Geology topics

Fred A. Johnson

Publications and source records attributed to Fred A. Johnson.

At least 19 recordsLinked to original sources

USGS2021

Cape Romain partnership for coastal protection

This final report summarizes activities, outcomes, and lessons learned from a 3-year project titled “Climate Change Adaptation for Coastal National Wildlife Refuges” with the Cape Romain National Wildlife Refuge (NWR) and local partners in the surrounding South Carolina Lowcountry. The Lowcountry is classified as the 10-county area encompassing the coastal plain of South Carolina (this report specifically focuses on Berkeley, Charleston, and Georgetown Counties). The goals of this work, sponsored by the U.S. Geological Survey’s Southeast Climate Adaptation Science Center (SECASC), were to foster active engagement with stakeholders; to develop a comprehensive definition of adaptation problems faced by agencies, organizations, and individuals near the Cape Romain NWR that accounts for global change, local values, knowledge and perceptions; and to encourage social learning and building of effective networks and trust across South Carolina Lowcountry organizations and individuals. Although project scoping began at the scale of the Atlantic seaboard, by engaging with NWRs from Massachusetts to Florida, participating refuge personnel eventually selected the Cape Romain NWR to serve as a case study for testing our goals. The Cape Romain Partnership for Coastal Conservation was established to address global change impacts at a regional level and includes representation from Federal and State resource agencies, local conservation nongovernmental organizations, and organizations representing underserved community interests. Research topics, originating from discussions with Cape Romain Partnership for Coastal Conservation members, focused on quantifying key drivers of change including localized sea-level rise (SLR) predictions, estimates of coastal hurricane inundation as amplified by SLR, and urban growth trends and forecasts. These key drivers provided a foundation to engage stakeholders in planning exercises to begin a process of collective understanding and collaborative decision making. The goal of this process was to develop collective strategies of adaptation to enhance community and ecosystem resilience in the South Carolina Lowcountry. South Carolina’s Lowcountry is experiencing rapid environmental and social transformation because of SLR rates approaching twice the global average, chronic tidal flooding and catastrophic storm surges, erosion and loss of habitats that provide essential services to wildlife and humans, and increasing social polarization fueled by aggressive low-density urban growth and other forms of land conversion. To support characterizations of plausible future scenarios, we used available or, in some cases, developed new models to project future conditions of key environmental and social-economic drivers. Because of the imprecision of mean global SLR projections, the SECASC commissioned a climatological study to account for local conditions and multiple representative concentration pathways to project a tailored distribution of future sea levels. These projections were matched to SLR scenarios provided by existing models to anticipate the range of future coastal habitat changes in the South Carolina Lowcountry. SLR scenarios were also incorporated into existing storm-surge models, which do not account for alternate baseline sea levels, to project the local effects of future hurricanes. To evaluate the extent and effects of population growth and urban expansion, we relied on an existing urban-growth model to map the spatial distribution of land-conversion probabilities, the total area of which is predicted to increase twofold to threefold over the next 60 years. In addition to this simplified model, an econometric model is in development to account for nonlinear feedback dynamics in land value, land use, and ecosystem service production. Although not yet completed, the goals of this model are to produce more-detailed projections of growth dynamics and to allow predictions of development patterns resulting from alternate land-use planning policies and incentives. Collaborative planning for an uncertain future requires more than providing decision makers with information on future physical and ecological conditions; developing effective and consensual strategies must also integrate sociological values, multiple cultural perspectives, and an understanding of human behavior. To support broad stakeholder engagement in integrative approaches to adaptation planning, emphasis was placed on the importance of considering differences in how individuals perceive their environment and create meaning. Because cultural frameworks form the basis for perceptions and, ultimately, the behaviors of individuals and institutions, we describe a model of human behavior and how it can be used to understand the effect of cultural complexity and variation in perception on choices, behavioral change, and long-term maintenance of behaviors. We consider a model commonly used in the field of behavioral health that accommodates variation in human perception when describing stages of behavior and the dynamics of behavioral change. Tailoring communication and engagement activities to targeted stakeholders is likely to benefit from increased understanding of behavioral change processes. The complex nature of this problem limited the usefulness of a traditional decision-analytic approach, we explored alternative methods for engagement, collaborative learning and decision making. Recognizing that project partners and Lowcountry stakeholders may be at different stages of preparedness and interest level for modifying behavior as a function of global change, we facilitated a scenario-planning exercise to familiarize partners with this well-established approach for communicating the opportunities and threats arising under alternative, plausible futures. We developed narratives for four alternative South Carolina Lowcountry scenarios to be used in later strategic planning that focus on quantitative trends for three primary drivers with high impact and high uncertainty: manifestations of climate change, social-political shifts at a global level, and forces of local value and power structures. This scenario-planning exercise underscored the complex relation between the temporospatial scale of the production of ecological goods and services and the institutional