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Dr Andrew L Jackson

Prof Andrew Jackson - Professor in Zoology

Irish Research Council Laureate 2018 - 2022

Email: jacksoan@tcd.ie
Research Gate: Andrew Jackson
Github: andrewljackson
Google Scholar: Andrew L Jackson

Research Interests

My research interests lie in understanding ecological systems from an evolutionary perspective. I tend to approach these questions by using computational / mathematical models to understand how the nuts and bolts of these systems work. Much of my current research focuses on understanding interactions among individual animals living in close proximity. These situations are well suited to analysis and simulation in computer models where each individual animal can be represented as an automaton which interacts with its local neighbours or physico-chemical environment according to some simple set of rules. Recently I have been working on group foraging behaviour when food is scarce and have been particularly interested in vultures as a theme with considerable conservation motivation. My interests also extend to community ecology where the challenge is to understand how communities of organisms and species compete and interact with what is often a self-organising and stable system. I have several projects running at the moment on a variety of topics.

Current Projects

Individual-level interactions

A main interest of mine is in the evolution of behaviours related to the generation, acquisition and processing of socially derived information. We are currently investigating processes of aggression and cooperation using a combination of theoretical and empirical methods. I am increasingly interested in linking animal behaviour and interactions at individual-levels to population level patterns and processes, such as specialism/generalism, niche width, community structure, population biology and ultimately conservation. In this context I have worked previously on vulture foraging in light of their conservation, marine turtle nesting patterns and population consequences, and predation driven colony fragmentation in penguins. We are continuing our research on vulture foraging behaviour in Swaziland in collaboration with Prof Ara Monadjem.

Variation in the framerate of visual perception

Close up of human eye with clock superimposed on iris

Some animals see the world faster than others. That is, the frame rate of vision varies considerably across species. This is related to how fast they have to move in the world and therefore has important functional and ecological consequences. Humans on average see the world at 36 “frames per second”, but this trait varies substantially between individuals and we know nothing about how normal variation might affect performance. This phenomenon can be measured using techniques such as Critical Flicker Fusion threshold, which measures the frequency at which a flickering stimulus can no longer be detected as such. We aim to develop robust psychophysical methods to reliably measure those differences in field conditions outside the laboratory and quantify the magnitude of variation within and among individuals. We will assess the real-world consequences of this variation in an arena where human perceptual abilities are tested to the limits and where small individual differences may make the difference between success and failure, namely in high-speed sports. This collaborative work is being undertaken by PhD candidate Clinton Haarlem with a co-supervisory team comprised of Dr Andrew Jackson (zoology), Dr Kevin Mitchell (genetics) and Prof Redmond O'Connell (psychology).

Thermal Ecology and Metabolic Rates

I am currently working on several projects in collaboration with my colleague Dr Nicholas Payne relating to how temperature affects an organisms metabolic rate and what the consequences of this is for their performance and ecology. We are developing new mathematical models to understand these systems and using data from biologging of sharks and tuna to develop real world applications.

SIAR - Stable Isotope Analysis in R.

Stable Isotopes in Ecology
This on-going project focuses primarily on the development of computational and statistical models for application to stable isotope ecology. The main output so far is the development of a Bayesian mixing model for inferring diet and/or organisms’ niches from stable isotope analysis of consumer and source tissues.