversial and all deep-phylogeny assignments are in continuous flow for many species occurring in the Hkakabo Razi Landscape (detailed in Online Supporting Information C). Meanwhile data on the functional traits of bird species from Hkakabo Razi Landscape remains incomplete and/or speculative with little detailed information on the functional groups beyond generalised descriptions, such as insectivores, granivores,… There are also no data available on seasonal variation, e.g. breeding versus non-breeding 18 . Therefore, rather than working with incomplete or speculative data sets, we focused on the parsimonious and relative robust analysis of the bird community.

Preliminary analysis of the long-term Hkakabo Razi Landscape datasets provide some very interesting information that is of importance not just to bird ecologists but to the much broader scientific community, especially those concerned with environmental change, including climate change and habitat fragmentation, and its impact on biodiversity. The datasets help put short-term fluctuations into a meaningful context, for example within monitoring programmes, and provide information that gives an insight into whether contemporary trends in diversity are simply a response to anthropogenic-induced changes or are the result of dynamics originating before the onset of the Anthropocene 78 , 79 . They also have important implications for conservationists who seek to interpret the meanings of changes in faunal composition both in natural and man-made habitats and who wish to develop conservation policies that take into account natural cycles in diversity and abundance. As with interesting studies in the USA and France, the next stage for the Hkakabo Razi Landscape data are to develop more sophisticated models to determine if significant changes in taxonomic diversity are also reflected in changes in phylogenetic and functional diversities 79 , 80 , as well as determining random portion of the species richness 5 , 6 , 7 , 8 .

The two Hkakabo Razi Landscape datasets, pre-1940 and post-2000, give an invaluable insight into the question ‘what is the underlying level of temporal turnover in a bird community?’ They help us to understand background turnover in birds in a subtropical pristine forest site, which will provide an invaluable foundation (despite the caveat of different methodologies in the two datasets) when trying to assess anthropogenic impacts in increasingly disturbed habitats elsewhere. The datasets further challenge the notion that bird communities in the tropics/subtropics, even in natural habitats, are stable systems. Rather they show that there is an important temporal component to biodiversity and that natural ecosystems are dynamic with a complex combination of stable and variable components and that this dynamic component impacts in different ways and with different severity on species diversity, species composition, and relative abundance.

Data availability

The data used for analysis is available in the Online Supporting Information.

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Acknowledgements

Our special thanks are for John H. Rappole, who invited S.C.R. the first time to join him on an expedition to the Hkakabo Razi National Park in 2001. We would also like to thank all friends and colleagues supporting the fieldwork of this study during the last two decades, namely: Marcela Suarez-Rubio, Thein Aung, Nay Myo Shwe, Myint Kyaw, Sang Nai Dee, Myint Aung, Braing Shaw, Kyaw Lin, Tu Myint U, A Jo, Chris Milensky, Tay Zah, Aung Maung, Aung Kyaw, Naing Lin, Dee Shin, Htin, Hdoa Dee and over 100 helpers during the eight trips to the region. We thank Aung Khin and Thandar Kyi, who organised the expeditions in 2004, 2005, and 2006, and Tay Za who managed the 2001 trip. We would like to thank the curators, managers and technicians of the various collections S.C.R. visited for the study, namely (indicating the collection while they were employed there during the visits): Martin Päckert SNHD, Paul Sweat AMNH, Leo Joseph and Nate Rice ANSP, Mark Adams and Robert Prys-Jones BMNH, Jack Dumbacher and Moe Flannery CAS, Sylke Frahnert MfN, Hein van Grown NMN, Carla Dove, Gary Graves, Helen James, and Terry Chesser NMNH, late Anita Gamauf NHMW, Ulf Johansson NRM, Freddy Woog SMNS, Jon Fjeldså ZMUC, Till Töpfer and late Stefanie Rick ZFMK. Funding to visit collections was provide by the European Union SYNTHESYS framework (FR-TAF-6275, DE-TAF-6206, ES-TAF-2501, AT-TAF-2481, GB-TAF-108, SE-TAF-1312, NL-TAF-4369, GB-TAF-4367, DK-TAF-4963), and to visit the field by the National Geographic Society (GEFNE48-12). Besides all professional disagreement, we thank Hannah Fraser plus two anonymous reviewers and the editor for their valuable input on previous versions of the manuscript. Late Uga, former Director of the Nature and Wildlife Conservation Division, initiated the 2001 trip and we thank him for his efforts to make the expeditions possible. Without his support, none of the work done in the region would have occurred. We thank the Nature and Wildlife Conservation Division of the Forestry Department, and especially former Director Khin Maung Zaw, for permission to conduct the study (Myanmar Collection and Export Permit # SI/4697/2004). Tin Tun was implementing the permits in 2005 and 2006. Open access funding provided by BOKU Vienna Open Access Publishing Fund.

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S.C.R. developed the study, collected that data, analysed all species’ statistics. P.J.J.B. scrutinized each sentence for English and supported significantly the discussion section and all discussions with Reviewer B. S.C.R. and P.J.J.B. equally wrote, contributed and finalized the text.

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Renner, S.C., Bates, P.J.J. Historic changes in species composition for a globally unique bird community. Sci Rep 10 , 10739 (2020). https://doi.org/10.1038/s41598-020-67400-z

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The Relationship between Landscape Construction and Bird Diversity: A Bibliometric Analysis

Yanqin zhang.

1 College of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou 350002, China

Ningjing Lai

Jianwen dong.

2 Engineering Research Center for Forest Park of National Forestry and Grassland Administration, Fuzhou 350002, China

Jiaying Dong

3 School of Architecture, Clemson University, Clemson, SC 29634, USA

Associated Data

The data used to support the findings of this study are available from the corresponding author upon request.

