Coal is increasingly evaluated as a source of rare earth elements (REEs) in the United States to address the overreliance on imported REEs. The objective of this study was to assess the distribution of REEs in lignites from selected mining areas in the Texas Gulf Coastal Plain region. Thirty-one archived lignite and rock samples previously collected by the U.S. Geological Survey were analyzed for their rare earth element and critical mineral content. These include samples from one core (5400 and 5500 lignite horizons) and two opencast lignite mines (Gibbons Creek 3500 and 4500 horizons, and San Miguel horizons A to D) in the Eocene Jackson Group of the Texas Gulf of Mexico Coastal Plain. Some lithologies in the Gibbons Creek 3500 and 4500 lignite-bearing sections have high total rare earth, yttrium (Y), and scandium (Sc) (REYSc) values, up to 7800 ppm (ash basis) REYSc. The lignite lithologies show an enrichment in rare earths, [samarium (Sm) through gadolinium (Gd)]. The basal Gibbons Creek 3500 lignite bench shows a heavy rare earth element enrichment pattern resembling that often seen in peats through high volatile A bituminous coals. The 5500 lignite sequence, overlying the latter lignite sections, shows a light rare earth enrichment. The San Miguel lignite benches have heavy rare earth enrichments with a negative europium (Eu) anomaly.
Salinity control efforts in the Colorado River Basin have focused on mobilization of salts from irrigated land, but nonirrigated rangelands are also a source of salinity. In particular, lands where soils have formed from the Late Cretaceous Mancos Shale under arid and semiarid climates contain considerable quantities of salt, mainly in the subsurface. Hundreds of thousands of contour furrows and check dams (gully plugs) were constructed by the Bureau of Land Management (BLM) and Bureau of Reclamation in the late 1950s and 1960s to reduce runoff, sedimentation, and salt mobilization from ephemeral stream channels on rangelands. Sediment-retention ponds associated with check dams are dry most of the year, except immediately following substantial rain events. Generally, no maintenance has been performed on these structures, some have degraded over time, and their current and past influence on salinity is poorly understood. To assess the influence of check dams and their associated ponds on salt retention and mobilization, the U.S. Geological Survey, in cooperation with the BLM, conducted a study of such ponds within the Gunnison Gorge National Conservation Area (GGNCA) near Delta, Colorado.
This report includes conceptual models of how sediment-retention ponds function relative to salinity, and a collection of environmental data to evaluate the conceptual models. An inventory of 69 ponds indicated that 38 percent no longer had water holding capacity, and another 20 percent could hold 1 foot or less of water. Check-dam degradation was the main cause, but sediment infill of ponds contributed as well. Water content of soil profiles collected beneath ponds and immediately downstream from check dams indicated little penetration of water below 60 centimeters for most ponds and little evidence for lateral movement of water beneath check dams. Patterns of salt content in the soil profiles indicated no accumulation of salts at the pond surface from evaporating waters and little evidence for salt redistribution in the form of salt bulges or salt depletion curves at intermediate depths. Based on the conceptual models presented and interpretations of data collected by this study, it appears that the sediment-retention ponds in the GGNCA have neither mobilized nor retained substantial quantities of salt during their lifetimes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235071","collaboration":"Prepared in cooperation with Bureau of Land Management","programNote":"Water Availability and Use Science Program","usgsCitation":"Richards, R.J., Bern, C.R., and Moreno, V., 2023, Assessment of salinity retention or mobilization by sediment-retention ponds near Delta, Colorado, 2019: U.S. Geological Survey Scientific Investigations Report 2023–5071, 21 p., https://doi.org/10.3133/sir20235071.","productDescription":"Report: v, 21 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-134766","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":418430,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WZNJL6","text":"USGS data release","linkHelpText":"Data from the assessment of sediment-retention ponds near Delta, Colorado, 2019"},{"id":418428,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5071/coverthb.jpg"},{"id":418429,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5071/sir20235071.pdf","text":"Report","size":"4.39 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5071"},{"id":500951,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114965.htm","linkFileType":{"id":5,"text":"html"}},{"id":418866,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20235071/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5071"},{"id":418837,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5071/sir20235071.xml"},{"id":418836,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5071/images"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.55,\n 38.4\n ],\n [\n -107.55,\n 38.36\n ],\n [\n -107.53,\n 38.36\n ],\n [\n -107.53,\n 38.4\n ],\n [\n -107.55,\n 38.4\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25048, Mail Stop 415
Denver, Colorado 80225
Remote cameras have become a widespread data-collection tool for terrestrial mammals, but classifying images can be labor intensive and limit the usefulness of cameras for broad-scale population monitoring. Machine learning algorithms for automated image classification can expedite data processing, but image misclassifications may influence inferences. Here, we used camera data for three sympatric species with disparate body sizes and life histories – black-tailed jackrabbits (Lepus californicus), kit foxes (Vulpes macrotis), and pronghorns (Antilocapra americana) – as a model system to evaluate the influence of competing image classification approaches on estimates of occupancy and inferences about space use. We classified images with: (i) single review (manual), (ii) double review (manual by two observers), (iii) an automated-manual review (machine learning to cull empty images and single review of remaining images), (iv) a pretrained machine-learning algorithm that classifies images to species (base model), (v) the base model accepting only classifications with ≥95% confidence, (vi) the base model trained with regional images (trained model), and (vii) the trained model accepting only classifications with ≥95% confidence. We compared species-specific results from alternative approaches to results from double review, which reduces the potential for misclassifications and was assumed to be the best approximation of truth. Despite high classification success, species-level misclassification rates for the base and trained models were sufficiently high to produce erroneous occupancy estimates and inferences related to space use across species. Increasing the confidence thresholds for image classification to 95% did not consistently improve performance. Classifying images as empty (or not) offered a reasonable approach to reduce effort (by 97.7%) and facilitated a semi-automated workflow that produced reliable estimates and inferences. Thus, camera-based monitoring combined with machine learning algorithms for image classification could facilitate monitoring with limited manual image classification.
","language":"English","publisher":"Wiley","doi":"10.1002/rse2.356","usgsCitation":"Lonsinger, R.C., Dart, M.M., Larsen, R., and Knight, R.N., 2023, Efficacy of machine learning image classification for automated occupancy-based monitoring: Remote Sensing in Ecology and Conservation, v. 10, no. 1, p. 56-71, https://doi.org/10.1002/rse2.356.","productDescription":"16 p.","startPage":"56","endPage":"71","ipdsId":"IP-150309","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":442810,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rse2.356","text":"Publisher Index Page"},{"id":432056,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Dugway Proving Ground, Lund, Mojave Desert, Beaver Dam Wash, Colorado Plateau Great Basin Desert","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-111.046551,41.251716],[-111.046723,40.997959],[-110.750727,40.996847],[-110.715026,40.996347],[-110.539819,40.996346],[-110.500718,40.994746],[-110.375714,40.994947],[-110.250709,40.996089],[-110.237848,40.995427],[-110.125709,40.99655],[-110.121639,40.997101],[-110.048476,40.997555],[-110.006495,40.997815],[-110.000708,40.997352],[-109.999838,40.99733],[-109.97553,40.997912],[-109.855299,40.997614],[-109.854302,40.997661],[-109.715409,40.998191],[-109.713877,40.998266],[-109.676421,40.998395],[-109.534926,40.998143],[-109.500694,40.999127],[-109.250735,41.001009],[-109.231985,41.002059],[-109.173682,41.000859],[-109.050076,41.000659],[-109.048455,40.826081],[-109.049088,40.714562],[-109.048373,40.662602],[-109.048249,40.653601],[-109.048044,40.619231],[-109.050074,40.540358],[-109.049955,40.539901],[-109.050698,40.499963],[-109.050314,40.495092],[-109.050946,40.444368],[-109.050969,40.222662],[-109.050973,40.180849],[-109.050944,40.180712],[-109.050813,40.059579],[-109.050873,40.058915],[-109.050615,39.87497],[-109.05104,39.660472],[-109.051363,39.497674],[-109.050765,39.366677],[-109.051512,39.126095],[-109.052436,38.999985],[-109.053292,38.942878],[-109.053233,38.942467],[-109.053797,38.905284],[-109.053943,38.904414],[-109.054189,38.874984],[-109.057388,38.795456],[-109.059541,38.719888],[-109.060253,38.599328],[-109.059962,38.499987],[-109.060062,38.275489],[-109.054648,38.244921],[-109.041762,38.16469],[-109.041837,38.153