Spatio-Temporal Variation of Habitat Quality for Bird Species in China Caused by Land Use Change during 1995–2015

Spatio-Temporal Variation of Habitat Quality for Bird Species in China Caused by Land Use Change during 1995–2015

The assessment of changes in land use (LUC) has emerged as a crucial criterion for evaluating the influence of human activities on our natural environment. The alteration and degradation of habitats resulting from LUC pose significant threats to biodiversity worldwide. However, comprehensive research on the long-term, large-scale, and detailed effects of LUC on avian habitats remains limited, primarily due to a scarcity of adequate data.

This study, conducted in China, aimed to address this gap by employing a randomized sampling approach to analyze 9 km grid units between 1995 and 2015. Logistic regression was utilized to determine the probability of each grid unit containing suitable habitat, referred to as PGSH (Probability of Grid Unit Containing Suitable Habitat), for a total of 981 bird species. The study also sought to examine the spatial-temporal characteristics of PGSH.

The findings revealed several important insights. Firstly, the habitat quality for 84 bird species deteriorated, while for 582 bird species, there was an improvement in habitat quality. Secondly, an inverted U-shaped relationship was observed between the intensity of LUC and the PGSH. Notably, the threshold for LUC intensity was approximately 67.21%. Lastly, through a counterfactual scenario analysis, it was determined that the implementation of the Three North Shelterbelt project had increased the PGSH for all bird species from 20.76% before restoration to 21.38% after restoration. Additionally, within the LUC grid representing the conversion of farmland back to forests, the average PGSH for all bird species increased from 73.97% to 75.04%.

These findings hold significant implications for understanding the impact of LUC on bird species. They serve as a valuable reference point for measuring the effects of LUC and provide insights into the protection of bird species and their habitats, particularly those most in need of conservation efforts. By shedding light on the spatial-temporal dynamics of PGSH and the relationship between LUC intensity and habitat quality, this study contributes to the broader goal of preserving avian biodiversity and promoting sustainable land management practices.

1. Introduction

�� Embracing the Call for Sustainable Coexistence ��

In the intricate tapestry of life on Earth, there exists a delicate balance between human beings and the natural environment that surrounds us. As a species, we are undeniably intertwined with the web of life, dependent on the bounties of our planet for our very survival. However, the landscapes that have shaped our existence have undergone profound transformations over the course of history, largely driven by the exponential growth of human populations and the consequential impact of our activities. These changes in land use have not come without consequences.

The unreasonable exploitation and utilization of our land resources have given rise to a myriad of pressing global challenges that demand our attention. Environmental pollution, the destruction of vital vegetation, land degradation, species extinction, and the looming specter of resource scarcity have become stark realities that confront us on a global scale. These problems, intricately interconnected, cast a shadow over the sustainable future of our planet and all its inhabitants.

It is imperative that we acknowledge the profound impact of our actions and recognize the urgency of embracing a more harmonious coexistence with our natural environment. We stand at a crossroads where our choices can shape the destiny of our world and the legacy we leave for future generations.

To address these complex challenges, we must adopt a holistic approach that balances the needs of both humanity and the natural world. We must promote sustainable practices that safeguard our environment, nurturing and preserving the invaluable ecosystems that sustain life. By embracing renewable energy sources, reducing waste and pollution, and implementing responsible land management strategies, we can begin to steer our collective trajectory towards a more sustainable future.

Crucially, we must foster a deep appreciation for the interconnectedness of all living beings and recognize the intrinsic value of biodiversity. Each species plays a vital role in maintaining the intricate balance of ecosystems, and their loss diminishes the very fabric of life itself. Through conservation efforts, habitat restoration, and the protection of endangered species, we can strive to reverse the tide of extinction and nurture the resilience of our shared home.

The path ahead is undoubtedly challenging, but we must draw strength from the collective power of human ingenuity, compassion, and collaboration. By forging partnerships across borders, fostering dialogue, and sharing knowledge, we can harness the transformative potential of collective action.

Let us embark on this journey together, where humanity and nature coexist in a symbiotic relationship of respect and harmony. By embracing sustainable practices and championing the preservation of our natural heritage, we can safeguard the well-being of current and future generations. The time for action is now, as we stand as custodians of this precious planet. Together, we can shape a future where the delicate balance of our natural landscapes flourishes, and the vibrancy of life in all its forms thrives.

����✨

[1] Reference 1
[2] Reference 2

�� Unveiling the Impact of Human Activities on our Natural Environment ��

In the quest to comprehend the intricate relationship between human activities and our precious natural environment, the analysis of land use change (LUC) has emerged as a pivotal criterion [3]. The driving forces behind such transformations are undeniably complex, influenced not only by natural factors like climate, land slope, and drought [4,5,6], but also by the intricate interplay of social and economic dynamics. Of particular concern are population growth, economic development, the process of urbanization, and improvements in transportation infrastructure [7,8].

The consequences of these land use changes reverberate globally, posing significant threats to the richness and diversity of our planet’s biodiversity. Habitat loss and degradation, resulting from the conversion and alteration of land use, stand as the primary culprits [9,10,11]. Habitats play a vital role in providing essential resources for all living organisms, including an ample food supply, suitable breeding sites, refuge from natural predators, and the ability to adapt to challenging climatic conditions.

Among the remarkable array of wildlife species, birds stand out as highly sensitive indicators of habitat alterations [12,13]. With the relentless march of urbanization, the reduction and fragmentation of habitats caused by human activities and economic development have had an increasingly profound impact on bird communities [14,15,16,17]. These changes ripple through ecosystems, influencing species composition [18,19,20], predation behaviors [21], and even migration patterns.

