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W. L. Kendall

Publications and source records attributed to W. L. Kendall.

At least 37 records · Page 2Linked to original sources
USGS2005

Estimating the number of animals in wildlife populations

INTRODUCTION In 1938, Howard M. Wight devoted 9 pages, which was an entire chapter in the first wildlife management techniques manual, to what he termed 'census' methods. As books and chapters such as this attest, the volume of literature on this subject has grown tremendously. Abundance estimation remains an active area of biometrical research, as reflected in the many differences between this chapter and the similar contribution in the previous manual. Our intent in this chapter is to present an overview of the basic and most widely used population estimation techniques and to provide an entree to the relevant literature. Several possible approaches could be taken in writing a chapter dealing with population estimation. For example, we could provide a detailed treatment focusing on statistical models and on derivation of estimators based on these models. Although a chapter using this approach might provide a valuable reference for quantitative biologists and biometricians, it would be of limited use to many field biologists and wildlife managers. Another approach would be to focus on details of actually applying different population estimation techniques. This approach would include both field application (e.g., how to set out a trapping grid or conduct an aerial survey) and detailed instructions on how to use the resulting data with appropriate estimation equations. We are reluctant to attempt such an approach, however, because of the tremendous diversity of real-world field situations defined by factors such as the animal being studied, habitat, available resources, and because of our resultant inability to provide detailed instructions for all possible cases. We believe it is more useful to provide the reader with the conceptual basis underlying estimation methods. Thus, we have tried to provide intuitive explanations for how basic methods work. In doing so, we present relevant estimation equations for many methods and provide citations of more detailed treatments covering both statistical considerations and field applications. We have chosen to present methods that are representative of classes of estimators, rather than address every available method. Our hope is that this chapter will provide the reader with enough background to make an informed decision about what general method(s) will likely perform well in any particular field situation. Readers with a more quantitative background may then be able to consult detailed references and tailor the selected method to suit their particular needs. Less quantitative readers should consult a biometrician, preferably one with experience in wildlife studies, for this 'tailoring,' with the hope they will be able to do so with a basic understanding of the general method, thereby permitting useful interaction and discussion with the biometrician. SUMMARY Estimating the abundance or density of animals in wild populations is not a trivial matter. Virtually all techniques involve the basic problem of estimating the probability of seeing, capturing, or otherwise detecting animals during some type of survey and, in many cases, sampling concerns as well. In the case of indices, the detection probability is assumed to be constant (but unknown). We caution against use of indices unless this assumption can be verified for the comparison(s) of interest. In the case of population estimation, many methods have been developed over the years to estimate the probability of detection associated with various kinds of count statistics. Techniques range from complete counts, where sampling concerns often dominate, to incomplete counts where detection probabilities are also important. Some examples of the latter are multiple observers, removal methods, and capture-recapture. Before embarking on a survey to estimate the size of a population, one must understand clearly what information is needed and for what purpose the information will be used. The key to derivin

Book chapter↗
USGS2004

Combining band recovery data and Pollock's robust design to model temporary and permanent emigration

Capture-recapture models are widely used to estimate demographic parameters of marked populations. Recently, this statistical theory has been extended to modeling dispersal of open populations. Multistate models can be used to estimate movement probabilities among subdivided populations if multiple sites are sampled. Frequently, however, sampling is limited to a single site, Models described by Burnham (1993, in Marked Individuals in the Study of Bird Populations , 199–213), which combined open population capture-recapture and band-recovery models, can be used to estimate permanent emigration when sampling is limited to a single population. Similarly, Kendall, Nichols, and Hines (1997, Ecology 51 , 563–578) developed models to estimate temporary emigration under Pollock's (1982, Journal of Wildlife Management 46 , 757–760) robust design. We describe a likelihood-based approach to simultaneously estimate temporary and permanent emigration when sampling is limited to a single population. We use a sampling design that combines the robust design and recoveries of individuals obtained immediately following each sampling period. We present a general form for our model where temporary emigration is a first-order Markov process, and we discuss more restrictive models. We illustrate these models with analysis of data on marked Canvasback ducks. Our analysis indicates that probability of permanent emigration for adult female Canvasbacks was 0.193 ( ) and that birds that were present at the study area in year i — 1 had a higher probability of presence in year i than birds that were not present in year i — 1.

