Consistent Extinction Risk Assessment under the U.S. Endangered Species Act

Boyd, Charlotte; DeMaster, Douglas P.; Waples, Robin S.; Ward, Eric J.; Taylor, Barbara L.

doi:10.1111/conl.12269

Cited by 12 publications

(12 citation statements)

References 23 publications

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“…The use of Bayesian approaches is increasingly being applied in status assessments and other conservation applications (e.g., Boyd et al. ; Hilbers et al. ) because they can accommodate sparse data sets and incorporate existing knowledge as prior information.…”

Section: Discussionmentioning

confidence: 99%

Predictability of demographic rates based on phylogeny and biological similarity

Che‐Castaldo

Neel

2018

Conservation Biology

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Lack of demographic data for most of the world's threatened species is a widespread problem that precludes viability-based status assessments for species conservation. A commonly suggested solution is to use data from species that are closely related or biologically similar to the focal species. This approach assumes similar species and populations of the same species have similar demographic rates, an assumption that has yet to be thoroughly tested. We constructed a Bayesian hierarchical model with data on 425 plant species to predict demographic rates (intrinsic rate of population growth, recruit survival, juvenile survival, adult survival, and fecundity) based on biological traits and phylogenetic relatedness. Generally, we found small effects of species-level traits (except woody polycarpic species tended to have high adult survival rates that increased with plant height) and a weak phylogenetic signal for 4 of the 5 demographic parameters examined. Patterns were stronger in adult survival and fecundity than other demographic rates; however, the unexplained variances at both the species and population levels were high for all demographic rates. For species lacking demographic data, our model produced large, often inaccurate, prediction intervals that may not be useful in a management context. Our findings do not support the assumption that biologically similar or closely related species have similar demographic rates and provide further evidence that direct monitoring of focal species and populations is necessary for informing conservation status assessments.

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Section: Discussionmentioning

confidence: 99%

Predictability of demographic rates based on phylogeny and biological similarity

Che‐Castaldo

Neel

2018

Conservation Biology

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“…In response to these pressures, research, policy, and education or conservation awareness campaigns regarding marine megafauna conservation issues have increased considerably (Authier et al, 2017). However, while megafauna research, conservation policies, and education efforts have produced important results (Taylor et al, 2000;Boyd et al, 2016;Morin et al, 2016), we suggest that many efforts have yet to adequately embrace the complexity of the systems in which marine megafauna reside. Given the mounting pressure on ocean resources and the growing concerns regarding marine megafauna conservation (National Academy of Sciences, 2017), failing to acknowledge and account for this inherent complexity may hinder much needed advances and success in marine megafauna research and conservation.…”

Section: Introductionmentioning

confidence: 89%

Embracing Complexity and Complexity-Awareness in Marine Megafauna Conservation and Research

Lewison¹,

Johnson²,

Verutes³

2018

Front. Mar. Sci.

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Conservation of marine megafauna is nested within an intricate tapestry of multiple ocean resource uses which are, in turn, embedded in a dynamic and complex ecological ocean system that varies and shifts across a wide range of spatial and temporal scales. Marine megafauna conservation is often further complicated by contemporaneous, and sometimes competing, social, economic, and ecological factors and related management objectives. Advances in emerging technologies and applications, such as remotely-sensed oceanographic data, animal-based telemetry, novel computational analyses, innovations in structured decision making, and stakeholder engagement and policy are supporting complex systems and complexity-aware approaches to megafauna conservation and research. Here we discuss several applications that focus on megafauna fisheries bycatch and exemplify how complex systems and complexity-aware approaches that inherently acknowledge and account for the complexity of ocean systems can advance megafauna conservation and research. Emerging technologies, applications and approaches that embrace, rather than ignore, complexity can drive innovation and success in megafauna conservation and research.

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“…Bayesian state–space models (BSSM) offer a powerful and flexible framework to model variable population trends (e.g., Boyd, DeMaster, Waples, Ward, & Taylor, ; Meyer & Millar, ; Winker, Carvalho, & Kapur, ). BSSMs also have three key properties that could help improve the objectivity of IUCN Red List assessments.…”

Section: Introductionmentioning

confidence: 99%

“…BSSMs have been used to assess extinction risk under the U.S. Endangered Species Act (Boyd et al., ), but rarely to assign IUCN categories (Regehr et al., ; Rueda‐Cediel, Anderson, Regan, & Regan, ).…”

Section: Introductionmentioning

confidence: 99%

Estimating IUCN Red List population reduction: JARA—A decision‐support tool applied to pelagic sharks

Sherley

Winker

Rigby

et al. 2019

CONSERVATION LETTERS

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The International Union for Conservation of Nature's (IUCN) Red List is the global standard for quantifying extinction risk but assessing population reduction (criterion A) of wide-ranging, long-lived marine taxa remains difficult and controversial. We show how Bayesian state-space models (BSSM), coupled with expert knowledge at IUCN Red List workshops, can combine regional abundance data into indices of global population change. To illustrate our approach, we provide examples of the process to assess four circumglobal sharks with differing temporal and spatial datadeficiency: Blue Shark (Prionace glauca), Shortfin Mako (Isurus oxyrinchus), Dusky Shark (Carcharhinus obscurus), and Great Hammerhead (Sphyrna mokarran). For each species, the BSSM provided global population change estimates over three generation lengths bounded by uncertainty levels in intuitive outputs, enabling informed decisions on the status of each species. Integrating similar analyses into future workshops would help conservation practitioners ensure robust, consistent, and transparent Red List assessments for other long-lived, wide-ranging species. K E Y W O R D SBayesian state-space model, biodiversity conservation, demography, elasmobranch, extinction risk, population decline, threatened speciesThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Consistent Extinction Risk Assessment under the U.S. Endangered Species Act

Cited by 12 publications

References 23 publications

Predictability of demographic rates based on phylogeny and biological similarity

Predictability of demographic rates based on phylogeny and biological similarity

Embracing Complexity and Complexity-Awareness in Marine Megafauna Conservation and Research

Estimating IUCN Red List population reduction: JARA—A decision‐support tool applied to pelagic sharks

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