Discriminating the biophysical signal from human-induced effects on long-term primary production dynamics. The case of Patagonia.

Autor: Irisarri JGN; Cátedra de Forrajicultura, Departamento de Producción Animal, Facultad de Agronomía, LART IFEVA, Universidad, de Buenos Aires, CONICET, Buenos Aires, Argentina., Texeira M; Departamento de Métodos Cuantitativos y Sistemas de Información, Facultad de Agronomía, LART IFEVA, Universidad, de Buenos Aires, CONICET, Buenos Aires, Argentina., Oesterheld M; Cátedra de Ecología, Facultad de Agronomía, LART IFEVA, Universidad, de Buenos Aires, CONICET, Buenos Aires, Argentina., Verón SR; Instituto de Clima y Agua, Instituto Nacional de Tecnología Agropecuaria (INTA), Departamento de Métodos Cuantitativos y Sistemas de. Información, Facultad de Agronomía, Universidad, de Buenos Aires, CONICET, Buenos Aires, Argentina., Della Nave F; Cátedra de Ecología, Facultad de Agronomía, LART IFEVA, Universidad, de Buenos Aires, CONICET, Buenos Aires, Argentina., Paruelo JM; Departamento de Métodos Cuantitativos y Sistemas de Información, Facultad de Agronomía, LART IFEVA, Universidad, de Buenos Aires, CONICET, Buenos Aires, Argentina.; Instituto Nacional de Investigaciones Agropecuarias (INIA) La Estanzuela, Colonia, Uruguay.; Facultad de Ciencias, IECA, Universidad de la República, Montevideo, Uruguay.
Jazyk: angličtina
Zdroj: Global change biology [Glob Chang Biol] 2021 Sep; Vol. 27 (18), pp. 4381-4391. Date of Electronic Publication: 2021 Jun 27.
DOI: 10.1111/gcb.15733
Abstrakt: The temporal trend of aboveground net primary production (ANPP) is frequently used to estimate the effect of humans on ecosystems. In water-limited ecosystems, like most grazing areas in the world, the effect of humans act upon ANPP in combination with environmental variations. Our main objective was to quantify long-term (1981-2012) changes of ANPP and discriminate the causes of these changes between environmental and human at a subcontinental scale, across vast areas of Patagonia. We estimated ANPP through a radiative model based on remote sensing data. Then, we evaluated the relation between ANPP and environmental interannual variations of two hierarchically related factors: El Niño Southern Oscillation (ENSO) through the Southern Oscillation Index (SOI), and precipitation. We described the effect of humans through the shape of the temporal trends of the residuals (RESTREND) of the environmental model and quantified human relative impact through the RESTREND: ANPP trend ratio. ANPP interannual variation was significantly explained by ENSO (through SOI) and precipitation in 65% of the study area. The SOI had a positive association with annual precipitation. The association between ANPP and annual precipitation was positive. RESTREND analysis was statistically significant in 92% of the area where the tested environmental model worked, representing 60% of the study area, and it was mostly negative. However, its magnitude, revealed through the RESTREND: ANPP trend ratio, was relatively mild. Our analysis revealed that most of ANPP trends were associated with climate and that even when human density is low, its incidence seems to be mainly negative.
(© 2021 John Wiley & Sons Ltd.)
Databáze: MEDLINE
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