Partitioning controls on Amazon forest photosynthesis between environmental and biotic factors at hourly to interannual timescales

Effects of diffuse radiation fraction on crop light absorption, light use efficiency and gross primary production on an instantaneous scale in South China

The fraction of absorbed photosynthetically active radiation (FAPAR), light use efficiency (LUE), and gross primary productivity (GPP) are the key driving factors of crop production and ecological models. Diffuse radiation fraction (DF) has been reported to profoundly affect FAPAR, LUE and GPP, and its impact on a short time scale needs to be emphasized. Based on the field observations at noon local time during 2021-2022 and the Two-Leaf light use efficiency model, this study investigated the magnitudes of the DF effect on the canopy FAPAR, LUE, and GPP for the three different crops (peanut, soybean and corn) on an instantaneous scale in South China. Different from that of peanut and soybean, the FAPAR of corn increased linearly with the rise of DF. The instantaneous LUE of each crop was highly sensitive to DF, and its linear regression slope was greater than 1.0 g C MJ- 1. On average, the DF accounted for around 69-74% of the variations in the instantaneous LUE and 59-64% of the variations in the instantaneous GPP over the entire observation period. The sky conditions with a DF value between 0.45 and 0.66 were favorable for the carbon fixation of the three crops. The linear coupling strength between GPP and PAR under diffuse radiation (DF ≥ 0.5) was stronger than that under direct radiation (DF < 0.5). The results will be helpful in accurate estimating of FAPAR, LUE, GPP and even crop production in both South China and other similar regions.

The stomatal response to vapor pressure deficit drives the apparent temperature response of photosynthesis in tropical forests

As temperature rises, net carbon uptake in tropical forests decreases, but the underlying mechanisms are not well understood. High temperatures can limit photosynthesis directly, for example by reducing biochemical capacity, or indirectly through rising vapor pressure deficit (VPD) causing stomatal closure. To explore the independent effects of temperature and VPD on photosynthesis we analyzed photosynthesis data from the upper canopies of two tropical forests in Panama with Generalized Additive Models. Stomatal conductance and photosynthesis consistently decreased with increasing VPD, and statistically accounting for VPD increased the optimum temperature of photosynthesis (Topt) of trees from a VPD-confounded apparent Topt of c. 30-31°C to a VPD-independent Topt of c. 33-36°C, while for lianas no VPD-independent Topt was reached within the measured temperature range. Trees and lianas exhibited similar temperature and VPD responses in both forests, despite 1500 mm difference in mean annual rainfall. Over ecologically relevant temperature ranges, photosynthesis in tropical forests is largely limited by indirect effects of warming, through changes in VPD, not by direct warming effects of photosynthetic biochemistry. Failing to account for VPD when determining Topt misattributes the underlying causal mechanism and thereby hinders the advancement of mechanistic understanding of global warming effects on tropical forest carbon dynamics.

Different model assumptions about plant hydraulics and photosynthetic temperature acclimation yield diverging implications for tropical forest gross primary production under warming

Tropical forest photosynthesis can decline at high temperatures due to (1) biochemical responses to increasing temperature and (2) stomatal responses to increasing vapor pressure deficit (VPD), which is associated with increasing temperature. It is challenging to disentangle the influence of these two mechanisms on photosynthesis in observations, because temperature and VPD are tightly correlated in tropical forests. Nonetheless, quantifying the relative strength of these two mechanisms is essential for understanding how tropical gross primary production (GPP) will respond to climate change, because increasing atmospheric CO2 concentration may partially offset VPD-driven stomatal responses, but is not expected to mitigate the effects of temperature-driven biochemical responses. We used two terrestrial biosphere models to quantify how physiological process assumptions (photosynthetic temperature acclimation and plant hydraulic stress) and functional traits (e.g., maximum xylem conductivity) influence the relative strength of modeled temperature versus VPD effects on light-saturated GPP at an Amazonian forest site, a seasonally dry tropical forest site, and an experimental tropical forest mesocosm. By simulating idealized climate change scenarios, we quantified the divergence in GPP predictions under model configurations with stronger VPD effects compared with stronger direct temperature effects. Assumptions consistent with stronger direct temperature effects resulted in larger GPP declines under warming, while assumptions consistent with stronger VPD effects resulted in more resilient GPP under warming. Our findings underscore the importance of quantifying the role of direct temperature and indirect VPD effects for projecting the resilience of tropical forests in the future, and demonstrate that the relative strength of temperature versus VPD effects in models is highly sensitive to plant functional parameters and structural assumptions about photosynthetic temperature acclimation and plant hydraulics.

A leaf age-dependent light use efficiency model for remote sensing the gross primary productivity seasonality over pantropical evergreen broadleaved forests

Tropical and subtropical evergreen broadleaved forests (TEFs) contribute more than one-third of terrestrial gross primary productivity (GPP). However, the continental-scale leaf phenology-photosynthesis nexus over TEFs is still poorly understood to date. This knowledge gap hinders most light use efficiency (LUE) models from accurately simulating the GPP seasonality in TEFs. Leaf age is the crucial plant trait to link the dynamics of leaf phenology with GPP seasonality. Thus, here we incorporated the seasonal leaf area index of different leaf age cohorts into a widely used LUE model (i.e., EC-LUE) and proposed a novel leaf age-dependent LUE model (denoted as LA-LUE model). At the site level, the LA-LUE model (average R2 = .59, average root-mean-square error [RMSE] = 1.23 gC m-2 day-1) performs better than the EC-LUE model in simulating the GPP seasonality across the nine TEFs sites (average R2 = .18; average RMSE = 1.87 gC m-2 day-1). At the continental scale, the monthly GPP estimates from the LA-LUE model are consistent with FLUXCOM GPP data (R2 = .80; average RMSE = 1.74 gC m-2 day-1), and satellite-based GPP data retrieved from the global Orbiting Carbon Observatory-2 (OCO-2) based solar-induced chlorophyll fluorescence (SIF) product (GOSIF) (R2 = .64; average RMSE = 1.90 gC m-2 day-1) and the reconstructed TROPOspheric Monitoring Instrument SIF dataset using machine learning algorithms (RTSIF) (R2 = .78; average RMSE = 1.88 gC m-2 day-1). Typically, the estimated monthly GPP not only successfully represents the unimodal GPP seasonality near the Tropics of Cancer and Capricorn, but also captures well the bimodal GPP seasonality near the Equator. Overall, this study for the first time integrates the leaf age information into the satellite-based LUE model and provides a feasible implementation for mapping the continental-scale GPP seasonality over the entire TEFs.

Amazon forest biogeography predicts resilience and vulnerability to drought

Amazonia contains the most extensive tropical forests on Earth, but Amazon carbon sinks of atmospheric CO2 are declining, as deforestation and climate-change-associated droughts1-4 threaten to push these forests past a tipping point towards collapse5-8. Forests exhibit complex drought responses, indicating both resilience (photosynthetic greening) and vulnerability (browning and tree mortality), that are difficult to explain by climate variation alone9-17. Here we combine remotely sensed photosynthetic indices with ground-measured tree demography to identify mechanisms underlying drought resilience/vulnerability in different intact forest ecotopes18,19 (defined by water-table depth, soil fertility and texture, and vegetation characteristics). In higher-fertility southern Amazonia, drought response was structured by water-table depth, with resilient greening in shallow-water-table forests (where greater water availability heightened response to excess sunlight), contrasting with vulnerability (browning and excess tree mortality) over deeper water tables. Notably, the resilience of shallow-water-table forest weakened as drought lengthened. By contrast, lower-fertility northern Amazonia, with slower-growing but hardier trees (or, alternatively, tall forests, with deep-rooted water access), supported more-drought-resilient forests independent of water-table depth. This functional biogeography of drought response provides a framework for conservation decisions and improved predictions of heterogeneous forest responses to future climate changes, warning that Amazonia's most productive forests are also at greatest risk, and that longer/more frequent droughts are undermining multiple ecohydrological strategies and capacities for Amazon forest resilience.

Seasonality of reproduction in an ever-wet lowland tropical forest in Amazonian Ecuador

Flowering and fruiting phenology have been infrequently studied in the ever-wet hyperdiverse lowland forests of northwestern equatorial Amazonía. These Neotropical forests are typically called aseasonal with reference to climate because they are ever-wet, and it is often assumed they are also aseasonal with respect to phenology. The physiological limits to plant reproduction imposed by water and light availability are difficult to disentangle in seasonal forests because these variables are often temporally correlated, and both are rarely studied together, challenging our understanding of their relative importance as drivers of reproduction. Here we report on the first long-term study (18 years) of flowering and fruiting phenology in a diverse equatorial forest, Yasuní in eastern Ecuador, and the first to include a full suite of on-site monthly climate data. Using twice monthly censuses of 200 traps and >1000 species, we determined whether reproduction at Yasuní is seasonal at the community and species levels and analyzed the relationships between environmental variables and phenology. We also tested the hypothesis that seasonality in phenology, if present, is driven primarily by irradiance. Both the community- and species-level measures demonstrated strong reproductive seasonality at Yasuní. Flowering peaked in September-November and fruiting peaked in March-April, with a strong annual signal for both phenophases. Irradiance and rainfall were also highly seasonal, even though no month on average experienced drought (a month with <100 mm rainfall). Flowering was positively correlated with current or near-current irradiance, supporting our hypothesis that the extra energy available during the period of peak irradiance drives the seasonality of flowering at Yasuní. As Yasuní is representative of lowland ever-wet equatorial forests of northwestern Amazonía, we expect that reproductive phenology will be strongly seasonal throughout this region.

