Relative Sea Levels (RSLs) derived primarily from marine bivalves near Petermann Glacier, NW Greenland, constrain past regional ice-mass changes through glacial isostatic adjustment (GIA) modeling. Oxygen isotopes measured on bivalves corrected for shell-depth habitat and document changing meltwater input. Rapid RSL fall of up to 62 m/kyr indicates ice loss at or prior to ∼9 ka. Transition to an RSL stillstand starting at ∼6 ka reflects renewed ice-mass loading followed by further mass loss over the past few millennia. GIA simulations of rapid early RSL fall suggest a low regional upper-mantle viscosity. Early loss of grounded ice tracks atmospheric warming and pre-dates the eventual collapse of Petermann Glacier's floating ice tongue near ∼7 ka, suggesting grounding zone stabilization during early phases of deglaciation. We hypothesize mid-Holocene regrowth of regional ice caps in response to cooling and increased precipitation, following loss of the floating shelf ice. Remnants of these ice caps remain present but are now melting.
As North America collided with Africa to form Pangea during the Alleghanian orogeny, crystalline and sedimentary rocks in the southeastern United States were thrust forelandward along the Appalachian décollement. We examined Ps receiver functions to better constrain the kinematics of this prominent subsurface structure. From Southeastern Suture of the Appalachian Margin Experiment (SESAME) and other EarthScope stations on the Blue Ridge–Piedmont crystalline megathrust, we find large arrivals from a 5–10-km-deep converter. We argue that a strong contrast in dipping anisotropic foliation occurs at the subhorizontal Appalachian décollement, and propose that such a geometry may be typical for décollement structures. Conversion polarity flips can be explained by an east-dipping foliation, but this orientation is at odds with the overlying northeast-trending surface tectonic grain. We suggest that prior to late Alleghanian northwest-directed head-on collision, the Appalachian décollement accommodated early Alleghanian west-vergence, independent of the overlying Blue Ridge–Piedmont structural inheritance. The geophysical expression of dipping anisotropic foliation provides a powerful tool for investigating subsurface kinematics, especially where they are obscured by overlying fabric, to disentangle the tectonic complexities that embody oblique collisional orogens.
Coyotes (Canis latrans) are expanding their range and due to conflicts with the public and concerns of Coyotes affecting natural resources such as game or sensitive species, there is interest and often a demand to monitor Coyote populations. A challenge to monitoring is that traditional invasive methods involving live-capture of individual animals are costly and can be controversial. Natural resource management agencies can benefit from contemporary noninvasive genetic sampling approaches aimed at determining key aspects of Coyote ecology (e.g., population density and food habits). However, the efficacy of such approaches under different environmental conditions is poorly understood. Our objectives were to 1) examine accumulation and nuclear DNA degradation rates of Coyote scats in metropolitan and rural sites in Florida to help optimize methods to estimate population density; and 2) explore new genetic methods for determining diet of Coyotes based on vertebrate, plant, and invertebrate species DNA identified in scat. Recently developed DNA metabarcoding approaches make it possible to simultaneously identify DNA from multiple prey species in predator scat samples, but an exploration of this tool for assessing Coyote diet has not been pursued. We observed that scat accumulation rates (0.02 scats/km/day) did not vary between sites and fecal DNA amplification success decreased and genotyping errors increased over time with exposure to sun and precipitation. DNA sampling allowed us to generate a Coyote density estimate for the urban environment of eight Coyotes per 100 km2, but lack of recaptures in the rural area precluded density estimation. DNA metabarcoding showed promise for assessing diet contributions of vertebrate species to Coyote diet. Feral Swine (Sus scrofa) were detected as prey at higher frequencies than previously reported. We identify several considerations that can be used to optimize future noninvasive sampling efforts for Coyotes in the southeastern United States. We also discuss strengths and drawbacks of utilizing DNA metabarcoding for assessing diet of generalist carnivores such as Coyotes.
Ground deformation during caldera collapse at Kīlauea Volcano in 2018 was recorded in unprecedented detail on a network of real-time GNSS (Global Navigation Satellite System) and tilt instruments. Observations informed hazard assessments during the eruption and now yield insight into collapse dynamics and the magma system. The caldera grew in size over 78 days in a series of repeating, quasi-periodic
Double-crested cormorants (Nannopterum auritum) have been implicated as causes of fish population declines in many locations across their breeding range. Two challenges facing managers are identifying fisheries population metrics indicative of cormorant impacts and determining when this evidence becomes actionable. Building upon existing studies, we conducted a meta-analysis of eight data-rich systems across the Laurentian Great Lakes region of the United States for common fish population responses to changes in cormorant abundance. Specifically, we examined trends in mean total female length at age-3 (TL3), female mean length and age at 50 % maturity, and mean age evenness as indicated by Shannon’s Equitability Index. Annual observations for these metrics were independently regressed linearly against cormorant density by system for walleye (Sander vitreus), yellow perch (Perca flavescens), smallmouth bass (Micropterus dolomieu), and northern pike (Esox lucius) populations. TL3 was the most sensitive with 9 of the 14 datasets statistically significant (r2 range 0.29 to 0.86). Maturity metrics were moderately sensitive to trends in cormorant predation with mean total length at 50 % maturity significant in 4 out of 11 datasets (r2 range 0.27–0.41) and mean age at 50 % maturity significant in 3 out of 11 datasets (r2 range 0.12 – 0.51). Least sensitive was age evenness with the Shannon Index significant in 3 out of 12 datasets (r2 typically < 0.25). Of metrics tested, TL3 was the most reliable indicator of changes in cormorant effects despite varying system changes and management responses among locations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2022.08.022","usgsCitation":"Schultz, D.W., Dorr, B.S., Fielder, D.G., Jackson, J.R., and DeBruyne, R.L., 2022, Indicators of fish population responses to avian predation with focus on double-crested cormorants: Journal of Great Lakes Research, v. 48, no. 6, p. 1659-1668, https://doi.org/10.1016/j.jglr.2022.08.022.","productDescription":"10 p.","startPage":"1659","endPage":"1668","ipdsId":"IP-140185","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":467164,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2022.08.022","text":"Publisher Index Page"},{"id":406437,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Minnesota, New York","otherGeospatial":"Bays de Noc, East Lake Ontario, East Vermillion Lake, Lake Oneida, Leech Lake, Les Cheneaux Islands, Green Bay, Saginaw Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.68841552734374,\n 46.922131240914\n ],\n [\n -94.06768798828122,\n 46.922131240914\n ],\n [\n -94.06768798828122,\n 47.37045451569322\n ],\n [\n -94.68841552734374,\n 47.37045451569322\n ],\n [\n -94.68841552734374,\n 46.922131240914\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.74658203125,\n 47.75779097897638\n ],\n [\n -92.120361328125,\n 47.75779097897638\n ],\n [\n -92.120361328125,\n 48.085418575511966\n ],\n [\n -92.74658203125,\n 48.085418575511966\n ],\n [\n -92.74658203125,\n 47.75779097897638\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n 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Center","active":true,"usgs":false}],"preferred":false,"id":851265,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fielder, David G.","contributorId":127535,"corporation":false,"usgs":false,"family":"Fielder","given":"David","email":"","middleInitial":"G.","affiliations":[{"id":7024,"text":"Michigan Department of Natural Resources, Fisheries Research Station","active":true,"usgs":false}],"preferred":false,"id":851266,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, James R.","contributorId":55709,"corporation":false,"usgs":false,"family":"Jackson","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":851267,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeBruyne, Robin L. 0000-0002-9232-7937 rdebruyne@usgs.gov","orcid":"https://orcid.org/0000-0002-9232-7937","contributorId":4936,"corporation":false,"usgs":true,"family":"DeBruyne","given":"Robin","email":"rdebruyne@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":851268,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70236899,"text":"70236899 - 2022 - Measured efficacy, bioaccumulation, and leaching of a transfluthrin-based insecticidal paint: A case study with a nuisance, nonbiting aquatic insect","interactions":[],"lastModifiedDate":"2022-12-01T16:10:07.961907","indexId":"70236899","displayToPublicDate":"2022-09-03T06:40:36","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3035,"text":"Pest Management Science","active":true,"publicationSubtype":{"id":10}},"title":"Measured efficacy, bioaccumulation, and leaching of a transfluthrin-based insecticidal paint: A case study with a nuisance, nonbiting aquatic insect","docAbstract":"Pest management professionals will require a diverse, adaptive abatement toolbox to combat advanced challenges from disease vector and nuisance insect populations. Designed for post-application longevity, insecticidal paints offer extended residual effects on targeted insect pest populations; a measured understanding of active ingredient bioavailability over time is valuable to fully assess treatment efficacy and potential environmental risks. This study was initiated because a nuisance net-spinning caddisfly, Smicridea fasciatella, is lowering the quality of life for riverfront residents at the type locality.
We tested the efficacy and potential mobility of a transfluthrin-based paint (a.i. 0.50%), comparing the impacts of UV exposure and substrate texture over time. Direct UV exposure decreased efficacy (β ± S.E. = 0.008 ± 0.001, P < 0.001) and a coarse texture maintained greater efficacy (β ± S.E. = −3.7 ± 1.3, P = 0.004) over time. Notably, the coarse texture + indirect UV treatment maintained 100% mortality after 240 days. UV exposure and substrate texture did not have a significant impact on leachate concentrations over time, and successive immersion tests indicated a two-phase emission pattern. Bioaccumulation increased with time on the cuticle of dead adult S. fasciatella; after 24 h of direct exposure the concentration of transfluthrin was 25.3 ± 0.9 ng/caddisfly with a maximum concentration of 345 ng/caddisfly after 7 days.
