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This dataset is one of a dozen or so datasets that provide the basis for a vulnerability assessment of the Great Northern LCC that examines land use and climate changes at landscape scales, for the full LCC boundary. It provides a measure of vulnerability based on temperature change using a watershed-based analysis. The values range from 0 to 1 and are unitless, where Vtw = Et x (1-Aw). The original floating point values ranging from 0-1.0 were multiplied by 100 and converted to integer format for this dataset.
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This dataset is one of a dozen or so datasets that provide the basis for a vulnerability assessment of the Great Northern LCC that examines land use and climate changes at landscape scales, for the full LCC boundary. It provides a measure of vulnerability based on biome velocity and using a terrestrial (moving window) anlaysis. The values range from 0 to 1 and are unitless, where Vhg = Eh x (1-Ag). The original floating point values ranging from 0-1.0 were multiplied by 100 and converted to integer format for this dataset.
Introduction (From Parks Stewardship Forum) Managers and scientists widely acknowledge climate change as one of the greatest threats to protected areas in the US and worldwide (Gross et al. 2016). The US National Park Service (NPS) began addressing climate change as early as the 1990s, and in 2010 NPS Director Jonathan Jarvis stated that “climate change is fundamentally the greatest threat to the integrity of our national parks that we have ever experienced” (NPS 2010). Today, parks throughout the NPS system experience impacts of human-caused climate change (e.g., Monahan and Fisichelli 2014; Gonzalez 2018) that threaten iconic park resources. Climate-related impacts include: melting glaciers (e.g., Glacier National...
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This dataset is one of a dozen or so datasets that provide the basis for a vulnerability assessment of the Great Northern LCC that examines land use and climate changes at landscape scales, for the full LCC boundary. It provides a measure of vulnerability based on climate velocity using a terrestrially-based analysis. The values range from 0 to 1 and are unitless, where Vvg = Ev x (1-Ag). The original floating point values ranging from 0-1.0 were multiplied by 100 and converted to integer format for this dataset.
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This dataset is one of a dozen or so datasets that provide the basis for a vulnerability assessment of the Great Northern LCC that examines land use and climate changes at landscape scales, for the full LCC boundary. It represents terrestrially-defined adaptive capacity, where values run from 0 to 1.0 and is calculated as the complement of the degree of human modification (1-H). The original floating point values ranging from 0-1.0 were multiplied by 100 and converted to integer format for this dataset.
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This dataset is one of a dozen or so datasets that provide the basis for a vulnerability assessment of the Great Northern LCC that examines land use and climate changes at landscape scales, for the full LCC boundary. It provides a measure of vulnerability based on climate velocity using a watershed-based analysis. The values range from 0 to 1 and are unitless, where Vvw = Ev x (1-Aw). The original floating point values ranging from 0-1.0 were multiplied by 100 and converted to integer format for this dataset.
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Most of the western United States is experiencing the effects of rapid and directional climate change (Garfin et al. 2013). These effects, along with forecasts of profound changes in the future, provide strong motivation for resource managers to learn about and prepare for future changes. Climate adaptation plans are based on an understanding of historic climate variation and their effects on ecosystems and on forecasts of future climate trends. Frameworks for climate adaptation thus universally identify the importance of a summary of historical, current, and projected climates (Glick, Stein, and Edelson 2011; Cross et al. 2013; Stein et al. 2014). Trends in physical climate variables are usually the basis for evaluating...
Categories: Publication; Types: Citation
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This dataset is one of a dozen or so datasets that provide the basis for a vulnerability assessment of the Great Northern LCC that examines land use and climate changes at landscape scales, for the full LCC boundary. It is an exposure variable that represents the temperature change (degrees C) from baseline (1950-2000) to future (2061-2080).
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This dataset is one of a dozen or so datasets that provide the basis for a vulnerability assessment of the Great Northern LCC that examines land use and climate changes at landscape scales, for the full LCC boundary. It is an exposure variable that represents the climate velocity for Rehfeldt biome-habitat types (from 2000 to 2060), where units are in km/year.
