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Copyright of Journal of Raptor Research is the property of Raptor Research Foundation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

West Nile virus (WNV) is a globally widespread arthropod‐borne virus that poses a significant public health concern. Mosquitoes transmit the virus in an enzootic cycle among birds, which act as reservoirs. Climate plays a crucial role in these outbreaks as mosquitoes are highly influenced by climatic conditions, and bird migrations are also affected by weather patterns. Consequently, changes in climate can potentially impact the occurrence of WNV outbreaks. We used biogeographic modelling based on machine learning algorithms and fuzzy logic to analyse and evaluate separately the risk of WNV outbreaks in two different biogeographic regions, the Afrotropical and the Western Palaearctic region. By employing fuzzy logic tools, we constructed a comprehensive risk model that integrates the Afro‐Palaearctic system as a unified operational unit for WNV spread. This innovative approach recognizes the Afro‐Palaearctic region as a pathogeographic system, characterized by biannual connections facilitated by billions of migratory bird reservoirs carrying the disease. Subsequently, we forecasted the effects of different climate change scenarios on the spread of WNV in the Afro‐Palaearctic system for the years 2040 and 2070. Our findings revealed an increasing epidemic and epizootic risk south of the Sahara. However, the area where an upsurge in risk was forecasted the most lies within Europe, with the anticipation of risk expansion into regions presently situated beyond the virus' distribution range, including central and northern Europe. Gaining insight into the risk within the Afro‐Palaearctic system is crucial for establishing coordinated and international One Health surveillance efforts. This becomes particularly relevant in the face of ongoing climate change, which disrupts the ecological equilibrium among vectors, reservoirs, and human populations. We show that the application of biogeographical tools to assess risk of infectious disease, i.e. pathogeography, is a promising approach for understanding distribution patterns of zoonotic diseases and for anticipating their future spread. [ABSTRACT FROM AUTHOR]

Climate change may increase the risk of dengue and yellow fever transmission by urban and sylvatic mosquito vectors. Previous research primarily focused on Aedes aegypti and Aedes albopictus. However, dengue and yellow fever have a complex transmission cycle involving sylvatic vectors. Our aim was to analyze how the distribution of areas favorable to both urban and sylvatic vectors could be modified as a consequence of climate change. We projected, to future scenarios, baseline distribution models already published for these vectors based on the favorability function, and mapped the areas where mosquitoes' favorability could increase, decrease or remain stable in the near (2041–2060) and distant (2061–2080) future. Favorable areas for the presence of dengue and yellow fever vectors show little differences in the future compared to the baseline models, with changes being perceptible only at regional scales. The model projections predict dengue vectors expanding in West and Central Africa and in South-East Asia, reaching Borneo. Yellow fever vectors could spread in West and Central Africa and in the Amazon. In some locations of Europe, the models suggest a reestablishment of Ae. aegypti, while Ae. albopictus will continue to find new favorable areas. The results underline the need to focus more on vectors Ae. vittatus, Ae. luteocephalus and Ae. africanus in West and Central sub-Saharan Africa, especially Cameroon, Central Africa Republic, and northern Democratic Republic of Congo; and underscore the importance of enhancing entomological monitoring in areas where populations of often overlooked vectors may thrive as a result of climate changes. [ABSTRACT FROM AUTHOR]

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]

Under the current pattern of climate change, mountain bird populations are generally shifting their ranges to higher elevations, tracking their climatic optima. Nevertheless, space limitations at high altitudes constrain mountain species' resilience to climatic change, making them particularly vulnerable. In extreme cases, the climatic niche of some species can move beyond mountaintops, ultimately driving such species to extinction. This study presents the case of the northern wheatear Oenanthe oenanthe in mainland Spain and compares its breeding distribution from 2003 to 2022. Spain, where the species mostly occupies mountain areas, represents its southernmost distribution limit in Europe. We built environmental favourability models using information from the two most recent Spanish bird atlases and a set of climatic, topographic, human activity and lithological variables to determine the factors affecting the occurrence of the species. The influence of climate compared to all other factors was obtained using variation partitioning analysis. The northern wheatear has suffered a strong reduction (67%) in occupied areas and also in favourability throughout mainland Spain (especially in the south) where climate change may have far‐reaching consequences, including local extinctions. Climate explained more than 90% of the variation in the model obtained for 2022. Interestingly, the occupied areas were, on average, 100 m higher in 2022 than in 2003. If the effects of climate warming persist, the northern wheatear will likely disappear in its southernmost distribution limit, being the Sierra de las Nieves National Park population the most vulnerable in mainland Spain. For this reason, it is necessary to implement monitoring programmes for northern wheatear populations, with priority for mountain systems wherein they already occupy higher elevations, as well as further studies on other mountain species. [ABSTRACT FROM AUTHOR]

