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Nitrogen (N) and phosphorus (P) are key limiting factors for carbon (C) fluxes in artificial grasslands. The impact of their management on ecosystem C fluxes, including net ecosystem productivity (NEP), ecosystem respiration (ER), and gross ecosystem productivity (GEP) in the Loess Plateau is unclear. An experiment was conducted to study changes in these C fluxes with varying N (0, 5, 10, 15, and 20 g N m−2) and P (0 and 10 g P m−2) additions from 2022 to 2023 in a lucerne plantation. Results showed that N addition positively influenced NEP and GEP in the first year after planting with N addition at the rate of 10 g N m−2 was optimal for C assimilation, but it had negligible effect on ER in both two years in the studied lucerne (Medicago sativa ssp. sativa) plantation. Phosphorus addition significantly increased ER and stimulated GEP, resulting in an increasing effect on NEP only at the early stage after planting. The addition of N and P enhanced soil N and P availability and further improved the leaf chemical stoichiometry characteristics, leading to changes in biomass distribution. The more belowground biomass under N addition and more aboveground production under P addition resulted in different responses of ecosystem C fluxes to N and P addition. The results suggest that the effects of N and P fertilization management on the ecosystem C cycle may be largely dependent on the distribution of above- and belowground plant biomass in the artificial grassland ecosystem. [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. Summary statement: Through a field manipulation experiment, we found that carbon fluxes decreased during a dry winter but increased in the subsequent warm season when no treatment was applied. This suggests the positive legacy effects of a dry winter and emphasizes the significance of the cool growing season's impacts. [ABSTRACT FROM AUTHOR]

Flow regimes of river ecosystems worldwide have undergone substantial changes because of water resource development, altering the way in which organic matter is generated and cycled throughout entire river catchments. Flow–ecology studies have focused on structural variables measured at small spatial scales. This creates a challenging mismatch when applying adaptive flow management for ecosystem functioning at a catchment or regional scale. Here, we sought to inform flow management by evaluating the drivers of ecosystem metabolism in a regulated river and assessing our ability to predict metabolism at unmonitored locations. We estimated rates of ecosystem metabolism from high-frequency monitoring of dissolved oxygen concentration at eight sites on the Lachlan River of Australia’s Murray–Darling Basin. We then applied a spatio-temporal stream network model to predict metabolism at unmonitored locations using only remotely sensed and gauging station predictor variables. Gross primary productivity (GPP) was higher at sites with lower mean annual discharge, and strong seasonal patterns in rates of productivity tended to be disrupted by rising flows. Similarly, ecosystem respiration (ER) was higher at sites with lower mean annual discharge and lower annual flow variation, but increased slightly in response to higher daily flows. Predictions at validation sites were generally accurate, albeit with substantial site-to-site variation. Our results suggest that flow changes may have altered metabolic rates from conditions prior to water abstraction and dam construction. These findings will assist in managing flows for ecosystem function outcomes and support extrapolation from monitored sites to the broad scales required for evaluating catchment-scale outcomes of river management. [ABSTRACT FROM AUTHOR]

The spatiotemporal variability of precipitation profoundly influences terrestrial carbon fluxes, driving shifts between carbon source and sink dynamics through gross primary productivity (GPP) and ecosystem respiration (ER). As a result, the sensitivities of GPP and ER to precipitation (SGPP and SER), along with their differential responses, are pivotal for understanding ecosystem reactions to precipitation changes and predicting future ecosystem functions. However, comprehensive evaluations of the spatiotemporal variability and differences in SGPP and SER remain notably scarce. In this study, we utilized eddy covariance flux data to investigate the spatial patterns, temporal dynamics, and differences in SGPP and SER. Spatially, SGPP and SER were generally strongly correlated. Among different ecosystems, the correlation between SGPP and SER was lowest in mixed forest and highest in broadleaf and needleleaf forest. Within the same ecosystem, SGPP and SER exhibited considerable variation but showed no significant differences. In contrast, they differed significantly across ecosystems, with pronounced variability in their magnitudes. For example, shrubland exhibited the highest values for SGPP, whereas needleleaf forest showed the highest values for SER. Temporally, SER demonstrated more pronounced changes than SGPP. Different ecosystems displayed distinct trends: shrubland exhibited an upward trend for both metrics, while grassland showed a downward trend in both SGPP and SER. Forest, on the other hand, maintained stable SGPP but displayed a downward trend in SER. Additionally, SGPP and SER exhibited a notable non-linear response to changes in the aridity index (AI), with both showing a rapid decline followed by stabilization. However, SER demonstrated a wider adaptive range to precipitation changes. Generally, this research enhances our understanding of the spatiotemporal variations in ecosystem carbon fluxes under changing precipitation patterns. [ABSTRACT FROM AUTHOR]