Urbanization development is the main cause of drastic habitat changes and biodiversity loss, and urban green space construction is one of the effective ways to mitigate biodiversity decay. The proper construction of urban green space landscapes can maintain or increase the resources provided by urban biodiversity, especially bird diversity. This paper is based on 4112 papers published in this research area between 2002 and 2022, and CiteSpace was used to conduct a bibliometric analysis of the research area in terms of the number of articles published, the country or region of publication, core authors, and academic development. The paper systematically reviews the hotspots, history, and frontiers of research on landscape architecture and bird diversity. At the same time, the relationship between landscape construction and bird diversity is discussed in the context of landscape features, vegetation characteristics, and human behavioral activities. The results revealed: (1) research on the association between landscape camping and bird diversity received high priority from 2002 to 2022. Moreover, this research area has become a mature discipline. (2) Throughout the research history, there are four research hotspots (fundamental research on bird communities, influencing factors related to changes in bird community characteristics, research on bird activity rhythms, and ecological and ornamental values of birds), four development stages (2002–2004, 2005–2009, 2010–2015, and 2016–2022), and several research frontiers. (3) Our aim was to reasonably consider the activity characteristics of birds in future landscape construction, and to thoroughly study the landscape construction strategies and management principles for the harmonious coexistence of humans and birds.

1. Introduction

The continued advance of urbanization has been identified as a major cause of habitat destruction and biodiversity loss [ 1 , 2 ]. As cities continue to expand, especially in biodiversity rich areas, urbanization will pose a serious threat to global biodiversity [ 3 ]. The loss of biodiversity due to urbanization is a serious issue of global concern [ 4 ]. Urbanization often leads to severe changes in the diversity and distribution of many species and affects the quality and quantity of ecosystem services available to people living in urban areas [ 5 , 6 ]. Global biodiversity is declining at a much faster rate than previously anticipated, and action must be taken to balance the relationship between people and nature. Development minimizes ecological loss and maximizes human wellbeing. Since the ratification of the Convention on Biological Diversity, local readjustment programs have become the primary tool used in many countries to manage biodiversity, promote local action, and inform overall urban planning and decision making [ 7 ].

In this context, green spaces are important for the conservation of urban biodiversity. Urban green spaces provide habitat for wildlife and increase the functional connectivity of local fauna [ 8 ]. At the same time, parks in urban areas are also “islands” or habitat fragments for wildlife [ 9 ]. At the same time, the construction of urban animal habitats is closely related to urban landscape construction. For example, urban green areas, parks, communities, tree corridors, gardens, etc. are important habitats for various bird species in cities [ 10 ]. Therefore, the urban landscape is closely related to wildlife survival. The factors influencing the level of landscape also affect the bird communities within cities [ 11 ]. Urban landscapes, including green spaces and park landscapes, are inhabited by a variety of native birds, which help maintain biodiversity in urban landscapes. However, the surrounding landscape affects their ability to support native birds and protect urban biodiversity [ 12 ].

As an important component of biodiversity, birds are an important indicator of the health of urban ecosystems [ 13 ]. Moreover, birds are an important part of the natural ecosystem and an important part of the food chain. Once the ecosystem is disturbed, it will have a great impact on birds. Birds are more sensitive to environmental changes, indicative of environmental changes, more numerous, and bird communities are easier to observe [ 14 ]. Birds are often used to evaluate environmental strengths and weaknesses and are often used to monitor ecosystems by studying bird communities. They are one of the indicators that indirectly respond to the state of the ecosystem. Therefore, there is a growing interest in studying the relationship between landscape characteristics and bird communities by observing the characteristics, status, and behavior of bird communities.

Urban landscape creation and bird diversity are correlated. Urban green space area has a positive effect on bird species richness [ 15 ]. Urban park green space size is an important factor affecting bird abundance and diversity [ 16 ]. Urban park area and bird diversity showed a positive correlation [ 17 ]. In addition, urban landscape fragmentation, connectivity, and urban rural gradients also have an impact on bird pair positivity. Meanwhile, the vegetation composition and structure of urban parks have an influence on birds, and horizontal vegetation cover is particularly important for birds [ 18 , 19 ]. In addition, the presence of humans is also generally considered to have a negative impact on the richness and diversity of bird species [ 20 , 21 ]. These suggest that urban green space landscaping needs to consider both human and bird habitats. Therefore, it is important to explore the influencing factors of bird diversity at the landscape level and to discuss how to build the landscape from the perspective of bird diversity in order to improve the habitat and enhance urban biodiversity.

The study used a comprehensive bibliometric analysis to explore the patterns and development history of research between landscape camping and bird diversity. This study analyzed the number of published articles, countries or regions of publication, core authors, and academic developments. This was followed by keyword analysis (research hotspots, research history, and research frontiers), combined with visual mapping drawn by bibliometric software to provide a systematic and detailed description of the intellectual background of the research area. The relationship that exists between landscape camping and bird diversity is also discussed from three aspects (landscape characteristics, vegetation characteristics, and human behavioral activities). It will help scholars to value the role of landscape architecture on urban bird diversity and to better understand the overview and recent progress in the field. These studies were retrieved from the Web of Science (WoS) core collection database and analyzed using CiteSpace visualization software to create a visual knowledge network with a focus on four key points:

• What are the current and growing trends in publishing in the field of landscape construction and bird diversity research?
• What countries/regions and authors have influenced landscape construction and bird diversity research?
• What are the research hotspots and historical and frontier issues in the field of landscape construction and bird diversity research?
• What relationships exist between landscape features, vegetation features and human behavioral activities and bird diversity?

In this study, this paper assesses the literature and its articles in the field of landscape camping and bird diversity research published between 2002 and 2022, and then provides a more precise and specific analysis based on a collaborative network map of countries/regions and authors in the research field. This study also includes a complete analysis and description of keywords (distribution, history, and frontiers) to better reflect research hotspots and directions, as well as the interactions between research hotspots and time scales. Based on this, the paper assesses the relationship between landscape camping and bird diversity in three ways. Finally, this paper proposes a research direction for the sustainable development of urban bird diversity through landscape architecture.

2. Materials and Methods

2.1. data collection.

