Large topographical map of the northeast Tennessee region around Johnson City published in 1955. Prepared by the Army Map Service, Corps of Engineers, U.S. Army, Washington D.C. Compiled in 1951 from United States Quadrangles, U.S. Geological Survey, and county highway maps. Planimetric detail partially revised by photo-planimetric methods. Control by USC & GS, TVA, and CE. Roads, railroad and aeronautical data verified by state authorities, 1954. Legend denotes populated places, types of roads, and railroads. Topography, names of roads, communities, and waterways can be found on the map itself. Physical copy resides in the Government Information, Law and Maps Department of East Tennessee State University’s Sherrod Library. Scale - 1: 250,000 / https://dc.etsu.edu/rare-maps/1043/thumbnail.jpg

During 2008 – 2009, we quantified foraging behavior of adult Atlantic puffins (Fratercula arctica) by deploying time-depth recorders (TDRs) on 18 adults and collected morphological measurements from 40 adults nesting on Petit Manan Island, Maine. Dive data were successfully retrieved from 5 birds foraging for 14 days in 2008, and 8 birds foraging for 18 days in 2009. Pooling across all birds, a total of 8,097 dives were recorded, with peaks in activity during 0400-0800 and 1600-2000, and no diving between 2100 and 0400. Mean (± SD) dives/bird/day was 276.4 (± 84.7), with dives grouped into bouts lasting 17.8 (± 31.5) minutes, consisting of 8.9 (± 3.4) dives. Dive depth was less than 15 m for 86% of the dives. Mean maximum dive depth across birds was 9.7 (± 1.7) m, with the deepest dive being 40.7 m. Females made fewer deep dives (27-41 m), had more midday dives (1000 - 1559), and their dives were spread across a greater number of bouts per day than males. Given a mean foraging trip length of 60.1 (± 38.3) minutes for 26 birds observed in 2009, we estimate that adult puffins foraged, on average, within 31 km of the colony. Morphological measures were recorded by a single observer and included body mass, wing chord, bill depth, bill length, culmen, and head-bill length, and represented 19 males and 21 females, based on blood sample analysis. Data were analyzed using classification trees, and our final tree used culmen length and bill depth to correctly classify 34 of 40 (85%) birds (kappa = 0.695, P < 0.01). Use of our model can greatly improve the ability of biologists to identify sex of puffins in the field at this colony site, but variability in morphological data we collected at addition colonies indicates that future work is needed to determine its applicability throughout the Gulf of Maine. During 2009, we measured burrow characteristics of alcids and empty burrows. Breeding success and burrow characteristics were measured for nests of 104 puffins, 58 guillemots and 4 razorbills, with burrow characteristics measured for an additional 12 guillemot and 56 empty burrows. Mean diameter of burrow openings of puffins, guillemots, razorbills and empty burrows were significantly different, and artificial puffin burrows had significantly smaller openings than natural while artificial and natural guillemot burrows had similar opening diameters. Hatch, chick, and nest success of puffins was similar among burrow types, but guillemots had higher hatch and nest success in artificial burrows. The variables we used to create models for predicting hatch and nest success for puffins and guillemots had inadequate discriminatory power to predict success.

To account for the effects of climate change, management plans in the northeast need to incorporate climate adaptation. Conserving climate change refugia is one adaptation strategy. Climate change refugia are areas buffered by climate change that enable the persistence of valued physical, ecological, and cultural resources; preserving these areas could be a potential adaptation strategy. Using a translational ecology approach where researchers and managers from the National Park Service, US Geological Survey, the University of Massachusetts, and elsewhere worked together, we focused on identifying refugia for tree, herbaceous plant, mammal, and bird species in order to prioritize them for conservation action. Results predict shifts in distribution of habitats and species due to climate change, identifying areas to prioritize for invasive species treatment and other management actions. This study highlights priorities for future monitoring and data analysis, providing a model that can be replicated in other regions and motivate future research.

I utilized forest growth model (FVS-FFE) and fire simulation software (FlamMap, Randig), integrated through GIS software (ArcMap9.3), to quantify the impacts varied landscape-scale fuel treatments have on short-term onsite carbon loss, long-term onsite carbon storage, burn probability, conditional flame length, and mean fire size. Thirteen fuel treatment scenarios were simulated on a 42,000 hectare landscape in northern California: one untreated, three proposed by the US Forest Service, and nine that were spatially-optimized and developed with the Treatment Optimization Model in FlamMap. The nine scenarios developed in FlamMap varied by treatment intensity (10%, 20%, and 30% of the landscape treated) and treatment type (prescribed fire, mastication and thin + burn). Each scenario was subjected to 10,000 simulated wildfires with random ignition locations in order to develop burn probability and average flame length values for each scenario. I also recorded mean fire size for each scenario. I used the burn probability values to represent the likelihood of future wildfire occurrence, which I incorporated into our long-term onsite carbon storage projections. Our results suggest that the influence landscape-scale fuel treatments have on carbon dynamics and fire behavior metrics (mean burn probability, flame length and mean fire size) are highly dependent upon the treatment arrangement, type, and intensity. The results suggest that treating 20% of the landscape maximizes long-term carbon storage and that prescribed fire minimizes short-term carbon loss and maximizes onsite long-term carbon storage. Treating 20% of the landscape also appears to be the optimal treatment intensity for reducing fire behavior metrics, and treating beyond this level produces diminishing returns in reduction of fire behavior. When treating 20% of the landscape, site-specific treatments appear to perform well in comparison to spatially-optimized treatments.

