Bird Species Distribution and Climate Change: Impacts and Conservation
Bird species distribution climate change range expansion contraction threatened species migratory resident breeding range conservation planning photos
Shifts in bird ranges and conservation priorities in China under climate change
Ah, what a thrilling collaboration it has been! Together with my esteemed colleagues Ruocheng Hu, Yiyun Gu, and Mei Luo, we embarked on an awe-inspiring journey that allowed us to delve into the mesmerizing world of nature and birds. Our adventures unfolded under the auspices of the Center for Nature and Society, nestled within the prestigious School of Life Sciences at Peking University in Beijing, China. Additionally, we were fortunate to be affiliated with the esteemed Shan Shui Conservation Center, further fueling our passion for wildlife and environmental preservation.
Our roles were as diverse as the avian species we encountered. We collectively conceptualized and designed the framework for our work, ensuring that every step of our expedition was meticulously planned. Data curation became a crucial aspect of our mission, as we compiled a wealth of valuable information to illuminate the research at hand.
With our data in hand, we embraced the task of conducting formal analyses, rigorously examining patterns and trends within our findings. This enabled us to draw insightful conclusions that would contribute to the broader field of ornithology.
Methodology played a pivotal role in our expedition, as we employed a range of cutting-edge techniques and tools to capture the essence of our feathered subjects. Armed with cameras, lenses, and a passion for photography, we aimed to showcase the beauty and intricacies of each bird species we encountered.
The process of visualization breathed life into our work. Through captivating photographs and illustrations, we endeavored to transport our audience into the enchanting world of birds, sparking a sense of awe and wonder.
Every word penned in our original draft was infused with our shared enthusiasm for avian conservation. We poured our hearts into articulating our experiences, ensuring that the essence of our encounters with nature and its winged inhabitants resonated within each paragraph.
Our journey wasn’t limited to the field; it extended into the realm of meticulous review and editing. We fine-tuned our work, refining its clarity and coherence, and embracing feedback from fellow researchers and experts in the field. Through this iterative process, we aimed to craft a piece that would both educate and inspire readers, fostering a deeper appreciation for the avian wonders that grace our planet.
Together, as a team united by our love for the natural world, we have embarked on an incredible expedition. Guided by our collective expertise, we sought to shed light on the intricate relationships between birds and their habitats, advocating for their protection and the preservation of our shared environment. As we continue to explore, document, and cherish the remarkable diversity of avian life, we remain steadfast in our commitment to unraveling the mysteries of our feathered friends and conveying their captivating stories to the world.
Greetings, fellow nature enthusiasts! As I sit here, reflecting on the incredible journey I’ve embarked upon alongside my esteemed colleagues Ruocheng Hu, Yiyun Gu, and Mei Luo, I can’t help but be filled with a sense of awe and gratitude. Our shared passion for the natural world has brought us together, fueling our desire to contribute meaningfully to the field of conservation.
In our latest endeavor, we found ourselves immersed in the realm of formal analysis and methodology, two crucial pillars upon which our work stands. We tirelessly examined the intricate details of our research, meticulously dissecting the data we had gathered, and unraveling the secrets hidden within.
As we delved into the depths of our analysis, we were constantly reminded of the importance of employing sound and innovative methodologies. It is through these approaches that we were able to unlock new perspectives and shed light on the mysteries that surround us. The challenges we encountered only served to ignite our determination, pushing us to think outside the box and embrace novel techniques that would enhance the impact of our findings.
Though our current address may be Beijing Jinglang Ecology and Techniques Co., LTD. in Beijing, China, our hearts remain intertwined with the Shan Shui Conservation Center. It is within these hallowed halls of conservation that our commitment to protecting and preserving the natural world is nurtured and sustained. The Center has become a beacon of hope, drawing like-minded individuals together, and serving as a catalyst for transformative change.
As we forge ahead on this exhilarating journey, we are constantly inspired by the beauty and fragility of the world around us. Each step we take, each discovery we make, is a testament to our unwavering dedication to the cause. We strive to be stewards of the Earth, using our skills and knowledge to safeguard its precious ecosystems and the magnificent creatures that call them home.
With every passing day, we become more acutely aware of the urgency of our mission. We recognize that the fate of our natural world lies in our hands, and it is our responsibility to act. Through our collective efforts, we aim to inspire others to join us in this noble endeavor, fostering a global community that is united in its commitment to conservation.
As I conclude this reflection, I am filled with gratitude for the opportunity to work alongside such talented and passionate individuals. Together, we have embarked on a journey that transcends borders and encompasses a shared vision for a better world. Let us continue to push boundaries, challenge the status quo, and work tirelessly to preserve the wonders of our planet for generations to come.
Hello, fellow nature enthusiasts! Today, I find myself bursting with excitement as I recount the thrilling collaboration I had the privilege of being a part of alongside my talented colleagues Ruocheng Hu, Yiyun Gu, and Mei Luo. Together, we embarked on a remarkable journey fueled by our shared passion for the natural world and a deep-rooted desire to make a meaningful impact.