On 24 February 2023, 4661 articles were retrieved from the Web of Science (WoS) core collection database. This WoS core collection database was chosen for the collection of the research literature for this study. The search formula was (TS = (landscape OR park OR green land OR plant OR bird habitat) AND TS = (bird Diversity) AND TS = (design* OR plan* OR build* OR construct*)) AND ((LA == (“ENGLISH”)) NOT (PY == (“2023”))). In this paper, the literature was imported into CiteSpace for deduplication. Article types were selected for article and review, and after screening and review 4549 articles were finally used for analysis.

2.2. Data Analysis

The bibliometric is a set of quantitative tools for analyzing bibliographic data. These tools can fully analyze information related to the published literature in the field of study, including publications (year, country or region, author, etc.), keywords, and citation trend analysis, to help scholars fully grasp the knowledge structure of the field of study [ 22 ].

Visualization and analysis software frequently used includes CiteSpace, VOSviewer, Histsite [ 23 ], Bibexcel [ 24 ], and R-Package Bibliography [ 25 ]. In particular, CiteSpace supports many types of bibliometric studies, including collaborative network analysis, co-word analysis, author co-citation analysis, document co-citation analysis, and textual and geospatial visualization, and its bibliographic and visualization functions can present the trends and knowledge association status of disciplinary frontiers in a very visual way, which can allow the key information of the research field to be grasped quickly [ 26 , 27 , 28 ]. Therefore, this paper uses CiteSpace (5.7.R5) to quantitatively evaluate the relevant literature (number of articles issued, country region of issue, core authors, academic development). In addition, we constructed corresponding knowledge maps (keyword co-occurrence map, time zone map, and highlight map) based on the literature in the field of landscape architecture and bird diversity research, and identified research hotspots, history, and frontiers, in order. We also explore the relationship between landscape architecture and bird diversity from three aspects of landscape architecture (landscape characteristics, vegetation characteristics, and human behavioral activities). The purpose is to provide a reference and foundation for future research.

3. Basic Situation Analysis

3.1. trends in the number of published papers.

By analyzing the annual changes in the number of publications in a research field, it is possible to assess the current state of research in the field and to predict future trends. In this paper, we analyzed a total of 4549 publications issued between 2002 and 2022 to obtain the number of publications per year for the last two decades and to forecast their trends ( Figure 1 ). The field of landscape camping and bird diversity research has steadily developed over the last two decades. Figure 1 shows that from 2002 to 2022 the number of studies in the subject area of the scientific network database increased year by year, and the research history can be divided into three phases: (1) the initial phase, from 2002 to 2005, with the number of articles between 95 and 105 per year; (2) the cumulative phase from 2006 to 2012, with the number of publications remaining relatively stable each year, with the number of articles between 130 and 200 per year, with 2012 being the inflection point for development; and (3) a steady growth phase from 2013 to 2022, with the volume of the literature steadily increasing year by year and fluctuating during 2017–2018, but remaining at 250 to 300 articles per year. The number of publications increased by 402 articles in 2021.

Statistical chart of the number of articles issued.

The growth trend of the field of study is predicted by compiling year-by-year statistics of the number of articles published in the field of study and by means of a Price’s curve. The growth of the scientific literature is exponentially related to time, and the closer the coefficient of determination of the trend line is to 1, the better the fit is. It also indicates the faster growth rate of the number of publications in a given subject area in the future [ 29 ] ( Figure 1 ). Figure 1 shows that the sample paper load versus time is given by the equation y = 2×10 3 -63e 0.0744x , and its trend line determinant is R 2 = 0.954. It reveals that the number of publications in this research area show a clear exponential growth trend as time advances. The exponential line of publications in recent years, with an R-squared value of R 2 = 0.954, represents its reliability. The closer the R-squared value is to 1, the better the fit of the exponential line to the figures. This demonstrates the reliability of the equation in predicting the number of articles published in this research area. Moreover, it indicates that the development of the field of landscape camping and bird diversity research is accelerating.

3.2. Country/Region Cooperation Networks

By analyzing the collaborative networks between countries/regions, it is possible to identify priority countries/regions that produce a large number of publications and have a significant impact on the research field, and to determine the collaborative relationships between them [ 30 ]. Academic articles in the field of landscape architecture and bird diversity have been published in 134 countries/regions. Centrality indicates the importance of a particular node in the network. Therefore, the greater the centrality, the greater the influence of the posting in that country/region [ 31 ]. A list of the top 20 countries with the largest number and impact of publications in this research area can be found in Table 1 . Most countries worldwide are involved in this field of study, with the USA being the most published country in this field (1311), followed by England (488), Germany (410), and Australia (387), among others. In terms of centrality, England (0.28) has the highest score, followed by Australia (0.1), France (0.1), and the USA (0.08); although the number of articles published in England, Australia and France is less than that of the USA, their impact is higher than that of the USA.

The 20 countries or regions with the highest total number and centrality of research papers published in the study.

The USA is dedicated to studying the effects of urbanization, habitat structure changes, and human drivers on birds, and the effects of urban landscape vegetation on birds [ 6 , 32 , 33 , 34 ]. In addition, the UK has focused on the impact of different environmental schemes on biodiversity [ 35 , 36 ], with an emphasis on the ecological impacts of changes in agricultural landscapes [ 37 , 38 ]. Moreover, the biodiversity values of forest, secondary forest and planted forest are compared [ 39 ]. Germany focuses on the effects of landscape structure and land use intensity on plant, bird and other flora and fauna communities [ 40 ]. Furthermore, the differences in biodiversity between managed and non-managed forests and the interrelationship between biodiversity and land use intensity are investigated [ 41 , 42 ]. Australia focuses on the relationship between urban–rural gradients and biodiversity [ 43 ]. The French studies include the effects of climate change on the phylogenetic diversity of plant, bird, and mammalian communities across Europe [ 44 ]. China ranks sixth in the number of articles published in this field, but its influence is not high and still needs further development.

