Geology topics

K. H. Pollock

Publications and source records attributed to K. H. Pollock.

At least 19 recordsLinked to original sources

USGS2016

Sources of variation in extinction rates, turnover, and diversity of marine invertebrate families during the Paleozoic

We have recently shown how capture-recapture models can be used in conjunction with stratigraphic range data to estimate taxonomic extinction rates and taxonomic diversity. Here we present a new method that can be used to estimate taxonomic turnover (defined here as the proportion of taxa extant at time i , that originated in the interval i – 1 to i ). We used these methods in conjunction with stratigraphic range data for families in five phyla of Paleozoic marine invertebrates. We estimated fossil encounter probabilities, extinction rates, diversity, and turnover and used these estimates to test hypotheses about variation among phyla and geologic series. Encounter probabilities varied among taxa and showed evidence of a decrease over time for the geologic series examined. The number of families varied substantially among the five phyla and showed some evidence of an increase over the series examined. There was no evidence of variation in extinction probabilities among the phyla. Although there was evidence of temporal variation in extinction probabilities within phyla, there was no evidence of a linear decrease in extinction probabilities over time, as has been reported by others. We did find evidence of high extinction probabilities for the two intervals that had been identified by others as periods of mass extinction. We found no evidence of variation in turnover among the five phyla. There was evidence of temporal variation in turnover, with greater turnover occurring in the older series.

Paleobiology↗

USGS2016

Estimating taxonomic diversity, extinction rates, and speciation rates from fossil data using capture-recapture models

Methods currently used to estimate taxonomic extinction probabilities from fossil data generally assume that the probability of encountering a specimen in a particular stratum, given that the taxon was extant in the time period and location represented by the stratum, either equals 1.0 or else is a constant for all strata. Methods used to estimate taxonomic diversity (number of taxa) and speciation rate generally assume that encounter probabilities equal 1.0. We suspect that these assumptions are often false. Capture-recapture models were historically developed for estimation in the face of variable and unknown sampling probabilities. These models can thus be used to estimate parameters of interest from paleobiological data when encounter probabilities are unknown and variable over time. These models also permit estimation of sampling variances, and goodness-of-fit tests are available for assessing the fit of data to most models. Here we describe capture-recapture models which should be useful in paleobiological analyses and discuss the assumptions which underlie them. We illustrate these models with examples and discuss aspects of study design. We conclude that these models should prove useful in paleobiological analyses.

Paleobiology↗

USGS2011

Evaluating the effect of predators on white-tailed deer: Movement and diet of coyotes

Coyotes ( Canis latrans ) may affect adult and neonate white-tailed deer ( Odocoileus virginianus ) survival and have been implicated as a contributor to the decline of deer populations. Additionally, coyote diet composition is influenced by prey availability, season, and region. Because coyote movement and diet vary by region, local data are important to understand coyote population dynamics and their impact on prey species. In southeast Minnesota, we investigated the effect of coyotes on white-tailed deer populations by documenting movement rates, distances moved, and habitats searched by coyotes during fawning and nonfawning periods. Additionally, we determined survival, cause-specific mortality, and seasonal diet composition of coyotes. From 2001 to 2003, we captured and radiocollared 30 coyotes. Per-hour rate of movement averaged 0.87 km and was greater ( P = 0.046) during the fawning (1.07 km) than the nonfawning period (0.80 km); areas searched were similar ( P = 0.175) between seasons. Coyote habitat use differed during both seasons; habitats were not used in proportion to their availability ( P < 0.001). Croplands were used more ( P < 0.001) than their proportional availability during both seasons. Use of grasslands was greater during the fawning period ( P = 0.030), whereas use of cropland was greater in the nonfawning period ( P < 0.001). We collected 66 fecal samples during the nonfawning period; coyote diets were primarily composed of Microtus spp. (65.2%), and consumption of deer was 9.1%. During the study, 19 coyotes died; annual survival rate range was 0.33–0.41, which was low compared with other studies. Consumption of deer was low and coyotes searched open areas (i.e., cropland) more than fawning areas with dense cover. These factors in addition to high coyote mortality suggested that coyote predation was not likely limiting white-tailed deer populations in southeast Minnesota.

