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USGS2025

Fiber-imaged supershear dynamics in the 2024 Mw 7 Mendocino Fault earthquake

Fault structure and rupture physics are deeply intertwined, and observations of this coupling are critical for understanding earthquake behavior. Rupture propagation is observable at fine scales using dense seismic networks. Fiber-optic sensing allows for long-term deployments of ultradense arrays that enable high-resolution measurements of infrequent, large earthquakes. We recorded the 2024 moment magnitude ( M w ) 7 Mendocino Fault earthquake with a nearby fiber-optic array and imaged its behavior with seismic beamforming. The rupture propagated to the east at subshear velocity; stagnated near the Mendocino Triple Junction, a zone of structural complexity; and subsequently transitioned to supershear velocity. The correlation between source physics and structure shows how lithospheric heterogeneity affects first-order characteristics of earthquake ruptures. Our results also demonstrate the potential for fiber-optic sensing to improve real-time estimation of key parameters for early warning.

California↗

USGS2024

A multidisciplinary approach that considers occurrence, geochemistry, bioavailability, and toxicity to prioritize critical minerals for environmental research

Critical minerals (or critical elements) are minerals or elements that are essential to global security and development and have supply chains vulnerable to disruption. In general, knowledge of the environmental behavior and health effects of critical elements is needed to support the development of safe and environmentally responsible supplies. This knowledge includes identifying potential consequences of increased critical element production and use, alternative critical element sources such as mine wastes, and adverse effects of critical elements on ecosystem condition and organismal health. Here we identify significant data gaps in the understanding of critical elements in surficial and aquatic environments, and the need, given the large number of commodities (50) identified on the 2022 critical minerals list for the United States, for an approach to prioritize them for study of their environmental fate and effects. We propose a multidisciplinary approach for this prioritization, considering measures of occurrence, geochemistry, bioavailability, and toxicity. We describe relatively easy-to-obtain metrics for each of these topic areas and demonstrate the utility of this integrated prioritization approach using indium and zinc as examples. This approach facilitates prioritizing research with a focus on those critical elements that are most mobile in the environment, bioavailable, toxic, or simply lacking data in these categories.

Environmental Science & Technology↗

USGS2025

Multi-scale geophysical mapping of the brine and bedrock surfaces along the Dolores River, Paradox Valley, Colorado, December 2023

Total dissolved solids derived from salt dome–sourced brine in the underlying alluvial aquifer substantially increase with distance in the reach of the Dolores River that passes through Paradox Valley in southwestern Colorado. The area has been the site of salinity control operations since the 1990s to reduce salt loading to the downstream Colorado River. Previous airborne and ground/water-based electromagnetic (EM) geophysical data have successfully mapped the top of the brine surface, albeit with relatively coarse near-surface resolution and limited spatial coverage. This present December 2023 study used ground-based high-resolution EM and passive seismic (horizontal-to-vertical spectral ratio, HVSR) tools to map in detail the depth and thickness of the brine zone in the alluvial aquifer (top of the brine down to bedrock contact) in areas immediately surrounding the Dolores River where previous airborne EM (AEM) results indicated brine within 10 m of land surface. Results indicate the deepest bedrock is generally associated with the shallowest brine and local depressions in the collapse breccia (caprock to the Paradox Formation salt) may facilitate vertical migration of brine into the alluvial aquifer. Additionally, the ground-based EM mapping corroborated general patterns in depth to brine that were observed in previous AEM results while also revealing additional detail, including suspected focused brine discharge zones to the Dolores River. A river-based survey wherein EM data, channel depth and river water–specific conductance information were collected augmented these findings and indicated specific areas on both the western and eastern sides of the river where focused brine discharge may occur. This study comprises a large-scale, ground- and water-based geophysical mapping effort, including hundreds of HVSR soundings and 100s of kilometres of EM data, which were successfully translated into digital brine and bedrock surfaces that could be incorporated into groundwater modelling efforts, future well siting or other decision-making.