022],[-109.04282,37.999301],[-109.042819,37.997068],[-109.043121,37.97426],[-109.041058,37.907236],[-109.041653,37.88117],[-109.041844,37.872788],[-109.041723,37.842051],[-109.041754,37.835826],[-109.041461,37.800105],[-109.042098,37.74999],[-109.041636,37.74021],[-109.04176,37.713182],[-109.041732,37.711214],[-109.042269,37.666067],[-109.042089,37.623795],[-109.042131,37.617662],[-109.041806,37.604171],[-109.041865,37.530726],[-109.041915,37.530653],[-109.043137,37.499992],[-109.043464,37.484711],[-109.04581,37.374993],[-109.046039,37.249993],[-109.045584,37.249351],[-109.045487,37.210844],[-109.045978,37.201831],[-109.045995,37.177279],[-109.045156,37.112064],[-109.045203,37.111958],[-109.045173,37.109464],[-109.045189,37.096271],[-109.044995,37.086429],[-109.045058,37.074661],[-109.045166,37.072742],[-109.045223,36.999084],[-109.181196,36.999271],[-109.233848,36.999266],[-109.246917,36.999346],[-109.26339,36.999263],[-109.268213,36.999242],[-109.270097,36.999266],[-109.378039,36.999135],[-109.381226,36.999148],[-109.495338,36.999105],[-109.625668,36.998308],[-109.875673,36.998504],[-110.000677,36.997968],[-110.000876,36.998502],[-110.021778,36.998602],[-110.47019,36.997997],[-110.490908,37.003566],[-110.50069,37.00426],[-110.599512,37.003448],[-110.625605,37.003416],[-110.62569,37.003721],[-110.75069,37.003197],[-111.066496,37.002389],[-111.133718,37.000779],[-111.254853,37.001077],[-111.278286,37.000465],[-111.405517,37.001497],[-111.405869,37.001481],[-111.412784,37.001478],[-112.35769,37.001025],[-112.368946,37.001125],[-112.534545,37.000684],[-112.538593,37.000674],[-112.540368,37.000669],[-112.545094,37.000734],[-112.558974,37.000692],[-112.609787,37.000753],[-112.899366,37.000319],[-112.966471,37.000219],[-113.965907,36.999976],[-113.965907,37.000025],[-114.0506,37.000396],[-114.051749,37.088434],[-114.051822,37.090976],[-114.052827,37.103961],[-114.051867,37.134292],[-114.052179,37.14711],[-114.051673,37.172368],[-114.051405,37.233854],[-114.051974,37.283848],[-114.051974,37.284511],[-114.0518,37.293044],[-114.0518,37.293548],[-114.051927,37.370459],[-114.051927,37.370734],[-114.051765,37.418083],[-114.052448,37.43144],[-114.052701,37.492014],[-114.052685,37.502513],[-114.052718,37.517264],[-114.052689,37.517859],[-114.052962,37.592783],[-114.052472,37.604776],[-114.051728,37.745997],[-114.051785,37.746249],[-114.05167,37.746958],[-114.051109,37.756276],[-114.049919,37.765586],[-114.048473,37.809861],[-114.049677,37.823645],[-114.049928,37.852508],[-114.049658,37.881368],[-114.050423,37.999961],[-114.049903,38.148601],[-114.050138,38.24996],[-114.049417,38.2647],[-114.05012,38.404536],[-114.050091,38.404673],[-114.050485,38.499955],[-114.049834,38.543784],[-114.049862,38.547764],[-114.050154,38.57292],[-114.049883,38.677365],[-114.049749,38.72921],[-114.049168,38.749951],[-114.049465,38.874949],[-114.048521,38.876197],[-114.048054,38.878693],[-114.049104,39.005509],[-114.047079,39.499943],[-114.047728,39.542742],[-114.047273,39.759413],[-114.047783,39.79416],[-114.047214,39.821024],[-114.047134,39.906037],[-114.046555,39.996899],[-114.046835,40.030131],[-114.046386,40.097896],[-114.046741,40.104231],[-114.046683,40.116931],[-114.046153,40.231971],[-114.046178,40.398313],[-114.045826,40.424823],[-114.045218,40.430282],[-114.045518,40.494474],[-114.045577,40.495801],[-114.045281,40.506586],[-114.043505,40.726292],[-114.043831,40.758666],[-114.043803,40.759205],[-114.043176,40.771675],[-114.042145,40.999926],[-114.041447,41.207752],[-114.042553,41.210923],[-114.041396,41.219958],[-114.040231,41.49169],[-114.040942,41.499921],[-114.040437,41.615377],[-114.039968,41.62492],[-114.039901,41.753781],[-114.041152,41.850595],[-114.041107,41.850573],[-114.039648,41.884816],[-114.041723,41.99372],[-113.993903,41.992698],[-113.893261,41.988057],[-113.822163,41.988479],[-113.796082,41.989104],[-113.76453,41.989459],[-113.500837,41.992799],[-113.496548,41.993305],[-113.431563,41.993799],[-113.40223,41.994161],[-113.396497,41.99425],[-113.357611,41.993859],[-113.340072,41.994747],[-113.250829,41.99561],[-113.249159,41.996203],[-113.000821,41.998223],[-113.00082,41.998223],[-112.979218,41.998263],[-112.909587,41.998791],[-112.882367,41.998922],[-112.880619,41.998921],[-112.833125,41.999345],[-112.833084,41.999305],[-112.788542,41.999681],[-112.709375,42.000309],[-112.648019,42.000307],[-112.450814,42.000953],[-112.450567,42.001092],[-112.38617,42.001126],[-112.264936,42.000991],[-112.239107,42.001217],[-112.192976,42.001167],[-112.173352,41.996568],[-112.163956,41.996708],[-112.109532,41.997598],[-112.01218,41.99835],[-111.915837,41.998519],[-111.915622,41.998496],[-111.876491,41.998528],[-111.750778,41.99933],[-111.507264,41.999518],[-111.471381,41.999739],[-111.425535,42.00084],[-111.420898,42.000793],[-111.415873,42.000748],[-111.046689,42.001567],[-111.045818,41.579845],[-111.045789,41.565571],[-111.046264,41.377731],[-111.0466,41.360692],[-111.046551,41.251716]]]},\"properties\":{\"name\":\"Utah\",\"nation\":\"USA \"}}]}","volume":"10","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Lonsinger, Robert Charles 0000-0002-1040-7299","orcid":"https://orcid.org/0000-0002-1040-7299","contributorId":340524,"corporation":false,"usgs":true,"family":"Lonsinger","given":"Robert","email":"","middleInitial":"Charles","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907444,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dart, Marlin M.","contributorId":340675,"corporation":false,"usgs":false,"family":"Dart","given":"Marlin","email":"","middleInitial":"M.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":907445,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Larsen, Randy T.","contributorId":340676,"corporation":false,"usgs":false,"family":"Larsen","given":"Randy T.","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":907446,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knight, Robert N.","contributorId":340677,"corporation":false,"usgs":false,"family":"Knight","given":"Robert","email":"","middleInitial":"N.","affiliations":[{"id":81648,"text":"US Army Dugway Proving Ground","active":true,"usgs":false}],"preferred":false,"id":907447,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70246549,"text":"sir20235075 - 2023 - Potential effects of projected pumping scenarios on future water-table elevations near Kirtland Air Force Base in Albuquerque, New Mexico","interactions":[],"lastModifiedDate":"2026-03-12T20:44:43.104195","indexId":"sir20235075","displayToPublicDate":"2023-07-10T12:38:28","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5075","displayTitle":"Potential Effects of Projected Pumping Scenarios on Future Water-Table Elevations Near Kirtland Air Force Base in Albuquerque, New Mexico","title":"Potential effects of projected pumping scenarios on future water-table elevations near Kirtland Air Force Base in Albuquerque, New Mexico","docAbstract":"The U.S. Geological Survey, in cooperation with the Air Force Civil Engineer Center, simulated different groundwater pumping scenarios from 2016 to 2050 to determine the potential future changes in groundwater levels in areas around the Kirtland Air Force Base Bulk Fuels Facility and an ethylene dibromide (EDB) plume. Projections of water supply and demand created by the Albuquerque Bernalillo County Water Utility Authority were used to develop the future groundwater pumping scenarios used as inputs for a refined local-scale model within the updated Middle Rio Grande Basin regional model.
The simulated water-table elevations in model cells that contain the EDB plume in the medium demand and medium supply scenario rose 29 feet (ft) until 2035, then remained within 10 ft of that elevation through 2050, whereas the water-table elevations in the high demand and low supply scenario rose about 26 ft until 2035 and then decreased by more than 10 ft. Simulated water-table elevations in the low demand and high supply scenario continued to rise throughout most of the future simulation period and peaked at about 44 ft over the 2016 water-table elevation. All of the scenarios ended the future simulation period with higher simulated water-table elevations than at the beginning of the future simulation period. Simulations that represented the potentially highest and lowest volume of groundwater pumping near the EDB plume by adjusting the spatial distribution of pumping had similar simulated water-table elevations as the nonadjusted scenarios, with maximum water-table elevation changes that only differed by about 2 ft from the nonadjusted scenarios. Consideration should be taken when using these model results to inform decisions because the model results are subject to uncertainty from many different sources, including uncertainty in the future pumping scenarios as well as the model itself because of the simplification of the hydrogeologic system.
Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
The “National Field Manual for the Collection of Water-Quality Data” (NFM) provides guidelines and procedures for U.S. Geological Survey (USGS) personnel who collect data used to assess the quality of the Nation’s surface-water and groundwater resources. This chapter, NFM A6.0, provides guidance and protocols for the measurement of field parameters on site, which include the selection of sites and methods for measurement in groundwater and surface water and procedures for measurement and reporting. It updates and supersedes USGS Techniques of Water-Resources Investigations, book 9, chapter A6.0, version 2.0, by Franceska D. Wilde. Field parameters are routinely measured when water samples are collected, are often measured continually at USGS streamgages, and are regularly measured during laboratory and field experiments. The field methods for measuring field parameters described in this chapter are applicable to most natural waters.
