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In the topographically and climatically diverse region of Yunnan, clarifying the driving mechanisms and threshold effects of factors influencing forest net primary productivity (NPP) is crucial for managing forest carbon sinks. In this study, we established a comparative analysis framework for the stable forest (SF) and the changing forest (CF). Yunnan was then divided into five subregions based on topography and climate. Using a random forest model and the SHAP method, we systematically analyzed drivers of spatiotemporal NPP variations. The results show that CF exhibits greater NPP variation and spatial heterogeneity than SF and maintains stronger trend persistence. At the provincial scale, elevation and precipitation are the main drivers of NPP in SF and CF, respectively, while at the subregional scale, dominant factors differ and include solar radiation, temperature, and forest age, indicating clear scale‐dependent effects. The explanatory power of multiple‐factor interactions for NPP variations is generally higher than that of single factors, with precipitation showing particularly strong synergistic effects. Human activities also have a pronounced impact on NPP in CF. Key driving factors exhibit nonlinear threshold responses, with NPP in SF most suitable under temperature (14°C–20°C), precipitation (100–125 mm), elevation (~2000 m), and forest age (50–70 years), whereas CF shows broader response ranges, reflecting greater adaptability. This study highlights the nonlinear responses and threshold characteristics of forest NPP to multiple driving factors in complex mountainous environments. It also emphasizes the importance of interactions and scale effects in ecological modeling. We first classified the forests in Yunnan Province into stable forest and change forest regions, and then further divided the province into five sub‐regions based on topography and climate. Based on this classification, we systematically analyzed the spatiotemporal variation of forest net primary productivity (NPP) across these regions. Moreover, by employing the Random Forest model and SHAP analysis, we identified the key driving factors behind the NPP changes in different sub‐regions.

• Understanding how plant water uptake interacts with acquisition of soil nitrogen (N) and other nutrients is fundamental for predicting plant responses to a changing environment, but it is an area where models disagree. • We present a novel isotopic labelling approach which reveals spatial patterns of water and N uptake, and their interaction, by trees. The stable isotopes 15N and ²H were applied to a small area of the forest floor in stands with high and low soil N availability. Uptake by surrounding trees was measured. The sensitivity of N acquisition to water uptake was quantified by statistical modelling. • Trees in the high-N stand acquired twice as much 15N as in the low-N stand and around half of their N uptake was dependent on water uptake (²H enrichment). By contrast, in the low-N stand there was no positive effect of water uptake on N uptake. • We conclude that tree N acquisition was only marginally dependent on water flux toward the root surface under low-N conditions whereas under high-N conditions, the water-associated N uptake was substantial. The results suggest a fundamental shift in N acquisition strategy under high-N conditions.

Dolomite karst systems are less common and less exploited than limestone systems, but still they can significantly contribute to drinking water supply in many countries. The knowledge about spatial and temporal variations of hydrochemical parameters of such systems is much more limited than for limestone karst aquifers. In the present research, 40-year-long observations of hydrochemical parameters gathered from five springs and a pumping well in Waidhofen an der Ybbs (Austria) were used to show the variability of chemical water composition in a small-scale ( ~ 10 km2) dolomite karst system. Integration of classic geochemical methods and multivariate statistical analysis revealed that the hydrofacies correlate directly with the lithofacies (dolomite) in the study area. At the same time, measured concentrations of Ca2+, Mg2+, Na+, Cl−, and HCO3− allow for a classification of the springs in three groups based on their ionic ratios. This classification highlights the spatial and temporal variability that can be encountered in dolomite karst systems, even on small spatial scales, that are relevant for water suppliers. Moreover, temporal observations of hydrochemical parameters show increasing trends of nitrate concentrations in all sampling points, though with different rates. The analysis of the stable isotopes δ15N–NO3 and δ18O–NO3 revealed that nitrification processes in forest floors and mineral soils are the main source of nitrate in most locations investigated. The findings of the present study highlight the necessity of a detailed temporal and spatial distributed monitoring to support water resources management in dolomitic karst aquifers.

Elucidating the water utilization strategy of trees during forest succession is a prerequisite for predicting the direction of forest succession. However, the water utilization characteristics of trees in forests across a successional gradient remain unclear. Here, we utilized the hydrogen and oxygen stable isotopes combined with the Bayesian mixed model (MixSIAR) to analyze the water utilization of dominant trees (Pinus massoniana, Castanea henryi, and Schima superba) in forests along a successional gradient in the Dinghushan Biosphere Reserve of China. Furthermore, we determined the primary factor affecting the water utilization of various trees based on variation partitioning analysis and a random forest model. Our results illustrated that in the early-successional forest, the water utilization ratios from shallow soil layers by P. massoniana were significantly lower than that in the mid-successional forest (51.3%–61.7% vs. 75.3%–81.4%), while its water utilization ratios from deep soil layers exhibited the opposite pattern (26.1%–30.1% vs. 9.0%–15.0%). Similarly, the ratios of water utilization from shallow soil layers by C. henryi (18.9%–29.5% vs. 32.4%–45.9%) and S. superba (10.0%–25.7% vs. 29.2%–66.4%) in the mid-successional forest were relatively lower than in the late-successional forest, whereas their water utilization ratios from deep soil layers showed the contrary tendency. Moreover, our results demonstrated that the diverse water utilization of each tree in different successional forests was mainly attributed to their distinct plant properties. Our findings highlight the increased percentage of water utilization of trees from shallow soil layers with forest succession, providing new insights for predicting the direction of forest succession under changing environments.

Knowledge is limited on the changes in tree water uptake over short timescales in shallow soils underlain by fractured rocks under humid climate conditions. This study explored the changing patterns of tree water uptake at two forests (camphor) and two orchards (peach and tea) over multi-day timescales. We collected water isotopic samples (δD and δ18O) from rainfall, spring, tree branch, soil and fissure between two rain events (8-day duration). The trees in the forest lands exhibited a larger variability in stem water isotopic composition than the trees in the orchards. Significantly different changing patterns of stem water isotopic composition were found between the orchards and the forest lands. On average, the fissure contributed most of the tree water uptake (46.1 ± 20.8%) compared to the soil layer (33.9 ± 17.7%) and shallow groundwater (20.0 ± 13.5%). Main water sources for the trees in this study shifted at a daily timescale. Compared to orchards, forest trees had a relatively large range of source water and a good water use strategy in the shallow soil–rock profile under humid climate conditions. This study emphasizes the importance of characterization of the changing patterns of stem water isotopic composition over short timescales.