scale at which they are managed. We then guided the partners through an assessment of the relevant strengths and weaknesses of the Cape Romain Partnership for Coastal Protection, using the threats and opportunities characterized by each scenario to understand how the partnership might respond when attempting to meet conservation and societal objectives. The partnership identified key strengths including partnership experience, outreach and technical capacities, a substantial conservation land base, and high social cohesion in the South Carolina Lowcountry. Limited communication expertise, institutional inertia, and insufficient staffing and funding were recognized as important weaknesses across the partnership. By examining and scoring combinations of internal strengths and weaknesses and external threats and opportunities, the partnership developed sets of prioritized strategies to consider in the context of a given scenario. Although we had insufficient time to examine all scenarios in detail, the intent was to identify a portfolio of strategic actions to address threats and opportunities represented in multiple plausible futures. Top-ranking strategies encompassed a range of actions that focused on strengthening the conservation community and communicating the benefits of nature (that is, ecosystem services) to leveraging partnerships to expand land protection. This report also details the methods and preliminary results of several models developed or applied in support of this project. Two parcel-selection algorithms were used to evaluate anticipated habitat changes and patterns of urban growth to guide decisions on optimal conservation reserve design to protect habitat communities. One approach used a widely available planning software (MARXAN) to maximize conservation benefits near the Cape Romain NWR, whereas the other approach was a novel application of economic theory to account for uncertainty in future conditions and for the risks of unanticipated habitat loss. This latter model applies modern portfolio theory to estimate the risk of investing in any portfolio of land parcels (that is, candidate “reserves”) under climate-change uncertainty by quantifying the variation and spatial correlation of conservation benefits derived from each portfolio. We expanded the range of actions beyond simply whether or not to invest in a set of land parcels, an approach commonly used in spatial conservation planning, to also include consideration of divestment from currently protected lands. Such refinements allow for better accounting of system dynamics and can evaluate the benefits of flexible conservation tools such as rolling easements. Model results were conditional on a decision maker’s risk tolerance but highlighted general strategies of land conservation to increase future habitat representation beyond what is expected under the current protected land base. We built models that may help inform coastal planning by estimating salinity dynamics and the performance of oyster reef restoration efforts to predict the combined effects of global change and management of freshwater flows on coastal habitats and the processes that contribute to their resilience. These models can support restoration decisions by evaluating the expected benefits of site locations for shoreline protection and fisheries production. Lastly, we developed a spatially explicit economic model that predicts feedback dynamics among land value, land-use change, and effects on ecosystem service provision to explore zoning policies and incentives on urban growth and ecosystem services. We summarize these efforts with insights and considerations for the Cape Romain Partnership for Coastal Protection to continue to engage stakeholders in effective adaptation planning. First, notions of place attachment (referred to as sense of place), and the role of culture in social discourse are increasingly being used to understand the complex interactions between society and the environment and how societies respond and adapt to climate change. Sense of place was a unifying theme whenever the future of the South Carolina Lowcountry was discussed. The contribution of the South Carolina Lowcountry’s environmental wealth, rich cultural heritage, and quality of life to sense of place has important implications for how adaptation planning might best be pursued. More community-based governance of the commons (in other words, natural and cultural resources held in common), in which broad stakeholder participation and power sharing are key elements, is considered important. This devolution of governance is characterized by polycentric institutions and self-organizing social networks that promote a local culture of knowledge sharing, problem solving, and learning. These so-called bridging organizations (or individuals) often provide the leadership necessary to bring together potentially disparate Government agencies and institutions, private organizations, and individuals in a collective process of problem solving. Our observations also suggest that the conservation community in the South Carolina Lowcountry views its activities as integral to the broader governance of social-ecological systems, in which responses to the forces of global change are mediated through culture, economics, and politics. Rather than directly competing with other interests, the South Carolina Lowcountry conservation community seems to embrace an interpretation of conservation in which the fundamental objective is the quality of human life rather than environmental protection. Fundamental to the types of governance reforms described above is the notion of coproduction, in which experts and users collaborate to develop a shared body of knowledge. In this approach, scientists work with stakeholders to help frame questions, design research, and collect and analyze data. Such sustained collaborations are increasingly believed to be an effective way to produce useable (or actionable) science. The emphasis on social learning, leveraging strong social networks, coordinating and deliberating among diverse stakeholders, and applying principles of adaptive management is an essential contribution to adaptive capacity. The diverse and robust set of scientific approaches, methods to help stakeholders collaborate in effective and goal-driven planning processes, and decision tools resulting from this project hopefully will assist Cape Romain NWR and its partners prepare for climatic, ecological, and social changes over the coming decades.

