Unseen overlap between fishing vessels and top predators in the northeast Pacific.

Accurate assessments of human-wildlife risk associated with industrial fishing are critical for the conservation of marine top predators. Automatic Identification System (AIS) data provide a means of mapping fishing and estimating human-wildlife risk; however, risk can be obscured by gaps in the AIS record due to technical issues and intentional disabling. We assessed the extent to which unseen fishing vessel activity due to AIS gaps obscured estimates of overlap between fishing vessel activity and 14 marine predators including sharks, tunas, mammals, seabirds, and critically endangered leatherback turtles. Among vessels equipped with AIS in the northeast Pacific, up to 24% of total predator overlap with fishing vessel activity was unseen, and up to 36% was unseen for some individual species. Waters near 10°N had high unseen overlap with sharks yet low reported shark catch, revealing potential discrepancies in self-reported datasets. Accounting for unseen fishing vessel activity illuminates hidden human-wildlife risk, demonstrating challenges and solutions for transparent and sustainable marine fisheries.

Satellite mapping reveals extensive industrial activity at sea.

The world's population increasingly relies on the ocean for food, energy production and global trade1-3, yet human activities at sea are not well quantified4,5. We combine satellite imagery, vessel GPS data and deep-learning models to map industrial vessel activities and offshore energy infrastructure across the world's coastal waters from 2017 to 2021. We find that 72-76% of the world's industrial fishing vessels are not publicly tracked, with much of that fishing taking place around South Asia, Southeast Asia and Africa. We also find that 21-30% of transport and energy vessel activity is missing from public tracking systems. Globally, fishing decreased by 12 ± 1% at the onset of the COVID-19 pandemic in 2020 and had not recovered to pre-pandemic levels by 2021. By contrast, transport and energy vessel activities were relatively unaffected during the same period. Offshore wind is growing rapidly, with most wind turbines confined to small areas of the ocean but surpassing the number of oil structures in 2021. Our map of ocean industrialization reveals changes in some of the most extensive and economically important human activities at sea.

Fishing through the cracks: The unregulated nature of global squid fisheries.

While most research has focused on the legality of global industrial fishing, unregulated fishing has largely escaped scrutiny. Here, we evaluate the unregulated nature of global squid fisheries using AIS data and nighttime imagery of the globalized fleet of light-luring squid vessels. We find that this fishery is extensive, fishing 149,000 to 251,000 vessel days annually, and that effort increased 68% over the study period 2017-2020. Most vessels are highly mobile and fish in multiple regions, largely (86%) in unregulated areas. While scientists and policymakers express concerns over the declining abundance of squid stocks globally and regionally, we find a net increase in vessels fishing squid globally and spatial expansion of effort to novel areas. Since fishing effort is static in areas with increasing management, and rising in unmanaged areas, we suggest actors may take advantage of fragmented regulations to maximize resource extraction. Our findings highlight a profitable, but largely unregulated fishery, with strong potential for improved management.

Tracking elusive and shifting identities of the global fishing fleet.

Illegal, unreported, and unregulated (IUU) fishing costs billions of dollars per year and is enabled by vessels obfuscating their identity. Here, we combine identities of ~35,000 vessels with a decade of GPS data to provide a global assessment of fishing compliance, reflagging patterns, and fishing by foreign-owned vessels. About 17% of high seas fishing is by potentially unauthorized or internationally unregulated vessels, with hot spots of this activity in the west Indian and the southwest Atlantic Oceans. In addition, reflagging, a tactic often used to obscure oversight, occurs in just a few ports primarily by fleets with high foreign ownership. Fishing by foreign-owned vessels is concentrated in parts of high seas and certain national waters, often flying flags of convenience. These findings can address the global scope of potential IUU fishing and enable authorities to improve oversight.

Revealing the global longline fleet with satellite radar.

