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Aim: Ongoing climate change is presently influencing the distribution ranges of numerous species, with both range expansions and latitudinal shifts being observed. In southern Europe, a biogeographical border that separates African and European biota, while at the same time acting as a migration bridge for many species, these changes are of particular relevance. This study aimed to analyse the responses of nine typically African birds to climate change to provide information on the ongoing and future occupation of Europe by these species. Location: Western Palearctic and surrounding areas. Methods: To this end, the distributions of the species in their native ranges were modelled, both in the present and in future climate scenarios, using their current breeding ranges and a set of topographic and climatic variables. The climatic favourability for the nine species was then combined using fuzzy logic. Results: The results showed that southern Europe is highly favourable for our set of African birds, except for Rüppell's Vulture, and future forecasts indicated that this favourability would increase further north, again excluding the African Vulture. Main conclusions: If the climate continues to warm, further arrivals of individuals are to be expected, increasing the possibility that self‐sustaining populations may become established in southern Europe. Furthermore, new African species may start to occupy this area, with the likelihood of an Africanisation of the European fauna. Considering the role played by southern Europe as a potential focal point for the colonisation of this continent by African species, it is important to track their northward expansion and future spread. [ABSTRACT FROM AUTHOR]

Aim: (i) To assess the dependence between the form of the decrease in biological similarity with distance (distance‐decay) and species range size and (ii) to introduce the use of a sigmoidal model, the Gompertz function, as a flexible alternative able to fit distance‐decay models under a wide variety of species range sizes. Location: Applicable worldwide. Methods: We computed distance‐decay curves from simulated communities to assess how the species range sizes shape the functional form of distance‐decay patterns (i.e. negative exponential, power‐law or sigmoidal [Gompertz] relationships). Simulations were performed using different sample sizes and species detection probabilities. We also used distribution data of South American mammals to explore the relationship between species range size and the distance‐decay form in an empirical dataset. Results: Our simulations showed that the power‐law is the best supported model when range sizes tend to be small. An increase in range sizes leads to a negative exponential relationship, taking the shape of a sigmoidal (Gompertz) relationship with the largest range size values. Similar results have been found in the distance‐decay pattern of South American mammals. Remarkably, the Gompertz function fits the data reasonably well in all scenarios. Main conclusions: The functional form of distance‐decay patterns depends on a key biogeographical attribute: species range size. This dependence makes it an interesting tool to detect biodiversity threats associated with species range expansion, such as the biotic homogenization of faunas. The Gompertz function is the mathematical model that best accommodates different frequency distributions of species range size and, thus, allows cross‐taxa comparison of this biogeographical and ecological pattern. [ABSTRACT FROM AUTHOR]

Aim: Species rarity is often used as a measure to assess the risk of extinction of species, and thus, different methods have been developed to describe the composition of rare species in biological communities. These methods usually depend on species attributes that are not always available and very often ignore imperfect species detection. In this work, we developed a new method to characterize species rarity in a community when species are detected imperfectly. Our modelling framework is based on Bayesian occupancy models to estimate species distributions under imperfect detection using presence‐nondetection data. Innovation: We propose a finite mixture occupancy model to identify rare species based on their occupancy and class‐membership probabilities. Here, we explored a two‐class finite mixture model to distinguish between rare and common species classes and presented the general modelling framework for a problem with more than two classes. By using simulations, we were able to compare our model results under different scenarios obtaining a high‐classification performance across all of them. Additionally, we applied our model to a data set of Odonata occurrence records that were partially observed due to imperfect detection and quantified the proportion of rare species on a national scale across waterbodies in the United Kingdom. Main conclusions: Nowadays, biodiversity conservation involves monitoring programmes that target multiple species within a community where individual species responses may vary widely. This high variability makes the task of identifying the ecological processes that drive distributions of rare species difficult. Thus, our method represents a new approach to characterize the composition of a community in terms of species rarity while correcting for detectability bias. Our modelling framework also suggests lines of research and future developments for the understanding of how species rarity can be measured in a wide range of scenarios. [ABSTRACT FROM AUTHOR]