Our predictions were validated with measured, time-dependent impacts on efficacy, leachability, and bioaccumulation. Because of the mobility of active ingredient in the environment, insecticidal paints merit low-impact protocols to improve public health outcomes and environmental safety. © 2022 Society of Chemical Industry.
","language":"English","publisher":"Wiley","doi":"10.1002/ps.7163","usgsCitation":"Cavallaro, M.C., Sanders, C., and Hladik, M.L., 2022, Measured efficacy, bioaccumulation, and leaching of a transfluthrin-based insecticidal paint: A case study with a nuisance, nonbiting aquatic insect: Pest Management Science, v. 78, no. 12, p. 5413-5422, https://doi.org/10.1002/ps.7163.","productDescription":"10 p.","startPage":"5413","endPage":"5422","ipdsId":"IP-142496","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":407124,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"78","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-09-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Cavallaro, Michael C.","contributorId":296789,"corporation":false,"usgs":false,"family":"Cavallaro","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":64177,"text":"Bullhead City Pest Abatement District","active":true,"usgs":false}],"preferred":false,"id":852487,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sanders, Corey 0000-0001-7743-6396","orcid":"https://orcid.org/0000-0001-7743-6396","contributorId":204711,"corporation":false,"usgs":true,"family":"Sanders","given":"Corey","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":852488,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":203857,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":852489,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70236294,"text":"fs20223048 - 2022 - Assessment of undiscovered conventional oil and gas resources of the Montana Thrust Belt Province, 2021","interactions":[],"lastModifiedDate":"2026-03-25T16:19:06.54123","indexId":"fs20223048","displayToPublicDate":"2022-09-02T11:50:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3048","displayTitle":"Assessment of Undiscovered Conventional Oil and Gas Resources of the Montana Thrust Belt Province, 2021","title":"Assessment of undiscovered conventional oil and gas resources of the Montana Thrust Belt Province, 2021","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated means of 783 million barrels of conventional oil and 17,606 billion (17.6 trillion) cubic feet of conventional gas in the Montana Thrust Belt Province.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223048","usgsCitation":"Schenk, C.J., Mercier, T.J., Woodall, C.A., Le, P.A., Cicero, A.D., Drake, R.M., II., Ellis, G.S., Finn, T.M., 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., 2022, Assessment of undiscovered conventional oil and gas resources of the Montana Thrust Belt Province, 2021: U.S. Geological Survey Fact Sheet 2022−3048, 2 p., https://doi.org/10.3133/fs20223048.","productDescription":"2 p.","onlineOnly":"Y","ipdsId":"IP-132654","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":406005,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J6IUZ2","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project-Montana Thrust Belt Province: Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables"},{"id":406004,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3048/fs20223048.pdf","text":"Report","size":"9.42 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3048"},{"id":406003,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3048/coverthb.jpg"},{"id":501505,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113430.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Montana","otherGeospatial":"Cordilleran orogenic belt, Montana Thrust Belt Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.411376953125,\n 48.97300592158682\n ],\n [\n -114.927978515625,\n 48.64016871811908\n ],\n [\n -115.059814453125,\n 48.40003249610685\n ],\n [\n -115.24658203125,\n 48.158757304569235\n ],\n [\n -115.213623046875,\n 47.85740289465826\n ],\n [\n -115.02685546875,\n 47.52461999690651\n ],\n [\n -114.71923828124999,\n 47.24194882163242\n ],\n [\n -114.36767578124999,\n 47.025206001585396\n ],\n [\n -114.136962890625,\n 46.77749276376827\n ],\n [\n -114.224853515625,\n 46.483264729155586\n ],\n [\n -114.2578125,\n 46.23305294479828\n ],\n [\n -114.169921875,\n 45.97406038956237\n ],\n [\n -113.917236328125,\n 45.744526980468436\n ],\n [\n -113.6865234375,\n 45.521743896993634\n ],\n [\n -113.44482421875,\n 45.166547157856016\n ],\n [\n -113.104248046875,\n 44.84029065139799\n ],\n [\n -112.774658203125,\n 44.574817404670306\n ],\n [\n -112.54394531249999,\n 44.457309801319305\n ],\n [\n -111.73095703125,\n 44.55916341529182\n ],\n [\n -111.456298828125,\n 44.59829048984011\n ],\n [\n -110.93994140625,\n 45.07352060670971\n ],\n [\n -110.401611328125,\n 45.56021795715051\n ],\n [\n -110.203857421875,\n 46.14178273759234\n ],\n [\n -110.401611328125,\n 46.50595444552049\n ],\n [\n -111.11572265625,\n 46.77749276376827\n ],\n [\n -111.357421875,\n 47.07760411715964\n ],\n [\n -112.30224609374999,\n 47.286681888764214\n ],\n [\n -112.576904296875,\n 47.517200697839414\n ],\n [\n -112.54394531249999,\n 48.011975126709956\n ],\n [\n -112.928466796875,\n 48.32703913063476\n ],\n [\n -113.170166015625,\n 48.46563710044979\n ],\n [\n -113.466796875,\n 49.001843917978526\n ],\n [\n -115.411376953125,\n 48.97300592158682\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
The Deepwater Horizon (DWH) disaster released 3.19 million barrels of crude oil into the Gulf of Mexico (GOM) in 2010, overlapping the habitat of pelagic fish populations. Using mahi-mahi (Coryphaena hippurus)─a highly migratory marine teleost present in the GOM during the spill─as a model species, laboratory experiments demonstrate injuries to physiology and behavior following oil exposure. However, more than a decade postspill, impacts on wild populations remain unknown. To address this gap, we exposed wild mahi-mahi to crude oil or control conditions onboard a research vessel, collected fin clip samples, and tagged them with electronic tags prior to release into the GOM. We demonstrate profound effects on survival and reproduction in the wild. In addition to significant changes in gene expression profiles and predation mortality, we documented altered acceleration and habitat use in the first 8 days oil-exposed individuals were at liberty as well as a cessation of apparent spawning activity for at least 37 days. These data reveal that even a brief and low-dose exposure to crude oil impairs fitness in wild mahi-mahi. These findings offer new perspectives on the lasting impacts of the DWH blowout and provide insight about the impacts of future deep-sea oil spills.
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change studies in Hawai'i","docAbstract":"Gridded bioclimatic variables representing yearly, seasonal, and monthly means and extremes in temperature and precipitation have been widely used for ecological modeling purposes and in broader climate change impact and biogeographical studies. As a result of their utility, numerous sets of bioclimatic variables have been developed on a global scale (e.g., WorldClim) but rarely represent the finer regional scale pattern of climate in Hawai'i. Recognizing the value of having such regionally downscaled products, we integrated more detailed projections from recent climate models developed for Hawai'i with current climatological datasets to generate updated regionally defined bioclimatic variables. We derived updated bioclimatic variables from new projections of baseline and future monthly minimum, mean, and maximum temperature (Tmin, Tmean, Tmax) and mean precipitation (Pmean) data at 250 m resolution. We used the most up-to-date dynamically downscaled projections based on the Weather Research and Forecasting (WRF) model from the International Pacific Research Center (IPRC) and the National Center for Atmospheric Research (NCAR). We summarized the monthly data from these two climate projections into a suite of 19 standard bioclimatic variables that provide detailed information about annual and seasonal mean climatic conditions for the Hawaiian Islands. These bioclimatic variables are available for three climate scenarios: baseline climate (1990-2009) and future climate (2080-2099) under representative concentration pathway (RCP) 4.5 (IPRC projections only) and RCP 8.5 (both IPRC and NCAR projections) climate scenarios. The resulting dataset provides a more robust set of climate products that can be used for modeling purposes, impact studies, and management planning.
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\"}}]}","volume":"45","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fortini, Lucas Berio 0000-0002-5781-7295","orcid":"https://orcid.org/0000-0002-5781-7295","contributorId":236984,"corporation":false,"usgs":true,"family":"Fortini","given":"Lucas Berio","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":862133,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaiser, Lauren R.","contributorId":200422,"corporation":false,"usgs":false,"family":"Kaiser","given":"Lauren","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":862134,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Xue, Lulin","contributorId":301129,"corporation":false,"usgs":false,"family":"Xue","given":"Lulin","email":"","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":862135,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wang, Yaping","contributorId":191943,"corporation":false,"usgs":false,"family":"Wang","given":"Yaping","email":"","affiliations":[],"preferred":false,"id":862136,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70236194,"text":"sir20225080 - 2022 - Water-level and recoverable water in storage changes, High Plains aquifer, predevelopment to 2017 and 2015–17","interactions":[],"lastModifiedDate":"2026-04-23T17:18:29.713864","indexId":"sir20225080","displayToPublicDate":"2022-09-02T07:50:04","publicationYear":"2022","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":"2022-5080","displayTitle":"Water-Level and Recoverable Water in Storage Changes, High Plains Aquifer, Predevelopment to 2017 and 2015–17","title":"Water-level and recoverable water in storage changes, High Plains aquifer, predevelopment to 2017 and 2015–17","docAbstract":"The High Plains aquifer underlies 111.8 million acres (about 175,000 square miles) in parts of eight States—Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming. Water-level declines began in parts of the High Plains aquifer soon after the beginning of substantial groundwater irrigation (about 1950). This report presents water-level changes and change in recoverable water in storage in the High Plains aquifer from predevelopment (about 1950) to 2017 and from 2015 to 2017.
