{"pageNumber":"161","pageRowStart":"4000","pageSize":"25","recordCount":41062,"records":[{"id":70238160,"text":"70238160 - 2022 - GCPs free photogrammetry for estimating tree height and crown diameter in Arizona cypress plantation using UAV-Mounted GNSS RTK","interactions":[],"lastModifiedDate":"2022-11-15T12:55:04.571611","indexId":"70238160","displayToPublicDate":"2022-11-12T06:53:06","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1689,"text":"Forests","active":true,"publicationSubtype":{"id":10}},"title":"GCPs free photogrammetry for estimating tree height and crown diameter in Arizona cypress plantation using UAV-Mounted GNSS RTK","docAbstract":"
One of the main challenges of using unmanned aerial vehicles (UAVs) in forest data acquisition is the implementation of Ground Control Points (GCPs) as a mandatory step, which is sometimes impossible for inaccessible areas or within canopy closures. This study aimed to test the accuracy of a UAV-mounted GNSS RTK (real-time kinematic) system for calculating tree height and crown height without any GCPs. The study was conducted on a Cupressus arizonica (Greene., Arizona cypress) plantation on the Razi University Campus in Kermanshah, Iran. Arizona cypress is commonly planted as an ornamental tree. As it can tolerate harsh conditions, this species is highly appropriate for afforestation and reforestation projects. A total of 107 trees were subjected to field-measured dendrometric measurements (height and crown diameter). UAV data acquisition was performed at three altitudes of 25, 50, and 100 m using a local network RTK system (NRTK). The crown height model (CHM), derived from a digital surface model (DSM), was used to estimate tree height, and an inverse watershed segmentation (IWS) algorithm was used to estimate crown diameter. The results indicated that the means of tree height obtained from field measurements and UAV estimation were not significantly different, except for the mean values calculated at 100 m flight altitude. Additionally, the means of crown diameter reported from field measurements and UAV estimation at all flight altitudes were not statistically different. Root mean square error (RMSE < 11%) indicated a reliable estimation at all the flight altitudes for trees height and crown diameter. According to the findings of this study, it was concluded that UAV-RTK imagery can be considered a promising solution, but more work is needed before concluding its effectiveness in inaccessible areas. 
","language":"English","publisher":"MDPI","doi":"10.3390/f13111905","usgsCitation":"Pourreza, M., Moradi, F., Khosravi, M., Deljouei, A., and Vanderhoof, M.K., 2022, GCPs free photogrammetry for estimating tree height and crown diameter in Arizona cypress plantation using UAV-Mounted GNSS RTK: Forests, v. 13, no. 11, 1905, 14 p., https://doi.org/10.3390/f13111905.","productDescription":"1905, 14 p.","ipdsId":"IP-143513","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":445892,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/f13111905","text":"Publisher Index Page"},{"id":409350,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Iran","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[53.9216,37.19892],[54.8003,37.39242],[55.51158,37.96412],[56.18037,37.93513],[56.61937,38.12139],[57.33043,38.02923],[58.43615,37.52231],[59.23476,37.41299],[60.37764,36.52738],[61.12307,36.4916],[61.21082,35.65007],[60.80319,34.4041],[60.52843,33.67645],[60.9637,33.52883],[60.53608,32.98127],[60.86365,32.18292],[60.94194,31.54807],[61.69931,31.37951],[61.78122,30.73585],[60.87425,29.82924],[61.36931,29.30328],[61.77187,28.69933],[62.72783,28.25964],[62.75543,27.37892],[63.2339,27.21705],[63.31663,26.75653],[61.87419,26.23997],[61.49736,25.07824],[59.61613,25.38016],[58.52576,25.60996],[57.39725,25.7399],[56.97077,26.96611],[56.49214,27.1433],[55.72371,26.96463],[54.71509,26.48066],[53.4931,26.81237],[52.4836,27.58085],[51.52076,27.86569],[50.85295,28.81452],[50.11501,30.14777],[49.57685,29.98572],[48.94133,30.31709],[48.56797,29.92678],[48.01457,30.45246],[48.0047,30.98514],[47.68529,30.98485],[47.8492,31.70918],[47.33466,32.46916],[46.10936,33.01729],[45.41669,33.9678],[45.64846,34.74814],[46.15179,35.09326],[46.07634,35.67738],[45.42062,35.97755],[44.77267,37.17045],[44.22576,37.97158],[44.4214,38.28128],[44.10923,39.42814],[44.79399,39.713],[44.95269,39.33576],[45.45772,38.87414],[46.14362,38.7412],[46.50572,38.77061],[47.68508,39.50836],[48.0601,39.58224],[48.35553,39.28876],[48.01074,38.79401],[48.63438,38.27038],[48.88325,38.32025],[49.19961,37.58287],[50.14777,37.37457],[50.84235,36.87281],[52.26402,36.70042],[53.82579,36.96503],[53.9216,37.19892]]]},\"properties\":{\"name\":\"Iran\"}}]}","volume":"13","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-11-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Pourreza, Morteza","contributorId":299071,"corporation":false,"usgs":false,"family":"Pourreza","given":"Morteza","email":"","affiliations":[{"id":64754,"text":"Department of Natural Resources, Razi University","active":true,"usgs":false}],"preferred":false,"id":857016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moradi, Fardin","contributorId":299072,"corporation":false,"usgs":false,"family":"Moradi","given":"Fardin","email":"","affiliations":[{"id":64756,"text":"Department of Forestry and Forest Economics, University of Tehran","active":true,"usgs":false}],"preferred":false,"id":857017,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Khosravi, Mohammad","contributorId":299073,"corporation":false,"usgs":false,"family":"Khosravi","given":"Mohammad","email":"","affiliations":[{"id":64754,"text":"Department of Natural Resources, Razi University","active":true,"usgs":false}],"preferred":false,"id":857018,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Deljouei, Azade","contributorId":299074,"corporation":false,"usgs":false,"family":"Deljouei","given":"Azade","email":"","affiliations":[{"id":64758,"text":"School of Forest, Fisheries and Geomatics Sciences, University of Florida","active":true,"usgs":false}],"preferred":false,"id":857019,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":857020,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70254883,"text":"70254883 - 2022 - Individual characteristics and abiotic factors influence out-migration dynamics of juvenile bull trout","interactions":[],"lastModifiedDate":"2024-06-11T00:11:39.995771","indexId":"70254883","displayToPublicDate":"2022-11-11T19:07:31","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6476,"text":"Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Individual characteristics and abiotic factors influence out-migration dynamics of juvenile bull trout","docAbstract":"
Fragmentation of rivers through anthropogenic modifications poses an imminent threat to the persistence of migratory fish, necessitating direct actions such as trap-and-haul programs to restore and conserve the migratory life-history component in populations of partially migratory species such as bull trout Salvelinus confluentus. We used a PIT-tag system to assess how biological and abiotic factors influence the out-migration dynamics of juvenile bull trout in Graves Creek, Montana, USA. The largest fish within a cohort were more likely to out-migrate at age 1 when compared to smaller fish within the cohort, and this was particularly evident in a high-density year-class (2018), where large bull trout out-migrated an average of 115 days earlier than bull trout in the medium size category, and 181 days earlier than bull trout in the small size category. Relative changes in abiotic factors, including discharge, water temperature, and photoperiod, appeared to act as cues to out-migration, with the direction of change varying by season. These results highlight the complex interplay between individual characteristics, population dynamics, and environmental conditions, which influence out-migration dynamics and can be used to inform management actions to conserve the migratory component in bull trout populations.

","language":"English","publisher":"MDPI","doi":"10.3390/fishes7060331","usgsCitation":"Lewis, M., Guy, C.S., Oldenburg, E.W., and McMahon, T., 2022, Individual characteristics and abiotic factors influence out-migration dynamics of juvenile bull trout: Fishes, v. 7, no. 6, 331, 16 p., https://doi.org/10.3390/fishes7060331.","productDescription":"331, 16 p.","ipdsId":"IP-145336","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":445894,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fishes7060331","text":"Publisher Index Page"},{"id":429801,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.72605569932105,\n 48.89584190331334\n ],\n [\n -116.72605569932105,\n 47.69725377691367\n ],\n [\n -113.92454202744604,\n 47.69725377691367\n ],\n [\n -113.92454202744604,\n 48.89584190331334\n ],\n [\n -116.72605569932105,\n 48.89584190331334\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"7","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-11-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Lewis, Madeline C.","contributorId":337894,"corporation":false,"usgs":false,"family":"Lewis","given":"Madeline C.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":902767,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":902768,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oldenburg, Eric W.","contributorId":337895,"corporation":false,"usgs":false,"family":"Oldenburg","given":"Eric","email":"","middleInitial":"W.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":902769,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McMahon, Thomas E.","contributorId":337896,"corporation":false,"usgs":false,"family":"McMahon","given":"Thomas E.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":902770,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70238122,"text":"70238122 - 2022 - Geochemical evidence for diachronous uplift and synchronous collapse of the high elevation Variscan hinterland","interactions":[],"lastModifiedDate":"2022-11-11T17:18:02.425627","indexId":"70238122","displayToPublicDate":"2022-11-11T11:01:18","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Geochemical evidence for diachronous uplift and synchronous collapse of the high elevation Variscan hinterland","docAbstract":"Competing end-member models for the late Paleozoic Variscan orogeny (ca. 360-290 Ma) alternatively suggest moderate 2-3 km elevations underlain by relatively thin crust (<50 km) or a thick crust (>55 km) that supported high 4-5 km elevations. We tested these models and quantified the crustal thickness and elevation evolution of the Variscan orogeny using igneous trace element geochemical proxies. The data suggest that thick crust (55-70 km) capable of supporting 3-5 km elevations developed diachronously from east to west between ca. 350 and 315 Ma. Crustal thinning occurred from ca. 315 Ma to 290 Ma across the orogen. Crustal thickness and elevation changes at ca. 340-325 Ma and 315-290 Ma correspond with increases in silicate weathering recorded by Sr and Li isotopes, consistent with models in which silicate weathering of the Variscan orogen contributed to global cooling associated with the late Paleozoic ice age.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022GL100435","usgsCitation":"Hillenbrand, I.W., and Williams, M.L., 2022, Geochemical evidence for diachronous uplift and synchronous collapse of the high elevation Variscan hinterland: Geophysical Research Letters, v. 49, no. 21, e2022GL100435, 10 p., https://doi.org/10.1029/2022GL100435.","productDescription":"e2022GL100435, 10 p.","ipdsId":"IP-142878","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":445899,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022gl100435","text":"Publisher Index Page"},{"id":409308,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Austria, Czech Republic, France, Germany, Portugal, Spain","otherGeospatial":"Black Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 14.553025242812566,\n 47.48404935806914\n ],\n [\n 16.0447443516276,\n 47.53336442518062\n ],\n [\n 17.079710695596162,\n 49.067532746271894\n ],\n [\n 14.892231965755002,\n 50.64321669700277\n ],\n [\n 10.140926401587848,\n 49.534630905755165\n ],\n [\n 12.89558834365286,\n 47.44197821901719\n ],\n [\n 14.553025242812566,\n 47.48404935806914\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 5.32794713350242,\n 49.24401989595435\n ],\n [\n 5.32794713350242,\n 47.64800803517562\n ],\n [\n 9.829522695087775,\n 47.64800803517562\n ],\n [\n 9.829522695087775,\n 49.24401989595435\n ],\n [\n 5.32794713350242,\n 49.24401989595435\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -3.177718486646853,\n 47.72567765905953\n ],\n [\n -1.2218185591223403,\n 46.21766447237533\n ],\n [\n -1.138786880839774,\n 44.28084125810739\n ],\n [\n 5.652571497586308,\n 43.08164755343117\n ],\n [\n 7.079442136310121,\n 47.293859826547305\n ],\n [\n -0.1333251343038171,\n 48.429766001622255\n ],\n [\n -3.177718486646853,\n 47.72567765905953\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -9.53849141829599,\n 43.73937056547598\n ],\n [\n -9.53849141829599,\n 40.493540772855994\n ],\n [\n -5.954925241206126,\n 40.493540772855994\n ],\n [\n -5.954925241206126,\n 43.73937056547598\n ],\n [\n -9.53849141829599,\n 43.73937056547598\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"49","issue":"21","noUsgsAuthors":false,"publicationDate":"2022-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Hillenbrand, Ian William 0000-0003-2801-3674","orcid":"https://orcid.org/0000-0003-2801-3674","contributorId":299032,"corporation":false,"usgs":true,"family":"Hillenbrand","given":"Ian","email":"","middleInitial":"William","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":856924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Michael L.","contributorId":215495,"corporation":false,"usgs":false,"family":"Williams","given":"Michael","email":"","middleInitial":"L.","affiliations":[{"id":37201,"text":"UMass Amherst","active":true,"usgs":false}],"preferred":false,"id":856925,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238157,"text":"70238157 - 2022 - Brown bear–sea otter interactions along the Katmai coast: Terrestrial and nearshore communities linked by predation","interactions":[],"lastModifiedDate":"2022-11-15T12:46:03.932912","indexId":"70238157","displayToPublicDate":"2022-11-11T06:42:50","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2373,"text":"Journal of Mammalogy","onlineIssn":"1545-1542","printIssn":"0022-2372","active":true,"publicationSubtype":{"id":10}},"title":"Brown bear–sea otter interactions along the Katmai coast: Terrestrial and nearshore communities linked by predation","docAbstract":"

Sea otters were extirpated throughout much of their range by the maritime fur trade in the 18th and 19th centuries, including the coast of Katmai National Park and Preserve in southcentral Alaska. Brown bears are an important component of the Katmai ecosystem where they are the focus of a thriving ecotourism bear-viewing industry as they forage in sedge meadows and dig clams in the extensive tidal flats that exist there. Sea otters began reoccupying Katmai in the 1970s where their use of intertidal clam resources overlapped that of brown bears. By 2008, the Katmai sea otter population had grown to an estimated 7,000 animals and was likely near carrying capacity; however, in 2006–2015, the age-at-death distribution (AADD) of sea otter carcasses collected at Katmai included a higher-than-expected proportion of prime-age animals compared to most other sea otter populations in Alaska. The unusual AADD warranted scientific investigation, particularly because the Katmai population is part of the Threatened southwest sea otter stock. Brown bears in Katmai are known to prey on marine mammals and sea otters, but depredation rates are unknown; thus, we investigated carnivore predation, especially by brown bears, as a potential explanation for abnormally high prime-age otter mortality. We installed camera traps at two island-based marine mammal haulout sites within Katmai to gather direct evidence that brown bears prey on seals and sea otters. Over a period of two summers, we gathered photo evidence of brown bears making 22 attempts to prey on sea otters of which nine (41%) were successful and 12 attempts to prey on harbor seals of which one (8%) was successful. We also developed a population model based on the AADD to determine if the living population is declining, as suggested by the high proportion of prime-age animals in the AADD. We found that the population trend predicted by the modeled AADDs was contradictory to aerial population surveys that indicated the population was not in steep decline but was consistent with otter predation. Future work should focus on the direct and indirect effects these top-level predators have on each other and the coastal community that connects them.