Aim: Identifying the mechanisms influencing species' distributions is critical for accurate climate change forecasts. However, current approaches are limited by correlative models that cannot distinguish between direct and indirect effects. Location: New Hampshire and Vermont, USA. Methods: Using causal and correlational models and new theory on range limits, we compared current (2014–2019) and future (2080s) distributions of ecologically important mammalian carnivores and competitors along range limits in the northeastern US under two global climate models (GCMs) and a high‐emission scenario (RCP8.5) of projected snow and forest biomass change. Results: Our hypothesis that causal models of climate‐mediated competition would result in different distribution predictions than correlational models, both in the current and future periods, was well‐supported by our results; however, these patterns were prominent only for species pairs that exhibited strong interactions. The causal model predicted the current distribution of Canada lynx (Lynx canadensis) more accurately, likely because it incorporated the influence of competitive interactions mediated by snow with the closely related bobcat (Lynx rufus). Both modeling frameworks predicted an overall decline in lynx occurrence in the central high‐elevation regions and increased occurrence in the northeastern region in the 2080s due to changes in land use that provided optimal habitat. However, these losses and gains were less substantial in the causal model due to the inclusion of an indirect buffering effect of snow on lynx. Main conclusions: Our comparative analysis indicates that a causal framework, steeped in ecological theory, can be used to generate spatially explicit predictions of species distributions. This approach can be used to disentangle correlated predictors that have previously hampered understanding of range limits and species' response to climate change. [ABSTRACT FROM AUTHOR]

Aim: Species distribution models (SDMs) have emerged as essential tools in the equipment of many ecologists, useful to explore species distributions in space and time and answering an assortment of questions related to biogeography, climate change biology and conservation biology. Historically, most SDM research concentrated on well‐known organisms, especially vertebrates. In recent years, these tools are becoming increasingly important for predicting the distribution of understudied invertebrate taxa. Here, we reviewed the literature published on main terrestrial arthropod predators (ants, ground beetles and spiders) to explore some of the challenges and opportunities of species distribution modelling in mega‐diverse arthropod groups. Location: Global. Methods: Systematic mapping of the literature and bibliometric analysis. Results: Most SDM studies of animals to date have focused either on broad samples of vertebrates or on arthropod species that are charismatic (e.g. butterflies) or economically important (e.g. vectors of disease, crop pests and pollinators). We show that the use of SDMs to map the geography of terrestrial arthropod predators is a nascent phenomenon, with a near‐exponential growth in the number of studies over the past ten years and still limited collaborative networks among researchers. There is a bias in studies towards charismatic species and geographical areas that hold lower levels of diversity but greater availability of data, such as Europe and North America. Conclusions: Arthropods pose particular modelling challenges that add to the ones already present for vertebrates, but they should also offer opportunities for future SDM research as data and new methods are made available. To overcome data limitations, we illustrate the potential of modern data sources and new modelling approaches. We discuss areas of research where SDMs may be combined with dispersal models and increasingly available phylogenetic and functional data to understand evolutionary changes in ranges and range‐limiting traits over past and contemporary time‐scales. [ABSTRACT FROM AUTHOR]

Aim: Information on the spatio‐temporal distribution of marine species is essential for developing proactive management strategies. However, sufficient information is seldom available at large spatial scales, particularly in polar areas. The Southern Ocean (SO) represents a critical habitat for various species, particularly migratory baleen whales. Still, the SO's remoteness and sea ice coverage disallow obtaining sufficient information on baleen whale distribution and niche preference. Here, we used presence‐only species distribution models to predict the circumantarctic habitat suitability of baleen whales and identify important predictors affecting their distribution. Location: The Southern Ocean (SO). Methods: We used Maxent to model habitat suitability for Antarctic minke, Antarctic blue, fin and humpback whales. Our models employ extensive circumantarctic data and carefully prepared predictors describing the SO's environment and two spatial sampling bias correction options. Species‐specific spatial‐block cross‐validation was used to optimize model complexity and for spatially independent model evaluation. Results: Model performance was high on cross‐validation, with generally little predicted uncertainty. The most important predictors were derived from sea ice, particularly seasonal mean and variability of sea ice concentration and distance to the sea ice edge. Main conclusions: Our models support the usefulness of presence‐only models as a cost‐effective tool in the marine realm, particularly for studying the migratory whales' distribution. However, we found discrepancies between our results and (within) results of similar studies, mainly due to using different species data quality and quantity, different study area extent and methodological reasons. We further highlight the limitations of implementing static distribution models in the highly dynamic marine realm. Dynamic models, which relate species information to environmental conditions contemporaneous to species occurrences, can predict near‐real‐time habitat suitability, necessary for dynamic management. Nevertheless, obtaining sufficient species and environmental predictors at high spatio‐temporal resolution, necessary for dynamic models, can be challenging from polar regions. [ABSTRACT FROM AUTHOR]

