Evidence map›Paper›PMID 33638664›Full record

ArticleEnvironmental management2021

Factors Associated with Listing Decisions under the U.S. Endangered Species Act.

Kathryn N Smith-Hicks, Michael L Morrison

Abstract read
PubMed Publisher
In one paragraph

Article in Environmental management, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Kathryn N Smith-HicksDepartment of Rangeland, Wildlife and Fisheries Management, Texas A&M University, College Station, TX, 77843, USA. kathryn.smith@ag.tamu.edu.
Michael L MorrisonDepartment of Rangeland, Wildlife and Fisheries Management, Texas A&M University, College Station, TX, 77843, USA.ORCID http://orcid.org/0000-0001-9298-8017

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Conservation efforts, including authorities outlined in the U.S. Endangered Species Act (ESA) of 1973, are attempting to slow the decline of species. Opinions on the success of the ESA vary widely, due in part to few species historically recovering to the point of delisting. Uncertainty surrounding the ESA relates to listing decisions and ambiguity of terminology within the ESA itself. Our goal was to evaluate the relationship, if any, of species characteristics, population metrics, threat level, and potential non-biological indicators to listing decisions under the ESA by the U.S. Fish and Wildlife Service (Service). We collected data from 143 ESA listing decisions published in the Federal Register from February 2011 to October 2014. Only 33 and 31% of listing decisions included population or range size estimates, respectively. Factors significantly correlated with ESA listing decision included taxonomic group, primary ownership of the species' habitat (federal or non-federal), whether the species is aquatic or terrestrial, and whether the species was part of a single or multiple-species listing decision. Increasing number of listed threats and time as a candidate species correlated positively with being listed as endangered. We have attempted to broadly identify the role both intrinsic (biological) and extrinsic (non-biological) factors play in listing decisions, and the importance of comprehensive data to understanding species distribution and abundance to facilitate more informed listing decisions.

Indexed as

Conservation of Natural ResourcesEndangered SpeciesAnimalsEcosystemFishesUncertaintyDeclining speciesExtinctionListing decisionsSpecies recoveryU.S. Endangered Species Act

Identifiers

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.