Distribution of Bird Communities and Habitat Corridor Composition Shaped by Environmental Factors in Urbanized Landscapes: A Case Study in Beijing, China

Abstract

Urban biodiversity is crucial for ecological security, balance, and important for fostering awareness on human-nature interconnectedness among the public. The diversity of birds, as an urban ecosystem indicator, reflects ecosystem services and is impacted by urban development. To explore the impacts of urbanization on bird diversity, stratified to songbirds, terrestrial birds, climbers, swimming birds, wading birds, and raptors, we specifically investigated the existing and potential distributions of selected bird species, analyzed different contributions of environmental factors, and compared these with urban biodiversity conservation policies. We used bird records from the China Birdwatching Record Center (over 1400 species of birds for querying) and remotely-sensed landcover data, based on the MaxEnt model, to analyze bird spatial distribution characteristics and potential habitat corridors throughout Beijing. The results showed that: (1) Songbirds and terrestrial birds were predominantly concentrated in water areas in urban areas. Wading birds, climbers, swimming birds, and raptors were gathered in forest-covered areas, near wetlands and farmland in suburban areas. Projections indicated that the raptor species Common Kestrel (Falco tinnunculus) showed a notable shift toward urban cores. (2) Among climbers, Gray-headed Pygmy Woodpecker (Dendrocopos canicapillus) occupied the highest proportion of high-quality habitats (10.34%), contrasting with the representative songbird species Blackbird (Turdus merula) at 1.38%, which demonstrated adaptability to urban environments. Critical habitats were concentrated in shrub forests, supporting habitat connectivity. Proximity to water bodies was critical for raptors, wading, swimming, and climbers, whereas terrestrial birds and songbirds were more affected by artificial lighting. (3) The “urban and suburban park rings” policy has effectively enhanced habitat quality and connectivity, promoting urban biodiversity resilience. This study improves our understanding of how different bird communities adapt to urbanization in terms of habitats and movement corridors, and provides useful information for formulating urban bird biodiversity conservation strategies.

1. Introduction

Urbanization has caused habitat loss, fragmentation, and declining habitat quality, significantly impacting biodiversity worldwide. Birds, which are essential indicators of urban ecosystem health, have garnered global attention for their responses to urbanization [1,2]. Investigating the factors influencing avian diversity in urban settings is crucial for biodiversity conservation.

As a widely distributed, easily observed, and environmentally sensitive species, birds are frequently studied in biodiversity research [3]. Urban birds depend heavily on green spaces such as parks, green belts, and street trees, which offer critical resources for feeding, roosting, and breeding. However, unlike natural habitats, urban environments are profoundly shaped by human activity and land-use policies, leading to complex and multifaceted drivers of urban biodiversity patterns that necessitate further research [4].

Global declines in bird diversity are alarming. Rosenberg et al. [5] reported a 57% decline in North American bird species (303 out of 529), representing nearly three billion fewer individuals since 1970. Similarly, breeding bird abundance in the EU dropped by 17%–19% (560–620 million individuals) between 1980 and 2017 [6]. Long-distance migratory species are particularly vulnerable [7].

While North American and European studies are well-established, urban biodiversity research in Southeast Asia remains underdeveloped, and urban park management often prioritizes aesthetics over biodiversity conservation [8]. China has a rich biodiversity and a rapidly growing urban population. Research indicates that citizen science data shows that the top 20 cities in China for bird diversity account for 48% of the country’s bird diversity and 42% of endangered species [9], indicating the great potential for urban biodiversity conservation. Among them, strengthening the study of urban birds in China as an indicator of biodiversity is particularly important. For instance, studies in Nanjing parks revealed that habitat diversity and proximity to city centers positively influence bird species richness [10]. This underscores the need for more systematic approaches to enhance urban biodiversity conservation in rapidly urbanizing regions. In March 2022, following COP15 in October 2021, Beijing introduced its vision of becoming a “capital of biodiversity”. Biodiversity protection is now integrated across all facets of the city’s urban planning. The recently approved “Beijing Urban Overall Planning (2016–2035)” (hereafter “Overall Planning”) emphasizes “protecting and restoring natural ecosystems and maintaining biodiversity”. A key goal is to develop urban habitat corridors to address Beijing’s uneven distribution of green spaces, facilitating wildlife movement and connecting fragmented habitats. This approach aims to increase passage routes for animal species to move, which ultimately allows gene flow.