Abstract (from http://www.esajournals.org/doi/abs/10.1890/13-0905.1): Many protected areas may not be adequately safeguarding biodiversity from human activities on surrounding lands and global change. The magnitude of such change agents and the sensitivity of ecosystems to these agents vary among protected areas. Thus, there is a need to assess vulnerability across networks of protected areas to determine those most at risk and to lay the basis for developing effective adaptation strategies. We conducted an assessment of exposure of U.S. National Parks to climate and land use change and consequences for vegetation communities. We first defined park protected-area centered ecosystems (PACEs) based on ecological...
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This e-book is the product of a second workshop that was funded and promoted by the United States Geological Survey to enhance cooperation between states for the management of chronic wasting disease (CWD). The first workshop addressed issues surrounding the statistical design and collection of surveillance data for CWD. The second workshop, from which this document arose, followed logically from the first workshop and focused on appropriate methods for analysis, interpretation, and use of CWD surveillance and related epidemiology data. Consequently, the emphasis of this e-book is on modeling approaches to describe and gain insight of the spatial epidemiology of CWD. We designed this e-book for wildlife managers...
Categories: Publication; Types: Citation
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This dataset is one of a dozen or so datasets that provide the basis for a vulnerability assessment of the Great Northern LCC that examines land use and climate changes at landscape scales, for the full LCC boundary. It represents terrestrially-defined adaptive capacity, where values run from 0 to 1.0 and is calculated as the complement of the degree of human modification (1-H). The original floating point values ranging from 0-1.0 were multiplied by 100 and converted to integer format for this dataset.
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This dataset is one of a dozen or so datasets that provide the basis for a vulnerability assessment of the Great Northern LCC that examines land use and climate changes at landscape scales, for the full LCC boundary. It represents hydrologically-defined adaptive capacity, where values run from 0 to 1.0 and is calculated as the complement of the degree of human modification (1-H), and are then averaged using hierarchical watersheds. The original floating point values ranging from 0-1.0 were multiplied by 100 and converted to integer format for this dataset.
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This dataset is one of a dozen or so datasets that provide the basis for a vulnerability assessment of the Great Northern LCC that examines land use and climate changes at landscape scales, for the full LCC boundary. It is an exposure variable that represents the climate velocity (km/year) which is computed as the mean rate of change in temperature over time (future-baseline; degrees C/km) divided by the rate of temperature change over space (degrees C/km).
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This dataset is one of a dozen or so datasets that provide the basis for a vulnerability assessment of the Great Northern LCC that examines land use and climate changes at landscape scales, for the full LCC boundary. It represents a combined measure of physiographic diversity (EH) and terrestrially-defined adaptive capacity (Ag). Values run from 0 to 1.0 and is calculated as: Agp = EH x Ag. The original floating point values ranging from 0-1.0 were multiplied by 100 and converted to integer format for this dataset.
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This dataset is one of a dozen or so datasets that provide the basis for a vulnerability assessment of the Great Northern LCC that examines land use and climate changes at landscape scales, for the full LCC boundary. It provides a measure of vulnerability based on biome velocity and using hydrological-based analysis (hierarchical watersheds). The values range from 0 to 1 and are unitless, where Vhw = Eh x (1-Aw). The original floating point values ranging from 0-1.0 were multiplied by 100 and converted to integer format for this dataset.
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Many U.S. national parks are already at the extreme warm end of their historical temperature distributions. With rapidly warming conditions, park resource management will be enhanced by information on seasonality of climate that supports adjustments in the timing of activities such as treating invasive species, operating visitor facilities, and scheduling climate-related events (e.g., flower festivals and fall leaf-viewing). Seasonal changes in vegetation, such as pollen, seed, and fruit production, are important drivers of ecological processes in parks, and phenology has thus been identified as a key indicator for park monitoring. Phenology is also one of the most proximate biological responses to climate change....
