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USGS2026

Decision-centered systems for the future of wildlife conservation

The future of wildlife conservation will be determined by how well we decide, not simply by how much we know. Advances in quantitative ecology, sensor networks, and artificial intelligence have enhanced the field's ability to estimate population states and predict ecological dynamics. Yet, these technological and analytical advancements have not translated into proportional improvements in wildlife conservation decision making. The prevailing science-centered paradigm, which prioritizes research production as the primary route to better management, was appropriate when limited ecological understanding was the primary constraint on decision making. Today, wildlife conservation challenges are more often restricted by inadequate decision-making processes rather than by insufficient information. This paper defines a decision-centered system as an institutional and organizational arrangement in which the generation, integration, and application of scientific knowledge are explicitly structured around the decisions required for wildlife conservation. Decision systems evaluate success not only through scientific rigor, but through the quality of decision-making processes and outcomes they support. Artificial intelligence (AI) is likely to deepen this mismatch by rapidly expanding analytical capacity while leaving the underlying challenges of decision making unresolved. As AI data synthesis, modeling, and estimation become increasingly automated, the comparative advantage of conservation professionals is likely to shift toward tasks requiring human judgment (e.g., eliciting stakeholder values, weighting competing management objectives). The conceptual basis for this shift already exists in structured decision making, adaptive management, and similar frameworks. The remaining barriers to implementation are both institutional and organizational. The rules, norms, and incentive structures governing what counts as good conservation work, including what gets funded, published, and rewarded, will benefit from shifting alongside the agencies, universities, and professional societies that train and employ wildlife professionals. Conditions for this transition include redesigning incentives, training, and governance so that organizations are prepared not only to generate knowledge, but to consistently translate it into effective action.

The Wildlife Society Bulletin↗
USGS2026

Production of secondary microbial methane from a gas hydrate-bearing reservoir at the HYDRATE P1 Production Test Well (PTW-1) on the Alaskan North Slope

Gas hydrate in the Alaskan North Slope (ANS) is believed to contain as much methane as the known conventional gas accumulations in the Prudhoe Bay field. The JOGMEC-DOE-USGS Collaborative Gas Hydrate R&D Project conducted an extended-duration production test from the sub-permafrost, gas-hydrate saturated B1 sand reservoir (unit B) at the Kuparuk State 7-11-12 Site in the Prudhoe Bay Unit of the ANS. Using compositional and stable isotopic data measured on gas produced from well cuttings and pressure cores collected from the HYDRATE 02 Geo Data Well (GDW), we differentiate primary microbial, secondary microbial, and trace thermogenic gas sources. The upper part of the well contained predominantly primary microbial methane from near the surface to the SV6 stratigraphic horizon at 1133 ft (345.3 m) measured depth (MD). Below that, the gas composition transitioned to a mixture of mostly primary and secondary microbial methane to near the base of ice-bearing permafrost at 1968 ft (599.8 m) MD. With greater depth to 3558 ft (1084.5 m) MD, which includes the D1 sand (unit D), the B1 sand (unit B), and the base of gas hydrate stability at 3113 ft (948.8 m) MD, the gas composition was greater than 98% secondary microbial methane with the remainder being oil-associated thermogenic gas migrated from the deep Sadlerochit Formation. The unit B vertical gas profile derived from degassed pressure cores demonstrated that gas dissolved in the clay-rich sediment intervals bounding the B1 sand reservoir was distinct from dissolved and hydrate-caged gases in the sand-rich hydrate-bearing reservoir. The HYDRATE P1 Production Test Well (PTW-1) targeted and successfully extracted gas dissociated from hydrate gas in the B1 sand for 151 days when using an electrical submersible pump to depressurize the reservoir with subsequent depressurization achieved through the use of a jet pump. Gas produced from PTW-1 was mostly indistinguishable from the gas compositional profile measured through the B1 sand and generally distinct from dissolved gas in the bounding clay-rich sediments, confirming that the upper and lower bounding units limited infiltration into the reservoir during production. Isolation of the bounding units from the reservoir contributed to the unexpectedly high ratio of production gas to water observed during the extended-duration gas hydrate production test at PTW-1.

