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Dengue and yellow fever have complex cycles, involving urban and sylvatic mosquitoes, and non‐human primate hosts. To date, efforts to assess the effect of climate change on these diseases have neglected the combination of such crucial factors. Recent studies only considered urban vectors. This is the first study to include them together with sylvatic vectors and the distribution of primates to analyse the effect of climate change on these diseases. We used previously published models, based on machine learning algorithms and fuzzy logic, to identify areas where climatic favourability for the relevant transmission agents could change: 1) favourable areas for the circulation of the viruses due to the environment and to non‐human primate distributions; 2) the favourability for urban and sylvatic vectors. We obtained projections of future transmission risk for two future periods and for each disease, and implemented uncertainty analyses to test for predictions reliability. Areas currently favourable for both diseases could keep being climatically favourable, while global favourability could increase a 7% for yellow fever and a 10% increase for dengue. Areas likely to be more affected in the future for dengue include West Africa, South Asia, the Gulf of Mexico, Central America and the Amazon basin. A possible spread of dengue could take place into Europe, the Mediterranean basin, the UK and Portugal; and, in Asia, into northern China. For yellow fever, climate could become more favourable in Central and Southeast Africa; India; and in north and southeast South America, including Brazil, Paraguay, Bolivia, Peru, Colombia and Venezuela. In Brazil, favourability for yellow fever will probably increase in the south, the west and the east. Areas where the transmission risk spread is consistent to the dispersal of vectors are highlighted in respect of areas where the expected spread is directly attributable to environmental changes. Both scenarios could involve different prevention strategies. [ABSTRACT FROM AUTHOR]

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Aim: As parapatric distributions are traditionally studied by pairs of species, this study aims to evaluate the causes of the maintenance of parapatry, specifically to assess whether the case of the three viper species present in the Iberian Peninsula is mainly caused by environmental conditions, historical events, interspecific competition among them, or a combination of these factors. Location: The Iberian Peninsula. Taxon: Vipera aspis, V. latastei and V. seoanei.. Methods: We applied the concept of favourability of occurrence to produce commensurate distribution units unaffected by the prevalence of different species in the Iberian Peninsula. We compared the favourability of each species individually with the favourability of occurrence of more than one species co‐occurring in their overlapping ranges, and identified the areas in which sympatric coexistence, environmental segregation and competitive exclusion are predicted to occur. Results: The main driver of the parapatric pattern was competitive exclusion, which was mediated by gradual changes in the environmental conditions favouring each species. The para‐Mediterranean V. aspis presented fragmented favourable areas outside its range that seemed to be unoccupied due to competitive exclusion by the other vipers. The Mediterranean V. latastei appeared to be limited by competition with the other viper species and by the environment in north‐western Iberia. V. seoanei prevented the other two species becoming established in the north‐western quarter of the Iberian Peninsula due to its better adaption to the humid conditions in this region. Some areas of sustainable coexistence were detected, mainly in the upper reaches of the River Ebro. Main conclusions: Each species is better adapted to particular conditions. However, the existence of ecotones forces them to occur sympatrically and compete for resources. The parapatric pattern is a result of the evolutionary history of the species and of strong competitive interactions between them, which form 'competitive‐exclusion barriers'. However, these barriers are environmentally dependent, so changes in the environment could rapidly affect the limits of the species distribution. [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: The boundaries of species distributions are often shaped by natural barriers, such as mountains and rivers, but species distribution models usually fail to include these constraints. We tested several approaches that include barriers as explanatory variables in species distribution models. Location: Africa and South America. Time period: Current. Major taxa studied: Primates. Methods: We modelled the ranges of pairs of species separated by a river, taking into account three explanatory components: the environment (ecosystems, topohydrography, climate and human pressure), the spatial structure shaped by history and population dynamics (using a trend‐surface approach) and rivers as naturals barriers to dispersal (using a binary cis–trans variable that describes both sides of the river). To assess how the addition of a spatial structure and the barrier could improve distribution models, we used a nested approach by comparing models based on: (a) the environment; (b) the environment and the spatial structure; and (c) the environment, the spatial structure and the river. These models were constructed using favourability functions. Results: There was a decreased occurrence of high‐favourability values on the opposite side of the rivers in models that included the spatial structure of distributions compared with models based on the environment alone. This decrease was more marked when the description of the spatial structure was made more flexible. However, model performance was significantly improved by the inclusion of cis–trans variables that identified areas on the opposite side as totally unfavourable. Main conclusions: The performance of distribution models can be improved by the use of approaches that describe barriers. Although adding the location of geographical units in relationship to a river appears to be the most accurate way to define the presence of a barrier, defining this variable may be challenging. A suitable alternative is to analyse the spatial structure of distributions using a flexible approach. [ABSTRACT FROM AUTHOR]

