Recreational fisheries represent a socially, ecologically, and economically significant component of global fisheries. The U.S. Inland Creel and Angler Survey Catalog (CreelCat) database includes inland recreational fisheries survey data across the United States to facilitate large-scale analyses. However, because survey methods differ, a statistical method capable of integrating these surveys is necessary to assess patterns and relationships across regions. Here, we developed a hierarchical generalized linear mixed modeling approach to estimate the relationship between daily recreational fisheries catch and effort based on waterbody, socio-economic, and ecological covariates. We applied this approach to CreelCat data on lentic waterbodies and found that recreational fisheries catch and effort were non-linearly related (i.e., catch per unit of effort declined as effort increased), where effort varied regionally and by waterbody area, median county age, and distance to nearest primary road. This modeling approach could be used to inform data-poor regions or waterbodies, make comparisons across spatial scales, and, with the inclusion of socio-economic and ecological factors, inform management techniques in an era of shifting demographics and landscapes.
The deposits of the upper Neoproterozoic Zerrissene Group of central-western Namibia represent a large siliciclastic deep-water depositional system that showcases the intricacies of facies and architectural relationships from bed-scale to fan-system-scale. The lack of vegetation in the Namib Desert and regular east–west repetition of folded stratigraphy (reflecting ca 50% tectonic shortening) provides quasi-three-dimensional exposure over a current area of approximately 2700 square kilometres. The Brak River Formation, the middle sand-rich unit of the Zerrissene Group, consists of nearly 600 m of strata exposed in multiple parallel continuous outcrops up to ca 10 km in length and oriented obliquely to depositional dip. Ten stratigraphic sections are correlated ca 32 km (ca 64 km restored) across the basin and offer exposure comparable in scale to modern submarine fans. Six sedimentary facies are identified and grouped into four facies associations that represent axial-to-marginal portions of deep-water lobes in an unconfined submarine fan system. Spatial facies patterns, regional thickness variations, and palaeocurrents indicate that Brak River Formation sediments were transported primarily from the north to south–south-west through a trough-like basin, and deposited within an unconfined basin plain at the junction of the Adamastor and Khomas oceans. The unique outcrop exposure and extent permits the documentation of system-scale architecture and basin configuration of the Brak River submarine fan system. A transition from the sand-rich lower Brak River Formation to more intercalated mudstone-dominated intervals in the middle and upper Brak River Formation is interpreted to record a change from aggradational to compensational stacking of lobe deposits. This records the evolution of a large submarine fan as it filled the subtle seafloor topography and became less confined at the system-scale. The documentation of these deep-water deposits from centimetre-scale to basin-scale provides a new model for a system with extensive long-distance transport of sand-rich sediment gravity flows to submarine lobes without apparent channelization.
","language":"English","publisher":"Wiley","doi":"10.1111/sed.13129","usgsCitation":"Nieminski, N.M., McHargue, T., Gooley, J.T., Fildani, A., and Lowe, D.R., 2024, Spatial distribution and variability of lobe facies in a large sand-rich submarine fan system: Neoproterozoic Zerrissene Group, Namibia: Sedimentology, v. 71, no. 1, p. 81-115, https://doi.org/10.1111/sed.13129.","productDescription":"35 p.","startPage":"81","endPage":"115","ipdsId":"IP-134081","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":441232,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/sed.13129","text":"Publisher Index Page"},{"id":422228,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Nambia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 13.149641654100066,\n -20.46530656931472\n ],\n [\n 13.149641654100066,\n -22.12350444593342\n ],\n [\n 15.775374075974895,\n -22.12350444593342\n ],\n [\n 15.775374075974895,\n -20.46530656931472\n ],\n [\n 13.149641654100066,\n -20.46530656931472\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"71","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-10-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Nieminski, Nora Maria 0000-0002-4465-8731","orcid":"https://orcid.org/0000-0002-4465-8731","contributorId":279764,"corporation":false,"usgs":true,"family":"Nieminski","given":"Nora","email":"","middleInitial":"Maria","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":887111,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McHargue, Tim","contributorId":222430,"corporation":false,"usgs":false,"family":"McHargue","given":"Tim","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":887112,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gooley, Jared T. 0000-0001-5620-3702","orcid":"https://orcid.org/0000-0001-5620-3702","contributorId":248710,"corporation":false,"usgs":true,"family":"Gooley","given":"Jared","email":"","middleInitial":"T.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":887113,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fildani, Andrea","contributorId":204134,"corporation":false,"usgs":false,"family":"Fildani","given":"Andrea","email":"","affiliations":[{"id":36863,"text":"Statoil","active":true,"usgs":false}],"preferred":false,"id":887114,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lowe, Donald R","contributorId":331256,"corporation":false,"usgs":false,"family":"Lowe","given":"Donald","email":"","middleInitial":"R","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":887115,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70247516,"text":"70247516 - 2024 - Contribution of arsenic and uranium in private wells and community water systems to urinary biomarkers in US adults: The Strong Heart Study and the Multi-Ethnic Study of Atherosclerosis","interactions":[],"lastModifiedDate":"2024-03-11T14:25:09.814951","indexId":"70247516","displayToPublicDate":"2023-08-09T06:55:56","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2282,"text":"Journal of Exposure Science and Environmental Epidemiology","active":true,"publicationSubtype":{"id":10}},"title":"Contribution of arsenic and uranium in private wells and community water systems to urinary biomarkers in US adults: The Strong Heart Study and the Multi-Ethnic Study of Atherosclerosis","docAbstract":"Chronic exposure to inorganic arsenic (As) and uranium (U) in the United States (US) occurs from unregulated private wells and federally regulated community water systems (CWSs). The contribution of water to total exposure is assumed to be low when water As and U concentrations are low.
We examined the contribution of water As and U to urinary biomarkers in the Strong Heart Family Study (SHFS), a prospective study of American Indian communities, and the Multi-Ethnic Study of Atherosclerosis (MESA), a prospective study of racially/ethnically diverse urban U.S. communities.
We assigned residential zip code-level estimates in CWSs (µg/L) and private wells (90th percentile probability of As >10 µg/L) to up to 1485 and 6722 participants with dietary information and urinary biomarkers in the SHFS (2001–2003) and MESA (2000–2002; 2010–2011), respectively. Urine As was estimated as the sum of inorganic and methylated species, and urine U was total uranium. We used linear mixed-effects models to account for participant clustering and removed the effect of dietary sources via regression adjustment.
The median (interquartile range) urine As was 5.32 (3.29, 8.53) and 6.32 (3.34, 12.48) µg/L for SHFS and MESA, respectively, and urine U was 0.037 (0.014, 0.071) and 0.007 (0.003, 0.018) µg/L. In a meta-analysis across both studies, urine As was 11% (95% CI: 3, 20%) higher and urine U was 35% (5, 73%) higher per twofold higher CWS As and U, respectively. In the SHFS, zip-code level factors such as private well and CWS As contributed 46% of variation in urine As, while in MESA, zip-code level factors, e.g., CWS As and U, contribute 30 and 49% of variation in urine As and U, respectively.
We found that water from unregulated private wells and regulated CWSs is a major contributor to urinary As and U (an estimated measure of internal dose) in both rural, American Indian populations and urban, racially/ethnically diverse populations nationwide, even at levels below the current regulatory standard. Our findings indicate that additional drinking water interventions, regulations, and policies can have a major impact on reducing total exposures to As and U, which are linked to adverse health effects even at low levels.
","language":"English","publisher":"Nature","doi":"10.1038/s41370-023-00586-2","usgsCitation":"Spaur, M., Glabonjat, R.A., Schilling, K., Lombard, M.A., , G., Lieberman-Cribbin, W., Hayek, C., Ilievski, V., Balac, O., Izuchukwu, C., Patterson, K., Basu, A., Bostick, B., Chen, Q., Sanchez, T., Navas-Acien, A., and Nigra, A., 2024, Contribution of arsenic and uranium in private wells and community water systems to urinary biomarkers in US adults: The Strong Heart Study and the Multi-Ethnic Study of Atherosclerosis: Journal of Exposure Science and Environmental Epidemiology, v. 34, p. 77-89, https://doi.org/10.1038/s41370-023-00586-2.","productDescription":"13 p.","startPage":"77","endPage":"89","ipdsId":"IP-148895","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":441234,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41370-023-00586-2","text":"Publisher Index Page"},{"id":419695,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","noUsgsAuthors":false,"publicationDate":"2023-08-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Spaur, Maya","contributorId":257947,"corporation":false,"usgs":false,"family":"Spaur","given":"Maya","email":"","affiliations":[{"id":52179,"text":"Columbia University Mailman School of Public Health","active":true,"usgs":false}],"preferred":false,"id":879947,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glabonjat, Ronald A. 0000-0003-3104-1940","orcid":"https://orcid.org/0000-0003-3104-1940","contributorId":225202,"corporation":false,"usgs":false,"family":"Glabonjat","given":"Ronald","email":"","middleInitial":"A.","affiliations":[{"id":41074,"text":"Institute of Chemistry, NAWI Graz, University of Graz, Graz Austria","active":true,"usgs":false}],"preferred":false,"id":879948,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schilling, Kathrin","contributorId":318215,"corporation":false,"usgs":false,"family":"Schilling","given":"Kathrin","email":"","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":879949,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lombard, Melissa A. 0000-0001-5924-6556 mlombard@usgs.gov","orcid":"https://orcid.org/0000-0001-5924-6556","contributorId":198254,"corporation":false,"usgs":true,"family":"Lombard","given":"Melissa","email":"mlombard@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - 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2024 - Low-complexity floodplain inundation model performs well for ecological and management applications in a large river ecosystem","interactions":[],"lastModifiedDate":"2024-02-26T15:33:19.341219","indexId":"70247442","displayToPublicDate":"2023-08-03T07:07:04","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Low-complexity floodplain inundation model performs well for ecological and management applications in a large river ecosystem","docAbstract":"Flooding is a dominant physical process that drives the form and function of river-floodplain ecosystems. Efficiently characterizing flooding dynamics can be challenging, especially over geographically broad areas or at spatial and temporal scales relevant for ecosystem management activities. Here, we empirically evaluated a low-complexity geospatial model of floodplain inundation in six study segments of the Upper Mississippi River System (UMRS) by pairing spatially extensive, temporally limited and spatially limited, temporally extensive sampling designs. We found little evidence of systematic bias in model performance although discrepancies between model predictions and empirical data did occur locally. Assessments of model predictions revealed low segment-wide discrepancies of wetted extent under contrasting flow conditions and agreement for inundation event detection and duration. Model performance for predicting event frequency and duration was similar among sites expected to exhibit contrasting patterns of hydrologic connectivity with the main channel. Our results suggest that low-complexity models can efficiently characterize a critical physical process across geographically broad, complex river-floodplain ecosystems. Such tools have the potential for advancing scientific understanding of landscape-scale ecological patterns and for prioritizing management actions in large, complex river-floodplain ecosystems like the UMRS.
