RT Journal Article
T1 Model-Assisted Bird Monitoring Based on Remotely Sensed Ecosystem Functioning and Atlas Data
A1 Regos Sanz, Adrián
A1 Gómez Rodríguez, Pablo
A1 Arenas Castro, Salvador
A1 Tapia del Río, Luis Enrique
A1 Vidal Malde, María José
A1 Domínguez Conde, Jesús
K1 IUCN conservation status
K1 Land-surface temperature
K1 Life-history traits
K1 Remotely sensed essential biodiversity variables (RS-EBVs)
K1 Surface energy balance and temperature
K1 Vegetation productivity
AB Urgent action needs to be taken to halt global biodiversity crisis. To be effective in the implementation of such action, managers and policy-makers need updated information on the status and trends of biodiversity. Here, we test the ability of remotely sensed ecosystem functioning attributes (EFAs) to predict the distribution of 73 bird species with different life-history traits. We run ensemble species distribution models (SDMs) trained with bird atlas data and 12 EFAs describing different dimensions of carbon cycle and surface energy balance. Our ensemble SDMs—exclusively based on EFAs—hold a high predictive capacity across 71 target species (up to 0.94 and 0.79 of Area Under the ROC curve and true skill statistic (TSS)). Our results showed the life-history traits did not significantly affect SDM performance. Overall, minimum Enhanced Vegetation Index (EVI) and maximum Albedo values (descriptors of primary productivity and energy balance) were the most important predictors across our bird community. Our approach leverages the existing atlas data and provides an alternative method to monitor inter-annual bird habitat dynamics from space in the absence of long-term biodiversity monitoring schemes. This study illustrates the great potential that satellite remote sensing can contribute to the Aichi Biodiversity Targets and to the Essential Biodiversity Variables framework (EBV class “Species distribution”)
PB MDPI
YR 2020
FD 2020
LK http://hdl.handle.net/10347/23576
UL http://hdl.handle.net/10347/23576
LA eng
NO Regos, A.; Gómez-Rodríguez, P.; Arenas-Castro, S.; Tapia, L.; Vidal, M.; Domínguez, J. Model-Assisted Bird Monitoring Based on Remotely Sensed Ecosystem Functioning and Atlas Data. Remote Sens. 2020, 12, 2549
NO Fieldwork campaigns were carried out within the project “Estudios sobre a biodiversidade do Macizo Central Galego. Lugar de Importancia Comunitaria” (PGIDT99PXI20002B) and “Caracterización de los vertebrados del LIC Macizo Central e Bidueiral de Montederramo”, code: 2008-CE227”, funded by SAYFOR S.L. This work also received funding from Xunta de Galicia through the grant to structure and consolidate competitive research groups of Galicia (ED431B 2018/36). A.R. was funded by the Xunta de Galicia, Spain (post-doctoral fellowship ED481B2016/084-0). S.A.-C. was financially supported by PORBIOTA—E-Infraestrutura Portuguesa de Informação e Investigação em Biodiversidade (POCI-01-0145-FEDER-022127)
DS Minerva
RD 25 abr 2026