|Thomas Brandeis||Assessing tree mortality probability in harvested hardwood stands using long-term forest inventory data||Tuesday||1a||Cherokee||FIA and ecology research: Shifting ranges, forest management and stand development||Retention trees in eastern US hardwood forests were 1.35 times more likely to die during or after partial harvesting than trees in unharvested stands, representing a 2.5% of volume removed. 83.7% of post-harvest mortality trees were under 11 inches DBH, which may have consequences for the future condition of these stands if not taken into account when planning management. These effects were seen equally with commercial and non-commercial species, and on both public and private lands.||Partial harvesting (here defined as removal of ? 50% of pre-harvest volume) is the predominant silvicultural scheme applied to hardwood forest types in the eastern US. Future stand conditions are largely reliant on trees retained after harvest so ensuring the survival of good quality trees can be essential to meeting long-term management goals. Retained tree mortality due to damage caused by harvesting activity should be minimized or taken into account when planning. We quantify partially harvested stand characteristics and post-harvest mortality using data from 27,671 forested conditions, 276,883 trees with a DBH ? 5 inches of which 15,061 trees were cut and utilized. On average 23.3% of stand volume was harvested with an additional 2.5% of volume lost to harvesting-caused mortality. The likelihood of mortality was 1.35 times higher (95% CI of 1.29 to 1.42) for trees retained in stands that had undergone partial harvesting than for trees growing in unharvested stands. 83.7% of post-harvest mortality trees were under 11 inches DBH. The increased odds of mortality were similar for both commercial and non-commercial species, and for trees on both privately and publicly-owned lands.|
|John Zobel||Assessing long-term implications of forest management on wildlife habitat in Minnesota.||Tuesday||1a||Cherokee||FIA and ecology research: Shifting ranges, forest management and stand development||The Wildlife Habitat Indicator for Native Genera and Species (WHINGS) is a forest habitat model that allows for rapid assessment of habitat based on forest inventory data and projected forest conditions. This talk will demonstrate the use of WHINGS across 40 years of statewide inventory data from the FIA program. Results will address long-term statewide forest management trends and their direct impact on wildlife habitat in Minnesota.||As part of the comprehensive evaluation of alternative harvesting scenarios, the Minnesota Generic Environmental Impact Statement (GEIS) used or created several methods to assess specific environmental conditions, including forest wildlife habitat. Over 25 wildlife professionals were involved in the development of the habitat models based on Forest Inventory and Analysis (FIA) data, and results were incorporated into the final GEIS report. Subsequently, the original models were updated and refined into the Wildlife Habitat Indicator for Native Genera and Species (WHINGS), a forest habitat model that allows for rapid assessment of habitat based on forest inventory data and projected forest conditions. The model uses Habitat Suitability Index (HSI) methodology for native, forest dependent wildlife species, including 138 birds, 22 small and medium mammals, four (4) large mammals, and eight (8) herptofauna. This talk will demonstrate the use of WHINGS across 40 years of statewide inventory data from the FIA program. Results will address long-term statewide forest management trends and their direct impact on wildlife habitat in Minnesota.|
|Courtney Giebink||Updating the Forest Vegetation Simulator with climate response recorded in tree rings||Tuesday||1a||Cherokee||FIA and ecology research: Shifting ranges, forest management and stand development||The Forest Vegetation Simulator (FVS), a widely used growth & yield model, currently lacks the ability to directly characterize the effect of climatic variability on diameter increment, and subsequently demographic processes. We integrate FIA remeasurement data, tree-ring data, and their climatic response to improve the FVS diameter increment model.||The Forest Vegetation Simulator (FVS) is a widely used growth & yield model that uses tree and plot data to simulate growth, mortality, and response to treatments for forest stands to inform management decisions. Although a climate extension of FVS modifies forest development based on spatial species distribution models, FVS lacks the direct effect of climate variation on diameter growth. We plan to use the climate response recorded in tree rings, complemented by inventory data from the ecologically unbiased Interior West-Forest Inventory and Analysis (IW-FIA) program to parameterize the diameter growth for several species in the Utah variant of FVS. Current models predict a ten-year growth increment using a multiple linear regression. Updated models will predict an annual growth increment with climate as a predictor using a mixed effects model. All focal species show positive sensitivity to precipitation variability and negative sensitivity to temperature variability, with differing strengths in response. The inclusion of climate in the diameter growth models will provide more accurate projections, allowing foresters to anticipate stand vulnerability to climate change and adaptively manage to increase stand resiliency.|
|Mark Brown||Mangrove Inventory Comparisons, Findings from Multi-Agency Tests in Florida||Tuesday||1a||Cherokee||FIA and ecology research: Shifting ranges, forest management and stand development||Ground based inventory of mangrove forests is difficult due to accessibility issues, time constraints, and hazardous conditions. To mitigate these issues and improve data collection, a collaborative multi-agency study was initiated. The study compared two plot designs, two diameter methods, and remotely sensed data with ground data. This presentation describes study parameters and findings from the methods compared. The study concludes with recommended changes to mangrove inventory methods.||Traditional ground based inventory of mangrove forests can be difficult and time consuming. Tides, mud flats, prop roots, and tree densities impede foot travel. To mitigate these issues and improve data collection, the Southern Research Station (SRS) initiated a collaborative study with the Florida Forest Service (FFS) and the National Aeronautics and Space Administration (NASA) to test alternative methods for mangrove inventory. Consultation with Mexicos National Forestry Commission (CONAFOR) mangrove inventory provided the diameter method studied. This presentation describes study parameters and findings from methods compared. First, inventory a one point plot design to reduce extensive traverse involved with current 4 subplot design. Second, measure tree diameter at 1.0 feet above highest prop root when encountered at or above normal diameter at breast height (dbh), to alleviate difficult measurement at 3.5 feet above that point under current methods. Third, synchronize NASA flyovers of mangrove plot locations using global positioning system (GPS) coordinates and Goddard LiDAR Hyperspectral Thermal (G-LiHT) airborne imaging to test viability of remotely sensed data to represent inaccessible mangrove plot locations in Florida.|
|Lance Vickers||Are current seedling demographics poised to regenerate northern US forests?||Tuesday||1a||Cherokee||FIA and ecology research: Shifting ranges, forest management and stand development||Detailed seedling inventories from 24 northern US states were examined for plausible regeneration outcomes following overstory removal. We examined the likelihood of meeting two fundamental regeneration objectives: 1) securing future forest and 2) securing upper canopy species. Almost half the plots lacked adequate seedlings to regenerate a stand after canopy removal and over half risked compositional shifts. In all, some regeneration difficulty may occur on two-thirds of the plots examined.||Securing desirable regeneration is essential to sustainable forest management, yet failures are common. Detailed seedling measurements from a new NRS-FIA regeneration indicator inventory across 24 northern US states were examined for plausible regeneration outcomes following overstory removal. The examination included two fundamental regeneration objectives: 1) stand replacement- securing future forest and 2) species maintenance- securing upper canopy species. Almost half the plots lacked adequate seedlings to regenerate a stand after canopy removal and over half risked compositional shifts. Based on those advance reproduction demographics, regeneration difficulties could occur on two-thirds of the plots examined. The remaining one-third were regeneration-ready. However, compared to historical norms, increased small-tree mortality rates reduces that proportion. Not all forest types rely on advance reproduction and results varied among the forest types examined. Some variability was associated with browsing intensity, as areas of high deer browsing had a lower proportion of regeneration-ready plots.|
|Kevin Potter||Leveraging the Forest Inventory and Analysis Design in a National, Spatially Explicit Assessment of Forest Tree Genetic Degradation Risk||Tuesday||1a||Cherokee||FIA and ecology research: Shifting ranges, forest management and stand development||For a national sustainability reporting effort, the USDA Forest Service needs to assess the Number and Geographic Distribution of Forest-Associated Species at Risk of Losing Genetic Variation and Locally Adapted Genotypes. To address this Montréal Process genetic diversity indicator, we use Forest Inventory and Analysis data to determine, for each species, the ratio of mature trees to saplings within provisional seed transfer zones, which encompass areas with similar environmental conditions.||Genetic diversity is essential for forest tree species because it provides a basis for adaptation and resilience to environmental stress and change. The Montréal Process, which the USDA Forest Service uses as a forest sustainability assessment framework, incorporates genetic variation among its indicators of biological diversity, including the following: Number and Geographic Distribution of Forest-Associated Species at Risk of Losing Genetic Variation and Locally Adapted Genotypes. To address this indicator, we intersect Forest Inventory and Analysis data with climatically and edaphically defined provisional seed zones, which encompass areas with similar geology, climate, vegetation and soils. These zones are proxies for among-population adaptive variation in tree species under the assumption that their adaptive genetic variation is associated with the environmental conditions that define the seed zones. We determine, for each species, the ratio of mature trees to saplings within each seed zone as an indicator of insufficient regeneration that could lead to the loss of genetic variation. The results offer insights into which species and which areas of the country may be experiencing degradation of genetic diversity.|
|Dacia Meneguzzo||Trees outside forests: where are they and what are they doing?||Tuesday||1a||Cherokee||FIA and ecology research: Shifting ranges, forest management and stand development||Forests in the agriculturally-dominant Great Plains region are not like traditional forests. Their placement is often intended to provide a specific ecological service, such as conserving soil, protecting crops, livestock, and humans, or improving water quality. We present mapping methodologies, output products, and data describing the non-traditional forest resource for multiple states in the central U.S. This endeavor provides information at a new scale appropriate for nontraditional forests.||Forests in the agriculturally-dominant Great Plains region are not like traditional forests. Their placement is often intended to provide a specific ecological service, such as conserving soil, protecting crops, livestock, and humans, or improving water quality. While these tree features often fail to meet the definition of "forest" employed by the Forest Inventory and Analysis program, they are viewed as such by the region's land managers. Windbreaks are a prime example; they are critically important yet little information describing their extent and location is available in formats (e.g., maps) that are useful for resource professionals and decision-makers. Collaborative research with the USDA National Agroforestry Center has led to the development of high-resolution tree cover maps as well as value-added map products depicting ecological services provided by trees outside forests (TOF). Mapping methodologies, output products, and data describing the TOF resource for multiple states in the central U.S. are presented. This endeavor is the first of its kind in the region and provides information at a new scale that is appropriate for inventory, monitoring, and decision-making related to nontraditional forests.|
|Hyeyoung Woo||Estimating wildfire effects with propensity score and spatial matching||Tuesday||1a||Cherokee||FIA and ecology research: Shifting ranges, forest management and stand development||Three propensity and spatial matching approaches were implemented to match burned Forest Inventory and Analysis plots with unburned plots based on topography, climate, and land cover variables. These matched plots were then used to estimate wildfire effects on standing tree carbon. The performance of the three matching methods was compared and we discuss advantages of the regional approach to wildfire effect estimation over existing case studies of individual fires.||Wildfire effects on standing tree carbon are often estimated based on observational studies of wildfires. Many of these studies focus on extreme, large wildfires that gained public interest and research support. Using Forest Inventory and Analysis (FIA) data in Oregon and Washington, USA, we identified plots (n=611) that burned in large forest wildfires within the Pacific Northwest between 2001 and 2016. We matched them with unburned FIA plots using three approaches: 1) propensity score matching based on topography, climate, and land cover variables, 2) spatial matching, and 3) distance-adjusted propensity score matching. With these matched plots we estimated wildfire effects with a quasi-experimental approach for the entire area that burned during that period. Therefore, our results provide estimates of wildfire effects that are representative of all wildfires across Oregon and Washington, USA. We discuss 1) the performance of the three different propensity score matching approaches for estimating wildfire effects from matched inventory plots, and 2) how this regional approach to wildfire effect estimation provides complementary information to that from detailed fire effects studies conducted as case studies in individual fires.|
|Robert Jespersen||Assessing potential chronology bias in the FIA increment core record with increment core data from densely sampled forest plots across North America||Tuesday||1b||Cherokee||Forests of Interior Alaska Insights from the Tanana Unit||We examined the potential for bias in increment core datasets collected through low density selective sampling strategies (LDSS), as practiced in some FIA units. Using datasets collected via high density sampling (HDS) from forests across North America, we compared the chronologies developed from HDS datasets with those developed from LDSS subsets. Preliminary results suggest that LDSS chronology bias varies strongly by species.||Increment cores collected through the United States Forest Inventory and Analysis (FIA) program offer the potential for unique insights into forest growth and its sensitivity to climate. While FIA plots are randomly located, trees selected for coring on FIA plots are generally a small number (n~5 trees) of dominant or co-dominant individuals whose growth patterns may or may not reflect the broader population. We took advantage of tree-ring data from densely sampled plots (n~30-60 trees) to examine the potential for chronology bias emerging from sampling primarily dominant and co-dominant trees. Data from densely sampled plots were acquired for the Tanana Valley of interior Alaska and from forested sites throughout North America. Preliminary results suggest the potential for chronology bias might vary strongly by species. Further analyses will examine the relative chronology quality from dominant and codominant trees across forest types, tree functional groups, and sampling designs. Our findings of bias, or lack thereof, may help inform the use and interpretation of FIA tree-ring chronologies.|
|Hans Andersen||Use of high-resolution, multi-sensor airborne remote sensing to support forest inventory in interior Alaska||Tuesday||1b||Cherokee||Forests of Interior Alaska Insights from the Tanana Unit||In this presentation, we describe how advanced, high-resolution, and multi-sensor airborne remote sensing data (airborne laser scanning, hyperspectral imaging, ultra-high resolution ( 3 cm pixels) stereo imagery) collected by NASA-Goddard are being used to support the FIA inventory in interior Alaska, with particular emphasis on the development of tools to make these technologies more accessible to end users.||Given the rapid development of several complementary advanced geospatial technologies (e.g. laser scanning, hyperspectral imaging, direct georeferencing) the role of airborne remote sensing in forest inventory is also continually changing. In this presentation, we describe how advanced, high-resolution, and multi-sensor airborne remote sensing data (airborne laser scanning, hyperspectral imaging, ultra-high resolution ( 3 cm pixels) stereo imagery) collected by NASA-Goddard are being used to support the FIA inventory in interior Alaska, with particular emphasis on the development of tools to make these technologies more accessible to end users. First, we describe how stereo imagery from a high-res mapping camera can be used to support field operations in the Susitna-Copper inventory unit, including detailed forest condition class mapping. Second, we describe how a combination of airborne lidar and hyperspectral imagery can be used to increase the reliability of inventory reporting for the Tanana inventory unit through the use of model-assisted survey regression estimators, including the development of an R package to facilitate calculations and presentation of tabular results.|
|Bruce Cook||High-resolution data from NASA's G-LiHT Airborne Imager for remote inventory and science applications||Tuesday||1b||Cherokee||Forests of Interior Alaska Insights from the Tanana Unit||Interior Alaska accounts for 15% of U.S. forest lands, yet the remoteness of interior Alaska presents a range of challenges for inventorying forest resources. Beginning in 2014, the USDA-Forest Service partnered with NASAs Goddard Space Flight Center to pilot a lidar-assisted forest inventory. This approach leverages the unique, multi-sensor, high-resolution data from NASA Goddards Lidar, Hyperspectral, and Thermal (G-LiHT) Airborne Imager (www.gliht.gsfc.nasa.gov).||Interior Alaska accounts for 15% of U.S. forest lands, yet the remoteness of interior Alaska presents a range of challenges for inventorying forest resources. Beginning in 2014, the USDA-Forest Service partnered with NASAs Goddard Space Flight Center to pilot a lidar-assisted forest inventory. This approach leverages the unique, multi-sensor, high-resolution data from NASA Goddards Lidar, Hyperspectral, and Thermal (G-LiHT) Airborne Imager (www.gliht.gsfc.nasa.gov). During 2014-19, G-LiHT flights have collected strip samples of data spaced every 9 km across three inventory units (Tanana Valley, Susitna-Copper River, and Southwest). Within these strips, the USFS implemented a 1/5th intensity grid of FIA plots. Here, we discuss the role of 1 m resolution airborne lidar, hyperspectral, thermal, and fine-resolution (<4 cm) stereo photographs for connecting the dots between inventory plot locations, including analyses of forest biomass, species composition, and trajectories of vegetation succession following stand-replacing wildfires. G-LiHT data also sample gradients in elevation, soils, and disturbance history needed to evaluate changing permafrost, insect outbreaks, expanding shrub biomass, and wildlife habitat.|
|Grant Domke||Toward estimating litter and soil carbon stocks on forest land in Alaska||Tuesday||1b||Cherokee||Forests of Interior Alaska Insights from the Tanana Unit||*I received an invitation to present this work in a session on Interior AK organized by Sean Cahoon and Hans Andersen.|
Soil organic carbon is the largest terrestrial carbon (C) sink on earth and management of this pool is a critical component of global efforts to mitigate atmospheric C concentrations. Here we describe how FIA data have been harmonized with auxiliary biophysical and geospatial data to develop models for predicting litter and soil carbon stocks on forest land in Alaska
|Soil organic carbon (SOC) is the largest terrestrial carbon (C) sink on earth and management of this pool is a critical component of global efforts to mitigate atmospheric C concentrations. Soil organic carbon is also a key indicator of soil quality as it affects essential biological, chemical, and physical soil functions such as nutrient cycling, water retention, and soil structure and maintenance. Much of the SOC on earth is found in forest ecosystems and is thought to be relatively stable. That said, several studies have documented the sensitivity of SOC to global change drivers, particularly in the northern circumpolar region where approximately 50% of the global SOC is stored. The Forest Inventory and Analysis (FIA) program within the United States Department of Agriculture, Forest Service has been measuring litter and soil attributes in forests of the US since 2001. These data have recently been harmonized with auxiliary biophysical and geospatial data to develop models for predicting litter and soil carbon stocks on forest land in the conterminous US. In this study we expand that work to estimate litter and soil carbon stocks and associated uncertainties for managed forest land in Alaska.|