Understanding interactions between environmental stress and genetic variation is crucial to predict the adaptive capacity of species to climate change. Leaf temperature is both a driver and a responsive indicator of plant physiological response to thermal stress, and methods to monitor it are needed. Foliar temperatures vary across leaf to canopy scales and are influenced by genetic factors, challenging efforts to map and model this critical variable. Thermal imagery collected using unoccupied aerial systems (UAS) offers an innovative way to measure thermal variation in plants across landscapes at leaf-level resolutions. We used a UAS equipped with a thermal camera to assess temperature variation among genetically distinct populations of big sagebrush (Artemisia tridentata), a keystone plant species that is the focus of intensive restoration efforts throughout much of western North America. We completed flights across a growing season in a sagebrush common garden to map leaf temperature relative to subspecies and cytotype, physiological phenotypes of plants, and summer heat stress. Our objectives were to (1) determine whether leaf-level stomatal conductance corresponds with changes in crown temperature; (2) quantify genetic (i.e., subspecies and cytotype) contributions to variation in leaf and crown temperatures; and (3) identify how crown structure, solar radiation, and subspecies-cytotype relate to leaf-level temperature. When considered across the whole season, stomatal conductance was negatively, non-linearly correlated with crown-level temperature derived from UAS. Subspecies identity best explained crown-level temperature with no difference observed between cytotypes. However, structural phenotypes and microclimate best explained leaf-level temperature. These results show how fine-scale thermal mapping can decouple the contribution of genetic, phenotypic, and microclimate factors on leaf temperature dynamics. As climate-change-induced heat stress becomes prevalent, thermal UAS represents a promising way to track plant phenotypes that emerge from gene-by-environment interactions.
","language":"English","publisher":"Zoological Society of London","doi":"10.1002/rse2.359","usgsCitation":"Olsoy, P.J., Zaiats, A., Delparte, D.M., Germino, M., Richardson, B., Roop, S., Roser, A.V., Forbey, J.S., Cattau, M.E., Buerki, S., Reinhardt, K., and Caughlin, T., 2024, High-resolution thermal imagery reveals how interactions between crown structure and genetics shape plant temperature: Remote Sensing in Ecology and Conservation, v. 10, no. 1, p. 106-120, https://doi.org/10.1002/rse2.359.","productDescription":"15 p.","startPage":"106","endPage":"120","ipdsId":"IP-142406","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":441247,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rse2.359","text":"Publisher Index Page"},{"id":419398,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","city":"Boise","otherGeospatial":"Orchard common gardens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116,\n 43.34\n ],\n [\n -116,\n 43.30\n ],\n [\n -115.97,\n 43.30\n ],\n [\n -115.97,\n 43.34\n ],\n [\n -116,\n 43.34\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-07-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Olsoy, Peter J. 0000-0002-8785-0459","orcid":"https://orcid.org/0000-0002-8785-0459","contributorId":317761,"corporation":false,"usgs":false,"family":"Olsoy","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":879270,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zaiats, Andrii 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University","active":true,"usgs":false}],"preferred":false,"id":879276,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Forbey, Jennifer S.","contributorId":194442,"corporation":false,"usgs":false,"family":"Forbey","given":"Jennifer","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":879277,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cattau, Megan E 0000-0003-2164-3809","orcid":"https://orcid.org/0000-0003-2164-3809","contributorId":295715,"corporation":false,"usgs":false,"family":"Cattau","given":"Megan","email":"","middleInitial":"E","affiliations":[{"id":63922,"text":"Department of Human-Environment Systems, Boise State University","active":true,"usgs":false}],"preferred":false,"id":879278,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Buerki, Sven","contributorId":257075,"corporation":false,"usgs":false,"family":"Buerki","given":"Sven","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":879279,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Reinhardt, Keith","contributorId":178543,"corporation":false,"usgs":false,"family":"Reinhardt","given":"Keith","email":"","affiliations":[],"preferred":false,"id":879280,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Caughlin, Trevor 0000-0001-6752-2055","orcid":"https://orcid.org/0000-0001-6752-2055","contributorId":256964,"corporation":false,"usgs":false,"family":"Caughlin","given":"Trevor","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":879281,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70248838,"text":"70248838 - 2024 - Sensitivity of North American grassland birds to weather and climate variability","interactions":[],"lastModifiedDate":"2024-02-07T17:04:13.498096","indexId":"70248838","displayToPublicDate":"2023-07-10T06:47:28","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Sensitivity of North American grassland birds to weather and climate variability","docAbstract":"Grassland birds in North America have experienced sharp declines over the last 60 years driven by the widespread loss and degradation of grassland habitats. In recent decades, modern climate change has amplified these pressures. Climate change is occurring more rapidly in grasslands relative to some other ecosystems, and exposure to extreme and novel climate conditions may affect grassland bird ecology and demographics. To understand the potential effects of weather and climate variability on grassland birds, we systematically reviewed published empirical relationships between temperature and precipitation and demographic responses in grassland bird species of North America. We used a vote-counting approach to quantify the frequency and direction of significant effects of weather and climate variability on grassland birds. We found that grassland birds were likely to experience both positive and negative effects of higher temperatures and altered precipitation, with moderate, sustained increases in mean temperature and precipitation potentially benefiting some species, but extreme heat, drought, and heavy rainfall often reducing abundance and nest success. These patterns varied among climate regions, temporal scales of temperature and precipitation (< 1 month or ≥ 1 month), and taxa. The sensitivity of grassland bird populations to extreme weather and altered climate variability will likely be mediated by regional climates, interaction with other stressors, life history strategies of various species, and species’ tolerances for novel climate conditions.
","language":"English","publisher":"Wiley","doi":"10.1111/cobi.14143","usgsCitation":"Maresh Nelson, S., Ribic, C., Niemuth, N.D., Bernath-Plaisted, J., and Zuckerberg, B., 2024, Sensitivity of North American grassland birds to weather and climate variability: Conservation Biology, v. 38, no. 1, e14143, 15 p., https://doi.org/10.1111/cobi.14143.","productDescription":"e14143, 15 p.","ipdsId":"IP-155942","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":441250,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/cobi.14143","text":"Publisher Index Page"},{"id":421062,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Maresh Nelson, Scott 0000-0003-4064-3935","orcid":"https://orcid.org/0000-0003-4064-3935","contributorId":330003,"corporation":false,"usgs":false,"family":"Maresh Nelson","given":"Scott","email":"","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":883843,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ribic, Christine 0000-0003-2583-1778","orcid":"https://orcid.org/0000-0003-2583-1778","contributorId":330005,"corporation":false,"usgs":false,"family":"Ribic","given":"Christine","affiliations":[{"id":34113,"text":"University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":883844,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Niemuth, Neal D. 0009-0006-9637-5588","orcid":"https://orcid.org/0009-0006-9637-5588","contributorId":204334,"corporation":false,"usgs":false,"family":"Niemuth","given":"Neal","email":"","middleInitial":"D.","affiliations":[{"id":36919,"text":"U.S. Fish and Wildlife Service Habitat and Population Evaluation Team","active":true,"usgs":false}],"preferred":false,"id":883845,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bernath-Plaisted, Jacy 0000-0003-4645-8132","orcid":"https://orcid.org/0000-0003-4645-8132","contributorId":330007,"corporation":false,"usgs":false,"family":"Bernath-Plaisted","given":"Jacy","email":"","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":883846,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zuckerberg, Benjamin","contributorId":329861,"corporation":false,"usgs":false,"family":"Zuckerberg","given":"Benjamin","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":883847,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70251717,"text":"70251717 - 2024 - Considering pollinators' ecosystem services in the remediation and restoration of contaminated lands: Overview of research and its gaps","interactions":[],"lastModifiedDate":"2024-02-26T12:27:12.433278","indexId":"70251717","displayToPublicDate":"2023-07-10T06:25:52","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2006,"text":"Integrated Environmental Assessment and Management","active":true,"publicationSubtype":{"id":10}},"title":"Considering pollinators' ecosystem services in the remediation and restoration of contaminated lands: Overview of research and its gaps","docAbstract":"The concept of ecosystem services provides a useful framework for understanding how people are affected by changes to the natural environment, such as when a contaminant is introduced (e.g., oil spills, hazardous substance releases) or, conversely, when contaminated lands are remediated and restored. Pollination is one example of an important ecosystem service; pollinators play a critical role in any functioning terrestrial ecosystem. Other studies have suggested that consideration of pollinators' ecosystem services could lead to better remediation and restoration outcomes. However, the associated relationships can be complex, and evaluation requires synthesis from numerous disciplines. In this article, we discuss the possibilities for considering pollinators and their ecosystem services when planning remediation and restoration of contaminated lands. To inform the discussion, we introduce a general conceptual model of how pollinators and the ecosystem services associated with them could be affected by contamination in the environment. We review the literature on the conceptual model components, including contaminant effects on pollinators and the direct and indirect ecosystem services provided by pollinators, and identify information gaps. Though increased public interest in pollinators likely reflects increasing recognition of their role in providing many important ecosystem services, our review indicates that many gaps in understanding—about relevant natural and social systems—currently impede the rigorous quantification and evaluation of pollinators' ecosystem services required for many applications, such as in the context of natural resource damage assessment. Notable gaps include information on non-honeybee pollinators and on ecosystem services beyond those benefitting the agricultural sector. We then discuss potential research priorities and implications for practitioners. Focused research attention on the areas highlighted in this review holds promise for increasing the possibilities for considering pollinators' ecosystem services in the remediation and restoration of contaminated lands.