Large diurnal compensatory effects mitigate the response of Amazonian forests to atmospheric warming and drying

Photosynthesis and evapotranspiration in Amazonian forests are major contributors to the global carbon and water cycles. However, their diurnal patterns and responses to atmospheric warming and drying at regional scale remain unclear, hindering the understanding of global carbon and water cycles. Here, we used proxies of photosynthesis and evapotranspiration from the International Space Station to reveal a strong depression of dry season afternoon photosynthesis (by 6.7 ± 2.4%) and evapotranspiration (by 6.1 ± 3.1%). Photosynthesis positively responds to vapor pressure deficit (VPD) in the morning, but negatively in the afternoon. Furthermore, we projected that the regionally depressed afternoon photosynthesis will be compensated by their increases in the morning in future dry seasons. These results shed new light on the complex interplay of climate with carbon and water fluxes in Amazonian forests and provide evidence on the emerging environmental constraints of primary productivity that may improve the robustness of future projections.

Seasonal controlling factors of CO2 exchange in a semiarid shrubland in the Chihuahuan Desert, Mexico

The still significant uncertainties associated with the future capacity of terrestrial systems to mitigate climate change are linked to the lack of knowledge of the biotic and abiotic processes that regulate CO₂ net ecosystem exchange (NEE) in space/time. Mainly, rates and controls of CO₂ exchange from arid ecosystems, despite dominating the global trends in interannual variability of the terrestrial CO₂ sink capacity, are probably the most poorly understood of all. We present a study on rates and controls of CO₂ exchange measured with the eddy covariance (EC) technique in the Chihuahuan Desert in the Northeast of Mexico, to understand how the environmental controls of the NEE switch throughout the year using a multilevel approach. Since this is a water-limited ecosystem, the hydroecological year, based on the last precipitation and the decay of air temperature, was used to compare the wet (from May 16 to October 30, 2019) and dry (November 1, 2019 to May 15, 2020) seasons' controlling mechanisms, both at diurnal and nocturnal times. Annual NEE was -303.5 g C m^-2, with a cumulative R_eco of 537.7 g C m^-2 and GPP of 841.3 g C m^-2. NEE showed radiation, temperature, and soil moisture sensitivity along the day, however, shifts in these controls along the year and between seasons were identified. The winter precipitations during the dry season led to fast C release followed by lagged C uptake. Despite this flux pulse, the ecosystem was a net sink throughout most of the year because the local vegetation is well adapted to grow and uptake C under these arid conditions, even during the dry season. Understanding the controls of the sink-source shifts is relevant since the predictions for future climate include changes in the precipitation patterns.

Water use efficiency control for a maize field under mulched drip irrigation

Agricultural ecosystem water use efficiency (WUE) is an important indicator reflecting carbon-water coupling, but its control mechanisms in managed fields remain unclear. In order to reveal the influencing factors of WUE in the agricultural field under mulched drip irrigation (DM), we carried out the 8-year continuous observations in a maize field from Northwestern China. The structural equation model, relative importance analysis and principal component analysis were used to quantify the regulation effects of environmental and biological factors on WUE at different time scales, in different growth stages and under different hydrothermal conditions. The results showed that annual WUE varied between 2.18 g C Kg^-1 H₂O and 3.60 g C Kg^-1 H₂O, with a multi-year mean of 2.91 g C Kg^-1 H₂O. The total effects of air temperature on the daily WUE in the whole growth period, the vegetative growth stage, the warm and dry years, the cold and wet years, and the warm and wet years were the largest, with values of 0.61, 0.80, 0.70, 0.70 and 0.91 respectively. However, vapor pressure deficit and net radiation had the largest total effect in the cold and dry years (-0.63) and the reproductive growth stage (-0.49), respectively. Leaf biomass played a leading role in regulating the daily and interannual WUE, and the relative importance of leaf biomass to WUE in the vegetative growth stage was up to 75 %. In the warm and wet years, the relative importance of root biomass to WUE was 33 %, slightly higher than that of leaf biomass (31 %). At the same time, we found that Ta has the potential to increase WUE under future climate warming. Our results improve the understanding of carbon-water coupling mechanisms and provide important enlightenment on how crop ecosystems should adapt to future climate change.

Aerosol pollution alters the diurnal dynamics of sun and shade leaf photosynthesis through different mechanisms

Anthropogenic aerosols have been shown to perturb CO₂ exchange between the vegetation and the atmosphere. However, the climate effects of aerosols through carbon cycle feedback still have significant uncertainties. Taking advantage of the periodic fluctuations of aerosol loading in Beijing, we intensively measured the diurnal course of leaf microclimates and photosynthesis under different aerosol conditions during the growing season in 2014 and 2015. We found that increasing aerosol loadings altered the diurnal course of microclimates and thus sun and shade leaf photosynthesis. Our mechanistic photosynthesis model experiments further showed that aerosol-induced increase in sun leaf photosynthesis occurred around noon and afternoon, mainly by alleviating the depression of photosynthesis caused by high leaf temperature and leaf-air vapour pressure deficit. Meanwhile, aerosols enhanced shade leaf photosynthesis throughout the day by mitigating the light limitation within the canopy, with the highest increase occurring around noon. Overall, our study suggested that aerosol's diffuse fertilization effect, cooling effect and the accompanying low leaf-air vapour pressure deficit collectively drove the changes in the diurnal courses of sun and shade leaf photosynthesis. Our results provided an important benchmark for assessing how anthropogenic aerosols regulate ecosystem C balance under different meteorological conditions.

Seasonal shifts in isoprenoid emission composition from three hyperdominant tree species in central Amazonia

Volatile isoprenoids regulate plant performance and atmospheric processes, and Amazon forests comprise the dominant source to the global atmosphere. Still, there is a poor understanding of how isoprenoid emission capacities vary in response to ecophysiological and environmental controls in Amazonian ecosystems. We measured isoprenoid emission capacities of three Amazonian hyperdominant tree species - Protium hebetatum, Eschweilera grandiflora, Eschweilera coriacea - across seasons and along a topographic and edaphic environmental gradient in the central Amazon. From wet to dry season, both photosynthesis and isoprene emission capacities strongly declined, while emissions increased among the heavier isoprenoids: monoterpenes and sesquiterpenes. Plasticity across habitats was most evident in P. hebetatum, which emitted sesquiterpenes only in the dry season, at rates that significantly increased along the hydro-topographic gradient from white sands (shallow root water access) to uplands (deep water table). We suggest that emission composition shifts are part of a plastic response to increasing abiotic stress (e.g. heat and drought) and reduced photosynthetic supply of substrates for isoprenoid synthesis. Our comprehensive measurements suggest that more emphasis should be placed on other isoprenoids, besides isoprene, in the context of abiotic stress responses. Shifting emission compositions have implications for atmospheric responses because of the strong variation in reactivity among isoprenoid compounds.

Soil moisture regulates warming responses of autumn photosynthetic transition dates in subtropical forests

Autumn phenology plays a key role in regulating the terrestrial carbon and water balance and their feedbacks to the climate. However, the mechanisms underlying autumn phenology are still poorly understood, especially in subtropical forests. In this study, we extracted the autumn photosynthetic transition dates (APTD) in subtropical China over the period 2003-2017 based on a global, fine-resolution solar-induced chlorophyll fluorescence (SIF) dataset (GOSIF) using four fitting methods, and then explored the temporal-spatial variations of APTD and its underlying mechanisms using partial correlation analysis and machine learning methods. We further predicted the APTD shifts under future climate warming conditions by applying process-based and machine learning-based models. We found that the APTD was significantly delayed, with an average rate of 7.7 days per decade, in subtropical China during 2003-2017. Both partial correlation analysis and machine learning methods revealed that soil moisture was the primary driver responsible for the APTD changes in southern subtropical monsoon evergreen forest (SEF) and middle subtropical evergreen forest (MEF), whereas solar radiation controlled the APTD variations in the northern evergreen-broadleaf deciduous mixed forest (NMF). Combining the effects of temperature, soil moisture and radiation, we found a significantly delayed trend in APTD during the 2030-2100 period, but the trend amplitude (0.8 days per decade) was much weaker than that over 2003-2017. In addition, we found that machine learning methods outperformed process-based models in projecting APTD. Our findings generate from different methods highlight that soil moisture is one of the key players in determining autumn photosynthetic phenological processes in subtropical forests. To comprehensively understand autumn phenological processes, in-situ manipulative experiments are urgently needed to quantify the contributions of different environmental and physiological factors in regulating plants' response to ongoing climate change.

