|Kate Marcille||TPO-Plus: A Western Value-added Perspective||Tuesday||3a||Sequoyah||Pusing timber producsts data in new directions||The western TPO-plus approach allows more powerful analyses of forest industry activity, timber harvest and the utilization of wood fiber to be conducted than the base TPO data alone. Collecting detailed information on the forest products industry in the west addresses a host of forest economic and policy questions, augments land management decision-making tools, helps National Forest System meet planning needs and enhances various collaborative forest-related research projects.||The FIAs Timber Product Output (TPO) program characterizes timber removals. For the western states, the University of Montanas Bureau of Business and Economic Research (BBER) conducts mill surveys, forest industry analyses and logging utilization studies. In addition to collecting the base data for the national FIA-TPO database, BBER maintains broader information on the forest products industry. This TPO-Plus approach adds value by providing a more complete accounting of harvested wood and enabling clients and data users to answer a variety of questions about timber flow and utilization. Western data are used by public land managers to guide strategic decision-making and meet National Forest System (NFS) planning needs. The TPO-Plus approach has: helped define economic impact areas; informed NFS transaction evidence appraisal systems; parameterized harvested wood products (HWP) carbon models; and linked mill infrastructure to forest restoration planning at various scales. TPO-Plus allows for applied research beyond tracking harvest volume and the product mix of utilized wood fiber, thus providing important information for forest-related policy and management decisions across the western United States.|
|Consuelo Brandeis||Pulpwood Production- An Analysis of Pulpmill Capacity and Feedstock Changes||Tuesday||3a||Sequoyah||Pusing timber producsts data in new directions||Indexed pulpwood production was used to assess shifts in consumption occurring along with pulpmill closures over the past decade. The index, based on 2006 volumes, shows an overall decline in mill residue use (close to 40 percent lower in 2016 compared to 2006) and an increase in roundwood use (close to 7 percent). Likewise, hardwood feedstocks declined while softwood volumes remained above 2006 levels. Most southern states followed similar trend patterns, but change magnitudes differed notably||Pulpwood is one of the primary uses for harvested volume across the U.S. However, changing market conditions have resulted in pulpmill closures and consequent fluctuations in volumes of pulpwood production. Annual pulpwood production data, gathered by the USDA Forest Service Forest Inventory and Analysis program, were used to analyze shifts in pulpwood consumption occurring along with pulpmill closures over the past decade. As preliminary analysis, southern feedstock production volumes were indexed using as reference volumes observed in 2006 (i.e. index=100 for 2006). Comparing index values across time revealed an overall decline in mill residue use (close to 40 percent lower in 2016 compared to 2006) and a slight increase in roundwood use (close to 7 percent increase). Likewise, hardwood feedstocks declined while softwood volumes remained above 2006 levels. Most southern states followed similar trend patterns, but change magnitudes differed notably. Research examining these trends and patterns at the state and county level is underway.|
|Nidia Panti||Mill Dynamics: Exploring mill entry and exit patterns in the Southern U.S.||Tuesday||3a||Sequoyah||Pusing timber producsts data in new directions||This research is being conducted as part of a Master of Forestry thesis and is funded by the US Forest Service under the Forest Inventory and Analysis (FIA) Timber Products Output (TPO) program. Entry and exit patterns of primary wood-using mills was studied using historical TPO mill information. A survival analysis (time to event analysis) was used to determine the survival of mills controlling for identified internal and external factors.||Timber is the most valuable commercial commodity taken from most forests. The US South produces approximately 60% of the Nations timber products, where the majority is obtained from private forests. U.S. mills were studied using information from the US Forest Service, Forest Inventory and Analysis (FIA) Timber Products Output (TPO) program survey of primary wood-using mills. Surveys were conducted biennially from 2005 to 2015 in 12 southern states and participants included all primary mills varying from sawmills, veneer mills, poles and post production mills. This historical TPO mill information was analyzed using a time to event analysis (survival analysis), controlling for size and other internal and external factors likely affecting its survival. Variables included plant size, plant structure (single-firm or multi-firm), mill consumption capacity, county demographics, etc. In terms of size and structure, studies have shown that larger plants are less likely to close while multi-firm plants are more likely to close. Competition is also another factor which has shown a positive influence on plant closure. We also studied how the changes in mill numbers and distribution affect wood procurement patterns. Studies indicate that plan|