Background: Experts use knowledge to infer the distribution of species based on fuzzy logical assumptions about the relationship between species and the environment. Thus, expert knowledge is amenable to fuzzy logic modelling, which give to propositions a continuous truth value between 0 and 1. In species distribution modelling, fuzzy logic may also be used to model, from a number of records, the degree to which conditions are favourable to the occurrence of a species. Therefore, fuzzy logic operations can be used to compare and combine models based on expert knowledge and species records. Here, we applied fuzzy logic modelling to the distribution of amphibians in Uruguay as inferred from expert knowledge and from observed records to infer favourable locations, with favourability being the commensurable unit for both kinds of data sources. We compared the results for threatened species, species considered by experts to be ubiquitous, and non-threatened, non-ubiquitous species. We calculated the fuzzy intersection of models based on both knowledge sources to obtain a unified prediction of favourable locations. Results: Models based on expert knowledge involved a larger number of variables and were less affected by sampling bias. Models based on experts had the same overprediction rate for the three types of species, whereas models based on species records had a lower prediction rate for ubiquitous species. Models based on expert knowledge performed equally as well or better than corresponding models based on species records for threatened species, even when they had to discriminate and classify the same set of records used to build the models based on species records. For threatened species, expert models predicted more restrictive favourable territories than those predicted based on records. Observed records generated the best-fitted models for non-threatened non-ubiquitous species, and ubiquitous species. Conclusions: Fuzzy modelling permitted the objective comparison of the potential of expert knowledge and incomplete distribution records to infer the territories favourable for different species. Distribution of threatened species was able to be better explained by subjective expert knowledge, while for generalist species models based on observed data were more accurate. These results have implications for the correct use of expert knowledge in conservation planning. [ABSTRACT FROM AUTHOR]

In the Northern Alboran Sea, artisanal small-scale fisheries using trammel nets suffer economic losses, and local fishermen see their way-of-life endangered, due to interactions with wildlife species such as alien species and dolphins. On the one hand, the alien seaweed Rugulopteryx okamurae, which was first recorded in the Alboran Sea in 2015, has undergone an intensive expansion in the sub-region, monopolizing the available seabed, causing radical changes in the underwater seascape and clogging the trammel nets. On the other hand, the damage caused to the fishing nets by dolphin fish predation is an ancient problem worldwide, but it is intensifying in the last years. The main objective of this study is to understand the main environmental and technical conditions that favor damages of fishing trammel nets in the Alboran Sea, which entails an important loss of catchability, due to (i) the clogging of the artisanal fishing trammel nets by invasive seaweed, and (ii) the breaking of the nets by dolphin predation. Through close monitoring of fishermen in port, we obtained direct information of 548 sets. Our results indicate that approximately 30% of trammel sets suffered a damage due to unwanted interaction with alien seaweeds and dolphins. As seaweeds invasion is a global problem while dolphin-fishing gear interaction is more local, we concluded that only a large-scale management of exotic algae, together with the involvement of local fishermen, could solve the economic problems of this activity. [ABSTRACT FROM AUTHOR]

Background: The current modification of species distribution ranges, as a response to a warmer climate, constitutes an interesting line of work and a recent challenge for biogeography. This study aimed to determine if the climatic conditions of southern Europe are adequate to host a typical African species, the House Bunting, which is registered regularly during the last years, still in low numbers. To this end, the distribution of the species in its native range was modelled, both in the present and in future climate scenarios, using its current breeding distribution areas and a set of environmental variables. Results: The results showed that the southern half of the Iberian Peninsula exhibits high values of favourability to host this African species for the current climatic conditions. Furthermore, future forecasts indicated an increase in favourability for this area. The highly favourable areas we detected in the south of the Iberian Peninsula are already regularly receiving individuals of the species. These observations are very likely vagrant birds dispersing from recently colonised breeding areas in northern Morocco, which may indicate a continuous process of colonisation towards the north, as has occurred during the last decades in Northern Africa. Conclusions: We cannot anticipate when the House Bunting will establish on the European continent because colonisation processes are usually slow but, according to our results, we predict its establishment in the near future. We have also identified those areas hosting favourable conditions for the species in Europe. These areas are a potential focal point for the colonisation of this and other African birds if the climate continues to warm. [ABSTRACT FROM AUTHOR]

