Diagnostic laboratories receive carcasses and samples for diagnostic evaluation and pathogen/toxin detection. Case definitions bring clarity and consistency to the evaluation process. Their use within and between organizations allows more uniform reporting of diseases and etiologic agents. The intent of a case definition is to provide scientifically based criteria for determining (a) if an individual carcass has a specific disease and degree of confidence in that diagnosis and (b) if there is evidence of a pathogen or toxin in a carcass or sample (for example, swab, tissue sample, skin scraping, blood/serum sample, environmental sample, or other). This case definition is specific to Stony Coral Tissue Loss Disease (SCTLC) and applies to several species of scleractinian corals across seven families: Faviidae, Meandrinidae, Merulinidae, Montastraeidae, Astrocoeniidae, Scleractinia, and Siderastreidae. Other species presumed to be susceptible are in Families Agaridiidae, Faviidae, and Pocilloporidae.
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6006 Schroeder Road
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Broadly distributed across the Western United States, ungulates (hooved mammals) play an important role in ecosystem function by affecting vegetation communities and forming the prey base for large carnivores. Additionally, ungulates provide economic benefits to regional communities through tourism and hunting and hold cultural significance for many Tribal communities. Many ungulates migrate seasonally between distinct summer and winter ranges to take advantage of spatially and temporally variable food sources and avoid threats such as predators and deep snow. Increasingly, these migrations are threatened by the growing human footprint and associated subdivisions, energy development, and increased traffic volume. Efforts to study ungulate populations and conserve their migrations received support in recent years from the U.S. Department of the Interior Secretarial Order No. 3362, which provided Federal support for enhancing habitat quality for ungulates across the Western States. In response to Secretarial Order No. 3362, the U.S. Geological Survey (USGS) established the Corridor Mapping Team, a collaboration among USGS and participating State and Federal wildlife management agencies and numerous Tribal Nations. Together, the Corridor Mapping Team maps ungulate migrations throughout the Western United States in the USGS “Ungulate Migrations of the Western United States” report series. This report (volume 4) details migrations and seasonal ranges from 31 new herds throughout nine Western States. Additionally, this report includes updates to two herds published in previous reports. Including this report, the report series has provided the mapped migrations and seasonal ranges of 182 unique herds and has provided a map-based inventory of the documented ungulate migrations across the Western United States for biologists, managers, policy makers, and conservation practitioners. This report also discusses how the mapping efforts associated with the Corridor Mapping Team can be used to guide management and policy regarding renewable energy development and ungulate disease, specifically chronic wasting disease, in the Western United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20245006","issn":"2328-031X; 2328-0328","isbn":"978-1-4113-4545-4","usgsCitation":"Kauffman, M., Lowrey, B., Beaupre, C., Bergen, S., Bergh, S., Blecha, K., Bundick, S., Burkett, H., Cain, J.W., III, Carl, P., Casady, D., Class, C., Courtemanch, A., Cowardin, M., Diamond, J., Dugger, K., Duvuvuei, O., Ennis, J.R., Flenner, M., Fort, J., Fralick, G., Freeman, I., Gagnon, J., Garcelon, D., Garrison, K., Gelzer, E., Greenspan, E., Hinojoza-Rood, V., Hnilicka, P., Holland, A., Hudgens, B., Kroger, B., Lawson, A., McKee, C., McKee, J.L., Merkle, J.R., Mong, T.W., Nelson, H., Oates, B., Poulin, M.-P., Reddell, C., Ritson, R., Sawyer, H., Schroeder, C., Shapiro, J., Sprague, S., Steiner, E., Steingisser, A., Stephens, S., Stringham, B., Swazo-Hinds, P.R., Tatman, N., Wallace, C.F., Whittaker, D., Wise, B., Wittmer, H.U., and Wood, E., 2024, Ungulate migrations of the Western United 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\"}}]}","contact":"Associate Director, Ecosystems Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 300
Reston, VA 20192
Ecosystems that are coupled by reciprocal flows of energy and nutrient subsidies can be viewed as a single “meta-ecosystem.” Despite these connections, the reciprocal flow of subsidies is greatly asymmetrical and seasonally pulsed. Here, we synthesize existing literature on stream–riparian meta-ecosystems to quantify global patterns of the amount of subsidy consumption by organisms, known as “allochthony.” These resource flows are important since they can comprise a large portion of consumer diets, but can be disrupted by human modification of streams and riparian zones. Despite asymmetrical subsidy flows, we found stream and riparian consumer allochthony to be equivalent. Although both fish and stream invertebrates rely on seasonally pulsed allochthonous resources, we find allochthony varies seasonally only for fish, being nearly three times greater during the summer and fall than during the winter and spring. We also find that consumer allochthony varies with feeding traits for aquatic invertebrates, fish, and terrestrial arthropods, but not for terrestrial vertebrates. Finally, we find that allochthony varies by climate for aquatic invertebrates, being nearly twice as great in arid climates than in tropical climates, but not for fish. These findings are critical to understanding the consequences of global change, as ecosystem connections are being increasingly disrupted.
Incorporating societal considerations into decisions related to invasive species management is desirable, but can be challenging because it requires a solid understanding of the ecological functions and socio-cultural and economic benefits and values of the invaded environment before and after invasion. The ecosystem service (ES) concept was designed to facilitate such decision-making by establishing direct connections between ecosystem properties and human well-being, but its application in invasive species management has not been systematic. In this Discussion paper, we propose the adoption of the ES cascade model as a framework for understanding the environmental effects, costs and benefits associated with controlling an invasive shrub (Tamarix spp.) in riparian systems of the western United States. The cascade model has the advantage of explicitly dissecting social-ecological systems into five components: ecosystem structure and processes, ecological functions, ecosystem services, benefits and the economic and socio-cultural valuation of these services and benefits. The first two have received significant attention in the evaluation of Tamarix control effectiveness. The last three have long been implicitly acknowledged over decades of Tamarix management in the region, but have not been formally accounted for, which we believe would increase the effectiveness, accountability and transparency of management efforts.
