Consequences of climatic change for water temperature and brown trout populations in Alpine rivers and streams

Twenty‐five years of extensive water temperature data show regionally coherent warming to have occurred in Alpine rivers and streams at all altitudes, reflecting changes in regional air temperature. Much of this warming occurred abruptly in 1987/1988. For brown trout populations, the warming resulted in an upward shift in thermal habitat that was accelerated by an increase in the incidence of temperature‐dependent Proliferative Kidney Disease at the habitat's lower boundary. Because physical barriers restrict longitudinal migration in mountain regions, an upward habitat shift in effect implies habitat reduction, suggesting the likelihood of an overall population decrease. Extensive brown trout catch data documenting an altitudinally dependent decline indicate that such a climate‐related population decrease has in fact occurred. Our analysis employs a quantitatively defined reference optimum temperature range for brown trout, based on the sinusoidal regression of seasonally varying field data.     

Habitat shifts of endangered species under altered climate conditions: importance of biotic interactions

Predicting changes in potential habitat for endangered species as a result of global warming requires considering more than future climate conditions; it is also necessary to evaluate biotic associations. Most distribution models predicting species responses to climate change include climate variables and occasionally topographic and edaphic parameters, rarely are biotic interactions included. Here, we incorporate biotic interactions into niche models to predict suitable habitat for species under altered climates. We constructed and evaluated niche models for an endangered butterfly and a threatened bird species, both are habitat specialists restricted to semiarid shrublands of southern California. To incorporate their dependency on shrubs, we first developed climate‐based niche models for shrubland vegetation and individual shrub species. We also developed models for the butterfly's larval host plants. Outputs from these models were included in the environmental variable dataset used to create butterfly and bird niche models. For both animal species, abiotic–biotic models outperformed the climate‐only model, with climate‐only models over‐predicting suitable habitat under current climate conditions. We used the climate‐only and abiotic–biotic models to calculate amounts of suitable habitat under altered climates and to evaluate species' sensitivities to climate change. We varied temperature (+0.6, +1.7, and +2.8 °C) and precipitation (50%, 90%, 100%, 110%, and 150%) relative to current climate averages and within ranges predicted by global climate change models. Suitable habitat for each species was reduced at all levels of temperature increase. Both species were sensitive to precipitation changes, particularly increases. Under altered climates, including biotic variables reduced habitat by 68–100% relative to the climate‐only model. To design reserve systems conserving sensitive species under global warming, it is important to consider biotic interactions, particularly for habitat specialists and species with strong dependencies on other species.     

Comparing stream-specific to generalized temperature models to guide salmonid management in a changing climate

Global climate change is predicted to increase air and stream temperatures and alter thermal habitat suitability for growth and survival of coldwater fishes, including brook charr (Salvelinus fontinalis), brown trout (Salmo trutta), and rainbow trout (Oncorhynchus mykiss). In a changing climate, accurate stream temperature modeling is increasingly important for sustainable salmonid management throughout the world. However, finite resource availability (e.g. funding, personnel) drives a tradeoff between thermal model accuracy and efficiency (i.e. cost-effective applicability at management-relevant spatial extents). Using different projected climate change scenarios, we compared the accuracy and efficiency of stream-specific and generalized (i.e. region-specific) temperature models for coldwater salmonids within and outside the State of Michigan, USA, a region with long-term stream temperature data and productive coldwater fisheries. Projected stream temperature warming between 2016 and 2056 ranged from 0.1 to 3.8 °C in groundwater-dominated streams and 0.2–6.8 °C in surface-runoff dominated systems in the State of Michigan. Despite their generally lower accuracy in predicting exact stream temperatures, generalized models accurately projected salmonid thermal habitat suitability in 82% of groundwater-dominated streams, including those with brook charr (80% accuracy), brown trout (89% accuracy), and rainbow trout (75% accuracy). In contrast, generalized models predicted thermal habitat suitability in runoff-dominated streams with much lower accuracy (54%). These results suggest that, amidst climate change and constraints in resource availability, generalized models are appropriate to forecast thermal conditions in groundwater-dominated streams within and outside Michigan and inform regional-level salmonid management strategies that are practical for coldwater fisheries managers, policy makers, and the public. We recommend fisheries professionals reserve resource-intensive stream-specific models for runoff-dominated systems containing high-priority fisheries resources (e.g. trophy individuals, endangered species) that will be directly impacted by projected stream warming.     

