We used datasets describing forest type, canopy structure, evapotranspiration components, hydroclimate, and several auxiliary background factors (Table 1). Forest type data were obtained from the 1990–2020 spatial distribution dataset of natural and plantation forests in China (Cheng et al., 2024b). This dataset was derived from Landsat imagery and extensive forest inventory samples using machine-learning classification and was resampled to 0.1° resolution to match the hydroclimatic datasets. Pixels with 100 % coverage of either natural forest (NF) or plantation forest (PF) were treated as pure pixels, and only these pixels were included in all major analyses. To maintain temporal consistency between forest masks and climate data, we adopted a period-based dynamic matching strategy. Specifically, forest maps for 1990, 1995, 2000, 2005, 2010, 2015, and 2020 were used to represent the periods 1990–1994, 1995–1999, 2000–2004, 2005–2009, 2010–2014, 2015–2019, and 2020, respectively.

LAI was derived from the GIMMS LAI4g dataset (Cao et al., 2023). The main evapotranspiration dataset used in this study was GLEAM v4.2a, from which transpiration (T), evapotranspiration (E), and soil moisture (SM) were extracted. GLEAM separately estimates the major components of terrestrial evaporation and provides both surface and root-zone soil moisture. In this study, SM refers to the root-zone soil moisture product, rather than surface soil moisture, because it more closely represents plant-available water relevant to transpiration regulation at the seasonal to interannual scales considered here. In GLEAM, root-zone soil moisture is represented as a vegetation-accessible multi-layer soil profile constrained by assimilated surface observations, rather than as a single shallow soil layer. Near-surface meteorological variables, including air pressure (Pa), relative humidity (RH), air temperature (Ta), precipitation (P), dewpoint temperature (Td), wind speed (WS), net radiation (Rn), and potential evapotranspiration (PET), were obtained from ERA5-Land. All environmental variables were aggregated over the growing season (April–October) for 1990–2020, using only growing-season data and excluding non-growing-season observations. Means were used for state variables (e.g., LAI, SM, Ta, and VPD), whereas cumulative values were used for flux variables (e.g., E, T, and P).

To evaluate the robustness of the estimated θ patterns and trends to data-product choice, we additionally used two alternative gridded products for cross-product comparison in supplementary analyses. One was the Simple Terrestrial Hydrosphere v2 (SiTHv2) product, which provides independent estimates of evapotranspiration and transpiration (Zhang et al., 2024). The other was the China terrestrial ecosystem transpiration fraction dataset (Niu et al., 2020), from which an alternative transpiration-fraction-based θ estimate was derived for comparison. These two datasets were used only for robustness assessment of θ, whereas all main calculations in the study were based on GLEAM.

To assess whether long-term changes in θ may also be modulated by non-hydroclimatic background factors, we further compiled several auxiliary datasets for supplementary analyses, including a global 1 km atmospheric carbon dioxide concentration dataset (Wang, 2026), a long-term reconstructed forest age dataset for China (Xia et al., 2023), and a 2020 forest age spatial distribution dataset for China (Cheng et al., 2024a). These auxiliary datasets were resampled to 0.1° resolution and used only to assess whether CO2 and stand age materially altered the observed θ patterns and trends. They were not included in the main analytical framework, in which the focus was on hydroclimatic controls.

Our study area covers terrestrial China, spanning temperate, subtropical, and tropical climate zones. The analysis focuses on China's NF and PF. NF are mainly concentrated in the mountains of Northeast and Southwest China, whereas PF are widely distributed across the plains and hills of East, Central, and South China (Fig. 1a). The vast majority of NF and PF are located in humid and semi-humid zones (Fig. 2).

We used the aridity index (AI) to characterize climatic background and to organize the spatial analyses within a unified framework. AI was defined as the ratio of annual potential evapotranspiration to annual precipitation (AI=PET/P). Based on the 1990–2020 multi-year mean AI, China was divided into four climatic zones: humid (AI<1), semi-humid (1≤AI<1.5), semi-arid (1.5≤AI<4), and arid (AI≥4). This four-zone classification was used as the geographic framework for mapping and descriptive comparisons. Because forest samples in the arid zone were extremely sparse, subsequent statistical analyses were restricted to the humid, semi-humid, and semi-arid zones.

