Prey resources are equally important as climatic conditions for predicting the distribution of a broad-ranged apex predator

Aim

A current biogeographic paradigm states that climate regulates species distributions at continental scales and that biotic interactions are undetectable at coarse-grain extents. However, advances in spatial modelling show that incorporating food resource distributions are important for improving model predictions at large distribution scales. This is particularly relevant to understand the factors limiting the distribution of widespread apex predators whose diets are likely to vary across their range.

Location

Neotropical Central and South America.

Methods

The harpy eagle (Harpia harpyja) is a large raptor, whose diet is largely comprised of arboreal mammals, all with broad distributions across Neotropical lowland forest. Here, we used a hierarchical modelling approach to determine the relative importance of abiotic factors and prey resource distribution on harpy eagle range limits. Our hierarchical approach consisted of the following modelling sequence of explanatory variables: (a) abiotic covariates, (b) prey resource distributions predicted by an equivalent modelling for each prey, (c) the combination of (a) and (b), and (d) as in (c) but with prey resources considered as a single prediction equivalent to prey species richness.

Results

Incorporating prey distributions improved model predictions but using solely biotic covariates still resulted in a high-performing model. In the Abiotic model, Climatic Moisture Index (CMI) was the most important predictor, contributing 76% to model prediction. Three-toed sloth (Bradypus spp.) was the most important prey resource, contributing 64% in a combined Abiotic-Biotic model, followed by CMI contributing 30%. Harpy eagle distribution had high environmental overlap across all individual prey distributions, with highest coincidence through Central America, eastern Colombia, and across the Guiana Shield into northern Amazonia.

Main Conclusions

With strong reliance on prey distributions across its range, harpy eagle conservation programmes must therefore consider its most important food resources as a key element in the protection of this threatened raptor.     

Determinants of palm species distributions across Africa: the relative roles of climate,non‐climatic environmental factors,and spatial constraints

Most of the Earth's biodiversity resides in the tropics. However, a comprehensive understanding of which factors control range limits of tropical species is still lacking. Climate is often thought to be the predominant range‐determining mechanism at large spatial scales. Alternatively, species’ ranges may be controlled by soil or other environmental factors, or by non‐environmental factors such as biotic interactions, dispersal barriers, intrinsic population dynamics, or time‐limited expansion from place of origin or past refugia. How species ranges are controlled is of key importance for predicting their responses to future global change. Here, we use a novel implementation of species distribution modelling (SDM) to assess the degree to which African continental‐scale species distributions in a keystone tropical group, the palms (Arecaceae), are controlled by climate, non‐climatic environmental factors, or non‐environmental spatial constraints. A comprehensive data set on African palm species occurrences was assembled and analysed using the SDM algorithm Maxent in combination with climatic and non‐climatic environmental predictors (habitat, human impact), as well as spatial eigenvector mapping (spatial filters). The best performing models always included spatial filters, suggesting that palm species distributions are always to some extent limited by non‐environmental constraints. Models which included climate provided significantly better predictions than models that included only non‐climatic environmental predictors, the latter having no discernible effect beyond the climatic control. Hence, at the continental scale, climate constitutes the only strong environmental control of palm species distributions in Africa. With regard to the most important climatic predictors of African palm distributions, water‐related factors were most important for 25 of the 29 species analysed. The strong response of palm distributions to climate in combination with the importance of non‐environmental spatial constraints suggests that African palms will be sensitive to future climate changes, but that their ability to track suitable climatic conditions will be spatially constrained.     

