Geology topics

Timothy R. Van Deelen

Publications and source records attributed to Timothy R. Van Deelen.

11 recordsLinked to original sources

USGS2026

Occupancy rates of river otters (Lontra canadensis) in the St. Louis River Area of Concern

The St. Louis River Area of Concern (AOC), an estuarine system along the northeastern Minnesota-Wisconsin border, experienced significant ecological disturbances and degradation from unregulated industrial development during the 19 th and 20 th centuries. Recent restoration and remediation efforts in the AOC have led to substantial improvements in water quality, habitat, and fisheries populations. However, the status of wildlife populations following restoration efforts in the AOC remain largely unknown. We used remote cameras to estimate occupancy rates of river otters Lontra canadensis in the AOC and at two reference areas that had not been subjected to historical degradation. Because river otters occupy a high trophic level within these systems, we hypothesized that they would be an effective indicator species of overall habitat quality and recovery. Using data collected from June 2015 to February 2016, we developed single-season occupancy models for both summer and winter seasons. We found no differences in occupancy between the AOC and the reference sites, suggesting that river otter populations within the AOC were comparable to those in unaffected areas. Our results indicate that habitat restoration and remediation efforts in the St. Louis River estuary have been successful in promoting healthy wildlife populations.

Minnesota, Wisconsin↗

USGS2024

Scale-dependence in elk habitat selection for a reintroduced population in Wisconsin, USA

Habitat selection is a critical aspect of a species' ecology, requiring complex decision-making that is both hierarchical and scale-dependent, since factors that influence selection may be nested or unequal across scales. Elk ( Cervus canadensis ) ranged widely across diverse ecoregions in North America prior to European settlement and subsequent eastern extirpation. Most habitat selection studies have occurred within their contemporary western range, even after eastern reintroductions began. As habitat selection can vary by geographic location, available cover, season, and diel period, it is important to understand how a non-migratory, reintroduced population in northern Wisconsin, USA, is limited by the lack of variation in topography, elevation, and vegetation. We tested scale-dependent habitat selection on 79 adult elk from 2017 to 2020 using resource selection functions across temporal (i.e., seasonal) and spatial scales (i.e., landscape and home range). We found that selection varied both spatially and temporally, and elk selected areas with the greatest potential to influence fitness at larger scales, meaning elk selected areas closer to escape cover and further from “risky” features (e.g., annual wolf territory centers, county roads, and highways). We found stronger avoidance of annual wolf territory centers during spring, suggesting elk were selecting safer habitats during calving season. Elk selected habitats with less canopy cover across both spatial scales and all seasons, suggesting that elk selected areas with better access to forage as early seral stage stands have greater forage biomass than closed-canopy forests and direct solar radiation to provide warmth in the cooler seasons. This study provides insight into the complexity of hierarchical decision-making, such as how risky habitat features and land cover type influence habitat selection differently across seasons and spatial scales, influencing the decision-making of elk. Scale-dependent behavior is crucial to understand within specific geographic regions, as these decisions scale up to influence population dynamics.

Wisconsin↗

USGS2023

Long-term assessment of relationships between changing environmental conditions and the physiology of southern Beaufort Sea polar bears (Ursus maritimus)

Climate change is influencing polar bear ( Ursus maritimus ) habitat, diet, and behavior but the effects of these changes on their physiology is not well understood. Blood-based biomarkers are used to assess the physiologic health of individuals but their usefulness for evaluating population health, especially as it relates to changing environmental conditions, has rarely been explored. We describe links between environmental conditions and physiologic functions of southern Beaufort Sea polar bears using data from blood samples collected from 1984 to 2018, a period marked by extensive environmental change. We evaluated associations between 13 physiologic biomarkers and circumpolar (Arctic oscillation index) and regional (wind patterns and ice-free days) environmental metrics and seasonal and demographic co-variates (age, sex, season, and year) known to affect polar bear ecology. We observed signs of dysregulation of water balance in polar bears following years with a lower annual Arctic oscillation index. In addition, liver enzyme values increased over time, which is suggestive of potential hepatocyte damage as the Arctic has warmed. Biomarkers of immune function increased with regional-scale wind patterns and the number of ice-free days over the Beaufort Sea continental shelf and were lower in years with a lower winter Arctic oscillation index, suggesting an increased allocation of energetic resources for immune processes under these conditions. We propose that the variation in polar bear immune and metabolic function is likely indicative of physiologic plasticity, a response that allows polar bears to remain in homeostasis even as they experience changes in nutrition and habitat in response to changing environments.

