Geology topics

T. L. McDonald

Publications and source records attributed to T. L. McDonald.

10 recordsLinked to original sources

USGS2011

Polar bear population status in the northern Beaufort Sea, Canada, 1971-2006

Polar bears ( Ursus maritimus ) of the northern Beaufort Sea (NB) population occur on the perimeter of the polar basin adjacent to the northwestern islands of the Canadian Arctic Archipelago. Sea ice converges on the islands through most of the year. We used open-population capture–recapture models to estimate population size and vital rates of polar bears between 1971 and 2006 to: (1) assess relationships between survival, sex and age, and time period; (2) evaluate the long-term importance of sea ice quality and availability in relation to climate warming; and (3) note future management and conservation concerns. The highest-ranking models suggested that survival of polar bears varied by age class and with changes in the sea ice habitat. Model-averaged estimates of survival (which include harvest mortality) for senescent adults ranged from 0.37 to 0.62, from 0.22 to 0.68 for cubs of the year (COY) and yearlings, and from 0.77 to 0.92 for 2–4 year-olds and adults. Horvtiz-Thompson (HT) estimates of population size were not significantly different among the decades of our study. The population size estimated for the 2000s was 980 ± 155 (mean and 95% CI). These estimates apply primarily to that segment of the NB population residing west and south of Banks Island. The NB polar bear population appears to have been stable or possibly increasing slightly during the period of our study. This suggests that ice conditions have remained suitable and similar for feeding in summer and fall during most years and that the traditional and legal Inuvialuit harvest has not exceeded sustainable levels. However, the amount of ice remaining in the study area at the end of summer, and the proportion that continues to lie over the biologically productive continental shelf (<300 m water depth) has declined over the 35-year period of this study. If the climate continues to warm as predicted, we predict that the polar bear population in the northern Beaufort Sea will eventually decline. Management and conservation practices for polar bears in relation to both aboriginal harvesting and offshore industrial activity will need to adapt.

Ecological Applications↗

USGS2006

Estimating Potential Effects of Hypothetical Oil Spills on Polar Bears

Much is known about the transport and fate of oil spilled into the sea and its toxicity to exposed wildlife. Previously, however, there has been no way to quantify the probability that wildlife dispersed over the seascape would be exposed to spilled oil. Polar bears, the apical predator of the arctic, are widely dispersed near the continental shelves of the Arctic Ocean, an area also undergoing considerable hydrocarbon exploration and development. We used 15,308 satellite locations from 194 radiocollared polar bears to estimate the probability that polar bears could be exposed to hypothetical oil spills. We used a true 2 dimensional Gausian kernel density estimator, to estimate the number of bears likely to occur in each 1.00 km2 cell of a grid superimposed over near shore areas surrounding 2 oil production facilities: the existing Northstar oil production facility, and the proposed offshore site for the Liberty production facility. We estimated the standard errors of bear numbers per cell with bootstrapping. Simulated oil spill footprints for September and October, the times during which we hypothesized effects of an oil-spill would be worst, were estimated using real wind and current data collected between 1980 and 1996. We used ARC/Info software to calculate overlap (numbers of bears oiled) between simulated oil-spill footprints and polar bear grid-cell values. Numbers of bears potentially oiled by a hypothetical 5912 barrel spill (the largest spill thought probable from a pipeline breach) ranged from 0 to 27 polar bears for September open water conditions, and from 0 to 74 polar bears in October mixed ice conditions. Median numbers oiled by the 5912 barrel hypothetical spill from the Liberty simulation in September and October were 1 and 3 bears, equivalent values for the Northstar simulation were 3 and 11 bears. In October, 75% of trajectories from the 5912 barrel simulated spill at Liberty oiled 9 or fewer bears while 75% of the trajectories affected 20 or fewer polar bears when we simulated an October spill at the Northstar site. Northstar Island is nearer the active ice flaw zone than Liberty. Simulations suggested that oil spilled at Northstar would spread more effectively and more consistently into surrounding areas. Also, polar bear densities are consistently higher near Northstar. Oil spills simulated for the Liberty site were more erratic in the areas they covered and the numbers of bears impacted, and numbers of bears hypothetically exposed were usually smaller. Methods described here are broadly applicable to other dispersed marine wildlife. Key words: Arctic, Beaufort Sea, clustering, kernel, management, oil spill, polar bears, population delineation, radiotelemetry, satellite, smoothing, Ursus maritimus

