Limited favorable weather windows for post-germination early seedling survival are associated with low restoration success in drylands. We examined whether post-fire seeding decisions could alter early seedling emergence and restoration success across western North American sagebrush ecosystems with a simulation approach. Seedling emergence estimates were based on germination of a specified percentile of sown seeds followed by favorable conditions for seedling development. We asked how three categories of seeding decisions affected emergence: post-fire seeding year, seasonal seeding delay (via seed coating technologies or later seeding timing), or native perennial grass seed source (via differing germination behavior). We also tested potential effects of mean annual precipitation on seeding decision outcomes (interactive effect) and included topographic microclimate and site (random effect) in models. Emergence was highest when the best seed source (of 10) was seeded in the best post-fire year (of 5). High emergence also resulted from seeding in the best post-fire year with an average seed source or seeding with the best source in the first post-fire year. Emergence was higher overall with higher mean precipitation. Seeding decision outcomes were sensitive to annual mean precipitation, with greater differences observed due to decisions at lower precipitation levels. While sensitive to assumptions related to seedling development and germination speed, these results suggest that restoration approaches linked to germination behavior and weather variability could improve restoration success rates in variable drylands like sagebrush ecosystems.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.14362","usgsCitation":"Copeland, S.M., Baughman, O.W., Bradford, J., Hardegree, S.P., Larson, J.E., Schlaepfer, D.R., and Badik, K.J., 2024, Managing to survive despite the weather: Seeding decisions affecting simulated dryland restoration outcomes: Restoration Ecology, v. 33, no. 6, e14362, 14 p., https://doi.org/10.1111/rec.14362.","productDescription":"e14362, 14 p.","ipdsId":"IP-163398","costCenters":[{"id":49226,"text":"Northwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":496333,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/rec.14362","text":"Publisher Index Page"},{"id":496270,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Nevada, Oregon, Utah","otherGeospatial":"Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.574531556712,\n 43.9234644270079\n ],\n [\n -120.04179285934424,\n 38.43059054059461\n ],\n [\n -111.74305139404657,\n 38.21318759330562\n ],\n [\n -111.10879379526153,\n 44.028804617635814\n ],\n [\n -119.574531556712,\n 43.9234644270079\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"33","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Copeland, Stella M. 0000-0001-6707-4803","orcid":"https://orcid.org/0000-0001-6707-4803","contributorId":361962,"corporation":false,"usgs":false,"family":"Copeland","given":"Stella","middleInitial":"M.","affiliations":[{"id":86403,"text":"USDA-Agricultural Research Service, Eastern Oregon Agricultural Research Center, Burns, OR, USA","active":true,"usgs":false}],"preferred":false,"id":949718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baughman, Owen W.","contributorId":361963,"corporation":false,"usgs":false,"family":"Baughman","given":"Owen","middleInitial":"W.","affiliations":[{"id":86404,"text":"The Nature Conservancy, Eastern Oregon Agricultural Research Center, Burns, OR, USA","active":true,"usgs":false}],"preferred":false,"id":949719,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":949720,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hardegree, Stuart P.","contributorId":361964,"corporation":false,"usgs":false,"family":"Hardegree","given":"Stuart","middleInitial":"P.","affiliations":[{"id":86405,"text":"USDA-Agricultural Research Service, Northwest Watershed Research Center, Boise, ID, USA","active":true,"usgs":false}],"preferred":false,"id":949721,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Larson, Julie E.","contributorId":361965,"corporation":false,"usgs":false,"family":"Larson","given":"Julie","middleInitial":"E.","affiliations":[{"id":86403,"text":"USDA-Agricultural Research Service, Eastern Oregon Agricultural Research Center, Burns, OR, USA","active":true,"usgs":false}],"preferred":false,"id":949722,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schlaepfer, Daniel Rodolphe 0000-0001-9973-2065","orcid":"https://orcid.org/0000-0001-9973-2065","contributorId":225569,"corporation":false,"usgs":true,"family":"Schlaepfer","given":"Daniel","email":"","middleInitial":"Rodolphe","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":949723,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Badik, Kevin J.","contributorId":361966,"corporation":false,"usgs":false,"family":"Badik","given":"Kevin","middleInitial":"J.","affiliations":[{"id":86407,"text":"The Nature Conservancy Reno, NV, USA","active":true,"usgs":false}],"preferred":false,"id":949724,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70261169,"text":"fs20243041 - 2024 - topoBuilder quick start guide","interactions":[],"lastModifiedDate":"2024-12-18T15:28:30.229357","indexId":"fs20243041","displayToPublicDate":"2024-12-18T07:04:39","publicationYear":"2024","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":"2024-3041","displayTitle":"topoBuilder Quick Start Guide","title":"topoBuilder quick start guide","docAbstract":"TopoBuilder is a public web application from the National Geospatial Program that enables anyone to create customized digital U.S. Geological Survey (USGS) topographic maps, called OnDemand Topos, with the best available, most up-to-date data from The National Map (nationalmap.gov). OnDemand Topos can be made at different scales or quadrangles and can cover anywhere within the United States and its territories.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20243041","usgsCitation":"Guidero, E.M., Doumbouya, A.T., Adkins, K.F., and Urban-Mathieux, B., 2024, topoBuilder quick start guide: U.S. Geological Survey Fact Sheet 2024–3041, 2 p., https://doi.org/10.3133/fs20243041.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-167174","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":464566,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2024/3041/coverthb.jpg"},{"id":464567,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3041/fs20243041.pdf","text":"Report","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":464568,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2024/3041/fs20243041.XML"},{"id":464569,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2024/3041/images"},{"id":464570,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20243041/full"}],"contact":"Director, National Geospatial Program
U.S. Geological Survey, MS 511
12201 Sunrise Valley Drive
Reston, VA 20192
No abstract available.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2024.110926","usgsCitation":"Petracca, L., Gardner, B., Maletzke, B., and Converse, S.J., 2024, Response to Santiago-Ávila et al. (2024): Biological Conservation, v. 302, 110926, 2 p., https://doi.org/10.1016/j.biocon.2024.110926.","productDescription":"110926, 2 p.","ipdsId":"IP-167848","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":503958,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"302","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Petracca, L.S.","contributorId":351913,"corporation":false,"usgs":false,"family":"Petracca","given":"L.S.","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":960939,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, B.","contributorId":341497,"corporation":false,"usgs":false,"family":"Gardner","given":"B.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":960940,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maletzke, B.T.","contributorId":351917,"corporation":false,"usgs":false,"family":"Maletzke","given":"B.T.","affiliations":[{"id":61815,"text":"wafg","active":true,"usgs":false}],"preferred":false,"id":960941,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":960942,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70261453,"text":"tm9A6.1 - 2024 - Temperature","interactions":[{"subject":{"id":80044,"text":"twri09A6.1 - 2006 - Chapter A6. Section 6.1. Temperature","indexId":"twri09A6.1","publicationYear":"2006","noYear":false,"displayTitle":"Chapter A6. Section 6.1. Temperature","title":"Chapter A6. Section 6.1. Temperature"},"predicate":"SUPERSEDED_BY","object":{"id":70261453,"text":"tm9A6.1 - 2024 - Temperature","indexId":"tm9A6.1","publicationYear":"2024","noYear":false,"title":"Temperature"},"id":1}],"lastModifiedDate":"2024-12-18T15:19:29.063796","indexId":"tm9A6.1","displayToPublicDate":"2024-12-17T13:20:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"9-A6.1","displayTitle":"Temperature","title":"Temperature","docAbstract":"The “National Field Manual for the Collection of Water-Quality Data” (NFM) provides guidelines and procedures for U.S. Geological Survey (USGS) personnel who collect data used to assess the quality of the Nation’s surface-water and groundwater resources. This chapter, NFM A6.1, provides guidance and protocols for the measurement of temperature of air, of a surface-water body or in groundwater, which include the scientific basis of the measurement, selection and maintenance of equipment, calibration verification, troubleshooting, and procedures for measurement and reporting. It updates and supersedes USGS Techniques of Water-Resources Investigations, book 9, chapter A6.1, version 2.0, by Franceska D. Wilde.
Temperature of air and water is routinely measured when water samples are collected, is often measured continually at USGS streamgages, and is a parameter regularly measured during laboratory and field experiments. The field method for measuring temperature described in this chapter is applicable to air and most natural waters.
Before 2017, the NFM chapters were released in the USGS Techniques of Water-Resources Investigations series. Effective in 2018, new and revised NFM chapters are being released in the USGS Techniques and Methods series; this series change does not affect the content and format of the NFM. More information is in the general introduction to the NFM (USGS Techniques and Methods, book 9, chapter A0) at https://doi.org/10.3133/tm9A0. The authoritative current versions of NFM chapters are available in the USGS Publications Warehouse at https://pubs.usgs.gov/. Comments, questions, and suggestions related to the NFM can be addressed to nfm@usgs.gov.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm9A6.1","usgsCitation":"U.S. Geological Survey, 2024, Temperature: U.S. Geological Survey Techniques and Methods, book 9, chap. A6.1, 14 p., https://doi.org/10.3133/tm9A6.1. [Supersedes USGS Techniques of Water-Resources Investigations, book 9, chap. A6.1, version 2.0.]","productDescription":"v, 14 p.","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-157281","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":465033,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/09/a6.1/images"},{"id":465035,"rank":7,"type":{"id":18,"text":"Project Site"},"url":"https://www.usgs.gov/mission-areas/water-resources/science/national-field-manual-collection-water-quality-data-nfm","text":"National Field Manual for the Collection of Water-Quality Data (NFM)"},{"id":465029,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/09/a6.1/coverthb.jpg"},{"id":465030,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/09/a6.1/tm9a6.1.pdf","text":"Report","size":"940 KB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 9-A6.1 PDF"},{"id":465031,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/tm9A6.1/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"TM 9-A6.1 HTML"},{"id":465032,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/09/a6.1/tm9a6.1.XML","linkFileType":{"id":8,"text":"xml"},"description":"TM 9-A6.1 XML"},{"id":465034,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/tm9A0","text":"Techniques and Methods 9-A0","linkHelpText":"- General introduction for the “National Field Manual for the Collection of Water-Quality Data”"}],"contact":"Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Email: nfm@usgs.gov
","tableOfContents":"Walleye Sander vitreus is an important species that has been widely introduced outside of its native distribution. The goal of this study was to assess the effects of an established Walleye population in the Lake Pend Oreille (LPO) system, Idaho.
Food habits of Walleyes were described using stomach contents and stable isotopes (δ15N, δ13C). Trophic structure of the LPO system's food web was identified using stable isotopes. Annual consumption by Walleyes of important prey items was estimated using a bioenergetics model.
Walleyes consumed a diversity of prey items, including macroinvertebrates and fishes. Kokanee Oncorhynchus nerka, the most frequently consumed prey item, occurred in 23% of all Walleye diets. Combined, native cyprinids and catostomids occurred in 31% of all Walleye stomachs. Select taxa (e.g., native cyprinids, kokanee) were consistently consumed by Walleyes across seasons, regions, and cohorts, whereas other taxa (e.g., Westslope Cutthroat Trout O. lewisi, Smallmouth Bass Micropterus dolomieu) were consumed inconsistently. Stable isotope analysis suggested that Walleyes occupied similar trophic positions as other top‐level piscivores in the system. As Walleye age increased, δ15N increased and δ13C decreased, indicating increased consumption of pelagic prey resources and prey at higher trophic positions. The estimated biomass of kokanee consumed annually by Walleyes was 27,121 kg (95% confidence interval = 9178–61,603). Comparatively, native cyprinids represented about 46% of the total biomass of kokanee consumed by Walleyes, whereas native catostomids represented about 11% and native salmonids represented about 15% of the total biomass of kokanee consumed by Walleyes.
This study revealed that Walleyes consumed various fishes across the LPO system. Although kokanee were the most frequently consumed prey item, native cyprinids and catostomids (combined) occurred at similar proportions. This study contributes to our growing knowledge of the effects of nonnative Walleyes on important salmonids and native fishes in western systems.
The Colorado River is an important water source in the southwestern United States and northern Mexico. High concentrations of dissolved solids in the river, sourced mainly from the Upper Colorado River Basin (UCOL), cause hundreds of millions of dollars in damages annually to crops and infrastructure. Determinations of total dissolved solids (TDS) in river and tributary samples often rely on summed concentrations of constituents in solution reported as the sum of constituents (SOC), which includes the bicarbonate concentration converted to the equivalent carbonate mass that would be present as a residue after drying. Alternatively, salinity, similar to SOC but including the entire concentration of bicarbonate in solution, may be used as a measure of dissolved solids. Use of SOC results may under-represent actual dissolved-solids concentrations and loads in streams where bicarbonate is a substantial component of the dissolved solids in solution. The objective of this manuscript is to evaluate the differences between the SOC and salinity determinations of dissolved solids in UCOL streams and rivers. Water-quality data from the U.S. Geological Survey were used to compute salinity concentrations at UCOL stream sites for comparison with SOC determinations. Results from 8,001 samples at 418 UCOL sites indicate a median increase in dissolved solids of 20% (13% and 30%, 25th and 75th percentiles, respectively) using the salinity method compared with SOC results. Differences in dissolved solids attributable to the computational approach for handling bicarbonate at UCOL sites were significantly greater than laboratory variability based on results from 890 replicate analyses. Salinity may be a more useful indicator of water quality than SOC in systems with substantial proportions of bicarbonate in the composition of dissolved solids, including the Colorado River and UCOL sites.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pwat.0000310","usgsCitation":"Tillman, F.D., Miller, M., Wise, D., McCleskey, R., and Day, N.K., 2024, Salinity or sum of constituents— Methods comparison for computing dissolved solids concentrations in streams of the Upper Colorado River Basin: PLOS Water, v. 3, no. 12, e0000310, 13 p., https://doi.org/10.1371/journal.pwat.0000310.","productDescription":"e0000310, 13 p.","ipdsId":"IP-151803","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":466711,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pwat.0000310","text":"Publisher Index Page"},{"id":465280,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","otherGeospatial":"Upper Colorado River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.07478126793694,\n 37.362761189486605\n ],\n [\n -110.7918874182937,\n 35.77503910288557\n ],\n [\n -106.92482149871722,\n 35.26377010349002\n ],\n [\n -105.78177189040801,\n 37.551686330409765\n ],\n [\n -106.7657709766068,\n 38.233772867977024\n ],\n [\n -105.31950823092234,\n 38.84018310941224\n ],\n [\n -104.67840732485422,\n 40.36065226066836\n ],\n [\n -106.71988351439666,\n 42.913593391958784\n ],\n [\n -109.98783943768271,\n 43.360892248620246\n ],\n [\n -110.9078832909733,\n 40.740953521572834\n ],\n [\n -112.07478126793694,\n 37.362761189486605\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"3","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":147809,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred","email":"ftillman@usgs.gov","middleInitial":"D.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":921472,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Matthew P. 0000-0002-2537-1823","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":220622,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew P.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":921473,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wise, Daniel R. 0000-0002-1215-9612","orcid":"https://orcid.org/0000-0002-1215-9612","contributorId":217259,"corporation":false,"usgs":true,"family":"Wise","given":"Daniel","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":921474,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCleskey, R. Blaine 0000-0002-2521-8052","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":205663,"corporation":false,"usgs":true,"family":"McCleskey","given":"R. Blaine","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":921475,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Day, Natalie K. 0000-0002-8768-5705","orcid":"https://orcid.org/0000-0002-8768-5705","contributorId":207302,"corporation":false,"usgs":true,"family":"Day","given":"Natalie","middleInitial":"K.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":921476,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261593,"text":"sir20245113 - 2024 - Perchlorate, metals, organic compounds, and lead isotopes in groundwater, surface water, shallow groundwater, and soil within and near the Middleton Municipal Airport–Morey Field (C29), Middleton, Wisconsin, 2022","interactions":[],"lastModifiedDate":"2025-08-15T16:34:23.184884","indexId":"sir20245113","displayToPublicDate":"2024-12-17T09:08:14","publicationYear":"2024","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":"2024-5113","displayTitle":"Perchlorate, Metals, Organic Compounds, and Lead Isotopes in Groundwater, Surface Water, Shallow Groundwater, and Soil Within and Near the Middleton Municipal Airport–Morey Field (C29), Middleton, Wisconsin, 2022","title":"Perchlorate, metals, organic compounds, and lead isotopes in groundwater, surface water, shallow groundwater, and soil within and near the Middleton Municipal Airport–Morey Field (C29), Middleton, Wisconsin, 2022","docAbstract":"The Middleton Municipal Airport–Morey Field (C29) is in the City of Middleton and adjacent to the towns of Middleton and Springfield, Wisconsin. Nearby homes in the towns rely on private drinking water wells, and residents are concerned about the potential contamination of groundwater and surface water by airport activities, including flights by small aircraft that use leaded aviation fuel and a fireworks display in July 2021.
The U.S. Geological Survey, in cooperation with the Town of Middleton, completed a study in 2022 to characterize the occurrence and sources of perchlorate, metals (including lead), and organic compounds in samples of groundwater, surface water, shallow groundwater, and soils within and near the airport. Lead isotopes were also measured to determine sources of lead by comparing samples to environmental references.
Magnitudes of concentrations from samples of water and soil collected in 2022, and their spatial patterns across site locations, indicate the fireworks display in July 2021 was a likely source of perchlorate and metals in the airport study area. The highest perchlorate concentration was measured in surface water at the southeastern corner of the airport near the fireworks launch site; the highest concentrations of fireworks-associated metals were measured in shallow groundwater near the same location. Fireworks were not the only possible source of perchlorate and metals in the airport study area because both were also detected upgradient and away from the fireworks launch site.
Ratios of lead isotopes indicate that lead measured in water and soil within the airport study area was primarily sourced from background atmospheric lead deposition or Wisconsin galena lead ore. However, two groundwater samples (one upgradient and one downgradient from the airport; both with concentrations less than 1 microgram per liter) had isotopic signatures matching leaded aviation fuel sold at the airport.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245113","collaboration":"Prepared in cooperation with the Town of Middleton, Wisconsin","usgsCitation":"Schachter, L.A., and Stuntebeck, T.D., 2024, Perchlorate, metals, organic compounds, and lead isotopes in groundwater, surface water, shallow groundwater, and soil within and near the Middleton Municipal Airport–Morey Field (C29), Middleton, Wisconsin, 2022: U.S. Geological Survey Scientific Investigations Report 2024–5113, 55 p., https://doi.org/10.3133/sir20245113.","productDescription":"Report: viii, 55 p.; Data Release; Dataset","numberOfPages":"68","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-166313","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":494232,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118085.htm","linkFileType":{"id":5,"text":"html"}},{"id":465140,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245113/full"},{"id":465139,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":465137,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5113/images/"},{"id":465135,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5113/sir20245113.pdf","text":"Report","size":"9.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5113"},{"id":465134,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5113/coverthb.jpg"},{"id":465138,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IEJULZ","text":"USGS data release","linkHelpText":"Lead concentrations and isotope ratios for selected water and soil samples near Middleton Municipal Airport–Morey Field (C29), Middleton, WI, 2022"},{"id":465136,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5113/sir20245113.XML"}],"country":"United States","state":"Wisconsin","city":"Middleton","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.55428476671052,\n 43.12980057216322\n ],\n [\n -89.55428476671052,\n 43.11162168312745\n ],\n [\n -89.51852520964913,\n 43.11162168312745\n ],\n [\n -89.51852520964913,\n 43.12980057216322\n ],\n [\n -89.55428476671052,\n 43.12980057216322\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1992 Folwell Avenue
St. Paul, MN 55108
Long-term drought caused Lake Powell, a reservoir on the Colorado River (USA), to decline to its lowest elevation in >50 years during 2022–2023, allowing warm water to pass through intakes of Glen Canyon Dam and facilitating invasion by non-native Smallmouth Bass (Micropterus dolomieu). Establishment of bass downstream of the dam could threaten persistence of several native fishes, including two federally listed species. Subsequent detection of larval Smallmouth Bass in a spring-fed slough (river mile -12 slough) connected to the river in Glen Canyon National Recreation Area (NRA) increased urgency to stem further invasion. The National Park Service is evaluating proposed actions to limit effects from non-native predators on native species in the Colorado River, including potentially channelizing the slough. This locally rare, spring-fed waterbody provides habitat for other species, including Western Tiger Salamanders (Ambystoma mavortium subsp.) of uncertain origin. We found salamanders from the slough had two distinct mitochondrial DNA haplotypes identical to sequences from nearby Arizona Tiger Salamander (A. m. nebulosum) populations, confirming they are the native genotype. We detected Red-spotted Toads (Anaxyrus punctatus) and Woodhouse’s Toads (A. woodhousii) from three other sites in Glen Canyon NRA and 34 sites in adjacent, downstream Grand Canyon National Park (spanning ∼464 km of river) with environmental DNA and traditional surveys. However, we did not detect salamanders elsewhere, matching prior information that salamanders are rare in the Colorado River corridor below Glen Canyon Dam. Based on this information, we discuss management options for the local population of Arizona Tiger Salamanders.
