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• A SIF-based mechanistic (qMLR-SIF) model is used to estimate canopy GPP. • Nonlinear SIF-GPP relationships exist in different plant functional types. • The qMLR-SIF model performs better than other two traditional models overall. • The qMLR-SIF model has wide applicability in quantifying canopy GPP. Mechanistically linking gross primary productivity (GPP) and sun-induced chlorophyll fluorescence (SIF) is an essential step to unleash the full potential of SIF for remote sensing-based predictions of GPP across biomes, climates, and spatiotemporal scales. The latest SIF-based mechanistic light response model that includes the fraction of open photosystem II reaction centers as key parameter (qMLR-SIF model), can accurately reproduce leaf-scale photosynthesis under various conditions. However, it remains unclear to what extent the qMLR-SIF model is suitable for estimating GPP at larger scales such as the canopy scale. Therefore, canopy-scale data of tower-based far-red SIF, GPP and key environmental variables from 10 study sites were collected to analyze the SIF-GPP relationship and to compare the qMLR-SIF model with the widely used Farquhar, von Caemmerer, Berry (FvCB) model and with a light use efficiency (LUE) model for different plant functional types (PFTs), photosynthetic pathways (C 3 and C 4), and temporal scales (hourly, daily and 4-day). Results showed that the nonlinear SIF-GPP relationship existed in all PFTs and the degree of linearity increased at larger temporal scales. The qMLR-SIF model exhibited wide applicability to quantify canopy GPP for different PFTs (R2 = 0.55–0.80, RMSE = 2.72–11.03 μmol CO 2 m-2 s-1), photosynthetic pathways (R2 = 0.70–0.78, RMSE = 5.29–9.05 μmol CO 2 m-2 s-1) and temporal scales (R2 = 0.82–0.97, RMSE = 3.42–8.32 μmol CO 2 m-2s-1). Compared with the two other models, the qMLR-SIF model performed best overall, which is mainly due to its simpler model structure and the mechanistic link between SIF and photosynthesis. Particularly, the qMLR-SIF model could more accurately estimate GPP in C 4 species, with higher R2 (0.78) and lower RMSE (8.46 μmol CO 2 m-2s-1). These findings highlight the advantages of the qMLR-SIF model in GPP estimation at the canopy scale, showing its potential in applications at regional and global scales. [ABSTRACT FROM AUTHOR]

• O 3 dose-response relationships can be derived using the mechanistic A net -g sto model. • The model can simulate the response of key physiological variables to O 3 exposure. • The model can simulate the start & end of senescence better than the empirical models. Ground-level ozone (O 3) pollution occurs across many important agricultural regions in Europe, North America, and Asia, negatively impacting O 3 -sensitive crops such as wheat. Risk assessment methods to quantify the magnitude and spatial extent of O 3 pollution have often used dose-response relationships. In Europe, the dose metrics used in these relationships have evolved from concentration- to flux-based metrics since stomatal O 3 flux has been found to correlate better with yield losses. Estimates of stomatal conductance (g s t o) have to date used an empirical multiplicative model. However, other more mechanistic approaches are available, namely the coupled photosynthetic-stomatal conductance (A n e t g s t o ) model. This study used a European O 3 OTC and solardome fumigation experimental dataset (comprising 6 cultivars, 4 countries and 14 years) to develop a new flux-based dose-response relationship for wheat yield using the mechanistic A n e t g s t o model (A n e t g s t o m e c h). The A n e t g s t o m e c h model marginally improved the regression of the dose-response relationship (R2 = 0.74) when compared to the flux-response models derived from empirical g s t o models. In addition, the A n e t g s t o m e c h model was somewhat better at predicting the effect of high O 3 concentrations on diurnal and seasonal profiles of g s t o and A n e t. It was also better able to simulate changes of up to 7 and 12 days, respectively, in the start (SOS) and end (EOS) of senescence, an important determinant of yield loss, over a range of O 3 treatments. We conclude that A n e t g s t o m e c h model can be used to derive robust flux-response relationships. [ABSTRACT FROM AUTHOR]

• Novel approach to isolate crop heat stress periods with GPP flux data. • Visible region was more important for heat stress detection than the NIR region. • Red reflectance was significantly elevated by heat stress. • EVI was the best-performing index for GPP estimation under heat stress. Stress caused by high temperatures is a critical limiting factor of crop growth and development. Although remote sensing has been used to investigate the impacts of high temperatures on crops, its ability to detect heat stress independently of other stressors and assess its effects on gross primary production (GPP) estimation is unclear. This study developed an innovative approach to distinguish crop heat stress periods from normal growth conditions in croplands independent of water stress and light limitation. Multispectral broad bands and spectral vegetation indices (VIs) derived from MODIS for 78 periods of heat stress were used to assess the sensitivity of canopy reflectance to heat stress and its impacts on GPP. Results reveal that heat stress significantly increased the reflectance in the red band. VIs, in general, enhanced the detection of heat-induced spectral variations, and exhibited sufficient skill in distinguishing crops under heat stress and normal conditions. Three visible-based indices (the Visible Atmospherically Resistant Index, the Green Leaf Index, and the Normalized Green–Red Difference Index) exhibited the highest discriminability (p -value < 0.01 in the Mann–Whitney U test), while the Enhanced Vegetation Index displayed the highest accuracy in GPP estimation (R2 = 0.62, RMSE = 5.49, RRMSE = 0.35) under heat conditions. Overall, the isolation of heat stress impact on crop growth has important implications for advancing large-scale crop modeling and climate change studies, for example, incorporating the suggested VIs into temperature response simulations within crop models. [ABSTRACT FROM AUTHOR]

• The USO series models significantly overestimated g sw at low VPD and irradiance; • The assumption of the g sw -A n linear relationship resulted in g sw overestimations by 9.7 %; • The issue of unbounded g sw at low VPD resulted in g sw overestimations by 18.5 %; • The g sw -A n relationship was non-linear due to the negative correlation between C i /C a and irradiance; • The photosynthesis-random forest inference tool is useful to reproduce physiologically based cause-effect relationships. The predictions of stomatal conductance (g sw) by the unified stomata optimization (USO) series models in tropical rainforest trees exhibited pronounced biases. However, little attention has been devoted to the structural issues within the USO series models themselves. This study introduced a novel approach by integrating the Farquhar photosynthesis model with the random forest (RF) algorithm to investigate diurnal variations in leaf stomatal responses among six tropical tree species in South China. The results revealed that the USO model and its derivative significantly overestimated g sw when vapor pressure deficit (VPD) and irradiance were low. The overestimation was primarily attributed to the assumption of a linear relationship between g sw and net assimilation rate (A n) and the issue of unbounded g sw when VPD was low. The relationship between g sw and A n was indeed non-linear due to a negative correlation between the intercellular: atmospheric CO 2 concentration ratio (C i /C a) and irradiance. The relationship between C i /C a and irradiance indicated that C i /C a was higher at low irradiance, declined and tended to gradually stabilize at high irradiance. An empirical coefficient was determined by using the monthly mean of daytime minimum VPD to represent g sw as finite values at low VPD. The revision achieved a substantial improvement in predictive accuracy of g sw at low VPD while preserving g sw responsiveness under high VPD. [ABSTRACT FROM AUTHOR]

• Current crop models poorly simulate leaf-level photosynthesis under low-temperature stress. • Improved algorithms based on accumulated cold degree days effectively quantify the damage of low-temperature stress on leaf-level photosynthesis. • Improved algorithms quantify the recovery process of leaf-level photosynthesis after low-temperature stress. • Improved algorithms consider sensitivities of different rice cultivars to low-temperature stress. Photosynthesis is crucial for crop growth and yield, yet remains a limitation in enhancing crop production under global climate change. Crop models have been widely used to project the impacts of climate change on crop yields, including extreme temperature events. However, most crop simulation models performed poorly on leaf-level photosynthesis simulation under low-temperature stress (LTS). Here, two rice cultivars, Huaidao 5 and Nangeng 46, were treated under seven LTS intensities (from 27/21 °C to 12/6 °C) and five LTS durations (from 3 to 9 days) during the flowering stage for three years under environment-controlled conditions. The results showed that the observed maximum photosynthetic rate (P max) and initial light-use efficiency (ε) decreased with increasing intensities and durations of LTS, and P max and ε were linearly correlated (R2 = 0.94). Experimental data under different LTS have been tested by four widely used rice models, including RiceGrow, ORYZA2000, RICEPSM, and GEMRICE, indicating that the effects of LTS durations on P max and ε have not been captured well by most existing models. By integrating accumulated cold degree days (ACDD, °C·d) as the LTS index with a cultivar-specific low-temperature threshold parameter (T h), algorithms of temperature factor (FT) and ε were improved, and the effects of LTS on P max and ε were quantified with a double exponential decay function in this research. Compared with the original models, the normalized root mean square error (NRMSE) between observed and simulated photosynthetic rates in the four improved models decreased by about 80 % under LTS treatments, indicating the better performance of the improved models. In addition, the recovery factor of LTS damage to photosynthesis (FLT recover) algorithm was developed to simulate the recovery of the leaf-level photosynthetic rate (P) after LTS treatments. This study could provide an effective quantitative tool for accurately estimating rice photosynthetic production and grain yield under future climate conditions. [ABSTRACT FROM AUTHOR]

• Canopy temperature was warmer than air temperature during most of the growing season. • T c :T air slopes increased following a water- to energy-limited gradient. • We introduced a framework linking canopy temperature, radiation, and soil moisture. Canopy temperature (T c) plays an important role in regulating the rates of mass and energy fluxes at the leaf surface. Better understanding of the relationship between T c and water availability may enable more accurate monitoring of ecosystem functioning in a changing climate. Here, we used high spatiotemporal resolution thermal infrared cameras deployed at three eddy covariance flux tower sites along a water- to energy-limited gradient – including a predominately water-limited grassland/shrubland site, a seasonally water-limited evergreen needleleaf forest, and a predominantly energy-limited deciduous broadleaf forest – to determine T c seasonality and its relationship with gross primary productivity (GPP) and environmental drivers. We found midday T c was generally warmer than air temperature (T air) during the growing season (T c :T air slope: 1.14–1.27) for all sites. Water-limited sites exhibited higher positive T c deviations from T air (2.30 ± 0.06 °C) compared to the energy-limited site (1.29 ± 0.09 °C) partly due to their reduced latent heat fluxes during water-limited periods. We further found that the T c :T air slope increased with site aridity, namely for 1.14 slope for the grassland, 1.15 for the evergreen forest, and 1.27 for the broadleaf forest. Peak GPP occurred when T c was higher than T air across all sites, with peak GPP at the grassland site occurring at +1.1 °C (T c -T air) and peak GPP at the broadleaf evergreen site occurring at +2.2 °C (T c -T air). T c -T air dynamics were mostly associated with soil water content at water-limited sites where canopies undergo a substantial cooling during the transition from dormancy to the peak GPP, while net radiation played a crucial role at the energy-limited site where the canopy heats up compared to T air over the same phenological transition. Our findings provide novel insights into T c -ecosystem water availability links, highlighting the drivers of T c -T air across diverse ecosystems in various phenological stages, which has implications for ecosystem management in a changing climate. [ABSTRACT FROM AUTHOR]

