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K.P. Burnham

Publications and source records attributed to K.P. Burnham.

At least 19 recordsLinked to original sources
USGS2010

Evaluation of some random effects methodology applicable to bird ringing data

Existing models for ring recovery and recapture data analysis treat temporal variations in annual survival probability (S) as fixed effects. Often there is no explainable structure to the temporal variation in S1,..., Sk; random effects can then be a useful model: Si = E(S) + ??i. Here, the temporal variation in survival probability is treated as random with average value E(??2) = ??2. This random effects model can now be fit in program MARK. Resultant inferences include point and interval estimation for process variation, ??2, estimation of E(S) and var (E??(S)) where the latter includes a component for ??2 as well as the traditional component for v??ar(S??\S??). Furthermore, the random effects model leads to shrinkage estimates, Si, as improved (in mean square error) estimators of Si compared to the MLE, S??i, from the unrestricted time-effects model. Appropriate confidence intervals based on the Si are also provided. In addition, AIC has been generalized to random effects models. This paper presents results of a Monte Carlo evaluation of inference performance under the simple random effects model. Examined by simulation, under the simple one group Cormack-Jolly-Seber (CJS) model, are issues such as bias of ??s2, confidence interval coverage on ??2, coverage and mean square error comparisons for inference about Si based on shrinkage versus maximum likelihood estimators, and performance of AIC model selection over three models: Si ??? S (no effects), Si = E(S) + ??i (random effects), and S1,..., Sk (fixed effects). For the cases simulated, the random effects methods performed well and were uniformly better than fixed effects MLE for the Si.

Journal of Applied Statistics↗
USGS2009

Model selection bias and Freedman's paradox

In situations where limited knowledge of a system exists and the ratio of data points to variables is small, variable selection methods can often be misleading. Freedman (Am Stat 37:152-155, 1983) demonstrated how common it is to select completely unrelated variables as highly "significant" when the number of data points is similar in magnitude to the number of variables. A new type of model averaging estimator based on model selection with Akaike's AIC is used with linear regression to investigate the problems of likely inclusion of spurious effects and model selection bias, the bias introduced while using the data to select a single seemingly "best" model from a (often large) set of models employing many predictor variables. The new model averaging estimator helps reduce these problems and provides confidence interval coverage at the nominal level while traditional stepwise selection has poor inferential properties. ?? The Institute of Statistical Mathematics, Tokyo 2009.

Annals of the Institute of Statistical Mathematics↗
USGS2009

Estimating the encounter rate variance in distance sampling

The dominant source of variance in line transect sampling is usually the encounter rate variance. Systematic survey designs are often used to reduce the true variability among different realizations of the design, but estimating the variance is difficult and estimators typically approximate the variance by treating the design as a simple random sample of lines. We explore the properties of different encounter rate variance estimators under random and systematic designs. We show that a design-based variance estimator improves upon the model-based estimator of Buckland et al. (2001, Introduction to Distance Sampling. Oxford: Oxford University Press, p. 79) when transects are positioned at random. However, if populations exhibit strong spatial trends, both estimators can have substantial positive bias under systematic designs. We show that poststratification is effective in reducing this bias. ?? 2008, The International Biometric Society.

Biometrics↗
USGS2009

A generalized mixed effects model of abundance for mark-resight data when sampling is without replacement

In recent years, the mark-resight method for estimating abundance when the number of marked individuals is known has become increasingly popular. By using field-readable bands that may be resighted from a distance, these techniques can be applied to many species, and are particularly useful for relatively small, closed populations. However, due to the different assumptions and general rigidity of the available estimators, researchers must often commit to a particular model without rigorous quantitative justification for model selection based on the data. Here we introduce a nonlinear logit-normal mixed effects model addressing this need for a more generalized framework. Similar to models available for mark-recapture studies, the estimator allows a wide variety of sampling conditions to be parameterized efficiently under a robust sampling design. Resighting rates may be modeled simply or with more complexity by including fixed temporal and random individual heterogeneity effects. Using information theory, the model(s) best supported by the data may be selected from the candidate models proposed. Under this generalized framework, we hope the uncertainty associated with mark-resight model selection will be reduced substantially. We compare our model to other mark-resight abundance estimators when applied to mainland New Zealand robin (Petroica australis) data recently collected in Eglinton Valley, Fiordland National Park and summarize its performance in simulation experiments.

