Search

Understanding how species ranges shift as climates rapidly change informs us how to effectively conserve vulnerable species. Species distribution models (SDMs) are an important method for examining these range shifts. The tools for performing SDMs are ever improving. Here, we present the megaSDM R package. This package facilitates realistic spatiotemporal SDM analyses by incorporating dispersal probabilities, creating time‐step maps of range change dynamics and efficiently handling large datasets and computationally intensive environmental subsampling techniques. Provided a list of species and environmental data, megaSDM synthesizes GIS processing, subsampling methods, MaxEnt modelling, dispersal rate restrictions and additional statistical tools to create a variety of outputs for each species, time period and climate scenario requested. For each of these, megaSDM generates a series of distribution maps and outputs visual representations of statistical data. megaSDM offers several advantages over other commonly used SDM tools. First, many of the functions in megaSDM natively implement parallelization, enabling the package to handle large amounts of data efficiently without the need for additional coding. megaSDM also implements environmental subsampling of occurrences, making the technique broadly available in a way that was not possible before due to computational considerations. Uniquely, megaSDM generates maps showing the expansion and contraction of a species range across all considered time periods (time‐maps), and constrains both presence/absence and continuous suitability maps of species ranges according to species‐specific dispersal constraints. The user can then directly compare non‐dispersal and dispersal‐limited distribution predictions. This paper discusses the unique features and highlights of megaSDM, describes the structure of the package and demonstrates the package's features and the model flow through examples. [ABSTRACT FROM AUTHOR]

Climate‐driven species redistribution is pervasive and accelerating, yet the complex mechanisms at play remain poorly understood. The implications of large‐scale species redistribution for natural systems and human societies have resulted in a large number of studies exploring the effects on individual species and ecological communities worldwide. Whilst many studies have investigated discrete components of species redistribution, the integration required for a more complete mechanistic understanding is lacking. In this paper, we provide a framework for synthesising approaches to more robustly understand and predict marine species redistributions. We conceptualise the stages and processes involved in climate‐driven species redistribution at increasing levels of biological organisation, and synthesize the laboratory, field and modelling approaches used to study redistribution related processes at individual, population and community levels. We then summarise links between scales of biological organisation and methodological approaches in a hierarchical framework that represents an integrated mechanistic assessment of climate‐driven species redistributions. In a rapidly expanding field of research, this framework provides direction for: 1) guiding future research, 2) highlighting key knowledge gaps, 3) fostering data exchange and collaboration between disciplines and 4) improving shared capacity to predict and therefore, inform the proactive management of climate impacts on natural systems. [ABSTRACT FROM AUTHOR]

Migration is a prevalent strategy among birds used to track seasonal resources throughout the year. Individual and population‐level migratory movements provide insight to life‐history variation, carry‐over effects, and impacts of climate change. Our understanding of how geographic variation in a species' breeding or wintering grounds can impact migration distances is limited. However, changes in migration distances can have important fitness consequences for individuals and conservation implications for populations, particularly if migratory connectivity is altered during the annual cycle. In this study, we use three decades of data from the United States Geological Survey Bird Banding Laboratory for six migratory species of Arctic and subarctic breeding geese. We employ a Bayesian hierarchical framework to test if the distance between breeding and wintering locations has changed over time, while accounting for the latitude of the breeding grounds. A model that included only a temporal trend estimated the average rate of change in migration distance, across all six species, at −3.0 km/year over the period 1990–2019. Five of the six species showed a significant decrease in migration distances. Including an interaction effect with breeding latitude revealed that the reduction in migration distance was strongest in the southernmost populations for four of the six species. For those species, migration distance in northern populations were all either relatively unchanged or increasing. This indicates that southern breeding populations of geese had a stronger association with the observed spatiotemporal changes in wintering ranges, potentially influenced by a combination of climatic and biotic factors (e.g. resource availability or competitive interactions) that uniquely impact these populations. Abundant, long‐term banding data shows promise for use in illuminating changes in migratory patterns under climate change, leading to improved management and conservation outcomes, from regional to continental scales. [ABSTRACT FROM AUTHOR]

Forests provide essential ecosystem services that range from the production of timber to the mitigation of natural hazards. Rapid environmental changes, such as climate warming or the intensification of disturbance regimes, threaten forests and endanger forest ecosystem services. In light of these challenges, it is essential to understand forests' demographic processes of regeneration, growth, and mortality and their relationship with environmental conditions. Specifically, understanding the regeneration process in present‐day forests is crucial since it lays the foundation for the structure of future forests and their tree species composition. We used Swiss National Forest Inventory (NFI) data covering vast bio‐geographic gradients over four decades to achieve this understanding. Trees that reached a diameter at breast height of 12 cm between two consecutive NFI campaigns were used to determine regeneration and were referred to as ingrowth. Employing three independent statistical models, we investigated the number, species, and diameter of these ingrowth trees. The models were subsequently implemented into a forest simulator to project the development of Swiss forests until the mid‐21st century. The simulation results showed an ingrowth decrease and a shift in its species composition, marked by a significant reduction in Norway spruce Picea abies and concurrent increases in broadleaves. Nevertheless, the pace of this change towards climatically better adapted species composition is relatively slow and is likely to slow down even further as ingrowth declines in the future, in contrast to the fast‐changing climatic conditions. Hence, support through adaptive planting strategies should be tested in case ingrowth does not ensure the resilience of forests in the future. We conclude that since the regeneration of forests is becoming increasingly challenging, the current level at which ecosystem services are provided might not be ensured in the coming decades. [ABSTRACT FROM AUTHOR]

Basic ecological theory suggests that a tradeoff between competitiveness and stress tolerance dictates species range limits at regional extents. However, empirical support for this key theory remains deficient because the necessary spatial and temporal coverage and scalability of field observations has rarely been achieved. We harnessed an extensive dendroecological network (> 22 000 tree‐ring samples from 816 forest inventory plots) to disentangle competition‐limited from climate‐limited growth in both overstory and understory trees. Growth synchrony among trees thereby served as an integral metric of climate sensitivity, an approach that we justify in supplementary analyses of growth responses to temperature, precipitation, and the standardized precipitation‐evapotranspiration index. Sampling plots were arranged along elevational climate and vegetation gradients throughout the Carpathian Mountains, ranging from mixed‐species lowland forests to coniferous forests at high elevations. With mixed‐effect modelling, we also identified non‐climatic factors (stand characteristics, species diversity, and disturbance history) that modulate spatial patterns in the growth rate and synchrony of European beech Fagus sylvatica and Norway spruce Picea abies. Beech exhibited reduced growth and increased climate sensitivity towards higher elevations but performed better when species diversity was higher. The growth of spruce increased towards its lower range boundary, but understory cohorts grew poorly under interspecific competition. Overall, climate sensitivity was lower in more productive stands with benign climatic conditions and in recently disturbed sites with reduced stand density. These contrasting performances at mid‐elevations where the two species overlap (900–1300 m a.s.l.) reflect their evolutionary history, which enables them to be competitive (beech) or cold‐stress tolerant (spruce). This history will affect interactions between the two species under climate warming and shape macroecological patterns in the Carpathian ecoregion and likely other parts of Europe. Our findings point to a growing advantage of competitively stronger species in montane and subalpine vegetation zones. [ABSTRACT FROM AUTHOR]

Community‐level climate change indicators have been proposed to appraise the impact of global warming on community composition. However, non‐climate factors may also critically influence species distribution and biological community assembly. The aim of this paper was to study how fire–vegetation dynamics can modify our ability to predict the impact of climate change on bird communities, as described through a widely‐used climate change indicator: the community thermal index (CTI). Potential changes in bird species assemblage were predicted using the spatially‐explicit species assemblage modelling framework – SESAM – that applies successive filters to constrained predictions of richness and composition obtained by stacking species distribution models that hierarchically integrate climate change and wildfire–vegetation dynamics. We forecasted future values of CTI between current conditions and 2050, across a wide range of fire–vegetation and climate change scenarios. Fire–vegetation dynamics were simulated for Catalonia (Mediterranean basin) using a process‐based model that reproduces the spatial interaction between wildfire, vegetation dynamics and wildfire management under two IPCC climate scenarios. Net increases in CTI caused by the concomitant impact of climate warming and an increasingly severe wildfire regime were predicted. However, the overall increase in the CTI could be partially counterbalanced by forest expansion via land abandonment and efficient wildfire suppression policies. CTI is thus strongly dependent on complex interactions between climate change and fire–vegetation dynamics. The potential impacts on bird communities may be underestimated if an overestimation of richness is predicted but not constrained. Our findings highlight the need to explicitly incorporate these interactions when using indicators to interpret and forecast climate change impact in dynamic ecosystems. In fire‐prone systems, wildfire management and land‐use policies can potentially offset or heighten the effects of climate change on biological communities, offering an opportunity to address the impact of global climate change proactively. [ABSTRACT FROM AUTHOR]