|Brett Butler||Wood Supply Assessment Using FIA Plot and Landowner Survey Data||Tuesday||3a||Sequoyah||Pusing timber producsts data in new directions||Of the nearly 13 billion cubic feet of wood annually harvested across the U.S., 89% comes from private forests. This presentation will combine FIA plot and landowner survey data to explore the private ownerships from which this timber is originating in term of detailed ownership types, size of forest holdings, and other attributes.||Although timber supply is a common topic of many studies, there is a surprising lack of information on exactly where the timber is coming from. We know, based on FIA plot data, that there are nearly 13 billion cubic feet of wood annually harvested across the USA with 3% of this wood coming from National Forests, 8% from other public forests, and the remaining 89% coming from private forests. But we do not know much more about the private ownerships from where this wood is originating. By combining data from the FIA plot and landowner survey programs, we will provide new insights to the origins of timber supplied in the USA including detailed information on ownership types, size of forest holdings, and other topics. For example, preliminary results from this analysis show that 47% of the total timber supply comes from family forest lands. This work will also be able to quantify the timber being supplied from lands owned by timber investment management organizations (TIMOs) and real estate investment trusts (REITs). Information such as this is important to those who rely on this timber supply and those designing policies that influence it.|
|Esther Parish||Use of FIA datasets to analyze effects of wood-based bioenergy production||Tuesday||3a||Sequoyah||Pusing timber producsts data in new directions||FIA data from 1978-2017 were analyzed for changes in two forested landscapes supplying biomass to SE US bioenergy wood pellet mills, including total forest and timberland area, growth and removal ratios, proportion of planted vs. naturally regenerating area, proportion of softwood vs. hardwood area, number of snags, stand size distributions, and carbon storage at three spatial extents: supply areas delineated with 35-mile, 50-mile, and 75-mile procurement distances around each major pellet mill.||FIA datasets gathered from 1978-2017 were used to estimate changes in two forested landscapes supplying biomass to SE US pellet mills. These fuelsheds supply over half of US industrial wood pellet exports to an established bioenergy market. The Chesapeake fuelshed supplies the port of Norfolk, VA with biomass from VA and NC timberlands, and the Savannah fuelshed supplies the port of Savannah, GA with biomass from GA and SC timberlands. We analyzed trends in total forestland and timberland area, growth and removal ratios, proportion of planted versus naturally regenerating area, proportion of softwood versus hardwood area, number of snags per hectare, stand size distributions, and tons of carbon stored in three different biomass pools. Because TPO data indicate that roundwood procurement distances for pellet production have increased over time, the analyses were conducted for three spatial extents: fuelsheds delineated with 35-mile, 50-mile, and 75-mile procurement distances around each major pellet mill operating as of April 2018. Results of the analyses indicate little sensitivity of the indicators to fuelshed size and no significant impacts of export bioenergy wood pellet production on SE US timberland health as of 2017.|
|Siriluck Thammanu||Assessment of Forest Biodiversity in Providing Non-Timber Forest Products and Effects of Environmental Factors on Tree Species in Deciduous Forests for Community Forest Management in Northern Thailand||Tuesday||3a||Sequoyah||Pusing timber producsts data in new directions||This study aims to assess the forest biodiversity as well as investigate the relationship between tree species and environmental factors in the Ban Mae Chiang Rai Lum Community Forest, Northern Thailand. The inventory of the subject forest area yielded a total of 18,555 stems encompassing 197 species, 144 genera and 60 plant families. The Shannon diversity index was 2.486. The CCA analysis showed that environmental factors had significant effects on 129 tree species (p < 0.05).||This study aims to assess the potential of forest biodiversity in providing NTFPs as well as investigate the relationship between tree species and environmental factors in the Ban Mae Chiang Rai Lum Community Forest, Northern Thailand. 0.1 % of the total forest inventory was sampled using the stratified systematic sampling method. Twenty-five 40m x 40 m (0.16 ha) square plots were established in an area of 3,925 ha. Species IVI values and environmental factors were evaluated the ecological gradient of vegetation using a Canonical Correspondence Analysis (CCA). The inventory of the subject forest area yielded a total of 18,555 stems encompassing 197 species, 144 genera and 60 plant families. The Shannon diversity index was 2.486. As NTFPs, 160 of these species have been classified as having medicinal uses, 89 species are used as food, 37 species as extractives, 32 species as fuelwoods and 12 species as fibers. The CCA analysis clearly showed that environmental factors had significant effects on 129 tree species in the community forest (p < 0.05). Organic matter, soil moisture, elevation, distance to streams and distance to communities were the most important factors explaining the species composition and distribution.|
