Author

S. N. Aitken

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Evolutionary Biology· 4

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Assay:DNA methylation· 2 Research Focus:chromatin & epigenetic regulation· 1 Research Focus:clustering· 1 Research Focus:development & morphogenesis· 1 Research Focus:ecology & biodiversity· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

B. M. Lind· 2 shared R. Candido-Ribeiro· 2 shared C. R. Mahony· 1 shared D. Obreht Vidakovic· 1 shared I. R. MacLachlan· 1 shared J. B. Yoder· 1 shared J. S. Elleouet· 1 shared M. C. Whitlock· 1 shared

Activity by Year

2018-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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2 shared papersEvolutionary Biology

B. M. Lind

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Author profile →

4 papers

Recent·Most cited

Weak local adaptation to drought in seedlings of a widespread conifer

R. Candido-Ribeiro, S. N. Aitken

This study examines drought tolerance and growth responses in Douglas-fir seedlings from 73 provenances, finding weak local adaptation and strong temperature-driven clinal variation.

bioRxiv · Jun 9, 2023Evolutionary Biology

How useful is genomic data for predicting maladaptation to future climate?

B. M. Lind, R. Candido-Ribeiro, P. Singh, M. Lu, D. Obreht Vidakovic, T. R. Booker, M. C. Whitlock, S. Yeaman, N. Isabel, S. N. Aitken

The paper evaluates two methods for predicting population maladaptation to climate change using genomic data and finds they outperform climatic distances but have limited predictive consistency across future climates.

bioRxiv · Feb 10, 2023Evolutionary Biology

Evaluating genomic data for management of local adaptation in a changing climate: A lodgepole pine case study

C. R. Mahony, I. R. MacLachlan, B. M. Lind, J. B. Yoder, T. Wang, S. N. Aitken

This study evaluates genomic data's ability to characterize local adaptation in lodgepole pine, finding genomic and climate data are nearly equivalent for describing adaptation in seedling traits.

bioRxiv · Mar 5, 2019Evolutionary Biology

Exploring Approximate Bayesian Computation for inferring recent demographic history with genomicmarkers in non-model species

J. S. Elleouet, S. N. Aitken

This study evaluates how ABC performs with genomic markers in non-model species, finding that unphased GBS-type data can accurately infer simple demographic models.

bioRxiv · Jan 24, 2018Evolutionary Biology