Mean θ showed clear spatial heterogeneity and was consistently higher in NF than in PF (Fig. 3a, b, and e). High-θ areas in NF were concentrated mainly within the semi-arid to semi-humid transition belt, whereas PF showed a distinctly more fragmented pattern. During 1990–2020, growing-season θ declined widely in both forest types, with a stronger mean decline in PF than in NF (Fig. 3c and d). Significant negative trends were concentrated mainly in semi-humid and semi-arid transition regions, while humid regions showed weaker negative trends. The zone-averaged time series further confirmed that θ decreased significantly across climatic zones in both forest types, with the strongest declines occurring under drier climatic conditions (Fig. 3f and g). Overall, the marginal enhancement of TF by increasing LAI weakened over the past three decades, especially in PF and in relatively dry regions.

The decomposition of θtotal provided additional insight into the mechanisms behind the observed decline (Fig. 4). Under the main TFE definition, the long-term decrease in θtotal reflected both position-dependent saturation and changes in the fitted TF–LAI curve shape, but their relative roles differed between forest types. In natural forests, the position/saturation component made a negative contribution to θtotal, whereas the shape component differed in sign and partly offset the decline. This contrast indicates that the total θ trend would be difficult to interpret from θtotal alone. In plantation forests, the position/saturation component also contributed to the weakening of θtotal, while the shape component indicated additional changes in the fitted TF–LAI sensitivity. These results show that the weakening of the LAI enhancement effect on TF is not merely a bounded geometric consequence of higher LAI or TF approaching saturation; it also reflects changes in the biophysical TF–LAI relationship under evolving hydroclimatic conditions.

Pathway analysis indicated that the effects of macroclimate change on θ varied strongly among drivers, climatic zones, and forest types (Fig. 10). In natural forests (NF), precipitation generally showed negative direct effects, especially in the semi-humid and semi-arid zones, while its indirect effects differed among pathways, including positive VPD-mediated effects in humid and semi-arid zones. Temperature was the most consistent negative direct driver in NF, with particularly strong negative effects in humid and semi-arid regions, while its indirect effects differed according to pathway, including positive VPD-mediated effects in humid and semi-arid zones. In plantation forests (PF), the pathway structure was more heterogeneous; specifically, precipitation showed a significant positive direct effect in the semi-arid zone, temperature showed opposite indirect effects through SM and VPD in the humid zone, and net radiation and wind speed mainly exerted pathway-specific effects in humid and semi-humid regions. Overall, the pathway coefficients indicated strong dependence on hydroclimatic context and forest type in how macroclimate trends were associated with changes in θ, with no single pathway dominating across all climate drivers and zones. A supplementary mediator-specification comparison showed that the direction of VPD-mediated indirect effects was generally more robust across single-mediator and joint models than that of SM-mediated effects, whereas SM-mediated pathways were more sensitive to model specification under SM–VPD coupling (Fig. S19).

The joint SM–VPD analysis shows that θ was highest under intermediate SM and moderate-to-high VPD, corresponding to relatively strong atmospheric demand, and declined toward both wetter/low-demand and drier/high-demand conditions (Figs. 5, S14 and S15). This pattern indicates that increased leaf area enhances TF most effectively when water supply is sufficient but not excessive and evaporative demand is strong enough to sustain canopy transpiration. Once soil water becomes limiting or atmospheric demand becomes too strong, stomatal regulation increasingly constrains transpiration to avoid hydraulic damage, so the marginal gain in transpiration per unit increase in LAI declines (Novick et al., 2016; Grossiord et al., 2020; McDowell et al., 2022). Under wetter and weak-demand conditions, the capacity of additional leaf area to increase TF is also reduced because energy limitations, weaker canopy–atmosphere coupling, and larger non-transpirational evaporation fractions all weaken the translation of additional leaf area into transpiration (Konings et al., 2017; Stoy et al., 2019). The θ decomposition and supplementary diagnostics further suggest that this nonlinearity cannot be explained solely as a bounded geometric effect of TF; part of the long-term change also reflects shifts in the LAI–TF relationship itself (Figs. 4 and S6–S13).

The widespread decline in θ, especially across semi-humid to semi-arid transition zones, indicates that the capacity of increasing LAI to enhance TF has weakened over the last three decades (Fig. 3). This trend is consistent with a background of warming, rising VPD, and increasing frequency of soil moisture limitation, all of which reduce the effective transpiration response of forests to additional canopy development (Yuan et al., 2019; Lian et al., 2020; Denissen et al., 2022). Rising atmospheric CO2 may also have contributed to this decline by lowering stomatal conductance and increasing intrinsic water-use efficiency, thereby reducing transpiration demand per unit leaf area even where greening continued (Keenan et al., 2013; Keenan et al., 2016; Lavergne et al., 2019; Liang et al., 2023). At the same time, the supplementary analyses are more consistent with interpreting CO2 as a temporally coherent background forcing rather than a spatially heterogeneous driver of θ across China's forests (Fig. S17 and Table S1 in the Supplement). Stand development may likewise have modulated this trajectory. Age-related changes in stand structure, rooting depth, canopy roughness, and interception can shift the partitioning of evapotranspiration between transpiration and non-transpirational components, and therefore alter the LAI–TF relationship even without large changes in total leaf area (Fan et al., 2017; Forrester, 2015). However, the age-stratified results show that the higher θ in NF than in PF persisted across age groups, and including stand age did not overturn the broad interpretation of the relative roles of SM and VPD, although the magnitude of change was heterogeneous across forest types and climatic zones (Fig. S18 and Table S2). Together, these results suggest that CO2 rise and stand development may act as background modifiers of θ, while the dominant large-scale patterns remain primarily associated with hydroclimatic variability.