|Miranda Mockrin||Supporting the USFS WUI research agenda: Framing the session||Wednesday||3a||Sequoyah||Supporting the USFS WUI research agenda||The wildland-urban interface, that area where houses meet or mix with undeveloped natural areas, is widespread and growing rapidly. At 10% of the conterminous U.S. in area and 33% of all homes in the US, the WUI is diverse, and we lack a comprehensive understanding of ecological and social conditions within this environment. The FIA program can make valuable contribution to our understanding of WUI forest conditions and family forest managers, furthering our national program of WUI research.||The wildland-urban interface, that area where houses meet or mix with undeveloped natural areas, is widespread and growing rapidly. As of 2010 the WUI covered 9.5% of the conterminous U.S. and included 33% of all homes. From 1990 to 2010, the WUI expanded by more than 189,000 km2, an area larger than Washington State. We know that WUI expansion in the U.S. occurs overwhelmingly as a result of housing growth, but we lack a comprehensive understanding of ecological and social conditions within the WUI. Much of the current research and management focuses on wildfire risk, but the WUI is widespread, including in areas that are not fire-prone, and the ramifications of residential development on natural resources extend far beyond implications for wildfire management. As the national inventory of forest extent and conditions, the FIA Program is well positioned to provide additional insight into forest conditions, invasive species distribution, carbon sequestration benefits, and family forest owners within the WUI. This broad perspective on datasets, WUI conditions, and management issues will contribute to a national assessment of WUI research being conducted by the Washington office of Forest Service R&D.|
|Rachel Riemann||Wildland-urban interface (WUI) analysis using datasets related to urbanization and fragmentation of forest land||Wednesday||3a||Sequoyah||Supporting the USFS WUI research agenda||Urbanization and fragmentation are dominant regional stressors on forests, and they are particularly relevant in the WUI. These factors reduce forest ecosystem resilience in the face of stresses associated with climate change, and increasing demand for ecosystem services. A series of geospatial datasets has been carefully selected to characterize the fragmentation, urbanization, and landscape context of forest land in the US. We will report on what they have been able to tell us about the WUI.||Urbanization and fragmentation are dominant forest stressors with substantial ecological, economic, cultural, and human health implications and they are particularly relevant in the WUI. They reduce forest ecosystem resilience in the face of stresses associated with climate change, and in the face of increasing human demand for processing (air/water pollution), use (recreation), and extractive ecosystem services (timber, non-timber and wildlife forest products). Measuring and monitoring the status and change in forest fragmentation, urbanization, and landscape conditions has become an invaluable tool in both understanding the impacts of these stressors and characterizing their nature and extent. This information has become vital for planning, management decisions, predicting future impacts, and policy development at all scales. Much work has gone into selecting and fine-tuning a series of geospatial datasets to characterize the fragmentation, urbanization, and landscape context associated with forest land in the US. We describe these datasets, how they fit together, and report on what they have been able to tell us about the WUI.|
|Nancy Sonti||Using FIA plot data to characterize forest in the WUI||Wednesday||3a||Sequoyah||Supporting the USFS WUI research agenda||The wildland-urban interface is rapidly expanding into forested areas across the United States, leading to widespread forest fragmentation. FIA data can be used to characterize forest condition in the WUI compared to wildland forest. In this presentation, we explore differences in forest structure, species composition, and ownership between wildland forest and areas of new or persistent WUI. We also look at regional differences across the Northern Research Station geographic footprint.||The wildland-urban interface (WUI) is rapidly expanding into forested areas across the United States, leading to widespread forest fragmentation. Forest Inventory and Analysis data can be used to characterize forest in the WUI, and to examine whether WUI forest conditions are different from wildland forest that remains outside the WUI. Based on FIA data circa 2013, 16% of total forestland area in the conterminous United States was in the WUI, of which one-third became WUI since 1990.
