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At least 235 records · Page 13

Climate Warming Alters Nutrient Storage in Seasonally Dry Forests: Insights From a 2,300 m Elevation Gradient

Understanding potential response of forest carbon (C) and nutrient storage to warming is important for climate mitigation policies. Unfortunately, those responses are difficult to predict in seasonally dry forests, in part, because ecosystem processes are highly sensitive to both changes in temperature and precipitation. We investigated how warming might alter stocks of C, nitrogen (N), and phosphorus (P) in vegetation and the entire regolith (soil + weathered bedrock or “saprock”) using a space-for-time substitution along a bioclimatic gradient in the Sierra Nevada, California. The pine-oak and mixed-conifer forests between 1,160–2,015 m elevation have more optimal climates (not too dry or hot) for ecosystem productivity, soil weathering, and cycling of essential elements than the oak savannah (405 m) and subalpine forest (2,700 m). We found decreases in overstory vegetation nutrient stocks with decreasing elevation because of enhanced water limitation and greater occurrence of disturbances. Stocks of C, N, and P in the entire regolith peaked at the pine-oak and mixed-conifer forests across the bioclimatic gradient, driven by thicker regolith profiles and greater nutrient input rates. These observations suggest long-term warming will decrease ecosystem nutrient storage at the warmer, transitional pine-oak zone, but will increase nutrient storage at the colder, subalpine zone. Assuming steady-state conditions, we found the mean residence time of ecosystem C decreased with projected rising air temperatures and increased following a major drought event across the bioclimatic gradient. Our study emphasizes potentially elevation-dependent changes in nutrient storage and C persistence with warming in seasonally dry forests.

54 ENVIRONMENTAL SCIENCES↗

N and P constrain C in ecosystems under climate change: Role of nutrient redistribution, accumulation, and stoichiometry

Abstract We use the Multiple Element Limitation (MEL) model to examine responses of 12 ecosystems to elevated carbon dioxide (CO 2 ), warming, and 20% decreases or increases in precipitation. Ecosystems respond synergistically to elevated CO 2 , warming, and decreased precipitation combined because higher water‐use efficiency with elevated CO 2 and higher fertility with warming compensate for responses to drought. Response to elevated CO 2 , warming, and increased precipitation combined is additive. We analyze changes in ecosystem carbon (C) based on four nitrogen (N) and four phosphorus (P) attribution factors: (1) changes in total ecosystem N and P, (2) changes in N and P distribution between vegetation and soil, (3) changes in vegetation C:N and C:P ratios, and (4) changes in soil C:N and C:P ratios. In the combined CO 2 and climate change simulations, all ecosystems gain C. The contributions of these four attribution factors to changes in ecosystem C storage varies among ecosystems because of differences in the initial distributions of N and P between vegetation and soil and the openness of the ecosystem N and P cycles. The net transfer of N and P from soil to vegetation dominates the C response of forests. For tundra and grasslands, the C gain is also associated with increased soil C:N and C:P. In ecosystems with symbiotic N fixation, C gains resulted from N accumulation. Because of differences in N versus P cycle openness and the distribution of organic matter between vegetation and soil, changes in the N and P attribution factors do not always parallel one another. Differences among ecosystems in C‐nutrient interactions and the amount of woody biomass interact to shape ecosystem C sequestration under simulated global change. We suggest that future studies quantify the openness of the N and P cycles and changes in the distribution of C, N, and P among ecosystem components, which currently limit understanding of nutrient effects on C sequestration and responses to elevated CO 2 and climate change.

