Over the past two decades, sharks have been increasingly recognized among the world’s most threatened wildlife and hence have received heightened scientific and regulatory scrutiny. Yet, the effect of protective regulations on shark fishing mortality has not been evaluated at a global scale. Here we estimate that total fishing mortality increased from at least 76 to 80 million sharks between 2012 and 2019, ~25 million of which were threatened species. Mortality increased by 4% in coastal waters but decreased by 7% in pelagic fisheries, especially across the Atlantic and Western Pacific. By linking fishing mortality data to the global regulatory landscape, we show that widespread legislation designed to prevent shark finning did not reduce mortality but that regional shark fishing or retention bans had some success. These analyses, combined with expert interviews, highlight evidence-based solutions to reverse the continued overexploitation of sharks.

Globally, one quarter of shark and ray species are threatened with extinction due to overfishing. Effective conservation and management can facilitate population recoveries. However, these efforts depend on robust data on movement patterns and stock structure, which are lacking for many threatened species, including the Critically Endangered soupfin shark Galeorhinus galeus, a circumglobal coastal‐pelagic species. Using passive acoustic telemetry, we continuously tracked 34 mature female soupfin sharks, surgically implanted with coded acoustic transmitters, for 7 years via 337 underwater acoustic receivers stationed along the west coast of North America. These sharks and an additional six were also externally fitted with spaghetti identification tags. Our tagging site was a shallow rocky reef off La Jolla (San Diego County), California, USA, where adult females were observed to aggregate every summer. Tagged soupfin sharks were highly migratory along the west coast of North America, between Washington, USA and Baja California Sur, Mexico. However, every 3 years, they returned to waters off La Jolla, California, where they underwent gestation. This is the first conclusive evidence of triennial migration and philopatry (‘home‐loving’) in any animal, which is apparently driven by this species’ unusual triennial reproductive cycle. Females of other shark and ray species with triennial reproductive cycles are also likely to exhibit triennial cycles of migration and philopatry. At least six (15%) of our tagged soupfin sharks were killed in commercial gillnets in Mexico. Policy implications. Identifying multiennial migratory cycles in mature female sharks can reveal hidden stock structure in the form of discrete breeding cohorts, which are spatially and temporally segregated as they cycle through different reproductive phases. Accounting for this complexity may improve the performance of spatially structured stock assessment models, particularly when fishery removals are spatially heterogeneous, as well as inform the spatiotemporal design of fishery‐independent surveys. In the United States, the soupfin shark is neither actively managed nor recognized as a Highly Migratory Species; however, given the highly migratory behaviour we report, this designation should be revisited by the US Pacific Fishery Management Council. Finally, given the extensive fishery removals in Mexico, any future management must be internationally cooperative.

Sharks are susceptible to industrial longline fishing due to their slow life histories and association with targeted tuna stocks. Identifying fished areas with high shark interaction risk is vital to protect threatened species. We harmonize shark catch records from global tuna Regional Fisheries Management Organizations (tRFMOs) from 2012–2020 and use machine learning to identify where sharks are most threatened by longline fishing. We find shark catch risk hotspots in all ocean basins, with notable high-risk areas off Southwest Africa and in the Eastern Tropical Pacific. These patterns are mostly driven by more common species such as blue sharks, though risk areas for less common, Endangered and Critically Endangered species are also identified. Clear spatial patterns of shark fishing risk identified here can be leveraged to develop spatial management strategies for threatened populations. Our results also highlight the need for coordination in data collection and dissemination by tRFMOs for effective shark management.

Widespread degradation of marine ecosystems and ecosystem services, coupled with national and global commitments to improve protection of the oceans, has led to a proliferation of efforts to designate new marine protected areas (MPAs) and MPA networks. A range of design features must be considered when designating MPAs, including MPA size and shape, level of protection, and the species and habitats protected, and evidence suggests these design elements can be crucial in determining MPA effectiveness. Over the past several decades, expansive literature has emerged providing recommendations for MPA design, and yet collectively these recommendations can be overwhelming and even contradictory for MPA planners. To address this barrier, we reviewed and synthesized 307 unique MPA design recommendations across 56 peer‐reviewed and gray literature publications. We created a new set of 24 condensed design guidelines grouped by conservation objectives: ecological spatial connectivity (e.g., genetic, larval, community); habitat representation; species or population persistence; mitigation of and complementarity to human activities; and permanence and adaptability. We then discuss examples of datasets, models, and tools that can be utilized to implement specific guidelines. Our review and novel synthesis can help decision‐makers understand and apply MPA design recommendations to achieve desired conservation objectives.

Contaminant Exposure Models (CEMs) were developed to predict population-level tissue contaminant concentrations in fishes by pairing sediment-bound contaminant concentrations (DDTs, PCBs) and fine-scale acoustic telemetry data from a habitat-associated species (Vermilion Rockfish, Sebastes miniatus), nomadic flatfish species (Hornyhead Turbot, Pleuronichthys verticalis), and nomadic benthic/midwater schooling species (White Croaker, Genyonemus lineatus) tagged near wastewater outfalls in southern California. Model results were compared to contaminant concentrations in tissue samples. The CEMs developed require further refinement before implementation into management efforts but may act as steppingstones to help shift primary monitoring methods away from the regular field collection of fish for tissue contaminant analyses and towards behavioral modeling and habitat mapping. We also developed Kernel Density Estimates that can be used by managers immediately to identify regions that contribute most to contaminant exposure in species of concern. Prioritizing remediation efforts in these areas are likely to be most effective at improving fish health.

Maps and spatial models inform natural resource management and policy decisions. However, the geospatial data needed for these decisions are often scattered across websites and services, and typically require technical skills to download, process and analyze. The R programming language is widely used in environmental science, and while there are some R packages available for obtaining terrestrial geospatial data, those for marine data are limited to specific datasets. To fill this gap, we introduce the oceandatr R package, an interface that provides streamlined access to a suite of global ocean data. It provides functions for acquiring and processing many data sources—including bathymetry, geomorphology, ecological, and human use data—and returns these in several grid‐based formats. The gridded output data can be used directly in modeling, spatial analysis and spatial planning. While oceandatr accesses marine data, the functions for retrieving boundaries and gridding data can also be used in other contexts. We outline uses of oceandatr and present two case studies where we use oceandatr to access and process data for a spatial planning application and a spatial model of fishing effort. Oceandatr simplifies the process of geospatial analysis for marine researchers and spatial planners, reducing technical barriers and supporting evidence‐based decision making.