Book chapter↗
USGS2007

Line transect estimation of population size: the exponential case with grouped data

Gates, Marshall, and Olson (1968) investigated the line transect method of estimating grouse population densities in the case where sighting probabilities are exponential. This work is followed by a simulation study in Gates (1969). A general overview of line transect analysis is presented by Burnham and Anderson (1976). These articles all deal with the ungrouped data case. In the present article, an analysis of line transect data is formulated under the Gates framework of exponential sighting probabilities and in the context of grouped data.

Communications in Statistics - Theory and Methods↗
USGS2007

Concerns regarding a call for pluralism of information theory and hypothesis testing

1. Stephens et al. (2005) argue for 'pluralism' in statistical analysis, combining null hypothesis testing and information-theoretic (I-T) methods. We show that I-T methods are more informative even in single variable problems and we provide an ecological example. 2. I-T methods allow inferences to be made from multiple models simultaneously. We believe multimodel inference is the future of data analysis, which cannot be achieved with null hypothesis-testing approaches. 3. We argue for a stronger emphasis on critical thinking in science in general and less reliance on exploratory data analysis and data dredging. Deriving alternative hypotheses is central to science; deriving a single interesting science hypothesis and then comparing it to a default null hypothesis (e.g. 'no difference') is not an efficient strategy for gaining knowledge. We think this single-hypothesis strategy has been relied upon too often in the past. 4. We clarify misconceptions presented by Stephens et al. (2005) . 5. We think inference should be made about models, directly linked to scientific hypotheses, and their parameters conditioned on data, Prob(Hj| data). I-T methods provide a basis for this inference. Null hypothesis testing merely provides a probability statement about the data conditioned on a null model, Prob(data |H0). 6. Synthesis and applications . I-T methods provide a more informative approach to inference. I-T methods provide a direct measure of evidence for or against hypotheses and a means to consider simultaneously multiple hypotheses as a basis for rigorous inference. Progress in our science can be accelerated if modern methods can be used intelligently; this includes various I-T and Bayesian methods.

Journal of Applied Ecology↗
USGS2007

Some comments on Anderson and Pospahala's correction of bias in line transect sampling

ANDERSON and POSPAHALA (1970) investigated the estimation of wildlife population size using the belt or line transect sampling method and devised a correction for bias, thus leading to an estimator with interesting characteristics. This work was given a uniform mathematical framework in BURNHAM and ANDERSON (1976). In this paper we show that the ANDERSON-POSPAHALA estimator is optimal in the sense of being the (unique) best linear unbiased estimator within the class of estimators which are linear combinations of cell frequencies, provided certain assumptions are met.

Biometrical Journal↗
USGS2006

A robust design mark-resight abundance estimator allowing heterogeneity in resighting probabilities

This article introduces the beta-binomial estimator (BBE), a closed-population abundance mark-resight model combining the favorable qualities of maximum likelihood theory and the allowance of individual heterogeneity in sighting probability (p). The model may be parameterized for a robust sampling design consisting of multiple primary sampling occasions where closure need not be met between primary occasions. We applied the model to brown bear data from three study areas in Alaska and compared its performance to the joint hypergeometric estimator (JHE) and Bowden's estimator (BOWE). BBE estimates suggest heterogeneity levels were non-negligible and discourage the use of JHE for these data. Compared to JHE and BOWE, confidence intervals were considerably shorter for the AICc model-averaged BBE. To evaluate the properties of BBE relative to JHE and BOWE when sample sizes are small, simulations were performed with data from three primary occasions generated under both individual heterogeneity and temporal variation in p. All models remained consistent regardless of levels of variation in p. In terms of precision, the AICc model-averaged BBE showed advantages over JHE and BOWE when heterogeneity was present and mean sighting probabilities were similar between primary occasions. Based on the conditions examined, BBE is a reliable alternative to JHE or BOWE and provides a framework for further advances in mark-resight abundance estimation. ?? 2006 American Statistical Association and the International Biometric Society.

Journal of Agricultural, Biological, and Environme↗
USGS2006

Comment on 'Are survival rates for northern spotted owls biased?'

