Implementation of a framework for multi-species, multi-objective adaptive management in Delaware Bay

McGowan, Conor P.; Smith, David R.; Nichols, James D.; Lyons, James E.; Sweka, John A.; Kalasz, Kevin S.; Niles, Lawrence J.; Wong, Richard; Brust, Jeffrey; Davis, Michelle C.; Spear, Braddock

doi:10.1016/j.biocon.2015.08.038

Cited by 41 publications

(37 citation statements)

References 36 publications

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“…Sweka et al (2007) examined the role of density-dependent egg mortality on population abundance under different harvest levels, and consistent with previous analyses, identified sustainable harvest levels that allowed for population growth. The Sweka et al (2007) model became the basis for predictive modeling to support adaptive management of horseshoe crab in Delaware Bay McGowan et al 2015;Millard et al 2015).…”

Section: Population Viability Analysesmentioning

confidence: 99%

“…New Jersey instituted a complete moratorium on harvesting horseshoe crabs from state waters in 2006, and this ban remains in effect. In February 2012, the ASMFC Horseshoe Crab Management Board approved Addendum VII, which provides for managing harvest of Delaware Bay-origin animals via an Adaptive Resource Management (ARM) framework, wherein annual harvest is derived via a suite of multispecies models and an optimization process which takes into account many biological variables, including the status of the horseshoe crab population and the red knot population (ASMFC 2009;McGowan et al 2011bMcGowan et al , 2015. The ARM framework also defines monitoring programs and procedures to update the modeling structure and parameterization including uncertainty.…”

Section: Conservation Approachesmentioning

confidence: 99%

See 1 more Smart Citation

Conservation status of the American horseshoe crab, (Limulus polyphemus): a regional assessment

Smith

Brockmann

Beekey³

et al. 2016

Rev Fish Biol Fisheries

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106

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Section: Population Viability Analysesmentioning

confidence: 99%

Section: Conservation Approachesmentioning

confidence: 99%

Conservation status of the American horseshoe crab, (Limulus polyphemus): a regional assessment

Smith

Brockmann

Beekey³

et al. 2016

Rev Fish Biol Fisheries

Self Cite

106

View full text Add to dashboard Cite

“…The first ecological recommendations for use of the evolving information state approach to accumulating evidence came from applied ecology in conjunction with the concept of adaptive management (e.g., Hilborn & Walters, ; Johnson et al, ; Walters, ; Walters & Hilborn, , ; Williams, ; Williams et al, ; Williams et al, ). In addition to the management program described in Box 2, this adaptive management approach with evolving information state is being used in a small number of other management programs (Martin et al, ; McGowan et al, ; U.S. Fish & Wildlife Service, ).…”

Section: Approaches To Accumulating Evidencementioning

confidence: 99%

Accumulating evidence in ecology: Once is not enough

Nichols

Kendall

Boomer

2019

Ecology and Evolution

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Many published studies in ecological science are viewed as stand‐alone investigations that purport to provide new insights into how ecological systems behave based on single analyses. But it is rare for results of single studies to provide definitive results, as evidenced in current discussions of the “reproducibility crisis” in science. The key step in science is the comparison of hypothesis‐based predictions with observations, where the predictions are typically generated by hypothesis‐specific models. Repeating this step allows us to gain confidence in the predictive ability of a model, and its corresponding hypothesis, and thus to accumulate evidence and eventually knowledge. This accumulation may occur via an ad hoc approach, via meta‐analyses, or via a more systematic approach based on the anticipated evolution of an information state. We argue the merits of this latter approach, provide an example, and discuss implications for designing sequences of studies focused on a particular question. We conclude by discussing current data collection programs that are preadapted to use this approach and argue that expanded use would increase the rate of learning in ecology, as well as our confidence in what is learned.

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“…Wildlife and fisheries professionals have been leaders in recognizing modeling uncertainty about how systems respond to management actions (Leopold , Beverton and Holt , Anderson , Walters and Hilborn ) and developed ARM in response to this recognition (Walters and Hilborn , ; Walters ; Johnson et al ; Williams et al ). The ARM approach has been adopted by a number of wildlife management programs (e.g., Johnson et al , Martin et al , McGowan et al , Williams et al , U.S. Fish and Wildlife Service ) but is not as widely used as could be hoped (Nichols ).…”

Section: Uncertainty In Management and Decision‐makingmentioning

confidence: 99%

Confronting uncertainty: Contributions of the wildlife profession to the broader scientific community

Nichols

2019

J Wildl Manag

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Most wildlife professionals are engaged in 1 or both of 2 basic endeavors: science and management. These endeavors are a focus of many other disciplines, leading to widespread sharing of general methodologies. Wildlife professionals have appropriately borrowed and assimilated many methods developed primarily in other disciplines but have also led the development of one class of quantitative methods, those that confront and incorporate uncertainty. Uncertainty arises in counts of focal entities, for which wildlife professionals have developed effective methods to deal with the common problems of nondetection and misclassification. These methods have been borrowed by disciplines as varied as paleobiology, medicine, human epidemiology, industrial quality control, military target acquisition, remote sensing, and human census. Uncertainty also arises in the modeling of those counts, specifically the observation and ecological processes that generated them. Wildlife professionals recognized the fundamental importance of model selection and rapidly assimilated methods for selecting the most appropriate model for a given data set. These methods for dealing with uncertainty inherent to counting and modeling are critical to the conduct of science and management. Wildlife professionals have developed additional methods for incorporating uncertainty in the accumulation of knowledge and the development of optimal decisions in an environment of learning. In some cases, professionals in other disciplines are using methods developed and popularized in the wildlife profession, but there is much potential for greater use. In this essay, I describe these areas of wildlife leadership, document their assimilation by other disciplines, and emphasize the potential for more interdisciplinary use of these methods. © 2019 The Wildlife Society.

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Implementation of a framework for multi-species, multi-objective adaptive management in Delaware Bay

Cited by 41 publications

References 36 publications

Conservation status of the American horseshoe crab, (Limulus polyphemus): a regional assessment

Conservation status of the American horseshoe crab, (Limulus polyphemus): a regional assessment

Accumulating evidence in ecology: Once is not enough

Confronting uncertainty: Contributions of the wildlife profession to the broader scientific community

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