The connections of climatic variables to zoonotic and wildlife diseases remain uncertain. Here, we compiled a systematic database for the prevalence of 121 pathogenic microbial taxa in birds (ca 376 species) and bats (ca 39 species), including 11 939 observations from over 450 000 individuals across Europe and surrounding regions. We modelled the potential connection of climatic variables with the prevalence of 75 pathogenic microbial taxa at a multi‐pathogenic‐taxa level and of 17 most‐studied pathogenic taxa at a single‐pathogenic‐taxon level. According to the multi‐taxa model, the prevalence of bacterial taxa was positively associated with temperature, while this association was significantly weaker for eukaryotes and viruses. The prevalence of bacterial taxa was negatively associated with rainfall, while viruses showed a positive association with rainfall. These associations between climatic variables and prevalence of pathogenic taxa were not different between bird and bat hosts. According to the single‐taxon models, the prevalence of influenza A viruses, Plasmodium, and several bacterial taxa in birds and bats was positively associated with temperature. Rainfall showed positive associations with the prevalence of Usutu, Sindbis and Influenza A viruses but the directions of significant associations varied among bacterial taxa. Strikingly, this was evidenced also between bacterial taxa that share hosts and transmission mechanism hinting towards hitherto unknown features on pathogen ecology, e.g. Salmonella versus Campylobacter and Anaplasma versus Borrelia. Our results suggest that rising temperature and increasing precipitation will accelerate the threat of bird‐ and bat‐associated bacterial and viral pathogens to wildlife, domesticated animals and humans, respectively. However, the idiosyncratic relationships with climatic conditions among pathogenic taxa highlight the need for pathogen‐specific predictive models to understand future pathogen distributions. [ABSTRACT FROM AUTHOR]

Species distribution models (SDMs) have been widely used to project terrestrial species' responses to climate change and are increasingly being used for similar objectives in the marine realm. These projections are critically needed to develop strategies for resource management and the conservation of marine ecosystems. SDMs are a powerful and necessary tool; however, they are subject to many sources of uncertainty, both quantifiable and unquantifiable. To ensure that SDM projections are informative for management and conservation decisions, sources of uncertainty must be considered and properly addressed. Here we provide ten overarching guidelines that will aid researchers to identify, minimize, and account for uncertainty through the entire model development process, from the formation of a study question to the presentation of results. These guidelines focus on correlative models and were developed at an international workshop attended by over 50 researchers and practitioners. Although our guidelines are broadly applicable across biological realms, we provide particular focus to the challenges and uncertainties associated with projecting the impacts of climate change on marine species and ecosystems. [ABSTRACT FROM AUTHOR]

Climate change causes considerable shifts in the geographic distribution of species worldwide. Most data on range movements, however, derive from relatively short periods, within which it is difficult to distinguish directional shifts from random fluctuations. For detecting a shift, it is indispensable to delineate the range precisely. We propose a new method for the delineation based on percolation theory. We suggest marking the boundary between the connected and fragmented occurrence of the species (the hull). We demonstrate the advantages of this connectivity‐based method on simulated examples in which a metapopulation is advancing vs retreating along an environmental gradient with different velocities. The simulations show that the hull is a fractal and has the same dimension (7/4) even when the front is advancing or retreating relatively fast, compared to the generation time. It is particularly robust in the retreating (trailing) edge. Accordingly, we propose marking the range edge at the mean position of the hull, the 'connectivity limit' of the species. Theoretical considerations suggest that the position of the connectivity limit is statistically more reliable than those limits that are delineated according to the outermost occurrences, and the connectivity‐based method is broadly applicable to real‐life data. [ABSTRACT FROM AUTHOR]

Climate change is affecting species distribution, composition of biological communities, and species traits. Despite the growing body of knowledge on the reaction of species to climate change, the potentially delayed response of species is still severely understudied. In this paper we modelled the time needed by ground-living invertebrates to effectively react to habitat modification induced by climate change in relation to dispersal abilities. We analyzed the occurrence pattern of alpine ground beetles (carabids) along areas recently freed by retreating glaciers in the central-eastern Italian Alps, to test how the synergic effects of time since deglaciation and environmental factors may affect the colonisation process. Different times of response to climate change in ground beetles were found. Sites already hosting the land cover type suitable for our study taxon, but ice-free for less than 100 yr, are mainly colonised by winged carabid beetles (which have high dispersal abilities and are mostly habitat generalists). No, or very few, wingless species (slow colonizers and ecologically specialized) occur within those sites. The overall pattern suggests that within a site, suitable land cover is established prior to colonization, due to a strong joint effect of time since deglaciation and land cover type. Long-lasting habitat development at the fine scale is likely to result in a lack of specific resources (e.g. food items, or microhabitat), which is likely to contribute to delayed colonisation, which potentially could be tied also to dispersal abilities. Whatever the reason, the existence of a time-lag often equal to or greater than 100 yr in species colonisation implies caution in predicting species' occurrence shifts following climate change. [ABSTRACT FROM AUTHOR]

The MaxEnt software package is one of the most popular tools for species distribution and environmental niche modeling, with over 1000 published applications since 2006. Its popularity is likely for two reasons: 1) MaxEnt typically outperforms other methods based on predictive accuracy and 2) the software is particularly easy to use. MaxEnt users must make a number of decisions about how they should select their input data and choose from a wide variety of settings in the software package to build models from these data. The underlying basis for making these decisions is unclear in many studies, and default settings are apparently chosen, even though alternative settings are often more appropriate. In this paper, we provide a detailed explanation of how MaxEnt works and a prospectus on modeling options to enable users to make informed decisions when preparing data, choosing settings and interpreting output. We explain how the choice of background samples reflects prior assumptions, how nonlinear functions of environmental variables (features) are created and selected, how to account for environmentally biased sampling, the interpretation of the various types of model output and the challenges for model evaluation. We demonstrate MaxEnt's calculations using both simplified simulated data and occurrence data from South Africa on species of the flowering plant family Proteaceae. Throughout, we show how MaxEnt's outputs vary in response to different settings to highlight the need for making biologically motivated modeling decisions. [ABSTRACT FROM AUTHOR]

The role of climate variability in determining the fluctuations of fish populations had been a traditional problem in ecology. In this paper, we studied the role of the Southern Oscillation Index (SO) and the Pacific Decadal Oscillation (PDO) on the population dynamics of the western stock of the skipjack tuna Katsuwonus pelamis. Our analysis was based in three sequential steeps: a diagnostic approach to deduce what kind of population dynamic model should be more appropriate, the modelling of capture per unit of effort data through a logistic model, and the use of population dynamic theory for analyzing the effect of exogenous perturbations. We find that direct and one-year lagged negative PDO effects and one-year lagged negative SO effects were needed to explain annual tuna fluctuations. Models including the combined effects of these climatic indexes explain 80% of the variance in tuna fluctuations. In addition, these models provided very accurate predictions of independent skipjack tuna observed dynamics. This result is encouraging because the inherent variability in CPUE data and the not well determined link between climate and ecological processes. Finally, this study demonstrates that simple models can offer reasonable explanations and accurate predictions of tuna fluctuations, provided they are based on a sound theoretical framework. [ABSTRACT FROM AUTHOR]

Variation in plant functional traits has been related to variation in environmental conditions. In particular, the relationship between leaf traits and climate has received much attention. This paper presents a functional-trait-centred approach to identify potential impacts of climate and land use change on plant species assemblages. Using species atlas data, we modelled the relative frequencies of species with different leaf anatomies (LARF) as a function of observed climate and land use data on a regular spatial grid across Germany. Subsequently, we projected the geographical distribution of LARF with simulated climate and land use data for the late 21st century under two future scenarios. We used a conditional autoregressive regression model to account for spatially structured variation in LARF that remained unexplained by the environmental factors considered. We found a clear relationship between the climatic gradient of water availability and shifts in LARF: increasing water deficit was associated with a decreasing proportion of species with hygromorphic leaves in the composition and increasing proportions of species with scleromorphic and mesomorphic leaves. The variation in LARF due to land use was only small. Under future environmental scenarios the proportion of species with hygromorphic leaves was projected to decrease in all parts of Germany, whereas the proportions of species with sclero- and mesomorphic leaves were projected to increase on average. In particular, Germany's south-western and north-eastern areas were projected to experience functional change in LARF. Our study highlights the relationship between functional traits and plant species vulnerability to climate change. Our results suggest that the functional-trait-centred approach can provide a powerful additional modelling tool to estimate potential impacts of climate change on plant species assemblages. [ABSTRACT FROM AUTHOR]

