Geology Reports⌕ Search

SEARCH · Geology Reports

Results for “Geological Society of London Special Publications”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

1,664 records · Page 59Linked to original sources
USGS2026

Thermal detectability of subsurface water ice on Mars: A comparative analysis for the Subsurface Water Ice Mapping (SWIM) Project

We have developed a new global map of shallow ground ice distribution, SWIM23, based on Mars Global Surveyor Thermal Emission Spectrometer data and made systematic comparisons between this new map and two similar, previously developed data products. We have explored the origin of differences between the three ice maps by detailing technical and procedural differences in their development, by making global pixel-by-pixel comparisons, and by carrying out a series of one-dimensional thermal simulations to explore fundamental physical limitations of thermal ice-detection techniques. These efforts and the production of a composite thermal ice-consistency map supported integration of multiple geophysical data products relevant to ice detection in the upper meter of the Martian regolith into the larger Mars Subsurface Water Ice Mapping project. Our work also highlights fundamental physical limitations to thermal ice detection as a technique, particularly the rapid fall-off in ice detection sensitivity at depths >30 cm, which produces maximum uncertainty in the presence and depth of ice within regions preferred for potential human landing sites. A future Mars orbiter mission designed to detect ice and support crewed landing site selection in the midlatitude region should give payload priority to an instrument capable of probing the 1–5 m depth range (i.e., a high-frequency radar), over a next-generation thermal spectrometer, which is unlikely to offer clarity on ice table depths or lateral continuity of the ice table in the locations of highest interest.

Planetary Science Journal↗
USGS2025

Fluid inclusion constraints on the geometry of the magmatic plumbing system beneath Mauna Loa – Part 2: Xenoliths

Mauna Loa volcano erupts crystal-poor material at its summit and more crystal-rich material on its rift zones. Some of the more olivine-rich lava flows contain xenoliths with diverse mineralogy, including cumulate harzburgites with high-Mg# orthopyroxenes and high-Fo olivines (both > 84). Previous experimental work and thermodynamic modelling has proposed that high-Mg# orthopyroxenes only crystallize from Mauna Loa melts at high pressures (> 6 kbar, > 20 km), leading to suggestions that there is a region of sub-Moho magma storage at Mauna Loa in addition to the geophysically imaged magma reservoir at 2–5 km depth below the summit. We use melt and fluid inclusion barometry combined with thermodynamic models to further investigate this suggestion. Fluid inclusion data from harzburgites and dunitic xenoliths yield storage depths remarkably similar to those found in non-xenolithic crystals from lavas and tephras, with a clear peak at ~ 2–3 km (below the summit). Depths from melt inclusions in these xenoliths overlap with fluid inclusion pressures, ruling out the possibility of fluid inclusion re-equilibration during a period of stalling in a shallower reservoir. We examine five different thermodynamic models and find that the minimum pressure of olivine-orthopyroxene co-saturation varies by ~ 4 kbar (~ 12 km). These models also fail to predict that orthopyroxene is stable in ~ 15–80% of compositionally relevant experimental charges which grew orthopyroxene. Overall, this shows that phase stability modelling is an unreliable method of determining magma storage depth at Mauna Loa. We suggest that model discrepancies reflect a lack of experimental constraints on orthopyroxene stability at > 1200 ℃ and 0.01–5 kbar. Based on the presence of large oikocrystic orthopyroxenes completely enclosing rounded olivine chadacrysts, we suggest that these harzburgitic xenoliths formed through the reaction of intruding melts with olivine mush piles within the Mauna Loa edifice at ~ 3 km depth below the summit, with no need for a deeper storage reservoir. The predominance of pre-eruptive shallow storage means that there is more chance of detecting reservoir destabilization with geophysical monitoring techniques compared to a scenario where melts are supplied from sub-Moho reservoirs.