3.3. Author Cooperation Networks

It is useful to know how scholars interact in the research field to understand the research dynamics of the research area. A total of 4549 studies were searched for in CiteSpace, and the authors were obtained with the time span from 2002 to 2022, node type “author”, and parameters set to the software default parameters. The collaborative network mapping is shown in Figure 2 and the table of the top ten authors in terms of number of publications and centrality is in Table 2 . The base information of the graph is N = 830, E = 1394, and Density = 0.0041. The size of the nodes in the graph reflects the number of articles published by scholars, and the node linkage and the thickness of the line segments reflect the cooperation relationship and the frequency of cooperation among scholars. From Figure 2 , it can be seen that authors in this research field form a rich collaborative network. There exists a group research network with multiple associates, showing the characteristics of local concentration. Katrin Boehninggaese (32, 0.02) and Matthias Schleuing (32, 0.02) have published the most articles in this field and are also highly influential. The research topics of Katrin Boehninggaese and Matthias Schleuing include interactions between human activities and bird diversity, analysis of climate change impacts on plant and animal diversity, and spatial patterns of plant and bird diversity [ 45 ]. Moreover, the role of anthropogenic disturbance on the effect of animal seed dispersal was jointly analyzed, and many citations were obtained [ 46 ]. The collaboration of Katrin Boehninggaese and Matthias Schleuing was initiated earlier and is maintained in close collaboration. Meanwhile, close collaboration is maintained with authors such as D. Matthias Dehling (12), Eliana Cazetta, Marco A. Pizo, and Pedro Jordano, forming the largest group of authors in the field. In addition, David B. Lindenmayer has 26 publications, as the third most published author, and has an independent network of collaborations.

Author collaboration network map.

The 10 authors with the highest total number and concentration of research papers published in the study.

Teja Tscharntke (18, 0.04) is the author with the highest centrality and the highest impact in the published literature. His research focuses on the influence of landscape features on the biodiversity of plants, birds, and insects, the summary of activity patterns of birds, bats, etc., in different landscapes, and the analysis of the importance of landscape benefits generated by landscape factors on bird diversity [ 47 , 48 , 49 , 50 ]. The second major research network consists of authors such as Ian Macgregorfors (21) and his associated team. In addition, influential articles by authors such as Jiri Reif (10, 0.04) form a more focused collaborative network with authors such as Federico Morelli (14, 0.01).

3.4. Academic Development

A dual-map overlay is an analysis method that shows the domain-level concentration of references by reference path [ 31 ]. Figure 3 was created using CiteSpace software with a source circle size = 0 and target circle size = 0. Then, the citation lines were merged by the z-score function to obtain Figure 3 . The z-score function allows the highlighting of strong connections, making them easier to identify. Figure 3 shows that there is only one major citation path in this research area, and Table 3 shows this path and trends along with the names of the citation and citation regions, where the z-score is rounded to the nearest thousand. Figure 3 and Table 3 show that the field of study has evolved from ecology, earth, and marine, with a gradual shift to plant, ecology, and zoology. The literature in the fields of ecology, earth and oceans is fundamental to the field of landscape architecture and bird diversity research.

The dual-map overlay.

The key citation trends.

4. Discussion

Keywords are a strong summary of a paper’s topic, the frequency of keyword co-occurrence reflects the frontier hotspot of a research topic in a certain period, and the keyword centrality reflects the importance of keywords in the co-occurrence network. CiteSpace is used in this study to generate keyword co-occurrence mapping, keyword time zone mapping and keyword highlighting mapping for the research area. The research area is analyzed in terms of research hotspots, research history, and research preamble, respectively. In this paper, the relationship between landscape architecture and bird diversity is investigated from three aspects of landscape architecture (landscape characteristics, vegetation characteristics, and human behavioral activities) in view of the severe urbanization decline.

4.1. Research Hotspots

4.1.1. research hotspots.

This paper uses CiteSpace to generate keyword co-occurrence plots ( Figure 4 ). The prune parameters (prune: pathfinder, and prune merge network) were used to create the keyword co-occurrence network graph, and the basic parameters of Figure 4 were N = 811, E = 1289, and D = 0.0039. The node size indicates the frequency of keyword occurrence; the larger the node, the more frequently the keyword occurs and the more representative of the hotspots in the domain. The depth of the connection line between nodes indicates the strength of association between nodes. Figure 4 shows that the research contents of this research domain are intertwined with each other with strong connections. Meanwhile, Table 4 counts the most frequently studied and influential keywords (the top 20) in the past two decades. Table 4 shows that the keywords with high frequency are diversity (1675), biodiversity (1338), conservation (1111), bird (1099), species richness (682), community (624), and habitat (598). The keywords show that biodiversity and conservation are widely studied by scholars in this research area. Among them, scholars focus on species richness and bird communities. Although these research keywords have been studied in high numbers, they have had less impact. Additionally, as shown in Table 4 , the most influential studies in this research area are farmland (0.16), butterfly (0.14), farmland bird (0.13), biogeography (0.13), agriculture (0.11), index (0.1), consequence (0.1), and bird species richness (0.1), keywords that rarely occur, but have a profound impact on the field of study.

Keyword co-occurrence map.

The 20 keywords with the highest total number and concentration of research papers published in the study.

Therefore, according to Figure 4 and Table 4 , the current research hotspots in this research area contain four research hotspots: basic research on bird communities, influencing factors related to changes in bird community characteristics, research on bird activity rhythms, and the ecological and ornamental values of birds.