Because many vessels use the Automatic Identification System (AIS) to broadcast GPS positions, recent advances in satellite technology have enabled us to map global fishing activity. Understanding of human activity at sea, however, is limited because an unknown number of vessels do not broadcast AIS. Those vessels can be detected by satellite-based Synthetic Aperture Radar (SAR) imagery, but this technology has not yet been deployed at scale to estimate the size of fleets in the open ocean. Here we combine SAR and AIS for large-scale open ocean monitoring, developing methods to match vessels with AIS to vessels detected with SAR and estimate the number of non-broadcasting vessels. We reveal that, between September 2019 and January 2020, non-broadcasting vessels accounted for about 35% of the longline activity north of Madagascar and 10% of activity near French Polynesia and Kiribati's Line Islands. We further demonstrate that this method could monitor half of the global longline activity with about 70 SAR images per week, allowing us to track human activity across the oceans.

Hot spots of unseen fishing vessels.

Illegal, unreported, and unregulated (IUU) fishing incurs an annual cost of up to US$25 billion in economic losses, results in substantial losses of aquatic life, and has been linked to human rights violations. Vessel tracking data from the automatic identification system (AIS) are powerful tools for combating IUU, yet AIS transponders can be disabled, reducing its efficacy as a surveillance tool. We present a global dataset of AIS disabling in commercial fisheries, which obscures up to 6% (>4.9 M hours) of vessel activity. Disabling hot spots were located near the exclusive economic zones (EEZs) of Argentina and West African nations and in the Northwest Pacific, all regions of IUU concern. Disabling was highest near transshipment hot spots and near EEZ boundaries, particularly contested ones. We also found links between disabling and location hiding from competitors and pirates. These inferences on where and why activities are obscured provide valuable information to improve fisheries management.

Satellites can reveal global extent of forced labor in the world's fishing fleet.

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.

Illuminating dark fishing fleets in North Korea.

Illegal, unreported, and unregulated fishing threatens resource sustainability and equity. A major challenge with such activity is that most fishing vessels do not broadcast their positions and are "dark" in public monitoring systems. Combining four satellite technologies, we identify widespread illegal fishing by dark fleets in the waters between the Koreas, Japan, and Russia. We find >900 vessels of Chinese origin in 2017 and >700 in 2018 fished illegally in North Korean waters, catching an estimated amount of Todarodes pacificus approximating that of Japan and South Korea combined (>164,000 metric tons worth >$440 million). We further find ~3000 small-scale North Korean vessels fished, mostly illegally, in Russian waters. These results can inform independent oversight of transboundary fisheries and foreshadow a new era in satellite monitoring of fisheries.

Seasonal variability in global industrial fishing effort.

Human beings are the dominant top predator in the marine ecosystem. Throughout most of the global ocean this predation is carried out by industrial fishing vessels, that can now be observed in unprecedented detail via satellite monitoring of Automatic Identification System (AIS) messages. The spatial and temporal distribution of this fishing effort emerges from the coupled interaction of ecological and socio-economic drivers and can therefore yield insights on the dynamics of both the ecosystem and fishers. Here we analyze temporal variability of industrial fishing effort from 2015-2017 as recorded by global AIS coverage, and differentiated by fishing gear type. The strongest seasonal signal is a reduction of total deployed effort during the annual fishing moratorium on the numerically-dominant Chinese fleet, which occurs during boreal summer. An additional societally-controlled reduction of effort occurs during boreal winter holidays. After accounting for these societal controls, the total deployed effort is relatively invariant throughout the year for all gear types except squid jiggers and coastal purse seiners. Despite constant deployment levels, strong seasonal variability occurs in the spatial pattern of fishing effort for gears targeting motile pelagic species, including purse seiners, squid jiggers and longliners. Trawlers and fixed gears target bottom-associated coastal prey and show very little overall seasonality, although they exhibit more seasonal variation at locations that are further from port. Our results suggest that societal controls dominate the total deployment of fishing effort, while the behavior of pelagic fish, including seasonal migration and aggregation, is likely the most prominent driver of the spatial seasonal variations in global fishing effort.

Predicted hotspots of overlap between highly migratory fishes and industrial fishing fleets in the northeast Pacific.

