Southern Appalachian Mountain Region Research Articles

Landscape influences on thermal sensitivity and predicted spatial variability among brook trout streams in the southeastern USA

AbstractWarming water temperatures as a result of climate change pose a major threat to coldwater organisms. However, the rate of warming is not spatially uniform due to surface‐ground‐water interactions and stream and watershed characteristics. Coldwater habitats that are most resistant to warming serve as thermal refugia and identifying their locations is critical to regional aquatic conservation planning. We quantified the thermal sensitivity of 203 streams providing current and potential habitat for brook trout (Salvelinus fontinalis) across nearly 1000 linear km of their native range in the southern and central Appalachian Mountains region, USA, and characterized their spatial variability with landscape variables available in the National Hydrography Dataset. Using the Bayesian framework, we calculated the maximum slope of the logistic function relating paired weekly mean air temperature and stream temperature as an index of stream thermal sensitivity. Streams differed greatly in thermal sensitivity and those with more resistant water temperature regimes (i.e., thermal refugia) were consistently characterized by southerly latitudes and groundwater input. Landscape variables derived from a principal component analysis explained 16% of the variation in thermal sensitivity, indicating that the existing landscape variables were modestly successful in explaining spatial thermal heterogeneity. Using our model and spatial interpolation, we predicted thermal sensitivity at 8695 stream segments potentially suitable for brook trout in the study region. Thermal refugia were more common southward presumably due to higher elevations, but elsewhere they were also clustered at finer spatial scales. Our analysis informs prioritizing habitat conservation and restoration of this native salmonid and other aquatic organisms that depend on coldwater habitats in a warming world.

Assessing impacts of sulfur deposition on aquatic ecosystems: A decision support system for the Southern Appalachians

AbstractWith climate change and ongoing impacts from human development and resource extraction, US federal land management agencies are acutely concerned with managing for healthy aquatic ecosystems in the Southern Appalachian Mountain (SAM) Region. Here, we describe development of a spatial decision support application to assess the biological and ecological impacts of atmospheric S and N deposition on aquatic ecosystems of the region. We first summarize foundational published work to predict continuous maps of surface water acid neutralizing capacity (ANC) and soil base cation weathering (BCw). We use the predicted ANC and BCw maps to estimate steady‐state critical loads (CLs) of atmospheric S and N deposition. We included estimated CLs of atmospheric N to get a complete picture of CLs and potential exceedances. We then present a logic‐based decision support model for assessing effects of S and N deposition based on statistically modeled stream ANC and CL exceedance. The model is easily modified for continuous monitoring of CL exceedance patterns as new S and N deposition and ANC data become available. We present mapped model results for the SAM study area and an important subset of the region, the Great Smoky Mountains National Park. ANC modeling results revealed that predicted acid sensitivity was spatially variable, with areas of relatively low stream ANC (<50 μeq · L−1) and soil BCw (<50 meq · m−2 · year−1) predominantly found in certain critical areas. Within the Great Smoky Mountains National Park, evidence for S CL exceedance based on an ANC criterion of 50 μeq · L−1 was strong at locations where ambient S deposition was at least two times the CL. We also predicted likely impacts of CL exceedances on aquatic insect species richness and native fish abundance. Responses for insect species richness and fish impact showed variability similar to CL exceedance, with increasing impact positively correlated with elevation. Finally, we discuss ways that the decision support system can be used to prioritize management across the region.

Fuel and vegetation changes in southwestern, unburned portions of Great Smoky Mountains National Park, USA, 2003–2019

Overstory basal area, ericaceous shrub cover (Kalmia latifolia L. and Rhododendron maximum L.), and fuels (i.e., woody fuel loads and depths and O Horizon thickness) were assessed within Great Smoky Mountains National Park, USA, in 2003 − 2004. Due to recent wildfire activity within the southern Appalachian Mountain region (including Great Smoky Mountains National Park), the potential spread and expansion of ericaceous shrubs, and the impacts of the hemlock woolly adelgid (Adelges tsugae Annand) on eastern hemlock (Tsuga canadensis (L.) Carrière), these same ecosystem components were again assessed in 2019. Elevation and moisture regime (xeric, intermediate, and mesic) were included in this assessment as potential influential factors. An evaluation of repeated measurements from 40 plots suggested that O Horizon thickness did not change significantly over the 16-year period, but increased as elevation increased, and moisture regime (xeric O Horizon thickness > mesic O Horizon thickness) was a significant, related factor. The sum of 1-, 10-, and 100-h fuel loads (fuels less < 7.6 cm diameter) increased, whereas woody fuel depth decreased over the 16-year period. No significant changes in 1000-h fuel loads (> 7.6 cm diameter), total woody fuel loads, ericaceous shrub cover, total basal area, or live T. canadensis basal area were observed. Live T. canadensis basal area decreased with increasing elevation. Dead, standing T. canadensis basal area increased from 2003–2019, and that increase was most pronounced as elevation increased on xeric and intermediate sites. Overall, we found that: 1. hypothesized increases in total woody fuel loads and ericaceous shrub cover were not present; and 2. elevation and moisture regime were most related to observed changes in vegetation and fuel condition.

