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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

AmeriFlux BR-Ma3 ZF3, Colosso farm

This is the AmeriFlux version of the carbon flux data for the site BR-Ma3 ZF3, Colosso farm. Site Description - The BR-Ma3, ZF3 tower, is deployed in a area from the Biological Dynamics of Forest Fragments Project (PDBFF, the portuguese acronym) in the city of Rio Preto da Eva (km 41 of BR-174), 64 km north of Manaus. BR-Ma3 is covered by forest fragment , pasture (Brachiaria humidicola) and secondary forest growth (resulted from an abandoned degraded pasture).

Araujo, Alessandro [Brazilian Agricultural Researc↗
DOE OSTI2026

AmeriFlux FLUXNET-1F BR-Ma3 ZF3, Colosso farm

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site BR-Ma3 ZF3, Colosso farm. This is the FLUXNET version of the carbon flux data for the site BR-Ma3 ZF3, Colosso farm produced by applying the standard ONEFlux (1F) software. Site Description - The BR-Ma3, ZF3 tower, is deployed in a area from the Biological Dynamics of Forest Fragments Project (PDBFF, the portuguese acronym) in the city of Rio Preto da Eva (km 41 of BR-174), 64 km north of Manaus. BR-Ma3 is covered by forest fragment , pasture (Brachiaria humidicola) and secondary forest growth (resulted from an abandoned degraded pasture).

Araujo, Alessandro [Brazilian Agricultural Researc↗
DOE OSTI2022

The Latent Dirichlet Allocation model applied to airborne LiDAR data: A case study on mapping forest degradation associated with fragmentation and fire in the Amazon region

1. LiDAR data are being increasingly used to provide a detailed characterization of the vertical profile of forests. This characterization enables the generation of new insights on the influence of environmental drivers and anthropogenic disturbances on forest structure as well as on how forest structure influences important ecosystem functions and services. Unfortunately, extracting information from LiDAR data in a way that enables the spatial visualization of forest structure, as well as its temporal changes, is challenging due to the high dimensionality of these data. 2. In this study, we show how the Latent Dirichlet Allocation model applied to LiDAR data (LidarLDA) can be used to identify forest structural types and how the relative abundance of these forest types changes throughout the landscape. The code to fit this model is made available through the open-source r package LidarLDA in github. We illustrate the use of LidarLDA both with simulated data and data from a large-scale fire experiment in the Brazilian Amazon region. 3. Using simulated data, we demonstrate that LidarLDA accurately identifies the number of forest types as well as their spatial distribution and absorptance probabilities. For the empirical data, we found that LidarLDA detects both landscape-level patterns in forest structure as well as the strong interacting effect of fire and forest fragmentation on forest structure based on the experimental fire plots. More specifically, LidarLDA reveals that proximity to forest edge exacerbates the impact of fires, and that burned forests remain structurally different from unburned areas for at least 7 years, even when burned only once. Importantly, LidarLDA generates insights on the 3D structure of forest that cannot be obtained using more standard approaches that just focus on top-of-the-canopy information (e.g. canopy height models based on LiDAR data). 4. By enabling the mapping of forest structure and its temporal changes, we believe that LidarLDA will be of broad utility to the ecological research community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The functional roles of species in metacommunities, as revealed by metanetwork analyses of bird–plant frugivory networks

Abstract Understanding how biodiversity and interaction networks change across environmental gradients is a major challenge in ecology. We integrated metacommunity and metanetwork perspectives to test species’ functional roles in bird–plant frugivory interactions in a fragmented forest landscape in Southwest China, with consequences for seed dispersal. Availability of fruit resources both on and under trees created vertical feeding stratification for frugivorous birds. Bird–plant interactions involving birds feeding only on‐the‐tree or both on and under‐the‐tree (shared) had a higher centrality and contributed more to metanetwork organisation than interactions involving birds feeding only under‐the‐tree. Moreover, bird–plant interactions associated with large‐seeded plants disproportionately contributed to metanetwork organisation and centrality. Consequently, on‐the‐tree and shared birds contributed more to metanetwork organisation whereas under‐the‐tree birds were more involved in local processes. We would expect that species’ roles in the metanetwork will translate into different conservation values for maintaining functioning of seed‐dispersal networks.