Aim: Asian forests are becoming increasingly degraded and fragmented by the extensive intensification of anthropogenic activities; these activities threaten wildlife and ecosystem sustainability. Facing a defaunation crisis, managers need more information on species assemblages to guide conservation efforts. We tested the relative influence of natural and anthropogenic factors on mammalian species richness and occupancy in temperate forests in Northeast Asia. Location: Northeast China. Methods: Camera‐trapping data and multispecies occupancy models were used to estimate the species richness of a terrestrial mammal community in a working landscape and assess community‐, group‐, and species‐specific responses to natural and anthropogenic features while accounting for imperfect detection. Species were grouped based on body size, diet and activity pattern. Results: We deployed 138 cameras and photographed 21 mammalian species over 22,976 trap days across the China–Russia border. Both natural and anthropogenic correlates varied in their importance in predicting the presence of different animals. Vegetation cover and cattle were found to have significantly positive and negative influences on community‐level mammalian occupancy, respectively. The positive relationship with vegetation cover was most evident for large or diurnal species; the negative relationship with cattle was most evident for diurnal and wild ungulate species. Large species occupancy was also negatively associated with human settlements. The predicted richness across each station varied from 5 to 14 unique species, and species had a mean occupancy probability of 0.45 (95% credible interval = 0.09–0.86). Species richness was generally the lowest in livestock grazing areas and close to human settlements. Human influence is more important than the influences of vegetation and environmental variables. Main conclusions: Our results highlight that livestock grazing was the primary human disturbance that had a negative impact on species occupancy and richness. Multispecies occupancy models helped to identify drivers of biodiversity declines and will inform conservation strategies in human‐dominated landscapes in Northeast Asian forests. We suggest that landscape conservation planning seeks to maximize forest protection and ecosystem services such as biodiversity and carbon storage. [ABSTRACT FROM AUTHOR]

Aim: As climate change presents a major threat to biodiversity in the next decades, it is critical to assess its impact on species habitat suitability to inform biodiversity conservation. Species distribution models (SDMs) are a widely used tool to assess climate change impacts on species' geographical distributions. As the name of these models suggests, the species level is the most commonly used taxonomic unit in SDMs. However, recently it has been demonstrated that SDMs considering taxonomic resolution below (or above) the species level can make more reliable predictions of biodiversity change when different populations exhibit local adaptation. Here, we tested this idea using the Japanese crayfish (Cambaroides japonicus), a threatened species encompassing two geographically structured and phylogenetically distinct genetic lineages. Location: Northern Japan. Methods: We first estimated niche differentiation between the two lineages of C. japonicus using n‐dimensional hypervolumes and then made climate change predictions of habitat suitability using SDMs constructed at two phylogenetic levels: species and intraspecific lineage. Results: Our results showed only intermediate niche overlap, demonstrating measurable niche differences between the two lineages. The species‐level SDM made future predictions that predicted much broader and severe impacts of climate change. However, the lineage‐level SDMs led to reduced climate change impacts overall and also suggested that the eastern lineage may be more resilient to climate change than the western one. Main conclusions: The two lineages of C. japonicus occupy different niche spaces. Compared with lineage‐level models, species‐level models can overestimate climate change impacts. These results not only have important implications for designing future conservation strategies for this threatened species, but also highlight the need for incorporating genetic information into SDMs to obtain realistic predictions of biodiversity change. [ABSTRACT FROM AUTHOR]

