Rangelands provide significant environmental benefits through many ecosystem services, which may include soil organic carbon (SOC) sequestration. However, quantifying SOC stocks and monitoring carbon (C) fluxes in rangelands are challenging due to the considerable spatial and temporal variability tied to rangeland C dynamics, as well as limited data availability. We developed a Rangeland Carbon Tracking and Management (RCTM) system to track long-term changes in SOC and ecosystem C fluxes by leveraging remote sensing inputs and environmental variable datasets with algorithms representing terrestrial C-cycle processes. Bayesian calibration was conducted using quality-controlled C flux datasets obtained from 61 Ameriflux and NEON flux tower sites from Western and Midwestern U.S. rangelands, to parameterize the model according to dominant vegetation classes (perennial and/or annual grass, grass-shrub mixture, and grass-tree mixture). The resulting RCTM system produced higher model accuracy for estimating annual cumulative gross primary productivity (GPP) (R2 > 0.6, RMSE < 390 g C m-2) than net ecosystem exchange of CO2 (NEE) (R2 > 0.4, RMSE < 180 g C m-2), and captured the spatial variability of surface SOC stocks with R2 = 0.6 when validated against SOC measurements across 13 NEON sites. Our RCTM simulations indicated slightly enhanced SOC stocks during the past decade, which is mainly driven by an increase in precipitation. Regression analysis identified slope, soil texture, and climate factors as the main controls on model-predicted C sequestration rate. Future efforts to refine the RCTM system will benefit from long-term network-based monitoring of rangeland vegetation biomass, C fluxes, and SOC stocks.

A long-standing challenge in studying the global carbon cycle has been understanding the factors controlling inter–annual variation (IAV) of carbon fluxes related to vegetation photosynthesis and respiration, and improving their representations in existing biogeochemical models. Here, we compared an optimality-based mechanistic model and a semi-empirical light use efficiency model to understand how current models can be improved to simulate IAV of gross primary production (GPP). Both models simulated hourly GPP and were parameterized for (1) each site–year, (2) each site with an additional constraint on IAV (CostIAV), (3) each site, (4) each plant–functional type, and (5) globally. This was followed by forward runs using calibrated parameters, and model evaluations at different temporal scales across 198 eddy covariance sites. Both models performed better on hourly scale than annual scale for most sites. Specifically, the mechanistic model substantially improved when drought stress was explicitly included. Most of the variability in model performances was due to model types and parameterization strategies. The semi-empirical model produced statistically better hourly simulations than the mechanistic model, and site–year parameterization yielded better annual performance for both models. Annual model performance did not improve even when parameterized using CostIAV. Furthermore, both models underestimated the peaks of diurnal GPP in each site–year, suggesting that improving predictions of peaks could produce a comparatively better annual model performance. GPP of forests were better simulated than grassland or savanna sites by both models. Our findings reveal current model deficiencies in representing IAV of carbon fluxes and guide improvements in further model development.

Water returned to the atmosphere as evapotranspiration (ET) is approximately 1.6x greater than global river discharge and has wide-reaching impacts on groundwater and streamflow. In the U.S. Midwest, widespread land conversion from prairie to cropland has altered spatiotemporal patterns of ET, yet there is no consensus on the direction of change in ET or the mechanisms controlling changes. We aimed to harmonize findings about how land use change affects ET in the Midwest. We measured ET at three locations within the Long-Term Agroecosystem Research (LTAR) network along a latitudinal gradient with paired rainfed cropland and prairie sites at each location. At the northern locations, the Upper Mississippi River Basin (UMRB) and Kellogg Biological Station (KBS), the cropland has annual ET that is 84 and 29 mm/year higher, respectively, caused primarily by higher ET, likely from soil evaporation during springtime when agricultural fields are fallow. At the southern location, the Central Mississippi River Basin (CMRB), the prairie has 69 mm/year higher ET, primarily due to a longer growing season. To attribute differences in springtime ET to specific mechanisms, we examine the energy balance using the Two-Resistance Method (TRM). Results from the TRM demonstrate that higher surface conductance in croplands is the primary factor leading to higher springtime ET from croplands, relative to prairies. Results from this study provide critical insight into the impact of land use change on the hydrology of the U.S. Corn Belt by providing a mechanistic understanding of how land use change affects the water budget.