Predicting the distribution of four species of raptors (Aves: Accipitridae) in southern Spain: statistical models work better than existing maps

Aim To test the effectiveness of statistical models based on explanatory environmental variables vs. existing distribution information (maps and breeding atlas), for predicting the distribution of four species of raptors (family Accipitridae): common buzzard Buteo buteo (Linnaeus, 1758), short‐toed eagle Circaetus gallicus (Gmelin, 1788), booted eagle Hieraaetus pennatus (Gmelin, 1788) and black kite Milvus migrans (Boddaert, 1783). Location Andalusia, southern Spain. Methods Generalized linear models of 10 × 10 km squares surveyed for the presence/absence of the species by road census. Statistical models use as predictors variables derived from topography, vegetation and land‐use, and the geographical coordinates (to take account of possible spatial trends). Predictions from the models are compared with current distribution maps from the national breeding atlas and leading reference works. Results The maps derived from statistical models for all four species were more predictive than the previously published range maps and the recent national breeding atlas. The best models incorporated both topographic and vegetation and land‐use variables. Further, in three of the four species the inclusion of spatial coordinates to account for neighbourhood effects improved these models. Models for the common buzzard and black kite were highly predictive and easy to interpret from an ecological point of view, while models for short‐toed eagle and, particularly, booted eagle were not so easy to interpret, but still predicted better than previous distribution information. Main conclusions It is possible to build accurate predictive models for raptor distribution with a limited field survey using as predictors environmental variables derived from digital maps. These models integrated in a geographical information system produced distribution maps that were more accurate than previously published ones for the study species in the study area. Our study is an example of a methodology that could be used for many taxa and areas to improve unreliable distribution information.     

Predicting current and future global distributions of whale sharks

The Vulnerable (IUCN) whale shark spans warm and temperate waters around the globe. However, their present‐day and possible future global distribution has never been predicted. Using 30 years (1980–2010) of whale shark observations recorded by tuna purse‐seiners fishing in the Atlantic, Indian and Pacific Oceans, we applied generalized linear mixed‐effects models to test the hypothesis that similar environmental covariates predict whale shark occurrence in all major ocean basins. We derived global predictors from satellite images for chlorophyll a and sea surface temperature, and bathymetric charts for depth, bottom slope and distance to shore. We randomly generated pseudo‐absences within the area covered by the fisheries, and included fishing effort as an offset to account for potential sampling bias. We predicted sea surface temperatures for 2070 using an ensemble of five global circulation models under a no climate‐policy reference scenario, and used these to predict changes in distribution. The full model (excluding standard deviation of sea surface temperature) had the highest relative statistical support (wAIC_c = 0.99) and explained ca. 60% of the deviance. Habitat suitability was mainly driven by spatial variation in bathymetry and sea surface temperature among oceans, although these effects differed slightly among oceans. Predicted changes in sea surface temperature resulted in a slight shift of suitable habitat towards the poles in both the Atlantic and Indian Oceans (ca. 5°N and 3–8°S, respectively) accompanied by an overall range contraction (2.5–7.4% and 1.1–6.3%, respectively). Predicted changes in the Pacific Ocean were small. Assuming that whale shark environmental requirements and human disturbances (i.e. no stabilization of greenhouse gas emissions) remain similar, we show that warming sea surface temperatures might promote a net retreat from current aggregation areas and an overall redistribution of the species.     

Distribution and diversity of palms in a tropical biodiversity hotspot (Thailand) assessed by species distribution modeling

Species distribution modeling has been widely used to address questions related to ecology, biogeography and species conservation on global and regional scales. Here, we study palms (Arecaceae) in a tropical biodiversity hotspot (Thailand) using species distribution modeling to assess range‐limiting factors and estimate distribution and diversity patterns based on a comprehensive compilation of occurrence records. We focused on palms as a model group due to their key‐stone importance for ecosystem functioning and socio‐economics. Different combinations of climatic, non‐climatic environmental and spatial predictors were used. The most accurate models as indicated by the ‘area under the receiver operating characteristic curve’ (AUC) statistic were those that combined all predictors. The four strongest single predictors of palm species distributions were, in decreasing order of importance, 1) latitude, 2) precipitation of driest quarter, 3) annual precipitation, and 4) minimum temperature of the coldest month, suggesting rainfall patterns and latitudinal spatial constraints as the main range determinants. Overlaying the predicted distributions revealed that potential palm hotspots are situated in the provinces of Satun and Yala in southern Thailand where vast areas remain relatively open to the discovery of new palm records and perhaps even new species.     