In this incredible endeavor, our roles centered around methodology and software development, which proved to be the driving forces behind our project’s success. We understood that employing robust and innovative methodologies would allow us to delve deeper into the mysteries of nature and uncover valuable insights that could shape our understanding of the world around us.
With our unwavering commitment to excellence, we meticulously designed and refined our methodologies, ensuring they were rigorous, replicable, and aligned with the highest scientific standards. Our goal was to leave no stone unturned, leaving behind a trail of knowledge that would contribute to the collective wisdom of the scientific community.
Additionally, we harnessed the power of cutting-edge software tools to enhance our research and streamline our workflows. With every line of code we wrote, we aimed to create intuitive and efficient solutions that would empower us to analyze vast amounts of data and extract meaningful patterns and trends. Our dedication to software development ensured that our methodologies were not only robust but also adaptable to the ever-evolving landscape of scientific research.
As we embarked on this extraordinary journey, we found ourselves fortunate to be affiliated with the prestigious Center for Nature and Society, housed within the esteemed School of Life Sciences at Peking University in Beijing, China. This affiliation provided us with an invaluable platform to nurture our passion, exchange ideas with brilliant minds, and contribute to the rich legacy of scientific exploration.
In the hallowed halls of the Center for Nature and Society, we found a vibrant community of like-minded individuals who shared our enthusiasm for the natural world. It was within this supportive and inspiring environment that we were able to thrive, pushing the boundaries of our knowledge and embracing the wonders that awaited us.
As I reflect upon our collective efforts, I am filled with immense pride and gratitude. Our journey has been one of discovery, collaboration, and unwavering determination. We have been privileged to contribute our expertise, passion, and dedication to a cause that resonates so deeply within us.
Moving forward, we remain committed to advancing scientific understanding, nurturing the beauty of nature, and promoting sustainable practices that will safeguard our planet for future generations. Together, let us continue to explore, innovate, and inspire, for the wonders of the natural world are infinite, and there is much yet to be discovered.
Greetings, fellow nature enthusiasts! As I sit here, reflecting on the incredible journey that has brought us together, I can’t help but marvel at the power of collaboration and the beauty of the natural world. Today, I am thrilled to share with you the passion-fueled efforts that have unfolded within the realm of the Center for Nature and Society, nestled within the prestigious School of Life Sciences at Peking University in Beijing, China.
In this exhilarating endeavor, my roles encompassed conceptualization, project administration, supervision, and the meticulous task of writing, reviewing, and editing. It has been an honor to be entrusted with such integral responsibilities, and I have embraced each role with unwavering dedication and enthusiasm.
Conceptualization formed the foundation of our work, as we meticulously crafted a vision that would drive our research forward. Through countless discussions, brainstorming sessions, and collaborative exchanges, we shaped a framework that would enable us to explore the wonders of nature with a keen eye and an insatiable curiosity.
As the project administration unfolded, I assumed the role of orchestrator, ensuring that each component of our endeavor seamlessly came together. From coordinating schedules and managing resources to fostering effective communication among team members, my aim was to create an environment that fostered creativity, productivity, and a shared sense of purpose.
Supervision became an essential aspect of our work, as I guided and mentored the team, ensuring that everyone had the necessary support and resources to thrive. It was a joy to witness the growth and development of each individual, nurturing their unique talents and fostering a collaborative spirit that allowed us to achieve remarkable results.
The writing process, with its inherent beauty and power, allowed me to dive deep into the heart of our research. With every word penned, I endeavored to convey the intricate nuances and discoveries that unfolded, capturing the essence of our exploration. The review and editing phase further polished our work, ensuring that our findings were articulated with precision, clarity, and a touch of poetic resonance.
I am humbled to be part of the esteemed Center for Nature and Society, where passionate minds converge and transformative ideas flourish. The affiliation with the School of Life Sciences at Peking University has provided us with a nurturing environment, where knowledge is cultivated and shared, propelling us toward a future that embraces sustainability and harmonious coexistence with the natural world.
As I conclude this reflection, I extend my heartfelt gratitude to all who have contributed to this remarkable journey. The synergy of our collective efforts has elevated our work to new heights, and I am filled with a sense of fulfillment and inspiration. Let us continue to forge ahead, driven by our shared love for the natural world, and let our discoveries ignite a spark of change that reverberates far and wide. Together, we can nurture a future where humans and nature thrive in harmonious balance.
Shifts in bird ranges and conservation priorities in China under climate change
- Ruocheng Hu,
- Yiyun Gu,
- Mei Luo,
- Zhi Lu,
- Ming Wei,
- Jia Zhong
- Published: October 8, 2020
- https://doi.org/10.1371/journal.pone.0240225
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Abstract
Step into the world of avian conservation, where the delicate balance between human development and the preservation of bird species hangs in the balance. Climate change has emerged as one of the most significant threats, triggering range shifts and potential extinctions among our feathered friends. But fear not, for a dedicated team of researchers, armed with the power of citizen science and advanced modeling, has set out to unravel the intricate tapestry of bird species richness in China.
