We surveyed for Southwestern Willow Flycatchers (Empidonax traillii extimus; flycatcher) along the upper San Luis Rey River near Lake Henshaw in Santa Ysabel, California, in 2022. Surveys were completed at four locations: three downstream from Lake Henshaw, where surveys occurred from 2015 to 2021 (Rey River Ranch [RRR], Cleveland National Forest [CNF], Vista Irrigation District [VID]), and one at VID Lake Henshaw (VLH) that has been surveyed annually since 2018. There were 71 territorial flycatchers detected at 3 locations (RRR, CNF, VLH), and 6 transient flycatchers of unknown subspecies detected at VID and VLH. Downstream from Lake Henshaw, four territorial flycatchers, including two males and two females, were detected at RRR and CNF. In total, two territories were established consisting of two pairs at these locations. At VLH, we detected 67 territorial flycatchers, including 30 males, 34 females, and 3 flycatchers of unknown sex. In total, 40 territories were established, containing 35 pairs (24 monogamous pairings and 5 polygynous groups consisting of 4 males each pairing with 2 different females, and 1 male pairing with 3 different females), and 5 flycatchers of undetermined breeding status (3 males and 2 flycatchers of unknown sex). Brown-headed cowbirds (Molothrus ater; cowbird) were detected at all four survey locations.
Flycatchers used five habitat types in the survey area: (1) mixed willow riparian, (2) willow-cottonwood, (3) willow-oak, (4) willow-ash, and (5) oak-sycamore. Of the flycatcher locations, 83 percent were located in habitat characterized as mixed willow riparian, and 92 percent were in habitat with greater than 95-percent native plant cover. Exotic vegetation was not prevalent in the survey area.
There were 22 nests incidentally located during surveys: 5 were successful, 1 was seen with eggs on the last visit, 10 failed, and the outcome of the remaining 6 nests was unknown. Three of these nests were parasitized by cowbirds. There were 13 juveniles detected at VLH; no juveniles were detected at RRR or CNF.
Five banded flycatchers were detected during surveys, three of which were confirmed to be adults that held territories in previous years. In addition, two flycatchers with a single dark blue federal band, indicating that they were banded as nestlings in a previous demographic study downstream from Lake Henshaw (Howell and others, 2022), were resighted during surveys.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1173","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Howell, S.L., and Kus, B.E., 2023, Distribution and abundance of Southwestern Willow Flycatchers (Empidonax traillii extimus) on the upper San Luis Rey River, San Diego County, California—2022 data summary: U.S. Geological Survey Data Report 1173, 12 p., https://doi.org/10.3133/dr1173.","productDescription":"Report: vi, 12 p.; Data Release","numberOfPages":"12","onlineOnly":"Y","ipdsId":"IP-147974","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":416147,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1173/full"},{"id":416146,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1173/images"},{"id":416145,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1173/dr1173.xml"},{"id":416144,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1173/covrthb.jpg"},{"id":416143,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1173/dr1173.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":416142,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96VC5Y4","text":"Southwestern Willow Flycatcher (Empidonax traillii extimus) surveys and nest monitoring in San Diego County, California","description":"Howell, S.L., and Kus, B.E., 2022, Southwestern Willow Flycatcher (Empidonax traillii extimus) surveys and nest monitoring in San Diego County, California: U.S. Geological Survey data release, https://doi.org/ 10.5066/ P96VC5Y4."}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.55,\n 33.21\n ],\n [\n -116.55,\n 33.07\n ],\n [\n -116.41,\n 33.07\n ],\n [\n -116.41,\n 33.21\n ],\n [\n -116.55,\n 33.21\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The ecologically and culturally vital tree species, ʻōhiʻa lehua (Metrosideros polymorpha), is threatened by the fungal pathogens Ceratocystis lukuohia and Ceratocystis huliohia, the causal agents of the disease complex called Rapid ʻŌhiʻa Death (ROD). Four invasive ambrosia beetle (Coleoptera: Curculionidae: Scolytinae) species in the Xyleborini tribe colonize ROD Ceratocystis-infested ‘ōhiʻa and produce inoculum through their frass; however, the potential for direct transmission of the ROD fungi by these beetles was unknown. We fulfilled Leach's rules to support insect transmission of ROD by documenting the visitation of these ambrosia beetles to healthy ‘ōhiʻa trees, culturing C. lukuohia and C. huliohia from the ROD-associated beetles using three different collection methods at multiple study sites, and challenging healthy ʻōhiʻa seedlings with beetles that were exposed to both C. lukuohia and C. huliohia cultures. We documented all four invasive ROD-associated ambrosia beetle species including Xyleborinus saxesenii, Xyleborus affinis, Xyleborus ferrugineus, and Xyleborus perforans to regularly visit healthy ʻōhiʻa trees on sticky traps. Viable Ceratocystis propagules were isolated from all species, and C. lukuohia was most commonly isolated of the two ROD-causing fungi. Consistently across all collection techniques, ROD Ceratocystis spp. were detected on just under 3% of all assayed beetles, with the highest detection rate from X. affinis. All four beetle species were capable of directly transmitting both pathogens to healthy ʻōhiʻa seedlings with a high rate of transfer. Ceratocystis spp. are highly virulent pathogens in trees, and a single inoculation can result in tree death, therefore any direct transmission is a cause for concern. After meeting the criteria of Leach's rules, we propose that Xi. saxesenii, X. affinis, X. ferrugineus, and X. perforans are vectors of C. lukuohia and C. huliohia, particularly in areas of high ROD pressure and tree stress.