Species distribution models have been widely used to predict species distributions for various purposes, including conservation planning, and climate change impact assessment. The success of these applications relies heavily on the accuracy of the models. Various measures have been proposed to assess the accuracy of the models. Rigorous statistical analysis should be incorporated in model accuracy assessment. However, since relevant information about the statistical properties of accuracy measures is scattered across various disciplines, ecologists find it difficult to select the most appropriate ones for their research. In this paper, we review accuracy measures that are currently used in species distribution modelling (SDM), and introduce additional metrics that have potential applications in SDM. For the commonly used measures (which are also intensively studied by statisticians), including overall accuracy, sensitivity, specificity, kappa, and area and partial area under the ROC curves, promising methods to construct confidence intervals and statistically compare the accuracy between two models are given. For other accuracy measures, methods to estimate standard errors are given, which can be used to construct approximate confidence intervals. We also suggest that as general tools, computer-intensive methods, especially bootstrap and randomization methods can be used in constructing confidence intervals and statistical tests if suitable analytic methods cannot be found. Usually, these computer-intensive methods provide robust results. [ABSTRACT FROM AUTHOR]

Determining the potential range of invasive alien species under current conditions is important. However, we also need to consider future distributions under scenarios of climate change and different management interventions when formulating effective long-term intervention strategies. This paper combines niche modelling and fine-scale process-based modelling to define regions at high risk of invasion and simulate likely dynamics at the landscape scale. Our study species is Schinus molle (Peruvian pepper tree; Anacardiaceae), a native of central South America, introduced to South Africa in about 1850 where it was widely planted along roads. Localities of planted and naturalized trees were mapped along 5380 km of roads - a transect that effectively samples a large part of western South Africa. Correlative modelling was used to produce profiles of present and future environmental conditions characterizing its planted and naturalized ranges. A cellular-automata simulation model was used to estimate the dynamics of S. molle under future climates and different management scenarios. The overall potential range of S. molle in the region is predicted to shrink progressively with predicted climate change. Some of the potential range of S. molle defined based on current conditions (including areas where it is currently highly invasive) is likely to become less favourable. The species could persist where it is well established long after conditions for recruitment have deteriorated. Some areas where the species is not widely naturalized now (notably the fynbos biome) are likely to become more favourable. Our modelling approach allows for the delineation of areas likely to be invaded in future by considering a range of factors at different scales that mediate the interplay of climatic variables and other drivers that define the dimensions of human intervention such as distance from planted trees and the density of planted plants, both of which affect propagule pressure. [ABSTRACT FROM AUTHOR]

Global climate change generated by human activities is likely to affect agroecosystems in several ways: reinforcing intensification in northern and western Europe, and extensification in the Mediterranean countries. If we are to predict the consequences of global warming for wildlife, distribution models have to include climate data. The METEOSAT temporal series from EWBMS offers an attractive alternative to using climatic surfaces derived from ground stations. The aim of this paper is to test whether this climatic satellite data can improve the distribution models obtained previously by Suárez-Seoane et al. using habitat variables for three agro-steppe bird species: great bustard, little bustard and calandra lark in Spain. Rainfall, radiation balance, evapotranspiration and soil moisture images were incorporated together with the other variables used as predictors in the published stepwise GAM models. Changes in the predicted distributions from the habitat only and climate-habitats models were assessed by reference to the CORINE land cover categories. Inclusion of climatic variables from METEOSAT led to statistically superior models for all three species. There were large differences in the climatic variables selected and the original variables dropped among the species. Evapotranspiration variables were the most frequently selected. Maps of the differences between the habitat and climate-habitat models showed very different patterns for the three species. Inclusion of climate variables led to a wider range of land cover types being deemed suitable. Despite the statistical superiority of models, care is needed in deciding whether to use climatic variables because they may emphasize the fundamental rather than the realized niche. Used together, however, habitat and climate models can provide new insights into factors limiting species distributions and how they may respond to climate change. [ABSTRACT FROM AUTHOR]

Populations along geographical range limits are often exposed to unsuitable climate and low resource availability relative to core populations. As such, there has been a renewed focus on understanding the factors that determine range limits to better predict how species will respond to global change. Using recent theory on range limits and classical understanding of density dependence, we evaluated the influence of resource availability on the snowshoe hare Lepus americanus along its trailing range edge. We estimated variation in population density, habitat use, survival, and parasite loads to test the Great Escape Hypothesis (GEH), i.e. that density dependence determines, in part, a species' persistence along trailing edges. We found that variability in resource availability affected density and population fluctuations and led to trade‐offs in survival for snowshoe hare populations in the northeastern USA. Hares living in resource‐limited environments had lower and less variable population density, yet higher survival and lower parasitism compared to populations living in resource‐rich environments. We suggest that density‐dependent dynamics, elicited by resource availability, provide hares a unique survival advantage and partly explain persistence along their trailing edge. We hypothesize that this low‐density escape from predation and parasitism occurs for other prey species along trailing edges, but the extent to which it occurs is likely conditional on the quality of matrix habitat. Our work indicates that biotic factors play an important role in shaping species' trailing edges and more detailed examination of non‐climatic factors is warranted to better inform conservation and management decisions. [ABSTRACT FROM AUTHOR]

Plant traits are useful for predicting how species may respond to environmental change and/or influence ecosystem properties. Understanding the extent to which traits vary within species and across climatic gradients is particularly important for understanding how species may respond to climate change. We explored whether climate drives spatial patterns of intraspecific trait variation for three traits (specific leaf area (SLA), plant height, and leaf nitrogen content (Nmass)) across 122 grass species (family: Poaceae) with a combined distribution across six continents. We tested the hypothesis that the sensitivity (i.e. slope) of intraspecific trait responses to climate across space would be related to the species' typical form and function (e.g. leaf economics, stature and lifespan). We observed both positive and negative intraspecific trait responses to climate with the distribution of slope coefficients across species straddling zero for precipitation, temperature and climate seasonality. As hypothesized, variation in slope coefficients across species was partially explained by leaf economics and lifespan. For example, acquisitive species with nitrogen‐rich leaves grew taller and produced leaves with higher SLA in warmer regions compared to species with low Nmass. Compared to perennials, annual grasses invested in leaves with higher SLA yet decreased height and Nmass in regions with high precipitation seasonality (PS). Thus, while the influence of climate on trait expression may at first appear idiosyncratic, variation in trait–climate slope coefficients is at least partially explained by the species' typical form and function. Overall, our results suggest that a species' mean location along one axis of trait variation (e.g. leaf economics) could influence how traits along a separate axis of variation (e.g. plant size) respond to spatial variation in climate. [ABSTRACT FROM AUTHOR]

The distribution ranges and spatio‐temporal patterns in the occurrence and activity of boreal bats are yet largely unknown due to their cryptic lifestyle and lack of suitable and efficient study methods. We approached the issue by establishing a permanent passive‐acoustic sampling setup spanning the area of Finland to gain an understanding on how latitude affects bat species composition and activity patterns in northern Europe. The recorded bat calls were semi‐automatically identified for three target taxa; Myotis spp., Eptesicus nilssonii or Pipistrellus nathusii and the seasonal activity patterns were modeled for each taxa across the seven sampling years (2015–2021). We found an increase in activity since 2015 for E. nilssonii and Myotis spp. For E. nilssonii and Myotis spp. we found significant latitude ‐dependent seasonal activity patterns, where seasonal variation in patterns appeared stronger in the north. Over the years, activity of P. nathusii increased during activity peak in June and late season but decreased in mid season. We found the passive‐acoustic monitoring network to be an effective and cost‐efficient method for gathering bat activity data to analyze spatio‐temporal patterns. Long‐term data on the composition and dynamics of bat communities facilitates better estimates of abundances and population trend directions for conservation purposes and predicting the effects of climate change. [ABSTRACT FROM AUTHOR]

Pioneer naturalists such as Whewell, Lyell, Humboldt, Darwin and Wallace acknowledged the interactions between ecological and evolutionary forces, as well as the roles of continental movement, mountain formation and climate variations, in shaping biodiversity patterns. Recent developments in computer modelling and paleo‐environmental reconstruction have made it possible for scientists to study in silico how biodiversity emerges from eco‐evolutionary and environmental dynamic processes and their interactions. Simulating emergent biodiversity enables the experimentation of multiple interconnected hypotheses in a largely fragmented scientific landscape, with the final objective of successfully approximating natural mechanisms (i.e. hypothetical spatio–temporally unrestricted generalizations that hold across multiple empirical biodiversity patterns). This new interdisciplinary approach opens unprecedented scientific pathways, facilitating the communication and contemplation of causal implications of complex eco‐evolutionary and environmental interactions. In this review I provide a comprehensive overview of the available population‐based spatially explicit mechanistic eco‐evolutionary models (MEEMs) that rely on paleo‐environmental reconstructions, critically discussing their relevance and limitations for our understanding of biodiversity. To achieve this, I first introduce diverse biodiversity models and contextualize MEEMs. Second, I define MEEMs and synthesize the major insights from studies using MEEMs combined with deep‐time environmental dynamics (> 0.1 Ma). Lastly, I discuss the challenges and perspectives of solving long‐standing biodiversity enigmas by coupling eco‐evolutionary mechanisms with deep‐time environmental dynamics. Studies show that linking dynamic environments and eco‐evolutionary processes is necessary to reproduce multiple large‐scale biodiversity patterns simultaneously. Mechanisms related to adaptations (e.g. niche evolution), dispersal abilities and other eco‐evolutionary interactions (e.g. those resulting in speciation or extinction events) show universal importance, although their signatures across spatial and temporal scales remain largely unknown. Investigations with MEEMS spanning multiple levels of complexity in space and time foster interdisciplinary cooperation across the natural sciences and show promise for solving some of the enigmas in Earth's biodiversity. [ABSTRACT FROM AUTHOR]