Before 2017, the NFM chapters were released in the USGS Techniques of Water-Resources Investigations series. Effective in 2018, new and revised NFM chapters are being released in the USGS Techniques and Methods series; this series change does not affect the content and format of the NFM. More information is in the general introduction to the NFM (USGS Techniques and Methods, book 9, chapter A0) at https://doi.org/10.3133/tm9A0. The authoritative current versions of NFM chapters are available in the USGS Publications Warehouse at https://pubs.er.usgs.gov/. Comments, questions, and suggestions related to the NFM can be addressed to nfm@usgs.gov.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"National Field Manual for the Collection of Water-Quality Data. U.S. Geological Survey Techniques of Water-Resources Investigations, Book 9","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm9A6.0","usgsCitation":"U.S. Geological Survey, 2023, Guidelines for field-measured water-quality properties: U.S. Geological Survey Techniques and Methods, book 9, chap. A6.0 [version 1.1, July 17, 2023), 22 p., https://doi.org/10.3133/tm9A6.0. [Supersedes USGS Techniques of Water-Resources Investigations, book 9, chap. A6.0, version 2.0.]","productDescription":"vi, 22 p.","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-118566","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":418758,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm9A0","text":"Techniques and Methods 9-A0","linkHelpText":"- General Introduction for the “National Field Manual for the Collection of Water-Quality Data”"},{"id":418759,"rank":5,"type":{"id":18,"text":"Project Site"},"url":"https://www.usgs.gov/mission-areas/water-resources/science/national-field-manual-collection-water-quality-data-nfm","text":"National Field Manual for the Collection of Water-Quality Data (NFM)"},{"id":418755,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/09/a6.0/coverthb2.jpg"},{"id":418757,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/tm/09/a6.0/versionHist.txt","size":"2.70 KB","linkFileType":{"id":2,"text":"txt"}},{"id":418756,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/09/a6.0/tm9a6.0.pdf","text":"Report","size":"1.33 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 9-A6.0"}],"edition":"Version 1.0: July 10, 2023; Version 1.1: July 17, 2023","contact":"Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Email: nfm@usgs.gov
","tableOfContents":"Coordinated wildlife disease surveillance (WDS) can help professionals across disciplines effectively safeguard human, animal, and environmental health. The aims of this study were to understand how WDS in Thailand is utilized, valued, and can be improved within a One Health framework. An online questionnaire was distributed to 183 professionals (55.7% response rate) across Thailand working in wildlife, marine animal, livestock, domestic animal, zoo animal, environmental, and public health sectors. Twelve semi-structured interviews with key professionals were then performed. Three-quarters of survey respondents reported using WDS data and information. Sectors agreed upon ranking disease control (76.5% of respondents) as the most beneficial outcome of WDS, while fostering new ideas through collaboration was valued by few participants (2.0%). Accessing data collected by ones own sector was identified as the most challenging (50%) yet least difficult to improve (88.3%). Having legal authority to conduct WDS was the second most frequently identified challenge. Interviewees explained that legal documentation required for crossinstitutional collaborations posed a barrier to efficient communication and use of human resources. Survey respondents identified allocation of human resources (75.5%), adequate budget (71.6%), and having a clear communication system between sectors (71.6%) as highest priority areas for improvement to WDS in Thailand. Authorization from administrative officials and support from local community members were identified as challenges during in-person interviews. Future outreach should be directed towards these groups. As 42.9% of marine health professionals had difficulty knowing whom to contact in other sectors and 28.4% of survey respondents indicated that communication with marine health professionals was not applicable to their work, connecting the marine sector with other sectors may be prioritized. This study identifies priorities for addressing current challenges in the establishment of a general WDS system and information management system in Thailand while presenting a model for such evaluation in other regions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.onehlt.2023.100600","usgsCitation":"George, S.E., Smink, M., Sangkachai, N., Wiratsudakul, A., Sakcamduang, W., Suwanpakdee, S., and Sleeman, J.M., 2023, Stakeholder attitudes and perspectives on wildlife disease surveillance as a component of a One Health approach in Thailand: One Health Newsletter, v. 17, 100600, 10 p., https://doi.org/10.1016/j.onehlt.2023.100600.","productDescription":"100600, 10 p.","ipdsId":"IP-154964","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":442811,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.onehlt.2023.100600","text":"Publisher Index Page"},{"id":419412,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Thailand","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[102.58493,12.18659],[101.68716,12.64574],[100.83181,12.62708],[100.97847,13.41272],[100.0978,13.40686],[100.01873,12.307],[99.47892,10.84637],[99.15377,9.96306],[99.2224,9.23926],[99.87383,9.20786],[100.27965,8.29515],[100.45927,7.42957],[101.01733,6.85687],[101.62308,6.74062],[102.14119,6.22164],[101.81428,5.81081],[101.15422,5.69138],[101.07552,6.20487],[100.2596,6.64282],[100.08576,6.46449],[99.69069,6.84821],[99.51964,7.34345],[98.98825,7.90799],[98.50379,8.38231],[98.33966,7.79451],[98.15001,8.35001],[98.25915,8.97392],[98.55355,9.93296],[99.03812,10.96055],[99.58729,11.89276],[99.19635,12.80475],[99.21201,13.26929],[99.09776,13.8275],[98.43082,14.62203],[98.19207,15.1237],[98.53738,15.3085],[98.90335,16.17782],[98.49376,16.83784],[97.85912,17.56795],[97.3759,18.44544],[97.79778,18.62708],[98.25372,19.7082],[98.95968,19.75298],[99.54331,20.1866],[100.11599,20.41785],[100.54888,20.10924],[100.60629,19.50834],[101.28201,19.46258],[101.03593,18.40893],[101.05955,17.5125],[102.11359,18.1091],[102.413,17.93278],[102.99871,17.96169],[103.20019,18.30963],[103.95648,18.24095],[104.71695,17.42886],[104.77932,16.44186],[105.58904,15.57032],[105.54434,14.72393],[105.21878,14.27321],[104.28142,14.41674],[102.98842,14.22572],[102.3481,13.39425],[102.58493,12.18659]]]},\"properties\":{\"name\":\"Thailand\"}}]}","volume":"17","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"George, Serena Elise","contributorId":317781,"corporation":false,"usgs":false,"family":"George","given":"Serena","email":"","middleInitial":"Elise","affiliations":[{"id":69152,"text":"University of Wisconsin-Madison, School of Veterinary Medicine","active":true,"usgs":false}],"preferred":false,"id":879297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smink, Moniek","contributorId":317782,"corporation":false,"usgs":false,"family":"Smink","given":"Moniek","email":"","affiliations":[{"id":69153,"text":"University of Wisconsin-Madison, Department of Computer Sciences,","active":true,"usgs":false}],"preferred":false,"id":879298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sangkachai, Nareerat","contributorId":317783,"corporation":false,"usgs":false,"family":"Sangkachai","given":"Nareerat","email":"","affiliations":[{"id":69154,"text":"Thailand National Wildlife Health Center, Faculty of Veterinary Science & The Monitoring and Surveillance Center for Zoonotic Diseases in Wildlife and Exotic Animals","active":true,"usgs":false}],"preferred":false,"id":879299,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wiratsudakul, Anuwat","contributorId":317784,"corporation":false,"usgs":false,"family":"Wiratsudakul","given":"Anuwat","email":"","affiliations":[{"id":69155,"text":"Thailand National Wildlife Health Center, Faculty of Veterinary Science, The Monitoring and Surveillance Center for Zoonotic Diseases in Wildlife and Exotic Animals & Department of Clinical Sciences and Public Health, Faculty of Veterinary Science","active":true,"usgs":false}],"preferred":false,"id":879300,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sakcamduang, Walasinee","contributorId":317785,"corporation":false,"usgs":false,"family":"Sakcamduang","given":"Walasinee","email":"","affiliations":[{"id":69156,"text":"Thailand National Wildlife Health Center, Faculty of Veterinary Science & Department of Clinical Sciences and Public Health, Faculty of Veterinary Science","active":true,"usgs":false}],"preferred":false,"id":879301,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Suwanpakdee, Sarin","contributorId":317786,"corporation":false,"usgs":false,"family":"Suwanpakdee","given":"Sarin","email":"","affiliations":[{"id":69155,"text":"Thailand National Wildlife Health Center, Faculty of Veterinary Science, The Monitoring and Surveillance Center for Zoonotic Diseases in Wildlife and Exotic Animals & Department of Clinical Sciences and Public Health, Faculty of Veterinary Science","active":true,"usgs":false}],"preferred":false,"id":879302,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sleeman, Jonathan M. 0000-0002-9910-6125 jsleeman@usgs.gov","orcid":"https://orcid.org/0000-0002-9910-6125","contributorId":128,"corporation":false,"usgs":true,"family":"Sleeman","given":"Jonathan","email":"jsleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":82110,"text":"Midcontinent Regional Director's Office","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":879303,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70246562,"text":"70246562 - 2023 - Dissolved organic carbon dynamics and fluxes in Mississippi-Atchafalaya deltaic system impacted by an extreme flood event and hurricanes: A multi-satellite approach using Sentinel-2/3 and Landsat-8/9 data","interactions":[],"lastModifiedDate":"2023-07-10T15:42:41.208404","indexId":"70246562","displayToPublicDate":"2023-07-10T10:15:59","publicationYear":"2023","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":"Dissolved organic carbon dynamics and fluxes in Mississippi-Atchafalaya deltaic system impacted by an extreme flood event and hurricanes: A multi-satellite approach using Sentinel-2/3 and Landsat-8/9 data","docAbstract":"Transport of riverine and wetland-derived dissolved organic carbon (DOC) spanning tidal wetlands, estuaries, and continental shelf waters functionally connects terrestrial and aquatic carbon reservoirs, yet the magnitude and ecological significance of this variable and its spatiotemporal linkage remains uncertain for coastal deltaic regions, such as Mississippi River Delta Plain, which includes Mississippi (MR) and Atchafalaya (AR) rivers and estuaries with vast expanses of wetlands and coastal forests. We examined DOC dynamics and fluxes in this large river-dominated wetland-estuarine system for the period between 2019 and 2021 that included an extreme river flood event in 2019, two major hurricanes (Barry in 2019 and Ida in 2021), and cold front passage using an improved adaptive quasi-analytical algorithm (QAA-AD) applied to multi-satellite sensors (Sentinel 3A/B OLCI, Landsat-8/OLI and Sentinel-2A/B MSI) with varying spectral and spatial (10/30/300 m) resolutions. The DOC estimates from multi-satellite sensors in combination with water fluxes were used to assess DOC fluxes from two large rivers (MR and AR) and small channels across the delta plain. Overall, this system delivered a total of 6.7 Tg C yr-1 (1 Tg = 1012g) into the estuarine zone and the northern Gulf of Mexico (nGoM) during 2019. High DOC fluxes from the AR (1.3 Tg C yr-1) and MR (4.5 Tg C yr-1) were associated with the extreme flood event in 2019. Hurricanes that occurred in the study period also contributed to the wetland and estuarine DOC fluxes into continental shelf waters; for example, the passage of Hurricane Barry in July 2019, delivered over a 3-day period ~1.33 ×109 g DOC from Barataria Basin into the nGoM. Sentinel 2-MSI land and water classification revealed that Hurricane Ida eroded a total of 1.34×108 m2 of marshes in middle Barataria Basin, converting those habitats into open water with 3.0 m inundation depth and high DOC concentrations (16.4 mg L-1), a potentially large DOC source to the coastal waters. Overall, storms and flood events are major sources of DOC flux that facilitate transport of upstream carbon as well as transformation of carbon in the wetlands, through the conversion of vegetated wetland to open water.