Alaska↗

USGS2022

A call to action: Standardizing white-tailed deer harvest data in the Midwestern United States and implications for quantitative analysis and disease management

Recreational hunting has been the dominant game management and conservation mechanism in the United States for the past century. However, there are numerous modern-day issues that reduce the viability and efficacy of hunting-based management, such as fewer hunters, overabundant wildlife populations, limited access, and emerging infectious diseases in wildlife. Quantifying the drivers of recreational harvest by hunters could inform potential management actions to address these issues, but this is seldom comprehensively accomplished because data collection practices limit some analytical applications (e.g., differing spatial scales of harvest regulations and harvest data). Additionally, managing large-scale issues, such as infectious diseases, requires collaborations across management agencies, which is challenging or impossible if data are not standardized. Here we discuss modern issues with the prevailing wildlife management framework in the United States from an analytical point of view with a case study of white-tailed deer ( Odocoileus virginianus ) in the Midwest. We have four aims: (1) describe the interrelated processes that comprise hunting and suggest improvements to current data collections systems, (2) summarize data collection systems employed by state wildlife management agencies in the Midwestern United States and discuss potential for large-scale data standardization, (3) assess how aims 1 and 2 influence managing infectious diseases in hunted wildlife, and (4) suggest actionable steps to help guide data collection standards and management practices. To achieve these goals, Wisconsin Department of Natural Resources disseminated a questionnaire to state wildlife agencies (Illinois, Indiana, Iowa, Kentucky, Michigan, Minnesota, Missouri, Ohio, Wisconsin), and we report and compare their harvest management structures, data collection practices, and responses to chronic wasting disease. We hope our “call to action” encourages re-evaluation, coordination, and improvement of harvest and management data collection practices with the goal of improving the analytical potential of these data. A deeper understanding of the strengths and deficiencies of our current management systems in relation to harvest and management data collection methods could benefit the future development of comprehensive and collaborative management and research initiatives (e.g., adaptive management) for wildlife and their diseases.

Illinois, Indiana, Iowa, Kentucky, Michigan, Minne↗

USGS2017

Using expert knowledge to incorporate uncertainty in cause-of-death assignments for modeling of cause-specific mortality

Implicit and explicit use of expert knowledge to inform ecological analyses is becoming increasingly common because it often represents the sole source of information in many circumstances. Thus, there is a need to develop statistical methods that explicitly incorporate expert knowledge, and can successfully leverage this information while properly accounting for associated uncertainty during analysis. Studies of cause-specific mortality provide an example of implicit use of expert knowledge when causes-of-death are uncertain and assigned based on the observer's knowledge of the most likely cause. To explicitly incorporate this use of expert knowledge and the associated uncertainty, we developed a statistical model for estimating cause-specific mortality using a data augmentation approach within a Bayesian hierarchical framework. Specifically, for each mortality event, we elicited the observer's belief of cause-of-death by having them specify the probability that the death was due to each potential cause. These probabilities were then used as prior predictive values within our framework. This hierarchical framework permitted a simple and rigorous estimation method that was easily modified to include covariate effects and regularizing terms. Although applied to survival analysis, this method can be extended to any event-time analysis with multiple event types, for which there is uncertainty regarding the true outcome. We conducted simulations to determine how our framework compared to traditional approaches that use expert knowledge implicitly and assume that cause-of-death is specified accurately. Simulation results supported the inclusion of observer uncertainty in cause-of-death assignment in modeling of cause-specific mortality to improve model performance and inference. Finally, we applied the statistical model we developed and a traditional method to cause-specific survival data for white-tailed deer, and compared results. We demonstrate that model selection results changed between the two approaches, and incorporating observer knowledge in cause-of-death increased the variability associated with parameter estimates when compared to the traditional approach. These differences between the two approaches can impact reported results, and therefore, it is critical to explicitly incorporate expert knowledge in statistical methods to ensure rigorous inference.