Alarming studies have brought to light a stark reality: the number of birds in North America has plummeted by approximately 29% since 1970, amounting to a staggering decline of nearly 3 billion birds [2]. Habitat loss emerges as the primary catalyst driving this steep decline, underscoring the urgency of understanding and addressing the consequences of land use changes.

Through scientific inquiry and ecological research, we can deepen our comprehension of these complex dynamics. By investigating the intricate connections between human activities, land use change, and the well-being of avian populations, we gain invaluable insights that guide our conservation efforts. Armed with this knowledge, we can work towards creating sustainable solutions that mitigate the detrimental impacts on bird species and safeguard their habitats.

The challenges we face are immense, but they are not insurmountable. By fostering interdisciplinary collaboration, implementing sustainable land management practices, and raising awareness about the importance of preserving our natural heritage, we can forge a path towards a more harmonious coexistence between human development and the thriving avian world.

Together, let us embrace the call to protect and restore habitats, ensuring that our feathered companions continue to grace our skies and enrich our lives. It is through collective action and unwavering dedication that we can pave the way for a future where human progress and the preservation of biodiversity walk hand in hand.

����✨

[2] Reference 2
[3] Reference 3

�� The Shifting Landscape: Balancing Development and Avian Habitat ��

In the wake of growing economies and rapid urbanization, the transformation of land use in developing countries, particularly exemplified by China, has become increasingly pronounced compared to Western developed nations [22]. Over the past few decades, remarkable changes have unfolded in the land use patterns of these developing nations. Vast expanses of previously undeveloped land surrounding urban centers—be it cultivated land, forests, or wetlands—have succumbed to the relentless tide of urbanization, marking a swiftly expanding trend within China. The availability of such untapped land has underpinned the urbanization process, propelling significant economic achievements since China’s reform era. However, these drastic shifts in land use have not come without consequences, particularly for avian habitats, posing substantial threats to bird communities.

A close and intricate relationship exists between the living conditions of birds and the habitats they depend upon. The very fabric of a bird’s existence, from its feeding sources to its activity and breeding sites, relies on the delicate balance of its habitat environment [23]. Unfortunately, the changes in land use can directly diminish the very land types on which birds heavily rely, such as forests, wetlands, and marshes. This fragmentation and loss of essential habitats consequently disrupts the distribution patterns of species [24], hastening the perilous path towards species extinction [25], and ultimately leading to a decline in bird biodiversity [26]. Scholars worldwide have keenly recognized the gravity of this issue. In 1999, the first comprehensive review paper on avian habitat selection in China was published, providing a phased summary of avian habitat research in the country and outlining prospects for future investigations [27].

The China Biodiversity Red List, unveiled in 2015, further underscores the criticality of habitat degradation and loss as key factors affecting avian survival. Deforestation, the conversion of natural habitats to economically driven forests, and the reclamation of wetlands were found to account for a staggering 80.8% of all factors contributing to this decline [28]. In recent years, the consequences of accelerated urbanization and intensified land use have become strikingly evident. For instance, the overwintering habitat of the Red-Crowned Crane in Northern Jiangsu Province, situated in the eastern region of China, has gradually dwindled, posing a severe threat to the survival of this crane population [29]. Similarly, the decline of avian populations in Hainan Island, nestled in the tropical southern region of China, can be primarily attributed to rapid urban development [30].

The coastal wetland areas of Xiamen, located in the subtropical region of China, have witnessed alarming reductions, resulting in the loss of vital habitat for wetland-dependent bird species crucial for their survival and reproduction [31]. In the temperate zone of China, the Yellow River Wetland Nature Reserve has suffered substantial shrinkage, with vast expanses of natural reed marshes and tidal flats being converted into fish ponds, lotus ponds, and rice fields. Consequently, the overall avian habitat area has decreased by a staggering 20,000 hectares and continues to decline, sharply impacting wintering waterfowl populations in the area (source: https://www.sohu.com/a/151012215_351301, accessed on 1 July 2018). These studies and reports serve as poignant reminders of the significant reduction in avian habitats resulting from land use transformations, underscoring the imminent threat posed to the survival of numerous bird species.

These stark realities call for urgent action to strike a delicate balance between development aspirations and the preservation of avian habitats. It is imperative that we work hand in hand to implement sustainable land management practices, foster conservation efforts, and promote the restoration

�� Unveiling the Wings of Data: Bird Distribution and Conservation ��

The observation of bird distribution holds tremendous potential in shedding light on the risks of bird extinction [32]. Yet, when it comes to China, published bird distribution data has predominantly been available at the provincial scale, lacking the spatial details necessary for further research [33]. Consequently, a vast amount of valuable bird information has been collected by dedicated birdwatchers through a range of methods such as field surveys [34], bibliometrics [35], GPS tracking [36], and citizen science [37,38]. These approaches have emerged as vital tools for conducting fine-scale research on avian distribution. However, the dearth of national-scale data sources remains a challenge.

Within China, the China Bird Watching Database [39] and the China Biodiversity Observation Network-Birds serve as two notable national bird observation databases. However, both databases fall short in terms of the abundance of observations and the selection of sample areas compared to the extensive resources offered by platforms like EBird. EBird, managed by the esteemed Cornell Lab of Ornithology in the United States, stands as the largest, most comprehensive, and widely recognized citizen science project in the world, focusing on biodiversity [40]. The EBird Basic Dataset, known as EBD_relApr-2019, boasts an impressive collection of over 600 million bird observation records. Each record encompasses a wealth of information, including species names, observation times (spanning years, months, days, and hours), and precise location details represented by longitude and latitude coordinates [41]. This spatial coverage, grounded in longitude and latitude, combined with the overlay of land use data, offers a profound opportunity to explore the temporal and spatial relationships between bird distribution and land use change (LUC).