Changes in potential habitat of 147 North American breeding bird species in response to redistribution of trees and climate following predicted climate change

Mounting evidence shows that organisms have already begun to respond to global climate change. Advances in our knowledge of how climate shapes species distributional patterns has helped us better understand the response of birds to climate change. However, the distribution of birds across the landscape is also driven by biotic and abiotic components, including habitat characteristics. We therefore developed statistical models of 147 bird species distributions in the eastern United States, using climate, elevation, and the distributions of 39 tree species to predict contemporary bird distributions. We used randomForest, a robust regression‐based decision tree ensemble method to predict contemporary bird distributions. These models were then projected onto three models of climate change under high and low emission scenarios for both climate and the projected change in suitable habitat for the 39 tree species. The resulting bird species models indicated that breeding habitat will decrease by at least 10% for 61–79 species (depending on model and emissions scenario) and increase by at least 10% for 38–52 species in the eastern United States. Alternatively, running the species models using only climate/elevation (omitting tree species), we found that the predictive power of these models was significantly reduced (p<0.001). When these climate/elevation‐only models were projected onto the climate change scenarios, the change in suitable habitat was more extreme in 60% of the species. In the end, the strong associations with vegetation tempers a climate/elevation‐only response to climate change and indicates that refugia of suitable habitat may persist for these bird species in the eastern US, even after the redistribution of tree species. These results suggest the importance of interacting biotic processes and that further fine‐scale research exploring how climate change may disrupt species specific requirements is needed.     

Population status and ecology of the Salmo trutta complex in an Italian river basin under multiple anthropogenic pressures

Salmonids inhabiting Mediterranean rivers are of particular concern for biodiversity conservation, as they are threatened by various stressors, including habitat alterations, overfishing, climate change, and introgressive hybridization with alien species. In the Tiber River basin (Central Italy), genetic introgression phenomena of the native Salmo cettii with the non‐native Salmo trutta hinder the separate analysis of the two species, which are both included in the S. trutta complex. Little is known about the factors currently limiting the trout populations in this area, particularly with respect to climate change. With the intention of filling this gap, the aims of the current study were to (a) quantify changes in the climate and (b) analyze the distribution, status, and ecology of trout populations, in the context of changing abiotic conditions over the last decades. Fish stock assessments were carried out by electrofishing during three census periods (1998–2004, 2005–2011, and 2012–2018) at 129 sites. The trend over time of meteorological parameters provided evidence for increased air temperature and decreased rainfall. Multivariate analysis of trout densities and environmental data highlighted the close direct correlation of trout abundance with water quality, altitude, and current speed. Climate‐induced effects observed over time in the sites where trout were sampled have not yet led to local extinctions or distribution shifts, indicating a marked resilience of trout, probably due to the buffering effect of intrinsic population dynamics. Decreasing body conditions over time and unbalanced age structures support the hypothesis that variations in hydraulic regime and water temperature could overcome these compensatory effects, which may lead to a severe decline in trout populations in the near future. In a climate change context, habitat availability plays a key role in the distribution of cold‐water species, which often do not have the possibility to move upstream to reach their thermal optimum because of water scarcity in the upper river stretches.     

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.     

Probabilistic accounting of uncertainty in forecasts of species distributions under climate change

Forecasts of species distributions under future climates are inherently uncertain, but there have been few attempts to describe this uncertainty comprehensively in a probabilistic manner. We developed a Monte Carlo approach that accounts for uncertainty within generalized linear regression models (parameter uncertainty and residual error), uncertainty among competing models (model uncertainty), and uncertainty in future climate conditions (climate uncertainty) to produce site‐specific frequency distributions of occurrence probabilities across a species' range. We illustrated the method by forecasting suitable habitat for bull trout (Salvelinus confluentus) in the Interior Columbia River Basin, USA, under recent and projected 2040s and 2080s climate conditions. The 95% interval of total suitable habitat under recent conditions was estimated at 30.1–42.5 thousand km; this was predicted to decline to 0.5–7.9 thousand km by the 2080s. Projections for the 2080s showed that the great majority of stream segments would be unsuitable with high certainty, regardless of the climate data set or bull trout model employed. The largest contributor to uncertainty in total suitable habitat was climate uncertainty, followed by parameter uncertainty and model uncertainty. Our approach makes it possible to calculate a full distribution of possible outcomes for a species, and permits ready graphical display of uncertainty for individual locations and of total habitat.     

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.     

