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The geographic redistributions of species due to a rapidly changing climate are poised to perturb ecological communities and significantly impact ecosystems and human livelihoods. Effectively managing these biological impacts requires a thorough understanding of the patterns and processes of species geographic range shifts. While substantial recent redistributions have been identified and recognized to vary by taxon, region, and range geometry, there are large gaps and biases in the available evidence. Here, we use the largest compilation of geographic range change observations to date, comprised of 33,016 potential redistributions across 12,009 species, to formally assess within‐ and cross‐species coverage and biases and to motivate future data collection. We find that species coverage varies strongly by taxon and underrepresents species at high and low latitudes. Within species, assessments of potential redistributions came from parts of their geographic range that were highly uneven and non‐representative. For most species and taxa, studies were strongly biased toward the colder parts of species' distributions and thus significantly underrepresented populations that might get pushed beyond their maximum temperature limits. Coverage of potential leading and trailing geographic range edges under a changing climate was similarly uneven. Only 8% of studied species were assessed at both high and low latitude and elevation range edges, with most only covered at one edge. This suggests that substantial within‐species biases exacerbate the considerable geographic and taxonomic among‐species unevenness in evidence. Our results open the door for a more quantitative accounting for existing knowledge biases in climate change ecology and a more informed management and conservation. Our findings offer guidance for future data collection that better addresses information gaps and provides a more effective foundation for managing the biological impacts of climate change. [ABSTRACT FROM AUTHOR]

As a consequence of anthropogenic climate change, marine species on continental shelves around the world are rapidly shifting deeper and poleward. However, whether these shifts deeper and poleward will allow species to access more, less, or equivalent amounts of continental shelf area and associated critical habitats remains unclear. By examining the proportion of seabed area at a range of depths for each large marine ecosystem (LME), we found that shelf area declined monotonically for 19% of LMEs examined. However, the majority exhibited a greater proportion of shelf area in mid-depths or across several depth ranges. By comparing continental shelf area across 2° latitudinal bands, we found that all coastlines exhibit multiple instances of shelf area expansion and contraction, which have the potential to promote or restrict poleward movement of marine species. Along most coastlines, overall shelf habitat increases or exhibits no significant change moving towards the poles. The exception is the Southern West Pacific, which experiences an overall loss of area with increasing latitude. Changes in continental shelf area availability across latitudes and depths are likely to affect the number of species local ecosystems can support. These geometric analyses help identify regions of conservation priority and ecological communities most likely to face attrition or expansion due to variations in available area.

Current analyses and predictions of spatially explicit patterns and processes in ecology most often rely on climate data interpolated from standardized weather stations. This interpolated climate data represents long-term average thermal conditions at coarse spatial resolutions only. Hence, many climate-forcing factors that operate at fine spatiotemporal resolutions are overlooked. This is particularly important in relation to effects of observation height (e.g. vegetation, snow and soil characteristics) and in habitats varying in their exposure to radiation, moisture and wind (e.g. topography, radiative forcing or cold-air pooling). Since organisms living close to the ground relate more strongly to these microclimatic conditions than to free-air temperatures, microclimatic ground and near-surface data are needed to provide realistic forecasts of the fate of such organisms under anthropogenic climate change, as well as of the functioning of the ecosystems they live in. To fill this critical gap, we highlight a call for temperature time series submissions to SoilTemp, a geospatial database initiative compiling soil and near-surface temperature data from all over the world. Currently, this database contains time series from 7,538 temperature sensors from 51 countries across all key biomes. The database will pave the way toward an improved global understanding of microclimate and bridge the gap between the available climate data and the climate at fine spatiotemporal resolutions relevant to most organisms and ecosystem processes.

Forecasting the future state of a species is a tricky process, as there are numerous hidden factors that influence species trajectories in addition to the obvious unknowns about the future state of the planet. We echo the guidance of Clare et al. (2024) to use near‐term and long‐term forecasting in complementary ways. Near‐term forecasts can be used to guide specific management and conservation actions, which can be updated as new data and evidence are collected. Long‐term forecasts can be used to characterize uncertainty further into the future, which can help guide longstanding conservation planning and legislative actions that are based on such uncertainty in possible future outcomes. [ABSTRACT FROM AUTHOR]

Microclimate research gained renewed interest over the last decade and its importance for many ecological processes is increasingly being recognized. Consequently, the call for high‐resolution microclimatic temperature grids across broad spatial extents is becoming more pressing to improve ecological models. Here, we provide a new set of open‐access bioclimatic variables for microclimate temperatures of European forests at 25 × 25 m2 resolution. [ABSTRACT FROM AUTHOR]