Recent global warming affects species compositions at an unprecedented rate. To predict climate‐induced changes in species assemblages, a better understanding of the link between species occurrence and climate is needed. Macrofungal fruit body assemblages are correlated with the thermal environment at the European scale. However, it is still unknown whether macrofungal communities are also phylogenetically structured by thermal environments. Thermal environments are characterized by annual temperature means but also by intra‐annual temperature variability (hereafter termed temperature seasonality), which are both considered in this study. Here, we used distribution data of 2882 species based on fruit body records across Europe to address two main questions: 1) are mushroom assemblages at the extremes of the mean (warm and cold) and seasonal (high intra‐annual variability, i.e. continental) climate gradient phylogenetically more similar than expected (phylogenetic alpha diversity); 2) are mushroom assemblages, that are subject to different mean and seasonal temperature conditions, composed of different lineages (phylogenetic beta diversity). Our phylogenetic alpha diversity analysis shows that mushroom assemblages are phylogenetically structured by warm and cold environments, indicating that phylogenetically related species with similar traits thrive under more extreme conditions. In contrast, assemblages are phylogenetically more dissimilar (overdispersed) in temperature seasonal environments, indicating limiting similarity. Phylogenetic beta diversity was significantly correlated with mean and seasonal temperature differences, a response mainly driven by a few genera. Our results show that macrofungal assemblages are phylogenetically structured by temperature across Europe, suggesting phylogenetically constrained specialization towards temperature extremes. Predicted anthropogenic warming is likely to affect species composition and phylogenetic diversity with additional consequences for the carbon‐ and nutrient cycles. [ABSTRACT FROM AUTHOR]

Alpine ecosystems are hotspots of biodiversity despite their cold climates. Here we investigate spatial patterns in the phylogenetic diversity (i.e. the degree of species relatedness) of European alpine floras and quantify the influence of climatic conditions since the late Pleistocene and historical climatic instability in shaping these patterns. We collected species‐pool data for 22 alpine regions in central and southern Europe and calculated phylogenetic diversity within and between regions using two metrics sensitive to terminal branching in the phylogeny. We regressed phylogenetic diversity against macroclimatic variables representing seasonal extremes between the Last Glacial Maximum (LGM; 21 000 years BP) and the present at 1000‐year intervals. We found the lowest phylogenetic diversity in the Carpathians and the central Alps, and the highest in the north‐eastern and southern Iberian Peninsula. Phylogenetic diversity decreased with temperature seasonality and low winter temperature. While the effect of temperature seasonality was relatively constant over time, the influence of winter temperature decreased after the LGM. We also found that phylogenetic diversity decreased with historical climatic instability. Between regions, phylogenetic diversity was mainly explained by current climatic distance rather than geographic distance, suggesting that alpine floras were primarily driven by species sorting along climatic gradients. Our results confirm the role of environmental filtering in shaping the current phylogenetic diversity of alpine floras, resulting in more closely related lineages in regions with relatively cold and unstable climates. We also highlight the importance of explicitly incorporating climatic variation through time to better understand the processes structuring the current biodiversity of alpine floras. [ABSTRACT FROM AUTHOR]

Although species distribution models (SDMs) are commonly used to hindcast fine‐scale population metrics, there remains a paucity of information about how well these models predict future responses to climate. Many conventional SDMs rely on spatially‐explicit but time‐invariant conditions to quantify species distributions and densities. We compared these status quo 'static' models with more climate‐informed 'dynamic' SDMs to assess whether the addition of time‐varying processes would improve hindcast performance and/or forecast skill. Here, we present two groundfish case studies from the Bering Sea – a high latitude system that has recently undergone considerable warming. We relied on conventional statistics (R2, % deviance explained, UBRE or GCV) to evaluate hindcast performance for presence–absence, numerical abundance and biomass of arrowtooth flounder Atheresthes stomias and walleye pollock Gadus chalcogrammus. We then used retrospective skill testing to evaluate near‐term forecast skill. Retrospective skill testing enables direct comparisons between forecasts and observations through a process of fitting and forecasting nested submodels within a given time series. We found that the inclusion of time‐varying covariates improved hindcasts. However, dynamic models either did not improve or decreased forecast skill relative to static SDMs. This is likely a result of rapidly changing temperatures within the ecosystem, which required models to predict species responses to environmental conditions that were outside the range of observed values. Until additional model development allows for fully dynamic predictions, static model forecasts (or persistence forecasts from dynamic models) may serve as reliable placeholders, especially when anomalous conditions are anticipated. Nonetheless, our findings demonstrate support for the use of retrospective skill testing rather than selecting forecast models a priori based on their ability to quantify species–habitat associations in the past. [ABSTRACT FROM AUTHOR]

Herbarium records provide a broad spatial and temporal range with which to investigate plant responses to environmental change. Research on plant phenology and its sensitivity to climate has advanced with the increasing availability of digitized herbarium specimens, but limitations of specimen‐derived data can undermine the inferences derived from such research. One issue that has received little attention is collection site uncertainty (i.e. error distance), a measure of confidence in the location from which a specimen was collected. We conducted comparative analyses of phenoclimatic models to determine whether spatial deviations of 2, 5, 15 or 25 km between recorded and simulated collection sites, as well as the error distance reported in digitized records, affect estimates of the phenological sensitivity of flowering time to annual temperature and precipitation in a widespread annual California wildflower. In this approach, we considered both spatial and interannual variation in climatic conditions. Simulated site displacements led to increasingly weak estimates of phenological sensitivity to temperature and precipitation anomalies with increasing distances. However, we found no significant effect of reported error distance magnitude on estimates of phenological sensitivity to climate normals or anomalies. These findings suggest that the spatial uncertainty of collection sites among specimens of widely collected plant species may not adversely affect estimates of phenological sensitivity to climate, even though real discrepancies and georeferencing inaccuracy can negatively impact such estimates. Collection site uncertainty merits further attention as a potential source of noise in herbarium data, especially for research on how plant traits respond to spatial and interannual climatic variation. [ABSTRACT FROM AUTHOR]

Understanding the effects of climate change on the phenological structure of plant communities will require measuring variation in sensitivity among thousands of co‐occurring species across regions. Herbarium collections provide vast resources with which to do this, but may also exhibit biases as sources of phenological data. Despite general recognition of these caveats, validation of herbarium‐based estimates of phenological sensitivity against estimates obtained using field observations remains rare and limited in scope. Here, we leveraged extensive datasets of herbarium specimens and of field observations from the USA National Phenology Network for 21 species in the United States and, for each species, compared herbarium‐ and field‐based estimates of peak flowering dates expected under standardized temperature conditions, and of sensitivity of peak flowering time to geographic and interannual variation in mean minimum temperatures (TMIN). We found strong agreement between herbarium‐ and field‐based estimates for standardized peak flowering time (r = 0.91, p < 0.001) and for the direction and magnitude of sensitivity to both geographic TMIN variation (r = 0.88, p < 0.001) and interannual TMIN variation (r = 0.82, p < 0.001). This agreement was robust to substantial differences between datasets in 1) the long‐term TMIN conditions observed among collection and phenological monitoring sites and 2) the interannual TMIN conditions observed in the time periods encompassed by both datasets for most species. Our results show that herbarium‐based sensitivity estimates are reliable among species spanning a wide diversity of life histories and biomes, demonstrating their utility in a broad range of ecological contexts, and underscoring the potential of herbarium collections to enable phenoclimatic analysis at taxonomic and spatiotemporal scales not yet captured by observational data. [ABSTRACT FROM AUTHOR]

Thermophilization – changes in community composition towards greater relative abundances of species associated with warmer environments – has been described for plants and animals in many locations around the world. Disturbances of various kinds have increased rates of thermophilization in temperate sites, and this has been proposed, but not demonstrated, for some tropical environments. In this study, we tested whether disturbance by a category 4 hurricane in 1988 (Hurricane Gilbert) increased thermophilization in a Jamaican montane forest by using pre‐ and post‐hurricane data collected over four decades (1974–2014). We analysed tree species composition in permanent plots at ca 1580 m above sea level in Jamaica's Blue Mountains. There were 66 tree species with stem diameters ≥ 3 cm at breast height. We used published data on the altitudinal distribution of 62 species (94% of genetic individuals (genets)) to calculate the mean community altitude scores (MCAS) of the trees recorded in each census, as well as the MCAS of the survivors, recruits and dead trees after each decade. We found that thermophilization did occur (i.e. MCAS decreased significantly over time), and that this was due both to a decreasing MCAS of recruits through the four decades (significantly lower than expected in the last three decades) as well as a high MCAS of trees that died. Thermophilization was fastest in the post‐hurricane decade, during which time there was marked and significant increase in the MCAS of dead trees; this change was above and beyond expectations of long‐term successional dynamics. The rate of compositional change equates to an overall decrease in MCAS of 1.6 m yr−1 over the forty‐year study period. We conclude that this Jamaican montane forest is undergoing thermophilization (likely due to rising temperature) and that the hurricane‐caused disturbance accelerated thermophilization through differential mortality. [ABSTRACT FROM AUTHOR]

