Theme section on “Mesophotic Coral Ecosystems: Characterization, Ecology, and Management”

Mesophotic coral ecosystems (MCEs) are characterized by the presence of light-dependent corals and associated communities that are typically found at depths ranging from 30 to 40 m and extending to over 150 m in tropical and subtropical regions. The dominant communities providing structural habitat in the mesophotic zone can be comprised of coral, sponge, and algal species. Because working in this depth range is constrained by traditional SCUBA limits, less is known about corals and associated organisms there compared to shallower coral communities. Following the first-ever gathering of international scientists to review and discuss existing knowledge of MCEs, this issue focuses on the ecological characterization, geomorphology, and concept of MCEs as refugia for shallow-water populations. The review and research papers comprising this special issue reflect the current scientific understanding of these ecosystems and the underlying mechanisms that regulate them, as well as potential resource management implications. It is important to understand the value and role of mesophotic coral ecosystems in tropical and subtropical regions as these areas face increasing environmental change and human impacts     

Community ecology of mesophotic coral reef ecosystems

Given the global degradation of shallow-water coral reef ecosystems resulting from anthropogenic activities, mesophotic coral reef ecosystems (MCEs) are gaining attention because they are generally considered a de facto refuge for shallow-water species. Despite their inferred importance, MCEs remain one of the most understudied reef habitats, and basic information on the taxonomic composition, depth range, habitat preferences, and abundance and distribution of MCE taxa is scarce. The processes that structure these communities are virtually unknown. Here, we provide a review of what is known about MCEs community ecology and outline essential gaps in our knowledge of these deeper water coral reef ecosystems. The primary findings of this review are as follows: (1) many dominant shallow-water species are absent from MCEs; (2) compared to shallow reefs, herbivores are relatively scarce, perhaps due to limited habitat complexity at depth; (3) changes in the dominant photosynthetic taxa with depth suggest adaptation and specialization to depth; (4) evidence regarding the importance of heterotrophy for zooxanthellate corals at depth is conflicting and inconclusive; and (5) decreased light with depth, but not temperature, appears to be the primary factor limiting the depth of MCEs. The majority of research done to date has been performed in the Caribbean, where some generalization can be made about the community structure and distribution of MCEs. The larger and more diverse Indo-Pacific remains largely unexplored with no apparent generalizations from the few sites that have been comparatively well studied. For MCEs, large gaps in knowledge remain on fundamental aspects of ecology. Advanced technologies must be harnessed and logistical challenges overcome to close this knowledge gap and empower resource managers to make informed decisions on conserving shallow-water and mesophotic coral reef ecosystems.     

Species Distribution Modelling predicts habitat suitability and reduction of suitable habitat under future climatic scenario for Sclerophrys perreti: A critically endangered Nigerian endemic toad

Sclerophrys perreti is a critically endangered Nigerian native frog currently imperilled by human activities. A better understanding of its potential distribution and habitat suitability will aid in conservation; however, such knowledge is limited for S. perreti. Herein, we used a species distribution model (SDM) approach with all known occurrence data (n = 22) from our field surveys and primary literature, and environmental variable predictors (19 bioclimatic variables, elevation and land cover) to elucidate habitat suitability and impact of climate change on this species. The SDM showed that temperature and precipitation were the predictors of habitat suitability for S. perreti with precipitation seasonality as the strongest predictor of habitat suitability. The following variable also had a significant effect on habitat suitability: temperature seasonality, temperature annual range, precipitation of driest month, mean temperature of wettest quarter and isothermality. The model predicted current suitable habitat for S. perreti covering an area of 1,115 km². However, this habitat is predicted to experience 60% reduction by 2050 owing to changes in temperature and precipitation. SDM also showed that suitable habitat exists in south-eastern range of the inselberg with predicted low impact of climate change compared to other ranges. Therefore, this study recommends improved conservation measures through collaborations and stakeholder's meeting with local farmers for the management and protection of S. perreti.     

