Geology topics

Jacob D. Hennig

Publications and source records attributed to Jacob D. Hennig.

7 recordsLinked to original sources

USGS2025

Estimating abundance of desert bighorn sheep with double-observer sightability modeling with residual heterogeneity

Accurate abundance estimates are critical for informed management of wildlife populations. In New Mexico, USA, minimum counts from aerial surveys are the primary basis for management decisions regarding desert bighorn sheep ( Ovis canadensis mexicana ); therefore, there is a need to assess methods that account for imperfect detection. Common survey methods for large mammals (i.e., sightability, double-observer, and double-observer sightability models) are known to result in biased estimates, but the presence of radio-collared individuals within a population allows for estimation of residual heterogeneity. Consequently, we explored the use of hybrid double-observer sightability approaches that account for residual heterogeneity when estimating abundance of desert bighorn sheep in the Fra Cristobal Mountains of New Mexico. We collected double-observer sightability data for 167 desert bighorn groups across 3 surveys between December 2016 and November 2017 and compared abundance estimates under 5 modeling methods: a standard sightability model (M S ), a standard double-observer sightability model (M DS ), a hybrid double-observer sightability model incorporating a recapture-type heterogeneity parameter (M R ), a hybrid double-observer sightability model incorporating a mark-type heterogeneity parameter (M H ), and a Lincoln-Petersen estimator. Across all model types, group behavior (moving vs. stationary) and group size influenced detection the most, followed by vegetation class, terrain type, and proportion of obscuring vegetation cover. Standard sightability models produced higher and less precise abundance estimates than all double-observer sightability models. Of the double-observer sightability models, M R was better supported and estimated greater abundance than M H and accounted for more bias than M DS . Both M R and M H yielded greater precision than M S . The M R models produced an average detection probability of p = 0.72 (SE = 0.02) and abundance estimates of N⌃ = 302 (95% CI = 262−385), N⌃ = 290 (95% CI = 261−340), and N⌃ = 352 (95% CI = 264−548) for the December 2016, May 2017, and November 2017 surveys, respectively. Lincoln-Petersen estimates of abundance were greater than all double-observer sightability models and similarly precise, but their usefulness is reduced given the requirement to permanently maintain a subset of animals with radio-collars combined with the inability to incorporate information from factors influencing detection probability. Further, because residual heterogeneity models better estimate visibility bias, are flexible in their accommodation of radio-collar data, and can be adapted to unique survey occasions, they present a viable and robust option for estimating desert bighorn sheep abundance.

New Mexico↗

USGS2024

Free-roaming horses exceeding appropriate management levels affect multiple vital rates in greater sage-grouse

Since the passage of the Wild Free-Roaming Horses and Burros Act of 1971, federal agencies have been responsible for managing free-roaming equids in the United States. Over the last 20 years, management has been hampered by direct opposition from advocacy groups, budget limitations, and a decline in the public’s willingness to adopt free-roaming horses ( Equus caballus ). As a result, free-roaming equid numbers have increased to more than 3 times the targeted goal of 26,785 (horses and burros [ E. asinus ] combined), the cumulative sum of the Appropriate Management Levels (AML) for all 177 designated Herd Management Areas (HMA) managed by the Bureau of Land Management. Recent research in the Great Basin has implicated these increases as one of the drivers of greater sage-grouse ( Centrocercus urophasianus ) population declines, due to habitat impacts exacerbated by ongoing drought conditions. To evaluate potential demographic mechanisms driving these declines, we compiled survival data from 4 studies in central Wyoming, USA, including 995 adult female (first year breeders or older) sage-grouse during the breeding season, 1,075 nests, 372 broods, and 136 juveniles (i.e., overwinter survival for fledged young), across a 15-year window (2008–2022). During this period, we also obtained population information for free-roaming horses from 9 HMAs used by individual grouse in our sample. Population estimates of free-roaming horses for these HMAs ranged from 59–700% of the maximum appropriate management level (AML max ). Sage-grouse monitored outside of HMAs represented control populations and, because we assumed they were not exposed to populations of free-roaming horses, values of AML max were set to zero for all grouse located outside of HMAs. To evaluate whether free-roaming horses were negatively impacting sage-grouse, we modeled daily survival of breeding age females, nest, broods, and juveniles. We found strong or moderate evidence that overabundant free-roaming horses negatively impacted nest, brood, and juvenile survival. When horse abundance increased to 300% from 100% of AML max , survival was reduced 8.1%, 18.3%, 18.2%, and 18.2% for nests, early broods (≤20 days after hatch), late broods (>20 days to 35 days after hatch), and juveniles, respectively. These results indicate increasing free-roaming horse numbers affected vital rates for critical life stages of sage-grouse, and that maintaining free-roaming horse numbers below AML max would minimize impacts to sage-grouse populations.

