Effects of biotic interactions on modeled species' distribution can be masked by environmental gradients

A fundamental goal of ecology is to understand the determinants of species' distributions (i.e., the set of locations where a species is present). Competition among species (i.e., interactions among species that harms each of the species involved) is common in nature and it would be tremendously useful to quantify its effects on species' distributions. An approach to studying the large‐scale effects of competition or other biotic interactions is to fit species' distributions models (SDMs) and assess the effect of competitors on the distribution and abundance of the species of interest. It is often difficult to validate the accuracy of this approach with available data. Here, we simulate virtual species that experience competition. In these simulated datasets, we can unambiguously identify the effects that competition has on a species' distribution. We then fit SDMs to the simulated datasets and test whether we can use the outputs of the SDMs to infer the true effect of competition in each simulated dataset. In our simulations, the abiotic environment influenced the effects of competition. Thus, our SDMs often inferred that the abiotic environment was a strong predictor of species abundance, even when the species' distribution was strongly affected by competition. The severity of this problem depended on whether the competitor excluded the focal species from highly suitable sites or marginally suitable sites. Our results highlight how correlations between biotic interactions and the abiotic environment make it difficult to infer the effects of competition using SDMs.     

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km² to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere.     

Mutualist‐mediated effects on species' range limits across large geographic scales

Understanding the processes determining species range limits is central to predicting species distributions under climate change. Projected future ranges are extrapolated from distribution models based on climate layers, and few models incorporate the effects of biotic interactions on species' distributions. Here, we show that a positive species interaction ameliorates abiotic stress, and has a profound effect on a species' range limits. Combining field surveys of 92 populations, 10 common garden experiments throughout the range, species distribution models and greenhouse experiments, we show that mutualistic fungal endophytes ameliorate drought stress and broaden the geographic range of their native grass host Bromus laevipes by thousands of square kilometres (~ 20% larger) into drier habitats. Range differentiation between fungal‐associated and fungal‐free grasses was comparable to species‐level range divergence of congeners, indicating large impacts on range limits. Positive biotic interactions may be underappreciated in determining species' ranges and species' responses to future climates across large geographic scales.     

Species interactions and climate change: How the disruption of species co‐occurrence will impact on an avian forest guild

Interspecific interactions are crucial in determining species occurrence and community assembly. Understanding these interactions is thus essential for correctly predicting species' responses to climate change. We focussed on an avian forest guild of four hole‐nesting species with differing sensitivities to climate that show a range of well‐understood reciprocal interactions, including facilitation, competition and predation. We modelled the potential distributions of black woodpecker and boreal, tawny and Ural owl, and tested whether the spatial patterns of the more widespread species (excluding Ural owl) were shaped by interspecific interactions. We then modelled the potential future distributions of all four species, evaluating how the predicted changes will alter the overlap between the species' ranges, and hence the spatial outcomes of interactions. Forest cover/type and climate were important determinants of habitat suitability for all species. Field data analysed with N‐mixture models revealed effects of interspecific interactions on current species abundance, especially in boreal owl (positive effects of black woodpecker, negative effects of tawny owl). Climate change will impact the assemblage both at species and guild levels, as the potential area of range overlap, relevant for species interactions, will change in both proportion and extent in the future. Boreal owl, the most climate‐sensitive species in the guild, will retreat, and the range overlap with its main predator, tawny owl, will increase in the remaining suitable area: climate change will thus impact on boreal owl both directly and indirectly. Climate change will cause the geographical alteration or disruption of species interaction networks, with different consequences for the species belonging to the guild and a likely spatial increase of competition and/or intraguild predation. Our work shows significant interactions and important potential changes in the overlap of areas suitable for the interacting species, which reinforce the importance of including relevant biotic interactions in predictive climate change models for increasing forecast accuracy.     

