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At least 415 records · Page 23

Colorado Front Range Disasters: Understanding the Impact of Forest Management on the Cameron Peak and CalWood Fire

Along the Colorado Front Range, forest management has gained significant attention due to uncharacteristically large fires that burned late in 2020. The Cameron Peak Fire (largest in Colorado recorded history) and the CalWood Fire collectively burned an estimated 219,019 acres from August through December of 2020. Project partners at the Coalition for the Poudre River Watershed, Colorado State Forest Service, Ben Delatour Scout Ranch, The Nature Conservancy, Colorado Forest Restoration Institute, and Colorado State University were interested in understanding the effectiveness of previous forest treatments in reducing burn severity within the Cameron Peak Fire and the CalWood Fire. We first collated a forest treatment dataset from pre-existing datasets by reclassifying over 29,000 treatments, which occurred across the Northern Colorado Front Range between 1970-2020. Secondly, we mapped three burn severity indices using Landsat 8 OLI and Sentinel-2 MSI Earth observations and compared them to soil burn severity field data. Thirdly, a total of 35 topographic, disturbance, forest structure, and treatment predictor variables were generated across the fires. Finally, we assessed relationships between these predictor variables and burn severity using the random forest algorithm. Model results indicate that the primary drivers of burn severity were elevation and distance to treatment edge for the Cameron Peak Fire and fire area and forest canopy cover for the CalWood Fire. Further analysis of these variables paired with field data is necessary to understand the relationship between burn severity and treatments to guide future restoration efforts, improve forest resiliency, and mitigate fire risks.

Neal Swayze↗

Microbial community data from throughfall exclusion experiment: Metadata, SI, community composition, LefSe, and FunGuilR data tables from PARCHED Panama tropical forest soils, 2024-2025

Soil contains more carbon (C) than terrestrial vegetation and the atmosphere combined, with some of the largest terrestrial C stocks in tropical rainforests. Soil microbes decompose organic matter, playing a vital role in the storage or loss of soil C. With climate change, drought conditions are predicted to increase in many tropical regions, including both chronic drying and extended drought, potentially influencing these processes. This project explored the effects of chronic and seasonal drying on soil microbial communities across four distinct tropical forests in a long-term drying experiment. We investigated the effects of a chronic drying manipulation on soil microbial community abundance and variation across different forests and seasons. We also compared findings with previously published data from these forests after short-term drying. This project used soils from a long-term drying experiment established in 2018 across four seasonal lowland forests in Panama. Soils were collected from 0 – 10 cm depths during three seasonal periods in control and drying plots in 2024 and 2025 from a total of 32 plots (n = 4 per forest per treatment). The forests varied in baseline rainfall and soil fertility. We calculated alpha and beta diversity indices and compared taxonomic community composition. We found significant biogeographic variation in microbial diversity and taxonomy, with significant differences across the forests and significant effects of the drying treatment. Metadata and sample IDs are within Metadata_16S.csv and Metadata_ITS.csv. Relative abundance tables of every sample at every season are shown in the Excel workbooks 16S Relative Abundance.xlsx and ITS Relative Abundance.xlsx. They are then also shown in CSV files by each taxonomic level. Linear discriminant analysis effect size (LefSe) tables are shown for the full 16S and ITS datasets (n = 96), subsets for every site at every season (n = 8), and then for the forests with each plot merged by season (n = 8). FunGuildR data table of ITS data is uploaded.

