Geology topics

Kent C. Jensen

Publications and source records attributed to Kent C. Jensen.

6 recordsLinked to original sources

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↗

USGS2016

Assessing spring direct mortality to avifauna from wind energy facilities in the Dakotas

T he Northern Great Plains (NGP) contains much of the remaining temperate grasslands, an ecosystem that is one of the most converted and least protected in the world. Within the NGP, the Prairie Pothole Region (PPR) provides important habitat for >50% of North America's breeding waterfowl and many species of shorebirds, waterbirds, and grassland songbirds. This region also has high wind energy potential, but the effects of wind energy developments on migratory and resident bird and bat populations in the NGP remains understudied. This is troubling considering >2,200 wind turbines are actively generating power in the region and numerous wind energy projects have been proposed for development in the future. Our objectives were to estimate avian and bat fatality rates for wind turbines situated in cropland- and grassland-dominated landscapes, document species at high risk to direct mortality, and assess the influence of habitat variables on waterfowl mortality at 2 wind farms in the NGP. From 10 March to 7 June 2013–2014, we completed 2,398 searches around turbines for carcasses at the Tatanka Wind Farm (TAWF) and the Edgeley-Kulm Wind Farm (EKWF) in South Dakota and North Dakota. During spring, we found 92 turbine-related mortalities comprising 33 species and documented a greater diversity of species ( n  = 30) killed at TAWF (predominately grassland) than at EKWF ( n  = 9; predominately agricultural fields). After accounting for detection rates, we estimated spring mortality of 1.86 (SE = 0.22) deaths/megawatt (MW) at TAWF and 2.55 (SE = 0.51) deaths/MW at EKWF. Waterfowl spring (Mar–Jun) fatality rates were 0.79 (SE = 0.11) and 0.91 (SE = 0.10) deaths/MW at TAWF and EKWF, respectively. Our results suggest that future wind facility siting decisions consider avoiding grassland habitats and locate turbines in pre-existing fragmented and converted habitat outside of high densities of breeding waterfowl and major migration corridors.

North Dakota, South Dakota↗

USGS2015

Evaluation of autonomous recording units for detecting 3 species of secretive marsh birds

Population status and habitat use of yellow rails ( Coturnicops noveboracensis ), Nelson's sparrows ( Ammodramus nelsoni ), and Le Conte's sparrows ( A. leconteii ) are poorly known, so standardized surveys of these species are needed to inform conservation planning and management. A protocol for monitoring secretive marsh birds exists; however, these species regularly call at night and may be missed during early morning surveys. We tested the effectiveness of autonomous recording units (hereafter, recording units) to survey these species by analyzing recorded vocalizations using bioacoustics software. We deployed 22 recording units at 54 sites in northern Minnesota and eastern North Dakota, USA, and conducted traditional broadcast surveys during May–June, 2010 and 2011. We compared detection probabilities between recording units and standard monitoring protocols using robust-design occupancy models. On average, recording units detected 0.59 (SE = 0.11) fewer Le Conte's sparrows, 0.76 (SE = 0.15) fewer Nelson's sparrows, and 1.01 (SE = 0.14) fewer yellow rails per survey than were detected using the standard protocol. Detection probabilities using the standard protocol averaged 0.95 (yellow rail; 95% CI = 0.86–0.98), 0.93 (Le Conte's sparrow; 95% CI = 0.78–0.98), and 0.89 (Nelson's sparrow; 95% CI = 0.56–0.98), but averaged 0.71 (yellow rail; 95% CI = 0.56–0.83), 0.61 (Le Conte's sparrow; 95% CI = 0.42–0.78), and 0.51 (Nelson's sparrow; 95% CI = 0.19–0.82) using recording units. Reduced detection by recording units was likely due to the ability of human listeners to identify birds calling at greater distances. Recording units may be effective for surveying nocturnal secretive marsh birds if investigators correct for differential detectability. Reduced detectability may be outweighed by the increased spatial and temporal coverage feasible with recording units.