Copyright of Mammal Review is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Deep-habitat cetaceans are generally difficult to study, leading to a limited knowledge of their population. This paper assesses the differential distribution patterns of three deep-habitat cetaceans (Sperm whale—Physeter macrocephalus, Risso's dolphin—Grampus griseus & Cuvier's beaked whale—Ziphius cavirostris). We used data of 842 opportunistic sightings of cetaceans in the western Mediterranean sea. We inferred environmental and spatio-temporal factors that affect their distribution. Binary logistic regression models were generated to compare the presence of deep-habitat cetaceans with the presence of other cetacean species in the dataset. Then, the favourability function was applied, allowing for comparison between all the models. Sperm whale and Risso's dolphin presence was differentially favoured by the distance to towns in the eastern part of the western Mediterranean sea. The differential distribution of sperm whale was also influenced by the stability of SST, and that of the Risso's dolphin by lower mean salinity and higher mean Chlorophyll A concentration. When modelling the three deep-habitat cetaceans (including Cuvier's beaked whale), the variable distance to towns had a negative influence on the presence of any of them more than it did to other cetaceans, being more favourable far from towns, so this issue should be further investigated. [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]

Yellow fever is transmitted by mosquitoes among human and non-human primates. In the last decades, infections are occurring in areas that had been free from yellow fever for decades, probably as a consequence of the rapid spread of mosquito vectors, and of the virus evolutionary dynamic in which non-human primates are involved. This research is a pathogeographic assessment of where enzootic cycles, based on primate assemblages, could be amplifying the risk of yellow fever infections, in the context of spatial changes shown by the disease since the late 20th century. In South America, the most relevant spread of disease cases affects parts of the Amazon basin and a wide area of southern Brazil, where forest fragmentation could be activating enzootic cycles next to urban areas. In Africa, yellow fever transmission is apparently spreading from the west of the continent, and primates could be contributing to this in savannas around rainforests. Our results are useful for identifying new areas that should be prioritised for vaccination, and suggest the need of deep yellow fever surveillance in primates of South America and Africa. Models based on primates and disease vectors indicate a risk of zoonotic and anthroponotic yellow fever expansion in South America and Africa. [ABSTRACT FROM AUTHOR]

Yellow fever is transmitted by mosquitoes among human and non-human primates. In the last decades, infections are occurring in areas that had been free from yellow fever for decades, probably as a consequence of the rapid spread of mosquito vectors, and of the virus evolutionary dynamic in which non-human primates are involved. This research is a pathogeographic assessment of where enzootic cycles, based on primate assemblages, could be amplifying the risk of yellow fever infections, in the context of spatial changes shown by the disease since the late 20th century. In South America, the most relevant spread of disease cases affects parts of the Amazon basin and a wide area of southern Brazil, where forest fragmentation could be activating enzootic cycles next to urban areas. In Africa, yellow fever transmission is apparently spreading from the west of the continent, and primates could be contributing to this in savannas around rainforests. Our results are useful for identifying new areas that should be prioritised for vaccination, and suggest the need of deep yellow fever surveillance in primates of South America and Africa. Models based on primates and disease vectors indicate a risk of zoonotic and anthroponotic yellow fever expansion in South America and Africa. [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]

West Nile virus (WNV) is an emergent arthropodborne virus that is transmitted from bird to bird by mosquitoes. Spillover events occur when infected mosquitoes bite mammals. We created a geopositioned database of WNV presence in Africa and considered reports of the virus in all animal components: reservoirs, vectors, and nonhuman dead-end hosts. We built various biogeographic models to determine which drivers explain the distribution of WNV throughout Africa. Wetlands of international importance for birds accounted for the detection of WNV in all animal components, whereas human-related drivers played a key role in the epizootic cases. We combined these models to obtain an integrative and large-scale perspective of the areas at risk for WNV spillover. Understanding which areas pose the highest risk would enable us to address the management of this spreading disease and to comprehend the translocation of WNV outside Africa through avian migration routes. [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]