","language":"English","publisher":"Frontiers Media S.A.","doi":"10.3389/fmars.2023.1159367","usgsCitation":"Liu, B., D’Sa, E.J., Messina, F., Baustian, M.M., Maiti, K., Rivera-Monroy, V.H., Huang, W., and Georgiou, I.Y., 2023, Dissolved organic carbon dynamics and fluxes in Mississippi-Atchafalaya deltaic system impacted by an extreme flood event and hurricanes: A multi-satellite approach using Sentinel-2/3 and Landsat-8/9 data: Frontiers in Marine Science, v. 10, 1159367, 24 p., https://doi.org/10.3389/fmars.2023.1159367.","productDescription":"1159367, 24 p.","ipdsId":"IP-148973","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":442812,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2023.1159367","text":"Publisher Index Page"},{"id":418810,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Atchafalaya River, Mississippi River, Mississippi River Delta Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.31893133610087,\n 30.458926156651998\n ],\n [\n -92.31893133610087,\n 27.86368380104267\n ],\n [\n -89.10966256396617,\n 27.86368380104267\n ],\n [\n -89.10966256396617,\n 30.458926156651998\n ],\n [\n -92.31893133610087,\n 30.458926156651998\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2023-06-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Liu, Bingqing","contributorId":304014,"corporation":false,"usgs":false,"family":"Liu","given":"Bingqing","email":"","affiliations":[{"id":13499,"text":"The Water Institute of the Gulf","active":true,"usgs":false}],"preferred":false,"id":877207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D’Sa, Eurico J.","contributorId":316255,"corporation":false,"usgs":false,"family":"D’Sa","given":"Eurico","email":"","middleInitial":"J.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":877208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Messina, Francesca","contributorId":316256,"corporation":false,"usgs":false,"family":"Messina","given":"Francesca","email":"","affiliations":[{"id":13499,"text":"The Water Institute of the Gulf","active":true,"usgs":false}],"preferred":false,"id":877209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baustian, Melissa Millman 0000-0003-2467-2533","orcid":"https://orcid.org/0000-0003-2467-2533","contributorId":304015,"corporation":false,"usgs":true,"family":"Baustian","given":"Melissa","email":"","middleInitial":"Millman","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":877210,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maiti, Kanchan","contributorId":316257,"corporation":false,"usgs":false,"family":"Maiti","given":"Kanchan","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":877211,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rivera-Monroy, Victor H. 0000-0003-2804-4139","orcid":"https://orcid.org/0000-0003-2804-4139","contributorId":200322,"corporation":false,"usgs":false,"family":"Rivera-Monroy","given":"Victor","email":"","middleInitial":"H.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":877212,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Huang, Wei","contributorId":316258,"corporation":false,"usgs":false,"family":"Huang","given":"Wei","email":"","affiliations":[{"id":40642,"text":"Oak Ridge National Lab","active":true,"usgs":false}],"preferred":false,"id":877213,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Georgiou, Ioannis Y.","contributorId":205361,"corporation":false,"usgs":false,"family":"Georgiou","given":"Ioannis","email":"","middleInitial":"Y.","affiliations":[{"id":37089,"text":"Pontchartrain Institute for Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":877214,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70257365,"text":"70257365 - 2023 - Development of conjugated secondary antibodies for wildlife disease surveillance","interactions":[],"lastModifiedDate":"2024-08-23T16:36:49.222723","indexId":"70257365","displayToPublicDate":"2023-07-10T09:25:50","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5620,"text":"Frontiers in Immunology","active":true,"publicationSubtype":{"id":10}},"title":"Development of conjugated secondary antibodies for wildlife disease surveillance","docAbstract":"Disease monitoring in free-ranging wildlife is a challenge and often relies on passive surveillance. Alternatively, proactive surveillance that relies on the detection of specific antibodies could give more reliable and timely insight into disease presence and prevalence in a population, especially if the evidence of disease occurs below detection thresholds for passive surveillance. Primary binding assays, like the indirect ELISA for antibody detection in wildlife, are hampered by a lack of species-specific conjugates. In this study, we developed anti-kudu (Tragelaphus strepsiceros) and anti-impala (Aepyceros melampus) immunoglobulin-specific conjugates in chickens and compared them to the binding of commercially available protein-G and protein-AG conjugates, using an ELISA-based avidity index. The conjugates were evaluated for cross-reaction with sera from other wild herbivores to assess future use in ELISAs. The developed conjugates had a high avidity of >70% against kudu and impala sera. The commercial conjugates (protein-G and protein-AG) had significantly low relative avidity (<20%) against these species. Eighteen other wildlife species demonstrated cross-reactivity with a mean relative avidity of >50% with the impala and kudu conjugates and <40% with the commercial conjugates. These results demonstrate that species-specific conjugates are important tools for the development and validation of immunoassays in wildlife and for the surveillance of zoonotic agents along the livestock-wildlife-human interface.
","language":"English","publisher":"Frontiers","doi":"10.3389/fimmu.2023.1221071","usgsCitation":"Ochai, S.O., Crafford, J.E., Kamath, P., Turner, W.C., and van Heerden, H., 2023, Development of conjugated secondary antibodies for wildlife disease surveillance: Frontiers in Immunology, v. 14, e1221071, 12 p., https://doi.org/10.3389/fimmu.2023.1221071.","productDescription":"e1221071, 12 p.","ipdsId":"IP-151072","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":442815,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fimmu.2023.1221071","text":"Publisher Index Page"},{"id":433111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","noUsgsAuthors":false,"publicationDate":"2023-07-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Ochai, Sunday O.","contributorId":342466,"corporation":false,"usgs":false,"family":"Ochai","given":"Sunday","email":"","middleInitial":"O.","affiliations":[{"id":48053,"text":"University of Pretoria","active":true,"usgs":false}],"preferred":false,"id":910121,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crafford, Jan E.","contributorId":342468,"corporation":false,"usgs":false,"family":"Crafford","given":"Jan","email":"","middleInitial":"E.","affiliations":[{"id":48053,"text":"University of Pretoria","active":true,"usgs":false}],"preferred":false,"id":910122,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kamath, Pauline L.","contributorId":342470,"corporation":false,"usgs":false,"family":"Kamath","given":"Pauline L.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":910123,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":910124,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"van Heerden, Henriette","contributorId":342472,"corporation":false,"usgs":false,"family":"van Heerden","given":"Henriette","email":"","affiliations":[{"id":48053,"text":"University of Pretoria","active":true,"usgs":false}],"preferred":false,"id":910125,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70246625,"text":"70246625 - 2023 - BioLake: A first assessment of lake temperature-derived bioclimatic predictors for aquatic invasive species","interactions":[],"lastModifiedDate":"2023-07-12T12:15:02.02119","indexId":"70246625","displayToPublicDate":"2023-07-10T07:10:53","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"BioLake: A first assessment of lake temperature-derived bioclimatic predictors for aquatic invasive species","docAbstract":"Aquatic invasive species (AIS) present major ecological and economic challenges globally, endangering ecosystems and human livelihoods. Managers and policy makers thus need tools to predict invasion risk and prioritize species and areas of concern, and they often use native range climate matching to determine whether a species could persist in a new location. However, climate matching for AIS often relies on air temperature rather than water temperature due to a lack of global water temperature data layers, and predictive power of models is seldom evaluated. We developed 12 global lake (water) temperature-derived “BioLake” bioclimatic layers for distribution modeling of aquatic species and compared “climatch” climate matching predictions (from climatchR package) from BioLake with those based on BioClim temperature layers and with a null model. We did this for 73 established AIS in the United States, training the models on their ranges outside of the United States and Canada. Models using either set of climate layers outperformed the null expectation by a similar (but modest) amount on average, but some species were occasionally found in locations with low climatch scores. Mean US climatch scores were higher for most species when using air temperature. Including additional climate layers in models reduced mean climatch scores, indicating that commonly used climatch score thresholds are not absolute but can be context specific and may require calibration based upon climate data used. Although finer resolution global lake temperature data would likely improve predictions, our BioLake layers provide a starting point for aquatic species distribution modeling. Climate matching was most effective for some species that originated at low latitudes or had small ranges. Climatch scores remain useful but limited for predicting AIS risk, perhaps because current ranges seldom fully reflect climatic tolerances (fundamental niches). Managers could consider climate matching as one of a suite of tools that can be used in AIS prioritization.
The Ibex Hollow Tuff, 12.08 ± 0.03 Ma (40Ar/39Ar), is a widespread tephra layer erupted from the Bruneau-Jarbidge volcanic field of southern Idaho. Tephra from this eruption was deposited across much of western and central North America and adjacent ocean areas. We identified the Ibex Hollow Tuff at Trapper Creek, Idaho, near its eruption site, and at 15 distal sites, from the Pacific Ocean to the Gulf of Mexico, by the chemical composition of its glass shards, using electron-microprobe analysis, instrumental neutron activation analysis, and laser-ablation–inductively coupled plasma–mass spectrometry. By these methods, we distinguished the Ibex Hollow Tuff from overlying and underlying tephra layers near its source and at distal sites. Fluvially reworked Ibex Hollow Tuff ash was transported by the ancestral Mississippi River drainage from the interior of the North American continent to the Gulf of Mexico, where it is present within an ~50-m-thick deposit in marine sediments in the subsurface. The minimum fallout area covered by the ash is ~2.7 million km2, with a minimum volume of ~800 km3, and potential dispersal farther to the north and northeast. The areal distribution for the Ibex Hollow Tuff is similar to that of the Lava Creek B (0.63 Ma) supereruption. The Ibex Hollow Tuff represents a unique chronostratigraphic marker allowing a synoptic view of paleoenvironments at a virtual moment in time across a large terrestrial and marine region. The Ibex Hollow Tuff is also an important marker bed for North American Land Mammal Ages, and it coincides with climatic cooling in the middle to late Miocene documented in marine cores.
Interventions of the host–pathogen dynamics provide strong tests of relationships, yet they are still rarely applied across multiple populations. After American bullfrogs (Rana catesbeiana) invaded a wildlife refuge where federally threatened Chiricahua leopard frogs (R. chiricahuensis) were reintroduced 12 years prior, managers launched a landscape-scale eradication effort to help ensure continued recovery of the native species. We used a before-after-control-impact design and environmental DNA sampling of 19 eradication sites and 18 control sites between fall 2016 and winter 2020–2021 to measure community-level responses to bullfrog eradication, including for two pathogens. Dynamic occupancy models revealed successful eradication from 94% of treatment sites. Native amphibians did not respond to bullfrog eradication, but the pathogens amphibian chytrid fungus (Batrachochytrium dendrobatidis) and ranaviruses were coextirpated with bullfrogs. Our spatially replicated experimental approach provides strong evidence that management of invasive species can simultaneously reduce predation and disease risk for imperiled species.