Many species of sharks and some tunas are threatened by overexploitation, yet the degree of overlap between industrial fisheries and pelagic fishes remains poorly understood. Using satellite tracks from 933 industrial fishing vessels and predictive habitat models from 876 electronic tags deployed on seven shark and tuna species, we developed fishing effort maps across the northeast Pacific Ocean and assessed overlap with core habitats of pelagic fishes. Up to 35% of species' core habitats overlapped with fishing effort. We identified overlap hotspots along the North American shelf, the equatorial Pacific, and the subtropical gyre. Results indicate where species require international conservation efforts and effective management within national waters. Only five national fleets (Mexico, Taiwan, China, Japan, and the United States) account for >90% of overlap with core habitats of our focal sharks and tunas on the high seas. These results inform global negotiations to achieve sustainability on the high seas.

Wealthy countries dominate industrial fishing.

The patterns by which different nations share global fisheries influence outcomes for food security, trajectories of economic development, and competition between industrial and small-scale fishing. We report patterns of industrial fishing effort for vessels flagged to higher- and lower-income nations, in marine areas within and beyond national jurisdiction, using analyses of high-resolution fishing vessel activity data. These analyses reveal global dominance of industrial fishing by wealthy nations. Vessels flagged to higher-income nations, for example, are responsible for 97% of the trackable industrial fishing on the high seas and 78% of such effort within the national waters of lower-income countries. These publicly accessible vessel tracking data have important limitations. However, insights from these new analyses can begin to strategically inform important international- and national-level efforts underway now to ensure equitable and sustainable sharing of fisheries.

Detecting suspicious activities at sea based on anomalies in Automatic Identification Systems transmissions.

Automatic Identification Systems (AIS) are a standard feature of ocean-going vessels, designed to allow vessels to notify each other of their position and route, to reduce collisions. Increasingly, the system is being used to monitor vessels remotely, particularly with the advent of satellite receivers. One fundamental problem with AIS transmission is the issue of gaps in transmissions. Gaps occur for three basic reasons: 1) saturation of the system in locations with high vessel density; 2) poor quality transmissions due to equipment on the vessel or receiver; and 3) intentional disabling of AIS transmitters. Resolving which of these mechanisms is responsible for generating gaps in transmissions from a given vessel is a critical task in using AIS to remotely monitor vessels. Moreover, separating saturation and equipment issues from intentional disabling is a key issue, as intentional disabling is a useful risk factor in predicting illicit behaviors such as illegal fishing. We describe a spatial statistical model developed to identify gaps in AIS transmission, which allows calculation of the probability that a given gap is due to intentional disabling. The model we developed successfully identifies high risk gaps in the test case example in the Arafura Sea. Simulations support that the model is sensitive to frequent gaps as short as one hour. Results in this case study area indicate expected high risk vessels were ranked highly for risk of intentional disabling of AIS transmitters. We discuss our findings in the context of improving enforcement opportunities to reduce illicit activities at sea.

Response to Comment on "Tracking the global footprint of fisheries".

Amoroso et al demonstrate the power of our data by estimating the high-resolution trawling footprint on seafloor habitat. Yet we argue that a coarser grid is required to understand full ecosystem impacts. Vessel tracking data allow us to estimate the footprint of human activities across a variety of scales, and the proper scale depends on the specific impact being investigated.

Mapping the yearly extent of surface coal mining in Central Appalachia using Landsat and Google Earth Engine.

Surface mining for coal has taken place in the Central Appalachian region of the United States for well over a century, with a notable increase since the 1970s. Researchers have quantified the ecosystem and health impacts stemming from mining, relying in part on a geospatial dataset defining surface mining's extent at a decadal interval. This dataset, however, does not deliver the temporal resolution necessary to support research that could establish causal links between mining activity and environmental or public health and safety outcomes, nor has it been updated since 2005. Here we use Google Earth Engine and Landsat imagery to map the yearly extent of surface coal mining in Central Appalachia from 1985 through 2015, making our processing models and output data publicly available. We find that 2,900 km2 of land has been newly mined over this 31-year period. Adding this more-recent mining to surface mines constructed prior to 1985, we calculate a cumulative mining footprint of 5,900 km2. Over the study period, correlating active mine area with historical surface mine coal production shows that each metric ton of coal is associated with 12 m2 of actively mined land. Our automated, open-source model can be regularly updated as new surface mining occurs in the region and can be refined to capture mining reclamation activity into the future. We freely and openly offer the data for use in a range of environmental, health, and economic studies; moreover, we demonstrate the capability of using tools like Earth Engine to analyze years of remotely sensed imagery over spatially large areas to quantify land use change.

