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This study uses the amphibian species of the Mediterranean basin to develop a consistent procedure based on fuzzy sets with which biogeographic regions and biotic transition zones can be objectively detected and reliably mapped. Biogeographical regionalizations are abstractions of the geographical organization of life on Earth that provide frameworks for cataloguing species and ecosystems, for answering basic questions in biogeography, evolutionary biology, and systematics, and for assessing priorities for conservation. On the other hand, limits between regions may form sharply defined boundaries along some parts of their borders, whereas elsewhere they may consist of broad transition zones. The fuzzy set approach provides a heuristic way to analyse the complexity of the biota within an area; significantly different regions are detected whose mutual limits are sometimes fuzzy, sometimes clearly crisp. Most of the regionalizations described in the literature for the Mediterranean biogeographical area present a certain degree of convergence when they are compared within the context of fuzzy interpretation, as many of the differences found between regionalizations are located in transition zones, according to our case study. Compared with other classification procedures based on fuzzy sets, the novelty of our method is that both fuzzy logic and statistics are used together in a synergy in order to avoid arbitrary decisions in the definition of biogeographic regions and transition zones.

We modelled the distributions of two toads (Bufo bufo and Epidalea calamita) in the Iberian Peninsula using the favourability function, which makes predictions directly comparable for different species and allows fuzzy logic operations to relate different models. The fuzzy intersection between individual models, representing favourability for the presence of both species simultaneously, was compared with another favourability model built on the presences shared by both species. The fuzzy union between individual models, representing favourability for the presence of any of the two species, was compared with another favourability model based on the presences of either or both of them. The fuzzy intersections between favourability for each species and the complementary of favourability for the other (corresponding to the logical operation "A and not B") were compared with models of exclusive presence of one species versus the exclusive presence of the other. The results of modelling combined species data were highly similar to those of fuzzy logic operations between individual models, proving fuzzy logic and the favourability function valuable for comparative distribution modelling. We highlight several advantages of fuzzy logic over other forms of combining distribution models, including the possibility to combine multiple species models for management and conservation planning.

Chorotypes--statistically significant groups of coincident distribution areas--constitute biogeographic units that are fuzzy by nature. This quality has been referred to in the literature but has not been analyzed in depth or methodologically developed. The present work redefines chorotypes as fuzzy sets from a pragmatic perspective and basically focuses on the methodological and interpretative implications of this approach. The amphibian fauna in the Iberian Peninsula was used as an example to explore the fuzzy nature of chorotypes. The method on which this article is based is a widely used technique to define chorotypes. This method involves the fuzziness that is inherent to the identification between degree of similarity and degree of membership and includes a probabilistic analysis of the classification for the objective delimitation of chorotypes. The main innovation of this paper is a procedure to analyze chorotypes as fuzzy biogeographic units. A set of fuzzy parameters to deal with the biogeographic interpretation of fuzzy chorotypes is also described. A computer program has been developed and is freely available. History may be related to the degree of fuzziness of chorotypes. In our example, with amphibian distributions in Iberia, less fuzzy chorotypes could have a historical explanation, and the internal fuzziness of chorotypes increases with their distance to hypothetical Pleistocene refugia.

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]

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]

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]

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]

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]

Distribution models should take into account the different limiting factors that simultaneously influence species ranges. Species distribution models built with different explanatory variables can be combined into more comprehensive ones, but the resulting models should maximize complementarity and avoid redundancy. Our aim was to compare the different methods available for combining species distribution models. We modelled 19 threatened vertebrate species in mainland Spain, producing models according to three individual explanatory factors: spatial constraints, topography and climate, and human influence. We used five approaches for model combination: Bayesian inference, Akaike weight averaging, stepwise variable selection, updating, and fuzzy logic. We compared the performance of these approaches by assessing different aspects of their classification and discrimination capacity. We demonstrated that different approaches to model combination give rise to disparities in the model outputs. Bayesian integration was systematically affected by an error in the equations that are habitually used in distribution modelling. Akaike weights produced models that were driven by the best single factor and therefore failed at combining the models effectively. The updating and the stepwise approaches shared recalibration as the basic concept for model combination, were very similar in their performance, and showed the highest sensitivity and discrimination capacity. The fuzzy-logic approach yielded models with the highest classification capacity according to Cohen's kappa. In conclusion: 1) Bayesian integration, employing the currently used equation, and the Akaike weight procedure should be avoided; 2) the updating and stepwise approaches can be considered minor variants of the same recalibrating approach; and 3) there is a trade-off between this recalibrating approach, which has the highest sensitivity, and fuzzy logic, which has the highest overall classification capacity. Recalibration is better if unfavourable conditions in one environmental factor may be counterbalanced with favourable conditions in a different factor, otherwise fuzzy logic is better. [ABSTRACT FROM AUTHOR]

