|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.|
|Mark Majewsky||Urban FIA: Integrating all lands inventories into the national work flow||Wednesday||1a||Cherokee||Urban FIA update and latest results||Installing plots in urban areas is just the first step in FIA's vision of an All trees, All lands, All the time approach to the long-term monitoring of our nation's trees. This session will cover the status of the program as well as efforts being made and challenges encountered while folding FIAs plots in urban areas into the existing national work-flow from prefield, field, data processing, analysis, and on to data delivery while thinking regionally but acting nationally across four units.||ABSTRACT.--The Forest Inventory and Analysis (FIA) Program of the USDA Forest Service reports on the status and trends in forest land health, growth, area, location, and ownership. The 2014 Farm Bill instructs FIA to Implement an annualized inventory of trees in urban settings, including the status and trends of trees and forests, and assessments of their ecosystem services, values, health, and risk to pests and diseases. Urban areas implementation started in Baltimore, MD, and Austin, TX, during the 2014 field season and expanded into 35 cities in 24 States; 15 of which have both their proposed cities and all their urban areas active as of the 2019 field season. Installing plots in urban areas is just the first step in FIA's vision of an All trees, All lands, All the time approach to the long-term monitoring of the nation's trees. This session will cover the status of the program as well as the efforts being made, and challenges encountered, while folding FIAs plots in urban areas into the existing national work-flow from prefield, field, data processing, analysis, and on to data delivery while taking an approach of thinking regionally while acting nationally as a unified national program representing four regional units.|
|Tonya Lister||Advances in urban FIA processing, data availability, tools, and products||Wednesday||1a||Cherokee||Urban FIA update and latest results||Recognizing the importance of urban forests, FIA initiated an annualized urban inventory program in 2014. After five years of program implementation, a number of cities now have nearly complete cycles of baseline data and data distribution frequency will soon be annual. In this presentation we describe advances in the processing of urban FIA data including database development, data review, publication, the development of analytical tools, and automated 5-year reporting.||FIA initiated an annualized urban inventory in 2014 and the program has grown to include urban forest monitoring in 35 cities, across 24 states, with new cities added each year. During this period of implementation, there has been limited published urban data available. However, a number of cities now have nearly complete cycles of baseline data and data distribution frequency will soon be annual. In this presentation we describe advances in the processing of urban FIA data including database development, the implementation of a data review process, data publication, the development of analytical tools, and automated 5-year reporting. An overview of the data release schedule and reporting timeline are also presented. We conclude with a discussion of future directions in urban data delivery, analysis, and reporting.|
|Rebekah Zehnder||My Citys Trees: Delivering Information from Urban FIA Data||Wednesday||1a||Cherokee||Urban FIA update and latest results||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.
|Michael Galvin||Going with the flow: tracking urban wood flows to test an Urban TPO approach||Wednesday||1a||Cherokee||Urban FIA update and latest results||The National Renewable Energy Laboratory estimates that over 41,000,000 tons of urban wood|
waste are generated annually in the U.S. With an inventory of urban trees, of those that generate urban wood waste (tree care
companies), and of those that process urban wood, we can understand the scope and potential
of your urban wood waste stream. We apply this model to Baltimore, share results, and also discuss approaches for intensification.
|Urban wood waste is a plentiful, underutilized resource. The National Renewable Energy Laboratory estimates that over 41,000,000 tons of urban wood waste are generated annually in the U.S., and that tree care crews generate ~ 1,000 tons of
urban wood waste per crew per year. Reports indicate that most of it is chipped or used for firewood.
We examined three models of various levels of intensity for an urban analog to the FIA TPO, which we subsequently refer to as Urban TPO. We found that the most basic level of Urban TPO, focusing on wood waste generators and volumes, would be most appropriate for a national program.
