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At least 127 records · Page 7Linked to original sources
USGS2008

Restoration of Circum-Arctic Upper Jurassic source rock paleolatitude based on crude oil geochemistry

Tectonic geochemical paleolatitude (TGP) models were developed to predict the paleolatitude of petroleum source rock from the geochemical composition of crude oil. The results validate studies designed to reconstruct ancient source rock depositional environments using oil chemistry and tectonic reconstruction of paleogeography from coordinates of the present day collection site. TGP models can also be used to corroborate tectonic paleolatitude in cases where the predicted paleogeography conflicts with the depositional setting predicted by the oil chemistry, or to predict paleolatitude when the present day collection locality is far removed from the source rock, as might occur due to long distance subsurface migration or transport of tarballs by ocean currents. Biomarker and stable carbon isotope ratios were measured for 496 crude oil samples inferred to originate from Upper Jurassic source rock in West Siberia, the North Sea and offshore Labrador. First, a unique, multi-tiered chemometric (multivariate statistics) decision tree was used to classify these samples into seven oil families and infer the type of organic matter, lithology and depositional environment of each organofacies of source rock [Peters, K.E., Ramos, L.S., Zumberge, J.E., Valin, Z.C., Scotese, C.R., Gautier, D.L., 2007. Circum-Arctic petroleum systems identified using decision-tree chemometrics. American Association of Petroleum Geologists Bulletin 91, 877-913]. Second, present day geographic locations for each sample were used to restore the tectonic paleolatitude of the source rock during Late Jurassic time (???150 Ma). Third, partial least squares regression (PLSR) was used to construct linear TGP models that relate tectonic and geochemical paleolatitude, where the latter is based on 19 source-related biomarker and isotope ratios for each oil family. The TGP models were calibrated using 70% of the samples in each family and the remaining 30% of samples were used for model validation. Positive relationships exist between tectonic and geochemical paleolatitude for each family. Standard error of prediction for geochemical paleolatitude ranges from 0.9?? to 2.6?? of tectonic paleolatitude, which translates to a relative standard error of prediction in the range 1.5-4.8%. The results suggest that the observed effect of source rock paleolatitude on crude oil composition is caused by (i) stable carbon isotope fractionation during photosynthetic fixation of carbon and (ii) species diversity at different latitudes during Late Jurassic time. ?? 2008 Elsevier Ltd. All rights reserved.

Organic Geochemistry↗
USGS2001

Coastline complexity: A parameter for functional classification of coastal environments

To understand the role of the world's coastal zone (CZ) in global biogeochemical fluxes (particularly those of carbon, nitrogen, phosphorus, and sediments) we must generalise from a limited number of observations associated with a few well-studied coastal systems to the global scale. Global generalisation must be based on globally available data and on robust techniques for classification and upscaling. These requirements impose severe constraints on the set of variables that can be used to extract information about local CZ functions such as advective and metabolic fluxes, and differences resulting from changes in biotic communities. Coastal complexity (plan-view tortuosity of the coastline) is a potentially useful parameter, since it interacts strongly with both marine and terrestrial forcing functions to determine coastal energy regimes and water residence times, and since 'open' vs. 'sheltered' categories are important components of most coastal habitat classification schemes. This study employs the World Vector Shoreline (WVS) dataset, originally developed at a scale of 1:250 000. Coastline complexity measures are generated using a modification of the Angle Measurement Technique (AMT), in which the basic measurement is the angle between two lines of specified length drawn from a selected point to the closest points of intersection with the coastline. Repetition of these measurements for different lengths at the same point yields a distribution of angles descriptive of the extent and scale of complexity in the vicinity of that point; repetition of the process at different points on the coast provides a basis for comparing both the extent and the characteristic scale of coastline variation along different reaches of the coast. The coast of northwestern Mexico (Baja California and the Gulf of California) was used as a case study for initial development and testing of the method. The characteristic angle distribution plots generated by the AMT analysis were clustered using LOICZVIEW, a high dimensionality clustering routine developed for large-scale coastal classification studies. The results show distinctive differences in coastal environments that have the potential for interpretation in terms of both biotic and hydrogeochemical environments, and that can be related to the resolution limits and uncertainties of the shoreline data used. These objective, quantitative measures of coastal complexity as a function of scale can be further developed and combined with other data sets to provide a key component of functional classification of coastal environments. ?? 2001 Elsevier Science B.V. All rights reserved.

