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Development of a Spatially Explicit Surface Coal Mining Predictive Model
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The goal of this project was to create a spatially explicit 1km2 grid cell model for the Appalachian Landscape Conservation Cooperative (Figure 1) predicting where surface coal mining is likely to occur in in a projected future time period, under two different scenarios. To accomplish this goal we combined GIS spatial analysis, a Random Forests predictive model, and future mining buildout scenarios. This report provides a detailed methodology of our approach and discussion of our results.
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Disturbance−diversity models: what do they really predict and how are they tested?
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The intermediate disturbance hypothesis (IDH) and the dynamic equilibrium model (DEM) are influential theories in ecology. The IDH predicts large species numbers at intermediate levels of disturbance and the DEM predicts that the effect of disturbance depends on the level of productivity. However, various indices of diversity are considered more commonly than the predicted number of species in tests of the hypotheses. This issue reaches beyond the scientific community as the predictions of the IDH and the DEM are used in the management of national parks and reserves. In order to compare responses with disturbance among measures of biodiversity, we used two different approaches of mathematical modelling and conducted an extensive meta-analysis. Two-thirds of the surveyed studies present different results for different diversity measures. Accordingly, the meta-analysis showed a narrow range of negative quadratic regression components for richness, but not evenness. Also, the two models support the IDH and the DEM, respectively, when biodiversity is measured as species richness, but predict evenness to increase with increasing disturbance, for all levels of productivity. Consequently, studies that use compound indices of diversity should present logical arguments, a priori, to why a specific index of diversity should peak in response to disturbance.
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Climate Science Documents
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Downscaling Scenarios of Climate Change Project to Map Entire Appalachian LCC Region
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A DOI Southeast Climate Science Center funded project will be evaluating the latest generation of global climate models to generate scenarios of future change to climate, hydrology, and vegetation for the Southeastern U.S. as well as the entire range of the Appalachian LCC.
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News & Events
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Duality in climate science
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Delivery of palatable 2 °C mitigation scenarios depends on speculative negative emissions or changing the past. Scientists must make their assumptions transparent and defensible, however politically uncomfortable the conclusions.
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Climate Science Documents
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Effects of Urbanization and Climate Change on Stream Health
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Estimation of stream health involves the analysis of changes in aquatic species, riparian vegetation, microinvertebrates, and channel degradation due to hydrologic changes occurring from anthropogenic activities. In this study, we quantified stream health changes arising from urbanization and climate change using a combination of the widely accepted Indicators of Hydrologic Alteration (IHA) and Dundee Hydrologic Regime Assessment Method (DHRAM) on a rapidly urbanized watershed in the Dallas-Fort Worth metropolitan area in Texas. Historical flow data were split into pre-alteration and post-alteration periods. The influence of climate change on stream health was analyzed by dividing the precipitation data into three groups of dry, average, and wet conditions based on recorded annual precipitation. Hydrologic indicators were evaluated for all three of the climate scenarios to estimate the stream health changes brought about by climate change. The effect of urbanization on stream health was analyzed for a specific subwatershed where urbanization occurred dramatically but no stream flow data were available using the widely used watershed-scale Soil and Water Assessment Tool (SWAT) model. The results of this study identify negative impacts to stream health with increasing urbanization and indicate that dry weather has more impact on stream health than wet weather. The IHA-DHRAM approach and SWAT model prove to be useful tools to estimate stream health at the watershed scale.
