Evaluating the performance of multiple remote sensing indices to predict the spatial variability of ecosystem structure and functioning in Patagonian steppes

Authors
Gaitan, Juan Jose; Bran, Donaldo Eduardo; Oliva, Gabriel Esteban; Ciari, Georgina; Nakamatsu, Viviana Beatriz; Salomone, Jorge Manuel; Ferrante, Daniela; Buono, Gustavo Gabriel; Massara Paletto, Virginia; Humano, Gervasio; Celdran, Diego Javier; Opazo, Walter Javier; Maestre, Fernando Tomás
Publication Year
2013
Language
English
Format
article
Status
Published version
Description
Assessing the spatial variability of ecosystem structure and functioning is an important step towards developing monitoring systems to detect changes in ecosystem attributes that could be linked to desertification processes in drylands. Methods based on ground-collected soil and plant indicators are being increasingly used for this aim, but they have limitations regarding the extent of the area that can be measured using them. Approaches based on remote sensing data can successfully assess large areas, but it is largely unknown how the different indices that can be derived from such data relate to ground-based indicators of ecosystem health. We tested whether we can predict ecosystem structure and functioning, as measured with a field methodology based on indicators of ecosystem functioning (the landscape function analysis, LFA), over a large area using spectral vegetation indices (VIs), and evaluated which VIs are the best predictors of these ecosystem attributes. For doing this, we assessed the relationship between vegetation attributes (cover and species richness), LFA indices (stability, infiltration and nutrient cycling) and nine VIs obtained from satellite images of the MODIS sensor in 194 sites located across the Patagonian steppe. We found that NDVI was the VI best predictor of ecosystem attributes. This VI showed a significant positive linear relationship with both vegetation basal cover (R2 = 0.39) and plant species richness (R2 = 0.31). NDVI was also significantly and linearly related to the infiltration and nutrient cycling indices (R2 = 0.36 and 0.49, respectively), but the relationship with the stability index was weak (R2 = 0.13). Our results indicate that VIs obtained from MODIS, and NDVI in particular, are a suitable tool for estimate the spatial variability of functional and structural ecosystem attributes in the Patagonian steppe at the regional scale.
Fil: Gaitan, Juan Jose. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; Argentina
Fil: Bran, Donaldo Eduardo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; Argentina
Fil: Oliva, Gabriel Esteban. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina
Fil: Ciari, Georgina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Esquel; Argentina
Fil: Nakamatsu, Viviana Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Esquel; Argentina
Fil: Salomone, Jorge Manuel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Chubut; Argentina
Fil: Ferrante, Daniela. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina
Fil: Buono, Gustavo Gabriel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Chubut; Argentina
Fil: Massara Paletto, Virginia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Chubut; Argentina
Fil: Humano, Gervasio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina
Fil: Celdran, Diego Javier. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Chubut; Argentina
Fil: Opazo, Walter Javier. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Esquel; Argentina
Fil: Maestre, Fernando T. Universidad Rey Juan Carlos. Escuela Superior de Ciencias Experimentales y Tecnología. Departamento de Biología y Geología, Física y Química Inorgánica; España
Source
Ecological indicators 34 : 181-191. (Nov. 2013)
Subject
Desertificación
Desertification
Ecosystems
Vegetation
Remote Sensing
Spatial Distribution
Ecosistema
Vegetación
Teledetección
Distribución Espacial
Vegetation Indices
Landscape Function Analysis
Región Patagónica
Access level
Restricted access
License
Repository
INTA Digital (INTA)
Institution
Instituto Nacional de Tecnología Agropecuaria
OAI Identifier
oai:localhost:20.500.12123/1449