Interspecific behavioural interference and range dynamics: current insights and future directions

Novel biotic interactions in shifting communities play a key role in determining the ability of species' ranges to track suitable habitat. To date, the impact of biotic interactions on range dynamics have predominantly been studied in the context of interactions between different trophic levels or, to a lesser extent, exploitative competition between species of the same trophic level. Yet, both theory and a growing number of empirical studies show that interspecific behavioural interference, such as interspecific territorial and mating interactions, can slow down range expansions, preclude coexistence, or drive local extinction, even in the absence of resource competition. We conducted a systematic review of the current empirical research into the consequences of interspecific behavioural interference on range dynamics. Our findings demonstrate there is abundant evidence that behavioural interference by one species can impact the spatial distribution of another. Furthermore, we identify several gaps where more empirical work is needed to test predictions from theory robustly. Finally, we outline several avenues for future research, providing suggestions for how interspecific behavioural interference could be incorporated into existing scientific frameworks for understanding how biotic interactions influence range expansions, such as species distribution models, to build a stronger understanding of the potential consequences of behavioural interference on the outcome of future range dynamics.     

Biotic and abiotic variables show little redundancy in explaining tree species distributions

Abiotic factors such as climate and soil determine the species fundamental niche, which is further constrained by biotic interactions such as interspecific competition. To parameterize this realized niche, species distribution models (SDMs) most often relate species occurrence data to abiotic variables, but few SDM studies include biotic predictors to help explain species distributions. Therefore, most predictions of species distributions under future climates assume implicitly that biotic interactions remain constant or exert only minor influence on large‐scale spatial distributions, which is also largely expected for species with high competitive ability. We examined the extent to which variance explained by SDMs can be attributed to abiotic or biotic predictors and how this depends on species traits. We fit generalized linear models for 11 common tree species in Switzerland using three different sets of predictor variables: biotic, abiotic, and the combination of both sets. We used variance partitioning to estimate the proportion of the variance explained by biotic and abiotic predictors, jointly and independently. Inclusion of biotic predictors improved the SDMs substantially. The joint contribution of biotic and abiotic predictors to explained deviance was relatively small (~9%) compared to the contribution of each predictor set individually (~20% each), indicating that the additional information on the realized niche brought by adding other species as predictors was largely independent of the abiotic (topo‐climatic) predictors. The influence of biotic predictors was relatively high for species preferably growing under low disturbance and low abiotic stress, species with long seed dispersal distances, species with high shade tolerance as juveniles and adults, and species that occur frequently and are dominant across the landscape. The influence of biotic variables on SDM performance indicates that community composition and other local biotic factors or abiotic processes not included in the abiotic predictors strongly influence prediction of species distributions. Improved prediction of species' potential distributions in future climates and communities may assist strategies for sustainable forest management.     

Scale dependence of temperature as an abiotic driver of species' distributions

Aim Scale dependence of patterns and processes remains one of the major unresolved problems in ecology. The responses of ecosystems to environmental stressors are reported to be strongly scale dependent, but projections of the effects of climate change on species' distributions are still restricted to particular scales and knowledge about scale dependence is lacking. Here we propose that the scale dependence of those species' niche dimensions related to climate change is strongly related to the strength of climatic cross‐scale links. More specifically, we hypothesize that the strong cross‐scale links between micro‐ and macroclimatic conditions are related to high cross‐scale similarity (low scale dependence) of species' realized temperature niches and, thus, species' spatial distributions. Location This study covers seven orders of magnitude of spatial scale, ranging from local‐scale (below a metre) and regional‐scale (kilometre) investigations in central European wetland ecosystems to continental‐scale (thousands of kilometres) studies of species' distributions. Methods We combined data on the spatial occurrence of species (vegetation records at local and regional scales, digitized distribution maps at the continental scale) with information about the corresponding temperature regime of vascular plant species occurring in environmentally stable wetland ecosystems characterized by strong cross‐scale links between micro‐ and macroclimatic conditions. Results We observed high cross‐scale similarity of the characteristics of species temperature niches across seven orders of magnitude of spatial scale. However, the importance of temperature as an abiotic driver decreased nonlinearly with decreasing scale, suggesting greater importance of additional (biotic) drivers of species' occurrence at small spatial scales. Main conclusions We report high cross‐scale similarity of realized temperature niches for species inhabiting ecosystems where small‐scale environmental noise is low and cross‐scale links between micro‐ and macroclimatic conditions are strong. By highlighting a strong relationship between abiotic and biotic cross‐scale similarity, our results will help to improve niche‐based species distribution modelling, one of the major assessment tools for determining the ecological effects of climate change.     