• Patterns of summer forest productivity were examined in the context of winter snow and summer rain. • The GPP season was longer in years with earlier snowmelt. • Total GPP was higher for a longer GPP season in sites with wetter summer climate. • Total GPP was lower for a longer GPP season in sites with drier summer climate. • These patterns were weaker in forests with snow as a higher annual fraction of precipitation. Seasonal snow cover is important in shaping ecosystem carbon uptake across many regions of the world, however forest responses to projected declines in snowpack remain uncertain. We studied the response of forest gross primary productivity (GPP) during the photosynthetically active season to interannual and spatial variability in snow water equivalent (SWE), timing of snowmelt, and length of the active season. We combined carbon flux and weather data from 14 temperate deciduous and evergreen forests in the US and southeast Canada with SWE and precipitation from the Snow Data Assimilation System to test these hypotheses: 1) earlier snowmelt leads to a longer active season; 2) a longer active season is associated with higher total GPP, and 3) GPP during the active season is dependent on peak SWE and timing of snowmelt the previous winter. Regression and correlation analyses did not reveal meaningful environmental predictors of interannual variability in GPP, so linear mixed effects models were used to analyze broader scale spatiotemporal patterns. We found that active season length was negatively correlated with total active season GPP in forests with drier summers on average (based on mean annual summer climatic water deficit), but positively correlated in areas with typically wetter summers. The magnitude of these effects decreased at forests with a higher percentage of annual precipitation falling as snow. Our results showed that the capacity for plants to gain more carbon during a longer active season appears to be dependent on soil water status determined by long-term climate, rather than interannual fluctuations in weather. We found no evidence that the magnitude of total snowfall or peak SWE had a legacy effect on subsequent active season GPP. Finally, we highlight that there was large interannual variability both within and between sites that was not well explained by seasonal climate or phenology. [ABSTRACT FROM AUTHOR]

• Leaf mass-based photosynthetic rate was more enhanced in evergreen trees with eCO2. • Branch hydraulic efficiency was more enhanced in deciduous trees with eCO2. • eCO2 strengthens the coordination of stem hydraulics with leaf gas exchange. Elevated CO 2 concentration (eCO 2) in the atmosphere is expected to impact plant water relations and growth in several ecosystems across the globe. However, we still know little about such impact on tree species in subtropical regions. The present study investigated the impact of eCO 2 on leaf gas exchange, nitrogen and phosphorus concentrations, leaf and stem hydraulic conductivity, and growth of seedlings of four evergreen and four deciduous tree species from a subtropical forest in Southwest China. We found that both evergreen and deciduous tree species at eCO 2 had higher leaf area-based photosynthetic rates and lower leaf stomatal conductance. Further, leaf mass-based photosynthetic rate was more enhanced in evergreen than in deciduous trees at eCO 2. Biomass of evergreen and deciduous species was significantly higher at eCO 2 , with large species-specific variation among the evergreen species. Leaf-specific hydraulic conductivity was more enhanced in deciduous tree species than that of evergreen tree species with eCO 2 , which was mainly driven by the increase of biomass at eCO 2. Interestingly, eCO 2 significantly strengthened the coordination of stem hydraulic conductivity with leaf-gas exchange, leaf phosphorus concentration, and plant biomass across evergreen and deciduous species. These results highlighted greater enhancement of photosynthesis and greater species-specific variation in biomass at eCO 2 for evergreen species compared to deciduous species, and stronger hydraulic-photosynthesis correlations at eCO 2 than at aCO 2 for tree species from subtropical forests. The present study provides important insights on the potential impacts of eCO 2 on plant eco-physiology, growth and forest succession in a subtropical forest under global climate change. [ABSTRACT FROM AUTHOR]

• Biophysical potential explains as much tree growth variance as photosynthesis. • Across space, aridity induces larger relative importance of biophysical potential. • Over time, photosynthesis and biophysical potential have mostly additive effects. • Sink representation in models need to reflect patterns of source-sink interactions. Tree growth is a key uncertainty in projections of forest productivity and the global carbon cycle. While global vegetation models commonly represent tree growth as a carbon assimilation (source)-driven process, accumulating evidence points toward widespread non-photosynthetic (sink) limitations. Notably, growth biophysical potential, defined as the upper-limit to tree growth imposed by temperature and turgor constraints on cell division, has been suggested to be a potent driver of observed decoupling between tree growth and photosynthesis. Understanding the interplay between biophysical potential and photosynthesis and how to accommodate it parsimoniously in models remains a challenge. Here, we use a soil-plant-atmosphere continuum model together with a regional network of forest structure and annual, radial tree growth observations extending over three decades to simulate tree photosynthesis and biophysical potential along an aridity gradient and across five tree species in NE Spain. We then apply a linear modelling framework to quantify the relative importance of photosynthesis, biophysical potential and their interactions to predict annual tree growth along the aridity gradient. Overall similar relative importance of photosynthesis and biophysical potential was underlain by strong variations with climate, photosynthesis being more relevant at wet sites and biophysical potential at dry sites. Observed spatial and temporal trends further suggested that tree growth is primarily limited by biophysical potential under dry conditions and that disregarding it could lead to underestimating tree growth decline with increased aridity under climate change. Our results support the idea that biophysical potential is an important component of sink limitations to tree radial growth. Its representation in vegetation models could accommodate spatially and temporally dynamic source-sink limitations on tree growth. [ABSTRACT FROM AUTHOR]

• We characterized the intra-annual variation in radial stem growth of four temperate tree species from 2019 to 2022. • The onset of cambial activity of ring-porous species is earlier than that of non-porous species. • The cessation of intra-annual radial growth does not seem to be controlled by environmental conditions. • There was a positive correlation between photosynthetic production rate and radial growth rate. • There was no time lag between radial stem growth and photosynthetic production, particularly in different classes. The comprehension of the linkage between radial stem growth and photosynthesis is fundamental to gaining insight into the growth and developmental mechanisms of trees, as well as their adaptive capacity to future climate change. However, such crucial information is rarely available, particularly on short-term temporal scales. In this study, we continuously monitored the intra-annual radial stem growth of a non-porous species (Pinus koraiensis) and three ring-porous species (Quercus mongolica, Fraxinus mandshurica, Ulmus japonica) with monthly measurements in 2019 and weekly measurements from 2020 to 2022(second part in 2022) in a temperate forest of Northeast China based on microcore techniques. Concurrently, we estimated the daily photosynthetic production at the individual tree level using a photosynthetic production model developed by our research team. Subsequently, a generalized linear model was conducted to determine the temporal lag of intra-annual radial stem increment and photosynthetic production. Our results indicate significant differences in the initiation of radial growth among the observed years, while the cessation of growth remained consistent. Specifically, ring-porous species exhibited an earlier onset of radial growth compared to non-porous species, but no consistent pattern was observed for the cessation of growth across different wood types. Additionally, we found a strong coupling between radial growth increment and photosynthetic production without any day lag, particularly in different classes. Furthermore, a notable linear association was observed between relative intra-annual radial growth and photosynthetic production, further indicating a positive correlation between photosynthesis and radial growth. We concluded that the carbohydrates required for radial growth are at least partially derived from photosynthetic production produced on the same day when the leaves were available for photosynthesis. These findings enhance our understanding of the seasonal dynamics of radial growth at the cellular level and provide new insights into the relationship between radial growth and photosynthetic production on short-term temporal scales. [ABSTRACT FROM AUTHOR]

• Shifts in the trends of vegetation growth on the Tibetan Plateau were explored. • Enhanced hydrothermal condition induced continuous greening in northeastern part. • Vegetation shifted from browning to greening since 2007 for the southwestern part. • Vegetation displayed more prominent greening since 2016 for the southeastern part. • Photosynthesis is more sensitive than greenness to climate change. Ecosystems on the Tibetan Plateau (TP) are fragile and sensitive to climate change and thus provide insight into the climate regulations on vegetation structure and function. In this study, we utilized the Normalized Difference Vegetation Index (NDVI) and solar-induced chlorophyll fluorescence (SIF) to explore vegetation dynamics during the growing season from 2000 to 2021, and further investigated how climate change has influenced them. Based on both NDVI and SIF, significant vegetation greening trends were observed in northeastern TP across the study period due to continuous increases in both temperature and water availability. Browning trends were observed in southwestern TP due to decreasing precipitation and enhanced warming stress during 2000–2007, but the trends reversed after 2007. In the southeastern region, we also detected a turning point of a more prominent greening trend in 2016. Moreover, changes in SIF exhibited greater magnitude compared to NDVI, implying vegetation photosynthesis is more sensitive to climate change than greenness, potentially due to variations in light use efficiency. This study strengthens our understanding of climate regulations on vegetation structure and function under different hydrothermal conditions and highlights the need for additional research on the differences between greenness and photosynthesis. [ABSTRACT FROM AUTHOR]

• Increased temperature improved plant growth and photosynthetic carbon fixation. • O 3 inhibited growth, and Quercus mongolica has a self-repair ability to O 3 stress. • The adverse effects of O 3 on growth and C fixation were mitigated by air warming. • Urban trees show a species-specific difference in plant functional traits. With continuous urbanization and climate warming, increased air temperature and elevated ozone (O 3) concentration often co-occur in many urban areas, but we still lack information about the interactive effects of warming and elevated O 3 on urban trees. In the present experiment, the single and combined effects of increased air temperature (IT, ambient air temperature + 2 °C) and elevated O 3 (EO, ambient air O 3 concentrations + 80 ppb) on carbon (C) fixation and allocation in Quercus mongolica and Pinus tabuliformis, which are widely used as street tree species in urban areas of China, were investigated over two consecutive growing seasons by using 13C isotope techniques. The results showed that IT increased biomass, photosynthetic gas exchange parameters and total 13C content of both tree species. Compared to ambient temperature, IT significantly increased the total 13C content labelled by 56.6 % in Q. mongolica and by 31.2 % in P. tabuliformis in 2021. Elevated O 3 induced a decrease in biomass and net photosynthetic rate (P n) in both tree species. Compared to ambient O 3, elevated O 3 significantly decreased P n by 52.6 % in Q. mongolica and by 37.4 % in P. tabuliformis in 2020. The treatment EO decreased 13C allocation to roots but increased 13C content and distribution in leaves in Q. mongolica. These findings demonstrated that EO inhibited the growth and photosynthesis of the two tree species. Our results showed that Q. mongolica was more sensitive to IT and EO than P. tabuliformis , but the former has a self-repair mechanism under increased O 3 stress as it is able to invest more carbon to repair leaf damage to a certain extent. Our study also found that the total biomass, relative growth rate, P n and total 13C content remained higher under the combination of IT and EO compared to EO alone, suggesting that moderate warming may mitigate the negative effects of elevated O 3 stress to some extent. [ABSTRACT FROM AUTHOR]

• A mechanistic model was used to estimate GPP from SIF in ENFs;. • This model avoids the GPP overestimation in winter and early spring;. • SIF-J (electron transport rate) relationship impacts the seasonal SIF–GPP dynamics. • Φ PSIImax largely explained the seasonal variation in SIF-J relationship. Solar-induced chlorophyll fluorescence (SIF) has shown great potential in estimating gross primary production (GPP). However, their quantitative relationship is not invariant, which undermines the reliability of empirical SIF-based GPP estimation at fine spatiotemporal scales, especially under extreme conditions. In this study, we developed a parsimonious mechanistic model for SIF-based GPP estimation in evergreen needle forests (ENF) by employing the Mechanistic Light Response framework and Eco-Evolutionary theory to describe the light and dark reactions during photosynthesis, respectively. Specifically, we found that considering the seasonal variation in a key parameter of the MLR framework, the maximum photochemical efficiency of photosystem II (Φ PSIImax), can avoid the GPP overestimation in winter and early spring due to the relatively low environmental sensitivity of SIF. Compared to the estimates from other benchmark models, our GPP estimates were closer to the 1: 1 line and had higher accuracy (average R 2 = 0.86, RMSE=1.99 μmol m−2 s−1) across sites. Furthermore, the changes in the relationship between SIF and J (refers to the electron transport rate) contribute a lot to the dynamic SIF–GPP relationship in this study, while the J–GPP relationship is less variant when the temperature drops. The seasonal variation in the SIF–J relationship, especially the reduction in its slope at low temperatures, is found largely explained by the Φ PSIImax. These results indicate the importance of the uncertainty caused by the variation in the SIF–J relationship for SIF-based GPP estimation, and the consideration of changes in Φ PSIImax under extreme conditions (such as severe winter in this study) is crucial for the improvement of GPP estimation via SIF. [ABSTRACT FROM AUTHOR]

