{"help":"Return the metadata of a dataset (package) and its resources. :param id: the id or name of the dataset :type id: string","success":true,"result":[{"id":"af6844a2-b0e4-4ff3-9dce-479f1a8b2cff","name":"central-yukon-rapid-ecoregional-assessment","title":"Central Yukon Rapid Ecoregional Assessment","author":"Alaska Center for Conservation Science","maintainer":"Alaska Conservation Science Catalog","maintainer_email":"twnawrocki@alaska.edu","license_title":"https:\/\/creativecommons.org\/licenses\/by-sa\/4.0\/","notes":"\u003Cp\u003E\u003Cimg alt=\u0022photo of moose near Fairbanks\u0022 title=\u0022Central Yukon Rapid Ecoregional Assessment\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Banner_CentralYukon.jpg\u0022 \/\u003E\u003C\/p\u003E\n\u003Cp\u003EThe Central Yukon Rapid Ecoregional Assessment (REA) was prepared by the Alaska Center for Conservation Science (ACCS) in cooperation with the Bureau of Land Management (BLM), the Institute for Social and Economic Research (ISER), and the Scenarios Network for Alaska Planning (SNAP). REAs are intended to target and answer important management questions identified by land managers, collect and in some cases develop new distribution maps for key resource values, document potential impact from environmental change agents, identify science gaps, and provide baseline data for future management decisions.\u003C\/p\u003E\n\u003Cp\u003EIn 2010, the BLM initiated seven Rapid Ecoregional Assessments to help understand the condition of western landscapes. These assessments help evaluate current conditions and predict future conditions of the landscape and the effects of environmental influences on the region, including wildfire, invasive species, and human development. REAs are rapid in nature, using existing data synthesized over an 18-month period. They also encompass broad geographic regions, crossing several different administrative boundaries.\u003C\/p\u003E\n\u003Cp\u003EThe version below is the final document reviewed and approved by BLM. The project report presents the detailed introduction, methods, results, limitations, and data gaps for all topics included in the Central Yukon Rapid Ecoregional Assessment.\u003C\/p\u003E\n","url":"https:\/\/accscatalog.uaa.alaska.edu\/dataset\/central-yukon-rapid-ecoregional-assessment","state":"Active","private":true,"revision_timestamp":"Fri, 10\/03\/2025 - 13:50","metadata_created":"Fri, 02\/23\/2018 - 14:05","metadata_modified":"Fri, 10\/03\/2025 - 13:50","creator_user_id":"d81d7a64-7e59-4e25-83b9-978a7a7aab2c","type":"Dataset","resources":[{"id":"7ad1d20a-efc6-4443-9f41-822c6a02b95a","revision_id":"","url":"https:\/\/accscatalog.uaa.alaska.edu\/sites\/default\/files\/REA_CentralYukon_Report.pdf","description":"\u003Cp\u003EThe assessment area, referred to in this REA as the Central Yukon (CYR) study area, includes a core of seven ecoregions selected by BLM: Brooks Range (south of the ridge crest), Davidson Mountains, Kobuk Ridges and Valleys, North Ogilvie Mountains, Ray Mountains, Yukon\u2013Old Crow Basin, and Yukon-Tanana Uplands. Ecoregions in this assessment were defined by Nowacki et al. (2001) and represent a unified mapping approach that blends traditional approaches with regionally-specific knowledge and ecological goals. Following BLM guidelines, the study area was formed by buffering the selected ecoregions by any 5th-level hydrologic units that intersected the ecoregion boundaries. Additionally, at the request of the BLM, the assessment boundary includes key lands surrounding the Dalton Highway on the north edge of the study area. Most of the Kotzebue Sound Lowlands are included in the study area because of the buffer region. The buffer region additionally causes the inclusion of small portions of several ecoregions along the southern boundary of the study area: these portions have been modified into a conglomerate unique to this REA referred to as the Tanana-Kuskokwim-Yukon Lowlands.\u003C\/p\u003E\n\u003Cp\u003EThis region has a boreal climate, with long cold winters and relatively brief but warm summers. Climate varies depending primarily upon elevation, proximity to the coast, and latitude. Although in general the most extreme cold occurs at high elevations, some areas experience localized temperature inversions. With mean annual temperatures below freezing in most areas, but above freezing in others, permafrost is discontinuous. This discontinuity occurs at both fine scales and broader scales.\u003C\/p\u003E\n\u003Cp\u003EThe Final Report contains the detailed results from the Central Yukon Rapid Ecoregional Assessment. The Central Yukon REA does not include a Manager\u0027s Summary document.\u003C\/p\u003E\n","format":"pdf","state":"Active","revision_timestamp":"Thu, 02\/07\/2019 - 20:45","name":"Central Yukon REA Final Report","mimetype":"application\/pdf","size":"76.95 MB","created":"Fri, 02\/23\/2018 - 14:06","resource_group_id":"","last_modified":"Date changed  Thu, 02\/07\/2019 - 20:45"},{"id":"eab1edf2-551b-4e14-ba81-95dc946adf62","revision_id":"","url":"https:\/\/accscatalog.uaa.alaska.edu\/sites\/default\/files\/REA_CentralYukon_AnthropogenicFootprint.zip","description":"\u003Cp\u003EInterior Alaska is a diverse socioeconomic region with remote subsistence-based communities, resource extraction activities, military bases, and western urban regions. In remote areas, rivers are commonly used as transportation pathways, but the region also contains five of the 13 highways in Alaska. Connection to the state highway system dramatically alters community dynamics, including but not limited to prices of fuel, employment, and access to hunting and fishing resources.\u003C\/p\u003E\n\u003Ch3\u003E\u003Cstrong\u003ECulverts\u003C\/strong\u003E\u003C\/h3\u003E\n\u003Cp\u003ECulverts that are sized or installed inappropriately can have several detrimental impacts to stream physical and chemical habitat, in addition to preventing fish passage. Water quality impairments from road crossings include increased sedimentation and delivery of toxic compounds from the road surface. Physical habitat impairments are numerous and include stream channelization; scouring or erosion downstream of perched culverts; ponding and sedimentation upstream; decreased transport of water, sediments, and wood downstream; and partial to complete blockage, which may lead to failure during flood event. Finally, roads are also an important pathway transporting invasive species to aquatic habitats. ADFG inventoried 374 culverts for juvenile fish passage. Culvert conditions that prevent passage to fish include perched outlets, steep gradients, or constricted culverts. These same failures lead to physical habitat impacts both upstream and downstream. Culverts were rated red when conditions were inadequate for fish passage, gray when conditions were unlikely to allow for fish passage, green when conditions allowed for fish passage, and black when more information was needed.\u003C\/p\u003E\n\u003Ch3\u003E\u003Cstrong\u003EBoat Launches\u003C\/strong\u003E\u003C\/h3\u003E\n\u003Cp\u003EThis data contains the boat access sites for interior Alaska located on flowing water bodies. This dataset was created for the analysis of waterweed (Elodea spp.) invasion vulnerability. Boat launches were hand-digitized from the Alaska Department of Fish and Game and the Bureau of Land Management website. Links to the source maps are stored in the attribute table.\u003C\/p\u003E\n\u003Ch3\u003E\u003Cstrong\u003EMines, Material Sale Sites, and Open Contaminated Sites\u003C\/strong\u003E\u003C\/h3\u003E\n\u003Ch3\u003EMaterial Sales Sites\u003C\/h3\u003E\n\u003Cp\u003EThis dataset was originally developed by Alaska Department of Natural Resources to track material sales sites (gravel pits).\u003C\/p\u003E\n\u003Ch3\u003ECurrent Mines\u003C\/h3\u003E\n\u003Cp\u003EThis dataset contains current active mines based on the Alaska Resource Data File (ARDF) and randomized mines representing mine density from Alaska Department of Natural Resources in interior Alaska.\u003C\/p\u003E\n\u003Ch3\u003EHistoric Mines\u003C\/h3\u003E\n\u003Cp\u003EThis dataset contains historic (inactive and closed) mines with past production based on the Alaska Resource Data File (ARDF).