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Evaluating the potential of co-located non-petroleum energy resources in the Gulf Coast using play fairwayaAnalysis

Geological resources critical to the energy transition, such as sedimentary geothermal, carbon storage potential, and lithium in brines, commonly struggle for economic feasibility as stand-alone developments but can have greater viability when the potential for more than one of these resources exist within the same reservoir or stacked in different stratigraphic intervals. There may also be instances where development of one resource inhibits development of others and decisions need to be made on how to best prioritize the use of those resources in the subsurface. Subsurface data sets were analyzed and integrated to evaluate the distribution of non-petroleum energy and related resources in the onshore and nearshore U.S. Gulf Coast. Temperature, pressure, brine composition (lithium content), and reservoir quality data for thirty-four depositional units have been compiled and visualized to high-grade areas where multiple resource opportunities likely coexist. For sedimentary geothermal, possible resource areas are defined as low potential (<90°C), moderate potential (90–150°C), and high potential (>150°C). For CO 2 storage, high potential areas exhibit supercritical CO 2 conditions less than 80% of the fracture gradient. Areas with pore pressure between 80% and 100% of the fracture gradient are considered to exhibit moderate potential and areas where the fracture gradient is equal to or greater than 100% are assigned low potential. Lithium resources in brines were defined by lithium concentrations as low potential (<100ppm), moderate potential (100-200ppm), or high potential (>200ppm). Reservoir quality affects the viability of all three of these resources and is evaluated using depositional environment maps of each unit. The resulting play fairway maps can be used for regional scale screening evaluations of these resources and to identify areas of interest where more detailed, prospect-scale studies can be undertaken.

Gulf Coast

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

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

Ecotoxicology

Thickness of the Saudi Arabian crust

As part of a joint Saudi Geological Survey (SGS) and U.S. Geological Survey (USGS) project, we analyzed P-wave receiver functions from seismic stations covering most of the Kingdom of Saudi Arabia to map the thickness of the crust across the Arabia Plate. We present an update of crustal-thickness estimates and fill in gaps for the western Arabian Shield and the rifted margin at the Red Sea (the coastal plain), as well as the eastern Arabian Platform. We applied a conventional H-k stacking algorithm and included careful attention to stacking weights, two forms of sedimentary corrections for stations located on the Arabian Platform, and additional processing for noisy stations. We obtained useful results at 154 stations from 898 teleseismic events over a 2-year period from 1995–1997 (for non-SGS stations) and a 6-year period from 2008–2014 (for SGS stations). Average crustal thickness (that is, depth to the Mohorovičić discontinuity [Moho] below the surface) beneath the Red Sea coastal plain (the rift margin) is 29 kilometers (km), beneath the volcanic fields (known in Arabic as harra [plural] or harrat [singular]) is 35 km, beneath the Arabian Shield (excluding harrats) is 37 km, and beneath the Arabian Platform is 38 km. Crustal thinning appears not to extend east of the rift escarpment, suggesting uniform extension that is no broader at depth than at the surface. In contrast to some previous claims that the Arabian Platform crust is thicker than that of the Arabian Shield, we find no statistically significant difference between their whole crustal thicknesses. However, the average subsedimentary crustal thickness (that is, the crystalline crust) for stations on the Arabian Platform is 34 km, 3 km thinner than the crust of the Arabian Shield. Individual station P-wave (pressure) velocity and S-wave (shear) velocity ratios ( V P / V S ) are highly variable for the Arabia Plate, ranging from 1.60 to 1.97 and averaging 1.75, with a standard deviation of 0.07. There are no statistically significant differences between V P / V S ratios of the different geologic regions of Saudi Arabia. Similar V P / V S ratios, coupled with similar crustal thicknesses for harrats and the Arabian Shield, indicate that Cenozoic magmatism has contributed negligibly to crustal growth.

