Remotely Sensed Variables of Ecosystem Functioning Support Robust Predictions of Abundance Patterns for Rare Species

• Tipo: Artigo em Revista Científica Internacional
• Data: 2019

Autores

Arenas Castro, S (Autor) Outra; Regos, A (Autor) Outra; Goncalves, JF (Autor) Outra; Alcaraz Segura, D (Autor) Outra; Joao Honrado (Autor) FCUP

Revista

Título: Remote Sensing

Vol. 11

Página Final: 2086

ISSN: 2072-4292

Editora: MDPI

Indexação

ISI Web of Knowledge - 25 Citações

Scopus - 27 Citações

Outras Informações

ID Authenticus: P-00R-3VD

DOI: 10.3390/rs11182086

Abstract (EN): Global environmental changes are affecting both the distribution and abundance of species at an unprecedented rate. To assess these effects, species distribution models (SDMs) have been greatly developed over the last decades, while species abundance models (SAMs) have generally received less attention even though these models provide essential information for conservation management. With population abundance defined as an essential biodiversity variable (EBV), SAMs could offer spatially explicit predictions of species abundance across space and time. Satellite-derived ecosystem functioning attributes (EFAs) are known to inform on processes controlling species distribution, but they have not been tested as predictors of species abundance. In this study, we assessed the usefulness of SAMs calibrated with EFAs (as process-related variables) to predict local abundance patterns for a rare and threatened species (the narrow Iberian endemic 'Geres lily' Iris boissieri; protected under the European Union Habitats Directive), and to project inter-annual fluctuations of predicted abundance. We compared the predictive accuracy of SAMs calibrated with climate (CLI), topography (DEM), land cover (LCC), EFAs, and combinations of these. Models fitted only with EFAs explained the greatest variance in species abundance, compared to models based only on CLI, DEM, or LCC variables. The combination of EFAs and topography slightly increased model performance. Predictions of the inter-annual dynamics of species abundance were related to inter-annual fluctuations in climate, which holds important implications for tracking global change effects on species abundance. This study underlines the potential of EFAs as robust predictors of biodiversity change through population size trends. The combination of EFA-based SAMs and SDMs would provide an essential toolkit for species monitoring programs.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 16