Research Document - 2015/038

Hierarchical modelling of spatiotemporal dynamics of biological characteristics of Lake Whitefish, Coregonus clupeaformis (Mitchill), in Great Slave Lake, Northwest Territories, Canada, 1972–2004

By Xinhua Zhu, A. Chris Day, W. E. Fred Taptuna, Theresa J. Carmichael, and Ross F. Tallman

Abstract

To monitor fisheries population dynamics, a fishery-dependent sampling program was initiated in 1972 for Lake Whitefish in Great Slave Lake (GSL). A set of fish biological data on scale age, fork length and dressed weight has been collected annually. The objectives of this study are to summarize the spatiotemporal variations in the biological characteristics and to evaluate the potential association of these biological characteristics with cumulative impacts from localized hydrology, meteorology, global climate changes and exploitation during 1972-2004.

Applying multimodel inference (MMI), relationships between log-transformed pairs of fork length and round weight were best described by a piece-wise regression model for fish in southern shallow areas and a cubic regression model for deep-water fish. In terms of the selected length-weight models, the relative condition index, KLC, was derived to reflect the effects of changing mesh sizes and fishing efforts. Statistically, a conventional linear regression model, which is used to relate body mass proportionally to the cube of body length, did not support the change in the morphological relationship of the fish in GSL.

Three length-at-age growth models, von Bertalanffy, generalized, and logistic growth, were employed to select for better representation of the growth patterns of the fish populations. Among those, the generalized growth model performed the best for describing length-based growth patterns of the fish. Spatial comparison of growth patterns indicated that the fish growth traits changed along a southwest to northeast gradient in GSL.

Throughout the history of the fishery, the profound variation in Lake Whitefish harvest corresponded to changes in social and economic factors. Thus, despite the spatiotemporal variations in the biological metrics and harvest, there was no indication of a decline in stock status among management areas. However, information gaps and uncertainties in the fish biological assessment were identified and further analyses were recommended combining fishery-dependent and fishery-independent survey results.

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