South Carolina↗

USGS2020

Category count models for adaptive management of metapopulations: Case study of an imperiled salamander

Managing spatially structured populations of imperiled species presents many challenges. Spatial structure can make it difficult to predict population responses to potential recovery activities, and learning through experimentation may not be advised if it could harm threatened populations. Adaptive management provides an appealing framework when experimentation is considered too risky or time consuming; we used such an approach for imperiled flatwoods salamanders at a Florida wildlife refuge. We represented this metapopulation with category count models and used stochastic dynamic programming to identify optimal decision policies that weighed trade‐offs between metapopulation persistence and management costs. We defined possible wetland categories in terms of habitat suitability and occupancy, specified category‐specific management actions, and identified transition probabilities via expert elicitation for two management strategies: “future” status quo (FSQ; frequent growing‐season burns) and extra management actions (EMA; restoration, translocation, head‐starting). We simulated metapopulation dynamics using the resulting optimal management policy and found that under model FSQ, occupancy steadily declined over time, indicating that populations would rapidly become extirpated; with model EMA, occupancy remained stable, suggesting that populations would persist only if additional actions are applied and are effective. This approach can be used to identify optimal solutions while accounting for uncertainty and considering both habitat and population dynamics, and to help managers make conservation decisions for populations at imminent risk of extinction.

Florida↗

USGS2020

Building adaptive capacity in a coastal region experiencing global change

Coastal ecosystems in the eastern U.S. have been severely altered by human development, and climate change and other stressors are now further degrading the capacity of those ecological and social systems to remain resilient in the face of such disturbances. We sought to identify potential ways in which local conservation interests in the Lowcountry of South Carolina (USA) could participate in a social process of adaptation planning, and how that process might ultimately be broadened to engage a more diverse set of partners. We engaged participants through a combination of informal meetings, workshops, and other collaborative interactions to explore how the conservation community perceives and pursues its various missions, and how that community might confront the threats and opportunities in its future. Coproduction of knowledge and meaning were facilitated by collaborative scenario planning and strategic planning evaluation, which illuminated how the conservation community is integral to the broader governance of the region and highlighted how responses to forces of change are mediated through local culture, economics, and politics. We suggest an interpretation of conservation in which the fundamental objectives of both social and ecological systems might be prioritized in tandem, rather than narrowly focusing on environmental protection without consideration of the social landscape. Ultimately, adaptive capacity depends on the ability to act collectively, and social capital, trust, and organization greatly influence the capacity to act. Thus, we conclude that the presence of strong social networks, coordination and deliberation among diverse stakeholders, mechanisms for experiential feedback, and emphasis on social learning are key elements needed to build adaptive capacity. Central to the evolving perspective of governance of the commons is recognition that social and ecological systems are coupled; the issues and problems of one cannot be addressed without considering the consequences for the other. Moreover, a dominant theme emerging from our research and that of other scholars is the importance of culture and place attachment, which generates social cohesion and facilitates problem solving. These ideas have important implications for when, where, and how stakeholders are engaged to address the rapid changes being experienced by social-ecological systems.