\u003C\/p\u003E\n\u003Ch3\u003EOpen Contaminated Sites\u003C\/h3\u003E\n\u003Cp\u003EThe Department of Environmental Conservation (ADEC) open contaminated sites layer shows past and present contaminated sites that still require clean-up. Contaminated sites are located within a variety of land management jurisdictions. There are 419 open contaminated sites in the dataset geography. Some contaminated sites are close to multiple aquatic habitats: 199 sites have the potential to affect 284 aquatic habitats. The majority of open contaminated sites are near small streams (130).\u003C\/p\u003E\n\u003Ch3\u003E\u003Cstrong\u003EPipelines and Oil and Gas Permits and Wells\u003C\/strong\u003E\u003C\/h3\u003E\n\u003Ch3\u003EPipelines\u003C\/h3\u003E\n\u003Cp\u003EThis data depicts pipeline infrastructure locations in Alaska as digitized primarily from 1:24,000, 1:63,360, and 1:250,000 USGS quadrangles. The source document that represented the newest information and best geographic location was used to capture the data. All infrastructure from the primary source document was digitized and then supplemented with the information from other source documents for additional or updated infrastructure or attributes.\u003C\/p\u003E\n\u003Ch3\u003ETrans-Alaska Pipeline System\u003C\/h3\u003E\n\u003Cp\u003EThis data depicts the Trans-Alaska Pipeline System, an oil pipeline infrastructure which runs from Prudhoe Bay to Valdez.\u003C\/p\u003E\n\u003Ch3\u003ENear-term Future Pipelines\u003C\/h3\u003E\n\u003Cp\u003EThis data depicts predicted pipelines for the future.\u003C\/p\u003E\n\u003Ch3\u003EOil and Gas Wells\u003C\/h3\u003E\n\u003Cp\u003EThis dataset depicts oil and gas wells, according to information retrieved from the Alaska Department of Natural Resources - Division of Oil and Gas in 2008. Due to limitations of the precision with which the locations of the wells is recorded within the table retrieved from the Department of Oil and Gas, the locations depicted in this dataset should be treated as approximate.\u003C\/p\u003E\n\u003Ch3\u003EOil and Gas Permits\u003C\/h3\u003E\n\u003Cp\u003EPermit or Lease - Mineral Estate includes a variety of permits or leases including Oil and Gas Lease, Shallow Gas Lease, Exploration License, Geothermal Permit or Lease, Mining Lease, Offshore Prospecting Permit or Lease, Coal Prospecting Permit or Lease. This dataset characterizes the geographic representation of land parcels within the State of Alaska contained by the Mineral Estate-Mineral Permit or Lease category.\u003C\/p\u003E\n\u003Ch3\u003E\u003Cstrong\u003ECommunity Locations and Footprints and Formerly Used Defense Sites\u003C\/strong\u003E\u003C\/h3\u003E\n\u003Ch3\u003EFormerly Used Defense Sites\u003C\/h3\u003E\n\u003Cp\u003EThe Formerly Used Defense Sites (FUDS) inventory is available by sites per state.  The data captures inventory as of September 30, 2013. DOD is responsible for the environmental restoration (cleanup) of properties that were formerly owned by, leased to or otherwise possessed by the United States and under the jurisdiction of the Secretary of Defense prior to October 1986. Such properties are known as Formerly Used Defense Sites or FUDS. The U.S. Army is DOD\u2019s lead agent for the FUDS Program. The U.S. Army Corps of Engineers executes the FUDS Program on behalf of the U.S. Army and DOD. The U.S. Army and DOD are dedicated to protecting human health and the environment by investigating and, if required, cleaning up potential contamination or munitions that may remain on these properties from past DOD activities.\u003C\/p\u003E\n\u003Ch3\u003EFairbanks and Community Footprints\u003C\/h3\u003E\n\u003Cp\u003EThe community footprints were produced by digitally tracing built areas from satellite imagery. This was done to represent the actual community footprints more accurately than would have been possible from the U.S. Census Bureau\u2019s Topologically Integrated Geographic Encoding and Referencing (TIGER) files. A majority of the communities are small and their footprints are concentrated in small areas with some activities scattered around each community\u0027s central location. Population in each community is often low and activity beyond identified footprint boundaries is limited to subsistence-use and inter-community trails.\u003C\/p\u003E\n\u003Ch3\u003EFairbanks and Community Locations\u003C\/h3\u003E\n\u003Cp\u003EThis point file was derived from the community footprints dataset. The points were manually edited and moved from their default position to a location that corresponded with the actual community location based on satellite imagery. The footprint feature class was produced by digitally tracing the built areas from satellite imagery. This was done to represent the actual footprints more accurately than would have been possible from the U.S. Census Bureau\u2019s Topologically Integrated Geographic Encoding and Referencing (TIGER) files. Generation of a point file from a polygon file is done by locating the point at the center of gravity of the polygon. Given the large polygons in the community TIGER file, centers of gravity are often well outside the actual community footprints. As a result, Census TIGER files were not used in identifying community footprints.\u003C\/p\u003E\n\u003Ch3\u003E\u003Cstrong\u003ETimber Sales: Prior to 1992, 1993-2009, and 2010-2014\u003C\/strong\u003E\u003C\/h3\u003E\n\u003Cp\u003EIn the 1980s, most timber harvest occurred only on the road system and the same pattern currently continues. Harvest in interior Alaska is limited by a 100\u2013120 year rotation length cycle and access. The main limiting factors for harvest are access, costs associated with extracting and shipping timber, and small diameter of the trees. Even though very little timber production actually occurs, climate change is threatening the future of upland white and black spruce and lowland black spruce in Interior Alaska and forest fire activity has been increasing, both of which could hinder future timber production. One limitation with harvesting timber is the cost to build roads, which can be more than the actual harvestable surplus.\u003C\/p\u003E\n\u003Ch3\u003E\u003Cstrong\u003ETransportation\u003C\/strong\u003E\u003C\/h3\u003E\n\u003Ch3\u003EAlternative Transportation: Current, Near-term Future, and Long-term Future\u003C\/h3\u003E\n\u003Cp\u003ETransportation networks are comprised of land (e.g. highways, roads, secondary roads, forestry roads, and trails), air (e.g. airports and airstrips), and water (e.g. rivers). Communities in the FNSB and a few outlying communities are connected by roads, but many communities in the area are only accessible by airplane, boat, or snowmachine in winter. Included in trails were those designated under the Revised Statute (RS) 2477 of the Mining Act of 1866 that granted public right-of-way across unreserved Federal land to guarantee access as land transferred to state or private ownership. Rights-of-way were created and granted under RS 2477 until its repeal in 1976. However, trails that existed in 1976 continue to be valid rights-of-way for public use and given the large area it is not feasible to examine this with satellite imagery. Along the Dalton Highway, there are a number of trails and access routes that were provided by the BLM, including: mining compliance trails, Dalton pipeline gravel access roads, and Dalton Highway ground transportation linear feature mining roads and trails. Alternative transportation contains trails, railroads, and rivers used for transportation.\u003C\/p\u003E\n\u003Ch3\u003ERailroads: Current and Proposed Extension\u003C\/h3\u003E\n\u003Cp\u003EThe availability of transportation routes is a major factor that influences the social and economic atmosphere of communities in the CYR study area. The influences of transportation routes can be both negative and positive, but nonetheless changes occur when a community becomes connected to a larger transportation network. The Alaska Railroad is the primary rail network throughout Alaska and the region. The Northern Rail Extension project will extend the current railroad system south of Fairbanks to Delta Junction. There are four phases of this project, with Phase 1 completed. Phase 2 includes expansion of the railroad from Moose Creek near North Pole to across the newly built Tanana River Bridge by Salcha. The completion of phases 3 and 4 is dependent on funding and therefore uncertain. During these phases the railroad will be extended to Delta Junction and temporary bridges across sloughs were removed.