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The development and application of a decision support system for land management in the Lake Tahoe Basin—The Land Use Simulation Model

This report describes and applies the Land Use Simulation Model (LUSM), the final modeling product for the long-term decision support project funded by the Southern Nevada Public Land Management Act and developed by the U.S. Geological Survey’s Western Geographic Science Center for the Lake Tahoe Basin. Within the context of the natural-resource management and anthropogenic issues of the basin and in an effort to advance land-use and land-cover change science, this report addresses the problem of developing the LUSM as a decision support system. It includes consideration of land-use modeling theory, fire modeling and disturbance in the wildland-urban interface, historical land-use change and its relation to active land management, hydrologic modeling and the impact of urbanization as related to the Lahontan Regional Water Quality Control Board’s recently developed Total Maximum Daily Load report for the basin, and biodiversity in urbanizing areas. The LUSM strives to inform land-management decisions in a complex regulatory environment by simulating parcel-based, land-use transitions with a stochastic, spatially constrained, agent-based model. The tool is intended to be useful for multiple purposes, including the multiagency Pathway 2007 regional planning effort, the Tahoe Regional Planning Agency (TRPA) Regional Plan Update, and complementary research endeavors and natural-resource-management efforts. The LUSM is an Internet-based, scenario-generation decision support tool for allocating retired and developed parcels over the next 20 years. Because USGS staff worked closely with TRPA staff and their “Code of Ordinances” and analyzed datasets of historical management and land-use practices, this report accomplishes the task of providing reasonable default values for a baseline scenario that can be used in the LUSM. One result from the baseline scenario for the model suggests that all vacant parcels could be allocated within 12 years. Results also include: assessment of model functionality, brief descriptions of the 7 basic output tables, assessment of the rate of change in land-use allocation pools over time, locations and amounts of the spatially explicit probabilities of land-use transitions by real estate commodity, and analysis of the state change from today’s existing land cover to potential land uses in the future. Assumptions and limitations of the model are presented. This report concludes with suggested next steps to support the continued utility of the LUSM and additional research avenues.

Nevada

Leveraging artificial intelligence and machine learning to advance Chesapeake Bay research and management: A review of status, challenges, and opportunities

The Chesapeake Bay and its watershed (hereafter “Chesapeake Bay region”) have been the focus of extensive restoration efforts for several decades. These restoration efforts are guided by the Chesapeake Bay Watershed Agreement (Chesapeake Executive Council 2014) which outlines 10 goals and 31 measurable outcomes. The Chesapeake Bay is globally recognized as a model for coastal restoration due to long-term investments in monitoring, modeling, implementation and research by the Chesapeake Bay Program (CBP) partnership. These monitoring network spans tidal and non-tidal regions and provides data across multiple scales. Artificial intelligence (AI), particularly machine-learning (ML) and deep learning (DL), has emerged as a powerful tool for analyzing large, complex datasets. These techniques have gained widespread adoption across various disciplines, including ecology, hydrology, and environmental science. In the Bay context, AI/ML is increasingly being used to explore drivers of environmental change, analyze system dynamics, and predict conditions in areas with limited monitoring. The CBP partnership, particularly its Scientific and Technical Advisory Committee (STAC), has increasingly recognized the growing role of AI/ML in watershed and estuarine management. Recent Chesapeake Community Research Symposium sessions and initiatives such as the Chesapeake Global Collaboratory highlight increasing regional momentum to apply big data and AI/ML for environmental solutions. Together, these developments underscore the timely need to explore how AI/ML can help advance Chesapeake Bay restoration and management. This STAC workshop, titled “Leveraging Artificial Intelligence and Machine learning to Advance Chesapeake Bay Research and Management: A review of status, challenges, and opportunities,” was held from February 24-25, 2025, in Edgewater, Maryland to bring together over 50 federal, state, and academic scientists and partners to synthesize the current state of AI/ML applications and identify research gaps in Chesapeake Bay research and management. The workshop focused on three main objectives: 1. Summarize recent AI/ML applications and lessons learned in both tidal and nontidal areas of the Chesapeake Bay region. 2. Identify challenges and gaps in applying AI/ML approaches to Chesapeake Bay data. Such challenges and gaps may include data limitations, harmonization issues, ineffective communication of AI/ML insights, and a lack of coordination among research and management institutions. 3. Develop recommendations and identify opportunities for leveraging AI/ML to address issues across the Chesapeake Bay region. Key areas of focus may include generating new information to support watershed management, delivering AI/MLgenerated insights to managers in a clear and actionable way, and fostering greater collaboration among stakeholders within the CBP Partnership. Workshop participants engaged in science presentations and breakout sessions to develop recommendations for advancing the integration of AI/ML techniques into research and management across the Chesapeake Bay region. By synthesizing current applications, identifying challenges, and exploring new opportunities, the workshop has provided valuable insights and recommendations for better leveraging AI/ML approaches to support the success of Bay restoration efforts. Together, these recommendations provide a roadmap for enhancing data-driven, science-based decision making aligned with the goals and outcomes of the Chesapeake Bay Watershed Agreement.