","language":"English","publisher":"BioRxiv","doi":"10.1101/2024.12.15.628570","usgsCitation":"Hossack, B., Stemp, K.M., Goldberg, C.S., Duke, A.C., Preston, T., Arnold, J.A., and Ray, A.R., 2024, Rare habitats, rare species, and invasive predators highlight management complexities in the Colorado River system: BioRxiv, https://doi.org/10.1101/2024.12.15.628570.","productDescription":"21 p.","ipdsId":"IP-173018","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":496928,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/2024.12.15.628570","text":"External Repository"},{"id":496819,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hossack, Blake 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":207343,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":950844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stemp, Kenzi Marie 0000-0001-7566-8513","orcid":"https://orcid.org/0000-0001-7566-8513","contributorId":362931,"corporation":false,"usgs":true,"family":"Stemp","given":"Kenzi","middleInitial":"Marie","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":950845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goldberg, Caren S","contributorId":362932,"corporation":false,"usgs":false,"family":"Goldberg","given":"Caren","middleInitial":"S","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":950846,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duke, Alexandra C.","contributorId":362933,"corporation":false,"usgs":false,"family":"Duke","given":"Alexandra","middleInitial":"C.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":950847,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Preston, Taryn","contributorId":292557,"corporation":false,"usgs":false,"family":"Preston","given":"Taryn","email":"","affiliations":[{"id":62075,"text":"National Park Service, Grand Canyon National Park","active":true,"usgs":false}],"preferred":false,"id":950848,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Arnold, J. Andrew","contributorId":213088,"corporation":false,"usgs":false,"family":"Arnold","given":"J.","email":"","middleInitial":"Andrew","affiliations":[{"id":36518,"text":"Old Dominion University","active":true,"usgs":false}],"preferred":false,"id":950849,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ray, Adam R","contributorId":148959,"corporation":false,"usgs":false,"family":"Ray","given":"Adam","email":"","middleInitial":"R","affiliations":[{"id":17603,"text":"Department of Fisheries and Wildlife, Oregon State University, 104 Nash Hall, 2820 Southwest Campus Way, Corvallis, OR 97331","active":true,"usgs":false}],"preferred":false,"id":950850,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70261851,"text":"70261851 - 2024 - Bee habitat, but not bee community structure, varies across grassland management in four national parks in the Mid-Atlantic, USA","interactions":[],"lastModifiedDate":"2024-12-31T15:24:53.181359","indexId":"70261851","displayToPublicDate":"2024-12-17T08:49:54","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Bee habitat, but not bee community structure, varies across grassland management in four national parks in the Mid-Atlantic, USA","docAbstract":"National parks in the U.S. play a large role in providing habitat for native pollinators. In parks that are established to preserve cultural landscapes, park managers recognize an opportunity to improve pollinator habitat while maintaining historically accurate conditions. In this study we document floral resources and native bees within managed park grasslands, with the goal of providing managers information to help them maximize pollinator habitat while meeting other management objectives. The study was performed on 37 grassland properties in the mid-Atlantic region of the eastern U.S., distributed across four national parks; each property was managed with one of three management types: cool-season hayed, cool-season pasture, or warm-season meadows managed with multiple approaches. We surveyed bees and open flowers on 50-m transects twice each year in 2021 and 2022. Repeated measures ANOVA models revealed mean bee abundance, richness, evenness, and diversity did not vary among sites or management types. This finding was further supported by a principal coordinates analysis that showed bee community composition was similar across management types. Nonetheless, we found evidence to indicate the three management types did not produce equivalent habitat for bees. Species accumulation curves showed that the effective number of flower species was consistently lower in cool-season pastures, relative to the other two management types. Furthermore, we detected positive correlations between bee and flower diversity metrics in one of the two years, suggesting that floral metrics can influence bee communities, at least under certain conditions. Collectively, our study suggests that cool-season fields that are hayed and warm-season meadows have higher floral diversity than cool-season pastures within national parks of the mid-Atlantic region, and this higher diversity of forbs has the potential to benefit native bee diversity.","language":"English","publisher":"Wiley","doi":"10.1002/ece3.70719","usgsCitation":"Larson, D., Landsman, A.P., Simanonok, M., Larson, J., Davies, C., and Otto, C., 2024, Bee habitat, but not bee community structure, varies across grassland management in four national parks in the Mid-Atlantic, USA: Ecology and Evolution, v. 14, no. 12, e70719, 12 p., https://doi.org/10.1002/ece3.70719.","productDescription":"e70719, 12 p.","ipdsId":"IP-165538","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":466712,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.70719","text":"Publisher Index Page"},{"id":465562,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Antietam National Battlefield, Chesapeake and Ohio Canal National Historical Park, Manassas National Battlefield Park, Monocacy National Battlefield","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -78.87075132703544,\n 38.76343738595514\n ],\n [\n -77.19342578059188,\n 38.76343738595514\n ],\n [\n -77.19342578059188,\n 39.7128528705739\n ],\n [\n -78.87075132703544,\n 39.7128528705739\n ],\n [\n -78.87075132703544,\n 38.76343738595514\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Larson, Diane L. 0000-0001-5202-0634","orcid":"https://orcid.org/0000-0001-5202-0634","contributorId":260165,"corporation":false,"usgs":true,"family":"Larson","given":"Diane L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":922029,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Landsman, Andrew P 0000-0002-4750-819X","orcid":"https://orcid.org/0000-0002-4750-819X","contributorId":291247,"corporation":false,"usgs":false,"family":"Landsman","given":"Andrew","email":"","middleInitial":"P","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":922030,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Simanonok, Michael 0000-0002-4710-4515","orcid":"https://orcid.org/0000-0002-4710-4515","contributorId":228829,"corporation":false,"usgs":false,"family":"Simanonok","given":"Michael","email":"","affiliations":[],"preferred":false,"id":922031,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larson, Jennifer L. 0000-0002-6259-0101","orcid":"https://orcid.org/0000-0002-6259-0101","contributorId":317994,"corporation":false,"usgs":false,"family":"Larson","given":"Jennifer L.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":922032,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davies, Cora","contributorId":347591,"corporation":false,"usgs":false,"family":"Davies","given":"Cora","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":922033,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":922034,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70261814,"text":"70261814 - 2024 - Partly cloudy with a chance of mosquitoes: Developing a flexible approach to forecasting mosquito populations","interactions":[],"lastModifiedDate":"2024-12-26T15:14:45.383291","indexId":"70261814","displayToPublicDate":"2024-12-17T08:05:06","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Partly cloudy with a chance of mosquitoes: Developing a flexible approach to forecasting mosquito populations","docAbstract":"Climate-induced shifts in mosquito phenology and population structure have important implications for the health of humans and wildlife. The timing and intensity of mosquito interactions with infected and susceptible hosts are a primary determinant of vector-borne disease dynamics. Like most ectotherms, rates of mosquito development and corresponding phenological patterns are expected to change under shifting climates. However, developing accurate forecast of mosquito phenology under climate change that can be used to inform management programs remains challenging despite an abundance of available data. As climate change will have variable effects on mosquito demography and phenology across species it is vital that we identify associated traits which may explain the observed variation. Here, we review a suite of modeling approaches that could be applied to generate forecasts of mosquito activity under climate change and evaluate the strengths and weaknesses of the different approaches. We describe four primary life-history and physiological traits that can be used to constrain models and demonstrate how this prior information can be harnessed to develop a more general understanding of how mosquito activity will shift under changing climates. Combining a trait-based approach with appropriate modeling techniques can allow for the development of actionable, flexible, and multi-scale forecasts of mosquito population dynamics and phenology for diverse stakeholders.","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.70074","usgsCitation":"Mcdevitt-Galles, T., DeGaetano, A., Elmendorf, S., Foster, J., Ginsberg, H., Hooten, M.B., LaDeau, S., McClure, K.M., Paull, S.H., Posthumus, E.E., Rochlin, I., and Grear, D.A., 2024, Partly cloudy with a chance of mosquitoes: Developing a flexible approach to forecasting mosquito populations: Ecosphere, v. 15, no. 12, e70074, 17 p., https://doi.org/10.1002/ecs2.70074.","productDescription":"e70074, 17 p.","ipdsId":"IP-155775","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":466713,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70074","text":"Publisher Index Page"},{"id":465460,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.66548403699112,\n 47.19667094970478\n ],\n [\n -88.50420169961106,\n 44.205989638511255\n ],\n [\n -87.90485319328981,\n 41.39073197003515\n ],\n [\n -82.86371026854579,\n 41.70904546715229\n ],\n [\n -82.40184439476982,\n 43.538614110411345\n ],\n [\n -83.49315804844203,\n 46.63943412739803\n ],\n [\n -86.86116175538491,\n 47.49199734956696\n ],\n [\n -88.28863179000962,\n 47.61050307535439\n ],\n [\n -89.66548403699112,\n 47.19667094970478\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Mcdevitt-Galles, Travis 0000-0002-4929-5431","orcid":"https://orcid.org/0000-0002-4929-5431","contributorId":315374,"corporation":false,"usgs":true,"family":"Mcdevitt-Galles","given":"Travis","email":"","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":921903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeGaetano, Arthur 0000-0002-0183-1346","orcid":"https://orcid.org/0000-0002-0183-1346","contributorId":347511,"corporation":false,"usgs":false,"family":"DeGaetano","given":"Arthur","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":921904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elmendorf, Sarah 0000-0003-1085-8521","orcid":"https://orcid.org/0000-0003-1085-8521","contributorId":347512,"corporation":false,"usgs":false,"family":"Elmendorf","given":"Sarah","affiliations":[{"id":83184,"text":"University of Colorado: Boulder","active":true,"usgs":false}],"preferred":false,"id":921905,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Foster, John R. 0000-0002-7526-3177","orcid":"https://orcid.org/0000-0002-7526-3177","contributorId":347513,"corporation":false,"usgs":false,"family":"Foster","given":"John R.","affiliations":[],"preferred":false,"id":921906,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ginsberg, Howard S. 0000-0002-4933-2466","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":347514,"corporation":false,"usgs":false,"family":"Ginsberg","given":"Howard S.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":921907,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hooten, Mevin B. 0000-0002-1614-723X","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":292295,"corporation":false,"usgs":false,"family":"Hooten","given":"Mevin","email":"","middleInitial":"B.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":921908,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"LaDeau, Shannon 0000-0003-4825-5435","orcid":"https://orcid.org/0000-0003-4825-5435","contributorId":347515,"corporation":false,"usgs":false,"family":"LaDeau","given":"Shannon","affiliations":[{"id":36248,"text":"Cary Institute of Ecosystem Studies","active":true,"usgs":false}],"preferred":false,"id":921909,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McClure, Katherine Maria 0000-0001-8595-7677","orcid":"https://orcid.org/0000-0001-8595-7677","contributorId":332279,"corporation":false,"usgs":true,"family":"McClure","given":"Katherine","email":"","middleInitial":"Maria","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":921910,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Paull, S. H. 0000-0001-5589-9568","orcid":"https://orcid.org/0000-0001-5589-9568","contributorId":292340,"corporation":false,"usgs":false,"family":"Paull","given":"S.","email":"","middleInitial":"H.","affiliations":[{"id":62877,"text":"Battelle, National Ecological Observatory Network, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":921911,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Posthumus, Erin E. 0000-0003-3855-2380","orcid":"https://orcid.org/0000-0003-3855-2380","contributorId":204418,"corporation":false,"usgs":false,"family":"Posthumus","given":"Erin","email":"","middleInitial":"E.","affiliations":[{"id":40537,"text":"USA National Phenology Network, National Coordinating Office; University of Arizona, School of Natural Resources and the Environment","active":true,"usgs":false}],"preferred":false,"id":921912,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rochlin, Ilia 0000-0001-7680-6965","orcid":"https://orcid.org/0000-0001-7680-6965","contributorId":347516,"corporation":false,"usgs":false,"family":"Rochlin","given":"Ilia","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":921913,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Grear, Daniel A. 0000-0002-5478-1549 dgrear@usgs.gov","orcid":"https://orcid.org/0000-0002-5478-1549","contributorId":189819,"corporation":false,"usgs":true,"family":"Grear","given":"Daniel","email":"dgrear@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":921914,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70261417,"text":"sim3530 - 2024 - Seabed maps showing topography, ruggedness, backscatter intensity, sediment mobility, and the distribution of geologic substrates in quadrangle 2 of the Stellwagen Bank National Marine Sanctuary region offshore of Boston, Massachusetts","interactions":[],"lastModifiedDate":"2026-04-02T18:59:12.90477","indexId":"sim3530","displayToPublicDate":"2024-12-16T15:35:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3530","displayTitle":"Seabed Maps Showing Topography, Ruggedness, Backscatter Intensity, Sediment Mobility, and the Distribution of Geologic Substrates in Quadrangle 2 of the Stellwagen Bank National Marine Sanctuary Region Offshore of Boston, Massachusetts","title":"Seabed maps showing topography, ruggedness, backscatter intensity, sediment mobility, and the distribution of geologic substrates in quadrangle 2 of the Stellwagen Bank National Marine Sanctuary region offshore of Boston, Massachusetts","docAbstract":"The U.S. Geological Survey, in cooperation with the National Marine Sanctuary Program of the National Oceanic and Atmospheric Administration, has conducted seabed mapping and related research in the Stellwagen Bank National Marine Sanctuary (SBNMS) region since 1993. The area being mapped using geophysical and geological data includes the SBNMS and the surrounding region, which totals approximately 3,700 square kilometers (km2) and is subdivided into 18 quadrangles. The seabed is a glaciated terrain that is topographically and texturally diverse. Quadrangle 2, the subject of this scientific investigations map, has a mapped area of 209 km2 and has water depths that range from about 19 meters (m) on the Stellwagen Bank crest to about 68 m in the Stellwagen Basin. Seven map types, each at a scale of 1:25,000, depict seabed topography, ruggedness, backscatter intensity, distribution of geologic substrates, sediment mobility, distribution of fine- and coarse-grained sand, and substrate mud content. These maps show the distribution of geologic substrates across the southwestern part of Stellwagen Bank, in Stellwagen Basin to the west and southwest of the bank, and in Little Stellwagen Basin and the western part of Race Point Channel to the south of the bank. Interpretations of multibeam sonar bathymetric and seabed backscatter imagery, photographs, video imagery, and grain-size analyses were used to create the geology-based maps. Data from 733 stations were analyzed, including 656 sediment samples. The geologic substrate maps of quadrangle 2 show the distribution of 19 geologic substrates that represent a wide range of textures, such as rippled and immobile sand, immobile muddy sand and sandy mud, sand that partially veneers gravel, and a boulder ridge. Mapped substrates are characterized by sediment grain-size composition, surface morphology, substrate layering, the mobility or immobility of substrate surfaces, and water depth range. This scientific investigations map portrays the major geological elements (substrates, topographic features, and processes) of environments in quadrangle 2. It is intended to provide a foundation for research into present and past sediment transport processes in a complex terrain, provide insights into the ecological requirements of invertebrate and vertebrate species that utilize the various substrates, and support seabed management in the region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3530","collaboration":"Prepared in cooperation with the National Oceanic and Atmospheric Administration","programNote":"Coastal/Marine Hazards and Resources Program","usgsCitation":"Valentine, P.C., and Cross, V.A., 2024, Seabed maps showing topography, ruggedness, backscatter intensity, sediment mobility, and the distribution of geologic substrates in quadrangle 2 of the Stellwagen Bank National Marine Sanctuary region offshore of Boston, Massachusetts: U.S. Geological Survey Scientific Investigations Map 3530, 8 sheets, scale 1:25,000, 27-p. pamphlet, https://doi.org/10.3133/sim3530.","productDescription":"Pamphlet: v, 27 p.; 8 Sheets: 26.98 x 35.69 inches or smaller; Data Release","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-153982","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":499036,"rank":17,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118083.htm","linkFileType":{"id":5,"text":"html"}},{"id":465083,"rank":16,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim3341","text":"Scientific Investigations Map 3341","linkHelpText":"- Seabed maps showing topography, ruggedness, backscatter intensity, sediment mobility, and the distribution of geologic substrates in Quadrangle 6 of the Stellwagen Bank National Marine Sanctuary Region offshore of Boston, Massachusetts"},{"id":465082,"rank":15,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim3515","text":"Scientific Investigations Map 3515","linkHelpText":"- Seabed Maps Showing Topography, Ruggedness, Backscatter Intensity, Sediment Mobility, and the Distribution of Geologic Substrates in Quadrangle 5 of the Stellwagen Bank National Marine Sanctuary Region Offshore of Boston, Massachusetts"},{"id":465080,"rank":13,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3530/sim3530_mapF.pdf","text":"Map F","size":"876 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3530 Map F","linkHelpText":"- Distribution of Fine- and Coarse-Grained Sand and Boulder Ridges"},{"id":465079,"rank":12,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3530/sim3530_mapE.pdf","text":"Map E","size":"882 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3530 Map E","linkHelpText":"- Sediment Mobility"},{"id":465078,"rank":11,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3530/sim3530_mapD2.pdf","text":"Map D, Sheet 2","size":"11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3530 Map D2","linkHelpText":"- Distribution of Geologic Substrates: Seabed geology and sun-illuminated topography"},{"id":502036,"rank":18,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim3544","text":"Scientific Investigations Map 3544","linkHelpText":"- Seabed Maps Showing Topography, Ruggedness, Backscatter Intensity, Sediment Mobility, and the Distribution of Geologic Substrates in Quadrangle 3 of the Stellwagen Bank National Marine Sanctuary Region Offshore of Boston, Massachusetts"},{"id":465081,"rank":14,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3530/sim3530_mapG.pdf","text":"Map G","size":"895 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3530 Map G","linkHelpText":"- Distribution of Substrate Mud Content and Boulder Ridges"},{"id":464927,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UL3LWN","text":"USGS data release","linkHelpText":"Geospatial datasets of seabed topography, sediment mobility, and the distribution of geologic substrates in quadrangle 2 of the Stellwagen Bank National Marine Sanctuary region offshore of Boston, Massachusetts"},{"id":465074,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3530/sim3530_mapA.pdf","text":"Map A","size":"10.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3530 Map A","linkHelpText":"- Sun-Illuminated Topography and Boulder Ridges"},{"id":465077,"rank":10,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3530/sim3530_mapD1.pdf","text":"Map D, Sheet 1","size":"1.47 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3530 Map D1","linkHelpText":"- Distribution of Geologic Substrates: Seabed geology and station data types"},{"id":465076,"rank":9,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3530/sim3530_mapC.pdf","text":"Map C","size":"22.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3530 Map C","linkHelpText":"- Backscatter Intensity and Sun-Illuminated Topography"},{"id":465075,"rank":8,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3530/sim3530_mapB.pdf","text":"Map B","size":"1.06 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3530 Map B","linkHelpText":"- Seabed Ruggedness"},{"id":464926,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sim/3530/images/"},{"id":464925,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sim/3530/sim3530.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIM 3530 XML"},{"id":464924,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sim3530/full","text":"Pamphlet","linkFileType":{"id":5,"text":"html"},"description":"SIM 3530 HTML"},{"id":464923,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3530/sim3530_pamphlet.pdf","text":"Pamphlet","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3530 PDF"},{"id":464922,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3530/coverthb2.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Stellwagen Bank National Marine Sanctuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -70.19346273969718,\n 42.097308493871026\n ],\n [\n -70.19346273969718,\n 42.21157101051443\n ],\n [\n -70.35655387736588,\n 42.21157101051443\n ],\n [\n -70.35655387736588,\n 42.097308493871026\n ],\n [\n -70.19346273969718,\n 42.097308493871026\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543–1598
Objective: Understanding angler responses to fisheries management actions such as regulation changes have important implications for the effectiveness and efficacy of such management strategies. We examined the ability of remote vehicle counters to provide a relative index of angler effort and present a case study demonstrating use of vehicle counters to assess potential changes in angler effort associated with implementation of more restrictive panfish regulations in a subset of Wisconsin lakes.
Methods: We compared vehicle counts with compulsory creel and game-camera based estimates of angler hours and number of angling parties. During 2016, a series of more restrictive panfish regulations were implemented across 132 Wisconsin lakes. We deployed vehicle counters at a subset of lakes within each regulation type during pre- (2015 and 2016) and post-regulation time periods (2021 and 2022) to assess whether the distribution of angler effort (as indexed using vehicle counters) among regulation types may have shifted in response to regulation implementation.
Result: At lakes with paired vehicle counters and compulsory creel data, vehicle counts explained 57-72% of variation in daily angler effort (h) and 65-85% of variation in daily number of angling parties. Across lakes with paired vehicle counters and game cameras, vehicle counters explained 77% of variation in the number of apparent angling parties; however, effectiveness of vehicle counters for explaining variation in number of apparent angling parties varied among lakes. Vehicle counters explained 63-74% of variation in number of apparent angling parties when considering paired vehicle counter-game camera observations pooled within regulation types. We did not observe any systematic shifts in effort indicative of redistribution of angler effort in response to panfish regulations.
Conclusion: Results suggest that, given appropriate validation measures, vehicle counters could be used as a cost-effective tool to index angler effort, particularly when interest lies in understanding effort dynamics over large spatial scales. Our findings suggest a localized scale for implementation of specialized regulations may be appropriate given angler behaviors and preferences for Wisconsin panfish.
","language":"English","publisher":"American Fisheries society","doi":"10.1002/nafm.11054","usgsCitation":"Dembkowski, D., Latzka, A., Feiner, Z., and Isermann, D.A., 2024, Use of vehicle counters to index and evaluate potential shifts in angler effort following implementation of more restrictive panfish regulations in Wisconsin lakes: North American Journal of Fisheries Management, v. 44, no. 6, p. 1342-1357, https://doi.org/10.1002/nafm.11054.","productDescription":"16 p.","startPage":"1342","endPage":"1357","ipdsId":"IP-163236","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480765,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","county":"Vilas County","otherGeospatial":"Escanaba Lake, Nebish Lake, Northern Highland Fishery Research Area","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-88.9879,46.0971],[-88.9329,46.0746],[-88.9332,45.9822],[-89.0478,45.9822],[-89.0477,45.8953],[-89.1091,45.8973],[-89.1752,45.8993],[-89.1754,45.859],[-89.3008,45.8606],[-89.3007,45.9014],[-89.3628,45.8987],[-89.4256,45.8987],[-89.5498,45.8988],[-89.6741,45.8987],[-89.7571,45.8985],[-89.797,45.898],[-89.8199,45.8984],[-89.9212,45.8981],[-89.9846,45.8974],[-90.0428,45.8972],[-90.0442,45.9823],[-90.0134,45.9824],[-89.9853,45.9821],[-89.9289,45.9818],[-89.9282,46.0693],[-89.9288,46.1558],[-89.9287,46.2428],[-89.929,46.3],[-89.7599,46.268],[-89.7368,46.2636],[-89.5829,46.2347],[-89.5331,46.2252],[-89.5133,46.2215],[-89.4272,46.2048],[-89.3759,46.1949],[-89.2666,46.1737],[-89.2302,46.1662],[-89.0854,46.1365],[-88.9879,46.0971]]]},\"properties\":{\"name\":\"Vilas\",\"state\":\"WI\"}}]}","volume":"44","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Dembkowski, Daniel J.","contributorId":275009,"corporation":false,"usgs":false,"family":"Dembkowski","given":"Daniel J.","affiliations":[{"id":33303,"text":"University of Wisconsin Stevens Point","active":true,"usgs":false}],"preferred":false,"id":923832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Latzka, Alexander W.","contributorId":348855,"corporation":false,"usgs":false,"family":"Latzka","given":"Alexander W.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":923833,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feiner, Zachary S.","contributorId":348857,"corporation":false,"usgs":false,"family":"Feiner","given":"Zachary S.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":923834,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923835,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70261327,"text":"sir20245092 - 2024 - Desert Tortoise translocation plan for the U.S. Department of the Army National Training Center and Fort Irwin Western Training Area","interactions":[],"lastModifiedDate":"2025-08-15T16:35:47.148112","indexId":"sir20245092","displayToPublicDate":"2024-12-16T12:46:53","publicationYear":"2024","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":"2024-5092","displayTitle":"Desert Tortoise Translocation Plan for the U.S. Department of the Army National Training Center and Fort Irwin Western Training Area","title":"Desert Tortoise translocation plan for the U.S. Department of the Army National Training Center and Fort Irwin Western Training Area","docAbstract":"The U.S. Department of the Army proposes to commence military activity at the Fort Irwin National Training Center within the Western Training Area (WTA) and to translocate Mojave Desert tortoises (Gopherus agassizii; hereafter tortoise) that will be affected to the Western Training Area Translocation Site (WTATS). This desert tortoise translocation plan provides a timeline of activities, actions for which permits may be required, and guidelines for assessing the short-term and long-term success of this desert tortoise translocation. Importantly, the monitoring projects described are designed to document the ultimate effects of the Army's translocation action (not just inform future translocations elsewhere). Results from the translocation, corresponding monitoring, and research projects will inform future translocations throughout the Mojave Desert for expanding human development. The plan has three main objectives: (1) provide guidelines to achieve a safe, humane, and successful translocation of tortoises from the WTA, with minimal effect to resident desert tortoises at sites where translocated animals are released (recipient sites); (2) study translocated, resident, and reference animals (tortoises living near translocation areas but whose home ranges do not overlap those of translocated or resident tortoises) to learn as much as possible about the ecology, conservation, and management of the desert tortoise; and (3) define best management practices for successful translocation and provide metrics to evaluate success over multiple time scales, which we identify for the short- and long-term.
The procedures to plan, implement, monitor, and study translocation of tortoises were written using terms and conditions outlined in the U.S. Fish and Wildlife Service Biological Opinion 2021 that described effects of the expansion of the military base boundary, as well as recommendations provided in the Desert Tortoise Recovery Plan (and 5-year review). We provide guidance on appropriate translocation timing and procedures, as well as on how tortoise ecology and habitat can best be studied to further knowledge on tortoise translocation. The plan provides analysis for landscape tortoise density and abundance estimates, suitable sites for translocation of tortoises, and short- and long-term metrics that are addressed and measured by specific monitoring and research projects that can be used to assess the success of translocation activities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245092","collaboration":"Prepared in cooperation with the U.S. Department of Defense, U.S. Army Garrison Fort Irwin, California","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Esque, T., Xiong, A., Doyle, S., Murphy, S., Wilhite, C., and Nussear, K., 2024, Desert Tortoise translocation plan for the U.S. Department of the Army National Training Center and Fort Irwin Western Training Area: U.S. Geological Survey Scientific Investigations Report 2024–5092, 94 p., https://doi.org/10.3133/sir20245092.","productDescription":"Report: x, 94 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-159450","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":494233,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118082.htm","linkFileType":{"id":5,"text":"html"}},{"id":465229,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245092/full"},{"id":464818,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5092/images"},{"id":464817,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5092/sir20245092.xml"},{"id":464815,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5092/covrthb.jpg"},{"id":464813,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93ZU0R9","text":"USGS Data Release","description":"Carr, N.B., and Leinwand, I.I.F., 2020, Terrestrial Development Index for the western United States—1-kilometer moving window: U.S. Geological Survey data release, https://doi.org/10.5066/P93ZU0R9.","linkHelpText":"Terrestrial Development Index for the western United States—1-kilometer moving window"},{"id":464816,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5092/sir20245092.pdf","text":"Report","size":"15 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","otherGeospatial":"Fort Irwin Western Training Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.5,\n 35.5\n ],\n [\n -117.5,\n 34.75\n ],\n [\n -116.25,\n 34.75\n ],\n [\n -116.25,\n 35.5\n ],\n [\n -117.5,\n 35.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Climate change coupled with large-scale surface disturbances necessitate active restoration strategies to promote resilient and genetically diverse native plant communities. However, scarcity of native plant materials hinders restoration efforts, leading practitioners to choose from potentially viable but nonlocal seed sources. Genome scans for genetic variation linked with selective environmental gradients have become a useful tool in such efforts, allowing rapid delineation of seed transfer zones along with predictions of genomic vulnerability to climate change. When properly applied, genome scans can reduce the risk of maladaptation due to mismatches between seed source and planting site. However, results are rarely replicated among complimentary data sources. Here, we compared RAD-seq datasets with 819 and 2699 SNPs (in 625 and 356 individuals, respectively) from the Mojave Desert winter annual Chylismia brevipes. Overall, we found that the datasets consistently characterized both neutral population structure and genetic–environmental associations. Ancestry analyses indicated consistent spatial genetic structuring into four regional populations. We also detected a marked signal of isolation by resistance (IBR), wherein spatial genetic structure was better explained by habitat resistance than by geographic distance. Potentially adaptive loci identified from genome scans were associated with the same environmental gradients—fall precipitation, winter minimum temperature, and precipitation timing—regardless of dataset. Paired with our finding that habitat resistance best explained genetic divergence, our results suggest that isolation of populations within environmentally similar habitats—and subsequent local adaption along gradients parallel to these habitats—drive genome-wide divergence in this species. Moreover, strong genetic associations with winter precipitation timing, along with forecasted shifts in precipitation regime due to midcentury climate change, could impact future population dynamics, habitat distribution, and genetic connectivity for C. brevipes populations within the Mojave Desert.
","language":"English","publisher":"Wiley","doi":"10.1111/eva.70046","usgsCitation":"Shryock, D., Lê, N., DeFalco, L., and Esque, T., 2024, Concordant signal of genetic variation across marker densities in the desert annual Chylismia brevipes is linked with timing of winter precipitation: Conservation Genetics, v. 17, no. 12, e70046, 18 p., https://doi.org/10.1111/eva.70046.","productDescription":"e70046, 18 p.","ipdsId":"IP-159454","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":466714,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eva.70046","text":"Publisher Index Page"},{"id":465575,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.2859722224079,\n 38.02841230408214\n ],\n [\n -120.2859722224079,\n 33.84962249242069\n ],\n [\n -113.08194078286547,\n 33.84962249242069\n ],\n [\n -113.08194078286547,\n 38.02841230408214\n ],\n [\n -120.2859722224079,\n 38.02841230408214\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Shryock, Daniel F. 0000-0003-0330-9815 dshryock@usgs.gov","orcid":"https://orcid.org/0000-0003-0330-9815","contributorId":208659,"corporation":false,"usgs":true,"family":"Shryock","given":"Daniel F.","email":"dshryock@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lê, Nila","contributorId":347238,"corporation":false,"usgs":false,"family":"Lê","given":"Nila","affiliations":[{"id":83101,"text":"California Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":922100,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeFalco, Lesley A. 0000-0002-7542-9261","orcid":"https://orcid.org/0000-0002-7542-9261","contributorId":208658,"corporation":false,"usgs":true,"family":"DeFalco","given":"Lesley A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922101,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922102,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70261686,"text":"70261686 - 2024 - Perfluorohexanesulfonic acid (PFHxS) induces hepatotoxicity through the PPAR signaling pathway in larval zebrafish (Danio rerio)","interactions":[],"lastModifiedDate":"2025-01-13T16:24:43.544311","indexId":"70261686","displayToPublicDate":"2024-12-16T10:55:41","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Perfluorohexanesulfonic acid (PFHxS) induces hepatotoxicity through the PPAR signaling pathway in larval zebrafish (Danio rerio)","title":"Perfluorohexanesulfonic acid (PFHxS) induces hepatotoxicity through the PPAR signaling pathway in larval zebrafish (Danio rerio)","docAbstract":"In recent years, the industrial substitution of long-chain per- and polyfluoroalkyl substances (PFAS) with short-chain alternatives has become increasingly prevalent, resulting in the widespread environmental detection of perfluorohexanesulfonic acid (PFHxS), a short-chain PFAS. However, there remains limited information about the potential adverse effects of PFHxS at environmental concentrations to wildlife. Here, early life stage zebrafish (Danio rerio) were exposed to environmentally relevant concentrations of PFHxS to better characterize the adverse effects of PFHxS on aquatic organisms. Nontargeted, transcriptomic analysis revealed potential hepatotoxic effects in exposed larvae, including macrovesicular and microvesicular hepatic steatosis, as well as focal liver necrosis. Morphological, histological, biochemical, and targeted transcript expression profiles further confirmed significant alterations in hepatocellular lesion numbers, liver pathological structures, relative liver size, liver biochemical parameters, and liver function genes. To validate the PPAR-mediated toxicological mechanism identified as an enriched pathway through in silico bioinformatics analysis, we tested the coexposure to an antagonist and PPAR morpholino knockdown. This intervention alleviated PFHxS-induced hepatic effects, including reductions in the levels of aspartate aminotransferase, alanine aminotransferase, total cholesterol, and total triglycerides. Our results demonstrate that environmentally relevant concentrations of PFHxS can impair liver development and function in fish, which could have potential risks to aquatic organisms.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.4c07056","usgsCitation":"Liao, H., He, Y., Zhang, S., Kang, X., Yang, X., Xu, B., Magnuson, J.T., Wang, S., Zheng, C., and Qiu, W., 2024, Perfluorohexanesulfonic acid (PFHxS) induces hepatotoxicity through the PPAR signaling pathway in larval zebrafish (Danio rerio): Environmental Science & Technology, v. 58, no. 52, p. 22894-22906, https://doi.org/10.1021/acs.est.4c07056.","productDescription":"13 p.","startPage":"22894","endPage":"22906","ipdsId":"IP-168048","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":465285,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"52","noUsgsAuthors":false,"publicationDate":"2024-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Liao, Haolin","contributorId":340032,"corporation":false,"usgs":false,"family":"Liao","given":"Haolin","email":"","affiliations":[{"id":81428,"text":"Southern University of Science and Technology - China","active":true,"usgs":false}],"preferred":false,"id":921422,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"He, Ying-Jie","contributorId":340031,"corporation":false,"usgs":false,"family":"He","given":"Ying-Jie","email":"","affiliations":[{"id":81428,"text":"Southern University of Science and Technology - China","active":true,"usgs":false}],"preferred":false,"id":921423,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Shuwen","contributorId":347339,"corporation":false,"usgs":false,"family":"Zhang","given":"Shuwen","email":"","affiliations":[{"id":83142,"text":"Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, Shenzhen, China","active":true,"usgs":false}],"preferred":false,"id":921424,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kang, Xinyuan","contributorId":347340,"corporation":false,"usgs":false,"family":"Kang","given":"Xinyuan","email":"","affiliations":[{"id":83142,"text":"Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, Shenzhen, China","active":true,"usgs":false}],"preferred":false,"id":921425,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yang, Xin","contributorId":340070,"corporation":false,"usgs":false,"family":"Yang","given":"Xin","email":"","affiliations":[],"preferred":false,"id":921426,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Xu, Bentuo","contributorId":329839,"corporation":false,"usgs":false,"family":"Xu","given":"Bentuo","email":"","affiliations":[{"id":78729,"text":"Wenzhou University","active":true,"usgs":false}],"preferred":false,"id":921427,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Magnuson, Jason Tyler 0000-0001-6841-8014","orcid":"https://orcid.org/0000-0001-6841-8014","contributorId":329838,"corporation":false,"usgs":true,"family":"Magnuson","given":"Jason","email":"","middleInitial":"Tyler","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":921428,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wang, Shuping","contributorId":347341,"corporation":false,"usgs":false,"family":"Wang","given":"Shuping","email":"","affiliations":[{"id":83144,"text":"Chinese Research Academy of Environmental Sciences, Beijing, China","active":true,"usgs":false}],"preferred":false,"id":921429,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Zheng, Chunmiao","contributorId":214041,"corporation":false,"usgs":false,"family":"Zheng","given":"Chunmiao","email":"","affiliations":[{"id":16675,"text":"U Alabama","active":true,"usgs":false}],"preferred":false,"id":921430,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Qiu, Wenhui","contributorId":334797,"corporation":false,"usgs":false,"family":"Qiu","given":"Wenhui","email":"","affiliations":[{"id":80251,"text":"Southern University of Science and Technology, China","active":true,"usgs":false}],"preferred":false,"id":921431,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70262812,"text":"70262812 - 2024 - How, what, and where you sample environmental DNA affects diversity estimates and species detection","interactions":[],"lastModifiedDate":"2025-01-23T16:01:32.840937","indexId":"70262812","displayToPublicDate":"2024-12-16T09:50:25","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5840,"text":"Environmental DNA","active":true,"publicationSubtype":{"id":10}},"title":"How, what, and where you sample environmental DNA affects diversity estimates and species detection","docAbstract":"Environmental DNA (eDNA) is a complex mixture of DNA, varying in particle sizes and distributed heterogeneously in aquatic systems. Optimizing eDNA sampling is crucial for maximizing species detection, particularly in high-risk scenarios like invasive species management. In this study, we compare two eDNA sampling methods - namely tow net and grab sample, where the tow nets process large volumes of water (3500–7000 L) through a 64 μm pore size and the grab samples process 1 L sample at a single point through 0.45–1.2 μm pore size membranes. We compared these methods to ascertain what most influences (1) the detection of invasive species (Dreissena mussels and Burmese pythons) using qPCR or ddPCR and (2) total diversity monitoring of metazoan, protist, and fungi community using a COI marker and plant communities using the ITS marker. Sampling was conducted across a wide geography and diverse aquatic environments in Minnesota and Florida, USA, and Switzerland. The tow net samples had significantly higher eDNA yield compared to grab samples; however, they exhibited equal or lower alpha diversity of OTUs (Operational Taxonomic Units). The two sampling methods measured different beta diversity of communities detected with the COI marker across all three regions, highlighting the impact of the sampling method on the diversity of eDNA captured. In comparison, the beta diversity of plant eDNA was less impacted by the sampling method. We found no clear difference in detection for the invasive species targets based on the eDNA sampling method. These results underscore the need for pilot studies before conducting biodiversity inventory and monitoring, and a need for a greater understanding of not just how much, but also what, eDNA is captured depending on method choice, considering both spatial and particle size heterogeneity.