The duration of inundation or saturation (i.e., hydroperiod) controls many wetland functions. In particular, it is a key determinant of whether a wetland will provide suitable breeding habitat for amphibians and other taxa that often have specific hydrologic requirements. Yet, scientists and land managers often are challenged by a lack of sufficient monitoring data to enable the understanding of the wetting and drying dynamics of small depressional wetlands. In this study, we present and evaluate an approach to predict daily inundation dynamics using a large wetland water-level dataset and a random forest algorithm. We relied on predictor variables that described characteristics of basin morphology of each wetland and atmospheric water budget estimates over various antecedent periods. These predictor variables were derived from datasets available over the conterminous United States making this approach potentially extendable to other locations. Model performance was evaluated using two metrics, median hydroperiod and the proportion of correctly classified days. We found that models performed well overall with a median balanced accuracy of 83% on validation data. Median hydroperiod was predicted most accurately for wetlands that were infrequently inundated and least accurate for permanent wetlands. The proportion of inundated days was predicted most accurately in permanent wetlands (99%) followed by frequently inundated wetlands (98%) and infrequently inundated wetlands (93%). This modeling approach provided accurate estimates of inundation and could be useful in other depressional wetlands where the primary water flux occurs with the atmosphere and basin morphology is a critical control on wetland inundation and hydroperiods.
River profiles are shaped by climatic and tectonic history, lithology, and internal feedbacks between flow hydraulics, sediment transport and erosion. In steep channels, waterfalls may self-form without changes in external forcing (i.e., autogenic formation) and erode at rates faster or slower than an equivalent channel without waterfalls. We use a 1-D numerical model to investigate how self-formed waterfalls alter the morphology of bedrock river longitudinal profiles. We modify the standard stream power model to include a slope threshold above which waterfalls spontaneously form and a rate constant allowing waterfalls to erode faster or slower than other fluvial processes. Using this model, we explore how waterfall formation alters both steady state and transient longitudinal profile forms. Our model predicts that fast waterfalls create km-scale reaches in a dynamic equilibrium with channel slope held approximately constant at the threshold slope for waterfall formation, while slow waterfalls can create local channel slope maxima at the location of slow waterfall development. Furthermore, slow waterfall profiles integrate past base level histories, leading to multiple possible profile forms, even at steady-state. Consistency between our model predictions and field observations of waterfall-rich rivers in the Kings and Kaweah drainages in the southern Sierra Nevada, California, supports the hypothesis that waterfall formation can modulate river profiles in nature. Our findings may help identify how bedrock channels are influenced by waterfall erosion and aid in distinguishing between signatures of external and internal perturbations, thereby strengthening our ability to interpret past climate and tectonic changes from river longitudinal profiles.
Welcome to the resurrected series of U.S. Geological Survey (USGS) reports on stratigraphy entitled “Stratigraphic Notes.” For several decades, until the mid-1990s, the USGS published volumes of short papers that highlighted stratigraphic studies, changes in stratigraphic nomenclature, and explanations of stratigraphic names and concepts used on published geologic maps. The purpose was to encourage formal documentation on these topics.
Today (2023) the need for such documentation has become especially important because of the increasing number of informal reports that use new or updated stratigraphic nomenclature. Because the North American Stratigraphic Code does not recognize informal reports as proper publications to formalize stratigraphic studies, a report series such as “Stratigraphic Notes” is needed to bridge this gap.
“Stratigraphic Notes” is a long-term (multiyear), multivolume publication containing articles that address updates or revisions to stratigraphic nomenclature (and whose content ultimately will be incorporated into Geolex, https://ngmdb.usgs.gov/Geolex/). The papers in “Stratigraphic Notes” are meant to be an outlet to communicate changes in stratigraphic nomenclature, to support geologic map publications, and to facilitate compilation of new geologic maps and their databases.
The goal is to publish a new volume each year, each of which will contain papers that present results of stratigraphic studies drawn from scientific interpretations of stratigraphic and biostratigraphic changes related to changes in environments of deposition and facies, as well as interpretations of igneous and metamorphic units.
We welcome papers for the “Stratigraphic Notes” series from geoscientists of the USGS, of State Geological Surveys, and from academicians. Papers can be submitted for publication in “Stratigraphic Notes” by contacting the USGS Geologic Names Committee (gnc@usgs.gov). As new “Stratigraphic Notes” volumes are published, links to the volumes will be posted here at https://doi.org/10.3133/pp1879.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1879","usgsCitation":"Orndorff, R.C., Stamm, N.R., and Soller, D.R., eds., 2023, Stratigraphic notes: U.S. Geological Survey Professional Paper 1879, https://doi.org/10.3133/pp1879.","productDescription":"Multiple volumes","onlineOnly":"Y","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":64806,"text":"National Cooperative Geologic Mapping","active":true,"usgs":true}],"links":[{"id":418718,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1879/covrthb_main.jpg"},{"id":480772,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1879V2","text":"Professional Paper 1879-2","description":"Orndorff, R.C., Stamm, N.R., and Soller, D.R., eds., 2025, Stratigraphic notes—Volume 2, 2025: U.S. Geological Survey Professional Paper 1879–2, 28 p., https://doi.org/10.3133/pp1879v2.","linkHelpText":"- Stratigraphic Notes—Volume 2, 2025 - Edited by: Randall C. Orndorff, Nancy R. Stamm, and David R. Soller"},{"id":419310,"rank":2,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1879v1","text":"Professional Paper 1879-1","description":"Orndorff, R.C., Stamm, N.R., and Soller, D.R., eds., 2023, Stratigraphic notes—Volume 1, 2022: U.S. Geological Survey Professional Paper 1879–1, 38 p., https://doi.org/10.3133/pp1879V1.","linkHelpText":"- Stratigraphic Notes - Volume 1, 2022 - Edited by: Randall C. Orndorff, Nancy R. Stamm, and David R. Soller"}],"contact":"National Cooperative Geologic Mapping Program
U.S. Geological Survey
12201 Sunrise Valley Drive Mail Stop 908
Reston, VA 20192
This is the first volume in the U.S. Geological Survey (USGS) series of reports on stratigraphy entitled “Stratigraphic Notes,” which consists of short papers that highlight stratigraphic studies, changes in stratigraphic nomenclature, and explanations of stratigraphic names and concepts used on published geologic maps. “Stratigraphic Notes” is a long-term (multiyear), multivolume publication containing articles that address updates or revisions to stratigraphic nomenclature (and whose content ultimately will be incorporated by National Geologic Map Database personnel into Geolex, https://ngmdb.usgs.gov/Geolex/).
We welcome papers for the “Stratigraphic Notes” series from geoscientists of the USGS, of State Geological Surveys, and from academicians. Papers can be submitted for publication in “Stratigraphic Notes” by contacting the USGS Geologic Names Committee (gnc@usgs.gov). As new “Stratigraphic Notes” volumes are published, links to the volumes will be posted at https://doi.org/10.3133/pp1879.
This first volume (\"Stratigraphic notes—Volume 1, 2022\") includes articles that provide guidance for those who wish to submit papers to “Stratigraphic Notes,” as well as information on how to make your manuscripts compliant for geologic names reviews and how to organize your paper’s content to facilitate inclusion of new or revised names in Geolex. This volume also includes some specific guidance on conducting geologic names reviews of geologic and hydrogeologic reports.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1879V1","usgsCitation":"Orndorff, R.C., Stamm, N.R., and Soller, D.R., eds., 2023, Stratigraphic notes—Volume 1, 2022: U.S. Geological Survey Professional Paper 1879–1, 38 p., https://doi.org/10.3133/pp1879V1.","productDescription":"v, 38 p.","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-127066","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":64806,"text":"National Cooperative Geologic Mapping","active":true,"usgs":true}],"links":[{"id":418722,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1879/v1/pp1879v1.pdf","text":"Stratigraphic Notes—Volume 1, 2022","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- All Chapters"},{"id":418723,"rank":3,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1879/v1/pp1879v1a.pdf","text":"Chapter A. \"Stratigraphic Notes”—An Outlet for Stratigraphic Studies","size":"150 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":418721,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1879/v1/covrthb.jpg"},{"id":418725,"rank":5,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1879/v1/pp1879v1c.pdf","text":"Chapter C. Divisions of Geologic Time—Major Chronostratigraphic and Geochronologic Units","size":"250 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":480770,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1879V2","text":"Professional Paper 1879-2","description":"Orndorff, R.C., Stamm, N.R., and Soller, D.R., eds., 2025, Stratigraphic notes—Volume 2, 2025: U.S. Geological Survey Professional Paper 1879–2, 28 p., https://doi.org/10.3133/pp1879v2.","linkHelpText":"- Stratigraphic Notes—Volume 2, 2025"},{"id":480769,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1879","text":"Professional Paper 1879","description":"Orndorff, R.C., Stamm, N.R., and Soller, D.R., eds., 2023, Stratigraphic notes: U.S. Geological Survey Professional Paper 1879, https://doi.org/10.3133/pp1879.","linkHelpText":"- This publication is Volume 1 in Stratigraphic Notes"},{"id":418727,"rank":7,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1879/v1/pp1879v1e.pdf","text":"Chapter E. Guidelines for Conducting Reviews of Geologic Names and Aquifer Names in U.S. Geological Survey Hydrogeologic Maps and Reports","size":"200 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":500194,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118314.htm","linkFileType":{"id":5,"text":"html"}},{"id":418724,"rank":4,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1879/v1/pp1879v1b.pdf","text":"Chapter B. Suggestions for Proposing Changes in Nomenclature in Papers Submitted to “Stratigraphic Notes”","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":418726,"rank":6,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/pp/1879/v1/pp1879v1d.pdf","text":"Chapter D. Guidance on Geologic Names Usage for Authors and Peer Reviewers of Geologic Maps and Reports—A Primer on Stratigraphic Nomenclature","size":"600 KB","linkFileType":{"id":1,"text":"pdf"}}],"volume":"1","contact":"National Cooperative Geologic Mapping Program
U.S. Geological Survey
12201 Sunrise Valley Drive Mail Stop 908
Reston, VA 20192
Citing published reports and their own diagnostic data, Kaleta and Taday (Citation2003) (https://doi.org/10.1080/03079450310001593613) reported that 469 domestic and free-living bird species were determined to be chlamydia-positive, based on isolation of the organism and antigen detection or on serological detection of circulating antibodies. However, I was unable to reconcile the designation of chlamydia-positive in some of the species listed by Kaleta and Taday (Citation2003) with the information provided in the corresponding references cited. For example, Eddie et al. (Citation1966) tested sera from 24 species of birds in Alaska (see their ) by “direct and indirect complement fixation techniques in the presence of the standard psittacosis antigen.” Eddie et al. (Citation1966) reported that serum samples from only two species reacted, and the authors considered those titres too low to be of diagnostic significance. However, Kaleta and Taday (Citation2003) listed 20 bird species from Eddie et al. (Citation1966) as being positive for chlamydia. Additional apparent discrepancies are listed in of the current article.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/03079457.2023.2225978","usgsCitation":"Franson, J.C., 2023, Apparent discrepancies in the review “Avian host range of Chlamydophila spp. based on isolation, antigen detection and serology” by Kaleta, E.F. & Taday, E.M.A. (2003), Avian Pathology, 32, 435–462: Avian Pathology, v. 52, no. 4, p. 283-284, https://doi.org/10.1080/03079457.2023.2225978.","productDescription":"2 p.","startPage":"283","endPage":"284","ipdsId":"IP-129523","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":418809,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-07-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Franson, J. Christian 0000-0002-0251-4238 jfranson@usgs.gov","orcid":"https://orcid.org/0000-0002-0251-4238","contributorId":177499,"corporation":false,"usgs":true,"family":"Franson","given":"J.","email":"jfranson@usgs.gov","middleInitial":"Christian","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":877142,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70246554,"text":"70246554 - 2023 - Postfire hydrologic response along the central California (USA) coast: Insights for the emergency assessment of postfire debris-flow hazards","interactions":[],"lastModifiedDate":"2023-10-23T14:41:47.420879","indexId":"70246554","displayToPublicDate":"2023-07-07T09:56:56","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2604,"text":"Landslides","active":true,"publicationSubtype":{"id":10}},"title":"Postfire hydrologic response along the central California (USA) coast: Insights for the emergency assessment of postfire debris-flow hazards","docAbstract":"The steep, tectonically active terrain along the Central California (USA) coast is well known to produce deadly and destructive debris flows. However, the extent to which fire affects debris-flow susceptibility in this region is an open question. We documented the occurrence of postfire debris floods and flows following the landfall of a storm that delivered intense rainfall across multiple burn areas. We used this inventory to evaluate the predictive performance of the US Geological Survey M1 likelihood model, a tool that presently underlies the emergency assessment of postfire debris-flow hazards in the western USA. To test model performance, we used the threat score skill statistic and found that the rainfall thresholds estimated by the M1 model for the Central California coast performed similarly to training (Southern California) and testing (Intermountain West) data associated with the original model calibration. Model performance decreased when differentiating between “minor” and “major” postfire hydrologic response types, which weigh effects on human life and infrastructure. Our results underscore that the problem of false positives is a major challenge for developing accurate rainfall thresholds for the occurrence of postfire debris flows. As wildfire activity increases throughout the western USA, so too will the demand for the assessment of postfire debris-flow hazards. We conclude that additional collection of field-verified inventories of postfire hydrologic response will be critical to prioritize which model variables may be suitable candidates for regional calibration or replacement.