Rapid global change has increased interest in developing ways to identify suitable refugia for species of conservation concern. Correlative and mechanistic species distribution models (SDMs) represent two approaches to generate spatially‐explicit estimates of climate vulnerability. Correlative SDMs generate distributions using statistical associations between environmental variables and species presence data. In contrast, mechanistic SDMs use physiological traits and tolerances to identify areas that meet the conditions required for growth, survival and reproduction. Correlative approaches assume modeled environmental variables influence species distributions directly or indirectly; however, the mechanisms underlying these associations are rarely verified empirically. We compared habitat suitability predictions between a correlative‐only SDM, a mechanistic SDM and a correlative framework that incorporated mechanistic layers ('hybrid models'). Our comparison focused on green salamanders Aneides aeneus, a priority amphibian threatened by climate change throughout their disjunct range. We developed mechanistic SDMs using experiments to measure the thermal sensitivity of resistance to water loss (ri) and metabolism. Under current climate conditions, correlative‐only, hybrid and mechanistic SDMs predicted similar overlap in habitat suitability; however, mechanistic SDMs predicted habitat suitability to extend into regions without green salamanders but known to harbor many lungless salamanders. Under future warming scenarios, habitat suitability depended on climate scenario and SDM type. Correlative and hybrid models predicted a 42% reduction or 260% increase in area considered to be suitable depending on the climate scenario. In mechanistic SDMs, energetically suitable habitat declined with both climate scenarios and was driven by the thermal sensitivity of ri. Our study indicates that correlative‐only and hybrid approaches produce similar predictions of habitat suitability; however, discrepancies can arise for species that do not occupy their entire fundamental niche, which may hold consequences of conservation planning of threatened species. [ABSTRACT FROM AUTHOR]

Climatic shifts to warmer and often drier conditions are challenging terrestrial species worldwide. These shifts are occurring more rapidly at higher elevations and latitudes, likely causing disproportionate effects to mammalian hibernators there. While there is some information about how these species' ranges are responding to climatic shifts, we lack an understanding of how climate components are affecting species' life history variation, which is key to individual success and population‐level resilience. We reviewed the literature to identify the direction of life history responses to climate change in mammalian hibernators along three axes: latitudinal, elevational and temporal. We found 39 studies involving 27 species that reported climate effects on our four target life history traits – phenology, body mass/condition and growth, reproduction and survival. We found warmer temperatures are advancing hibernator phenology and increasing reproductive success. By contrast, warming and drying trends are having uncertain effects on body condition, and complex effects on survival – depending on season, age class, latitude and elevation. We found no pattern of significant climate‐trait outcomes by duration or decade of study. More research on drought conditions – particularly in relation to resource availability – would help inform hibernator susceptibility to increased drying trends expected to intensify globally. Notably, our results are highly biased towards small mammal hibernators in Northern Hemisphere alpine/mountain ecosystems, with few long‐term studies conducted on Southern Hemisphere hibernators. This review highlights that phenological shifts constitute one of the most obvious consequences of climate change, yet, the timing of life history events (e.g. timing of migration, reproduction, hibernation) remains poorly understood. Further integration of insights from physiologists, evolutionary biologists and population ecologists working on wild populations will improve our collective understanding of the effects of seasonal climatic shifts on mammalian hibernator life history traits, key drivers of their population‐level persistence. [ABSTRACT FROM AUTHOR]

Landscapes of vertical relief, such as mountains and continental slopes, intensify ecological and climatological variation within narrow spatial windows. Seasonal vertical migrants exploit this variation during their residence in, and movements between, vertically stratified seasonal ranges. Animals in terrestrial, marine and even human‐ecological systems undergo similar patterns of seasonal vertical movements. The diversity of arenas in which vertical migration evolved lends insight to the factors promoting seasonal use of landscapes of relief. Because animals must contend with both endogenous circannual rhythms and exogenous environmental seasonality, vertical migrants may be sensitive to inconsistent change across stratified seasonal ranges under climate change. To better understand how ongoing and future climatic and environmental changes are likely to impact vertical migrants, we examine vertical migration in the context of niche tracking and niche switching. Whereas niche trackers minimize variation in realized environmental conditions throughout their seasonal movements, niche switchers undergo seasonal transitions in realized niche space. These strategies mediate the relationship between migrants and their changing environment, and can be used to forecast impacts of future change and effectively conserve systems of vertical migration. Niche tracking may be hindered by inconsistent or unpredictable environmental change along a single niche axis across strata, while niche switching may be sensitive to incongruous spatiotemporal change across factors. We suggest that climate change will affect seasonal patterns in vertical environments discontinuously across time, space and strata, and that vertical migrants are likely to face additional anthropogenic threats that interact with environmental seasonality. Conservation of vertical migrants should prioritize the availability of, and facilitate movement between, stratified seasonal ranges. [ABSTRACT FROM AUTHOR]

Squamate reptiles exhibit two reproductive modes: oviparity and viviparity. Existing large‐scale studies suggest that viviparous species are more vulnerable to climate warming based on viviparous species occupying relatively colder environments, which are predicted to decline in availability under climate warming. However, oviparous and viviparous squamates are geographically widespread and their distributions often overlap. Are oviparous or viviparous squamates more vulnerable to climate warming when they inhabit similar thermal environments? We used Sceloporus lizards in North America as a model system to predict the impact of climate warming on oviparous and viviparous species in sympatric zones. We used mechanistic models to quantify the changes in maternal energy balance (MEB) and offspring energy balance (OEB) under a climate warming scenario. We then projected the fitness impacts of future climate warming based on estimates of MEB and OEB. Under a climate warming scenario (RCP8.5), oviparous females are predicted to increase reproductive frequency more than viviparous females, which restricts time for postpartum energy accumulation before the end of the season and decreases MEB. Under climate warming, OEB of oviparous species increased more than viviparous species, but the increases were less geographically widespread. Interestingly, the developmental success and OEB of oviparous species are predicted to decline at some sites under climate warming, which is not predicted to happen for viviparous species. Our results highlight that oviparous species will respond more variably to climate warming than viviparous species. More specifically, oviparous species in hot areas with high temperature variation may be especially vulnerable under climate warming compared to sympatric viviparous species. [ABSTRACT FROM AUTHOR]

Large‐scale ecological restoration is crucial for effective biodiversity conservation and combating climate change. However, perspectives on the goals and values of restoration are highly diverse, as are the different approaches to restoration e.g. ranging from the restoration of cultural ecosystems to rewilding. We assess how the future of nature is envisioned in participatory scenarios, focusing on which elements of rewilding and nature contributions to people have been considered in scenario narratives across Europe. We used the Nature Futures Framework archetypes as a template to synthesize pluralistic perspectives of nature. We found that different values of nature are often represented as counteracting elements and fail to integrate the plural views of nature. Nature as Culture was the main archetype found in the scenarios, usually associated with positive impacts on the non‐material benefits to people. Intrinsic values of nature (i.e., Nature forNature) were associated with positive impacts on regulating benefits and negative impacts on material benefits, being the only archetype of future associated with positive impacts on all three components of rewilding. Nature for Society was associated with moderate positive impacts on material and regulatory nature contributions to people. Business as usual futures were associated with negative impacts on regulating and non‐material benefits to people and on all three components of rewilding. Our results highlight two major gaps in the scenarios that should be addressed in participatory restoration planning and models. Firstly, there is a paucity of spatially explicit approaches, with most studies failing to transform the results of participatory scenario planning into model projections. Secondly, we found scenarios that explored co‐benefits between multiple nature perspectives were overall missing from the literature. Novel scenario narratives and approaches that explore synergies among different nature values are needed to design future large‐scale restoration where biodiversity recovery and human well‐being are intrinsically linked and fostered. [ABSTRACT FROM AUTHOR]

Species interactions are known to structure ecological communities. Still, the influence of climate change on biodiversity has primarily been evaluated by correlating individual species distributions with local climatic descriptors, then extrapolating into future climate scenarios. We ask whether predictions on arctic arthropod response to climate change can be improved by accounting for species interactions. For this, we use a 14‐year‐long, weekly time series from Greenland, resolved to the species level by mitogenome mapping. During the study period, temperature increased by 2°C and arthropod species richness halved. We show that with abiotic variables alone, we are essentially unable to predict species responses, but with species interactions included, the predictive power of the models improves considerably. Cascading trophic effects thereby emerge as important in structuring biodiversity response to climate change. Given the need to scale up from species‐level to community‐level projections of biodiversity change, these results represent a major step forward for predictive ecology. [ABSTRACT FROM AUTHOR]

