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Geology topics

J.D. Nichols

Publications and source records attributed to J.D. Nichols.

At least 127 records · Page 7Linked to original sources
USGS2001

Methods for estimating dispersal probabilities and related parameters using marked animals

Deriving valid inferences about the causes and consequences of dispersal from empirical studies depends largely on our ability reliably to estimate parameters associated with dispersal. Here, we present a review of the methods available for estimating dispersal and related parameters using marked individuals. We emphasize methods that place dispersal in a probabilistic framework. In this context, we define a dispersal event as a movement of a specified distance or from one predefined patch to another, the magnitude of the distance or the definition of a `patch? depending on the ecological or evolutionary question(s) being addressed. We have organized the chapter based on four general classes of data for animals that are captured, marked, and released alive: (1) recovery data, in which animals are recovered dead at a subsequent time, (2) recapture/resighting data, in which animals are either recaptured or resighted alive on subsequent sampling occasions, (3) known-status data, in which marked animals are reobserved alive or dead at specified times with probability 1.0, and (4) combined data, in which data are of more than one type (e.g., live recapture and ring recovery). For each data type, we discuss the data required, the estimation techniques, and the types of questions that might be addressed from studies conducted at single and multiple sites.

Book chapter↗
USGS2001

Introduction

Explore the source record for details and available documents.

Book chapter↗
USGS2001

Regional patterns in proportion of bird species detected in the North American Breeding Bird Survey

Counts from the North American Breeding Bird Survey (BBS) underestimate species richness. We use capture-recapture methods to estimate species richness from BBS count data collected in 1996 and show that detection probabilities demonstrate clear regional patterns. Capture-recapture methods should be used to estimate species richness from count data, and failure to use estimation procedures for species richness could result in biased estimates of spatial change in species richness.

Book chapter↗
USGS2001

Modeling avian detection probabilities as a function of habitat using double-observer point count data

Point counts are a controversial sampling method for bird populations because the counts are not censuses, and the proportion of birds missed during counting generally is not estimated. We applied a double-observer approach to estimate detection rates of birds from point counts in Maryland, USA, and test whether detection rates differed between point counts conducted in field habitats as opposed to wooded habitats. We conducted 2 analyses. The first analysis was based on 4 clusters of counts (routes) surveyed by a single pair of observers. A series of models was developed with differing assumptions about sources of variation in detection probabilities and fit using program SURVIV. The most appropriate model was selected using Akaike's Information Criterion. The second analysis was based on 13 routes (7 woods and 6 field routes) surveyed by various observers in which average detection rates were estimated by route and compared using a t-test. In both analyses, little evidence existed for variation in detection probabilities in relation to habitat. Double-observer methods provide a reasonable means of estimating detection probabilities and testing critical assumptions needed for analysis of point counts.

Book chapter↗
USGS2001

Systems identification and the adaptive management of waterfowl in the United States

Waterfowl management in the United States is one of the more visible conservation success stories in the United States. It is authorized and supported by appropriate legislative authorities, based on large-scale monitoring programs, and widely accepted by the public. The process is one of only a limited number of large-scale examples of effective collaboration between research and management, integrating scientific information with management in a coherent framework for regulatory decision-making. However, harvest management continues to face some serious technical problems, many of which focus on sequential identification of the resource system in a context of optimal decision-making. The objective of this paper is to provide a theoretical foundation of adaptive harvest management, the approach currently in use in the United States for regulatory decision-making. We lay out the legal and institutional framework for adaptive harvest management and provide a formal description of regulatory decision-making in terms of adaptive optimization. We discuss some technical and institutional challenges in applying adaptive harvest management and focus specifically on methods of estimating resource states for linear resource systems.

Wildlife Biology↗
USGS2001

Hunting statistics: what data for what use? An account of an international workshop

Hunting interacts with the underlying dynamics of game species in several different ways and is, at the same time, a source of valuable information not easily obtained from populations that are not subjected to hunting. Specific questions, including the sustainability of hunting activities, can be addressed using hunting statistics. Such investigations will frequently require that hunting statistics be combined with data from other sources of population-level information. Such reflections served as a basis for the meeting, ?Hunting Statistics: What Data for What Use,? held on January 15-18, 2001 in Saint-Benoist, France. We review here the 20 talks held during the workshop and the contribution of hunting statistics to our knowledge of the population dynamics of game species. Three specific topics (adaptive management, catch-effort models, and dynamics of exploited populations) were highlighted as important themes and are more extensively presented as boxes.

