Geology topics

B. Kenneth Williams

Publications and source records attributed to B. Kenneth Williams.

At least 19 recordsLinked to original sources

USGS2017

Review of dynamic optimization methods in renewable natural resource management

In recent years, the applications of dynamic optimization procedures in natural resource management have proliferated. A systematic review of these applications is given in terms of a number of optimization methodologies and natural resource systems. Optimization methods are characterized by (1) the mathematical model used to describe a natural resource system, (2) a set of feasible strategies available to the resource manager, and (3) an objective functional by which to measure benefits and costs of strategies. A formal statement of the control problem is used to describe six approaches to optimal utilization of renewable natural resources: variational mathematics, specifically Pontryagin's Maximum Principle; dynamic programming; linear programming; nonlinear programming; simulation-optimization; and classical procedures. Solution methodologies are illustrated for each of these approaches, and examples from the ecological and natural resource literature are described for various subject matter areas. Applications are highlighted in terms of model structures, objective functionals, and system constraints. To the extent possible, optimal management patterns are characterized. Finally, the applicability of the methods to renewable natural resource systems are compared in terms of system complexity, system size, and precision of the optimal solutions. Recommendations are made concerning the appropriate methods for certain kinds of biological resource problems.

Natural Resource Modeling↗

USGS2017

Modeling and the management of migratory birds

Mathematical modeling of migratory bird populations is reviewed in the context of migratory bird management. We focus on dynamic models of waterfowl, since most management-oriented migratory bird models concern waterfowl species. We describe the management context for these modeling efforts, with a focus on large-scale operational data collection programs and on processes by which waterfowl harvest is regulated and waterfowl habitats are protected and managed. Through their impacts on key population parameters such as recruitment and survival rate, these activities can influence population dynamics, thereby providing managers some measure of control over the status of populations. Recent applications of the modeling of waterfowl are described in terms of objectives, mathematical structures, and contributions to management. Finally, we discuss research needs and data limitations in migratory bird modeling, and offer suggestions to increase the value to managers of future modeling efforts.

Natural Resource Modeling↗

USGS2015

Markov decision processes in natural resources management: observability and uncertainty

The breadth and complexity of stochastic decision processes in natural resources presents a challenge to analysts who need to understand and use these approaches. The objective of this paper is to describe a class of decision processes that are germane to natural resources conservation and management, namely Markov decision processes, and to discuss applications and computing algorithms under different conditions of observability and uncertainty. A number of important similarities are developed in the framing and evaluation of different decision processes, which can be useful in their applications in natural resources management. The challenges attendant to partial observability are highlighted, and possible approaches for dealing with it are discussed.

Ecological Modelling↗

USGS2011

Climate change, uncertainty, and natural resource management

Climate change and its associated uncertainties are of concern to natural resource managers. Although aspects of climate change may be novel (e.g., system change and nonstationarity), natural resource managers have long dealt with uncertainties and have developed corresponding approaches to decision-making. Adaptive resource management is an application of structured decision-making for recurrent decision problems with uncertainty, focusing on management objectives, and the reduction of uncertainty over time. We identified 4 types of uncertainty that characterize problems in natural resource management. We examined ways in which climate change is expected to exacerbate these uncertainties, as well as potential approaches to dealing with them. As a case study, we examined North American waterfowl harvest management and considered problems anticipated to result from climate change and potential solutions. Despite challenges expected to accompany the use of adaptive resource management to address problems associated with climate change, we conclude that adaptive resource management approaches will be the methods of choice for managers trying to deal with the uncertainties of climate change. ?? 2010 The Wildlife Society.

Journal of Wildlife Management↗

USGS2011

Resolving structural uncertainty in natural resources management using POMDP approaches

In recent years there has been a growing focus on the uncertainties of natural resources management, and the importance of accounting for uncertainty in assessing management effectiveness. This paper focuses on uncertainty in resource management in terms of discrete-state Markov decision processes (MDP) under structural uncertainty and partial observability. It describes the treatment of structural uncertainty with approaches developed for partially observable resource systems. In particular, I show how value iteration for partially observable MDPs (POMDP) can be extended to structurally uncertain MDPs. A key difference between these process classes is that structurally uncertain MDPs require the tracking of system state as well as a probability structure for the structure uncertainty, whereas with POMDPs require only a probability structure for the observation uncertainty. The added complexity of the optimization problem under structural uncertainty is compensated by reduced dimensionality in the search for optimal strategy. A solution algorithm for structurally uncertain processes is outlined for a simple example in conservation biology. By building on the conceptual framework developed for POMDPs, natural resource analysts and decision makers who confront structural uncertainties in natural resources can take advantage of the rapid growth in POMDP methods and approaches, and thereby produce better conservation strategies over a larger class of resource problems.

