Evidence map›Paper›PMID 30026796›Full record

ReviewEvolutionary applications2018

Guidelines for planning genomic assessment and monitoring of locally adaptive variation to inform species conservation.

Sarah P Flanagan, Brenna R Forester, Emily K Latch, Sally N Aitken, Sean Hoban

Abstract readReview
In one paragraph

Review in Evolutionary applications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 95 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
95citing papers in PubMed, 2 pooled it
–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

95 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  7. Omics Technologies in Molecular Biology.International journal of molecular sciences · 2026
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35 more citing papers are in PubMed but not listed here.

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.

Sarah P FlanaganNational Institute for Mathematical and Biological Synthesis University of Tennessee Knoxville TN USA.ORCID 0000-0002-2226-4213
Brenna R ForesterDuke University, Nicholas School of the Environment Durham NC USA.ORCID 0000-0002-1608-1904
Emily K LatchDepartment of Biological Sciences University of Wisconsin-Milwaukee Milwaukee WI USA.ORCID 0000-0002-9892-1056
Sally N AitkenFaculty of Forestry University of British Columbia Vancouver BC Canada.
Sean HobanThe Morton Arboretum Lisle IL USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identifying and monitoring locally adaptive genetic variation can have direct utility for conserving species at risk, especially when management may include actions such as translocations for restoration, genetic rescue, or assisted gene flow. However, genomic studies of local adaptation require careful planning to be successful, and in some cases may not be a worthwhile use of resources. Here, we offer an adaptive management framework to help conservation biologists and managers decide when genomics is likely to be effective in detecting local adaptation, and how to plan assessment and monitoring of adaptive variation to address conservation objectives. Studies of adaptive variation using genomic tools will inform conservation actions in many cases, including applications such as assisted gene flow and identifying conservation units. In others, assessing genetic diversity, inbreeding, and demographics using selectively neutral genetic markers may be most useful. And in some cases, local adaptation may be assessed more efficiently using alternative approaches such as common garden experiments. Here, we identify key considerations of genomics studies of locally adaptive variation, provide a road map for successful collaborations with genomics experts including key issues for study design and data analysis, and offer guidelines for interpreting and using results from genomic assessments to inform monitoring programs and conservation actions.

Indexed as

adaptive managementconservation geneticsconservation planninglocal adaptationnatural selectionnext‐generation sequencingoutlier detection

Identifiers

PMID30026796
PMCPMC6050180

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.