Spatiotemporal Variation in Gross Primary Productivity and Their Responses to Climate in the Great Lakes Region of Sub-Saharan Africa during 2001–2020

The impacts of climate on spatiotemporal variations of eco-physiological and bio-physical factors have been widely explored in previous research, especially in dry areas. However, the understanding of gross primary productivity (GPP) variations and its interactions with climate in humid and semi-humid areas remains unclear. Based on hyperspectral satellite remotely sensed vegetation phenology processes and related indices and the re-analysed climate datasets, we investigated the seasonal and inter-annual variability of GPP by using different light-use efficiency (LUE) models including the Carnegie-Ames-Stanford Approaches (CASA) model, vegetation photosynthesis models (VPMChl and VPMCanopy) and Moderate Resolution Imaging Spectroradiometer (MODIS) GPP products (MOD17A2H) during 2001–2020 over the Great Lakes region of Sub-Saharan Africa (GLR-SSA). The models’ validation against the in situ GPP-based upscaled observations (GPP-EC) indicated that these three models can explain 82%, 79% and 80% of GPP variations with root mean square error (RMSE) values of 5.7, 8.82 and 10.12 g C·m−2·yr−1, respectively. The spatiotemporal variations of GPP showed that the GLR-SSA experienced: (i) high GPP values during December-May; (ii) high annual GPP increase during 2002–2003, 2011–2013 and 2015–2016 and annual decreasing with a marked alternation in other years; (iii) evergreen broadleaf forests having the highest GPP values while grasslands and croplands showing lower GPP values. The spatial correlation between GPP and climate factors indicated 60% relative correlation between precipitation and GPP and 65% correction between surface air temperature and GPP. The results also showed high GPP values under wet conditions (in rainy seasons and humid areas) that significantly fell by the rise of dry conditions (in long dry season and arid areas). Therefore, these results showed that climate factors have potential impact on GPP variability in this region. However, these findings may provide a better understanding of climate implications on GPP variability in the GLR-SSA and other tropical climate zones.

Forest fragmentation impacts the seasonality of Amazonian evergreen canopies

Predictions of the magnitude and timing of leaf phenology in Amazonian forests remain highly controversial. Here, we use terrestrial LiDAR surveys every two weeks spanning wet and dry seasons in Central Amazonia to show that plant phenology varies strongly across vertical strata in old-growth forests, but is sensitive to disturbances arising from forest fragmentation. In combination with continuous microclimate measurements, we find that when maximum daily temperatures reached 35 °C in the latter part of the dry season, the upper canopy of large trees in undisturbed forests lost plant material. In contrast, the understory greened up with increased light availability driven by the upper canopy loss, alongside increases in solar radiation, even during periods of drier soil and atmospheric conditions. However, persistently high temperatures in forest edges exacerbated the upper canopy losses of large trees throughout the dry season, whereas the understory in these light-rich environments was less dependent on the altered upper canopy structure. Our findings reveal a strong influence of edge effects on phenological controls in wet forests of Central Amazonia.

Seasonal Variations of Solar-Induced Fluorescence, Precipitation, and Carbon Dioxide Over the Amazon

Previous studies suggested that the Amazon, the largest rainforest on Earth, changes from a CO₂ sink to a CO₂ source during the dry/fire season. However, the biospheric contributions to atmospheric CO₂ are not well understood during the two main seasons, the dry/fire season and the wet season. In this article, we utilize Orbiting Carbon Observatory 2 (OCO-2) Solar-Induced Fluorescence (SIF) to explore photosynthetic activity during the different seasons. The spatiotemporal variability of OCO-2 SIF, OCO-2 CO₂, precipitation, and burned area are investigated over the Amazon from September 2014 to December 2019. Averaging over the entire Amazon region, we found a positive temporal correlation (0.94) between OCO-2 SIF and Global Precipitation Climatology Project precipitation and a negative temporal correlation (-0.64) between OCO-2 SIF and OCO-2 CO₂, consistent with the fact that precipitation enhances photosynthesis, which results in higher values for SIF and rate of removal of CO₂ from the atmosphere above the Amazon region. We also observed seasonality in the spatial variability of these variables within the Amazon region. During the dry/fire (August-October) season, low SIF values, low precipitation, high vapor pressure deficit (VPD), large burned areas, and high atmospheric CO₂ are mainly found over the southern Amazon region. In contrast, during the wet season (January-March), high SIF values, high precipitation, low VPD, smaller burned areas, and low CO₂ are found over both the central and southern Amazon regions. The seasonal difference in SIF suggests that photosynthetic activity is reduced during the dry/fire season relative to the wet season as a result of low precipitation and high VPD, especially over the southern Amazon region, which will contribute to more CO₂ in the atmosphere during the dry/fire season.

Environmental factors modulate the diffuse fertilization effect on gross primary productivity across Chinese ecosystems

Diffuse radiation allocated by cloud cover and aerosols can promote vegetation photosynthesis, which is known as the diffuse fertilization effect (DFE). As an important uncertain factor regulating the DFE, understanding the role of environmental conditions in the response of terrestrial ecosystems to diffuse radiation is vital for quantitative and intensive studies. By using a light use efficiency model and statistical methods with satellite data and ChinaFLUX observation data, the optimal environmental range of DFE was estimated, the indirect role of vapor pressure deficit (VPD) and air temperature (T_a) on DFE was explored, and the relative contribution of diffuse photosynthetically active radiation (PAR_dif) on gross primary productivity (GPP) was analyzed across Chinese ecosystems under different sky conditions. The results showed that the DFE increased with leaf area index (LAI), but distributed a unimodal curve along with VPD and T_a, both of which had an optimum range that was lower in the forest (or cropland) and higher in the grass (or desert) ecosystem. When considering the co-effect of VPD and T_a, the strongest positive effect of DFE was found at 0-5 h Pa and 20-25 °C. Based on path analysis, PAR_dif promoted GPP and served as the main controlling factor in forest ecosystems predominantly through a direct pathway from half-hourly to the daily scale, while T_a and VPD occupied the dominant position at single-canopy ecosystem sites. When the aerosol optical depth (AOD) increased, the relative contribution of PAR_dif increased in multiple-canopy ecosystems and decreased in single-canopy ecosystems; when the sky conditions changed from sunny to cloudy, the relative contribution of PAR_dif was higher in the forest ecosystem and increased significantly in the grass ecosystem. These findings offer a more comprehensive understanding of the environmental effects of regulating DFE on GPP across ecosystems.

Thermal optima of gross primary productivity are closely aligned with mean air temperatures across Australian wooded ecosystems

Gross primary productivity (GPP) of wooded ecosystems (forests and savannas) is central to the global carbon cycle, comprising 67%-75% of total global terrestrial GPP. Climate change may alter this flux by increasing the frequency of temperatures beyond the thermal optimum of GPP (T_opt ). We examined the relationship between GPP and air temperature (Ta) in 17 wooded ecosystems dominated by a single plant functional type (broadleaf evergreen trees) occurring over a broad climatic gradient encompassing five ecoregions across Australia ranging from tropical in the north to Mediterranean and temperate in the south. We applied a novel boundary-line analysis to eddy covariance flux observations to (a) derive ecosystem GPP-Ta relationships and T_opt (including seasonal analyses for five tropical savannas); (b) quantitatively and qualitatively assess GPP-Ta relationships within and among ecoregions; (c) examine the relationship between T_opt and mean daytime air temperature (MDTa) across all ecosystems; and (d) examine how down-welling short-wave radiation (Fsd) and vapour pressure deficit (VPD) influence the GPP-Ta relationship. GPP-Ta relationships were convex parabolas with narrow curves in tropical forests, tropical savannas (wet season), and temperate forests, and wider curves in temperate woodlands, Mediterranean woodlands, and tropical savannas (dry season). Ecosystem T_opt ranged from 15℃ (temperate forest) to 32℃ (tropical savanna-wet and dry seasons). The shape of GPP-Ta curves was largely determined by daytime Ta range, MDTa, and maximum GPP with the upslope influenced by Fsd and the downslope influenced by VPD. Across all ecosystems, there was a strong positive linear relationship between T_opt and MDTa (Adjusted R² : 0.81; Slope: 1.08) with T_opt exceeding MDTa by >1℃ at all but two sites. We conclude that ecosystem GPP has adjusted to local MDTa within Australian broadleaf evergreen forests and that GPP is buffered against small Ta increases in the majority of these ecosystems.

Accurate Simulation of Both Sensitivity and Variability for Amazonian Photosynthesis: Is It Too Much to Ask?