Carbon fluxes are valuable indicators of soil and ecosystem health, particularly in the context of climate change, where reducing carbon emissions from anthropogenic activities, such as forest fires, is a global priority. This study aimed to evaluate the impact of prescribed burns on soil respiration in semi-arid grasslands. Two treatments were applied: a prescribed burn on a 12.29 ha paddock of an introduced grass (Eragostis curvula) with 11.6 t ha−1 of available fuel, and a simulation of three fire intensities, over 28 circular plots (80 cm in diameter) of natural grasslands (Bouteloua gracilis). Fire intensities were simulated by burning with butane gas inside an iron barrel, which represented three amounts of fuel biomass and an unburned treatment. Soil respiration was measured with a soil respiration chamber over two months, with readings collected in the morning and afternoon. Moreover, CO2 emissions by combustion and productivity after fire treatment were quantified. The prescribed burns significantly reduced soil respiration: all fire intensities resulted in a decrease in soil respiration when compared with the unburned area. Changes in albedo increased the soil temperature; however, there was no relationship between changes in temperature and soil respiration; in contrast, precipitation highly stimulated it. These findings suggest that fire, under certain conditions, may not lead to more CO2 being emitted into the atmosphere by stimulating soil respiration, whereas aboveground biomass was reduced by 60%. However, considering the effects of fire in the long-term on changes in nutrient deposition, aboveground and belowground biomass, and soil properties is crucial to effectively quantify its impact on the global carbon cycle. [ABSTRACT FROM AUTHOR]

Understanding the sensitivity of ecosystem respiration (ER) to increasing temperature is crucial to predict how the terrestrial carbon sink responds to a warming climate. The temperature sensitivity of ER may vary on a diurnal basis but is poorly understood due to the paucity of observational sites documenting real ER during daytime at a global scale. Here, we used an improved flux partitioning approach to estimate the apparent temperature sensitivity of ER during the daytime (E0,day) and nighttime (E0,night) derived from multiyear observations of 189 FLUXNET sites. Our results demonstrated that E0,night is significantly higher than E0,day across all biomes, with significant seasonal variations in the day–night discrepancy in the temperature sensitivity of ER (ΔE0 = E0,night/E0,day) except for evergreen broadleaf forest and savannas. Such seasonal variations in ΔE0 mainly result from the effect of temperature and the seasonal amplitude of NDVI. We predict that future warming will decrease ΔE0 due to the reduced E0,night by the end of the century in most regions. Moreover, we further find that disregarding the ΔE0 leads to an overestimation of annual ER by 10~80% globally. Thus, our study highlights that the divergent temperature dependencies between day- and nighttime ER should be incorporated into Earth system models to improve predictions of carbon–climate change feedback under future warming scenarios. [ABSTRACT FROM AUTHOR]

