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The evaluation of protected area networks on their capacity to preserve species distributions is a key topic in conservation biology. There are different types of protected areas, with National Parks those with highest level of protection. National Parks can be declared attending to many ecological features that include the presence of certain animal species. Here, we selected 37 vertebrate species that were highlighted as having relevant natural value for at least one of the 10 National Parks of mainland Spain. We modelled species distributions with the favourability function, and applied the Insecurity Index to detect the degree of protection of favourable areas for each species. Two metrics of Insecurity Index were defined for each species: the Insecurity Index in each of the cells, and the Overall Insecurity Index of a species. The former allows the identification of insecure areas for each species that can be used to establish spatial conservation priorities. The latter gives a value of Insecurity for each species, which we used to calculate the Representativeness of favourable areas for the species in the network. As expected, due to the limited extension of the National Park network, all species have high values of Insecurity; i.e., just a narrow proportion of their favourable areas are covered by a National Park. However, the majority of species favourable areas are well represented in the network, i.e., the percentage of favourable areas covered by the National Park network is higher than the percentage of mainland Spain covered by the network (result also supported by a randomization approach). Even if a reserve network only covers a low percentage of a country, the Overall Insecurity Index allows an objective assessment of its capacity to represent species. Beyond the results presented here, the Insecurity Index has the potential to be extrapolated to other areas and to cover a wide range of species.

Entropy is intrinsic to the geographical distribution of a biological species. A species distribution with higher entropy involves more uncertainty, i.e., is more gradually constrained by the environment. Species distribution modelling tries to yield models with low uncertainty but normally has to reduce uncertainty by increasing their complexity, which is detrimental for another desirable property of the models, parsimony. By modelling the distribution of 18 vertebrate species in mainland Spain, we show that entropy may be computed along the forward-backwards stepwise selection of variables in Logistic Regression Models to check whether uncertainty is reduced at each step. In general, a reduction of entropy was produced asymptotically at each step of the model. This asymptote could be used to distinguish the entropy attributable to the species distribution from that attributable to model misspecification. We discussed the use of fuzzy entropy for this end because it produces results that are commensurable between species and study areas. Using a stepwise approach and fuzzy entropy may be helpful to counterbalance the uncertainty and the complexity of the models. The model yielded at the step with the lowest fuzzy entropy combines the reduction of uncertainty with parsimony, which results in high efficiency.

Aim To describe the population trend for European turtle doves in Spain. To identify favourable and unfavourable areas for the species and to test whether favourability or land use explain spatial variation in abundance change. Location Mainland Spain. Methods We used generalized linear models with extensive abundance data to describe population change for the European turtle dove across Spain. We used breeding distribution (presence/absence) data at 100 km2 resolution to model environmental favourability in relation to topo‐climatic and land use variables. Finally, we tested whether land use and favourability explained spatial variation in abundance trends. Results The large Spanish turtle dove population declined by 37% between 1996 and 2018. Favourability was highest in the south, east and north–west of Spain and lowest in the north and at higher altitudes. Abundance trends were more negative in areas of lower environmental favourability and in localities dominated by arboreal habitats such as forests, “dehesas” (open agro‐forestry landscapes with scattered Quercus trees), transitional woodland shrubs or sclerophyllous vegetation (a mixture of sclerophyllous shrubs with some scattered trees). Trends were more positive in localities dominated by complex cultivation (small parcels of mixed crop types, including woody permanent crops like olive, or almond trees or vineyards). Main conclusions Our study highlights a substantial recent decline in the numerically important turtle dove breeding population in Spain. Declines in abundance were more strongly associated with arboreal (forest and shrub areas) rather than agricultural habitats, highlighting an urgent need for further research into the ecology of this important quarry species in arboreal breeding habitats in southern Europe.

