Length-at-age data are commonly used to describe growth of fish, and obtaining these data typically involves estimating ages from calcified structures (e.g., fin spines or rays, otoliths, or cleithra). Verifying the accuracy of age and growth estimates for long-lived fish is often difficult because known-age fish are not available for all ages in a population. Mark–recapture methods offer nonlethal alternatives for estimating growth of fish that do not require age data. However, few studies have compared growth trajectories estimated from mark–recapture data with trajectories estimated using the standard von Bertalanffy growth function (VBGF) incorporating length-at-age data from known-age fish. We used a robust data set of Muskellunge Esox masquinongy sampled from Green Bay, Lake Michigan, during 1990–2018 to compare growth trajectories estimated from three mark–recapture models and a VBGF fitted to length-at-age data from known-age individuals. Growth trajectories estimated with mark–recapture models were similar to trajectories estimated with a VBGF using known-age fish. Our results suggest that using recapture of tagged fish provides a viable alternative for describing Muskellunge growth trajectories compared with using ages estimated from calcified structures, where incorrect age estimates represent an additional source of error.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10757","usgsCitation":"Sheffer, R., Hogler, S., and Isermann, D.A., 2022, Mark-recapture models accurately predict growth trajectories of known-age Muskellunge in Green Bay, Lake Michigan: North American Journal of Fisheries Management, v. 42, no. 2, p. 410-424, https://doi.org/10.1002/nafm.10757.","productDescription":"15 p.","startPage":"410","endPage":"424","ipdsId":"IP-129450","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480851,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Green Bay, Lake Michigan, Sturgeon Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.27706007733632,\n 44.35374357415128\n ],\n [\n -86.88196993224543,\n 44.35374357415128\n ],\n [\n -86.88196993224543,\n 45.190198563184424\n ],\n [\n -88.27706007733632,\n 45.190198563184424\n ],\n [\n -88.27706007733632,\n 44.35374357415128\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"42","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-02-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Sheffer, Robert J.","contributorId":349585,"corporation":false,"usgs":false,"family":"Sheffer","given":"Robert J.","affiliations":[{"id":17613,"text":"University of Wisconsin - Stevens Point","active":true,"usgs":false}],"preferred":false,"id":924493,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hogler, Steven R.","contributorId":349586,"corporation":false,"usgs":false,"family":"Hogler","given":"Steven R.","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":924494,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":924492,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227601,"text":"fs20213057 - 2022 - National assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources — Summary","interactions":[],"lastModifiedDate":"2026-03-25T14:46:01.13385","indexId":"fs20213057","displayToPublicDate":"2022-02-01T12:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-3057","displayTitle":"National Assessment of Carbon Dioxide Enhanced Oil Recovery and Associated Carbon Dioxide Retention Resources—Summary","title":"National assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources — Summary","docAbstract":"In 2020, the U.S. Geological Survey (USGS) completed a probabilistic assessment of the volume of technically recoverable oil resources that might be produced by using current carbon dioxide enhanced oil recovery (CO2-EOR) technologies in amenable conventional oil reservoirs underlying the onshore and State waters areas of the conterminous United States. The assessment also includes estimates of the mass of CO2 that could be stored (retained) in the assessed oil reservoirs following the application of the CO2-EOR process. The USGS assessment team evaluated more than 3,500 oil reservoirs that were miscible to injected CO2. The assessed reservoirs are in 185 previously defined USGS plays in 33 petroleum provinces of 7 national regions. The team estimated that the total technically recoverable oil resulting from the application of the CO2-EOR process ranges from approximately 25,000 million barrels (MMbbl) at the P5 percentile to as much as 32,000 MMbbl at the P95 percentile, with a mean of 29,000 MMbbl. The associated CO2 retention ranges from approximately 7,400 million metric tons (Mt) at the P5 percentile to as much as 9,500 Mt at the P95 percentile, with a mean of 8,400 Mt. The results are summarized in this fact sheet and are provided in more detail in the companion data release and circular.
The West Texas and Eastern New Mexico region (primarily its Permian Basin) and the Gulf Coast region together contain 60 percent of the mean assessed CO2-EOR oil potential and 61 percent of the mean assessed CO2 retention. Other regions with significant resource potential include the Midcontinent region and the Rocky Mountains and Northern Great Plains region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213057","programNote":"Energy Resources Program","usgsCitation":"Warwick, P.D., Attanasi, E.D., Blondes, M.S., Brennan, S.T., Buursink, M.L., Cahan, S.M., Doolan, C.A., Freeman, P.A., Karacan, C.Ö., Lohr, C.D., Merrill, M.D., Olea, R.A., Shelton, J.L., Slucher, E.R., and Varela, B.A., 2022, National assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources—Summary: U.S. Geological Survey Fact Sheet 2021–3057, 6 p., https://doi.org/10.3133/fs20213057.","productDescription":"Report: 6 p.; Data Release","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-122387","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":395071,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2021/3057/coverthb.jpg"},{"id":395072,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2021/3057/fs20213057.pdf","text":"Report","size":"1.78 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2021-3057"},{"id":395073,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/cir1489","text":"U.S. Geological Survey Circular 1489","linkHelpText":"- National Assessment of Carbon Dioxide Enhanced Oil Recovery and Associated Carbon Dioxide Retention Resources—Results"},{"id":395074,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AG37KI","text":"USGS data release","linkHelpText":"National assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources—Data"},{"id":501481,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112324.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Continental United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 46.90008\n ],\n [\n -84.77924,\n 46.6371\n ],\n [\n -84.54375,\n 46.53868\n ],\n [\n -84.6049,\n 46.4396\n ],\n [\n -84.3367,\n 46.40877\n ],\n [\n -84.14212,\n 46.51223\n ],\n [\n -84.09185,\n 46.27542\n ],\n [\n -83.89077,\n 46.11693\n ],\n [\n -83.61613,\n 46.11693\n ],\n [\n -83.46955,\n 45.99469\n ],\n [\n -83.59285,\n 45.81689\n ],\n [\n -82.55092,\n 45.34752\n ],\n [\n -82.33776,\n 44.44\n ],\n [\n -82.13764,\n 43.57109\n ],\n [\n -82.43,\n 42.98\n ],\n [\n -82.9,\n 42.43\n ],\n [\n -83.12,\n 42.08\n ],\n [\n -83.142,\n 41.97568\n ],\n [\n -83.02981,\n 41.8328\n ],\n [\n -82.69009,\n 41.67511\n ],\n [\n -82.43928,\n 41.67511\n ],\n [\n -81.27775,\n 42.20903\n ],\n [\n -80.24745,\n 42.3662\n ],\n [\n -78.93936,\n 42.86361\n ],\n [\n -78.92,\n 42.965\n ],\n [\n -79.01,\n 43.27\n ],\n [\n -79.17167,\n 43.46634\n ],\n [\n -78.72028,\n 43.62509\n ],\n [\n -77.73789,\n 43.62906\n ],\n [\n -76.82003,\n 43.62878\n ],\n [\n -76.5,\n 44.01846\n ],\n [\n -76.375,\n 44.09631\n ],\n [\n -75.31821,\n 44.81645\n ],\n [\n -74.867,\n 45.00048\n ],\n [\n -73.34783,\n 45.00738\n ],\n [\n -71.50506,\n 45.0082\n ],\n [\n -71.405,\n 45.255\n ],\n [\n -71.08482,\n 45.30524\n ],\n [\n -70.66,\n 45.46\n ],\n [\n -70.305,\n 45.915\n ],\n [\n -69.99997,\n 46.69307\n ],\n [\n -69.23722,\n 47.44778\n ],\n [\n -68.905,\n 47.185\n ],\n [\n -68.23444,\n 47.35486\n ],\n [\n -67.79046,\n 47.06636\n ],\n [\n -67.79134,\n 45.70281\n ],\n [\n -67.13741,\n 45.13753\n ],\n [\n -66.96466,\n 44.8097\n ],\n [\n -68.03252,\n 44.3252\n ],\n [\n -69.06,\n 43.98\n ],\n [\n -70.11617,\n 43.68405\n ],\n [\n -70.64548,\n 43.09024\n ],\n [\n -70.81489,\n 42.8653\n ],\n [\n -70.825,\n 42.335\n ],\n [\n -70.495,\n 41.805\n ],\n [\n -70.08,\n 41.78\n ],\n [\n -70.185,\n 42.145\n ],\n [\n -69.88497,\n 41.92283\n ],\n [\n -69.96503,\n 41.63717\n ],\n [\n -70.64,\n 41.475\n ],\n [\n -71.12039,\n 41.49445\n ],\n [\n -71.86,\n 41.32\n ],\n [\n -72.295,\n 41.27\n ],\n [\n -72.87643,\n 41.22065\n ],\n [\n -73.71,\n 40.9311\n ],\n [\n -72.24126,\n 41.11948\n ],\n [\n -71.945,\n 40.93\n ],\n [\n -73.345,\n 40.63\n ],\n [\n -73.982,\n 40.628\n ],\n [\n -73.95232,\n 40.75075\n ],\n [\n -74.25671,\n 40.47351\n ],\n [\n -73.96244,\n 40.42763\n ],\n [\n -74.17838,\n 39.70926\n ],\n [\n -74.90604,\n 38.93954\n ],\n [\n -74.98041,\n 39.1964\n ],\n [\n -75.20002,\n 39.24845\n ],\n [\n -75.52805,\n 39.4985\n ],\n [\n -75.32,\n 38.96\n ],\n [\n -75.07183,\n 38.78203\n ],\n [\n -75.05673,\n 38.40412\n ],\n [\n -75.37747,\n 38.01551\n ],\n [\n -75.94023,\n 37.21689\n ],\n [\n -76.03127,\n 37.2566\n ],\n [\n -75.72205,\n 37.93705\n ],\n [\n -76.23287,\n 38.31921\n ],\n [\n -76.35,\n 39.15\n ],\n [\n -76.54272,\n 38.71762\n ],\n [\n -76.32933,\n 38.08326\n ],\n [\n -76.99,\n 38.23999\n ],\n [\n -76.30162,\n 37.91794\n ],\n [\n -76.25874,\n 36.9664\n ],\n [\n -75.9718,\n 36.89726\n ],\n [\n -75.86804,\n 36.55125\n ],\n [\n -75.72749,\n 35.55074\n ],\n [\n -76.36318,\n 34.80854\n ],\n [\n -77.39763,\n 34.51201\n ],\n [\n -78.05496,\n 33.92547\n ],\n [\n -78.55435,\n 33.86133\n ],\n [\n -79.06067,\n 33.49395\n ],\n [\n -79.20357,\n 33.15839\n ],\n [\n -80.30132,\n 32.50935\n ],\n [\n -80.86498,\n 32.0333\n ],\n [\n -81.33629,\n 31.44049\n ],\n [\n -81.49042,\n 30.72999\n ],\n [\n -81.31371,\n 30.03552\n ],\n [\n -80.98,\n 29.18\n ],\n [\n -80.53558,\n 28.47213\n ],\n [\n -80.53,\n 28.04\n ],\n [\n -80.05654,\n 26.88\n ],\n [\n -80.08801,\n 26.20576\n ],\n [\n -80.13156,\n 25.81677\n ],\n [\n -80.38103,\n 25.20616\n ],\n [\n -80.68,\n 25.08\n ],\n [\n -81.17213,\n 25.20126\n ],\n [\n -81.33,\n 25.64\n ],\n [\n -81.71,\n 25.87\n ],\n [\n -82.24,\n 26.73\n ],\n [\n -82.70515,\n 27.49504\n ],\n [\n -82.85526,\n 27.88624\n ],\n [\n -82.65,\n 28.55\n ],\n [\n -82.93,\n 29.1\n ],\n [\n -83.70959,\n 29.93656\n ],\n [\n -84.1,\n 30.09\n ],\n [\n -85.10882,\n 29.63615\n ],\n [\n -85.28784,\n 29.68612\n ],\n [\n -85.7731,\n 30.15261\n ],\n [\n -86.4,\n 30.4\n ],\n [\n -87.53036,\n 30.27433\n ],\n [\n -88.41782,\n 30.3849\n ],\n [\n -89.18049,\n 30.31598\n ],\n [\n -89.59383,\n 30.15999\n ],\n [\n -89.41373,\n 29.89419\n ],\n [\n -89.43,\n 29.48864\n ],\n [\n -89.21767,\n 29.29108\n ],\n [\n -89.40823,\n 29.15961\n ],\n [\n -89.77928,\n 29.30714\n ],\n [\n -90.15463,\n 29.11743\n ],\n [\n -90.88022,\n 29.14854\n ],\n [\n -91.62678,\n 29.677\n ],\n [\n -92.49906,\n 29.5523\n ],\n [\n -93.22637,\n 29.78375\n ],\n [\n -93.84842,\n 29.71363\n ],\n [\n -94.69,\n 29.48\n ],\n [\n -95.60026,\n 28.73863\n ],\n [\n -96.59404,\n 28.30748\n ],\n [\n -97.14,\n 27.83\n ],\n [\n -97.37,\n 27.38\n ],\n [\n -97.38,\n 26.69\n ],\n [\n -97.33,\n 26.21\n ],\n [\n -97.14,\n 25.87\n ],\n [\n -97.53,\n 25.84\n ],\n [\n -98.24,\n 26.06\n ],\n [\n -99.02,\n 26.37\n ],\n [\n -99.3,\n 26.84\n ],\n [\n -99.52,\n 27.54\n ],\n [\n -100.11,\n 28.11\n ],\n [\n -100.45584,\n 28.69612\n ],\n [\n -100.9576,\n 29.38071\n ],\n [\n -101.6624,\n 29.7793\n ],\n [\n -102.48,\n 29.76\n ],\n [\n -103.11,\n 28.97\n ],\n [\n -103.94,\n 29.27\n ],\n [\n -104.45697,\n 29.57196\n ],\n [\n -104.70575,\n 30.12173\n ],\n [\n -105.03737,\n 30.64402\n ],\n [\n -105.63159,\n 31.08383\n ],\n [\n -106.1429,\n 31.39995\n ],\n [\n -106.50759,\n 31.75452\n ],\n [\n -108.24,\n 31.75485\n ],\n [\n -108.24194,\n 31.34222\n ],\n [\n -109.035,\n 31.34194\n ],\n [\n -111.02361,\n 31.33472\n ],\n [\n -113.30498,\n 32.03914\n ],\n [\n -114.815,\n 32.52528\n ],\n [\n -114.72139,\n 32.72083\n ],\n [\n -115.99135,\n 32.61239\n ],\n [\n -117.12776,\n 32.53534\n ],\n [\n -117.29594,\n 33.04622\n ],\n [\n -117.944,\n 33.62124\n ],\n [\n -118.4106,\n 33.74091\n ],\n [\n -118.51989,\n 34.02778\n ],\n [\n -119.081,\n 34.078\n ],\n [\n -119.43884,\n 34.34848\n ],\n [\n -120.36778,\n 34.44711\n ],\n [\n -120.62286,\n 34.60855\n ],\n [\n -120.74433,\n 35.15686\n ],\n [\n -121.71457,\n 36.16153\n ],\n [\n -122.54747,\n 37.55176\n ],\n [\n -122.51201,\n 37.78339\n ],\n [\n -122.95319,\n 38.11371\n ],\n [\n -123.7272,\n 38.95166\n ],\n [\n -123.86517,\n 39.76699\n ],\n [\n -124.39807,\n 40.3132\n ],\n [\n -124.17886,\n 41.14202\n ],\n [\n -124.2137,\n 41.99964\n ],\n [\n -124.53284,\n 42.76599\n ],\n [\n -124.14214,\n 43.70838\n ],\n [\n -124.02053,\n 44.6159\n ],\n [\n -123.89893,\n 45.52341\n ],\n [\n -124.07963,\n 46.86475\n ],\n [\n -124.39567,\n 47.72017\n ],\n [\n -124.68721,\n 48.18443\n ],\n [\n -124.5661,\n 48.37971\n ],\n [\n -123.12,\n 48.04\n ],\n [\n -122.58736,\n 47.096\n ],\n [\n -122.34,\n 47.36\n ],\n [\n -122.5,\n 48.18\n ],\n [\n -122.84,\n 49\n ],\n [\n -120,\n 49\n ],\n [\n -117.03121,\n 49\n ],\n [\n -116.04818,\n 49\n ],\n [\n -113,\n 49\n ],\n [\n -110.05,\n 49\n ],\n [\n -107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","contact":"Program Coordinator, Energy Resources Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Telephone: 703–648–6470
The Living Shoreline Demonstration Project (PO-148) used five bio-engineered reef technologies (Reef Balls in two configurations; Figure 1) acting as breakwaters to protect vulnerable shorelines. While the primary goal is to attenuate wave energy, the sustainability and success of these products as “living” shorelines are based on their ability to enhance oyster habitat, enabling the reef to maintain elevation within the rapidly changing environment (i.e., sea level rise, subsidence). This report documents the recruitment, survival, and growth of the living components of the reef – oysters and other encrusting organisms (e.g. mussels, barnacles). This final technical report provides data from five years of monitoring (November 2017 – December 2021) of reefs located along the western side of Eloi Bay in Pontchartrain Basin (Figure 2). Monitoring goals included assessment of (1) annual oyster densities and population dynamics on the reefs, (2) annual density and diversity of other encrusting organisms, and (3) comparisons of outcomes by reef technology, exposure, and water quality. Detailed information on technologies used, construction design, as-built elevations are available in Coast & Harbor Engineering (2016) Design Memorandum dated March 25, 2016, submitted to Louisiana Coastal Protection and Restoration Authority.
