Response Of Gross Primary Production Research Articles

Vegetation canopy structure mediates the response of gross primary production to environmental drivers across multiple temporal scales

Gross primary production (GPP) is a critical component of the global carbon cycle and plays a significant role in the terrestrial carbon budget. The impact of environmental factors on GPP can occur through both direct (by influencing photosynthetic efficiency) and indirect (through the modulation of vegetation structure) pathways, but the extent to which these mechanisms contribute has been seldom quantified. In this study, we used structural equation modeling and observations from the FLUXNET network to investigate the direct and indirect effects of environmental factors on terrestrial ecosystem GPP at multiple temporal scales. We found that canopy structure, represented by leaf area index (LAI), is a crucial intermediate factor in the GPP response to environmental drivers. Environmental factors affect GPP indirectly by altering canopy structure, and the relative proportion of indirect effects decreased with increasing LAI. The study also identified different effects of environmental factors on GPP across time scales. At the half-hourly time scale, radiation was the primary driver of GPP. In contrast, the influences of temperature and vapor pressure deficit took on greater prominence at longer time scales. About half of the total effect of temperature on GPP was indirect through the regulation of canopy structure, and the indirect effect increased with increasing time scale (GPPNT-based models: 0.135 (half-hourly) vs. 0.171 (daily) vs. 0.189 (weekly) vs. 0.217 (monthly); GPPDT-based models: 0.139 vs. 0.170 vs. 0.187 vs. 0.215; all values were reported in gC m−2 d−1 °C−1, P < 0.001); while the indirect effect of radiation on GPP was comparatively lower, accounting for less than a quarter of the total effect. Furthermore, we observed a direct, negative-to-positive impact of precipitation on GPP across timescales. These findings provide crucial information on the interplay between environmental factors and LAI on GPP and enable a deeper understanding of the driving mechanisms of GPP.

The Difference between the Responses of Gross Primary Production and Sun-Induced Chlorophyll Fluorescence to the Environment Based on Tower-Based and TROPOMI SIF Data

The strong correlation between gross primary production (GPP) and sun-induced chlorophyll fluorescence (SIF) has been reported in many studies and is the basis of the SIF-based GPP estimation. However, GPP and SIF are not fully synchronous under various environmental conditions, which may destroy a stable GPP–SIF relationship. Therefore, exploring the difference between responses of GPP and SIF to the environment is essential to correctly understand the GPP–SIF relationship. As the common driver of GPP and SIF, the incident radiation could cause GPP and SIF to have similar responses to the environment, which may obscure the discrepancies in the responses of GPP and SIF to the other environmental variables, and further result in the ambiguity of the GPP–SIF relationship and uncertainties in the application of SIF. Therefore, we tried to exclude the dominant role of radiation in the responses of GPP and SIF to the environment based on the binning method, in which continuous tower-based SIF, satellite SIF, and eddy covariance GPP data from two growing seasons were used to investigate the differences in the responses of GPP and SIF to radiation, air temperature (Ta), and evaporation fraction (EF). We found that the following: (1) At both the site and satellite scales, there were divergences in the light response speeds between GPP and SIF which were affected by Ta and EF. (2) SIF and its light response curves were insensitive to EF and Ta compared to GPP, and the consistency in GPP and SIF light responses was gradually improved with the improvement of Ta and EF. (3) The dynamic slope values of the GPP–SIF relationship were mostly caused by the different sensitivities of GPP and SIF to EF and Ta. Our results highlighted that GPP and SIF were not highly consistent, having differences in environmental responses that further confused the GPP–SIF relationship, leading to complex SIF application.