With an inventory of urban trees, of those that generate urban wood waste (tree care companies), and of those that process urban wood, we can understand the scope and potential of an urban wood waste system. We apply this model to Baltimore and share our results and their limitations. We also discuss potential approaches for intensification by including urban wood processors, producers, and customers.
|Kathryn Baer||An Inventory of San Diegos Forest Resources: Urban FIA in the Wild West||Wednesday||1a||Cherokee||Urban FIA update and latest results||In 2017, San Diego, California became the first urban area in FIAs PNW Region to be inventoried as part of the Urban FIA (UFIA) initiative. This presentation will highlight key findings of the San Diego UFIA analysis and report, including species composition and distribution of the citys urban forest and the ecosystem services provided. Attributes of San Diegos urban forest will be compared to results from urban areas within different ecoregions previously inventoried by the UFIA program.||In 2017, San Diego, California became the first urban area in FIAs Pacific Northwest Region to be inventoried as part of the Urban FIA (UFIA) initiative outlined in the 2014 Farm Bill. A full complement of 200 plots were selected in San Diego, of which 190 were sampled by UFIA crews from September to November of 2017. The results of this inventory will be released in 2019 in what is anticipated to be the first standardized UFIA report. This presentation will describe novel techniques utilized in the San Diego urban inventory, including methods for the consistent measurement of the citys many palm trees. We will highlight key findings of the San Diego UFIA analysis and report, including descriptions of the species composition and distribution of the citys urban forest and the ecosystem services it provides. Attributes of San Diegos urban forest will be compared to those of two urban areas within FIAs Southern Region that were previously inventoried as part of the UFIA initiative: Houston and Austin, Texas. These comparisons will include a discussion of differences in tree cover and regeneration among urban areas within different ecoregions, and unique threats to the sustainability of San Diegos urban forest.|
|Thomas Brandeis||Implementing Urban FIA in the U.S. Virgin Islands||Wednesday||1a||Cherokee||Urban forest research and advances in urban inventory and monitoring||Forest cover in the US Virgin Islands provides watershed protection, endemic species conservation and support for an economy heavily dependent on tourism. FIA currently does not capture the ecosystem services contribution of trees in urban areas in this landscape dominated by low density, dispersed development. In the upcoming fourth forest inventory in these Caribbean islands, data collection will transition from forest only to applying urban FIA protocols on all sampling points.||Forest cover is of particular importance on Caribbean islands. Trees capture rainfall and stabilize soils, improving aquifer recharge and protecting fringing coral reefs vital to fisheries and tourism. It preserves endemic plant and animal species and mitigates ambient temperatures on these subtropical islands. The FIA program began inventorying forests in the US Virgin Islands (USVI) in 2004 with an intensified sample (6-12 times for a total of 106 sampling points), remeasured these plots in 2009 and 2014, and will again in late 2019. While the islands of St. Croix (53,870 ac. total area; 56% forested, 50, 601 people), St. Thomas (20,480 ac., 44% forested, 51,634 people) and St. John (12,800 ac., 81% forested, 4,170 people) vary in size and population, they share similar dispersed, low density development. 46% of FIA sampling points on St. Croix fall within the Christiansted urban cluster (UC) and 70% of points on St. Thomas fall within the Charlotte Amalie UC. Trees on the islands developed lands also contribute ecosystem services and the goal of the urban FIA program is to quantify them. In this latest cycle, all USVI sampling points will treated as falling within an UC and have the full suite of urban FIA data collection.|
|Mark Nelson||FIA contributions to Montréal Process Criteria & Indicators for monitoring biological diversity||Thursday||1a||Cherokee||FIA contributions to monitoring biological diversity||Forests support a variety of ecosystems, species, and genes collectively referred to as biological diversity along with their ecological processes. In the United States, conservation of forest-associated biological diversity is monitored through Montréal Process (MP) Criteria & Indicators, including three indicators each for ecosystem, species, and genetic diversity. Forest Inventory and Analysis products contribute to MP monitoring of biological diversity in a variety of ways.