China tends to be relatively static and pays less attention to the ecological processes of the organisms themselves, despite strong policy support for advancing urban biodiversity conservation efforts. Furthermore, there is a dearth of long-term, medium-scale research and practice [11,12]. The majority of these studies have gathered bird data using time-limited, structured survey techniques such as point or line counts [13,14]. As a result, it is challenging to gain dynamic data to support the implementation of pertinent planning and policies. Thanks to technological advancements, the development and use of remote sensing technology and data-sharing platforms in biodiversity over the past decade [15,16] have enabled the public to collect and manage bird data through mobile platforms such as smartphones [17]. Additionally, international research on bird distribution has reached certain results through citizen science [15,18].

This study collected bird records from one of China’s most comprehensive and complete public bird databases, the China Birdwatching Record Center. The selection of representative bird species was based on the background of international hot spots and the current state of domestic research, combined with the existing implementation results of the “Overall Plan”, and taking into consideration the potential of citizen science in biodiversity research. The article aimed to (1) ascertain and predict the density distribution of six representative species of birds; (2) explore the critical habitats and potential habitat corridors of selected bird species, and investigate the proportion of seven environmental factors’ contributions; (3) compare the critical habitats and habitat corridors with planning. To achieve the aims, the objectives of the study included:

(1)

Using ArcGIS 10.8.2 for kernel density analysis, the spatial density distribution is evaluated to assess bird distribution, and MaxEnt 3.4.1 is used to predict the spatial distribution of representative species of six bird communities based on environmental factors.

(2)

Using the ROC curve to evaluate the availability of bird habitats based on the proportion of critical habitats, and analyzing the contribution rate of environmental factors to the prediction results using the Jackknife method in MaxEnt 3.4.1.

(3)

Employing a least-cost distance model to construct potential ecological corridors, tailored to the movement and habitat needs of different bird species, and overlay the potential habitat corridors for birds and important habitat spaces with the policy-planned ecological corridors for comparative analysis.

2. Materials and Methods

2.1. Study Area

The research area covers Beijing’s metropolitan region, including plains and hilly terrain with diverse land types such as grasslands, shrublands, arable land, wetlands, forests, and developed areas in both urban and rural zones (Figure 1). Over the past 20 years, urbanization has increased substantially [19], with major land-use changes including the conversion of suburban farmland to construction land, wetlands to farmland and construction land, and a rapid expansion of built areas. This has fragmented Beijing’s landscape, although forest area has notably grown, with forest patches now frequently interspersed among urban developments. According to the “2020 Statistical Bulletin on Beijing’s National Economic and Social Development”, the city’s forest coverage reached 44.4%, covering 62.5% of residents and offering significant potential for urban biodiversity habitats and corridors.

2.2. Assessment Framework

The study area’s bird distribution was predicted using the MaxEnt 3.4.1, which was based on the maximum entropy model in ecological niche modelling. Studies on corridors point out that every theory and technique in locating corridors has its own pros and cons [20,21]. Thus, the relevance of combining multiple tools made up the main emphasis of this study [22]. The resistance model, which contended that species must overcome various degrees of resistance in order to move through various landscape features, was the primary model. The idea of a “minimum resistance corridor” connecting ecosystems arose naturally from the idea that the path with the least amount of accumulated resistance is the optimal corridor or best pathway. The key technologies were as follows (Figure 2).

2.3. Data Sources

The USGS (United States Geological Survey) open data website provided the remote sensing image data for Beijing. The data was processed to create raster data for land use and landcover (LULC) types and has a 30 m picture resolution. We selected construction land (including developed open Space, developed low intensity, developed medium intensity, and developed high intensity), water area (including open water and wetlands), forest land (including deciduous forest, evergreen forest, and mixed forest), shrubland, grassland, cultivated land (Files S1 in Supplementary Materials).

The OpenStreetMap public mapping website provided the vector data for the Beijing water systems, railways, and water bodies. The data on DEM and normalized vegetation index (NDVI) were sourced from the Geospatial Data Cloud website. The official Luojia-1 website was the source of the data on nighttime light. We standardized all raster data to a resolution of 30 m.

The coordinates of the bird observation points on the China Bird Watching Record Centre platform were the source of the bird point data. The information recorded on the website included, among other things, the number of observations, the species of birds observed, the latitude and longitude of the observation point, and the observation time for each record point.