Alaska↗
USGS2026

Multiple lines of evidence reveal rapid, seasonal watershed responses to enhanced weathering

Enhanced weathering accelerates carbon dioxide removal from the atmosphere through the rapid dissolution of land amendments of crushed, cation-rich rocks. The export of enhanced weathering dissolution products to drainage networks has important implications for carbon dioxide removal durability and measurement yet has received little attention. Here we observe rapid and pronounced streamwater chemistry responses within weeks of a crushed basalt application to a temperate headwater catchment: alkalinity exceeded counterfactual estimates by as much as 557 μeq l −1 , accompanied by changes in silica, lithium and major-ion chemistry consistent with basalt weathering. Difference-in-differences analysis identified repeated treatment effects with enhanced weathering accounting for 7–17% of streamwater alkalinity in successive summers and autumns, but less in winter and spring. This seasonal response reflects a combination of temperature controls on basalt dissolution kinetics and hydrologic controls on weathering-product export. Over 2 years, 9.5–11% of theoretical carbon dioxide removal potential was exported as alkalinity (34.7 t CO 2 km −2 yr −1 ).

Vermont↗
USGS2026

Fish locomotor dynamics quantified using multiple inertial measurement units

Animals exhibit a diversity of locomotor behaviours that vary with body shape, ontogeny, motivation and environment. Documenting these behaviours often relies on recording videos of animals in controlled conditions displaying stereotyped behaviours. By contrast, animal-borne motion sensing data loggers can document diverse behaviours of animals in their natural environment. Traditionally, one data logger is used to infer body dynamics; however, a single location presents an incomplete picture of body movement. Here, we deploy multiple independent inertial measurement units on individual fish to study within-body dynamics and assess the accuracy of this approach compared to traditional video methods. Using a combination of robotic and animal experiments, we accurately measure the timing, direction and magnitude of movement of multiple locations along the body and can recreate accurate three-dimensional midline kinematics without video data. Furthermore, we show that with as few as two data loggers, parameters such as propulsive wavelength can be calculated, even during high-intensity behaviours. Using multiple data loggers has the potential to provide unbiased spatio-temporal estimates of fish kinematics, allowing kinematic studies to be extended to new species, new habitats and a diversity of natural fish locomotor behaviours beyond those traditionally studied in laboratory settings.

Royal Society Open Science↗
USGS2026

Tapwater contaminant mixtures and cumulative risk screening on the Crow (Apsáalooke) Reservation

Introduction: Water insecurity is a challenge for the Apsáalooke (Crow) Tribal Nation in south-central Montana, United States. Both private-well and public-supply tapwater (TW) are vulnerable to a range of contaminants, posing potential risks to community health and well-being. Ongoing community concerns about unrecognized inorganic, organic, and microbial contaminants underscore the need for continued comprehensive monitoring and improved water management strategies. Materials and methods: TW samples were collected from 26 private-well and 12 public-supply participant locations, selected and recruited by the Crow Water Quality Project. A total of 35 inorganic, 450 organic, and three microbial analytes were assessed in these samples. Public-Supply Maximum Contaminant Levels and Health benchmark-based screening levels were used to evaluate contaminant concentrations. Results: Sixty-one organic and 34 inorganic contaminants were detected. Screening levels were frequently exceeded, particularly due to multiple inorganic contaminants in private TW and both chlorine-based disinfection byproducts (DBPs) and inorganics in public TW. These findings highlight gaps in current source-water protection and water treatment practices. Conclusions: After reporting results to participants, anonymized data were shared at community events to inform risk management decisions. The study underscores the importance of broad monitoring and analysis throughout the upper Missouri River basin and across the United States to address Tribal concerns over water insecurity and mitigate potential unrecognized TW contaminant risks, particularly to vulnerable subpopulations.