","language":"English","publisher":"Wiley","doi":"10.1111/efp.12812","usgsCitation":"Roy, K., Jaenecke, K., Dunkle, E., Mikros, D., and Peck, R., 2023, Ambrosia beetles (Coleoptera: Curculionidae) can directly transmit the fungal pathogens responsible for Rapid ʻŌhiʻa Death: Forest Pathology, v. 53, no. 3, e12812, 11 p., https://doi.org/10.1111/efp.12812.","productDescription":"e12812, 11 p.","ipdsId":"IP-145289","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":443755,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/efp.12812","text":"Publisher Index Page"},{"id":435360,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99TXGKI","text":"USGS data release","linkHelpText":"Hawaiʻi Ambrosia Beetle Direct ROD Transmission 2018-2022 (ver. 2.0, April 2023)"},{"id":419344,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Waiākea Forest Reserve, Hawai'i Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.2042510429986,\n 19.668151060180463\n ],\n [\n -155.2042510429986,\n 19.58628926243462\n ],\n [\n -155.07169530880805,\n 19.58628926243462\n ],\n [\n -155.07169530880805,\n 19.668151060180463\n ],\n [\n -155.2042510429986,\n 19.668151060180463\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"53","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-04-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Roy, Kylle 0000-0002-7993-9031","orcid":"https://orcid.org/0000-0002-7993-9031","contributorId":213271,"corporation":false,"usgs":true,"family":"Roy","given":"Kylle","email":"","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":879137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaenecke, Kelly 0000-0002-7124-4788","orcid":"https://orcid.org/0000-0002-7124-4788","contributorId":211063,"corporation":false,"usgs":false,"family":"Jaenecke","given":"Kelly","email":"","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":879138,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunkle, Ellen 0000-0002-7081-0717","orcid":"https://orcid.org/0000-0002-7081-0717","contributorId":244898,"corporation":false,"usgs":false,"family":"Dunkle","given":"Ellen","email":"","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":879139,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mikros, Dan","contributorId":238975,"corporation":false,"usgs":false,"family":"Mikros","given":"Dan","email":"","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":879140,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peck, Robert W. 0000-0002-8739-9493","orcid":"https://orcid.org/0000-0002-8739-9493","contributorId":193088,"corporation":false,"usgs":false,"family":"Peck","given":"Robert W.","affiliations":[],"preferred":false,"id":879141,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70243122,"text":"70243122 - 2023 - A novel assembly pipeline and functional annotations for targeted sequencing: A case study on the globally threatened Margaritiferidae (Bivalvia: Unionida)","interactions":[],"lastModifiedDate":"2023-07-11T15:58:46.447837","indexId":"70243122","displayToPublicDate":"2023-04-24T06:55:01","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2776,"text":"Molecular Ecology Resources","active":true,"publicationSubtype":{"id":10}},"title":"A novel assembly pipeline and functional annotations for targeted sequencing: A case study on the globally threatened Margaritiferidae (Bivalvia: Unionida)","docAbstract":"The proliferation of genomic sequencing approaches has significantly impacted the field of phylogenetics. Target capture approaches provide a cost-effective, fast and easily applied strategy for phylogenetic inference of non-model organisms. However, several existing target capture processing pipelines are incapable of incorporating whole genome sequencing (WGS). Here, we develop a new pipeline for capture and de novo assembly of the targeted regions using whole genome re-sequencing reads. This new pipeline captured targeted loci accurately, and given its unbiased nature, can be used with any target capture probe set. Moreover, due to its low computational demand, this new pipeline may be ideal for users with limited resources and when high-coverage sequencing outputs are required. We demonstrate the utility of our approach by incorporating WGS data into the first comprehensive phylogenomic reconstruction of the freshwater mussel family Margaritiferidae. We also provide a catalogue of well-curated functional annotations of these previously uncharacterized freshwater mussel-specific target regions, representing a complementary tool for scrutinizing phylogenetic inferences while expanding future applications of the probe set.
The rate of fault zone restrengthening between earthquakes can be influenced by both frictional and cohesive healing processes. Friction is dependent on effective normal stress while cohesion is independent of normal stress, potentially explaining—in part—the lack of depth dependence of earthquake stress drops. Although amenable to laboratory testing, few studies have systematically addressed the normal stress dependence of restrengthening rate. This is partially due to difficulty in separating relative contributions of friction and cohesion in recovery of fault strength. We present results from a series of slide-hold-slide tests on thin layers (≤10 \uD835\uDF07m) of ultrafine quartz gouge that develop during shearing of initially bare-surface quartzite. Tests were conducted at 10 MPa constant pore pressure, 20–200 MPa constant effective normal stress, and temperatures of 22°–200°C. Restrengthening, defined as the difference between peak shear stress measured after resumption of sliding and steady-state sliding shear stress, increases with the log of hold duration. The 200°C healing rate, 0.014 per e-fold increase in time, is comparable to that determined from seismological observations along the Calaveras Fault, California. Construction of Mohr-Coulomb failure envelopes shows that changes in cohesion are small (<1 MPa) and independent of hold durations to 105 s, indicating that the increased strength is due to changes in the friction coefficient. These experimental results are inconsistent with the hypothesis that cohesive healing explains the depth independence of earthquake stress drop, but higher temperatures, longer time-scales, and more complex mineralogy could facilitate cohesive healing in natural fault systems.
Understanding how species are responding to environmental change is a central challenge for stewards and managers of fish and wildlife who seek to maintain harvest opportunities for communities and Indigenous peoples. This is a particularly daunting but increasingly important task in remote, high-latitude regions where environmental conditions are changing rapidly and data collection is logistically difficult. The Arctic-Yukon-Kuskokwim (AYK) region encompasses the northern extent of the Chinook Salmon Oncorhynchus tshawytscha range where populations are experiencing rapid rates of environmental change across both freshwater and marine habitats due to global climate change. Climate–salmon interactions in the AYK region are a particularly pressing issue as many local communities have a deep reliance on a subsistence way of life. Here, we synthesize perspectives shared at a recent workshop on Chinook Salmon declines in the AYK region. The objectives were to discuss current understandings of climate-Chinook Salmon interactions, develop a set of outstanding questions, review available data and its limitations in addressing these questions, and describe the perspectives expressed by participants in this workshop from diverse backgrounds. We conclude by suggesting pathways forward to integrate different types of information and build relationships among communities, academic partners, and fishery management agencies.
American Kestrel (Falco sparverius) populations are generally declining across the species' North American distribution but the population in the Southern High Plains region currently appears to be stable. Historical evidence suggests the region formerly had a low abundance of kestrels, and that their current numbers are due to landscape changes associated with European settlement. We conducted monthly surveys for American Kestrels across 2 yr to estimate seasonal densities and identify land cover associations in the Southern High Plains of Texas. We found an overall estimated density of 0.99 birds/km2 (95% CI = 0.406, 1.582) across the 2-yr period, with seasonal estimated densities highest in autumn and winter (0.92–2.53/ km2), and lowest in spring (0.49–0.67/km2). Whereas other studies have found that temperature influenced detection of wintering kestrels, we found an interaction of drought conditions and snow most strongly influenced the number of kestrels in our study area. Kestrels largely used land cover types in proportion to availability but there was some evidence of seasonal shifts. Generally, they tended to avoid cotton fields and sometimes selected for areas with woodlots, abandoned or occupied houses, and barns, all of which likely provided nesting and roosting opportunities. Our study provides the first contemporary assessment of seasonal abundance and habitat associations of American Kestrels in the Southern High Plains, where their presence and abundance has been unintentionally facilitated by landscape changes following settlement. We provide a baseline for population monitoring and studies assessing response to additional landscape changes (e.g., development of wind energy facilities) and a changing climate.
","language":"English","publisher":"BioOne","doi":"10.3356/JRR-22-22","usgsCitation":"Linner-Warren, K., Bibles, B., and Boal, C.W., 2023, Seasonal abundance and habitat associations of American Kestrels on the Southern High Plains of Texas: Journal of Raptor Research, v. 57, no. 2, p. 251-263, https://doi.org/10.3356/JRR-22-22.","productDescription":"13 p.","startPage":"251","endPage":"263","ipdsId":"IP-137751","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":433224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Linner-Warren, Kristen","contributorId":341438,"corporation":false,"usgs":false,"family":"Linner-Warren","given":"Kristen","email":"","affiliations":[{"id":81738,"text":"Department of Natural Resources Management, Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":908420,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bibles, Brent D.","contributorId":341439,"corporation":false,"usgs":false,"family":"Bibles","given":"Brent D.","affiliations":[{"id":81739,"text":"Unity College","active":true,"usgs":false}],"preferred":false,"id":908422,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","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":908421,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70263407,"text":"70263407 - 2023 - Earthquake detection with tinyML","interactions":[],"lastModifiedDate":"2025-02-10T15:44:17.596407","indexId":"70263407","displayToPublicDate":"2023-04-24T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Earthquake detection with tinyML","docAbstract":"Earthquake detection is the critical first step in earthquake early warning (EEW) systems. For robust EEW systems, detection accuracy, detection latency, and sensor density are critical to providing real‐time earthquake alerts. Traditional EEW systems use fixed sensor networks or, more recently, networks of mobile phones equipped with microelectromechanical systems (MEMS) accelerometers. Internet of things edge devices, with built‐in tiny machine learning (tinyML) capable microcontrollers, and always‐on, internet‐connected, stationary MEMS accelerometers provide the opportunity to deploy ML‐based earthquake detection and warning using a single‐station approach at a global scale. Here, I test and evaluate tinyML deep learning algorithms for earthquake detection on a microcontroller. I show that the tinyML earthquake detection models can generalize to earthquakes outside the training set.
