Robust and Defensible Mark-Recapture Methodologies for Salmonid Escapement: Modernizing the Use of Data and Resources
|Author||Vélez-Espino, L. A., Irvine, J. R., Winther, I., Dunlop, R., Mullins, G., Singer, K., and Trouton, N|
|Subjects||Mark–Recapture, Salmonid Escapement|
|Download File||Download , 0.2 MB|
Estimates of population size, required for most ecological investigations, are often achieved by mark-recapture experiments, frequently by applying pooled or stratified Petersen estimators. Unfortunately, the closure assumption required by Petersen estimators is frequently violated in the estimation of salmonid escapement, even though the consequences of this violation have been known for decades. We illustrate how biologists and analysts can and should make better use of statistical, mathematical, and computational advances in their analysis of mark recapture data. Modern, easily applied approaches address and minimize the effects of violations to the model assumptions on which abundance estimators are based. Using examples from research estimating the numbers of Chinook Salmon Oncorhynchus tshawytscha escaping fisheries to spawn, this study demonstrates and provides evidence in support of the use of a robust and defensible approach to salmonid escapement estimation based on the analysis of individual encounter histories. The main attributes of the approach include (1) testing for demographic closure, (2) allowing different hypotheses about the demographic attributes and capture history of the studied population to be expressed within a model selection framework, encompassing suites of open- or closed-population approaches, and (3) optimizing the use of information by embracing the opportunities that mark–recapture experiments generate to increase our knowledge of salmonid ecology and hence improve both future study designs and management decisions. This study also demonstrates that discrepancies (positive) in abundance estimates produced with the Petersen estimator relative to those produced by the “best models” fromrobust estimators are inversely proportional to sampling rates.
Please follow this link for access to the journal article: http://www.tandfonline.com/toc/ujfm20/36/1