Report↗

USGS2004

Using satellite radiotelemetry data to delineate and manage wildlife populations

The greatest promise of radiotelemetry always has been a better understanding of animal movements. Telemetry has helped us know when animals are active, how active they are, how far and how fast they move, the geographic areas they occupy, and whether individuals vary in these traits. Unfortunately, the inability to estimate the error in animals utilization distributions (UDs), has prevented probabilistic linkage of movements data, which are always retrospective, with future management actions. We used the example of the harvested population of polar bears ( Ursus maritimus ) in the Southern Beaufort Sea to illustrate a method that provides that linkage. We employed a 2-dimensional Gaussian kernel density estimator to smooth and scale frequencies of polar bear radio locations within cells of a grid overlying our study area. True 2-dimensional smoothing allowed us to create accurate descriptions of the UDs of individuals and groups of bears. We used a new method of clustering, based upon the relative use collared bears made of each cell in our grid, to assign individual animals to populations. We applied the fast Fourier transform to make bootstrapped estimates of the error in UDs computationally feasible. Clustering and kernel smoothing identified 3 populations of polar bears in the region between Wrangel Island, Russia, and Banks Island, Canada. The relative probability of occurrence of animals from each population varied significantly among grid cells distributed across the study area. We displayed occurrence probabilities as contour maps wherein each contour line corresponded with a change in relative probability. Only at the edges of our study area and in some offshore regions were bootstrapped estimates of error in occurrence probabilities too high to allow prediction. Error estimates, which also were displayed as contours, allowed us to show that occurrence probabilities did not vary by season. Near Barrow, Alaska, 50% of bears observed are predicted to be from the Chukchi Sea population and 50% from the Southern Beaufort Sea population. At Tuktoyaktuk, Northwest Territories, Canada, 50% are from the Southern Beaufort Sea and 50% from the Northern Beaufort Sea population. The methods described here will aid managers of all wildlife that can be studied by telemetry to allocate harvests and other human perturbations to the appropriate populations, make risk assessments, and predict impacts of human activities. They will aid researchers by providing the refined descriptions of study populations that are necessary for population estimation and other investigative tasks. Arctic, Beaufort Sea, boundaries, clustering, Fourier transform, kernel, management, polar bears, population delineation, radiotelemetry, satellite, smoothing, Ursus maritimus

Beaufort Sea, Chukchi Sea↗

USGS2004

Population dynamics of the California Spotted Owl (Strix occidentalis occidentalis): a meta-analysis

We conducted a meta-analysis to provide a current assessment of the population characteristics of California Spotted Owls (Strix occidentalis occidentalis) resident on four study areas in the Sierra Nevada and one study area in southern California. Our meta-analysis followed rigorous a priori analysis protocols, which we derived through extensive discussion during a week-long analysis workshop. Because there is great interest in the owl?s population status, we used state-of-the-art analytical methods to obtain results as precise as possible. Our meta-analysis included data from five California study areas located on the Lassen National Forest (1990-2000), Eldorado National Forest (1986-2000), Sierra National Forest (1990-2000), Sequoia and Kings Canyon national parks (1990-2000), and San Bernardino National Forest (1987-1998). Four of the five study areas spanned the length of the Sierra Nevada, whereas the fifth study area encompassed the San Bernardino Mountains in southern California. Study areas ranged in size from 343 km2 (Sequoia and Kings Canyon) to 2,200 km (Lassen). All studies were designed to use capture-recapture methods and analysis. We used survival in a meta-analysis because field methods were very similar among studies. However, we did not use reproduction in a meta-analysis because it was not clear if variation among individual study-area protocols used to assess reproductive output of owls would confound results. Thus, we analyzed fecundity only by individual study area. We examined population trend using the reparameterized Jolly-Seber capture-recapture estimator (8t) We did not estimate juvenile survival rates because of estimation problems and potential bias because of juvenile emigration from study areas. We used mark-recapture estimators under an information theoretic framework to assess apparent survival rates of adult owls. The pooled estimate for adult apparent survival for the five study areas was 0.833, which was lower than pooled adult survival rates (0.850) from 15 Northern Spotted Owl (S. o. caurina) studies. Estimates of survival from the best model on the Lassen (N = 0.829, 95% confidence intervals [CI = 0.798 to 0.857), Eldorado (N = 0.815, 95% CI = 0.772 to 0.851), Sierra (N = 0.818, 95% CI = 0.781 to 0.850), and San Bernardino (N = 0.813, 95% CI = 0.782 to 0.841) were not different. However, the Sequoia and Kings Canyon population had a higher survival rate (N = 0.877, 95% CI = 0.842 to 0.905) than the other study areas. Management history and forest structure (e.g. presence of giant sequoia [Sequoiadendron giganteum]) on the Sequoia and Kings Canyon study area differed from all other study areas. There appears to be little or no evidence for temporal variation in adult apparent survival on any of the study areas. Although we did not directly compare fecundity estimates were highly variable among years within all study areas (CV of temporal process variation = 0.672-0.817). Estimates for fecundity among the study populations were Lassen (b = 0.336, SE = 0.083), Eldorado (b = 0.409, SE = 0.087), Sierra (b = 0.284, SE = 0.073), Sequoia and Kings Canyon (b = 0.289, SE = 0.074), and San Bernardino (b = 0.362, SE = 0.038). During most years, the Sierra Nevada populations showed either moderate or poor fecundity. However, 1992 appeared to be an exceptional reproductive year for owls in the Sierra Nevada. In contrast, the San Bernardino population had less variable reproduction (CV of temporal process variation = 0.217), but experienced neither the exceptional reproduction of 1992 nor the extremely poor years that characterized all of the Sierra Nevada study areas. Because fecundity may be influenced by weather patterns, it was possible that the different weather patterns between southern California and the Sierra Nevada accounted for that difference. Except for Eldorado, all estimates for 8t, were <1.0, but none was different from 8 = 1.0 given the 95% confidence i