Bacteria↗

Effects of Topography on Tropical Forest Structure Depend on Climate Context

Topography affects abiotic conditions which can influence the structure, function, and dynamics of ecological communities. An increasing number of studies have demonstrated biological consequences of fine-scale topographic heterogeneity but we have a limited understanding of how We merged high-resolution (1 sq. meter) data on topography and canopy height derived from airborne lidar with ground-based data from 15 forest plots in Puerto Rico distributed along a precipitation gradient spanning ca. 800 to 3,500 mm yr(exp -1). Ground-based data included species composition, estimated above-ground biomass (AGB), and two key functional traits (wood density and leaf mass per area, LMA) that reflect resource-use strategies and a trade-off between hydraulic safety and hydraulic efficiency. We used hierarchical Bayesian models to evaluate how the interaction between topography climate is related to metrics of forest structure (i.e., canopy height and AGB), as well as taxonomic and functional alpha- and beta-diversity. Fine-scale topography (characterized with the topographic wetness index, TWI) significantly affected forest structure and the strength (and in some cases direction) of these effects varied across the precipitation gradient. In all plots, canopy height increased with topographic wetness but the effect was much stronger in dry compared to wet forest plots. In dry forest plots, topographically wetter microsites also had higher levels of AGB but in wet forest plots, topographically drier microsites had higher AGB. Fine-scale topography influenced functional composition but had only weak or non-significant effects on taxonomic and functional alpha- and beta-diversity. For instance, community-weighted wood density followed a similar pattern to AGB across plots. We also found a marginally significant association between variation of wood density and topographic heterogeneity that depended on climate context. Synthesis: The effects of fine-scale topographic heterogeneity on tropical forest structure and composition depend on the climate context. Our study demonstrates how a stronger integration of topographic heterogeneity across precipitation gradients could improve estimates of forest structure and biomass, and may provide insight to the ways that topography might mediate species responses to drought and climate change.

Tropical dry forest↗

Exploring Natural and Social Drivers of Forest Degradation in Post-Soviet Georgia

The Caucasus Mountains harbor high concentrations of endemic species and provide an abundance of ecosystem services yet are significantly understudied compared to other ecosystems in Eurasia. In the country of Georgia, at the heart of the Caucasus region, forest degradation has been the largest land change process over the last thirty years. The prevailing narrative is that legal and illegal cutting of trees for fuelwood is primarily responsible for this process. Yet, since independence from the Soviet Union in 1991, the country has undergone rapid socioeconomic and institutional changes which have not been explored as drivers of forest change. We combine newly available land-cover change estimates, Georgian statistical data, and historical institutional change data to examine socioeconomic drivers of forest degradation. Our analysis controls for concurrent changes in climate that would affect degradation and examines variation at the regional (state) level from 2011 to 2019, as well as at the national level from 1987 to 2019. We find that higher winter temperature and drought are associated with higher degradation at the regional scale, while major institutional changes and drought are associated with higher forest degradation at the national level. Access to natural gas, the major energy alternative to fuelwood, had no significant association with degradation. Our results challenge the narrative that poverty and a lack of alternative energy infrastructure drive forest degradation and suggest that government policies banning household fuelwood cutting, including the new Forest Code of 2020, may not reduce forest degradation. Given these results, improved data on wood harvesting and more research on the commercial drivers of degradation and their links to economic and political reforms is needed to better inform forest policy in the region, especially given ongoing risks from climate change.

Institutions↗

Northern forest winters have lost cold, snowy conditions that are important for ecosystems and human communities

Winter is an understudied but key period for the socioecological systems of northeastern North American forests. A growing awareness of the importance of the winter season to forest ecosystems and surrounding communities has inspired several decades of research, both across the northern forest and at other mid- and high-latitude ecosystems around the globe. Despite these efforts, we lack a synthetic understanding of how winter climate change may impact hydrological and biogeochemical processes and the social and economic activities they support. Here, we take advantage of 100 years of meteorological observations across the northern forest region of the northeastern United States and eastern Canada to develop a suite of indicators that enable a cross-cutting understanding of (1) how winter temperatures and snow cover have been changing and (2) how these shifts may impact both ecosystems and surrounding human communities. We show that cold and snow covered conditions have generally decreased over the past 100 years. These trends suggest positive outcomes for tree health as related to reduced fine root mortality and nutrient loss associated with winter frost but negative outcomes as related to the northward advancement and proliferation of forest insect pests. In addition to effects on vegetation, reductions in cold temperatures and snow cover are likely to have negative impacts on the ecology of the northern forest through impacts on water, soils, and wildlife. The overall loss of coldness and snow cover may also have negative consequences for logging and forest products, vector-borne diseases, and human health, recreation, and tourism, and cultural practices, which together represent important social and economic dimensions for the northern forest region. These findings advance our understanding of how our changing winters may transform the socioecological system of a region that has been defined by the contrasting rhythm of the seasons. Our research also identifies a trajectory of change that informs our expectations for the future as the climate continues to warm.