Delaware, Maryland, Virginia

U.S. mineral supply chain security in the age of pandemics and trade wars

Modern technology makes use of numerous mineral commodities whose production is concentrated in a few countries. New research identifies the commodities whose supply disruption poses the greatest risk to the manufacturing sector. While the analysis is applied to the U.S. manufacturing sector, the principles are equally applicable to other economies heavily reliant on imported mineral materials.

The Science Breaker

Capacity assessment for Earth Monitoring, Analysis, and Prediction (EarthMAP) and future integrated monitoring and predictive science at the U.S. Geological Survey

Executive Summary Managers of our Nation’s resources face unprecedented challenges driven by the convergence of increasing, competing societal demands and a changing climate that affects the stability, vulnerability, and predictability of those resources. To help meet these challenges, the scientific community must take advantage of all available technologies, data, and integrative Earth systems modeling capacity to better inform resource and risk management decisions. This is the overarching goal of the U.S. Geological Survey (USGS) Earth Monitoring, Analysis, and Prediction (EarthMAP) vision: “By 2030, the USGS will deliver well integrated observations and predictions of the future state of natural systems—water, ecosystems, energy, minerals, hazards—at regional and national scales, working primarily with federal, state, and academic partners to develop and operate the capability” (U.S. Geological Survey, 2021). Providing more integrated Earth systems science and actionable information to decision makers, stakeholders, and the public requires a better understanding of the depth and distribution of existing capacity (capabilities, tools, and techniques) across the Bureau. Identifying existing capacity is also a critical first step toward gap analysis and targeted investments to increase capacity over time. The USGS formed a Capacity Assessment Team (CAT) and charged it with (1) conducting a Request for Information (RFI) to identify existing USGS expertise and activities supportive of integrated and predictive science to inform decision making, (2) developing a strategy and proof-of-concept for a continuously updated capacity assessment capability, and (3) identifying lessons learned to inform development of best practices for future capacity assessment efforts. The RFI took the form of a survey, with content guided by the science and technology needs identified in a USGS report titled “Grand Challenges for Integrated U.S. Geological Survey Science—A Workshop Report” (Jenni and others, 2017). The 44-question survey provided respondents the ability to rate their level of experience with a suite of priority disciplines, analysis and modeling approaches, technologies, and stakeholder engagement strategies and to enter optional narrative text for supporting context. An introductory portion focused on general science capacity assessment, followed by three sections targeting capabilities related to the foundational components of EarthMAP: (1) data and information integration, (2) integrated predictive science, and (3) actionable information. The survey results provided a high-level snapshot of USGS capacity in the targeted areas. Respondents (1,035 individuals) represented approximately 13 percent of the USGS across all mission areas and regions. Seventy-four percent of the respondents held a science-focused position title and the remainder had position titles in information technology, computer science, management, administrative, or other (contractors, volunteers, emeritus, and unknown). To provide greater insight into respondent capabilities and activities, information from the U.S. Department of the Interior and USGS enterprise information systems were used to further characterize topical expertise and organizational associations of survey respondents. To address the ongoing need to assess the Bureau’s capacity to address integrated predictive science priorities, the CAT developed a software-based proof-of-concept called the Integrated Science Assessment Information Database (iSAID) for assembling various information sources together toward making the full extent of USGS capabilities and scientific assets available for