In this presentation, we explore differences in forest structure and species composition between areas that are outside the WUI (wildland forest), that have been in the WUI since 1990 (persistent WUI), or that have more recently been characterized as WUI (since 1990). Is the WUI associated with certain forest types or stand size? And how might that relationship vary by region? We also look at patterns in forest ownership among these WUI classes, finding that WUI is more likely to develop on private or local public lands rather than state or federal lands. Finally, we highlight regional differences in these trends across the Northern Research Station geographic footprint impacted by a combination of ecological and social drivers.
|Cassandra Kurtz||Does the WUI predict invasive plant occurrence on FIA plots?||Wednesday||3a||Sequoyah||Supporting the USFS WUI research agenda||A strong correlation of invasive plant presence to housing density and natural vegetation dominance reflects the important role of human disturbance on ecosystems. Fragmentation of uninhabited, vegetated lands may increase invasive spread into formerly uninvaded areas. To help curb the spread into less invaded areas, careful monitoring to eradicate new populations and reducing numbers elsewhere is important. Using the WUI map along with site monitoring can help managers care for the resources.||Invasive plants are spreading across ecosystems causing concern and threatening the future environment. We explored the occurrence of invasive forest plants on FIA plots in the eastern US in relation to the WUI class which contained the plots, with and without adjusting for site and landscape variables known to influence invasion rates. Invasion was defined as the presence of at least one individual of any invasive plant species. Compared to an overall invasion rate of 58%, a smaller rate (38%) was observed only for plots in WUIs that were uninhabited and dominated by natural vegetation, and the highest rates (~85%) were observed in the WUI classes with low to medium housing density that were not dominated by natural vegetation. To account for potentially confounding effects of ecological province, site quality, forest cover fragmentation, and distance from road, we used logistic regression to estimate adjusted odds of invasion among four housing density classes and two classes of natural vegetation dominance. The results indicated that both housing density and natural vegetation dominance are strong predictors of the occurrence of invasive forest plants on FIA plots.|
|Jacqueline Dias||Family Forest Owners Along The Urban-Rural Spectrum||Wednesday||3a||Sequoyah||Supporting the USFS WUI research agenda||Family Forest Owners living in areas of high housing density face different pressures and decisions compared to those living in more rural areas. We combine landowner information from the National Woodland Owners Survey with the landscape context of the Wildland-Urban Interface to better understand how landowner characteristics vary across this gradient.||Family Forest Owners (FFOs) hold a plurality of forest land in the United States. Much of this land falls within the Wildland-Urban Interface (WUI), the intersection of housing density and wild vegetation. FFOs living in areas of high housing density (i.e., urban areas) face different pressures and decisions compared to those living in rural areas, and the WUI classifications allows for comparison of dynamics along a gradient within this critical area. As land continues to be developed and the WUI expands to new areas, it is important to understand who the landowners are in these areas and how they plan for and manage their land. Using data from the US Department of Agriculture Forest Service National Woodland Owner Survey, we can contextualize landowner responses within the WUI landscape. We analyze a range of FFO characteristics and behaviors to quantify how they vary across the WUI, including recreational use, forest management, and demographics.|
|Grant Domke||Toward estimating carbon stocks and stock changes across the wildland urban interface||Wednesday||3a||Sequoyah||Supporting the USFS WUI research agenda||Carbon sequestration from live trees in forests, woodlands, and settlements in the United States offsets more than 7 percent of total greenhouse gas emissions each year. How much of this carbon is sequestered and stored in the wildland urban interface (WUI)? This study combines FIA data with auxiliary information to estimate ecosystem carbon stocks and stock changes within and beyond the WUI with particular emphasis on carbon dynamics associated with land change.||* This is for an organized session on WUI coordinated by Rachel Reimann et al.