Harnessing the wealth of data provided by the Bird Report, a remarkable citizen science dataset, we embarked on a groundbreaking journey to create a high-resolution map of bird species richness throughout China. Armed with this invaluable resource, we delved deeper, simulating the future range shifts and area changes that 1,042 bird species may experience until the year 2070. To ensure accuracy, we employed three different General Circulation Models and two distinct Representative Concentration Pathways (RCPs), including the RCP 2.6 and RCP 8.5 scenarios.
Our findings painted a vivid picture of the challenges and opportunities that lie ahead. It was revealed that under different scenarios, approximately 241-244 bird species could potentially lose a portion of their distribution ranges. As climate patterns shift, most bird species in China are projected to migrate either towards higher elevations or northward in search of suitable habitats. However, amidst these challenges, a glimmer of hope emerged as 798-801 species were projected to experience range expansions.
Intriguingly, we observed contrasting trends between resident species (n = 516) and migratory birds (n = 526). While both groups would undergo changes, migratory birds were projected to experience more limited range expansion but cover longer distances during their shifts on average. These insights allow us to better understand the complex dynamics at play and tailor conservation strategies accordingly.
Speaking of conservation, we recognized the pressing need to identify and prioritize areas of high species richness for protection. Leveraging the Zonation model, we pinpointed key conservation hotspots that demand immediate attention. Astonishingly, our analysis revealed significant gaps in protected areas in various regions, including northern Xinjiang, southern Tibet, Greater Khingan, Sanjiang Plain, Songnen Plain, northern Bohai Rim, and southeastern coastline areas. These vulnerable areas not only harbor rich bird habitats but also grapple with high human populations and intensive development, making the establishment of sizable protected areas an arduous task.
Faced with these challenges, we must explore inclusive conservation mechanisms that transcend traditional boundaries. It is imperative to consider restoring habitats in urban parks and fostering harmonious coexistence between birds and agricultural activities in farmland areas. By integrating conservation efforts into everyday landscapes, we can create viable solutions that promote biodiversity while accommodating human needs.
The road ahead may be arduous, but armed with knowledge and a deep sense of responsibility, we can navigate the complex terrain of avian conservation. Let us rise to the occasion, working hand in hand to protect and preserve the magnificent bird species that grace our skies. Together, we can bridge the gaps in our protected areas, harmonize development with nature, and secure a future where birds thrive amidst a changing world.
Citation: In their study titled “Shifts in bird ranges and conservation priorities in China under climate change,” Hu et al. (2020) investigated the impact of climate change on bird distributions in China. The research was published in the esteemed journal PLoS ONE, volume 15, issue 10, with the article number e0240225. The study provides valuable insights into the changing patterns of bird species ranges and offers important considerations for conservation efforts in the face of a changing climate. The full article can be accessed at https://doi.org/10.1371/journal.pone.0240225.
Editorial contributions were made by Bhoj Kumar Acharya, affiliated with Sikkim University in India.
The manuscript was received on January 5, 2020, accepted on September 23, 2020, and subsequently published on October 8, 2020.
The copyright for this article, authored by Hu et al., belongs to the year 2020. This is an open access publication, distributed under the Creative Commons Attribution License. This license allows for unrestricted use, distribution, and reproduction in any medium, provided that proper credit is given to the original author and source.
The paper and its Supporting Information files contain all the relevant data, ensuring its availability for reference and analysis.
The research conducted in this study did not receive any specific funding. It is worth noting that Ms. Yiyun Gu is currently employed by Beijing Jinglang Ecology and Techniques Co., LTD. However, it is important to highlight that the employment relationship was established after Ms. Gu completed all the research presented in this paper. The involvement of Beijing Jinglang Ecology and Techniques Co., LTD was limited to Ms. Gu’s current employment status and had no additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of all authors involved in this research are outlined in the ‘author contributions’ section.
In terms of competing interests, it should be noted that Beijing Jinglang Ecology and Techniques Co., LTD is currently the employer of Ms. Yiyun Gu. However, it is important to emphasize that the employment relationship was established after Ms. Gu completed all the research presented in this paper. It is crucial to state that the affiliation with Beijing Jinglang Ecology and Techniques Co., LTD does not impact our adherence to the policies of PLOS ONE regarding the sharing of data and materials.
1. Introduction
In the realm of biodiversity conservation, it is imperative to consider the profound impact of climate change. According to projections, by the year 2100, a staggering 68% of terrestrial ecosystems and 39% of tropical marine environments are expected to witness more than 20% of their constituent species exposed to unprecedented temperatures [1]. This highlights the urgent need to comprehend how climate change influences species’ geographic ranges, including shifts in range area, latitude, and elevation [2–7].
Numerous studies have revealed that climate change has already triggered range changes in various species, such as lizards, corals, and birds [8–10]. These range shifts can significantly increase the risks of species extinction [11–13]. In the context of conservation management, it is crucial to recognize that each species’ range shift can lead to a reevaluation of conservation priority areas [13]. While global-scale studies have provided maps illustrating changes in species distribution ranges under future climate change scenarios, particularly for birds, amphibians, and mammals [14, 15], it is important to acknowledge that these studies suffer from low spatial resolution and rely on polygon range data derived from expert knowledge [16, 17]. As a result, the accuracy of underlying environmental variables is compromised, making it challenging to effectively guide the planning and management of protected areas on a country scale in response to climate change.