","language":"English","publisher":"Wiley","doi":"10.1002/edn3.70042","usgsCitation":"Kirtane, A., Howard, L., Beaver, C., Hunter, M., Luikart, G., and Deiner, K., 2024, How, what, and where you sample environmental DNA affects diversity estimates and species detection: Environmental DNA, v. 6, no. 6, e70042, 18 p., https://doi.org/10.1002/edn3.70042.","productDescription":"e70042, 18 p.","ipdsId":"IP-164488","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":481043,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/edn3.70042","text":"Publisher Index Page"},{"id":480999,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Switzerland, United States","state":"Florida, Minnesota","otherGeospatial":"Greater Everglades, Lake Bemidji, Lake Constance, Lake Hallwil, Wolf Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.01798404723112,\n 26.550246448677925\n ],\n [\n -81.53599072519242,\n 26.550246448677925\n ],\n [\n -81.53599072519242,\n 25.096468312997132\n ],\n [\n -80.01798404723112,\n 25.096468312997132\n ],\n [\n -80.01798404723112,\n 26.550246448677925\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.89029157031179,\n 47.55346749658318\n ],\n [\n -94.91231460556368,\n 47.44125697369489\n ],\n [\n -94.84279860432603,\n 47.45402343957852\n ],\n [\n -94.790887164091,\n 47.54603420634177\n ],\n [\n -94.89029157031179,\n 47.55346749658318\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.42231636805072,\n 46.84143387368516\n ],\n [\n -95.42231636805072,\n 46.7997449143445\n ],\n [\n -95.35145285614063,\n 46.7997449143445\n ],\n [\n -95.35145285614063,\n 46.84143387368516\n ],\n [\n -95.42231636805072,\n 46.84143387368516\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 9.764414200551101,\n 47.555375259048276\n ],\n [\n 9.139242153384458,\n 47.779117924009995\n ],\n [\n 9.037477332319312,\n 47.82773952502753\n ],\n [\n 8.852018078975334,\n 47.64622984307617\n ],\n [\n 9.414419301934203,\n 47.48258089324767\n ],\n [\n 9.764414200551101,\n 47.47658156173782\n ],\n [\n 9.764414200551101,\n 47.555375259048276\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 8.190367045996055,\n 47.32164406724627\n ],\n [\n 8.190367045996055,\n 47.24371458795892\n ],\n [\n 8.237168205819756,\n 47.24371458795892\n ],\n [\n 8.237168205819756,\n 47.32164406724627\n ],\n [\n 8.190367045996055,\n 47.32164406724627\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"6","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Kirtane, Anish","contributorId":349813,"corporation":false,"usgs":false,"family":"Kirtane","given":"Anish","affiliations":[{"id":83518,"text":"Institute of Biogeochemistry and Pollutant Dynamics, Eidgenössische Technische Hochschule Zürich, Switzerland","active":true,"usgs":false}],"preferred":false,"id":924861,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Howard, Leif","contributorId":349814,"corporation":false,"usgs":false,"family":"Howard","given":"Leif","affiliations":[{"id":83519,"text":"Division of Biological Sciences, Flathead Lake Biology Station, University of Montana","active":true,"usgs":false}],"preferred":false,"id":924862,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beaver, Caitlin 0000-0002-9269-7604","orcid":"https://orcid.org/0000-0002-9269-7604","contributorId":219703,"corporation":false,"usgs":true,"family":"Beaver","given":"Caitlin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":924863,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunter, Margaret 0000-0002-4760-9302","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":207589,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":924864,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luikart, Gordon","contributorId":124531,"corporation":false,"usgs":false,"family":"Luikart","given":"Gordon","affiliations":[{"id":5091,"text":"Flathead Lake Biological Station, Fish and Wildlife Genomics Group, Division of Biological Sciences, University of Montana, Polson, MT 59860, USA","active":true,"usgs":false}],"preferred":false,"id":924865,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Deiner, Kristy","contributorId":176866,"corporation":false,"usgs":false,"family":"Deiner","given":"Kristy","email":"","affiliations":[],"preferred":false,"id":924866,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70261674,"text":"70261674 - 2024 - Northern Great Plains native seed strategy","interactions":[],"lastModifiedDate":"2024-12-18T15:49:10.312152","indexId":"70261674","displayToPublicDate":"2024-12-16T09:45:08","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesNumber":"6","title":"Northern Great Plains native seed strategy","docAbstract":"No abstract available.
","language":"English","publisher":"South Dakota State University","usgsCitation":"Perkins, L., Symstad, A., Zavaleta-Cheek, J., Rohrer, E., and Ehlert, K., 2024, Northern Great Plains native seed strategy, 27 p.","productDescription":"27 p.","ipdsId":"IP-170770","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":465249,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://openprairie.sdstate.edu/nativeplant_news/6/"},{"id":465276,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, Montana, North Dakota, South Dakota, Wyoming","otherGeospatial":"Northern Great Plains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.89600749280534,\n 48.95669012895394\n ],\n [\n -110.00701022506142,\n 47.318500559121645\n ],\n [\n -107.89459357384864,\n 45.01649067418961\n ],\n [\n -105.58122725722289,\n 42.64666032525162\n ],\n [\n -103.77512636846386,\n 42.969903560300054\n ],\n [\n -98.24394876940691,\n 43.00915601967853\n ],\n [\n -96.57995429633301,\n 42.66516479070239\n ],\n [\n -96.46219456413773,\n 43.43226125596277\n ],\n [\n -95.37394352069838,\n 44.53220121284053\n ],\n [\n -96.10444507064126,\n 48.97226434619046\n ],\n [\n -112.89600749280534,\n 48.95669012895394\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Perkins, Lora B.","contributorId":224968,"corporation":false,"usgs":false,"family":"Perkins","given":"Lora B.","affiliations":[{"id":26958,"text":"South Dakota State University, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":921391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Symstad, Amy 0000-0003-4231-2873 asymstad@usgs.gov","orcid":"https://orcid.org/0000-0003-4231-2873","contributorId":201095,"corporation":false,"usgs":true,"family":"Symstad","given":"Amy","email":"asymstad@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":921392,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zavaleta-Cheek, Jennifer","contributorId":347331,"corporation":false,"usgs":false,"family":"Zavaleta-Cheek","given":"Jennifer","email":"","affiliations":[{"id":26958,"text":"South Dakota State University, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":921393,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rohrer, Emily","contributorId":347333,"corporation":false,"usgs":false,"family":"Rohrer","given":"Emily","email":"","affiliations":[{"id":83137,"text":"USDA-NRCS, Rapid City, SD","active":true,"usgs":false}],"preferred":false,"id":921394,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ehlert, Krista","contributorId":347334,"corporation":false,"usgs":false,"family":"Ehlert","given":"Krista","email":"","affiliations":[{"id":83139,"text":"South Dakota State University Extension, Rapid City, SD","active":true,"usgs":false}],"preferred":false,"id":921395,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261618,"text":"70261618 - 2024 - Antibodies to influenza A virus in Lesser (Aythya affinis) and Greater Scaup (Aythya marila) in the USA","interactions":[],"lastModifiedDate":"2024-12-17T15:50:15.832349","indexId":"70261618","displayToPublicDate":"2024-12-16T09:39:33","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Antibodies to influenza A virus in Lesser (Aythya affinis) and Greater Scaup (Aythya marila) in the USA","title":"Antibodies to influenza A virus in Lesser (Aythya affinis) and Greater Scaup (Aythya marila) in the USA","docAbstract":"Scaup, including both Lesser and Greater (Aythya affinis and Aythya marila, respectively), are a grouping of populous and widespread North American diving ducks. Few influenza type A viruses (IAV) have been reported from these species despite a high prevalence of antibodies to IAV being reported. Existing virologic and serologic data indicate that IAV infection routinely occurs in scaup, yet it is unknown which IAV subtypes are linked to these infections. In this study, we aimed to gain a more complete picture of IAV natural history in Lesser and Greater Scaup from two coastal flyways in North America in 2015–18 (302 samples from California in the Pacific Flyway and 471 samples from Maryland in the Atlantic Flyway). Low prevalence of active IAV infection was detected by real-time reverse-transcription PCR in Lesser Scaup sampled in Maryland and California (2.8% and 8.1%, respectively). A single IAV (H1N1) was isolated in embryonated chicken eggs from a bird sampled in California. Similarly low levels were observed in Greater Scaup in California (3.3%). Antibodies to the nucleoprotein as detected with a commercial blocking ELISA were observed in all species and flyway combinations. Antibody seroprevalence estimates were higher in adult Lesser Scaup than in juveniles at both the ≤0.5 (P<0.001, z=–3.582) and ≤0.7 serum-sample-to-negative-control absorbance thresholds (P=0.003, z=–2.996). Neutralizing antibodies to H1–H12, H14, and H15 were detected using a microtiter virus neutralization assay, with the highest prevalence of antibodies against H1 (38%), H6 (36%), and H11 (35%). The high prevalence of antibodies to IAV and evidence of previous exposure to numerous subtypes are consistent with a high level of population immunity and a low prevalence of infection. These results must be interpreted in the context of season (winter sampling), as results may vary with the annual influx of naïve juvenile birds.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/JWD-D-24-00021","usgsCitation":"Huang, H., Poulson, R., Sullivan, J.D., De La Cruz, S.E., Walbridge, H., Stallknecht, D., and Prosser, D., 2024, Antibodies to influenza A virus in Lesser (Aythya affinis) and Greater Scaup (Aythya marila) in the USA: Journal of Wildlife Diseases, v. 60, no. 4, p. 940-949, https://doi.org/10.7589/JWD-D-24-00021.","productDescription":"10 p.","startPage":"940","endPage":"949","ipdsId":"IP-141598","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":465195,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Maryland","county":"Dorchester County","otherGeospatial":"Eden Landing Ecological Reserve, Suisun Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"id\": 1198,\n \"properties\": {\n \"name\": \"Dorchester\",\n \"state\": \"MD\"\n },\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -75.8344,\n 38.7037\n ],\n [\n -75.8403,\n 38.7038\n ],\n [\n -75.8516,\n 38.7017\n ],\n [\n -75.8557,\n 38.7008\n ],\n [\n -75.8569,\n 38.7008\n ],\n [\n -75.8593,\n 38.6999\n ],\n [\n -75.8611,\n 38.6986\n ],\n [\n -75.8628,\n 38.6977\n ],\n [\n -75.8659,\n 38.6955\n ],\n [\n -75.873,\n 38.6924\n ],\n [\n -75.8795,\n 38.6925\n ],\n [\n -75.8859,\n 38.694\n ],\n [\n -75.8947,\n 38.6986\n ],\n [\n -75.8971,\n 38.6977\n ],\n [\n -75.8983,\n 38.6964\n ],\n [\n -75.8989,\n 38.6946\n ],\n [\n -75.9001,\n 38.6919\n ],\n [\n -75.9014,\n 38.6896\n ],\n [\n -75.9038,\n 38.6878\n ],\n [\n -75.9061,\n 38.6874\n ],\n [\n -75.9091,\n 38.6879\n ],\n [\n -75.9126,\n 38.687\n ],\n [\n -75.9144,\n 38.6848\n ],\n [\n -75.9198,\n 38.6817\n ],\n [\n -75.921,\n 38.6817\n ],\n [\n -75.9234,\n 38.679\n ],\n [\n -75.924,\n 38.6786\n ],\n [\n -75.9282,\n 38.6768\n ],\n [\n -75.9299,\n 38.6782\n ],\n [\n -75.934,\n 38.681\n ],\n [\n -75.9367,\n 38.6786\n ],\n [\n -75.9367,\n 38.6781\n ],\n [\n -75.9358,\n 38.6764\n ],\n [\n -75.9361,\n 38.6761\n ],\n [\n -75.9383,\n 38.675\n ],\n [\n -75.9392,\n 38.6758\n ],\n [\n -75.9508,\n 38.6553\n ],\n [\n -75.9486,\n 38.6531\n ],\n [\n -75.9505,\n 38.6507\n ],\n [\n -75.956,\n 38.6445\n ],\n [\n -75.9569,\n 38.6439\n ],\n [\n -75.9328,\n 38.6325\n ],\n [\n -75.9331,\n 38.6322\n ],\n [\n -75.9733,\n 38.6192\n ],\n [\n -75.9583,\n 38.6122\n ],\n [\n -75.9556,\n 38.6117\n ],\n [\n -75.96,\n 38.6108\n ],\n [\n -75.9639,\n 38.6111\n ],\n [\n -75.9675,\n 38.6108\n ],\n [\n -75.9764,\n 38.5864\n ],\n [\n -75.9761,\n 38.5861\n ],\n [\n -75.9742,\n 38.5861\n ],\n [\n -75.9756,\n 38.5842\n ],\n [\n -75.9786,\n 38.5825\n ],\n [\n -75.99,\n 38.5767\n ],\n [\n -75.9897,\n 38.5769\n ],\n [\n -75.9942,\n 38.5828\n ],\n [\n -75.9944,\n 38.5831\n ],\n [\n -75.9989,\n 38.5845\n ],\n [\n -76,\n 38.5844\n ],\n [\n -76.0056,\n 38.5769\n ],\n [\n -76.0053,\n 38.5767\n ],\n [\n -76.013,\n 38.5703\n ],\n [\n -76.0125,\n 38.5697\n ],\n [\n -76.0164,\n 38.5672\n ],\n [\n -76.0172,\n 38.5681\n ],\n [\n -76.0194,\n 38.5667\n ],\n [\n -76.0206,\n 38.5661\n ],\n [\n -76.0233,\n 38.5653\n ],\n [\n -76.0242,\n 38.5636\n ],\n [\n -76.0231,\n 38.5606\n ],\n [\n -76.0244,\n 38.5592\n ],\n [\n -76.0256,\n 38.5619\n ],\n [\n -76.0272,\n 38.5647\n ],\n [\n -76.0297,\n 38.5656\n ],\n [\n -76.0303,\n 38.565\n ],\n [\n -76.0314,\n 38.565\n ],\n [\n -76.0403,\n 38.5625\n ],\n [\n -76.0406,\n 38.5622\n ],\n [\n -76.0425,\n 38.5622\n ],\n [\n -76.0428,\n 38.5619\n ],\n [\n -76.0536,\n 38.565\n ],\n [\n -76.0533,\n 38.565\n ],\n [\n -76.0528,\n 38.5622\n ],\n [\n -76.0569,\n 38.5669\n ],\n [\n -76.06,\n 38.5692\n ],\n [\n -76.0606,\n 38.5692\n ],\n [\n -76.0617,\n 38.5703\n ],\n [\n -76.0633,\n 38.5714\n ],\n [\n -76.0697,\n 38.5736\n ],\n [\n -76.07,\n 38.5733\n ],\n [\n -76.1014,\n 38.5872\n ],\n [\n -76.1114,\n 38.5775\n ],\n [\n -76.125,\n 38.59\n ],\n [\n -76.1392,\n 38.6033\n ],\n [\n -76.1392,\n 38.6042\n ],\n [\n -76.1406,\n 38.6056\n ],\n [\n -76.1467,\n 38.6006\n ],\n [\n -76.1564,\n 38.595\n ],\n [\n -76.1567,\n 38.5947\n ],\n [\n -76.1806,\n 38.5998\n ],\n [\n -76.1839,\n 38.6078\n ],\n [\n -76.1675,\n 38.6061\n ],\n [\n -76.1956,\n 38.6172\n ],\n [\n -76.2025,\n 38.6114\n ],\n [\n -76.205,\n 38.6094\n ],\n [\n -76.2075,\n 38.6044\n ],\n [\n -76.2172,\n 38.6097\n ],\n [\n -76.2175,\n 38.61\n ],\n [\n -76.2372,\n 38.615\n ],\n [\n -76.2375,\n 38.6217\n ],\n [\n -76.2353,\n 38.6236\n ],\n [\n -76.2347,\n 38.6242\n ],\n [\n -76.2406,\n 38.6267\n ],\n [\n -76.2408,\n 38.6263\n ],\n [\n -76.2572,\n 38.6108\n ],\n [\n -76.265,\n 38.6144\n ],\n [\n -76.265,\n 38.6117\n ],\n [\n -76.2686,\n 38.6106\n ],\n [\n -76.2694,\n 38.6089\n ],\n [\n -76.2689,\n 38.6083\n ],\n [\n -76.2739,\n 38.6183\n ],\n [\n -76.2747,\n 38.6183\n ],\n [\n -76.2758,\n 38.6194\n ],\n [\n -76.2811,\n 38.6167\n ],\n [\n -76.2753,\n 38.6042\n ],\n [\n -76.2715,\n 38.6022\n ],\n [\n -76.2718,\n 38.603\n ],\n [\n -76.2611,\n 38.6039\n ],\n [\n -76.2614,\n 38.6036\n ],\n [\n -76.2678,\n 38.5967\n ],\n [\n -76.2731,\n 38.5919\n ],\n [\n -76.2672,\n 38.5842\n ],\n [\n -76.2678,\n 38.5842\n ],\n [\n -76.2747,\n 38.5808\n ],\n [\n -76.2772,\n 38.5778\n ],\n [\n -76.2808,\n 38.5733\n ],\n [\n -76.2808,\n 38.5694\n ],\n [\n -76.2814,\n 38.57\n ],\n [\n -76.3003,\n 38.5719\n ],\n [\n -76.2994,\n 38.5711\n ],\n [\n -76.2867,\n 38.5656\n ],\n [\n -76.272,\n 38.549\n ],\n [\n -76.2714,\n 38.5514\n ],\n [\n -76.2719,\n 38.5519\n ],\n [\n -76.2692,\n 38.5544\n ],\n [\n -76.2714,\n 38.5561\n ],\n [\n -76.2722,\n 38.5569\n ],\n [\n -76.2731,\n 38.5589\n ],\n [\n -76.2731,\n 38.5597\n ],\n [\n -76.2744,\n 38.5625\n ],\n [\n -76.2753,\n 38.5644\n ],\n [\n -76.2733,\n 38.5658\n ],\n [\n -76.2708,\n 38.5708\n ],\n [\n -76.2711,\n 38.5747\n ],\n [\n -76.2689,\n 38.5756\n ],\n [\n -76.2661,\n 38.5739\n ],\n [\n -76.2656,\n 38.5647\n ],\n [\n -76.2656,\n 38.5644\n ],\n [\n -76.2678,\n 38.5622\n ],\n [\n -76.2658,\n 38.5611\n ],\n [\n -76.2647,\n 38.5611\n ],\n [\n -76.2614,\n 38.5519\n ],\n [\n -76.2606,\n 38.5519\n ],\n [\n -76.26,\n 38.5489\n ],\n [\n -76.2567,\n 38.5475\n ],\n [\n -76.2461,\n 38.5378\n ],\n [\n -76.2467,\n 38.5395\n ],\n [\n -76.2481,\n 38.5401\n ],\n [\n -76.2553,\n 38.5514\n ],\n [\n -76.2531,\n 38.5542\n ],\n [\n -76.2536,\n 38.5636\n ],\n [\n -76.25,\n 38.5725\n ],\n [\n -76.2511,\n 38.5761\n ],\n [\n -76.2497,\n 38.5761\n ],\n [\n -76.2539,\n 38.5933\n ],\n [\n -76.2533,\n 38.5933\n ],\n [\n -76.2439,\n 38.5914\n ],\n [\n -76.2436,\n 38.5917\n ],\n [\n -76.2372,\n 38.5947\n ],\n [\n -76.2397,\n 38.5919\n ],\n [\n -76.2411,\n 38.5897\n ],\n [\n -76.2414,\n 38.59\n ],\n [\n -76.2436,\n 38.5808\n ],\n [\n -76.2433,\n 38.5806\n ],\n [\n -76.2433,\n 38.5786\n ],\n [\n -76.2439,\n 38.5725\n ],\n [\n -76.2442,\n 38.5706\n ],\n [\n -76.2403,\n 38.5689\n ],\n [\n -76.2403,\n 38.5675\n ],\n [\n -76.2447,\n 38.5594\n ],\n [\n -76.2419,\n 38.5522\n ],\n [\n -76.2422,\n 38.5525\n ],\n [\n -76.2425,\n 38.5569\n ],\n [\n -76.2414,\n 38.5603\n ],\n [\n -76.2372,\n 38.5617\n ],\n [\n -76.2386,\n 38.555\n ],\n [\n -76.2392,\n 38.5508\n ],\n [\n -76.2408,\n 38.5456\n ],\n [\n -76.2394,\n 38.545\n ],\n [\n -76.2392,\n 38.5447\n ],\n [\n -76.2369,\n 38.5436\n ],\n [\n -76.2378,\n 38.5428\n ],\n [\n -76.2347,\n 38.5417\n ],\n [\n -76.2344,\n 38.5419\n ],\n [\n -76.2353,\n 38.545\n ],\n [\n -76.2361,\n 38.5458\n ],\n [\n -76.2361,\n 38.5478\n ],\n [\n -76.2331,\n 38.5475\n ],\n [\n -76.2267,\n 38.5511\n ],\n [\n -76.2231,\n 38.5531\n ],\n [\n -76.2239,\n 38.5564\n ],\n [\n -76.2247,\n 38.5572\n ],\n [\n -76.2247,\n 38.5611\n ],\n [\n -76.2233,\n 38.5633\n ],\n [\n -76.2203,\n 38.5642\n ],\n [\n -76.221,\n 38.5643\n ],\n [\n -76.2222,\n 38.5667\n ],\n [\n -76.2222,\n 38.5678\n ],\n [\n -76.2289,\n 38.5694\n ],\n [\n -76.2303,\n 38.5708\n ],\n [\n -76.2303,\n 38.5714\n ],\n [\n -76.2292,\n 38.5733\n ],\n [\n -76.2294,\n 38.5778\n ],\n [\n -76.2231,\n 38.5819\n ],\n [\n -76.2192,\n 38.5858\n ],\n [\n -76.2178,\n 38.5875\n ],\n [\n -76.2164,\n 38.5875\n ],\n [\n -76.2161,\n 38.5872\n ],\n [\n -76.2181,\n 38.5839\n ],\n [\n -76.2181,\n 38.5831\n ],\n [\n -76.2265,\n 38.5722\n ],\n [\n -76.2261,\n 38.5719\n ],\n [\n -76.2197,\n 38.5714\n ],\n [\n -76.2186,\n 38.5694\n ],\n [\n -76.2136,\n 38.5678\n ],\n [\n -76.2133,\n 38.5681\n ],\n [\n -76.2108,\n 38.5672\n ],\n [\n -76.2103,\n 38.5672\n ],\n [\n -76.2069,\n 