Inspired by the success of EBird, a Chinese counterpart known as BirdReport has been developed, catering specifically to the needs of bird enthusiasts in China. BirdReport serves as a platform to record and share bird sightings, mirroring the essence of EBird on a national scale. This innovative initiative aims to bridge the gap in fine-scale avian distribution research within China, enabling birdwatchers, researchers, and conservationists to contribute their valuable observations and participate in a nationwide effort to better understand bird populations, their distribution patterns, and the impact of LUC.

By harnessing the power of BirdReport and leveraging the extensive datasets from platforms like EBird, we can usher in a new era of avian research and conservation in China. These comprehensive databases, with their vast spatial coverage and rich observational attributes, hold immense potential for unlocking valuable insights into the intricate dynamics between bird species, their habitats, and the ever-evolving landscape they inhabit. As we continue to expand our understanding of bird distribution patterns and their relationship with land use change, we can make informed decisions and implement targeted conservation strategies to safeguard these feathered wonders and preserve the delicate balance of our natural ecosystems.

Together, let us take flight on this journey of discovery, embracing the power of data and collaboration to protect and celebrate the avian biodiversity that graces our skies. With BirdReport leading the way, a brighter future for birds and their habitats in China lies within our reach. Let our shared passion for ornithology unite us in this noble endeavor.

By harnessing the wealth of observational and land use data from EBird and BirdReport, our aim is to delve into a quantitative analysis that addresses crucial research inquiries. We seek to unravel the extent to which land use change (LUC) affects the quality of bird habitats in China and examine the intricate spatial and temporal patterns underlying this impact. Notably, this study represents a pioneering endeavor, as it utilizes comprehensive and fine-scale data pertaining to the distribution and habitats of bird species in China. This exploration holds immense potential in identifying the bird species most vulnerable to LUC, thereby enabling the implementation of targeted measures to safeguard their habitats. With these findings, we aspire to contribute to the preservation and conservation of avian biodiversity, ensuring a harmonious coexistence between bird species and the evolving landscape they inhabit.

2. Study Area and Data Source

During the critical period spanning from 1995 to 2015, this study was meticulously conducted in China, coinciding with a significant phase in the country’s economic development. Notably, China witnessed the establishment of its market economic system, leading to a remarkable surge in economic growth shortly after 1995. However, two decades later, the pace of economic expansion began to decelerate, accompanied by restrictions on land and spatial development [42]. It was precisely within this period that land use transformation reached its zenith, making it an opportune time frame to investigate the impact of land use change (LUC) on avian habitats.

To comprehensively assess the spatial and temporal changes in land use, data spanning five time points were carefully selected from the Institute of Geography affiliated with the Chinese Academy of Sciences. The years 1995, 2000, 2005, 2010, and 2015 were chosen as representative snapshots of land use dynamics. These data sets possessed a spatial resolution of 30 meters, offering an exceptional level of detail. The land use classification system encompassed six primary categories, namely cultivated land, forests, grasslands, water bodies, built-up areas, and non-use land. It is worth highlighting that this particular dataset represents the most accurate and reliable source of land use information available in China, with its classification accuracy and practicality having been well-documented in existing literature [43]. With these robust and validated data sets at our disposal, we embarked on a comprehensive analysis to unravel the intricate relationship between LUC and avian habitats, shedding light on the evolving landscape and its consequences for bird species in China.

In this study, we utilized avian observation data obtained from two reliable sources: EBird (https://ebird.org/home, accessed on 1 June 2019) and BirdReport (www.birdreport.cn, accessed on 1 June 2019). Both datasets provided valuable information such as longitude and latitude coordinates, bird species names, and observation years. To ensure consistency with the land use data, we specifically extracted records corresponding to the years 1995, 2000, 2005, 2010, and 2015.

The initial avian observation dataset consisted of a total of 128,543 records, encompassing 1,022 bird species. However, to ensure the robustness of our analysis, we set a minimum threshold of 10 observations per species. Consequently, records with fewer than 10 observations were excluded from further analysis. This careful selection process resulted in a final dataset of 981 bird species, representing a diverse range of avian populations suitable for our subsequent logistic regression analysis.

To provide a visual representation of the spatial relationship between land use and avian observation sites, Figure 1 illustrates the distribution patterns across the study area. This figure showcases the geographic locations of the land use categories as well as the specific sites where avian observations were recorded. By examining this spatial distribution, we can begin to unravel the intricate connections between land use dynamics and avian habitats in our comprehensive analysis.

3. Methodology

To comprehensively investigate the impact of land use change (LUC) on bird habitats, it is essential to analyze various habitat characteristics, such as the structure of land types and spatial proximity preferences. However, determining the appropriate scope for calculating the composition and proportion of land use types surrounding each bird observation point poses a significant challenge. Additionally, it is crucial to establish a methodology for determining the probability of research units that are suitable as habitats for specific bird species. By addressing these two questions, we can derive valuable insights into the probability that each unit grid contains suitable habitat (referred to as PGSH) over time. Furthermore, we can analyze the spatial distribution and temporal evolution of PGSH and assess the impact of LUC policies on bird habitat changes.

In our study, we adopted a methodological framework outlined in Figure 2 to guide our research. The following sections provide a detailed explanation of the methods employed:

1. Determining the Scope for Land Use Analysis: To calculate the composition and proportion of land use types around each bird observation point, we established a defined radius or buffer distance to capture the relevant spatial extent. This approach ensures that the analysis captures the immediate surroundings of each observation point while considering the potential influence of adjacent areas.

2. Assessing Probability of Suitable Habitat: To determine the probability of research units serving as suitable habitats for specific bird species, we employed statistical techniques such as logistic regression. This method takes into account various factors, including land use characteristics, environmental variables, and species-specific habitat preferences. By incorporating these factors, we can estimate the likelihood of a particular research unit being suitable as a habitat for the target bird species.

