1. The relationships between macrophytes and the physical and biological characteristics of the environments that aquatic organisms inhabit are complex. Previous studies have shown that the macrophytes, Ranunculus (subgenus Batrachium), which are dominant in lowland chalk streams and widespread across Europe, can enhance juvenile Atlantic salmon abundance and growth to a greater degree than other physical and biological habitat characteristics. However, mechanistic understanding of how this effect might arise requires consideration of the direct and indirect relationships among habitat characteristics that are likely to be influenced by the presence of macrophyte cover.
2. We applied structural equation modelling to data collected during a 2-year in-river manipulative experiment in the River Frome (southern England, U.K.) designed to quantify the magnitude and the relative importance of direct and indirect influences of Ranunculus cover and other physical and biological variables, including water velocity, water depth, prey biomass and body size, and abundance of con- and hetero-specifics, on abundance and somatic growth of 0+ salmon.
3. Results indicated a strongly positive direct influence of Ranunculus cover on salmon abundance, as well as positive influences of Ranunculus on velocity heterogeneity and water depth that are indirectly related to decreased salmon abundance. Interestingly, there was no indication of a direct influence of Ranunculus cover on salmon growth, although Ranunculus was indirectly related to increased salmon growth through its positive influence on prey biomass, an effect mediated by velocity heterogeneity and proportion of fast velocities.
4. These findings provide novel mechanistic insights into the key role of Ranunculus in their native lowland rivers to enhance abundance and improve conditions for multiple food web components. Strategies to maintain or enhance naturally occurring Ranunculus in these rivers are therefore likely to return wide ranging ecosystem benefits, including for species of high conservation value, such as salmon. These mechanistic impacts on habitat heterogeneity and ecosystem productivity could generalise to native macrophytes in other river systems, particularly where habitat is dominated by vegetation in the absence of large substrates.
Since 2008, large-scale restoration programs have been implemented along the Willamette River, Oregon, to address historical losses of floodplain habitats caused by dam construction, bank protection, large wood removal, land conversion, and other anthropogenic influences. The Willamette Focused Investment Partnership (WFIP) restoration initiative brings together more than 16 organizations to improve floodplain habitats on more than 35,000 hectares upstream from Willamette Falls with the overarching goal to expand and enhance native fish habitats through the following restoration activities implemented along the floodplains and off-channel areas of the Willamette River: (A) modify floodplain topography and human-made barriers to inundation; (B) enhance gravel pits; (C) remove revetments; (D) construct off-channel features; (E) increase and enhance floodplain forest vegetation; and (F) treat aquatic invasive plant species (AIS). The WFIP Effectiveness Monitoring Program was initiated to inform future refinement of Willamette River restoration program goals and activities and has three goals: (1) evaluate the effectiveness of different restoration activities at increasing and enhancing native fish habitat, (2) improve overall understanding of the physical and ecological responses associated with different restoration activities undertaken by the WFIP, and (3) relate site-scale responses to restoration with broader patterns of fish communities, hydrogeomorphology, stream temperature, and vegetation across the Willamette River floodplain, so that the relative importance of restoration activities on habitat availability for native fish can be assessed.
A monitoring framework was developed to evaluate effectiveness of floodplain restoration activities at increasing and enhancing habitat for native fish in the Willamette River corridor, northwestern Oregon. This framework describes monitoring indicators, metrics, and approaches for evaluating responses in native fish communities and physical habitat conditions to restoration activities and determining effectiveness of restoration activities at improving habitats for native fish. The monitoring indicators and approaches are grouped into five restoration monitoring categories that are useful for characterizing ecological and physical habitat responses to restoration activities: fish, hydrogeomorphology, floodplain forest vegetation, birds, and