Natural and Cultural History of Xanthorhiza simplicissima

Yellowroot (Xanthorhiza simplicissima Marshall, Ranunculaceae) is a low-growing deciduous shrub native to hardwood forests in the eastern United States. This review synthesizes existing knowledge about yellowroot's natural and cultural history including traditional uses, contemporary applications, and future implications. Emphasis is placed on the southern Appalachian mountain region, which is the core of its cultural importance. Natural history and ethnobotanical knowledge about yellowroot were collected from published literature, oral histories, and field observations. While it was first described by botanists in the 18th Century, yellowroot was already a well-established and culturally significant plant to the Native peoples of southern Appalachia for centuries. At least 34 Indigenous medicinal and craft uses are documented, confirming that yellowroot was, and to an extent still is, a culturally significant plant for Indigenous people in the southern Appalachian region. European and African American settlers to the region also incorporated the plant into many of their folk traditions, and wild harvesting and cultivation continues to this day. Modern analytical techniques have identified key phytoactive compounds in yellowroot extracts, lending credence to its traditional medicinal uses and potential applications in modern medicine.

Watershed‐scale vegetation, water quantity, and water quality responses to wildfire in the southern Appalachian mountain region, United States

AbstractWildfires are landscape scale disturbances that can significantly affect hydrologic processes such as runoff generation and sediment and nutrient transport to streams. In Fall 2016, multiple large drought‐related wildfires burned forests across the southern Appalachian Mountains. Immediately after the fires, we identified and instrumented eight 28.4–344 ha watersheds (four burned and four unburned) to measure vegetation, soil, water quantity, and water quality responses over the following two years. Within burned watersheds, plots varied in burn severity with up to 100% tree mortality and soil O‐horizon loss. Watershed scale high burn severity extent ranged from 5% to 65% of total watershed area. Water quantity and quality responses among burned watersheds were closely related to the high burn severity extent. Total water yield (Q) was up to 39% greater in burned watersheds than unburned reference watersheds. Total suspended solids (TSS) concentration during storm events were up to 168 times greater in samples collected from the most severely burned watershed than from a corresponding unburned reference watershed, suggesting that there was elevated risk of localized erosion and sedimentation of streams. NO3‐N concentration, export, and concentration dependence on streamflow were greater in burned watersheds and increased with increasing high burn severity extent. Mean NO3‐N concentration in the most severely burned watershed increased from 0.087 mg L−1 in the first year to 0.363 mg L−1 (+317%) in the second year. These results suggest that the 2016 wildfires degraded forest condition, increased Q, and had negative effects on water quality particularly during storm events.

Fossil tabulate corals reveal outcrops of Paleozoic sandstones in the Atlantic Coastal Plain Province, Southeastern USA.

The geologic history of the Southeastern United States of America is missing nearly 350-million-years of rocks, sediments, and fossils. This gap defines the Fall Line nonconformity where Upper Ordovician consolidated rocks are directly overlain by Upper Cretaceous unconsolidated sediments of the Atlantic Coastal Plain Province. Here we begin to fill in the missing geologic record by reporting the discovery of fossils of lower-to-middle Paleozoic tabulate corals (Syringophyllidae) in angular, quartz-rich, ferruginous sandstones that crop out in the Carolina Sandhills Physiographic Province that forms the updip margin of the Atlantic Coastal Plain Province near the Fall Line. These fossils of extinct tabulate corals are the first evidence that Paleozoic (Upper Ordovician–Lower Silurian) sandstones crop out amidst the mostly Mesozoic-to-Cenozoic deposits of the Atlantic Coastal Plain Province of the United States of America. This discovery of Paleozoic fossils and strata in a region in which they were previously entirely unknown offers a more complete insight into the geologic history of the Southern Appalachian Mountains Region, Carolina Sandhills and updip margin of the Atlantic Coastal Plain Province and extends the previously identified range of Syringophyllidae in North America.