Species around the world are shifting their ranges in response to climate change. To make robust predictions about climate-related colonizations and extinctions, it is vital to understand the dynamics of range edges. This study is among the first to examine annual dynamics of cold and warm range edges, as most global change studies average observational data over space or over time. We analyzed annual range edge dynamics of marine fishes-both at the individual species level and pooled into cold- and warm-edge assemblages-in a multi-decade time-series of trawl surveys conducted on the Northeast US Shelf during a period of rapid warming. We tested whether cold edges show stronger evidence of climate tracking than warm edges (due to non-climate processes or time lags at the warm edge; the biogeography hypothesis or extinction debt hypothesis), or whether they tracked temperature change equally (due to the influence of habitat suitability; the ecophysiology hypothesis). In addition to exploring correlations with regional temperature change, we calculated species- and assemblage-specific sea bottom and sea surface temperature isotherms and used them to predict range edge position. Cold edges shifted further and tracked sea surface and bottom temperature isotherms to a greater degree than warm edges. Mixed-effects models revealed that for a one-degree latitude shift in isotherm position, cold edges shifted 0.47 degrees of latitude, and warm edges shifted only 0.28 degrees. Our results suggest that cold range edges are tracking climate change better than warm range edges, invalidating the ecophysiology hypothesis. We also found that even among highly mobile marine ectotherms in a global warming hotspot, few species are fully keeping pace with climate.

Urbanization and agricultural intensification of landscapes are important drivers of global change, which in turn have direct impacts on local ecological communities leading to shifts in species distributions and interactions. Here, we illustrate how human-altered landscapes, with novel ornamental and crop plant communities, result not only in changes to local community diversity of floral-dependent species, but also in shifts in seasonal abundance of bee pollinators. Three years of data on the spatio-temporal distributions of 91 bee species show that seasonal patterns of abundance and species richness in human-altered landscapes varied significantly less compared to natural habitats in which floral resources are relatively scarce in the dry summer months. These findings demonstrate that anthropogenic environmental changes in urban and agricultural systems, here mediated through changes in plant resources and water inputs, can alter the temporal dynamics of pollinators that depend on them. Changes in phenology of interactions can be an important, though frequently overlooked, mechanism of global change.

Biological communities in the Arctic are changing through the climate‐driven encroachment of subarctic species. This "Atlantification" extends to keystone Calanoid copepods, as the small‐bodied Calanus finmarchicus increases in abundance in areas where it overlaps with larger Arctic congeners. The environmental factors that are facilitating this shift, whether related to optimal conditions in temperature or seasonality, remain unclear. Assessing these drivers at an Arctic‐wide scale is necessary to predict future ecosystem change and impacts. Here we have compiled range‐wide occurrences of C. finmarchicus and a suite of seasonal biophysical climatologies to build a boreo‐Arctic ecological niche model. The data set was divided into two eras, 1955–1984 and 1985–2017, and an optimized MaxEnt model was used to predict the seasonal distribution of the abiotic niche of C. finmarchicus in both eras. Comparing outputs between eras reveals an increase in habitat suitability at the Arctic range edge. Large and significant increases in suitability are predicted in the regions of the Greenland, Labrador, and Southern Barents Seas that have experienced reduced sea‐ice cover. With the exception of the Barents Sea, these areas also show a seasonal shift in the timing of peak habitat suitability toward an earlier season. Our findings suggest that the Atlantification of Arctic zooplankton communities is accompanied by climate‐driven phenology changes. Although seasonality is a critical constraint to the establishment of C. finmarchicus at Arctic latitudes, earlier sea‐ice retreat and associated productivity is making these environments increasingly favorable for this subarctic species. [ABSTRACT FROM AUTHOR]