Hawaii↗
USGS2026

Estimating the importance of floating surface material to the total phosphorus transport in Silver Creek, Wisconsin using Particle Image Velocimetry

Various techniques are used to estimate nutrient delivery in streams that combine flow and water-quality data. However, the transport of surface floating material is difficult to measure, and is therefore typically neglected when stream sampling and in the estimated nutrient delivery. Here, we describe an approach to estimate the amount of material (duckweed ( Lemna genus), filamentous algae, and other macrophyte fragments) and associated nutrients (in this case, phosphorus, P) transported on the surface of Silver Creek, Wisconsin, to determine if this material is an important transport mechanism and if historical P loads were underestimated. This approach includes estimating the transport of surface material using 10 s videos collected every 15 min from a downward-looking camera installed beneath a bridge. The average velocity of the surface material was first determined using Large-Scale Particle Image Velocimetry (LSPIV), which uses short videos to analyze surface particle movement. The amount of surface material in each video was then computed using computer-vision techniques. The P load associated with the transported surface material was then estimated by combining surface velocities, coverage of floating material, and laboratory-measured P content. Surface material transported ~9–11% of the total summer P load and ~4–7% of the annual load in Silver Creek.

Wisconsin↗
USGS2025

Relationship of basin structure and bedrock lithology to faulting in the 2019 Ridgecrest earthquake region, California, from gravity and aeromagnetic data

We investigate patterns of cumulative offsets on the faults that ruptured in 2019 and along the Garlock Fault in the Ridgecrest region, California using recently published gravity and aeromagnetic data. We also examine the relationship of basin structure and bedrock structure to the 2019 M7.1 Ridgecrest earthquake ruptures (Fig. 1A), which were primarily along a dextral northwest-striking fault system, and along a sinistral northeast-striking fault, which ruptured hours earlier with a M6.4 event.

California↗
USGS1984

Techniques for estimating magnitude and frequency of floods on streams in Indiana

Equations are presented for estimating the magnitude and frequency of floods at ungaged sites on unregulated and nonurban streams in Indiana. The equations were developed by multiple-regression, analysis of basin characteristics and peak-flow statistical data from 242 gaged locations in Indiana, Ohio, and Illinois. The State of Indiana was divided into seven areas on the basis of the regression analysis. A set of equations for estimating peak discharges with recurrence intervals of 2, IO, 25, 50, and 100 years was developed for each area. Significant basin characteristics in the equations are drainage area, channel length, channel slope, mean annual precipitation, storage, precipitation intensity, and a runoff coefficient. Standard errors of estimate for the equations range from 24 to 45 percent. Methods are also presented for estimating flood magnitude and frequency at sites on gaged streams. Flood-frequency data based on observed peaks are given for 270 gaged locations. Twenty of these are on regulated streams, and six are on urban streams. Basin characteristics are also included car 245 of the gaged locations on unregulated and nonurban streams. No techniques are given for estimating flood magnitude and frequency at ungaged sites on regulated or urban streams. A rainfall-runoff model was tlsed to synthesize long-term peak data at 11 gaged locations on small streams. Flood-frequency curves developed from the long-term synthetic data were combined with curves based on short-term observed data to provide weighted estimates of flood magnitude and frequency at the rainfall-runoff stations.

Indiana↗
USGS2024

Predicted exposure of communities in southeastern United States to climate-related coastal hazards

A rigorous analysis of 21st Century multi-hazard exposure for U.S. Southeast Atlantic coastal communities indicates that up to 70% of residents will be exposed daily to shallow and emerging groundwater by ~2100, 15 times higher than from surficial flooding alone. This threat further exacerbates other coastal stressors, such as flooding, subsidence, and beach erosion, that impact these vulnerable coastal communities and ecosystems under expected future climate change scenarios.

Florida, Georgia, North Carolina, South Carolina, ↗
USGS2025

Component identification of solid biomass fuels using reflected light microscopy: Interlaboratory study 2

As nations transition toward sustainable energy systems , biomass has become a vital component of global energy portfolios. Derived from organic materials such as wood, agricultural residues, forestry byproducts, and organic waste, biomass is a renewable energy source with significant environmental and economic benefits. Responsible biomass energy production can improve waste management, reduce emissions of greenhouse gases, and mitigate environmental pollution. However, as the diversity of biomass-derived fuels increases, robust quality assessment methods are essential to ensure their efficiency, safety, and minimal environmental impact. Reflected light microscopy (RLM) is one such technique with the potential to complement conventional physico-chemical analyses by enabling a rapid identification of material constituents and impurities. To refine this methodology and evaluate the reproducibility of solid biomass component identification using RLM, an interlaboratory study (ILS) was conducted. The study involved the recognition of 58 components across 45 photomicrographs, with the participation of 65 scientists and students from 25 countries. The participants faced high difficulty identifying some of the marked components, and as a result, the percentage of correct answers ranged from 19.0 % to 98.3 %, with an average correct identification rate of 62.7 %. The most challenging aspects of the identification process included distinguishing between woody and non-woody (agro) biomass, accurately identifying petroleum-derived materials, and differentiating agro biomass from inorganic matter. The results suggest that while RLM is an important tool for characterizing solid biomass, further development of methodology guidelines and training are necessary to enhance its effectiveness. Future research should prioritize preparing detailed, image-rich, microscopic morphological descriptions of biomass fuel components, which could improve the accuracy and reliability of using RLM in biomass fuel characterization.

