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Dr Stuart Daines

Research Fellow

 2633

 Laver Building 719

 

Laver Building, University of Exeter, North Park Road, Exeter, EX4 4QE, UK

Overview

My overall research interest is in understanding the coevolution of life and the physical environment, focussing on understanding the links between marine ecology and biogeochemistry.

Biochemical processes such as oxygenic photosynthesis are linked to the biosphere and physical Earth System by a hierarchy of processes on scales from the molecular biology of the cell through organisms and ecosystems to geochemistry. Evolutionary ecology is then key to understanding how global properties such as atmospheric oxygen level and element cycling arise as emergent properties from natural selection and physiological, biochemical and biophysical constraints at lower levels, and geochemistry at large scales. My work uses models from simple box models to agent-based computational models to ultimately seek to understand overall organising principles for ecosytem structure and function in the Earth system.

Qualifications

BA (Cambridge)

PhD (Cambridge)

Research

Research interests

I use models from simple box models to agent-based computational models to ultimately seek to understand overall organising principles for ecosytem structure, and function in the Earth system. Understanding the principles underlying emergent properties such as biogeography, biodiversity and element cycling will help understand when ecosystem response to an environmental perturbation or evolutionary innovation results in gradual and predictable adaptive change, and when to a catastrophic regime shift, and ultimately how life has coevolved with the physical environment over Earth history.

Research projects

The EVolutionary Ecosystem model (EVE). Representing both ecological and evolutionary processes in a model for the contemporary marine ecosystem allows us to test hypotheses for emergent biogeography and ecosystem structure. I am specifically interested in seeing what properties of the microbial ecosystem we can understand from a new trait-based approach with a model for cell physiology,  sub-cellular resource allocation, and predation and defence strategies. This links emergent properties such as organism ecotypes, metabolic diversity, population size structure, and ecosystem nutrient cycling across scales to evolutionarily conserved biochemistry and fundamental ecophysiological and biophysical constraints. See our recent poster from AMEMR 2011 for an overview of the EVE project.

Proterozoic marine ecology and biogeochemistry. The Precambrian marine ecosystem apparently remained in an almost static state with relatively low oxygen for a billion years, followed by a major reorganisation with a rise in oxygen, the first animals, and the greening of the continents. Why was the Proterozoic ecosystem organised so differently, why was the tempo of evolution so different, and what combination of triggers and feedbacks resulted in the Neoproterozoic revolution? We are using a hierarchy of models linking ecophysiology to biogeochemistry to test hypotheses against geochemical and paleontological data.

Gaia and design principles for the biosphere. Biotic feedbacks play a large role in regulating CO2 and climate, nutrient cycling, and atmospheric oxygen. Qualitative arguments and simple models suggest we can understand the structure and properties of these feedbacks as a result of selection at multiple scales, from natural selection at organism level, to ‘sequential selection’ and observer self-selection (the anthropic principle) at planetary scale. See poster from GSL Life and the Planet meeting 2011.

Links


Publications

Key publications | Publications by category | Publications by year

Publications by category


Journal articles

Lenton TM, Daines SJ (2017). Biogeochemical Transformations in the History of the Ocean. Ann Rev Mar Sci, 9, 31-58. Abstract.  Author URL.  Full text.

Publications by year


2017

Lenton TM, Daines SJ (2017). Biogeochemical Transformations in the History of the Ocean. Ann Rev Mar Sci, 9, 31-58. Abstract.  Author URL.  Full text.

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