Microclimate species distribution models estimate lower levels of climate-related habitat loss for salamanders

Species distribution models (SDMs) largely rely on free-air temperatures at coarse spatial resolutions to predict habitat suitability, potentially overlooking important microhabitat. Integrating microclimate data into SDMs may improve predictions of organismal responses to climate change and support targeting of conservation assets at biologically relevant scales, especially for small, dispersal-limited species vulnerable to climate-change-induced range loss. We integrated microclimate data that account for the buffering effects of forest vegetation into SDMs at a very high spatial resolution (3 m²) for three plethodontid salamander species in Great Smoky Mountains National Park (North Carolina and Tennessee). Microclimate SDMs were used to characterize potential changes to future plethodontid habitat, including habitat suitability and habitat spatial patterns. Additionally, we evaluated spatial discrepancies between predictions of habitat suitability developed with microclimate and coarse-resolution, free-air climate data. Microclimate SDMs indicated substantial losses to plethodontid ranges and highly suitable habitat by mid-century, but at much more conservative levels than coarse-resolution models. Coarse-resolution SDMs generally estimated higher mid-century losses to plethodontid habitat compared to microclimate models and consistently undervalued areas containing highly suitable microhabitat. Furthermore, microclimate SDMs revealed potential areas of future gain in highly suitable habitat within current species’ ranges, which may serve as climatic microrefugia. Taken together, this study highlights the need to develop microclimate SDMs that account for vegetation and its biophysical effects on near-surface temperatures. As microclimate datasets become increasingly available across the world, their integration into correlative and mechanistic SDMs will be imperative for accurately estimating organismal responses to climate change and helping environmental managers tasked with spatially prioritizing conservation assets.     

An ecophysiological perspective on likely giant panda habitat responses to climate change

Threatened and endangered species are more vulnerable to climate change due to small population and specific geographical distribution. Therefore, identifying and incorporating the biological processes underlying a species’ adaptation to its environment are important for determining whether they can persist in situ. Correlative models are widely used to predict species’ distribution changes, but generally fail to capture the buffering capacity of organisms. Giant pandas (Ailuropoda melanoleuca) live in topographically complex mountains and are known to avoid heat stress. Although many studies have found that climate change will lead to severe habitat loss and threaten previous conservation efforts, the mechanisms underlying panda's responses to climate change have not been explored. Here, we present a case study in Daxiangling Mountains, one of the six Mountain Systems that giant panda distributes. We used a mechanistic model, Niche Mapper, to explore what are likely panda habitat response to climate change taking physiological, behavioral and ecological responses into account, through which we map panda's climatic suitable activity area (SAA) for the first time. We combined SAA with bamboo forest distribution to yield highly suitable habitat (HSH) and seasonal suitable habitat (SSH), and their temporal dynamics under climate change were predicted. In general, SAA in the hottest month (July) would reduce 11.7%–52.2% by 2070, which is more moderate than predicted bamboo habitat loss (45.6%–86.9%). Limited by the availability of bamboo and forest, panda's suitable habitat loss increases, and only 15.5%–68.8% of current HSH would remain in 2070. Our method of mechanistic modeling can help to distinguish whether habitat loss is caused by thermal environmental deterioration or food loss under climate change. Furthermore, mechanistic models can produce robust predictions by incorporating ecophysiological feedbacks and minimizing extrapolation into novel environments. We suggest that a mechanistic approach should be incorporated into distribution predictions and conservation planning.     

Mechanistic variables can enhance predictive models of endotherm distributions: the American pika under current,past, and future climates

How climate constrains species’ distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat‐balance model, to convert macroclimate data to pika‐specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8–19% less habitat loss in response to annual temperature increases of ~3–5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect: climate‐imposed restrictions on activity. This more complete understanding is necessary to inform climate adaptation actions, management strategies, and conservation plans.     