West Nile virus infections in humans are continuously increasing, and the virus has spread considerably in Europe over the past decade. The incidence of the disease was unusually high between 2018 and 2020. The resulting model identifies the West Nile virus outbreak‐prone areas during 2021, even in regions where the virus has not yet been discovered. It is remarkable that in Central Europe, new favourable areas are emerging, where early actions could lessen the impact of the disease. [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]

This document is a correction notice for an article titled "Using fuzzy logic to compare species distribution models developed on the basis of expert knowledge and sampling records" published in Frontiers in Zoology. The authors reported that the link to the data repository was missing in the original article. The correction provides the correct link to access the dataset supporting the conclusions of the article. The original article has been updated accordingly. [Extracted from the article]

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]

Dengue is a viral disease transmitted by mosquitoes. The rapid spread of dengue could lead to a global pandemic, and so the geographical extent of this spread needs to be assessed and predicted. There are also reasons to suggest that transmission of dengue from non-human primates in tropical forest cycles is being underestimated. We investigate the fine-scale geographic changes in transmission risk since the late 20th century, and take into account for the first time the potential role that primate biogeography and sylvatic vectors play in increasing the disease transmission risk. We apply a biogeographic framework to the most recent global dataset of dengue cases. Temporally stratified models describing favorable areas for vector presence and for disease transmission are combined. Our models were validated for predictive capacity, and point to a significant broadening of vector presence in tropical and non-tropical areas globally. We show that dengue transmission is likely to spread to affected areas in China, Papua New Guinea, Australia, USA, Colombia, Venezuela, Madagascar, as well as to cities in Europe and Japan. These models also suggest that dengue transmission is likely to spread to regions where there are presently no or very few reports of occurrence. According to our results, sylvatic dengue cycles account for a small percentage of the global extent of the human case record, but could be increasing in relevance in Asia, Africa, and South America. The spatial distribution of factors favoring transmission risk in different regions of the world allows for distinct management strategies to be prepared. Author summary: The rate of disease emergence is increasing globally, and many long-existing diseases are extending their distribution ranges. This is the case for dengue, a global pandemic whose mosquito vectors are currently occupying ever-increasing numbers of regions worldwide. We updated the most complete global dataset of dengue cases available, and addressed the fine-scale analysis of the geographic changes experienced in dengue-transmission risk since the late 20th century. Our approach is the first to take into account the potential role of primates and sylvatic vectors in increasing the disease transmission risk in tropical forests. We built models that describe the favorable areas for vector presence and for disease occurrence, and combined them in order to obtain a novel model for predicting transmission risk. We show that dengue transmission is likely to spread to affected areas in Asia, Africa, North and South America, and Oceania, and to regions with presently no or very few cases, including cities in Europe and Japan. The global contribution of sylvatic dengue cycles is small but meaningful. Our methodological approach can differentiate the factors favoring risk in different world regions, thus allowing for management strategies to be prepared specifically for each of these regions. [ABSTRACT FROM AUTHOR]

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]

The North Atlantic Oscillation (NAO) is the most important large-scale climatic oscillation affecting the North Atlantic region. The variability introduced by the NAO affects many meteorological parameters, including wind speed and direction, and differences in air temperature and rainfall, particularly during the boreal winter. The NAO is also known to affect the ocean by changing heat content, sea surface temperature, gyre circulation, mixed layer depth, salinity, high-latitude deep water formation, and sea ice cover. Consequently, the NAO has been widely used to analyze the variability of marine ecosystems. Several researchers found that fishery resources were teleconnected with the NAO variability, resulting in a significant relationship between this climatic oscillation and fishery yields. More precisely, the NAO affects the target species abundance, recruitment, catchability, and body condition. These effects can be cumulative over time and act synergistically. In this study, the available information about this topic is reviewed, and the importance of the NAO as a large-scale climatic oscillation in fisheries management is discussed using an ecosystem approach. We also discuss the possible effects of climate change on Atlantic and Mediterranean fisheries if this change were to affect the NAO pattern. [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]