Knowledge of the spatial and temporal distribution of surface water is important for water resource management, flood risk assessment, monitoring ecosystem health, constraining estimates of biogeochemical cycles and understanding our climate. While global-scale spatiotemporal change detection of surface water has significantly improved in recent years due to planetary-scale remote sensing and computing, it has remained challenging to distinguish the changing characteristics of rivers and lakes. Here we analyze the spatial extent of permanent and seasonal rivers and lakes globally over the past 38 years based on new data of river system extents and surface water trends. Results show that while the total permanent surface area of both rivers and lakes has remained relatively constant, the areas with intermittent seasonal coverage have increased by 12 % and 27 % for rivers and lakes, respectively. The increase is statistically significant in over 84 % of global water catchments based on Spearman's rank correlations (rho) above 0.05 and p values less than 0.05. The seasonal river extent is nearly 32 % larger than the previously observed annual mean river extent, suggesting large seasonal variations that impact not only ecosystem health but also estimations of terrestrial biogeochemical cycles of carbon. The outcomes of our analysis are shared as the Surface Area of Rivers and Lakes (SARL) database, serving as a valuable resource for monitoring and research of hydrological cycles, ecosystem accounting, and water management.
Volcanic islands are often subject to flank instability, resulting from a combination of magmatic intrusions along rift zones and gravitational spreading causing extensional faulting at the surface. Here, we study the Koaʻe fault system (KFS), located south of the summit caldera of Kīlauea volcano in Hawaiʻi, one of the most active volcanoes on Earth, prone to active faulting, episodic dike intrusions, and flank instability. Two rift zones and the KFS are major structures controlling volcanic flank instability and magma propagation. Although several magmatic intrusions occurred over the KFS, the link between these faults, two nearby rift zones and the flank instability, is still poorly studied. To better characterize the KFS and its structural linkage with the surrounding fault and rift zones, we performed a detailed structural analysis of the extensional fault system, coupled with a helicopter photogrammetric survey, covering part of the south flank of Kīlauea. We generated a high-resolution DEM (~ 8 cm) and orthomosaic (~ 4 cm) to map the fracture field in detail. We also collected ~ 1000 ground structural measurements of extensional fractures during our three field missions (2019, 2022, and 2023). We observed many small, interconnected grabens, monoclines, rollover structures, and en-echelon fractures that were in part previously undocumented. We estimate the cumulative displacement rate across the KFS during the last 600 ~ 700 years and found a decrease toward the west of the horizontal component from 2 to 6 cm per year, consistent with GNSS data. Integrating morphology observations, fault mapping, and kinematic measurements, we propose a new kinematic model of the upper part of the Kīlauea’s south flank, suggesting a clockwise rotation and a translation of a triangular wedge. This wedge is bordered by the extensional structures (ERZ, SWRZ, and the KFS), largely influenced by gravitational spreading. These findings illustrate a structural linkage between the two rift zones and the KFS, the latter being episodically affected by dike intrusions.
Infectious diseases are influenced by interactions between host and pathogen, and the number of infected hosts is rarely homogenous across the landscape. Areas with elevated pathogen prevalence can maintain a high force of infection and may indicate areas with disease impacts on host populations. However, isolating the ecological processes that result in increases in infection prevalence and intensity remains a challenge. Here we elucidate the contribution of pathogen clade and host species in disease hotspots caused by Ophidiomyces ophidiicola, the pathogen responsible for snake fungal disease, in 21 species of snakes infected with multiple pathogen strains across 10 countries in Europe. We found isolated areas of disease hotspots in a landscape where infections were otherwise low. O. ophidiicola clade had important effects on transmission, and areas with multiple pathogen clades had higher host infection prevalence. Snake species further influenced infection, with most positive detections coming from species within the Natrix genus. Our results suggest that both host and pathogen identity are essential components contributing to increased pathogen prevalence.
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Hungary","active":true,"usgs":false}],"preferred":false,"id":899415,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kolanek, Aleksandra","contributorId":335754,"corporation":false,"usgs":false,"family":"Kolanek","given":"Aleksandra","email":"","affiliations":[{"id":64462,"text":"University of Wroclaw","active":true,"usgs":false}],"preferred":false,"id":899416,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kurek, Katarzyna","contributorId":335755,"corporation":false,"usgs":false,"family":"Kurek","given":"Katarzyna","email":"","affiliations":[{"id":80500,"text":"Institute of Nature Conservation Polish Academy of Science","active":true,"usgs":false}],"preferred":false,"id":899417,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lourdais, Olivier","contributorId":335756,"corporation":false,"usgs":false,"family":"Lourdais","given":"Olivier","email":"","affiliations":[{"id":80501,"text":"Centre d’Etudes Biologiques de Chizé","active":true,"usgs":false}],"preferred":false,"id":899418,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Michon, Alix","contributorId":335757,"corporation":false,"usgs":false,"family":"Michon","given":"Alix","email":"","affiliations":[{"id":80502,"text":"LPO Bourgogne-Franche-Comté, Maison de l’environnement de BFC","active":true,"usgs":false}],"preferred":false,"id":899419,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Musilova, Radka","contributorId":335758,"corporation":false,"usgs":false,"family":"Musilova","given":"Radka","email":"","affiliations":[{"id":80503,"text":"Zamenis Civic Association","active":true,"usgs":false}],"preferred":false,"id":899420,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Schweiger, Silke","contributorId":335759,"corporation":false,"usgs":false,"family":"Schweiger","given":"Silke","email":"","affiliations":[{"id":80504,"text":"Natural History Museum, Vienna","active":true,"usgs":false}],"preferred":false,"id":899421,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Szulc, Barbara","contributorId":335760,"corporation":false,"usgs":false,"family":"Szulc","given":"Barbara","email":"","affiliations":[{"id":80505,"text":"Kazimierz Wielki University","active":true,"usgs":false}],"preferred":false,"id":899422,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Ursenbacher, Sylvain","contributorId":335761,"corporation":false,"usgs":false,"family":"Ursenbacher","given":"Sylvain","email":"","affiliations":[{"id":37150,"text":"University of Neuchâtel","active":true,"usgs":false}],"preferred":false,"id":899423,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Zinenko, Oleksandr","contributorId":335762,"corporation":false,"usgs":false,"family":"Zinenko","given":"Oleksandr","email":"","affiliations":[{"id":80506,"text":"Museum of Nature at V.N. Karazin Kharkiv National University","active":true,"usgs":false}],"preferred":false,"id":899424,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Hoyt, Joseph R.","contributorId":201314,"corporation":false,"usgs":false,"family":"Hoyt","given":"Joseph","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":899425,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70254548,"text":"70254548 - 2024 - Concept of a satellite cross-calibration radiometer for in-orbit calibration of commercial optical satellites","interactions":[],"lastModifiedDate":"2024-05-31T14:14:31.067436","indexId":"70254548","displayToPublicDate":"2024-04-10T08:48:19","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Concept of a satellite cross-calibration radiometer for in-orbit calibration of commercial optical satellites","docAbstract":"The satellite Earth observation (EO) sector is burgeoning with hundreds of commercial satellites being launched each year, delivering a rich source of data that could be exploited for societal benefit. Data streams from the growing number of commercial satellites are of variable quality, limiting the potential for their combined use in science applications that need long time-series data from multiple sources. The quality of calibration performed on optical sensors onboard many satellite systems is highly variable due to calibration methods, sensor design, mission objective, budget, or other operational constraints. A small number of currently operating well-characterised satellite systems with onboard calibration, such as Landsat-8/9 and Sentinel-2, and planned future missions, like the NASA Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder, the European Space Agency (ESA)’s Traceable Radiometry Underpinning Terrestrial and Helio Studies (TRUTHS), and LIBRA from China, are considered benchmarks for optical data quality due to their traceability to international measurement standards. This paper describes the concept of a space-based transfer calibration radiometer called the Satellite Cross-Calibration Radiometer (SCR) that would enable the calibration parameters from satellites such as Landsat-8/9, Sentinel-2, or other benchmark systems to be transferred to a range of commercial optical EO satellite systems while in orbit. A description of the key characteristics of the SCR to successfully operate in orbit and transfer calibration from reference systems to client systems is presented. A system like the SCR in orbit could complement SI-Traceable satellites (SITSats) to improve data quality and consistency and facilitate the interoperable use of data from multiple optical sensor systems for delivering higher returns on the global investment in EO.