The data was input into the database after being examined by the platform’s computer system and manually verified for accuracy (

Table 1. Details of the dataset of geographical sources and the dataset of bird records in Beijing.

Data Type	Data	Data Format/Accuracy	Time	Data Source
Geographical data	Administrative boundary data	Shp	2019	National Catalogue Service for Geographic Information
	LULC data	Raster/30 m	2020	United States Geological Survey (USGS) (https://glovis.usgs.gov/app, accessed on 1 December 2021)
	Railway network data	Shp	2019	OpenStreetMap (https://www.openstreetmap.org/, accessed on 1 January 2020)
	Water network data	Shp	2019	OpenStreetMap (https://www.openstreetmap.org/, accessed on 1 January 2020)
	Normalized difference vegetation index (NDVI) data	Raster/500 m	2019	GSCloud (http://www.gscloud.cn/, accessed on 1 January 2020)
	DEM	Raster/30 m	2019	GSCloud (http://www.gscloud.cn/, accessed on 1 January 2020)
	Night light data	Raster/30 m	2019	Luojia No.1 (http://59.175.109.173:8888/index.html, accessed on 1 January 2020)
Public data	Bird species occurrence point data	POI	2019	BirdReport.cn (http://www.birdreport.cn/, accessed on 22 December 2020)

).

2.4. Selection of Research Subjects

Between 2015 and 2020, there seems to have been a significant increase in the number of birds (Figure 3). The year 2019 had the biggest shift of all, with a sharp rise in bird habitats. From a spatial distribution perspective, the density of birds in the urban center of Beijing significantly increased from 2018 to 2019, indicating that some bird species have gradually adapted to the trend of urbanization (Figure 4). Concurrently, the first stage of the “Beijing Urban Master Plan”, which was authorized and put into effect in 2017, was expected to be finished by 2020. The best available public bird data from 2019 was selected as the source data for processing in light of the aforementioned considerations.

The common birds of Beijing could be categorized into six main groups according to their ecological habits: songbirds, terrestrial birds, climbers, swimming birds, wading birds, and raptors. Additionally, if more than 100 submissions were available, a preliminary screening based on the type of bird residency would be conducted, and the birds would be classified as either resident or migratory in Beijing. A flexible selection process was used because the data available for some bird species was restricted and did not meet the criteria of over 100 entries. We skipped the data amount requirement and went on to the next flow channel if the quantity criteria were not met and there were no appropriate representative birds. The preliminary screening results were in accordance with the “Beijing Terrestrial Wild Animal List (2024)” [23] and the “List of Terrestrial Wild Animals that were Beneficial or Have Important Economic and Scientific Research Value and are Nationally Protected” [24]. We chose representative species of birds from each category to study, taking into account factors such as protection status, scientific or commercial significance, and body size, that represented variations in the habits of different bird species (

Table 2. Selection of representative species of birds relying on public observation databases.

Number	English Name	LatinName	Birds’ Living Habits	Residence Type 1	Frequency of Occurrence in 2019	Basis of Selecting the Species
1	Jungle Crow	Corvus macrorhynchos	Songbirds	R	307	(1) Corvus macrorhynchos and Turdus merula are contrasting resident songbirds in Beijing with ample data, making them ideal representative species.
2	Blackbird	Turdus merula		R	288
3	Spotted Dove	Streptopelia chinensis	Terrestrial birds	R	420	(1) It has sufficient data available. (2) It has important economic and scientific research value
4	Gray-headed Pygmy Woodpecker	Dendrocopos canicapillus	Climbers	R	208	(1) Both have important economic and scientific research value. (2) Dendrocopos canicapillus belongs to the most important protective bird species in Beijing.
5	Common Kingfisher	Alcedo atthis		S/R	110
6	Mandarin Duck	Aix galericulata	Swimming birds	P/R	154	(1) Aix galericulata belongs to the second most important protective bird species in China. (2) Gallinula chloropus has important economic and scientific research value.
7	Gray Moorhen	Gallinula chloropus		S/P	94
8	Great egret	Ardea alba	Wading birds	P	80	(1) Ardea alba and Ardea cinerea are of similar size, have a protected status, and have ample data in Beijing. (2) Both have important economic and scientific research value and belong to the important protective bird species in Beijing.
9	Gray Heron	Ardea cinerea		S/P	271
10	Common Kestrel	Falco tinnunculus	Raptors	R/S	119	(1) It belongs to the second most important protective bird species in Beijing. (2) It possesses the most data.

