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1,664 records · Page 67Linked to original sources
USGS2026

Rapid hydrothermal triggering of induced seismicity at the Coso Geothermal Field

The long-term producing Coso Geothermal Field (CGF) in California operates over 100 wells tapping into a reservoir characterized by an extensive fracture network, complex fluid pathways, and regular seismic activity. Understanding the interaction between seismicity and injection can shed important light on the hydrothermal characteristics of the field. Here, we analyze 15 years of local seismic and daily operational data from the CGF, identifying a strong correlation between short-term increase in seismicity rate and seasonal volumetric and temperature variations in the reinjected fluid. Furthermore, the seismic footprint during peak injection of colder fluids reveals a near-instantaneous response up to 2 km away from the injection well, too rapid for pore pressure diffusion alone. This short-term and distant response is observed to have directional preference, indicating structural or permeability anisotropy within the reservoir. Additionally, the seismic response correlates with the initial volumetric increase of colder fluids, but also with temperature decrease during stable injection periods, suggesting thermal effects alone can play an important role in triggering distant seismicity.

California↗
USGS2025

Geochemistry and radiogenic isotopes constrain the mantle source region of the Mountain Pass Intrusive Suite, California

The Mountain Pass carbonatite stock is the largest rare earth element (REE) deposit and only active REE mine in the United States. The carbonatite intrusion and spatially associated alkaline silicate intrusions constitute the Mountain Pass Intrusive Suite, which is located within the Mojave Province in California. Both the carbonatite and the alkaline silicate rocks are enriched in large ion lithophile elements and light REEs, and less enriched to depleted in high field strength elements, indicating the mantle source region was metasomatically enriched in incompatible trace elements. The cause of this metasomatic mantle enrichment and the genetic relationship between the carbonatite and the alkaline silicate stocks are poorly understood. In this study, major and trace element geochemical data and isotopic (Rb-Sr, Sm-Nd, and Lu-Hf) data are presented to constrain genesis of the Mountain Pass Intrusive Suite, from mantle source region to the intrusion of the stocks. Our geochemical data are consistent with derivation of the alkaline silicate and carbonatite melts through partial melting from a shared mantle source region rather than through liquid immiscibility or fractional crystallization and separation of a carbothermal fluid. Although the Rb-Sr isotopic system in the Mountain Pass Intrusive Suite is disturbed at the whole-rock scale, the isotopic systems for whole-rock Sm-Nd (εNd i = ‐2.2 ± 0.8) and zircon Lu-Hf (εHf i = 0.1 ± 1.1) are robust and support mantle derivation of the magmas. Geochemical modeling using experimentally derived partition coefficients was used to identify possible causes of enrichment in incompatible elements through metasomatism in the mantle source region. Modeling of metasomatism by melts derived by partial melting of deeply subducted carbonated sediments approximates observed Mountain Pass Intrusive Suite trace element chemistry. Scattered εHf i in inherited zircon (2.8 ± 2.6) is consistent with derivation from an arc-related environment with substantial crustal contamination. Paleotectonic studies in the Mojave Province indicate that regional subduction preceded emplacement of the Mountain Pass Intrusive Suite by ∼300 Ma. Melting of the Mountain Pass source region may have been caused by post-collisional thermal relaxation and extension.

California↗
USGS2024

New 10Be-26Al isochron burial dating informs the Pliocene and Pleistocene evolution of the lower Colorado River, southwestern United States