Colorado↗

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

Assessing environmental drivers of denitrification in restored riverine floodplains

Restoration of impaired floodplains is an increasingly prevalent strategy for alleviating water quality concerns and reducing downstream flooding at watershed scales. Floodplains temporarily store water and slow flow velocity to promote sedimentation during overbank flooding and remove inorganic nitrogen from floodwater and groundwater via denitrification. Evaluating the impacts of different restoration strategies on denitrification can inform more strategic investments into floodplain modifications that improve water quality outcomes. Our research investigates how denitrification rates in floodplains respond to environmental factors that are actionable from an engineering perspective through design and water resources management. We seasonally measured soil denitrification enzyme activity and various environmental characteristics in 4 floodplains with different restoration design and management approaches at the confluence of the Wabash and Tippecanoe Rivers in Indiana, United States. Our results showed that denitrification rates in an agricultural floodplain were significantly lower than in restored floodplains with native vegetation. Certain soil conditions characteristic of floodplain wetlands were associated with higher denitrification, particularly elevated total nitrogen, moisture, silt, and organic matter contents. Vegetation species composition was correlated with denitrification rates. This link may reflect the direct effects of vegetation on soil conditions, such as supplying labile organic carbon, or indirect effects, such as vegetation acting as an indicator of hydrologic regime and land use. Denitrification seasonally varied, peaking in winter when nitrate supply from rivers draining agricultural watersheds in the region is also high. Substrate limitation of soil denitrification enzyme activity was most significant during the summer when overbank flooding, which replenishes soil nitrogen stocks, rarely occurs. Our findings indicate that denitrification capacity will likely be maximized in riverine floodplains that are restored as wetlands with diverse native vegetation and enhanced hydrologic connectivity. Such restoration activities promote higher denitrification rates via elevated moisture, fine sediment deposition, and soil organic matter.

Tippecanoe River, Wabash River↗

USGS2026

The value of electronic tagging and tracking studies for understanding fish–hypoxia interactions

Objective Hypoxia (i.e., low dissolved oxygen availability) is a natural phenomenon but can also be induced by human activities (e.g., nutrient enrichment from runoff). Given that dissolved oxygen is essential for aquatic life, periods of hypoxia tend to have negative consequences (e.g., sublethal disturbances, mortality) for most fishes. Extensive laboratory research has documented hypoxia thresholds and physiological and behavioral outcomes for a variety of freshwater and marine fishes and there is also an extensive body of fieldwork assessing population-level responses (e.g., survival, distribution). Yet, studying how individual fish respond to hypoxia in the wild has proved challenging; electronic tagging and tracking tools (e.g., biotelemetry, biologging) have made it easier to study individual responses to hypoxia and complement other tools like hydroacoustics that tend to focus on population-level responses. Methods We review what has been learned from contemporary studies that employ electronic tagging and tracking tools to understand how fish respond to hypoxia in the wild. Topics explored include identifying and validating hypoxia thresholds, habitat compression, connectivity, mortality, physiological and bioenergetic consequences, and extreme weather conditions. We also consider what we have learned about evaluating various management plans for hypoxia and reflect on how electronic tags have also been used in aquaculture systems and in hybrid studies that combine laboratory and field research. We highlight fishes in Lake Erie as a research narrative to demonstrate how electronic tagging and tracking have markedly improved our understanding of a longstanding hypoxia issue. Results Our synthesis revealed that electronic tagging and tracking have provided critical information on how fish respond to hypoxia in the field, revealing complex trade-offs and compensatory mechanisms as well as cryptic hypoxia-induced mortality. Beyond just illuminating space use and mortality, tags equipped with various sensors are revealing how fish deal with hypoxia in real time in terms of physiology, bioenergetics, and behavior. Conclusions As electronic tagging and tracking methods experience further innovation and are increasingly applied to understand the effects of hypoxia on fish, we expect more unanticipated findings about the effects of hypoxia on fish in all aquatic ecosystems, which will strengthen our ability to manage and mitigate hypoxia. Combining tools and approaches (e.g., lab and field) is perhaps the best way to generate comprehensive understanding.

