USGS Science⌕ Search

Geology topics

Lora B. Perkins

Publications and source records attributed to Lora B. Perkins.

5 recordsLinked to original sources
USGS2024

Genetic analysis of harvest samples reveals population structure in a highly mobile generalist carnivore

Delineating wildlife population boundaries is important for effective population monitoring and management. The bobcat ( Lynx rufus ) is a highly mobile generalist carnivore that is ecologically and economically important. We sampled 1225 bobcats harvested in South Dakota, USA (2014–2019), of which 878 were retained to assess genetic diversity and infer population genetic structure using 17 microsatellite loci. We assigned individuals to genetic clusters ( K ) using spatial and nonspatial Bayesian clustering algorithms and quantified differentiation ( F ST and GST″ ) among clusters. We found support for population genetic structure at K = 2 and K = 4, with pairwise F ST and GST″ values indicating weak to moderate differentiation, respectively, among clusters. For K = 2, eastern and western clusters aligned closely with historical bobcat management units and were consistent with a longitudinal suture zone for bobcats previously identified in the Great Plains. We did not observe patterns of population genetic structure aligning with major rivers or highways. Genetic divergence observed at K = 4 aligned roughly with ecoregion breaks and may be associated with environmental gradients, but additional sampling with more precise locational data may be necessary to validate these patterns. Our findings reveal that cryptic population structure may occur in highly mobile and broadly distributed generalist carnivores, highlighting the importance of considering population structure when establishing population monitoring programs or harvest regulations. Our study further demonstrates that for elusive furbearers, harvest can provide an efficient, broad-scale sampling approach for genetic population assessments.

South Dakota↗
USGS2022

The effect of scent lures on detection is not equitable among sympatric species

Context: Camera trapping is an effective tool for cost-efficient monitoring of species over large temporal and spatial scales and it is becoming an increasingly popular method for investigating wildlife communities and trophic interactions. However, camera trapping targeting rare and elusive species can be hampered by low detection rates, which can decrease the accuracy and precision of results from common analytical approaches (e.g., occupancy modeling, capture-recapture). Consequently, researchers often employ attractants to increase detection without accounting for how attractants influence detection of species among trophic levels. Aims: We aimed to evaluate the influences of a commonly used non-species-specific olfactory lure (i.e. sardines) and sampling design on detection of four species (i.e. bobcat [ Lynx rufus ], coyote [ Canis latrans ], raccoon [ Procyon lotor ], and eastern cottontail [ Sylvilagus floridanus ]) that represented a range of foraging guilds in an agricultural landscape. Methods: We set 180 camera stations, each for ∼28 days, during the summer of 2019. We set cameras with one of three lure treatments: (1) olfactory lure, (2) no olfactory lure, or (3) olfactory lure only during the latter half of the survey. We evaluated the influence of the lure at three temporal scales of detection (i.e. daily probability of detection, independent sequences per daily detection, and triggers per independent sequence). Key results: The lure tended to positively influence detection of coyotes and raccoons but negatively influenced detection of bobcats and eastern cottontails. The influence of the lure varied among temporal scales of detection. Conclusions: Scent lures can differentially influence detection of species within or among tropic levels, and the influence of a scent lure may vary among temporal scales. Implications: Our results demonstrate the importance of evaluating the influence of an attractant for each focal species when using camera data to conduct multi-species or community analyses, accounting for variation in sampling strategies across cameras, and identifying the appropriate species-specific temporal resolution for assessing variation in detection data. Furthermore, we highlight that care should be taken when using camera data as an index of relative abundance (e.g. as is commonly done with prey species) when there is variation in the use of lures across cameras.

Wildlife Research↗
USGS2020

Managing invasive plants on Great Plains grasslands: A discussion of current challenges

The Great Plains of North America encompass approximately 1,300,000 km 2 of land from Texas to Saskatchewan. The integrity of these lands is under continual assault by long-established and newly-arrived invasive plant species, which can threaten native species and diminish land values and ecological goods and services by degrading desired grassland resources. The Great Plains are a mixture of privately and publicly owned lands, which leads to a patchwork of varying management goals and strategies for controlling invasive plants. Continually updated knowledge is required for efficient and effective management of threats posed by changing environments and invasive plants. Here we discuss current challenges, contemporary management strategies, and management tools and their integration, in hopes of presenting a knowledge resource for new and experienced land managers and others involved in making decisions regarding invasive plant management in the Great Plains.

Great Plains↗
USGS2020

Vegetation sampling and management

What is the utility of vegetation measurements for wildlife managers? In the prairie, savanna, tundra, forest, steppe, and wetland regions of the world, mixtures of plant species provide wildlife with food, cover and, in some circumstances, water; the 3 essential habitat elements necessary to sustain viable wildlife populations. We define habitat in reference to use of a vegetation type by an animal (e.g., deer habitat) and vegetation type when referring to differences in vegetation stands (e.g., marsh vegetation type versus tall grass prairie vegetation type; Hall et al. 1997). In strict definition, the variety of wildlife using plants ranges from snails and voles (Microtus spp.) to bison (Bison bison) and elephants (Loxodonta spp.) in uplands and from mosquitoes and ducks to muskrats (Ondatra zibethicus) and manatees (Trichechus manatus) in wetlands. Through evolutionary processes, some wildlife species are totally dependent on vegetation for all annual life requirements, whereas other species use vegetation only for cover or food. Regardless of the role of vegetation in the sustenance of wildlife, any management or research project that requires evaluation of wildlife and vegetation type relationships on a unit of land will necessitate some form of vegetation measurement. The term vegetation can refer to a single plant or species on a specific site or a community in the landscape. Vegetation may occur naturally or be introduced, and may be live or dead. Uses of vegetation measurements are many: (1) evaluation of vegetation response to management practices, (2) estimation of carrying capacity and/or forage production, (3) characterization of cover and habitat components for an endangered species, or (4) long-term monitoring of the general trend of plant vigor or vegetation type condition. Surveying and measuring quantity and quality of vegetation within habitats are basic to wildlife research and management. Grassland, shrubland, and woodland vegetation types are comprised of populations in which individual plants are usually too numerous to inventory completely. Consequently, wildlife biologists usually use sampling techniques to make inferences about the total plant population within a given vegetation type. Vegetation sampling methodologies have evolved within several ecological disciplines (e.g., plant ecology, forestry, rangeland science) and for a variety of management or research objectives (e.g., estimating forage for ungulates, describing habitat use by passerine birds). Description of every method that has been used to sample vegetation is beyond the scope of this chapter. We describe how to measure vegetation structure, which Dansereau (1957) defined as the spatial organization (distribution) of individuals that form a stand. We have organized this chapter into a description of basic methods of vegetation sampling with examples of how those methods have been applied or modified in wildlife research and management. We assume the investigator/reader has adequate knowledge of the concepts of wildlife ecology, primary habitat requirements of wildlife species under study, and ability to systematically identify the species of wildlife and vascular plants within the geographical area of investigation.

Book chapter↗