West Nile virus is a widely spread arthropod-born virus, which has mosquitoes as vectors and birds as reservoirs. Humans, as dead-end hosts of the virus, may suffer West Nile Fever (WNF), which sometimes leads to death. In Europe, the first large-scale epidemic of WNF occurred in 1996 in Romania. Since then, human cases have increased in the continent, where the highest number of cases occurred in 2018. Using the location of WNF cases in 2017 and favorability models, we developed two risk models, one environmental and the other spatio-environmental, and tested their capacity to predict in 2018: 1) the location of WNF; 2) the intensity of the outbreaks (i.e. the number of confirmed human cases); and 3) the imminence of the cases (i.e. the Julian week in which the first case occurred). We found that climatic variables (the maximum temperature of the warmest month and the annual temperature range), human-related variables (rain-fed agriculture, the density of poultry and horses), and topo-hydrographic variables (the presence of rivers and altitude) were the best environmental predictors of WNF outbreaks in Europe. The spatio-environmental model was the most useful in predicting the location of WNF outbreaks, which suggests that a spatial structure, probably related to bird migration routes, has a role in the geographical pattern of WNF in Europe. Both the intensity of cases and their imminence were best predicted using the environmental model, suggesting that these features of the disease are linked to the environmental characteristics of the areas. We highlight the relevance of river basins in the propagation dynamics of the disease, as outbreaks started in the lower parts of the river basins, from where WNF spread towards the upper parts. Therefore, river basins should be considered as operational geographic units for the public health management of the disease. Author summary: West Nile virus is a widely spread flavivirus, which is transmitted from birds to humans by mosquitoes. In humans, the virus can cause West Nile Fever (WNF) and in some cases, it affects the nervous system leading to severe symptoms that may result in death. Human cases have increased in Europe since the large-scale epidemic in 1996, being 2018 the year with the highest number of cases registered to date. We developed risk models based on 2017 cases, and predicted in 2018: 1) the occurrence of the disease; 2) the intensity of the outbreaks; and 3) the imminence of the cases. We identified favorable areas for the incidence of the virus in which environmental and human-related variables had an important role. The outbreaks began in the lower areas of large river basins and spread to higher areas, which highlights the importance of river basins in the propagation of outbreaks. Consequently, the early warning should be based on a basin scale. [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: 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]

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]

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]

Currently, there are naturalized populations of feral pigeon (Columba livia var. domestica) worldwide with an estimated global population between 165 and 330 million individuals. Feral pigeons are adapted to urban environments, creating problems related to human health, damage to architectural structures, unpleasant soiling, and foul odors. Thus, local governments usually implement measures to reduce feral pigeon populations in cities to a suitable size. We monitored a feral pigeon trapping campaign to investigate the use of cage traps as control method in residential zones. We analyzed efficiency (daily capture rate), effectiveness (defined as the number of feral pigeons captured relative to the total number of potential pigeon captures), animal welfare, selectivity (the proportion of captured feral pigeons in relation to the total number of captured animals), and the effect on feral pigeon abundance. All procedures were conducted in compliance with current European and Spanish legislation. Overall efficiency was 0.25 feral pigeons/trap-day, effectiveness was 22.5%, and selectivity was 99.7%. Over the study period, there was a decreasing trend in abundances. A significant decrease was found in the relative abundances of feral pigeons after 2 months of extractions, and population abundances remained low up to the end of the extraction period. The use of cage traps was a useful and effective method to reduce local feral pigeon populations in isolated urban areas with low building density in which the feral pigeon population has not yet reached high densities. [ABSTRACT FROM AUTHOR]