54 ENVIRONMENTAL SCIENCES↗

Impact of Salinity on Ground Ice Distribution Across an Arctic Coastal Polygonal Tundra Environment

The heterogeneous distribution of ground ice in the Arctic is a key driver of uneven ground subsidence as permafrost thaws, significantly impacting infrastructure and surface/subsurface hydrology. These topographic and hydrological changes contribute to major uncertainties in energy and carbon fluxes and storage in a warming Arctic. This study aims to improve our understanding of the controls on ground ice and organic matter distribution within the top 3 m of permafrost in coastal polygonal tundra near Utqiagvik, Alaska. To this end, we apply a neural network approach to bulk density distributions derived from nondestructive X-ray tomography of soil cores, trained with laboratory analyses, to improve the resolution and spatial coverage of estimates of dry bulk density, ice content, and organic matter content. In addition, we use capacitively coupled geophysical imaging to map soil electrical conductivity and salinity variations. The results show that sedimentary deposits from ocean transgressions, along with subsequent ice wedge polygon geomorphological processes, jointly influence the distribution of ice content at various scales. The impact of the latter decreases with depth, whereas the influence of salinity and sedimentary history increases. Although the controls on the distribution of soil organic matter content (g/cm 3 ) remain unclear, the pronounced heterogeneity in bulk density strongly influences its calculation from laboratory mass fraction measurements (g/g). From a methodological perspective, the interdependencies among soil components and the need for increased data coverage underscore the value of high-resolution density measurements, such as using X-ray tomography. Overall, this study emphasizes the importance of considering salinity constraints on ice content distribution in coastal permafrost regions. The results are expected to aid in the development of data products and process representations in geomorphological and ecosystem models.

Dafflon, Baptiste [Lawrence Berkeley National Labo↗

Soil incubation methods lead to large differences in inferred methane production temperature sensitivity

Abstract Quantifying the temperature sensitivity of methane (CH 4 ) production is crucial for predicting how wetland ecosystems will respond to climate warming. Typically, the temperature sensitivity (often quantified as a Q 10 value) is derived from laboratory incubation studies and then used in biogeochemical models. However, studies report wide variation in incubation-inferred Q 10 values, with a large portion of this variation remaining unexplained. Here we applied observations in a thawing permafrost peatland (Stordalen Mire) and a well-tested process-rich model ( ecosys ) to interpret incubation observations and investigate controls on inferred CH 4 production temperature sensitivity. We developed a field-storage-incubation modeling approach to mimic the full incubation sequence, including field sampling at a particular time in the growing season, refrigerated storage, and laboratory incubation, followed by model evaluation. We found that CH 4 production rates during incubation are regulated by substrate availability and active microbial biomass of key microbial functional groups, which are affected by soil storage duration and temperature. Seasonal variation in substrate availability and active microbial biomass of key microbial functional groups led to strong time-of-sampling impacts on CH 4 production. CH 4 production is higher with less perturbation post-sampling, i.e. shorter storage duration and lower storage temperature. We found a wide range of inferred Q 10 values (1.2–3.5), which we attribute to incubation temperatures, incubation duration, storage duration, and sampling time. We also show that Q 10 values of CH 4 production are controlled by interacting biological, biochemical, and physical processes, which cause the inferred Q 10 values to differ substantially from those of the component processes. Terrestrial ecosystem models that use a constant Q 10 value to represent temperature responses may therefore predict biased soil carbon cycling under future climate scenarios.

54 ENVIRONMENTAL SCIENCES↗

CarbStor: Development, Analysis and Modification of Carbon Storing Model Soil Communities