Li, Hai‐Dong↗
DOE OSTI2023

Integrated global assessment of the natural forest carbon potential

Forests are a substantial terrestrial carbon sink, but anthropogenic changes in land use and climate have considerably reduced the scale of this system. Remote-sensing estimates to quantify carbon losses from global forests are characterized by considerable uncertainty and we lack a comprehensive ground-sourced evaluation to benchmark these estimates. Here we combine several ground-sourced and satellite-derived approaches to evaluate the scale of the global forest carbon potential outside agricultural and urban lands. Despite regional variation, the predictions demonstrated remarkable consistency at a global scale, with only a 12% difference between the ground-sourced and satellite-derived estimates. At present, global forest carbon storage is markedly under the natural potential, with a total deficit of 226 Gt (model range = 151–363 Gt) in areas with low human footprint. Most (61%, 139 Gt C) of this potential is in areas with existing forests, in which ecosystem protection can allow forests to recover to maturity. The remaining 39% (87 Gt C) of potential lies in regions in which forests have been removed or fragmented. Although forests cannot be a substitute for emissions reductions, our results support the idea that the conservation, restoration and sustainable management of diverse forests offer valuable contributions to meeting global climate and biodiversity targets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Impacts of Degradation on Water, Energy, and Carbon Cycling of the Amazon Tropical Forests

Selective logging, fragmentation, and understory fires directly degrade forest structure and composition. However, studies addressing the effects of forest degradation on carbon, water, and energy cycles are scarce. Here, we integrate field observations and high-resolution remote sensing from airborne lidar to provide realistic initial conditions to the Ecosystem Demography Model (ED-2.2) and investigate how disturbances from forest degradation affect gross primary production (GPP), evapotranspiration (ET), and sensible heat flux (H). We used forest structural information retrieved from airborne lidar samples (13,500 ha) and calibrated with 817 inventory plots (0.25 ha) across precipitation and degradation gradients in the eastern Amazon as initial conditions to ED-2.2 model. Our results show that the magnitude and seasonality of fluxes were modulated by changes in forest structure caused by degradation. During the dry season and under typical conditions, severely degraded forests (biomass loss ≥66%) experienced water stress with declines in ET (up to 34%) and GPP (up to 35%) and increases of H (up to 43%) and daily mean ground temperatures (up to 6.5°C) relative to intact forests. In contrast, the relative impact of forest degradation on energy, water, and carbon cycles markedly diminishes under extreme, multiyear droughts, as a consequence of severe stress experienced by intact forests. Our results highlight that the water and energy cycles in the Amazon are driven by not only climate and deforestation but also the past disturbance and changes of forest structure from degradation, suggesting a much broader influence of human land use activities on the tropical ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Shifts in belowground processes along a temperate forest edge

Abstract Context Forests are increasingly fragmented, and as a result most forests in the United States are within one km of an edge. Edges change environmental conditions of the forest—especially radiation, roughness, temperature, and moisture—that can have consequences for plant productivity and ecosystem functions. However, edge effects on aboveground characteristics of plants and the environment are better understood relative to plant roots and soil in the belowground environment. Objectives Our main objectives were to determine if soil C pools and fluxes are higher at the edge relative to other landscape positions, and to understand how specific belowground processes contribute to bulk differences in pools and fluxes. Methods We measured environmental conditions, live and dead fine root traits, soil chemistry, and soil respiration along a 75 m transect from interior forest to meadow in Gaithersburg, MD. Results We observed differences in the soil chemical, biological and hydrological environment between the forest interior, edge and adjacent meadow. In some cases, the forest edge represented a mid-point in environmental or belowground characteristics between the forest interior and meadow ( e.g. , pH, C-to-N ratio [C:N], live fine root biomass, heterotrophic respiration), likely reflecting the change in litter type and quality associated with the transition from grass to woody species. In other cases, neighboring landscape positions were different from the forest edge, which was drier and had higher dead fine root biomass. Although soil C contents were not significantly different across landscape positions, there was a tendency towards higher average soil C content at the edge relative to other landscape positions, suggesting that increased C loss related to root decay and greater soil respiration at the edge relative to the forest interior may have been offset by increased C gain from high plant productivity and subsequent inputs to soil. Conclusions This research provides insight into how forest edge environments may differ from the interior and how concurrent processes above- and belowground may contribute to those differences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Modeling the distribution of the endangered Jemez Mountains salamander (Plethodon neomexicanus) in relation to geology, topography, and climate