Theme section on mesophotic coral ecosystems: advances in knowledge and future perspectives

The Second International Mesophotic Coral Ecosystems (MCEs) workshop was held in Eilat, Israel, October 26–31, 2014. Here we provide an account of: (1) advances in our knowledge of MCE ecology, including the central question of the potential vertical connectivity between MCEs and shallow-water reefs (SWRs), and that of the validity of the deep-reef refugia hypothesis (DRRH); (2) the contribution of the 2014 MCE workshop to the central question presented in (1), as well as its contribution to novel MCE studies on corals, sponges, fish, and crabs; and (3) gaps, priorities, and recommendations for future research stemming from the workshop. Despite their close proximity to well-studied SWRs, and the growing evidence of their importance, our scientific knowledge of MCEs is still in its infancy. During the last five years, we have witnessed an ever-increasing scientific interest in MCEs, expressed in the exponential increase in the number of publications studying this unique environment. The emerging consensus is that lower MCE benthic assemblages represent unique communities, either of separate species or genetically distinct individuals within species, and any significant support for the DRRH will be limited to upper MCEs. Determining the health and stability of MCEs, their biodiversity, and the degree of genetic connectivity among SWRs and MCEs, will ultimately indicate the ability of MCEs to contribute to the resilience of SWRs and help to guide future management and conservation strategies. MCEs deserve therefore management consideration in their own right. With the technological advancements taking place in recent years that facilitate access to MCEs, the prospects for exciting and innovative discoveries resulting from MCE research, spanning a wide variety of fields, are immense.     

The impact of climate change and potential distribution of the endangered white winged wood duck (Asarcornis scutulata, 1882) in Indian eastern Himalaya

The White-Winged Wood duck (Asarcornis scutulata) is an endangered forest wetland bird currently on the verge of extinction due to an array of anthropogenic pressures. It has been reported that global climate change could affect the distribution of many bird species globally. Therefore, an understanding the potential distribution of the White-Winged Wood duck in future climate scenarios could facilitate the creation of immediate conservation plans and the mitigation of subsequent threats. This is the first ever study on the distribution of White-Winged Wood Duck (WWWD) where Representative Concentration Pathway (RCP) 8.5 scenario was used to forecast the distribution of the WWWD in the Indian Eastern Himalayan region in the 2050s and 2070s. The study revealed that 1.87 % of the total area of IEH has the high potential distribution of WWWD. The state of Assam alone includes 1.68 % of the highly potential habitat in the region. It was predicted that 436.61 km² of highly potential habitat would be lost by 2070. Changes in the annual temperature range, precipitation in the wettest months (June to September), and precipitation decrease in the warmest quarter (October to December) would result in the loss of highly potential habitats. Under the influence of climate change, the habitat of WWWD in the eastern part of the region is likely to shift towards the western part. It was found that there will be a decline in potential habitat in the Indian states of Arunachal Pradesh, Assam, Nagaland, and Tripura located in the IEH under future climate scenarios. The potential of areas located at the Bhutan and Assam border would increase for supporting WWWD as this species' requires the average annual precipitation about 1000–1200 mm. However, the simultaneous anthropogenic activity would further destroy potential habitats in the future. The current study has provided baseline data on the potential distribution of WWWD in the IEH region for immediate conservation management plans.     