","language":"English","publisher":"MDPI","doi":"10.3390/rs16081333","usgsCitation":"Thankappan, M., Christopherson, J., Cantrell, S.J., Ryan, R., Pagnutti, M., Bright, C., Naughton, D., Ruslander, K.L., Wang, L., Hudson, D., Shaw, J., Ramaseri Chandra, S.N., and Anderson, C., 2024, Concept of a satellite cross-calibration radiometer for in-orbit calibration of commercial optical satellites: Remote Sensing, v. 16, no. 8, 1333, 20 p., https://doi.org/10.3390/rs16081333.","productDescription":"1333, 20 p.","ipdsId":"IP-161574","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":439890,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs16081333","text":"Publisher Index Page"},{"id":429400,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"8","noUsgsAuthors":false,"publicationDate":"2024-04-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Thankappan, Medhavy","contributorId":337054,"corporation":false,"usgs":false,"family":"Thankappan","given":"Medhavy","email":"","affiliations":[{"id":80959,"text":"Geosciences Australia (GA)","active":true,"usgs":false}],"preferred":false,"id":901854,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christopherson, Jon 0000-0002-2472-0059 jonchris@usgs.gov","orcid":"https://orcid.org/0000-0002-2472-0059","contributorId":2552,"corporation":false,"usgs":true,"family":"Christopherson","given":"Jon","email":"jonchris@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":901855,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cantrell, Simon John 0000-0001-6909-1973","orcid":"https://orcid.org/0000-0001-6909-1973","contributorId":337055,"corporation":false,"usgs":true,"family":"Cantrell","given":"Simon","email":"","middleInitial":"John","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":901856,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ryan, Robert","contributorId":337056,"corporation":false,"usgs":false,"family":"Ryan","given":"Robert","affiliations":[{"id":80960,"text":"Innovative Imaging and Research Inc. (I2R)","active":true,"usgs":false}],"preferred":false,"id":901857,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pagnutti, Mary","contributorId":337057,"corporation":false,"usgs":false,"family":"Pagnutti","given":"Mary","email":"","affiliations":[{"id":80960,"text":"Innovative Imaging and Research Inc. (I2R)","active":true,"usgs":false}],"preferred":false,"id":901858,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bright, Courtney","contributorId":337058,"corporation":false,"usgs":false,"family":"Bright","given":"Courtney","email":"","affiliations":[{"id":80961,"text":"Commonwealth Scientific and Industrial Research Organisation (CSIRO)","active":true,"usgs":false}],"preferred":false,"id":901860,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Naughton, Denis","contributorId":337059,"corporation":false,"usgs":false,"family":"Naughton","given":"Denis","email":"","affiliations":[{"id":80959,"text":"Geosciences Australia (GA)","active":true,"usgs":false}],"preferred":false,"id":901861,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ruslander, Kathryn Lynn 0000-0003-3036-1731","orcid":"https://orcid.org/0000-0003-3036-1731","contributorId":337060,"corporation":false,"usgs":true,"family":"Ruslander","given":"Kathryn","email":"","middleInitial":"Lynn","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":901862,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wang, Lan-Wei","contributorId":337061,"corporation":false,"usgs":false,"family":"Wang","given":"Lan-Wei","affiliations":[{"id":80959,"text":"Geosciences Australia (GA)","active":true,"usgs":false}],"preferred":false,"id":901863,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hudson, David","contributorId":337062,"corporation":false,"usgs":false,"family":"Hudson","given":"David","affiliations":[{"id":80959,"text":"Geosciences Australia (GA)","active":true,"usgs":false}],"preferred":false,"id":901864,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Shaw, Jerad 0000-0002-8319-2778 jshaw@usgs.gov","orcid":"https://orcid.org/0000-0002-8319-2778","contributorId":3564,"corporation":false,"usgs":true,"family":"Shaw","given":"Jerad","email":"jshaw@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":901865,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ramaseri Chandra, Shankar N. 0000-0002-4434-4468","orcid":"https://orcid.org/0000-0002-4434-4468","contributorId":216043,"corporation":false,"usgs":true,"family":"Ramaseri Chandra","given":"Shankar","email":"","middleInitial":"N.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":901859,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Anderson, Cody 0000-0001-5612-1889 chanderson@usgs.gov","orcid":"https://orcid.org/0000-0001-5612-1889","contributorId":195521,"corporation":false,"usgs":true,"family":"Anderson","given":"Cody","email":"chanderson@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":901866,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70256587,"text":"70256587 - 2024 - Artificial structure selection by economically important reef fishes at North Carolina artificial reefs","interactions":[],"lastModifiedDate":"2024-08-06T12:30:55.981873","indexId":"70256587","displayToPublicDate":"2024-04-10T07:23:05","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Artificial structure selection by economically important reef fishes at North Carolina artificial reefs","docAbstract":"Artificial reefs can play an important role in marine fisheries management by supplementing or enhancing natural habitats. Despite their increased use in recent years, the choice of structures used at artificial reefs remains largely haphazard due to the lack of information on reef structure performance. Few studies have examined the use of different artificial reef structures by individual fish. From 2021-2022, we acoustically tagged 72 black sea bass (Centropristis striata), 34 gag (Mycteroperca mircrolepis), 27 greater amberjack (Seriola dumerili), nine almaco jack (S. rivoliana), and eight red snapper (Lutjanus campechanus) on four artificial reef complexes near Cape Lookout, North Carolina, U.S. Available artificial reef structures consisted of materials of various sizes and heights made of concrete and metal. We tracked tagged fish using a fine-scale positioning system for ~100 days. Black sea bass exhibited high site fidelity to the artificial structure where we caught them, rarely moving away from that structure. The limited movement resulted in low transition probabilities; we conclude that black sea bass do not select for particular artificial structures. Gag and red snapper moved greater distances away from artificial structures and routinely moved between them. Greater amberjack and almaco jack moved the most within the complexes displaying circling behavior around individual structures and were the only species that regularly moved off the artificial reef complexes. Greater amberjack movements away from artificial sites were most commonly directed to surrounding shipwrecks. Whereas gag, red snapper, almaco jack, and greater amberjack used all available structures, they consistently selected for high relief structures, such as vessels, more than other structures. These results will be useful to managers charged with decisions on what types of structures to place at artificial reef complexes to supplement or enhance habitat for economically important fishes.
