Characterization of terrestrial ecosystems state based on interannual variations of RUE (Rain Use Efficiency)

Authors

DOI:

https://doi.org/10.4995/raet.2023.19980

Keywords:

RUE, GPP, ecosystems degradation, annual precipitation

Abstract

Ecosystems degradation has increased in recent decades and climate change is expected to increase the risk of such processes in the coming years, especially in arid and semi-arid ecosystems. The purpose of this work is to characterize the state of the terrestrial ecosystems of the Spanish mainland and the Balearic Islands through the temporal analysis of the variable RUE (Rain Use Efficiency) during the period 2004-2018. Annual RUE images have been calculated as the quotient between annual gross primary production (GPP) and annual cumulative precipitation (PPT) in a 1 km spatial resolution, and the values have been later normalized. The annual GPP is derived from the daily GPP, obtained using an optimization of the Monteith model and the PPT from daily precipitation images, which are computed by applying a kriging to the data from AEMet network stations. Temporal analysis of the RUE has been made by calculating the slope from a Mann-Kendall test and Sen-Theil method. RUE has been analyzed at three levels of study: at regional level, by vegetation types and at pixel level. The results have shown a negative trend of the normalized RUE (between -0.05 and -0.25 year-1) for most of the area, for the 9 classes of vegetation (the forest classes being the ones that have presented the steepest slopes) and in 5 of the 8 ecosystems analyzed at pixel level. A decline in the RUE indicates some degree of degradation in vegetation cover. From the analysis of the results it has been extracted that the interannual variability of the RUE is largely mediated by precipitation, presenting a negative correlation. On the other hand, it has been observed that GPP has experienced a progressive increase in recent years known as greening process.

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Author Biographies

Marina Simó-Martí, Universitat Politècnica de València

Geo-Environmental Cartography and Remote Sensing Group (CGAT), Department of Cartographic Engineering,Geodesy and Photogrammetry

Beatriz Martínez, University of Valencia

UV-Environmental Remote Sensing Group (UV-ERS). Departament de Física de la Terra i Termodinàmica. Facultat de Física

María Amparo Gilabert, University of Valencia

UV-Environmental Remote Sensing Group (UV-ERS). Departament de Física de la Terra i Termodinàmica. Facultat de Física

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Published

2023-07-28

Issue

Section

Practical cases

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