Aim: To evaluate the potential of models based on opportunistic reporting (OR) compared to models based on data from a systematic protocol (SP) for modelling species distributions. We compared model performance for eight forest bird species with contrasting spatial distributions, habitat requirements and rarity. Differences in the reporting of species were also assessed. Finally, we tested potential improvement of models when inferring high‐quality absences from OR based on questionnaires sent to observers. Location: Both datasets cover the same large area (Sweden) and time period (2000–2013). Methods: Species distributions were modelled using logistic regression. Predictive performance of OR models to predict SP data was assessed based on AUC. We quantified the congruence in spatial predictions using Spearman's rank correlation coefficient. We related these results to species characteristics and reporting behaviour of observers. We also assessed the gain in predictive performance of OR models by adding inferred absences. Finally, we investigated the potential impact of sampling bias in OR. Results: For all species, and despite the sampling biases, results from OR overall agreed well with those of SP, for the nationwide spatial congruence of habitat suitability maps and the selection and directions of species–environment relationships. The OR models also performed well in predicting the SP data. The predictive performance of the OR models increased with species rarity and even outperformed the SP model for the rarest species. No significant impact of observer behaviour was found. Main conclusions: Relatively simple analyses with inferred absences could produce reliable spatial predictions of habitat suitability. This was especially true for rare species. OR data should be seen as a complement to SP, as the weakness of one is the strength of the other, and OR may be especially useful at large spatial scales or where no systematic data collection protocols exist. [ABSTRACT FROM AUTHOR]

Aim: Estimating species richness from a series of samples is an important and widely debated issue in ecology and biodiversity conservation. Numerous tests of respective richness estimators gave insights into the precision, the limitations and the pitfalls of richness forecasting. However, few benchmark tests used almost complete empiric census data obtained at those spatial scales where richness estimation is most useful for conservation management. Location: Japan. Methods: We use an extraordinary dataset on the spatial distribution of Japanese plants containing complete information on the occurrence of each Japanese plant species at the 10 × 10 km2 grid cell level. We link the estimates of four estimators representing different theoretical approaches, Chao2, rarefaction, species–area relationships (SAR) and species abundance distributions (SAD), to environmental data using a fully nested sampling design. Results: Chao2 and rarefaction behaved very similar in all tests and significantly underestimated true richness below 40% sampling fraction. SAR and SAD were less precise than Chao2 and rarefaction at higher sampling fraction but also less affected by low sample size. In general, SAD provided robust estimates over the whole range of sampling fraction and 67.4% of estimates ranged within the 10% error level. Higher species spatial turnover increased and high evenness in occurrence decreased the precision of the SAD estimator. Precision of the four estimators was largely unaffected by environmental variability but increased with increasing latitude. Main conclusions: Our results strongly indicate that the pattern of Japanese plant species spatial distribution is sufficiently scale invariant for richness estimators to provide precise forecasting results at the country level. The simplest process to generate such a spatial distribution is ecological drift. [ABSTRACT FROM AUTHOR]

Aim: Sample size and species characteristics, including prevalence and habitat specialization, can influence the predictive performance of species distribution models (SDMs). There is little agreement, however, on which metric of model performance to use. Here, we directly compare AUC and partial ROC as metrics of SDM performance through analyses on the effects of species traits and sample size on SDM performance. Location: Three counties dominated by agricultural lands and coniferous forest in Oregon's Willamette Valley and Coast Range ecoregions. Methods: We systematically reduced a large avian point count dataset to alter sample sizes of 22 species of songbird. We used boosted regression trees to run SDMs for each species, quantified habitat specialization, and used mixed effects models to compare the influence of sample size, prevalence, and habitat specialization on SDM performance, calculated as AUC and partial ROC, across species. We calculated AUC and partial ROC with subset and independent evaluation data separately to more comprehensively investigate differences in metrics. Results: We found a positive quadratic effect of sample size and a strongly positive effect of habitat specialization on both metrics of model performance. We found a weak effect of prevalence on partial ROC and no effect in AUC. Contrary to expectations, when evaluated with a subset evaluation data, partial ROC was consistently highest in models with the smallest sample sizes. These small sample size models had correspondingly small sample sizes in subset evaluation datasets. Partial ROC evaluated with independent data and AUC evaluated with subset or independent data showed the expected positive correlation between sample size and model performance. Main Conclusions: We found that small evaluation datasets can artificially inflate partial ROC. With literature recommended minimum SDM sample sizes as low as three, attention must be given to the effects of correspondingly low sample sizes in evaluation datasets. [ABSTRACT FROM AUTHOR]