For several decades, there have been changes in the distance of bird migration. The Eurasian Reed Warbler Acrocephalus scirpaceus is a Trans-Saharan migratory species, which, as recent records suggest, is increasingly wintering in the Iberian Peninsula. This study investigated the strength of the influence of climate on the wintering of this insectivorous species in the Iberian Peninsula, and also used geospatial modelling to identify the most favourable areas. The model was constructed to identify the most relevant explanatory factors of this distribution and it was assessed by applying calibration and discrimination criteria, and the influence of each factor was analysed using variation partitioning. Theminimum winter temperature is themost relevant factor affecting sites suitable for the wintering of this species in Europe. The best areas are located in the southern and eastern coasts of the Iberian Peninsula and in some locations on the northern Atlantic coast of Spain. Spatial trends analysis corroborated the orientation of the flight paths of the species from their breeding areas to their wintering areas. To pography refined the model in that it is associated with habitat selection at a fine-scale. As the case of the Eurasian Reed Warbler is not unique, the results show the role of the Iberian Peninsula as a new wintering site for species usually wintering in the Sub-Saharan region, modifying their wintering strategy from Trans-Saharan to Pre-Saharanmigrants, and whether the recent increase in temperature is the main cause. [ABSTRACT FROM AUTHOR]

Monitoring progress towards global goals and biodiversity targets require reliable descriptions of species distributions over time and space. Current gaps in accessible information on species distributions urges the need for integrating all available data and knowledge sources, and intensifying cooperations to more effectively support global environmental governance. For many areas and species groups, experts can constitute a valuable source of information to fill the gaps by offering their knowledge on species-environment interactions. However, expert knowledge is always subject to uncertainty, and incorporating that into species distribution mapping poses a challenge. We propose the use of the dempster-shafer theory of evidence (DST) as a novel approach in this field to extract expert knowledge, to incorporate the associated uncertainty into the procedure, and to produce reliable species distribution maps. We applied DST to model the distribution of two species of eagle in Spain. We invited experts to fill in an online questionnaire and express their beliefs on the habitat of the species by assigning probability values for given environmental variables, along with their confidence in expressing the beliefs. We then calculated evidential functions, and combined them using Dempster's rules of combination to map the species distribution based on the experts' knowledge. We evaluated the performances of our proposed approach using the atlas of Spanish breeding birds as an independent test dataset, and further compared the results with the outcome of an ensemble of conventional SDMs. Purely based on expert knowledge, the DST approach yielded similar results as the data driven SDMs ensemble. Our proposed approach offers a strong and practical alternative for species distribution modelling when species occurrence data are not accessible, or reliable, or both. The particular strengths of the proposed approach are that it explicitly accounts for and aggregates knowledge uncertainty, and it capitalizes on the range of data sources usually considered by an expert. [ABSTRACT FROM AUTHOR]

The fin whale (Balaenoptera physalus) is a cosmopolitan species with a resident population in the Mediterranean Sea. Due to its habitat, open seas often far from ports and airfields, and its long-distance migratory behaviour, studying and monitoring its distribution is costly. Currently, many opportunistic sightings (OS) reports are available, which provide a source of potentially useful, low-cost information about the spatio-temporal distribution of this species. Since 1993, the Spanish Institute of Oceanography has compiled a dataset comprising 874 records of OS of nine species of cetaceans in the western Mediterranean Sea and adjacent waters. The aim of this study was to use this dataset to investigate the differential use of these waters by the fin whale when compared with other cetaceans. We compared the presence of fin whales with the presence of any other cetacean species in the dataset. Binary logistic regression was then used to model these occurrences according to several spatio-temporal variables expected to reflect their habitat use. Several significant models reveal that fin whales are more prone than other cetaceans to use the waters over the slope of the Gulf of Lion in summer. This finding confirms that the Gulf of Lion is an area of importance for this species and suggests that the slope of the continental shelf could be particularly important. Our study shows how OS can be a source of useful information when appropriately analyzed. [ABSTRACT FROM AUTHOR]

Observed species richness (OSR) is a widely used and well-studied biodiversity metric. However, non-observed species in favorable ecosystems are also relevant. Two metrics that include observed and potential species were recently defined: potential biodiversity (hereafter potential species richness—PSR) and geometric mean of favorabilities (GMF). We used these metrics to evaluate the national park network of mainland Spain at two time periods (2002 and 2015), using terrestrial mammals on a UTM 100-km2 grid. PSR and GMF are based on the favorability function, a species distribution model that assesses how favorable an area is for the presence of a species, over and above its prevalence in the study area. For each park and for the whole network, we calculated the mean and sum of OSR, PSR, and GMF in each time period, as well as changes between periods. OSR and PSR were higher inside than outside the park network in both time periods. Thus, although the network covers a very small proportion of the country, it performs well for the representation of mammal species and their favorable areas. However, mean PSR was lower in 2015 than in 2002 inside the national park network, whereas the opposite was the case outside the network. Mountainous Parks generally not only concentrated highly favorable areas for mammals, but they also showed less favorable areas in 2015 compared to 2002, although the reduction was moderate to low. This is a result to consider for future analyses because if the tendency increases, it may have consequences for the conservation of mammals and for the adequacy of the national park network. [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]

