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I am particularly interested in areas such as spatial ecological processes/patterns, conservation priorization of species/populations, multispecies management, understanding the impact of land use/climate change over biodiversity.

Generally the extinction is a process which began with the extirpation of populations. Probability to extirpation is spatially variable and is influenced by environmental factors. Also, some intrinsic species traits, like life history, ecological and behavior traits influence in vulnerability to extinction of the species dealing to a different probability to extinction. Identify the environmental factors and intrinsic traits which affect probability to extirpation/extinction could contribute to understand the actual species tendencies and to predict future risks. My doctoral thesis focus on identify and understand these variables assessing range dynamics and the interaction with mentioned factors and vulnerabilities. More to the point the goals are: (1) to asses the null models of range contraction, (2) study the influence of the spatial configuration in the vulnerability of species, (3) to asses the environmental patterns in range contraction, (4) to study the possible interactions between land use change and climatic change in range contractions, and (5) to explore possible bias in analysis of extinction risk. To answer this questions we will use terrestrial vertebrate species as model group, using spatial data describing process of range dynamic, databases of intrinsic traits, demographic parameters of different populations/species and different vulnerability categories like the red list.

Predicting direct and impacts of climate change and land use change over biodiversity:

Climate change and land use are the main drivers of biodiversity loss and species distribut
ion range contractions. Previous studies have 
primarily explored the direct effects of these drivers on biodiversity while ignoring the indirect effects that come through other species. Models ignoring these mechanisms are prone to erroneous predictions of how global change impacts biodiversity, which impedes our ability to make effective management decision for biodiversity conservation. Here, we focus on the brown bear (Ursus arctos), a well-studied omnivore species that has trophic interactions with many different taxa, to understand how direct and indirect impacts of climate change and land use would affect the future distribution and vulnerability of different populations across Europe. 

Invasive species

Feral goat in the Pyrinees

Human impacts over biodiversity

Predictions of the supported regression models explaining probability of extirpation of an area as a function of its distance to the historical border (Border) and its human land use (Land use) with a possible interaction of Land use and the percentage of contraction (Contraction). At the range scale, panel (a), Model Combined_2 (including the interaction) was the single supported model (Table 1). At the fragment scale both Model Combined_2 (b) and Model Combined_1 (c, no interaction) were supported. To visualize the effect of the interaction between Border and Contraction (a, b), we represent predictions at three levels of contraction: 20% in darker grey, 50% in medium dark grey, and 80% in light grey.

The contraction of a species’ distribution range, which results from the extirpation of local populations, generally precedes its extinction. Therefore, understanding drivers of range contraction is important for conservation and management. Although there are many processes that can potentially lead to local extirpation and range contraction, three main null models have been proposed: demographic, contagion, and refuge. The first two models postulate that the probability of local extirpation for a given area depends on its relative position within the range; but these models generate distinct spatial predictions because they assume either a ubiquitous (demographic) or a clinal (contagion) distribution of threats. The third model (refuge) postulates that extirpations are determined by the intensity of human impacts, leading to heterogeneous spatial predictions potentially compatible with those made by the other two null models. A few previous studies have explored the generality of some of these null models, but we present here the first comprehensive evaluation of all three models. Using descriptive indices and regression analyses we contrast the predictions made by each of the null models using empirical spatial data describing range contraction in 386 terrestrial vertebrates (mammals, birds, amphibians, and reptiles) distributed across the World. Observed contraction patterns do not consistently conform to the predictions of any of the three models, suggesting that these may not be adequate null models to evaluate range contraction dynamics among terrestrial vertebrates. Instead, our results support alternative null models that account for both relative position and intensity of human impacts. These new models provide a better multifactorial baseline to describe range contraction patterns in vertebrates. This general baseline can be used to explore how additional factors influence contraction, and ultimately extinction for particular areas or species as well as to predict future changes in light of current and new threats.



Exploring biases in species/geographical data and its 

Global distribution of terrestrial mammalian species and data availability. Panels: (a) species richness; (b) data richness; (c) coefficient of variation in the number of data entries per terrestrial mammal per cell.

influence in analysis of extinction risk

A key issue in conservation biology is to understand what species are more prone to extinction. Comparative analysis of extinction risk are a powerful method which links intrinsic, life-history species traits and extrinsic factors with vulnerability. This method use large datasets which describe the characteristics of each species. To compile these datasets requires a huge effort and it is rare a species which have all the required data for analysis. We analysed the possible taxonomic, spatial and data type biases in the database PanTHERIA and the effects in the prediction of vulnerability of these biases. Our results showed that threre are important biases in data availability, being the most studied species the larger ones and with the larger range areas, and with geographical more studied than others. We also found that these biases affected to the results of comparative analysis. We concluded that missing data are a problem to makes inferences about the vulnerability of species and that methods to fill data need to account that these bias are not random. 

Species distribution models

A newly-born Iberian wild goat in the study area.

Species distribution models are mathematical tools that correlate the presence/abundance of species in space/time with environmental variables used impacts/interactions/problems from species in the environment or in human uses and for management and conservation of species.as predictors. They have numerous applications such as test ecological hypothesis, predict current/future distributions.

After a drastic contraction in the species’ range, the Iberian wild goat Capra pyrenaica (Schinz, 1838) has recolonized semi-arid steppe areas where the availability of resources is lower than it is in the species typical habitat. There is a gap in the habitat characteristics that allow the species to survive in an environment that lacks high cliffs and rocky outcrops. We hypothesize that microhabitat characteristics allow the species to find the resources necessary for survival in atypical areas. To test that, we measured several topographic variables (slope, distance to small cliffs and elevation) as well as land use/cover variables (distance to bushes, forests, agriculture, artificial and rivers). To model the habitat in the Middle Ebro Valley, Spain, we used data from 7-yr of monitoring of the species in an averaged-model with Generalized Linear Mixed Model (GLMM-Logit). Distance to small cliffs and distance to bushes explained most of the variance in the model which reflected a fragmented potential habitat. The fragmented structure of the habitat which might act as a metapopulation system, and the spatial configuration of fragments along rivers might act as corridors that favor the dispersal should be taken in consideration in the conservation and management of the species.


Predicted distribution for the Iberian wild goat