Habitat availability and gene flow influence diverging local population trajectories under scenarios of climate change: a place‐based approach

Ecological niche theory holds that species distributions are shaped by a large and complex suite of interacting factors. Species distribution models (SDMs) are increasingly used to describe species’ niches and predict the effects of future environmental change, including climate change. Currently, SDMs often fail to capture the complexity of species’ niches, resulting in predictions that are generally limited to climate‐occupancy interactions. Here, we explore the potential impact of climate change on the American pika using a replicated place‐based approach that incorporates climate, gene flow, habitat configuration, and microhabitat complexity into SDMs. Using contemporary presence–absence data from occupancy surveys, genetic data to infer connectivity between habitat patches, and 21 environmental niche variables, we built separate SDMs for pika populations inhabiting eight US National Park Service units representing the habitat and climatic breadth of the species across the western United States. We then predicted occurrence probability under current (1981–2010) and three future time periods (out to 2100). Occurrence probabilities and the relative importance of predictor variables varied widely among study areas, revealing important local‐scale differences in the realized niche of the American pika. This variation resulted in diverse and – in some cases – highly divergent future potential occupancy patterns for pikas, ranging from complete extirpation in some study areas to stable occupancy patterns in others. Habitat composition and connectivity, which are rarely incorporated in SDM projections, were influential in predicting pika occupancy in all study areas and frequently outranked climate variables. Our findings illustrate the importance of a place‐based approach to species distribution modeling that includes fine‐scale factors when assessing current and future climate impacts on species’ distributions, especially when predictions are intended to manage and conserve species of concern within individual protected areas.     

Climate,competition and connectivity affect future migration and ranges of European trees

Aim Species ranges have adapted during the Holocene to altering climate conditions, but it remains unclear if species will be able to keep pace with recent and future climate change. The goal of our study is to assess the influence of changing macroclimate, competition and habitat connectivity on the migration rates of 14 tree species. We also compare the projections of range shifts from species distribution models (SDMs) that incorporate realistic migration rates with classical models that assume no or unlimited migration. Location Europe. Methods We calibrated SDMs with species abundance data from 5768 forest plots from ICP Forest Level 1 in relation to climate, topography, soil and land‐use data to predict current and future tree distributions. To predict future species ranges from these models, we applied three migration scenarios: no migration, unlimited migration and realistic migration. The migration rates for the SDMs incorporating realistic migration were estimated according to macroclimate, inter‐specific competition and habitat connectivity from simulation experiments with a spatially explicit process model (TreeMig). From these relationships, we then developed a migration cost surface to constrain the predicted distributions of the SDMs. Results The distributions of early‐successional species during the 21st century predicted by SDMs that incorporate realistic migration matched quite well with the unlimited migration assumption (mean migration rate over Europe for A1fi/GRAS climate and land‐use change scenario 156.7 ± 79.1 m year^?1 and for B1/SEDG 164.3 ± 84.2 m year^?1). The predicted distributions of mid‐ to late‐successional species matched better with the no migration assumption (A1fi/GRAS, 15.2 ± 24.5 m year^?1 and B1/SEDG, 16.0 ± 25.6 m year^?1). Inter‐specific competition, which is higher under favourable growing conditions, reduced range shift velocity more than did adverse macroclimatic conditions (i.e. very cold or dry climate). Habitat fragmentation also led to considerable time lags in range shifts. Main conclusions Migration rates depend on species traits, competition, spatial habitat configuration and climatic conditions. As a result, re‐adjustments of species ranges to climate and land‐use change are complex and very individualistic, yet still quite predictable. Early‐successional species track climate change almost instantaneously while mid‐ to late‐ successional species were predicted to migrate very slowly.     

