Search for: All records

ABSTRACT Cover crops, a promising strategy to increase soil organic carbon (SOC) storage in croplands and mitigate climate change, have typically been shown to benefit soil carbon (C) storage from increased plant C inputs. However, input‐driven C benefits may be augmented by the reduction of C outputs induced by cover crops, a process that has been tested by individual studies but has not yet been synthesized. Here we quantified the impact of cover crops on organic C loss via soil erosion (SOC erosion) and revealed the geographical variability at the global scale. We analyzed the field data from 152 paired control and cover crop treatments from 57 published studies worldwide using meta‐analysis and machine learning. The meta‐analysis results showed that cover crops widely reduced SOC erosion by an average of 68% on an annual basis, while they increased SOC stock by 14% (0–15 cm). The absolute SOC erosion reduction ranged from 0 to 18.0 Mg C⁻¹ ha⁻¹ year⁻¹and showed no correlation with the SOC stock change that varied from −8.07 to 22.6 Mg C⁻¹ ha⁻¹ year⁻¹at 0–15 cm depth, indicating the latter more likely related to plant C inputs. The magnitude of SOC erosion reduction was dominantly determined by topographic slope. The global map generated by machine learning showed the relative effectiveness of SOC erosion reduction mainly occurred in temperate regions, including central Europe, central‐east China, and Southern South America. Our results highlight that cover crop‐induced erosion reduction can augment SOC stock to provide additive C benefits, especially in sloping and temperate croplands, for mitigating climate change. 

Abstract The global forest carbon stocks represent the amount of carbon stored in woody vegetation and are important for quantifying the ability of the global forests to sequester atmospheric CO₂and to provide ecosystem services (e.g., timber) under climate change. The forest ecosystem carbon pool estimates are highly variable and poorly quantified in areas lacking forest inventory estimates. Here, we compare and analyze aboveground biomass (AGB) estimates from five satellite‐based global data sets and nine dynamic global vegetation models (DVGMs). We find that across the data sets, mean AGB exhibits the largest variability around the tropical area. In addition, AGB shows a similar latitudinal trend but large variability among the data sets. Satellite‐based AGB estimates are lower than those simulated by DVGMs. The divergence among the satellite‐based AGB estimates can be driven by the methodology, input satellite products, and the forested areas used to estimate AGB. The modeled NPP, autotrophic respiration, and carbon allocation mostly drive the variability of AGB simulated by DGVMs. The future availability of a high‐quality global forest area map is anticipated to improve AGB estimate accuracy and to reduce the discrepancies among different satellite‐ and model‐based AGB estimates. We suggest the carbon‐modeling community reexamine the methodology used to estimate AGB and forested areas for a more robust global forest carbon stock estimation. 

Abstract Spring and summer vegetation productivity in Siberia shows opposing responses to warmer spring. Spring warming causes excessive vegetation growth and earlier start of photosynthesis, enhancing productivity in spring. However, this leads to reduced productivity in the following season (i.e., summer) through soil moisture depletion. To understand how an exceptional spring heatwave (HW) affected ecosystem carbon uptake, we investigated the spatiotemporal cascade of gross primary production (GPP) and multiple climate variables over Siberia in 2020, using a satellite‐retrieved GPP product (GOSIF‐GPP) and the ERA5‐Land reanalysis data set for 2001–2020. Results showed a positive impact of anomalous spring warming on annual GPP (GPP_ann). GPP_annfrom GOSIF‐GPP in West Siberia (55°–70°N, 50°–90°E) was enhanced by up to 10% above the 2001–2019 average despite continued dry conditions from May to August. In East Siberia (55–70°N, 90–130°E), the GPP increases for May and June were sufficient to compensate for marked reduction of GPP in July due to negative anomaly in radiation. In addition, the higher sensitivity of GPP_annto spring temperature in West Siberia than in East Siberia suggests that GPP increase coupled with strong warming and respective excessive vegetation growth might be more pronounced in the western region, as observed in 2020. Our results indicate that the warming trend in spring, combined with possible extreme heat events, could elevate annual carbon uptake in Siberia, particularly in West Siberia. Further, this case study for the extreme HW event that occurred in 2020 can provide useful insight for understanding future change in carbon uptake over Siberia. 