Transactions of the American Fisheries Society↗

USGS2025

Rapid emplacement of the Keaiwa Lava Flow of 1823 from the Great Crack in the Southwest Rift Zone of Kilauea volcano

The Keaīwa Lava Flow of 1823 in the Southwest Rift Zone of Kīlauea volcano is unusual for its expansive pāhoehoe sheet flow morphology and lack of constructive vent topography, despite having a similar tholeiitic basalt composition to other lavas erupted from Kīlauea. This lava flow issued from a ∼10-km-long continuous fissure now known as the Great Crack, and has an unusually thin sheet flow morphology with margin thicknesses of ∼15–110 cm (average of 42 cm). Based on field observations of the lava flow at its fissure vent (e.g., drain-back features), we propose that the Great Crack formed, or at least significantly widened, just prior to and syn-eruptively with this 1823 eruption. The absence of pyroclastic cones or spatter ramparts indicates that the eruption consisted of a rapid outpouring of relatively degassed lava as the fissure unzipped. The rapidly moving lava flow overtopped pre-existing tumuli and scoria cones (e.g., Lava Plastered Cones) up to ∼10 m tall. Glass and whole-rock chemistry yield homogeneous compositions for the lavas erupted from the Great Crack, with glass compositions of 6.40 ± 0.10 wt% MgO and whole-rock compositions of 7.39 ± 0.07 wt% MgO. Lava pads erupted from a short western fissure system are richer in mafic minerals (e.g., olivine and clinopyroxene), and show slightly more MgO-rich whole-rock compositions (7.79 ± 0.05 wt%). MgO-in-glass thermometry on juvenile spatter yield eruption temperatures of 1153 ± 13°C that are typical of Kīlauea lavas. Thus, the extensive sheet-like lava flow morphology is not a direct consequence of unusual magmatic or rheological conditions (i.e., low viscosity). Instead, the flow morphology is associated with high effusion rates caused by sudden drainage of uprift magma as it erupted from the Great Crack. Lava flow modeling on a 2-m-resolution digital elevation model indicates that a minimum bulk effusion rate of ∼5800 m 3 /s (∼3500 m 3 /s dense rock equivalent) and a minimum flow velocity of ∼11 m/s are required for the lava flow to overcome the topography of the Lava Plastered Cones. This effusion rate is among the highest inferred for eruptions in Hawaiʻi and around the world. This study highlights a less frequent eruption style at Hawaiian volcanoes characterized by a sudden outpouring of lava from an unusual fissure system. Local eyewitness accounts indicate that the 1823 eruption was preceded by seismicity. Given the complex magmatic-volcanic-tectonic relations across Kīlauea, we speculate that the south flank could have slipped over one or more events that ultimately triggered unzipping of the Great Crack and passive release of briefly stored uprift magma. An eruption similar to 1823 at Kīlauea or Mauna Loa, with an eruptive timeframe that could be as short as an hour, with high effusion rates and rapid flow front velocities, would not easily allow for a timely response.

Hawaii↗

USGS2026

Determining Volcanic Risk in Auckland (DEVORA) Research Programme—A transdisciplinary approach to address the challenge of distributed volcanism in an urban environment