Climate connectivity of the bobcat in the Great Lakes region

The Great Lakes and the St. Lawrence River are imposing barriers for wildlife, and the additive effect of urban and agricultural development that dominates the lower Great Lakes region likely further reduces functional connectivity for many terrestrial species. As the climate warms, species will need to track climate across these barriers. It is important therefore to investigate land cover and bioclimatic hypotheses that may explain the northward expansion of species through the Great Lakes. We investigated the functional connectivity of a vagile generalist, the bobcat, as a representative generalist forest species common to the region. We genotyped tissue samples collected across the region at 14 microsatellite loci and compared different landscape hypotheses that might explain the observed gene flow or functional connectivity. We found that the Great Lakes and the additive influence of forest stands with either low or high canopy cover and deep lake‐effect snow have disrupted gene flow, whereas intermediate forest cover has facilitated gene flow. Functional connectivity in southern Ontario is relatively low and was limited in part by the low amount of forest cover. Pathways across the Great Lakes were through the Niagara region and through the Lower Peninsula of Michigan over the Straits of Mackinac and the St. Marys River. These pathways are important routes for bobcat range expansion north of the Great Lakes and are also likely pathways that many other mobile habitat generalists must navigate to track the changing climate. The extent to which species can navigate these routes will be important for determining the future biodiversity of areas north of the Great Lakes.     

Exploring the spatiotemporal dynamics of habitat suitability to improve conservation management of a vulnerable plant species

Ongoing declines in biodiversity caused by global environmental changes call for adaptive conservation management, including the assessment of habitat suitability spatiotemporal dynamics potentially affecting species persistence. Remote sensing (RS) provides a wide-range of satellite-based environmental variables that can be fed into species distribution models (SDMs) to investigate species-environment relations and forecast responses to change. We address the spatiotemporal dynamics of species’ habitat suitability at the landscape level by combining multi-temporal RS data with SDMs for analysing inter-annual habitat suitability dynamics. We implemented this framework with a vulnerable plant species (Veronica micrantha), by combining SDMs with a time-series of RS-based metrics of vegetation functioning related to primary productivity, seasonality, phenology and actual evapotranspiration. Besides RS variables, predictors related to landscape structure, soils and wildfires were ranked and combined through multi-model inference (MMI). To assess recent dynamics, a habitat suitability time-series was generated through model hindcasting. MMI highlighted the strong predictive ability of RS variables related to primary productivity and water availability for explaining the test-species distribution, along with soil, wildfire regime and landscape composition. The habitat suitability time-series revealed the effects of short-term land cover changes and inter-annual variability in climatic conditions. Multi-temporal SDMs further improved predictions, benefiting from RS time-series. Overall, results emphasize the integration of landscape attributes related to function, composition and spatial configuration for improving the explanation of ecological patterns. Moreover, coupling SDMs with RS functional metrics may provide early-warnings of future environmental changes potentially impacting habitat suitability. Applications discussed include the improvement of biodiversity monitoring and conservation strategies.     

Beyond species distribution modeling: A landscape genetics approach to investigating range shifts under future climate change

Understanding how biodiversity will respond to future climate change is a major conservation and societal challenge. Climate change is predicted to force many species to shift their ranges in pursuit of suitable conditions. This study aims to use landscape genetics, the study of the effects of environmental heterogeneity on the spatial distribution of genetic variation, as a predictive tool to assess how species will shift their ranges to track climatic changes and inform conservation measures that will facilitate movement. The approach is based on three steps: 1) using species distribution models (SDMs) to predict suitable ranges under future climate change, 2) using the landscape genetics framework to identify landscape variables that impede or facilitate movement, and 3) extrapolating the effect of landscape connectivity on range shifts in response to future climate change. I show how this approach can be implemented using the publicly available genetic dataset of the grey long-eared bat, Plecotus austriacus, in the Iberian Peninsula. Forest cover gradient was the main landscape variable affecting genetic connectivity between colonies. Forest availability is likely to limit future range shifts in response to climate change, primarily over the central plateau, but important range shift pathways have been identified along the eastern and western coasts. I provide outputs that can be directly used by conservation managers and review the viability of the approach. Using landscape genetics as a predictive tool in combination with SDMs enables the identification of potential pathways, whose loss can affect the ability of species to shift their range into future climatically suitable areas, and the appropriate conservation management measures to increase landscape connectivity and facilitate movement.     

Extension of the Geographical Range of White-browed Titi Monkeys (<Emphasis Type="BoldItalic">Callicebus discolor</Emphasis>) and Evidence for Sympatry with San Martin Titi Monkeys (<Emphasis Type="BoldItalic">Callicebus oenanthe</Emphasis>)

White-browed titi monkeys (Callicebus discolor) have one of the largest distribution ranges of all titi monkey species, occurring from central Peru to southern Colombia. During a long-term study on the distribution of titi monkeys and other primates in Peru, we conducted extensive surveys in the San Martin Department of northeastern Peru. We encountered Callicebus discolor at the left bank of the Huallaga River, where the species most probably lives in sympatry with endemic San Martin titi monkeys (Callicebus oenanthe). Our study reveals an important extension of its formerly known distribution range. Massive deforestation activities in the region make studies on the habitat preferences of both species difficult, as most titi monkeys are confined to the remaining small remnants of the original forest. Urgent conservation measures are necessary to preserve the last lowland forests of San Martin.     