First of all, the basic study of bird communities was pioneered and a solid foundation laid for this research field. The main keywords are diversity, abundance, community, pattern, habitat, bird species richness, etc., focusing on the study of bird community structure, bird behavioral characteristics and bird habitat. Moreover, the research does not only stop at the study of birds, but also gradually expands to the study of biodiversity, including butterflies and insects. Bird residence type, food habits, feeding methods and habitat layers can be used as the basis for classifying bird community structure [ 51 ]. In addition, the ecological behavior of birds can be divided into four aspects: feeding behavior, breeding behavior, spatial behavior, and community behavior. Feeding behavior is mainly the study of birds’ feeding response, including the selection of food habits and feeding bases, group feeding and feeding rhythm, etc. The feeding behavior of birds is also a behavioral adaptation to the local environment, so habitat degradation is the main reason for birds’ feeding behavior [ 52 , 53 ]. Birds differ in their plant preferences, and the distribution pattern of plant flowering and fruiting periods has a significant positive effect on the level of bird diversity. Bird feeding behavior is also a means for plant seed dispersal, and dispersal by birds is important for plant communities and for ecosystem stability [ 54 , 55 , 56 ]. Meanwhile, the “community structure analysis method” is used in the study of urban bird habitat landscape [ 57 ]. Moreover, it has gradually become an important indicator and hotspot for maintaining landscape ecology and sustainable urban development.

The factors influencing the changes of bird community characteristics (natural factors, human disturbance) are studied in depth. The main keywords are forest, vegetation, landscape, agriculture, farmland, tree, plant, etc. The correlation of bird diversity (abundance, multiplicity, etc.) with trees, plants, vegetation, etc., and even forests and farmland, are studied. We will investigate the correlation between bird diversity and forest and farmland and seek measures to protect and enhance them. Scholars have conducted exploratory studies on bird communities from various aspects and have achieved many useful results. There are many studies on wetland landscapes, forest landscapes, urban landscapes, and farm landscapes in different habitats [ 58 , 59 , 60 , 61 ]. A series of studies on the distribution types of bird habitats, the relationship between vegetation and bird communities, and the effects of forests on bird communities have been conducted in considerable depth. Among them, vegetation characteristics and structure and intensity of human disturbance are important factors affecting bird species composition. Some current domestic and international studies have shown that plant species or structures are more attractive to certain kinds of birds, that certain plant phenological periods show peaks in the degree of attraction to birds, and that factors such as tree species diameter at breast height and height, plant density, age, rotation time, tree density, plantation landscape connectivity, understory type, number of species planted, and origin of planted species largely determine local bird diversity and also affect local bird diversity [ 62 ]. For example, native plant vegetation is more capable of enhancing bird diversity [ 63 ]. The positive benefits of tree cover density should be very important [ 64 ]. There is a significant linear positive effect of shrub density on both bird species richness and abundance [ 65 ]. Tree and shrub density were also the main drivers of bird community composition, followed by tree species diversity and landscape forest cover. The degree of variation in bird diversity varies more with mean breast size. Compared to other arthropods and mammals, birds are more sensitive to disturbance by human activities. This is especially true for the conversion of forests to agriculture. Although several studies have investigated the effects of disturbance on the functional diversity of birds, the results varied widely, with differences between positive, negative and no effects [ 62 , 66 ]. It is possible that this variation is due to the type of disturbance investigated in the study, such as land use change and logging, as well as the intensity or frequency and the wide variation in environmental type [ 67 , 68 ].

Focusing on the study of the rhythm of bird activity, the key words are these: conservation, land use, urbanization, impact, management, population, consequence, conservation planning, etc. With the advancement of urbanization, climate change, and land use change, the change of bird community characteristics is gradually emphasized as an important ecological indicator into cities. In parallel with the development, landscape pollution has increased, which has a greater impact on birds. Therefore, more and more studies are focusing on the rhythm of bird activity, seeking strategies to address the decline in environmental quality and biodiversity. Bird community characteristics change with temporal, spatial and temporal changes. As urbanization accelerates, natural forests are gradually replaced by gray buildings and artificial forests, leaving less and less space for birds to roost. Urban green spaces such as parks, gardens, campuses and greenways have become important refuges for urban biodiversity, even playing an equal or greater role than nonurban environments [ 69 ]. Due to the rise of urban parks, urban landscape diversification is built upon. The urbanization process has a certain species conservation function, bird communities change in the same direction as plant communities, and the spatial and temporal changes in bird communities are inextricably linked to the food provided in urban forests and to habitat characteristics [ 70 ]. Research on the spatial variation of bird community characteristics is broadly divided into two aspects. On the one hand, there are large scale studies, which usually study different patch sizes [ 71 ], variation in patch shape [ 72 ], land use type, elevation, temperature, climate [ 73 ], etc. On the one hand, microscale studies were conducted to examine the differences in vegetation landscape, water landscape, management frequency, human disturbance, noise, and other factors between different site types within a single park in relation to changes in bird community characteristics for linkage and analysis. For example, current and past climate, elevation, green space, normalized vegetation index (NDVI), and population density [ 74 ]. Broadly, the composition of bird communities varies with the gradient of urbanization [ 75 ]. In addition, species richness decreases with increasing urbanization and bird richness and density increases with increasing urbanization. How different land use plots such as protected forests, forest sanitation areas, and urban farmland affect the behavior of birds such as foraging, roosting, and breeding has been examined, and the characteristics of their changes throughout the year were studies [ 76 ]. The correlation of bird diversity with urban green space was noted in 112 urban green spaces in 51 cities of eight countries [ 77 ]. Therefore, bird diversity is often used as an important assessment indicator of the strengths and weaknesses of environmental ecology. In landscape construction, urban construction, and artificial forestation, bird diversity is often used as the main goal of landscape construction to be close to nature. Therefore, landscape construction and management methods with bird diversity as the main goal have been proposed and practiced in research.

Last but not least, bird habitat construction was born, and the ecological and ornamental values of birds are becoming better known to the public. Urban birds may play a key role in providing various aspects of the landscape and ecology. One of the greatest values and roles of urban birds is to serve as a link between the natural environment and the increasingly deprived urban population [ 78 ]. Birds in urban residential areas are often valued for their color and song, for providing mental and physical health, as indicators of seasonal change, education, and familiarity for residents [ 79 ]. Birds are also a source of inspiration for arts and recreational activities such as bird watching and wildlife gardening [ 80 ]. In addition, birdwatching tourism is also a low-carbon tourism mode, and most of the current studies focus on the study of site design of birdwatching locations and the planning of birdwatching routes. However, most of them only stay in the planning of one bird watching route, without diversified design, and lack of specifics regarding bird watching as to the type, location and time, one by one correspondence, and low practicability. There is a lack of targeted design for specific groups of people such as the elderly, children, and birdwatching enthusiasts [ 81 ]. At the same time, the design of bird watching routes is based on “bird song”, and there are few designs that advocate barrier-free bird watching [ 82 ].