A significant link between forest loss and fragmentation and outbreaks of Ebola virus disease (EVD) in humans has been documented. Deforestation may alter the natural circulation of viruses and change the composition, abundance, behaviour and possibly viral exposure of reservoir species. This in turn might increase contact between infected animals and humans.Fruit bats of the family Pteropodidae have been suspected as reservoirs of the Ebola virus. At present, the only evidence associating fruit bats with EVD is the presence of seropositive individuals in eight species and polymerase chain reaction‐positive individuals in three of these.Our study investigates whether human activities can increase African fruit bat geographical ranges and whether this influence overlaps geographically with EVD outbreaks that, in turn, are favoured by deforestation.We use species observation records for the 20 fruit bat species found in favourable areas for the Ebola virus to determine factors affecting the bats' range inside the predicted Ebola virus area. We do this by employing a hypothetico‐deductive approach based on favourability modelling.We show that the range of some fruit bat species is linked to human activities within the favourable areas for the Ebola virus. More specifically, the areas where human activities favour the presence of five fruit bat species overlap with the areas where EVD outbreaks in humans were themselves favoured by deforestation. These five species are as follows: Eidolon helvum, Epomops franqueti, Megaloglossus woermanni, Micropteropus pusillus and Rousettus aegyptiacus. Of these five, all but Megaloglossus woermanni have recorded seropositive individuals. For the remaining 15 bat species, we found no biogeographical support for the hypothesis that positive human influence on fruit bats could be associated with EVD outbreaks in deforested areas within the tropical forest biome in West and Central Africa.Our work is a useful first step allowing further investigation of the networks and pathways that may lead to an EVD outbreak. The modelling framework we employ here can be used for other emerging infectious diseases. [ABSTRACT FROM AUTHOR]

Abstract: The dynamic analysis of geographical distribution is relevant to identify the processes that underlie any changes of geographical ranges. This is an essential element of both biogeography and conservation biology. Fuzzy logic, in particular the fuzzy concept of favourability for species occurrence, helps to perform a dynamic interpretation of the internal complexity of species ranges. We modelled the distributions of the 222 Iberian butterflies using favourability functions and 92 environmental variables (spatial, climatic, topographic, geological and indicators of human activity). We obtained a significant environmental favourability model for each butterfly. We identified the potential sources and sinks in the distribution area of each butterfly species using their respective favourability and presence–absence maps, considering as sources only those areas with high favourability where the butterfly is present, and sinks only those areas with low favourability where the butterfly is present too. The source areas for the Iberian butterflies are concentrated in the north of the peninsula, mainly in the mountain ranges (Cantabrian Range, Pyrenees and Central Range). Sink areas are more dispersed all around the peninsula. We found a concentration of sink locations in eastern Iberia (Alicante and Murcia provinces) and in the southwestern area (Doñana National Park). This may be helpful when implementing conservation measures, by providing a biogeographical dynamic interpretation of the roles of different parts of the distribution range of the species. Preserving the processes that link sources with sinks is critical for maintaining or improving the sustainability of populations. [ABSTRACT FROM AUTHOR]

