Is there an ecological basis for species abundance distributions?

Community ecologists have attempted to explain species abundance distribution (SAD) shape for more than 80 years, but usually without relating SAD shape explicitly to ecological variables. We explored whether the scale (total assemblage abundance) and shape (assemblage evenness) of avifaunal SADs were related to ecological covariates. We used data on avifaunas, in-site habitat structure and landscape context that were assembled from previous studies; this amounted to 197 transects distributed across 16,000 km² of the box-ironbark forests of southeastern Australia. We used Bayesian conditional autoregressive models to link SAD scale and shape to these ecological covariates. Variation in SAD scale was relatable to some ecological covariates, especially to landscape vegetation cover and to tree height. We could not find any relationships between SAD shape and ecological covariates. SAD shape, the core component in SAD theory, may hold little information about how assemblages are governed ecologically and may result from statistical processes, which, if general, would indicate that SAD shape is not useful for distinguishing among theories of assemblage structure.     

Multivariate analysis of a fine-scale breeding bird atlas using a geographical information system and partial canonical correspondence analysis: environmental and spatial effects

Aim To assess the relative roles of environment and space in driving bird species distribution and to identify relevant drivers of bird assemblage composition, in the case of a fine‐scale bird atlas data set. Location The study was carried out in southern Belgium using grid cells of 1 × 1 km, based on the distribution maps of the Oiseaux nicheurs de Famenne: Atlas de Lesse et Lomme which contains abundance for 103 bird species. Methods Species found in < 10% or > 90% of the atlas cells were omitted from the bird data set for the analysis. Each cell was characterized by 59 landscape metrics, quantifying its composition and spatial patterns, using a Geographical Information System. Partial canonical correspondence analysis was used to partition the variance of bird species matrix into independent components: (a) ‘pure’ environmental variation, (b) spatially‐structured environmental variation, (c) ‘pure’ spatial variation and (d) unexplained, non‐spatial variation. Results The variance partitioning method shows that the selected landscape metrics explain 27.5% of the variation, whilst ‘pure’ spatial and spatially‐structured environmental variables explain only a weak percentage of the variation in the bird species matrix (2.5% and 4%, respectively). Avian community composition is primarily related to the degree of urbanization and the amount and composition of forested and open areas. These variables explain more than half of the variation for three species and over one‐third of the variation for 12 species. Main conclusions The results seem to indicate that the majority of explained variation in species assemblages is attributable to local environmental factors. At such a fine spatial resolution, however, the method does not seem to be appropriated for detecting and extracting the spatial variation of assemblages. Consequently, the large amount of unexplained variation is probably because of missing spatial structures and ‘noise’ in species abundance data. Furthermore, it is possible that other relevant environmental factors, that were not taken into account in this study and which may operate at different spatial scales, can drive bird assemblage structure. As a large proportion of ecological variation can be shared by environment and space, the applied partitioning method was found to be useful when analysing multispecific atlas data, but it needs improvement to factor out all‐scale spatial components of this variation (the source of ‘false correlation’) and to bring out the ‘pure’ environmental variation for ecological interpretation.     

Biogeography of parasitism in freshwater fish: spatial patterns in hot spots of infection

Contrary to species occurrence, little is known about the determinants of spatial patterns of intraspecific variation in abundance, particularly for parasitic organisms. In this study, we provide a multi‐faceted overview of spatial patterns in parasite abundance and examine several potential underlying processes. We first tested for a latitudinal gradient in local abundance of the regionally most common parasite species and whether these species achieve higher abundances at the same localities (shared hot spots of infection). Secondly, we tested whether intraspecific similarity in local abundance between sites follows a spatial distance decay pattern or is better explained by variation in extrinsic biotic and abiotic factors between localities related to local parasite transmission success. We examined the infection landscape of a model fish host system (common and upland bullies, genus Gobiomorphus: Eleotridae) across its entire distributional range. We applied general linear models to test the effect of latitude on each species local abundance independently, including the abundance of each co‐infecting species as another predictor. We computed multiple regressions on distance matrices among localities based on abundance of each of the four most common trematode species, as well as for geographic distance, biotic and abiotic distinctness of the localities. Our results showed that the most widely distributed parasites of bullies also achieve the highest mean local abundances, following the abundance – occupancy relationship. Variation in local abundance of any focal parasite species was independent of latitude, the abundance of co‐occurring species and spatial distance or disparity in biotic attributes between localities. For only one parasite species, similarity of abundance between sites covaried with the extent of abiotic differences between sites. The lack of association between hot spots of infection for co‐occurring species reinforces the geographic mosaic scenario in which hosts and parasites coevolve by suggesting non‐deterministic, species‐specific variation in parasite abundance across space.     

