|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.|
|Charles Perry||Can I get fries with that? Successes and continued challenges for BIGMAP||Wednesday||2a||Salon D/E||Large-scale computing applications in FIA||FIA entered into a partnership to deliver BIGMAP (Big Data Mapping and Analytics Platform): a cloud-based system for scalable production, analysis, and delivery of integrated geospatial products. Authoritative, science-based outputs support decision-making for private and public land management planning, resource allocation, and landscape sustainability. We will also review persisting challenges associated with partnerships and IT applications in a rapidly evolving political environment.||The Forest Inventory and Analysis (FIA) Program entered into a public:private partnership with the USDA FS CIO Geospatial Services Branch and Esri, Inc. to configure BIGMAP: the Big Data Mapping and Analytics Platform. We are entering the final year of our four-year agreement to deliver a prototype cloud-based system for scalable production, analysis, and on-the-fly delivery of massive, integrated, geospatial products. This solution is notable for its use of a commercial off-the-shelf (COTS) software solutions in a secure cloud environment. The resulting authoritative science-based products are designed to support decision-making for private and public land management planning, resource allocation, and landscape sustainability assessments. BIGMAP is designed to address several agency priorities, and this presentation will highlight several applications available for hands-on exploration during the digital engagement session. We will also review several persisting challenges associated with this type of partnership and IT applications in a rapidly evolving political environment.|
|Barry Wilson||Development of BIGMAP: a cloud-based national scale modeling, mapping, and analysis environment using Esri Raster Analytics||Wednesday||2a||Salon D/E||Large-scale computing applications in FIA||This presentation describes efforts to configure BIGMAP, a cloud-based national scale modeling and analysis environment built upon Esri software in Amazon's cloud. A pilot project was designed for testing BIGMAP with a set of use cases covering the range functionality required. This presentation focuses on use cases to support for national carbon reporting and small area estimation. It provides an overview of the architecture and configuration, example workflows and outputs, and lessons learned.||With the burgeoning remote sensing sector and the growing volume of imagery available at finer resolutions, new approaches are needed to support FIAs techniques research and national scale applications. Cloud-based solutions provide the flexibility to marshal the computing resources needed, and place algorithms and data together in a common environment.
This presentation summarizes efforts to configure the BIGMAP environment, built upon Esri software utilizing Amazon Web Services (AWS). A pilot project was designed to test this environment with a set of use cases intended to cover much of the range of functionality required. This presentation focuses on two of these use cases: a) support for national carbon reporting, and b) small area estimation.
The presenters will provide a brief overview of Esri Raster Analytics. They will discuss the process of architecting the AWS infrastructure and subsequent software configuration and performance testing of environment. They will address the technical challenges of taking use case workflows that were originally developed under different programming paradigms and adapting them to fit within BIGMAP. Finally, they will present some of the outputs produced to date and lessons learned.
|Sean Healey||Cloud computing supporting land cover change mapping||Wednesday||2a||Salon D/E||Large-scale computing applications in FIA||We highlight uses of a cloud platform for: detecting forest disturbances in the US; mapping land cover and use change across East Africa; and, merging a global sample of lidar data with wall-to-wall image data from Landsat to make statistical estimates of biomass over user-requested areas. Were learning lessons about forest cover and land use change that would have been inconceivable without huge expense just five years ago.||Since the beginning of the Landsat program in the 1970s, scientists have been using the platforms imagery to map land cover and land cover change. When the Landsat archive became free in 2008, algorithms using annual or even all acquisitions began to proliferate, with demonstrable benefits in sensitivity and accuracy. However, these algorithms have only begun to reach their potential as cloud computing has become more accessible. Several developments have driven the entire remote sensing field toward cloud platforms: 1) emerging evidence of the effectiveness of new, computationally intensive algorithms; 2) the sheer number of images now available; 3) the need to share ideas and code across increasingly diverse teams, and 4) the need for on-the-fly access to imagery for new user engagement applications.
