Transferability of environmental favourability models in geographic space: The case of the Iberian desman (Galemys pyrenaicus) in Portugal and Spain

Local niches explain coexistence in environmentally-distinct contact zones between Western Mediterranean vipers

Species' ecological niches are frequently analysed to gain insights into how anthropogenic changes affect biodiversity. Coping with these changes often involves shifts in niche expression, which can disrupt local biotic interactions. Secondary contact zones, where competition and ecological segregation commonly occur, are ideal for studying the ecological factors influencing species' niches. In this study, we investigated the effect of climate and landscape factors on the ecological niches of two viper species, Vipera aspis and Vipera latastei, across three contact zones in northern Iberia, characterized by varying levels of landscape alteration. Using niche overlap tests, ecological niche models and spatial analyses we observed local variation in the expression of the species' niches across the three contact zones, resulting from the different abiotic and biotic conditions of each area. Rather than spatial niche segregation, we observed high niche overlap, suggesting niche convergence. A pattern of asymmetrical niche variation was identified in all contact zones, driven by species' climatic tolerances and the environmental conditions of each area. V. aspis generally exhibited a wider niche, except in the southernmost zone where the pure Mediterranean climate favored V. latastei. Human-induced landscape changes intensified niche asymmetry, by favoring the most generalist V. aspis over the specialist V. latastei, increasing habitat overlap, and likely competition. This study presents a comprehensive analysis of niche expression at range margins, anticipating a heightened impact of landscape changes in V. latastei. The methodological framework implemented here, and our findings, hold significant relevance for biodiversity management and conservation in human-impacted areas.

Shrew Communities in Mediterranean Agro-Ecosystems of Central Greece: Associations with Crop Types, Land Uses, and Soil Parameters

Shrew communities play a crucial role in a diverse range of natural, urban, and agricultural ecosystems. We used Barn owl diet analysis as the ideal proxy to assess small-mammal distribution patterns on large spatial scales. More than 10,000 pellets were analyzed from Thessaly, the largest agricultural prefecture located in central Greece. A total of more than 29,000 prey items were identified, one of the largest datasets used in similar analyses in Europe. Three discrete shrew species were present in Thessaly agricultural plains, central Greece (Güldenstädt's shrew Crocidura gueldenstaedtii, Bi-coloured shrew Crocidura leucodon, and Pygmy white-toothed shrew Suncus etruscus), which comprised a total of 7452 shrews, representing 25.64% of the total small-mammals' dataset. C. gueldenstaedtii and S. etruscus demonstrated strong associations with heavy argillaceous-clay soils and Vertisol soil types, whereas S. etruscus was also associated with non-irrigated land and non-intensive cultivated plots. C. leucodon demonstrated no significant associations to any environmental gradient and demonstrated habitat plasticity, most possibly shaped by existing resources and competition. Our study highlights the important insights gained from Barn owl diet analysis in respect of small-mammal assemblages on broad geographical scales, and the inclusion of soil parameters as drivers of habitat suitability and distribution patterns for small-mammal responses.

Distribution model transferability for a wide-ranging species, the Gray Wolf

Using existing data can be a reliable and cost-effective way to predict species distributions, and particularly useful for recovering or expanding species. We developed a current gray wolf (Canis lupus) distribution model for the western Great Lakes region, USA, and evaluated the spatial transferability of single-state models to the region. This study is the first assessment of transferability in a wide-ranging carnivore, as well as one of few developed for large spatial extents. We collected 3500 wolf locations from winter surveys in Minnesota (2017–2019), Wisconsin (2019–2020), and Michigan (2017–2020). We included 10 variables: proportion of natural cover, pastures, and crops; distance to natural cover, agriculture, developed land, and water; major and minor road density; and snowfall (1-km res.). We created a regional ensemble distribution by weight-averaging eight models based on their performance. We also developed single-state models, and estimated spatial transferability using two approaches: state cross-validation and extrapolation. We assessed performance by quantifying correlations, receiver operating characteristic curves (ROC), sensitivities, and two niche similarity indices. The regional area estimated to be most suitable for wolves during winter (threshold = maximum sensitivity/specificity) was 106,465 km² (MN = 48,083 km², WI = 27,757 km², MI = 30,625 km²) and correctly predicted 88% of wolf locations analyzed. Increasing natural cover and distance to crops were consistently important for determining regional and single-state wolf distribution. Extrapolation (vs. cross-validation) produced results with the greatest performance metrics, and were most similar to the regional model, yet good internal performance was unrelated to greater extrapolation performance. Factors influencing species distributions are scale-dependent and can vary across areas due to behavioral plasticity. When extending inferences beyond the current occurrence of individuals, assessing variation in ecology such as habitat selection, as well as methodological factors including model performance, will be critical to avoid poor scientific interpretations and develop effective conservation applications. In particular, accurate distribution models for recovering or recovered carnivores can be used to develop plans for habitat management, quantify potential of unoccupied habitat, assess connectivity modeling, and mitigate conflict, facilitating long-term species persistence.

