Geology topics

Sarah J. Converse

Publications and source records attributed to Sarah J. Converse.

At least 109 records · Page 6Linked to original sources

USGS2013

Hierarchical spatial capture-recapture models: Modeling population density from stratified populations

Capture–recapture studies are often conducted on populations that are stratified by space, time or other factors. In this paper, we develop a Bayesian spatial capture–recapture (SCR) modelling framework for stratified populations – when sampling occurs within multiple distinct spatial and temporal strata. We describe a hierarchical model that integrates distinct models for both the spatial encounter history data from capture–recapture sampling, and also for modelling variation in density among strata. We use an implementation of data augmentation to parameterize the model in terms of a latent categorical stratum or group membership variable, which provides a convenient implementation in popular BUGS software packages. We provide an example application to an experimental study involving small-mammal sampling on multiple trapping grids over multiple years, where the main interest is in modelling a treatment effect on population density among the trapping grids. Many capture–recapture studies involve some aspect of spatial or temporal replication that requires some attention to modelling variation among groups or strata. We propose a hierarchical model that allows explicit modelling of group or strata effects. Because the model is formulated for individual encounter histories and is easily implemented in the BUGS language and other free software, it also provides a general framework for modelling individual effects, such as are present in SCR models.

Methods in Ecology and Evolution↗

USGS2013

A hierarchical nest survival model integrating incomplete temporally varying covariates

Nest success is a critical determinant of the dynamics of avian populations, and nest survival modeling has played a key role in advancing avian ecology and management. Beginning with the development of daily nest survival models, and proceeding through subsequent extensions, the capacity for modeling the effects of hypothesized factors on nest survival has expanded greatly. We extend nest survival models further by introducing an approach to deal with incompletely observed, temporally varying covariates using a hierarchical model. Hierarchical modeling offers a way to separate process and observational components of demographic models to obtain estimates of the parameters of primary interest, and to evaluate structural effects of ecological and management interest. We built a hierarchical model for daily nest survival to analyze nest data from reintroduced whooping cranes (Grus americana) in the Eastern Migratory Population. This reintroduction effort has been beset by poor reproduction, apparently due primarily to nest abandonment by breeding birds. We used the model to assess support for the hypothesis that nest abandonment is caused by harassment from biting insects. We obtained indices of blood-feeding insect populations based on the spatially interpolated counts of insects captured in carbon dioxide traps. However, insect trapping was not conducted daily, and so we had incomplete information on a temporally variable covariate of interest. We therefore supplemented our nest survival model with a parallel model for estimating the values of the missing insect covariates. We used Bayesian model selection to identify the best predictors of daily nest survival. Our results suggest that the black fly Simulium annulus may be negatively affecting nest survival of reintroduced whooping cranes, with decreasing nest survival as abundance of S. annulus increases. The modeling framework we have developed will be applied in the future to a larger data set to evaluate the biting-insect hypothesis and other hypotheses for nesting failure in this reintroduced population; resulting inferences will support ongoing efforts to manage this population via an adaptive management approach. Wider application of our approach offers promise for modeling the effects of other temporally varying, but imperfectly observed covariates on nest survival, including the possibility of modeling temporally varying covariates collected from incubating adults.

Wisconsin↗

USGS2013

Demographics of reintroduced populations: estimation, modeling, and decision analysis

Reintroduction can be necessary for recovering populations of threatened species. However, the success of reintroduction efforts has been poorer than many biologists and managers would hope. To increase the benefits gained from reintroduction, management decision making should be couched within formal decision-analytic frameworks. Decision analysis is a structured process for informing decision making that recognizes that all decisions have a set of components—objectives, alternative management actions, predictive models, and optimization methods—that can be decomposed, analyzed, and recomposed to facilitate optimal, transparent decisions. Because the outcome of interest in reintroduction efforts is typically population viability or related metrics, models used in decision analysis efforts for reintroductions will need to include population models. In this special section of the Journal of Wildlife Management, we highlight examples of the construction and use of models for informing management decisions in reintroduced populations. In this introductory contribution, we review concepts in decision analysis, population modeling for analysis of decisions in reintroduction settings, and future directions. Increased use of formal decision analysis, including adaptive management, has great potential to inform reintroduction efforts. Adopting these practices will require close collaboration among managers, decision analysts, population modelers, and field biologists.