We highlight uses of a cloud platform for: detecting forest disturbances in the US; mapping land cover and use change across East Africa; and, merging a global sample of lidar data with wall-to-wall image data from Landsat to make statistical estimates of biomass over user-requested areas. Were learning lessons about forest cover and land use change that would have been inconceivable without huge expense just five years ago.
|Kasey Legaard||Use of multi-objective machine learning and high performance computing to reduce prediction bias in forest maps||Wednesday||2a||Salon D/E||Large-scale computing applications in FIA||We have developed machine learning techniques that reduce systematic error when mapping forest attributes from multispectral satellite imagery and FIA plot data. Our approach combines support vector machines with a genetic algorithm to simultaneously minimize total and systematic error. Large-scale applications are supported through the use of modular and highly parallelized software executed on University of Maine cloud computing resources and computing clusters.||Methods used to produce maps from satellite imagery and forest inventory plot data generally result in patterns of error that are detrimental to many applications. We have developed machine learning techniques that reduce systematic error when mapping forest attributes from multispectral satellite imagery and geospatial data. Our approach is based on the optimization of support vector machines using a multi-objective genetic algorithm designed to simultaneously minimize total and systematic error. Using FIA plot data we have mapped tree species occurrence and relative abundance across Maine and obtained outcomes that compare well against other approaches. Our methods are highly generalizable and automatable, but also computationally demanding. Large-scale applications require use of high performance computing resources. We have developed efficient software for use on University of Maine cyberinfrastructure, including modular image processing and data handling workflows implemented on the cloud, and highly parallelized model training and map production code executed on a computing cluster. Our intention is to support a broad set of research and management applications through the production of high-quality spatial data at low cost.|
|Tony Chang||Utilizing cloud-computing for implementing a deep convolutional neural network based forest structure and classification model||Wednesday||2a||Salon D/E||Large-scale computing applications in FIA||Development and implementation of new biomass/carbon models require increased computational hardware that include large amounts of memory and access to GPUs. Contemporary cloud-compute platforms allow for such computational loads for parameter fitting state-of-the-art deep learning models. This research demonstrates a cloud-based approach to perform both classification and regression concurrently based on a large FIA training data set and these next generation models.||In recent years, the increased availability of high-resolution (<30 m) imagery and advancements in machine learning algorithms have opened up a new opportunity to fuse multiple datasets of varying spatial, spectral, and temporal resolutions. Here, we present a new model, based on a deep learning architecture, that performs both classification and regression concurrently, thereby consolidating what was previously several independent tasks and models into one stream. The model, a multi-task recurrent convolutional neural network that we call the Chimera, integrates varying resolution, freely available aerial and satellite imagery, as well as relevant environmental factors (e.g., climate, terrain) to simultaneously classify five forest cover types (conifer, deciduous, mixed, dead, none (non-forest)) and to estimate four continuous forest structure metrics (above ground biomass, quadratic mean diameter, basal area, canopy cover). We demonstrate the models ability and performance on the Azure cloud-computing platform for model training on 9967 georeferenced FIA field plots within California and Nevada, and then implement a large scale prediction for the Sierra Nevada region to understand the viability of this new approach.|
|David Bell||An integrated disturbance and vegetation mapping fra,ework highlights landscape level changes in forest dynamics during a multiyear drought||Wednesday||2a||Salon D/E||Large-scale computing applications in FIA||NEED||NEED|
|Chad Babcock||Remote sensing-assisted multivariate hierarchical spatial models for simultaneous prediction of multiple forest carbon pools||Wednesday||2b||Salon D/E||Advances in estimating carbon stocks and fluxes on forest land, woodlands, and urban trees across space and through time||We build a multivariate hierarchical spatial model to simultaneously predict six forest carbon pools across the continental US. Leveraging Landsat remote sensing information and cross-correlations between separate carbon pools, we are able to improve spatial prediction and generate small-area forest carbon estimates with better precision than current FIA procedures that use only field plot data.