AIS. This monitoring framework provides a common science foundation to support collaborative decisions on future interdisciplinary effectiveness monitoring activities for Willamette River restoration programs. To evaluate restoration effectiveness, data must be evaluated according to metrics and thresholds that permit direct comparison between habitat conditions at the restoration site and restoration program goals; this framework provides examples of metrics and thresholds for evaluating data, recognizing that the precise evaluation criteria for a particular site or program will need to be tailored to meet program questions and available resources. Refining restoration goals and activities as part of an adaptively managed process requires addressing critical uncertainties between restoration goals, restoration activities, and outcomes for habitats used by native fish. Although the monitoring activities of this framework will generate important datasets useful for evaluating restoration effectiveness, additional research, syntheses, and reporting is ultimately necessary to provide a common science foundation to support adaptively managed restoration programs. This report is intended as a resource for restoration program managers, practitioners, scientists, and contractors as they develop detailed annual monitoring plans for data collection and identify the monitoring indicators, metrics, and approaches that are appropriate for evaluating effectiveness of different restoration activities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221037","collaboration":"Prepared in cooperation with Benton Soil and Water Conservation District and Oregon Watershed Enhancement Board","usgsCitation":"Keith, M.K., Wallick, J.R., Flitcroft, R.L., Kock, T.J., Brown, L.A., Miller, R., Hagar, J.C., Guillozet, K., and Jones, K.L., 2022, Monitoring framework to evaluate effectiveness of aquatic and floodplain habitat restoration activities for native fish along the Willamette River, northwestern Oregon: U.S. Geological Survey Open-File Report 2022–1037, 116 p., https://doi.org/10.3133/ofr20221037.","productDescription":"Report: xi,116 p.; Data Reease","onlineOnly":"Y","ipdsId":"IP-117547","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":501771,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113503.htm","linkFileType":{"id":5,"text":"html"}},{"id":405744,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9N55MYW","text":"USGS data release","description":"USGS data release","linkHelpText":"Native and non-native fish species in the Willamette River Basin, Oregon"},{"id":405742,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1037/coverthb.jpg"},{"id":405743,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1037/ofr20221037.pdf","text":"Report","size":"77.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1037"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.42041015624999,\n 43.96119063892024\n ],\n [\n -122.36572265625,\n 43.96119063892024\n ],\n [\n -122.36572265625,\n 45.537136680398596\n ],\n [\n -123.42041015624999,\n 45.537136680398596\n ],\n [\n -123.42041015624999,\n 43.96119063892024\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Understanding the effects of extreme weather on animal populations is fundamental to ecological and conservation sciences and species management. Climate change has resulted in both warm and cold temperature extremes, including an increased frequency of severe cold snaps at middle latitudes in North America. These unusually cold air masses cause rapid declines in nearshore ocean temperatures in coastal areas, with detrimental effects on marine organisms. Acute cold-stun events (hereafter cold stuns) occur when hundreds to thousands of resident juvenile sea turtles fail to escape shallow water during cold snaps. Human intervention through rescue and recovery largely mitigates direct juvenile sea turtle mortality, but delayed effects of cold stuns on rescued individuals are not well understood. Our objective was to examine long-term juvenile green turtle (Chelonia mydas) survival across four cold stuns of varying severity in St. Joseph Bay, Florida, between 2010 and 2018. We used the classic Cormack–Jolly–Seber model in a hierarchical Bayesian framework to estimate apparent survival (i.e., emigration and mortality) of rescued turtles at different time intervals. Our results indicated about half of a cohort rescued during a severe cold stun in January 2010 likely remained in the population 1 year later, with 10%–20% remaining 4 years later, and as few as 5% by 2018. The results also suggested higher apparent survival for cohorts rescued during two subsequent milder cold stuns. Emigration was a more plausible