Four new 10 Be- 26 Al isochron burial ages ranging from 4.4 to 2 Ma on ancestral Colorado River deposits in the lower Colorado River corridor (LCRC) help constrain the river’s evolution during the Pliocene and early Pleistocene. They help fill a gap between previous work that focused on older and younger deposits: Older dated deposits include the 5 Ma Bouse Formation, which records the integration of the Colorado River through a series of preexisting basins to the Gulf of California and the ca. 4.5 - 3.5 Ma Bullhead Alluvium, a 200 to 300 m thick aggregational package that immediately followed integration. The much younger, 100 - 70 ka, Chemehuevi Formation is another major aggradation package mapped throughout the LCRC. The new burial ages on the facies of Santa Fe Railway (4.37 ± 0.71 Ma), boulder conglomerate of Bat Cave Wash (2.12 ± 0.26 and 2.05 ± 0.31 Ma), and the Palo Verde alluvium (3.03 ± 0.26 Ma) partially fill in a 3.5 M.y. gap between the deposition of the Bullhead Alluvium and the Chemeheuvi Formation and document the timescales over which the Colorado River was able to remove the Bullhead aggradational package and initiate newer and smaller aggradational pulses.

Arizona, California, Nevada↗
USGS2025

Petrogenesis and mineralization potential of the Bradley Peak komatiitic basalts, Wyoming Province

The ca. 2.72 Ga Bradley Peak greenstone terrane in the Wyoming Province contains spinifex- and cumulate-textured komatiitic volcanic rocks that may host Ni-Cu-PGE sulfide mineralization. New whole rock geochemistry classifies these rocks as Al-undepleted komatiitic basalts derived from a parental melt with ~17 wt. % MgO. Isotopic data (Sm-Nd, Re-Os) and REE profiles suggest a plume source and possible assimilation of juvenile footwall volcanic rocks. Calculated sulfur concentrations at sulfide saturation and low-detection PGE geochemistry indicate these magmas did not saturate a sulfide liquid resulting in sulfide mineralization. Although the Bradley Peak komatiitic basalt flows are unlikely to host magmatic sulfide mineralization, they are likely the source of Au for regional orogenic gold deposits.

Wyoming↗
USGS2026

Patterns and drivers of cliff erosion in Big Sur, California, USA using repeat photogrammetry, 2017–2023

Seacliff erosion in steep terrain poses major risks to transportation and critical infrastructure. In Big Sur, California, USA, seacliff erosion threatens the sustainability of the central coast stretch of California State Route 1, a transportation corridor that is critical to the region's economy. Published cliff retreat rates for the region range from 1 to 40 cm yr −1 , highlighting that high-resolution, process-based studies could enhance understanding of the causes of spatial and temporal variability. We quantified cliff erosion and investigated its drivers along ∼13 km of the Big Sur coastline at week–month timescales during the late fall to early spring wet seasons between January 2017 and June 2023 by analyzing 3D point clouds developed from aerial imagery using four-dimensional structure-from-motion (4D SfM) photogrammetry techniques. We calculated cliff face retreat rates of 2.23 ± 3.06 cm yr −1 (mean ±1 σ ), an order of magnitude lower than long-term estimated rates for the region (which included large deep-seated landslides), but in line with short-term rates reported across California. Change detection imagery comparison, cliff profiles through time, and statistical analysis reveal a cyclical cliff evolution process in which erosion by wave action at the cliff base destabilizes the cliff and primes it for subsequent failure during precipitation events. Although more erosion by volume could be attributed to precipitation-induced increases in soil moisture (784 m 3 km −1 yr −1 ) compared with erosion attributed to wave power (282 m 3 km −1 yr −1 ), our observations underscore the coupled nature of these processes in driving cliff evolution, consistent with established theory and observations.

California↗
USGS2025

Using gridded seismicity to forecast the long-term spatial distribution of earthquakes for the 2025 Puerto Rico and U.S. Virgin Islands National Seismic Hazard Model