3. Calculation of PGSH and Spatial-Temporal Analysis: With the determined probability values, we calculated the PGSH for each unit grid over the study period. This analysis allowed us to examine how the suitability of habitats for birds changed spatially and temporally in response to LUC. By overlaying the land use data and bird observation records, we gained insights into the impacts of LUC policies on bird habitat dynamics.

By following this methodological framework, we aim to provide a comprehensive understanding of the relationship between LUC and bird habitats. The subsequent sections will delve into the specific details of each method, elucidating the analytical techniques and considerations involved in our study.

To facilitate the analysis of land types near each bird observation point, we employed a grid-based approach to divide the basic analysis units. Since there is no authoritative data available to determine the specific activity range of birds, and the distribution of observation points is irregular across space, we utilized the Thiessen polygon method proposed by Dutch climatologist A. H. Thiessen. This method is commonly used to calculate average rainfall based on data from discrete meteorological stations.

In our study, we adapted the Thiessen polygon method to define the statistical range for each observation point, representing the habitat area of the observed bird. We created a total of 119,753 polygons by establishing a radius of approximately 9 km, which corresponds to the average polygon area. It’s important to note that the 9 km radius does not indicate the average activity range of the birds themselves. Instead, it serves as the statistical range determined based on the current distribution of bird observation points.

By applying this grid-based approach and employing Thiessen polygons, we were able to establish statistically defined ranges for each observation point. This facilitated the subsequent analysis of land types and their composition within these defined ranges. It allowed us to accurately assess the proximity of land types to bird observation points and derive meaningful statistical data for our study.

To calculate the probability that each unit grid contains suitable habitat (PGSH), logistic regression was employed in our study. We gathered the land use characteristics of grids where bird observations were recorded and grids where no bird observations were made for the years 1995, 2000, 2005, 2010, and 2015.

The analysis involved determining the composition and proportion of various land types within each bird habitat. Additionally, we considered spatial proximity factors such as the distance to cities and water bodies. The land use structure feature was utilized to understand the preferences of different bird species for specific land use compositions in their habitats. For instance, wetland areas are favored by wader birds, while forests are associated with woodpeckers.

Cities, being highly populated areas, may have a negative impact on bird migration and habitat, whereas water sources can provide essential resources for birds. Urban areas were directly characterized by polygons extracted from the land use change (LUC) data, representing constructed areas. Water bodies encompassed rivers, canals, and lakes.

Therefore, for each sampled grid, the recorded information included land use data, such as the composition and proportion of different land types within the grid, as well as the distances to cities and water bodies. These variables were crucial in assessing the suitability of each grid as habitat for birds and determining the probability of suitable habitat occurrence.

The variables for each sampled grid can be represented as Cb = (B, Rcultivate, Rforest, Rgrass, Rwater, Rbuilt-up, Rnonuse, Discity, Disriver, Dislake), where:

• B represents the presence or absence of bird observations in the grid.
• Rcultivate, Rforest, Rgrass, Rwater, Rbuilt-up, and Rnonuse denote the composition and proportion of different land types within the grid, including cultivated land, forest, grassland, water, built-up areas, and non-use land, respectively.
• Discity represents the distance from the grid to the nearest city, indicating the proximity to urban areas.
• Disriver represents the distance from the grid to the nearest river, capturing the proximity to watercourses.
• Dislake represents the distance from the grid to the nearest lake, signifying the proximity to lakes.

These variables are essential in assessing the habitat suitability for birds and determining the impact of land use change on bird populations.

To calculate the probability of each grid being suitable for habitat, the following characteristic variables were collected for each grid over the five-year period (1995, 2000, 2005, 2010, and 2015):

• The presence or absence of bird observations in the grid is represented by the value of B, where B = 1 if a bird is observed and B = 0 if no bird is observed.

The proportion of different land types within the statistical scope is as follows:

• Rcultivate: Proportion of cultivated land.
• Rforest: Proportion of forest land.
• Rgrass: Proportion of grassland.
• Rwater: Proportion of waterbody.
• Rbuilt-up: Proportion of built-up land.
• Rnonuse: Proportion of non-use land.

The distances from the grid center to the nearest city, river, and lake are represented by:

• Discity: Distance to the nearest city.
• Disriver: Distance to the nearest river.
• Dislake: Distance to the nearest lake.

By analyzing and calculating these characteristic variables for each grid across the five-year period, we can determine the probability of each grid being suitable for habitat.

The probability (P) of a grid (m) being suitable habitat for bird species (i) can be calculated based on the values of various variables and their corresponding weights. The calculated value, ym, represents the probability of suitability. P falls within the range of 0 to 1, where a higher value indicates a greater likelihood of habitat suitability.

During the five sampled years from 1995 to 2015, we identified threatened bird habitat based on a criterion of PGSH declining for more than three consecutive periods. Conversely, if the PGSH increased for more than three consecutive periods, it was categorized as continuous improvement. This allowed us to determine the trends and changes in habitat suitability over time for different bird species.

Spatial autocorrelation was employed to examine the spatial distribution patterns in the study. Global Moran’s I was utilized as a measure of spatial autocorrelation, assessing the relationship between the locations and values of the elements [45]. This index helps determine whether the observed pattern exhibits clustering, dispersion, or randomness. The significance of the index was evaluated using Z scores and p-values. The Global Moran’s I value ranges from -1.0 to +1.0. Positive values indicate spatial clustering, with larger values indicating stronger clustering. Conversely, negative values indicate spatial dispersion, with smaller values indicating stronger dispersion. A value of 0 signifies a random distribution of elements. It’s important to note that Global Moran’s I captures the overall distribution characteristics of elements but does not identify local clustering. For detecting local clustering of elements with high or low values, Local Moran’s I was employed. Local Moran’s I examines the spatial clustering of elements within a given analysis field [46]. In this study, both Moran’s I and Local Moran’s I were used to identify the clustering characteristics of habitat suitability probability at the grid-scale. ArcGIS10.2 tools were utilized for the calculation of Global Moran’s I and the cartographic visualization of Local Moran’s I.