Asymmetric response of vegetation GPP to impervious surface expansion: Case studies in the Yellow and Yangtze River Basins

Terrestrial gross primary production (GPP) changes due to impervious surfaces significantly impact ecosystem services in watersheds. Understanding the asymmetric response of vegetation GPP to impervious surface expansion is essential for regional development planning and ecosystem management. However, the asymmetric response of vegetation GPP to the impacts of impervious surface expansion is unknown in different watersheds. This paper selected the Yellow River and Yangtze River basins as case studies. We characterized the overall change in GPP based on changes in impervious surface ratio (ISR), determined impervious surface expansion's direct and indirect impacts on GPP in the two watersheds, and further analyzed the asymmetric response of the compensatory effects of indirect influences on the impervious surface expansion in different watersheds. The results showed that: (1) The vegetation GPP decreased with increasing ISR in the Yangtze River Basin, while that in the Yellow River Basin first increased and then reduced. (2) The direct impacts of increased ISR reduced vegetation GPP, while the indirect impacts both had a growth-compensating effect. Growth compensation stabilized at approximately 0.40 and 0.30 in the Yellow and Yangtze River Basins. (3) When the ISR was 0.34–0.56, the growth compensation could offset the reduction of GPP due to direct impact and ensure that the background vegetation GPP was not damaged in the Yellow River Basin. In contrast, the background vegetation GPP was inevitably impaired with increased ISR in the Yangtze River Basin. Therefore, this study suggests that the ISR should be ensured to be between 0.34 and 0.56 to maximize the impervious surface of the Yellow River Basin without compromising the background vegetation GPP. While pursuing impervious surface expansion in the Yangtze River Basin, other programs should be sought to compensate for the loss to GPP.

Higher global gross primary productivity under future climate with more advanced representations of photosynthesis.

Gross primary productivity (GPP) is the key determinant of land carbon uptake, but its representation in terrestrial biosphere models (TBMs) does not reflect our latest physiological understanding. We implemented three empirically well supported but often omitted mechanisms into the TBM CABLE-POP: photosynthetic temperature acclimation, explicit mesophyll conductance, and photosynthetic optimization through redistribution of leaf nitrogen. We used the RCP8.5 climate scenario to conduct factorial model simulations characterizing the individual and combined effects of the three mechanisms on projections of GPP. Simulated global GPP increased more strongly (up to 20% by 2070-2099) in more comprehensive representations of photosynthesis compared to the model lacking the three mechanisms. The experiments revealed non-additive interactions among the mechanisms as combined effects were stronger than the sum of the individual effects. The modeled responses are explained by changes in the photosynthetic sensitivity to temperature and CO2 caused by the added mechanisms. Our results suggest that current TBMs underestimate GPP responses to future CO2 and climate conditions.

Scaling up benthic primary productivity estimates in a large intertidal estuary using remote sensing

As two main primary producers in temperate intertidal regions, seagrass and microphytobenthos (MPB) support estuarine ecosystem functions in multiple ways including stabilizing food webs and regulating sediment resuspension among others. Monitoring estuary productivity at large scales can inform ecosystem scale responses to environmental stressors (climate change, pollution and habitat degradation). Here we use a case study to show how Sentinel-2 data can be used to estimate estuary-wide emerged and submerged gross primary productivity (GPP) on intertidal flats by coupling a new machine learning model to map seagrass and unvegetated habitats with literature-derived photosynthesis-irradiance (P – I) relationships. The model consisted of (1) supervised classification with random forest to delineate seagrass and unvegetated areas and (2) artificial neural network (ANN) regression to predict % seagrass coverage. Our seagrass delineation by supervised classification had an overall accuracy of 0.96, while the ANN regression on seagrass coverage provided high predictive accuracy (R2 = 0.71 and RMSE = 0.11). The estimated GPP showed seagrass contributed slightly more to intertidal benthic productivity than MPB in the case-study estuary over the 3-year study period. This model can be used to predict the response of seagrass and MPB GPP to sea level rise, which shows that the future state may be very sensitive to increased turbidity. For example, by the year 2100, the model shows a sharp decline in productivity with sea level rise, assuming current turbidity trends, (loss of up to 52–53 % for seagrass and 23–45 % for MPB, a function of whether shoreward migration of seagrass is incorporated). However, GPP under conditions of unchanging turbidity (and no seagrass migration), exhibits minimal negative impact of sea level rise (loss of 3 % for seagrass and increase of 29 % for MPB). Therefore, controlling water turbidity might be an efficient solution to maintaining the current GPP as sea level rises.