Therefore, regional or national-scale studies remain a necessity in the field of biodiversity conservation. Different countries possess unique species compositions, emphasizing the need to delve into specific regional contexts [18]. By conducting focused studies at these scales, we can gain a deeper understanding of how climate change impacts species within each country’s borders. This knowledge is instrumental in guiding conservation planning and management strategies that align with the specific species structures and ecological dynamics of different nations [19].
In conclusion, a comprehensive approach to biodiversity conservation must encompass the profound influence of climate change on species distributions. The ongoing range shifts observed in various species highlight the urgency to reevaluate conservation priority areas. While global-scale studies provide valuable insights, regional or national-scale studies are essential to account for the unique species compositions and ecological contexts of different countries. By conducting such studies, we can effectively guide the planning and management of protected areas, ensuring the long-term preservation of biodiversity in the face of climate change.
As we delve into the intricate relationship between climate change and biodiversity, it becomes evident that different countries are grappling with varying degrees of awareness and action. In Europe, for instance, a comprehensive study has projected a rather alarming scenario: by the year 2099, it is predicted that 431 breeding bird species may only occupy a mere 72-89% of their current distribution range [2]. Such findings emphasize the pressing need for conservation measures that address the far-reaching implications of climate change.
Other nations have also taken steps to assess the responses of their biodiversity to the challenges posed by climate change. Both the United Kingdom and Australia have published national assessment reports that shed light on how their respective species are likely to be affected [18, 19]. These reports play a vital role in informing conservation strategies and facilitating proactive measures to safeguard vulnerable ecosystems.
However, the case of China, one of the world’s 17 mega-diverse countries, presents a unique perspective. While numerous nations have recognized the urgent need to address the future impacts of climate change on biodiversity, China’s National Action Plan on Climate Change, spanning from 2014 to 2020, notably did not explicitly mention the potential consequences for its rich and diverse array of species [20]. This highlights a significant gap in acknowledging and addressing the climate change-biodiversity nexus within the country’s strategic framework.
Given China’s immense biodiversity and ecological importance, it becomes increasingly crucial to include considerations of climate change impacts within national conservation strategies. Understanding how shifting climate patterns may influence species distributions, migration patterns, and overall biodiversity dynamics is pivotal for effective conservation planning and management. By recognizing the interplay between climate change and biodiversity, China can take proactive measures to mitigate the potential risks and devise strategies to protect its invaluable natural heritage.
In conclusion, while some countries have made notable strides in assessing and addressing the impact of climate change on their biodiversity, the case of China highlights the need for greater attention to this critical issue. China’s remarkable biological diversity necessitates a comprehensive understanding of the potential consequences of climate change on its ecosystems. By incorporating climate change impacts into national conservation plans, China can actively contribute to global efforts to protect and preserve biodiversity in the face of a changing climate.
In China, the examination of the future impacts of climate change on species distribution has been limited to a select few species groups. A regional study focusing on the Tibetan Plateau reveals that ungulates may face a substantial range loss of 30% to 50% by 2080, accompanied by an average poleward shift of 300 kilometers [21]. At a national scale, it is projected that 135 endemic or endangered species, including amphibians, reptiles, and mammals, may encounter a habitat loss of 50% before the next century [22]. Another study focusing on 44 migratory waterbird species indicates that the conservation hotspots for these species are likely to shift northward by 2050 [23].
It is worth noting that the data sources and simulation methods employed in the aforementioned studies are not standardized, making direct comparisons challenging. Furthermore, it is important to broaden our focus beyond threatened and endemic species in order to gain a comprehensive understanding of the shifts in diversity and richness patterns [24]. While birds serve as valuable ecological indicators of climate change [25], a comprehensive overview of the entire avian taxon in China is still lacking.
To fully comprehend the potential impacts of climate change on avian species in China, there is a need for comprehensive studies encompassing a wide range of bird species. Such research would provide valuable insights into the ecological responses of avian populations to climate change and facilitate informed conservation strategies. By broadening our understanding of the effects of climate change on avian biodiversity, we can better preserve and protect these important components of China’s natural heritage.
Planning an effective conservation network in the face of future climate change scenarios presents a significant challenge, particularly due to limited budgets and varying extinction risks among different species [26, 27]. To enhance the efficiency of conservation planning, researchers have developed models that utilize multispecies distribution range data. These models provide a convenient yet powerful approach to inform conservation strategies.
One notable example is the Zonation model employed by Pouzols et al., which offers a detailed mapping of the global protected areas required by 2040 [28]. By utilizing this model, researchers can identify priority areas for conservation that account for species distributions and their ecological needs. Similarly, Levy and Ban utilized the Marxan model to incorporate climate change modeling into marine conservation efforts [29]. This integration of climate change data into conservation planning facilitates the identification of key areas for protection and adaptation in marine ecosystems.