|Lixia Lambert||FIA Use in Developing the Forest Sustainable and Economic Analysis Model (ForSEAM)||Tuesday||1c||Cherokee||Advances in modeling distributions, structure, and sustainability||The use of Forest Inventory and Analysis (FIA) database in developing the Forest Sustainable Economic Analysis Model (ForSEAM) to conduct spatial optimization analysis on timber resource for renewable energy development.||The Forest Sustainable and Economic Analysis Model (ForSEAM) is a dynamic linear optimization model developed to determine where conventional wood and energy feedstocks could be acquired from timberland. The model is compartmentalized into three sections including supply, demand, and sustainability. The supply component includes timber-sector production activities for 305 production regions in the lower 48 U.S. states. Each region is composed of a set of production activities including sawlog, pulpwood, and energy feedstock (woody biomass). The model currently considers two sources of energy feedstock: 1) logging residue and 2) removal of whole pulpwood and non-merchantable trees as energy feedstock. The growth rates and yields of different size and types of timber were calculated based on information from the Forest Inventory and Analysis (FIA) database. The conventional timber demand component is based on U.S. Forest Service Scenarios determined by the U.S. Forest Products Module. The sustainability component insures that harvest in each region does not exceed annual timber growth, forest tracts are located within reasonable distance of the roads,and current year forest attributes reflect previous period harvests and removals.|
|Kathryn Baer||Species distribution models predict shifting climatic suitability for important subsistence species in interior Alaskan forests||Tuesday||1c||Cherokee||Advances in modeling distributions, structure, and sustainability||Changing climatic conditions in subarctic forests may shift the distribution of understory vegetation, including important berry-producing species. We utilized occurrence records of berry species from Interior Alaska FIA data paired with current climate data and future climate models to estimate berry species distributions in the present and predict future shifts. Models predicted a decrease in highly suitable habitat along with shifts towards higher elevations and away from population centers.||Rapidly changing climatic conditions in subarctic forests have the potential to drive dramatic shifts in the distribution and abundance of their component vegetation. Of particular concern in Alaska is the potential for changes in the distribution and productivity of berry-producing understory species, which represent an important cultural and subsistence resource. FIA inventory data for Interior Alaska offer a unique dataset from which models can be constructed to estimate current berry species distributions and project how these distributions may shift under future climate change. In this study, we utilized records of berry species presence and absence paired with current climate data to estimate the current extent of berry species distributions. We then applied these models to three global circulation models for future climate to predict how these distributions might shift in the study area under future climatic conditions. Models predicted a decrease in the incidence of highly suitable habitat along with shifts towards higher elevations and away from population centers. These results indicate that subsistence berry species may become less abundant in interior Alaska and suggest areas for intensified future monitoring.|
|Margaret Evans||Using forest inventory data to build demography-driven models of the geographic distribution: a case study of Pinus edulis (two-needle piñon)||Tuesday||1c||Cherokee||Advances in modeling distributions, structure, and sustainability||We present a case study using FIA data to parameterize a demographic range model a model of the geographic distribution of Pinus edulis based on core variables of the annualized FIA Program along with PRISM climate data. This demography-driven range model suggests that negative density-dependent regulation, in addition to climatic factors, are important in shaping the distribution, and further that fire plays an important role in excluding this species from more productive forest types.||Climate change is expected to affect species distributions. Species distribution models based on occurrence data, using bioclimatic predictors alone, are widely criticized as phenomenological. Here we view the FIA database as the worlds largest repository of demographic data on trees, and use these data to parameterize a demographic model, an integral projection model, for a species whose entire geographic distribution is contained within the FIA domain, Pinus edulis (two-needle piñon). We evaluate competing hypotheses for piñons distribution: climate alone limits this species vs. climate and competition are both important limiting factors. We find support for the importance of both, with respect to the response of vital rates (growth, mortality, and regeneration) to variation in climatic and competitive conditions, and in terms of the fit between projected population growth rate and observed occurrences of Pinus edulis. Drawing on both disturbance ecology and a deep time perspective on the importance of fire in shaping the evolution of pines, we further suggest that fire may a missing factor that leads to a mismatch between occurrence data and predicted population growth rate above a mean annual precipitation of ~750 mm.|
|Patricia Manley||Data solutions for large-scale modeling and planning: Using FIA-based SilviaTerra Data for resilience planning in the central Sierra Nevada||Tuesday||1c||Cherokee||Advances in modeling distributions, structure, and sustainability||The Tahoe Central Sierra Initiative is a collaborative of 10 organizations in California that is restoring forest resilience across 2.4 M acres of high value watersheds. SilviaTerra data was identified as a singular, high quality data source for vegetation data across the entire landscape. Our detailed assessment addressed forest structure and composition, wildlife habitat, and timber supply over 100 years using the Landis II dynamic growth model to inform restoration options.||Western coniferous forests are exhibiting substantial stress from lack of fire, drought, and changing climates. Large-scale mortality events have been increasing in extent and frequency, and they are raising concerns that the opportunity to restore forest resilience may be slipping away. A common barrier to increasing the pace and scale of restoration is the availability of vegetation data that is consistent across large areas and multiple ownerships, and that describes forest conditions with sufficient detail, accuracy, and precision to support management actions. The Tahoe Central Sierra Initiative, a collaborative of Federal, State and non-profit organizations in California was formed to restore forest resilience across 2.4 M acres of mixed land ownership in some of the most ecologically and socially important watersheds in California. SilviaTerra data was identified as a singular, high quality data source for vegetation data across the entire landscape that provided spatially explicit, high resolution data on forest structure and composition. We conducted a detailed assessment of forest structure and composition, wildlife habitat, and timber supply, and then modeled changes in these parameters over 100 years using the Landis|
|David Bell||An application of generalized joint attribute modeling for modeling forest structure and composition||Tuesday||1c||Cherokee||Advances in modeling distributions, structure, and sustainability||Wall-to-wall maps of forest structure and composition are needed for landscape monitoring and planning. We apply a new hierarchical Bayesian modeling approach for complex, multivariate ecological data to predict multivariate forest inventory structure and composition based on environment and multispectral remote sensing. We compare the results of this model with those of an existing multivariate nearest neighbor imputation approach.||Wall-to-wall maps of forest structure and composition are needed for landscape monitoring and planning. Any such mapping strategy should generate statistically rigorous estimates of multiple response variables (e.g., species-level abundances) that are consistent with emergent properties (e.g., total abundance and species richness). In this study, we will apply the generalized joint attribute modeling (GJAM) approach, a hierarchical Bayesian modeling method for complex, multivariate ecological data, to predict multivariate Forest Inventory and Analysis structure and composition data based on environmental gradients and multispectral remote sensing. We will compare GJAM with an existing multivariate approach (gradient nearest neighbor imputation) in terms of (1) individual species basal area, (2) total tree basal area, and (3) total species richness. Comparisons will include plot-level accuracy assessments as well as comparisons of resulting map products, including both mean predictions and prediction precision (e.g., standard deviations). By comparing GJAM with existing nearest neighbor imputation methods, we will provide new guidance regarding the mapping of complex, multivariate forest attribute datasets.|
|Brian Miranda||Combining FIA data with the LANDIS forest simulation model to improve projections||Tuesday||1c||Cherokee||Advances in modeling distributions, structure, and sustainability||FIA data has been used widely with the LANDIS forest simulation model to provide information about current forest conditions and to calibrate and validate model initialization and growth parameters. The USDA Forest Service Northern Research Station is now pursuing improved integration between the LANDIS modeling community and the FIA research program to draw on the strengths of these two lines of research.||Forest simulation models allow users to project potential forest conditions into the future under different conditions and scenarios. Forest inventory and analysis (FIA) data provides rigorous information about past forest conditions. When used in combination, FIA data and forest simulations models, such as LANDIS, can utilize the information from the recent past to inform the projections of future conditions. FIA data has been used widely in LANDIS simulation studies to provide information about current forest conditions and to calibrate and validate model initialization and growth parameters. The USDA Forest Service Northern Research Station is now pursuing improved integration between the LANDIS modeling community and the FIA research program to draw on the strengths of these two lines of research. FIA data can be used to develop seamless forest condition maps meeting the specific model requirements for the simulation starting conditions, and for statistically rigorous evaluation of model behavior at different spatial scales utilizing the FIA data structure. In turn, the LANDIS model has the potential to inform aspects of the FIA carbon accounting by modeling growth and disturbance processed between plot measurement years.|
|Laurel Haavik||Historical activity of major pests in the Lake States||Tuesday||2a||Salon D/E||Damage, Disease, Disturbance: Forest Health Research with FIA||This project integrates Forest Health Highlights, Forest Health Monitoring, and Forest Inventory and Analyses data to create a series of technical reports and story maps that summarize and synthesize the historical patterns of major pests in the Lake States.||Our goal is to create a series of technical reports and story maps that summarize the historical patterns of major pests in the Lake States. Detailed information on insect activity has been collected by state agencies (Forest Health Highlights) and the USDA Forest Service (Forest Health Monitoring, Forest Inventory and Analysis) since the 1950s. Although these data and observations have been carefully documented in annual and periodic reports, the existing format is not easy to use. Historical patterns in insect activity and concurrent forest conditions can be a useful predictive tool for future forest conditions. We will synthesize this information and present it in a visually intuitive format that forest managers can readily use. Each installment in the series will include a different major pest, with brief sections on basic biology and ecology, historical activity, forest conditions, and management implications. The series will focus most on patterns of insect activity over time in relation to changing forest conditions. The first installment is spruce budworm, Choristoneura fumiferana, a native insect with a well-documented history of outbreaks affecting balsam fir and white spruce in the Lake States.|
|Sarah Jovan||Lichen and Moss Metrics for Monitoring Air Quality in Wilderness and Urban Areas||Tuesday||2a||Salon D/E||Damage, Disease, Disturbance: Forest Health Research with FIA||Land managers commonly use lichen bio-indicator data to supplement instrument-based air monitoring networks. Client priorities focus on environments where our typical community-based metrics dont work, like high elevation Wilderness and urban forests. Recent research uses low cost assays of pollutants in lichen and moss tissue as an alternative. Three ongoing studies are highlighted. In a nutshell, results help decision-makers allocate scarce resources, like air instruments, more effectively.||Its widely acknowledged that monitoring mandates under the Clean Air Act (CAA) arent well met using existing instrument-based networks. Federal land managers (FLMs) in the West often supplement with bio-indicator datasets to gain smaller-scale perspectives on air quality, including the 9,000+ lichen community surveys collected by FIA and NFS since 1989. Stakeholder priorities, however, increasingly focus on air quality in high elevation ecosystems and urban forests. Both environments are hostile to most lichens, making our typical community-based metrics unreliable. Three studies are underway to develop the use of low cost chemical assays of lichen and moss tissue as an alternative: 1) The CAA tasks FLMs with monitoring air quality in Wilderness, many acres of which lie above the elevation limit for epiphytic lichens. We collaborate with R6 NFS to establish an N mapping protocol for their Wilderness Monitoring Plan. 2) We also work with air regulators, state, city, and municipal organizations in Portland, OR, to map air toxics regulated under the CAA using a hardy moss. Results guide placement of limited air instruments. 3) A 1-yr urban study comparing pollutants in moss to PM10 and precipitation is also underway.|
|KaDonna Randolph||The rise and fall of individual and multifactor damage agents in forests of the United States: a retrospective look at FIA damage collection protocols||Tuesday||2a||Salon D/E||Damage, Disease, Disturbance: Forest Health Research with FIA||The FIA Program has included damage collection protocols in its inventory since the initiation of forest surveys in the 1930s. These protocols have naturally undergone revisions over time as information needs and technologies for data collection, storage, and analysis have evolved. An examination of the protocols utilized at various points in history highlights shifts in the agents considered to be most important.||The Forest Inventory and Analysis (FIA) Program of the U.S. Department of Agriculture, Forest Service, has included damage collection protocols in its inventory since the initiation of forest surveys in the 1930s. These protocols have naturally undergone revisions over time as information needs and technologies for data collection, storage, and analysis have evolved. Although changes in the damage collection protocols may impede long-term trend analyses, an examination of the protocols utilized at various points in history highlights shifts in the agents considered to be most important. Many agents such as dwarf mistletoe and fusiform rust have persisted in importance over the years whereas other agents, e.g., turpentining, are no longer of great concern. Agents on the rise include declines, diebacks, and wilts resulting from multiple interacting factors and individual agents introduced into the U.S. or moved outside their native ranges within the U.S.|
|Mark Ambrose||Using EVALIDator to Report on National Scale Mortality Trends for the Forest Health Monitoring Annual Report||Tuesday||2a||Salon D/E||Damage, Disease, Disturbance: Forest Health Research with FIA||In recent years EVALIDator has been used to report on mortality for the Forest Health Monitoring national report. EVALIDator output by ecoregion section has been used to identify regions of highest mortality, forest types affected, and major mortality-causing agents. Examples of analyses from the most recent FHM national report will be presented, as well as other uses of EVALIDator that may provide greater insight into tree mortality trends.||Since 2001, the national Forest Health Monitoring Program (FHM) has produced an annual report on the forest health status and trends across the US using monitoring data from a variety of sources. The method of analyzing mortality has changed several times since the first FHM report. Most recently, EVALIDator has been used to produce growth and mortality estimates by ecoregion section for the most recent cycle of measurements for each State and to identify regions with unusually high mortality. EVALIDator output also has been used to identify the forest types suffering the greatest mortality and major mortality-causing agents. Limitations on the use of EVALIDator for national-scale analyses are failures when the system times-out waiting for a response. In this talk, examples of analyses from the most recent FHM national report will be presented, as well as other uses of EVALIDator that may provide greater insight into tree mortality trends.|
|Zackary Holden||Using climate and biophysical attributes to predict the distribution of root disease across the U.S. Northern Rocky Mountains||Tuesday||2a||Salon D/E||Damage, Disease, Disturbance: Forest Health Research with FIA||We used a database of 15,000 root disease measurements at FIA plots collected across the U.S. Northern Rocky mountains coupled with high resolution (30 m) gridded climate and soil water balance datasets to examine the climatic and biophysical factors associated with presence and severity of root disease. Root disease occurrence was moderately well explained by dewpoint temperature, evapotranspiration and climatic water deficit (AUC = 0.77) with higher root disease prevalence at moist, humid site||We used a database of more than 15,000 root disease measurements at FIA plots collected across the U.S. Northern Rocky mountains coupled with high resolution (30 m) gridded climate and soil water balance datasets to examine the climatic and biophysical factors associated with presence and severity of root disease. Root disease occurrence was moderately well explained by dewpoint temperature, evapotranspiration and climatic water deficit (AUC = 0.77) with higher root disease prevalence at moist, humid sites with low or moderate soil water balance deficits. Root disease severity was not well explained by climatic and biophysical factors alone (R2 = 0.19). Variogram analysis indicated little spatial autocorrelation beyond a 5 km range, suggesting that the distribution of FIA plot samples may not be well suited for capturing the spatial processes governing root disease spread. We used the fitted models to estimate root disease probability of occurrence and severity across the US Forest Service Northern Region and to produce spatially explicit maps that will be used to help identify and quantify potential impacts and help prioritize areas for broad scale planning and analysis.|
|Sunil Nepal||The relationship of 19th century vegetation to 21st century oak decline and mortality in Missouri Ozark Highlands||Tuesday||2a||Salon D/E||Damage, Disease, Disturbance: Forest Health Research with FIA||Recurrent droughts and high stand stocking levels are often blamed for oak decline and mortality in the Ozark Highlands. Historical land use change, especially changes in species composition and structure oftentimes overlooked. We have examined the impacts of historical vegetation conditions in current oak decline and mortality by using early nineteenth-century trees records and current FIA data. The highest red oaks mortality was found in historical oak/pine closed woodland forest condition.||To examine the role of historical vegetation condition change in current oak decline and mortality, we investigated annual FIA data and early nineteenth-century public land survey (PLS) in the Missouri Ozark Highlands. Historical tree data revealed that white oaks were the most frequent species (50%), followed by red oaks (30%), shortleaf pine (8%), hickories (5%), and other species (7%). At present, white oaks, red oaks, and pine decreased to 34, 25, and 6% respectively, but hickories and other species increased to 10 and 25% respectively. Changes in species composition varied among historical vegetation conditions. Hickory and other species increased in all conditions. In contrast, oaks decreased in oak closed woodland, oak forest, oak open woodland and oak savanna, and increased in Oak/pine closed woodland, oak/pine forest, and oak/pine open woodland. Red oaks mortality reached up to 2.6% per year which was significantly higher than other species. The highest red oak mortality was found in the Oak/pine closed woodland. In the future, we plan to develop a modeling system that includes all factors contributing to oak mortality at different spatial scales to aid in the development of applicable mitigation methods of oak decline.|
|Valerie Pasquarella||Combining novel remote sensing methods with FIA data to evaluate effects of drought and gypsy moth defoliation on tree mortality at landscape scales||Tuesday||2b||Salon D/E||Integration of Forest Health Data Sources: Leveraging Big Data Tools to Shape the Future of Sharing Information||Gypsy moth defoliation is contributing to declining abundance of oaks in the Northeast. We combine Landsat-based estimates of defoliation severity with FIA plot data to examine relationships between defoliation, drought, mortality, and the net growth of trees. We present a new Google Earth Engine toolset for mapping and monitoring the intensity of gypsy moth defoliation based on new and historic Landsat imagery, as well as an evaluation of regional-scale forest condition assessment products.||Gypsy moth (Lymantria dispar) defoliation is contributing to declining abundance of oaks in Eastern North America. Stand-level observations suggest drought predisposes trees defoliated by gypsy moths to mortality, however the extent to which drought and defoliation have joint effects on tree mortality and growth at regional scales is less understood. We combine Landsat-based estimates of defoliation severity with FIA plot data to examine relationships between defoliation, drought, mortality, and the net growth of trees.