||Conservation of biological diversity is critical for maintaining many ecological services. Biological diversity includes diversity within species, between species, and of ecosystems, as defined by the Convention on Biological Diversity. Many countries have implemented programs for monitoring biological diversity across these scales. The Montréal Process (MP) was developed to provide a standard, international framework for assessing the sustainability of temperate and boreal forest ecosystems across twelve countries, including the United States. The first of seven MP criteria is Conservation of Biological Diversity, containing nine indicators, three each for ecosystem, species, and genetic diversity. Data, information, and knowledge produced by the U.S. Forest Service Forest Inventory and Analysis program contribute to MP monitoring at national, regional, and state scales. We present the MP, other regional and state variations of indicators, and corresponding applications of FIA for monitoring biological diversity. This presentation provides introduction and context for subsequent presentations in this session.|
|Randall Morin||Use of Forest Inventory to Assess Trends in Habitat Abundance for the Indiana Bat across Forests of the Northern United States||Thursday||1a||Cherokee||FIA contributions to monitoring biological diversity||FIA data can support estimates of habitat abundance for some wildlife species whose habitat requirements have corresponding FIA attributes of composition and structure. The federally endangered Indiana bat (Myotis sodalis) lives in hardwood and hardwood-pine forests, requiring particular tree characteristics for roosting habitat features. We estimated habitat distribution and trends for Indiana bat, and demonstrate a multi-scale tool for presenting habitat information.||Forest Inventory and Analysis (FIA) data has long been used to address broad classes of forest habitat types and address global, national, and regional biodiversity assessments. For example, forest inventory data can be used estimate the current status of and trends in early-successional forest. In cases where specific habitat requirements related to trees are well documented for forest-associated species it becomes possible to make habitat estimates for specific wildlife species. The Indiana bat (Myotis sodalis) was listed as endangered by the US Fish & Wildlife Service in 1967. Indiana bats live in hardwood and hardwood-pine forests across much of the midwestern, southern, and mid-Atlantic regions of the United States. They have specific requirements for the number of live and standing dead trees per acre that are necessary to provide suitable and optimal habitat for roosting and nesting. Here we analyze forest inventory data distributed across the eastern USA to estimate the current distribution and trends of suitable and optimal forest habitat for the Indiana bat and demonstrate a digital tool for sharing this information at multiple spatial scales.|
|Alexa McKerrow||Joining USGS GAP species-habitat relationships to FIA via USNVC Macrogroups||Thursday||1a||Cherokee||FIA contributions to monitoring biological diversity||Nationally consistent population trend data are available for some forest-associated species, but not for others. Species-specific habitat abundance and change estimates provide indirect indices of biological diversity. To support such estimates we joined the GAP species-habitat relationships database to FIA database using attributes of composition and structure within U.S. National Vegetation Classification macrogroups; we incorporated geospatial datasets to further refine these associations.||Forest Inventory and Analysis (FIA) data provide opportunities for monitoring biological diversity by creating linkages between forest characteristics and wildlife habitat. Tree species data recorded during FIA field visits provide direct estimates of tree species distribution, abundance, and change. Some forest-associated terrestrial vertebrate species also have nationally consistent population trend data (e.g., Breeding Bird Survey), but many do not. For those species, diversity can be monitored indirectly via species-specific estimates of habitat abundance and change. Most forest species-habitat relationships include detailed attributes of forest composition and structure, which FIA data can provide if species habitat data can be efficiently linked to FIA via common attributes. We joined USGS Gap Analysis Program (GAP) species-habitat relationships at the macrogroup level to FIA using the recently added U.S. National Vegetation Classification (USNVC) macrogroups in the FIA condition attributes across the Eastern US. GAP species-habitat relationships data were recently completed for birds, mammals, reptiles, and amphibians. To further refine GAP-USNVC-FIA linkages we incorporated vertebrate species range maps.|
