Evaluation of performance of alternative management models of Pacific salmon (Oncorhynchus spp.) in the presence of climatic change and outcome uncertainty using Monte Carlo simulations

Abstract

An important management challenge is to maintain productive populations of Pacific salmon ( Oncorhynchus spp.), despite highly variable environments and our weak understanding of future climatic conditions and mechanisms that link them to salmon. This understanding could be improved by including environmental covariates in salmon population models and applying advanced “meta-analyses” to large data sets to better estimate underlying functional relationships. However, the performance of such models needs to be determined in the context of an overall system. We therefore simulated a 15-population salmon fishery system and compared the performance (in terms of catch and an index of conservation concern) of 10 forecasting and stock assessment models, ranging from simple to complex, by stochastically simulating components of a salmon fishery using a “closed-loop simulation” (or “management strategy evaluation”) under a variety of plausible future climatic scenarios. We found that complex models perform better in some situations. However, their incremental benefits are small and are swamped by the large variability in outcomes of management actions caused by “outcome uncertainty”, which reflects noncompliance of fishing vessels with regulations as well as variation in catchability. Reduction of this outcome uncertainty should therefore be a top priority, as should evaluations of more complex stock assessment models before adopting them.

Comparison of stock management with production, difference, and age-structured models using operating models

“…These results are qualitatively similar to those obtained in the present study. Dorner et al (2009) evaluated management models for Pacific salmon. They used several assessment and prediction models and found that although complex models performed better in some cases, their benefits were small.…”

Emerging Adaptation Approaches for Climate-Ready Fisheries Management

“…Balance harvest across multiple subpopulations in Bristol Bay (Hilborn et al, 2003) Use stock assessments with temporally variable productivity Increased complexity of assessment models (Dorner et al, 2009) Declining productivity in northern Alaska salmon (Collie et al, 2012) Multidecadal oscillations and directional anthropogenic climate change…”

“…Model-free forecasting methods that account for nonlinear population dynamics and physical forcing from climate may also hold promise for shortterm forecasts for one or a couple years ahead (Deyle et al, 2013). The additional sources of bias and uncertainty in more complex statistical methods appear to limit their practical utility at the moment (Dorner et al, 2009;Glaser et al, 2013). Part of the challenge is to separate the effects of climate from those of fishing because both are often operating at the same time (Haltuch and Punt, 2011).…”

Consideration of uncertainties in environmental science and management with examples from Pacific salmon

“…As well, a Management Strategy Evaluation (MSE) is needed to evaluate management options using a set of alternative but plausible system models (not just "the best" single model or the one "new and improved" model) to represent uncertainties in our understanding of the system's underlying dynamic processes. Other types of uncertainty, such as 8 those that cause deviations between management targets and actual outcomes, could mask or swamp any improvement garnered from a better system model, as was found, for example, in a MSE that included alternative models for sockeye salmon (Oncorhynchus nerka) populations (Dorner, Peterman & Su, 2009). …”