Coastal wetlands are one of the most productive ecosystems on Earth with the capacity to sequester large amounts of carbon dioxide (CO2). Wetland loss due to anthropogenic and natural causes reduces the carbon (C) storage capacity and potentially releases previously fixed C in biomass and soil to the water column and atmosphere through decomposition. Coastal wetland restoration has the potential to mitigate some of the C losses depending on the balance of C fluxes. However, the role of vegetation and environmental conditions in governing rates of C accumulation in restoration sites is not well resolved. The purpose of this study was to examine seasonal C fluxes, specifically, gross ecosystem productivity (GEP), ecosystem respiration (ER), and net ecosystem exchange (NEE) of CO2 in unvegetated and vegetated (Spartina alterniflora) areas of a 2‐year old created marsh, and S. alterniflora and Spartina patens communities in a "natural" reference brackish marsh. S. alterniflora‐dominated areas were sinks for CO2 in both the newly created and reference marsh with an average CO2 uptake rate of 7.0 ± 1.0 μmol m−2 s−1. The unvegetated areas in the newly created marsh and S. patens areas in the reference marsh had approximately net neutral CO2 fluxes. S. alterniflora areas of the created marsh had similar carbon fluxes to that in the reference marsh, despite a much lower soil organic matter content. Because vegetation develops much faster than soil properties, restored marshes can be a C sink equivalent to natural marshes as soon as the marsh is vegetated. Ecosystem productivity and C assimilation in S. alterniflora areas of the reference marsh were enhanced by lower elevations (up to 6 cm) and higher soil bulk density (up to 0.28 g cm−3). At similar elevations, S. alterniflora in both the created and reference marshes was a greater C sink than S. patens areas of the reference marsh. Our findings illustrate that establishment of vegetation is critical to promoting C sink functions in created marshes and, notably, species do matter. [ABSTRACT FROM AUTHOR]

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]

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]

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]

The permafrost region has accumulated organic carbon in cold and waterlogged soils over thousands of years and now contains three times as much carbon as the atmosphere. Global warming is degrading permafrost with the potential to accelerate climate change as increased microbial decomposition releases soil carbon as greenhouse gases. A 19-year time series of soil and ecosystem respiration radiocarbon from Alaska provides long-term insight into changing permafrost soil carbon dynamics in a warmer world. Nine per cent of ecosystem respiration and 23% of soil respiration observations had radiocarbon values more than 50‰ lower than the atmospheric value. Furthermore, the overall trend of ecosystem and soil respiration radiocarbon values through time decreased more than atmospheric radiocarbon values did, indicating that old carbon degradation was enhanced. Boosted regression tree analyses showed that temperature and moisture environmental variables had the largest relative influence on lower radiocarbon values. This suggested that old carbon degradation was controlled by warming/permafrost thaw and soil drying together, as waterlogged soil conditions could protect soil carbon from microbial decomposition even when thawed. Overall, changing conditions increasingly favoured the release of old carbon, which is a definitive fingerprint of an accelerating feedback to climate change as a consequence of warming and permafrost destabilization. This article is part of the Theo Murphy meeting issue 'Radiocarbon in the Anthropocene'.

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]

Abstract Coastal wetlands are one of the most productive ecosystems on Earth with the capacity to sequester large amounts of carbon dioxide (CO2). Wetland loss due to anthropogenic and natural causes reduces the carbon (C) storage capacity and potentially releases previously fixed C in biomass and soil to the water column and atmosphere through decomposition. Coastal wetland restoration has the potential to mitigate some of the C losses depending on the balance of C fluxes. However, the role of vegetation and environmental conditions in governing rates of C accumulation in restoration sites is not well resolved. The purpose of this study was to examine seasonal C fluxes, specifically, gross ecosystem productivity (GEP), ecosystem respiration (ER), and net ecosystem exchange (NEE) of CO2 in unvegetated and vegetated (Spartina alterniflora) areas of a 2‐year old created marsh, and S. alterniflora and Spartina patens communities in a “natural” reference brackish marsh. S. alterniflora‐dominated areas were sinks for CO2 in both the newly created and reference marsh with an average CO2 uptake rate of 7.0 ± 1.0 μmol m−2 s−1. The unvegetated areas in the newly created marsh and S. patens areas in the reference marsh had approximately net neutral CO2 fluxes. S. alterniflora areas of the created marsh had similar carbon fluxes to that in the reference marsh, despite a much lower soil organic matter content. Because vegetation develops much faster than soil properties, restored marshes can be a C sink equivalent to natural marshes as soon as the marsh is vegetated. Ecosystem productivity and C assimilation in S. alterniflora areas of the reference marsh were enhanced by lower elevations (up to 6 cm) and higher soil bulk density (up to 0.28 g cm−3). At similar elevations, S. alterniflora in both the created and reference marshes was a greater C sink than S. patens areas of the reference marsh. Our findings illustrate that establishment of vegetation is critical to promoting C sink functions in created marshes and, notably, species do matter.

