Endangered Species Constrained by Natural and Human Factors: the Case of Brown Bears in Northern Spain

Abstract

We developed a conceptual framework for classifying habitat quality that requires the construction of separate habitat models for each key demographic feature; the framework can be applied when the factors that determine different demographic processes differ substantially. For example, survival of large carnivores is mainly determined by human‐induced mortality, whereas nutritional condition determines reproductive rate. Hence, a two‐dimensional habitat model built for reproduction and survival yields five hypothetical habitat categories: matrix, with no reproduction and/or very high mortality; sink, with low reproduction and high mortality; refuge, with low reproduction and low mortality; attractive sink, with high reproduction and high mortality; and source, with high reproduction and low mortality. We applied this framework to two endangered brown bear ( Ursus arctos ) populations in the Cantabrian Mountains, Spain. Our aim was to generate working hypotheses about the quality and spatial arrangement of bear habitat to analyze the present conditions of the different population nuclei and to facilitate identification of core areas of high conservation value, conflictive areas, or areas with unoccupied potential habitat. We used a geographic information system and two spatial long‐term data sets on presence and reproduction and performed logistic regressions for building a two‐dimensional model. The analysis reveals that both populations exist under different suboptimal conditions: the eastern population mainly occupies areas of suboptimal natural habitat and relatively low human impact, whereas the western population is located mainly in areas with high human impact but otherwise good natural quality. To test hypotheses about demographic features of the obtained habitat categories, we classified data on historic extinction in northern Spain ( fourteenth to nineteenth centuries ) with the two‐dimensional model. Extinction probabilities within each habitat category confirmed the hypotheses: most extinctions occurred in matrix habitat, and the fewest occurred in source habitat.

Estimating effective landscape distances and movement corridors: comparison of habitat and genetic data

“…Brown bear is highly dependent on large landscapes with low human-footprint and large extents of forest cover (Clevenger et al 1997, Apps et al 2004, Mateo-Sánchez et al 2014a. The brown bear population in the Cantabrian Range suffered a dramatic decline in the last several centuries as a result of human persecution and progressive loss and fragmentation of its habitat (Naves et al 2003). We considered this population highly suited for this analysis for the following reasons.…”

Habitat selection models for European wildcat conservation

“…Habitat models based on presence-absence data are the most standard approach to habitat modelling (e.g. Schadt et al, 2002b;Woolf et al, 2002;Naves et al, 2003;Seoane et al, 2003;Niedzialkowska et al, 2006). These models are often based on coarse-grained landscape and species information allowing coarse habitat inferences and predictions, but they may overlook biological details important for species conservation.…”

Do well-connected landscapes promote road-related mortality?

“…If the objective is a more accurate assessment of landscape constraints on species movement and mortality risk, we argue that studies that account for the effects of both variables are more meaningful. Sunquist and Sunquist (2001), Crooks (2002), andMcRae et al (2005) have shown that some endangered mammalian carnivores are particularly vulnerable to habitat fragmentation and road network expansion and are facing threats of local extinction in some regions (Ferreras 2001;Naves et al 2003). Although the stone marten is currently a widespread and common carnivore, recent research documented that they are particularly sensitive to forest fragmentation in cork oak woodlands, hereafter called montado (Virgós and García 2002;Santos-Reis et al 2004;Mortelliti and Boitani 2008), and are vulnerable to traffic (Grilo et al 2009).…”