Anticipated climate and land‐cover changes reveal refuge areas for Borneo's orang‐utans

Habitat loss and climate change pose a double jeopardy for many threatened taxa, making the identification of optimal habitat for the future a conservation priority. Using a case study of the endangered Bornean orang‐utan, we identify environmental refuges by integrating bioclimatic models with projected deforestation and oil‐palm agriculture suitability from the 1950s to 2080s. We coupled a maximum entropy algorithm with information on habitat needs to predict suitable habitat for the present day and 1950s. We then projected to the 2020s, 2050s and 2080s in models incorporating only land‐cover change, climate change or both processes combined. For future climate, we incorporated projections from four model and emission scenario combinations. For future land cover, we developed spatial deforestation predictions from 10 years of satellite data. Refuges were delineated as suitable forested habitats identified by all models that were also unsuitable for oil palm – a major threat to tropical biodiversity. Our analyses indicate that in 2010 up to 260 000 km² of Borneo was suitable habitat within the core orang‐utan range; an 18–24% reduction since the 1950s. Land‐cover models predicted further decline of 15–30% by the 2080s. Although habitat extent under future climate conditions varied among projections, there was majority consensus, particularly in north‐eastern and western regions. Across projections habitat loss due to climate change alone averaged 63% by 2080, but 74% when also considering land‐cover change. Refuge areas amounted to 2000–42 000 km² depending on thresholds used, with 900–17 000 km² outside the current species range. We demonstrate that efforts to halt deforestation could mediate some orang‐utan habitat loss, but further decline of the most suitable areas is to be expected given projected changes to climate. Protected refuge areas could therefore become increasingly important for ongoing translocation efforts. We present an approach to help identify such areas for highly threatened species given environmental changes expected this century.     

Synergistic effects of climate and land-use change on representation of African bats in priority conservation areas

Bats are considered important bioindicators and deliver key ecosystem services to humans. However, it is not clear how the individual and combined effects of climate change and land-use change will affect their conservation in the future. We used a spatial conservation prioritization framework to determine future shifts in the priority areas for the conservation of 169 bat species under projected climate and land-use change scenarios across Africa. Specifically, we modelled species distribution models under four different climate change scenarios at the 2050 horizon. We used land-use change scenarios within the spatial conservation prioritization framework to assess habitat quality in areas where bats may shift their distributions. Overall, bats’ representation within already existing protected areas in Africa was low (∼5% of their suitable habitat in protected areas which cover ∼7% of Africa). Accounting for future land-use change resulted in the largest shift in spatial priority areas for conservation actions, and species representation within priority areas for conservation actions decreased by ∼9%. A large proportion of spatial conservation priorities will shift from forested areas with little disturbance under present conditions to agricultural areas in the future. Planning land use to reduce impacts on bats in priority areas outside protected areas where bats will be shifting their ranges in the future is crucial to enhance their conservation and maintain the important ecosystem services they provide to humans.     

Hopes and challenges for giant panda conservation under climate change in the Qinling Mountains of China

One way that climate change will impact animal distributions is by altering habitat suitability and habitat fragmentation. Understanding the impacts of climate change on currently threatened species is of immediate importance because complex conservation planning will be required. Here, we mapped changes to the distribution, suitability, and fragmentation of giant panda habitat under climate change and quantified the direction and elevation of habitat shift and fragmentation patterns. These data were used to develop a series of new conservation strategies for the giant panda. Qinling Mountains, Shaanxi, China. Data from the most recent giant panda census, habitat factors, anthropogenic disturbance, climate variables, and climate predictions for the year 2050 (averaged across four general circulation models) were used to project giant panda habitat in Maxent. Differences in habitat patches were compared between now and 2050. While climate change will cause a 9.1% increase in suitable habitat and 9% reduction in subsuitable habitat by 2050, no significant net variation in the proportion of suitable and subsuitable habitat was found. However, a distinct climate change‐induced habitat shift of 11 km eastward by 2050 is predicted firstly. Climate change will reduce the fragmentation of suitable habitat at high elevations and exacerbate the fragmentation of subsuitable habitat below 1,900 m above sea level. Reduced fragmentation at higher elevations and worsening fragmentation at lower elevations have the potential to cause overcrowding of giant pandas at higher altitudes, further exacerbating habitat shortage in the central Qinling Mountains. The habitat shift to the east due to climate change may provide new areas for giant pandas but poses severe challenges for future conservation.     

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.     