","language":"English","publisher":"GeoScienceWorld","doi":"10.1785/0220220322","usgsCitation":"Clements, T., 2023, Earthquake detection with tinyML: Seismological Research Letters, v. 94, no. 4, p. 2030-2039, https://doi.org/10.1785/0220220322.","productDescription":"10 p.","startPage":"2030","endPage":"2039","ipdsId":"IP-145890","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":481861,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"94","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-04-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Clements, Timothy Hugh 0000-0001-6632-1796","orcid":"https://orcid.org/0000-0001-6632-1796","contributorId":350753,"corporation":false,"usgs":true,"family":"Clements","given":"Timothy Hugh","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":926877,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70256479,"text":"70256479 - 2023 - A coupled human and natural systems framework to characterize emerging infectious diseases: The case of fibropapillomatosis in marine turtles","interactions":[],"lastModifiedDate":"2024-08-06T16:48:50.431037","indexId":"70256479","displayToPublicDate":"2023-04-23T11:46:19","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5762,"text":"Animals","active":true,"publicationSubtype":{"id":10}},"title":"A coupled human and natural systems framework to characterize emerging infectious diseases: The case of fibropapillomatosis in marine turtles","docAbstract":"Emerging infectious diseases of wildlife have markedly increased in the last few decades. Unsustainable, continuous, and rapid alterations within and between coupled human and natural systems have significantly disrupted wildlife disease dynamics. Direct and indirect anthropogenic effects, such as climate change, pollution, encroachment, urbanization, travel, and trade, can promote outbreaks of infectious diseases in wildlife. We constructed a coupled human and natural systems framework identifying three main wildlife disease risk factors behind these anthropogenic effects: (i) immune suppression, (ii) viral spillover, and (iii) disease propagation. Through complex and convoluted dynamics, each of the anthropogenic effect listed in our framework can lead, to some extent, to one or more of the identified risk factors accelerating disease outbreaks in wildlife. In this review, we present a novel framework to study anthropogenic impacts within coupled human and natural systems that facilitate emergence of infectious disease involving wildlife. We demonstrate the utility of the framework by applying it to Fibropapillomatosis disease of marine turtles. We aim to articulate the intricate and complex nature of anthropogenically-exacerbated wildlife infectious diseases as multifactorial. This paper supports the adoption of a One Health approach and invites the collaboration of multiple disciplines for the achievement of effective and long-lasting conservation and wildlife emerging diseases mitigation outcomes.","language":"English","publisher":"MDPI","doi":"10.3390/ani13091441","usgsCitation":"Manes, C., Carthy, R., and Hull, V., 2023, A coupled human and natural systems framework to characterize emerging infectious diseases: The case of fibropapillomatosis in marine turtles: Animals, v. 13, no. 9, 1441, 16 p., https://doi.org/10.3390/ani13091441.","productDescription":"1441, 16 p.","ipdsId":"IP-151093","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":443768,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/ani13091441","text":"Publisher Index Page"},{"id":432296,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"9","noUsgsAuthors":false,"publicationDate":"2023-04-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Manes, Costanza","contributorId":340789,"corporation":false,"usgs":false,"family":"Manes","given":"Costanza","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":907560,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":907561,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hull, Vanessa","contributorId":340791,"corporation":false,"usgs":false,"family":"Hull","given":"Vanessa","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":907562,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70268406,"text":"70268406 - 2023 - Chapter 12 - Explainable AI for understanding ML-derived vegetation products","interactions":[],"lastModifiedDate":"2025-06-25T14:17:08.250239","indexId":"70268406","displayToPublicDate":"2023-04-23T09:15:24","publicationYear":"2023","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Chapter 12 - Explainable AI for understanding ML-derived vegetation products","docAbstract":"Current machine learning applications and algorithms have developed promise to produce autonomous systems that automatically perceive, learn, predict, and act on their own. However, the effectiveness of these systems is limited by the machine's current inability to explain their decisions, algorithmic paths, and actions to human users. The purpose of this chapter is to apply explainable artificial intelligence (XAI) to black-box models using an example of the U.S. Geological Survey's LANDFIRE Existing Vegetation Type (EVT). This chapter also demonstrates the tools developed to assist scientists/analysts in understanding and trusting prediction outcomes of vegetation type that streamline development of the LANDFIRE EVT product.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Artificial intelligence in earth science: Best practices and fundamental challenges","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier Inc","doi":"10.1016/B978-0-323-91737-7.00008-6","usgsCitation":"Ganji, G., and Chow Lin, W., 2023, Chapter 12 - Explainable AI for understanding ML-derived vegetation products, chap. of Artificial intelligence in earth science: Best practices and fundamental challenges, p. 317-335, https://doi.org/10.1016/B978-0-323-91737-7.00008-6.","productDescription":"19 p.","startPage":"317","endPage":"335","ipdsId":"IP-135266","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":491276,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2023-04-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Ganji, Geetha Satya Mounika 0000-0003-2763-2617","orcid":"https://orcid.org/0000-0003-2763-2617","contributorId":357334,"corporation":false,"usgs":false,"family":"Ganji","given":"Geetha Satya Mounika","affiliations":[{"id":85411,"text":"KBR under contract to the USGS","active":true,"usgs":false}],"preferred":false,"id":941237,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chow Lin, Wai Hang 0000-0003-0628-7711","orcid":"https://orcid.org/0000-0003-0628-7711","contributorId":357335,"corporation":false,"usgs":false,"family":"Chow Lin","given":"Wai Hang","affiliations":[{"id":85411,"text":"KBR under contract to the USGS","active":true,"usgs":false}],"preferred":false,"id":941238,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70248270,"text":"70248270 - 2023 - Exploring the relevance of the multidimensionality of wildlife recreationists to conservation behaviors: A case study in Virginia","interactions":[],"lastModifiedDate":"2023-09-06T12:26:20.072182","indexId":"70248270","displayToPublicDate":"2023-04-23T07:22:30","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Exploring the relevance of the multidimensionality of wildlife recreationists to conservation behaviors: A case study in Virginia","docAbstract":"Wildlife recreationists' participation in conservation behaviors could provide key support to the conservation efforts of state fish and wildlife agencies. However, little is known about how identifying with multiple forms of wildlife recreation (i.e., hunters, anglers, birders, wildlife viewers) may influence participation in conservation behaviors, specifically for supporting state fish and wildlife agencies and their conservation goals. Using a mixed-mode survey of Virginia wildlife recreationists, we explored the hypothesized relationship between individuals' participation in conservation behaviors and their identification with multiple forms of consumptive and nonconsumptive wildlife recreation. We found wildlife recreation identity is multidimensional, with many individuals identifying with consumptive and nonconsumptive identities simultaneously. Further, consumptive-only recreationists (i.e., hunters and/or anglers) participated in conservation behaviors less often than nonconsumptive-only recreationists (i.e., birders and/or wildlife viewers) and recreationists with both consumptive and nonconsumptive identities were less likely to support a state fish and wildlife agency in the future. Our findings underscore the importance of all types of wildlife recreationists, especially those with intersecting identities, as state fish and wildlife agencies work to advance conservation. Hence, developing multi-faceted engagement strategies may enhance support for state fish and wildlife agencies among their growing wildlife recreation constituency.