\u003C\/p\u003E\n\u003Ch3\u003ERoads and Trails\u003C\/h3\u003E\n\u003Cp\u003E\u003Cem\u003EHighways, Secondary Roads and Proposed Forestry Roads\u003C\/em\u003E\u003C\/p\u003E\n\u003Cp\u003EHighways digitized by Alaska Department of Natural Resources from USGS topographic maps and corrected by Alaska Center for Conservation Science by comparison to satellite imagery. Secondary roads were digitized by Alaska Department of Natural Resources, Fairbanks North Star Borough, and other sources and corrected by Alaska Center for Conservation Science by comparison to satellite imagery. Datasets were developed for Northwest Boreal LCC.\u003C\/p\u003E\n\u003Cp\u003E\u003Cem\u003EPrimary and Secondary Trails\u003C\/em\u003E\u003C\/p\u003E\n\u003Cp\u003ERS 2477 stands for Revised Statute 2477 from the Mining Act of 1866, which states: \u0022The right-of-way for the construction of highways over public lands, not reserved for public uses, is hereby granted.\u0022 The act granted a public right-of-way across unreserved federal land to guarantee access as land transferred to state or private ownership. Rights-of-way were created and granted under RS 2477 until its repeal in 1976. In Alaska, federal land was \u0022reserved for public uses\u0022 in December 1968, with passage of PLO 4582, also known as the \u0022land freeze.\u0022 This date ends the window of RS 2477 qualification in Alaska.\u003C\/p\u003E\n\u003Cp\u003E\u003Cem\u003EProposed Roads to Resources\u003C\/em\u003E\u003C\/p\u003E\n\u003Cp\u003EThe Alaska Department of Transportation and Public Facilities (ADOT) has funded studies of preferred routes for proposed roads. According to the ADOT-funded studies, the community of Galena would potentially be influenced by the road to Nome. Future road development has the potential to greatly alter the landscape and provide access to consumptive and non-consumptive users. The effects of proposed roads must be evaluated in case they become implemented in the near-term or long-term future. Of the four routes suggested to the Ambler mining district, the southern route has been deemed the most likely because it uses existing highways, minimizes crossing federal lands, which require additional scrutiny, facilitates access to rural communities, and provides the most access to mineral resources along the Yukon River. Of all proposed roads, the road to Umiat is the shortest (29 km), followed by the preferred option for the road to Nome (459 km). The longest proposed road would provide access to the Ambler mining district from the Dalton Highway (1,325 km).\u003C\/p\u003E\n\u003Cp\u003E\u003Cem\u003ELong-term Future Road to Tanana\u003C\/em\u003E\u003C\/p\u003E\n\u003Cp\u003EPossible route for a future road to the community of Tanana.\u003C\/p\u003E\n\u003Ch3\u003EUtility Lines\u003C\/h3\u003E\n\u003Cp\u003EUtility lines were merged from various sources to provide the best comprehensive coverage. This dataset depicts the spatial extent of electrical powerlines in the interior area. Electrical lines, telephone lines, and pipelines were provided by Alaska Department of Natural Resources. The original statewide data was digitized from 1:63,360 and 1:250,000 USGS topographic maps. The source document that represented the newest information and best geographic location was used to capture the data. All infrastructure from the primary source document was digitized and then supplemented with the information from other source documents for additional or updated infrastructure or attributes.\u003C\/p\u003E\n","format":"zip","state":"Active","revision_timestamp":"Fri, 02\/01\/2019 - 11:30","name":"Central Yukon Anthropogenic Footprint","mimetype":"application\/zip","size":"10.94 MB","created":"Fri, 02\/23\/2018 - 12:43","resource_group_id":"","last_modified":"Date changed  Fri, 02\/01\/2019 - 11:30"},{"id":"c499fbb9-5b39-4053-bfea-938732c2dad7","revision_id":"","url":"https:\/\/accscatalog.uaa.alaska.edu\/sites\/default\/files\/REA_CentralYukon_BoatLaunches.zip","description":"\u003Cp\u003EThis data contains the boat access sites for interior Alaska located on flowing water bodies. This dataset was created for the analysis of waterweed (Elodea spp.) invasion vulnerability. Boat launches were hand-digitized from the Alaska Department of Fish and Game and the Bureau of Land Management website. Links to the source maps are stored in the attribute table.\u003C\/p\u003E\n\u003Cp\u003E\u003Ca target=\u0022_blank\u0022 href=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_CentralYukonBoatLaunches.jpg\u0022\u003E\u003Ccenter\u003E\u003Cimg alt=\u0022Boat launches in the Central Yukon Region\u0022 title=\u0022Boat launches in the Central Yukon Region\u0022 width=\u0022600\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_CentralYukonBoatLaunches.jpg\u0022 \/\u003E\u003C\/center\u003E\u003C\/a\u003E\u003C\/p\u003E\n","format":"zip","state":"Active","revision_timestamp":"Fri, 02\/01\/2019 - 11:30","name":"Boat Launches in the Central Yukon Region","mimetype":"application\/zip","size":"14.44 KB","created":"Sun, 02\/25\/2018 - 13:02","resource_group_id":"","last_modified":"Date changed  Fri, 02\/01\/2019 - 11:30"},{"id":"197aa3c2-f592-4d8d-82ad-97ead6a97dec","revision_id":"","url":"https:\/\/accscatalog.uaa.alaska.edu\/sites\/default\/files\/REA_CentralYukon_LandscapeCondition.zip","description":"\u003Cp\u003EAs a final measure of potential human impacts to the ecoregions, the impacts of current anthropogenic development are summarized in a 60 x 60 m grid by the landscape condition model (LCM). The LCM weighs the relative influence of different types of human footprints based on factors like permanence, nature of the activity, etc. Permanent human modification is weighted the highest, while temporary use receive less weight. Intensive land uses like mining are also weighted higher than less intensive land uses like trails. These weights are summed across the landscape and coalesced into a single surface identifying how impacted a given area is due to human modification. Categories of human impacts included in this analysis are transportation infrastructure, urban and industrial development, and invasive species. Distance decay values are assigned to each impact such that the impact declines with increasing distance from infrastructure. Human impacts of each type are merged according to MIN rules to create a final dataset. This analysis is intended to identify the current level of human impact in the study area. The output for landscape condition is a relative scale from 1 to 5, with values of 5 representing \u0022Very High\u0022 landscape condition and values of 1 representing \u0022Very Low\u0022 landscape condition.\u003C\/p\u003E\n\u003Cp\u003E\u003Ca href=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_CentralYukonLandscapeCondition.jpg\u0022\u003E\u003Ccenter\u003E\u003Cimg alt=\u0022Central Yukon Landscape Condition\u0022 title=\u0022Central Yukon Landscape Condition\u0022 width=\u0022600\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_CentralYukonLandscapeCondition.jpg\u0022 \/\u003E\u003C\/center\u003E\u003C\/a\u003E\u003C\/p\u003E\n","format":"zip","state":"Active","revision_timestamp":"Thu, 01\/31\/2019 - 19:10","name":"Central Yukon Landscape Condition","mimetype":"application\/zip","size":"1.8 MB","created":"Sun, 02\/25\/2018 - 13:32","resource_group_id":"","last_modified":"Date changed  Thu, 01\/31\/2019 - 19:10"},{"id":"1587cba6-f3a0-4358-bae4-2cedb2757e0a","revision_id":"","url":"https:\/\/accscatalog.uaa.alaska.edu\/sites\/default\/files\/REA_CentralYukon_StreamNetworkLandscapeCondition.zip","description":"\u003Cp\u003EThe current (2015) and long-term future (2060) landscape condition model (LCM) was modified to develop condition scores for both the stream network and individual 6th-level hydrologic units. Landscape condition is a measurement of the impact of the human footprint on a landscape. Human modifications were categorized into different levels of impact (site impact scores) based on the current state of knowledge about the impacts of specific human land uses. An artificial stream network was calculated from the USGS National Elevation Dataset 2 Arc Second Digital Elevation Model using TauDEM. The flow direction grid and LCM grids were used to create a condition-weighted contributing area grid that summed condition scores upstream of each cell in the synthetic stream network. The resulting sums were divided by the total accumulation (number of upstream cells per individual cell) of each cell to create mean watershed condition scores along the stream network. Mean watershed condition scores only represented those parts of the watershed within the area since the extent of input data ended at the boundary. Current and long-term future (2060) condition scores for the stream network were classified into five equal intervals and summarized across the area.