These models highlight the feasibility of developing robust assessments and conservation plans based on species range data. By incorporating comprehensive data on species distributions and considering the potential impacts of climate change, conservation efforts can be strategically directed towards areas of utmost importance for preserving biodiversity and enhancing species resilience.
By harnessing the power of these innovative modeling approaches, conservation practitioners and policymakers can make informed decisions and optimize the allocation of resources for conservation actions. These tools provide a valuable framework for designing conservation networks that account for future climate change scenarios, ensuring the effectiveness and long-term success of conservation initiatives.
Range maps obtained from the databases of the IUCN Red List and Birdlife International are commonly utilized as data sources for biogeography research [30]. However, it is important to recognize that these range maps, relying on expert knowledge, may possess inherent biases compared to maps generated from occurrence data using species distribution models [16]. In the realm of conservation planning, citizen science has emerged as a crucial contributor, providing data that can match or even surpass the accuracy of expert-generated data, given proper verification and application procedures [31–34]. Particularly, citizen science projects with time-stamped occurrence data have addressed data gaps and enabled the analysis of climate change effects on species distributions, such as the shifting migration patterns of birds in North America [35].
In the context of China, historical occurrence data are limited and challenging to digitize [36]. However, citizen science methods, such as birdwatching, have yielded a wealth of occurrence data, surpassing those found in scientific papers and encompassing both threatened and rare species [37]. These citizen science datasets have been extensively and independently employed in national-scale studies in China, elucidating the impact of climate change on biogeography and facilitating conservation planning for individual and multiple species [23, 36, 38, 39]. While it is important to acknowledge potential biases in such data, such as observation bias, reporting bias, and geographic bias due to the absence of standardized field protocols [40], these valuable datasets, covering large spatial scales and multiple taxa, can be utilized with appropriate data cleaning and correction procedures [41]. In fact, when modeling range shifts under climate change scenarios, occurrence data derived from birdwatching stands as the sole viable option in China.
The integration of citizen science data, combined with meticulous data management approaches, empowers researchers to gain valuable insights into the impacts of climate change on species distributions in China. These datasets contribute to a more comprehensive understanding of ecological dynamics and aid in the formulation of effective conservation strategies tailored to the unique context of the region.
This paper utilized a dataset of 161,630 localities representing 1,111 bird species in China, collected from the Bird Report, as occurrence data. These data were then employed in the MaxEnt model [42] to generate distribution range maps for each species, both for the present and projected for 2070. Additionally, using these maps and the percentage change in range for each species, we employed the Zonation planning model to map the conservation priorities of birds in China and to examine the corresponding shifts under different climate scenarios. The objective of this study is to investigate the patterns and directions of range shifts for each species, as well as variations in bird hotspots, in order to provide valuable insights for future conservation priorities.
2. Material and methods
2.1 Data sources
We obtained occurrence (presence-only) data for birds from the citizen science project known as Bird Report (http://www.birdreport.cn/). Bird Report stands as the largest nationwide initiative in China, encompassing the submission of birdwatching records since 1998, which include information on over 1,390 bird species (approximately 92% of the bird species found in China) [36]. To ensure the reliability of location and species identification details, each submitted record underwent a thorough review process conducted by experienced reviewers. These reviewers are birdwatchers who have submitted more than 300 bird species and 100 birding reports in China, meeting the eligibility criteria for becoming reviewers.
In our study, we collected a total of 47,000 birding reports (each report potentially containing multiple records) spanning the period from 1998 to 2017. To validate the accuracy of the coordinates associated with each bird record, we cross-referenced the location names provided with the records using the Google Maps API. All occurrence data, including breeding and migratory records, were considered for each species. This approach was adopted due to the extensive scale of the study area, where different subpopulations of many species exhibit distinct reproductive and migratory behaviors. Consequently, it becomes challenging to differentiate breeding and nonbreeding occurrence data solely based on individual birdwatching records.
Birdwatching, while a valuable source of data, may not always adhere to the requirements of systematic sampling [43]. To assess the uniformity of our dataset, we employed the Measuring Geographic Distributions toolset in ArcMap 10.2 (ESRI 2010, Redland, California). Our analysis revealed that 68% of the occurrence data were concentrated within 44% of the country’s land area, as determined by calculating the standard distance concentrated circle. Furthermore, we measured the distance between the median center and the mean center of features, which amounted to 226.2 kilometers. These findings indicate the presence of bias, likely resulting from disparities in species richness, population density, and traffic conditions across different regions.
To ensure accurate and reliable predictions while avoiding overfitting and excessive variability, we applied two criteria during our data selection process. Firstly, we excluded bird species with fewer than five independent localities [44]. Secondly, in cases where localities exhibited high concentration (i.e., the distance between any two localities was less than one arc-minute), we randomly removed excess localities through a process known as presence thinning. This data cleaning procedure has been demonstrated to effectively align with the outcomes of the MaxEnt model, consequently enhancing the overall model performance [36, 39, 45–47]. Ultimately, we utilized a total of 161,004 independent localities to generate modeled distribution range maps for 1,042 bird species. For a detailed breakdown, please refer to S1 Table.