气候变化对黄土高原及邻近地区稀有种枯蝉分布的潜在影响(英文)

【目的】未来数十年的气候变化预计会是造成很多物种生境丧失的一个重要因素。对适应能力相对脆弱的地方性物种,预测气候变化对其生境的影响将对生物多样性保护具有重要意义。【方法】本文基于最大熵模型,对珍稀蝉科中国特有种枯蝉Subpsaltria yangi在当前和未来气候条件下的生境适宜度进行了评估。【结果】结果表明,枯蝉主要局限分布于黄土高原及邻近地区。预计至2050年,即使在温和的气候变化情景下,枯蝉的生境面积也会明显减少。影响枯蝉栖息地分布的关键因素为年平均气温、最冷月的最低气温、最冷季的平均气温和最潮湿月份的降水量。枯蝉现存种群栖息地应当受到保护,甘肃天水和陕西延安地区应作为枯蝉分布的核心区予以保护,以应对气候变化对其生境带来的影响。【结论】本研究获得的枯蝉适宜生境分布图可以为该稀有物种的新种群发现、现生种群分布地土地规划管理以及有效的自然保护区设立提供重要信息。     

Managed relocation as an adaptation strategy for mitigating climate change threats to the persistence of an endangered lizard

The distributional ranges of many species are contracting with habitat conversion and climate change. For vertebrates, informed strategies for translocations are an essential option for decisions about their conservation management. The pygmy bluetongue lizard, Tiliqua adelaidensis, is an endangered reptile with a highly restricted distribution, known from only a small number of natural grassland fragments in South Australia. Land‐use changes over the last century have converted perennial native grasslands into croplands, pastures and urban areas, causing substantial contraction of the species' range due to loss of essential habitat. Indeed, the species was thought to be extinct until its rediscovery in 1992. We develop coupled‐models that link habitat suitability with stochastic demographic processes to estimate extinction risk and to explore the efficacy of potential climate adaptation options. These coupled‐models offer improvements over simple bioclimatic envelope models for estimating the impacts of climate change on persistence probability. Applying this coupled‐model approach to T. adelaidensis, we show that: (i) climate‐driven changes will adversely impact the expected minimum abundance of populations and could cause extinction without management intervention, (ii) adding artificial burrows might enhance local population density, however, without targeted translocations this measure has a limited effect on extinction risk, (iii) managed relocations are critical for safeguarding lizard population persistence, as a sole or joint action and (iv) where to source and where to relocate animals in a program of translocations depends on the velocity, extent and nonlinearities in rates of climate‐induced habitat change. These results underscore the need to consider managed relocations as part of any multifaceted plan to compensate the effects of habitat loss or shifting environmental conditions on species with low dispersal capacity. More broadly, we provide the first step towards a more comprehensive framework for integrating extinction risk, managed relocations and climate change information into range‐wide conservation management.     

Effects of Climate Change on Habitat Availability and Configuration for an Endemic Coastal Alpine Bird

North America’s coastal mountains are particularly vulnerable to climate change, yet harbour a number of endemic species. With little room “at the top” to track shifting climate envelopes, alpine species may be especially negatively affected by climate-induced habitat fragmentation. We ask how climate change will affect the total amount, mean patch size, and number of patches of suitable habitat for Vancouver Island White-tailed Ptarmigan (Lagopus leucura saxatilis; VIWTP), a threatened, endemic alpine bird. Using a Random Forest model and a unique dataset consisting of citizen science observations combined with field surveys, we predict the distribution and configuration of potential suitable summer habitat for VIWTP under baseline and future (2020s, 2050s, and 2080s) climates using three general circulation models and two greenhouse gas scenarios. VIWTP summer habitat is predicted to decline by an average of 25%, 44%, and 56% by the 2020s, 2050s, and 2080s, respectively, under the low greenhouse gas scenario and 27%, 59%, and 74% under the high scenario. Habitat patches are predicted to become fragmented, with a 52–79% reduction in mean patch size. The average elevation of suitable habitat patches is expected to increase, reflecting a loss of patches at lower elevations. Thus ptarmigan are in danger of being “squeezed off the mountain”, as their remaining suitable habitat will be increasingly confined to mountaintops in the center of the island. The extent to which ptarmigan will be able to persist in increasingly fragmented habitat is unclear. Much will depend on their ability to move throughout a more heterogeneous landscape, utilize smaller breeding areas, and survive increasingly variable climate extremes. Our results emphasize the importance of continued monitoring and protection for high elevation specialist species, and suggest that White-tailed Ptarmigan should be considered an indicator species for alpine ecosystems in the face of climate change.     

