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Geology topics

W.R. Clark

Publications and source records attributed to W.R. Clark.

5 recordsLinked to original sources
USGS2011

Stochastic population dynamics in populations of western terrestrial garter snakes with divergent life histories

Comparative evaluations of population dynamics in species with temporal and spatial variation in life‐history traits are rare because they require long‐term demographic time series from multiple populations. We present such an analysis using demographic data collected during the interval 1978–1996 for six populations of western terrestrial garter snakes ( Thamnophis elegans ) from two evolutionarily divergent ecotypes. Three replicate populations from a slow‐living ecotype, found in mountain meadows of northeastern California, were characterized by individuals that develop slowly, mature late, reproduce infrequently with small reproductive effort, and live longer than individuals of three populations of a fast‐living ecotype found at lakeshore locales. We constructed matrix population models for each of the populations based on 8–13 years of data per population and analyzed both deterministic dynamics based on mean annual vital rates and stochastic dynamics incorporating annual variation in vital rates. (1) Contributions of highly variable vital rates to fitness (λ s ) were buffered against the negative effects of stochastic variation, and this relationship was consistent with differences between the meadow (M‐slow) and lakeshore (L‐fast) ecotypes. (2) Annual variation in the proportion of gravid females had the greatest negative effect among all vital rates on λ s . The magnitude of variation in the proportion of gravid females and its effect on λ s was greater in M‐slow than L‐fast populations. (3) Variation in the proportion of gravid females, in turn, depended on annual variation in prey availability, and its effect on λ s was 4–23 times greater in M‐slow than L‐fast populations. In addition to differences in stochastic dynamics between ecotypes, we also found higher mean mortality rates across all age classes in the L‐fast populations. Our results suggest that both deterministic and stochastic selective forces have affected the evolution of divergent life‐history traits in the two ecotypes, which, in turn, affect population dynamics. M‐slow populations have evolved life‐history traits that buffer fitness against direct effects of variation in reproduction and that spread lifetime reproduction across a greater number of reproductive bouts. These results highlight the importance of long‐term demographic and environmental monitoring and of incorporating temporal dynamics into empirical studies of life‐history evolution.

California↗
USGS2010

Sampling considerations for disease surveillance in wildlife populations

Disease surveillance in wildlife populations involves detecting the presence of a disease, characterizing its prevalence and spread, and subsequent monitoring. A probability sample of animals selected from the population and corresponding estimators of disease prevalence and detection provide estimates with quantifiable statistical properties, but this approach is rarely used. Although wildlife scientists often assume probability sampling and random disease distributions to calculate sample sizes, convenience samples (i.e., samples of readily available animals) are typically used, and disease distributions are rarely random. We demonstrate how landscape-based simulation can be used to explore properties of estimators from convenience samples in relation to probability samples. We used simulation methods to model what is known about the habitat preferences of the wildlife population, the disease distribution, and the potential biases of the convenience-sample approach. Using chronic wasting disease in free-ranging deer (Odocoileus virginianus) as a simple illustration, we show that using probability sample designs with appropriate estimators provides unbiased surveillance parameter estimates but that the selection bias and coverage errors associated with convenience samples can lead to biased and misleading results. We also suggest practical alternatives to convenience samples that mix probability and convenience sampling. For example, a sample of land areas can be selected using a probability design that oversamples areas with larger animal populations, followed by harvesting of individual animals within sampled areas using a convenience sampling method.

Journal of Wildlife Management↗
USGS2004

Analysis of predator movement in prairie landscapes with contrasting grassland composition

Mammalian predation influences waterfowl breeding success in the U.S. northern Great Plains, yet little is known about the influence of the landscape on the ability of predators to find waterfowl nests. We used radiotelemetry to record nightly movements of red foxes ( Vulpes vulpes ) and striped skunks ( Mephitis mephitis ) in two 41.4-km 2 study areas in North Dakota. Study areas contained either 15–20% grassland (low grassland composition) or 45–55% grassland (high grassland composition). Grasslands included planted cover, pastureland, and hayland. We predicted that the type and composition of cover types in the landscape would influence both predator movement across the landscape (as measured by the fractal dimension and displacement ratio) as well as localized movement (as measured by the rate of movement and turning angle between locations) within patches of different cover types. Red fox movements were straighter (lower fractal dimensions and higher displacements) across landscapes with a low grassland composition, indicating directed movement between the more isolated patches of planted cover. Striped skunk movements did not differ between landscape types, illustrating their movement along wetland edges, which had similar compositions in both landscape types. The high variability in turning angles by red fox in planted cover and pastureland in both landscape types is consistent with restricted-area foraging. The high rate of movement by red foxes in planted cover and by striped skunks in wetland edges suggests that spatial memory may influence movement patterns. Understanding the behavior of predators in fragmented prairie landscape is essential for managing breeding habitat for grassland birds and for predicting the spatial and temporal dynamics of predators and their prey.

North Dakota↗
USGS1993

A model of the productivity of the northern pintail

We adapted a stochastic computer model to simulate productivity of the northern pintail (Anas acuta). Researchers at the Northern Prairie Wildlife Research Center of the U.S. Fish and Wildlife Service originally developed the model to simulate productivity of the mallard (A. platyrhynchos). We obtained data and descriptive information on the breeding biology of pintails from a literature review and from discussions with waterfowl biologists. All biological parameters in the productivity component of the mallard model (e.g, initial body weights, weight loss during laying and incubation, incubation time, clutch size, nest site selection characteristics) were compared with data on pintails and adjusted accordingly. The function in the mallard model that predicts nest initiation in response to pond conditions adequately mimicked pintail behavior and did not require adjustment.Recruitment rate was most sensitive to variations in parameters that control nest success, seasonal duckling survival rate, and yearling and adult body weight. We simulated upland and wetland habitat conditions in central North Dakota and compared simulation results with observed data. Simulated numbers were not significantly different from observed numbers of successful nests during wet, average, and dry wetland conditions. The simulated effect of predator barrier fencing in a study area in central North Dakota increased recruitment rate by an average of 18.4%. This modeling synthesized existing knowledge on the breeding biology of the northern pintail, identified necessary research, and furnished a useful tool for the examination and comparison of various management options.

Biological Report↗