Alpine glacial relict species losing out to climate change: The case of the fragmented mountain hare population (Lepus timidus) in the Alps

Alpine and Arctic species are considered to be particularly vulnerable to climate change, which is expected to cause habitat loss, fragmentation and—ultimately—extinction of cold‐adapted species. However, the impact of climate change on glacial relict populations is not well understood, and specific recommendations for adaptive conservation management are lacking. We focused on the mountain hare (Lepus timidus) as a model species and modelled species distribution in combination with patch and landscape‐based connectivity metrics. They were derived from graph‐theory models to quantify changes in species distribution and to estimate the current and future importance of habitat patches for overall population connectivity. Models were calibrated based on 1,046 locations of species presence distributed across three biogeographic regions in the Swiss Alps and extrapolated according to two IPCC scenarios of climate change (RCP 4.5 & 8.5), each represented by three downscaled global climate models. The models predicted an average habitat loss of 35% (22%–55%) by 2100, mainly due to an increase in temperature during the reproductive season. An increase in habitat fragmentation was reflected in a 43% decrease in patch size, a 17% increase in the number of habitat patches and a 34% increase in inter‐patch distance. However, the predicted changes in habitat availability and connectivity varied considerably between biogeographic regions: Whereas the greatest habitat losses with an increase in inter‐patch distance were predicted at the southern and northern edges of the species’ Alpine distribution, the greatest increase in patch number and decrease in patch size is expected in the central Swiss Alps. Finally, both the number of isolated habitat patches and the number of patches crucial for maintaining the habitat network increased under the different variants of climate change. Focusing conservation action on the central Swiss Alps may help mitigate the predicted effects of climate change on population connectivity.     

Assessing the suitable habitat for reintroduction of brown trout (Salmo trutta forma fario) in a lowland river: A modeling approach

Huge efforts have been made during the past decades to improve the water quality and to restore the physical habitat of rivers and streams in western Europe. This has led to an improvement in biological water quality and an increase in fish stocks in many countries. However, several rheophilic fish species such as brown trout are still categorized as vulnerable in lowland streams in Flanders (Belgium). In order to support cost‐efficient restoration programs, habitat suitability modeling can be used. In this study, we developed an ensemble of habitat suitability models using metaheuristic algorithms to explore the importance of a large number of environmental variables, including chemical, physical, and hydromorphological characteristics to determine the suitable habitat for reintroduction of brown trout in the Zwalm River basin (Flanders, Belgium), which is included in the Habitats Directive. Mean stream velocity, water temperature, hiding opportunities, and presence of pools or riffles were identified as the most important variables determining the habitat suitability. Brown trout mainly preferred streams with a relatively high mean reach stream velocity (0.2–1 m/s), a low water temperature (7–15°C), and the presence of pools. The ensemble of models indicated that most of the tributaries and headwaters were suitable for the species. Synthesis and applications. Our results indicate that this modeling approach can be used to support river management, not only for brown trout but also for other species in similar geographical regions. Specifically for the Zwalm River basin, future restoration of the physical habitat, removal of the remaining migration barriers and the development of suitable spawning grounds could promote the successful restoration of brown trout.     

Thermal controls of Yellowstone cutthroat trout and invasive fishes under climate change

We combine large observed data sets and dynamically downscaled climate data to explore historic and future (2050–2069) stream temperature changes over the topographically diverse Greater Yellowstone Ecosystem (elevation range = 824–4017 m). We link future stream temperatures with fish growth models to investigate how changing thermal regimes could influence the future distribution and persistence of native Yellowstone cutthroat trout (YCT) and competing invasive species. We find that stream temperatures during the recent decade (2000–2009) surpass the anomalously warm period of the 1930s. Climate simulations indicate air temperatures will warm by 1 °C to >3 °C over the Greater Yellowstone by mid‐21st century, resulting in concomitant increases in 2050–2069 peak stream temperatures and protracted periods of warming from May to September (MJJAS). Projected changes in thermal regimes during the MJJAS growing season modify the trajectories of daily growth rates at all elevations with pronounced growth during early and late summer. For high‐elevation populations, we find considerable increases in fish body mass attributable both to warming of cold‐water temperatures and to extended growing seasons. During peak July to August warming, mid‐21st century temperatures will cause periods of increased thermal stress, rendering some low‐elevation streams less suitable for YCT. The majority (80%) of sites currently inhabited by YCT, however, display minimal loss (<10%) or positive changes in total body mass by midcentury; we attribute this response to the fact that many low‐elevation populations of YCT have already been extirpated by historical changes in land use and invasions of non‐native species. Our results further suggest that benefits to YCT populations due to warmer stream temperatures at currently cold sites could be offset by the interspecific effects of corresponding growth of sympatric, non‐native species, underscoring the importance of developing climate adaptation strategies that reduce limiting factors such as non‐native species and habitat degradation.     