Coupled Downscaled Climate Models and Ecophysiological Metrics Forecast Habitat Compression for an Endangered Estuarine Fish

Climate change is driving rapid changes in environmental conditions and affecting population and species’ persistence across spatial and temporal scales. Integrating climate change assessments into biological resource management, such as conserving endangered species, is a substantial challenge, partly due to a mismatch between global climate forecasts and local or regional conservation planning. Here, we demonstrate how outputs of global climate change models can be downscaled to the watershed scale, and then coupled with ecophysiological metrics to assess climate change effects on organisms of conservation concern. We employed models to estimate future water temperatures (2010–2099) under several climate change scenarios within the large heterogeneous San Francisco Estuary. We then assessed the warming effects on the endangered, endemic Delta Smelt, Hypomesus transpacificus, by integrating localized projected water temperatures with thermal sensitivity metrics (tolerance, spawning and maturation windows, and sublethal stress thresholds) across life stages. Lethal temperatures occurred under several scenarios, but sublethal effects resulting from chronic stressful temperatures were more common across the estuary (median >60 days above threshold for >50% locations by the end of the century). Behavioral avoidance of such stressful temperatures would make a large portion of the potential range of Delta Smelt unavailable during the summer and fall. Since Delta Smelt are not likely to migrate to other estuaries, these changes are likely to result in substantial habitat compression. Additionally, the Delta Smelt maturation window was shortened by 18–85 days, revealing cumulative effects of stressful summer and fall temperatures with early initiation of spring spawning that may negatively impact fitness. Our findings highlight the value of integrating sublethal thresholds, life history, and in situ thermal heterogeneity into global change impact assessments. As downscaled climate models are becoming widely available, we conclude that similar assessments at management-relevant scales will improve the scientific basis for resource management decisions.     

Cetacean range and climate in the eastern North Atlantic: future predictions and implications for conservation

There is increasing evidence that the distributions of a large number of species are shifting with global climate change as they track changing surface temperatures that define their thermal niche. Modelling efforts to predict species distributions under future climates have increased with concern about the overall impact of these distribution shifts on species ecology, and especially where barriers to dispersal exist. Here we apply a bio‐climatic envelope modelling technique to investigate the impacts of climate change on the geographic range of ten cetacean species in the eastern North Atlantic and to assess how such modelling can be used to inform conservation and management. The modelling process integrates elements of a species' habitat and thermal niche, and employs “hindcasting” of historical distribution changes in order to verify the accuracy of the modelled relationship between temperature and species range. If this ability is not verified, there is a risk that inappropriate or inaccurate models will be used to make future predictions of species distributions. Of the ten species investigated, we found that while the models for nine could successfully explain current spatial distribution, only four had a good ability to predict distribution changes over time in response to changes in water temperature. Applied to future climate scenarios, the four species‐specific models with good predictive abilities indicated range expansion in one species and range contraction in three others, including the potential loss of up to 80% of suitable white‐beaked dolphin habitat. Model predictions allow identification of affected areas and the likely time‐scales over which impacts will occur. Thus, this work provides important information on both our ability to predict how individual species will respond to future climate change and the applicability of predictive distribution models as a tool to help construct viable conservation and management strategies.     

