Evidence map›Paper›PMID 34117681›Full record

ArticleGlobal change biology2021

Predicting species and community responses to global change using structured expert judgement: An Australian mountain ecosystems case study.

James S Camac, Kate D L Umbers, John W Morgan, Sonya R Geange, Anca Hanea, Rachel A Slatyer, Keith L McDougall, Susanna E Venn, Peter A Vesk, Ary A Hoffmann and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Global change biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
4.5field-weighted citation impact, top 6% of its field
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

2 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
  2. 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

11 authors at 6 institutions in 1 country.

James S CamacCentre of Excellence for Biosecurity Risk Analysis, School of BioSciences, The University of Melbourne, Parkville, Vic., Australia.ORCID https://orcid.org/0000-0003-4785-0742
Kate D L UmbersSchool of Science, Western Sydney University, Penrith, NSW, Australia.ORCID https://orcid.org/0000-0002-9375-4527
John W MorganResearch Centre for Applied Alpine Ecology, La Trobe University, Bundoora, Vic., Australia.
Sonya R GeangeResearch School of Biology, Australian National University, Acton, ACT, Australia.ORCID https://orcid.org/0000-0001-5344-7234
Anca HaneaCentre of Excellence for Biosecurity Risk Analysis, School of BioSciences, The University of Melbourne, Parkville, Vic., Australia.ORCID https://orcid.org/0000-0003-3870-5949
Rachel A SlatyerResearch School of Biology, Australian National University, Acton, ACT, Australia.
Keith L McDougallNSW Department of Planning, Industry and Environment, Queanbeyan, NSW, Australia.ORCID https://orcid.org/0000-0002-8288-6444
Susanna E VennCentre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Burwood, Vic., Australia.ORCID https://orcid.org/0000-0002-7433-0120
Peter A VeskSchool of BioSciences, The University of Melbourne, Parkville, Vic., Australia.ORCID https://orcid.org/0000-0003-2008-7062
Ary A HoffmannBio21 Institute, School of BioSciences, The University of Melbourne, Parkville, Vic., Australia.ORCID https://orcid.org/0000-0001-9497-7645
Adrienne B NicotraResearch School of Biology, Australian National University, Acton, ACT, Australia.ORCID https://orcid.org/0000-0001-6578-369X
The University of Melbourne · AUAustralian National University · AUDeakin University · AULa Trobe University · AUNSW Department of Planning and Environment · AUWestern Sydney University · AU

Funding

Centre for Biodiversity Analysis, ANUCentre of Excellence for Biosecurity Risk Analysis National Climate Change Adaptation Research FacilityDepartment of Industry Conference Support Program
6 · The paper itself

Abstract

Conservation managers are under increasing pressure to make decisions about the allocation of finite resources to protect biodiversity under a changing climate. However, the impacts of climate and global change drivers on species are outpacing our capacity to collect the empirical data necessary to inform these decisions. This is particularly the case in the Australian Alps which have already undergone recent changes in climate and experienced more frequent large-scale bushfires. In lieu of empirical data, we use a structured expert elicitation method (the IDEA protocol) to estimate the change in abundance and distribution of nine vegetation groups and 89 Australian alpine and subalpine species by the year 2050. Experts predicted that most alpine vegetation communities would decline in extent by 2050; only woodlands and heathlands are predicted to increase in extent. Predicted species-level responses for alpine plants and animals were highly variable and uncertain. In general, alpine plants spanned the range of possible responses, with some expected to increase, decrease or not change in cover. By contrast, almost all animal species are predicted to decline or not change in abundance or elevation range; more species with water-centric life-cycles are expected to decline in abundance than other species. While long-term ecological data will always be the gold standard for informing the future of biodiversity, the method and outcomes outlined here provide a pragmatic and coherent basis upon which to start informing conservation policy and management in the face of rapid change and a paucity of data.

Indexed as

Climate ChangeEcosystemAnimalsAustraliaBiodiversityPlantsadaptive capacityalpinebiodiversity conservationclimate changeexpert elicitationexposure risk

Identifiers

PMID34117681
PMCPMC8457067
OpenAlexW3168378476

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.