Soil microbial communities carry out a number of key processes including plant growth promotion, bioremediation and cycling of nutrients. Carbon cycling is among the most important of these nutrients that are metabolized and processed by the soil microbial community. Many of the carbon inputs are converted to alternative organic forms of carbon that can be used by plants or act as biomass for microbial growth. However, inorganic forms of carbon can also be produced by soil microbial communities including calcium carbonate (CaCO 3 ). Production of calcium carbonate is beneficial for the ecosystem in several ways: it can stabilize soils and improve soil health, especially denser soils with high clay content, it can act as a method of bioremediation, it can serve as an alternative carbon source for plants and it can be a way to store carbon in soil in a stable, inorganic manner for the long term. While the chemistry surrounding individual species carrying out this process is well known what is lacking is an understanding of how species interact in a community to drive carbonate production. As all microbial species in soil exist in a community setting gaining this knowledge is critical to our predicting and controlling this microbial phenotype to greatly improve soil health. The CarbStor project is focused on developing, analyzing and modifying defined microbial soil consortia that express phenotypes at both the species and community level to convert carbon into recalcitrant stable sources such as precipitated carbonate or microbial necromass. To take full advantage of the soil community for this process we will need to fill several key knowledge gaps (KG), three of which are the focus of CarbStor. KG1: Whether and to what degree microbial communities can be developed that produce precipitated carbon via microbial metabolism. KG2: What interspecies interactions drive the individual member phenotypes in defined communities that lead to carbon precipitation. KG3: How can these interactions be modified to enhance carbon sequestration beyond what native communities are capable of. We hypothesize that in a carbon sequestering community only a subset of species will express phenotypes related to carbon storage processes. We also hypothesize that these phenotypes are expressed as a result of interactions with other species in the community that are not involved in carbon storage processes and that these interactions can be harnessed to enhance community carbon sequestration.

54 ENVIRONMENTAL SCIENCES↗

Consequences of Altered Root Nutrient Uptake for Soil Carbon Stabilization (Final Report)

Objectives: The primary objectives of this project are to improve our understanding of tropical forest belowground processes, and to increase representation of this biome in ecosystem-scale and global C cycle models. Belowground dynamics present a major source of uncertainty inhibiting our ability to predict C cycle responses to climate change. Representation of tropical forests in these models is particularly lacking, even though these ecosystems hold >25% of terrestrial C stocks. While the majority of humid tropical forests exist on relatively infertile soils (i.e. poor in rock-derived nutrients), enormous gradients in soil nutrient availability exist at landscape-scales due to shifts in geology and soil order. Soil fertility is likely to greatly influence how tropical soil C storage will respond to the declines in precipitation predicted for the tropics. In particular, root dynamics vary across soil fertility gradients, with roots representing the major input of C to subsurface soils. Root characteristics related to soil fertility include biomass, turnover, C exudates, tissue chemistry, and nutrient uptake rates, with each of these likely sensitive to changes in moisture. The proposed project will fully integrate field research with an existing ecosystem model to assess potential effects of drying on belowground tropical C dynamics across a range of soil fertilities. Project Description:. This project will identify key linkages among soil fertility, root nutrient uptake, root dynamics, and soil C storage. The hypothesized framework for understanding these linkages is: Tropical rainforest roots in relatively fertile soils have lesser root biomass, faster turnover, fewer exudates, and improved root tissue quality relative to infertile sites, all resulting from increased root nutrient uptake. Ultimately, these root characteristics in fertile soils promote proportionally greater long-term soil C storage in organo-mineral associations. Specifically, lower root exudates and improved root tissue quality in fertile soils reduce microbial respiration of extant soil C (i.e. “priming) and increase microbial C use efficiency, leading to sorption of protein-rich microbial and plant organic matter on soil mineral surfaces. However, the larger pools of mineral-associated C in fertile tropical soils are more vulnerable to decreased rainfall than smaller C pools in infertile soils, in part because of the lesser root biomass, faster turnover, and softer, more labile root tissues. Also, the shallower lateral rooting structures typical in fertile soils experience greater desiccation and death than deeper roots in infertile sites, with little short-term adaptation to drying.