Asymmetric response of gross primary productivity to precipitation changes over China’s karst areas

China’s karst areas play an important role in regulating the global carbon dynamic and mitigating atmospheric CO2 concentration. Yet, extreme drought events have occurred frequently in recent years over China’s karst areas, which have a negative effect on the gross primary productivity (GPP) in the region. It is unclear whether gross primary productivity gains in the wet years can compensate for its losses in the dry years over the karst areas. In this study, we selected the asymmetry indices to assess the potential asymmetric response of gross primary productivity to the change in precipitation over China’s karst areas during the 2003 to 2018 period, using the gross primary productivity and precipitation dataset. Our results show that the gross primary productivity exhibits a positive asymmetry in response to precipitation changes, namely, the gains caused by increased precipitation in the wet years overcompensate the losses caused by decreased precipitation in the dry years. In addition, the gross primary productivity asymmetry shows an increasing trend over the study period despite extreme drought events occurring frequently, which is due to the response of gross primary productivity to drought has significantly decreased over the study period. For each biome, grasslands show the highest positive gross primary productivity asymmetry, indicating that the grassland biomes have a stronger capacity to utilize the increased precipitation during the wet years to increase gross primary productivity compared to other biomes. Furthermore, the gross primary productivity asymmetry over China’s karst areas can be effected by the precipitation asymmetry as well as mean annual precipitation. Our results will contribute to our knowledge of the response of gross primary productivity to precipitation changes in the karst areas of China.

Diverse responses of gross primary production and leaf area index to drought on the Mongolian Plateau

Drought is a crucial factor regulating vegetation growth on the Mongolian Plateau (MP). Previous studies of drought effects on the MP have mainly concentrated on drought characterization, while the response of vegetation to drought remains unclear. To close this knowledge gap, we examined the response of MP vegetation to drought in terms of gross primary production (GPP) and leaf area index (LAI) from 1982 to 2018. Our findings show that intra-seasonally the frequency of drought occurrence in autumn had a greater impact on GPP (relative importance over 70 %), while the intensity of drought was more influential for LAI (relative importance approximately 60 %). Inter-seasonally, summer droughts had the most pronounced effect on vegetation (with median standardized anomalies of −0.72 for GPP and −0.4 for LAI, respectively). Additionally, we found that meteorological drought was more consistent with atmospheric aridity (high vapor pressure deficit) than soil drought (low soil moisture). This study advances knowledge of vegetation's susceptibility to climate extremes and improves the precision of predicting ecosystem response to climate change.

Forest productivity recovery or collapse? Model-data integration insights on drought-induced tipping points.

More frequent and severe droughts are driving increased forest mortality around the globe. We urgently need to describe and predict how drought affects forest carbon cycling and identify thresholds of environmental stress that trigger ecosystem collapse. Quantifying the effects of drought at an ecosystem level is complex because dynamic climate-plant relationships can cause rapid and/or prolonged shifts in carbon balance. We employ the CARbon DAta MOdel fraMework (CARDAMOM) to investigate legacy effects of drought on forest carbon pools and fluxes. Our Bayesian model-data fusion approach uses tower observed meteorological forcing and carbon fluxes to determine the response and sensitivity of aboveground and belowground ecological processes associated with the 2012-2015 California drought. Our study area is a mid-montane mixed conifer forest in the Southern Sierras. CARDAMOM constrained with gross primary productivity (GPP) estimates covering 2011-2017 show a ~75% reduction in GPP, compared to negligible GPP change when constrained with 2011 only. Precipitation across 2012-2015 was 45% (474 mm) lower than the historical average and drove a cascading depletion in soil moisture and carbon pools (foliar, labile, roots, and litter). Adding 157 mm during an especially stressful year (2014, annual rainfall = 293 mm) led to a smaller depletion of water and carbon pools, steering the ecosystem away from a state of GPP tipping-point collapse to recovery. We present novel process-driven insights that demonstrate the sensitivity of GPP collapse to ecosystem foliar carbon and soil moisture states-showing that the full extent of GPP response takes several years to arise. Thus, long-term changes in soil moisture and carbon pools can provide a mechanistic link between drought and forest mortality. Our study provides an example for how key precipitation threshold ranges can influence forest productivity, making them useful for monitoring and predicting forest mortality events.