Conference Paper↗
USGS2005

Can superior natural amenities create high-quality employment opportunities? The case of nonconsumptive river recreation in central Idaho

Central Idaho has superior environmental amenities, as evidenced by exceptionally high-value tourism, such as guided whitewater rafting. The focus of our study concerns the attainment of high-quality jobs in a high-quality natural environment. We estimate cumulative wage rate effects unique to nonconsumptive river recreation in central Idaho for comparison with other sectors. The cumulative effects are based on a detailed survey of recreation spending and a modified synthesized input–output model. Cumulative wage rate effects support using the abundance of environmental amenities to expand and attract high-wage, environmentally sensitive firms, as opposed to expanded tourism to improve employment quality.

Society and Natural Resources↗
USGS2022

Long-term ocean observing for international capacity development around tsunami early warning

The 2004 magnitude (M) 9.1 Sumatra-Andaman Islands earthquake in the Indian Ocean triggered the deadliest tsunami ever, killing more than 230,000 people. In response, the United Nations Educational, Scientific, and Cultural Organization (UNESCO) established three additional Intergovernmental Coordination Groups (ICGs) for the Tsunami and Other Coastal Hazards Early Warning System: for the Caribbean and Adjacent Regions (ICG/CARIBE-EWS), for the Indian Ocean, and for the Northeastern Atlantic, Mediterranean, and Connected Seas. Along with the ICG for the Pacific Ocean, which was established in 1965, one of the goals of the new ICGs was to improve earthquake and tsunami monitoring and early warning. This need was further demonstrated by the 2011 Great East Japan (Tōhoku-oki) earthquake and tsunami, which killed more than 20,000 people, and other destructive tsunamis that occurred in the Solomon Islands, Samoa, Tonga, Chile, Indonesia, and Peru. In response to the call to action by the UN Decade of Ocean Science for Sustainable Development (2021–2030), as well as the desired safe ocean outcome (von Hillebrandt-Andrade et al., 2021), the Intergovernmental Oceanographic Commission (IOC) of UNESCO approved the Ocean Decade Tsunami Programme in June 2021. One of its goals is to develop the capability to issue actionable alerts for tsunamis from all sources with minimum uncertainty within 10 minutes (Angove et al., 2019). While laudable, this goal presents complexities. Currently, warning depends on quick detection as well as the location and initial magnitude estimates of an earthquake that may generate a tsunami. Other factors that affect tsunamis, such as the faulting mechanism (how the faults slide past each other) and areal extent of the earthquake, currently take at least 20–30 minutes to forecast and are still subject to large uncertainties. Hence, agencies charged with tsunami early warning need to broadcast public alerts within minutes after an earthquake occurs but may struggle to meet this 10-minute goal without further technological advances, some of which are outlined in this article. To reduce loss of life through adequate tsunami warning requires global ocean-based seismic, sea level, and geodetic initiatives to detect high-impact earthquakes and tsunamis, combined with sufficient communication and education so that people know how to respond when they receive alerts and warnings. The United Nations International Strategy for Disaster Reduction defines an early warning system as “a set of capacities needed to generate and disseminate timely and meaningful warning information to enable individuals, communities, and organizations threatened by a hazard to prepare and to act appropriately and in sufficient time to reduce the possibility of harm or loss” (UNISDR, 2012). In short, a successful early warning system requires technology coupled with human factors (Kelman and Glantz, 2014). In this article, we explore case studies from Japan and Canada, where scientists are leading the way in incorporating ocean observing capabilities in their early warning systems. We also explore advancements and challenges in the Caribbean, an area with a complex tectonic environment that would benefit greatly from increased global ocean observing capabilities. We also explore physical and social science interventions necessary to reduce loss of life.

