Asymmetric Decline in Hydrological Efficiency of China's Natural and Planted Forests

Abstract. The vegetation transpiration fraction (TF) is a key parameter linking terrestrial water and carbon cycles. Against the backdrop of global greening and climate change, the response of TF sensitivity to Leaf Area Index (LAI) changes (θ), and the relative roles of soil moisture (SM) and atmospheric drought (VPD), remain unclear, especially lacking a systematic comparison between China's Natural Forests (NF) and Planted Forests (PF). This study utilized multi-source datasets from 1990–2020 (including forest types, GLEAM, and ERA5-Land) and employed methods including sliding windows, partial correlation, ridge regression, and mediation effect models to systematically analyze the spatiotemporal dynamics of θ in NF and PF, and to quantify the independent contributions and dynamic shifts of SM and VPD. Results show: 1) Forest θ spatially increases from humid to semi-arid regions (NF > PF); temporally, θ shows a widespread significant decline, with PF declining more (mean of −0.262 %∙m⁻² · m² · decade⁻¹) than NF, especially in semi-arid/semi-humid transition zones. 2) θ exhibits a "hump-shaped" nonlinear response to the joint SM-VPD gradient, peaking at moderate SM and medium-high VPD. 3) The key hydrological drivers of θ are undergoing a dynamic shift from "atmospheric demand" (VPD) to "soil supply" (SM); the independent control of SM (βSM) has significantly strengthened over time, while that of VPD (βVPD) has weakened. 4) The two forest types show distinct response mechanisms: NF is more sensitive to VPD, while PF is more sensitive to SM stress. Overall, China's forests are shifting towards a more "conservative" water-use strategy, and the enhancing effect of LAI on TF has significantly weakened under strengthening SM constraints and VPD stress. The differentiated high sensitivity – NF to atmospheric drought and PF to soil drought – provides critical insights for forest water resource management and afforestation planning under future climate change scenarios.