Predicted increases in extreme droughts will likely cause major shifts in carbon sequestration and forest composition. Although growth declines during drought are widely documented, an increasing number of studies have reported both positive and negative responses to the same drought. These divergent growth patterns may reflect thresholds (i.e., nonlinear responses) promoted by changes in the dominant climatic constraints on tree growth. Here we tested whether stemwood growth exhibited linear or nonlinear responses to temperature and precipitation and whether stemwood growth thresholds co-occurred with multiple thresholds in source and sink processes that limit tree growth. We extracted 772 tree cores, 1398 needle length records, and 1075 stable isotope samples from 27 sites across whitebark pine's (Pinus albicaulis Engelm.) climatic niche in the Sierra Nevada. Our results indicated that a temperature threshold in stemwood growth occurred at 8.4°C (7.12–9.51°C; estimated using fall-spring maximum temperature). This threshold was significantly correlated with thresholds in foliar growth, as well as carbon (δ13C) and nitrogen (δ15N) stable isotope ratios, that emerged during drought. These co-occurring thresholds reflected the transition between energy- and water-limited tree growth (i.e., the E–W limitation threshold). This transition likely mediated carbon and nutrient cycling, as well as important differences in growth-defense trade-offs and drought adaptations. Furthermore, whitebark pine growing in energy-limited regions may continue to experience elevated growth in response to climate change. The positive effect of warming, however, may be offset by growth declines in water-limited regions, threatening the long-term sustainability of the recently listed whitebark pine species in the Sierra Nevada.
Salinity regimes in coastal ecosystems are highly dynamic and driven by complex geomorphic and hydrological processes. Estuarine biota are generally adapted to salinity fluctuation, but are vulnerable to salinity extremes. Characterizing coastal salinity regime for ecological studies therefore requires representing extremes of salinity ranges at time scales relevant to ecology (e.g., daily, monthly, and seasonally). Here, we propose a framework for modeling coastal salinity with these overall goals: (1) quantify uncertainty in salinity associated with important terrestrial and oceanographic drivers, (2) examine time scales of salinity response to river streamflow events, and (3) predict salinity continuously over space at key time scales. Salinity is modeled as quantile surfaces related to river discharge, tidal dynamics, wind, and spatial location, applied to Suwannee Sound estuary, FL, USA, where salinity has been monitored spatially since 1981. Each quantile level is regressed independently, and together they comprise a distribution of salinity uncertainty across space, with upper and lower quantiles describing salinity extremes. Effects of physical drivers on salinity are compared through four base models with various combinations of tide and wind variables, each including spatial coordinates and a single streamflow metric (in cubic meters per second). Multiple time scales of streamflow are considered by taking means across various periods, from 1 to 12 days, and at various lagged intervals prior to salinity sample, totaling 144 streamflow metrics. We found that the Suwannee coastal salinity regime is dynamic at multiple time scales and varies nonlinearly across space from the river effluence outward. Salinity increases nonlinearly with decreasing river flow rates below 200 m3/s, most prominently in the lower quantiles of salinity (τ = 0.05–0.25). Wind appears to have a stronger influence on salinity than astronomic tides for this estuary. The regression approach developed here can be applied to any coastal system that has sufficient spatial and temporal monitoring coverage to capture multiple flood and drought events. It is implemented with a simple R routine, and is less computationally-intensive than finite difference hydrodynamic modeling. The characterizations of salinity uncertainty developed in these analyses can be directly applied to future studies of fish and wildlife responses to changes in watershed management.
Keys to Dickcissel (Spiza americana) management include providing dense, moderate-to-tall vegetation, particularly with a well-developed forb component, and moderately deep litter. Dickcissels have been reported to use grassland habitats with 4–166 centimeters (cm) average vegetation height, 6–85 cm visual obstruction reading, 11–68 percent grass cover, 1–86 percent forb cover, less than or equal to (≤) 10 percent shrub cover, less than (<) 27 percent bare ground cover, <30 percent litter cover, and ≤ 6 cm litter depth.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1842OO","usgsCitation":"Shaffer, J.A., Igl, L.D., Johnson, D.H., Sondreal, M.L., Goldade, C.M., Zimmerman, A.L., and Euliss, B.R., 2023, The effects of management practices on grassland birds—Dickcissel (Spiza americana), chap. OO of Johnson, D.H., Igl, L.D., Shaffer, J.A., and DeLong, J.P., eds., The effects of management practices on grassland birds: U.S. Geological Survey Professional Paper 1842, 47 p., https://doi.org/10.3133/pp1842OO.","productDescription":"v, 47 p.","numberOfPages":"58","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-097130","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":416091,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1842/oo/coverthb.jpg"},{"id":416092,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1842/oo/pp1842oo.pdf","text":"Report","size":"2.24 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1842–OO"}],"contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
The ability of reefs to protect coastlines from storm-driven flooding hinges on their capacity to keep pace with sea-level rise. Here, we show how and whether coral restoration could achieve the often-cited goal of reversing the impacts of coral-reef degradation to preserve this essential function. We combined coral-growth measurements and carbonate-budget assessments of reef-accretion potential at Buck Island Reef, U.S. Virgin Islands, with hydrodynamic modeling to quantify future coastal flooding under various coral-restoration, sea-level rise, and storm scenarios. Our results provide guidance on how restoration of Acropora palmata, if successful, could mitigate the most extreme impacts of coastal flooding by reversing projected trajectories of reef erosion and allowing reefs to keep pace with the ~0.5 m of sea-level rise expected by 2100 with moderate carbon-emissions reductions. This highlights the potential long-term benefits of pursuing coral-reef restoration alongside climate-change mitigation to support the persistence of essential coral-reef ecosystem services.