Higher sensitivity of gross primary productivity than ecosystem respiration to experimental drought and warming across six European shrubland ecosystems

Shrubland ecosystems across Europe face a range of threats including the potential impacts of climate change. Within the INCREASE project, six shrubland ecosystems along a European climatic gradient were exposed to ecosystem-level year-round experimental nighttime warming and long-term, repeated growing season droughts. We quantified the ecosystem level CO2 fluxes, i.e. gross primary productivity (GPP), ecosystem respiration (Reco) and net ecosystem exchange (NEE), in control and treatment plots and compared the treatment effects along the Gaussen aridity index. In general, GPP exhibited higher sensitivity to drought and warming than Reco and was found to be the dominant contributor to changes in overall NEE. Across the climate gradient, northern sites were more likely to have neutral to positive responses of NEE, i.e. increased CO2 uptake, to drought and warming partly due to seasonal rewetting. While an earlier investigation across the same sites showed a good cross-site relationship between soil respiration responses to climate over the Gaussen aridity index, the responses of GPP, Reco and NEE showed a more complex response pattern suggesting that site-specific ecosystem traits, such as different growing season periods and plant species composition, affected the overall response pattern of the ecosystem-level CO2 fluxes. We found that the observed response patterns of GPP and Reco rates at the six sites could be explained well by the hypothesized position of each site on site-specific soil moisture response curves of GPP/Reco fluxes. Such relatively simple, site-specific analyses could help improve our ability to explain observed CO2 flux patterns in larger meta-analyses as well as in larger-scale model upscaling exercises and thereby help improve our ability to project changes in ecosystem CO2 fluxes in response to future climate change.

Elucidating climatic drivers of photosynthesis by tropical forests.

Tropical forests play a pivotal role in regulating the global carbon cycle. However, the response of these forests to changes in absorbed solar energy and water supply under the changing climate is highly uncertain. Three-year (2018-2021) spaceborne high-resolution measurements of solar-induced chlorophyll fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI) provide a new opportunity to study the response of gross primary production (GPP) and more broadly tropical forest carbon dynamics to differences in climate. SIF has been shown to be a good proxy for GPP on monthly and regional scales. Combining tropical climate reanalysis records and other contemporary satellite products, we find that on the seasonal timescale, the dependence of GPP on climate variables is highly heterogeneous. Following the principal component analyses and correlation comparisons, two regimes are identified: water limited and energy limited. GPP variations over tropical Africa are more correlated with water-related factors such as vapor pressure deficit (VPD) and soil moisture, while in tropical Southeast Asia, GPP is more correlated with energy-related factors such as photosynthetically active radiation (PAR) and surface temperature. Amazonia is itself heterogeneous: with an energy-limited regime in the north and water-limited regime in the south. The correlations of GPP with climate variables are supported by other observation-based products, such as Orbiting Carbon Observatory-2 (OCO2) SIF and FluxSat GPP. In each tropical continent, the coupling between SIF and VPD increases with the mean VPD. Even on the interannual timescale, the correlation of GPP with VPD is still discernable, but the sensitivity is smaller than the intra-annual correlation. By and large, the dynamic global vegetation models in the TRENDY v8 project do not capture the high GPP seasonal sensitivity to VPD in dry tropics. The complex interactions between carbon and water cycles in the tropics illustrated in this study and the poor representation of this coupling in the current suite of vegetation models suggest that projections of future changes in carbon dynamics based on these models may not be robust.

