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SGS-LTER Long-Term Monitoring Project: Spermophilus tridecemlineatus on Small Mammal Trapping Webs on the Central Plains Experimental Range, Nunn, Colorado, USA 1999 -2006, ARS Study Number 118
,This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/83456. Small mammals (rabbits, rodents) are integral components of semiarid ecosystems because of their roles as consumers of plants, seeds and arthropods, as soil disturbance agents, and as food for raptors, snakes and mammalian carnivores. Because of their vagility and intermediate trophic position, populations of small mammals may track changes in vegetation and the abiotic environment that may result from shifts in land-use and other anthropogenic disturbances. However, these populations are variable over space and time, and their response to environmental changes may not be immediately apparent given their behavioral flexibility and relatively long life-spans and generation times. Patterns in the distribution and abundance of small mammals thus may simultaneously reflect and affect the stability of the shortgrass-steppe ecosystem. Long-term studies of population and community dynamics therefore are needed to fully understand the role of small mammals in grassland ecosystems. Thirteen-lined ground squirrels (Spermophilus tridecemlineatus, SPTR) are the most widely distributed rodent species in shortgrass steppe and the most important in terms of abundance and biomass. Like most rodents in shortgrass steppe, they are omnivorous; unlike other species, however, they are diurnal and active aboveground only 5-6 months each year, and therefore required a separate sampling scheme from other rodents. In 1999, we initiated studies to track long-term changes in relative abundance of ground squirrels in representative habitats of shortgrass steppe. We live-trapped squirrels twice each year, which corresponded to periods of high aboveground activity of adults (early June, SPR) and the emergence of juveniles (mid-July, SUM). Three 3.14-ha webs were established in upland prairie (GRASS) and saltbush-dominated (SHRUB) habitats. Each web had 62 Sherman traps, which were spaced 20-m apart on 12 100-m spokes, with 30 degrees between spokes. Two traps were set in the center of the web. Traps were set for four consecutive mornings in each trapping session. Traps were baited with a mix of peanut butter and oats, set at dawn and closed 4-6 hours later. Traps were shaded with pieces of PVC pipe to reduce heat mortality in traps. We recorded sex, age and weight upon first capture of all individuals. Because the ears of squirrels are too small to consistently hold ear tags, all individuals were batch-marked with a colored Sharpie felt marker to distinguish recaptures ® from new (N) individuals, providing the minimum information necessary to use distance-sampling methods to estimate density. NOTE: In this dataset, ages and weights may not correspond well. Weight, combined with sampling date, can be used to better determine age class; contact Paul Stapp for more information.,,
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SGS-LTER Long-Term Monitoring Project: Vegetation Cover on Small Mammal Trapping Webs on the Central Plains Experimental Range, Nunn, Colorado, USA 1999 -2006, ARS Study Number 118
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,This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/83458. The abundance and diversity of small mammals in shortgrass steppe is strongly influenced by the structure and composition of vegetation. Vegetation structure provides cover from predators and harsh abiotic conditions. Plant species composition affects the types of seeds and herbaceous material available to granivores and herbivores, and influences arthropod populations, which are important prey for the omnivorous species that dominate in shortgrass steppe. Both vegetation structure and plant community composition are sensitive to the availability of precipitation as well as the activity of large mammalian herbivores. In 1999, we began measuring vegetation structure and plant community composition on the three grassland and three shrubland trapping webs where we live-trap small mammals. Vegetation measurements are made once each year, usually in mid-July. Percent canopy cover of each plant species was estimated visually in 30 0.10-m2 Daubenmire quadrats on each web. To estimate habitat structure, we measured the height of grass, forb and shrub plants adjacent to each quadrat, the density of half-shrubs, small mammal mounds and burrows, harvester ant mounds and the dimensions of large shrubs and animal mounds.,,
SGS-LTER Long-Term Monitoring Project: Vegetation Structure on Small Mammal Trapping Webs on the Central Plains Experimental Range, Nunn, Colorado, USA 1999 -2006, ARS Study Number 118
공공데이터포털
,This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/83458. The abundance and diversity of small mammals in shortgrass steppe is strongly influenced by the structure and composition of vegetation. Vegetation structure provides cover from predators and harsh abiotic conditions. Plant species composition affects the types of seeds and herbaceous material available to granivores and herbivores, and influences arthropod populations, which are important prey for the omnivorous species that dominate in shortgrass steppe. Both vegetation structure and plant community composition are sensitive to the availability of precipitation as well as the activity of large mammalian herbivores. In 1999, we began measuring vegetation structure and plant community composition on the three grassland and three shrubland trapping webs where we live-trap small mammals. Vegetation measurements are made once each year, usually in mid-July. Percent canopy cover of each plant species was estimated visually in 30 0.10-m2 Daubenmire quadrats on each web. To estimate habitat structure, we measured the height of grass, forb and shrub plants adjacent to each quadrat, the density of half-shrubs, small mammal mounds and burrows, harvester ant mounds and the dimensions of large shrubs and animal mounds.,,
