Evidence map›Paper›PMID 32440370›Full record

ArticlePeerJ2020

Inventory statistics meet big data: complications for estimating numbers of species.

Ali Khalighifar, Laura Jiménez, Claudia Nuñez-Penichet, Benedictus Freeman, Kate Ingenloff, Daniel Jiménez-García, Town Peterson

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PubMed Full text at PMC Publisher
In one paragraph

Article in PeerJ, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Ali KhalighifarBiodiversity Institute, University of Kansas, Lawrence, KS, USA.ORCID 0000-0002-2949-8143
Laura JiménezBiodiversity Institute, University of Kansas, Lawrence, KS, USA.ORCID 0000-0002-6683-9576
Claudia Nuñez-PenichetBiodiversity Institute, University of Kansas, Lawrence, KS, USA.ORCID 0000-0001-7442-8593
Benedictus FreemanBiodiversity Institute, University of Kansas, Lawrence, KS, USA.ORCID 0000-0003-0895-4952
Kate IngenloffBiodiversity Institute, University of Kansas, Lawrence, KS, USA.ORCID 0000-0001-5942-9053
Daniel Jiménez-GarcíaBiodiversity Institute, University of Kansas, Lawrence, KS, USA.
Town PetersonBiodiversity Institute, University of Kansas, Lawrence, KS, USA.ORCID 0000-0003-0243-2379

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We point out complications inherent in biodiversity inventory metrics when applied to large-scale datasets. The number of units of inventory effort (e.g., days of inventory effort) in which a species is detected saturates, such that crucial numbers of detections of rare species approach zero. Any rare errors can then come to dominate species richness estimates, creating upward biases in estimates of species numbers. We document the problem via simulations of sampling from virtual biotas, illustrate its potential using a large empirical dataset (bird records from Cape May, NJ, USA), and outline the circumstances under which these problems may be expected to emerge.

Indexed as

Chao estimatorData qualitySpecies richnessVirtual biotas

Identifiers

PMID32440370
PMCPMC7229767

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.