The Determining Volcanic Risk in Auckland (DEVORA) Research Programme was launched in 2008 to address the challenges associated with monogenetic volcanism in an urban setting and to enhance volcanic risk management in Tāmaki Makaurau Auckland in Aotearoa New Zealand. It is a multi-agency, increasingly transdisciplinary (defined here as research that transcends traditional disciplinary boundaries by integrating diverse types of knowledge, perspectives, and methods from academic and non-academic participants to create novel solutions to complex problems), and collaborative research program jointly led by Waipapa Taumata Rau University of Auckland and Earth Sciences New Zealand (ESNZ; formerly GNS Science), with core funding from Natural Hazards Commission Toka Tū Ake (NHC; formerly the Earthquake Commission, EQC) and Te Kaunihera o Tāmaki Makaurau Auckland Council (AC). The primary research focus of DEVORA is to investigate the geologic history, volcanic hazards, and risk posed by the basaltic intraplate Auckland Volcanic Field. Disruption from ash fall and gas from other Aotearoa New Zealand volcanoes is also considered. DEVORA’s work to explore exposure and vulnerability in Tāmaki Makaurau Auckland is also useful for assessing risks from other non-volcanic natural hazards, such as seismic and tsunami hazards. The greater Tāmaki Makaurau Auckland region has an ethnically and socio-economically diverse population of approximately 1.7 million, representing about one-third of the Aotearoa New Zealand population, and hosts critical infrastructure of national significance. The size and nature of the populace, consequential economic base, and important infrastructure within Tāmaki Makaurau Auckland mean that the effects of a volcanic eruption would be felt nationally, including through the disruption of air travel to Aotearoa New Zealand. The hazards from such an eruption could potentially affect hundreds of thousands of people, businesses, and lifelines (critical infrastructure). A considerable challenge for emergency and risk managers is the monogenetic nature of the volcanic field. It is not known where or when the next eruption will occur, how much warning we may get before an eruption, nor how an eruption and its effects might unfold. In this contribution, we highlight the concept and collaborative intent of the DEVORA Programme and show how it has evolved over the 16 years since its inception. We describe how DEVORA has unified more than 100 researchers (including more than 50 graduate students) and numerous stakeholders to address key issues facing Tāmaki Makaurau Auckland and describe how research findings are being implemented into policy and communicated to stakeholder agencies and the public. We also illustrate the broader influence of the DEVORA Programme and provide some learnings that might benefit others embarking on similar integrated projects, especially those focused on distributed volcanism in and near populated areas.

Auckland↗

USGS2026

Comparative crop yield forecasting using satellite-derived biophysical and agro-climatic predictors in Sub-Saharan Africa

Timely and accurate crop yield forecasting is central to food security early warning systems, particularly in climate-vulnerable regions. While operational forecasting frameworks commonly rely on precipitation and vegetation indices such as NDVI, their ability to provide actionable lead time remains limited. Here, we evaluate the added value of satellite-derived biophysical Essential Climate Variables (ECVs): Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation (FAPAR), for forecasting millet yield in Burkina Faso (BF) and maize yield in South Africa (ZA) and Malawi (MW). Using Random Forest models, we quantify forecast skill across the growing season at both national and sub-national scales. Results show that LAI and FAPAR provide effective forecast lead times of approximately 4 months in BF, 2 months in ZA, and up to 6 months in MW relative to harvest. At peak performance, Mean Absolute Percentage Error (MAPE) reaches 19.8% (LAI) and 23.8% (FAPAR) in BF, 12.0% and 9.8% in ZA, and 21.8% and 20.8% in MW, respectively. Across countries, biophysical parameters often outperform NDVI and precipitation, particularly in arid and semi-arid regions. At the sub-national level, LAI and FAPAR enable classification of administrative units into high and moderate-skill forecast units, revealing strong spatial heterogeneity linked to crop dominance. However, forecast skill declines where the target crop is not the dominant type, highlighting an important limitation for operational deployment. Overall, the findings suggest that satellite-derived biophysical parameters can provide earlier and more spatially resolved yield signals than commonly used predictors, with potential to improve the timeliness and effectiveness of food security early warning systems.

Remote Sensing Applications: Society and Environme↗

USGS2026

Cambrian and Ordovician stratigraphy, conodont biostratigraphy, and microfacies analysis to support 1:24,000-scale geologic mapping of the southern Lake Champlain valley, New York and Vermont