Magnetotelluric (MT) and audiomagnetotelluric (AMT) data are used to better understand the subsurface geology and mineral resources in the San Juan–Silverton caldera complex located near Silverton, Colorado, western United States, as part of the extensive southern Rocky Mountains volcanic field that covers much of southwestern Colorado and northern New Mexico. Seven MT and AMT profiles of varying lengths image resistivity structure to depths of ~5 km. The AMT inversion models characterize geophysical responses of near-surface lithologies, structures, and mineralized systems and also help corroborate airborne electromagnetic data at shallow levels. The MT inversion models extend our depth of investigation from near the surface to great depths (~5 km) and help to form hypotheses about roots of the hydrothermal plumbing that fed shallower mineralized systems. Subsurface high resistivities occur beneath intermediate-composition lava flows and Proterozoic units. Subsurface moderate- to low-resistivity values may reflect hydrothermal plumbing that served as flow paths for mineralizing fluids and metallic ore formation. The model interpretations presented in this study could be utilized in remediation planning or mineral resource applications. The methods used could be applied to other watersheds with similar volcanic environments containing acid-generating historical mines or hydrothermally altered and mineralized source rocks.
This paper aims to expand fisheries managers' understanding of how the science of communication can facilitate effective fisheries management. We offer context-specific definitions of four communication approaches that are commonly performed by fisheries managers but poorly defined and can easily be confused or conflated. These are as follows:
Genetic variation in Arctic species is often influenced by vicariance during the Pleistocene, as ice sheets fragmented the landscape and displaced populations to low- and high-latitude refugia. The formation of secondary contact or suture zones during periods of ice sheet retraction has important consequences on genetic diversity by facilitating genetic connectivity between formerly isolated populations. Brant geese (Branta bernicla) are a maritime migratory waterfowl (Anseriformes) species that almost exclusively uses coastal habitats. Within North America, brant geese are characterized by two phenotypically distinct subspecies that utilize disjunct breeding and wintering areas in the northern Pacific and Atlantic. In the Western High Arctic of Canada, brant geese consist of individuals with an intermediate phenotype that are rarely observed nesting outside this region. We examined the genetic structure of brant geese populations from each subspecies and areas consisting of intermediate phenotypes using mitochondrial DNA (mtDNA) control region sequence data and microsatellite loci. We found a strong east–west partition in both marker types consistent with refugial populations. Within subspecies, structure was also observed at mtDNA while microsatellite data suggested the presence of only two distinct genetic clusters. The Western High Arctic (WHA) appears to be a secondary contact zone for both Atlantic and Pacific lineages as mtDNA and nuclear genotypes were assigned to both subspecies, and admixed individuals were observed in this region. The mtDNA sequence data outside WHA suggests no or very restricted intermixing between Atlantic and Pacific wintering populations which is consistent with published banding and telemetry data. Our study indicates that, although brant geese in the WHA are not a genetically distinct lineage, this region may act as a reservoir of genetic diversity and may be an area of high conservation value given the potential of low reproductive output in this species.
We introduce a Python package for computing focal mechanism solutions. This algorithm, which we refer to as SKHASH, is largely based on the HASH algorithm originally written in Fortran over 20 yr ago. HASH innovated the use of suites of solutions, spanning the expected errors in polarities and takeoff angles, to estimate focal mechanism uncertainty. SKHASH benefits from new features with flexible input formats and allows users to take advantage of recent advances in constraining focal mechanisms for small magnitude or poorly recorded earthquakes. The 3D locations of earthquakes and the velocity models used are varied when finding acceptable solutions. As a result, source–receiver azimuths are reflective of errors from the earthquake locations and velocity models, in addition to the takeoff angles. Users can consider weighted P‐wave first‐motion polarities derived from traditional or machine‐learning picks, cross‐correlation consensus, and/or imputation techniques using SKHASH. Focal mechanism solutions can also be further constrained using traditional, machine learning, and/or cross‐correlation consensus S/P amplitude ratios. With improved reporting of individual and collective P polarity and S/P amplitude misfits, users can better evaluate the success of the solutions and the quality of the measurements. The reporting also makes it easier to identify potential issues with metadata, including incorrectly reported station polarity reversals. In addition, by leveraging vectorized operations, taking advantage of an efficient backend Python C Application Programming Interface, and the use of a parallel environment, the Python SKHASH routine may compute mechanisms quicker than the HASH routine.
