Research areas
lab webpage:
Evolutionary statistical quantitative genetics, or, analysis of longitudinal data from populations of unmanipulated animals
Some of the most valuable data for understanding how evolution works in natural populations is individual-based longitudinal data from pedigreed populations.听 Longitudinal data on individuals provides possibilities to link aspects of phenotype to life histories and fitness.听 Pedigree data allows inference of the genetic basis of variation in phenotypic traits, based on patterns of similarity of relatives.
With听听at the University of Edinburgh and elsewhere, a portion of my research revolves around the study of the selection and genetics of a range of traits in听听(pictured) and other long-term animal datasets from around the world.
Evolutionary genetic theory
I use analytical and computational approaches to understanding what patterns of genetic variation are expected in nature, and also of how to interpret observed patterns in microevolutionary parameters, including both aspects of genetics and selection.听 I have an ongoing interest in the patterns of genetic variation that are generated by complex landscape arrangements, especially in dendritic systems, which characterize all freshwater landscapes.听 I have recently been working on the interpretation of relationships between phenotypic traits and fitness mean in terms 鈥渃hains of causation鈥� in the context of characterizing the form of natural selection.
Software for empirical microevolutionary studies in nature
Analysis of data from natural populations is often very challenging.听 Datasets are often incomplete due to practical realities such as limited molecular information to resolve pedigrees, and/or imperfect detection of individuals for recording of life history information.听 I work on developing statistical tools to link fundamental evolutionary genetic theory to real data from the field. 听听packages include听, and听.
PhD supervision
- Luisa听Lucresia De Sales Ribeiro
Selected publications
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Open access
Janeiro, M. J., Henshaw, J. M., Pemberton, J. M., Pilkington, J. G. & Morrissey, M. B., 13 Sept 2025, (E-pub ahead of print) In: Evolution Letters. Advance Article, p. 14 14 p., qraf029.
Research output: Contribution to journal 鈥� Letter 鈥� peer-review
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Open access
Mittell, E. A., Leblanc, C. A., Kristj谩nsson, B. K., Ferguson, M. M., R盲s盲nen, K. & Morrissey, M. B., Jan 2025, In: Royal Society Open Science. 12, 1, p. 1-17 17 p., 241802.
Research output: Contribution to journal 鈥� Article 鈥� peer-review
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Open access
Mittell, E. A., Pemberton, J. M., Kruuk, L. E. B. & Morrissey, M. B., 2 Dec 2025, In: Proceedings of the National Academy of Sciences of the United States of America. 122, 48, p. 1-7 7 p., e2513969122.
Research output: Contribution to journal 鈥� Article 鈥� peer-review
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Open access
Nagel, R., Ruxton, G. D. & Morrissey, M. B., May 2024, In: Methods in Ecology and Evolution. 15, 5, p. 843-855 13 p.
Research output: Contribution to journal 鈥� Article 鈥� peer-review
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Open access
Leblanc, C. A., R盲s盲nen, K., Morrissey, M., Sk煤lason, S., Ferguson, M. & Kristj谩nsson, B. K., 15 Apr 2024, (E-pub ahead of print) In: BMC Ecology and Evolution. 24, 19 p., 45.
Research output: Contribution to journal 鈥� Article 鈥� peer-review
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Open access
Jessop, A., Morrissey, M. & Barbosa, M., 27 Apr 2024, (E-pub ahead of print) In: Animal Behaviour. 212, p. 93-100 8 p.
Research output: Contribution to journal 鈥� Article 鈥� peer-review
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Mittell, E. A. & Morrissey, M. B., 1 Apr 2024, In: Evolution. 78, 4, p. 601-611 11 p.
Research output: Contribution to journal 鈥� Article 鈥� peer-review
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Open access
Morrissey, M. B. & Goudie, I. B. J., Jul 2022, In: Evolution. 76, 7, 28 p., 14486.
Research output: Contribution to journal 鈥� Article 鈥� peer-review
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Purchase, C. F., Rooke, A. C., Gaudry, M. J., Treberg, J. R., Mittell, E. A., Morrissey, M. B. & Rennie, M. D., 12 Jan 2022, In: Proceedings. Biological sciences. 289, 1966, p. 1-10 10 p., 20212146.
Research output: Contribution to journal 鈥� Article 鈥� peer-review
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Open access
Froman Walmsley, S. & Morrissey, M., Jun 2022, In: Evolution Letters. 6, 3, p. 234-244 11 p.
Research output: Contribution to journal 鈥� Article 鈥� peer-review
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