Co‐occurrence patterns of trees along macro‐climatic gradients and their potential influence on the present and future distribution of Fagus sylvatica L.

Aim During recent and future climate change, shifts in large‐scale species ranges are expected due to the hypothesized major role of climatic factors in regulating species distributions. The stress‐gradient hypothesis suggests that biotic interactions may act as major constraints on species distributions under more favourable growing conditions, while climatic constraints may dominate under unfavourable conditions. We tested this hypothesis for one focal tree species having three major competitors using broad‐scale environmental data. We evaluated the variation of species co‐occurrence patterns in climate space and estimated the influence of these patterns on the distribution of the focal species for current and projected future climates. Location Europe. Methods We used ICP Forest Level 1 data as well as climatic, topographic and edaphic variables. First, correlations between the relative abundance of European beech (Fagus sylvatica) and three major competitor species (Picea abies, Pinus sylvestris and Quercus robur) were analysed in environmental space, and then projected to geographic space. Second, a sensitivity analysis was performed using generalized additive models (GAM) to evaluate where and how much the predicted F. sylvatica distribution varied under current and future climates if potential competitor species were included or excluded. We evaluated if these areas coincide with current species co‐occurrence patterns. Results Correlation analyses supported the stress‐gradient hypothesis: towards favourable growing conditions of F. sylvatica, its abundance was strongly linked to the abundance of its competitors, while this link weakened towards unfavourable growing conditions, with stronger correlations in the south and at low elevations than in the north and at high elevations. The sensitivity analysis showed a potential spatial segregation of species with changing climate and a pronounced shift of zones where co‐occurrence patterns may play a major role. Main conclusions Our results demonstrate the importance of species co‐occurrence patterns for calibrating improved species distribution models for use in projections of climate effects. The correlation approach is able to localize European areas where inclusion of biotic predictors is effective. The climate‐induced spatial segregation of the major tree species could have ecological and economic consequences.     

Host species,and not environment,predicts variation in blood parasite prevalence,distribution, and diversity along a humidity gradient in northern South America

Environmental factors strongly influence the ecology and evolution of vector‐borne infectious diseases. However, our understanding of the influence of climatic variation on host–parasite interactions in tropical systems is rudimentary. We studied five species of birds and their haemosporidian parasites (Plasmodium and Haemoproteus) at 16 sampling sites to understand how environmental heterogeneity influences patterns of parasite prevalence, distribution, and diversity across a marked gradient in water availability in northern South America. We used molecular methods to screen for parasite infections and to identify parasite lineages. To characterize spatial heterogeneity in water availability, we used weather‐station and remotely sensed climate data. We estimated parasite prevalence while accounting for spatial autocorrelation, and used a model selection approach to determine the effect of variables related to water availability and host species on prevalence. The prevalence, distribution, and lineage diversity of haemosporidian parasites varied among localities and host species, but we found no support for the hypothesis that the prevalence and diversity of parasites increase with increasing water availability. Host species and host × climate interactions had stronger effects on infection prevalence, and parasite lineages were strongly associated with particular host species. Because climatic variables had little effect on the overall prevalence and lineage diversity of haemosporidian parasites across study sites, our results suggest that independent host–parasite dynamics may influence patterns in parasitism in environmentally heterogeneous landscapes.     

Is current climatic equilibrium a guarantee for the transferability of distribution model predictions? A case study of the spotted hyena