Accelerating climate and land‐use change are rapidly transforming Earth's biodiversity. While there is substantial evidence on the exposure and vulnerability of biodiversity to global change at the species level, the global exposure of intraspecific genetic diversity (GD) is still unknown. Here, we assess the exposure of mitochondrial GD to mid‐21st century climate and land‐use change in terrestrial mammal assemblages at grid‐cell and bioclimatic region scales under alternative narratives of future societal development. We used global predictions of mammal GD distribution based on thousands of georeferenced mitochondrial genes for hundreds of mammal species, the latest generation of global climate models from the ongoing sixth phase of the Coupled Model Intercomparison Project (CMIP6), and global future projections of land‐use prepared for CMIP6. We found that more than 50% of the genetically poorest geographic areas (grid‐cells), primarily distributed in tundra, boreal forests/taiga and temperate bioclimatic regions, will be exposed to mean annual temperature rise that exceeds 2°C compared to the baseline period under all considered future scenarios. We also show that at least 30% of the most genetically rich areas in tropical, subtropical and montane regions will be exposed to an increase of mean annual temperature > 2°C under less optimal scenarios. Genetic diversity in these rich regions is also predicted to be exposed to severe reductions of primary vegetation area and increasing human activities (an average loss of 5–10% of their total area under the less sustainable land‐use scenarios). Our findings reveal a substantial exposure of mammal GD to the combined effects of global climate and land‐use change. Meanwhile the post‐2020 conservation goals are overlooking genetic diversity, our study identifies both genetically poor and highly diverse areas severely exposed to global change, paving the road to better estimate the geography of biodiversity vulnerability to global change. [ABSTRACT FROM AUTHOR]

Habitat suitability estimated with probability of occurrence in species distribution models (SDMs) is used in conservation to identify geographic areas that are most likely to harbor individuals of interest. In theory, probability of occurrence is coupled with individual fitness so that individuals have higher fitness at the centre of their species environmental niche than at the edges, which we here define as 'fitness‐centre' hypothesis. However, such relationship is uncertain and has been rarely tested across multiple species. Here, we quantified the relationship between coarse‐scale probability of occurrence projected with SDMs and individual fitness in 66 tree species native of North America. We used 1) field data of individuals' growth rate (height and diameter standardized by age) available from the United States Forest Inventory Analysis plots; and 2) common garden data collected from 23 studies reporting individual growth rate, survival, height and diameter of individuals originated from different provenances in United States and Canada. We show 'fitness–centre' relationships are rare, with only 12% and 11% of cases showing a significant positive correlation for field and common garden data, respectively. Furthermore, we found the 'fitness–centre' relationship is not affected by the precision of the SDMs and it does not depend upon dispersal ability and climatic breath of the species. Thus, although the 'fitness–centre' relationship is supported by theory, it does not hold true in nearly any species. Because individual fitness plays a relevant role in buffering local extinction and range contraction following climatic changes and biotic invasions, our results encourage conservationists not to assume the 'fitness–centre' relationship when modelling species distribution. [ABSTRACT FROM AUTHOR]

Environmental stress from abiotic conditions imposes physiological limits on individuals within communities, and these stressful conditions can act as a filter on the species present in any given environment. Such abiotic stressors can reduce a community's diversity and make its composition more phylogenetically clustered. Using a decade of staphylinid beetle (Staphylinidae, Coleoptera, rove beetles) collections made across a 1500 m elevation gradient in northwestern Costa Rica (2008–2017) we asked what species lived there, how large and overlapping were the communities across this gradient, and what relationship was there between elevation and diversity. Using DNA barcodes for identification and phylogenetic estimates of community structure, we found high turnover across elevation, and that staphylinid diversity increased linearly with elevation. Because of this, we found staphylinid diversity was negatively related to surface area and temperature, and positively with precipitation. We suggest that historical biogeography and contemporary environmental stress have combined to produce these observed patterns. The forests in which these beetles are found are heating and drying rapidly and our finding that diversity increases with elevation suggests that there will be catastrophic biodiversity loss in the coming decades. [ABSTRACT FROM AUTHOR]

Body size is a key parameter of organism fitness. While the impact of climate change on body size has received increasing attention, the long‐term consequences of landscape fragmentation are still poorly known. These two major global threats may potentially induce opposite trends: the decrease of body size in warmer environments (e.g. individuals developing faster) or the selection of larger individuals in fragmented habitats (e.g. large individuals more capable of reaching distant patches). We assessed the relationship between temperature and landscape fragmentation with mean body size during the last century, within four European regions (Austria, Belgium, England and above the Arctic circle in Scandinavia) and among queens of five bumblebee species. At the regional scale, we first analysed the variation over time of body size and the two hypothesised drivers, temperature and landscape fragmentation. Then, at the local landscape scale, we tested whether body size varied according to these drivers irrespective of the region. At the regional level, we observed a statistically clear increase of queen body size corresponding to an increase of landscape fragmentation (i.e. in Belgium and England). There was no increase of size when fragmentation did not increase (i.e. in Austria and above the Arctic Circle). Temperature also increased through time in all regions. At the local landscape scale, we found that all species were impacted by changes in both climate and landscape fragmentation but show different trends. The body size of the two largest species significantly increased at landscape level with higher fragmentation while body size of the two smallest species decreased with higher fragmentation. We highlight that, in a context of global changes, landscape fragmentation can also be a major driver of body size clines. Depending on the dispersal abilities of species, larger species could be positively selected for and overcome landscape fragmentation. [ABSTRACT FROM AUTHOR]

Globally, treeline ecotones vary from abrupt lines to extended zones of increasingly small, stunted and/or dispersed trees. These spatial patterns contain information about the processes that control treeline dynamics. Describing these patterns consistently along ecologically meaningful dimensions is needed for generalizing hypotheses and knowledge about controlling processes and expected treeline shifts globally. However, existing spatial categorizations of treelines are very loosely defined, leading to ambiguities in their use and interpretation. To help better understand treeline‐forming processes, we present a new framework for describing alpine treeline ecotones, focusing on hillside‐scale patterns, using pattern dimensions with distinct indicative values: 1) the spatial pattern in the x‐y plane: a) decline in tree cover, and b) change in the level of clustering. Variation along these dimensions results in more or less 'discrete' or 'diffuse' treelines with or without islands. These patterns mainly indicate demographic processes: establishment and mortality. 2) Changes in tree stature: a) decline in tree height, and b) change in tree shape. Variation along these dimensions results in more or less 'abrupt' or 'gradual' treelines with or without the formation of environmental krummholz. These patterns mainly indicate growth and dieback processes. Additionally, tree population structure can help distinguish alternative hypotheses about pattern formation, while analysing the functional composition of the ecotonal vegetation is essential to understand community‐level processes, controlled by species‐specific demographic processes. Our graphical representation of this framework can be used to place any treeline pattern in the proposed multi‐dimensional space to guide hypotheses on underlying processes and associated dynamics. To quantify the dimensions and facilitate comparative research, we advocate a joint effort in gathering and analysing spatial patterns from treelines globally. The improved recognition of treeline patterns should allow more effective comparative research and monitoring and advance our understanding of treeline‐forming processes and vegetation dynamics in response to climate warming. [ABSTRACT FROM AUTHOR]

Coincident with recent global warming, species have shifted their geographic distributions to cooler environments, generally by moving along thermal axes to higher latitudes, higher elevations or deeper waters. While these shifts allow organisms to track their thermal niche, these three thermal axes also covary with non‐climatic abiotic factors that could pose challenges to range‐shifting plants and animals. Such novel abiotic conditions also present an unappreciated pitfall for researchers – from both empirical and predictive viewpoints – who study the redistribution of species under global climate change. Climate, particularly temperature, is often assumed to be the primary abiotic factor in limiting species distributions, and decades of thermal biology research have made the correlative and mechanistic understanding of temperature the most accessible and commonly used response to any abiotic factor. Receiving far less attention, however, is that global gradients in oxygen, light, pressure, pH and water availability also covary with latitude, elevation, and/or ocean depth, and species show strong physiological and behavioral adaptations to these abiotic variables within their historic ranges. Here, we discuss how non‐climatic abiotic factors may disrupt climate‐driven range shifts, as well as the variety of adaptations species use to overcome abiotic conditions, emphasizing which taxa may be most limited in this capacity. We highlight the need for scientists to extend their research to incorporate non‐climatic, abiotic factors to create a more ecologically relevant understanding of how plants and animals interact with the environment, particularly in the face of global climate change. We demonstrate how additional abiotic gradients can be integrated into global climate change biology to better inform expectations and provide recommendations for addressing the challenge of predicting future species distributions in novel environments. [ABSTRACT FROM AUTHOR]