Despite advances in toxicity testing and development of new approach methodologies (NAMs) for hazard assessment, the ecological risk assessment (ERA) framework for terrestrial wildlife (i.e., air-breathing amphibians, reptiles, birds, and mammals) has remained unchanged for decades. While survival, growth, and reproductive endpoints derived from whole animal toxicity tests are central to hazard assessment, non-standard measures of biological effects at multiple levels of biological organization (e.g., molecular, cellular, tissue, organ, organism, population, community, ecosystem) have potential to enhance the relevance of prospective and retrospective wildlife ERAs. Other factors (e.g., indirect effects of contaminants on food supplies and infectious disease processes) are influenced by toxicants at individual, population, and community levels, and need to be factored into chemically-based risk assessments to enhance the “eco” component of ERAs. Regulatory and logistical challenges often relegate such non-standard endpoints and indirect effects to post-registration evaluations of pesticides and industrial chemicals, and contaminated site evaluations. While NAMs are being developed, to date their applications in ERAs focused on wildlife have been limited. No single magic tool or model will address all uncertainties in hazard assessment. Modernizing wildlife ERAs will likely entail combinations of laboratory and field-derived data at multiple levels of biological organization, knowledge collection solutions (e.g., systematic review, adverse outcome pathway frameworks), and inferential methods that facilitate integrations and risk estimations focused on species, populations, interspecific extrapolations, and ecosystem services modeling, with less dependence on whole animal data and simple hazard ratios.
Despite growing support for ecosystem-based approaches, conservation is mostly implemented at the species level. However, genetic differentiation exists within this taxonomic level, putting genetically distinct populations at risk of local extinction. In the diablotin black-capped petrel Pterodroma hasitata, an endangered gadfly petrel endemic to the Caribbean, 2 phenotypes have been described: a smaller dark form and a heavier light form, which are genetically distinct. To assess possible differences in the marine distributions of phenotypes, in May 2019, we captured 5 adult black-capped petrels of each phenotype at sea in the western North Atlantic and equipped them with satellite transmitters. We used generalized linear mixed models to test the importance of phenotype on geographic distribution. Using kernel density estimations, we located use areas, quantified spatial overlap between forms, and assessed form-specific exposure to marine threats. Petrels were tracked for 11 to 255 d (mean ± SD: 102.1 ± 74.2 d). During the non-breeding period, all individuals ranged from 28.4 to 43.0° latitude. Phenotypes had significantly distinct non-breeding distributions, independent of time of year. The dark form used waters of the Carolinian marine ecoregion, and the light form used pelagic waters of the Virginian ecoregion, to the north. The dark form was more exposed to marine threats than the light form, in particular to mercury, microplastics, and marine traffic. The light form overlapped with proposed wind energy areas off the central US coast. These differences in exposure suggest possible differences in vulnerability, which can have repercussions on the viability of this imperiled species.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.1101/2022.06.02.491532","usgsCitation":"Satgé, Y., Keitt, B., Gaskin, C., Patteson, J., and Jodice, P.G., 2024, Spatial segregation between phenotypes of the diablotin black-capped petrel Pterodroma hasitata during the non-breeding period: Endangered Species Research, v. 51, p. 183-201, https://doi.org/10.1101/2022.06.02.491532.","productDescription":"19 p.","startPage":"183","endPage":"201","ipdsId":"IP-140054","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":467058,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/2022.06.02.491532","text":"External Repository"},{"id":465532,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Atlantic Ocean, Cape Hatteras, Gulf Stream","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.8923537451853,\n 35.443875566777706\n ],\n [\n -75.8923537451853,\n 30.989743965000244\n ],\n [\n -71.14475202578238,\n 30.989743965000244\n ],\n [\n -71.14475202578238,\n 35.443875566777706\n ],\n [\n -75.8923537451853,\n 35.443875566777706\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"51","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Satgé, Yvan G.","contributorId":341479,"corporation":false,"usgs":false,"family":"Satgé","given":"Yvan G.","affiliations":[{"id":81653,"text":"South Carolina Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":908484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keitt, Brad","contributorId":341480,"corporation":false,"usgs":false,"family":"Keitt","given":"Brad","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":908485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gaskin, Chris","contributorId":341481,"corporation":false,"usgs":false,"family":"Gaskin","given":"Chris","affiliations":[{"id":81744,"text":"Northern New Zealand Seabird Trust","active":true,"usgs":false}],"preferred":false,"id":908486,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Patteson, J. Brian","contributorId":347588,"corporation":false,"usgs":false,"family":"Patteson","given":"J. Brian","affiliations":[],"preferred":false,"id":922023,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":219852,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908487,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70256449,"text":"70256449 - 2024 - Accuracy and precision of sea-finding orientation as a function of dune proximity in hatchlings of two species of sea turtles","interactions":[],"lastModifiedDate":"2024-08-26T15:04:49.69881","indexId":"70256449","displayToPublicDate":"2023-06-26T10:48:55","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2681,"text":"Marine and Freshwater Research","active":true,"publicationSubtype":{"id":10}},"title":"Accuracy and precision of sea-finding orientation as a function of dune proximity in hatchlings of two species of sea turtles","docAbstract":"Context: Sea turtle hatchlings generally emerge at night from nests on sand beaches and immediately orient using visual cues, which are believed to entail the difference in brightness between the light seen in the seaward direction and that seen in the duneward direction.
Aim: The aim of this study was to understand how dune proximity affected hatchling orientations in two sea turtle species that share a nesting beach 15 km long and 25.3 ± 9.4 m (N = 215) from dune to waterline, with low to moderate artificial light nearby.
Methods: For hatchling loggerhead and green turtles, we measured accuracy and precision of orientation, tested differences in distance from nest to dune, and investigated the effect of dune proximity on hatchling orientation.
Key results: We found a significant decrease in hatchling orientation accuracy and precision in both species as the distance increased from nests to dune. Loggerhead and green turtles showed similar orientation ability when in the same proximity to the dune.
Conclusions: We conclude that dune features provide important cues for hatchling orientation on sea turtle nesting beaches.
Implications: Restoring and maintaining natural beach profiles, especially dune systems, is likely to increase the accuracy and precision of sea finding in hatchling sea turtles.
","language":"English","publisher":"CSIRO","doi":"10.1071/MF23052","usgsCitation":"Hirama, S., Witherington, B., Sylvia, A., and Carthy, R., 2024, Accuracy and precision of sea-finding orientation as a function of dune proximity in hatchlings of two species of sea turtles: Marine and Freshwater Research, v. 74, no. 11, p. 994-1001, https://doi.org/10.1071/MF23052.","productDescription":"8 p.","startPage":"994","endPage":"1001","ipdsId":"IP-146660","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":441263,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1071/mf23052","text":"Publisher Index Page"},{"id":432601,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","county":"Palm Beach County","otherGeospatial":"Juno Beach","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.08267111365518,\n 26.969659914048705\n ],\n [\n -80.08,\n 26.97\n ],\n [\n -80.041,\n 26.858556495771765\n ],\n [\n -80.04786857797046,\n 26.858073293512533\n ],\n [\n -80.08267111365518,\n 26.969659914048705\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"74","issue":"11","noUsgsAuthors":false,"publicationDate":"2023-06-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Hirama, Shigetomo","contributorId":340649,"corporation":false,"usgs":false,"family":"Hirama","given":"Shigetomo","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":907425,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Witherington, Blair","contributorId":340650,"corporation":false,"usgs":false,"family":"Witherington","given":"Blair","affiliations":[{"id":61821,"text":"Inwater Research Group, Inc","active":true,"usgs":false}],"preferred":false,"id":907426,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sylvia, Andrea","contributorId":340652,"corporation":false,"usgs":false,"family":"Sylvia","given":"Andrea","email":"","affiliations":[{"id":81641,"text":"Loggerhead Marinelife Cente","active":true,"usgs":false}],"preferred":false,"id":907427,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carthy, Raymond 0000-0001-8978-5083","orcid":"https://orcid.org/0000-0001-8978-5083","contributorId":219303,"corporation":false,"usgs":true,"family":"Carthy","given":"Raymond","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907428,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70268870,"text":"70268870 - 2024 - Estimating groundwater pumping for irrigation: A method comparison","interactions":[],"lastModifiedDate":"2025-07-10T16:27:16.465704","indexId":"70268870","displayToPublicDate":"2023-06-22T09:41:30","publicationYear":"2024","noYear":false,"publicationType":{"id":26,"text":"Extramural-Authored Publication Paper"},"publicationSubtype":{"id":31,"text":"Extramural-Authored Publication"},"seriesTitle":{"id":21990,"text":"Groundwater","active":true,"publicationSubtype":{"id":31}},"title":"Estimating groundwater pumping for irrigation: A method comparison","docAbstract":"Effective groundwater management is critical to future environmental, ecological, and social sustainability and requires accurate estimates of groundwater withdrawals. Unfortunately, these estimates are not readily available in most areas due to physical, regulatory, and social challenges. Here, we compare four different approaches for estimating groundwater withdrawals for agricultural irrigation. We apply these methods in a groundwater-irrigated region in the state of Kansas, USA, where high-quality groundwater withdrawal data are available for evaluation. The four methods represent a broad spectrum of approaches: (1) the hydrologically-based Water Table Fluctuation method (WTFM); (2) the demand-based SALUS crop model; (3) estimates based on satellite-derived evapotranspiration (ET) data from OpenET; and (4) a landscape hydrology model which integrates hydrologic- and demand-based approaches. The applicability of each approach varies based on data availability, spatial and temporal resolution, and accuracy of predictions. In general, our results indicate that all approaches reasonably estimate groundwater withdrawals in our region, however, the type and amount of data required for accurate estimates and the computational requirements vary among approaches. For example, WTFM requires accurate groundwater levels, specific yield, and recharge data, whereas the SALUS crop model requires adequate information about crop type, land use, and weather. This variability highlights the difficulty in identifying what data, and how much, are necessary for a reasonable groundwater withdrawal estimate, and suggests that data availability should drive the choice of approach. Overall, our findings will help practitioners evaluate the strengths and weaknesses of different approaches and select the appropriate approach for their application.