South Carolina↗

USGS2019

Optimal spatial allocation of control effort to manage invasives in the face of imperfect detection and misclassification

Imperfect detection and misclassification errors are often ignored in the context of invasive species management. Here we present an approach that combines spatially explicit models and an optimization technique to design optimal search and destroy strategies based on noisy monitoring observations. We focus on two invasive plants, melaleuca ( Melaleuca quinquenervia ) and Old World climbing fern ( Lygodium microphyllum ), which continue to cause important damages to the Everglades ecosystem. We present a methodological framework that combines Hidden Markov Random Field (HMRF, initially developed for image analysis) and linear programming to optimally search for invasive species. A benefit of this approach is that it accounts for the spatial structure of the system by using a spatially explicit modeling approach (i.e. HMRF), and does not require repeated visits to model the probability of occurrence of species. We found on simulated cases that our approach can lead to substantial improvements in control efficiency when compared to state of the art model-free approaches. For example, in the case of the old world fern, simulations showed that the optimal strategy would allow managers to control up to 34% more sites than with model-free approaches that ignored misclassification and imperfect detection. For melaleuca it was possible to control up to 20% more sites. The vast increase in imagery data obtained from different sources (e.g. unmanned aerial systems, and satellite) provides great opportunities to improve management of natural resources by applying modern computational methods such as the one we present. Our approach can substantially increases the efficiency of invasive species control by accounting for imperfect detection, misclassification error and the spatial structure of the system. Our approach is applicable to other systems and problems, for example it could be applied to the control of plant pathogens, or optimal extraction of resources (e.g. minerals or biological resources).

Ecological Modelling↗

USGS2018

Designing a protected area to safeguard imperiled species from urbanization

Reserve design is a process that can address ecological, social, and political factors to identify parcels of land needed to sustain wildlife populations and other natural resources. Acquisition of parcels for a large terrestrial reserve is difficult because it typically occurs over a long timeframe and thus invokes consideration of future conditions such as climate and urbanization changes. In central Florida, a new protected area, the Everglades Headwaters National Wildlife Refuge, has been authorized by the United States Government. The new refuge will host important threatened and endangered species and habitats, as well as be located to allow for species adaptation from climate change impacts. For this study we combined habitat objectives defined by the U.S. Fish and Wildlife Service and projections from two urbanization models to provide guidance for Everglades Headwaters National Wildlife Refuge design. We used Marxan with Zones to find near-optimal solutions for protecting explicit amounts of five target habitats. We identified parcels for inclusion into the reserve design that the model allocated among two zones representing different methods of protection: fee-simple purchase (up to 20,234 hectares authorized by the United States government), and conservation easement agreements (up to 40,469 hectares authorized). As expected, for all scenarios we found an increase in costs as the proportion of fee-simple purchases was increased, reflecting the lesser cost of easements, but the number of parcels required for protection differed little among scenarios. The two urbanization models showed considerable agreement over which habitat patches were not forecast to be developed, and showed some agreement over which parcels might be developed. The U.S. Fish and Wildlife Service may benefit from focusing on parcels that are selected frequently by our analyses under both urban scenarios because these parcels are more likely to be in areas where urbanization threats and demand for land is reduced. The reserve designs we generated met U.S. Fish and Wildlife Service habitat goals within fee and easement zone restrictions, and we found reserve configurations that fell well below the mandated size limit.

Florida↗

USGS2018

Value of sample information in dynamic, structurally uncertain resource systems

Few if any natural resource systems are completely understood and fully observed. Instead, there almost always is uncertainty about the way a system works and its status at any given time, which can limit effective management. A natural approach to uncertainty is to allocate time and effort to the collection of additional data, on the reasonable assumption that more information will facilitate better understanding and lead to better management. But the collection of more data, either through observation or investigation, requires time and effort that often can be put to other conservation activities. An important question is whether the use of limited resources to improve understanding is justified by the resulting potential for improved management. In this paper we address directly a change in value from new information collected through investigation. We frame the value of information in terms of learning through the management process itself, as well as learning through investigations that are external to the management process but add to our base of understanding. We provide a conceptual framework and metrics for this issue, and illustrate them with examples involving Florida scrub-jays (Aphelocoma coerulescens).

PLoS ONE↗

USGS2018

Dynamic minimum set problem for reserve design: Heuristic solutions for large problems

Conversion of wild habitats to human dominated landscape is a major cause of biodiversity loss. An approach to mitigate the impact of habitat loss consists of designating reserves where habitat is preserved and managed. Determining the most valuable areas to preserve in a landscape is called the reserve design problem. There exists several possible formulations of the reserve design problem, depending on the objectives and the constraints. In this article, we considered the dynamic problem of designing a reserve that contains a desired area of several key habitats. The dynamic case implies that the reserve cannot be designed in one time step, due to budget constraints, and that habitats can be lost before they are reserved, due for example to climate change or human development. We proposed two heuristics strategies that can be used to select sites to reserve each year for large reserve design problem. The first heuristic is a combination of the Marxan and site-ordering algorithms and the second heuristic is an augmented version of the common naive myopic heuristic. We evaluated the strategies on several simulated examples and showed that the augmented greedy heuristic is particularly interesting when some of the habitats to protect are particularly threatened and/or the compactness of the network is accounted for.