Guidelines for model adaptation: A study of the transferability of a general seagrass ecosystem Dynamic Bayesian Networks model

In general, it is not feasible to collect enough empirical data to capture the entire range of processes that define a complex system, either intrinsically or when viewing the system from a different geographical or temporal perspective. In this context, an alternative approach is to consider model transferability, which is the act of translating a model built for one environment to another less well-known situation. Model transferability and adaptability may be extremely beneficial-approaches that aid in the reuse and adaption of models, particularly for sites with limited data, would benefit from widespread model uptake. Besides the reduced effort required to develop a model, data collection can be simplified when transferring a model to a different application context. The research presented in this paper focused on a case study to identify and implement guidelines for model adaptation. Our study adapted a general Dynamic Bayesian Networks (DBN) of a seagrass ecosystem to a new location where nodes were similar, but the conditional probability tables varied. We focused on two species of seagrass (Zostera noltei and Zostera marina) located in Arcachon Bay, France. Expert knowledge was used to complement peer-reviewed literature to identify which components needed adjustment including parameterization and quantification of the model and desired outcomes. We adopted both linguistic labels and scenario-based elicitation to elicit from experts the conditional probabilities used to quantify the DBN. Following the proposed guidelines, the model structure of the general DBN was retained, but the conditional probability tables were adapted for nodes that characterized the growth dynamics in Zostera spp. population located in Arcachon Bay, as well as the seasonal variation on their reproduction. Particular attention was paid to the light variable as it is a crucial driver of growth and physiology for seagrasses. Our guidelines provide a way to adapt a general DBN to specific ecosystems to maximize model reuse and minimize re-development effort. Especially important from a transferability perspective are guidelines for ecosystems with limited data, and how simulation and prior predictive approaches can be used in these contexts.

Determinants of habitat suitability models transferability across geographically disjunct populations: Insights from Vipera ursinii urs inii

Transferability of habitat suitability models (HSMs), essential to accurately predict outside calibration conditions, has been seldom investigated at intraspecific level. We targeted Vipera ursinii ursinii, a meadow viper from southeastern France and central Italy, to assess determinants of transferability among geographically disjunct populations. We fitted HSMs upon occurrences of the Italian and French populations separately, as well as on the combined occurrence dataset. Internal transferability of HSMs, on spatially independent test data drawn from the calibration region, and their external transferability on the geographically disjunct populations were evaluated according to (a) use of full or spatially rarefied presence datasets; (b) ecology-driven or statistics-driven filtering of predictors; (c) modeling algorithm, testing generalized additive models and gradient boosting models; and (d) multivariate environmental novelty within test data. Niche overlap between French and Italian populations was also tested. Niche overlap was low, but niche divergence between the two populations' clusters was not corroborated. Nonetheless, wider niche breadth and heterogeneity of background environmental conditions characterizing the French populations led to low intercluster transferability. Although models fitted on the combined datasets did not attain consistently higher internal transferability than those separately fitted for the French and Italian populations, ensemble projection from the HSMs fitted on the joint occurrences produced more consistent suitability predictions across the full range of V. u. ursinii. Spatial thinning of occurrences ameliorated internal transferability but did not affect external transferability. The two approaches to predictors filtering did not differ in transferability of the respective HSMs but led to discrepant estimated environment-occurrence relationships and spatial predictions, while the two algorithms attained different relative rankings depending on the considered prediction task. Multivariate novelty of projection sites was negatively correlated to both internal transferability and external transferability. Our findings clarify issues researchers should keep in mind when using HSMs to get predictions across geographically disjunct populations.

WOODIV, a database of occurrences, functional traits, and phylogenetic data for all Euro-Mediterranean trees

Trees play a key role in the structure and function of many ecosystems worldwide. In the Mediterranean Basin, forests cover approximately 22% of the total land area hosting a large number of endemics (46 species). Despite its particularities and vulnerability, the biodiversity of Mediterranean trees is not well known at the taxonomic, spatial, functional, and genetic levels required for conservation applications. The WOODIV database fills this gap by providing reliable occurrences, four functional traits (plant height, seed mass, wood density, and specific leaf area), and sequences from three DNA-regions (rbcL, matK, and trnH-psbA), together with modelled occurrences and a phylogeny for all 210 Euro-Mediterranean tree species. We compiled, homogenized, and verified occurrence data from sparse datasets and collated them on an INSPIRE-compliant 10 × 10 km grid. We also gathered functional trait and genetic data, filling existing gaps where possible. The WOODIV database can benefit macroecological studies in the fields of conservation, biogeography, and community ecology.

