Search

Hector is an open-source reduced-complexity climate–carbon cycle model that models critical Earth system processes on a global and annual basis. Here, we present an updated version of the model, Hector V3.2.0 (hereafter Hector V3), and document its new features, implementation of new science, and performance. Significant new features include permafrost thaw, a reworked energy balance submodel, and updated parameterizations throughout. Hector V3 results are in good general agreement with historical observations of atmospheric CO 2 concentrations and global mean surface temperature, and the future temperature projections from Hector V3 are consistent with more complex Earth system model output data from the sixth phase of the Coupled Model Intercomparison Project. We show that Hector V3 is a flexible, performant, robust, and fully open-source simulator of global climate changes. We also note its limitations and discuss future areas for improvement and research with respect to the model's scientific, stakeholder, and educational priorities. [ABSTRACT FROM AUTHOR]

Peer review is a crucial but time‐consuming and sometimes frustrating part of science. The Editors of JGR: Biogeosciences are deeply appreciative of, and sincerely thank, the many 2023 reviewers who donated their time and expertise in support of the journal. Plain Language Summary: The editorial team of JGR: Biogeosciences recognizes and thanks the researchers who reviewed manuscripts for the journal in 2023. Key Points: The JGR: Biogeosciences Editors thank and recognize our 2023 reviewersThese experts donated their time, expertise, and insight to improving the science of their colleagues and community [ABSTRACT FROM AUTHOR]

Soil respiration (Rs), the soil‐to‐atmosphere flux of CO2, is a dominant but uncertain part of the carbon cycle, even after decades of study. This review focuses on progress in understanding Rs from laboratory incubations to global estimates. We survey key developments of in situ ecosystem‐scale Rs observations and manipulations, synthesize Rs meta‐analyses and global flux estimates, and discuss the most compelling challenges and opportunities for the future. Increasingly sophisticated lab experiments have yielded insights into the interaction among heterotrophic respiration, substrate supply, and enzymatic kinetics, and extended incubation‐based analyses across space and time. Observational and manipulative field‐based experiments have used improved measurement approaches to deepen our understanding of the integrated effects of environmental change and disturbance on Rs. Freely‐available observational databases have enabled meta‐analyses and studies probing the magnitude of, and constraints on, the global Rs flux. Key challenges for the field include expanding Rs measurements, experiments, and opportunities to under‐represented communities and ecosystems; reconciling independent estimates of global respiration fluxes and trends; testing and leveraging the power of machine learning and process‐based models, both independently and in conjunction with each other; and continuing the field's tradition of using novel experiments to explore diverse mechanisms and ecosystems. Plain Language Summary: "Soil respiration" refers to the flow of carbon dioxide, mostly generated by plant roots and microbes, from the soil to the atmosphere. This flux is large and highly uncertain, and understanding it has significant implications for our ability to predict the effects of land use and climate change. This review summarizes advances, insights, and challenges in soil respiration science. It examines laboratory approaches and findings; documents changes in how researchers measure and understand soil respiration in the natural world; and describes efforts to estimate the global dynamics of soil respiration from openly‐available databases of observations. We conclude by discussing the most compelling challenges and opportunities for the future. Key Points: Recent decades have seen large advances in measurement methods, experimental approaches, and data availability in soil respiration scienceLab and field‐based experiments have improved our understanding of the integrated effect of environmental change on soil respirationKey challenges include broadening access and continuing to explore diverse mechanisms and ecosystems using novel model‐experiment approaches [ABSTRACT FROM AUTHOR]

Nuclear magnetic resonance (NMR) spectroscopy is a useful tool for detection and identification of molecular structural information, with increasing applications in environmental sciences. NMR instrument outputs are however heterogeneous and require extensive post‐processing, creating barriers to their use and application by non‐specialists. Here, we report on a new open‐source R package, nmrrr, that processes and visualizes spectral data obtained from one‐dimensional solution‐state and solid‐state NMR experiments; the package also performs relevant calculations commonly applied in natural organic matter communities, such as computing the relative abundance of various functional groups. We document the package's installation, dependencies, and functions; and provide a standard workflow for processing NMR data. This package is currently available on CRAN and GitHub, and community contributions are welcome. Plain Language Summary: Nuclear magnetic resonance (NMR) spectroscopy is used to detect and identify the structure of molecules, and it has become increasingly important in environmental science. The data produced from NMR analyses need a lot of additional processing in order to be useful. This makes it difficult for non‐experts to use and apply this technique. We introduce a new R package "nmrrr" for processing and visualization of NMR data. This is an open‐source package and can be integrated into existing NMR processing workflows. The package can be used to process spectra and peaks data, perform relative abundance calculations, and plot graphs of spectra. The nmrrr package is currently available on two platforms: CRAN and GitHub. Key Points: The nmrrr package provides a reproducible workflow for binning and visualizing nuclear magnetic resonance (NMR) dataThe package works for solid and solution‐state experiments, as well as multiple solvents and nucleiThis package can be easily integrated into existing NMR workflows by users [ABSTRACT FROM AUTHOR]