Landscape resistance mediates native fish species distribution shifts and vulnerability to climate change in riverscapes

A broader understanding of how landscape resistance influences climate change vulnerability for many species is needed, as is an understanding of how barriers to dispersal may impact vulnerability. Freshwater biodiversity is at particular risk, but previous studies have focused on popular cold‐water fishes (e.g., salmon, trout, and char) with relatively large body sizes and mobility. Those fishes may be able to track habitat change more adeptly than less mobile species. Smaller, less mobile fishes are rarely represented in studies demonstrating effects of climate change, but depending on their thermal tolerance, they may be particularly vulnerable to environmental change. By revisiting 280 sites over a 20 year interval throughout a warming riverscape, we described changes in occupancy (i.e., site extirpation and colonization probabilities) and assessed the environmental conditions associated with those changes for four fishes spanning a range of body sizes, thermal and habitat preferences. Two larger‐bodied trout species exhibited small changes in site occupancy, with bull trout experiencing a 9.2% (95% CI = 8.3%–10.1%) reduction, mostly in warmer stream reaches, and westslope cutthroat trout experiencing a nonsignificant 1% increase. The small‐bodied cool water slimy sculpin was originally distributed broadly throughout the network and experienced a 48.0% (95% CI = 42.0%–54.0%) reduction in site occupancy with declines common in warmer stream reaches and areas subject to wildfire disturbances. The small‐bodied comparatively warmer water longnose dace primarily occupied larger streams and increased its occurrence in the lower portions of connected tributaries during the study period. Distribution shifts for sculpin and dace were significantly constrained by barriers, which included anthropogenic water diversions, natural step‐pools and cascades in steeper upstream reaches. Our results suggest that aquatic communities exhibit a range of responses to climate change, and that improving passage and fluvial connectivity will be important climate adaptation tactics for conserving aquatic biodiversity.     

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.     

Predicting impacts of climate change on habitat connectivity of Kalopanax septemlobus in South Korea

Understanding the drivers of habitat distribution patterns and assessing habitat connectivity are crucial for conservation in the face of climate change. In this study, we examined a sparsely distributed tree species, Kalopanax septemlobus (Araliaceae), which has been heavily disturbed by human use in temperate forests of South Korea. We used maximum entropy distribution modeling (MaxEnt) to identify the climatic and topographic factors driving the distribution of the species. Then, we constructed habitat models under current and projected climate conditions for the year 2050 and evaluated changes in the extent and connectivity of the K. septemlobus habitat. Annual mean temperature and terrain slope were the two most important predictors of species distribution. Our models predicted the range shift of K. septemlobus toward higher elevations under medium-low and high emissions scenarios for 2050, with dramatic reductions in suitable habitat (51% and 85%, respectively). In addition, connectivity analysis indicated that climate change is expected to reduce future levels of habitat connectivity. Even under the Representative Construction Pathway (RCP) 4.5 medium-low warming scenario, the projected climate conditions will decrease habitat connectivity by 78%. Overall, suitable habitats for K. septemlobus populations will likely become more isolated depending on the severity of global warming. The approach presented here can be used to efficiently assess species and habitat vulnerability to climate change.     

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.     

Genetic diversity is related to climatic variation and vulnerability in threatened bull trout

Understanding how climatic variation influences ecological and evolutionary processes is crucial for informed conservation decision‐making. Nevertheless, few studies have measured how climatic variation influences genetic diversity within populations or how genetic diversity is distributed across space relative to future climatic stress. Here, we tested whether patterns of genetic diversity (allelic richness) were related to climatic variation and habitat features in 130 bull trout (Salvelinus confluentus) populations from 24 watersheds (i.e., ~4–7th order river subbasins) across the Columbia River Basin, USA. We then determined whether bull trout genetic diversity was related to climate vulnerability at the watershed scale, which we quantified on the basis of exposure to future climatic conditions (projected scenarios for the 2040s) and existing habitat complexity. We found a strong gradient in genetic diversity in bull trout populations across the Columbia River Basin, where populations located in the most upstream headwater areas had the greatest genetic diversity. After accounting for spatial patterns with linear mixed models, allelic richness in bull trout populations was positively related to habitat patch size and complexity, and negatively related to maximum summer temperature and the frequency of winter flooding. These relationships strongly suggest that climatic variation influences evolutionary processes in this threatened species and that genetic diversity will likely decrease due to future climate change. Vulnerability at a watershed scale was negatively correlated with average genetic diversity (r = ?0.77; P < 0.001); watersheds containing populations with lower average genetic diversity generally had the lowest habitat complexity, warmest stream temperatures, and greatest frequency of winter flooding. Together, these findings have important conservation implications for bull trout and other imperiled species. Genetic diversity is already depressed where climatic vulnerability is highest; it will likely erode further in the very places where diversity may be most needed for future persistence.     