Gridded (or background) seismicity models are a critical component of probabilistic seismic hazard assessments, accounting for off‐fault and smaller‐magnitude earthquakes. They are typically developed by declustering and spatially smoothing an earthquake catalog to estimate a long‐term seismicity rate that can be used to forecast future earthquakes. Here, we present new gridded seismicity models for use in the 2025 National Seismic Hazard Model (NSHM) for Puerto Rico and the U.S. Virgin Islands (PRVI). The previous PRVI NSHM was released in 2003, and our new models incorporate updates to both data and methodology. We utilize an updated earthquake catalog based on improved Puerto Rico Seismic Network data with newly characterized completeness epochs. The catalog is divided into crustal, subduction interface, and intraslab seismicity using new methods and Slab2 subduction zone geometries. To forecast the long‐term spatial distribution of earthquakes, we use an updated methodology developed for the 2023 U.S. 50‐state NSHM, considering three declustering methods and two spatial smoothing methods based on 2D Gaussian kernels. To adapt it for the complex seismotectonics of the region, we also adopt probabilistic methods to account for events with unknown depths and uncertainties in tectonic classification, and develop a new method for spatial scaling to counteract the effects of spatial variability in network coverage while maintaining the use of smaller events. Finally, we test the performance of these spatial models in forecasting the location of M w ≥ 5earthquakes in the region. Our updated methodology improves the representation of epistemic uncertainty relative to the 2003 model, and our results demonstrate the effectiveness of the new measures we have introduced to address heterogeneities in network detection and systematically evaluate forecast performance.

Puerto Rico, U.S. Virgin Islands↗
USGS2025

Estimating the probability of export restrictions to inform mineral criticality

As demand for advanced technologies rises, mineral commodities will increase in geopolitical importance. To assess risks associated with mineral commodity supply chain disruptions, governmental agencies and others have developed "criticality" assessments, with criticality described using the economic impact and probability of supply chain disruptions. In previous work, subjective supply risk indicators were developed to approximate this probability, typically combining several factors such as supply diversity and political stability of trading partners, where indicator weightings can substantially impact results. This work explicitly quantifies trade barrier probability using an ensemble of several machine learning classifiers, with probability estimates informed by exogenous variables such as prior trade barrier implementation and global export dominance. Major differences in the high-probability countries and commodities are observed across models, but the ensemble method highlights Indonesia, China, Tanzania, and the United States as particularly high risk. This approach enables a direct, quantitative, objective approach to assessing trade barrier probability, enhancing risk identification and prioritization for policymakers.

SSRN↗
USGS2024

Biogeochemical and community ecology responses to the wetting of non-perennial streams

Transitions between dry and wet hydrologic states are the defining characteristic of non-perennial rivers and streams, which constitute the majority of the global river network. Although past work has focused on stream drying characteristics, there has been less focus on how hydrology, ecology and biogeochemistry respond and interact during stream wetting. Wetting mechanisms are highly variable and can range from dramatic floods and debris flows to gradual saturation by upwelling groundwater. This variation in wetting affects ecological and biogeochemical functions, including nutrient processing, sediment transport and the assembly of biotic communities. Here we synthesize evidence describing the hydrological mechanisms underpinning different types of wetting regimes, the associated biogeochemical and organismal responses, and the potential scientific and management implications for downstream ecosystems. This combined multidisciplinary understanding of wetting dynamics in non-perennial streams will be key to predicting and managing for the effects of climate change on non-perennial ecosystems.

Nature Water↗
USGS2026

Localization of spatiotemporally heterogeneous subsurface flows using autoencoder-based deep learning framework for time-lapse self-potential tomography

Self-potential (SP) monitoring has emerged as a valuable method for characterizing subsurface hydrogeological features and processes due to its sensitivity to fluid-induced electrokinetic effects. Despite advancements in SP inversion, challenges remain in imaging groundwater dynamics from SP activities due to complex hydrological settings and transient noise. In this study, a deep learning autoencoder (AE)-based framework is proposed for the spatiotemporal localization of subsurface fluid movement from time-lapse SP tomography. Temporal segments of time-lapse numerical inversions were first derived from long-term SP monitoring conducted from a floodplain site in Oak Ridge, Tennessee, known for active hyporheic exchange. Subsequently, AE models based on vision transformer (ViT), convolutional long short-term memory (ConvLSTM), convolutional neural network, and temporal convolutional network were individually trained and compared on the SP tomography segments for reconstruction performance. Finally, the reconstruction error over time serves as an anomaly score to identify moments of active SP variation, whereas spatial distributions of errors within these moments are analyzed to image and localize regions associated with anomalous subsurface fluid movement. The results demonstrate that ConvLSTM- and ViT-AE are most capable for the localization task with contrasting error distributions and consistent delineation of anomalies. Applying the method to both SP arrays parallel and perpendicular to the stream produced consistent anomaly zones near a fault or karst feature, validating the robustness and generalization of the approach. These results demonstrate the potential of the proposed framework as a scalable and interpretable tool for spatiotemporal analysis of subsurface flow dynamics in complex hydrogeological systems.

