Use of coarse-resolution models of species' distributions to guide local conservation inferences.
Distribution models are used increasingly for species conservation assessments over extensive areas, but the spatial resolution of the modeled data and, consequently, of the predictions generated directly from these models are usually too coarse for local conservation applications. Comprehensive distribution data at finer spatial resolution, however, require a level of sampling that is impractical for most species and regions. Models can be downscaled to predict distribution at finer resolutions, but this increases uncertainty because the predictive ability of models is not necessarily consistent beyond their original scale. We analyzed the performance of downscaled, previously published models of environmental favorability (a generalized linear modeling technique) for a restricted endemic insectivore, the Iberian desman (Galemys pyrenaicus), and a more widespread carnivore, the Eurasian otter (Lutra lutra), in the Iberian Peninsula. The models, built from presence-absence data at 10 × 10 km resolution, were extrapolated to a resolution 100 times finer (1 × 1 km). We compared downscaled predictions of environmental quality for the two species with published data on local observations and on important conservation sites proposed by experts. Predictions were significantly related to observed presence or absence of species and to expert selection of sampling sites and important conservation sites. Our results suggest the potential usefulness of downscaled projections of environmental quality as a proxy for expensive and time-consuming field studies when the field studies are not feasible. This method may be valid for other similar species if coarse-resolution distribution data are available to define high-quality areas at a scale that is practical for the application of concrete conservation measures.
Barbosa
A Márcia
AM
CIBIO, University of Évora, Largo dos Colegiais, 7004-516 Évora, Portugal. barbosa@uevora.pt
Real
Raimundo
R
Vargas
J Mario
JM
D000818:Animals; D003247:Conservation of Natural Resources / Q000379:methods*; D003710:Demography; D005843:Geography; D016015:Logistic Models; D008954:Models, Biological; D010041:Otters / Q000502:physiology*; D011174:Portugal; D013030:Spain