||The FIA monitors six forest carbon pools by taking repeat measurements on plots, including (1) live tree, (2) understory, (3) standing dead, (4) downed dead wood, (5) litter and (6) soil organic carbon. Some pools, such as live tree and standing dead, can be highly correlated with remote sensing data. However, other pools, such as litter and soil organic carbon, can be very weakly correlated with remote sensing products. All six forest carbon pools themselves typically are highly related, i.e., cross-correlated. These cross-correlations are useful information that, if appropriately modeled, can improve remote sensing-assisted prediction for all six pools. We demonstrate how a multivariate hierarchical spatial model can be paired with remote sensing data to predict multiple forest carbon pools simultaneously. Because we are using a unified multivariate framework for spatial prediction, we can explicitly model the cross-correlations between the six carbon pools. Our model is informed by FIA forest carbon pool plot data as response variables and Landsat-derived metrics as explanatory variables. Using this model framework, we make 30 meter spatial predictions for all NLCD-classified forest areas in the continental US.|
|Lucia Fitts||Effects of disturbances and land use change on carbon stocks in six US states||Wednesday||2b||Salon D/E||Advances in estimating carbon stocks and fluxes on forest land, woodlands, and urban trees across space and through time||This research focuses on how disturbances and land use change affect carbon stocks by first doing a model using a machine learning algorithm and a generalized mixed effects model to predict the probability of land use change in FIA plots from 2000 to 2017. Predictions from these models were used to create a regression with spectral information from Landsat imagery and produce a wall-to-wall probability map of land use change.||Forests serve as a large terrestrial carbon sink. Land use change is a major threat to forested areas, but the likelihood of change in forested areas is unknown. This research focuses on forest as a land use, and how forest conditions and population growth affect the carbon stocks in six U.S. states. The goals of the study are (1) to quantify the impacts of forest disturbances on the probability of forest becoming non-forest and (2) to quantify the resiliency of forest carbon stocks when faced with forest disturbances. FIA data was used to generate models with two approaches: a machine learning algorithm (random forest), and generalized mixed effects models. Predictions from these models were used to create a regression with spectral information from Landsat imagery and produce a wall-to-wall probability map of land use change. Results indicate that land use change from forests is more likely with increasing population and housing growth rates, and non-public areas have a higher probability of forest change. Furthermore, disturbances were not a major predictor of land use change. This study provides information for decision makers and land managers for designing policies and practices aimed at mitigating climate change.|
|Richard Birdsey||A User Protocol for Greenhouse Gas Inventories of Forests and Trees at Community Scale: Combining Forest Inventory and Remote Sensing||Wednesday||2b||Salon D/E||Advances in estimating carbon stocks and fluxes on forest land, woodlands, and urban trees across space and through time||A new GHG protocol is designed to support forestry-related decisions by communities for achieving net reductions in emissions. Land management decisions are typically made at small scales; yet, barriers to accessing and using data and models has prevented consideration of land management options. We have designed and tested a protocol that can be used by local planners to access publicly available data and compile estimates of GHG emissions and removals for forests and trees outside forests.||A new greenhouse gas (GHG) protocol is designed to support forestry-related decisions by communities (i.e., municipalities, counties, land-based cooperatives, large ownerships, states) for the purpose of achieving net reductions in GHG emissions. Land management decisions are typically made at relatively small scales such as U.S. counties; yet, barriers to accessing and using data and models has resulted in a lack of consideration of land management options in the hundreds of city and county climate action plans across the country. Working closely with city, county and municipal stakeholders, we have designed and tested a protocol that can be used by local planners to access publicly available data and compile estimates of GHG emissions and removals for forests and trees outside forests. Foundational data include the National Land Cover Data (NLCD) and Forest Inventory Data (FIA), both readily accessible for all areas of the conterminous U.S. The results of three case studies demonstrate how the protocol works. This protocol is associated with ICLEI - Local Governments for Sustainability, whose ClearPath is the online software platform used by US communities to report greenhouse gas inventories.|