High subsidence rates are inherent to coastal deltas worldwide, contributing to rapid rates of relative sea-level rise and compromising the sustainability of coastal wetlands. Different parts of river deltas, however, experience accretion or erosion, depending on the coupling between ecological and morphological processes. Wetland expansion occurs in active deltaic coastal basins that are connected to riverine sedimentation. In contrast, wetland degradation occurs in inactive deltaic coastal basins where river engineering strategies associated with flood control restrict river connectivity. Here, we investigated the relative role of inorganic and organic loading to marsh accretion rates spanning fresh to brackish to saline zones between active and inactive coastal deltaic floodplains of the Mississippi River Delta. Marsh surface accretion rates monitored over 36 months using the feldspar marker horizon technique ranged from 1.24 ± 0.35 cm yr−1 in the freshwater marsh to 2.94 ± 0.51 cm yr−1 in the saline marsh in the inactive coastal basin compared to an opposite trend in the active coastal basin with a low vertical accretion rate in the saline site at 1.12 ± 0.17 cm yr−1 and higher accretion values at the freshwater site (2.14 ± 0.49 cm yr−1). Our results suggest that saline marshes have high resilience identified by high vertical accretion rates exceeding those of river-dominated freshwater marshes in active deltaic floodplains. Overall, the marsh surface accretionary patterns detected in this study underscores the relative contribution of organic and inorganic sediments to elevation capital across salinity gradients between active and inactive basins in coastal Louisiana with particular interest to river management and restoration strategies. These findings, however, are applicable to coastal deltaic floodplains elsewhere given the repetition geomorphic forcings (e.g., relative contribution of riverine, tidal and wave power) and coastal typologies worldwide.
In 2021, the Alaska Volcano Observatory responded to eruptions, volcanic unrest or suspected unrest, increased seismicity, and other significant activity at 15 volcanic centers in Alaska and the Commonwealth of the Northern Mariana Islands. Eruptive activity in Alaska consisted of repeated small, ash-producing, phreatomagmatic explosions from Mount Young on Semisopochnoi Island; an explosion at Great Sitkin Volcano followed by the eruption of a thick lava flow that filled and overflowed the summit crater; weak explosive activity and the eruption of small, channelized flows at Pavlof Volcano; and a short-lived eruption at Mount Veniaminof that produced ash emissions from an intracaldera cone, as well as lava flows confined to a melt pit in the ice mantling the cone’s flank. Mount Cleveland had a period of unrest, but no eruptive activity took place there. Anomalous seismicity was also detected at Atka volcanic complex, Mount Gareloi, and Davidof volcano. New warm springs opened and deposited mud at the summit and north base of Shrub mud volcano. Other activity of note in Alaska consisted of large ice and rock avalanches at Iliamna Volcano and Mount Spurr, ash resuspension events at Mount Katmai and Aniakchak Crater, and anomalous deformation at Mount Okmok that was consistent with a shallow intrusion of magma. In the Commonwealth of the Northern Marianas Islands, a brief, ash-producing eruption occurred at Mount Pagan.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245014","collaboration":"The Alaska Volcano Observatory is a consortium between the U.S. Geological Survey, the University of Alaska Fairbanks Geophysical Institute, and the Alaska Division of Geological & Geophysical Surveys","usgsCitation":"Orr, T.R., Dietterich, H.R., Fee D., Girona, T., Grapenthin, R., Haney, M.M., Loewen, M.W., Lyons, J.J., Power, J.A., Schwaiger, H.F., Schneider, D.J., Tan, D., Toney, L., Wasser, V.K., Waythomas, C.F., 2024, 2021 Volcanic activity in Alaska and the Commonwealth of the Northern Mariana Islands—Summary of events and response of the Alaska Volcano Observatory: U.S. Geological Survey Scientific Investigations Report 2024–5014, 64 p., https://doi.org/10.3133/sir20245014.","productDescription":"ix, 64 p.","numberOfPages":"64","onlineOnly":"Y","ipdsId":"IP-139235","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":427361,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5014/sir20245014.pdf","text":"Report","size":"26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5014"},{"id":427360,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5014/covrthb.jpg"}],"country":"Northern Mariana Islands, United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -180.91039541038674,\n 52.397333461784\n ],\n [\n -179.15258291038657,\n 50.647658713281515\n ],\n [\n -154.36742666038634,\n 54.59269911796724\n ],\n [\n -144.8752391603861,\n 61.7067556778085\n ],\n [\n -148.56664541038634,\n 63.09098661447797\n ],\n [\n -154.01586416038626,\n 61.95569747993264\n ],\n [\n -158.93773916038643,\n 59.28407472678845\n ],\n [\n -165.7932079103864,\n 55.399337204164055\n ],\n [\n -173.17602041038666,\n 53.76976304468752\n ],\n [\n -178.62523916038657,\n 52.71793714020785\n ],\n [\n -180.91039541038674,\n 52.397333461784\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 146,\n 20\n ],\n [\n 146,\n 14\n ],\n [\n 144,\n 14\n ],\n [\n 144,\n 20\n ],\n [\n 146,\n 20\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Alaska Volcano Observatory
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Anchorage, AK 99508
The Alaska Volcano Observatory responded to eruptions, volcanic unrest or suspected unrest, increased seismicity, and other significant activity at nine volcanic centers in Alaska in 2020. The most notable volcanic activity in 2020 was an eruption of Shishaldin Volcano, which produced lava flows, lahars, and ash. Mount Cleveland had one small ash-producing eruption in June but was quiet thereafter. Other activity documented in 2020 consisted of elevated seismicity at the volcanoes Mount Veniaminof, Pavlof Volcano, Makushin Volcano, Atka volcanic complex (Korovin Volcano), Great Sitkin Volcano, and Semisopochnoi Island. Finally, the resuspension of ash deposited during the 1912 Novarupta-Katmai eruption was documented on three occasions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245004","collaboration":"The Alaska Volcano Observatory is a consortium between the U.S. Geological Survey, the University of Alaska Fairbanks Geophysical Institute, and the Alaska Division of Geological & Geophysical Surveys","usgsCitation":"Orr, T., Cameron, C., Dietterich, H., Loewen, M., Lopez, T., Lyons, J., Nakai, J., Power, J., Searcy, C., Tepp, G., and Waythomas, C., 2024, 2020 Volcanic activity in Alaska—Summary of events and response of the Alaska Volcano Observatory (ver. 1.1, September 2024): U.S. Geological Survey Scientific Investigations Report 2024–5004, 34 p., https://doi.org/10.3133/sir20245004.","productDescription":"vii, 34 p.","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-139376","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":428469,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2024/5004/versionHist.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"}},{"id":427363,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5004/sir20245004.pdf","text":"Report","size":"14 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":427362,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5004/covrthb2.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -180.91039541038674,\n 52.397333461784\n ],\n [\n -179.15258291038657,\n 50.647658713281515\n ],\n [\n -154.36742666038634,\n 54.59269911796724\n ],\n [\n -144.8752391603861,\n 61.7067556778085\n ],\n [\n -148.56664541038634,\n 63.09098661447797\n ],\n [\n -154.01586416038626,\n 61.95569747993264\n ],\n [\n -158.93773916038643,\n 59.28407472678845\n ],\n [\n -165.7932079103864,\n 55.399337204164055\n ],\n [\n -173.17602041038666,\n 53.76976304468752\n ],\n [\n -178.62523916038657,\n 52.71793714020785\n ],\n [\n -180.91039541038674,\n 52.397333461784\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: April 9, 2024; Version 1.1: September 9, 2024","contact":"Alaska Volcano Observatory
U.S. Geological Survey
4210 University Drive
Anchorage, AK 99508
Subtropical coastlines are impacted by both tropical and extratropical cyclones. While both may lead to substantial damage to coastal communities, it is difficult to determine the contribution of tropical cyclones to coastal flooding relative to that of extratropical cyclones. We conduct a large-scale flood hazard and impact assessment across the subtropical Southeast Atlantic Coast of the United States, from Virginia to Florida, including different flood hazards. The physics-based hydrodynamic modeling skillfully reproduces coastal water levels based on a comprehensive validation of tides, almost two hundred historical storms, and an in-depth hindcast of Hurricane Florence. We show that yearly flood impacts are two times as likely to be driven by extratropical than tropical cyclones. On the other hand, tropical cyclones are 30 times more likely to affect people during rarer 100-year events than extratropical cyclones and contribute to more than half of the regional flood risk. With increasing sea levels, more areas will be flooded, regardless of whether flooding is driven by tropical or extratropical cyclones. Most of the absolute flood risk is contained in the greater Miami metropolitan area. However, several less populous counties have the highest relative risks. The results of this study provide critical information for understanding the source and frequency of compound flooding across the Southeast Atlantic Coast of the United States.
