Revenue loss due to whale entanglement mitigation and fishery closures

Modeling the spatiotemporal patterns and drivers of Dungeness crab fishing effort to inform whale entanglement risk mitigation on the U.S. West Coast

Understanding and characterizing the spatiotemporal dynamics of fishing fleets is crucial for ecosystem-based fisheries management (EBFM). EBFM must not only account for the sustainability of target species catches, but also for the collateral impacts of fishing operations on habitats and non-target species. Increased rates of large whale entanglements in commercial Dungeness crab fishing gear have made reducing whale-fishery interactions a current and pressing challenge on the U.S. West Coast. While several habitat models exist for different large whale species along the West Coast, less is known about the crab fishery and the degree to which different factors influence the intensity and distribution of aggregate fishing effort. Here, we modeled the spatiotemporal patterns of Dungeness crab fishing effort in Oregon and Washington as a function of environmental, economic, temporal, social, and management related predictor variables using generalized linear mixed effects models. We then assessed the predictive performance of such models and discussed their usefulness in informing fishery management. Our models revealed low between-year variability and consistent spatial and temporal patterns in commercial Dungeness crab fishing effort. However, fishing effort was also responsive to multiple environmental, economic and management cues, which influenced the baseline effort distribution pattern. The best predictive model, chosen through out-of-sample cross-validation, showed moderate predictive performance and relied upon environmental, economic, and social covariates. Our results help fill the current knowledge gap around Dungeness crab fleet dynamics, and support growing calls to integrate fisheries behavioral data into fisheries management and marine spatial planning.

Ecological forecasts for marine resource management during climate extremes

Forecasting weather has become commonplace, but as society faces novel and uncertain environmental conditions there is a critical need to forecast ecology. Forewarning of ecosystem conditions during climate extremes can support proactive decision-making, yet applications of ecological forecasts are still limited. We showcase the capacity for existing marine management tools to transition to a forecasting configuration and provide skilful ecological forecasts up to 12 months in advance. The management tools use ocean temperature anomalies to help mitigate whale entanglements and sea turtle bycatch, and we show that forecasts can forewarn of human-wildlife interactions caused by unprecedented climate extremes. We further show that regionally downscaled forecasts are not a necessity for ecological forecasting and can be less skilful than global forecasts if they have fewer ensemble members. Our results highlight capacity for ecological forecasts to be explored for regions without the infrastructure or capacity to regionally downscale, ultimately helping to improve marine resource management and climate adaptation globally.