Journal of Wildlife Management↗

USGS2013

Social learning of migratory performance

Successful bird migration can depend on individual learning, social learning, and innate navigation programs. Using 8 years of data on migrating whooping cranes, we were able to partition genetic and socially learned aspects of migration. Specifically, we analyzed data from a reintroduced population wherein all birds were captive bred and artificially trained by ultralight aircraft on their first lifetime migration. For subsequent migrations, in which birds fly individually or in groups but without ultralight escort, we found evidence of long-term social learning, but no effect of genetic relatedness on migratory performance. Social learning from older birds reduced deviations from a straight-line path, with 7 years of experience yielding a 38% improvement in migratory accuracy.

Science↗

USGS2013

Demography and population status of polar bears in western Hudson Bay

We evaluated the demography and population status of the Western Hudson Bay (WH) polar bear subpopulation for the period 1984-2011, using live-recapture data from research studies and management actions, and dead-recovery data from polar bears harvested for subsistence purposes or removed during human-bear conflicts. We used a Bayesian implementation of multistate capture-recapture models, coupled with a matrix-based demographic projection model, to integrate several types of data and to incorporate sampling uncertainty, and demographic and environmental stochasticity across the polar bear life cycle. This approach allowed for estimation of a suite of vital rates, including survival and reproduction. These vital rates were used to parameterize a Bayesian population model to evaluate population trends and project potential population outcomes under different environmental scenarios. Survival of female polar bears of all age classes was significantly correlated with sea ice conditions; particularly with the timing of sea ice break-up in the spring and formation in the fall and the interaction of the two. This is consistent with previous findings linking body condition and survival of WH polar bears to environmental changes associated with climatic warming and supports the ecological dependence of polar bears on the availability of sea ice. Survival of male polar bears was not correlated with sea ice conditions. This was likely because a higher proportion of mortality for males was caused by humans rather than by natural factors. For example, approximately 73% of mortality for young male bears (i.e., 5-9 years old) was due to direct human-caused removals, largely because of sex selectivity in the subsistence harvest. The declining trend in size of the WH subpopulation over the period 1987-2004 was similar to a previous analysis (Regehr et al. 2007), suggesting consistency between the two demographic evaluations. Point estimates of abundance were somewhat lower using the updated statistical approach. It is important to recognize that the analyzed data were not collected in a manner that is optimal for estimating abundance and that the goal of the current analysis was to estimate vital rates and demographic trends. Estimates of population growth rate were also derived using a Bayesian population model based on estimated survival and reproductive rates from the multistate capture-recapture model. For the recent decade 2001-2011, the growth rate of the female segment of the population was 1.02 (95% CI = 0.98-1.06). Apparently stable to positive population growth for females may be due in large part to nonlinearity (i.e., short-term stability) in the long-term observed and forecasted trend toward earlier sea ice break-up in western Hudson Bay. The 2011 abundance estimate from this analysis was 806 bears with a 95% Bayesian credible interval of 653-984. This is lower than, but broadly consistent with, the abundance estimate of 1,030 (95% confidence interval = 745-1406) from a 2011 aerial survey (Stapleton et al. 2014). The capture-recapture and aerial survey approaches have different spatial and temporal coverage of the WH subpopulation and, consequently, the effective study population considered by each approach is different.

Report↗

USGS2012

A matter of tradeoffs: reintroduction as a multiple objective decision

Decision making in guidance of reintroduction efforts is made challenging by the substantial scientific uncertainty typically involved. However, a less recognized challenge is that the management objectives are often numerous and complex. Decision makers managing reintroduction efforts are often concerned with more than just how to maximize the probability of reintroduction success from a population perspective. Decision makers are also weighing other concerns such as budget limitations, public support and/or opposition, impacts on the ecosystem, and the need to consider not just a single reintroduction effort, but conservation of the entire species. Multiple objective decision analysis is a powerful tool for formal analysis of such complex decisions. We demonstrate the use of multiple objective decision analysis in the case of the Florida non-migratory whooping crane reintroduction effort. In this case, the State of Florida was considering whether to resume releases of captive-reared crane chicks into the non-migratory whooping crane population in that state. Management objectives under consideration included maximizing the probability of successful population establishment, minimizing costs, maximizing public relations benefits, maximizing the number of birds available for alternative reintroduction efforts, and maximizing learning about the demographic patterns of reintroduced whooping cranes. The State of Florida engaged in a collaborative process with their management partners, first, to evaluate and characterize important uncertainties about system behavior, and next, to formally evaluate the tradeoffs between objectives using the Simple Multi-Attribute Rating Technique (SMART). The recommendation resulting from this process, to continue releases of cranes at a moderate intensity, was adopted by the State of Florida in late 2008. Although continued releases did not receive support from the International Whooping Crane Recovery Team, this approach does provide a template for the formal, transparent consideration of multiple, potentially competing, objectives in reintroduction decision making.