","language":"English","publisher":"U.S. Fish & Wildlife Service","doi":"10.3996/css70529922","usgsCitation":"Swam, L.M., Marshall, D.A., and La Peyre, M., 2022, Five years of monitoring a bio-engineered living shoreline: Comparison of oyster population development by reef technology.: Cooperator Science Series 139-2022, ii, 19 p., https://doi.org/10.3996/css70529922.","productDescription":"ii, 19 p.","ipdsId":"IP-137095","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":433383,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.38780223527601,\n 29.790840321829222\n ],\n [\n -89.42069143656458,\n 29.790840321829222\n ],\n [\n -89.42069143656458,\n 29.750906524072846\n ],\n [\n -89.38780223527601,\n 29.750906524072846\n ],\n [\n -89.38780223527601,\n 29.790840321829222\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2022-02-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Swam, Lauren M.","contributorId":341585,"corporation":false,"usgs":false,"family":"Swam","given":"Lauren","email":"","middleInitial":"M.","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":908644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marshall, Danielle Aguilar","contributorId":341509,"corporation":false,"usgs":false,"family":"Marshall","given":"Danielle","email":"","middleInitial":"Aguilar","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":908645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908646,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70249400,"text":"70249400 - 2022 - Comment on ‘Evidence for a large strike-slip component during the 1960 Chilean earthquake’ by H. Kanamori, L. Rivera, and S. Lambotte","interactions":[],"lastModifiedDate":"2023-10-05T15:52:18.805799","indexId":"70249400","displayToPublicDate":"2022-02-01T10:40:16","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Comment on ‘Evidence for a large strike-slip component during the 1960 Chilean earthquake’ by H. Kanamori, L. Rivera, and S. Lambotte","docAbstract":"Based on numerous studies of the relevant geodetic data, a low-angle thrusting mechanism has been assigned to the 1960 Chile earthquake. Kanamori, Rivera and Lambotte recently suggested that a component of dextral slip comparable to the thrusting be included in the mechanism to satisfy long-period, teleseismic observations. The absence of geodetic evidence for that huge strike-slip component is the subject of this comment. The geodetic data are largely measurements of coseismic uplift associated with the earthquake but include eight measurements of the coseismic change in shear strain. Because strike-slip produces relatively little uplift except near the end points of the rupture, identification of that strike-slip component in the geodetic data depends upon the measured, shear-strain change. I consider elastic, half-space models of oblique slip on the plate interface possibly supplemented by simultaneous dextral slip on the nearby, intra-arc Liquiñe-Ofqui Fault Zone. Slip is assumed to be uniform along strike. The best fits to the geodetic data for these models furnish little evidence for strike-slip on those structures. To satisfy the long-period, teleseismic data, Kanamori et al. proposed six examples, each of which requires a large amount of dextral slip. Because the long-period, teleseismic data do not define the slip distributions, I have used the best fits of those examples to the geodetic data to define those distributions. The large thrusting near the deformation front required by those slip distributions implies large uplift there, contrary to the uplift inferred from the inversion of tsunami data. However, an acceptable fit to the geodetic data and the tsunami data for the six examples suggested by Kanamori et al. can be obtained if the seismic moments specified by them are reduced by a factor ∼1.8, a factor within the uncertainties in estimating seismic moments of the 1960 Chile earthquake. The presence of strike-slip in those reduced-moment examples despite the lack of geodetic evidence for strike-slip is due to a remarkable coincidence that requires careful balancing of contributions from the shallower (depths < 70 km) coseismic sources against those from the deeper coseismic sources to nullify the geodetic evidence for strike-slip. Such balancing is possible, but it is remarkable that the balancing is so nearly perfect that it nullifies the geodetic evidence for strike-slip and thereby confounds the interpretation of the geodetic data.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/gji/ggab364","usgsCitation":"Savage, J.C., 2022, Comment on ‘Evidence for a large strike-slip component during the 1960 Chilean earthquake’ by H. Kanamori, L. Rivera, and S. Lambotte: Geophysical Journal International, v. 228, no. 2, p. 1171-1183, https://doi.org/10.1093/gji/ggab364.","productDescription":"13 p.","startPage":"1171","endPage":"1183","ipdsId":"IP-125867","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":448933,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggab364","text":"Publisher Index Page"},{"id":421685,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.62290268776883,\n -41.93096350040826\n ],\n [\n -73.34570838839286,\n -41.974387007121464\n ],\n [\n -72.9825894437626,\n -41.75429549982772\n ],\n [\n -72.96763150248628,\n -41.60736935174207\n ],\n [\n -72.78858236142116,\n -41.64958770812911\n ],\n [\n -72.6369576528433,\n -41.80724579413819\n ],\n [\n -72.23671514143334,\n -41.649346857885725\n ],\n [\n -71.69201845499569,\n -41.984312584455814\n ],\n [\n -71.69522438666706,\n -41.815697968432445\n ],\n [\n -71.76740783030051,\n -41.64787879126947\n ],\n [\n -71.78552671993323,\n -41.38614438190676\n ],\n [\n -71.7751833482054,\n -41.17737714562025\n ],\n [\n -71.74953816876892,\n -41.07311875681735\n ],\n [\n -71.8191943798925,\n -40.97985288105001\n ],\n [\n -71.89009398382824,\n -40.77257691857091\n ],\n [\n -71.73215655619865,\n -40.46132365518655\n ],\n [\n -71.57185347461736,\n -40.36738376439485\n ],\n [\n -71.64065488059424,\n -40.285265884029286\n ],\n [\n -71.73517047813846,\n -40.265204013747464\n ],\n [\n -71.75075334149443,\n -40.12099718383629\n ],\n [\n -71.62946724233072,\n -40.15116165120311\n ],\n [\n -71.6311844303666,\n -40.048174584913525\n ],\n [\n -71.52655838859442,\n -39.903372705911956\n ],\n [\n -71.63487095408577,\n -39.82189181562215\n ],\n [\n -71.63763511126382,\n -39.64727812965828\n ],\n [\n -71.50354864226543,\n -39.69762968642218\n ],\n [\n -71.39948707981034,\n -39.56327662927413\n ],\n [\n -71.40300434894162,\n -39.378627532533095\n ],\n [\n -71.32502388971716,\n -39.29586592902667\n ],\n [\n -71.38465226260745,\n -38.937832524455835\n ],\n [\n -71.05843113276248,\n -38.780583277932294\n ],\n [\n -70.88694272902154,\n -38.78855203695805\n ],\n [\n -70.81101116479402,\n -38.66451207316676\n ],\n [\n -70.7749501265044,\n -38.53077415884645\n ],\n [\n -70.97560579588131,\n -38.36981973750506\n ],\n [\n -70.99202400689082,\n -38.21640781046331\n ],\n [\n -70.92937366185248,\n -38.092556412144305\n ],\n [\n -71.07689021790793,\n -37.8897193455203\n ],\n [\n -71.14597806410444,\n -37.66510265373406\n ],\n [\n -71.06985432025033,\n -37.571690637564295\n ],\n [\n -71.12540509007076,\n -37.35686997541755\n ],\n [\n -71.10234501080248,\n -37.19207224989094\n ],\n [\n -71.10370587474827,\n -37.10979459818274\n ],\n [\n -71.27163983536528,\n -37.081310719795184\n ],\n [\n -71.51758878863824,\n -36.960807838492244\n ],\n [\n -71.63168278398086,\n -37.1060414103173\n ],\n [\n -71.7862661334001,\n -37.0765757199202\n ],\n [\n -71.96566406387075,\n -37.14983819514507\n ],\n [\n -72.22267571707626,\n -37.17168020165095\n ],\n [\n -72.1719207919991,\n -37.027567751702875\n ],\n [\n -72.37763330461355,\n -36.87388865798685\n ],\n [\n -72.49293042971885,\n -36.88437582165398\n ],\n [\n -72.58264974461675,\n -36.66802712808646\n ],\n [\n -72.77421646777714,\n -36.55433080327922\n ],\n [\n -72.7867946962433,\n -36.450987531259614\n ],\n [\n -72.91428399618187,\n -36.41961548989544\n ],\n [\n -73.00427382175775,\n -36.59490463447269\n ],\n [\n -73.11934181053206,\n -36.604653547565476\n ],\n [\n -73.26092674532464,\n -36.74818753211576\n ],\n [\n -73.18486563937319,\n -36.87233386904783\n ],\n [\n -73.22449496178183,\n -37.047036770722414\n ],\n [\n -73.28989240084661,\n -37.20078628735616\n ],\n [\n -73.62373347135131,\n -37.12595923386511\n ],\n [\n -73.72850785216865,\n -37.26872196897685\n ],\n [\n -73.62770553112973,\n -37.46486690459594\n ],\n [\n -73.73327770553277,\n -37.627889999154256\n ],\n [\n -73.67098260968089,\n -37.81303289741536\n ],\n [\n -73.53011925024327,\n -37.96796874878164\n ],\n [\n -73.50667826068906,\n -38.18313122011774\n ],\n [\n -73.57451585639208,\n -38.38723832447627\n ],\n [\n -73.48714073858804,\n -38.715361623259064\n ],\n [\n -73.30775121946283,\n -39.12595001996541\n ],\n [\n -73.2710518678547,\n -39.40277109120861\n ],\n [\n -73.44773686426382,\n -39.719848877533835\n ],\n [\n -73.51641573140785,\n -39.85299271524701\n ],\n [\n -73.74537198350639,\n -39.94389488614135\n ],\n [\n -73.74780066320706,\n -40.067407450495644\n ],\n [\n -73.77802006647198,\n -40.23207437215475\n ],\n [\n -73.83755526957401,\n -40.48977371770219\n ],\n [\n -73.78526674836363,\n -40.572932656630286\n ],\n [\n -73.91192477377425,\n -40.768793546889555\n ],\n [\n -74.01153449460568,\n -40.934110805707476\n ],\n [\n -73.97783023195865,\n -41.20512015334285\n ],\n [\n -73.92794672882377,\n -41.39351048195232\n ],\n [\n -73.97329894538674,\n -41.539766884958496\n ],\n [\n -73.7560278109315,\n -41.68813965279518\n ],\n [\n -73.62290268776883,\n -41.93096350040826\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"228","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-10-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Savage, James C. 0000-0002-5114-7673 jasavage@usgs.gov","orcid":"https://orcid.org/0000-0002-5114-7673","contributorId":2412,"corporation":false,"usgs":true,"family":"Savage","given":"James","email":"jasavage@usgs.gov","middleInitial":"C.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":885482,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70227892,"text":"70227892 - 2022 - Health surveillance of a potential bridge host: Pathogen exposure risks posed to avian populations augmented with captive-bred pheasants","interactions":[],"lastModifiedDate":"2022-05-13T14:39:58.812289","indexId":"70227892","displayToPublicDate":"2022-02-01T10:17:04","publicationYear":"2022","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":"Health surveillance of a potential bridge host: Pathogen exposure risks posed to avian populations augmented with captive-bred pheasants","docAbstract":"Augmentation of wild populations with captive-bred individuals presents an inherent risk of co-introducing novel pathogens to naïve species, but it can be an important tool for supplementing small or declining populations. Game species used for human enterprise and recreation such as the ring-necked pheasant (Phasianus colchicus) are commonly raised in captivity and released onto public and private wildlands as a method of augmenting naturalized pheasant populations. This study presents findings on pathogen exposure from three sources of serological data collected in California during 2014–2017 including (a) 71 pen-reared pheasants sampled across seven game bird breeding farms, (b) six previously released pen-reared pheasants captured at two study sites where wild pheasants occurred and (c) 79 wild pheasants captured across six study sites. In both pen-reared and wild pheasants, antibodies were detected against haemorrhagic enteritis virus (HEV), infectious laryngotracheitis (ILT), infectious bursal disease virus (IBDV), paramyxovirus type 1 (PMV-1) and Pasteurella multocida (PM). Previously released pen-reared pheasants were seropositive for HEV, ILT, and PM. Generalized linear mixed models accounting for intraclass correlation within groups indicated that pen-reared pheasants were more than twice as likely to test positive for HEV antibodies. Necropsy and ancillary diagnostics were performed in addition to serological testing on 40 pen-reared pheasants sampled from five of the seven farms. Pheasants from three of these farms tested positive by PCR for Siadenovirus, the causative agent of both haemorrhagic enteritis in turkeys and marble spleen disease of pheasants, which are serologically indistinguishable. Following necropsy, owners from the five farms were surveyed regarding husbandry and biosecurity practices. Farms ranged in size from 10,000 to more than 100,000 birds, two farms raised other game bird species on premises, and two farms used some form of vaccination. Biosecurity practices varied by farm, but the largest farm implemented the strictest practices.
","language":"English","publisher":"Wiley","doi":"10.1111/tbed.14068","usgsCitation":"Dwight, I., Coates, P.S., Stoute, S.T., and Pitesky, M.E., 2022, Health surveillance of a potential bridge host: Pathogen exposure risks posed to avian populations augmented with captive-bred pheasants: Transboundary and Emerging Diseases, v. 69, no. 3, p. 1095-1107, https://doi.org/10.1111/tbed.14068.","productDescription":"13 p.","startPage":"1095","endPage":"1107","ipdsId":"IP-119580","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":448936,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/tbed.14068","text":"Publisher Index Page"},{"id":395209,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento and San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.33349609375,\n 34.88593094075317\n ],\n [\n -118.71826171875,\n 35.191766965947394\n ],\n [\n -118.41064453125,\n 35.871246850027966\n ],\n [\n -119.44335937499999,\n 37.3002752813443\n ],\n [\n -120.80566406250001,\n 39.14710270770074\n ],\n [\n -121.53076171875,\n 40.51379915504413\n ],\n [\n -120.43212890625,\n 41.244772343082076\n ],\n [\n -120.4541015625,\n 42.01665183556825\n ],\n [\n -122.32177734375,\n 42.032974332441405\n ],\n [\n -122.9150390625,\n 41.07935114946899\n ],\n [\n -122.87109375,\n 39.26628442213066\n ],\n [\n -121.88232421875,\n 37.75334401310656\n ],\n [\n -120.73974609374999,\n 36.155617833818525\n ],\n [\n -119.33349609375,\n 34.88593094075317\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"69","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-05-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Dwight, Ian 0000-0002-8393-5391 idwight@usgs.gov","orcid":"https://orcid.org/0000-0002-8393-5391","contributorId":192077,"corporation":false,"usgs":true,"family":"Dwight","given":"Ian","email":"idwight@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":832482,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":832483,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stoute, Simone T.","contributorId":202770,"corporation":false,"usgs":false,"family":"Stoute","given":"Simone","email":"","middleInitial":"T.","affiliations":[{"id":36526,"text":"California Animal Health and Food Safety Laboratory","active":true,"usgs":false}],"preferred":false,"id":832484,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pitesky, Maurice E.","contributorId":176920,"corporation":false,"usgs":false,"family":"Pitesky","given":"Maurice","email":"","middleInitial":"E.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":832485,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70229539,"text":"70229539 - 2022 - Guiding principles for using satellite-derived maps in rangeland management","interactions":[],"lastModifiedDate":"2024-05-17T16:00:34.965217","indexId":"70229539","displayToPublicDate":"2022-02-01T09:27:16","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3230,"text":"Rangelands","active":true,"publicationSubtype":{"id":10}},"title":"Guiding principles for using satellite-derived maps in rangeland management","docAbstract":"On the Ground
Floods are the leading cause of natural disaster damages in the United States, with billions of dollars incurred every year in the form of government payouts, property damages, and agricultural losses. The Federal Emergency Management Agency oversees the delineation of floodplains to mitigate damages, but disparities exist between locations designated as high risk and where flood damages occur due to land use and climate changes and incomplete floodplain mapping. We harnessed publicly available geospatial datasets and random forest algorithms to analyze the spatial distribution and underlying drivers of flood damage probability caused by excessive rainfall and overflowing water bodies across the conterminous United States. From this, we produced the first spatially complete map of flood damage probability for the nation, along with spatially explicit standard errors for four selected cities. We trained models using the locations of historical reported flood damage events (n = 71,434) and a suite of geospatial predictors (e.g., flood severity, climate, socio-economic exposure, topographic variables, soil properties, and hydrologic characteristics). We developed independent models for each hydrologic unit code level 2 watershed and generated a flood damage probability for each 100-m pixel. Our model classified damage or no damage with an average area under the curve accuracy of 0.75; however, model performance varied by environmental conditions, with certain land cover classes (e.g., forest) resulting in higher error rates than others (e.g., wetlands). Our results identified flood damage probability hotspots across multiple spatial and regional scales, with high probabilities common in both inland and coastal regions. The highest flood damage probabilities tended to be in areas of low elevation, in close proximity to streams, with extreme precipitation, and with high urban road density. Given rapid environmental changes, our study demonstrates an efficient approach for updating flood damage probability estimates across the nation.