International Journal of Coal Geology↗
USGS2026

Chronic exposure to waterborne nickel significantly reduced growth of juvenile crayfish (Faxonius virilis)

Crayfish are critical functional components of aquatic ecosystems. Previous research has documented adverse effects of mineral extraction on crayfish. Here, we characterize potential risks of mining-derived waterborne nickel (Ni) to crayfish by documenting the effects of dissolved Ni on growth and food consumption of juvenile virile crayfish ( Faxonius virilis) in a 28-day chronic laboratory exposure. Nominal Ni concentrations ranged from 31.25 to 500 micrograms per liter (µg/L; pH = 7.96 ± 0.20, hardness = 150 ± 1 milligrams per liter as calcium carbonate). Crayfish survival, carapace length, and wet weight were measured. After 28 days of exposure, a 24-h feeding trial was performed to determine differences in food consumption. During the growth trial, 99% of crayfish survived. Change in wet weight and final wet weight were the most sensitive endpoints, with 20% effect concentrations of 24.8 and 22.6 µg/L Ni, respectively. Crayfish exposed to an average of 438 µg/L Ni consumed 41% less, and weighed 65.1% less, than control crayfish. These results suggest chronic, sublethal exposure to waterborne Ni may have negative effects on crayfish growth. Reduced growth and consumption rates in crayfish could have wide-ranging consequences throughout aquatic ecosystems since crayfish are consumers, prey, keystone trophic regulators, and ecosystem engineers. Finally, these results could inform bioenergetics and may be coupled with population models to predict potential changes in population sizes of native and invasive crayfishes.

Ecotoxicology↗
USGS2024

Distribution of ancient carbon in groundwater and soil gas from degradation of petroleum near the Red Hill Bulk Fuel Storage Facility, O‘ahu, Hawai‘i

The groundwater below the Red Hill Bulk Fuel Storage Facility (the facility) in Oʻahu, Hawaiʻi, contains fuel compounds from past spills. This study used carbon-14 analyses to distinguish fuel-derived carbon from background carbon, along with other biodegradation indicators, to address two goals: (1) determine the extent and migration direction of groundwater affected by residual fuel below the facility and (2) determine if residual fuel locations in the subsurface could be identified by analyzing soil gas at the surface above the facility. Groundwater from 19 wells was sampled between September 2022 and April 2023. Nonvolatile dissolved organic carbon (NVDOC) from a well presumed to be unaffected by past spills contained 38 percent ancient carbon indicating a natural source of ancient carbon in the subsurface. The NVDOC concentrations and ancient carbon percentages indicate fuel biodegradation products are likely present on the north and south of Red Hill with the greatest effects at well RHMW02 near the 2014 spill site. The NVDOC concentrations are almost three times higher than diesel range organic (DRO) concentrations in groundwater from the same sites. Major ion data indicate that iron reduction is an important biodegradation process. Soil probe samples and soil carbon traps were used to determine the carbon-14 content of soil carbon dioxide. Ancient carbon from fuel biodegradation was not detected at any soil probe or carbon trap site in contrast to a 2017 study which reported ancient carbon detections. A reanalysis of the 2017 results using a range of local values for background carbon-14 indicates that ancient carbon from fuel biodegradation was probably only detected in lower tunnel exhaust system samples and not in any soil carbon trap samples. Measurements of carbon dioxide efflux with a dynamic closed chamber were highly variable. The soil gas results indicate that soil gas measurements at land surface were not useful for detecting residual fuel at the facility.