Ecological research heavily relies on coarse‐gridded climate data based on standardized temperature measurements recorded at 2 m height in open landscapes. However, many organisms experience environmental conditions that differ substantially from those captured by these macroclimatic (i.e. free air) temperature grids. In forests, the tree canopy functions as a thermal insulator and buffers sub‐canopy microclimatic conditions, thereby affecting biological and ecological processes. To improve the assessment of climatic conditions and climate‐change‐related impacts on forest‐floor biodiversity and functioning, high‐resolution temperature grids reflecting forest microclimates are thus urgently needed. Combining more than 1200 time series of in situ near‐surface forest temperature with topographical, biological and macroclimatic variables in a machine learning model, we predicted the mean monthly offset between sub‐canopy temperature at 15 cm above the surface and free‐air temperature over the period 2000–2020 at a spatial resolution of 25 m across Europe. This offset was used to evaluate the difference between microclimate and macroclimate across space and seasons and finally enabled us to calculate mean annual and monthly temperatures for European forest understories. We found that sub‐canopy air temperatures differ substantially from free‐air temperatures, being on average 2.1°C (standard deviation ± 1.6°C) lower in summer and 2.0°C higher (±0.7°C) in winter across Europe. Additionally, our high‐resolution maps expose considerable microclimatic variation within landscapes, not captured by the gridded macroclimatic products. The provided forest sub‐canopy temperature maps will enable future research to model below‐canopy biological processes and patterns, as well as species distributions more accurately. [ABSTRACT FROM AUTHOR]

Marine species are declining at an unprecedented rate, catalyzing many nations to adopt conservation and management targets within their jurisdictions. However, marine species and the biophysical processes that sustain them are naive to international borders. An understanding of the prevalence of cross‐border species distributions is important for informing high‐level conservation strategies, such as bilateral or regional agreements. Here, we examined 28,252 distribution maps to determine the number and locations of transboundary marine plants and animals. More than 90% of species have ranges spanning at least two jurisdictions, with 58% covering more than 10 jurisdictions. All jurisdictions have at least one transboundary species, with the highest concentrations of transboundary species in the USA, Australia, Indonesia, and the Areas Beyond National Jurisdiction. Distributions of mapped biodiversity indicate that overcoming the challenges of multinational governance is critical for a much wider suite of species than migratory megavertebrates and commercially exploited fish stocks—the groups that have received the vast majority of multinational management attention. To effectively protect marine biodiversity, international governance mechanisms (particularly those related to the Convention on Biological Diversity, the Convention on Migratory Species, and Regional Seas Organizations) must be expanded to promote multinational conservation planning, and complimented by a holistic governance framework for biodiversity beyond national jurisdiction. [ABSTRACT FROM AUTHOR]

As a source of emerging infectious diseases, wildlife assemblages (and related spatial patterns) must be quantitatively assessed to help identify high‐risk locations. Previous assessments have largely focussed on the distributions of individual species; however, transmission dynamics are expected to depend on assemblage composition. Moreover, disease–diversity relationships have mainly been studied in the context of species loss, but assemblage composition and disease risk (e.g. infection prevalence in wildlife assemblages) can change without extinction. Based on the predicted distributions and abundances of 4466 mammal species, we estimated global patterns of disease risk through the calculation of the community‐level basic reproductive ratio R0, an index of invasion potential, persistence, and maximum prevalence of a pathogen in a wildlife assemblage. For density‐dependent diseases, we found that, in addition to tropical areas which are commonly viewed as infectious disease hotspots, northern temperate latitudes included high‐risk areas. We also forecasted the effects of climate change and habitat loss from 2015 to 2035. Over this period, many local assemblages showed no net loss of species richness, but the assemblage composition (i.e. the mix of species and their abundances) changed considerably. Simultaneously, most areas experienced a decreased risk of density‐dependent diseases but an increased risk of frequency‐dependent diseases. We further explored the factors driving these changes in disease risk. Our results suggest that biodiversity and changes therein jointly influence disease risk. Understanding these changes and their drivers and ultimately identifying emerging infectious disease hotspots can help health officials prioritize resource distribution. [ABSTRACT FROM AUTHOR]

Assessing the degree to which climate explains the spatial distributions of different taxonomic and functional groups is essential for anticipating the effects of climate change on ecosystems. Most effort so far has focused on above‐ground organisms, which offer only a partial view on the response of biodiversity to environmental gradients. Here including both above‐ and below‐ground organisms, we quantified the degree of topoclimatic control on the occurrence patterns of >1,500 taxa and phylotypes along a c. 3,000 m elevation gradient, by fitting species distribution models. Higher model performances for animals and plants than for soil microbes (fungi, bacteria and protists) suggest that the direct influence of topoclimate is stronger on above‐ground species than on below‐ground microorganisms. Accordingly, direct climate change effects are predicted to be stronger for above‐ground than for below‐ground taxa, whereas factors expressing local soil microclimate and geochemistry are likely more important to explain and forecast the occurrence patterns of soil microbiota. Detailed mapping and future scenarios of soil microclimate and microhabitats, together with comparative studies of interacting and ecologically dependent above‐ and below‐ground biota, are thus needed to understand and realistically forecast the future distribution of ecosystems. [ABSTRACT FROM AUTHOR]