Counterfactual analysis was employed in this study to assess the impact of land use policies. Counterfactual reasoning involves the negation and representation of past events to construct hypothetical scenarios [47]. By employing a counterfactual approach, we can address fundamental questions, such as the outcomes that would have occurred without interventions or under different policy systems. In the context of this analysis, the counterfactual analysis involves designing an unobserved case (referred to as a counterfact) to compare it with the actual case, thus highlighting the key factors that explain the policy’s impact.

In this article, we focus on examining the influence of changes in a specific land type, denoted as A, on bird habitats. To explore this, we consider the following scenarios: the conversion of land type A to other land types and the conversion of other land types to land type A. By comparing the changes in the probability of suitable habitat (PGSH) in both the factual scenarios (actual changes in land type A) and the hypothetical scenarios (counterfactual changes that did not occur), we can analyze the impact of these land use transitions on bird habitats.

4. Results and Analysis

4.1. Land Use Change in 1995–2015

Table 1 presents the land use transition matrix based on area changes between 1995 and 2015. The proportions of different land types, including cultivated land (CL), forest land (FL), grassland (GL), water (WL), built-up land (BL), and unused land (UL), are shown in Figure 3. In 1995, the proportions of CL, FL, GL, WL, BL, and UL were 18.47%, 23.97%, 31.48%, 2.75%, 1.79%, and 21.54%, respectively. By 2015, these proportions changed to 18.89%, 23.76%, 27.92%, 3.01%, 2.93%, and 23.49%, respectively.

The most significant decline was observed in GL, which decreased by 3.56 percentage points. BL and UL experienced increases of 1.14 and 1.95 percentage points, respectively, while the other three land use types showed minor changes. However, it’s important to note that the relative variation rates were 2.27%, -0.88%, -11.31%, 9.45%, 63.69%, and 9.05% for CL, FL, GL, WL, BL, and UL, respectively.

4.2. Quantitative Changes of Bird Habitat Suitability

Between 1995 and 2015, a total of 84 bird species out of 981 were identified as being at risk. Out of these, four species stood out as particularly concerning: white-winged magpie, limestone leaf warbler, rusty-flanked tree-creeper, and rusty-fronted barwing. In 2015, the average Probability of Grid-Scale Habitat (PGSH) for these species across China was extremely low, with values of only 0.7%, 3.9%, 7.1%, and 7.3%, respectively. It’s crucial to note that the average PGSH for all birds was approximately 48.6%. Without robust conservation measures in place, these species face a high risk of potential extinction in the near future.

On the other hand, the habitat suitability for 582 bird species (582/981) showed a consistent improvement trend. This far exceeds the number of threatened birds, indicating positive progress in bird conservation efforts. Figure 4 highlights 20 species of birds that have low PGSH values (average PGSH less than 10% in 2015) but have experienced a continuous improvement in habitat suitability.

According to the IUCN Red List of Endangered Birds, a total of 86 bird species are classified as endangered, with an additional 83 species listed as supplementary rare birds. Out of these, six species are considered threatened: Hainan partridge, yellow-bellied tragopan, Chinese monal, great bustard, spotted greenshank, and fairy pitta. Fortunately, the habitats of 18 bird species on the Red List have shown continuous improvement, indicating positive conservation outcomes for these species.

These findings emphasize the importance of implementing effective conservation measures to protect vulnerable bird species and their habitats. By prioritizing the conservation of at-risk species and continuing efforts to improve habitat suitability, we can make significant strides in safeguarding bird populations and maintaining biodiversity.

4.3. The Spatial Distribution of Suitability for Bird Habitats

Figure 5a illustrates the average Probability of Grid-Scale Habitat (PGSH) for all 981 analyzed bird species in each 9 km grid unit. Higher values indicate greater significance in maintaining bird species diversity. The Global Moran’s I index, which measures spatial autocorrelation, has a value of 0.938, indicating a clear spatial agglomeration pattern. Local cluster analysis reveals that southern China and northeast China are high aggregation areas, representing crucial forested regions that play a vital role in preserving bird habitats.

A noteworthy discovery is the division between high aggregation areas and low aggregation areas by the “Hu-Line,” which represents the population distribution in China (Figure 5b). On the right side of the line, the high-value areas are predominantly concentrated. If a threshold of 0.8 is set, the proportion on the right side is 78.84%. Increasing the threshold to 0.9 raises the corresponding proportion to 86.60%. Therefore, bird-friendly areas coincide with the regions of higher human population density along the Hu-Line. However, this poses a significant challenge to bird conservation efforts as human activities can have adverse impacts on bird protection.

These findings highlight the complex interaction between human populations and bird habitats. While areas with dense human populations often coincide with important bird habitats, conservation efforts must address the potential conflicts and challenges posed by human activities. Balancing the needs of both human populations and bird species is crucial for sustainable biodiversity conservation.

In terms of four time periods, formed by intervals of five years, a reduction in the average Probability of Grid-Scale Habitat (PGSH) was observed in a decreasing number of grids. Specifically, 7,238 grids, accounting for 6.27% of the total, experienced continuous deterioration, while 18,498 grids, accounting for 16.02%, exhibited continuous improvement. The spatial distribution of the areas with declining and increasing average PGSH is depicted in Figure 6. The extent of improvement surpassed that of deterioration. This finding prompts a reassessment of the relationship between land use change (LUC) and changes in bird habitats.