38.5714\n ],\n [\n -76.2069,\n 38.5722\n ],\n [\n -76.2028,\n 38.5789\n ],\n [\n -76.2028,\n 38.585\n ],\n [\n -76.2017,\n 38.5869\n ],\n [\n -76.2,\n 38.5783\n ],\n [\n -76.2003,\n 38.5781\n ],\n [\n -76.2042,\n 38.5703\n ],\n [\n -76.2047,\n 38.5667\n ],\n [\n -76.2044,\n 38.5664\n ],\n [\n -76.2047,\n 38.5639\n ],\n [\n -76.2072,\n 38.5619\n ],\n [\n -76.2014,\n 38.5619\n ],\n [\n -76.2011,\n 38.5622\n ],\n [\n -76.1961,\n 38.5617\n ],\n [\n -76.1969,\n 38.5647\n ],\n [\n -76.1939,\n 38.5625\n ],\n [\n -76.1894,\n 38.5619\n ],\n [\n -76.1856,\n 38.5619\n ],\n [\n -76.1836,\n 38.5631\n ],\n [\n -76.1836,\n 38.5667\n ],\n [\n -76.1792,\n 38.5711\n ],\n [\n -76.1825,\n 38.5858\n ],\n [\n -76.1822,\n 38.5856\n ],\n [\n -76.1806,\n 38.58\n ],\n [\n -76.1793,\n 38.5782\n ],\n [\n -76.1739,\n 38.5747\n ],\n [\n -76.1706,\n 38.5814\n ],\n [\n -76.1647,\n 38.5764\n ],\n [\n -76.1636,\n 38.5764\n ],\n [\n -76.175,\n 38.5714\n ],\n [\n -76.1741,\n 38.5694\n ],\n [\n -76.1767,\n 38.5642\n ],\n [\n -76.1767,\n 38.5636\n ],\n [\n -76.1758,\n 38.5628\n ],\n [\n -76.1719,\n 38.5594\n ],\n [\n -76.1714,\n 38.5594\n ],\n [\n -76.1703,\n 38.5583\n ],\n [\n -76.1778,\n 38.5583\n ],\n [\n -76.1783,\n 38.5583\n ],\n [\n -76.1814,\n 38.5492\n ],\n [\n -76.1814,\n 38.5497\n ],\n [\n -76.1839,\n 38.5558\n ],\n [\n -76.1942,\n 38.5536\n ],\n [\n -76.1947,\n 38.5542\n ],\n [\n -76.1989,\n 38.5539\n ],\n [\n -76.2039,\n 38.5531\n ],\n [\n -76.2089,\n 38.5506\n ],\n [\n -76.2047,\n 38.5356\n ],\n [\n -76.2044,\n 38.5353\n ],\n [\n -76.1992,\n 38.5319\n ],\n [\n -76.195,\n 38.5297\n ],\n [\n -76.1919,\n 38.53\n ],\n [\n -76.1917,\n 38.5303\n ],\n [\n -76.1847,\n 38.5297\n ],\n [\n -76.1844,\n 38.53\n ],\n [\n -76.1825,\n 38.53\n ],\n [\n -76.1822,\n 38.5303\n ],\n [\n -76.1792,\n 38.5303\n ],\n [\n -76.1758,\n 38.5364\n ],\n [\n -76.175,\n 38.5356\n ],\n [\n -76.175,\n 38.5336\n ],\n [\n -76.1728,\n 38.5328\n ],\n [\n -76.1703,\n 38.5328\n ],\n [\n -76.1631,\n 38.5339\n ],\n [\n -76.1597,\n 38.5353\n ],\n [\n -76.1583,\n 38.5347\n ],\n [\n -76.1581,\n 38.5344\n ],\n [\n -76.1544,\n 38.5356\n ],\n [\n -76.1503,\n 38.5339\n ],\n [\n -76.1497,\n 38.5339\n ],\n [\n -76.1486,\n 38.535\n ],\n [\n -76.1467,\n 38.5392\n ],\n [\n -76.1461,\n 38.5398\n ],\n [\n -76.1464,\n 38.5417\n ],\n [\n -76.1381,\n 38.5417\n ],\n [\n -76.1366,\n 38.5418\n ],\n [\n -76.1358,\n 38.5408\n ],\n [\n -76.1364,\n 38.5403\n ],\n [\n -76.1442,\n 38.5328\n ],\n [\n -76.1439,\n 38.5325\n ],\n [\n -76.1433,\n 38.5294\n ],\n [\n -76.135,\n 38.5297\n ],\n [\n -76.1366,\n 38.5283\n ],\n [\n -76.1433,\n 38.5225\n ],\n [\n -76.1531,\n 38.5297\n ],\n [\n -76.1578,\n 38.5289\n ],\n [\n -76.1578,\n 38.5281\n ],\n [\n -76.1592,\n 38.5247\n ],\n [\n -76.1586,\n 38.5253\n ],\n [\n -76.1592,\n 38.5283\n ],\n [\n -76.1603,\n 38.5317\n ],\n [\n -76.1717,\n 38.5294\n ],\n [\n -76.1719,\n 38.5297\n ],\n [\n -76.1758,\n 38.5114\n ],\n [\n -76.1758,\n 38.5111\n ],\n [\n -76.17,\n 38.5069\n ],\n [\n -76.1678,\n 38.5061\n ],\n [\n -76.1594,\n 38.5017\n ],\n [\n -76.1622,\n 38.5028\n ],\n [\n -76.1761,\n 38.5075\n ],\n [\n -76.1764,\n 38.5072\n ],\n [\n -76.1803,\n 38.5078\n ],\n [\n -76.1806,\n 38.5078\n ],\n [\n -76.1833,\n 38.5064\n ],\n [\n -76.18,\n 38.5103\n ],\n [\n -76.1806,\n 38.5239\n ],\n [\n -76.1808,\n 38.5269\n ],\n [\n -76.1811,\n 38.5272\n ],\n [\n -76.1844,\n 38.5267\n ],\n [\n -76.1867,\n 38.5258\n ],\n [\n -76.1869,\n 38.5261\n ],\n [\n -76.1925,\n 38.524\n ],\n [\n -76.1933,\n 38.5206\n ],\n [\n -76.1933,\n 38.52\n ],\n [\n -76.1953,\n 38.5208\n ],\n [\n -76.2081,\n 38.5247\n ],\n [\n -76.2081,\n 38.525\n ],\n [\n -76.2064,\n 38.5267\n ],\n [\n -76.2083,\n 38.5292\n ],\n [\n -76.2178,\n 38.5375\n ],\n [\n -76.2142,\n 38.5267\n ],\n [\n -76.2153,\n 38.5228\n ],\n [\n -76.2139,\n 38.5197\n ],\n [\n -76.2171,\n 38.5133\n ],\n [\n -76.2217,\n 38.5106\n ],\n [\n -76.2269,\n 38.5181\n ],\n [\n -76.2286,\n 38.5189\n ],\n [\n -76.2286,\n 38.5194\n ],\n [\n -76.23,\n 38.5261\n ],\n [\n -76.2306,\n 38.5256\n ],\n [\n -76.2369,\n 38.5222\n ],\n [\n -76.2383,\n 38.52\n ],\n [\n -76.2381,\n 38.5197\n ],\n [\n -76.2383,\n 38.5167\n ],\n [\n -76.2383,\n 38.5156\n ],\n [\n -76.2389,\n 38.515\n ],\n [\n -76.2386,\n 38.5094\n ],\n [\n -76.2428,\n 38.5136\n ],\n [\n -76.2422,\n 38.5142\n ],\n [\n -76.2442,\n 38.5197\n ],\n [\n -76.2433,\n 38.5219\n ],\n [\n -76.2472,\n 38.5233\n ],\n [\n -76.2475,\n 38.5233\n ],\n [\n -76.2611,\n 38.5017\n ],\n [\n -76.2606,\n 38.5017\n ],\n [\n -76.2594,\n 38.5006\n ],\n [\n -76.2597,\n 38.4986\n ],\n [\n -76.2608,\n 38.4917\n ],\n [\n -76.2675,\n 38.4975\n ],\n [\n -76.2769,\n 38.4911\n ],\n [\n -76.2786,\n 38.4881\n ],\n [\n -76.2794,\n 38.4872\n ],\n [\n -76.2864,\n 38.4767\n ],\n [\n -76.2889,\n 38.4714\n ],\n [\n -76.2807,\n 38.459\n ],\n [\n -76.2764,\n 38.4517\n ],\n [\n -76.2775,\n 38.4517\n ],\n [\n -76.2828,\n 38.4547\n ],\n [\n -76.2831,\n 38.4547\n ],\n [\n -76.2919,\n 38.4661\n ],\n [\n -76.2919,\n 38.4667\n ],\n [\n -76.2939,\n 38.4694\n ],\n [\n -76.3003,\n 38.4742\n ],\n [\n -76.3003,\n 38.4744\n ],\n [\n -76.3008,\n 38.4769\n ],\n [\n -76.2975,\n 38.4733\n ],\n [\n -76.2928,\n 38.4797\n ],\n [\n -76.2831,\n 38.4942\n ],\n [\n -76.2842,\n 38.4972\n ],\n [\n -76.2844,\n 38.4975\n ],\n [\n -76.2872,\n 38.4969\n ],\n [\n -76.2883,\n 38.5\n ],\n [\n -76.3128,\n 38.4936\n ],\n [\n -76.313,\n 38.4936\n ],\n [\n -76.3242,\n 38.4925\n ],\n [\n -76.3261,\n 38.4867\n ],\n [\n -76.3331,\n 38.485\n ],\n [\n -76.3319,\n 38.4744\n ],\n [\n -76.3319,\n 38.4742\n ],\n [\n -76.3217,\n 38.4622\n ],\n [\n -76.3217,\n 38.4619\n ],\n [\n -76.32,\n 38.4603\n ],\n [\n -76.3203,\n 38.46\n ],\n [\n -76.3142,\n 38.4569\n ],\n [\n -76.3144,\n 38.4567\n ],\n [\n -76.3128,\n 38.4533\n ],\n [\n -76.3061,\n 38.4461\n ],\n [\n -76.3061,\n 38.4458\n ],\n [\n -76.3011,\n 38.4389\n ],\n [\n -76.2867,\n 38.4206\n ],\n [\n -76.2814,\n 38.4106\n ],\n [\n -76.2811,\n 38.4103\n ],\n [\n -76.2825,\n 38.3925\n ],\n [\n -76.2789,\n 38.3867\n ],\n [\n -76.2783,\n 38.3861\n ],\n [\n -76.2728,\n 38.3786\n ],\n [\n -76.2728,\n 38.3775\n ],\n [\n -76.2336,\n 38.3375\n ],\n [\n -76.2325,\n 38.3225\n ],\n [\n -76.2317,\n 38.3225\n ],\n [\n -76.2297,\n 38.3189\n ],\n [\n -76.2294,\n 38.3186\n ],\n [\n -76.2294,\n 38.3167\n ],\n [\n -76.2297,\n 38.3164\n ],\n [\n -76.2267,\n 38.3106\n ],\n [\n -76.2094,\n 38.3006\n ],\n [\n -76.2106,\n 38.3039\n ],\n [\n -76.2281,\n 38.3231\n ],\n [\n -76.2217,\n 38.3164\n ],\n [\n -76.2206,\n 38.3164\n ],\n [\n -76.2194,\n 38.3189\n ],\n [\n -76.2217,\n 38.3244\n ],\n [\n -76.22,\n 38.3292\n ],\n [\n -76.2172,\n 38.3339\n ],\n [\n -76.2169,\n 38.3339\n ],\n [\n -76.2144,\n 38.3317\n ],\n [\n -76.2133,\n 38.3292\n ],\n [\n -76.2117,\n 38.3286\n ],\n [\n -76.2108,\n 38.3289\n ],\n [\n -76.2169,\n 38.3369\n ],\n [\n -76.2233,\n 38.3464\n ],\n [\n -76.2236,\n 38.3464\n ],\n [\n -76.23,\n 38.3589\n ],\n [\n -76.2328,\n 38.3642\n ],\n [\n -76.2336,\n 38.365\n ],\n [\n -76.2322,\n 38.3672\n ],\n [\n -76.2328,\n 38.3739\n ],\n [\n -76.2325,\n 38.3758\n ],\n [\n -76.2317,\n 38.3778\n ],\n [\n -76.2136,\n 38.38\n ],\n [\n -76.215,\n 38.375\n ],\n [\n -76.2183,\n 38.3719\n ],\n [\n -76.2192,\n 38.3705\n ],\n [\n -76.2181,\n 38.3675\n ],\n [\n -76.2083,\n 38.3747\n ],\n [\n -76.2083,\n 38.3753\n ],\n [\n -76.2097,\n 38.3767\n ],\n [\n -76.2103,\n 38.3767\n ],\n [\n -76.2078,\n 38.3813\n ],\n [\n -76.1675,\n 38.335\n ],\n [\n -76.1608,\n 38.3469\n ],\n [\n -76.1597,\n 38.3425\n ],\n [\n -76.1611,\n 38.3405\n ],\n [\n -76.1625,\n 38.3361\n ],\n [\n -76.1625,\n 38.335\n ],\n [\n -76.1606,\n 38.3333\n ],\n [\n -76.1536,\n 38.3214\n ],\n [\n -76.1576,\n 38.3209\n ],\n [\n -76.1674,\n 38.3217\n ],\n [\n -76.1756,\n 38.33\n ],\n [\n -76.1781,\n 38.3339\n ],\n [\n -76.1856,\n 38.3339\n ],\n [\n -76.1883,\n 38.3319\n ],\n [\n -76.1942,\n 38.3256\n ],\n [\n -76.1986,\n 38.3256\n ],\n [\n -76.1967,\n 38.3206\n ],\n [\n -76.1964,\n 38.3203\n ],\n [\n -76.1917,\n 38.3175\n ],\n [\n -76.1775,\n 38.3247\n ],\n [\n -76.1772,\n 38.3244\n ],\n [\n -76.1697,\n 38.3208\n ],\n [\n -76.1344,\n 38.3003\n ],\n [\n -76.1394,\n 38.2989\n ],\n [\n -76.14,\n 38.2983\n ],\n [\n -76.1386,\n 38.295\n ],\n [\n -76.1486,\n 38.2781\n ],\n [\n -76.1489,\n 38.2778\n ],\n [\n -76.1492,\n 38.2742\n ],\n [\n -76.1497,\n 38.2736\n ],\n [\n -76.1475,\n 38.2772\n ],\n [\n -76.1236,\n 38.3006\n ],\n [\n -76.1114,\n 38.2975\n ],\n [\n -76.1108,\n 38.2935\n ],\n [\n -76.1117,\n 38.2931\n ],\n [\n -76.1072,\n 38.2889\n ],\n [\n -76.0997,\n 38.2917\n ],\n [\n -76.0991,\n 38.2836\n ],\n [\n -76.0994,\n 38.2833\n ],\n [\n -76.0994,\n 38.2814\n ],\n [\n -76.0997,\n 38.2806\n ],\n [\n -76.0978,\n 38.2802\n ],\n [\n -76.0833,\n 38.2786\n ],\n [\n -76.0842,\n 38.2786\n ],\n [\n -76.0867,\n 38.2761\n ],\n [\n -76.0864,\n 38.2758\n ],\n [\n -76.0891,\n 38.2725\n ],\n [\n -76.0886,\n 38.2719\n ],\n [\n -76.0836,\n 38.2647\n ],\n [\n -76.0917,\n 38.2625\n ],\n [\n -76.1025,\n 38.26\n ],\n [\n -76.0983,\n 38.2539\n ],\n [\n -76.0981,\n 38.2542\n ],\n [\n -76.0811,\n 38.2525\n ],\n [\n -76.0764,\n 38.2553\n ],\n [\n -76.0742,\n 38.2503\n ],\n [\n -76.0739,\n 38.25\n ],\n [\n -76.0711,\n 38.2414\n ],\n [\n -76.0586,\n 38.2283\n ],\n [\n -76.0486,\n 38.2256\n ],\n [\n -76.0361,\n 38.2319\n ],\n [\n -76.0398,\n 38.2342\n ],\n [\n -76.0564,\n 38.2511\n ],\n [\n -76.0394,\n 38.2553\n ],\n [\n -76.0344,\n 38.2708\n ],\n [\n -76.0369,\n 38.2733\n ],\n [\n -76.0272,\n 38.2806\n ],\n [\n -76.0286,\n 38.2822\n ],\n [\n -76.0306,\n 38.2864\n ],\n [\n -76.0372,\n 38.2922\n ],\n [\n -76.0525,\n 38.3042\n ],\n [\n -76.0528,\n 38.3039\n ],\n [\n -76.0567,\n 38.3047\n ],\n [\n -76.0508,\n 38.3092\n ],\n [\n -76.0486,\n 38.3111\n ],\n [\n -76.0486,\n 38.3119\n ],\n [\n -76.0481,\n 38.3147\n ],\n [\n -76.0458,\n 38.3175\n ],\n [\n -76.0403,\n 38.3222\n ],\n [\n -76.04,\n 38.3225\n ],\n [\n -76.0342,\n 38.3236\n ],\n [\n -76.0139,\n 38.3436\n ],\n [\n -76.0128,\n 38.3481\n ],\n [\n -76.0125,\n 38.3483\n ],\n [\n -76.0122,\n 38.3508\n ],\n [\n -76.0111,\n 38.3542\n ],\n [\n -76.0211,\n 38.3614\n ],\n [\n -76.0213,\n 38.3623\n ],\n [\n -76.0317,\n 38.3581\n ],\n [\n -76.0333,\n 38.3581\n ],\n [\n -76.0339,\n 38.3536\n ],\n [\n -76.0347,\n 38.3528\n ],\n [\n -76.0353,\n 38.3533\n ],\n [\n -76.0106,\n 38.3636\n ],\n [\n -76.0064,\n 38.3667\n ],\n [\n -76.0053,\n 38.3678\n ],\n [\n -76.0075,\n 38.37\n ],\n [\n -76.0122,\n 38.3728\n ],\n [\n -76.0131,\n 38.3747\n ],\n [\n -76.0072,\n 38.3742\n ],\n [\n -76.0069,\n 38.3739\n ],\n [\n -76.0041,\n 38.3742\n ],\n [\n -76.0025,\n 38.3131\n ],\n [\n -76.0056,\n 38.3125\n ],\n [\n -76.0058,\n 38.3122\n ],\n [\n -76.0131,\n 38.3108\n ],\n [\n -76.0179,\n 38.3096\n ],\n [\n -76.0164,\n 38.3081\n ],\n [\n -76.0169,\n 38.3068\n ],\n [\n -76.0159,\n 38.3069\n ],\n [\n -76.0078,\n 38.3042\n ],\n [\n -76.0019,\n 38.2949\n ],\n [\n -75.999,\n 38.293\n ],\n [\n -75.9983,\n 38.2925\n ],\n [\n -75.9958,\n 38.2889\n ],\n [\n -75.9914,\n 38.2842\n ],\n [\n -75.9911,\n 38.2842\n ],\n [\n -75.9886,\n 38.28\n ],\n [\n -75.9839,\n 38.2769\n ],\n [\n -75.9781,\n 38.2753\n ],\n [\n -75.9783,\n 38.275\n ],\n [\n -75.9817,\n 38.2742\n ],\n [\n -75.9825,\n 38.2722\n ],\n [\n -75.9825,\n 38.2719\n ],\n [\n -75.9831,\n 38.2675\n ],\n [\n -75.9619,\n 38.2522\n ],\n [\n -75.9594,\n 38.2497\n ],\n [\n -75.96,\n 38.2492\n ],\n [\n -75.9611,\n 38.2503\n ],\n [\n -75.9606,\n 38.2453\n ],\n [\n -75.9581,\n 38.2461\n ],\n [\n -75.9572,\n 38.2417\n ],\n [\n -75.9594,\n 38.2386\n ],\n [\n -75.9658,\n 38.2392\n ],\n [\n -75.9695,\n 38.2358\n ],\n [\n -75.9653,\n 38.2347\n ],\n [\n -75.965,\n 38.235\n ],\n [\n -75.9594,\n 38.2358\n ],\n [\n -75.9592,\n 38.2361\n ],\n [\n -75.9494,\n 38.2378\n ],\n [\n -75.9489,\n 38.2378\n ],\n [\n -75.9453,\n 38.2422\n ],\n [\n -75.9422,\n 38.2442\n ],\n [\n -75.9411,\n 38.2453\n ],\n [\n -75.9429,\n 38.2482\n ],\n [\n -75.9436,\n 38.2489\n ],\n [\n -75.9531,\n 38.2606\n ],\n [\n -75.955,\n 38.2619\n ],\n [\n -75.9572,\n 38.2614\n ],\n [\n -75.9578,\n 38.2619\n ],\n [\n -75.9589,\n 38.2619\n ],\n [\n -75.9583,\n 38.2633\n ],\n [\n -75.9567,\n 38.2625\n ],\n [\n -75.9561,\n 38.2625\n ],\n [\n -75.8808,\n 38.3544\n ],\n [\n -75.8789,\n 38.3533\n ],\n [\n -75.8639,\n 38.3631\n ],\n [\n -75.8639,\n 38.3644\n ],\n [\n -75.8658,\n 38.3669\n ],\n [\n -75.8669,\n 38.3689\n ],\n [\n -75.8669,\n 38.3692\n ],\n [\n -75.8689,\n 38.3714\n ],\n [\n -75.8708,\n 38.3769\n ],\n [\n -75.8625,\n 38.3847\n ],\n [\n -75.8606,\n 38.3864\n ],\n [\n -75.8583,\n 38.3875\n ],\n [\n -75.8572,\n 38.3886\n ],\n [\n -75.8561,\n 38.3903\n ],\n [\n -75.8561,\n 38.3897\n ],\n [\n -75.855,\n 38.3886\n ],\n [\n -75.8456,\n 38.3872\n ],\n [\n -75.8519,\n 38.3972\n ],\n [\n -75.8533,\n 38.4003\n ],\n [\n -75.8511,\n 38.4097\n ],\n [\n -75.8406,\n 38.425\n ],\n [\n -75.8403,\n 38.4253\n ],\n [\n -75.8369,\n 38.4253\n ],\n [\n -75.8367,\n 38.425\n ],\n [\n -75.8339,\n 38.425\n ],\n [\n -75.8336,\n 38.4247\n ],\n [\n -75.8303,\n 38.4242\n ],\n [\n -75.8281,\n 38.4247\n ],\n [\n -75.836,\n 38.4427\n ],\n [\n -75.8367,\n 38.4433\n ],\n [\n -75.8366,\n 38.4445\n ],\n [\n -75.8381,\n 38.4469\n ],\n [\n -75.8383,\n 38.4472\n ],\n [\n -75.8369,\n 38.4544\n ],\n [\n -75.8364,\n 38.4564\n ],\n [\n -75.8325,\n 38.46\n ],\n [\n -75.8322,\n 38.4597\n ],\n [\n -75.8269,\n 38.4625\n ],\n [\n -75.8267,\n 38.4628\n ],\n [\n -75.8239,\n 38.4628\n ],\n [\n -75.8236,\n 38.4631\n ],\n [\n -75.8181,\n 38.4683\n ],\n [\n -75.8203,\n 38.4706\n ],\n [\n -75.8208,\n 38.4706\n ],\n [\n -75.8222,\n 38.4719\n ],\n [\n -75.8258,\n 38.4769\n ],\n [\n -75.8261,\n 38.4772\n ],\n [\n -75.8217,\n 38.4844\n ],\n [\n -75.8217,\n 38.4847\n ],\n [\n -75.8147,\n 38.4894\n ],\n [\n -75.8067,\n 38.4922\n ],\n [\n -75.8064,\n 38.4925\n ],\n [\n -75.7992,\n 38.4928\n ],\n [\n -75.7992,\n 38.4931\n ],\n [\n -75.7961,\n 38.4933\n ],\n [\n -75.7944,\n 38.4944\n ],\n [\n -75.7942,\n 38.4944\n ],\n [\n -75.7725,\n 38.5061\n ],\n [\n -75.7715,\n 38.5061\n ],\n [\n -75.7671,\n 38.5069\n ],\n [\n -75.7564,\n 38.5181\n ],\n [\n -75.7633,\n 38.5278\n ],\n [\n -75.7661,\n 38.5317\n ],\n [\n -75.7625,\n 38.5364\n ],\n [\n -75.7622,\n 38.5367\n ],\n [\n -75.7583,\n 38.5381\n ],\n [\n -75.7586,\n 38.5381\n ],\n [\n -75.7614,\n 38.5408\n ],\n [\n -75.7647,\n 38.5456\n ],\n [\n -75.7692,\n 38.5469\n ],\n [\n -75.7694,\n 38.5472\n ],\n [\n -75.7728,\n 38.5547\n ],\n [\n -75.77,\n 38.5561\n ],\n [\n -75.7728,\n 38.5625\n ],\n [\n -75.7731,\n 38.5628\n ],\n [\n -75.8069,\n 38.5903\n ],\n [\n -75.8153,\n 38.5978\n ],\n [\n -75.8153,\n 38.5981\n ],\n [\n -75.82,\n 38.6006\n ],\n [\n -75.8206,\n 38.6011\n ],\n [\n -75.8239,\n 38.6036\n ],\n [\n -75.8233,\n 38.6067\n ],\n [\n -75.8236,\n 38.6069\n ],\n [\n -75.8236,\n 38.6125\n ],\n [\n -75.8242,\n 38.6158\n ],\n [\n -75.8219,\n 38.6178\n ],\n [\n -75.8203,\n 38.6247\n ],\n [\n -75.8206,\n 38.625\n ],\n [\n -75.8172,\n 38.6339\n ],\n [\n -75.8133,\n 38.6378\n ],\n [\n -75.8128,\n 38.6378\n ],\n [\n -75.8106,\n 38.6389\n ],\n [\n -75.8142,\n 38.6358\n ],\n [\n -75.8178,\n 38.6236\n ],\n [\n -75.8189,\n 38.6197\n ],\n [\n -75.8189,\n 38.6192\n ],\n [\n -75.8214,\n 38.6117\n ],\n [\n -75.8214,\n 38.6081\n ],\n [\n -75.8222,\n 38.6061\n ],\n [\n -75.8225,\n 38.6058\n ],\n [\n -75.8214,\n 38.6025\n ],\n [\n -75.8211,\n 38.6022\n ],\n [\n -75.7961,\n 38.5861\n ],\n [\n -75.7956,\n 38.5844\n ],\n [\n -75.7953,\n 38.5842\n ],\n [\n -75.795,\n 38.5783\n ],\n [\n -75.7806,\n 38.5739\n ],\n [\n -75.7775,\n 38.5706\n ],\n [\n -75.7769,\n 38.57\n ],\n [\n -75.7692,\n 38.5608\n ],\n [\n -75.7689,\n 38.5608\n ],\n [\n -75.7661,\n 38.5572\n ],\n [\n -75.7661,\n 38.5567\n ],\n [\n -75.7703,\n 38.5544\n ],\n [\n -75.7714,\n 38.5489\n ],\n [\n -75.7711,\n 38.5486\n ],\n [\n -75.7625,\n 38.5442\n ],\n [\n -75.7586,\n 38.5408\n ],\n [\n -75.7561,\n 38.5369\n ],\n [\n -75.7603,\n 38.535\n ],\n [\n -75.7606,\n 38.5353\n ],\n [\n -75.7628,\n 38.5353\n ],\n [\n -75.7636,\n 38.53\n ],\n [\n -75.7603,\n 38.5294\n ],\n [\n -75.7578,\n 38.5297\n ],\n [\n -75.7567,\n 38.5297\n ],\n [\n -75.7447,\n 38.5383\n ],\n [\n -75.7261,\n 38.5408\n ],\n [\n -75.7258,\n 38.5408\n ],\n [\n -75.7228,\n 38.5439\n ],\n [\n -75.7225,\n 38.5439\n ],\n [\n -75.7139,\n 38.5508\n ],\n [\n -75.7136,\n 38.5508\n ],\n [\n -75.7088,\n 38.5584\n ],\n [\n -75.7088,\n 38.5605\n ],\n [\n -75.7052,\n 38.5618\n ],\n [\n -75.702,\n 38.5622\n ],\n [\n -75.7036,\n 38.579\n ],\n [\n -75.7069,\n 38.5976\n ],\n [\n -75.7095,\n 38.6371\n ],\n [\n -75.7392,\n 38.6643\n ],\n [\n -75.7439,\n 38.6666\n ],\n [\n -75.7468,\n 38.668\n ],\n [\n -75.748,\n 38.668\n ],\n [\n -75.7641,\n 38.686\n ],\n [\n -75.767,\n 38.6855\n ],\n [\n -75.7712,\n 38.682\n ],\n [\n -75.7719,\n 38.6802\n ],\n [\n -75.7725,\n 38.677\n ],\n [\n -75.7749,\n 38.6761\n ],\n [\n -75.7955,\n 38.6769\n ],\n [\n -75.7965,\n 38.6869\n ],\n [\n -75.7969,\n 38.695\n ],\n [\n -75.8021,\n 38.6969\n ],\n [\n -75.8162,\n 38.6985\n ],\n [\n -75.8257,\n 38.7\n ],\n [\n -75.8344,\n 38.7037\n ]\n ]\n ],\n [\n [\n [\n -76.0636,\n 38.2053\n ],\n [\n -76.0642,\n 38.2053\n ],\n [\n -76.0644,\n 38.205\n ],\n [\n -76.065,\n 38.2044\n ],\n [\n -76.0653,\n 38.2042\n ],\n [\n -76.0656,\n 38.2035\n ],\n [\n -76.0659,\n 38.203\n ],\n [\n -76.0661,\n 38.2028\n ],\n [\n -76.0667,\n 38.2031\n ],\n [\n -76.0669,\n 38.2033\n ],\n [\n -76.0669,\n 38.2036\n ],\n [\n -76.0672,\n 38.2039\n ],\n [\n -76.0678,\n 38.2039\n ],\n [\n -76.0681,\n 38.2036\n ],\n [\n -76.0683,\n 38.2036\n ],\n [\n -76.0686,\n 38.2039\n ],\n [\n -76.07,\n 38.2039\n ],\n [\n -76.0713,\n 38.2034\n ],\n [\n -76.0715,\n 38.2029\n ],\n [\n -76.0708,\n 38.2025\n ],\n [\n -76.0702,\n 38.2023\n ],\n [\n -76.0698,\n 38.2026\n ],\n [\n -76.0687,\n 38.2023\n ],\n [\n -76.0686,\n 38.2014\n ],\n [\n -76.0686,\n 38.2011\n ],\n [\n -76.0679,\n 38.2006\n ],\n [\n -76.0661,\n 38.2006\n ],\n [\n -76.0658,\n 38.2003\n ],\n [\n -76.0656,\n 38.2003\n ],\n [\n -76.0653,\n 38.2006\n ],\n [\n -76.065,\n 38.2006\n ],\n [\n -76.0647,\n 38.2003\n ],\n [\n -76.0644,\n 38.2003\n ],\n [\n -76.0642,\n 38.2\n ],\n [\n -76.0631,\n 38.1992\n ],\n [\n -76.0628,\n 38.1989\n ],\n [\n -76.0614,\n 38.1989\n ],\n [\n -76.0603,\n 38.1978\n ],\n [\n -76.06,\n 38.1978\n ],\n [\n -76.0594,\n 38.1972\n ],\n [\n -76.0592,\n 38.1972\n ],\n [\n -76.0589,\n 38.1975\n ],\n [\n -76.0575,\n 38.1975\n ],\n [\n -76.0572,\n 38.1972\n ],\n [\n -76.0567,\n 38.1972\n ],\n [\n -76.0564,\n 38.1969\n ],\n [\n -76.0561,\n 38.1967\n ],\n [\n -76.0558,\n 38.1964\n ],\n [\n -76.0556,\n 38.1952\n ],\n [\n -76.0558,\n 38.195\n ],\n [\n -76.0558,\n 38.1947\n ],\n [\n -76.0564,\n 38.1942\n ],\n [\n -76.0564,\n 38.1931\n ],\n [\n -76.0567,\n 38.1928\n ],\n [\n -76.0569,\n 38.1925\n ],\n [\n -76.0575,\n 38.1919\n ],\n [\n -76.0581,\n 38.1919\n ],\n [\n -76.0583,\n 38.1917\n ],\n [\n -76.0594,\n 38.1917\n ],\n [\n -76.0597,\n 38.1914\n ],\n [\n -76.0599,\n 38.1913\n ],\n [\n -76.06,\n 38.1906\n ],\n [\n -76.0603,\n 38.19\n ],\n [\n -76.0608,\n 38.1896\n ],\n [\n -76.0628,\n 38.1899\n ],\n [\n -76.0634,\n 38.1901\n ],\n [\n -76.0636,\n 38.1897\n ],\n [\n -76.0636,\n 38.1894\n ],\n [\n -76.0642,\n 38.1889\n ],\n [\n -76.0644,\n 38.1886\n ],\n [\n -76.0654,\n 38.1885\n ],\n [\n -76.0664,\n 38.188\n ],\n [\n -76.0671,\n 38.1881\n ],\n [\n -76.0683,\n 38.1883\n ],\n [\n -76.0688,\n 38.1885\n ],\n [\n -76.0695,\n 38.1884\n ],\n [\n -76.0704,\n 38.1883\n ],\n [\n -76.0718,\n 38.1885\n ],\n [\n -76.0725,\n 38.1884\n ],\n [\n -76.0729,\n 38.1889\n ],\n [\n -76.0744,\n 38.1892\n ],\n [\n -76.0747,\n 38.1892\n ],\n [\n -76.0754,\n 38.1894\n ],\n [\n -76.0759,\n 38.1894\n ],\n [\n -76.0763,\n 38.1895\n ],\n [\n -76.0768,\n 38.1895\n ],\n [\n -76.0772,\n 38.1897\n ],\n [\n -76.0782,\n 38.1896\n ],\n [\n -76.0792,\n 38.1893\n ],\n [\n -76.0802,\n 38.189\n ],\n [\n -76.0814,\n 38.1889\n ],\n [\n -76.082,\n 38.1889\n ],\n [\n -76.0825,\n 38.189\n ],\n [\n -76.0831,\n 38.1892\n ],\n [\n -76.0836,\n 38.1895\n ],\n [\n -76.084,\n 38.1899\n ],\n [\n -76.0849,\n 38.1907\n ],\n [\n -76.0853,\n 38.1911\n ],\n [\n -76.0857,\n 38.1916\n ],\n [\n -76.0861,\n 38.192\n ],\n [\n -76.0866,\n 38.1923\n ],\n [\n -76.0871,\n 38.1924\n ],\n [\n -76.0875,\n 38.1922\n ],\n [\n -76.0878,\n 38.1919\n ],\n [\n -76.0881,\n 38.1915\n ],\n [\n -76.0883,\n 38.1905\n ],\n [\n -76.0883,\n 38.19\n ],\n [\n -76.0882,\n 38.1895\n ],\n [\n -76.088,\n 38.1891\n ],\n [\n -76.0877,\n 38.1887\n ],\n [\n -76.0868,\n 38.1881\n ],\n [\n -76.0863,\n 38.1878\n ],\n [\n -76.0853,\n 38.1873\n ],\n [\n -76.0848,\n 38.1869\n ],\n [\n -76.0842,\n 38.1858\n ],\n [\n -76.0839,\n 38.1852\n ],\n [\n -76.0837,\n 38.1845\n ],\n [\n -76.0836,\n 38.1839\n ],\n [\n -76.0837,\n 38.1832\n ],\n [\n -76.0839,\n 38.1825\n ],\n [\n -76.0843,\n 38.1818\n ],\n [\n -76.0844,\n 38.1817\n ],\n [\n -76.0844,\n 38.1811\n ],\n [\n -76.0839,\n 38.1795\n ],\n [\n -76.0833,\n 38.1789\n ],\n [\n -76.0831,\n 38.1786\n ],\n [\n -76.0828,\n 38.1783\n ],\n [\n -76.0825,\n 38.1778\n ],\n [\n -76.0822,\n 38.1775\n ],\n [\n -76.0817,\n 38.1766\n ],\n [\n -76.0817,\n 38.1758\n ],\n [\n -76.0814,\n 38.1756\n ],\n [\n -76.0814,\n 38.1753\n ],\n [\n -76.0817,\n 38.175\n ],\n [\n -76.0817,\n 38.1747\n ],\n [\n -76.0814,\n 38.1744\n ],\n [\n -76.0811,\n 38.1742\n ],\n [\n -76.0811,\n 38.1739\n ],\n [\n -76.0806,\n 38.1733\n ],\n [\n -76.0806,\n 38.1731\n ],\n [\n -76.0808,\n 38.1728\n ],\n [\n -76.0811,\n 38.1728\n ],\n [\n -76.0817,\n 38.1722\n ],\n [\n -76.0822,\n 38.1722\n ],\n [\n -76.0828,\n 38.1728\n ],\n [\n -76.0847,\n 38.1728\n ],\n [\n -76.085,\n 38.1725\n ],\n [\n -76.085,\n 38.1722\n ],\n [\n -76.0856,\n 38.1717\n ],\n [\n -76.0858,\n 38.1717\n ],\n [\n -76.0861,\n 38.1714\n ],\n [\n -76.0872,\n 38.1714\n ],\n [\n -76.0878,\n 38.1714\n ],\n [\n -76.0881,\n 38.1717\n ],\n [\n -76.0883,\n 38.1717\n ],\n [\n -76.0889,\n 38.1722\n ],\n [\n -76.0894,\n 38.1722\n ],\n [\n -76.0897,\n 38.1719\n ],\n [\n -76.09,\n 38.1717\n ],\n [\n -76.0889,\n 38.1703\n ],\n [\n -76.0886,\n 38.17\n ],\n [\n -76.0886,\n 38.1697\n ],\n [\n -76.0883,\n 38.1694\n ],\n [\n -76.0883,\n 38.1689\n ],\n [\n -76.0881,\n 38.1686\n ],\n [\n -76.0881,\n 38.1683\n ],\n [\n -76.0878,\n 38.1681\n ],\n [\n -76.0878,\n 38.1675\n ],\n [\n -76.0881,\n 38.1672\n ],\n [\n -76.0883,\n 38.1662\n ],\n [\n -76.0883,\n 38.1658\n ],\n [\n -76.0889,\n 38.1653\n ],\n [\n -76.0889,\n 38.165\n ],\n [\n -76.0886,\n 38.1647\n ],\n [\n -76.0875,\n 38.1606\n ],\n [\n -76.0861,\n 38.1592\n ],\n [\n -76.0861,\n 38.1589\n ],\n [\n -76.0858,\n 38.1586\n ],\n [\n -76.0856,\n 38.1583\n ],\n [\n -76.0853,\n 38.1569\n ],\n [\n -76.085,\n 38.1566\n ],\n [\n -76.0833,\n 38.1567\n ],\n [\n -76.0833,\n 38.1569\n ],\n [\n -76.083,\n 38.1572\n ],\n [\n -76.0828,\n 38.1575\n ],\n [\n -76.0831,\n 38.1578\n ],\n [\n -76.0836,\n 38.1586\n ],\n [\n -76.0836,\n 38.1592\n ],\n [\n -76.0828,\n 38.1597\n ],\n [\n -76.0822,\n 38.1597\n ],\n [\n -76.0815,\n 38.1594\n ],\n [\n -76.0808,\n 38.1597\n ],\n [\n -76.0801,\n 38.1594\n ],\n [\n -76.0796,\n 38.159\n ],\n [\n -76.0791,\n 38.1588\n ],\n [\n -76.0788,\n 38.1588\n ],\n [\n -76.0783,\n 38.1587\n ],\n [\n -76.078,\n 38.1585\n ],\n [\n -76.0775,\n 38.1583\n ],\n [\n -76.0774,\n 38.1581\n ],\n [\n -76.0769,\n 38.158\n ],\n [\n -76.0766,\n 38.1579\n ],\n [\n -76.0764,\n 38.1579\n ],\n [\n -76.0759,\n 38.158\n ],\n [\n -76.0756,\n 38.1581\n ],\n [\n -76.075,\n 38.1581\n ],\n [\n -76.0744,\n 38.159\n ],\n [\n -76.0744,\n 38.1592\n ],\n [\n -76.0747,\n 38.1594\n ],\n [\n -76.0753,\n 38.1594\n ],\n [\n -76.0778,\n 38.1619\n ],\n [\n -76.0778,\n 38.1622\n ],\n [\n -76.0781,\n 38.1625\n ],\n [\n -76.0775,\n 38.1631\n ],\n [\n -76.0772,\n 38.1631\n ],\n [\n -76.0769,\n 38.1633\n ],\n [\n -76.0767,\n 38.1633\n ],\n [\n -76.0758,\n 38.1625\n ],\n [\n -76.0756,\n 38.1625\n ],\n [\n -76.0753,\n 38.1622\n ],\n [\n -76.075,\n 38.1622\n ],\n [\n -76.0747,\n 38.1619\n ],\n [\n -76.0742,\n 38.1619\n ],\n [\n -76.0739,\n 38.1617\n ],\n [\n -76.0736,\n 38.1617\n ],\n [\n -76.0733,\n 38.1614\n ],\n [\n -76.0725,\n 38.1614\n ],\n [\n -76.0722,\n 38.1617\n ],\n [\n -76.0719,\n 38.1619\n ],\n [\n -76.0719,\n 38.1625\n ],\n [\n -76.0722,\n 38.1628\n ],\n [\n -76.0717,\n 38.1628\n ],\n [\n -76.0714,\n 38.1625\n ],\n [\n -76.0711,\n 38.1625\n ],\n [\n -76.0708,\n 38.1628\n ],\n [\n -76.0703,\n 38.1628\n ],\n [\n -76.0694,\n 38.1636\n ],\n [\n -76.0694,\n 38.1639\n ],\n [\n -76.0697,\n 38.1642\n ],\n [\n -76.07,\n 38.1644\n ],\n [\n -76.0703,\n 38.1647\n ],\n [\n -76.0711,\n 38.1647\n ],\n [\n -76.0714,\n 38.165\n ],\n [\n -76.0717,\n 38.165\n ],\n [\n -76.0719,\n 38.1653\n ],\n [\n -76.0722,\n 38.1656\n ],\n [\n -76.0722,\n 38.1658\n ],\n [\n -76.0725,\n 38.1661\n ],\n [\n -76.0725,\n 38.1664\n ],\n [\n -76.0731,\n 38.1669\n ],\n [\n -76.0733,\n 38.1672\n ],\n [\n -76.0736,\n 38.1672\n ],\n [\n -76.0739,\n 38.1675\n ],\n [\n -76.0744,\n 38.1675\n ],\n [\n -76.0747,\n 38.1678\n ],\n [\n -76.0756,\n 38.1678\n ],\n [\n -76.0758,\n 38.1681\n ],\n [\n -76.0769,\n 38.1681\n ],\n [\n -76.0772,\n 38.1683\n ],\n [\n -76.0775,\n 38.1683\n ],\n [\n -76.0778,\n 38.1686\n ],\n [\n -76.0773,\n 38.1689\n ],\n [\n -76.0769,\n 38.1687\n ],\n [\n -76.0758,\n 38.1689\n ],\n [\n -76.075,\n 38.1689\n ],\n [\n -76.0747,\n 38.1692\n ],\n [\n -76.0742,\n 38.1692\n ],\n [\n -76.0739,\n 38.1694\n ],\n [\n -76.0736,\n 38.1692\n ],\n [\n -76.0731,\n 38.1692\n ],\n [\n -76.0726,\n 38.1688\n ],\n [\n -76.0722,\n 38.1684\n ],\n [\n -76.0718,\n 38.1679\n ],\n [\n -76.0707,\n 38.1671\n ],\n [\n -76.0698,\n 38.1665\n ],\n [\n -76.0689,\n 38.1666\n ],\n [\n -76.0684,\n 38.1668\n ],\n [\n -76.0681,\n 38.167\n ],\n [\n -76.0677,\n 38.1675\n ],\n [\n -76.0669,\n 38.1675\n ],\n [\n -76.0661,\n 38.1683\n ],\n [\n -76.0658,\n 38.1683\n ],\n [\n -76.0653,\n 38.1689\n ],\n [\n -76.065,\n 38.1692\n ],\n [\n -76.065,\n 38.1694\n ],\n [\n -76.0656,\n 38.17\n ],\n [\n -76.0658,\n 38.17\n ],\n [\n -76.0661,\n 38.1703\n ],\n [\n -76.0661,\n 38.1708\n ],\n [\n -76.0658,\n 38.1711\n ],\n [\n -76.065,\n 38.1711\n ],\n [\n -76.0647,\n 38.1714\n ],\n [\n -76.0644,\n 38.1711\n ],\n [\n -76.0642,\n 38.1714\n ],\n [\n -76.0628,\n 38.1714\n ],\n [\n -76.0625,\n 38.1717\n ],\n [\n -76.0614,\n 38.1717\n ],\n [\n -76.0611,\n 38.1714\n ],\n [\n -76.0605,\n 38.1719\n ],\n [\n -76.0598,\n 38.1719\n ],\n [\n -76.0594,\n 38.1714\n ],\n [\n -76.0592,\n 38.1717\n ],\n [\n -76.0589,\n 38.1717\n ],\n [\n -76.0581,\n 38.1725\n ],\n [\n -76.0581,\n 38.1728\n ],\n [\n -76.0572,\n 38.1736\n ],\n [\n -76.0569,\n 38.1736\n ],\n [\n -76.0567,\n 38.1733\n ],\n [\n -76.0567,\n 38.1731\n ],\n [\n -76.0564,\n 38.1728\n ],\n [\n -76.0567,\n 38.1725\n ],\n [\n -76.0567,\n 38.1722\n ],\n [\n -76.0569,\n 38.1719\n ],\n [\n -76.0574,\n 38.1715\n ],\n [\n -76.0578,\n 38.1711\n ],\n [\n -76.0575,\n 38.1704\n ],\n [\n -76.0582,\n 38.1696\n ],\n [\n -76.0587,\n 38.1695\n ],\n [\n -76.0594,\n 38.1697\n ],\n [\n -76.0611,\n 38.1697\n ],\n [\n -76.0614,\n 38.1694\n ],\n [\n -76.0617,\n 38.1692\n ],\n [\n -76.0611,\n 38.1686\n ],\n [\n -76.0603,\n 38.1681\n ],\n [\n -76.06,\n 38.1678\n ],\n [\n -76.06,\n 38.1644\n ],\n [\n -76.0594,\n 38.1639\n ],\n [\n -76.0592,\n 38.1636\n ],\n [\n -76.0589,\n 38.1636\n ],\n [\n -76.0586,\n 38.1633\n ],\n [\n -76.0583,\n 38.1631\n ],\n [\n -76.0583,\n 38.1628\n ],\n [\n -76.0581,\n 38.1625\n ],\n [\n -76.0581,\n 38.1622\n ],\n [\n -76.0578,\n 38.1619\n ],\n [\n -76.0578,\n 38.1617\n ],\n [\n -76.0581,\n 38.1614\n ],\n [\n -76.0578,\n 38.1611\n ],\n [\n -76.0578,\n 38.1594\n ],\n [\n -76.0575,\n 38.1592\n ],\n [\n -76.0575,\n 38.1583\n ],\n [\n -76.0572,\n 38.1581\n ],\n [\n -76.0569,\n 38.1578\n ],\n [\n -76.0567,\n 38.1575\n ],\n [\n -76.0561,\n 38.1569\n ],\n [\n -76.0558,\n 38.1567\n ],\n [\n -76.0558,\n 38.1561\n ],\n [\n -76.0556,\n 38.1558\n ],\n [\n -76.0556,\n 38.1544\n ],\n [\n -76.0558,\n 38.1542\n ],\n [\n -76.0558,\n 38.1525\n ],\n [\n -76.0556,\n 38.1519\n ],\n [\n -76.0556,\n 38.1514\n ],\n [\n -76.0553,\n 38.1511\n ],\n [\n -76.0553,\n 38.1508\n ],\n [\n -76.055,\n 38.1506\n ],\n [\n -76.0528,\n 38.1488\n ],\n [\n -76.0524,\n 38.1485\n ],\n [\n -76.0519,\n 38.1483\n ],\n [\n -76.0515,\n 38.148\n ],\n [\n -76.0511,\n 38.1478\n ],\n [\n -76.0502,\n 38.1475\n ],\n [\n -76.0497,\n 38.1474\n ],\n [\n -76.0494,\n 38.1475\n ],\n [\n -76.0478,\n 38.1477\n ],\n [\n -76.0461,\n 38.1475\n ],\n [\n -76.0458,\n 38.1477\n ],\n [\n -76.0452,\n 38.1478\n ],\n [\n -76.045,\n 38.1482\n ],\n [\n -76.0445,\n 38.1484\n ],\n [\n -76.0439,\n 38.1484\n ],\n [\n -76.0433,\n 38.1483\n ],\n [\n -76.0426,\n 38.1483\n ],\n [\n -76.042,\n 38.1484\n ],\n [\n -76.0414,\n 38.1486\n ],\n [\n -76.0407,\n 38.1487\n ],\n [\n -76.0401,\n 38.1487\n ],\n [\n -76.0394,\n 38.1485\n ],\n [\n -76.0389,\n 38.1482\n ],\n [\n -76.0385,\n 38.1477\n ],\n [\n -76.0381,\n 38.1474\n ],\n [\n -76.0362,\n 38.1473\n ],\n [\n -76.0356,\n 38.1474\n ],\n [\n -76.0343,\n 38.1478\n ],\n [\n -76.0337,\n 38.148\n ],\n [\n -76.0331,\n 38.1483\n ],\n [\n -76.0325,\n 38.1484\n ],\n [\n -76.0319,\n 38.1486\n ],\n [\n -76.0314,\n 38.1492\n ],\n [\n -76.0314,\n 38.1494\n ],\n [\n -76.0311,\n 38.1497\n ],\n [\n -76.0311,\n 38.15\n ],\n [\n -76.0308,\n 38.1503\n ],\n [\n -76.0308,\n 38.1508\n ],\n [\n -76.0306,\n 38.1511\n ],\n [\n -76.0306,\n 38.1514\n ],\n [\n -76.0303,\n 38.1517\n ],\n [\n -76.0303,\n 38.1519\n ],\n [\n -76.0297,\n 38.1525\n ],\n [\n -76.0294,\n 38.1525\n ],\n [\n -76.0291,\n 38.1528\n ],\n [\n -76.0288,\n 38.1532\n ],\n [\n -76.0287,\n 38.1538\n ],\n [\n -76.0297,\n 38.1551\n ],\n [\n -76.0301,\n 38.1555\n ],\n [\n -76.0303,\n 38.1559\n ],\n [\n -76.0306,\n 38.1564\n ],\n [\n -76.031,\n 38.1568\n ],\n [\n -76.0313,\n 38.1572\n ],\n [\n -76.0317,\n 38.1575\n ],\n [\n -76.0319,\n 38.1578\n ],\n [\n -76.0344,\n 38.1583\n ],\n [\n -76.0347,\n 38.1586\n ],\n [\n -76.035,\n 38.1586\n ],\n [\n -76.0356,\n 38.1592\n ],\n [\n -76.0356,\n 38.1614\n ],\n [\n -76.0353,\n 38.1614\n ],\n [\n -76.035,\n 38.1617\n ],\n [\n -76.0353,\n 38.1619\n ],\n [\n -76.0353,\n 38.1622\n ],\n [\n -76.0354,\n 38.1625\n ],\n [\n -76.0357,\n 38.163\n ],\n [\n -76.0361,\n 38.1633\n ],\n [\n -76.0365,\n 38.1637\n ],\n [\n -76.0369,\n 38.164\n ],\n [\n -76.0372,\n 38.1644\n ],\n [\n -76.038,\n 38.1651\n ],\n [\n -76.0383,\n 38.1653\n ],\n [\n -76.0389,\n 38.1653\n ],\n [\n -76.0392,\n 38.1656\n ],\n [\n -76.04,\n 38.1656\n ],\n [\n -76.0403,\n 38.1653\n ],\n [\n -76.0422,\n 38.1653\n ],\n [\n -76.0431,\n 38.1661\n ],\n [\n -76.0428,\n 38.1664\n ],\n [\n -76.0425,\n 38.1664\n ],\n [\n -76.0422,\n 38.1667\n ],\n [\n -76.0419,\n 38.1667\n ],\n [\n -76.0417,\n 38.1669\n ],\n [\n -76.0411,\n 38.1669\n ],\n [\n -76.0408,\n 38.1672\n ],\n [\n -76.0406,\n 38.1675\n ],\n [\n -76.0394,\n 38.1675\n ],\n [\n -76.0392,\n 38.1672\n ],\n [\n -76.0381,\n 38.1672\n ],\n [\n -76.0378,\n 38.1673\n ],\n [\n -76.0366,\n 38.1677\n ],\n [\n -76.0361,\n 38.1678\n ],\n [\n -76.0357,\n 38.1678\n ],\n [\n -76.0356,\n 38.1681\n ],\n [\n -76.0356,\n 38.1686\n ],\n [\n -76.0353,\n 38.1689\n ],\n [\n -76.035,\n 38.1689\n ],\n [\n -76.035,\n 38.1692\n ],\n [\n -76.0347,\n 38.1694\n ],\n [\n -76.0342,\n 38.1694\n ],\n [\n -76.0339,\n 38.1692\n ],\n [\n -76.0333,\n 38.1692\n ],\n [\n -76.0325,\n 38.1683\n ],\n [\n -76.0325,\n 38.1681\n ],\n [\n -76.0319,\n 38.1681\n ],\n [\n -76.0311,\n 38.1678\n ],\n [\n -76.0298,\n 38.168\n ],\n [\n -76.0288,\n 38.1685\n ],\n [\n -76.0284,\n 38.1688\n ],\n [\n -76.0281,\n 38.1692\n ],\n [\n -76.0278,\n 38.1697\n ],\n [\n -76.0276,\n 38.17\n ],\n [\n -76.0272,\n 38.1702\n ],\n [\n -76.0268,\n 38.1703\n ],\n [\n -76.0263,\n 38.1706\n ],\n [\n -76.026,\n 38.171\n ],\n [\n -76.0258,\n 38.1716\n ],\n [\n -76.0257,\n 38.1721\n ],\n [\n -76.0254,\n 38.1726\n ],\n [\n -76.0251,\n 38.173\n ],\n [\n -76.0247,\n 38.1734\n ],\n [\n -76.0236,\n 38.1732\n ],\n [\n -76.0231,\n 38.173\n ],\n [\n -76.0226,\n 38.1732\n ],\n [\n -76.0222,\n 38.1737\n ],\n [\n -76.0223,\n 38.175\n ],\n [\n -76.0225,\n 38.1757\n ],\n [\n -76.0225,\n 38.1765\n ],\n [\n -76.0224,\n 38.1772\n ],\n [\n -76.0226,\n 38.1778\n ],\n [\n -76.024,\n 38.179\n ],\n [\n -76.0245,\n 38.1794\n ],\n [\n -76.0249,\n 38.1799\n ],\n [\n -76.0252,\n 38.1806\n ],\n [\n -76.0254,\n 38.1813\n ],\n [\n -76.0257,\n 38.1819\n ],\n [\n -76.0262,\n 38.1824\n ],\n [\n -76.0279,\n 38.1834\n ],\n [\n -76.0285,\n 38.1837\n ],\n [\n -76.029,\n 38.1839\n ],\n [\n -76.0306,\n 38.1844\n ],\n [\n -76.0322,\n 38.1848\n ],\n [\n -76.0332,\n 38.1851\n ],\n [\n -76.0337,\n 38.1853\n ],\n [\n -76.0339,\n 38.1856\n ],\n [\n -76.0344,\n 38.1858\n ],\n [\n -76.0347,\n 38.1861\n ],\n [\n -76.0361,\n 38.1861\n ],\n [\n -76.0367,\n 38.1858\n ],\n [\n -76.0383,\n 38.1853\n ],\n [\n -76.0388,\n 38.1852\n ],\n [\n -76.039,\n 38.1855\n ],\n [\n -76.0397,\n 38.1854\n ],\n [\n -76.0406,\n 38.1851\n ],\n [\n -76.0408,\n 38.1847\n ],\n [\n -76.0411,\n 38.1844\n ],\n [\n -76.0414,\n 38.1844\n ],\n [\n -76.0417,\n 38.1847\n ],\n [\n -76.0419,\n 38.1847\n ],\n [\n -76.0422,\n 38.185\n ],\n [\n -76.0422,\n 38.1853\n ],\n [\n -76.0425,\n 38.1856\n ],\n [\n -76.0425,\n 38.1861\n ],\n [\n -76.0422,\n 38.1864\n ],\n [\n -76.0422,\n 38.1867\n ],\n [\n -76.0431,\n 38.1875\n ],\n [\n -76.0431,\n 38.1878\n ],\n [\n -76.0428,\n 38.1881\n ],\n [\n -76.0425,\n 38.1881\n ],\n [\n -76.0422,\n 38.1883\n ],\n [\n -76.041,\n 38.1886\n ],\n [\n -76.0404,\n 38.189\n ],\n [\n -76.0401,\n 38.1894\n ],\n [\n -76.0394,\n 38.19\n ],\n [\n -76.0392,\n 38.1901\n ],\n [\n -76.0389,\n 38.19\n ],\n [\n -76.0386,\n 38.19\n ],\n [\n -76.0383,\n 38.1903\n ],\n [\n -76.0382,\n 38.1903\n ],\n [\n -76.0375,\n 38.1906\n ],\n [\n -76.0372,\n 38.1909\n ],\n [\n -76.0364,\n 38.1914\n ],\n [\n -76.0365,\n 38.1928\n ],\n [\n -76.0367,\n 38.1928\n ],\n [\n -76.0375,\n 38.1936\n ],\n [\n -76.0381,\n 38.1936\n ],\n [\n -76.0385,\n 38.1945\n ],\n [\n -76.0393,\n 38.1946\n ],\n [\n -76.04,\n 38.1953\n ],\n [\n -76.0406,\n 38.1958\n ],\n [\n -76.0406,\n 38.1961\n ],\n [\n -76.0411,\n 38.1967\n ],\n [\n -76.0411,\n 38.1969\n ],\n [\n -76.0417,\n 38.1975\n ],\n [\n -76.0419,\n 38.1975\n ],\n [\n -76.0419,\n 38.1981\n ],\n [\n -76.0426,\n 38.1983\n ],\n [\n -76.0434,\n 38.1984\n ],\n [\n -76.045,\n 38.2003\n ],\n [\n -76.0453,\n 38.2006\n ],\n [\n -76.0453,\n 38.2008\n ],\n [\n -76.0458,\n 38.2014\n ],\n [\n -76.0458,\n 38.2019\n ],\n [\n -76.0461,\n 38.2022\n ],\n [\n -76.0469,\n 38.2022\n ],\n [\n -76.0472,\n 38.2025\n ],\n [\n -76.0474,\n 38.2028\n ],\n [\n -76.0483,\n 38.2032\n ],\n [\n -76.0488,\n 38.2036\n ],\n [\n -76.0489,\n 38.2039\n ],\n [\n -76.0494,\n 38.2044\n ],\n [\n -76.0497,\n 38.2044\n ],\n [\n -76.0506,\n 38.2036\n ],\n [\n -76.0507,\n 38.2037\n ],\n [\n -76.0514,\n 38.2038\n ],\n [\n -76.0518,\n 38.2039\n ],\n [\n -76.0522,\n 38.2041\n ],\n [\n -76.0526,\n 38.2041\n ],\n [\n -76.0531,\n 38.204\n ],\n [\n -76.0535,\n 38.2037\n ],\n [\n -76.0545,\n 38.2032\n ],\n [\n -76.055,\n 38.203\n ],\n [\n -76.0556,\n 38.2029\n ],\n [\n -76.0568,\n 38.203\n ],\n [\n -76.0574,\n 38.2031\n ],\n [\n -76.0579,\n 38.2031\n ],\n [\n -76.0589,\n 38.2034\n ],\n [\n -76.0593,\n 38.2036\n ],\n [\n -76.0601,\n 38.2034\n ],\n [\n -76.0604,\n 38.2032\n ],\n [\n -76.0609,\n 38.2033\n ],\n [\n -76.0614,\n 38.2036\n ],\n [\n -76.0617,\n 38.2039\n ],\n [\n -76.0619,\n 38.2039\n ],\n [\n -76.0628,\n 38.2047\n ],\n [\n -76.0631,\n 38.205\n ],\n [\n -76.0633,\n 38.205\n ],\n [\n -76.0636,\n 38.2053\n ]\n ]\n ],\n [\n [\n [\n -76.1713,\n 38.2963\n ],\n [\n -76.1717,\n 38.2967\n ],\n [\n -76.172,\n 38.2967\n ],\n [\n -76.1719,\n 38.2969\n ],\n [\n -76.1722,\n 38.2972\n ],\n [\n -76.1731,\n 38.2972\n ],\n [\n -76.1732,\n 38.2971\n ],\n [\n -76.1736,\n 38.2967\n ],\n [\n -76.1739,\n 38.2967\n ],\n [\n -76.1744,\n 38.2962\n ],\n [\n -76.1744,\n 38.2961\n ],\n [\n -76.175,\n 38.2967\n ],\n [\n -76.1753,\n 38.2967\n ],\n [\n -76.1761,\n 38.2958\n ],\n [\n -76.1761,\n 38.2953\n ],\n [\n -76.1758,\n 38.295\n ],\n [\n -76.1764,\n 38.2944\n ],\n [\n -76.1767,\n 38.2944\n ],\n [\n -76.1775,\n 38.2936\n ],\n [\n -76.1775,\n 38.2933\n ],\n [\n -76.1783,\n 38.2925\n ],\n [\n -76.1789,\n 38.2925\n ],\n [\n -76.1794,\n 38.2931\n ],\n [\n -76.1797,\n 38.2931\n ],\n [\n -76.18,\n 38.2933\n ],\n [\n -76.1811,\n 38.2933\n ],\n [\n -76.1817,\n 38.2928\n ],\n [\n -76.1819,\n 38.2928\n ],\n [\n -76.1823,\n 38.2931\n ],\n [\n -76.1831,\n 38.2931\n ],\n [\n -76.1833,\n 38.2933\n ],\n [\n -76.1833,\n 38.2936\n ],\n [\n -76.1834,\n 38.2936\n ],\n [\n -76.1839,\n 38.2936\n ],\n [\n -76.1845,\n 38.2941\n ],\n [\n -76.185,\n 38.2942\n ],\n [\n -76.1851,\n 38.2943\n ],\n [\n -76.1853,\n 38.2944\n ],\n [\n -76.1859,\n 38.2945\n ],\n [\n -76.1861,\n 38.2947\n ],\n [\n -76.1867,\n 38.2947\n ],\n [\n -76.1869,\n 38.295\n ],\n [\n -76.1872,\n 38.2947\n ],\n [\n -76.1881,\n 38.2947\n ],\n [\n -76.1883,\n 38.295\n ],\n [\n -76.1897,\n 38.295\n ],\n [\n -76.19,\n 38.2947\n ],\n [\n -76.1914,\n 38.2947\n ],\n [\n -76.1917,\n 38.2944\n ],\n [\n -76.1919,\n 38.2944\n ],\n [\n -76.1922,\n 38.2942\n ],\n [\n -76.1933,\n 38.2942\n ],\n [\n -76.1939,\n 38.2947\n ],\n [\n -76.1944,\n 38.2947\n ],\n [\n -76.1947,\n 38.295\n ],\n [\n -76.1964,\n 38.2933\n ],\n [\n -76.1964,\n 38.2931\n ],\n [\n -76.1967,\n 38.2928\n ],\n [\n -76.1967,\n 38.2922\n ],\n [\n -76.1964,\n 38.2919\n ],\n [\n -76.1964,\n 38.2911\n ],\n [\n -76.1977,\n 38.2897\n ],\n [\n -76.1981,\n 38.2897\n ],\n [\n -76.1984,\n 38.2895\n ],\n [\n -76.1986,\n 38.2897\n ],\n [\n -76.2,\n 38.2897\n ],\n [\n -76.2011,\n 38.2908\n ],\n [\n -76.2011,\n 38.2914\n ],\n [\n -76.2028,\n 38.2931\n ],\n [\n -76.2028,\n 38.2933\n ],\n [\n -76.2031,\n 38.2936\n ],\n [\n -76.2031,\n 38.2942\n ],\n [\n -76.2036,\n 38.2947\n ],\n [\n -76.2039,\n 38.2944\n ],\n [\n -76.2042,\n 38.2944\n ],\n [\n -76.2044,\n 38.2942\n ],\n [\n -76.2044,\n 38.2931\n ],\n [\n -76.2039,\n 38.2925\n ],\n [\n -76.2039,\n 38.2922\n ],\n [\n -76.2031,\n 38.2914\n ],\n [\n -76.2031,\n 38.2908\n ],\n [\n -76.2028,\n 38.2906\n ],\n [\n -76.2028,\n 38.29\n ],\n [\n -76.2008,\n 38.288\n ],\n [\n -76.2008,\n 38.2872\n ],\n [\n -76.1997,\n 38.2861\n ],\n [\n -76.1994,\n 38.2861\n ],\n [\n -76.1992,\n 38.2858\n ],\n [\n -76.1986,\n 38.2858\n ],\n [\n -76.1983,\n 38.2856\n ],\n [\n -76.1981,\n 38.2856\n ],\n [\n -76.1975,\n 38.285\n ],\n [\n -76.1972,\n 38.285\n ],\n [\n -76.1967,\n 38.2844\n ],\n [\n -76.1967,\n 38.2842\n ],\n [\n -76.1961,\n 38.2836\n ],\n [\n -76.1961,\n 38.2833\n ],\n [\n -76.1958,\n 38.2831\n ],\n [\n -76.1958,\n 38.2828\n ],\n [\n -76.1956,\n 38.2825\n ],\n [\n -76.1953,\n 38.2825\n ],\n [\n -76.195,\n 38.2828\n ],\n [\n -76.1947,\n 38.2825\n ],\n [\n -76.1942,\n 38.2819\n ],\n [\n -76.1942,\n 38.2817\n ],\n [\n -76.1933,\n 38.2808\n ],\n [\n -76.1933,\n 38.2806\n ],\n [\n -76.1922,\n 38.2794\n ],\n [\n -76.1922,\n 38.2792\n ],\n [\n -76.1908,\n 38.2778\n ],\n [\n -76.1908,\n 38.2775\n ],\n [\n -76.1903,\n 38.2769\n ],\n [\n -76.1903,\n 38.2756\n ],\n [\n -76.19,\n 38.2753\n ],\n [\n -76.19,\n 38.2747\n ],\n [\n -76.1897,\n 38.2744\n ],\n [\n -76.1897,\n 38.2736\n ],\n [\n -76.19,\n 38.2733\n ],\n [\n -76.19,\n 38.2722\n ],\n [\n -76.1892,\n 38.2714\n ],\n [\n -76.1892,\n 38.2708\n ],\n [\n -76.1886,\n 38.2703\n ],\n [\n -76.1886,\n 38.27\n ],\n [\n -76.1883,\n 38.2697\n ],\n [\n -76.1883,\n 38.2694\n ],\n [\n -76.1881,\n 38.2692\n ],\n [\n -76.1881,\n 38.2672\n ],\n [\n -76.1877,\n 38.2669\n ],\n [\n -76.1875,\n 38.2667\n ],\n [\n -76.1875,\n 38.2664\n ],\n [\n -76.1869,\n 38.2658\n ],\n [\n -76.1869,\n 38.265\n ],\n [\n -76.1867,\n 38.2647\n ],\n [\n -76.1867,\n 38.2644\n ],\n [\n -76.1858,\n 38.2636\n ],\n [\n -76.1847,\n 38.2636\n ],\n [\n -76.1844,\n 38.2633\n ],\n [\n -76.1842,\n 38.2633\n ],\n [\n -76.1836,\n 38.2628\n ],\n [\n -76.1836,\n 38.2625\n ],\n [\n -76.1814,\n 38.2603\n ],\n [\n -76.1814,\n 38.26\n ],\n [\n -76.18,\n 38.2586\n ],\n [\n -76.1797,\n 38.2586\n ],\n [\n -76.1797,\n 38.2583\n ],\n [\n -76.1794,\n 38.2581\n ],\n [\n -76.1794,\n 38.2578\n ],\n [\n -76.1789,\n 38.2572\n ],\n [\n -76.1789,\n 38.2569\n ],\n [\n -76.1769,\n 38.255\n ],\n [\n -76.1767,\n 38.255\n ],\n [\n -76.1758,\n 38.2541\n ],\n [\n -76.1758,\n 38.2539\n ],\n [\n -76.1756,\n 38.2536\n ],\n [\n -76.1756,\n 38.2533\n ],\n [\n -76.1753,\n 38.2531\n ],\n [\n -76.1756,\n 38.2528\n ],\n [\n -76.1756,\n 38.2522\n ],\n [\n -76.1758,\n 38.2519\n ],\n [\n -76.1758,\n 38.2517\n ],\n [\n -76.1742,\n 38.25\n ],\n [\n -76.1742,\n 38.2497\n ],\n [\n -76.1736,\n 38.2492\n ],\n [\n -76.1736,\n 38.2489\n ],\n [\n -76.1728,\n 38.2481\n ],\n [\n -76.1728,\n 38.2478\n ],\n [\n -76.1725,\n 38.2478\n ],\n [\n -76.1719,\n 38.2472\n ],\n [\n -76.1717,\n 38.2472\n ],\n [\n -76.1714,\n 38.2475\n ],\n [\n -76.1711,\n 38.2475\n ],\n [\n -76.1708,\n 38.2478\n ],\n [\n -76.1706,\n 38.2478\n ],\n [\n -76.1703,\n 38.2481\n ],\n [\n -76.1692,\n 38.2481\n ],\n [\n -76.1689,\n 38.2478\n ],\n [\n -76.1686,\n 38.2478\n ],\n [\n -76.1683,\n 38.2475\n ],\n [\n -76.1681,\n 38.2475\n ],\n [\n -76.1672,\n 38.2467\n ],\n [\n -76.1672,\n 38.2461\n ],\n [\n -76.1675,\n 38.2458\n ],\n [\n -76.1675,\n 38.2453\n ],\n [\n -76.1667,\n 38.2444\n ],\n [\n -76.1667,\n 38.2442\n ],\n [\n -76.1658,\n 38.2433\n ],\n [\n -76.1658,\n 38.2431\n ],\n [\n -76.1656,\n 38.2431\n ],\n [\n -76.1653,\n 38.2428\n ],\n [\n -76.1647,\n 38.2428\n ],\n [\n -76.1636,\n 38.2439\n ],\n [\n -76.1633,\n 38.2439\n ],\n [\n -76.1629,\n 38.2443\n ],\n [\n -76.1625,\n 38.2447\n ],\n [\n -76.1617,\n 38.2447\n ],\n [\n -76.1614,\n 38.245\n ],\n [\n -76.16,\n 38.245\n ],\n [\n -76.1595,\n 38.2445\n ],\n [\n -76.1592,\n 38.2442\n ],\n [\n -76.1592,\n 38.2439\n ],\n [\n -76.1583,\n 38.2431\n ],\n [\n -76.1578,\n 38.2431\n ],\n [\n -76.1572,\n 38.2425\n ],\n [\n -76.1567,\n 38.2425\n ],\n [\n -76.1561,\n 38.2419\n ],\n [\n -76.1561,\n 38.2417\n ],\n [\n -76.1558,\n 38.2414\n ],\n [\n -76.1558,\n 38.2411\n ],\n [\n -76.155,\n 38.2403\n ],\n [\n -76.1547,\n 38.2403\n ],\n [\n -76.1544,\n 38.24\n ],\n [\n -76.1539,\n 38.24\n ],\n [\n -76.1533,\n 38.2394\n ],\n [\n -76.1522,\n 38.2406\n ],\n [\n -76.1522,\n 38.2411\n ],\n [\n -76.1518,\n 38.2415\n ],\n [\n -76.1517,\n 38.2417\n ],\n [\n -76.1517,\n 38.2422\n ],\n [\n -76.1519,\n 38.2425\n ],\n [\n -76.1517,\n 38.2428\n ],\n [\n -76.1514,\n 38.2428\n ],\n [\n -76.1503,\n 38.2439\n ],\n [\n -76.15,\n 38.2439\n ],\n [\n -76.1494,\n 38.2444\n ],\n [\n -76.1492,\n 38.2444\n ],\n [\n -76.1483,\n 38.2453\n ],\n [\n -76.1469,\n 38.2453\n ],\n [\n -76.1467,\n 38.245\n ],\n [\n -76.1464,\n 38.245\n ],\n [\n -76.1461,\n 38.2447\n ],\n [\n -76.1456,\n 38.2447\n ],\n [\n -76.1444,\n 38.2436\n ],\n [\n -76.1444,\n 38.2428\n ],\n [\n -76.1461,\n 38.2411\n ],\n [\n -76.1464,\n 38.2411\n ],\n [\n -76.1467,\n 38.2408\n ],\n [\n -76.1469,\n 38.2408\n ],\n [\n -76.1472,\n 38.2406\n ],\n [\n -76.1475,\n 38.2406\n ],\n [\n -76.1489,\n 38.2392\n ],\n [\n -76.1489,\n 38.2389\n ],\n [\n -76.149,\n 38.2388\n ],\n [\n -76.1497,\n 38.2381\n ],\n [\n -76.1497,\n 38.2378\n ],\n [\n -76.1492,\n 38.2372\n ],\n [\n -76.1492,\n 38.2369\n ],\n [\n -76.15,\n 38.2361\n ],\n [\n -76.1503,\n 38.2364\n ],\n [\n -76.1503,\n 38.2372\n ],\n [\n -76.1506,\n 38.2375\n ],\n [\n -76.1511,\n 38.2375\n ],\n [\n -76.1519,\n 38.2367\n ],\n [\n -76.1522,\n 38.2364\n ],\n [\n -76.1519,\n 38.2361\n ],\n [\n -76.1519,\n 38.2356\n ],\n [\n -76.1514,\n 38.235\n ],\n [\n -76.1514,\n 38.2347\n ],\n [\n -76.1511,\n 38.2347\n ],\n [\n -76.1508,\n 38.2344\n ],\n [\n -76.1497,\n 38.2344\n ],\n [\n -76.1494,\n 38.2342\n ],\n [\n -76.1486,\n 38.2342\n ],\n [\n -76.1483,\n 38.2339\n ],\n [\n -76.1481,\n 38.2339\n ],\n [\n -76.1478,\n 38.2336\n ],\n [\n -76.1475,\n 38.2336\n ],\n [\n -76.1472,\n 38.2333\n ],\n [\n -76.1467,\n 38.2333\n ],\n [\n -76.1464,\n 38.2331\n ],\n [\n -76.1458,\n 38.2331\n ],\n [\n -76.1456,\n 38.2328\n ],\n [\n -76.1453,\n 38.2328\n ],\n [\n -76.145,\n 38.2331\n ],\n [\n -76.1442,\n 38.2331\n ],\n [\n -76.1439,\n 38.2333\n ],\n [\n -76.1431,\n 38.2333\n ],\n [\n -76.1428,\n 38.2331\n ],\n [\n -76.1422,\n 38.2331\n ],\n [\n -76.1419,\n 38.2328\n ],\n [\n -76.1417,\n 38.2328\n ],\n [\n -76.1408,\n 38.2319\n ],\n [\n -76.1408,\n 38.2317\n ],\n [\n -76.1406,\n 38.2317\n ],\n [\n -76.1403,\n 38.2314\n ],\n [\n -76.1389,\n 38.2314\n ],\n [\n -76.1386,\n 38.2317\n ],\n [\n -76.1381,\n 38.2317\n ],\n [\n -76.1378,\n 38.2319\n ],\n [\n -76.1367,\n 38.2319\n ],\n [\n -76.1364,\n 38.2317\n ],\n [\n -76.1361,\n 38.2317\n ],\n [\n -76.1358,\n 38.2314\n ],\n [\n -76.1347,\n 38.2325\n ],\n [\n -76.1342,\n 38.2325\n ],\n [\n -76.1339,\n 38.2328\n ],\n [\n -76.1331,\n 38.2328\n ],\n [\n -76.1328,\n 38.2331\n ],\n [\n -76.1319,\n 38.2331\n ],\n [\n -76.1314,\n 38.2336\n ],\n [\n -76.1311,\n 38.2336\n ],\n [\n -76.1308,\n 38.2339\n ],\n [\n -76.1306,\n 38.2339\n ],\n [\n -76.1303,\n 38.2342\n ],\n [\n -76.1297,\n 38.2342\n ],\n [\n -76.1292,\n 38.2347\n ],\n [\n -76.1289,\n 38.2347\n ],\n [\n -76.1278,\n 38.2358\n ],\n [\n -76.1278,\n 38.2361\n ],\n [\n -76.1272,\n 38.2367\n ],\n [\n -76.1272,\n 38.2378\n ],\n [\n -76.1272,\n 38.2381\n ],\n [\n -76.1264,\n 38.2389\n ],\n [\n -76.1258,\n 38.2389\n ],\n [\n -76.1253,\n 38.2394\n ],\n [\n -76.1253,\n 38.24\n ],\n [\n -76.1256,\n 38.2403\n ],\n [\n -76.1256,\n 38.2411\n ],\n [\n -76.1258,\n 38.2414\n ],\n [\n -76.1258,\n 38.2419\n ],\n [\n -76.1261,\n 38.2422\n ],\n [\n -76.1272,\n 38.2422\n ],\n [\n -76.1275,\n 38.2425\n ],\n [\n -76.1283,\n 38.2425\n ],\n [\n -76.1286,\n 38.2422\n ],\n [\n -76.1292,\n 38.2428\n ],\n [\n -76.1292,\n 38.2431\n ],\n [\n -76.1297,\n 38.2436\n ],\n [\n -76.1297,\n 38.2444\n ],\n [\n -76.1303,\n 38.245\n ],\n [\n -76.1322,\n 38.245\n ],\n [\n -76.1325,\n 38.2453\n ],\n [\n -76.1333,\n 38.2453\n ],\n [\n -76.1336,\n 38.2456\n ],\n [\n -76.1344,\n 38.2456\n ],\n [\n -76.1347,\n 38.2458\n ],\n [\n -76.1356,\n 38.2458\n ],\n [\n -76.1358,\n 38.2461\n ],\n [\n -76.1361,\n 38.2461\n ],\n [\n -76.1364,\n 38.2464\n ],\n [\n -76.1367,\n 38.2464\n ],\n [\n -76.1369,\n 38.2467\n ],\n [\n -76.1375,\n 38.2467\n ],\n [\n -76.1378,\n 38.2469\n ],\n [\n -76.1383,\n 38.2469\n ],\n [\n -76.1389,\n 38.2464\n ],\n [\n -76.1394,\n 38.2464\n ],\n [\n -76.1397,\n 38.2467\n ],\n [\n -76.1403,\n 38.2467\n ],\n [\n -76.1414,\n 38.2478\n ],\n [\n -76.1419,\n 38.2478\n ],\n [\n -76.1422,\n 38.2481\n ],\n [\n -76.1431,\n 38.2481\n ],\n [\n -76.1433,\n 38.2483\n ],\n [\n -76.1439,\n 38.2483\n ],\n [\n -76.1442,\n 38.2481\n ],\n [\n -76.145,\n 38.2481\n ],\n [\n -76.1464,\n 38.2494\n ],\n [\n -76.1469,\n 38.2494\n ],\n [\n -76.1472,\n 38.2497\n ],\n [\n -76.1475,\n 38.2497\n ],\n [\n -76.1481,\n 38.2492\n ],\n [\n -76.1481,\n 38.2489\n ],\n [\n -76.1483,\n 38.2486\n ],\n [\n -76.1489,\n 38.2486\n ],\n [\n -76.1492,\n 38.2483\n ],\n [\n -76.15,\n 38.2492\n ],\n [\n -76.1514,\n 38.2492\n ],\n [\n -76.1531,\n 38.2475\n ],\n [\n -76.1533,\n 38.2475\n ],\n [\n -76.1536,\n 38.2472\n ],\n [\n -76.1547,\n 38.2483\n ],\n [\n -76.1572,\n 38.2483\n ],\n [\n -76.1575,\n 38.2486\n ],\n [\n -76.1603,\n 38.2486\n ],\n [\n -76.1606,\n 38.2483\n ],\n [\n -76.1625,\n 38.2483\n ],\n [\n -76.1639,\n 38.2497\n ],\n [\n -76.1639,\n 38.2503\n ],\n [\n -76.1642,\n 38.2506\n ],\n [\n -76.1642,\n 38.2517\n ],\n [\n -76.1644,\n 38.2519\n ],\n [\n -76.1644,\n 38.2525\n ],\n [\n -76.1647,\n 38.2528\n ],\n [\n -76.1647,\n 38.2531\n ],\n [\n -76.1656,\n 38.2539\n ],\n [\n -76.1656,\n 38.2542\n ],\n [\n -76.1681,\n 38.2567\n ],\n [\n -76.1683,\n 38.2567\n ],\n [\n -76.1686,\n 38.2569\n ],\n [\n -76.1689,\n 38.2569\n ],\n [\n -76.1694,\n 38.2575\n ],\n [\n -76.1697,\n 38.2575\n ],\n [\n -76.17,\n 38.2572\n ],\n [\n -76.1703,\n 38.2572\n ],\n [\n -76.1706,\n 38.2569\n ],\n [\n -76.1708,\n 38.2569\n ],\n [\n -76.1711,\n 38.2567\n ],\n [\n -76.1714,\n 38.2567\n ],\n [\n -76.1722,\n 38.2558\n ],\n [\n -76.1736,\n 38.2558\n ],\n [\n -76.1739,\n 38.2561\n ],\n [\n -76.1742,\n 38.2561\n ],\n [\n -76.1744,\n 38.2564\n ],\n [\n -76.1742,\n 38.2567\n ],\n [\n -76.1744,\n 38.2567\n ],\n [\n -76.1758,\n 38.2581\n ],\n [\n -76.1761,\n 38.2581\n ],\n [\n -76.1769,\n 38.258\n ],\n [\n -76.1776,\n 38.258\n ],\n [\n -76.1778,\n 38.2583\n ],\n [\n -76.1785,\n 38.2589\n ],\n [\n -76.1784,\n 38.2594\n ],\n [\n -76.1781,\n 38.2599\n ],\n [\n -76.1774,\n 38.2608\n ],\n [\n -76.1766,\n 38.2619\n ],\n [\n -76.1768,\n 38.2625\n ],\n [\n -76.1767,\n 38.2628\n ],\n [\n -76.1775,\n 38.2638\n ],\n [\n -76.1775,\n 38.2642\n ],\n [\n -76.1778,\n 38.2645\n ],\n [\n -76.1783,\n 38.2649\n ],\n [\n -76.1799,\n 38.266\n ],\n [\n -76.1801,\n 38.267\n ],\n [\n -76.1801,\n 38.2674\n ],\n [\n -76.1804,\n 38.2681\n ],\n [\n -76.1814,\n 38.2692\n ],\n [\n -76.1811,\n 38.2697\n ],\n [\n -76.1815,\n 38.2705\n ],\n [\n -76.1811,\n 38.2715\n ],\n [\n -76.1803,\n 38.2714\n ],\n [\n -76.1797,\n 38.2714\n ],\n [\n -76.1789,\n 38.271\n ],\n [\n -76.1786,\n 38.2708\n ],\n [\n -76.1785,\n 38.2708\n ],\n [\n -76.178,\n 38.2707\n ],\n [\n -76.1778,\n 38.2704\n ],\n [\n -76.1773,\n 38.2705\n ],\n [\n -76.1772,\n 38.2703\n ],\n [\n -76.1765,\n 38.2701\n ],\n [\n -76.1762,\n 38.2698\n ],\n [\n -76.1757,\n 38.2698\n ],\n [\n -76.1756,\n 38.27\n ],\n [\n -76.1754,\n 38.2706\n ],\n [\n -76.1764,\n 38.2711\n ],\n [\n -76.1771,\n 38.2715\n ],\n [\n -76.1778,\n 38.2719\n ],\n [\n -76.1779,\n 38.2722\n ],\n [\n -76.1783,\n 38.2725\n ],\n [\n -76.1788,\n 38.273\n ],\n [\n -76.179,\n 38.2731\n ],\n [\n -76.1796,\n 38.2732\n ],\n [\n -76.1797,\n 38.2734\n ],\n [\n -76.1797,\n 38.2736\n ],\n [\n -76.18,\n 38.2736\n ],\n [\n -76.1803,\n 38.2739\n ],\n [\n -76.1803,\n 38.2742\n ],\n [\n -76.1806,\n 38.2744\n ],\n [\n -76.1806,\n 38.2747\n ],\n [\n -76.1808,\n 38.275\n ],\n [\n -76.1811,\n 38.2767\n ],\n [\n -76.1811,\n 38.2769\n ],\n [\n -76.1815,\n 38.2772\n ],\n [\n -76.1819,\n 38.2781\n ],\n [\n -76.1819,\n 38.2783\n ],\n [\n -76.1822,\n 38.2786\n ],\n [\n -76.1826,\n 38.2794\n ],\n [\n -76.1827,\n 38.2797\n ],\n [\n -76.1817,\n 38.2806\n ],\n [\n -76.1815,\n 38.2806\n ],\n [\n -76.1803,\n 38.2817\n ],\n [\n -76.18,\n 38.2817\n ],\n [\n -76.1797,\n 38.2819\n ],\n [\n -76.1789,\n 38.2823\n ],\n [\n -76.1783,\n 38.2825\n ],\n [\n -76.1772,\n 38.2825\n ],\n [\n -76.1769,\n 38.2822\n ],\n [\n -76.1767,\n 38.2825\n ],\n [\n -76.1764,\n 38.2825\n ],\n [\n -76.1761,\n 38.2828\n ],\n [\n -76.1758,\n 38.2828\n ],\n [\n -76.1756,\n 38.2831\n ],\n [\n -76.1753,\n 38.2831\n ],\n [\n -76.175,\n 38.2833\n ],\n [\n -76.1747,\n 38.2833\n ],\n [\n -76.1728,\n 38.2853\n ],\n [\n -76.1736,\n 38.2861\n ],\n [\n -76.1744,\n 38.2861\n ],\n [\n -76.1758,\n 38.2875\n ],\n [\n -76.1764,\n 38.2875\n ],\n [\n -76.1764,\n 38.2878\n ],\n [\n -76.1775,\n 38.2889\n ],\n [\n -76.1769,\n 38.2894\n ],\n [\n -76.1769,\n 38.2897\n ],\n [\n -76.1767,\n 38.29\n ],\n [\n -76.1764,\n 38.29\n ],\n [\n -76.1761,\n 38.2903\n ],\n [\n -76.1756,\n 38.2903\n ],\n [\n -76.1747,\n 38.2911\n ],\n [\n -76.1742,\n 38.2911\n ],\n [\n -76.1733,\n 38.2919\n ],\n [\n -76.1731,\n 38.2919\n ],\n [\n -76.1717,\n 38.2933\n ],\n [\n -76.17,\n 38.2933\n ],\n [\n -76.1689,\n 38.2922\n ],\n [\n -76.1689,\n 38.2914\n ],\n [\n -76.1683,\n 38.2914\n ],\n [\n -76.1681,\n 38.2911\n ],\n [\n -76.1678,\n 38.2911\n ],\n [\n -76.1675,\n 38.2908\n ],\n [\n -76.1672,\n 38.2908\n ],\n [\n -76.1669,\n 38.2906\n ],\n [\n -76.1656,\n 38.2906\n ],\n [\n -76.1653,\n 38.2908\n ],\n [\n -76.1647,\n 38.2908\n ],\n [\n -76.1644,\n 38.2906\n ],\n [\n -76.1621,\n 38.2906\n ],\n [\n -76.1608,\n 38.2906\n ],\n [\n -76.1603,\n 38.2911\n ],\n [\n -76.1603,\n 38.2914\n ],\n [\n -76.1608,\n 38.2919\n ],\n [\n -76.1618,\n 38.2919\n ],\n [\n -76.1625,\n 38.2919\n ],\n [\n -76.1631,\n 38.2925\n ],\n [\n -76.1647,\n 38.2925\n ],\n [\n -76.165,\n 38.2928\n ],\n [\n -76.1653,\n 38.2925\n ],\n [\n -76.1656,\n 38.2925\n ],\n [\n -76.1658,\n 38.2928\n ],\n [\n -76.1664,\n 38.2928\n ],\n [\n -76.1667,\n 38.2931\n ],\n [\n -76.1672,\n 38.2931\n ],\n [\n -76.1678,\n 38.2936\n ],\n [\n -76.1681,\n 38.2936\n ],\n [\n -76.1694,\n 38.295\n ],\n [\n -76.1697,\n 38.295\n ],\n [\n -76.1706,\n 38.2958\n ],\n [\n -76.1708,\n 38.2958\n ],\n [\n -76.1713,\n 38.2963\n ]\n ]\n ],\n [\n [\n [\n -76.2596,\n 38.3418\n ],\n [\n -76.2603,\n 38.342\n ],\n [\n -76.2608,\n 38.3424\n ],\n [\n -76.2609,\n 38.3424\n ],\n [\n -76.2615,\n 38.3429\n ],\n [\n -76.262,\n 38.3433\n ],\n [\n -76.2626,\n 38.3436\n ],\n [\n -76.2632,\n 38.3434\n ],\n [\n -76.2636,\n 38.3429\n ],\n [\n -76.264,\n 38.3423\n ],\n [\n -76.2645,\n 38.3419\n ],\n [\n -76.265,\n 38.3415\n ],\n [\n -76.2655,\n 38.3411\n ],\n [\n -76.2657,\n 38.3406\n ],\n [\n -76.2656,\n 38.3402\n ],\n [\n -76.2653,\n 38.3398\n ],\n [\n -76.2648,\n 38.3395\n ],\n [\n -76.2645,\n 38.3391\n ],\n [\n -76.2642,\n 38.3387\n ],\n [\n -76.2639,\n 38.3383\n ],\n [\n -76.2634,\n 38.3381\n ],\n [\n -76.2629,\n 38.3379\n ],\n [\n -76.2625,\n 38.3377\n ],\n [\n -76.2621,\n 38.3375\n ],\n [\n -76.262,\n 38.3373\n ],\n [\n -76.2621,\n 38.3371\n ],\n [\n -76.2619,\n 38.3367\n ],\n [\n -76.2617,\n 38.3364\n ],\n [\n -76.2613,\n 38.3361\n ],\n [\n -76.2608,\n 38.3356\n ],\n [\n -76.2604,\n 38.3352\n ],\n [\n -76.26,\n 38.3349\n ],\n [\n -76.2596,\n 38.3347\n ],\n [\n -76.2597,\n 38.3344\n ],\n [\n -76.2592,\n 38.3339\n ],\n [\n -76.2592,\n 38.3336\n ],\n [\n -76.2589,\n 38.3333\n ],\n [\n -76.2589,\n 38.3328\n ],\n [\n -76.2586,\n 38.3325\n ],\n [\n -76.2586,\n 38.3319\n ],\n [\n -76.2581,\n 38.3314\n ],\n [\n -76.2581,\n 38.3308\n ],\n [\n -76.2578,\n 38.3306\n ],\n [\n -76.2578,\n 38.3272\n ],\n [\n -76.2581,\n 38.3269\n ],\n [\n -76.2581,\n 38.3258\n ],\n [\n -76.2578,\n 38.3256\n ],\n [\n -76.2581,\n 38.3253\n ],\n [\n -76.2581,\n 38.325\n ],\n [\n -76.2583,\n 38.3247\n ],\n [\n -76.2583,\n 38.3244\n ],\n [\n -76.2581,\n 38.3244\n ],\n [\n -76.2575,\n 38.3239\n ],\n [\n -76.2572,\n 38.3242\n ],\n [\n -76.2569,\n 38.3242\n ],\n [\n -76.2567,\n 38.3244\n ],\n [\n -76.2558,\n 38.3244\n ],\n [\n -76.2556,\n 38.3247\n ],\n [\n -76.2547,\n 38.3247\n ],\n [\n -76.2544,\n 38.325\n ],\n [\n -76.2542,\n 38.325\n ],\n [\n -76.2539,\n 38.3253\n ],\n [\n -76.2533,\n 38.3258\n ],\n [\n -76.2531,\n 38.3261\n ],\n [\n -76.2514,\n 38.3278\n ],\n [\n -76.2519,\n 38.3283\n ],\n [\n -76.2519,\n 38.3286\n ],\n [\n -76.2522,\n 38.3289\n ],\n [\n -76.2522,\n 38.3292\n ],\n [\n -76.2525,\n 38.3294\n ],\n [\n -76.2528,\n 38.3297\n ],\n [\n -76.253,\n 38.33\n ],\n [\n -76.2536,\n 38.3306\n ],\n [\n -76.2547,\n 38.3317\n ],\n [\n -76.255,\n 38.3317\n ],\n [\n -76.2561,\n 38.3328\n ],\n [\n -76.2567,\n 38.3333\n ],\n [\n -76.2569,\n 38.3336\n ],\n [\n -76.2569,\n 38.3339\n ],\n [\n -76.2572,\n 38.3342\n ],\n [\n -76.2575,\n 38.3344\n ],\n [\n -76.2575,\n 38.3347\n ],\n [\n -76.2578,\n 38.335\n ],\n [\n -76.2578,\n 38.3353\n ],\n [\n -76.2581,\n 38.3357\n ],\n [\n -76.258,\n 38.336\n ],\n [\n -76.2581,\n 38.3364\n ],\n [\n -76.2582,\n 