routine capacity assessment. This proof-of-concept is intended to serve as a catalyst for further development. The process of implementing the EarthMAP capacity assessment survey, analyzing survey responses, and developing the proof-of-concept resulted in lessons learned, findings, and recommendations. Example scenarios throughout the report demonstrate how capacity assessment data can inform science planning. Three overarching findings and recommendations are: (1) Finding: Capacity is limited in some critical disciplines, skills, and technology applications, but “sufficient” depends on the question and the need relative to availability at a given point in time. Recommendation: Develop an on-demand capacity assessment framework that enables rapid identification and evaluation of existing and available expertise to support decision needs as they arise. (2) Finding: Institutional barriers and lack of awareness constrain the ability of USGS staff to adopt new technologies, collaborate across administrative boundaries, and deliver actionable information to stakeholders in a timely manner. However, these barriers are not universally experienced. Recommendation: Pursue more targeted inquiries to clarify which institutional barriers are obstructing the adoption of new technologies and approaches or the sharing of expertise and equipment across organizational and regional boundaries. These inquiries should inform USGS leadership, mission areas, and regions whether policies can be revised or whether a lack of understanding is creating perceived obstacles. Highlight cases when staff have successfully adopted new technologies and approaches to advance EarthMAP priorities and provide actionable information in a timely manner to spread awareness of how perceived obstacles can be navigated and overcome when appropriate. (3) Finding: Examples of people and projects integrating across disciplines and scales and applying advanced approaches to meet complex stakeholder needs exist. Such examples provide transfer value across the spectrum from approach to decision making. Many projects, already underway, appear to meet elements of the EarthMAP vision, and the USGS has people who can provide leadership in multiple types of specific integrated science efforts. Recommendation: Use these findings as a starting point for near-term strategic planning for integrated science. Highlight, incentivize, and build on existing interdisciplinary predictive science and information delivery activities across the USGS to advance toward further realization of an EarthMAP capacity. The CAT efforts to develop and assess existing USGS capacity to advance the EarthMAP vision revealed a fundamental challenge for not only this effort but any effort to assess existing capacity: A considerable amount of thought, time, and effort is required to survey and assess capabilities and tools available to support a given need, yet best results are still likely to provide an incomplete assessment. To better meet the frequent need to assess capabilities, tools, products, and projects that address an expressed strategic priority, the CAT proposes the concept of an on-demand capacity assessment framework supported by a software package that dynamically pulls and integrates information from existing USGS information systems and public domain registries. Although existing USGS enterprise information systems currently lack the structure, cross-system consistency, interoperability, and stability to support a continuously updated capacity assessment capability, we identify reasonable near-term steps to improve the utility of information gathered on expertise and project capacity and to improve the consistency and completeness of information and the ability of USGS systems to share that information. The ability to search and characterize this information will make future assessments of capacity faster, more complete, more efficient, and more targeted. This approach would grow the Bureau’s capacity knowledge over time, iteratively improving the ability to access, leverage, and synthesize existing capabilities and assets as well as identify and fill critical gaps. The greatest promise for developing integrated science could lie in linking across existing projects and expertise to create a multi-project capacity for addressing large, complex environmental issues.