Oceanography↗
USGS2023

Assembling the right pieces: Developing an interdisciplinary team to study disease, decline, and recovery of a world-class Smallmouth Bass fishery

Managing and understanding fisheries dynamics are becoming more complex as new and seemingly more complicated environmental factors are identified. Often management requires resources beyond that of any one entity and calls for collaboration among partners with differing priorities and backgrounds to account for the complexity of factors influencing fisheries. We present a collaborative case study from the Susquehanna River basin, Pennsylvania, where Smallmouth Bass Micropterus dolomieu have faced population declines, mortality events, and notable signs of disease in recent years. Collaboration was required to study many facets of the fishery and the environment simultaneously to better understand risk factors and underlying relationships influencing Smallmouth Bass health. The outcomes from this interdisciplinary collaboration allowed for identification of contributing risk factors, led to the development of products and analytical techniques that were mutually beneficial to all partners involved, and provided knowledge that was integrated into fish health and fisheries management.

Maryland, New York, Pennsylvania↗
USGS2018

Before the storm: Antecedent conditions as regulators of hydrologic and biogeochemical response to extreme climate events

While the influence of antecedent conditions on watershed function is widely recognized under typical hydrologic regimes, gaps remain in the context of extreme climate events (ECEs). ECEs are those events that far exceed seasonal norms of intensity, duration, or impact upon the physical environment or ecosystem. In this synthesis, we discuss the role of source availability and hydrologic connectivity on antecedent conditions and propose a conceptual framework to characterize system response to ECEs at the watershed scale. We present four case studies in detail that span a range of types of antecedent conditions and type of ECE to highlight important controls and feedbacks. Because ECEs have the potential to export large amounts of water and materials, their occurrence in sequence can disproportionately amplify the response. In fact, multiple events may not be considered extreme in isolation, but when they occur in close sequence they may lead to extreme responses in terms of both supply and transport capacity. Therefore, to advance our understanding of these complexities, we need continued development of a mechanistic understanding of how antecedent conditions set the stage for ECE response across multiple regions and climates, particularly since monitoring of these rare events is costly and difficult to obtain. Through focused monitoring of critical ecosystems during rare events we will also be able to extend and validate modeling studies. Cross-regional comparisons are also needed to define characteristics of resilient systems. These monitoring, modeling, and synthesis efforts are more critical than ever in light of changing climate regimes, intensification of human modifications of the landscape, and the disproportionate impact of ECEs in highly populated regions.

Biogeochemistry↗
USGS2015

A centroid model of species distribution with applications to the Carolina wren Thryothorus ludovicianus and house finch Haemorhous mexicanus in the United States

Drastic shifts in species distributions are a cause of concern for ecologists. Such shifts pose great threat to biodiversity especially under unprecedented anthropogenic and natural disturbances. Many studies have documented recent shifts in species distributions. However, most of these studies are limited to regional scales, and do not consider the abundance structure within species ranges. Developing methods to detect systematic changes in species distributions over their full ranges is critical for understanding the impact of changing environments and for successful conservation planning. Here, we demonstrate a centroid model for range-wide analysis of distribution shifts using the North American Breeding Bird Survey. The centroid model is based on a hierarchical Bayesian framework which models population change within physiographic strata while accounting for several factors affecting species detectability. Yearly abundance-weighted range centroids are estimated. As case studies, we derive annual centroids for the Carolina wren and house finch in their ranges in the U.S. We further evaluate the first-difference correlation between species’ centroid movement and changes in winter severity, total population abundance. We also examined associations of change in centroids from sub-ranges. Change in full-range centroid movements of Carolina wren significantly correlate with snow cover days (r = −0.58). For both species, the full-range centroid shifts also have strong correlation with total abundance (r = 0.65, and 0.51 respectively). The movements of the full-range centroids of the two species are correlated strongly (up to r = 0.76) with that of the sub-ranges with more drastic population changes. Our study demonstrates the usefulness of centroids for analyzing distribution changes in a two-dimensional spatial context. Particularly it highlights applications that associate the centroid with factors such as environmental stressors, population characteristics, and progression of invasive species. Routine monitoring of changes in centroid will provide useful insights into long-term avian responses to environmental changes.