","language":"English","publisher":"Oxford Academic","doi":"10.1093/jmammal/gyac095","usgsCitation":"Monson, D., Taylor, R.L., Hilderbrand, G., Erlenbach, J., Coletti, H., and Bodkin, J.L., 2022, Brown bear–sea otter interactions along the Katmai coast: Terrestrial and nearshore communities linked by predation: Journal of Mammalogy, gyac095, 13 p., https://doi.org/10.1093/jmammal/gyac095.","productDescription":"gyac095, 13 p.","ipdsId":"IP-109601","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":445905,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyac095","text":"Publisher Index Page"},{"id":409348,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Katmai National Park and Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -156.9563357076709,\n 59.34074602972433\n ],\n [\n -156.9563357076709,\n 57.706193986474744\n ],\n [\n -153.1440798482959,\n 57.706193986474744\n ],\n [\n -153.1440798482959,\n 59.34074602972433\n ],\n [\n -156.9563357076709,\n 59.34074602972433\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2022-11-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Monson, Daniel 0000-0002-4593-5673 dmonson@usgs.gov","orcid":"https://orcid.org/0000-0002-4593-5673","contributorId":196670,"corporation":false,"usgs":true,"family":"Monson","given":"Daniel","email":"dmonson@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":857010,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Rebecca L. 0000-0001-8459-7614 rebeccataylor@usgs.gov","orcid":"https://orcid.org/0000-0001-8459-7614","contributorId":5112,"corporation":false,"usgs":true,"family":"Taylor","given":"Rebecca","email":"rebeccataylor@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":857011,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hilderbrand, Grant 0000-0002-0051-8315 ghilderbrand@usgs.gov","orcid":"https://orcid.org/0000-0002-0051-8315","contributorId":297939,"corporation":false,"usgs":false,"family":"Hilderbrand","given":"Grant","email":"ghilderbrand@usgs.gov","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":857012,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erlenbach, Joy","contributorId":200750,"corporation":false,"usgs":false,"family":"Erlenbach","given":"Joy","affiliations":[],"preferred":false,"id":857013,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Coletti, Heather","contributorId":258849,"corporation":false,"usgs":false,"family":"Coletti","given":"Heather","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":857014,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bodkin, James L. 0000-0003-1641-4438 jbodkin@usgs.gov","orcid":"https://orcid.org/0000-0003-1641-4438","contributorId":748,"corporation":false,"usgs":true,"family":"Bodkin","given":"James","email":"jbodkin@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":857015,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70256723,"text":"70256723 - 2022 - Reproductive success of Red-Billed Tropicbirds (Phaethon aethereus) on St. Eustatius, Caribbean Netherlands","interactions":[],"lastModifiedDate":"2024-08-15T11:12:13.575616","indexId":"70256723","displayToPublicDate":"2022-11-11T06:09:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"title":"Reproductive success of Red-Billed Tropicbirds (Phaethon aethereus) on St. Eustatius, Caribbean Netherlands","docAbstract":"

The daily nest-survival rates of Red-billed Tropicbirds (Phaethon aethereus) were estimated over six breeding seasons on St. Eustatius in the Caribbean. We analyzed 338 nesting attempts between 2013 and 2020. The daily survival rate (DSR) of tropicbird nests was modeled as a function of nest initiation date, sea surface temperature (SST), elevation, vegetation in front of the nest, and year. Yearly nest survival rates (± SE) of the best fitting models ranged from 0.21 ± 0.06–0.74 ± 0.13 (n = 338 nests). DSR of the most parsimonious models averaged 0.39 ± 0.04 during the incubation period, 0.83 ± 0.05 during the chick-rearing period, and 0.30 ± 0.04 during the nesting period (incubation through fledging) when data were pooled across all years. Models with linear and quadratic trends of nest initiation date combined with SST and elevation received strong support in the incubation and nesting periods. Nests initiated in peak nesting season, when SSTs were lower, had higher DSR estimates than nests initiated early or late in the season. Compared to studies of the same species from Saba and the Gulf of California, survival probability on St. Eustatius was lower during the incubation stage but higher during the chick-rearing period. Similar to populations in the Gulf of California, tropicbird reproduction differed and laying date varied among years, and survival was influenced by SST. Our results are consistent with a study on White-tailed Tropicbirds (Phaethon lepturus) in Bermuda which found that survival was affected by temporal factors rather than physical site characteristics. Our study contributes to a better understanding of the factors that influence Red-billed Tropicbird survival on a small Caribbean island.

","language":"English","publisher":"BioONe","doi":"10.1675/063.045.0106","usgsCitation":"Madden, H., Leopold, M., Rivera-Milán, F., Verdel, K., Eggermont, E., and Jodice, P.G., 2022, Reproductive success of Red-Billed Tropicbirds (Phaethon aethereus) on St. Eustatius, Caribbean Netherlands: Waterbirds, v. 45, no. 1, p. 39-50, https://doi.org/10.1675/063.045.0106.","productDescription":"12 p.","startPage":"39","endPage":"50","ipdsId":"IP-124153","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":497353,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://research.wur.nl/en/publications/reproductive-success-of-red-billed-tropicbirds-phaethon-aethereus","text":"External Repository"},{"id":432684,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"St. Eustatius","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -63.05720028548774,\n 17.552131774383994\n ],\n [\n -63.05720028548774,\n 17.443422797991275\n ],\n [\n -62.9081982102923,\n 17.443422797991275\n ],\n [\n -62.9081982102923,\n 17.552131774383994\n ],\n [\n -63.05720028548774,\n 17.552131774383994\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"45","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Madden, H.","contributorId":288694,"corporation":false,"usgs":false,"family":"Madden","given":"H.","email":"","affiliations":[{"id":61828,"text":"Caribbean Netherlands Science Institute","active":true,"usgs":false}],"preferred":false,"id":908781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leopold, M.","contributorId":341697,"corporation":false,"usgs":false,"family":"Leopold","given":"M.","email":"","affiliations":[{"id":37803,"text":"Wageningen University","active":true,"usgs":false}],"preferred":false,"id":908782,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rivera-Milán, F.","contributorId":341699,"corporation":false,"usgs":false,"family":"Rivera-Milán","given":"F.","affiliations":[{"id":40296,"text":"United States Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":908783,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Verdel, K.","contributorId":341701,"corporation":false,"usgs":false,"family":"Verdel","given":"K.","email":"","affiliations":[{"id":79370,"text":"University of Utrecht","active":true,"usgs":false}],"preferred":false,"id":908784,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eggermont, E.","contributorId":341703,"corporation":false,"usgs":false,"family":"Eggermont","given":"E.","email":"","affiliations":[{"id":79370,"text":"University of Utrecht","active":true,"usgs":false}],"preferred":false,"id":908785,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":219852,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908786,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70256616,"text":"70256616 - 2022 - Use of a riverscape-scale model of fundamental physical habitat requirements for freshwater mussels to quantify mussel declines in a mining-contaminated stream: The Big River, Old Lead Belt, Southeast Missouri","interactions":[],"lastModifiedDate":"2024-09-09T16:02:05.252845","indexId":"70256616","displayToPublicDate":"2022-11-10T10:55:28","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"FWS/CSS-147-2022","title":"Use of a riverscape-scale model of fundamental physical habitat requirements for freshwater mussels to quantify mussel declines in a mining-contaminated stream: The Big River, Old Lead Belt, Southeast Missouri","docAbstract":"

The research described in this report was conducted as part of the Natural Resource Damage Assessment and Restoration process in the Big River. Our purpose was to compare habitat features and landscape factors that may be important for the establishment and persistence of mussel concentrations between the Big River and the adjacent Bourbeuse and Meramec rivers, thereby testing their appropriateness as reference systems for establishing baseline expectations of mussel populations in the absence of mining impacts for the Big River. Based on these comparisons and a published model dileneating suitable habitat for freshwater mussels, we establish expected baseline conditions related to suitable freshwater mussel habitat in the Big River to assist injury determination for mining-related impacts in the Southeast Missouri Lead Mining District Natural Resource Damage Assessment case.

","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Rosenberger, A.E., and Lindner, G.A., 2022, Use of a riverscape-scale model of fundamental physical habitat requirements for freshwater mussels to quantify mussel declines in a mining-contaminated stream: The Big River, Old Lead Belt, Southeast Missouri: Cooperator Science Series FWS/CSS-147-2022, ii, 32 p.","productDescription":"ii, 32 p.","ipdsId":"IP-132994","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":431949,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fws.gov/media/use-riverscape-scale-model-fundamental-physical-habitat-requirements-freshwater-mussels"},{"id":433629,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Big River watershed, Bourbeuse River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.34550598548627,\n 38.669645646671654\n ],\n [\n -91.90534506180033,\n 38.65386249841083\n ],\n [\n -91.86155171390972,\n 37.44368900102869\n ],\n [\n -90.22760081808802,\n 37.470421694633586\n ],\n [\n -90.34550598548627,\n 38.669645646671654\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rosenberger, Amanda E. 0000-0002-5520-8349 arosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5520-8349","contributorId":5581,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Amanda","email":"arosenberger@usgs.gov","middleInitial":"E.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908322,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lindner, Garth A.","contributorId":201828,"corporation":false,"usgs":false,"family":"Lindner","given":"Garth","email":"","middleInitial":"A.","affiliations":[{"id":36266,"text":"University of Missouri Cooperative Research Unit","active":true,"usgs":false}],"preferred":false,"id":908323,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238513,"text":"70238513 - 2022 - Framework for assessing and mitigating the impacts of offshore wind energy development on marine birds","interactions":[],"lastModifiedDate":"2022-11-28T14:05:54.906225","indexId":"70238513","displayToPublicDate":"2022-11-10T07:56:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Framework for assessing and mitigating the impacts of offshore wind energy development on marine birds","docAbstract":"

Offshore wind energy development (OWED) is rapidly expanding globally and has the potential to contribute significantly to renewable energy portfolios. However, development of infrastructure in the marine environment presents risks to wildlife. Marine birds in particular have life history traits that amplify population impacts from displacement and collision with offshore wind infrastructure. Here, we present a broadly applicable framework to assess and mitigate the impacts of OWED on marine birds. We outline existing techniques to quantify impact via monitoring and modeling (e.g., collision risk models, population viability analysis), and present a robust mitigation framework to avoid, minimize, or compensate for OWED impacts. Our framework addresses impacts within the context of multiple stressors across multiple wind energy developments. We also present technological and methodological approaches that can improve impact estimation and mitigation. We highlight compensatory mitigation as a tool that can be incorporated into regulatory frameworks to mitigate impacts that cannot be avoided or minimized via siting decisions or alterations to OWED infrastructure or operation. Our framework is intended as a globally-relevant approach for assessing and mitigating OWED impacts on marine birds that may be adapted to existing regulatory frameworks in regions with existing or planned OWED.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2022.109795","usgsCitation":"Croll, D.A., Ellis, A.A., Adams, J., Cook, A.S., Garthe, S., Wing Goodale, M., Hall, C.S., Hazen, E.L., Keitt, B.S., Kelsey, E.C., Leirness, J.B., Lyons, D.E., McKown, M., Potiek, A., Searle, K.R., Soudjin, F.H., Rockwood, R.C., Tershy, B.R., Tinker, M., Vanderwerf, E.A., Williams, K.A., Young, L.C., and Zilliacus, K., 2022, Framework for assessing and mitigating the impacts of offshore wind energy development on marine birds: Biological Conservation, v. 276, 109795, 15 p., https://doi.org/10.1016/j.biocon.2022.109795.","productDescription":"109795, 15 p.","ipdsId":"IP-142666","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":445913,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2022.109795","text":"Publisher Index Page"},{"id":409690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"276","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Croll, Donald A","contributorId":299391,"corporation":false,"usgs":false,"family":"Croll","given":"Donald","email":"","middleInitial":"A","affiliations":[{"id":64830,"text":"UC Santa Cruz, Ocean Health Building, 115 McAllister Way, Santa Cruz, CA 95060, United States","active":true,"usgs":false}],"preferred":false,"id":857691,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellis, Aspen A","contributorId":299392,"corporation":false,"usgs":false,"family":"Ellis","given":"Aspen","email":"","middleInitial":"A","affiliations":[{"id":64830,"text":"UC Santa Cruz, Ocean Health Building, 115 McAllister Way, Santa Cruz, CA 95060, United States","active":true,"usgs":false}],"preferred":false,"id":857692,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Josh 0000-0003-3056-925X","orcid":"https://orcid.org/0000-0003-3056-925X","contributorId":213442,"corporation":false,"usgs":true,"family":"Adams","given":"Josh","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857693,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cook, Aonghais S. C. P.","contributorId":299393,"corporation":false,"usgs":false,"family":"Cook","given":"Aonghais","email":"","middleInitial":"S. C. P.","affiliations":[{"id":64832,"text":"British Trust for Ornithology, The Nunnery, Thetford, Norfolk IP26 4BG, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":857694,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garthe, Stefan","contributorId":243464,"corporation":false,"usgs":false,"family":"Garthe","given":"Stefan","affiliations":[],"preferred":false,"id":857695,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wing Goodale, Morgan","contributorId":299394,"corporation":false,"usgs":false,"family":"Wing Goodale","given":"Morgan","email":"","affiliations":[{"id":64834,"text":"Biodiversity Research Institute, 276 Canco Road, Portland, ME 04103, United States","active":true,"usgs":false}],"preferred":false,"id":857696,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hall, C. Scott","contributorId":299395,"corporation":false,"usgs":false,"family":"Hall","given":"C.","email":"","middleInitial":"Scott","affiliations":[{"id":64835,"text":"National Fish and Wildlife Foundation, 1133 15thSt. N.W., Suite 1000, Washington, DC 20005, United States","active":true,"usgs":false}],"preferred":false,"id":857697,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hazen, Elliott L.","contributorId":217590,"corporation":false,"usgs":false,"family":"Hazen","given":"Elliott","email":"","middleInitial":"L.","affiliations":[{"id":39677,"text":"National Marine Fisheries Service, National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":857698,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Keitt, Bradford S.","contributorId":299396,"corporation":false,"usgs":false,"family":"Keitt","given":"Bradford","email":"","middleInitial":"S.","affiliations":[{"id":64836,"text":"American Bird Conservancy, Santa Cruz, CA, United States","active":true,"usgs":false}],"preferred":false,"id":857699,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kelsey, Emily C. 0000-0002-0107-3530 ekelsey@usgs.gov","orcid":"https://orcid.org/0000-0002-0107-3530","contributorId":206505,"corporation":false,"usgs":true,"family":"Kelsey","given":"Emily","email":"ekelsey@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857700,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Leirness, Jeffery B","contributorId":299397,"corporation":false,"usgs":false,"family":"Leirness","given":"Jeffery","email":"","middleInitial":"B","affiliations":[{"id":64837,"text":"CSS Inc., 2750 Prosperity Avenue, Suite 220, Fairfax, VA 22031, United States","active":true,"usgs":false}],"preferred":false,"id":857701,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lyons, Don E","contributorId":299398,"corporation":false,"usgs":false,"family":"Lyons","given":"Don","email":"","middleInitial":"E","affiliations":[{"id":64838,"text":"Audubon Seabird Institute, National Audubon Society, 12 Audubon Road, Bremen, ME 04551, United States","active":true,"usgs":false}],"preferred":false,"id":857702,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"McKown, Matthew W.","contributorId":298878,"corporation":false,"usgs":false,"family":"McKown","given":"Matthew W.","affiliations":[{"id":64717,"text":"Conservation Metrics, Inc., Santa Cruz, CA, USA","active":true,"usgs":false}],"preferred":false,"id":857703,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Potiek, Astrid","contributorId":299399,"corporation":false,"usgs":false,"family":"Potiek","given":"Astrid","email":"","affiliations":[{"id":64839,"text":"Waardenburg Ecology, Varkensmarkt 9, 4101 CK Culemborg, the Netherlands","active":true,"usgs":false}],"preferred":false,"id":857704,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Searle, Kate R","contributorId":299400,"corporation":false,"usgs":false,"family":"Searle","given":"Kate","email":"","middleInitial":"R","affiliations":[{"id":64840,"text":"UK Centre for Ecology & Hydrology, Bush Estate, Penicuik EH26 0QB, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":857705,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Soudjin, Floor H.","contributorId":299401,"corporation":false,"usgs":false,"family":"Soudjin","given":"Floor","email":"","middleInitial":"H.","affiliations":[{"id":64841,"text":"Ecological Dynamics Group, Wageningen Marine Research, 1976 CP Ijmuiden, the Netherlands","active":true,"usgs":false}],"preferred":false,"id":857706,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Rockwood, R. Cotton","contributorId":299402,"corporation":false,"usgs":false,"family":"Rockwood","given":"R.","email":"","middleInitial":"Cotton","affiliations":[{"id":64842,"text":"Point Blue Conservation Science, 3820 Cypress Drive, Suite 11, Petaluma, CA 94954, United States","active":true,"usgs":false}],"preferred":false,"id":857707,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Tershy, Bernie R.","contributorId":299403,"corporation":false,"usgs":false,"family":"Tershy","given":"Bernie","email":"","middleInitial":"R.","affiliations":[{"id":64830,"text":"UC Santa Cruz, Ocean Health Building, 115 McAllister Way, Santa Cruz, CA 95060, United States","active":true,"usgs":false}],"preferred":false,"id":857708,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Tinker, Martin","contributorId":299404,"corporation":false,"usgs":false,"family":"Tinker","given":"Martin","email":"","affiliations":[{"id":64843,"text":"Nhydra Ecological, Head of St Margarets Bay, Nova Scotia, Canada","active":true,"usgs":false}],"preferred":false,"id":857709,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Vanderwerf, Eric A.","contributorId":104689,"corporation":false,"usgs":false,"family":"Vanderwerf","given":"Eric","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":857710,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Williams, Kathryn A","contributorId":299405,"corporation":false,"usgs":false,"family":"Williams","given":"Kathryn","email":"","middleInitial":"A","affiliations":[{"id":64834,"text":"Biodiversity Research Institute, 276 Canco Road, Portland, ME 04103, United States","active":true,"usgs":false}],"preferred":false,"id":857711,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Young, Lindsay C.","contributorId":149044,"corporation":false,"usgs":false,"family":"Young","given":"Lindsay","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":857712,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Zilliacus, Kelly","contributorId":299406,"corporation":false,"usgs":false,"family":"Zilliacus","given":"Kelly","email":"","affiliations":[{"id":64830,"text":"UC Santa Cruz, Ocean Health Building, 115 McAllister Way, Santa Cruz, CA 95060, United States","active":true,"usgs":false}],"preferred":false,"id":857713,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}} ,{"id":70238049,"text":"sir20225102 - 2022 - Effect of uncertainty of discharge data on uncertainty of discharge simulation for the Lake Michigan Diversion, northeastern Illinois and northwestern Indiana","interactions":[],"lastModifiedDate":"2026-04-28T14:22:43.03477","indexId":"sir20225102","displayToPublicDate":"2022-11-10T07:15:06","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":"2022-5102","displayTitle":"Effect of Uncertainty of Discharge Data on Uncertainty of Discharge Simulation for the Lake Michigan Diversion, Northeastern Illinois and Northwestern Indiana","title":"Effect of uncertainty of discharge data on uncertainty of discharge simulation for the Lake Michigan Diversion, northeastern Illinois and northwestern Indiana","docAbstract":"