4.1.2. Research History

The time zone map provides a clear picture of the development of the research field. In this paper, CiteSpace was used to obtain the time zone map ( Figure 5 ), using prune: pathfinder, and prune merge network, with the rest of the parameters as default parameters. Figure 5 shows the richness and diversity of the development process of this research area. At the same time, the study is constantly evolving in the development process, generating new keywords every year. Figure 6 shows the history of the research field through a total of four developmental stages.

Research keyword time zone view map.

Top 25 keywords with the strongest citation bursts.

Phase I (2002–2004): The key words generated in 2002 had a profound influence on future research and were practiced in the process of research development. The fundamental studies of bird communities, including bird habitat surveys, influencing factors related to changes in bird community characteristics, and ecological values of birds, all started in this period. The basic research on bird communities includes the study of basic diversity, abundance, habitat, pattern, species richness, and community. In addition, the ecological value of birds has been studied. In addition, the research shows that the diversity of birds decreases with development. Therefore, it was realized that scientific and effective management measures can have a positive effect on bird diversity.

Phase II (2005–2009): Studies related to the influencing factors of changes in bird community characteristics, the rhythm of bird activities, and the ecological value of birds were emphasized in this phase. The forest environment changed with climate change, urbanization development, and the rise of agroforestry industry. These land use changes occupy bird habitats. This leads to urban ecological decline, habitat homogenization, and a declining quality of vegetation structure. The bird community structure is unstable, the number of species decreases, and diversity decreases, and even the ecosystem services weaken. Society became aware of the ecological value of bird diversity conservation. In addition, the sites of concern at this stage begin to diversify to include water, the countryside, and national parks.

Phase III (2010–2015): In this phase, the research on the ecological value, function and role of birds was further promoted, focusing on the functional diversity and functional traits of birds, landscape, and environmental factors, while the investigation of bird communities themselves was continued and extended to insects, etc. The study of the factors influencing the change in bird community characteristics was further developed. In addition, the important role of landscape composition of urban biodiversity and landscape heterogeneity on urban bird diversity at this stage was realized, among which the effective transformation of land use is more critical. As a result, parks and green areas have been consciously built in cities to restore urban bird diversity. However, the conservation and enhancement of urban bird diversity takes a long time to operate. The survival and diversity of urban birds are still facing great challenges.

Phase IV (2016–2022): This phase focuses on the impact of macrostructure on bird diversity. With the urban expansion, the ecological quality of the city is weakened and the bird diversity is reduced. Thus, it is proposed to value urban planning and environmental heterogeneity and construct ecological networks scientifically. In particular, the focus is on urban landscape construction and ecological construction through strategies such as tree plantation, rational creation of green space, urban green space, urban park, and green infrastructure. In addition, factors influencing changes in bird community characteristics, such as increased elevation and tallgrass prairie were studied.

4.1.3. Research Frontiers

Keyword burst detection is used to detect the decline or rise of a keyword, and the greater the burst intensity the more frequently the keyword appears in a given period, indicating that many studies related to it have appeared in that period. These keywords are called burst keywords. These burst keywords can help scholars to identify new trends in that research area. In this paper, CiteSpace was used to obtain the top 25 keywords in this research area in terms of explosiveness ( Figure 6 ), and all parameters are the default parameters of the system. In this paper, the description of the highlighted words will be developed in chronological order.

Early outbreak vocabulary: breeding bird (12.93), Australia (9.2), success (7.66), England (7), Costa Rica (8.49), hotspot (8.31), reserve selection (7.76) and agroecosystem (7.35). These keywords indicate that, during this period, the main goal of this research area was to improve breeding bird diversity [ 83 ]. The basic research on bird communities and the correlation of factors influencing the changes of bird community characteristics were actively carried out. In the second half of the twentieth century, countries such as Australia, England, etc., underwent modernized industrial agricultural production. However, the environment was damaged, and biodiversity was lost. Therefore, different countries adopted different environmental policies to enhance biodiversity, and bird diversity and bird habitat became a hot topic of research. In particular, bird reserve selection and the breeding of urban birds are important frontiers in this research area.

Medium-term outbreak vocabulary: tropical rain forest (9.63), system (8.77), Los Tuxtla (7.09), coffee plantation (6.95), bird population (6.71), woodland (6.76), agri-environment scheme (6.53), biodiversity indicator (7.03), competition (6.59). The ecological value of birds, the factors influencing the changes in the characteristics of bird communities, and the activity patterns of birds continue to be studied at this stage. However, the scope of research was further expanded, not only to single habitats and vegetation structures, but also to systematic and agro-ecological systems. In addition, more macroscopic plans and strategies, such as agro-environmental plans and biodiversity indicators, are being developed. In addition, the large-scale deforestation of tropical forests worldwide has become a major driver of biodiversity loss and decline [ 84 ].

Recent outbreaks of vocabulary: city (7.27), matrix (7.13), functional diversity (14.73), ecosystem service (9.89). Recently, rapid urban expansion has led to the destruction of habitats for wildlife, including birds. Urban ecosystems are in urgent need of restoration and a series of studies on biodiversity, including bird diversity, are of great interest. Urban green spaces, including urban parks, are important habitats for birds, and therefore an increase in the functional diversity (size, heterogeneity, etc.) of urban green spaces has a positive impact on bird diversity. In addition, the research frontiers in this phase pay more attention to the construction of urban networks and the linking of urban green spaces. Incorporating different landscape matrices into urban planning can maintain the diversity of urban birds. Moreover, it is a more cost-effective solution [ 85 , 86 ].