54 ENVIRONMENTAL SCIENCES↗

Reviving the carbon sink: The influence of moderate wind disturbance in a secondary temperate mixed forest

Global forests are increasingly exposed to climate-driven perturbations, which may in turn alter their climate mitigation potential. As tropical cyclones expand poleward due to climate warming, wind disturbances in temperate forests have become increasingly frequent. The consequences of moderate wind disturbances remain poorly understood, hindering efforts to quantify their role in the global carbon cycle. Here, we used 16 years of continuous eddy covariance and biometric measurements to investigate the impacts of moderate wind disturbances on the structure and carbon sink dynamics of a temperate forest in Northeast China. Following Typhoon Maysak in 2020, the mortality of large trees (particularly the aging pioneer species) increased ninefold, whereas that of small trees decreased by nearly half. Both stand basal area and leaf area index were reduced between 2019 and 2023, with aging pioneer tree species being more vulnerable than mid-to-late species to wind disturbances. Shifts in species composition altered the environmental sensitivity of forest carbon sink function. Unexpectedly, wind disturbances reversed the declining trends in net ecosystem production and ecosystem carbon use efficiency of this secondary forest. A novel composite structural indicator—the standardized leaf area index (the maximum leaf area supported by per basal area of the stand)—provided robust predictions (R 2 > 0.4) of carbon sink dynamics throughout the study period. The selective removal of less efficient pioneer trees accelerated succession and reversed the aging-related decline in forest carbon sink strength and carbon use efficiency. In conclusion, these findings highlight the potential role of moderate wind disturbances in enhancing forest carbon sink function and offer a framework for understanding, assessing, and predicting forest carbon dynamics under increasing disturbance frequencies driven by climate change.

Carbon sink↗

Leaf area density from airborne LiDAR: Comparing sensors and resolutions in a temperate broadleaf forest ecosystem

Forest processes that play an essential role in carbon sequestration, such as light use efficiency, photosynthetic capacity, and trace gas exchange, are closely tied to the three-dimensional structure of forest canopies. However, the vertical distribution of leaf traits is not uniform; leaves at varying vertical positions within the canopy are physiologically unique due to differing light and environmental conditions, which leads to higher carbon storage than if light conditions were constant throughout the canopy. Due to this within-canopy variation, three-dimensional structural traits are critical to improving our estimates of global carbon cycling and storage by Earth system models and to better understanding the effects of disturbances on carbon sequestration in forested ecosystems. In this study, we describe a reproducible and open-source methodology using the R programming language for estimating leaf area density (LAD; the total leaf area per unit of volume) from airborne LiDAR. Using this approach, we compare LAD estimates at the Smithsonian Environmental Research Center in Maryland, USA, from two airborne LiDAR systems, NEON AOP and NASA G-LiHT, which differ in survey and instrument specifications, collections goals, and laser pulse densities. Furthermore, we address the impacts of the spatial scale of analysis as well as differences in canopy penetration and pulse density on LAD and leaf area index (LAI) estimates, while offering potential solutions to enhance the accuracy of these estimates. LAD estimates from airborne LiDAR can be used to describe the three-dimensional structure of forests across entire landscapes. Furthermore, this information can help inform forest management and conservation decisions related to the estimation of aboveground biomass and productivity, the response of forests to large-scale disturbances, the impacts of drought on forest health, the conservation of bird habitat, as well as a host of other important forest processes and responses.

54 ENVIRONMENTAL SCIENCES↗

Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (≤ 5 m) from very-high-resolution (VHR) data. Here we assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severity was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal — pre- and post-fire event — WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). Lastly, this work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the < 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.