Open-File Report

Documentation of the U.S. Geological Survey Oceanographic time-series measurement database

The U.S. Geological Survey (USGS) Oceanographic Time-Series Measurement Database contains oceanographic observations made as part of studies designed to increase understanding of sediment transport processes and associated dynamics. Analysis of these data has contributed to more accurate prediction of the movement and fate of sediments and other suspended materials in the coastal ocean. The measurements were collected primarily by investigators at the USGS Woods Hole Coastal and Marine Science Center (WHCMSC) and colleagues, beginning in 1975. Most of the field experiments were carried out on the U.S. continental shelf and slope. This report describes the instrumentation and platforms used to make the measurements; the methods used to process, apply quality-control criteria, and archive the data; the data storage format, and how the data are released and distributed. The report also includes instructions on how to access the data from the online database at http://stellwagen.er.usgs.gov/ . As of 2016, the database contains about 5,000 files, which may include observations of current velocity, wave statistics, ocean temperature, conductivity, pressure, and light transmission at one or more depths over some duration of time.

Open-File Report

The principle of superposition and its application in ground-water hydraulics

The principle of superposition, a powerful methematical technique for analyzing certain types of complex problems in many areas of science and technology, has important application in ground-water hydraulics and modeling of ground-water systems. The principle of superposition states that solutions to individual problems can be added together to obtain solutions to complex problems. This principle applies to linear systems governed by linear differential equations. This report introduces the principle of superposition as it applies to groundwater hydrology and provides background information, discussion, illustrative problems with solutions, and problems to be solved by the reader. (USGS)

Open-File Report

Resource assessments, geologic deposit models, and offshore minerals with an example of heavy-mineral sands

A resource assessment method for offshore minerals based on descriptive and grade-tonnage models is proposed. Historical development and applications of this method are summarized. Based on this approach, descriptive and quantitative deposit models for strand-line titanium placer deposits have been developed. Descriptive statistics were also computed using the worldwide deposit data set upon which the grade-tonnage models are based. Certain guidelines and limitations in applying onshore titanium deposit models to offshore assessment and exploration must, however, be observed. The descriptive model points out the specific features of strandline titanium placer deposits which can be of use in selection of areas for exploration; the grade-tonnage models display the expected size distribution for this type of deposit. Used with an estimate of expected number of deposits, this information can be applied to quantify probable values associated with deposits of this type within a given area.

NATO Science Series

Refining the earthquake history of south-central Alaska through lake records

The Alaska–Aleutian subduction zone (AASZ) is one of the world's most seismically active plate boundaries and the source of the 1964 M w 9.2 Great Alaska earthquake–the second largest instrumentally recorded earthquake in the world. Understanding the nature and frequency of such earthquakes is necessary for seismic and tsunami hazard assessment, but instrumental and historical records that span less than 150 years are too short to allow a statistically reliable analysis of earthquake recurrence times. This calls for studies of evidence of past earthquakes, extending the earthquake catalog further back in time. Subduction-zone paleoseismology in south-central Alaska is predominantly based on coastal evidence of land-level changes and tsunamis generated by megathrust earthquakes and preserved in the geological record. A complementary approach is lacustrine paleoseismology, which is still a relatively young discipline in Alaska. However, globally, lake basins are well-established high-resolution and continuous recorders of paleoseismic activity along subduction zones, relying on the identification of underwater landslide deposits and turbidites generated by seismic shaking. As a result, lake basins not only register ground shaking from megathrust earthquakes, but also from intraslab and crustal earthquakes, which are typically not accompanied by significant land-level changes. In this review paper, we combine coastal and lacustrine paleoseismology approaches to refine the south-central Alaskan earthquake history by comparing the paleoseismic records from two lakes (i.e., Eklutna Lake, located in the Chugach Mountain Range, and Skilak Lake, situated on the Kenai Peninsula) with the coastal and crustal earthquake catalog in Alaska. The resulting age ranges of all known megathrust earthquakes involving the Alaskan megathrust between the Kodiak and Prince William Sound (PWS) sections are more precise and accurate for the last 1.3 kyrs BP than the previously published age ranges from coastal records. As a result, this study supports the following key conclusions: (1) The 1964 CE earthquake was an exceptionally strong and unique event in the last 2000 years, rupturing the PWS, Kenai, Barren Islands, and Kodiak sections simultaneously. (2) The high-resolution and seasonal markings of the varved lake records now disentangle for the first time closely timed earthquakes, which was not possible based on the coastal evidence alone. (3) No persistent megathrust rupture boundaries exist. So, the possibility of a full rupture of the entire eastern AASZ, from PWS to Semidi cannot be excluded. (4) The rupture pattern in the eastern AASZ reveals superimposed cycles of multi-asperity ruptures (1964 earthquake) and clustered complementary partial ruptures, or rupture cascades. (5) The PWS section hosts the largest asperity in the eastern AASZ. (6) The shaking record of megathrust earthquakes indicates a time-dependent (quasiperiodic) behavior for the study area, but the observation of complementary clusters means that the hazards will not drop to zero but instead may even increase for a neighboring section. (7) The time-independent behavior of intraplate earthquakes implies that the intraslab hazard did not decrease following the 2016 and 2018 earthquakes. This study utilizes an integrated approach for subduction zone paleoseismology as a solution for unraveling recurrence and rupture patterns in Alaska, which can be applied worldwide.