Blue intensity as a temperature proxy in the eastern United States: A pilot study from a southern disjunct population of Picea rubens (Sarg.)

Annual surface air temperatures across the eastern United States (US) have increased by more than 1 °C within the last century, with the recent decades marked by an unprecedented warming trend. Tree-rings have long been used as a proxy for climate reconstruction, but few truly temperature-sensitive trees have been documented for the eastern US, much less the Appalachian Mountains in the Southeast. Here, we measure blue intensity (BI) and ring width (RWI) in red spruce growing at the southernmost latitudinal range margin of the species on the North Carolina-Tennessee border to test the efficacy of using either metric as a temperature proxy in the eastern US. The BI and RWI chronologies spanned 1883–2008 and had an interseries correlations of 0.42 and 0.54, respectively, but time series were trimmed to the period 1950–2008 due to low sample depth. We discovered strong, positive, and stable correlations between both current-year early fall (September–October) Tmax (r = 0.62; p < 0.001) and Tmean (r = 0.51; p < 0.001) and ΔBI during the period 1950–2008, but found no significant relationships between temperature and RWI. We show BI metrics measured in red spruce to be a promising temperature proxy for the southern Appalachian Mountain region. Future research should focus on testing [1] the efficacy of using BI on red spruce collected from across the species range, and [2] the potential for using BI as a temperature proxy in other conifers distributed in the eastern US.

Lecanora markjohnstonii(Lecanoraceae, lichenized Ascomycetes), a new sorediate crustose lichen from the southeastern United States

Lecanora markjohnstonii is described as new to science from the southeastern United States, with a primary center of distribution in the southern Appalachian Mountain region. This sterile, sorediate crust is saxicolous on both sandstone and granite and occurs commonly in mixed hardwood-conifer forests with rock outcrops. It is characterized by a gray-green, rimose-areolate thallus, erumpent, raised soralia, and the production of atranorin together with 2-0-methylperlatolic acid. Molecular phylogenetic analyses of newly generated rDNA assemblies from a broad sampling of lineages within the Lecanoromycetes and Arthoniomycetes inferred placement of the unknown crust in the Lecanoraceae, specifically within Lecanora. Analysis of the mtSSU gene region then inferred placement in the Lecanora subfusca group. Finally, a fully assembled and annotated mitochondrial genome was compared to other lichenized fungal mitogenomes, including the publicly available Lecanora strobilina mitogenome, and showed that the gene region atp9 was missing as in other members of the Lecanorales.

Late Hemphillian Colubrid Snakes (Serpentes, Colubridae) from the Gray Fossil Site of Northeastern Tennessee

Abstract The Gray Fossil Site (GFS) of northeastern Tennessee is a late Hemphillian fossil locality in the southern Appalachian mountain region of eastern North America with a diverse vertebrate fauna. Snakes make up a substantial microfossil portion of the GFS herpetofauna, particularly the Colubridae, comprised of members of the Colubrinae and Natricinae. Seven colubrid taxa have been identified from the site so far, including three natricines (cf. Neonatrix, Nerodia, Thamnophis) and at least four colubrines (Coluber/Masticophis, Pantherophis, Pituophis, gen. et sp. nov.). Indeed, cf. Neonatrix and the new genus (and species) are the only extinct genera identified. Although Neonatrix is tentatively identified for the first time east of Nebraska, the new species represents a distinct taxon. In addition, the oldest reported definitive occurrence of Masticophis is presented herein. Some of the snakes suggest a pond or other aquatic habitat at GFS, particularly cf. Neonatrix and Nerodia, whereas others, suc...