","language":"English","publisher":"Springer","doi":"10.1007/s10346-023-02106-7","usgsCitation":"Thomas, M.A., Kean, J.W., McCoy, S., Lindsay, D.N., Kostelnik, J., Cavagnaro, D.B., Rengers, F.K., East, A.E., Schwartz, J., Smith, D.P., and Collins, B.D., 2023, Postfire hydrologic response along the central California (USA) coast: Insights for the emergency assessment of postfire debris-flow hazards: Landslides, v. 20, p. 2421-2436, https://doi.org/10.1007/s10346-023-02106-7.","productDescription":"16 p.","startPage":"2421","endPage":"2436","ipdsId":"IP-139528","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":442830,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10346-023-02106-7","text":"Publisher Index Page"},{"id":435262,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91O03Y7","text":"USGS data release","linkHelpText":"Field-verified inventory of postfire hydrologic response for the 2020 CZU Lightning Complex, River, Camel, and Dolan Fires following a 26-29 January 2021 atmospheric river storm sequence"},{"id":418804,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.47368381570269,\n 35.81897449008355\n ],\n [\n -120.78708136085193,\n 36.2836437903476\n ],\n [\n -121.84398626326276,\n 37.24464732874951\n ],\n [\n -122.37243871446816,\n 36.97394608796073\n ],\n [\n -121.47368381570269,\n 35.81897449008355\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"20","noUsgsAuthors":false,"publicationDate":"2023-07-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Thomas, Matthew A. 0000-0002-9828-5539 matthewthomas@usgs.gov","orcid":"https://orcid.org/0000-0002-9828-5539","contributorId":200616,"corporation":false,"usgs":true,"family":"Thomas","given":"Matthew","email":"matthewthomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":877143,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":877144,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCoy, Scott W.","contributorId":267182,"corporation":false,"usgs":false,"family":"McCoy","given":"Scott W.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":877145,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindsay, Donald N.","contributorId":216337,"corporation":false,"usgs":false,"family":"Lindsay","given":"Donald","email":"","middleInitial":"N.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":877146,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kostelnik, Jaime 0000-0002-1817-5461","orcid":"https://orcid.org/0000-0002-1817-5461","contributorId":300717,"corporation":false,"usgs":true,"family":"Kostelnik","given":"Jaime","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":877147,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cavagnaro, David B.","contributorId":267181,"corporation":false,"usgs":false,"family":"Cavagnaro","given":"David","email":"","middleInitial":"B.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":877148,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":877149,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":877150,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schwartz, Jonathan","contributorId":312505,"corporation":false,"usgs":false,"family":"Schwartz","given":"Jonathan","email":"","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":877151,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Smith, Douglas P.","contributorId":201716,"corporation":false,"usgs":false,"family":"Smith","given":"Douglas","email":"","middleInitial":"P.","affiliations":[{"id":35924,"text":"California State University, Monterey Bay","active":true,"usgs":false}],"preferred":false,"id":877152,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Collins, Brian D. 0000-0003-4881-5359 bcollins@usgs.gov","orcid":"https://orcid.org/0000-0003-4881-5359","contributorId":149278,"corporation":false,"usgs":true,"family":"Collins","given":"Brian","email":"bcollins@usgs.gov","middleInitial":"D.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":877153,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70246596,"text":"70246596 - 2023 - Translating stakeholder narratives for participatory modeling in landscape ecology","interactions":[],"lastModifiedDate":"2023-09-06T16:23:41.955537","indexId":"70246596","displayToPublicDate":"2023-07-07T06:57:50","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Translating stakeholder narratives for participatory modeling in landscape ecology","docAbstract":"Engaging stakeholders in research is needed for many of the sustainability challenges that landscape ecologists address. Involving stakeholders’ perspectives through narratives in participatory modeling fosters better understanding of the problem and evaluation of the acceptability of tradeoffs and creates buy-in for management actions. However, stakeholder-driven inputs often take the form of complex qualitative descriptions, rather than model-ready numerical or categorical inputs.
Translating narratives into models, model parameters, or scenarios is essential for leveraging stakeholder knowledge and engagement. Drawing from varied experiences to identify lessons learned and pitfalls, we address the practice of translating narratives into models and using those narratives to interpret and communicate results.
We drew from seven participatory landscape ecology projects across North America to synthesize lessons for the inclusion of stakeholder narratives in modeling studies.
We offer 8 lessons as practical guidance for other landscape ecologists to move the science beyond a unilateral focus on ecological systems and to maximize the benefits of landscape sustainability science.