The economics of fishing the high seas.

While the ecological impacts of fishing the waters beyond national jurisdiction (the "high seas") have been widely studied, the economic rationale is more difficult to ascertain because of scarce data on the costs and revenues of the fleets that fish there. Newly compiled satellite data and machine learning now allow us to track individual fishing vessels on the high seas in near real time. These technological advances help us quantify high-seas fishing effort, costs, and benefits, and assess whether, where, and when high-seas fishing makes economic sense. We characterize the global high-seas fishing fleet and report the economic benefits of fishing the high seas globally, nationally, and at the scale of individual fleets. Our results suggest that fishing at the current scale is enabled by large government subsidies, without which as much as 54% of the present high-seas fishing grounds would be unprofitable at current fishing rates. The patterns of fishing profitability vary widely between countries, types of fishing, and distance to port. Deep-sea bottom trawling often produces net economic benefits only thanks to subsidies, and much fishing by the world's largest fishing fleets would largely be unprofitable without subsidies and low labor costs. These results support recent calls for subsidy and fishery management reforms on the high seas.

Tracking the global footprint of fisheries.

Although fishing is one of the most widespread activities by which humans harvest natural resources, its global footprint is poorly understood and has never been directly quantified. We processed 22 billion automatic identification system messages and tracked >70,000 industrial fishing vessels from 2012 to 2016, creating a global dynamic footprint of fishing effort with spatial and temporal resolution two to three orders of magnitude higher than for previous data sets. Our data show that industrial fishing occurs in >55% of ocean area and has a spatial extent more than four times that of agriculture. We find that global patterns of fishing have surprisingly low sensitivity to short-term economic and environmental variation and a strong response to cultural and political events such as holidays and closures.

Carbon sequestration in California agriculture, 1980-2000.

To better understand agricultural carbon fluxes in California, USA, we estimated changes in soil carbon and woody material between 1980 and 2000 on 3.6 x 10(6) ha of farmland in California. Combining the CASA (Carnegie-Ames-Stanford Approach) model with data on harvest indices and yields, we calculated net primary production, woody production in orchard and vineyard crops, and soil carbon. Over the 21-yr period, two trends resulted in carbon sequestration. Yields increased an average of 20%, corresponding to greater plant biomass and more carbon returned to the soils. Also, orchards and vineyards increased in area from 0.7 x 10(6) ha to 1.0 x 10(6) ha, displacing field crops and sequestering woody carbon. Our model estimates that California's agriculture sequestered an average of 19 g C x m(-2) x yr(-1). Sequestration was lowest in non-rice annual cropland, which sequestered 9 g C x m(-2) x yr(-1) of soil carbon, and highest on land that switched from annual cropland to perennial cropland. Land that switched from annual crops to vineyards sequestered 68 g C x m(-2) x yr(-1), and land that switched from annual crops to orchards sequestered 85 g C x m(-2) x yr(-1). Rice fields, because of a reduction in field burning, sequestered 55 g C x m(-2) x yr(-1) in the 1990s. Over the 21 years, California's 3.6 x 10(6) ha of agricultural land sequestered 11.0 Tg C within soils and 3.5 Tg C in woody biomass, for a total of 14.5 Tg C statewide. This is equal to 0.7% of the state's total fossil fuel emissions over the same time period. If California's agriculture adopted conservation tillage, changed management of almond and walnut prunings, and used all of its orchard and vineyard waste wood in the biomass power plants in the state, California's agriculture could offset up to 1.6% of the fossil fuel emissions in the state.