Biotic Interactions Overrule Plant Responses to Climate,Depending on the Species' Biogeography

This study presents an experimental approach to assess the relative importance of climatic and biotic factors as determinants of species'' geographical distributions. We asked to what extent responses of grassland plant species to biotic interactions vary with climate, and to what degree this variation depends on the species'' biogeography. Using a gradient from oceanic to continental climate represented by nine common garden transplant sites in Germany, we experimentally tested whether congeneric grassland species of different geographic distribution (oceanic vs. continental plant range type) responded differently to combinations of climate, competition and mollusc herbivory. We found the relative importance of biotic interactions and climate to vary between the different components of plant performance. While survival and plant height increased with precipitation, temperature had no effect on plant performance. Additionally, species with continental plant range type increased their growth in more benign climatic conditions, while those with oceanic range type were largely unable to take a similar advantage of better climatic conditions. Competition generally caused strong reductions of aboveground biomass and growth. In contrast, herbivory had minor effects on survival and growth. Against expectation, these negative effects of competition and herbivory were not mitigated under more stressful continental climate conditions. In conclusion we suggest variation in relative importance of climate and biotic interactions on broader scales, mediated via species-specific sensitivities and factor-specific response patterns. Our results have important implications for species distribution models, as they emphasize the large-scale impact of biotic interactions on plant distribution patterns and the necessity to take plant range types into account.     

Positive species interactions shape species' range limits

The relationship between niche and distribution, and especially the role of biotic interactions in shaping species' geographic distributions, has gained increasing interest in the last two decades. Most ecological research has focused on negative species interactions, especially competition, predation and parasitism. Yet the relevance of positive interactions – mutualisms and commensalisms – have been brought to the fore in recent years by an increasing number of empirical studies exploring their impact on range limits. Based on a review of 73 studies from a Web of Science search, we found strong evidence that positive interactions can influence the extent of species' geographic or ecological ranges through a diversity of mechanisms. More specifically, we found that while obligate interactions, and especially obligate mutualisms, tend to constrain the ranges of one or both partners, facultative positive interactions tend to widen ranges. Nonetheless, there was more variation in effects of facultative interactions on range limits, pointing to important context-dependencies. Therefore, we propose that conceptual development in this field will come from studying ecological interactions in the context of networks of many species across environmental gradients, since pairwise interactions alone might overlook the indirect and environmentally-contingent effects that species have on each other in communities of many interacting species. Finally, our study also revealed key data gaps that limit our current understanding of the pervasiveness of effects that positive interactions have on species' ranges, highlighting potential avenues for future theoretical and experimental work.     

The role of abiotic and biotic factors in determining coexistence of multiple pollinators in the yucca–yucca moth mutualism

