Landscape connectivity estimates are affected by spatial resolution, habitat seasonality and population trends

Connectivity assessments and corridor delineation are key contributions to landscape management and biodiversity conservation. We examined the influence of three potentially crucial factors on the results of connectivity analyses, using the two subpopulations of the endangered brown bear in the Cantabrian Range (NW Spain) as a case study. First, we evaluated the spatial resolution of vegetation data, using three types of datasets ranging from coarse resolution land-cover maps to high-resolution LiDAR data. Second, the seasonal variation in the distribution of habitat resources and in the species use of the landscape. Third, multi-annual periods with different population status. The estimates of subpopulation isolation (effective distances) and the trajectory of the identified corridors were substantially influenced by (i) the spatial resolution of vegetation data; the more robust results were obtained when incorporating fine-scale LiDAR data; (ii) the season over which species occurrence data and landscape characteristics were considered; the spring mating season yielded higher connectivity estimates than any other season; (iii) the status of the populations, with higher landscape connectivity estimated for expanding populations. Our study reveals that the use of coarse-resolution data may underestimate the resistance of the non-habitat landscape matrix to species movements. The use of year-round estimates of habitat connectivity may miss the key seasonal temporal windows for species movements. Landscape resistance may be overestimated when data from periods with declining or restricted populations are used. We recommend carefully disentangling the effects of demography and landscape heterogeneity on realized species dispersal movements for improving the insights from connectivity modelling.