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Climate Science Documents
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El Nino in a changing climate
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El Nino events, characterized by anomalous warming in the eastern equatorial Pacific Ocean, have global climatic teleconnections and are the most dominant feature of cyclic climate variability on subdecadal timescales. Understanding changes in the frequency or characteristics of El Nino events in a changing climate is therefore of broad scientific and socioeconomic interest. Recent studies (1–5) show that the canonical El Nino has become less frequent and that a different kind of El Nino has become more common during the late twentieth century, in which warm sea surface temperatures (SSTs) in the central Pacific are flanked on the east and west by cooler SSTs. This type of El Nino, termed the central Pacific El Nino (CP-El Nino; also termed the dateline El Nino (2), El Nino Modoki (3) or a warm pool El Nino (5), differs from the canonical eastern Pacific El Nino (EP-El Nino) in both the location of maximum SST anomalies and tropical–midlatitude teleconnections. Here we show changes in the ratio of CP-El Nino to EP-El Nino under projected global EQ warming scenarios from the Coupled Model Intercomparison Project phase 3 multi-model data set (6). Using calculations based 10o S on historical El Nino indices, we find that projections of anthropogenic climate change are associated with an increased frequency of the CP-El Nino compared to the EP-El Nino. When restricted to the six climate models with the best representation of the twentieth-century ratio of CP-El Nino to EP-El Nino, the occurrence ratio of CP-El Nino/EP-El Nino is projected to increase as 10o N much as five times under global warming. The change is related to a flattening of the thermocline in the equatorial Pacific.
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Climate Science Documents
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Environmental Flows from Water Withdrawals in the Marcellus Shale Region
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The Appalachian LCC collaborated with Cornell University to study the environmental impacts of water withdrawals in the Central Appalachian region. The rivers and streams of the Central Appalachians are home to more than 200 species of fish and other aquatic life. They also provide a reliable source of drinking water, recreational opportunities and associated economic benefits to people living in large cities and surrounding communities. This research looks at how the region’s surface freshwater supply – and the health of natural systems delivering this resource – have been impacted and may be altered in the coming years under increasing water withdrawals. It focuses on the Marcellus Shale region in the Central Appalachians, including portions of NY, PA, OH, MD, WV and VA.
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Evaluating Effect of Climate Change on River Flows in the Clinch River Basin
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A new project by the U.S. Geological Survey is evaluating the potential cascading effects to river flows and quality aquatic habitat due to changes in climate within an ecologically important area of the Appalachian LCC. A greater understanding of likely flow changes within the Virginia portion of the Clinch River Basin will allow managers to better respond to alterations and degradation of physical habitat. Information and results from this study will also provide managers with methods to be applied throughout the Appalachian LCC region. (Photo by Virginia Department of Game and Inland Fisheries)
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Global non-linear effect of temperature on economic production
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Growing evidence demonstrates that climatic conditions can have a profound impact on the functioning of modern human societies (1,2), but effects on economic activity appear inconsistent. Fundamental productive elements of modern economies, such as workers and crops, exhibit highly non-linear responses to local temperature even in wealthy countries (3,4). In contrast, aggregate macroeconomic productivity of entire wealthy countries is reported not to respond to temperature (5), while poor countries respond only linearly (5,6). Resolving this conflict between micro and macro observations is critical to understanding the role of wealth in coupled human–natural systems (7,8) and to anticipating the global impact of climate change (9,10). Here we unify these seemingly contradictory results by accounting for non-linearity at the macro scale. We show that overall economic productivity is non- linear in temperature for all countries, with productivity peaking at an annual average temperature of 13 6C and declining strongly at higher temperatures. The relationship is globally generalizable, unchanged since 1960, and apparent for agricultural and non-agricultural activity in both rich and poor countries. These results provide the first evidence that economic activity in all regions is coupled to the global climate and establish a new empirical foundation for modelling economic loss in response to climate change (11,12), with important implications. If future adaptation mimics past adaptation, unmitigated warming is expected to reshape the global economy by reducing average global incomes roughly 23% by 2100 and widening global income inequality, relative to scenarios without climate change. In contrast to prior estimates, expected global losses are approximately linear in global mean temperature, with median losses many times larger than leading models indicate.
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Impact of Urbanization on Priority Bird Populations
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25 bird species models were developed to determine the sensitivity of priority bird species populations to urbanization.
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