Ecography↗
USGS2014

Development of a generic auto-calibration package for regional ecological modeling and application in the Central Plains of the United States

Process-oriented ecological models are frequently used for predicting potential impacts of global changes such as climate and land-cover changes, which can be useful for policy making. It is critical but challenging to automatically derive optimal parameter values at different scales, especially at regional scale, and validate the model performance. In this study, we developed an automatic calibration (auto-calibration) function for a well-established biogeochemical model—the General Ensemble Biogeochemical Modeling System (GEMS)-Erosion Deposition Carbon Model (EDCM)—using data assimilation technique: the Shuffled Complex Evolution algorithm and a model-inversion R package—Flexible Modeling Environment (FME). The new functionality can support multi-parameter and multi-objective auto-calibration of EDCM at the both pixel and regional levels. We also developed a post-processing procedure for GEMS to provide options to save the pixel-based or aggregated county-land cover specific parameter values for subsequent simulations. In our case study, we successfully applied the updated model (EDCM-Auto) for a single crop pixel with a corn–wheat rotation and a large ecological region (Level II)—Central USA Plains. The evaluation results indicate that EDCM-Auto is applicable at multiple scales and is capable to handle land cover changes (e.g., crop rotations). The model also performs well in capturing the spatial pattern of grain yield production for crops and net primary production (NPP) for other ecosystems across the region, which is a good example for implementing calibration and validation of ecological models with readily available survey data (grain yield) and remote sensing data (NPP) at regional and national levels. The developed platform for auto-calibration can be readily expanded to incorporate other model inversion algorithms and potential R packages, and also be applied to other ecological models.

Ecological Informatics↗
USGS1995

A survey of recent results in passive sampling of water and air by semipermeable membrane devices

A survey is presented of some recent results for passive sampling of water and air for trace organic contaminants using lipid-filled semipermeable membrane devices (SPMDs). Results of water sampling for trace organochlorine compounds using simultaneously exposed SPMDs and the most universally applied biomonitor (bivalves) are discussed. In general, the total amounts of accumulated analytes available for analysis in bivalves and SPMDs were comparable. However, SPMD controls typically had negligible levels of contamination, which was not always the case for transplanted bivalves, even after prolonged depuration prior to exposure. In surveys of the spatial trends of organochlorines at a series of sites, data from bivalves and SPMDs provided the same picture of contaminant distribution and severity. An exception was ionizable contaminants such as the chlorinated phenolic compounds and their transformation products found in pulp mill effluents. In these cases the two monitoring approaches compliment each other, i.e. what is not found in bivalves appears in SPMDs and vice versa. SPMDs have also been applied in environments where biomonitoring is not feasible. SPMDs have shown their utility in studies of trace levels of polyaromatic hydrocarbons by locating and characterizing point sources. An example is given of their application to the calculation of contaminant half-lives from aqueous SPMD residues, a direct measurement of the persistence of contaminants in an environmental compartment. Similarly, results of air sampling with SPMDs in a relatively pristine coastal location are cited which reveal a tremendous enhancement in p,p′ -DDE relative to open ocean values.

Marine Pollution Bulletin↗
USGS2006

Numerical Simulation of the Hydrologic Effects of Redistributed and Additional Ground-Water Withdrawal, Island of Molokai, Hawaii