Improved prediction of Canada lynx distribution through regional model transferability and data efficiency

The application of species distribution models (SDMs) to areas outside of where a model was created allows informed decisions across large spatial scales, yet transferability remains a challenge in ecological modeling. We examined how regional variation in animal-environment relationships influenced model transferability for Canada lynx (Lynx canadensis), with an additional conservation aim of modeling lynx habitat across the northwestern United States. Simultaneously, we explored the effect of sample size from GPS data on SDM model performance and transferability. We used data from three geographically distinct Canada lynx populations in Washington (n = 17 individuals), Montana (n = 66), and Wyoming (n = 10) from 1996 to 2015. We assessed regional variation in lynx-environment relationships between these three populations using principal components analysis (PCA). We used ensemble modeling to develop SDMs for each population and all populations combined and assessed model prediction and transferability for each model scenario using withheld data and an extensive independent dataset (n = 650). Finally, we examined GPS data efficiency by testing models created with sample sizes of 5%-100% of the original datasets. PCA results indicated some differences in environmental characteristics between populations; models created from individual populations showed differential transferability based on the populations' similarity in PCA space. Despite population differences, a single model created from all populations performed as well, or better, than each individual population. Model performance was mostly insensitive to GPS sample size, with a plateau in predictive ability reached at ~30% of the total GPS dataset when initial sample size was large. Based on these results, we generated well-validated spatial predictions of Canada lynx distribution across a large portion of the species' southern range, with precipitation and temperature the primary environmental predictors in the model. We also demonstrated substantial redundancy in our large GPS dataset, with predictive performance insensitive to sample sizes above 30% of the original.

Local habitat preferences of a semi-aquatic mammal, the Pyrenean desman Galemys pyrenaicus

To date, the large-scale distribution of the endangered Pyrenean desman, Galemys pyrenaicus, has been related to various abiotic factors (e.g. riverbed and riverbank characteristics, hydrology, topography, climate). However, none could fully explain the recent observed range contraction of the species, suggesting the influence of other drivers. In this study, the potential effect of some unexplored variables on the Pyrenean desman presence was investigated at the local scale (i.e. stream reaches) in the French Pyrenees. They described not only the riverbed, riverbanks, water chemistry, topography and pedology but also the presence of potential interacting species. Generalised linear models were implemented to select the best drivers of the Pyrenean desman presence. Our results stressed the relevance of considering human impacts at the riverbed scale, river narrowing and water chemistry to explain the local distribution of the Pyrenean desman. The presence of two potential competitors, the Eurasian water shrew Neomys fodiens and the dipper Cinclus cinclus, was also highly correlated to the species presence in stream reaches. This suggests that all three species may use the same resources within streams, which could be a potential source of competitive interactions. This study not only highlights the importance of maintaining the riverbed integrity for the Pyrenean desman but also stresses the need to assess the extent to which biotic interactions may affect its distribution in order to understand its current decline.

Non-native freshwater fauna in Portugal: A review

We present the most updated list of non-native freshwater fauna established in Portugal, including the Azores and Madeira archipelagos. This list includes 67 species at national level but corresponds to 84 species records, of which 53 are in the mainland, 23 in the Azores and 8 in Madeira archipelagos. We also discuss the progression of the cumulative number of introductions since 1800 and identify the most probable vectors of introduction, main taxonomic groups and their regions of origin. Furthermore, we review the existing knowledge about ecological and economic impacts, invasion risk and potential distribution of invaders, under present and future climatic conditions, and the applied management actions, including the production of legislation. Along the 20th century the number of successful introductions increased at an approximate rate of two new species per decade until the beginning of 1970s. Since then, this rate increased to about 14 new species per decade. These introductions were mainly a result of fisheries, as contaminants or for ornamental purposes. Fish and mollusks are the taxonomic groups with more established species, representing more than half of the total. Most species (>70%) are native from other regions of Europe and North America. Studies about ecological or socioeconomic impacts are more common for fish, crustaceans and mollusks. Impacts for most amphibians, reptiles and mammals are not thoroughly studied. A few studies on the impacts and management actions of health-threatening mosquitoes are also available. The potential distribution in the Portuguese territory was modelled for 26 species. Only a minority of these models provides projections of distributions under scenarios of future climate change. A comparison of the Portuguese and EU legislation shows large discrepancies in the invasive species lists. Using the EU list and a ranking procedure for the national context, we identify freshwater species of high national concern for which actions are urgently needed.