Sub-regional snow cover distribution across the southern Appalachian Mountains

Snowfall in the Southern Appalachian Mountain region of the eastern US is characterized by much spatiotemporal variability. Annual snowfall totals vary by up to 75 cm, and variations in snowfall intensity can lead to large differences in the local snowfall distribution. Research has shown that the synoptic pattern associated with the snowfall strongly influences the regional-scale distribution of snow cover. However, topographic variability results in locally complex snow cover patterns that are not well understood or documented. In this study, we characterize the snow covered area (SCA) and fractional snow cover associated with different synoptic patterns in 14 individual sub-regions. We analyze 63 snow events using Moderate-resolution Imaging Spectroradiometer standard snow cover products to ascertain both qualitative and quantitative differences in snow cover across sub-regions. Among sub-regions, there is significant variation in the snow cover pattern from individual synoptic classes. Furthermore, the percent SCA follows the regional snowfall climatology, and sub-regions with the highest elevations and northerly latitudes exhibit the greatest variability. Results of the sub-regional analysis provide valuable guidance to forecasters by contributing a deeper understanding of local snow cover patterns and their relationship to synoptic-scale circulation features.

Ghosts of Cultivation Past - Native American Dispersal Legacy Persists in Tree Distribution.

A long-term assumption in ecology is that species distributions correspond with their niche requirements, but evidence that species can persist in unsuitable habitat for centuries undermines the link between species and habitat. Moreover, species may be more dependent on mutualist partners than specific habitats. Most evidence connecting indigenous cultures with plant dispersal is anecdotal, but historical records suggest that Native Americans transported and cultivated many species, including Gleditsia triacanthos ("Honey locust"). Gleditsia triacanthos was an important medicinal/culinary (e.g., sugar), cultural (e.g., game sticks) and spiritual tree for the Cherokee (southeastern U.S. Native Americans). This study tests the hypothesis that a Cherokee cultivation legacy drives current regional G. triacanthos distribution patterns. Gleditsia triacanthos occurs in rocky uplands and xeric fields, but inexplicably also occurs in mesic riverine corridors and floodplains where Cherokee once settled and farmed. I combined field experiments and surveys in the Southern Appalachian Mountain region (U.S.) to investigate G. triacanthos recruitment requirements and distribution patterns to determine whether there is a quantifiable G. triacanthos association with former Cherokee settlements. Moreover, I also investigated alternate dispersal mechanisms, such as stream transport and domestic cattle. The results indicate that a centuries-old legacy of Native American cultivation remains intact as G. triacanthos' current southern Appalachian distribution appears better explained Cherokee settlement patterns than habitat. The data indicate that the tree is severely dispersal limited in the region, only moving appreciable distances from former Cherokee settlements where cattle grazing is prevalent. Human land use legacy may play a long-term role in shaping species distributions, and pre-European settlement activity appears underrated as a factor influencing modern tree species distributions.

Landscape patterns of bioenergy in a changing climate: implications for crop allocation and land-use competition.

Rural landscapes face changing climate, shifting development pressure, and loss of agricultural land. Perennial bioenergy crops grown on existing agricultural land may provide an opportunity to conserve rural landscapes while addressing increased demand for biofuels. However, increased bioenergy production and changing land use raise concerns for tradeoffs within the food-energy-environment trilemma. Heterogeneity of climate, soils, and land use complicate assessment of bioenergy potential in complex landscapes, creating challenges to evaluating future tradeoffs. The hypothesis addressed herein is that perennial bioenergy production can provide an opportunity to avoid agricultural land conversion to development. Using a process-based crop model, we assessed potential bioenergy crop growth through 2100 in a southern Appalachian Mountain region and asked: (1) how mean annual yield differed among three crops (switchgrass Panicum virgatum, giant miscanthus Miscanthus x giganteus, and hybrid poplar Populus x sp.) under current climate and climate change scenarios resulting from moderate and very high greenhouse gas emissions; (2) how maximum landscape yield, spatial allocation of crops, and bioenergy hotspots (areas with highest potential yield) varied among climate scenarios; and (3) how bioenergy hotspots overlapped with current crop production or lands with high development pressure. Under both climate change scenarios, mean annual yield of perennial grasses decreased (-4% to -39%), but yield of hybrid poplar increased (+8% to +20%) which suggests that a switch to woody crops would maximize bioenergy crop production. In total, maximum landscape yield increased by up to 90 000 Mg/yr (6%) in the 21st century due to increased poplar production. Bioenergy hotspots (> 18 Mg x ha(-1) x yr(-1)) consistently overlapped with high suburban/exurban development likelihood and existing row crop production. If bioenergy production is constrained to marginal (non-crop) lands, landscape yield decreased by 27%. The removal of lands with high development probability from crop production resulted in losses of up to 670 000 Mg/yr (40%). This study demonstrated that tradeoffs among bioenergy production, crop production, and exurban expansion in a mountainous changing rural landscape vary spatially with climate change over time. If markets develop, bioenergy crops could potentially counter losses of agricultural land to development.