Because of increased demand for water associated with a growing population, projected increases in demand over the next few decades, and rising salinity of the water pumped from some existing wells, the County of Maui Department of Water Supply (DWS) is currently (2006) considering drilling additional wells to replace or supplement existing wells on the Island of Molokai, Hawaii. Redistributed and additional ground-water withdrawals will affect ground-water levels, discharge of ground water to the nearshore environment, and, possibly, salinity of the water pumped from existing wells. For this study, an existing numerical ground-water-flow model was used to estimate water-level and coastal-discharge changes, relative to 2005 base-case conditions, caused by withdrawals in the area between Kualapuu and Ualapue on Molokai. For most of the scenarios tested, total withdrawals were either equal to or 0.28 million gallons per day greater than those in the 2005 base case. Model results indicate that a redistribution of withdrawals causes a corresponding redistribution of water levels and coastal discharge. Water levels rise and coastal discharge increases near sites of reduced withdrawal, whereas water levels decline and coastal discharge decreases near sites of increased withdrawal. The magnitude and areal extent of hydrologic changes caused by a redistribution of withdrawals increase with larger changes in withdrawal rates. Simulated water-level changes are greatest at withdrawal sites and decrease outward with distance elsewhere. Simulated water-level declines at proposed withdrawal sites generally were less than 0.5 feet. The low-permeability dike complex of East Molokai Volcano impedes the spread of water-level changes to perennial streams in the northeastern part of the island, and discharge to these streams in the dike complex therefore is unaffected by the proposed withdrawals. Simulated coastal-discharge changes generally are greatest immediately downgradient from sites of withdrawal change. Simulated coastal-discharge reductions generally are less than 30,000 gallons per day (and everywhere less than 75,000 gallons per day) within model elements for scenarios that exclude the Hawaii Department of Hawaiian Home Lands reservation (2.905 million gallons per day). (Model elements cover discrete 1,640-feet by 1,640-feet square areas.) Simulated coastal-discharge reductions generally represent less than 5 percent change relative to 2005 base-case conditions. Simulated discharge to some fishponds and springs increased in response to decreased withdrawal at upgradient sites, and simulated discharge to other fishponds and springs decreased in response to increased withdrawal. Simulated water-level declines associated with the Hawaii Department of Hawaiian Home Lands reservation were as much as 4 feet at three arbitrarily selected withdrawal sites, and simulated reductions in coastal discharge between Umipaa and Kamiloloa along the south coast exceeded 200,000 gallons per day from several model elements.

Scientific Investigations Report↗
USGS2012

Automating calibration, sensitivity and uncertainty analysis of complex models using the R package Flexible Modeling Environment (FME): SWAT as an example

Parameter optimization and uncertainty issues are a great challenge for the application of large environmental models like the Soil and Water Assessment Tool (SWAT), which is a physically-based hydrological model for simulating water and nutrient cycles at the watershed scale. In this study, we present a comprehensive modeling environment for SWAT, including automated calibration, and sensitivity and uncertainty analysis capabilities through integration with the R package Flexible Modeling Environment (FME). To address challenges (e.g., calling the model in R and transferring variables between Fortran and R) in developing such a two-language coupling framework, 1) we converted the Fortran-based SWAT model to an R function (R-SWAT) using the RFortran platform, and alternatively 2) we compiled SWAT as a Dynamic Link Library (DLL). We then wrapped SWAT (via R-SWAT) with FME to perform complex applications including parameter identifiability, inverse modeling, and sensitivity and uncertainty analysis in the R environment. The final R-SWAT-FME framework has the following key functionalities: automatic initialization of R, running Fortran-based SWAT and R commands in parallel, transferring parameters and model output between SWAT and R, and inverse modeling with visualization. To examine this framework and demonstrate how it works, a case study simulating streamflow in the Cedar River Basin in Iowa in the United Sates was used, and we compared it with the built-in auto-calibration tool of SWAT in parameter optimization. Results indicate that both methods performed well and similarly in searching a set of optimal parameters. Nonetheless, the R-SWAT-FME is more attractive due to its instant visualization, and potential to take advantage of other R packages (e.g., inverse modeling and statistical graphics). The methods presented in the paper are readily adaptable to other model applications that require capability for automated calibration, and sensitivity and uncertainty analysis.

Environmental Modelling and Software↗
USGS2019

Individual based modelling of fish migration in a 2-D river system: Model description and case study

