Geology topics

Fred A. Johnson

Publications and source records attributed to Fred A. Johnson.

At least 37 records · Page 2Linked to original sources

USGS2017

Expert elicitation, uncertainty, and the value of information in controlling invasive species

We illustrate the utility of expert elicitation, explicit recognition of uncertainty, and the value of information for directing management and research efforts for invasive species, using tegu lizards (Salvator merianae) in southern Florida as a case study. We posited a post-birth pulse, matrix model in which four age classes of tegus are recognized: hatchlings, 1 year-old, 2 year-olds, and 3 + year-olds. This matrix model was parameterized using a 3-point process to elicit estimates of tegu demographic rates in southern Florida from 10 herpetology experts. We fit statistical distributions for each parameter and for each expert, then drew and pooled a large number of replicate samples from these to form a distribution for each demographic parameter. Using these distributions, as well as the observed correlations among elicited values, we generated a large sample of matrix population models to infer how the tegu population would respond to control efforts. We used the concepts of Pareto efficiency and stochastic dominance to conclude that targeting older age classes at relatively high rates appears to have the best chance of minimizing tegu abundance and control costs. We conclude that expert opinion combined with an explicit consideration of uncertainty can be valuable in conducting an initial assessment of what control strategy, effort, and monetary resources are needed to reduce and eventually eliminate the invader. Scientists, in turn, can use the value of information to focus research in a way that not only increases the efficacy of control, but minimizes costs as well.

Ecological Economics↗

USGS2017

Structured decision making as a conservation tool for recovery planning of two endangered salamanders

At least one-third of all amphibian species face the threat of extinction, and current amphibian extinction rates are four orders of magnitude greater than background rates. Preventing extirpation often requires both ex situ (i.e., conservation breeding programs) and in situ strategies (i.e., protecting natural habitats). Flatwoods salamanders ( Ambystoma bishopi and A. cingulatum ) are protected under the U.S. Endangered Species Act. The two species have decreased from 476 historical locations to 63 recently extant locations (86.8% loss). We suggest that recovery efforts are needed to increase populations and prevent extinction, but uncertainty regarding optimal actions in both ex situ and in situ realms hinders recovery planning. We used structured decision making (SDM) to address key uncertainties regarding both captive breeding and habitat restoration, and we developed short-, medium-, and long-term goals to achieve recovery objectives. By promoting a transparent, logical approach, SDM has proven vital to recovery plan development for flatwoods salamanders. The SDM approach has clear advantages over other previous approaches to recovery efforts, and we suggest that it should be considered for other complex decisions regarding endangered species.

Journal for Nature Conservation↗

USGS2016

Learning and adaptation in waterfowl conservation: By chance or by design?

The most recent revision of the North American Waterfowl Management Plan seeks to increase the adaptive capacity of the management enterprise to cope with accelerating changes in climate, land-use patterns, agency priorities, and the waterfowl and wetlands constituency. Institutional and cultural changes of the magnitude envisioned are necessarily slow, messy processes, involving many actors who at a minimum must agree on the need for change. Waterfowl conservation now finds itself in the transition zone between business as usual and some new mode of operation. There are at least 2 different perspectives of this transition: one focuses on process, accountability, and planning for change; another focuses on solutions generated from an organic process of creativity, information sharing, and risk-taking. Both of these views have something to contribute, but some in the wildlife management enterprise may tend to focus more on the first view. We suggest that ideas from panarchy theory, especially those related to the behaviors of complex adaptive systems, can help waterfowl managers better understand and foster the institutional changes they seek.

Wildlife Society Bulletin↗

USGS2016

State-dependent resource harvesting with lagged information about system states

Markov decision processes (MDPs), which involve a temporal sequence of actions conditioned on the state of the managed system, are increasingly being applied in natural resource management. This study focuses on the modification of a traditional MDP to account for those cases in which an action must be chosen after a significant time lag in observing system state, but just prior to a new observation. In order to calculate an optimal decision policy under these conditions, possible actions must be conditioned on the previous observed system state and action taken. We show how to solve these problems when the state transition structure is known and when it is uncertain. Our focus is on the latter case, and we show how actions must be conditioned not only on the previous system state and action, but on the probabilities associated with alternative models of system dynamics. To demonstrate this framework, we calculated and simulated optimal, adaptive policies for MDPs with lagged states for the problem of deciding annual harvest regulations for mallards (Anas platyrhynchos) in the United States. In this particular example, changes in harvest policy induced by the use of lagged information about system state were sufficient to maintain expected management performance (e.g. population size, harvest) even in the face of an uncertain system state at the time of a decision.