Divergent effects of intensified precipitation on primary production in global drylands

Amplification of hydrological cycle under warming climate is anticipated to result in intensified precipitation characterized by fewer, more intense events and correspondingly longer dry intervals between events, even without major changes in annual total precipitation. Vegetation gross primary production (GPP) in drylands is highly responsive to intensified precipitation, however, how intensified precipitation influences GPP in global drylands is not well understood. Based on multiple satellite datasets from 2001 to 2020 and in-situ measurements, we investigated the effects of intensified precipitation on global drylands GPP under diverse annual total precipitation along the bioclimate gradient. Dry, normal, and wet years were identified as years with annual precipitation anomalies below, within, and above the range of one standard deviation. Intensified precipitation led to increases or decreases of GPP during dry or normal years, respectively. However, such effects were largely weakened during wet years. The responses of GPP to intensified precipitation were mirrored by soil water availability, as intensified precipitation enhanced root zone soil moisture, and thus vegetation transpiration and precipitation use efficiency during dry years. During wet years, root zone soil moisture showed less response to changed precipitation intensity. Land cover types and soil texture regulated the magnitude of the effects along the bioclimate gradient. Under intensified precipitation, shrubland and grassland distributed in drier region with coarse soil texture showed greater increases of GPP during dry years. As global precipitation will likely further intensify, the impacts of intensified precipitation on dryland carbon uptake capacity will be highly diverse along the bioclimate gradients.

Identifying the Responses of Vegetation Gross Primary Productivity and Water Use Efficiency to Climate Change under Different Aridity Gradients across China

Despite the fact that gross primary productivity (GPP) and water use efficiency (WUE) have been widely used as indicators to evaluate the water-carbon cycle, uncertainties exist in the patterns of GPP and WUE responses to climate variability along different aridity gradients. In this study, the aridity index was used to divide China into four arid-humid zones. The spatiotemporal variability of multiple vegetation types GPP and WUE in response to climate change under different arid-humid zones were investigated based on remote sensing data. The results indicated that the increasing trend of WUE in the four arid-humid zones of China was less pronounced than GPP from 2001 to 2021. The GPP value decreased gradually from the humid to the arid zone, and the WUE value in the arid zone was slightly higher than in the semi-arid zone. The GPP of all vegetation types in China showed a tendency to increase, while shrubland and wetland WUE tended to decrease. The major vegetation types (e.g., forest, cropland and grassland) in each aridity gradient contributed to the changes in local GPP and WUE. However, in individual arid-humid zones, wetland and shrubland also exhibited high GPP and WUE values that were not inferior to forest and cropland. Temperature and precipitation were the main climatic factors responsible for the increase in vegetation GPP in different aridity gradients, with a higher positive correlation for temperature than precipitation. WUE showed a distinct positive and negative correlation with the thermal factors (temperature and net radiation) and the moisture factors (precipitation and relative humidity); this pattern was more pronounced in the humid and semi-humid zones. Net radiation and precipitation may be the main climatic factors causing a slight upward trend in WUE across the arid-humid zones, while the decrease in shrubland and wetland WUE may be related to relative humidity and precipitation.

Environmental Drivers of Gross Primary Productivity and Light Use Efficiency of a Temperate Spruce Forest

AbstractVarious environmental variables drive gross primary productivity (GPP) and light use efficiency (LUE) of forest ecosystems. However, due to their intertwined nature and the complexity of measuring absorbed photosynthetically active radiation (APAR) of forest canopies, the assessment of LUE and the importance of its environmental drivers are difficult. Here, we present a unique combination of measurements during the 2021 growing season including eddy covariance derived GPP, sap flow, Sentinel‐2 derived canopy chlorophyll content and in situ measured APAR. The importance of environmental variables for GPP models is quantified with state‐of‐the‐art machine learning techniques. A special focus is put on photosynthesis‐limiting conditions, which are identified by a comparison of GPP and sap flow hysteretic responses to Vapor pressure deficit (VPD) and APAR. Results demonstrate that (a) LUE of the canopy's green part was on average 4.0% ± 2.3%, (b) canopy chlorophyll content as a seasonal variable for photosynthetic capacity was important for GPP predictions, and (c) on days with high VPD, tree‐scale sap flow and ecosystem‐scale GPP both shift to a clockwise hysteretic response to APAR. We demonstrate that the onset of such a clockwise hysteretic pattern of sap flow to APAR is a good indicator of stomatal closure related to water‐limiting conditions at the ecosystem‐scale.