\u003C\/p\u003E\n\u003Cp\u003E\u003Ca href=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_CentralYukonStreamCondition.jpg\u0022\u003E\u003Ccenter\u003E\u003Cimg alt=\u0022Stream Network Landscape Condition in Interior Alaska\u0022 title=\u0022Stream Network Landscape Condition in Interior Alaska\u0022 width=\u0022600\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_CentralYukonStreamCondition.jpg\u0022 \/\u003E\u003C\/center\u003E\u003C\/a\u003E\u003C\/p\u003E\n","format":"zip","state":"Active","revision_timestamp":"Fri, 02\/01\/2019 - 11:02","name":"Stream Network Landscape Condition in Interior Alaska","mimetype":"application\/zip","size":"45.28 MB","created":"Sun, 02\/25\/2018 - 13:39","resource_group_id":"","last_modified":"Date changed  Fri, 02\/01\/2019 - 11:02"},{"id":"9c27fed8-3b29-473b-903e-94f52e648de2","revision_id":"","url":"https:\/\/accscatalog.uaa.alaska.edu\/sites\/default\/files\/REA_CentralYukon_LandscapeIntactness.zip","description":"\u003Cp\u003ELandscape condition should not be assessed at a particular location without some explicit consideration of the surrounding environment. Landscape intactness provides a quantifiable and readily assessable measure of naturalness: it is a measure of how contiguous a landscape is. The purpose of these datasets is to provide an assessment of the relative landscape condition across a region to identify if the areas with degraded conditions are isolated or connected, which corresponds to how resilient an area might be to future changes. Some elements of human modification, specifically subsistence harvest, are not captured well in current models of intactness. Therefore, we modeled landscape intactness by extracting areas from the Landscape Condition Model (LCM) with a value equal to 5 (corresponding to a score of 0.8 or higher) for the ecoregion, realizing that we likely underrepresented the true degree of human modification. Areas that meet the condition criteria were then lumped together into Large Intact Blocks (LIBs) and total areas of contiguous high condition landscape blocks were calculated. LIBs that are greater than or equal to 50,000 acres are considered as having the highest landscape intactness. Blocks that are less than 50,000 acres but greater than or equal to 10,000 acres correspond to high landscape integrity. Third, we identified all the blocks that are less than 10,000 acres as potentially vulnerable to disturbances. Most of the study area falls within the highest landscape integrity category. However, a substantial amount of small, fragmented areas were indeed identified throughout the region. Most of these fragmented habitats are located around communities and mining operations, but also include some areas fragmented by the larger rivers that serve as snowmachine travel corridors during winter months.\u003C\/p\u003E\n\u003Cp\u003E\u003Ca href=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_CentralYukonMinimumDynamicReserve.jpg\u0022\u003E\u003Ccenter\u003E\u003Cimg alt=\u0022minimum dynamic reserve in Interior Alaska\u0022 title=\u0022Minimum dynamic reserve in Interior Alaska\u0022 width=\u0022600\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_CentralYukonMinimumDynamicReserve.jpg\u0022 \/\u003E\u003C\/center\u003E\u003C\/a\u003E\u003C\/p\u003E\n","format":"zip","state":"Active","revision_timestamp":"Fri, 02\/01\/2019 - 10:43","name":"Central Yukon Landscape Intactness and Minimum Dynamic Reserve","mimetype":"application\/zip","size":"2.68 MB","created":"Sun, 02\/25\/2018 - 13:26","resource_group_id":"","last_modified":"Date changed  Fri, 02\/01\/2019 - 10:43"},{"id":"0c4f6d48-5bf1-4400-a5a7-875e5afe9781","revision_id":"","url":"https:\/\/accscatalog.uaa.alaska.edu\/sites\/default\/files\/REA_CentralYukon_CumulativeImpacts.zip","description":"\u003Cp\u003EThe Cumulative Impacts analysis included the primary, measurable change agent variables that are likely to have the largest and most direct impact in the area in the future. However, in order to \u201csum\u201d the impacts, thresholds for meaningful change had to be defined for each variable. Cumulative Impacts are not specific to any ecosystem constituent or process but are intended to be representative of the ecosystem as a whole, so thresholds for meaningful change are based on model variability and the potential to impact management decisions. This dataset does not assess the likely collinearity of the change agents, but rather considers each change agent as a separate stressor that will differentially impact resources in the area. The inverse of this dataset could be seen as a landscape vulnerability index (LVI) that could be used to assist in future resource planning efforts.\u003C\/p\u003E\n\u003Cp\u003E\u003Ca href=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_CentralYukonCumulativeImpacts.jpg\u0022\u003E\u003Ccenter\u003E\u003Cimg alt=\u0022Central Yukon Cumulative Impacts\u0022 title=\u0022Cumulative Impacts in Central Yukon Region\u0022 width=\u0022600\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_CentralYukonCumulativeImpacts.jpg\u0022 \/\u003E\u003C\/center\u003E\u003C\/a\u003E\u003C\/p\u003E\n","format":"zip","state":"Active","revision_timestamp":"Thu, 01\/31\/2019 - 18:51","name":"Central Yukon Cumulative Impacts","mimetype":"application\/zip","size":"1.73 MB","created":"Fri, 02\/23\/2018 - 15:43","resource_group_id":"","last_modified":"Date changed  Thu, 01\/31\/2019 - 18:51"},{"id":"e6a9c1bd-4856-4599-90e6-9c1f37fe4bd0","revision_id":"","url":"https:\/\/accscatalog.uaa.alaska.edu\/sites\/default\/files\/REA_CentralYukon_BiophysicalSettings.zip","description":"\u003Cp\u003EBiophysical settings are regionally important habitat types that share similar vegetation and biophysical site characteristics including permafrost characteristics, surficial deposit, disturbance and succession. Together, these (floodplain forest and shrub, lowland woody wetland, upland mesic spruce-hardwood forest, upland mesic spruce forest, upland low and tall shrub, alpine and Arctic tussock tundra, and alpine dwarf shrub tundra) biophysical settings represent the majority of the terrestrial landscape within the interior Alaska geography.\u003C\/p\u003E\n","format":"zip","state":"Active","revision_timestamp":"Thu, 01\/31\/2019 - 18:44","name":"Biophysical Settings of Interior Alaska","mimetype":"application\/zip","size":"104.38 MB","created":"Fri, 02\/23\/2018 - 15:17","resource_group_id":"","last_modified":"Date changed  Thu, 01\/31\/2019 - 18:44"},{"id":"acb4ef02-377b-4a2d-ab74-d2dbe30a27c2","revision_id":"","url":"https:\/\/accscatalog.uaa.alaska.edu\/sites\/default\/files\/REA_CentralYukon_SummerWarmthIndex.zip","description":"\u003Cp\u003ESummer warmth index (SWI) is calculated as the sum of mean monthly temperatures \u0026gt; 0 \u00b0C. SWI is an index that has been used to measure linkages between climate change and changes in vegetation. SWI can be used instead of date of thaw (DOT), date of freeze (DOF), length of growing season (LOGS), and July temperature data or in conjunctions with these metrics to determine potential impacts, depending on whether a species or assemblage is more dependent on the duration, extremes, timing, or overall warmth of the summer season. While LOGS is measured in units of time, SWI is measured in units of degrees Celsius. This dataset includes a downscaled projection of Summer Warmth Index (cumulative mean June, July, and August temperatures above 0\u00b0C), in degrees Celsius, for the decades 2010-2019, 2020-2029, and 2060-2069 at 771x771 meter spatial resolution. The file represents a sum of decadal monthly mean temperatures, using the A2 emissions scenario.