Nitrogen (N) and phosphorus (P) are key limiting factors for carbon (C) fluxes in artificial grasslands. The impact of their management on ecosystem C fluxes, including net ecosystem productivity (NEP), ecosystem respiration (ER), and gross ecosystem productivity (GEP) in the Loess Plateau is unclear. An experiment was conducted to study changes in these C fluxes with varying N (0, 5, 10, 15, and 20 g N m−2) and P (0 and 10 g P m−2) additions from 2022 to 2023 in a lucerne plantation. Results showed that N addition positively influenced NEP and GEP in the first year after planting with N addition at the rate of 10 g N m−2 was optimal for C assimilation, but it had negligible effect on ER in both two years in the studied lucerne (Medicago sativa ssp. sativa) plantation. Phosphorus addition significantly increased ER and stimulated GEP, resulting in an increasing effect on NEP only at the early stage after planting. The addition of N and P enhanced soil N and P availability and further improved the leaf chemical stoichiometry characteristics, leading to changes in biomass distribution. The more belowground biomass under N addition and more aboveground production under P addition resulted in different responses of ecosystem C fluxes to N and P addition. The results suggest that the effects of N and P fertilization management on the ecosystem C cycle may be largely dependent on the distribution of above- and belowground plant biomass in the artificial grassland ecosystem.

Global warming is expected to intensify carbon loss, as ecosystem respiration (RECO) rates increase exponentially with rising temperatures. However, a comprehensive analysis of the response of the apparent temperature sensitivity of RECO ( ${Q_{10}}$ ) to rising temperature is lacking. This study leverages observational data from 254 sites from the FLUXNET2015 and AmeriFlux datasets to address this knowledge gap. We found a strong influence of non-temperature factors on the seasonality of RECO. The similar seasonality of this effect and temperature can lead to underestimating or overestimating ${Q_{10}}$ . In this study, ${Q_{10}}$ was quantified using a temporal moving window and a linear-mixed effect model to account for the effects of non-temperature factors on RECO. Our results show that ${Q_{10}}$ decreases from 1.55 ± 0.24 (mean ± one standard error) at 5 °C to 1.35 ± 0.18 at 25 °C over all sites. The mean slope of ${Q_{10}}$ to temperature across all sites is about −0.02 °C ^−1 . In this study, we found lower values of Q _10 and a lower decreasing rate of Q _10 with rising temperature compared to previous studies. Our study suggests that ${Q_{10}}$ might be systematically overestimated due to the confounding effect of non-temperature factors, potentially leading to overestimated simulation of RECO rate. Our study also emphasizes the necessity of developing a process-based model, rather than simply incorporating the influences of non-temperature factors into ${Q_{10}}$ .

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.

Understanding the sensitivity of ecosystem respiration (ER) to increasing temperature is crucial to predict how the terrestrial carbon sink responds to a warming climate. The temperature sensitivity of ER may vary on a diurnal basis but is poorly understood due to the paucity of observational sites documenting real ER during daytime at a global scale. Here, we used an improved flux partitioning approach to estimate the apparent temperature sensitivity of ER during the daytime (E0,day) and nighttime (E0,night) derived from multiyear observations of 189 FLUXNET sites. Our results demonstrated that E0,night is significantly higher than E0,day across all biomes, with significant seasonal variations in the day–night discrepancy in the temperature sensitivity of ER (ΔE0 = E0,night/E0,day) except for evergreen broadleaf forest and savannas. Such seasonal variations in ΔE0 mainly result from the effect of temperature and the seasonal amplitude of NDVI. We predict that future warming will decrease ΔE0 due to the reduced E0,night by the end of the century in most regions. Moreover, we further find that disregarding the ΔE0 leads to an overestimation of annual ER by 10~80% globally. Thus, our study highlights that the divergent temperature dependencies between day- and nighttime ER should be incorporated into Earth system models to improve predictions of carbon–climate change feedback under future warming scenarios.