Ecological Modelling↗

USGS2007

Adaptive harvest management of North American waterfowl populations: a brief history and future prospects

Since 1995, the US Fish and Wildlife Service has used an adaptive approach to the management of sport harvest of mid-continent Mallard ducks (Anas platyrhynchos) in North America. This approach differs from many current approaches to conservation and management in requiring close collaboration between managers and scientists. Key elements of this process are objectives, alternative management actions, models permitting prediction of system responses, and a monitoring program. The iterative process produces optimal management decisions and leads to reduction in uncertainty about response of populations to management. This general approach to management has a number of desirable features and is recommended for use in many other programs of management and conservation.

Journal of Ornithology↗

USGS2007

Optimal management of non-Markovian biological populations

Wildlife populations typically are described by Markovian models, with population dynamics influenced at each point in time by current but not previous population levels. Considerable work has been done on identifying optimal management strategies under the Markovian assumption. In this paper we generalize this work to non-Markovian systems, for which population responses to management are influenced by lagged as well as current status and/or controls. We use the maximum principle of optimal control theory to derive conditions for the optimal management such a system, and illustrate the effects of lags on the structure of optimal habitat strategies for a predator-prey system.

Ecological Modelling↗

USGS2006

The use of analysis of variance procedures in biological studies

The analysis of variance (ANOVA) is widely used in biological studies, yet there remains considerable confusion among researchers about the interpretation of hypotheses being tested. Ambiguities arise when statistical designs are unbalanced, and in particular when not all combinations of design factors are represented in the data. This paper clarifies the relationship among hypothesis testing, statistical modelling and computing procedures in ANOVA for unbalanced data. A simple two-factor fixed effects design is used to illustrate three common parametrizations for ANOVA models, and some associations among these parametrizations are developed. Biologically meaningful hypotheses for main effects and interactions are given in terms of each parametrization, and procedures for testing the hypotheses are described. The standard statistical computing procedures in ANOVA are given along with their corresponding hypotheses. Throughout the development unbalanced designs are assumed and attention is given to problems that arise with missing cells.

Applied Stochastic Models and Data Analysis↗

USGS2006

MARKOV: A methodology for the solution of infinite time horizon MARKOV decision processes

Algorithms are described for determining optimal policies for finite state, finite action, infinite discrete time horizon Markov decision processes. Both value-improvement and policy-improvement techniques are used in the algorithms. Computing procedures are also described. The algorithms are appropriate for processes that are either finite or infinite, deterministic or stochastic, discounted or undiscounted, in any meaningful combination of these features. Computing procedures are described in terms of initial data processing, bound improvements, process reduction, and testing and solution. Application of the methodology is illustrated with an example involving natural resource management. Management implications of certain hypothesized relationships between mallard survival and harvest rates are addressed by applying the optimality procedures to mallard population models.

Applied Stochastic Models and Data Analysis↗

USGS2006

Monitoring for conservation

Human-mediated environmental changes have resulted in appropriate concern for the conservation of ecological systems and have led to the development of many ecological monitoring programs worldwide. Many programs that are identified with the purpose of `surveillance? represent an inefficient use of conservation funds and effort. Here, we revisit the 1964 paper by Platt and argue that his recommendations about the conduct of science are equally relevant to the conduct of ecological monitoring programs. In particular, we argue that monitoring should not be viewed as a stand-alone activity, but instead as a component of a larger process of either conservation-oriented science or management. Corresponding changes in monitoring focus and design would lead to substantial increases in the efficiency and usefulness of monitoring results in conservation.

Trends in Ecology and Evolution↗

USGS2006

Adaptive harvest management of North American waterfowl populations - recent successes and future prospects

The history of North American waterfowl harvest management has been characterized by attempts to use population monitoring data to make informed harvest management decisions. Early attempts can be characterized as intuitive decision processes, and later efforts were guided increasingly by population models and associated predictions. In 1995, a formal adaptive management process was implemented, and annual decisions about duck harvest regulations in the United States are still based on this process. This formal decision process is designed to deal appropriately with the various forms of uncertainty that characterize management decisions, environmental uncertainty, structural uncertainty, partial controllability and partial observability. The key components of the process are (1) objectives, (2) potential management actions, (3) model(s) of population response to management actions, (4) credibility measures for these models, and (5) a monitoring program. The operation of this iterative process is described, and a brief history of a decade of its use is presented. Future challenges range from social and political issues such as appropriate objectives and management actions, to technical issues such as multispecies management, geographic allocation of harvest, and incorporation of actions that include habitat acquisition and management.