These lessons are starting points, as real projects are complex, nuanced, and sometimes contradictory. Translating narratives into models is important for addressing complex sustainability challenges; we hope that these starting points are helpful to those foraying into this type of research.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-023-01724-9","usgsCitation":"Vukomanovic, J., Smart, L., Koch, J., Dale, V., Plassin, S., Byrd, K.B., Beier, C., and Doyon, F., 2023, Translating stakeholder narratives for participatory modeling in landscape ecology: Landscape Ecology, v. 38, p. 2453-2474, https://doi.org/10.1007/s10980-023-01724-9.","productDescription":"22 p.","startPage":"2453","endPage":"2474","ipdsId":"IP-136700","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":502612,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://research.wur.nl/en/publications/translating-stakeholder-narratives-for-participatory-modeling-in-","text":"External Repository"},{"id":418854,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","noUsgsAuthors":false,"publicationDate":"2023-07-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Vukomanovic, Jelena","contributorId":316275,"corporation":false,"usgs":false,"family":"Vukomanovic","given":"Jelena","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":877297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smart, Lindsey","contributorId":316276,"corporation":false,"usgs":false,"family":"Smart","given":"Lindsey","affiliations":[{"id":68543,"text":"North Carolina State University, The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":877298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koch, Jennifer","contributorId":316277,"corporation":false,"usgs":false,"family":"Koch","given":"Jennifer","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":877299,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dale, Virginia","contributorId":316278,"corporation":false,"usgs":false,"family":"Dale","given":"Virginia","email":"","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":877300,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Plassin, Sophie","contributorId":316279,"corporation":false,"usgs":false,"family":"Plassin","given":"Sophie","email":"","affiliations":[{"id":34610,"text":"Universite de Toulouse","active":true,"usgs":false}],"preferred":false,"id":877301,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Byrd, Kristin B. 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":3814,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":877302,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Beier, Colin","contributorId":316280,"corporation":false,"usgs":false,"family":"Beier","given":"Colin","affiliations":[{"id":37519,"text":"SUNY College of Environmental Science and Forestry","active":true,"usgs":false}],"preferred":false,"id":877303,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Doyon, Frederik","contributorId":316282,"corporation":false,"usgs":false,"family":"Doyon","given":"Frederik","email":"","affiliations":[{"id":68544,"text":"Institut des sciences de la foret temperee, Universite du Quebec","active":true,"usgs":false}],"preferred":false,"id":877304,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70249249,"text":"70249249 - 2023 - Introduction to the special section on seismoacoustics and seismoacoustic data fusion","interactions":[],"lastModifiedDate":"2023-10-03T11:59:00.224775","indexId":"70249249","displayToPublicDate":"2023-07-07T06:56:48","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Introduction to the special section on seismoacoustics and seismoacoustic data fusion","docAbstract":"A variety of geophysical hazards (e.g., volcanic activity, earthquakes, mass movements, marine storms, bolides) and anthropogenic sources (e.g., chemical and nuclear explosions, mining blasts, rocket launches) can release energy as mechanical waves in the ground, ocean, and atmosphere (Arrowsmith et al., 2010; Campus and Christie, 2009). Due to the mechanical coupling between a planetary body, its ocean, and its atmosphere, waves can propagate across these interfaces (Ben-Menahem and Singh, 1981) and carry information about the source and the media they propagated through. The field of seismoacoustics, driven by geophysical observations of both seismic and low-frequency acoustic (infrasound) waves, has several interdisciplinary applications. Observations of both seismic and infrasonic waves can be used to discriminate between atmospheric and subsurface events, such as sonic booms and earthquakes. Moreover, seismoacoustic analyses can provide useful information for the source characterization of shallow anthropogenic events, such as underground or surface explosions, volcanic, and tectonic events (e.g., Arrowsmith et al., 2020; Assink et al., 2016; de Groot-Hedlin and Hedlin, 2019; Matoza et al., 2009). Similarly, remote observations (e.g., on regional seismic and infrasonic arrays) can help monitor natural events such as volcanic eruptions and provide additional details about eruption dynamics. Recent works additionally suggest that infrasound can be used to discriminate between different volcanic processes (Watson et al., 2022). Finally, looking outwards, the study of seismo-acoustics has been a particularly valuable tool for planetary science (e.g., Krishnamoorthy et al., 2018; Martire et al., 2018; Krishnamoorthy et al., 2019; Martire et al., 2020; Garcia et al., 2020; Brissaud et al., 2021).","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120230049","usgsCitation":"Dannemann Dugick, F.K., Bishop, J.W., Martire, L., Iezzi, A.M., Assink, J.D., Brissaud, Q., and Arrowsmith, S., 2023, Introduction to the special section on seismoacoustics and seismoacoustic data fusion: Bulletin of the Seismological Society of America, v. 113, no. 4, p. 1383-1389, https://doi.org/10.1785/0120230049.","productDescription":"7 p.","startPage":"1383","endPage":"1389","ipdsId":"IP-149117","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":442836,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1992277","text":"External Repository"},{"id":421528,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"113","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-07-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Dannemann Dugick, Fransiska K.","contributorId":330421,"corporation":false,"usgs":false,"family":"Dannemann Dugick","given":"Fransiska","email":"","middleInitial":"K.","affiliations":[{"id":78886,"text":"Sandia National Laboratories, Albuquerque, NM 87110","active":true,"usgs":false}],"preferred":false,"id":884899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bishop, Jordan W.","contributorId":330422,"corporation":false,"usgs":false,"family":"Bishop","given":"Jordan","email":"","middleInitial":"W.","affiliations":[{"id":78887,"text":"Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK, USA","active":true,"usgs":false}],"preferred":false,"id":884900,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martire, Leo 0000-0002-9402-6150","orcid":"https://orcid.org/0000-0002-9402-6150","contributorId":296471,"corporation":false,"usgs":false,"family":"Martire","given":"Leo","email":"","affiliations":[{"id":64057,"text":"NASA Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr, Pasadena, CA 91109","active":true,"usgs":false}],"preferred":false,"id":884901,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Iezzi, Alexandra M. 0000-0002-6782-7681","orcid":"https://orcid.org/0000-0002-6782-7681","contributorId":304206,"corporation":false,"usgs":true,"family":"Iezzi","given":"Alexandra","email":"","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":884902,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Assink, Jelle D.","contributorId":236650,"corporation":false,"usgs":false,"family":"Assink","given":"Jelle","email":"","middleInitial":"D.","affiliations":[{"id":47493,"text":"R and D Seismology and Acoustics, Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3731 GA De Bilt, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":884903,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brissaud, Quentin 0000-0001-8189-4699","orcid":"https://orcid.org/0000-0001-8189-4699","contributorId":296470,"corporation":false,"usgs":false,"family":"Brissaud","given":"Quentin","email":"","affiliations":[{"id":64063,"text":"NORSAR, Kjeller, Norway","active":true,"usgs":false}],"preferred":false,"id":884904,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Arrowsmith, Stephen 0000-0002-9150-0363","orcid":"https://orcid.org/0000-0002-9150-0363","contributorId":296478,"corporation":false,"usgs":false,"family":"Arrowsmith","given":"Stephen","email":"","affiliations":[{"id":64065,"text":"Roy M. Huffington Department of Earth Sciences, Southern Methodist University, Dallas, Texas, U.S.A","active":true,"usgs":false}],"preferred":false,"id":884905,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70246336,"text":"ofr20231027 - 2023 - Atmospheric deposition of inorganic reactive nitrogen at the Rocky Flats National Wildlife Refuge, 2017–19","interactions":[],"lastModifiedDate":"2023-07-07T10:49:17.029975","indexId":"ofr20231027","displayToPublicDate":"2023-07-06T15:55:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1027","displayTitle":"Atmospheric Deposition of Inorganic Reactive Nitrogen at the Rocky Flats National Wildlife Refuge, 2017–19","title":"Atmospheric deposition of inorganic reactive nitrogen at the Rocky Flats National Wildlife Refuge, 2017–19","docAbstract":"The Rocky Flats National Wildlife Refuge (RFNWR) in Colorado is home to increasingly rare, xeric tallgrass prairie. The RFNWR is also located near many combustion and agricultural sources of inorganic reactive nitrogen (Nr), which emit Nr to the atmosphere. Wet atmospheric deposition of Nr was monitored at RFNWR during 2017–19 by the U.S. Geological Survey in cooperation with the U.S. Fish and Wildlife Service. Comparison of measured Nr deposition amounts to critical load values indicated local urban air pollution is at a level that could impair the protected RFNWR habitat.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231027","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Wetherbee, G.A., 2023, Atmospheric deposition of inorganic reactive nitrogen at the Rocky Flats National Wildlife Refuge, 2017–19: U.S. Geological Survey Open-File Report 2023–1027, 1 sheet, available at https://doi.org/10.3133/ofr20231027.","productDescription":"1 Sheet: 40.00 × 30.00 inches; Data Release; Project Site","onlineOnly":"Y","ipdsId":"IP-136270","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":418692,"rank":4,"type":{"id":18,"text":"Project Site"},"url":"https://nadp.slh.wisc.edu/","text":"National Atmospheric Deposition Program"},{"id":418689,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1027/coverthb.jpg"},{"id":418690,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1027/ofr20231027.pdf","text":"Report","size":"1.74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1027"},{"id":418691,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OOIQ0E","text":"USGS data release","linkHelpText":"Chemical analyses and precipitation depth data for wet deposition samples collected as part of the National Atmospheric Deposition Program in the Colorado Front Range, 2017-2019"}],"country":"United States","state":"Colorado","otherGeospatial":"Rocky Flats National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.26103714983329,\n 39.95142757778845\n ],\n [\n -105.26103714983329,\n 39.83241452322963\n ],\n [\n -105.11415803005896,\n 39.83241452322963\n ],\n [\n -105.11415803005896,\n 39.95142757778845\n ],\n [\n -105.26103714983329,\n 39.95142757778845\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Observing Systems Division
Hydrologic Instrumentation Facility
U.S. Geological Survey
Buildings 2101 2204 HIF
Stennis Space Center
Bay St Louis, MS 39529
Using a geology-based assessment methodology, the U.S. Geological Survey estimated a mean of 5.2 trillion cubic feet of coalbed gas in the Vermejo Formation and Raton Formation of the Raton Basin-Sierra Grande Uplift Province.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233020","programNote":"National and Global Petroleum Assessment","usgsCitation":"Schenk, C.J., Finn, T.M., Mercier, T.J., Woodall, C.A., Le, P.A., Cicero, A.D., Drake, R.M., II, Ellis, G.S., Gardner, M.H., Gelman, S.E., Hearon, J.S., Johnson, B.G., Lagesse, J.H., Leathers-Miller, H.M., Marra, K.R., Timm, K.K., and Young, S.S., 2023, Assessment of coalbed gas resources in the Raton Basin-Sierra Grande Uplift Province, Colorado and New Mexico, 2022: U.S. Geological Survey Fact Sheet 2023–3020, 4 p., https://doi.org/10.3133/fs20233020.","productDescription":"Report: 4 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-145278","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":418687,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96I4K6F","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project—Raton Basin-Sierra Grande Uplift Province: Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables"},{"id":418729,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3020/fs20233020.xml"},{"id":418930,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/fs20233020/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2023-3020"},{"id":418685,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3020/coverthb.jpg"},{"id":499685,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114956.htm","linkFileType":{"id":5,"text":"html"}},{"id":418686,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3020/fs20233020.pdf","text":"Report","size":"1.