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Doctoral Student Supervision (Jan 2008 - May 2021)
Populations of Chinook (Oncorhynchus tshawytscha) and coho salmon (O. kisutch) haveexperienced significant declines in abundance and productivity over the last 50 years in theSalish Sea as harbour seals (Phoca vitulina) recovered from hunting and culling. Some havehypothesized that increased predation by seals may be responsible for the declines in salmonsurvival, and their failure to recover after reductions in fishing effort. However, it is not known ifthese correlations exist for every population of salmon in the Salish Sea, or how many youngChinook and coho salmon are consumed by seals each year. I developed mathematical andstatistical models to investigate the potential causal relationship between seal predation anddeclines in Chinook and coho salmon populations in the Salish Sea. I also used simulationmodeling to evaluate outcomes that may result if managers reduced British Columbia’s harbourseal population to promote the recovery of salmon populations. I found that harbour sealdensities were strongly negatively associated with productivity of most wild Chinook salmonpopulations in the Salish Sea and Washington Coast that were included in the study. Integratingrecently collected seal diet data with a novel predation model indicates that large numbers ofjuvenile Chinook and coho salmon are eaten by seals, and that predation-related mortality haslikely increased significantly over the last 50 years. The results of my simulation model suggestboth lethal removals and contraception could reduce the seal population, but that importanttradeoffs exist between the two approaches. Overall, my findings increase understanding of therole that marine mammal predation plays in the early marine life stage of juvenile salmon, andidentifies potential outcomes and tradeoffs of actively managing predator populations.
No abstract available.
Catches from bottom longline surveys are used to construct relative abundance indices for many demersal species. Due to their careful design, survey-based relative abundance indices are assumed to be proportional to the true species abundance. However, longlines catches may be affected by interspecific competition, gear saturation, and fine-scale gear and species interactions created by feeding behaviours and habitat preferences. A hook-based relative abundance index, the instantaneous rate of bait loss per species (λs), which accounts for hook competition and gear saturation, may resolve some of the problems with the common catch per unit effort (CPUE) index. I evaluated whether a linear or non-linear relationship exists between the λs index and abundance, and whether assumptions about bare hooks, species behaviours and fine-scale habitat affect the λs index. Using longlines targeting Yelloweye Rockfish (Sebastes ruberrimus) and Quillback Rockfish (S. maliger) in the inside waters of Vancouver Island, British Columbia, Canada, as a case study, I compared longline catches with underwater observations of the hooks and surrounding species from a Remotely Operated Vehicle in March (n = 13) and August (n = 12) of 2010. The results did not refute a linear model between the λs index and observed density, when compared to a non-linear model, except for the August Yelloweye index. The λs index did have a better fit with observed density than CPUE for Yelloweye, but not for Quillback. Adding hook-level habitat into the λs index improved the fit for Yelloweye, but not for Quillback. Additionally, observations showed that bare hooks were mainly due to non-target species, including large invertebrates. The annual λs index for the rockfish survey was estimated under different scenarios for bare hooks and species interactions, but the trends in the λs index were robust. Trends in the λs index differed from CPUE trends in some areas. My research results cast some doubt on the assumption that for a few inshore rockfish the λs index is consistently linearly related to abundance. Caution needs to be taken in extrapolating these results to other situations, as the experiments occurred in a small area and incorporated limited seasonal and temporal variation.
Lethal control of red foxes is often implemented on restricted areas where immigration from neighbouring sources is expected to make it difficult to keep local fox density low. The justification of lethal wildlife control should include demonstrating its effectiveness. To this end, population dynamics modelling may help to assess the performance of different control strategies in a range of real-world circumstances. A Bayesian state-space model for within-year fox population dynamics was developed that could be fitted to data on daily culling effort and success obtained from gamekeepers on shooting estates in Britain. The estimation model included parameters for key population processes within the culling area: immigration, cub recruitment and non-culling mortality. A simulation-estimation study showed that given a minimum of three years’ data the estimation of fox density and demographic parameters was reliable. Informative priors for the key model parameters were constructed using empirical data and meta-analysis. Data from 22 estates were modelled on a two-weekly time-step. Most estates achieved some suppression of the fox population relative to estimated carrying capacity, but few maintained consistently low densities. The number of foxes killed was a poor indicator of culling effectiveness, highlighting the need for modelling. Estimated immigration rates onto estates were typically high, indicating rapid replacement of culled foxes. There was unexpectedly high spatial variation among estates in estimated carrying capacity and immigration rate. There was evidence from a limited subset of estates that the variable density of released game birds may explain this. The food requirement of the fox population during the nesting period was assumed to indicate predation pressure on wild birds. Alternative culling strategies to reduce this requirement were evaluated using posterior parameter estimates from some estates. Culling concentrated in spring and summer only was more effective than culling uniformly throughout the year. Autumn-only culling was not an effective strategy for wild birds. Open-loop strategies were most effective as culling effort was used all the time. However, closed-loop strategies, where culling effort was conditional on feedback from simulated field-sign searches, achieved similar effects on food requirements using less effort. This revealed trade-offs between effectiveness, cost and animal welfare.