The determinants of a species' geographic distribution are a combination of both abiotic and biotic factors. Environmental niche modeling of climatic factors has been instrumental in documenting the role of abiotic factors in a species' niche. Integrating this approach with data from species interactions provides a means to assess the relative roles of abiotic and biotic components. Here, we examine whether the high host specificity typically exhibited in the active pollination mutualism between yuccas and yucca moths is the result of differences in climatic niche requirements that limit yucca moth distributions or the result of competition among mutualistic moths that would co‐occur on the same yucca species. We compared the species distribution models of two Tegeticula pollinator moths that use the geographically widespread plant Yucca filamentosa. Tegeticula yuccasella occurs throughout eastern North America whereas T. cassandra is restricted to the southeastern portion of the range, primarily occurring in Florida. Species distribution models demonstrate that T. cassandra is restricted climatically to the southeastern United States and T. yuccasella is predicted to be able to live across all of eastern North America. Data on moth abundances in Florida demonstrate that both moth species are present on Y. filamentosa; however, T. cassandra is numerically dominant. Taken together, the results suggest that moth geographic distributions are heavily influenced by climate, but competition among pollinating congeners will act to restrict populations of moth species that co‐occur.     

Species coexistence in resource-limited patterned ecosystems is facilitated by the interplay of spatial self-organisation and intraspecific competition

The exploration of mechanisms that enable species coexistence under competition for a sole limiting resource is widespread across ecology. Two examples of such facilitative processes are intraspecific competition and spatial self-organisation. These processes determine the outcome of competitive dynamics in many resource-limited patterned ecosystems, classical examples of which include dryland vegetation patterns, intertidal mussel beds and subalpine ribbon forests. Previous theoretical investigations have explained coexistence within patterned ecosystems by making strong assumptions on the differences between species (e.g. contrasting dispersal behaviours or different functional responses to resource availability). In this paper, I show that the interplay between the detrimental effects of intraspecific competition and the facilitative nature of self-organisation forms a coexistence mechanism that does not rely on species-specific assumptions and captures coexistence across a wide range of the environmental stress gradient. I use a theoretical model that captures the interactions of two generic consumer species with an explicitly modelled resource to show that coexistence relies on a balance between species' colonisation abilities and their local competitiveness, provided intraspecific competition is sufficiently strong. Crucially, the requirements on species' self-limitation for coexistence to occur differ on opposite ends of the resource input spectrum. For low resource levels, coexistence is facilitated by strong intraspecific dynamics of the species superior in its colonisation abilities, but for larger volumes of resource input, strong intraspecific competition of the locally superior species enables coexistence. Results presented in this paper also highlight the importance of hysteresis in understanding tipping points, in particular extinction events. Finally, the theoretical framework provides insights into spatial species distributions within single patches, supporting verbal hypotheses on coexistence of herbaceous and woody species in dryland vegetation patterns and suggesting potential empirical tests in the context of other patterned ecosystems.     

Microhabitat selection in the common lizard: implications of biotic interactions,age, sex,local processes,and model transferability among populations

Modeling species' habitat requirements are crucial to assess impacts of global change, for conservation efforts and to test mechanisms driving species presence. While the influence of abiotic factors has been widely examined, the importance of biotic factors and biotic interactions, and the potential implications of local processes are not well understood. Testing their importance requires additional knowledge and analyses at local habitat scale. Here, we recorded the locations of species presence at the microhabitat scale and measured abiotic and biotic parameters in three different common lizard (Zootoca vivipara) populations using a standardized sampling protocol. Thereafter, space use models and cross‐evaluations among populations were run to infer local processes and estimate the importance of biotic parameters, biotic interactions, sex, and age. Biotic parameters explained more variation than abiotic parameters, and intraspecific interactions significantly predicted the spatial distribution. Significant differences among populations in the relationship between abiotic parameters and lizard distribution, and the greater model transferability within populations than between populations are in line with effects predicted by local adaptation and/or phenotypic plasticity. These results underline the importance of including biotic parameters and biotic interactions in space use models at the population level. There were significant differences in space use between sexes, and between adults and yearlings, the latter showing no association with the measured parameters. Consequently, predictive habitat models at the population level taking into account different sexes and age classes are required to understand a specie's ecological requirements and to allow for precise conservation strategies. Our study therefore stresses that future predictive habitat models at the population level and their transferability should take these parameters into account.     

