Evidence map›Paper›PMID 40747995›Full record

ArticleEcology letters2025

Natural History Collections at the Crossroads: Shifting Priorities and Data-Driven Opportunities.

Owen Forbes, Peter H Thrall, Andrew G Young, Cheng Soon Ong

Abstract read
In one paragraph

Article in Ecology letters, 2025. 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

4 authors.

Owen ForbesCSIRO National Research Collections Australia, Canberra, Australia.ORCID https://orcid.org/0000-0002-7634-8279
Peter H ThrallCSIRO National Research Collections Australia, Canberra, Australia.ORCID https://orcid.org/0000-0003-1670-4240
Andrew G YoungCSIRO National Research Collections Australia, Canberra, Australia.
Cheng Soon OngCSIRO Data61, Canberra, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Natural history collections face a critical juncture as environmental change and biodiversity crises accelerate. While collections data are key components of eco-evolutionary and environmental research in both fundamental and applied contexts, collecting strategies remain primarily taxonomically motivated. We argue that sampling strategies must evolve to better address broader ecological challenges, through emerging applications enabled by advances in data science and digital technology. Here, we propose a flexible framework using modern statistical approaches to optimise sampling design and research prioritisation. By considering biodiversity, environmental, spatial and temporal dimensions, we demonstrate how information theory and decision science tools can support strategic collecting, databasing and digitisation efforts. Our framework provides an evidence-based pathway for collections to enhance their role as critical research infrastructure for addressing 21st century environmental challenges. To illustrate this data-driven approach to research prioritisation, we present an example based on sampling design for wombats (Vombatus ursinus) in Australia.

Indexed as

EcologyNatural HistoryAnimalsAustraliaBiodiversityConservation of Natural ResourcesData Scienceadaptive sampling designBayesian decision theoryconservation planningdata sciencedigital extended specimenFAIR data principlesmuseum genomicsnatural history collectionsresearch prioritisationvalue of information

Identifiers

PMID40747995
PMCPMC12315612

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.