Ornithological Monographs↗

USGS2003

Detecting denning polar bears with forward looking infra-red imagery (FLIR)

Polar bears give birth in snow dens in mid winter, and remain in dens until early spring. Survival and development of neonates is dependent on the stable environment within the maternal den. Petroleum related activities currently span approximately 200 km of the Alaskan Beaufort Sea coastal area. New and proposed developments are expected to dramatically expand the area influenced by petroleum activities. These activities are a potential threat to polar bears, especially as they might disturb denning females. In order to help manage and mitigate potential disruptions of polar bear denning, we tested whether we could detect heat, rising through the roofs of maternal dens, with forward-looking infrared (FLIR) viewing devices. We tested detectability of dens by flying transects, over habitats known to hold dens, with FLIR equipped aircraft. We recorded flight and weather conditions at each observation and tallied whether or not the den was detected.

Conference Paper↗

USGS2001

Comparing movement patterns of satellite-tagged male and female polar bears

Satellite radiotelemetry has provided great insights into the movements and behaviors of polar bears ( Ursus maritimus ). The diameter of the neck of adult male polar bears exceeds that of their head, however, and radio collars slip off. This has limited collection of movement information to that from radio-collared females. To overcome this difficulty and gather information about their movements, we surgically implanted satellite radio transmitters into 7 male polar bears during 1996 and 1997. We compared movements of implanted males with those of 104 adult females radio-collared between 1985 and 1995. Transmitters were implanted under the skin on the midline of the top of the neck and were equipped with percutaneous antennae. Implanted transmitters operated for up to 161 days providing 3217 satellite relocations. While transmitting, radios implanted in males provided a larger proportion of the highest quality category of position fixes than was obtained from radio-collared females. However, all implanted radios ceased transmitting before reaching their projected life-span. The abrupt termination of transmission from implanted radios suggested mechanical rather than electronic failure. Mean rates of short-term movement for males (1.18 km/h) were lower than for solitary females, females with cubs, and females with yearlings (1.70, 1.84, and 1.95 km/h, respectively). Net geographic movements from the beginning to the end of each month were comparable for males (mean = 135 km) and females (mean = 114, 152, and 168 km). Mean azimuths of these net movements also appeared to be similar. Monthly activity-area sizes for males (mean = 8541 km 2 ) were comparable to those for females (mean = 3698, 9397, and 10 585 km 2 ) during the time period of comparison. In contrast to the other movement measures, males traveled longer mean distances (387 km) each month than did females (217, 289, and 302 km). Movements of males, it appears, were more directed than those of females, but males confined their travels to similar-sized areas.