• Average start of the photosynthetic period in China was on the 123rd day of the year. • The average start of the photosynthetic period advances at a rate of 4.3 d (10 a)−1. • 64% of the region is temperature controlled, others are precipitation controlled. • Importance of temperature and precipitation determined by pre-season precipitation. • Climate change increases NPP by advancing the start of the photosynthetic period. In the context of global warming, the advancement of spring phenology in northern and temperate regions due to increased temperatures has been widely reported. Early and delayed start of the photosynthetic period (SOP) directly affects the vegetation net primary productivity (NPP). However, the interrelationship between climate change, the SOP, and the NPP is unclear. In this paper, we use the dynamics of decadal daily solar-induced chlorophyll fluorescence data to calculate the response of Chinese vegetation photosynthetic phenology to climate change and its impact on the NPP over the last 20 years. The results found that over the last 20 years, the average SOP in China was on the 123rd day of the year, and the SOP has advanced at an average rate of 4.3 d (10 a)−1, with a faster trend of SOP advancement in highland and high-altitude areas. 64% of SOP in China is controlled by temperature; 36% of the SOP in China is controlled by precipitation, and the relative importance of temperature and precipitation was reversed as the precipitation gradient decreased, with SOP dominated by temperature when pre-season precipitation ≧300 mm, and SOP dominated by precipitation when pre-season precipitation ≦300 mm. Finally, we find that climate change indirectly increases vegetation NPP by advancing SOP. Our study emphasizes the importance of precipitation on phenology. It provides a scientific basis for understanding and predicting the response of spring photosynthetic phenology to climate change and the contribution of spring phenology to carbon estimation in terrestrial ecosystems. [ABSTRACT FROM AUTHOR]

• A two-leaf model is proposed to estimate gross primary production (GPP). • Solar-induced fluorescence (SIF) is separated into sunlit and shaded components. • Total SIF emissions of sunlit and shaded leaves are derived from TROPOMI. • SIF is linearly related to GPP for shaded leaves but nonlinearly for sunlit leaves. • The two-leaf model is superior to the big-leaf model on GPP estimation. Recently, solar-induced chlorophyll fluorescence (SIF) is a promising tool to estimate gross primary production (GPP). Photosynthesis gradually saturates with the increasing light, but fluorescence tends to keep increasing, leading to a nonlinear SIF-GPP relationship. This nonlinearity occurs for sunlit leaves but not for shaded leaves for which photosynthesis is light-limited. However, the separation of sunlit and shaded SIF has not been systematically investigated when estimating GPP from SIF. Therefore, it is promising to develop a model for GPP estimation considering such differences. This study proposed an approach to separate the total canopy SIF emission (SIF total) from TROPOspheric Monitoring Instrument (TROPOMI) SIF into their sunlit and shaded components (SIF sun and SIF shade). The nonlinearity and linearity in SIF-GPP relationships for sunlit and shaded leaves were incorporated into a two-leaf hybrid model, which was fitted using flux tower data and then evaluated using leave-one-site-out crossing validation. We also elucidated the distinct SIF-GPP relationships between sunlit and shaded leaves using the Soil-Canopy-Observation of Photosynthesis and the Energy balance (SCOPE) model simulation. Compared to previously used linear (R2 = 0.68, RMSE = 2.13 gC·m−2·d−1) or hyperbolic (R2 = 0.72, RMSE = 2.01 gC·m−2·d−1) model based on the big-leaf assumption, our proposed two-leaf hybrid model has the best performance on GPP estimation (R2 = 0.77, RMSE = 1.79 gC·m−2·d−1). We also applied this two-leaf hybrid model to estimate the global GPP during the main growing season in Northern Hemisphere, which were highly correlated with several existing GPP products, with R2 ranging from 0.79 to 0.88. These results will improve our understanding of the relationship between SIF and GPP for sunlit and shaded leaves and will advance application of satellite SIF data to GPP estimation. [ABSTRACT FROM AUTHOR]

• Enhanced photosynthesis is the main driver of the increased iWUE at the treeline. • Reduction of stomatal conductance is the prime regulator of iWUE at lower-altitude forests. • Higher iWUE is accompanied by higher temperature and greater VPD at lower-altitude forests. Tree intrinsic water-use efficiency (iWUE) has dramatically increased in recent decades in global forests. The rising iWUE can be a result of either enhanced photosynthesis rate (A), or decreased stomatal conductance (g s) or both. The underlying physiological mechanisms are still not well understood. Here, we investigated tree-ring isotopes δ13C and δ18O from two tree species in three altitudinal transects on the southeast Tibetan plateau. We found that the relationship between iWUE and ∆18O lw was negative at lower-altitude forests, whereas it was positive at the treeline, indicating that enhanced photosynthesis was the main driver of the increasing iWUE at the treeline, whereas reduction in stomatal conductance was the prime regulator at lower-altitude forests. Furthermore, vapor pressure deficit (VPD) and precipitation during the main growing season showed the highest and significant correlations with leaf water 18O (Δ18O lw) at lower-altitude forests, suggesting that g s was strongly controlled by moisture conditions in the growing season particularly in the lower-altitude forests. These findings shed light to a better understanding of the regulatory mechanism of iWUE changes under the background of rising atmospheric CO 2 and climate change and serve to improve the reliability of ecophysiological modeling. [ABSTRACT FROM AUTHOR]

• The soil water content and temperature determined the maximum photosynthesis. • Sufficient soil water elevated the optimal temperature and maximum photosynthesis. • The optimal environmental configuration for the alpine meadow was detected. • If soil water is high, higher temperature and VPD are beneficial for carbon uptake. The changes in the carbon sink function of sensitive and fragile alpine ecosystems under climate change are widely concerned. Radiation, temperature, and water resources play important roles in regulating carbon assimilation. Therefore, it is important to detect the optimal configuration of environmental factors for the photosynthesis of alpine meadow ecosystems. In this study, based on 10-year flux and corresponding environmental observations in a typical alpine meadow ecosystem, the optimal environmental configuration that could realistically occur in the natural world for photosynthesis was detected. The results indicated that the temperature and water conditions were the primary limiting factors, as radiation resources are abundant on the Tibetan Plateau. The optimal temperature for photosynthesis (TA opt) was determined to be 11.92 ℃ based on the entire observation dataset, with a maximum photosynthetic capacity (GPP max) of 0.20 mg CO 2 m−2 s−1. However, the TA opt and the corresponding GPP max could be elevated when the soil water content (SWC) was abundant. When SWC exceeded 0.26 m3 m−3, TA opt increased to 13.41 ℃, and the corresponding GPP max reached as high as 0.30 mg CO 2 m−2 s−1, which is the maximum the ecosystem could reach. Thus, the optimal environmental configuration for photosynthesis that could realistically occur in the natural world in this alpine meadow was air temperature (TA)=13.41 ℃, SWC=0.28 m3 m−3, vapor pressure deficit (VPD)=0.61 kPa, net radiation (RN)=411.53 J m−2 s−1. According to this study, it could be inferred that within a reasonable range, higher temperatures and VPD would benefit photosynthesis in this alpine meadow as long as the soil water supply is sufficient. The climate on the Tibetan Plateau is arid with high VPD and is experiencing warming due to climate change. Consequently, alpine ecosystems situated in relatively humid regions with sufficient soil water resources may exhibit greater potential for carbon sequestration than previously estimated. [ABSTRACT FROM AUTHOR]

• Proximal remote sensing tools can be used for estimating gross primary productivity. • The most relevant electromagnetic regions were ∼550 nm and ∼710 nm. • Daily gross primary productivity was related to Plant Senescence Reflectance Index (PSRI) and the Greenness Index (GCC). • Sun Induced Fluorescence (SIF) was not a good predictor for GPP. Salt marshes are highly productive ecosystems relevant for Blue Carbon assessments, but information for estimating gross primary productivity (GPP) from proximal remote sensing (PRS) is limited. Temperate salt marshes have seasonal canopy structure and metabolism changes, defining different canopy phenological phases, GPP rates, and spectral reflectance. We combined multi-annual PRS data (i.e., PhenoCam, discrete hyperspectral measurements, and automated spectral reflectance sensors) with GPP derived from eddy covariance. We tested the performance of empirical models to predict GPP from 12 common vegetation indices (VIs; e.g., NDVI, EVI, PSRI, GCC), Sun-Induced Fluorescence (SIF), and reflectance from different areas of the electromagnetic spectrum (i.e., VIS-IR, RedEdge, IR, and SIF) across the annual cycle and canopy phenological phases (i.e., Greenup, Maturity, Senescence, and Dormancy). Plant Senescence Reflectance Index (PSRI) from hyperspectral data and the Greenness Index (GCC) from PhenoCam, showed the strongest relationship with daily GPP across the annual cycle and within phenological phases (r2=0.30–0.92). Information from the visible-infrared electromagnetic region (VIS-IR) coupled with a partial least square approach (PLSR) showed the highest data-model agreement with GPP, mainly because of its relevance to respond to physiological and structural changes in the canopy, compared with indices (e.g., GCC) that particularly react to changes in the greenness of the canopy. The most relevant electromagnetic regions to model GPP were ∼550 nm and ∼710 nm. Canopy phenological phases impose challenges for modeling GPP with VIs and the PLSR approach, particularly during Maturity, Senescence, and Dormancy. As more eddy covariance sites are established in salt marshes, the application of PRS can be widely tested. Our results highlight the potential to use canopy reflectance from the visible spectrum region for modeling annual GPP in salt marshes as an example of advances within the AmeriFlux network. [ABSTRACT FROM AUTHOR]

• SOS NDVI dates occurred much earlier than SOS dates from EVI, LSWI, GPP, and SIF. • SOS LSWI dates were more linearly consistent with SOS GPP and SOS SIF than EVI and NDVI. • Temperature analysis showed that early SOS NDVI dates were more likely affected by snowmelt. Accurate phenology characterization is of great importance for measuring ecosystem dynamics, especially for carbon and water exchange between land and the atmosphere. Vegetation indices (VIs), calculated from land surface reflectance, are widely used to estimate phenology from the leaf and canopy structure perspective. Gross Primary Production (GPP) and solar-induced chlorophyll fluorescence (SIF) are used to estimate phenology from the canopy functional (physiological) perspective. To what degree are the spring phenology estimated from these different perspectives consistent with each other? In this study, we evaluated the consistency of the start of the growing season (SOS) in spring for snow-covered evergreen needleleaf forests (ENF) and deciduous broadleaf forests (DBF) using three vegetation indices, in-situ GPP data from the eddy covariance flux towers (GPP EC), GPP data from the Vegetation Photosynthesis Model (GPP VPM), and SIF data from the GOME-2. Results showed that SOS NDVI dates were much earlier than SOS dates from EVI (SOS EVI), land surface water index (LSWI) (SOS LSWI), GPP (SOS GPP ; SOS GPP-EC , SOS GPP_VPM) and SIF (SOS SIF) for both snow-covered evergreen needleleaf forest (ENF) and deciduous broadleaf forest (DBF). SOS LSWI dates were more linearly correlated with SOS GPP and SOS SIF than SOS dates from NDVI and EVI. At ENF sites, SOS LSWI dates were 17 (± 27) days later and SOS EVI were 25 (± 34) days later than SOS GPP_EC dates. At DBF sites, SOS LSWI and SOS EVI dates were 1-week (± 13 days) later than SOS GPP_EC dates. In the snow-covered regions at mid- to high-latitude in the Northern Hemisphere, SOS LSWI dates were 2˜3 weeks (± 5 days) later than those of SOS GPP_VPM and SOS SIF for both ENF and DBF. Our results clearly highlight the need for further investigation of NDVI-based SOS dates, which were likely affected by snowmelt in snow-covered forests, and the potential of LSWI for tracking the effects of snow on SOS dates. Estimations of SOS dates in snow-covered forests should consider the effects of both snow cover and temperature on leaf emergence (green-up) and gross primary production. [ABSTRACT FROM AUTHOR]