Soil Moisture Assimilation Improves Terrestrial Biosphere Model GPP Responses to Sub-Annual Drought at Continental Scale

Due to the substantial gross exchange fluxes with the atmosphere, the terrestrial carbon cycle plays a significant role in the global carbon budget. Drought commonly affects terrestrial carbon absorption negatively. Terrestrial biosphere models exhibit significant uncertainties in capturing the carbon flux response to drought, which have an impact on estimates of the global carbon budget. Through plant physiological processes, soil moisture tightly regulates the carbon cycle in the environment. Therefore, accurate observations of soil moisture may enhance the modeling of carbon fluxes in a model–data fusion framework. We employ the Carbon Cycle Data Assimilation System (CCDAS) to assimilate 36-year satellite-derived surface soil moisture observations in combination with flask samples of atmospheric CO2 concentrations. We find that, compared to the default model, the performance of optimized net ecosystem productivity (NEP) and gross primary productivity (GPP) has increased with the RMSEs reduced by 1.62 gC/m2/month and 10.84 gC/m2/month, which indicates the added value of the ESA-CCI soil moisture observations as a constraint on the terrestrial carbon cycle. Additionally, the combination of soil moisture and CO2 concentration in this study improves the representation of inter-annual variability of terrestrial carbon fluxes as well as the atmospheric CO2 growth rate. We thereby investigate the ability of the optimized GPP in responding to drought by comparing continentally aggregated GPP with the drought index. The assimilation of surface soil moisture has been shown to efficiently capture the influences of the sub-annual (≤9 months drought durations) and large-scale (e.g., regional to continental scales) droughts on GPP. This study highlights the significant potential of satellite soil moisture for constraining inter-annual models of the terrestrial biosphere’s carbon cycle and for illustrating how GPP responds to drought at a continental scale.

Carbon uptake of the sugarcane agroecosystem is profoundly impacted by climate variations due to seasonality and topography

Sugarcane is an economically important crop whose growth and carbon uptake play vital roles in the carbon cycle, food security, and global trade development. However, the response of the carbon uptake of sugarcane to climate variations and the influencing factors are still unclear. In this study, seven sugarcane plantation distribution maps during 2000 and 2018 in Guangxi, China, were generated using time series Landsat and Sentinel-2 imagery, and these maps were used to produce stable sugarcane sites by identifying pixels without land cover transformation. Time series gross primary production (GPP) and climate datasets were used to analyze the response of annual GPP to temperature, precipitation, and their interacting effects under different landforms (rugged ground and flat ground) and growing periods. The results showed a significantly positive correlation between annual GPP change and temperature variations. Extreme precipitation, including extreme drought and extreme wetness, caused the annual GPP to decrease sharply, except for extreme wetness in the early growing period. The decrease in annual GPP mainly appeared when extreme drought and hot conditions or extreme wet and cold conditions coexisted, ranging from −20.37% to −0.23%, while the increase in annual GPP especially appeared when non-extreme precipitation and high temperature co-occurred, ranging from 0.02% to 8.44%. In addition, the responses of sugarcane annual GPP change to extreme temperature and precipitation were significantly different between rugged and flat ground. Overall, this study indicated that spatiotemporal heterogeneities existed in the response of sugarcane carbon uptake to climate variations. In the future, effective measures should be adopted in sugarcane management and cultivation to reduce the negative effects of climate change on crop production. • Sugarcane’s carbon uptake response discrepantly to heat and water stresses. • Impacts of climate variations on sugarcane GPP varied with growing stages. • Rugged grounds change the response of sugarcane GPP to extreme climates.