In order to provide consistent, repeatable assessments of changes in forest condition over time, we utilize a new remote sensing approach to map and monitor the intensity of gypsy moth defoliation based on new and historic Landsat imagery. Because this approach is data-intensive, it has previously only been applied to parts of New England. To assess changes in forest condition over larger areas, we have implemented in Google Earth Engine, and this presentation will focus on this new toolset and our evaluation of regional-scale defoliation products. We also highlight challenges in combining plot re-measurements with the Landsat record, as well as preliminary analysis of defoliation and tree mortality.
|Christopher Asaro||Estimating baseline mortality for white pine in the central Appalachians to assess the impact of a novel scale insect/pathogen complex||Tuesday||2b||Salon D/E||Integration of Forest Health Data Sources: Leveraging Big Data Tools to Shape the Future of Sharing Information||In the Central and Southern Appalachians, a novel and poorly understood die-back phenomenon in white pine (Pinus strobus L.) has been attributed to a scale insect and and weak fungal pathogen. Monitoring plots established in 2012 show considerable mortality primarily in younger age cohorts in mixed pine-hardwood stands. After 5+ years of monitoring, baseline mortality analysis indicated that five (2 cm) diameter classes had observed mortality that was significantly greater than baseline.||In the Central and Southern Appalachians, a novel and poorly understood die-back phenomenon in white pine (Pinus strobus L.) has been attributed to a scale insect and and a weak fungal pathogen. Monitoring plots established in 2012 show considerable mortality, primarily in younger age cohorts in mixed pine-hardwood stands. While overall decline in white pine volume has been minimal thus far, baseline mortality analysis indicated that five (2 cm) diameter classes (4-6, 6-8, 8-10, 14-16, 24-26) had observed mortality that was significantly greater that the established baseline mortality after only 5 years of monitoring. Initially, only one of these diameter classes (4-6) had observed mortality significantly greater than the baseline. Baseline mortality across all white pine cohorts was estimated to be approximately 12% based on study plot data and 13-14% based on FIA data. Observed mortality on study plots was over 30% for the smallest diameter classes (4-6, 6-8), and over 20% for the other three diameter classes. If these trends continue, white pine abundance or sustainability in these mixed stands could eventually be compromised as mature trees gradually die and fewer cohorts of younger trees are available to replace them.|
|Erin Berryman||Rating FIA plots for southern pine beetle hazard and applications for the National Insect and Disease Risk Map||Tuesday||2b||Salon D/E||Integration of Forest Health Data Sources: Leveraging Big Data Tools to Shape the Future of Sharing Information||Here, we explore the use of plot data obtained from the Forest Inventory and Analysis database as inputs to southern pine beetle hazard models. Model output is presented and compared to predictions in the most recent National Insect and Disease Risk Map. A possible future outcome of this work is a risk rating system for plots that can be added as a supporting table in FIADB.||The National Insect and Disease Risk Map (NIDRM) estimates areas and magnitudes of tree mortality due to major insect and disease (pest) outbreaks, over a 15 year future time horizon. There is a need for annual assessments of hazard. Many NIDRM models are based on metrics that can be solely derived from FIA plot measurements. We applied southern pine beetle (SPB) models to FIA data. Outputs for each FIA plot location were relative hazard rating (0-10, unitless), and total predicted percent basal area loss over the next 15 years. Because of the importance of geographic representation of model outputs for making adjustments and coordination with state and regional entomologists and pathologists, we compared two scales for spatially-averaging plot hazard: counties, and 6000-acre hexagonal lattices which included the 3-4 nearest plot locations for each hexagon using a buffer of 2600 m outside the edge. We compare results to the most recent (2018) NIDRM model for SPB and explore opportunities for including additional FIA measurements that would allow us to develop more complex models of insect and disease hazard. A possible future outcome of this work is a risk rating system for plots that can be added as a supporting table in FIADB.|
|Kevin Potter||Insect and disease threats to United States tree species and geographic patterns of their potential impacts: Combining FIA data with agent-specific distributions and severities||Tuesday||2b||Salon D/E||We identified the most serious insect and disease threats to each of 419 tree species native to the conterminous 48 United States. By combining the information from this list with FIA data, we were able to assess the potential ecological impacts of important forest insects and diseases within a geospatial context. In general, the potential impacts of insects and diseases were greater in the West. The potential impact of exotic invasive agents was greater in the East, however.||Diseases and insects arguably pose the most destructive threat to North American forests. As part of an effort to identify United States tree species and forests most vulnerable to these epidemics, we compiled a list of the most serious insect and disease threats for 419 native tree species and assigned a severity rating for each of the 1378 combinations between mature tree hosts and 339 distinct insect and disease agents. We then joined this list with Forest Inventory and Analysis data to assess the potential ecological impacts of insect and disease infestations. Specifically, we used the potential host species mortality for each host/agent combination to weight species importance values on approximately 132,000 FIA plots. When summed on each plot, these weighted importance values represent an estimate of the proportion of the plots existing importance value at risk of being lost. In general, the potential impacts of insects and diseases were greater in the West, where there are both fewer agents and less diverse forests. The impact of non-native invasive agents, however, was potentially greater in the East.|
|Susan Crocker||Using forest inventories to assess long-term change in the structure and composition of the Northeastern ash resource in relation to the EAB invasion||Tuesday||2b||Salon D/E||Here, the long-term structural and compositional response of northeastern US ash forests to the invasion of EAB was examined. Using a measure of EAB presence based on county-level detections and tree-ring records, we evaluated changes in ash density, basal area, and regeneration in states that were first affected by EAB (Michigan, Indiana, and Ohio) to determine impact trajectories in recently invaded states. Results are based on analysis of 12,363 FIA plots measured 3x between 2001 and 2017.||While insects are natural disturbance agents that help regulate forest ecosystem processes, the introduction of nonnative insects can significantly alter forest structure and composition, and in turn, stand productivity and biodiversity. Originating in Asia, emerald ash borer (EAB), Agrilus planipennis, Coleoptera: Buprestidae, was introduced to southeastern Michigan in the early to mid-1990s, though it was not detected until 2002. In this study, the long-term structural and compositional response of northeastern United States (US) ash forests to the invasion of EAB was examined. Using a measure of EAB presence based on county-level detections and tree-ring records, we evaluated changes in ash density, basal area, and regeneration in states that were first affected by EAB (Michigan, Indiana, and Ohio) to determine impact trajectories in recently invaded states. Results are based on analysis of 12,363 FIA plots that were measured three times between 2001 and 2017. Quantifying the cumulative changes to ash forests in the northeastern US since the arrival of EAB will help inform land management practices designed to minimize the impacts of this insect.|
|Randall Morin||Carbon losses resulting from insect and diseases invasions in USA forests||Tuesday||2b||Salon D/E||Worldwide, forests are increasingly affected by non-native insects and diseases, many of which cause substantial tree mortality across large regions. Here we analyze forest inventory plots distributed across the USA to estimate the composite impact of the 15 most damaging forest insects and diseases on total tree biomass and carbon loss. From 2009-2015, all non-native forest pest species combined induced an average annual mortality rate (above background mortality) of 4.7% of living tree biomass||Worldwide, forests are increasingly affected by non-native insects and diseases, many of which cause substantial tree mortality across large regions. North America has been invaded by a particularly large number of such species; over 400 forest insect and pathogen species are known to be established and damage has been recorded from about 70 of these. While information exists about ecological impacts of certain individual species, a comprehensive analysis assessing the composite ecosystem impacts of these species is lacking. Here we analyze > 120,000 forest inventory plots distributed across the USA to estimate the composite impact of the 15 most damaging forest insects and diseases on total tree biomass and carbon loss. We determine that the most damaging agents, in terms of biomass and carbon loss, are Dutch elm disease, emerald ash borer, beech bark disease, and hemlock woolly adelgid. From 2009-2015, all non-native forest pest species combined induced an average annual mortality rate (above background mortality) of 4.7% of living tree biomass. These results indicate that forest pest invasions, driven primarily by globalization, are contributing to the accumulation of atmospheric greenhouse gases.|
|Bradley Lalande||Assessment of landscape-level microbial community diversity throughout FIA monitoring plots||Tuesday||2b||Salon D/E||Soil samples were collected during the 2018 field season in conjunction with 49 FIA plots located within Colorado and Wyoming. Soils were sampled in association to all bulk density/duff and litter collections (125 samples). Soil DNA was extracted and sequenced at the 16S (bacterial) and ITS2 (fungal) regions to identify specific microbial communities. Analyses will be prepared to assess the relationship between soil microbes, forest ecotypes, and other relevant site and stand characteristics.||Soil microbes are primary drivers of forest ecosystem processes and play important roles in nutrient cycling, soil structure formation, decomposition, detoxification, regulating plant productivity, influencing plant diversity, and suppression of root diseases. Soil microbial communities are critical to the forest health components of sustainability, productivity, and resilience. However, our understanding of their synergistic interactions tends to be localized and difficult to apply to the landscape or ecoregion level. Soil samples were collected during the 2018 field season in conjunction with 49 FIA plots located within Colorado and Wyoming (125 samples). Using molecular approaches, we can determine taxonomic diversity of microbial communities directly from DNA extracted from environmental soil samples. The identification of microbial communities will increase our understanding of landscape level microbial diversity in forested ecosystems. Additionally, documenting potential drivers of microbial communities (i.e. changes in silvicultural treatments, forest types, land use, and regional climate change) across landscapes and over time is a valuable resource for modeling/predicting and managing western forests.|
|William Severud||Combining FIA and land cover data for assessing watershed conditions for cold water fish within Great Lakes basins||Tuesday||2c||Salon D/E||Linking forest disturbance and forest dynamics to water quantity and quality||Landscape characteristics of watersheds can be important determinants of water quality and consequently fish ecology. We investigated patterns of coldwater stream fish distribution and spatiotemporal distribution of landscape characteristics across all US watersheds within Great Lakes basins. We present models and results for predicting brook trout distribution and abundance and use these predictions to prioritize watersheds where restoration may be most effective.||Landscape characteristics of watersheds can be important determinants of water quality and consequently fish ecology. We investigated patterns of coldwater stream fish distribution and spatiotemporal distribution of landscape characteristics across all US watersheds within Great Lakes basins. Land cover attributes were obtained from the NLCD, a tree canopy cover dataset, and Landsat time series-based forest canopy disturbance data. Attributes of land use were obtained from the Forest Inventory and Analysis (FIA) database. At a fine-scale, we examined patterns within Minnesotas portion of Lake Superiors basin from 1984 to 2015 across 346 HUC 12 watersheds. Overall, lands in these watersheds are 83% forested and >17% have experienced disturbance at least once during 19842015. At a broad-scale, the entire Great Lakes basin is comprised of land uses of agriculture/range/undeveloped (35%), developed (15%), forest (48%), and open water (3%). Composition varied among five Great Lakes basins: 8-52% agricultural, 5-26% developed, 20-84% forested, and 1-4% water. We present models and results for predicting brook trout distribution and abundance and use these predictions to prioritize watersheds where restoration may be most effective.|
|Sara Goeking||Forests and Water Yield: A Review of Recent Disturbance Effects on Streamflow and Snowpack in Western Forests||Tuesday||2c||Salon D/E||Linking forest disturbance and forest dynamics to water quantity and quality||We present a review of 78 papers on the effects of recent forest disturbance on streamflow in western coniferous forests. While some studies observed post-disturbance increases in water yield, as expected, in many cases water yield did not change or even decreased. We summarize recommendations for meeting specific management objectives in forested watersheds of the semi-arid West and for improving our understanding of complex hydrologic responses to disturbance.||A long-held theory in forest hydrology is that forest cover loss leads to increased water yield. We reviewed 78 studies of hydrologic response to recent widespread tree mortality in western coniferous forests and reassessed this theory. Results included increases, no change, or even decreases in streamflow or snow accumulation. Studies that found unexpected hydrologic responses help to improve the predictability of when water yield or snowpack may actually decrease following disturbance: 1) when increased sub-canopy radiation results in increases in sublimation and evaporation from snowpack and soil that overcompensate for reduced canopy interception losses, and 2) when post-disturbance understory transpiration overcompensates for reduced canopy transpiration. However, most studies did not quantitatively characterize pre- or post-disturbance conditions. New hypotheses continue to be formulated and tested in this rapidly evolving discipline, and the US Forest Services Forest Inventory & Analysis program is poised to provide better information on forest cover than is currently available for hydrologic modeling and analysis.|
|Sara Goeking||An enhanced representation of forest cover for distributed hydrologic modeling based on forest inventory data||Tuesday||2c||Salon D/E||Linking forest disturbance and forest dynamics to water quantity and quality||Forest canopies exert stronger controls than understory vegetation on hydrologic processes, yet most hydrologic assessments lack canopy data. We developed a method to produce overstory and understory leaf area index (LAI) datasets using FIA plot data, remote sensing, and biophysical predictors in a random forests model. These datasets will help enhance understanding of hydrologic responses to forest disturbance and allows water resources projections under future climate and land cover scenarios.||Tree canopies exert stronger controls than understory vegetation on hydrologic processes. Although many distributed, physically based hydrologic models are capable of distinguishing overstory vs. understory influences on water resources, most assessments lack stratified canopy data and thus rely on total leaf area index (LAI) datasets. We developed a method to produce 30-m overstory and understory LAI datasets using plot data, remote sensing, and biophysical predictors in a random forests model. Training data consisted of overstory and understory measurements collected by the US Forest Services Forest Inventory & Analysis (FIA) program combined with satellite-based estimates of total LAI. Predictors included topographic, soils, and climate variables. We tested our method by producing gridded overstory and understory LAI layers in the South Fork Flathead Basin, Montana, USA. Observed decreases in basin-scale LAI coincide with mortality caused by drought, insects, and wildfire, as well as an increase in runoff. Stratified LAI datasets will enable enhanced understanding of hydrologic responses to forest disturbance as well as projections of future water availability under alternative climate and land cover scenarios.|