Water-level changes from predevelopment to 2017, by well, ranged from a rise of 84 feet to a decline of 262 feet; the range for 99 percent of the wells was from a rise of 39 feet to a decline of 200 feet. Water-level changes from 2015 to 2017, by well, ranged from a rise of 41 feet to a decline of 21 feet; the range for 99 percent of the wells was from a rise of 14 feet to a decline of 10 feet. The area-weighted, average water-level changes in the aquifer were an overall decline of 16.8 feet from predevelopment to 2017 and a rise of 0.1 foot from 2015 to 2017. Total recoverable water in storage in the aquifer in 2017 was about 2.91 billion acre-feet, which was a decline of about 291.8 million acre-feet since predevelopment and a rise of 0.1 million acre-feet from 2015 to 2017.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225080","programNote":"Groundwater and Streamflow Information Program","usgsCitation":"McGuire, V.L., and Strauch, K.R., 2022, Water-level and recoverable water in storage changes, High Plains aquifer, predevelopment to 2017 and 2015–17: U.S. Geological Survey Scientific Investigations Report 2022–5080, 15 p., https://doi.org/10.3133/sir20225080.","productDescription":"Report: vi, 15 p.; Data Release; Dataset","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-106333","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":503400,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113429.htm","linkFileType":{"id":5,"text":"html"}},{"id":405916,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YN7PY3","text":"USGS data release","linkHelpText":"Data from maps of water-level changes in the High Plains aquifer in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming, predevelopment (about 1950) to 2017 and 2015–17"},{"id":405915,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":405914,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5080/images"},{"id":405913,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5080/sir20225080.XML"},{"id":405912,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5080/sir20225080.pdf","text":"Report","size":"5.31 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5080"},{"id":405911,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5080/coverthb.jpg"}],"country":"United States","state":"Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, Wyoming","otherGeospatial":"High Plains aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.4912109375,\n 33.32134852669881\n ],\n [\n -102.216796875,\n 32.24997445586331\n ],\n [\n -100.45898437499999,\n 34.52466147177172\n ],\n [\n -99.6240234375,\n 36.06686213257888\n ],\n [\n -99.6240234375,\n 38.09998264736481\n ],\n [\n -97.20703125,\n 40.74725696280421\n ],\n [\n -97.119140625,\n 42.293564192170095\n ],\n [\n -98.9208984375,\n 42.87596410238256\n ],\n [\n -101.7333984375,\n 43.77109381775651\n ],\n [\n -103.22753906249999,\n 42.90816007196054\n ],\n [\n -105.0732421875,\n 42.52069952914966\n ],\n [\n -105.908203125,\n 42.293564192170095\n ],\n [\n -105.8203125,\n 41.07935114946899\n ],\n [\n -104.150390625,\n 40.97989806962013\n ],\n [\n -104.7216796875,\n 39.50404070558415\n ],\n [\n -104.67773437499999,\n 38.30718056188316\n ],\n [\n -103.1396484375,\n 38.20365531807149\n ],\n [\n -103.974609375,\n 37.23032838760387\n ],\n [\n -103.88671875,\n 35.496456056584165\n ],\n [\n -104.1064453125,\n 34.95799531086792\n ],\n [\n -103.4912109375,\n 33.32134852669881\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
In 2020, the Appropriations Committee for the U.S. House of Representatives directed the CDC to develop a national One Health framework to combat zoonotic diseases, including sylvatic plague, which is caused by the flea-borne bacterium Yersinia pestis. This review builds upon that multisectoral objective. We aim to increase awareness of Y. pestis and to highlight examples of plague mitigation for One Health purposes (i.e., to achieve optimal health outcomes for people, animals, plants, and their shared environment). We draw primarily upon examples from the USA, but also discuss research from Madagascar and Uganda where relevant, as Y. pestis has emerged as a zoonotic threat in those foci.
Historically, the bulk of plague research has been directed at the disease in humans. This is not surprising, given that Y. pestis is a scourge of human history. Nevertheless, the ecology of Y. pestis is inextricably linked to other mammals and fleas under natural conditions. Accumulating evidence demonstrates Y. pestis is an unrelenting threat to multiple ecosystems, where the bacterium is capable of significantly reducing native species abundance and diversity while altering competitive and trophic relationships, food web connections, and nutrient cycles. In doing so, Y. pestis transforms ecosystems, causing “shifting baselines syndrome” in humans, where there is a gradual shift in the accepted norms for the condition of the natural environment. Eradication of Y. pestis in nature is difficult to impossible, but effective mitigation is achievable; we discuss flea vector control and One Health implications in this context.
There is an acute need to rapidly expand research on Y. pestis, across multiple host and flea species and varied ecosystems of the Western US and abroad, for human and environmental health purposes. The fate of many wildlife species hangs in the balance, and the implications for humans are profound in some regions. Collaborative multisectoral research is needed to define the scope of the problem in each epidemiological context and to identify, refine, and implement appropriate and effective mitigation practices.
","language":"English","publisher":"Springer","doi":"10.1007/s40475-022-00265-6","usgsCitation":"Eads, D.A., Biggins, D.E., Wimsatt, J., Eisen, R., Hinnebusch, B.J., Matchett, M.R., Goldberg, A., Livieri, T., Hacker, G., Novak, M., Buttke, D., Grassel, S.M., Hughes-Clarke, J., and Atiku, L., 2022, Exploring and mitigating plague for One Health purposes: Current Tropical Medicine Reports, v. 9, p. 169-184, https://doi.org/10.1007/s40475-022-00265-6.","productDescription":"16 p.","startPage":"169","endPage":"184","ipdsId":"IP-136407","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":446558,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11358858","text":"External Repository"},{"id":406299,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationDate":"2022-09-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Eads, David A. 0000-0002-4247-017X deads@usgs.gov","orcid":"https://orcid.org/0000-0002-4247-017X","contributorId":173639,"corporation":false,"usgs":true,"family":"Eads","given":"David","email":"deads@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":851035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Biggins, Dean E. 0000-0003-2078-671X bigginsd@usgs.gov","orcid":"https://orcid.org/0000-0003-2078-671X","contributorId":2522,"corporation":false,"usgs":true,"family":"Biggins","given":"Dean","email":"bigginsd@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":851036,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wimsatt, Jeffrey","contributorId":173421,"corporation":false,"usgs":false,"family":"Wimsatt","given":"Jeffrey","email":"","affiliations":[],"preferred":false,"id":851037,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eisen, Rebecca J.","contributorId":148027,"corporation":false,"usgs":false,"family":"Eisen","given":"Rebecca J.","affiliations":[{"id":16974,"text":"US Centers for Disease Control and Prevention (CDC)","active":true,"usgs":false}],"preferred":false,"id":851038,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hinnebusch, B. Joseph","contributorId":295326,"corporation":false,"usgs":false,"family":"Hinnebusch","given":"B.","email":"","middleInitial":"Joseph","affiliations":[{"id":13450,"text":"NIH","active":true,"usgs":false}],"preferred":false,"id":851039,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Matchett, Marc R.","contributorId":193409,"corporation":false,"usgs":false,"family":"Matchett","given":"Marc","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":851040,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Goldberg, Amanda R.","contributorId":288043,"corporation":false,"usgs":false,"family":"Goldberg","given":"Amanda R.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":851041,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Livieri, Travis M.","contributorId":279912,"corporation":false,"usgs":false,"family":"Livieri","given":"Travis","middleInitial":"M.","affiliations":[{"id":6753,"text":"Prairie Wildlife Research","active":true,"usgs":false}],"preferred":false,"id":851042,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hacker, Gregory","contributorId":296262,"corporation":false,"usgs":false,"family":"Hacker","given":"Gregory","email":"","affiliations":[{"id":33266,"text":"California Department of Public Health","active":true,"usgs":false}],"preferred":false,"id":851043,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Novak, Mark","contributorId":45229,"corporation":false,"usgs":false,"family":"Novak","given":"Mark","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":851044,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Buttke, Danielle","contributorId":225082,"corporation":false,"usgs":false,"family":"Buttke","given":"Danielle","affiliations":[],"preferred":false,"id":851045,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Grassel, Shaun M.","contributorId":150648,"corporation":false,"usgs":false,"family":"Grassel","given":"Shaun","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":851046,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hughes-Clarke, John","contributorId":41698,"corporation":false,"usgs":false,"family":"Hughes-Clarke","given":"John","email":"","affiliations":[{"id":18889,"text":"University of New Brunswick","active":true,"usgs":false}],"preferred":false,"id":851047,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Atiku, Linda","contributorId":296263,"corporation":false,"usgs":false,"family":"Atiku","given":"Linda","email":"","affiliations":[{"id":64008,"text":"Uganda Virus Research Institute","active":true,"usgs":false}],"preferred":false,"id":851048,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70245397,"text":"70245397 - 2022 - Modelling the transport and deposition of ash following a magnitude 7 eruption: The distal Mazama tephra","interactions":[],"lastModifiedDate":"2023-06-22T12:05:22.567726","indexId":"70245397","displayToPublicDate":"2022-09-02T06:59:56","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Modelling the transport and deposition of ash following a magnitude 7 eruption: The distal Mazama tephra","docAbstract":"Volcanic ash transport and dispersion models (VATDMs) are necessary for forecasting tephra dispersal during volcanic eruptions and are a useful tool for estimating the eruption source parameters (ESPs) of prehistoric eruptions. Here we use Ash3D, an Eulerian VATDM, to simulate the tephra deposition from the ~ 7.7 ka climactic eruption of Mount Mazama. We investigate how best to apply a VATDM using the ESPs characteristic of a large magnitude eruption (M ≥ 7). We simplify the approach to focus on the distal deposit as if it were formed by a single phase of Plinian activity. Our results demonstrate that it is possible to use modern wind profiles to simulate the tephra dispersal from a prehistoric eruption; however, this introduces an inherent uncertainty to the subsequent simulations where we explore different ESPs. We show, using the well-documented distal Mazama tephra, that lateral umbrella cloud spreading, rather than advection–diffusion alone, must be included in the VATDM to reproduce the width of the isopachs. In addition, the Ash3D particle size distribution must be modified to simulate the transport and deposition of distal fine-grained (< 125 µm) Mazama ash. With these modifications, the Ash3D simulations reproduce the thickness and grain size of the Mazama tephra deposit. Based on our simulations, however, we conclude that the exact relationship between mass eruption rate and the scale of umbrella cloud spreading remains unresolved. Furthermore, for ground-based grain size distributions to be input directly into Ash3D, further research is required into the atmospheric and particle processes that control the settling behaviour of fine volcanic ash.