","language":"English","publisher":"National Groundwater Association","doi":"10.1111/gwat.13336","usgsCitation":"Brookfield, A.E., Zipper, S., Kendall, A., Ajami, H., and Deines, J.M., 2024, Estimating groundwater pumping for irrigation: A method comparison: Groundwater, v. 62, no. 1, p. 15-33, https://doi.org/10.1111/gwat.13336.","productDescription":"19 p.","startPage":"15","endPage":"33","ipdsId":"IP-180562","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":492078,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.13336","text":"Publisher Index Page"},{"id":491893,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","county":"Sheridan County, Thomas County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -100.9,\n 39.6\n ],\n [\n -100.9,\n 39.2\n ],\n [\n -100.3,\n 39.2\n ],\n [\n -100.3,\n 39.6\n ],\n [\n -100.9,\n 39.6\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"62","issue":"1","noUsgsAuthors":true,"publicationDate":"2023-07-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Brookfield, Andrea E.","contributorId":202677,"corporation":false,"usgs":false,"family":"Brookfield","given":"Andrea","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":942441,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zipper, Samuel 0000-0002-8735-5757","orcid":"https://orcid.org/0000-0002-8735-5757","contributorId":225160,"corporation":false,"usgs":false,"family":"Zipper","given":"Samuel","email":"","affiliations":[{"id":41056,"text":"Kansas Geological Survey, University of Kansas, Lawrence KS 66047, USA","active":true,"usgs":false}],"preferred":false,"id":942442,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kendall, Anthony D.","contributorId":357745,"corporation":false,"usgs":false,"family":"Kendall","given":"Anthony D.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":942443,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ajami, Hoori 0000-0001-6883-7630","orcid":"https://orcid.org/0000-0001-6883-7630","contributorId":303806,"corporation":false,"usgs":false,"family":"Ajami","given":"Hoori","email":"","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":942444,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Deines, Jillian M. 0000-0002-4279-8765","orcid":"https://orcid.org/0000-0002-4279-8765","contributorId":303808,"corporation":false,"usgs":false,"family":"Deines","given":"Jillian","email":"","middleInitial":"M.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":942445,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70244184,"text":"70244184 - 2024 - Toxicological effects assessment for wildlife in the 21st Century: Review of current methods and recommendations for a path forward","interactions":[],"lastModifiedDate":"2024-05-07T14:11:13.974271","indexId":"70244184","displayToPublicDate":"2023-06-01T09:30:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2006,"text":"Integrated Environmental Assessment and Management","active":true,"publicationSubtype":{"id":10}},"title":"Toxicological effects assessment for wildlife in the 21st Century: Review of current methods and recommendations for a path forward","docAbstract":"Model species (e.g., granivorous gamebirds, waterfowl, passerines, domesticated rodents) have been used for decades in guideline laboratory tests to generate survival, growth and reproductive data for prospective Ecological Risk Assessments (ERAs) for birds and mammals, while officially adopted risk assessment schemes for amphibians and reptiles do not exist. There are recognized shortcomings of current in vivo methods as well as uncertainty around the extent to which species with different life histories (e.g., terrestrial amphibians, reptiles, bats) than these commonly used models are protected by existing ERA frameworks. Approaches other than validating additional animal models for testing are being developed, but incorporation of such new approach methodologies (NAMs) into risk assessment frameworks will require robust validations against in vivo responses. This takes time, and the ability to extrapolate findings from non-animal studies to organism- and population-level effects in terrestrial wildlife remains weak. Failure to adequately anticipate and predict hazards could have economic and potentially even legal consequences for regulators and product registrants. In order to be able to use fewer animals or replace them altogether in the long-term, vertebrate use and whole organism data will be needed to provide data for NAMs validation in the short term. Therefore, it is worth investing resources for potential updates to existing standard test guidelines used in the laboratory as well as addressing the need for clear guidance on conduct of field studies. Herein we review the potential for improving standard in vivo test methods and for advancing the use of field studies in wildlife risk assessment, as these tools will be needed into the foreseeable future.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/ieam.4795","usgsCitation":"Bean, T., Beasley, V., Berny, P., Eisenreich, K., Elliott, J.E., Eng, M.L., Fuchsman, P., Johnson, M.S., King, M., Mateo Soria, R., Meyer, C., Salice, C., and Rattner, B.A., 2024, Toxicological effects assessment for wildlife in the 21st Century: Review of current methods and recommendations for a path forward: Integrated Environmental Assessment and Management, v. 20, no. 3, p. 699-724, https://doi.org/10.1002/ieam.4795.","productDescription":"26 p.","startPage":"699","endPage":"724","ipdsId":"IP-147218","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":441268,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ieam.4795","text":"Publisher Index Page"},{"id":417915,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-06-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Bean, Thomas G.","contributorId":306122,"corporation":false,"usgs":false,"family":"Bean","given":"Thomas G.","affiliations":[{"id":39755,"text":"FMC","active":true,"usgs":false}],"preferred":false,"id":874793,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beasley, Val R.","contributorId":306123,"corporation":false,"usgs":false,"family":"Beasley","given":"Val R.","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":874794,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berny, Philippe","contributorId":306124,"corporation":false,"usgs":false,"family":"Berny","given":"Philippe","affiliations":[{"id":66373,"text":"UR ICE-VETAGRO-SUP, Université de Lyon","active":true,"usgs":false}],"preferred":false,"id":874795,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eisenreich, Karen M.","contributorId":306125,"corporation":false,"usgs":false,"family":"Eisenreich","given":"Karen M.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":874796,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Elliott, John E.","contributorId":306126,"corporation":false,"usgs":false,"family":"Elliott","given":"John","email":"","middleInitial":"E.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":874797,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eng, Margaret L.","contributorId":306127,"corporation":false,"usgs":false,"family":"Eng","given":"Margaret","email":"","middleInitial":"L.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":874798,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fuchsman, Phyllis C.","contributorId":306128,"corporation":false,"usgs":false,"family":"Fuchsman","given":"Phyllis C.","affiliations":[{"id":62153,"text":"Ramboll","active":true,"usgs":false}],"preferred":false,"id":874799,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johnson, Mark S.","contributorId":306129,"corporation":false,"usgs":false,"family":"Johnson","given":"Mark","email":"","middleInitial":"S.","affiliations":[{"id":66374,"text":"U.S. Army Public Health Center","active":true,"usgs":false}],"preferred":false,"id":874800,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"King, Mason D.","contributorId":306130,"corporation":false,"usgs":false,"family":"King","given":"Mason D.","affiliations":[{"id":36678,"text":"Simon Fraser University","active":true,"usgs":false}],"preferred":false,"id":874801,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mateo Soria, Rafael","contributorId":306131,"corporation":false,"usgs":false,"family":"Mateo Soria","given":"Rafael","email":"","affiliations":[{"id":66375,"text":"IREC (CSIC-UCLM)","active":true,"usgs":false}],"preferred":false,"id":874802,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Meyer, Carolyn B.","contributorId":306132,"corporation":false,"usgs":false,"family":"Meyer","given":"Carolyn B.","affiliations":[{"id":36715,"text":"Arcadis","active":true,"usgs":false}],"preferred":false,"id":874803,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Salice, Christopher J.","contributorId":306133,"corporation":false,"usgs":false,"family":"Salice","given":"Christopher J.","affiliations":[{"id":33107,"text":"Towson University","active":true,"usgs":false}],"preferred":false,"id":874804,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rattner, Barnett A. 0000-0003-3676-2843 brattner@usgs.gov","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":4142,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett","email":"brattner@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":874805,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70246566,"text":"70246566 - 2024 - FloPy workflows for creating structured and unstructured MODFLOW models","interactions":[],"lastModifiedDate":"2024-02-07T16:31:19.78664","indexId":"70246566","displayToPublicDate":"2023-05-29T09:54:02","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"FloPy workflows for creating structured and unstructured MODFLOW models","docAbstract":"FloPy is a popular Python package for creating, running, and post-processing MODFLOW-based groundwater flow and transport models. FloPy functionality has expanded to support the latest version of MODFLOW (MODFLOW 6) including support for unstructured grids. FloPy can be used to download MODFLOW-based and other executables for Linux, MacOS, and Windows operating systems, which simplifies the process required to download and use these executables. Expanded FloPy capabilities include (1) full support for structured and unstructured spatial discretizations; (2) geoprocessing of spatial features and raster data to develop model input for supported discretization types; (3) the addition of functionality to provide direct access to simulated output data; (4) extension of plotting capabilities to unstructured MODFLOW 6 discretization types; and (5) the ability to export model data to shapefiles, NetCDF, and VTK formats for processing, analysis, and visualization by other software products. Examples of using expanded FloPy capabilities are presented for a hypothetical watershed. An unstructured groundwater flow and transport model, with several advanced stress packages, is presented to demonstrate how FloPy can be used to develop complicated unstructured model datasets from original source data (shapefiles and rasters), post-process model results, and plot simulated results.","language":"English","publisher":"National Groundwater Association","doi":"10.1111/gwat.13327","usgsCitation":"Hughes, J.D., Langevin, C.D., Paulinski, S., Larsen, J., and Brakenhoff, D., 2024, FloPy workflows for creating structured and unstructured MODFLOW models: Groundwater, v. 62, no. 1, p. 124-139, https://doi.org/10.1111/gwat.13327.","productDescription":"16 p.","startPage":"124","endPage":"139","ipdsId":"IP-147421","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":441271,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.13327","text":"Publisher Index Page"},{"id":418801,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Hughes, Joseph D. 0000-0003-1311-2354 jdhughes@usgs.gov","orcid":"https://orcid.org/0000-0003-1311-2354","contributorId":2492,"corporation":false,"usgs":true,"family":"Hughes","given":"Joseph","email":"jdhughes@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":877222,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Langevin, Christian D. 0000-0001-5610-9759 langevin@usgs.gov","orcid":"https://orcid.org/0000-0001-5610-9759","contributorId":1030,"corporation":false,"usgs":true,"family":"Langevin","given":"Christian","email":"langevin@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":877223,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paulinski, Scott R. 0000-0001-6548-8164","orcid":"https://orcid.org/0000-0001-6548-8164","contributorId":204240,"corporation":false,"usgs":true,"family":"Paulinski","given":"Scott R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":877224,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larsen, Joshua 0000-0002-1218-800X jlarsen@usgs.gov","orcid":"https://orcid.org/0000-0002-1218-800X","contributorId":272403,"corporation":false,"usgs":true,"family":"Larsen","given":"Joshua","email":"jlarsen@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":877225,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brakenhoff, David 0000-0002-2993-2202","orcid":"https://orcid.org/0000-0002-2993-2202","contributorId":316259,"corporation":false,"usgs":false,"family":"Brakenhoff","given":"David","email":"","affiliations":[{"id":68536,"text":"Artesia Water","active":true,"usgs":false}],"preferred":false,"id":877226,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70243167,"text":"70243167 - 2024 - Oligocene–Miocene northward growth of the Tibetan Plateau: Insights from intermontane basins in the West Qinling Belt, NW China","interactions":[],"lastModifiedDate":"2023-12-20T17:41:56.604529","indexId":"70243167","displayToPublicDate":"2023-04-28T06:44:44","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Oligocene–Miocene northward growth of the Tibetan Plateau: Insights from intermontane basins in the West Qinling Belt, NW China","docAbstract":"Growth of the Tibetan Plateau, Earth’s broadest and highest elevation collisional system, shapes orographic barriers, reorganizes drainage networks, and influences surface erosion and sediment delivery, whose changes in space and provenance feed back to intracontinental tectonic processes. Studies of interior basins within the northern Tibetan Plateau provide new sediment accumulation, provenance, paleodrainage, and deformation timing data that enable a reconstruction of the far-field tectono-geomorphic evolution of the rising Tibetan Plateau. Along the northern plateau margin, topographic growth in the West Qinling Belt is inferred to have initiated in the Eocene, nearly coeval with the India-Asia collision, as well as in the late Miocene. However, geological knowledge about the intervening period remains at present enigmatic, and the kinematics and dynamics are uncertain. This study presents a multidisciplinary data set from the intermontane Anhua-Huicheng Basin (AHB; Gansu Province, China) to fill this gap. Magnetostratigraphic dating, regional mapping, and sedimentological analysis imply that contractional deformation and thrust-top basin systems formed within the West Qinling Belt in the Oligocene (not later than ca. 24 Ma). A combination of observations including paleocurrent changes, detrital zircon U-Pb age variations, and appearance of growth strata along the Anhua-Huicheng Basin reveal the rapid uplift of the West Qinling Belt at ca. 15 Ma. Sedimentation in the intermontane basins ended after the late Miocene (ca. 8 Ma), when the region experienced intrabasinal deformation, uplift, and erosion with the establishment of an external drainage system. Since the late Miocene, the growth of the West Qinling Belt reached a climax with the lack of substantial contractional deformation in Cenozoic sequences heralding the onset of the modern kinematic regime and attainment of high elevation. Observed transitions in the tectonostratigraphy and paleodrainage define different phases of deformation and plateau-wide shifts in stress reorganization, which led to the northward growth and later lateral expansion of the Tibetan Plateau.