Abstract There are twenty experimental forest and range sites (EFRs) across the southeastern United States that are currently maintained by the USDA Forest Service (Forest Service) to conduct forest ecosystem research for addressing ecosystem management challenges. The overall objective of this study was to use multiple gridded datasets to assess the extent to which the twenty EFRs represent the climate, ecosystem structure, and ecosystem functions of southeastern forests. The EFRs represent the large variability of climate conditions across the region relatively well, but we identified small representation gaps. The representativeness of ecosystem structure by these EFRs can be improved by establishing EFRs in forests with relatively low tree cover, leaf area index, or tree canopy height. The current EFRs also represent the forest ecosystem functions of the region relatively well, although areas with intermediate and low aboveground biomass and water yield are not well represented. The trends in climate, ecosystem structure, and ecosystem functions were generally consistent between the region and the EFRs. Our study indicates that the current EFRs represent the region relatively well, but establishing additional EFRs in specific areas within the region could help more completely assess how southeastern forests respond to climate change, disturbance, and management practices. Study Implications: This study across the experimental forests and ranges (EFRs) and the southeastern forest region fills the knowledge gap regarding climate, ecosystem structure, and ecosystem functions of EFRs in the context of the broader southeastern forest region. Understanding ecosystem functions and structures across the EFR network can help the Southern Research Station to address new research questions. Our study indicates that the current EFRs represent the climate, ecosystem structure, and ecosystem functions of southeastern forests well. However, establishing additional EFRs in certain regions could help more completely assess how southeastern forests respond to climate change, disturbance, and management practices. 

Abstract The timing and progression of the spring thaw transition in high northern latitudes (HNL) coincides with warmer temperatures and landscape thawing, promoting increased soil moisture and growing season onset of gross primary productivity (GPP), heterotrophic respiration (HR), and evapotranspiration (ET). However, the relative order and spatial pattern of these events is uncertain due to vast size and remoteness of the HNL. We utilized satellite environmental data records (EDRs) derived from complementary passive microwave and optical sensors to assess the progression of spring transition events across Alaska and Northern Canada from 2016 to 2020. Selected EDRs included land surface and soil freeze‐thaw status, solar‐induced chlorophyll fluorescence (SIF) signifying canopy photosynthesis, root zone soil moisture (RZSM), and GPP, HR, and ET as indicators of ecosystem carbon and water‐energy fluxes. The EDR spring transition maps showed thawing as a precursor to rising RZSM and growing season onset. Thaw timing was closely associated with ecosystem activation from winter dormancy, including seasonal increases in SIF, GPP, and ET. The HR onset occurred closer to soil thawing and prior to GPP activation, reducing spring carbon (CO₂) sink potential. The mean duration of the spring transition spanned ∼6 ± 1.5 weeks between initial and final onset events. Spring thaw timing and maximum RZSM were closely related to active layer thickness in HNL permafrost zones, with deeper active layers showing generally earlier thawing and greater RZSM. Our results confirm the utility of combined satellite EDRs for regional monitoring and better understanding of the complexity of the spring transition. 

Abstract Extreme climate events are becoming more frequent, with poorly understood implications for carbon sequestration by terrestrial ecosystems. A better understanding will critically depend on accurate and precise quantification of ecosystems responses to these events. Taking the 2019 US Midwest floods as a case study, we investigate current capabilities for tracking regional flux anomalies with “top‐down” inversion analyses that assimilate atmospheric CO₂observations. For this analysis, we develop a regionally nested version of the NASA Carbon Monitoring System‐Flux system for North America (CMS‐Flux‐NA) that allows high resolution atmospheric transport (0.5° × 0.625°). Relative to a 2018 baseline, we find the 2019 US Midwest growing season net carbon uptake is reduced by 11–57 TgC (3%–16%, range across assimilated CO₂data sets). These estimates are found to be consistent with independent “bottom‐up” estimates of carbon uptake based on vegetation remote sensing (15–78 TgC). We then investigate current limitations in tracking regional carbon budgets using “top‐down” methods. In a set of observing system simulation experiments, we show that the ability of atmospheric CO₂inversions to capture regional carbon flux anomalies is still limited by observational coverage gaps for both in situ and satellite observations. Future space‐based missions that allow for daily observational coverage across North America would largely mitigate these observational gaps, allowing for improved top‐down estimates of ecosystem responses to extreme climate events. 