PLoS ONE↗

USGS2018

Making do with less: Must sparse data preclude informed harvest strategies for European waterbirds?

The demography of many European waterbirds is not well understood because most countries have conducted little monitoring and assessment, and coordination among countries on waterbird management has little precedent. Yet intergovernmental treaties now mandate the use of sustainable, adaptive harvest strategies, whose development is challenged by a paucity of demographic information. In this study, we explore how a combination of allometric relationships, fragmentary monitoring and research information, and expert judgment can be used to estimate the parameters of a theta-logistic population model, which in turn can be used in a Markov decision process to derive optimal harvesting strategies. We show how to account for considerable parametric uncertainty, as well as for different management objectives. We illustrate our methodology with a poorly understood population of taiga bean geese ( Anser fabalis fabalis ), which is a popular game bird in Fennoscandia. Our results for taiga bean geese suggest that they may have demographic rates similar to other, well-studied species of geese, and our model-based predictions of population size are consistent with the limited monitoring information available. Importantly, we found that by using a Markov decision process, a simple scalar population model may be sufficient to guide harvest management of this species, even if its demography is age-structured. Finally, we demonstrated how two different management objectives can lead to very different optimal harvesting strategies, and how conflicting objectives may be traded off with each other. This approach will have broad application for European waterbirds by providing preliminary estimates of key demographic parameters, by providing insights into the monitoring and research activities needed to corroborate those estimates, and by producing harvest management strategies that are optimal with respect to the managers’ objectives, options, and available demographic information.

Ecological Applications↗

USGS2018

An interim harvest strategy for Taiga Bean geese

In 2016 the AEWA European Goose Management International Working Group (EGM IWG) adopted document AEWA/EGM IWG 1.8 (Johnson et al. 2016), which contained initial elements of an Adaptive Harvest Management programme for Taiga Bean Geese. This report addresses a number of limitations with the population model presented in that document, and provides up-to-date population projections for the Central Management Unit under a range of constant harvest rates. Based on simulations for the 2017-2025 timeframe, median population size was near the median goal of 70,000 in 2019, 2020, and 2021 for harvest rates of birds aged one year or more of 0.00, 0.02, and 0.04, respectively. Simulated population sizes generally increased over the timeframe, albeit with a lot of variation and with the degree of uncertainty increasing over time. With a harvest rate of 0.02, harvests averaged 1,848 (95% CI: 1,403 – 2,492) over the timeframe; a harvest rate of 0.04 produced an average harvest of 3,484 (95% CI: 2,617 – 4,884). Future work for the Central Management Unit will involve development of a dynamic harvest strategy by employing a Markov decision process, in which multiple, possibly competing, management objectives can be addressed.

Conference Paper↗

USGS2018

Adaptive harvest management for the Svalbard population of pink-footed geese: 2018 progress summary