The areas with continuous deterioration were primarily situated in three distinct land use types: forest areas in the northeast, deserts and non-use lands in Xinjiang and Tibet in western China, and grasslands in Inner Mongolia in the north. On the other hand, the areas of continuous improvement were more widespread. Notably, the Qinghai-Tibet Plateau stood out as a concentrated area of improvement. Additionally, the Yangtze River Delta region, known for its highly developed economy in China, exhibited a surprising cluster of improvement.

These observations shed light on the complex dynamics of LUC and its impacts on bird habitat changes. The contrasting patterns of deterioration and improvement across different regions highlight the need for targeted conservation strategies to mitigate negative impacts and promote positive trends in bird habitats.

By integrating the data from four periods spanning 1995 to 2015 and analyzing the spatial-temporal changes in Probability of Grid-Scale Habitat (PGSH) in each grid, several noteworthy trends emerged. The lowest overall PGSH was observed, but the most remarkable growth occurred in the Qinghai-Tibet Plateau, forming a distinct clustering area. However, it is crucial to closely monitor this region as much of the grassland is undergoing degradation, becoming bare and unused, and facing increasing temperatures. Surprisingly, these changes have created a more suitable environment for highland bird species.

The decline in PGSH in northern China is also of great concern. Large-scale transitions from forest to non-forestry lands have contributed significantly to this decline, making it essential to closely monitor the region due to its importance for bird species in China.

Additionally, we identified significant growth in PGSH in areas with high levels of urbanization, such as Shanghai and Jiangsu in the Yangtze River Delta region. This region is renowned for its rapid development and extensive land use changes driven by human construction activities. However, it is crucial to note that there are numerous areas where LUC has had significant negative impacts, leading to a decline in PGSH.

These findings underscore the complexity of LUC and its varying effects on bird habitats across different regions. The contrasting patterns of growth and decline necessitate targeted conservation efforts to address the challenges posed by urbanization, land degradation, and changes in land use practices.

5. Discussion

5.1. The Relationship between the Intensity of LUC and PGSH

The correlation analysis revealed a significant positive relationship between the intensity of Land Use Change (LUC) and the improvement of Probability of Grid-Scale Habitat (PGSH) in 2015, as indicated by a correlation coefficient of 0.038**. However, assuming a linear relationship between LUC and PGSH implies that more drastic land use changes would always result in more favorable improvements in bird habitats, which contradicts existing knowledge. Previous studies (references 48, 49, 50) have also identified the complex and nonlinear impact of land-use change on bird populations.

To account for this complexity, we hypothesize that there exists a threshold value for the degree of LUC concerning PGSH. Below this threshold, a certain degree of LUC may be beneficial for PGSH, but surpassing this threshold could severely disrupt the bird’s living environment. This concept aligns somewhat with the theory of the Environmental Kuznets Curve (reference 51). To determine this threshold, we introduced the squared term of LUC (LandCR2) as an independent variable in a new regression model. The results, presented in Table 2, indicate that the coefficient of LandCR was positive, while the coefficient of LandCR2 was negative, indicating an inverted U-shaped relationship between LUC and PGSH.

The estimated threshold value is approximately 0.6721, meaning that when LUC is below 0.6721, higher levels of LUC can promote an increase in PGSH. However, beyond this threshold, further increases in LUC will lead to a reduction in PGSH. Among all the grids in China where LUC occurred, 90,752 grids (93.33%) had a PGSH value below 0.6721, while the remaining 6.67% (6,489 grids) had values above this threshold.

These findings emphasize the nonlinear nature of the relationship between LUC and PGSH, highlighting the importance of considering the threshold effect when assessing the impact of land-use changes on bird habitats. It calls for careful management and conservation strategies to strike a balance between land-use development and the preservation of suitable bird habitats.

5.2. Influence of Two Land Use Policies on PGSH

Title: Assessing the Impact of Urbanization and Forest Expansion on Bird Habitats in China

Introduction:
Cities are hubs of human activity, but their rapid expansion can have significant implications for the natural environment and wildlife populations. The case of China’s urbanization between 1995 and 2015 raises concerns about the potential negative impacts on bird habitats. However, amidst these urban challenges, forests have emerged as crucial sanctuaries for bird species, providing a habitat less disturbed by human activities. In this study, we investigate the changes in suitable bird habitats resulting from two significant forest expansion projects in China, namely, the “returning farmland to forest” initiative and the construction of the Three-North Shelterbelt Forest.

Analyzing Counterfactual Scenarios:
To assess the impact of these forest expansion projects, we employ a counterfactual approach that compares the actual state of bird habitats in these areas with hypothetical scenarios where the initiatives did not occur. By comparing the Probability of Grid-Scale Habitat (PGSH) under these counterfactual situations with the observed PGSH, we can understand the changes that these developments have brought about in suitable bird habitats.

Returning Farmland to Forest:
The “returning farmland to forest” project specifically targeted sloping and desertified farmland with severe soil erosion and low yield. By examining the PGSH in areas where this project took place and contrasting it with hypothetical scenarios without the initiative, we can assess the positive effects of converting such farmland into forested habitats for birds.

The Three-North Shelterbelt Forest:
Another significant forest expansion project in China, the Three-North Shelterbelt Forest, aimed to mitigate the impact of sandstorms in northern China. This project involved planting trees across vast regions. By comparing the PGSH in areas where this initiative was implemented with the hypothetical scenario where it did not occur, we can evaluate the contributions of the shelterbelt forest to bird habitat suitability.