Montana↗
USGS2026

Floods of June 20–July 6, 2024, in the Big Sioux River, Rock River, Little Sioux River, Ocheyedan River, and Floyd River Basins, northwestern Iowa

Major flooding occurred on June 20–July 6, 2024, in northwestern Iowa affecting the Big Sioux, Rock, Little Sioux, Ocheyedan, and Floyd River Basins. Heavy rain fell in northwestern Iowa, southwestern Minnesota, and southeastern South Dakota on June 20–22, 2024. Parts of northwestern Iowa recorded 2–6 inches of rainfall and localized amounts exceeding 12 inches. A maximum peak-of-record streamflow of 175,000 cubic feet per second at the U.S. Geological Survey streamgage Big Sioux River at Akron, Iowa (06485500), was recorded on June 22, 2024, and had an annual exceedance probability range of 0.2–0.49 percent. High-water marks were measured at four locations along the Big Sioux River between U.S. Interstate 29 at Sioux City, Iowa, upstream to Iowa Highway 10 north of Hawarden, Iowa, a distance of 75.7 river miles. A maximum peak-of-record streamflow of 157,000 cubic feet per second at the U.S. Geological Survey streamgage Rock River near Rock Valley, Iowa (06483500), was recorded on June 22, 2024, and had an annual exceedance probability of less than 0.2 percent. High-water marks were measured at eight locations along the Rock River between County Road B30 east of Hudson, South Dakota, upstream to Iowa Highway 9 at Rock Rapids, Iowa, a distance of 39.3 river miles. A maximum peak-of-record streamflow of 63,000 cubic feet per second at the U.S. Geological Survey streamgage Little Sioux River at Correctionville, Iowa (06606600), was recorded on June 24, 2024, and had an annual exceedance probability range of 0.2–0.49 percent. High-water marks were measured at 11 locations along the Little Sioux River between Iowa Highway 31 west of Correctionville, Iowa, upstream to U.S. Highway 18 north of Spencer, Iowa, a distance of 134.8 river miles. A maximum streamflow of 24,500 cubic feet per second at the U.S. Geological Survey streamgage Ocheyedan River near Spencer, Iowa (06605000), was recorded on June 22, 2024, and had an annual exceedance probability range of 0.2–0.49 percent. High-water marks were measured at three locations along the Ocheyedan River between County Road M38 west of Spencer, Iowa, upstream to U.S. Highway 18 west of Everly, Iowa, a distance of 12.8 river miles. A maximum streamflow of 41,000 cubic feet per second at the U.S. Geological Survey streamgage Floyd River at Alton, Iowa (06600100), was recorded on June 22, 2024, and had an annual exceedance probability range of 1–1.99 percent. High-water marks were measured at six locations along the Floyd River between Iowa Highway 3 at Le Mars, Iowa, upstream to Iowa Highway 10 at Alton, Iowa, a distance of 27.5 river miles. The high-water marks were used to develop flood profiles for the Big Sioux, Rock, Little Sioux, Ocheyedan, and Floyd Rivers.

Iowa, Minnesota, South Dakota↗
USGS2026

A range-wide summary of western grebe and Clark’s grebe breeding lakes across North America

Western grebes ( Aechmophorus occidentalis ) and Clark’s grebes ( Aechmophorus clarkii ) are iconic waterbirds of North America that breed in colonies on inland lakes. Both species are patchily distributed and not surveyed well by the North American Breeding Bird Survey and, hence, we know relatively little about their population trends or the lakes that support the largest colonies. Knowing the distribution of western and Clark’s grebe breeding populations across their range is a critical first step to better monitor and manage these two waterbirds. We compiled published and unpublished data summarizing the status of current and historical western and Clark’s grebe breeding colonies on lakes across North America. We summarized count numbers for adults, nests, and chicks during the breeding season, including date of the most recent count from local survey efforts. We also summarized the most common threats to these birds at their breeding colonies. Sixty-seven percent of the Aechmophorus grebes during the breeding season were in 5% of the 770 breeding lakes identified range-wide, and 73% of the 770 breeding lakes supported < 100 breeding adults. The most common threats at breeding lakes were egg predation, wind and wave impact on nests, changes in populations of forage fish, anthropogenic disturbances, rapid fluctuation of water levels at breeding colonies, and decrease in nesting habitat availability. Our range-wide summary of the locations and sizes of breeding colonies and the presumed threats at these colonies provide a foundation for thorough range-wide survey efforts and conservation prioritizations for western and Clark’s grebes in North America.