Categories: Publication; Types: Citation; Tags: Ecosphere
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Phenology is the study of periodic plant and animal life cycle events, how these are influenced by seasonal and interannual variations in climate, and how they modulate the abundance, diversity, and interactions of organisms. The USA National Phenology Network (USA-NPN) is currently being organized to engage federal agencies, environmental networks and field stations, educational institutions, and citizen scientists. The first USA-NPN planning workshop was held August 2005, in Tucson, Ariz. (Betancourt et al. [2005]; http://www.uwm.edu/Dept/Geography/npn/; by 1 June 2007, also see http://www.usanpn.org). With sponsorship from the U.S. National Science Foundation, the U.S. Geological Survey (USGS), the U.S. Fish...
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This dataset is one of a dozen or so datasets that provide the basis for a vulnerability assessment of the Great Northern LCC that examines land use and climate changes at landscape scales, for the full LCC boundary. It is an exposure variable that represents the physiographic diversity of landforms and parent material that is unitless, and then normalized, run from 0 to 1.
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This dataset is one of a dozen or so datasets that provide the basis for a vulnerability assessment of the Great Northern LCC that examines land use and climate changes at landscape scales, for the full LCC boundary. It represents terrestrially-defined adaptive capacity, where values run from 0 to 1.0 and is calculated as the complement of the degree of human modification (1-H). The original floating point values ranging from 0-1.0 were multiplied by 100 and converted to integer format for this dataset.


map background search result map search result map Ag: terrestrially defined adaptive capacity for Great Northern LCC Agp: combined measure of physiographic diversity (EH) and terrestrially-defined adaptive capacity (Ag) for Great Northern LCC Aw: hydrologically-defined adaptive capacity for Great Northern LCC Awp: combined measure of physiographic diversity (EH) and hydrologically-defined adaptive capacity (Aw) for Great Northern LCC EH: physiographic diversity of landforms and parent material for Great Northern LCC Vhg: terrestrially-defined vulnerability, biome velocity for Great Northern LCC Vhw: hydrologically-defined vulnerability, biome velocity for Great Northern LCC Vtg: terrestrially-defined vulnerability, temperature change for Great Northern LCC Vtw: hydrologically-defined vulnerability, temperature change for Great Northern LCC Vvg: terrestrially-defined vulnerability, climate velocity for Great Northern LCC Vvw: hydrologically-defined vulnerability, climate velocity for Great Northern LCC Ehv: climate velocity for Rehfeldt biome-habitat types (km/year). Et: temperature change (degrees C) from baseline (1950-2000) to future (2061-2080) for Great Northern LCC Ev: climate velocity (km/year) for Great Northern LCC Vhw: hydrologically-defined vulnerability, biome velocity for Great Northern LCC Vvw: hydrologically-defined vulnerability, climate velocity for Great Northern LCC Ag: terrestrially defined adaptive capacity for Great Northern LCC Agp: combined measure of physiographic diversity (EH) and terrestrially-defined adaptive capacity (Ag) for Great Northern LCC Aw: hydrologically-defined adaptive capacity for Great Northern LCC Awp: combined measure of physiographic diversity (EH) and hydrologically-defined adaptive capacity (Aw) for Great Northern LCC EH: physiographic diversity of landforms and parent material for Great Northern LCC Vhg: terrestrially-defined vulnerability, biome velocity for Great Northern LCC Vtg: terrestrially-defined vulnerability, temperature change for Great Northern LCC Vvg: terrestrially-defined vulnerability, climate velocity for Great Northern LCC Ehv: climate velocity for Rehfeldt biome-habitat types (km/year). Et: temperature change (degrees C) from baseline (1950-2000) to future (2061-2080) for Great Northern LCC Ev: climate velocity (km/year) for Great Northern LCC Vtw: hydrologically-defined vulnerability, temperature change for Great Northern LCC