Abstract
Understanding the interaction between land surface and atmosphere processes is fundamental for predicting the effects of future climate change on ecosystem functioning and carbon dynamics. The objectives of this work were to analyze the trends in land surface phenology (LSP) metrics from remote sensing data, and to reveal their relationship with precipitation and ENSO phenomenon in the Argentina Pampas. Using a time series of MODIS Normalized Difference Vegetation Index (NDVI) data from 2000 to 2014, the start of the growing season (SOS), the annual integral of NDVI (i-NDVI, linear estimator of annual productivity), the timing of the annual maximum NDVI (t-MAX) and the annual relative range of NDVI (RREL, estimator of seasonality) were obtained for the Argentina Pampas. Then, spatial and temporal relationships with the Multivariate ENSO Index (MEI) and precipitation were analyzed. Results showed a negative trend in annual productivity over a 53.6% of the study area associated to natural and semi-natural grassland under cattle grazing, whereas a 40.3% of Argentina Pampas showed a significant positive trend in seasonality of carbon gains. The study also reveals that climate variability has a significant impact on land surface phenology in Argentina Pampas, although the impact is heterogeneous. SOS and t-MAX showed a significant negative correlation with the precipitation indicating an earlier occurrence. 23.6% and 28.4% of the study area showed a positive correlation of the annual productivity with MEI and precipitation, respectively, associated to rangelands (in the first case) and to both rangeland and croplands, in the second case. Climate variability did not explain the seasonal variability of phenology. The relationships found between LSP metrics and climate variability could be important for implementation of strategies for natural resource management.
Highlights
Phenology can be defined as the study of the timing of recurrent biological events, the causes of their timing with regard to biotic and abiotic forces, and the interrelation among phases of the same or different species (Lieth, 1974)
Most of the start of the growing season (SOS) values occur on days of year (DOY) 213-263 (August-September), whereas in the southwestern region SOS occurs on DOY 274344 (October-November) (Fig. 2a)
The i-Normalized Difference Vegetation Index (NDVI) mean values increased from the southwestern to the northeastern regions (Fig. 2c). 53.6% of the study area showed a significant negative trend in integral of NDVI (i-NDVI) during the period 2000-2014, representing a surface of 76,035.4 km2 mainly located in the centre of our study area (Fig. 2d)
Summary
Phenology can be defined as the study of the timing of recurrent biological events, the causes of their timing with regard to biotic and abiotic forces, and the interrelation among phases of the same or different species (Lieth, 1974). Vegetation phenology is a key aspect for the global carbon and water cycles, influencing the exchange of energy and water vapor between the atmosphere and land surface (Cong et al, 2013; Luo et al, 2013) In this sense, phenology is one of the most important biological indicators of the effects of climate change on biological systems at different scales (Bertin, 2008; Dai et al, 2013). From the applications of satellite datasets, the concept of land surface phenology (LSP) is often used, referring to the seasonal pattern of variation in vegetated cover that is observed through remote sensing (Helman, 2018; Reed et al, 2009) This approach differs from phenological records of individual species, which refers to events as flowering, senescence, etc. It is difficult to provide a sufficiently dense network of phenological events, satellite-derived measures of phenology is an essential approach to include them in carbon dynamics or other more complex climatic models (Müller et al, 2014)
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