Temperate bats exhibit seasonal and sex differences in resource selection and activity patterns that are influenced by ambient conditions. During fall, individuals face energetic trade-offs as they make choices relating to migration, mating, and hibernation that may diverge for populations throughout their range. However, research has largely focused on the summer maternity and winter hibernation seasons, whereas the prehibernation period remains comparatively understudied. Northern Myotis (Myotis septentrionalis) have experienced precipitous population declines from white-nose syndrome (WNS), leading to their protected status in the United States and Canada. Therefore, understanding their ecology throughout the year is paramount to inform conservation. We compared seasonal roosts and documented fall behaviors between study sites and sexes on 3 islands: Long Island (New York), Martha’s Vineyard, and Nantucket Island (Massachusetts). Between 2017 and 2020, we radio-tracked 54 individuals to analyze activity patterns and characterize fall roosts to compare with previously known summer roosts. Summer tree roosts were of smaller diameter, later stages of decay, and lower canopy closure than those used in fall. Both sexes selected trees of similar diameter and decay stage during fall. Anthropogenic roost use was documented in both seasons but use of anthropogenic structures was greater during fall and increased as the season progressed. Bats made short inter-roost movements with males traveling greater distances than females on average. Activity occurred until late November, with males exhibiting a longer active period than females. We tracked 23% of tagged bats to local hibernacula in subterranean anthropogenic structures, the majority of which were crawlspaces underneath houses. Use of anthropogenic structures for roosts and hibernacula may facilitate survival of this species in coastal regions despite the presence of WNS infections. Timing of restrictions on forest management activities for bat conservation may be mismatched based on prehibernation activity observed in these coastal populations, and the conservation of habitat surrounding anthropogenic roosts or hibernacula may be warranted if the structures themselves cannot be protected.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/jmammal/gyad102","usgsCitation":"Hoff, S., Pendergast, C., Johnson, L., Olson, E., O’Dell, D., Dowling, Z., Gorman, K., Herzog, C., and Turner, W.C., 2024, Seasonal roost characteristics and fall behavior of coastal populations of Northern Myotis (Myotis septentrionalis): Journal of Mammalogy, v. 105, no. 2, p. 277-288, https://doi.org/10.1093/jmammal/gyad102.","productDescription":"12 p.","startPage":"277","endPage":"288","ipdsId":"IP-143346","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480894,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts, New York","otherGeospatial":"Long Island, Martha’s Vineyard, Nantucket","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.35153543822253,\n 40.68250728063771\n ],\n [\n -71.20425429974898,\n 40.959427713267786\n ],\n [\n -69.7340634070562,\n 41.120884608917265\n ],\n [\n -69.74435677665623,\n 41.588231118968196\n ],\n [\n -71.56829797040606,\n 41.4328465540017\n ],\n [\n -73.37265407958067,\n 40.99602747786929\n ],\n [\n -73.35153543822253,\n 40.68250728063771\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"105","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Hoff, Samantha","contributorId":348917,"corporation":false,"usgs":false,"family":"Hoff","given":"Samantha","affiliations":[{"id":81956,"text":"University at Albany","active":true,"usgs":false}],"preferred":false,"id":923865,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pendergast, Casey","contributorId":348918,"corporation":false,"usgs":false,"family":"Pendergast","given":"Casey","affiliations":[{"id":81956,"text":"University at Albany","active":true,"usgs":false}],"preferred":false,"id":923866,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Luanne","contributorId":348919,"corporation":false,"usgs":false,"family":"Johnson","given":"Luanne","affiliations":[{"id":83415,"text":"Biodiversity Works","active":true,"usgs":false}],"preferred":false,"id":923867,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olson, Elizabeth","contributorId":348920,"corporation":false,"usgs":false,"family":"Olson","given":"Elizabeth","affiliations":[{"id":83415,"text":"Biodiversity Works","active":true,"usgs":false}],"preferred":false,"id":923868,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O’Dell, Danielle","contributorId":348921,"corporation":false,"usgs":false,"family":"O’Dell","given":"Danielle","affiliations":[{"id":81960,"text":"Nantucket Conservation Foundation","active":true,"usgs":false}],"preferred":false,"id":923869,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dowling, Zara R.","contributorId":348922,"corporation":false,"usgs":false,"family":"Dowling","given":"Zara R.","affiliations":[{"id":49179,"text":"University of Massachusetts-Amherst","active":true,"usgs":false}],"preferred":false,"id":923870,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gorman, Katherine M.","contributorId":348923,"corporation":false,"usgs":false,"family":"Gorman","given":"Katherine M.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":923871,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Herzog, Carl","contributorId":348924,"corporation":false,"usgs":false,"family":"Herzog","given":"Carl","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":923872,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Turner, Wendy Christine 0000-0002-0302-1646","orcid":"https://orcid.org/0000-0002-0302-1646","contributorId":287053,"corporation":false,"usgs":true,"family":"Turner","given":"Wendy","email":"","middleInitial":"Christine","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923873,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70252826,"text":"70252826 - 2024 - Rainfall reduces the potential for competitive suppression of a globally endangered ungulate by livestock","interactions":[],"lastModifiedDate":"2024-04-09T00:05:20.345762","indexId":"70252826","displayToPublicDate":"2024-04-08T08:35:17","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Rainfall reduces the potential for competitive suppression of a globally endangered ungulate by livestock","docAbstract":"Protected areas often are too small to house populations of wide-ranging species. Viability of wildlife populations therefore depends on whether interactions with humans and their land uses are negative, neutral, or positive. In central Iran, we measured interactions between globally endangered onagers (Equus hemionus