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Geology topics

Jeremy M. Nicholson

Publications and source records attributed to Jeremy M. Nicholson.

5 recordsLinked to original sources

Detecting occurrence and timing of grizzly bear parturition based on anomalies in accelerometer data

Documenting natality of brown (grizzly) bears ( Ursus arctos ) is an important component of many population monitoring and research programs. Brown bears give birth during hibernation, so observation of litters is generally not feasible until females exit dens, and detection of litters can be compromised by poor observability. Using triaxial accelerometer activity data stored on radiocollars, we developed a technique that predicts births by the presence of brief upsurges in activity likely associated with postnatal maternal behaviors. We developed presence criteria with a training sample of known parturient females ( n = 22) to detect anomalies within time-series of daily motion-counts (i.e., activity readings >0 measured at 10-min intervals) during 25 December–7 March. To test performance, we applied criteria to a blinded sample of activity data obtained from female grizzly bears (captured and collared during 2012–2022) in 4 populations in interior North America ( n = 295). We assigned predicted status and compared assignments to reproductive status at first visual observation. The true positive rate was 91% ( n = 47 females observed with cubs of the year) and the false-positive rate was 17% ( n = 65 females observed with older offspring). Births were predicted for 50% of females with unknown reproductive status ( n = 48), 21% of females observed without offspring ( n = 114), and 10% of subadult females considered too young to reproduce ( n = 21). Dates of predicted births varied from 27 December to 28 February. Our anomaly detection technique was successful at estimating parturition events, and despite some error, indicated that a number of litters were born but not observed, presumably due to mortality in or shortly after den emergence. This technique provides an additional tool for supplementing visual observations for natality estimation and population modeling, provided that potential biases stemming from increased detection rates are considered.

Alaska, British Columbia, Idaho, Montana

Evidence for density-dependent effects on body composition of a large omnivore in a changing Greater Yellowstone Ecosystem

Understanding the density-dependent processes that drive population demography in a changing world is critical in ecology, yet measuring performance–density relationships in long-lived mammalian species demands long-term data, limiting scientists' ability to observe such mechanisms. We tested performance–density relationships for an opportunistic omnivore, grizzly bears ( Ursus arctos , Linnaeus, 1758) in the Greater Yellowstone Ecosystem, with estimates of body composition (lean body mass and percent body fat) serving as indicators of individual performance over two decades (2000–2020) during which time pronounced environmental changes have occurred. Several high-calorie foods for grizzly bears have mostly declined in recent decades (e.g., whitebark pine [ Pinus albicaulis , Engelm, 1863]), while increasing human impacts from recreation, development, and long-term shifts in temperatures and precipitation are altering the ecosystem. We hypothesized that individual lean body mass declines as population density increases (H1), and that this effect would be more pronounced among growing individuals (H2). We also hypothesized that omnivory helps grizzly bears buffer energy intake from changing foods, with body fat levels being independent from population density and environmental changes (H3). Our analyses showed that individual lean body mass was negatively related to population density, particularly among growing-age females, supporting H1 and partially H2. In contrast, population density or sex had little effect on body fat levels and rate of accumulation, indicating that sufficient food resources were available on the landscape to accommodate successful use of shifting food sources, supporting H3. Our results offer important insights into ecological feedback mechanisms driving individual performances within a population undergoing demographic and ecosystem-level changes. However, synergistic effects of continued climate change and increased human impacts could lead to more extreme changes in food availability and affect observed population resilience mechanisms. Our findings underscore the importance of long-term studies in protected areas when investigating complex ecological relationships in an increasingly anthropogenic world.

Idaho, Montana, Wyoming

Enhancements to population monitoring of Yellowstone grizzly bears

In the Greater Yellowstone Ecosystem, counts of female grizzly bears ( Ursus arctos ) with cubs-of-the-year (females with cubs) from systematic aerial surveys and opportunistic ground sightings are combined with demographic data to derive annual population estimates. We addressed 2 limitations to the monitoring approach. As part of a rule set, a conservative distance of > 30 km currently is used as a threshold to assign sightings to unique females with cubs, resulting in underestimation bias. Using telemetry locations of females with cubs collected during 1997–2019, we created 1,000 data sets for each of 5 levels of simulated number of females with cubs, simulated sightings by selecting among these locations, and evaluated the classification performance of alternative distance criteria (12–30 km). Under all scenarios, 12–16-km criteria maximized classification performance and minimized estimation bias; the 16-km criterion was optimal for current conditions and sampling efforts. Our second objective was to test generalized additive models (GAMs) as a flexible trend analysis technique. We simulated 1,000 time series for each of 10 scenarios (10, 15, and 20% decline over periods of 5, 10, and 15 yrs, plus stability), applied GAMs, and assessed metrics associated with the posterior distribution of the instantaneous rate of change. We detected declines among > 99.6% of replicates under the 15 and 20% decline scenarios and in 84.7–94.7% of replicates under the 10% decline scenario. From decline onset to first detection, periods ranged from 3.7 (20% decline over 5 yrs) to 11.1 (10% decline over 15 yrs), with 3.9–8.8 years mean duration of detection events. The GAM approach allows detection of directional changes in population trend, including early warning metrics, and stabilization after such changes. Retrospective application of the 16-km distance criterion and GAMs resulted in higher population estimates and growth rates than are reported using current methods.

