Linking fish population dynamics to habitat conditions: insights from the application of a process-oriented approach to several Great Lakes species

Abstract

One of the major challenges facing fishery scientists and managers today is determining how fish populations are influenced by habitat conditions. Many approaches have been explored to address this challenge, all of which involve modeling at one level or another. In this paper, we explore a process-oriented model approach whereby the critical population processes of birth and death rates are explicitly linked to habitat conditions. Application of this approach to five species of Great Lakes fishes including: walleye (Sander vitreus), lake trout (Salvelinus namaycush), smallmouth bass (Micropterus dolomieu), yellow perch (Perca flavescens), and rainbow trout (Onchorynchus mykiss), yielded a number of insights into the modeling process. One of the foremost insights is that processes determining movement and transport of fish are critical components of such models since these processes largely determine the habitats fish occupy. Because of the importance of fish location, an individual-based model appears to be a nearly inescapable modeling requirement. There is, however, a paucity of field-based data directly relating birth, death, and movement rates to habitat conditions experienced by individual fish. There is also a paucity of habitat information at a fine temporal and spatial scale for many important habitat variables. Finally, the general occurrence of strong ontogenetic changes in the response of different life stages to habitat conditions emphasizes the need for a modeling approach that considers all life stages in an integrated fashion.

Modelling Tools to Analyze and Assess the Ecological Impact of Hydropower Dams

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“…Therefore, Coops et al (2003) and more recently Tao et al (2016) highlighted the urgency of collecting ecological data on fish-habitat relationship. Fish habitat use is a key driver of population dynamics (Hayes et al, 2009) and an essential knowledge for predicting how populations will respond to management interventions (Koster et al, 2015;Cooke et al, 2016). In particular, the identification of crucial habitats is important for efficient aquatic conservation in areas with strong human influence (Halpern et al, 2005;Sale et al, 2005).…”