Habitat suitability models for freshwater mussels can inform conservation of these imperiled animals. Riverscape-scale hydrogeomorphic variables were previously used to predict suitable mussel habitat in the Meramec River basin, Missouri. We evaluated transferability of the Meramec River habitat suitability model to the Gasconade and Little Black rivers, in the Ozark Highlands ecoregion, Missouri. The best-fit models relied on transferring and adapting the original modeling framework to better represent the unique habitat characteristics of each river. Mussel bed occurrence in both rivers was associated with reaches that were classified as pools. Mussel beds in the Gasconade River were also associated with laterally stable reaches adjacent to small bluffs, distant from gravel bars, and with higher stream power indices. Mussel beds in the Little Black River were associated with reaches with higher surface water availability during low-flow conditions, lower stream power indices, and bluffs located downstream. Our results show that existing habitat models can be transferred to other streams with similar environmental conditions, but differences in watershed characteristics can affect transferability.
","language":"English","publisher":"Freshwater Mollusk Conservation Society","doi":"10.31931/fmbc-d-21-00005","usgsCitation":"Hartman, J.H., Rosenberger, A.E., Key, K.N., and Lindner, G.A., 2024, Assessing potential habitat for freshwater mussels by transferring a habitat suitability model within the Ozark Ecoregion, Missouri: Freshwater Mollusk Biology and Conservation, v. 26, no. 1, p. 32-44, https://doi.org/10.31931/fmbc-d-21-00005.","productDescription":"13 p.","startPage":"32","endPage":"44","ipdsId":"IP-128365","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":441286,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.31931/fmbc-d-21-00005","text":"Publisher Index Page"},{"id":433222,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Ozark Highlands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.48277091924116,\n 37.56996609191134\n ],\n [\n -90.43622532050725,\n 38.406472750075494\n ],\n [\n -90.85898340408788,\n 38.88418454557933\n ],\n [\n -92.88282529356854,\n 38.3923742230769\n ],\n [\n -92.75689735377867,\n 36.62295716381152\n ],\n [\n -90.08542605966407,\n 36.48567275312169\n ],\n [\n -89.48277091924116,\n 37.56996609191134\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"26","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hartman, Jordan H.","contributorId":341437,"corporation":false,"usgs":false,"family":"Hartman","given":"Jordan","email":"","middleInitial":"H.","affiliations":[{"id":56209,"text":"Tennessee Tech University","active":true,"usgs":false}],"preferred":false,"id":908416,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenberger, Amanda E. 0000-0002-5520-8349 arosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5520-8349","contributorId":5581,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Amanda","email":"arosenberger@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":908417,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Key, Kayla N.","contributorId":206919,"corporation":false,"usgs":false,"family":"Key","given":"Kayla","email":"","middleInitial":"N.","affiliations":[{"id":13706,"text":"University of Missouri-Columbia","active":true,"usgs":false}],"preferred":false,"id":908418,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindner, Garth A.","contributorId":201828,"corporation":false,"usgs":false,"family":"Lindner","given":"Garth","email":"","middleInitial":"A.","affiliations":[{"id":36266,"text":"University of Missouri Cooperative Research Unit","active":true,"usgs":false}],"preferred":false,"id":908419,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70254867,"text":"70254867 - 2024 - Diet composition and resource overlap of sympatric native and introduced salmonids across neighboring streams during a peak discharge event","interactions":[],"lastModifiedDate":"2024-06-10T16:45:07.388178","indexId":"70254867","displayToPublicDate":"2023-01-24T11:37:09","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Diet composition and resource overlap of sympatric native and introduced salmonids across neighboring streams during a peak discharge event","docAbstract":"Species assemblages composed of non-native and native fishes are found in freshwater systems throughout the world, and interactions such as interspecific competition that may negatively affect native species are expected when non-native species are present. In the Smith River watershed, Montana, rainbow trout were introduced by 1930. Native mountain whitefish and non-native rainbow trout have presumably occurred in sympatry since the introduction of rainbow trout; however, knowledge about how these two species compete with one another for food resources is sparse. We quantified diet compositions of rainbow trout and mountain whitefish in the mainstem Smith River and in a tributary to the Smith River—Sheep Creek—to determine the degree of overlap in the diets of mountain whitefish and rainbow trout in the Smith River and between the mainstem Smith River and a tributary stream. Rainbow trout and mountain whitefish had generalist feeding strategies, which probably contribute to the amicable coexistence of these species. Diet overlap between rainbow trout and mountain whitefish was high (Pianka’s index value = 0.85) in the Smith River and moderate in Sheep Creek (Pianka’s index value = 0.57). Despite overlap in diets, some resource partitioning may alleviate resource competition (e.g., rainbow trout consumed far more Oligochaeta than mountain whitefish but fewer Brachycentridae and Chironomidae). Diet composition of rainbow trout and mountain whitefish did not differ greatly between the Smith River and Sheep Creek. Prey categories most commonly used by mountain whitefish at the population and individual levels (i.e., Ephemeroptera and Trichoptera) are sensitive taxa and many species within these orders have experienced extinctions and population declines. Therefore, future changes in resource availability or competition could be of concern.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0280833","usgsCitation":"Cox, T.L., Lance, M., Albertson, L., Briggs, M., Dutton, A.J., and Zale, A.V., 2024, Diet composition and resource overlap of sympatric native and introduced salmonids across neighboring streams during a peak discharge event: PLoS ONE, v. 18, no. 1, e0280833, 15 p., https://doi.org/10.1371/journal.pone.0280833.","productDescription":"e0280833, 15 p.","ipdsId":"IP-140511","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":441297,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0280833","text":"Publisher Index Page"},{"id":429778,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Smith River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.6705061351432,\n 47.43858839540755\n ],\n [\n -111.6705061351432,\n 46.8636526954179\n ],\n [\n -111.00332112471752,\n 46.8636526954179\n ],\n [\n -111.00332112471752,\n 47.43858839540755\n ],\n [\n -111.6705061351432,\n 47.43858839540755\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-01-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Cox, Tanner L.","contributorId":337858,"corporation":false,"usgs":false,"family":"Cox","given":"Tanner","email":"","middleInitial":"L.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":902735,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lance, Michael J.","contributorId":337859,"corporation":false,"usgs":false,"family":"Lance","given":"Michael J.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":902736,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Albertson, Lindsey K.","contributorId":337860,"corporation":false,"usgs":false,"family":"Albertson","given":"Lindsey K.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":902737,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Briggs, Michelle A.","contributorId":337861,"corporation":false,"usgs":false,"family":"Briggs","given":"Michelle A.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":902738,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dutton, Adeline J.","contributorId":337862,"corporation":false,"usgs":false,"family":"Dutton","given":"Adeline","email":"","middleInitial":"J.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":902739,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zale, Alexander V. 0000-0003-1703-885X","orcid":"https://orcid.org/0000-0003-1703-885X","contributorId":244099,"corporation":false,"usgs":true,"family":"Zale","given":"Alexander","email":"","middleInitial":"V.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":902740,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70255216,"text":"70255216 - 2024 - A scaled Denil fishway for upstream passage of Arctic Grayling","interactions":[],"lastModifiedDate":"2024-06-17T14:23:35.438379","indexId":"70255216","displayToPublicDate":"2022-08-10T09:19:23","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5513,"text":"Journal of Ecohydraulics","active":true,"publicationSubtype":{"id":10}},"title":"A scaled Denil fishway for upstream passage of Arctic Grayling","docAbstract":"Denil fishways have been used with varying success to help fish pass impediments to upstream passage such as low head dams or irrigation diversion structures. They have been tested for hydraulic and fish passage performance in laboratory and field settings, usually with only minor modifications to the fishway geometry or dimensions. We tested a reduced (0.6) scale prototype of the standard-sized Denil fishway to determine if the smaller fishway, which requires less water flow, would successfully pass Arctic Grayling (Thymallus arcticus). The scaling factor was informed by analyzing previously published scalable Denil fishway rating equations. A prototype was tested in an open-channel flume using 8 treatments with 3 trials per treatment and 8 fish per trial. Each treatment had a prescribed combination of headwater and tailwater depths. Overall, 93% (178/191) of the fish volitionally entered the fishway and of these 91% (162/178) passed successfully. Entrance and passage were reduced only in treatments with the highest hydraulic slopes and highest water velocities at the downstream end of the fishway (i.e. with high headwater depths and low tailwater depths). The 0.6-scaled Denil fishway is likely a good alternative to standard-sized Denil fishways to enhance upstream mobility of Arctic Grayling in small, water-limited streams.