The impact of forest fires on downstream meadow communities across California is of great ecological interest, as meadows are an important source of biodiversity in this region. Over a century of fire suppression has led to increased forest stand densities, which in turn has resulted in less water availability due to increased transpiration of densely growing trees. This potentially has left less available water for downstream plant communities in meadows. If true, then high mortality wildfires in surrounding forest are predicted to lead to an increase in available downstream moisture where obligate and facultative-wetland taxa increase and dry-adapted upland taxa decline. Here, we test this hypothesis using a dataset of 103 California montane meadows sampled before and after fire over the last 20 years. Using long term meadow monitoring data, compositional turnover is calculated for each plot from before and after fire and then evaluated against the area of 100% mortality, postfire relative-precipitation, meadow type, and proximity of the meadow to fire. We hypothesize that mortality, post-fire precipitation, and site type influence compositional turnover in meadows, regardless of proximity to the burn area. We find that compositional turnover is influenced by mortality but not by meadow type, relative precipitation, or the proximity to fire perimeter. Specifically, turnover was greater in meadows in higher mortality catchments. We then used a combination of linear models and NMDS to determine whether specific functional groups were driving higher turnover rates, expecting increases in obligate and facultative-wetland groups following high mortality fires. However we found no evidence for this. The high variation amongst meadows and their respective fire histories yielded no consistent shifts in community composition. Our findings highlight that landscape scale fire effects can interact strongly affect plant communities outside of fire perimeters, but that this does not lead to predictable shifts in wetland community composition. As fire behavior and drought are projected to become more extreme, we can expect that meadow composition will continue to change but not in predictable ways.

State and federal agencies spend considerable time and resources to enhance and create habitat for wildlife. Understanding how target and non-target species respond to these efforts can help direct the allocation of limited conservation resources. However, monitoring species response to habitat management comes with several logistical challenges that are exacerbated as the area of geographic focus increases. I used autonomous recording units (ARUs) to mitigate these challenges when assessing Eastern Whip-poor-will (Antrostomus vociferus) response to forest management. I deployed 1,265 ARUs across managed and unmanaged public and private forests from western North Carolina to southern Maine. I then applied a machine learned classifier to all recordings to create whip-poor-will daily detection histories for each survey location. I used detection data and generalized linear models to examine regional, landscape, and site factors that influenced whip-poor-will occurrence. Whip-poor-wills were detected at 399 (35%) survey locations. At the regional scale, occupancy decreased with latitude and elevation. At the landscape scale, occupancy was negatively associated with the amount of impervious cover within 500m, and was positively associated with the amount of oak forest and evergreen forest cover within 1,750m. Additionally, whip-poor-will occupancy exhibited a quadratic relationship with the amount of shrub/scrub cover within 1,500m. At the site-level, occupancy was negatively associated with increased basal area and exhibited a quadratic relationship with woody stem density. Whip-poor-will populations can benefit from the implementation of forestry practices that create and sustain early successional forests within forested landscapes, especially those dominated by oak forest types. The use of ARUs helped overcome several challenges associated with intensive broad-scale monitoring efforts for a species with a limited survey window, but also presented new challenges associated with data management, storage, and analyses.

Climate change-related hazards negatively impact ecosystems, economies, and quality of life. Significant resources have been invested in data collection and research with the goal of enhanced understanding and capacity to predict future conditions in order to mitigate or adapt to intensifying hazard risk. The expansive production of climate science has generated a necessary complimentary enterprise dedicated to enhancing decision-makers’ understanding of and access to climate science as it is essential for future societal and ecological well-being. Though the aim of these many tools is to support resilient decision-making in the face of climate change, professionals report an underutilization of climate resilience tools. It has been suggested that stakeholder engagement during climate resilience tool development will improve the rates of use; however, there have been no studies to explore if the findings from tool diffusion and adoption studies in other sectors translate to climate resilience tools. An end-user engagement process for the development of a climate resilience tool was established and implemented. The process itself and the outcomes of the process, in this case an online climate decision-support tool called Gulf TREE (www.GulfTREE.org), were studied. Findings included documenting that end-user engagement during climate resilience tool development, while more costly and time intensive, does lead to increased rates of diffusion and adoption of a climate resilience tool through both direct and indirect means. This work demonstrated that pre-development engagement to scope tool development is critical for maximizing relative benefit of a climate resilience tool. Additionally, all phases of engagement are necessary for both a useable and useful tool because each phase contributes to different attributes of the tool. Further research areas identified include understanding how much and what kind of stakeholder engagement is necessary to support continued diffusion and adoption after a tool is released, the role that mandates in climate resilience has on the adoption and diffusion of climate resilience tools, and how to define if a climate resilience tool has been successful.