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.     

Testing projected wild bee distributions in agricultural habitats: predictive power depends on species traits and habitat type

Species distribution models (SDM) are increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. However, these models are rarely validated with independently collected data and it is unclear whether SDM performance is maintained across distinct habitats and for species with different functional traits. Highly mobile species, such as bees, can be particularly challenging to model. Here, we use independent sets of occurrence data collected systematically in several agricultural habitats to test how the predictive performance of SDMs for wild bee species depends on species traits, habitat type, and sampling technique. We used a species distribution modeling approach parametrized for the Netherlands, with presence records from 1990 to 2010 for 193 Dutch wild bees. For each species, we built a Maxent model based on 13 climate and landscape variables. We tested the predictive performance of the SDMs with independent datasets collected from orchards and arable fields across the Netherlands from 2010 to 2013, using transect surveys or pan traps. Model predictive performance depended on species traits and habitat type. Occurrence of bee species specialized in habitat and diet was better predicted than generalist bees. Predictions of habitat suitability were also more precise for habitats that are temporally more stable (orchards) than for habitats that suffer regular alterations (arable), particularly for small, solitary bees. As a conservation tool, SDMs are best suited to modeling rarer, specialist species than more generalist and will work best in long‐term stable habitats. The variability of complex, short‐term habitats is difficult to capture in such models and historical land use generally has low thematic resolution. To improve SDMs’ usefulness, models require explanatory variables and collection data that include detailed landscape characteristics, for example, variability of crops and flower availability. Additionally, testing SDMs with field surveys should involve multiple collection techniques.     

Contracting montane cloud forests: a case study of the Andean alder (Alnus acuminata) and associated fungi in the Yungas

Alnus acuminata is a keystone tree species in the Yungas forests and host to a wide range of fungal symbionts. While species distribution models (SDMs) are routinely used for plants and animals to study the effects of climate change on montane forest communities, employing SDMs in fungi has been hindered by the lack of data on their geographic distribution. The well‐known host specificity and common biogeographic history of A. acuminata and associated ectomycorrhizal (ECM) fungi provide an exceptional opportunity to model the potential habitat for this symbiotic assemblage and to predict possible climate‐driven changes in the future. We (1) modeled the present and future distributions of suitable habitats for A. acuminata; (2) characterized fungal communities in different altitudinal zones of the Yungas using DNA metabarcoding of soil and root samples; and (3) selected fungi that were significant indicators of Alnus. Fungal communities were strongly structured according to altitudinal forest types and the presence of Alnus. Fungal indicators of Alnus, particularly ECM and root endophytic fungi, were also detected in Alnus roots. Current and future (year 2050) habitat models developed for A. acuminata predict a 25–50 percent decrease in suitable area and an upslope shift of the suitable habitat by ca. 184–380 m, depending on the climate change scenario. Although A. acuminata is considered to be an effective disperser, recent studies suggest that Andean grasslands are remarkably resistant to forest invasion, and future range contraction for A. acuminata may be even more pronounced than predicted by our models.     

Effects of landscape matrix on population connectivity of an arboreal mammal,Petaurus breviceps

Ongoing habitat loss and fragmentation is considered a threat to biodiversity as it can create small, isolated populations that are at increased risk of extinction. Tree‐dependent species are predicted to be highly sensitive to forest and woodland loss and fragmentation, but few studies have tested the influence of different types of landscape matrix on gene flow and population structure of arboreal species. Here, we examine the effects of landscape matrix on population structure of the sugar glider (Petaurus breviceps) in a fragmented landscape in southeastern South Australia. We collected 250 individuals across 12 native Eucalyptus forest remnants surrounded by cleared agricultural land or exotic Pinus radiata plantations and a large continuous eucalypt forest. Fifteen microsatellite loci were genotyped and analyzed to infer levels of population differentiation and dispersal. Genetic differentiation among most forest patches was evident. We found evidence for female philopatry and restricted dispersal distances for females relative to males, suggesting there is male‐biased dispersal. Among the environmental variables, spatial variables including geographic location, minimum distance to neighboring patch, and degree of isolation were the most important in explaining genetic variation. The permeability of a cleared agricultural matrix to dispersing gliders was significantly higher than that of a pine matrix, with the gliders dispersing shorter distances across the latter. Our results added to previous findings for other species of restricted dispersal and connectivity due to habitat fragmentation in the same region, providing valuable information for the development of strategies to improve the connectivity of populations in the future.     