Eco-evolutionary interactions following ecosystem change provide critical insight into the ability of organisms to adapt to shifting resource landscapes. Here we explore evidence for the rapid parallel evolution of trout feeding morphology following eco-evolutionary interactions with zooplankton in alpine lakes stocked at different points in time in the Wind River Range (Wyoming, USA). In this system, trout predation has altered the zooplankton species community and driven a decrease in average zooplankton size. In some lakes that were stocked decades ago, we find shifts in gill raker traits consistent with the hypothesis that trout have rapidly adapted to exploit available smaller-bodied zooplankton more effectively. We explore this morphological response in multiple lake populations across two species of trout (cutthroat trout, Oncorhynchus clarkii, and golden trout Oncorhynchus aguabonita) and examine the impact of resource availability on morphological variation in gill raker number among lakes. Furthermore, we present genetic data to provide evidence that historically stocked cutthroat trout populations likely derive from multiple population sources, and incorporate variation from genomic relatedness in our exploration of environmental predictors of feeding morphology. These findings describe rapid adaptation and eco-evolutionary interactions in trout and document an evolutionary response to novel, contemporary ecosystem change.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/evolut/qpad059","usgsCitation":"Combrink, L., Rosenthal, W.C., Boyle, L.J., Rick, J.A., Krist, A.C., Mandeville, E.G., Walters, A.W., and Wagner, C., 2023, Parallel shifts in trout feeding morphology suggest rapid adaptation to alpine lake environments: Evolution, v. 77, no. 7, p. 1522-1538, https://doi.org/10.1093/evolut/qpad059.","productDescription":"17 p.","startPage":"1522","endPage":"1538","ipdsId":"IP-145950","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":443789,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10309971","text":"External Repository"},{"id":429628,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"77","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-04-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Combrink, Lucia L.","contributorId":337367,"corporation":false,"usgs":false,"family":"Combrink","given":"Lucia L.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":902391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenthal, William C.","contributorId":337368,"corporation":false,"usgs":false,"family":"Rosenthal","given":"William","email":"","middleInitial":"C.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":902392,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyle, Lindsey J.","contributorId":337370,"corporation":false,"usgs":false,"family":"Boyle","given":"Lindsey","email":"","middleInitial":"J.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":902393,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rick, Jessica A.","contributorId":337372,"corporation":false,"usgs":false,"family":"Rick","given":"Jessica","email":"","middleInitial":"A.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":902394,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krist, Amy C","contributorId":337613,"corporation":false,"usgs":false,"family":"Krist","given":"Amy","email":"","middleInitial":"C","affiliations":[],"preferred":false,"id":902562,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mandeville, Elizabeth G.","contributorId":166947,"corporation":false,"usgs":false,"family":"Mandeville","given":"Elizabeth","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":902395,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902396,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wagner, Catherine E.","contributorId":337377,"corporation":false,"usgs":false,"family":"Wagner","given":"Catherine E.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":902397,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70243123,"text":"70243123 - 2023 - Modeling impacts of saltwater intrusion on methane and nitrous oxide emissions in tidal forested wetlands","interactions":[],"lastModifiedDate":"2023-07-11T15:57:57.974985","indexId":"70243123","displayToPublicDate":"2023-04-21T06:26:43","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Modeling impacts of saltwater intrusion on methane and nitrous oxide emissions in tidal forested wetlands","docAbstract":"Emissions of methane (CH4) and nitrous oxide (N2O) from soils to the atmosphere can offset the benefits of carbon sequestration for climate change mitigation. While past study has suggested that both CH4 and N2O emissions from tidal freshwater forested wetlands (TFFW) are generally low, the impacts of coastal droughts and drought-induced saltwater intrusion on CH4 and N2O emissions remain unclear. In this study, a process-driven biogeochemistry model, Tidal Freshwater Wetland DeNitrification-DeComposition (TFW-DNDC) was applied to examine the responses of CH4 and N2O emissions to episodic drought-induced saltwater intrusion in TFFW along the Waccamaw River and Savannah River, USA. These sites encompass landscape gradients of both surface and porewater salinity as influenced by Atlantic Ocean tides superimposed on periodic droughts. Surprisingly, CH4 and N2O emission responsiveness to coastal droughts and drought-induced saltwater intrusion varied greatly between river systems and among local geomorphologic settings. This reflected the complexity of wetland CH4 and N2O emissions and suggests that simple linkages to salinity may not always be relevant, as non-linear relationships dominated our simulations. Along the Savannah River, N2O emissions in the moderate-oligohaline tidal forest site tended to increase dramatically under the drought condition, while CH4 emission decreased. For the Waccamaw River, emissions of both CH4 and N2O in the moderate-oligohaline tidal forest site tended to decrease under the drought condition, but the capacity of the moderate-oligohaline tidal forest to serve as a carbon sink was substantially reduced due to significant declines in net primary productivity and soil organic carbon sequestration rates as salinity killed the dominant freshwater vegetation. These changes in fluxes of CH4 and N2O reflect crucial synergistic effects of soil salinity and water level on C and N dynamics in TFFW due to drought-induced seawater intrusion.
South Manitou Island, part of Sleeping Bear Dunes National Lakeshore in northern Lake Michigan, is a post-glacial lacustrine landscape with substantial geomorphic changes including landslides, shoreline and bluff retreat, and sand dune movement. These changes involve interrelated processes, and are influenced to different extents by lake level, climate change, and land use patterns, among other factors. The utility of DEM of Difference (DoD) and other terrain analyses were investigated as a means of understanding interrelated geomorphologic changes and processes across multiple decades and at multiple scales. A 1m DEM was developed from 1955 historical aerial imagery using Structure from Motion Multi-View Stereo (SfM-MVS) and compared to a 2016 lidar-based DEM to quantify change. Landslides, shoreline erosion, bluff retreat, and sand dune movement were investigated throughout South Manitou Island. While the DoD indicates net loss or gain, interpretation of change must take into consideration the SfM-MVS source of the historical DEM. In the case of landslides, where additional understanding may be gleaned through review of the timing of lake high- and lowstands together with DoD values. Landscape-scale findings quantified cumulative feedbacks between interrelated processes. These findings could be upscaled to assess changes across the entire park, informing future change investigations and land management decisions.