In order to understand the ecological effects of climate change it is essential to forecast suitable areas for species in the future. However, species’ ability to reach potentially suitable areas is also critical for species survival. These ‘range-shift’ abilities can be studied using life-history traits related to four range-shift stages: emigration, movement, establishment, and proliferation. Here, we use the extent to which species’ ranges fill the climatically suitable area available (‘range filling’) as a proxy for the ability of European mammals and birds to shift their ranges under climate change. We detect which traits associate most closely with range filling. Drawing comparisons with a recent analysis for plants, we ask whether the latitudinal position of species’ ranges supports the assertion that post-glacial range-shift limitations cause disequilibrium between ranges and climate. We also disentangle which of the three taxonomic groups has greatest range filling. For mammals, generalists and early-reproducing species have the greatest range filling. For birds, generalist species with high annual fecundity, which live longer than expected based on body size, have the greatest range filling. Although we consider traits related to the four range-shift stages, only traits related to establishment and proliferation ability significantly influence range filling of mammals and birds. Species with the greatest range filling are those whose range centroid falls in the latitudinal centre of Europe, suggesting that post-glacial range expansion is a leading cause of disequilibrium with climate, although other explanations are also possible. Range filling of plants is lower than that of mammals or birds, suggesting that plants are more range-limited by non-climatic factors. Therefore, plants might be face greater non-climatic restraints on range shifts than mammals or birds.

We modelled the distribution of two vulnerable steppe birds, Otis tarda and Tetrax tetrax, in the Western Palearctic and projected their suitability up to the year 2080. We performed two types of models for each species: one that included environmental and geographic variables (space-included model) and a second one that only included environmental variables (space-excluded model). Our assumption was that ignoring geographic variables in the modelling procedure may result in inaccurate forecasting of species distributions. On the other hand, the inclusion of geographic variables may generate an artificial constraint on future projections. Our results show that space-included models performed better than space-excluded models. While distribution of suitable areas for T. tetrax in the future was approximately the same as at present in the space-included model, the space-excluded model predicted a pronounced geographic change of suitable areas for this species. In the case of O. tarda, the space-included model showed that many areas of current presence shifted to low or medium suitability in the future, whereas a northward expansion of intermediate suitable areas was predicted by the space-excluded one. According to the best models, current distribution of these species can restrict future distribution, probably due to dispersal constraints and site fidelity. Species ranges would be expected to shift gradually over the studied time period and, therefore, we consider it unlikely that most of the current distribution of these species in southern Europe will disappear in less than one hundred years. Therefore, populations currently occupying suitable areas should be a priority for conservation policies. Our results also show that climate-only models may have low explanatory power, and could benefit from adjustments using information on other environmental variables and biological traits; if the latter are not available, including the geographic predictor may improve the reliability of predicted results.

Understanding what determines species' geographic distributions is crucial for assessing global change threats to biodiversity. Measuring limits on distributions is usually, and necessarily, done with data at large geographic extents and coarse spatial resolution. However, survival of individuals is determined by processes that happen at small spatial scales. The relative abundance of coexisting species (i.e. `community structure') reflects assembly processes occurring at small scales, and are often available for relatively extensive areas, so could be useful for explaining species distributions. We demonstrate that Bayesian Network Inference (BNI) can overcome several challenges to including community structure into studies of species distributions, despite having been little used to date. We hypothesized that the relative abundance of coexisting species can improve predictions of species distributions. In 1570 assemblages of 68 Mediterranean woody plant species we used BNI to incorporate community structure into Species Distribution Models (SDMs), alongside environmental information. Information on species associations improved SDM predictions of community structure and species distributions moderately, though for some habitat specialists the deviance explained increased by up to 15%. We demonstrate that most species associations (95%) were positive and occurred between species with ecologically similar traits. This suggests that SDM improvement could bebecause species co-occurrences are a proxy for local ecological processes. Our study shows that Bayesian Networks, when interpreted carefully, can be used to include local conditions into measurements of species' large-scale distributions, and this information can improve the predictions of species distributions.

[This corrects the article DOI: 10.1371/journal.pone.0197877.].