Effects of environment,habitat configuration and forest continuity on the distribution of forest plant species

In present day European landscapes many forest plant species are restricted to isolated remnants of a formerly more or less continuous forest cover. The two major objectives of this study were (1) to determine the relative importance of habitat quality (mainly in terms of soil parameters), habitat configuration (patch size and isolation) and habitat continuity for the distribution of herbaceous forest plant species in a highly fragmented landscape and (2) to examine if groups of species with different habitat requirements are affected differently. Deciduous forest patches in northwestern Germany were surveyed for the presence of a large set of forest species. For each patch, habitat quality, configuration and continuity were determined. Data were analysed by Redundancy Analysis with variation partitioning for effects on total species composition and multivariate logistic regression for effects on individual species, for two different data sets (base‐rich and base‐poor forest patches). Overall, we found strong effects of habitat quality (particularly of soil pH, water content and topographic heterogeneity in the base‐rich forest patches; and of calcium content and disturbance in the base‐poor patches), but only relatively weak effects of habitat configuration and habitat continuity. However, a number of species were positively affected by patch area and negatively affected by patch isolation. Furthermore, the relative importance of habitat configuration tended to be higher for species predominantly growing in closed forests compared to species occurring both in the forest and in the open landscape.     

The fate of European breeding birds under climate,land‐use and dispersal scenarios

Many species have already shifted their distributions in response to recent climate change. Here, we aimed at predicting the future breeding distributions of European birds under climate, land‐use, and dispersal scenarios. We predicted current and future distributions of 409 species within an ensemble forecast framework using seven species distribution models (SDMs), five climate scenarios and three emission and land‐use scenarios. We then compared results from SDMs using climate‐only variables, habitat‐only variables or both climate and habitat variables. In order to account for a species’ dispersal abilities, we used natal dispersal estimates and developed a probabilistic method that produced a dispersal scenario intermediate between the null and full dispersal scenarios generally considered in such studies. We then compared results from all scenarios in terms of future predicted range changes, range shifts, and variations in species richness. Modeling accuracy was better with climate‐only variables than with habitat‐only variables, and better with both climate and habitat variables. Habitat models predicted smaller range shifts and smaller variations in range size and species richness than climate models. Using both climate and habitat variables, it was predicted that the range of 71% of the species would decrease by 2050, with a 335 km median shift. Predicted variations in species richness showed large decreases in the southern regions of Europe, as well as increases, mainly in Scandinavia and northern Russia. The partial dispersal scenario was significantly different from the full dispersal scenario for 25% of the species, resulting in the local reduction of the future predicted species richness of up to 10%. We concluded that the breeding range of most European birds will decrease in spite of dispersal abilities close to a full dispersal hypothesis, and that given the contrasted predictions obtained when modeling climate change only and land‐use change only, both scenarios must be taken into consideration.     

Likelihood of changes in forest species suitability,distribution, and diversity under future climate: The case of Southern Europe

Forest conservation strategies and plans can be unsuccessful if the new habitat conditions determined by climate change are not considered. Our work aims at investigating the likelihood of future suitability, distribution and diversity for some common European forest species under the projected changes in climate, focusing on Southern Europe. We combine an Ensemble Platform for Species Distribution Models (SDMs) to five Global Circulation Models (GCMs) driven by two Representative Concentration Pathways (RCPs), to produce maps of future climate‐driven habitat suitability for ten categories of forest species and two time horizons. For each forest category and time horizon, ten maps of future distribution (5 GCMs by 2 RCPs) are thus combined in a single suitability map supplied with information about the “likelihood” adopting the IPCC terminology based on consensus among projections. Then, the statistical significance of spatially aggregated changes in forest composition at local and regional level is analyzed. Finally, we discuss the importance, among SDMs, that environmental predictors seem to have in influencing forest distribution. Future impacts of climate change appear to be diversified across forest categories. A strong change in forest regional distribution and local diversity is projected to take place, as some forest categories will find more suitable conditions in previously unsuitable locations, while for other categories the same new conditions will become less suited. A decrease in species diversity is projected in most of the area, with Alpine region showing the potentiality to become a refuge for species migration.     

