NDVI dynamics in different phases of the ENSO phenomenon in the laguna blanca biosphere reserve (catamarca, Argentina)

Abstract

El Niño-Southern Oscillation (ENSO) is an oceanic-climatic phenomenon which shows two contrasting phases and an intermediate or neutral phase that affect different regions of the world. In some ecoregions of northwestern Argentina (NOA), these phases would induce years with lower or higher rainfall than the historical average, corresponding to El Niño and La Niña, respectively. These differences in water availability cause changes in vegetation cover and land degradation, as well. Changes in the water regime due to natural or anthropic causes, which affect the productivity of different ecosystems, can be inferred through differences in spectral indices, such as NDVI (Normalized Difference Vegetation Index). The main objectives of this research were to characterize the dynamics of the vegetation cover estimated by mean of NDVI and study the temporal relationships among ENSO, rainfall and NDVI in the most conspicuous communities of the Puna in the Laguna Blanca Biosphere Reserve. NDVI data from the MODIS sensor (Moderate Resolution Imaging Spectroradiometer) were obtained from a published map of plant communities in the reserve; precipitation, from the GPCC (Global Precipitation Climatology Center), and the El Niño Oceanic Index (ONI), from the National Oceanic and Atmospheric Administration (NOAA). The highest difference of this last index among the different phases of the ENSO was reached between September and February. As a consequence of the monsoon regime, rainfall reached its peak a quarter later, being the highest in La Niña events. The maximum NDVI also showed a delay of one to two quarters with respect to ONI depending on the community considered. Results suggest that there is a connection among NDVI, rainfall and ENSO phases in Catamarca’s Puna. In extreme years La Niña and El Niño, both in steppes of the arid and semi-arid Puna, significant differences in NDVI values were observed. The results suggest that ONI monitoring would allow anticipating the application of appropriate strategies for desertification control.