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The inhibition of foliar respiration by light is a crucial yet often overlooked component in estimating ecosystem respiration. However, current estimations of the light inhibition of ecosystem respiration are biased by ignoring the effects of moisture factors. We developed a novel physics‐constrained machine learning method to quantify the extent of light inhibition (Reli) driven by multiple factors in global ecosystems. Our findings revealed significant seasonal variations in light inhibition rate aligned with vegetation growth. Temperature predominantly influenced variations in Reli, and the temperature‐Reli relationship was regulated by vapor pressure deficit rather than soil water content. A reassessment of global ecosystem respiration revealed that current Earth system models (ESMs) overestimate ecosystem respiration in mid‐to‐high latitude dryland regions, with a global average light inhibition strength of 0.51 (±0.16). Knowledge from this study provides an accurate understanding of light inhibition driven by temperature and moisture coupling in simulating carbon cycle. Plain Language Summary: Ecosystem respiration is mainly composed of vegetation respiration and soil respiration. However, estimates of ecosystem respiration are biased by ignoring the inhibition of leaf respiration in the light. We developed a novel physics‐constrained machine learning method to estimate the ecosystem respiration incorporating the ecological process of light inhibition. We found a clear relationship between light inhibition rate and vegetation growth on a seasonal scale. The light inhibition of ecosystem respiration was driven by both temperature and moisture factors. The global average light inhibition strength was 0.51 (±0.16). Key Points: Light inhibition of ecosystem respiration showed seasonal variations that match vegetation growthRelationship between temperature and light inhibition was regulated by vapor pressure deficitCurrent Earth system models overestimated ecosystem respiration in mid‐to‐high latitude dryland regions [ABSTRACT FROM AUTHOR]

Polar‐orbiting satellites have significantly improved our understanding of the terrestrial carbon cycle, yet they are not designed to observe sub‐daily dynamics that can provide unique insight into carbon cycle processes. Geostationary satellites offer remote sensing capabilities at temporal resolutions of 5‐min, or even less. This study explores the use of geostationary satellite data acquired by the Geostationary Operational Environmental Satellite—R Series (GOES‐R) to estimate terrestrial gross primary productivity (GPP) and ecosystem respiration (RECO) using machine learning. We collected and processed data from 126 AmeriFlux eddy covariance towers in the Contiguous United States synchronized with imagery from the GOES‐R Advanced Baseline Imager (ABI) from 2017 to 2022 to develop ML models and assess their performance. Tree‐based ensemble regressions showed promising performance for predicting GPP (R2 of 0.70 ± 0.11 and RMSE of 4.04 ± 1.65 μmol m−2 s−1) and RECO (R2 of 0.77 ± 0.10 and RMSE of 0.90 ± 0.49 μmol m−2 s−1) on a half‐hourly time step using GOES‐R surface products and top‐of‐atmosphere observations. Our findings align with global efforts to utilize geostationary satellites to improve carbon flux estimation and provide insight into how to estimate terrestrial carbon dioxide fluxes in near‐real time. Plain Language Summary: Fighting climate change requires an understanding of how ecosystems absorb and release carbon dioxide. While most Earth‐orbiting satellites provide limited snapshots, this study explores how more frequent imagery—every 5 min—from geostationary satellites, also known as weather satellites, can be used to estimate ecosystem carbon dioxide flux. By combining this data with machine learning techniques, we successfully estimated carbon uptake and release at over 100 US sites at half‐hourly intervals. This paves the way for near‐real‐time global monitoring of carbon exchange, offering a powerful tool for scientists and policymakers tackling climate change. Key Points: Advanced Baseline Imager (ABI) observations can estimate sub‐daily ecosystem carbon uptake and respiration at 126 AmeriFlux sitesIntegration of top‐of‐atmosphere products enhances the accuracy of monitoring land surface functionsABI observations can fill eddy covariance data gaps: up to 1 week (high accuracy), 6 months (low accuracy) [ABSTRACT FROM AUTHOR]

We measured dark CO2 fluxes and CH4 emissions from two naturally vegetated ecosystems of the Mezquital Valley irrigated with wastewater from Mexico City. The ecosystems were characterized by high groundwater levels; the vegetation was represented mainly by saltgrass in the first plot and chairmaker's bulrush in the second. A dark chamber technique was used for the study from August 2008 to June 2009. For the two studied plots, mean values (mean ± SE) for dark ecosystem CO2 fluxes (Rtot), soil CO2 emission (Rsoil), and heterotrophic respiration (Rhet) were 26 ± 5, 14 ± 3 and 12 ± 3 mg C m–2 h–1, respectively, The annual cumulative fluxes Rtot, Rsoil and Rhet equal to 234, 127 and 103 g C m–2 y–1, respectively. The contribution of Rsoil to Rtot, and Rhet to Rsoil varied significantly over the study period, with no clear relationship to seasonal dynamics. The observed low CO2 fluxes may be due to soil salinization resulting from wastewater flooding. The fluxes of CH4 were observed in the flooded plot, with peaks up to 370 µg C m–2 h–1. The fluxes of CH4 were significantly higher when plants were present in the measurement chamber than when there were no plants, confirming the important role of plant cover in CH4 transport. Unlike CH4 fluxes, CO2 fluxes show seasonal dynamics, mainly due to their strong dependence on temperature. The observed results may be useful for properly estimating the global C budget and the contribution of saline soils to C fluxes. [ABSTRACT FROM AUTHOR]

Warming-induced carbon loss via ecosystem respiration (Re) is probably intensifying in the alpine grassland ecosystem of the Tibetan Plateau owing to more accelerated warming and the higher temperature sensitivity of Re (Q10). However-little is known about the patterns and controlling factors of Q10 on the plateau, impeding the comprehension of the intensity of terrestrial carbon–climate feedbacks for these sensitive and vulnerable ecosystems. Here, we synthesized and analyzed multiyear observations from 14 sites to systematically compare the spatiotemporal variations of Q10 values in diverse climate zones and ecosystems, and further explore the relationships between Q10 and environmental factors. Moreover, structural equation modeling was utilized to identify the direct and indirect factors predicting Q10 values during the annual, growing, and non-growing seasons. The results indicated that the estimated Q10 values were strongly dependent on temperature, generally, with the average Q10 during different time periods increasing with air temperature and soil temperature at different measurement depths (5 cm, 10 cm, 20 cm). The Q10 values differentiated among ecosystems and climatic zones, with warming-induced Q10 declines being stronger in colder regions than elsewhere based on spatial patterns. NDVI was the most cardinal factor in predicting annual Q10 values, significantly and positively correlated with Q10. Soil temperature (Ts) was identified as the other powerful predictor for Q10, and the negative Q10–Ts relationship demonstrates a larger terrestrial carbon loss potentiality in colder than in warmer regions in response to global warming. Note that the interpretations of the effect of soil moisture on Q10 were complicated, reflected in a significant positive relationship between Q10 and soil moisture during the growing season and a strong quadratic correlation between the two during the annual and non-growing season. These findings are conducive to improving our understanding of alpine grassland ecosystem carbon–climate feedbacks under warming climates. [ABSTRACT FROM AUTHOR]