Abstract Solar‐induced chlorophyll fluorescence (SIF) shows enormous promise as a proxy for photosynthesis and as a tool for modeling variability in gross primary productivity and net biosphere exchange (NBE). In this study, we explore the skill of SIF and other vegetation indicators in predicting variability in global atmospheric CO₂observations, and thus global variability in NBE. We do so using a 4‐year record of CO₂observations from NASA's Orbiting Carbon Observatory 2 satellite and using a geostatistical inverse model. We find that existing SIF products closely correlate with space‐time variability in atmospheric CO₂observations, particularly in the extratropics. In the extratropics, all SIF products exhibit greater skill in explaining variability in atmospheric CO₂observations compared to an ensemble of process‐based CO₂flux models and other vegetation indicators. With that said, other vegetation indicators, when multiplied by photosynthetically active radiation, yield similar results as SIF and may therefore be an effective structural SIF proxy at regional to global spatial scales. Furthermore, we find that using SIF as a predictor variable in the geostatistical inverse model shifts the seasonal cycle of estimated NBE and yields an earlier end to the growing season relative to other vegetation indicators. These results highlight how SIF can help constrain global‐scale variability in NBE. 

Abstract Understanding the controlling mechanisms of soil properties on ecosystem productivity is essential for sustaining productivity and increasing resilience under a changing climate. Here we investigate the control of topsoil depth (e.g., A horizons) on long‐term ecosystem productivity. We used nationwide observations (n = 2401) of topsoil depth and multiple scaled datasets of gross primary productivity (GPP) for five ecosystems (cropland, forest, grassland, pasture, shrubland) over 36 years (1986–2021) across the conterminous USA. The relationship between topsoil depth and GPP is primarily associated with water availability, which is particularly significant in arid regions under grassland, shrubland, and cropland (r = .37, .32, .15, respectively,p < .0001). For every 10 cm increase in topsoil depth, the GPP increased by 114 to 128 g C m⁻² year⁻¹in arid regions (r = .33 and .45,p < .0001). Paired comparison of relatively shallow and deep topsoils while holding other variables (climate, vegetation, parent material, soil type) constant showed that the positive control of topsoil depth on GPP occurred primarily in cropland (0.73, confidence interval of 0.57–0.84) and shrubland (0.75, confidence interval of 0.40–0.94). The GPP difference between deep and shallow topsoils was small and not statistically significant. Despite the positive control of topsoil depth on productivity in arid regions, its contribution (coefficients: .09–.33) was similar to that of heat (coefficients: .06–.39) but less than that of water (coefficients: .07–.87). The resilience of ecosystem productivity to climate extremes varied in different ecosystems and climatic regions. Deeper topsoils increased stability and decreased the variability of GPP under climate extremes in most ecosystems, especially in shrubland and grassland. The conservation of topsoil in arid regions and improvements of soil depth representation and moisture‐retention mechanisms are critical for carbon‐sequestration ecosystem services under a changing climate. These findings and relationships should also be included in Earth system models. 

Abstract Satellite‐derived sun‐induced chlorophyll fluorescence (SIF) has been increasingly used for estimating gross primary production (GPP). However, the relationship between SIF and GPP has not been well defined, impeding the translation of satellite observed SIF to GPP. Previous studies have generally assumed a linear relationship between SIF and GPP at daily and longer time scales, but support for this assumption is lacking. Here, we used the GPP/SIF ratio to investigate seasonal variations in the relationship between SIF and GPP over the Northern Hemisphere (NH). Based on multiple SIF products and MODIS and FLUXCOM GPP data, we found strong seasonal hump‐shaped patterns for the GPP/SIF ratio over northern latitudes, with higher values in the summer than in the spring or autumn. This hump‐shaped GPP/SIF seasonal variation was confirmed by examining different SIF products and was evident for most vegetation types except evergreen broadleaf forests. The seasonal amplitude of the GPP/SIF ratio decreased from the boreal/arctic region to drylands and the tropics. For most of the NH, the lowest GPP/SIF values occurred in October or September, while the maximum GPP/SIF values were evident in June and July. The most pronounced seasonal amplitude of GPP/SIF occurred in intermediate temperature and precipitation ranges. GPP/SIF was positively related to temperature in the early and late parts of the growing season, but not during the peak growing months. These shifting relationships between temperature and GPP/SIF across different months appeared to play a key role in the seasonal dynamics of GPP/SIF. Several mechanisms may explain the patterns we observed, and future research encompassing a broad range of climate and vegetation settings is needed to improve our understanding of the spatial and temporal relationships between SIF and GPP. Nonetheless, the strong seasonal variation in GPP/SIF we identified highlights the importance of incorporating this behavior into SIF‐based GPP estimations.