","language":"English","publisher":"MDPI","doi":"10.3390/ijgi12040173","usgsCitation":"DeWitt, J.D., and Ashland, F., 2023, Investigating geomorphic change using a structure from motion elevation model created from historical aerial imagery: A case study in northern Lake Michigan, USA: ISPRS International Journal of Geo-information, v. 12, no. 4, 173, 26 p., https://doi.org/10.3390/ijgi12040173.","productDescription":"173, 26 p.","ipdsId":"IP-135951","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":443795,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/ijgi12040173","text":"Publisher Index Page"},{"id":420775,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Lake Michigan, Sleeping Bear Dunes National Lakeshore, South Manitou Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -86.11501011248272,\n 44.99859848151604\n ],\n [\n -86.11151860548817,\n 45.0008204742272\n ],\n [\n -86.10593219429762,\n 45.001314238683136\n ],\n [\n -86.10348813940179,\n 45.00316581749374\n ],\n [\n -86.10086950915604,\n 45.005017336463794\n ],\n [\n -86.09598139936371,\n 45.00538763307685\n ],\n [\n -86.09283904306896,\n 45.00699222407434\n ],\n [\n -86.09091871422216,\n 45.009954427829854\n ],\n [\n -86.09301361841888,\n 45.01242281393826\n ],\n [\n -86.09685427611251,\n 45.013780380951914\n ],\n [\n -86.09842545426024,\n 45.015508146971996\n ],\n [\n -86.09999663240727,\n 45.0192103271973\n ],\n [\n -86.09999663240727,\n 45.02291226806037\n ],\n [\n -86.09929833100836,\n 45.02673735548902\n ],\n [\n -86.09580682401447,\n 45.02969853796566\n ],\n [\n -86.09161701562104,\n 45.03117907175729\n ],\n [\n -86.0863797551296,\n 45.031425823665614\n ],\n [\n -86.07922216579134,\n 45.030438809648956\n ],\n [\n -86.07485778204867,\n 45.02920501819111\n ],\n [\n -86.07974589184035,\n 45.03574380985694\n ],\n [\n -86.08428485093289,\n 45.03993811304554\n ],\n [\n -86.08882381002545,\n 45.04215850202999\n ],\n [\n -86.0940610705169,\n 45.04203514934687\n ],\n [\n -86.10209153660396,\n 45.04351536398906\n ],\n [\n -86.10628134499738,\n 45.04474884693579\n ],\n [\n -86.11186775618796,\n 45.04622899136464\n ],\n [\n -86.11727959202933,\n 45.04931250258707\n ],\n [\n -86.12531005811573,\n 45.047339074553776\n ],\n [\n -86.13246764745402,\n 45.044872193767304\n ],\n [\n -86.13857778469426,\n 45.04326866420851\n ],\n [\n -86.142243867038,\n 45.04067825228134\n ],\n [\n -86.14398962053563,\n 45.03623727324839\n ],\n [\n -86.14800485357848,\n 45.027230896540175\n ],\n [\n -86.151496360573,\n 45.02315905560701\n ],\n [\n -86.15586074431567,\n 45.01711245445824\n ],\n [\n -86.15708277176357,\n 45.01291647839395\n ],\n [\n -86.15673362106448,\n 45.00600478877976\n ],\n [\n -86.15725734711346,\n 45.00452360392279\n ],\n [\n -86.15586074431567,\n 45.001314238683136\n ],\n [\n -86.15376584011963,\n 45.00180799888372\n ],\n [\n -86.14765570287939,\n 45.000079819564775\n ],\n [\n -86.14119641494,\n 44.997610901540185\n ],\n [\n -86.13822863399447,\n 44.99711710516928\n ],\n [\n -86.13351509955272,\n 44.99600604777606\n ],\n [\n -86.131420195356,\n 44.99699365541156\n ],\n [\n -86.12775411301226,\n 44.99724055466106\n ],\n [\n -86.12548463346563,\n 44.99859848151604\n ],\n [\n -86.11919992087614,\n 44.997610901540185\n ],\n [\n -86.11501011248272,\n 44.99859848151604\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-04-20","publicationStatus":"PW","contributors":{"authors":[{"text":"DeWitt, Jessica D. 0000-0002-8281-8134 jdewitt@usgs.gov","orcid":"https://orcid.org/0000-0002-8281-8134","contributorId":5804,"corporation":false,"usgs":true,"family":"DeWitt","given":"Jessica","email":"jdewitt@usgs.gov","middleInitial":"D.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":882939,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ashland, Francis 0000-0001-9948-0195 fashland@usgs.gov","orcid":"https://orcid.org/0000-0001-9948-0195","contributorId":198587,"corporation":false,"usgs":true,"family":"Ashland","given":"Francis","email":"fashland@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":882940,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70242863,"text":"pp1842O - 2023 - The effects of management practices on grassland birds—Golden Eagle (Aquila chrysaetos)","interactions":[{"subject":{"id":70242863,"text":"pp1842O - 2023 - The effects of management practices on grassland birds—Golden Eagle (Aquila chrysaetos)","indexId":"pp1842O","publicationYear":"2023","noYear":false,"chapter":"O","displayTitle":"The Effects of Management Practices on Grassland Birds—Golden Eagle (Aquila chrysaetos)","title":"The effects of management practices on grassland birds—Golden Eagle (Aquila chrysaetos)"},"predicate":"IS_PART_OF","object":{"id":70203022,"text":"pp1842 - 2019 - The effects of management practices on grassland birds","indexId":"pp1842","publicationYear":"2019","noYear":false,"title":"The effects of management practices on grassland birds"},"id":1}],"isPartOf":{"id":70203022,"text":"pp1842 - 2019 - The effects of management practices on grassland birds","indexId":"pp1842","publicationYear":"2019","noYear":false,"title":"The effects of management practices on grassland birds"},"lastModifiedDate":"2023-12-20T21:15:22.8997","indexId":"pp1842O","displayToPublicDate":"2023-04-20T14:09:32","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1842","chapter":"O","displayTitle":"The Effects of Management Practices on Grassland Birds—Golden Eagle (Aquila chrysaetos)","title":"The effects of management practices on grassland birds—Golden Eagle (Aquila chrysaetos)","docAbstract":"Keys to Golden Eagle (Aquila chrysaetos) management in western North America’s grasslands, particularly those of the Great Plains region, include maintaining open, mostly undeveloped landscapes that sustain at least modest population levels of suitable prey (most typically rabbits [Leporidae] and prairie dogs or ground squirrels [Sciuridae]); safeguarding nesting territories (that is, breeding areas), especially nest structures within territories, from human disturbances; mitigating major sources of anthropogenic mortality, particularly electrocution on powerlines, shooting, collisions with structures and vehicles, and poisoning by lead and rodenticides; and averting climate change.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1842O","usgsCitation":"Murphy, R.K., DeLong, J.P., Igl, L.D., and Shaffer, J.A., 2023, The effects of management practices on grassland birds—Golden Eagle (Aquila chrysaetos), chap. O of Johnson, D.H., Igl, L.D., Shaffer, J.A., and DeLong, J.P., eds., The effects of management practices on grassland birds: U.S. Geological Survey Professional Paper 1842, 65 p., https://doi.org/10.3133/pp1842O.","productDescription":"v, 65 p.","numberOfPages":"76","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-093912","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":416072,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1842/o/coverthb.jpg"},{"id":416073,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1842/o/pp1842o.pdf","text":"Report","size":"2.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1842–O"}],"contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
The U.S. Geological Survey, in cooperation with Gwinnett County Department of Water Resources, established the Long-Term Trend Monitoring program in 1996 to monitor and analyze the hydrologic and water-quality conditions in Gwinnett County, Georgia. Gwinnett County is a suburban to urban area northeast of the city of Atlanta in north-central Georgia. The monitoring program currently consists of 15 watersheds ranging in size from 1.3 to about 161 square miles. This report synthesizes watershed characteristics and hydrologic and water-quality monitoring data collected for water years (WYs) 2002–20.
The 15 study watersheds were characterized for land-surface elevations, average land-surface slopes, septic densities, sanitary sewer densities, and detention pond areas. Temporal patterns in watershed characteristics were determined for land cover (2001–19), percent imperviousness (2000–20), population density (2000–20), and building density (1950–2022). In 2001, most of the watersheds had at least 45 percent of their land cover composed of developed land cover groups, and by 2019, at least 59 percent of each watershed was developed. Land cover changes occurred most rapidly between 2004 and 2008 at most watersheds. Percent imperviousness in the study watersheds varied substantially and ranged from 14.75 to 55.13 percent in 2019.