The growth of Sphagnum is influenced by the lunar cycle, which suggests a corresponding carbon (C) accumulation rhythm in peatlands. However, this rhythm can only occur if C accumulation from Sphagnum growth is not offset by its total losses through respiration and other processes. To address the uncertainty, through correlation-regression analysis we examine the influence of the lunar cycle on recent measurements of ecosystem (ER) and heterotrophic (Rh) respiration conducted by Järveoja and colleagues on the oligotrophic peatland of Degerö Stormyr. We found that ER and Rh accelerated near the full moon and slowed down near the new moon. The response of the hourly ER to the lunar cycle is significant from 22:00 to 8:00 and is not significant beyond this range. This response was concentrated in the initial and finished phases of the season, but during the middle of the season it disappeared. This behavior could potentially be caused by the high sensitivity of the Sphagnum cover to moonlight, as well as the sensitivity to the lunar cycle of only the nocturnal component ER. During most of the day, the lunar cycle had a significant effect on hourly Rh, with the highest impact observed between 5:00 and 10:00 and at 20:00. The greatest impact occurs during those hours when ER declines, and possibly Sphagnum photosynthetic productivity peaks. The findings suggest a circalunar rhythm of C accumulation in peatlands due to the opposite trends between C accumulation during Sphagnum growth and C losses with respiration during the lunar cycle. [ABSTRACT FROM AUTHOR]

Empirical models for estimating ecosystem respiration (ER) are widely used in CO2 flux partitioning algorithms that partition net ecosystem CO2 exchange (NEE) into gross primary productivity (GPP) and ER due to advantages of simple structures. However, empirical ER models remain limited due to single-source conceptualization that doesn’t discriminate different responses of aboveground respiration (AGR) and belowground respiration (BGR) to environmental factors (i.e., temperature and/or soil moisture). In this study, a dual-source module with only one parameter α was proposed and incorporated into six widely used ER models to enhance model capabilities. Long-term flux measurements of six typical terrestrial ecosystems and soil chamber respiration data at two sites were collected to evaluate models. Results showed that integration of the dual-source module can significantly improve the performance of empirical models in selected ecosystems with mean R2 improvement of 0.10 ± 0.16. The site years with relative increased R2 (ΔR2) larger than 10 % range from 6 % to 79 % amongst different models. Further validation between soil respiration and estimated BGR showed good correlations (r > 0.7) and demonstrated that proposed method can provide robust estimate of above/belowground respiration. Calibrated α varies amongst ecosystem types. Further analysis indicates variation of α is largely influenced by ratio of above/belowground biomass and annual average moisture conditions. Our findings highlight the critical need for partitioning ER models into dual-source for developing CO2 flux partitioning algorithms and support the approach as an effective means to enhance the understanding of global carbon cycles with changing climate.

Generally, with increasing elevation, there is a corresponding decrease in annual mean air and soil temperatures, resulting in an overall decrease in ecosystem carbon dioxide (CO2) exchange. However, there is a lack of knowledge on the variations in CO2 exchange along elevation gradients in tundra ecosystems. Aiming to quantify CO2 exchange along elevation gradients in tundra ecosystems, we measured ecosystem CO2 exchange in the peak growing season along an elevation gradient (9–387 m above sea level, m.a.s.l) in an arctic heath tundra, West Greenland. We also performed an ex-situ incubation experiment based on soil samples collected along the elevation gradient, to assess the sensitivity of soil respiration to changes in temperature and soil moisture. There was no apparent temperature gradient along the elevation gradient, with the lowest air and soil temperatures at the second lowest elevation site (83 m). The lowest elevation site exhibited the highest net ecosystem exchange (NEE), ecosystem respiration (ER) and gross ecosystem production (GEP) rates, while the other three sites generally showed intercomparable CO2 exchange rates. Topography aspect-induced soil microclimate differences rather than the elevation were the primary drivers for the soil nutrient status and ecosystem CO2 exchange. The temperature sensitivity of soil respiration above 0 °C increased with elevation, while elevation did not regulate the temperature sensitivity below 0 °C or the moisture sensitivity. Soil total nitrogen, carbon, and ammonium contents were the controls of temperature sensitivity below 0 °C. Overall, our results emphasize the significance of considering elevation and microclimate when predicting the response of CO2 balance to climate change or upscaling to regional scales, particularly during the growing season. However, outside the growing season, other factors such as soil nutrient dynamics, play a more influential role in driving ecosystem CO2 fluxes. To accurately upscale or predict annual CO2 fluxes in arctic tundra regions, it is crucial to incorporate elevation-specific microclimate conditions into ecosystem models.

Abstract The inhibition of foliar respiration by light is a crucial yet often overlooked component in estimating ecosystem respiration. However, current estimations of the light inhibition of ecosystem respiration are biased by ignoring the effects of moisture factors. We developed a novel physics‐constrained machine learning method to quantify the extent of light inhibition (Reli) driven by multiple factors in global ecosystems. Our findings revealed significant seasonal variations in light inhibition rate aligned with vegetation growth. Temperature predominantly influenced variations in Reli, and the temperature‐Reli relationship was regulated by vapor pressure deficit rather than soil water content. A reassessment of global ecosystem respiration revealed that current Earth system models (ESMs) overestimate ecosystem respiration in mid‐to‐high latitude dryland regions, with a global average light inhibition strength of 0.51 (±0.16). Knowledge from this study provides an accurate understanding of light inhibition driven by temperature and moisture coupling in simulating carbon cycle.