\u003C\/p\u003E\n\u003Cp\u003E\u003Ca href=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_CentralYukonSummerWarmth.jpg\u0022\u003E\u003Ccenter\u003E\u003Cimg alt=\u0022Central Yukon Summer Warmth Index\u0022 title=\u0022Central Yukon Summer Warmth Index\u0022 width=\u0022600\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_CentralYukonSummerWarmth.jpg\u0022 \/\u003E\u003C\/center\u003E\u003C\/a\u003E\u003C\/p\u003E\n","format":"zip","state":"Active","revision_timestamp":"Thu, 01\/31\/2019 - 18:57","name":"Central Yukon Summer Warmth Index","mimetype":"application\/zip","size":"2.71 MB","created":"Fri, 02\/23\/2018 - 17:47","resource_group_id":"","last_modified":"Date changed  Thu, 01\/31\/2019 - 18:57"},{"id":"a6dc133f-eeca-4bf4-9686-67b18dab3d97","revision_id":"","url":"https:\/\/accscatalog.uaa.alaska.edu\/sites\/default\/files\/REA_CentralYukon_CaribouForageQuality.zip","description":"\u003Cp\u003ECaribou have adapted a life cycle that favors nutrient and energy conservation in the winter months and rapid growth and energy\/nutrient storage in summer months. Preferred forage species are highly dependent on season. Nutrient and digestible energy content in plants is linked to growth stage. Seasonal forage preferences of caribou correlate to the plants species, plant parts, and growth stage that contain the highest available nutrients and energy at the time. Vegetation communities preferred by caribou are thus seasonally dependent.\u003C\/p\u003E\n\u003Cp\u003E\u003Ca href=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_CaribouForageQualityInterior.jpg\u0022\u003E\u003Ccenter\u003E\u003Cimg alt=\u0022caribou forage quality in Interior Alaska\u0022 title=\u0022Areas of moderate and good quality calving season and summer forage for caribou\u0022 width=\u0022600\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_CaribouForageQualityInterior.jpg\u0022 \/\u003E\u003C\/center\u003E\u003C\/a\u003E\u003C\/p\u003E\n","format":"zip","state":"Active","revision_timestamp":"Thu, 01\/31\/2019 - 18:43","name":"Caribou Forage Quality During Summer and Winter in Interior Alaska","mimetype":"application\/zip","size":"99.49 MB","created":"Fri, 02\/23\/2018 - 15:31","resource_group_id":"","last_modified":"Date changed  Thu, 01\/31\/2019 - 18:43"},{"id":"8f7f4933-c39e-4fbe-99d9-098516f1dfc1","revision_id":"","url":"https:\/\/accscatalog.uaa.alaska.edu\/sites\/default\/files\/REA_CentralYukon_DollyVardenResidentHabitat.zip","description":"\u003Cp\u003EResident Dolly Varden habitats were modeled for the entire study area. Dolly Varden generally mature at five to nine years of age and can spawn multiple times throughout their lifetimes. Tagging studies have shown that anadromous Dolly Varden maintain a strong fidelity to overwintering and spawning areas and that spawning typically occurs in overwintering areas. However, some Dolly Varden may overwinter in areas not connected to their natal streams. Dolly Varden use habitats associated with discharging groundwater for spawning, rearing, and overwintering. Peak spawning occurs in September and October, usually in headwater streams in the study area. Females lay eggs in small nests dug into gravel streambeds. Hatching of eggs generally occurs in March, and juvenile fish emerge from the gravel in late spring. Juvenile Dolly Varden rear in streams, rivers, and\/or lakes for a few years, after which time individuals from anadromous populations may migrate to nearshore coastal. Dolly Varden consume aquatic macroinvertebrates, salmon eggs and fry, and other small fishes. Juveniles feed primarily on macroinvertebrates.\u003C\/p\u003E\n\u003Cp\u003E\u003Ca href=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_DollyVardenInteriorAlaska.jpg\u0022\u003E\u003Ccenter\u003E\u003Cimg alt=\u0022Dolly varden resident habitat in Interior Alaska\u0022 title=\u0022Dolly varden resident habitat in Interior Alaska\u0022 width=\u0022600\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_DollyVardenInteriorAlaska.jpg\u0022 \/\u003E\u003C\/center\u003E\u003C\/a\u003E\u003C\/p\u003E\n","format":"zip","state":"Active","revision_timestamp":"Fri, 02\/01\/2019 - 10:15","name":"Dolly Varden Resident Habitat in Interior Alaska","mimetype":"application\/zip","size":"9.86 MB","created":"Fri, 02\/23\/2018 - 16:06","resource_group_id":"","last_modified":"Date changed  Fri, 02\/01\/2019 - 10:15"},{"id":"bbc9e844-182a-4dd3-b1a1-3e82c798b499","revision_id":"","url":"https:\/\/accscatalog.uaa.alaska.edu\/sites\/default\/files\/REA_CentralYukon_GoldenEagle.zip","description":"\u003Cp\u003EIn Alaska, the golden eagle ranges from the Brooks Range in the north, south throughout much of the mainland, with limited distribution in Southeast, and rare occurrence in the Aleutians and the Alaska Peninsula. They inhabit areas that are open or barren, such as arctic and alpine tundra, prairie, open wooded country, and hilly or mountainous regions. Golden eagles typically breed in semi-open habitats such as tundra, grasslands, woodland-brushlands and coniferous forests. In Alaska, breeding occurs in areas of rugged topography or mountainous terrain, near or above treeline and along riparian areas. Nests are large (up to 3 m across and 1.2 m thick), and can be found on rugged alpine areas with bluffs or cliffs, but trees can also be used. Factors that influence golden eagle abundance include: food availability, severe weather, habitat availability, anthropogenic disturbances, and accidental poisoning (caused by ingesting poisoned meat intended for coyotes).\u003C\/p\u003E\n\u003Cp\u003E\u003Ca href=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_CentralYukonGoldenEagle.jpg\u0022\u003E\u003Ccenter\u003E\u003Cimg alt=\u0022potential habitat of golden eagle in Interior Alaska\u0022 title=\u0022potential habitat of golden eagle in Interior Alaska\u0022 width=\u0022600\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_CentralYukonGoldenEagle.jpg\u0022 \/\u003E\u003C\/center\u003E\u003C\/a\u003E\u003C\/p\u003E\n","format":"zip","state":"Active","revision_timestamp":"Fri, 02\/01\/2019 - 10:19","name":"Golden Eagle Potential Habitat in Interior Alaska","mimetype":"application\/zip","size":"3.05 MB","created":"Fri, 02\/23\/2018 - 16:00","resource_group_id":"","last_modified":"Date changed  Fri, 02\/01\/2019 - 10:19"},{"id":"be2a0889-3df5-4925-9aa2-f4c64c9a2607","revision_id":"","url":"https:\/\/accscatalog.uaa.alaska.edu\/sites\/default\/files\/REA_CentralYukon_SnowshoeHare.zip","description":"\u003Cp\u003ESnowshoe hare occur year-round throughout the Taiga of Alaska and inhabit mixed spruce forests, wooded swamps and brushy areas. They prefer dense brush and forest cover, which provide protection from both avian and terrestrial predators. Their diet varies between summer and winter depending on forage availability. In the summer, forage consists mainly of grasses, buds, twigs and leaves, while in the winter, spruce twigs and needles, bark and willow buds are consumed.\u003C\/p\u003E\n\u003Cp\u003E\u003Ca href=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_SnowshoeHarePotentialHabitat.jpg\u0022\u003E\u003Ccenter\u003E\u003Cimg alt=\u0022Snowshoe hare potential habitat in Interior Alaska\u0022 title=\u0022Snowshoe hare potential habitat in Interior Alaska\u0022 width=\u0022600\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_SnowshoeHarePotentialHabitat.jpg\u0022 \/\u003E\u003C\/center\u003E\u003C\/a\u003E\u003C\/p\u003E\n","format":"zip","state":"Active","revision_timestamp":"Fri, 02\/01\/2019 - 10:53","name":"Snowshoe Hare Potential Habitat in Interior Alaska","mimetype":"application\/zip","size":"103.37 MB","created":"Fri, 02\/23\/2018 - 17:51","resource_group_id":"","last_modified":"Date changed  Fri, 02\/01\/2019 - 10:53"},{"id":"94314a96-ae86-405b-8b67-919834b4c475","revision_id":"","url":"https:\/\/accscatalog.uaa.alaska.edu\/sites\/default\/files\/REA_CentralYukon_SwainsonsThrush.zip","description":"\u003Cp\u003ESwainson\u2019s thrush is a small aerial insectivore common throughout Alaska. It is a long-distant migrant that breeds in western to northern North America, and spends its winters from southern Mexico to northern Argentina. In the Yukon Territory, Swainson\u2019s thrush inhabits willow shrub and various forest types. In the Alaska taiga, Swainson\u2019s thrush typically inhabits forested areas more than shrub thickets. While Swainson\u2019s thrush are common throughout Alaska, populations are reported as declining across their range, particularly in Alaska and the Northeast.