54 ENVIRONMENTAL SCIENCES↗

Insights Into Nature-Based Climate Solutions: Managing Forests for Climate Resilience and Carbon Stability

Successful implementation of forest management as a nature-based climate solution is dependent on the durability of management-induced changes in forest carbon storage and sequestration. As forests face unprecedented stability risks in the face of ongoing climate change, much remains unknown regarding how management will impact forest stability, or how interactions with climate might shift the response of forests to management across spatiotemporal scales. Here, we used a process-based model to simulate multidecadal projections of forest dynamics in response to changes in management and climate. Simulations were conducted across gradients in forest type, edaphic factors, and management intensity under two alternate radiative forcing scenarios (RCP4.5 and RCP8.5). This allowed for the quantification of forest stability shifts in response to climate change, and the role of management in modulating that response, where ecosystem stability is characterized as the resilience and temporal stability of net primary production, aboveground biomass, and soil carbon. Our results indicate that forest structure is primarily shaped by management, but the same management strategy often produced divergent structures over time, due to interactions with regional climate change. We found that management can be used to increase stability and minimize the release of stored carbon by reducing mortality, but also highlight the regional dependency of management-induced changes in resilience to climate change.

54 ENVIRONMENTAL SCIENCES↗

Definition of a Technology Validation Mission for P-band Reflectometry using Signals of Opportunity

Root-Zone Soil Moisture (RZSM) (moisture profile in the top meter of soil) and Snow Water Equivalent (SWE) (total snow pack water content) are identified as priority target variables in the ESAS 2017 decadal survey [1] with critical roles in hydrology and water management. RZSM estimates are vital for understanding multiple Earth system processes and forecasting (for example, droughts [2]). Simultaneous knowledge of surface and RZSM could enable a breakthrough in estimating key unobserved hydrologic fluxes and reduce uncertainty in net ecosystem exchange (NEE), carbon balance [3] discharge estimates, and crop yield forecasts [4] .With the high albedo and insulating properties of snow, monitoring, SWE accumulation would provide a key constraint on the potential runoff during spring ablation while monitoring SWE disappearance rates would provide a key constraint on SWE partition into runoff vs. infiltration/recharge. [5] demonstrated that knowledge of early-spring SWE generally contributes most to streamflow forecast skill in the Western U.S. SWE is also a source of water storage that provides the water resources during spring snowmelt. Despite such potentially transformative contributions, accurate RZSM and SWE measurements are unattainable with current technology. While active/passive L-band methods (e.g. SMAP, SMOS) can reliably retrieve surface soil moisture in the top 5 cm of soil [6], [7]. RZSM estimates are only available through model assimilation of brightness temperatures with a radiative transfer and land surface models [8]. SWE estimation uses multi-frequency passive microwave techniques (e.g. [9]-[11]), which have significant problems with deeper snow and in forested and mountainous environments [12]. Signals of opportunity (SoOp) in P-band (200-400 MHz) is a new remote sensing technique with the capability of estimating both essential hydrologic variables, RZSM and SWE, circumventing many of the aforementioned limitations under all weather conditions day and night. SoOp is the re-utilization of existing powerful satellite transmissions within bands allocated for communications or navigation. P-band SoOp sensitivity to soil moisture has been demonstrated in an airborne experiment over Oklahoma in 2016 [13]. Recent theory [14] and experiments [15] have also confirmed that the reflection coefficient phase is proportional to SWE.

Garrison, J. L.↗

Unveiling Feedstock Variability: Insights into Corn Stover Conversion - Part I: Physicochemical Properties and Self-Degradation

Transforming agricultural waste into biofuels and bioproducts is crucial to advancing a low-carbon bioeconomy. However, the inherent variability in the composition and quality introduces uncertainties in the conversion efficiency and poses challenges in process development. Through integrating a high-throughput conversion system, material characterization techniques, and advanced data analysis tools, this study investigates the variability of corn stover and its subsequent impacts on carbohydrate conversion. The findings reveal that indoor storage substantially reduces the moisture and ash content and soil contamination, while other properties remain largely unchanged. Self-degradation due to microbial activity during storage decreases the carbohydrate content of corn stover but enhances glucose and xylose yields. A negative correlation is observed between sugar yields and lignin content across samples with varying ash and moisture content. The inhibitory effect of lignin diminishes in self-degraded samples likely due to the disrupted cell wall structure. Although self-degradation slightly increases cellulose crystallinity, no strong correlation was observed between the crystallinity and sugar yield. Hot water pretreatment under mild conditions effectively mitigates inherent variability, consistently improving the sugar yield from corn stover by up to 50%. By elucidating the feedstock variability and its impact on convertibility, these findings offer valuable insights into appropriate feedstock handling and management, highlighting potential strategies to address variability challenges.