Abstract Polar‐orbiting satellites have significantly improved our understanding of the terrestrial carbon cycle, yet they are not designed to observe sub‐daily dynamics that can provide unique insight into carbon cycle processes. Geostationary satellites offer remote sensing capabilities at temporal resolutions of 5‐min, or even less. This study explores the use of geostationary satellite data acquired by the Geostationary Operational Environmental Satellite—R Series (GOES‐R) to estimate terrestrial gross primary productivity (GPP) and ecosystem respiration (RECO) using machine learning. We collected and processed data from 126 AmeriFlux eddy covariance towers in the Contiguous United States synchronized with imagery from the GOES‐R Advanced Baseline Imager (ABI) from 2017 to 2022 to develop ML models and assess their performance. Tree‐based ensemble regressions showed promising performance for predicting GPP (R2 of 0.70 ± 0.11 and RMSE of 4.04 ± 1.65 μmol m−2 s−1) and RECO (R2 of 0.77 ± 0.10 and RMSE of 0.90 ± 0.49 μmol m−2 s−1) on a half‐hourly time step using GOES‐R surface products and top‐of‐atmosphere observations. Our findings align with global efforts to utilize geostationary satellites to improve carbon flux estimation and provide insight into how to estimate terrestrial carbon dioxide fluxes in near‐real time.

Livestock grazing can strongly determine how grasslands function and their role in the carbon cycle. However, how ecosystem carbon exchange responds to grazing and the underlying mechanisms remain unclear. We measured ecosystem carbon fluxes to explore the changes in carbon exchange and their driving mechanisms under different grazing intensities (CK, control; HG, heavy grazing; LG, light grazing; MG, moderate grazing) based on a 16‐year long‐term grazing experimental platform in a desert steppe. We found that grazing intensity influenced aboveground biomass during the peak growing season, primarily by decreasing shrubs and semi‐shrubs and perennial forbs. Furthermore, grazing decreased net ecosystem carbon exchange by decreasing aboveground biomass, especially the functional group of shrubs and semi‐shrubs. At the same time, we found that belowground biomass and soil ammonium nitrogen were the driving factors of soil respiration in grazed systems. Our study indicates that shrubs and semi‐shrubs are important factors in regulating ecosystem carbon exchange under grazing disturbance in the desert steppe, whereas belowground biomass and soil available nitrogen are important factors regulating soil respiration under grazing disturbance in the desert steppe; this results provide deeper insights for understanding how grazing moderates the relationships between soil nutrients, plant biomass, and ecosystem CO2 exchange, which provide a theoretical basis for further grazing management. [ABSTRACT FROM AUTHOR]

Oil palm (OP) plantations have replaced large areas of forest in the tropical landscape of Southeast Asia and are major emitters of greenhouse gases (GHGs). To move towards more environmentally friendly plantation management, a hopeful approach is to implement strategies to increase vegetation complexity. These options include relaxed management of understory vegetation to increase complexity in productive plantations, passive restoration of forest areas around rivers by leaving mature oil palm during replanting, and active forest restoration along river margins with planting of forest trees. These practices have the potential to deliver a range of benefits such as soil protection, reduced erosion and sedimentation in rivers, pest control and support for biodiversity, but little is known about their impact on greenhouse gas fluxes. The aim of this study was to assess the impact of improved understory growth management and the use of riparian forestry on GHG fluxes in OP plantations, making use of two long-term experiments (the Biodiversity and Ecosystem Function in Tropical Agriculture Understory Vegetation (BEFTA UV) Project; the Riparian Ecosystem Restoration in Tropical Agriculture (RERTA) Project) in Riau Province, Sumatra, Indonesia. We measured nitrous oxide (N2O), methane (CH4) and ecosystem respiration (CO2) from mature OP sites with different levels of understory vegetation and different riparian buffer restoration treatments using the static chamber method. We used linear mixed effects models to test for treatment effects, whilst accounting for soil moisture and experimental design factors (time and space). The understory vegetation treatments (normal, reduced and enhanced complexity of understory) had no effect on N2O and CH4 flux. Regarding differences in ecosystem respiration, effects attributable to the understory vegetation treatments were not strong. For the riparian restoration treatments, the fixed effects variables in the models explained little variation in the fluxes of all GHGs. Therefore, given the proven benefits of more complex understory vegetation for supporting biodiversity and healthy ecosystem functioning, plus the potential for restored riparian buffers to support biodiversity and services and to reduce GHG emissions over time, our findings reinforce the concept that these features bring environmental benefits in OP landscapes, with no measurable effects on GHG emissions. [ABSTRACT FROM AUTHOR]

Microbial biofilms form the base of many stream food webs. Because biofilm activity shapes the energy flow and material cycle of stream ecosystems, understanding what limits biofilm productivity provides a foundation for understanding how streams respond to seasonal changes or nutrient inputs. Streams can exhibit seasonal and spatial patterns in nutrient concentrations, light, and temperature, all of which can influence biofilm production. In particular, stream N and P often limit biofilm production, but nutrients besides N and P are rarely tested. Moreover, biofilm nutrient limitation has generally been tested only in the summer and not across the spatial gradient within a single watershed. Using nutrient diffusing substrates, we tested whether biofilm nutrient limitation (N, P, and Si) varied spatially and seasonally across a mixed land-use watershed in the inland Pacific Northwest, USA. We found that heterotrophic respiration was primarily limited by N, secondarily limited by P, and tertiarily limited by Si. The magnitude of limitation was greatest in summer and in the nutrient-poor headwaters, and it was most variable in tributaries. In contrast, autotrophic biofilm limitation was idiosyncratic, with no clear spatial patterns. Si inhibition occurred at many sites, particularly in the autumn, possibly because of biofilm community shifts in response to nutrient amendments. Overall, our results suggest that in watersheds with mixed land use, heterotrophic limitation of N, P, and Si will follow semipredictable longitudinal patterns, driven by gradients in land use and nutrient concentration, whereas autotrophic nutrient limitation may depend on site-specific variables. [ABSTRACT FROM AUTHOR]