Identifying climate refugia and its potential impact on Tibetan brown bear (Ursus arctos pruinosus) in Sanjiangyuan National Park,China

Climate change has direct impacts on wildlife and future biodiversity protection efforts. Vulnerability assessment and habitat connectivity analyses are necessary for drafting effective conservation strategies for threatened species such as the Tibetan brown bear (Ursus arctos pruinosus). We used the maximum entropy (MaxEnt) model to assess the current (1950–2000) and future (2041–2060) habitat suitability by combining bioclimatic and environmental variables, and identified potential climate refugia for Tibetan brown bears in Sanjiangyuan National Park, China. Next, we selected Circuit model to simulate potential migration paths based on current and future climatically suitable habitat. Results indicate a total area of potential suitable habitat under the current climate scenario of approximately 31,649.46 km², of which 28,778.29 km² would be unsuitable by the 2050s. Potentially suitable habitat under the future climate scenario was projected to cover an area of 23,738.6 km². Climate refugia occupied 2,871.17 km², primarily in the midwestern and northeastern regions of Yangtze River Zone, as well as the northern region of Yellow River Zone. The altitude of climate refugia ranged from 4,307 to 5,524 m, with 52.93% lying at altitudes between 4,300 and 4,600 m. Refugia were mainly distributed on bare rock, alpine steppe, and alpine meadow. Corridors linking areas of potentially suitable brown bear habitat and a substantial portion of paths with low‐resistance value were distributed in climate refugia. We recommend various actions to ameliorate the impact of climate change on brown bears, such as protecting climatically suitable habitat, establishing habitat corridors, restructuring conservation areas, and strengthening monitoring efforts.     

Predicting potential distribution and identifying priority areas for conservation of the lowland tapir (Tapirus terrestris) in Peruvian Amazon

A key conservation biology tool is the information on the geographic distribution of species as well as the variables driving those patterns. Here, we used maximum entropy modeling, MaxEnt, to model the total potential distribution of Tapirus terrestris, classified as “Vulnerable” on the IUCN Red List of Threatened Species. In this study, we recorded 117 occurrence records and considered 18 environmental variables. The total potential distribution area covers 96,055.6 km², meaning 12.3 % of the territory of the Peruvian Amazon, with “high potential” habitat covering 3,891.36 km², “moderate potential” habitat covering 22,849.5 km², and “low potential” habitat covering 69,314.7 km². Natural Protected Areas (NPAs) shelter 32.2 % (30,966.2 km²) of the total potential distribution area of the species, being the Bahuaja Sonene and Manu National Parks, the NPAs with the largest total potential distribution, 8,220.2 km² and 7,619.7 km² respectively. Eventually, 67.8 % (65,089.4 km²) of the total potential distribution were identified without any type of protection category by SINANPE and its complementary categories; therefore, we consider this area as a priority for the conservation of T. terrestris in Peru.     

The interaction between island geomorphology and environmental parameters drives Adélie penguin breeding phenology on neighboring islands near Palmer Station,Antarctica

Despite many studies on Adélie penguin breeding phenology, understanding the drivers of clutch initiation dates (CIDs, egg 1 lay date) is limited or lacks consensus. Here, we investigated Adélie penguin CIDs over 25 years (1991–2016) on two neighboring islands, Torgersen and Humble (<1 km apart), in a rapidly warming region near Palmer Station, Antarctica. We found that sea ice was the primary large‐scale driver of CIDs and precipitation was a secondary small‐scale driver that fine‐tunes CID to island‐specific nesting habitat geomorphology. In general, CIDs were earlier (later) when the spring sea ice retreat was earlier (later) and when the preceding annual ice season was shorter (longer). Island‐specific effects related to precipitation and island geomorphology caused greater snow accumulation and delayed CIDs by ~2 days on Torgersen compared to Humble Island. When CIDs on the islands were similar, conditions were mild with less snow across breeding sites. At Torgersen Island, the negative relationship between CID and breeding success highlights detrimental effects of delayed breeding and/or snow on penguin fitness. Past phenological studies reported a relationship between air temperature and CID, assumed to be related to precipitation, but we found air temperature was more highly correlated to sea ice, revealing a misinterpretation of temperature effects. Finally, contrasting trends in CIDs based on temporal shifts in regional sea ice patterns revealed trends toward earlier CIDs (4–6 day advance) from 1979 to 2009 as the annual ice season shortened, and later CIDs (7–10 day delay) from 2010 to 2016 as the annual ice season lengthened. Adélie penguins tracked environmental conditions with flexible breeding phenology, but their life history remains vulnerable to subpolar weather conditions that can delay CIDs and decrease breeding success, especially on landscapes where geomorphology facilitates snow accumulation.     