Precipitation and runoff were quantified at all study watersheds for WYs 2002–20, and the hydrologic cycle was evaluated both annually and seasonally. Several 1-year or longer droughts occurred during this period. Study area precipitation averaged 51.5 inches per year and runoff averaged 22.5 inches per year. Variations in annual runoff were largely determined by annual precipitation but were also dependent upon watershed storage. Runoff varied seasonally because of high evapotranspiration rates in the summer and changes in base flow associated with seasonal changes in watershed storage. Fifty-one percent of runoff in the study area occurred as base flow. Watersheds with higher imperviousness had higher stormflows because of increased surface runoff and lower base flows because of reduced infiltration that recharges watershed storage.
Turbidity, water temperature, and specific conductance were continuously measured at each study site. These constituents varied seasonally, diurnally, and with streamflow. A minimum of two base-flow and six stormflow samples were collected per year at each watershed and were analyzed for 21 water-quality constituents (water temperature, laboratory specific conductance, pH, and turbidity, biochemical and chemical oxygen demand, suspended sediments, nutrients, base cations, trace metals, and total dissolved solids). Concentrations of most particulate constituents were approximately one-half or more orders of magnitude higher in stormflow samples than in base-flow samples. Total copper and zinc stormflow concentrations exceeded the national recommended aquatic life criteria for acute conditions to varying degrees.
Annual loads and yields were estimated for 12 constituents (which include suspended sediments, nutrients, base cations, trace metals, and total dissolved solids) using a surrogate regression model approach and the Beale load estimator. Loads were typically higher for years with higher runoff. The proportional range of annual loads for total suspended solids, suspended-sediment concentrations, total phosphorus, and total lead, however, were 3.2 to 4.8 times larger than for annual runoff. Higher-than-expected annual sediment loads occurred in the years that also had some of the highest peak flows during the period, indicating that large storms are responsible for much of the sediment transport. Large development projects in proximity to streams also were related to years with high sediment loads. Yields from the Crooked Creek and North Fork Peachtree Creek watersheds were typically among the highest for 8 of the 12 constituents. These watersheds had the two highest amounts of developed medium plus high intensity land cover and the two highest percentages of imperviousness. Moderate to strong correlations were identified between seven of the constituent yields and the percentage of developed medium and high intensity land cover groups. Temporal trends in concentrations and loads were identified for 140 of the 300 possible watershed-time period-constituent combinations. There were substantially more negative than positive temporal trends identified during WYs 2003–10, whereas the number of negative and positive temporal trends were similar during WYs 2010–20. Measures of sediment transport had the most negative temporal trends. A few watersheds had consistent trends across several constituents; however, these trends did not appear to be associated with temporal changes in development or imperviousness.
This study provides a thorough assessment of watershed characteristics, hydrology, and water-quality conditions and trends for the 15 study watersheds and can be used to identify possible factors that affect runoff and water quality and determine changes in water-quality conditions. Watershed managers can use these data and analyses to inform management decisions regarding the designated uses of streams, minimization of flooding, protection of aquatic habitats, and optimization of the effectiveness of best management practices.
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South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive, Suite 500
Norcross, GA 30093
https://www.usgs.gov/centers/lsawsc
Researchers routinely study streamflow data to understand the effects of natural climate variability and anthropogenic climate change, and to develop methods for estimating streamflow at ungaged locations. These studies require streamflow data that are not modified or largely altered by other anthropogenic activities, such as reservoirs or diversions. This report discusses a method for identifying basins with reservoir regulation using a decadal impact metric that characterizes the degree of regulation of a given river reach. The method is applied to U.S. Geological Survey streamgage basins from eight States in the Central United States. Using this metric, 140 streamgages with known regulation effects (annual peak streamflow values qualified with a code 6) were evaluated for their impact metric values in decades with annual peak streamflow values qualified with code 6. Based on the distribution of median impact metric values at these regulated basins, a threshold value of 0.1 was identified as the value that when exceeded was the most characteristic of the regulated streamgage basins in the study area. Streamgage basins from nine States with peak streamflow values that were not qualified with code 6 were evaluated for impact metric values equal to or greater than the established threshold. About 13 percent of streamgages (136 of 1,017) had an impact metric equal to or greater than the identified regulated threshold at some point in their periods of record. The method discussed in this report, which has limitations owing to characteristics of the data underlying the dam impact metric, provides a regionally consistent approach to identifying regulated U.S. Geological Survey streamgage basins.
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The groundwater and surface-water supply of the Central Platte Natural Resources District supports a large agricultural economy from the High Plains aquifer and Platte River, respectively. This study provided the Central Platte Natural Resources District with an advanced numerical modeling tool to assist with the update of their Groundwater Management Plan.
An integrated hydrologic model, called the Central Platte Integrated Hydrologic Model, was constructed using the MODFLOW-One-Water Hydrologic Model code with the Newton solver. This code integrates climate, landscape, surface water, and groundwater-flow processes in a fully coupled approach. Model framework included 163 rows; 327 columns; 2,640 feet cell sides; and 3 vertical layers. A predevelopment model simulated steady-state hydrologic conditions prior to April 30, 1895, and a development period model discretized into 610 stress periods simulated transient hydrologic conditions from May 1, 1895, to December 31, 2016, using 170 biannual stress periods from 1895 to 1980, and monthly stress periods from May 1, 1980, to December 31, 2016.
Calibration of the Central Platte Integrated Hydrologic Model involved two phases: a manual adjustment of parameters, followed by the automated calibration completed using BeoPEST that was facilitated by the employment of the singular value decomposition-assist features of PEST that specified 50 super parameters assembled from the 435 adjustable parameters and Tikhonov regularization. The average absolute groundwater-level residuals for model layers one, two, and three were 6.1, 12.4, and 7.4 feet, respectively. Calibrated horizontal hydraulic conductivity was about 70, 32, and 35 feet per day for layers 1, 2, and 3, respectively. The largest development period inflow to groundwater was recharge from deep percolation past the root zone, averaging 1,122,257 acre-feet per year (2.7 inches per year), and the largest outflow was to irrigation wells, averaging 693,171 acre-feet per year (10.2 inches per year for the Central Platte Natural Resources District). Other substantial groundwater outflows included evapotranspiration and base flow. For the total development period, there was a net change in storage of −122,393 acre-feet per year (−0.3 inch per year).