Journal of Wildlife Management↗

USGS2010

An experimental assessment of vehicle disturbance effects on migratory shorebirds

Off-road vehicle (ORV) traffic is one of several forms of disturbance thought to affect shorebirds at migration stopover sites. Attempts to measure disturbance effects on shorebird habitat use and behavior at stopover sites are difficult because ORV disturbance is frequently confounded with habitat and environmental factors. We used a before-after-control-impact experimental design to isolate effects of vehicle disturbance from shorebird responses to environmental and habitat factors. We manipulated disturbance levels within beach closures along South Core Banks, North Carolina, USA, and measured changes in shorebird abundance and location, as well as the activity of one focal species, the sanderling (Calidris alba), within paired control and impact plots. We applied a discrete treatment level of one flee-response-inducing event every 10 minutes on impact plots. We found that disturbance reduced total shorebird and black-bellied plover (Pluvialis squatarola) abundance and reduced relative use of microhabitat zones above the swash zone (wet sand and dry sand) by sanderlings, black-bellied plovers, willets (Tringa semipalmata), and total shorebirds. Sanderlings and total shorebirds increased use of the swash zone in response to vehicle disturbance. Disturbance reduced use of study plots by sanderlings for resting and increased sanderling activity, but we did not detect an effect of vehicle disturbance on sanderling foraging activity. We provide the first estimates of how a discrete level of disturbance affects shorebird distributions among ocean beach microhabitats. Our findings provide a standard to which managers can compare frequency and intensity of disturbance events at other shorebird stopover and roosting sites and indicate that limiting disturbance will contribute to use of a site by migratory shorebirds. ?? 2010 The Wildlife Society.

Journal of Wildlife Management↗

USGS2010

Experimental investigation of observation error in anuran call surveys

Occupancy models that account for imperfect detection are often used to monitor anuran and songbird species occurrence. However, presenceabsence data arising from auditory detections may be more prone to observation error (e.g., false-positive detections) than are sampling approaches utilizing physical captures or sightings of individuals. We conducted realistic, replicated field experiments using a remote broadcasting system to simulate simple anuran call surveys and to investigate potential factors affecting observation error in these studies. Distance, time, ambient noise, and observer abilities were the most important factors explaining false-negative detections. Distance and observer ability were the best overall predictors of false-positive errors, but ambient noise and competing species also affected error rates for some species. False-positive errors made up 5 of all positive detections, with individual observers exhibiting false-positive rates between 0.5 and 14. Previous research suggests false-positive errors of these magnitudes would induce substantial positive biases in standard estimators of species occurrence, and we recommend practices to mitigate for false positives when developing occupancy monitoring protocols that rely on auditory detections. These recommendations include additional observer training, limiting the number of target species, and establishing distance and ambient noise thresholds during surveys. ?? 2010 The Wildlife Society.

Journal of Wildlife Management↗

USGS2010

Uncovering a latent multinomial: Analysis of mark–recapture data with misidentification

Natural tags based on DNA fingerprints or natural features of animals are now becoming very widely used in wildlife population biology. However, classic capture-recapture models do not allow for misidentification of animals which is a potentially very serious problem with natural tags. Statistical analysis of misidentification processes is extremely difficult using traditional likelihood methods but is easily handled using Bayesian methods. We present a general framework for Bayesian analysis of categorical data arising from a latent multinomial distribution. Although our work is motivated by a specific model for misidentification in closed population capture-recapture analyses, with crucial assumptions which may not always be appropriate, the methods we develop extend naturally to a variety of other models with similar structure. Suppose that observed frequencies f are a known linear transformation f=A'x of a latent multinomial variable x with cell probability vector pi= pi(theta). Given that full conditional distributions [theta | x] can be sampled, implementation of Gibbs sampling requires only that we can sample from the full conditional distribution [x | f, theta], which is made possible by knowledge of the null space of A'. We illustrate the approach using two data sets with individual misidentification, one simulated, the other summarizing recapture data for salamanders based on natural marks.