Biometrics↗
USGS2004

On the estimation of dispersal and movement of birds

The estimation of dispersal and movement is important to evolutionary and population ecologists, as well as to wildlife managers. We review statistical methodology available to estimate movement probabilities. We begin with cases where individual birds can be marked and their movements estimated with the use of multisite capture-recapture methods. Movements can be monitored either directly, using telemetry, or by accounting for detection probability when conventional marks are used. When one or more sites are unobservable, telemetry, band recoveries, incidental observations, a closed- or open-population robust design, or partial determinism in movements can be used to estimate movement. When individuals cannot be marked, presence-absence data can be used to model changes in occupancy over time, providing indirect inferences about movement. Where abundance estimates over time are available for multiple sites, potential coupling of their dynamics can be investigated using linear cross-correlation or nonlinear dynamic tools.

Condor↗
USGS2004

Estimating survival and breeding probability for pond-breeding amphibians: a modified robust design

Many studies of pond-breeding amphibians involve sampling individuals during migration to and from breeding habitats. Interpreting population processes and dynamics from these studies is difficult because (1) only a proportion of the population is observable each season, while an unknown proportion remains unobservable (e.g., non-breeding adults) and (2) not all observable animals are captured. Imperfect capture probability can be easily accommodated in capture-recapture models, but temporary transitions between observable and unobservable states, often referred to as temporary emigration, is known to cause problems in both open- and closed-population models. We develop a multistate mark-recapture (MSMR) model, using an open-robust design that permits one entry and one exit from the study area per season. Our method extends previous temporary emigration models (MSMR with an unobservable state) in two ways. First, we relax the assumption of demographic closure (no mortality) between consecutive (secondary) samples, allowing estimation of within-pond survival. Also, we add the flexibility to express survival probability of unobservable individuals (e.g., ‘ ‘non-breeders’ ’ ) as a function of the survival probability of observable animals while in the same, terrestrial habitat. This allows for potentially different annual survival probabilities for observable and unobservable animals. We apply our model to a relictual population of eastern tiger salamanders ( Ambystoma tigrinum tigrinum ). Despite small sample sizes, demographic parameters were estimated with reasonable precision. We tested several a priori biological hypotheses and found evidence for seasonal differences in pond survival. Our methods could be applied to a variety of pond-breeding species and other taxa where individuals are captured entering or exiting a common area (e.g., spawning or roosting area, hibernacula).

Ecology↗
USGS2004

Estimation of sex-specific survival from capture-recapture data when sex is not always known

Many animals lack obvious sexual dimorphism, making assignment of sex difficult even for observed or captured animals. For many such species it is possible to assign sex with certainty only at some occasions; for example, when they exhibit certain types of behavior. A common approach to handling this situation in capture-recapture studies has been to group capture histories into those of animals eventually identified as male and female and those for which sex was never known. Because group membership is dependent on the number of occasions at which an animal was caught or observed (known sex animals, on average, will have been observed at more occasions than unknown-sex animals), survival estimates for known-sex animals will be positively biased, and those for unknown animals will be negatively biased. In this paper, we develop capture-recapture models that incorporate sex ratio and sex assignment parameters that permit unbiased estimation in the face of this sampling problem. We demonstrate the magnitude of bias in the traditional capture-recapture approach to this sampling problem, and we explore properties of estimators from other ad hoc approaches. The model is then applied to capture-recapture data for adult Roseate Terns ( Sterna dougallii ) at Falkner Island, Connecticut, 1993-2002. Sex ratio among adults in this population favors females, and we tested the hypothesis that this population showed sex-specific differences in adult survival. Evidence was provided for higher survival of adult females than males, as predicted. We recommend use of this modeling approach for future capture-recapture studies in which sex cannot always be assigned to captured or observed animals. We also place this problem in the more general context of uncertainty in state classification in multistate capture-recapture models.