Context: Metabolic balance determines whether an ecosystem acts as a source or sink of carbon dioxide (CO2) and considering that a substantial portion of inland aquatic ecosystems act as a source of CO2 to the atmosphere, it is important to highlight that there is still no agreement on how global change will affect the ecosystem metabolic-balance response. It then becomes more important to study the interactions between global-change drivers and aquatic metabolism. Aims: Assess possible shifts in ecosystem metabolic balance owing to global-change factors. Methods: Collapsed factorial designs and novel experimental units have been used to study responses to future conditions. Key results: In the study site, bacterial production was not affected by an increased temperature alone; however, increased nutrient availability may unmask UV or CO2 as a source of stress to bacteria. A synergistic effect between temperature and the combined effect of nutrients and CO2 on primary producers was also found. Conclusions: In future scenarios, some heterotrophic inland water ecosystems may shift from heterotrophic to autotrophic states and therefore act as CO2 sinks. Implications: This study provides a framework to support a deepening of knowledge on this topic. Many inland waters act as a source of carbon dioxide (CO2) to the atmosphere. The ecosystem metabolic balance determines this response, making it a key topic of study, including its interactions with drivers of global change to acknowledge future responses. In this study, new experimental units and novel collapsed factorial designs are employed to address the potential shift from source to sink of CO2 from inland freshwaters. [ABSTRACT FROM AUTHOR]

Cultivated grasslands are an important part of grassland ecosystems and have been proven to be major carbon sinks, then playing an important role in the global carbon balance. The effect of cultivated grassland type (Medicago sativa, Triticum aestivum, Secale cereale, and Vicia villosa grasslands) on carbon flux (including net ecosystem CO2 exchange (NEE), ecosystem respiration (ER), and gross ecosystem productivity (GEP)) downstream of the Yellow River was studied via the static chamber technique and a portable photosynthetic system. Bare land was used as a control. The results showed that the four cultivated grassland types were mainly carbon sinks, and bare land was a carbon source. The cultivated grassland types significantly affected carbon flux. The average NEE and GEP of the grassland types were in the following order from high to low: Medicago sativa, Secale cereale, Triticum aestivum, and Vicia villosa grassland. Stepwise regression analysis showed that among all measured environmental factors, soil pH, soil bulk density (BD), soil organic carbon (SOC), and soil microbial carbon (MBC) were the main factors affecting CO2 flux. The combined influence of soil BD, SOC, and pH accounted for 77.6% of the variations in NEE, while soil BD, SOC, and MBC collectively explained 79.8% of changes in ER and 72.9% of the changes in GEP. This finding indicates that Medicago sativa grassland is a cultivated grassland with a high carbon sink level. The changes in carbon flux were dominated by the effects of soil physicochemical properties. [ABSTRACT FROM AUTHOR]

Increased soil nutrient availability, and associated increases in vegetation productivity, could create a negative feedback between Arctic ecosystems and the climate system, thereby reducing the contribution of Arctic ecosystems to future climate change. To predict whether this feedback will develop, it is important to understand the environmental controls over nutrient cycling in High Arctic ecosystems and their impact on carbon cycling processes. Here, we examined the environmental controls over soil nitrogen availability in a High Arctic wet sedge meadow and how abiotic factors and soil nitrogen influenced carbon dioxide exchange processes. The importance of environmental variables was consistent over the 3 years, but the magnitudes of their effect varied depending on climate conditions. Ammonium availability was higher in warmer years and wetter conditions, while drier areas within the wetland had higher nitrate availability. Carbon uptake was driven by soil moisture, active layer depth, and variability between sampling sites and years (R2 = 0.753), while ecosystem respiration was influenced by nitrogen availability, soil temperature, active layer depth, and sampling year (R2 = 0.848). Considered together, the future carbon dioxide source or sink potential of high latitude wetlands will largely depend on climate-induced changes in moisture and subsequent impacts on nutrient availability.

Inland waters emit large amounts of nitrous oxide (N2O) to the atmosphere, which has attracted extensive attention worldwide. The goal of this study was to investigate the relationship between N2O flux and ecosystem respiration (ER) in aquatic ecosystems. We measured N2O and ER in 10 typical exogenous and endogenous static water bodies in eastern China and identified the relationship between N2O flux and ER in the aquatic environments using a Bayesian method from April 29 to May 4, in 2022. The results showed that N2O flux and ER were significantly higher in exogenous water bodies than in endogenous water bodies. There was a significant positive correlation between N2O flux and carbon dioxide (CO2) flux and BOD5 in the water. The Bayesian model explained 61% to 71% of the variability of N2O flux and clarified the uncertainty of the model. We also distinguished the relationship between N2O flux and ER in endogenous and exogenous water bodies. In endogenous water bodies, the effect of carbon source limitation on N2O flux is greater than the effect of nitrogen source limitation. However, the coupling relationship between N2O and CO2 is stronger in exogenous water bodies than in endogenous water bodies. In summary, ER indirectly promotes N2O emission, which provides a basis for an estimation method of N2O flux from water bodies and the coupling mechanism of ER. [ABSTRACT FROM AUTHOR]

Improving the accuracy of monitoring cropland CO2 exchange at heterogeneous spatial scales is of high importance to limit spatial and temporal uncertainty of terrestrial carbon (C) dynamic estimates. A combination of field scale eddy covariance EC) CO2 flux data and spatially matched Sentinel-2 derived vegetation indices (VIs) was tested as an approach to upscale agricultural C flux. The ability of different VIs to estimate daily net ecosystem exchange (NEE) and gross primary productivity GPP) based on linear regression models was assessed. Most VIs showed high (>0.9) and statistically significant (p<0.001) correlations with GPP and NEE although some VIs deviated from the seasonal pattern of CO2 exchange. In contrast, correlations between ecosystem respiration (Reco) and VIs were weak and statistically not significant, and no attempt was made to estimate Reco from VIs. Linear regression models explained generally more than 80% and 70% of the variability of NEE and GPP, respectively, with high variability amongst the individual VIs. The performance in estimating daily C fluxes varied amongst VIs depending on C flux component (NEE or GPP) and observation period. RMSE values ranged from 1.35 g C m-2 d-1 using the Green Normilized Difference Vegetation Index (GNDVI) for NEE to 5 g C m-2 d-1 using the Simple Ratio SR) for GPP. This equated to an underestimated net C uptake of only 41 g C m-2 (18%) and an overestimation of gross C uptake of 854 g C m-2 (73%). Differences between measured and estimated C fluxes were mainly explained by the diversion of the C flux and VI signal during winter, when C uptake stayed low while VI values indicated an increased C uptake due to relatively high crop leaf area. Overall, results exhibited similar error margins as mechanistic crop models. Thus, they indicated suitability and developability of the proposed approach to monitor cropland C exchange with satellite derived VIs. [ABSTRACT FROM AUTHOR]