North America↗
USGS2026

Anthropogenic and geogenic factors affecting groundwater arsenic and potential drinking water exposure in the San Luis Valley, Colorado

Groundwater arsenic is a serious health threat in many regions with limited surface water drinking supplies. In the San Luis Valley, Colorado, USA, where most residents rely on groundwater for drinking water, elevated groundwater arsenic concentrations (≥5 μg/L) were observed in 19.8% of private wells. Many recent studies have leveraged data science methods to estimate the spatial variability of arsenic at local, regional, and global scales. These studies typically predict depth-independent arsenic concentrations due to limited well depth information. However, arsenic concentrations may vary greatly with depth due to heterogeneous aquifer geochemistry, including redox potential, pH, and biogeochemical conditions. In this study, we apply random forest modeling to predict elevated groundwater arsenic concentrations (≥5 μg/L) over space and depth continuously across the San Luis Valley using a community-driven data set of 435 groundwater measurements of major ions and trace metals. Our model reveals the influence of several known or hypothesized drivers or proxy drivers of arsenic in groundwater, including surface elevation, fraction of fine-grained aquifer sediments, well depth, soil pH, long-term subsidence, and geothermal influences. Elevation, percentage of fine-grained sediments, and elemental indicators of geothermal fluid influence are some of the most important predictors of arsenic, while long-term subsidence is found to have a weak but positive relationship with arsenic. The model has a specificity of 0.82 and a sensitivity of 0.81 on held-out test data sets. In addition to improving understanding of drivers of arsenic in the region, this model produces pseudo-3D estimates of groundwater arsenic. The model can also be used to assess the time-dependent exposure to arsenic as the depth of domestic wells changes over time.

Colorado↗
USGS2026

Describing Yellow Perch population characteristics in Wisconsin to better understand observed declines in size structure

Objective Recent studies suggest that Yellow Perch Perca flavescens size structure has declined in Wisconsin and Minnesota. Little is known about most of the Yellow Perch populations that exist across the upper Midwestern USA because Yellow Perch are not a focus of standardized sampling and age estimation rarely occurs. To better understand Yellow Perch population dynamics and demographics, we described age- and length-based characteristics of 31 Yellow Perch populations in Wisconsin and assessed potential correlations with abiotic and biotic variables. Methods During 2018–2019, Yellow Perch were collected from 31 populations during spring fyke-net surveys to calculate mean total length (TL) at age 4 (ML4), maximum age, proportional size distribution (PSD), and mean TL of the five largest fish (MXL5). Pearson correlations were used to identify associations among these metrics and with a suite of abiotic and biotic variables. Results Mean TL at age 4 was <175 mm for 54% of our study populations, median maximum age was 8 years, median PSD was 15, and median MXL5 was 229 mm TL. There were positive correlations among ML4, PSD, and MXL5 and between maximum age and MXL5. Yellow Perch metrics were not correlated with catch per effort of Walleye Sander vitreus , Largemouth Bass Micropterus nigricans , or Bluegill Lepomis macrochirus . Yellow Perch population metrics were generally not correlated to environmental variables except for ML4, which was positively correlated to shoreline development index and maximum age, which was negatively correlated to growing degree-days and lake surface area. Conclusions Many Wisconsin Yellow Perch populations we evaluated were slow growing with low size structure and limited capacity to produce fish ≥200 mm TL. Populations where PSD is ≥32 and MXL5 ≥245 mm TL may represent exceptional opportunities for anglers to catch relatively large fish and could warrant additional investigation to identify factors contributing to high size structure.