Connecticut↗
USGS2004

Evaluating mallard adaptive management models with time series

Wildlife practitioners concerned with midcontinent mallard ( Anas platyrhynchos ) management in the United States have instituted a system of adaptive harvest management (AHM) as an objective format for setting harvest regulations. Under the AHM paradigm, predictions from a set of models that reflect key uncertainties about processes underlying population dynamics are used in coordination with optimization software to determine an optimal set of harvest decisions. Managers use comparisons of the predictive abilities of these models to gauge the relative truth of different hypotheses about density-dependent recruitment and survival, with better-predicting models giving more weight to the determination of harvest regulations. We tested the effectiveness of this strategy by examining convergence rates of 'predictor' models when the true model for population dynamics was known a priori. We generated time series for cases when the a priori model was 1 of the predictor models as well as for several cases when the a priori model was not in the model set. We further examined the addition of different levels of uncertainty into the variance structure of predictor models, reflecting different levels of confidence about estimated parameters. We showed that in certain situations, the model-selection process favors a predictor model that incorporates the hypotheses of additive harvest mortality and weakly density-dependent recruitment, even when the model is not used to generate data. Higher levels of predictor model variance led to decreased rates of convergence to the model that generated the data, but model weight trajectories were in general more stable. We suggest that predictive models should incorporate all sources of uncertainty about estimated parameters, that the variance structure should be similar for all predictor models, and that models with different functional forms for population dynamics should be considered for inclusion in predictor model sets. All of these suggestions should help lower the probability of erroneous learning in mallard ABM and adaptive management in general.

Journal of Wildlife Management↗
USGS2004

Exploitation

Explore the source record for details and available documents.

Book chapter↗
USGS2004

On the use of capture-recapture models in mist-net studies

Capture-recapture models provide a statistical framework for estimating population parameters from mist-net data. Although Cormack-Jolly-Seber and related models have recently been used to estimate survival rates of birds sampled with mist nets, we believe that the full potential for use of capture-recapture models has not been realized by many researchers involved in mist-net studies. We present a brief discussion of the overall framework for estimation using capture-recapture methods, and review several areas in which recent statistical methods can be, but generally have not yet been, applied to mist-net studies. These areas include estimation of (I) rates of movement among areas; (2) survival rates in the presence of transients: (3) population sizes or migrating birds: (4) proportion of birds alive but not present at a breeding site (one definition of proportion of nonbreeding birds in a population): (5) population change and recruitment: and (6) species richness. Using these models will avoid the possible bias associated with use of indices. and provide statistically valid variance estimates and inference.

Book chapter↗
USGS2004

Modeling survival and movement of resident giant Canada goose populations in the Atlantic flyway

Distribution of resident giant Canada geese (Branta canadensis maxima) has changed markedly in the Atlantic Flyway in recent decades. This change may be related to habitat variation or to changes in hunting regulations. We attempt to assess impacts of hunting regulations on survival, movement, and harvest rate of Canada goose populations from Maine to South Carolina. During 15 June-31 July 1991-1995, a total of 20,923 Canada geese were individually marked with unique metal leg bands and rubber neck collars. Capture-recapture, resighting, and recovery data will be used in a multi-state model of Canada goose populations in New England, the Mid-Atlantic, the Chesapeake Region, and the Carolinas. We plan to model annual survival, movement, and harvest rate as a function of harvest regulations while controlling for collar loss. Inferences will be drawn about the effects of harvest regulations on these parameters. Such inferences should be useful in management of resident Canada goose populations throughout the eastern United States.

Book chapter↗
USGS2004

Coping with unobservable and mis-classified states in capture-recapture studies

Multistate mark-recapture methods provide an excellent conceptual framework for considering estimation in studies of marked animals. Traditional methods include the assumptions that (1) each state an animal occupies is observable, and (2) state is assigned correctly at each point in time. Failure of either of these assumptions can lead to biased estimates of demographic parameters. I review design and analysis options for minimizing or eliminating these biases. Unobservable states can be adjusted for by including them in the state space of the statistical model, with zero capture probability, and incorporating the robust design, or observing animals in the unobservable state through telemetry, tag recoveries, or incidental observations. Mis-classification can be adjusted for by auxiliary data or incorporating the robust design, in order to estimate the probability of detecting the state an animal occupies. For both unobservable and mis-classified states, the key feature of the robust design is the assumption that the state of the animal is static for at least two sampling occasions.