|Nancy Harris||Mapping global climate mitigation potential from reforestation||Wednesday||2b||Salon D/E||Research suggests that reforestation is the single largest natural solution for mitigating climate change, but the geographic distribution of reforestations sequestration opportunity remains poorly characterized. Here we combine plot networks with machine learning to map near-term forest carbon sequestration potential with more geographic specificity than the regional estimates that currently exist.||Recent research suggests that reforestation is the single largest natural climate solution for mitigating climate change, and many countries have prioritized forest activities in their Nationally Determined Contributions (NDCs) to the Paris Agreement. However, the magnitude and geographic distribution of reforestations sequestration opportunity remains poorly characterized. One contributing factor is limited data on rates of biomass accumulation, which are spatially highly variable and influenced by numerous biophysical and management factors. By combining existing georeferenced field plot networks from around the globe (including FIA plots), biophysical predictor variables, and machine learning, we mapped current and potential future carbon sequestration potential of natural forest regeneration over the next 20-30 years with more geographic specificity than the regional estimates that currently exist. This type of information can help improve existing GHG inventories at subnational scales where management decisions often take place, and enable local decision makers to evaluate the feasibility, time frame, magnitude, and extent to which reforestation could contribute to and enhance NDCs and local Climate Action Plans.|
|Glenn Christensen||U.S. West Coast Forest Carbon Stocks and Flux: Results from recent analysis and using FIA data as basis informing state-led forest carbon emission mitigation policies||Wednesday||2b||Salon D/E||Following Californias lead, Oregon and Washington along the U.S. West Coast increasingly seek to adopt climate goals through specific strategies reducing carbon (C) emissions. The PNW Research Station developed new partnerships with Oregon and Washington that use FIA data to assess current C stocks and flux on forest land and estimate statewide rates of carbon dioxide (CO2) sequestration. Findings by state including notable differences in growth and mortality in the tree C pool are presented.||Following Californias lead, Oregon and Washington along the U.S. West Coast has increasingly sought to adopt climate goals through specific strategies to reduce carbon (C) emissions. Understanding the role forests play in each states overall C stocks and flux is critical to developing, implementing, and monitoring these strategies. Similar to the role FIA continues to play in California and our partnership with the California Department of Forestry and Fire Protection (CAL FIRE), the Pacific Northwest Research Station has developed new partnerships with the Oregon Department of Forestry and Washington State Department of Natural Resources to assess current C stocks and flux on forest land in order to estimate a statewide rate of carbon dioxide (CO2) sequestration. We present the latest findings from California, Oregon, and Washington including notable differences in growth and mortality in the tree C pool. The future direction of this work are discussed including state-led efforts improving the reporting and confidence of FIAs forest C stock and flux estimates.|
|Todd Morgan||Leveraging TPO data for HWP carbon storage in the PNW||Wednesday||2b||Salon D/E||Stakeholders in FIAs Pacific Northwest (PNW) region have interest in quantifying carbon (C) stored in harvested wood products (HWP) because of state climate goals regarding C emissions. University of Montana researchers have used timber product output (TPO) information and an IPCC based carbon storage model developed by the Forest Service to quantify C stored in landfills and products made from historic and recently harvested timber in California and Oregon, with a Washington study pending.||Stakeholders in FIAs Pacific Northwest (PNW) region have interest in quantifying carbon (C) stored in harvested wood products (HWP) because of state climate goals regarding carbon emissions. The FIAs Timber Product Output (TPO) program quantifies and characterizes timber used for products and disposition of mill residue, using mill surveys and logging utilization studies. In the PNW Region, this survey work is conducted by the University of Montanas Bureau of Business and Economic Research (BBER). Working with PNW-FIA, BBER researchers are using the Intergovernmental Panel on Climate Change (IPCC) production accounting approach to estimate HWP-C storage in California, Oregon, and Washington with a model developed by the Forest Service as well as timber harvest, primary products and residue generated by timber-processing facilities. Results from California and Oregon indicate HWP-C storage is a fraction of ecosystem C storage. However, being able to consistently quantify C stored in HWP through time and across political boundaries will allow stakeholders and policy makers to better understand the role that timber harvested and used for wood products plays in total forest carbon storage and flux.|