\u003C\/p\u003E\n\u003Cp\u003E\u003Ca href=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_SwainsonsThrushPotentialHabitat.jpg\u0022\u003E\u003Ccenter\u003E\u003Cimg alt=\u0022Swainson\u0027s thrush potential habitat in Interior Alaska\u0022 title=\u0022Swainson\u0027s thrush potential habitat in Interior Alaska\u0022 width=\u0022600\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_SwainsonsThrushPotentialHabitat.jpg\u0022 \/\u003E\u003C\/center\u003E\u003C\/a\u003E\u003C\/p\u003E\n","format":"zip","state":"Active","revision_timestamp":"Fri, 02\/01\/2019 - 10:58","name":"Swainson\u0027s Thrush Potential Habitat in Interior Alaska","mimetype":"application\/zip","size":"4.74 MB","created":"Sun, 02\/25\/2018 - 12:42","resource_group_id":"","last_modified":"Date changed  Fri, 02\/01\/2019 - 10:58"},{"id":"8d0d32a2-e2f0-4af3-9903-d952281bead9","revision_id":"","url":"https:\/\/accscatalog.uaa.alaska.edu\/sites\/default\/files\/RA_CentralYukon_DallSheep.zip","description":"\u003Cp\u003EDall sheep inhabit Alaska\u2019s mountain ranges and are found in the highest, most rugged peaks and cliffs in the Central Alaska region. They typically inhabit semi-open, steep terrain with rocky slopes, ridges, and cliffs or rugged canyons; dry mountainous terrain, subalpine grass-low shrub communities. They are mainly present in alpine habitats including low shrub areas and forage on a variety of vegetation such as forbs and grasses during summer. During winter when vegetation is sparse, sheep seek out locations with shallow snow and increased forage accessibility. Winter forage consists of grasses, sedge stems, and lichens and mosses exposed on windblown slopes.\u003C\/p\u003E\n\u003Ch3\u003ETotal Annual Range of Dall Sheep\u003C\/h3\u003E\n\u003Cp\u003EPolygon ranges of Dall sheep in Alaska were digitized from the 1985 ADFG Habitat Management Guide and modified in 2015 by ADFG to reflect updates in known sheep ranges. This version of Dall sheep range was modified based on known occurrences of Dall sheep to serve as a more accurate boundary for the conversion of a potential habitat distribution to a realized habitat distribution.\u003C\/p\u003E\n\u003Ch3\u003EDall Sheep Realized Habitat\u003C\/h3\u003E\n\u003Cp\u003EMales and females typically live in sexually segregated groups throughout the year, coming together in late November and early December for mating. In spring (late May\/early June), when lambs are born, reproductive females prefer higher altitude habitat and rely on steep mountain areas for protection from predators. Thus the realized habitat distribution reflects the habitat Dall sheep are known to inhabit.\u003C\/p\u003E\n\u003Cp\u003E\u003Ca href=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_DallSheepInteriorAlaska.jpg\u0022\u003E\u003Ccenter\u003E\u003Cimg alt=\u0022Realized habitat of dall sheep in Interior Alaska\u0022 title=\u0022Realized habitat of dall sheep in Interior Alaska \u0022 width=\u0022600\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_DallSheepInteriorAlaska.jpg\u0022 \/\u003E\u003C\/center\u003E\u003C\/a\u003E\u003C\/p\u003E\n","format":"zip","state":"Active","revision_timestamp":"Fri, 02\/01\/2019 - 10:22","name":"Realized Habitat and Total Annual Range for Dall Sheep","mimetype":"application\/zip","size":"1.77 MB","created":"Fri, 02\/23\/2018 - 15:55","resource_group_id":"","last_modified":"Date changed  Fri, 02\/01\/2019 - 10:22"},{"id":"ae5f4364-8a41-4ff6-88b4-7ac7c0393d56","revision_id":"","url":"https:\/\/accscatalog.uaa.alaska.edu\/sites\/default\/files\/REA_CentralYukon_SpruceBeetleDamage.zip","description":"\u003Cp\u003EModeling future potential for spruce beetle outbreaks is not possible because of stochasticity of outbreaks and poor understanding of some environmental factors influencing outbreaks. However, linkages have been previously demonstrated for several climate variables with spruce beetle life cycle and with potential for severe, regional outbreaks.\u003C\/p\u003E\n\u003Ch3\u003EClimate vulnerability to spruce beetle outbreaks from 2000 to 2009\u003C\/h3\u003E\n\u003Cp\u003ERegional spruce beetle outbreaks in Alaska have been linked with warmer, longer summers compared to historic averages. Higher summer temperature increased reproductive success and reduced the generation time of spruce beetles on the Kenai Peninsula, where spruce beetle outbreaks have been concurrent with 5 to 6 years of sustained warm summers for at least the past 200 years when stands of mature spruce were available. Longer growing seasons have allowed earlier emergence, attack, and breeding of adult spruce beetles. Warmer decadal average January temperatures would be likely to increase spruce beetle overwinter survival in the study area because temperatures cold enough to kill spruce beetles would be reached less frequently and sustained for less time. Climate vulnerable areas are defined for each decade by the area where mean June-July-August temperatures were \u2265 10.5\u00b0C, mean January temperatures were \u2265 -21.3\u00b0C, and growing season length was \u2265 173 days. Kernel Density Estimation was performed using Geospatial Modeling Environment (GME) with points of spruce beetle-related damage from 2000 to 2009. The kernel density was used to determine climate thresholds for spruce beetle outbreaks.\u003C\/p\u003E\n\u003Cp\u003E\u003Ca href=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_SpruceBeetleClimateVulnerability2000s.jpg\u0022\u003E\u003Ccenter\u003E\u003Cimg alt=\u0022Climate vulnerability to spruce beetle outbreaks from 2000 to 2009\u0022 title=\u0022Climate vulnerability to spruce beetle outbreaks from 2000 to 2009\u0022 width=\u0022600\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_SpruceBeetleClimateVulnerability2000s.jpg\u0022 \/\u003E\u003C\/center\u003E\u003C\/a\u003E\u003C\/p\u003E\n\u003Ch3\u003EFuture climate vulnerability to spruce beetle outbreaks\u003C\/h3\u003E\n\u003Cp\u003EFuture climate vulnerability indicates 5th level hydrologic units where the majority of the hydrologic unit is predicted to have mean June-July-August temperatures \u2265 10.5\u00b0C, mean January temperatures \u2265 -21.3\u00b0C, and growing season length \u2265 173 days. During the 2020s decade, conditions along the central Tanana River and north of Fairbanks will be climate-vulnerable to severe, regional spruce beetle outbreaks. By the 2060s decade, climate-vulnerable regions will include: along most of the Tanana River, Fairbanks north to the Yukon River, along the upper Yukon River between Eagle and Circle, along the Yukon River from the confluence with the Tanana River to Galena at the edge of the study area, and along the southern Koyukuk River. Much of the area will not likely become climate-vulnerable to severe, regional spruce beetle outbreaks by the 2060s decade. Kernel Density Estimation was performed using Geospatial Modeling Environment (GME) with points of spruce beetle-related damage from 2000 to 2009. The kernel density was used to determine climate thresholds for spruce beetle outbreaks.\u003C\/p\u003E\n\u003Cp\u003E\u003Ca href=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_SpruceBeetleClimateVulnerabilityFuture.jpg\u0022\u003E\u003Ccenter\u003E\u003Cimg alt=\u0022Future climate vulnerability to spruce beetle outbreaks\u0022 title=\u0022Future climate vulnerability to spruce beetle outbreaks\u0022 width=\u0022600\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_SpruceBeetleClimateVulnerabilityFuture.jpg\u0022 \/\u003E\u003C\/center\u003E\u003C\/a\u003E\u003C\/p\u003E\n","format":"zip","state":"Active","revision_timestamp":"Fri, 02\/01\/2019 - 10:37","name":"Climate Vulnerability to Spruce Beetle Outbreaks in Interior Alaska","mimetype":"application\/zip","size":"6.99 MB","created":"Fri, 02\/23\/2018 - 16:50","resource_group_id":"","last_modified":"Date changed  Fri, 02\/01\/2019 - 10:37"},{"id":"42b9108b-f34c-47d3-966a-a14b52d0ceec","revision_id":"","url":"https:\/\/accscatalog.uaa.alaska.edu\/sites\/default\/files\/REA_CentralYukon_InsectDamage.zip","description":"\u003Cp\u003EThe four host\/damage type combinations that have contributed the largest areas of forest damage within the study area were correlated to their causal agent(s). Area of forest damage was calculated and described for each of the four most prevalent host\/damage type combinations at five year intervals from 2000 to 2014. Severity of damage for the entire 15-year period from 2000 to 2014 was summarized for insect agents that had associated severity data.