Predicting the potential distribution of a riparian invasive plant: the effects of changing climate,flood regimes and land‐use patterns

Climate change is likely to affect plants in multiple ways, but predicting the consequences for habitat suitability requires a process‐based understanding of the interactions. This is at odds with existing approaches that are mostly phenomenological and largely restricted to predicting the effects of changing temperature and rainfall on species distributions at a coarse spatial scale. We examine the multiple effects of climate change, including predicting the effects of altered flood regimes and land‐use change, on the potential distribution of the invasive riparian species lippia (Phyla canescens) across a 26 000 km² catchment in eastern Australia. We determined habitat suitability for lippia by combining process‐understanding of experts and an eco‐physiological bioclimatic model within a Bayesian belief network. The bioclimatic model predicted substantial changes in habitat suitability by 2070 under both a wetter (Echam Mark 3) and drier (Hadley Centre Mark 2) climate change scenario, but only the more likely drier scenario reduced suitability in our test region. The area suitable for lippia was predicted to increase at least threefold with increased flooding under a wet climate scenario, although this would be partially negated by land‐use change to cultivation. The region would become unsuitable to lippia with reduced flooding under a drier scenario irrespective of land‐use changes, although existing populations would persist if grazing persisted. Independent field validation verified model structure and parameterization, and therefore the opinion of experts, but identified site‐scale deficiencies in the available environmental data layers. Model predictions suggest that adaptation options for managing lippia will be greatly reduced under a drying scenario, but identify potential restoration opportunities under either scenario. This work highlights the value of predictive models that incorporate process‐understanding at sufficiently fine spatial resolution to capture the important processes underpinning habitat suitability.     

Habitat assessment of Marco Polo sheep (Ovis ammon polii) in Eastern Tajikistan: Modeling the effects of climate change

Identifying the factors predicting the high‐elevation suitable habitats of Central Asian argali wild sheep and how these suitable habitats are affected by the changing climate regimes could help address conservation and management efforts and identify future critical habitat for the species in eastern Tajikistan. This study used environmental niche models (ENMs) to map and compare potential present and future distributions of suitable environmental conditions for Marco Polo argali. Argali occurrence points were collected during field surveys conducted from 2009 to 2016. Our models showed that terrain ruggedness and annual mean temperature had strong correlations on argali distribution. We then used two greenhouse gas concentration trajectories (RCP 4.5 and RCP 8.5) for two future time periods (2050 and 2070) to model the impacts of climate change on Marco Polo argali habitat. Results indicated a decline of suitable habitat with majority of losses observed at lower elevations (3,300–4,300 m). Models that considered all variables (climatic and nonclimatic) predicted losses of present suitable areas of 60.6% (6,928 km²) and 63.2% (7,219 km²) by 2050 and 2070, respectively. Results also showed averaged habitat gains of 46.2% (6,106 km²) at much higher elevations (4,500–6,900 m) and that elevational shifts of habitat use could occur in the future. Our results could provide information for conservation planning for this near threatened species in the region.     

Identifying refugia and corridors under climate change conditions for the Sichuan snub‐nosed monkey (Rhinopithecus roxellana) in Hubei Province,China