|Nicholas Shaw||Flexible Model Approach to Modeling of Soluble and Total Nutrient Transport from Wildfires.||Tuesday||2c||Salon D/E||Linking forest disturbance and forest dynamics to water quantity and quality||A new model for Nutrient Loss Modelling (NLM) has been developed as the latest iteration version of the BURN (wildfire burn nutrient transport simulation model). This is a user-friendly, model, which has a potential for increased applications and use for various scenarios and uses output data from WEPP (Water Erosion Prediction Project - WEPP Cloud version).||A new model for Nutrient Loss Modelling (NLM) has been developed as the latest iteration version of the BURN (wildfire burn nutrient transport simulation model). This is a user-friendly, model, which has a potential for increased applications and use for various scenarios. The new NLM uses output data from WEPP (Water Erosion Prediction Project - WEPP Cloud version), including the soil hillslope detachment, the soil hillslope deposition, and the soil stream channel yield for each soil texture to calculate particulate carbon, nitrogen, and phosphorus. Following this, the new NLM model calculates soluble carbon, nitrogen, and phosphorus using three different approaches. The same approach, with the exception of using base flow, has been also formulated for GeoWEPP (ArcGIS based application). The model uses particulate and soluble concentrations to calculate total carbon, nitrogen, and phosphorus. Three different models that calculate the soluble nutrient losses were included in the model to increase its versatility and to allow applications in relatively simple cases as well as in more complex scenarios. We compare results of modeling using these three different approaches for various types of watersheds and soil types.|
|Nicholas Shaw||Modeling of Carbon, Nitrogen, and Phosphorus Fluxes from Wildfires.||Tuesday||2c||Salon D/E||Linking forest disturbance and forest dynamics to water quantity and quality||We have been developing computer models which simulate fluxes of carbon, nitrogen, and phosphorus at the watershed scale. Our approach assumed that both, particulate and dissolved forms of these nutrients, are controlled by soil erosion and water flow. We utilized the existing WEPP (Water Erosion Prediction Project) and the GEOWEPP models as a starting point and the main source of the input data.||In order to evaluate the influence of forest disturbances, including wildfires, on water quality, we have been developing computer models which simulate fluxes of carbon, nitrogen, and phosphorus at the watershed scale. Our approach assumed that both, particulate and dissolved forms of these nutrients, are controlled by soil erosion and water flow. We utilized the existing WEPP (Water Erosion Prediction Project) model as a starting point and the main source of the input data to our nutrient transport model. We have built our nutrient transport model, BURN, and coupled it with WEPP algorithms integrated with spatial analysis and geographic information systems at the watershed scale (GeoWEPP program). We have utilized hillslope sediment detachment and deposition for each erosion event in the GeoWEPP simulation, and we separated it into the 5 soil classes. The soil classes for detachment and deposition at each hillslope were then transformed into soil textures. All of these processes have been maintained for the new Nutrient Loss Model (NLM). Our latest attempt uses a more intuitive approach of using soil concentrations of nutrients in sands, silts, and clays and flows of water as surface runoff, subsurface water, and the baseflow.|
|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.|
|John Coulston||Overview of timber products monitoring: recent changes and applications||Tuesday||3b||Sequoyah||Advances in timber products monitoring||The timber products monitoring component of the FIA program is shifting to an annual effort. Here we provide an overview of the statistical design and provide relevant examples of how annual information can enhance reporting efforts in the Western United States.||The Advances in timber products monitoring session aims to highlight key technical changes to how the estimates of roundwood consumption and production are constructed. The annual timber products design is based on an innovative stratified simple random sample approach that approximates probability proportional to size design. We will review this design to provide context for subsequent presentations in the session. Given the programmatic thrust to shift to an annual sample based design we will also provide examples of some assessment applications that can be enhanced with annual timber products estimates. Our examples will focus on application in the Western United States.|
|James Westfall||Estimating change in annual timber products output using a stratified sampling with certainty design||Tuesday||3b||Sequoyah||Advances in timber products monitoring||Estimation of change is a key output of the TPO monitoring program in the U.S. Approaches to estimating the covariance between successive samples were evaluated, where often only a single sample unit occurred in both samples within a stratum. While the covariance estimation methods performed poorly, treating the samples as being independent provided results that were consistent with the Monte Carlo simulation variance. This outcome was partially due to some strata being sampled with certainty.||The national timber products output (TPO) monitoring program in the U.S. is adopting a stratified sampling approach to be conducted annually. Estimation of change from year-to-year is necessary, but is complicated due to shifts in the population as well as changing strata over time. In this study, various approaches to estimating the covariance between successive samples were evaluated. A primary challenge was that often only a single sample unit occurred in both samples within a given stratum. The result that none of the covariance estimation approaches performed adequately was largely overshadowed by the outcome that treating the samples as being independent provided an overall variance estimate that was very consistent with the Monte Carlo variance obtained via simulation. It is proposed that this outcome was a derivative of the sampling design, which included some strata that were sampled with certainty. Due to the complexities introduced through changes in populations and strata over time, being able to treat the samples as independent is very beneficial because it avoids the need to introduce complex covariance calculations into the estimation process.|
|Christopher Edgar||Alternative measures of size and sample-with-certainty thresholds in monitoring of timber production in the Lake States||Tuesday||3b||Sequoyah||Advances in timber products monitoring||A new sample design for annual monitoring of timber production is currently being implemented in the Lake States. We examine two key areas of the new sample design: the selection of an effective measure of size used in constructing strata and the identification of a threshold value for allocating mills into sample-with-certainty strata. We discuss the efficiency of the new design, implementation considerations, and potential areas for further research.||The Forest Inventory and Analysis program is implementing a new sample design for annual monitoring of timber production in the Lake States and other regions of the United States. We examine two key areas of the new design: the selection of an effective measure of size used in constructing strata and the identification of a threshold value for allocating mills into sample-with-certainty strata. Precision of estimates can be increased by using measures of size that are more highly correlated with the variable of interest. We review the availability of mill profile information in Minnesota, Michigan, and Wisconsin and discuss the strength of relationships of candidate measures of size and timber production. When sampling skewed populations, a few large units may account for a large portion of the total. We examine different approaches to allocating mills to sample-with-certainty strata and the impacts on precision of the estimates. We conclude the presentation with general discussion of the efficiency of the new design, implementation considerations, and potential areas for further research.|
|Erik Berg||Western region TPO annual sampling- first year experience||Tuesday||3b||Sequoyah||Advances in timber products monitoring||To guide TPO annual sampling plans, University of Montana staff simulated sampling of active mills in 11 western states. The national TPO R program was used to select mills to sample; outputs were post-processed for nonresponse. Differences in FIA TPO censused (the true volumes) and sample-predicted timber volumes varied from 0.44 to 4.73 percent and standard errors varied from 0.10 to 4.77 percent by state. Accounting for nonresponse was the most critical component of this work.||Annual mill sampling has been added to the suite of FIA TPO services, such as the periodic censuses of facilities, to provide stakeholders timely estimates of received roundwood and mill residue volumes. To help guide future sampling plans University of Montana (UM) staff developed non-replicated simulations of sampling protocols for 11 western states. Our goal was to identify protocols which minimized differences in state-level received timber volumes between the most recent UM censuses (assumed to represent true volumes, including nonresponse) and annual sampling estimates, and which also produced standard errors of the mean of less than five percent. The national TPO R program was used to select active mills to sample; we tailored program sampling percent, certainty volumes and product type mixes for each state. Program outputs were post-processed to adjust for nonresponse. Differences in censused and program-predicted state-level roundwood volumes varied from 0.44 to 4.73 percent and standard errors varied from 0.10 to 4.77 percent. Accounting for anticipated nonresponse was the most critical component of this work. These efforts have helped prepare UM staff to conduct informative annual samples.|
|Marcus Taylor||Improving residential fuelwood estimates for TPO||Tuesday||3b||Sequoyah||Advances in timber products monitoring||TPO is implementing a new methodology to estimate residential fuelwood use. In the past the program simply reported data from the Energy Information Administration (EIA) as firewood is typically obtained through a path not captured by TPOs surveys of primary wood processors. However, EIA estimates are only available for the four Census Regions while TPO strives to provide county-level data. This new model estimates residential fuelwood by county using EIA, Census, climate, and fuel price data.||Timber Products Output (TPO) studies report estimates of forest removals by county. The majority of data for the TPO program are collected by surveying primary wood processors, such as sawmills. This survey methodology largely omits fuelwood for residential use as many users of residential fuelwood obtain the product themselves or through a path not captured by the industrial surveys. Previously, data from the U.S. Energy Information Administration (EIA) was used for the residential fuelwood component of TPO reporting, however EIA data are not available on the same spatial scale as other TPO estimates nor do they provide geographic sourcing information. FIA is developing, testing, and implementing a new methodology to estimate residential fuelwood use that will better align with other TPO estimates. Using data from the EIAs Residential Energy Consumption Survey, Census American Community Survey, the National Climatic Data Center, and EIAs home heating fuel prices, volumetric data for annual residential fuelwood usage in TPO will be modeled to the county level as well as species distribution and county-of-origin information using ancillary TPO and FIA data.|
|Brett Butler||Timber Products Output Field Data Collection Methods: Past, Present, and Future||Tuesday||3b||Sequoyah||Advances in timber products monitoring||The past and current methods used to collect TPO data from mills will be reviewed. Potential future data collection protocols, based on the current science of survey design and implementation, will then be discussed. Specific components to be considered include questionnaire design, the use of incentives, and data collection modes.||The FIA Timber Products Output program has been collecting data from primary wood processing facilities across the U.S. for decades. The TPO program has recently switched to a sample-based data collection protocol and it is time to thoroughly review the field data collection methods. Traditional techniques often involved visits to mill locations and working with mill managers to complete the questionnaires. More recent effort have started to rely more on self-administered, mail-back questionnaires. This presentation will summarize the past and current methods used to collect TPO data. Potential future data collection protocols based on the current science of survey design and implementation will be discussed along with methods for testing these new approaches. Specific components to be considered include questionnaire design, the use of incentives, and data collection modes.|
|Rebekah Zehnder||Southern Timber Supply Analysis: Forest Inventory Data for All||Tuesday||3b||Sequoyah||Advances in timber products monitoring||The Southern Timber Supply Analysis web application summarizes USDA Forest Service Forest Inventory and Analysis (FIA) data for a user-defined supply area. The easy-to-use application produces estimates of the amount of timberland and standing timber, growth, and removals within a user-specified distance or trucking time of a site of interest in the U.S. South. Southern Timber Supply Analysis broadens delivery of FIA data, simplifying the process of examining forest inventory and sustainability.||The Southern Timber Supply Analysis web application summarizes USDA Forest Service Forest Inventory and Analysis (FIA) data for a user-defined supply area. The application produces estimates of the amount of timberland and standing timber, growth, and removals within a user-specified distance (50, 75, or 100 miles) or trucking time (1, 1.5, or 2 hours) of the users site of interest in the U.S. South. The analysis can be filtered by state and ownership, and timber quantities can be displayed by volume or by green weight. The results can be downloaded in a PDF report. The application also contains pre-made statewide reports available for download.
Designed specifically for ease of use, Southern Timber Supply Analysis simplifies the process of examining forest inventory levels and sustainability within a custom area. It presents the results equivalent to running numerous EVALIDator queries in a matter of seconds, with very little effort required by the user. The information available through Southern Timber Supply Analysis will support economic development, conservation and sustainability efforts, and state forestry agencies and associations.
|David Walker||Data needs and availability for developing and testing national scale biomass estimators||Tuesday||3c||Sequoyah||Development and implementation of new volume/biomass/carbon models for the FIA program||Felled-tree records were compiled from legacy sources and new field campaigns in order to build a database suitable for developing and testing models for use in FIA national volume, biomass and carbon inventories. Some of the issues associated with the complex data set will be addressed, including the use of both US and Canadian data, dealing with missing observations within trees, and existing gaps in tree species, size, and specific geographic locations where no data are yet available.||A two-track approach involving legacy data compilation and new data collection was pursued to provide sufficient data for developing and testing models to use in FIAs national-scale biomass estimation. Legacy data sources included agency, university, and industry studies from the US, as well as government studies from both provincial and national agencies in Canada. The main data type involved stem taper and volume measurements, mainly from felled-tree studies conducted over the past 120 years in the US and Canada. Weight and biomass data including wood properties such as specific gravity comprised the second largest type of data, almost exclusively from felled-tree studies conducted in North America over the past 60 years. Major gaps in legacy data tree species, size, and geographic location were addressed by conducting field campaigns at strategic locations in the US over a period of about eight years since 2011. In total, data from nearly a quarter-million trees were compiled, about one-tenth of which include biomass measurements. Despite existing needs to be addressed in ongoing model development, the database is among the largest known collections of felled-tree records ever compiled for national-scale model development.|
|David Affleck||Alternative Modeling Strategies for Estimating Tree Biomass Across a Nationwide System of Inventory Plots||Tuesday||3c||Sequoyah||Development and implementation of new volume/biomass/carbon models for the FIA program||We review the biological, practical, and statistical and limitations of alternative model systems for estimating volume and component biomass at the tree-level over the US Forest Inventory & Analysis (FIA) plot network. Developed under FIAs National Biomass Estimators Project include systems that model|
1) total tree mass directly or indirectly;
2) mass as a function of volume, or independently of volume; and
3) trans-species or individual species trends.
|We review the advantages and limitations of alternative model systems for estimating tree volume and biomass over the Forest Inventory & Analysis (FIA) plot network. Systems proposed under FIAs National Biomass Estimators Project have been structured according to biological and dimensional principles. Yet user needs and FIA protocols have also figured prominently in development and evaluation. Chief among the former are demands for being data-driven, for additivity among biomass components, and for smoothness across administrative boundaries, as well as the desirability of compatibility between stem volume and mass estimates. Considerations related to inventory protocols include retrospective applicability and the economics associated with collection of alternative variables. Similarly, the form, quantity, and distribution of tree data, as well as inherent data dependence structures, have motivated alternative statistical specifications. We thus describe the biological, practical, and statistical strengths of systems that model
1) total tree mass directly or indirectly;
2) mass as a function of, or independently of, volume; and
3) trans-species or individual species trends.