\u003C\/p\u003E\n\u003Ch3\u003EKernel Density of Willow Defoliation Caused by Willow Leafblotch Miner\u003C\/h3\u003E\n\u003Cp\u003EFrom 1991 to 1993, willow leafblotch miner defoliated large areas of willow along the Yukon and Kuskokwim Rivers. From 1998 to 1999, a regional willow leafblotch miner outbreak occurred around the Yukon Flats National Wildlife Refuge. Defoliation has occurred on numerous tall and low shrub willow species with the notable exception of felt-leaf willow, which is protected by dense hairs on lower leaf surfaces. The defoliation of willow caused by willow leafblotch miner accounted for over 20% of observed forest damage by area from 2000 to 2014. The area of observed willow defoliation doubled every 5-year period from 2000 to 2014. From 2010 to 2014, approximately 40% of observed forest damage was caused by willow leafblotch miner. This may indicate that environmental conditions are becoming more favorable for willow leafblotch miner within the study area. Most of the defoliation caused by willow leafblotch miner in Alaska occurred within the study area, although more sporadic, widely separated defoliation sites occurred throughout the state.  Kernel Density Estimation was performed using Geospatial Modeling Environment (GME) with points of aspen defoliation damage from 2000 to 2014. The raw kernel density output was interpolated as 5% quantiles of the kernel density values extracted to the original input points. This dataset provides a visualization of area and intensity of impact of aspen leafminer within Alaska from 2000 to 2014.\u003C\/p\u003E\n\u003Cp\u003E\u003Ca href=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_WillowLeafblotchMinerDamage.jpg\u0022\u003E\u003Ccenter\u003E\u003Cimg alt=\u0022Kernel density of willow leafblotch miner damage\u0022 title=\u0022Kernel density of willow leafblotch miner damage\u0022 width=\u0022600\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_WillowLeafblotchMinerDamage.jpg\u0022 \/\u003E\u003C\/center\u003E\u003C\/a\u003E\u003C\/p\u003E\n\u003Ch3\u003EKernel Density of Damage Caused by Spruce Budworm\u003C\/h3\u003E\n\u003Cp\u003ESpruce defoliation caused by spruce budworm accounted for 6% of observed forest damage by area from 2000 to 2014. However, most of the observed spruce defoliation (around 85%) was low severity (less than half of spruce within damage polygon were defoliated). Spruce budworm did not cause large areas of forest damage from 2010 to 2014: spruce defoliation was relatively high from 2000 to 2004 and 2005 to 2009, and then dropped to almost undetected levels from 2010 to 2014. Spruce budworm outbreaks from 2000 to 2014 were concentrated in areas along the Tanana River near Fairbanks and around the confluence of the Porcupine and Yukon rivers. An additional small aggregation of spruce budworm damage was located on the Kobuk River. Only sporadic, widely separated outbreaks occurred outside these areas. Kernel Density Estimation was performed using Geospatial Modeling Environment (GME) with points of spruce defoliation damage from 2000 to 2014. The raw kernel density output was interpolated as 5% quantiles of the kernel density values extracted to the original input points. This dataset provides a visualization of area and intensity of impact of spruce budworm within Alaska from 2000 to 2014.\u003C\/p\u003E\n\u003Cp\u003E\u003Ca href=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_SpruceBudwormDamage.jpg\u0022\u003E\u003Ccenter\u003E\u003Cimg alt=\u0022Kernel density of spruce budworm damage\u0022 title=\u0022Kernel density of spruce budworm damage\u0022 width=\u0022600\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_SpruceBudwormDamage.jpg\u0022 \/\u003E\u003C\/center\u003E\u003C\/a\u003E\u003C\/p\u003E\n\u003Ch3\u003EKernel Density of Spruce Mortality Caused by Spruce Beetle\u003C\/h3\u003E\n\u003Cp\u003EWhite spruce has been the most susceptible tree or shrub to mortality from insect and disease agents within the study area. Severity of damage has not been consistently identified for spruce mortality. While spruce beetle outbreaks have caused severe, regional spruce mortality in Southcentral Alaska, spruce beetles have caused only localized and sporadic damage in Interior Alaska. From 2000 to 2014, relatively little spruce beetle damage occurred within the study area. A small region of the 90% isopleth existed along the Yukon River upstream from the confluence with the Porcupine River. However, none of the 80% to 10% isopleths included any area within the study area, and spruce beetle activity was limited north of the eastern and central Alaska Range. From 1990 to 2014, spruce beetle caused only 370 sq km of spruce mortality. This long-term trend suggests that environmental conditions in the study area have historically prevented severe, regional spruce beetle outbreaks. Despite outbreaks being uncommon in the study area, spruce beetles are present in stressed or dying spruce throughout Interior Alaska. Spruce mortality caused by both spruce beetle and northern spruce engraver beetle remained the dominant form of mortality from 2010 to 2014. Kernel Density Estimation was performed using Geospatial Modeling Environment (GME) with points of spruce beetle damage from 2000 to 2014. The raw kernel density output was interpolated as 5% quantiles of the kernel density values extracted to the original input points. This dataset provides a visualization of area and intensity of impact of spruce beetle within Alaska from 2000 to 2014.\u003C\/p\u003E\n\u003Cp\u003E\u003Ca href=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_SpruceBeetleDamage.jpg\u0022\u003E\u003Ccenter\u003E\u003Cimg alt=\u0022Kernel density of spruce beetle damage\u0022 title=\u0022Kernel density of spruce beetle damage\u0022 width=\u0022600\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_SpruceBeetleDamage.jpg\u0022 \/\u003E\u003C\/center\u003E\u003C\/a\u003E\u003C\/p\u003E\n\u003Ch3\u003EKernel Density of Spruce Mortality Caused by Northern Spruce Engraver Beetle\u003C\/h3\u003E\n\u003Cp\u003EWhite spruce has been the most susceptible tree or shrub to mortality from insect and disease agents within the study area, but the severity of its damage has not been consistently identified. Northern spruce engraver beetle caused approximately 5 times more observed damage by area than spruce beetle. Much of the spruce mortality caused by northern spruce engraver beetle in Alaska fell within the study area, with a high density of the damage occurring north of the confluence of the Porcupine and Yukon Rivers. Northern spruce engraver beetle damage occurred along the lower Noatak River and sporadically throughout the length of the Kobuk River. Spruce mortality caused by both spruce beetle and northern spruce engraver beetle remained the dominant form of mortality from 2010 to 2014, with the northern spruce engraver beetle continuing to contribute more mortality than spruce beetle during those 4 years. The area of spruce mortality caused by northern spruce engraver beetle increased by more than five times between 2000 to 2004 and 2005 to 2009. During 2010 to 2014, activity of northern spruce engraver beetle declined from the amount observed from 2005 to 2009, though not to the levels of 2000 to 2004. Kernel Density Estimation was performed using Geospatial Modeling Environment (GME) with points of spruce damage from 2000 to 2014. The raw kernel density output was interpolated as 5% quantiles of the kernel density values extracted to the original input points. This dataset provides a visualization of area and intensity of impact of northern spruce engraver beetle within Alaska from 2000 to 2014.