Professional Paper

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

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

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

MethodsX

Static and dynamic strain in the 1886 Charleston, South Carolina, earthquake

During the 1886 Mw 7.3 Charleston, South Carolina, earthquake, three railroads emanating from the city were exposed to severe shaking. Expansion joints in segmented railroad tracks are designed to allow railroad infrastructure to withstand a few parts in 10,000 of thermoelastic strain. We show that, in 1886, transient contractions exceeding this limiting value buckled rails, and transient extensions pulled rails apart. Calculated values for dynamic strain in the meizoseismal region are in reasonable agreement with those anticipated from the relation between strain and moment magnitude proposed by Barbour et al. (2021) and exceed estimated tectonic strain released by the earthquake by an order of magnitude. Almost all of the documented disturbances of railroad lines, including evidence for shortening of the rails, can thus be ascribed to the effects of dynamic strain changes, not static strain. Little or no damage to railroads was reported outside the estimated 10 −4 dynamic strain contour. The correspondence between 10 −3 and 2×10 −4 contours of dynamic strain and Mercalli intensity 9 and 8, anticipated from the dependence of each quantity on peak ground velocity, suggests it may be possible to use railroad damage to quantitatively estimate shaking intensity. At one location, near Rantowles, ≈20 km west of Charleston, a photograph of buckled track taken one day after the earthquake has been cited as evidence for shallow dextral slip and has long focused a search for a causal fault in this region. Photogrammetric analysis reveals that the buckle was caused by transient contraction of <10 cm with no dextral offset. Our results further weaken the evidence for faulting in the swamps and forests south of the Ashley River in 1886, hitherto motivated by the photograph and limited macroseismic evidence for high‐intensity shaking.

South Carolina

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

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

Texas

Peri-Gondwanan sediment in the Arkoma Basin derived from the north: The detrital zircon record of a uniquely concentrated non-Laurentian source signal in the late Paleozoic

During the assembly of Pangea, peri-Gondwanan terranes collided with the eastern and southern margins of Laurentia and brought with them unique detrital zircon U-Pb signatures. Discriminating between individual peri-Gondwanan terranes in the detrital record is difficult due to their similar geologic histories. However, characterization of this provenance is critical for understanding late Paleozoic sediment routing during development of Pangea. Along southeastern Laurentia, in the Arkoma Basin (present-day Arkansas and eastern Oklahoma, southeastern United States), we identified Middle Pennsylvanian (Desmoinesian) strata that exhibit a concentrated peri-Gondwanan detrital zircon signature (e.g., ca. 800–550 Ma). Although several southern peri-Gondwanan terranes (e.g., Maya, Suwannee) are closer to the Arkoma Basin, geologic data, such as predominantly north-to-south paleocurrents and proximal-to-distal facies relationships in these Desmoinesian strata, support a northern source (e.g., Ganderia, Avalonia, Meguma). Further evidence of a northern source comes from detrital zircon source mapping, which reveals the persistence of this peri-Gondwanan signal in depocenters to the north of the basin after the signal had diminished in the Arkoma Basin. To this end, bottom-up detrital zircon source modeling, source mapping, regional stratigraphy, paleocurrent data, and sandstone petrography allow us to reconstruct the evolution of this Middle Pennsylvanian (Desmoinesian) sediment pathway in the context of intraplate and plate-margin tectonic activity. This reconstruction documents processes affecting Earth’s surface (e.g., tectonics, climate) during the assembly of Pangea and describes in detail part of a dynamic continental-scale drainage system.

Geosphere

Decadal trends in the quality of groundwater used for public drinking-water supply in California, 2004–2023, California groundwater ambient monitoring and assessment program, priority basin project

This study provides a comprehensive assessment of decadal changes in the quality of groundwater used for public drinking-water supply at 444 monitoring sites across California during 2004–2023. We assessed decadal step trends in groundwater quality for 145 water-quality constituents and geochemical indicators statewide and across geographic and land-use based network groups. We evaluated the statistical significance of directional changes (predominant increase or decrease of constituent concentrations) and the magnitude of those changes across all network groups. Uranium showed the most widespread directional and high-magnitude increases of all constituents with regulatory benchmarks statewide, particularly in the agriculture-dominated Central Valley as well as urban- and desert-dominated regions of Southern California. Fluoride and perchlorate showed the most widespread directional and high-magnitude decreases of all constituents with regulatory benchmarks statewide, which were also most pronounced in Southern California. Although arsenic and nitrate did not often register significant directional changes across network groups, they showed widespread, high-magnitude changes in both directions (increase and decrease) at levels often exceeding 10 percent of respective regulatory benchmarks statewide. Triazine herbicides (atrazine and simazine) and the gasoline oxygenate methyl tert-butyl ether (MTBE) showed significant directional decreases statewide, but not at levels considered to be of high magnitude compared to respective regulatory benchmarks. We observed significant directional and high-magnitude increases of total dissolved solids (TDS) statewide, which were most pronounced in agricultural areas. Analysis of explanatory geochemical indicators indicated that prevalent statewide increases of alkalinity and calcium were the predominant components of the observed statewide increases in TDS by mass. Widespread increases in groundwater alkalinity and calcium across agricultural and urban areas may be related, in part, to warm-season irrigation and other anthropogenic factors that have shifted soil weathering dynamics over the long term. Increasing alkalinity concentrations were related to increasing uranium concentrations, particularly in areas with aquifer materials derived from granitic rocks. Conversely, increasing calcium concentrations were related to decreasing fluoride concentrations, particularly in areas where fluoride occurred naturally at elevated concentrations. Decrease of perchlorate, triazine herbicides, and MTBE are likely related to decreased anthropogenic source inputs over time and natural attenuation in aquifers.