• Leaf chlorophyll and N contents with LAIc showed significant quadratic relationships. • Drought and rewatering impact the vertical distributions of N, Chl, and photosynthetic activities. • Watering regimes increase the sensitivity of N changes to changes in Chl. • Associations between Chl and N contents indicate responses to drought and rewatering. In this study, we characterize the vertical leaf distribution of chlorophyll (Chl) and nitrogen (N) content and their associations with leaf photosynthetic responses in Zea mays L. under field watering regimes. We simulated five precipitation patterns, including a drought-rewatering sequence using an electric-powered, rainproof shelter. The results indicate the vertical leaf Chl and N distribution versus the cumulative leaf-area index (LAIc) fit well into a significant quadratic function. The simulated precipitation patterns significantly influenced the parabolic curve trajectory patterns and their parameters. Chlorophyll and N contents had the same trend, with a close and positive relationship. Drought stress followed by rewatering increased the slopes of the linear equations but narrowed the parabolic opening of the quadratic functions. This finding implies that the relationship between Chl and N content can be used to estimate responses to drought and rewatering. The findings also suggested that the relationship patterns between Chl and N levels could be an assessment tool for N-fertilizer managements under different drought conditions to maintain high yields in maize production. Principal component analysis indicated the correlations between functional traits in maize leaves and the responses to drought and rehydration. These findings help to improve drought management and cultivar selection, which will be important in coping with the severe intensity and high frequency of episodic drought events expected from climate change. [ABSTRACT FROM AUTHOR]

• SIF captures seasonal GPP dynamics better than EVI over the TP. • SIF shows strong response to interannual variability of snow cover. • SIF shows weak response to interannual variability of summer precipitation. Snow cover, which has been declining over recent decades because of rising temperatures, impacts alpine vegetation in various ways on the Tibetan Plateau (TP). However, it is still unclear how the alpine ecosystem responses to the rapid changes of snow cover on the TP. Here, we use the novel spaceborne measurements of solar-induced fluorescence (SIF) from the GOME-2 instrument, a direct proxy of photosynthetic activity, along with traditional vegetation indices (VIs) to study the responses of an alpine ecosystem to changes in snow cover over the TP. We find that seasonal dynamics of SIF are more consistent with alpine vegetation gross primary productivity (GPP) than those of enhanced vegetation index (EVI), suggesting the decoupling of photosynthesis and changes in greenness-based VIs. The snow cover explains most of the interannual variability of SIF, with secondary effects due to summer air temperature, while summer precipitation has little impact on alpine vegetation photosynthesis, indicating the critical role of snow cover in regulating alpine vegetation growth on the TP. This study suggests that the alpine vegetation photosynthesis on the TP is highly dependent on the snow cover at the start of the growing season and air temperature at the end of the growing season. Our results also demonstrate that the on-going satellite measurements of SIF shed new light on the understanding of future vegetation growth and vegetation–atmosphere interactions under a changing climate on the TP. [ABSTRACT FROM AUTHOR]

• An alternative method for improving the MODIS GPP over East Asia is proposed. • The approach combines high and middle resolution land cover maps for LUE. • New meteorological thresholds to climate classes are applied instead of the BPLUT. • The approach-derived GPP showed higher accuracy than MODIS GPP. • The optimization of the VPDmin parameter was effective in East Asia. Gross primary production (GPP) is a crucial factor in the carbon cycle especially for the absorption of carbon dioxide into the biosphere from the atmosphere. A large discrepancy between a satellite-based GPP product named MOD17A2H GPP and in-situ data measured at eddy covariance flux towers has been identified over East Asia where the biome types and climatic characteristics are heterogeneous with rugged terrain. For that reason, this study focuses on two potential major error sources in MOD17A2H GPP, which are the coarse resolution land cover information and inappropriate meteorological parameters. The finer resolution observation and monitoring global land cover (FROM-GLC) and the MODIS land cover product collection 5.1 (MCD12Q1) were used to describe biome types in detail, by combining spatial distribution from FROM-GLC and the phenological characteristics of land cover from MCD12Q1. Meteorological parameters were optimized using the 55-years Japanese reanalysis meteorological data (JRA-55). The light use efficiency of the MOD17 GPP algorithm was modified using the combined land cover information (FROM-MCD). Although the use of FROM-MCD and JRA-55 did not improve MOD17A2H GPP, the optimization of two meteorological parameters—daily minimum air temperature (TMIN) and vapor pressure deficit (VPD) significantly improved the GPP algorithm for East Asia. The results show that the root mean square errors (RMSEs) between the estimated and in situ GPPs decreased from 21.83 (gC/m2/8days) to 16.11 (gC/m2/8days) through optimizing the two parameters at 9 flux tower sites. The optimized TMIN and VPD thresholds in the MOD17 GPP algorithm were applied to the entire study area (i.e., East Asia) according to the Köppen-Geiger climate classes. The estimated GPP using the proposed approach was compared to GPPs from widely used process-based models (i.e., VISIT, BEAMS, and BESS), which confirmed that the proposed approach with locally optimized meteorological parameters improved on the underestimation of the MOD17 GPP algorithm for East Asia. The uncertainty of the VPDmin parameter was revealed to be larger than that of TMINmax. [ABSTRACT FROM AUTHOR]

• The forest floor contributed 43–49% to the total production of the stand. • The annual cycle of forest floor vegetation lagged that of pines in the spring. • Forest floor photosynthesis had a notable interannual variability. • Annual variation in the photosynthetic production and length increment were not connected. • The carbon sink at the site was highest in the warmest year. We studied the inter- and intra-annual dynamics of the photosynthesis of forest floor vegetation and tree canopy in a subarctic Scots pine stand at the northern timberline in Finland. We tackled the issue using three different approaches: 1) measuring carbon dioxide exchange above and below canopy with the eddy covariance technique, 2) modelling the photosynthesis of the tree canopy based on shoot chamber measurements, and 3) upscaling the forest floor photosynthesis using biomass estimates and available information on the annual cycle of photosynthetic capacity of those species. The studied ecosystem was generally a weak sink of carbon but the sink strength showed notable year-to-year variation. Total ecosystem respiration and photosynthesis indicated a clear temperature limitation for the carbon exchange. However, the increase in photosynthetic production was steeper than the increase in respiration with temperature, indicating that warm temperatures increase the sink strength and do not stimulate the total ecosystem respiration as much in the 4-year window studied. The interannual variation in the photosynthetic production of the forest stand mainly resulted from the forest floor vegetation, whereas the photosynthesis of the tree canopy seemed to be more stable from year to year. Tree canopy photosynthesis increased earlier in the spring, whereas that of the forest floor increased after snowmelt, highlighting that models for photosynthesis in the northern area should also include snow cover in order to accurately estimate the seasonal dynamics of photosynthesis in these forests. [ABSTRACT FROM AUTHOR]

Highlights • Canopy conductance and SIF show similar diurnal and seasonal patterns. • Tower-based and satellite-based SIF significantly correlate with canopy conductance. • Model integrated SIF generally yields reasonable estimation of transpiration. • Drought decouples the relationship between carbon and water exchange. Abstract Vegetation transpiration (T) is the process of plant water loss through the stomata on the leaf surface and plays a key role in the energy and water balance of the land surface, especially with dense vegetation cover. To date, however, estimation of ecosystem-scale T is still rather uncertain mainly due to errors in modeling canopy resistance or conductance. Considering the intrinsic link between photosynthesis and chlorophyll fluorescence, the recent available remote sensing of solar-induced chlorophyll fluorescence (SIF) provides a valuable opportunity to estimate plants T at large scales. In this study, we demonstrate how remote sensing of SIF relates to canopy stomatal conductance and transpiration at diurnal and seasonal scales with continuous ground measurements of SIF at three flux sites in forest, cropland and grassland ecosystems. The results show that both ground and spaceborne SIF observations are good indicators of canopy conductance at both diurnal and seasonal scales (R2 = 0.57 and 0.74 for forest, R2 = 0.62 and 0.80 for cropland, R2 = 0.52 and 0.63 for grassland, respectively). Then, empirical SIF-based canopy conductance models are employed to estimate hourly and daily transpiration. We evaluate our ecosystem T estimations against latent heat fluxes measured by eddy covariance systems with more satisfactory results for forest (R2 = 0.57 and 0.71), and cropland (R2 = 0.77 and 0.83) than for grassland (R2 = 0.13 and 0.22) at hourly and daily time scales. Our results suggest the potential of remotely-sensed SIF for estimating canopy conductance and plant transpiration, but a more mechanistic understanding is needed for their link. [ABSTRACT FROM AUTHOR]

Highlights • The modulation of elevated CO 2 on stomatal response to progressive drought was studied in tomato plants. • Elevated CO 2 retarded the response of photosynthesis and stomatal conductance to soil water deficits. • The responsiveness of stomatal conductance to ABA was unaffected by CO 2 environment. • Elevated CO 2 enhanced both water use efficiency and nitrogen use efficiency in tomato plants. Abstract The objective of this study was to investigate the response of leaf gas exchange of tomato plant to progressive drought stress under ambient (a [CO 2 ], 400 ppm) and elevated (e [CO 2 ], 800 ppm) atmospheric CO 2 concentration. The fraction of transpirable soil water (FTSW) was used to evaluate soil water status in the pots. The results showed that stomatal conductance (g s) and transpiration rate (T r) were significantly lower while the net photosynthetic rate (A n) was significantly higher in plants grown under e [CO 2 ] than those under a [CO 2 ] at onset of drought stress. Along with soil drying, the FTSW thresholds at which g s and A n started to decrease were significantly lower in plants grown under e [CO 2 ] as compared to plants grown under a [CO 2 ]. The intrinsic water use efficiency and instantaneous water use efficiency of plants grown under e [CO 2 ] was significantly higher than those under a [CO 2 ]. Under e [CO 2 ], the drought-stressed plants had greater leaf area, dry matter and water use efficiency than those grown under a [CO 2 ]. e [CO 2 ] notably enhanced shoot C concentration while decreased shoot N concentration hereby increased the C:N ratio. With the decrease of FTSW, the concentration of abscisic acid in leaf ([ABA] leaf) and xylem sap ([ABA] xylem) increased exponentially. When FTSW > 0.2, under both CO 2 environments, g s decreased linearly with increasing [ABA] leaf and [ABA] xylem ; and similar slopes but different intercepts were noticed for the regression lines, indicating that the responsiveness of g s to ABA was unaffected by CO 2. In conclusion, CO 2 elevation retarded the response of leaf gas exchange to progressive soil drying in tomato plants. This result provides novel knowledge for more precise prediction of plant response to drought stress in a future CO 2 -enriched environment. [ABSTRACT FROM AUTHOR]