Aim The transferability of species distribution models requires that species show climatic equilibrium throughout their entire distribution area. We test this assumption for the case of the spotted hyena, Crocuta crocuta, a large carnivore that has shifted its distribution over the last 100,000 years from a widespread Eurasian and African range to its current geographical distribution, restricted to the Sub‐Saharan areas of the African continent. Location Western Eurasia and Africa. Methods The current realized distribution of C. crocuta was estimated using presences and reliable absences as well as climatic, land‐cover and anthropic variables as predictors. The potential distribution was estimated using presences and a set of pseudo‐absences selected from localities outside climatically suitable localities, with only climatic variables serving as predictors. The current potential distribution was transferred to the Last Interglacial period (126,000 yr bp ) using the palaeoclimatic data yielded by the GENESIS 2 general circulation model, and validated with European fossil data. Generalized linear models were used on all occasions. Results Climatic variables are able to predict the current distribution of the species with high accuracy. The geographical projection of this model indicates that the species is distributed over almost all of its potential suitable area, which allows us to suppose that the current distribution of this species is in climatic equilibrium. However, the time transference of model predictions for the western Eurasian region reveals almost no suitable conditions for hyenas, despite the widespread presence of C. crocuta fossil remains on this continent during the Last Interglacial period. Main conclusions Our results indicate that, even when model results suggest a climatic equilibrium for a species distribution, the time transferability of such models does not necessarily provide realistic results. This occurs because the current geographical range does not allow estimations of all of the environmental requirements of a species. Therefore, any model trained with current data risks underestimating the potential suitable environmental and geographical range for species in a new area or time period.     

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.     

Isolation by instability: Historical climate change shapes population structure and genomic divergence of treefrogs in the Neotropical Cerrado savanna

Although the impact of Pleistocene glacial cycles on the diversification of the tropical biota was once dismissed, increasing evidence suggests that Pleistocene climatic fluctuations greatly affected the distribution and population divergence of tropical organisms. Landscape genomic analyses coupled with paleoclimatic distribution models provide a powerful way to understand the consequences of past climate changes on the present‐day tropical biota. Using genome‐wide SNP data and mitochondrial DNA, combined with projections of the species distribution across the late Quaternary until the present, we evaluate the effect of paleoclimatic shifts on the genetic structure and population differentiation of Hypsiboas lundii, a treefrog endemic to the South American Cerrado savanna. Our results show a recent and strong genetic divergence in H. lundii across the Cerrado landscape, yielding four genetic clusters that do not seem congruent with any current physical barrier to gene flow. Isolation by distance (IBD) explains some of the population differentiation, but we also find strong support for past climate changes promoting range shifts and structuring populations even in the presence of IBD. Post‐Pleistocene population persistence in four main areas of historical stable climate in the Cerrado seems to have played a major role establishing the present genetic structure of this treefrog. This pattern is consistent with a model of reduced gene flow in areas with high climatic instability promoting isolation of populations, defined here as “isolation by instability,” highlighting the effects of Pleistocene climatic fluctuations structuring populations in tropical savannas.     

When and where to move: Dynamic occupancy models explain the range dynamics of a food nomadic bird under climate and land cover change

Globally, long‐term research is critical to monitor the responses of tropical species to climate and land cover change at the range scale. Citizen science surveys can reveal the long‐term persistence of poorly known nomadic tropical birds occupying fragmented forest patches. We applied dynamic occupancy models to 13 years (2002–2014) of citizen science‐driven presence/absence data on Cape parrot (Poicephalus robustus), a food nomadic bird endemic to South Africa. We modeled its underlying range dynamics as a function of resource distribution, and change in climate and land cover through the estimation of colonization and extinction patterns. The range occupancy of Cape parrot changed little over time (ψ = 0.75–0.83) because extinction was balanced by recolonization. Yet, there was considerable regional variability in occupancy and detection probability increased over the years. Colonizations increased with warmer temperature and area of orchards, thus explaining their range shifts southeastwards in recent years. Although colonizations were higher in the presence of nests and yellowwood trees (Afrocarpus and Podocarpus spp.), the extinctions in small forest patches (≤227 ha) and during low precipitation (≤41 mm) are attributed to resource constraints and unsuitable climatic conditions. Loss of indigenous forest cover and artificial lake/water bodies increased extinction probabilities of Cape parrot. The land use matrix (fruit farms, gardens, and cultivations) surrounding forest patches provides alternative food sources, thereby facilitating spatiotemporal colonization and extinction in the human‐modified matrix. Our models show that Cape parrots are vulnerable to extreme climatic conditions such as drought which is predicted to increase under climate change. Therefore, management of optimum sized high‐quality forest patches is essential for long‐term survival of Cape parrot populations. Our novel application of dynamic occupancy models to long‐term citizen science monitoring data unfolds the complex relationships between the environmental dynamics and range fluctuations of this food nomadic species.     