Game and Wildlife Science↗
USGS2000

A double-observer approach for estimating detection probability and abundance from point counts

Although point counts are frequently used in ornithological studies, basic assumptions about detection probabilities often are untested. We apply a double-observer approach developed to estimate detection probabilities for aerial surveys (Cook and Jacobson 1979) to avian point counts. At each point count, a designated 'primary' observer indicates to another ('secondary') observer all birds detected. The secondary observer records all detections of the primary observer as well as any birds not detected by the primary observer. Observers alternate primary and secondary roles during the course of the survey. The approach permits estimation of observer-specific detection probabilities and bird abundance. We developed a set of models that incorporate different assumptions about sources of variation (e.g. observer, bird species) in detection probability. Seventeen field trials were conducted, and models were fit to the resulting data using program SURVIV. Single-observer point counts generally miss varying proportions of the birds actually present, and observer and bird species were found to be relevant sources of variation in detection probabilities. Overall detection probabilities (probability of being detected by at least one of the two observers) estimated using the double-observer approach were very high (>0.95), yielding precise estimates of avian abundance. We consider problems with the approach and recommend possible solutions, including restriction of the approach to fixed-radius counts to reduce the effect of variation in the effective radius of detection among various observers and to provide a basis for using spatial sampling to estimate bird abundance on large areas of interest. We believe that most questions meriting the effort required to carry out point counts also merit serious attempts to estimate detection probabilities associated with the counts. The double-observer approach is a method that can be used for this purpose.

The Auk↗
USGS2000

The AOU Conservation Committee Review of the biology, status, and management of Cape Sable Seaside Sparrows: Final report

The Cape Sable Seaside Sparrow ( Ammodramus maritimus mirabilis ) was listed as an original member of the federal list of endangered species in 1968. It is restricted to seasonally flooded prairies of extreme southern Florida and is disjunct from all other conspecific breeding populations (Kushlan et al 1982, McDonald 1988). Since the subspecies was described in 1919, its populations have been discovered and rediscovered, often only to disappear or decline to a handful of individuals (Werner and Woolfenden 1983, Kushlan and Bass 1983). Although the sparrow historically is known from six distinct areas, at present only two of these areas support populations numbering in the hundreds or low thousands of individuals. Debates swirl around the status of these remnant populations. The main controversy encompasses whether the sparrow, now largely restricted to Everglades National Park, is in jeopardy of global extinction and if so, what actions must be taken to prevent this from happening. In November 1998, a panel of scientists was assembled under the auspices of the Conservation Committee of the American Ornithologists' Union (AOU) to evaluate the scientific evidence relevant to this controversy. The Panel was charged with scrutinizing the evidence for the existence and probable causes of global population decline in this subspecies, evaluating proposed management actions, and suggesting further research necessary to manage the remaining populations to maximize their chances of long-term persistence. This document presents the conclusions of the Panel, which are based on our reading of the peer-reviewed and “gray” literature, interactions during a workshop held 9 to 11 February 1999 at Florida International University in Miami with researchers investigating the sparrow's biology, and site visits associated with the workshop. In addition, researchers provided the Panel with position papers summarizing their findings and conclusions prior to the workshop and provided information in response to specific questions following the workshop. Further information was obtained through public comment on an initial draft of this report.

The Auk↗
USGS2000

Estimation of contributions to population growth: A reverse-time capture-recapture approach

We consider methods for estimating the relative contributions of different demographic components, and their associated vital rates, to population growth. We identify components of the population at time i (including a component for animals not in the population at i ). For each such component we ask the following question: “What is the probability that an individual randomly selected from the population at time i + 1 was a member of this component at i ?” The estimation methods for these probabilities (γ i ) are based on capture–recapture studies of marked animal populations and use reverse-time modeling. We consider several different sampling situations and present example analyses for meadow voles, Microtus pennsylvanicus. The relationship between these γ i parameters and elasticities (and other parameters based on projection matrix asymptotics) is noted and discussed. We conclude by suggesting that model-based asymptotics be viewed as demographic theory and that direct estimation approaches be used to test this theory with data from sampled populations with marked animals.