Can we disentangle predator–prey interactions from species distributions at a macro‐scale? A case study with a raptor species

There is a debate on whether an influence of biotic interactions on species distributions can be reflected at macro‐scale levels. Whereas the influence of biotic interactions on spatial arrangements is beginning to be studied at local scales, similar studies at macro‐scale levels are scarce. There is no example disentangling, from other similarities with related species, the influence of predator–prey interactions on species distributions at macro‐scale levels. In this study we aimed to disentangle predator–prey interactions from species distribution data following an experimental approach including a factorial design. As a case of study we selected the short‐toed eagle because of its known specialization on certain prey reptiles. We used presence–absence data at a 100 km2 spatial resolution to extract the explanatory capacity of different environmental predictors (five abiotic and two biotic predictors) on the short‐toed eagle species distribution in peninsular Spain. Abiotic predictors were relevant climatic and topographic variables, and relevant biotic predictors were prey richness and forest density. In addition to the short‐toed eagle, we also obtained the predictor's explanatory capacities for 1) species of the same family Accipitridae (as a reference), 2) for other birds of different families (as controls) and 3) artificial species with randomly selected presences (as null models). We run 650 models to test for similarities of the short‐toed eagle, controls and null models with reference species, assessed by regressions of explanatory capacities. We found higher similarities between the short‐toed eagle and other species of the family Accipitridae than for the other two groups. Once corrected by the family effect, our analyses revealed a signal of predator–prey interaction embedded in species distribution data. This result was corroborated with additional analyses testing for differences in the concordance between the distributions of different bird categories and the distributions of either prey or non‐prey species of the short‐toed eagle. Our analyses were useful to disentangle a signal of predator–prey interactions from species distribution data at a macro‐scale. This study highlights the importance of disentangling specific features from the variation shared with a given taxonomic level.     

Species partitioning in a temperate mountain chain: Segregation by habitat vs. interspecific competition

Disentangling the relative influence of the environment and biotic interactions in determining species coexistence patterns is a major challenge in ecology. The zonation occurring along elevation gradients, or at bioclimatic contact zones, offers a good opportunity to improve such understanding because the small scale at which the partitioning occurs facilitates inference based on experiments and ecological modelling. We studied the influence of abiotic gradients, habitat types, and interspecific competition in determining the spatial turnover between two pipit and two bunting species in NW Spain. We explored two independent lines of evidence to draw inference about the relative importance of environment and biotic interactions in driving range partitioning along elevation, latitude, and longitude. We combined occurrence data with environmental data to develop joint species distribution models (JSDM), in order to attribute co‐occurrence (or exclusion) to shared (or divergent) environmental responses and to interactions (attraction or exclusion). In the same region, we tested for interference competition by means of playback experiments in the contact zone. The JSDMs highlighted different responses for the two species pairs, although we did not find direct evidence of interspecific aggressiveness in our playback experiments. In pipits, partitioning was explained by divergent climate and habitat requirements and also by the negative correlations between species not explained by the environment. This significant residual correlation may reflect forms of competition others than direct interference, although we could not completely exclude the influence of unmeasured environmental predictors. When bunting species co‐occurred, it was because of shared habitat preferences, and a possible limitation to dispersal might cause their partitioning. Our results indicate that no single mechanism dominates in driving the distribution of our study species, but rather distributions are determined by the combination of many small forces including biotic and abiotic determinants of niche, whose relative strengths varied among species.     

Coupled plant traits adapted to wetting/drying cycles of substrates co-define niche multidimensionality

Theories attempting to explain species coexistence in plant communities have argued in favour of species' capacities to occupy a multidimensional niche with spatial, temporal and biotic axes. We used the concept of hydrological niche segregation to learn how ecological niches are structured both spatially and temporally and whether small scale humidity gradients between adjacent niches are the main factor explaining water partitioning among tree species in a highly water-limited semiarid forest ecosystem. By combining geophysical methods, isotopic ecology, plant ecophysiology and anatomical measurements, we show how coexisting pine and oak species share, use and temporally switch between diverse spatially distinct niches by employing a set of functionally coupled plant traits in response to changing environmental signals. We identified four geospatial niches that turned into nine, when considering the temporal dynamics of the wetting/drying cycles in the substrate and the particular plant species adaptations to garner, transfer, store and use water. Under water scarcity, pine and oak exhibited water use segregation from different niches, yet under maximum drought when oak trees crossed physiological thresholds, niche overlap occurred. The identification of niches and mechanistic understanding of when and how species use them will help unify theories of plant coexistence and competition.     