Effects of ecohydrological variables on current and future ranges,local suitability patterns,and model accuracy in big sagebrush

Forecasting of species and ecosystem responses to novel conditions, including climate change, is one of the major challenges facing ecologists at the start of the 21st century. Climate change studies based on species distribution models (SDMs) have been criticized because they extend correlational relationships beyond the observed data. Here, we compared conventional climate‐based SDMs against ecohydrological SDMs that include information from process‐based simulations of water balance. We examined the current and future distribution of Artemisia tridentata (big sagebrush) representing sagebrush ecosystems, which are widespread in semiarid western North America. For each approach, we calculated ensemble models from nine SDM methods and tested accuracy of each SDM with a null distribution. Climatic conditions included current conditions for 1970–1999 and two IPCC projections B1 and A2 for 2070–2099. Ecohydrological conditions were assessed by simulating soil water balance with SOILWAT, a daily time‐step, multiple layer, mechanistic, soil water model. Under current conditions, both climatic and ecohydrological SDM approaches produced comparable sagebrush distributions. Overall, sagebrush distribution is forecasted to decrease, with larger decreases under the A2 than under the B1 scenario and strong decreases in the southern part of the range. Increases were forecasted in the northern parts and at higher elevations. Both SDM approaches produced accurate predictions. However, the ecohydrological SDM approach was slightly less accurate than climatic SDMs (?1% in AUC, ?4% in Kappa and TSS) and predicted a higher number of habitat patches than observed in the input data. Future predictions of ecohydrological SDMs included an increased number of habitat patches whereas climatic SDMs predicted a decrease. This difference is important for understanding landscape‐scale patterns of sagebrush ecosystems and management of sagebrush obligate species for future conditions. Several mechanisms can explain the diverging forecasts; however, we need better insights into the consequences of different datasets for SDMs and how these affect our understanding of future trajectories.     

Persistence at distributional edges: Columbia spotted frog habitat in the arid Great Basin,USA

A common challenge in the conservation of broadly distributed, yet imperiled species is understanding which factors facilitate persistence at distributional edges, locations where populations are often vulnerable to extirpation due to changes in climate, land use, or distributions of other species. For Columbia spotted frogs (Rana luteiventris) in the Great Basin (USA), a genetically distinct population segment of conservation concern, we approached this problem by examining (1) landscape‐scale habitat availability and distribution, (2) water body‐scale habitat associations, and (3) resource management‐identified threats to persistence. We found that areas with perennial aquatic habitat and suitable climate are extremely limited in the southern portion of the species’ range. Within these suitable areas, native and non‐native predators (trout and American bullfrogs [Lithobates catesbeianus]) are widespread and may further limit habitat availability in upper‐ and lower‐elevation areas, respectively. At the water body scale, spotted frog occupancy was associated with deeper sites containing abundant emergent vegetation and nontrout fish species. Streams with American beaver (Castor canadensis) frequently had these structural characteristics and were significantly more likely to be occupied than ponds, lakes, streams without beaver, or streams with inactive beaver ponds, highlighting the importance of active manipulation of stream environments by beaver. Native and non‐native trout reduced the likelihood of spotted frog occupancy, especially where emergent vegetation cover was sparse. Intensive livestock grazing, low aquatic connectivity, and ephemeral hydroperiods were also negatively associated with spotted frog occupancy. We conclude that persistence of this species at the arid end of its range has been largely facilitated by habitat stability (i.e., permanent hydroperiod), connectivity, predator‐free refugia, and a commensalistic interaction with an ecosystem engineer. Beaver‐induced changes to habitat quality, stability, and connectivity may increase spotted frog population resistance and resilience to seasonal drought, grazing, non‐native predators, and climate change, factors which threaten local or regional persistence.     

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.     