54 ENVIRONMENTAL SCIENCES↗

A legacy of fire emerges from multiple disturbances to most shape microbial and nitrogen dynamics in a deciduous forest

Healthy forests are vital components of terrestrial ecosystems for their raw materials, high biodiversity, cycling of nutrients, and potential to sequester carbon. However, these ecosystems are sensitive to disturbances, and anthropogenic activities pose a serious threat to forest ecosystems globally. For example, human activities have dramatically altered multiple historical disturbance regimes in forests, including suppressing fire, increasing the density of large herbivores, and reducing the size of canopy gaps, among other disturbances. Such disturbances can have dramatic impacts on microbially-mediated forest soil functions, but more research is needed to determine the collective impacts of these disturbances. In this study, we investigated the interactive effects of disturbances, namely the legacies of fire, large herbivore densities, and canopy gap creation, in a deciduous forest soil. We determined that forest floor and mineral soil carbon and nitrogen pools were shaped by multiple disturbances, but fire was more influential than the other disturbances. The abundance of several functionally-relevant microbial taxa were significantly impacted by fire, and the effect was more pronounced in the mineral soil than in the forest floor. Together, these findings demonstrate that multiple disturbances, especially a legacy of fire, exerts long-term control over soil carbon, nitrogen and microbial dynamics in a deciduous forest system.

59 BASIC BIOLOGICAL SCIENCES↗

Characterizing the vertical structure of forests in the Brazilian Amazon

Little is known about the structure of tropical forests despite its critical role in the provisioning of ecosystem services. Here we assess the vertical structure of forests in the Brazilian Amazon with a large-scale airborne LiDAR dataset. We show that fire has greater impact in the lowest forest strata, differently from selective logging and windthrow. We also find that secondary forests quickly recover or even exceed reference areas at the 1-10 m height stratum but that full recovery for the 20-30 m height stratum has not been achieved even after 35 years. Our modeling results suggest that proximity to roads, elevation, precipitation, soil pH, and proportion of sand in the soil are the most important predictors of forest structure. Finally, we identify 5 forest structural types (FSTs) and use them to visualize the spatial distribution of forest structure. This study provides important information for forest monitoring, management, and conservation.

Biogeography↗

Methane production and emissions in trees and forests

Forest ecosystem methane (CH 4 ) research has focused on soils, but trees are also important sources and sinks in forest CH 4 budgets. Living and dead trees transport and emit CH 4 produced in soils; living trees and dead wood emit CH 4 produced inside trees by microorganisms; and trees produce CH 4 through an abiotic photochemical process. Here, we review the state of the science on the production, consumption, transport, and emission of CH 4 by living and dead trees, and the spatial and temporal dynamics of these processes across hydrologic gradients inclusive of wetland and upland ecosystems. Emerging research demonstrates that tree CH 4 emissions can significantly increase the source strength of wetland forests, and modestly decrease the sink strength of upland forests. Scaling from stem or leaf measurements to trees or forests is limited by knowledge of the mechanisms by which trees transport soil-produced CH 4 , microbial processes produce and oxidize CH 4 inside trees, a lack of mechanistic models, the diffuse nature of forest CH 4 fluxes, complex overlap between sources and sinks, and extreme variation across individuals. Understanding the complex processes that regulate CH 4 source–sink dynamics in trees and forests requires cross-disciplinary research and new conceptual models that transcend the traditional binary classification of wetland vs upland forest.

59 BASIC BIOLOGICAL SCIENCES↗

Large Trees Dominate Carbon Storage in Forests East of the Cascade Crest in the United States Pacific Northwest