Study on selecting sensitive environmental variables in modelling species spatial distribution

ABSTRACTThis study explores the effects of different environmental variables on the accuracy of species distribution models. Forest inventory and analysis data sets were used to generate absence and pseudo-absence points of chestnut oak (Quercus prinus) in the central and southern Appalachian mountain region of the US. We simulate chestnut oak distribution using different criteria for selecting environmental variables: (1) the selection of sensitive variables using factor analysis and the calculation of a sensitivity index, (2) principal components analysis. Factor analysis to environmental variables at both occurrence and pseudo-absence points was conducted to calculate the sensitivity index for each environmental variable. The identification of sensitive variables may use the factor loadings of first one or two factors of environmental variables. Modelling with sensitive variables (mean Kappa > 0.60; mean true skill statistic (TSS) > 0.60) can enhance model accuracy more than using PCA variables or all available environmental variables (mean Kappa ranges from 0.45 to 0.65; mean TSS ranges from 0.40 to 0.70). Modelling with leading principal components (larger than 90% variations) can achieve similar or higher accuracy than modelling with all variables. The influence of redundant information on species modelling varies with the model used. Our results suggest that selecting environmental variables using a sensitivity index defined by factor analysis may improve model accuracy and reduce redundant information in species modelling. The proposed method for selecting sensitive variables is easy to implement and has strong ecological interpretability.

Downstream Warming and Headwater Acidity May Diminish Coldwater Habitat in Southern Appalachian Mountain Streams.

Stream-dwelling species in the U.S. southern Appalachian Mountains region are particularly vulnerable to climate change and acidification. The objectives of this study were to quantify the spatial extent of contemporary suitable habitat for acid- and thermally sensitive aquatic species and to forecast future habitat loss resulting from expected temperature increases on national forest lands in the southern Appalachian Mountain region. The goal of this study was to help watershed managers identify and assess stream reaches that are potentially vulnerable to warming, acidification, or both. To our knowledge, these results represent the first regional assessment of aquatic habitat suitability with respect to the combined effects of stream water temperature and acid-base status in the United States. Statistical models were developed to predict July mean daily maximum water temperatures and air-water temperature relations to determine potential changes in future stream water temperatures. The length of stream considered suitable habitat for acid- and thermally sensitive species, based on temperature and acid neutralizing capacity thresholds of 20°C and 50 μeq/L, was variable throughout the national forests considered. Stream length displaying temperature above 20°C was generally more than five times greater than the length predicted to have acid neutralizing capacity below 50 μeq/L. It was uncommon for these two stressors to occur within the same stream segment. Results suggested that species’ distributional shifts to colder, higher elevation habitats under a warming climate can be constrained by acidification of headwater streams. The approach used in this study can be applied to evaluate climate change impacts to stream water resources in other regions.

Snowfall event characteristics from a high‑elevation site in the Southern Appalachian Mountains, USA

CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 63:171-190 (2015) - DOI: https://doi.org/10.3354/cr01291 Snowfall event characteristics from a high‑elevation site in the Southern Appalachian Mountains, USA Daniel T. Martin1, L. Baker Perry1,*, Douglas K. Miller2, Peter T. Soulé1 1Department of Geography and Planning, Appalachian State University, Rankin Science West, 572 Rivers Street, Boone, NC 28608, USA 2Department of Atmospheric Sciences, University of North Carolina at Asheville, Robinson Hall, Asheville, NC 28804, USA *Corresponding author: perrylb@appstate.edu ABSTRACT: Accurate assessment of snowfall patterns in high-elevation remote areas is essential to providing a foundation for further climatological analyses. The Southern Appalachian Mountain (SAM) region of the eastern US provides a unique study area due to its low latitude and proximity to the Gulf of Mexico and Atlantic Ocean. Major snowstorms, such as the remnants of Hurricane Sandy in October 2012, can result in heavy snowfall of 100 cm or greater in favorable upslope regions. Understanding the behavior of these precipitation patterns is important due to flooding threats caused by a combination of factors including deep snowpack exposed to heavy rainfall, cloud immersion, and high dew point temperatures, further exacerbating flooding threats. To contribute to this understanding, we installed the Mobile Precipitation Research and Monitoring (MOPRAM) station at Roan Mountain (1875 m) on the Tennessee/North Carolina border in October 2012. MOPRAM allowed us to analyze liquid equivalent precipitation, new snowfall, snow depth, air temperature, and relative humidity at high temporal resolutions during the 2012-2013 snow season. We present the observed snowfall event characteristics (e.g. new snowfall, liquid equivalent precipitation, atmospheric conditions, and synoptic patterns) along with how these characteristics compare to other sites in the SAM. In our 25 event dataset, we observed the following patterns: conditionally unstable upstream lapse rates; predominantly northwest winds; high-to-low elevation precipitation enhancement near a factor of 3; and 364 mm of snow liquid equivalent on Roan Mountain. An estimated 391 cm of snow fell at Roan during the 2012-2013 season using nearby snow liquid ratios as an estimate for snowfall. KEY WORDS: Orographic snowfall · New snowfall properties · Southern Appalachian Mountains Full text in pdf format NextCite this article as: Martin DT, Perry LB, Miller DK, Soulé PT (2015) Snowfall event characteristics from a high‑elevation site in the Southern Appalachian Mountains, USA. Clim Res 63:171-190. https://doi.org/10.3354/cr01291 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 63, No. 3. Online publication date: May 20, 2015 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2015 Inter-Research.

Steady-state sulfur critical loads and exceedances for protection of aquatic ecosystems in the U.S. southern Appalachian Mountains

Atmospherically deposited sulfur (S) causes stream water acidification throughout the eastern U.S. Southern Appalachian Mountain (SAM) region. Acidification has been linked with reduced fitness and richness of aquatic species and changes to benthic communities. Maintaining acid-base chemistry that supports native biota depends largely on balancing acidic deposition with the natural resupply of base cations. Stream water acid neutralizing capacity (ANC) is maintained by base cations that mostly originate from weathering of surrounding lithologies. When ambient atmospheric S deposition exceeds the critical load (CL) an ecosystem can tolerate, stream water chemistry may become lethal to biota. This work links statistical predictions of ANC and base cation weathering for streams and watersheds of the SAM region with a steady-state model to estimate CLs and exceedances. Results showed that 20.1% of the total length of study region streams displayed ANC <100 μeq∙L−1, a level at which effects to biota may be anticipated; most were 4th or lower order streams. Nearly one-third of the stream length within the study region exhibited CLs of S deposition <50 meq∙m−2∙yr−1, which is less than the regional average S deposition of 60 meq∙m−2∙yr−1. Owing to their geologic substrates, relatively high elevation, and cool and moist forested conditions, the percentage of stream length in exceedance was highest for mountain wilderness areas and in national parks, and lowest for privately owned valley bottom land. Exceedance results were summarized by 12-digit hydrologic unit code (subwatershed) for use in developing management goals and policy objectives, and for long-term monitoring.

Machine learning and linear regression models to predict catchment‐level base cation weathering rates across the southern Appalachian Mountain region, USA

AbstractAccurate estimates of soil mineral weathering are required for regional critical load (CL) modeling to identify ecosystems at risk of the deleterious effects from acidification. Within a correlative modeling framework, we used modeled catchment‐level base cation weathering (BCw) as the response variable to identify key environmental correlates and predict a continuous map of BCw within the southern Appalachian Mountain region. More than 50 initial candidate predictor variables were submitted to a variety of conventional and machine learning regression models. Predictors included aspects of the underlying geology, soils, geomorphology, climate, topographic context, and acidic deposition rates. Low BCw rates were predicted in catchments with low precipitation, siliceous lithology, low soil clay, nitrogen and organic matter contents, and relatively high levels of canopy cover in mixed deciduous and coniferous forest types. Machine learning approaches, particularly random forest modeling, significantly improved model prediction of catchment‐level BCw rates over traditional linear regression, with higher model accuracy and lower error rates. Our results confirmed findings from other studies, but also identified several influential climatic predictor variables, interactions, and nonlinearities among the predictors. Results reported here will be used to support regional sulfur critical loads modeling to identify areas impacted by industrially derived atmospheric S inputs. These methods are readily adapted to other regions where accurate CL estimates are required over broad spatial extents to inform policy and management decisions.