This article is composed of three independent commentaries about the state of ICON principles (Goldman et al. 2021) in the AGU Biogeosciences section and discussion on the opportunities and challenges of adopting them. Each commentary focuses on a different topic: Global collaboration, technology transfer and application (Section 2), Community engagement, citizen science, education, and stakeholder involvement (Section 3), and Field, experimental, remote sensing, and real-time data research and application (Section 4). We discuss needs and strategies for implementing ICON and outline short- and long-term goals. The inclusion of global data and international community engagement are key to tackle grand challenges in biogeosciences. Although recent technological advances and growing open-access information across the world have enabled global collaborations to some extent, several barriers ranging from technical to organizational to cultural have remained in advancing interoperability and tangible scientific progress in biogeosciences. Overcoming these hurdles is necessary to address pressing large-scale research questions and applications in the biogeosciences, where ICON principles are essential. Here, we list several opportunities for ICON, including coordinated experimentation and field observations across global sites, that are ripe for implementation in biogeosciences as a means to scientific advancements and social progress.

Our presentation represents a brief overview of recent climatic and environmental changes over the Dry Lands of Northern Eurasia. The Dry Land Belt (DLB) in Northern Eurasia is the largest contiguous dryland on Earth. During the last century, changes here have included land use change (e.g., rapid virgin land development in the mid of the 1950s; cf. Figure 1), resource extraction, rapid institutional shifts (e.g., collapse of the Soviet Union), climatic changes, and natural disturbances. These factors intertwine, overlap, sometimes mitigate but sometimes feedback upon each other to exacerbate their synergistic and cumulative effects. Thus, it is important to document properly each of these external and internal factors and to characterize structural relationships among them in order to develop better approaches to alleviating negative consequences of these regional environmental changes. This paper addresses the climatic changes observed over the DLB in recent decades and outlines possible links of these changes (both impacts and feedbacks) with other external and internal factors of contemporary regional environmental change and human activities within the DLB.

Accounting for temporal changes in carbon dioxide (CO2) emissions from freshwaters remains a challenge for global and regional carbon budgets. Here, we synthesize 171 site-months of eddy covariance flux measurements of CO2 from 13 lakes and reservoirs in the Northern Hemisphere (NH) and quantify the magnitude and dynamics at multiple temporal scales. We found pronounced diel and sub-monthly oscillatory variations in CO2 flux at all sites. Diel variation converted sites to daily net sinks of CO2 in only 11% of site-months. Upscaled annual emissions had an average of 25% (range 3-58%) interannual variation. Given temporal variation remains under-represented in inventories of CO2 emissions from lakes and reservoirs, revisions in CO2 flux are needed using a better representation of sub-daily to interannual variability. Constraining short- and long-term variability is necessary to improve detection of temporal changes of CO2 fluxes in response to natural and anthropogenic drivers.

Accounting for temporal changes in carbon dioxide (CO2) emissions from freshwaters remains a challenge for global and regional carbon budgets. Here, we synthesize 171 site-months of eddy covariance flux measurements of CO2 from 13 lakes and reservoirs in the Northern Hemisphere (NH) and quantify dynamics at multiple temporal scales. We found pronounced sub-annual variability in CO2 flux at all sites. Accounting for diel variation, only 11% of site-months were net daily sinks of CO2. Annual CO2 emissions had an average of 25% (range 3-58%) interannual variation. Nighttime emissions regularly exceeded daytime emissions. Sources of CO2 flux variability were delineated through mutual information analysis. Sample analysis of CO2 fluxes indicate importance of continuous sampling. Constraining short- and long-term variability is necessary to improve detection of temporal changes of CO2 fluxes in response to natural and anthropogenic drivers.