Wisconsin↗
USGS2026

Effects of turbulence-inducing baffles on passage performance of brook trout, white sucker, and sea lamprey: Implications for conservation and control

Invasive sea lamprey ( Petromyzon marinus ) control in the Great Lakes is ongoing. Installing passive selective passage structures could reduce costs, yet there is a need to evaluate such methods under realistic hydraulic conditions to inform designs. In this study, we evaluated the swimming performance of brook trout ( Salvelinus fontinalis ), white sucker ( Catostomus commersonii ), and sea lamprey under manipulated flows and baffle configurations in a 35 m flume lined with substrate preventing attachment. Using accelerated failure time models, we examined ascent distance (Dmax) under two slopes (1% and 3%) and velocities from 0.25–3.0 m s⁻¹. Responses varied by species: white sucker had the greatest Dmax, especially at 1% slope, whereas sea lamprey, despite lacking paired fins/rays, occasionally exceeded white sucker at 3% with small spoiler baffles and bare substrate. Contrary to common perception, brook trout, the only salmonid in this study, performed less well than the other two species. Across species, higher velocities impaired performance, with declines linked to energy dissipation (EDF). Findings show how hydraulic structures shape species-specific passage.

Great Lakes↗
USGS2026

Volcanoes are mighty mountains

Volcanoes are evidence of the remarkable journey of molten rock, which begins miles (kilometers) beneath our feet. What happens on magma’s ascent determines whether it erupts explosively (like Mount St. Helens on May 18, 1980), oozes lava (like Mount St. Helens during its 2004–2008 dome-building event), or cools and crystallizes underground, never to erupt at all. This two-page educational activity uses a conceptual model of a stratovolcano to connect volcanic processes with personal growth. On page 1, students explore how magma is generated and moves through the crust to form a volcano, using core concepts we can relate to: strengths, support, challenges, motivations, and goals. On page 2, students reflect on their own journeys to draw parallels between what happens at volcanoes and how personal motivations and challenges shape them, just as magma shapes volcanoes, and volcanoes transform landscapes.

General Information Product↗
USGS2026

Pre-eruptive volatiles and magma storage depth for the 2018 eruption at Mount Veniaminof, Alaska

Mount Veniaminof is a frequently active, open-system arc volcano on the Alaska Peninsula, part of the Alaska-Aleutian arc. Mount Veniaminof's September–December 2018 eruption began with small lava flows and culminated in a larger explosive event in November that produced a 450 km long continuous ash plume—one of the volcano's most significant ash-producing events in recently observed eruptions. A temporally constrained tephra record was sampled after the eruption. We present volatile element concentrations (H, C, S, Cl, F) from a total of 65 olivine-hosted melt inclusions (MIs) across six tephra layers to assess potential variations in magma chemistry throughout the course of the eruption. No variation is observed in volatile concentrations across the tephra layers, and there is no correlation between volatile concentrations and the explosivity of eruptive pulses leading to the November explosive event. H 2 O concentrations within MI suggest moderately hydrous magmas up to 2.4 wt% H 2 O and a large range in CO 2 concentrations in the MI (14–2,180 ppm) from Secondary Ion Mass Spectrometry and vapor bubble reconstructions. H 2 O and CO 2 measurements correspond to entrapment pressures up to 400 MPa (entrapment depths ∼15 km), but with modal storage around 100–200 MPa. H 2 O contents can be reconciled with previous microlite number density estimates using a polybaric storage history.