Using a case study of an isolated management unit of Sichuan snub‐nosed monkey (Rhinopithecus roxellana), we assess the extent that climate change will impact the species’ habitat distribution in the current period and projected into the 2050s. We identify refugia that could maintain the population under climate change and determine dispersal paths for movement of the population to future suitable habitats. Hubei Province, China. We identified climate refugia and potential movements by integrating bioclimatic models with circuit theory and least‐cost model for the current period (1960–1990) and the 2050s (2041–2060). We coupled a maximum entropy algorithm to predict suitable habitat for the current and projected future periods. Suitable habitat areas that were identified during both time periods and that also satisfied home range and dispersal distance conditions were delineated as refugia. We mapped potential movements measured as current flow and linked current and future habitats using least‐cost corridors. Our results indicate up to 1,119 km² of currently suitable habitat within the study range. Based on our projections, a habitat loss of 67.2% due to climate change may occur by the 2050s, resulting in a reduced suitable habitat area of 406 km² and very little new habitat. The refugia areas amounted to 286 km² and were located in Shennongjia National Park and Badong Natural Reserve. Several connecting corridors between the current and future habitats, which are important for potential movements, were identified. Our assessment of the species predicted a trajectory of habitat loss following anticipated future climate change. We believe conservation efforts should focus on refugia and corridors when planning for future species management. This study will assist conservationists in determining high‐priority regions for effective maintenance of the endangered population under climate change and will encourage increased habitat connectivity.     

Forecasting the future suitable growth areas and constructing ecological corridors for the vulnerable species Ephedra sinica in China

Ephedra sinica is a rare and vulnerable species in China, and the habitat of Ephedra sinica is seriously threatened (by climate change and human activities). Predicting the suitable growth areas and constructing ecological corridors for Ephedra sinica in China will help to protect it scientifically. Based on 306 valid distribution records and 13 selected environmental factors, the maximum entropy (MaxEnt) model was used to simulate the potential current habitat zones and future (2050 and 2070) habitat zones of Ephedra sinica under four climate change scenarios. The minimum cumulative resistance (MCR) model was applied to extract important ecological corridors of Ephedra sinica. The results indicate that: (1) Under the current environment, the total area of the suitable habitat for Ephedra sinica in China is 42.24 × 10⁵ km², mainly distributed in Northwest China and North China. (2) Suitable area increases as the RCP rises. The center of mass of the habitat zone moved northward from Shaanxi Province to Ordos City in Inner Mongolia Autonomous Region. (3) Of the 13 environmental factors selected, the primary factor was elevation (20.8 %), followed by wettest month precipitation (18.2 %) and temperature seasonality (15.2 %). (4) Built 19 ecological corridors, with a total corridor length of 430.2 km, including seven long-distance passages and 12 short-distance corridors. All corridors are far from the artificial surface, mostly near high-altitude areas. The 19 ecological corridors constructed using the MCR model will also provide considerable importance for the survival of Ephedra sinica on a longer time scale in the future.     

Potential distribution of Notopterygium incisum Ting ex H. T. Chang and its predicted responses to climate change based on a comprehensive habitat suitability model

Notopterygium incisum Ting ex H. T. Chang is a rare and endangered traditional Chinese medicinal plant. In this research, we built a comprehensive habitat suitability (CHS) model to analyze the potential suitable habitat distribution of this species in the present and future in China. First, using nine different algorithms, we built an ensemble model to explore the possible impacts of climate change on the habitat distribution of this species. Then, based on this model, we built a CHS model to further identify the distribution characteristics of N. incisum‐suitable habitats in three time periods (current, 2050s, and 2070s) while considering the effects of soil and vegetation conditions. The results indicated that the current suitable habitat for N. incisum covers approximately 83.76 × 10³ km², and these locations were concentrated in the Tibet Autonomous Region, Gansu Province, Qinghai Province, and Sichuan Province. In the future, the areas of suitable habitat for N. incisum would significantly decrease and would be 69.53 × 10³ km² and 60.21 × 10³ km² in the 2050s and 2070s, respectively. However, the area of marginally suitable habitat would remain relatively stable. This study provides a more reliable and comprehensive method for modelling the current and future distributions of N. incisum, and it provides valuable insights for highlighting priority areas for medicinal plant conservation and resource utilization.     