Carbon sequestration from live trees in forests, woodlands, and settlements in the United States offsets more than 7 percent of total greenhouse gas emissions each year. How much of this carbon is sequestered and stored in the wildland urban interface (WUI)? How are total carbon stocks distributed across the ecosystem pools within the WUI and on the margins of these landscapes? How are carbon stocks and stock changes within the WUI quantified in national reports? This study combines FIA data with auxiliary information to estimate ecosystem carbon stocks and stock changes within and beyond the WUI with particular emphasis on carbon dynamics associated with land change. We will describe how FIA data and auxiliary information were used to classify the WUI and estimate carbon stocks on forest land, woodlands, and settlements. We will also point to future research needs to better characterize carbon stock changes in these dynamic landscapes.
|Yingfang Wang||Using FIA Volume and Biomass Equations through National Volume Estimator Library||Thursday||3a||Sequoyah||Biomass and Carbon: New Techniques, Big Potential, and Novel Equations||FIA volume and biomass equations have been incorporated into the National Volume Estimator Library (NVEL). The NVEL was programmed in FORTRAN and compiled into a dynamic link library and a shared library. The library is available to use in Windows, Linux, and Android applications. The NVEL Excel Addins has functions to calculate cubicfoot and boardfoot volume. The NVEL has built-in interface functions for use with C#, VB, C/C++, Python, and R program. It also calculates tree component biomass.||FIA volume and biomass equations were programmed in the National Information Management System (NIMS) Oracle database and were not accessible outside of NIMS. The National Volume Estimator Library (NVEL) has been expanded to incorporate all FIA volume and biomass equations. The NVEL was programmed in FORTRAN and compiled into a dynamic link library (DLL) and a shared library. The library is available to use in Windows, Linux, and Android applications. The NVEL Excel Addins functions can be easily configured to calculate total cubic foot volume from the stump to the tip, merchantable cubic foot volume from the stump to a specified top diameter, boardfoot volume, and topwood volume for tree data stored in Excel spreadsheet. For profile model equations, there are also functions to calculate diameters at a given height, the height to a given diameter on the stem, and log diameters and volumes. The NVEL has built-in interface functions for use with C#, VB, C/C++, Python, and R program. The NVEL also has the National Biomass Estimator Library (NBEL) combined with it. It contains published biomass equations to calculate tree component biomass. The FIA existing volume and biomass equation number could be used in NVEL.|
|Lucas Clay||South Carolina Forests Potential to Contribute to the California Carbon Market||Thursday||3a||Sequoyah||Biomass and Carbon: New Techniques, Big Potential, and Novel Equations||Private forest management can greatly affect forest carbon stocks in SC. The California Carbon Market gives a monetary value to sequestered carbon. This study aims to educate landowners on how forest management can increase carbon stocks. FIA data was used in the Forest Vegetation Simulator to project carbon stocks for 130 forested plots in SC. 10 management practices were simulated to see how carbon stocks differed. This is beneficial for forest landowners interested in a carbon project.||South Carolina (SC) has a variety of different forest types, and they all have potential to sequester a certain amount of carbon. Private forest landowners control a significant portion of the overall forestland in SC, and their management efforts can maintain or improve forest carbon stocks. Currently, the California Carbon Market gives a monetary value to sequestered carbon. One carbon credit is equal to one metric ton of carbon, and is currently worth around $15.00. This study aims to educate forest landowners about various forest management practices that contribute to increasing carbon stocks by looking at various forest types SC and their current and projected carbon stocks. Forest Inventory Analysis (FIA) data was used in the Forest Vegetation Simulator to project carbon sequestration for 100 years for 130 forested plots in SC. 10 different management practices were employed to see the variance in carbon sequestration. Results showed that carbon sequestration would increase for certain management practices such as thinning and prescribed fire. This data will be beneficial for forest landowners interested in a carbon project and those interested in seeing how different management practices affect carbon sequestration.|