Alaska↗
USGS2026

Spontaneous combustion of metal sulfide minerals and implications for seafloor massive sulfide mining

Metal sulfide minerals are abundant phases in many environments on earth, including seafloor massive sulfide (SMS) deposits, which occur at hydrothermal vents throughout the global ocean. These deep-sea settings are currently undergoing exploration for potential future mining. Here, we describe rocks from Escanaba Trough on the southern Gorda Ridge that underwent spontaneous combustion during laboratory processing. We compared the mineralogy, composition, and thermogravimetric behavior of the combusting samples to rocks from the same location that did not combust. We then used thermodynamic analyses to evaluate the exothermic nature of different metal sulfide oxidation reactions. The combusting rocks are primarily composed of nanocrystalline marcasite pseudomorphing blades of primary pyrrhotite. These altered, nanocrystalline rocks are less stable than their primary predecessors. Typically, recrystallization decreases reactivity as minerals trend towards steady state; however, both of the combusting samples we characterized are secondary, and demonstrate the instability of this metastable intermediate phase. Further, thermodynamic calculations indicate that metal sulfide oxidation is more exothermic when oxygen serves as the oxidant, as occurs in seawater or air. The distinct mineralogy, texture, and setting of SMS deposits in the modern oceans thus suggests a greater potential for self-heating in comparison to their ancient analogues.

Scientific Reports↗
USGS2026

Geospatial Agentic Services: A framework for interoperable geospatial intelligence

Autonomous GIS uses large language models as its reasoning core to automate spatial data collection, analysis, modeling, and visualization for solving spatial problems with minimal human intervention. Often implemented through autonomous geospatial agents that work independently or collaboratively, it represents a shift from GIS as a passive software environment requiring expert operation towards systems capable of task-oriented interaction, workflow generation and increasingly autonomous spatial analysis and decision support. However, current GIS agents are often isolated and tightly coupled with specific platforms, tools, or applications, which limits their reuse and interoperability across systems and domains. In this paper, we introduce Geospatial Agentic Services, or GAS, as a service-oriented framework for publishing, discovering, invoking, and composing GIS agents as interoperable geospatial services. GAS extends traditional geospatial interoperability beyond access to data and predefined operations towards geospatial intelligence interoperability, where GIS agents function as discoverable, reusable, and collaborative service entities that encapsulate spatial knowledge and reasoning. Building on service-oriented architecture, GAS supports structured geospatial skill declarations, agentic service registry and discovery, and distributed agent orchestration. It also integrates validation, provenance, reproducibility, and governance to support transparent and trustworthy geospatial analyses. To demonstrate the framework, we present a GAS implementation and illustrate its use through common invocation modes and representative AI-orchestrated workflows. By connecting traditional geospatial service architecture with emerging agentic interoperability, GAS provides a conceptual and architectural foundation for interoperable, reusable, and scalable agentic geospatial services and workflows in the era of autonomous GIS.

Annals of GIS↗
USGS2026

Solar energy development selectively filters avian taxonomic and functional diversity across a perennial agricultural landscape

Solar energy is rapidly expanding across agricultural landscapes, yet its consequences for avian communities remain poorly understood, particularly among heterogeneous land-use matrices. In 2024 and 2025, we surveyed birds across 107 sites in New York State, including conventional solar arrays with mowing or sheep grazing to manage vegetation, solar-adjacent working lands (e.g. hayfields, pastures) and reference working lands independently located from solar arrays. We integrated diversity metrics across four trait dimensions—taxonomic, morphological, ecological and conservation status—and examined interactions between species-level abundance and traits to understand avian community responses to solar energy development. Avian species in solar sites tended to be common, non-migratory (in behaviour and wing morphology) and associated with shrubland or forest. Compared to reference working lands, bird communities in solar and solar-adjacent sites were less taxonomically diverse and were composed of fewer declining and range-restricted species. However, solar and solar-adjacent sites retained comparable diversity of intrinsic traits, suggesting that ecological function may persist despite apparent species filtering and functional reshuffling. While solar energy development can support avian communities with unique functional signatures, our findings suggest that conventional solar arrays sited on agricultural working lands in New York maintain low bird diversity and are unlikely to support conservation-priority species—such as grassland birds characterized by declining populations, migratory tendencies and open-habitat dependence. Synthesis and applications . Our study provides a pathway to leverage functional diversity to quantitatively characterize solar-associated avian communities and the ecological mechanisms that shape them. Our results suggest that meeting biodiversity conservation goals while achieving solar energy targets requires ecologically informed siting and processes, particularly across regions in which co-prioritization of conservation, agriculture and energy presents sustainability trade-offs.