Alaska, Northwest Territories↗

USGS2001

Estimation of population size using open capture-recapture models

One of the most important needs for wildlife managers is an accurate estimate of population size. Yet, for many species, including most marine species and large mammals, accurate and precise estimation of numbers is one of the most difficult of all research challenges. Open-population capture-recapture models have proven useful in many situations to estimate survival probabilities but typically have not been used to estimate population size. We show that open-population models can be used to estimate population size by developing a Horvitz-Thompson-type estimate of population size and an estimator of its variance. Our population size estimate keys on the probability of capture at each trap occasion and therefore is quite general and can be made a function of external covariates measured during the study. Here we define the estimator and investigate its bias, variance, and variance estimator via computer simulation. Computer simulations make extensive use of real data taken from a study of polar bears (Ursus maritimus) in the Beaufort Sea. The population size estimator is shown to be useful because it was negligibly biased in all situations studied. The variance estimator is shown to be useful in all situations, but caution is warranted in cases of extreme capture heterogeneity.

Journal of Agricultural, Biological, and Environme↗

USGS2001

Polar bears in the Beaufort Sea: A 30-year mark-recapture case history

Knowledge of population size and trend is necessary to manage anthropogenic risks to polar bears ( Ursus maritimus ). Despite capturing over 1,025 females between 1967 and 1998, previously calculated estimates of the size of the southern Beaufort Sea (SBS) population have been unreliable. We improved estimates of numbers of polar bears by modeling heterogeneity in capture probability with covariates. Important covariates referred to the year of the study, age of the bear, capture effort, and geographic location. Our choice of best approximating model was based on the inverse relationship between variance in parameter estimates and likelihood of the fit and suggested a growth from ≈ 500 to over 1,000 females during this study. The mean coefficient of variation on estimates for the last decade of the study was 0.16—the smallest yet derived. A similar model selection approach is recommended for other projects where a best model is not identified by likelihood criteria alone.

Beaufort Sea↗

USGS1997

Interactive effects of prey and weather on golden eagle reproduction

1. The reproduction of the golden eagle Aquila chrysaetos was studied in southwestern Idaho for 23 years, and the relationship between eagle reproduction and jackrabbit Lepus californicus abundance, weather factors, and their interactions, was modelled using general linear models. Backward elimination procedures were used to arrive at parsimonious models. 2. The number of golden eagle pairs occupying nesting territories each year showed a significant decline through time that was unrelated to either annual rabbit abundance or winter severity. However, eagle hatching dates were significantly related to both winter severity and jackrabbit abundance. Eagles hatched earlier when jackrabbits were abundant, and they hatched later after severe winters. 3. Jackrabbit abundance influenced the proportion of pairs that laid eggs, the proportion of pairs that were successful, mean brood size at fledging, and the number of young fledged per pair. Weather interacted with prey to influence eagle reproductive rates. 4. Both jackrabbit abundance and winter severity were important in predicting the percentage of eagle pairs that laid eggs. Percentage laying was related positively to jackrabbit abundance and inversely related to winter severity. 5. The variables most useful in predicting percentage of laying pairs successful were rabbit abundance and the number of extremely hot days during brood-rearing. The number of hot days and rabbit abundance were also significant in a model predicting eagle brood size at fledging. Both success and brood size were positively related to jackrabbit abundance and inversely related to the frequency of hot days in spring. 6. Eagle reproduction was limited by rabbit abundance during approximately twothirds of the years studied. Weather influenced how severely eagle reproduction declined in those years. 7. This study demonstrates that prey and weather can interact to limit a large raptor population's productivity. Smaller raptors could be affected more strongly, especially in colder or wetter climates.

Journal of Animal Ecology↗

USGS1989

Breeding canvasbacks: a test of a habitat model

Schroeder (1984) proposed a habitat suitability model for breeding canvasbacks (Aythya valisineria) based on the size, water regime, and emergent vegetation of wetlands. We evaluated the model with data from surveys of canvasbacks on 2265 wetlands in North Dakota, South Dakota, and Minnesota. The model proved inadequate as a predictor of canvasback pair density; the correlation between values produced by the model and canvasback pair densities was r = 0.0023 (P = 0.911). There were, however, suggestions of (1) higher canvasback density and frequency of occurrence on wetlands with more open interiors, and (2) a relation between canvasback density and wetland size that varied according to wetland permanence. We recommend that the model be improved by testing these relations, and possibly by incorporating determinants of water quality or pondweed (Potamogeton spp.) occurrence.

Prairie Naturalist↗