Response of the endangered tropical dry forests to climate change and the role of Mexican Protected Areas for their conservation

Assuming that co‐distributed species are exposed to similar environmental conditions, ecological niche models (ENMs) of bird and plant species inhabiting tropical dry forests (TDFs) in Mexico were developed to evaluate future projections of their distribution for the years 2050 and 2070. We used ENM‐based predictions and climatic data for two Global Climate Models, considering two Representative Concentration Pathway scenarios (RCP4.5/RCP8.5). We also evaluated the effects of habitat loss and the importance of the Mexican system of protected areas (PAs) on the projected models for a more detailed prediction of TDFs and to identify hot spots that require conservation actions. We identified four major distributional areas: the main one located along the Pacific Coast (from Sonora to Chiapas, including the Cape and Bajío regions, and the Balsas river basin), and three isolated areas: the Yucatán peninsula, central Veracruz, and southern Tamaulipas. When considering the effect of habitat loss, a significant reduction (~61%) of the TDFs predicted area occurred, whereas climate‐change models suggested (in comparison with the present distribution model) an increase in area of 3.0–10.0% and 3.0–9.0% for 2050 and 2070, respectively. In future scenarios, TDFs will occupy areas above its current average elevational distribution that are outside of its present geographical range. Our findings show that TDFs may persist in Mexican territory until the middle of the XXI century; however, the challenges about long‐term conservation are partially addressed (only 7% unaffected within the Mexican network of PAs) with the current Mexican PAs network. Based on our ENM approach, we suggest that a combination of models of species inhabiting present TDFs and taking into account change scenarios represent an invaluable tool to create new PAs and ecological corridors, as a response to the increasing levels of habitat destruction and the effects of climate change on this ecosystem.     

Vulnerability of mires under climate change: implications for nature conservation and climate change adaptation

Wetlands in general and mires in particular belong to the most important terrestrial carbon stocks globally. Mires (i.e. bogs, transition bogs and fens) are assumed to be especially vulnerable to climate change because they depend on specific, namely cool and humid, climatic conditions. In this paper, we use distribution data of the nine mire types to be found in Austria and habitat distribution models for four IPCC scenarios to evaluate climate change induced risks for mire ecosystems within the 21st century. We found that climatic factors substantially contribute to explain the current distribution of all nine Austrian mire ecosystem types. Summer temperature proved to be the most important predictor for the majority of mire ecosystems. Precipitation—mostly spring and summer precipitation sums—was influential for some mire ecosystem types which depend partly or entirely on ground water supply (e.g. fens). We found severe climate change induced risks for all mire ecosystems, with rain-fed bog ecosystems being most threatened. Differences between scenarios are moderate for the mid-21st century, but become more pronounced towards the end of the 21st century, with near total loss of climate space projected for some ecosystem types (bogs, quagmires) under severe climate change. Our results imply that even under minimum expected, i.e. inevitable climate change, climatic risks for mires in Austria will be considerable. Nevertheless, the pronounced differences in projected habitat loss between moderate and severe climate change scenarios indicate that limiting future warming will likely contribute to enhance long-term survival of mire ecosystems, and to reduce future greenhouse gas emissions from decomposing peat. Effectively stopping and reversing the deterioration of mire ecosystems caused by conventional threats can be regarded as a contribution to climate change mitigation. Because hydrologically intact mires are more resilient to climatic changes, this would also maintain the nature conservation value of mires, and help to reduce the severe climatic risks to which most Austrian mire ecosystems may be exposed in the 2nd half of the 21st century according to IPCC scenarios.     

Modeling plant species distributions under future climates: how fine scale do climate projections need to be?

Recent studies suggest that species distribution models (SDMs) based on fine‐scale climate data may provide markedly different estimates of climate‐change impacts than coarse‐scale models. However, these studies disagree in their conclusions of how scale influences projected species distributions. In rugged terrain, coarse‐scale climate grids may not capture topographically controlled climate variation at the scale that constitutes microhabitat or refugia for some species. Although finer scale data are therefore considered to better reflect climatic conditions experienced by species, there have been few formal analyses of how modeled distributions differ with scale. We modeled distributions for 52 plant species endemic to the California Floristic Province of different life forms and range sizes under recent and future climate across a 2000‐fold range of spatial scales (0.008–16 km²). We produced unique current and future climate datasets by separately downscaling 4 km climate models to three finer resolutions based on 800, 270, and 90 m digital elevation models and deriving bioclimatic predictors from them. As climate‐data resolution became coarser, SDMs predicted larger habitat area with diminishing spatial congruence between fine‐ and coarse‐scale predictions. These trends were most pronounced at the coarsest resolutions and depended on climate scenario and species' range size. On average, SDMs projected onto 4 km climate data predicted 42% more stable habitat (the amount of spatial overlap between predicted current and future climatically suitable habitat) compared with 800 m data. We found only modest agreement between areas predicted to be stable by 90 m models generalized to 4 km grids compared with areas classified as stable based on 4 km models, suggesting that some climate refugia captured at finer scales may be missed using coarser scale data. These differences in projected locations of habitat change may have more serious implications than net habitat area when predictive maps form the basis of conservation decision making.     