Tennessee↗
USGS2025

Comparative assessment of a restored and natural wetland using 13C-DNA SIP reveals a higher potential for methane production in the restored wetland

Wetlands are the largest natural source of methane (CH 4 ), a potent greenhouse gas produced by methanogens. Methanogenesis rates are controlled by environmental factors such as redox potential, temperature, and carbon and electron acceptor availability and are presumably dependent on the composition of the active methanogen community. We collected intact soil cores from a restored and natural freshwater depressional wetland on Maryland’s Delmarva Peninsula (USA) to assess the effects of wetland restoration and redox shifts on microbial processes. Intact soil cores were incubated under either saturated (anoxic) or unsaturated (oxic) conditions and amended with 13 C-acetate for quantitative stable isotope probing (qSIP) of the 16S rRNA gene. Restored wetland cores supported a distinct community of methanogens compared to natural cores, and acetoclastic methanogens putatively identified in the genus Methanosarcina were among the most abundant taxa in restored anoxic and oxic cores. The active microbial communities in the restored wetland cores were also distinguished by the unique presence of facultatively anaerobic bacteria belonging to the orders Firmicutes and Bacteroidetes . In natural wetland incubations, methanogen populations were not among the most abundant taxa, and these communities were instead distinguished by the unique presence of aerobic bacteria in the phyla Acidobacteria , Actinobacteria , and class Alphaproteobacteria . Iron-reducing bacteria, in the genus Geobacter , were active across all redox conditions in both the restored and the natural cores, except the natural oxic–anoxic condition. These findings suggest an overall higher potential for methanogenesis in the restored wetland site compared to the natural wetland site, even when there is evidence of Fe reduction.

Maryland↗
USGS2024

Onset of aftershocks: Constraints on the Rate-and-State model

Aftershock rates typically decay with time t after the mainshock according to the Omori–Utsu law, R (t)=K(c+t) −p ⁠ , with parameters K , c , and p . The rate‐and‐state (RS) model, which is currently the most popular physics‐based seismicity model, also predicts an Omori–Utsu decay with p = 1 and a c ‐value that depends on the size of the coseismic stress change. Because the mainshock‐induced stresses strongly vary in space, the c ‐value should vary accordingly. Short‐time aftershock incompleteness (STAI) in earthquake catalogs has prevented a detailed test of this prediction so far, but the newly developed a ‐positive method for reconstructing the true earthquake rate now allows its testing. Using previously published slip models, we calculate the coseismic stress changes for the six largest mainshocks in Southern California in recent decades and estimate the maximum shear as a scalar proxy of the coseismic stress tensor. Aftershock rates reconstructed for events in different stress ranges show that the rates follow a power law with p = 1 independent of stress with no clear sign of a c ‐value. The onset of the power‐law decay is abrupt and more delayed in areas with smaller stress changes. The observations do not necessarily contradict the RS model, as STAI limits the resolution for early aftershocks, and the RS model can reproduce the observations for specific Aσ values. However, the observations lead to strong constraints, namely Aσ <10 kPa and a power‐law decay of the background rate with distance to the fault, with exponent 2.7.