Biometrics↗

USGS2009

Modeling misidentification errors that result from use of genetic tags in capture-recapture studies

Misidentification of animals is potentially important when naturally existing features (natural tags) such as DNA fingerprints (genetic tags) are used to identify individual animals. For example, when misidentification leads to multiple identities being assigned to an animal, traditional estimators tend to overestimate population size. Accounting for misidentification in capture–recapture models requires detailed understanding of the mechanism. Using genetic tags as an example, we outline a framework for modeling the effect of misidentification in closed population studies when individual identification is based on natural tags that are consistent over time (non-evolving natural tags). We first assume a single sample is obtained per animal for each capture event, and then generalize to the case where multiple samples (such as hair or scat samples) are collected per animal per capture occasion. We introduce methods for estimating population size and, using a simulation study, we show that our new estimators perform well for cases with moderately high capture probabilities or high misidentification rates. In contrast, conventional estimators can seriously overestimate population size when errors due to misidentification are ignored.

Environmental and Ecological Statistics↗

USGS2009

COMDYN: Software to study the dynamics of animal communities using a capture-recapture approach

COMDYN is a set of programs developed for estimation of parameters associated with community dynamics using count data from two locations or time periods. It is Internet-based, allowing remote users either to input their own data, or to use data from the North American Breeding Bird Survey for analysis. COMDYN allows probability of detection to vary among species and among locations and time periods. The basic estimator for species richness underlying all estimators is the jackknife estimator proposed by Burnham and Overton. Estimators are presented for quantities associated with temporal change in species richness, including rate of change in species richness over time, local extinction probability, local species turnover and number of local colonizing species. Estimators are also presented for quantities associated with spatial variation in species richness, including relative richness at two locations and proportion of species present in one location that are also present at a second location. Application of the estimators to species richness estimation has been previously described and justified. The potential applications of these programs are discussed.

Bird Study↗

USGS2009

A combined telemetry - tag return approach to estimate fishing and natural mortality rates of an estuarine fish

A joint analysis of tag return and telemetry data should improve estimates of mortality rates for exploited fishes; however, the combined approach has thus far only been tested in terrestrial systems. We tagged subadult red drum (Sciaenops ocellatus) with conventional tags and ultrasonic transmitters over 3 years in coastal North Carolina, USA, to test the efficacy of the combined telemetry - tag return approach. There was a strong seasonal pattern to monthly fishing mortality rate (F) estimates from both conventional and telemetry tags; highest F values occurred in fall months and lowest levels occurred during winter. Although monthly F values were similar in pattern and magnitude between conventional tagging and telemetry, information on F in the combined model came primarily from conventional tags. The estimated natural mortality rate (M) in the combined model was low (estimated annual rate ?? standard error: 0.04 ?? 0.04) and was based primarily upon the telemetry approach. Using high-reward tagging, we estimated different tag reporting rates for state agency and university tagging programs. The combined telemetry - tag return approach can be an effective approach for estimating F and M as long as several key assumptions of the model are met.

Canadian Journal of Fisheries and Aquatic Sciences↗

USGS2009

Modeling misidentification errors in capture-recapture studies using photographic identification of evolving marks

Misidentification of animals is potentially important when naturally existing features (natural tags) are used to identify individual animals in a capture-recapture study. Photographic identification (photoID) typically uses photographic images of animals' naturally existing features as tags (photographic tags) and is subject to two main causes of identification errors: those related to quality of photographs (non-evolving natural tags) and those related to changes in natural marks (evolving natural tags). The conventional methods for analysis of capture-recapture data do not account for identification errors, and to do so requires a detailed understanding of the misidentification mechanism. Focusing on the situation where errors are due to evolving natural tags, we propose a misidentification mechanism and outline a framework for modeling the effect of misidentification in closed population studies. We introduce methods for estimating population size based on this model. Using a simulation study, we show that conventional estimators can seriously overestimate population size when errors due to misidentification are ignored, and that, in comparison, our new estimators have better properties except in cases with low capture probabilities (<0.2) or low misidentification rates (<2.5%). ?? 2009 by the Ecological Society of America.