Interspecific competition constrains local abundance in highly suitable areas

Sites with high environmental suitability for species’ occurrence, in terms of abiotic conditions, may hold populations with higher local abundances by increasing reproductive and survival rates and decreasing extinction rate. Interspecific competition, however, may affect this relationship. Here we tested the hypothesis that local abundance of the gray slender opossum Marmosops incanus is affected by the local richness of potential competitors and environmental suitability derived from ecological niche models (ENMs). We also discuss the ability of distinct modelling methods to predict species’ abundance. We compiled occurrence records and information about M. incanus’ relative abundance from museums and published articles. Environmental suitability was derived from five algorithms using seven environmental predictors. To assess our hypothesis, we chose the best statistical models among generalised linear models and quantile regressions, and then tested whether the effects of richness of competitors on local abundance are stronger under highly suitable conditions. We found that environmental suitability given by presence-only methods are positively related to the maximum abundance of M. incanus. That is, species’ local abundance is low when suitability is low but can be either low or high when suitability is high. The richness of competitors, in turn, explains the abundance variation within sites with high environmental suitability. We strongly recommend that the relationship between abundance and suitability must be carefully interpreted when using ENMs to predict species’ distribution because biotic interactions can be the main driver of local abundance within highly suitable environments.     

Tree species distribution in temperate forests is more influenced by soil than by climate

Knowledge of the ecological requirements determining tree species distributions is a precondition for sustainable forest management. At present, the abiotic requirements and the relative importance of the different abiotic factors are still unclear for many temperate tree species. We therefore investigated the relative importance of climatic and edaphic factors for the abundance of 12 temperate tree species along environmental gradients. Our investigations are based on data from 1,075 forest stands across Switzerland including the cold‐induced tree line of all studied species and the drought‐induced range boundaries of several species. Four climatic and four edaphic predictors represented the important growth factors temperature, water supply, nutrient availability, and soil aeration. The climatic predictors were derived from the meteorological network of MeteoSwiss, and the edaphic predictors were available from soil profiles. Species cover abundances were recorded in field surveys. The explanatory power of the predictors was assessed by variation partitioning analyses with generalized linear models. For six of the 12 species, edaphic predictors were more important than climatic predictors in shaping species distribution. Over all species, abundances depended mainly on nutrient availability, followed by temperature, water supply, and soil aeration. The often co‐occurring species responded similar to these growth factors. Drought turned out to be a determinant of the lower range boundary for some species. We conclude that over all 12 studied tree species, soil properties were more important than climate variables in shaping tree species distribution. The inclusion of appropriate soil variables in species distribution models allowed to better explain species' ecological niches. Moreover, our study revealed that the ecological requirements of tree species assessed in local field studies and in experiments are valid at larger scales across Switzerland.     

Effect of Environmental and Temporal Factors on Patterns of Rarity of Ephemeroptera in Stream of the Brazilian Cerrado

Patterns of species’ abundance and occurrence over time and space allow division of species into (i) common species, which are abundant, but have a low diversity, and (ii) rare species, which are far more diverse and less abundant. Understanding the relationships among these two species groups and how they are affected by environmental conditions is a major challenge for ecologists, especially considering the distinction between local environmental factors and regional factors and variations in abundance over the course of the year. In this study, we focused on the long-term relationship between the abundance of rare and common ephemeropterans and abiotic factors on local and regional scales. Our hypotheses are that common species will be affected primarily by regional environmental variables (i), whereas rare species will be influenced more by temporal variation (ii). Together, both local and regional abiotic variables, plus temporal variation, best explained the abundance of the common species, whereas temporal variation was the best predictor of rare species. Considering the theoretical aspects and the empirical evidence, we discuss the results based on the plasticity of the common species and the life cycle of the rare ones. We believe that our findings reinforce the need for the deconstruction of communities for a deeper understanding of their relationships with abiotic variables and, in particular, the specific aspects of these relationships in the context of the different guilds of the community.     