The Jemez Mountains salamander (Plethodon neomexicanus; hereafter JMS) is an endangered salamander restricted to the Jemez Mountains in north-central New Mexico, United States. This strictly terrestrial and lungless species requires moist surface conditions for activities such as mating and foraging. Threats to its current habitat include fire suppression and ensuing severe fires, changes in forest composition, habitat fragmentation, and climate change. Forest composition changes resulting from reduced fire frequency and increased tree density suggest that its current aboveground habitat does not mirror its historically successful habitat regime. However, because of its limited habitat area and underground behavior, we hypothesized that geology and topography might play a significant role in the current distribution of the salamander. We modeled the distribution of the JMS using a machine learning algorithm to assess how geology, topography, and climate variables influence its distribution. The best habitat suitability model indicates that geology type and maximum winter temperature (November to March) were most important in predicting the distribution of the salamander (23.5% and 50.3% permutation importance, respectively). Minimum winter temperature was also an important variable (21.4%), suggesting this also plays a role in salamander habitat. Our habitat suitability map reveals low uncertainty in model predictions, and we found slight discrepancies between the designated critical habitat and the most suitable areas for the JMS. Because geological features are important to its distribution, we recommend that geological and topographical data are considered, both during survey design and in the description of localities of JMS records once detected.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

The erosion of biodiversity and biomass in the Atlantic Forest biodiversity hotspot

Tropical forests are being deforested worldwide, and the remaining fragments are suffering from biomass and biodiversity erosion. Quantifying this erosion is challenging because ground data on tropical biodiversity and biomass are often sparse. Here, we use an unprecedented dataset of 1819 field surveys covering the entire Atlantic Forest biodiversity hotspot. We show that 83-85% of the surveys presented losses in forest biomass and tree species richness, functional traits, and conservation value. On average, forest fragments have 25-32% less biomass, 23-31% fewer species, and 33, 36, and 42% fewer individuals of late-successional, large-seeded, and endemic species, respectively. Biodiversity and biomass erosion are lower inside strictly protected conservation units, particularly in large ones. We estimate that biomass erosion across the Atlantic Forest remnants is equivalent to the loss of 55-70 thousand km 2 of forests or US$2.3-2.6 billion in carbon credits. These figures have direct implications on mechanisms of climate change mitigation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Degradation and deforestation increase the sensitivity of the Amazon Forest to climate extremes

About 40% of the Brazilian Amazon has been deforested or suffered changes in forest structure through degradation (selective logging, fires, and fragmentation). The impact of forest degradation on the forest’s sensitivity to climate extremes has not been fully explored because of a lack of data and the complex interplay of forest structure and climate drivers. Here, we combined forest structure data from 545 airborne lidar transects (375 ha each) across the Brazilian Amazon with the Ecosystem Demography Model (ED2). We explore the forest’s functional response to near-present (1981–2019) climate extremes under observed forest structure from lidar ( Control ) and two forest structure change scenarios: (1) forest recovery by excluding all future deforestation and degradation ( Recovery ) and (2) expansion of selective logging and deforestation ( Degradation ). Using the Control simulation, we found a close and positive association between local forest aboveground biomass and the predicted gross primary productivity (GPP) and evapotranspiration (ET). Moreover, both GPP and ET respond negatively to extremes in vapor pressure deficit and downwelling shortwave irradiance in degraded forests in Eastern and Southern Amazon, indicating high sensitivity to droughts. Locally high-biomass forest patches showed little or no negative response of GPP and ET to extreme drought conditions whereas low-biomass forest patches in the same locations—typically degraded forest canopies—responded negatively to higher moisture stress. The results from the Recovery scenario showed similar results to simulations with observed structure; however, under the Degradation scenario, low-biomass forest patches became more abundant, resulting in more regions where GPP and ET are negatively impacted by hot drought conditions according to the ED2 model. Our results suggest that local forest structure is a critical determinant of an ecosystem’s response to climate variability, and that the loss of canopy trees in the Amazon through forest degradation could increase and expand forest vulnerability to droughts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Urbanization and edge effects interact to drive mutualism breakdown and the rise of unstable pathogenic communities in forest soil