Instances of these are explored further in this session.
|Philip Radtke||Evaluating Modeling systems for National-Scale Biomass Estimators: A Scorecard Approach with Preliminary Results||Tuesday||3c||Sequoyah||Development and implementation of new volume/biomass/carbon models for the FIA program||Modeling approaches for live tree aboveground biomass (AGB) estimators will be evaluated for desirable modeling properties: a) component additivity; b) compatibility of multiple attribute predictions; c) greatest accuracy in predicting AGB for major species; d) performance of models used to predict for minor species; e) well-behaved prediction patterns in models when used to extrapolate to very large trees; and f) effectiveness of incorporating stand or site-level predictors.||Numerous approaches will be evaluated to ensure desirable modeling properties in live tree aboveground biomass (AGB) estimators for national forest and carbon inventories, including: a) component additivity for stem and branch wood or bark, branches, and foliage; b) compatibility of volume, taper, biomass, and specific gravity predictions; c) accuracy in predicting AGB for species well-represented in model fitting data sets and for those lacking data; d) performance of models used to predict for species lacking adequate data; e) well-behaved prediction patterns in models when used to extrapolate beyond the range of observed data; and f) the effectiveness of incorporating stand and site-level predictors to reduce prediction uncertainty.
A scorecard approach has been developed for delivering concise yet complete information to aid in the model evaluation process. The scorecard approach enumerates categorically which properties proposed modeling systems are designed to achieve and provides a means for reporting quantitative measures of models performance. Examination of both the intended design and measured performance of proposed models will lead to a transparent modeling solution with highly favorable predictive abilities.
|David MacFarlane||Functional, species-specific or hybrid groups for new tree models for FIA plots?||Tuesday||3c||Sequoyah||Development and implementation of new volume/biomass/carbon models for the FIA program||This talk describes ideas, data and models are presented from several studies to examine alternative, tree-functional approaches to species-specific models, along with hybrid approaches that use both species and functional types to better characterize tree to tree variation, both within and between species, across the large spatial domain of FIA.||The Forest Inventory and Analysis (FIA) program of the USDA Forest Service is compiling continent-wide data to create new mass and volume models to be applied to trees on FIA inventory plots. FIA will need to consider how these models should be constructed to capture variation in tree attributes across the vast array of tree species, forest ecosystems, climatic regions and forest disturbance regimes that comprise the scope of FIAs inventory. In practical terms, this means allowing model coefficients and model forms to vary and, traditionally, this would mean allowing model coefficients to vary by species or groups of species. Here, ideas, data and models are presented from several studies to examine alternative, tree-functional approaches to species-specific models, along with hybrid approaches that use both species and functional types to better characterize tree to tree variation, both within and between species, across the large spatial domain of FIA. A new species form type volume modeling approach, developed for the Michigan state forest inventory system, is presented, as case study of the potential utility of a species-functional group approach for both volume and mass estimation for trees on FIA plots.|
|Krishna Poudel||Approaches to Estimate Individual Tree Aboveground Biomass||Tuesday||3c||Sequoyah||Development and implementation of new volume/biomass/carbon models for the FIA program||For the past six years, the FIA along with university partners across the nation have worked together to compile long-term legacy data as well as to collect new set of destructively sampled data to develop new models. This unified national-scale dataset was used to test different approaches to estimate total aboveground live tree biomass as well as the biomass of aboveground components.||Forest ecosystems contribute substantially to global climate change mitigation by sequestering and storing carbon. Forest carbon inventories are obtained by using tree and area measurements along with biomass equations. Therefore, large-scale forest biomass estimation is important to assess the role of forestry sector in mitigating climate change impacts. Methods to estimate total aboveground biomass as well biomass of different tree components (stem, bark, branch, and foliage) were developed using large dataset compiled from studies over the years. Missing components in the dataset were imputed using species-specific or combined-species Dirichlet imputation. Alternative model formulations and fitting techniques for obtaining biomass estimates were tested. Specifically, the independent estimation of biomass is compared with the biomass estimates derived from volume estimates that are obtained using volume equations fitted in this study. Error produced by the methods developed in this study are compared with the error produced by the Component Ratio Method currently being used for official U.S. forest carbon inventories.|
|Aaron Weiskittel||National Scale Biomass Estimator (NSBE) Project: Next steps, implications, and future timeline||Tuesday||3c||Sequoyah||Development and implementation of new volume/biomass/carbon models for the FIA program||The National Scale Biomass Estimator (NSBE) has been a joint collaborative project between several universities and the US Forest Service Forest Inventory & Analysis (FIA) program. The overall goal is to refine FIAs approach to estimating aboveground tree biomass and carbon for the primary species in the US using existing and newly collected data. Current efforts have shifted to evaluating alternative have shifted to evaluating alternative modeling approaches based on this available data.||The National Scale Biomass Estimator (NSBE) has been a joint collaborative project between several universities and the US Forest Service Forest Inventory & Analysis (FIA) program. The overall goal is to refine FIAs approach to estimating aboveground tree biomass and carbon for the primary species in the US using existing and newly collected data. Acquiring and strategically collecting biomass data was an initial focus of the project, while current efforts have shifted to evaluating alternative modeling approaches based on this available data. A current target for the project is to deliver a revised methodology to FIA for estimating tree biomass in 2020. Implementation and testing of this revised methodology by FIA will then occur with particular focus on communicating the revisions to FIAs broad array of key stakeholders. However, preliminary results indicate rather significant shifts in total biomass for certain species and regions, which have important implications for US biomass and carbon estimates. This presentation will review past accomplishments, current plans for next steps in the coming year, and the broader implications of revising FIAs approach to estimating biomass nationally.|
|Francis Roesch||Re-visiting the Re-measurement Period||Tuesday||4a||Hiwassee||How do you do that, again? Exploring methods in forest inventories||A discussion of how different linear combinations of the basic building blocks of first differences in successive observations can lead to estimators of starkly different statistical properties is given.||Estimates of growth in a forest attribute are often made from observation intervals of varying lengths of time. In FIA analyses, these estimates are usually obtained from the first differences of all observations for a particular panel, regardless of differences in observation interval length, or the actual times of measurement. This set of aggregate first differences between successive observations on re-measured forest sample plots is usually treated as a simple linear combination, while forest growth is usually assumed to be non-linear. The resulting estimators cannot be assumed to be unbiased when a linear combination is used to estimate a specific segment of an underlying non-linear trend. The bias depends upon the relationship of the intended estimation interval relative to the set of observation intervals used in any particular analysis. Recent work at SRS-FIA has evaluated the extent and nature of the resulting bias relative to three specific temporal segments which form the bases for a standard set of three estimands. A discussion of how different linear combinations of the basic building blocks of first differences in successive observations can lead to estimators of starkly different statistical properties is given.|
|Christopher Edgar||Interpreting effects of multiple, large-scale disturbances with different approaches to temporal aggregation of Forest Inventory and Analysis data||Tuesday||4a||Hiwassee||How do you do that, again? Exploring methods in forest inventories||Large-scale disturbances can greatly alter forest composition and structure. Forest Inventory and Analysis (FIA) data are used to assess forest condition changes following disturbance. We compare how temporal aggregation approaches with FIA data affects estimates of standing dead trees in east Texas, an area impacted by three large scale disturbance events in a short span. We found that interpretations of disturbance event impacts varied depending on which sets of estimates were considered.||Large-scale disturbances can greatly alter the composition and structure of forests and thereby impact the economic and ecological character of a region. Forest Inventory and Analysis (FIA) is a key information source in assessment of regional forest conditions. Here we compare how temporal aggregation of annual FIA data (i.e. panels) affects population estimates of standing dead trees as these respond to extreme disturbance events. East Texas was selected as a case study owing to the occurrence of three significant disturbance events: Hurricane Rita in 2005, Hurricane Ike in 2008, and a historic drought in 2011. Using the standard FIA estimation approach, we computed population estimates using data from the full set of panels (FSP), multiple sets of panels (MSP), and single set of panels (SSP). We found that interpretations of disturbance event impacts varied depending on which sets of estimates were considered. In the case of the drought, FSP estimates showed clear lag bias and smoothing of trends relative to the SSP estimates. Given the potential for lag bias and smoothing, we recommend that SSP and MSP estimates be considered along with FSP estimates in assessments of large-scale disturbance impacts on forest conditions.|
|Christopher Woodall||Real-time monitoring of downed dead wood moisture: Do micro-sensors hold promise for forest inventories?||Tuesday||4a||Hiwassee||How do you do that, again? Exploring methods in forest inventories||Although FIA monitors the amount and condition of downed dead wood (DDW) across the US at multi-year time intervals, it is the sub-diurnal time step that informs assessments such as wildfire risk. As moisture micro-sensors and communication networks may afford an opportunity to leverage DDW inventories to inform daily assessments of wildfire risks, such technology was developed and applied to a series of logs in varying stand conditions to record/transmit moisture at 15-minute intervals.||The attributes of downed dead wood (DDW) in forests such as quantity, arrangement, and condition is a driver of numerous ecosystem processes such as wildfire behavior, tree regeneration, and carbon cycling. Forest inventories typically monitor the amount, condition, and arrangement of DDW across large spatial scales at multi-year time intervals. However, numerous attributes of DDW of interest to managers and/or communities vary at diurnal or even sub-diurnal time steps such as wildfire risk. Technological advances in efficient micro-sensors and associated communication networks may afford an opportunity to leverage DDW inventories such as those conducted by FIA to inform daily assessments of forest attributes such as wildfire risks. In order to explore potential applicability of sensor arrays to FIAs DDW inventory, moisture sensors and communication technology was developed and applied to a series of logs in varying stand conditions in a northern hardwood forest to record/transmit moisture at 15-minute intervals. Results suggest that the moisture of DDW is highly dynamic with significant soil interactions while the recording and transmittal of streaming data was achieved if cell service was within reach of a plot. Future re|
|Graham Stinson||A new, biome-specific framework for distinguishing primary forests from other naturally-regenerated forests using remote sensing and design-based forest inventory||Tuesday||4a||Hiwassee||How do you do that, again? Exploring methods in forest inventories||Primary forests are forests where there are no clearly visible indications of human activity and the ecological processes are undisturbed. Information about primary forest extent is inconsistent because no standard or common approach exists for distinguishing primary forests from other natural forests. We propose a biome-specific framework using existing remote sensing technologies in combination with the design-based national forest inventories of the United States, Mexico and Canada.||Primary forests are forests where there are no clearly visible indications of human activities and the ecological processes are not significantly disturbed. Their loss, either through deforestation or through conversion to managed forests or tree plantations, is a concern with respect to at least three identified planetary boundaries: loss of biosphere integrity, land system change and climate change. There is broad consensus on the importance of primary forest inventory and monitoring, but no standard or common approach exists for distinguishing these forests from other naturally regenerated forests. Development of a globally standard approach may be desirable, but biome-specific standard approaches are more likely to yield ecologically relevant information. Forest dynamics, including natural disturbance regimes and successional pathways, differ markedly between tropical, temperate and boreal forests. Using North America as a case study, we propose a biome-specific framework for primary forest inventory and monitoring using existing remote sensing technologies in combination with the design-based national forest inventories of the United States, Mexico and Canada.|
|Aishwarya Chandrasekaran||Photogrammetric measurement of hardwood species at a stand level using RGB images from Unmanned aerial vehicle (UAV)||Tuesday||4a||Hiwassee||How do you do that, again? Exploring methods in forest inventories||I am specialised in Remote sensing and Image processing. Most of my work deals with satellite image processing. My works include assessing the carbon storage in wetland, oil spill studies, drought monitoring. Now I am exploring drone image processing for forests by combining machine learning and deep learning techniques.||Nowadays, for many remote sensing applications, drones are employed for gathering data, as it provides low cost image acquisition with minimal human intervention. Drone remote sensing has an extensive use in forestry for maintaining inventories, mapping canopies structure, measuring canopy height and monitoring forest fires. Maintaining a Forest inventory database is a crucial task as it is the only means of keeping a record of the forests. This study aims to explore UAV based image acquisition (consumer-grade sensor) and analysis for forest studies. The main objective is to derive a methodology for computing tree parameters such as tree height, diameter at breast height and crown width from drone images. We also aim to classify each tree with its species. This study as a whole aims to create a database that will contain information on the physical attributes of trees that is necessary for an inventory. This work will have high significance in urban forestry as time can be saved from measuring trees manually for maintaining inventories.|
|Eric Bullock||Tuesday||4a||Hiwassee||How do you do that, again? Exploring methods in forest inventories|
|KaDonna Randolph||Nickels and dimes: End-digit preference in forest inventory data||Tuesday||4a||Hiwassee||How do you do that, again? Exploring methods in forest inventories||The affinity for numbers that end in zero or five or that are associated with even quantities, e.g., four weeks, has been observed in a variety of situations, including consumer spending, athletic events, and activity recollections. Variables collected by the Forest Inventory and Analysis Program appear to include this form of bias. The costs and consequences associated with this practice, known as end-digit or terminal-digit preference, rounding, and heaping, differ by variable.||The affinity for numbers that end in zero or five or that are associated with even quantities, e.g., four weeks, has been observed in a variety of situations, including consumer spending, athletic events, and activity recollections, e.g., number of cigarettes smoked. This phenomenon, termed end-digit or terminal-digit preference, rounding, or heaping, is a form of bias, and depending on the circumstance may have serious consequences. An examination of data collected by the Forest Inventory and Analysis Program suggests a preference for values ending in zero and five among visually estimated variables such as live crown ratio, cull volume, and canopy cover, as well as heights and diameters of irregular trees. Heaping also appears when values are estimated above a certain threshold, e.g., seedling counts. The degree to which this phenomenon occurs varies across variables and FIA regions. The costs and consequences associated with this practice depend upon the variable under consideration.|
|Andrew Hartsell||Global Forest Monitoring: How Nordic countries perform their forest inventories||Tuesday||4a||Hiwassee||How do you do that, again? Exploring methods in forest inventories||There are a host of similarities between how these countries operate amongst themselves. They all use nested, fixed radius plots, have plot grids that intensify toward the south, and have field crews who are permanent employees that have other duties during the non-measurement season. Most use a combination of high-tech and traditional forest measurement tools. Many of these align with the U.S. FIA system, but differ in many ways as well.||In May of 2019, the Norwegian Institute of Bioeconomy Research (NIBIO) celebrated its 100th birthday. To commemorate this event, they held a conference to celebrate their discoveries as well as learn from other countries who perform large scale forest monitoring. Part of the curriculum was a session and field trip that allowed the five Nordic countries (Norway, Denmark, Finland, Iceland, and Sweden) the opportunity to demonstrate how they carry out their mission. This presentation encapsulates these presentations and discuses similarities, differences and various methods used to conduct their National Forest Inventories. This includes plot grids and intensities, plot descriptions, tree and plot variables collected, field composition and instruments used to collect the data.|