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.

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]

Due to the urge to reduce greenhouse gas emissions in agricultural systems, studies are being conducted in the fields of the Pampa biome to understand the dynamics of carbon exchanges and propose mitigation measures. In this study, a model was calibrated to estimate the net ecosystem exchange (NEE) of CO2 in the native fields of the Pampa biome used for livestock, based on classical equations of ecosystem respiration and carbon assimilation through photosynthesis. For this purpose, NEE data obtained using the Eddy Covariance (EC) technique from a native field at the Santa Maria site in the years 2015 and 2016 were used to obtain the parameters utilized in the model. The parameters were obtained for each season, and the model was evaluated for the years 2019 and 2020 for both the Santa Maria site and the Aceguá site, located about 300 km from Santa Maria. The results showed that the model was able to estimate the NEE for the Santa Maria site with an average R² = 0.80 and RMSE 0.08 g C m-2 30 min-1, and for the Aceguá site with R² = 0.75 and RMSE 0.10 g C m-2 30 min-1. However, the model showed higher R² and higher RMSE during the summer and spring periods and lower values in winter and autumn at both sites. This model can be used to estimate the NEE of CO2 in the native fields of the Pampa biome as a basis for predicting CO2 absorption/emission across different seasons. [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]

Earlier snowmelt and more frequent summer drought due to climate warming are considered particularly influential for extratropical alpine plants, which are adapted to a short growing season and high water availability.Here, we explored the combined effects of the two drivers with a field experiment in late‐successional alpine grassland in the Swiss Alps (2500 m a.s.l.) over 6–7 years. We advanced and delayed snowmelt by removing and adding snow to experimental plots prior to natural snowmelt for 7 years and combined this treatment with 5 and 10 weeks of summer drought for 6 years. We measured plant biomass formation, community composition and ecosystem respiration, and monitored soil moisture as well as soil temperature.Natural snowmelt dates varied by 42 days across years. Snow manipulations advanced and delayed snowmelt by 4.6 and 8.0 days on average but did not affect annual growth (peak biomass) above‐ nor below‐ground. Interactions between snowmelt and drought were nonsignificant, implying that drought effects were independent of snowmelt.Drought reduced total annual above‐ground biomass in the 10‐week treatment by 16 ± 7% across years, while the 5‐week treatment lowered biomass in the last year only. This decline in biomass was accountable to high drought sensitivity of biomass production in a few forb and graminoid species. In contrast, drought did not affect the biomass production of the dominant sedge Carex curvula, whose proportion of total plant cover increased from 36% in controls to 48% in 10‐week drought.Below‐ground biomass slightly increased under drought (5‐week treatment only), resulting in a higher root mass fraction (both treatments). Despite continued root formation, drought reduced ecosystem respiration by 13%–23% per season, assessed nine times during three growing seasons. Since more than 85% of ecosystem respiration stemmed from below‐ground activities and roots continued growing under drought, we assume that soil microorganisms were heavily constrained by the drought treatments.Synthesis. We conclude that snowmelt timing is unrelated to productivity, while recurrent drought will shift biomass allocation from shoots to roots in this typical alpine grassland, with potential implications for grazers but also for nutrient and carbon cycling. Species‐specific drought‐sensitivity will considerably alter community composition under more frequent drought. [ABSTRACT FROM AUTHOR]

Question: What is the effect of long‐term grazing and no grazing (NG) on carbon dioxide flux and soil carbon storage in Icelandic semi‐natural grasslands. Location: Three farms, with known history of land use, in W Iceland. Methods: On each farm, we located an intensively and an extensively grazed site, which both had been constantly grazed for centuries, and a parallel site with no grazing for over 50 years. We measured net ecosystem exchange (NEE), ecosystem respiration and normalized difference vegetation index on a regular basis over the growing season. Samples were taken from 60 cm deep soil profiles for analysis of soil organic carbon (SOC). Results: The grazed sites showed significantly more negative NEE than the NG sites, indicating more carbon dioxide uptake on the grazed sites compared to the NG sites. The normalized difference vegetation index was also significantly higher on the grazed sites. On all farms, the total SOC content was higher in the grazed sites than in the parallel NG sites. Conclusions: The study indicates that cessation of grazing decreases productivity and carbon dioxide uptake in a semi‐natural grassland in Iceland, as well as SOC content in the soil. Historically, all the NG sites in the study had the same grazing history as the continuously grazed sites until grazing exclusion. The measured lower SOC on the NG sites seems to indicate that, without grazing, SOC is lost with time and/or grazing is needed to maintain SOC in these grasslands. [ABSTRACT FROM AUTHOR]