38.3368\n ],\n [\n -76.2583,\n 38.3372\n ],\n [\n -76.2584,\n 38.3377\n ],\n [\n -76.2584,\n 38.3383\n ],\n [\n -76.2579,\n 38.3388\n ],\n [\n -76.2573,\n 38.3393\n ],\n [\n -76.2567,\n 38.3394\n ],\n [\n -76.2561,\n 38.3392\n ],\n [\n -76.2556,\n 38.3392\n ],\n [\n -76.2551,\n 38.3394\n ],\n [\n -76.2548,\n 38.3395\n ],\n [\n -76.2547,\n 38.3396\n ],\n [\n -76.2543,\n 38.3398\n ],\n [\n -76.2541,\n 38.3402\n ],\n [\n -76.2543,\n 38.3409\n ],\n [\n -76.2549,\n 38.3413\n ],\n [\n -76.2557,\n 38.3416\n ],\n [\n -76.256,\n 38.3416\n ],\n [\n -76.2565,\n 38.3417\n ],\n [\n -76.2573,\n 38.3419\n ],\n [\n -76.2581,\n 38.3419\n ],\n [\n -76.2588,\n 38.3417\n ],\n [\n -76.2596,\n 38.3418\n ]\n ]\n ],\n [\n [\n [\n -76.0864,\n 38.1533\n ],\n [\n -76.0867,\n 38.1536\n ],\n [\n -76.0869,\n 38.1536\n ],\n [\n -76.0872,\n 38.1533\n ],\n [\n -76.0875,\n 38.1536\n ],\n [\n -76.0881,\n 38.1536\n ],\n [\n -76.0883,\n 38.1533\n ],\n [\n -76.0883,\n 38.1528\n ],\n [\n -76.0886,\n 38.1525\n ],\n [\n -76.0894,\n 38.1525\n ],\n [\n -76.09,\n 38.1519\n ],\n [\n -76.0903,\n 38.1517\n ],\n [\n -76.0906,\n 38.1514\n ],\n [\n -76.0908,\n 38.1511\n ],\n [\n -76.0908,\n 38.1508\n ],\n [\n -76.0911,\n 38.1506\n ],\n [\n -76.0914,\n 38.1503\n ],\n [\n -76.0914,\n 38.1494\n ],\n [\n -76.0911,\n 38.1492\n ],\n [\n -76.0908,\n 38.1489\n ],\n [\n -76.0906,\n 38.1486\n ],\n [\n -76.0903,\n 38.1483\n ],\n [\n -76.09,\n 38.1481\n ],\n [\n -76.09,\n 38.1478\n ],\n [\n -76.0897,\n 38.1475\n ],\n [\n -76.0897,\n 38.1472\n ],\n [\n -76.09,\n 38.1469\n ],\n [\n -76.09,\n 38.1467\n ],\n [\n -76.0903,\n 38.1464\n ],\n [\n -76.0903,\n 38.1462\n ],\n [\n -76.0905,\n 38.1458\n ],\n [\n -76.0907,\n 38.1454\n ],\n [\n -76.0907,\n 38.1449\n ],\n [\n -76.0905,\n 38.1444\n ],\n [\n -76.0903,\n 38.144\n ],\n [\n -76.09,\n 38.1436\n ],\n [\n -76.0897,\n 38.1432\n ],\n [\n -76.0894,\n 38.1429\n ],\n [\n -76.0892,\n 38.1425\n ],\n [\n -76.0891,\n 38.142\n ],\n [\n -76.0894,\n 38.1414\n ],\n [\n -76.0892,\n 38.141\n ],\n [\n -76.0888,\n 38.1407\n ],\n [\n -76.0883,\n 38.1405\n ],\n [\n -76.0878,\n 38.1402\n ],\n [\n -76.0875,\n 38.14\n ],\n [\n -76.0872,\n 38.1397\n ],\n [\n -76.0872,\n 38.1394\n ],\n [\n -76.0869,\n 38.1392\n ],\n [\n -76.0867,\n 38.1389\n ],\n [\n -76.0864,\n 38.1386\n ],\n [\n -76.0858,\n 38.1386\n ],\n [\n -76.0856,\n 38.1389\n ],\n [\n -76.0856,\n 38.1392\n ],\n [\n -76.0853,\n 38.1394\n ],\n [\n -76.0853,\n 38.1397\n ],\n [\n -76.0856,\n 38.14\n ],\n [\n -76.0856,\n 38.1406\n ],\n [\n -76.0853,\n 38.1408\n ],\n [\n -76.0854,\n 38.141\n ],\n [\n -76.0852,\n 38.1415\n ],\n [\n -76.085,\n 38.142\n ],\n [\n -76.0847,\n 38.1425\n ],\n [\n -76.0844,\n 38.1428\n ],\n [\n -76.0841,\n 38.1432\n ],\n [\n -76.0839,\n 38.1435\n ],\n [\n -76.0839,\n 38.1439\n ],\n [\n -76.084,\n 38.1443\n ],\n [\n -76.0841,\n 38.1446\n ],\n [\n -76.0842,\n 38.1449\n ],\n [\n -76.0843,\n 38.1452\n ],\n [\n -76.0843,\n 38.1455\n ],\n [\n -76.0844,\n 38.1458\n ],\n [\n -76.085,\n 38.1464\n ],\n [\n -76.0852,\n 38.1464\n ],\n [\n -76.0856,\n 38.1466\n ],\n [\n -76.0861,\n 38.1467\n ],\n [\n -76.0866,\n 38.1469\n ],\n [\n -76.0871,\n 38.147\n ],\n [\n -76.0876,\n 38.1471\n ],\n [\n -76.0881,\n 38.1473\n ],\n [\n -76.0883,\n 38.1475\n ],\n [\n -76.0889,\n 38.1481\n ],\n [\n -76.0889,\n 38.1483\n ],\n [\n -76.0892,\n 38.1486\n ],\n [\n -76.0892,\n 38.1489\n ],\n [\n -76.0897,\n 38.1494\n ],\n [\n -76.0872,\n 38.1519\n ],\n [\n -76.0867,\n 38.1519\n ],\n [\n -76.0864,\n 38.1522\n ],\n [\n -76.0861,\n 38.1522\n ],\n [\n -76.0858,\n 38.1525\n ],\n [\n -76.0858,\n 38.1528\n ],\n [\n -76.0861,\n 38.1531\n ],\n [\n -76.0864,\n 38.1533\n ]\n ]\n ],\n [\n [\n [\n -76.0861,\n 38.1258\n ],\n [\n -76.0878,\n 38.1275\n ],\n [\n -76.0878,\n 38.1278\n ],\n [\n -76.0872,\n 38.1283\n ],\n [\n -76.0883,\n 38.1294\n ],\n [\n -76.0886,\n 38.1294\n ],\n [\n -76.0889,\n 38.1292\n ],\n [\n -76.0889,\n 38.1289\n ],\n [\n -76.0892,\n 38.1286\n ],\n [\n -76.0892,\n 38.1281\n ],\n [\n -76.0897,\n 38.1275\n ],\n [\n -76.0903,\n 38.1275\n ],\n [\n -76.0886,\n 38.1258\n ],\n [\n -76.0881,\n 38.1258\n ],\n [\n -76.0878,\n 38.1256\n ],\n [\n -76.0878,\n 38.1247\n ],\n [\n -76.0875,\n 38.1244\n ],\n [\n -76.0875,\n 38.1231\n ],\n [\n -76.0883,\n 38.1222\n ],\n [\n -76.0886,\n 38.1222\n ],\n [\n -76.0889,\n 38.1225\n ],\n [\n -76.0897,\n 38.1225\n ],\n [\n -76.09,\n 38.1222\n ],\n [\n -76.09,\n 38.1219\n ],\n [\n -76.0903,\n 38.1217\n ],\n [\n -76.0906,\n 38.1214\n ],\n [\n -76.0906,\n 38.1211\n ],\n [\n -76.0904,\n 38.1206\n ],\n [\n -76.0905,\n 38.1199\n ],\n [\n -76.0906,\n 38.1192\n ],\n [\n -76.0908,\n 38.1186\n ],\n [\n -76.0908,\n 38.118\n ],\n [\n -76.0907,\n 38.1174\n ],\n [\n -76.0907,\n 38.1168\n ],\n [\n -76.0907,\n 38.1162\n ],\n [\n -76.0904,\n 38.1157\n ],\n [\n -76.09,\n 38.1153\n ],\n [\n -76.0894,\n 38.1152\n ],\n [\n -76.0889,\n 38.1153\n ],\n [\n -76.0884,\n 38.1155\n ],\n [\n -76.0879,\n 38.1157\n ],\n [\n -76.0874,\n 38.1159\n ],\n [\n -76.0869,\n 38.1161\n ],\n [\n -76.0864,\n 38.1162\n ],\n [\n -76.086,\n 38.1165\n ],\n [\n -76.0857,\n 38.1168\n ],\n [\n -76.0855,\n 38.1172\n ],\n [\n -76.0854,\n 38.1174\n ],\n [\n -76.0853,\n 38.1176\n ],\n [\n -76.0852,\n 38.1181\n ],\n [\n -76.0848,\n 38.1185\n ],\n [\n -76.0844,\n 38.1189\n ],\n [\n -76.0842,\n 38.1193\n ],\n [\n -76.0842,\n 38.1197\n ],\n [\n -76.0843,\n 38.1201\n ],\n [\n -76.0843,\n 38.1204\n ],\n [\n -76.084,\n 38.1206\n ],\n [\n -76.0839,\n 38.1208\n ],\n [\n -76.0836,\n 38.1208\n ],\n [\n -76.0833,\n 38.1211\n ],\n [\n -76.0831,\n 38.1211\n ],\n [\n -76.0828,\n 38.1214\n ],\n [\n -76.0828,\n 38.1219\n ],\n [\n -76.0831,\n 38.1222\n ],\n [\n -76.0833,\n 38.1225\n ],\n [\n -76.0837,\n 38.1229\n ],\n [\n -76.0839,\n 38.123\n ],\n [\n -76.0839,\n 38.1239\n ],\n [\n -76.0841,\n 38.1242\n ],\n [\n -76.0844,\n 38.1241\n ],\n [\n -76.0846,\n 38.124\n ],\n [\n -76.0849,\n 38.1239\n ],\n [\n -76.0853,\n 38.1239\n ],\n [\n -76.0856,\n 38.1239\n ],\n [\n -76.0861,\n 38.1244\n ],\n [\n -76.0861,\n 38.1247\n ],\n [\n -76.0864,\n 38.125\n ],\n [\n -76.0864,\n 38.1256\n ],\n [\n -76.0861,\n 38.1258\n ]\n ]\n ],\n [\n [\n [\n -76.2753,\n 38.5425\n ],\n [\n -76.2761,\n 38.5433\n ],\n [\n -76.277,\n 38.5433\n ],\n [\n -76.2772,\n 38.5433\n ],\n [\n -76.2772,\n 38.5431\n ],\n [\n -76.2775,\n 38.5428\n ],\n [\n -76.2775,\n 38.5419\n ],\n [\n -76.2778,\n 38.5417\n ],\n [\n -76.2778,\n 38.5414\n ],\n [\n -76.2779,\n 38.5409\n ],\n [\n -76.2779,\n 38.5403\n ],\n [\n -76.2781,\n 38.54\n ],\n [\n -76.2781,\n 38.5397\n ],\n [\n -76.2781,\n 38.5394\n ],\n [\n -76.2783,\n 38.5383\n ],\n [\n -76.2787,\n 38.5378\n ],\n [\n -76.2789,\n 38.5372\n ],\n [\n -76.2792,\n 38.5369\n ],\n [\n -76.2792,\n 38.5367\n ],\n [\n -76.2794,\n 38.5364\n ],\n [\n -76.2794,\n 38.5353\n ],\n [\n -76.2796,\n 38.535\n ],\n [\n -76.2794,\n 38.5347\n ],\n [\n -76.2792,\n 38.5347\n ],\n [\n -76.2778,\n 38.5333\n ],\n [\n -76.2775,\n 38.5333\n ],\n [\n -76.2772,\n 38.5331\n ],\n [\n -76.2767,\n 38.5331\n ],\n [\n -76.2763,\n 38.5331\n ],\n [\n -76.2753,\n 38.5318\n ],\n [\n -76.2753,\n 38.5317\n ],\n [\n -76.275,\n 38.5317\n ],\n [\n -76.2747,\n 38.5314\n ],\n [\n -76.2744,\n 38.5314\n ],\n [\n -76.2739,\n 38.5319\n ],\n [\n -76.274,\n 38.5322\n ],\n [\n -76.2743,\n 38.5329\n ],\n [\n -76.2745,\n 38.5334\n ],\n [\n -76.2744,\n 38.5338\n ],\n [\n -76.274,\n 38.5342\n ],\n [\n -76.274,\n 38.5356\n ],\n [\n -76.2738,\n 38.536\n ],\n [\n -76.2736,\n 38.5364\n ],\n [\n -76.2728,\n 38.5372\n ],\n [\n -76.2725,\n 38.5372\n ],\n [\n -76.272,\n 38.5378\n ],\n [\n -76.2719,\n 38.5381\n ],\n [\n -76.2747,\n 38.5402\n ],\n [\n -76.2747,\n 38.5411\n ],\n [\n -76.275,\n 38.5417\n ],\n [\n -76.2753,\n 38.5417\n ],\n [\n -76.2753,\n 38.5425\n ]\n ]\n ],\n [\n [\n [\n -76.3378,\n 38.5028\n ],\n [\n -76.3375,\n 38.5032\n ],\n [\n -76.3373,\n 38.5036\n ],\n [\n -76.3374,\n 38.5041\n ],\n [\n -76.3377,\n 38.5045\n ],\n [\n -76.3378,\n 38.505\n ],\n [\n -76.3379,\n 38.5054\n ],\n [\n -76.3377,\n 38.5058\n ],\n [\n -76.3376,\n 38.5061\n ],\n [\n -76.3377,\n 38.5065\n ],\n [\n -76.3377,\n 38.5068\n ],\n [\n -76.3376,\n 38.5071\n ],\n [\n -76.3375,\n 38.5073\n ],\n [\n -76.3375,\n 38.5075\n ],\n [\n -76.3372,\n 38.5078\n ],\n [\n -76.3372,\n 38.5083\n ],\n [\n -76.3369,\n 38.5086\n ],\n [\n -76.3369,\n 38.5092\n ],\n [\n -76.3367,\n 38.5094\n ],\n [\n -76.3367,\n 38.5097\n ],\n [\n -76.3378,\n 38.5109\n ],\n [\n -76.338,\n 38.5107\n ],\n [\n -76.3389,\n 38.5097\n ],\n [\n -76.3392,\n 38.5094\n ],\n [\n -76.3392,\n 38.5089\n ],\n [\n -76.3394,\n 38.5086\n ],\n [\n -76.3393,\n 38.5084\n ],\n [\n -76.3394,\n 38.508\n ],\n [\n -76.3394,\n 38.5079\n ],\n [\n -76.3399,\n 38.5074\n ],\n [\n -76.3403,\n 38.5068\n ],\n [\n -76.3406,\n 38.5063\n ],\n [\n -76.3407,\n 38.5056\n ],\n [\n -76.3405,\n 38.505\n ],\n [\n -76.3402,\n 38.5045\n ],\n [\n -76.3398,\n 38.504\n ],\n [\n -76.3394,\n 38.5036\n ],\n [\n -76.3391,\n 38.5032\n ],\n [\n -76.3387,\n 38.5028\n ],\n [\n -76.3383,\n 38.5026\n ],\n [\n -76.3378,\n 38.5028\n ]\n ]\n ],\n [\n [\n [\n -76.0653,\n 38.1317\n ],\n [\n -76.0656,\n 38.1317\n ],\n [\n -76.0658,\n 38.1317\n ],\n [\n -76.0661,\n 38.1314\n ],\n [\n -76.0661,\n 38.1311\n ],\n [\n -76.0658,\n 38.1308\n ],\n [\n -76.0658,\n 38.1306\n ],\n [\n -76.0656,\n 38.1303\n ],\n [\n -76.0656,\n 38.1297\n ],\n [\n -76.0658,\n 38.1294\n ],\n [\n -76.0658,\n 38.1289\n ],\n [\n -76.0656,\n 38.1286\n ],\n [\n -76.0656,\n 38.1281\n ],\n [\n -76.0653,\n 38.1278\n ],\n [\n -76.0656,\n 38.1275\n ],\n [\n -76.0656,\n 38.1272\n ],\n [\n -76.0658,\n 38.1272\n ],\n [\n -76.0661,\n 38.1269\n ],\n [\n -76.0661,\n 38.1267\n ],\n [\n -76.0653,\n 38.1258\n ],\n [\n -76.065,\n 38.1258\n ],\n [\n -76.0644,\n 38.1253\n ],\n [\n -76.0639,\n 38.1253\n ],\n [\n -76.0636,\n 38.1256\n ],\n [\n -76.0636,\n 38.1258\n ],\n [\n -76.0633,\n 38.1261\n ],\n [\n -76.0636,\n 38.1264\n ],\n [\n -76.0633,\n 38.1267\n ],\n [\n -76.0633,\n 38.1269\n ],\n [\n -76.0636,\n 38.1272\n ],\n [\n -76.0631,\n 38.1272\n ],\n [\n -76.0628,\n 38.1269\n ],\n [\n -76.0622,\n 38.1269\n ],\n [\n -76.0619,\n 38.1267\n ],\n [\n -76.0617,\n 38.1267\n ],\n [\n -76.0614,\n 38.1264\n ],\n [\n -76.0606,\n 38.1272\n ],\n [\n -76.0617,\n 38.1283\n ],\n [\n -76.0619,\n 38.1283\n ],\n [\n -76.0653,\n 38.1317\n ]\n ]\n ],\n [\n [\n [\n -76.3344,\n 38.5186\n ],\n [\n -76.3344,\n 38.5192\n ],\n [\n -76.3342,\n 38.5194\n ],\n [\n -76.3342,\n 38.52\n ],\n [\n -76.3339,\n 38.5203\n ],\n [\n -76.3342,\n 38.5206\n ],\n [\n -76.3342,\n 38.5231\n ],\n [\n -76.3344,\n 38.5233\n ],\n [\n -76.3344,\n 38.5236\n ],\n [\n -76.3342,\n 38.5239\n ],\n [\n -76.3342,\n 38.5244\n ],\n [\n -76.3347,\n 38.525\n ],\n [\n -76.3353,\n 38.5244\n ],\n [\n -76.3356,\n 38.5244\n ],\n [\n -76.3358,\n 38.5242\n ],\n [\n -76.3367,\n 38.5233\n ],\n [\n -76.3367,\n 38.5225\n ],\n [\n -76.3369,\n 38.5222\n ],\n [\n -76.3369,\n 38.5219\n ],\n [\n -76.3378,\n 38.5211\n ],\n [\n -76.3364,\n 38.5197\n ],\n [\n -76.3361,\n 38.5192\n ],\n [\n -76.3364,\n 38.5189\n ],\n [\n -76.3364,\n 38.5186\n ],\n [\n -76.3361,\n 38.5186\n ],\n [\n -76.3353,\n 38.5178\n ],\n [\n -76.335,\n 38.5178\n ],\n [\n -76.3347,\n 38.5181\n ],\n [\n -76.3347,\n 38.5183\n ],\n [\n -76.3344,\n 38.5186\n ]\n ]\n ],\n [\n [\n [\n -76.3361,\n 38.5142\n ],\n [\n -76.3367,\n 38.5147\n ],\n [\n -76.3367,\n 38.515\n ],\n [\n -76.3369,\n 38.5153\n ],\n [\n -76.3369,\n 38.5161\n ],\n [\n -76.3367,\n 38.5164\n ],\n [\n -76.3367,\n 38.5167\n ],\n [\n -76.3375,\n 38.5175\n ],\n [\n -76.3378,\n 38.5172\n ],\n [\n -76.3389,\n 38.5172\n ],\n [\n -76.339,\n 38.5172\n ],\n [\n -76.3392,\n 38.5172\n ],\n [\n -76.34,\n 38.5164\n ],\n [\n -76.3397,\n 38.5161\n ],\n [\n -76.3397,\n 38.5158\n ],\n [\n -76.3392,\n 38.5153\n ],\n [\n -76.3392,\n 38.515\n ],\n [\n -76.3389,\n 38.5147\n ],\n [\n -76.3389,\n 38.5144\n ],\n [\n -76.3383,\n 38.5139\n ],\n [\n -76.3381,\n 38.5139\n ],\n [\n -76.3378,\n 38.5137\n ],\n [\n -76.3375,\n 38.5136\n ],\n [\n -76.3372,\n 38.5133\n ],\n [\n -76.3369,\n 38.5133\n ],\n [\n -76.3361,\n 38.5142\n ]\n ]\n ],\n [\n [\n [\n -76.0722,\n 38.1517\n ],\n [\n -76.0725,\n 38.1517\n ],\n [\n -76.0728,\n 38.1514\n ],\n [\n -76.0733,\n 38.1514\n ],\n [\n -76.0733,\n 38.1511\n ],\n [\n -76.0736,\n 38.1508\n ],\n [\n -76.0736,\n 38.1506\n ],\n [\n -76.0725,\n 38.1494\n ],\n [\n -76.0719,\n 38.1494\n ],\n [\n -76.0717,\n 38.1492\n ],\n [\n -76.0708,\n 38.1492\n ],\n [\n -76.0703,\n 38.1497\n ],\n [\n -76.07,\n 38.1497\n ],\n [\n -76.07,\n 38.15\n ],\n [\n -76.0697,\n 38.1503\n ],\n [\n -76.0703,\n 38.1508\n ],\n [\n -76.0706,\n 38.1508\n ],\n [\n -76.0708,\n 38.1511\n ],\n [\n -76.0714,\n 38.1511\n ],\n [\n -76.0717,\n 38.1514\n ],\n [\n -76.0719,\n 38.1514\n ],\n [\n -76.0722,\n 38.1517\n ]\n ]\n ],\n [\n [\n [\n -76.2117,\n 38.5639\n ],\n [\n -76.2119,\n 38.5636\n ],\n [\n -76.2133,\n 38.5636\n ],\n [\n -76.2139,\n 38.5631\n ],\n [\n -76.2139,\n 38.5628\n ],\n [\n -76.2131,\n 38.5619\n ],\n [\n -76.2128,\n 38.5619\n ],\n [\n -76.2125,\n 38.5617\n ],\n [\n -76.2122,\n 38.5617\n ],\n [\n -76.2119,\n 38.5614\n ],\n [\n -76.2111,\n 38.5614\n ],\n [\n -76.2106,\n 38.5619\n ],\n [\n -76.2106,\n 38.5625\n ],\n [\n -76.2103,\n 38.5628\n ],\n [\n -76.2103,\n 38.5633\n ],\n [\n -76.2106,\n 38.5636\n ],\n [\n -76.2114,\n 38.5636\n ],\n [\n -76.2117,\n 38.5639\n ]\n ]\n ],\n [\n [\n [\n -75.8427,\n 38.4219\n ],\n [\n -75.8436,\n 38.4219\n ],\n [\n -75.8439,\n 38.4217\n ],\n [\n -75.8439,\n 38.4214\n ],\n [\n -75.8442,\n 38.4211\n ],\n [\n -75.8444,\n 38.4208\n ],\n [\n -75.8442,\n 38.4206\n ],\n [\n -75.8442,\n 38.42\n ],\n [\n -75.8439,\n 38.4197\n ],\n [\n -75.8439,\n 38.4192\n ],\n [\n -75.8437,\n 38.4189\n ],\n [\n -75.8427,\n 38.4219\n ]\n ]\n ],\n [\n [\n [\n -75.7183,\n 38.5458\n ],\n [\n -75.7186,\n 38.5458\n ],\n [\n -75.7194,\n 38.5451\n ],\n [\n -75.7183,\n 38.5458\n ]\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.12484663930263,\n 38.08153640999504\n ],\n [\n -122.12484663930263,\n 38.046185350601434\n ],\n [\n -122.01358933993971,\n 38.046185350601434\n ],\n [\n -122.01358933993971,\n 38.08153640999504\n ],\n [\n -122.12484663930263,\n 38.08153640999504\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.11111128182661,\n 37.46403767223656\n ],\n [\n -122.11111128182661,\n 37.417702497726054\n ],\n [\n -122.02702351243062,\n 37.417702497726054\n ],\n [\n -122.02702351243062,\n 37.46403767223656\n ],\n [\n -122.11111128182661,\n 37.46403767223656\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"60","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Huang, Harrison","contributorId":344295,"corporation":false,"usgs":false,"family":"Huang","given":"Harrison","email":"","affiliations":[{"id":26951,"text":"The University of Georgia","active":true,"usgs":false}],"preferred":false,"id":921216,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poulson, Rebecca L.","contributorId":198807,"corporation":false,"usgs":false,"family":"Poulson","given":"Rebecca L.","affiliations":[{"id":7125,"text":"Southeastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA.","active":true,"usgs":false}],"preferred":false,"id":921217,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sullivan, Jeffery D. 0000-0002-9242-2432","orcid":"https://orcid.org/0000-0002-9242-2432","contributorId":265822,"corporation":false,"usgs":true,"family":"Sullivan","given":"Jeffery","email":"","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":921218,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"De La Cruz, Susan E.W. 0000-0001-6315-0864","orcid":"https://orcid.org/0000-0001-6315-0864","contributorId":202774,"corporation":false,"usgs":true,"family":"De La Cruz","given":"Susan","email":"","middleInitial":"E.W.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":921219,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walbridge, Hutchison","contributorId":347272,"corporation":false,"usgs":false,"family":"Walbridge","given":"Hutchison","email":"","affiliations":[{"id":83121,"text":"Maryland DNR","active":true,"usgs":false}],"preferred":false,"id":921220,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stallknecht, David E.","contributorId":225107,"corporation":false,"usgs":false,"family":"Stallknecht","given":"David E.","affiliations":[{"id":36701,"text":"Southeastern Cooperative Wildlife Disease Study, Department of Population Health, College of Veterinary Medicine, University of Georgia","active":true,"usgs":false}],"preferred":false,"id":921221,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Prosser, Diann 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":217931,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":921222,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70261452,"text":"sir20245122 - 2024 - Flood-inundation maps for the Cuyahoga River in and near Independence, Ohio, 2024","interactions":[],"lastModifiedDate":"2024-12-16T14:39:31.386387","indexId":"sir20245122","displayToPublicDate":"2024-12-16T08:30:00","publicationYear":"2024","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":"2024-5122","displayTitle":"Flood-Inundation Maps for the Cuyahoga River in and Near Independence, Ohio, 2024","title":"Flood-inundation maps for the Cuyahoga River in and near Independence, Ohio, 2024","docAbstract":"Digital flood-inundation maps for a 9.9-mile reach of the Cuyahoga River in and near Independence, Ohio, were created by the U.S. Geological Survey (USGS) in cooperation with the Northeast Ohio Regional Sewer District Board of Trustees. Water-surface profiles were computed for the stream reach by using a one-dimensional steady-state step-backwater model. The model was calibrated to the current (2024) stage-streamflow relation (rating curve 43.0) for the USGS streamgage 04208000, Cuyahoga River at Independence, Ohio. The resulting hydraulic model was then used to compute 13 water-surface profiles for water levels (flood stages) ranging from 14.00 to 26.00 feet. The flood stages range from “action stage” to above “major flood stage” as reported by the National Weather Service. The simulated water-surface profiles were then used in combination with a digital elevation model derived from light detection and ranging data to map the inundated areas associated with each flood profile.