|George Gaines||Small area estimation of post-fire regeneration using the Forest Inventory & Analysis plot network||Tuesday||4a||Hiwassee||How do you do that, again? Exploring methods in forest inventories||Effective forest planning necessitates accurate estimates of seedling regeneration in burned areas. The Forest Inventory & Analysis (FIA) plot network provides significant sample data on tree regeneration at the national level, but the networks spatial and temporal coverage is too sparse for direct estimation of regeneration in regional burned area domains. We evaluate alternative small area estimators of domain properties that leverage data from outside the spatiotemporal domain of interest.||In the western United States, wildfire activity is expanding and many forests are struggling to regenerate post-fire under increasingly warm, dry climatic conditions. Effective forest planning necessitates accurate estimates of seedling densities and proportions of area reforested within burned areas, and in some cases federal legislation requires it. The Forest Inventory & Analysis (FIA) plot network provides substantial sample information on tree regeneration at the national level, but the networks spatial and temporal coverage is too sparse for traditional direct estimation of regeneration attributes within regional burned area domains. Thus, we describe and evaluate alternative small area estimators that leverage data from outside the spatiotemporal domain of interest while providing domain-specific estimates. These estimators rely on the availability of informative auxiliary variables, and we outline several promising sources of auxiliary data and the means by which they can support model-assisted and model-based estimation of regeneration for regions and periods of interest. Chief among these are fire severity metrics from the Monitoring Trends in Burn Severity (MTBS) program and remotely sensed vegetation indices.|
|Joseph McCollum||South Texas Non-response||Tuesday||4a||Hiwassee||How do you do that, again? Exploring methods in forest inventories||The U.S. Forest Inventory and Analysis (FIA) program develops design-based estimates of various forest attributes to monitor the status and condition of Americas forests. When field crews are denied access or hazardous conditions are encountered plots go unsampled, resulting in lower estimate precision and higher sampling errors. Here data from South Texas is used to explore the possibility of using photo-based observations from FIAs ICE project to fill in missing nonresponse plots.||The U.S. Forest Inventory and Analysis (FIA) program is a field-based inventory system that derives design-based estimates of forest attributes to monitor the status and condition of Americas forests. For various reasons plots can go unsampled, such as when field crews are denied access or hazardous conditions are encountered. When these situations arise the unmeasured plots are essentially dropped from the estimation process, which results in lower estimate precision and higher sampling errors. In certain areas of the country non-response rates are so high that FIA estimates are seriously compromised. For example, in south Texas nonresponse rates approach 30% for some counties. One possible solution is to fill in missing plots with photo-based observations, such as those collected by FIAs Image-based Change Estimation (ICE) project. In this presentation we show how FIA and ICE tend to agree at a higher level than FIA and the National Land Cover Database (NLCD) map, which is typically used to post-stratify FIA estimates. Estimates developed with FIA, ICE, and FIA and ICE blended together are used to discuss potential for using ICE to address other FIA nonresponse issues.|
|Vicente Monleon||Small area estimation of zero-inflated, spatially correlated forest variables using copula models||Tuesday||4a||Hiwassee||How do you do that, again? Exploring methods in forest inventories||We propose a modeling approach based on Gaussian copulas that accommodates both spatial dependence and excess zeros. We apply our approach to forest inventory variables with increasing proportion of zero values (total volume, volume of Douglas-fir and volume of western hemlock in Northwest Oregon). Our model is capable of spatial prediction and small area estimation and we compare the performance of different approaches within this context.||Modeling forest inventory variables present a number of challenges, including accounting for spatial correlation, excess zeros, and non-standard distributions. Gaussian copulas can be used to flexibly model the spatial dependence between random variables with very different marginal distributions. They may provide a useful tool to model the complex variables measured in forest inventories and could be used for spatial prediction and estimation for small areas. We apply copula models to predict inventory variables for increasingly narrower domains and, therefore, greater proportion of zero values (total volume, volume of Douglas-fir and volume of western hemlock in Northwest Oregon). In general, after including covariates derived from geographic and remote sensing data, the spatial correlation was relatively weak, indicating that synthetic prediction based on zero-inflated models may suffice for most applications. We thus compare the performance of copulas with or without spatial dependency in the context of small area estimation.|
|Christopher Woodall||Uncertainty in Measurements of Standing Trees and Downed Coarse Woody Debris in the US Forest Service Forest Inventory and Analysis (FIA) Program||Tuesday||4a||Hiwassee||How do you do that, again? Exploring methods in forest inventories||As knowledge of the uncertainty in estimates of forest live and dead biomass is important for interpreting forest inventory data used in applications such as national greenhouse gas inventories and biodiversity assessments, we used blind remeasurement data from the FIA quality assurance program to assess measurement uncertainty in trees and downed coarse woody debris.||As knowledge of the uncertainty in estimates of forest live and dead biomass is important for interpreting forest inventory data used in applications such as national greenhouse gas inventories and biodiversity assessments, we used blind remeasurement data from the FIA quality assurance program to assess measurement uncertainty in trees and downed coarse woody debris (DCWD). For trees, diameter measurements had better agreement between the two crews (0.14 ± 0.53 cm or 1% of diameter) than did height (0.96 ± 1.1 m), with hardwoods, being more difficult to identify than conifers. Tree status (live, dead, or cut), crown class, crown ratio, grade, and decay class were also subject to error. However, aggregated at larger scales, differences between estimates of volume or biomass based on production or QA crew measurement were negligible. In contrast, estimates of DCWD volume, averaging 31.2 m3 ha-1 across the 79 plots evaluated, were highly. Estimates of carbon storage were more uncertain, due to poorly constrained estimates of wood density. This study demonstrates how uncertainty analysis can be used to quantify confidence in estimates and to help identify where best to allocate resources to improve monitoring designs.|
|Zhengyang Hou||Updating Annual State- and County-Level Forest Inventories with Data Assimilation and FIA Data||Tuesday||4a||Hiwassee||How do you do that, again? Exploring methods in forest inventories||The objectives of this study were to propose and illustrate an updating procedure using data assimilation that integrates design-based estimates with a model-based (mixed) estimator for updating the annual estimates of forestland area at both the state- and county-level. This procedure effectively reduced the sampling error of annual estimation at both population levels and achieved annual estimates with sampling errors comparable with those based on using pooled observations.||The National Report on Sustainable Forests provides a new opportunity to produce and distribute annual updates for Montréal Process Criteria and Indicators. An annual update for forestland area is particularly important because of its association with other indicators such as forest biomass and carbon. As a result, the National Greenhouse Gas Inventory Reporting program has similar needs for forestland area, both in a timely fashion and at flexible geographical scales. The Forest Survey Handbook advises that the sampling error (SE) shall not exceed 3% error per one million acres for estimating area, a target that is achievable by pooling FIA panel observations inventoried from respective years of an inventory cycle. Consequently, the objectives of this study were to propose and illustrate an updating procedure using data assimilation that integrates design-based estimates with a model-based (mixed) estimator for updating the annual estimates of forestland area at both the state- and county-level. This procedure effectively reduced the SE of annual estimation at both population levels and achieved annual estimates with SEs comparable with those based on using pooled observations.|
|Joanne White||Monitoring post-disturbance forest recovery: improving capacity for large-area assessments||Tuesday||4b||Hiwassee||Evolving approaches for impact assessment to forests after hurricanes||Landsat time series data enable the characterization of both forest disturbance and recovery on an annual time step. Spectral metrics of post-disturbance recovery have been analyzed and corroborated with airborne laser scanning and field plot data in boreal forest environments. These data provide a spatially-exhaustive and spatially-explicit framework for forest recovery assessments that can be integrated with other sources of reference data to inform on the efficacy of forest regeneration.||With some rare exceptions, plot-based studies of post-disturbance forest recovery are limited by sample size, and spatial and temporal extent, precluding a comprehensive analysis of recovery across a range of site types, forest types, and disturbance magnitudes. Spectral recovery, as measured using a time series of optical satellite data, provide quantitative insights on the return of vegetation following disturbance. Satellite-derived spectral recovery assessments are therefore useful as they provide a consistent, large-area spatially explicit framework for assessing recovery that can be integrated with field plots and other sources of reference data such as airborne laser scanning (ALS) data. Our research generated a national assessment of recovery following wildfire and harvest using Landsat time series for Canadas forested ecosystems. Subsequent research has used measures of forest height and cover derived from ALS data as well as field plot data. Results corroborate the use of spectral recovery metrics to provide a spatially exhaustive and retrospective assessment of recovery, and to provide baseline data on the potential for natural regeneration at a given location.|
|Humfredo Marcano-Vega||Wood salvage efforts in Puerto Rico after hurricanes Irma and Maria||Tuesday||4b||Hiwassee||Evolving approaches for impact assessment to forests after hurricanes||Research in tropical forest ecology and forest products within the insular Caribbean. Analyst of data collected by the FIA program in Puerto Rico and the U.S. Virgin Islands.||Hurricanes Irma and María made landfall in Puerto Rico (PR) on September 2017, leaving hundreds of thousands of logs along the roads. Although this fallen material included wood of high value, the initial response was to dispose of it in landfills or burn it after removal. To explore beneficial alternatives for a growing industry of wood products in PR, a post-hurricane wood salvage project was initiated by the Caribbean Climate Hub. This initiative included assembling a team of specialists to assess and characterize woods recovered from debris management operations, and collected at 17 sites around PR. Various methods were employed including procedures used by the FIA program to sample residue piles, transects to characterize the size of logs, and collection of samples for species identification. The mean volume of the piles was 51,323 ft3 from a total of 1,180,429 ft3 of wood. More than 2/3 of the logs were < 6.5 ft. in length as most were cut into short pieces, but 58% had more than 8 inches of diameter. Logs of mahogany and other valuable tropical species were found with a mean decay class close to 3 after 18 months of the storms. Pre-approved plans and procedures for post-storm, hardwood recovery are recommended.|
|Dennis Jacobs||Rapid Projections of the Effects on the Forest Resource Impacted by a Major Hurricane||Tuesday||4b||Hiwassee||Evolving approaches for impact assessment to forests after hurricanes||With hurricanes being a common occurrence along the Gulf and Atlantic Coasts, the 12-year absence of major hurricane landfalls came to an end in 2017 with Hurricanes Harvey and Irma. FIA conducts an assessment soon after landfall of major hurricanes in order to provide early projections of immediate impacts to the forest resource, as determined from forest inventory data. Outputs include both spatial and tabular projections of potential timber volume and acreage losses.||With hurricanes being a common occurrence along the Gulf and Atlantic Coasts, the 12-year absence of major hurricane landfalls (Category 3 or greater) came to an end in 2017 with Hurricanes Harvey and Irma. FIA conducts a preliminary assessment within a few days after landfall for major hurricanes in order to provide early projections for immediate and direct impacts to the forest resource, as determined from forest inventory data available as of the day of the storm. The initial product generated is GIS polygon data a draft map developed from iso-lines of wind speed provided by the National Hurricane Center, which may then be improved via aerial reconnaissance and possible ground visits performed by State personnel to determine percentage impact within forest areas. Percentages of forest damage are applied to forest inventory data to provide tabular output for forest acreage along with cubic-foot volume of hardwoods, softwoods and baldcypress for all live trees on forestland. Only through more intensive aerial and ground surveys can more precise timber volume losses be determined.|
|Brian Mitchell||Modernization and Standardization of Forest Disturbance Assessment and Valuation Methodologies for Southern State Forestry Agencies||Tuesday||4b||Hiwassee||Evolving approaches for impact assessment to forests after hurricanes||The Southern Group of State Foresters (SGSF) is working to modernize and standardize forest damage assessment and valuation methodologies. This is a multidisciplinary, collaborative effort led by the SGSF Forest Management committee and involving members from the GIS, Forest Health and Ecosystem Services Utilization and Marking committees as well as key USFS partners from FIA and Remote Sensing Analysts from the Southern Research Station.||The Southern Group of State Foresters (SGSF) is working to modernize and standardize forest damage assessment and valuation methodologies. This is a multidisciplinary, collaborative effort led by the SGSF Forest Management committee and involving members from the GIS, Forest Health and Ecosystem Services Utilization and Marking committees as well as key USFS partners from FIA and Remote Sensing Analysts from the Southern Research Station. Fine resolution forest disturbance mapping techniques developed by the USFS SRS have proven very useful for assessing both small and large scale forest disturbances. We will present examples of these forest disturbance maps and provide an update on this SGSF effort.|
|Todd Schroeder||Assessing post-hurricane damage in mangrove forests of south Florida using repeat LiDAR, Landsat and U.S. Forest Inventory and Analysis (FIA) data||Tuesday||4b||Hiwassee||Evolving approaches for impact assessment to forests after hurricanes||In this presentation a spatial scaling approach is used to extrapolate LiDAR canopy height and cover models across southwest Florida to study impacts after Hurricane Irma. Mangrove maps developed with Landsat imagery and other spatial predictors are used to analyze patterns of mangrove canopy height and cover change in 5 sub-regions with different orientations from the eye wall of the storm. Potential for mapping mangrove species and other structure-related variables will also be discussed.||With hurricane frequency, intensity and duration on the rise, the economic and ecological benefits of mangrove forests are becoming more valued across the globe. To facilitate better management and protection there is an urgent need for more accurate information regarding the distribution, abundance and health of mangrove forests. To date, airborne laser scanning (ALS) data has been widely used to map changes in mangrove canopy height, however most previous studies have focused on limited geographic areas. In this study, a large collection of ALS strips collected before and after Hurricane Irma are combined with Landsat imagery and other predictors to map mangrove canopy height and cover change across all of southwest Florida. Prior to mapping, tree heights measured on U.S. Forest Service FIA plots are used to adjust the LiDAR data to account for the fact FIA measures total height, including length of leaning crowns. The maps are used to analyze distributions and spatial patterns of mangrove canopy height and cover change in 5 sub-regions with different orientations from the eye wall of the storm. Results are used to evaluate potential for broad scale mapping of mangrove species and other structure-related LiDAR variables.|
|Bjorn Brooks||A monitoring framework for tracking flood impacts to forests||Tuesday||4b||Hiwassee||Evolving approaches for impact assessment to forests after hurricanes||Flood inundation of the Coastal Plain bottomlands of the Southeastern US could pose important threats to tree species that are already poised near their water and anaerobic tolerances. This paper describes our efforts to combine USGS water data with spaceborne imaging radar to estimate the impacts and extent of flooding caused by Hurricane Michael.We also describe a method for tree species vulnerability assessment, how it can be informed by FIA, and SAR techniques used.||The Coastal Plain bottomlands of the Southeastern United States are occupied by relatively uncommon forest community types. These bottomlands support tree species adapted to edaphic conditions and seasonal hydroperiods that are beyond the tolerance threshold of many other tree species. Trends in the frequency and intensity of weather extremes (e.g., climate change and hurricanes) may spell out significant changes for the occurrence and distribution of vulnerable species. The Coastal Plain is a characteristically low gradient landscape that grades from swamp to upland transition zone. Flood inundation could pose important threats to tree species that are already poised near their water and anaerobic tolerances. This paper describes our efforts to combine USGS water data with spaceborne imaging radar (Sentinel-1 Synthetic Aperture Radar) to address challenges in estimating the impacts and extent of flooding caused by Hurricane Michael (2018) as it made landfall in Florida's Panhandle and surged northeast. We describe the methodology of our approach to tree species vulnerability assessment, how it can be informed by FIA, as well as SAR techniques used to quantify impacts.|
|Steve Norman||Session Review||Tuesday||4b||Hiwassee||Evolving approaches for impact assessment to forests after hurricanes|
|Mila Alvarez||The State of Americas Forests: An Interactive Guide||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||The State of Americas Forests is a website that tells a story of consumption and conservation, of conflict and collaboration. But most of all, it is a story of regrowth, renewal, and abundance. This online multimedia guide presents a comprehensive overview of Americas forests, the many ecosystem services they provide to society, and challenges that threaten forests. It offers a graphical view of authoritative data from the FIA Program and many other public and private sources.||State of Americas Forests is an online multimedia guide that puts authoritative information related to our nation´s forests in the hands of the public and professionals in intuitive ways. Exploratory maps, graphs, charts and videos help users to better understand the importance of forests as a source of clean water, clean air, human wellbeing, biodiversity, recreation, products, economic development, and many other benefits and services.