Independent effects of habitat loss,habitat fragmentation and structural connectivity on forest‐dependent birds

Aim Habitat loss and fragmentation are amongst the greatest threats to biodiversity world‐wide. However, there is still little evidence on the relative influence of these two distinct processes on biodiversity, and no study, to date, has investigated the independent contribution of structural connectivity in addition to habitat loss and fragmentation. The aim of this study is to evaluate the independent effects of habitat loss (the decrease in total amount of habitat), habitat fragmentation per se (habitat subdivision) and structural connectivity (in the form of hedgerow networks) on the distribution of seven resident forest‐dependent birds in central Italy. Location Central Italy. Methods We strategically selected 30 landscapes (each of 16 km² in size) with decreasing total amount of forest cover and with contrasting configuration of patches and contrasting lengths of hedgerow networks. Presence/absence of birds in each landscape unit was studied through point counts. Results The amount of forest cover in the landscape had the strongest relative influence on birds’ occupancy, whilst habitat subdivision played a negligible role. Structural connectivity and the geographic position of the landscape unit played a relatively important role for four species. Main conclusions Our study shows the importance of disentangling the contribution of different landscape properties in determining distribution patterns. Our results are consistent with the fact that halting habitat loss and carrying out habitat restoration should be conservation priorities, since habitat loss is the main factor affecting the distribution of the target species; implementation of structural connectivity through hedgerows, instead, should be evaluated with caution since its contribution is secondary to the predominant role of habitat loss.     

Range reshuffling: Climate change,invasive species,and the case of Nothofagus forests in Aotearoa New Zealand

Aim

The impact of climate change on forest biodiversity and ecosystem services will be partly determined by the relative fortunes of invasive and native forest trees under future conditions. Aotearoa New Zealand has high conservation value native forests and one of the world's worst invasive tree problems. We assess the relative effects of habitat redistribution on native Nothofagus and invasive conifer (Pinaceae) species in New Zealand as a case study on the compounding impacts of climate change and tree invasions.

Location

Aotearoa New Zealand.

Methods

We use species distribution models (SDMs) to predict the current and future distribution of habitat for five native Nothofagus species and 13 invasive conifer species under two 2070 climate scenarios. We calculate habitat loss/gain for all species and examine overlap between the invasive and native species now and in future.

Results

Most species will lose habitat overall. The native species saw large changes in the distribution of habitat with extensive losses in North Island and gains mostly in South Island. Concerningly, we found that most new habitat for Nothofagus was also suitable for at least one invasive species. However, there were refugia for the native species in the wetter parts of the climate space.

Main Conclusion

If the predicted changes in habitat distribution translate to shifts in forest distribution, it would cause widespread ecological disruption. We discuss how acclimation, adaptation and biotic interactions may prevent/delay some changes. But we also highlight that the poor establishment capacity of Nothofagus, and the contrasting ability of the conifers to invade, will present persistent conservation challenges in areas of both new habitat and forest retreat. Pinaceae are problematic invaders globally, and our results highlight that control of invasions and active native forest restoration will likely be key to managing forest biodiversity under future climates.     

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.     

A species‐centered approach for uncovering generalities in organism responses to habitat loss and fragmentation

Theoretical models predict strong influences of habitat loss and fragmentation on species distributions and demography, but empirical studies have shown relatively inconsistent support across species and systems. We argue that species’ responses to landscape‐scale habitat loss and fragmentation are likely to appear less idiosyncratic if it is recognized that species perceive the same landscapes in different ways. We present a new quantitative approach that uses species distribution models (SDMs) to measure landscapes (e.g. patch size, isolation, matrix amount) from the perspective of individual species. First, we briefly summarize the few efforts to date demonstrating that once differences in habitat distributions are controlled, consistencies in species’ responses to landscape structure emerge. Second, we present a detailed example providing step‐by‐step methods for application of a species‐centered approach using freely available land‐cover data and recent statistical modeling approaches. Third, we discuss pitfalls in current applications of the approach and recommend avenues for future developments. We conclude that the species‐centered approach offers considerable promise as a means to test whether sensitivity to habitat loss and fragmentation is mediated by phylogenetic, ecological, and life‐history traits. Cross‐species generalities in responses to habitat loss and fragmentation will be challenging to uncover unless landscape mosaics are defined using models that reflect differing species‐specific distributions, functional connectivity, and domains of scale. The emergence of such generalities would not only enhance scientific understanding of biotic processes driving fragmentation effects, but would allow managers to estimate species sensitivities in new regions.