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Population Viability Analysis of Atlantic Salmon in Maine, USA
Author(s) -
Legault Christopher M.
Publication year - 2005
Publication title -
transactions of the american fisheries society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.696
H-Index - 86
eISSN - 1548-8659
pISSN - 0002-8487
DOI - 10.1577/t04-017.1
Subject(s) - endangered species , population viability analysis , salmo , extinction (optical mineralogy) , population , fishery , range (aeronautics) , stocking , habitat , extinction probability , geography , environmental science , population size , ecology , biology , demography , fish <actinopterygii> , engineering , paleontology , sociology , aerospace engineering
Populations of Atlantic salmon Salmo salar in eight rivers of Maine, USA, are listed as endangered under the U.S. Endangered Species Act. This listing has required the creation of measurable and objective delisting criteria. One component of these criteria is the determination of the abundance levels associated with recovered populations. Population viability analysis (PVA) was chosen as the method to estimate these recovery levels because it (1) formalizes the combination of information available on the species. (2) quantifies the uncertainty in the population parameters and evaluates the impact of this uncertainty on the probability of extinction, and (3) allows examination of potential management strategies. A PVA specific to the Atlantic salmon populations in Maine was conducted based on the life history characteristics of the endangered populations (i.e., multiple ages of return from sea, kelting, river‐specific habitat limitations, and use of stocking as a recovery tool). The model was verified by using data from a single river and by comparing the results with those of a simpler PVA model. Projections for the eight rivers were conducted for a range of future conditions and management strategies to produce extinction probabilities that managers could use to set recovery criteria. Results beyond extinction risk, such as population age or stage structure, are also shown to be important for management consideration.

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