In summary, the research in this research area is progressive and closely follows the social development situation. The research area has progressed from small to large, from surface to deep. From focusing on the basic research of bird communities, it has developed to research on the influencing factors (natural factors, human disturbances) related to the changes in bird community characteristics. We even push the research in different dimensions of time and space. Additionally, in this way, the theoretical and action plans in urban planning practice are discussed in reverse.

4.2. The Relationship between Landscape Construction and Bird Diversity

Urban biodiversity has declined rapidly as a result of rapid urban expansion. Urban landscape factors are important in determining both the survival and maintenance of bird species diversity [ 87 , 88 ]. It is important to investigate the relationship between landscape creation and urban bird diversity, so this collection focuses on the analysis and discussion of urban landscape creation and bird diversity. Bird diversity in urban areas depends mainly on landscape characteristics (fragment area, isolation, shape, habitat diversity, etc.), vegetation characteristics (plant species, plant phenology, tree size, plant density, plant structure, etc.), and human behavioral activities (noise level, number of people). In particular, landscape characteristics of land structure use and vegetation structure are the best predictors of taxonomic diversity, functional diversity and evolutionary uniqueness of bird communities in urban parks [ 89 ]. Moreover, human behavioral activities still have some influence on birds. It so happens that these influences are part of the urban landscape and can be addressed through scientifically based landscaping to address the declining diversity of birds. In addition, the factors influencing bird diversity vary greatly from region to region and from site to site, and local studies are needed to develop appropriate conservation plans [ 70 ]. Therefore, this paper focuses on the relationship between landscape architecture and bird diversity from three aspects of landscape architecture (landscape characteristics, vegetation characteristics, and human behavioral activities).

4.2.1. The Relationship between Landscape Features and Bird Diversity

Urban landscapes are rich in types, including urban parks, street green spaces, botanical gardens, etc. These urban landscapes include different types of landscapes such as urban parks, urban street green spaces, large wetlands, rain gardens, etc. Moreover, there may even be a special green space wetland in the city, and wetland creation is a common conservation measure to mitigate the loss of biodiversity caused by global wetland destruction. Studies have shown that several small (1 ha) wetlands with high flooded areas are better able to nurture wetland bird communities [ 58 ]. Spatial heterogeneity of the landscape is a key factor affecting biodiversity [ 90 ]. The construction of different landscape features such as landscape structure, habitat configuration, spatial arrangement, area, isolation, shape index, distance to the city center and habitat diversity can enhance landscape spatial heterogeneity, and thus influence bird richness. The most useful indicators of landscape heterogeneity for bird diversity are land cover richness, weighted edge density and edge density as a scale [ 91 ]. In addition, the distance of the site from the main road and water bodies, the hardness rate of the site, and the openness of the site will also have some influence on bird diversity [ 92 , 93 ]. For example, even in forests with low levels of recreation, highly sensitive species (large FID) tend to avoid areas near trails. The shift from natural habitats to human-dominated landscapes has had a significant impact on bird communities in the study area. Human-dominated habitats inhabited more bird species worthy of conservation [ 94 ]. Therefore, urban plans should include measures to provide suitable breeding habitats for threatened forest species to increase their populations, thereby increasing biodiversity and promoting the well-being of urban residents [ 60 ]. Urban planning in combination with green spaces can contribute to the diversity of birds in cities [ 3 ].

4.2.2. The Relationship between Vegetation Characteristics and Bird Diversity

Certainly, more green spaces and more plant species promote higher bird diversity. Plant landscape camping in green space, and features such as plant species, plant dominant family, plant canopy characteristics, plant density and cover, canopy width, diameter at breast height, height, number, density, etc., have an effect. First, the selection of plant species, including food source species, deciduous species, coniferous species, etc., is important, as are measures to attract urban birds through the selection and matching of greening tree species [ 95 ]. Some birds are particularly adapted to deciduous forests, and the physical advantages of deciduous forests are crucial to their distribution, such as the medium-spotted woodpecker, which specializes in deciduous forest food and breeding resources [ 96 , 97 ]. Overall bird diversity in coniferous stands is low [ 98 ]. Moreover, the effect of plant canopy structure variables on predicting bird diversity associated with coniferous forest habitats was the most important [ 99 ]. Unmanaged, large, and dense urban forests can serve as a safe habitat for large numbers of birds, regardless of the level of disturbance in the urban environment [ 100 ]. For the average percentage of canopy cover, ground (below 1 m), shrub level (1 to 5 m), low canopy (5 m to canopy level) and top level, each life form percentage is calculated independently so that total cover can be over 100% [ 101 ]. Vegetation cover under the forest canopy is key to increasing species diversity and richness [ 102 ]. The current stage uses LiDAR to measure and calculate the relationship between plant canopy features and bird communities [ 103 ]. The effect of canopy density on bird diversity is generally bell-shaped, while the effect on functional diversity and phylogenetic diversity is U-shaped [ 104 ]. Meanwhile, plant density and cover usually contribute to increase bird species richness and diversity. Tree and shrub density were the main drivers of bird community composition, and shrub density had a significant linear positive effect on both bird species richness and abundance [ 65 ]. This is followed by tree species diversity and landscape forest cover [ 105 ]. Tree cover in oases and olive groves positively affects bird diversity, and the positive benefits of tree cover density should be important when interpreting bird diversity in oases and olive groves [ 64 ]. In addition, the degree of variation in bird diversity varied more with mean breast size. Benjamin James Barth et al. found that the number of species and total bird abundance were positively correlated with the total number of mature trees retained within the vegetated street [ 106 ].