In all ecosystems, metabolism is an essential process that controls the biogeochemical carbon cycle through the fixation and mineralization of organic matter. However, the ecological metabolic balance in the semi-riverine and eutrophic reservoir remains poorly understood. In this study, seasonal variations in gross primary production (GPP), ecosystem respiration (ER), net ecosystem production (NEP = GPP−ER), chlorophyll a (Chl a) concentration, and zooplankton abundance were investigated within the euphotic layer of Lake Sagami from May to December both in 2016 and 2017. The Chl a concentration, GPP, ER, and NEP integrated vertically in the euphotic layer varied in the range of 0.7–92.4 mg m−3, 0.3–221.4, 0.6–59.2, −43.5–202 mmol O2 m−3 d−1, respectively. A significant positive linear relationship was observed between the GPP and NEP. The threshold GPP, where GPP equals ER, was 15.6 mmol O2 m−3 d−1, which is very low compared to the values in other eutrophic lakes. As no significant relationship was found between Chl a concentration, GPP and zooplankton abundance, it is possible that most zooplankton feed on allochthonous organic matter rather than autochthonous organic matter. Furthermore, no significant relationship was observed between the ER and zooplankton abundance, suggesting that the ER represents the activity of heterotrophic communities other than zooplankton. The ER was positively correlated with the water temperature. The variation in ER in Lake Sagami is most likely influenced by water temperature rather than particulate organic matter. [ABSTRACT FROM AUTHOR]

Increasing temperatures and winter precipitation can influence the carbon (C) exchange rates in arctic ecosystems. Feedbacks can be both positive and negative, but the net effects are unclear and expected to vary strongly across the Arctic. There is a lack of understanding of the combined effects of increased summer warming and winter precipitation on the C balance in these ecosystems. Here we assess the short‐term (1–3 years) and long‐term (5–8 years) effects of increased snow depth (snow fences) (on average + 70 cm) and warming (open top chambers; 1–3°C increase) and the combination in a factorial design on all key components of the daytime carbon dioxide (CO2) fluxes in a wide‐spread heath tundra ecosystem in West Greenland. The warming treatment increased ecosystem respiration (ER) on a short‐ and long‐term basis, while gross ecosystem photosynthesis (GEP) was only increased in the long term. Despite the difference in the timing of responses of ER and GEP to the warming treatment, the net ecosystem exchange (NEE) of CO2 was unaffected in the short term and in the long term. Although the structural equation model (SEM) indicates a direct relationship between seasonal accumulated snow depth and ER and GEP, there were no significant effects of the snow addition treatment on ER or GEP measured over the summer period. The combination of warming and snow addition turned the plots into net daytime CO2 sources during the growing season. Interestingly, despite no significant changes in air temperature during the snow‐free time during the experiment, control plots as well as warming plots revealed significantly higher ER and GEP in the long term compared to the short term. This was in line with the satellite‐derived time‐integrated normalized difference vegetation index of the study area, suggesting that more factors than air temperature are drivers for changes in arctic tundra ecosystems. [ABSTRACT FROM AUTHOR]

Abstract Livestock grazing can strongly determine how grasslands function and their role in the carbon cycle. However, how ecosystem carbon exchange responds to grazing and the underlying mechanisms remain unclear. We measured ecosystem carbon fluxes to explore the changes in carbon exchange and their driving mechanisms under different grazing intensities (CK, control; HG, heavy grazing; LG, light grazing; MG, moderate grazing) based on a 16‐year long‐term grazing experimental platform in a desert steppe. We found that grazing intensity influenced aboveground biomass during the peak growing season, primarily by decreasing shrubs and semi‐shrubs and perennial forbs. Furthermore, grazing decreased net ecosystem carbon exchange by decreasing aboveground biomass, especially the functional group of shrubs and semi‐shrubs. At the same time, we found that belowground biomass and soil ammonium nitrogen were the driving factors of soil respiration in grazed systems. Our study indicates that shrubs and semi‐shrubs are important factors in regulating ecosystem carbon exchange under grazing disturbance in the desert steppe, whereas belowground biomass and soil available nitrogen are important factors regulating soil respiration under grazing disturbance in the desert steppe; this results provide deeper insights for understanding how grazing moderates the relationships between soil nutrients, plant biomass, and ecosystem CO2 exchange, which provide a theoretical basis for further grazing management.

Oil palm (OP) plantations have replaced large areas of forest in the tropical landscape of Southeast Asia and are major emitters of greenhouse gases (GHGs). To move towards more environmentally friendly plantation management, a hopeful approach is to implement strategies to increase vegetation complexity. These options include relaxed management of understory vegetation to increase complexity in productive plantations, passive restoration of forest areas around rivers by leaving mature oil palm during replanting, and active forest restoration along river margins with planting of forest trees. These practices have the potential to deliver a range of benefits such as soil protection, reduced erosion and sedimentation in rivers, pest control and support for biodiversity, but little is known about their impact on greenhouse gas fluxes. The aim of this study was to assess the impact of improved understory growth management and the use of riparian forestry on GHG fluxes in OP plantations, making use of two long-term experiments (the Biodiversity and Ecosystem Function in Tropical Agriculture Understory Vegetation (BEFTA UV) Project; the Riparian Ecosystem Restoration in Tropical Agriculture (RERTA) Project) in Riau Province, Sumatra, Indonesia. We measured nitrous oxide (N2O), methane (CH4) and ecosystem respiration (CO2) from mature OP sites with different levels of understory vegetation and different riparian buffer restoration treatments using the static chamber method. We used linear mixed effects models to test for treatment effects, whilst accounting for soil moisture and experimental design factors (time and space). The understory vegetation treatments (normal, reduced and enhanced complexity of understory) had no effect on N2O and CH4 flux. Regarding differences in ecosystem respiration, effects attributable to the understory vegetation treatments were not strong. For the riparian restoration treatments, the fixed effects variables in the models explained little variation in the fluxes of all GHGs. Therefore, given the proven benefits of more complex understory vegetation for supporting biodiversity and healthy ecosystem functioning, plus the potential for restored riparian buffers to support biodiversity and services and to reduce GHG emissions over time, our findings reinforce the concept that these features bring environmental benefits in OP landscapes, with no measurable effects on GHG emissions.