|Jeremy Fried||Propensity score matching analysis of FIA remeasurement across diverse West Coast forests yields insights on drivers of in-forest carbon sequestration||Wednesday||2b||Salon D/E||Marginal impact of stand structure, management and disturbance on above-ground net carbon increment was analyzed via propensity score matching on NFS and private FIA plot subsets in WA, OR and CA. Carbon increment associated positively with active management, site quality, and initial inventory everywhere. Even-aged stand structure elevated increment in coastal PNW. Fire, insect, and disease reduced increment inland. High QMD reduced stand level carbon accumulation everywhere.||To estimate stand structure, management and disturbance influence on above-ground net carbon increment on timberland, we developed matched subsets totaling 3920, not recently harvested, remeasured, forest service and private FIA plots in WA, OR and CA. Grouping plots into four regions (PNW coast/inland and PSW coast/inland), we applied propensity score matching (PSM) to generate comparable plot subsets for a better apples to apples evaluation of the marginal influence of those drivers on above-ground live tree carbon increment. As expected, carbon increment associated positively with site quality and initial inventory everywhere. Even-aged stand structure associated with higher increment only in PNW coastal. Negative impacts of fire, insect, and disease were evident in only inland regions. Higher quadratic mean diameter of trees reduced carbon increment in all regions. The more active forest management common on private timberlands elevated carbon increment in all regions, all else equal. PSM presents a promising approach for creating datasets amenable to evaluating the effect of discrete variables that arent randomly distributed across the forested landscape but are key to testing policy relevant forest management hypotheses.|
|Marin Palmer||Intensified FIA grid for BLM and NFS; partnership success in the Pacific Northwest||Wednesday||2c||Salon D/E||Building Strong Partnerships: NFS and FIA||In 2018, OR BLM adopted the FIA sampling design as their strategic vegetation inventory. This expanded the partnership between PNW-FIA and NFS Region 6 to include OR BLM, integrating the vegetation inventories of both agencies. The FIA infrastructure enables both agencies to make inventory data available to the public and capitalize on FIAs national estimation tools, and is an example of the all lands approach to shared stewardship.||Forest Inventory and Analysis (FIA) is a key data source for monitoring late-successional old growth and associated wildlife habitat components in the Pacific Northwest. Through a strong partnership with the Pacific Northwest Research Station FIA program (PNW-FIA), NFS R6 implemented a 3x spatial intensification of FIA plots across all non-wilderness NFS R6 lands beginning in 2001, providing more detailed information about the status and trends of forest resources on NFS lands. Prior to FIA annual inventory, both NFS R6 and OR BLM had a similar inventory known as CVS (current vegetation survey).
In 2018, OR BLM adopted the FIA sampling design as their strategic vegetation inventory. This expanded the partnership between PNW-FIA and NFS Region 6 to include OR BLM, integrating the vegetation inventories of both agencies. The FIA infrastructure enables both agencies to make inventory data available to the public and capitalize on FIAs national estimation tools, and is an example of the all lands approach to shared stewardship.
|John Shaw||A New Source for FIA Data Suitable for Use in the Forest Vegetation Simulator||Wednesday||2c||Salon D/E||Building Strong Partnerships: NFS and FIA||The Forest Vegetation Simulator (FVS) is an essential tool for National Forest planning, and also has a large user base outside National Forest Systems. A large portion of FVS users have an interest in using FIA data, but FVS-ready data have not been available for several years. A new translation and data delivery process makes FVS-ready data available for all plots available in FIADB, allowing users to download data by state and project FIA plot data at the condition, plot, or subplot level.||Not since the retirement of the Forest Inventory Mapmaker in 2008 has the FIA program provided users with FIA data prepared for direct use with the Forest Vegetation Simulator (FVS). The Forest Management Service Center, developers of FVS, provided a translator for several years, but upkeep was difficult in light of frequent changes to FIADB and regional variation in data. Other FIA-based tools, such as BioSum and DATIM, extract FIA data into FVS-usable format, but these translations are not readily usable to users of FVS as a stand-alone tool. The new process pre-translates all plots present in FIADB into FVS-ready format and stores the FVS-ready data in a separate schema. The tables are then added to FIADB tables in a single, state-level SQLite database and delivered through the FIA Datamart. Having FIADB and FVS-ready tables in a common database provides FVS users with capabilities not previously available. With a simple Group selection in the current FVS interface tools, Suppose and FVS Online/Onlocal, users can project FIA data by condition, whole plot, or subplot. A series of user guides will cover topics such as properties and manipulation of the FVS-ready tables, and guidance on FVS projections for use in forest planning.|
|Kevin Megown||Landscape Change Monitoring System - Delivery and Use For Forest Service (NFS)||Wednesday||2c||Salon D/E||Building Strong Partnerships: NFS and FIA||This talk will briefly describe the LCMS outputs, the delivery of LCMS data and applications identified within the NFS Deputy area.||The Landscape Change Monitoring System (LCMS) is a Forest Service, Landsat based, annual national geospatial data product describing land cover change for every year from 1984 to the present. The LCMS product used together with other Forest Service enterprise data can support multiple business needs across FS Deputy areas, including R&D, NFS and S&P. This talk will briefly describe the LCMS outputs, the delivery of LCMS data and applications identified within the NFS Deputy area.|
