[Population Modeling] introduction

[Lucas Brotz]

Hi all,

My name is Lucas Brotz, and I am in my final year of a PhD program in marine biology and fisheries science at the University of British Columbia. Although population modelling (we spell it with 2 L’s in Canada ;-) is not my primary focus, I am interested in the population dynamics of marine species, especially jellyfish. While I was examining the dynamics of various jellyfish populations around the globe, I was met with the challenge of how to combine data of different ‘types’ together, in order to evaluate the underlying signal(s). With the help of colleagues, we developed a framework to do this using ‘fuzzy logic’. I will give a brief explanation of fuzzy logic below, along with links to the relevant papers in question, with the hope that it might be interesting and perhaps even useful to others. 

You can find out more about my work here: http://oceans.ubc.ca/person/lucas-brotz/ <http://oceans.ubc.ca/person/lucas-brotz/>

Cheers,
Lucas

Brotz, L, WWL Cheung, K Kleisner, E Pakhomov, & D Pauly (2012) Increasing jellyfish populations: trends in Large Marine Ecosystems. Hydrobiologia 690(1): 3-20. <http://link.springer.com/article/10.1007/s10750-012-1039-7>

Brotz, L (2011) Changing jellyfish populations: trends in Large Marine Ecosystems. Fisheries Centre Research Report 19(5), Fisheries Centre, University of British Columbia, 105 pp. <http://publications.oceans.ubc.ca/webfm_send/149>

Modified from Brotz (2011):

Fuzzy set theory and fuzzy logic, originally developed by Zadeh (1965), allows the representation of variables according to a gradation or degree of membership, rather than the classic true and false membership of conventional Boolean sets. Fuzzy logic also allows a conclusion to be reached with an associated gradation or degree of belief. As such, fuzzy set theory and logic provide a useful system for combining information of variable cardinality and/or confidence. 

Fuzzy set theory is firmly established in engineering and science, and is increasingly being used for ecological applications. A review of ecological models using fuzzy logic is available in Adriaenssens et al. (2004).

Adriaenssens, V, BD Baets, PLM Goethals, & ND Pauw (2004) Fuzzy rule-based models for decision support in ecosystem management. Science of the Total Environment 319(1-3): 1-12.

Zadeh, LA (1965) Fuzzy sets. Information and Control 8(3): 338-353.

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