The calibrated Central Platte Integrated Hydrologic Model was used to simulate eight different potential future climate and irrigation pumping conditions from January 1, 2017, to December 31, 2049. Simulated future groundwater levels within the Central Platte Natural Resources District varied significantly between scenarios and locally, from 13.8 feet below to 7.6 feet above baseline 1982 groundwater levels. Most areas exhibited groundwater-level declines for the drought scenarios and rises for the alternate irrigation scenarios. Changes in scenario groundwater levels correlated with the relations between farm net recharge and irrigation pumping. Linear “first order second moment” techniques indicated that the uncertainty in projected groundwater altitudes was reduced by 15.33 feet through model calibration.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235024","collaboration":"Prepared in cooperation with the Central Platte Natural Resources District and the Nebraska Natural Resources Commission","usgsCitation":"Traylor, J.P., Guira, M., and Peterson, S.M., 2023, An integrated hydrologic model to support the Central Platte Natural Resources District Groundwater Management Plan, central Nebraska: U.S. Geological Survey Scientific Investigations Report 2023–5024, 143 p., https://doi.org/10.3133/sir20235024.","productDescription":"Report: xii, 143 p.; 2 Tables; Data Release; Dataset; 3 Figures: 11.00 x 8.50 inches","numberOfPages":"160","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-123254","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":416070,"rank":12,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235024/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":500878,"rank":13,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114681.htm","linkFileType":{"id":5,"text":"html"}},{"id":416058,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5024/sir20235024_tables1.1_to_4.24.zip","text":"Appendix tables","size":"36 kB","linkFileType":{"id":7,"text":"csv"}},{"id":416057,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9G3Q5XK","text":"USGS data release","linkHelpText":"MODFLOW-One-Water model used to support the Central Platte Natural Resources District Groundwater Management Plan, central Nebraska"},{"id":416056,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":416068,"rank":11,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2023/5024/sir20235024_fig11.pdf","text":"Figure 11 (layered)","size":"1.60 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":416055,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5024/downloads","text":"Appendix tables","linkFileType":{"id":3,"text":"xlsx"}},{"id":416054,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5024/images"},{"id":416067,"rank":10,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2023/5024/sir20235024_fig07b.pdf","text":"Figure 7B (layered)","size":"3.37 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":416053,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5024/sir20235024.XML","text":"Report","linkFileType":{"id":8,"text":"xml"}},{"id":416052,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5024/sir20235024.pdf","text":"Report","size":"14.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5024"},{"id":416066,"rank":9,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2023/5024/sir20235024_fig04b.pdf","text":"Figure 4B (layered)","size":"847 kB","linkFileType":{"id":1,"text":"pdf"}},{"id":416051,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5024/coverthb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Platte River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -97.333,\n 41.51085969164163\n ],\n [\n -100.35,\n 41.51085969164163\n ],\n [\n -100.35,\n 40.11583169634787\n ],\n [\n -97.333,\n 40.11583169634787\n ],\n [\n -97.333,\n 41.51085969164163\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
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Field relations as well as geochemical and petrologic studies of metaigneous rocks assigned to the Pennsylvanian–Permian Petersburg batholith identify at least two distinct rock types: foliated metagranitoid gneiss and massive to porphyritic granite. Foliated metagranitoid gneiss of mostly granodioritic composition is geochemically distinct from associated massive and porphyritic granitic rocks. These gneissic rocks yield radiometric ages from ca. 425 Ma to ca. 403 Ma and document that many of the rocks assigned to the late Paleozoic Petersburg batholith are 100 m.y. older than the youngest portions of the composite batholith and are part of an earlier infrastructural terrane. Two samples of massive equigranular granite southwest of Petersburg, Virginia, yield ages of ca. 321 Ma and ca. 317 Ma, which are 15–20 m.y. older than ca. 300 Ma ages for porphyritic granite, massive granite, and monzodiorite near Richmond, Virginia. Geologic mapping shows that the Early Pennsylvanian granite southwest of Petersburg is separated from Late Pennsylvanian to early Permian granite near Richmond by a map-scale septum of Silurian–Devonian foliated metagranitoid gneiss, referred to herein as the informal Pocoshock Creek gneiss. Laser ablation–inductively coupled plasma–mass spectrometry data from one sample of a quartz-muscovite felsic schist xenolith show a peak age mode of ca. 529 Ma that we interpret to be the maximum depositional age. Inherited zircons from foliated metagranitoid gneiss and massive equigranular granite range from ca. 631 Ma to ca. 376 Ma, but many are Cambrian. Neoproterozoic–Cambrian quartz-muscovite felsic schist and amphibolite, Silurian–Devonian Pocoshock Creek gneiss, and Pennsylvanian–Permian granite comprise a fault-bounded terrane referred to herein as the Dinwiddie terrane. Ages of inherited cores in zircon from igneous rocks and limited detrital zircon geochronology suggest the terrane is of peri-Gondwanan affinity. U/Pb ages of healed fractures in zircon grains from foliated metagranitoid gneiss indicate low-grade deformation of the gneiss at ca. 378–376 Ma, while ca. 320–280 Ma rims on many grains record intrusion of late Paleozoic granite. The temperature-time-deformation history of the Dinwiddie terrane is distinct from the adjacent Goochland and Roanoke Rapids terranes. Orogen-scale dextral transpression likely translated the Dinwiddie terrane southward during the Alleghanian orogeny, at which time they were intruded by Pennsylvanian to Permian granite.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02546.1","usgsCitation":"Carter, M.W., McAleer, R.J., Holm-Denoma, C., Occhi, M.E., Owens, B.E., and Vazquez, J.A., 2023, Redefinition of the Petersburg batholith and implications for crustal inheritance in the Dinwiddie terrane, Virginia, USA: Geosphere, v. 19, no. 3, p. 900-932, https://doi.org/10.1130/GES02546.1.","productDescription":"33 p.","startPage":"900","endPage":"932","ipdsId":"IP-133680","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":443798,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1130/ges02546.1","text":"Publisher Index Page"},{"id":435366,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92IZPID","text":"USGS data release","linkHelpText":"Whole Rock Geochemistry and Uranium Lead Isotopic Data from the Dinwiddie Terrane, Virginia, USA"},{"id":420240,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Dinwiddie terrane","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -77.49748525226563,\n 37.798681296457076\n ],\n [\n -78.21468653839521,\n 37.79869080070846\n ],\n [\n -78.24158158662492,\n 36.599064764101655\n ],\n [\n -77.49748525226563,\n 36.599064764101655\n ],\n [\n -77.49748525226563,\n 37.798681296457076\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"19","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-04-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Carter, Mark W. 0000-0003-0460-7638 mcarter@usgs.gov","orcid":"https://orcid.org/0000-0003-0460-7638","contributorId":4808,"corporation":false,"usgs":true,"family":"Carter","given":"Mark","email":"mcarter@usgs.gov","middleInitial":"W.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":881212,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":881213,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holm-Denoma, Christopher S. 0000-0003-3229-5440","orcid":"https://orcid.org/0000-0003-3229-5440","contributorId":219763,"corporation":false,"usgs":true,"family":"Holm-Denoma","given":"Christopher S.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":881214,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Occhi, Marcie E.","contributorId":328758,"corporation":false,"usgs":false,"family":"Occhi","given":"Marcie","email":"","middleInitial":"E.","affiliations":[{"id":78483,"text":"Virginia Energy - Geology and Mineral Resources","active":true,"usgs":false}],"preferred":false,"id":881215,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Owens, Brent E.","contributorId":178190,"corporation":false,"usgs":false,"family":"Owens","given":"Brent","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":881216,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vazquez, Jorge A. 0000-0003-2754-0456 jvazquez@usgs.gov","orcid":"https://orcid.org/0000-0003-2754-0456","contributorId":4458,"corporation":false,"usgs":true,"family":"Vazquez","given":"Jorge","email":"jvazquez@usgs.gov","middleInitial":"A.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":881217,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}