ecological explanation for low apparent survival than delayed mortality. Potential ecological mechanisms underlying emigration include a reduction in food availability and a behavioral response to either the severe weather event or handling during rescue (or both). However, the typical annual turnover of juvenile green turtles, though assumed low, is not well known in St. Joseph Bay. Thus, our apparent survival estimates may be reflective of higher-than-expected emigration in the broader population. Our study provides important baseline information about long-term juvenile sea turtle survival after cold stuns in temperate regions. We also highlight the importance of strategic monitoring between cold stuns to examine additional ecological questions.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4221","usgsCitation":"Mollenhauer, R.M., Lamont, M., and Foley, A.M., 2022, Long-term apparent survival of a cold-stunned subpopulation of juveniles green turtles: Ecosphere, e4221, 14 p., https://doi.org/10.1002/ecs2.4221.","productDescription":"e4221, 14 p.","ipdsId":"IP-133328","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":446509,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4221","text":"Publisher Index Page"},{"id":406608,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"St Joseph Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.43243408203125,\n 29.673735421779128\n ],\n [\n -85.29579162597655,\n 29.673735421779128\n ],\n [\n -85.29579162597655,\n 29.891257492496305\n ],\n [\n -85.43243408203125,\n 29.891257492496305\n ],\n [\n -85.43243408203125,\n 29.673735421779128\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2022-09-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Mollenhauer, Robert Michael 0000-0002-4033-8685","orcid":"https://orcid.org/0000-0002-4033-8685","contributorId":290165,"corporation":false,"usgs":true,"family":"Mollenhauer","given":"Robert","email":"","middleInitial":"Michael","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":848930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lamont, Margaret 0000-0001-7520-6669","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":222403,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":848931,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foley, Allen M.","contributorId":195874,"corporation":false,"usgs":false,"family":"Foley","given":"Allen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":848932,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70256679,"text":"70256679 - 2022 - Predation probabilities and functional responses: How piscivorous waterbirds respond to pulses in fish abundance","interactions":[],"lastModifiedDate":"2024-09-06T17:06:22.193305","indexId":"70256679","displayToPublicDate":"2022-09-06T09:54:48","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":"Predation probabilities and functional responses: How piscivorous waterbirds respond to pulses in fish abundance","docAbstract":"How predators respond to changes in prey abundance (i.e., functional responses) is foundational to consumer–resource interactions, predator–prey dynamics, and the stability of predator–prey systems. Predation by piscivorous waterbirds on out-migrating juvenile steelhead trout (Oncorhynchus mykiss) is considered a factor affecting the recovery of multiple Endangered Species Act-listed steelhead populations in the Columbia River basin. Waterbird functional responses, however, may vary by predator species and location, with important implications to predator management strategies. We used a 13-year dataset on waterbird abundance across seven breeding colonies (three Caspian tern [Hydroprogne caspia], two double-crested cormorant [Nannopterum auritum], and two California and ring-billed gull [Larus californicus and Larus delawarensis] colonies) and steelhead tag-recovery data (>645,000 tagged and >32,000 recovered steelhead) to quantify weekly predation probabilities and functional responses across waterbird species, colonies, and years. Weekly predation probabilities were highly variable, ranging from 0.01 to 0.30 at tern colonies, 0.01 to 0.20 at cormorant colonies, and 0.03 to 0.13 at gull colonies. Per capita predation probabilities were an order of magnitude higher at inland tern and cormorant colonies relative to estuary colonies of the same species. Terns displayed Type II functional responses across colonies and years, where predation probabilities peaked at low steelhead abundances and declined as steelhead abundance increased (i.e., predator swamping). Cormorants nesting at the large estuary colony (several thousand birds) displayed a Type III functional response, but cormorants nesting at the smaller inland colony (several