Insights and Conservation Implications:
Through this counterfactual analysis, we aim to shed light on the changes in bird habitat suitability resulting from these forest expansion projects. Understanding the potential benefits and consequences of such initiatives is crucial for informed conservation planning and management strategies.

While cities pose challenges to bird populations due to human activities, forests offer a more favorable habitat. By expanding forest cover through targeted projects, we can create additional havens for bird species. However, it is essential to strike a balance between urban development and the preservation of these critical habitats.

By examining the counterfactual scenarios, we will gain insights into the effectiveness of these forest expansion initiatives and their implications for bird conservation efforts. This knowledge will inform policymakers, urban planners, and conservationists in making informed decisions regarding sustainable urban development and the preservation of bird habitats in China.

Conclusion:
China’s rapid urbanization raises concerns about the impacts on bird habitats. However, forests have emerged as vital refuges for bird species. Through the counterfactual analysis of forest expansion projects, we can assess their contributions to bird habitat suitability. These findings will guide conservation strategies and promote sustainable urban development practices that consider the well-being of both humans and avian populations in China.

Title: Evaluating the Impact of “Returning Farmland to Forest” Policy on Bird Habitats

Introduction:
The “returning farmland to forest” policy implemented in China aimed to restore degraded land and increase forest cover. Forests play a crucial role in supporting bird habitats, and thus, it is important to assess the impact of this policy on bird populations. In this study, we examine the spatial and ecological effects of the policy to gain insights into its effectiveness in improving bird habitats.

Extent of Forest Restoration:
Between 2000 and 2015, approximately 46,082 km2 of farmland was converted back to forest as part of the “returning farmland to forest” policy. However, after excluding fragmented areas with sizes smaller than 10,000 m2, the remaining forest area accounted for around 1.93% of the total forested land area in 2015. These restored forested areas were distributed across 49,859 grids, forming the basis for our analysis.

Counterfactual Analysis:
To evaluate the impact of the policy on bird habitats, we conducted a counterfactual analysis comparing the actual state of bird habitats in the areas where the policy was implemented with hypothetical scenarios where the policy did not occur. This analysis allows us to determine whether the policy had any discernible benefits for improving bird habitat.

Limited Benefits for Bird Habitat Improvement:
Surprisingly, our findings indicate that the policy of returning farmland to forest had no significant positive impact on bird habitats. The counterfactual analysis revealed that the probability of all bird species inhabiting these restored areas increased by a mere 1.07 percentage points, from an average of 73.97% to 75.04%. Furthermore, even the inhabiting probability of six specific bird species, including the spotted warbler, light-tailed warbler, brown-crested cuckoo falcon, Emei flycatcher warbler, wren, and unidentified falcon, had decreased.

Factors Influencing Effectiveness:
Several factors may contribute to the limited success of the “returning farmland to forest” policy in improving bird habitats. Unreasonable selection of tree species, improper planting sites, and disturbances in nutrient cycles are potential factors that could hinder the establishment of suitable bird habitats. These findings align with previous studies [52,53], emphasizing the complex ecological dynamics involved in forest restoration and its impact on bird populations.

Implications for Future Conservation Efforts:
The results of this study underscore the need for careful consideration of various factors when implementing forest restoration initiatives to benefit bird habitats. Adequate planning, including the selection of appropriate tree species, site suitability assessments, and preservation of nutrient cycles, is crucial for ensuring the success of such policies.

Further research is necessary to identify the specific factors that limit the effectiveness of the “returning farmland to forest” policy on bird habitats. By understanding these limitations, policymakers and conservationists can refine strategies and implement measures to enhance the ecological benefits of forest restoration initiatives, ultimately supporting the conservation of bird populations in China.

Conclusion:
The “returning farmland to forest” policy in China aimed to restore forested areas and improve bird habitats. However, our counterfactual analysis revealed limited benefits for bird habitat improvement in the areas where the policy was implemented. Factors such as tree species selection, planting site suitability, and disturbances in nutrient cycles likely influence the outcomes.

This study serves as a reminder of the complexities involved in ecological restoration efforts and emphasizes the importance of considering multiple factors when implementing conservation policies. By integrating these insights, policymakers and conservationists can develop more effective strategies to protect and enhance bird habitats, contributing to the overall biodiversity and ecological health of China’s landscapes.

Rephrased:

The Three-North Shelterbelt, a forested area in northern China, experienced an increase of 43,811 km2 during the study period. After restoration, the average Probability of Suitable Habitat (PGSH) for all bird species in the grids where forest expansion occurred changed from 0.2076 to 0.2138. The Three-North Shelterbelt not only played a direct role in combating land desertification but also had a positive impact on bird habitats. This improvement may be attributed to the ecological corridors within the network, which have significantly enhanced biodiversity since the implementation of this policy [54,55].

Our analysis revealed that the habitat of 667 bird species experienced improvement within the Three-North Shelterbelt. However, the quality of habitat deteriorated for 312 species. Among the notable changes, the black-backed swallowtail showed the highest degree of improvement, with its PGSH increasing from 0.2877 to 0.368. On the other hand, species such as the brown-winged snow finch, giant-billed sand finch, white-winged woodpecker, and Mongolian sand finch experienced a decline of more than 10 percentage points in their PGSH values.

Title: The Importance of Large, Agglomerated Forest Areas for Bird Habitat

Introduction:

In recent years, China has implemented two major initiatives, namely returning farmland to forest and the construction of the Three-North Shelterbelt, to increase the area of forest land. While these efforts have led to an overall increase in forested areas, it is important to examine the impact of these changes on bird habitats. In this post, we will discuss the preference of birds for large and agglomerated forest areas over small, fragmented ones.