EarthArXiv

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

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

Frontiers in Enviornmental Science

Long-term dynamics of earthquake swarms in the Yellowstone caldera

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

Idaho, Montana, Wyoming

lasertram: A Python library for time resolved analysis of laser ablation inductively coupled plasma mass spectrometry data

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) data has a wide variety of uses in the geosciences for in-situ chemical analysis of complex natural materials. Improvements to instrument capabilities and operating software have drastically reduced the time required to generate large volumes of data relative to previous methodologies. Raw data from LA-ICP-MS, however, is in counts per unit time (typically counts per second), not elemental concentrations and converting these count ratesto concentrations requires additional processing. For complex materials where the ablated volume may contain a range of material compositions, a moderate amount of user input is also required if appropriate concentrations are to be accurately calculated. In geologic materials such as glasses and minerals that potentially have numerous heterogeneities (e.g., microlites or other inclusions) within them, this is typically determiningwhether the total ablation signal should be filtered to remove these heterogeneities. This necessitates that the LA-ICP-MS data processing pipeline is one that is not automated, but is also designed to enable rapid and efficient processing of large volumes of data. Here we introduce , a Python library for the time resolved analysis of LA-ICP-MS data. We outline its mathematical theory, code structure, and provide an example of how it can be used to provide the time resolved analysis necessitated by LA-ICP-MS data of complex geologic materials. Throughout the pipeline we show how metadata and data are incrementally added to the objects created such that virtually any aspect of an experiment may be interrogated and its quality assessed. We also show, that when combined with other Python libraries for building graphical user interfaces, it can be utilized outside of a pure scripting environment. can be found at https://doi.org/10.5066/P1DZUR3Z

Applied Computing and Geosciences

Gaps in water quality modeling of hydrologic systems

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

Water

Neotectonic mapping of Puerto Rico

Puerto Rico is part of the Puerto Rico-Virgin Islands microplate, along the Caribbean–North American plate boundary between the Puerto Rico trench subduction zone and the Muertos Trough incipient subduction zone. Despite recent seismicity and geodetically constrained deformation of ~3 mm/yr of left-lateral shear across the island, Quaternary fault locations remain largely uncertain. Preservation of recent faulting in the landscape is masked by distributed faulting, high weathering rates of the tropical climate, steep topography, frequent landsliding, and extensive agriculture and urbanization along coastlines and river valleys. We present remote neotectonic mapping of historical aerial imagery from the 1930s-60s and <1-m lidar topography, integrated with field observations, to create an updated active fault map of Puerto Rico. We focus on faults that offset younger geomorphic surfaces, with ages estimated by geologic mapping, OSL and radiocarbon dating, and morphologic interpretations. We present new evidence for Quaternary activity on seven faults, including the South Lajas, Salinas, Punta Montalva, Great Southern Puerto Rico, Cerro Goden, Parguera, and San Marcos faults. We find that active faulting occurs preferentially along the southern and western coasts and does not always spatially coincide with preexisting bedrock faults, possibly reflecting partial reactivation of older faults in the modern strain field.

Puerto Rico

Uppermost Oligocene and Miocene diatom biostratigraphy of Ocean Drilling Program Sites 682 and 688 from the Peru Margin

The diatom biochronology of ODP (Ocean Drilling Program) Holes 682A and 688E provides a detailed framework for refiningMiocene diatom zonation in the East Pisco Basin of southern Peru, establishing both a nearly complete offshore reference section and a correlation tool for the fragmentary onshore vertebrate-bearing deposits. This new biostratigraphic record documents a complete succession of low latitude and/or northeastern Pacific Miocene diatom zones, with two notable exceptions: a dissolution and/or hiatus interval (*16.5–14 Ma) during the Middle Miocene Climatic Optimum and a likely earliest Miocene hiatus (*23.4–21.8 Ma). Although eastern equatorial Pacific diatom zones characterize the Upper Oligocene and Lower Miocene strata, an increased abundance of cool-water diatoms that lived during the Middle and Late Miocene allows better application of northeast Pacific diatom zones, except during the Messinian (7–6 Ma) when warm-water diatoms predominate. The effects of eustatic sea level and tectonics on depositional sequences in the EPB and in offshore cores off central Peru are discussed.