Losing ground: past history and future fate of Arctic small mammals in a changing climate

According to the IPCC, the global average temperature is likely to increase by 1.4–5.8 °C over the period from 1990 to 2100. In Polar regions, the magnitude of such climatic changes is even larger than in temperate and tropical biomes. This amplified response is particularly worrisome given that the so‐far moderate warming is already impacting Arctic ecosystems. Predicting species responses to rapid warming in the near future can be informed by investigating past responses, as, like the rest of the planet, the Arctic experienced recurrent cycles of temperature increase and decrease (glacial–interglacial changes) in the past. In this study, we compare the response of two important prey species of the Arctic ecosystem, the collared lemming and the narrow‐skulled vole, to Late Quaternary climate change. Using ancient DNA and Ecological Niche Modeling (ENM), we show that the two species, which occupy similar, but not identical ecological niches, show markedly different responses to climatic and environmental changes within broadly similar habitats. We empirically demonstrate, utilizing coalescent model‐testing approaches, that collared lemming populations decreased substantially after the Last Glacial Maximum; a result consistent with distributional loss over the same period based on ENM results. Given this strong association, we projected the current niche onto future climate conditions based on IPCC 4.0 scenarios, and forecast accelerating loss of habitat along southern range boundaries with likely associated demographic consequences. Narrow‐skulled vole distribution and demography, by contrast, was only moderately impacted by past climatic changes, but predicted future changes may begin to affect their current western range boundaries. Our work, founded on multiple lines of evidence suggests a future of rapidly geographically shifting Arctic small mammal prey communities, some of whom are on the edge of existence, and whose fate may have ramifications for the whole Arctic food web and ecosystem.     

The significance of geographic range size for spatial diversity patterns in Neotropical palms

We examined the effect of range size in commonly applied macroecological analyses using continental distribution data for all 550 Neotropical palm species (Arecaceae) at varying grain sizes from 0.5° to 5°. First, we evaluated the relative contribution of range-restricted and widespread species on the patterns of species richness and endemism. Second, we analysed the impact of range size on the predictive value of commonly used predictor variables. Species sequences were produced arranging species according to their range size in ascending, descending, and random order. Correlations between the cumulative species richness patterns of these sequences and environmental predictors were performed in order to analyse the effect of range size. Despite the high proportion of rare species, patterns of species richness were found to be dominated by a minority of widespread species (∼20%) which contained 80% of the spatial information. Climatic factors related to energy and water availability and productivity accounted for much of the spatial variation of species richness of widespread species. In contrast, species richness of range-restricted species was to a larger extent determined by topographical complexity. However, this effect was much more difficult to detect due to a dominant influence of widespread species. Although the strength of different environmental predictors changed with spatial scale, the general patterns and trends proved to be relatively stabile at the examined grain sizes. Our results highlight the difficulties to approximate causal explanations for the occurrence of a majority of species and to distinguish between contemporary climatic factors and history.     

Backcasting the decline of a vulnerable Great Plains reproductive ecotype: identifying threats and conservation priorities

Conservation efforts for threatened or endangered species are challenging because the multi‐scale factors that relate to their decline or inhibit their recovery are often unknown. To further exacerbate matters, the perceptions associated with the mechanisms of species decline are often viewed myopically rather than across the entire species range. We used over 80 years of fish presence data collected from the Great Plains and associated ecoregions of the United States, to investigate the relative influence of changing environmental factors on the historic and current truncated distributions of the Arkansas River shiner Notropis girardi. Arkansas River shiner represent a threatened reproductive ecotype considered especially well adapted to the harsh environmental extremes of the Great Plains. Historic (n = 163 records) and current (n = 47 records) species distribution models were constructed using a vector‐based approach in MaxEnt by splitting the available data at a time when Arkansas River shiner dramatically declined. Discharge and stream order were significant predictors in both models; however, the shape of the relationship between the predictors and species presence varied between time periods. Drift distance (river fragment length available for ichthyoplankton downstream drift before meeting a barrier) was a more important predictor in the current model and indicated river segments 375–780 km had the highest probability of species presence. Performance for the historic and current models was high (area under the curve; AUC > 0.95); however, forecasting and backcasting to alternative time periods suggested less predictive power. Our results identify fragments that could be considered refuges for endemic plains fish species and we highlight significant environmental factors (e.g., discharge) that could be manipulated to aid recovery.     