Journal of Wildlife Management↗

USGS2012

Archive eggs: a research and management tool for avian conservation breeding

Worldwide, approximately 168 bird species are captive-bred for reintroduction into the wild. Programs tend to be initiated for species with a high level of endangerment. Depressed hatching success can be a problem for such programs and has been linked to artificial incubation. The need for artificial incubation is driven by the practice of multiclutching to increase egg production or by uncertainty over the incubation abilities of captive birds. There has been little attempt to determine how artificial incubation differs from bird-contact incubation. We describe a novel archive (data-logger) egg and use it to compare temperature, humidity, and egg-turning in 5 whooping crane (Grus americana) nests, 4 sandhill crane (G. canadensis) nests, and 3 models of artificial incubator; each of which are used to incubate eggs in whooping crane captive-breeding programs. Mean incubation temperature was 31.7° C for whooping cranes and 32.83° C for sandhill cranes. This is well below that of the artificial incubators (which were set based on a protocol of 37.6° C). Humidity in crane nests varied considerably, but median humidity in all 3 artificial incubators was substantially different from that in the crane nests. Two artificial incubators failed to turn the eggs in a way that mimicked crane egg-turning. Archive eggs are an effective tool for guiding the management of avian conservation breeding programs, and can be custom-made for other species. They also have potential to be applied to research on wild populations.

Wildlife Society Bulletin↗

USGS2012

Dealing with incomplete and variable detectability in multi-year, multi-site monitoring of ecological populations

An ecological monitoring program should be viewed as a component of a larger framework designed to advance science and/or management, rather than as a stand-alone activity. Monitoring targets (the ecological variables of interest; e.g. abundance or occurrence of a species) should be set based on the needs of that framework (Nichols and Williams 2006; e.g. Chapters 2–4). Once such monitoring targets are set, the subsequent step in monitoring design involves consideration of the field and analytical methods that will be used to measure monitoring targets with adequate accuracy and precision. Long-term monitoring programs will involve replication of measurements over time, and possibly over space; that is, one location or each of multiple locations will be monitored multiple times, producing a collection of site visits (replicates). Clearly this replication is important for addressing spatial and temporal variability in the ecological resources of interest (Chapters 7–10), but it is worth considering how this replication can further be exploited to increase the effectiveness of monitoring. In particular, defensible monitoring of the majority of animal, and to a lesser degree plant, populations and communities will generally require investigators to account for imperfect detection (Chapters 4, 18). Raw indices of population state variables, such as abundance or occupancy (sensu MacKenzie et al. 2002), are rarely defensible when detection probabilities are < 1, because in those cases detection may vary over time and space in unpredictable ways. Myriad authors have discussed the risks inherent in making inference from monitoring data while failing to correct for differences in detection, resulting in indices that have an unknown relationship to the parameters of interest (e.g. Nichols 1992, Anderson 2001, MacKenzie et al. 2002, Williams et al. 2002, Anderson 2003, White 2005, Kéry and Schmidt 2008). While others have argued that indices may be preferable in some cases due to the challenges associated with estimating detection probabilities (e.g. McKelvey and Pearson 2001, Johnson 2008), we do not attempt to resolve this debate here. Rather, we are more apt to agree with MacKenzie and Kendall (2002) that the burden of proof ought to be on the assertion that detection probabilities are constant. Furthermore, given the wide variety of field methods available for estimating detection probabilities and the inability for an investigator to know, a priori, if detection probabilities will be constant over time and space, we believe that development of monitoring programs ought to include field and analytical methods to account for the imperfect detection of organisms.

Book chapter↗

USGS2012

Do predators control prey species abundance? An experimental test with brown treesnakes on Guam

