Seasonal and temporal changes in species use of the landscape: how do they impact the inferences from multi-scale habitat modeling?

• Published in: Landscape ecology 2016-08, Vol.31 (6), p.1261-1276
• Main Authors: Mateo-Sánchez, María C., Gastón, Aitor, Ciudad, Carlos, García-Viñas, Juan I., Cuevas, Jorge, López-Leiva, César, Fernández-Landa, Alfredo, Algeet-Abarquero, Nur, Marchamalo, Miguel, Fortin, Marie-Josée, Saura, Santiago
• Format: Article
• Language: English
• Subjects: Animal populations; Bears; Biomedical and Life Sciences; Ecology; Environmental conditions; Environmental factors; Environmental Management; Habitat utilization; Habitats; Landscape Ecology; Landscape/Regional and Urban Planning; Lidar; Life Sciences; Nature Conservation; Population status; Research Article; Scale models; Seasons; Sustainable Development
• ISSN: 0921-2973; 1572-9761
• DOI: 10.1007/s10980-015-0324-z

Context Multi-scale approaches to habitat modeling have been shown to provide more accurate understanding and predictions of species-habitat associations. It remains however unexplored how spatial and temporal variations in habitat use may affect multi-scale habitat modeling. Objectives We aimed at assessing how seasonal and temporal differences in species habitat use and distribution impact operational scales, variable influence, habitat suitability spatial patterns, and performance of multi-scale models. Methods We evaluated the environmental factors driving brown bear habitat relationships in the Cantabrian Range (Spain) based on species presence records (ground observations) for the period 2000–2010, LiDAR data on forest structure, and seasonal estimates of foraging resources. We separately developed multi-scale habitat models for (i) each season (spring, summer, fall and winter) (ii) two sub-periods with different population status: 2000–2004 (with brown bear distribution restricted to the main population nuclei) and 2005–2010 (with expanding bear population and range); and (iii) the entire 2000–2010 period. Results Scales of effect remained considerably stable across seasonal and temporal variations, but not the influence of certain environmental variables. The predictive ability of multi-scale models was lower in the seasons or periods in which populations used larger areas and a broader variety of environmental conditions. Seasonal estimates of foraging resources, together with LiDAR data, appeared to improve the performance of multi-scale habitat models. Conclusions We highlight that the understanding of multi-scale behavioral responses of species to spatial patterns that continually shift over time may be essential to unravel habitat relationships and produce reliable estimates of species distributions.