Seismological Research Letters↗
USGS2025

Characterizing the scale of regional landslide triggering from storm hydrometeorology

Rainfall strongly affects landslide triggering; however, understanding how storm characteristics relate to the severity of landslides at the regional scale has thus far remained unclear, despite the societal benefits that would result from defining this relationship. As mapped landslide inventories typically cover a small region relative to a storm system, here we develop a dimensionless index for landslide-inducing rainfall, A * , based on extremes of modeled soil water relative to its local climatology. We calibrate A * using four landslide inventories, comprising over 11 000 individual landslides over four unique storm events, and find that a common threshold can be applied to estimate regional shallow-landslide-triggering potential across diverse climatic regimes in California (USA). We then use the spatial distribution of A * , along with topography, to calculate the landslide potential area (LPA) for nine landslide-inducing storm events over the past 20 years, and we test whether atmospheric metrics describing the strength of landfalling storms, such as integrated water vapor transport, correlate with the magnitude of hazardous landslide-inducing rainfall. We find that although the events with the largest LPA do occur during exceptional atmospheric river (AR) storms, the strength of landfalling atmospheric rivers does not scale neatly with landslide potential area, and even exceptionally strong ARs may yield minimal landslide impacts. Other factors, such as antecedent soil moisture driven by storm frequency and mesoscale precipitation features within storms, are instead more likely to dictate the patterns of landslide-generating rainfall throughout the state.

California↗
USGS2024

Rainfall intensification amplifies exposure of American Southwest to conditions that trigger postfire debris flows

Short-duration, high-intensity rainfall can initiate deadly and destructive debris flows after wildfire. Methods to estimate the conditions that can trigger debris flows exist and guidance to determine how often those thresholds will be exceeded under the present climate are available. However, the limited spatiotemporal resolution of climate models has hampered efforts to characterize how rainfall intensification driven by global warming may affect debris-flow hazards. We use novel, dynamically downscaled (3.75-km), convection-permitting simulations of short-duration (15-min) rainfall to evaluate threshold exceedance for late 21st-century climate scenarios in the American Southwest. We observe significant increases in the frequency and magnitude of exceedances for regions dominated by cool- and warm-season rainfall. We also observe an increased frequency of exceedance in regions where postfire debris flows have not been documented, and communities are unaccustomed to the hazard. Our findings can inform planning efforts to increase resiliency to debris flows under a changing climate.

Arizona, California, Nevada, New Mexico, Utah↗
USGS2026

Apatite (U-Th)/He thermochronology from Marsh Creek anticline reconciles Cenozoic and Holocene strain patterns and elucidates the Cenozoic canning displacement zone of Arctic Alaska

The northeastern Brooks Range is a vast fold-thrust belt that records the northernmost expression of Cenozoic deformation in Alaska, likely with complex dynamic linkages to distant tectonic elements. The principal focus of this manuscript is the Marsh Creek anticline (MCA), which is a large and recently active structure within the broader northeastern Brooks Range. The MCA is a complex, polyphase structure mostly buried beneath the Arctic coastal plain. We present apatite (U-Th)/He (AHe) dates from six outcrop samples, all near the structural crest of the anticline, as well as supporting detrital zircon U/Pb (ZUPb) age spectra from five outcrop samples. The AHe sample transect spans ~3 km of structural relief. The four shallowest AHe samples are not reset. However, the two deepest samples exhibit low intrasample variability among replicates and strong date versus grain radius correlations, suggesting post-depositional burial heating to within the AHe partial retention zone. Inverse thermal history modeling of these data resolves a protracted phase of exhumational cooling that began around 33–28 Ma. Detrital ZUPb age spectra from Paleogene strata support an interpretation of diverse inherited thermal histories recorded by the AHe data, and they are also consistent with extant reconstructions of Paleogene sediment dispersal. Placed into regional context, the results constrain a phase of increasing structural relief in the northeastern Brooks Range fold-thrust belt that began by the Eocene. The relief developed in a zone characterized by diminishing structural relief to the west called the Canning displacement zone. Although this zone was active since the Eocene, several structures including the studied part of the MCA were rapidly exhumed in the Oligocene. Lastly, we argue for kinematic compatibility between Cenozoic contraction and active strike-slip in the northeastern Brooks Range, with the temporal change in strain style likely reflecting the increase in structural relief and topography.