¹ R (resident); S (summer visitor); P (passage migrant).

) [25,26].

2.5. Data Analysis Methods

2.5.1. Evaluation Methods and Distribution Characteristics of Birds

We examined the distribution characteristics of birds based on the distribution patterns of six representative bird communities of birds in 2019. In this study, we processed the latitude and longitude information of the locations using the ArcGIS kernel density analysis tool. The point count method is a simple and easy-to-use bird counting technique suitable for various habitat types. This study utilized public observations and recordings of the number and types of birds passing through as bird sampling points in Beijing to derive the relative density of birds.

2.5.2. Prediction of Potential Bird Distribution

The maximal entropy method (MaxEnt) is widely employed in the niche model [27]. It can reliably estimate species distribution with just data on species existence and environmental factors. This is important in circumstances where field observations are difficult or when the research region is too big, allowing for the prediction of species distribution and the mapping of habitat suitability using various current data (such as museum data, citizen science data, etc.). As one of the better niche modelling programs available, it can also use the Jackknife method that is included with the model to determine the contribution rates of different environmental elements. The formula is as follows:

$${\mathrm{E}}_{\mathrm{j}}=\sum _{\mathrm{x}ϵ\mathrm{X}}\mathrm{P}\left(\mathrm{x}\right){\mathrm{F}}_{\mathrm{j}}\left(\mathrm{x}\right),\mathrm{j}=1,2,\cdots \mathrm{n}$$

(1)

where ${\mathrm{E}}_{\mathrm{j}}$ is the expected value of the j-th feature estimated based on species occurrence records, X is the domain, the possible combinations of environmental variables, $\mathrm{P}\left(\mathrm{x}\right)$ represents the probability distribution of species occurrence at a certain location, ${\mathrm{F}}_{\mathrm{j}}\left(\mathrm{x}\right)$ represents the feature function related to environmental factors, and n is the number of constraints, the number of environmental variables.

Numerous studies show that physical geography and vegetation can have both direct and indirect effects on island bird diversity [10,28], and urban habitat heterogeneity may increase bird abundance [29]. Liu et al. [30] found that migratory birds were more sensitive to the negative impact of the surroundings of UGI, such as impervious surfaces and nighttime light. Considering the analysis of climate data is relatively complex, and since 2019 coincided with the pandemic, the acquisition of data was limited due to human interference. Therefore, this study focuses on the main environmental factors in the city, including DEM, distance to water bodies, distance to rivers, distance to railways, NDVI, LULC, and night lights index. The data was processed in ArcGIS 10.2, uniformly resampled to a resolution of 30 m, and then loaded into MaxEnt 3.4.1 together with representative bird species point data chosen from the six bird communities. This produced predicted bird distributions and ROC curves.

2.5.3. Contributions of Environmental Factors

We obtained the importance of various environmental factors on representative bird species based on the Jackknife test model. A factor’s contribution to the overall result was measured in the Jackknife test model, which quantified the contribution rate of the major environmental elements in the statistical habitat to the projected distribution results. A larger contribution rate suggested that the factor had a greater bearing on the distribution prediction of that particular species of bird. The NDVI vegetation index, LULC types, elevation, distance to rivers, distance to water bodies, distance to railroads, and night lights index were among the chosen environmental parameters. Grassland, shrubland, arable land, wetlands, forest land, and urban-rural building land are among the several LULC types.

2.5.4. Construction of Potential Habitat Corridors for Various Bird Species

We constructed potential habitat corridors for various bird species through the least-cost distance model. The MaxEnt 3.4.1 prediction distribution results and ROC curve were used to determine the best threshold for converting the anticipated probability values into particular appropriateness classes. ArcGIS 10.2 reclassified the raster data based on the threshold that has been chosen, classifying the quality of the habitat for birds into three categories: “low habitat quality”, “moderate habitat quality”, and “high habitat quality”. Considering that overly fragmented habitat patches are not conducive to corridor design, habitat patches larger than 500 ha with reasonable distribution locations were extracted using spatial analysis tools as critical habitats for bird species. Using the Linkage Mapper 2.0.0 based on the minimum cost–distance model. The ultimate goal of Linkage Mapper in optimizing paths is to minimize the following objective function. The formula is as follows:

$$\mathrm{M}\mathrm{i}\mathrm{n}\mathrm{i}\mathrm{m}\mathrm{i}\mathrm{z}\mathrm{e} {\mathrm{C}}_{\mathrm{t}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l}}=\sum _{\mathrm{p}ϵ\mathrm{P}}\sum _{\mathrm{i}=1}^{\mathrm{n}}\mathrm{C}\mathrm{o}\mathrm{s}\mathrm{t}\left(\mathrm{i}\right)$$

