Terrestrial ecosystems have been serving as a strong carbon sink that offsets one-quarter of anthropogenic CO₂ emissions. Carbon use efficiency (CUE), the percentage of photosynthesized carbon that is available for biomass production and other secondary carbon products, is one factor determining the carbon sink size. The global variation in CUE remains unclear, however, as recent reports disagree over the responses of CUE to temperature, dryness, forest types and stand age, and there are limited direct observations to constrain the related uncertainty. Here, we propose to infer CUE from spatially distributed observations of land–atmosphere CO₂ exchange from global eddy covariance sites based on the degree of ecosystem respiration–photosynthesis coupling. Across 2,737 site-years, CUE derived from eddy covariance observations is 0.43 ± 0.12, consistent with previous inventory-based estimates (0.47 ± 0.12, n = 301) but with a better representation of spatial–temporal variation in CUE. We find that CUE consistently decreases with temperature, precipitation, light availability and stand age, with a substantial difference in the baseline CUE among biomes. Importantly, CUE of deciduous forests is typically 15% higher than that of evergreen forests, suggesting that over the long-term deciduous forests are more efficient in using photosynthate. Our study advances the understanding of the global variation in CUE and provides insights to guide best practices of forest conservation, management and restoration for carbon sequestration.

Accurate estimation of photosynthesis is crucial for ecosystem carbon cycle modelling. Previous studies have established an empirical relationship between photosynthetic capacity (maximum carboxylation rate, V_cmax; maximum electron transport rate, J_max) and leaf chlorophyll (Chl) content to infer global photosynthetic capacity. However, the basis for the Chl‐V_cmax relationship remains unclear, which is further evidenced by the temporal variations in the Chl‐V_cmax relationship. Using multiple years of observations of four deciduous tree species, we found that V_cmax and J_max acclimate to photosynthetically active radiation faster (4–8 weeks) than Chl (10–12 weeks). This mismatch in temporal scales causes seasonality in the V_cmax‐Chl relationship. To account for the mismatch, we used a Chl fluorescence parameter (quantum yield of Photosystem II, Φ(II)) to tighten the relationship and found Φ(II) × Chl correlated with V_cmax and J_max (r² = 0.74 and 0.72 respectively) better than only Chl (r² = 0.7 and 0.6 respectively). It indicates that Φ(II) accounts for the short‐term adjustment of leaf photosynthetic capacity to light, which was not captured by Chl. Our study advances our understanding of the ecophysiological basis for the empirical V_cmax‐Chl relationship and how to better infer V_cmax from Chl and fluorescence, which guides large‐scale photosynthesis simulations using remote sensing.

Leaves acclimate to day-to-day fluctuating levels of photosynthetic photon flux density (PPFD) by adjusting their morphological and physiological parameters. Accurate estimation of these parameters under day-to-day fluctuating PPFD conditions benefits crop growth modeling and light environment management in greenhouses, although it remains challenging. We quantified the relationships between day-to-day PPFD changes over 6 days and light acclimation parameters for cucumber seedling leaves, including leaf mass per area (LMA), chlorophyll (Chl) a/b ratio, maximum net photosynthetic rate (P_nmax), maximum rate of ribulose-1,5-bisphosphate (RuBP) carboxylase/oxygenase (V_cmax), and maximum rate of electron transport (J_max). The last two parameters reflect the capacity of the photosynthetic partial reactions. We built linear regression models of these parameters based on average or time-weighted averages of daily PPFDs. For time-weighted averages of daily PPFDs, the influence of daily PPFD was given a specific weight. We employed three types of functions to calculate this weight, including linear, quadratic, and sigmoid derivative types. We then determined the trend of weights that estimated each parameter most accurately. Moreover, we introduced saturating functions to calibrate the average or time-weighted averages of daily PPFDs, considering that light acclimation parameters are usually saturated under high PPFDs. We found that time-weighted average PPFDs, in which recent PPFD levels had larger weights than earlier levels, better estimated LMA than average PPFDs. This suggests that recent PPFDs contribute more to LMA than earlier PPFDs. Except for the Chl a/b ratio, the average PPFDs estimated P_nmax, V_cmax, and J_max with acceptable accuracy. In contrast, time-weighted averages of daily PPFDs did not improve the estimation accuracy of these four parameters, possibly due to their low response rates and plasticity. Calibrating functions generally improved estimation of Chl a/b ratio, V_cmax, and J_max because of their saturating tendencies under high PPFDs. Our findings provide a reasonable approach to quantifying the extent to which the leaves acclimate to day-to-day fluctuating PPFDs, especially the extent of LMA.

Plants modify their functional traits in response to changing environmental conditions under climate change. However, it remains unclear whether tree planting alters patterns and acclimation of hydraulic traits across spatial scales. Here, we compiled a site‐level data set of hydraulic traits in natural (NF) and planted forests (PF) to examine trait patterns and relationships, quantified environmental and ecological drivers on ecosystem‐scale hydraulic traits of PF and NF across China, and computationally projected future trait acclimation using the space‐for‐time approach. We identified distinct differences in hydraulic traits between NF and PF, with PF exhibiting higher hydraulic safety but lower hydraulic efficiency than NF at the species level. NF demonstrated a trade‐off between hydraulic efficiency and safety, whereas PF exhibited a contrasting positive correlation between these traits. We confirmed that both environmental and ecological factors influence ecosystem‐scale hydraulic traits in NF and PF, although dominant drivers vary among specific traits. Projections under future climate scenarios suggest that, despite persistent differences in trait acclimation between NF and PF, both forest types tend to exhibit increased water‐use efficiency and enhanced drought resistance in response to rising precipitation and air dryness. These findings provide a valuable benchmark for estimating potential changes in hydraulic traits under climate change, supporting improved simulations of carbon and water fluxes in response to climate and anthropogenic influences.