Animal Biodiversity and Conservation↗
USGS2004

Costs of detection bias in index-based population monitoring

Managers of wildlife populations commonly rely on indirect, count-based measures of the population in making decisions regarding conservation, harvest, or control. The main appeal in the use of such counts is their low material expense compared to methods that directly measure the population. However, their correct use rests on the rarely-tested but often-assumed premise that they proportionately reflect population size, i.e., that they constitute a population index. This study investigates forest management for the endangered Red-cockaded Woodpecker (Picoides borealis) and the Wood Thrush (Hylocichla mustelina) at the Piedmont National Wildlife Refuge in central Georgia, U.S.A. Optimal decision policies for a joint species objective were derived for two alternative models of Wood Thrush population dynamics. Policies were simulated under scenarios of unbiasedness, consistent negative bias, and habitat-dependent negative bias in observed Wood Thrush densities. Differences in simulation outcomes between biased and unbiased detection scenarios indicated the expected loss in resource objectives (here, forest habitat and birds) through decision-making based on biased population counts. Given the models and objective function used in our analysis, expected losses were as great as 11%, a degree of loss perhaps not trivial for applications such as endangered species management. Our analysis demonstrates that costs of uncertainty about the relationship between the population and its observation can be measured in units of the resource, costs which may offset apparent savings achieved by collecting uncorrected population counts.

Animal Biodiversity and Conservation↗
USGS2004

Detecting warning signs of trouble within population fluctuations: using capture-recapture modeling to uncover changes in population dynamics leading to declines

An intensive mark-recapture/resighting program has been carried out on the Roseate Terns nesting at Falkner Island, Connecticut, since the late 1980s as part of a regional study of the metapopulation dynamics and ecology of the endangered Northwest Atlantic breeding population of this species. Substantial losses of tern eggs and chicks to predation at this colony site began in 1996 when at least five Black-crowned Night-Herons started nocturnal raids. This depredation has been a major factor in the reduction of productivity from an average of about 1.0 chicks/pair for the 10 years before night-heron predation began to as low as about 0.2 chicks/pair in 2002. Recent capture-recapture modelling analyses have detected other important impacts on the population dynamics of the Roseate Terns at this site including a reduction by about half in the 'development-of-residency' rates of first-time breeders, and a substantial decline in the local 'survival-and-fidelity' rates of experienced breeders believed due mostly to increased immigration rates to other colony sites.

Annual Meeting of the Association of Field Ornitho↗
USGS2003

On the use of the robust design with transient capture-recapture models

Capture-mark-recapture studies provide a useful mechanism for estimating the components of the population dynamics of birds, especially survival. In such studies, it is important that the population being captured matches the population of interest. In many studies, transients are captured along with the population of interest (e.g. resident breeders). Ignoring that phenomenon produces negatively biased survival estimates, because transients do not return. Although transients cannot be distinguished from residents in the hand, previous methods have adjusted for transience by relying on those captured in more than one year to provide direct estimates of survival rate for residents. Here, we extend that approach by supplementing that cohort of known residents with those previously unmarked birds captured twice or more, at least d days apart, within a season. We provide an ad hoc approach to that extension in detail and outline two more formal approaches. That extension increases the precision of survival estimates.

The Auk↗
USGS2003

Adjusting multistate capture-recapture models for misclassification bias: manatee breeding proportions

Matrix population models are important tools for research and management of populations. Estimating the parameters of these models is an important step in applying them to real populations. Multistate capture-recapture methods have provided a useful means for estimating survival and parameters of transition between locations or life history states but have mostly relied on the assumption that the state occupied by each detected animal is known with certainty. Nevertheless, in some cases animals can be misclassified. Using multiple capture sessions within each period of interest, we developed a method that adjusts estimates of transition probabilities for bias due to misclassification. We applied this method to 10 years of sighting data for a population of Florida manatees (Trichechus manatus latirostris) in order to estimate the annual probability of transition from nonbreeding to breeding status. Some sighted females were unequivocally classified as breeders because they were clearly accompanied by a first-year calf. The remainder were classified, sometimes erroneously, as nonbreeders because an attendant first-year calf was not observed or was classified as more than one year old. We estimated a conditional breeding probability of 0.31 + 0.04 (estimate + 1 SE) when we ignored misclassification bias, and 0.61 + 0.09 when we accounted for misclassification.