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. [ABSTRACT FROM AUTHOR]

Ebola virus disease (EVD) is a contagious, severe and often lethal form of hemorrhagic fever in humans. The association of EVD outbreaks with forest clearance has been suggested previously but many aspects remained uncharacterized. We used remote sensing techniques to investigate the association between deforestation in time and space, with EVD outbreaks in Central and West Africa. Favorability modeling, centered on 27 EVD outbreak sites and 280 comparable control sites, revealed that outbreaks located along the limits of the rainforest biome were significantly associated with forest losses within the previous 2 years. This association was strongest for closed forests (>83%), both intact and disturbed, of a range of tree heights (5–>19 m). Our results suggest that the increased probability of an EVD outbreak occurring in a site is linked to recent deforestation events, and that preventing the loss of forests could reduce the likelihood of future outbreaks. [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]

Wind power, as an alternative to fossil fuels, is increasingly common, and is expanding worldwide. Wind farms cause mortality of flying animals through collision with moving rotor blades, and from electrocution on associated power lines. Avian mortality rates have been estimated from birds collected under turbines over varying time intervals. However, without adequate and frequent monitoring, dead birds may be removed by scavengers and thus cause an underestimation of fatalities. In this paper, we tested experimentally for possible errors arising in avian mortality caused by the removal of carcasses by scavengers. At two different wind farms and associated power lines in southern Spain, we placed pigeon and quail carcasses to determine their disappearance rate. All dead pigeons were radio-tagged to estimate distances taken by scavengers. We found significant differences in carcass disappearance rates of pigeons and quails, and between wind farms and power lines but not between habitats. All quails and 45% of pigeon carcasses had disappeared by the third and fourteenth day, respectively. Less than half (40%) of the carcasses were found < 100 m from where they were deposited. While scavenging losses may vary according to the location of the wind farm or power line, here we propose a method to estimate correctly the number of fatalities at any wind farm and power line. Using this method, we can improve our understanding of the real impact of wind structures on adjacent bird communities, and adopt appropriate measures to ensure their conservation. [ABSTRACT FROM PUBLISHER]

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]

Winters have become warmer under the impact of climate change, which has modified the phenology as well as the distribution ranges of birds. The African Long-legged Buzzard Buteo rufinus cirtensis has recently colonized Europe via the Strait of Gibraltar. We aim to explain the native distribution of this species and to predict favourable areas in newly colonized parts of Europe using geospatial modelling to identify the most influential factors in this process. We applied the favourability function, a generalized linear model describing environmental favourability, for the presence/absence of breeding areas in northern Morocco and the southern Iberian Peninsula, according to a set of variables describing climate, topography, human activity, vegetation and purely spatial trends. A model was built using some known breeding sites in northern Morocco, and was used to forecast future suitable breeding areas in Europe. A second model was built with the available data for northern Morocco and Europe to explain the current distribution of breeding sites. Both models were assessed according to discrimination, calibration and parsimony criteria, and the influence of each factor was analysed using variation partitioning. We conclude that the Iberian Peninsula could provide new suitable areas for the species and facilitate its northward expansion. This result, together with the increasing number of records available, suggests that this species could soon spread throughout Europe. Steady temperatures and abundant but seasonally distributed precipitation showed the strongest predictive power in the models. This indicates a close relationship between the species' distribution and climate in the study area, and suggests that this species finds its most favourable environments in the Mediterranean biome. Topography and vegetation, specifically cliffs and woods near hunting zones, point to a fine-scale habitat selection for breeding. As the case of the African Long-legged Buzzard is not a unique event, our results may be useful to determine whether a northward expansion of the Mediterranean biome could be followed by distribution shifts of bird species that have so far been restricted to Africa. [ABSTRACT FROM AUTHOR]

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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]

The article discusses the protected African rainforest mammals and climate change.