\u003C\/p\u003E\n\u003Cp\u003E\u003Ca href=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_NorthernSpruceEngraverBeetleDamage.jpg\u0022\u003E\u003Ccenter\u003E\u003Cimg alt=\u0022Kernel density of northern spruce engraver beetle damage\u0022 title=\u0022Kernel density of northern spruce engraver beetle damage\u0022 width=\u0022600\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_NorthernSpruceEngraverBeetleDamage.jpg\u0022 \/\u003E\u003C\/center\u003E\u003C\/a\u003E\u003C\/p\u003E\n\u003Ch3\u003EKernel Density of Aspen Defoliation Caused by Aspen Leaf Miner\u003C\/h3\u003E\n\u003Cp\u003EThe defoliation of quaking aspen (Populus tremuloides) caused by aspen leaf miner (Phyllocnistis populiella) accounted for over 60% of observed forest damage by area from 2000 to 2014 within the study area. Approximately 40% of aspen defoliation by area was high severity (over half of aspen within the damage polygon were defoliated). From 2010 to 2014, quaking aspen defoliation remained one of the major forms of insect- and disease-related forest damage and accounted for approximately 45% of observed forest damage by area. The area of quaking aspen defoliation has fluctuated every 5-year period between 2000 and 2014 (i.e. 2000 to 2004, 2005 to 2009, and 2010 to 2014) but has always remained the most common form of insect- and disease-related forest damage by area within the study area. The consistently high area of quaking aspen defoliation suggests that environmental conditions steadily favor high populations and\/or frequent outbreaks of aspen leaf miner. Temperature and precipitation have, among other environmental factors, driven the distribution of aspen leaf miner in Alaska. Most aspen defoliation caused by aspen leaf miner in Alaska from 2000 to 2014 occurred within the study area. Kernel Density Estimation was performed using Geospatial Modeling Environment (GME) with points of aspen defoliation damage from 2000 to 2014. The raw kernel density output was interpolated as 5% quantiles of the kernel density values extracted to the original input points. This dataset provides a visualization of area and intensity of impact of aspen leafminer within Alaska from 2000 to 2014.\u003C\/p\u003E\n\u003Cp\u003E\u003Ca href=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_AspenLeafminerDamage.jpg\u0022\u003E\u003Ccenter\u003E\u003Cimg alt=\u0022Kernel density of aspen leafminer damage\u0022 title=\u0022Kernel density of aspen leafminer damage\u0022 width=\u0022600\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_AspenLeafminerDamage.jpg\u0022 \/\u003E\u003C\/center\u003E\u003C\/a\u003E\u003C\/p\u003E\n","format":"zip","state":"Active","revision_timestamp":"Fri, 02\/01\/2019 - 11:16","name":"Kernel Densities of Insect-related Forest Damage from 2000 to 2014","mimetype":"application\/zip","size":"817.32 KB","created":"Fri, 02\/23\/2018 - 16:20","resource_group_id":"","last_modified":"Date changed  Fri, 02\/01\/2019 - 11:16"},{"id":"4670bf50-0df7-46d4-806b-3e5bc52ca302","revision_id":"","url":"https:\/\/accscatalog.uaa.alaska.edu\/sites\/default\/files\/REA_CentralYukon_InfestationVulnerability.zip","description":"\u003Cp\u003ESurvey intensity for non-native plant infestations in the area is not strong or consistent; we therefore developed an analytical model to identify areas that are perceived to be currently vulnerable to invasion by non-native plant species. This analysis is intended to supplement the empirical data, identify areas in which future surveys may be directed, and evaluate the potential change in vulnerability in the future. The analytical approach used here (variance partitioning via classification and regression tree) facilitates the evaluation of a large number of variables that may have non-linear relationships and complex interactions. This approach has been used elsewhere to understand patterns of plant invasion vulnerabilities. The purpose of this dataset is too identify vulnerability to invasion by non-native plants per 5th level hydrologic unit. We first determined the climate, habitat, and anthropogenic variables that are associated with watersheds having weed problems in Interior Alaska based on the AKEPIC dataset. We then determined which watersheds in the area match those climate, habitat, and anthropogenic variables currently. Finally, we determined which watersheds in the area are projected to have those climate, habitat, and anthropogenic variables in the future. Overall, we anticipate that invasive plant establishment will be geographically restricted in the current, near-term future, and long-term future.\u003C\/p\u003E\n\u003Cp\u003E\u003Ca href=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_CentralYukonInfestationVulnerability.jpg\u0022\u003E\u003Ccenter\u003E\u003Cimg alt=\u0022Non-native Plant Infestation Vulnerability in the Central Yukon Region\u0022 title=\u0022Non-native Plant Infestation Vulnerability in the Central Yukon Region\u0022 width=\u0022600\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_CentralYukonInfestationVulnerability.jpg\u0022 \/\u003E\u003C\/center\u003E\u003C\/a\u003E\u003C\/p\u003E\n","format":"zip","state":"Active","revision_timestamp":"Fri, 02\/01\/2019 - 11:35","name":"Non-native Plant Infestation Vulnerability in the Central Yukon Region","mimetype":"application\/zip","size":"6.7 MB","created":"Sun, 02\/25\/2018 - 13:17","resource_group_id":"","last_modified":"Date changed  Fri, 02\/01\/2019 - 11:35"},{"id":"03bf1ec5-9cfc-4f25-ab89-49b590d3e22c","revision_id":"","url":"https:\/\/accscatalog.uaa.alaska.edu\/sites\/default\/files\/REA_CentralYukon_FloatplaneLakes.zip","description":"\u003Cp\u003EFloatplanes are a potential vector for Elodea introductions and we therefore identified lakes \u2265 1 km in length along their longest axis as \u201clikely accessible\u201d by floatplane and those 0.5 to less than 1.0 km in length as \u201cpossibly accessible\u201d. This distance criterion was developed based on a review of lakes used for floatplane landings in the Kanuti National Wildlife Refuge. Other features such as lake depth or shape, presence of obstructions, high waves, lack of appropriate approach to shore, etc., may result in inaccessibility of lakes longer than 1 km; however, these features are not readily assessed with GIS or other datasets at hand. Additionally, this approach only considers a component of the likelihood of Elodea transport and does not encompass habitat suitability (e.g., lake depths less than 9 feet, pH from 6.0-7.5, etc.), or probability\/frequency of landings (e.g., lakes closer to urban centers, or those with greater recreational uses). Over 1,500 lakes and ponds are road accessible in the study area, with the majority located in the Fairbanks-North Pole area where Elodea is already known to occur. Elodea infestations in the state are primarily known from shallow lakes and ponds, indicating these waterbodies are particularly at risk. We identified 3,500 lakes in the region that are likely floatplane accessible, in which waterweed may be accidentally transported on float rudders. Smaller lakes with marginal accessibility to aircraft number nearly 11,000 in the study area.\u003C\/p\u003E\n\u003Cp\u003E\u003Ca href=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_CentralYukonFloatplaneLakes.jpg\u0022\u003E\u003Ccenter\u003E\u003Cimg alt=\u0022Floatplane accessible lakes susceptible to Elodea introduction\u0022 title=\u0022Floatplane accessible lakes susceptible to Elodea introduction\u0022 width=\u0022600\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Figure_CentralYukonFloatplaneLakes.jpg\u0022 \/\u003E\u003C\/center\u003E\u003C\/a\u003E\u003C\/p\u003E\n","format":"zip","state":"Active","revision_timestamp":"Fri, 02\/01\/2019 - 11:42","name":"Floatplane Accessible Lakes in Interior Alaska","mimetype":"application\/zip","size":"46.34 MB","created":"Fri, 02\/23\/2018 - 11:49","resource_group_id":"","last_modified":"Date changed  Fri, 02\/01\/2019 - 11:42"}],"tags":[{"id":"6ef07fb9-64c6-4a23-b121-466b54050771","vocabulary_id":"2","name":"Central Yukon"},{"id":"f00468ed-41f9-45e6-8566-2778195de86e","vocabulary_id":"2","name":"Rapid Ecoregional Assessments"}]}]}