An accurate estimation of the expected consequences of climate change requires the proper quantification of the effect of climate on current species distributions. Several interrelated sources of uncertainty may affect the likelihood of species distribution models (SDMs) to determine the relative importance of climate. Our aim was to assess the relationship between the influence of geographical background (GB) delimitation and that of subtracting the non-climate effects from the weight of climatic predictors to estimate the combined influence of these two factors on predictions in climate change scenarios. The distribution of 40 endemic mammals in Western Europe have been modeled by (i) using the whole territory of Western Europe as the GB and also specifically delimiting the GB with a geographical criterion and (ii) considering climatic predictors in addition to other non-climatic variables in order to extract the pure effect of climate. The models were used to quantify species' sensitivity to new climate scenarios. Results showed discrepancies among the analytical approaches. Changes in distribution obtained by considering the pure effect of climate were lower than those obtained by considering the apparent effect, and GB-delimited models yielded higher changes than those trained in Western Europe. We evidence that climate weighting and GB delimitation have dramatic influences on the projections of models when transferred to new scenarios. We emphasize that scientific studies and derived adaptation policies based on SDMs without an explicit consideration of the GB and the weighting of the climate-related variables may be misleading and in need of revision. [ABSTRACT FROM AUTHOR]

Species distributions are typically represented by records of their observed occurrence at a given spatial and temporal scale. Such records are inevitably incomplete and contingent on the spatial-temporal circumstances under which the observations were made. Moreover, organismsmay respond differently to similar environmental conditions at different places or moments, so their distribution is, in principle, not completely predictable. We argue that this uncertainty exists, and warrants considering species distributions as analogous to coherent quantum objects, whose distributions are better described by a wavefunction rather than by a set of locations. We use this to extend the existing concept of "dark diversity", which incorporates into biodiversity metrics those species that could, but which have not yet been observed to, inhabit a region--thereby developing the idea of "potential biodiversity". We show how conceptualizing species' distributions in this way could help overcome important weaknesses in current biodiversity metrics, both in theory and by using a worked case study of mammal distributions in Spain over the last decade. We propose that considerable theoretical advances could eventually be gained through interdisciplinary collaboration between biogeographers and quantum physicists. [ABSTRACT FROM AUTHOR]

Chondrichthyes, which include Elasmobranchii (sharks and batoids) and Holocephali (chimaeras), are a relatively small group in the Mediterranean Sea (89 species) playing a key role in the ecosystems where they are found. At present, many species of this group are threatened as a result of anthropogenic effects, including fishing activity. Knowledge of the spatial distribution of these species is of great importance to understand their ecological role and for the efficient management of their populations, particularly if affected by fisheries. This study aims to analyze the spatial patterns of the distribution of Chondrichthyes species richness in the Mediterranean Sea. Information provided by the studied countries was used to model geographical and ecological variables affecting the Chondrichthyes species richness. The species were distributed in 16 Operational Geographical Units (OGUs), derived from the Geographical Sub-Areas (GSA) adopted by the General Fisheries Commission of the Mediterranean Sea (GFCM). Regression analyses with the species richness as a target variable were adjusted with a set of environmental and geographical variables, being the model that links richness of Chondrichthyes species with distance to the Strait of Gibraltar and number of taxonomic families of bony fishes the one that best explains it. This suggests that both historical and ecological factors affect the current distribution of Chondrichthyes within the Mediterranean Sea. [ABSTRACT FROM AUTHOR]