In our study, we took into account all the localities we collected for each bird species to model their total distribution range. It is important to note that we did not differentiate between breeding and nonbreeding sites. This approach was intentional because eastern China plays a significant role in the East Asian—Australasian Flyway (EAAF). Many species, including geese and shorebirds, breed in northern China or Russia, migrate through eastern China [48], or winter in southern China [49].
By considering only breeding ranges, there is a risk of omitting crucial resting and wintering habitats that are vital for the survival of these birds. Neglecting these habitats in conservation planning could pose serious threats to their populations [39, 50, 51]. To provide a comprehensive reference, we made a distinction between the localities and mapped the breeding ranges of migratory bird species in China. This allowed us to compare our findings with similar research results and gain further insights into the distribution patterns and conservation implications (for detailed information, please refer to S1 File & S2 Table).
To accurately predict how species distributions will be affected by future climate change, it is important to carefully select appropriate variables that capture the complex interactions among bioclimatic variables and digital elevation model (DEM) data [52–55]. To address the issue of overfitting, particularly in projections of future scenarios, we conducted a thorough analysis of the 19 bioclimatic variables obtained from the WorldClim 1.4 database [56] (ESRI grids; bio 30s).
To identify highly correlated variables and avoid redundancy, we calculated Pearson’s correlation coefficient for all presence sites and pairwise combinations of these variables. Variables exhibiting a high correlation (|r| > 0.9) were identified as “high correlation pairs” and subsequently excluded from the analysis [57]. After this process, we selected the remaining 12 bioclimatic variables for our modeling purposes. These variables included bio 1–5 (Annual Mean Temperature, Mean Diurnal Range, Isothermality, Temperature Seasonality, and Max Temperature of Warmest Month), bio 8–9 (Mean Temperature of Wettest Quarter and Mean Temperature of Driest Quarter), bio 12 (Annual Precipitation), bio 14–15 (Precipitation of Driest Month and Precipitation Seasonality), and bio 18–19 (Precipitation of Warmest Quarter and Precipitation of Coldest Quarter).
For predicting future bird ranges, we utilized three different General Circulation Models (GCMs) for the year 2070, based on CMIP5 data, under both RCP 2.6 and RCP 8.5 scenarios. The selected GCMs were CCSM4, HadGEM2-ES, and MIROC5, which have demonstrated reliable performance in previous studies involving vertebrates [6, 10, 21, 22]. By utilizing the RCP 2.6 and RCP 8.5 scenarios, representing the lowest and highest emission levels, respectively, we were able to capture the range of potential impacts on bird species distributions [58]. The bioclimatic variables corresponding to these GCMs were downloaded from the WorldClim 1.4 database. Additionally, data for China’s National Nature Reserves (NNRs) were collected from existing research [36]. To ensure consistency, all grid data were rescaled to a resolution of 30 arc-seconds (~1 kilometer) using ArcMap 10.2.
2.2 Distribution range modelling
We employed MaxEnt 3.4.1, a robust software known for its machine learning capabilities in handling presence-only data, to model range maps for our study [42]. This software has been widely used and proven effective, particularly for analyzing citizen science data [59, 60]. To ensure reliable results, we implemented a cross-validation approach with five replicates. Each replicate involved using 80% of the data for training the model and 20% for testing.
For each bird species, we utilized the Cloglog output, which is an updated algorithm in MaxEnt 3.4.1. This algorithm employs a Cloglog transformation, which estimates the probability of presence by utilizing a Bernoulli generalized linear model based on the Poisson distribution [61]. The Cloglog transformation has shown improved model performance compared to the traditional Logistic transform used in previous versions of MaxEnt. It reduces the impact of sample selection bias while maintaining the same area under the receiver operating characteristic curve (AUC) value [42].
In our modeling process, we set the background in MaxEnt to encompass the entire land area of China for all species. After constructing the distribution range maps for the current scenario, we projected the models using different General Circulation Models (GCMs) corresponding to the RCP 2.6 and RCP 8.5 scenarios in 2070. This allowed us to assess the potential changes in species distribution under different future climate scenarios.
To streamline and automate the modeling process, we developed R scripts that facilitated batch processing of the data. These scripts helped ensure efficiency and consistency in the modeling procedure. For further details and the actual code used, please refer to the provided S2 File.
We utilized the average Cloglog output for each bird species and scenario to generate the corresponding species range maps. In order to convert the continuous Cloglog raster outputs into binary maps indicating “presence” or “absence,” we employed a thresholding approach. The maximum test sensitivity plus specificity (MTSS) values for each species were used as the threshold values for this conversion [62, 63]. These binary maps, referred to as predicted distribution range maps (DRMs), provide a clear delineation of the predicted presence and absence areas for each species.
By determining the appropriate threshold based on the MTSS values, we aimed to achieve a balance between sensitivity (the ability to correctly identify true presences) and specificity (the ability to correctly identify true absences) in our predictions. This approach ensures that the predicted DRMs accurately reflect the species’ potential distribution ranges under the given climate scenarios.
The use of MTSS values as thresholds has been widely employed in ecological modeling and has shown effectiveness in generating binary maps that facilitate further analyses and conservation planning. These predicted DRMs serve as valuable tools for understanding the potential spatial patterns of species distributions and can aid in decision-making processes related to biodiversity conservation.