Machine learning and hurdle models for improving regional predictions of stream water acid neutralizing capacity

[1] In many industrialized regions of the world, atmospherically deposited sulfur derived from industrial, nonpoint air pollution sources reduces stream water quality and results in acidic conditions that threaten aquatic resources. Accurate maps of predicted stream water acidity are an essential aid to managers who must identify acid-sensitive streams, potentially affected biota, and create resource protection strategies. In this study, we developed correlative models to predict the acid neutralizing capacity (ANC) of streams across the southern Appalachian Mountain region, USA. Models were developed using stream water chemistry data from 933 sampled locations and continuous maps of pertinent environmental and climatic predictors. Environmental predictors were averaged across the upslope contributing area for each sampled stream location and submitted to both statistical and machine-learning regression models. Predictor variables represented key aspects of the contributing geology, soils, climate, topography, and acidic deposition. To reduce model error rates, we employed hurdle modeling to screen out well-buffered sites and predict continuous ANC for the remainder of the stream network. Models predicted acid-sensitive streams in forested watersheds with small contributing areas, siliceous lithologies, cool and moist environments, low clay content soils, and moderate or higher dry sulfur deposition. Our results confirmed findings from other studies and further identified several influential climatic variables and variable interactions. Model predictions indicated that one quarter of the total stream network was sensitive to additional sulfur inputs (i.e., ANC < 100 µeq L−1), while <10% displayed much lower ANC (<50 µeq L−1). These methods may be readily adapted in other regions to assess stream water quality and potential biotic sensitivity to acidic inputs.

Conspecific Plant-Soil Feedbacks of Temperate Tree Species in the Southern Appalachians, USA

Many tree species have seedling recruitment patterns suggesting that they are affected by non-competitive distance-dependent sources of mortality. We conducted an experiment, with landscape-level replication, to identify cases of negative distance-dependent effects and whether variation in these effects corresponded with tree recruitment patterns in the southern Appalachian Mountains region. Specifically, soil was collected from 14 sites and used as inocula in a 62 day growth chamber experiment determining whether tree seedling growth was less when interacting with soil from conspecific (like) than heterospecific (other) tree species. Tests were performed on six tree species. Three of the tree species had been previously described as having greater recruitment around conspecifics (i.e. facilitator species group) compared to the other half (i.e. inhibitor species group). We were then able to determine whether variation in negative distance-dependent effects corresponded with recruitment patterns in the field. Across the six species, none were negatively affected by soil inocula from conspecific relative to heterospecific sources. Most species (four of six) were unaffected by soil source. Two species (Prunus serotina and Tsuga canadensis) had enhanced growth in pots inoculated with soil from conspecific trees vs. heterospecifics. Species varied in their susceptibility to soil pathogens, but trends across all species revealed that species classified as inhibitors were not more negatively affected by conspecific than heterospecific soil inocula or more susceptible to pathogenic effects than facilitators. Although plant-soil biota interactions may be important for individual species and sites, it may be difficult to scale these interactions over space or levels of ecological organization. Generalizing the importance of plant-soil feedbacks or other factors across regional scales may be especially problematic for hyperdiverse temperate forests where interactions may be spatially variable.

Spatio-temporal trend analysis of long-term development patterns (1900–2030) in a Southern Appalachian County

Many mountainous areas in the U.S. have experienced significant changes in residential development patterns over the past century, in large part due to changing economies and in-migration from outsiders seeking the scenic resources of these areas. To evaluate changes in the Southern Appalachian mountain region, we reconstructed building and road locations in Macon County, North Carolina, since 1906 from historic maps, aerial photographs, county parcel records and emergency response program data. We used these data to analyze growth trends using spatio-temporal classification and quantile regression analysis. We also forecast future development patterns through 2030 using a multi-step model incorporating population growth projections, extrapolations of recent development density trends, and spatial logistic regression models. We characterize new development in the county as primarily rural from 1906 to 1960, exurban from 1960 to 1975 and increasingly suburban since 1975. While the rate of population growth and new building construction peaked in the 1980s, the total road length and rate of development in forested areas continued to increase from 1990 to 2009. We forecast that through 2030 approximately 75% of new buildings will be constructed at urban and suburban densities and that 67% of all new buildings will be constructed in forested areas. In addition to establishing the utility of using spatial analysis to draw together disparate data sources to understand urbanization over long time scales, this analysis identifies trends that have important implications for land-use planning, hydrology, forest management, and wildlife conservation.