Ecology↗

USGS2008

Inference methods for spatial variation in species richness and community composition when not all species are detected

Inferences about spatial variation in species richness and community composition are important both to ecological hypotheses about the structure and function of communities and to community-level conservation and management. Few sampling programs for animal communities provide censuses, and usually some species in surveyed areas are not detected. Thus, counts of species detected underestimate the number of species present. We present estimators useful for drawing inferences about comparative species richness and composition between different sampling locations when not all species are detected in sampling efforts. Based on capture-recapture models using the robust design, our methods estimate relative species richness, proportion of species in one location that are also found in another, and number of species found in one location but not in another. The methods use data on the presence or absence of each species at different sampling occasions (or locations) to estimate the number of species not detected at any occasions (or locations). This approach permits estimation of the number of species in the sampled community and in subsets of the community useful for estimating the fraction of species shared by two communities. We provide an illustration of our estimation methods by comparing bird species richness and composition in two locations sampled by routes of the North American Breeding Bird Survey. In this example analysis, the two locations (and associated bird communities) represented different levels of urbanization. Estimates of relative richness, proportion of shared species, and number of species present on one route but not the other indicated that the route with the smaller fraction of urban area had greater richness and a larger number of species that were not found on the more urban route than vice versa. We developed a software package, COMDYN, for computing estimates based on these methods. Because these estimation methods explicitly deal with sampling in which not all species are detected, we recommend their use for addressing questions about species richness and community composition.

Conservation Biology↗

USGS2007

Estimating fishing mortality, natural mortality, and selectivity using recoveries from tagging young fish

Current methods for estimation of age- and year-specific instantaneous mortality rates based on multiyear, multiple-age tagging studies assume that it is feasible to tag fish in a wide range of ages. For some species, however, only the youngest one or two age-classes are readily available for tagging. Given the practical advantages of tagging young fish only, an important question is whether such studies would provide the information needed for estimation of age-dependent mortality rates. We investigated three designs: tagging only the youngest available age-class, tagging the two youngest age-classes, and tagging the first five age-classes. We carried out simulation studies to assess estimator performance under these three designs, in each case assuming the same total number of tagged fish. Data were generated assuming fishing mortality rates to be age and year dependent and natural mortality rates to be constant or with limited age dependence. Estimator performance is best when fish are tagged in five age-classes, and tagging fish in the two youngest age-classes shows substantial improvement compared with tagging one age-class only. External information about the tag-reporting rate is necessary to obtain estimators with reasonable properties, especially in the case of models with age-dependent natural mortality. Such information can be obtained from auxiliary studies by means of high-reward tags or planted tags. Collecting recovery information for several additional years after the last release produces small improvements in precision and bias. If tagging fish in multiple age-classes is impractical, reasonable precision can be obtained by tagging one or preferably two age-classes and obtaining supplemental information on the reporting rate. For illustration, estimates of age-dependent fishing and natural mortality rates were obtained from tag returns on Chesapeake Bay striped bass Morone saxatilis tagged at ages 3 and 4 years. ?? Copyright by the American Fisheries Society 2007.

North American Journal of Fisheries Management↗

USGS2007

Tag return models allowing for harvest and catch and release: Evidence of environmental and management impacts on striped bass fishing and natural mortality rates

Catch-and-release fisheries have become very important in the management of overexploited recreational fish stocks. Tag return studies, where the tag is removed regardless of fish disposition, have been used to assess the effectiveness of restoration efforts for these fisheries. We extend the instantaneous rate formulation of tag return models to allow for catch and release as well as harvest. The key point of our methods is that, given an estimate of the tag reporting rate, the fishing mortality rate (F) is separated into two components: the mortality on harvested fish and the "mortality" on tags (because the lags are removed) of fish released alive. The total fishing mortality rate for untagged fish is the sum of the Fs due to harvest and hooking mortality suffered by fish released alive. Natural mortality rates can also be estimated. Both age-independent models and age-dependent models are constructed, and the age-dependent models are illustrated by application to data from a study of striped bass Morone saxatilis in Chesapeake Bay from 1991 to 2003 by the Maryland Department of Natural Resources. By fitting models of the natural mortality rate with limited age and year dependence, we demonstrate an overall decrease in natural mortality rates as fish age and provide evidence of an increase in natural mortality beginning in the late 1990s, when an outbreak of the disease mycobacteriosis is thought to have begun. Our results indicate that fishing mortality is age dependent; selectivity increases up to age 6, when fish appear to be fully recruited to the fishery. There is also evidence of an increase in fishing mortality since 1995, when regulations were relaxed. ?? Copyright by the American Fisheries Society 2007.

