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Aims Climate change (extreme rainfall) and water management activities have led to variation in hydrological regimes, especially inundation, which may alter the function and structure of wetlands as well as wetland-atmosphere carbon (C) exchange. However, the degree to which different inundation depths (standing water depth above the soil surface) affect ecosystem CH 4 fluxes, ecosystem respiration (R eco ) and net ecosystem CO 2 exchange (NEE) remains uncertain in wetland ecosystems. Methods We conducted a field inundation depth manipulation experiment (no inundation, i.e. only natural precipitation; 0, water-saturated; 5, 10, 20, 30 and 40 cm inundation depth) in a freshwater wetland of the Yellow River Delta, China. The CH 4 fluxes, R eco and NEE were measured with a static chamber technique during the growing seasons (May–October) of 2018 and 2019. Results Inundation depth significantly increased plant shoot density, above-water level leaf area index (WLAI), above-water level plant shoot height (WHeight), aboveground and belowground biomass of the dominant grass Phragmites australis in both years. Meanwhile, inundation depth increased the CH 4 fluxes, R eco (except for 0 cm) and NEE compared to no inundation, which could be attributed partly to the increased plant productivity (shoot density, WLAI, WHeight, biomass). Additionally, the CH 4 fluxes, R eco or NEE exhibited parabolic responses to inundation depth. Furthermore, global warming potential (GWP) was significantly decreased under different inundation depths during the growing season, especially from 5 to 40 cm inundation depth in 2019. NEE was the largest contributor to the seasonal GWP, which indicates that the inundated wetlands are a net sink of C and have a cooling climate effect in the Yellow River Delta. Conclusions Inundation depth substantially affects the magnitude of CH 4 fluxes, R eco and NEE, which were correlated with altered plant traits in wetland ecosystems. Inundation depth could mitigate greenhouse gas emissions in the P. australis wetlands during the growing season. Inundation depth-induced ecosystem C exchange should be considered when estimating C sequestration capacity of wetlands due to climate change and water management activities, which will assist to accurately predict the impact of hydrological regimes on C cycles in future climate change scenarios.

During the last decade, advances in the remote sensing of greenhouse gas (GHG) concentrations by the Greenhouse Gases Observing SATellite-1 (GOSAT-1), GOSAT-2, and Orbiting Carbon Observatory-2 (OCO-2) have produced finer-resolution atmospheric carbon dioxide (CO2) datasets. These data are applicable for a top-down approach towards the verification of anthropogenic CO2 emissions from megacities and updating of the inventory. However, great uncertainties regarding natural CO2 flux estimates remain when back-casting CO2 emissions from concentration data, making accurate disaggregation of urban CO2 sources difficult. For this study, we used Moderate Resolution Imaging Spectroradiometer (MODIS) land products, meso-scale meteorological data, SoilGrids250 m soil profile data, and sub-daily soil moisture datasets to calculate hourly photosynthetic CO2 uptake and biogenic CO2 emissions with 500 m resolution for the Kantō Plain, Japan, at the center of which is the Tokyo metropolis. Our hourly integrated modeling results obtained for the period 2010–2018 suggest that, collectively, the vegetated land within the Greater Tokyo Area served as a daytime carbon sink year-round, where the hourly integrated net atmospheric CO2 removal was up to 14.15 ± 4.24% of hourly integrated anthropogenic emissions in winter and up to 55.42 ± 10.39% in summer. At night, plants and soil in the Greater Tokyo Area were natural carbon sources, with hourly integrated biogenic CO2 emissions equivalent to 2.27 ± 0.11%–4.97 ± 1.17% of the anthropogenic emissions in winter and 13.71 ± 2.44%–23.62 ± 3.13% in summer. Between January and July, the hourly integrated biogenic CO2 emissions of the Greater Tokyo Area increased sixfold, whereas the amplitude of the midday hourly integrated photosynthetic CO2 uptake was enhanced by nearly five times and could offset up to 79.04 ± 12.31% of the hourly integrated anthropogenic CO2 emissions in summer. The gridded hourly photosynthetic CO2 uptake and biogenic respiration estimates not only provide reference data for the estimation of total natural CO2 removal in our study area, but also supply prior input values for the disaggregation of anthropogenic CO2 emissions and biogenic CO2 fluxes when applying top-down approaches to update the megacity’s CO2 emissions inventory. The latter contribution allows unprecedented amounts of GOSAT and ground measurement data regarding CO2 concentration to be analyzed in inverse modeling of anthropogenic CO2 emissions from Tokyo and the Kantō Plain.

