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Quantifying and predicting variation in gross primary productivity (GPP) is important for accurate assessment of the ecosystem carbon budget under global change. Scaling traits to community scales for predicting ecosystem functions (i.e., GPP) remain challenging, while it is promising and well appreciated with the rapid development of trait-based ecology. In this study, we aim to integrate multiple plant traits with the recently developed trait-based productivity (TBP) theory, verify it via Bayesian structural equation modeling (SEM) and complementary independent effect analysis. We further distinguish the relative importance of different traits in explaining the variation in GPP. We apply the TBP theory based on plant community traits to a multi-trait dataset containing more than 13,000 measurements of approximately 2,500 species in Chinese forest and grassland systems. Remarkably, our SEM accurately predicts variation in annual and monthly GPP across China (R2 values of 0.87 and 0.73, respectively). Plant community traits play a key role. This study shows that integrating multiple plant functional traits into the TBP theory strengthens the quantification of ecosystem primary productivity variability and further advances understanding of the trait-productivity relationship. Our findings facilitate integration of the growing plant trait data into future ecological models. Integration of plant functional traits into trait-based productivity theory helps quantify primary productivity in terrestrial ecosystems. [ABSTRACT FROM AUTHOR]

Seasonal non-structural carbohydrate (NSC) dynamics in different organs can indicate the strategies trees use to cope with water stress; however, these dynamics remain poorly understood along a large precipitation gradient. In this study, we hypothesized that the correlation between water availability and NSC concentrations in different organs might be strengthened by decreasing precipitation in Pinus tabulaeformis Carr. forests in temperate China. Our results show that the concentrations of soluble sugars were lower in stems and coarse roots, and starch was higher in branches in the early growing season at drier sites. Throughout the growing season, the concentrations of soluble sugars increased in drier sites, especially for leaves, and remained stable in wetter sites, while starch concentrations were relatively stable in branches and stems at all sites. The NSC concentrations, mainly starch, decreased in coarse roots along the growing season at drier sites. Trees have a faster growth rate with an earlier cessation in active stem growth at drier sites. Interestingly, we also found a divergent relationship between NSCs in different organs and mean growing season water availability, and a stronger correlation was observed in drier sites. These results show that pine forests in arid and semi-arid regions of northern China exhibit different physiological responses to water availability, improving our understanding of the adaptive mechanisms of trees to water limitations in a warmer and drier climate. [ABSTRACT FROM AUTHOR]

Intensified anthropogenic activities have drastically altered many ecosystems, motivating the use of restoration to regain key ecosystem functions and services and to stem biodiversity losses. Restoration is particularly difficult when human activities have pushed an area into a new state with self‐reinforcing feedbacks. This study investigated a long‐term restoration project in a dryland ecosystem of the Tengger Desert in northwestern China, initiated in 1956. We analyzed shrub and grass cover for 49 yr after the installation of restoration infrastructure that altered external conditions (i.e., using packed straw to reduce wind erosion) and system state (by planting shrubs). After 37–40 yr, the re‐vegetation project was successful in restoring the system to a state similar to native vegetation, with high grass cover (30–50%), low shrub cover (8–10%), and a thick biological soil crust (biocrust). However, the shift to high grass cover did not begin until year 37, before which shrub cover was high (15–20%) and grasses were subdominant (usually <10%). The shift from shrub to grass dominance was abrupt, registering significant nonlinear changes over time and relative to a key driver of vegetation dynamics, estimated biocrust thickness. Biocrust thickness increased gradually over time, which reduced rainfall infiltration into deep soil and thus increased soil moisture available for the shallow‐rooted grasses. The shift from the bare soil state to the steppe state exhibited a long time lag, suggesting that it can take decades to determine whether dryland restoration efforts succeed. The results indicate that persistence might be critical to forcing desired state transitions and that dryland restoration can proceed as a series of time lags, punctuated by abrupt changes in ecosystem state. [ABSTRACT FROM AUTHOR]