","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/ac4f0f","usgsCitation":"Collins, E., Sanchez, G., Terando, A., Stillwell, C.C., Mitasova, H., Sebastian, A., and Meentemeyer, R.K., 2022, Predicting flood damage probability across the conterminous United States: Environmental Research Letters, v. 17, 034006, 15 p., https://doi.org/10.1088/1748-9326/ac4f0f.","productDescription":"034006, 15 p.","ipdsId":"IP-133941","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":448948,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ac4f0f","text":"Publisher Index Page"},{"id":435984,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P954TTQN","text":"USGS data release","linkHelpText":"Data and Code for Predicting Flood Damage Probability Across the Conterminous United States"},{"id":406535,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 46.90008\n ],\n [\n -84.77924,\n 46.6371\n ],\n [\n -84.54375,\n 46.53868\n ],\n [\n -84.6049,\n 46.4396\n ],\n [\n -84.3367,\n 46.40877\n ],\n [\n -84.14212,\n 46.51223\n ],\n [\n -84.09185,\n 46.27542\n ],\n [\n -83.89077,\n 46.11693\n ],\n [\n -83.61613,\n 46.11693\n ],\n [\n -83.46955,\n 45.99469\n ],\n [\n -83.59285,\n 45.81689\n ],\n [\n -82.55092,\n 45.34752\n ],\n [\n -82.33776,\n 44.44\n ],\n [\n -82.13764,\n 43.57109\n ],\n [\n -82.43,\n 42.98\n ],\n [\n -82.9,\n 42.43\n ],\n [\n -83.12,\n 42.08\n ],\n [\n -83.142,\n 41.97568\n ],\n [\n -83.02981,\n 41.8328\n ],\n [\n -82.69009,\n 41.67511\n ],\n [\n -82.43928,\n 41.67511\n ],\n [\n -81.27775,\n 42.20903\n ],\n [\n -80.24745,\n 42.3662\n ],\n [\n -78.93936,\n 42.86361\n ],\n [\n -78.92,\n 42.965\n ],\n [\n -79.01,\n 43.27\n ],\n [\n -79.17167,\n 43.46634\n ],\n [\n -78.72028,\n 43.62509\n ],\n [\n -77.73789,\n 43.62906\n ],\n [\n -76.82003,\n 43.62878\n ],\n [\n -76.5,\n 44.01846\n ],\n [\n -76.375,\n 44.09631\n ],\n [\n -75.31821,\n 44.81645\n ],\n [\n -74.867,\n 45.00048\n ],\n [\n -73.34783,\n 45.00738\n ],\n [\n -71.50506,\n 45.0082\n ],\n [\n -71.405,\n 45.255\n ],\n [\n -71.08482,\n 45.30524\n ],\n [\n -70.66,\n 45.46\n ],\n [\n -70.305,\n 45.915\n ],\n [\n -69.99997,\n 46.69307\n ],\n [\n -69.23722,\n 47.44778\n ],\n [\n -68.905,\n 47.185\n ],\n [\n -68.23444,\n 47.35486\n ],\n [\n -67.79046,\n 47.06636\n ],\n [\n -67.79134,\n 45.70281\n ],\n [\n -67.13741,\n 45.13753\n ],\n [\n -66.96466,\n 44.8097\n ],\n [\n -68.03252,\n 44.3252\n ],\n [\n -69.06,\n 43.98\n ],\n [\n -70.11617,\n 43.68405\n ],\n [\n -70.64548,\n 43.09024\n ],\n [\n -70.81489,\n 42.8653\n ],\n [\n -70.825,\n 42.335\n ],\n [\n -70.495,\n 41.805\n ],\n [\n -70.08,\n 41.78\n ],\n [\n -70.185,\n 42.145\n ],\n [\n -69.88497,\n 41.92283\n ],\n [\n -69.96503,\n 41.63717\n ],\n [\n -70.64,\n 41.475\n ],\n [\n -71.12039,\n 41.49445\n ],\n [\n -71.86,\n 41.32\n ],\n [\n -72.295,\n 41.27\n ],\n [\n -72.87643,\n 41.22065\n ],\n [\n -73.71,\n 40.9311\n ],\n [\n -72.24126,\n 41.11948\n ],\n [\n -71.945,\n 40.93\n ],\n [\n -73.345,\n 40.63\n ],\n [\n -73.982,\n 40.628\n ],\n [\n -73.95232,\n 40.75075\n ],\n [\n -74.25671,\n 40.47351\n ],\n [\n -73.96244,\n 40.42763\n ],\n [\n -74.17838,\n 39.70926\n ],\n [\n -74.90604,\n 38.93954\n ],\n [\n -74.98041,\n 39.1964\n ],\n [\n -75.20002,\n 39.24845\n ],\n [\n -75.52805,\n 39.4985\n ],\n [\n -75.32,\n 38.96\n ],\n [\n -75.07183,\n 38.78203\n ],\n [\n -75.05673,\n 38.40412\n ],\n [\n -75.37747,\n 38.01551\n ],\n [\n -75.94023,\n 37.21689\n ],\n [\n -76.03127,\n 37.2566\n ],\n [\n -75.72205,\n 37.93705\n ],\n [\n -76.23287,\n 38.31921\n ],\n [\n -76.35,\n 39.15\n ],\n [\n -76.54272,\n 38.71762\n ],\n [\n -76.32933,\n 38.08326\n ],\n [\n -76.99,\n 38.23999\n ],\n [\n -76.30162,\n 37.91794\n ],\n [\n -76.25874,\n 36.9664\n ],\n [\n -75.9718,\n 36.89726\n ],\n [\n -75.86804,\n 36.55125\n ],\n [\n -75.72749,\n 35.55074\n ],\n [\n -76.36318,\n 34.80854\n ],\n [\n -77.39763,\n 34.51201\n ],\n [\n -78.05496,\n 33.92547\n ],\n [\n -78.55435,\n 33.86133\n ],\n [\n -79.06067,\n 33.49395\n ],\n [\n -79.20357,\n 33.15839\n ],\n [\n -80.30132,\n 32.50935\n ],\n [\n -80.86498,\n 32.0333\n ],\n [\n -81.33629,\n 31.44049\n ],\n [\n -81.49042,\n 30.72999\n ],\n [\n -81.31371,\n 30.03552\n ],\n [\n -80.98,\n 29.18\n ],\n [\n -80.53558,\n 28.47213\n ],\n [\n -80.53,\n 28.04\n ],\n [\n -80.05654,\n 26.88\n ],\n [\n -80.08801,\n 26.20576\n ],\n [\n -80.13156,\n 25.81677\n ],\n [\n -80.38103,\n 25.20616\n ],\n [\n -80.68,\n 25.08\n ],\n [\n -81.17213,\n 25.20126\n ],\n [\n -81.33,\n 25.64\n ],\n [\n -81.71,\n 25.87\n ],\n [\n -82.24,\n 26.73\n ],\n [\n -82.70515,\n 27.49504\n ],\n [\n -82.85526,\n 27.88624\n ],\n [\n -82.65,\n 28.55\n ],\n [\n -82.93,\n 29.1\n ],\n [\n -83.70959,\n 29.93656\n ],\n [\n -84.1,\n 30.09\n ],\n [\n -85.10882,\n 29.63615\n ],\n [\n -85.28784,\n 29.68612\n ],\n [\n -85.7731,\n 30.15261\n ],\n [\n -86.4,\n 30.4\n ],\n [\n -87.53036,\n 30.27433\n ],\n [\n -88.41782,\n 30.3849\n ],\n [\n -89.18049,\n 30.31598\n ],\n [\n -89.59383,\n 30.15999\n ],\n [\n -89.41373,\n 29.89419\n ],\n [\n -89.43,\n 29.48864\n ],\n [\n -89.21767,\n 29.29108\n ],\n [\n -89.40823,\n 29.15961\n ],\n [\n -89.77928,\n 29.30714\n ],\n [\n -90.15463,\n 29.11743\n ],\n [\n -90.88022,\n 29.14854\n ],\n [\n -91.62678,\n 29.677\n ],\n [\n -92.49906,\n 29.5523\n ],\n [\n -93.22637,\n 29.78375\n ],\n [\n -93.84842,\n 29.71363\n ],\n [\n -94.69,\n 29.48\n ],\n [\n -95.60026,\n 28.73863\n ],\n [\n -96.59404,\n 28.30748\n ],\n [\n -97.14,\n 27.83\n ],\n [\n -97.37,\n 27.38\n ],\n [\n -97.38,\n 26.69\n ],\n [\n -97.33,\n 26.21\n ],\n [\n -97.14,\n 25.87\n ],\n [\n -97.53,\n 25.84\n ],\n [\n -98.24,\n 26.06\n ],\n [\n -99.02,\n 26.37\n ],\n [\n -99.3,\n 26.84\n ],\n [\n -99.52,\n 27.54\n ],\n [\n -100.11,\n 28.11\n ],\n [\n -100.45584,\n 28.69612\n ],\n [\n -100.9576,\n 29.38071\n ],\n [\n -101.6624,\n 29.7793\n ],\n [\n -102.48,\n 29.76\n ],\n [\n -103.11,\n 28.97\n ],\n [\n -103.94,\n 29.27\n ],\n [\n -104.45697,\n 29.57196\n ],\n [\n -104.70575,\n 30.12173\n ],\n [\n -105.03737,\n 30.64402\n ],\n [\n -105.63159,\n 31.08383\n ],\n [\n -106.1429,\n 31.39995\n ],\n [\n -106.50759,\n 31.75452\n ],\n [\n -108.24,\n 31.75485\n ],\n [\n -108.24194,\n 31.34222\n ],\n [\n -109.035,\n 31.34194\n ],\n [\n -111.02361,\n 31.33472\n ],\n [\n -113.30498,\n 32.03914\n ],\n [\n -114.815,\n 32.52528\n ],\n [\n -114.72139,\n 32.72083\n ],\n [\n -115.99135,\n 32.61239\n ],\n [\n -117.12776,\n 32.53534\n ],\n [\n -117.29594,\n 33.04622\n ],\n [\n -117.944,\n 33.62124\n ],\n [\n -118.4106,\n 33.74091\n ],\n [\n -118.51989,\n 34.02778\n ],\n [\n -119.081,\n 34.078\n ],\n [\n -119.43884,\n 34.34848\n ],\n [\n -120.36778,\n 34.44711\n ],\n [\n -120.62286,\n 34.60855\n ],\n [\n -120.74433,\n 35.15686\n ],\n [\n -121.71457,\n 36.16153\n ],\n [\n -122.54747,\n 37.55176\n ],\n [\n -122.51201,\n 37.78339\n ],\n [\n -122.95319,\n 38.11371\n ],\n [\n -123.7272,\n 38.95166\n ],\n [\n -123.86517,\n 39.76699\n ],\n [\n -124.39807,\n 40.3132\n ],\n [\n -124.17886,\n 41.14202\n ],\n [\n -124.2137,\n 41.99964\n ],\n [\n -124.53284,\n 42.76599\n ],\n [\n -124.14214,\n 43.70838\n ],\n [\n -124.02053,\n 44.6159\n ],\n [\n -123.89893,\n 45.52341\n ],\n [\n -124.07963,\n 46.86475\n ],\n [\n -124.39567,\n 47.72017\n ],\n [\n -124.68721,\n 48.18443\n ],\n [\n -124.5661,\n 48.37971\n ],\n [\n -123.12,\n 48.04\n ],\n [\n -122.58736,\n 47.096\n ],\n [\n -122.34,\n 47.36\n ],\n [\n -122.5,\n 48.18\n ],\n [\n -122.84,\n 49\n ],\n [\n -120,\n 49\n ],\n [\n -117.03121,\n 49\n ],\n [\n -116.04818,\n 49\n ],\n [\n -113,\n 49\n ],\n [\n -110.05,\n 49\n ],\n [\n -107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","volume":"17","noUsgsAuthors":false,"publicationDate":"2022-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Collins, Elyssa 0000-0002-8054-8468","orcid":"https://orcid.org/0000-0002-8054-8468","contributorId":294952,"corporation":false,"usgs":false,"family":"Collins","given":"Elyssa","email":"","affiliations":[{"id":63800,"text":"Center for Geospatial Analytics, North Carolina State University, Raleigh, NC, USA","active":true,"usgs":false}],"preferred":false,"id":851449,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sanchez, Georgina M. 0000-0002-2365-6200","orcid":"https://orcid.org/0000-0002-2365-6200","contributorId":210477,"corporation":false,"usgs":false,"family":"Sanchez","given":"Georgina M.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":851450,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Terando, Adam 0000-0002-9280-043X","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":205908,"corporation":false,"usgs":true,"family":"Terando","given":"Adam","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":851451,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stillwell, Charles C. 0000-0002-4571-4897","orcid":"https://orcid.org/0000-0002-4571-4897","contributorId":270394,"corporation":false,"usgs":true,"family":"Stillwell","given":"Charles","email":"","middleInitial":"C.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":851452,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mitasova, Helena 0000-0002-6906-3398","orcid":"https://orcid.org/0000-0002-6906-3398","contributorId":296416,"corporation":false,"usgs":false,"family":"Mitasova","given":"Helena","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":851453,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sebastian, Antonia 0000-0002-4309-2561","orcid":"https://orcid.org/0000-0002-4309-2561","contributorId":296417,"corporation":false,"usgs":false,"family":"Sebastian","given":"Antonia","email":"","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":false,"id":851454,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meentemeyer, Ross K.","contributorId":179341,"corporation":false,"usgs":false,"family":"Meentemeyer","given":"Ross","email":"","middleInitial":"K.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":851455,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70236483,"text":"70236483 - 2022 - General guidance for custom-built structural equation models","interactions":[],"lastModifiedDate":"2022-09-09T10:55:46.482391","indexId":"70236483","displayToPublicDate":"2022-02-01T09:23:30","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5943,"text":"One Ecosystem","active":true,"publicationSubtype":{"id":10}},"title":"General guidance for custom-built structural equation models","docAbstract":"Structural Equation Modeling (SEM) represents a quantitative methodology for specifying and evaluating causal network hypotheses. The application of SEM typically involves the use of specialized software packages that implement estimation procedures and automate model checking and the output of summary results. There are times when the specification details an investigator wishes to implement to represent their data relationships are not supported by available SEM packages. In such cases, it may be desirable to develop and evaluate SE models “by hand”, using specialized regression tools. In this paper, I demonstrate a general approach to custom-built applications of SEM. The approach illustrated can be used for a wide array of specialized applications of non-linear, multi-level, and other custom specifications in SE models.","language":"English","publisher":"Pensoft Publishers","doi":"10.3897/oneeco.7.e72780","usgsCitation":"Grace, J., 2022, General guidance for custom-built structural equation models: One Ecosystem, v. 7, e72780, 13 p., https://doi.org/10.3897/oneeco.7.e72780.","productDescription":"e72780, 13 p.","ipdsId":"IP-132365","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":448951,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3897/oneeco.7.e72780","text":"Publisher Index Page"},{"id":406379,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Acadia National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.28380584716795,\n 44.41514524311076\n ],\n [\n -68.28861236572266,\n 44.411711905198004\n ],\n [\n -68.28895568847656,\n 44.40484462467532\n ],\n [\n -68.2803726196289,\n 44.403618239739515\n ],\n [\n -68.28243255615234,\n 44.396504700115536\n ],\n [\n -68.27659606933592,\n 44.37785821716272\n ],\n [\n -68.2855224609375,\n 44.377122049920416\n ],\n [\n -68.28311920166016,\n 44.381784286142434\n ],\n [\n -68.29479217529297,\n 44.38669150215206\n ],\n [\n -68.31161499023438,\n 44.382520394767475\n ],\n [\n -68.32122802734375,\n 44.37295026072434\n ],\n [\n -68.31607818603516,\n 44.363869456900595\n ],\n [\n -68.30646514892578,\n 44.36067856998804\n ],\n [\n -68.29032897949219,\n 44.36313311380771\n ],\n [\n -68.28998565673828,\n 44.359942186789134\n ],\n [\n -68.30303192138672,\n 44.349140836553076\n ],\n [\n -68.30509185791016,\n 44.340056341964114\n ],\n [\n -68.30852508544922,\n 44.328023358092224\n ],\n [\n -68.32157135009766,\n 44.327777761284416\n ],\n [\n -68.32569122314453,\n 44.33146160542641\n ],\n [\n -68.34457397460938,\n 44.322865609179345\n ],\n [\n -68.34697723388672,\n 44.3177074067743\n ],\n [\n -68.35590362548828,\n 44.315987905196906\n ],\n [\n -68.36311340332031,\n 44.32974250695349\n ],\n [\n -68.3737564086914,\n 44.337109717061864\n ],\n [\n -68.37272644042969,\n 44.34889532818253\n ],\n [\n -68.3792495727539,\n 44.35626013196649\n ],\n [\n -68.39298248291014,\n 44.35527821160296\n ],\n [\n -68.3902359008789,\n 44.33637303769866\n ],\n [\n -68.40843200683594,\n 44.33661859851472\n ],\n [\n -68.4122085571289,\n 44.33170718680922\n ],\n [\n -68.40259552001953,\n 44.319918120477425\n ],\n [\n -68.39950561523438,\n 44.30935506997107\n ],\n [\n -68.39710235595703,\n 44.29141809546585\n ],\n [\n -68.39984893798828,\n 44.2783919270538\n ],\n [\n -68.3737564086914,\n 44.26831309827905\n ],\n [\n -68.37890625,\n 44.263395969186675\n ],\n [\n -68.3730697631836,\n 44.25823254096765\n ],\n [\n -68.35418701171874,\n 44.25552770711544\n ],\n [\n -68.34423065185547,\n 44.25060950862162\n ],\n [\n -68.33667755126953,\n 44.23782026763518\n ],\n [\n -68.33358764648438,\n 44.22945656830167\n ],\n [\n -68.34388732910156,\n 44.22601234661563\n ],\n [\n -68.33942413330078,\n 44.22109168032017\n ],\n [\n -68.31916809082031,\n 44.222567923394735\n ],\n [\n -68.3023452758789,\n 44.23437653539356\n ],\n [\n -68.29444885253906,\n 44.24323143968471\n ],\n [\n -68.31127166748047,\n 44.24716652494939\n ],\n [\n -68.3133316040039,\n 44.255281806959275\n ],\n [\n -68.33118438720702,\n 44.26093725039923\n ],\n [\n -68.33736419677734,\n 44.25700308645885\n ],\n [\n -68.33736419677734,\n 44.27617964929813\n ],\n [\n -68.34354400634766,\n 44.2867486691176\n ],\n [\n -68.3517837524414,\n 44.2867486691176\n ],\n [\n -68.34354400634766,\n 44.297070062271175\n ],\n [\n -68.33942413330078,\n 44.29903583625904\n ],\n [\n -68.33221435546875,\n 44.297070062271175\n ],\n [\n -68.3236312866211,\n 44.29952726947296\n ],\n [\n -68.3133316040039,\n 44.29731578761873\n ],\n [\n -68.30337524414062,\n 44.31009208868226\n ],\n [\n -68.28174591064453,\n 44.307389641495384\n ],\n [\n -68.2638931274414,\n 44.307389641495384\n ],\n [\n -68.25084686279297,\n 44.31353138696479\n ],\n [\n -68.24913024902344,\n 44.30861804200505\n ],\n [\n -68.23230743408203,\n 44.299281553380155\n ],\n [\n -68.22269439697266,\n 44.302230078625456\n ],\n [\n -68.21617126464844,\n 44.29362979943358\n ],\n [\n -68.19007873535156,\n 44.30468706988256\n ],\n [\n -68.17188262939453,\n 44.327777761284416\n ],\n [\n -68.17256927490234,\n 44.33735527479289\n ],\n [\n -68.17806243896484,\n 44.34938634389529\n ],\n [\n -68.1808090209961,\n 44.36067856998804\n ],\n [\n -68.18286895751952,\n 44.36902359940364\n ],\n [\n -68.19282531738281,\n 44.37663126661702\n ],\n [\n -68.20690155029297,\n 44.37785821716272\n ],\n [\n -68.22269439697266,\n 44.386200799061896\n ],\n [\n -68.22269439697266,\n 44.395278140353646\n ],\n [\n -68.2357406616211,\n 44.40803310518651\n ],\n [\n -68.24810028076172,\n 44.41318336041361\n ],\n [\n -68.26663970947266,\n 44.41710705999032\n ],\n [\n -68.28380584716795,\n 44.41514524311076\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","noUsgsAuthors":false,"publicationDate":"2022-02-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Grace, James B. 0000-0001-6374-4726","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":220095,"corporation":false,"usgs":true,"family":"Grace","given":"James B.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":851191,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70226588,"text":"70226588 - 2022 - Incorporating interpreter variability into estimation of the total variance of land cover area estimates under simple random sampling","interactions":[],"lastModifiedDate":"2024-05-17T16:56:00.80531","indexId":"70226588","displayToPublicDate":"2022-02-01T07:25:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Incorporating interpreter variability into estimation of the total variance of land cover area estimates under simple random sampling","docAbstract":"Area estimates of land cover and land cover change are often based on reference class labels determined by analysts interpreting satellite imagery and aerial photography. Different interpreters may assign different reference class labels to the same sample unit. This interpreter variability is typically not accounted for in variance estimators applied to area estimates of land cover. A simple measurement model provides the basis for an estimator of the total variance (VTotal) that takes into account both sampling variance and interpreter variance. This method requires two or more reference class interpretations (i.e., repeated measurements) obtained by analysts, working independently of each other, for the full sample or a random subsample of the full sample. Estimators of the total variance (
Urban development and associated land cover and land use change alter the thermal, hydrological, and physical properties of the land surface. Assessments of surface urban heat island (UHI) usually focused on using remote sensing and land cover data to quantify UHI intensity and spatial distribution within a certain period. However, the mechanisms and complex interactions in landscape dynamics and land surface thermal features are still being assessed. In this study, we developed and implemented a novel approach to characterize landscape thermal conditions by focusing on UHI intensity and its spatiotemporal variation using the recently available time series of Landsat land surface temperature and land cover change products. We analyzed land surface temperature changes in urban and surrounding non-urban lands to quantify the UHI intensity and landscape thermal conditions in the Atlanta and Minneapolis metropolitan areas of the United States. Our results revealed that UHI intensities had averages of 3.4 °C and 3.3 °C in the Atlanta and Minneapolis metropolitan areas, respectively. The dominant land cover type in rural areas and urban imperviousness cover determines the UHI intensity. Increasing trends of 0.04 °C/year and 0.01 °C/year in UHI intensity between 1985 and 2018 were found in Atlanta and Minneapolis, respectively. The UHI intensity variations in 1985 and 2018 suggest that the magnitudes and temporal variations of UHI intensity averaged from all urban land cover classes are close to the UHI intensity estimated from the low intensity urban area only while the UHI intensities are more than 2 °C larger in medium to high and high intensity urban areas. The UHI intensities estimated from the maximum temperature that have statistically significant increasing trends suggest that the maximum temperature is a good element for measuring UHI effect. Urban land cover dynamics play an important role in controlling temporal variation of UHI and the UHI hotspots. Our findings support the scientific value of implementing the prototype approach as an objective framework to quantify and monitor UHI intensity at a large geographic extent.
Forested stream ecosystems involve complex physical and biotic pathways that can influence fish in numerous ways. Consequently, the responses of fish communities to disturbance can be difficult to understand. In this study, we employed a food web model that links biotic (e.g., physiology, predator–prey interactions) and abiotic (e.g., temperature, sunlight) attributes to address fish responses to changes in stream-riparian ecosystems. We modeled responses to food web dynamics in four streams, using scenarios that included responses to riparian disturbance, climate change, and shifts in top consumers. The two consumers we focused on were coastal cutthroat trout (Oncorhynchus clarkii clarkii) and sculpin (Cottus spp., collectively treated as a functional group). We found the responses to environmental changes varied by fish species and among streams, and that responses were not independent due to exploitative interspecific competition. Simulations based on long-term data indicated that coastal cutthroat trout were responsive to changes in allochthonous resources including terrestrial detritus and invertebrates, whereas sculpin were more responsive to changes to autochthonous resources that included, periphyton and aquatic invertebrates. These results may be, in part, a consequence of species-specific foraging behavior. Trout have a higher propensity to drift feed and therefore receive a substantial subsidy from terrestrial invertebrates, whereas sculpin feed mostly on aquatic insects on the streambed. Simulations of changes in summer temperature and stream discharge suggest decreased biomass of both fish species because of physiological constraints on invertebrate prey which reduce fish foraging opportunities. Exploitative competition also may be important in fish responses: when one fish taxon was removed, the other showed increased biomass. Although the pattern of simulation results was consistent across the four streams, the magnitude of change varied among streams. Streams with food webs fueled by multiple energy sources may be more resilient to changes to riparian forests and climate. Through application of a systems model, we gained insights into pathways of productivity for fish in forested stream ecosystems that provide understanding of processes that influence fish and streams, as well as implications for management of both.
