Open Collections

Understanding, modeling and predicting trophic interactions between marine species

University of British Columbia

In this thesis, I explore and propose new methodologies and intend to provide new insights for understanding, modeling and predicting trophic interactions between marine species. I introduce the importance of trophic interactions in marine ecosystems and the common ecosystem modeling approaches applied to marine food webs. First, I present an attempt to synthetize information from all published Ecopath with Ecosim (EwE) models worldwide, gathered in the EcoBase digital repository. Through the compilation and standardization of a suite of metadata, I describe and discuss the usage of the EwE modeling approach and its evolution over time, since its very first application. I also present a meta-analysis of Ecopath models based on these metadata, where I select the models of potential interest, using a scoring method, and focus on one particular aspect of food web modeling, relating to the identification of keystone species. I propose a comprehensive and critical review of the ill-defined concept of keystone species and argue for a restored, exclusive and operational definition of the concept. The proposed definition is placed in a larger framework that considers different categories of ecologically important species. Then, a new functional index of keystoneness is derived from the EwE modeling approach, so as to identify potential keystone species in marine food webs. The proposed index addresses some of the biases observed in previously applied indices. Finally, I present an attempt to predict diet composition for predatory fish species. The intention is to build on existing large datasets, provided in the FishBase biodiversity information system, to identify predictors of fish feeding selectivity. The determination of clear or consistent pattern between biological and ecological species straits and diet composition is challenged by data restrictions, but some recommendations for future studies are provided. In conclusion, data availability may be a critical issue when considering some aspects of trophic interactions, especially for modeling and predictions at the species level. Data sharing within the scientific community, notably through the use of digital and open-access information repositories, is critical for the development of global meta-analyses in marine ecology.

Text

2015-01-08

Attribution-NonCommercial-NoDerivs 2.5 Canada

http://hdl.handle.net/2429/51860

Zoology

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/2.5/ca/