Added Na was used to determine whether litter decomposition and associated fungal biomass and termites are limited by Na availability in a lowland tropical rainforest at Yasuni, Ecuador. This is a partial test of the \"sodium ecosystem respiration\" (SER) hypothesis that posits Na is critical for consumers but not plants, that Na shortfall is more likely on highly weathered soils inland from oceanic aerosols, and that this shortfall results in decreased decomposer activity. We fertilized 4 × 4 m plots twice a month for a year with quantities of Na comparable to those falling on a coastal tropical rainforest. Decomposition rates of four substrates were consistently higher on +NaCl plots by up to 70% for cellulose, and 78%, 68%, and 29% for three woods of increasing percentage lignin. The density of termite workers averaged 17-fold higher on +NaCl plots; fungal biomass failed to differ. After controlling for temperature and precipitation, which co-limit gross primay productivity (GPP) and ecosystem respiration (ER), these results suggest that Na shortfall is an agent enhancing the storage of coarse woody debris in inland tropical forests.

Sandy cropland ecosystems are major terrestrial ecosystems in semi-arid regions of northern China’s Horqin Sandy Land, where they play an important role in the regional carbon balance. Continuous observation of the CO 2 flux was conducted from 2014 to 2018 using the eddy covariance technique in a sandy maize cropland ecosystem in the Horqin Sandy Land. We analyzed carbon fluxes (the net ecosystem exchange ( NEE ) of CO 2 , ecosystem respiration ( R eco ), and the gross primary productivity ( GPP ) and their responses to environmental factors at different temporal scales using Random Forest models and correlation analysis. We found that the sandy cropland was a carbon sink, with an annual mean NEE of –124.4 g C m −2 yr −1 . However, after accounting for carbon exports and imports, the cropland became a net carbon source, with net biome production ranging from –501.1 to –266.7 g C m −2 yr −1 . At a daily scale, the Random Forest algorithm revealed that photosynthetic photon flux density, soil temperature, and soil moisture were the main drivers for variation of GPP , R eco , and NEE at different integration periods. At a monthly scale, GPP and R eco increased with increasing leaf area index ( LAI ), so the maize ecosystem’s carbon sequestration capacity increased with increasing LAI . At an annual scale, water availability (precipitation and irrigation) played a dominant role in explaining inter-annual variability of GPP and R eco . Affected by climate (e.g., precipitation) and field management (e.g., cultivation, irrigation), carbon fluxes differed greatly between years in the maize system.

Ecosystem metabolism is an important determinant of trophic structure, nutrient cycling, and other critical ecosystem processes in streams. Whereas watershed- and local-scale controls on stream metabolism have been independently investigated, little is known about how controls exerted at different scales interact to determine stream metabolic rates, particularly in urban streams and across seasons. To address this knowledge gap, we measured ecosystem metabolism in four urban and four reference streams in northern Kentucky, USA, with paired closed and open riparian canopies, during each of the four seasons. Gross primary production (GPP), ecosystem respiration, and net ecosystem production (NEP) were all best predicted by models with season as a main effect, but interactions between season, canopy, and watershed varied for each response. Urban streams exhibited higher GPP during most seasons, likely due to elevated nutrient loads. Open canopy reaches in both urban and forested streams, supported higher rates of GPP than the closed canopy which reaches during the summer and fall, when the overhead vegetation shaded the closed reaches. The effect of canopy cover on GPP was similar among urban and forested streams. The combination of watershed and local-scale controls resulted in urban streams that alternated between net heterotrophy (NEP < 0) and net autotrophy (NEP > 0) at the reach-scale during seasons with dense canopy cover. This finding has management relevance because net production can lead to accumulation of algal biomass and associated issues like nighttime hypoxia. Our study suggests that although watershed urbanization fundamentally alters ecosystem function, the preservation and restoration of canopied riparian zones can provide an important management tool at the local scale, with the strongest impacts on stream metabolism during summer.