Greenhouse gases (GHGs) emissions from high-cold terrestrial ecosystems underlain by permafrost on the Qinghai–Tibet Plateau (QTP) have received widespread attention. However, the dominant factors regulating ecosystem respiration (Re) and its components (soil respiration Rs and heterotrophic respiration Rh) and how the differences in carbon emissions from different ecotypes and seasons remain are still unclear. We conducted a 2-year field investigation (August 2018 to October 2020) and applied the structural equation model (SEM) to clarify the changes in the factors controlling the respiration components during different seasons. The results indicate that the Re and its controlling factors in three alpine grassland ecosystems (alpine steppe, alpine meadow, and swamp meadow) vary with seasons. Furthermore, autotrophic respiration (Ra) contributes the most to the seasonal changes in Re. The Re gradually increases in the early growing season and rapidly decreases in the late growing season. Rh remains relatively stable during the year. Under these seasonal variations in the respiration components, the dominant factors controlling Re in the nongrowing season are the temperature of the atmosphere–soil interface (heat flux, atmospheric temperature, and soil temperature at 5 cm depth) and microbial activity (microbial carbon and pH) with the variable importance projections >1.5. During the growing season, the dominant factors regulating Re, Rs, and Rh are the soil temperature with a standardized direct effect (SDE) of 0.424, soil nutrient conditions (total nitrogen and pH) with SDEs of 0.570–0.614, and microbial activity (microbial carbon) with a SDE of 0.591, respectively. In addition, meteorological conditions have an important impact on the respiration components during the growing season. Specifically, the atmospheric vapor pressure is the dominant factor regulating the three respiration components (standardized total effects = 0.44−0.53, p

Interannual variation in net ecosystem carbon production (NEP) plays an important role in the carbon cycle processes. An agricultural ecosystem may fluctuate between carbon net source and carbon sink, or it may remain neutral. Thus, the long-term trends in NEP and the relevant meteorological, soil and biotic control of interannual variation in NEP remain unclear in farmland agroecosystems. To effectively assess the carbon sequestration potential of the farmland ecosystem, the eddy covariance dataset of rain-fed spring maize in Northeast China from 2005 to 2020 are used to investigate the interannual variations in NEP and the relevant meteorological, soil and biotic influences. NEP is partitioned into gross ecosystem productivity (GEP) and ecosystem respiration (RE) to explain the interannual variations of NEP and its influencing factors. The average annual NEP, GEP and RE are 272±109, 1086±177, 820±130 g·m-2·a-1, respectively, with no significant changes. The day-to-day dynamics of NEP, GEP and RE show single peak curves. NEP and GEP reach the maximums at the very time of maize tasseling, and the maximum value of RE occurs 13 days after NEP and GEP. Compared with RE, NEP variations are mainly caused by GEP. The redundancy analysis shows the interannual variations in NEP are mainly affected by precipitation as the meteorological factor and water use efficiency as the biotic factor, and the influence weights of the meteorological and biotic factors are 28.4% and 31.4%. Meanwhile, the influence weights of the meteorological factors (photosynthetically active radiation, carbon dioxide and precipitation), soil (soil volumetric water content and soil organic carbon) and biotic factors (leaf area index and water use efficiency) are 61.0%, 43.8% and 62.8% for the interannual variations in GEP. The interannual variations in RE are mainly affected by the soil (soil volumetric water content and soil organic carbon) and the biotic factors (leaf area index), and the influence weight of the soil factors (39.3%) is larger than that of the biotic factor (29.2%). The results indicate that, under the background of climate warming, interannual variations in NEP in rain-fed spring maize agroecosystems are likely to be more sensitive to changes in moisture, while radiation and temperature will contribute to interannual NEP variations by affecting vapor pressure difference and soil water content.