PLoS ONE↗

USGS2016

Spatially explicit control of invasive species using a reaction-diffusion model

Invasive species, which can be responsible for severe economic and environmental damages, must often be managed over a wide area with limited resources, and the optimal allocation of effort in space and time can be challenging. If the spatial range of the invasive species is large, control actions might be applied only on some parcels of land, for example because of property type, accessibility, or limited human resources. Selecting the locations for control is critical and can significantly impact management efficiency. To help make decisions concerning the spatial allocation of control actions, we propose a simulation based approach, where the spatial distribution of the invader is approximated by a reaction–diffusion model. We extend the classic Fisher equation to incorporate the effect of control both in the diffusion and local growth of the invader. The modified reaction–diffusion model that we propose accounts for the effect of control, not only on the controlled locations, but on neighboring locations, which are based on the theoretical speed of the invasion front. Based on simulated examples, we show the superiority of our model compared to the state-of-the-art approach. We illustrate the use of this model for the management of Burmese pythons in the Everglades (Florida, USA). Thanks to the generality of the modified reaction–diffusion model, this framework is potentially suitable for a wide class of management problems and provides a tool for managers to predict the effects of different management strategies.

Ecological Modelling↗

USGS2016

Regulation of the hunting season as a tool for adaptive harvest management — First results for pink-footed geese Anser brachyrhynchus

Adjustment of hunting season length is often used to regulate harvest of waterbirds but the effects are disputed. We describe the first results of season length extension on the harvest of the pink-footed goose, which has been selected as the first test case of adaptive harvest management of waterbirds in Europe. In Denmark, the season (previously 1 September to 31 December) was extended to include January in 2014-15 with the aim to increase the harvest and, in the longer term, reduce the population size. The total harvest in Denmark increased by 52% compared to previous years, and almost 50% of the Danish harvest was taken in the January extension. In the course of the hunting season, the proportion of adults in the bag increased. In this case, the outcomes from the first extension of season suggest that season length adjustment can be an effective tool to regulate harvest, though dependent on winter weather conditions and hunters’ motivation for shooting geese.

Wildlife Biology↗

USGS2016

Adaptive harvest management for the Svalbard population of pink‐footed geese: 2016 progress summary: Technical Report from DCE – Danish Centre for Environment and Energy, No. 86

This document describes progress to date on the development of an adaptive harvest management strategy for maintaining the Svalbard population of pink‐footed geese (Anser brachyrhynchus) near their agreed target level (60,000) by providing for sustainable harvests in Norway and Denmark. This report provides an assessment of the most recent monitoring information (1991-2015) and its implications for the harvest management strategy. By combining varying hypotheses about survival and reproduction, a suite of nine models have been developed that represent a wide range of possibilities concerning the extent to which demographic rates are density dependent or independent. These results suggest that the pink‐footed goose population may have recently experienced a release from density‐dependent mechanisms, corresponding to the period of most rapid growth in population size. Beginning with the 2016 hunting season, harvest quotas will be prescribed on an annual basis rather than every three years because of the potential to better meet population management objectives. Based on updated model weights, the recent observations of population size (74,800), the proportion of the population comprised of one-year-old birds (0.138), and temperature days in Svalbard (20), the optimal harvest quota for the 2016 hunting season is 25,000. The large increase in quota compared to that during first three years of AHM reflects stakeholders’ desire to reduce population size to the goal of 60,000, recognizing that population size remains relatively high and above-average production is expected in 2016 due to a warm spring.

Report↗

USGS2016

Application of decision science to resilience management in Jamaica Bay

This book highlights the growing interest in management interventions designed to enhance the resilience of the Jamaica Bay socio-ecological system. Effective management, whether the focus is on managing biological processes or human behavior or (most likely) both, requires decision makers to anticipate how the managed system will respond to interventions (i.e., via predictions or projections). In systems characterized by many interacting components and high uncertainty, making probabilistic predictions is often difficult and requires careful thinking not only about system dynamics, but also about how management objectives are specified and the analytic method used to select the preferred action(s). Developing a clear statement of the problem(s) and articulation of management objectives is often best achieved by including input from managers, scientists and other stakeholders affected by the decision through a process of joint problem framing (Marcot and others 2012; Keeney and others 1990). Using a deliberate, coherent and transparent framework for deciding among management alternatives to best meet these objectives then ensures a greater likelihood for successful intervention. Decision science provides the theoretical and practical basis for developing this framework and applying decision analysis methods for making complex decisions under uncertainty and risk.