Graphical abstract We calibrated and implemented a new phenology module for evergreen conifers in the global model ORCHIDEE with an explicit representation of both needle budburst and senescence. The new phenology module now allows to represent the seasonality of observed leaf area for evergreen conifers at the regional scale. Sensitivity tests in ORCHIDEE show a strong impact on the simulated carbon cycle for which we highlighted a 15% increase of the growth primary productivity and a doubling of the needle turnover compared to default simulations. We argue that global ecosystem models have to simulate explicit phenological processes for evergreen species if we want to improve future projections of the carbon budget. Highlights • A new module with explicit budburst and senescence for coniferous is developed. • It reproduces observed budburst and leaf area index dynamics. • Budburst models calibrated on sites lose predictability at a coarser resolution. • Future projections showed an advancement of the budburst of 12.3 ± 4.1 days in 2100. • Explicit phenology increases the simulated carbon assimilation of conifers by 15%. Abstract Global ecosystem models lack an explicit representation of budburst and senescence for evergreen conifers despite their primordial role in the carbon cycle. In this study we evaluated eight different budburst models, combining forcing, chilling and photoperiod, for their ability to describe spring budburst, and one model of needle senescence for temperate evergreen coniferous forests. The models' parameters were optimized against field observations from a national forest monitoring network in France. The best fitting budburst model was determined according to a new metrics which accounts for both temporal and spatial variabilities of budburst events across sites. The best model could reproduce observed budburst dates both at the site scale (±5 days) and at regional scale (±12 days). We also showed that the budburst models parameterized at site scale lose some predictive capability when applied at coarser spatial resolution, e.g., in grid-based simulations. The selected budburst model was then coupled to a senescence function defined from needle survivorship observations in order to describe the full phenology cycle of coniferous forests. Implemented in the process-driven ecosystem model ORCHIDEE, this new conifer phenology module represented accurately the intra and inter-annual dynamics of leaf area index at both the local and regional scales when compared against MODIS remote sensing observations. A sensitivity analysis showed only a small impact of the new budburst model on the timing of the seasonal cycle of photosynthesis (GPP). Yet, due to the faster renewal of needles compared to the standard version of ORCHIDEE, we simulated an increase in the GPP by on average 15% over France, while the simulated needle turnover was doubled. Compared to 1970–2000, projections indicated an advancement of the budburst date of 10.3 ± 2.8 and 12.3 ± 4.1 days in average over the period 2060–2100 with the best forcing and chilling-forcing models respectively. Our study suggests that including an explicit simulation of needle budburst and senescence for evergreen conifers in global terrestrial ecosystem models may significantly impact future projections of carbon budgets. [ABSTRACT FROM AUTHOR]

Highlights • Soil respiration (Rs) was measured over five growing seasons in northern China. • Light and moderate thinning increased the autotrophic respiration (Ra). • Thinning intensity had no significant effect on heterotrophic respiration (Rh). • Thinning effects on Ra and Rh were related to different biotic processes involved. • Effects of thinning on soil respiration components varied over time. Abstract Understanding the responses of soil respiration (Rs) to thinning is essential to evaluate the effects of management practices on carbon cycling in plantation forest ecosystems. However, how Rs and its components (autotrophic, Ra and heterotrophic respiration, Rh) vary with thinning intensity and the underlying mechanisms are not well understood. In the present study we monitored Rs, Ra and Rh over five growing seasons using a trenching method in a Pinus tabuliformis plantation subjected to four thinning treatments (no thinning, CK; light thinning, LT; moderate thinning, MT and heavy thinning, HT). On average, LT and MT significantly increased Rs by 13% and 17%, respectively, compared with the CK. These increments of Rs were ascribed to the enhanced Ra in LT and MT plots, because light and moderate thinning promoted root growth and productivity (higher fine root biomass). However, HT did not result in a further increase in Ra, suggesting that increases in the activity of remaining trees and understory plants did not compensate for the reduced photosynthesis and the amount of respiring tree roots by extensive tree-cut. In contrast to Ra, variation in Rh was unrelated to thinning, partly due to the stable forest floor mass (non-living organic materials such as litter and fine woody debris) and microbial biomass carbon content (MBC) between thinned and control plots. The temperature sensitivity (Q 10) of Ra and Rh ranged from 1.40 to 3.07 and 2.34–3.42, respectively. The highest Q 10 of Ra was observed in MT while that of Rh occurred in LT. Soil moisture was significantly correlated with Rh but a poor predictor for Ra. Our findings demonstrated that Ra and Rh responded to thinning intensity independently of each other. The intensity of management and plant-mediated biological processes are of particular importance in evaluating the impacts of forest management on C sequestration potential in plantation forests. [ABSTRACT FROM AUTHOR]

We used eddy-covariance (EC) measurements of net ecosystem exchange (NEE) above canopy to assess the effects of thinning on CO 2 fluxes at the ICOS Sweden site Norunda in central Sweden. This forest site consists of mixed pine and spruce stands approx. 100 years old. The thinning during late autumn 2008, performed in a semi-circle from the mast extending 200 m outwards harvested about 25% of the volume. Measurements were conducted from 2007 to 2016 and thus, above canopy fluxes were recorded two years before and eight years after the thinning. We also measured the net flux from the forest floor with automatic chambers in three locations and with below-canopy EC during shorter periods before and after thinning. The chamber measurements during the first part of the growing season after thinning showed strongly enhanced effluxes in the order of 150–250% of the pre-thinning values. These chamber measurements were made on drier places within the thinned area because waterlogging made it impossible to use chambers at all available locations. The below-canopy EC measurements, which had a larger footprint as compared to the chambers, showed less enhanced fluxes (in the order of 35%). This footprint included also wetter areas. The above canopy EC measurements showed a reduction of daytime net flux by approx. 30% during the first summer after thinning. The median growing season fluxes then slowly increased but were not restored to the pre-thinning levels eight years after thinning. There was also a small decrease in growing season ecosystem respiration during the first summer after thinning and with a continued decreasing trend over time. It was concluded that this decrease in respiration was caused by successively decreasing decomposition of coarse organic substrates resulting from the thinning. This respiration decrease over time persisted even under gradual biomass increase, which otherwise would indicate increasing autotrophic respiration. The light-response and respiration models fitted to all data did not show any trends in daytime or nighttime fluxes so the conclusion was that the trends were caused by the thinning and not because of trends in meteorological drivers. The annual values contrasted with the summertime results since only a minor effect was observed on the annual NEE. Both ecosystem respiration and gross primary productivity were reduced as an effect of thinning. We explained the different summertime versus annual effects to be caused by the decrease in ecosystem respiration since respiration is dominating the NEE during non-growing season periods when photosynthesis is very low or even zero. Our results are a strong indication that the NEE of a forest could be maintained over time with harvesting practices that avoids clear-cutting and thereby enhance the total carbon uptake of forests. [ABSTRACT FROM AUTHOR]

The flux-variance similarity (FVS) partitioning method to estimate transpiration/photosynthesis and evaporation/respiration, using only high frequency Eddy Covariance (EC) measurements, was studied. The FVS method was applied to two crops in successive growing seasons of a typical cropping system in Mediterranean region: fava bean followed by winter wheat. FVS applies the flux-variance arguments derived from Monin-Obukhov similarity theory separately to the stomatal (photosynthesis and transpiration) and non-stomatal (respiration and evaporation) processes. The leaf-level water use efficiency, an input of FVS method, is here calculated by using EC outputs and estimated humidity after the direct measurement of surface infrared temperature. The two experimental seasons were characterized by exceptionally rainy periods (262 mm in 85 days in 2014, 344 mm in 149 days in 2015). Nevertheless, the partitioning results are consistent with expected trends and absolute values of flux components throughout both seasons. In particular, heterotrophic soil respiration measured by chamber systems and modelled FVS respiration components are comparable at the beginning and at the end of the growing crop cycles, when crop biomass and leaf area are very low. Furthermore, the coupling of FVS method and root exclusion method for measuring soil respiration is able to give the heterotrophic and autotrophic components of respiration. Finally, the results showed that the succession fava bean to wheat permits a mitigation of the loss of carbon to the atmosphere and increases carbon sequestration. [ABSTRACT FROM AUTHOR]

• This study mapped the primary climatic constraint on alpine plant photosynthesis. • Peak plant growth timing (DOY Pmax) was delayed 1.1 ± 0.1 days/100 m along elevation. • Elevational gradient in DOY Pmax decreased by −0.8 ± 0.2 days/100 m/decade since 2001. The Tibetan Plateau has experienced elevation-dependent climate warming, which has profoundly influenced the seasonal dynamics of plant growth. However, how peak photosynthesis timing (DOY Pmax), a key component of plant growth seasonality, responds to climate change on the Tibetan Plateau remains unclear. Here, we investigated the change in the elevational gradient in DOY Pmax on the Tibetan Plateau during 2001–2018 and its drivers. We mapped the primary climatic constraint on plant photosynthesis and found that it was temperature at 3000–4000 m a.s.l. in the central and eastern parts but soil water at 4000–5000 m a.s.l. in the southwestern part. DOY Pmax increased by 1.0 ± 0.1 days/100 m with increasing elevation from 3000 to 5000 m a.s.l., but the elevational gradient in DOY Pmax decreased by -0.8 ± 0.2 days/100 m/decade during 2001–2018 due to both direct and indirect effects of climate change. Specifically, at 3000–4000 m a.s.l., DOY Pmax was delayed because of the direct effect of the increase in soil water. At 4000–5000 m a.s.l., DOY Pmax advanced due to the warming-induced earlier green-up date in the central plateau and the drought-induced later spring phenology in the southwestern plateau. Such a change in plant growth seasonality should alter seasonal carbon cycle of alpine ecosystems, summer diets of the migrant herbivores and alpine plant–animal interactions along elevation gradients, but further efforts are needed to clarify how herbivores that migrate long distances, e.g., Tibetan antelope, adapt to changes in the elevational gradient in peak plant growth timing. [ABSTRACT FROM AUTHOR]

• The flash drought events in the Pearl river basin are analyzed by a new method. • The flash drought event has developed more rapidly. • Except in summer, flash droughts in spring and autumn should be taken seriously. • Response time of crops to flash drought is the fast compared to other vegetations. Flash drought events pose serious threats to terrestrial ecosystems due to their rapid intensification. However, the comprehensive assessment of recovery stage in flash drought is hindered by the insufficient consideration of reduplicative decline in soil moisture. Besides, how the vegetation photosynthesis respond to flash drought remains unknown. Here, a new method for explicitly characterizing flash drought events was proposed, incorporating both development rate and duration, with particular emphasis on the process of soil moisture change during the recovery stage. Then the temporal and spatial evolutions of the flash drought over the Pearl River Basin were analyzed. Solar-induced chlorophyll fluorescence (SIF) was used to explore the responses of different vegetation types to flash drought. The results indicated that the onset speed may be increasing, and the flash drought in 2007 was quite serious. Most flash drought events lasted 32 to 48 days. Besides, this study focused on the response of forests, grasslands and crops to flash drought, and the forestlands were less sensitive to flash droughts, while croplands experienced the most flash drought events, and the time of photosynthesis loss of croplands was the shortest. Moreover, precipitation deficit, high temperature, high evapotranspiration (ET) and high potential evapotranspiration (PET) were the main driving factors triggering flash drought. The soil moisture was above 40th percentile after the end of a flash drought, which demonstrate the accuracy of the framework in identifying the development of flash drought in the concern area. Our findings also demonstrated the great effectiveness of SIF in monitoring the resistance of ecosystems, deepening our understanding of the response of vegetation photosynthetic capacity to flash drought events. [ABSTRACT FROM AUTHOR]

