Biologically Enhanced Carbon Sequestration: Research Needs and Opportunities

Fossil fuel combustion, deforestation, and biomass burning are the dominant contributors to increasing atmospheric carbon dioxide (CO{sub 2}) concentrations and global warming. Many approaches to mitigating CO{sub 2} emissions are being pursued, and among the most promising are terrestrial and geologic carbon sequestration. Recent advances in ecology and microbial biology offer promising new possibilities for enhancing terrestrial and geologic carbon sequestration. A workshop was held October 29, 2007, at Lawrence Berkeley National Laboratory (LBNL) on Biologically Enhanced Carbon Sequestration (BECS). The workshop participants (approximately 30 scientists from California, Illinois, Oregon, Montana, and New Mexico) developed a prioritized list of research needed to make progress in the development of biological enhancements to improve terrestrial and geologic carbon sequestration. The workshop participants also identified a number of areas of supporting science that are critical to making progress in the fundamental research areas. The purpose of this position paper is to summarize and elaborate upon the findings of the workshop. The paper considers terrestrial and geologic carbon sequestration separately. First, we present a summary in outline form of the research roadmaps for terrestrial and geologic BECS. This outline is elaborated upon in the narrative sections that follow. The narrative sections start with the focused research priorities in each area followed by critical supporting science for biological enhancements as prioritized during the workshop. Finally, Table 1 summarizes the potential significance or 'materiality' of advances in these areas for reducing net greenhouse gas emissions

Soil carbon loss in warmed subarctic grasslands is rapid and restricted to topsoil

Global warming may lead to carbon transfers from soils to the atmosphere, yet this positive feedback to the climate system remains highly uncertain, especially in subsoils (Ilyina and Friedlingstein, 2016; Shi et al., 2018). Using natural geothermal soil warming gradients of up to +6.4 degrees C in subarctic grasslands (Sigurdsson et al., 2016), we show that soil organic carbon (SOC) stocks decline strongly and linearly with warming (-2.8 t ha(-1) degrees C-1). Comparison of SOC stock changes following medium-term (5 and 10 years) and long-term (> 50 years) warming revealed that all SOC stock reduction occurred within the first 5 years of warming, after which continued warming no longer reduced SOC stocks. This rapid equilibration of SOC observed in Andosol suggests a critical role for ecosystem adaptations to warming and could imply short-lived soil carbon-climate feedbacks. Our data further revealed that the soil C loss occurred in all aggregate size fractions and that SOC stock reduction was only visible in topsoil (0-10 cm). SOC stocks in subsoil (10-30 cm), where plant roots were absent, showed apparent conservation after > 50 years of warming. The observed depth-dependent warming responses indicate that explicit vertical resolution is a prerequisite for global models to accurately project future SOC stocks for this soil type and should be investigated for soils with other mineralogies

Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites

Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 103 to 107 m2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applications and to provide general guidance for data use

An open-source database for the synthesis of soil radiocarbon data: International Soil Radiocarbon Database (ISRaD) version 1.0