09 BIOMASS FUELS↗

Controls and relationships of soil organic carbon abundance and persistence vary across pedo–climatic regions

One of the largest uncertainties in the terrestrial carbon cycle is the timing and magnitude of soil organic carbon (SOC) response to climate and vegetation change. This uncertainty prevents models from adequately capturing SOC dynamics and challenges the assessment of management and climate change effects on soils. Reducing these uncertainties requires simultaneous investigation of factors controlling the amount (SOC abundance) and duration (SOC persistence) of stored C. We present a global synthesis of SOC and radiocarbon profiles (n Profile = 597) to assess the timescales of SOC storage. We use a combination of statistical and depth–resolved compartment models to explore key factors controlling the relationships between SOC abundance and persistence across pedo–climatic regions and with soil depth. This allows us to better understand (i) how SOC abundance and persistence covary across pedo–climatic regions and (ii) how the depth dependence of SOC dynamics relates to climatic and mineralogical controls on SOC abundance and persistence. We show that SOC abundance and persistence are differently related; the controls on these relationships differ substantially between major pedo–climatic regions and soil depth. For example, large amounts of persistent SOC can reflect climatic constraints on soils (e.g., in tundra/polar regions) or mineral absorption, reflected in slower decomposition and vertical transport rates. In contrast, lower SOC abundance can be found with lower SOC persistence (e.g., in highly weathered tropical soils) or higher SOC persistence (e.g., in drier and less productive regions). We relate variable patterns of SOC abundance and persistence to differences in the processes constraining plant C input, microbial decomposition, vertical C transport and mineral SOC stabilization potential. This process–oriented grouping of SOC abundance and persistence provides a valuable benchmark for global C models, highlighting that pedo–climatic boundary conditions are crucial for predicting the effects of climate change and soil management on future C abundance and persistence.

54 ENVIRONMENTAL SCIENCES↗

Biological Carbon Sequestration for Climate and Soil Health

The United States recently launched the Net Zero World Initiative on decarbonization. As temperatures and sea levels rise, strong action is needed to mitigate high atmospheric CO 2 levels. In response to this need, a joint workshop between the US Department of Energy’s Oak Ridge National Laboratory (ORNL) and Lawrence Berkeley National Laboratory (LBNL) was convened to assess the challenges and opportunities within biological carbon (C) capture. The virtual workshop on Biological Carbon Sequestration for Climate and Soil Health focused on three aspects of biological C capture research: natural systems, engineered systems, and modeling. For this workshop, the scope of natural systems included unmanaged (e.g., grasslands, wetlands, natural forests) and managed (e.g., agricultural lands, commercial forests, forest biofuels) ecosystems. The engineered systems group covered topics in genetically modified plants and microbes, synthetic microbiomes, and altered plant–microbe interactions for enhancing C capture, storage, and utilization. The modeling group focused on computational tools and data collection to predict and assess the effectiveness of new biocarbon sequestration advances. Participant expertise included plant and microbial systems biology, synthetic biology, soil biogeochemistry, and techno-economic analysis. Together, participants outlined key scientific advances in support of biological C capture and storage. Among the major findings of the meeting were the need to better measure C flux within natural, agricultural, and fabricated ecosystems for experimentation; better understand the role of soil composition, plant roots, and the rhizosphere (i.e., the soil surrounding the plant root) in the underground storage of organic C; and design plant–microbe systems for maximal C storage.