Most studies on the biological effects of future climatic changes rely on seasonally aggregated, coarse‐resolution data. Such data mask spatial and temporal variability in microclimate driven by terrain, wind and vegetation, and ultimately bear little resemblance to the conditions that organisms experience in the wild. Here, I present the methods for providing fine‐grained, hourly and daily estimates of current and future temperature and soil moisture over decadal timescales. Observed climate data and spatially coherent probabilistic projections of daily future weather were disaggregated to hourly and used to drive empirically calibrated physical models of thermal and hydrological microclimates. Mesoclimatic effects (cold‐air drainage, coastal exposure and elevation) were determined from the coarse‐resolution climate surfaces using thin‐plate spline models with coastal exposure and elevation as predictors. Differences between micro and mesoclimate temperatures were determined from terrain, vegetation and ground properties using energy balance equations. Soil moisture was computed in a thin upper layer and an underlying deeper layer, and the exchange of water between these layers was calculated using the van Genuchten equation. Code for processing the data and running the models is provided as a series of R packages. The methods were applied to the Lizard Peninsula, United Kingdom, to provide hourly estimates of temperature (100 m grid resolution over entire area, 1 m for a selected area) for the periods 1983–2017 and 2041–2049. Results indicated that there is a fine‐resolution variability in climatic changes, driven primarily by interactions between landscape features and decadal trends in weather conditions. High‐temporal resolution extremes in conditions under future climate change were predicted to be considerably less novel than the extremes estimated using seasonally aggregated variables. The study highlights the need to more accurately estimate the future climatic conditions experienced by organisms and equips biologists with the means to do so. [ABSTRACT FROM AUTHOR]

Opportunistic citizen science (CS) programs allow volunteers to report species observations from anywhere, at any time, and can assemble large volumes of historic and current data at faster rates than more coordinated programs with standardized data collection. This can quickly provide large amounts of species distributional data, but whether this focus on participation comes at a cost in data quality is not clear. Although automated and expert vetting can increase data reliability, there is no guarantee that opportunistic data will do anything more than confirm information from professional surveys. Here, we use eButterfly, an opportunistic CS program, and a comparable dataset of professionally collected observations, to measure the amount of new distributional species information that opportunistic CS generates. We also test how well opportunistic CS can estimate regional species richness for a large group of taxa (>300 butterfly species) across a broad area. We find that eButterfly contributes new distributional information for >80% of species, and that opportunistically submitting observations allowed volunteers to spot species ~35 days earlier than professionals. Although eButterfly did a relatively poor job at predicting regional species richness by itself (detecting only about 35–57% of species per region), it significantly contributed to regional species richness when used with the professional dataset (adding ~3 species that had gone undetected in professional surveys per region). Overall, we find that the opportunistic CS model can provide substantial complementary species information when used alongside professional survey data. Our results suggest that data from opportunistic CS programs in conjunction with professional datasets can strongly increase the capacity of researchers to estimate species richness, and provide unique information on species distributions and phenologies that are relevant to the detection of the biological consequences of global change. Opportunistic citizen science programs allow volunteers to log species sightings from anywhere, at any time. These programs rapidly assemble large databases of reliable observations, but may only confirm information from professional, researcher‐led surveys. Here, Soroye et al compared eButterfly, an opportunistic citizen science program, to a comparable dataset of professionally collected observations. They find that combining both datasets improves estimates of species richness and reveals large amounts of previously unknown information on species distributions and seasonal timings. The authors show that opportunistic citizen science has an incredible potential to improve detection of biological signals for global change research. [ABSTRACT FROM AUTHOR]