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.     

Predicting the distributions of predator (snow leopard) and prey (blue sheep) under climate change in the Himalaya

Future climate change is likely to affect distributions of species, disrupt biotic interactions, and cause spatial incongruity of predator–prey habitats. Understanding the impacts of future climate change on species distribution will help in the formulation of conservation policies to reduce the risks of future biodiversity losses. Using a species distribution modeling approach by MaxEnt, we modeled current and future distributions of snow leopard (Panthera uncia) and its common prey, blue sheep (Pseudois nayaur), and observed the changes in niche overlap in the Nepal Himalaya. Annual mean temperature is the major climatic factor responsible for the snow leopard and blue sheep distributions in the energy‐deficient environments of high altitudes. Currently, about 15.32% and 15.93% area of the Nepal Himalaya are suitable for snow leopard and blue sheep habitats, respectively. The bioclimatic models show that the current suitable habitats of both snow leopard and blue sheep will be reduced under future climate change. The predicted suitable habitat of the snow leopard is decreased when blue sheep habitats is incorporated in the model. Our climate‐only model shows that only 11.64% (17,190 km²) area of Nepal is suitable for the snow leopard under current climate and the suitable habitat reduces to 5,435 km² (reduced by 24.02%) after incorporating the predicted distribution of blue sheep. The predicted distribution of snow leopard reduces by 14.57% in 2030 and by 21.57% in 2050 when the predicted distribution of blue sheep is included as compared to 1.98% reduction in 2030 and 3.80% reduction in 2050 based on the climate‐only model. It is predicted that future climate may alter the predator–prey spatial interaction inducing a lower degree of overlap and a higher degree of mismatch between snow leopard and blue sheep niches. This suggests increased energetic costs of finding preferred prey for snow leopards – a species already facing energetic constraints due to the limited dietary resources in its alpine habitat. Our findings provide valuable information for extension of protected areas in future.     

Linking climate change projections for an Alaskan watershed to future coho salmon production

Climate change is predicted to dramatically change hydrologic processes across Alaska, but estimates of how these impacts will influence specific watersheds and aquatic species are lacking. Here, we linked climate, hydrology, and habitat models within a coho salmon (Oncorhynchus kisutch) population model to assess how projected climate change could affect survival at each freshwater life stage and, in turn, production of coho salmon smolts in three subwatersheds of the Chuitna (Chuit) River watershed, Alaska. Based on future climate scenarios and projections from a three‐dimensional hydrology model, we simulated coho smolt production over a 20‐year span at the end of the century (2080–2100). The direction (i.e., positive vs. negative) and magnitude of changes in smolt production varied substantially by climate scenario and subwatershed. Projected smolt production decreased in all three subwatersheds under the minimum air temperature and maximum precipitation scenario due to elevated peak flows and a resulting 98% reduction in egg‐to‐fry survival. In contrast, the maximum air temperature and minimum precipitation scenario led to an increase in smolt production in all three subwatersheds through an increase in fry survival. Other climate change scenarios led to mixed responses, with projected smolt production increasing and decreasing in different subwatersheds. Our analysis highlights the complexity inherent in predicting climate‐change‐related impacts to salmon populations and demonstrates that population effects may depend on interactions between the relative magnitude of hydrologic and thermal changes and their interactions with features of the local habitat.     

Habitat microclimates drive fine‐scale variation in extreme temperatures

Most multicellular terrestrial organisms experience climate at scales of millimetres to metres, yet most species‐climate associations are analysed at resolutions of kilometres or more. Because individuals experience heterogeneous microclimates in the landscape, species sometimes survive where the average background climate appears unsuitable, and equally may be eliminated from sites within apparently suitable grid cells where microclimatic extremes are intolerable. Local vegetation structure and topography can be important determinants of fine‐resolution microclimate, but a literature search revealed that the vast majority of bioclimate studies do not include fine‐scale habitat information, let alone a representation of how habitat affects microclimate. In this paper, we show that habitat type (grassland, heathland, deciduous woodland) is a major modifier of the temperature extremes experienced by organisms. We recorded differences among these habitats of more than 5°C in monthly temperature maxima and minima, and of 10°C in thermal range, on a par with the level of warming expected for extreme future climate change scenarios. Comparable differences were found in relation to variation in local topography (slope and aspect). Hence, we argue that the microclimatic effects of habitat and topography must be included in studies if we are to obtain sufficiently detailed projections of the ecological impacts of climate change to develop detailed adaptation strategies for the conservation of biodiversity.