Aim The way in which environmental conditions determine the distribution and abundance of species is a crucial topic in ecology, biogeography and conservation. It is especially important to understand the nature of this relationship regarding threatened species. The ability to forecast local densities over the geographic range of species provides a way to link population ecology and biogeography. Particularly, our aim was to test whether predictions derived from species distribution modelling data provide useful information on spatial patterns of abundance and, consequently, may act as surrogates for local density estimates. Location Andalusia (southern Spain). Methods Logistic regression and the favourability function were applied as modelling tools to presence-absence data to compare the predicted results with current abundance. This approach is useful in the identification of local priorities for the target species whenever broad-scale surveys need to be performed. Results The model included variables related to topography, vegetation and spatial location to explain the presence of Bonelli's eagle. A positive relationship was found between both probability and favourability and the density of this species, but a triangular fit only with favourability, suggesting that the physiological and ecological requirements of this species in the study area are better reflected in the favourability model. Main conclusions We suggest that favourability models derived from presence-absence data provide insights into abundance data and valuable information on carrying capacity over large scales. To minimize costs, maximize output and optimize results, priority could be given to detecting the presence of the species, instead of investing resources aimed at estimating abundance, which is more expensive. [ABSTRACT FROM AUTHOR]

Models based on species distributions are widely used and serve important purposes in ecology, biogeography and conservation. Their continuous predictions of environmental suitability are commonly converted into a binary classification of predicted (or potential) presences and absences, whose accuracy is then evaluated through a number of measures that have been the subject of recent reviews. We propose four additional measures that analyse observation-prediction mismatch from a different angle - namely, from the perspective of the predicted rather than the observed area - and add to the existing toolset of model evaluation methods. We explain how these measures can complete the view provided by the existing measures, allowing further insights into distribution model predictions. We also describe how they can be particularly useful when using models to forecast the spread of diseases or of invasive species and to predict modifications in species' distributions under climate and land-use change. [ABSTRACT FROM AUTHOR]

Aim The spatial resolution of species atlases and therefore resulting model predictions are often too coarse for local applications. Collecting distribution data at a finer resolution for large numbers of species requires a comprehensive sampling effort, making it impractical and expensive. This study outlines the incorporation of existing knowledge into a conventional approach to predict the distribution of Bonelli's eagle ( Aquila fasciata) at a resolution 100 times finer than available atlas data. Location Malaga province, Andalusia, southern Spain. Methods A Bayesian expert system was proposed to utilize the knowledge from distribution models to yield the probability of a species being recorded at a finer resolution (1 × 1 km) than the original atlas data (10 × 10 km). The recorded probability was then used as a weight vector to generate a sampling scheme from the species atlas to enhance the accuracy of the modelling procedure. The maximum entropy for species distribution modelling (MaxEnt) was used as the species distribution model. A comparison was made between the results of the MaxEnt using the enhanced and, the random sampling scheme, based on four groups of environmental variables: topographic, climatic, biological and anthropogenic. Results The models with the sampling scheme enhanced by an expert system had a higher discriminative capacity than the baseline models. The downscaled (i.e. finer scale) species distribution maps using a hybrid MaxEnt/expert system approach were more specific to the nest locations and were more contrasted than those of the baseline model. Main conclusions The proposed method is a feasible substitute for comprehensive field work. The approach developed in this study is applicable for predicting the distribution of Bonelli's eagle at a local scale from a national-level occurrence data set; however, the usefulness of this approach may be limited to well-known species. [ABSTRACT FROM AUTHOR]