Habitat suitability of Gymnocladus assamicus - A critically endangered plant of Arunachal Pradesh,India using machine learning and statistical modeling

The present study sought to identify the potential distribution range of critically endangered Gymnocladus assamicus in Arunachal Pradesh based on published data and field collection. We used the Maxent model to estimate the range of distribution and the result was then compared with three other models, i.e., the Generalized Linear Model (GLM), the Bioclim and the Random Forest model to assess the species' habitat suitability. A total of 23 different environmental variables were used, including bioclimatic ones, monthly minimum and maximum temperature, monthly precipitation and elevation data. The Maxent output listed 12 variables explaining 99.9% variation in the model. In comparison, Maxent showed the maximum region under habitat suitability criteria (1884.48 km²), followed by Random Forest (70.73 km²) and Bioclim (11.62 km²) model. Except for the Maxent model, suitable habitats predicted by other models are highly restricted within and across the study species' current distribution range. The average model prediction shows an expanded distribution range for the species up to Tawang which is the closest district of currently known distribution of the species in the state. Thus, the present study recognizes the importance of the geographic range of G. assamicus, a critically endangered species with very limited spatial distribution range and also provides some specific details to explore possible habitats for the species in new areas of potential occurrence in Arunachal Pradesh, India.     

Challenges of predicting the potential distribution of a slow-spreading invader: a habitat suitability map for an invasive riparian tree

Understanding the potential spread of invasive species is essential for land managers to prevent their establishment and restore impacted habitat. Habitat suitability modeling provides a tool for researchers and managers to understand the potential extent of invasive species spread. Our goal was to use habitat suitability modeling to map potential habitat of the riparian plant invader, Russian olive (Elaeagnus angustifolia). Russian olive has invaded riparian habitat across North America and is continuing to expand its range. We compiled 11 disparate datasets for Russian olive presence locations (n = 1,051 points and 139 polygons) in the western US and used Maximum entropy (Maxent) modeling to develop two habitat suitability maps for Russian olive in the western United States: one with coarse-scale water data and one with fine-scale water data. Our models were able to accurately predict current suitable Russian olive habitat (Coarse model: training AUC = 0.938, test AUC = 0.907; Fine model: training AUC = 0.923, test AUC = 0.885). Distance to water was the most important predictor for Russian olive presence in our coarse-scale water model, but it was only the fifth most important variable in the fine-scale model, suggesting that when water bodies are considered on a fine scale, Russian olive does not necessarily rely on water. Our model predicted that Russian olive has suitable habitat further west from its current distribution, expanding into the west coast and central North America. Our methodology proves useful for identifying potential future areas of invasion. Model results may be influenced by locations of cultivated individuals and sampling bias. Further study is needed to examine the potential for Russian olive to invade beyond its current range. Habitat suitability modeling provides an essential tool for enhancing our understanding of invasive species spread.     

Population genetic structure and demographic history of the lone star tick,Amblyomma americanum (Ixodida: Ixodidae): New evidence supporting old records

Range expansions are a potential outcome of changes in habitat suitability, which commonly result as a consequence of climate change. Hypotheses on such changes in the geographic distribution of a certain species can be evaluated using population genetic structure and demography. In this study we explore the population genetic structure, genetic variability, demographic history of, and habitat suitability for Amblyomma americanum, a North American tick species that is a known vector of several pathogenic microorganisms. We used a double digestion restriction site‐associated DNA sequencing technique (dd‐RAD seq) and discovered 8,181 independent single nucleotide polymorphisms (SNPs) in 189 ticks from across the geographic range of the species. Genetic diversity was low, particularly when considering the broad geographic range of this species. The edge populations were less diverse than populations belonging to the historic range, possibly indicative of a range expansion, but this hypothesis was not statistically supported by a test based on genetic data. Nonetheless, moderate levels of population structure and substructure were detected between geographic regions. For New England, demographic and species distribution models support a scenario where A. americanum was present in more northern locations in the past, underwent a bottleneck, and subsequently recovered. These results are consistent with a hypothesis that this species is re‐establishing in this area, rather than one focused on range expansion from the south. This hypothesis is consistent with old records describing the presence of A. americanum in the northeastern US in the early colonial period.     