Book chapter↗

USGS2016

Development of an adaptive harvest management program for Taiga bean geese

This report describes recent progress in specifying the elements of an adaptive harvest program for taiga bean goose. It describes harvest levels appropriate for first rebuilding the population of the Central Management Unit and then maintaining it near the goal specified in the AEWA International Single Species Action Plan (ISSAP). This report also provides estimates of the length of time it would take under ideal conditions (no density dependence and no harvest) to rebuild depleted populations in the Western and Eastern Management Units. We emphasize that our estimates are a first approximation because detailed demographic information is lacking for taiga bean geese. Using allometric relationships, we estimated parameters of a thetalogistic matrix population model. The mean intrinsic rate of growth was estimated as r = 0.150 (90% credible interval: 0.120 – 0.182). We estimated the mean form of density dependence as   2.361 (90% credible interval: 0.473 – 11.778), suggesting the strongest density dependence occurs when the population is near its carrying capacity. Based on expert opinion, carrying capacity (i.e., population size expected in the absence of hunting) for the Central Management Unit was estimated as K  87,900 (90% credible interval: 82,000 – 94,100). The ISSAP specifies a population goal for the Central Management Unit of 60,000 – 80,000 individuals in winter; thus, we specified a preliminary objective function as one which would minimize the difference between this goal and population size. Using the concept of stochastic dominance to explicitly account for uncertainty in demography, we determined that optimal harvest rates for 5, 10, 15, and 20-year time horizons were h = 0.00, 0.02, 0.05, and 0.06, respectively. These optima represent a tradeoff between the harvest rate and the time required to achieve and maintain a population size within desired bounds. We recognize, however, that regulation of absolute harvest rather than harvest rate is more practical, but our matrix model does not permit one to calculate an exact harvest associated with a specific harvest rate. Approximate harvests for current population size in the Central Management Unit are 0, 1,200, 2,300, and 3,500 for the 5, 10, 15, and 20-year time horizons, respectively. Populations of taiga bean geese in the Western and Eastern Units would require at least 10 and 13 years, respectively, to reach their minimum goals under the most optimistic of scenarios. The presence of harvest, density dependence, or environmental variation could extend these time frames considerably. Finally, we stress that development and implementation of internationally coordinated monitoring programs will be essential to further development and implementation of an adaptive harvest management program.

Conference Paper↗

USGS2015

Value of information and natural resources decision-making

Though the potential for information to measurably improve management has been highlighted for several decades, in recent years the “value of information” has surfaced with increasing frequency in natural resources. However, the use of this phrase belies the fact that many in natural resources have only a limited understanding about what it actually means, how to measure it, and what to do with it. We introduce and describe several forms of the value of information in a context of the management of renewable natural resources. The value of information is discussed in terms of a potential gain in value with the addition of new information, as well as a loss in value associated with the absence of information. Value metrics are developed for uncertainty about resource status as well as resource processes and responses to management. We provide a common notation for the metrics of value, and discuss linkages of the value of information to strategic approaches such as adaptive resources management and partially observable decision processes.

Wildlife Society Bulletin↗

USGS2015

Training conservation practitioners to be better decision makers

Traditional conservation curricula and training typically emphasizes only one part of systematic decision making ( i.e. , the science), at the expense of preparing conservation practitioners with critical skills in values-setting, working with decision makers and stakeholders, and effective problem framing. In this article we describe how the application of decision science is relevant to conservation problems and suggest how current and future conservation practitioners can be trained to be better decision makers. Though decision-analytic approaches vary considerably, they all involve: (1) properly formulating the decision problem; (2) specifying feasible alternative actions; and (3) selecting criteria for evaluating potential outcomes. Two approaches are available for providing training in decision science, with each serving different needs. Formal education is useful for providing simple, well-defined problems that allow demonstrations of the structure, axioms and general characteristics of a decision-analytic approach. In contrast, practical training can offer complex, realistic decision problems requiring more careful structuring and analysis than those used for formal training purposes. Ultimately, the kinds and degree of training necessary depend on the role conservation practitioners play in a decision-making process. Those attempting to facilitate decision-making processes will need advanced training in both technical aspects of decision science and in facilitation techniques, as well as opportunities to apprentice under decision analysts/consultants. Our primary goal should be an attempt to ingrain a discipline for applying clarity of thought to all decisions.

Sustainability↗

USGS2015

Optimization and resilience in natural resources management

We consider the putative tradeoff between optimization and resilience in the management of natural resources, using a framework that incorporates different sources of uncertainty that are common in natural resources management. We address one-time decisions, and then expand the decision context to the more complex problem of iterative decision making. For both cases we focus on two key sources of uncertainty: partial observability of system state and uncertainty as to system dynamics. Optimal management strategies will vary considerably depending on the timeframe being considered and the amount and quality of information that is available to characterize system features and project the consequences of potential decisions. But in all cases an optimal decision making framework, if properly identified and focused, can be useful in recognizing sound decisions. We argue that under the conditions of deep uncertainty that characterize many resource systems, an optimal decision process that focuses on robustness does not automatically induce a loss of resilience.