Global soils store at least twice as much carbon as Earth's atmosphere.sup.1,2. The global soil-to-atmosphere (or total soil respiration, R.sub.S) carbon dioxide (CO.sub.2) flux is increasing.sup.3,4, but the degree to which climate change will stimulate carbon losses from soils as a result of heterotrophic respiration (R.sub.H) remains highly uncertain.sup.5-8. Here we use an updated global soil respiration database.sup.9 to show that the observed soil surface R.sub.H:R.sub.S ratio increased significantly, from 0.54 to 0.63, between 1990 and 2014 (P = 0.009). Three additional lines of evidence provide support for this finding. By analysing two separate global gross primary production datasets.sup.10,11, we find that the ratios of both R.sub.H and R.sub.S to gross primary production have increased over time. Similarly, significant increases in R.sub.H are observed against the longest available solar-induced chlorophyll fluorescence global dataset, as well as gross primary production computed by an ensemble of global land models. We also show that the ratio of night-time net ecosystem exchange to gross primary production is rising across the FLUXNET2015.sup.12 dataset. All trends are robust to sampling variability in ecosystem type, disturbance, methodology, CO.sub.2 fertilization effects and mean climate. Taken together, our findings provide observational evidence that global R.sub.H is rising, probably in response to environmental changes, consistent with meta-analyses.sup.13-16 and long-term experiments.sup.17. This suggests that climate-driven losses of soil carbon are currently occurring across many ecosystems, with a detectable and sustained trend emerging at the global scale.Global soil respiration is rising, probably in response to environmental changes, suggesting that climate-driven losses of soil carbon are occurring worldwide., Author(s): Ben Bond-Lamberty [sup.1] , Vanessa L. Bailey [sup.2] , Min Chen [sup.1] , Christopher M. Gough [sup.3] , Rodrigo Vargas [sup.4] Author Affiliations:(1) Pacific Northwest National Laboratory, Joint Global [...]

Isotopic pool dilution is a powerful approach to quantify gross biogeochemical transformation rates, but remains seldom used despite its potential.To facilitate broader implementation of pool dilution methods, we present a user‐friendly R package that optimizes gross production and consumption rates (and optionally fractionation constants as well) based on standard pool dilution time series data.This package features extensive documentation and example analyses, and is easily integrated into analytical pipelines.With this open‐source tool, the biogeochemistry community will be able to readily apply isotope pool dilution to a wide range of processes. [ABSTRACT FROM AUTHOR]

Hector, an open-source reduced complexity climate-carbon cycle model. Hector is a computationally efficient source of climate information, capable of completing a run in a fraction of a second. Hector models critical Earth system processes on a global and annual basis. Here we present an updated version of the model, Hector V3. In this manuscript, we document Hector's new features, and implementation of new science (e.g., radiative forcing calculations, carbon cycle, etc.). Hector V3 results are in good agreement with historical observations of CO2 concentrations and global mean surface temperature, and its future temperature projections are consistent with more complex Earth System Model output data from the Sixth Coupled Model Intercomparison Project. We document that Hector V3 is a flexible, performant, and robust simulator of contemporary and 21st-century global climate, and in closing, discuss future areas of improvement and research with respect to the model's scientific, stakeholder, and educational priorities. [ABSTRACT FROM AUTHOR]

We made a commitment to better include underrepresented members of our community in the publication pipeline of JGR: Biogeosciences. This commitment consists of regular updates on our policies and practices, and concrete actions we intend to implement over the next year. So far, our progress to tackle biases and ensure equitable research in the biogeosciences has focused on improving diversity of our associate editor and reviewer pools, increasing awareness of unconscious bias in peer‐review, and promoting inclusion in global collaborations. In this update, we explore manuscript submissions and manuscript decisions by gender, and we present a pilot that aims to promote ethical and equitable global collaborations in resource‐poor settings. We end our editorial by presenting our next set of actions that we plan on completing over the next year, which include a more thorough analysis of reviewer demographics. Key Points: Here we report on our progress for equitable and inclusive peer‐review and publishing for JGR: BiogeosciencesIn the past year we prioritized a pilot program to ensure equitable global collaborationsOur next set of key priorities to expand and diversify our reviewer pool and publishing community are highlighted [ABSTRACT FROM AUTHOR]

