Metapopulation Patterns of Iberian Butterflies Revealed by Fuzzy Logic.

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.

A large-scale assessment of European rabbit damage to agriculture in Spain.

BACKGROUND: Numerous small and medium-sized mammal pests cause widespread and economically significant damage to crops all over the globe. However, most research on pest species has focused on accounts of the level of damage. There are fewer studies concentrating on the description of crop damage caused by pests at large geographical scales, or on analysis of the ecological and anthropogenic factors correlated with these observed patterns. We investigated the relationship between agricultural damage by the European rabbit (Oryctolagus cuniculus) and environmental and anthropogenic variables throughout Spain. RESULTS: Rabbit damage was mainly concentrated within the central-southern regions of Spain. We found that rabbit damage increased significantly between the early 2000s and 2013. Greater losses were typical of those areas where farming dominated and natural vegetation was scarce, where main railways and highways were present, and where environmental conditions were generally favourable for rabbit populations to proliferate. CONCLUSION: From our analysis, we suggest that roads and railway lines act as potential corridors along which rabbits can spread. The recent increase in Spain of such infrastructure may explain the rise in rabbit damage reported in this study. Our approach is valuable as a method for assessing drivers of wildlife pest damage at large spatial scales, and can be used to propose methods to reduce human - wildlife conflict. © 2017 Society of Chemical Industry.

Differences between Pygmy and Non-Pygmy Hunting in Congo Basin Forests.

We use data on game harvest from 60 Pygmy and non-Pygmy settlements in the Congo Basin forests to examine whether hunting patterns and prey profiles differ between the two hunter groups. For each group, we calculate hunted animal numbers and biomass available per inhabitant, P, per year (harvest rates) and killed per hunter, H, per year (extraction rates). We assess the impact of hunting of both hunter groups from estimates of numbers and biomass of prey species killed per square kilometre, and by examining the proportion of hunted taxa of low, medium and high population growth rates as a measure of their vulnerability to overhunting. We then map harvested biomass (kg-1P-1Yr-1) of bushmeat by Pygmies and non-Pygmies throughout the Congo Basin. Hunting patterns differ between Pygmies and non-Pygmies; Pygmies take larger and different prey and non-Pygmies sell more for profit. We show that non-Pygmies have a potentially more severe impact on prey populations than Pygmies. This is because non-Pygmies hunt a wider range of species, and twice as many animals are taken per square kilometre. Moreover, in non-Pygmy settlements there was a larger proportion of game taken of low population growth rate. Our harvest map shows that the non-Pygmy population may be responsible for 27 times more animals harvested than the Pygmy population. Such differences indicate that the intense competition that may arise from the more widespread commercial hunting by non-Pygmies is a far more important constraint and source of conflict than are protected areas.

An approach to consider behavioral plasticity as a source of uncertainty when forecasting species' response to climate change.

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.

Integrating sustainable hunting in biodiversity protection in Central Africa: hot spots, weak spots, and strong spots.

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

Mapping hotspots of threatened species traded in bushmeat markets in the Cross-Sanaga rivers region.

Bushmeat markets exist in many countries in West and Central Africa, and data on species sold can be used to detect patterns of wildlife trade in a region. We surveyed 89 markets within the Cross-Sanaga rivers region, West Africa. In each market, we counted the number of carcasses of each taxon sold. During a 6-month period (7594 market days), 44 mammal species were traded. Thirteen species were on the International Union for Conservation of Nature (IUCN) Red List or protected under national legislation, and at least 1 threatened species was traded in 88 of the 89 markets. We used these data to identify market groups that traded similar species assemblages. Using cluster analyses, we detected 8 market groups that were also geographically distinct. Market groups differed in the diversity of species, evenness of species, and dominant, prevalent, and characteristic species traded. We mapped the distribution of number of threatened species traded across the study region. Most threatened species were sold in markets nearest 2 national parks, Korup National Park in Cameroon and Cross River in Nigeria. To assess whether the threatened-species trade hotspots coincided with the known ranges of these species, we mapped the overlap of all threatened species traded. Markets selling more threatened species overlapped with those regions that had higher numbers of these. Our study can provide wildlife managers in the region with better tools to discern zones within which to focus policing efforts and reduce threats to species that are threatened by the bushmeat trade.

Updating known distribution models for forecasting climate change impact on endangered species.

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

A broad assessment of factors determining Culicoides imicola abundance: modelling the present and forecasting its future in climate change scenarios.

Bluetongue (BT) is still present in Europe and the introduction of new serotypes from endemic areas in the African continent is a possible threat. Culicoides imicola remains one of the most relevant BT vectors in Spain and research on the environmental determinants driving its life cycle is key to preventing and controlling BT. Our aim was to improve our understanding of the biotic and abiotic determinants of C. imicola by modelling its present abundance, studying the spatial pattern of predicted abundance in relation to BT outbreaks, and investigating how the predicted current distribution and abundance patterns might change under future (2011-2040) scenarios of climate change according to the Intergovernmental Panel on Climate Change. C. imicola abundance data from the bluetongue national surveillance programme were modelled with spatial, topoclimatic, host and soil factors. The influence of these factors was further assessed by variation partitioning procedures. The predicted abundance of C. imicola was also projected to a future period. Variation partitioning demonstrated that the pure effect of host and topoclimate factors explained a high percentage (>80%) of the variation. The pure effect of soil followed in importance in explaining the abundance of C. imicola. A close link was confirmed between C. imicola abundance and BT outbreaks. To the best of our knowledge, this study is the first to consider wild and domestic hosts in predictive modelling for an arthropod vector. The main findings regarding the near future show that there is no evidence to suggest that there will be an important increase in the distribution range of C. imicola; this contrasts with an expected increase in abundance in the areas where it is already present in mainland Spain. What may be expected regarding the future scenario for orbiviruses in mainland Spain, is that higher predicted C. imicola abundance may significantly change the rate of transmission of orbiviruses.

Long-term changes in game species over a long period of transformation in the Iberian Mediterranean landscape.

Agricultural change has transformed large areas of traditional farming landscapes, leading to important changes in the species community assemblages in most European countries. We suspect that the drastic changes in land-use that have occurred in Andalusia (southern Spain) over recent decades, may have affected the distribution and abundance of game species in this region. This article compares the distribution of the main game species in Andalusia during the 1960s and 1990s, using data from maps available from the Mainland Spanish Fish, Game and National Parks Service and from recent datasets on hunting yield distributions, respectively. Big-game and small-game species were significantly segregated in southern Spain during the 1990s, as two clearly independent chorotypes (groups of species whose abundances are similarly distributed) were obtained from the classification analysis. In contrast, big-game and small-game species were not significantly segregated several decades ago, when there was only one chorotype consisting of small-game species and wild boar. The other three ungulates did not constitute a significant chorotype, as they showed positive correlations with some species in the group mentioned above. These changes seem to be a consequence of the transformations that have occurred in the Iberian Mediterranean landscape over the last few decades. The abandoning of traditional activities, and the consequent formation of dense scrubland and woodland, has led to an expansion of big-game species, and a decrease of small-game species in mountain areas. Moreover, agricultural intensification has apparently depleted small-game species populations in some agricultural areas. On the other hand, the increasingly intensive hunting management could be artificially boosting this segregation between small-game and big-game species. Our results suggest that the conservation and regeneration of traditional agricultural landscapes (like those predominating in the 1960s) should be a priority for the conservation of small-game species.