Temperate forests are threatened by urbanization and fragmentation, with over 20% (118,300 km 2 ) of U.S. forest land projected to be subsumed by urban land development. We leveraged a unique, well-characterized urban-to-rural and forest edge-to-interior gradient to identify the combined impact of these two land use changes—urbanization and forest edge creation—on the soil microbial community in native remnant forests. We found evidence of mutualism breakdown between trees and their fungal root mutualists [ectomycorrhizal (ECM) fungi] with urbanization, where ECM fungi colonized fewer tree roots and had less connectivity in soil microbiome networks in urban forests compared to rural forests. However, urbanization did not reduce the relative abundance of ECM fungi in forest soils; instead, forest edges alone led to strong reductions in ECM fungal abundance. At forest edges, ECM fungi were replaced by plant and animal pathogens, as well as copiotrophic, xenobiotic-degrading, and nitrogen-cycling bacteria, including nitrifiers and denitrifiers. Urbanization and forest edges interacted to generate new “suites” of microbes, with urban interior forests harboring highly homogenized microbiomes, while edge forest microbiomes were more heterogeneous and less stable, showing increased vulnerability to low soil moisture. When scaled to the regional level, we found that forest soils are projected to harbor high abundances of fungal pathogens and denitrifying bacteria, even in rural areas, due to the widespread existence of forest edges. Our results highlight the potential for soil microbiome dysfunction—including increased greenhouse gas production—in temperate forest regions that are subsumed by urban expansion, both now and in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Monthly averages of ED2 model simulations initialized with airborne lidar structure, Jan 1981-Dec 2018, Brazilian Amazon

Deforestation and forest degradation (selective logging, fires, fragmentation) have impacted nearly 40% of the original extent of the Brazilian Amazon, and have markedly impacted forest structure across the region. To date, few studies analysed how shifts in forest structure from degradation influence the forest sensitivity to climate extremes, because of the complex interactions between forest structure and micro-environmental conditions. To address this knowledge gap, we carried out a series of simulations across the Brazilian Amazon using the Ecosystem Demography Model (ED2), using observed forest structure derived from 541 airborne lidar transects (375 ha each) and two scenarios representing forest recovery and expansion of degradation to investigate how shifts in forest structure impact ecosystem function under near-average and extreme climate conditions, as part of the manuscript Longo et al 2025 "Degradation and Deforestation Increase the Sensitivity of the Amazon Forest to Climate Extremes". This dataset provides the output results from the ED2 model simulations for the three simulations at monthly time scales, in NetCDF format. For all simulations, we used bias-corrected hourly reanalyses (WFDE5) for most meteorological drivers, except for precipitation, which was obtained from CHIRPS. The meteorological drivers used in the study span 38 years (Jan 1981–Dec 2018). The output results correspond to the last 38 years of simulation (one full cycle of meteorological drivers), in which ED2 simulations used static stand structure (i.e., the forest structure was held constant). The following files are provided:ED2_emean_Global_R004_BrAmaz_s1c0t0l0f0.nc. This corresponds to the Control simulation. The forest structure was obtained from the airborne lidar.ED2_emean_Global_R005_BrAmaz_s1c0t1l1f0.nc. This corresponds to the Degraded simulation. The forest structure was obtained from a spin-up simulation initialized with airborne lidar and a scenario that expanded deforestation and selective logging across the Amazon.ED2_emean_Global_R006_BrAmaz_s1c0t1l0f0.nc. This corresponds to the Recovery simulation. The forest structure was obtained from a spin-up simulation initialized with airborne lidar and a scenario that completely halted deforestation and degradation, allowing degraded forests to recover for 38 years.We also provide file ED2_zones_R004_BrAmaz_s1c0t0l0f0.nc, which classifies each grid cell into zones used in the reference manuscript: 1: Southeast. 2: South. 3: West. 4: Central. 5: Northeast. 6: North. 7: Northwest". Index 0 corresponds to grid cells excluded from sub-region analyses because they were dominated by flooded forests, deforestation, and naturally non-forest vegetation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Raccoon densities across four land cover types in the southeastern United States