Partial correlation, ridge regression, and pathway analysis consistently indicate that the hydroclimatic controls on θ have changed over time, with the relative role of SM strengthening and that of VPD weakening in many regions (Figs. 6–10). This does not mean that atmospheric demand has ceased to matter; VPD still explains a slightly larger share of the present spatial pattern of θ, as also supported by the dominance statistics and multicollinearity diagnostics (Figs. 8 and S16). The more important point is that the sensitivity of θ to soil moisture limitation has intensified under recent climatic conditions. This interpretation is physically consistent with the increasing prevalence of water-limited ecosystem behavior under warming, in which rising evaporative demand is increasingly translated into ecological stress through soil-water depletion rather than through atmospheric forcing alone (Berg et al., 2016; Denissen et al., 2022). Once ecosystems approach critical soil-moisture thresholds more frequently, stomatal and hydraulic regulation become more tightly constrained by water supply, and the explanatory role of SM rises accordingly (Fu et al., 2022; Liu et al., 2025). The pathway results add the same message at a broader scale: temperature exerted generally negative effects on θ, whereas the effects of precipitation and radiation varied by forest type and climatic zone, implying that macroclimate trends influence θ through multiple hydroclimatic pathways rather than through a single dominant mechanism.

The contrast between natural and plantation forests remained one of the clearest features of the analysis. NF consistently showed higher θ, and high-θ values in NF were maintained across a wider range of SM–VPD backgrounds, whereas PF showed lower θ and a more restricted range of hydroclimatic conditions under which high θ occurred. This pattern likely reflects differences between long-term spatial hydroclimatic contrasts and within-pixel temporal variability. Spatial contrasts integrate longer-term differences in stand structure, species composition, hydraulic diversity, and belowground water access, whereas temporal anomalies are expressed more directly through canopy–atmosphere coupling and stomatal–hydraulic regulation during drought (Martínez-Vilalta and García-Forner, 2017; Grossiord et al., 2020; Novick et al., 2024; Bachofen et al., 2024). Under this interpretation, the broader hydroclimatic response of NF may reflect the greater structural and functional heterogeneity often associated with natural forests, while the narrower response of PF may reflect the relative structural simplification typical of many plantation stands. This interpretation is also consistent with evidence that higher hydraulic diversity can buffer ecosystem drought responses (Anderegg et al., 2018). The age-stratified supplementary results are consistent with this interpretation, because the higher θ in NF than in PF persisted across age classes and this pattern is therefore unlikely to be explained solely by stand age.

These results imply that further greening will not necessarily translate into proportionally higher transpiration fractions under continued warming and drying. In regions where hydroclimatic water stress is increasing, especially across semi-humid to semi-arid transition zones, the ecohydrological consequences of increasing canopy leaf area depend increasingly on soil water supply, and this dependence appears more evident in plantation forests than in natural forests. This has direct management implications: plantation design may benefit from greater rooting-depth and trait diversity and from stand structures that reduce rapid soil-water depletion, whereas natural forests may benefit more from maintaining multilayer canopy structure and hydraulic diversity under rising atmospheric demand. Several limitations should remain explicit. A nationwide in situ benchmark for θ trends is not yet available because long-term observations that simultaneously resolve transpiration partitioning, LAI dynamics, and stand development remain too sparse across China's forests. We therefore evaluated robustness through cross-product consistency rather than direct site-based validation. In addition, because θ, SM, and VPD were analyzed from growing-season aggregates and moving-window series, the results characterize seasonal-to-interannual hydroclimatic controls rather than instantaneous stomatal responses to short-lived atmospheric fluctuations. Even with these constraints, the convergence among the main analyses, the supplementary robustness checks, and the CO2- and age-sensitivity diagnostics supports the central inference that the enhancement of TF by increasing LAI has weakened across China's forests and is increasingly shaped by soil moisture limitation.