The world is spatially autocorrelated. Both abiotic and biotic properties are more similar among neighboring than distant locations, and their temporal co‐fluctuations also decrease with distance. P. A. P. Moran realized the ecological importance of such 'spatial synchrony' when he predicted that isolated populations subject to identical log‐linear density‐dependent processes should have the same correlation in fluctuations of abundance as the correlation in environmental noise. The contribution from correlated weather to synchrony of populations has later been coined the 'Moran effect'. Here, we investigate the potential role of the Moran effect in large‐scale ecological outcomes of global warming. Although difficult to disentangle from dispersal and species interaction effects, there is compelling evidence from across taxa and ecosystems that spatial environmental synchrony causes population synchrony. Given this, and the accelerating number of studies reporting climate change effects on local population dynamics, surprisingly little attention has been paid to the implications of global warming for spatial population synchrony. However, a handful of studies of insects, birds, plants, mammals and marine plankton indicate decadal‐scale changes in population synchrony due to trends in environmental synchrony. We combine a literature review with modeling to outline potential pathways for how global warming, through changes in the mean, variability and spatial autocorrelation of weather, can impact population synchrony over time. This is particularly likely under a 'generalized Moran effect', i.e. when relaxing Moran's strict assumption of identical log‐linear density‐dependence, which is highly unrealistic in the wild. Furthermore, climate change can influence spatial population synchrony indirectly, through its effects on dispersal and species interactions. Because changes in population synchrony may cascade through food‐webs, we argue that the (generalized) Moran effect is key to understanding and predicting impacts of global warming on large‐scale ecological dynamics, with implications for extinctions, conservation and management. [ABSTRACT FROM AUTHOR]

Widespread declines in farmland biodiversity have led to state‐funded schemes which take land out of production to create (semi‐)natural habitats for biodiversity (e.g. EU agri‐environment schemes; US Conservation Reserve Program). Common features of such schemes are grassland strips at the edges of agricultural fields, and we examine potential co‐benefits of these biodiversity set‐asides for contributing to grassland connectivity. Although set‐aside strips had negligible impact on landscape‐scale species persistence (using metapopulation models parameterized for flying insects run on 267 landscapes of ~30 000 ha across England), they nonetheless improved connectivity in 74% (198/267) of landscapes (comparing landscapes with and without set‐asides), as shown by range expansion rates increasing by up to 100%. Benefits of set‐aside strips varied according to species type (high/low dispersal, high/low population density), but had little benefit for species with low dispersal and small population sizes, which generally failed to expand. High dispersal/high density species were already successful expanders regardless of set‐asides (> 75% of simulations were successful without set‐asides) although expansion rates were still improved when set‐asides were added. Whilst alternative strategies for placement of set‐aside strips (more/less aggregated), revealed no consensus 'better' strategy across species types, set‐aside benefits were generally greatest in landscapes with intermediate availability of semi‐natural grassland (0.5‐4% cover). We conclude that small‐scale set‐asides have the potential to improve connectivity, which we expect to help some species track climate change, and connect habitat patches within existing climate space for others. However, set‐asides are unlikely to benefit low dispersal species which are probably at greatest risk from agricultural intensification. [ABSTRACT FROM AUTHOR]

The Neotropical region exhibits the greatest worldwide diversity and the diversification history of several clades is related to the puzzling geomorphologic and climatic history of this region. The freshwater Amazon ecoregion contains the main hydrographic basins of the Neotropical region that are highly dendritic and ecologically diverse. It contains a rich and endemic fish fauna, including one of its most iconic and economically important representatives, the bony‐tongue Arapaima gigas (Teleostei, Osteoglossiformes). Here, we evaluated the projected distribution of the genus in different historical periods (Present, Last Glacial Maximum, Last Interglacial Maximum and Near Future) and interpreted these results in light of the genomic diversity and modeled historical demography. For that, we combined species distribution models, population genetic analysis using SNPs and deep learning model selection. We analyzed a representative sample of the genus from the two basins where it naturally occurs, four localities in the Amazon (Am) and three in the Tocantins‐Araguaia (To‐Ar) basin, as well as individuals from three fish farms. We inferred a potentially smaller distribution in the glacial period, with a possible refuge in central Am. Our genetic data agrees with this result, suggesting a higher level of genetic diversity in the Am basin, compared to that observed in To‐Ar. Our deep learning model comparison indicated that the To‐Ar basin was colonized by the population from the Am basin. Considering a global warming scenario in the near future, A. gigas could reach an even larger range, especially if anthropogenic related dispersal occurs, potentially invading new areas and impacting their communities. [ABSTRACT FROM AUTHOR]

Mechanisms underlying species richness patterns remain a central yet controversial issue in biology. Climate has been regarded as a major determinant of species richness. However, the relative influences of different evolutionary processes, (i.e. niche conservatism, diversification rate and time for speciation) on species richness–climate relationships remain to be tested. Here, using newly compiled distribution maps for 11 422 woody plant species in eastern Eurasia, we estimated species richness patterns for all species and for families with tropical and temperate affinities separately, and explored the phylogenetic signals in species richness patterns of different families and their relationships with contemporary climate and climate change since the Last Glacial Maximum (LGM). We further compared the effects of niche conservatism (represented by contemporary‐ancestral climatic niches differences), diversification rate and time for speciation (represented by family age) on variation in the slopes of species richness–climate relationships. We found that winter coldness was the best predictor for species richness patterns of most tropical families while Quaternary climate change was the best predictor for those of most temperate families. Species richness patterns of closely‐related families were more similar than those of distantly‐related families within eudicots, and significant phylogenetic signals characterized the slopes of species richness–climate relationships across all angiosperm families. Contemporary‐ancestral climatic niche differences dominated variation in the relationships between family‐level species richness and most climate variables. Our results indicate significant phylogenetic conservatism in family‐level species richness patterns and their relationships with contemporary climate within eudicots. These findings shed light on the mechanisms underlying large‐scale species richness patterns and suggest that ancestral climatic niche may influence the evolution of species richness–climate relationships in plants through niche conservatism. [ABSTRACT FROM AUTHOR]

The catastrophic loss of large‐bodied mammals during the terminal Pleistocene likely led to cascading effects within communities. While the extinction of the top consumers probably expanded the resources available to survivors of all body sizes, little work has focused on the responses of the smallest mammals. Here, we use a detailed fossil record from the southwestern United States to examine the response of the hispid cotton rat Sigmodon hispidus to biodiversity loss and climatic change over the late Quaternary. In particular, we focus on changes in diet and body size. We characterize diet through carbon (δ13C) and nitrogen (δ15N) isotope analysis of bone collagen in fossil jaws and body size through measurement of fossil teeth; the abundance of material allows us to examine population level responses at millennial scale for the past 16 ka. Sigmodon was not present at the cave during the full glacial, first appearing at ~16 ka after ice sheets were in retreat. It remained relatively rare until ~12 ka when warming temperatures allowed it to expand its species range northward. We find variation in both diet and body size of Sigmodon hispidus over time: the average body size of the population varied by ~20% (90–110 g) and mean δ13C and δ15N values ranged between −13.5 to −16.5‰ and 5.5 to 7.4‰ respectively. A state–space model suggested changes in mass were influenced by diet, maximum temperature and community structure, while the modest changes in diet were most influenced by community structure. Sigmodon maintained a fairly similar dietary niche over time despite contemporaneous changes in climate and herbivore community composition that followed the megafauna extinction. Broadly, our results suggest that small mammals may be as sensitive to shifts in local biotic interactions within their ecosystem as they are to changes in climate and large‐scale biodiversity loss. [ABSTRACT FROM AUTHOR]

Rapid human population growth has driven conversion of land for uses such as agriculture, transportation and buildings. The removal of natural vegetation changes local climate, with human‐dominated land uses often warmer and drier than natural habitats. Yet, it remains an open question whether land‐use changes influence the composition of ecological assemblages in a direction consistent with the mechanism of local climatic change. Here, we used a global database of terrestrial vertebrates (mammals, birds, reptiles and amphibians) to test whether human‐dominated land uses systematically favour species with distinctive realised climatic niches. We 1) explored the responses of community‐average temperature and precipitation niches to different types of land use, 2) quantified the abundances of species with distinctive climatic niches across land uses and 3) tested for differences in emergent patterns in communities from tropical versus temperate latitudes. We found that, in comparison to species from undisturbed natural habitats, the average animal found in human‐altered habitats lives in areas with higher maximum and lower minimum temperatures and higher maximum and lower minimum precipitation levels. We further found that tropical assemblages diverged more strongly than temperate assemblages between natural and human‐altered habitats, possibly because tropical species are more sensitive to climatic conditions. These results strongly implicate the role of land‐use change in favouring species affiliated with more extreme climatic conditions, thus systematically reshaping the composition of terrestrial biological assemblages. Our findings have the potential to inform species' vulnerability assessments and highlight the importance of preserving local climate refugia. [ABSTRACT FROM AUTHOR]