54 ENVIRONMENTAL SCIENCES↗

Accumulation of Soil Microbial Necromass Controlled by Microbe–Mineral Interactions

Soil organic matter (SOM) is a key reservoir for global carbon (C), supporting soil fertility and influencing greenhouse gas emissions. Microbial residues, composed of dead cells and cellular fragments, are major contributors to SOM formation. Yet, mechanisms by which minerals enhance the accumulation of microbial residues remain poorly understood. Here, we used 13 C-labeled glucose in a year-long incubation to trace microbial residue in sandy and silty soils. Across both soils, approximately 89% of retained microbial 13 C was recovered in the fine (<53 μm) mineral-associated organic matter (MAOM) pool. Within this pool, the light MAOM fraction, enriched in poorly crystalline Fe minerals, held 4.3 times more 13 C than the heavy, phyllosilicate-dominated MAOM fraction, despite accounting for only 17.2% of the total MAOM mass and 12.3% of the total soil mass. Along with 13 C enrichment, the light MAOM fraction showed greater abundance of N-containing groups, e.g., (amides and amino groups), indicative of microbial-derived compounds like proteins and amino sugars. Fe oxides in light MAOM from both soils were spatially dispersed. Microbial residue accumulation was greater in finer-textured silty soil. These findings demonstrate that mineral composition and texture jointly regulate microbial necromass accrual, highlighting light MAOM as a key pool for enhancing soil C storage.

13C isotope labeling↗

Carbon content of soil fractions varies with season, rainfall, and soil fertility across a lowland tropical moist forest gradient

Tropical forests contain some of the largest soil carbon (C) stocks on Earth, making them broadly relevant to terrestrial-climate feedbacks, yet our understanding of how their soil organic C (SOC) fractions vary over space and time is limited. We studied effects of season, fertility, and mean annual precipitation (MAP) on the C contents of soil fractions across 14 lowland forests in Panama. We measured free-debris, occluded-debris, and mineral-associated SOC fractions, as well as soluble C associated with each fraction. We hypothesized that mineral-associated SOC would be greatest in infertile, strongly weathered soils with large reactive mineral contents. We also hypothesized that the debris SOC fractions would accumulate during the dry season, reflecting seasonal increases in litterfall. To address this, we compared soil fractions in wet and dry seasons from fertile and infertile soils across a range of 1809 – 2864 mm MAP. The C content (mg C / g soil) of all soil fractions varied with fertility and MAP: specifically, free-debris SOC was greatest in wet, high-fertility soils, and occluded-debris SOC was greater in high-fertility than low-fertility soils. The mineral-associated SOC fraction, which contained the majority of bulk soil C, showed increasing C content with greater MAP in infertile sites, presumably driving similar spatial patterns in the bulk soil. Only the free-debris SOC fraction showed strong seasonal variation, increasing in mass during the dry season. Nitrogen behaved similarly to C. In summary, soil C contents increased with MAP in infertile sites but not fertile sites, driven by the mineral-associated SOC fraction. The dry season had greater free-debris SOC, but this seasonal trend was not apparent in bulk soil C, likely because of the small size of the free-debris SOC fraction. Furthermore, changes in the quantity and seasonality of precipitation, which are projected for tropical forests, might shift spatial and temporal patterns of soil C storage, which would in turn influence forest-climate feedbacks for this C-rich biome.

