Filters: Tags: moose (X) > Date Range: {"choice":"year"} (X)
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This volume's release consists of 64642 media files captured by autonomous wildlife monitoring devices under the project, Maine Department of Inland Fisheries and Wildlife. The attached files listed below include several CSV files that provide information about the data release. The file, "media.csv" provides the metadata about the media, such as filename and date/time of capture. The actual media files are housed within folders under the volume's "child items" as compressed files. A critical CSV file is "dictionary.csv", which describes each CSV file, including field names, data types, descriptions, and the relationship of each field to fields other CSV files. Some of the media files may have been "tagged" or "annotated"...
Categories: Data,
Data Release - In Progress;
Tags: AMBER,
AMMonitor,
American marten,
American mink,
Canada lynx,
There have been increasing concerns regarding the decline in moose numbers along the southern range of their North American distribution. This has prompted varied research efforts to determine the factors contributing to the reduced local populations. Although heat stress from increasing temperatures could be a potential factor for declining populations in Minnesota, temperature increases have also occurred in New York, Massachusetts, and Connecticut where populations have been expanding in recent years. Alternatively, indirect climate effects from warmer temperatures may be playing a role, such as increased prevalence of parasites (e.g., brainworm, winter tick) to levels lethal to moose. Additionally, factors such...
Categories: Project;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: 2016,
CASC,
Genomics,
Health,
Mammals,
Scenario planning, while not a new process, is relatively new to applications in conservation and natural resource management. Not surprisingly, managers want to learn about scenario planning to help them understand whether incorporating it into their current planning processes will provide desired outcomes and is the best use of their time. This newsletter summarizes the recently attended Northeast Moose Group Meeting as well as a session on scenario planning at the Northeast Association of Fish and Wildlife Agencies (NEAFWA) annual meeting highlighting ongoing efforts in the region. The aim in broadening our engagement is to share information, exchange ideas, and build from others’ endeavors with relevance to...
Scenario planning is one decision support method that can help natural resource managers incorporate information about uncertain future changes in climate into management decisions. To provide a proof of concept of the value of scenario planning in helping managers prepare for climate change, we conducted a pilot scenario planning effort aimed at helping state agencies in the northeastern United States develop climate-informed moose management goals and actions. To encourage participation by wildlife managers, we provided several opportunities for them to learn about scenario planning and examples of its application in natural resource management. We shared this information via guidance documents on incorporating...
Northeastern boreal forests are an important habitat for many wildlife species, including migratory birds and moose. These animals play vital roles in the boreal forest ecosystem, are a source of pleasure for bird and wildlife watchers, and contribute to tourism revenue for many communities. However, moose and migratory birds are thought to be particularly vulnerable to the impacts of climate change. For example, in New York’s Adirondack State Park, six species of boreal birds have shown population declines over the past ten years. Meanwhile, moose in many parts of the northeast are threatened by winter ticks that thrive in warmer climates and spread disease. Building upon earlier work related to climate impacts...
Categories: Publication;
Types: Citation;
Tags: Birds,
Forests,
Landscapes,
National CASC,
Northern Boreal Forest,
Maine Department of Inland Fisheries and Wildlife is a project within the AMMonitor community, which features projects that monitor wildlife and ecosystems with remotely deployed monitoring devices. Devices that capture media typically include trail cameras (photos, video) and/or autonomous recording units (audio). As with all AMMonitor projects, Maine Department of Inland Fisheries and Wildlife utilizes an AMMonitor SQLite database to track wildlife monitoring data in a standardized format, permitting cross-project collaboration. The monitoring data are released to the public in "volumes". Releases include the raw media files and their metadata, including the date, time, and location of media capture. Additional...
This volume's release consists of 26 media files captured by autonomous wildlife monitoring devices under the project, MiddleEarth Wildlife Study. The attached files listed below include several CSV files that provide information about the data release. The file, "media.csv" provides the metadata about the media, such as filename and date/time of capture. The actual media files are housed within folders under the volume's "child items" as compressed files. A critical CSV file is "dictionary.csv", which describes each CSV file, including field names, data types, descriptions, and the relationship of each field to fields other CSV files. Some of the media files may have been "tagged" or "annotated" by either humans...
Data represent the metrics measured to validate the novel technique for isolating DNA from the supernatant of an RNA isolation protocol using blood collected into Tempus blood RNA tubes.
Hair samples were collected in discrete areas during radio-collar studies in Vermont under the auspices of University of Vermont IACUC protocol #17-035 (n=106), New Hampshire (n=34), and Maine (n=57). Hair and tissue samples were opportunistically collected from animals that were harvested, died in vehicle collisions, or translocated throughout Vermont (n = 105), Quebec (n = 198), Massachusetts (n = 5), and New York (n = 24). Of the 317 previously identified autosomal moose SNPs, 136 loci were utilized to develop a MALDI-TOF MS genotyping assay. After filtering problematic loci and individuals, genotypes from 112 of 136 SNPs (82%) were obtained for 507 individuals and all loci met Hardy-Weinberg expectations in...
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