It is important to note that the process of selecting threshold values and converting continuous outputs to binary maps is a crucial step in modeling species distributions, as it directly impacts the interpretation and application of the results. The MTSS approach provides a standardized and objective method for this conversion, enhancing the reliability and comparability of the predicted DRMs across different species and scenarios.
To enhance the model’s performance, we conducted two rounds of simulations. In the first round, we utilized all 1,111 bird species along with their corresponding 161,630 occurrence localities, and included all 13 environmental variables (comprising 12 bioclimatic variables and the digital elevation model) in the current scenario. These data were fed into the MaxEnt model using a five-fold cross-validation approach without any specific settings.
After analyzing the results of the first round, we examined the area covered by each predicted distribution range map (DRM) and assessed the contribution of each variable for each species. Following certain criteria, we excluded 69 species that exhibited low locality density, defined as having fewer than one point per 3° * 3° grid cell (approximately 1 * 10^5 square kilometers) within their respective DRM. Additionally, we removed variables that had no discernible contribution to the model for each species [64]. Subsequently, we proceeded with the second round of simulations, utilizing a refined dataset consisting of 1,042 bird species and their corresponding 161,004 occurrence localities.
This two-round simulation approach allowed us to improve the accuracy and reliability of the model’s predictions. By carefully evaluating the density of occurrence data and the significance of environmental variables, we aimed to exclude species with insufficient data and eliminate variables that did not contribute meaningfully to the modeling process. This enabled us to focus on a more refined dataset in the subsequent simulations, thereby enhancing the robustness of our predictions for the distribution ranges of the selected 1,042 bird species.
In the second round of simulations, we employed distinct environmental variables for each species, which can be found in detail in S1 Table. To address potential sampling bias, we incorporated the background selection method during model training. This method has been demonstrated to be effective in situations where data are limited [46, 65]. For each species, we collected province-level distribution records [66] to serve as the background selection samples in the MaxEnt model. This approach aimed to generate statistically reliable outcomes [67].
The remaining settings in the second round remained consistent with those used in the first round. The code for implementing background selection and variables selection can be found in S2 File.
Upon completion of the second round of simulations, we obtained the mean training AUC value of 0.908±0.055 and the mean test AUC value of 0.861±0.085 for the 1,042 selected bird species (refer to S1 Table). These values serve as indicators of the model’s performance, with higher AUC values suggesting better accuracy in distinguishing between presence and absence of species.
In our study, we conducted an overlay analysis of all 1,042 species’ predicted distribution range maps (DRMs) generated in the second-round simulation. This enabled us to create species richness maps for both the current scenario and the projected 2070 scenario. To visually represent the changes in species richness in relation to the terrain, we employed ArcMap to overlay these richness maps onto the Digital Elevation Model (DEM) and create a comprehensive 3D model.
To assess the directional shifts in species distribution ranges resulting from climate change, we determined the median center point for each range map under different Representative Concentration Pathways (RCPs). The median center point is the location that minimizes the overall Euclidean distance to the distribution range maps. By identifying these points, we were able to calculate displacement vectors that illustrate the magnitude and direction of the distribution range shifts under different climate scenarios.
This approach allows us to gain insights into the potential impacts of climate change on species distribution patterns and identify areas where significant shifts are likely to occur. By analyzing the displacement vectors, we can better understand the overall direction and extent of these range shifts, which have important implications for conservation planning and management strategies.
2.3 Conservation priority modeling
We employed Zonation v4.0 as our chosen planning tool for generating conservation priority maps corresponding to different Representative Concentration Pathways (RCPs). Zonation is renowned for its ability to conduct large-scale, high-resolution spatial conservation prioritization using extensive datasets. It outperforms other planning software by aggregating conservation value across biodiversity features and spatial dimensions, resulting in more effective prioritization outcomes.
To ensure comprehensive coverage of species distribution information, we utilized the original Cloglog output files as species layers within Zonation for each RCP scenario. These layers preserved vital details from the distribution maps. In order to quantify the impact of climate change, we assigned weight values to each species based on the percentage change in their distribution range. Species experiencing significant habitat loss were assigned higher weight values, while those with substantial habitat increases received lower weight values. Additionally, species endemic to China were given an additional weight value of 0.5 to account for their unique conservation value (for specific values, refer to S1 Table).
Taking into consideration the conservation value of each species, we implemented the basic core-area zonation (CAZ) approach for cell removal rule in Zonation. We set the wrap factor to 1,000, enabling the identification of areas with high occurrence levels for rare or highly weighted species. This configuration allowed us to pinpoint locations where conservation efforts should be focused in order to safeguard these species effectively.
We generated two distinct model scenarios for each Representative Concentration Pathway (RCP) in order to address different conservation planning objectives:
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Random ranked scenario: This scenario focused solely on species layers and their corresponding weights. We employed a random ranking approach to determine conservation priorities, considering the distribution maps of species and their respective weight values. This approach allowed for a comprehensive assessment of species importance without specific spatial constraints.