Abstract: Treeline advance has occurred throughout the twentieth century in mountainous regions around the world; however, local variation and temporal lags in responses to climate warming indicate that the upper limits of some treelines are not necessarily in climatic equilibrium. These observations suggest that factors other than climate are constraining tree establishment beyond existing treelines. Using a seed addition experiment, we tested the effects of seed availability, predation and microsite limitation on the establishment of two subalpine tree species (Picea engelmannii and Abies lasiocarpa) across four treelines in the Canadian Rocky Mountains. The effect of vegetation removal on seedling growth was also determined, and microclimate conditions were monitored. Establishment limitations observed in the field were placed in context with the effects of soil properties observed in a parallel experiment. The seed addition experiment revealed reduced establishment with increasing elevation, suggesting that although establishment within the treeline ecotone is at least partially seed limited, other constraints are more important beyond the current treeline. The effects of herbivory and microsite availability significantly reduced seedling establishment but were less influential beyond the treeline. Microclimate monitoring revealed that establishment was negatively related to growing season temperatures and positively related to the duration of winter snow cover, counter to the conventional expectation that establishment is limited by low temperatures. Overall, it appears that seedling establishment beyond treeline is predominantly constrained by a combination of high soil surface temperatures during the growing season, reduced winter snowpack and unfavourable soil properties. Our study supports the assertion that seedling establishment in alpine treeline ecotones is simultaneously limited by various climatic and nonclimatic drivers. Together, these factors may limit future treeline advance in the Canadian Rocky Mountains and should be considered when assessing the potential for treeline advance in alpine systems elsewhere [ABSTRACT FROM AUTHOR]

Predicting how species will respond to the rapid climatic changes predicted this century is an urgent task. Species distribution models (SDMs) use the current relationship between environmental variation and species' abundances to predict the effect of future environmental change on their distributions. However, two common assumptions of SDMs are likely to be violated in many cases: (i) that the relationship of environment with abundance or fitness is constant throughout a species' range and will remain so in future and (ii) that abiotic factors (e.g. temperature, humidity) determine species' distributions. We test these assumptions by relating field abundance of the rainforest fruit fly Drosophila birchii to ecological change across gradients that include its low and high altitudinal limits. We then test how such ecological variation affects the fitness of 35 D. birchii families transplanted in 591 cages to sites along two altitudinal gradients, to determine whether genetic variation in fitness responses could facilitate future adaptation to environmental change. Overall, field abundance was highest at cooler, high-altitude sites, and declined towards warmer, low-altitude sites. By contrast, cage fitness (productivity) increased towards warmer, lower-altitude sites, suggesting that biotic interactions (absent from cages) drive ecological limits at warmer margins. In addition, the relationship between environmental variation and abundance varied significantly among gradients, indicating divergence in ecological niche across the species' range. However, there was no evidence for local adaptation within gradients, despite greater productivity of high-altitude than low-altitude populations when families were reared under laboratory conditions. Families also responded similarly to transplantation along gradients, providing no evidence for fitness trade-offs that would favour local adaptation. These findings highlight the importance of (i) measuring genetic variation in key traits under ecologically relevant conditions, and (ii) considering the effect of biotic interactions when predicting species' responses to environmental change. [ABSTRACT FROM AUTHOR]

The existence of fine-grain climate heterogeneity has prompted suggestions that species may be able to survive future climate change in pockets of suitable microclimate, termed 'microrefugia'. However, evidence for microrefugia is hindered by lack of understanding of how rates of warming vary across a landscape. Here, we present a model that is applied to provide fine-grained, multidecadal estimates of temperature change based on the underlying physical processes that influence microclimate. Weather station and remotely derived environmental data were used to construct physical variables that capture the effects of terrain, sea surface temperatures, altitude and surface albedo on local temperatures, which were then calibrated statistically to derive gridded estimates of temperature. We apply the model to the Lizard Peninsula, United Kingdom, to provide accurate (mean error = 1.21 °C; RMS error = 1.63 °C) hourly estimates of temperature at a resolution of 100 m for the period 1977-2014. We show that rates of warming vary across a landscape primarily due to long-term trends in weather conditions. Total warming varied from 0.87 to 1.16 °C, with the slowest rates of warming evident on north-east-facing slopes. This variation contributed to substantial spatial heterogeneity in trends in bioclimatic variables: for example, the change in the length of the frost-free season varied from +11 to −54 days and the increase in annual growing degree-days from 51 to 267 °C days. Spatial variation in warming was caused primarily by a decrease in daytime cloud cover with a resulting increase in received solar radiation, and secondarily by a decrease in the strength of westerly winds, which has amplified the effects on temperature of solar radiation on west-facing slopes. We emphasize the importance of multidecadal trends in weather conditions in determining spatial variation in rates of warming, suggesting that locations experiencing least warming may not remain consistent under future climate change. [ABSTRACT FROM AUTHOR]