Simulation models of watershed hydrology (also referred to as “rainfall-runoff models”) are calibrated to the best available streamflow data, which are typically published discharge time series at the outlet of the watershed. Even after calibration, the model generally cannot replicate the published discharges because of simplifications of the physical system embedded in the model structure and uncertainties of the input data and of the estimated model parameters, which, although optimized for the given calibration data, remain uncertain. The input data errors are caused by uncertainties in the forcing data, such as precipitation and other climatological data, and in the published discharges used for calibration. In the numerical algorithms used for calibration, the published discharges are often assumed to be without error, but they are themselves uncertain, typically having been computed using ratings, which are models fitted to uncertain discharge measurements.

In this study, uncertainty of published daily discharge data and how the discharge uncertainty is transmitted to the parameter values of the Hydrological Simulation Program–FORTRAN (HSPF) rainfall-runoff model and to the simulated discharge at both calibration and prediction locations were investigated for the Lake Michigan diversion in northeastern Illinois and northwestern Indiana. The HSPF model used in this study is used by the U.S. Army Corps of Engineers as part of quantifying the diversion of water from Lake Michigan by the State of Illinois. In this study, the model is calibrated jointly at two watersheds in the study area; the resulting model is considered the base model in this study. Seven other gaged watersheds in the study area are used for testing predictive simulations. A Bayesian rating curve estimation (BaRatin) approach, the BaRatin stage-period-discharge (SPD) method, was used to estimate the uncertainty of the published discharge from the calibration watersheds. To characterize the effect of the discharge uncertainty on parameter values, the HSPF model parameters were recalibrated to 17 nonrandomly selected pairs of discharge series from the BaRatin SPD analysis. To provide an indicator of the effect of parameter uncertainty to compare to the effect of discharge uncertainty, 1,000 parameter sets also were randomly generated from the estimated parameter covariance matrix of the base model. The recalibrated and random parameter sets were then used in HSPF simulations of discharge at the two calibration watersheds and at the seven prediction watersheds. Selected discharge summary statistics—the period-of-study (POS, water years 1997 to 2015) mean discharge, selected flow-duration curve (FDC) quantiles, and water year mean discharges—are used to characterize the variability between simulated and published discharge.

A normalized variability index (VN) is used as a measure of the uncertainty of flow statistics arising from the uncertainty of the sources considered in this study. When this index is at least 1, the variability of the simulations is large enough to explain the median error between simulated and published values, although offsetting errors from other sources are also likely. When the index is appreciably less than 1, the variability of the simulations is clearly insufficient to explain the median error between simulated and published values. At the two calibration watersheds and for results of the two simulation sets considered together, the VN values ranged from 0.2 to 0.8 for POS mean discharge, from 0.3 to 0.6 in the median for a set of FDC quantiles, and from 0.1 to 0.2 in the median for water year mean discharges. These values indicate that substantial uncertainty remains unexplained. Even though two watersheds were used in calibration, that calibration was highly constrained because it was applied to the watersheds simultaneously and was subject to parameter regularization that constrained the adjustment of the parameters from their initial values. These constraints were applied to avoid overfitting to the calibration watersheds and thus to increase the likelihood that the resulting parameters would give accurate results at watersheds not used in the calibration, but they created a parameter transfer error in the calibration watershed results shown by the balancing of errors between the two watersheds. Additional remaining error sources include model structural error and meteorological forcing error to the degree that the calibration was unable to adjust the parameters to account for these errors. At the prediction watersheds, the corresponding VN values were almost always substantially lower than those values at the calibration watersheds. This result is expected because the prediction watersheds have additional uncertainty, including parameter transfer error.

The work described in this report provides preliminary estimates of a limited range of sources of error in predicted discharge uncertainty. Future work would be beneficial to obtain a better statistical characterization of the effect of the uncertainty of calibration discharge series and to address additional sources of uncertainty, such as from precipitation input data used in calibration and prediction and from structural (model) errors.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225102","collaboration":"Prepared in cooperation with U.S. Army Corps of Engineers, Chicago District","usgsCitation":"Soong, D.T., and Over, T.M., 2022, Effect of uncertainty of discharge data on uncertainty of discharge simulation for the Lake Michigan Diversion, northeastern Illinois and northwestern Indiana: U.S. Geological Survey Scientific Investigations Report 2022–5102, 54 p., https://doi.org/10.3133/sir20225102.","productDescription":"Report: ix, 54 p.; 2 Data Releases; Dataset","numberOfPages":"68","onlineOnly":"Y","ipdsId":"IP-120412","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":503564,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113826.htm","linkFileType":{"id":5,"text":"html"}},{"id":409202,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97S2IID","text":"USGS data release","linkHelpText":"National Land Cover Database (NLCD) 2011 Land Cover Conterminous United States"},{"id":409201,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UC21B0","text":"USGS data release","linkHelpText":"Models, inputs, and outputs for estimating the uncertainty of discharge simulations for the Lake Michigan Diversion using the Hydrological Simulation Program – FORTRAN model"},{"id":409200,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":409198,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5102/sir20225102.XML"},{"id":409196,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5102/coverthb.jpg"},{"id":409197,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5102/sir20225102.pdf","text":"Report","size":"8.21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5102"},{"id":409199,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5102/images"}],"country":"United States","state":"Illinois, Indiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.34881814497747,\n 42.492126793048925\n ],\n [\n -88.34881814497747,\n 41.20266079763215\n ],\n [\n -87.22772634687415,\n 41.20266079763215\n ],\n [\n -87.22772634687415,\n 42.492126793048925\n ],\n [\n -88.34881814497747,\n 42.492126793048925\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-11-10","noUsgsAuthors":false,"publicationDate":"2022-11-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Soong, David 0000-0003-0404-2163","orcid":"https://orcid.org/0000-0003-0404-2163","contributorId":206523,"corporation":false,"usgs":true,"family":"Soong","given":"David","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Over, Thomas M. 0000-0001-8280-4368 tmover@usgs.gov","orcid":"https://orcid.org/0000-0001-8280-4368","contributorId":1819,"corporation":false,"usgs":true,"family":"Over","given":"Thomas","email":"tmover@usgs.gov","middleInitial":"M.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856709,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70240115,"text":"70240115 - 2022 - The 2020 Westmorland, California earthquake swarm as aftershocks of a slow slip event sustained by fluid flow","interactions":[],"lastModifiedDate":"2023-01-27T13:14:40.120096","indexId":"70240115","displayToPublicDate":"2022-11-10T07:12:05","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"The 2020 Westmorland, California earthquake swarm as aftershocks of a slow slip event sustained by fluid flow","docAbstract":"

Swarms are bursts of earthquakes without an obvious mainshock. Some have been observed to be associated with transient aseismic fault slip, while others are thought to be related to fluids. However, the association is rarely quantitative due to insufficient data quality. We use high-quality GPS/GNSS, InSAR, and relocated seismicity to study a swarm of >2,000 earthquakes which occurred between 30 September and 6 October 2020, near Westmorland, California. Using 5 min sampled Global Positioning System (GPS) supplemented with InSAR, we document a spontaneous shallow Mw 5.2 slow slip event that preceded the swarm by 2–15 hr. The earthquakes in the early phase were predominantly non-interacting and driven primarily by the slow slip event resulting in a nonlinear expansion. A stress-driven model based on the rate-and-state friction successfully explains the overall spatial and temporal evolution of earthquakes, including the time lag between the onset of the slow slip event and the swarm. Later, a distinct back front and a square root of time expansion of clustered seismicity on en-echelon fault structures suggest that fluids helped sustain the swarm. Static stress triggering analysis using Coulomb stress and statistics of interevent times suggest that 45%–65% of seismicity was driven by the slow slip event, 10%–35% by inter-earthquake interactions, and 10%–30% by fluids. Our model also provides constraints on the friction parameter and the pore pressure and suggests that this swarm behaved like an aftershock sequence but with the mainshock replaced by the slow slip event.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JB024693","usgsCitation":"Sirorattanakul, K., Ross, Z., Khoshmanesh, M., Cochran, E.S., Acosta, M., and Avouac, J., 2022, The 2020 Westmorland, California earthquake swarm as aftershocks of a slow slip event sustained by fluid flow: Journal of Geophysical Research, v. 127, no. 11, e2022JB024693, 35 p., https://doi.org/10.1029/2022JB024693.","productDescription":"e2022JB024693, 35 p.","ipdsId":"IP-140529","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":445916,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022jb024693","text":"Publisher Index Page"},{"id":412402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.58133623631194,\n 32.749809599509504\n ],\n [\n -114.58133623631194,\n 33.67317085297434\n ],\n [\n -116.15171424960513,\n 33.67317085297434\n ],\n [\n -116.15171424960513,\n 32.749809599509504\n ],\n [\n -114.58133623631194,\n 32.749809599509504\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"127","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-11-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Sirorattanakul, K.","contributorId":301811,"corporation":false,"usgs":false,"family":"Sirorattanakul","given":"K.","email":"","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":862627,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ross, Z.E.","contributorId":301812,"corporation":false,"usgs":false,"family":"Ross","given":"Z.E.","email":"","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":862628,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Khoshmanesh, M.","contributorId":301813,"corporation":false,"usgs":false,"family":"Khoshmanesh","given":"M.","email":"","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":862629,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":862630,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Acosta, M.","contributorId":301814,"corporation":false,"usgs":false,"family":"Acosta","given":"M.","email":"","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":862631,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Avouac, J.-P.","contributorId":196004,"corporation":false,"usgs":false,"family":"Avouac","given":"J.-P.","email":"","affiliations":[],"preferred":false,"id":862632,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70238509,"text":"70238509 - 2022 - Ecological and socioeconomic factors associated with the human burden of environmentally mediated pathogens: A global analysis","interactions":[],"lastModifiedDate":"2022-11-28T13:12:50.258246","indexId":"70238509","displayToPublicDate":"2022-11-10T07:10:45","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":11451,"text":"The Lancet Planetary Health","active":true,"publicationSubtype":{"id":10}},"title":"Ecological and socioeconomic factors associated with the human burden of environmentally mediated pathogens: A global analysis","docAbstract":"

Background

Billions of people living in poverty are at risk of environmentally mediated infectious diseases—that is, pathogens with environmental reservoirs that affect disease persistence and control and where environmental control of pathogens can reduce human risk. The complex ecology of these diseases creates a global health problem not easily solved with medical treatment alone.

Methods

We quantified the current global disease burden caused by environmentally mediated infectious diseases and used a structural equation model to explore environmental and socioeconomic factors associated with the human burden of environmentally mediated pathogens across all countries.