Alaska

Prevalence of neonicotinoids and sulfoxaflor in alluvial aquifers in a high corn and soybean producing region of the Midwestern United States

Neonicotinoids have been previously detected in Iowa surface waters, but less is known regarding their occurrence in groundwater. To help fill this research gap, a groundwater study was conducted in eastern Iowa and southeastern Minnesota, a corn and soybean producing area with known heavy neonicotinoid use. Neonicotinoids were studied in alluvial aquifers, a hydrogeologic setting known to be vulnerable to surface-applied contaminants. Groundwater samples were analyzed from 40 wells for six neonicotinoid compounds (acetamiprid, clothianidin , dinotefuran, imidacloprid, thiacloprid, thiamethoxam), and sulfoxaflor. Samples were analyzed using liquid chromatography tandem mass spectrometry (LC/MS/MS) with both direct aqueous injection and solid phase extraction methods. Neonicotinoids were prevalent in the alluvial aquifers with 73% of the wells having at least one neonicotinoid detection. Clothianidin (68%, max: 391.7 ng/L) was the most commonly detected, followed by imidacloprid (43%, max: 6.7 ng/L) and thiamethoxam (3%, max: 0.2 ng/L). Acetamiprid, dinotefuran, sulfoxaflor, and thiacloprid were not detected during the study. The solid phase extraction method was more sensitive than direct aqueous injection, where only clothianidin detected in 23% of samples. SPE is the preferred method for detecting low concentrations of hydrophilic pesticides in water. This study documented that the combination of heavy chemical use overlying a hydrogeologic setting vulnerable to surface applied contaminants leads to transport of neonicotinoids into an important groundwater resource.

Iowa

Do two wrongs make a right? Persistent uncertainties regarding environmental selenium-mercury interactions

Mercury (Hg) is a pervasive environmental pollutant and contaminant of concern for both people and wildlife that has been a focus of environmental remediation efforts for decades. A growing body of literature has motivated calls for revising Hg consumption advisories to co-consider selenium (Se) levels in seafood and implies that remediating aquatic ecosystems with ecosystem-scale Se additions could be a robust solution to Hg contamination. Provided that elevated Se concentrations are also known toxicological threats to aquatic animals, we performed a literature search to evaluate the strength of evidence supporting three assertions underpinning the ameliorating benefits of Se: (1) dietary Se reduces MeHg toxicity in consumers; (2) environmental Se reduces Hg bioaccumulation and biomagnification in aquatic food webs; and (3) Se inhibits Hg bioavailability to, and/or methylmercury production by, microbial communities. Limited or ambiguous support for each criterion indicates that many scientific uncertainties and gaps remain regarding Se mediation of Hg behavior and toxicity in abiotic and biotic compartments. Significantly more information is needed to provide a strong scientific basis for modifying current fish consumption advisories on the basis of Se:Hg ratios or for applying Se amendments to remediate Hg-contaminated ecosystems.

Environmental Science and Technology

Amino acid specific stable nitrogen isotope values in avian tissues: Insights from captive American kestrels and wild herring gulls

Through laboratory and field studies, the utility of amino acid compound-specific nitrogen isotope analysis (AA-CSIA) in avian studies is investigated. Captive American kestrels ( Falco sparverius ) were fed an isotopically characterized diet and patterns in δ 15 N values of amino acids (AAs) were compared to those in their tissues (muscle and red blood cells) and food. Based upon nitrogen isotope discrimination between diet and kestrel tissues, AAs could mostly be categorized as source AAs (retaining baseline δ 15 N values) and trophic AAs (showing 15 N enrichment). Trophic discrimination factors based upon the source (phenylalanine, Phe) and trophic (glutamic acid, Glu) AAs were 4.1 (muscle) and 5.4 (red blood cells), lower than those reported for metazoan invertebrates. In a field study involving omnivorous herring gulls ( Larus argentatus smithsonianus ), egg AA isotopic patterns largely retained those observed in the laying female’s tissues (muscle, red blood cells, and liver). Realistic estimates of gull trophic position were obtained using bird Glu and Phe δ 15 N values combined with β values (difference in Glu and Phe δ 15 N in primary producers) for aquatic and terrestrial food webs. Egg fatty acids were used to weight β values for proportions of aquatic and terrestrial food in gull diets. This novel approach can be applied to generalist species that feed across ecosystem boundaries.