Peatlands play an important role in the global carbon cycle as they contain a large soil carbon stock. However, current climate change could potentially shift peatlands from being carbon sinks to carbon sources. Remote sensing methods provide an opportunity to monitor carbon dioxide (CO2) exchange in peatland ecosystems at large scales under these changing conditions. In this study, we developed empirical models of the CO2 balance (net ecosystem exchange, NEE), gross primary production (GPP), and ecosystem respiration (ER) that could be used for upscaling CO2 fluxes with remotely sensed data. Two to three years of eddy covariance (EC) data from five peatlands in Sweden and Finland were compared to modelled NEE, GPP and ER based on vegetation indices from 10 m resolution Sentinel-2 MSI and land surface temperature from 1 km resolution MODIS data. To ensure a precise match between the EC data and the Sentinel-2 observations, a footprint model was applied to derive footprint-weighted daily means of the vegetation indices. Average model parameters for all sites were acquired with a leave-one-out-cross-validation procedure. Both the GPP and the ER models gave high agreement with the EC-derived fluxes (R2 = 0.70 and 0.56, NRMSE = 14% and 15%, respectively). The performance of the NEE model was weaker (average R2 = 0.36 and NRMSE = 13%). Our findings demonstrate that using optical and thermal satellite sensor data is a feasible method for upscaling the GPP and ER of northern boreal peatlands, although further studies are needed to investigate the sources of the unexplained spatial and temporal variation of the CO2 fluxes.

Global carbon fluxes describe the carbon exchange between land and atmosphere. However, already available global carbon fluxes datasets have not been adjusted by the available site data and deep learning tools. In this work, a global carbon fluxes dataset (named as GCFD) of gross primary productivity (GPP), terrestrial ecosystem respiration (RECO), and net ecosystem exchange (NEE) has been developed via a deep learning based convolutional neural network (CNN) model. The dataset has a spatial resolution of 1 km at three time steps per month from January 1999 to June 2020. Flux measurements were used as a training target while remote sensing of vegetation conditions and meteorological data were used as predictors. The results showed that CNN could outperform other commonly used machine learning methods such as random forest (RF) and artificial neural network (ANN) by leading to satisfactory performance with R2 values of the validation stage as 0.82, 0.72 and 0.62 for GPP, RECO, and NEE modelling, respectively. Thus, CNN trained using reanalysis meteorological data and remote sensing data was chosen to produce the global dataset. GCFD showed higher accuracy and more spatial details than some other global carbon flux datasets with reasonable spatial pattern and temporal variation. GCFD is also in accordance with vegetation conditions detected by remote sensing. Owing to the obtained results, GCFD can be a useful reference for various meteorological and ecological analyses and modelling, especially when high resolution carbon flux maps are required.