(2)

where ${\mathrm{C}}_{\mathrm{t}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l}}$ is the total path cost from one core area to another core area, $\mathrm{P}$ is the set of all possible paths, and the path with the smallest ${\mathrm{C}}_{\mathrm{t}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l}}$ is ultimately chosen. $\mathrm{i}$ represents each pixel in the path, and $\mathrm{n}$ is the total number of pixels in that path.

Selecting the Linkage Pathways Tool, we considered both bird conservation and urban planning. We chose a corridor width parameter of 200 m that can support ecological functions such as promoting bird diversity, reducing edge effects, encompassing diverse habitats, and protecting bird populations [31,32,33].

3. Results

3.1. Spatiotemporal Variation in Density Distribution of Birds in Beijing

3.1.1. Spatiotemporal Variation in Density Distribution of Bird Communities

In terms of distribution, the majority of birds represented by songbirds and terrestrial birds were significantly concentrated in water areas in the Haidian District. Secondly, wading birds, climbers, swimming birds, and raptors were also gathered in forest-covered areas and near wetlands and farmland in Changping District. In terms of the distribution range, songbirds and climbers had the broadest distribution range and a high density, while raptors had a rather dispersed distribution pattern and the smallest observed range (Figure 5).

3.1.2. Predicted Spatiotemporal Variation in Density Distribution of Representative Bird Species

Overall, as illustrated in Figure 6, the predicted distribution range of songbirds was projected to expand for Corvus macrorhynchos, particularly toward areas with water bodies, including the Yanqing District and Miyun District. In contrast, Turdus merula remained predominantly concentrated in Beijing’s central metropolitan area.

Within the predicted range of terrestrial birds, species such as Streptopelia chinensis were observed to show an increasing presence along a northeast–southwest axis, encompassing areas near the reservoir in the Miyun District and extending southwest toward the Fangshan District and Mentougou District.

For climbers, Dendrocopos canicapillus and Alcedo atthis were expected to retain their primary distribution in Beijing’s central metropolitan area, while also expanding their activity range in the Miyun District, Yanqing District, and Changping District. However, within the urban boundary of the Fangshan District, the presence of climbers was projected to decrease.

In terms of swimming birds, Aix galericulata was predicted to expand its distribution in the Yanqing District and Miyun District, while Gallinula chloropus extended its range southeastward, encompassing the Tongzhou District and Daxing District.

Wading birds, such as Ardea alba, demonstrated strengthened aggregation patterns in the Yanqing District, with an overall increase in distribution from the northeastern part of the Changping District to the Miyun District. Similarly, Ardea cinerea showed a growing presence in the Dongcheng District and Xicheng District.

Lastly, in the predicted range of raptors, the distribution of Falco tinnunculus in the Changping District appeared to decrease, with its distribution center shifting towards the core urban areas, primarily represented by the Dongcheng District and Xicheng District.

3.2. Analysis of the Critical Habitats and Habitat Corridors

We used ArcGIS and Linkage Mapper corridor simulation software to derive critical habitats and potential habitat corridors (Figure 7). Six representative bird species’ critical habitats were distributed in a way that demonstrated the following common traits: they were concentrated most heavily in urban built-up areas and radiated outward from this central location to nearby reservoirs and rivers. Ardea alba had a scattered critical habitat distribution and a strong reliance on water, while Falco tinnunculus had the widest distribution area and the strongest connectivity of its critical habitats. It can be found in highly urbanized areas as well as in river, lake, and forest environments. Turdus merula had the smallest critical habitat distribution range among them. It was closely associated with urban construction areas. An examination of the possible places for habitat corridors showed that there was little contact with urban highways and some overlap with Beijing’s water systems. The majority of the bird-representative prospectives pass through picturesque places found in Beijing’s shallow mountainous regions, as well as ecological wetlands.