Chronic wasting disease (CWD) continues to expand in distribution and prevalence across North America. Upon detection, either for the first time in a novel area or in a region with an existing outbreak, wildlife management agencies are tasked with responding to mitigate the disease. This response often entails creation or modification of a management zone with modified rules and regulations that support an agency's disease management plan. To guide the process of creating an appropriately sized CWD management zone, assuming that wild deer movements are a major risk factor for disease spread, we used data from global positioning system (GPS)-collared white-tailed deer (Odocoileus virginianus) in southeastern Minnesota and southcentral Pennsylvania, USA, between 2018 and 2021 to estimate long-distance movements associated with dispersal and migratory behaviors. These contrasting study areas with active CWD outbreaks permitted an evaluation of deer movement dynamics in different parts of their range. We quantified the proportion, distribution, timing, and orientation of dispersing and migratory deer. We observed 21% of female and 58% of male yearlings disperse from their apparent natal home range in Minnesota, while in Pennsylvania 4% of female and 68% of male yearlings dispersed. We also documented 20% of females and 6% of males migrated between seasonal home ranges in Minnesota, while in Pennsylvania no females and 5% of males migrated. The average distance deer dispersed or migrated in Minnesota was 20 km and 11 km, respectively, while in Pennsylvania male deer dispersed only about 4 km. Both sexes in Minnesota tended to disperse in a consistent, westerly direction; however, there was no directional preference observed for migratory deer or for dispersing deer in Pennsylvania. We found differences between natal and adult home range size for both sexes in Minnesota but not for males in Pennsylvania. Our results identify the considerable variability in dispersal and migration dynamics of white-tailed deer in disparate landscapes, which is important to agencies managing CWD. We summarize the distribution of these movements and suggest agencies use this information to help make decisions about optimal management zone size. We suggest the development of formalized assessments of the tradeoffs associated with optimizing decisions about creation of CWD management zones across white-tailed deer populations that exhibit variation in dispersal behavior and suggest careful evaluation to avoid using an arbitrary size or shape to create disease management zones.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22306","usgsCitation":"Jennelle, C., Walter, W., Crawford, J., Rosenberry, C., and Wallingford, B., 2022, Movement of white‐tailed deer in contrasting landscapes influences management of chronic wasting disease: Journal of Wildlife Management, v. 86, no. 8, e22306, 21 p., https://doi.org/10.1002/jwmg.22306.","productDescription":"e22306, 21 p.","ipdsId":"IP-136125","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480944,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, 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\"}}]}","volume":"86","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-09-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Jennelle, Christopher S.","contributorId":349404,"corporation":false,"usgs":false,"family":"Jennelle","given":"Christopher S.","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":924292,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walter, W. David 0000-0003-3068-1073","orcid":"https://orcid.org/0000-0003-3068-1073","contributorId":219540,"corporation":false,"usgs":true,"family":"Walter","given":"W. David","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":924293,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crawford, Joanne","contributorId":349406,"corporation":false,"usgs":false,"family":"Crawford","given":"Joanne","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":924294,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rosenberry, Christopher S.","contributorId":349408,"corporation":false,"usgs":false,"family":"Rosenberry","given":"Christopher S.","affiliations":[{"id":83357,"text":"Bureau of Wildlife Management","active":true,"usgs":false}],"preferred":false,"id":924295,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wallingford, Bret D.","contributorId":349410,"corporation":false,"usgs":false,"family":"Wallingford","given":"Bret D.","affiliations":[{"id":83357,"text":"Bureau of Wildlife Management","active":true,"usgs":false}],"preferred":false,"id":924296,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70245165,"text":"70245165 - 2022 - Microgravity change during the 2008-2018 Kı̄lauea summit eruption: Nearly a decade of subsurface mass accumulation","interactions":[],"lastModifiedDate":"2023-06-19T18:30:40.041096","indexId":"70245165","displayToPublicDate":"2022-09-01T13:15:51","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Microgravity change during the 2008-2018 Kı̄lauea summit eruption: Nearly a decade of subsurface mass accumulation","docAbstract":"Results from nine microgravity campaigns from Kı̄lauea, Hawaiʻi, spanning most of the volcano's 2008–2018 summit eruption, indicate persistent mass accumulation at shallow levels. A weighted least squares approach is used to recover microgravity results from a network of benchmarks around Kı̄lauea's summit, eliminate instrumental drift, and restore suspected data tares. A total mass of 1.9 × 1011 kg was determined from these microgravity campaigns to have accumulated below Kı̄lauea Caldera during 2009–2015 at an estimated depth of 1.3 km below sea level. Only a fraction of this mass is reflected in surface deformation, and this is consistent with previously reported discrepancies between subsurface mass accumulation and observed surface deformation. The discrepancy, amongst other independent evidence from gas emissions, seismicity, and continuous gravimetry, indicate densification of magma in the reservoirs below the volcano summit. This densification may have been driven by degassing through the summit vent. It is hypothesized that during the final years of the summit eruption, magma densification resulted in a buildup of pressure in the reservoirs that may have contributed to the lower East Rift Zone outbreak of 2018. The observed mass accumulation beneath Kı̄lauea could not have been detected through other techniques and illustrates the importance of microgravity measurements in volcano monitoring.