Ecology↗
USGS2000

Relative species richness and community completeness: avian communities and urbanization in the mid-Atlantic states

The idea that local factors govern local richness has been dominant for years, but recent theoretical and empirical studies have stressed the influence of regional factors on local richness. Fewer species at a site could reflect not only the influence of local factors, but also a smaller regional pool. The possible dependency of local richness on the regional pool should be taken into account when addressing the influence of local factors on local richness. It is possible to account for this potential dependency by comparing relative species richness among sites, rather than species richness per se. We consider estimation of a metric permitting assessment of relative species richness in a typical situation in which not all species are detected during sampling sessions. In this situation, estimates of absolute or relative species richness need to account for variation in species detection probability if they are to be unbiased. We present a method to estimate relative species richness based on capture-recapture models. This approach involves definition of a species list from regional data, and estimation of the number of species in that list that are present at a site-year of interest. We use this approach to address the influence of urbanization on relative richness of avian communities in the Mid-Atlantic region of the United States. There is a negative relationship between relative richness and landscape variables describing the level of urban development. We believe that this metric should prove very useful for conservation and management purposes because it is based on an estimator of species richness that both accounts for potential variation in species detection probability and allows flexibility in the specification of a 'reference community.' This metric can be used to assess ecological integrity, the richness of the community of interest relative to that of the 'original' community, or to assess change since some previous time in a community.

Delaware, Maryland, New Jersey, New York, Pennsylv↗
USGS2000

Simultaneous use of mark-recapture and radiotelemetry to estimate survival, movement, and capture rates

Biologists often estimate separate survival and movement rates from radio-telemetry and mark-recapture data from the same study population. We describe a method for combining these data types in a single model to obtain joint, potentially less biased estimates of survival and movement that use all available data. We furnish an example using wood thrushes ( Hylocichla mustelina ) captured at the Piedmont National Wildlife Refuge in central Georgia in 1996. The model structure allows estimation of survival and capture probabilities, as well as estimation of movements away from and into the study area. In addition, the model structure provides many possibilities for hypothesis testing. Using the combined model structure, we estimated that wood thrush weekly survival was 0.989 ± 0.007 ( ± SE). Survival rates of banded and radio-marked individuals were not different ( α [ S radioed , S banded ] =log[ S radioed / S banded ]=0.0239 ± 0.0435). Fidelity rates (weekly probability of remaining in a stratum) did not differ between geographic strata ( Ψ = 0.911 ± 0.020; α [ Ψ 11 , Ψ 22 ]=0.0161 ± 0.047), and recapture rates ( p = 0.097 ± 0.016) banded and radio-marked individuals were not different ( α [ P radioed , P banded ]=0.145 ± 0.655). Combining these data types in a common model resulted in more precise estimates of movement and recapture rates than separate estimation, but ability to detect stratum or mark-specific differences in parameters was week. We conducted simulation trials to investigate the effects of varying study designs on parameter accuracy and statistical power to detect important differences. Parameter accuracy was high (relative bias [RBIAS] <2 %) and confidence interval coverage close to nominal, except for survival estimates of banded birds for the 'off study area' stratum, which were negatively biased (RBIAS -7 to -15%) when sample sizes were small (5-10 banded or radioed animals 'released' per time interval). To provide adequate data for useful inference from this model, study designs should seek a minimum of 25 animals of each marking type observed (marked or observed via telemetry) in each time period and geographic stratum.

Journal of Wildlife Management↗
USGS2000

Monitoring is not enough: on the need for a model-based approach to migratory bird management

Informed management requires information about system state and about effects of potential management actions on system state. Population monitoring can provide the needed information about system state, as well as information that can be used to investigate effects of management actions. Three methods for investigating effects of management on bird populations are (1) retrospective analysis, (2) formal experimentation and constrained-design studies, and (3) adaptive management. Retrospective analyses provide weak inferences, regardless of the quality of the monitoring data. The active use of monitoring data in experimental or constrained-design studies or in adaptive management is recommended. Under both approaches, learning occurs via the comparison of estimates from the monitoring program with predictions from competing management models.