3.2.1. The Potential Corridor Area of Different Bird Species

The ecological movement corridors’ buffer zone analysis (Figure 8) showed that the Turdus merula’s potential corridor area was the lowest and was concentrated in urban growth areas, while Aix galericulata’s potential corridor area could span up to 300 km².

3.2.2. The Availability of Critical Habitats

In the ratio of the area of high-quality habitats to the area of moderate-quality habitats for different bird species (Figure 9), only Dendrocopos canicapillus (10.34%) exceeded 10%, while the two types of habitat areas for the other five representative bird species were both less than 10%. Among them, the unsuitable habitat area for Turdus merula was the largest, reaching 96.82%.

Regarding LULC types (Figure 10), all six bird species exhibited a marked preference for shrub forests, with Falco tinnunculus showing the highest reliance (95.81%) on this habitat type. Dendrocopos canicapillus, possessing the largest proportion of suitable habitat, ranked second in its dependence on shrub forests while exhibiting minimal demand for built-up areas. Conversely, the movement corridors of Turdus merula, which had the smallest proportion of suitable habitat, included the highest proportion of built-up land (29.41%), reflecting some adaptability to urban environments.

3.2.3. The Contribution of Environmental Factors to the Prediction Results of Potential Bird Habitat Corridors

To obtain the main factors that provide a habitat for birds and to assess the importance of these factors, we analyzed the contribution of environmental factors based on the predicted distribution of bird communities. The analysis identified that (Figure 11) among the seven selected factors, the most significant environmental factor for raptors, wading birds, swimming birds, and climbers was the distance to water bodies. Among these groups, the wading bird species Ardea cinerea was the most influenced by the distance to water bodies, with a contribution rate of 69.05%, followed by the swimming bird Alcedo atthis, at 61.75%. Wading birds, being relatively large, were well-suited for habitats such as marshes, water edges, shallow wetlands, and coastal regions.

In contrast, terrestrial birds and songbirds were most strongly influenced by nighttime lighting. The representative songbird species Turdus merula demonstrated the greatest adaptability to nighttime illumination, with a contribution rate of 65.75%. This reflects the general adaptability of smaller songbirds, which can thrive in diverse ecological settings and human-modified environments, where light intensity at night is a critical factor in predicting their distribution.

Although the overall contribution of altitude was minimal, it was notably higher for Falco tinnunculus and Corvus macrorhynchos, which are primarily distributed in the forested mountainous regions of northwest Beijing. For these species, altitude played a relatively significant role in shaping their activity corridors.

Lastly, the analysis revealed that LULC had minimal impact on the preferences and requirements of the six bird communities within their activity corridors, indicating broad adaptability across varying landscapes.

3.3. Comparison of Critical Habitats and Habitat Corridors in the Light of Planning

Based on a comparative analysis of the study results and the ecological spatial network outlined in the “Beijing Urban Overall Plan (2016–2035)” (Overall Planning), the critical habitats of the six representative bird species partially overlapped with the urban green space structure plan, including the urban park ring and the wilderness park ring in areas such as the Fangshan District, which hosts terrestrial bird populations. The potential habitat corridors predominantly traversed ecological control zones designated in the “two belts and three zones” framework of the city and restricted construction zones closely connected to the centralized urban development areas, such as those in the Changping District and Yanqing District (Figure 12).

However, policy efforts still needed to be strengthened for regions predicted to experience an increase in bird populations. For instance, enhanced protection of water bodies in the Yanqing and Miyun Districts was crucial for attracting climbing bird species and other bird communities. Similarly, greater attention was required for key areas in the Tongzhou, Daxing, and Changping Districts, which were projected to attract flocks of swimming birds, songbirds, and other species.

For regions where bird populations were expected to decline, conservation measures needed to focus on protecting migratory ranges. For example, raptors in the Changping District were anticipated to become less common and shift their distribution toward core urban areas, such as the Dongcheng and Xicheng Districts. Therefore, policies should prioritize increasing suitable habitats for raptors within these central urban zones.