We examined the hypothesis that ecological niche models ( ENMs) more accurately predict species distributions when they incorporate information on population genetic structure, and concomitantly, local adaptation. Local adaptation is common in species that span a range of environmental gradients (e.g., soils and climate). Moreover, common garden studies have demonstrated a covariance between neutral markers and functional traits associated with a species' ability to adapt to environmental change. We therefore predicted that genetically distinct populations would respond differently to climate change, resulting in predicted distributions with little overlap. To test whether genetic information improves our ability to predict a species' niche space, we created genetically informed ecological niche models ( gENMs) using Populus fremontii (Salicaceae), a widespread tree species in which prior common garden experiments demonstrate strong evidence for local adaptation. Four major findings emerged: (i) gENMs predicted population occurrences with up to 12-fold greater accuracy than models without genetic information; (ii) tests of niche similarity revealed that three ecotypes, identified on the basis of neutral genetic markers and locally adapted populations, are associated with differences in climate; (iii) our forecasts indicate that ongoing climate change will likely shift these ecotypes further apart in geographic space, resulting in greater niche divergence; (iv) ecotypes that currently exhibit the largest geographic distribution and niche breadth appear to be buffered the most from climate change. As diverse agents of selection shape genetic variability and structure within species, we argue that gENMs will lead to more accurate predictions of species distributions under climate change. [ABSTRACT FROM AUTHOR]

Predicting biodiversity responses to climate change remains a difficult challenge, especially in climatically complex regions where precipitation is a limiting factor. Though statistical climatic envelope models are frequently used to project future scenarios for species distributions under climate change, these models are rarely tested using empirical data. We used long-term data on bird distributions and abundance covering five states in the western US and in the Canadian province of British Columbia to test the capacity of statistical models to predict temporal changes in bird populations over a 32-year period. Using boosted regression trees, we built presence-absence and abundance models that related the presence and abundance of 132 bird species to spatial variation in climatic conditions. Presence/absence models built using 1970-1974 data forecast the distributions of the majority of species in the later time period, 1998-2002 (mean AUC = 0.79 ± 0.01). Hindcast models performed equivalently (mean AUC = 0.82 ± 0.01). Correlations between observed and predicted abundances were also statistically significant for most species (forecast mean Spearman′s ρ = 0.34 ± 0.02, hindcast = 0.39 ± 0.02). The most stringent test is to test predicted changes in geographic patterns through time. Observed changes in abundance patterns were significantly positively correlated with those predicted for 59% of species (mean Spearman′s ρ = 0.28 ± 0.02, across all species). Three precipitation variables (for the wettest month, breeding season, and driest month) and minimum temperature of the coldest month were the most important predictors of bird distributions and abundances in this region, and hence of abundance changes through time. Our results suggest that models describing associations between climatic variables and abundance patterns can predict changes through time for some species, and that changes in precipitation and winter temperature appear to have already driven shifts in the geographic patterns of abundance of bird populations in western North America. [ABSTRACT FROM AUTHOR]

Climate change is expected to cause geographic redistributions of species. To the extent that species within assemblages have different niche requirements, assemblages may no longer remain intact and dis- and reassemble at current or new geographic locations. We explored how climate change projected by 2100 may transform the world's avian assemblages (characterized at a 110 km spatial grain) by modeling environmental niche-based changes to their dietary guild structure under 0, 500, and 2000 km-dispersal distances. We examined guild structure changes at coarse (primary, high-level, and mixed consumers) and fine (frugivores, nectarivores, insectivores, herbivores, granivores, scavengers, omnivores, and carnivores) ecological resolutions to determine whether or not geographic co-occurrence patterns among guilds were associated with the magnitude to which guilds are functionally resolved. Dietary guilds vary considerably in their global geographic prevalence, and under broad-scale niche-based redistribution of species, these are projected to change very heterogeneously. A nondispersal assumption results in the smallest projected changes to guild assemblages, but with significant losses for some regions and guilds, such as South American insectivores. Longer dispersal distances are projected to cause greater degrees of disassembly, and lead to greater homogenization of guild composition, especially in northern Asia and Africa. This arises because projected range gains and losses result in geographically heterogeneous patterns of guild compensation. Projected decreases especially of primary and mixed consumers most often are compensated by increases in high-level consumers, with increasing uncertainty about these outcomes as dispersal distance and degree of guild functional resolution increase. Further exploration into the consequences of these significant broad-scale ecological functional changes at the community or ecosystem level should be increasingly on the agenda for conservation science. [ABSTRACT FROM AUTHOR]