hundred birds) displayed a Type II response. Consumption probabilities of steelhead by gulls remained consistent across a large range of steelhead availability, suggesting a Type I or a Type III functional response, but a lack of colony abundance data prevented quantifying functional responses. The level of tern predation combined with Type II functional responses indicate possible population-level impacts that could destabilize small or declining prey populations. Conversely, the apparent Type III functional responses of gulls and estuary nesting cormorants are indicative of prey switching behaviors targeted at periods of high steelhead abundance. Our results illustrate the complexity of predator–prey interactions and the importance of quantifying predator- and location-specific functional responses when predicting the efficacy of management strategies to enhance prey populations.
","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.4220","usgsCitation":"Hostetter, N.J., Payton, Q., Roby, D., Collis, K., and Evans, A., 2022, Predation probabilities and functional responses: How piscivorous waterbirds respond to pulses in fish abundance: Ecosphere, v. 13, no. 9, e4220, 15 p., https://doi.org/10.1002/ecs2.4220.","productDescription":"e4220, 15 p.","ipdsId":"IP-131458","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":446512,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4220","text":"Publisher Index Page"},{"id":433574,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Columbia River basin","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-116.915989,45.995413],[-116.892935,45.974396],[-116.859795,45.907264],[-116.796051,45.858473],[-116.782676,45.825376],[-116.759787,45.816167],[-116.736268,45.826179],[-116.711822,45.826267],[-116.698079,45.820852],[-116.665344,45.781998],[-116.593004,45.778541],[-116.546643,45.750972],[-116.535698,45.734231],[-116.535396,45.691734],[-116.487894,45.649769],[-116.463504,45.615785],[-116.463635,45.602785],[-116.481943,45.577898],[-116.523638,45.54661],[-116.553473,45.499107],[-116.554829,45.46293],[-116.588195,45.44292],[-116.597447,45.41277],[-116.619057,45.39821],[-116.673793,45.321511],[-116.674493,45.276349],[-116.691388,45.263739],[-116.703607,45.239757],[-116.729607,45.142091],[-116.754643,45.113972],[-116.774847,45.105536],[-116.797329,45.060267],[-116.847944,45.022602],[-116.844625,45.001435],[-116.858313,44.978761],[-116.83199,44.933007],[-116.852427,44.887577],[-116.931099,44.804781],[-116.9347,44.783881],[-116.970902,44.773881],[-116.998903,44.756382],[-117.03827,44.748179],[-117.062273,44.727143],[-117.061799,44.706654],[-117.095868,44.664737],[-117.098221,44.640689],[-117.120522,44.614658],[-117.124754,44.583834],[-117.148255,44.564371],[-117.14293,44.557236],[-117.149242,44.536151],[-117.161033,44.525166],[-117.181583,44.52296],[-117.200237,44.492027],[-117.224104,44.483734],[-117.215072,44.427162],[-117.22698,44.405583],[-117.242675,44.396548],[-117.235117,44.373853],[-117.189769,44.336585],[-117.203323,44.313024],[-117.222451,44.298963],[-117.198147,44.273828],[-117.170342,44.25889],[-117.143394,44.258262],[-117.121037,44.277585],[-117.104208,44.27994],[-117.089503,44.258234],[-117.05303,44.229076],[-117.031862,44.248635],[-116.975905,44.242844],[-116.971675,44.197256],[-116.925392,44.191544],[-116.900103,44.176851],[-116.894083,44.160191],[-116.933704,44.100039],[-116.977351,44.085364],[-116.973185,44.049425],[-116.943361,44.035645],[-116.934485,44.021249],[-116.942346,43.989106],[-116.971436,43.964998],[-116.96247,43.928336],[-116.977332,43.905812],[-116.982347,43.86884],[-117.01077,43.862269],[-117.02678,43.829841],[-117.026222,42.000252],[-118.696409,41.991794],[-119.872929,41.997641],[-121.035195,41.993323],[-122.378193,42.009518],[-122.893961,42.002605],[-123.145959,42.009247],[-123.656998,41.995137],[-124.126194,41.996992],[-124.211605,41.99846],[-124.270464,42.045553],[-124.299649,42.051736],[-124.356229,42.114952],[-124.351784,42.134965],[-124.366832,42.15845],[-124.360318,42.162272],[-124.361009,42.180752],[-124.374949,42.193129],[-124.383633,42.22716],[-124.410982,42.250547],[-124.405148,42.278107],[-124.410556,42.307431],[-124.429288,42.331746],[-124.424863,42.395426],[-124.435105,42.440163],[-124.422038,42.461226],[-124.421381,42.491737],[-124.390664,42.566593],[-124.400918,42.597518],[-124.401177,42.627192],[-124.416774,42.661594],[-124.45074,42.675798],[-124.448418,42.689909],[-124.473864,42.732671],[-124.491679,42.741789],[-124.513368,42.735068],[-124.524439,42.789793],[-124.552441,42.840568],[-124.500141,42.917502],[-124.456918,43.000315],[-124.436198,43.071312],[-124.434451,43.115986],[-124.401726,43.184896],[-124.38246,43.270167],[-124.402814,43.305872],[-124.373037,43.338953