Introduced cats Felis catus eating a continental fauna: inventory and traits of Australian mammal species killed

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Spatial modelling of ecological indicator values improves predictions of plant distributions in complex landscapes

Ecologically meaningful predictors are often neglected in plant distribution studies, resulting in incomplete niche quantification and low predictive power of species distribution models (SDMs). Because environmental data are rare and expensive to collect, and because their relationship with local climatic and topographic conditions are complex, mapping them over large geographic extents and at high spatial resolution remains a major challenge. Here, we propose to derive environmental data layers by mapping ecological indicator values in space. We combined ~6 million plant occurrences with expert-based plant ecological indicator values (EIVs) of 3600 species in Switzerland. EIVs representing local soil properties (pH, moisture, moisture variability, aeration, humus and nutrients) and climatic conditions (continentality, light) were modelled at 93 m spatial resolution with the Random Forest algorithm and 16 predictors representing meso-climate, land use, topography and geology. Models were evaluated and predictions of EIVs were compared with soil inventory data. We mapped each EIV separately and evaluated EIV importance in explaining the distribution of 500 plant species using SDMs with a set of 30 environmental predictors. Finally, we tested how they improve an ensemble of SDMs compared to a standard set of predictors for ca 60 plant species. All EIV models showed excellent performance (|r| > 0.9) and predictions were correlated reasonably (|r| > 0.4) to soil properties measured in the field. Resulting EIV maps were among the most important predictors in SDMs. Also, in ensemble SDMs overall predictive performance increased, mainly through improved model specificity reducing species range overestimation. Combining large citizen science databases to expert-based EIVs is a powerful and cost–effective approach for generalizing local edaphic and climatic conditions over large areas. Producing ecologically meaningful predictors is a first step for generating better predictions of species distribution which is of main importance for decision makers in conservation and environmental management projects.     

Habitat distribution models for intertidal seaweeds: responses to climatic and non‐climatic drivers

Aim Because intertidal organisms often live close to their physiological tolerance limits, they are potentially sensitive indicators of climate‐driven changes in the environment. The goals of this study were to assess the effect of climatic and non‐climatic factors on the geographical distribution of intertidal macroalgae, and to predict future distributions under different climate‐warming scenarios. Location North‐western Iberian Peninsula, southern Europe. Methods We developed distribution models for six ecologically important intertidal seaweed species. Occurrence and microhabitat data were sampled at 1‐km² resolution and analysed with climate variables measured at larger spatial scales. We used generalized linear models and applied the deviance and Bayesian information criterion to model the relationship between environmental variables and the distribution of each target species. We also used hierarchical partitioning (HP) to identify predictor variables with higher independent explanatory power. Results The distributions of Himanthalia elongata and Bifurcaria bifurcata were correlated with measures of terrestrial and marine climate, although in opposite directions. Model projections under two warming scenarios indicated the extinction of the former at a faster rate in the Cantabrian Sea (northern Spain) than in the Atlantic (west). In contrast, these models predicted an increase in the occurrence of B. bifurcata in both areas. The occurrences of Ascophyllum nodosum and Pelvetia canaliculata, species showing rather static historical distributions, were related to specific non‐climatic environmental conditions and locations, such as the location of sheltered sites. At the southernmost distributional limit, these habitats may present favourable microclimatic conditions or provide refuges from competitors or natural enemies. Model performances for Fucus vesiculosus and F. serratus were similar and poor, but several climatic variables influenced the occurrence of the latter in the HP analyses. Main conclusions The correlation between species distributions and climate was evident for two species, whereas the distributions of the others were associated with non‐climatic predictors. We hypothesize that the distribution of F. serratus responds to diverse combinations of factors in different sections of the north‐west Iberian Peninsula. Our study shows how the response of species distributions to climatic and non‐climatic variables may be complex and vary geographically. Our analyses also highlight the difficulty of making predictions based solely on variation in climatic factors measured at coarse spatial scales.     

