Remote sensing depicts riparian vegetation responses to water stress in a humid Atlantic region

• Autor(a) principal: Pace, Giorgio
• Data de Publicação: 2021
• Outros Autores: Cánovas, Cayetano Gutiérrez, Henriques, R., Boeing, F., Cássio, Fernanda, Pascoal, Cláudia
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/1822/72903
• topic: Ecosystem; Environmental Monitoring; Humans; Portugal; Rivers; Dehydration; Remote Sensing Technology; NDVI; Primary productivity; Forestry; Sentinel 2; Climate change; Ciências Naturais::Ciências Biológicas; Engenharia e Tecnologia::Biotecnologia Ambiental; Science & Technology

Riparian areas in the Cantabrian Atlantic ecoregion (northwest Portugal) play a key role in soil formation and conservation, regulation of nutrient and water cycle, creation of landscape aesthetic value and the preservation of biodiversity. The maintenance of their ecological integrity is crucial given the ever increase in multiple anthropogenic (water demand and agriculture) and climatic pressures (droughts and extreme events). We developed a transferable remote sensing approach, taking advantage of the latest freely available technologies (Sentinel-2 and Copernicus Land products), to detect intra-annual and inter-annual changes in riparian vegetation productivity at the river basin scale related to water stress. This study has used the normalized difference vegetation index (NDVI) to investigate riparian vegetation productivity dynamics on three different vegetation types (coniferous, broadleaved and grassland) over the past 5 years (2015-2019). Our results indicated that inter-annual seasonality differed between drier (2017) and wetter (2016) years. We found that intra-annual dynamics of NDVI were influenced by the longitudinal river zonation. Our model ranked first (r2m = 0.73) showed that the productivity of riparian vegetation during the dry season was positively influenced by annual rainfall and by the type of riparian vegetation. The emergent long lags between climatic variation and riparian plant productivity provides opportunities to forecast early warnings of climatically-driven impacts. In addition, the different average productivity levels among vegetation types should be considered when assessing climatic impacts on riparian vegetation. Future applications of Sentinel 2 products could seek to distinguish riparian areas that are likely to be more vulnerable to changes in the annual water balance from those that are more resistant under longer-term changes in climate.