The website alerts of the many challenges that threaten forests existence and health, and undermine the many ecosystem services they provide to society, and particularly, to rural, forest-dependent communities. A careful analysis of wildfire, insect and disease outbreaks, invasive species, species at risk of extinction, housing development, forest fragmentation, and drought shows the degree of vulnerability forests face today and how one threat often compounds another.
Users also can explore trends over time, conditions defining our forest landscapes, the stewardship embraced throughout the different regions, and strategies adopted to conserve and protect a resource that blankets fully one-third of our landscape.
Visit State of Americas Forests at www.usaforests.org.
|Michael Bell||The Critical Loads Mapper Tool: Mapping FIA tree and lichen responses to air pollution for management applications||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||The Critical Loads Mapper tool (CL Mapper) is a joint project supported by the Environmental Protection Agency (EPA), USDA Forest Service (USFS), and the National Park Service (NPS) to make information more accessible on effects from atmospheric deposition of nitrogen (N) and sulfur (S). The CL Mapper is an interactive mapping tool that enables decision makers, researchers, and the public to easily access information for the coterminous U.S. on: 1) atmospheric deposition of N and S (estimates through time are provided for several different air quality models), 2) critical loads for terrestrial and aquatic ecosystems (from the National Atmospheric Deposition Program's National Critical Loads Database), and 3) critical load exceedances (defined as the deposition minus the critical load).|
|Erik Berg||Volume equations for planted Paulownia grown in unmanaged stands in the Southern Appalachians||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||Three combined-species stem volume models were developed for three Paulownia species as functions of 1) DBH squared, 2) the product DBH squared and total height and 3) the product diameter ground line squared and total height. Parameterized equations generally aligned with those developed for Paulownia species in China. Results of our study provide managers information on productivity of three species of Paulownia that can be used for estimating plantation yields.||Little is known of the individual tree volumes of planted Paulownia left unmanaged until harvest in the southeastern United States. We sought to remedy this lack of information needed by land managers to make informed decisions by characterizing individual tree volumes of planted P. elongata, P. fortunei, and P. tomentosa in the cool-moist environment of the southern Appalachian Mountains. Three combined-species stem volume models were developed as functions of 1) DBH squared, 2) the product DBH squared and total height and 3) the product diameter ground line squared and total height. Parameterized equations generally aligned with those developed for Paulownia species in China. Results of our study provide managers information on Paulownia tree volumes that can be used for estimating plantation yields.|
|Mike Boyle||Leveraging Visual Analytics for Data-Driven Customer-Focused Decision Making||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||In every governmental agency, data is a strategic asset. For USDA, becoming a facts-based, data-driven, customer-focused organization is a top priority. To help realize this goal, USDA is leveraging Tableau as a visual analytics departmental standard to analyze, visualize, and share information to make fact-based, customer-focused decisions.|
Building on last years CXO Dashboard effort, the USDA Data Analytics Center of Excellence has partnered with mission areas, including Forest Service, to stand up dashboards to improve program effectiveness, availability and expenditure of resources, customer distribution and needs, customer service, and highlight key indicators of risk.
The initial twelve dashboards at Forest Service used existing datasets to build visualizations for Recreation, Fire, Hazardous Fuels, Engineering, Timber, Watershed, NEPA, Grants and Agreements, Budget and Safety. The dashboards use robust analytical tools and data visualizations to summarize and present information and support executive decision-making.
|Greg Brunner||Development and delivery of raster forest inventory data products and decision support tools using FIA field plots, dense time series of Landsat imagery, and Esri ArcGIS Enterprise in the AWS Cloud||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||NEED - TY Wilson has be asked|
|Jesse Caputo||The National Woodland Owner Survey (NWOS) Dashboard and Custom Reporting Tool||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||The NWOS Data Visualization Tool is being built using the R Shiny platform, an open-source tool for creating interactive data dashboards and visualization tools that integrate fully with the R language, as well as with CSS and HTML. In order to maintain data security and avoid disclosure issues, the tool will not interact with any raw data. Instead, the tool will be built around pre-calculated arrays containing estimates for many (ultimately most) permutations of question, population, and domain||The official estimates resulting from the previous cycle (2011-2013) of the National Woodland Owner Survey (NWOS) resulted in almost two thousand pages, with many tens of thousands of individual estimates. These tables were published electronically as a USDA Forest Service General Technical Report comprising dozens of individual files. Although static documents have an important place in any data dissemination strategy, these formats are not the most intuitive or accessible for many users of public data. Since public utility is one of the primary justifications for public investment in data, it is important to seek to do better. In the current NWOS cycle, we intend on once again releasing a comprehensive publication containing tables of estimates for states, regions, and the country as a whole. In addition, however, we plan on providing a dynamic, interactive tool for accessing plots and tables of estimates across the populations, domains, and questions of the NWOS. Here we present an early version of this tool (using R Shiny), with an emphasis on univariate statistics. Future iterations of the tool will include functionality for cross-tabulations as well as custom data reporting, building off of the current NWOS Table Maker.|
|Brian Clough||Model-assisted, pixel level inventories for regional management planning: an application of SilviaTerra Basemap||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||This presentation introduces SilviaTerra Basemap, a pixel-level model assisted inventory product that is based on FIA and remote sensing datasets. To demonstrate the utility of our approach for regional management planning, we use Basemap information to map the distribution of mixed conifer forest and associated risk of bark beetle outbreak in the Carson National Forest, New Mexico, USA.||Using FIA data to guide management decisions at local to regional scales requires computational systems that are capable of predicting forest composition at fine resolution. Collaborating with Microsoft's AI for Earth program in 2018 and 2019, SilviaTerra has developed Basemap, a pixel-level data product based on FIA and remote sensing data that carries the forest attributes necessary to estimate forest populations at any scale. To demonstrate its utility for guiding management decisions, we use Basemap to derive the distribution of mixed conifer forests and associated risk for bark beetle outbreak in the Carson National Forest, New Mexico, USA. While the core of the data product is a suite of predictive models, we make use of model-assisted inventory methods to ensure top level consistency with large area estimates from FIA data. This feature makes Basemap highly scalable, and allows it to accommodate general attribution of a variety of derived variables (e.g., volume, biomass, wildlife habitat quality, etc.) within the FIA inventory framework. In addition to demonstrating its potential, planned future improvements to improve the accuracy and precision of the data will be discussed.|
|Jason Cooper||One Click for Timber Products Output data and a table generator built with Tableau.||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||The Southern Timber Product Output (TPO) Group has developed new TPO digital engagement tools which include the One-Click TPO Factsheets and the TPO Core Tables Generator. The One-Click TPO application allows users to view the most recent TPO survey summary data by state by using an interactive map interface. TPO Core Tables Generator populates ten core TPO tables for viewing once users select a state of interest from an interactive map interface. Both digital products will allow customers access to TPO data in a timelier manner with visual tables and charts customized by the user.|
|Sarah Crow||Forests in Focus: Assess Risk, Identify Opportunities, Make an Impact||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||Forest in Focus (FF) is an innovative new platform to identify risk in forest product supply chains and provide opportunities for achieving positive conservation impacts through the engagement of family forest owners. Currently under development, Forests in Focus is a powerful data tool that gives users the business intelligence to help define, measure, and communicate their commitment to sustainable forest management to consumers, shareholders, and other stakeholders.||Forests in Focus provides a brand new view into woodbaskets with a dynamic, landscape-scale assessment of risk that offers insights to help verify responsible sourcing of wood fiber as well as identifying opportunities to invest in conservation impact through engagement of family forest owners. The American Forest Foundation (AFF) and GreenBlue have partnered with leaders at Forest Inventory and Analysis (FIA), Esri and NatureServe to develop an innovative interactive online dashboard to provide easy access to critical sustainability understanding and insight. With funding and partnership of a suite of companies including McDonald's, Mars, Staples, Georgia-Pacific, Domtar, Weyerhaeuser, WestRock and others, Forests in Focus represents a practical and powerful leveraging of FIA data and talent.|
|Mansfield Fisher||Spatial and Temporal Trends of Forest Type Transitions in the US Southeast||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||Land use change literature focused on the US South demonstrates that increased returns to forestland leads to forest acreage expansion. Previous work links increased wood pellet demand with forest management intensification, the objective of this study is to analyze the relationship between expanding industrial plantation acreage and forest type transitions. Using data from the FIA Program, we look at forest type transitions temporally and spatially across the US South.||Land use change literature focused on the US South demonstrates that increased returns to forestland ultimately leads to forest acreage expansion. However, there is substantially less work on the relationship between forest rents and the expansion or contraction of specific forest types. Expanding on previous work linking increased wood pellet demand with forest management intensification, the objective of this study is to analyze the relationship between expanding industrial plantation acreage and forest type transitions. Using data from the Forest Inventory and Analysis Program, we look at forest type transitions temporally and spatially across the US South. Building forest type transition matrices based on state and intrastate-regions allows us to understand which forest types are experiencing the highest levels of intensification. Ongoing research is being performed to determine the statistical significance of spatial and temporal trends of forest type conversions. Developing a better understanding of which types of natural systems are being converted to plantations, and understanding the factors driving these conversions, will enable a more comprehensive analysis of the impact of expanding wood pellet demand.|
|Tracey Frescino||FIESTA!||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||FIESTA (Forest Inventory ESTimation and Analysis) is an open-source, R estimation package designed to efficiently process and translate multi-scale resource data to information. It provides a flexible platform to accommodate unique research questions such as on-the-fly estimation over user-defined polygons. It enables use of auxiliary data from a wide variety of remote sensing instruments and allows FIA to make use of statistical advances in areas such as model-assisted and small area estimation||Come to the party! This will be a lively demonstration of FIESTA (Forest Inventory ESTimation and Analysis) which is an open-source, R estimation package designed to efficiently process and translate multi-scale resource data to information. FIESTA was developed to support current available FIA tools such as EVALIDator. It provides a flexible platform to accommodate unique research questions such as on-the-fly estimation over user-defined polygons. It enables the use of auxiliary data from a wide variety of remote sensing instruments. It also allows FIA to make use of statistical advances in areas such as model-assisted, model-based and small area estimation. In this live demo, we provide an overview of the package, demonstrate complex spatial manipulations, illustrate estimation options for applications on National Forest Systems lands, and show options for creating rapid response estimates for disturbance events. Visitors will get a sense of how FIESTAs flexible, open-source strategy allows for accessibility, adaptability, and integration with other R packages and other software platforms -- helping bridge the gap between science and FIA production. Early visitors will have the opportunity to win prizes, so dont be late!|
|James Garner||Forests of Southern New England 2017 Digital Report||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||NRS FIA has adapted its quinquennial comprehensive forest status and trends report from a traditional printed layout into a suite of interconnected applications integrating the next generation of ArcGIS Online (AGOL) story maps with AGOL and Tableau dashboards. This dynamic presentation platform enables the user interact with and explore the maps, charts, and dashboards included in the report, along with an entire network of supporting information available in related websites and applications,||NRS FIA has adapted its quinquennial comprehensive forest status and trends report from a traditional printed layout into a suite of interconnected applications integrating the next generation of ArcGIS Online (AGOL) story maps with AGOL and Tableau dashboards. This dynamic presentation platform enables the user interact with and explore the maps, charts, and dashboards included in the report, along with an entire network of supporting information available in related websites and applications, all within the same browser window.|
|Andrew Hait||Census Bureau Data Dashboards||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||An overview of both the demographic and business data available from the US Census Bureau and how forest industry researchers and others can use the information in their work. We will also explore various Census data platforms that include these data, including the Census API that makes it easier for web site and software developers to access these data. One of these platforms, Census Business Builder, makes it easier for users who are unfamiliar with Census data products to access the key information they need via an interactive, cloud-based tool. Real-life use cases will be explored, using both the Small Business and Regional Analyst Editions of CBB.|
|Salma Huque||Forestry Data Science: Classification and Estimation||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||We explored alternatives to the current existing vegetation type variable's classification created by the USDA's LANDFIRE program using k-means clustering. We also investigated the underestimation issues of the out-of-bag mean squared error in random forest models using longitudinal data. We demonstrated this underestimation in a simulation incorporating remote-sensing data and satellite imagery from Daggett County, UT and offered solutions for using random forests with longitudinal data.||In this poster, we will present the findings of a forestry data science undergraduate research experience. This opportunity was a joint venture between FIA, Reed College, and Swarthmore College. We explored alternatives to the current existing vegetation type (EVT) classification method created by the USDA's LANDFIRE program. We used k-means clustering to create two new classification schemes that grouped EVT according to four key response variables. FIA can apply this scheme to improve existing estimators that rely on auxiliary data, such as the post-stratified estimator. We also investigated the underestimation of the predicted mean squared error of a random forest model when estimated by the out-of-bag mean squared error of a model built using longitudinal data. We demonstrated this underestimation in a simulation incorporating remote-sensing data and satellite imagery from Daggett County, UT. Finally, we offer potential solutions and best practices for using random forests with longitudinal data. These findings have implications for how FIA approaches classification and regression in their estimation methods.|
|Scott Jones||A Novel Approach to Using FIA Data in the Assessment of Biodiversity||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||The use of FIA data in the assessment of biological diversity is associated with improvements to the indicators of the Conservation of Biological Diversity which is Criterion 1 of the Montreal Process Criteria and Indicator framework for forest sustainability. It is part of a larger effort focusing on further development of the entire criteria and indicator framework to make it more useful to managers, address smaller jurisdictions/landscapes that nations and to use existing data.||There have been many state of the forest reports and Forest Action Plan landscape assessments that have used the indicators of the Montreal Process for the Conservation of Biological Diversity and all attempts have produced less than useful results that also don't compare across time periods of assessment. A new approach is proposed using readily available FIA data sets for forest unit type (Community Diversity) and tree species type (Species Diversity) which allow for the calculation of Simpson's Diversity Index and a measure of evenness for forest communities and tree species. This approach allows for easy cross-period comparison, the identification of trends and eliminates the weakness of using only species richness. The approach also uses a new way of looking at Genetic Diversity using the categories of leading edge species, trailing edge species and herbaceous plant outlier species in addition to threatened and endangered species.|
|Kasey Legaard||The Maine ForEST (Forest Ecosystem Status and Trends) App: Data and tools to support landscape planning and forest risk analysis in real time||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||The Maine ForEST (Forest Ecosystem Status and Trends) App was developed to support risk analysis and landscape planning during an upcoming outbreak of the eastern spruce budworm. The ForEST App delivers up-to-date spatial information on key timber and non-timber resources through an intuitive web interface that includes visualization and summary analysis tools. Our intent is to enhance decision support by simplifying the delivery of valuable information to Maines diverse forest stakeholders.||The southern expansion of an ongoing outbreak of eastern spruce budworm is without question a leading threat to Maine's forest economy. In principle, timber loss to defoliation can be mitigated by early harvesting of vulnerable trees, application of insecticides, or salvage logging of infested trees. In practice, mitigation incurs economic, ecological, and social costs. Reducing the costs and enhancing the benefits of management decisions will require knowledge of both timber and non-timber resources, and their vulnerabilities. The Maine ForEST (Forest Ecosystem Status and Trends) App is a web mapping application that delivers high-value geospatial data relevant to budworm risk analysis and landscape planning through a user-friendly interface. Accurate and up-to-date spatial information on forest resources of high interest is provided through state-of-the-art machine learning methods applied to multispectral satellite imagery and FIA data. Visualization and summary analysis tools distill the complexity of forest landscape conditions into key pieces of information with minimal user effort. Our intent is to provide decision support to Maines diverse forest stakeholders throughout the next budworm outbreak.|
|Sarah Maebius||Post-Stratification and Variance Estimation in Forestry Data Science||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||We compared the relative efficiencies of FIA-IW's current post-stratification scheme with five other post-stratification schemes that stratify by groups including auxiliary data for three other variables: biomass, forest probability, and tree canopy cover. We also evaluated the performance of several model-assisted estimators for variance of the mean estimate of ndvi values for Daggett County under a systematic sample.||This poster presents the culmination of undergraduate research focused on the field of forestry data science. The experience combined efforts of representatives from FIA, Reed College, and Swarthmore College. For data collected under a systematic sampling design, we investigated the impacts of estimating the variance of a mean estimator using the standard FIA estimator, which assumes the systematic design can be approximated by a simple random sampling design and we tested out variance estimators that account for spatial autocorrelation. Conducting a simulation study, which involved taking many systematic samples from ndvi values in Daggett County, we concluded that the standard method of variance estimation could lead to biased approximations.
