Identifying breeding habitat for the Iberian lynx: inferences from a fine-scaled spatial analysis

Empirical landscape habitat models are valuable tools for addressing species conser vation issues in heterogeneous landscapes. These have been particularly useful for animal populations requiring extensive areas, like large mammalian carnivores. Although models are scale-dependent, they are often based exclusively on coarse-grained information on landscape structure and species distribution. However, accurate discrimination and qual- ity assessment of breeding habitats may require more detailed information on both indi- viduals’ habitat use and landscape patterns. Here, we modeled breeding habitat for the Iberian lynx (Lynx pardinus), an endangered specialist of Mediterranean native ecosystems, in a human-dominated landscape. For this, we used radiotelemetr y data on breeding individuals and fine-grained landscape variables obtained over an areal extent encompassing an entire lynx metapopulation. In addition, we restricted the study domain to areas of potential presence within this extent based on previous habitat analyses. This fine-scale landscape analysis and design aimed to test wheth- er it was possible to obtain detailed inferences on breeding habitat distribution and quality within more coarsely defined habitats that only indicate where the species can be found. Landscape composition factors (i.e., fine-grain variables of landscape pattern within ter- ritories) and context factors (variables on geographical location of territories) were com- bined in different candidate habitat models. These reflected various hypotheses involving territor y presence and size, including vegetation structure characteristics, landscape het- erogeneity and complexity, favorable prey habitat, and human disturbance. The best ap- proximating model for territor y presence included only one landscape composition variable, namely, density of ecotones between scrubland and pastureland, which favored presence. For this model, classification accuracy was >80% in 94% of cross-validation tests per- formed. The best approximating model for territor y size explained 65% of the variation in size and included also density of ecotones, plus mean coverage of tall shrubs within ter- ritories; both correlated negatively with size. We show how these predictors are also related to prey density and suggest that this low-hierarchical-level relationship between the prey and patterns of the landscape can be interpreted as a likely mechanism explaining breeding habitat distribution and quality at a higher level. Our approach shows the potential of fine- scale landscape analysis to understand patterns of breeder abundance, and to better manage population viability of threatened species in human-populated areas.

Peer reviewed