Implications of Climate Change for Bird Conservation in the Southwestern U.S. under Three Alternative Futures

Future expected changes in climate and human activity threaten many riparian habitats, particularly in the southwestern U.S. Using Maximum Entropy (MaxEnt3.3.3) modeling, we characterized habitat relationships and generated spatial predictions of habitat suitability for the Lucy’s warbler (Oreothlypis luciae), the Southwestern willow flycatcher (Empidonax traillii extimus) and the Western yellow-billed cuckoo (Coccyzus americanus). Our goal was to provide site- and species-specific information that can be used by managers to identify areas for habitat conservation and/or restoration along the Rio Grande in New Mexico. We created models of suitable habitat for each species based on collection and survey samples and climate, biophysical, and vegetation data. We projected habitat suitability under future climates by applying these models to conditions generated from three climate models for 2030, 2060 and 2090. By comparing current and future distributions, we identified how habitats are likely to change as a result of changing climate and the consequences of those changes for these bird species. We also examined whether land ownership of high value sites shifts under changing climate conditions. Habitat suitability models performed well. Biophysical characteristics were more important that climate conditions for predicting habitat suitability with distance to water being the single most important predictor. Climate, though less important, was still influential and led to declines of suitable habitat of more than 60% by 2090. For all species, suitable habitat tended to shrink over time within the study area leaving a few core areas of high importance. Overall, climate changes will increase habitat fragmentation and reduce breeding habitat patch size. The best strategy for conserving bird species within the Rio Grande will include measures to maintain and restore critical habitat refugia. This study provides an example of a presence-only habitat model that can be used to inform the management of species at intermediate scales.     

Interactions between climate and habitat loss effects on biodiversity: a systematic review and meta‐analysis

Climate change and habitat loss are both key threatening processes driving the global loss in biodiversity. Yet little is known about their synergistic effects on biological populations due to the complexity underlying both processes. If the combined effects of habitat loss and climate change are greater than the effects of each threat individually, current conservation management strategies may be inefficient and at worst ineffective. Therefore, there is a pressing need to identify whether interacting effects between climate change and habitat loss exist and, if so, quantify the magnitude of their impact. In this article, we present a meta‐analysis of studies that quantify the effect of habitat loss on biological populations and examine whether the magnitude of these effects depends on current climatic conditions and historical rates of climate change. We examined 1319 papers on habitat loss and fragmentation, identified from the past 20 years, representing a range of taxa, landscapes, land‐uses, geographic locations and climatic conditions. We find that current climate and climate change are important factors determining the negative effects of habitat loss on species density and/or diversity. The most important determinant of habitat loss and fragmentation effects, averaged across species and geographic regions, was current maximum temperature, with mean precipitation change over the last 100 years of secondary importance. Habitat loss and fragmentation effects were greatest in areas with high maximum temperatures. Conversely, they were lowest in areas where average rainfall has increased over time. To our knowledge, this is the first study to conduct a global terrestrial analysis of existing data to quantify and test for interacting effects between current climate, climatic change and habitat loss on biological populations. Understanding the synergistic effects between climate change and other threatening processes has critical implications for our ability to support and incorporate climate change adaptation measures into policy development and management response.     