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","language":"English","publisher":"Society for the Study of Amphibians and Reptiles","usgsCitation":"Barnhart, P.D., Quiogue, Z.C., Frasch, E., Vice, D., Hopkins, C.B., Yackel Adams, A.A., Reed, R., and Nafus, M., 2022, Boiga irregularis (brown treesnake): Herpetological Review, v. 53, no. 3, p. 444-445.","productDescription":"2 p.","startPage":"444","endPage":"445","ipdsId":"IP-126596","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":420632,"type":{"id":24,"text":"Thumbnail"},"url":"http://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Cocos Island, Guam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 144.65870053775183,\n 13.24430283369017\n ],\n [\n 144.64368253164076,\n 13.24430283369017\n ],\n [\n 144.64368253164076,\n 13.232788830081347\n ],\n [\n 144.65870053775183,\n 13.232788830081347\n ],\n [\n 144.65870053775183,\n 13.24430283369017\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"53","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Barnhart, Patrick D 0000-0002-3966-9444","orcid":"https://orcid.org/0000-0002-3966-9444","contributorId":224635,"corporation":false,"usgs":true,"family":"Barnhart","given":"Patrick","email":"","middleInitial":"D","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":880820,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quiogue, Zachary C.","contributorId":270995,"corporation":false,"usgs":false,"family":"Quiogue","given":"Zachary","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":880821,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frasch, Elisabeth","contributorId":328628,"corporation":false,"usgs":false,"family":"Frasch","given":"Elisabeth","email":"","affiliations":[{"id":54632,"text":"Research Corporation of the University of Guam","active":true,"usgs":false}],"preferred":false,"id":880822,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vice, Diane","contributorId":328629,"corporation":false,"usgs":false,"family":"Vice","given":"Diane","affiliations":[{"id":78429,"text":"Guam Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":880823,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hopkins, Charlene Beverly 0000-0002-2537-8275","orcid":"https://orcid.org/0000-0002-2537-8275","contributorId":328630,"corporation":false,"usgs":true,"family":"Hopkins","given":"Charlene","email":"","middleInitial":"Beverly","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":880824,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":880825,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reed, Robert 0000-0001-8349-6168","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":267796,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":880826,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nafus, Melia Gail 0000-0002-7325-3055","orcid":"https://orcid.org/0000-0002-7325-3055","contributorId":245717,"corporation":false,"usgs":true,"family":"Nafus","given":"Melia Gail","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":880827,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70238578,"text":"70238578 - 2022 - Advancing geophysical techniques to image a stratigraphic hydrothermal resource","interactions":[],"lastModifiedDate":"2022-11-30T17:25:35.358802","indexId":"70238578","displayToPublicDate":"2022-09-01T11:18:57","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1827,"text":"Geothermal Resources Council Transactions","active":true,"publicationSubtype":{"id":10}},"title":"Advancing geophysical techniques to image a stratigraphic hydrothermal resource","docAbstract":"Sedimentary-hosted geothermal energy systems are permeable structural, structural-stratigraphic, and/or stratigraphic horizons with sufficient temperature for direct use and/or electricity generation. Sedimentary-hosted (i.e., stratigraphic) geothermal reservoirs may be present in multiple locations across the central and eastern Great Basin of the USA, thereby constituting a potentially large base of untapped, economically accessible energy resources. Sandia National Laboratories has partnered with a multi-disciplinary group of collaborators to evaluate a stratigraphic system in Steptoe Valley, Nevada using both established and novel geophysical imaging techniques. The goal of this study is to inform an optimized strategy for subsequent exploration and development of this and analogous resources. Building from prior Nevada Play Fairway Analysis (PFA), this team is primarily 1) collecting additional geophysical data, 2) employing novel joint geophysical inversion/modeling techniques to update existing 3D geologic models, and 3) integrating the geophysical results to produce a working, geologically constrained thermo-hydrological reservoir model. Prior PFA work highlights Steptoe Valley as a favorable resource basin that likely has both sedimentary and hydrothermal characteristics. However, there remains significant uncertainty on the nature and architecture of the resource(s) at depth, which increases the risk in exploratory drilling. Newly acquired gravity, magnetic, magnetotelluric, and controlled-source electromagnetic data, in conjunction with new and preceding geoscientific measurements and observations, are being integrated and evaluated in this study for efficacy in understanding stratigraphic geothermal resources and mitigating exploration risk. Furthermore, the influence of hydrothermal activity on sedimentary-hosted reservoirs in favorable structural settings (i.e., whether fault-controlled systems may locally enhance temperature and permeability in some deep stratigraphic reservoirs) will also be evaluated. This paper provides details and current updates on the course of this study in-progress.","language":"English","publisher":"Geothermal Rising","usgsCitation":"Schwering, P., Winn, C., Jaysaval, P., Knox, H., Siler, D.L., Hardwick, C., Ayling, B., Faulds, J., Mlawsky, E., McConville, E., Norbeck, J., Hinz, N., Matson, G., and Queen, J., 2022, Advancing geophysical techniques to image a stratigraphic hydrothermal resource: Geothermal Resources Council Transactions, v. 46, p. 976-991.","productDescription":"16 p.","startPage":"976","endPage":"991","ipdsId":"IP-141659","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":409862,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":409843,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1034650","linkFileType":{"id":5,"text":"html"}}],"volume":"46","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schwering, Paul","contributorId":299507,"corporation":false,"usgs":false,"family":"Schwering","given":"Paul","email":"","affiliations":[{"id":34829,"text":"Sandia National Laboratories","active":true,"usgs":false}],"preferred":false,"id":857964,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Winn, Carmen","contributorId":299508,"corporation":false,"usgs":false,"family":"Winn","given":"Carmen","email":"","affiliations":[{"id":34829,"text":"Sandia National Laboratories","active":true,"usgs":false}],"preferred":false,"id":857965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jaysaval, Piyoosh","contributorId":299509,"corporation":false,"usgs":false,"family":"Jaysaval","given":"Piyoosh","email":"","affiliations":[{"id":38914,"text":"Pacific Northwest National Laboratory","active":true,"usgs":false}],"preferred":false,"id":857966,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knox, Hunter","contributorId":299510,"corporation":false,"usgs":false,"family":"Knox","given":"Hunter","email":"","affiliations":[{"id":38914,"text":"Pacific Northwest National Laboratory","active":true,"usgs":false}],"preferred":false,"id":857967,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":857968,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hardwick, Christian","contributorId":299511,"corporation":false,"usgs":false,"family":"Hardwick","given":"Christian","affiliations":[{"id":17626,"text":"Utah Geological Survey","active":true,"usgs":false}],"preferred":false,"id":857969,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ayling, Bridget","contributorId":299512,"corporation":false,"usgs":false,"family":"Ayling","given":"Bridget","affiliations":[{"id":64865,"text":"Great Basin Center for Geothermal Energy; 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Marine research and management organizations use these data to help ensure safe navigation, promote sustainable fisheries, extract energy, and protect marine habitats in the coastal and ocean waters of the U.S. Exclusive Economic Zone (EEZ) and Laurentian Great Lakes. Many of these organizations may have overlapping or shared mapping interests without knowing it.
In a multi-jurisdictional planning environment, it can be challenging and cumbersome to determine where other entities have shared or overlapping mapping interests, especially across a transnational region such as the Great Lakes. State and provincial governments, federal governments, academia, tribes and First Nations, and other stakeholders from both the U.S. and Canada all have mapping interests across Great Lakes waters. Identifying and communicating target geographies for new data collection that are shared among multiple organizations can both help to avoid redundancy of new mapping efforts, and create opportunities for greater efficiency through collaboration.
To address this issue, a spatial priorities study was conducted using a geospatial tool developed by the National Ocean Services National Centers for Coastal and Ocean Science (NCCOS). The tool provided an easy-to-use online interface in which programs can identify their priorities in a simple and straightforward way. This study asked representatives of Great Lakes management and science organizations to identify the areas for which they needed maps of lakebed features on a near-term, mid-term, and long-term timeframe, and why. Then, the responses were analyzed and overlaid to determine areas of shared mapping need and opportunity and to determine the types of map products needed.
The analysis revealed high interest among multiple organizations in discrete geographies including the Minnesota and Wisconsin shoreline from Duluth to the eastern extent of the Bayfield Peninsula, Green Bay in Lake Michigan, and the southern coastlines of Lake Erie and Lake Ontario, the St. Marys River, and the northern Lake Superior coastal waters near Grand Portage, MN. Lower priority mapping interest were distributed widely across all lakes, but tended to be concentrated in nearshore areas (<30 m depth).
The analysis also indicated that the top mapping justifications were Habitat/biota/natural area, Benthic exploration, Commercial and recreational fishing, and Scientific research. The top desired map product types were Elevation, Substrate/sub-bottom geologic characterization, and Habitat map/characterization, although participants on some lakes noted other less prevalent product types.
Following from previously conducted NOAA and non-NOAA Federal spatial prioritization exercises, the results of this regional focus can help mapping organizations better understand how their priorities align with the needs of regional organizations, allow for more efficient coordination and funding, and enable partners to leverage assets and resources to fill their most pressing data and information gaps across Great Lakes waters. The U.S. Mapping Coordination Site hosts the results of this study and other spatial prioritization studies. Through this website, one can interact with the study results along with recent and planned mapping efforts.
NOAA intends to update their spatial priorities on a three- to five-year basis. Future studies should strive to expand participation of federal agencies, state and local governments, federally-recognized tribes, academia, and private industry (among other stakeholders) to seek out ocean mapping partnerships in conjunction with the National Ocean Mapping, Exploration and Characterization (NOMEC) goals map once, use many times.”
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geodesy","interactions":[],"lastModifiedDate":"2023-06-19T16:06:57.613709","indexId":"70245163","displayToPublicDate":"2022-09-01T10:56:22","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"The centenary of IAVCEI 1919–2019 and beyond: The people, places, and things of volcano geodesy","docAbstract":"Over the first century of the International Association of Volcanology and Chemistry of the Earth’s Interior (IAVCEI), volcano geodesy grew from roots as an accidental and incidental system of measurements to an important method for monitoring volcanic activity and forecasting eruptions. The first practitioners in volcano geodesy were experts in other disciplines, and it was not until the latter half of the twentieth century that specialists in the field emerged—scientists who developed new methods, measured geodetic change at volcanoes, and quantitatively interpreted the results in terms of magmatic processes. Much of the early work in the field was restricted to a few volcanoes and involved techniques that had been adapted from other applications; relatively few methods were developed specifically for use on volcanoes. These volcanoes, however, provided the natural laboratories needed to advance the field. By the start of the twenty-first century, geodetic studies, especially using space-based techniques, contributed to the recognition of deformation and gravity change at hundreds of volcanoes on Earth. In coming years, IAVCEI researchers will focus on comprehensive exploitation of the growing volumes of geodetic data to better model, forecast, and track activity at volcanoes worldwide. Meanwhile, the field needs to become more diverse, better representing people who live in the shadows of volcanoes around the globe.
