This study developed a robust technique for the assessment of morphometric differences among overwintering northern fish populations. Arctic charr were sampled soon before the freeze-up and just after ice break-up at two subarctic Quebec lakes. A homogenous sample of 397 fish was used. Regression analyses of the length-weight relationships and their derived condition indices were insufficient, due to their inherent limitations, to recognize the differences between sampling groups. A series of multivariate analyses (canonical, stepwise and discriminant analysis), based on eleven morphometric characters of the fish, provided a better assessment. The analysis recognized the distinctions between sampling groups, correctly classified 70-100% of the fish into their appropriate groupings, and indicated that body height measured at the anal opening was the most discriminatory variable. Landmark variables related to shape differences were effective in discriminating fish according to their lake of origin, whereas length and weight variables, which closely reflected the size differences, were better at distinguishing seasonal changes. The study provides a simple, efficient assessment method based on phenotypic variations to explain different survival strategies, and the associated life history traits, adopted by fish.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.27346 |
| Date | January 1996 |
| Creators | Idrus, Muhammad Rijal. |
| Contributors | Curtis, Mark A. (advisor) |
| Publisher | McGill University |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Format | application/pdf |
| Coverage | Master of Science (Department of Natural Resource Sciences.) |
| Rights | All items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated. |
| Relation | alephsysno: 001574728, proquestno: MQ29721, Theses scanned by UMI/ProQuest. |
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