Context: Diadromous fish populations in the Pacific Northwest face challenges along their migratory routes from declining habitat quality, harvest, and barriers to longitudinal connectivity. These stressors complicate the prioritization of proposed management actions intended to improve conditions for migratory fishes including anadromous salmon and trout. Objectives: We describe a multi-scale hybrid mechanistic–probabilistic simulation model linking migration corridor conditions to fish fitness outcomes. We demonstrate the model’s utility using a case study of salmon and steelhead adults in the Columbia River migration corridor exposed to spatially- and temporally-varying stressors. Methods: The migration corridor simulation model is based on a behavioral decision tree that governs individual interactions with the environment, and an energetic submodel that estimates the hourly costs of migration. Emergent properties of the migration corridor simulation model include passage time, energy use, and survival. Results: We observed that the simulated fish’s initial energy density, the migration corridor temperatures they experienced, and their history of behavioral thermoregulation were the primary determinants of their fitness outcomes. Insights gained from use of the model might be exploited to identify management interventions that increase successful migration outcomes. Conclusions: This paper describes new methods that extend the suite of tools available to aquatic biologists and conservation practitioners. We have developed a 2-dimensional spatially-explicit behavioral and physiological model and illustrated how it can be used to simulate fish migration within a river system. Our model can be used to evaluate trade-offs between behavioral thermoregulation and fish fitness at population scales.

Landscape Ecology↗
USGS2012

A support system for assessing local vulnerability to weather and climate

The changing number and nature of weather- and climate-related natural hazards is causing more communities to need to assess their vulnerabilities. Vulnerability assessments, however, often require considerable expertise and resources that are not available or too expensive for many communities. To meet the need for an easy-to-use, cost-effective vulnerability assessment tool for communities, a prototype online vulnerability assessment support system was built and tested. This prototype tool guides users through a stakeholder-based vulnerability assessment that breaks the process into four easy-to-implement steps. Data sources are integrated in the online environment so that perceived risks—defined and prioritized qualitatively by users—can be compared and discussed against the impacts that past events have had on the community. The support system is limited in scope, and the locations of the case studies do not provide a sufficiently broad range of sample cases. The addition of more publicly available hazard databases combined with future improvements in the support system architecture and software will expand opportunities for testing and fully implementing the support system.

Natural Hazards↗
USGS2026

Sustainability trade-offs at the nexus of solar energy, agriculture, and biodiversity

A rapid transition to renewable energy is necessary for achieving global decarbonization targets, but siting conflicts, particularly beyond the built environment, remain a key barrier to sustainable development. At the same time, climate-induced pressures on biodiversity intensify the socio-ecological trade-offs within the energy-agriculture-biodiversity nexus. Using New York State as a case study, we assess the geographic implications of utility-scale solar energy development under competing land-use priorities. We apply a mixed-integer linear programming (MILP) optimization model to evaluate solar buildout across three distinct scenarios: minimizing cost, prioritizing agricultural preservation, and conserving biodiversity, employing a lexicographic hierarchy to enforce a strict ordering of stakeholder priorities. Results indicate that New York can meet its mid-century decarbonization goals by deploying 46,216 MW dc of solar energy, however, achieving this goal involves considerable land-use trade-offs. A cost-minimizing scenario disproportionately targets pasture and hay lands (>40,000 ha), nearly half of which overlap with grassland bird habitat and broader biodiversity areas. Prioritizing agriculture spares ∼80 % of farmland but creates potential for deforestation of over 41,000 ha. Biodiversity-conscious siting avoids ecologically sensitive areas and increases the annualized total costs by 0.17 %, indicating economic feasibility. Our findings highlight the need for spatially informed, integrative land-use strategies that reconcile climate goals with ecological and agricultural values. By linking geospatial optimization with socio-ecological criteria, this work contributes a transferable framework to inform just and ecologically responsible energy transitions in multifunctional landscapes, offering new insights into how geography can advance sustainable development.

New York↗
USGS2012

Parasite invasion following host reintroduction: a case of Yellowstone’s wolves

Wildlife reintroductions select or treat individuals for good health with the expectation that these individuals will fare better than infected animals. However, these individuals, new to their environment, may also be particularly susceptible to circulating infections and this may result in high morbidity and mortality, potentially jeopardizing the goals of recovery. Here, using the reintroduction of the grey wolf (Canis lupus) into Yellowstone National Park as a case study, we address the question of how parasites invade a reintroduced population and consider the impact of these invasions on population performance. We find that several viral parasites rapidly invaded the population inside the park, likely via spillover from resident canid species, and we contrast these with the slower invasion of sarcoptic mange, caused by the mite Sarcoptes scabiei. The spatio-temporal patterns of mange invasion were largely consistent with patterns of host connectivity and density, and we demonstrate that the area of highest resource quality, supporting the greatest density of wolves, is also the region that appears most susceptible to repeated disease invasion and parasite-induced declines. The success of wolf reintroduction appears not to have been jeopardized by infectious disease, but now shows signs of regulation or limitation modulated by parasites.