|Dehai Zhao||Developing new taper, volume and biomass model systems for FIA to meet the needs of diverse clients||Thursday||3a||Sequoyah||Biomass and Carbon: New Techniques, Big Potential, and Novel Equations||We present the structures, conditions, and estimation methods that are required to achieve the compatibility and additivity of taper, volume and biomass model systems. The main subtopics include (1) new variable-top merchantable volume and weight equations; (2) how to develop and estimate the completely compatible taper and volume equations; and (3) strategies for developing additive biomass component and biomass allocation equations.||FIA is striving to develop/update estimators of volume, biomass, and carbon contents of trees and tree components for the major tree species of the United States. In addition to total volume and total biomass, some clients need to accurately estimate biomass of each component for improving stand carbon/biomass estimates or nutrient accounting due to the variation of carbon and nutrient concentrations among different components, and some industrial partners are more interested in estimating volumes or weights of various portions of tree boles with changing utilization standards. It is desirable and possible to develop taper, volume and biomass model systems to meet such a variety of needs. Here, we present the structures, conditions, and estimation methods that are required to achieve the compatibility and additivity of the model systems. The main subtopics include (1) new variable-top merchantable volume and weight equations; (2) how to develop and estimate the completely compatible taper and volume equations; and (3) strategies for developing additive biomass component and biomass allocation equations.|
|Matthew Russell||Development of downed woody debris diameter and length models for application in forest biomass and carbon estimation||Thursday||3a||Sequoyah||Biomass and Carbon: New Techniques, Big Potential, and Novel Equations||Historical measurements in FIAs downed and dead wood inventory were used to develop new models of large- and small-end diameters and length using decay class, species, and diameter at transect. Despite a number of changes in FIA measurement protocols on downed woody debris, these models can be used to quantify carbon attributes, estimate fuel loads, and determine wildlife habitat.||An accurate assessment of the dimensions of downed woody debris (DWD) are required to obtain reliable estimates of the volume, biomass, and carbon attributes of forest dead wood. Measurement protocols in FIAs downed and dead wood inventory have changed tremendously over the past two decades, with current procedures forgoing detailed measurements on DWD pieces such as large- and small-end diameters and length. Despite this, over 400,000 observations of DWD pieces have been collected by the FIA program across the US that contain these detailed measurements. These historical data were used to develop new models of DWD end-point diameters and length using simpler measurements such as the decay class, species, and diameter at transect. Models were fit with linear quantile mixed models and were subsequently used to determine plot-level volume, biomass, and carbon stocks in the DWD pool. Results indicate important differences in plot-level attributes depending on whether direct measurements or modeled estimates were used to determine DWD diameter and length. These findings have important implications in quantifying carbon attributes, estimating fuel loads, and determining wildlife habitat.|
|Andrew Gray||Disentangling direct disturbance impacts from other carbon fluxes on remeasured plots on the West Coast||Thursday||3a||Sequoyah||Biomass and Carbon: New Techniques, Big Potential, and Novel Equations||The impacts of disturbance on forest carbon (C) are a common concern after a large fire event or insect outbreak. However, estimates often vary wildly. We explore alternative approaches to estimating immediate and longer-term impacts of disturbance. The mechanistic approach estimated pre- and post-disturbance growth, decay, and combustion of different C pools. The plot-matching approach compares trajectories of C pools on disturbed and undisturbed plots that share the same starting conditions.||The impacts of disturbance on forest carbon (C) stores are a common concern among managers, policy-makers, and the public, especially after a large fire event or insect outbreak. However, estimates of impacts often vary wildly, confuse short- and long-term impacts, or dont consider all C pools. Our objectives were to explore alternative approaches to estimating immediate and longer-term (e.g., 10 years) impacts of disturbance, with a focus on fire on the West Coast, USA (i.e., California, Oregon, and Washington). We compiled remeasured tree, dead wood, and forest floor estimates from 11,892 inventory plots distributed across 33.4 million ha of forestland and assessed changes in forest C pools by disturbance severity. The mechanistic approach estimated pre- and post-disturbance growth of live trees, decay of dead wood, combustion of live and dead vegetation parts, and combustion and accumulation of forest floor. The plot-matching approach compares trajectories of C pools on disturbed and undisturbed plots that share the same starting conditions. We discuss the strengths and limitations of each approach in terms of assumptions and data availability.|