|Alexa Dugan||Innovations in addressing carbon in NEPA and National Forest Planning||Wednesday||2c||Salon D/E||Building Strong Partnerships: NFS and FIA||The U.S. Forest Service produced two nationally-consistent reports for all NFS units using FIA data and several empirical modeling tools to provide key information on forest carbon trends and influences. Drawing on the best available science and aligning with current policy, we developed four templates to serve different NFS needs. These templates have greatly increased efficiency, while improving the quality and legal defensibility of information used for decision making.||There has been a growing demand for forest carbon information to support national forest system (NFS) planning and National Environmental Policy Act disclosures. The U.S. Forest Service produced two carbon reports for all NFS units using Forest Inventory and Analysis (FIA) data and several empirical modeling tools to evaluate forest carbon trends and influences. Because these reports are nationally-consistent, we were able to develop a template-based approach to address carbon in decision making documents that align with current policy. This approach has improved understanding of forest carbon dynamics by managers and stakeholders. These templates have also greatly increased efficiency, while improving the quality and legal defensibility of information used for decision making. The templates work synergistically with one another and embody a number of innovations, creating an effective information delivery system that staff with even little training in carbon can use accurately. The data on which these templates are based are becoming dated and information needs and estimation methods have evolved, so we are looking to support the development of new FIA-based carbon reports to continue to serve NFS needs.|
|Melissa Hamid||Collaborative Governance Leadership Competencies in Federal Natural Resource Management Partnerships||Wednesday||2c||Salon D/E||Building Strong Partnerships: NFS and FIA||This talk will review research on natural resource management partnerships and collaborative governance theory/frameworks. The talk will also present growing calls in the global literature to identify non-technical and interpersonal leadership competencies that could help improve future partnership outcomes.||Effective leadership is important to collaborative governance outcomes in Federal natural resource management partnerships. Within the natural resource field, there is a growing call in the literature to continue to explore interpersonal and other leadership competencies that could be leveraged by government to facilitate more effective collaborative partnership outcomes. It is not known how Federal government and natural resource management partner organization executives perceive the influence of leadership competencies on the formation and maintenance of effective collaborative governance processes and partnerships. There is a paucity of empirical information relating to leadership competencies that would benefit intended public outcomes involving collaborative governance partnerships. A qualitative descriptive study is planned to explore leadership competency perceptions from participants in natural resource management partnerships to study the phenomenon of collaborative governance.|
|Kristen Pelz||Integrating FIA data into National Forest management through the Forest Plan Revision process: Work in progress on the Salmon-Challis National Forest||Wednesday||2c||Salon D/E||Building Strong Partnerships: NFS and FIA||On the Salmon-Challis National Forest, FIA data were used in the assessment, and with an interdisciplinary team analysis is being used to help with development of plan components and identify potential uses of data for monitoring. This presentation will outline what has worked, challenges of working with FIA data in the plan revision context, and potential monitoring plans for the future.||National Forests, under the current planning rule are required to use best available scientific information (BASI) for assessing forest conditions, developing a forest plan, and monitoring conditions as they relate to the plan. Forest Inventory and Analysis data can be one source of BASI, but because of the scale of data and lack of familiarity with it, the data can be difficult to integrate with other data sources. On the Salmon-Challis National Forest, FIA data were used in their assessment, and with an interdisciplinary team analysis is being used to help with development of plan components and identify potential uses of data for monitoring. This presentation will outline what has worked, challenges of working with FIA data in the plan revision context, and potential monitoring plans for the future.|