Amphibians are vital elements of ecosystems, serving as predator and prey. Their biphasic nature makes them dependent on aquatic and terrestrial habitats; as wet-skinned ectotherms, they are vulnerable to a range of environmental threats, including climate change. Yellowstone National Park (YNP) is becoming warmer and drier, and some wetlands important to amphibians have diminished. Continued climate change is predicted to reduce snowpack, soil moisture, and forest cover. We used data from models of future climate and vegetation cover to mechanistically model how climate change might affect the movements of Western Toads (Anaxyrus boreas) across the landscape of three test areas in YNP for the years 2050 and 2090, compared to 2000 as a baseline. Least-cost path analysis produced mixed results: for 2050 and 2090, physiological costs of movement increased in one test area and decreased in another; they were mixed in the third. These changes generally reflect the preference by toads for more open forests. Estimating costs for other species of YNP amphibians produced more negative results. For Columbia Spotted Frogs (Rana luteiventris) and Boreal Chorus Frogs (Pseudacris maculata) (both more aquatic and less adapted to terrestrial habitats), movement costs increased by about 2–15X. Reduced frequency or duration of rain events might limit the nocturnal movements of Western Tiger Salamanders (Ambystoma mavortium). Climate change may not have negative impacts on all amphibians throughout YNP, but increased movement costs for terrestrial habitats will accentuate effects of drying wetlands in at least parts of YNP. Land management actions that preserve habitat structure of both forest and low shrub cover may help mitigate continued drying conditions of climate change.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2022.108575","usgsCitation":"Bartelt, P., Thornton, P., and Klaver, R.W., 2022, Modelling physiological costs to assess impacts of climate change on amphibians in Yellowstone National Park, U.S.A: Ecological Indicators, v. 135, 108575, 12 p., https://doi.org/10.1016/j.ecolind.2022.108575.","productDescription":"108575, 12 p.","ipdsId":"IP-134835","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481093,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2022.108575","text":"Publisher Index Page"},{"id":480736,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.13112916264933,\n 45.42187928380869\n ],\n [\n -111.13112916264933,\n 43.87067545981952\n ],\n [\n -109.15957965370097,\n 43.87067545981952\n ],\n [\n -109.15957965370097,\n 45.42187928380869\n ],\n [\n -111.13112916264933,\n 45.42187928380869\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"135","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bartelt, Paul E.","contributorId":349463,"corporation":false,"usgs":false,"family":"Bartelt","given":"Paul E.","affiliations":[{"id":56262,"text":"Waldorf University","active":true,"usgs":false}],"preferred":false,"id":924323,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thornton, Peter E.","contributorId":349464,"corporation":false,"usgs":false,"family":"Thornton","given":"Peter E.","affiliations":[{"id":83486,"text":"Oak Ridge National Laborabory","active":true,"usgs":false}],"preferred":false,"id":924324,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":924322,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70263749,"text":"70263749 - 2022 - Galliform exclusion from the Migratory Bird Treaty Act has produced an alternate conservation path, but no evidence for differences in population status","interactions":[],"lastModifiedDate":"2025-02-21T15:41:18.181211","indexId":"70263749","displayToPublicDate":"2022-02-01T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9101,"text":"Ornithological Applications","printIssn":"0010-5422","active":true,"publicationSubtype":{"id":10}},"title":"Galliform exclusion from the Migratory Bird Treaty Act has produced an alternate conservation path, but no evidence for differences in population status","docAbstract":"The Migratory Bird Treaty Act (MBTA) is critical to avian conservation in the United States, both through its protection of migratory birds and as a catalyst for a century of coordinated avian conservation. While more than 1,000 species are protected by MBTA, of extant bird species native to the continental U.S., only 20 species belonging to the order Galliformes are explicitly excluded. Management of galliforms has occurred largely without direct federal oversight, placing this group on a fundamentally different conservation path during the century following MBTA passage. In this paper, we review the historical context and biological justification for exclusion of galliforms from MBTA and synthesize how their present-day conservation differs from that of migratory birds. We find the most prominent difference between the two groups involves the scope of coordination among stakeholders. The U.S. government, primarily via the Department of Interior, acts as de facto coordinating body for migratory bird conservation and plays the central role in oversight, funding, and administration of management in the United States. In contrast, galliform management falls primarily to individual state wildlife agencies, and coordinated conservation efforts have been more ad hoc and unevenly spread across species. Migratory birds benefit from an almost universally greater scope of research and monitoring, scale of habitat conservation, and sophistication of harvest management compared with galliforms. Galliform harvest management plans, in particular, are less likely to use measurable objectives, reporting of uncertainty in population parameters, and explanation of harvest management techniques. Based on a review of species status lists (e.g., the U.S. Endangered Species Act), we found no evidence that galliforms were more frequently listed than migratory species. Regional trend estimates from the North American Breeding Bird Survey (BBS) were more likely to be negative for galliforms over the period 1966–2015, but this was primarily driven by Northern Bobwhite (Colinus virginianus). Data to assess galliform population status are generally poor, which complicates assessment for roughly half of galliform species. Increased support for coordination among state agencies and other stakeholders, similar to that applied to migratory birds, could help to ensure that galliform conservation is poised to tackle forthcoming challenges associated with global change.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ornithapp/duab051","usgsCitation":"Blomberg, E., Ross, B., Cardinal, C., Ellis-Felege, S., Gibson, D., Monroe, A., and Schwalenberg, P., 2022, Galliform exclusion from the Migratory Bird Treaty Act has produced an alternate conservation path, but no evidence for differences in population status: Ornithological Applications, v. 124, no. 1, duab051, 21 p., https://doi.org/10.1093/ornithapp/duab051.","productDescription":"duab051, 21 p.","ipdsId":"IP-112860","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":482332,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Mexico, United States","otherGeospatial":"North America","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-63.6645,46.55],[-62.0121,46.4431],[-62.8743,45.9682],[-64.1428,46.3927],[-64.3926,46.7275],[-64.0149,47.036],[-63.6645,46.55]]],[[[-61.8063,49.1051],[-63.5893,49.4007],[-64.5191,49.873],[-62.8583,49.7064],[-61.8063,49.1051]]],[[[-123.51,48.51],[-124.0129,48.3709],[-125.655,48.825],[-127.03,49.815],[-128.0593,49.995],[-128.4446,50.5391],[-128.3584,50.7707],[-125.755,50.295],[-124.9208,49.4753],[-123.9225,49.0625],[-123.51,48.51]]],[[[-56.134,50.687],[-56.7959,49.8123],[-56.1431,50.1501],[-55.4715,49.9358],[-55.8224,49.5871],[-54.9351,49.313],[-54.4738,49.5567],[-53.4766,49.2491],[-53.786,48.5168],[-53.0861,48.6878],[-52.6481,47.5356],[-53.0692,46.6555],[-54.1789,46.8071],[-53.9619,47.6252],[-54.2405,47.7523],[-55.4008,46.885],[-55.9975,46.9197],[-55.2912,47.3896],[-56.2508,47.6326],[-59.266,47.6034],[-59.4195,47.8995],[-58.7966,48.2515],[-59.2316,48.5232],[-58.3918,49.1256],[-57.3587,50.7183],[-56.7387,51.2874],[-55.407,51.5883],[-56.134,50.687]]],[[[-133.18,54.17],[-131.75,54.12],[-132.0495,52.9846],[-131.179,52.1804],[-131.5778,52.1824],[-133.0546,53.4115],[-133.18,54.17]]],[[[-79.2658,62.1587],[-79.6575,61.6331],[-80.3622,62.0165],[-79.9294,62.3856],[-79.2658,62.1587]]],[[[-81.8983,62.7108],[-83.0686,62.1592],[-83.7746,62.1823],[-83.9937,62.4528],[-83.2505,62.9141],[-81.877,62.9046],[-81.8983,62.7108]]],[[[-85.1613,65.6573],[-84.9758,65.2175],[-84.464,65.3718],[-81.642,64.4551],[-81.5534,63.9796],[-80.8174,64.0575],[-80.1035,63.726],[-80.991,63.4113],[-82.5472,63.6517],[-83.1088,64.1019],[-85.5234,63.0524],[-85.8668,63.6373],[-87.222,63.5412],[-86.3528,64.0358],[-85.8839,65.7388],[-85.1613,65.6573]]],[[[-75.8659,67.1489],[-76.9869,67.0987],[-77.2364,67.5881],[-76.8117,68.1486],[-75.8952,68.2872],[-75.1145,68.0104],[-75.216,67.4443],[-75.8659,67.1489]]],[[[-95.6477,69.1077],[-96.2695,68.757],[-97.6174,69.06],[-98.4318,68.9507],[-99.7974,69.4],[-98.2183,70.1435],[-96.5574,69.68],[-95.6477,69.1077]]],[[[-90.5471,69.4977],[-90.5515,68.475],[-89.2152,69.2587],[-88.0197,68.6151],[-88.3175,67.8734],[-87.3502,67.1987],[-86.3061,67.9215],[-85.5766,68.7846],[-85.522,69.8821],[-82.6226,69.6583],[-81.2804,69.162],[-81.2202,68.6657],[-81.9644,68.1325],[-81.2593,67.5972],[-81.3865,67.1108],[-83.3446,66.4115],[-84.7354,66.2573],[-85.7694,66.5583],[-87.3232,64.7756],[-88.483,64.099],[-89.9144,64.0327],[-90.704,63.6102],[-90.77,62.9602],[-91.9334,62.8351],[-93.157,62.0247],[-94.2415,60.8987],[-94.6293,60.1102],[-94.6846,58.9488],[-93.215,58.7821],[-92.297,57.0871],[-90.8977,57.2847],[-89.0395,56.8517],[-87.3242,55.9991],[-85.0118,55.3026],[-82.2729,55.1483],[-82.4362,54.2823],[-82.125,53.277],[-81.4008,52.1579],[-79.9129,51.2084],[-79.143,51.5339],[-78.6019,52.5621],[-79.1242,54.1415],[-79.8296,54.6677],[-78.2287,55.1365],[-77.0956,55.8374],[-76.5414,56.5342],[-76.6232,57.2026],[-77.3023,58.0521],[-78.5169,58.8046],[-77.3368,59.8526],[-78.1069,62.3196],[-77.4107,62.5505],[-74.6682,62.1811],[-73.8399,62.4438],[-71.6771,61.5254],[-71.3737,61.1372],[-69.5904,61.0614],[-69.2879,58.9574],[-68.3746,58.8011],[-67.6498,58.2121],[-66.2018,58.7673],[-64.5835,60.3356],[-61.3966,56.9675],[-61.7987,56.3395],[-59.5696,55.2041],[-57.3332,54.6265],[-56.9369,53.7803],[-56.1581,53.6475],[-55.7563,53.2704],[-55.6834,52.1466],[-57.1269,51.4197],[-58.7748,51.0643],[-60.0331,50.2428],[-61.7237,50.0805],[-66.3991,50.229],[-67.2363,49.5116],[-68.5111,49.0684],[-71.1046,46.8217],[-70.2552,46.9861],[-68.65,48.3],[-66.5524,49.1331],[-65.0563,49.2328],[-64.171,48.7425],[-65.1155,48.0709],[-64.4722,46.2385],[-63.1733,45.739],[-61.5207,45.8838],[-60.5182,47.0079],[-60.4486,46.2826],[-59.8029,45.9204],[-61.0399,45.2653],[-64.2466,44.2655],[-65.3641,43.5452],[-66.1234,43.6187],[-66.1617,44.4651],[-64.4255,45.292],[-67.1374,45.1375],[-66.9647,44.8097],[-70.1162,43.6841],[-70.6455,43.0902],[-70.825,42.335],[-70.495,41.805],[-70.08,41.78],[-70.185,42.145],[-69.885,41.9228],[-69.965,41.6372],[-73.71,40.9311],[-72.2413,41.1195],[-71.945,40.93],[-74.2567,40.4735],[-73.9624,40.4276],[-74.1784,39.7093],[-74.906,38.9395],[-75.5281,39.4985],[-75.0567,38.4041],[-75.9402,37.2169],[-75.7221,37.9371],[-76.2329,38.3192],[-76.35,39.15],[-76.5427,38.7176],[-76.3293,38.0833],[-76.99,38.24],[-76.3016,37.9179],[-76.2587,36.9664],[-75.9718,36.8973],[-75.7275,35.5507],[-76.3632,34.8085],[-77.3976,34.512],[-78.055,33.9255],[-79.0607,33.494],[-79.2036,33.1584],[-80.3013,32.5094],[-81.3363,31.4405],[-81.4904,30.73],[-81.3137,30.0355],[-80.0565,26.88],[-80.381,25.2062],[-81.1721,25.2013],[-81.33,25.64],[-81.71,25.87],[-82.8553,27.8862],[-82.65,28.55],[-83.7096,29.9366],[-84.1,30.09],[-85.1088,29.6362],[-86.4,30.4],[-89.5938,30.16],[-89.2177,29.2911],[-89.4082,29.1596],[-89.7793,29.3071],[-90.8802,29.1485],[-91.6268,29.677],[-93.8484,29.7136],[-94.69,29.48],[-95.6003,28.7386],[-96.594,28.3075],[-97.37,27.38],[-97.14,25.87],[-97.703,24.2723],[-97.8724,22.4442],[-97.1893,20.6354],[-95.9009,18.828],[-94.8391,18.5627],[-94.4257,18.1444],[-91.4079,18.8761],[-90.7719,19.2841],[-90.2786,20.9999],[-88.5439,21.4937],[-87.0519,21.5435],[-86.812,21.3315],[-86.8459,20.8499],[-87.6211,19.6466],[-87.4368,19.4724],[-87.8372,18.2598],[-88.3,18.5],[-88.1068,18.3487],[-88.3554,16.5308],[-88.9306,15.8873],[-88.1212,15.6887],[-87.9018,15.8645],[-86.9032,15.7567],[-84.9837,15.9959],[-83.4104,15.2709],[-83.1472,14.9958],[-83.1821,14.3107],[-83.5198,13.5677],[-83.4733,12.4191],[-83.8555,11.3733],[-83.4023,10.3954],[-82.1871,9.2075],[-82.2076,8.9956],[-81.7142,9.032],[-81.4393,8.7862],[-79.5733,9.6116],[-78.0559,9.2477],[-77.3534,8.6705],[-77.2426,7.9353],[-77.4311,7.6381],[-77.7534,7.7098],[-77.8816,7.2238],[-78.4292,8.052],[-78.1821,8.3192],[-79.1203,8.9961],[-79.5579,8.9324],[-79.7606,8.5845],[-80.3827,8.2984],[-80.4807,8.0903],[-80.0037,7.5475],[-80.4212,7.2716],[-80.8864,7.2205],[-81.0595,7.8179],[-81.5195,7.7066],[-81.7213,8.109],[-82.8201,8.2909],[-82.851,8.0738],[-83.5084,8.4469],[-83.7115,8.6568],[-83.6326,9.0514],[-84.6476,9.6155],[-84.7134,9.9081],[-84.9757,10.0867],[-85.1109,9.557],[-85.6608,9.9334],[-85.6593,10.7543],[-85.9417,10.8953],[-85.7125,11.0884],[-87.6685,12.9099],[-87.3167,12.9847],[-87.4894,13.2975],[-88.4833,13.164],[-90.6086,13.9098],[-91.2324,13.9278],[-93.3595,15.6154],[-94.6917,16.201],[-96.5574,15.6535],[-100.8295,17.1711],[-101.9185,17.9161],[-103.501,18.2923],[-104.992,19.3161],[-105.493,19.9468],[-105.7314,20.4341],[-105.3978,20.5317],[-105.2658,21.4221],[-106.0287,22.7738],[-108.4019,25.1723],[-109.2602,25.5806],[-109.4441,25.8249],[-109.2916,26.4429],[-110.3917,27.1621],[-110.641,27.8599],[-111.1789,27.9412],[-112.2282,28.9544],[-113.1638,30.7869],[-113.1487,31.171],[-114.7765,31.7995],[-114.9367,31.3935],[-114.6739,30.1627],[-111.6165,26.6628],[-110.6551,24.2986],[-110.1729,24.2656],[-109.4334,23.1856],[-110.0314,22.8231],[-110.2951,23.431],[-112.182,24.7384],[-112.3007,26.012],[-114.4658,27.1421],[-115.0551,27.7227],[-114.5704,27.7415],[-114.1993,28.115],[-114.162,28.5661],[-115.5187,29.5564],[-117.2959,33.0462],[-118.4106,33.7409],[-118.5199,34.0278],[-120.6229,34.6086],[-120.7443,35.1569],[-121.7146,36.1615],[-122.512,37.7834],[-123.7272,38.9517],[-123.8652,39.767],[-124.3981,40.3132],[-124.2137,41.9996],[-124.5328,42.766],[-124.1421,43.7084],[-123.8989,45.5234],[-124.0796,46.8648],[-124.6872,48.1844],[-124.5661,48.3797],[-123.12,48.04],[-122.5874,47.096],[-122.34,47.36],[-122.84,49],[-125.6246,50.4166],[-127.4356,50.8306],[-127.9928,51.7158],[-127.8503,52.3296],[-129.1298,52.7554],[-129.3052,53.5616],[-130.515,54.2876],[-130.5361,54.8028],[-131.9672,55.4978],[-132.25,56.37],[-133.5392,57.1789],[-134.0781,58.1231],[-136.6281,58.2122],[-137.8,58.5],[-139.8678,59.5378],[-142.5744,60.0845],[-143.9589,59.9992],[-147.1144,60.8847],[-148.2243,60.673],[-148.0181,59.9783],[-151.7164,59.1558],[-151.8594,59.745],[-151.4097,60.7258],[-150.3469,61.0336],[-150.6211,61.2844],[-154.0192,59.3503],[-153.2875,58.8647],[-154.2325,58.1464],[-156.3083,57.4228],[-156.5561,56.98],[-158.1172,56.4636],[-158.4333,55.9942],[-164.7856,54.4042],[-164.9422,54.5722],[-161.8042,55.895],[-160.5636,56.0081],[-157.7228,57.57],[-157.5503,58.3283],[-157.0417,58.9189],[-158.1947,58.6158],[-158.5172,58.7878],[-159.0586,58.4242],[-159.7117,58.9314],[-159.9813,58.5726],[-160.3553,59.0711],[-161.9689,58.6717],[-161.8742,59.6336],[-162.5181,59.9897],[-163.8183,59.7981],[-165.3464,60.5075],[-165.3508,61.0739],[-166.1214,61.5],[-164.5625,63.1464],[-163.0672,63.0595],[-162.2606,63.5419],[-161.5345,63.4558],[-160.7725,63.7661],[-160.9583,64.2228],[-161.5181,64.4028],[-160.7778,64.7886],[-162.7578,64.3386],[-163.5464,64.5592],[-164.9608,64.447],[-166.4253,64.6867],[-168.1106,65.67],[-164.4747,66.5767],[-163.6525,66.5767],[-163.7886,66.0772],[-161.6778,66.1161],[-162.4897,66.7356],[-163.7197,67.1164],[-165.3903,68.0428],[-166.7644,68.3589],[-166.2047,68.883],[-164.4308,68.9155],[-163.1686,69.3711],[-162.9306,69.8581],[-161.9089,70.3333],[-159.0392,70.8916],[-158.1197,70.8247],[-156.5808,71.3578],[-155.0678,71.1478],[-154.3442,70.6964],[-153.9,70.89],[-152.21,70.83],[-152.27,70.6],[-150.74,70.43],[-149.72,70.53],[-144.92,69.99],[-143.5895,70.1525],[-136.5036,68.898],[-134.4146,69.6274],[-132.9293,69.5053],[-129.7947,70.1937],[-129.1077,69.7793],[-128.3616,70.0129],[-128.1382,70.4838],[-127.4471,70.3772],[-125.7563,69.4806],[-124.4248,70.1584],[-124.2897,69.3997],[-123.0611,69.5637],[-122.6835,69.8555],[-121.4723,69.7978],[-117.6027,69.0113],[-115.2469,68.9059],[-113.8979,68.3989],[-115.3049,67.9026],[-113.4973,67.6882],[-109.9462,67.981],[-108.8802,67.3814],[-107.7924,67.8874],[-108.813,68.3116],[-108.1672,68.6539],[-106.15,68.8],[-104.3379,68.018],[-103.2212,68.0978],[-101.4543,67.6469],[-98.4432,67.7817],[-98.5586,68.4039],[-97.6695,68.5786],[-96.1199,68.2394],[-96.1259,67.2934],[-95.4894,68.0907],[-94.685,68.0638],[-94.2328,69.069],[-96.4713,70.0898],[-96.3912,71.1948],[-95.2088,71.9205],[-93.89,71.7602],[-92.8782,71.3187],[-91.5196,70.1913],[-92.4069,69.7],[-90.5471,69.4977]]],[[[-114.1672,73.1215],[-114.6663,72.6528],[-112.441,72.9554],[-111.0504,72.4504],[-109.9204,72.9611],[-109.0065,72.6334],[-108.1884,71.6509],[-107.686,72.0655],[-108.3964,73.0895],[-107.5165,73.236],[-106.5226,73.076],[-105.4025,72.6726],[-104.4648,70.993],[-100.9808,70.0243],[-101.0893,69.5845],[-102.7312,69.504],[-102.0933,69.1196],[-102.4302,68.7528],[-105.96,69.18],[-113.3132,68.5355],[-113.855,69.0074],[-115.22,69.28],[-116.1079,69.1682],[-117.34,69.96],[-112.4161,70.3664],[-114.35,70.6],[-117.9048,70.5406],[-118.4324,70.9092],[-116.1131,71.3092],[-119.402,71.5586],[-117.8664,72.7059],[-115.1891,73.3146],[-114.1672,73.1215