Evidence map›Paper›PMID 25568043›Full record

ArticleEvolutionary applications2012

Adaptive potential of ash (Fraxinus excelsior) populations against the novel emerging pathogen Hymenoscyphus pseudoalbidus.

Erik Dahl Kjær, Lea Vig McKinney, Lene Rostgaard Nielsen, Lars Nørgaard Hansen, Jon Kehlet Hansen

Abstract read
In one paragraph

Article in Evolutionary applications, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Article
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  4. Genomic prediction of resistance toEvolutionary applications · 2024
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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

5 authors.

Erik Dahl KjærForest & Landscape, Faculty of Life Sciences, University of Copenhagen Frederiksberg, Denmark.
Lea Vig McKinneyForest & Landscape, Faculty of Life Sciences, University of Copenhagen Frederiksberg, Denmark.
Lene Rostgaard NielsenForest & Landscape, Faculty of Life Sciences, University of Copenhagen Frederiksberg, Denmark.
Lars Nørgaard HansenForest & Landscape, Faculty of Life Sciences, University of Copenhagen Frederiksberg, Denmark.
Jon Kehlet HansenForest & Landscape, Faculty of Life Sciences, University of Copenhagen Frederiksberg, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An emerging infectious pathogen Hymenoscyphus pseudoalbidus has spread across much of Europe within recent years causing devastating damage on European common ash trees (Fraxinus excelsior) and associated plant communities. The present study demonstrates the presence of additive genetic variation in susceptibility of natural F. excelsior populations to the new invasive disease. We observe high levels of additive variation in the degree of susceptibility with relatively low influence of environmental factors (narrow-sense heritability = 0.37-0.52). Most native trees are found to be highly susceptible, and we estimate that only around 1% has the potential of producing offspring with expected crown damage of <10% under the present disease pressure. The results suggest that the presence of additive genetic diversity in natural F. excelsior populations can confer the species with important ability to recover, but that low resistance within natural European populations is to be expected because of a low frequency of the hypo-sensitive trees. Large effective population sizes will be required to avoid genetic bottlenecks. The role of artificial selection and breeding for protection of the species is discussed based on the findings.

Indexed as

adaptationconservation geneticsecologicalemerging infectious disease geneticsinvasive species

Identifiers

PMID25568043
PMCPMC3353348

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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.