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023-3020"},{"id":418728,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3020/images"}],"country":"United States","state":"Colorado, New Mexico","otherGeospatial":"Raton Basin-Sierra Grande Uplift Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.30,\n 37.40\n ],\n [\n -105.30,\n 36.30\n ],\n [\n -104.00,\n 36.30\n ],\n [\n -104.00,\n 37.40\n ],\n [\n -105.30,\n 37.40\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Wildfire events are becoming more frequent and severe on a global scale. Rising temperatures, prolonged drought, and the presence of pyrophytic invasive grasses are contributing to the degradation of native vegetation communities. Within the Great Basin region of the western U.S., increasing wildfire frequency is transforming the ecosystem toward a higher degree of homogeneity, one dominated by invasive annual grasses and declining landscape productivity. Greater sage-grouse (Centrocercus urophasianus; hereafter sage-grouse) are a species of conservation concern that rely on large tracts of structurally and functionally diverse sagebrush (Artemisia spp.) communities. Using a 12-year (2008–2019) telemetry dataset, we documented immediate impacts of wildfire on demographic rates of a population of sage-grouse that were exposed to two large wildfire events (Virginia Mountains Fire Complex—2016; Long Valley Fire—2017) near the border of California and Nevada. Spatiotemporal heterogeneity in demographic rates were accounted for using a Before-After Control-Impact Paired Series (BACIPS) study design. Results revealed a 40% reduction in adult survival and a 79% reduction in nest survival within areas impacted by wildfires. Our results indicate that wildfire has strong and immediate impacts to two key life stages of a sagebrush indicator species and underscores the importance of fire suppression and immediate restoration following wildfire events.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-023-32937-2","usgsCitation":"Tyrrell, E.A., Coates, P.S., Prochazka, B.G., Brussee, B.E., Espinosa, S.P., and Hull, J.M., 2023, Wildfire immediately reduces nest and adult survival of greater sage-grouse: Scientific Reports, v. 13, 10970, 12 p., https://doi.org/10.1038/s41598-023-32937-2.","productDescription":"10970, 12 p.","ipdsId":"IP-146503","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":442838,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-023-32937-2","text":"Publisher Index Page"},{"id":435263,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WA2M2Y","text":"USGS data release","linkHelpText":"Greater Sage-Grouse Adult and Nest Observations Before and After Wildfire in Northwest Nevada (2008-2019)"},{"id":418807,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.05463957331938,\n 40.372305246838636\n ],\n [\n -120.02911844443898,\n 40.02532619716558\n ],\n [\n -119.87905420662038,\n 39.93067219828927\n ],\n [\n -119.64119728545204,\n 39.97214835081692\n ],\n [\n -119.66671841433293,\n 40.07455694499603\n ],\n [\n -119.77696969109726,\n 40.26645064715103\n ],\n [\n -119.96072181903847,\n 40.3777491537939\n ],\n [\n -120.05463957331938,\n 40.372305246838636\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2023-07-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Tyrrell, Emily A 0000-0002-9937-9713","orcid":"https://orcid.org/0000-0002-9937-9713","contributorId":306167,"corporation":false,"usgs":false,"family":"Tyrrell","given":"Emily","email":"","middleInitial":"A","affiliations":[{"id":66381,"text":"previously Western Ecological Research Center","active":true,"usgs":false}],"preferred":false,"id":877215,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":877216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":174839,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":877217,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brussee, Brianne E. 0000-0002-2452-7101 bbrussee@usgs.gov","orcid":"https://orcid.org/0000-0002-2452-7101","contributorId":4249,"corporation":false,"usgs":true,"family":"Brussee","given":"Brianne","email":"bbrussee@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":877218,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Espinosa, Shawn P.","contributorId":195583,"corporation":false,"usgs":false,"family":"Espinosa","given":"Shawn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":877219,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hull, Joshua M.","contributorId":127686,"corporation":false,"usgs":false,"family":"Hull","given":"Joshua","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":877220,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70246650,"text":"70246650 - 2023 - Changes in abiotic drivers of green sea urchin demographics following the loss of a keystone predator","interactions":[],"lastModifiedDate":"2023-07-12T15:00:47.316627","indexId":"70246650","displayToPublicDate":"2023-07-06T09:47:22","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16299,"text":"Journal of Marine Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Changes in abiotic drivers of green sea urchin demographics following the loss of a keystone predator","docAbstract":"Sea urchin population demographics can respond to changes in keystone species abundances, with the magnitude of these responses varying depending on environmental influences. In this study, sea urchin populations were surveyed across 15 Aleutian archipelago islands over a 30-year period to understand how patterns of sea urchin demography (density, biomass, and size structure) varied through different ecological regimes that were caused by changes in the abundance of sea otters, a keystone species in this system. To examine long-term changes in sea urchin demographics, four time periods across the recent decline of sea otters were examined: during sea otter presence (1987-1994), nearing absence at the end of the decline (1997-2000), 10 years postdecline (2008-2010), and 15-20 years following the loss of sea otters from the ecosystem (2014-2017). Our results show that when sea otters were broadly present, sea urchin demographics were generally similar across the archipelago, with few urchins that had large-sized bodies. During this time, bottom-up environmental controls were muted relative to top-down forces from keystone predation. However, as sea otters declined and remained absent from the system, abiotic factors became more influential on sea urchin biomass, density, and size structure. In particular, differences among island groups during these periods were correlated with variation in ocean temperature, bathymetric complexity, and habitat availability. Sea urchin recruitment also varied among island groups, corresponding to ecoregions delineated by oceanic passes across the archipelago. The functional extinction of sea otters revealed an increasing influence of abiotic forcing in the absence of top-down control. This study further highlights the importance of understanding how keystone predators regulate herbivore demographics.
","language":"English","publisher":"Hindawi","doi":"10.1155/2023/1198953","usgsCitation":"Weitzman, B., Konar, B., Edwards, M.S., Rasher, D., Kenner, M.C., Tinker, M.T., and Estes, J., 2023, Changes in abiotic drivers of green sea urchin demographics following the loss of a keystone predator: Journal of Marine Sciences, v. 2023, 1198953, 18 p., https://doi.org/10.1155/2023/1198953.","productDescription":"1198953, 18 p.","ipdsId":"IP-110692","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":442841,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1155/2023/1198953","text":"Publisher Index Page"},{"id":418898,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Aleutian archipelago","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -165.28604507308413,\n 54\n ],\n [\n -179.9,\n 54\n ],\n [\n -179.9,\n 47.0490457932118\n ],\n [\n -165.28604507308413,\n 47.0490457932118\n ],\n [\n -165.28604507308413,\n 54\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 167,\n 54\n ],\n [\n 167,\n 47.07788267220468\n ],\n [\n 179.9,\n 47.07788267220468\n ],\n [\n 179.9,\n 54\n ],\n [\n 167,\n 54\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2023","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Weitzman, Ben P. 0000-0001-7559-3654 bweitzman@usgs.gov","orcid":"https://orcid.org/0000-0001-7559-3654","contributorId":5123,"corporation":false,"usgs":true,"family":"Weitzman","given":"Ben P.","email":"bweitzman@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":877757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Konar, B.","contributorId":93658,"corporation":false,"usgs":true,"family":"Konar","given":"B.","email":"","affiliations":[],"preferred":false,"id":877758,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edwards, M. S.","contributorId":316595,"corporation":false,"usgs":false,"family":"Edwards","given":"M.","email":"","middleInitial":"S.","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":877797,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rasher, D. B.","contributorId":316596,"corporation":false,"usgs":false,"family":"Rasher","given":"D. B.","affiliations":[{"id":13692,"text":"Bigelow Laboratory for Ocean Sciences","active":true,"usgs":false}],"preferred":false,"id":877798,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kenner, Michael C. 0000-0003-4659-461X","orcid":"https://orcid.org/0000-0003-4659-461X","contributorId":208151,"corporation":false,"usgs":true,"family":"Kenner","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":877760,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tinker, M. T. 0000-0002-3314-839X","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":54152,"corporation":false,"usgs":false,"family":"Tinker","given":"M.","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":877761,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Estes, J. A.","contributorId":316594,"corporation":false,"usgs":false,"family":"Estes","given":"J. A.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":877759,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70246616,"text":"70246616 - 2023 - A detailed view of the 2020-2023 southwestern Puerto Rico seismic sequence with deep learning","interactions":[],"lastModifiedDate":"2023-12-04T16:59:36.832347","indexId":"70246616","displayToPublicDate":"2023-07-06T08:36:24","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"A detailed view of the 2020-2023 southwestern Puerto Rico seismic sequence with deep learning","docAbstract":"The 2020–2023 southwestern Puerto Rico seismic sequence, still ongoing in 2023, is remarkable for its multiple‐fault rupture complexity and elevated aftershock productivity. We applied an automatic workflow to continuous data from 43 seismic stations in Puerto Rico to build an enhanced earthquake catalog with ∼180,000 events for the 3+ yr sequence from 28 December 2019 to 1 January 2023. This workflow contained the EQTransformer (EQT) deep learning model for event detection and phase picking, the EikoNet‐Hypocenter Inversion with Stein Variational Inference probabilistic earthquake location approach with a neural network trained to solve the eikonal wave equation, and relocation with event‐pair waveform cross correlation. EQT increased the number of catalog events in the sequence by about seven times, though its performance was not quite as good as thorough analyst review. The enhanced catalog revealed new structural details of the sequence space–time evolution, including sudden changes in activity, on a complex system of many small normal and strike‐slip faults. This sequence started on 28 December 2019 with an M 4.7 strike‐slip earthquake followed by 10 days of shallow strike‐slip foreshocks, including several M 5+ earthquakes, in a compact region. The oblique normal fault
Faults are important controls on hydrothermal circulation worldwide. More specifically, structural discontinuities, i.e. locations where faults interact and intersect, host many hydrothermal systems. In the Great Basin, western USA, an extensive characterization effort demonstrated that hydrothermal systems are controlled by one (or more) of eight types of structural discontinuities. Presumably, specific attributes of these structural settings control the generation and maintenance of permeability and porosity, and therefore localize hydrothermal processes. Herein, I examine representative examples of the eight structural settings that host hydrothermal systems in the Great Basin. For each setting, I use a boundary element method to model fault slip on the major faults and track the distribution of stress and strain in the surrounding crust. Results demonstrate that the largest magnitude and most localized stress and strain effects occur in the structural settings that host the largest number of hydrothermal systems; fault stepovers and fault terminations. Structural settings that are common in areas of strike-slip faulting also show localized stress and strain effects. The modelling presented provides process-based explanations for the empirical and conceptual results of regional characterization of Great Basin hydrothermal systems.
","language":"English","publisher":"Geological Society of London","doi":"10.1144/geoenergy2023-009","usgsCitation":"Siler, D.L., 2023, Structural discontinuities and their control on hydrothermal systems in the Great Basin, USA: Geoenergy, v. 1, no. 1, 10 p., https://doi.org/10.1144/geoenergy2023-009.","productDescription":"10 p.","ipdsId":"IP-146721","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":442846,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1144/geoenergy2023-009","text":"Publisher Index Page"},{"id":435264,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9S73O5C","text":"USGS data release","linkHelpText":"Stress transfer modeling of Great Basin, USA structural discontinuities; Data and MATLAB functions (ver. 1.1, June 2023)"},{"id":418922,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.971198043698,\n 43.70678410718071\n ],\n [\n -120.971198043698,\n 33.361880330157675\n ],\n [\n -107.7054053941411,\n 33.361880330157675\n ],\n [\n -107.7054053941411,\n 43.70678410718071\n ],\n [\n -120.971198043698,\n 43.70678410718071\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"1","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-07-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Siler, Drew L. 0000-0001-7540-8244","orcid":"https://orcid.org/0000-0001-7540-8244","contributorId":203341,"corporation":false,"usgs":true,"family":"Siler","given":"Drew","email":"","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":877837,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}