This report describes progress on development and implementation of an adaptive harvest management program for maintaining the Svalbard population of Pink-footed Geese (Anser brachyrhynchus) near their target level (60,000) by providing sustainable harvests in Norway and Denmark. Specifically, this report provides an assessment of recent monitoring information and its implications for hunting seasons in 2018. An Adaptive Harvest Management (AHM) program requires specification of four elements: (a) A set of alternative population models, which bound the uncertainty about population dynamics; (b) A set of weights 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 to choose; and (d) An objective function, by which alternative harvest strategies are evaluated and an optimal strategy chosen. The most current set of monitoring information was used to update model weights for the 1991-2017 period. Current model weights suggest little evidence for density-dependent survival and reproduction. These results suggest that the Pink-footed Goose population may have experienced a release from density-dependent mechanisms, corresponding to the period of rapid growth in population size. There is equivocal evidence for the effect of the number of days above freezing in May in Svalbard on survival, but the evidence for an effect on reproduction has been increasing in recent years. Since the 2016 hunting season, harvest quotas are prescribed on an annual basis rather than every three years because of the potential to better meet management objectives. Based on updated model probabilities, the November 2017 population size (72,000), the proportion of the population comprised of one-year-old birds (0.076), and days above freezing in Svalbard in May 2018 (27), the optimal harvest quota for the 2018 hunting season is approximately 27,000. With the agreed upon harvest allocation of 30% Norway and 70% Denmark, the national quotas are 8,100 and 18,900, respectively, which are higher than the harvests realized in previous years. In 2017 the quota for the two countries combined was 36,000, but only a harvest of about 11,400 was realized. The decrease in harvest quota for 2018 is largely attributable to the apparent decline in population size. We also describe the ongoing development of an Integrated Population Model (IPM), which uses all available demographic data for Pink-footed Geese in a single, unified analysis. IPM estimates of harvest rates of adult geese were variable and relatively low prior to the implementation of AHM (2013), and have been relatively high since. The increase in harvest rates has been accompanied by a decline in annual survival. The ratio of young-of-the-year to older birds just prior to the hunting season has been variable over time, and since about 2005 has been highly correlated with the number of days above freezing in May in Svalbard. IPM estimates of population size suggest that abundance of Pink-footed Geese has been relatively stable, or declining slightly, in recent years. Based on the IPM estimate of population size in November 2017 of 68,800 (95% credible interval: 58,200 – 79,400), the optimal harvest quota for the 2018 hunting season is 15,000. This is lower than that derived from the set of nine discrete models because the IPM estimate of November population size is lower than the November count, and because the IPM model does not consider May temperatures in Svalbard, but rather assumes reproductive success varies randomly about the mean.

Report↗

USGS2018

Taiga bean goose: Harvest assessment for the Central Management Unit: 2018

In 2016 the European Goose Management International Working Group (EGM IWG) began development of an adaptive harvest management program for Taiga Bean Geese (TBG). In 2017, the EGM IWG adopted an interim harvest strategy consisting of a constant harvest rate (on adults) of 3% for the Central Management of Taiga Bean Geese. The interim strategy is intended to provide limited hunting opportunity while rebuilding the population. Recent efforts have involved development of a dynamic strategy in which the harvest rate can vary each year with changes in population size, and in which multiple, possibly competing, management objectives can be addressed. This report provides examples of dynamic harvest strategies and compares them with the interim, constant harvest-rate strategy. Until such time that a dynamic strategy is adopted by the EGM IWG, the annual harvest quota and its allocation among Range States is predicated on the interim strategy. Based on a January count of 38,717, the harvest quota for the 2018 hunting season is 1,610 Taiga Bean Geese (compared to 2,335 for the 2017 season). We emphasize that these quotas include both harvest during the regular season and derogation shooting. We acknowledge that the January 2018 count of Taiga Bean Geese in the Central Management Unit was likely biased low, as counts in the autumn and spring in Sweden were higher. Additionally, the size of the harvest during the fall and winter of 2017-18 is unknown, due to an inability to differentiate taiga and Tundra Bean Geese in the harvest, compilation of data too late to be used in this report, and a lack of reporting. Because of problems with both the population and harvest monitoring programs it is difficult to estimate a harvest quota for 2018 with any degree of confidence.

Report↗

USGS2018

Science alive and well in North American wildlife management

Artelle et al. (1) entitled a recent article with the provocative claim: “Hallmarks of science missing from North American wildlife management”. Although we agree with some of the concerns and recommendations of Artelle et al. (1), we believe that the article is misleading about the distinction between science and management, the role of science in wise management, and the degree to which science is used in North American wildlife management. Here we distinguish between science and management, specify an appropriate role of science in management, and document the explicit use of science in at least some programs of North American wildlife management.

Science Advances↗

USGS2017

Implementing the 2012 North American Waterfowl Management Plan revision: Populations, habitat, and people

The North American Waterfowl Management Plan (NAWMP) has established a model for wildlife conservation planning over the last 3 decades. Management at a continental scale, leveraged funding, regional partnerships, and a strong science basis have been notable features. Periodic updates to the NAWMP occurred since implementation in 1986; however, a fundamental revision was accomplished in 2012 after extensive stakeholder engagement. An explicit fundamental goal for waterfowl conservation supporters was added in 2012, complementing existing goals for sustainable populations and sufficient habitat found in previous updates. We present a synopsis of progress toward implementation of the 2012 NAWMP and challenge the waterfowl management community to continue with meaningful steps toward achieving NAWMP goals. Adding goals and objectives for supporters increases potential relevance of NAWMP; however, it also presents a level of complexity that was not entirely anticipated. Additionally, the 2012 NAWMP recognized that traditional support from waterfowl hunters alone will not be sufficient to support waterfowl conservation in the future. Simultaneous consideration of multiple objectives, although implicit before, now is a specific focus for habitat and harvest management affecting hunters and other users of the waterfowl resource. The waterfowl management community is faced with revisiting objectives and management actions related to harvest regulations, landscape priorities, habitat conservation, and public engagement to garner broader support. These persistent management challenges are tangible and relevant candidates for greater integration. Ultimately, the structures and processes supporting waterfowl management also will need to be reconsidered.