Environmental Science & Technology

Hydrological controls on methylmercury distribution and flux in a tidal marsh

The San Francisco Estuary, California, contains mercury (Hg) contamination originating from historical regional gold and Hg mining operations. We measured hydrological and geochemical variables in a tidal marsh of the Palo Alto Baylands Nature Preserve to determine the sources, location, and magnitude of hydrological fluxes of methylmercury (MeHg), a bioavailable Hg species of ecological and health concern. Based on measured concentrations and detailed finite-element simulation of coupled surface water and saturated-unsaturated groundwater flow, we found pore water MeHg was concentrated in unsaturated pockets that persisted over tidal cycles. These pockets, occurring over 16% of the marsh plain area, corresponded to the marsh root zone. Groundwater discharge (e.g., exfiltration) to the tidal channel represented a significant source of MeHg during low tide. We found that nonchannelized flow accounted for up to 20% of the MeHg flux to the estuary. The estimated net flux of filter-passing (0.45 μm) MeHg toward estuary was 10 ± 5 ng m –2 day –1 during a single 12-h tidal cycle, suggesting an annual MeHg load of 1.17 ± 0.58 kg when the estimated flux was applied to present tidal marshes and planned marsh restorations throughout the San Francisco Estuary.

Environmental Science & Technology

Use of the smeltCam as an efficient fish sampling alternative within the San Francisco Estuary

Resource managers often rely on long-term monitoring surveys to detect trends in biological data. However, no survey gear is 100% efficient, and many sources of bias can be responsible for detecting or not detecting biological trends. The SmeltCam is an imaging apparatus developed as a potential sampling alternative to long-term trawling gear surveys within the San Francisco Estuary, California, to reduce handling stress on sensitive species like the Delta Smelt ( Hypomesus transpacificus ). Although believed to be a reliable alternative to closed cod-end trawling surveys, no formal test of sampling efficiency has been implemented using the SmeltCam. We used a paired deployment of the SmeltCam and a conventional closed cod-end trawl within the Napa River and San Pablo Bay, a Bayesian binomial N -mixture model, and data simulations to determine the sampling efficiency of both deployed gear types to capture a Delta Smelt surrogate (Northern Anchovy, Engraulis mordax ) and to test potential bias in our modeling framework. We found that retention efficiency—a component of detection efficiency that estimates the probability a fish is retained by the gear, conditional on gear contact—was slightly higher using the SmeltCam (mean = 0.58) than the conventional trawl (mean = 0.47, Probability SmeltCam retention efficiency > trawl retention efficiency = 94%). We also found turbidity did not affect the SmeltCam’s retention efficiency, although total fish density during an individual tow improved the trawl’s retention efficiency. Simulations also showed the binomial model was accurate when model assumptions were met. Collectively, our results suggest the SmeltCam to be a reliable alternative to sampling with conventional trawling gear, but future tests are needed to confirm whether the SmeltCam is as reliable when applied to taxa other than Northern Anchovy over a greater range of conditions.

California

The United States Geological Survey Science Data Lifecycle Model

U.S. Geological Survey (USGS) data represent corporate assets with potential value beyond any immediate research use, and therefore need to be accounted for and properly managed throughout their lifecycle. Recognizing these motives, a USGS team developed a Science Data Lifecycle Model (SDLM) as a high-level view of data—from conception through preservation and sharing—to illustrate how data management activities relate to project workflows, and to assist with understanding the expectations of proper data management. In applying the Model to research activities, USGS scientists can ensure that data products will be well-described, preserved, accessible, and fit for re-use. The Model also serves as a structure to help the USGS evaluate and improve policies and practices for managing scientific data, and to identify areas in which new tools and standards are needed.

Open-File Report

Review and update of the applications of organic petrology: Part 1, geological applications

Organic petrology developed as coal petrology at the beginning of the 20th century dedicated mainly to the study of coals because of their utilization in industry. Coal petrology was then considered a branch of coal science. Later, with the development of specialized nomenclature, classification of coal components, and the standardization and improvement of analytical (microscopical) methods, this discipline expanded in interests and name, becoming organic petrology. Organic petrology carries a broader context, being as well a tool applied in the study of dispersed organic matter in sedimentary rocks due to its importance in exploration for fossil fuel resources. At present, organic petrology is a discipline widely recognized for its role in fundamental and applied research with respect to both coal utilization and in geosciences. Throughout the 20th century several important monographs have been published on the discipline of organic petrology, including “Stach's textbook of coal petrology” (1st edition 1935, 2nd 1975, 3rd 1982), updated as the more general “Organic petrology” by Taylor et al. (1998). More recently, the text “Applied coal petrology: the role of petrology in coal utilization” was published by Suárez-Ruiz and Crelling (2008). This review is the first in a two-part review series that describes and updates the role of organic petrology in geosciences. A second part complementing this one and focused on the applications of organic petrology to other scientific fields will follow.