Effects of Shifting Spring Phenology on Growing Season Carbon Uptake in High Latitudes

AbstractPhenological shifts not only alter the growing season length, but also modify land‐atmosphere exchanges of water and energy, which in turn affects ecosystem carbon uptake. However, how changes in the start of the growing season (SOS) affect carbon uptake throughout growing season has not been fully explored for high‐latitude ecosystems. Here, we investigated the impacts of SOS shifts on carbon uptake and the mechanisms over 2000–2020 in the northern high latitudes (&gt;50°N) using multiple satellite and climate data sets. We found a contrasting response of gross primary productivity (GPP) in the early (April–June) and late (July–September) growing season to SOS shifts. Advanced SOS resulted in increased early‐season GPP, whereas slightly decreased late‐season GPP. The earlier SOS resulted from a warmer early season, which induced a decline of snow to precipitation ratio, therefore drier soil and atmosphere. In the early season, when water requirement of vegetation was low, the warm and dry conditions ensured favorable solar radiation and improved vegetation water use efficiency (WUE), thus enhancing photosynthesis. The dry soil and atmosphere conditions extended to the late season due to less snow and excessive water utilization by vegetation in the early season, which therefore slightly suppressed photosynthesis by weakening WUE. Conversely, the delayed SOS resulted in reduced early‐season GPP and slightly enhanced late‐season GPP due to the opposite thermal and moisture conditions to that of advanced SOS. The SOS is likely to be further advanced as warming continues in the high latitudes, intensifying seasonal contrasts in vegetation photosynthesis capacity.

How Do Sky Conditions Affect the Relationships Between Ground‐Based Solar‐Induced Chlorophyll Fluorescence and Gross Primary Productivity Across Different Plant Types?

AbstractSolar‐induced chlorophyll fluorescence (SIF) has been used as a proxy for gross primary productivity (GPP) estimations. However, knowledge on how links between SIF and GPP across different plant types vary in response to sky conditions remain unclear. Here, we investigated the effects of sky conditions on the GPP‐SIF relationship based on continuous measurements of SIF and flux across four different plant types. Our analysis shows that the GPP‐SIF links are affected by sky conditions and these linking patterns respond differently across plant types. We propose that the inconsistent responses of SIF and GPP to sky conditions are primarily driven by variations in light use efficiency (LUE = GPP/absorbed photosynthetic active radiation (APAR)). Furthermore, we explore a quantitative variation in LUE and SIFyield (SIF/APAR) separately via a decoupling of clearness index (CI) and photosynthetic active radiation under different sky conditions. LUE is more sensitive to sky conditions for the C3 plants (Forest, Wheat and Rice) than the C4 plant (Maize), and SIFyield shows more sensitivity to sky conditions for the forest than croplands. Due to the tight link between CI and other environmental factors, the incorporation of CI into the SIF‐based GPP model improves GPP estimates for all C3 plants at both instantaneous and daily scales. Our study implies that a consideration of sky conditions into the SIF‐based GPP model can significantly advance the GPP modeling under all sky conditions.

Pan-Arctic soil moisture control on tundra carbon sequestration and plant productivity.

Long-term atmospheric CO2 concentration records have suggested a reduction in the positive effect of warming on high-latitude carbon uptake since the 1990s. A variety of mechanisms have been proposed to explain the reduced net carbon sink of northern ecosystems with increased air temperature, including water stress on vegetation and increased respiration over recent decades. However, the lack of consistent long-term carbon flux and in situ soil moisture data has severely limited our ability to identify the mechanisms responsible for the recent reduced carbon sink strength. In this study, we used a record of nearly 100 site-years of eddy covariance data from 11 continuous permafrost tundra sites distributed across the circumpolar Arctic to test the temperature (expressed as growing degree days, GDD) responses of gross primary production (GPP), net ecosystem exchange (NEE), and ecosystem respiration (ER) at different periods of the summer (early, peak, and late summer) including dominant tundra vegetation classes (graminoids and mosses, and shrubs). We further tested GPP, NEE, and ER relationships with soil moisture and vapor pressure deficit to identify potential moisture limitations on plant productivity and net carbon exchange. Our results show a decrease in GPP with rising GDD during the peak summer (July) for both vegetation classes, and a significant relationship between the peak summer GPP and soil moisture after statistically controlling for GDD in a partial correlation analysis. These results suggest that tundra ecosystems might not benefit from increased temperature as much as suggested by several terrestrial biosphere models, if decreased soil moisture limits the peak summer plant productivity, reducing the ability of these ecosystems to sequester carbon during the summer.