Ecology and Evolution↗

USGS2015

Mortality patterns and detection bias from carcass data: An example from wolf recovery in Wisconsin

We developed models and provide computer code to make carcass recovery data more useful to wildlife managers. With these tools, wildlife managers can understand the spatial, temporal (e.g., across time periods, seasons), and demographic patterns in mortality causes from carcass recovery datasets. From datasets of radio-collared and non-collared carcasses, managers can calculate the detection bias by mortality cause in a non-collared carcass dataset compared to a collared carcass dataset. As a first step, we provide a standard procedure to assign mortality causes to carcasses. We provide an example of these methods for radio-collared wolves ( n  = 208) and non-collared wolves ( n  = 668) found dead in Wisconsin (1979–2012). We analyzed differences in mortality cause relative to season, age and sex classes, wolf harvest zones, and recovery phase (1979–1995: initial recovery, 1996–2002: early growth, 2003–2012: late growth). Seasonally, illegal kills and natural deaths were proportionally higher in winter (Oct–Mar) than summer (Apr–Sep) for collared wolves, whereas vehicle strikes and legal kills were higher in summer than winter. Spatially, more illegally killed collared wolves occurred in eastern wolf harvest zones where wolves reestablished more slowly and in the central forest region where optimal habitat is isolated by agriculture. Natural mortalities of collared wolves (e.g., disease, intraspecific strife, or starvation) were highest in western wolf harvest zones where wolves established earlier and existed at higher densities. Calculating detection bias in the non-collared dataset revealed that more than half of the non-collared carcasses on the landscape are not found. The lowest detection probabilities for non-collared carcasses (0.113–0.176) occurred in winter for natural, illegal, and unknown mortality causes.

Wisconsin↗

USGS2014

Estimating ages of white-tailed deer: Age and sex patterns of error using tooth wear-and-replacement and consistency of cementum annuli

The age structure of harvested animals provides the basis for many demographic analyses. Ages of harvested white-tailed deer ( Odocoileus virginianus ) and other ungulates often are estimated by evaluating replacement and wear patterns of teeth, which is subjective and error-prone. Few previous studies however, examined age- and sex-specific error rates. Counting cementum annuli of incisors is an alternative, more accurate method of estimating age, but factors that influence consistency of cementum annuli counts are poorly known. We estimated age of 1,261 adult (≥1.5 yr old) white-tailed deer harvested in Wisconsin and Illinois (USA; 2005–2008) using both wear-and-replacement and cementum annuli. We compared cementum annuli with wear-and-replacement estimates to assess misclassification rates by sex and age. Wear-and-replacement for estimating ages of white-tailed deer resulted in substantial misclassification compared with cementum annuli. Age classes of females were consistently underestimated, while those of males were underestimated for younger age classes but overestimated for older age classes. Misclassification resulted in an impression of a younger age-structure than actually was the case. Additionally, we obtained paired age-estimates from cementum annuli for 295 deer. Consistency of paired cementum annuli age-estimates decreased with age, was lower in females than males, and decreased as age estimates became less certain. Our results indicated that errors in the wear-and-replacement techniques are substantial and could impact demographic analyses that use age-structure information.

Wildlife Society Bulletin↗

USGS2013

Evaluating spatial overlap and relatedness of white-tailed deer in a chronic wasting disease management zone

Wildlife disease transmission, at a local scale, can occur from interactions between infected and susceptible conspecifics or from a contaminated environment. Thus, the degree of spatial overlap and rate of contact among deer is likely to impact both direct and indirect transmission of infectious diseases such chronic wasting disease (CWD) or bovine tuberculosis. We identified a strong relationship between degree of spatial overlap (volume of intersection) and genetic relatedness for female white-tailed deer in Wisconsin’s area of highest CWD prevalence. We used volume of intersection as a surrogate for contact rates between deer and concluded that related deer are more likely to have contact, which may drive disease transmission dynamics. In addition, we found that age of deer influences overlap, with fawns exhibiting the highest degree of overlap with other deer. Our results further support the finding that female social groups have higher contact among related deer which can result in transmission of infectious diseases. We suggest that control of large social groups comprised of closely related deer may be an effective strategy in slowing the transmission of infectious pathogens, and CWD in particular.