Findings

We found that around 80% (455 of 560) of WHO-tracked pathogen species known to infect humans are environmentally mediated, causing about 40% (129 488 of 359 341 disability-adjusted life years) of contemporary infectious disease burden (global loss of 130 million years of healthy life annually). The majority of this environmentally mediated disease burden occurs in tropical countries, and the poorest countries carry the highest burdens across all latitudes. We found weak associations between disease burden and biodiversity or agricultural land use at the global scale. In contrast, the proportion of people with rural poor livelihoods in a country was a strong proximate indicator of environmentally mediated infectious disease burden. Political stability and wealth were associated with improved sanitation, better health care, and lower proportions of rural poverty, indirectly resulting in lower burdens of environmentally mediated infections. Rarely, environmentally mediated pathogens can evolve into global pandemics (eg, HIV, COVID-19) affecting even the wealthiest communities.

Interpretation

The high and uneven burden of environmentally mediated infections highlights the need for innovative social and ecological interventions to complement biomedical advances in the pursuit of global health and sustainability goals.

Funding

Bill & Melinda Gates Foundation, National Institutes of Health, National Science Foundation, Alfred P. Sloan Foundation, National Institute for Mathematical and Biological Synthesis, Stanford University, and the US Defense Advanced Research Projects Agency.

","language":"English","publisher":"Elsevier","doi":"10.1016/S2542-5196(22)00248-0","usgsCitation":"Sokolow, S.H., Nova, N., Jones, I.J., Wood, C.L., Lafferty, K.D., Garchitorena, A., Hopkins, S.R., Lund, A.J., MacDonald, A.J., LeBoa, C., Peel, A.J., Mordecai, E.A., Howard, M.E., Buck, J.C., Lopez-Carr, D., Barry, M., Bonds, M.H., and De Leo, G.A., 2022, Ecological and socioeconomic factors associated with the human burden of environmentally mediated pathogens: A global analysis: The Lancet Planetary Health, v. 6, no. 11, p. e870-e879, https://doi.org/10.1016/S2542-5196(22)00248-0.","productDescription":"10 p.","startPage":"e870","endPage":"e879","ipdsId":"IP-141097","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":445921,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1016/s2542-5196(22)00248-0","text":"External Repository"},{"id":409673,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sokolow, Susanne H.","contributorId":52503,"corporation":false,"usgs":false,"family":"Sokolow","given":"Susanne","email":"","middleInitial":"H.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":857670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nova, Nicole","contributorId":218822,"corporation":false,"usgs":false,"family":"Nova","given":"Nicole","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":857671,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Isabel J.","contributorId":173135,"corporation":false,"usgs":false,"family":"Jones","given":"Isabel","email":"","middleInitial":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":857672,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wood, Chelsea L.","contributorId":192504,"corporation":false,"usgs":false,"family":"Wood","given":"Chelsea","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":857673,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857674,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Garchitorena, Andres","contributorId":294698,"corporation":false,"usgs":false,"family":"Garchitorena","given":"Andres","email":"","affiliations":[],"preferred":false,"id":857675,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hopkins, Skylar R.","contributorId":203515,"corporation":false,"usgs":false,"family":"Hopkins","given":"Skylar","email":"","middleInitial":"R.","affiliations":[{"id":36642,"text":"National Center for Ecological Analysis and Synthesis, Santa Barbara,","active":true,"usgs":false}],"preferred":false,"id":857676,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lund, Andrea J","contributorId":221868,"corporation":false,"usgs":false,"family":"Lund","given":"Andrea","email":"","middleInitial":"J","affiliations":[{"id":40447,"text":"Emmett Interdisciplinary Program in Environment and Resources, Stanford University","active":true,"usgs":false}],"preferred":false,"id":857677,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"MacDonald, Andrew J","contributorId":245162,"corporation":false,"usgs":false,"family":"MacDonald","given":"Andrew","email":"","middleInitial":"J","affiliations":[{"id":49103,"text":"Department of Biology, Stanford University, Stanford, CA, USA","active":true,"usgs":false}],"preferred":false,"id":857678,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"LeBoa, Christopher","contributorId":245161,"corporation":false,"usgs":false,"family":"LeBoa","given":"Christopher","email":"","affiliations":[{"id":41637,"text":"Hopkins Marine Station, Stanford University, Pacific Grove, CA, USA","active":true,"usgs":false}],"preferred":false,"id":857679,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Peel, Alison J.","contributorId":212134,"corporation":false,"usgs":false,"family":"Peel","given":"Alison","email":"","middleInitial":"J.","affiliations":[{"id":38431,"text":"Environmental Futures Research Institute, Griffith University, Nathan, Queensland, Australia","active":true,"usgs":false}],"preferred":false,"id":857680,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mordecai, Erin A.","contributorId":221801,"corporation":false,"usgs":false,"family":"Mordecai","given":"Erin","email":"","middleInitial":"A.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":857681,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Howard, Meghan E","contributorId":299384,"corporation":false,"usgs":false,"family":"Howard","given":"Meghan","email":"","middleInitial":"E","affiliations":[{"id":49103,"text":"Department of Biology, Stanford University, Stanford, CA, USA","active":true,"usgs":false}],"preferred":false,"id":857682,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Buck, Julia C","contributorId":192180,"corporation":false,"usgs":false,"family":"Buck","given":"Julia","email":"","middleInitial":"C","affiliations":[],"preferred":false,"id":857683,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Lopez-Carr, David","contributorId":193003,"corporation":false,"usgs":false,"family":"Lopez-Carr","given":"David","email":"","affiliations":[],"preferred":false,"id":857684,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Barry, Michele","contributorId":299387,"corporation":false,"usgs":false,"family":"Barry","given":"Michele","email":"","affiliations":[{"id":49102,"text":"Woods Institute for the Environment, Stanford University, Stanford, CA, USA","active":true,"usgs":false}],"preferred":false,"id":857685,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Bonds, Matthew H","contributorId":299388,"corporation":false,"usgs":false,"family":"Bonds","given":"Matthew","email":"","middleInitial":"H","affiliations":[{"id":64827,"text":"PIVOT, Division of Global Health Equity, Brigham and Women's Hospital, Boston, MA, USA","active":true,"usgs":false}],"preferred":false,"id":857686,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"De Leo, Giulio A.","contributorId":146323,"corporation":false,"usgs":false,"family":"De Leo","given":"Giulio","email":"","middleInitial":"A.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":857687,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70238108,"text":"70238108 - 2022 - Tough places and safe spaces: Can refuges save salmon from a warming climate?","interactions":[],"lastModifiedDate":"2022-11-10T13:30:41.807133","indexId":"70238108","displayToPublicDate":"2022-11-09T07:28:41","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Tough places and safe spaces: Can refuges save salmon from a warming climate?","docAbstract":"

The importance of thermal refuges in a rapidly warming world is particularly evident for migratory species, where individuals encounter a wide range of conditions throughout their lives. In this study, we used a spatially explicit, individual-based simulation model to evaluate the buffering potential of cold-water thermal refuges for anadromous salmon and trout (Oncorhynchus spp.) migrating upstream through a warm river corridor that can expose individuals to physiologically stressful temperatures. We considered upstream migration in relation to migratory phenotypes that were defined in terms of migration timing, spawn timing, swim speed, and use of cold-water thermal refuges. Individuals with different migratory phenotypes migrated upstream through riverine corridors with variable availability of cold-water thermal refuges and mainstem temperatures. Use of cold-water refuges (CWRs) decreased accumulated sublethal exposures to physiologically stressful temperatures when measured in degree-days above 20, 21, and 22°C. The availability of CWRs was an order of magnitude more effective in lowering accumulated sublethal exposures under current and future mainstem temperatures for summer steelhead than fall Chinook Salmon. We considered two emergent model outcomes, survival and percent of available energy used, in relation to thermal heterogeneity and migratory phenotype. Mean percent energy loss attributed to future warmer mainstem temperatures was at least two times larger than the difference in energy used in simulations without CWRs for steelhead and salmon. We also found that loss of CWRs reduced the diversity of energy-conserving migratory phenotypes when we examined the variability in entry timing and travel time outside of CWRs in relation to energy loss. Energy-conserving phenotypic space contracted by 7%–23% when CWRs were unavailable under the current thermal regime. Our simulations suggest that, while CWRs do not entirely mitigate for stressful thermal exposures in mainstem rivers, these features are important for maintaining a diversity of migration phenotypes. Our study suggests that the maintenance of diverse portfolios of migratory phenotypes and cool- and cold-water refuges might be added to the suite of policies and management actions presently being deployed to improve the likelihood of Pacific salmonid persistence into a future characterized by climate change.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4265","usgsCitation":"Snyder, M.N., Schumaker, N.H., Dunham, J., Ebersole, J.L., Keefer, M.L., Halama, J., Comeleo, R.L., Leinenbach, P., Brookes, A., Cope, B., Wu, J., and Palmer, J., 2022, Tough places and safe spaces: Can refuges save salmon from a warming climate?: Ecosphere, v. 13, no. 11, e4265, 18 p., https://doi.org/10.1002/ecs2.4265.","productDescription":"e4265, 18 p.","ipdsId":"IP-118264","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":445928,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4265","text":"Publisher Index Page"},{"id":409292,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.46784663732885,\n 47.37962406684906\n ],\n [\n -119.46784663732885,\n 44.13083272327515\n ],\n [\n -114.72175288732899,\n 44.13083272327515\n ],\n [\n -114.72175288732899,\n 47.37962406684906\n ],\n [\n -119.46784663732885,\n 47.37962406684906\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-11-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Snyder, Marcia N. 0000-0003-2202-2668","orcid":"https://orcid.org/0000-0003-2202-2668","contributorId":217972,"corporation":false,"usgs":false,"family":"Snyder","given":"Marcia","email":"","middleInitial":"N.","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":856889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schumaker, Nathan H.","contributorId":199151,"corporation":false,"usgs":false,"family":"Schumaker","given":"Nathan","email":"","middleInitial":"H.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":856890,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunham, Jason 0000-0002-6268-0633","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":220078,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":856892,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ebersole, Joseph L.","contributorId":146938,"corporation":false,"usgs":false,"family":"Ebersole","given":"Joseph","email":"","middleInitial":"L.","affiliations":[{"id":12657,"text":"EPA 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south-central Idaho, 2000–19","indexId":"sir20215078C","publicationYear":"2022","noYear":false,"chapter":"C","displayTitle":"Groundwater Budgets for the Big Lost River Basin, South-Central Idaho, 2000–19","title":"Groundwater budgets for the Big Lost River Basin, south-central Idaho, 2000–19"},"predicate":"IS_PART_OF","object":{"id":70224602,"text":"sir20215078 - 2021 - Characterization of water resources in the Big Lost River Basin, south-central Idaho","indexId":"sir20215078","publicationYear":"2021","noYear":false,"title":"Characterization of water resources in the Big Lost River Basin, south-central Idaho"},"id":1}],"isPartOf":{"id":70224602,"text":"sir20215078 - 2021 - Characterization of water resources in the Big Lost River Basin, south-central Idaho","indexId":"sir20215078","publicationYear":"2021","noYear":false,"title":"Characterization of water resources in the Big Lost River Basin, south-central Idaho"},"lastModifiedDate":"2026-04-02T19:31:10.532467","indexId":"sir20215078C","displayToPublicDate":"2022-11-09T06:54:19","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":"2021-5078","chapter":"C","displayTitle":"Groundwater Budgets for the Big Lost River Basin, South-Central Idaho, 2000–19","title":"Groundwater budgets for the Big Lost River Basin, south-central Idaho, 2000–19","docAbstract":"

The Big Lost River Basin, located in parts of Butte and Custer Counties in south-central Idaho, supports the communities surrounding the cities of Arco, Leslie, Mackay, and Moore and provides for agricultural resources that depend on a sustainable supply of surface water from the Big Lost River and its tributaries and groundwater from an unconfined aquifer. The aquifer, situated in a structurally controlled intermontane valley, is composed of unconsolidated alluvium, consolidated sedimentary and volcanic rocks, and younger interbedded volcanic rocks.

This report presents two separate groundwater budgets for the aquifer, one above and one below Mackay Dam, as well as a combined groundwater budget for the aquifer within the entire Big Lost River Basin. The budgets span a 20-year period (2000–19), characterizing average conditions, a dry year (2014), and a wet year (2017). The groundwater budgets will help address questions regarding the availability of groundwater supply in the Big Lost River Basin and inform future groundwater modeling. The Idaho Geological Survey has prepared the groundwater budgets as part of a larger hydrogeologic investigation completed by the U.S. Geological Survey and the Idaho Geological Survey in cooperation with the Idaho Department of Water Resources during 2018–21. Other reports describe the hydrogeologic framework and several streamflow-measurement events to evaluate gains and losses on the Big Lost River. Collectively, these reports provide an updated characterization of groundwater resources in the Big Lost River Basin which will help address water resources challenges.

A groundwater budget is a conceptual and numerical accounting of inflow (recharge) to groundwater and outflow (discharge) from groundwater. The predominant sources of recharge to the aquifer include losing river reaches (33 percent), areal recharge (as precipitation less evapotranspiration and surface runoff, comprising about 23 percent of the total inflow), tributary canyon underflow from higher altitudes (20 percent), canal seepage (13 percent), recharge through applied irrigation on fields below the root zone and other minor sources (11 percent), and Mackay Reservoir seepage (less than 1 percent). The primary sources of discharge from the aquifer are groundwater pumpage to meet irrigation demand, domestic supply, and municipal supply (76 percent) and gaining river reaches (24 percent).

The positive or negative difference between the sum of all inflows and outflows is regarded as the residual, representing the change in groundwater storage, groundwater outflow from the basin or subbasins, and uncertainty and errors in the budget. In the Big Lost River Basin, groundwater outflow is at the mouth of the basin below Arco into the eastern Snake River Plain aquifer.

The total mean annual estimated recharge to the Big Lost River Basin was 439,100 acre-feet per year (acre-ft/yr; 607 cubic feet per second [ft3/s]) for 2000–19, 373,900 acre-ft/yr (516 ft3/s) in 2014, and 762,100 acre-ft/yr (1,053 ft3/s) in 2017. The mean annual estimated groundwater discharge from the aquifer was about 112,300 acre-ft/yr (155 ft3/s) for 2000–19, 153,500 acre-ft/yr (212 ft3/s) in 2014, and 53,400 acre-ft/yr (74 ft3/s) in 2017. The estimated mean annual groundwater residual was 326,800 acre-ft/yr (451 ft3/s) for 2000–19, 220,400 acre-ft/yr (304 ft3/s) in 2014, and 708,700 acre-ft/yr (979 ft3/s) in 2017. The mean annual residual above Mackay Dam was 100,400 acre-ft/yr (2000-19), 96,700 acre-ft (2014), and 248,300 acre-ft (2017). The mean annual residual contribution below Mackay Dam, minus any groundwater-flow above Mackay Dam, was 226,400 acre-ft/yr (2000-19), 123,700 acre-ft (2014), and 460,400 acre-ft (2017).