Large-diameter trees store disproportionally massive amounts of carbon and are a major driver of carbon cycle dynamics in forests worldwide. In the temperate forests of the western United States, proposed changes to Forest Plans would significantly weaken protections for a large portion of trees greater than 53 cm (21 inches) in diameter (herein referred to as “large-diameter trees”) across 11.5 million acres (~4.7 million ha) of National Forest lands. This study is among the first to report how carbon storage in large trees and forest ecosystems would be affected by a proposed policy. We examined the proportion of large-diameter trees on National Forest lands east of the Cascade Mountains crest in Oregon and Washington, their contribution to overall aboveground carbon (AGC) storage, and the potential reduction in carbon stocks resulting from widespread harvest. We analyzed forest inventory data collected on 3,335 plots and found that large trees play a major role in the accumulated carbon stock of these forests. Tree AGC (kg) increases sharply with tree diameter at breast height (DBH; cm) among five dominant tree species. Large trees accounted for 2.0 to 3.7% of all stems (DBH ≥ 1” or 2.54 cm) among five tree species; but held 33 to 46% of the total AGC stored by each species. Pooled across the five dominant species, large trees accounted for 3% of the 636,520 trees occurring on the inventory plots but stored 42% of the total AGC. A recently proposed large-scale vegetation management project that involved widespread harvest of large trees, mostly grand fir, would have removed ~44% of the AGC stored in these large-diameter trees, and released a large amount of carbon dioxide to the atmosphere. Given the urgency of keeping additional carbon out of the atmosphere and continuing carbon accumulation from the atmosphere to protect the climate system, it would be prudent to continue protecting ecosystems with large trees for their carbon stores, and also for their co-benefits of habitat for biodiversity, resilience to drought and fire, and microclimate buffering under future climate extremes.

21-inch rule↗

An Automated Approach to Map the History of Forest Disturbance from Insect Mortality and Harvest with Landsat Time-Series Data

Forests contain a majority of the aboveground carbon (C) found in ecosystems, and understanding biomass lost from disturbance is essential to improve our C-cycle knowledge. Our study region in the Wisconsin and Minnesota Laurentian Forest had a strong decline in Normalized Difference Vegetation Index (NDVI) from 1982 to 2007, observed with the National Ocean and Atmospheric Administration's (NOAA) series of Advanced Very High Resolution Radiometer (AVHRR). To understand the potential role of disturbances in the terrestrial C-cycle, we developed an algorithm to map forest disturbances from either harvest or insect outbreak for Landsat time-series stacks. We merged two image analysis approaches into one algorithm to monitor forest change that included: (1) multiple disturbance index thresholds to capture clear-cut harvest; and (2) a spectral trajectory-based image analysis with multiple confidence interval thresholds to map insect outbreak. We produced 20 maps and evaluated classification accuracy with air-photos and insect air-survey data to understand the performance of our algorithm. We achieved overall accuracies ranging from 65% to 75%, with an average accuracy of 72%. The producer's and user's accuracy ranged from a maximum of 32% to 70% for insect disturbance, 60% to 76% for insect mortality and 82% to 88% for harvested forest, which was the dominant disturbance agent. Forest disturbances accounted for 22% of total forested area (7349 km2). Our algorithm provides a basic approach to map disturbance history where large impacts to forest stands have occurred and highlights the limited spectral sensitivity of Landsat time-series to outbreaks of defoliating insects. We found that only harvest and insect mortality events can be mapped with adequate accuracy with a non-annual Landsat time-series. This limited our land cover understanding of NDVI decline drivers. We demonstrate that to capture more subtle disturbances with spectral trajectories, future observations must be temporally dense to distinguish between type and frequency in heterogeneous landscapes.