54 ENVIRONMENTAL SCIENCES↗

The influence of assimilating leaf area index in a land surface model on global water fluxes and storages

Vegetation plays a fundamental role not only in theenergy and carbon cycles but also in the global water balanceby controlling surface evapotranspiration (ET). Thus, accu-rately estimating vegetation-related variables has the poten-tial to improve our understanding and estimation of the dy-namic interactions between the water, energy, and carbon cy-cles. This study aims to assess the extent to which a land sur-face model (LSM) can be optimized through the assimilationof leaf area index (LAI) observations at the global scale. Twoobserving system simulation experiments (OSSEs) are per-formed to evaluate the efficiency of assimilating LAI into anLSM through an ensemble Kalman filter (EnKF) to estimateLAI, ET, canopy-interception evaporation (CIE), canopy wa-ter storage (CWS), surface soil moisture (SSM), and terres-trial water storage (TWS). Results show that the LAI dataassimilation framework not only effectively reduces errorsin LAI model simulations but also improves all the modeledwater flux and storage variables considered in this study (ET,CIE, CWS, SSM, and TWS), even when the forcing pre-cipitation is strongly positively biased (extremely wet con-ditions). However, it tends to worsen some of the modeledwater-related variables (SSM and TWS) when the forcingprecipitation is affected by a dry bias. This is attributed tothe fact that the amount of water in the LSM is conservative,and the LAI assimilation introduces more vegetation, whichrequires more water than what is available within the soil

Terrestrial Vegetation↗

CO2 Profiling System for CO2 Storage (a1-level)

The Southern Great Plains (SGP) carbon dioxide flux (CO2FLUX) measurement systems provide half-hour average fluxes of CO2, H2O (latent heat), sensible heat, and momentum. The systems use the eddy covariance technique, which computes the fluxes from the vertical wind speed in combination with the concentrations of CO2 and H2O, temperature, and horizontal wind speed, respectively. A 3D sonic anemometer obtains the wind components and the temperature, while an infrared gas analyzer measures CO2 and H2O. A sub-system also measures half-hour averages of radiation, meteorological, and soil measurements.

54 ENVIRONMENTAL SCIENCES↗

An Improved Analysis of Forest Carbon Dynamics using Data Assimilation

There are two broad approaches to quantifying landscape C dynamics - by measuring changes in C stocks over time, or by measuring fluxes of C directly. However, these data may be patchy, and have gaps or biases. An alternative approach to generating C budgets has been to use process-based models, constructed to simulate the key processes involved in C exchange. However, the process of model building is arguably subjective, and parameters may be poorly defined. This paper demonstrates why data assimilation (DA) techniques - which combine stock and flux observations with a dynamic model - improve estimates of, and provide insights into, ecosystem carbon (C) exchanges. We use an ensemble Kalman filter (EnKF) to link a series of measurements with a simple box model of C transformations. Measurements were collected at a young ponderosa pine stand in central Oregon over a 3-year period, and include eddy flux and soil C02 efflux data, litterfall collections, stem surveys, root and soil cores, and leaf area index data. The simple C model is a mass balance model with nine unknown parameters, tracking changes in C storage among five pools; foliar, wood and fine root pools in vegetation, and also fresh litter and soil organic matter (SOM) plus coarse woody debris pools. We nested the EnKF within an optimization routine to generate estimates from the data of the unknown parameters and the five initial conditions for the pools. The efficacy of the DA process can be judged by comparing the probability distributions of estimates produced with the EnKF analysis vs. those produced with reduced data or model alone. Using the model alone, estimated net ecosystem exchange of C (NEE)= -251 f 197g Cm-2 over the 3 years, compared with an estimate of -419 f 29gCm-2 when all observations were assimilated into the model. The uncertainty on daily measurements of NEE via eddy fluxes was estimated at 0.5gCm-2 day-1, but the uncertainty on assimilated estimates averaged 0.47 g Cm-2 day-1, and only exceeded 0.5gC m-2 day-1 on days where neither eddy flux nor soil efflux data were available. In generating C budgets, the assimilation process reduced the uncertainties associated with using data or model alone and the forecasts of NEE were statistically unbiased estimates. The results of the analysis emphasize the importance of time series as constraints. Occasional, rare measurements of stocks have limited use in constraining the estimates of other components of the C cycle. Long time series are particularly crucial for improving the analysis of pools with long time constants, such as SOM, woody biomass, and woody debris. Long-running forest stem surveys, and tree ring data, offer a rich resource that could be assimilated to provide an important constraint on C cycling of slow pools. For extending estimates of NEE across regions, DA can play a further important role, by assimilating remote-sensing data into the analysis of C cycles. We show, via sensitivity analysis, how assimilating an estimate of photosynthesis - which might be provided indirectly by remotely sensed data - improves the analysis of NEE.

