Quantifying long-term population growth rates of threatened bull trout: challenges, lessons learned, and opportunities
| Autor: | Phaedra Budy, Robert Al-Chokhachy, Mary M. Conner, Howard A. Schaller, Tracy Bowerman |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
0106 biological sciences
education.field_of_study Ecology 010604 marine biology & hydrobiology Bayesian probability Population Markov chain Monte Carlo Aquatic Science Biology Logistic regression 010603 evolutionary biology 01 natural sciences Confidence interval Term (time) symbols.namesake Threatened species symbols Population growth education Ecology Evolution Behavior and Systematics Demography |
| Zdroj: | Canadian Journal of Fisheries and Aquatic Sciences. 74:2131-2143 |
| ISSN: | 1205-7533 0706-652X |
| DOI: | 10.1139/cjfas-2016-0336 |
| Popis: | Temporal symmetry models (TSM) represent advances in the analytical application of mark–recapture data to population status assessments. For a population of char, we employed 10 years of active and passive mark–recapture data to quantify population growth rates using different data sources and analytical approaches. Estimates of adult population growth rate were 1.01 (95% confidence interval = 0.84–1.20) using a temporal symmetry model (λTSM), 0.96 (0.68–1.34) based on logistic regressions of annual snorkel data (λA), and 0.92 (0.77–1.11) from redd counts (λR). Top-performing TSMs included an increasing time trend in recruitment (f) and changes in capture probability (p). There was only a 1% chance the population decreased ≥50%, and a 10% chance it decreased ≥30% (λMCMC; based on Bayesian Markov chain Monte Carlo procedure). Size structure was stable; however, the adult population was dominated by small adults, and over the study period there was a decline in the contribution of large adults to total biomass. Juvenile condition decreased with increasing adult densities. Utilization of these different information sources provided a robust weight-of-evidence approach to identifying population status and potential mechanisms driving changes in population growth rates. |
| Databáze: | OpenAIRE |
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