International Journal of Coal Geology

Lakes as paleoseismic records in a seismically-active, low-relief area (Rieti Basin, central Italy)

Small lakes in low relief areas are atypical candidates for studies on paleoseismicity, but their sediments can contain seismically induced event layers (seismites) generated through strong ground shaking, sediment transport, hydrological reorganization and/or changes in groundwater chemistry and flow. Lakes Lungo and Ripasottile are shallow lakes (<10m deep) located in the tectonically active Rieti Basin in the central Apennines, Italy, where strong normal faulting earthquakes (Mw 6.5 to 7.0) regularly occur. Sediment cores from these lakes provide paleoseismic indicators for the past ~1000 years. Sedimentological and geochemical analysis reveals four event layers identified in both lakes that correspond with documented large-scale earthquakes in 1298, 1349, 1639, and 1703 AD. Chronological correlation between earthquakes and possible seismites is reliable because of the unusually high resolution of sediment dating available for the studied cores. The common physical structure is a physically homogenous bed (homogenite) of re-suspended sediment consisting of a denser, high magnetic susceptibility (MS) clastic base, with organic matter concentrated above. Chemical signatures are associated with some event layers and may represent abrupt or transient shifts to a groundwater-dominated system, or permanent changes in groundwater flow and/or spring discharge. Excursions in δ13Corg may represent disruptions or changes in carbon source. Not all event layers show the same features, a result attributed to differences in seismic processes as well as the lake attributes, and anthropogenic modification. The observations made here may provide a new means of detecting paleoseismicity and may be applied to other low relief lakes in seismically active areas.

Rieti Basin

OpenCLC: An open-source software tool for similarity assessment of linear hydrographic features

The National Hydrography Dataset (NHD) is a foundational geospatial data source in the United States that enables extensive and diverse environmental research and supports decision-making in numerous contexts. However, the NHD requires regular validation and update given possible inconsistent initial collection and hydrographic changes. Furthermore, systems or tools that use NHD data must manage regular updates that occur within the high-resolution version of the NHD (NHD HR). This research contributes to filling this gap by establishing an open-source software tool named OpenCLC, which automatically identifies matching and mismatching line features between two sets of hydrographic flowlines. Aside from identifying differences among two version of NHD lines, results can be applied to improve the quality of NHD HR content. OpenCLC significantly outperforms the best available commercial off-the-shelf software in computational scalability, and it is made widely available as part of the CyberGIS Toolkit to benefit broad environmental and geospatial science communities.

SoftwareX

Bovine tuberculosis management in northwest Minnesota and implications of the Risk Information Seeking and Processing (RISP) model for wildlife disease management

Bovine tuberculosis (bTB) is an infectious, zoonotic disease caused by Mycobacterium bovis that can spread between domestic and wild animals, as well as to humans. The disease is characterized by the progressive development of lesions that compromise the victim's lungs and lymph system. The disease was first identified in northwest Minnesota in both cattle and white-tailed deer ( Odocoileus virginianus ) in 2005. Due to its risks to human and animal health, bTB has numerous implications related to population management, policy outcomes, stakeholder relations, and economic impacts. When dealing with complicated risks, like bTB, individuals often seek out and process information as a method to learn about, and cope, with the risk. We developed a questionnaire that adapted components of the Risk Information Seeking and Processing (RISP) model and surveyed northwest Minnesota deer hunters. Our objectives were to better understand how stakeholders perceive and act on information regarding disease management in wildlife and to understand the utility of the RISP model for such management contexts. We drew a random proportional sample of licensed deer hunters ( n = 2100) from the area affected by bTB and conducted a multi-contact mail survey. We found that 43% of the variability in the information-seeking behaviors of respondents was explained by demographics, hunting importance, personal risk perceptions, attitudes, and subjective norms. However, these results are largely attributable to the factors in the RISP model encompassed by components of the Theory of Planned Behavior (i.e., attitudes, subjective norms, perceived behavioral control, and behavioral intentions). This information can help managers contextualize individuals' perceived risks to better frame communication efforts to address stakeholder concerns and develop best practices for disease communication. While the state of Minnesota is currently considered free of bTB, future outbreaks remain possible in Minnesota and elsewhere. Understanding the key factors in the processes through which deer hunters seek out information pertaining to the disease can help managers collect the data necessary to aid decisions about desired future management outcomes. In addition, testing RISP model performance in applied research improves its future use across a broad spectrum of topics throughout veterinary disease management.

Minnesota