The Tibet Plateau, with its extensive carbon pools, plays a pivotal role in the global carbon budget. Nevertheless, the driving factors of the carbon dioxide budget remain disputed, and the impact of freeze–thaw process on carbon release is still unclear due to the harsh climate and lack of monitoring data. To clarify the primary factors affecting the alpine meadow ecosystems and to examine the impact of freeze–thaw on carbon release, we employed the LI-8150 automated continuous measurement system. This system, in conjunction with eddy covariance meteorological data, The Boosted Regression Tree (BRT) model, and multiple stepwise regression analysis, were used to analyze the seasonal variations in carbon flux (e.g., net ecosystem carbon exchange [NEE], gross primary productivity [GPP], and ecosystem respiration [Reco]). We also investigate the carbon sources and sinks in the alpine meadow ecosystem, as well as the predominant factor of carbon flux. Our findings include: (1) the carbon sources and sinks in the alpine meadow ecosystem shift seasonally on monthly and daily scales. On a monthly scale, the ecosystem functions as a moderate carbon sink in June, July, August, and September and as a weak carbon source from October through May. (2) Overall, the alpine meadow ecosystem, located in the northeastern Qinghai Lake basin, serves as a weak carbon sink (-58.53 g C m−2 year−1). (3) Soil temperature is the primary factor driving most variations observed in NEE, Reco, and GPP, contributing 48.05 %, 78.61 %, and 65.05 %, respectively. Soil temperature, soil water dynamics influenced by freeze and thaw processes, and their interaction with plant growth collectively play a crucial role in regulating the carbon sources and sinks in ecosystems. We provide first-hand observational data for monitoring the carbon sources and sinks in the alpine meadow ecosystem of the Tibet Plateau, as well as offer future guidance for studying the carbon budget of the Tibet Plateau.

This article is a Commentary on Marshall et al. (2023), 239: 2166–2179. [ABSTRACT FROM AUTHOR]

Drought timing determines the degree to which dry events impact ecosystems, with the ability of key processes to withstand change differing between drought periods. Findings indicate that drought timing effects vary across ecosystems, with few studies focusing on alpine grasslands. We conducted a mesocosm experiment using small grassland monoliths collected in September from the high Alps and left to overwinter at 0 °C until the experiment began in lowland Italy under late-winter outdoor conditions. Together with watered controls, we imposed three different drought treatments (zero precipitation): (1) one-month early-drought immediately after simulated snowmelt; (2) one-month mid-drought a month after melt-out; and (3) continuous two-month drought across the entire experimental period. Ecosystem responses were assessed by measuring CO2 fluxes, while vegetation responses were investigated by measuring aboveground net primary production (ANPP) of graminoids and forbs and post-harvest resprouting after one-month rehydration. We found that ecosystem respiration and gross ecosystem production (GEP) during the day were more negatively affected by mid-season drought compared to drought starting early in the season. By the end of treatments, GEP reduction under mid-season drought was similar to that of a continuous two-month drought. ANPP reduction was similar in early- and mid-drought treatments, showing a greater decrease under an enforced two-month period without precipitation. Plant resprouting, however, was only reduced in full- and mid-season drought pots, with forbs more negatively affected than graminoids. Seasonal soil moisture variation can account for these patterns: remaining winter moisture allowed almost full canopy development during the first month of the season, despite precipitation being withheld, while soil moisture depletion in the second month, resulting from higher temperatures and greater biomass, caused a collapse of gas exchange and diminished plant resprouting. Our data illustrates the importance of the timing of zero-precipitation periods for both plant and ecosystem responses in alpine grasslands. [ABSTRACT FROM AUTHOR]