Wyoming↗

USGS2024

Effects of telemetry collars on two free-roaming feral equid species

There are two species of free-roaming feral equids in North America: horses ( Equus caballus ) and donkeys or “burros” ( E . asinus ). Both species were introduced as domestic animals to North America in the early 1500s and currently inhabit rangelands across the western United States, Canada, and all continents except Antarctica. Despite their global distribution, little is known about their fine scale spatial ecology. Contemporary research tools to assess space use include global positioning system (GPS) tracking collars, but older models were problematic due to stiff collar belting causing poor fit. We tested modern designs of GPS collars on n = 105 horses and n = 60 burros for 4 years in five populations (3 horse, 2 burro) across the western United States, to assess whether collars posed welfare risks to horses or burros. We found no difference in survival of collared versus uncollared mares and jennies, and no difference in survival of their foals. In 4036 of 4307 observations for horses (93.7%) and 2115 of 2258 observations for burros (93.6%), collars were observed symmetrical, maintaining proper fit on the neck. Fur effects from collars (sweaty neck, indented fur, broken fur) were seen in 3% of horse observations and 25% of burro observations. Superficial effects (chafes and marks on skin surface) were seen in 2% of horse observations and 11% of burro observations; no severe effects from collars were seen. Body condition was not affected by collars; mean body condition of collared horses was 4.70 ± 0.54 (mean ± s.d) and 4.71 ± 0.65 for collared burros. Behavior results indicated minimal effects; collared horses stood slightly more than uncollared, and collared burros stood and foraged more in one population, but not in the other. For 6.3% of observations of horses and 6.4% of observations of burros, we found an effect of time wearing a collar on the cumulative sum of fur effects which increased over time (burros: r s = 0.87, P = <0.0001; horses: r s = 0.31, P = 0.002). Burros also showed an increase over time in the number of superficial effects, but horses did not. Collars occasionally moved into the wrong position, shifting forward over the ears; we observed this on 19 horses and 1 burro. Of those, most collars went over the ears in summer ( n = 12). All collars were equipped with a remote release mechanism as well as a timed-release mechanism for redundancy, thus removed when observed in wrong position to avoid rubbing or discomfort. Our finding of no consequential physical effects in 98% of horse observations, and 89% of burro observations suggests the consequences of collars on free-roaming equid welfare and survival is biologically insignificant, although collars should be monitored regularly and continue to be equipped with a remote release mechanism to remove a collar if needed. With frequent welfare-driven, visual monitoring, collaring of free-roaming equids can be a safe and useful tool to increase our understanding of their spatial ecology, demography, habitat use, behavior, and interactions with other wildlife.

Arizona, Utah, Wyoming↗

USGS2023

Comparing methods to estimate feral burro abundance

Obtaining precise and unbiased estimates of feral burro ( Equus asinus ) abundance in the western United States is challenging due to their cryptic pelage and the rugged terrain they inhabit. Management agencies employ helicopter-based, simultaneous double-observer sightability surveys (hereafter denoted as DOS) to estimate abundance of burros; but the DOS method routinely produces negatively biased estimates due to residual heterogeneity in detection probability. Consequently, testing alternative methods to improve upon current procedures is warranted. Residual heterogeneity in DOS surveys can be minimized by including radio-collared individuals in the population. Alternatively, if distance measurements are recorded, residual heterogeneity can also be reduced via a mark-recapture distance sampling (MRDS) approach. Aerial infrared (IR) surveys offer a safer alternative than helicopter-based surveys because they can be flown at a higher altitude and require fewer observers in the aircraft. Further, IR surveys using a distance sampling approach have been shown to generate accurate and precise estimates of feral horse ( E. caballus ) populations. Accordingly, we compared results of surveys using aerial IR distance sampling, the standard DOS survey, a DOS survey incorporating detections of radio-collared individuals, and an MRDS analysis of a feral burro population with a known minimum population size in central Utah, winter 2015–2016 and spring 2016. The minimum number of burros known alive during the winter and spring surveys were 236 and 136, respectively. The average detection probability of IR surveys was P = 0.88 (SE = 0.16) and distance models produced estimates of 127 burros (95% CIs = 99–175) for the winter survey, and 94 burros (CIs = 72–134) for the spring survey. Mean detection probability of the standard DOS surveys was P = 0.78 (SE = 0.09), and model-generated abundance estimates were 155 burros (CIs = 133–227) in winter, and 92 burros (CIs = 79–139) in spring. Incorporating detections of radio-collared individuals in the DOS survey resulted in a decreased detection probability ( P = 0.46; SE = 0.06) and increased abundance estimates to 267 (CIs = 169–571) and 155 (CIs = 128–263) for winter and spring, respectively. Mark-recapture distance sampling produced a mean detection probability of P = 0.48 (SE = 0.12) and resulted in estimates of 282 (CIs = 178–385) and 169 (CIs = 73–310) burros in winter and spring, respectively. Our study demonstrated that aerial IR surveys conducted using standard distance sampling can produce precise estimates of burro population sizes; however, estimates were negatively biased relative to the known population size. Small sample size limits generalization of our results, but the IR-based distance approach did not improve upon DOS surveys. Accounting for residual heterogeneity through use of radio-collars and mark-recapture distance sampling eliminated the negative bias from the standard DOS survey but decreased survey precision. Managers will need to decide whether unbiased but less precise abundance estimates are preferable compared to a more precise, but biased, estimate.