Are Species Coexistence Areas a Good Option for Conservation Management? Applications from Fine Scale Modelling in Two Steppe Birds

Biotic interactions and land uses have been proposed as factors that determine the distribution of the species at local scale. The presence of heterospecifics may modify the habitat selection pattern of the individuals and this may have important implications for the design of effective conservation strategies. However, conservation proposals are often focused on a single flagship or umbrella species taken as representative of an entire assemblage requirements. Our aim is to identify and evaluate the role of coexistence areas at local scale as conservation tools, by using distribution data of two endangered birds, the Little Bustard and the Great Bustard. Presence-only based suitability models for each species were built with MaxEnt using variables of substrate type and topography. Probability maps of habitat suitability for each species were combined to generate a map in which coexistence and exclusive use areas were delimitated. Probabilities of suitable habitat for each species inside coexistence and exclusive areas were compared. As expected, habitat requirements of Little and Great Bustards differed. Coexistence areas presented lower probabilities of habitat suitability than exclusive use ones. We conclude that differences in species'' habitat preferences can hinder the efficiency of protected areas with multi-species conservation purposes. Our results highlight the importance of taking into account the role of biotic interactions when designing conservation measurements.     

扩散模式对高阶相互作用物种共存机制的影响

物种共存机制是群落生态学研究的核心问题之一,但以成对物种间直接相互作用为主的传统共存理论,并未在实际群落中得到普遍证实。近年来,有研究表明,高阶相互作用,即一个物种对另一个物种的直接作用强度受到其他物种的间接影响,在群落竞争过程中的重要性不断得到发展。目前,对高阶相互作用的理论研究还主要集中在非空间理论模型。事实上,群落中个体的空间分布和扩散模式等对种群动态的影响均至关重要。故考虑空间因素,以三物种为例构建空间显式的群落动态模拟,通过引入不同的物种扩散模式,研究高阶相互作用对群落物种共存结果的影响。研究表明:(1)高阶相互作用可以促进也可能抑制物种共存,具体共存结果取决于高阶相互作用的方向、强度和分类;(2)当全部高阶相互作用都存在,且取值为正时,物种共存位置会发生偏移,原本生态位分化下共存的区域不再共存,而在生态位重叠度较高的区域,物种可以在更大范围的适合度差异下共存;(3)扩散模式对高阶相互作用的上述调节机制有一定的影响,且无论正高阶还是负高阶,当种群趋于局部扩散时,高阶相互作用的正向及负向调节效果均有所减弱。以上结论强调了在理论模型和实际保护工作中考虑相互作用网络的重要性,有助于进一步理解物种共存机制,能够为保护生物多样性提供理论依据。     

Biotic predictors with phenological information improve range estimates for migrating monarch butterflies in Mexico

