Liyao Yu

Photosynthesis is a fundamental biological process that supports nearly all life on Earth. The tropics contribute the majority of global photosynthesis; however, this region also faces the greatest challenges in monitoring photosynthesis using either ground‐based methods (e.g., logistics in deploying eddy covariance flux towers) or remote sensing (e.g., cloud contamination). In this study, we tested the use of a low‐budget near‐infrared enabled cameras (typically less than $5000 USD) to monitor gross primary productivity (GPP) across 26 sites spanning diverse ecosystem types. Across these sites, near‐infrared enabled cameras were collocated with eddy covariance flux towers, which provide continuous measurements of carbon exchange used to estimate GPP. We found that the camera‐based near‐infrared reflectance and photosynthetic active radiation (NIRvP) are strongly correlated with GPP, with the coefficient of determination ranging from 0.35 to 0.92. One unit of camera‐based NIRvP corresponds to 13–130 mol CO ₂ /m ² /s in GPP, largely depending on the radiation intensity and plant functional types of the site. The relationship between NIRvP—GPP obtained at the sites was extrapolated globally to estimate GPP using cameras at non‐eddy covariance sites. Our study demonstrates the potential of using near‐infrared enabled cameras as a cost‐effective and reliable method for estimating GPP, offering a valuable alternative for monitoring ecosystem productivity, particularly in tropical regions with sparse eddy covariance observations.

Tree planting is regarded as one of the most cost-effective ways to mitigate climate change impacts. As part of the global tree planting movement, the tropical city-state of Singapore initiated a project to plant one million trees in 10 years. However, the environmental impacts (e.g., carbon sequestration, urban cooling) of this tree planting effort are challenging to assess, as historically, we lack an understanding of key plant traits (i.e., photosynthetic capacity, or V _cmax ) for species in tropical Asia. Here, a survey was conducted to assess key photosynthetic traits of the nine most popular tree species planted in Singapore and their short-term temperature response. We found a threefold interspecific variation in their photosynthetic capacities (e.g., V _cmax ranges from 20 to 60 μmol m ^–2 s ^–1 ) as well as a large discrepancy in their temperature response. Photosynthesis in some species (e.g., Cyrtophyllum fragrans and Terminalia catappa ) is more sensitive to rising temperature than others (e.g., Rhizophora apiculata and Barringtonia asiatica ), while a commonly used photosynthesis model consistently overestimates photosynthesis but underestimates many species’ temperature sensitivities. Species with lower temperature sensitivity of photosynthesis are likely to have a stronger ability to adjust leaf temperature. This study provides critical information on the temperature response of photosynthesis of tree species in tropical Asia, which can be used to guide tree planting in Singapore and broadly in Southeast Asia.

Diurnal patterns of photosynthesis of ecosystems are theoretically expected to mimic those of incoming solar radiation (SW) and peaks at noon. By examining global ecosystem eddy covariance observations, however, we found ecosystem photosynthesis often peaks before noon, indicating widespread midday or afternoon photosynthesis depression. While some studies have attributed this depression to stomatal closure, a strategy that limits water loss under high atmospheric vapor pressure deficit (VPD), leaf-level studies suggest that excess light can trigger photoprotective responses and also cause the depression. Following the hypothesis, we studied the gaps between ecosystem carbon uptake peak and that of SW (0.48 ± 0.26 h), and found that the gaps advance increases with SW even on site-days characterized by the lowest VPD. Biomes receiving the highest SW, such as savannas and evergreen broadleaf forests, exhibit the largest gap between carbon uptake peak and SW peak. Together, these findings indicate that excess light is a key yet underappreciated driver of ecosystem-scale midday depression. Incorporating light-driven photoprotective processes into terrestrial carbon models may improve simulations of diurnal carbon fluxes.

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.

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.

Plant leaves adjust their properties under changing photosynthetic photon flux density (PPFD) through acclimation. Accurate estimation of leaf photosynthetic properties (e.g., maximum photosynthetic rate, Amax) using experienced PPFD helps to estimate canopy photosynthesis. So far, Amax and its underlying properties could reportedly be estimated using a simple average PPFD (Qa) in recent days or weeks. We have recently proposed a time-weighted average PPFD (Qw), which improved the estimation of leaf mass per area but not that of photosynthetic properties of cucumber leaves. Results on cucumber leaves exposed to a one-day increase or decrease in PPFD at different timings suggested that responses of photosynthetic properties to an increase or decrease in PPFD were asymmetrical, with different extents and lengths of time lag. To incorporate these asymmetrical responses, we calculated a Q’a, in which Qa was calibrated by time-weighting the change of PPFD from the previous day, ΔQ(t). A test using measurement data under random day-to-day PPFD showed that this method using Q’a achieved more accurate estimations (determination coefficient, R2 = 0.77) of photosynthetic properties than those using Qa or Qw (R2 = 0.68). Moreover, the optimal weight trends of ΔQ(t) were asymmetrical, consistent with those suggested by our previous independent measurement data. This asymmetry was also confirmed by experiments, where photosynthetic properties acclimated faster to a decrease in PPFD than to an increase in PPFD. Our results indicate that these asymmetrical responses to changes in PPFD should be incorporated to improve the estimation of photosynthetic properties.

Tree planting is regarded as one of the most cost-effective ways to mitigate climate change impacts. As a part of the global tree planting movement, the tropical city-state of Singapore initiated a project to plant one million trees in 10 years. However, the environmental impacts (e.g., carbon sequestration, urban cooling) of this reforestation effort are challenging to assess as historically we lack understanding of key plant traits (i.e. photosynthetic capacity, or V _cmax ) for species in tropical Asia. Here, we conducted a comprehensive survey of key photosynthetic traits of the nine most popular tree species planted in Singapore and their short-term temperature dependence. We found a three-fold inter-species variation in their photosynthetic capacities (e.g., V _cmax ranges from 20 to 60 μmol m ⁻² s ⁻¹ ) as well as a large discrepancy in their temperature dependence. The photosynthesis of some species (e.g., Tembusu) is more sensitive to rising temperature than others (e.g., Mangroves) while a commonly-used photosynthesis model consistently overestimates photosynthesis but underestimates many species’ temperature sensitivities. The species with smaller temperature sensitivity of photosynthesis is likely related to their stronger ability to adjust leaf temperature via transpiration. Our study provides critical information on the temperature-dependence of photosynthesis of tree species in tropical Asia, which can be used to guide reforestation in Singapore and broadly in Southeast Asia.

Summary: The quantum yield ( α ) of photosynthesis represents the maximum efficiency of light use as indicated by the initial slope of photosynthetic light response curves. Understanding α is crucial for accurate modeling of photosynthesis and terrestrial carbon cycle. Despite its importance, the spatial and temporal variations in α at large scales remain largely elusive. We leveraged long-term eddy-covariance observations from 90 sites globally and examined the spatiotemporal variations in α due to climatic drivers, using statistical and machine learning approaches. We found significant spatial variability in α across and within biomes, primarily driven by atmospheric vapor pressure deficit and soil moisture variations. Meanwhile, the temporal changes in α are mainly driven by the negative effect of vapor pressure deficit, which weakens the positive effects of elevated CO ₂ and leaf area index. Our results highlight the dominant role of vapor pressure deficit in controlling the spatiotemporal variations of α as well as the unneglectable impacts of soil water content, CO ₂ , and leaf area on α . Those new results provide insights for improving the representation of α in ecosystem photosynthesis models.

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.