Utah↗

USGS2021

Body size and digestive system shape resource selection by ungulates: A cross-taxa test of the forage maturation hypothesis

The forage maturation hypothesis (FMH) states that energy intake for ungulates is maximised when forage biomass is at intermediate levels. Nevertheless, metabolic allometry and different digestive systems suggest that resource selection should vary across ungulate species. By combining GPS relocations with remotely sensed data on forage characteristics and surface water, we quantified the effect of body size and digestive system in determining movements of 30 populations of hindgut fermenters (equids) and ruminants across biomes. Selection for intermediate forage biomass was negatively related to body size, regardless of digestive system. Selection for proximity to surface water was stronger for equids relative to ruminants, regardless of body size. To be more generalisable, we suggest that the FMH explicitly incorporate contingencies in body size and digestive system, with small-bodied ruminants selecting more strongly for potential energy intake, and hindgut fermenters selecting more strongly for surface water.

Ecology Letters↗

USGS2017

Science framework for conservation and restoration of the sagebrush biome: Linking the Department of the Interior’s Integrated Rangeland Fire Management Strategy to long-term strategic conservation actions, Part 1. Science basis and applications

The Science Framework is intended to link the Department of the Interior’s Integrated Rangeland Fire Management Strategy with long-term strategic conservation actions in the sagebrush biome. The Science Framework provides a multiscale approach for prioritizing areas for management and determining effective management strategies within the sagebrush biome. The emphasis is on sagebrush (Artemisia spp.) ecosystems and Greater sage-grouse (Centrocercus urophasianus). The approach provided in the Science Framework links sagebrush ecosystem resilience to disturbance and resistance to nonnative, invasive plant species to species habitat information based on the distribution and abundance of focal species. A geospatial process is presented that overlays information on ecosystem resilience and resistance, species habitats, and predominant threats and that can be used at the mid-scale to prioritize areas for management. A resilience and resistance habitat matrix is provided that can help decisionmakers evaluate risks and determine appropriate management strategies. Prioritized areas and management strategies can be refined by managers and stakeholders at the local scale based on higher resolution data and local knowledge. Decision tools are discussed for determining appropriate management actions for areas that are prioritized for management. Geospatial data, maps, and models are provided through the U.S. Geological Survey (USGS) ScienceBase and Bureau of Land Management (BLM) Landscape Approach Data Portal. The Science Framework is intended to be adaptive and will be updated as additional data become available on other values and species at risk. It is anticipated that the Science Framework will be widely used to: (1) inform emerging strategies to conserve sagebrush ecosystems, sagebrush dependent species, and human uses of the sagebrush system, and (2) assist managers in prioritizing and planning on-the-ground restoration and mitigation actions across the sagebrush biome.

California, Colorado, Idaho, Montana, Nevada, Oreg↗

USGS2016

Using resilience and resistance concepts to manage threats to sagebrush ecosystems, Gunnison sage-grouse, and Greater sage-grouse in their eastern range: A strategic multi-scale approach

This report provides a strategic approach developed by a Western Association of Fish and Wildlife Agencies interagency working group for conservation of sagebrush ecosystems, Greater sage-grouse, and Gunnison sage-grouse. It uses information on (1) factors that influence sagebrush ecosystem resilience to disturbance and resistance to nonnative invasive annual grasses and (2) distribution and relative abundance of sage-grouse populations to address persistent ecosystem threats, such as invasive annual grasses and wildfire, and land use and development threats, such as oil and gas development and cropland conversion, to develop effective management strategies. A sage-grouse habitat matrix links relative resilience and resistance of sagebrush ecosystems with modeled sage-grouse breeding habitat probabilities to help decisionmakers assess risks and determine appropriate management strategies at both landscape and site scales. Areas for targeted management are assessed by overlaying matrix components with Greater sage-grouse Priority Areas for Conservation and Gunnison sage-grouse critical habitat and linkages, breeding bird concentration areas, and specific habitat threats. Decision tools are discussed for determining the suitability of target areas for management and the most appropriate management actions. A similar approach was developed for the Great Basin that was incorporated into the Federal land use plan amendments and served as the basis of a Bureau of Land Management Fire and Invasives Assessment Tool, which was used to prioritize sage-grouse habitat for targeted management activities.

General Technical Report↗