Hawaii↗
USGS2026

Morphodynamics of snow barchans at Concordia Station, Antarctica

Barchans are crescent-shaped dunes that form and migrate under unimodal wind regimes in areas of low sediment availability. While sand barchan morphodynamics has been extensively studied, snow barchans remain poorly documented. Here, using hourly time-series images taken near Concordia Station, Antarctica, we measure the sizes (lengths 0.3 m to 13 m, widths 0.4 m to 7.5 m) and migration rates (0.13 m h −1 to 3.5 m h −1 ) of 44 populations of snow barchans during 2017–2022. We compare this dataset with established height–velocity and length-width relationships for sand barchans in both air and water. Our results show that snow barchans follow the same scaling as sand barchans, allowing us to estimate a characteristic sintering (bonding of snow particles) time of about one day. This sintering process limits the size of snow barchans when active, reduces their aspect ratios, and, once wind falls below the transport threshold, explains their preservation over a few years. During wind events, migrating barchans are too small to maintain their shape and orientation, making them highly responsive to fluctuations in wind direction. Thus, studying snow barchans improves understanding of an elementary bedform encountered in multiple environments and also of the surface properties of snow on different timescales, offering insights into snow accumulation and wind-blown snow in ice cores.

Geomorphica↗
USGS2026

Generating geochemical and mineralogy distributions of soil in the conterminous United States using Bayesian hierarchical spatial models

Characterizing geochemical and mineralogical soil distributions across large spatial extents is essential for understanding mineral resources, ecosystem processes, and environmental risks. Rasters of soil geochemical distributions for the conterminous United States, however, are limited. We present a Bayesian modeling workflow and tool for generating predictive geochemical and mineralogy distribution maps for the conterminous United States using integrated nested Laplace approximation (INLA) with the stochastic partial differential equation approach. By modeling soil geostatistical data with environmental covariates (soil properties, topography, climate, and land cover), we generate predictive distributions of soil geochemistry that can be mapped or extracted for further analyses. As an example, we model the spatial distribution of trace elements in soil relevant to vertebrate health (cobalt, copper, iron, manganese, selenium, and zinc) and provide a workflow that can be used to generate and visualize predictive distributions of 39 other major and trace elements and 21 minerals of the soil survey, supporting a variety of ecological, environmental, and agricultural applications.

MethodsX↗
USGS2026

Comparative assessment of STIC sensors, streamflow and rain gauges for quantifying river connectivity in intermittent systems

In intermittent stream systems, including those occurring in Texas, USA, the severity of low-flow conditions, duration of seasonal disconnection, and frequency of no-flow events have been amplified by drought. Documentation of these no-flow events is necessary to evaluate ecosystem health. However, many intermittent reaches remain un-gauged given that perennial river sec-tions are often prioritized for gauge placement. Our objectives were to 1) document stream flow using Stream Temperature, Intermittency, and Conductivity (STIC) loggers to determine the frequency and duration of no-flow events in intermittent tributaries of the Colorado River, Texas and 2) compare logger data to publicly available data from streamflow discharge and precipitation gauge networks to understand differences among these data types for drying event characterization. We use these comparisons to summarize benefits and limitations of the application of in-stream data loggers. STIC loggers were deployed at 19 sites, one in each pool and riffle habitat of a stream reach. STIC loggers recorded a measurement of relative conductance every six hours from June 2022 to March 2024, which was used to determine the presence or absence of flow connectivity in a reach. No-flow duration among intermittent reaches varied between 37 and 270 days across tributaries during an ongoing drought in the study area. Overall, logger data was more precise than discharge data for characterizing no-flow events or precipitation data when documenting presence of water in the stream channel due to runoff. Lack of discharge gauges in intermittent tributaries left large sections of stream reaches undocumented and resulted in mischaracterization of flow patterns. Drought severity across the tributaries did not follow longitudinal patterns that would be expected by the climatic precipitation gradient of the study area. More research is needed to determine if factors such as population size affect severity. Likewise, precipitation data did not correlate well with logger water presence data, lacking consideration for groundwater recharge, soil hydrophobicity, and surface compaction. This study shows that to monitor no-flow events, detailed spatial datasets are necessary and that STIC loggers are useful tools that provide data to fill spatial information gaps and facilitate more accurate flow characterization and water presence data in intermittent systems.