onager) and livestock by analyzing remotely-sensed vegetation metrics within livestock grazing areas, tracking 9 animals with GPS telemetry, and assessing onagers' diet quality through analysis of fecal samples. Resource selection by onagers depended both on season and the presence of livestock. During the dry season, livestock reduced forage (some combination of forage biomass and forage quality) compared to pre-grazing periods, demonstrating potential for competitive suppression of onagers by livestock when resources are scarce. Additionally, and during both seasons, selection for forage by onagers was accentuated at night when livestock were absent, indicating onager avoidance of livestock. During the wet season, onagers exposed to livestock exhibited higher-quality diets than those that did not co-occur with livestock, suggesting that livestock grazing may potentially enhance forage quality for onagers. Consequently, collaboration with pastoralists to regularly rotate the locations of dry and wet season leases could alleviate negative effects of livestock grazing on onagers. Similar to other cases in multi-use landscapes, temporal shifts in the strength of competition—driven by diel cycles and seasonal rainfall—may characterize wildlife-livestock interactions in Iran and elsewhere in Asian rangelands. Our study highlights the possibility that conservation of an endangered mammal could be compatible with livestock production, at least during wet seasons.","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2024.110476","usgsCitation":"Esmaeili, S., Hemami, M., Kaczensky, P., Schoenecker, K., King, S., Shahriari, B., Walzer, C., and Goheen, J., 2024, Rainfall reduces the potential for competitive suppression of a globally endangered ungulate by livestock: Biological Conservation, v. 292, 110476, 12 p., https://doi.org/10.1016/j.biocon.2024.110476.","productDescription":"110476, 12 p.","numberOfPages":"12","ipdsId":"IP-133511","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":502586,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":427555,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Iran","otherGeospatial":"Bahram-e-Goor Protected Area (BPA), Qatrouiyeh National Park (QNP)","volume":"292","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Esmaeili, Saeideh","contributorId":335448,"corporation":false,"usgs":false,"family":"Esmaeili","given":"Saeideh","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":898371,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hemami, Mahmoud-Reza","contributorId":335449,"corporation":false,"usgs":false,"family":"Hemami","given":"Mahmoud-Reza","affiliations":[{"id":37792,"text":"Isfahan University of Technology, Iran","active":true,"usgs":false}],"preferred":false,"id":898372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kaczensky, Petra","contributorId":335450,"corporation":false,"usgs":false,"family":"Kaczensky","given":"Petra","affiliations":[{"id":80409,"text":"Norwegian Institute for Nature Research, Norway","active":true,"usgs":false}],"preferred":false,"id":898373,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schoenecker, Kathryn A. 0000-0001-9906-911X","orcid":"https://orcid.org/0000-0001-9906-911X","contributorId":202531,"corporation":false,"usgs":true,"family":"Schoenecker","given":"Kathryn A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":898374,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"King, Sarah R.B.","contributorId":335451,"corporation":false,"usgs":false,"family":"King","given":"Sarah R.B.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":898375,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shahriari, Bahareh","contributorId":335453,"corporation":false,"usgs":false,"family":"Shahriari","given":"Bahareh","email":"","affiliations":[{"id":80410,"text":"Iranian Department of Environment, Iran.","active":true,"usgs":false}],"preferred":false,"id":898376,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Walzer, Chris","contributorId":335455,"corporation":false,"usgs":false,"family":"Walzer","given":"Chris","email":"","affiliations":[{"id":80411,"text":"Wildlife Conservation Society, Bronx, New York","active":true,"usgs":false}],"preferred":false,"id":898377,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Goheen, Jake","contributorId":335456,"corporation":false,"usgs":false,"family":"Goheen","given":"Jake","email":"","affiliations":[{"id":17842,"text":"University of Wyoming, Laramie","active":true,"usgs":false}],"preferred":false,"id":898378,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70252849,"text":"70252849 - 2024 - A high-resolution, daily hindcast (1990-2021) of Alaskan river discharge and temperature from coupled and optimized physical models","interactions":[],"lastModifiedDate":"2024-04-09T12:27:57.23433","indexId":"70252849","displayToPublicDate":"2024-04-08T07:25:53","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"A high-resolution, daily hindcast (1990-2021) of Alaskan river discharge and temperature from coupled and optimized physical models","docAbstract":"Water quality and freshwater ecosystems are affected by river discharge and temperature. Models are frequently used to estimate river temperature on large spatial and temporal scales due to limited observations of discharge and temperature. In this study, we use physically based river routing and temperature models to simulate daily discharge and river temperature for rivers in 138 basins in Alaska, including the entire Yukon River basin, from 1990–2021. The river temperature model was optimized for ice free months using a surrogate-based model optimization method, improving model performance at uncalibrated river gages. A common statistical model relating local air and water temperature was used as a benchmark. The physically based river temperature model exhibited superior performance compared to the benchmark statistical model after optimization, suggesting river temperature model optimization could become more routine. The river temperature model demonstrated high sensitivity to air temperature and model parameterization, and lower sensitivity to discharge. Validation of the models showed a Kling-Gupta Efficiency of 0.46 for daily river discharge and a root mean square error of 2.04°C for daily river temperature, improving on the non-optimized physical model and the benchmark statistical model, which had root mean square errors of 3.24 and 2.97°C, respectively. The simulation shows that rivers in northern Alaska have higher maximum summer temperatures and more variability than rivers in the Central and Southern regions. Furthermore, this framework can be readily adapted for use across models and regions.
