Dr Cóilín Minto

Senior Research Fellow
+353 (0)91 742514

Standing on the seashore I am ever excited by the beautifully complex and dynamic system just under the waves. Trying to understand small parts of that system and how we interact with it fascinates me and is the core of my research. My general approach in the presence of many uncertainties is to simplify with relevant probabilistic descriptions and allow observation, experiment and predictive capacity humble hypotheses. A statistical approach is vital to capture uncertainties and point towards the truth in what are often observation-only systems. I strive to continually develop the symbiotic relationship between marine science and statistical modelling. I therefore focus on the development and application of tailored statistical methodologies to understand dynamics at individual, population and community levels. Statistical research interests include hierarchical analysis, longitudinal analysis, mixture modelling and dynamic time series analysis, particularly state space modelling. Current and ongoing applications include mixture modelling of life histories, discontinuous time series filters, design and analysis of fishing gear experimental trials, and management strategy evaluation for wild population monitoring. I am fortunate to: collaborate with many great scientists and students of different disciplines, lecture in quantitative ecology and biostatistics, contribute to European stock assessments and be a founding developer of the RAM Legacy Stock Assessment Database.


This collaborative project with the Marine Institute takes a whole life cycle approach to investigate how commercial fish stocks are responding to climate change.
Simon Berrow IWDG
The aim of this project is to investigate the influence of environmental and observational effects on Harbour Porpoise survey counts from the NPWS monitoring programme conducted across three spatial areas of conservation in 2007, 2008, 2013-2016 and 2018.
Close-up of a trawler fishing net with tassels and floats
FishKOSM aims to increase our operational understanding of sustainable yields in mixed and multi-species fisheries.
Crew of Fishermen Work on Commercial Fishing Ship that Pulls Trawl Net.
The MyDas project developped and tested a range of assessment models and methods to establish Maximum Sustainable Yield (MSY), or proxy MSY reference points across the spectrum of data-limited stocks.
DATALO focusses on statistical design and analysis of gear trials and survival experiments in collaboration with Bord Iascaigh Mhara. Outputs from the project have direct policy relevance in a time of considerable change.
This European collaborative project developed novel methods of estimating fish age using the chemical composition of hard parts.
This collaboration with the Marine Institute is unlocking the value of fish scale and otolith collections to marine ecosystem and climate change research.
This project assessed the conservation status of the white-clawed crayfish, Austropotamobius pallipes, in all fifteen Special Areas of Conservation (SACs) in Ireland
The Tipping Points project (2015-2019) developped novel statistical methods for detecting and forecasting ecosystem change.