Williams, Mathew↗

Young People's Burden: Requirement of Negative CO2 Emissions

Global temperature is a fundamental climate metric highly correlated with sea level, which implies that keeping shorelines near their present location requires keeping global temperature within or close to its preindustrial Holocene range. However, global temperature excluding short-term variability now exceeds +1 C relative to the 1880 - 1920 mean and annual 2016 global temperature was almost +1.3 C. We show that global temperature has risen well out of the Holocene range and Earth is now as warm as it was during the prior (Eemian) interglacial period, when sea level reached 6 - 9 m higher than today. Further, Earth is out of energy balance with present atmospheric composition, implying that more warming is in the pipeline, and we show that the growth rate of greenhouse gas climate forcing has accelerated markedly in the past decade. The rapidity of ice sheet and sea level response to global temperature is difficult to predict, but is dependent on the magnitude of warming. Targets for limiting global warming thus, at minimum, should aim to avoid leaving global temperature at Eemian or higher levels for centuries. Such targets now require "negative emissions", i.e., extraction of CO2 from the air. If phasedown of fossil fuel emissions begins soon, improved agricultural and forestry practices, including reforestation and steps to improve soil fertility and increase its carbon content, may provide much of the necessary CO2 extraction. In that case, the magnitude and duration of global temperature excursion above the natural range of the current interglacial (Holocene) could be limited and irreversible climate impacts could be minimized. In contrast, continued high fossil fuel emissions today place a burden on young people to undertake massive technological CO2 extraction if they are to limit climate change and its consequences. Proposed methods of extraction such as bioenergy with carbon capture and storage (BECCS) or air capture of CO2 have minimal estimated costs of USD 89 - 535 trillion this century and also have large risks and uncertain feasibility. Continued high fossil fuel emissions unarguably sentences young people to either a massive, implausible cleanup or growing deleterious climate impacts or both.

Hansen, James↗

Supply chain optimization of sustainable aviation fuel from carinata in the Southeastern United States

We report carinata is a purpose-grown oilseed feedstock for renewable fuels, including sustainable aviation fuel (SAF) that can replace conventional aviation fuel (CAF). Given carinata is a new crop in the Southeastern United States, it is crucial to analyze its sustainability from a supply chain perspective. This study developed a mixed-integer linear programming (MILP) model and simulated it for 20 years, starting from a farm (county-level data) and ending at the airport. About 2.06 million ha in Alabama, Florida, and Georgia combined were found suitable for carinata production. Given the three-year rotation period, about 0.69 million hectares can be cultivated annually, approximately 65% of which was in Georgia. About 2.4% of the combined SAF annual demand of four major airports (about 210 thousand t) in the study area is satisfied at that level of carinata cultivation. However, all available SAF was supplied to the Atlanta airport as this decision minimizes the supply chain cost. A total of 1343 storage units, one oil extraction mill, and one biorefinery were needed to meet the overall demand. We found that SW Georgia is the top supplier of carinata seeds. The unit cost of production and carbon intensity were estimated to be $\$$0.89 L -1 (or $\$$26.79 GJ -1 ) and 0.91 kg CO 2 e L -1 (or 27.28 kg CO 2 e GJ -1 ), respectively. This carbon intensity of carinata-based SAF was 67.8% lower than that of CAF. With variations included in SAF demand, yield, and soil carbon sequestration, carbon savings remained between 66.5% and 67.8%. Given the GHG advantage of SAF over CAF, there is justification for subsidies required to make SAF competitive.

10 SYNTHETIC FUELS↗