Wild boar mapping using population-density statistics: From polygons to high resolution raster maps

The wild boar is an important crop raider as well as a reservoir and agent of spread of swine diseases. Due to increasing densities and expanding ranges worldwide, the related economic losses in livestock and agricultural sectors are significant and on the rise. Its management and control would strongly benefit from accurate and detailed spatial information on species distribution and abundance, which are often available only for small areas. Data are commonly available at aggregated administrative units with little or no information about the distribution of the species within the unit. In this paper, a four-step geostatistical downscaling approach is presented and used to disaggregate wild boar population density statistics from administrative units of different shape and size (polygons) to 5 km resolution raster maps by incorporating auxiliary fine scale environmental variables. 1) First a stratification method was used to define homogeneous bioclimatic regions for the analysis; 2) Under a geostatistical framework, the wild boar densities at administrative units, i.e. subnational areas, were decomposed into trend and residual components for each bioclimatic region. Quantitative relationships between wild boar data and environmental variables were estimated through multiple regression and used to derive trend components at 5 km spatial resolution. Next, the residual components (i.e., the differences between the trend components and the original wild boar data at administrative units) were downscaled at 5 km resolution using area-to-point kriging. The trend and residual components obtained at 5 km resolution were finally added to generate fine scale wild boar estimates for each bioclimatic region. 3) These maps were then mosaicked to produce a final output map of predicted wild boar densities across most of Eurasia. 4) Model accuracy was assessed at each different step using input as well as independent data. We discuss advantages and limits of the method and its potential application in animal health.

Species Distributions, Quantum Theory, and the Enhancement of Biodiversity Measures

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, organisms may 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. [Biogeography; favorability; physics; predictability; probability; species occurrence; uncertainty; wavefunction.

Changes in potential mammal diversity in national parks and their implications for conservation

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.

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.

Can Recent Global Changes Explain the Dramatic Range Contraction of an Endangered Semi-Aquatic Mammal Species in the French Pyrenees?

Species distribution models (SDMs) are the main tool to predict global change impacts on species ranges. Climate change alone is frequently considered, but in freshwater ecosystems, hydrology is a key driver of the ecology of aquatic species. At large scale, hydrology is however rarely accounted for, owing to the lack of detailed stream flow data. In this study, we developed an integrated modelling approach to simulate stream flow using the hydrological Soil and Water Assessment Tool (SWAT). Simulated stream flow was subsequently included as an input variable in SDMs along with topographic, hydrographic, climatic and land-cover descriptors. SDMs were applied to two temporally-distinct surveys of the distribution of the endangered Pyrenean desman (Galemys pyrenaicus) in the French Pyrenees: a historical one conducted from 1985 to 1992 and a current one carried out between 2011 and 2013. The model calibrated on historical data was also forecasted onto the current period to assess its ability to describe the distributional change of the Pyrenean desman that has been modelled in the recent years. First, we found that hydrological and climatic variables were the ones influencing the most the distribution of this species for both periods, emphasizing the importance of taking into account hydrology when SDMs are applied to aquatic species. Secondly, our results highlighted a strong range contraction of the Pyrenean desman in the French Pyrenees over the last 25 years. Given that this range contraction was under-estimated when the historical model was forecasted onto current conditions, this finding suggests that other drivers may be interacting with climate, hydrology and land-use changes. Our results imply major concerns for the conservation of this endemic semi-aquatic mammal since changes in climate and hydrology are expected to become more intense in the future.

Distribution and Numbers of Pygmies in Central African Forests

Pygmy populations occupy a vast territory extending west-to-east along the central African belt from the Congo Basin to Lake Victoria. However, their numbers and actual distribution is not known precisely. Here, we undertake this task by using locational data and population sizes for an unprecedented number of known Pygmy camps and settlements (n = 654) in five of the nine countries where currently distributed. With these data we develop spatial distribution models based on the favourability function, which distinguish areas with favourable environmental conditions from those less suitable for Pygmy presence. Highly favourable areas were significantly explained by presence of tropical forests, and by lower human pressure variables. For documented Pygmy settlements, we use the relationship between observed population sizes and predicted favourability values to estimate the total Pygmy population throughout Central Africa. We estimate that around 920,000 Pygmies (over 60% in DRC) is possible within favourable forest areas in Central Africa. We argue that fragmentation of the existing Pygmy populations, alongside pressure from extractive industries and sometimes conflict with conservation areas, endanger their future. There is an urgent need to inform policies that can mitigate against future external threats to these indigenous peoples’ culture and lifestyles.