Book chapter↗

USGS2015

On formally integrating science and policy: walking the walk

The contribution of science to the development and implementation of policy is typically neither direct nor transparent. In 1995, the U.S. Fish and Wildlife Service (FWS) made a decision that was unprecedented in natural resource management, turning to an unused and unproven decision process to carry out trust responsibilities mandated by an international treaty. The decision process was adopted for the establishment of annual sport hunting regulations for the most economically important duck population in North America, the 6 to 11 million mallards Anas platyrhynchos breeding in the mid-continent region of north-central United States and central Canada. The key idea underlying the adopted decision process was to formally embed within it a scientific process designed to reduce uncertainty (learn) and thus make better decisions in the future. The scientific process entails use of models to develop predictions of competing hypotheses about system response to the selected action at each decision point. These prediction not only are used to select the optimal management action, but also are compared with the subsequent estimates of system state variables, providing evidence for modifying degrees of confidence in, and hence relative influence of, these models at the next decision point. Science and learning in one step are formally and directly incorporated into the next decision, contrasting with the usual ad hoc and indirect use of scientific results in policy development and decision-making. Application of this approach over the last 20 years has led to a substantial reduction in uncertainty, as well as to an increase in transparency and defensibility of annual decisions and a decrease in the contentiousness of the decision process. As resource managers are faced with increased uncertainty associated with various components of global change, this approach provides a roadmap for the future scientific management of natural resources.

Journal of Applied Ecology↗

USGS2015

Multilevel learning in the adaptive management of waterfowl harvests: 20 years and counting

In 1995, the U.S. Fish and Wildlife Service implemented an adaptive harvest management program (AHM) for the sport harvest of midcontinent mallards ( Anas platyrhynchos ). The program has been successful in reducing long-standing contentiousness in the regulatory process, while integrating science and policy in a coherent, rigorous, and transparent fashion. After 20 years, much has been learned about the relationship among waterfowl populations, their environment, and hunting regulations, with each increment of learning contributing to better management decisions. At the same time, however, much has been changing in the social, institutional, and environmental arenas that provide context for the AHM process. Declines in hunter numbers, competition from more pressing conservation issues, and global-change processes are increasingly challenging waterfowl managers to faithfully reflect the needs and desires of stakeholders, to account for an increasing number of institutional constraints, and to (probabilistically) predict the consequences of regulatory policy in a changing environment. We review the lessons learned from the AHM process so far, and describe emerging challenges and ways in which they may be addressed. We conclude that the practice of AHM has greatly increased an awareness of the roles of social values, trade-offs, and attitudes toward risk in regulatory decision-making. Nevertheless, going forward the waterfowl management community will need to focus not only on the relationships among habitat, harvest, and waterfowl populations, but on the ways in which society values waterfowl and how those values can change over time.

Wildlife Society Bulletin↗

USGS2015

Value of information in natural resource management: technical developments and application to pink-footed geese

The “value of information” (VOI) is a generic term for the increase in value resulting from better information to guide management, or alternatively, the value foregone under uncertainty about the impacts of management (Yokota and Thompson, Medical Decision Making 2004; 24 : 287). The value of information can be characterized in terms of several metrics, including the expected value of perfect information and the expected value of partial information. We extend the technical framework for the value of information by further developing the relationship between value metrics for partial and perfect information and describing patterns of their performance. We use two different expressions for the expected value of partial information to highlight its relationship to the expected value of perfect information. We also develop the expected value of partial information for hierarchical uncertainties. We highlight patterns in the value of information for the Svalbard population of the pink-footed goose ( Anser brachyrhynchus ), a population that is subject to uncertainty in both reproduction and survival functions. The framework for valuing information is seen as having widespread potential in resource decision making, and serves as a motivation for resource monitoring, assessment, and collaboration.