Aim Using six free-living deer species in Great Britain as a case study, we studied biogeographical relationships of ecologically related species composed of both native and introduced species. Location Great Britain. Methods  We modelled the environmental favourability for the deer species using variables related with spatial location, climate, topography, human disturbances and habitat structure. Favourability values of each pair of native (naturalized)-introduced species were used to estimate the fuzzy overlap index (FOvI) as a measure of overall similarity between the environmental requirements for the species in Great Britain. The absolute local overlap values (FOvI-L) were also used to measure the degree to which a given location was favourable simultaneously for each pair of species. We assessed the trends of species favourability across a range defined by the absolute local overlap values and studied the shape of the obtained curves since they informs us about the favourability balance between the studied species. Results Muntjac and Chinese water deer attained higher favourability values than native species in localities with intermediate values of FOvI-L (a reduced number in the study area), suggesting that if competitive relationships were established in these localities the introduced deer species may have some advantages over natives. Sika deer only achieved higher values than fallow deer in those localities clearly unfavourable for the naturalized species. Our analyses predicted that fallow deer will be less affected by the introduced deer species than native species. Main conclusions We developed an approach based on the favourability function to describe biogeographical relationships between species, natives and introduced and to assess from a biogeographical perspective if introduced species could pose a competitive risk to natives. Although the results of present analyses do not conclusively demonstrate competitive exclusion, they provide directional hypotheses that can be tested in experimental field and laboratory studies. [ABSTRACT FROM AUTHOR]

Aim To relate the recent Iberian lynx decline to changes in the distribution of the European rabbit after the haemorrhagic disease outbreak of 1989. As Iberian rabbits evolved in two geographically separated lineages, being the recent lynx range practically restricted to the southwestern lineage, we also test if differential range dynamics exists for these lineages, with the consequent implications for lynx conservation and reintroduction planning. Location The Iberian Peninsula. Methods We modelled environmental favourability for the lynx based on its distribution before 1989, and for the rabbit using distribution data collected primarily after 1989, and validated them using independent abundance data. We compared both models and combined them in a lynx occurrence forecast. We correlated the prevalence of southwestern rabbit lineage with the environmental favourability for the rabbit. Results The environmental lynx model correlated with past lynx abundance data, but did not reflect its recent strong range contraction. The rabbit model correlated with recent rabbit abundance, but was negatively correlated with the environmental model for the lynx. The combination of both models forecasted lynx occurrence in a few separated nuclei, which encompass all recent lynx records. The prevalence of rabbit's southwestern lineage correlated negatively with favourability for the rabbit. Main conclusions The region to which the lynx became confined before 1989 is currently less favourable for rabbits, whereas more favourable areas remain outside lynx reach. This differential favourability correlates with rabbit phylogeographical structure, suggesting that the southwestern lineage is facing more unfavourable conditions or is less resilient to recent diseases. The loss of concordance between lynx distribution and the whole rabbit phylogeographical structure has prevented lynx persistence in northeastern rabbit lineage areas, which should be considered in lynx reintroduction planning. Similar conservation problems could affect other ecologically interacting species whose distributions’ overlapping has sharply diminished. [ABSTRACT FROM AUTHOR]

