Evidence map›Paper›PMID 37016137›Full record

ArticleHeredity2023

Drivers of strong isolation and small effective population size at a leading range edge of a widespread plant.

Anita Cisternas-Fuentes, Matthew H Koski

Abstract read
In one paragraph

Article in Heredity, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
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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

2 authors.

Anita Cisternas-FuentesDepartment of Biological Sciences, Clemson University, 132 Long Hall, Clemson, SC, 29634, USA. anita.cisternas.fuentes@gmail.com.ORCID 0000-0002-8951-0773
Matthew H KoskiDepartment of Biological Sciences, Clemson University, 132 Long Hall, Clemson, SC, 29634, USA. mkoski@clemson.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Climate change has influenced species distributions worldwide with upward elevational shifts observed in many systems. Leading range edge populations, like those at upper elevation limits, are crucial for climate change responses but can exhibit low genetic diversity due to founder effects, isolation, or limited outbreeding. These factors can hamper local adaptation at range limits. Using the widespread herb, Argentina anserina, we measured ecological attributes (population density on the landscape, area of population occupancy, and plant and flower density) spanning a 1000 m elevation gradient, with high elevation populations at the range limit. We measured vegetative clonal potential in the greenhouse for populations spanning the gradient. We combined these data with a ddRAD-seq dataset to test the hypotheses that high elevation populations would exhibit ecological and genomic signatures of leading range edge populations. We found that population density on the landscape declined towards the high elevation limit, as is expected towards range edges. However, plant density was elevated within edge populations. In the greenhouse, high elevation plants exhibited stronger clonal potential than low elevation plants, likely explaining increased plant density in the field. Phylogeographic analysis supported more recent colonization of high elevation populations which were also more genetically isolated, had more extreme heterozygote excess and had smaller effective population size than low. Results support that colonization of high elevations was likely accompanied by increased asexuality, contributing to a decline in effective population size. Despite high plant density in leading edge populations, their small effective size, isolation and clonality could constrain adaptive potential.

Indexed as

AltitudePlantsAcclimatizationAdaptation, PhysiologicalPopulation Density

Identifiers

PMID37016137
PMCPMC10238488

What OpenQuestion holds

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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.