Journal of Wildlife Management↗

USGS2017

Optimal control of an invasive species using a reaction-diffusion model and linear programming

Managing an invasive species is particularly challenging as little is generally known about the species’ biological characteristics in its new habitat. In practice, removal of individuals often starts before the species is studied to provide the information that will later improve control. Therefore, the locations and the amount of control have to be determined in the face of great uncertainty about the species characteristics and with a limited amount of resources. We propose framing spatial control as a linear programming optimization problem. This formulation, paired with a discrete reaction-diffusion model, permits calculation of an optimal control strategy that minimizes the remaining number of invaders for a fixed cost or that minimizes the control cost for containment or protecting specific areas from invasion. We propose computing the optimal strategy for a range of possible model parameters, representing current uncertainty on the possible invasion scenarios. Then, a best strategy can be identified depending on the risk attitude of the decision-maker. We use this framework to study the spatial control of the Argentine black and white tegus ( Salvator merianae ) in South Florida. There is uncertainty about tegu demography and we considered several combinations of model parameters, exhibiting various dynamics of invasion. For a fixed one-year budget, we show that the risk-averse strategy, which optimizes the worst-case scenario of tegus’ dynamics, and the risk-neutral strategy, which optimizes the expected scenario, both concentrated control close to the point of introduction. A risk-seeking strategy, which optimizes the best-case scenario, focuses more on models where eradication of the species in a cell is possible and consists of spreading control as much as possible. For the establishment of a containment area, assuming an exponential growth we show that with current control methods it might not be possible to implement such a strategy for some of the models that we considered. Including different possible models allows an examination of how the strategy is expected to perform in different scenarios. Then, a strategy that accounts for the risk attitude of the decision-maker can be designed.

Florida↗

USGS2017

Strengthening links between waterfowl research and management

Waterfowl monitoring, research, regulation, and adaptive planning are leading the way in supporting science-informed wildlife management. However, increasing societal demands on natural resources have created a greater need for adaptable and successful linkages between waterfowl science and management. We presented a special session at the 2016 North American Duck Symposium, Annapolis, Maryland, USA on the successes and challenges of linking research and management in waterfowl conservation, and we summarize those thoughts in this commentary. North American waterfowl management includes a diversity of actions including management of harvest and habitat. Decisions for waterfowl management are structured using decision analysis by incorporating stakeholder values into formal objectives, identifying research relevant to objectives, integrating scientific knowledge, and choosing an optimal strategy with respect to objectives. Recently, the consideration of the value of information has been proposed as a means to evaluate the utility of research designed to meet objectives. Despite these advances, the ability to conduct waterfowl research with direct management application may be increasingly difficult in research institutions for several reasons including reduced funding for applied research and the lower perceived value of applied versus theoretical research by some university academics. In addition, coordination between researchers and managers may be logistically constrained, and communication may be ineffective between the 2 groups. Strengthening these links would help develop stronger and more coordinated approaches for the conservation of waterfowl and the wetlands upon which they depend.

Journal of Wildlife Management↗

USGS2017

Frequencies of decision making and monitoring in adaptive resource management

Adaptive management involves learning-oriented decision making in the presence of uncertainty about the responses of a resource system to management. It is implemented through an iterative sequence of decision making, monitoring and assessment of system responses, and incorporating what is learned into future decision making. Decision making at each point is informed by a value or objective function, for example total harvest anticipated over some time frame. The value function expresses the value associated with decisions, and it is influenced by system status as updated through monitoring. Often, decision making follows shortly after a monitoring event. However, it is certainly possible for the cadence of decision making to differ from that of monitoring. In this paper we consider different combinations of annual and biennial decision making, along with annual and biennial monitoring. With biennial decision making decisions are changed only every other year; with biennial monitoring field data are collected only every other year. Different cadences of decision making combine with annual and biennial monitoring to define 4 scenarios. Under each scenario we describe optimal valuations for active and passive adaptive decision making. We highlight patterns in valuation among scenarios, depending on the occurrence of monitoring and decision making events. Differences between years are tied to the fact that every other year a new decision can be made no matter what the scenario, and state information is available to inform that decision. In the subsequent year, however, in 3 of the 4 scenarios either a decision is repeated or monitoring does not occur (or both). There are substantive differences in optimal values among the scenarios, as well as the optimal policies producing those values. Especially noteworthy is the influence of monitoring cadence on valuation in some years. We highlight patterns in policy and valuation among the scenarios, and discuss management implications and extensions.