Ebola virus is responsible for the fatal Ebola virus disease ( EVD)., Identifying the distribution area of the Ebola virus is crucial for understanding the risk factors conditioning the emergence of new EVD cases. Existing distribution models have underrepresented the potential contribution that reservoir species and vulnerable species make in sustaining the presence of the virus., In this paper, we map favourable areas for Ebola virus in Africa according to environmental and zoogeographical descriptors, independent of human-to-human transmissions. We combine two different biogeographical approaches: analysis of mammalian distribution types (chorotypes), and distribution modelling of the Ebola virus., We first obtain a model defining the distribution of environmentally favourable areas for the presence of Ebola virus. Based on a review of mammal taxa affected by or suspected of exposure to the Ebola virus, we model favourable areas again, this time according to mammalian chorotypes. We then build a combined model in which both the environment and mammalian distributions explain the favourable areas for Ebola virus in the wild., We demonstrate that mammalian biogeography contributes to explaining the distribution of Ebola virus in Africa, although vegetation may also underscore clear limits to the presence of the virus. Our model suggests that the Ebola virus may be even more widespread than previously suspected, given that additional favourable areas are found throughout the coastal areas of West and Central Africa, stretching from Cameroon to Guinea, and extend further East into the East African Lakes region., Our findings show that the most favourable area for the Ebola virus is significantly associated with the presence of the virus in non-human mammals. Core areas are surrounded by regions of intermediate favourability, in which human infections of unknown source were found. The difference in association between humans and other mammals and the virus may offer further insights on how EVD can spread. [ABSTRACT FROM AUTHOR]

Aim The use of atlas data in combination with a variety of modelling approaches has become a common practice in species distribution studies. The spatial extent over which species distribution models ( SDMs) should be fitted (i.e. the spatial extent) is often arbitrary and coincides with the extent of the atlases. In order to develop reliable SDMs using species atlas data, we propose an approach that incorporates the taxonomy of species and therefore delineates the spatial extent for SDMs. Location Mainland Spain. Methods We used atlas data to generate taxonomically delineated datasets for 365 terrestrial species. The presence records in the datasets were identical to those in the atlas, while the absence records were delimited to the presence of at least one species in the same family or order. We also generated two randomly delineated datasets that were the same size as the taxonomically delineated datasets. We assessed the predictive performance of the SDMs specifically by studying the model calibration ( Miller's statistic) and discrimination capacity (area under the curve of the receiver operating characteristic plot), along with the geographical similarity pattern of the predicted maps. Results The models that were trained using the taxonomically delineated datasets produced significantly improved models in terms of calibration, while their discrimination capacity was no greater than that of the models trained using the atlas dataset. The improvements to the calibration of the taxonomically delineated datasets were significantly greater than those with random absence sets. Main conclusion Delineating the spatial extent using taxonomical information leads to a significant improvement in the model performance of SDMs. This restriction can reduce the effect of environmental events beyond the species history during model parameterization, thus allowing the models obtained to more precisely depict the potential distribution of the species. We therefore recommend considering the delineation of spatial extent using species taxonomy when atlas data are employed in SDMs. [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]

Wild animals are a primary source of protein (bushmeat) for people living in or near tropical forests. Ideally, the effect of bushmeat harvests should be monitored closely by making regular estimates of offtake rate and size of stock available for exploitation. However, in practice, this is possible in very few situations because it requires both of these aspects to be readily measurable, and even in the best case, entails very considerable time and effort. As alternative, in this study, we use high-resolution, environmental favorability models for terrestrial mammals (N = 165) in Central Africa to map areas of high species richness (hot spots) and hunting susceptibility. Favorability models distinguish localities with environmental conditions that favor the species' existence from those with detrimental characteristics for its presence. We develop an index for assessing Potential Hunting Sustainability (PHS) of each species based on their ecological characteristics (population density, habitat breadth, rarity and vulnerability), weighted according to restrictive and permissive assumptions of how species' characteristics are combined. Species are classified into five main hunting sustainability classes using fuzzy logic. Using the accumulated favorability values of all species, and their PHS values, we finally identify weak spots, defined as high diversity regions of especial hunting vulnerability for wildlife, as well as strong spots, defined as high diversity areas of high hunting sustainability potential. Our study uses relatively simple models that employ easily obtainable data of a species' ecological characteristics to assess the impacts of hunting in tropical regions. It provides information for management by charting the geography of where species are more or less likely to be at risk of extinction from hunting. [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]

