Browsing by Author "Odom, Richard H."

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    Assessing the Vulnerability of Military Installations in the Coterminous United States to Potential Biome Shifts Resulting from Rapid Climate Change
    Odom, Richard H.; Ford, W. Mark (2020-10)
    Climate-change impacts to Department of Defense (DoD) installations will challenge military mission and natural resource stewardship efforts by increasing vulnerability to flooding, drought, altered fire regimes, and invasive species. We developed biome classifications based on current climate for the coterminous United States using the Holdridge Life Zone system to assess potential change on DoD lands. We validated classifications using comparisons to existing ecoregional classifications, the distribution of major forest types, and tree species in eastern North America. We projected future life zones for mid- and late-century time periods under three greenhouse gas emission scenarios (low-B1, moderate-A1B, and high-A2) using an ensemble of global climate models. To assess installation vulnerability (n = 529), we analyzed biome shifts using spatial cluster analysis to characterize interregional variation, and identified representative installations for subsequent landscape-level analyses. Although mean annual temperatures are expected to increase, installations located in the Northeast, Lake States, and western Great Plains are likely to experience the largest proportional increases in temperature. Accordingly, forest and grassland communities at these installations managed to support a wide range of training, and environmental objectives may be adversely affected by altered disturbance regimes, heat, and moisture stress. However, precipitation is projected to increase in the Northeast and Lake States mitigating some effects of increased temperatures on biological communities. Given the uncertain response to climate change in different ecoregions, additional environmental and stewardship attributes are needed within a decision-support framework to understand vulnerabilities and provide appropriate responses.
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    Developing a Topographic Model to Predict the Northern Hardwood Forest Type within Carolina Northern Flying Squirrel (Glaucomys sabrinus coloratus) Recovery Areas of the Southern Appalachians
    Evans, Andrew M.; Odom, Richard H.; Resler, Lynn M.; Ford, W. Mark; Prisley, Stephen P. (Hindawi, 2014-08-28)
    The northern hardwood forest type is an important habitat component for the endangered Carolina northern flying squirrel (CNFS; Glaucomys sabrinus coloratus) for den sites and corridor habitats between boreo-montane conifer patches foraging areas. Our study related terrain data to presence of northern hardwood forest type in the recovery areas of CNFS in the southern Appalachian Mountains of western North Carolina, eastern Tennessee, and southwestern Virginia. We recorded overstory species composition and terrain variables at 338 points, to construct a robust, spatially predictive model. Terrain variables analyzed included elevation, aspect, slope gradient, site curvature, and topographic exposure. We used an information-theoretic approach to assess seven models based on associations noted in existing literature as well as an inclusive global model. Our results indicate that, on a regional scale, elevation, aspect, and topographic exposure index (TEI) are significant predictors of the presence of the northern hardwood forest type in the southern Appalachians. Our elevation + TEI model was the best approximating model (the lowest AICc score) for predicting northern hardwood forest type correctly classifying approximately 78% of our sample points. We then used these data to create region-wide predictive maps of the distribution of the northern hardwood forest type within CNFS recovery areas.
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    Developing Species-Age Cohorts from Forest Inventory and Analysis Data to Parameterize a Forest Landscape Model
    Odom, Richard H.; Ford, W. Mark (Hindawi, 2021-03-04)
    Simulating long-term, landscape level changes in forest composition requires estimates of stand age to initialize succession models. Detailed stand ages are rarely available, and even general information on stand history often is lacking. We used data from USDA Forest Service Forest Inventory and Analysis (FIA) database to estimate broad age classes for a forested landscape to simulate changes in landscape composition and structure relative to climate change at Fort Drum, a 43,000 ha U.S. Army installation in northwestern New York. Using simple linear regression, we developed relationships between tree diameter and age for FIA site trees from the host and adjacent ecoregions and applied those relationships to forest stands at Fort Drum. We observed that approximately half of the variation in age was explained by diameter breast height (DBH) across all species studied (r2 = 0.42 for sugar maple Acer saccharum to 0.63 for white ash Fraxinus americana). We then used age-diameter relationships from published research on northern hardwood species to calibrate results from the FIA-based analysis. With predicted stand age, we used tree species life histories and environmental conditions represented by ecological site types to parameterize a stochastic forest landscape model (LANDIS-II) to spatially and temporally model successional changes in forest communities at Fort Drum. Forest stands modeled over 100 years without significant disturbance appeared to reflect expected patterns of increasing dominance by shade-tolerant mesophytic tree species such as sugar maple, red maple (Acer rubrum), and eastern hemlock (Tsuga canadensis) where soil moisture was sufficient. On drier sandy soils, eastern white pine (Pinus strobus), red pine (P. resinosa), northern red oak (Quercus rubra), and white oak (Q. alba) continued to be important components throughout the modeling period with no net loss at the landscape scale. Our results suggest that despite abundant precipitation and relatively low evapotranspiration rates for the region, low soil water holding capacity and fertility may be limiting factors for the spread of mesophytic species on excessively drained soils in the region. Increasing atmospheric temperatures projected for the region could alter moisture regimes for many coarse-textured soils providing a possible mechanism for expansion of xerophytic tree species.
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    Predictive habitat models derived from nest-box occupancy for the endangered Carolina northern flying squirrel in the southern Appalachians
    Ford, W. Mark; Evans, Andrew M.; Odom, Richard H.; Rodrigue, Jane L.; Kelly, Christine A.; Abaid, Nicole; Diggins, Corinne A.; Newcomb, Douglas (Inter-Research Science Center, 2015-03-06)
    In the southern Appalachians, artificial nest-boxes are used to survey for the endangered Carolina northern flying squirrel (CNFS; Glaucomys sabrinus coloratus), a disjunct subspecies associated with high elevation (>1385 m) forests. Using environmental parameters diagnostic of squirrel habitat, we created 35 a priori occupancy models in the program PRESENCE for boxes surveyed in western North Carolina, 1996−2011. Our best approximating model showed CNFS denning associated with sheltered landforms and montane conifers, primarily red spruce Picea rubens. As sheltering decreased, decreasing distance to conifers was important. Area with a high probability (>0.5) of occupancy was distributed over 18 662 ha of habitat, mostly across 10 mountain ranges. Because nest-box surveys underrepresented areas >1750 m and CNFS forage in conifers, we combined areas of high occupancy with conifer GIS coverages to create an additional distribution model of likely habitat. Regionally, above 1385 m, we determined that 31 795 ha could be occupied by CNFS. Known occupied patches ranged from <50 ha in the Long Hope Valley in North Carolina to approximately 20 000 ha in the Great Smoky Mountains National Park along the North Carolina−Tennessee boundary. These findings should allow managers to better define, protect and enhance existing CNFS habitat and provide a basis for future surveys. Owing to model biases, we view this as only a first approximation. Further research combining den selection with foraging habitat use across the full range of elevations, landforms and forest types is needed to increase predictive accuracy of CNFS distribution and sub-population viability.