Book chapter↗
USGS2000

The role of population monitoring in the management of North American waterfowl

Despite the effort and expense devoted to large-scale monitoring programs, few existing programs have been designed with specific objectives in mind and few permit strong inferences about the dynamics of monitored systems. The waterfowl population monitoring programs of the U.S. Fish and Wildlife Service, Canadian Wildlife Service and state and provincial agencies provide a nice example with respect to program objectives, design and implementation. The May Breeding Grounds Survey provides an estimate of system state (population size) that serves two primary purposes in the adaptive management process: identifying the appropriate time-specific management actions and updating the information state (model weights) by providing a basis for evaluating predictions of competing models. Other waterfowl monitoring programs (e.g., banding program, hunter questionnaire survey, parts collection survey, winter survey) provide estimates of vital rates (rates of survival, reproduction and movement) associated with system dynamics and variables associated with management objectives (e.g., harvest). The reliability of estimates resulting from monitoring programs depends strongly on whether considerations about spatial variation and detection probability have been adequately incorporated into program design and implementation. Certain waterfowl surveys again provide nice examples of monitoring programs that incorporate these considerations.

Book chapter↗
USGS2000

A removal model for estimating detection probabilities from point-count surveys

We adapted a removal model to estimate detection probability during point count surveys. The model assumes one factor influencing detection during point counts is the singing frequency of birds. This may be true for surveys recording forest songbirds when most detections are by sound. The model requires counts to be divided into several time intervals. We used time intervals of 2, 5, and 10 min to develop a maximum-likelihood estimator for the detectability of birds during such surveys. We applied this technique to data from bird surveys conducted in Great Smoky Mountains National Park. We used model selection criteria to identify whether detection probabilities varied among species, throughout the morning, throughout the season, and among different observers. The overall detection probability for all birds was 75%. We found differences in detection probability among species. Species that sing frequently such as Winter Wren and Acadian Flycatcher had high detection probabilities (about 90%) and species that call infrequently such as Pileated Woodpecker had low detection probability (36%). We also found detection probabilities varied with the time of day for some species (e.g. thrushes) and between observers for other species. This method of estimating detectability during point count surveys offers a promising new approach to using count data to address questions of the bird abundance, density, and population trends.

Book chapter↗
USGS2000

Estimates of population change in selected species of tropical birds using mark-recapture data

The population biology of tropical birds is known for a only small sample of species; especially in the Neotropics. Robust estimates of parameters such as survival rate and finite rate of population change (A) are crucial for conservation purposes and useful for studies of avian life histories. We used methods developed by Pradel (1996, Biometrics 52:703-709) to estimate A for 10 species of tropical forest lowland birds using data from a long-term (> 20 yr) banding study in Panama. These species constitute a ecologically and phylogenetically diverse sample. We present these estimates and explore if they are consistent with what we know from selected studies of banded birds and from 5 yr of estimating nesting success (i.e., an important component of A). A major goal of these analyses is to assess if the mark-recapture methods generate reliable and reasonably precise estimates of population change than traditional methods that require more sampling effort.

Book chapter↗
USGS2000

Consideraciones para la estimacion de abundancia de poblaciones de mamiferos. [Considerations for the estimation of abundance of mammal populations.]

Estimation of abundance of mammal populations is essential for monitoring programs and for many ecological investigations. The first step for any study of variation in mammal abundance over space or time is to define the objectives of the study and how and why abundance data are to be used. The data used to estimate abundance are count statistics in the form of counts of animals or their signs. There are two major sources of uncertainty that must be considered in the design of the study: spatial variation and the relationship between abundance and the count statistic. Spatial variation in the distribution of animals or signs may be taken into account with appropriate spatial sampling. Count statistics may be viewed as random variables, with the expected value of the count statistic equal to the true abundance of the population multiplied by a coefficient p. With direct counts, p represents the probability of detection or capture of individuals, and with indirect counts it represents the rate of production of the signs as well as their probability of detection. Comparisons of abundance using count statistics from different times or places assume that the p are the same for all times or places being compared (p= pi). In spite of considerable evidence that this assumption rarely holds true, it is commonly made in studies of mammal abundance, as when the minimum number alive or indices based on sign counts are used to compare abundance in different habitats or times. Alternatives to relying on this assumption are to calibrate the index used by testing the assumption of p= pi, or to incorporate the estimation of p into the study design.

Mastozoologia Neotropical / Journal of Neotropical↗