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/24705357.2022.2105756","usgsCitation":"Plymesser, K., Blank, M., Conley, M., Kappenman, K., Cahoon, J., Dockery, D., and Zale, A.V., 2024, A scaled Denil fishway for upstream passage of Arctic Grayling: Journal of Ecohydraulics, v. 9, no. 1, p. 96-106, https://doi.org/10.1080/24705357.2022.2105756.","productDescription":"11 p.","startPage":"96","endPage":"106","ipdsId":"IP-137179","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":430274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-08-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Plymesser, Katey","contributorId":339030,"corporation":false,"usgs":false,"family":"Plymesser","given":"Katey","email":"","affiliations":[{"id":81234,"text":"Montana State University Civil Engineering Department","active":true,"usgs":false}],"preferred":false,"id":903752,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blank, Matt","contributorId":339031,"corporation":false,"usgs":false,"family":"Blank","given":"Matt","email":"","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":903753,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conley, Megan","contributorId":339032,"corporation":false,"usgs":false,"family":"Conley","given":"Megan","email":"","affiliations":[{"id":81234,"text":"Montana State University Civil Engineering Department","active":true,"usgs":false}],"preferred":false,"id":903754,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kappenman, Kevin","contributorId":339033,"corporation":false,"usgs":false,"family":"Kappenman","given":"Kevin","affiliations":[{"id":81237,"text":"USFWS, Bozeman Fish Technology Center","active":true,"usgs":false}],"preferred":false,"id":903755,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cahoon, Joel","contributorId":339034,"corporation":false,"usgs":false,"family":"Cahoon","given":"Joel","email":"","affiliations":[{"id":81234,"text":"Montana State University Civil Engineering Department","active":true,"usgs":false}],"preferred":false,"id":903756,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dockery, David","contributorId":339035,"corporation":false,"usgs":false,"family":"Dockery","given":"David","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":903757,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zale, Alexander V. 0000-0003-1703-885X","orcid":"https://orcid.org/0000-0003-1703-885X","contributorId":244099,"corporation":false,"usgs":true,"family":"Zale","given":"Alexander","email":"","middleInitial":"V.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":903758,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70256665,"text":"70256665 - 2024 - Recovery of working grasslands following a megafire in the southern mixed-grass prairie","interactions":[],"lastModifiedDate":"2024-08-29T16:23:29.084243","indexId":"70256665","displayToPublicDate":"2022-05-05T11:11:32","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Recovery of working grasslands following a megafire in the southern mixed-grass prairie","docAbstract":"While fire is a necessary ecological driver for grassland systems, Great Plains grasslands have undergone extensive land use change following European settlement (conversion, fragmentation, fire suppression, intensive grazing, etc.). Recent studies have documented the benefits of re-introducing fire to grasslands, but work has largely focused on small-scale, low-intensity fire, often at a pasture scale (i.e., prescribed fire). Over the last 30–40 years, the size and frequency of wildfires in the Great Plains has increased due to long-term fire suppression, woody encroachment, and climate change, resulting in megafires (wildfire >40,000 ha). While there is a wealth of information regarding effects of prescribed fire on Great Plains grasslands, knowledge of how large megafire events affect modern, fragmented working grasslands (i.e., grazed grasslands) is lacking and needed in the face of increasing megafire activity. To assess grassland response and recovery following a 2017 megafire (~254,000 ha), we compared vegetation characteristics pre- (2014–2015) and post-fire (2018–2019) in the mixed-grass prairie of Kansas, USA. We examined linkages between vegetation characteristics and a metric of burn severity (differenced normalized burn ratio [dNBR]) and evaluated megafire effects on limiting reproductive habitat for a declining grassland species, the lesser prairie-chicken (Tympanuchus pallidicinctus). One-year post-fire, we documented increased bare ground (+59%) and decreased visual obstruction (−39%), litter depth (−31%), and forb cover (−35%). Decreased visual obstruction and increased bare ground led to an 81% decrease of lesser prairie-chicken nest habitat in the first-year post-fire, but grassland structure, functional group cover, and available nest habitat largely recovered 2.5 years post-fire. Recovery to pre-fire conditions 2.5 years post-fire was primarily due to elevated growing season precipitation received in the years following the fire (>700 mm/year). Percent cover of grass (β = 0.38) and bare ground (β = −0.36) exhibited the strongest relationships with burn severity pre-fire, but overall grassland structure and functional group cover were not strongly influenced dNBR burn severity post-fire. While our results suggested that recovering grasslands were more homogenous due to the large size of megafire, working grasslands in the mixed-grass prairie appeared largely resilient to the effects of megafire.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2022.e02142","usgsCitation":"Parker, N., Sullins, D., Haukos, D.A., Fricke, K., and Hagen, C., 2024, Recovery of working grasslands following a megafire in the southern mixed-grass prairie: Global Ecology and Conservation, v. 36, e02142, 15 p., https://doi.org/10.1016/j.gecco.2022.e02142.","productDescription":"e02142, 15 p.","ipdsId":"IP-136300","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":441313,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2022.e02142","text":"Publisher Index Page"},{"id":433320,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas, Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -99.48507488919212,\n 37.46258659472579\n ],\n [\n -100.30527026898844,\n 37.46258659472579\n ],\n [\n -100.30527026898844,\n 36.83587876246861\n ],\n [\n -99.48507488919212,\n 36.83587876246861\n ],\n [\n -99.48507488919212,\n 37.46258659472579\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"36","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Parker, Nicholas J.","contributorId":341525,"corporation":false,"usgs":false,"family":"Parker","given":"Nicholas J.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":908560,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sullins, Daniel S.","contributorId":341526,"corporation":false,"usgs":false,"family":"Sullins","given":"Daniel S.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":908561,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":908562,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fricke, Kent A.","contributorId":341527,"corporation":false,"usgs":false,"family":"Fricke","given":"Kent A.","affiliations":[{"id":81167,"text":"Kansas Department of Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":908563,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hagen, Christian A.","contributorId":341528,"corporation":false,"usgs":false,"family":"Hagen","given":"Christian A.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":908564,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70255090,"text":"70255090 - 2024 - Occurrence, abundance, movement, and habitat associations of Bonneville Cutthroat Trout in tributaries to Bear Lake, Idaho-Utah","interactions":[],"lastModifiedDate":"2024-06-12T22:33:57.342609","indexId":"70255090","displayToPublicDate":"2022-02-08T17:30:39","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Occurrence, abundance, movement, and habitat associations of Bonneville Cutthroat Trout in tributaries to Bear Lake, Idaho-Utah","docAbstract":"Bonneville Cutthroat Trout (BCT) Oncorhynchus clarkii utah in Bear Lake, Idaho–Utah, is an important endemic and recreational species and plays a vital ecological role in systems throughout the basin. Although the distribution and abundance of BCT have declined due to anthropogenic disturbances, production of wild BCT in Bear Lake has increased over the past decade as a result of extensive habitat improvement in spawning tributaries. The objective of this study was to assess the occurrence, distribution, and out-migration of BCT in tributaries of Bear Lake. Surveys were conducted at 75 stream reaches across three study streams (i.e., St. Charles, Fish Haven, and Swan creeks) during 2019 and 2020. A total of 1,064 BCT was sampled from 55 of 75 total reaches (73%). Total length of BCT varied from 22 to 650 mm, and the average TL was 117 mm (SE = 2.2). Regression models were used to identify abiotic and biotic features associated with BCT distribution, abundance, and probability of out-migration. Regardless of the tributary, elevation was negatively related to BCT occurrence and relative abundance. Other habitat characteristics associated with the presence and abundance of BCT were similar to those of other Cutthroat Trout species. For example, BCT were often associated with large substrates, instream cover, canopy cover, and heterogeneity in several habitat characteristics. The probability of a BCT out-migrating was positively associated with fish length and age but negatively related to distance to Bear Lake and number of downstream irrigation diversions. Results from this study provide critical information on the ecology and early life history characteristics of BCT that can be used to guide additional conservation and management efforts (i.e., removal of nonnative fish species; continued habitat restoration efforts).
