BUSCADOR RECOLECTA

Digital.CSIC. Repositorio Institucional del CSIC

oai:digital.csic.es:10261/149381

Plant primary production is a key driver of several ecosystem functions in seasonal marshes, such as water purification and secondary production by wildlife and domestic animals. Knowledge of the spatio-temporal dynamics of biomass production is therefore essential for the management of resources—particularly in seasonal wetlands with variable flooding regimes. We propose a method to estimate standing aboveground plant biomass using NDVI Land Surface Phenology (LSP) derived from MODIS, which we calibrate and validate in the Doñana National Park’s marsh vegetation. Out of the different estimators tested, the Land Surface Phenology maximum NDVI (LSP-Maximum-NDVI) correlated best with ground-truth data of biomass production at five locations from 2001–2015 used to calibrate the models (R² = 0.65). Estimators based on a single MODIS NDVI image performed worse (R² ≤ 0.41). The LSP-Maximum-NDVI estimator was robust to environmental variation in precipitation and hydroperiod, and to spatial variation in the productivity and composition of the plant community. The determination of plant biomass using remote-sensing techniques, adequately supported by ground-truth data, may represent a key tool for the long-term monitoring and management of seasonal marsh ecosystems., We acknowledge support by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI)., David Aragonés, Isabel Afán, Ricardo Díaz-Delgado and Diego García Díaz (EBD-LAST) provided support for remote-sensing and LSP analyses. Alfredo Chico, José Luis del Valle and Rocío Fernández Zamudio (ESPN, ICTS-RBD) provided logistic support and taxonomic expertise during the field work (validation dataset). Ernesto García and Cristina Pérez assisted with biomass harvesting and processing (calibration dataset). Gerrit Heil provided support in the project design. This study received funding from Ministerio de Medio Ambiente-Parque Nacional de Doñana, Consejeria de Medio Ambiente, Junta de Andalucia (1999–2000): RNM118 Junta de Andalucia (2003); the European Union’s Horizon 2020 Research and Innovation Program under grant agreement No. 641762 to ECOPOTENTIAL project; and the Spanish Ministry of Economy, Plan Estatal de I+D+i 2013–2016, under grant agreement CGL2016-81086-R to GRAZE project.