Estimates of Amazon rainforest gross primary productivity (GPP) differ by a factor of 2 across a suite of three statistical and 18 process models. This wide spread contributes uncertainty to predictions of future climate. We compare the mean and variance of GPP from these models to that of GPP at six eddy covariance (EC) towers. Only one model's mean GPP across all sites falls within a 99% confidence interval for EC GPP, and only one model matches EC variance. The strength of model response to climate drivers is related to model ability to match the seasonal pattern of the EC GPP. Models with stronger seasonal swings in GPP have stronger responses to rain, light, and temperature than does EC GPP. The model to data comparison illustrates a trade-off inherent to deterministic models between accurate simulation of a mean (average) and accurate responsiveness to drivers. The trade-off exists because all deterministic models simplify processes and lack at least some consequential driver or interaction. If a model's sensitivities to included drivers and their interactions are accurate, then deterministically predicted outcomes have less variability than is realistic. If a GPP model has stronger responses to climate drivers than found in data, model predictions may match the observed variance and seasonal pattern but are likely to overpredict GPP response to climate change. High or realistic variability of model estimates relative to reference data indicate that the model is hypersensitive to one or more drivers.

Understanding water and energy fluxes in the Amazonia: Lessons from an observation-model intercomparison

Tropical forests are an important part of global water and energy cycles, but the mechanisms that drive seasonality of their land-atmosphere exchanges have proven challenging to capture in models. Here, we (1) report the seasonality of fluxes of latent heat (LE), sensible heat (H), and outgoing short and longwave radiation at four diverse tropical forest sites across Amazonia-along the equator from the Caxiuanã and Tapajós National Forests in the eastern Amazon to a forest near Manaus, and from the equatorial zone to the southern forest in Reserva Jaru; (2) investigate how vegetation and climate influence these fluxes; and (3) evaluate land surface model performance by comparing simulations to observations. We found that previously identified failure of models to capture observed dry-season increases in evapotranspiration (ET) was associated with model overestimations of (1) magnitude and seasonality of Bowen ratios (relative to aseasonal observations in which sensible was only 20%-30% of the latent heat flux) indicating model exaggerated water limitation, (2) canopy emissivity and reflectance (albedo was only 10%-15% of incoming solar radiation, compared to 0.15%-0.22% simulated), and (3) vegetation temperatures (due to underestimation of dry-season ET and associated cooling). These partially compensating model-observation discrepancies (e.g., higher temperatures expected from excess Bowen ratios were partially ameliorated by brighter leaves and more interception/evaporation) significantly biased seasonal model estimates of net radiation (R_n ), the key driver of water and energy fluxes (LE ~ 0.6 R_n and H ~ 0.15 R_n ), though these biases varied among sites and models. A better representation of energy-related parameters associated with dynamic phenology (e.g., leaf optical properties, canopy interception, and skin temperature) could improve simulations and benchmarking of current vegetation-atmosphere exchange and reduce uncertainty of regional and global biogeochemical models.

Assessment of SITE for CO2 and Energy Fluxes Simulations in a Seasonally Dry Tropical Forest (Caatinga Ecosystem)

Although seasonally dry tropical forests are considered invaluable to a greater understanding of global carbon fluxes, they remain as one of the ecosystems with the fewest observations. In this context, ecological and ecosystem models can be used as alternative methods to answer questions related to the interactions between the biosphere and the atmosphere in dry forests. The objective of this study was to calibrate the simple tropical ecosystem model (SITE) and evaluate its performance in characterizing the annual and seasonal behavior of the energy and carbon fluxes in a preserved fragment of the Caatinga biome. The SITE model exhibited reasonable applicability to simulate variations in CO2 and energy fluxes (r > 0.7). Results showed that the calibrated set of vegetation parameters adequately simulated gross primary productivity (GPP) and net ecosystem CO2 exchange (NEE). The SITE model was also able to accurately retrieve the time at which daily GPP and NEE peaked. The model was able to simulate the partition of the available energy into sensible and latent heat fluxes and soil heat flux when the calibrated parameters were used. Therefore, changes in the dynamics of dry forests should be taken into consideration in the modeling of ecosystem carbon balances.

A Bornean peat swamp forest is a net source of carbon dioxide to the atmosphere

Tropical peat forests are a globally important reservoir of carbon, but little is known about CO₂ exchange on an annual basis. We measured CO₂ exchange between the atmosphere and tropical peat swamp forest in Sarawak, Malaysia using the eddy covariance technique over 4 years from 2011 to 2014. The CO₂ fluxes varied between seasons and years. A small carbon uptake took place during the rainy season at the beginning of 2011, while a substantial net efflux of >600 g C/m² occurred over a 2 month period in the middle of the dry season. Conversely, the peat ecosystem was a source of carbon during both the dry and rainy seasons in subsequent years and more carbon was lost during the rainy season relative to the dry season. Our results demonstrate that the forest was a net source of CO₂ to the atmosphere during every year of measurement with annual efflux ranging from 183 to 632 g C m^-2  year^-1 , noting that annual flux values were sensitive to gap filling methodology. This is in contrast to the typical view of tropical peat forests which must have acted as net C sinks over time scales of centuries to millennia to create the peat deposits. Path analyses revealed that the gross primary productivity (GPP) and ecosystem respiration (RE) were primarily affected by vapour pressure deficit (VPD). Results suggest that future increases in VPD could further reduce the C sink strength and result in additional net CO₂ losses from this tropical peat swamp forest in the absence of plant acclimation to such changes in atmospheric dryness.

Empirical evidence for resilience of tropical forest photosynthesis in a warmer world

Tropical forests may be vulnerable to climate change^1-3 if photosynthetic carbon uptake currently operates near a high temperature limit^4-6. Predicting tropical forest function requires understanding the relative contributions of two mechanisms of high-temperature photosynthetic declines: stomatal limitation (H1), an indirect response due to temperature-associated changes in atmospheric vapour pressure deficit (VPD)⁷, and biochemical restrictions (H2), a direct temperature response^8,9. Their relative control predicts different outcomes-H1 is expected to diminish with stomatal responses to future co-occurring elevated atmospheric [CO₂], whereas H2 portends declining photosynthesis with increasing temperatures. Distinguishing the two mechanisms at high temperatures is therefore critical, but difficult because VPD is highly correlated with temperature in natural settings. We used a forest mesocosm to quantify the sensitivity of tropical gross ecosystem productivity (GEP) to future temperature regimes while constraining VPD by controlling humidity. We then analytically decoupled temperature and VPD effects under current climate with flux-tower-derived GEP trends in situ from four tropical forest sites. Both approaches showed consistent, negative sensitivity of GEP to VPD but little direct response to temperature. Importantly, in the mesocosm at low VPD, GEP persisted up to 38 °C, a temperature exceeding projections for tropical forests in 2100 (ref. ¹⁰). If elevated [CO₂] mitigates VPD-induced stomatal limitation through enhanced water-use efficiency as hypothesized^9,11, tropical forest photosynthesis may have a margin of resilience to future warming.

Sensitivity of gross primary productivity to climatic drivers during the summer drought of 2018 in Europe

In summer 2018, Europe experienced a record drought, but it remains unknown how the drought affected ecosystem carbon dynamics. Using observations from 34 eddy covariance sites in different biomes across Europe, we studied the sensitivity of gross primary productivity (GPP) to environmental drivers during the summer drought of 2018 versus the reference summer of 2016. We found a greater drought-induced decline of summer GPP in grasslands (-38%) than in forests (-10%), which coincided with reduced evapotranspiration and soil water content (SWC). As compared to the 'normal year' of 2016, GPP in different ecosystems exhibited more negative sensitivity to summer air temperature (Ta) but stronger positive sensitivity to SWC during summer drought in 2018, that is, a stronger reduction of GPP with soil moisture deficit. We found larger negative effects of Ta and vapour pressure deficit (VPD) but a lower positive effect of photosynthetic photon flux density on GPP in 2018 compared to 2016, which contributed to reduced summer GPP in 2018. Our results demonstrate that high temperature-induced increases in VPD and decreases in SWC aggravated drought impacts on GPP. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

Interactive effects of air pollutants and atmospheric moisture stress on aspen growth and photosynthesis along an urban-rural gradient

Atmospheric pollution could significantly alter tree growth independently and synergistically with meteorological conditions. North China offers a natural experiment for studying how plant growth responds to air pollution under different meteorological conditions, where rapid economic growth has led to severe air pollution and climate changes increase drought stress. Using a single aspen clone (Populus euramericana Neva.) as a 'phytometer', we conducted three experiments to monitor aspen leaf photosynthesis and stem growth during in situ exposure to atmospheric pollutants along the urban-rural gradient around Beijing. We used stepwise model selection to select the best multiple linear model, and we used binned regression to estimate the effects of air pollutants, atmospheric moisture stress and their interactions on aspen leaf photosynthesis and growth. Our results indicated that ozone (O₃) and vapor pressure deficit (VPD) inhibited leaf photosynthesis and stem growth. The interactive effect of O₃ and VPD resulted in a synergistic response: as the concentration of O₃ increased, the negative impact of VPD on leaf photosynthesis and stem growth became more severe. We also found that nitrogen (N) deposition had a positive effect on stem growth, which may have been caused by an increase in canopy N uptake, although this hypothesis needs to be confirmed by further studies. The positive impact of aerosol loading may be due to diffuse radiation fertilization effects. Given the decline in aerosols and N deposition amidst increases in O₃ concentration and drought risk, the negative effects of atmospheric pollution on tree growth may be aggravated in North China. In addition, the interaction between O₃ and VPD may lead to a further reduction in ecosystem productivity.