Sun-induced fluorescence as a proxy for primary productivity across vegetation types and climates

Abstract. Sun-induced chlorophyll a fluorescence (SIF) retrieved from satellites has shown potential as a remote sensing proxy for gross primary productivity (GPP). However, to fully exploit the potential of this signal, the robustness and stability of the SIF–GPP relationship across vegetation types and climates must be assessed. For this purpose, current studies have been limited by the availability of SIF datasets with sufficient spatial resolution to disentangle the signal between different vegetation cover types. To overcome this limitation, this analysis uses GOME-2 (Global Ozone Monitoring Experiment-2) SIF retrievals, downscaled to a resolution of 0.05∘ (∼5 km) to explore the relationship between SIF and FLUXCOM GPP (GPPFX), a data-driven dataset of primary productivity obtained by upscaling flux-tower measurements. The high resolution of the downscaled SIF (SIFDS) dataset allows the relationships to be broken down by vegetation cover for separate climate zones, thus enabling a confrontation between GPP and SIF at fine granularity. This analysis first investigates the spatial and temporal relationships between FLUXCOM GPP and downscaled SIF at a global scale. A reasonably strong linear relationship is generally observed between SIFDS and GPPFX in all vegetation categories, and an analysis of covariance (ANCOVA) shows that the spatial response is similar between certain plant traits, with some distinction between herbaceous and woody vegetation and notable exceptions, such as equatorial broadleaf forests. Geographical regions of non-linearity suggest where SIFDS could potentially provide information about ecosystem dynamics that are not represented in the FLUXCOM GPP dataset. With the demonstration of downscaled SIF as a proxy for GPP, the response of SIFDS to short-term fluctuations in several meteorological variables is analysed and the most significant short-term environmental driving and limiting meteorological variables determined. Vegetation groupings of similar SIF–meteorological response reinforce the vegetation categorisations suggested by the ANCOVA. This comparative exploration of two of the most recent products in carbon productivity estimation shows the value in downscaling SIF data, provides an independent probe of the FLUXCOM GPP model, enhances our understanding of the global SIF–GPP spatio-temporal relationship with a particular focus on the role of vegetation cover, and explores the similarity of the SIF and GPP responses to meteorological fluctuations. Additional analyses with alternative SIF and GPP datasets support these conclusions.

Effect of diffuse fraction on gross primary productivity and light use efficiency in a warm-temperate mixed plantation.

Diffuse radiation (I f) is one of important variables determining photosynthetic rate and carbon uptake of forest ecosystems. However, the responses of gross primary productivity (GPP) and light use efficiency (LUE) to diffuse fraction (DF) are still poorly understood. We used a 6-year dataset of carbon flux at a warm-temperate mixed plantation site in North China to explore the impacts of DF on GPP and LUE. During 2011-2017, ecosystem apparent quantum yield (α) and photosynthesis at photosynthetically active radiation (PAR) of 1800 µmol m-2 s-1 (P 1800) on cloudy days were 63% and 17% higher than on clear days, respectively. Under lower vapor pressure deficit (VPD) and air temperature (T a) conditions, canopy photosynthesis was significantly higher on cloudy skies than on clear skies. On half-hourly scale, increased DF enhanced α and P 1800. Daily GPP peaked at a median DF (=0.5), while daily LUE significantly increased with DF (p<0.01). Both GPP and LUE were mainly controlled directly by DF and PAR. DF had an indirect effect on LUE and GPP mainly through PAR. At high DF levels (>0.5), the increase in LUE did not make GPP enhancement. The direct effect of DF on GPP and LUE under lower T a and VPD was more sensitive than under higher T a and VPD. When DF was incorporated into the Michaelis-Menten model, it performed well in the GPP estimation, and the determination coefficient increased by 32.61% and the root mean square error decreased by 25.74%. These findings highlight the importance of incorporating DF into carbon sequestration estimation in North China.