Alaska↗
USGS2025

False positives in the identification of dynamic earthquake triggering

Dynamic earthquake triggering is commonly identified through the temporal correlation between increased seismicity rates and global earthquakes that are possible triggering events. However, correlation does not imply causation. False positives may occur when unrelated seismicity rate changes coincidently occur at around the time of candidate triggers. We investigate the expected false positive rate in Southern California with global M ≥ 6 earthquakes as candidate triggers. We compute the false positive rate by applying the statistical tests used by DeSalvio and Fan (2023), https://doi.org/10.1029/2023jb026487 to synthetic earthquake catalogs with no real dynamic triggering. We find a false positive rate of ∼3.5%–8.5% when realistic earthquake clustering is present, consistent with the 95% confidence typically used in seismology. However, when this false positive rate is applied to the tens of thousands of spatial-temporal windows in Southern California tested in DeSalvio and Fan (2023), https://doi.org/10.1029/2023jb026487 , thousands of false positives are expected. The expected false positive occurrence is large enough to explain the observed apparent triggering following 70% of large global earthquakes (DeSalvio & Fan, 2023, https://doi.org/10.1029/2023jb026487 ), without requiring any true dynamic triggering. Aside from the known triggering from the nearby El Mayor-Cucapah, Mexico, earthquake, the spatial and temporal characteristics of the reported triggering are indistinguishable from random false positives. This implies that best practice for dynamic triggering studies that depend on temporal correlation is to estimate the false positive rate and investigate whether the observed apparent triggering is distinguishable from the correlations that may occur by chance.

JGR Solid Earth↗
USGS2024

Layered intrusions in the Precambrian: Observations and perspectives

Layered intrusions are plutonic bodies of cumulates that form by the crystallization of mantle-derived melts. These intrusions are characterized by igneous layering distinguishable by shifts in mineralogy, texture, or composition. Layered intrusions have been fundamental to our understanding of igneous petrology; however, it is their status as important repositories of critical metals – such as platinum-group elements, chromium, and vanadium – that has predominantly driven associated research in recent decades. Many layered intrusions were emplaced during the Precambrian, predominantly at the margins of ancient cratons during intervals of supercontinent accretion and destruction. It appears that large, layered intrusions require rigid crust to ensure their preservation, and their geometry and layering is primarily controlled by the nature of melt emplacement. Layered intrusions are best investigated by integrating observations from various length-scales. At the macroscale, intrusion geometries can be discerned, and their presence understood in the context of the regional geology. At the mesoscale, the layering of an intrusion may be characterized, intrusion-host rock contact relationships studied, and the nature of stratiform mineral occurrences described. At the microscale, the mineralogy and texture of cumulate rocks and any mineralization are elucidated, particularly when novel microtextural and mineral chemical datasets are integrated. For example, here we demonstrate how mesoscale observations and microscale datasets can be combined to understand the petrogenesis of the perplexing snowball oiks outcrop located in the Upper Banded Series of the Stillwater Complex. Our data suggest that the orthopyroxene oikocrysts did not form in their present location, but rather formed in a dynamic magma chamber where crystals were transported either by convective currents or within crystal-rich slurries. Critical metals may be transported to the level of a nascent intrusion as dissolved components in the melt. Alternatively, ore minerals are entrained from elsewhere in a plumbing system, potentially facilitated by volatile-rich phases. There are many ore-forming processes propounded by researchers to occur at the level of emplacement; however, each must address the arrival of the ore mineral, its concentration of metals, and its accumulation into orebodies. In this contribution, several of these processes are described as well as our perspectives on the future of layered intrusion research.