Book chapter↗

USGS2002

Analysis and Management of Animal Populations: Modeling, Estimation and Decision Making

This book deals with the processes involved in making informed decisions about the management of animal populations. It covers the modeling of population responses to management actions, the estimation of quantities needed in the modeling effort, and the application of these estimates and models to the development of sound management decisions. The book synthesizes and integrates in a single volume the methods associated with these themes, as they apply to ecological assessment and conservation of animal populations. KEY FEATURES * Integrates population modeling, parameter estimation and * decision-theoretic approaches to management in a single, cohesive framework * Provides authoritative, state-of-the-art descriptions of quantitative * approaches to modeling, estimation and decision-making * Emphasizes the role of mathematical modeling in the conduct of science * and management * Utilizes a unifying biological context, consistent mathematical notation, * and numerous biological examples

Book↗

USGS2001

Uncertainty, learning, and the optimal management of wildlife

Wildlife management is limited by uncontrolled and often unrecognized environmental variation, by limited capabilities to observe and control animal populations, and by a lack of understanding about the biological processes driving population dynamics. In this paper I describe a comprehensive framework for management that includes multiple models and likelihood values to account for structural uncertainty, along with stochastic factors to account for environmental variation, random sampling, and partial controllability. Adaptive optimization is developed in terms of the optimal control of incompletely understood populations, with the expected value of perfect information measuring the potential for improving control through learning. The framework for optimal adaptive control is generalized by including partial observability and non-adaptive, sample-based updating of model likelihoods. Passive adaptive management is derived as a special case of constrained adaptive optimization, representing a potentially efficient suboptimal alternative that nonetheless accounts for structural uncertainty.

Environmental and Ecological Statistics↗

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↗

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↗

USGS1999

Evaluation of waterfowl conservation under the North American Waterfowl Management Plan

In 1986, the North American Waterfowl Management Plan (Plan) was signed by the U.S. Secretary of the Interior and the Canadian Minister of the Environment, with a goal of restoring waterfowl populations to levels of the 1970s via habitat conservation. Central to the Plan is a set of ambitious continental population goals and habitat objectives to be met through broad-based public-private partnerships. Inadequate attention has been paid to evaluation of the Plan, despite the fact that Plan delivery can be enhanced via improved understanding of the effects of habitat conservation on waterfowl population dynamics. Several factors confound the effort to evaluate the Plan at regional and continental levels, including difficulties in accounting for national land-use policies. To date, evaluation has proceeded along 2 avenues of investigation: (1) the study of conservation actions at local-regional levels, and (2) statistical assessment of Plan assumptions. Among other things, results thus far indicate duck production from the U.S. Northern Great Plains has increased in recent years, and intensive treatments such as planted cover have had positive effects on local reproductive success. Many duck species currently exceed Plan population goals; however, population levels of some species, most notably northern pintail (Anas acuta), remain below expectations based on historic relationships with precipitation. Management implications include the need for ongoing and more carefully prioritized conservation efforts, broader partnerships, and improved understanding of the linkages between habitats and biological processes. Delivery of the Plan must involve collaboration among the Continental Evaluation Team, joint Venture partners, the Adaptive Management and Assessment Team of the U.S. Fish and Wildlife Service, and other conservation groups. Although the challenges and projected costs of Plan conservation efforts are considerable, the long-term potential benefits to waterfowl conservation are great.

Journal of Wildlife Management↗

USGS1995

Use of solicited bands and separation of hunting and natural mortality: a comment

We previously presented (Conroy 1985, Conroy et al. 1989) models for analysis of band recovery data stratified into those voluntarily reported and those obtained by solicitation, similar to models described by Pollock et al. (1994). We discuss differences between the 2 modeling approaches and suggest designs and analyses involving overlapping samples of standard and reward bands to enable adjustment for temporal and geographic variation in reporting and solicitation rates,

Journal of Wildlife Management↗

USGS1989

Patterns of species co-occurrence of nesting colonial Ciconiiformes in Atlantic coast estuarine areas

Patterns of co-occurrence of 11 species of nesting colonial Ciconiiformes in estuarine areas of the Atlantic coast from Maine to Florida were examined using Reciprocal Averaging and Detrended Correspondence Analyses. The first RA ordination axis categorized the species into two groups: species of large birds that often nest in the tops of large trees, and species of smaller birds that usually nest lower down in trees, bushes, or on the ground. The Great Blue Heron (Ardea herodias) showed the largest positive ordination score on this axis, followed by the Wood Stork (Mycteria americana) and the Great Egret (Casmerodius albus). The other 8 species were clumped on the first ordination axis and showed little separation. The second RA axis showed an ordering of relative species abundances along an apparent north-south gradientThere were no consistent similarities of ordination scores of any species pairs or groups on all the major axes, suggesting that no consistent similarities in relative abundances of 2- or 3-species 'assemblages' were found throughout the entire Atlantic Coastal Plain.

Colonial Waterbirds↗