New York↗
USGS2026

Stability changes after weak layer collapse: Insights from an unexpected dataset

While conducting avalanche mitigation or traveling through the backcountry, avalanche professionals sometimes experience a "whumpf": a collapse-mode crack accompanied by surface cracking that does not produce an avalanche. These whumpfs are a clear warning sign of instability in the surrounding terrain. But assessing the collapsed slope itself, if it is steep enough to avalanche, carries much more uncertainty. Can slopes that whumpf and are steep enough to slide still avalanche? The answer to this question supports avalanche mitigators and ski guides in assessing whether to open such slopes. Previous research on collapsed slopes is limited to one study conducted before tests that estimate crack propagation propensity, such as the Propagation Saw Test (PST), were developed. This work showed that weak layer shear strength decreased immediately after collapsing and then increased over time. However, no research has examined crack propagation propensity after a whumpf. Studying propagation propensity is key for assessing how whumpfs immediately affect slope stability. To improve our understanding of changes in propagation propensity following weak layer collapse, we conducted PSTs on a test slope in the hours and days after an unexpected collapse occurred on a layer of surface hoar. Two PSTs at our study site three days prior to this collapse provided an estimate of weak layer propagation propensity. PST cut lengths decreased immediately following the collapse, suggesting that the collapse increased the propagation propensity. However, over the next 4-5 hours, PST cut lengths steadily increased at our site, likely due to ongoing sintering and strengthening in the collapsed weak layer. By the end of day two, we were no longer able to initiate propagation, suggesting substantial stabilization of the weak layer. Our results support prior findings and observations suggesting that slopes may remain capable of producing avalanches immediately after a collapse but likely stabilize over the next day or two. Although this research does not provide answers about precisely when a slope becomes stable after a collapse, it does highlight uncertainties in our understanding and interpretation of the stability of slopes that have whumped.

Montana↗
USGS2026

Revisiting avalanche destructive scale and associated mass estimates

Avalanche destructive (D) size classifications are essential for forecasting, communication, and risk management, yet size estimation remains one of the more subjective elements of avalanche assessment. Practitioners typically rely on visual impressions of destructive potential, path length, and estimated mass and volume. Recent work indicates that size is often underestimated even by experienced observers, especially when based on photographs or distant observations. Although mass is central to defining destructive size, the empirical foundations of mass–size relationships have rarely been revisited, and expert variability in size assignment could be decreased if more consistent operational tools were available. We evaluated whether a simple, practitioner-focused calculation tool using slab dimensions, snow density, and snow water equivalent can provide reliable mass estimates that correspond meaningfully with existing destructive size classes. Using this tool, we estimated avalanche mass and compared the results to observer-assigned D sizes. We also simulated mass outputs using a dense flow avalanche simulation module and compared observer estimates and simple-tool outputs to recent volume-based methods for D-size classification. Across 143 well-documented dry snow avalanches from multiple avalanche climates, the size estimation tool tends to classify avalanches larger than field-based observers. We found a mean bias of 0.47 D-size units and a typical (mean absolute) disagreement of 0.56. Our results show that 95% of events landed within one whole D-class of each other and 71% within a half-class. Agreement between the simple tool mass estimates and dense flow avalanche simulations was generally strong, though discrepancies emerged in cases with substantial entrainment or complex terrain. We compared the size tool to the simulation module with entrainment (n=4) and without entrainment (n=8). With entrainment, the two methods estimate the same D-size class in 4 of 4 comparable events and 7 of 8 events without entrainment. Also, the simulation module estimates larger sizes than the observer in 7 of 8 cases without entrainment and all 4 cases with entrainment. These findings support that development of practical, mass-based tools could improve D-size consistency and emphasize the value of revisiting historical mass–size relationships. The accompanying application offers practitioners an accessible and operationally useful resource for improving D-size estimation from field observations.

Conference Paper↗