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David L. Otis

Publications and source records attributed to David L. Otis.

25 records · Page 2Linked to original sources

Analysis of the influence of spatial pattern in habitat selection studies

Design and analysis of wildlife habitat selection studies typically do not assess the effect of spatial pattern on the habitat selection process. Effects of landscape scale pattern on habitat selection cannot be accomplished without replicate study areas, because pattern is a single, albeit multifaceted, attribute of an area. For a single area, however, the influence of pattern-related characteristics, such as shape and edge shared with adjacent patches, can be estimated by using GLIM (McCullough and Neider 1983) procedures to model patch-specific frequency counts of animal use as a function of these parameters. This approach is evaluated and illustrated with simulated breeding-bird counts in a South Carolina study area for which a GIS land cover classification is available. A related technique for evaluating whether movement from patch to patch is selective is developed and illustrated for designs that involve collection of trajectory data from monitored individuals. These designs and analyses are feasible given current GIS and GPS technology. Statistical inferences from habitat selection studies should be interpreted within the context of a range of scales at which animals differentiate between patch attributes.

Journal of Agricultural, Biological, and Environme

Population demographics of two local South Carolina mourning dove populations

The mourning dove ( Zenaida macroura ) call-count index had a significant (P < 0.01) negative trend in South Carolina and the Eastern Management Unit (EMU) during 1988-97. We initiated a banding study in 2 areas in the Coastal Plain of South Carolina to estimate population demographic parameters of doves to generate hypotheses that address the purported population declines. During 1992-96, we banded >2,300 doves and examined >6,000 individuals during harvest bag checks. An age-specific band recovery model with time- and area-specific recovery rates, and constant survival rates, was chosen for estimation via Akaike's Information Criterion (AIC), likelihood ratio, and goodness-of-fit criteria. After-hatching-year (AHY) annual survival rate was 0.359 (SE = 0.056), and hatching-year (HY) annual survival rate was 0.118 (SE = 0.042). Average estimated recruitment per adult female into the prehunting season population was 3.40 (SE = 1.25) and 2.32 (SE = 0.46) for the 2 study areas. Our movement data support earlier hypotheses of nonmigratory breeding and harvested populations in South Carolina. Low survival rates and estimated population growth rate in the study areas may be representative only of small-scale areas that are heavily managed for dove hunting. Source-sink theory was used to develop a model of region-wide populations that is composed of source areas with positive growth rates and sink areas of declining growth. We suggest management of mourning doves in the Southeast might benefit from improved understanding of local population dynamics, as opposed to regional-scale population demographics.

South Carolina

Analysis of habitat selection studies with multiple patches within cover types

Current statistical methods are inadequate for evaluation of the relation between spatial pattern of the landscape and observed patterns of habitat use by individuals or populations. For example, traditional habitat selection analysis methods do not use information about the size and distribution of the several patches of each cover type that may exist within the study area. Statistical tests are presented for hypotheses about disproportional use of cover types and patches within cover types. These tests require that use of individual patches is recorded, as well as the size of individual patches. Different designs are considered in which there are (1) single or multiple samples of use, and (2) equal or unequal habitat availability. Formulas for calculating Type II statistical errors of the tests are presented and Monte Carlo simulation is used to assess the accuracy of the formulas and to check the Type I error rates of the proposed test statistics. With adequate sample sizes, Type II error formulas can be a useful tool for planning of habitat selection studies. An example analysis is presented of a hypothetical study of habitat selection by ring-necked pheasants ( Phasianus colchicus ) in a Midwestern landscape. The proposed tests also represent a contribution toward bringing together concepts of landscape ecology and wildlife habitat selection.

Journal of Wildlife Management

Density estimation of small-mammal populations using a trapping web and distance sampling methods

Distance sampling methodology is adapted to enable animal density (number per unit of area) to be estimated from capture-recapture and removal data. A trapping web design provides the link between capture data and distance sampling theory. The estimator of density is D = M t+1 f(0) , where M t+1 is the number of individuals captured and f(0) is computed from the M t+1 distances from the web center to the traps in which those individuals were first captured. It is possible to check qualitatively the critical assumption on which the web design and the estimator are based. This is a conceptual paper outlining a new methodology, not a definitive investigation of the best specific way to implement this method. Several alternative sampling and analysis methods are possible within the general framework of distance sampling theory; a few alternatives are discussed and an example is given.