Carbon Dynamics in a Human-Modified Tropical Forest: A Case Study Using Multi-Temporal LiDAR Data

Tropical forests hold significant amounts of carbon and play a critical role on Earth´s climate system. To date, carbon dynamics over tropical forests have been poorly assessed, especially over vast areas of the tropics that have been affected by some type of disturbance (e.g., selective logging, understory fires, and fragmentation). Understanding the multi-temporal dynamics of carbon stocks over human-modified tropical forests (HMTF) is crucial to close the carbon cycle balance in the tropics. Here, we used multi-temporal and high-spatial resolution airborne LiDAR data to quantify rates of carbon dynamics over a large patch of HMTF in eastern Amazon, Brazil. We described a robust approach to monitor changes in aboveground forest carbon stocks between 2012 and 2018. Our results showed that this particular HMTF lost 0.57 m·yr−1 in mean forest canopy height and 1.38 Mg·C·ha−1·yr−1 of forest carbon between 2012 and 2018. LiDAR-based estimates of Aboveground Carbon Density (ACD) showed progressive loss through the years, from 77.9 Mg·C·ha−1 in 2012 to 53.1 Mg·C·ha−1 in 2018, thus a decrease of 31.8%. Rates of carbon stock changes were negative for all time intervals analyzed, yielding average annual carbon loss rates of −1.34 Mg·C·ha−1·yr−1. This suggests that this HMTF is acting more as a source of carbon than a sink, having great negative implications for carbon emission scenarios in tropical forests. Although more studies of forest dynamics in HMTFs are necessary to reduce the current remaining uncertainties in the carbon cycle, our results highlight the persistent effects of carbon losses for the study area. HMTFs are likely to expand across the Amazon in the near future. The resultant carbon source conditions, directly associated with disturbances, may be essential when considering climate projections and carbon accounting methods.

High ecosystem stability of evergreen broadleaf forests under severe droughts

Global increase in drought occurrences threatens the stability of terrestrial ecosystem functioning. Evergreen broadleaf forests (EBFs) keep leaves throughout the year, and therefore could experience higher drought risks than other biomes. However, the recent temporal variability of global vegetation productivity or land carbon sink is mainly driven by non-evergreen ecosystems, such as semiarid grasslands, croplands, and boreal forests. Thus, we hypothesize that EBFs have higher stability than other biomes under the increasingly extreme droughts. Here we use long-term Standardized Precipitation and Evaporation Index (SPEI) data and satellite-derived Enhanced Vegetation Index (EVI) products to quantify the temporal stability (ratio of mean annual EVI to its SD), resistance (ability to maintain its original levels during droughts), and resilience (rate of EVI recovering to pre-drought levels) at biome and global scales. We identified significantly increasing trends of annual drought severity (SPEI range: -0.08 to -1.80), area (areal fraction range: 2%-19%), and duration (month range: 7.9-9.1) in the EBF biome over 2000-2014. However, EBFs showed the highest resistance of EVI to droughts, but no significant differences in resilience of EVI to droughts were found among biomes (forests, grasslands, savannas, and shrublands). Global resistance and resilience of EVI to droughts were largely affected by temperature and solar radiation. These findings suggest that EBFs have higher stability than other biomes despite the greater drought exposure. Thus, the conservation of EBFs is critical for stabilizing global vegetation productivity and land carbon sink under more-intense climate extremes in the future.

The exchange of water and energy between a tropical peat forest and the atmosphere: Seasonal trends and comparison against other tropical rainforests

Tropical rainforests control the exchange of water and energy between the land surface and the atmosphere near the equator and thus play an important role in the global climate system. Measurements of latent (LE) and sensible heat exchange (H) have not been synthesized across global tropical rainforests to date, which can help place observations from individual tropical forests in a global context. We measured LE and H for four years in a tropical peat forest ecosystem in Sarawak, Malaysian Borneo using eddy covariance, and hypothesize that the study ecosystem will exhibit less seasonal variability in turbulent fluxes than other tropical ecosystems as soil water is not expected to be limiting in a tropical forested wetland. LE and H show little variability across seasons in the study ecosystem, with LE values on the order of 11 MJ m^-2 day and H on the order of 3 MJ m^-2 day^-1. Annual evapotranspiration (ET) did not differ among years and averaged 1579 ± 47 mm year^-1. LE exceeded characteristic values from other tropical rainforest ecosystems in the FLUXNET2015 database with the exception of GF-Guy near coastal French Guyana, which averaged 8-11 MJ m^-2 day^-1. The Bowen ratio (Bo) in tropical rainforests in the FLUXNET2015 database either exhibited little seasonal trend, one seasonal peak, or two peaks. Volumetric water content (VWC) and VPD explained a trivial amount of the variability of LE and Bo in some of the tropical rainforests including the study ecosystem, but were strong controls in others, suggesting differences in stomatal regulation and/or the partitioning between evaporation and transpiration. Results demonstrate important differences in the seasonal patterns in water and energy exchange across different tropical rainforest ecosystems that need to be understood to quantify how ongoing changes in tropical rainforest extent will impact the global climate system.

Prolonged tropical forest degradation due to compounding disturbances: Implications for CO2 and H2 O fluxes

Drought, fire, and windstorms can interact to degrade tropical forests and the ecosystem services they provide, but how these forests recover after catastrophic disturbance events remains relatively unknown. Here, we analyze multi-year measurements of vegetation dynamics and function (fluxes of CO₂ and H₂ O) in forests recovering from 7 years of controlled burns, followed by wind disturbance. Located in southeast Amazonia, the experimental forest consists of three 50-ha plots burned annually, triennially, or not at all from 2004 to 2010. During the subsequent 6-year recovery period, postfire tree survivorship and biomass sharply declined, with aboveground C stocks decreasing by 70%-94% along forest edges (0-200 m into the forest) and 36%-40% in the forest interior. Vegetation regrowth in the forest understory triggered partial canopy closure (70%-80%) from 2010 to 2015. The composition and spatial distribution of grasses invading degraded forest evolved rapidly, likely because of the delayed mortality. Four years after the experimental fires ended (2014), the burned plots assimilated 36% less carbon than the Control, but net CO₂ exchange and evapotranspiration (ET) had fully recovered 7 years after the experimental fires ended (2017). Carbon uptake recovery occurred largely in response to increased light-use efficiency and reduced postfire respiration, whereas increased water use associated with postfire growth of new recruits and remaining trees explained the recovery in ET. Although the effects of interacting disturbances (e.g., fires, forest fragmentation, and blowdown events) on mortality and biomass persist over many years, the rapid recovery of carbon and water fluxes can help stabilize local climate.

The capacity to emit isoprene differentiates the photosynthetic temperature responses of tropical plant species

Experimental research shows that isoprene emission by plants can improve photosynthetic performance at high temperatures. But whether species that emit isoprene have higher thermal limits than non-emitting species remains largely untested. Tropical plants are adapted to narrow temperature ranges and global warming could result in significant ecosystem restructuring due to small variations in species' thermal tolerances. We compared photosynthetic temperature responses of 26 co-occurring tropical tree and liana species to test whether isoprene-emitting species are more tolerant to high temperatures. We classified species as isoprene emitters versus non-emitters based on published datasets. Maximum temperatures for net photosynthesis were ~1.8°C higher for isoprene-emitting species than for non-emitters, and thermal response curves were 24% wider; differences in optimum temperatures (T_opt ) or photosynthetic rates at T_opt were not significant. Modelling the carbon cost of isoprene emission, we show that even strong emission rates cause little reduction in the net carbon assimilation advantage over non-emitters at supraoptimal temperatures. Isoprene emissions may alleviate biochemical limitations, which together with stomatal conductance, co-limit photosynthesis above T_opt . Our findings provide evidence that isoprene emission may be an adaptation to warmer thermal niches, and that emitting species may fare better under global warming than co-occurring non-emitting species.

