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

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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 < 0.01), including both a substantial increase (p < 0.01) and a moderate increase (0.01 ≤ p < 0.05). The areas witnessing heightened NPP were predominantly situated in the northeastern, southeastern, northwestern sections, and the southwestern portion of Sichuan. The fluctuations in NPP trends displayed mild persistence or slight antipersistence traits, with regions where 0 < H < 0.5 constituting 80.26% of the overall area. Natural factors (such as elevation, mean annual temperature, NDVI, and topographic relief) along with human influences (changes in land use type) were identified as effectively accounting for the fluctuations in NPP. These factors demonstrated interactive effects on NPP, with the synergistic effect resulting in nonlinear enhancement and bilinear enhancement effects. The interaction between these two factors strengthened the influence of each individual factor. Identifying the optimal characteristics or ranges of these factors can facilitate ecological conservation and vegetation restoration. These factors exhibited interactive effects on NPP, with the synergistic effect resulting in nonlinear enhancement and bilinear enhancement effects. The interplay between these two factors heightened the influence of each separate element. Determining the optimal attributes or ranges of these factors can contribute to the facilitation of ecological preservation and the restoration of vegetation.