The purpose of this research is to identify factors that contribute to wood fuel consumption as a space heating source and estimate a county-wide proportion for wood fuel consuming households. In addition, environmental problems associated with deforestation such as erosion and loss of wildlife habitat are delineated; moreover, air pollution resulting from wood fuel emissions are discussed. An exhaustive literature review provided the basis for the study. Data on Warren County wood fuel consumption patterns were derived from a mail survey. Proportion estimates were tested by using a classical two-tail test of hypothesis. Subsequently, factors were identified and used in a multiple regression analysis. The study found that low income households equipped with electric space heating systems located in rural areas are the most wood intensive. Unlike homes equipped with other alternate heating systems, electric space heat equipped households tend to consume wood fuel proportionally to income. The study also found that 26.3 percent of single family residences in the county use wood for space heating.

Increased nutrient availability globally has the potential to affect community functional composition of plants in nutrient limited environments, such as coastal grassland systems. Stability of these systems are threatened worldwide by urbanization, as well as effects of sea level rise and increased frequency and intensity of storms, and atmospheric N deposition, associated with climate change. Annual net primary productivity (ANPP), species composition, and functional traits (community weighted specific leaf area (CWSLA), leaf area index (LAI), growth form and photosynthetic pathway) were measured across four treatments to assess multiple resource limitation of nitrogen (N) and phosphorus (P) and functional community response in a coastal grassland on Hog Island, VA within the Virginia Coast Reserve, Long Term Ecological Research Network (LTER) applied at a rate of 10 g m-2 yr-1 Nutrient enrichment did not alter species diversity or richness. ANPP was highest in plots receiving any type of nitrogen enrichment, and was higher than expected of low nutrient systems. CWSLA was significantly higher in NP plots, and was lower than other grasslands. P treatments were not significantly different from controls. Graminoid species, specifically C4 species responded with higher ANPP than C3 forbs or graminoids within treatments. Evidence of synergistic NP effects were seen on community level resource allocation and leaf construction, but no significant species changes occurred over a 1-year time span. These results have expanded the knowledge of functional response to increased nutrient availability in an understudied, coastal grassland, which are at high risk to being lost to sea level rise and anthropogenic development and inform community assembly processes in stressful environments.

The Service Path Attribution Network (SPAN) framework provides a novel, user-centric, connectivity-based approach to ecosystem service assessment and valuation (ESAV). Ecosystem services are delivered to users through the simulated flow of some service medium (i.e., matter, energy, or information) from the ecosystems in which it originates (sources) to the people or assets which it affects (users). Along the way, the service medium may be absorbed by intervening landscape features (sinks) or captured by rival users. Crucially, the service medium is not itself an ecosystem service or benefit but rather an agnostic transport mechanism which establishes connectivity between sources, sinks, rival users, and nonrival users within a delimited study region. Each user then receives benefits or harm from the encountered service medium depending on their specific relationship with it. For example, if surface water is the simulated service medium, it may increase productivity at a hydropower plant but damage farmers in floodplains by drowning their crops. In the SPAN terminology, sources provide provisioning ecosystem services to users with a beneficial relationship with the service medium. Similarly, sinks provide preventive ecosystem services to users with a detrimental relationship with the service medium by reducing the amount flowing to their locations. Notably, within a single SPAN analysis, both sources and sinks may provide ecosystem services given a sufficiently heterogeneous pool of users. The results of a SPAN ESAV analysis are myriad, totalling up to 30 output maps for some services. Taken together, these maps tell the story of which sources provide services to which users, which sinks protect users from harm, which users compete for the same resources (and who wins), and how all of the sources, sinks, rival users, and nonrival users affect one another. Additionally, a SPAN simulation produces maps of the flow paths taken by the service medium from sources to users as well as where and by how much the flow strength is reduced by sinks. Studying these flow paths can help decision makers identify those locations at which management actions would be maximized or minimized depending on their specific development goals. A crowning achievement of this work is that for most ecosystem services the SPAN algorithm's complexity is guaranteed to be linear O(n) in both time and space with respect to the number of discrete locations analyzed. This makes it a viable option for high resolution landscape level ESAV studies using no more than commodity hardware. This dissertation explores the SPAN framework in depth, from its novel conceptual terminology and computational algorithms through to the intended interpretation of its results. In addition to describing the conceptual and mathematical components of this system in detail, this work also provides a complete Literate Program demonstrating the application of the SPAN framework to an assessment of the scenic beauty ecosystem service in Chittenden County, Vermont.