Svalbard↗

USGS2015

Global change and conservation triage on National Wildlife Refuges

National Wildlife Refuges (NWRs) in the United States play an important role in the adaptation of social-ecological systems to climate change, land-use change, and other global-change processes. Coastal refuges are already experiencing threats from sea-level rise and other change processes that are largely beyond their ability to influence, while at the same time facing tighter budgets and reduced staff. We engaged in workshops with NWR managers along the U.S. Atlantic coast to understand the problems they face from global-change processes and began a multidisciplinary collaboration to use decision science to help address them. We are applying a values-focused approach to base management decisions on the resource objectives of land managers, as well as those of stakeholders who may benefit from the goods and services produced by a refuge. Two insights that emerged from our workshops were a conspicuous mismatch between the scale at which management can influence outcomes and the scale of environmental processes, and the need to consider objectives related to ecosystem goods and services that traditionally have not been explicitly considered by refuges (e.g., protection from storm surge). The broadening of objectives complicates the decision-making process, but also provides opportunities for collaboration with stakeholders who may have agendas different from those of the refuge, as well as an opportunity for addressing problems across scales. From a practical perspective, we recognized the need to (1) efficiently allocate limited staff time and budgets for short-term management of existing programs and resources under the current refuge design and (2) develop long-term priorities for acquiring or protecting new land/habitat to supplement or replace the existing refuge footprint and thus sustain refuge values as the system evolves over time. Structuring the decision-making problem in this manner facilitated a better understanding of the issues of scale and suggested that a long-term solution will require a significant reassessment of objectives to better reflect the comprehensive values of refuges to society. We discuss some future considerations to integrate these two problems into a single framework by developing novel optimization approaches for dynamic problems that account for uncertainty in future conditions.

Ecology and Society↗

USGS2015

Adaptive harvest management for the Svalbard population of Pink-Footed Geese: 2014 progress summary

This document describes progress to date on the development of an adaptive harvest-management strategy for maintaining the Svalbard population of pink-footed geese (Anser brachyrhynchus) near their agreed target level (60 thousand) by providing for sustainable harvests in Norway and Denmark. Specifically, this report provides an assessment of the most recent monitoring information and its implications for the harvest management strategy. The development of a passively adaptive harvest management strategy requires specification of four elements: (a) a set of alternative population models, describing the effects of harvest and other relevant environmental factors; (b) a set of probabilities describing the relative credibility of the alternative models, which are updated each year based on a comparison of model predictions and monitoring information; (c) a set of alternative harvest quotas, from which a 3-year quota is chosen; and (d) an objective function, by which alternative harvest strategies can be evaluated and an optimal strategy chosen. By combining varying hypotheses about survival and reproduction, a suite of nine models have been developed that represent a wide range of possibilities concerning the extent to which demographic rates are density dependent or independent, and the extent to which spring temperatures are important. Five of the models incorporate density-dependent mechanisms that would maintain the population near a carrying capacity (i.e., in the absence of harvest) of 65k – 129k depending on the specific model. The remaining four models are density independent and predict an exponentially growing population even with moderate levels of harvest. The most current set of monitoring information was used to update model weights for the period 1991 – 2013. Current model weights suggest little or no evidence for density-dependent survival and reproduction. These results suggest that the pink-footed goose population may have recently experienced a release from density-dependent mechanisms, corresponding to the period of most rapid growth in population size. There was equivocal evidence for the effect of May temperature days (number of days with temperatures above freezing: TempDays) on survival and on reproduction. During the summer of 2013 we computed an optimal harvest strategy for the 3-year period 2013 – 2015. The strategy suggested that the appropriate annual harvest quota is 15 thousand. The 1-year harvest strategy calculated to determine whether an emergency closure of the hunting season is required this year suggested an allowable harvest of 25.0 thousand; thus, a hunting-season closure is not warranted. If the harvest quota of 15 thousand were met in the coming hunting season, the next population count would be expected to be 71.0 thousand. If only the most recent 4-year mean harvest were realized (11.3 thousand), a population size of 74.8 thousand would be expected. Simulations suggest that it will take approximately seven years at current harvest levels to reduce population size to the goal of 60 thousand. However, it is possible that the extension of the forthcoming hunting season in Denmark could result in a total harvest approaching 15 thousand; in this case, simulations suggest it would only take about three years to reach the goal.

Svalbard↗

USGS2015

Adaptive harvest management: Adjustments for SEIS 2013

This report provides a summary of revised methods and assessment results based on updated adaptive harvest management (AHM) protocols developed in response to the preferred alternative specified in the Final Supplemental Environmental Impact Statement on the Issuance of Annual Regulations Permitting the Hunting of Migratory Birds (SEIS; U.S. Department of the Interior 2013). We describe necessary changes to optimization procedures and decision processes for the implementation of AHM for midcontinent, eastern and western mallards (Anas platyrhynchos), northern pintails (Anas acuta), and scaup (Aythya affinis, A. marila) decision frameworks. We present this final report for communication purposes, and acknowledge that any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

U.S. Fish and Wildlife Service Report↗