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10754","usgsCitation":"Heller, M., Dillon, J., and Quist, M.C., 2024, Occurrence, abundance, movement, and habitat associations of Bonneville Cutthroat Trout in tributaries to Bear Lake, Idaho-Utah: North American Journal of Fisheries Management, v. 42, no. 3, p. 684-700, https://doi.org/10.1002/nafm.10754.","productDescription":"17 p.","startPage":"684","endPage":"700","ipdsId":"IP-130593","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":430044,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Utah","otherGeospatial":"Bear Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.43188970410537,\n 42.20225725843633\n ],\n [\n -111.43188970410537,\n 41.82810660832243\n ],\n [\n -111.2373990493141,\n 41.82810660832243\n ],\n [\n -111.2373990493141,\n 42.20225725843633\n ],\n [\n -111.43188970410537,\n 42.20225725843633\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"42","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-02-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Heller, Megan","contributorId":338594,"corporation":false,"usgs":false,"family":"Heller","given":"Megan","email":"","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":903380,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dillon, Jeff","contributorId":337718,"corporation":false,"usgs":false,"family":"Dillon","given":"Jeff","email":"","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":903381,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903382,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70256729,"text":"70256729 - 2024 - Habitat selection in a southern Lake Sturgeon population: Implications of temporal, spatial, and ontogenetic variation for restoration","interactions":[],"lastModifiedDate":"2024-09-03T16:54:10.020352","indexId":"70256729","displayToPublicDate":"2021-11-05T11:50:12","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Habitat selection in a southern Lake Sturgeon population: Implications of temporal, spatial, and ontogenetic variation for restoration","docAbstract":"Successful species reintroduction requires restoration of receiving habitats to support growth, survival, and reproduction that reverse the initial causes of decline. Little is known about whether present habitat conditions can support all life stages of reintroduced southern Lake Sturgeon populations that were possibly extirpated by the mid-1900s due to overharvest and habitat degradation. Therefore, we conducted a telemetry study to assess annual adult and subadult and overwinter age-0 Lake Sturgeon habitat selection and suitability in two Missouri River U.S. tributaries near the southern edge of the species range. Spring habitat selection models were unable to define spawning habitat criteria, but criteria from other studies suggest that substrate and depths for spawning are suitable in both rivers. In the summer and winter, adult and subadult Lake Sturgeon exhibited strong selection for pools greater than 8 m deep, which comprised less than 5% of our study streams. Habitat selection in the fall and winter by age-0 Lake Sturgeon differed from adults with age-0s selecting shallower habitats both rivers and swifter current velocities in the Gasconade River. General habitat patterns persisted for both life stages in each river regardless of habitat availability, suggesting specialized habitat requirements in southern Lake Sturgeon that differ from previously studied populations further north. These results may be used to direct sampling for validation of reproduction and restoration of not only spawning habitats, but age-0 and summer and winter refugia that may be potential restoration bottlenecks for southern Lake Sturgeon populations.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.13602","usgsCitation":"Moore, M., Paukert, C.P., Owens, S., and Moore, T., 2024, Habitat selection in a southern Lake Sturgeon population: Implications of temporal, spatial, and ontogenetic variation for restoration: Restoration Ecology, v. 30, no. 7, e13602, 15 p., https://doi.org/10.1111/rec.13602.","productDescription":"e13602, 15 p.","ipdsId":"IP-130802","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":433417,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Gasconade River, Osage River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.76822559173715,\n 40.12199149318826\n ],\n [\n -94.76822559173715,\n 36.2622290687403\n ],\n [\n -89.55006706959847,\n 36.2622290687403\n ],\n [\n -89.55006706959847,\n 40.12199149318826\n ],\n [\n -94.76822559173715,\n 40.12199149318826\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"30","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, M.J.","contributorId":341714,"corporation":false,"usgs":false,"family":"Moore","given":"M.J.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":908800,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paukert, Craig P. 0000-0002-9369-8545","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":245524,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","middleInitial":"P.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":908801,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Owens, S.","contributorId":341715,"corporation":false,"usgs":false,"family":"Owens","given":"S.","email":"","affiliations":[{"id":81779,"text":"University of Illinois Springfield","active":true,"usgs":false}],"preferred":false,"id":908802,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moore, T.","contributorId":257287,"corporation":false,"usgs":false,"family":"Moore","given":"T.","affiliations":[],"preferred":false,"id":908803,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70261887,"text":"70261887 - 2024 - A latest Pleistocene and Holocene composite tephrostratigraphic framework for northeastern North America","interactions":[],"lastModifiedDate":"2024-12-31T16:08:38.559478","indexId":"70261887","displayToPublicDate":"2021-11-01T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"A latest Pleistocene and Holocene composite tephrostratigraphic framework for northeastern North America","docAbstract":"Lakes and bogs in northeastern North America preserve tephra deposits sourced from multiple volcanic systems in the Northern Hemisphere. However, most studies of these deposits focus on specific Holocene intervals and the latest Pleistocene, providing snapshots rather than a full picture. We combine new data with previous work, supplemented by a broad review of the characteristics and ages of potential source regions and volcanoes, to develop the first composite tephrostratigraphic framework covering the last ~14,000 years for this region. We report new cryptotephra records from three ombrotrophic peat bogs—Irwin Smith (Michigan), Bloomingdale (New York), and Sidney Bog (Maine)—as well as new analyses and age models from previously reported sites, Nordan’s Pond Bog (Newfoundland) and Thin-Ice Pond (Nova Scotia). A new tephra (Iliinsky) from the NGRIP and GRIP ice cores is also presented as it can be correlated to new data from these terrestrial records and helps validate radiocarbon age models. We identify 21 new tephra in addition to the 15 already known, several of which cover the entire region – the White River Ash east, Newberry Pumice, Ruppert (NDN230), and Mazama. For the first time we find Mount St. Helens Yn (ca. 3660 cal yr BP) and a set P tephra (~3000–2550 cal yr BP), and confirm the presence of Jala Pumice from Volcan Ceboruco, Mexico, and KS1 from Ksudach volcano, Kamchatka. We describe new “ultra-distal” tephra, including the early Holocene KS2 eruption, and propose correlations to volcanoes Iliinsky and Shiveluch of Kamchatka, and Ushishir of the Kurile Islands. Not all of these tephra represent large eruptions, with several plausible correlations to sub-Plinian events. Using Bayesian age-modeling, we present new age estimates for the newly described tephra, for tephra with previously poor age control, and for several proximal correlatives. Overall, we demonstrate northeastern North America’s importance for providing transcontinental linkages between paleoenvironmental records and providing insights into ash distribution from different styles and sizes of eruptions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2021.107242","usgsCitation":"Jensen, B.J., Davies, L.J., Nolan, C.J., Pyne-O’Donnell, S., Monteath, A., Ponomareva, V., Portnyagin, M., Booth, R.K., Bursik, M., Cook, E., Plunkett, G., Vallance, J.W., Luo, Y., Cwynar, L., Hughes, P., and Pearson, D., 2024, A latest Pleistocene and Holocene composite tephrostratigraphic framework for northeastern North America: Quaternary Science Reviews, v. 272, 107242, 31 p., https://doi.org/10.1016/j.quascirev.2021.107242.","productDescription":"107242, 31 p.","ipdsId":"IP-133544","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467060,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2021.107242","text":"Publisher Index Page"},{"id":465569,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"northeastern North America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -86.70710190314398,\n 45.89875407338073\n ],\n [\n -87.25715165097691,\n 41.88494584293869\n ],\n [\n -70.39038584514105,\n 42.568403377972174\n ],\n [\n -61.02421079487245,\n 44.282776992445974\n ],\n [\n -51.839625858910196,\n 47.329526024513775\n ],\n [\n -51.90792307454112,\n 48.349799922260345\n ],\n [\n -54.77047158421425,\n 51.839642161004456\n ],\n [\n -65.24334883460824,\n 49.434251662776575\n ],\n [\n -86.70710190314398,\n 45.89875407338073\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"272","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jensen, Britta J.L. 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University","active":true,"usgs":false}],"preferred":false,"id":922154,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Plunkett, Gill 0000-0003-1014-3454","orcid":"https://orcid.org/0000-0003-1014-3454","contributorId":288522,"corporation":false,"usgs":false,"family":"Plunkett","given":"Gill","email":"","affiliations":[{"id":61787,"text":"Queen’s University Belfast","active":true,"usgs":false}],"preferred":false,"id":922155,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Vallance, James W. 0000-0002-3083-5469 jvallance@usgs.gov","orcid":"https://orcid.org/0000-0002-3083-5469","contributorId":547,"corporation":false,"usgs":true,"family":"Vallance","given":"James","email":"jvallance@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":922156,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Luo, Yantao","contributorId":204972,"corporation":false,"usgs":false,"family":"Luo","given":"Yantao","email":"","affiliations":[{"id":37017,"text":"College of Mathematics and System Sciences, Xinjiang University","active":true,"usgs":false}],"preferred":false,"id":922157,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Cwynar, Les C. 0000-0002-4415-6352","orcid":"https://orcid.org/0000-0002-4415-6352","contributorId":347678,"corporation":false,"usgs":false,"family":"Cwynar","given":"Les C.","affiliations":[{"id":83204,"text":"Department of Biology, University of New Brunswick, Fredericton, Canada","active":true,"usgs":false}],"preferred":false,"id":922158,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Hughes, Paul","contributorId":220209,"corporation":false,"usgs":false,"family":"Hughes","given":"Paul","email":"","affiliations":[{"id":40153,"text":"University of South Hampton, UK","active":true,"usgs":false}],"preferred":false,"id":922159,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Pearson, D. Graham","contributorId":347679,"corporation":false,"usgs":false,"family":"Pearson","given":"D. Graham","affiliations":[{"id":83205,"text":"Department of Earth and Atmospheric Sciences, University of Alberta, Canada","active":true,"usgs":false}],"preferred":false,"id":922160,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70261208,"text":"70261208 - 2024 - Mapping and classification of volcanic deposits using multi-sensor unoccupied aerial systems","interactions":[],"lastModifiedDate":"2024-11-29T15:29:11.814371","indexId":"70261208","displayToPublicDate":"2021-10-01T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Mapping and classification of volcanic deposits using multi-sensor unoccupied aerial systems","docAbstract":"The deposits from volcanic eruptions represent the record of activity at a volcano. Identification, classification, and interpretation of these deposits are crucial to the understanding of volcanic processes and assessing hazards. However, deposits often cover large areas and can be difficult or dangerous to access, making field mapping dangerous and time-consuming. Remote sensing techniques are often used to map and identify the deposits of volcanic eruptions, though these techniques present their own trade-offs in terms of image resolution, wavelength, and observation frequency. Here, we present a new approach for mapping and classifying volcanic deposits using a multi-sensor unoccupied aerial system (UAS), and demonstrate its application on lava and tephra