Use of satellite images to characterize the spatio-temporal dynamics of primary productivity in hotspots of endemic Iberian butterflies

Abstract

Abstract The Iberian Peninsula is one of the European regions with the highest number of endemic species. Therefore, it is imperative to identify species populations potentially affected by variations in ecosystem functioning. Since the emergence of data processed from satellites, the possibility of carrying out studies covering both a spatial and temporal dimension has increased, providing more comprehensive information about species population dynamics and ecosystems. Primary productivity is a crucial parameter for understanding ecosystem function and services because it is the basis of the trophic chain. This study examines the spatiotemporal variation in primary productivity over a 14-year temporal series (2000–2013) through the enhanced vegetation index (EVI). We focused on the hotspots of endemic diurnal butterflies in the Iberian Peninsula and obtained data on the primary productivity dynamics at these locations as indicators to optimize further conservation efforts. Within these hotspots, statistically significant yet spatially irregular trends were found at localized sites, mostly in mountain systems (the Cantabrian Mountains, Iberian System, Sierra de Guadarrama and Sierra Nevada). At 60% of these sites, primary productivity significantly decreased. Two endemic species, the Sierra Nevada blue (Polyommatus golgus) and the Puerto del Lobo butterfly (Agriades zullichi), which are classified by the International Union for Nature Conservation (IUCN) as “Vulnerable” and “Endangered”, respectively, are present in localities where primary productivity showed a marked decline despite being within the Natura 2000 Network. The procedures developed here, which are based on consistent temporal trends of primary productivity, can serve as a tool to detect among biodiversity hotspots those locations where environmental change is unequivocal and hence further monitoring is needed.