RT info:eu-repo/semantics/article
T1 Landscape heterogeneity as a surrogate of biodiversity in mountain systems: what is the most appropriate spatial analytical unit?
A1 García Llamas, Paula
A1 Calvo Galván, María Leonor
A1 Cruz, Marcelino de la
A1 Suárez Seoane, Susana
A2 Ecologia
K1 Biología
K1 Ecología. Medio ambiente
K1 Zoología
K1 Habitat diversity
K1 Mammals
K1 Birds
K1 Reptiles
K1 Terrestrial vertebrates
K1 Watersheds
AB The estimated potential of landscape metrics as a surrogate for biodiversity is strongly dependent on the spatial analytical unit used for evaluation. We assessed the relationship between terrestrial vertebrate species richness (total and taxonomic) and structural landscape heterogeneity, testing the impact of using different spatial analytical units in three mountain systems in Spain. Landscape heterogeneity was quantified through an additive partitioning of the Shannon diversity index of landscape classes. Both landscape heterogeneity and species richness were calculated using two spatial analytical unit approaches: eco-geographic vs. arbitrary (i.e., watersheds vs. square windows of different sizes 20 × 20 km, 50 × 50 km, 100 × 100 km). We predicted species richness on the basis of landscape heterogeneity by fitting separate linear models for each spatial analytical unit approach. The main results obtained showed that landscape heterogeneity influenced terrestrial vertebrate species richness. However, the emerging relationships were dependent on the spatial analytical unit approach. The eco-geographic approach showed significant relationships between landscape heterogeneity and total and taxonomic species richness in almost all cases (except mammals). Considering the arbitrary approach, landscape heterogeneity appeared as a predictor of species richness only for mammals and breeding birds and at the coarsest spatial scales. Our results claim for further consideration of eco-geographical spatial analytical unit approaches in biodiversity studies and show that the methods of this study offer a valuable cost-effective framework for biodiversity management and spatial modeling, with potential to be adapted to national and global applications.
PB Elsevier
YR 2018
FD 2018-03-03
LK http://hdl.handle.net/10612/7435
UL http://hdl.handle.net/10612/7435
NO Ecological indicators, 2018, vol. 85
NO P. 285-294
DS BULERIA. Repositorio Institucional de la Universidad de León
RD 19-abr-2024