Introduction Geologic mapping in the southern Lake Champlain valley of New York and Vermont (fig. 1) has required evaluation of stratigraphic nomenclature used since the early 1900s. The paleogeography of the Cambrian and Ordovician adjacent to the Adirondack Highlands, the high-relief mountains of Proterozoic igneous and metamorphic rocks of northern New York, has impacted the lithostratigraphic succession, facies changes, and several hiatuses that occur within the package of clastic and carbonate rocks that demonstrates overall deepening consistent from the southern to northern Appalachians. The stratigraphic nomenclature used for the geologic mapping of the Cambrian and Ordovician strata of the study area is derived from evaluation of names put forth by previous workers from areas of northern New York and western Vermont. Descriptions of type localities or type sections and other criteria set forth by the North American Stratigraphic Code (North American Commission on Stratigraphic Nomenclature [NACSN], 2021) were consulted. The North American Stratigraphic Code states that lithostratigraphic units, such as the fundamental unit, the formation, be defined by lithic character and be mappable (NACSN, 2021, Article 24). However, some early workers (Walcott, 1912; Kay, 1937; Fisher and Hanson, 1951; Oxley and Kay, 1959) have defined stratigraphic units based on fossil content, which may or may not be facies dependent, and hence may not be mappable as lithostratigraphic units. Although preservation of older names takes priority in stratigraphic nomenclature (NACSN, 2021, Article 7), some do not have adequately defined stratotypes or are located a distance away with different lithologies than that in the study area. Biostratigraphy can be a helpful tool for understanding correlations and facies changes. Herein, conodont biostratigraphy is utilized to date and correlate separate lithologic units. Further, microfacies analyses of units through inspection of petrographic thin sections provide paleogeographic information that helps in understanding the genesis of geologic units.

New York, Vermont↗

USGS2024

Distinguishing natural sources from anthropogenic events in seismic data

As seismic data are increasingly used to investigate a diverse range of subsurface phenomena beyond regular fast-rupturing earthquakes (Peng and Gomberg, 2010; Beroza and Ide, 2011), it is important to acknowledge that human-generated ground vibrations may be mistaken for naturally generated subsurface processes (Larose et al., 2015; Li et al., 2018). Correct discrimination of natural processes from anthropogenic noise is especially pressing given the trend in seismic detection research toward automated algorithms and machine learning methods (Yoon et al., 2015; Kong et al., 2019;Mousavi and Beroza, 2022) and the growth in seismic data collection in new environments such as urban and industry settings (e.g., Díaz et al.,2017).

Seismological Research Letters↗

USGS2026

Northern bobwhites select for native grasses on working grazing land

Northern bobwhite ( Colinus virginianus ; bobwhite) populations have experienced an 85% decline across most of its range since the 1960s. The most drastic decreases have been in the southeastern United States where biologists attribute the decline to widespread habitat loss, including conversion of native grasslands to tall fescue ( Lolium arundinaceum ) and other exotic cool-season grass (CSG) pasture and hayfields. Including agricultural lands in conservation programs could improve habitat conditions on a regional scale. One working-lands conservation strategy involves the use of native warm-season grasses (NWSGs) rather than cool-season exotic grasses as economically viable cattle forage. To evaluate this management practice for creating bobwhite habitat, we conducted a field study on a bobwhite population in eastern Kentucky, USA, where grazed NWSG and burned NWSG fields were adjacent to exotic grazed and exotic hayed CSG fields. Between April 2019 and October 2022, we used radio telemetry to track bobwhites to evaluate resource selection at second- and third-order scales. Bobwhites used traditionally managed CSGs less than would be expected by chance at the second-order scale in both breeding and non-breeding seasons. Bobwhite use of grazed NWSG and burned NWSG was greater than would be expected by chance at the second-order scale in both breeding and non-breeding seasons. Similarly, at the third-order scale, bobwhites used CSGs less than would be expected by chance, whereas NWSGs and woody stems were used more than by chance alone. Our study suggests that bobwhites select NWSGs at multiple spatial scales despite broad-scale availability of managed exotic CSGs. Under a working-lands framework, the integration of NWSGs into working lands could create bobwhite habitat in the southeastern United States, especially if woody stems are present.