In nearly all large-scale terrestrial ecosystem models, soil respiration is represented as a function of soil temperature. However, the relationship between soil respiration and soil temperature is highly variable across sites and there is often a pronounced hysteresis in the soil respiration-temperature relationship over the course of the growing season. This phenomenon indicates the importance of biophysical factors beyond just temperature in controlling soil respiration. To identify the potential mechanisms of the seasonal soil respiration-temperature hysteresis, we developed a set of numerical models to demonstrate how photosynthesis, soil moisture, and soil temperature, alone and in combination, affect the hysteresis relationship. Then, we used a variant of the model informed by observations of soil respiration, soil temperature, photosynthesis, and soil moisture from multiple mesic and semi-arid ecosystems to quantify the frequency of hysteresis and identify its potential controls. We show that the hysteresis can result from the seasonal cycle of photosynthesis (which supplies carbon to rhizosphere respiration), and soil moisture (which limits heterotrophic respiration when too low or too high). Using field observations of soil respiration, we found evidence of seasonal hysteresis in 9 out of 15 site-years across 8 diverse biomes. Specifically, clockwise hysteresis occurred when photosynthesis preceded seasonal soil temperature and counterclockwise hysteresis occurred when photosynthesis lagged soil temperature. We found that across all sites, much of the respiration-temperature lag was explained by the decoupling of photosynthesis and temperature, highlighting the importance of recently assimilated carbon to soil respiration. An analysis of observations from 129 FLUXNET sites revealed that time lags between gross primary productivity (a proxy for canopy photosynthesis) and soil temperature were common phenomena, which would tend to drive counterclockwise hysteresis at low-latitude sites and clockwise hysteresis at high-latitude sites. Collectively, our results show that incorporating photosynthesis and soil moisture in the standard exponential soil respiration-temperature model (i.e., Q 10 model) improves the explanatory power of models at local scales. [ABSTRACT FROM AUTHOR]

Photosynthesis plays an important role in terrestrial carbon cycle, and simulation of photosynthesis through terrestrial biosphere models usually requires a specification of maximum carboxylation rate ( V cmax ). However, estimating V cmax by gas-exchange experiments is laborious and tedious, resulting in a general paucity of V cmax data. In this study, a reliable assimilation scheme to derive temporally continuous V cmax from measured sunlit gross photosynthesis productivity (GPP) was proposed and validated at three Canadian tower flux sites. To fulfill this purpose, the Boreal Ecosystem Productivity Simulator (BEPS) and light response curve were combined to separate the eddy covariance GPP data into sunlit GPP and shaded GPP, due to the lack of measured sunlit GPP. The reliability of V cmax was validated through the correlation analysis between the normalized difference vegetation index (NDVI) and V cmax . To illustrate the advantages of the proposed scheme in our study, BEPS simulated GPP using the derived V cmax from sunlit GPP in our study, the derived V cmax from canopy GPP and the reference V cmax as constants were respectively compared with corresponding eddy covariance GPP measurements. Results showed that (1) the proposed assimilation scheme based on sunlit GPP can be used to derive reliable temporally continuous V cmax . The V cmax obtained in our study was significantly correlated with NDVI (R 2  = 0.77); (2) the seasonal variations in V cmax could significantly improve the accuracy of photosynthesis simulation. The GPP difference between eddy covariance GPP and BEPS simulated GPP using derived V cmax from sunlit GPP (mean = 0.12, std = 0.92) were significantly smaller than those between eddy covariance GPP and BEPS simulated GPP using reference V cmax as constants (mean = 1.37, std = 1.37); (3) the sunlit GPP is able to obtain the relatively accurate V cmax that can improve the simulation of photosynthesis. GPP difference between eddy covariance GPP and BEPS simulated GPP using derived V cmax from sunlit GPP (mean = 0.12, std = 0.92) showed lower mean values and standard deviations than those between eddy covariance GPP and BEPS simulated GPP using derived V cmax from canopy GPP (mean = 0.67, std = 1.00). Our study illustrated the reliability that sunlit GPP can be used to derive relatively accurate temporally continuous V cmax , and the assimilation scheme gives new potential to improve the simulation of photosynthesis through terrestrial biosphere models. [ABSTRACT FROM AUTHOR]

Carbohydrates availability, which are directly related to photosynthesis (A N ), and turgor are the main determinants of fruit growth. Since stomatal conductance (g s ) is the main limiting factor of A N in fruit trees in most environments, and is strongly regulated by turgor, its measurement is pivotal to understanding fruit growth dynamics. Despite its relevance, the use of g s to estimate A N faces the major limitation of being difficult to measure in an automated and continuous manner. Based on these observations, and considering the control that the stomata exert on transpiration, and thus on sap flux density (J s ) under conditions of high coupling to the atmosphere, we conducted a multi-faceted experiment in olive trees. The main objective was to assess the use of continuously modelled A N , derived using a simulated g s , as a tool to study fruit growth and oil accumulation and other components of vegetative above-ground growth (leaf area and number of shoot internodes) in a super-high-density olive orchard under different irrigation levels. Sixteen olive trees under four different irrigation treatments (two control and two deficit irrigated, with one and two drip lines each) were continuously monitored with J s sensors from May to November 2016. Gas exchange, fruit growth, number of shoot internodes and leaf area were measured periodically. Stomatal conductance was empirically simulated through J s , and A N was modelled using previously simulated g s and a biochemical model of photosynthesis. Results showed that A N can be accurately modelled from simulated g s , obtained in turn from J s measurements divided by pressure deficit. Moreover, the approach was shown to be sensitive enough to infer the response of g s and A N to soil water content and vapour pressure deficit. Interestingly, accumulated A N was significantly related to fruit growth and oil content for all the irrigation treatments which determine the slope of these relations. In contrast, the relationship with leaf area was only significant for the control irrigation treatments, where the number of shoot internodes increased significantly more than in the water-stressed trees. Our results show that under water stress conditions trees prioritize fruit growth and oil content accumulation over vegetative growth, suggesting a higher sink strength for reproductive growth than for vegetative growth. We conclude that the use of sap flow and the proposed approach provides reliable g s and A N data, and allows the modelling of the relations between carbon assimilation and allocation, which are helpful to estimate fruit growth. [ABSTRACT FROM AUTHOR]

Manual chamber campaigns are a versatile method to study management effects at plot scale in factorial experiments. The eddy covariance technique has the advantage of continuous measurements but it requires large homogeneous areas. By pairing the two techniques, the uncertainties of the CO 2 fluxes modeled from the chamber campaigns can be quantified through cross-validation with the continuous eddy covariance data. This is particularly important in managed ecosystems with high temporal dynamics. At our agricultural site in Northern Germany, we installed both techniques in parallel for two crop cultivation periods, winter oilseed rape in 2012/13 and winter wheat in 2013/14. First, we compared measured net CO 2 exchange (NEE) obtained from the closed chambers with the corresponding half-hourly fluxes from the eddy covariance technique. Despite largely different footprints and measurement windows, the measured fluxes were highly correlated (R 2  = 0.83 in 2012/13 und R 2  = 0.93 in 2013/14). Interpolating from chamber campaigns to the entire measurement period is commonly performed by modeling half-hourly fluxes based on non-linear regressions for photosynthesis and respiration. These modeled fluxes were compared to the fluxes measured with the eddy covariance technique. To understand the observed differences, we performed five modeling setups: 1) Non-linear regressions based algorithm with default settings, 2) non-linear regressions with expert settings, 3) purely empirical modeling with artificial neural networks, 4) cross-validation using eddy covariance measurements as campaign fluxes on original campaign days, and 5) cross-validation on weekly campaign days. The modeled seasonal course of daily NEE agreed well with the eddy covariance measurements for all five setups (R 2 from 0.77 to 0.92) but with periods of systematic offsets in the range of ±5 g C m −2  day −1 . Though the pattern of the offsets was different, all setups had comparable root mean square errors around 1.5 g C m −2  day -1 despite having opposite limitations. Cross-validation by simulating campaigns with artificial gaps from the continuous eddy dataset in setup 4) and 5) resulted in bias errors of around 0.4 g C m −2 day −1 . This translates to a total uncertainty on annual NEE of around ±175 g C m −2  a −1 purely from the modeling, i.e. the interpolation in-between campaigns. By leave-one-campaign-out scenarios, the sensitivity to single campaigns was examined. The mean effect on the annual total was higher for setup 4 (30 g C m −2 ) with the original number of campaigns than for setup 5 (9 g C m −2 ) with four times more campaigns. Furthermore, the interpolation in-between the campaigns can be improved by deriving vegetation proxies from the continuous eddy covariance measurements, such as an effective green area index (GAI) presented herein. [ABSTRACT FROM AUTHOR]

Despite decades of research, gaining a comprehensive understanding of carbon (C) cycling in forests remains a considerable challenge. Uncertainties stem from persistent methodological limitations and the difficulty of resolving top-down estimates of ecosystem C exchange with bottom-up measurements of individual pools and fluxes. To address this, we derived estimates and associated uncertainties of ecosystem C fluxes for a 100–125 year old mixed temperate forest stand at the Bartlett Experimental Forest, New Hampshire, USA, using three different approaches: (1) tower-based eddy covariance, (2) a biometric approach involving C flux measurements of individual ecosystem subcomponents, and (3) an inventory approach involving changes in major C stocks over time. Our analysis made use of 13 years of data, collected over the period from 2004 to 2016. Estimates of mean annual net ecosystem production (NEP) ranged from 120 to 133 g C m −2 , demonstrating strong agreement among methods and suggesting that this aging forest acts as a moderate C sink. The use of multiple approaches to measure C fluxes and their uncertainties helped place constraints on difficult-to-measure processes such as aboveground contributions to ecosystem respiration and belowground allocation to mycorrhizal fungal biomass (which was estimated at 20% of net primary production). Analysis of interannual variability in C fluxes revealed a decoupling between annual wood growth and either current year or lagged NEP or GPP, suggesting that source limitation (C supply) is likely not controlling rates of wood production, at least on an interannual scale. Results also demonstrated a strong association between the maximum rate of C uptake during the growing season (Amax) and the length of the vernal window, defined as the period of time between soil thaw and the onset of photosynthesis. This suggests an important, but poorly understood, influence of winter and spring climate on mid-summer canopy physiology. Efforts to resolve the mechanisms responsible should be prioritized in light of ongoing and predicted changes in climate for the northeastern U.S. region, particularly during the winter and winter-spring transition period. [ABSTRACT FROM AUTHOR]

In models of photosynthetic gas exchange, leaf temperature ( T leaf ) is often calculated using a combination of derivations of the energy balance equation and measurements of air temperature ( T air ). Yet, there are frequently large differences between T leaf and T air under natural field conditions, and an energy balance is complicated in complex canopies, especially in tropical ecosystems. In the present study, we aimed to quantify the variation in T leaf relative to T air under naturally varying PPFD values in two representative species ( Espeletia grandiflora and Chusquea tessellata ) of a tropical alpine ecosystem (páramo, Colombian Andes) during both wet and dry seasons. The results of a Structural Equation Model showed that T leaf was strongly correlated with changes in T air during both seasons, but large differences (up to 14 °C) occurred between T air and T leaf , during the dry season when PPFD varied the most, especially in C. tessellata . Thus, using T air to proximate T leaf under variable conditions of incident sunlight could generate substantial errors in estimates of temperature-sensitive physiological processes. These results should be valuable for evaluating the accuracy of carbon and water exchange models within current and future scenarios of climate change in tropical páramos, as well as other ecosystems. [ABSTRACT FROM AUTHOR]