We investigated the existence of chorotypes – assemblages of species with similar geographical ranges – of invasive species in a host territory, and their potential use to advocate similar control or management strategies for species in the same chorotype. We analysed the distribution of 13 exotic terrestrial vertebrate species (six birds, six mammals, and one reptile) with well-known distributions in mainland Spain. We used the presence/absence data on a grid of 10 km × 10 km UTM cells from the Atlases of terrestrial vertebrates of Spain. These data were aggregated to a grid of 50 km × 50 km UTM cells, because it entailed no loss of meaningful information and allowed dealing with a much lower number of cells. Using cluster analysis and a probabilistic assessment of the classification, we identified seven significant chorotypes: four multispecific and three monospecific. The compound chorotypes grouped together species that tended to share certain characteristics about their introduction, release cause, establishment, and spread. We modelled the chorotypes using a favourability function based on a generalized linear model and 31 variables related to spatial situation, topography, lithology, climatic stability, energy availability, water availability, disturbances, productivity, and human activity. Climatic factors affected the favourability for every chorotype, whereas human variables had a high influence in the distribution of three chorotypes involving eight species. On the basis of these variables, we identified favourable areas for all the chorotypes in mainland Spain. The favourability for a chorotype in an area may be a useful criterion for evaluating the local conservation concern due to the whole set of species. Favourable but unoccupied areas can be used to infer possible colonization areas for each chorotype. We recommend using chorotypes to optimize broad-scale surveillance of invasive species. [ABSTRACT FROM AUTHOR]

In this study we determine favourable areas for the monk parakeet, Myiopsitta monachus, in peninsular Spain to account for its current distribution and predict its future course according to its potential range. We applied a favourability function based on generalized linear models using the presence/absence of breeding colonies of the species and the values of a set of variables on the 5167 UTM 10 × 10 km squares comprising the study area. We calculated the factor of distribution change in presences predicted by the model, and grouped the variables into explanatory factors performing a variation partitioning to assess the explanatory power of each factor. Our model included six predictors to explain the presence and absence of the species. These predictors were grouped into three factors: human activity, climate, and topography. Purely human influences accounted for 63.8% of the variation of the final model, while topographical variables explained 15.2% and climate only 5.7%. We obtained a high distribution change factor in which the presences of the species were predicted to increase between two- and sevenfold. Taking into account highly favourable squares, we conclude that the species is still absent in more than 72% of potential settlement areas, and thus we expect a continuous increase in the distribution of the species. Human activity is the main force moulding the distribution of the species, and lies behind its fast expansion, which is not only active, but is also passive via releases and escapes. We identified the areas of likely future expansion of the exotic monk parakeet in Spain. The pest status of the species in its native range, together to its distribution trend, should be taken into account by wildlife agencies to consider options for management. [ABSTRACT FROM AUTHOR]

Bonelli's eagle, Hieraaetus fasciatus, has recently suffered a severe population decline and is currently endangered. Spain supports about 70% of the European population. We used stepwise logistic regression on a set of environmental, spatial and human variables to model Bonelli's eagle distribution in the 5167 UTM 10 × 10 km quadrats of peninsular Spain. We obtained a model based on 16 variables, which allowed us to identify favourable and unfavourable areas for this species in Spain, as well as intermediate favourability areas. We assessed the stepwise progression of the model by comparing the model's predictions in each step with those of the final model, and selected a parsimonious explanatory model based on three variables — slope, July temperature and precipitation — comprising 76% of the predictive capacity of the final model. The reported presences in favourable and unfavourable areas suggest a source–sink dynamics in Bonelli's eagle populations. The fragmented spatial structure of the favourable areas suggests the existence of a superimposed metapopulation dynamics. Previous LIFE (The Financial Instrument of the European Union for the Environment and Nature) projects for the conservation of this species have focused mainly on the northern limit of its range, where the sharpest population decline has been recorded. In these areas, favourability is low and Bonelli's eagle populations are probably maintained by the immigration of juveniles produced in more favourable zones. However, southern populations, although stable, show signs of reduction in productivity, which could menace the population sizes in the whole study area. We suggest that conservation efforts should focus also on known favourable areas, which might favour population persistence in unfavourable areas through dispersal. [ABSTRACT FROM AUTHOR]

GLO:EU3/01apr21:ddi13263-toc-0001.jpg PHOTO (COLOR): . gl The photo (taken in 2009) shows an eastern lineage Japanese crayfi sh (Cambaroides japonicus) in a small woodland stream in Hokkaido, Japan. The cover image relates to the Research Article https://doi.org/10.1111/ddi.13225 "Lineage-level distribution models lead to more realistic climate change predictions for a threatened crayfi sh" by Zhixin Zhang et al. [Extracted from the article]