4. Discussion

4.1. Bird Distribution and Urban Adaptability

The analysis of bird distributions in 2019 indicates that songbirds and swimming birds exhibit the highest levels of adaptability to urban environments. These species are predominantly concentrated in urban core areas. Songbirds rely on vocalizations for reproduction and communication. Research by Henrik [34] suggests that urban noise can alter the structure of bird calls. Similarly, Nemeth and Brumm [35] demonstrated that birds in urban settings call louder than their forest-dwelling counterparts or shift to higher frequencies to counteract low-frequency noise from traffic. These adaptations enable songbirds to maintain effective communication in noisy urban areas.

Predicted bird distributions suggest a shift toward greater dispersion. Human activities, such as reduced mobility during the COVID-19 pandemic, have influenced bird migration patterns and habitat usage, resulting in broader spatial distribution [36,37]. Songbirds, terrestrial birds, climbers, and wading birds are expected to extend their ranges toward water bodies and western forested regions. Among swimming species, Aix galericulata is projected to expand its presence in the Yanqing and Miyun districts. These areas offer the clear waters and dense vegetation preferred by this species. In contrast, Gallinula chloropus is expected to shift toward urbanized areas in the Tongzhou and Daxing districts. This bird’s ability to tolerate lower water quality enables it to thrive in artificial habitats, such as lakes in urban parks. Swimming birds, on the other hand, depend on both forested habitats and urban environments. Certain reservoirs can act as critical refuges for swimming species, particularly during dry seasons [38,39]. This dual reliance highlights the complex relationship between urbanization and the ecological needs of swimming birds.

Certain wading birds, such as Ardea cinerea, and raptors, including Falco tinnunculus, are likely to migrate toward urban centers. These areas provide essential resources, such as prey and nesting opportunities, making them valuable for breeding and survival [40,41]. However, the availability of prey can limit the reproductive success of some bird species, particularly those with flexible diets, where identifying primary prey types poses challenges [42]. Urban environments also introduce ecological pressures, such as competition from invasive species, which may threaten native bird populations. Simultaneously, urban features like constructed lakes and reservoirs can offer alternative habitats for species otherwise reliant on natural environments. The observed and predicted trends highlight the need for targeted conservation strategies. Enhancing water quality in urban water bodies and preserving green spaces can support both swimming and terrestrial birds. Addressing urban noise pollution is particularly important for songbirds, as it directly impacts their communication and reproductive behaviors.

Efforts to integrate biodiversity considerations into urban planning are crucial. Establishing habitat corridors that connect urban green spaces with surrounding forests and wetlands can improve habitat connectivity and resilience. These measures will help balance urban development with the preservation of avian biodiversity. For example, the contrasting habitat preferences of Aix galericulata and Gallinula chloropus reflect differing responses to urbanization. While Aix galericulata favors undisturbed, vegetation-rich habitats, Gallinula chloropus demonstrates a higher tolerance for human-altered landscapes.

4.2. The Influence of Environmental Factors Influencing Bird Habitats and Potential Habitat Corridors

Extensive research has established that natural geographic factors and vegetation characteristics exert both direct and indirect influences on bird diversity. These effects are closely linked to the scale of the landscape and the complexity of vegetation structure. At broader spatial scales, a positive correlation exists between bird diversity and plant diversity [24], aligning with their ecological needs and behaviors [43].

Bird populations are predominantly distributed near green spaces and water bodies. Their distribution patterns are significantly influenced by urban vegetation patches and swimming environments [44,45]. For species such as raptors, wading birds, swimming birds, and climbers, proximity to water bodies emerges as a key environmental determinant. Mayer et al. [46] observed that birds initiate flights at longer distances over lakes than over rivers, with the starting distance increasing in tandem with population size. Wading birds, characterized by their relatively large body size, thrive in habitats like marshes, shorelines, shallow wetlands, and coastal regions. Simultaneously, urban artificial wetlands are increasingly recognized as critical habitats for waterbirds, addressing the need for enhanced urban biodiversity [47].

In contrast, terrestrial birds and songbirds are notably impacted by artificial lighting during nighttime in their habitat corridors. This highlights the resilience and adaptability of small songbirds, which can flourish in varied ecological settings, including those altered by human activity. Studies reveal that artificial light at night (ALAN) significantly influences barn swallow nesting and reproductive behaviors. For example, research conducted in Taipei demonstrated that ALAN positively affects the fledging success rate of barn swallows. Furthermore, the combined impact of light and noise on avian activity shows complex dynamics. While nighttime activity often increases under these combined stressors, daytime activity can decline. These interactions vary depending on the original habitat of the birds, underscoring the need to consider habitat-specific responses [48].