Successful species interactions require that both partners share a similar cue. For many species, spring warming acts as a shared signal to synchronize mutualist behaviors. Spring flowering plants and the ants that disperse their seeds respond to warming temperatures so that ants forage when plants drop seeds. However, where warm-adapted ants replace cold-adapted ants, changes in this timing might leave early seeds stranded without a disperser. We investigate plant seed dispersal south and north of a distinct boundary between warm- and cold-adapted ants to determine if changes in the ant species influence local plant dispersal. The warm-adapted ants forage much later than the cold-adapted ants, and so we first assess natural populations of early and late blooming plants. We then transplant these plants south and north of the ant boundary to test whether distinct ant climate requirements disrupt the ant-plant mutualism. Whereas the early blooming plant's inability to synchronize with the warm-adapted ant leaves its populations clumped and patchy and its seedlings clustered around the parents in natural populations, when transplanted into the range of the cold-adapted ant, effective seed dispersal recovers. In contrast, the mutualism persists for the later blooming plant regardless of location because it sets seed later in spring when both warm- and cold-adapted ant species forage, resulting in effective seed dispersal. These results indicate that the climate response of species interactions, not just the species themselves, is integral in understanding ecological responses to a changing climate. Data linking phenological synchrony and dispersal are rare, and these results suggest a viable mechanism by which a species' range is limited more by biotic than abiotic interactions - despite the general assumption that biotic influences are buried within larger climate drivers. These results show that biotic partner can be as fundamental a niche requirement as abiotic resources. [ABSTRACT FROM AUTHOR]

Rapid climate change may prompt species distribution shifts upward and poleward, but species movement in itself is not sufficient to establish climate causation. Other dynamics, such as disturbance history, may prompt species distribution shifts resembling those expected from rapid climate change. Links between species distributions, regional climate trends and physiological mechanism are needed to convincingly establish climate-induced species shifts. We examine a 38-year shift (1974-2012) in an elevation ecotone between two closely related ant species, Aphaenogaster picea and A. rudis. Even though A. picea and A. rudis are closely related with North American distributions that sometimes overlap, they also exhibit local- and regional-scale differences in temperature requirements so that A. rudis is more southerly and inhabits lower elevations whereas A. picea is more northerly and inhabits high elevations. We find considerable movement by the warm-habitat species upward in elevation between 1974 and 2012 with A. rudis, replacing the cold-habitat species, A. picea, along the southern edge of the Appalachian Mountain chain in north Georgia, USA. Concomitant with the distribution shifts, regional mean and maximum temperatures remain steady (1974-2012), but minimum temperatures increase. We collect individuals from the study sites and subject them to thermal tolerance testing in a controlled setting and find that maximum and minimum temperature acclimatization occurs along the elevation gradient in both species, but A. rudis consistently becomes physiologically incapacitated at minimum and maximum temperatures 2 °C higher than A. picea. These results indicate that rising minimum temperatures allow A. rudis to move upward in elevation and displace A. picea. Given that Aphaenogaster ants are the dominant woodland seed dispersers in eastern deciduous forests, and that their thermal tolerances drive distinct differences in temperature-cued synchrony with early blooming plants, these climate responses not only impact ant-ant interactions, but might have wide implications for ant-plant interactions. [ABSTRACT FROM AUTHOR]

There is compelling evidence from glacial and interglacial periods of the Quaternary of the utilization of microrefugia. Microrefugia are sites that support locally favorable climates amidst unfavorable regional climates, which allow populations of species to persist outside of their main distributions. Knowledge of the location of microrefugia has important implications for climate change research as it will influence our understanding of the spatial distribution of species through time, their patterns of genetic diversity, and potential dispersal rates in response to climate shifts. Indeed, the implications of microrefugia are profound and yet we know surprisingly little about their climatic basis; what climatic processes can support their subsistence, where they may occur, their climatic traits, and the relevance of these locations for climate change research. Here I examine the climatic basis for microrefugia and assert that the interaction between regional advective influences and local terrain influences will define the distribution and nature of microrefugia. I review the climatic processes that can support their subsistence and from this climatic basis: (1) infer traits of the spatial distribution of microrefugia and how this may change through time; (2) review assertions about their landscape position and what it can tell us about regional climates; and (3) demonstrate an approach to forecasting where microrefugia may occur in the future. This synthesis highlights the importance of landscape physiography in shaping the adaptive response of biota to climate change. [ABSTRACT FROM AUTHOR]