The effect of predators on the abundance of prey species is a topic of ongoing debate in ecology; the effect of snake predators on their prey has been less debated, as there exists a general consensus that snakes do not negatively influence the abundance of their prey. However, this viewpoint has not been adequately tested. We quantified the effect of brown treesnake ( Boiga irregularis ) predation on the abundance and size of lizards on Guam by contrasting lizards in two 1-ha treatment plots of secondary forest from which snakes had been removed and excluded vs. two 1-ha control plots in which snakes were monitored but not removed or excluded. We removed resident snakes from the treatment plots with snake traps and hand capture, and snake immigration into these plots was precluded by electrified snake barriers. Lizards were sampled in all plots quarterly for a year following snake elimination in the treatment plots. Following the completion of this experiment, we used total removal sampling to census lizards on a 100-m 2 subsample of each plot. Results of systematic lizard population monitoring before and after snake removal suggest that the abundance of the skink, Carlia ailanpalai, increased substantially and the abundance of two species of gekkonids, Lepidodactylus lugubris and Hemidactylus frenatus , also increased on snake-free plots. No treatment effect was observed for the skink Emoia caeruleocauda . Mean snout–vent length of all lizard species only increased following snake removal in the treatment plots. The general increase in prey density and mean size was unexpected in light of the literature consensus that snakes do not control the abundance of their prey species. Our findings show that, at least where alternate predators are lacking, snakes may indeed affect prey populations.

Ecology↗

USGS2011

Decision analysis for conservation breeding: Maximizing production for reintroduction of whooping cranes

Captive breeding is key to management of severely endangered species, but maximizing captive production can be challenging because of poor knowledge of species breeding biology and the complexity of evaluating different management options. In the face of uncertainty and complexity, decision-analytic approaches can be used to identify optimal management options for maximizing captive production. Building decision-analytic models requires iterations of model conception, data analysis, model building and evaluation, identification of remaining uncertainty, further research and monitoring to reduce uncertainty, and integration of new data into the model. We initiated such a process to maximize captive production of the whooping crane ( Grus americana ), the world's most endangered crane, which is managed through captive breeding and reintroduction. We collected 15 years of captive breeding data from 3 institutions and used Bayesian analysis and model selection to identify predictors of whooping crane hatching success. The strongest predictor, and that with clear management relevance, was incubation environment. The incubation period of whooping crane eggs is split across two environments: crane nests and artificial incubators. Although artificial incubators are useful for allowing breeding pairs to produce multiple clutches, our results indicate that crane incubation is most effective at promoting hatching success. Hatching probability increased the longer an egg spent in a crane nest, from 40% hatching probability for eggs receiving 1 day of crane incubation to 95% for those receiving 30 days (time incubated in each environment varied independently of total incubation period). Because birds will lay fewer eggs when they are incubating longer, a tradeoff exists between the number of clutches produced and egg hatching probability. We developed a decision-analytic model that estimated 16 to be the optimal number of days of crane incubation needed to maximize the number of offspring produced. These results show that using decision-analytic tools to account for uncertainty in captive breeding can improve the rate at which such programs contribute to wildlife reintroductions.

Journal of Wildlife Management↗

USGS2011

Bayesian analysis of multi-state data with individual covariates for estimating genetic effects on demography

Inbreeding depression is frequently a concern of managers interested in restoring endangered species. Decisions to reduce the potential for inbreeding depression by balancing genotypic contributions to reintroduced populations may exact a cost on long-term demographic performance of the population if those decisions result in reduced numbers of animals released and/or restriction of particularly successful genotypes (i.e., heritable traits of particular family lines). As part of an effort to restore a migratory flock of Whooping Cranes (Grus americana) to eastern North America using the offspring of captive breeders, we obtained a unique dataset which includes post-release mark-recapture data, as well as the pedigree of each released individual. We developed a Bayesian formulation of a multi-state model to analyze radio-telemetry, band-resight, and dead recovery data on reintroduced individuals, in order to track survival and breeding state transitions. We used studbook-based individual covariates to examine the comparative evidence for and degree of effects of inbreeding, genotype, and genotype quality on post-release survival of reintroduced individuals. We demonstrate implementation of the Bayesian multi-state model, which allows for the integration of imperfect detection, multiple data types, random effects, and individual- and time-dependent covariates. Our results provide only weak evidence for an effect of the quality of an individual's genotype in captivity on post-release survival as well as for an effect of inbreeding on post-release survival. We plan to integrate our results into a decision-analytic modeling framework that can explicitly examine tradeoffs between the effects of inbreeding and the effects of genotype and demographic stochasticity on population establishment.