The frequency and extent of wildfires have increased in recent decades with immediate and cascading effects on water availability in many regions of the world. Precipitation is used as primary input to hydrologic models and is a critical driver of post-wildfire hydrologic hazards including debris flows, flash floods, water-quality effects, and reservoir sedimentation. These models are valuable tools for understanding the hydrologic response to wildfire but require accurate precipitation data at suitable spatial and temporal resolutions. Wildfires often occur in data-sparse, headwater catchments in complex terrain, and post-wildfire hydrologic effects are particularly sensitive to high-intensity, short-duration precipitation events, which are highly variable and difficult to measure or estimate. Therefore, the assessment and prediction of wildfire-induced changes to watershed hydrology, including the associated effects on ecosystems and communities, are complicated by uncertainty in precipitation data. When direct measurements of precipitation are not available, datasets of indirect measurements or estimates are often used. Choosing the most appropriate precipitation dataset can be difficult as different datasets have unique trade-offs in terms of spatial and temporal accuracy, resolution, and completeness. Here, we outline the challenges and opportunities associated with different precipitation datasets as they apply to post-wildfire hydrologic models and modeling objectives. We highlight the need for expanded precipitation gage deployment in wildfire-prone areas and discuss potential opportunities for future research and the integration of precipitation data from disparate sources into a common hydrologic modeling framework.
","language":"English","publisher":"Wiley","doi":"10.1002/wat2.1728","usgsCitation":"Partridge, T.F., Johnson, Z., Sleeter, R., Qi, S.L., Walvoord, M.A., Murphy, S.F., Peterman-Phipps, C.L., and Ebel, B., 2024, Opportunities and challenges for precipitation forcing data in post-wildfire hydrologic modeling applications: WIREs Water, v. 11, no. 5, e1728, 27 p., https://doi.org/10.1002/wat2.1728.","productDescription":"e1728, 27 p.","ipdsId":"IP-155206","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":427613,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":439910,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wat2.1728","text":"Publisher Index Page"}],"volume":"11","issue":"5","noUsgsAuthors":false,"publicationDate":"2024-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Partridge, Trevor Fuess 0000-0003-1589-4783","orcid":"https://orcid.org/0000-0003-1589-4783","contributorId":302668,"corporation":false,"usgs":true,"family":"Partridge","given":"Trevor","email":"","middleInitial":"Fuess","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":898394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Zachary 0000-0002-0149-5223 zjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-0149-5223","contributorId":190399,"corporation":false,"usgs":true,"family":"Johnson","given":"Zachary","email":"zjohnson@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":898395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sleeter, Rachel 0000-0003-3477-0436 rsleeter@usgs.gov","orcid":"https://orcid.org/0000-0003-3477-0436","contributorId":666,"corporation":false,"usgs":true,"family":"Sleeter","given":"Rachel","email":"rsleeter@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":898396,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Qi, Sharon L. 0000-0001-7278-4498 slqi@usgs.gov","orcid":"https://orcid.org/0000-0001-7278-4498","contributorId":1130,"corporation":false,"usgs":true,"family":"Qi","given":"Sharon","email":"slqi@usgs.gov","middleInitial":"L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":898397,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walvoord, Michelle A. 0000-0003-4269-8366","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":211843,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":898398,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":898399,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Peterman-Phipps, Cara L. 0000-0003-1822-2552","orcid":"https://orcid.org/0000-0003-1822-2552","contributorId":259166,"corporation":false,"usgs":true,"family":"Peterman-Phipps","given":"Cara","email":"","middleInitial":"L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":898400,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ebel, Brian A. 0000-0002-5413-3963","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":211845,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":898401,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70253160,"text":"70253160 - 2024 - Predator disturbance contributed to Common Murre Uria aalge breeding failures in Cook Inlet, Alaska following the 2014–2016 Pacific marine heatwave","interactions":[],"lastModifiedDate":"2024-04-23T12:11:34.910115","indexId":"70253160","displayToPublicDate":"2024-04-07T07:07:59","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7948,"text":"Marine Onithology","active":true,"publicationSubtype":{"id":10}},"title":"Predator disturbance contributed to Common Murre Uria aalge breeding failures in Cook Inlet, Alaska following the 2014–2016 Pacific marine heatwave","docAbstract":"Winter cover crops are planted during the fall to reduce nitrogen losses and soil erosion and improve soil health. Accurate estimations of winter cover crop performance and biophysical traits including biomass and fractional vegetative groundcover support accurate assessment of environmental benefits. We examined the comparability of measurements between ground-based and spaceborne sensors as well as between processing levels (e.g., surface vs. top-of-atmosphere reflectance) in estimating cover crop biophysical traits. This research examined the relationships between SPOT 5, Landsat 7, and WorldView-2 same-day paired satellite imagery and handheld multispectral proximal sensors on two days during the 2012–2013 winter cover crop season. We compared two processing levels from three satellites with spatially aggregated proximal data for red and green spectral bands as well as the normalized difference vegetation index (NDVI). We then compared NDVI estimated fractional green cover to in-situ photographs, and we derived cover crop biomass estimates from NDVI using existing calibration equations. We used slope and intercept contrasts to test whether estimates of biomass and fractional green cover differed statistically between sensors and processing levels. Compared to top-of-atmosphere imagery, surface reflectance imagery were more closely correlated with proximal sensors, with intercepts closer to zero, regression slopes nearer to the 1:1 line, and less variance between measured values. Additionally, surface reflectance NDVI derived from satellites showed strong agreement with passive handheld multispectral proximal sensor-sensor estimated fractional green cover and biomass (adj. R 2 = 0.96 and 0.95; RMSE = 4.76% and 259 kg ha−1, respectively). Although active handheld multispectral proximal sensor-sensor derived fractional green cover and biomass estimates showed high accuracies (R 2 = 0.96 and 0.96, respectively), they also demonstrated large intercept offsets (−25.5 and 4.51, respectively). Our results suggest that many passive multispectral remote sensing platforms may be used interchangeably to assess cover crop biophysical traits whereas SPOT 5 required an adjustment in NDVI intercept. Active sensors may require separate calibrations or intercept correction prior to combination with passive sensor data. Although surface reflectance products were highly correlated with proximal sensors, the standardized cloud mask failed to completely capture cloud shadows in Landsat 7, which dampened the signal of NIR and red bands in shadowed pixels.
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