Stratigraphy

3D Dynamic rupture modeling of the 6 February 2023, Kahramanmaraş, Turkey Mw 7.8 and 7.7 earthquake doublet using early observations

The 2023 Turkey earthquake sequence involved unexpected ruptures across numerous fault segments. We present 3D dynamic rupture simulations to illuminate the complex dynamics of the earthquake doublet. Our models are constrained by observations available within days of the sequence and deliver timely, mechanically consistent explanations of the unforeseen rupture paths, diverse rupture speeds, multiple slip episodes, heterogeneous fault offsets, locally strong shaking, and fault system interactions. Our simulations link both earthquakes, matching geodetic and seismic observations and reconciling regional seismotectonics, rupture dynamics, and ground motions of a fault system represented by 10 curved dipping segments and embedded in a heterogeneous stress field. The M w 7.8 earthquake features delayed backward branching from a steeply branching splay fault, not requiring supershear speeds. The asymmetrical dynamics of the distinct, bilateral M w 7.7 earthquake are explained by heterogeneous fault strength, prestress orientation, fracture energy, and static stress changes from the previous earthquake. Our models explain the northward deviation of its eastern rupture and the minimal slip observed on the Sürgü fault. 3D dynamic rupture scenarios can elucidate unexpected observations shortly after major earthquakes, providing timely insights for data‐driven analysis and hazard assessment toward a comprehensive, physically consistent understanding of the mechanics of multifault systems.

The Seismic Record

A conceptual framework to assess post-wildfire water quality: State of the science and knowledge gaps

Wildfire substantially alters aquatic ecosystems by inducing moderate to catastrophic physical and chemical changes. However, the relations of environmental and watershed variables that drive those effects are complex. We present a Driver-Factor-Stressor-Effect (DFSE) conceptual framework to assess the current state of the science related to post-wildfire water-quality. We reviewed 64 peer-reviewed papers using the DFSE framework to identify drivers, factors, stressors, and effects associated with each study. A total of five drivers were identified and ranked according to their frequency of occurrence in the literature: atmospheric processes > fire characteristics > ecologic processes and characteristics > land surface characteristics > soil characteristics. Commonly reported stressors include increased nutrients, runoff, and sediment transport. Furthermore, although several different factors have been used at least once to explain water-quality effects, relatively few factors outside of precipitation and fire characteristics are frequently studied. We identified several gaps indicating the need for long-term monitoring, multi-factor studies, consideration of organic contaminants, consideration of groundwater, and inclusion of soil characteristics. This assessment expands on other reviews and meta-analyses by exploring causal linkages between influential variables and overall effects in post-wildfire watersheds. Information gathered from our assessment and the framework itself can be used to inform future monitoring plans and as a guide for modeling efforts focused on better understanding specific processes or to mitigate potential risks of post-wildfire water quality.

Water Resources Research

Evaluating harvest liberalization strategies on population dynamics of southern latitude temperate-breeding Canada geese

The recovery of the Canada goose ( Branta canadensis ) is one of North America's greatest conservation success stories. Today, continental abundance of temperate-breeding Canada geese (those breeding in southern Canada and lower 48 states in the United States) greatly exceeds historical levels. As a result of increased abundance, human–goose conflicts have also increased, ranging from private and agricultural property damage to human health concerns. Managers have primarily attempted to lower Canada goose populations using hunter harvest via liberalized hunting regulations (increased bag limits and total hunting days). To evaluate the effectiveness of harvest strategies for temperate-breeding Canada geese, managers need a better understanding of how liberalized hunting regulations affect population dynamics. We estimated survival and harvest probabilities, abundance, and recovery distribution of temperate-breeding Canada geese banded in Arkansas, USA, during 2005–2020. We found that adult harvest probabilities declined overall during the study and adult survival probabilities increased. Annual abundances of juvenile geese (≤1 year old) declined during the study, whereas there was no detectable trend in abundance of the adult population over time. Most Canada geese breeding in Arkansas were shot in Arkansas, indicating potential for population dynamics to be influenced largely by state-specific harvest regulations. However, our results suggest that harvest liberalization as a management tool may have limited capacity to further influence population dynamics of Canada geese. Declines in productivity and recruitment likely had a greater influence on the similar observed declines in juvenile and adult abundances, respectively, during our study. More research is needed to better understand the ecological mechanism affecting the population dynamics of Canada geese in both urban and rural environments.

Arkansas