Restoration of riparian vegetation is widely recognized as a tool in stream rehabilitation, but information on whether local riparian characteristics can mitigate the effects of catchment-level stressors on in-stream processes is limited. We measured community metabolism in 21 streams in the Canterbury region of New Zealand along 2 independent gradients of agricultural intensity and riparian cover (from closed canopied to open canopied) to assess relative effects of landscape and local factors on stream trophic state. We measured stream metabolism with the single-station open-channel diel O2 method. We found a correlation between gross primary production (GPP) and ecosystem respiration (ER), indicating a gradient of trophic states across sites. Streams were strongly heterotrophic with P:R values varying from 0.01 to 0.25. GPP and ER increased with % agriculture and % macrophyte cover, but decreased with % shade from riparian vegetation. Hierarchical partitioning analysis indicated that % agriculture was the only landuse variable to have a significant independent effect on GPP and ER. Among local variables, % shade and % macrophyte cover had significant independent effects on GPP. Percent shade was the only local variable to have a significant independent effect on ER. Percent shade had a stronger effect on both GPP and ER than did % agriculture, and a trade-off exists between the importance of agricultural and forest cover on stream metabolism at different spatial scales. Our results highlight the role of local riparian conditions in controlling trophic state and the importance of riparian buffers as a tool to mitigate eutrophication in streams and rivers.

Climate change projections predict an intensifying hydrologic cycle and an increasing frequency of droughts, yet quantitative understanding of the effects on ecosystem carbon exchange remains limited. Here, the effect of contrasting precipitation and soil moisture dynamics were evaluated on forest carbon exchange using 2 yr of eddy covariance and microclimate data from a 50-yr-old mixed oak woodland in northern Ohio, USA. The stand accumulated 40% less carbon in a year with drought between bud-break and full leaf expansion (354 ± 81 g C m⁻² yr⁻¹ in 2004 and 252 ± 45 g C m⁻² yr⁻¹ in 2005). This was caused by greater suppression of gross ecosystem productivity (GEP; 16% = 200 g) than of ecosystem respiration (ER; 11% = 100 g) by drought. Suppressed GEP was traced to lower leaf area, lower apparent quantum yield and lower canopy conductance. The moisture sensitivity of ER may have been mediated by GEP. The results highlight the vulnerability of the ecosystem to even a moderate drought, when it affects a critical aspect of development. Although the drought was preceded by rain, the storage capacity of the soil seemed limited to 1-2 wk, and therefore droughts longer than this are likely to impair productivity in the region.

Management, environment, and agroecosystem type are key factors influencing photosynthetic carbon (C) uptake and C use efficiency (CUE), calculated as the ratio of net ecosystem production to gross ecosystem production (NEP:GEP). Current literature has mainly emphasized annual C balance in studies involving multiple years with continuous monitoring of ecosystem C fluxes, yet CUE has not been thoroughly analyzed during the growing season, particularly in paired comparisons of contrasting types of pasture under semiarid conditions. From 2009 through 2013, we used eddy covariance method to determine daily, seasonal, and annual C budgets in rainfed alfalfa (Medicago sativa L.) and grass ecosystems subjected to periodic harvest (haying) near Mandan, North Dakota, USA. We found consistently higher magnitudes of C fluxes (ecosystem respiration [ER], NEP, GEP) and hay production in alfalfa than grassland. Leaf area and canopy nitrogen content per unit land area were key driving factors for daily, seasonal, and annual differences in C fluxes between agroecosystems. Net ecosystem C balance indicated C losses occurred through haying in both ecosystems, though no changes in soil C stocks were detected in either ecosystem over the course of the study. Mean NEP:GEP ratios (±standard error) during periods of steady carbon dioxide (CO2) uptake before and after haying were 0.43 ± 0.01 and 0.26 ± 0.03 for alfalfa and grassland, respectively, implying more efficient C use in the former. Moreover, alfalfa had consistently greater CUE than grassland despite variations in sunlight, temperature, and precipitation within and between growing seasons. Ratios of ER to GEP were also repeatedly lower in alfalfa than grassland in all five growing seasons. Under drought conditions, we infer alfalfa roots accessed water in the soil profile unavailable to more shallow‐rooted grass species. Overall, hayed alfalfa was more efficient and tolerant than grassland in assimilating and using atmospheric CO2 under variable intra‐ and inter‐seasonal conditions. Outcomes from this study suggest the inclusion of alfalfa in unirrigated crop rotations can sustain high CUE, C uptake, and hay production while mitigating C losses in a semiarid environment.