For another project, we explored new post-stratification schemes for FIA-IW. With access to auxiliary data, we proposed five schemes stratifying by levels of biomass, forest probability, and tree canopy cover. We concluded that a stratification scheme based on forest probability separated into four strata improves precision over FIAs current method of post-stratifying by forested and non-forested areas.
|Dacia Meneguzzo||Tree resources of the Great Plains interactive map viewer||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||Statewide high-resolution (1-m) datasets of tree cover have been created and published for Kansas and Nebraska. Having such detailed spatial information about tree cover provides opportunities to create value-added products that quantify the ecosystem services provided by trees outside forests. In this digital presentation, the user can view these fine-scale geospatial products that describe the location, extent, and services provided by these important tree resources.||Windbreaks and narrow riparian corridors are an undercounted tree resource particularly in agricultural landscapes. Existing geospatial datasets developed using 30-m Landsat data often prone to high rates of commission errors because these features are generally small relative to the pixel size. To address this challenge, the Forest Inventory and Analysis program and the USDA National Agroforestry Center have partnered to develop methodologies for mapping tree cover using high-resolution 1-m NAIP imagery. In this showcase, we will take the user on a tour highlighting the prevalence and diversity of trees outside forests in Nebraska and Kansas. Digital datasets have been created in partnership with the Kansas Forest Service and the University of Nebraska-Lincoln. Using ArcGIS Online, this map application will allow the user to view the high resolution datasets as well as other readily available layers which can be useful for quantifying ecosystem functions of these trees. The detailed spatial products represent the potential for scalable and consistent monitoring of these tree resources across the agricultural areas prevalent in the central United States.|
|Scott Pugh||APPLYING THE TIMBER PRODUCT OUTPUT (TPO) EXPLORER DASHBOARD WITH THE TPO SURVEY OF THE FOREST INVENTORY & ANALYSIS PROGRAM||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||The TPO Explorer is an online dashboard for investigating the current status and trends of timber harvest and roundwood use across the United States. Dashboard users can analyze and download TPO data by interacting with tables, graphs and maps. The data are from nationally consistent tables still in development and supplied by the TPO Survey Program. After finalizing the tables, the dashboard will be available as one of the new national TPO reporting tools.||The TPO Explorer is an online dashboard for investigating the current status and trends of timber harvest and roundwood use across the United States. Dashboard users can analyze and download TPO data by interacting with tables, graphs and maps. Views can be exported in various formats. The data are from nationally consistent tables still in development and originate from historic periodic and recent annual mill surveys of the TPO Survey Program. The program tracks the size and location of mills, the volume of roundwood product received, use of roundwood, and the disposition of mill and logging residue. The program is working toward achieving national consistency in data collection, processing and reporting tools. After finalizing the tables, the dashboard will be available as one of the new national TPO reporting tools.|
|Tracy Roof||Demonstrating the use of the Design and Analysis Toolkit for Inventory and Monitoring (DATIM) primarily using ATIM and SIT modules.||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||The Design and Analysis Toolkit for Inventory and Monitoring (DATIM) is a collection of applications and tools for inventory and planning purposes. This digital engagement will demonstrate DATIM focusing on ATIM and the Spatial Intersection Tool (SIT).||ATIM and EVALIDator are integrated to provide access to new estimates and allows users to run reports using the latest FIADB data. The SIT tool provides a streamlined user interface to allow users to generate new attributes using their own spatial data and will soon allow authorized users to securely intersect against real plot coordinates. DATIMs report management tool allows users to edit and share their existing reports. This digital engagement will present these new features within DATIM.
The Toolkit consists of :
(ATIM) Analysis Tool for Inventory and Monitoring
(DTIM) Design Tool for Inventory and Monitoring
(SIT) Spatial Intersection Tool
(DCS) DATIM Compilation System
|Ernesto Rubio-Camacho||Multilevel tree height models for the Mexican NFI: An alternative for data imputation and prediction||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||The aim of this study is to contribute to Mexico's NFI through the generation of a unique model for predicting the height of pine trees. For this purpose, we used 150,649 pairs of tree height-diameter data from Mexicos NFI; Three classical models were fitted throughout non-linear mixed effects approximation. The best was the Näslund model with AIC = 647279, RMSE = 1.83 and R2 = 0.88. This is the first model fitted at national scale in Mexico and it is proposed a tool for the Mexican NFI.||Tree height is used to calculate a variety of parameters such as volume, biomass and site index. However, estimating tree height is time-consuming, labor-intensive and prone to measurement errors, especially in national forest inventories (NFI). The aim of this study is to contribute to Mexico's NFI through the generation of a unique model for predicting the height of pine trees. For this purpose, we used 150,649 pairs of tree height-diameter data from 6,334 plots of Mexicos NFI database (2009-14). Three classical models, i) Näslund, ii) Curtis and iii) Schumacher were fitted throughout non-linear mixed effects approximation, using the plot as random effect. The parameters were estimated via restricted maximum likelihood (REML), while Aike's Information Criterion (AIC), root mean squared error (RMSE) and coefficient of determination R2 were used for ranking purposes. The best was the Näslund model with AIC = 647279, RMSE = 1.83 and R2 = 0.88. These results are consistent with similar studies in other countries. This is the first model fitted at national scale in Mexico, using the plot as source of random-effects for Pinus and it is proposed as a new tool for the Mexican NFI, representing an alternative for database management.|
|Karen Schleeweis||FIA and LANDFIRE 15 Years of Partnership||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||More than 15 years ago the need was recognized for national breath, locally relevant geospatial data to support Wildland Fire Decision Support. The LANDFIRE project was created to fill this need and FIA plot data and expertise has been critical to helping the LANDFIRE project meet its mission. This story map will guide its audience through a multi-media experience on this partnership, LANDFIRE data and applications over parts of the National Forest System.||More than 15 years ago the need was recognized for national breath, locally relevant geospatial data to support Wildland Fire Decision Support. The LANDFIRE project was created to fill this need and FIA plot data and expertise has been critical to helping the LANDFIRE project meet its mission. This story map will guide its audience through a multi-media experience to understand how FIA has helped support national LANDFIRE vegetation and structure mapping, how the project data supports fire decision management community and other ecological applications and how FIA partners, such as national forests are meeting planning needs by using LANDFIRE maps.|
|John Shaw||Using FIA Data in the Forest Vegetation Simulator||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||This digital engagement session is designed to provide a basic overview of FVS and its capabilities, and to illustrate a few of the many ways that FIA data can be used. It is a companion to the regular program presentation A New Source for FIA Data Suitable for Use in the Forest Vegetation Simulator.||The Forest Vegetation Simulator (FVS), maintained by the U.S. Forest Service Forest Management Service Center, is the primary tool for stand projection within the Forest Service, but FVS is widely used in other federal and state agencies, academia, and private consulting. The return of FVS-ready FIA data to the FIA Datamart begins a new period of easy access to FIA plot data for use in FVS, and new opportunities for use of projected FIA data in state reports and other analyses. This digital engagement session is designed to provide a basic overview of FVS and its capabilities, and to illustrate a few of the many ways that FIA data can be used. This Digital Engagement Session is a companion to the regular program presentation A New Source for FIA Data Suitable for Use in the Forest Vegetation Simulator.|
|Douglas Stevenson||The Plague of the Edge Zone - New correction method for area, individual tree probability and statistical distortion of cruises created by the presence of edge plots.||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||A look at mathematics and computations of forest inventory plots that fall in or near the edge zone. Edge plots may violate homoscedasticity and independence, two conditions necessary for successful measurement. Double Meridian Distance provides a new way to correct for reduced plot area. Use of a computer allows the forester/cruiser to make the proper measurements while in the field. Plot area, individual- tree sampling probability and statistics of "ghost trees" are examined.||Inventory plots overlapping a stand boundary create size, probability and statistical problems plaguing foresters. Double Meridian Distance allows a correction factor to be calculated for the smaller (net) plot area. A zigzagging stand boundary is used as a reflection surface to determine individual tree weights for the Mirage Method. Both techniques are applied to curving stand boundaries such as roads and rivers. The method works on plots with any number of sides up to infinity. The methods are computationally intensive and require programming and a computational device to use in the field.
Trees in the edge strip have a reduced sampling probability which invalidates homoscedasticity; edge plots cannot be moved or deleted, but must be corrected instead. A process similar to the mirage method can be used to compute corrections on a tree-by-tree basis.
Ghost trees created by the Mirage Method and as a result of applying correction factors are not real trees. They do not contribute to degrees of freedom. Cruise statistics are distorted by their presence and must be corrected.
Correction methods will be reviewed and illustrated using a PowerPoint presentation and/or a printed poster presentation.
|Sergio Villela Gaytán||National inventory plots as random effects help explain the crown plasticity of mangroves||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||We contribute to the knowledge of mangrove ecosystems on the NFI of México using information from 74 plots to construct a multiple linear mixed effects model, the covariates were the diameter of the tree and the total height, while the random effects were the plots. The final mixed model had a cAIC = 7386.6 RMSE = 1,141 of and R2 = 0.66. In conclusion, mixed effects models become a useful tool not only for prediction but also to explain ecological processes.||We contribute to the knowledge of mangrove ecosystems through the Mexican National Forest Inventory information through building a model for prediction the crown width of mangroves using mixed effects models. We used information of 74 plots to build a multiple linear mixed effects model, the covariates were tree diameter and total height, while the random effects were the plots. The parameters were estimated via REML and AIC, the root mean squared error and the coefficient of determination R2 to evaluate the model. The mixed model was tested against the regular linear model through the Likelihood Ratio Test in order to assess the influence of the random effects. The random effects help explain the crown variation of mangroves. The results of the comparative procedures showed a better behaviour of the mixed model (x2(1) = 1424, p < 0.0001). The final mixed model had a cAIC=7386.6 RMSE = 1.141 of and R2 = 0.66. In conclusion, the mixed effects models become a useful tool not only for prediction but also to explain the ecological processes that influence the structure of the mangrove in response to changes in time that may be related to the effect of storms, changes in land use or the long-term effects of climate change.|
|Christopher Woodall||Monitoring a Future of Burning Forests: Combining a FIA fuel inventory dashboard with real-time fuel moisture measurements||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||Given an expected future of increased tree mortality and rising temperatures, it is expected that forest fire hazards will increase. In order to meet expected future resource management and wildfire fighting needs, a FIA down woody materials data dashboard was combined with emerging data from a real-time fuel moisture monitoring sensor network to enable user exploration of sub-diurnal forest wildfire hazards.||The FIA program conducts an annual inventory of Down Woody Materials (DWM) across the United States which enables creation of a spatial data dashboard of fuel attributes. Such National Fire Danger Rating System fuel attributes includes the mass of fine and coarse woody debris, otherwise defined as 1-hr to 1,000-hr fuels. Beyond fuel loading estimates, another vital component of estimating the probability of fuel ignition at any location is the air temperature and fuel moisture. In order to create a more temporally and spatially resolved estimate of wildfire hazards, a FIA DWM fuels dashboard was combined with real-time fuel moisture measurements from a sensor network to explore the opportunities and remaining hurdles towards creating such a real-time wildfire hazard digital tool for the wildfire community.|
|Rebekah Zehnder||Southern Timber Supply Analysis: Forest Inventory Data for All||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||The Southern Timber Supply Analysis web application summarizes USDA Forest Service Forest Inventory and Analysis (FIA) data for a user-defined supply area. The easy-to-use application produces estimates of the amount of timberland and standing timber, growth, and removals within a user-specified distance or trucking time of a site of interest in the U.S. South. Southern Timber Supply Analysis broadens delivery of FIA data, simplifying the process of examining forest inventory and sustainability.||The Southern Timber Supply Analysis web application summarizes USDA Forest Service Forest Inventory and Analysis (FIA) data for a user-defined supply area. The application produces estimates of the amount of timberland and standing timber, growth, and removals within a user-specified distance (50, 75, or 100 miles) or trucking time (1, 1.5, or 2 hours) of the users site of interest in the U.S. South. The analysis can be filtered by state and ownership, and timber quantities can be displayed by volume or by green weight. The results can be downloaded in a PDF report. The application also contains pre-made statewide reports available for download.
Designed specifically for ease of use, Southern Timber Supply Analysis simplifies the process of examining forest inventory levels and sustainability within a custom area. It presents the results equivalent to running numerous EVALIDator queries in a matter of seconds, with very little effort required by the user. The information available through Southern Timber Supply Analysis will support economic development, conservation and sustainability efforts, and state forestry agencies and associations.
|Rebekah Zehnder||My Citys Trees: Delivering Information from Urban FIA Data||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||My Citys Trees delivers Urban FIA data to a broad audience in a user-friendly interface, making the complex database accessible to average users. The information presented in the application provides a basis for strengthening urban forest management and advocacy efforts by empowering city government, non-profit organizations, and consultants with valuable data that is easy to access and understand.||My Citys Trees delivers Urban FIA data to a broad audience in a user-friendly interface, making the complex database accessible to average users. The use of themes to break down city-wide estimates into selected areas of the city remains a main feature of My Citys Trees. Themes, such as ecoregions, watersheds, or income level, are selected independently for each city to reflect local resource issues. Available estimates include tree counts, carbon storage, energy savings, and more.
The web application received some major updates in 2019, including improved functionality and additional features as well as data for more cities. Information on the status of Urban FIA in participating cities is available on the map. The revamped app has better reporting capability users are now able to produce a full report or one-page summary for their area in PDF format and share it directly from the application. Estimates now include breakdowns by diameter class and land use in addition to ownership. Data for San Diego and San Antonio are now available along with Austin and Houston data. The 2019 release of My Citys Trees is designed to work seamlessly across devices of all sizes, from smart phones to desktops.