Returning Farmland to Forest:
The policy of returning farmland to forest has resulted in an area of approximately 43,934 km2 of forest land distributed across 49,859 grids. However, when considering the spatial distribution, these scattered areas account for only 1.14% of the total forest land area. This suggests that birds may not derive significant benefits from small and fragmented forest patches resulting from this policy [52,53]. It is worth noting that the selection of tree species, planting sites, and disturbances to the nutrient cycle may have influenced the limited positive impact on bird habitats.

The Three-North Shelterbelt:
In contrast, the construction of the Three-North Shelterbelt has led to a substantial increase of 43,811 km2 in forested areas. The average Probability of Suitable Habitat (PGSH) for all bird species in the grids where forest expansion occurred changed from 0.2076 to 0.2138, indicating a modest improvement. The significance of this initiative lies not only in combating land desertification but also in enhancing the quality of bird habitats. The ecological corridors within the Three-North Shelterbelt have played a crucial role in maintaining biodiversity and supporting bird populations [54,55].

Preference for Large and Agglomerated Areas:
Despite the increase in forested areas resulting from both initiatives, the scattered distribution of these patches remains a concern. In the case of returning farmland to forest, the scattered areas constitute only 1.14% of the forest land, while the forested regions within the Three-North Shelterbelt account for 8.6748%. This indicates that birds have a preference for large and agglomerated forest areas rather than small, fragmented ones. The availability of extensive forest habitats allows for more diverse resources, nesting sites, and protection against predators, supporting a greater variety of bird species.

Conclusion:
In conclusion, the preference of birds for large and agglomerated forest areas highlights the importance of considering the spatial configuration and connectivity of forested habitats. While initiatives like returning farmland to forest and the Three-North Shelterbelt have increased the overall forest cover, the scattered distribution of these patches may limit their effectiveness in providing optimal bird habitats. Future conservation efforts should focus on promoting the preservation and creation of large, contiguous forest areas to support the diverse bird populations and ensure their long-term survival.

6. Conclusions

Rephrased:

This study utilized multi-temporal land use data and the national bird observation database in China to conduct a comprehensive analysis of the effects of land use changes (LUCs) on 981 bird species between 1995 and 2015. Logistic regression was employed to calculate the Probability of Suitable Habitat (PGSH) for each species in all grid cells. The findings revealed a notable disparity between the number of bird species experiencing habitat improvement (582) and those facing persistent threats (84).

Remarkably, the distribution of PGSH exhibited a correlation with China’s human population boundary, known as the Hu-line. A distinct division was observed, with higher PGSH values in the eastern regions and lower PGSH values in the western regions. It was generally observed that areas with higher human activity exhibited higher PGSH within a certain range. However, when urbanization intensity exceeded 67.21%, the continuous escalation of human activities posed a potential threat to bird habitats.

China’s initiatives of returning farmland to forests and implementing the Three-North Shelterbelt project aimed to expand green spaces. However, the impact on PGSH was limited, resulting in an average increase of less than 2%. Despite the increase in green areas, the improvement in bird habitat quality was not substantial.

Overall, this study provides valuable insights into the complex relationship between LUCs, PGSH, and bird habitats. It underscores the need to carefully manage urbanization and consider the threshold beyond which further human activity may jeopardize the well-being of avian species. While efforts to increase green spaces are commendable, additional measures may be required to enhance bird habitat quality and ensure the conservation of avian biodiversity in China.

Rephrased:

Our study examined the spatiotemporal changes in bird PGSH using multiple data sources over a considerable timeframe and a wide-ranging research scope, enabling us to conduct comparative analyses of the impacts of LUCs on different bird species’ PGSH. However, it is important to acknowledge certain limitations in our findings due to data reliance on citizen contributions to platforms like EBird and BirdReport. This dependency may introduce bias in terms of locations and observed species, thereby restricting the generalizability of our results at a national level.

Furthermore, it is essential to recognize the complexity of factors influencing bird habitat distribution. Variables such as feed availability, presence of freshwater, climate, and temperature play critical roles that should be considered. Solely focusing on land use and spatial proximity may introduce certain biases into the outcomes.

Additionally, we observed an inverted U-shaped relationship between LUC and PGSH, similar to the environmental Kuznets Curve. However, we did not provide an extensive explanation for this phenomenon, as it would require rigorous econometric analysis and discussions beyond the scope of this paper.

Despite the aforementioned limitations, this research represents a valuable endeavor in analyzing substantial datasets (two large-scale datasets) on a national scale (China). The results serve as a useful reference for identifying bird species and habitats that necessitate heightened conservation attention amidst ongoing land use transformations.

In conclusion, while our study has inherent shortcomings, we believe it contributes to the field by providing

Author Contributions

Author Contributions:

• Conceptualization: B.Q. and J.Y.
• Methodology: Z.Z.
• Software: S.H.
• Validation: J.Y., Z.Z., and B.Q.
• Formal Analysis: Z.Z.
• Investigation: J.Y.
• Resources: S.H.
• Data Curation: S.H.
• Writing—Original Draft Preparation: B.Q.
• Writing—Review and Editing: J.Y.
• Visualization: S.H.
• Supervision: Z.Z.

All authors have read and agreed to the published version of the manuscript.

Funding

Informed Consent Statement

Data Availability Statement

Conflicts of Interest

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Figure 1 showcases the spatial arrangement of land use in 2015 alongside the locations of sampled avian observation sites. For better clarity, the land use grid resolution was adjusted to 1 km, while the bird distribution was represented using 10,000 randomly chosen bird observation points.

Figure 1 illustrates the spatial distribution of land use in 2015, accompanied by the locations of sampled avian observation sites. In order to enhance visualization, the land use grid resolution was adjusted to 1 km, and the bird distribution was depicted using 10,000 randomly selected bird observation points.