]]],[[[-104.5,73.42],[-105.38,72.76],[-106.94,73.46],[-105.26,73.64],[-104.5,73.42]]],[[[-76.34,73.1027],[-76.2514,72.8264],[-79.4863,72.7422],[-80.8761,73.3332],[-80.8339,73.6932],[-80.3531,73.7597],[-78.0644,73.6519],[-76.34,73.1027]]],[[[-86.5622,73.1575],[-85.7744,72.5341],[-84.8501,73.3403],[-82.3156,73.751],[-80.6001,72.7165],[-80.7489,72.0619],[-78.7706,72.3522],[-77.8246,72.7496],[-74.2286,71.7671],[-74.0991,71.3308],[-72.2422,71.5569],[-71.2,70.92],[-68.7861,70.525],[-67.915,70.122],[-66.969,69.1861],[-68.8051,68.7202],[-64.8623,67.8475],[-63.4249,66.9285],[-61.852,66.8621],[-62.1632,66.1603],[-63.9184,64.9987],[-65.1489,65.426],[-66.7212,66.388],[-68.015,66.2627],[-68.1413,65.6898],[-65.3202,64.3827],[-64.6694,63.3929],[-65.0138,62.6742],[-68.7832,63.7457],[-66.3283,62.2801],[-66.1656,61.9309],[-71.0234,62.9107],[-72.2354,63.3978],[-71.8863,63.68],[-74.8344,64.6791],[-74.8185,64.3891],[-77.71,64.2295],[-78.556,64.5729],[-77.8973,65.3092],[-73.9598,65.4548],[-74.2939,65.8118],[-72.6512,67.2846],[-72.9261,67.7269],[-73.3116,68.0694],[-74.8433,68.5546],[-76.8691,68.8947],[-76.2287,69.1478],[-77.2874,69.7695],[-78.9572,70.1669],[-79.4925,69.8718],[-81.3055,69.7432],[-84.9447,69.9666],[-88.6817,70.4107],[-89.5134,70.762],[-88.4677,71.2182],[-89.8882,71.2226],[-90.2052,72.2351],[-89.4366,73.1295],[-88.4082,73.5379],[-85.8262,73.8038],[-86.5622,73.1575]]],[[[-100.3564,73.8439],[-99.1639,73.6334],[-97.38,73.76],[-97.12,73.47],[-98.0536,72.9905],[-96.54,72.56],[-96.72,71.66],[-98.3597,71.2729],[-99.3229,71.3564],[-102.5,72.51],[-102.48,72.83],[-100.4384,72.7059],[-101.54,73.36],[-100.3564,73.8439]]],[[[-93.1963,72.772],[-94.2691,72.0246],[-95.4099,72.0619],[-96.0338,72.9403],[-96.0183,73.4374],[-95.4958,73.8624],[-94.5037,74.1349],[-90.5098,73.8567],[-92.004,72.9662],[-93.1963,72.772]]],[[[-120.46,71.3836],[-123.0922,70.9016],[-123.62,71.34],[-125.929,71.8687],[-123.94,73.68],[-124.9178,74.2928],[-121.5379,74.4489],[-117.5556,74.1858],[-115.5108,73.4752],[-119.22,72.52],[-120.46,71.82],[-120.46,71.3836]]],[[[-93.6128,74.98],[-94.1569,74.5924],[-96.8209,74.9276],[-96.2886,75.3778],[-94.8508,75.6472],[-93.6128,74.98]]],[[[-98.5,76.72],[-97.7356,76.2566],[-97.7044,75.7434],[-98.16,75],[-99.8087,74.8974],[-100.8837,75.0574],[-100.8629,75.6408],[-102.5021,75.5638],[-102.5655,76.3366],[-98.5,76.72]]],[[[-108.2114,76.2017],[-107.8194,75.8455],[-105.881,75.9694],[-105.705,75.4795],[-106.3135,75.0053],[-109.7,74.85],[-112.2231,74.417],[-113.7438,74.3943],[-113.8714,74.7203],[-111.7942,75.1625],[-116.3122,75.0434],[-117.7104,75.2222],[-116.346,76.199],[-115.4049,76.4789],[-112.5906,76.1413],[-110.8142,75.5492],[-109.0671,75.4732],[-110.4973,76.4298],[-109.5811,76.7942],[-108.5486,76.6783],[-108.2114,76.2017]]],[[[-94.6841,77.0979],[-93.5739,76.7763],[-91.605,76.7785],[-90.7419,76.4496],[-90.9697,76.074],[-89.1871,75.6102],[-86.3792,75.4824],[-81.1285,75.714],[-80.0575,75.3369],[-79.8339,74.9231],[-81.9488,74.4425],[-89.7647,74.5156],[-92.4224,74.8378],[-92.8899,75.8827],[-93.8938,76.3192],[-95.9625,76.4414],[-97.1214,76.7511],[-96.7451,77.1614],[-94.6841,77.0979]]],[[[-116.1986,77.6453],[-116.3358,76.877],[-117.1061,76.53],[-121.5,75.9],[-122.8549,76.1165],[-119.1039,77.5122],[-116.1986,77.6453]]],[[[-93.84,77.52],[-96.1697,77.5551],[-96.4363,77.8346],[-94.4226,77.82],[-93.7207,77.6343],[-93.84,77.52]]],[[[-110.1869,77.697],[-112.0512,77.4092],[-113.5343,77.7322],[-112.7246,78.0511],[-109.8545,77.9963],[-110.1869,77.697]]],[[[-109.6632,78.602],[-112.5421,78.4079],[-111.5,78.85],[-109.6632,78.602]]],[[[-95.8303,78.0569],[-97.3098,77.8506],[-98.1243,78.0829],[-98.5529,78.4581],[-98.632,78.8719],[-96.7544,78.7658],[-95.5593,78.4183],[-95.8303,78.0569]]],[[[-100.0602,78.3248],[-99.6709,77.9075],[-102.9498,78.3432],[-105.1761,78.3803],[-104.2104,78.6774],[-105.4196,78.9183],[-105.4923,79.3016],[-100.8252,78.8005],[-100.0602,78.3248]]],[[[-87.02,79.66],[-85.8144,79.3369],[-89.0354,78.2872],[-90.8044,78.2153],[-92.8767,78.3433],[-93.9512,78.751],[-93.9357,79.1137],[-93.1452,79.3801],[-94.974,79.3725],[-96.0761,79.705],[-96.7097,80.1578],[-95.3235,80.9073],[-94.2984,80.9773],[-94.7354,81.2065],[-92.4098,81.2574],[-91.1329,80.7235],[-87.81,80.32],[-87.02,79.66]]],[[[-68.5,83.1063],[-61.85,82.6286],[-61.8939,82.3617],[-67.6576,81.5014],[-65.4803,81.5066],[-69.4697,80.6168],[-71.18,79.8],[-76.9077,79.3231],[-75.5292,79.1977],[-76.2205,79.0191],[-75.3935,78.5258],[-79.7595,77.2097],[-79.6197,76.9834],[-77.9109,77.0221],[-77.8891,76.778],[-80.5613,76.1781],[-83.1744,76.454],[-86.1118,76.299],[-89.4907,76.4724],[-89.6161,76.9521],[-87.7674,77.1783],[-88.26,77.9],[-84.9763,77.5387],[-86.34,78.18],[-87.9619,78.3718],[-87.152,78.7587],[-85.3787,78.9969],[-85.095,79.3454],[-86.5073,79.7362],[-86.9318,80.2515],[-83.4087,80.1],[-81.8482,80.4644],[-87.599,80.5163],[-89.3666,80.8557],[-91.3679,81.5531],[-91.587,81.8943],[-86.9702,82.2796],[-85.5,82.6523],[-83.18,82.32],[-82.42,82.86],[-79.3066,83.1306],[-68.5,83.1063]]],[[[-71.7124,19.7145],[-70.8067,19.8803],[-69.9508,19.648],[-69.7693,19.2933],[-69.2221,19.3132],[-69.2544,19.0152],[-68.3179,18.6122],[-68.6893,18.2051],[-69.9529,18.4283],[-70.5171,18.1843],[-70.6693,18.4269],[-71,18.2833],[-71.4002,17.5986],[-71.7083,18.045],[-72.3725,18.215],[-73.9224,18.031],[-74.458,18.3426],[-74.3699,18.6649],[-72.6949,18.4458],[-72.3349,18.6684],[-72.7917,19.1016],[-72.7841,19.4836],[-73.415,19.6396],[-73.1898,19.9157],[-71.7124,19.7145]]],[[[-77.5696,18.4905],[-76.8966,18.4009],[-76.1997,17.8869],[-77.2063,17.7011],[-78.3377,18.226],[-78.2177,18.4545],[-77.5696,18.4905]]],[[[-66.2824,18.5148],[-65.591,18.228],[-65.8472,17.9759],[-67.1842,17.9466],[-67.1007,18.5206],[-66.2824,18.5148]]],[[[-155.5421,19.0835],[-155.6882,18.9162],[-155.9367,19.0594],[-156.0735,19.7029],[-155.8611,20.2672],[-155.2245,19.993],[-154.8074,19.5087],[-155.5421,19.0835]]],[[[-156.0793,20.644],[-156.4145,20.5724],[-156.7106,20.9268],[-156.2571,20.9175],[-156.0793,20.644]]],[[[-157.6528,21.3222],[-158.1267,21.3124],[-158.2927,21.5791],[-158.0252,21.717],[-157.6528,21.3222]]],[[[-159.3451,21.982],[-159.8005,22.0653],[-159.3657,22.2149],[-159.3451,21.982]]],[[[-153.0063,57.1158],[-154.0051,56.7347],[-154.5164,56.9928],[-154.671,57.4612],[-153.2287,57.969],[-152.5648,57.9014],[-152.1412,57.5911],[-153.0063,57.1158]]],[[[-165.5792,59.91],[-166.1928,59.7544],[-167.4553,60.2131],[-165.6744,60.2936],[-165.5792,59.91]]],[[[-171.7317,63.7825],[-168.6894,63.2975],[-169.5294,62.9769],[-170.6714,63.3758],[-171.5531,63.3178],[-171.7911,63.4059],[-171.7317,63.7825]]],[[[-82.2682,23.1886],[-80.6188,23.106],[-79.2815,22.3992],[-78.3474,22.5122],[-76.5238,21.2068],[-75.5982,21.0166],[-75.6711,20.7351],[-74.9339,20.6939],[-74.178,20.2846],[-74.2967,20.0504],[-74.9616,19.9234],[-77.7555,19.8555],[-77.0851,20.4134],[-78.1373,20.74],[-78.7199,21.5981],[-79.285,21.5592],[-82.17,22.3871],[-81.795,22.637],[-82.7759,22.6882],[-84.0522,21.9106],[-84.9749,21.896],[-83.7782,22.7881],[-82.2682,23.1886]]],[[[-77.5347,23.7598],[-77.78,23.71],[-78.4085,24.5756],[-78.1909,25.2103],[-77.89,25.17],[-77.5347,23.7598]]],[[[-77.82,26.58],[-78.91,26.42],[-78.98,26.79],[-77.85,26.84],[-77.82,26.58]]],[[[-77,26.59],[-77.1726,25.8792],[-77.34,26.53],[-77.79,27.04],[-77,26.59]]],[[[-61.68,10.76],[-60.895,10.855],[-60.935,10.11],[-61.95,10.09],[-61.66,10.365],[-61.68,10.76]]],[[[-46.7638,82.628],[-43.4064,83.2252],[-39.8975,83.1802],[-38.6221,83.5491],[-27.1005,83.5197],[-20.8454,82.7267],[-22.6918,82.3417],[-31.9,82.2],[-31.3965,82.0215],[-27.8567,82.1318],[-24.8445,81.787],[-22.9033,82.0932],[-22.0718,81.7345],[-23.1696,81.1527],[-15.7682,81.9125],[-12.7702,81.7189],[-12.2086,81.2915],[-16.85,80.35],[-20.0462,80.1771],[-17.7304,80.1291],[-19.705,78.7513],[-19.6735,77.6386],[-18.4729,76.9857],[-21.6794,76.628],[-19.8341,76.0981],[-19.599,75.2484],[-20.6682,75.1559],[-19.3728,74.2956],[-21.5942,74.2238],[-20.4345,73.8171],[-20.7623,73.4644],[-23.5659,73.3066],[-22.3131,72.6293],[-22.2995,72.1841],[-24.2783,72.5979],[-24.793,72.3302],[-23.443,72.0802],[-22.1328,71.469],[-21.7536,70.6637],[-23.536,70.471],[-25.5434,71.4309],[-25.2014,70.7523],[-26.3628,70.2265],[-22.349,70.1295],[-27.7474,68.4705],[-31.7767,68.1208],[-32.8111,67.7355],[-34.202,66.6797],[-36.3528,65.9789],[-39.8122,65.4585],[-40.669,64.84],[-40.6828,64.139],[-41.1887,63.4825],[-42.8194,62.6823],[-42.4167,61.9009],[-43.3784,60.0977],[-44.7875,60.0368],[-46.2636,60.8533],[-48.2629,60.8584],[-49.2331,61.4068],[-49.9004,62.3834],[-51.6333,63.6269],[-52.1401,64.2784],[-52.2766,65.1767],[-53.6617,66.0996],[-53.3016,66.8365],[-53.9691,67.189],[-52.9804,68.3576],[-51.4754,68.7296],[-51.0804,69.1478],[-50.8712,69.9291],[-53.4563,69.2836],[-54.6834,69.61],[-54.75,70.2893],[-54.3588,70.8213],[-51.3901,70.5698],[-54.0042,71.5472],[-55,71.4065],[-55.8347,71.6544],[-54.7182,72.5863],[-57.3236,74.7103],[-58.5968,75.0986],[-58.5852,75.5173],[-61.2686,76.1024],[-68.5044,76.0614],[-71.4026,77.0086],[-66.764,77.376],[-71.0429,77.636],[-73.297,78.0442],[-73.1594,78.4327],[-65.7107,79.3944],[-65.3239,79.7581],[-68.023,80.1172],[-67.1513,80.5158],[-62.2344,81.3211],[-62.6512,81.7704],[-57.2074,82.1907],[-54.1344,82.1996],[-53.0433,81.8883],[-50.3906,82.4388],[-44.523,81.6607],[-46.9007,82.1998],[-46.7638,82.628]]]]},\"properties\":{\"name\":\"North America\"}}]}","volume":"124","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Blomberg, Erik J.","contributorId":351183,"corporation":false,"usgs":false,"family":"Blomberg","given":"Erik J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":928117,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ross, Beth 0000-0001-5634-4951 bross@usgs.gov","orcid":"https://orcid.org/0000-0001-5634-4951","contributorId":199242,"corporation":false,"usgs":true,"family":"Ross","given":"Beth","email":"bross@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":928118,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cardinal, Casey J.","contributorId":351184,"corporation":false,"usgs":false,"family":"Cardinal","given":"Casey J.","affiliations":[{"id":24672,"text":"New Mexico Department of Game and Fish","active":true,"usgs":false}],"preferred":false,"id":928119,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ellis-Felege, Susan N.","contributorId":351185,"corporation":false,"usgs":false,"family":"Ellis-Felege","given":"Susan N.","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":928120,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gibson, Daniel","contributorId":94984,"corporation":false,"usgs":false,"family":"Gibson","given":"Daniel","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":928171,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Monroe, Adrian P.","contributorId":351186,"corporation":false,"usgs":false,"family":"Monroe","given":"Adrian P.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":928122,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schwalenberg, P","contributorId":300551,"corporation":false,"usgs":false,"family":"Schwalenberg","given":"P","email":"","affiliations":[{"id":65194,"text":"Alaska Migratory Bird Co-Management Council","active":true,"usgs":false}],"preferred":false,"id":928123,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70229212,"text":"70229212 - 2022 - Loss of phylogenetic diversity under landscape change","interactions":[],"lastModifiedDate":"2022-03-03T17:14:57.143913","indexId":"70229212","displayToPublicDate":"2022-01-31T11:10:43","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Loss of phylogenetic diversity under landscape change","docAbstract":"Habitat alteration and destruction are primary drivers of biodiversity loss. However, the evolutionary dimensions of biodiversity loss remain largely unexplored in many systems. For example, little is known about how habitat alteration/loss can lead to phylogenetic deconstruction of ecological assemblages at the local level. That is, while species loss is evident, are some lineages favored over others? Using a long-term dataset of a globally, ecologically important guild of invertebrate consumers, stream leaf “shredders,” we created a phylogenetic tree of the taxa in the regional species pool, calculated mean phylogenetic distinctiveness for >1000 communities spanning >10 year period, and related species richness, phylogenetic diversity, and distinctiveness to watershed-scale impervious cover. Using a combination of changepoint and compositional analyses, we learned that increasing impervious cover produced marked reductions in all three measures of diversity. These results aid in understanding both phylogenetic diversity and mean assemblage phylogenetic distinctiveness. Our findings indicate that, not only are species lost when there is an increase in watershed urbanization, as other studies have demonstrated, but that those lost are members of more distinct lineages relative to the community as a whole.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2022.153595","usgsCitation":"Swan, C.M., Baker, M., Borowy, D., Johnson, A., Shcheglovitova, M., Sparkman, A., Neto, F.V., Van Appledorn, M., and Voelker, N., 2022, Loss of phylogenetic diversity under landscape change: Science of the Total Environment, v. 822, 153595, 8 p., https://doi.org/10.1016/j.scitotenv.2022.153595.","productDescription":"153595, 8 p.","ipdsId":"IP-123163","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":448976,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/11603/24929","text":"External Repository"},{"id":396713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"822","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Swan, Christopher M.","contributorId":265549,"corporation":false,"usgs":false,"family":"Swan","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":836946,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baker, Matthew","contributorId":196362,"corporation":false,"usgs":false,"family":"Baker","given":"Matthew","affiliations":[],"preferred":false,"id":836947,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Borowy, Dorothy 0000-0002-2569-9757","orcid":"https://orcid.org/0000-0002-2569-9757","contributorId":287610,"corporation":false,"usgs":false,"family":"Borowy","given":"Dorothy","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":836948,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Anna","contributorId":287611,"corporation":false,"usgs":false,"family":"Johnson","given":"Anna","email":"","affiliations":[{"id":52650,"text":"Pennsylvania Natural Heritage Program","active":true,"usgs":false}],"preferred":false,"id":836949,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shcheglovitova, Mariya","contributorId":287612,"corporation":false,"usgs":false,"family":"Shcheglovitova","given":"Mariya","email":"","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":836950,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sparkman, April","contributorId":287614,"corporation":false,"usgs":false,"family":"Sparkman","given":"April","email":"","affiliations":[{"id":38069,"text":"University of Maryland, Baltimore County","active":true,"usgs":false}],"preferred":false,"id":836951,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Neto, Francisco V.","contributorId":287617,"corporation":false,"usgs":false,"family":"Neto","given":"Francisco","email":"","middleInitial":"V.","affiliations":[{"id":61620,"text":"Laboratório de Ecologia, Instituto de Biociências","active":true,"usgs":false}],"preferred":false,"id":836952,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Van Appledorn, Molly 0000-0002-8029-0014","orcid":"https://orcid.org/0000-0002-8029-0014","contributorId":205785,"corporation":false,"usgs":true,"family":"Van Appledorn","given":"Molly","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":836953,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Voelker, Nicole","contributorId":287619,"corporation":false,"usgs":false,"family":"Voelker","given":"Nicole","email":"","affiliations":[{"id":38069,"text":"University of Maryland, Baltimore County","active":true,"usgs":false}],"preferred":false,"id":836954,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70227800,"text":"sir20225001 - 2022 - Hydrogeologic characterization of the San Antonio Creek Valley watershed, Santa Barbara County, California","interactions":[],"lastModifiedDate":"2026-04-08T17:04:17.61002","indexId":"sir20225001","displayToPublicDate":"2022-01-31T11:06:53","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5001","displayTitle":"Hydrogeologic Characterization of the San Antonio Creek Valley Watershed, Santa Barbara County, California","title":"Hydrogeologic characterization of the San Antonio Creek Valley watershed, Santa Barbara County, California","docAbstract":"The San Antonio Creek Valley watershed (SACVW) is located in western Santa Barbara County, about 15 miles south of Santa Maria and 55 miles north of Santa Barbara, California. The SACVW is about 135 square miles and encompasses the San Antonio Creek Valley groundwater basin; the SACVW is separated from adjacent groundwater basins by the Casmalia and Solomon Hills to the north, and the Purisima Hills to the south. At the western, downstream part of the valley, uplifted, consolidated rocks cause groundwater to discharge at land surface at Barka Slough. Since the late 1800s, groundwater has been the primary source of water for agricultural, military, municipal, and domestic uses. Groundwater withdrawal by pumping exceeded the amount of water replenishing the aquifer system during water years 1948–2018, causing groundwater-level declines of more than 150 feet in parts of the valley and reducing base flow at Barka Slough. Reliance on groundwater for agricultural water use (primarily for the irrigation and frost protection of vineyards, and fruit and berry crops) continues to strain the sustainability of the groundwater system.