Ecology

Capture-recapture and removal methods for sampling closed populations

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.

Report

Statistical inference from capture data on closed animal populations

The estimation of animal abundance is an important problem in both the theoretical and applied biological sciences. Serious work to develop estimation methods began during the 1950s, with a few attempts before that time. The literature on estimation methods has increased tremendously during the past 25 years (Cormack 1968, Seber 1973). However, in large part, the problem remains unsolved. Past efforts toward comprehensive and systematic estimation of density (D) or population size (N) have been inadequate, in general. While more than 200 papers have been published on the subject, one is generally left without a unified approach to the estimation of abundance of an animal population This situation is unfortunate because a number of pressing research problems require such information. In addition, a wide array of environmental assessment studies and biological inventory programs require the estimation of animal abundance. These needs have been further emphasized by the requirement for the preparation of Environmental Impact Statements imposed by the National Environmental Protection Act in 1970. This publication treats inference procedures for certain types of capture data on closed animal populations. This includes multiple capture-recapture studies (variously called capture-mark-recapture, mark-recapture, or tag-recapture studies) involving livetrapping techniques and removal studies involving kill traps or at least temporary removal of captured individuals during the study. Animals do not necessarily need to be physically trapped; visual sightings of marked animals and electrofishing studies also produce data suitable for the methods described in this monograph. To provide a frame of reference for what follows, we give an exampled of a capture-recapture experiment to estimate population size of small animals using live traps. The general field experiment is similar for all capture-recapture studies (a removal study is, of course, slightly different). A typical field experiment is the following: a number of traps are positioned in the area to be studied, say 144 traps in a 12 X 12 grid, 7 m apart. At the beginning of the study (j=1) a sample size of n 1 is taken from the population, the animals are tagged and marked for future identification, and then returned to the population, usually at the same point where they were trapped. After allowing time of the marked and unmarked animals to mix, a second sample (j=2, often the following day) or n 2 animals is then taken.the second sample normally contains both marked and unmarked animals. The unmarked animals are marked and all captured animals are released back into the population. This procedure continues for t periods where t ≥ 2. The animals should be marked in such a way that the capture-recapture history of each animal caught during the study is known. In practice, toes are often clipped to uniquely identify individual animals (Taber and Cowan 1969) or serially numbered tags are sometimes used on larger animals. Such capture studies are classified by 2 schemes that are directly related to what class of models are appropriate and what parameters can be estimated. The first classification addresses the subject of closure. Closure usually means the size of the population is constant over the priod of investigation, i.e., no recruitment (birth or immigration) or losses (death or emigration). This is a strong assumption and, of course, never completely true in a natural biological population. For greater generality, we define closure to mean there are no unknown changes to the initial population. In practice, this means known losses (trap death), or deliberate removals) do not violate our definition of closure. If the study is properly designed, closure can be met at least approximately. Open or nonclosed populations explicitly allow for one or more types of recruitment or losses to operate during the course of the experiment (Jolly 1965, Seber 1965, Robson 1969, Pollock 1975). Only closed populations will be considered in this monograph. The second classification depends on the type of data collected with 2 possibilities occurring (Pollock 1974, unpublished doctoral dissertation, Cornell University, Ithaca, New York): (1) only information on the recovery of marked animals is available for each sampling occasion, j, j=1, 2, ... t. (2) information on both marked and unmarked animals is available for each sampling occasion, j, j=1, 2, ... t. In case (1), population size (N) is not identifiable, however, other parameters can be estimated (Brownie et al. 1978). In case (2), N can be estimated using a wide variety of approaches depending upon what we wish to assume. Only case (2) will be dealt with here.

Wildlife Monographs