Although long-standing theory suggests that biotic variables are only relevant at local scales for explaining the patterns of species' distributions, recent studies have demonstrated improvements to species distribution models (SDMs) by incorporating predictor variables informed by biotic interactions. However, some key methodological questions remain, such as which kinds of interactions are permitted to include in these models, how to incorporate the effects of multiple interacting species, and how to account for interactions that may have a temporal dependence. We addressed these questions in an effort to model the distribution of the monarch butterfly Danaus plexippus during its fall migration (September–November) through Mexico, a region with new monitoring data and uncertain range limits even for this well-studied insect. We estimated species richness of selected nectar plants (Asclepias spp.) and roosting trees (various highland species) for use as biotic variables in our models. To account for flowering phenology, we additionally estimated nectar plant richness of flowering species per month. We evaluated three types of models: climatic variables only (abiotic), plant richness estimates only (biotic) and combined (abiotic and biotic). We selected models with AICc and additionally determined if they performed better than random on spatially withheld data. We found that the combined models accounting for phenology performed best for all three months, and better than random for discriminatory ability but not omission rate. These combined models also produced the most ecologically realistic spatial patterns, but the modeled response for nectar plant richness matched ecological predictions for November only. These results represent the first model-based monarch distributional estimates for the Mexican migration route and should provide foundations for future conservation work. More generally, the study demonstrates the potential benefits of using SDM-derived richness estimates and phenological information for biotic factors affecting species distributions.     

Incorporating spatial autocorrelation into species distribution models alters forecasts of climate‐mediated range shifts

Species distribution models (SDMs) are widely used to forecast changes in the spatial distributions of species and communities in response to climate change. However, spatial autocorrelation (SA) is rarely accounted for in these models, despite its ubiquity in broad‐scale ecological data. While spatial autocorrelation in model residuals is known to result in biased parameter estimates and the inflation of type I errors, the influence of unmodeled SA on species' range forecasts is poorly understood. Here we quantify how accounting for SA in SDMs influences the magnitude of range shift forecasts produced by SDMs for multiple climate change scenarios. SDMs were fitted to simulated data with a known autocorrelation structure, and to field observations of three mangrove communities from northern Australia displaying strong spatial autocorrelation. Three modeling approaches were implemented: environment‐only models (most frequently applied in species' range forecasts), and two approaches that incorporate SA; autologistic models and residuals autocovariate (RAC) models. Differences in forecasts among modeling approaches and climate scenarios were quantified. While all model predictions at the current time closely matched that of the actual current distribution of the mangrove communities, under the climate change scenarios environment‐only models forecast substantially greater range shifts than models incorporating SA. Furthermore, the magnitude of these differences intensified with increasing increments of climate change across the scenarios. When models do not account for SA, forecasts of species' range shifts indicate more extreme impacts of climate change, compared to models that explicitly account for SA. Therefore, where biological or population processes induce substantial autocorrelation in the distribution of organisms, and this is not modeled, model predictions will be inaccurate. These results have global importance for conservation efforts as inaccurate forecasts lead to ineffective prioritization of conservation activities and potentially to avoidable species extinctions.     

Scaling up from local competition to regional coexistence across two scales of spatial heterogeneity: insect larvae in the fruits of <Emphasis Type="Italic">Apeiba membranacea</Emphasis>

Species that live in patchy and ephemeral habitats can compete strongly for resources within patches at a small scale. The ramifications of these interactions for population dynamics and coexistence at regional scales will depend on the intraspecific and interspecific distributions of individuals among patches. Spatial heterogeneity due to independent aggregation of competitors among patchy habitats is an important mechanism maintaining species diversity. I describe regional patterns of aggregation for four species of insect larvae in the fruits of Apeiba membranacea, a Neotropical rainforest tree. This aggregation results from variation in densities at a small scale (among the fruits under a single tree), compounded by significant variation among trees in both mean densities and degrees of aggregation. Both the degrees of aggregation and mean densities are statistically independent within and across species at both spatial scales. I evaluate the regional consequences of these spatial patterns by using maximum likelihood methods to parameterize a model that includes both explicit measures of the strength of competition and spatial variation at both within- and among-tree spatial scales. Despite strong competitive interactions among these species, during 2 years the observed spatial variation at both scales combined was sufficient to explain the coexistence of these species, although other coexistence mechanisms may also operate simultaneously. The observed spatial variation at small spatial scales may not be sufficient for coexistence, indicating the importance of considering multiple sources of spatial heterogeneity when scaling up from experiments that investigate local interactions to regional patterns of coexistence.