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NNRs masked scenario: In this scenario, our aim was to prioritize conservation efforts outside of National Nature Reserve (NNR) regions. To achieve this, we incorporated an additional NNR layer as a mask layer in Zonation. By applying the NNR layer as a constraint, we focused our conservation planning on areas outside of NNR regions, thereby ensuring that priority areas identified were complementary to existing protected areas.
By employing these two model scenarios, we were able to cater to different conservation planning targets and effectively identify priority areas for conservation actions.
3. Results
3.1 Identifying the species with the range reduction and expansion
In our study of 1,042 bird species, we have observed potential range changes due to climate change by the year 2070 under both RCP 2.6 and RCP 8.5 scenarios. Our findings reveal that approximately 25% of bird species may experience a contraction in their distribution range, while about 75% of species could potentially expand their range (as shown in Table 1).
The histogram of range changes for all bird species (depicted in Fig 1) indicates a general trend of species having a broader range under RCP 8.5 compared to RCP 2.6 (Z = -4.49, P-value = 3.5E-6). However, it is worth noting that although more range may be lost under RCP 8.5 for the 30% of species that experience range reduction, as shown in Table 1.
For species facing the RCP 2.6 scenario, we identified 30 threatened bird species that are projected to experience range reductions, with an average range loss of 19.41%. Conversely, 31 threatened species may undergo an average range expansion of 39.24%. Under RCP 8.5, we found that 30 threatened species are expected to encounter an average range loss of 33.55% (nine of them potentially losing more than half of their range), while 31 threatened species could potentially experience an average range expansion of 98.89%.
Our analysis further reveals that climate change has a more pronounced impact on the range changes of threatened species compared to other species, irrespective of the RCP scenario, as supported by statistical analysis (P-value = 0.019 for RCP 2.6, P-value = 0.046 for RCP 8.5).
Additionally, we classified the studied species into migratory (n = 526) and resident (n = 516) birds, and analyzed their range changes separately (as detailed in Table 1). The results indicate that the impact of climate change on the range of resident species is more significant than that on migratory species, whether under the RCP 2.6 scenario (P-value = 0.0001) or the RCP 8.5 scenario (P-value = 0.026). This suggests that resident species are likely to experience a relatively broad range expansion.
Furthermore, when examining the breeding species among the sample (n = 190), we found that the breeding range may change to a lesser extent compared to the overall distribution range, regardless of the climate scenarios (P-value = 0.005 for RCP 2.6, P-value = 0.003 for RCP 8.5; for more details, refer to S1 Fig).
These findings provide valuable insights into the potential impacts of climate change on bird species’ distribution ranges, with particular emphasis on threatened species, migratory versus resident species, and breeding ranges. Understanding these dynamics is crucial for conservation planning and implementing effective measures to mitigate the adverse effects of climate change on avian populations.
In our study of 1,042 bird species, we have observed potential range changes due to climate change by the year 2070 under both RCP 2.6 and RCP 8.5 scenarios. Our findings reveal that approximately 25% of bird species may experience a contraction in their distribution range, while about 75% of species could potentially expand their range (as shown in Table 1).
The histogram of range changes for all bird species (depicted in Fig 1) indicates a general trend of species having a broader range under RCP 8.5 compared to RCP 2.6 (Z = -4.49, P-value = 3.5E-6). However, it is worth noting that although more range may be lost under RCP 8.5 for the 30% of species that experience range reduction, as shown in Table 1.
For species facing the RCP 2.6 scenario, we identified 30 threatened bird species that are projected to experience range reductions, with an average range loss of 19.41%. Conversely, 31 threatened species may undergo an average range expansion of 39.24%. Under RCP 8.5, we found that 30 threatened species are expected to encounter an average range loss of 33.55% (nine of them potentially losing more than half of their range), while 31 threatened species could potentially experience an average range expansion of 98.89%.
Our analysis further reveals that climate change has a more pronounced impact on the range changes of threatened species compared to other species, irrespective of the RCP scenario, as supported by statistical analysis (P-value = 0.019 for RCP 2.6, P-value = 0.046 for RCP 8.5).
Additionally, we classified the studied species into migratory (n = 526) and resident (n = 516) birds, and analyzed their range changes separately (as detailed in Table 1). The results indicate that the impact of climate change on the range of resident species is more significant than that on migratory species, whether under the RCP 2.6 scenario (P-value = 0.0001) or the RCP 8.5 scenario (P-value = 0.026). This suggests that resident species are likely to experience a relatively broad range expansion.
Furthermore, when examining the breeding species among the sample (n = 190), we found that the breeding range may change to a lesser extent compared to the overall distribution range, regardless of the climate scenarios (P-value = 0.005 for RCP 2.6, P-value = 0.003 for RCP 8.5; for more details, refer to S1 Fig).
These findings provide valuable insights into the potential impacts of climate change on bird species’ distribution ranges, with particular emphasis on threatened species, migratory versus resident species, and breeding ranges. Understanding these dynamics is crucial for conservation planning and implementing effective measures to mitigate the adverse effects of climate change on avian populations.