Joint species distribution modelling for spatio‐temporal occurrence and ordinal abundance data

Aim

Species distribution models are important tools used to study the distribution and abundance of organisms relative to abiotic variables. Dynamic local interactions among species in a community can affect abundance. The abundance of a single species may not be at equilibrium with the environment for spreading invasive species and species that are range shifting because of climate change. Innovation : We develop methods for incorporating temporal processes into a spatial joint species distribution model for presence/absence and ordinal abundance data. We model non‐equilibrium conditions via a temporal random effect and temporal dynamics with a vector‐autoregressive process allowing for intra‐ and interspecific dependence between co‐occurring species. The autoregressive term captures how the abundance of each species can enhance or inhibit its own subsequent abundance or the subsequent abundance of other species in the community and is well suited for a ‘community modules’ approach of strongly interacting species within a food web. R code is provided for fitting multispecies models within a Bayesian framework for ordinal data with any number of locations, time points, covariates and ordinal categories.

Main conclusions

We model ordinal abundance data of two invasive insects (hemlock woolly adelgid and elongate hemlock scale) that share a host tree and were undergoing northwards range expansion in the eastern U.S.A. during the period 1997–2011. Accounting for range expansion and high inter‐annual variability in abundance led to improved estimation of the species–environment relationships. We would have erroneously concluded that winter temperatures did not affect scale abundance had we not accounted for the range expansion of scale. The autoregressive component revealed weak evidence for commensalism, in which adelgid may have predisposed hemlock stands for subsequent infestation by scale. Residual spatial dependence indicated that an unmeasured variable additionally affected scale abundance. Our robust modelling approach could provide similar insights for other community modules of co‐occurring species.     

Testing for local adaptation and evolutionary potential along altitudinal gradients in rainforest Drosophila: beyond laboratory estimates

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

Microhabitat relationships among five lizard species associated with granite outcrops in fragmented agricultural landscapes of south‐eastern Australia

A fundamental part of developing effective biodiversity conservation is to understand what factors affect the distribution and abundance of particular species. However, there is a paucity of data on ecological requirements and habitat relationships for many species, especially for groups such as reptiles. Furthermore, it is not clear whether habitat relationships for particular species in a given environment are transferable to other environments within their geographical range. This has implications for the type of ‘landscape model’ used to guide management decisions in different environments worldwide. To test the hypothesis that species‐specific habitat relationships are transferable to other environments, we present microhabitat models for five common lizard species from a poorly studied habitat – insular granite outcrops, and then compared these relationships with studies from other environments in south‐eastern Australia. We recorded twelve species from five families, representing 699 individuals, from 44 outcrops in the south‐west slopes of New South Wales. Five lizard species were abundant and accounted for 95% of all observations: Egernia striolata, Ctenotus robustus, Cryptoblepharus carnabyi, Morethia boulengeri and Carlia tetradactyla (Scincidae). Linear regression modelling revealed suites of different variables related to the abundance patterns of individual species, some of which were broadly congruent with those measured for each species in other environments. However, additional variables, particular to rocky environments, were found to relate to reptile abundance in this environment. This finding means that species' habitat relationships in one habitat may not be readily transferable to other environments, even those relatively close by. Based on these data, management decisions targeting reptile conservation in agricultural landscapes, which contain rocky outcrops, will be best guided by landscape models that not only recognize gradients in habitat suitability, but are also flexible enough to incorporate intraspecies habitat variability.     

Accounting for dispersal and biotic interactions to disentangle the drivers of species distributions and their abundances

Although abiotic factors, together with dispersal and biotic interactions, are often suggested to explain the distribution of species and their abundances, species distribution models usually focus on abiotic factors only. We propose an integrative framework linking ecological theory, empirical data and statistical models to understand the distribution of species and their abundances together with the underlying community assembly dynamics. We illustrate our approach with 21 plant species in the French Alps. We show that a spatially nested modelling framework significantly improves the model's performance and that the spatial variations of species presence-absence and abundances are predominantly explained by different factors. We also show that incorporating abiotic, dispersal and biotic factors into the same model bring new insights to our understanding of community assembly. This approach, at the crossroads between community ecology and biogeography, is a promising avenue for a better understanding of species co-existence and biodiversity distribution.     