Through a cooperative agreement, the Santa Barbara County Water Agency and Vandenberg Space Force Base invited the U.S. Geological Survey to address declines in groundwater levels, develop a better understanding of the hydrogeologic system, and provide tools to help evaluate and manage the effects of future development of the San Antonio Creek Valley groundwater basin within the encompassing San Antonio Creek Valley watershed (SACVW). The objectives of this study were to (1) refine the hydrogeologic framework of the San Antonio Creek Valley watershed, (2) quantify the hydrologic budget of the valley, and (3) develop hydrologic modeling tools to evaluate and aid in managing the groundwater resource. This report focuses on the first and second objectives to construct a hydrogeologic framework and characterize the historical and present-day hydrologic conditions of the SACVW during water years 1948–2018. As part of the second objective, work included quantifying the hydrologic budget and evaluating the hydrogeologic system using a combination of existing data and geologic and hydrologic data collected for this study.
The groundwater-flow system in the SACVW consists of five hydrogeologic units. These separate water-bearing units were identified based on hydrogeologic properties, such as sediment grain size, vertical-head differences in multiple-depth, monitoring-well sites, long-term groundwater level responses to pumping and climate, and the chemical character of groundwater and groundwater age in the mostly semi-consolidated to unconsolidated basin-fill sediments. The hydrogeologic units that comprise the different aquifers vary in their lithologic composition. The upper and lower aquifers (upper Paso Robles Formation, and lower Paso Robles Formation and Careaga Sandstone, respectively) are relatively coarse grained and are comprised of sand, gravel, and clay; the middle confining unit (the middle Paso Robles Formation) is relatively fine grained and is comprised of primarily clay, silt, and sand. The Pezzoni-Casmalia and Los Alamos faults, which are inferred to transect the SACVW between the western and eastern areas of the valley floor, do not appear to substantially affect the groundwater system.
Present-day recharge to the study area occurs primarily as infiltration from precipitation and streams in the upland areas of the Casmalia Hills and Solomon Hills, and along the main channel of San Antonio Creek. Reported estimates of annual natural recharge during water years 1948–2018 generally ranged from about 5,000 acre-feet to more than about 30,000 acre-feet. Stable and radioactive isotopes show that groundwater from the lower aquifer is old and probably was recharged as infiltration from precipitation and streams in the eastern upland areas of the Solomon Hills; however, the infiltration and recharge from these sources probably does not occur under present-day climatic conditions. Anthropogenic recharge, from sources such as return flow from agricultural irrigation, municipal water systems, and wastewater effluent, was estimated to range from about 600 acre-feet in 1948 to about 6,600 acre-feet in 2018. The average annual amount of groundwater removed from the SACVW by pumping during 1948–2018 was estimated to be about 17,200 acre-feet per year, increasing from about 3,000 acre-feet in 1948 to about 32,600 acre-feet in 2018. Estimates of annual pumpage generally exceeded estimates of annual recharge beginning in the mid-1970s and continuing through 2018. The predominant direction of groundwater flow under historical and present-day conditions was from the eastern uplands in the Solomon Hills to the west along San Antonio Creek to the discharge area in Barka Slough, and from the northern uplands in the Casmalia Hills south to San Antonio Creek.
Pumpage since the early 1900s and the subsequent groundwater-level declines have substantially reduced the amount of natural groundwater discharge at Barka Slough. Estimates of base flow to San Antonio Creek at the western, downstream extent of the SACVW have varied over time in response to changes in groundwater pumpage and climate; however, there was an overall decline in base flow during water years 1956–2018, decreasing from an average of about 1,700 acre-feet per year during 1956–69, to about 300 acre-feet per year during 2016–18. The long-term extraction of groundwater correlates with a decrease in groundwater levels by more than about 150 feet since the early 1940s in the eastern part of the basin near Los Alamos, and as much as about 50 feet in the upland areas and in the western part of the basin. At Barka Slough, groundwater levels have declined below land surface in some places, altering native riparian vegetation in and around the slough.
Surface-water quality in the SACVW varied depending on location and the time of year the samples were collected and on the amount of annual precipitation Most groundwater in the SACVW was calcium-bicarbonate-type water with total dissolved-solids concentrations of about 500–800 milligrams per liter generally representing water naturally recharged as infiltration from precipitation and streams. Total dissolved-solids concentrations in some wells ranged from 800 to 8,000 milligrams per liter, suggesting mixing of naturally recharged infiltrated water with water associated with oil-bearing geologic formations, agricultural products, or the evaporation of shallow groundwater. Concentrations of total dissolved solids and the chemical constituents chloride, nitrate plus nitrite (as nitrogen), calcium, and magnesium at selected wells generally increased during water years 1980–2018; increasing concentrations of these constituents may be associated with the expansion of agriculture in the watershed over time and the corresponding increase in the use of nitrates and calcium- and magnesium-based fertilizers and soil additives in modern agricultural practices.
The predominant direction of groundwater flow during historical and present-day conditions was from the eastern uplands in the Solomon Hills to the west along San Antonio Creek toward Barka Slough, and from the western uplands in the Casmalia Hills south to San Antonio Creek. The age of groundwater in the SACVW was evaluated using radioactive isotopes, and the flow of groundwater within the SACVW was evaluated using radioactive and stable isotopes. Modern groundwater (recharged after 1952) was generally found adjacent to San Antonio Creek and its tributaries in wells with perforated depths that averaged about 270 feet below land surface. Pre-modern groundwater (recharged before 1952) was found in wells that had average perforation depths of about 540 ft below land surface. Pre-modern groundwater identified in wells in the eastern upland area is interpreted to have had long, slow travel times to the western part of the SACVW where it was eventually discharged as base flow at Barka Slough or extracted as groundwater pumpage.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225001","collaboration":"Prepared in cooperation with Santa Barbara County Water Agency and Vandenberg Space Force Base","programNote":"Groundwater Availability and Use Assessments","usgsCitation":"Cromwell, G., Sweetkind, D.S., Densmore, J.N., Engott, J.A., Seymour, W.A., Larsen, J.D., Ely, C.P., Stamos, C.L., and Faunt, C.C., 2022, Hydrogeologic characterization of the San Antonio Creek Valley watershed, Santa Barbara County, California: U.S. Geological Survey Scientific Investigations Report 2022–5001, 124 p., https://doi.org/10.3133/sir20225001.","productDescription":"Report: xiv, 124 p.; Data Release","numberOfPages":"124","onlineOnly":"Y","ipdsId":"IP-106483","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":395163,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5001/images"},{"id":395162,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5001/sir20225001.xml"},{"id":502288,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112320.htm","linkFileType":{"id":5,"text":"html"}},{"id":395158,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AD7DL8","linkHelpText":"Data release of hydrogeologic data from the San Antonio Creek Valley watershed, Santa Barbara County, California"},{"id":395161,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5001/sir20225001.pdf","text":"Report","size":"15 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":395160,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5001/covrthb.jpg"}],"country":"United States","state":"California","county":"Santa Barbara County","otherGeospatial":"San Antonio Creek Valley watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.50079345703125,\n 34.71113805795655\n ],\n [\n -120.09292602539062,\n 34.71113805795655\n ],\n [\n -120.09292602539062,\n 34.854382885097905\n ],\n [\n -120.50079345703125,\n 34.854382885097905\n ],\n [\n -120.50079345703125,\n 34.71113805795655\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
A suite of gas standards was developed to serve as international secondary reference materials (RMs) for the determination of the compound-specific carbon-13/carbon-12 (δ13C) and hydrogen-2/hydrogen-1 (δ2H) values of hydrocarbon gases. This report provides background information on the project, the methods used to produce and analyze the gases, as well as the data analysis and recommended stable isotopic values. Additionally, samples of older hydrocarbon gas RMs no longer available were analyzed along with the new RMs to allow for traceability to historical data. These secondary RMs are intended for interlaboratory standardization and traceability to primary RMs. The gaseous RMs are currently (at time of publication) available for purchase from the U.S. Geological Survey Energy Resources Program.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20215136","usgsCitation":"Ellis, G.S., and Dias, R.F., 2022, Development of hydrocarbon gas reference materials for stable isotopic composition (δ13C and δ2H): U.S. Geological Survey Scientific Investigations Report 2021–5136, 22 p., https://doi.org/10.3133/sir20215136.","productDescription":"Report: vii, 22 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-125531","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":395084,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RBXUMD","text":"USGS data release","linkHelpText":"Stable Isotopic Data (δ13C and δ2H) for Reference Materials HCG-1, HCG-2, and HCG-3"},{"id":395083,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5136/sir20215136.pdf","text":"Report","size":"2.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5136"},{"id":395082,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5136/coverthb.jpg"}],"contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Bathymetric and velocimetric data were collected by the U.S. Geological Survey, in cooperation with the Missouri Department of Transportation, near 9 bridges at 8 highway crossings of the Missouri River near Kansas City, Missouri, on August 13–14, 2019. A multibeam echosounder mapping system was used to obtain channel-bed elevations for river reaches about 1,550 to 1,660 feet longitudinally and generally extending laterally across the active channel from bank to bank during moderate flood-flow conditions. These surveys indicated the channel conditions at the time of the surveys and provided characteristics of scour holes that may be useful in developing predictive guidelines or equations for scour holes. These data also may be useful to the Missouri Department of Transportation as a low to moderate flood-flow assessment of the bridges for stability and integrity issues with respect to bridge scour during floods.
Bathymetric data were collected around every pier that was in water, except around the nose of one pier that was surrounded by a persistent debris raft. Scour holes were present at most piers for which bathymetry could be obtained, except those on banks or surrounded by riprap. The observed scour holes at the surveyed bridges generally were examined with respect to shape and depth.
Comparisons between bathymetric surfaces from previous surveys and this study do not indicate any consistent correlation in channel-bed elevations with streamflow conditions at the times of the surveys. The predominant overall scour observed between the various surveys implies the channel bed in the 2019 surveys might have been rebounding from more substantial scour caused by the high streamflow earlier in March and June 2019, which was the highest streamflow since 1993. Pier size and nose shape had a substantial effect on the size of the scour hole observed at a given pier. Many of the piers at the Kansas City area bridges have wide or blunt noses caused by exposed footings, seal courses, or caissons, which resulted in large, deep scour holes at most piers. Several of the structures had piers that were skewed to primary approach flow; and, at most of the structures, the scour hole was deeper and longer on the side of the pier with impinging flow than the leeward side, with some amount of deposition on the leeward side, as typically has been observed at piers skewed to approach flow.