","language":"English","publisher":"Springer","doi":"10.1007/s00445-022-01598-w","usgsCitation":"Poland, M.P., and de Zeeuw-van Dalfsen, E., 2022, The centenary of IAVCEI 1919–2019 and beyond: The people, places, and things of volcano geodesy: Bulletin of Volcanology, v. 84, 90, 23 p., https://doi.org/10.1007/s00445-022-01598-w.","productDescription":"90, 23 p.","ipdsId":"IP-138073","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":418215,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"84","noUsgsAuthors":false,"publicationDate":"2022-09-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":875725,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Zeeuw-van Dalfsen, Elske 0000-0003-2527-4932","orcid":"https://orcid.org/0000-0003-2527-4932","contributorId":217967,"corporation":false,"usgs":false,"family":"de Zeeuw-van Dalfsen","given":"Elske","email":"","affiliations":[{"id":39727,"text":"KNMI","active":true,"usgs":false}],"preferred":false,"id":875726,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70256750,"text":"70256750 - 2022 - Seasonal context of bristly cave crayfish Cambarus setosus habitat use and life history","interactions":[],"lastModifiedDate":"2024-09-04T15:39:26.083626","indexId":"70256750","displayToPublicDate":"2022-09-01T10:33:33","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2201,"text":"Journal of Cave and Karst Studies","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal context of bristly cave crayfish Cambarus setosus habitat use and life history","docAbstract":"Cave crayfishes are important members of groundwater communities, but many cave crayfishes are threatened or endangered. Unfortunately, we lack basic life history and ecological data that are needed for developing conservation plans for most cave crayfishes, especially the role of seasonal and annual fluctuations in structuring populations. Therefore, we determined the seasonal life history and habitat use of Cambarus setosus in Smallin Civil War Cave, Christian County, Missouri, United States. We conducted visual crayfish surveys over a 400 m section of the cave from 2006 to 2019. We used multinomial logit, multiple linear regression, and logistic regression models to estimate crayfish substrate, water depth, and water velocity use, respectively. All models included sex, carapace length, season, distance into the cave, and interactions between all variables and sex as predictor terms. We also used t-tests to assess morphometric differences between male and female crayfish. Six mark-recapture events (2010 to 2019) were used to estimate population sizes using a nil-recapture model. We attempted to age eight individuals using gastric mill bands, but annual bands were not discernable. We found reproductively active males during all seasons. We captured one ovigerous female during the spring, though ovigerous females were observed during show cave tours during spring, summer, and autumn. Male C. setosus were more likely to use homogenous and heterogeneous rock substrates and shallower and calmer water when compared to females; however, these relationships varied based on distance into the cave and season. Females sampled were significantly larger than males, and males regenerated chelae more often. Minimum population size estimates ranged from 9 to 159 individuals and indicated the population was relatively stable. Our data provide both a baseline population estimate for comparison with future studies and valuable trait information that is often lacking but useful for developing conservation efforts.
","language":"English","publisher":"National Speleological Society","doi":"10.4311/2021LSC0110","usgsCitation":"Mouser, J., Ashley, D., Zenter, D., and Brewer, S.K., 2022, Seasonal context of bristly cave crayfish Cambarus setosus habitat use and life history: Journal of Cave and Karst Studies, v. 84, no. 3, p. 85-95, https://doi.org/10.4311/2021LSC0110.","productDescription":"11 p.","startPage":"85","endPage":"95","ipdsId":"IP-127872","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":446569,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://doi.org/10.4311/2021lsc0110","text":"Publisher Index Page"},{"id":433451,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","county":"Christian County","otherGeospatial":"Smallin Civil War Cave","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.18894102326013,\n 37.05222350256189\n ],\n [\n -93.18894102326013,\n 37.04918995811687\n ],\n [\n -93.18586955215672,\n 37.04918995811687\n ],\n [\n -93.18586955215672,\n 37.05222350256189\n ],\n [\n -93.18894102326013,\n 37.05222350256189\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"84","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mouser, J.B.","contributorId":244447,"corporation":false,"usgs":false,"family":"Mouser","given":"J.B.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":908855,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ashley, D.C.","contributorId":244487,"corporation":false,"usgs":false,"family":"Ashley","given":"D.C.","email":"","affiliations":[{"id":48915,"text":"Missouri Western State University","active":true,"usgs":false}],"preferred":false,"id":908856,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zenter, D.L.","contributorId":341751,"corporation":false,"usgs":false,"family":"Zenter","given":"D.L.","email":"","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":908857,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":908858,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70233185,"text":"70233185 - 2022 - Basis for technical guidance to evaluate evapotranspiration covers","interactions":[],"lastModifiedDate":"2022-12-12T15:58:40.79318","indexId":"70233185","displayToPublicDate":"2022-09-01T09:55:22","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesNumber":"NUREG/CR-7297","title":"Basis for technical guidance to evaluate evapotranspiration covers","docAbstract":"This report provides technical guidance to evaluate evapotranspiration (ET) cover design criteria with emphasis on applications to long-term disposal sites such as Uranium Mill Tailings Radiation Control Act of 1978 (UMTRCA) sites. Water balance covers, also known as ET covers, reduce percolation by storing precipitation then allowing vegetation to cycle it back to the atmosphere. For long-term (over 200 years) waste isolation, ET covers may provide significant benefits over conventional, resistive covers that rely on engineered components, such as compacted clay barriers and geomembranes, to divert precipitation. UMTRCA covers were designed to impede and attenuate radioactive radon-222 gas flux from the underlying tailings, while minimizing percolation of any contaminants to groundwater. Such covers have implicit regulatory compliance post-construction. Alternative cover systems, such as ET covers, must explicitly meet some anticipated performance, and demonstrate beneficial use. While all engineered structures will change over time, an ET cover evolves with nature rather than resisting it, which may perpetuate a more reliable waste isolation system. For example, UMTRCA sites must provide safe and environmentally sound disposal, long-term stabilization, and control of uranium mill tailings and remain effective for up to 1,000 years, to the extent reasonably achievable, and, in any case, for at least 200 years. UMTRCA covers rely on the engineered properties to meet regulatory requirements during and immediately after construction. Subsequent compliance is implicit in the design. The design of an ET cover is far more dependent on mesoscale meteorology, native vegetation, and edaphic soil properties which are site-specific. Therefore, the design and anticipated performance of an ET cover must be demonstrated through a combination of modeling, natural analogues and pilot studies, and then verified with monitoring data. There is no single ET cover design that can likely meet performance standards across different climates, available soils, and vegetation. The technical information presented in this report reviews guidelines and performance criteria commonly used for ET covers at municipal waste facilities and the consideration factors of such covers to meet the regulatory requirements at long-term disposal sites.","language":"English","publisher":"U.S. Nuclear Regulatory Commission","usgsCitation":"Caldwell, T., Huntington, J., Davies, G.E., Tabatabai, S., and Fuhrmann, M., 2022, Basis for technical guidance to evaluate evapotranspiration covers, 127 p.","productDescription":"127 p.","ipdsId":"IP-120445","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":410286,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":403886,"type":{"id":15,"text":"Index Page"},"url":"https://www.nrc.gov/reading-rm/doc-collections/nuregs/contract/cr7297/index.html"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Caldwell, Todd 0000-0003-4068-0648","orcid":"https://orcid.org/0000-0003-4068-0648","contributorId":217924,"corporation":false,"usgs":true,"family":"Caldwell","given":"Todd","email":"","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":846716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huntington, Jena 0000-0002-9291-1404","orcid":"https://orcid.org/0000-0002-9291-1404","contributorId":204033,"corporation":false,"usgs":true,"family":"Huntington","given":"Jena","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":846717,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davies, Gwendolyn Elizabeth 0000-0003-1538-8610","orcid":"https://orcid.org/0000-0003-1538-8610","contributorId":293203,"corporation":false,"usgs":true,"family":"Davies","given":"Gwendolyn","email":"","middleInitial":"Elizabeth","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":846718,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tabatabai, S.","contributorId":293205,"corporation":false,"usgs":false,"family":"Tabatabai","given":"S.","affiliations":[{"id":12536,"text":"U.S. Nuclear Regulatory Commission","active":true,"usgs":false}],"preferred":false,"id":846719,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuhrmann, M.","contributorId":138800,"corporation":false,"usgs":false,"family":"Fuhrmann","given":"M.","affiliations":[{"id":12528,"text":"US Nuclear Regulatory Commission","active":true,"usgs":false}],"preferred":false,"id":846720,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70236641,"text":"70236641 - 2022 - A process-model perspective on recent changes in the carbon cycle of North America","interactions":[],"lastModifiedDate":"2022-09-14T14:51:20.282288","indexId":"70236641","displayToPublicDate":"2022-09-01T09:43:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7359,"text":"Journal of Geophysical Research Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"A process-model perspective on recent changes in the carbon cycle of North America","docAbstract":"Continental North America has been found to be a carbon (C) sink over recent decades by multiple studies employing a variety of estimation approaches. However, several key questions and uncertainties remain with these assessments. Here we used results from an ensemble of 19 state-of-the-art dynamic global vegetation models from the TRENDYv9 project to improve these estimates and study the drivers of its interannual variability. Our results show that North America has been a C sink with a magnitude of 0.37 ± 0.38 (mean and one standard deviation) PgC year−1 for the period 2000–2019 (0.31 and 0.44 PgC year−1 in each decade); split into 0.18 ± 0.12 PgC year−1 in Canada (0.15 and 0.20), 0.16 ± 0.17 in the United States (0.14 and 0.17), 0.02 ± 0.05 PgC year−1 in Mexico (0.02 and 0.02) and 0.01 ± 0.02 in Central America and the Caribbean (0.01 and 0.01). About 57% of the new C assimilated by terrestrial ecosystems is allocated into vegetation, 30% into soils, and 13% into litter. Losses of C due to fire account for 41% of the interannual variability of the mean net biome productivity for all North America in the model ensemble. Finally, we show that drought years (e.g., 2002) have the potential to shift the region to a small net C source in the simulations (−0.02 ± 0.46 PgC year−1). Our results highlight the importance of identifying the major drivers of the interannual variability of the continental-scale land C cycle along with the spatial distribution of local sink-source dynamics.