Spatiotemporal Patterns and Phenology of Tropical Vegetation Solar-Induced Chlorophyll Fluorescence across Brazilian Biomes Using Satellite Observations

Solar-induced fluorescence (SIF) has been empirically linked to gross primary productivity (GPP) in multiple ecosystems and is thus a promising tool to address the current uncertainties in carbon fluxes at ecosystem to continental scales. However, studies utilizing satellite-measured SIF in South America have concentrated on the Amazonian tropical forest, while SIF in other regions and vegetation classes remain uninvestigated. We examined three years of Orbiting Carbon Observatory-2 (OCO-2) SIF data for vegetation classes within and across the six Brazilian biomes (Amazon, Atlantic Forest, Caatinga, Cerrado, Pampa, and Pantanal) to answer the following: (1) how does satellite-measured SIF differ? (2) What is the relationship (strength and direction) of satellite-measured SIF with canopy temperature (Tcan), air temperature (Tair), and vapor pressure deficit (VPD)? (3) How does the phenology of satellite-measured SIF (duration and amplitude of seasonal integrated SIF) compare? Our analysis shows that OCO-2 captures a significantly higher mean SIF with lower variability in the Amazon and lower mean SIF with higher variability in the Caatinga compared to other biomes. OCO-2 also distinguishes the mean SIF of vegetation types within biomes, showing that evergreen broadleaf (EBF) mean SIF is significantly higher than other vegetation classes (deciduous broadleaf (DBF), grassland (GRA), savannas (SAV), and woody savannas (WSAV)) in all biomes. We show that the strengths and directions of correlations of OCO-2 mean SIF to Tcan, Tair, and VPD largely cluster by biome: negative in the Caatinga and Cerrado, positive in the Pampa, and no correlations were found in the Pantanal, while results were mixed for the Amazon and Atlantic Forest. We found mean SIF most strongly correlated with VPD in most vegetation classes in most biomes, followed by Tcan. Seasonality from time series analysis reveals that OCO-2 SIF measurements capture important differences in the seasonal timing of SIF for different classes, details masked when only examining mean SIF differences. We found that OCO-2 captured the highest base integrated SIF and lowest seasonal pulse integrated SIF in the Amazon for all vegetation classes, indicating continuous photosynthetic activity in the Amazon exceeds other biomes, but with small seasonal increases. Surprisingly, Pantanal EBF SIF had the highest total integrated SIF of all classes in all biomes due to a large seasonal pulse. Additionally, the length of seasons only accounts for about 30% of variability in total integrated SIF; thus, integrated SIF is likely captures differences in photosynthetic activity separate from structural differences. Our results show that satellite measurements of SIF can distinguish important functioning and phenological differences in vegetation classes and thus has the potential to improve our understanding of productivity and seasonality in the tropics.

Species-Specific Shifts in Diurnal Sap Velocity Dynamics and Hysteretic Behavior of Ecophysiological Variables During the 2015-2016 El Niño Event in the Amazon Forest

Current climate change scenarios indicate warmer temperatures and the potential for more extreme droughts in the tropics, such that a mechanistic understanding of the water cycle from individual trees to landscapes is needed to adequately predict future changes in forest structure and function. In this study, we contrasted physiological responses of tropical trees during a normal dry season with the extreme dry season due to the 2015-2016 El Niño-Southern Oscillation (ENSO) event. We quantified high resolution temporal dynamics of sap velocity (Vs), stomatal conductance (gs) and leaf water potential (ΨL) of multiple canopy trees, and their correlations with leaf temperature (Tleaf) and environmental conditions [direct solar radiation, air temperature (Tair) and vapor pressure deficit (VPD)]. The experiment leveraged canopy access towers to measure adjacent trees at the ZF2 and Tapajós tropical forest research (near the cities of Manaus and Santarém). The temporal difference between the peak of gs (late morning) and the peak of VPD (early afternoon) is one of the major regulators of sap velocity hysteresis patterns. Sap velocity displayed species-specific diurnal hysteresis patterns reflected by changes in Tleaf. In the morning, Tleaf and sap velocity displayed a sigmoidal relationship. In the afternoon, stomatal conductance declined as Tleaf approached a daily peak, allowing ΨL to begin recovery, while sap velocity declined with an exponential relationship with Tleaf. In Manaus, hysteresis indices of the variables Tleaf-Tair and ΨL-Tleaf were calculated for different species and a significant difference (p < 0.01, α = 0.05) was observed when the 2015 dry season (ENSO period) was compared with the 2017 dry season ("control scenario"). In some days during the 2015 ENSO event, Tleaf approached 40°C for all studied species and the differences between Tleaf and Tair reached as high at 8°C (average difference: 1.65 ± 1.07°C). Generally, Tleaf was higher than Tair during the middle morning to early afternoon, and lower than Tair during the early morning, late afternoon and night. Our results support the hypothesis that partial stomatal closure allows for a recovery in ΨL during the afternoon period giving an observed counterclockwise hysteresis pattern between ΨL and Tleaf.

Evaluating the Effectiveness of Using Vegetation Indices Based on Red-Edge Reflectance from Sentinel-2 to Estimate Gross Primary Productivity

Gross primary productivity (GPP) is the most important component of terrestrial carbon flux. Red-edge (680–780 nm) reflectance is sensitive to leaf chlorophyll content, which is directly correlated with photosynthesis as the pigment pool, and it has the potential to improve GPP estimation. The European Space Agency (ESA) Sentinel-2A and B satellites provide red-edge bands at 20-m spatial resolution on a five-day revisit period, which can be used for global estimation of GPP. Previous studies focused mostly on improving cropland GPP estimation using red-edge bands. In this study, we firstly evaluated the relationship between eight vegetation indices (VIs) retrieved from Sentinel-2 imagery in association with incident photosynthetic active radiation (PARin) and carbon flux tower GPP (GPPEC) across three forest and two grassland sites in Australia. We derived a time series of five red-edge VIs and three non-red-edge VIs over the CO2 flux tower footprints at 16-day time intervals and compared both temporal and spatial variations. The results showed that the relationship between the red-edge index (CIr, ρ 783 ρ 705 − 1 ) multiplied by PARin and GPPEC had the highest correlation (R2 = 0.77, root-mean-square error (RMSE) = 0.81 gC∙m−2∙day−1) at the two grassland sites. The CIr also showed consistency (rRMSE defined as RMSE/mean GPP, lower than 0.25) across forest and grassland sites. The high spatial resolution of the Sentinel-2 data provided more detailed information to adequately characterize the GPP variance at spatially heterogeneous areas. The high revisit period of Sentinel-2 exhibited temporal variance in GPP at the grassland sites; however, at forest sites, the flux-tower-based GPP variance could not be fully tracked by the limited satellite images. These results suggest that the high-spatial-resolution red-edge index from Sentinel-2 can improve large-scale spatio-temporal GPP assessments.

Air temperature optima of vegetation productivity across global biomes

The global distribution of the optimum air temperature for ecosystem-level gross primary productivity ([Formula: see text]) is poorly understood, despite its importance for ecosystem carbon uptake under future warming. We provide empirical evidence for the existence of such an optimum, using measurements of in situ eddy covariance and satellite-derived proxies, and report its global distribution. [Formula: see text] is consistently lower than the physiological optimum temperature of leaf-level photosynthetic capacity, which typically exceeds 30 °C. The global average [Formula: see text] is estimated to be 23 ± 6 °C, with warmer regions having higher [Formula: see text] values than colder regions. In tropical forests in particular, [Formula: see text] is close to growing-season air temperature and is projected to fall below it under all scenarios of future climate, suggesting a limited safe operating space for these ecosystems under future warming.

Time course of the photochemical reflectance index during photosynthetic induction: its relationship with the photochemical yield of photosystem II

Time courses of photochemical reflectance index (PRI) of an attached cucumber leaf during a dark-light transition were compared with those of photochemical yields of photosystem II (Y_II ) to discuss the feasibility of PRI imaging for estimating the efficiency of photosynthetic light use. Y_II and PRI were simultaneously evaluated with a pulse-amplitude modulation chlorophyll fluorometer and a low-cost imaging system consisting of digital cameras and band-pass filters, respectively. Y_II decreased immediately after the transition and then increased under various photon flux densities. Although PRI exhibited delayed time courses with respect to Y_II under low light conditions, PRI decreased monotonically under high light conditions. There was no correlation between Y_II and the changes in PRI (ΔPRI) immediately after the transition but Y_II was correlated with ΔPRI under the steady-state photosynthesis. These results indicate that the use of PRI to estimate Y_II under fluctuating light based on the regression obtained at steady state can overestimate Y_II . The imaging system was also applied to evaluate the spatial PRI distribution within a leaf. While PRI of leaf areas that remained untreated, or had been treated with H₂ O again, first dropped and then rose under low light and monotonically decreased under high light conditions, leaf areas treated with inhibitor (dichlorophenyl dimethylurea) did not exhibit any changes. It is likely that the inhibitor suppressed lumen acidification, which triggers a decrease in PRI. It was suggested that Y_II of leaves with malfunctions in the photosynthetic electron transport can be overestimated by the PRI-based estimation.