The eddy covariance method is regularly used for measuring gas fluxes over agricultural fields and natural ecosystems. For many applications, it is desirable to partition the measured fluxes into constitutive components: the water vapor flux into transpiration and direct evaporation components, and the carbon dioxide flux into photosynthesis and respiration components. The flux variance similarity (FVS) partitioning method is based on flux variance similarity relationships and correlation analyses of high-frequency eddy covariance data ( Scanlon and Sahu, 2008; Scanlon and Kustas, 2010, 2012 ). The FVS method is relatively complex computationally, and that complexity has likely been an impediment to greater use and testing of the procedure. In this work, we present a new algebraic solution to the key computational task in the partitioning algorithm, which significantly simplifies the FVS method. We also introduce Fluxpart, a free and open source Python 3 module that implements the FVS partitioning procedure. Example flux partitioning calculations are presented. [ABSTRACT FROM AUTHOR]

Temperate and boreal conifer forests are dormant for many months during the cold season. Climate change is altering the winter environment, with increased temperature, altered precipitation, and earlier snowmelt in many locations. If significant enough, these changes may alter patterns of dormancy and activity of evergreens. Here we studied the factors limiting photosynthetic activity of a high-elevation subalpine forest that has undergone substantial warming in recent decades. We tested the hypothesis that this warming has been significant enough to allow photosynthesis during sunny warm days in winter. Using thermal imagery, we found that foliage in winter was sometimes near the temperature optimum for photosynthesis, but no net carbon gain occurred for most of the cold season. Water transport was limited by blockage of sap transport by frozen boles, but not by frozen soils. Foliar carotenoid content was much higher during winter, driven largely by increases in the pool size of the photoprotective xanthophyll cycle. There was no seasonal change in chlorophyll or lutein content. Net carbon uptake began only as boles thawed, with no difference in timing among tree species, and the spring increase in canopy-level photosynthetic capacity occurred before sap transport was detected. The seasonality of gross primary productivity (GPP) was strongly linked to seasonality of xanthophyll cycle deepoxidation state in all species. Seasonality of GPP was detectable with two metrics of canopy color – the Green Chromatic Coordinate and Green-Red Vegetation Index (a proxy for the newly proposed MODIS-based chlorophyll/carotenoid index or CCI). Both indices were significantly correlated with GPP. Together these results indicate the potential for airborne or near-surface remote sensing of leaf color to serve as a metric of photosynthetic activity in evergreen forests, and to monitor physiological changes associated with the progression in and out of winter dormancy. [ABSTRACT FROM AUTHOR]

Recent earlier greening trends are believed to enhance terrestrial ecosystem productivity. However, advanced onset of growing season may also deplete soil water in early spring, leading to summer water stress for plant growth. In this study, we linked soil moisture with start of growing season (SGS, represented by day of year) to examine the responses of ecosystem productivity to water stress during 1982–2011 on the Mongolian Plateau. Results showed that, though not significant, earlier SGS has tendency to enhance spring productivity at north part of the study area. Nonetheless, we observed that suppressed summer photosynthesis due to phenology-induced water stress dramatically reduced annual carbon assimilation. Thus, phenology-associated changes in soil moisture have profound potential in regulating seasonal and annual productivity in arid and semi-arid ecosystems. The relationship between SGS and GPP was not observed in more mesic forest ecosystems (R 2 = 0.04, p > 0.10) nor in the agricultural area (R 2 = 0.03, p > 0.10) where practices like irrigation aim to alleviate summer water stress. Therefore, at the scale of the entire study area, earlier growing season did not translate to higher productivity (R 2 = 0.006). On the contrary, advanced SGS aggravated growing-season water stress, which in turn, supressed annual carbon assimilation in water limited area. This mechanism implies the advanced greening trends may not necessarily lead to more carbon uptake in terrestrial ecosystems but rather a carbon loss, especially in the arid and semi-arid regions. [ABSTRACT FROM AUTHOR]

Energy flow through ecosystems plays a critical role in processes at multiple spatial and temporal scales, from phonologically driven growing season or monthly temporal scales of landscapes to sub-diurnal responses of soil respiration to temperature, photosynthesis and water inputs. The interaction of short and longwave radiation and their partitioning through ecosystems is complex with terrestrial canopies and aquatic structure both connecting above- and below-ground processes via energy fluxes. Previous work has shown that at 30-min timescales, only 8% of eddy covariance sites in the La Thuile dataset observe energy closure and when averaged to 24-h timescales, this goes up to 45%. This work examines the effect of temporal lags in energy storage in both terrestrial and aquatic ecosystems. Analyses show energy storage terms have unique temporal lags that vary between ecosystem and time of year, from having zero lag to several hour timelags within terrestrial ecosystems, depending primarily on water content. Large differences between ecosystem types are also highlighted as aquatic ecosystems have lags that range between daily and monthly timescales. Furthermore, ecosystem disturbance can alter time-lags as well and results from a native bark beetle disturbance show both vegetation and soil lag increasing following changes to ecosystem processes from tree mortality. Considering energy storage lags can improve site energy closure in 20% of site-days in the FLUXNET2015 dataset and these results will lead to a better understanding of surface energy budget closure as well as highlighting the importance of time-dependency of ecosystem energy fluxes as a unique method to infer ecosystem processes. [ABSTRACT FROM AUTHOR]

As the lifetime of regional flux networks approach twenty years, there is a growing number of papers that have published long term records (5 years or more) of net carbon fluxes between ecosystems and the atmosphere. Unanswered questions from this body of work are: 1) how variable are carbon fluxes on a year to year basis?; 2) what are the biophysical factors that may cause interannual variability and/or temporal trends in carbon fluxes?; and 3) how does the biophysical control on this carbon flux variability differ by climate and ecological spaces? To address these questions, we surveyed published data from 59 sites that reported on five or more years of continuous measurements, yielding 544 site-years of data. We found that the standard deviation of the interannual variability in net ecosystem carbon exchange (162 gC m −2 y −1 ) is large relative to its population mean (−200 gC m −2 y −1 ). Broad-leaved evergreen forests and crops experienced the greatest absolute variability in interannual net carbon exchange (greater than ±300 gC m −2 y −1 ) and boreal evergreen forests and maritime wetlands were among the least variable (less than  ±40 gC m −2 y −1 ). A disproportionate fraction of the yearly variability in net ecosystem exchange was associated with biophysical factors that modulated ecosystem photosynthesis rather than ecosystem respiration. Yet, there was appreciable and statistically significant covariance between ecosystem photosynthesis and respiration. Consequently, biophysical conditions that conspired to increase ecosystem photosynthesis to from one year to the next were associated with an increase in ecosystem respiration, and vice versa; on average, the year to year change in respiration was 40% as large as the year to year change in photosynthesis. The analysis also identified sets of ecosystems that are on the verge of switching from being carbon sinks to carbon sources. These include sites in the Arctic tundra, the evergreen forests in the Pacific northwest and some grasslands, where year to year changes in respiration are outpacing those in photosynthesis. While a select set of climatic and ecological factors (e.g. light, rainfall, temperature, phenology) played direct and indirect roles on this variability, their impact differed conditionally, as well as by climate and ecological spaces. For example, rainfall had both positive and negative effects. Deficient rainfall caused a physiological decline in photosynthesis in temperate and semi-arid regions. Too much rain, in the humid tropics, limited photosynthesis by limiting light. In peatlands and tundra, excess precipitation limited ecosystem respiration when it raised the water table to the surface. For deciduous forests, warmer temperatures lengthened the growing season, increasing photosynthesis, but this effect also increased soil respiration. Finally, statistical analysis was performed to evaluate the detection limit of trends; we computed the confidence intervals of trends in multi-year carbon fluxes that need to be resolved to conclude whether the differences are to be attributed to randomness or biophysical forcings. Future studies and reports on interannual variations need to consider the role of the duration of the time series on random errors when quantifying potential trends and extreme events. [ABSTRACT FROM AUTHOR]

Global-scale studies suggest that dryland ecosystems dominate an increasing trend in the magnitude and interannual variability of the land CO 2 sink. However, such model-based analyses are poorly constrained by measured CO 2 exchange in open shrublands, which is the most common global land cover type, covering ∼14% of Earth’s surface. Here we evaluate how the amount and seasonal timing of water availability regulate CO 2 exchange between shrublands and the atmosphere. We use eddy covariance data from six US sites across the three warm deserts of North America with observed ranges in annual precipitation of ∼100–400mm, annual temperatures of 13–18°C, and records of 2–8 years (33 site-years in total). The Chihuahuan, Sonoran and Mojave Deserts present gradients in both mean annual precipitation and its seasonal distribution between the wet-winter Mojave Desert and the wet-summer Chihuahuan Desert. We found that due to hydrologic losses during the wettest summers in the Sonoran and Chihuahuan Deserts, evapotranspiration (ET) was a better metric than precipitation of water available to drive dryland CO 2 exchange. In contrast with recent synthesis studies across diverse dryland biomes, we found that NEP could not be directly predicted from ET due to wintertime decoupling of the relationship between ecosystem respiration (R eco ) and gross ecosystem productivity (GEP). Ecosystem water use efficiency (WUE=GEP/ET) did not differ between winter and summer. Carbon use efficiency (CUE=NEP/GEP), however, was greater in winter because R eco returned a smaller fraction of carbon to the atmosphere (23% of GEP) than in summer (77%). Combining the water-carbon relations found here with historical precipitation since 1980, we estimate that lower average winter precipitation during the 21st century reduced the net carbon sink of the three deserts by an average of 6.8TgC yr 1 . Our results highlight that winter precipitation is critical to the annual carbon balance of these warm desert shrublands. [ABSTRACT FROM AUTHOR]

As leaves are the basic elements of plants that conduct photosynthesis and transpiration, vegetation leaf dynamics controls canopy physical and biogeochemical processes and hence largely influences the interactive exchanges of energy and materials between the land surface and the atmosphere. Given that the processes of plant leaf allocation is highly sensitive to climatological and environmental conditions, developing robust models that simulate leaf dynamics via climate variables contributes a key component to land surface models and coupled land-atmosphere models. Here we propose a new method to simulate seasonal leaf dynamics based on the idea of applying vegetation productivity as a synthesized metric to track and assess the climate suitability to plant growth over time. The method first solves two closed simultaneous equations of leaf phenology and canopy photosynthesis as modeled using the Growing Production-Day model iteratively for deriving the time series of steady-state leaf area index (LAI), and then applies the method of simple moving average to account for the time lagging of leaf allocation behind steady-state LAI. The seasonal LAI simulated using the developed method agree with field measurements from a selection of AmeriFlux sites as indicated by high coefficient of determination (R 2 = 0.801) and low root mean square error (RMSE = 0.924 m 2 /m 2 ) and with satellite-derived data (R 2 = 0.929 and RMSE = 0.650 m 2 /m 2 ) for the studied flux tower sites. Moreover, the proposed method is able to simulate seasonal LAI of deciduous broadleaf forests that match with satellite-derived LAI time series across the entire eastern United States. Comparative modeling studies suggest that the proposed method produces more accurate results than the method based on Growing Season Index in terms of correlation coefficients and error metrics. The developed method provides a complete solution to modeling seasonal leaf dynamics as well as canopy productivity solely using climate variables. [ABSTRACT FROM AUTHOR]