Minnesota, North Dakota↗

USGS2015

Mate replacement and alloparental care in Ferruginous Hawk (Buteo regalis)

Alloparental care (i.e., care for unrelated offspring) has been documented in various avian species (Maxson 1978, Smith et al. 1996, Tella et al. 1997, Lislevand et al. 2001, Literak and Mraz 2011). A male replacement mate that encounters existing broods has options, which include alloparental care or infanticide. Infanticide may be beneficial in some species (Rohwer 1986, Kermott et al. 1990), but in long-lived avian species, like the ferruginous hawk (Buteo regalis) that do not renest within a season, infanticide might be detrimental. Adoption and rearing success likely provide direct evidence of competence of replacement mates as potential parents for future seasons, a benefit that might outweigh the investment of time and effort associated with adoption and rearing (after Rohwer 1986). Anticipated mating opportunity at the cost of adoption (Gori et al. 1996, Rohwer et al. 1999) may explain step-parental benevolence and therefore, in such a scenario would enhance individual fitness through subsequent recruitment of related young.

The Prairie Naturalist↗

USGS2012

Greater sage-grouse winter habitat use on the eastern edge of their range

Greater sage-grouse (Centrocercus urophasianus) at the western edge of the Dakotas occur in the transition zone between sagebrush and grassland communities. These mixed sagebrush (Artemisia sp.) and grasslands differ from those habitats that comprise the central portions of the sage-grouse range; yet, no information is available on winter habitat selection within this region of their distribution. We evaluated factors influencing greater sage-grouse winter habitat use in North Dakota during 2005–2006 and 2006–2007 and in South Dakota during 2006–2007 and 2007–2008. We captured and radio-marked 97 breeding-age females and 54 breeding-age males from 2005 to 2007 and quantified habitat selection for 98 of these birds that were alive during winter. We collected habitat measurements at 340 (177 ND, 163 SD) sage-grouse use sites and 680 random (340 each at 250 m and 500 m from locations) dependent sites. Use sites differed from random sites with greater percent sagebrush cover (14.75% use vs. 7.29% random; P < 0.001), percent total vegetation cover (36.76% use vs. 32.96% random; P ≤ 0.001), and sagebrush density (2.12 plants/m 2 use vs. 0.94 plants/m 2 random; P ≤ 0.001), but lesser percent grass cover (11.76% use vs. 16.01% random; P ≤ 0.001) and litter cover (4.34% use vs. 5.55% random; P = 0.001) and lower sagebrush height (20.02 cm use vs. 21.35 cm random; P = 0.13) and grass height (21.47 cm use vs. 23.21 cm random; P = 0.15). We used conditional logistic regression to estimate winter habitat selection by sage-grouse on continuous scales. The model sagebrush cover + sagebrush height + sagebrush cover × sagebrush height (w i = 0.60) was the most supported of the 13 models we considered, indicating that percent sagebrush cover strongly influenced selection. Logistic odds ratios indicated that the probability of selection by sage-grouse increased by 1.867 for every 1% increase in sagebrush cover (95% CI = 1.627–2.141) and by 1.041 for every 1 cm increase in sagebrush height (95% CI = 1.002–1.082). The interaction between percent sagebrush canopy cover and sagebrush height (β = −0.01, SE ≤ 0.01; odds ratio = 0.987 [95% CI = 0.983–0.992]) also was significant. Management could focus on avoiding additional loss of sagebrush habitat, identifying areas of critical winter habitat, and implementing management actions based on causal mechanisms (e.g., soil moisture, precipitation) that affect sagebrush community structure in this region.

Journal of Wildlife Management↗

USGS2011

Nesting success and resource selection of greater sage grouse in South Dakota: Chapter 8

Declines of Greater Sage-Grouse ( Centrocercus urophasianus ) in South Dakota are a concern because further population declines may lead to isolation from populations in Wyoming and Montana. Furthermore, little information exists about reproductive ecology and resource selection of sage grouse on the eastern edge of their distribution. We investigated Greater Sage-Grouse nesting success and resource selection in South Dakota during 2006-2007. Radiomarked females were tracked to estimate nesting rates, nest success, and habitat resources selected for nesting. Nest initiation was 98.0%, with a maximum likelihood estimate of nest success of 45.6 ± 5.3%. Females selected nest sites that had greater sagebrush canopy cover and visual obstruction of the nest bowl compared to random sites. Nest survival models indicated that taller grass surrounding nests increased nest survival. Tall grass may supplement the low sagebrush cover in this area in providing suitable nest sites for Greater Sage-Grouse. Land managers on the eastern edge of Greater Sage-Grouse range could focus on increasing sagebrush density while maintaining tall grass by developing range management practices that accomplish this goal. To achieve nest survival rates similar to other populations, predictions from our models suggest 26 cm grass height would result in approximately 50% nest survival. Optimal conditions could be accomplished by adjusting livestock grazing systems and stocking rates.

South Dakota↗