|Jeremy Fried||Extending BioSum to optimize multi-decade forest restoration and evaluate biochar facility feasibility in the Upper Klamath Basin||Thursday||3a||Sequoyah||Biomass and Carbon: New Techniques, Big Potential, and Novel Equations||Capacity of national forests in the Upper Klamath Basin to generate a biochar feedstock supply under restoration management regimes designed to enhance fire resistance was analyzed using Forest Inventory and Analysis data. The BioSum framework, extended with custom scripting for landscape optimization, showed that modeled treatments elevated fire resistance on most forested area, usually at positive net revenue, producing sufficient feedstock to keep a biochar facility operating for 20 years.||Capacity of the dry national forests of southern Oregon and northern California to generate a sustainable and economically feasible supply of biochar feedstock under restoration management regimes designed to enhance fire resistance was analyzed using Forest Inventory and Analysis data. The BioSum analysis framework, combined with recently developed effectiveness metrics, offered a compelling foundation for this analysis, which, thanks to BioSums modular design, could be extended with custom scripting to more accurately represent wood value recovered and to encompass landscape scale optimization of the treatment program over time. This case illustrates the value of inventory-linked, open analytic tools adaptable to problems not originally envisioned at the onset of tool development, and the mutual benefits that flow from collaborating with users with different analytic perspectives. Implemented with tethered harvest systems, modeled treatments elevated fire resistance on most forested area; the most effective ones usually more than covered treatment cost with sales of wood. At current, 100-yr management intervals, biochar feedstock is sufficient to supply at least one large-scale facility over the next 20 years.|
|Paul Patterson||Evaluation of Estimates of Biomass from Initial On-orbit Data of the Global Ecosystem Dynamics Investigation Lidar Mission||Thursday||3a||Sequoyah||Biomass and Carbon: New Techniques, Big Potential, and Novel Equations||In Dec 2018 the NASA GEDI (Global Ecosystem Dynamics Investigation) mission installed a full-waveform lidar instrument on the International Space Station for the purpose of measuring global forest structure. The waveforms are collected in spatially discontinuous footprints. Based on the first 6 months of on-orbit GEDI science data a post-launch evaluation of the GEDI footprint level above ground biomass density (ABGD) estimators and hybrid estimate of the mean AGBD within regions is presented.||In December 2018 the NASA GEDI (Global Ecosystem Dynamics Investigation) mission installed a full-waveform lidar instrument on the International Space Station for the purpose of measuring global forest structure. The waveforms are collected in footprints that are spatially discontinuous; the waveform data is expected to be strongly correlated with aboveground forest biomass density (AGBD in Mg/ha). Using simulated GEDI waveforms, models of AGBD have been constructed for the footprints by plant functional types within the six continental regions. The estimates for the discontinuous footprint level AGBD will be combined to estimate the mean AGBD within geographical regions, e.g., 1 km grid cell, administrative unit, national park, etc. using a hybrid estimator. Using a diverse set of global sites a simulation study was conducted to empirically assess the statistical properties of hybrid estimator and the proposed estimated variance. In this talk we present an overview of the first 6 months of on-orbit GEDI science data. Based on the on-orbit GEDI science data a post-launch evaluation of the GEDI footprint level AGBD biomass estimators and hybrid estimate of the mean AGBD with geographical regions will be presented.|
|Ram Deo||Evaluating forest biomass inventory models based on integration of fixed-radius and variable-radius plot data with different modes of LiDAR and Photogrammetric metrics||Thursday||3a||Sequoyah||Biomass and Carbon: New Techniques, Big Potential, and Novel Equations||The area of interest has three types of LiDAR and DAP metrics. We collected aboveground biomass data at 51 locations using one-tenth acre, one-twenty-fourth acre (i.e. FIA subplot size) and BAF5 coverage areas that were concentric. AGB models were developed by relating the three types of LiDAR and DAP metrics separately with the fixed and variable plot AGB data. Modeling and analyses are ongoing.||LiDAR and digital aerial photogrammetry (DAP) data have become an integral part in enhanced forest inventories (EFI). However, the sensor characteristics, season of data acquisition and field sampling techniques (e.g., plot size, fixed radius vs variable radius plots) can affect the accuracy of spatial inventory models. This study was implemented in Lake County, MN where an overlap area (~ 20,000 ac) had DAP and three types of LiDAR data: high density linear LiDAR (55 points/m2), Single Photon LiDAR (33 points/m2) and low density linear LiDAR (1.5 points/m2). We evaluated aboveground forest biomass (AGB) models developed using DAP-derived predictors and grid metrics derived from the three types of LiDAR. The spatial predictors were integrated with field sampling data based on fixed and variable radius plots that were measured in summer 2018 by MN DNR at 51 locations using concentric 1/10 acre, 1/24 acre (i.e., the size of FIA subplot) and BAF 5 prism plots. AGB was calculated for the three plot sizes and the three types of AGBs were separately related to the three types of LiDAR and DAP metrics in Random Forest modeling framework to obtain the inventory models. The modeling and analyses are underway.|