Raccoons (Procyon lotor) are the primary reservoir for rabies virus in eastern North America. Management of rabies in raccoons is achieved primarily with the use of oral rabies vaccination (ORV) and effective ORV bait densities are determined in part by the densities of raccoons. Decisions regarding ORV bait densities, however, are limited by an incomplete understanding of raccoon densities across the spectrum of landscapes they occupy. We carried out a mark-recapture study of raccoons on the Savannah River Site in South Carolina, USA, from 2017–2019, to develop sex- and landscape-specific raccoon density estimates across 4 rural land cover types in the southeastern United States: bottomland hardwood, riparian forest, isolated wetland, and upland pine (Pinus spp.). We captured 404 unique raccoons 773 times over the 3-year trapping period. Estimated densities were 5.44 ± 0.37 (SE) animals/km 2 in bottomland hardwood forest, 2.62 ± 0.32 animals/km 2 in riparian forest, 2.19 ± 0.29 animals/km 2 in isolated wetlands, and 2.14 ± 0.23 animals/km 2 in upland pine. Densities were significantly higher in bottomland hardwood than all other land cover types, whereas densities among the remaining cover types were similar. These patterns are likely the result of landscape fragmentation and configuration, with riparian forests typically embedded in a matrix of less suitable cover types, leading to low densities despite presumably high resource availability. There were higher densities of males than females in every cover type except upland pine, where the sex ratio was balanced. Densities on our site were low compared to other rural areas, which likely results from the lack of human influence in terms of agriculture or development. The financial cost of baiting for ORV distribution may be reduced by considering the comparatively low densities of raccoons in these rural landscapes in the southeastern United States.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Effects of forest degradation classification on the uncertainty of aboveground carbon estimates in the Amazon

Tropical forests are critical for the global carbon budget, yet they have been threatened by deforestation and forest degradation by fire, selective logging, and fragmentation. Existing uncertainties on land cover classification and in biomass estimates hinder accurate attribution of carbon emissions to specific forest classes. In this study, we used textural metrics derived from PlanetScope images to implement a probabilistic classification framework to identify intact, logged and burned forests in three Amazonian sites. We also estimated biomass for these forest classes using airborne lidar and compared biomass uncertainties using the lidar-derived estimates only to biomass uncertainties considering the forest degradation classification as well. Our classification approach reached overall accuracy of 0.86, with accuracy at individual sites varying from 0.69 to 0.93. Logged forests showed variable biomass changes, while burned forests showed an average carbon loss of 35%. We found that including uncertainty in forest degradation classification significantly increased uncertainty and decreased estimates of mean carbon density in two of the three test sites. Our findings indicate that the attribution of biomass changes to forest degradation classes needs to account for the uncertainty in forest degradation classification. By combining very high-resolution images with lidar data, we could attribute carbon stock changes to specific pathways of forest degradation. This approach also allows quantifying uncertainties of carbon emissions associated with forest degradation through logging and fire. Both the attribution and uncertainty quantification provide critical information for national greenhouse gas inventories.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Assessing impacts of selective logging on water, energy, and carbon budgets and ecosystem dynamics in Amazon forests using the Functionally Assembled Terrestrial Ecosystem Simulator