Precambrian Research↗
USGS2026

Distributed volcanic fields—Patterns, products, processes, and plumbing

Distributed volcanic fields—also referred to as “monogenetic fields” or simply “volcanic fields”—are found on every continent, on the seafloors, and in every tectonic setting on Earth. Yet, our understanding of what constitutes a distributed volcanic field, and our knowledge of the common products, spatiotemporal patterns in activity, and plumbing systems of these fields, are commonly poor and (or) debated. Here we provide an overview of the current understanding of distributed volcanic fields (DVFs) through review and compilation of published data, with an emphasis on understanding the characteristics of fields that are essential to prepare for future hazardous volcanic activity. Distributed fields can erupt restricted to variable magma compositions. Activity in these fields produces nearly all types of volcanoes, including scoria and spatter cones, maars, low shields, lava fields, stratovolcanoes, and calderas, but monogenetic volcanoes are the defining characteristic of DVFs. The number of vents and lifespans of DVFs vary greatly; vent numbers range from 2 to greater than 1,000, and fields can remain active for 150,000 to 10 million years. Some characteristics of DVFs appear field dependent. Although the volumes of single monogenetic eruptions within DVFs globally are variable (from less than 0.1 to a few cubic kilometers), each field may have a characteristic range in eruption volumes. Eruptions within distributed volcanic fields can have a random distribution and timing, but spatial and (or) temporal vent clustering and alignment are common, and eruptions may be time or volume predictable. Average eruption recurrence intervals in DVFs span over an order of magnitude, from less than 3 to greater than 100 thousand years. Exposures of the shallow portions of older systems reveal that many magma batches end their ascent before reaching the surface, with some dikes stopping within only meters of the surface. Petrologic insights into the deeper plumbing systems of DVF volcanoes indicate variable depths of magma crystallization and (or) stalling, and that magma transport and storage systems may be unique to a particular DVF and its underlying crustal structure. Both seismic and petrologic data for mafic DVF eruptions corroborate intrusions of magma into storage systems in the months to years before eruption, as well as variable ascent rates through the crust (days to weeks). Few distributed fields are closely monitored, as they erupt infrequently, but these observations imply that the amount of time available to install monitoring instrumentation after the first felt seismicity may be short, as precursory activity is frequently on the order of days to months for modern DVF eruptions. Satellite-based geodesy may provide useful warning in such cases. This chapter concludes with outstanding questions and areas for future research that will aid in our understanding and preparedness for future DVF eruptions.

Professional Paper↗
USGS2025

Beyond the mangroves: A global synthesis of tidal forested wetland types, drivers and future information opportunities

There is increasing awareness of the global diversity of tidal forested wetlands (TFWs) and their significance in the provision of ecosystem services. These ecosystems, including mangrove forests, tidal freshwater forested wetlands, supratidal forests and transitional forests together span multiple climatic zones, geomorphic settings, and inundation and salinity regimes. We utilise case studies across five continents to demonstrate the state of knowledge among TFWs. Intertidal mangroves are the best-defined of the TFWs thanks to decades of research on their geomorphology, hydrology and ecology across their broad distribution. Non-mangrove forest settings, however, demonstrate more diverse hydrological, biochemical and vegetation conditions. In many cases, non-mangrove forests are situated at upper intertidal or supratidal elevations, where surface waters and groundwater are subject to interactions between tides freshwater inputs. Salinity datasets show variations ranging from tidal freshwater forested wetlands and ‘low-salinity mangroves’ to mesohaline or marine salinities, often with high temporal variability. While the floristic composition of non-mangrove forests vary among biogeographic regions, locally dominant TFW species are commonly distributed beyond the tidal niche into non-tidal wetland and upland forests. This presents challenges for traditional remote sensing approaches to ecosystem mapping, which are mostly lacking for non-mangrove forests. Geomorphic approaches and developments in machine learning offer opportunities to address this.

Preprint↗