Kentucky↗

USGS2025

Evolution of permeability and strength recovery of shear fracture under hydrothermal conditions

Geothermal energy is a clean and renewable resource that depends on the ability to move water through hot rock. In many locations, the ability to move water through rock requires the presence of extensive natural or human-made systems of fractures. However, these fracture systems are influenced by a variety of complex processes that occur at the temperature and pressure conditions found in geothermal reservoirs. To make geothermal systems more efficient, it is important to understand how these fractures evolve over time in response to these processes. This study explored how fractures in rock change under high-temperature and pressure conditions, like those found in geothermal reservoirs, through laboratory experiments and numerical simulations. In general fractures, tend to close due to pressure from the surrounding rock preventing the flow of water. One set of laboratory experiments revealed that fractures in granitic rock can weaken over time at elevated temperatures. These weak fractures can then slip slowly potentially keeping the fracture open for a longer period. This study also showed that at the highest temperature examined (250 °C) large differences between the chemical composition of the rock and the fluid moving through it could improve water flow temporarily likely due to the water dissolving parts of the rock. Flow rate predicted by models shows overall good agreement with the flow rate measured in our experiments but with some long time-scale variations that may be due to mechanical wear of the fracture surface. A second set of experiments found that, over the temperature range examined, the closure of fractures was caused by brittle failure driven by high stresses at points where fracture surfaces were in contact. This result suggests that fracture closure in geothermal reservoirs could be counteracted by maintaining high pore pressures. Additionally, we also tested a new method using electrical resistance to measure fracture closure in controlled systems with high precision.

Final Technical Report↗

USGS2025

The role of bedrock circulation depth and porosity in mountain streamflow response to prolonged drought

Quantitative understanding is lacking on how the depth of active groundwater circulation in bedrock affects mountain streamflow response to a multi‐year drought. We use an integrated hydrological model to explore the sensitivity of a variety of streamflow metrics to bedrock circulation depth and porosity under a plausible extreme drought scenario lasting up to 5 years. Endmember depth versus hydraulic conductivity relationships and porosity values for fractured crystalline rock are simulated. With drought, a deeper circulation system with higher drainable porosity more effectively buffers minimum flow and significantly limits perennial stream loss in comparison to a shallow circulation system. Streamflow buffering is accomplished through extensive groundwater storage loss. However, deeper circulation systems experience prolonged recovery from drought in comparison to storage‐limited shallow systems. Research highlights the importance of characterizing the deeper bedrock hydrogeology in mountainous watersheds to better understand and predict drought impacts on stream ecosystem health and water resource sustainability.

Colorado↗

USGS2024

A robust quantitative method to distinguish runoff-generated debris flows from floods

Debris flows and floods generated by rainfall runoff occur in rocky mountainous landscapes and burned steeplands. Flow type is commonly identified post-event through interpretation of depositional structures, but these may be poorly preserved or misinterpreted. Prior research indicates that discharge magnitude is commonly amplified in debris flows relative to floods due to volumetric bulking and increased frictional resistance. Here, we use this flow amplification to develop a metric ( Q* ) to separate debris flows from floods based on the ratio of observed peak discharge to the theoretical maximum water discharge from rainfall runoff. We compile 642 observations of floods and debris flows and demonstrate that Q* distinguishes flow type to ∼92% accuracy. Q* allows for accurate identification of debris flows through simple channel cross-section surveys rather than through qualitative interpretation of deposits, and therefore should increase the performance of models and engineered structures that require accurate flow-type observations.

Geophysical Research Letters↗

USGS2026

A Lake Charr pangenome reveals highly conserved Ohnologs as drivers of phenotypic diversity