Quantification of the canopy photosynthesis of crops is essential for elucidation of the effects of environmental changes on CO 2 fluxes in agricultural ecosystems and crop productivity. This study was conducted to characterize the CO 2 fluxes of paddy rice ( Oryza sativa ), simulate CO 2 assimilation based on the development of a photosynthesis model, and project spatiotemporal variations in CO 2 assimilation using a crop model based on remotely sensed data in an effort to identify a link between photosynthetic productivity and accumulation of plant biomass. To perform the research practically under actual farming conditions, we investigated the effects of nitrogen (N) fertilization on canopy photosynthesis of rice grown under two levels of N application. Gross primary productivity (GPP) was calculated using net ecosystem exchange and ecosystem respiration measured in a closed-system canopy chamber. GPP was the highest in the maximum tillering stage and its minimum in the heading stage. The initial slope of the light response curve was similar during the four growth stages observed. The sensitivity of GPP to the amount of chlorophyll in the lower N treatment was higher than that in the optimum N treatment, whereas the GPP and yield in plants in the lower N treatment were lower. The photosynthesis model that was developed simulated CO 2 assimilation that had statistically acceptable agreement with the corresponding experimental measurements. In addition, projections of spatiotemporal variations in CO 2 assimilation were established using the GRAMI-rice model using remotely sensed data. These results indicated that CO 2 fluxes in paddy rice could be well quantified based on measurement and simulation projecting spatiotemporal CO 2 assimilation. As most of the information was derived from fields, it is not well organized to form one acceptable scientific streamline, efforts should be made to seek ecological implications through a fusion between at-ground measurements and remote sensing observations via model development. [ABSTRACT FROM AUTHOR]

The fraction of diffuse photosynthetic active radiation (PAR) reaching the land surface is one of the biophysical factors regulating carbon and water exchange between terrestrial ecosystems and the atmosphere. This is especially relevant for high latitude ecosystems, where cloudy days are prevalent. Without considering impacts of diffuse PAR, traditional ‘top-down’ models of ecosystem gross primary productivity (GPP) and evapotranspiration (ET), which use satellite remote sensing observations, are biased towards clear sky conditions. This study incorporated a cloudiness index (CI), an index for the fraction of diffuse PAR, into a joint ‘top-down’ model that uses the same set of biophysical constraints to simulate GPP and ET for a high latitude temperate deciduous forest. To quantify the diffuse PAR effects, CI along with other environmental variables derived from an eleven-year eddy covariance data set were used to statistically explore the independent and joint effects of diffuse PAR on GPP, ET, incident light use efficiency (LUE), evaporative fraction (EF) and ecosystem water use efficiency (WUE). The independent and joint effects of CI were compared from global sensitivity analysis of the ‘top-down’ models. Results indicate that for independent effects, CI increased GPP, LUE, ET, EF and WUE. Analysis of joint effects shows that CI mainly interacted with the radiation intercepted in the canopy (PAR, net radiation and leaf area index) to influence GPP, ET and WUE. Moreover, Ta and vapor pressure saturation deficit played a major role for the joint influence of CI on LUE and EF. In the growing season from May to October, variation in CI accounts for 11.9%, 3.0% and 7.8% of the total variation of GPP, ET and transpiration, respectively. As the influence of CI on GPP is larger than that on ET, this leads to an increase in WUE with CI. Joint GPP and ET model results showed that when including CI, the root mean square errors (RMSE) of daily GPP decreased from 1.64 to 1.45 g C m −2 d −1 (11.7% reduction) and ET from 15.79 to 14.50 W m −2 (8.2% reduction). Due to the interaction of diffuse PAR with plant canopies, the largest model improvements using CI for GPP and ET occurred during the growing season and for the transpiration component, as suggested by comparisons to sap flow measurements. Furthermore, our study suggests a potential biophysical mechanism, not considered in other studies: under high diffuse PAR conditions, due to the increased longwave emission from clouds, canopy temperature gets higher and enhances GPP and transpiration in this temperature-limited high latitude ecosystem. [ABSTRACT FROM AUTHOR]

Chlorophyll is the main light-harvesting pigment in leaves, facilitating photosynthesis and indicating the supply of nitrogen for photosynthetic enzymes. In this study, we explore the feasibility of integrating leaf chlorophyll content (Chl leaf ) into a Terrestrial Biosphere Model (TBM), as a proxy for the leaf maximum carboxylation rate at 25 °C ( V max 25 ), for the purpose of improving carbon and water flux estimation. Measurements of Chl leaf and V max 25 were made in a deciduous forest stand at the Borden Forest Research Station in southern Ontario, Canada, where carbon and water fluxes were measured by the eddy covariance method. The use of Chl leaf -based V max 25 in the TBM significantly reduces the bias of estimated gross primary productivity (GPP) and evapotranspiration (ET) and improves the temporal correlations between the simulated and the measured fluxes, relative to the commonly employed cases of using specified constant V max 25 , leaf area index (LAI)-based V max 25 or specific leaf area (SLA)-based V max 25 . The biggest improvements are found in spring and fall, when the mean absolute errors (MAEs) between modelled and measured GPP are reduced from between 2.2–3.2 to 1.8 g C m −2 d −1 in spring and from between 2.1–2.8 to 1.8 g C m −2 d −1 in fall. The MAEs in ET estimates are reduced from 0.7–0.8 mm d −1 to 0.6 mm d −1 in spring, but no significant improvement is noted in autumn. A two-leaf upscaling scheme is used to account for the uneven distribution of incoming solar radiation inside canopies and the associated physiological differences between leaves. We found that modelled V max 25 in sunlit leaves is 34% larger than in the shaded leaves of the same Chl leaf , which echoes previous physiological studies on light acclimation of plants. This study represents the first case of the incorporation of chlorophyll as a proxy for V max 25 in a two-leaf TBM at a forest stand and demonstrates the efficacy of using chlorophyll to constrain V max 25 and reduce the uncertainties in GPP and ET simulations. [ABSTRACT FROM AUTHOR]

Forests are structurally complex ecosystems with several canopy layers, each with distinct functional properties contributing differently to the net ecosystem CO 2 exchange. A large number of studies have addressed ecosystem-scale net CO 2 fluxes in forests, but only few studies have investigated the role of the forest understory. The goal of this study was to quantify the below-canopy contribution to ecosystem CO 2 fluxes of a mixed deciduous forest in Switzerland. Below- and above-canopy eddy-covariance (EC) measurements were made continuously over two years, complemented by within canopy wind and CO 2 concentration profile measurements. On an annual basis, the below-canopy fluxes indicated a net carbon source dominated by soil respiration, while the above-canopy fluxes were dominated by tree photosynthesis leading to a net carbon sink. Below-canopy fluxes showed a net carbon sink only in spring, with the early emergence of understory plants before overstory canopy leaf-out. Below-canopy respiration partitioned from the EC measurements agreed well with previous chamber-based soil respiration measurements. However, below- and above-canopy fluxes became decoupled under full canopy closure, thus leading to unaccounted below-canopy fluxes when measured only above the canopy. Wind and CO 2 concentration profile measurements supported this finding. Decoupling was independent of low turbulence conditions and decoupled periods could be identified using the relationship between the below- and above-canopy standard deviation in vertical wind velocity. A decoupling correction was applied to the above-canopy measurements during decoupled periods and corrected annual net ecosystem production (NEP) agreed well with independent estimates from biomass inventory combined with models. Overall, the below-canopy fluxes contributed 79% to annual ecosystem respiration, but only 9% to annual ecosystem photosynthesis. The decoupling correction reduced annual NEP for the site from about 760 to 330 g C m −2 yr −1 . Our results showed that below-canopy EC measurements are essential in this mixed deciduous forest, and likely in many other forests, to fully understand the carbon dynamics within structurally complex ecosystems. [ABSTRACT FROM AUTHOR]

There are great variations of inter-annual ecosystem photosynthetic productivity (GPP) in rice agricultural mosaic landscapes in Asian monsoon regions, consisting of relatively small land holdings. It is therefore of great importance to capture and interpret spatiotemporal aspects of per-field GPP. This goal, however, remains challenging partially due to absence of adequate methodology that applies ecophysiological data to broader spatial and temporal dimensions to explicitly quantify influences of environment change on per-field GPP. To accomplish the goal, field experiments were carried out at spatially adjacent flooding paddy (PD) and rainfed (RF) lowland rice ( Oryza sativa ) fields, taking year-round measurements in micrometeorological factors, leaf and canopy photosynthesis, and field reflectance with help from an unmanned aviation vehicle (UAV) system. A spatially hierarchical integration (PIXel based CANopy photosynthesis model, PIXCAN) that fuses measurements from leaf to canopy and field scales was then developed. Our results showed that the PIXCAN fusion could well capture and characterize spatial properties of per-field ecosystem GPP. Spatial variations (SV) of ecosystem carbon uptake capacity (GPP max ) at the PD and RF fields decreased over the growing season. However, occurrence of prolonged non-precipitation period due to climate anormaly in mid-August led to severe constraints of GPP max and counter-seasonally strengthened SV that would decrease in the RF rice field, primarily due to drought impacts on light-harvesting efficiency and less to stomatal conductance. Collectively, we highlighted ecological implications of the integration applied at field niche in spatially hierarchical observation of ecosystem regulating/production provisions from leaf to landscape dimensions. [ABSTRACT FROM AUTHOR]

Drought strongly influences terrestrial C cycling via its effects on plant H 2 O and CO 2 exchange. However, the treatment of photosynthetic physiology under drought by many ecosystem and earth system models remains poorly constrained by data. We measured the drought response of four tree species and evaluated alternative model formulations for drought effects on photosynthesis ( A ). We implemented a series of soil drying and rewetting events (i.e. multiple droughts) with four contrasting tree species in large pots (75 L) placed in the field under rainout shelters. We measured leaf-level gas exchange, predawn and midday leaf water potential (Ψ pd and Ψ md ), and leaf isotopic composition (δ 13 C) and calculated discrimination relative to the atmosphere (Δ). We then evaluated eight modeling frameworks that simulate the effects of drought in different ways. With moderate reductions in volumetric soil water content ( θ ), all species reduced stomatal conductance ( g s ), leading to an equivalent increase in water use efficiency across species inferred from both leaf gas exchange and Δ, despite a small reduction in photosynthetic capacity. With severe reductions in θ , all species strongly reduced g s along with a coincident reduction in photosynthetic capacity, illustrating the joint importance of stomatal and non-stomatal limitations of photosynthesis under strong drought conditions. Simple empirical models as well as complex mechanistic model formulations were equally successful at capturing the measured variation in A and g s , as long as the predictor variables were available from direct measurements ( θ , Ψ pd , and Ψ md ). However, models based on leaf water potential face an additional challenge, as we found that Ψ pd was substantially different from Ψ soil predicted by standard approaches based on θ . Modeling frameworks that combine gas exchange and hydraulic traits have the advantage of mechanistic realism, but sacrificed parsimony without an improvement in predictive power in this comparison. Model choice depends on the desired balance between simple empiricism and mechanistic realism. We suggest that empirical models implementing stomatal and non-stomatal limitations based on θ are highly predictive simple models. Mechanistic models that incorporate hydraulic traits have excellent potential, but several challenges currently limit their widespread implementation. [ABSTRACT FROM AUTHOR]