Automated Author Profile

McKinney, Lea Vig

University of Copenhagen

Current S-Index

2.2

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

2.2

Average Dataset Index per dataset

Total Datasets

1

Total datasets for this author

Average FAIR Score

76.9%

Average FAIR Score per dataset

Total Citations

1

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Data from: Adaptive potential of ash (Fraxinus excelsior) populations against the novel emerging pathogen Hymenoscyphus pseudoalbidus (Version: 1)

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 highly susceptible, and we estimate that only around 1% has the potential of producing offspring with expected crown damage of less than 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 due to 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.

Authors

  • Kjær, Erik Dahl ;
  • McKinney, Lea Vig ;
  • Nielsen, Lene Rostgaard ;
  • Hansen, Lars Nørgaard ;
  • Hansen, Jon Kehlet
1 Citation0 Mentions77% FAIR2.2 Dataset Index
10.5061/dryad.62v0p8q22011