Type and spatial structure of distribution data and the perceived determinants of geographical gradients in ecology: the species richness of African birds

Aim Studies exploring the determinants of geographical gradients in the occurrence of species or their traits obtain data by: (1) overlaying species range maps; (2) mapping survey‐based species counts; or (3) superimposing models of individual species’ distributions. These data types have different spatial characteristics. We investigated whether these differences influence conclusions regarding postulated determinants of species richness patterns. Location Our study examined terrestrial bird diversity patterns in 13 nations of southern and eastern Africa, spanning temperate to tropical climates. Methods Four species richness maps were compiled based on range maps, field‐derived bird atlas data, logistic and autologistic distribution models. Ordinary and spatial regression models served to examine how well each of five hypotheses predicted patterns in each map. These hypotheses propose productivity, temperature, the heat–water balance, habitat heterogeneity and climatic stability as the predominant determinants of species richness. Results The four richness maps portrayed broadly similar geographical patterns but, due to the nature of underlying data types, exhibited marked differences in spatial autocorrelation structure. These differences in spatial structure emerged as important in determining which hypothesis appeared most capable of explaining each map's patterns. This was true even when regressions accounted for spurious effects of spatial autocorrelation. Each richness map, therefore, identified a different hypothesis as the most likely cause of broad‐scale gradients in species diversity. Main conclusions Because the ‘true’ spatial structure of species richness patterns remains elusive, firm conclusions regarding their underlying environmental drivers remain difficult. More broadly, our findings suggest that care should be taken to interpret putative determinants of large‐scale ecological gradients in light of the type and spatial characteristics of the underlying data. Indeed, closer scrutiny of these underlying data — here the distributions of individual species — and their environmental associations may offer important insights into the ultimate causes of observed broad‐scale patterns.     

Demographic consequences of climate change and land cover help explain a history of extirpations and range contraction in a declining snake species

Developing conservation strategies for threatened species increasingly requires understanding vulnerabilities to climate change, in terms of both demographic sensitivities to climatic and other environmental factors, and exposure to variability in those factors over time and space. We conducted a range‐wide, spatially explicit climate change vulnerability assessment for Eastern Massasauga (Sistrurus catenatus), a declining endemic species in a region showing strong environmental change. Using active season and winter adult survival estimates derived from 17 data sets throughout the species' range, we identified demographic sensitivities to winter drought, maximum precipitation during the summer, and the proportion of the surrounding landscape dominated by agricultural and urban land cover. Each of these factors was negatively associated with active season adult survival rates in binomial generalized linear models. We then used these relationships to back‐cast adult survival with dynamic climate variables from 1950 to 2008 using spatially explicit demographic models. Demographic models for 189 population locations predicted known extant and extirpated populations well (AUC = 0.75), and models based on climate and land cover variables were superior to models incorporating either of those effects independently. These results suggest that increasing frequencies and severities of extreme events, including drought and flooding, have been important drivers of the long‐term spatiotemporal variation in a demographic rate. We provide evidence that this variation reflects nonadaptive sensitivity to climatic stressors, which are contributing to long‐term demographic decline and range contraction for a species of high‐conservation concern. Range‐wide demographic modeling facilitated an understanding of spatial shifts in climatic suitability and exposure, allowing the identification of important climate refugia for a dispersal‐limited species. Climate change vulnerability assessment provides a framework for linking demographic and distributional dynamics to environmental change, and can thereby provide unique information for conservation planning and management.