Cultivated grasslands are an important part of grassland ecosystems and have been proven to be major carbon sinks, then playing an important role in the global carbon balance. The effect of cultivated grassland type (Medicago sativa, Triticum aestivum, Secale cereale, and Vicia villosa grasslands) on carbon flux (including net ecosystem CO2 exchange (NEE), ecosystem respiration (ER), and gross ecosystem productivity (GEP)) downstream of the Yellow River was studied via the static chamber technique and a portable photosynthetic system. Bare land was used as a control. The results showed that the four cultivated grassland types were mainly carbon sinks, and bare land was a carbon source. The cultivated grassland types significantly affected carbon flux. The average NEE and GEP of the grassland types were in the following order from high to low: Medicago sativa, Secale cereale, Triticum aestivum, and Vicia villosa grassland. Stepwise regression analysis showed that among all measured environmental factors, soil pH, soil bulk density (BD), soil organic carbon (SOC), and soil microbial carbon (MBC) were the main factors affecting CO2 flux. The combined influence of soil BD, SOC, and pH accounted for 77.6% of the variations in NEE, while soil BD, SOC, and MBC collectively explained 79.8% of changes in ER and 72.9% of the changes in GEP. This finding indicates that Medicago sativa grassland is a cultivated grassland with a high carbon sink level. The changes in carbon flux were dominated by the effects of soil physicochemical properties.

More than half of the world’s rivers experience occasional, seasonal, or permanent drying, and this may increase because of climate change. Drying, i.e. severe reduction in water flow even leading to streambed desiccation, can have a profound impact on the available aquatic habitat, biodiversity, and functions of rivers. Yet, to date, it is unclear whether similar drying events in comparable climate zones result in similar changes in ecosystem processes, such as river metabolism or greenhouse gas (GHG) emissions. Here, we synthesise the detected effects of drying on gross primary production (GPP) and ecosystem respiration (ER), as well as on the emissions of GHGs (CO _2 , CH _4 , and N _2 O) in rivers and streams. We examined the current available scientific literature detailing the impact of drying on these variables when measured either in the field or in the laboratory. We extracted data from 30 studies analysing GPP and ER responses, and data on GHG emissions from another 35 studies. Then, we conducted a meta-analysis to determine whether the magnitude and direction of the effects varied across the systems and climate zones studied, or according to the type (natural or human-induced) and severity of drying. In general, drying enhanced GPP (under low flows) and CH _4 emissions, and decreased CO _2 and N _2 O emissions. The hydrological phases throughout streambed drying (low water flow, isolated pools, or desiccation) had differential effects on metabolism and GHG emissions. The effects of drying were generally more severe when it induced desiccation, rather than just periods of low flow. Desiccation strongly reduced GPP, likely because of the die-off of algae, while its negative effect on ER was smaller. Greater decrease in GPP than in ER under desiccation would lead to increase in CO _2 emissions; our results showed accordingly that desiccation increased CO _2 emissions. Furthermore, the magnitude and direction of the effects varied depending on the study type. Experimental studies conducted in micro- and mesocosms demonstrated greater effects than field studies, thus the extrapolation of results from these to real conditions should be done with caution. Overall, the effects’ direction was inconsistent across climate zones, except for the Mediterranean climate zone, where drying was showing a negative effect on both metabolism and GHG emissions. Our synthesis may contribute to identifying the worldwide trends and patterns of drying on riverine functions associated to global change impacts on river and stream ecosystems.

The phenological cycles of terrestrial ecosystems have shifted with the changing climate, and the altered timings of biogeochemical fluxes may also exert feedback on the climate system. As regulators of land carbon balance, relative shifts in photosynthetic and respiratory phenology under climate change are of great importance. However, the relative seasonal dynamics of these individual processes and their sensitivity to climate factors as well as the implications for carbon cycling are not well understood. In this study, we examined the relationship in the seasonality of gross primary production (GPP) and ecosystem respiration (RE) as well as their temperature sensitivities and the implications for carbon uptake with around 1500 site-years’ of data from FLUXNET 2015 and Boreal Ecosystem Productivity Simulator (BEPS) at 212 sites. The results showed that RE started earlier in the spring and ended later in the autumn than GPP over most biomes. Furthermore, the flux phenology metrics responded differently to temperature: GPP phenology was more sensitive to changes during the spring temperature than RE phenology, and less sensitive to autumn temperature than RE. We found large BEPS-observation discrepancies in seasonality metrics and their apparent temperature sensitivity. The site-based BEPS projections did not capture the observed seasonal metrics and temperature sensitivities in either GPP or RE seasonality metrics. Improved understanding of the asynchrony of GPP and RE as well as different sensitivity of environmental factors are of great significance for reliable future carbon balance projections.

This study analyzed the sensitivities of carbon cycle to surface air temperature using the CO _2 flux data collected from June to September for six years (2014–2019) over a moist tundra site in Council, Alaska. The tundra ecosystem was a strong sink of carbon in June and July, a weak sink in August with rapidly decreasing photosynthesis, and a carbon source in September. The ecosystem respiration (Re) and gross primary production (GPP) were obtained from the net ecosystem exchange (NEE) of eddy-covariance system. Both the Re and GPP increased with temperature, enhancing carbon emission and uptake during observation period. Notably, Re showed higher sensitivity to temperature than GPP did. This result means that as global warming continues, the increase in carbon release is greater than the increase in carbon uptake. In other words, the tundra ecosystem is expected to become a weaker carbon sink in June and July and a stronger source of carbon in September. Possible mechanism of different temperature sensitivities of Re and GPP as well as temporal variations of temperature sensitivities are suggested. Present results highlight the importance of understanding the temperature sensitivities of Re and GPP in various tundra ecosystems to accurately understand changes in the carbon cycle in the Arctic region.