This study, however, differs from prior research by finding no substantial influence of land-use types on the preferences or requirements of six bird groups within their activity corridors in Beijing. This discrepancy may be attributed to the study’s spatial scale, which focuses solely on Beijing and does not encompass the complete migration routes of these birds. The interplay of spatial scale and landscape complexity shapes birds’ adaptability to urban environments in distinct ways. Sacco et al. demonstrated a negative correlation between urbanization intensity and bird richness, abundance, and functional diversity. Highly urbanized regions tend to attract birds that favor aerial foraging, omnivorous diets, and cavity nesting. Conversely, areas with lower urbanization levels, characterized by abundant trees and open habitats, are associated with vegetation-nesting species and carnivorous birds [49]. Xie et al. further emphasized that species richness and population numbers of forest and swimming birds peak under moderate urbanization levels [38]. Despite these insights, there remains a scarcity of research on the threshold effects of urbanization and environmental factors on bird distribution. Future investigations should prioritize understanding how physical factors (e.g., topography) and anthropogenic influences (e.g., artificial wetlands and nighttime lighting) interact to shape avian habitats effectively.

4.3. Effectiveness of Current Conservation Policies in Urbanized Areas

The predicted distribution results of birds are somewhat compatible with the ecological control zones and green space structure in the “Overall Planning” The existing policy of “building urban park rings and suburban park rings” is effective in maintaining and improving bird habitats. Although urban parks are artificial habitats, they are significant for maintaining bird diversity. The research results emphasize the importance of certain native vegetation structures in urban parks (such as ancient trees and shrub transition zones) for maintaining urban bird biodiversity [50]. However, for areas not yet covered by existing policies, such as the Tongzhou, Daxing, and Changping Districts, areas predicted to see a decrease in bird populations (such as raptors migrating from Changping to the Dongcheng and Xicheng Districts) or key corridors not covered in water body areas (such as the Miyun District), habitat protection for bird preferences should be strengthened.

To sustain urban bird diversity, expanding habitat patches and developing corridor networks are essential to enhance urban habitat connectivity [51]. In Beijing, where landscape fragmentation is significant, spatial planning must strengthen green area connectivity across planning levels—general, detailed, and special—to support urban bird diversity and corridor development [52,53]. First, at the macro level, it is recommended to establish large corridors within green spaces, utilizing waterways and major roads for connectivity. Relevant authorities should enhance the protection of forests near farmland and wetlands to improve green space connectivity. This is beneficial for increasing the proportion of high-quality habitats for bird communities to over 10%. Detailed planning should ensure linear greenbelt landscapes that boost environmental quality and ecological services, with corridor widths tailored to species needs: 30–60 m for small fauna and at least 100 m for bird protection [54]. At the specialized planning level, urban biodiversity conservation programs prioritize green spaces as primary habitat carriers and grey spaces as supplementary, emphasizing multi-species habitat compatibility [55]. For example, integrating the main habitat corridors of songbirds and climbers with urban road construction, while increasing nighttime lighting, can benefit avian biodiversity. On the other hand, it is necessary to consider the threats posed by external bird communities to local bird species and the potential threats and panic caused to the public by wild animals entering urban areas. Research indicates that raptors tend to enter core areas, so while emphasizing habitat protection, corresponding monitoring and rescue measures need to be established. Future conservation efforts should increase public participation.

5. Conclusions

The study results emphasize that some bird species have shown adaptability to urban environments. The predicted bird distribution aligns with the ecological control zones and green space structure outlined in “Overall Planning”. The policy promoting urban and suburban park rings effectively supports bird habitats. However, areas like the Tongzhou, Daxing, and Changping Districts remain underrepresented, where bird populations, such as raptors migrating from Changping to Dongcheng and Xicheng, may decline. Additionally, critical bird habitat corridors, such as those in the Miyun district, require enhanced protection. To improve habitat connectivity, large green corridors should integrate waterways and roads, with species-specific corridor adaptations and increased public participation for effective conservation. This highlights the importance of multi-level green space connectivity and multi-type habitat restoration for key species. Integrating public observation data provides an effective method for mapping urban bird habitats and corridors, offering key insights for urban biodiversity conservation in spatial planning.