Evidence map›Paper›PMID 35118675›Full record

ArticleThe New phytologist2022

Multivariate selection mediated by aridity predicts divergence of drought-resistant traits along natural aridity gradients of an invasive weed.

Carter Carvalho, Rochelle Davis, Tim Connallon, Roslyn M Gleadow, Joslin L Moore, Akane Uesugi

Abstract read
In one paragraph

Article in The New phytologist, 2022. 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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Carter CarvalhoSchool of Biological Sciences, Monash University, Clayton, Vic., 3800, Australia.
Rochelle DavisSchool of Biological Sciences, Monash University, Clayton, Vic., 3800, Australia.
Tim ConnallonSchool of Biological Sciences, Monash University, Clayton, Vic., 3800, Australia.ORCID 0000-0002-1962-4951
Roslyn M GleadowSchool of Biological Sciences, Monash University, Clayton, Vic., 3800, Australia.ORCID 0000-0003-4756-0411
Joslin L MooreSchool of Biological Sciences, Monash University, Clayton, Vic., 3800, Australia.ORCID 0000-0001-9809-5092
Akane UesugiSchool of Biological Sciences, Monash University, Clayton, Vic., 3800, Australia.ORCID 0000-0003-3363-5312

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Geographical variation in the environment underpins selection for local adaptation and evolutionary divergence among populations. Because many environmental conditions vary across species' ranges, identifying the specific environmental variables underlying local adaptation is profoundly challenging. We tested whether natural selection mediated by aridity predicts clinal divergence among invasive populations of capeweed (Arctotheca calendula) that established and spread across southern Australia during the last two centuries. Using common garden experiments with two environmental treatments (wet and dry) that mimic aridity conditions across capeweed's invasive range, we estimated clinal divergence and effects of aridity on fitness and multivariate phenotypic selection in populations sampled along aridity gradients in Australia. We show that: (1) capeweed populations have relatively high fitness in aridity environments similar to their sampling locations; (2) the magnitude and direction of selection strongly differs between wet and dry treatments, with drought stress increasing the strength of selection; and (3) differences in directional selection between wet and dry treatments predict patterns of clinal divergence across the aridity gradient, particularly for traits affecting biomass, flowering phenology and putative antioxidant expression. Our results suggest that aridity-mediated selection contributes to trait diversification among invasive capeweed populations, possibly facilitating the expansion of capeweed across southern Australia.

Indexed as

DroughtsPlant WeedsAdaptation, PhysiologicalPhenotypeSelection, GeneticArctotheca calendulacapeweedclinesdrought toleranceinvasive specieslocal adaptationphenotypic selectionselection gradient

Identifiers

PMID35118675
PMCPMC9311224

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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.