• There was no temperature gradient along 9–387 m elevation gradient in arctic tundra. • Topography aspect-induced soil microclimate differences drove ecosystem CO 2 exchange. • Temperature sensitivity of soil respiration above 0 °C increased with elevation. • Elevation did not regulate temperature sensitivity below 0 °C or moisture sensitivity. Generally, with increasing elevation, there is a corresponding decrease in annual mean air and soil temperatures, resulting in an overall decrease in ecosystem carbon dioxide (CO 2) exchange. However, there is a lack of knowledge on the variations in CO 2 exchange along elevation gradients in tundra ecosystems. Aiming to quantify CO 2 exchange along elevation gradients in tundra ecosystems, we measured ecosystem CO 2 exchange in the peak growing season along an elevation gradient (9–387 m above sea level, m.a.s.l) in an arctic heath tundra, West Greenland. We also performed an ex-situ incubation experiment based on soil samples collected along the elevation gradient, to assess the sensitivity of soil respiration to changes in temperature and soil moisture. There was no apparent temperature gradient along the elevation gradient, with the lowest air and soil temperatures at the second lowest elevation site (83 m). The lowest elevation site exhibited the highest net ecosystem exchange (NEE), ecosystem respiration (ER) and gross ecosystem production (GEP) rates, while the other three sites generally showed intercomparable CO 2 exchange rates. Topography aspect-induced soil microclimate differences rather than the elevation were the primary drivers for the soil nutrient status and ecosystem CO 2 exchange. The temperature sensitivity of soil respiration above 0 °C increased with elevation, while elevation did not regulate the temperature sensitivity below 0 °C or the moisture sensitivity. Soil total nitrogen, carbon, and ammonium contents were the controls of temperature sensitivity below 0 °C. Overall, our results emphasize the significance of considering elevation and microclimate when predicting the response of CO 2 balance to climate change or upscaling to regional scales, particularly during the growing season. However, outside the growing season, other factors such as soil nutrient dynamics, play a more influential role in driving ecosystem CO 2 fluxes. To accurately upscale or predict annual CO 2 fluxes in arctic tundra regions, it is crucial to incorporate elevation-specific microclimate conditions into ecosystem models. [ABSTRACT FROM AUTHOR]

In the semi-arid grasslands of the southwest United States, annual precipitation is divided between warm-season (July-September) convective precipitation and cool-season (December-March) frontal storms. While evidence suggests shifts in precipitation seasonal distribution, there is a poor understanding of the ecosystem carbon flux responses to cool-season precipitation and the potential legacy effects on subsequent warm-season carbon fluxes. Results from a two-year experiment with three cool-season precipitation treatments (dry, received 5th percentile cool-season total precipitation; normal, 50th; wet, 95th) and constant warm-season precipitation illustrate the direct and legacy effects on carbon fluxes, but in opposing ways. In wet cool-season plots, gross primary productivity (GPP) and ecosystem respiration (ER) were 103% and 127% higher than in normal cool-season plots. In dry cool-season plots, GPP and ER were 47% and 85% lower compared to normal cool-season plots. Unexpectedly, we found a positive legacy effect of the dry cool-season treatment on warm-season carbon flux, resulting in a significant increase in both GPP and ER in the subsequent warm season, compared to normal cool-season plots. Our results reveal positive legacy effects of cool-season drought on warm-season carbon fluxes and highlight the importance of the relatively under-studied cool-growing season and its direct/indirect impact on the ecosystem carbon budget., (© 2024 John Wiley & Sons Ltd.)

• We measured CO 2 fluxes with eddy-covariance technique in a semiarid Patagonian steppe. • The shrub-grass steppe was a carbon sink during the three study years. • The strength of the carbon sink was higher in a relatively wet year. • Global radiation, leaf area index and deep soil moisture were the main controlling factors of C fluxes. • During the growing season the relevance of deep soil moisture increased for NEE, GPP and R eco. Arid and semiarid ecosystems comprise approximately 40 % of the global terrestrial surface and play an important role in the carbon-climate system. However, despite their large geographic extension in South America, they are largely under-represented in studies of ecosystem carbon fluxes. Eddy-covariance measurements of net ecosystem carbon exchange (NEE) were carried out in a Patagonian steppe co-dominated by grasses and shrubs in southern Argentina, for four years, including relatively dry and wet years. We evaluated the seasonal and annual variation of NEE, gross primary productivity (GPP) and ecosystem respiration (R eco), and their environmental controls. This ecosystem exhibits large seasonal fluctuations in global radiation (Rg), air temperature, vapor pressure deficit, soil moisture and leaf area index (LAI). This steppe was a net carbon sink with a mean annual cumulative NEE of -249 g C m−2 yr−1. The strength as carbon sink was higher (-283.9 g C m−2 yr−1) in the wet year. NEE was tightly coupled to GPP with a marked peak at the middle of the growing season when LAI achieved its maximum value. R eco exhibited less fluctuation throughout time than GPP. A random forest machine-learning analysis indicated that Rg, LAI and deep soil moisture are the main drivers contributing to variability in daily and monthly cumulative NEE, GPP and R eco during the growing season and across the entire study period. Results suggest that deep-rooted shrubs contribute substantially to C fluxes during the growing season (low precipitation and high VPD period) by acceding to deep and more stable water sources which allow extending the period of net carbon capture. This study helps to understand how this ecosystem functions and to predict how this steppe will respond to future climate. In addition, this research highlights the need for conservation of this ecosystem due to its large extension and carbon sequestration capacity. [ABSTRACT FROM AUTHOR]

• Eddy-covariance was used at two forest sites disturbed by windthrow with contrasting management. • Unmanaged site showed greater gross primary production but also higher ecosystem respiration. • Both sites showed similar levels of evapotranspiration. • The managed site had lower gross but higher net water-use efficiency compared to unmanaged site. • The unmanaged site turned into net carbon sink 17 years after windthrow. Windthrow is a major forest disturbance source in Europe. The impact of management (salvage logging) and no-management (deadwood left in ecosystem) treatments on carbon and water fluxes of Norway spruce stand affected by windthrow were analysed. The net ecosystem production (NEP), gross primary production (GPP), ecosystem respiration (R eco) and evapotranspiration (ET) were measured with eddy-covariance tower during 2019–2022 period. Additional chamber gas-exchange measurements, and vegetation inventory were performed. The unmanaged site had greater vegetation diversity and plant abundance, with higher leaf area index (LAI). The managed site showed overall higher NEP, lower GPP, lower R eco , lower GPP based water-use efficiency (WUE GPP), but higher NEP based WUE NEP , compared with unmanaged site. The ET showed no clear trend between the two treatments. The higher GPP of unmanaged site can be linked to greater abundance of herbaceous species, which showed significantly higher photosynthetic capacity than the tree species. Moreover, the higher WUE GPP of unmanaged site can be affected also by the higher LAI of the unmanaged site. Nevertheless, if the R eco is accounted for in WUE NEP , the differences between sites are reversed and the unmanaged site had lower WUE NEP compared to the managed site. The option to leave the disturbed site without management leads to more productive ecosystem (GPP), with greater species diversity and abundance, but also with greater R eco and lower WUE NEP. The discrepancy between WUE GPP and WUE NEP suggests that studies analysing natural ecosystems affected by disturbances should use WUE NEP to account for R eco carbon losses and avoid mis-interpreting the ecosystem carbon-water balance with WUE GPP. [Display omitted] [ABSTRACT FROM AUTHOR]