|Emrys Treasure||Evaluating Existing Longleaf Pine Ecosystem Condition with Forest Inventory and Analysis (FIA)||Wednesday||2c||Salon D/E||Building Strong Partnerships: NFS and FIA||The Range-Wide Conservation Plan for Longleaf Pine established condition-based restoration goals for 2025. Initial estimates were based on FIA forest-type and FSVeg data, with condition calls based on professional judgement. We used metrics developed in conjunction with NatureServe to assess condition on all FIA plots containing at least one longleaf pine using plot measurements. Though this approach likely overestimates longleaf area, it shows great promise in characterizing existing condition.||The Range-Wide Conservation Plan for Longleaf Pine established condition-based restoration goals to meet by 2025. The initial 2009 estimate of 3.4 million existing acres was based on a combination of FIA and local inventory data (i.e., FSVeg) for NFS lands. The split between maintain and improve/restore was based on professional judgement with limited sampling. Since then, NatureServe led an interagency effort to better define condition classes for longleaf pine ecosystems. These Open Pine Metrics score various criteria, which are combined to produce an overall condition class. There are 13 Open Pine Metrics, though FIA protocol only collects sufficient data to score 7 of them. We selected all FIA plots that contained at least one longleaf pine, and used the relevant FIA plot measurements to assign a condition. Preliminary results estimate considerably more longleaf pine area than previous estimates based on FIA forest-type, though this likely is an overestimate from including plots where longleaf ecosystems are not desired. Despite the need for further refinement, this approach shows promise in characterizing existing condition based on the best available science using the most robust data available.|
|Rebecca Tavani||The importance of NFIs in the international context||Thursday||2a||Salon D/E||Global view of national forest inventories (NFIs): how they have progressed, ways they have utilized partnerships, and possibilities for the future.||Rebecca Tavani is a Forestry Officer working for FAO in support of national forest inventories. She has 12 years of experience in providing technical and programmatic NFI support to countries in the African region (e.g. The Gambia, Uganda, Liberia, Ethiopia, Zambia) under the National Forest Monitoring and Assessment (NFMA) & REDD+ programmes at FAO. She has a B.A. in Biology from Brown University and a Masters of Forestry from the Yale School of Forestry and Environmental Studies (FES).||For more than 50 years, FAO has been supporting countries to collect forest information through national forest inventories (NFI) that meet national and international information needs operating on the premise that better information leads to improved decisions, which leads to more effective action in the forest sector and beyond. Today, FAO is supporting multipurpose NFIs in over 20 countries. The data collected has supported countries in both national and international reporting, particularly in meeting the reporting requirements of the Paris Agreement. NFI data has been critical to the construction of national & sub-national forest reference levels as well as in providing improved biomass estimates for updating IPCC default emission factors. In this presentation, current FAO support to global NFI efforts will be presented focusing on the application of the data to REDD+ processes and related challenges.|
|Andrew Lister||Progress on National Forest Inventories||Thursday||2a||Salon D/E||Global view of national forest inventories (NFIs): how they have progressed, ways they have utilized partnerships, and possibilities for the future.||The panel will discuss elements of the progress of the participants national forest inventories. These include technical challenges and solutions; efforts to achieve institutionalization; management of data processing, reporting and information technology; and use of technologies like data recorders and remote sensing to help improve the inventories. Other topics will include how to manage change and adjust inventory design as lessons are learned.||See summary -- this is for the panel 2 of the international session|
|Andrew Lister||Thursday||2a||Salon D/E||Global view of national forest inventories (NFIs): how they have progressed, ways they have utilized partnerships, and possibilities for the future.|
|Kaffo Eric||State of the National Forest Inventories in Cameroon: challenges and perspectives||Thursday||2a||Salon D/E||Cameroon carried out its last national inventory of its forest resources with the technical support of the FAO between 2002 to 2004, FAO. The process covered only 45% of the country's area. As part of regular small inventories for forest concessions and other small areas, Cameroon is planning to realize a new national forest inventory which will help the country updating most of the forest data but also provide information for the REDD+ process.||Cameroon carried out a national inventory of its forest resources with the technical support of the Canadian International Development Agency (CIDA) between 1982 and 1990 on about 14 million hectares, or 29.47% of the territory. From 2002 to 2004, FAO decided to support a second national forest inventory, which covered 45% of the country's area this time around.
The methodology used in these inventories was based on stratified sampling. As part of the work, partnerships were established with academic and research institutions, as well as the national herbarium. As the main results, the FAO NFI helped for development of volume rates for the estimation of standing tree volumes as well as updating the phytogeographic map of Cameroon.