4.2.3. The Relationship between Human Behavioral Activities and Bird Diversity

The impact of various anthropogenic disturbances (e.g., agriculture, logging, urbanization, etc.), coupled with increasing population demand, is a constant threat to biodiversity on a global scale. The consequences of human pressure are not limited to species loss, but also affect other biodiversity aspects such as phylogenetic, genetic, and functional diversity. In the field of bird biology, reduced bird community activity is associated with reduced abundance and reduced species richness [ 107 ]. When exposed to human presence, birds undergo significant changes in behavior and physiology and respond immediately, with reactions such as increased vigilance, flight, and the release of stress hormones, which in turn may have effects on individual bird health and bird population dynamics. In addition to these direct effects, indirect effects can also affect wildlife primarily through the loss or alteration of bird habitats. The response of wildlife to human recreational activities depends not only on the characteristics of the animals involved (e.g., species, sex) and the type of human disturbance (e.g., noise level, number of people), but also on environmental conditions (e.g., habitat) and animal ecotype [ 108 ]. The temporal variation of disturbance events also shows different changes in bird communities, a phenomenon that also requires more attention from researchers [ 109 ]. For the study of human disturbance, the startle distance is one of the most frequently studied indicators, and the startle distance of different species of birds responding to human approach varies, with a high degree of similarity between birds of different species of the same family. For example, the startle distances of finches are about 16.2 m, those of chickadees are about 42.9 m, and those of falcons are up to 134.5 m [ 110 ]. Environmental noise is a limiting factor for urban birds, and noise level is a key influence on whether migratory birds call. Although the structure of vegetation features has a more significant impact on bird communities, influences such as human disturbance, noise level, and frequency of site management cannot be ignored [ 93 , 111 ].

Anthropogenic behavior: Studies have shown that trails and roads can significantly affect bird community composition and abundance, not only by altering habitats along trails, but also primarily through recreationist use. There were significant differences in bird startle distances when humans approached birds between park and cemetery-dwelling individuals, and differences in human activity villages between the two habitats made differences in startle distances [ 112 ].

Site noise: Anthropogenic noise is becoming more prevalent in the world and has been shown to affect many animal species, including birds. The effects of such noise were measured in a neotropical urban park to assess how noise affects bird diversity and species richness. Noise was negatively correlated with bird species richness, total abundance, and pellet-feeding species richness [ 113 ].

Frequency of site management: Bird responses varied by land use and season, and important and beneficial behaviors were observed in sample plots with high site management frequency. Birds showed different activities in different sample sites [ 114 ].

5. Conclusions

Rapid urban development poses a global challenge to mitigate the impacts of urbanization on biodiversity, and enhancing and conserving urban bird diversity is an important component of biodiversity enhancement. Landscape architecture is one of the indispensable technical tools. In this study, a bibliometric study was conducted by mining the literature studying landscape architecture and bird diversity to discover the background knowledge and research frontiers in this research area. Therefore, analysis using CiteSpace can help scholars to quickly understand a field of research. Firstly, this research area has a research history with an increasing number of publications in the literature year by year. Secondly, most countries and regions around the world are involved in this research area. Moreover, the authors are highly involved and there is a research network of authors associated with multiple people, showing the characteristics of local concentration. At the same time, the discipline maintains its traditional development during the development process. In addition, this study delves into four research hotspots (fundamental studies of bird communities, factors influencing changes in bird community characteristics, studies of bird activity rhythms, and ecological and ornamental values of birds), four developmental stages (2002–2004, 2005–2009, 2010–2015, 2016–2022), and several research frontiers (breeding birds, tropical rain forest, functional diversity, etc.). Meanwhile, the relationship that exists between landscape architecture and bird diversity is discussed in three aspects (landscape characteristics, vegetation characteristics, and human behavioral activities). This paper systematically summarizes the knowledge of the literature in this field to deepen the understanding of this research area and to quickly grasp the correlation between landscape architecture and bird diversity. The results of this study will help to reveal the important role of scientific landscape architecture in achieving the mitigation of urban bird diversity decline.

In the future, there is a need for landscape construction around the goal of bird diversity. Firstly, we will use multiple big data to monitor conservation and development dynamics, and effectively summarize the behavioral characteristics and spatio-temporal activity patterns of birds. We will draw a cloud map of bird distribution in each block combined with GIS to obtain dynamic big data and grasp the changes in bird diversity. Secondly, we will reasonably consider the activity characteristics of birds when constructing the landscape, and thoroughly study the landscape construction strategy and management principle of harmonious coexistence of human and birds, in addition paying attention to the landscape features, the construction mode and level of landscape vegetation, and the need to consider human behavior activities. Plots with good ecological substrates will be used as bird diversity enhancement areas, while the opposite will be focused on the space for human activities. We also will pay attention to the transition of levels, and reasonably reserve some plots for harmonious coexistence between humans and birds. At the same time, appropriate science education should be carried out to get into birds, ecology, and nature. Finally, multi-disciplinary and multi-departmental collaboration will establish a construction model that is both scientific and practical. It is often not enough to focus on a single block to enhance bird diversity, but rather necessary to link it to urban planning to form an overall block chain. This often requires multidisciplinary integration and innovative construction and planning models. This will help to mitigate the decline of bird diversity, preserve biodiversity, and enhance human well-being.

Funding Statement

(1) Forest Park Engineering Technology Research Center of the State Forestry Administration (PTJH15002); (2) Wuyishan National Park Research Institute Special Project (KJg20009A); (3) National Non-Profit Research Institutions of the Chinese Academy of Forestry (CAFYBB2020ZB008).

Author Contributions

Y.Z. and J.D. (Jianwen Dong) provided the research idea and purpose of this study; J.D. (Jiaying Dong) dominated the conception and framework of the preliminary paper; Y.Z., E.Y. and J.D. (Jianwen Dong) designed the research; Y.Z. and F.L. collected and analyzed the data; Y.Z. wrote the paper; J.D. (Jiaying Dong), N.L. and X.Y. supervised, corrected, and revised the paper; J.D. (Jiaying Dong), X.Y. and Y.Z. corrected the article language and made some suggestions. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Data availability statement, conflicts of interest.

The authors declare no conflict of interest.

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