|James Berdeen||Estimating potential abundance of wood duck nest cavities||Thursday||1a||Cherokee||FIA contributions to monitoring biological diversity||Wood duck (Aix sponsa) hens nest in tree cavities. FIA annual inventories do not record the presence of tree cavities. Therefore, we upscaled an intensive field survey of tree cavities to FIA data on tree species, size, and health status to estimate tree cavity abundance and trends in northern Minnesota. Numbers of trees >= 22 cm DBH in seven species most associated with cavities increased from 1990 to 1999-2003, then decreased during subsequent annual inventories through 2014-2018.||Tree cavities provide nesting substrate for Wood duck (Aix sponsa) hens. Habitats used by wood ducks in Minnesota have changed in recent decades. We initiated a study to explain the variation in suitable cavity presence in the broader Laurentian Mixed Forest Province of north central Minnesota between 1990 and 2014-2018, and used these results with FIA data to make inferences about temporal changes of cavity abundance in northern Minnesota. We measured 7,869 trees >22 cm DBH in Cass County, Minnesota. We classified 223 cavities as suitable and 111 as marginally suitable for nesting. Data were sparse for large DBH trees of all species, so we surveyed additional plots to obtain sufficient data on large-DBH stems (>40 cm for early and mid-successional species, >50 cm for late successional species). Logistic regression models fit to these data explained the variation of cavity presence in seven common tree species for which there was adequate cavity data. The estimated number of these trees increased between 1990 and 1999-2003, then decreased during subsequent periods. We will discuss our projections of the temporal change in cavity abundance.|
|Andrew Hartsell||THE IMPACTS OF VARYING SPATIAL SCALE IN DETERMINNG PREDICTORS OF TREE SPECIES DIVERSITY USING NESTED WATERSHEDS AND FOREST INVENTORY DATA IN THE SOUTHEASTERN UNITED STATES||Thursday||1a||Cherokee||FIA contributions to monitoring biological diversity||This study uses FIA data and nested watershed to investigate the impact of spatial scale on ecological processes. Multi-response permutation procedures (MRPP), non-metric multidimensional scaling (NMS), and regression trees were used. Getis-Ord Gi* hot-spot analysis was utilized to determine if diversity hot and cold spots clustered. Finally, ordinary least squares, spatial lag, and spatial error models were developed.||The relationship between tree species diversity and various climatic, environmental, and anthropogenic factors in the southeastern United States in multifaceted and complex. Key among these is the impact of plantation forestry, agricultural establishment, and urban development on three measures of tree species diversity: species richness, Shannon-Wiener index, and Simpsons index. Forest Inventory and Analysis data as the source of tree species data and nested watersheds from the Watershed Boundary Dataset (WBD) were used as spatial boundaries. The measures of diversity were calculated for the differing watershed scales. Multivariate analysis and spatial analysis techniques were incorporated to understand how possible predictors and covariates of tree species diversity vary with spatial scale. Multivariate analysis techniques such as multi-response permutation procedures (MRPP), non-metric multidimensional scaling (NMS), and regression trees were used to assess relationships within the data. A species-area curves was created to determine appropriate spatial scales. Getis-Ord Gi* hot-spot analysis was utilized to determine if diversity hot and cold spots clustered, as well as if clustering patterns changed in regards to changes in|
|Christopher Looney||Variation in individual-tree growth across species mixtures provides evidence of complementarity effects in Interior West forests||Thursday||1a||Cherokee||FIA contributions to monitoring biological diversity||In some forest types, species complementarity could potentially enhance productivity and resilience to climate change. We used Interior West FIA data to model the growth-effects of complementarity, stand structure, and tree characteristics on ponderosa pine, Douglas-fir, quaking aspen, and Engelmann spruce. Preliminary results suggest that species mixtures enhance individual-tree growth depending on shade tolerance. Stand structure may also modify complementarity effects.||A central challenge to contemporary forest management is maintaining forest productivity in the face of climate change. Research suggests species diversity could be used to enhance both stand productivity and resilience through complementarity effects (e.g. facilitation) However, this research has focused on European forests, with limited North American examples. To fill this knowledge gap, we investigated the relative influence of complementarity, stand structure, and tree characteristics on the growth of four major species in the Interior West: ponderosa pine, Douglas-fir, quaking aspen, and Engelmann spruce. Using 10yr FIA remeasurements, we created individual-tree (>4.9 in. DBH) models and examined the growth of each of the four species along community gradients. Our preliminary results indicate that only shade-tolerant Engelmann spruce and Douglas-fir increase in growth with decreasing stand purity. Light partitioning between shade-tolerant and intolerant species, modified by stand structure, may drive mixture effects on growth. These implications of species mixtures for individual-tree growth and vigor will help guide future efforts to sustain function across the Adaptive Silviculture for Climate Change (ASCC) Network.|