Wyoming

A reassessment of Chao2 estimates for population monitoring of grizzly bears in the Greater Yellowstone Ecosystem

The Yellowstone Ecosystem Subcommittee (YES) asked the Interagency Grizzly Bear Study Team (IGBST) to re-assess a technique used in annual population estimation and trend monitoring of grizzly bears in the Greater Yellowstone Ecosystem (GYE). This technique is referred to as the Chao2 approach and estimates the number of females with cubs-of-the-year (hereafter, females with cubs) and, in association with other demographic data, is used by the IGBST to produce annual population estimates. Females with cubs are an easily recognizable population segment, and trends for this reproductive segment of the population are assumed to be representative of trend for the entire population. The overarching objective of the analyses presented in this report was to provide a more accurate representation of the GYE grizzly bear population using the current methodologies in place. Specifically, we addressed two limitations of the current Chao2 approach: 1) underestimation bias associated with a distance criterion used to differentiate annual sightings of females with cubs into unique individuals and 2) limitations of the model-averaging approach to effectively distinguish among potential future population trajectories (decline, stability, and growth). The first issue addressed in this report is the underestimation bias associated with the rule set that Knight et al. (1995) developed to differentiate sightings of females with cubs into unique individuals (i.e., unique family groups). The rule set was originally designed to be conservative by reducing the risk of identifying more females with cubs than actually existed, primarily through use of a distance criterion of 30 km to separate sightings of unique females. This approach resulted in an underestimation bias, and previous research demonstrated that this bias increases with increasing number of females with cubs. Using location data from radio-marked females with cubs, we evaluated alternative distance criteria by simulating scenarios with varying numbers of true females with cubs and sightings. Findings from these analyses demonstrate that bias in estimates of females with cubs can be substantially reduced by changing the 30-km distance criterion in the rule set to 16 km, which produced relatively unbiased estimates. Findings also indicate, however, the importance of adaptability with regard to the distance criteria because of the complex relationships and biases among the various parameters involved in estimation of unique females with cubs. The total number of annual sightings and the true number of females with cubs play particularly important roles. Whereas these analyses remind us that there is no perfect approach to estimating the number of females with cubs from sightings under various scenarios, they provide us with new tools to determine when and how to adapt the monitoring program. The second issue we were tasked to investigate was the potential for improvement of the technique referred to as model-averaging, which serves to smooth relatively high variation in annual estimates. This technique was chosen by YES as the basis for monitoring the Yellowstone grizzly bear population, as described in the 2016 Conservation Strategy. This choice was made in part because the technique has been well documented and population estimates derived from counts of females with cubs are conservative. Using simulations of population trends, we demonstrate why the model-averaging technique currently used cannot distinguish between plausible future trend scenarios. As a suitable alternative to model averaging, we propose the use of generalized additive models (GAMs). Using a suite of simulated trend dynamics relevant to management, we demonstrate GAM performance for tracking trends in females with cubs within the context of the annual monitoring program. We demonstrate the ability to not only document directional changes in population trend but also patterns of stabilization or resiliency after such changes. Furthermore, the proposed monitoring framework provides objective measures useful for early detection of directional changes in trend. The new framework is flexible, allowing retrospective analysis of Chao2-based estimates and future applications to time series of other population metrics, such as vital rates. The aforementioned updates provide us with new tools to determine when and how to adapt the monitoring program. Within the context of current monitoring protocols and effort, and considering the full suite of simulations presented in this report and previous studies, the IGBST plans to incorporate the following changes to the population monitoring protocol: 1) modify the distance criterion, starting with 16 km under current sampling conditions and 2) revise the population monitoring framework using GAMs as the basis for smoothing of annual estimates and detecting trends and changes in trend. Implementation of the 16-km distance criterion combined with use of GAM techniques would affect some of the population metrics (e.g., annual population size and uncertainty, population trend, mortality rates) used to inform management responses. A primary consideration is that the 16-km distance criterion results in total population estimates derived from the Chao2 estimates that are greater than those we have reported in the past. This increase is due to a change in the implementation of the technique and more accurately represents the number of females with cubs in the GYE grizzly bear population. Additionally, interpretation of retrospective trend patterns may change due to the combination of a different distance criterion and enhanced trend monitoring based on the GAM approach we present here. Implementation will require relatively minor changes in the monitoring protocols described in Appendices B and C of the 2016 Conservation Strategy. Finally, we note that the IGBST has ongoing investigations into the merits of an Integrated Population Model (IPM), for which annual Chao2-based estimates are important input data. The IGBST plans to continue those investigations using the 16-km distance criterion to derive Chao2 estimates.