Species distribution,ecology, abundance,body size and phylogeny originate interrelated rarity patterns at regional scale

The most pervasive macroecological patterns concern (1) the frequency distribution of range size, (2) the relationship between range size and species abundance and (3) the effect of body size on range size. We investigated these patterns at a regional scale using the tenebrionid beetles of Latium (Central Italy). For this, we calculated geographical range size (no. of 10‐km square cells), ecological tolerance (no. of phytoclimatic units) and abundance (no. of sampled individuals) using a large database containing 3561 georeferenced records for 84 native species. For each species, we also calculated body mass and its ‘phylogenetic diversity’ on the basis of cladistic relationships. Frequency distribution of range size followed a log‐normal distribution as found in many other animal groups. However, a log‐normal distribution accommodated well the frequency distribution of ecological tolerance, a so far unexplored issue. Range size was correlated with abundance and ecological tolerance, thus supporting the hypothesis that a positive correlation between distribution and abundance is a reflection of interspecific differences in ecological specialization. Larger species tended to have larger ranges and broader ecological tolerance. However, contrary to what known in most vertebrates, not only small‐sized, but also many medium‐to‐large‐sized species exhibited great variability in their range size, probably because tenebrionids are not so strictly influenced by body size constraints (e.g. home ranges) as vertebrates. Moreover, in contrast to other animals, tenebrionid body size does not influence species abundances, probably because these detritivorous animals are not strongly regulated by competition. Finally, contrary to the assumption that rare species should be mainly found among lineages that split from basal nodes, rarity of a tenebrionid species was not influenced by the phylogenetic position of its tribe. However, lineages that split from more basal nodes had lower variability in terms of species geographical distribution, ecological tolerance and abundance, which suggests that lineages that split from more basal nodes are not only morphologically conservative but also tend to have an ecological ‘inertia’.     

Spatial segregation of sympatric marten and fishers: the influence of landscapes and species‐scapes

Co‐occurring species are rarely considered as a factor influencing habitat selection. However, niche theory predicts that sharing resources, predators, and other interspecific interactions can limit the environmental conditions under which a species may exist. How does the spatial distribution of one species affect that of another within shared landscapes? We tested whether sympatric marten Martes americana and fishers M. pennanti in a mountain landscape in Alberta, Canada exhibit local‐scale spatial segregation, beyond differential habitat selection. We modelled marten and fisher distribution in relation to remotely‐sensed habitat data and species co‐occurrence, using generalized linear models and information‐theoretic model selection. Marten and fishers selected different habitat types and showed different responses to habitat fragmentation. Even after accounting for these differences, the absence of one species significantly explained the occurrence of the other. We conclude that the spatial distribution of marten and fishers influences habitat selection by each other at landscape scales, and hypothesize that this pattern may result from competition in a spatially heterogeneous environment. Species‐habitat models that consider only resources may fail to capture key predictors of species’ occurrence. Reliable prediction and inference requires that ecologists expand from landscapes to also include species‐scapes: a spatial plane of species interactions that combines with resources to drive species’ distributions.     

Untangling associations between chironomid taxa in Neotropical streams using local and landscape filters