Effects of sky conditions on net ecosystem productivity of a subtropical coniferous plantation vary from half-hourly to daily timescales

The dynamic changes of solar radiation have received wide attention in global change studies, but there are controversies about the influence of diffuse radiation on ecosystem carbon sequestration. Using eddy covariance measurements from 2010 to 2012, the effects of sky conditions extracted from adjacent sunny, cloudy, and overcast days on net ecosystem productivity (NEP) of a subtropical coniferous plantation were examined from half-hourly to daily scales. Half-hourly NEP responded to the changing radiation more efficiently on overcast days compared to sunny days, but such response did not differ obviously between cloudy and sunny days. Compared with sunny conditions, apparent quantum yield (α) under overcast (cloudy) conditions changed 282.4% (41.7%) in spring, 140.3% (-4.2%) in summer, 218.5% (38.9%) in autumn, and 146.2% (0.5%) in winter, respectively; annually, α under overcast (cloudy) conditions increased by 225.9% (19.8%) in 2010, 189.8% (6.0%) in 2011, and 159.5% (21.4%) in 2012, respectively. Moreover, the potential NEP at the light intensity of 150 and 750 W m^-2 was improved due to increased diffuse fraction. However, both daytime NEP and daily NEP were significantly lower under overcast skies than under sunny and cloudy skies. Compared with sunny days, daily NEP on overcast days decreased by 127.7% in spring, 126.4% in summer, 121.8% in autumn, and 100.6% in winter, respectively; annually, daily NEP decreased by 122.5% in 2010, 141.7% in 2011, and 109.9% in 2012, respectively. Diurnal patterns of daily NEP were quite similar between sunny and cloudy days. Both path analysis and multiple regression showed that solar radiation, especially diffuse radiation, was responsible for the variations of NEP under different skies across seasons, but this effect may be weakened by seasonal droughts. This study implies that the effects of sky conditions on NEP are timescale dependent and should be paid more attention in ecosystem carbon cycle study.

Prediction of forest aboveground net primary production from high-resolution vertical leaf-area profiles

Temperature and precipitation explain about half the variation in aboveground net primary production (ANPP) among tropical forest sites, but determinants of remaining variation are poorly understood. Here, we test the hypothesis that the amount of leaf area, and its vertical arrangement, predicts ANPP when other variables are held constant. Using measurements from airborne lidar in a lowland Neotropical rain forest, we quantify vertical leaf-area profiles and develop models of ANPP driven by leaf area and other measurements of forest structure. Vertical leaf-area profiles predict 38% of the variation among plots. This number is 4.5 times greater than models using total leaf area (disregarding vertical arrangement) and 2.1 times greater than models using canopy height alone. Furthermore, ANPP predictions from vertical leaf-area profiles were less biased than alternate metrics. Variation in ANPP not attributable to temperature or precipitation can be predicted by the vertical distribution of leaf area in this system.

Field evidences for the positive effects of aerosols on tree growth

Theoretical and eddy covariance studies demonstrate that aerosol-loading stimulates canopy photosynthesis, but field evidence for the aerosol effect on tree growth is limited. Here, we measured in situ daily stem growth rates of aspen trees under a wide range of aerosol-loading in China. The results showed that daily stem growth rates were positively correlated with aerosol-loading, even at exceptionally high aerosol levels. Using structural equation modeling analysis, we showed that variations in stem growth rates can be largely attributed to two environmental variables covarying with aerosol loading: diffuse fraction of radiation and vapor pressure deficit (VPD). Furthermore, we found that these two factors influence stem growth by influencing photosynthesis from different parts of canopy. Using field observations and a mechanistic photosynthesis model, we demonstrate that photosynthetic rates of both sun and shade leaves increased under high aerosol-loading conditions but for different reasons. For sun leaves, the photosynthetic increase was primarily attributed to the concurrent lower VPD; for shade leaves, the positive aerosol effect was tightly connected with increased diffuse light. Overall, our study provides the first field evidence of increased tree growth under high aerosol loading. We highlight the importance of understanding biophysical mechanisms of aerosol-meteorology interactions, and incorporating the different pathways of aerosol effects into earth system models to improve the prediction of large-scale aerosol impacts, and the associated vegetation-mediated climate feedbacks.

Effects of Forest Canopy Vertical Stratification on the Estimation of Gross Primary Production by Remote Sensing

Gross primary production (GPP) in forests is the most important carbon flux in terrestrial ecosystems. Forest ecosystems with high leaf area index (LAI) values have diverse species or complex forest structures with vertical stratifications that influence the carbon–water–energy cycles. In this study, we used three light use efficiency (LUE) GPP models and site-level experiment data to analyze the effects of the vertical stratification of dense forest vegetation on the estimates of remotely sensed GPP during the growing season of two forest sites in East Asia: Dinghushan (DHS) and Tomakomai (TMK). The results showed that different controlling environmental factors of the vertical layers, such as temperature and vapor pressure deficit (VPD), produce different responses for the same LUE value in the different sub-ecosystems (defined as the tree, shrub, and grass layers), which influences the GPP estimation. Air temperature and VPD play important roles in the effects of vertical stratification on the GPP estimates in dense forests, which led to differences in GPP uncertainties from −50% to 30% because of the distinct temperature responses in TMK. The unequal vertical LAI distributions in the different sub-ecosystems led to GPP variations of 1–2 gC/m2/day with uncertainties of approximately −30% to 20% because sub-ecosystems have unique absorbed fractions of photosynthetically active radiation (APAR) and LUE. A comparison with the flux tower-based GPP data indicated that the GPP estimations from the LUE and APAR values from separate vertical layers exhibited better model performance than those calculated using the single-layer method, with 10% less bias in DHS and more than 70% less bias in TMK. The precision of the estimated GPP in regions with thick understory vegetation could be effectively improved by considering the vertical variations in environmental parameters and the LAI values of different sub-ecosystems as separate factors when calculating the GPP of different components. Our results provide useful insight that can be used to improve the accuracy of remote sensing GPP estimations by considering vertical stratification parameters along with the LAI of sub-ecosystems in dense forests.

Age-dependent leaf physiology and consequences for crown-scale carbon uptake during the dry season in an Amazon evergreen forest

Satellite and tower-based metrics of forest-scale photosynthesis generally increase with dry season progression across central Amazônia, but the underlying mechanisms lack consensus. We conducted demographic surveys of leaf age composition, and measured the age dependence of leaf physiology in broadleaf canopy trees of abundant species at a central eastern Amazon site. Using a novel leaf-to-branch scaling approach, we used these data to independently test the much-debated hypothesis - arising from satellite and tower-based observations - that leaf phenology could explain the forest-scale pattern of dry season photosynthesis. Stomatal conductance and biochemical parameters of photosynthesis were higher for recently mature leaves than for old leaves. Most branches had multiple leaf age categories simultaneously present, and the number of recently mature leaves increased as the dry season progressed because old leaves were exchanged for new leaves. These findings provide the first direct field evidence that branch-scale photosynthetic capacity increases during the dry season, with a magnitude consistent with increases in ecosystem-scale photosynthetic capacity derived from flux towers. Interactions between leaf age-dependent physiology and shifting leaf age-demographic composition are sufficient to explain the dry season photosynthetic capacity pattern at this site, and should be considered in vegetation models of tropical evergreen forests.

Estimating forest carbon fluxes using four different data-driven techniques based on long-term eddy covariance measurements: Model comparison and evaluation

With the recent availability of large amounts of data from the global flux towers across different terrestrial ecosystems based on the eddy covariance technique, the use of data-driven techniques has been viable. In this study, two advanced techniques, namely adaptive neuro-fuzzy inference system (ANFIS) and extreme learning machine (ELM), were developed and investigated for their viability in estimating daily carbon fluxes at the ecosystem level. All the data used in this study were based upon the long-term chronosequence observations derived from the flux towers in eight forest ecosystems. Both ANFIS and ELM methods were further compared with the most widely used artificial neural network (ANN) and support vector machine (SVM) methods. Moreover, we also focused on probing into the effects of internal parameters on their corresponding approaches. Our estimates showed that most variation in each carbon flux could be effectively explained by the developed models at almost all the sites. Moreover, the forecasting accuracy of each method was strongly dependent upon their respective internal algorithms. The best training function for ANN model can be acquired through the trial and error procedure. The SVM model with the radial basis kernel function performed considerably better than the SVM models with the polynomial and sigmoid kernel functions. The hybrid ELM models achieved similar predictive accuracy for the three fluxes and were consistently superior to the original ELM models with different transfer functions. In most instances, both the subtractive clustering and fuzzy c-means algorithms for the ANFIS models outperformed the most popular grid partitioning algorithm. It was demonstrated that the newly proposed ELM and ANFIS models were able to produce comparable estimates to the ANN and SVM models for forecasting terrestrial carbon fluxes.