Whole-genome duplication (WGD) is hypothesized to spur evolutionary diversification by producing genome-wide duplicate gene sets (Ohnologs) that are initially functionally redundant but can diverge markedly as the effects of relaxed selection accumulate over time. However, the underlying mechanisms remain unclear, in part because genomic studies often reconstruct Ohnolog evolution over millions of years, during which subsequent mutations can obscure deep-time signals. Investigating the relationship between Ohnolog evolution and diversification on a contemporary timescale offers clearer insights. We explore this relationship in Lake Charr ( Salvelinus namaycush ), where ∼10% of genes are retained highly conserved polyploid duplicates following the Salmonid-Specific Fourth Round WGD. Using 31 chromosome-level assemblies of Lake Charr from morphologically and ecologically diverse populations, joined into a pangenome graph, we characterized 189,555 structural variants (SVs) that were significantly less likely to affect genes retained as sequence-conserved Ohnolog pairs, nuancing the hypothesis that gene redundancy, relaxed selection, and functional diversification are intertwined. However, we found that SVs affecting such conserved Ohnologs may be potent drivers of adaptive evolution. Notably, we identified a putative 938-Kb interchromosomal translocation containing 25 genes with highly conserved Ohnologs in a paralogous (but untranslocated) genomic block. This putative translocation appears to have facilitated Ohnolog divergence in ankrd11 and hp , genes putatively linked to craniofacial and lipid metabolic diversity in sympatric Lake Superior morphs. This research reveals that conserved Ohnologs previously presumed to be redundant remain a reservoir for adaptive change.

BioRxiv↗

USGS2025

Forecasting water levels using the ConvLSTM algorithm in the Everglades, USA

Forecasting water levels in complex ecosystems like wetlands can support effective water resource management, ecological conservation, and understanding surface and groundwater hydrology. Predictive models can be used to simulate the complex interactions among natural processes, hydrometeorological factors, and human activities. The Greater Everglades in the USA is a well-known example of an ecosystem where complexity has motivated adoption of machine learning algorithms in water level prediction studies. This paper aims to contribute to extending existing machine learning algorithms by integrating spatiotemporal data with deep-learning algorithms in the forecasting process. In this study, a deep-learning model is developed to predict water levels on a regional scale, covering a large area of approximately 9,138 square kilometers in the Everglades ecosystem. This model has the architecture of Convolutional Long Short-Term Memory which can deal with spatiotemporal data by capturing both spatial and temporal dependencies in the training data. The forecasting capabilities of this model (referred to as the global model) are assessed by comparing the global model to two Artificial Neural Networks developed at two different gaging stations, referred to here as local models. One local model is developed at a gaging station directly influenced by nearby water control structures, whereas the other is developed at a gaging station located farther away from these structures. By leveraging data from the Everglades Depth Estimation Network spanning from January 2002 to May 2023, the global and local models were trained to forecast water levels with a two-day lead time. Our findings suggest that both the global and local models perform with approximately the same level of accuracy, with Mean Absolute Relative Error values ranging from 0.38% to 1.4% at the selected stations. The developed global model has demonstrated strong potential as a standalone forecasting tool for the entire study area in the Everglades and could eliminate the need for developing multiple local models. This finding also highlights how machine learning can capture complex spatial and temporal relationships to generate accurate water level predictions on a regional scale.

Florida↗

USGS2025

The effects of line simplification on planform geometry

Data on maps should retain accuracy regardless of scale. Yet, as cartographic lines are generalized, there can be impacts on properties such as topology, density, and planform geometry. Here, we investigate the use of the Scale Specific Sinuosity (S3) metric (Stanislawski et al., 2023) to evaluate the effects of line simplification on planform geometry, which is the bends of streams in map view. We employ an open-source Python S3 workflow to characterize the geometry of five diverse stream channels in the United States. The original data are extracted from the U.S. Geological Survey National Hydrography Dataset 1:24,000-scale vector data (U.S. Geological Survey, 2000) (Table 1), and the simplification is done using the Visvalingam and Whyatt method (2017) with a simplification tolerance of 0.5, 1.0, 1.5, and 2.0 km. The S3 analysis is calculated at each level of simplification and S3 derivatives are generated. Derivatives include measures of sinuosity, fractal dimension, and the dominant bend wavelength. The findings show that the change in planform geometry is scale-dependent, though simplification will have little effect on straighter lines. The change becomes more apparent in complex lines as the degree of simplification aligns with the scale of the dominant bend geometries. These logical conclusions are evidence that the S3 is a useful metric for automated characterization of bend geometry regardless of line complexity.

Conference Paper↗