Idaho, Montana, Wyoming

Short-term impacts of a 4-lane highway on black bears in eastern North Carolina

Among numerous anthropogenic impacts on terrestrial landscapes, expanding transportation networks represent one of the primary challenges to wildlife conservation worldwide. Larger mammals may be particularly vulnerable because of typically low densities, low reproductive rates, and extensive movements. Although numerous studies have been conducted to document impacts of road networks on wildlife, inference has been limited because of experimental design limitations. During the last decade, the North Carolina Department of Transportation (NCDOT) rerouted and upgraded sections of United States Highway 64 between Raleigh and the Outer Banks to a 4-lane, divided highway. A new route was selected for a 24.1-km section in Washington County. The new section of highway included 3 wildlife underpasses with adjacent wildlife fencing to mitigate the effects of the highway on wildlife, particularly American black bears (Ursus americanus). We assessed the short-term impacts of the new highway on spatial ecology, population size, survival, occupancy, and gene flow of black bears. We tested our research hypotheses using a before-after control-impact (BACI) study design. We collected data during 2000–2001 (preconstruction phase) and 2006–2007 (postconstruction phase) in the highway project area and a nearby control area (each approx. 11,000 ha), resulting in 4 groups of data (i.e., pre- or postconstruction study phase, treatment or control area). We captured and radiocollared 57 bears and collected 5,775 hourly locations and 4,998 daily locations. Using mixed-model analysis of variance and logistic regression, we detected no differences in home ranges, movement characteristics, proximity to the highway alignment, or habitat use between the 2 study phases, although minimum detectable effect sizes were large for several tests. However, after completion of the new highway, bears on the treatment area became less inactive in morning, when highway traffic was low, compared with bears on the control area (F 1, 43 = 6.05, P = 0.018). We used DNA from hair samples to determine if population size and site occupancy decreased following highway construction. For each study phase, we collected black bear hair from 70 hair snares on each study area during 7 weekly sampling periods and generated genotypes using 10 microsatellite loci. We used the multilocus genotypes to obtain capture histories for 226 different bears and used capture-mark-recapture models to estimate population size. Model-averaged estimates of population size decreased on the treatment area from 87.7 bears before construction to 31.6 bears after construction (64% reduction) and on the control area from 163.6 bears to 108.2 bears (34% reduction). Permutation procedures indicated this reduction was proportionally greater for the treatment area (P = 0.086). We also applied a spatially explicit capture-recapture technique to test our research hypothesis. The model with the most support indicated a greater change in density on the treatment area (69% reduction) compared with the control area (24% reduction). We did not observe a treatment effect based on survival of radiocollared bears. We used bear visits to hair snares as detections in multi-season occupancy models and found that occupancy decreased more on the treatment area (preconstruction: Ψ = 0.84; postconstruction: Ψ = 0.44; 48% decline) than the control area (preconstruction: Ψ = 0.91; postconstruction: Ψ = 0.81; 11% decline), primarily as a function of a greater probability of site extinctions (ε) on the treatment area (ε = 0.57) than the control area (ε = 0.17). Finally, individual- and population-based analyses of contemporary gene flow did not indicate the highway was a barrier to movements. Black bear use of the 3 wildlife underpasses was infrequent (17 verified crossings based on remote cameras, track surveys, and telemetry). Only 4 of 8 bears with home ranges near the highway were documented crossing the highway (n = 36 crossings), of which 2 were killed in vehicle collisions. Six additional bears were killed in vehicle collisions from May 2007 to November 2008, after we completed field work. Harvest data indicated that hunting mortality alone could explain the population decline on the control area. On the treatment area, however, hunting mortality only accounted for an approximately 40% population decline; the additional 30% decline we observed likely was caused by other mortality. We speculate vehicle collisions were primarily responsible. We conclude that impacts of the new highway on resident black bears occurred at the population level, rather than the individual or genetic level, but that the impact was smaller than harvest mortality. Increased activity by remaining bears when traffic volumes were low indicated behavioral plasticity. Bear use of the underpasses seemed sufficient to maintain gene flow between areas north and south of the new highway. Effectiveness of wildlife underpasses to reduce mortality of black bears may be enhanced if mitigation includes continuous fencing between crossing structures. For small, isolated populations of threatened or endangered large mammals, the potential demographic impacts of highways are an essential consideration in the transportation planning process. Control of mortality factors and maintaining demographic connectivity are particularly important.

California