Carbon exchanges and their responses to temperature and precipitation in forest ecosystems in Yunnan, Southwest China

Forest ecosystems play an increasingly important role in the global carbon cycle. However, knowledge on carbon exchanges, their spatio-temporal patterns, and the extent of the key controls that affect carbon fluxes is lacking. In this study, we employed 29-site-years of eddy covariance data to observe the state, spatio-temporal variations and climate sensitivity of carbon fluxes (gross primary productivity (GPP), ecosystem respiration (R_eco), and net ecosystem carbon exchange (NEE)) in four representative forest ecosystems in Yunnan. We found that 1) all four forest ecosystems were carbon sinks (the average NEE was -3.40tCha^-1yr^-1); 2) contrasting seasonality of the NEE among the ecosystems with a carbon sink mainly during the wet season in the Yuanjiang savanna ecosystem (YJ) but during the dry season in the Xishuangbanna tropical rainforest ecosystem (XSBN), besides an equivalent NEE uptake was observed during the wet/dry season in the Ailaoshan subtropical evergreen broad-leaved forest ecosystem (ALS) and Lijiang subalpine coniferous forest ecosystem (LJ); 3) as the GPP increased, the net ecosystem production (NEP) first increased and then decreased when the GPP>17.5tCha^-1yr^-1; 4) the precipitation determines the carbon sinks in the savanna ecosystem (e.g., YJ), while temperature did so in the tropical forest ecosystem (e.g., XSBN); 5) overall, under the circumstances of warming and decreased precipitation, the carbon sink might decrease in the YJ but maybe increase in the ALS and LJ, while future strength of the sink in the XSBN is somewhat uncertain. However, based on the redundancy analysis, the temperature and precipitation combined together explained 39.7%, 32.2%, 25.3%, and 29.6% of the variations in the NEE in the YJ, XSBN, ALS and LJ, respectively, which indicates that considerable changes in the NEE could not be explained by variations in the temperature and precipitation. Therefore, the effects of other factors (e.g., CO₂ concentration, N/P deposition, aerosol and other variables) on the NEE still require extensive research and need to be considered seriously in carbon-cycle-models.

Progress in Remote Sensing of Photosynthetic Activity over the Amazon Basin

Although quantifying the massive exchange of carbon that takes place over the Amazon Basin remains a challenge, progress is being made as the remote sensing community moves from using traditional, reflectance-based vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), to the more functional Photochemical Reflectance Index (PRI). This new index, together with satellite-derived estimates of canopy light interception and Sun-Induced Fluorescence (SIF), provide improved estimates of Gross Primary Production (GPP). This paper traces the development of these new approaches, compares the results of their analyses from multiple years of data acquired across the Amazon Basin and suggests further improvements in instrument design, data acquisition and processing. We demonstrated that our estimates of PRI are in generally good agreement with eddy-flux tower measurements of photosynthetic light use efficiency (ε) at four sites in the Amazon Basin: r² values ranged from 0.37 to 0.51 for northern flux sites and to 0.78 for southern flux sites. This is a significant advance over previous approaches seeking to establish a link between global-scale photosynthetic activity and remotely-sensed data. When combined with measurements of Sun-Induced Fluorescence (SIF), PRI provides realistic estimates of seasonal variation in photosynthesis over the Amazon that relate well to the wet and dry seasons. We anticipate that our findings will steer the development of improved approaches to estimate photosynthetic activity over the tropics.

Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling

Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very limited. Efforts to model climate change impacts on carbon fluxes in tropical forests have not reached a consensus. Here, we use the Ecosystem Demography model (ED2) to predict carbon fluxes of a Puerto Rican tropical forest under realistic climate change scenarios. We parameterized ED2 with species-specific tree physiological data using the Predictive Ecosystem Analyzer workflow and projected the fate of this ecosystem under five future climate scenarios. The model successfully captured interannual variability in the dynamics of this tropical forest. Model predictions closely followed observed values across a wide range of metrics including aboveground biomass, tree diameter growth, tree size class distributions, and leaf area index. Under a future warming and drying climate scenario, the model predicted reductions in carbon storage and tree growth, together with large shifts in forest community composition and structure. Such rapid changes in climate led the forest to transition from a sink to a source of carbon. Growth respiration and root allocation parameters were responsible for the highest fraction of predictive uncertainty in modeled biomass, highlighting the need to target these processes in future data collection. Our study is the first effort to rely on Bayesian model calibration and synthesis to elucidate the key physiological parameters that drive uncertainty in tropical forests responses to climatic change. We propose a new path forward for model-data synthesis that can substantially reduce uncertainty in our ability to model tropical forest responses to future climate.

In situ temperature relationships of biochemical and stomatal controls of photosynthesis in four lowland tropical tree species

Net photosynthetic carbon uptake of Panamanian lowland tropical forest species is typically optimal at 30-32 °C. The processes responsible for the decrease in photosynthesis at higher temperatures are not fully understood for tropical trees. We determined temperature responses of maximum rates of RuBP-carboxylation (V_CMax ) and RuBP-regeneration (J_Max ), stomatal conductance (G_s ), and respiration in the light (R_Light ) in situ for 4 lowland tropical tree species in Panama. G_s had the lowest temperature optimum (T_Opt ), similar to that of net photosynthesis, and photosynthesis became increasingly limited by stomatal conductance as temperature increased. J_Max peaked at 34-37 °C and V_CMax ~2 °C above that, except in the late-successional species Calophyllum longifolium, in which both peaked at ~33 °C. R_Light significantly increased with increasing temperature, but simulations with a photosynthesis model indicated that this had only a small effect on net photosynthesis. We found no evidence for Rubisco-activase limitation of photosynthesis. T_Opt of V_CMax and J_Max fell within the observed in situ leaf temperature range, but our study nonetheless suggests that net photosynthesis of tropical trees is more strongly influenced by the indirect effects of high temperature-for example, through elevated vapour pressure deficit and resulting decreases in stomatal conductance-than by direct temperature effects on photosynthetic biochemistry and respiration.

The phenology of leaf quality and its within-canopy variation is essential for accurate modeling of photosynthesis in tropical evergreen forests

Leaf quantity (i.e., canopy leaf area index, LAI), quality (i.e., per-area photosynthetic capacity), and longevity all influence the photosynthetic seasonality of tropical evergreen forests. However, these components of tropical leaf phenology are poorly represented in most terrestrial biosphere models (TBMs). Here, we explored alternative options for the representation of leaf phenology effects in TBMs that employ the Farquahar, von Caemmerer & Berry (FvCB) representation of CO₂ assimilation. We developed a two-fraction leaf (sun and shade), two-layer canopy (upper and lower) photosynthesis model to evaluate different modeling approaches and assessed three components of phenological variations (i.e., leaf quantity, quality, and within-canopy variation in leaf longevity). Our model was driven by the prescribed seasonality of leaf quantity and quality derived from ground-based measurements within an Amazonian evergreen forest. Modeled photosynthetic seasonality was not sensitive to leaf quantity, but was highly sensitive to leaf quality and its vertical distribution within the canopy, with markedly more sensitivity to upper canopy leaf quality. This is because light absorption in tropical canopies is near maximal for the entire year, implying that seasonal changes in LAI have little impact on total canopy light absorption; and because leaf quality has a greater effect on photosynthesis of sunlit leaves than light limited, shade leaves and sunlit foliage are more abundant in the upper canopy. Our two-fraction leaf, two-layer canopy model, which accounted for all three phenological components, was able to simulate photosynthetic seasonality, explaining ~90% of the average seasonal variation in eddy covariance-derived CO₂ assimilation. This work identifies a parsimonious approach for representing tropical evergreen forest photosynthetic seasonality in TBMs that utilize the FvCB model of CO₂ assimilation and highlights the importance of incorporating more realistic phenological mechanisms in models that seek to improve the projection of future carbon dynamics in tropical evergreen forests.

In situ temperature response of photosynthesis of 42 tree and liana species in the canopy of two Panamanian lowland tropical forests with contrasting rainfall regimes

Tropical forests contribute significantly to the global carbon cycle, but little is known about the temperature response of photosynthetic carbon uptake in tropical species, and how this varies within and across forests. We determined in situ photosynthetic temperature-response curves for upper canopy leaves of 42 tree and liana species from two tropical forests in Panama with contrasting rainfall regimes. On the basis of seedling studies, we hypothesized that species with high photosynthetic capacity - light-demanding, fast-growing species - would have a higher temperature optimum of photosynthesis (T_Opt ) than species with low photosynthetic capacity - shade-tolerant, slow-growing species - and that, therefore, T_Opt would scale with the position of a species on the slow-fast continuum of plant functional traits. T_Opt was remarkably similar across species, regardless of their photosynthetic capacity and other plant functional traits. Community-average T_Opt was almost identical to mean maximum daytime temperature, which was higher in the dry forest. Photosynthesis above T_Opt appeared to be more strongly limited by stomatal conductance in the dry forest than in the wet forest. The observation that all species in a community shared similar T_Opt values suggests that photosynthetic performance is optimized under current temperature regimes. These results should facilitate the scaling up of photosynthesis in relation to temperature from leaf to stand level in species-rich tropical forests.