Wyoming↗
USGS1992

Metallogenic map of volcanogenic massive sulfide occurrences in Wyoming

Volcanogenic massive sulfide occurrences of Late Archean age and Early Proterozoic age occur in metavolcanic and associated metasedimentary rocks in southeastern, eastern, and central Wyoming. Vein deposits in Archean volcanic terrane have accounted for a large part of the gold production in the State (Miners Delight, locality 8). Past production from all massive sulfide occurrences in the State is poorly known, but it probably did not exceed $13 million at current metal prices. The bulk of the production was from gold mines in the southern Wind River Range (localities 8 and 17). For the most part, the host rocks of the massive sulfide occurrences have been metamorphosed to amphibolite facies. As a result, the depositional environments are, in many cases, difficult to determine. For purposes of discussion, the occurrences are classified by geologic age.

Wyoming↗
USGS2016

Development and use of mathematical models and software frameworks for integrated analysis of agricultural systems and associated water use impacts

The development of appropriate water management strategies requires, in part, a methodology for quantifying and evaluating the impact of water policy decisions on regional stakeholders. In this work, we describe the framework we are developing to enhance the body of resources available to policy makers, farmers, and other community members in their e orts to understand, quantify, and assess the often competing objectives water consumers have with respect to usage. The foundation for the framework is the construction of a simulation-based optimization software tool using two existing software packages. In particular, we couple a robust optimization software suite (DAKOTA) with the USGS MF-OWHM water management simulation tool to provide a flexible software environment that will enable the evaluation of one or multiple (possibly competing) user-defined (or stakeholder) objectives. We introduce the individual software components and outline the communication strategy we defined for the coupled development. We present numerical results for case studies related to crop portfolio management with several defined objectives. The objectives are not optimally satisfied for any single user class, demonstrating the capability of the software tool to aid in the evaluation of a variety of competing interests.

AIMS Agriculture and Food↗
USGS2025

Land use and soil characteristics are associated with increased risk of treponeme-associated hoof disease in elk

Environments can shape the occurrence and extent of disease outbreaks in wildlife. We studied the effects of environmental features on the occurrence of treponeme-associated hoof disease (TAHD), an emerging infectious disease of free-ranging elk ( Cervus canadensis ), in southwestern Washington, USA. During the 2016–2022 harvest seasons, successful elk hunters returned mandatory harvest reports and noted the presence or absence of hoof abnormalities indicative of TAHD. We used generalized linear models and an information-theoretic approach to model selection to relate (1) the spatial distribution of hoof abnormalities to features of landscapes (land cover, topography, and soil characteristics) and (2) the temporal distribution of hoof abnormalities to precipitation during the year preceding the harvest season. The probability of hoof disease increased with soil clay content and proportion of agricultural land (88% of model weight). We found no conclusive evidence for an effect of precipitation on the occurrence of TAHD, but this could relate to relatively high annual precipitation (>140 cm) in the study area. Nevertheless, disease cases may have been negatively associated with precipitation during February–June (55% of model weight). Soils and land management practices may increase the risk of hoof disease by promoting the survival of pathogens that cause TAHD, the susceptibility of elk to infection, or the intensity of pathogen transmission among elk when congregated. Focusing on areas where the risk of disease is greatest may facilitate the detection of TAHD during surveillance. Likewise, removing infected elk and dispersing uninfected elk from areas with the greatest risk of disease may enhance the effectiveness of efforts to reduce transmission. Basing this work on the knowledge that disease risk is modified by factors of hosts, pathogens, and environments, this study serves as an application of the epidemiological triad framework to better understand the ecology and epidemiology of an emerging infectious disease in wildlife.

Washington↗