Climate is one of the main drivers of species distribution. However, as different environmental factors tend to co-vary, the effect of climate cannot be taken at face value, as it may be either inflated or obscured by other correlated factors. We used the favourability models of four species (Alytes dickhilleni, Vipera latasti, Aquila fasciata and Capra pyrenaica) inhabiting Spanish mountains as case studies to evaluate the relative contribution of climate in their forecasted favourability by using variation partitioning and weighting the effect of climate in relation to non-climatic factors. By calculating the pure effect of the climatic factor, the pure effects of non-climatic factors, the shared climatic effect and the proportion of the pure effect of the climatic factor in relation to its apparent effect (r), we assessed the apparent effect and the pure independent effect of climate. We then projected both types of effects when modelling the future favourability for each species and combination of AOGCM-SRES (two Atmosphere-Ocean General Circulation Models: CGCM2 and ECHAM4, and two Special Reports on Emission Scenarios (SRES): A2 and B2). The results show that the apparent effect of climate can be either inflated (overrated) or obscured (underrated) by other correlated factors. These differences were species-specific; the sum of favourable areas forecasted according to the pure climatic effect differed from that forecasted according to the apparent climatic effect by about 61% on average for one of the species analyzed, and by about 20% on average for each of the other species. The pure effect of future climate on species distributions can only be estimated by combining climate with other factors. Transferring the pure climatic effect and the apparent climatic effect to the future delimits the maximum and minimum favourable areas forecasted for each species in each climate change scenario.

Aim: The risk climate change poses to biodiversity is often estimated by forecasting the areas that will be climatically suitable for species in the future and measuring the distance of the \"range shifts\" species would have to make to reach these areas. Species' traits could indicate their capacity to undergo range shifts. However, it is not clear how range-shift capacity influences risk. We used traits from a recent evidence review to measure the relative potential of species to track changing climatic conditions. Location: Europe. Time period: Baseline period (1961-1990) and forecast period (2035-2064). Major taxa studied: 62 mammal species. Methods: We modelled species distributions using two general circulation models and two representative concentration pathways (RCPs) to calculate three metrics of \"exposure\" to climate change: range area gained, range area lost and distance moved by the range margin. We identified traits that could inform species' range-shift capacity (i.e., potential to establish new populations and proliferate, and thus undertake range shifts), from a recent evidence-based framework. The traits represent ecological generalization and reproductive strategy. We ranked species according to each metric of exposure and range-shift capacity, calculating sensitivity to ranking methods, and synthesized both exposure and range-shift capacity into \"risk syndromes.\" Results: Many species studied whose survival depends on colonizing new areas were relatively unlikely to undergo range shifts. Under the worst-case scenario, 62% of species studied were relatively highly exposed. 47% were highly exposed and had relatively low range-shift capacity. Only 14% of species faced both low exposure and high range-shift capacity. Both range-shift and exposure metrics had a greater effect on risk assessments than climate models. Main conclusions: The degree to which species' potential ranges will be altered by climate change often does not correspond to species' range-shift capacities. Both exposure and range-shift capacity should be considered when evaluating biodiversity risk from climate change.

Aim Ongoing climate change is currently modifying the geographical location of areas that are climatically suitable for species. Understanding a species’ ability to successfully shift its geographical range would allow us to assess extinction risks and predict future community compositions. We investigate how habitat configuration impedes or promotes climate‐driven range shifts, given different speeds of climate change and dispersal abilities. Location Theoretical, but illustrated with European examples. Methods We model how a species’ ability to track a directional shift in climatic conditions is affected by (a) species’ dispersal abilities; (b) speed of climatic shift; and (c) spatial arrangement of the habitat. Our modelling framework includes within‐and between‐patch population dynamics and uses ecologically realistic habitat distributions and dispersal scenarios (verified with data from a set of European mammal species) and, as such, is an improvement of classical range shift models. Results In landscapes with a homogeneous distribution of suitable habitats, all but the least dispersive species will be able to range shift. However, species with high dispersal ability will have lower population densities after range shift. In heterogeneous landscapes species’ ability to range shift is far more variable and heavily dependent on the habitat configuration. This means that landscape configuration in combination with the speed of climate change and species dispersal abilities give rise to nonlinear effects on population sizes and survival after a climatic shift. Main conclusions Our analyses point out the importance of accounting for the interplay of species dispersal and the landscape configuration when estimating future climate impact on species. These results link ecologically important attributes of both species and their landscapes to outcomes of species range shift, and thereby long‐term persistence of ecological communities.