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ABSTRACT Net primary productivity (NPP) is an important indicator of ecosystem functioning and carbon sequestration capacity. Its changes reflect natural ecosystem health and support addressing global warming, resource security, and sustainable progress. This study estimated vegetation NPP at 500-m resolution in Liaoning (2001–2020) using a revised Carnegie Ames Stanford Approach model, with Theil–Sen, Mann–Kendall, Hurst index, variation coefficient, and optimal parameters geographical detector to explore spatiotemporal dynamics and drivers. The results are as follows: (1) annual average NPP was 731.55 gC m−2 a−1, rising overall, with high values on both sides and low in the middle. Forests had the highest multiyear average (845.82 gC m−2 a−1). (2) The plant NPP in Liaoning Province generally stayed steady (making up 50.99%), followed by an advancing trend (47.12%), among which 39.82% of the area showed a notable advancement. In the study area, 99.4% of the regions had high ecological steadiness, 0.60% had low ecological steadiness, and 27.28% were in regions with medium fluctuations. (3) Plant type and rainfall are the key driving elements affecting NPP, with their explanatory abilities being 0.91 and 0.65, respectively; vegetation type and precipitation showed the highest explanatory power for NPP spatial differentiation. Additionally, there are strong interactive impacts between different influencing elements, especially between plant type and rainfall, and between land use type and solar radiation, with the explanatory ability of their interactions reaching as high as 0.98.
Jia et al. (Tue,) studied this question.