The dune ecosystem plays a significant role in the global carbon cycle. The Horqin Sandy Land is a typical semi-arid fragile ecosystem in northern China. Understanding the magnitudes and dynamics of carbon dioxide fluxes within this region is essential for understanding the carbon balance. Used 6 years (2013–2018) measurements from an eddy-covariance system, we analyzed the dynamic patterns of net ecosystem carbon exchange (NEE), gross primary production (GPP), and ecosystem respiration (Reco) of the dune ecosystem in Horqin Sandy Land and examined their responses to climate factors with a focus on the precipitation. The results showed that the NEE of the dune ecosystem fluctuated from −166 to 100 gCO 2 ·m−2·year−1 across the 6 growing seasons, with an average of −56 gCO 2 ·m−2·year−1. The precipitation was not a key factor influencing the carbon flux variability. During the mid-growth stage, GPP was primarily affected by the effective precipitation frequency (R2 ranging from 0.65 to 0.85, P < 0.05), followed by fractional vegetation cover (R2 ranging from 0.65 to 0.68, P < 0.05). However, in the early and late growth stages, temperature predominantly drove the carbon flux (R2 = 0.75, P < 0.01). The interannual variability of carbon flux can be predominantly elucidated by phenological indicators such as CO 2 uptake (CU start), end of CO 2 uptake (CU end), CO 2 uptake period (CUP), and Spring lag. The results demonstrated the dune ecosystem is a weak carbon sink in semi-arid ecosystems. Furthermore, we emphasized the significance of effective precipitation frequency in regulating carbon fluxes. Our results provide a foundational understanding of the carbon balance in semi-arid ecosystems. [Display omitted] • Six-year monitoring of carbon fluxes from a semi-arid dune ecosystem. • The CO 2 sink was weak in the dune ecosystem located in Horqin Sandy Land (−56 gCO 2 ·m−2·year−1). • The amount of precipitation is not the main factor affecting carbon fluxes. • The carbon fluxes are mainly influenced by the effective precipitation frequency. [ABSTRACT FROM AUTHOR]

This study investigated variability in ecosystem metabolism in the meromictic, oligotrophic, and deep Lake Tanganyika. A large buoy equipped with a weather station, oxygen and temperature sensors for every 10 m down to 102 m depth and an irradiance sensor at 0 and 22 m depth, provided a three-month data with one-minute frequency. These data enabled us to derive detailed description of water column mixing and light conditions along with daily depth specific rates of gross primary production, ecosystem respiration and net production over a 3-month period. We applied a mass balance approach which included dissolved oxygen exchange between depth layers driven by mixed-layer deepening and eddy diffusivity from a one-dimensional hydrodynamic model. The vertical extent of the upper mixed layer varied between 21–40 m and the extent of the metalimnion varied between 48–75 m, with the euphotic zone (20–38 m) extending into the metalimnion on several days, providing enough light for primary production to occur below the upper mixed layer. Vertical profiles of metabolism showed several periods with elevated primary production in the metalimnion around the deep chlorophyll maximum. This deep productivity may compensate for the decreasing primary production in the epilimnion caused by climate change induced reductions in nutrient inputs from deeper waters. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a methodology that can improve the estimations of Gross Primary Productivity (GPP) and ecosystem Respiration (R eco ) processes at a regional scale. This method is based on a satellite data-driven approach which is suitable for regions like India where there exists a serious shortage of ground-based observations of biospheric carbon fluxes (e.g., Eddy Covariance (EC) flux measurements). We relied on the Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance for capturing vegetation dynamics in the Light-Use Efficiency (LUE)-based vegetation model. Further, we utilised recently available satellite-based Solar-Induced Fluorescence (SIF) and other variables such as Soil Moisture (SM) and Soil Temperature (ST) to refine the predictions of GPP and R eco . The methodology involves establishing a relationship between SIF and GPP for different vegetation classes over India. The SIF-GPP relationship established across the biomes was then used to correct the GPP fluxes simulated by the LUE-based model. Similarly, the ecosystem respiration estimations by the model have undergone refinement by incorporating ST and SM information. This innovative method shows remarkable potential to improve biospheric CO 2 uptake and release, especially for in situ data-constrained regions like India. • SIF-based information is introduced to a light-use efficiency-based vegetation model. • SIF-GPP relationship is established for major biomes across India. • SM and ST information is incorporated into the R eco simulations in the model., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author(s).)

• Seasonality and annual values of the energy balance and CO 2 exchange components are closely related to rainfall variability. • Evaporative stress index (ESI) can reach values of extreme water stress during the dry season. • Rain pulses caused systematic increases in G s and higher CO 2 absorption. Several aspects of the hydrological regime influence the CO 2 exchanges between the atmosphere and drylands. The objective of this study was to carry out a thorough assessment of the role of rainfall pulses on the energy fluxes, water vapor and CO 2 exchanges over the Caatinga Biome using data collected in 2014 and 2015. We conducted an unprecedented analysis on the effects of precipitation pulses on the different components of the CO 2 balance between the Caatinga and the atmosphere. Data was collected in a flux tower equipped with an eddy covariance system in a preserved Caatinga area in Northeast Brazil. Results showed a well defined relationship between rainfall variability and energy balance and CO 2 exchange. Rain pulses caused systematic increases in surface conductance (G s), leading to a higher CO 2 absorption in the short-term. In 2014, the higher amount of rain pulse events along with higher overall rainfall amounts resulted in 68 % of total absorbed CO 2 being assimilated during post-pulse events. In 2015, fewer but more intense pulses occurred, contributing to 39 % of total CO 2 absorbed in the wet season. The overall effect of rain pulses on the CO 2 balance over the Caatinga site in the Semiarid Brazil depends on the distribution and amount of rainfall in each pulse event. [ABSTRACT FROM AUTHOR]