There has been considerable recent interest concerning the impact of climate change on a wide range of taxa. However, little is known about how the biogeographic affinities of taxa may affect their responses to these impacts. Our main aim was to study how predicted climate change will affect the distribution of 28 European bat species grouped by their biogeographic patterns as determined by a spatial Principal Component Analysis. Using presence-only modelling techniques and climatic data (minimum temperature, average temperature, precipitation, humidity and daily temperature range) for four different climate change scenarios (IPCC scenarios ranging from the most extreme A1FI, A2, B2 to the least severe, B1), we predict the potential geographic distribution of bat species in Europe grouped according to their biogeographic patterns for the years 2020–2030, 2050–2060 and 2090–2100. Biogeographic patterns exert a great influence on a species' response to climate change. Bat species more associated with colder climates, hence northern latitudes, could be more severely affected with some extinctions predicted by the end of the century. The Mediterranean and Temperate groups seem to be more tolerant of temperature increases, however, their projections varied considerably under different climate change scenarios. Scenario A1FI was clearly the most detrimental for European bat diversity, with several extinctions and declines in occupied area predicted for several species. The B scenarios were less damaging and even predicted that some species could increase their geographical ranges. However, all models only took into account climatic envelopes whereas available habitat and species interactions will also probably play an important role in delimiting future distribution patterns. The models may therefore generate ‘best case’ predictions about future changes in the distribution of European bats. [ABSTRACT FROM AUTHOR]

Global temperatures are rising, and are expected to produce a poleward shift in the distribution of many organisms. We quantified changes in fish assemblages within seagrass meadows of the northern Gulf of Mexico (GOM) between the 1970s and 2006–2007, and observed changes consistent with this forecast. During 2006–2007 we sampled seagrass meadows using the same gears and methods previously employed by R. J. Livingston in coastal waters of northwest Florida throughout the 1970s. Comparisons between datasets revealed numerous additions to the fish fauna during 2006–2007 that were completely absent in the 1970s, including: Lutjanus synagris (lane snapper), Epinephelus morio (red grouper), Chaetodon ocellatus (spotfin butterflyfish), Mycteroperca sp (grouper, non gag), Centropristis philadelphica (rock sea bass), Fistularia tabacaria (bluespotted cornetfish), Ocyurus chrysurus (yellowtail snapper), Thalassoma bifasciatum (bluehead wrasse), Abudefduf saxatilis (sergeant major), Acanthuridae spp. (surgeonfishes) and Sparisoma viride (stoplight parrotfish). Several other species showed large increases in abundance during the interval between 1979 and 2006, including Mycteroperca microlepis (gag grouper, up ∼200 ×), Lutjanus griseus (gray snapper, up ∼105 ×), and Nicholsina usta (emerald parrotfish, up ∼22 ×). All of these are tropical or subtropical species that now make up a greater percentage of seagrass-associated fish assemblages in the northern GOM than in the past. Additionally, we observed regional increases in air and sea surface temperatures (> 3 °C) during the ∼30 years that separate Livingston's samples and ours that correlate with northern shifts in the distribution of warm-water fishes. Documenting these range shifts is a critical first step in investigating the consequences of global warming for endemic marine communities and fishery production in the northern GOM. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Climate envelope models (CEMs) have been used to predict the distribution of species under current, past, and future climatic conditions by inferring a species' environmental requirements from localities where it is currently known to occur. CEMs can be evaluated for their ability to predict current species distributions but it is unclear whether models that are successful in predicting current distributions are equally successful in predicting distributions under different climates (i.e. different regions or time periods). We evaluated the ability of CEMs to predict species distributions under different climates by comparing their predictions with those obtained with a mechanistic model (MM). In an MM the distribution of a species is modeled based on knowledge of a species' physiology. The potential distributions of 100 plant species were modeled with an MM for current conditions, a past climate reconstruction (21 000 years before present) and a future climate projection (double preindustrial CO2 conditions). Point localities extracted from the currently suitable area according to the MM were used to predict current, future, and past distributions with four CEMs covering a broad range of statistical approaches: Bioclim (percentile distributions), Domain (distance metric), GAM (general additive modeling), and Maxent (maximum entropy). Domain performed very poorly, strongly underestimating range sizes for past or future conditions. Maxent and GAM performed as well under current climates as under past and future climates. Bioclim slightly underestimated range sizes but the predicted ranges overlapped more with the ranges predicted with the MM than those predicted with GAM did. Ranges predicted with Maxent overlapped most with those produced with the MMs, but compared with the ranges predicted with GAM they were more variable and sometimes much too large. Our results suggest that some CEMs can indeed be used to predict species distributions under climate change, but individual modeling approaches should be validated for this purpose, and model choice could be made dependent on the purpose of a particular study. [ABSTRACT FROM AUTHOR]