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JG006904","usgsCitation":"Murray-Tortarolo, G., Poulter, B., Vargas, R., Hayes, D., Michalak, A., Williams , C., Windham-Myers, L., Wang, J., Wickland, K., Butman, D., Tian, H., Sitch, S., Friedlingstein, P., O’Sullivan, M., Briggs, P., Arora, V., Lombardozzi, D., Jain, A., Yuan, W., Seferian, R., Nabel, J., Wiltshire, A., Arneth, A., Lienerte, S., Zaehle, S., Bastrikov, V., Goll, D., Vuichard, N., Walker, A.P., Kato, E., Xu, Y., Zhang, Z., Chaterjee, A., and Kurz, W., 2022, A process-model perspective on recent changes in the carbon cycle of North America: Journal of Geophysical Research Biogeosciences, v. 127, no. 9, e2022JG006904, 19 p., https://doi.org/10.1029/2022JG006904.","productDescription":"e2022JG006904, 19 p.","ipdsId":"IP-144503","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":446574,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022jg006904","text":"Publisher Index Page"},{"id":406674,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -42.1875,\n 60.413852350464914\n ],\n [\n -20.7421875,\n 70.61261423801925\n ],\n [\n -12.3046875,\n 82.02137801950887\n ],\n [\n -28.828124999999996,\n 83.63810565804015\n ],\n [\n -83.671875,\n 83.31873282163234\n ],\n [\n -130.78125,\n 75.58493740869223\n ],\n [\n -131.1328125,\n 70.72897946208789\n ],\n [\n -164.1796875,\n 71.74643171904148\n ],\n [\n -172.96875,\n 62.91523303947614\n ],\n [\n -159.9609375,\n 52.696361078274485\n ],\n [\n -142.03125,\n 58.07787626787517\n ],\n [\n -128.671875,\n 47.989921667414194\n ],\n [\n -120.9375,\n 24.84656534821976\n ],\n [\n -83.3203125,\n 4.915832801313164\n ],\n [\n -76.640625,\n 11.178401873711785\n ],\n [\n -67.8515625,\n 17.97873309555617\n ],\n [\n -42.1875,\n 60.413852350464914\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"127","issue":"9","noUsgsAuthors":false,"publicationDate":"2022-09-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Murray-Tortarolo, Guillermo","contributorId":296446,"corporation":false,"usgs":false,"family":"Murray-Tortarolo","given":"Guillermo","email":"","affiliations":[{"id":64038,"text":"Instituto de Investigaciones en Ecosistemas y Sustentabilidad. 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A.","contributorId":50644,"corporation":false,"usgs":true,"family":"Kurz","given":"Werner A.","affiliations":[],"preferred":false,"id":851707,"contributorType":{"id":1,"text":"Authors"},"rank":34}]}} ,{"id":70236665,"text":"70236665 - 2022 - Integrating climate-informed planning into State Wildlife Action Plans in the north central United States","interactions":[],"lastModifiedDate":"2022-09-15T14:42:45.086223","indexId":"70236665","displayToPublicDate":"2022-09-01T09:34:34","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Integrating climate-informed planning into State Wildlife Action Plans in the north central United States","docAbstract":"State fish and wildlife agencies are required to submit a State Wildlife Action Plan (SWAP) every 10 years to be eligible for grants through the State Wildlife Grant Program. With the next round of revisions due in 2025, the U.S. Geological Survey North Central Climate Adaptation Science Center is evaluating how to best support states with further integrating climate-informed planning in their SWAPs. Here, we summarize how states in the North Central region, which includes Colorado, Kansas, Montana, Nebraska, North Dakota, South Dakota, and Wyoming, addressed adaptation planning in their 2015 SWAPs. We review climate adaptation considerations in required SWAP elements one through five, including species, habitats, threats, conservation actions, and conservation monitoring, respectively. We also include a list of potential strategies that the North Central Climate Adaptation Science Center could use to support states in the North Central region with further advancing the integration of climate informed planning in ongoing and future SWAP revisions. These strategies were primarily identified during meetings in 2021 with six of seven state fish and wildlife agencies in the North Central region where we discussed their priority needs relating to climate-informed planning. Our hope is that these strategies will enhance existing efforts in the region to advance the integration of climate change in conservation planning.
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0000-0001-7456-9564","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":229347,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":851808,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wade, Alisa 0000-0003-3976-2224","orcid":"https://orcid.org/0000-0003-3976-2224","contributorId":266157,"corporation":false,"usgs":true,"family":"Wade","given":"Alisa","email":"","affiliations":[{"id":40927,"text":"North Central Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":851809,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237260,"text":"70237260 - 2022 - Little bugs, big data, and Colorado River adaptive management: Preliminary findings from the ongoing bug flow experiment at Glen Canyon Dam","interactions":[],"lastModifiedDate":"2025-03-14T15:11:55.173887","indexId":"70237260","displayToPublicDate":"2022-09-01T09:22:40","publicationYear":"2022","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":8569,"text":"Boatman's Quarterly Review","active":true,"publicationSubtype":{"id":30}},"title":"Little bugs, big data, and Colorado River adaptive management: Preliminary findings from the ongoing bug flow experiment at Glen Canyon Dam","docAbstract":"The undammed Colorado River in Grand Canyon was characterized by spring snow-melt floods that sometimes exceeded 100,000 cubic feet per second (cfs). These were followed by occasional flash floods during summer monsoons, then by low flows from fall through early spring (Figure 1; Topping and others, 2003). This seasonally variable flow regime carried huge loads of sediment and was an important driver of natural processes that sustained the Colorado River ecosystem. For instance, high turbidity associated with this flow regime likely restricted algal growth to the river’s edge or shallow cobble habitats, similar to other desert rivers. Aquatic invertebrate assemblages were probably diverse and adapted to these variable conditions (Vinson, 2001; Haden and others, 2003). Native fishes were likely opportunistic feeders, consuming ants, seeds, and other terrestrial resources during times of flooding and switching to aquatic-derived resources like algae and aquatic invertebrates at other times (Minckley, 1991; Behn and Baxter, 2019). Regulation of the Colorado River by Glen Canyon Dam in 1963 eliminated the annual snowmelt floods, it sharply increased base flows by more than 50 percent, and dramatically increased within-day fluctuations in discharge for hydropower production (the ‘daily tides’ of the river, Figure 1 and 2; Topping and others, 2003). Glen Canyon Dam also changed other aspects of the river’s physical template, particularly temperature, sediment, and nutrient regimes. These changes to the physical template of the river led to fundamental changes in the natural processes that the sustain Colorado River ecosystem. For example, algae are common throughout the river during periods of clear water and represent the foundation of aquatic food webs (Stevens and others, 1997; Cross and others 2013). Many types of aquatic insects have disappeared or become rare, particularly sensitive groups such as mayflies, stoneflies, and caddisflies (Kennedy and others, 2016). Because aquatic insect assemblages in the Colorado River in Grand Canyon are neither diverse nor productive, food webs are simplified and inherently unstable, limiting populations of hungry fish (Cross and others 2013; Korman and others 2021).
","language":"English","publisher":"Grand Canyon River Guides Association","usgsCitation":"Kennedy, T., Metcalfe, A., Deemer, B., Ford, M., Szydlo, C.M., Yackulic, C., and Muehlbauer, J., 2022, Little bugs, big data, and Colorado River adaptive management: Preliminary findings from the ongoing bug flow experiment at Glen Canyon Dam: Boatman's Quarterly Review, v. 35, no. 3, p. 26-31.","productDescription":"6 p.","startPage":"26","endPage":"31","ipdsId":"IP-143763","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":483348,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.gcrg.org/bqr"},{"id":407960,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Glen Canyon Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.48968696594237,\n 36.93095788125762\n ],\n [\n -111.47878646850586,\n 36.93095788125762\n ],\n [\n -111.47878646850586,\n 36.94021961852396\n ],\n [\n -111.48968696594237,\n 36.94021961852396\n ],\n [\n -111.48968696594237,\n 36.93095788125762\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kennedy, Theodore 0000-0003-3477-3629","orcid":"https://orcid.org/0000-0003-3477-3629","contributorId":221741,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853868,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Metcalfe, Anya 0000-0002-6286-4889","orcid":"https://orcid.org/0000-0002-6286-4889","contributorId":221738,"corporation":false,"usgs":true,"family":"Metcalfe","given":"Anya","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853869,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deemer, Bridget R. 0000-0002-5845-1002 bdeemer@usgs.gov","orcid":"https://orcid.org/0000-0002-5845-1002","contributorId":198160,"corporation":false,"usgs":true,"family":"Deemer","given":"Bridget","email":"bdeemer@usgs.gov","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853870,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ford, Morgan 0000-0001-5104-9566","orcid":"https://orcid.org/0000-0001-5104-9566","contributorId":221740,"corporation":false,"usgs":true,"family":"Ford","given":"Morgan","email":"","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853871,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Szydlo, Cheyenne Maxime 0000-0003-4818-2395","orcid":"https://orcid.org/0000-0003-4818-2395","contributorId":297340,"corporation":false,"usgs":true,"family":"Szydlo","given":"Cheyenne","email":"","middleInitial":"Maxime","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853872,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853873,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Muehlbauer, Jeffrey 0000-0003-1808-580X","orcid":"https://orcid.org/0000-0003-1808-580X","contributorId":221739,"corporation":false,"usgs":true,"family":"Muehlbauer","given":"Jeffrey","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853874,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70236341,"text":"70236341 - 2022 - Comparing root cohesion estimates from three models at a shallow landslide in the Oregon Coast Range","interactions":[],"lastModifiedDate":"2022-09-02T14:17:32.925032","indexId":"70236341","displayToPublicDate":"2022-09-01T09:13:29","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12565,"text":"GeoHazards","active":true,"publicationSubtype":{"id":10}},"title":"Comparing root cohesion estimates from three models at a shallow landslide in the Oregon Coast Range","docAbstract":"Although accurate root cohesion model estimates are essential to quantify the effect of vegetation roots on shallow slope stability, few means exist to independently validate such model outputs. One validation approach for cohesion estimates is back-calculation of apparent root cohesion at a landslide site with well-documented failure conditions. The catchment named CB1, near Coos Bay, Oregon, USA, which experienced a shallow landslide in 1996, is a prime locality for cohesion model validation, as an abundance of data and observations from the site generated broad insights related to hillslope hydrology and slope stability. However, previously published root cohesion values at CB1 used the Wu and Waldron model (WWM), which assumes simultaneous root failure and therefore likely overestimates root cohesion. Reassessing published cohesion estimates from this site is warranted, as more recently developed models include the fiber bundle model (FBM), which simulates progressive failure with load redistribution, and the root bundle model-Weibull (RBMw), which accounts for differential strain loading. We applied the WWM, FBM, and RBMw at CB1 using post-failure root data from five vegetation species. At CB1, the FBM and RBMw predict values that are less than 30% of the WWM-estimated values. All three models show that root cohesion has substantial spatial heterogeneity. Most parts of the landslide scarp have little root cohesion, with areas of high cohesion concentrated near plant roots. These findings underscore the importance of using physically realistic models and considering lateral and vertical spatial heterogeneity of root cohesion in shallow landslide initiation and provide a necessary step towards independently assessing root cohesion model validity.