Limited additional bathymetric data were collected by the U.S. Geological Survey, in cooperation with Clarkson Construction, near the main channel piers of the U.S. Highway 169 (Broadway) and the Interstate 435 (Randolph) bridges on August 17 and October 23, 2020, to determine the channel-bed conditions before and after installation of scour countermeasures near those piers. Survey results from before and after installation of these countermeasures show these features had a substantial effect on mitigating the observed scour at these piers, particularly when compared to piers at other sites without such features.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215098","collaboration":"Prepared in cooperation with the Missouri Department of Transportation and Clarkson Construction","usgsCitation":"Huizinga, R.J., 2022, Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River near Kansas City, Missouri, August 2019, August 2020, and October 2020: U.S. Geological Survey Scientific Investigations Report 2021–5098, 112 p., https://doi.org/10.3133/sir20215098.","productDescription":"Report: xii, 112 p.; Data Release; Dataset","numberOfPages":"128","onlineOnly":"Y","ipdsId":"IP-124626","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":395010,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96TX8AE","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Bathymetry and velocity data from surveys at highway bridges crossing the Missouri River in Kansas City, Missouri, in August 2019, August 2020, and October 2020"},{"id":395008,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5098/coverthb.jpg"},{"id":395013,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5098/images"},{"id":395012,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5098/sir20215098.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2021–5098 XML"},{"id":395011,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":395009,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5098/sir20215098.pdf","text":"Report","size":"38.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5098"},{"id":502114,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112326.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Missouri","city":"Kansas City","otherGeospatial":"Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.68086242675781,\n 39.102357437817595\n ],\n [\n -94.48722839355467,\n 39.102357437817595\n ],\n [\n -94.48722839355467,\n 39.193948213963665\n ],\n [\n -94.68086242675781,\n 39.193948213963665\n ],\n [\n -94.68086242675781,\n 39.102357437817595\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Tidal wetlands provide myriad ecosystem services across local to global scales. With their uncertain vulnerability or resilience to rising sea levels, there is a need for mapping flooding drivers and vulnerability proxies for these ecosystems at a national scale. However, tidal wetlands in the conterminous USA are diverse with differing elevation gradients, and tidal amplitudes, making broad geographic comparisons difficult. To address this, a national-scale map of relative tidal elevation (Z*MHW), a physical metric that normalizes elevation to tidal amplitude at mean high water (MHW), was constructed for the first time at 30 × 30-m resolution spanning the conterminous USA. Contrary to two study hypotheses, watershed-level median Z*MHW and its variability generally increased from north to south as a function of tidal amplitude and relative sea-level rise. These trends were also observed in a reanalysis of ground elevation data from the Pacific Coast by Janousek et al. (Estuaries and Coasts 42 (1): 85–98, 2019). Supporting a third hypothesis, propagated uncertainty in Z*MHW increased from north to south as light detection and ranging (LiDAR) errors had an outsized effect under narrowing tidal amplitudes. The drivers of Z*MHW and its variability are difficult to determine because several potential causal variables are correlated with latitude, but future studies could investigate highest astronomical tide and diurnal high tide inequality as drivers of median Z*MHW and Z*MHW variability, respectively. Watersheds of the Gulf Coast often had propagated Z*MHW uncertainty greater than the tidal amplitude itself emphasizing the diminished practicality of applying Z*MHW as a flooding proxy to microtidal wetlands. Future studies could focus on validating and improving these physical map products and using them for synoptic modeling of tidal wetland carbon dynamics and sea-level rise vulnerability analyses.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-021-01027-9","usgsCitation":"Holmquist, J.R., and Windham-Myers, L., 2022, A conterminous USA-scale map of relative tidal marsh elevation: Estuaries and Coasts, v. 45, p. 1596-1614, https://doi.org/10.1007/s12237-021-01027-9.","productDescription":"19 p.","startPage":"1596","endPage":"1614","ipdsId":"IP-120531","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":448992,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-021-01027-9","text":"Publisher Index Page"},{"id":395143,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 46.90008\n ],\n [\n -84.77924,\n 46.6371\n ],\n [\n -84.54375,\n 46.53868\n ],\n [\n -84.6049,\n 46.4396\n ],\n [\n -84.3367,\n 46.40877\n ],\n [\n -84.14212,\n 46.51223\n ],\n [\n -84.09185,\n 46.27542\n ],\n [\n -83.89077,\n 46.11693\n ],\n [\n -83.61613,\n 46.11693\n ],\n [\n -83.46955,\n 45.99469\n ],\n [\n -83.59285,\n 45.81689\n ],\n [\n -82.55092,\n 45.34752\n ],\n [\n -82.33776,\n 44.44\n ],\n [\n -82.13764,\n 43.57109\n ],\n [\n -82.43,\n 42.98\n ],\n [\n -82.9,\n 42.43\n ],\n [\n -83.12,\n 42.08\n ],\n [\n -83.142,\n 41.97568\n ],\n [\n -83.02981,\n 41.8328\n ],\n [\n -82.69009,\n 41.67511\n ],\n [\n -82.43928,\n 41.67511\n ],\n [\n -81.27775,\n 42.20903\n ],\n [\n -80.24745,\n 42.3662\n ],\n [\n -78.93936,\n 42.86361\n ],\n [\n -78.92,\n 42.965\n ],\n [\n -79.01,\n 43.27\n ],\n [\n -79.17167,\n 43.46634\n ],\n [\n -78.72028,\n 43.62509\n ],\n [\n -77.73789,\n 43.62906\n ],\n [\n -76.82003,\n 43.62878\n ],\n [\n -76.5,\n 44.01846\n ],\n [\n -76.375,\n 44.09631\n ],\n [\n -75.31821,\n 44.81645\n ],\n [\n -74.867,\n 45.00048\n ],\n [\n -73.34783,\n 45.00738\n ],\n [\n -71.50506,\n 45.0082\n ],\n [\n -71.405,\n 45.255\n ],\n [\n -71.08482,\n 45.30524\n ],\n [\n -70.66,\n 45.46\n ],\n [\n -70.305,\n 45.915\n ],\n [\n -69.99997,\n 46.69307\n ],\n [\n -69.23722,\n 47.44778\n ],\n [\n -68.905,\n 47.185\n ],\n [\n -68.23444,\n 47.35486\n ],\n [\n -67.79046,\n 47.06636\n ],\n [\n -67.79134,\n 45.70281\n ],\n [\n -67.13741,\n 45.13753\n ],\n [\n -66.96466,\n 44.8097\n ],\n [\n -68.03252,\n 44.3252\n ],\n [\n -69.06,\n 43.98\n ],\n [\n -70.11617,\n 43.68405\n ],\n [\n -70.64548,\n 43.09024\n ],\n [\n -70.81489,\n 42.8653\n ],\n [\n -70.825,\n 42.335\n ],\n [\n -70.495,\n 41.805\n ],\n [\n -70.08,\n 41.78\n ],\n [\n -70.185,\n 42.145\n ],\n [\n -69.88497,\n 41.92283\n ],\n [\n -69.96503,\n 41.63717\n ],\n [\n -70.64,\n 41.475\n ],\n [\n -71.12039,\n 41.49445\n ],\n [\n -71.86,\n 41.32\n ],\n [\n -72.295,\n 41.27\n ],\n [\n -72.87643,\n 41.22065\n ],\n [\n -73.71,\n 40.9311\n ],\n [\n -72.24126,\n 41.11948\n ],\n [\n -71.945,\n 40.93\n ],\n [\n -73.345,\n 40.63\n ],\n [\n -73.982,\n 40.628\n ],\n [\n -73.95232,\n 40.75075\n ],\n [\n -74.25671,\n 40.47351\n ],\n [\n -73.96244,\n 40.42763\n ],\n [\n -74.17838,\n 39.70926\n ],\n [\n -74.90604,\n 38.93954\n ],\n [\n -74.98041,\n 39.1964\n ],\n [\n -75.20002,\n 39.24845\n ],\n [\n -75.52805,\n 39.4985\n ],\n [\n -75.32,\n 38.96\n ],\n [\n -75.07183,\n 38.78203\n ],\n [\n -75.05673,\n 38.40412\n ],\n [\n -75.37747,\n 38.01551\n ],\n [\n -75.94023,\n 37.21689\n ],\n [\n -76.03127,\n 37.2566\n ],\n [\n -75.72205,\n 37.93705\n ],\n [\n -76.23287,\n 38.31921\n ],\n [\n -76.35,\n 39.15\n ],\n [\n -76.54272,\n 38.71762\n ],\n [\n -76.32933,\n 38.08326\n ],\n [\n -76.99,\n 38.23999\n ],\n [\n -76.30162,\n 37.91794\n ],\n [\n -76.25874,\n 36.9664\n ],\n [\n -75.9718,\n 36.89726\n ],\n [\n -75.86804,\n 36.55125\n ],\n [\n -75.72749,\n 35.55074\n ],\n [\n -76.36318,\n 34.80854\n ],\n [\n -77.39763,\n 34.51201\n ],\n [\n -78.05496,\n 33.92547\n ],\n [\n -78.55435,\n 33.86133\n ],\n [\n -79.06067,\n 33.49395\n ],\n [\n -79.20357,\n 33.15839\n ],\n [\n -80.30132,\n 32.50935\n ],\n [\n -80.86498,\n 32.0333\n ],\n [\n -81.33629,\n 31.44049\n ],\n [\n -81.49042,\n 30.72999\n ],\n [\n -81.31371,\n 30.03552\n ],\n [\n -80.98,\n 29.18\n ],\n [\n -80.53558,\n 28.47213\n ],\n [\n -80.53,\n 28.04\n ],\n [\n -80.05654,\n 26.88\n ],\n [\n -80.08801,\n 26.20576\n ],\n [\n -80.13156,\n 25.81677\n ],\n [\n -80.38103,\n 25.20616\n ],\n [\n -80.68,\n 25.08\n ],\n [\n -81.17213,\n 25.20126\n ],\n [\n -81.33,\n 25.64\n ],\n [\n -81.71,\n 25.87\n ],\n [\n -82.24,\n 26.73\n ],\n [\n -82.70515,\n 27.49504\n ],\n [\n -82.85526,\n 27.88624\n ],\n [\n -82.65,\n 28.55\n ],\n [\n -82.93,\n 29.1\n ],\n [\n -83.70959,\n 29.93656\n ],\n [\n -84.1,\n 30.09\n ],\n [\n -85.10882,\n 29.63615\n ],\n [\n -85.28784,\n 29.68612\n ],\n [\n -85.7731,\n 30.15261\n ],\n [\n -86.4,\n 30.4\n ],\n [\n -87.53036,\n 30.27433\n ],\n [\n -88.41782,\n 30.3849\n ],\n [\n -89.18049,\n 30.31598\n ],\n [\n -89.59383,\n 30.15999\n ],\n [\n -89.41373,\n 29.89419\n ],\n [\n -89.43,\n 29.48864\n ],\n [\n -89.21767,\n 29.29108\n ],\n [\n -89.40823,\n 29.15961\n ],\n [\n -89.77928,\n 29.30714\n ],\n [\n -90.15463,\n 29.11743\n ],\n [\n -90.88022,\n 29.14854\n ],\n [\n -91.62678,\n 29.677\n ],\n [\n -92.49906,\n 29.5523\n ],\n [\n -93.22637,\n 29.78375\n ],\n [\n -93.84842,\n 29.71363\n ],\n [\n -94.69,\n 29.48\n ],\n [\n -95.60026,\n 28.73863\n ],\n [\n -96.59404,\n 28.30748\n ],\n [\n -97.14,\n 27.83\n ],\n [\n -97.37,\n 27.38\n ],\n [\n -97.38,\n 26.69\n ],\n [\n -97.33,\n 26.21\n ],\n [\n -97.14,\n 25.87\n ],\n [\n -97.53,\n 25.84\n ],\n [\n -98.24,\n 26.06\n ],\n [\n -99.02,\n 26.37\n ],\n [\n -99.3,\n 26.84\n ],\n [\n -99.52,\n 27.54\n ],\n [\n -100.11,\n 28.11\n ],\n [\n -100.45584,\n 28.69612\n ],\n [\n -100.9576,\n 29.38071\n ],\n [\n -101.6624,\n 29.7793\n ],\n [\n -102.48,\n 29.76\n ],\n [\n -103.11,\n 28.97\n ],\n [\n -103.94,\n 29.27\n ],\n [\n -104.45697,\n 29.57196\n ],\n [\n -104.70575,\n 30.12173\n ],\n [\n -105.03737,\n 30.64402\n ],\n [\n -105.63159,\n 31.08383\n ],\n [\n -106.1429,\n 31.39995\n ],\n [\n -106.50759,\n 31.75452\n ],\n [\n -108.24,\n 31.75485\n ],\n [\n -108.24194,\n 31.34222\n ],\n [\n -109.035,\n 31.34194\n ],\n [\n -111.02361,\n 31.33472\n ],\n [\n -113.30498,\n 32.03914\n ],\n [\n -114.815,\n 32.52528\n ],\n [\n -114.72139,\n 32.72083\n ],\n [\n -115.99135,\n 32.61239\n ],\n [\n -117.12776,\n 32.53534\n ],\n [\n -117.29594,\n 33.04622\n ],\n [\n -117.944,\n 33.62124\n ],\n [\n -118.4106,\n 33.74091\n ],\n [\n -118.51989,\n 34.02778\n ],\n [\n -119.081,\n 34.078\n ],\n [\n -119.43884,\n 34.34848\n ],\n [\n -120.36778,\n 34.44711\n ],\n [\n -120.62286,\n 34.60855\n ],\n [\n -120.74433,\n 35.15686\n ],\n [\n -121.71457,\n 36.16153\n ],\n [\n -122.54747,\n 37.55176\n ],\n [\n -122.51201,\n 37.78339\n ],\n [\n -122.95319,\n 38.11371\n ],\n [\n -123.7272,\n 38.95166\n ],\n [\n -123.86517,\n 39.76699\n ],\n [\n -124.39807,\n 40.3132\n ],\n [\n -124.17886,\n 41.14202\n ],\n [\n -124.2137,\n 41.99964\n ],\n [\n -124.53284,\n 42.76599\n ],\n [\n -124.14214,\n 43.70838\n ],\n [\n -124.02053,\n 44.6159\n ],\n [\n -123.89893,\n 45.52341\n ],\n [\n -124.07963,\n 46.86475\n ],\n [\n -124.39567,\n 47.72017\n ],\n [\n -124.68721,\n 48.18443\n ],\n [\n -124.5661,\n 48.37971\n ],\n [\n -123.12,\n 48.04\n ],\n [\n -122.58736,\n 47.096\n ],\n [\n -122.34,\n 47.36\n ],\n [\n -122.5,\n 48.18\n ],\n [\n -122.84,\n 49\n ],\n [\n -120,\n 49\n ],\n [\n -117.03121,\n 49\n ],\n [\n -116.04818,\n 49\n ],\n [\n -113,\n 49\n ],\n [\n -110.05,\n 49\n ],\n [\n -107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","volume":"45","noUsgsAuthors":false,"publicationDate":"2022-01-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Holmquist, James R.","contributorId":173462,"corporation":false,"usgs":false,"family":"Holmquist","given":"James","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":832239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Windham-Myers, Lisamarie 0000-0003-0281-9581 lwindham-myers@usgs.gov","orcid":"https://orcid.org/0000-0003-0281-9581","contributorId":2449,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","email":"lwindham-myers@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":832240,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70230384,"text":"70230384 - 2022 - Human-cougar interactions: A literature review related to common management questions","interactions":[],"lastModifiedDate":"2022-04-11T13:23:17.531367","indexId":"70230384","displayToPublicDate":"2022-01-31T08:20:27","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"title":"Human-cougar interactions: A literature review related to common management questions","docAbstract":"Interactions between humans and cougars (Puma concolor) present unique challenges for wildlife managers; reducing occurrences that lead to conflict is a priority for state and provincial wildlife agencies throughout western North America, including Washington. With an increase in management emphasis of human-wildlife conflict resolution, a growing body of scientific literature related to cougar wildland-urban ecology and the factors that contribute to interactions between cougars and people has developed. Based on discussions with the Fish and Wildlife Commission, our 10-member Human-Cougar Interaction Science Review Team assessed both the analytical and ecological merits of current literature, focusing on data and methods, to summarize the current state of knowledge on human-cougar interactions and factors affecting these interactions. We did not use our review findings to provide management recommendations or evaluate/suggest policy alternatives, but we did highlight important information gaps, research needs, and proposed strategies for conducting scientific investigations to benefit managers and policy makers in the future. We used bibliographic lists, keyword searches in research databases, and new literature encountered as citations within papers we reviewed to identify 96 potential studies for review. We evaluated 41 studies that aligned with eight commonly asked questions regarding how various factors contribute to cougar proximity to, and interactions with people. Our review concluded that the roles of cougar removals (Question 1), cougar population size or trajectory (Question 2), the abundance or diversity of prey (Question 3), human population size, distribution, or recreation levels (Question 6), human attitudes (Question 7), and competition with other large carnivores (Question 8) in cougar interactions with people remain uncertain. We found the studies evaluating the efficacy of nonlethal deterrents (Question 4) provided some evidence that these methods reduce conflict, most notably that flashing lights can reduce interactions in specific situations. Our review of papers investigating the role of landscape characteristics (Question 5) revealed spatial ecology to be the most reliably studied and best understood facet of cougar wildland-urban ecology; study designs in these investigations were also the most rigorous. Most cougar use, and subsequent interactions with people, occur at the wildland-urban interface or in exurban and rural residential settings immediately adjacent because these habitats provide both abundant native prey (deer) and stalking cover, or they retain enough native landcover, connectivity, and prey to support cougar use, but with a human presence at a level that does not substantially deter cougars. We identified only a limited number of informative studies in our review, primarily because many studies did not collect data to specifically address relevant management questions after developing testable hypotheses. Much of the literature we reviewed was derived from ad hoc mining of pre-existing data that had been collected for other routine reasons, data were often not assessed for accuracy, and confounding factors were inadequately addressed. Consequently, many factors theorized to contribute to cougar interactions with people require more rigorous investigation. Because wildland-urban systems are complex, and interactions encompass both human and cougar behavior, we recommend the use of long-term studies that incorporate both ecological and anthropogenic factors within a control-treatment design with replicate study sites to address questions with direct management relevance.
","language":"English","publisher":"Washington Department of Fish and Wildlife","usgsCitation":"Kertson, B., McCorquodale, S.M., Anderson, C.R., Aoude, A.N., Beausoleil, R., Cope, M.G., Hurley, M.A., Johnson, B.K., Sargeant, G., and Simek, S., 2022, Human-cougar interactions: A literature review related to common management questions, v, 73 p.","productDescription":"v, 73 p.","ipdsId":"IP-137083","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":398461,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":398450,"type":{"id":15,"text":"Index Page"},"url":"https://wdfw.wa.gov/publications/02296"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kertson, B. N.","contributorId":289999,"corporation":false,"usgs":false,"family":"Kertson","given":"B. N.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":840135,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCorquodale, S. M.","contributorId":290000,"corporation":false,"usgs":false,"family":"McCorquodale","given":"S.","email":"","middleInitial":"M.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":840136,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, C. R.","contributorId":290001,"corporation":false,"usgs":false,"family":"Anderson","given":"C.","email":"","middleInitial":"R.","affiliations":[{"id":39887,"text":"Colorado Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":840137,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aoude, Anis N.","contributorId":290003,"corporation":false,"usgs":false,"family":"Aoude","given":"Anis","email":"","middleInitial":"N.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":840138,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beausoleil, R. A.","contributorId":290006,"corporation":false,"usgs":false,"family":"Beausoleil","given":"R. A.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":840139,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cope, M. G.","contributorId":290009,"corporation":false,"usgs":false,"family":"Cope","given":"M.","email":"","middleInitial":"G.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":840140,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hurley, M. A.","contributorId":290012,"corporation":false,"usgs":false,"family":"Hurley","given":"M.","email":"","middleInitial":"A.","affiliations":[{"id":62300,"text":"Idaho Fish and Game","active":true,"usgs":false}],"preferred":false,"id":840141,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johnson, B. K.","contributorId":290015,"corporation":false,"usgs":false,"family":"Johnson","given":"B.","email":"","middleInitial":"K.","affiliations":[{"id":62301,"text":"Oregon Department of Fish and Wildlife (retired)","active":true,"usgs":false}],"preferred":false,"id":840142,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sargeant, Glen A. 0000-0003-3845-8503","orcid":"https://orcid.org/0000-0003-3845-8503","contributorId":219538,"corporation":false,"usgs":true,"family":"Sargeant","given":"Glen A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":840143,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Simek, S. L.","contributorId":290019,"corporation":false,"usgs":false,"family":"Simek","given":"S. L.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":840144,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70227734,"text":"mcs2022 - 2022 - Mineral commodity summaries 2022","interactions":[],"lastModifiedDate":"2026-03-25T16:48:33.121414","indexId":"mcs2022","displayToPublicDate":"2022-01-31T08:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":323,"text":"Mineral Commodity Summaries","code":"MCS","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022","displayTitle":"Mineral Commodity Summaries 2022","title":"Mineral commodity summaries 2022","docAbstract":"Each mineral commodity chapter of the 2022 edition of the U.S. Geological Survey (USGS) Mineral Commodity Summaries (MCS) includes information on events, trends, and issues for each mineral commodity as well as discussions and tabular presentations on domestic industry structure, Government programs, tariffs, 5-year salient statistics, and world production, reserves, and resources. The MCS is the earliest comprehensive source of 2021 mineral production data for the world. More than 90 individual minerals and materials are covered by 2-page synopses.
For mineral commodities for which there is a Government stockpile, detailed information concerning the stockpile status is included in the 2-page synopsis.
Abbreviations and units of measure and definitions of selected terms used in the report are in Appendix A and Appendix B, respectively. Reserves and resources information is in Appendix C, which includes “Part A—Resource and Reserve Classification for Minerals” and “Part B—Sources of Reserves Data.” A directory of USGS minerals information country specialists and their responsibilities is in Appendix D.
The USGS continually strives to improve the value of its publications to users. Constructive comments and suggestions by readers of the MCS 2022 are welcomed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/mcs2022","usgsCitation":"U.S. Geological Survey, 2022, Mineral commodity summaries 2022: U.S. Geological Survey, 202 p., https://doi.org/10.3133/mcs2022.","productDescription":"Report: 202 p.; Data Release","numberOfPages":"202","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-135364","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":394990,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/periodicals/mcs2022/coverthb.jpg"},{"id":394991,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/periodicals/mcs2022/mcs2022.pdf","text":"Report","size":"14.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"MCS 2022"},{"id":394992,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://www.usgs.gov/centers/national-minerals-information-center/mineral-commodity-summaries","text":"Mineral Commodity Summaries Prior to 2022"},{"id":501519,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112322.htm","linkFileType":{"id":5,"text":"html"}},{"id":395043,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KKMCP4","text":"USGS data release","linkHelpText":"Data release for mineral commodity summaries 2022"},{"id":394993,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://www.usgs.gov/centers/national-minerals-information-center/commodity-statistics-and-information","text":"Commodity Statistics and Information"}],"contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
The Interagency Ocean Observation Committee (IOOC) is chartered by the White House Office of Science and Technology Policy (OSTP) Subcommittee on Ocean Science and Technology (SOST). The purpose of the IOOC is to advise, assist, and make recommendations to the SOST on matters related to ocean observations via task teams such as the Biology - Integrating Core to Essential Variables (Bio-ICE) task team. The goal of the Bio-ICE task team is to advance the integration of biological observations from local, regional, and federal sources using best practices to inform national needs and ultimately feed seamlessly into the Global Ocean Observing System (GOOS), as appropriate. To accomplish this goal, and for the first time at the U.S. federal government level, a subgroup of the Bio-ICE task team focused on tropical, shallow-water (0-30 m) hard corals to identify commonalities between the U.S. Integrated Ocean Observing System (IOOS) core biological variable1 of “coral species and abundance,” the GOOS Essential Ocean Variable2 (EOV) “hard coral cover and composition,” the Group on Earth Observations Biological Observation Network (GEO BON) Essential Biodiversity Variables3 (EBVs), and the Global Climate Observing System (GCOS) Essential Climate Variables4 (ECVs) (Figure 1). The EOV data allows production of EBVs such as time series of maps of genetic composition, species populations, etc. Recognizing the complementarity of the different essential variable frameworks helps to promote best practices in observing and information management to facilitate data interoperability (Figure 1). The task team was charged with identifying where there are synergies in terms of spatial and temporal observing requirements and existing observation infrastructure and data delivery, including best practices and standard operating procedures. The task team also made suggestions to improve pathways for data flow for observations of these variables from Regional Associations of the U.S. IOOS, other nonfederal partners, and federal sources. The focus of the task team was on identifying and implementing best practices surrounding standardized data collection and data delivery to make continued progress toward adhering to the Findability, Accessibility, Interoperability, and Reuse (FAIR) and Collective benefit, Authority to control, Responsibility, and Ethics (CARE) data principles.