Alpine marmot (Marmota marmota) distribution evolution under climate change: The use of species distribution models at a local scale in the western Pyrenees massif (France)

The Alpine marmot (Marmota marmota) is a social mammal living in mountainous grassland areas and has the particularity to hibernate in winter. Recent studies on a population in the French Alps found that climate change is affecting Alpine marmot population dynamics and might impact their overall distribution in the future. Using Species Distribution Models (SDMs), the effect of climate change on Alpine marmot's future distribution was investigated at a local scale, in the western part of the Pyrenean massif (New-Aquitaine region, France). This scale was chosen as an appropriate action scale for the conservation strategy for the species. Three climatic scenarios were used (RCP 2.6, RCP 4.5, and RCP 8.5) over three future 30-year periods (2021–2050, 2040–2070, 2071–2100) to predict the short- to long-term potential distribution of the target species. The results are consistent with naturalistic knowledge of the species´ ecological needs in terms of variable importance and response type. Mean maximum temperature in winter, standard-deviation of daily temperature in winter, along with the median rainfall amount in summer were the three most important climatic variables. Predictions under the two most pessimistic climate scenarios showed potential large habitat loss. In the long term, for RCP 4.5, an estimated habitat loss of 18% was predicted. In the case of RCP 8.5, a higher impact was predicted, with a 54% habitat loss. Our results show that high impact due to climate change can be expected at a long term. In addition, if winter climatic conditions are important for marmot survival through hibernation, drought in summer might be one of the drivers of future population dynamic and distribution. Our findings can be applied for other species living in grassland mountainous environments and for which access to food resources in summer is essential, facilitating the conservation of target areas.     

Large-Scale Range Collapse of Hawaiian Forest Birds under Climate Change and the Need 21st Century Conservation Options

Hawaiian forest birds serve as an ideal group to explore the extent of climate change impacts on at-risk species. Avian malaria constrains many remaining Hawaiian forest bird species to high elevations where temperatures are too cool for malaria’s life cycle and its principal mosquito vector. The impact of climate change on Hawaiian forest birds has been a recent focus of Hawaiian conservation biology, and has centered on the links between climate and avian malaria. To elucidate the differential impacts of projected climate shifts on species with known varying niches, disease resistance and tolerance, we use a comprehensive database of species sightings, regional climate projections and ensemble distribution models to project distribution shifts for all Hawaiian forest bird species. We illustrate that, under a likely scenario of continued disease-driven distribution limitation, all 10 species with highly reliable models (mostly narrow-ranged, single-island endemics) are expected to lose >50% of their range by 2100. Of those, three are expected to lose all range and three others are expected to lose >90% of their range. Projected range loss was smaller for several of the more widespread species; however improved data and models are necessary to refine future projections. Like other at-risk species, Hawaiian forest birds have specific habitat requirements that limit the possibility of range expansion for most species, as projected expansion is frequently in areas where forest habitat is presently not available (such as recent lava flows). Given the large projected range losses for all species, protecting high elevation forest alone is not an adequate long-term strategy for many species under climate change. We describe the types of additional conservation actions practitioners will likely need to consider, while providing results to help with such considerations.     

Conservation of Chinese Theaceae species under future climate and land use changes

Aim

Climate and land use changes are two major pervasive and growing global causes of rapid changes in the distribution patterns of biodiversity, challenging the future effectiveness of protected areas (PAs), which were mainly designed based on a static view of biodiversity. Therefore, evaluating the effectiveness of protected areas for protecting the species threatened by climate and land use change is critical for future biodiversity conservation.

Location

China.

Methods

Here, using distributions of 200 Chinese Theaceae species and ensemble species distribution models, we identified species threatened by future climate and land use change (i.e. species with predicted loss of suitable habitat ≥30%) under scenarios incorporating climate change, land use change and dispersal. We then estimate the richness distribution patterns of threatened species and identify priority conservation areas and conservation gaps of the current PA network.

Results

Our results suggest that 36.30%–51.85% of Theaceae species will be threatened by future climate and land use conditions and that although the threatened species are mainly distributed at low latitudes in China under both current and future periods, the mean richness of the threatened species per grid cell will decline by 0.826–3.188 species by the 2070s. Moreover, we found that these priority conservation areas are highly fragmented and that the current PA network only covers 14.21%–20.87% of the ‘areas worth exploring’ and 6.91%–7.91% of the ‘areas worth attention’.

Main Conclusions

Our findings highlight the necessity of establishing new protected areas and ecological corridors in priority conservation areas to protect the threatened species. Moreover, our findings also highlight the importance of taking into consideration the potential threatened species under future climate and land use conditions when designating priority areas for biodiversity conservation.