North American Journal of Fisheries Management↗

USGS2007

Multiple-species analysis of point count data: A more parsimonious modelling framework

1. Although population surveys often provide information on multiple species, these data are rarely analysed within a multiple-species framework despite the potential for more efficient estimation of population parameters. 2. We have developed a multiple-species modelling framework that uses similarities in capture/detection processes among species to model multiple species data more parsimoniously. We present examples of this approach applied to distance, time of detection and multiple observer sampling for avian point count data. 3. Models that included species as a covariate and individual species effects were generally selected as the best models for distance sampling, but group models without species effects performed best for the time of detection and multiple observer methods. Population estimates were more precise for no-species-effect models than for species-effect models, demonstrating the benefits of exploiting species' similarities when modelling multiple species data. Partial species-effect models and additive models were also useful because they modelled similarities among species while allowing for species differences. 4. Synthesis and applications. We recommend the adoption of multiple-species modelling because of its potential for improved population estimates. This framework will be particularly beneficial for modelling count data from rare species because information on the detection process can be 'borrowed' from more common species. The multiple-species modelling framework presented here is applicable to a wide range of sampling techniques and taxa. ?? 2007 The Authors.

Journal of Applied Ecology↗

USGS2007

Experimental analysis of the auditory detection process on avian point counts

We have developed a system for simulating the conditions of avian surveys in which birds are identified by sound. The system uses a laptop computer to control a set of amplified MP3 players placed at known locations around a survey point. The system can realistically simulate a known population of songbirds under a range of factors that affect detection probabilities. The goals of our research are to describe the sources and range of variability affecting point-count estimates and to find applications of sampling theory and methodologies that produce practical improvements in the quality of bird-census data. Initial experiments in an open field showed that, on average, observers tend to undercount birds on unlimited-radius counts, though the proportion of birds counted by individual observers ranged from 81% to 132% of the actual total. In contrast to the unlimited-radius counts, when data were truncated at a 50-m radius around the point, observers overestimated the total population by 17% to 122%. Results also illustrate how detection distances decline and identification errors increase with increasing levels of ambient noise. Overall, the proportion of birds heard by observers decreased by 28 ± 4.7% under breezy conditions, 41 ± 5.2% with the presence of additional background birds, and 42 ± 3.4% with the addition of 10 dB of white noise. These findings illustrate some of the inherent difficulties in interpreting avian abundance estimates based on auditory detections, and why estimates that do not account for variations in detection probability will not withstand critical scrutiny.

The Auk↗

USGS2006

Occupancy Estimation and Modeling : Inferring Patterns and Dynamics of Species Occurrence

This is the first book to examine the latest methods in analyzing presence/absence data surveys. Using four classes of models (single-species, single-season; single-species, multiple season; multiple-species, single-season; and multiple-species, multiple-season), the authors discuss the practical sampling situation, present a likelihood-based model enabling direct estimation of the occupancy-related parameters while allowing for imperfect detectability, and make recommendations for designing studies using these models. It provides authoritative insights into the latest in estimation modeling; discusses multiple models which lay the groundwork for future study designs; addresses critical issues of imperfect detectibility and its effects on estimation; and explores the role of probability in estimating in detail.

Book↗

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↗

USGS2005

Statistical approaches to the analysis of point count data: A little extra information can go a long way

Point counts are a standard sampling procedure for many bird species, but lingering concerns still exist about the quality of information produced from the method. It is well known that variation in observer ability and environmental conditions can influence the detection probability of birds in point counts, but many biologists have been reluctant to abandon point counts in favor of more intensive approaches to counting. However, over the past few years a variety of statistical and methodological developments have begun to provide practical ways of overcoming some of the problems with point counts. We describe some of these approaches, and show how they can be integrated into standard point count protocols to greatly enhance the quality of the information. Several tools now exist for estimation of detection probability of birds during counts, including distance sampling, double observer methods, time-depletion (removal) methods, and hybrid methods that combine these approaches. Many counts are conducted in habitats that make auditory detection of birds much more likely than visual detection. As a framework for understanding detection probability during such counts, we propose separating two components of the probability a bird is detected during a count into (1) the probability a bird vocalizes during the count and (2) the probability this vocalization is detected by an observer. In addition, we propose that some measure of the area sampled during a count is necessary for valid inferences about bird populations. This can be done by employing fixed-radius counts or more sophisticated distance-sampling models. We recommend any studies employing point counts be designed to estimate detection probability and to include a measure of the area sampled.

Book chapter↗