Loehle et al. recently estimated survival rates from radio-telemetered northern spotted owls (Strix occidentalis caurina (Merriam, 1898)) and suggested that survival rates estimated for this species from capture-recapture studies were negatively biased, which subsequently resulted in the negatively biased estimates of rates of population change (lambda) reported by Anthony et al. (Wildl. Monogr. No. 163, pp. 1-47 (2006)). We argue that their survival estimates were inappropriate for comparison with capture-recapture estimates because (i) the manner in which they censored radio-telemetered individuals had the potential to positively bias their survival estimates, (ii) their estimates of survival were not valid for evaluating bias, and (iii) the size and distribution of their radiotelemetry study areas were sufficiently different from capture-recapture study areas to preclude comparisons. In addition, their inferences of negative bias in rates of population change estimated by Anthony et al. were incorrect and reflected a misunderstanding about those estimators.

Canadian Journal of Zoology↗
USGS2006

Status and trends in demography of northern spotted owls, 1985-2003

We analyzed demographic data from northern spotted owls (Strix occidentalis caurina) from 14 study areas in Washington, Oregon, and California for 1985-2003. The purpose of our analyses was to provide an assessment of the status and trends of northern spotted owl populations throughout most of their geographic range. The 14 study areas made up approximately 12% of the range of the subspecies and included federal, tribal, private, and mixed federal and private lands. The study areas also included all the major forest types that the subspecies inhabits. The analyses followed rigorous protocols that were developed a priori and were the result of extensive discussions and consensus among the authors. Our primary objectives were to estimate fecundity, apparent survival (??), and annual rate of population change (??) and to determine if there were any temporal trends in these population parameters. In addition to analyses of data from individual study areas, we conducted 2 meta-analyses on each demographic parameter. One meta-analysis was conducted on all 14 areas, and the other was restricted to the 8 areas that constituted the Effectiveness Monitoring Plan for northern spotted owls under the Northwest Forest Plan. The average number of years of reproductive data per study area was 14 (range = 5-19), and the average number of recapture occasions per study area was 13 (range = 4-18). Only 1 study area had <12 years of data. Our results were based on 32,054 captures and resightings of 11,432 banded individuals for estimation of survival and 10,902 instances in which we documented the number of young produced by territorial females. The number of young fledged (NYF) per territorial female was analyzed by testing a suite of a priori models that included (1) effects of age, (2) linear or quadratic time trends, (3) presence of barred owls (Strix varia) in spotted owl territories, and (4) an even-odd year effect. The NYF varied among years on most study areas with a biennial cycle of high reproduction in even-numbered years and low reproduction in odd-numbered years. These cyclic fluctuations did not occur on all study areas, and the even-odd year effect waned during the last 5 years of the study. Fecundity was highest for adults (x??=0.372, SE=0.029), lower for 2-year-olds (x??=0.208, SE=0.032), and very low for 1-year-olds (x??=0.074, SE = 0.029). Fecundity was stable over time for 6 areas (Rainier, Olympic, Warm Springs, H. J. Andrews, Klamath, and Marin), declining for 6 areas (Wenatchee, Cle Elum, Oregon Coast Range, Southern Oregon Cascades, Northwest California, and Simpson), and slightly increasing for 2 areas (Tyee, Hoopa). We found little association between NYF and the proportion of northern spotted owl territories where barred owls were detected, although results were suggestive of a negative effect of barred owls on the Wenatchee and Olympic study areas. The meta-analysis on fecundity indicated substantial annual variability with no increasing or decreasing trends. Fecundity was highest in the mixed-conifer region of eastern Washington (x??=0.560, SE=0.041) and lowest in the Douglas-fir (Pseudotsuga menziesii) region of the Oregon coast (x??=0.306, SE=0.039). We used Cormack-Jolly-Seber open population models and Program MARK to estimate apparent survival rates of owls >1 year old. We found no differences in apparent survival rates between sexes except for 1 area (Marin), which had only 6 years of data. Estimates of apparent survival from individual study areas indicated that there were differences among age classes with adults generally having higher survival than 1- and 2-year-olds. Apparent survival rates ranged from 0.750 (SE=0.026) to 0.886 (SE=0.010) for adults, 0.626 (SE=0.073) to 0.886 (SE=0.010) for 2-year-olds, and 0.415 (SE=0.111) to 0.860 (SE=0.017) for 1-year-olds. These estimates were comparable to survival rates from previous studies on the subspecies. We found evidence for negative time trends in survival rate

Wildlife Monographs↗
USGS2005

Evaluation of trapping-web designs

The trapping web is a method for estimating the density and abundance of animal populations. A Monte Carlo simulation study is performed to explore performance of the trapping web for estimating animal density under a variety of web designs and animal behaviours. The trapping performs well when animals have home ranges, even if the home ranges are large relative to trap spacing. Webs should contain at least 90 traps. Trapping should continue for 5-7 occasions. Movement rates have little impact on density estimates when animals are confined to home ranges. Estimation is poor when animals do not have home ranges and movement rates are rapid. The trapping web is useful for estimating the density of animals that are hard to detect and occur at potentially low densities. ?? CSIRO 2005.