1. Analyses of species association have major implications for selecting indicators for freshwater biomonitoring and conservation, because they allow for the elimination of redundant information and focus on taxa that can be easily handled and identified. These analyses are particularly relevant in the debate about using speciose groups (such as the Chironomidae) as indicators in the tropics, because they require difficult and time‐consuming analysis, and their responses to environmental gradients, including anthropogenic stressors, are poorly known. 2. Our objective was to show whether chironomid assemblages in Neotropical streams include clear associations of taxa and, if so, how well these associations could be explained by a set of models containing information from different spatial scales. For this, we formulated a priori models that allowed for the influence of local, landscape and spatial factors on chironomid taxon associations (CTA). These models represented biological hypotheses capable of explaining associations between chironomid taxa. For instance, CTA could be best explained by local variables (e.g. pH, conductivity and water temperature) or by processes acting at wider landscape scales (e.g. percentage of forest cover). 3. Biological data were taken from 61 streams in Southeastern Brazil, 47 of which were in well‐preserved regions, and 14 of which drained areas severely affected by anthropogenic activities. We adopted a model selection procedure using Akaike’s information criterion to determine the most parsimonious models for explaining CTA. 4. Applying Kendall’s coefficient of concordance, seven genera (Tanytarsus/Caladomyia, Ablabesmyia, Parametriocnemus, Pentaneura, Nanocladius, Polypedilum and Rheotanytarsus) were identified as associated taxa. The best‐supported model explained 42.6% of the total variance in the abundance of associated taxa. This model combined local and landscape environmental filters and spatial variables (which were derived from eigenfunction analysis). However, the model with local filters and spatial variables also had a good chance of being selected as the best model. 5. Standardised partial regression coefficients of local and landscape filters, including spatial variables, derived from model averaging allowed an estimation of which variables were best correlated with the abundance of associated taxa. In general, the abundance of the associated genera tended to be lower in streams characterised by a high percentage of forest cover (landscape scale), lower proportion of muddy substrata and high values of pH and conductivity (local scale). 6. Overall, our main result adds to the increasing number of studies that have indicated the importance of local and landscape variables, as well as the spatial relationships among sampling sites, for explaining aquatic insect community patterns in streams. Furthermore, our findings open new possibilities for the elimination of redundant data in the assessment of anthropogenic impacts on tropical streams.     

Role of topography and soils in grassland structuring at the landscape and community scales

The relative importance of abiotic factors in community assembly is debated and thought to be dependent on the scale. I investigated the relative role of topography and soils as structuring agents at the landscape and the community scales in 126 subalpine calcareous grasslands in the Pyrenees, in terms of species composition and abundance. I wished to know: (1) the role of abiotic factors in the organization of plant communities across the landscape; (2) how much of the variation in community distribution was accounted for by abiotic factors; and (3) how well their role applied to the distribution of dominant species at the landscape and the community scales. The hypothesis was: abiotic factors play an important role in community distribution in the landscape, but species interactions are more important within communities. Multivariate methods generated four communities, organized in two contrasting groups along the main vegetation axis, which explained 13% of the variation: mesic grasslands (Nardus stricta and Festuca nigrescens communities) and xeric grasslands (Carex humilis and Festuca gautieri communities). Mesic communities were more acidic and fertile than xeric communities. Changes in the abiotic environment, accounting for up to 80% of the variation in the vegetation, were smooth, while the transition between xeric and mesic grasslands was sharp in terms of species composition. The distribution in the landscape of the first main species from each community was closely related to abiotic factors, which modeled poorly the abundance of the main species at smaller scales. At the within-community scale, the explanatory power of biotic relationships was community dependent, producing the most significant models for plants highly dominant within their communities, such as N. stricta and F. gautieri. Contrary to current hypothesis, there was a shift from mainly positive relationships among dominant species in fertile mesic communities to mainly negative in infertile xeric ones.     

The shape of abundance distributions across temperature gradients in reef fishes

Improving predictions of ecological responses to climate change requires understanding how local abundance relates to temperature gradients, yet many factors influence local abundance in wild populations. We evaluated the shape of thermal‐abundance distributions using 98 422 abundance estimates of 702 reef fish species worldwide. We found that curved ceilings in local abundance related to sea temperatures for most species, where local abundance declined from realised thermal ‘optima’ towards warmer and cooler environments. Although generally supporting the abundant‐centre hypothesis, many species also displayed asymmetrical thermal‐abundance distributions. For many tropical species, abundances did not decline at warm distribution edges due to an unavailability of warmer environments at the equator. Habitat transitions from coral to macroalgal dominance in subtropical zones also influenced abundance distribution shapes. By quantifying the factors constraining species’ abundance, we provide an important empirical basis for improving predictions of community re‐structuring in a warmer world.     

