ABSTRACT Accurately estimating the net primary productivity (NPP) of forests in high‐latitude, ecologically fragile regions and understanding its spatiotemporal drivers are crucial for assessing global carbon balance and achieving sustainable development under climate change. This study focuses on the Tahe River Basin in the Greater Khingan Mountains; utilising the Carnegie Ames Stanford Approach (CASA) model, we simulated the spatiotemporal dynamics of watershed NPP and investigated its driving mechanisms. Notably, this research reveals the asymmetric response mechanisms of NPP to water deficit and surplus states among different forest types in the northern forests. The results indicate that the multi‐year average NPP in the Tahe River Basin from 1982 to 2022 was 483.01 g C m −2 a −1 , exhibiting a significant increasing trend at a rate of 5.62 g C m −2 a −1 . NPP decreased with elevation but showed no slope dependence. Precipitation dominated NPP variation, with forest‐type ranking: deciduous broadleaf > deciduous coniferous > evergreen coniferous. Mild drought reduced watershed NPP by 20.39 g C m −2 a −1 , while severe drought led to a loss of 45.27 g C m −2 a −1 . Mild wetness slightly promoted NPP, whereas severe wetness exerted an even stronger disruptive effect on NPP than severe drought. Responses of NPP to drought varied significantly among vegetation types, with coniferous forests demonstrating stronger resistance. Severe wetness significantly reduced NPP in all three vegetation types, resulting in losses of 20.66%, 11.97% and 19.06% for deciduous broadleaf forest, evergreen coniferous forest and deciduous coniferous forest, respectively. The asymmetric response mechanism to water deficit/surplus revealed in this study, along with its dependence on forest type, addresses a critical gap in the theoretical framework of forest carbon cycle driving mechanisms in high‐latitude ecologically fragile zones. It is critical for reliably evaluating the stability of forest carbon sinks and for guiding the design of effective, nature‐based adaptation strategies in these regions facing climate change.
Hu et al. (Sun,) studied this question.