Seasonal and interannual variation in spatio-temporal models for index standardization and phenology studies

Climate change is rapidly affecting the seasonal timing of spatial demographic processes. Consequently, resource managers require information from models that simultaneously measure seasonal, interannual, and spatial variation. We present a spatio-temporal model that includes annual, seasonal, and spatial variation in density and then highlight two important uses: (i) standardizing data that are spatially unbalanced within multiple seasons and (ii) identifying interannual changes in seasonal timing (phenology) of population processes. We demonstrate these uses with two contrasting case studies: three bottom trawl surveys for yellowtail flounder (Limanda ferruginea) in the Northwest Atlantic Ocean from 1985 to 2017 and pelagic tows for copepodite stage 3+ copepod (Calanus glacialis/marshallae) densities in the eastern Bering Sea from 1993 to 2016. The yellowtail analysis illustrates how data from multiple surveys can be used to infer density hot spots in an area that is not sampled one or more surveys. The copepod analysis assimilates seasonally unbalanced samples to estimate an annual index of the seasonal timing of copepod abundance and identifies a positive correlation between this index and cold-pool extent. We conclude by discussing additional potential uses of seasonal spatio-temporal models and emphasize their ability to identify climate-driven shifts in the seasonal timing of fish movement and ecosystem productivity.

In what direction should the fishing mortality target change when natural mortality increases within an assessment?

Traditionally, the natural mortality rate (M) in a stock assessment is assumed to be constant. When M increases within an assessment, the question arises how to change the fishing mortality rate target (FTarget). Per recruit considerations lead to an increase in FTarget, while limiting total mortality leads to a decrease in FTarget. Application of either approach can result in nonsensical results. Short-term gains in yield associated with high FTarget values should be considered in light of potential losses in future yield if the high total mortality rate leads to a decrease in recruitment. Examples using yellowtail flounder (Limanda ferruginea) and Atlantic cod (Gadus morhua) are used to demonstrate that FTarget can change when M increases within an assessment and to illustrate the consequences of different FTarget values. When a change in M within an assessment is contemplated, first consider the amount and strength of empirical evidence to support the change. When the empirical evidence is not strong, we recommend using a constant M. If strong empirical evidence exists, we recommend estimating FTarget for a range of stock–recruitment relationships and evaluating the trade-offs between risk of overfishing and forgone yield.

Testing the performance of a spatially explicit tag-integrated stock assessment model of yellowtail flounder (Limanda ferruginea) through simulation analysis

In any stock assessment application, the implicit assumptions regarding spatial population structure must be carefully evaluated. Tag-integrated models offer a promising approach for incorporating spatial structure and movement patterns in stock assessments, but the complexity of the framework makes implementation challenging and the appraisal of performance difficult. A flounder-like fishery was simulated to emulate the metapopulation dynamics of the three yellowtail flounder (Limanda ferruginea) stocks off New England, and the robustness of spatially explicit tag-integrated models were compared with closed population assessments. Different movement parametrizations and data uncertainty scenarios were simulated, while the ability of the tag-integrated model to estimate reporting rate and time-varying movement were also evaluated. Results indicated that the tag-integrated framework was robust for the simulated fishery across a wide range of connectivity levels and that tag reporting rates were accurately estimated. Closed population models also demonstrated limited error. Therefore, spatially explicit approaches may not always be warranted even when regional connectivity is occurring, but tag-integrated models can provide improved parameter estimates when reliable tagging data are available. Tag-integrated models also serve as valuable tools for informing spatially explicit operating models, which can then be used to evaluate the assumptions and performance of closed population models.

Demonstration of a spatially explicit, tag-integrated stock assessment model with application to three interconnected stocks of yellowtail flounder off of New England

Ignoring population structure and connectivity in stock assessment models can introduce bias into important management metrics. Tag-integrated assessment models can account for spatially explicit population dynamics by modelling multiple population components, each with unique demographics, and estimating movement among them. A tagging submodel is included to calculate predicted tag recaptures, and observed tagging data are incorporated in the objective function to inform estimates of movement and mortality. We describe the tag-integrated assessment framework and demonstrate its use through an application to three stocks of yellowtail flounder (Limanda ferruginea) off New England. Movement among the three yellowtail flounder stocks has been proposed as a potential source of uncertainty in the closed population assessments of each. A tagging study was conducted during 2003–2006 with over 45 000 tagged fish released in the region, and the tagging data were included in the tag-integrated model. Results indicated that movement among stocks was low, estimates of stock size and fishing mortality were similar to those from conventional stock assessments, and incorporating stock connectivity did not resolve residual patterns. Despite low movement estimates, new interpretations of regional stock dynamics may have important implications for regional fisheries management given the source-sink nature of movement estimates.