Texas↗
USGS2025

Comparison of creek and bay influences on salt marsh sediment budget and deposition patterns

The resilience of salt marshes with low organic production depends on their effective capture and retention of mineral sediment from adjacent waters. Little prior work has directly compared mechanisms of sediment import from wave-influenced marsh boundaries against those of tidal creeks. We used simultaneous deployment of net-deposition tiles and oceanographic sensors to identify the timing and magnitude of sediment import/export to, and redistribution within, a marsh in south San Francisco Bay. As the marsh has both an eroding bay-exposed scarp and a prominent tidal creek, we investigated the mechanisms and magnitudes of sediment import from the marsh-bay versus the marsh-creek interface. The strong daily sea breezes of the summer season produced most of the wave-driven erosion of the marsh scarp and controlled suspended sediment concentrations; the winter season had weaker winds punctuated by a few storms. A large seasonal difference in suspended sediment concentrations influenced both flood and ebb sediment fluxes to the marsh and led to much higher rates of import in the summer. Both bay-side and creek-side processes were important to total marsh sediment budget. Bay-side sediment contributions were more variable in time due to the bay-influenced environment, and creek-side contributions were overall larger, reflecting the large proportion of the marsh fed by creek water. Sediment was redistributed throughout the system, with erosion near the bay-edge, accretion near the creek-edge and slow import to the marsh interior. The marsh was net importing sediment in the summer and exporting in the winter from different rates of these processes; on an annual scale, the marsh was net importing despite rapid lateral marsh loss. These findings emphasize that a positive sediment budget does not imply a stable marsh and that both creek- and edge-side dynamics are important for marsh sedimentation and geomorphic trajectories. Further, we expand understandings of non-storm and seasonal controls on marsh sedimentation.

California↗
USGS2024

Effects of stochastically-simulated near-fault ground motions on soil liquefaction

The scarcity of historically recorded near-fault ground motions poses a challenge to systematically understanding the influence of near-fault effects on various types of seismic demands for engineering purposes. In particular, the current state of knowledge of the influence of ground-shaking intensity on soil liquefaction and its consequences does not specifically account for the effects of near-fault ground motion characteristics. In this study, the influence of near-fault ground motions on liquefaction triggering and lateral spreading are investigated using non-linear modeling of a hypothetical liquefiable soil column in the finite-element computational platform OpenSees subjected to simulated ground motion time series that represent strong earthquake shaking in the near field. The simulated ground motion time series and resulting datasets are based on a parametric stochastic model and are developed for a range of source and path parameters to represent a realistic variability of ground motion characteristics. Dependencies between ground motion intensity measures (IMs) and liquefaction demand parameters are investigated for near-fault pulse and nonpulse-like ground motion sets. Evolutionary IMs, such as cumulative absolute velocity (CAV) and the time-varying magnitude-adjusted peak ground acceleration (PGAM), are considered in developing liquefaction triggering probability density functions. Post-liquefaction triggering responses such as lateral spreading displacements are examined in relation to PGA M and CAV. The ground motion simulations are validated by comparing their liquefaction-capacity PGA M fragilities and post-triggering CAV vulnerability relationships to historical records from the 1994 Northridge earthquake in California, USA. Finally, a path forward for future studies that includes finding systematic differences in the IM-liquefaction demand relationships between near-fault and far-field stochastic ground motion sets is outlined.

Conference Paper↗
USGS2025

Machine learning provides reconnaissance-type estimates of carbon dioxide storage resources in oil and gas reservoirs

Oil and gas reservoirs represent suitable containers to sequester carbon dioxide (CO 2 ) in a supercritical state because they are accessible, reservoir properties are known, and they previously contained stored buoyant fluids. However, planners must quantify the relative magnitude of the CO 2 storage resource in these reservoirs to formulate a comprehensive strategy for CO 2 mitigation. Even reconnaissance-type estimates of CO 2 storage resources of known oil and gas reservoirs may require complicated calculations involving 1) estimates of recoverable oil and gas, 2) reservoir properties (depth, temperature, pressure, etc.), and 3) the physical qualities of the retained fluids. We demonstrate the application of machine learning (ML) algorithms to bypass these computations to yield more rapid estimates of CO 2 storage resources in reservoirs capable of hosting CO 2 in a supercritical state. ML algorithms are computationally efficient because they do not impose the strong assumptions on the data-generating process that standard statistical or engineering procedures require. Further, ML algorithms can capture highly complex, particularly nonlinear, relationships among predictor variables. We demonstrate the application of four different ML algorithms using data from onshore and offshore oil and gas reservoirs in Europe, and show they perform well when predictions are compared to engineering estimates. The proposed methods and models provide an effective and novel way to more rapidly and directly determine the subsurface CO 2 storage capacity of oil and gas reservoirs around the world, information that operators, researchers, and policymakers alike require to meet energy transition and decarbonization goals.