There is increasing interest in utilizing the high carbon sequestration capacity of wetlands as a rationale for their restoration, but this requires careful assessment of their greenhouse gas (GHG) fluxes. We used a spatially extensive sampling approach across salinity gradients and management regimes (disturbed, restored, and reference) in 22 wetland sites across two Oregon, USA estuaries, Tillamook and Coos Bays, to measure fluxes of methane (CH4), ecosystem respiration as carbon dioxide (CO2), and nitrous oxide (N2O) over 1 year and related them to environmental forcing variables. Boosted regression tree (BRT) models explained drivers of GHG fluxes reasonably well despite highly nonlinear and interactive relationships and many flux measurements below detection. We used the BRT models to predict annual GHG fluxes in a subset of restored and reference sites where continuous environmental data were recorded and compared them to previously published soil carbon sequestration rates. Most sites had net removal of CO2-equivalents from the atmosphere over both 20 and 100 year timeframes. Our results show that a spatially extensive GHG flux sampling scheme and machine-learning statistical techniques can be used to estimate GHG fluxes in other current and former wetlands within the region if environmental data are collected at a spatial resolution that reflects site variability and at sufficient duration to reflect seasonality (i.e., at least one full year). Such an approach can save time and money in determining the feasibility of wetland restoration as a climate mitigation strategy. We use our results to suggest wetland restoration strategies that optimize climate benefits. [ABSTRACT FROM AUTHOR]

Upscaling chamber measurements of soil greenhouse gas (GHG) fluxes from points to landscape scales remain challenging due to high variability of fluxes in space and time. This study measured GHG fluxes and soil parameters at selected point locations (n=268), thereby implementing a stratified sampling approach on a mixed land-use landscape (~5.8 km2). Based on these field-based measurements and remotely-sensed data on landscape and vegetation properties, we used Random Forest models to predict GHG fluxes at a landscape scale (1 m resolution) in summer and autumn. The results showed improved GHG flux prediction performance when combining field25 measured soil parameters with remotely-sensed data. Available satellite data products from Sentinel-2 on vegetation cover and water content played a more significant role than attributes derived from a digital elevation model, possibly due to their ability to capture both spatial and seasonal changes of ecosystem parameters within the landscape. Similar seasonal patterns of higher soil/ecosystem respiration (SR/ER-CO2) and nitrous oxide (N2O) fluxes in summer and higher methane (CH4) uptake in autumn were observed in both the measured and predicted landscape fluxes. Based on the upscaled fluxes, we also assessed the contribution of hot spots to total landscape fluxes. The identified emission hot spots occupied a small landscape area (7 to 16%) but accounted for up to 42% of the landscape GHG fluxes. Our study showed that combining remotely-sensed data with chamber measurements and soil properties is a promising approach for identifying spatial patterns and hot spots of GHG fluxes across heterogeneous landscapes. Such information may be used to inform targeted mitigation strategies at landscape-scale. [ABSTRACT FROM AUTHOR]

Peatland ecosystems are a highly effective long-term carbon sink. However, the CO2 fluxes could be substantially altered by climate changes and the fate of carbon stored in these ecosystems is still uncertain. Currently, most studies concerning the carbon fluxes in peatlands were performed at high latitude sites, where these ecosystems are more widely distributed compared to temperate regions, where peatlands are less frequent and, in addition to climate pressure, increasingly threatened by human activities. However, the information we have on these peatlands is very scarce. To fill this knowledge gap, we studied CO2 fluxes in an alpine peatland, through light and dark incubations. Using the natural variation in ecological conditions, we identified the main drivers of CO2 fluxes, considering in particular their interactions and covariation. Ecosystem respiration and gross primary production were primarily stimulated by the lowering of the water table and the amount of photosynthetic radiation, respectively, whereas net ecosystem CO2 exchange showed greater variation along the growing season. The influence on CO2 fluxes of the interactions between the drivers investigated, including soil temperature and moisture as well as vegetation type and plant functional diversity, was found to be of pivotal importance. Finally, a substantial part of the variation in CO2 emission and uptake processes was regulated by the joint variation of atmospheric and edaphic factors. To understand and predict the CO2 dynamics of alpine peatlands, it is necessary to consider the interplays among ecological factors, especially in relation to the expected changes in climate and vegetation. [ABSTRACT FROM AUTHOR]