These results are highly sensitive to assumptions about certain budget inflow parameters. In particular, the magnitude of the budget residuals during especially dry and wet periods is amplified by the groundwater-budget terms tributary streamflow and tributary underflow that contribute appreciable recharge but also have high uncertainty.

The results of the groundwater-budget evaluation describe an interconnected and complex hydrologic response throughout the basin to various climatic and water-use trends. The part of the basin above Mackay Dam typically has a positive groundwater residual derived from snowmelt recharge to tributary canyons and areal recharge in excess of groundwater pumpage for irrigation demand. This supply is used to meet irrigation demand above Mackay Dam and to provide for water supply below Mackay Dam. On average, groundwater inflow from above Mackay Dam to below Mackay Dam, assuming negligible reservoir storage effects, accounts for about 25 percent of the total groundwater recharge below Mackay Dam. Considerable recharge to groundwater below Mackay Dam occurs through seepage from the Big Lost River and canals and ditches. Most groundwater discharge from the aquifer is through irrigation pumping. The water supply below Mackay Dam is highly dependent on available upstream surface-water flows, the magnitude of the groundwater residual from above Mackay Dam, and annual variability in local groundwater conditions.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215078C","collaboration":"Prepared in cooperation with the Idaho Department of Water Resources","usgsCitation":"Clark, A., 2022, Groundwater budgets for the Big Lost River Basin, south-central Idaho, 2000–19, chap. C of Zinsser, L.M., ed., Characterization of water resources in the Big Lost River Basin, south-central Idaho: U.S. Geological Survey Scientific Investigations Report 2021–5078–C, 111 p., https://doi.org/10.3133/sir20215078C.","productDescription":"xi, 111 p.","ipdsId":"IP-125226","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":409232,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5078/c/coverthb.jpg"},{"id":409233,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5078/c/sir20215078C.pdf","text":"Reports","size":"6.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5078-C"},{"id":409235,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5078/c/images"},{"id":409236,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5078/c/sir20215078C.XML"},{"id":502105,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113824.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Idaho","otherGeospatial":"Big Lost River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.1863738631967,\n 43.10571945845362\n ],\n [\n -113.42308735779262,\n 43.54649028685452\n ],\n [\n -112.13258233834704,\n 44.22138739870667\n ],\n [\n -112.23487846793722,\n 44.737914300373745\n ],\n [\n -114.26506595862107,\n 46.10751185031063\n ],\n [\n -115.75229430420214,\n 46.493497990156555\n ],\n [\n -117.884775159506,\n 45.476547804668826\n ],\n [\n -117.57788677073549,\n 45.01671717637413\n ],\n [\n -116.38967788087962,\n 44.5307302025393\n ],\n [\n -115.2014689910242,\n 43.60919623765622\n ],\n [\n -114.1863738631967,\n 43.10571945845362\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director , Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702-4520

","tableOfContents":"","publishedDate":"2022-11-09","noUsgsAuthors":false,"publicationDate":"2022-11-09","publicationStatus":"PW","contributors":{"editors":[{"text":"Zinsser, Lauren M. 0000-0002-8582-066X","orcid":"https://orcid.org/0000-0002-8582-066X","contributorId":205756,"corporation":false,"usgs":true,"family":"Zinsser","given":"Lauren","email":"","middleInitial":"M.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856978,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Clark, Alexis","contributorId":298944,"corporation":false,"usgs":false,"family":"Clark","given":"Alexis","email":"","affiliations":[{"id":33778,"text":"Idaho Geological Survey","active":true,"usgs":false}],"preferred":false,"id":856757,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70237910,"text":"sir20225081 - 2022 - Suspended-sediment transport and water management, Jemez Canyon Dam, New Mexico, 1948–2018","interactions":[],"lastModifiedDate":"2026-04-23T17:19:38.569434","indexId":"sir20225081","displayToPublicDate":"2022-11-08T11:41:15","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":"2022-5081","displayTitle":"Suspended-Sediment Transport and Water Management, Jemez Canyon Dam, New Mexico, 1948–2018","title":"Suspended-sediment transport and water management, Jemez Canyon Dam, New Mexico, 1948–2018","docAbstract":"

Construction and operation of dams provide sources of clean drinking water, support large-scale irrigation, generate hydroelectricity, control floods, and improve river navigation. Yet these benefits are not without cost. Dams affect the natural flow regime, downstream sediment fluxes, and riverine and riparian ecosystems. The Jemez Canyon Dam in New Mexico was constructed in 1953 by the U.S. Army Corps of Engineers with authorizations for flood control and sediment retention. Water managers of the dam use various operational techniques to restore peak streamflow, improve sediment management, and restore altered ecosystem processes, while maintaining the authorized purposes of the dam. This study focuses on four distinct reservoir management operation periods implemented at the Jemez Canyon Dam: (1) predam (pre-1953), (2) a seasonal 24-hour hold pool (1953–79), (3) a permanent pool (1979–2001), and (4) dry reservoir (2001–18).

Results of this study indicate successful flood control and reduction in peak instantaneous streamflow events following construction of the dam, specifically documented in 1958 and 2013. During the second water management operation period, moderate sediment retention (also defined as trap efficiency, which is the percentage of incoming sediments trapped within a reservoir during a given time) occurred (between 41.0 and 67.0 percent of sediments were retained). During the third period (1979–2001), between 61.2 and 99.8 percent of sediments were retained. During the fourth period (2001–18), at least 1,909 acre-feet of accumulated sediment were remobilized. The estimated dam trap efficiency during the fourth water management operation period was −37.2 percent, indicating that more sediments were being removed from the Jemez Canyon Reservoir than were being deposited. These remobilized sediments supplemented the natural sediment delivery in the Jemez River to the middle Rio Grande. The current (2022) dry reservoir operation allows sediment delivery during periods when flooding is not a concern while still providing flood control when needed.

Suspended-sediment particle size data indicate potential coarsening of suspended sediments during the fourth water management operation period, likely resulting from erosion of coarse bed sediments deposited in the reservoir. Suspended-sediment particle size data during the first and fourth water management operation periods indicate that finer sediment mobilized during monsoon season than during snowmelt. Also, suspended-sediment concentrations during the predam and post-hold pool periods indicate concentrations were higher during monsoon season than during snowmelt. Seasonal variations in suspended-sediment concentration and particle size may help dam managers make operational decisions by increasing the understanding of particle size, concentration, and variation of suspended sediment during a given year. The seasonality of suspended-sediment transport can also vary, depending not only on concentration and particle size, but on precipitation. The maximum annual suspended-sediment loads occurred during all three seasonal categories analyzed in this study: snowmelt, monsoon, and the remainder of the year. This indicates that, in addition to sediment particle size and concentration, understanding the variability of transport mechanisms of suspended-sediment load can also guide optimal water management operations at a dam.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225081","isbn":"978-1-4113-4481-5","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Brown, J.E., Matherne, A.M., Reale, J.K., and Miltenberger, K.E., 2022, Suspended-sediment transport and water management, Jemez Canyon Dam, New Mexico, 1948–2018: U.S. Geological Survey Scientific Investigations Report 2022–5081, 30 p., https://doi.org/10.3133/sir20225081.","productDescription":"Report: vii, 30 p.; 2 Datasets","numberOfPages":"42","onlineOnly":"N","ipdsId":"IP-107586","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":408905,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":408902,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5081/sir20225081.XML"},{"id":408901,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5081/sir20225081.pdf","text":"Report","size":"2.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5081"},{"id":408900,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5081/coverthb.jpg"},{"id":503401,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113825.htm","linkFileType":{"id":5,"text":"html"}},{"id":409231,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225081/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":408904,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://earthexplorer.usgs.gov/","text":"USGS Earth Resources Observation and Science Center database","linkHelpText":"—EarthExplorer"},{"id":408903,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5081/images"}],"country":"United States","state":"New Mexico","otherGeospatial":"Jemez Canyon Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.61655311950582,\n 35.438783063650746\n ],\n [\n -106.61655311950582,\n 35.32720598341298\n ],\n [\n -106.46641220000733,\n 35.32720598341298\n ],\n [\n -106.46641220000733,\n 35.438783063650746\n ],\n [\n -106.61655311950582,\n 35.438783063650746\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2022-11-08","noUsgsAuthors":false,"publicationDate":"2022-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Brown, Jeb E. 0000-0001-7671-2379 jebbrown@usgs.gov","orcid":"https://orcid.org/0000-0001-7671-2379","contributorId":4357,"corporation":false,"usgs":true,"family":"Brown","given":"Jeb","email":"jebbrown@usgs.gov","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856172,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matherne, Anne-Marie 0000-0002-5873-2226","orcid":"https://orcid.org/0000-0002-5873-2226","contributorId":32279,"corporation":false,"usgs":true,"family":"Matherne","given":"Anne-Marie","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856173,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reale, Justin K.","contributorId":298654,"corporation":false,"usgs":false,"family":"Reale","given":"Justin","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":856174,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miltenberger, K. E. 0000-0002-3874-4609","orcid":"https://orcid.org/0000-0002-3874-4609","contributorId":243647,"corporation":false,"usgs":true,"family":"Miltenberger","given":"K.","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856176,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70238960,"text":"70238960 - 2022 - Geologic, geomorphic, and edaphic underpinnings of dryland ecosystems: Colorado Plateau landscapes in a changing world","interactions":[],"lastModifiedDate":"2022-12-19T13:43:37.234094","indexId":"70238960","displayToPublicDate":"2022-11-08T07:36:03","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Geologic, geomorphic, and edaphic underpinnings of dryland ecosystems: Colorado Plateau landscapes in a changing world","docAbstract":"

Drylands represent more than 41% of the global land surface and are at degradation risk due to land use and climate change. Developing strategies to mitigate degradation and restore drylands in the face of these threats requires an understanding of how drylands are shaped by not only soils and climate, but also geology and geomorphology. However, few studies have completed such a comprehensive analysis that relates spatial variation in plant communities to all aspects of the geologic–geomorphic–edaphic–plant–climate system. The focus of this study is the Colorado Plateau, a high-elevation dryland in the southwestern United States, which is particularly sensitive to future change due to climate vulnerability and increasing land-use pressure. Here, we examined 135 long-term vegetation-monitoring sites in three national parks and characterized connections between geology, geomorphology, soils, climate, and dryland plant communities. To first understand the geologic and geomorphic influences on soil formation and characteristics, we explore associations between soil pedons, bedrock geology, and geomorphology. Then, we characterize principal axes of variation in plant communities and ascertain controls and linkages between components of the edaphic–geomorphic system and plant community ordinations. Geologic and geomorphic substrate exerted controls on important properties of the soil profile, particularly depth, water-holding capacity, rockiness, salinity, and fine sands. Ordination identified five distinct plant communities and three primary axes of variation, representing gradients of woody- to herbaceous-dominated communities (Axis 1), saline scrublands to C3 grasslands (Axis 2), and annual to perennial communities (Axis 3). Geology, geomorphology, and soil explained a large proportion of variation in Axis 1 (74%), while climate variables largely explained Axis 2 (68%), and Axis 3 was not well explained by the random forest models. The variables identified as most influential to each axis were, respectively: (1) soil depth; (2) aridity, lithology, and soil salinity; and (3) temperature and precipitation. We posit that Axis 3 represents a land degradation gradient due to historic grazing, likely exacerbated by dry conditions. Results provide a novel framework that links the geologic and geomorphic evolution of landscapes, with the distribution of soils and plant communities that can guide ecosystem management, exemplifying an approach applicable to drylands globally.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4273","usgsCitation":"Duniway, M.C., Benson, C., Nauman, T.W., Knight, A.C., Bradford, J., Munson, S.M., Witwicki, D.L., Livensperger, C., Van Scoyoc, M.W., Fisk, T.T., Thoma, D., and Miller, M.E., 2022, Geologic, geomorphic, and edaphic underpinnings of dryland ecosystems: Colorado Plateau landscapes in a changing world: Ecosphere, v. 13, no. 11, e4273, 27 p., https://doi.org/10.1002/ecs2.4273.","productDescription":"e4273, 27 p.","ipdsId":"IP-135505","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":488760,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4273","text":"Publisher Index Page"},{"id":435625,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92Z8NDP","text":"USGS data release","linkHelpText":"Soil, geologic, geomorphic, climate, and vegetation data from long-term monitoring plots (2009 - 2018) in Arches, Canyonlands, and Capitol Reef National Parks, Utah, USA"},{"id":410697,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","otherGeospatial":"Colorado Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.63689444724997,\n 36.734805586098716\n ],\n [\n -108.00129122959586,\n 36.72595486884292\n ],\n [\n -107.41606847690218,\n 37.63008491281205\n ],\n [\n -107.57066880734789,\n 38.70708139014661\n ],\n [\n -107.76120496171856,\n 39.973850096503895\n ],\n [\n -108.78556565774403,\n 40.46292505503848\n ],\n [\n -110.23348660705287,\n 40.36792094423029\n ],\n [\n -111.02839675350845,\n 39.403592925523014\n ],\n [\n -111.43291910676305,\n 38.05141646696123\n ],\n [\n -112.77571792678364,\n 37.21069090791468\n ],\n [\n -112.28678230930984,\n 36.79511547655869\n ],\n [\n -111.63689444724997,\n 36.734805586098716\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":859388,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Benson, Christopher","contributorId":296064,"corporation":false,"usgs":false,"family":"Benson","given":"Christopher","email":"","affiliations":[{"id":63978,"text":"formerly) US Geological Survey, Southwest Biological Science Center, Moab, UT","active":true,"usgs":false}],"preferred":false,"id":859389,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nauman, Travis W. 0000-0001-8004-0608 tnauman@usgs.gov","orcid":"https://orcid.org/0000-0001-8004-0608","contributorId":169241,"corporation":false,"usgs":true,"family":"Nauman","given":"Travis","email":"tnauman@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":859390,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knight, Anna C. 0000-0002-9455-2855","orcid":"https://orcid.org/0000-0002-9455-2855","contributorId":255113,"corporation":false,"usgs":true,"family":"Knight","given":"Anna","email":"","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":859391,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":859392,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":859393,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Witwicki, Dana L.","contributorId":207763,"corporation":false,"usgs":false,"family":"Witwicki","given":"Dana","email":"","middleInitial":"L.","affiliations":[{"id":37628,"text":"National Park Service Inventory and Monitoring Program, P.O. Box 848, Moab, UT 84532, USA","active":true,"usgs":false}],"preferred":false,"id":859394,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Livensperger, Carolyn","contributorId":260927,"corporation":false,"usgs":false,"family":"Livensperger","given":"Carolyn","email":"","affiliations":[{"id":52723,"text":"National Park Service, Capitol Reef National Park, 52 Headquarters Dr., Torrey UT 84775","active":true,"usgs":false}],"preferred":false,"id":859395,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Van Scoyoc, Matthew W. 0000-0001-6821-4476","orcid":"https://orcid.org/0000-0001-6821-4476","contributorId":290213,"corporation":false,"usgs":false,"family":"Van Scoyoc","given":"Matthew","email":"","middleInitial":"W.","affiliations":[{"id":62383,"text":"Southeast Utah Group, National Park Service, Moab, UT","active":true,"usgs":false}],"preferred":false,"id":859396,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Fisk, Terry T","contributorId":289096,"corporation":false,"usgs":false,"family":"Fisk","given":"Terry","email":"","middleInitial":"T","affiliations":[{"id":62042,"text":"Water Resources Division, National Park Service","active":true,"usgs":false}],"preferred":false,"id":859397,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Thoma, David","contributorId":265911,"corporation":false,"usgs":false,"family":"Thoma","given":"David","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":859398,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Miller, Mark E.","contributorId":91580,"corporation":false,"usgs":false,"family":"Miller","given":"Mark","email":"","middleInitial":"E.","affiliations":[{"id":6959,"text":"National Park Service Southeast Utah Group","active":true,"usgs":false}],"preferred":false,"id":859399,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70238582,"text":"70238582 - 2022 - Mapping 2-D bedload rates throughout a sand-bed river reach from high-resolution acoustical surveys of migrating bedforms","interactions":[],"lastModifiedDate":"2022-11-30T12:53:57.31331","indexId":"70238582","displayToPublicDate":"2022-11-08T06:50:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Mapping 2-D bedload rates throughout a sand-bed river reach from high-resolution acoustical surveys of migrating bedforms","docAbstract":"