SGS-LTER Long-Term Monitoring Project: Body weights of rodents captured during SGS-LTER live-trapping on the Central Plains Experimental Range, Nunn, Colorado, USA 1994 -2011, ARS Study Number 118
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,This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/83452. Body size is a fundamental biological measurement that is known to be related to an organism's physiology, life-history and ecology. Estimates of body size are also widely used in comparative evolutionary and ecological studies, including food web and diet studies that require estimates of biomass. Beginning in 1994, small mammals are live-trapped twice each year on the three grassland and three shrubland trapping webs. Individuals are weighed (to nearest 0.5 g using a Pesola spring scale) when first captured during a given trapping session but not upon recapture during the same session. Weights are calculated by subtracting the weight of an empty capture (ziploc) bag from the weight of animal in the bag. Individuals are classified into age classes (adult, subadult, juvenile) in the field based on a combination of size and pelage characteristics. This dataset gives means, standard deviations, minimum and maximum values for body weight, in grams, of small mammals captured between September 1994 and September 2008. All sites and sampling periods were combined. Most individuals (~93%) were classified as new captures, although a few individuals that were captured multiple times across different trapping sessions may appear in the dataset more than once. Values may differ from estimates calculated using the entire capture dataset because age and weight data were screened more closely to omit obvious errors and outliers.,,
GPS locations of feral horses in Utah, USA, from 2016-2020
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Data represent locations of mares and stallions in Utah. Data were collected using GPS radio collars on mares or tail transmitters braided into the tails of stallions, at a 2-hour fix rate for a period spanning 2016 to 2020. Horses were located at Conger Herd Management Area (HMA) or Frisco HMA in the Great Basin ecosystem of Utah, USA.
GPS locations of feral horses in Utah, USA, from 2016-2020
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Data represent locations of mares and stallions in Utah. Data were collected using GPS radio collars on mares or tail transmitters braided into the tails of stallions, at a 2-hour fix rate for a period spanning 2016 to 2020. Horses were located at Conger Herd Management Area (HMA) or Frisco HMA in the Great Basin ecosystem of Utah, USA.
Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Nevada and Wyoming, Interim
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the Greater sage-grouse range, 3) be used to track the outcomes of local and regional populations by comparing population changes across scales, and 4) be used to inform where to best spatially target studies that identify the processes and mechanisms causing population trends to change among spatial scales. The spatial variability in the amount and quality of habitat resources can affect local population success and result in different population growth rates among smaller clusters. Equally so, the spatial structure and ecological organization driving scale-dependent systems in a fragmented landscape affects dispersal behavior, suggesting inclusion in population monitoring frameworks. Studies that compare conditions among spatially explicit hierarchical clusters may elucidate the cause of differing growth rates, indicating the appropriate location and spatial scale of a management action. The data presented here reflect the results from developing a hierarchical monitoring framework and then applying these methods to Greater Sage-grouse in Nevada and Wyoming, US. When using these data for evaluating population changes or when identifying a spatially balanced sampling protocol, all cluster levels are designed to work together and therefore we recommend evaluating multiple cluster levels prior to selecting a single cluster level, if a single scale is desired, when analyzing population growth rates or other analyses, as these data are intended for multi-scale efforts. In other words, let your data decide which scale(s) are appropriate for the given species. These cluster levels are specific to Greater Sage-grouse but they may be appropriate for other sagebrush obligate species, but the user will need to make this determination. The products from this study aim to support multiple research and management needs. However, these data represent an interim data product because there may be errors associated with clusters along the edges of the state boundaries (due to the lack of lek data in neighboring states). We are planning to release new data that we will develop for the Greater sage-grouse range. We recommend using the new data products once available instead of these data products. These data will remain online as they are associated with the following citation, which provides a detailed explanation of the methods used to develop these data: O’Donnell, Michael S., David R. Edmunds, Cameron L. Aldridge, Julie A. Heinrichs, Peter S. Coates, Brian G. Prochazka, and Steve E. Hanser. 2018. Designing hierarchically nested and biologically relevant monitoring frameworks to study populations across scales. Ecosphere
Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Nevada and Wyoming, Interim
공공데이터포털
We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the Greater sage-grouse range, 3) be used to track the outcomes of local and regional populations by comparing population changes across scales, and 4) be used to inform where to best spatially target studies that identify the processes and mechanisms causing population trends to change among spatial scales. The spatial variability in the amount and quality of habitat resources can affect local population success and result in different population growth rates among smaller clusters. Equally so, the spatial structure and ecological organization driving scale-dependent systems in a fragmented landscape affects dispersal behavior, suggesting inclusion in population monitoring frameworks. Studies that compare conditions among spatially explicit hierarchical clusters may elucidate the cause of differing growth rates, indicating the appropriate location and spatial scale of a management action. The data presented here reflect the results from developing a hierarchical monitoring framework and then applying these methods to Greater Sage-grouse in Nevada and Wyoming, US. When using these data for evaluating population changes or when identifying a spatially balanced sampling protocol, all cluster levels are designed to work together and therefore we recommend evaluating multiple cluster levels prior to selecting a single cluster level, if a single scale is desired, when analyzing population growth rates or other analyses, as these data are intended for multi-scale efforts. In other words, let your data decide which scale(s) are appropriate for the given species. These cluster levels are specific to Greater Sage-grouse but they may be appropriate for other sagebrush obligate species, but the user will need to make this determination. The products from this study aim to support multiple research and management needs. However, these data represent an interim data product because there may be errors associated with clusters along the edges of the state boundaries (due to the lack of lek data in neighboring states). We are planning to release new data that we will develop for the Greater sage-grouse range. We recommend using the new data products once available instead of these data products. These data will remain online as they are associated with the following citation, which provides a detailed explanation of the methods used to develop these data: O’Donnell, Michael S., David R. Edmunds, Cameron L. Aldridge, Julie A. Heinrichs, Peter S. Coates, Brian G. Prochazka, and Steve E. Hanser. 2018. Designing hierarchically nested and biologically relevant monitoring frameworks to study populations across scales. Ecosphere
Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Nevada and Wyoming, Interim
공공데이터포털
We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the Greater sage-grouse range, 3) be used to track the outcomes of local and regional populations by comparing population changes across scales, and 4) be used to inform where to best spatially target studies that identify the processes and mechanisms causing population trends to change among spatial scales. The spatial variability in the amount and quality of habitat resources can affect local population success and result in different population growth rates among smaller clusters. Equally so, the spatial structure and ecological organization driving scale-dependent systems in a fragmented landscape affects dispersal behavior, suggesting inclusion in population monitoring frameworks. Studies that compare conditions among spatially explicit hierarchical clusters may elucidate the cause of differing growth rates, indicating the appropriate location and spatial scale of a management action. The data presented here reflect the results from developing a hierarchical monitoring framework and then applying these methods to Greater Sage-grouse in Nevada and Wyoming, US. When using these data for evaluating population changes or when identifying a spatially balanced sampling protocol, all cluster levels are designed to work together and therefore we recommend evaluating multiple cluster levels prior to selecting a single cluster level, if a single scale is desired, when analyzing population growth rates or other analyses, as these data are intended for multi-scale efforts. In other words, let your data decide which scale(s) are appropriate for the given species. These cluster levels are specific to Greater Sage-grouse but they may be appropriate for other sagebrush obligate species, but the user will need to make this determination. The products from this study aim to support multiple research and management needs. However, these data represent an interim data product because there may be errors associated with clusters along the edges of the state boundaries (due to the lack of lek data in neighboring states). We are planning to release new data that we will develop for the Greater sage-grouse range. We recommend using the new data products once available instead of these data products. These data will remain online as they are associated with the following citation, which provides a detailed explanation of the methods used to develop these data: O’Donnell, Michael S., David R. Edmunds, Cameron L. Aldridge, Julie A. Heinrichs, Peter S. Coates, Brian G. Prochazka, and Steve E. Hanser. 2018. Designing hierarchically nested and biologically relevant monitoring frameworks to study populations across scales. Ecosphere