PLoS ONE↗

USGS2013

Deer density and disease prevalence influence transmission of Chronic Wasting Disease in White-tailed Deer

Host-parasite dynamics and strategies for managing infectious diseases of wildlife depend on the functional relationship between disease transmission rates and host density. However, the disease transmission function is rarely known for free-living wildlife, leading to uncertainty regarding the impacts of diseases on host populations and effective control actions. We evaluated the influence of deer density, landscape features, and soil clay content on transmission of chronic wasting disease (CWD) in young (<2-year-old) white-tailed deer ( Odocoileus virginianus ) in south-central Wisconsin, USA. We evaluated how frequency-dependent, density-dependent, and intermediate transmission models predicted CWD incidence rates in harvested yearling deer. An intermediate transmission model, incorporating both disease prevalence and density of infected deer, performed better than simple density- and frequency-dependent models. Our results indicate a combination of social structure, non-linear relationships between infectious contact and deer density, and distribution of disease among groups are important factors driving CWD infection in young deer. The landscape covariates % deciduous forest cover and forest edge density also were positively associated with infection rates, but soil clay content had no measurable influences on CWD transmission. Lack of strong density-dependent transmission rates indicates that controlling CWD by reducing deer density will be difficult. The consequences of non-linear disease transmission and aggregation of disease on cervid populations deserves further consideration.

Ecosphere↗

USGS2011

Envisioning the future of wildlife in a changing climate: Collaborative learning for adaptation planning

Natural resource managers are tasked with assessing the impacts of climate change on conservation targets and developing adaptation strategies to meet agency goals. The complex, transboundary nature of climate change demands the collaboration of scientists, managers, and stakeholders in this effort. To share, integrate, and apply knowledge from these diverse perspectives, we must engage in social learning. In 2009, we initiated a process to engage university researchers and agency scientists and managers in collaborative learning to assess the impacts of climate change on terrestrial fauna in the state of Wisconsin, USA. We constructed conceptual Bayesian networks to depict the influence of climate change, key biotic and abiotic factors, and existing stressors on the distribution and abundance of 3 species: greater prairie-chicken ( Tympanuchus cupido ), wood frog ( Lithobates sylvaticus ), and Karner blue butterfly ( Plebejus melissa samuelis ). For each species, we completed a 2-stage expert review that elicited dialogue on information gaps, management opportunities, and research priorities. From our experience, collaborative network modeling proved to be a powerful tool to develop a common vision of the potential impacts of climate change on conservation targets.

Wildlife Society Bulletin↗

USGS2011

Comparison of visual-based helicopter and fixed-wing forward-looking infrared surveys for counting white-tailed deer Odocoileus virginianus

Aerial surveys using direct counts of animals are commonly used to estimate deer abundance. Forward-looking infrared (FLIR) technology is increasingly replacing traditional methods such as visual observation from helicopters. Our goals were to compare fixed-wing FLIR and visual, helicopter-based counts in terms of relative bias, influence of snow cover and cost. We surveyed five plots: four 41.4 km 2 plots with free-ranging white-tailed deer Odocoileus virginianus populations in Wisconsin and a 5.3 km 2 plot with a white-tailed deer population contained by a high fence in Michigan. We surveyed plots using both fixed-wing FLIR and helicopters, both with snow cover and without snow. None of the methods counted more deer than the other when snow was present. Helicopter counts were lower in the absence of snow, but lack of snow cover did not apparently affect FLIR. Group sizes of observed deer were similar regardless of survey method or season. We found that FLIR counts were generally precise (CV = 0.089) when two or three replicate surveys were conducted within a few hours. However, at the plot level, FLIR counts differed greatly between seasons, suggesting that detection rates vary over larger time scales. Fixed-wing FLIR was more costly than visual observers in helicopters and was more restrictive in terms of acceptable survey conditions. Further research is needed to understand what factors influence the detection of deer during FLIR surveys.

Michigan, Wisconsin↗