The expansion of marine protected areas (MPAs) is a core focus of global conservation efforts, with the 30x30 initiative to protect 30% of the ocean by 2030 serving as a prominent example of this trend. We consider a series of proposed MPA network expansions of various sizes, and we forecast the impact this increase in protection would have on global patterns of fishing effort. We do so by building a predictive machine learning model trained on a global dataset of satellite-based fishing vessel monitoring data, current MPA locations, and spatiotemporal environmental, geographic, political, and economic features. We then use this model to predict future fishing effort under various MPA expansion scenarios compared to a business-as-usual counterfactual scenario that includes no new MPAs. The difference between these scenarios represents the predicted change in fishing effort associated with MPA expansion. We find that regardless of the MPA network objectives or size, fishing effort would decrease inside the MPAs, though by much less than 100%. Moreover, we find that the reduction in fishing effort inside MPAs does not simply redistribute outside-rather, fishing effort outside MPAs would also decline. The overall magnitude of the predicted decrease in global fishing effort principally depends on where networks are placed in relation to existing fishing effort. MPA expansion will lead to a global redistribution of fishing effort that should be accounted for in network design, implementation, and impact evaluation.

Climate change is driving shifts in the abundance and distribution of marine fish and invertebrates and is having direct and indirect impacts on seafood catches and fishing communities, exacerbating the already negative effects of unsustainably high fishing pressure that exist for some stocks. Although the majority of fisheries in the world are managed at the national or local scale, most existing approaches to assessing climate impacts on fisheries have been developed on a global scale. It is often difficult to translate from the global to regional and local settings because of limited relevant data. To address the need for fisheries management entities to identify those fisheries with the greatest potential for climate change impacts, we present an approach for estimating expected climate change-driven impacts on the productivity and spatial range of fisheries at the regional scale in a data-poor context. We use a set of representative Mexican fisheries as test cases. To assess the implications of climate impacts, we compare biomass, harvest, and profit outcomes from a bioeconomic model under contrasting management policies and with and without climate change. Overall results show that climate change is estimated to negatively affect nearly every fishery in our study. However, the results indicate that overfishing is a greater threat than climate change for these fisheries, hence fixing current management challenges has a greater upside than the projected future costs of moderate levels of climate change. Additionally, this study provides meaningful first approximations of potential effects of both climate change and management reform in Mexican fisheries. Using the climate impact estimations and model outputs, we identify high priority stocks, fleets, and regions for policy reform in Mexico in the face of climate change. This approach can be applied in other data-poor circumstances to focus future research and policy reform efforts on stocks now subject to additional stress due to climate change. Considering their growing relevance as a critical source of protein and micronutrients to nourish our growing population, it is urgent for regions to develop sound fishery management policies in the short-term as they are the most important intervention to mitigate the adverse effects of climate change on marine fisheries.

Climate change is driving shifts in the abundance and distribution of marine fish and invertebrates and is having direct and indirect impacts on seafood catches and fishing communities, exacerbating the already negative effects of unsustainably high fishing pressure that exist for some stocks. Although the majority of fisheries in the world are managed at the national or local scale, most existing approaches to assessing climate impacts on fisheries have been developed on a global scale. It is often difficult to translate from the global to regional and local settings because of limited relevant data. To address the need for fisheries management entities to identify those fisheries with the greatest potential for climate change impacts, we present an approach for estimating expected climate change-driven impacts on the productivity and spatial range of fisheries at the regional scale in a data-poor context. We use a set of representative Mexican fisheries as test cases. To assess the implications of climate impacts, we compare biomass, harvest, and profit outcomes from a bioeconomic model under contrasting management policies and with and without climate change. Overall results show that climate change is estimated to negatively affect nearly every fishery in our study. However, the results indicate that overfishing is a greater threat than climate change for these fisheries, hence fixing current management challenges has a greater upside than the projected future costs of moderate levels of climate change. Additionally, this study provides meaningful first approximations of potential effects of both climate change and management reform in Mexican fisheries. Using the climate impact estimations and model outputs, we identify high priority stocks, fleets, and regions for policy reform in Mexico in the face of climate change. This approach can be applied in other data-poor circumstances to focus future research and policy reform efforts on stocks now subject to additional stress due to climate change. Considering their growing relevance as a critical source of protein and micronutrients to nourish our growing population, it is urgent for regions to develop sound fishery management policies in the short-term as they are the most important intervention to mitigate the adverse effects of climate change on marine fisheries.

The worlds oceans supply food and livelihood to billions of people, yet species shifting geographic ranges and changes in productivity arising from climate change are expected to profoundly affect these benefits. We ask how improvements in fishery management can offset the negative consequences of climate change; we find that the answer hinges on the current status of stocks. The poor current status of many stocks combined with potentially maladaptive responses to range shifts could reduce future global fisheries yields and profits even more severely than previous estimates have suggested. However, reforming fisheries in ways that jointly fix current inefficiencies, adapt to fisheries productivity changes, and proactively create effective transboundary institutions could lead to a future with higher profits and yields compared to what is produced today.

While forced labor in the world's fishing fleet has been widely documented, its extent remains unknown. No methods previously existed for remotely identifying individual fishing vessels potentially engaged in these abuses on a global scale. By combining expertise from human rights practitioners and satellite vessel monitoring data, we show that vessels reported to use forced labor behave in systematically different ways from other vessels. We exploit this insight by using machine learning to identify high-risk vessels from among 16,000 industrial longliner, squid jigger, and trawler fishing vessels. Our model reveals that between 14% and 26% of vessels were high-risk, and also reveals patterns of where these vessels fished and which ports they visited. Between 57,000 and 100,000 individuals worked on these vessels, many of whom may have been forced labor victims. This information provides unprecedented opportunities for novel interventions to combat this humanitarian tragedy. More broadly, this research demonstrates a proof of concept for using remote sensing to detect forced labor abuses.

The world's oceans supply food and livelihood to billions of people, yet species' shifting geographic ranges and changes in productivity arising from climate change are expected to profoundly affect these benefits. We ask how improvements in fishery management can offset the negative consequences of climate change; we find that the answer hinges on the current status of stocks. The poor current status of many stocks combined with potentially maladaptive responses to range shifts could reduce future global fisheries yields and profits even more severely than previous estimates have suggested. However, reforming fisheries in ways that jointly fix current inefficiencies, adapt to fisheries productivity changes, and proactively create effective transboundary institutions could lead to a future with higher profits and yields compared to what is produced today.