Ecology↗
USGS2002

How should detection probability be incorporated into estimates of relative abundance?

Determination of the relative abundance of two populations, separated by time or space, is of interest in many ecological situations. We focus on two estimators of relative abundance, which assume that the probability that an individual is detected at least once in the survey is either equal or unequal for the two populations. We present three methods for incorporating the collected information into our inference. The first method, proposed previously, is a traditional hypothesis test for evidence that detection probabilities are unequal. However, we feel that, a priori, it is more likely that detection probabilities are actually different; hence, the burden of proof should be shifted, requiring evidence that detection probabilities are practically equivalent. The second method we present, equivalence testing, is one approach to doing so. Third, we suggest that model averaging could be used by combining the two estimators according to derived model weights. These differing approaches are applied to a mark-recapture experiment on Nuttail's cottontail rabbit ( Sylvilagus nuttallii ) conducted in central Oregon during 1974 and 1975, which has been previously analyzed by other authors.

Oregon↗
USGS2002

Estimating state-transition probabilities for unobservable states using capture-recapture/resighting data

Temporary emigration was identified some time ago as causing potential problems in capture-recapture studies, and in the last five years approaches have been developed for dealing with special cases of this general problem. Temporary emigration can be viewed more generally as involving transitions to and from an unobservable state, and frequently the state itself is one of biological interest (e.g., 'nonbreeder'). Development of models that permit estimation of relevant parameters in the presence of an unobservable state requires either extra information (e.g., as supplied by Pollock's robust design) or the following classes of model constraints: reducing the order of Markovian transition probabilities, imposing a degree of determinism on transition probabilities, removing state specificity of survival probabilities, and imposing temporal constancy of parameters. The objective of the work described in this paper is to investigate estimability of model parameters under a variety of models that include an unobservable state. Beginning with a very general model and no extra information, we used numerical methods to systematically investigate the use of ancillary information and constraints to yield models that are useful for estimation. The result is a catalog of models for which estimation is possible. An example analysis of sea turtle capture-recapture data under two different models showed similar point estimates but increased precision for the model that incorporated ancillary data (the robust design) when compared to the model with deterministic transitions only. This comparison and the results of our numerical investigation of model structures lead to design suggestions for capture-recapture studies in the presence of an unobservable state.

Long Island↗
USGS2002

Conditions and limitations on learning in the adaptive management of mallard harvests

In 1995, the United States Fish and Wildlife Service adopted a protocol for the adaptive management of waterfowl hunting regulations (AHM) to help reduce uncertainty about the magnitude of sustainable harvests. To date, the AHM process has focused principally on the midcontinent population of mallards (Anas platyrhynchos), whose dynamics are described by 4 alternative models. Collectively, these models express uncertainty (or disagreement) about whether harvest is an additive or a compensatory form of mortality and whether the reproductive process is weakly or strongly density-dependent. Each model is associated with a probability or 'weight,' which describes its relative ability to predict changes in population size. These Bayesian probabilities are updated annually using a comparison of population size predicted under each model with that observed by a monitoring program. The current AHM process is passively adaptive, in the sense that there is no a priori consideration of how harvest decisions might affect discrimination among models. We contrast this approach with an actively adaptive approach, in which harvest decisions are used in part to produce the learning needed to increase long-term management performance. Our investigation suggests that the passive approach is expected to perform nearly as well as an optimal actively adaptive approach, particularly considering the nature of the model set, management objectives and constraints, and current regulatory alternatives. We offer some comments about the nature of the biological hypotheses being tested and describe some of the inherent limitations on learning in the AHM process.

Wildlife Society Bulletin↗