The flood-inundation maps and the supporting hydraulic model produced by this study can be used by emergency managers and local officials to assess flood mitigation strategies and to define flood hazard areas to protect life and property, to coordinate flood response activities such as evacuations and road closures, and to aid postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245122","collaboration":"Prepared in cooperation with the Northeast Ohio Regional Sewer District Board of Trustees","usgsCitation":"Ostheimer, C.J., and Whitehead, M.T., 2024, Flood-inundation maps for the Cuyahoga River in and near Independence, Ohio, 2024: U.S. Geological Survey Scientific Investigations Report 2024–5122, 16 p., https://doi.org/10.3133/sir20245122.","productDescription":"Report: vi, 16 p.; Data Release","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-158401","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":464970,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5122/coverthb.jpg"},{"id":464971,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5122/sir20245122.pdf","text":"Report","size":"1.57 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5122 PDF"},{"id":464972,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245122/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5122 HTML"},{"id":464976,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20245115","text":"Scientific Investigations Report 2024–5115","linkHelpText":"Flood-Inundation Maps for the Cuyahoga River at Jaite, Ohio, 2024"},{"id":464973,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5122/sir20245122.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2024-5122 XML"},{"id":464974,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5122/images/"},{"id":464975,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZFZK0L","text":"USGS data release","linkHelpText":"Geospatial data sets and hydraulic model for the Cuyahoga River in and near the city of Independence, Ohio"}],"country":"United States","state":"Ohio","city":"Independence","otherGeospatial":"Cuyahoga River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.7238278506537,\n 41.48\n ],\n [\n -81.7238278506537,\n 41.373775959357204\n ],\n [\n -81.61067566475016,\n 41.373775959357204\n ],\n [\n -81.61067566475016,\n 41.48\n ],\n [\n -81.7238278506537,\n 41.48\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Blvd, Suite 100
Columbus, OH 43229
Objective
Growth is one of the primary drivers of fish population dynamics and understanding factors influencing growth is vital to effective management of fish populations. This study investigated potential factors influencing growth of a recently established, non-native population of Walleye Sander vitreus in the Lake Pend Oreille system in northern Idaho.
Methods
We used relative growth index to describe growth of Walleyes relative to populations across North America. Mixed‐effects modeling was used to relate growth to abiotic (i.e., mean summer water temperature, river inflow) and biotic (i.e., kokanee Oncorhynchus nerka abundance and biomass; opossum shrimp Mysis diluviana density) variables. Models were ranked using Akaike's information criterion corrected for small sample size. Individual variability in growth was related to diet represented by stable isotopes (i.e., δ15N, δ13C) using linear regression for age‐1, age‐2, age‐3, and age‐5 individuals. Subsequently, for each age‐class, we evaluated differences in δ15N and δ13C between fast‐growing (i.e., 75th and higher percentiles of growth) and slow‐growing (i.e., 25th and lower percentiles of growth) individuals.
Results
The relative growth index suggested that Walleye grew fast relative to other populations, particularly those at similar latitudes to the Lake Pend Oreille system. Mixed-effects regression modeling indicated that growth of Walleyes was positively associated with temperature as well as abundance and biomass of kokanee; growth was negatively associated with inflow from the Clark Fork River and Mysis diluviana density. The top model explaining growth of Walleyes contained temperature and abundance of kokanee as environmental variables. The second equally plausible (i.e., within 2 AICc) model contained temperature. Growth of Walleyes varied among individuals. Generally, fast-growing Walleyes had higher δ15N than slow-growing Walleyes. Similarly, δ13C was more depleted in the fast-growing individuals for all age classes, except age 1, suggesting that age-1 individuals used higher proportions of littoral prey items compared to other age classes.
Conclusion
This study showed that kokanee abundance and temperature appeared to be important factors influencing growth of Walleyes in the Lake Pend Oreille system. Additionally, variability in growth appeared to be related to variability in diet, particularly for age-1 Walleyes. Impact statement Growth of Walleyes has been extensively studied, yet few studies have evaluated growth of Walleyes in novel systems or assessed individual variability in growth. Our research adds to the understanding of individual variability in growth and factors influencing population dynamics of non-native Walleyes.
","language":"English","publisher":"Oxford Academic","doi":"10.1002/nafm.11056","collaboration":"Idaho Department of Fish and Game","usgsCitation":"Frawley, S., Corsi, M., Dux, A.M., Hardy, R.S., and Quist, M.C., 2024, Abiotic and biotic factors related to growth of non-native Walleyes in Lake Pend Oreille, Idaho: North American Journal of Fisheries Management, v. 44, no. 6, p. 1325-1341, https://doi.org/10.1002/nafm.11056.","productDescription":"17 p.","startPage":"1325","endPage":"1341","ipdsId":"IP-163539","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":485351,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Lake Pend Oreille","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.79187320079157,\n 48.33908577891279\n ],\n [\n -116.79187320079157,\n 47.933452975307574\n ],\n [\n -116.12337645556701,\n 47.933452975307574\n ],\n [\n -116.12337645556701,\n 48.33908577891279\n ],\n [\n -116.79187320079157,\n 48.33908577891279\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Frawley, Susan","contributorId":354288,"corporation":false,"usgs":false,"family":"Frawley","given":"Susan","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":935346,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corsi, Matthew P.","contributorId":171811,"corporation":false,"usgs":false,"family":"Corsi","given":"Matthew P.","affiliations":[],"preferred":false,"id":935347,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dux, Andrew M.","contributorId":175256,"corporation":false,"usgs":false,"family":"Dux","given":"Andrew","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":935348,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hardy, Ryan S.","contributorId":167032,"corporation":false,"usgs":false,"family":"Hardy","given":"Ryan","email":"","middleInitial":"S.","affiliations":[{"id":6764,"text":"Idaho Department of Fish and Game, Nampa, Idaho","active":true,"usgs":false}],"preferred":false,"id":935349,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":935350,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261643,"text":"70261643 - 2024 - Controls on lake pelagic primary productivity: Formalizing the nutrient-color paradigm","interactions":[],"lastModifiedDate":"2024-12-18T14:16:18.362641","indexId":"70261643","displayToPublicDate":"2024-12-15T12:08:58","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9326,"text":"JGR Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Controls on lake pelagic primary productivity: Formalizing the nutrient-color paradigm","docAbstract":"Understanding controls on primary productivity is essential for describing ecosystems and their responses to environmental change. Lake primary production is strongly controlled by inputs of nutrients and colored dissolved organic matter. While past studies have developed mathematical models of this nutrient-color paradigm, broad empirical tests of these models are scarce. We used data from 58 diverse and globally distributed temperate lakes to test such a model and improve understanding and prediction of the controls on lake primary production. These lakes varied widely in size (0.02-2300 km2), pelagic gross primary production (20-8000 mg C m-2 d-1), and other characteristics. Across these diverse systems, and given relatively limited inputs, model predictions of primary production were highly correlated with observed values derived from high-frequency sensor data. Our analysis provides a model structure, including calibrated parameter estimates, that may be broadly useful for understanding current and future patterns in lake primary production.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024JG008140","usgsCitation":"Oleksy, I., Solomon, C.T., Jones, S.E., Olson, C., Bertolet, B., Adrian, R., Bansal, S., Baron, J., Brothers, S., Chandra, S., Chou, H., Colom-Montero, W., Culpeper, J., de Eyto, E., Farragher, M., Hilt, S., Holeck, K.T., Kazanjian, G., Klaus, M., Klug, J., Kohler, J., Laas, A., Lundin, E., Parkes, A., Rose, K.C., Rustam, L., Rusak, J.A., Scordo, F., Vanni, M.J., Verburg, P., and Weyhenmeyer, G.A., 2024, Controls on lake pelagic primary productivity: Formalizing the nutrient-color paradigm: JGR Biogeosciences, v. 129, no. 12, e2024JG008140, 15 p., https://doi.org/10.1029/2024JG008140.","productDescription":"e2024JG008140, 15 p.","ipdsId":"IP-154658","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":466715,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024jg008140","text":"Publisher Index Page"},{"id":465207,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"129","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Oleksy, Isabella","contributorId":267296,"corporation":false,"usgs":false,"family":"Oleksy","given":"Isabella","affiliations":[{"id":33412,"text":"Cary Institute for Ecosystem Studies","active":true,"usgs":false}],"preferred":false,"id":921253,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Solomon, Christopher T.","contributorId":34014,"corporation":false,"usgs":false,"family":"Solomon","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":921254,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Stuart E.","contributorId":203400,"corporation":false,"usgs":false,"family":"Jones","given":"Stuart","email":"","middleInitial":"E.","affiliations":[{"id":36611,"text":"Notre Dame","active":true,"usgs":false}],"preferred":false,"id":921255,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olson, Carly","contributorId":347287,"corporation":false,"usgs":false,"family":"Olson","given":"Carly","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":921256,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bertolet, Brittni","contributorId":347288,"corporation":false,"usgs":false,"family":"Bertolet","given":"Brittni","email":"","affiliations":[{"id":13696,"text":"University of California Irvine","active":true,"usgs":false}],"preferred":false,"id":921257,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Adrian, Rita 0000-0002-6318-7189","orcid":"https://orcid.org/0000-0002-6318-7189","contributorId":166831,"corporation":false,"usgs":false,"family":"Adrian","given":"Rita","email":"","affiliations":[{"id":24542,"text":"Department of Ecosystem Research, Leibniz Institute of Freshwater Ecology and Inland Fisheries, Müggelseedamm 301, D- 12587 Berlin, Germany","active":true,"usgs":false}],"preferred":false,"id":921258,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bansal, Sheel 0000-0003-1233-1707 sbansal@usgs.gov","orcid":"https://orcid.org/0000-0003-1233-1707","contributorId":167295,"corporation":false,"usgs":true,"family":"Bansal","given":"Sheel","email":"sbansal@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":921259,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Baron, Jill 0000-0002-5902-6251 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":194124,"corporation":false,"usgs":true,"family":"Baron","given":"Jill","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":921260,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Brothers, Soren","contributorId":267291,"corporation":false,"usgs":false,"family":"Brothers","given":"Soren","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":921261,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Chandra, Sudeep","contributorId":296069,"corporation":false,"usgs":false,"family":"Chandra","given":"Sudeep","affiliations":[{"id":38163,"text":"UNR","active":true,"usgs":false}],"preferred":false,"id":921262,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Chou, Hsiu-Mei","contributorId":347293,"corporation":false,"usgs":false,"family":"Chou","given":"Hsiu-Mei","email":"","affiliations":[{"id":83124,"text":"National Center for High-performance computing, Taiwan","active":true,"usgs":false}],"preferred":false,"id":921263,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Colom-Montero, William","contributorId":194458,"corporation":false,"usgs":false,"family":"Colom-Montero","given":"William","email":"","affiliations":[],"preferred":false,"id":921264,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Culpeper, Joshua","contributorId":347294,"corporation":false,"usgs":false,"family":"Culpeper","given":"Joshua","email":"","affiliations":[{"id":83125,"text":"York University Canada","active":true,"usgs":false}],"preferred":false,"id":921265,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"de Eyto, Elvira","contributorId":166838,"corporation":false,"usgs":false,"family":"de Eyto","given":"Elvira","email":"","affiliations":[{"id":24549,"text":"Fisheries Ecosystems Advisory Services, Marine Institute, Furnace, Newport, Co. Mayo, Ireland.","active":true,"usgs":false}],"preferred":false,"id":921266,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Farragher, Matthew","contributorId":347295,"corporation":false,"usgs":false,"family":"Farragher","given":"Matthew","email":"","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":921267,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Hilt, Sabine","contributorId":267295,"corporation":false,"usgs":false,"family":"Hilt","given":"Sabine","email":"","affiliations":[{"id":55465,"text":"Leibniz Institute of Freshwater Ecology and Inland Fisheries, Germany","active":true,"usgs":false}],"preferred":false,"id":921268,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Holeck, Kristen T.","contributorId":105549,"corporation":false,"usgs":false,"family":"Holeck","given":"Kristen","email":"","middleInitial":"T.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":921269,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Kazanjian, Garabet","contributorId":347296,"corporation":false,"usgs":false,"family":"Kazanjian","given":"Garabet","email":"","affiliations":[{"id":83128,"text":"American University of Armenia","active":true,"usgs":false}],"preferred":false,"id":921270,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Klaus, Marcus 0000-0003-0747-3524","orcid":"https://orcid.org/0000-0003-0747-3524","contributorId":332791,"corporation":false,"usgs":false,"family":"Klaus","given":"Marcus","email":"","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":921271,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Klug, Jennifer","contributorId":194475,"corporation":false,"usgs":false,"family":"Klug","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":921272,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Kohler, Jan","contributorId":347297,"corporation":false,"usgs":false,"family":"Kohler","given":"Jan","email":"","affiliations":[{"id":83129,"text":"Leibnitz Institute for Freshwater Biology","active":true,"usgs":false}],"preferred":false,"id":921273,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Laas, Alo 0000-0002-4801-0377","orcid":"https://orcid.org/0000-0002-4801-0377","contributorId":261753,"corporation":false,"usgs":false,"family":"Laas","given":"Alo","email":"","affiliations":[{"id":18000,"text":"Estonian University of Life Sciences","active":true,"usgs":false}],"preferred":false,"id":921274,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Lundin, Erik","contributorId":347298,"corporation":false,"usgs":false,"family":"Lundin","given":"Erik","email":"","affiliations":[{"id":83130,"text":"Abisko Research Station, Sweden","active":true,"usgs":false}],"preferred":false,"id":921275,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Parkes, Alice","contributorId":347299,"corporation":false,"usgs":false,"family":"Parkes","given":"Alice","email":"","affiliations":[{"id":83131,"text":"University du Quebec","active":true,"usgs":false}],"preferred":false,"id":921276,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Rose, Kevin C.","contributorId":174809,"corporation":false,"usgs":false,"family":"Rose","given":"Kevin","email":"","middleInitial":"C.","affiliations":[{"id":12656,"text":"Rensselaer Polytechnic Institute","active":true,"usgs":false}],"preferred":false,"id":921277,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Rustam, Lars","contributorId":347300,"corporation":false,"usgs":false,"family":"Rustam","given":"Lars","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":921278,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Rusak, James A. 0000-0002-4939-6478","orcid":"https://orcid.org/0000-0002-4939-6478","contributorId":150301,"corporation":false,"usgs":false,"family":"Rusak","given":"James","email":"","middleInitial":"A.","affiliations":[{"id":17970,"text":"Dorset Environmental Science Centre, Ontario Ministry of the Environment and Climate Change, Dorset, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":921279,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Scordo, Facundo","contributorId":298282,"corporation":false,"usgs":false,"family":"Scordo","given":"Facundo","email":"","affiliations":[{"id":64520,"text":"Instituto Argentino de Oceanografía","active":true,"usgs":false}],"preferred":false,"id":921280,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Vanni, Michael J.","contributorId":204106,"corporation":false,"usgs":false,"family":"Vanni","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":36846,"text":"Department of Zoology, Miami University (Ohio)","active":true,"usgs":false}],"preferred":false,"id":921281,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Verburg, Piet","contributorId":150311,"corporation":false,"usgs":false,"family":"Verburg","given":"Piet","email":"","affiliations":[{"id":17985,"text":"National Institute of Water and Atmospheric Research, Hamilton, New Zealand","active":true,"usgs":false}],"preferred":false,"id":921282,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Weyhenmeyer, Gesa A.","contributorId":150314,"corporation":false,"usgs":false,"family":"Weyhenmeyer","given":"Gesa","email":"","middleInitial":"A.","affiliations":[{"id":17988,"text":"Department of Ecology and Genetics/Limnology, Uppsala University, Uppsala, Sweden","active":true,"usgs":false}],"preferred":false,"id":921283,"contributorType":{"id":1,"text":"Authors"},"rank":31}]}} ,{"id":70262437,"text":"70262437 - 2024 - Detection of tick-borne pathogen coinfections and coexposures to foot-and-mouth disease, brucellosis, and Q fever in selected wildlife from Kruger National Park, South Africa, and Etosha National Park, Namibia","interactions":[],"lastModifiedDate":"2025-01-24T14:13:19.130902","indexId":"70262437","displayToPublicDate":"2024-12-15T11:41:42","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3849,"text":"Transboundary and Emerging Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Detection of tick-borne pathogen coinfections and coexposures to foot-and-mouth disease, brucellosis, and Q fever in selected wildlife from Kruger National Park, South Africa, and Etosha National Park, Namibia","docAbstract":"Background: Although the rate of emerging infectious diseases that originate in wildlife has been increasing globally in recent decades, there is currently a lack of epidemiological data from wild animals.
Methodology: We used serology to determine prior exposure to foot-and-mouth disease virus (FMDV), Brucella spp., and Coxiella burnetii and used genetic testing to detect blood-borne parasitic infections in the genera Ehrlichia, Anaplasma, Theileria, and Babesia from wildlife in two national parks, Kruger National Park (KNP), South Africa, and Etosha National Park (ENP), Namibia. Serum and whole blood samples were obtained from free-roaming plains zebra (Equus quagga), greater kudu (Tragelaphus strepsiceros), impala (Aepyceros melampus), and blue wildebeest (Connochaetes taurinus). Risk factors (host species, sex, and sampling park) for infection with each pathogen were assessed, as well as the prevalence and distribution of co-occurring infections.
Results: In KNP 13/29 (45%; confidence interval [CI]: 26%–64%) kudus tested positive for FMD, but none of these reacted to SAT serotypes. For brucellosis, seropositive results were obtained for 3/29 (10%; CI: 2%–27%) kudu samples. Antibodies against C. burnetii were detected in 6/29 (21%; CI: 8%–40%) kudus, 14/21 (67%; CI: 43%–85%) impalas, and 18/39 (46%; CI: 30%–63%) zebras. A total of 28/28 kudus tested positive for Theileria spp. (100%; CI: 88%–100%) and 27/28 for Anaplasma/Ehrlichia spp. (96%; CI: 82%–100%), whereas 12/19 impalas (63%) and 2/39 zebra (5%) tested positive for Anaplasma centrale. In ENP, only 1/29 (3%; CI: 0%–18%) wildebeest samples tested positive for FMD. None of the samples tested positive for brucellosis, while C. burnetii antibodies were detected in 26/30 wildebeests (87%; CI: 69%–96%), 16/40 kudus (40%; CI: 25%–57%), and 26/26 plains zebras (100%; CI: 87%–100%). A total of 60% Anaplasma/Ehrlichia spp. and 35% Theileria/Babesia spp. in kudu and 37% wildebeest tested positive to Theileria sp. (sable), 30% to Babesia occultans, and 3%–7% to Anaplasma spp. The seroprevalence of Q fever was significantly higher in ENP, while Brucella spp., Anaplasma, Ehrlichia, Theileria, and Babesia species were significantly higher in KNP. Significant coinfections were also identified.
Conclusion: This work provided baseline serological and molecular data on 40+ pathogens in four wildlife species from two national parks in southern Africa.
","language":"English","publisher":"Wiley","doi":"10.1155/tbed/2417717","usgsCitation":"Cossu, C., Ochai, S., Troskie, M., Hartmann, A., Godfroid, J., de Klerk, L., Turner, W.C., Kamath, P., van Schalkwyk, O., Cassini, R., Bhoora, R., and van Heerden, H., 2024, Detection of tick-borne pathogen coinfections and coexposures to foot-and-mouth disease, brucellosis, and Q fever in selected wildlife from Kruger National Park, South Africa, and Etosha National Park, Namibia: Transboundary and Emerging Diseases, v. 2024, no. 1, 417717, 17 p., https://doi.org/10.1155/tbed/2417717.","productDescription":"417717, 17 p.","ipdsId":"IP-164915","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481044,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1155/tbed/2417717","text":"Publisher Index Page"},{"id":481020,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Namibia, South Africa","otherGeospatial":"Etosha National Park, Kruger National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 17.267747001056733,\n -18.251315973348596\n ],\n [\n 14.165360844846447,\n -18.251315973348596\n ],\n [\n 14.165360844846447,\n -19.553795569320044\n ],\n [\n 17.267747001056733,\n -19.553795569320044\n ],\n [\n 17.267747001056733,\n -18.251315973348596\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 31.62859728200445,\n -25.462225929230073\n ],\n [\n 32.02451863484694,\n -25.449299138508493\n ],\n [\n 32.01969032566612,\n -24.356928902710862\n ],\n [\n 31.877255204826724,\n -23.978159081244584\n ],\n [\n 31.561000953470142,\n -23.42283728028572\n ],\n [\n 31.561000953470142,\n -23.196692386847204\n ],\n [\n 31.3147571852393,\n -22.39102678165297\n ],\n [\n 30.92849245075851,\n -22.462436938380122\n ],\n [\n 30.846411194681252,\n -22.76551868913387\n ],\n [\n 30.952633996663053,\n -22.752161539326522\n ],\n [\n 30.885037668129627,\n -23.112344213827342\n ],\n [\n 31.044371871102896,\n -23.56010945242086\n ],\n [\n 31.329242112782197,\n -25.54072038355234\n ],\n [\n 31.62859728200445,\n -25.462225929230073\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2024","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Cossu, C.A.","contributorId":349298,"corporation":false,"usgs":false,"family":"Cossu","given":"C.A.","affiliations":[{"id":48053,"text":"University of Pretoria","active":true,"usgs":false}],"preferred":false,"id":924203,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ochai, S.","contributorId":349300,"corporation":false,"usgs":false,"family":"Ochai","given":"S.","affiliations":[{"id":48053,"text":"University of Pretoria","active":true,"usgs":false}],"preferred":false,"id":924204,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Troskie, M.","contributorId":349302,"corporation":false,"usgs":false,"family":"Troskie","given":"M.","affiliations":[{"id":48053,"text":"University of Pretoria","active":true,"usgs":false}],"preferred":false,"id":924205,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hartmann, A.","contributorId":213859,"corporation":false,"usgs":false,"family":"Hartmann","given":"A.","email":"","affiliations":[{"id":38911,"text":"Universities of Freiburg","active":true,"usgs":false}],"preferred":false,"id":924206,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Godfroid, J.","contributorId":349304,"corporation":false,"usgs":false,"family":"Godfroid","given":"J.","affiliations":[{"id":83468,"text":"UiT – The Arctic University of Norway","active":true,"usgs":false}],"preferred":false,"id":924207,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"de Klerk, L.-M.","contributorId":349307,"corporation":false,"usgs":false,"family":"de Klerk","given":"L.-M.","affiliations":[{"id":83470,"text":"Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":924208,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Turner, Wendy Christine 0000-0002-0302-1646","orcid":"https://orcid.org/0000-0002-0302-1646","contributorId":287053,"corporation":false,"usgs":true,"family":"Turner","given":"Wendy","email":"","middleInitial":"Christine","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":924209,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kamath, P.L.","contributorId":349309,"corporation":false,"usgs":false,"family":"Kamath","given":"P.L.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":924210,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"van Schalkwyk, O. Louis","contributorId":343075,"corporation":false,"usgs":false,"family":"van Schalkwyk","given":"O. Louis","affiliations":[{"id":48053,"text":"University of Pretoria","active":true,"usgs":false}],"preferred":false,"id":924211,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cassini, R.","contributorId":349311,"corporation":false,"usgs":false,"family":"Cassini","given":"R.","affiliations":[{"id":38039,"text":"University of Padova","active":true,"usgs":false}],"preferred":false,"id":924212,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Bhoora, R.","contributorId":349312,"corporation":false,"usgs":false,"family":"Bhoora","given":"R.","affiliations":[{"id":48053,"text":"University of Pretoria","active":true,"usgs":false}],"preferred":false,"id":924213,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"van Heerden, H.","contributorId":349313,"corporation":false,"usgs":false,"family":"van Heerden","given":"H.","affiliations":[{"id":48053,"text":"University of Pretoria","active":true,"usgs":false}],"preferred":false,"id":924214,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70262506,"text":"70262506 - 2024 - Model predictions of global geologic hydrogen resources","interactions":[],"lastModifiedDate":"2025-01-21T17:43:53.627887","indexId":"70262506","displayToPublicDate":"2024-12-13T11:41:56","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Model predictions of global geologic hydrogen resources","docAbstract":"Geologic hydrogen could be a low-carbon primary energy resource; however, the magnitude of Earth’s subsurface endowment has not yet been assessed. Knowledge of the occurrence and behavior of natural hydrogen on Earth has been combined with information from geologic analogs to construct a mass balance model to predict the resource potential. Given the associated uncertainty, stochastic model results predict a wide range of values for the potential in-place hydrogen resource [103 to 1010 million metric tons (Mt)] with the most probable value of ~5.6 × 106 Mt. Although most of this hydrogen is likely to be impractical to recover, a small fraction (e.g., 1 × 105 Mt) would supply the projected hydrogen needed to reach net-zero carbon emissions for ~200 years. This amount of hydrogen contains more energy (~1.4 × 1016 MJ) than all proven natural gas reserves on Earth (~8.4 × 1015 MJ). Study results demonstrate that further research into understanding the potential for geologic hydrogen resources is merited.
","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.ado0955","usgsCitation":"Ellis, G.S., and Gelman, S.E., 2024, Model predictions of global geologic hydrogen resources: Science Advances, v. 10, no. 50, eado0955, 11 p., https://doi.org/10.1126/sciadv.ado0955.","productDescription":"eado0955, 11 p.","ipdsId":"IP-158355","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":481046,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.ado0955","text":"Publisher Index Page"},{"id":480846,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"50","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ellis, Geoffrey S. 0000-0003-4519-3320 gsellis@usgs.gov","orcid":"https://orcid.org/0000-0003-4519-3320","contributorId":1058,"corporation":false,"usgs":true,"family":"Ellis","given":"Geoffrey","email":"gsellis@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":924399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gelman, Sarah E. 0000-0003-2549-9509","orcid":"https://orcid.org/0000-0003-2549-9509","contributorId":270004,"corporation":false,"usgs":true,"family":"Gelman","given":"Sarah","email":"","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":924400,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}