Radiocarbon is a critical constraint on our estimates of the timescales of soil carbon cycling that can aid in identifying mechanisms of carbon stabilization and destabilization and improve the forecast of soil carbon response to management or environmental change. Despite the wealth of soil radiocarbon data that have been reported over the past 75 years, the ability to apply these data to global-scale questions is limited by our capacity to synthesize and compare measurements generated using a variety of methods. Here, we present the International Soil Radiocarbon Database (ISRaD; http://soilradiocarbon.org, last access: 16 December 2019), an open-source archive of soil data that include reported measurements from bulk soils, distinct soil carbon pools isolated in the laboratory by a variety of soil fractionation methods, samples of soil gas or water collected interstitially from within an intact soil profile, CO2 gas isolated from laboratory soil incubations, and fluxes collected in situ from a soil profile. The core of ISRaD is a relational database structured around individual datasets (entries) and organized hierarchically to report soil radiocarbon data, measured at different physical and temporal scales as well as other soil or environmental properties that may also be measured and may assist with interpretation and context. Anyone may contribute their own data to the database by entering it into the ISRaD template and subjecting it to quality assurance protocols. ISRaD can be accessed through (1) a web-based interface, (2) an R package (ISRaD), or (3) direct access to code and data through the GitHub repository, which hosts both code and data. The design of ISRaD allows for participants to become directly involved in the management, design, and application of ISRaD data. The synthesized dataset is available in two forms: the original data as reported by the authors of the datasets and an enhanced dataset that includes ancillary geospatial data calculated within the ISRaD framework. ISRaD also provides data management tools in the ISRaD-R package that provide a starting point for data analysis; as an open-source project, the broader soil community is invited and encouraged to add data, tools, and ideas for improvement. As a whole, ISRaD provides resources to aid our evaluation of soil dynamics across a range of spatial and temporal scales. The ISRaD v1.0 dataset is archived and freely available at https://doi.org/10.5281/zenodo.2613911 (Lawrence et al., 2019).Max Planck Institute for Biogeochemistry; European Research CouncilEuropean Research Council (ERC) [695101]; USGS Land Change Science mission area; US Department of AgricultureUnited States Department of Agriculture (USDA) [2018-67003-27935]; US Geological Survey Powell Center for the working group on Soil Carbon Storage and FeedbacksOpen access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Statistical upscaling of ecosystem CO2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties

The regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink-source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990-2015 from 148 terrestrial high-latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km(2)) across the high-latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE-focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE -46 and -29 g C m(-2) yr(-1), respectively) compared to tundra (average annual NEE +10 and -2 g C m(-2) yr(-1)). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high-latitude region was on average an annual CO2 sink during 1990-2015, although uncertainty remains high

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.Peer reviewe

A model-data comparison of gross primary productivity: Results from the North American Carbon Program site synthesis

Accurately simulating gross primary productivity (GPP) in terrestrial ecosystem models is critical because errors in simulated GPP propagate through the model to introduce additional errors in simulated biomass and other fluxes. We evaluated simulated, daily average GPP from 26 models against estimated GPP at 39 eddy covariance flux tower sites across the United States and Canada. None of the models in this study match estimated GPP within observed uncertainty. On average, models overestimate GPP in winter, spring, and fall, and underestimate GPP in summer. Models overpredicted GPP under dry conditions and for temperatures below 0°C. Improvements in simulated soil moisture and ecosystem response to drought or humidity stress will improve simulated GPP under dry conditions. Adding a low-temperature response to shut down GPP for temperatures below 0°C will reduce the positive bias in winter, spring, and fall and improve simulated phenology. The negative bias in summer and poor overall performance resulted from mismatches between simulated and observed light use efficiency (LUE). Improving simulated GPP requires better leaf-to-canopy scaling and better values of model parameters that control the maximum potential GPP, such as ε[subscript max] (LUE), V[subscript cmax] (unstressed Rubisco catalytic capacity) or J[subscript max] (the maximum electron transport rate)

Warming accelerates decomposition of decades-old carbon in forest soils.

Global climate carbon-cycle models predict acceleration of soil organic carbon losses to the atmosphere with warming, but the size of this feedback is poorly known. The temperature sensitivity of soil carbon decomposition is commonly determined by measuring changes in the rate of carbon dioxide (CO(2)) production under controlled laboratory conditions. We added measurements of carbon isotopes in respired CO(2) to constrain the age of carbon substrates contributing to the temperature response of decomposition for surface soils from two temperate forest sites with very different overall rates of carbon cycling. Roughly one-third of the carbon respired at any temperature was fixed from the atmosphere more than 10 y ago, and the mean age of respired carbon reflected a mixture of substrates of varying ages. Consistent with global ecosystem model predictions, the temperature sensitivity of the carbon fixed more than a decade ago was the same as the temperature sensitivity for carbon fixed less than 10 y ago. However, we also observed an overall increase in the mean age of carbon respired at higher temperatures, even correcting for potential substrate limitation effects. The combination of several age constraints from carbon isotopes showed that warming had a similar effect on respiration of decades-old and younger (<10 y) carbon but a greater effect on decomposition of substrates of intermediate (between 7 and 13 y) age. Our results highlight the vulnerability of soil carbon to warming that is years-to-decades old, which makes up a large fraction of total soil carbon in forest soils globally