ABOVE-GROUND NET PRIMARY PRODUCTIVITY AND RAIN USE EFFICIENCY OF Megathyrsus maximus PASTORAL SYSTEMS: CASE STUDY OF EL 14 ESTABLISHMENT, DEPARTAMENTO MORENO, SANTIAGO DEL ESTERO, ARGENTINA

• Autor: Tiedemann, Jose Luis
• Formato: artículo
• Fecha de Publicación: 2022
• Institución: Universidad Nacional Agraria La Molina
• Repositorio: Revistas - Universidad Nacional Agraria La Molina
• Lenguaje: inglés
• OAI Identifier: oai:revistas.lamolina.edu.pe:article/1871
• Enlace del recurso: https://revistas.lamolina.edu.pe/index.php/eau/article/view/1871
• Nivel de acceso: acceso abierto
• Materia: NDVI time series; seasonality; rainfall anomalies; thresholds; series de tiempo NDVI; estacionalidad; anomalías de precipitación; umbrales

The objectives of this work were: to delimit the growing seasons of the M. maximus pastoral systems in El 14 establishment, Departamento Moreno, Santiago del Estero, Argentina, in the 2000-2021 period using time series of NDVIMODIS and threshold 0.5 NDVIRATIO; to quantify their aboveground net primary productivity (ANPP) and their responses to seasonal rainfall anomalies; to quantify the rain use efficiency (RUE), relate it to seasonal rainfall and determine its trend in the period. Growing seasons (GS) start in November and end in May. Significant differences were found in the ANPP of GS with anomalies positive and negative of seasonal rainfall. ANPP recovers after GS with negative rainfall anomalies, evidencing their resilience capacity after extreme weather events. The RUE had a high negative trend in the period. Significant differences were found in the RUE and seasonal rainfall. Most of RUE are related to the normal range of rainfall for the study area. In turn, growing season with lowest RUE were related to rainfall ≥ 700 mm. Seasonal rainfall of 700 mm could be considered the threshold in the loss of water of pastoral systems. Anthropic activities like deforestation and livestock, added to shifts in seasonal storm in intensity/magnitude, number of rainy, timing and frequency, they would contribute to the loss of large amounts of water by surface runoff in the study area. The local information obtained enables the implementation of appropriate management strategies in order to mitigate extreme climatic adversities.