This paper introduces a method for determining spatially-distributed, 2-D bedload rates using repeat, high-resolution surveys of the bed topography. As opposed to existing methods, bedform parameters and bedload rates are computed from bed elevation profiles interpolated along the local bedform velocities. The bedform velocity fields are computed applying Large-Scale Particle Image Velocimetry, initially developed for surface velocity measurements, to pairs of successive Digital Elevation Models (DEMs). The bathymetry data are interpolated along the direction of each bedform velocity and the mean height of the closest bedform is computed. The dune shape factor is also evaluated along each bedform direction of travel. The local bedload fluxes can be computed by multiplying the bedform velocity by its mean height averaged over the successive two DEMs, and they can be time-averaged over a series of DEM pairs. This method is applied to a high-resolution acoustical survey of an approximately 300 m long by 40 m wide reach of the Colorado River in Grand Canyon upstream from Diamond Creek, USA. The repeat period was about 6–10 min and bed elevation was interpolated every 0.25 m. The obtained results provide insight to the spatial and temporal variability of bedload rates, bedform parameters and bedload fluxes through cross-sections. The method can be applied to other repeated acoustical surveys of river reaches provided that the space and time resolutions are high enough to capture the local movement of bedforms.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022WR032434","usgsCitation":"Le Coz, J., Perret, E., Camenen, B., Topping, D.J., Buscombe, D.D., Leary, K., Dramais, G., and Grams, P.E., 2022, Mapping 2-D bedload rates throughout a sand-bed river reach from high-resolution acoustical surveys of migrating bedforms: Water Resources Research, v. 58, no. 11, e2022WR032434, 16 p., https://doi.org/10.1029/2022WR032434.","productDescription":"e2022WR032434, 16 p.","ipdsId":"IP-139516","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":445937,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2022wr032434","text":"External Repository"},{"id":409857,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.85660930265428,\n 37.076564530984584\n ],\n [\n -113.84362202724009,\n 37.076564530984584\n ],\n [\n -113.84362202724009,\n 35.44740531531292\n ],\n [\n -110.85660930265428,\n 35.44740531531292\n ],\n [\n -110.85660930265428,\n 37.076564530984584\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"58","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-11-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Le Coz, Jérôme","contributorId":299550,"corporation":false,"usgs":false,"family":"Le Coz","given":"Jérôme","affiliations":[{"id":64876,"text":"INRAE, UR RiverLy, centre de Lyon-Villeurbanne, 5 Rue de la Doua, CS 20244, F-69625 Villeurbanne Dedex, France","active":true,"usgs":false}],"preferred":false,"id":858015,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perret, Emeline","contributorId":299551,"corporation":false,"usgs":false,"family":"Perret","given":"Emeline","email":"","affiliations":[{"id":64877,"text":"INRAE, UR RiverLy, centre de Lyon-Villeurbanne, 5 Rue de la Doua, CS 20244, F-69625 Villeurbanne Dedex, France; Compagnie nationale du Rhone, Lyon, France","active":true,"usgs":false}],"preferred":false,"id":858016,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Camenen, Benoît","contributorId":299552,"corporation":false,"usgs":false,"family":"Camenen","given":"Benoît","affiliations":[{"id":64876,"text":"INRAE, UR RiverLy, centre de Lyon-Villeurbanne, 5 Rue de la Doua, CS 20244, F-69625 Villeurbanne Dedex, France","active":true,"usgs":false}],"preferred":false,"id":858017,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Topping, David J. 0000-0002-2104-4577","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":215068,"corporation":false,"usgs":true,"family":"Topping","given":"David","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":858018,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buscombe, Daniel D. 0000-0001-6217-5584 dbuscombe@usgs.gov","orcid":"https://orcid.org/0000-0001-6217-5584","contributorId":5020,"corporation":false,"usgs":false,"family":"Buscombe","given":"Daniel","email":"dbuscombe@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":858019,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leary, Kate","contributorId":299553,"corporation":false,"usgs":false,"family":"Leary","given":"Kate","email":"","affiliations":[{"id":64879,"text":"New Mexico Institute of Mining and Technology, Department of Earth and Environmental Sciences, Socorro, NM, 87801 USA","active":true,"usgs":false}],"preferred":false,"id":858020,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dramais, Guillaume 0000-0002-2703-9314","orcid":"https://orcid.org/0000-0002-2703-9314","contributorId":238955,"corporation":false,"usgs":false,"family":"Dramais","given":"Guillaume","email":"","affiliations":[{"id":47837,"text":"Ph.D. student, IRSTEA, Flagstaff, Arizona","active":true,"usgs":false}],"preferred":false,"id":858021,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Grams, Paul E. 0000-0002-0873-0708","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":216115,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":858022,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70274032,"text":"70274032 - 2022 - Regularizing priors for Bayesian VAR applications to large ecological datasets","interactions":[],"lastModifiedDate":"2026-02-24T16:53:30.35343","indexId":"70274032","displayToPublicDate":"2022-11-08T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"title":"Regularizing priors for Bayesian VAR applications to large ecological datasets","docAbstract":"

Using multi-species time series data has long been of interest for estimating inter-specific interactions with vector autoregressive models (VAR) and state space VAR models (VARSS); these methods are also described in the ecological literature as multivariate autoregressive models (MAR, MARSS). To date, most studies have used these approaches on relatively small food webs where the total number of interactions to be estimated is relatively small. However, as the number of species or functional groups increases, the length of the time series must also increase to provide enough degrees of freedom with which to estimate the pairwise interactions. To address this issue, we use Bayesian methods to explore the potential benefits of using regularized priors, such as Laplace and regularized horseshoe, on estimating interspecific interactions with VAR and VARSS models. We first perform a large-scale simulation study, examining the performance of alternative priors across various levels of observation error. Results from these simulations show that for sparse matrices, the regularized horseshoe prior minimizes the bias and variance across all inter-specific interactions. We then apply the Bayesian VAR model with regularized priors to a output from a large marine food web model (37 species) from the west coast of the USA. Results from this analysis indicate that regularization improves predictive performance of the VAR model, while still identifying important inter-specific interactions.

","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.14332","usgsCitation":"Ward, E.J., Marshall, K.N., Scheuerell, M.D., 2022, Regularizing priors for Bayesian VAR applications to large ecological datasets: PeerJ, v. 10, e14332, 18 p., https://doi.org/10.7717/peerj.14332.","productDescription":"e14332, 18 p.","ipdsId":"IP-144838","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500605,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.14332","text":"Publisher Index Page"},{"id":500429,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationDate":"2022-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Ward, Eric J.","contributorId":366786,"corporation":false,"usgs":false,"family":"Ward","given":"Eric","middleInitial":"J.","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":956224,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marshall, Kristin N.","contributorId":366787,"corporation":false,"usgs":false,"family":"Marshall","given":"Kristin","middleInitial":"N.","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":956225,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scheuerell, Mark David 0000-0002-8284-1254","orcid":"https://orcid.org/0000-0002-8284-1254","contributorId":288621,"corporation":false,"usgs":true,"family":"Scheuerell","given":"Mark","email":"","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956226,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70237990,"text":"tm17A1 - 2022 - Rapidly assessing social characteristics of drought preparedness and decision making: A guide for practitioners","interactions":[],"lastModifiedDate":"2022-11-07T17:14:33.667614","indexId":"tm17A1","displayToPublicDate":"2022-11-07T11:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"17-A1","displayTitle":"Rapidly Assessing Social Characteristics of Drought Preparedness and Decision Making: A Guide for Practitioners","title":"Rapidly assessing social characteristics of drought preparedness and decision making: A guide for practitioners","docAbstract":"

Executive Summary

This guide is intended to provide managers, decision makers, and other practitioners with advice on conducting a rapid assessment of the social dimensions of drought. Findings from a rapid assessment can provide key social context that may aid in decision making, such as when preparing a drought plan, allocating local drought resilience funding, or gathering the support of local agencies and organizations for collective action related to drought mitigation.

Part I—In the introduction to Part I, we describe the unique problems associated with drought—particularly its slow onset and long duration, which make it difficult to define drought—and highlight five major types of drought (see Box 1). We introduce a few social dimensions of drought (such as economic and institutional perspectives), demonstrate how these dimensions can be interrelated, and describe a few of the modern challenges (such as transformational change and cascading risks) that practitioners face.

We also provide background on the rapid assessment method, first describing it as a “snapshot” of the social landscape, then providing some key advantages of the method (it can be quicker and cheaper than more in-depth methods), and lastly describing how secondary data and other methods can help overcome some of the disadvantages of rapid assessments.

Then, after summarizing the process of developing this guide, we outline the process of using the guide. Importantly, we compare the guide to a travel guide, which provides many different types of information and is best approached with specific interests in mind. Ultimately, we hope for this guide to be malleable enough that it can be helpful to researchers and practitioners in many different contexts, using many different research methods. Related to how to use the guide, we characterize the type of person who might be motivated to use this guide. We also specify key qualifications for a researcher conducting a rapid assessment, drawing particular attention to training on ethical considerations.

We sketch out key considerations when choosing social dimensions of drought to focus on, and the type of data used for analysis. First, it is important to note that in this guide we provide nine important social dimensions of drought, but this is by no means a comprehensive list, and a researcher may find that other dimensions better fit their local context. Second, we provide some pros and cons to a narrow (focusing on just a few dimensions or at a smaller scale) versus broad research focus. Lastly, we describe the pros and cons of using primary versus secondary data (one strategy is to use both, sequentially) and qualitative versus quantitative data.

Ultimately, Part I of this guide functions as an exploration of the various decisions a researcher will make when designing a rapid assessment. These decisions will inform the type of findings and other outcomes that result from the rapid assessment.

Part II—Part II of this guide introduces nine key social dimensions of drought: defining the problem of drought, individual perceptions, social relationships, technology, economics and livelihoods, water governance, decision making, information, and social vulnerability. Each section provides background and key considerations related to a particular dimension, as well as ideas for how to explore the dimension via a rapid assessment.

Part III—Part III of this guide provides two hypothetical examples of how one might use this guide to aid the practitioner in implementing the lessons learned here. In the first example, a watershed group uses two dimensions, defining the problem of drought and social relationships, to inform a community meeting about protecting fisheries from drought. In the second example, a resource manager uses the economics and livelihoods and social vulnerability dimensions to inform the development of a livestock grazing drought management plan.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm17A1","usgsCitation":"Clifford, K.R., Goolsby, J.B., Cravens, A.E., and Cooper, A.E., 2022, Rapidly assessing social characteristics of drought preparedness and decision making: A guide for practitioners: U.S. Geological Survey Techniques and Methods 17-A1, 41 p., https://doi.org/10.3133/tm17A1.","productDescription":"vii, 41 p.","onlineOnly":"Y","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":409066,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/17/a1/tm17a1.xml"},{"id":409065,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/17/a1/images"},{"id":409061,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/17/a1/coverthb.jpg"},{"id":409062,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/17/a1/tm17a1.pdf","text":"Report","size":"1.47 MB","linkFileType":{"id":1,"text":"pdf"},"description":"T and M 17-A1"}],"contact":"

Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118

","tableOfContents":"","publishedDate":"2022-11-07","noUsgsAuthors":false,"publicationDate":"2022-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Clifford, Katherine R. 0000-0002-1385-8765","orcid":"https://orcid.org/0000-0002-1385-8765","contributorId":259886,"corporation":false,"usgs":true,"family":"Clifford","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":856454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goolsby, Julia B. 0000-0002-2229-5685","orcid":"https://orcid.org/0000-0002-2229-5685","contributorId":269631,"corporation":false,"usgs":true,"family":"Goolsby","given":"Julia","email":"","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":856455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cravens, Amanda E. 0000-0002-0271-7967 aecravens@usgs.gov","orcid":"https://orcid.org/0000-0002-0271-7967","contributorId":196752,"corporation":false,"usgs":true,"family":"Cravens","given":"Amanda","email":"aecravens@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":856456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cooper, Ashley E. 0000-0001-9817-4444","orcid":"https://orcid.org/0000-0001-9817-4444","contributorId":257654,"corporation":false,"usgs":true,"family":"Cooper","given":"Ashley","email":"","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":856457,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70242697,"text":"70242697 - 2022 - Stream corridor and upland sources of fluvial sediment and phosphorus from a mixed urban-agricultural tributary to the Great Lakes","interactions":[],"lastModifiedDate":"2023-04-13T12:18:36.893973","indexId":"70242697","displayToPublicDate":"2022-11-06T07:13:22","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Stream corridor and upland sources of fluvial sediment and phosphorus from a mixed urban-agricultural tributary to the Great Lakes","docAbstract":"