To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli's Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species' distribution, instead of building new models that are based on climate change variables only. [ABSTRACT FROM AUTHOR]

The Iberian wild goat (Capra pyrenaica), an endemic species to the Iberian Peninsula, was represented in the past by four subspecies. Currently, the conservation status of the recognized subspecies –C. p. hispanica and C. p. victoriae – is quite different, being the former broadly distributed while the latter inhabits fewer and smaller areas. In this global context, our specific aims were to assess the biogeographical relationships, similarities and differences between the Iberian wild goat subspecies, and to evaluate their conservation status from a biogeographical perspective. We modelled the ecogeographical favourability for each subspecies, and also for the whole species, and we comparatively analyzed the spatial relationships among models in order to detect differential biogeographical patterns. Our results showed a differential pattern for each Iberian wild goat subspecies, and thus each one should be independently considered when designing management strategies. The distribution of C. p. victoriae was closely related to climatic conditions, thus it is highly sensitive to variations in climatic characteristics. Finally, from the perspective of metapopulation theory, and according to the geographical structure of their favourable areas, C. p. victoriae is at higher risk than C. p. hispanica. We discuss the implications of our results for species/subspecies conservation, and highlight the importance of conservation biogeography. [Copyright &y& Elsevier]

The aim of the present paper is to identify the possible existence of groups of species in the genera Audouinella (Rhodophyta), Cystoseira (Phaeophyceae) and Cladophora (Chloropyta) with significantly similar distribution patterns (chorotypes), in the western Mediterranean Sea and the Adriatic Sea. Of the 98 species studied, 59 were grouped into 11 chorotypes, whereas 39 species remained ungrouped. Thirty-eight species were included in a generalist chorotype, whereas 6 chorotypes were monospecific. The relationships with the environmental factors that could explain the chorotypes are discussed. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Simple Summary: We tested the usefulness of new analytical tools such as fuzzy set theory to reveal the hidden internal complexity of the geographic distribution of species. Fuzzy set theory replaces the crisp notion of presence/absence of a species, typical of species distribution atlases, with the fuzzy notion of favorability for the species occurrence. Species distribution ranges are then revealed as more complex than recorded presences suggest, and metapopulation theory, which predicts fragmented favorable patches with connectivity among them, can be operationally analyzed. We identified the favorable patches for 222 butterfly species in the Iberian Peninsula using high values of favorability. We calculated the cost of reaching any part of the territory from a favorable patch using low values of favorability and distance and computed the inverse as connectivity. Some of the favorable territories can be vacant patches but also belong to the metapopulation structure, as they may be recolonized. This information is relevant for territory management and biodiversity conservation, serving to justify the protection of new areas or the modification of contours of reserves based on the role they play for the populations of interest. Metapopulation theory considers that the populations of many species are fragmented into patches connected by the migration of individuals through an interterritorial matrix. We applied fuzzy set theory and environmental favorability (F) functions to reveal the metapopulational structure of the 222 butterfly species in the Iberian Peninsula. We used the sets of contiguous grid cells with high favorability (F ≥ 0.8), to identify the favorable patches for each species. We superimposed the known occurrence data to reveal the occupied and empty favorable patches, as unoccupied patches are functional in a metapopulation dynamics analysis. We analyzed the connectivity between patches of each metapopulation by focusing on the territory of intermediate and low favorability for the species (F < 0.8). The friction that each cell opposes to the passage of individuals was computed as 1-F. We used the r.cost function of QGIS to calculate the cost of reaching each cell from a favorable patch. The inverse of the cost was computed as connectivity. Only 126 species can be considered to have a metapopulation structure. These metapopulation structures are part of the dark biodiversity of butterflies because their identification is not evident from the observation of the occurrence data but was revealed using favorability functions. [ABSTRACT FROM AUTHOR]