Journal of Ornithology↗

USGS2011

A decision-analytic approach to the optimal allocation of resources for endangered species consultation

The resources available to support conservation work, whether time or money, are limited. Decision makers need methods to help them identify the optimal allocation of limited resources to meet conservation goals, and decision analysis is uniquely suited to assist with the development of such methods. In recent years, a number of case studies have been described that examine optimal conservation decisions under fiscal constraints; here we develop methods to look at other types of constraints, including limited staff and regulatory deadlines. In the US, Section Seven consultation, an important component of protection under the federal Endangered Species Act, requires that federal agencies overseeing projects consult with federal biologists to avoid jeopardizing species. A benefit of consultation is negotiation of project modifications that lessen impacts on species, so staff time allocated to consultation supports conservation. However, some offices have experienced declining staff, potentially reducing the efficacy of consultation. This is true of the US Fish and Wildlife Service's Washington Fish and Wildlife Office (WFWO) and its consultation work on federally-threatened bull trout (Salvelinus confluentus). To improve effectiveness, WFWO managers needed a tool to help allocate this work to maximize conservation benefits. We used a decision-analytic approach to score projects based on the value of staff time investment, and then identified an optimal decision rule for how scored projects would be allocated across bins, where projects in different bins received different time investments. We found that, given current staff, the optimal decision rule placed 80% of informal consultations (those where expected effects are beneficial, insignificant, or discountable) in a short bin where they would be completed without negotiating changes. The remaining 20% would be placed in a long bin, warranting an investment of seven days, including time for negotiation. For formal consultations (those where expected effects are significant), 82% of projects would be placed in a long bin, with an average time investment of 15. days. The WFWO is using this decision-support tool to help allocate staff time. Because workload allocation decisions are iterative, we describe a monitoring plan designed to increase the tool's efficacy over time. This work has general application beyond Section Seven consultation, in that it provides a framework for efficient investment of staff time in conservation when such time is limited and when regulatory deadlines prevent an unconstrained approach. ?? 2010.

Biological Conservation↗

USGS2011

Which uncertainty? Using expert elicitation and expected value of information to design an adaptive program

Natural resource management is plagued with uncertainty of many kinds, but not all uncertainties are equally important to resolve. The promise of adaptive management is that learning in the short-term will improve management in the long-term; that promise is best kept if the focus of learning is on those uncertainties that most impede achievement of management objectives. In this context, an existing tool of decision analysis, the expected value of perfect information (EVPI), is particularly valuable in identifying the most important uncertainties. Expert elicitation can be used to develop preliminary predictions of management response under a series of hypotheses, as well as prior weights for those hypotheses, and the EVPI can be used to determine how much management could improve if uncertainty was resolved. These methods were applied to management of whooping cranes ( Grus americana ), an endangered migratory bird that is being reintroduced in several places in North America. The Eastern Migratory Population of whooping cranes had exhibited almost no successful reproduction through 2009. Several dozen hypotheses can be advanced to explain this failure, and many of them lead to very different management responses. An expert panel articulated the hypotheses, provided prior weights for them, developed potential management strategies, and made predictions about the response of the population to each strategy under each hypothesis. Multi-criteria decision analysis identified a preferred strategy in the face of uncertainty, and analysis of the expected value of information identified how informative each strategy could be. These results provide the foundation for design of an adaptive management program.

Biological Conservation↗

USGS2011

Adaptive management of bull trout populations in the Lemhi Basin

The bull trout Salvelinus confluentus , a stream-living salmonid distributed in drainages of the northwestern United States, is listed as threatened under the Endangered Species Act because of rangewide declines. One proposed recovery action is the reconnection of tributaries in the Lemhi Basin. Past water use policies in this core area disconnected headwater spawning sites from downstream habitat and have led to the loss of migratory life history forms. We developed an adaptive management framework to analyze which types of streams should be prioritized for reconnection under a proposed Habitat Conservation Plan. We developed a Stochastic Dynamic Program that identified optimal policies over time under four different assumptions about the nature of the migratory behavior and the effects of brook trout Salvelinus fontinalis on subpopulations of bull trout. In general, given the current state of the system and the uncertainties about the dynamics, the optimal policy would be to connect streams that are currently occupied by bull trout. We also estimated the value of information as the difference between absolute certainty about which of our four assumptions were correct, and a model averaged optimization assuming no knowledge. Overall there is little to be gained by learning about the dynamics of the system in its current state, although in other parts of the state space reducing uncertainties about the system would be very valuable. We also conducted a sensitivity analysis; the optimal decision at the current state does not change even when parameter values are changed up to 75% of the baseline values. Overall, the exercise demonstrates that it is possible to apply adaptive management principles to threatened and endangered species, but logistical and data availability constraints make detailed analyses difficult.