","language":"English","publisher":"MDPI","doi":"10.3390/geohazards3030022","usgsCitation":"Cronkite-Ratcliff, C., Schmidt, K.M., and Wirion, C., 2022, Comparing root cohesion estimates from three models at a shallow landslide in the Oregon Coast Range: GeoHazards, v. 3, no. 3, p. 428-451, https://doi.org/10.3390/geohazards3030022.","productDescription":"24 p.","startPage":"428","endPage":"451","ipdsId":"IP-133079","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":446579,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/geohazards3030022","text":"Publisher Index Page"},{"id":406136,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","city":"Coos Bay","otherGeospatial":"Coast Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.56298828125001,\n 43.14909399920127\n ],\n [\n -123.50830078125,\n 43.14909399920127\n ],\n [\n -123.50830078125,\n 43.75522505306928\n ],\n [\n -124.56298828125001,\n 43.75522505306928\n ],\n [\n -124.56298828125001,\n 43.14909399920127\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"3","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-09-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Cronkite-Ratcliff, Collin 0000-0001-5485-3832 ccronkite-ratcliff@usgs.gov","orcid":"https://orcid.org/0000-0001-5485-3832","contributorId":203951,"corporation":false,"usgs":true,"family":"Cronkite-Ratcliff","given":"Collin","email":"ccronkite-ratcliff@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":850664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmidt, Kevin M. 0000-0003-2365-8035 kschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-2365-8035","contributorId":1985,"corporation":false,"usgs":true,"family":"Schmidt","given":"Kevin","email":"kschmidt@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":850665,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wirion, Charlotte 0000-0003-0721-3036","orcid":"https://orcid.org/0000-0003-0721-3036","contributorId":296101,"corporation":false,"usgs":false,"family":"Wirion","given":"Charlotte","email":"","affiliations":[{"id":63984,"text":"ETH Zurich, Switzerland (now at WEO, Luxembourg)","active":true,"usgs":false}],"preferred":false,"id":850666,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70256644,"text":"70256644 - 2022 - Seabird vulnerability to oil: Exposure potential, sensitivity, and uncertainty in the northern Gulf of Mexico","interactions":[],"lastModifiedDate":"2024-08-29T14:09:34.922004","indexId":"70256644","displayToPublicDate":"2022-09-01T09:02:56","publicationYear":"2022","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":"Seabird vulnerability to oil: Exposure potential, sensitivity, and uncertainty in the northern Gulf of Mexico","docAbstract":"The northern Gulf of Mexico (nGoM) is a globally important region for oil extraction and supports a diverse assemblage of marine birds. Due to their frequent contact with surface waters, diverse foraging strategies, and the ease with which oil adheres to feathers, seabirds are particularly susceptible to hydrocarbon contamination. Given the chronic and acute exposure of seabirds to oiling and a lack of studies that focus on the exposure of seabirds to oiling in sub-tropical and tropical regions, a greater understanding of the vulnerability of seabirds to oil in the nGoM appears warranted. We present an oil vulnerability index for seabirds in the nGoM tailored to the current state of knowledge using new, spatiotemporally expensive vessel-based seabird observations. We use information on the exposure and sensitivity of seabirds to oil to rank seabird vulnerability. Exposure variables characterized the potential to encounter oil and gas (O&G). Sensitivity variables characterized the potential impact of seabirds interacting with O&G and are related to life history and productivity. We also incorporated uncertainty in each variable, identifying data gaps. We found that the percent of seabirds’ habitat defined as highly suitable within 10 km of an O&G platform ranged from 0%-65% among 24 species. Though O&G platforms only overlap with 15% of highly suitable seabird habitat, overlap occurs in areas of moderate to high vulnerability of seabirds, particularly along the shelf-slope. Productivity-associated sensitivity variables were primarily responsible for creating the gradient in vulnerability scores and had greater uncertainty than exposure variables. Highly vulnerable species (e.g., Northern gannet (Morus bassanus)) tended to have high exposure to the water surface via foraging behaviors (e.g., plunge-diving), older age at first breeding, and an extended incubating and fledging period compared to less vulnerable species (e.g., Pomarine jaeger (Stercorarius pomarinus)). Uncertainty related to productivity could be reduced through at-colony monitoring. Strategic seabird satellite tagging could help target monitoring efforts to colonies known to use the nGoM, and continued vessel-based observations could improve habitat characterization. As offshore energy development in the nGoM continues, managers and researchers could use these vulnerability ranks to identify information gaps to prioritize research and focal species.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2022.880750","usgsCitation":"Michael, P.E., Hixson, K.M., Haney, J., Satge, Y., Gleason, J., and Jodice, P.G., 2022, Seabird vulnerability to oil: Exposure potential, sensitivity, and uncertainty in the northern Gulf of Mexico: Frontiers in Marine Science, v. 9, 880750, 20 p., https://doi.org/10.3389/fmars.2022.880750.","productDescription":"880750, 20 p.","ipdsId":"IP-136731","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":446580,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2022.880750","text":"Publisher Index Page"},{"id":433301,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"northern Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.65064732144825,\n 24.16865530700734\n ],\n [\n -80.74028091647656,\n 24.49674089923498\n ],\n [\n -80.6110475132637,\n 25.375716312633244\n ],\n [\n -82.48124501487644,\n 27.87595132514076\n ],\n [\n -82.50401354053463,\n 28.975470074471573\n ],\n [\n -84.01377542803263,\n 30.278116834370664\n ],\n [\n -85.21105352771927,\n 29.813919882762193\n ],\n [\n -86.41030861654544,\n 30.53771106924384\n ],\n [\n -88.05949534476994,\n 30.614388650912403\n ],\n [\n -89.250977846713,\n 30.128789114669402\n ],\n [\n -88.84045762268858,\n 28.94436305824601\n ],\n [\n -90.45644421555457,\n 29.213975074748845\n ],\n [\n -91.6391457751865,\n 29.567867845383958\n ],\n [\n -92.61153919455367,\n 29.52398569897167\n ],\n [\n -94.15861129214014,\n 29.615060750195013\n ],\n [\n -95.85111266718562,\n 28.497269906948034\n ],\n [\n -97.05244440317941,\n 27.930797727982196\n ],\n [\n -97.4997935110664,\n 26.841188159759383\n ],\n [\n -97.23172322974906,\n 26.093166420472286\n ],\n [\n -86.07549373074224,\n 26.17610757333493\n ],\n [\n -85.31650372657558,\n 24.614391708025977\n ],\n [\n -83.65064732144825,\n 24.16865530700734\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2022-09-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Michael, Pamela E.","contributorId":341457,"corporation":false,"usgs":false,"family":"Michael","given":"Pamela","email":"","middleInitial":"E.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":908453,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hixson, K. M.","contributorId":341458,"corporation":false,"usgs":false,"family":"Hixson","given":"K.","email":"","middleInitial":"M.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":908454,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haney, J.C.","contributorId":288019,"corporation":false,"usgs":false,"family":"Haney","given":"J.C.","email":"","affiliations":[{"id":61685,"text":"Terra Mar Applied Sciences","active":true,"usgs":false}],"preferred":false,"id":908455,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Satge, Y.G.","contributorId":279816,"corporation":false,"usgs":false,"family":"Satge","given":"Y.G.","email":"","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":908456,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gleason, J.S.","contributorId":288017,"corporation":false,"usgs":false,"family":"Gleason","given":"J.S.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":908457,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":219852,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908458,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}