Forest↗

Multiple Pathways of Commodity Crop Expansion in Tropical Forest Landscapes

Commodity crop expansion, for both global and domestic urban markets, follows multiple land change pathways entailing direct and indirect deforestation, and results in various social and environmental impacts. Here we compare six published case studies of rapid commodity crop expansion within forested tropical regions. Across cases, between 1.7 percent and 89.5 percent of new commodity cropland was sourced from forestlands. Four main factors controlled pathways of commodity crop expansion: (i) the availability of suitable forestland, which is determined by forest area, agroecological or accessibility constraints, and land use policies, (ii) economic and technical characteristics of agricultural systems, (iii) differences in constraints and strategies between small-scale and large-scale actors, and (iv) variable costs and benefits of forest clearing. When remaining forests were unsuitable for agriculture and/or policies restricted forest encroachment, a larger share of commodity crop expansion occurred by conversion of existing agricultural lands, and land use displacement was smaller. Expansion strategies of large-scale actors emerge from context-specific balances between the search for suitable lands; transaction costs or conflicts associated with expanding into forests or other state-owned lands versus smallholder lands; net benefits of forest clearing; and greater access to infrastructure in already cleared lands. We propose five hypotheses to be tested in further studies: (i) land availability mediates expansion pathways and the likelihood that land use is displaced to distant, rather than to local places; (ii) use of already-cleared lands is favored when commodity crops require access to infrastructure; (iii) in proportion to total agricultural expansion, large-scale actors generate more clearing of mature forests than smallholders; (iv) property rights and land tenure security influence the actors participating in commodity crop expansion, the form of land use displacement, and livelihood outcomes; (v) intensive commodity crops may fail to spare land when inducing displacement. We conclude that understanding pathways of commodity crop expansion is essential to improve land use governance.

Forest↗

Aboveground carbon loss associated with the spread of ghost forests as sea levels rise

Coastal forests sequester and store more carbon than their terrestrial counterparts but are at greater risk of conversion due to sea level rise. Saltwater intrusion from sea level rise converts freshwater-dependent coastal forests to more salt-tolerant marshes, leaving 'ghost forests' of standing dead trees behind. Although recent research has investigated the drivers and rates of coastal forest decline, the associated changes in carbon storage across large extents have not been quantified. We mapped ghost forest spread across coastal North Carolina, USA, using repeat Light Detection and Ranging (LiDAR) surveys, multi-temporal satellite imagery, and field measurements of aboveground biomass to quantify changes in aboveground carbon. Between 2001 and 2014, 15% (167 km2) of unmanaged public land in the region changed from coastal forest to transition-ghost forest characterized by salt-tolerant shrubs and herbaceous plants. Salinity and proximity to the estuarine shoreline were significant drivers of these changes. This conversion resulted in a net aboveground carbon decline of 0.13 ± 0.01 TgC. Because saltwater intrusion precedes inundation and influences vegetation condition in advance of mature tree mortality, we suggest that aboveground carbon declines can be used to detect the leading edge of sea level rise. Aboveground carbon declines along the shoreline were offset by inland aboveground carbon gains associated with natural succession and forestry activities like planting (2.46 ± 0.25 TgC net aboveground carbon across study area). Our study highlights the combined effects of saltwater intrusion and land use on aboveground carbon dynamics of temperate coastal forests in North America. By quantifying the effects of multiple interacting disturbances, our measurement and mapping methods should be applicable to other coastal landscapes experiencing saltwater intrusion. As sea level rise increases the landward extent of inundation and saltwater exposure, investigations at these large scales are requisite for effective resource allocation for climate adaptation. In this changing environment, human intervention, whether through land preservation, restoration, or reforestation, may be necessary to prevent aboveground carbon loss.

ghost forests↗

Modelling above-ground biomass stock over Norway using national forest inventory data with ArcticDEM and Sentinel-2 data