Prediction of habitat suitability,connectivity, and corridors in the future to conserve roe deer (Capreolus capreolus) as a locally endangered species in northern Iran

Roe deer is a protected species in Iran as its population and distribution in the country have considerably declined. Roe deer are threatened by several factors such as habitat fragmentation and road mortality, so studying their distribution and movement through the increasing habitat destruction and fragmentation is necessary. This will become increasingly important because climate change will transform the species’ future habitat and connectivity patterns. We evaluated the roe deer’s potential distribution range in northern Iran and, for the first time, developed connectivity models and designed corridors for the present and future to make better conservation plans. We collected 91 points indicating the presence of roe deer in the study region. After developing ensemble models using six species distribution algorithms, we defined high-ranked habitat cores using the concept of landscape suitability prioritization. From these, we designed connectivity and corridors in two time-frames with the help of least-cost paths and circuit theories to predict the potential movement throughout the study area. We estimated that the overall core habitats for roe deer in the present and future periods are, respectively, around 1200 km² and 2600 km², corresponding to 2 and 4 percent of the whole area. This suggests that the habitat core will expand in the future as a result of climate change. Similarly, the connectivity among the cores will strengthen. We also conclude that the temperature-driven and anthropogenic variables significantly affect the distribution of roe deer in northern Iran. It is necessary that conservationists and managers consider the designed corridors in the present study while planning conservation strategies.     

Near term climate projections for invasive species distributions

Climate change and invasive species pose important conservation issues separately, and should be examined together. We used existing long term climate datasets for the US to project potential climate change into the future at a finer spatial and temporal resolution than the climate change scenarios generally available. These fine scale projections, along with new species distribution modeling techniques to forecast the potential extent of invasive species, can provide useful information to aide conservation and invasive species management efforts. We created habitat suitability maps for Pueraria montana (kudzu) under current climatic conditions and potential average conditions up to 30 years in the future. We examined how the potential distribution of this species will be affected by changing climate, and the management implications associated with these changes. Our models indicated that P. montana may increase its distribution particularly in the Northeast with climate change and may decrease in other areas.     

气候变化对丹顶鹤秋季迁徙路线潜在生境适宜性的影响

目前全球变暖趋势的加剧对丹顶鹤等大型濒危水禽的栖息地造成了严重的威胁。由于监测方法和技术手段的限制,丹顶鹤在迁徙路线上潜在生境的分布范围尚不清楚,气候变化对丹顶鹤迁徙路线生境适宜性的影响机理有待进一步研究。基于138个丹顶鹤样本分布信息和19种环境变量数据,利用 BIOMOD2 软件包构建了丹顶鹤潜在生境评价的组合模型,对丹顶鹤在亚洲东部秋季迁徙路线上的生境适宜性进行数值模拟,并预测SSP1.2-6气候背景下2021-2040年、2041-2060年、2061-2080年、2081-2100年四个不同阶段的丹顶鹤潜在生境范围的变化趋势。研究结果表明:与单模型的模拟结果相比,集成9种单模型的BIOMOD2组合模型预测精度更高。集成模型的重要性分析表明,气温日较差是丹顶鹤生境适宜性变化的最重要的影响因子。受气候变化的影响2021-2040年、2041-2060年、2061-2080年、2081-2100年丹顶鹤潜在生境的面积将分别减少到2.60×10⁵km²、2.58×10⁵km²、2.75×10⁵km²、2.56×10⁵km²,迁徙路线上胶东半岛和环渤海地区适栖生境面积减少的最为显著。本研究对于迁徙路线上珍稀水禽潜在适宜生境的模拟及全球变化背景下珍稀水禽栖息地的保育和修复具有重要意义。