Wildlife Research↗
USGS2005

Human land use influences chronic wasting disease prevalence in mule deer

Human alteration of landscapes can affect the distribution, abundance, and behavior of wildlife. We explored the effects of human land use on the prevalence of chronic wasting disease (CWD) in mule deer (Odocoileus hemionus) populations residing in north-central Colorado. We chose best approximating models estimating CWD prevalence in relation to differences in human land use, sex, and geographic location. Prevalence was higher in developed areas and among male deer, suggesting anthropogenic influences on the occurrence of disease. We also found a relatively high degree of variation in prevalence across the three study sites, suggesting that spatial patterns in disease may be influenced by other factors operating at a broader, landscape scale. Our results suggest that multiple factors, including changes in land use, differences in exposure risk between sexes, and landscape-scaled heterogeneity, are associated with CWD prevalence in north-central Colorado.

Ecological Applications↗
USGS2004

A goodness-of-fit test for capture-recapture model Mt under closure

A new, fully efficient goodness-of-fit test for the time-specific closed-population capture-recapture model M t is presented. This test is based on the residual distribution of the capture history data given the maximum likelihood parameter estimates under model M t , is partitioned into informative components, and is based on chi-square statistics. Comparison of this test with Leslie's test (Leslie, 1958, Journal of Animal Ecology , 27 , 84–86) for model M t , using Monte Carlo simulations, shows the new test generally outperforms Leslie's test. The new test is frequently computable when Leslie's test is not, has Type I error rates that are closer to nominal error rates than Leslie's test, and is sensitive to behavioral variation and heterogeneity in capture Probabilities. Leslie's test is not sensitive to behavioral variation in capture probabilities but, when computable, has greater power to detect heterogeneity than the new test.

Biometrics↗
USGS2004

Estimating survival probabilities of unmarked dependent young when detection is imperfect

We present a capture–recapture modeling approach to the estimation of survival probability of dependent chicks when only the attending adult bird is marked. The model requires that the bird's nest is found prior to hatching and that the number of eggs that hatch are counted. Subsequent data are sightings of the marked adult and a count of chicks with the adult. The model allows for imperfect detection of chicks, but the number of chicks can never exceed the number of eggs in the nest (i.e., adults cannot adopt chicks). We use data from radio-tagged adult Mountain Plovers ( Charadrius montanus ) and their unmarked chicks as an example. We present the model in terms of precocial bird species, but the method extends to many other taxa.

The Condor↗
USGS2004

Goals and strategies for estimating trends in landbird abundance

Reliable estimates of trends in population size are critical to effective management of landbirds. We propose a standard for considering that landbird populations are adequately monitored: 80% power to detect a 50% decline occuning within 20 years, using a 2-tailed test and a significance level of 0.10, and incorporating effects of potential bias. Our standard also requires that at least two-thirds of the target region be covered by the monitoring program. We recommend that the standard be achieved for species' entire ranges or for any area one-third the size of the temperate portions of Canada and the United States, whichever is smaller. We applied our approach to North American Breeding Bird Survey (BBS) data. At present, potential annual bias for the BBS is estimated at ??0.008. Further, the BBS achieves the monitoring standard for only about 42% of landbirds for which the BBS is considered the most effective monitoring approach. Achieving the proposed monitoring target for ???80% of these species would require increasing the number of BBS - or similar survey - routes by several-fold, a goal that probably is impractical. We suggest several methods for reducing potential bias and argue that if our methods are implemented, potential bias would fall to ??0.003. The required number of BBS or similar routes would then be 5,106, about 40% more than in the current BBS program. Most of the needed increases are in 15 states or provinces. Developing a comprehensive land-bird monitoring program will require increased support for coordination of the BBS (currently 2 people) and new programs for species that are poorly covered at present. Our results provide a quantitative goal for long-term land-bird monitoring and identify the sample sizes needed, within each state and province, to achieve the monitoring goal for most of the roughly 300 landbird species that are well suited to monitoring with the BBS and similar surveys.

Journal of Wildlife Management↗