Boreal forests constitute a large portion of the global forest area, yet they are undersampled through field surveys, and only a few remotely sensed data sources provide structural information wall-to-wall throughout the boreal domain. ArcticDEM is a collection of high-resolution (2 m) space-borne stereogrammetric digital surface models (DSM) covering the entire land area north of 60° of latitude. The free-availability of ArcticDEM data offers new possibilities for aboveground biomass mapping (AGB) across boreal forests, and thus it is necessary to evaluate the potential for these data to map AGB over alternative open-data sources (i.e., Sentinel-2). This study was performed over the entire land area of Norway north of 60° of latitude, and the Norwegian national forest inventory (NFI) was used as a source of field data composed of accurately geolocated field plots (n=7710) systematically distributed across the study area. Separate random forest models were fitted using NFI data, and corresponding remotely sensed data consisting of either: i) a canopy height model (ArcticCHM) obtained by subtracting a high-quality digital terrain model (DTM) from the ArcticDEM DSM height values, ii) Sentinel-2 (S2), or iii) a combination of the two (ArcticCHM+S2). Furthermore, we assessed the effect of the forest- and terrain-specific factors on the models’ predictive accuracy. The best model (,i.e., ArcticCHM+S2) explained nearly 60% of the variance of the training set, which translated in the largest accuracy in terms of root mean square error (RMSE=41.4 t/ha). This result highlights the synergy between 3D and multispectral data in AGB modelling. Furthermore, this study showed that despite the importance of ArcticCHM variables, the S2 model performed slightly better than ArcticCHM model. This finding highlights some of the limitations of ArcticDEM, which, despite the unprecedented spatial resolution, is highly heterogeneous due to the blending of multiple acquisitions across different years and seasons. We found that both forest- and terrain-specific characteristics affected the uncertainty of the ArcticCHM+S2 model and concluded that the combined use of ArcticCHM and Sentinel-2 represents a viable solution for AGB mapping across boreal forests. The synergy between the two data sources allowed for a reduction of the saturation effects typical of multispectral data while ensuring the spatial consistency in the output predictions due to the removal of artifacts and data voids present in ArcticCHM data. While the main contribution of this study is to provide the first evidence of the best-case-scenario (i.e., availability of accurate terrain models) that ArcticDEM data can provide for large-scale AGB modelling, it remains critically important for other studies to investigate how ArcticDEM may be used in areas where no DTMs are available as is the case for large portions of the boreal zone.

space-borne imagery↗

Modeling the effects of carbon payments and forest owner cooperatives on carbon storage and revenue in Pacific Northwest forestlands

The forestlands of the Pacific Northwest store a significant amount of carbon, provide wildlife habitat, generate revenue for forestland owners, and provide for sustainable generation of forest products. Promoting forest carbon storage is increasingly recognized as a key management objective to mitigate climate change. We developed an agent-based model to examine the effectiveness of current land management practices in sustaining forest carbon storage and revenue flows, and the utility of market-based carbon payments in improving carbon storage while also improving revenue generation in the Pacific Northwest. We find that while market based incentives can improve both forest carbon storage and revenue, they are limited in their benefit to small forest owners. Our results highlight the crucial need for additional policy interventions to reduce barriers to market access for small private owners and ensure sustainable forest management in this region. We further show that a forest owners’ cooperative, which aggregates small owners to reduce the costs of participating in a carbon market, can help overcome these barriers and result in both greater carbon storage and a more equitable benefit from carbon payments.

54 ENVIRONMENTAL SCIENCES↗

Assimilation of repeated woody biomass observations constrains decadal ecosystem carbon cycle uncertainty in aggrading forests

Forest carbon sink strengths are governed by plant growth, mineralization of dead organic matter, and disturbance. Across landscapes, remote sensing can provide information about aboveground states of forests and this information can be linked to models to estimate carbon cycling in forests close to steady state. For aggrading forests this approach is more challenging and has not been demonstrated. Here in this paper we apply a Bayesian approach, linking a simple model to a range of data, to evaluate their information content, for two aggrading forests. We compare high information content analyses using local observations with retrievals using progressively sparser remotely sensed information (repeated, single, and no woody biomass observations). The net biome productivity of both forests is constrained to be a net sink with <2 Mg C ha -1 yr -1 variation across the range of inputs. However, the sequestration of particular carbon pool(s) varies with assimilated biomass information. Assimilation of repeated biomass observations reduces uncertainty and/or bias in all ecosystem C pools not just wood, compared to analyses using single or no stock information. As verification, our repeated biomass analysis explains 78–86% of variation in litter dynamics at one forest, while at the second forest total dead organic matter estimates are within observational uncertainty. The uncertainty of retrieved ecosystem traits in the repeated biomass analysis is reduced by up to 50% compared to analyses with less biomass information. This study quantifies the importance of repeated woody observations in constraining the dynamics of both wood and dead organic matter, highlighting the benefit of proposed remote sensing missions.

59 BASIC BIOLOGICAL SCIENCES↗