Abstract. Tropical forest degradation from logging, fire, and fragmentation not only alters carbon stocks and carbon fluxes, but also impacts physical land surface properties such as albedo and roughness length. Such impacts are poorly quantified to date due to difficulties in accessing and maintaining observational infrastructures, as well as the lack of proper modeling tools for capturing the interactions among biophysical properties, ecosystem demography, canopy structure, and biogeochemical cycling in tropical forests. As a first step to address these limitations, we implemented a selective logging module into the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) by mimicking the ecological, biophysical, and biogeochemical processes following a logging event. The model can specify the timing and aerial extent of logging events, splitting the logged forest patch into disturbed and intact patches; determine the survivorship of cohorts in the disturbed patch; and modifying the biomass and necromass (total mass of coarse woody debris and litter) pools following logging. We parameterized the logging module to reproduce a selective logging experiment at the Tapajós National Forest in Brazil and benchmarked model outputs against available field measurements. Our results suggest that the model permits the coexistence of early and late successional functional types and realistically characterizes the seasonality of water and carbon fluxes and stocks, the forest structure and composition, and the ecosystem succession following disturbance. However, the current version of FATES overestimates water stress in the dry season and therefore fails to capture seasonal variation in latent and sensible heat fluxes. Moreover, we observed a bias towards low stem density and leaf area when compared to observations, suggesting that improvements are needed in both carbon allocation and establishment of trees. The effects of logging were assessed by different logging scenarios to represent reduced impact and conventional logging practices, both with high and low logging intensities. The model simulations suggest that in comparison to old-growth forests the logged forests rapidly recover water and energy fluxes in 1 to 3 years. In contrast, the recovery times for carbon stocks, forest structure, and composition are more than 30 years depending on logging practices and intensity. This study lays the foundation to simulate land use change and forest degradation in FATES, which will be an effective tool to directly represent forest management practices and regeneration in the context of Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Managing ecosystem damage from extreme events

Large disturbances to ecosystems can severely impact the stability of a region's natural resources, habitats, and outdoor recreation. Because extreme events can be large and relatively infrequent, they test institutional capacity to support recovery and restoration. Here, when hurricanes and other large-scale disturbances like wildfires occur, much of the impacted landscape receives little to no active management. Ecosystems are often allowed to either recover or transition without much direct intervention, and successional dynamics are sometimes altered by novel invasive species, management history, or other environmental changes. Recovery and restoration are especially challenging for landscapes with highly fragmented private ownership, such as the forests of the eastern US. Acting alone, non-industrial private forest landowners have little capacity to effectively respond to unexpected forest loss and to oversee forest recovery, as the scale of actions needed after extreme events may require cooperation across ownerships or jurisdictions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Tidal–hydrological dynamics of water temperature across freshwater forested wetlands on the northeastern Pacific coast

Abstract Tidal freshwater forests were once extensive across temperate coastlines, but loss and fragmentation have made estimation of their ecosystem functions challenging. We measured water temperature for 2 years in three Sitka spruce tidal forests, a restoration site, and an adjacent emergent marsh on the Columbia River, Washington, United States. We assessed spatial variability of water temperature within sites including the effects of hydrology, differences among bay and tributary tidal forests, and differences between the tidal forests and the mainstem Columbia, the restoration site, and the emergent marsh. The tidal forests nearest to the bay had lower interior water temperatures than their channel confluences by up to 2.5°C (weekly median temperature) and 2.0°C (weekly maximum temperature), with most cooling occurring during the low‐flow months of July–September. Tributary sites had maximum temperatures up to 1.9°C cooler than bay sites and 4.2°C cooler than the mainstem. Temperatures in the two bay sites decreased by −0.16°C/100 m and −0.07°C/100 m, on average. The restoration site had the smallest within‐site temperature gradient. Differences in maximum temperatures were greatest when tidal range was low, while higher tidal ranges were associated with warmer and more variable site interiors relative to their confluences. These results suggest that water temperatures in these tidal forests can provide temperature refugia for cold water biota including salmon.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Decision Support System

Forest-based value chains involve decisions that begin at the landscape level and extend through processing, product manufacturing, and end-use markets. However, these decisions are often made independently across sectors, with limited visibility into how upstream resource conditions, incentives, and land management choices influence downstream production systems. In forested regions of the United States, wildfire risk, fragmented ownership, and uncertain markets for low-value residues complicate efforts to align extraction, processing, and utilization decisions. Without tools that link these stages, stakeholders may overlook opportunities to improve resource utilization or inadvertently shift impacts elsewhere in the value chain. This repository introduces a decision support system (DSS) that applies a system-impact-analysis approach to forest biomass residues and co-products. The framework integrates forest inventory data, geospatial resource assessments, and economic modeling to evaluate how biomass extraction decisions influence downstream product pathways. By linking regional feedstock avail- ability with market incentives and processing options—such as fuels, wood products, or soil amendments like biochar—the tool allows decision-makers to compare value chain outcomes across multiple utilization strategies.

Davis, Maggie [Oak Ridge National Laboratory (ORNL↗