Past, present and future distributions of an Iberian Endemic, Lepus granatensis: ecological and evolutionary clues from species distribution models

The application of species distribution models (SDMs) in ecology and conservation biology is increasing and assuming an important role, mainly because they can be used to hindcast past and predict current and future species distributions. However, the accuracy of SDMs depends on the quality of the data and on appropriate theoretical frameworks. In this study, comprehensive data on the current distribution of the Iberian hare (Lepus granatensis) were used to i) determine the species' ecogeographical constraints, ii) hindcast a climatic model for the last glacial maximum (LGM), relating it to inferences derived from molecular studies, and iii) calibrate a model to assess the species future distribution trends (up to 2080). Our results showed that the climatic factor (in its pure effect and when it is combined with the land-cover factor) is the most important descriptor of the current distribution of the Iberian hare. In addition, the model's output was a reliable index of the local probability of species occurrence, which is a valuable tool to guide species management decisions and conservation planning. Climatic potential obtained for the LGM was combined with molecular data and the results suggest that several glacial refugia may have existed for the species within the major Iberian refugium. Finally, a high probability of occurrence of the Iberian hare in the current species range and a northward expansion were predicted for future. Given its current environmental envelope and evolutionary history, we discuss the macroecology of the Iberian hare and its sensitivity to climate change.

Favourability: concept, distinctive characteristics and potential usefulness

The idea of analysing the general favourability for the occurrence of an event was presented in 2006 through a mathematical function. However, even when favourability has been used in species distribution modelling, the conceptual framework of this function is not yet well perceived among many researchers. The present paper is conceived for providing a wider and more in-depth presentation of the idea of favourability; concretely, we aimed to clarify both the concept and the main distinctive characteristics of the favourability function, especially in relation to probability and suitability, the most common outputs in species distribution modelling. As the capabilities of the favourability function go beyond species distribution modelling, we also illustrate its usefulness for different research disciplines for which this function remains unknown. In particular, we stressed that the favourability function has potential to be applied in all the cases where the probability of occurrence of an event is analysed, such as, for example, habitat selection or epidemiological studies.

Applying fuzzy logic to comparative distribution modelling: a case study with two sympatric amphibians

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.

Modeling rare species distribution at the edge: the case for the vulnerable endemic Pyrenean desman in France

The endemic Pyrenean Desman (Galemys pyrenaicus) is an elusive, rare, and vulnerable species declining over its entire and narrow range (Spain, Portugal, France, and Andorra). The principal set of conservation measures in France is a 5-years National Action Plan based on 25 conservation actions. Priority is given to update its present distribution and develop tools for predictive distribution models. We aim at building the first species distribution model and map for the northern edge of the range of the Desman and confronting the outputs of the model to target conservation efforts in the context of environmental change. Contrasting to former comparable studies, we derive a simpler model emphasizing the importance of factors linked to precipitation and not to the temperature. If temperature is one of the climate change key factors, depicted shrinkage in Desman distribution could be lower or null at the northern (French) edge suggesting thus a major role for this northern population in terms of conservation of the species. Finally, we question the applied issue of temporal and spatial transferability for such environmental favourability models when it is made at the edge of the distribution range.

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.

Use of coarse-resolution models of species' distributions to guide local conservation inferences

Distribution models are used increasingly for species conservation assessments over extensive areas, but the spatial resolution of the modeled data and, consequently, of the predictions generated directly from these models are usually too coarse for local conservation applications. Comprehensive distribution data at finer spatial resolution, however, require a level of sampling that is impractical for most species and regions. Models can be downscaled to predict distribution at finer resolutions, but this increases uncertainty because the predictive ability of models is not necessarily consistent beyond their original scale. We analyzed the performance of downscaled, previously published models of environmental favorability (a generalized linear modeling technique) for a restricted endemic insectivore, the Iberian desman (Galemys pyrenaicus), and a more widespread carnivore, the Eurasian otter (Lutra lutra), in the Iberian Peninsula. The models, built from presence-absence data at 10 × 10 km resolution, were extrapolated to a resolution 100 times finer (1 × 1 km). We compared downscaled predictions of environmental quality for the two species with published data on local observations and on important conservation sites proposed by experts. Predictions were significantly related to observed presence or absence of species and to expert selection of sampling sites and important conservation sites. Our results suggest the potential usefulness of downscaled projections of environmental quality as a proxy for expensive and time-consuming field studies when the field studies are not feasible. This method may be valid for other similar species if coarse-resolution distribution data are available to define high-quality areas at a scale that is practical for the application of concrete conservation measures.