Forest soil respiration (Rs) plays an important role in the carbon balance of terrestrial ecosystems. China's forest occupies a large part of the world's forest. However, due to the lack of integrated observation data and appropriate upscaling methodologies, substantial uncertainties exist in the Rs evaluation, which limits our understanding of the carbon balance. Here, we re‐evaluated the total soil carbon effluxes across China by combining field observations from 634 published annual Rs with a machine learning technique (i.e., Random Forest (RF)). Our results revealed that the combination of systematic measurements with the RF model allowed a definite estimate. The average annual Rs was 776.9 g C m−2 yr−1, ranging from 411.5 to 1,770.7 g C m−2 yr−1. Total forest soil carbon effluxes amounted to 1.17 Pg C yr−1 in China. Geographically, annual Rs showed a clear spatially increasing trend from northeast to southwest. Forest type is an important factor in determining the soil respiration rate. Bamboo and Evergreen broadleaf forests were higher than other types of forests. These results provide a unique insight into the magnitudes and mechanisms of soil CO2 emissions in China's forest ecosystems. Plain Language Summary: Soil respiration refers to the soil‐to‐atmosphere flux of CO2, primarily generated by root and microbial respiration. Accurate assessment of forest soil respiration in China is a significant part of global‐scale carbon cycles. However, due to the lack of integrated observation data and appropriate upscaling methodologies, substantial uncertainties exist in soil respiration evaluation. Here, we assembled a new database and used a random forest approach to re‐explore the total forest soil respiration and obtained reliable annual forest soil carbon efflux in China. These results contribute to a better understanding and quantification of the national and global carbon cycle. Key Points: The combination of systematic measurements with the random forest model allowed a definite estimateTotal forest soil carbon effluxes amounted to 1.17 Pg C yr−1 in ChinaForest type is an important factor in determining the soil respiration rate [ABSTRACT FROM AUTHOR]

The editorial team at JGR: Biogeosciences would like to extend thanks to the 2022 reviewers who offered their time and expertise to help make decisions and improve our papers. Plain Language Summary: The editorial team at JGR: Biogeosciences would like to extend thanks to the 2022 reviewers who offered their time and expertise to help make decisions and improve our papers. Key Points: JGR Biogeosciences relies on hundreds of reviewers with wide ranging expertiseThank you to our 2022 reviewers [ABSTRACT FROM AUTHOR]

Earth System Models (ESMs) are increasingly representing agriculture due to its impact on biogeochemical cycles, local and regional climate, and fundamental importance for human society. Realistic large scale simulations may require spatially varying crop parameters that capture crop growth at various scales and among different cultivars, as well as common crop management practices, but their importance is uncertain, and they are often not represented in ESMs. In this study, we examine the impact of using constant versus spatially varying crop parameters using a novel, realistic crop rotation scenario in the Energy Exascale Earth System Model (E3SM) Land Model version 2 (ELMv2). We implemented crop rotation by using ELMv2's dynamic land unit capability, and then calibrated and validated the model against observations collected at three AmeriFlux sites in the US Midwest with corn soybean rotation. The calibrated model closely captured the magnitude and observed seasonality of carbon and energy fluxes across crops and sites. We performed regional simulations for the US Midwest using the calibrated model and found that spatially varying only a few crop parameters across the region, as opposed to using constant parameters, had a large impact, with the carbon fluxes and energy fluxes both varying by up to 40%. These results imply that large scale ESM simulations using spatially invariant crop parameters may result in biased energy and carbon fluxes estimation from agricultural land, and underline the importance of improving human‐earth systems interactions in ESMs. Plain Language Summary: Crops are increasingly being characterized in global land models because of their impact on local and regional climate. However, there is limited understanding of the impact of crop rotation and of different crop cultivars on carbon and energy fluxes from the land surface. Our study implements crop rotation and spatially varying crop parameters in the Energy Exascale Earth System Model Land Model and finds that doing so improves carbon and energy flux estimation from cropland area. These findings emphasize the importance of capturing agricultural management practices and variability in growth characteristics across different crop cultivars in global land models. Key Points: This study implements corn soybean rotation and spatially varying crop parameters in the Energy Exascale Earth System Land ModelThe model is calibrated and validated against observations collected at three AmeriFlux sites in the US MidwestWe find that spatially varying crop parameters resulted in improved flux estimation from cropland areas [ABSTRACT FROM AUTHOR]