In addition to these inventories, others are carried out on a regular basis on smaller areas, including management inventories, as well as exploitation inventories, in each parcel of forest to be logged. Unfortunatly, most of the data are out of date and qualified personnel are retired.
As prospects, it is envisaged to the realization of a new forest inventory to update the volume rates, and estimate the the biomass, as well as carbon stocks in connection with the REDD + mechanism.
|Sara Goeking||Partnerships in national forest inventories: Benefits, challenges, and characteristics||Thursday||2a||Salon D/E||This panel will discuss partnerships in national forest inventories (NFIs), which often involve cooperation among multiple in-country institutions, neighboring countries, and global organizations. Panelists will discuss benefits and challenges derived from partnerships, including their effects on information sharing and data transparency. Other topics include decision-making for international reporting and strategies for engaging stakeholders who can offer critical feedback to the NFI.||See summary. This Summary applies to a single Panel discussion, labeled as Panel 1.a and 1.b in the session submission.|
|Sara Goeking||Thursday||2a||Salon D/E|
|Sonja Oswalt||Forest Resources of the United States, 2017: Informing the Nation, the Continent, and the Globe||Thursday||2a||Salon D/E||This presentation shares the outcome of the 2017 U.S. Forest Resources Report, progress on the North American Forest Database as well as lessons learned, and the process by which the United States participates in the global Forest Resources Report.||The FIA program contributes statistics to the federally mandated Resources Planning Act every 10 years, with 5 year updates. These statistics contribute not only to domestic policy action, but have international implications, as well. Currently, through the work of the North American Forest Commission, forestry agencies in the U.S., Canada, and Mexico have worked to align data definitions from their respective forest inventories in a manner sufficient for combination in a continent-wide database. Additionally, FIA statistics continue to feed into the United Nations Food and Agriculture Organization (UN FAO) report on global forest resources. This presentation shares the outcome of the 2017 U.S. Forest Resources Report, progress on the North American Forest Database as well as lessons learned, and the process by which the United States participates in the global Forest Resources Report.|
|Dooley Kerry||Possibilities for national forest inventories||Thursday||2a||Salon D/E||This panel discusses possibilities for national forest inventories (NFIs) growing into the future. Discussions will include how to manage competing demands of producing consistent data over time versus incorporating data of emerging importance, including how to anticipate changing demands and building in resilience for inventories. Panelists will share specific examples of challenges they have overcome; how NFIs improve research, management or policies; and their hopes for NFIs in the future.||See summary|
|Dooley Kerry||Thursday||2a||Salon D/E|
|Aurea Erica Aponte||"The challenge of the Peruvian State in leading the conservation of relict forests of Polylepis through the National Forestry and Wildlife Inventory: Challenges and opportunities to make decisions"||Thursday||2a||Salon D/E||In recent years, communities around the world have had a central role in local forest management and ecosystem conservation. In the Andes of Peru, peasant communities have a long tradition of forest management based on a particular world view. The information generated by the National Forestry and Wildlife Inventory (Inventario Nacional Forestal y de Fauna Silvestre -INFFS in Spanish) provides information on the current situation of the relict forests of Polylepis "Queuña."||In recent years, communities around the world have had a central role in local forest management and ecosystem conservation. In the Andes of Peru, peasant communities have a long tradition of forest management based on a particular world view. The information generated by the National Forestry and Wildlife Inventory (Inventario Nacional Forestal y de Fauna Silvestre -INFFS in Spanish) provides information on the current situation of the relict forests of Polylepis "Queuña." In this context, the Government of Peru, through SERFOR, implements the INFFS in all forests. Through 1855 sample units, of which 489 are in the Andes ecozone, mountain forests containing "queñuales" (local name for Polylepis trees) are examined. The challenge is to characterize the composition, structure, state of conservation and benefits that the Polylepis forests generate for rural communities. The methodology consists in organizing permanent sample units in "L" shaped conglomerates of ten circular sampling subunits of 500 m2 each, where trees larger than 10cm dap are measured. Currently, 67 Sample Units (SU) have been evaluated, of which Polylepis trees are found in 13 SU. Additionally, it should be noted that in Peru there are approximately 21 Polylepis|
|Dooley Kerry||International session Wrap-up||Thursday||2a||Salon D/E|