Evidence map›Paper›PMID 24820139›Full record

ArticleConservation biology : the journal of the Society for Conservation Biology2014

Linking indices for biodiversity monitoring to extinction risk theory.

Michael A McCarthy, Alana L Moore, Jochen Krauss, John W Morgan, Christopher F Clements

Abstract read
In one paragraph

Article in Conservation biology : the journal of the Society for Conservation Biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

5 authors.

Michael A McCarthySchool of Botany, The University of Melbourne, Parkville, Victoria 3010, Australia. mamcca@unimelb.edu.au.
Alana L Moore
Jochen Krauss
John W Morgan
Christopher F Clements

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biodiversity indices often combine data from different species when used in monitoring programs. Heuristic properties can suggest preferred indices, but we lack objective ways to discriminate between indices with similar heuristics. Biodiversity indices can be evaluated by determining how well they reflect management objectives that a monitoring program aims to support. For example, the Convention on Biological Diversity requires reporting about extinction rates, so simple indices that reflect extinction risk would be valuable. We developed 3 biodiversity indices that are based on simple models of population viability that relate extinction risk to abundance. We based the first index on the geometric mean abundance of species and the second on a more general power mean. In a third index, we integrated the geometric mean abundance and trend. These indices require the same data as previous indices, but they also relate directly to extinction risk. Field data for butterflies and woodland plants and experimental studies of protozoan communities show that the indices correlate with local extinction rates. Applying the index based on the geometric mean to global data on changes in avian abundance suggested that the average extinction probability of birds has increased approximately 1% from 1970 to 2009.

Indexed as

BiodiversityExtinction, BiologicalAnimalsButterfliesCiliophoraConservation of Natural ResourcesMagnoliopsidaModels, BiologicalPopulation Densitybiodiversity indexbiodiversity measureextinction riskgeometric meanÍndice de biodiversidadmedia geométricamedida de la biodiversidadriesgo de extinción

Identifiers

PMID24820139
PMCPMC4253318

What OpenQuestion holds

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LicenceCC BY
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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.