Field methods and statistical analyses for monitoring small salmonid streams
Explore the source record for details and available documents.
Geology topics
Publications and source records attributed to Kenneth P. Burnham.
Explore the source record for details and available documents.
In 1975, 3.2 km of Summit Creek, Idaho were fenced by the Bureau of Land Management to exclude livestock from the riparian area. Six stream sections were electrofished in 1979 to determine differences in trout abundance, size, and growth between grazed and ungrazed stream sections. Electrofishing stations were paired by habitat type. There were more trout in ungrazed sections than in grazed sections in all three habitat types sampled. With one exception, there were more catachable-sized (200 mm long or longer) rainbow trout (Salmo gairdneri) and brook trout (Salvelinus fontinalis) in the ungrazed area than in the grazed area. There was also evidence that the average size of the fish was less in grazed sections. Fish population data were not collected prior to fencing; therefore, it cannot be firmly concluded that the trout population increased within the livestock enclosure as a result of fencing the riparian area. However, the combined results of previous trout habitat improvements documented for Summit Creek, as a result of the fencing, and this study support the conclusion that trout prefer stream areas in ungrazed habitat over grazed habitat.
The asymptotic mean and error mean square are determined for the nonparametric estimator of plant density by distance sampling proposed by Patil, Burnham and Kovner (1979, Biometrics 35 , 597-604. On the basis of these formulae, a bias-reduced version of this estimator is given, and its specific form is determined which gives minimum mean square error under varying assumptions about the true probability density function of the sampled data. Extension is given to line-transect sampling.
The problem of estimating animal abundance is common in wildlife management and environmental impact asessment. Capture-recapture and removal methods are often used to estimate population size. Statistical Inference From Capture Data On Closed Animal Populations, a monograph by Otis et al. (1978), provides a comprehensive synthesis of much of the wildlife and statistical literature on the methods, as well as some extensions of the general theory. In our primer, we focus on capture-recapture and removal methods for trapping studies in which a population is assumed to be closed and do not treat open-population models, such as the Jolly-Seber model, or catch-effort methods in any detail. The primer, written for students interested in population estimation, is intended for use with the more theoretical monograph.
Use and interpretation of statistics in wildlife journals are reviewed, and suggestions for improvement are offered. Populations from which inferences are to be drawn should be clearly defined, and conclusions should be limited to the range of the data analyzed. Authors should be careful to avoid improper methods of plotting data and should clearly define the use of estimates of variance, standard deviation, standard error, or confidence intervals. Biological and statistical significant are often confused by authors and readers. Statistical hypothesis testing is a tool, and not every question should be answered by hypothesis testing. Meeting assumptions of hypothesis tests is the responsibility of authors, and assumptions should be reviewed before a test is employed. The use of statistical tools should be considered carefully both before and after gathering data.
Explore the source record for details and available documents.
No abstract available.
Recently, Roseberry (1979) attempted to (1) clarify the theoretical basis for harvesting bobwhite ( Colinus virginianus ), (2) assess the impact of varying intensities of harvest on standing densities and long-term yields, and (3) define a harvest strategy appropriate for the bobwhite resource in Illinois. That paper, based on 24 years of field data, unfortunately contains 2 methodological or conceptual errors that are fundamental to the three objectives. Both errors are subtle, and as other have made the same or similar errors in analysis, we identify the problems in a way we hope will be taken constructively.
No abstract available.
Brownie et al. (U.S. Fish and Wildl. Serv., Resource Publ. 131, 1978) presented 14 models based on an array of explicit assumptions for the study of survival in avian populations. These methods are replacing the life table methods previously used to estimate survival rates (e.g., Burnham and Anderson, J. Wildl. Manage. , 43: 356-366, 1979). The new methods allow survival or recovery rates, or both, to be constant, time-specific, or time- and age-specific. In studies to estimate survival rates for birds the data are often from recoveries of birds shot or found dead during the hunting season and reported to the Bird Banding Laboratory by sportsmen, conservation agency employees, or the general public. This note examines the bias in estimating annual survival due to a proportion of the recoveries being incorrectly reported a year late. Specifically, a few recoveries each year of, for example, adult male American Widgeon ( Anas americana ) banded in California are reported as being recovered in year i + 1 when in fact they were actually recovered the previous year i. Delayed reporting might typically be caused by people finding a band in their health clothing in the fall of the year and, being embarrassed about their failure to report the band when it was taken, report it a year late not mentioning the actual year of recovery. Heuristically, delayed reporting should bias estimated annual survival rates upwards because it appears from the data that the birds corresponding to the "delayed" recoveries actually lived an additional year.
Banding has proven to be a useful technique in the study of population dynamics of avian species. However, band loss has long been recognized as a potential problem, (Hickey, 1952; Ludwig, 1967). Recently, Brownie et al. (1978) presented 14 models based on an array of explicit assumptions for the analysis of band recovery data. Various estimation models (assumption sets) allowed survival and/or recovery rates to be (a) constant, (b) time-specific, or (c) time- and age-specific. Optimal inference methods were employed and statistical tests of critical assumptions were developed and emphasized. The methods of Brownie et al. (1978), as with all previously published methods of which we are aware, assume no loss of bands during the study. However, some band loss is certain to occur and this potentially biases the estimates of annual survival rates whatever the analysis method. A few empirical studies have estimated band loss rates (a notable exception is Ludwig, 1967); consequently, for almost all band recovery data, the exact rate of band loss is unknown. In this paper we investigate the bias in estimates of annual survival rates due to varying degrees of hypothesized band loss. Our main results are based on perhaps the most useful model, originally developed by Seber (1970), for estimation of annual survival rate. Inferences are made concerning the bias of estimated survival rates in other models because the structure of these estimators is similar.
The Hayne model for line transect sampling is generalized by using an elliptical (rather than circular) flushing model for animal detection. By assuming the ration of major and minor axes lengths is constant for all animals, a model results which allows estimation of population density based directly upon sighting distances and sighting angles. The derived estimator of animal density is a generalization of the Hayne estimator for line transect sampling.
For the past 25 years estimation of mortality rates for waterfowl has been based almost entirely on the composite dynamic life table. We examined the specific assumptions for this method and derived a valid goodness of fit test. We performed this test on 45 data sets representing a cross section of banded sampled for various waterfowl species, geographic areas, banding periods, and age/sex classes. We found that: (1) the composite dynamic method was rejected (P <0.001) in 37 of the 45 data sets (in fact, 29 were rejected at P <0.00001) and (2) recovery and harvest rates are year-specific (a critical violation of the necessary assumptions). We conclude that the restrictive assumptions required for the composite dynamic method to produce valid estimates of mortality rates are not met in waterfowl data. Also we demonstrate that even when the required assumptions are met, the method produces very biased estimates of age-specific mortality rates. We believe the composite dynamic method should not be used in the analysis of waterfowl banding data. Furthermore, the composite dynamic method does not provide valid evidence for age-specific mortality rates in waterfowl.
Line transect sampling often provides a practical way to approach estimation of wildlife population density (Seber 1973, Eberhardt 1978). Burnham and Anderson (1976) provided a general framework for the estimation of animal density from line transect data, and many specific analytical methods have been proposed in the literature. Numerous persons are researching methods of statistical analysis for line transect data; however, little consideration has been given to specifying criteria for "good" methods of line transect estimation. We present here some criteria which we believe line transect estimators should satisfy. We do not deal with the case where objects may move from their initial location before being detected.
Explore the source record for details and available documents.