deposits associated with the 2018 eruption of Sierra Negra volcano (Galápagos Archipelago, Ecuador). We surveyed the study area and collected visible and thermal infrared (TIR) images. We used structure-from-motion photogrammetry to create a digital elevation model (DEM) from the visual images and calculated the solar heating rate of the surface from temperature maps based on the TIR images. We find that the solar heating rate is highest for tephra deposits and lowest for ʻaʻā lava, with pāhoehoe lava having intermediate values. This is consistent with the solar heating rate correlating to the density and particle size of the surface. The solar heating rate for the lava flow also decreases with increasing distance from the vent, consistent with an increase in density as the lava degasses. We combined the surface roughness (calculated from the DEM) and the solar heating rate of the surface to remotely classify tephra deposits and different lava morphologies. We applied both supervised and unsupervised machine learning algorithms and demonstrate that supervised methods can replicate the manual classification while the unsupervised method can identify major surface units with no ground truth information. These methods allow for remote mapping and classification at high spatial resolution (< 1 meter) of a variety of volcanic deposits, with potential for application to deposits from other processes (e.g., fluvial, glacial) and deposits on other planetary bodies.","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2021.112581","usgsCitation":"Carr, B.B., Lev, E., Sawi, T., Bennett, K.A., Edwards, C., Soule, S.A., Vallejo Vargas, S., and Marliyani, G.I., 2024, Mapping and classification of volcanic deposits using multi-sensor unoccupied aerial systems: Remote Sensing of Environment, v. 264, 112581, 19 p., https://doi.org/10.1016/j.rse.2021.112581.","productDescription":"112581, 19 p.","ipdsId":"IP-120876","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467061,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2021.112581","text":"Publisher Index Page"},{"id":464592,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Ecuador","otherGeospatial":"Galápagos Archipelago, Sierra Negra volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.2511100637289,\n -0.5953009426430782\n ],\n [\n -91.2511100637289,\n -0.8970296668221494\n ],\n [\n -91.0263665395592,\n -0.8970296668221494\n ],\n [\n -91.0263665395592,\n -0.5953009426430782\n ],\n [\n -91.2511100637289,\n -0.5953009426430782\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"264","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Carr, Brett B. 0000-0002-1033-3082","orcid":"https://orcid.org/0000-0002-1033-3082","contributorId":305984,"corporation":false,"usgs":true,"family":"Carr","given":"Brett","email":"","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":919860,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lev, Einat 0000-0002-8174-0558","orcid":"https://orcid.org/0000-0002-8174-0558","contributorId":194355,"corporation":false,"usgs":false,"family":"Lev","given":"Einat","email":"","affiliations":[{"id":27369,"text":"Lamont-Doherty Earth Observatory at Columbia University","active":true,"usgs":false}],"preferred":false,"id":919861,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sawi, Theresa","contributorId":346761,"corporation":false,"usgs":false,"family":"Sawi","given":"Theresa","email":"","affiliations":[{"id":82958,"text":"Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY","active":true,"usgs":false}],"preferred":false,"id":919862,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bennett, Kristen A. 0000-0001-8105-7129","orcid":"https://orcid.org/0000-0001-8105-7129","contributorId":237068,"corporation":false,"usgs":true,"family":"Bennett","given":"Kristen","email":"","middleInitial":"A.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":919863,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Edwards, Christopher S.","contributorId":206168,"corporation":false,"usgs":false,"family":"Edwards","given":"Christopher S.","affiliations":[{"id":7202,"text":"NAU","active":true,"usgs":false}],"preferred":false,"id":919864,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Soule, S. Adam 0000-0002-4691-6300","orcid":"https://orcid.org/0000-0002-4691-6300","contributorId":221052,"corporation":false,"usgs":false,"family":"Soule","given":"S.","email":"","middleInitial":"Adam","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":919865,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vallejo Vargas, Silvia","contributorId":212772,"corporation":false,"usgs":false,"family":"Vallejo Vargas","given":"Silvia","email":"","affiliations":[{"id":38680,"text":"Instituto Geofisico","active":true,"usgs":false}],"preferred":false,"id":919866,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Marliyani, Gayatri Indah 0000-0003-1356-9645","orcid":"https://orcid.org/0000-0003-1356-9645","contributorId":346762,"corporation":false,"usgs":false,"family":"Marliyani","given":"Gayatri","email":"","middleInitial":"Indah","affiliations":[{"id":82960,"text":"Department of Geological Engineering, Faculty of Engineering, Universitas Gadjah Mada, Yogyakarta, Indonesia","active":true,"usgs":false}],"preferred":false,"id":919867,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70261217,"text":"70261217 - 2024 - Historical and prehistorical water levels of Mormon Lake, Arizona as a measure of climate change on the southwest Colorado Plateau, USA","interactions":[],"lastModifiedDate":"2024-12-02T15:12:29.409176","indexId":"70261217","displayToPublicDate":"2021-03-01T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"Historical and prehistorical water levels of Mormon Lake, Arizona as a measure of climate change on the southwest Colorado Plateau, USA","docAbstract":"Mormon Lake, elevation 2166 m with maximum historic surface area of 31.4 km2, lies in a forested endorheic basin covering 103 km2. It is the largest unaltered freshwater body on the 337,000 km2 Colorado Plateau. Prehistorical (before AD 1878) highstands were ca. 9 and 24 m relative to depocenter datum. These levels likely occurred during four multidecadal episodes of cool, wet conditions between ca. 3.55 and 0.20 ka BP. Maximum historical levels (early 1900s) were up to 7.9 m, whereas modern (post-1941) levels were frequently zero or relatively low. Historical climate records indicate reconstructed lake levels correlate directly with annual precipitation and inversely with temperature. Early highstands were associated with above average precipitation and the lowest temperatures of the 116 yr record. The lake receded after 1941; thereafter, frequent drying and low-water levels resulted from recurrent drought and steadily increasing temperatures. Consequently, a wet episode from the 1970s to the 1990s had precipitation like the early 1900s, but highstands were only ca. 3.8 m. The historical lake-level chronology is consistent with changes of hydrologic balance predicted by climate models, that is, reduced effective precipitation (precipitation minus evaporation). These changes, particularly aridification, apparently began in the 1970s or earlier. Global oceanic and atmospheric climate modulate lake levels and regional hydroclimate.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/qua.2020.92","usgsCitation":"Hereford, R., and Amoroso, L., 2024, Historical and prehistorical water levels of Mormon Lake, Arizona as a measure of climate change on the southwest Colorado Plateau, USA: Quaternary Research, v. 100, p. 32-51, https://doi.org/10.1017/qua.2020.92.","productDescription":"20 p.","startPage":"32","endPage":"51","ipdsId":"IP-113940","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":464625,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Mormon Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.48876598336788,\n 34.98966103819039\n ],\n [\n -111.48876598336788,\n 34.906130634842924\n ],\n [\n -111.42028354514014,\n 34.906130634842924\n ],\n [\n -111.42028354514014,\n 34.98966103819039\n ],\n [\n -111.48876598336788,\n 34.98966103819039\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"100","noUsgsAuthors":false,"publicationDate":"2020-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Hereford, Richard 0000-0002-0892-7367 rhereford@usgs.gov","orcid":"https://orcid.org/0000-0002-0892-7367","contributorId":3620,"corporation":false,"usgs":true,"family":"Hereford","given":"Richard","email":"rhereford@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":919934,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Amoroso, Lee 0000-0003-1342-7487","orcid":"https://orcid.org/0000-0003-1342-7487","contributorId":346805,"corporation":false,"usgs":false,"family":"Amoroso","given":"Lee","affiliations":[],"preferred":false,"id":919935,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70261874,"text":"70261874 - 2024 - Petrology and geochemistry of three early Holocene eruptions from Makushin volcano, Alaska","interactions":[],"lastModifiedDate":"2024-12-31T15:58:26.095859","indexId":"70261874","displayToPublicDate":"2020-10-19T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Petrology and geochemistry of three early Holocene eruptions from Makushin volcano, Alaska","docAbstract":"Makushin stratovolcano, Alaska, produced three, highly explosive, andesitic eruptions between ~ 9292 and 6215 yBP. Those eruptions are informally named the CFE (“crater-forming eruption”), Nateekin, and Driftwood Pumice, and they deposited significant tephra fallout in the present-day port of Dutch Harbor and City of Unalaska area. The focus of this study is to examine the geochemistry and petrology of those eruptions to better understand Makushin volcano hazards, andesite petrogenesis and eruption triggering by mafic recharge processes. The CFE, Nateekin, and Driftwood Pumice samples range from basaltic andesite to dacite but are predominantly andesitic (SiO2 = 55.6 to 63.5 wt%). The CFE deposits are slightly compositionally stratified, with the top CFE samples slightly more mafic (55 to 60 wt% SiO2) than the basal deposits (58 to 60 wt% SiO2). Disequilibrium mineral compositions and textures in the CFE, Nateekin, and Driftwood Pumice samples, combined with two pyroxene thermometry and An-rich plagioclase microlites (An80) found only in the top of the CFE deposits, provide evidence for repetitive mafic recharge triggering those eruptions, consistent with prior studies. We compare the Makushin geochemical data with data from select satellite vents and cones in the Makushin Volcanic Field (MVF) from prior studies, to examine possible genetic relationships. The geochemical data and Rhyolite-MELTS models run at crustal storage conditions (2 kbar, fO2 = Ni-NiO, and 1.5 and 3.5 wt% H2O) indicate that no single parental magma supplies the MVF satellite cones and Makushin volcano. Instead, two component mixing models better fit the MVF geochemical array. Our Makushin results compare well with models of predominantly andesitic volcanoes that require mafic recharge to mobilize the andesites and trigger eruptions.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s00445-020-01412-5","usgsCitation":"Larsen, J., Schaefer, J., Vallance, J.W., and Neill, O., 2024, Petrology and geochemistry of three early Holocene eruptions from Makushin volcano, Alaska: Bulletin of Volcanology, v. 82, 72, 17 p., https://doi.org/10.1007/s00445-020-01412-5.","productDescription":"72, 17 p.","ipdsId":"IP-120635","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":465566,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Makushin volcano, Unalaska Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -167.01083004545683,\n 53.926684657654704\n ],\n [\n -167.01083004545683,\n 53.84297653402467\n ],\n [\n -166.85080239678533,\n 53.84297653402467\n ],\n [\n -166.85080239678533,\n 53.926684657654704\n ],\n [\n -167.01083004545683,\n 53.926684657654704\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2020-10-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Larsen, Jessica 0000-0003-1171-129X","orcid":"https://orcid.org/0000-0003-1171-129X","contributorId":242808,"corporation":false,"usgs":false,"family":"Larsen","given":"Jessica","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":922107,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schaefer, Janet","contributorId":199547,"corporation":false,"usgs":false,"family":"Schaefer","given":"Janet","affiliations":[],"preferred":false,"id":922108,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vallance, James W. 0000-0002-3083-5469 jvallance@usgs.gov","orcid":"https://orcid.org/0000-0002-3083-5469","contributorId":547,"corporation":false,"usgs":true,"family":"Vallance","given":"James","email":"jvallance@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":922109,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Neill, O.K.","contributorId":347659,"corporation":false,"usgs":false,"family":"Neill","given":"O.K.","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":922110,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}