Fine scale prediction of ecological community composition using a two-step sequential Machine Learning ensemble

Prediction is one of the last frontiers in ecology. Indeed, predicting fine-scale species composition in natural systems is a complex challenge as multiple abiotic and biotic processes operate simultaneously to determine local species abundances. On the one hand, species intrinsic performance and their tolerance limits to different abiotic pressures modulate species abundances. On the other hand, there is growing recognition that species interactions play an equally important role in limiting or promoting such abundances within ecological communities. Here, we present a joint effort between ecologists and data scientists to use data-driven models to predict species abundances using reasonably easy to obtain data. We propose a sequential data-driven modeling approach that in a first step predicts the potential species abundances based on abiotic variables, and in a second step uses these predictions to model the realized abundances once accounting for species competition. Using a curated data set over five years we predict fine-scale species abundances in a highly diverse annual plant community. Our models show a remarkable spatial predictive accuracy using only easy-to-measure variables in the field, yet such predictive power is lost when temporal dynamics are taken into account. This result suggests that predicting future abundances requires longer time series analysis to capture enough variability. In addition, we show that these data-driven models can also suggest how to improve mechanistic models by adding missing variables that affect species performance such as particular soil conditions (e.g. carbonate availability in our case). Robust models for predicting fine-scale species composition informed by the mechanistic understanding of the underlying abiotic and biotic processes can be a pivotal tool for conservation, especially given the human-induced rapid environmental changes we are experiencing. This objective can be achieved by promoting the knowledge gained with classic modelling approaches in ecology and recently developed data-driven models.     

Frequent and occasional species and the shape of relative-abundance distributions

Recently, three different models have been proposed to explain the distribution of abundances in natural communities: the self‐similarity model; the zero‐sum ecological drift model; and the occasional–frequent species model of Magurran and Henderson. Here we study patterns of relative abundance in a large community of forest Hymenoptera and show that it is indeed possible to divide the community into a group of frequent species and a group of occasional species. In accordance with the third model, frequent species followed a lognormal distribution. Relative abundances of the occasional species could be described by the self‐similarity model, but did not follow a log‐series as proposed by the occasional–frequent model. The zero‐sum ecological drift model makes no explicit predictions about frequent and occasional species but the abundance distributions of the hymenopteran species did not show the excess of rare species predicted by this model. Separate fits of this model to the frequent and to the occasional species were worse than the respective fits of the lognormal and the self‐similarity model.     

Impact of landscape predictors on climate change modelling of species distributions: a case study with Eucalyptus fastigata in southern New South Wales,Australia

Aim We consider three questions. (1) How different are the predicted distribution maps when climate‐only and climate‐plus‐terrain models are developed from high‐resolution data? (2) What are the implications of differences between the models when predicting future distributions under climate change scenarios, particularly for climate‐only models at coarse resolution? (3) Does the use of high‐resolution data and climate‐plus‐terrain models predict an increase in the number of local refugia? Location South‐eastern New South Wales, Australia. Methods We developed two species distribution models for Eucalyptus fastigata under current climate conditions using generalized additive modelling. One used only climate variables as predictors (mean annual temperature, mean annual rainfall, mean summer rainfall); the other used both climate and landscape (June daily radiation, topographic position, lithology, nutrients) variables as predictors. Predictions of the distribution under current climate and climate change were then made for both models at a pixel resolution of 100 m. Results The model using climate and landscape variables as predictors explained a significantly greater proportion of the deviance than the climate‐only model. Inclusion of landscape variables resulted in the prediction of much larger areas of existing optimal habitat. An overlay of predicted future climate on the current climate space indicated that extrapolation of the statistical models was not occurring and models were therefore more robust. Under climate change, landscape‐defined refugia persisted in areas where the climate‐only model predicted major declines. In areas where expansion was predicted, the increase in optimal habitat was always greater with landscape predictors. Recognition of extensive optimal habitat conditions and potential refugia was dependent on the use of high‐resolution landscape data. Main conclusions Using only climate variables as predictors for assessing species responses to climate change ignores the accepted conceptual model of plant species distribution. Explicit statements justifying the selection of predictors based on ecological principles are needed. Models using only climate variables overestimate range reduction under climate change and fail to predict potential refugia. Fine‐scale‐resolution data are required to capture important climate/landscape interactions. Extrapolation of statistical models to regions in climate space outside the region where they were fitted is risky.