Lemhi River Basin↗

USGS2011

Dynamic resource allocation in conservation planning

Consider the problem of protecting endangered species by selecting patches of land to be used for conservation purposes. Typically, the availability of patches changes over time, and recommendations must be made dynamically. This is a challenging prototypical example of a sequential optimization problem under uncertainty in computational sustainability. Existing techniques do not scale to problems of realistic size. In this paper, we develop an efficient algorithm for adaptively making recommendations for dynamic conservation planning, and prove that it obtains near-optimal performance. We further evaluate our approach on a detailed reserve design case study of conservation planning for three rare species in the Pacific Northwest of the United States.

Conference Paper↗

USGS2011

Keeping Hawai’i’s forest birds one step ahead of avian diseases in a warming world: a focus on Hakalau Forest National Wildlife Refuge. A case study from the National Conservation and Training Center Structured Decision Making Workshop

This report is a product of a one-week workshop on using Structured Decision Making to identify and prioritize conservation actions to address the threat of climate change on Hawaii‟s native forest bird community. Specifically, t his report addresses the issue of global warming ‟s likely role in increasing disease prevalence in upper elevation forests of Hawaii, negatively impacting native bird populations susceptible to the disease but currently disease - free because of the cooler temperatures at high elevations.

Hawaii↗

USGS2010

Evaluating release alternatives for a long-lived bird species under uncertainty about long-term demographic rates

The release of animals to reestablish an extirpated population is a decision problem that is often attended by considerable uncertainty about the probability of success. Annual releases of captive-reared juvenile Whooping Cranes (Grus americana) were begun in 1993 in central Florida, USA, to establish a breeding, non-migratory population. Over a 12-year period, 286 birds were released, but by 2004, the introduced flock had produced only four wild-fledged birds. Consequently, releases were halted over managers' concerns about the performance of the released flock and uncertainty about the efficacy of further releases. We used data on marked, released birds to develop predictive models for addressing whether releases should be resumed, and if so, under what schedule. To examine the outcome of different release scenarios, we simulated the survival and productivity of individual female birds under a baseline model that recognized age and breeding-class structure and which incorporated empirically estimated stochastic elements. As data on wild-fledged birds from captive-reared parents were sparse, a key uncertainty that confronts release decision-making is whether captive-reared birds and their offspring share the same vital rates. Therefore, we used data on the only population of wild Whooping Cranes in existence to construct two alternatives to the baseline model. The probability of population persistence was highly sensitive to the choice of these three models. Under the baseline model, extirpation of the population was nearly certain under any scenario of resumed releases. In contrast, the model based on estimates from wild birds projected a high probability of persistence under any release scenario, including cessation of releases. Therefore, belief in either of these models suggests that further releases are an ineffective use of resources. In the third model, which simulated a population Allee effect, population persistence was sensitive to the release decision: high persistence probability was achieved only through the release of more birds, whereas extirpation was highly probable with cessation of releases. Despite substantial investment of time and effort in the release program, evidence collected to date does not favor one model over another; therefore, any decision about further releases must be made under considerable biological uncertainty. However, given an assignment of credibility weight to each model, a best, informed decision about releases can be made under uncertainty. Furthermore, if managers can periodically revisit the release decision and collect monitoring data to further inform the models, then managers have a basis for confronting uncertainty and adaptively managing releases through time.

Florida↗

USGS2010

Optimal control of native predators

We apply decision theory in a structured decision-making framework to evaluate how control of raccoons ( Procyon lotor ), a native predator, can promote the conservation of a declining population of American Oystercatchers ( Haematopus palliatus ) on the Outer Banks of North Carolina. Our management objective was to maintain Oystercatcher productivity above a level deemed necessary for population recovery while minimizing raccoon removal. We evaluated several scenarios including no raccoon removal, and applied an adaptive optimization algorithm to account for parameter uncertainty. We show how adaptive optimization can be used to account for uncertainties about how raccoon control may affect Oystercatcher productivity. Adaptive management can reduce this type of uncertainty and is particularly well suited for addressing controversial management issues such as native predator control. The case study also offers several insights that may be relevant to the optimal control of other native predators. First, we found that stage-specific removal policies (e.g., yearling versus adult raccoon removals) were most efficient if the reproductive values among stage classes were very different. Second, we found that the optimal control of raccoons would result in higher Oystercatcher productivity than the minimum levels recommended for this species. Third, we found that removing more raccoons initially minimized the total number of removals necessary to meet long term management objectives. Finally, if for logistical reasons managers cannot sustain a removal program by removing a minimum number of raccoons annually, managers may run the risk of creating an ecological trap for Oystercatchers.

North Carolina↗