Like many impaired Great Lakes tributaries, Apple Creek, Wisconsin (119 km2) has Total Maximum Daily Load (TMDL) targets for reducing suspended sediment and total phosphorus by 51.2 % and 64.2 %, respectively. From August 2017 - October 2018, a stream sediment budget and fingerprinting integrated study was conducted to quantify upland and stream corridor sources of suspended sediment and sediment-bound phosphorus. Phosphorus concentrations varied among source groups and fluvial sediments, with higher concentrations among suspended sediment and cropland soils. Eroding streambanks identified in the stream corridor sediment budget accounted for 100 % of the TMDL Soil and Water Assessment Tool (SWAT) suspended sediment load but only 20 % of the total phosphorus load. Fine-grained streambed sediment equated to approximately-three years of modeled suspended sediment load but only one third of total phosphorus load. The two primary sources of fine-grained streambed sediment were streambanks and cropland, with relative streambank contributions increasing with downstream direction and watershed area. The relative proportion of suspended sediment varied by season and streamflow; however, cropland and streambank erosion accounted for 54 % and 23 % of the suspended sediment when weighted by of the proportion for representative streamflow. Urban land was a source in the upper watershed, but the signature was sequestered by a mid-watershed detention basin. Contributions from construction sites were higher in the fall 2018, likely corresponding to increased activity following a wet spring. These integrated techniques helped describe sources, transport, and sinks of fluvial sediment and phosphorus throughout the watershed at a range of spatial and temporal scales.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2022.08.024","usgsCitation":"Blount, J.D., Kammel, L., and Fitzpatrick, F., 2022, Stream corridor and upland sources of fluvial sediment and phosphorus from a mixed urban-agricultural tributary to the Great Lakes: Journal of Great Lakes Research, v. 48, no. 6, p. 1536-1549, https://doi.org/10.1016/j.jglr.2022.08.024.","productDescription":"14 p.","startPage":"1536","endPage":"1549","ipdsId":"IP-130233","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":494972,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13USQVX","text":"USGS data release","linkHelpText":"Chemical and Physical Data for Streambed Sediment-Source Fingerprinting in the Apple Creek Watershed, Outagamie County, Wisconsin, 2017-2018"},{"id":445940,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2022.08.024","text":"Publisher Index Page"},{"id":435626,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F8QS08","text":"USGS data release","linkHelpText":"Apple Creek Rapid Geomorphic Assessment, Outagamie County, Wisconsin"},{"id":415706,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","city":"Appleton","otherGeospatial":"Apple Creek basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.4047337275233,\n 44.361963714867386\n ],\n [\n -88.4047337275233,\n 44.245437009909836\n ],\n [\n -88.17063678311628,\n 44.245437009909836\n ],\n [\n -88.17063678311628,\n 44.361963714867386\n ],\n [\n -88.4047337275233,\n 44.361963714867386\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"48","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Blount, James D. 0000-0002-0006-3947 jblount@usgs.gov","orcid":"https://orcid.org/0000-0002-0006-3947","contributorId":200231,"corporation":false,"usgs":true,"family":"Blount","given":"James","email":"jblount@usgs.gov","middleInitial":"D.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869395,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kammel, Leah 0000-0003-4613-0858","orcid":"https://orcid.org/0000-0003-4613-0858","contributorId":211840,"corporation":false,"usgs":true,"family":"Kammel","given":"Leah","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869396,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fitzpatrick, Faith 0000-0002-9748-7075","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":209540,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith","email":"","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869397,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70238042,"text":"ofr20221083 - 2022 - Passage of adult coho salmon (Oncorhynchus kisutch) over Lake Creek Falls, Oregon, 2019","interactions":[],"lastModifiedDate":"2022-12-08T18:11:30.705283","indexId":"ofr20221083","displayToPublicDate":"2022-11-04T11:13:16","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":"2022-1083","displayTitle":"Passage of Adult Coho Salmon (Oncorhynchus kisutch) over Lake Creek Falls, Oregon, 2019","title":"Passage of adult coho salmon (Oncorhynchus kisutch) over Lake Creek Falls, Oregon, 2019","docAbstract":"

Across the Pacific Northwest, there are many examples of artificial structures created to allow passage of upstream-migrating salmon over natural barriers. We studied upstream passage across three structures installed in 1989 to allow passage of salmon over Lake Creek Falls, a series of three natural waterfalls at the outlet of Triangle Lake on Lake Creek, in the central Oregon Coast Range (lat 123.57508°; long 44.15735°). To track upstream passage by adult coho salmon (Oncorhynchus kisutch), 87 fish were tagged using gastrically implanted radio tags. Tracking was accomplished with a series of stationary receivers installed to detect crossings at each of three structures—over Lake Creek Falls using two upstream Denil-type ladders and a bypass downstream constructed to mimic a natural side channel. Tracking spanned the upstream migration and spawn timing for adult coho salmon in the basin and extended from October 2019 to February 2020. A total of 15 coho salmon (17 percent) were tagged in October, 30 coho salmon (35 percent) were tagged in November, and 42 coho salmon (48 percent) were tagged in December. Later-than-normal precipitation and associated low discharge delayed upstream migrations. Accordingly, most fish arrived late in the season (late November and December) and in sudden flushes with the erratic rain events. Fish that were tagged earlier were more likely to cross all three ladders, with more than 93 percent of fish tagged in October compared to 46.7 and 19.0 percent of November and December fish passing, respectively. The decline in passage rate could be attributed to the overlapping influences of stream discharge and advanced stage of maturation (lower energy reserves) of fish later in the season. Near the end of the study, both fish that crossed and fish obstructed by barriers were observed in tributaries known to be used for spawning by coho salmon. Without a much longer-term study involving many more fish than the current study, more intensive tracking, and coverage of different flow years, firm conclusions are difficult to draw regarding the overall influences of the passage structures on the likelihood of upstream passage by adult coho salmon. However, substantial numbers of fish are capable of crossing during certain conditions. The population-level consequences of the barriers on spawning distribution and the production of coho salmon in the watershed are not clear. Additional empirical study or population modeling could be used to address this question in more detail.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221083","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Fischer, R.B., Dunham, J., Scheidt, N., Hansen, A.C., and Heaston, E.D., 2022, Passage of adult coho salmon (Oncorhynchus kisutch) over Lake Creek Falls, Oregon, 2019: U.S. Geological Survey Open-File Report 2022–1083, 19 p., https://doi.org/10.3133/ofr20221083.","productDescription":"vii, 19 p.","onlineOnly":"Y","ipdsId":"IP-130393","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":409177,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1083/coverthb.jpg"},{"id":409181,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1083/ofr20221083.XML"},{"id":409180,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1083/images"},{"id":409179,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221083/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1083"},{"id":409178,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1083/ofr20221083.pdf","text":"Report","size":"21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1083"}],"country":"United States","state":"Oregon","otherGeospatial":"Lake Creek Falls","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.61844237310005,\n 44.17170307975459\n ],\n [\n -123.61844237310005,\n 44.131057340436286\n ],\n [\n -123.5593908594283,\n 44.131057340436286\n ],\n [\n -123.5593908594283,\n 44.17170307975459\n ],\n [\n -123.61844237310005,\n 44.17170307975459\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Forest and Rangeland Ecosystem Science Center
777 NW 9th Street, Suite 400
Corvallis, OR 97330

","tableOfContents":"","publishedDate":"2022-11-04","noUsgsAuthors":false,"publicationDate":"2022-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Fischer, Reed B.","contributorId":298909,"corporation":false,"usgs":false,"family":"Fischer","given":"Reed","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":856685,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunham, Jason 0000-0002-6268-0633","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":220078,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":856686,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scheidt, Nicholas","contributorId":298910,"corporation":false,"usgs":false,"family":"Scheidt","given":"Nicholas","email":"","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":856687,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hansen, Amy C. 0000-0002-0298-9137 achansen@usgs.gov","orcid":"https://orcid.org/0000-0002-0298-9137","contributorId":4350,"corporation":false,"usgs":true,"family":"Hansen","given":"Amy","email":"achansen@usgs.gov","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":856688,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heaston, Emily D. 0000-0002-3949-391X","orcid":"https://orcid.org/0000-0002-3949-391X","contributorId":236919,"corporation":false,"usgs":false,"family":"Heaston","given":"Emily","email":"","middleInitial":"D.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":false,"id":856689,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70238045,"text":"70238045 - 2022 - Rock alteration mapping in and around fossil shallow intrusions at Mt. Ruapehu New Zealand with laboratory and aerial hyperspectral imaging","interactions":[],"lastModifiedDate":"2022-11-07T12:50:24.402862","indexId":"70238045","displayToPublicDate":"2022-11-04T06:42:58","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Rock alteration mapping in and around fossil shallow intrusions at Mt. Ruapehu New Zealand with laboratory and aerial hyperspectral imaging","docAbstract":"

Diagnostic absorption features in hyperspectral data can be used to identify a specific mineral or mineral associations. However, it is unknown how accurate hyperspectral mapping can be for identifying alteration mineral compositions at the resolution required to describe structures such as fossil intrusions, or whether it can accurately quantify the alteration present. This study compared petrographic observation with visible, near-infrared (VNIR), and shortwave infrared (SWIR) hyperspectral remote sensing at laboratory- (centimetre-scale) and aerial- (metre-scale) scales to characterise the abundance of surface hydrothermal rock alteration in and around a shallow fossil intrusion on Pinnacle Ridge, Mt. Ruapehu, New Zealand. We classified a high-resolution aerial hyperspectral image to develop a new surface alteration map using Spectral Angle Mapper (SAM) algorithm. The petrographic thin-section and the laboratory and aerial hyperspectral imaging revealed a spectrum of hydrous alteration phases as indicated by the presence of an absorption feature at 2207 nm. Moderate correlation exists between the depth of the absorption feature at 2207 nm and the point counting-derived alteration percent values, indicating reliability of laboratory-based hyperspectral analytical methods. In contrast, aerial hyperspectral data failed to provide any clear correlations to field-mapped alteration using a band-depth approach, and we interpret this due to ‘oversampling’ of surface (supergene) alteration, spectral mixing, and sensor limitations (e.g., bandwidth, signal-to-noise ratio). The hyperspectral image-derived alteration map, created using supervised image classification, can loosely be translated to a geotechnical map where porosity and permeability play a major role in localizing hydrothermal fluid flow and the formation of alteration mineral associations.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2022.107700","usgsCitation":"Douglas, A., Kereszturi, G., Schaefer, L.N., and Kennedy, B.M., 2022, Rock alteration mapping in and around fossil shallow intrusions at Mt. Ruapehu New Zealand with laboratory and aerial hyperspectral imaging: Journal of Volcanology and Geothermal Research, 107700, 15 p., https://doi.org/10.1016/j.jvolgeores.2022.107700.","productDescription":"107700, 15 p.","ipdsId":"IP-141155","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":409188,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","otherGeospatial":"Mt. Ruapehu","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 175.18450850284427,\n -38.81524047528322\n ],\n [\n 175.18450850284427,\n -39.6149627891337\n ],\n [\n 176.05242842471847,\n -39.6149627891337\n ],\n [\n 176.05242842471847,\n -38.81524047528322\n ],\n [\n 175.18450850284427,\n -38.81524047528322\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Douglas, Abbey","contributorId":298912,"corporation":false,"usgs":false,"family":"Douglas","given":"Abbey","email":"","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":856697,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kereszturi, Gabor 0000-0003-4336-2012","orcid":"https://orcid.org/0000-0003-4336-2012","contributorId":247601,"corporation":false,"usgs":false,"family":"Kereszturi","given":"Gabor","email":"","affiliations":[{"id":49587,"text":"Volcanic Risk Solutions, Massey University, Palmerston North, 4474, New Zealand","active":true,"usgs":false}],"preferred":false,"id":856698,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schaefer, Lauren N. 0000-0003-3216-7983","orcid":"https://orcid.org/0000-0003-3216-7983","contributorId":241997,"corporation":false,"usgs":true,"family":"Schaefer","given":"Lauren","email":"","middleInitial":"N.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":856699,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kennedy, Ben M. 0000-0001-7235-6493","orcid":"https://orcid.org/0000-0001-7235-6493","contributorId":270276,"corporation":false,"usgs":false,"family":"Kennedy","given":"Ben","email":"","middleInitial":"M.","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":856700,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70238436,"text":"70238436 - 2022 - Insight into Hurricane Maria peak flows from the development and application of the Precipitation-Runoff Modeling System (PRMS): Including Río Grande de Arecibo, Puerto Rico, 1981–2017","interactions":[],"lastModifiedDate":"2022-11-23T12:37:26.148964","indexId":"70238436","displayToPublicDate":"2022-11-04T06:33:28","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10778,"text":"Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Insight into Hurricane Maria peak flows from the development and application of the Precipitation-Runoff Modeling System (PRMS): Including Río Grande de Arecibo, Puerto Rico, 1981–2017","docAbstract":"
The Precipitation-Runoff Modeling System (PRMS) was used to develop a simulation of watershed hydrology on the island of Puerto Rico for the period 1981–2017, concentrating on the Río Grande de Arecibo, a river with some of the highest streamflows on the island. This development is part of the U.S. Geological Survey’s (USGS) National Hydrologic Model (NHM) infrastructure which supports coordinated, comprehensive, and consistent hydrologic modeling at the watershed scale for the coterminous United States (CONUS). A goal of the NHM program is to expand the domain outside of CONUS, leading to a PRMS application in Puerto Rico. This model was used to simulate the effects of Hurricane Maria on daily streamflow and provide information at locations where streamgages were damaged by the hurricane. Comparisons with streamflow estimates made by indirect methods in the field, up to ten times higher than simulated values, lends insight into the uncertainties in both the indirect methods and model simulated values and helps to identify potential error in the daily streamflow estimates. The PRMS can be applied to look at the effects of changes in climate and land use, water management, industrial and public water usage, and many other factors that affect hydrology on the island of Puerto Rico. The model is also designed as a support tool for the USGS National Water Census which provides comprehensive reporting of national information on withdrawal, conveyance, consumptive use, and return flow by water-use category.