","language":"English","publisher":"Interagency Ocean Observation Committee (IOOC)","usgsCitation":"Towle, E.K., Benson, A., Biddle, M., Bingo, S., Brucker, K., Canonico, G., Chory, M., Desai, K., Edmondson, M., Figuerola, M., Horstmann, C., Jackson, S., Koss, J., Landrum, J., Lohr, K., Lorenzoni, L., Mayfield, A., Melzin, B., Muller-Karger, F., O’Conner, S., Santavy, D., Storlazzi, C.D., Toline, A., Torres-Perez, J., and Yates, K.K., 2022, Biology: Integrating core to essential variables (Bio-ICE) task team report for hard corals: Task Team Report, 30 p.","productDescription":"30 p.","ipdsId":"IP-136937","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":409792,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":409777,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.iooc.us/task-teams/bio-ice/"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Towle, E. K.","contributorId":299459,"corporation":false,"usgs":false,"family":"Towle","given":"E.","email":"","middleInitial":"K.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":857849,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Benson, Abigail 0000-0002-4391-107X","orcid":"https://orcid.org/0000-0002-4391-107X","contributorId":202078,"corporation":false,"usgs":true,"family":"Benson","given":"Abigail","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":857850,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Biddle, Matt","contributorId":299460,"corporation":false,"usgs":false,"family":"Biddle","given":"Matt","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":857851,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bingo, Sarah","contributorId":299462,"corporation":false,"usgs":false,"family":"Bingo","given":"Sarah","email":"","affiliations":[{"id":64853,"text":"PacIOOS","active":true,"usgs":false}],"preferred":false,"id":857852,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brucker, Kaitlyn","contributorId":299463,"corporation":false,"usgs":false,"family":"Brucker","given":"Kaitlyn","email":"","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":857853,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Canonico, Gabrielle","contributorId":217563,"corporation":false,"usgs":false,"family":"Canonico","given":"Gabrielle","email":"","affiliations":[{"id":39659,"text":"National Oceanographic and Atmospheric Administration, US Integrated Ocean Observing System, Silver Spring, MD, USA","active":true,"usgs":false}],"preferred":false,"id":857867,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chory, Maggie","contributorId":299465,"corporation":false,"usgs":false,"family":"Chory","given":"Maggie","email":"","affiliations":[{"id":64854,"text":"COL","active":true,"usgs":false}],"preferred":false,"id":857854,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Desai, Kruit","contributorId":299466,"corporation":false,"usgs":false,"family":"Desai","given":"Kruit","email":"","affiliations":[{"id":64854,"text":"COL","active":true,"usgs":false}],"preferred":false,"id":857855,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Edmondson, Masha","contributorId":299467,"corporation":false,"usgs":false,"family":"Edmondson","given":"Masha","email":"","affiliations":[{"id":64854,"text":"COL","active":true,"usgs":false}],"preferred":false,"id":857856,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Figuerola, Miguel","contributorId":299468,"corporation":false,"usgs":false,"family":"Figuerola","given":"Miguel","email":"","affiliations":[{"id":64856,"text":"PR-DNRA","active":true,"usgs":false}],"preferred":false,"id":857857,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Horstmann, Christina","contributorId":272093,"corporation":false,"usgs":false,"family":"Horstmann","given":"Christina","email":"","affiliations":[{"id":56350,"text":"Oak Ridge Institute for Science Education Participant at US EPA","active":true,"usgs":false}],"preferred":false,"id":857858,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jackson, Susan K","contributorId":272091,"corporation":false,"usgs":false,"family":"Jackson","given":"Susan K","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":857859,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Koss, Jen","contributorId":299477,"corporation":false,"usgs":false,"family":"Koss","given":"Jen","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":857868,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Landrum, J.","contributorId":299496,"corporation":false,"usgs":false,"family":"Landrum","given":"J.","email":"","affiliations":[],"preferred":false,"id":857912,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Lohr, Kathryn","contributorId":299472,"corporation":false,"usgs":false,"family":"Lohr","given":"Kathryn","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":857861,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Lorenzoni, Laura","contributorId":212785,"corporation":false,"usgs":false,"family":"Lorenzoni","given":"Laura","email":"","affiliations":[{"id":38682,"text":"NASA Earth Science Division","active":true,"usgs":false}],"preferred":false,"id":857913,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Mayfield, Anderson","contributorId":299473,"corporation":false,"usgs":false,"family":"Mayfield","given":"Anderson","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":857862,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Melzin, Brian","contributorId":299474,"corporation":false,"usgs":false,"family":"Melzin","given":"Brian","email":"","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":857863,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Muller-Karger, Frank","contributorId":218424,"corporation":false,"usgs":false,"family":"Muller-Karger","given":"Frank","affiliations":[],"preferred":false,"id":857864,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"O’Conner, Sarah","contributorId":299475,"corporation":false,"usgs":false,"family":"O’Conner","given":"Sarah","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":857865,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Santavy, Deb","contributorId":299476,"corporation":false,"usgs":false,"family":"Santavy","given":"Deb","email":"","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":857866,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":857869,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Toline, Anna","contributorId":299478,"corporation":false,"usgs":false,"family":"Toline","given":"Anna","email":"","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":857870,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Torres-Perez, Juan","contributorId":299479,"corporation":false,"usgs":false,"family":"Torres-Perez","given":"Juan","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":857871,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Yates, Kimberly K. 0000-0001-8764-0358","orcid":"https://orcid.org/0000-0001-8764-0358","contributorId":214349,"corporation":false,"usgs":true,"family":"Yates","given":"Kimberly","email":"","middleInitial":"K.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":857872,"contributorType":{"id":1,"text":"Authors"},"rank":25}]}} ,{"id":70256719,"text":"70256719 - 2022 - Tracking spatial regimes in animal communities: Implications for resilience-based management","interactions":[],"lastModifiedDate":"2024-09-03T16:17:05.511321","indexId":"70256719","displayToPublicDate":"2022-01-29T11:08:28","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Tracking spatial regimes in animal communities: Implications for resilience-based management","docAbstract":"Spatial regimes (the spatial extents of ecological states) exhibit strong spatiotemporal order as they expand or contract in response to retreating or encroaching adjacent spatial regimes (e.g., woody plant invasion of grasslands) and human management (e.g., fire treatments). New methods enable tracking spatial regime boundaries via vegetation landcover data, and this approach is being used for strategic management across biomes. A clear advancement would be incorporating animal community data to track spatial regime boundaries alongside vegetation data. In a 41,170-hectare grassland experiencing woody plant encroachment, we test the utility of using animal community data to track spatial regimes via two hypotheses. (H1) Spatial regime boundaries identified via independent vegetation and animal datasets will exhibit spatial synchrony; specifically, grassland:woodland bird community boundaries will synchronize with grass:woody vegetation boundaries. (H2) Negative feedbacks will stabilize spatial regimes identified via animal data; specifically, frequent fire treatments will stabilize grassland bird community boundaries. We used 26 years of bird community and vegetation data alongside 32 years of fire history data. We identified spatial regime boundaries with bird community data via a wombling approach. We identified spatial regime boundaries with vegetation data by calculating spatial covariance between remotely-sensed grass and woody plant cover per pixel. For fire history data, we calculated the cumulative number of fires per pixel. Setting bird boundary strength (wombling R2 values) as the response variable, we tested our hypotheses with a hierarchical generalized additive model (HGAM). Both hypotheses were supported: animal boundaries synchronized with vegetation boundaries in space and time, and grassland bird communities stabilized as fire frequency increased (HGAM explained 38% of deviance). We can now track spatial regimes via animal community data pixel-by-pixel and year-by-year. Alongside vegetation boundary tracking, tracking animal community boundaries can inform the scale of management necessary to maintain animal communities endemic to desirable ecological states. Our approach will be especially useful for conserving animal communities requiring large-scale, unfragmented landscapes—like grasslands and steppes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2022.108567","usgsCitation":"Roberts, C.P., Uden, D.R., Allen, C., Angeler, D., Powell, L., Allred, B.W., Jones, M., Maestas, J.D., and Twidwell, D., 2022, Tracking spatial regimes in animal communities: Implications for resilience-based management: Ecological Indicators, v. 136, 108567, 9 p., https://doi.org/10.1016/j.ecolind.2022.108567.","productDescription":"108567, 9 p.","ipdsId":"IP-133356","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":448996,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2022.108567","text":"Publisher Index Page"},{"id":433414,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","otherGeospatial":"Fort Riley Army Base","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.96213921773204,\n 39.311060889325915\n ],\n [\n -96.96422797821519,\n 39.2045692635035\n ],\n [\n -96.9059515607264,\n 39.170753927787935\n ],\n [\n -96.87441127742586,\n 39.12982552331178\n ],\n [\n -96.87065150855537,\n 39.06172160474132\n ],\n [\n -96.83117393541791,\n 39.03739558273512\n ],\n [\n -96.75242766519114,\n 39.027994666034715\n ],\n [\n -96.70313291778122,\n 39.08988085180364\n ],\n [\n -96.68057430455956,\n 39.133608110581775\n ],\n [\n -96.68057430455947,\n 39.2068138331922\n ],\n [\n -96.74490812745047,\n 39.242505115215266\n ],\n [\n -96.84683963904419,\n 39.30135970662323\n ],\n [\n -96.96213921773204,\n 39.311060889325915\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"136","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Roberts, Caleb Powell 0000-0002-8716-0423","orcid":"https://orcid.org/0000-0002-8716-0423","contributorId":288567,"corporation":false,"usgs":true,"family":"Roberts","given":"Caleb","email":"","middleInitial":"Powell","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908767,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Uden, Daniel R.","contributorId":74258,"corporation":false,"usgs":true,"family":"Uden","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":908768,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Craig R.","contributorId":246029,"corporation":false,"usgs":false,"family":"Allen","given":"Craig R.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":908769,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Angeler, David G.","contributorId":25027,"corporation":false,"usgs":true,"family":"Angeler","given":"David G.","affiliations":[],"preferred":false,"id":908770,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Powell, Larkin A.","contributorId":15100,"corporation":false,"usgs":true,"family":"Powell","given":"Larkin A.","affiliations":[],"preferred":false,"id":908771,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allred, Brady W","contributorId":216378,"corporation":false,"usgs":false,"family":"Allred","given":"Brady","email":"","middleInitial":"W","affiliations":[{"id":39397,"text":"W.A. Franke College of Forestry and Conservation University of Montana, Missoula","active":true,"usgs":false}],"preferred":false,"id":908772,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jones, Matthew O.","contributorId":341488,"corporation":false,"usgs":false,"family":"Jones","given":"Matthew O.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":908773,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Maestas, Jeremy D","contributorId":191086,"corporation":false,"usgs":false,"family":"Maestas","given":"Jeremy","email":"","middleInitial":"D","affiliations":[],"preferred":false,"id":908774,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Twidwell, Dirac","contributorId":341491,"corporation":false,"usgs":false,"family":"Twidwell","given":"Dirac","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":908775,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70227702,"text":"ofr20211123 - 2022 - Optimization of salt marsh management at the Petit Manan National Wildlife Refuge of the Maine Coastal Islands National Wildlife Refuge Complex, Maine, through use of structured decision making","interactions":[],"lastModifiedDate":"2026-03-25T17:53:23.031994","indexId":"ofr20211123","displayToPublicDate":"2022-01-27T12:50:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1123","displayTitle":"Optimization of Salt Marsh Management at the Petit Manan National Wildlife Refuge of the Maine Coastal Islands National Wildlife Refuge Complex, Maine, Through Use of Structured Decision Making","title":"Optimization of salt marsh management at the Petit Manan National Wildlife Refuge of the Maine Coastal Islands National Wildlife Refuge Complex, Maine, through use of structured decision making","docAbstract":"Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Petit Manan National Wildlife Refuge of the Maine Coastal Islands National Wildlife Refuge Complex in Maine. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of two marsh management units within the refuge complex, totaling about 47 hectares, and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that could be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that could maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to $9,545, and may continue to increase at a lower rate with further expenditures. Potential management actions in optimal portfolios at total costs less than or equal to $9,545 included removing dikes to restore tidal flow in the Gouldsboro Bay management unit and installing runnels to improve surface-water drainage in the Sawyers Marsh management unit. The potential management benefits were derived from expected increases in the numbers of tidal marsh obligate breeding birds and density of spiders (as an indicator of trophic health), reduced duration of flooding, and increased capacity of marsh elevation to keep pace with sea-level rise. The prototype presented here does not resolve management decisions; rather, it provides a framework for decision making at the Maine Coastal Islands National Wildlife Refuge Complex that can be updated for implementation as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuge complex.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211123","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Neckles, H.A., Lyons, J.E., Nagel, J.L., Adamowicz, S.C., Mikula, T., and Williams, S., 2022, Optimization of salt marsh management at the Petit Manan National Wildlife Refuge of the Maine Coastal Islands National Wildlife Refuge Complex, Maine, through use of structured decision making: U.S. Geological Survey Open-File Report 2021–1123, 27 p., https://doi.org/10.3133/ofr20211123.","productDescription":"Report: vi, 27 p.; Database","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-135555","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":501535,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112158.htm","linkFileType":{"id":5,"text":"html"}},{"id":394950,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://ecos.fws.gov/ServCat/Reference/Profile/121918","text":"U.S. Fish and Wildlife Service database","linkHelpText":"- Salt marsh integrity and Hurricane Sandy vegetation, bird and nekton data"},{"id":394949,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1123/images/"},{"id":394948,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1123/ofr20211123.XML"},{"id":394947,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1123/ofr20211123.pdf","text":"Report","size":"3.08 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1123"},{"id":394946,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1123/coverthb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Petit Manan National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.0438232421875,\n 44.36902359940364\n ],\n [\n -67.64556884765625,\n 44.36902359940364\n ],\n [\n -67.64556884765625,\n 44.570415145955515\n ],\n [\n -68.0438232421875,\n 44.570415145955515\n ],\n [\n -68.0438232421875,\n 44.36902359940364\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
As part of a long-term cooperative program to monitor water quality within the Scituate Reservoir drainage area, the U.S. Geological Survey in cooperation with the Providence Water Supply Board collected streamflow and water-quality data at the Scituate Reservoir and tributaries. Streamflow and concentrations of chloride and sodium estimated from records of specific conductance were used to calculate loads of chloride and sodium during water year 2019 (October 1, 2018, through September 30, 2019) for tributaries to the Scituate Reservoir, Rhode Island. Streamflow was measured or estimated by the U.S. Geological Survey following standard methods at 23 streamgages; 14 of these streamgages are equipped with instrumentation capable of continuously monitoring water level, specific conductance, and water temperature. Water-quality samples were collected by the Providence Water Supply Board at 37 sampling stations, which also include the 14 continuous-record streamgages maintained by the U.S. Geological Survey, during water year 2019 as part of a long-term sampling program; all stations are in the Scituate Reservoir drainage area. Water-quality data collected by the Providence Water Supply Board are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for water year 2019.
The largest tributary to the reservoir, the Ponaganset River, which was monitored by the U.S. Geological Survey, contributed a mean streamflow of 40 cubic feet per second to the reservoir during water year 2019. For the same period, annual mean streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.55 to about 26 cubic feet per second. Together, tributaries equipped with instrumentation capable of continuously monitoring specific conductance transported about 3,500 metric tons of chloride and 2,100 metric tons of sodium to the Scituate Reservoir during water year 2019; annual chloride yields for the tributaries ranged from 20 to 180 metric tons per square mile, and annual sodium yields ranged from 14 to 100 metric tons per square mile.
At the stations where water-quality samples were collected by the Providence Water Supply Board, the medians of the median concentrations were 25.1 milligrams per liter for chloride, 0.001 milligram per liter as nitrogen for nitrite, 0.08 milligram per liter as nitrogen for nitrate, 0.03 milligram per liter as phosphate for orthophosphate, 1,000 colony forming units per 100 milliliters for total coliform bacteria, and 10 colony forming units per 100 milliliters for Escherichia coli (E. coli). The medians of the median daily loads of chloride, nitrite, nitrate, orthophosphate, total coliform, and E. coli bacteria were 340 kilograms per day, 18 grams per day, 1,000 grams per day, 410 grams per day, 81,000 million colony forming units per day, and less than 1,800 million colony forming units per day, respectively. The medians of the median yields of chloride, nitrite, nitrate, orthophosphate, total coliform, and E. coli bacteria were 140 kilograms per day per square mile, 6.8 grams per day per square mile, 440 grams per day per square mile, 140 grams per day per square mile, 32,000 million colony forming units per day per square mile, and 660 million colony forming units per day per square mile, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1145","collaboration":"Prepared in cooperation with the Providence Water Supply Board","usgsCitation":"Smith, K.P., 2022, Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2019: U.S. Geological Survey Data Report 1145, 35 p., https://doi.org/10.3133/dr1145.","productDescription":"Report: v, 35 p.; Data release; Dataset","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-125608","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":394951,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1145/coverthb.jpg"},{"id":501201,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112157.htm","linkFileType":{"id":5,"text":"html"}},{"id":394956,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":394955,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WK8N0F","text":"USGS data release","linkHelpText":"Water quality data from the Providence Water Supply Board for tributary streams to the Scituate Reservoir, water year 2018–19"},{"id":394954,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1145/dr1145.XML"},{"id":394953,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1145/images/"},{"id":394952,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1145/dr1145.pdf","text":"Report","size":"1.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1145"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir Drainage Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.78192138671875,\n 41.71187978193456\n ],\n [\n -71.50177001953125,\n 41.71187978193456\n ],\n [\n -71.50177001953125,\n 41.947234477977766\n ],\n [\n -71.78192138671875,\n 41.947234477977766\n ],\n [\n -71.78192138671875,\n 41.71187978193456\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
The interagency Civil Applications Committee (CAC) facilitates the appropriate civil uses of overhead remote sensing technologies and data collected by military and intelligence capabilities, including from commercial sources. The CAC is operated and staffed by the U.S. Geological Survey on behalf of the U.S. Department of the Interior and its interagency partners. The director of the U.S. Geological Survey is the chair of the committee, and the vice-chair is a non-Department of the Interior senior official. The CAC ensures certain Federal civil agencies have access to these remotely sensed assets to meet their statutory missions in ways that do not threaten the civil rights, civil liberties, and personal privacy of U.S. citizens. To meet its mandate, the CAC hosts various working groups and communities of interest including those focused on thermal issues (wildland fires and volcanoes), environmental security, and historical satellite imagery.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223002","usgsCitation":"Opstal, D.W., and Rogers, R.T., 2022, Civil Applications Committee (ver. 1.4, January 2026): U.S. Geological Survey Fact Sheet 2022–3002, 2 p., https://doi.org/10.3133/fs20223002.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-126482","costCenters":[{"id":36171,"text":"National Civil Applications Center","active":true,"usgs":true}],"links":[{"id":394944,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3002/coverthb5.jpg"},{"id":394945,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3002/fs20223002.pdf","text":"Report","size":"1.37 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3002"},{"id":395432,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2022/3002/versionHist.txt","size":"1.43 KB","linkFileType":{"id":2,"text":"txt"}}],"edition":"Version 1.0: January 27, 2022; Version 1.1: February 4, 2022; Version 1.2: March 7, 2023; Version 1.3: March 4, 2025; Version 1.4: January 14, 2026","contact":"CAC Secretariat
National Land Imaging Program
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 562
Reston, VA 20192