Quantifying the impacts of natural and human factors on changes in NPP using an optimal parameters-based geographical detector

Autor: Guangjie Wang, Wenfu Peng, Lindan Zhang, Ji Zhang
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Ecological Indicators, Vol 155, Iss , Pp 111018- (2023)
Druh dokumentu: article
ISSN: 1470-160X
DOI: 10.1016/j.ecolind.2023.111018
Popis: Investigating the driving mechanisms behind fluctuations in vegetation net primary productivity (NPP) has the potential to enhance our comprehension of ecosystem dynamics and their response to environmental changes. However, identifying the nonlinear and spatiotemporal heterogeneity of factors contributing to NPP variation remains a challenge. This research employed the Theil-Sen trend, Hurst index, and nonparametric Mann-Kendall test methodologies through the utilization of Google Earth Engine (GEE) to detect monotonic trends in NPP, distinguishing between upward and downward trends. The influence of individual factors and their interactive effects on NPP changes were quantified using the optimized parameter-based geographical detector (OPGD) model. The findings revealed a general upward trend in NPP, exhibiting an average growth rate of around 85.06 gC m−2.a-1. Nevertheless, these rates of growth were not uniform, leading to noteworthy fluctuations spanning from 447.44 to 543.69 gC m−2.a-1. The eastern and central regions showcased relatively elevated NPP, whereas the western and southern regions demonstrated comparatively reduced levels. Roughly 51.66% of the areas displayed a rising trend in NPP, with 44.81% of the entire area indicating a noteworthy increase (p
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