Frontiers in Enviornmental Science↗
USGS2025

Long-term dynamics of earthquake swarms in the Yellowstone caldera

The factors controlling the spatial distribution and temporal evolution of earthquake swarms in volcanic systems remain unclear. We leverage leading-edge deep learning algorithms and a detailed three-dimensional velocity model to construct a 15-year high-resolution earthquake catalog of the Yellowstone caldera region. More than half of the region’s earthquakes are clustered into swarm-like families characterized by episodes of hypocenter expansion and migration. Adjacent earthquake swarms, separated by long quiescent periods, are found to be a dominant feature. We suggest that these swarms are controlled by the interplay between slowly diffusing aqueous fluids and rapid episodic fluid injections, which may result from the breaking of permeability seals. Our analyses also indicate that clustered seismicity beneath the caldera occurs on relatively immature, rougher fault structures, compared to more planar faults outside. Our results provide additional context for understanding seismicity in hydrothermal systems, highlighting the key role played by long-term fluid diffusion processes in driving the occurrence of earthquake swarms.

Idaho, Montana, Wyoming↗
USGS2025

Gaps in water quality modeling of hydrologic systems

This review assesses gaps in water quality modeling, emphasizing opportunities to improve next-generation models that are essential for managing water quality and are integral to meeting goals of scientific and management agencies. In particular, this paper identifies gaps in water quality modeling capabilities that, if addressed, could support assessments, projections, and evaluations of management alternatives to support ecosystem health and human beneficial use of water resources. It covers surface water and groundwater quality modeling, dealing with a broad suite of physical, biogeochemical, and anthropogenic drivers. Modeling capabilities for six constituents (or constituent categories) are explored: water temperature, salinity, nutrients, sediment, geogenic constituents, and contaminants of emerging concern. Each constituent was followed through the coupled atmospheric-hydrologic-human system, with prominent modeling gaps described for a diverse array of relevant inputs, processes, and human activities. Commonly identified modeling gaps primarily fall under three types: (1) model gaps, (2) data gaps, and (3) process understanding gaps. In addition to potential solutions for addressing specific individual modeling limitations, some broad approaches (e.g., enhanced data collection and compilation, machine learning, reduced-complexity modeling) are discussed as ways forward for tackling multiple gaps. This gap analysis establishes a framework of diverse approaches that may support improved process representation, scale, and accuracy of models for a wide range of water quality issues.

Water↗
USGS2026

Satellite tracking of Galapagos Petrel Pterodroma phaeopygia reveals distribution and movements during chick rearing

We tracked 19 adult Galapagos Petrels Pterodroma phaeopygia during the chick-rearing seasons in 2009 and 2010 (Santa Cruz Island [ n = 16] and Floreana Island [ n = 3]) in the Galápagos Islands, Ecuador. Eight petrels performed 27 complete foraging trips lasting 0.6 to 18.8 days. Short trips (3.2 ± 2.1 days; 785 km; max displacement 671 km) and long trips (10.8 ± 3.9 days; 2,856 km; max displacement 1,034 km) resulted in concentrated use of waters off southern and western Isabela Island and within the Galápagos Marine Reserve (GMR). Less concentrated time extended farther southwest and eastward, in that case toward mainland Ecuador. Total distance covered among all completed trips, independent of duration, was strongly correlated with trip duration ( R ² = 0.92), indicating a strategy favoring active searching and foraging over commuting. Petrels ranged across Ecuador's exclusive economic zone (EEZ), as well as other countries' (Colombia, Costa Rica, Perú), and waters beyond; they spent 46%, 27%, and 34% of their time in the GMR during short, long, and apparent (incomplete) trips, respectively. However, overlap with EEZs or marine protected areas (MPAs) does not necessarily confer protection, because commercial tuna fishing, including legal fishing historically permitted inside the GMR, occurs within these waters. Including all complete and incomplete trips, petrels spent 37% of their time in high-seas waters without formal protection, outside both MPAs and EEZs. While some hot spots overlapped Galápagos MPAs, the far-ranging nature of chick-provisioning petrels underscores the importance for this species of also having coordinated, multinational protection of the high seas.

Floreana Island, Galápagos Islands, Santa Cruz Isl↗