Climate change is likely to impact multiple dimensions of biodiversity. Species range shifts are expected and may drive changes in the composition of species assemblages. In some regions, changes in climate may precipitate the loss of geographically restricted, niche specialists and facilitate their replacement by more widespread, niche generalists, leading to decreases in β‐diversity and biotic homogenization. However, in other regions climate change may drive local extinctions and range contraction, leading to increases in β‐diversity and biotic heterogenization. Regional topography should be a strong determinant of such changes as mountainous areas often are home to many geographically restricted species, whereas lowlands and plains are more often inhabited by widespread generalists. Climate warming, therefore, may simultaneously bring about opposite trends in β‐diversity in mountainous highlands versus relatively flat lowlands. To test this hypothesis, we used species distribution modelling to map the present‐day distributions of 2669 Neotropical anuran species, and then generated projections of their future distributions assuming future climate change scenarios. Using traditional metrics of β‐diversity, we mapped shifts in biotic homogenization across the entire Neotropical region. We used generalized additive models to then evaluate how changes in β‐diversity were associated with shifts in species richness, phylogenetic diversity and one measure of ecological generalism. Consistent with our hypothesis, we find increasing biotic homogenization in most highlands, associated with increased numbers of generalists and, to a lesser extent, losses of specialists, leading to an overall increase in alpha diversity, but lower mean phylogenetic diversity. In the lowlands, biotic heterogenization was more common, and primarily driven by local extinctions of generalists, leading to lower α‐diversity, but higher mean phylogenetic diversity. Our results suggest that impacts of climate change on β‐diversity are likely to vary regionally, but will generally lead to lower diversity, with increases in β‐diversity offset by decreases in α‐diversity. [ABSTRACT FROM AUTHOR]

For many ectothermic animals, the acquisition, storage and depletion of lipids is integral to successfully coping with reduced metabolic rates and activity levels associated with cold, winter periods. In fish, lipids are crucial for overwinter survival and successful reproduction. The timing and magnitude of seasonal lipid storage should therefore vary predictably among fish with different thermal preferences and spawn times. Small‐ and large‐bodied fish should also face different constraints associated with season that influence lipid cycling. However, much work to date has been species‐ and location‐specific and a general conceptual model for the seasonal energy budgets of freshwater fish is lacking. Here, we conducted a comprehensive literature review of seasonal lipid levels in freshwater fishes. We predicted that warm and cool water species would be more likely to demonstrate peak lipid levels during warm months than cold water species, and expected a larger magnitude of annual lipid cycling in warm and cool water compared to cold water fish. We also expected dampened lipid cycling in larger fish due to their lower mass‐specific metabolic rates. Observed patterns in the timing and magnitude of lipid storage contradicted our prediction because lipid cycling was widespread across species, despite thermal guild, with peak lipid levels commonly occurring during warmer months, even in cold water fish. For body size effects, larger bodied fish species had dampened seasonal lipid cycling, as predicted. We developed a conceptual framework describing how the 'scope' for variation in annual lipid cycling changes with body size both among and within species in order to guide future work. Together, our findings suggest that energy acquired during warm months is broadly important for overwinter survival and reproduction in fishes, and provide a new perspective on the differential constraints and physiological responses to seasonality among freshwater fish. Improving our understanding of these dynamics is especially pressing given that a changing global climate is anticipated to alter existing seasonal signals. [ABSTRACT FROM AUTHOR]

A primary focus of historical biogeography is to understand changes in species ranges, abundance and genetic connectivity, and changes in community composition. Traditionally, biogeographic inference has relied on distinct lines of evidence, including DNA sequences, fossils and hindcasted ecological niche models. In this review we propose that the development of integrative modeling approaches that leverage multiple distinct data types from diverse disciplines has the potential to revolutionize the field of biogeography. Although each data type contains information on a distinct aspect of species' biogeographic histories, few studies formally integrate multiple types in analysis. For example, post hoc congruence among analyses based on different data types (e.g. fossils and genetics) is commonly assumed to indicate likely biogeographic histories. Unfortunately, analyses of different data often reach discordant conclusions. Thus, fundamental and unresolved debates continue regarding speed and timing of postglacial migration, location and size of glacial refugia, and degree of long distance dispersal. Formal statistical integration can help address these issues. More specifically, formal integration can leverage all available evidence, account for inherent biases associated with different data types, and quantify data and process uncertainty. Novel, quantitative integration of data and models across fields is now possible due to recent advances in cyberinfrastructure, spatial modeling, online and aggregated ecological databases, data processing and quantitative methods. Our purpose is to make the case for and give examples of rigorous integration of genetic, fossil and environmental/occurrence data for inferring biogeographic history. In particular, we 1) review the need for such a framework; 2) explain common data types and approaches used to infer biogeographic history (and the challenges with each); 3) review state‐of‐the‐art examples of data integration in biogeography; 4) lay out a series of novel, suggested improvements on current methods; and 5) provide an outlook on technical feasibility and future opportunities. [ABSTRACT FROM AUTHOR]

Climate change will redistribute the global biodiversity in the Anthropocene. As climates change, species might move from one place to another, due to local extinctions and colonization of new environments. However, the existence of permeable migratory routes precedes faunal migrations in fragmented landscapes. Here, we investigate how dispersal will affect the outcome of climate change on the distribution of Amazon's primate species. We modeled the distribution of 80 Amazon primate species, using ecological niche models, and projected their potential distribution on scenarios of climate change. Then, we imposed landscape restrictions to primate dispersal, derived from a natural biogeographical barrier to primates (the main tributaries of the Amazon river) and an anthropogenic constraint to the migration of many canopy‐dependent animals (deforested areas). We also highlighted potential conflict zones, i.e. regions of high migration potential but predicted to be deforested. Species response to climate change varied across dispersal limitation scenarios. If species could occupy all newly suitable climate, almost 70% of species could expand ranges. Including dispersal barriers (natural and anthropogenic), however, led to range expansion in only less than 20% of the studied species. When species were not allowed to migrate, all of them lost an average of 90% of the suitable area, suggesting that climate may become unsuitable within their present distributions. All Amazon primate species may need to move as climate changes to avoid deleterious effects of exposure to non‐analog climates. The effect of climate change on the distribution of Amazon primates will ultimately depend on whether landscape permeability will allow climate‐driven faunal migrations. The network of protected areas in the Amazon could work as 'stepping stones' but most are outside important migratory routes. Therefore, protecting important dispersal corridors is foremost to allow effective migrations of the Amazon fauna in face of climate change and deforestation. [ABSTRACT FROM AUTHOR]

The koala's Phascolarctos cinereus distribution is currently restricted to eastern and south‐eastern Australia. However, fossil records dating from 70 ± 4 ka (ka = 103 yr) from south‐western Australia and the Nullarbor Plain are evidence of subpopulation extinctions in the southwest at least after the Last Interglacial (~128–116 ka). We hypothesize that koala sub‐population extinctions resulted from the eastward retraction of the koala's main browse species in response to unsuitable climatic conditions. We further posit a general reduction in the distribution of main koala‐browse trees in the near future in response climate change. We modelled 60 koala‐browse species and constructed a set of correlative species distribution models for five time periods: Last Interglacial (~128–116 ka), Last Glacial Maximum (~23–19 ka), Mid‐Holocene (~7–5 ka), present (interpolations of observed data, representative of 1960–1990), and 2070. We based our projections on five hindcasts and one forecast of climatic variables extracted from WorldClim based on two general circulation models (considering the most pessimistic scenario of high greenhouse‐gas emissions) and topsoil clay fraction. We used 17 dates of koala fossil specimens identified as reliable from 70 (± 4) to 535 (± 49) ka, with the last appearance of koalas at 70 ka in the southwest. The main simulated koala‐browse species were at their greatest modelled extent of suitability during the Last Glacial Maximum, with the greatest loss of koala habitat occurring between the Mid‐Holocene and the present. We predict a similar habitat loss between the present and 2070. The spatial patterns of habitat change support our hypothesis that koala extinctions in the southwest, Nullarbor Plain and central South Australia resulted from the eastward retraction of the dominant koala‐browse species in response to long‐term climate changes. Future climate patterns will likely increase the extinction risk of koalas in their remaining eastern ranges. [ABSTRACT FROM AUTHOR]

Climate change vulnerability assessments are an important tool for understanding the threat that climate change poses to species and populations, but do not generally yield insight into the spatial variation in vulnerability throughout a species' habitat. We demonstrate how to adapt the method of ecological‐niche factor analysis (ENFA) to objectively quantify aspects of species sensitivity to climate change. We then expand ENFA to quantify aspects of exposure and vulnerability to climate change as well, using future projections of global climate models. This approach provides spatially‐explicit insight into geographic patterns of vulnerability, relies only on readily‐available spatial data, is suitable for a wide range of species and habitats, and invites comparison between different species. We apply our methods to a case study of two species of montane mammals, the American pika Ochotona princeps and the yellow‐bellied marmot Marmota flaviventris. [ABSTRACT FROM AUTHOR]