PLoS ONE↗

USGS2017

Evaluation of harvest and information needs for North American sea ducks

Wildlife managers routinely seek to establish sustainable limits of sport harvest or other regulated forms of take while confronted with considerable uncertainty. A growing body of ecological research focuses on methods to describe and account for uncertainty in management decision-making and to prioritize research and monitoring investments to reduce the most influential uncertainties. We used simulation methods incorporating measures of demographic uncertainty to evaluate risk of overharvest and prioritize information needs for North American sea ducks (Tribe Mergini ). Sea ducks are popular game birds in North America, yet they are poorly monitored and their population dynamics are poorly understood relative to other North American waterfowl. There have been few attempts to assess the sustainability of harvest of North American sea ducks, and no formal harvest strategy exists in the U.S. or Canada to guide management. The popularity of sea duck hunting, extended hunting opportunity for some populations (i.e., special seasons and/or bag limits), and population declines have led to concern about potential overharvest. We used Monte Carlo simulation to contrast estimates of allowable harvest and observed harvest and assess risk of overharvest for 7 populations of North American sea ducks: the American subspecies of common eider ( Somateria mollissima dresseri ), eastern and western populations of black scoter ( Melanitta americana ) and surf scoter ( M . perspicillata ), and continental populations of white-winged scoter ( M . fusca ) and long-tailed duck ( Clangula hyemalis ). We combined information from empirical studies and the opinions of experts through formal elicitation to create probability distributions reflecting uncertainty in the individual demographic parameters used in this assessment. Estimates of maximum growth ( r max ), and therefore of allowable harvest, were highly uncertain for all populations. Long-tailed duck and American common eider appeared to be at high risk of overharvest (i.e., observed harvest < allowable harvest in 5–7% and 19–26% of simulations, respectively depending on the functional form of density dependence), whereas the other populations appeared to be at moderate risk to low risk (observed harvest < allowable harvest in 22–68% of simulations, again conditional on the form of density dependence). We also evaluated the sensitivity of the difference between allowable and observed harvest estimates to uncertainty in individual demographic parameters to prioritize information needs. We found that uncertainty in overall fecundity had more influence on comparisons of allowable and observed harvest than adult survival or observed harvest for all species except long-tailed duck. Although adult survival was characterized by less uncertainty than individual components of fecundity, it was identified as a high priority information need given the sensitivity of growth rate and allowable harvest to this parameter. Uncertainty about population size was influential in the comparison of observed and allowable harvest for 5 of the 6 populations where it factored into the assessment. While this assessment highlights a high degree of uncertainty in allowable harvest, it provides a framework for integration of improved data from future research and monitoring. It could also serve as the basis for harvest strategy development as management objectives and regulatory alternatives are specified by the management community.

PLoS ONE↗

USGS2017

Implementation of the first adaptive management plan for a European migratory waterbird population: The case of the Svalbard pink-footed goose Anser brachyrhynchus

An International Species Management Plan for the Svalbard population of the pink-footed goose was adopted under the Agreement on the Conservation of African-Eurasian Migratory Waterbirds in 2012, the first case of adaptive management of a migratory waterbird population in Europe. An international working group (including statutory agencies, NGO representatives and experts) agreed on objectives and actions to maintain the population in favourable conservation status, while accounting for biodiversity, economic and recreational interests. Agreements include setting a population target to reduce agricultural conflicts and avoid tundra degradation, and using hunting in some range states to maintain stable population size. As part of the adaptive management procedures, adjustment to harvest is made annually subject to population status. This has required streamlining of monitoring and assessment activities. Three years after implementation, indicators suggest the attainment of management results. Dialogue, consensus-building and engagement among stakeholders represent the major process achievements.

Ambio↗