The rapid ecological shifts that are occurring due to climate change present major challenges for managers and policymakers and, therefore, are one of the main concerns for environmental modelers and evolutionary biologists. Species distribution models ( SDM) are appropriate tools for assessing the relationship between species distribution and environmental conditions, so being customarily used to forecast the biogeographical response of species to climate change. A serious limitation of species distribution models when forecasting the effects of climate change is that they normally assume that species behavior and climatic tolerances will remain constant through time. In this study, we propose a new methodology, based on fuzzy logic, useful for incorporating the potential capacity of species to adapt to new conditions into species distribution models. Our results demonstrate that it is possible to include different behavioral responses of species when predicting the effects of climate change on species distribution. Favorability models offered in this study show two extremes: one considering that the species will not modify its present behavior, and another assuming that the species will take full advantage of the possibilities offered by an increase in environmental favorability. This methodology may mean a more realistic approach to the assessment of the consequences of global change on species' distribution and conservation. Overlooking the potential of species' phenotypical plasticity may under- or overestimate the predicted response of species to changes in environmental drivers and its effects on species distribution. Using this approach, we could reinforce the science behind conservation planning in the current situation of rapid climate change. [ABSTRACT FROM AUTHOR]

Abstract: The effectiveness of selecting umbrella species or groups of species to protect other groups is a key and unresolved issue in conservation planning. We detected areas important to the four groups of terrestrial vertebrates inhabiting Andalusia (southern Spain) according to four conservation-value criteria, i.e., richness, rarity, vulnerability, and endemicity. We calculated coincidences between criteria and taxa by the degree of correlation and fuzzy overlap between the different criteria for the same group (intra-group coincidence) and between the different groups of species for the same criteria (inter-group coincidence). For the groups to be appropriate umbrella species, inter-group coincidence should be high. The results showed that intra-group coincidence was high, but inter-group coincidence was low. Thus, zones of importance to each group of species tended to be located in different places compared to the other groups, and therefore none of them should be used as an indicator or umbrella group to protect the others. This result has implications for conservation policy, as the Andalusian authorities should not assume that protecting a site important to one group of species will also be relevant to conserve the other groups. Nevertheless, we identified the areas of relatively high conjoint importance for all the groups, and the best umbrella group in this region, which proved to be reptiles. [Copyright &y& Elsevier]

We compared the effect of general circulation models and greenhouse gas emission scenarios on the uncertainty associated with models predicting changes in areas favourable to animal species. Given that mountain species are particularly at risk due to climate warming, we selected one amphibian (Baetic midwife toad), one reptile (Lataste's viper), one bird (Bonelli's eagle), and one mammal (Iberian wild goat) present in Spanish mountains to model their distributional response to climate change during this century. Climate forecasts for the whole century were provided by the Agencia Estatal de Meteorología (AEMET; National Meteorological Agency) of Spain, which adapted the general circulation models CGCM2 and ECHAM4 and produced expected temperature and precipitation values for Spain according to the A2 and B2 emission scenarios. We constructed separate models of the species response to spatial, topographic, human, and climate variables using current values of the corresponding variables. We predicted future areas favourable to the species by replacing the current climate values with those expected according to each climate change scenario, while keeping spatial, topographic and human variables constant. Fuzzy logic was used to compute the coincidence between predictions for different emission scenarios in the same global circulation model, and the consistency between predictions for the same emission scenario applying different general circulation models. In general, coincidences were higher than consistencies and, thus, discrepancies between predictions were more attributable to uncertainty in global circulation models, i.e. our insufficient knowledge concerning the effect of the oceans and atmosphere on climate, than to the putative effect of different emission scenarios on future climates. Our conclusion is that species distribution models in climate warming scenarios are still not useful for informing emission policy planning, although they have great potential as tools once consistencies become higher than coincidences. [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]

Background: Over the last decade, reports about dengue cases have increase worldwide, which is particularly worrisome in South America due to the historic record of dengue outbreaks from the seventeenth century until the first half of the twentieth century. Dengue is a viral disease that involves insect vectors, namely Aedes aegypti and Ae. albopictus, which implies that, to prevent and combat outbreaks, it is necessary to understand the set of ecological and biogeographical factors affecting both the vector species and the virus. Methods: We contribute with a methodology based on fuzzy logic that is helpful to disentangle the main factors that determine favorable environmental conditions for vectors and diseases. Using favorability functions as fuzzy logic modelling technique and the fuzzy intersection, union and inclusion as fuzzy operators, we were able to specify the territories at biogeographical risk of dengue outbreaks in South America. Results: Our results indicate that the distribution of Ae. aegypti mostly encompasses the biogeographical framework of dengue in South America, which suggests that this species is the principal vector responsible for the geographical extent of dengue cases in the continent. Nevertheless, the intersection between the favorability for dengue cases and the union of the favorability for any of the vector species provided a comprehensive map of the biogeographical risk for dengue. Conclusions: Fuzzy logic is an appropriate conceptual and operational tool to tackle the nuances of the vector-illness biogeographical interaction. The application of fuzzy logic may be useful in decision-making by the public health authorities to prevent, control and mitigate vector-borne diseases. [ABSTRACT FROM AUTHOR]