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Lauderdale","active":true,"usgs":true}],"preferred":true,"id":857495,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bellino, Jason C. 0000-0001-9046-9344 jbellino@usgs.gov","orcid":"https://orcid.org/0000-0001-9046-9344","contributorId":3724,"corporation":false,"usgs":true,"family":"Bellino","given":"Jason","email":"jbellino@usgs.gov","middleInitial":"C.","affiliations":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"preferred":true,"id":857496,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70237995,"text":"70237995 - 2022 - Integrating Bayesian networks to forecast sea-level rise impacts on barrier island characteristics and habitat availability","interactions":[],"lastModifiedDate":"2022-11-03T17:07:22.337181","indexId":"70237995","displayToPublicDate":"2022-11-03T12:01:18","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5026,"text":"Earth and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"Integrating Bayesian networks to forecast sea-level rise impacts on barrier island characteristics and habitat availability","docAbstract":"

Evaluation of sea-level rise (SLR) impacts on coastal landforms and habitats is a persistent need for informing coastal planning and management, including policy decisions, particularly those that balance human interests and habitat protection throughout the coastal zone. Bayesian networks (BNs) are used to model barrier island change under different SLR scenarios that are relevant to management and policy decisions. BNs utilized here include a shoreline change model and two models of barrier island biogeomorphological evolution at different scales (50 and 5 m). These BNs were then linked to another BN to predict habitat availability for piping plovers (Charadrius melodus), a threatened shorebird reliant on beach habitats. We evaluated the performance of the two linked geomorphology BNs and further examined error rates by generating hindcasts of barrier island geomorphology and habitat availability for 2014 conditions. Geomorphology hindcasts revealed that model error declined with a greater number of known inputs, with error rates reaching 55% when multiple outputs were hindcast simultaneously. We also found that, although error in predictions of piping plover nest presence/absence increased when outputs from the geomorphology BNs were used as inputs in the piping plover habitat BN, the maximum error rate for piping plover habitat suitability in the fully-linked BNs was only 30%. Our findings suggest this approach may be useful for guiding scenario-based evaluations where known inputs can be used to constrain variables that produce higher uncertainty for morphological predictions. Overall, the approach demonstrates a way to assimilate data and model structures with uncertainty to produce forecasts to inform coastal planning and management.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022EA002286","usgsCitation":"Gutierrez, B.T., Zeigler, S., Lentz, E.E., Sturdivant, E., and Plant, N., 2022, Integrating Bayesian networks to forecast sea-level rise impacts on barrier island characteristics and habitat availability: Earth and Space Science, v. 9, no. 11, e2022EA002286, 24 p., https://doi.org/10.1029/2022EA002286.","productDescription":"e2022EA002286, 24 p.","ipdsId":"IP-133519","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":445946,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022ea002286","text":"Publisher Index Page"},{"id":435628,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R63EMY","text":"USGS data release","linkHelpText":"LinkedBNs_4Habitat - Matlab files to link Bayesian networks to generate habitat predictions"},{"id":409116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.29594026716985,\n 40.63299474223902\n ],\n [\n -73.3215230252425,\n 40.62686351437537\n ],\n [\n -73.31075133763278,\n 40.61664355031391\n ],\n [\n -73.26429843481641,\n 40.61766561708444\n ],\n [\n -73.18687693012288,\n 40.63299474223902\n ],\n [\n -73.03405361216147,\n 40.66823837708819\n ],\n [\n -72.97548256078474,\n 40.69019238633578\n ],\n [\n -72.90142720846879,\n 40.71673176155275\n ],\n [\n -72.75498136755509,\n 40.76126281049005\n ],\n [\n -72.75113811514511,\n 40.771161378285385\n ],\n [\n -72.79008117864493,\n 40.76709873688291\n ],\n [\n -72.82145002511935,\n 40.7537050773594\n ],\n [\n -72.84023809567569,\n 40.75014350867727\n ],\n [\n -72.87497858406178,\n 40.735821347504924\n ],\n [\n -72.91489181798045,\n 40.735609108172895\n ],\n [\n -72.93239581034598,\n 40.71979331664596\n ],\n [\n -72.98894717029637,\n 40.70040108981058\n ],\n [\n -73.00241177980864,\n 40.69019238633578\n ],\n [\n -73.07512067117331,\n 40.66977028676959\n ],\n [\n -73.19495569582996,\n 40.64729875129544\n ],\n [\n -73.26631812624335,\n 40.628907319545874\n ],\n [\n -73.29594026716985,\n 40.63299474223902\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"9","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Gutierrez, Benjamin T. 0000-0002-1879-7893 bgutierrez@usgs.gov","orcid":"https://orcid.org/0000-0002-1879-7893","contributorId":2924,"corporation":false,"usgs":true,"family":"Gutierrez","given":"Benjamin","email":"bgutierrez@usgs.gov","middleInitial":"T.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":856469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zeigler, Sara L. 0000-0002-5472-769X","orcid":"https://orcid.org/0000-0002-5472-769X","contributorId":222703,"corporation":false,"usgs":true,"family":"Zeigler","given":"Sara","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":856470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lentz, Erika E. 0000-0002-0621-8954 elentz@usgs.gov","orcid":"https://orcid.org/0000-0002-0621-8954","contributorId":173964,"corporation":false,"usgs":true,"family":"Lentz","given":"Erika","email":"elentz@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":856471,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sturdivant, Emily J.","contributorId":297196,"corporation":false,"usgs":false,"family":"Sturdivant","given":"Emily J.","affiliations":[{"id":56085,"text":"Woodwell Climate Research Center","active":true,"usgs":false}],"preferred":false,"id":856472,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Plant, Nathaniel 0000-0002-5703-5672","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":81234,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":856473,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237895,"text":"70237895 - 2022 - Klamath natural flow study, Upper Klamath Basin groundwater flow model","interactions":[],"lastModifiedDate":"2023-08-23T13:26:00.51571","indexId":"70237895","displayToPublicDate":"2022-11-03T09:13:58","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":21,"text":"Fact Sheet","active":false,"publicationSubtype":{"id":1}},"displayTitle":"Klamath Natural Flow Study, Upper Klamath Basin Groundwater Flow Model","title":"Klamath natural flow study, Upper Klamath Basin groundwater flow model","docAbstract":"

The purpose of the Upper Klamath Basin Groundwater Flow Model (UKBGFM) is to simulate groundwater conditions in the Upper Klamath Basin under historical and predevelopment conditions. The UKBGFM quantifies estimates of and changes in groundwater levels, storage, pumping, drainage flow to tile drains, evapotranspiration, and flow between the Upper Klamath Basin and neighboring basins. The quantifications of base flow to streams and seepage to and from lakes and reservoirs can be used as inputs to the RiverWare Mass Balance Model (Zagona and others, 2001), a companion model being developed as part of the Klamath Natural Flow Study (KNFS).

","language":"English","publisher":"U.S. Bureau of Reclamation","usgsCitation":"Traum, J.A., and Boyce, S.E., 2022, Klamath natural flow study, Upper Klamath Basin groundwater flow model: Fact Sheet, 2 p.","productDescription":"2 p.","ipdsId":"IP-145778","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":418055,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://www.usbr.gov/mp/kbao/docs/04-factsheet-gwmodeling-final.pdf"},{"id":418057,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Upper Klamath basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.54532325728275,\n 42.588031447169925\n ],\n [\n -124.57092240453784,\n 42.588031447169925\n ],\n [\n -124.57092240453784,\n 41.175\n ],\n [\n -121.54532325728275,\n 41.175\n ],\n [\n -121.54532325728275,\n 42.588031447169925\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Traum, Jonathan A. 0000-0002-4787-3680 jtraum@usgs.gov","orcid":"https://orcid.org/0000-0002-4787-3680","contributorId":4780,"corporation":false,"usgs":true,"family":"Traum","given":"Jonathan","email":"jtraum@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856125,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyce, Scott 0000-0003-0626-9492 seboyce@usgs.gov","orcid":"https://orcid.org/0000-0003-0626-9492","contributorId":4766,"corporation":false,"usgs":true,"family":"Boyce","given":"Scott","email":"seboyce@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856126,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238104,"text":"70238104 - 2022 - Plant community trajectories following livestock exclusion for conservation vary and hinge on initial invasion and soil-biocrust conditions in shrub steppe","interactions":[],"lastModifiedDate":"2022-12-15T15:37:49.27015","indexId":"70238104","displayToPublicDate":"2022-11-03T07:25:01","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Plant community trajectories following livestock exclusion for conservation vary and hinge on initial invasion and soil-biocrust conditions in shrub steppe","docAbstract":"

Adjustments or complete withdrawal of livestock grazing are among the most common conservation actions in semiarid uplands, but outcomes can vary considerably with ecological context. Invasion by exotic annual grasses and the excessive wildfire they promote are increasing threats to semiarid shrub-steppe, and plant-community response to livestock exclusion in these areas may be complicated by the rapid colonization ability of invaders. We evaluated vegetation-community changes over 14-year interval (2007–2021) in a shrub-steppe landscape where a >100-year history of livestock grazing had been terminated in 1996. Field surveys revealed that bare-soil exposure decreased >20% over the 14 years owing to biomass accumulation, but this was primarily due to large increases in exotic annual “cheatgrass” (Bromus tectorum, +1.8-fold) and the litter it produces (+1.5-fold). Soil biocrusts increased 11.9% and perennial bunchgrasses increased 3% over the 14 years. These community changes varied at the patch scale and entailed inverse relationships of (1) both cheatgrass and biocrusts to plant-community basal cover, (2) cheatgrass to both biocrusts and perennial grasses, and (3) biocrusts to cheatgrass and litter. The spatiotemporal variability in vegetation constituted changes in plant-community states, according to cluster analysis. The modeled probability of a community transitioning to a cheatgrass state was (1) strongly and positively related to the initial (2007) cover of cheatgrass in hotspots where initial cheatgrass cover was >20%, and (2) negatively related to biocrust cover where initial biocrust cover was >4% of ground area. The decision space for this landscape can be framed as a shifting from acceptance towards resisting further degradation by removing livestock and their trampling of soil surfaces and utilization of perennial herbs. However, cheatgrass appears to be the most impactful agent of change and continued invasion appears imminent. Active restoration may help resist further degradation and direct change towards tolerable conditions.

","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/csp2.12838","usgsCitation":"Germino, M., Kluender, C.R., and Anthony, C.R., 2022, Plant community trajectories following livestock exclusion for conservation vary and hinge on initial invasion and soil-biocrust conditions in shrub steppe: Conservation Science and Practice, v. 4, no. 12, e12838, 14 p., https://doi.org/10.1111/csp2.12838.","productDescription":"e12838, 14 p.","ipdsId":"IP-138776","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":445949,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.12838","text":"Publisher Index Page"},{"id":435629,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SO99W8","text":"USGS data release","linkHelpText":"Vegetation and soil cover data for long-term monitoring plots within Browns Park National Wildlife Refuge, Colorado, USA"},{"id":409290,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","county":"Moffat County","otherGeospatial":"Browns Park National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.04917851176388,\n 40.831912228720284\n ],\n [\n -109.0482710374729,\n 40.80650230407173\n ],\n [\n -109.04010376885081,\n 40.802380858575475\n ],\n [\n -109.02513044304374,\n 40.79001498646366\n ],\n [\n -109.00607348292577,\n 40.78039549350518\n ],\n [\n -108.9847478370798,\n 40.771805483132596\n ],\n [\n -108.96251471694198,\n 40.754622130399156\n ],\n [\n -108.93710543678475,\n 40.74774754543358\n ],\n [\n -108.86677617920702,\n 40.747403797528335\n ],\n [\n -108.87539718497439,\n 40.74774754543358\n ],\n [\n -108.87539718497439,\n 40.791045563782774\n ],\n [\n -108.89536161938372,\n 40.79173260644234\n ],\n [\n -108.89581535652943,\n 40.81199716659302\n ],\n [\n -108.94255028253308,\n 40.81302740265849\n ],\n [\n -108.94300401967877,\n 40.82367223859845\n ],\n [\n -108.95253249973753,\n 40.82367223859845\n ],\n [\n -108.95253249973753,\n 40.83397206626529\n ],\n [\n -108.97204319700117,\n 40.8346586645591\n ],\n [\n -108.97204319700117,\n 40.845643270193364\n ],\n [\n -109.01832438585872,\n 40.84530002882232\n ],\n [\n -109.0187781230044,\n 40.86623449905673\n ],\n [\n -109.02876034020929,\n 40.86589136435694\n ],\n [\n -109.02876034020929,\n 40.87412610643992\n ],\n [\n -109.0487247746186,\n 40.87412610643992\n ],\n [\n -109.04917851176388,\n 40.831912228720284\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"4","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Germino, Matthew J. 0000-0001-6326-7579 mgermino@usgs.gov","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":152582,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","email":"mgermino@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":856869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kluender, Chad Raymond 0000-0002-4108-4437","orcid":"https://orcid.org/0000-0002-4108-4437","contributorId":296077,"corporation":false,"usgs":true,"family":"Kluender","given":"Chad","email":"","middleInitial":"Raymond","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":856870,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anthony, Christopher R. 0000-0003-0968-224X","orcid":"https://orcid.org/0000-0003-0968-224X","contributorId":296314,"corporation":false,"usgs":true,"family":"Anthony","given":"Christopher","email":"","middleInitial":"R.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":856871,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70238071,"text":"70238071 - 2022 - Bulk and intramolecular carbon isotopic compositions of hydrocarbon gases from laboratory pyrolysis of oil shale of the Green River Formation: Implications for isotope structures of kerogens","interactions":[],"lastModifiedDate":"2022-11-08T12:56:15.194903","indexId":"70238071","displayToPublicDate":"2022-11-03T06:49:55","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Bulk and intramolecular carbon isotopic compositions of hydrocarbon gases from laboratory pyrolysis of oil shale of the Green River Formation: Implications for isotope structures of kerogens","docAbstract":"

Evaluation of intramolecular isotope distributions within organic compounds can provide important insights into gas formation processes and structural properties of gas-generating precursors, such as kerogen, bitumen, and oil, in natural reservoirs. Until recently, little has been known about the intramolecular isotope distributions within kerogens. In this study, we conducted systematic pyrolysis experiments of gas generation from a lacustrine oil shale of the Eocene Green River Formation under hydrous and anhydrous conditions (equivalent maturity or Easy %Ro: 0.76 to 3.27 at 310 to 480 °C for 3 to 50 days), measuring gas yields and compositions, as well as bulk and position-specific (PS) carbon isotope compositions. Gas generation processes were investigated in combination with kinetic Monte Carlo (kMC) simulations on a model Type I kerogen based on the chemical structures of oil shale of the Green River Formation. The comparison of our experimental results with kMC modelling indicates a series of β-scission, radical isomerization, and recombination reactions better represent the bulk isotope compositions of propane in the pyrolysis of the oil shale of the Green River Formation, but the ΔCc-t (= δ13Ccen – δ13Cter) values of propane at Easy %Ro > 1.5 can be better simulated by a simple combination of propyl groups with H radicals. Combining our previous works on marine shale of the Woodford Formation and Springfield Coal Member of the Carbondale Formation, PS carbon isotopes of propane indicate that in the lacustrine shales of the Green River Formation and the marine Woodford Shale, propane is sourced from C\"singleC bond cleavage, while C\"singleO bond cracking generates propane from coal at the initial kerogen cracking stage. At high maturity, the differences of late-stage propane production among the source rocks lead to the different bulk and PS C kinetic isotope effects of propane. Our findings suggest that the δ13C at the terminal position of propane precursors is likely up to 3.6‰ higher than at the central position in the Green River kerogen, while they are similar in the marine shale of Woodford Formation. In addition, the δ13C at the central position of propyl groups attached to heteroatom compounds is relatively more positive in the Springfield Coal Member of the Carbondale Formation than in Green River kerogen. A comparison of intramolecular C isotopes of propyl groups in the kerogens with their bulk δ13C, based on the PS δ13C of early-generated propane, contributes to our understanding of heterogeneities of isotopic structures of sedimentary organic matter.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2022.104141","usgsCitation":"Li, X., Birdwell, J.E., and Horita, J., 2022, Bulk and intramolecular carbon isotopic compositions of hydrocarbon gases from laboratory pyrolysis of oil shale of the Green River Formation: Implications for isotope structures of kerogens: International Journal of Coal Geology, v. 264, 104141, 14 p., https://doi.org/10.1016/j.coal.2022.104141.","productDescription":"104141, 14 p.","ipdsId":"IP-142309","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":409228,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"264","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Li, Xiaoqiang","contributorId":298943,"corporation":false,"usgs":false,"family":"Li","given":"Xiaoqiang","email":"","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":856753,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":856754,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Horita, Juske","contributorId":146205,"corporation":false,"usgs":false,"family":"Horita","given":"Juske","email":"","affiliations":[{"id":16625,"text":"Department of Geosciences, Texas Tech University, Lubbock, Texas","active":true,"usgs":false}],"preferred":false,"id":856755,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}