],[-124.341587,43.351337],[-124.315012,43.388389],[-124.233534,43.55713],[-124.168392,43.808903],[-124.150267,43.91085],[-124.122406,44.104442],[-124.125824,44.12613],[-124.108945,44.265475],[-124.1152,44.286486],[-124.084401,44.415611],[-124.067569,44.428582],[-124.079301,44.430863],[-124.084429,44.486927],[-124.067251,44.60804],[-124.084476,44.611056],[-124.065202,44.622445],[-124.058281,44.658866],[-124.070394,44.683514],[-124.059077,44.737656],[-124.075473,44.771403],[-124.074066,44.798107],[-124.066746,44.831191],[-124.048814,44.850007],[-124.025136,44.928175],[-124.004598,45.044959],[-124.017991,45.049808],[-124.015851,45.064759],[-124.006057,45.084736],[-123.989529,45.094045],[-123.975425,45.145476],[-123.964169,45.317026],[-123.972899,45.33689],[-124.007756,45.336813],[-123.973398,45.354791],[-123.965728,45.386242],[-123.960557,45.430778],[-123.976544,45.489733],[-123.96634,45.493417],[-123.957568,45.510399],[-123.947556,45.564878],[-123.956711,45.571303],[-123.939005,45.661923],[-123.943121,45.727031],[-123.968563,45.757019],[-123.982578,45.761815],[-123.969459,45.782371],[-123.962736,45.869974],[-123.96763,45.907807],[-123.993703,45.946431],[-123.969991,45.969139],[-123.937471,45.977306],[-123.927891,46.009564],[-123.933366,46.071672],[-123.947531,46.116131],[-123.996766,46.20399],[-124.010344,46.223514],[-124.024305,46.229256],[-124.001998,46.237316],[-123.988429,46.224132],[-123.987196,46.211521],[-123.950148,46.204097],[-123.9042,46.169293],[-123.854801,46.157342],[-123.842849,46.160529],[-123.841521,46.169824],[-123.863347,46.18235],[-123.864209,46.189527],[-123.821834,46.190293],[-123.759976,46.2073],[-123.71278,46.198751],[-123.666751,46.218228],[-123.636474,46.214359],[-123.622812,46.23664],[-123.605487,46.2393],[-123.586205,46.228654],[-123.548194,46.248245],[-123.547636,46.265595],[-123.613544,46.259988],[-123.669501,46.266832],[-123.679125,46.272502],[-123.680574,46.296025],[-123.700764,46.305278],[-123.724273,46.301161],[-123.727913,46.289661],[-123.741478,46.290274],[-123.766682,46.273499],[-123.806139,46.283588],[-123.875525,46.239787],[-123.909306,46.245491],[-123.954353,46.277001],[-123.974509,46.303063],[-124.020551,46.315737],[-124.044018,46.275925],[-124.060961,46.278761],[-124.082187,46.269159],[-124.064624,46.326899],[-124.057425,46.409315],[-124.068655,46.634879],[-124.048444,46.645827],[-124.035874,46.630822],[-124.052708,46.622796],[-124.050842,46.617421],[-124.023566,46.582559],[-124.031737,46.496375],[-124.026032,46.462978],[-123.990615,46.463019],[-123.99268,46.488617],[-123.983688,46.498542],[-123.968044,46.473497],[-123.943667,46.477197],[-123.921192,46.507731],[-123.896703,46.522665],[-123.894254,46.537028],[-123.928861,46.588875],[-123.955556,46.60357],[-123.960642,46.636364],[-123.921913,46.650262],[-123.923269,46.672708],[-123.851356,46.70256],[-123.84621,46.716795],[-123.898641,46.750205],[-123.916371,46.741322],[-123.916874,46.726739],[-123.948683,46.725369],[-123.974994,46.733391],[-123.979655,46.724658],[-123.966886,46.705184],[-123.994242,46.707929],[-124.003458,46.702337],[-124.092176,46.741624],[-124.108078,46.836388],[-124.138225,46.905534],[-124.110641,46.91252],[-124.093392,46.901168],[-124.089286,46.867716],[-124.073113,46.861493],[-124.055085,46.870429],[-124.046344,46.893972],[-123.985082,46.921916],[-123.957493,46.921261],[-123.86018,46.948556],[-123.898245,46.971927],[-123.939214,46.969739],[-123.959185,46.981759],[-124.012218,46.985176],[-124.019727,46.991189],[-124.005248,47.003915],[-124.026345,47.030187],[-124.065856,47.04114],[-124.122057,47.04165],[-124.141517,47.035142],[-124.151288,47.021112],[-124.124386,46.94387],[-124.180111,46.926357],[-124.169113,46.994508],[-124.182802,47.134041],[-124.236349,47.287287],[-124.25359,47.30248],[-124.271193,47.305025],[-124.299943,47.34836],[-124.319379,47.355559],[-124.336724,47.415996],[-124.355955,47.545698],[-124.425195,47.738434],[-124.453927,47.765334],[-124.47657,47.769671],[-124.489737,47.816988],[-124.539927,47.836967],[-124.562363,47.866216],[-124.625512,47.887963],[-124.645442,47.935338],[-124.672427,47.964414],[-124.682157,48.035987],[-124.696542,48.069274],[-124.687101,48.098657],[-124.733174,48.163393],[-124.696111,48.198599],[-124.690389,48.219745],[-124.705031,48.238774],[-124.684677,48.255228],[-124.676319,48.295143],[-124.665908,48.299324],[-124.65894,48.331057],[-124.727022,48.371101],[-124.731828,48.381157],[-124.725839,48.386012],[-124.653243,48.390691],[-124.631108,48.376522],[-124.599278,48.381035],[-124.395593,48.288772],[-124.361351,48.287582],[-124.272017,48.25441],[-124.250882,48.264773],[-124.238582,48.262471],[-124.101773,48.216883],[-124.107215,48.200082],[-124.050734,48.177747],[-123.981032,48.164761],[-123.858821,48.154273],[-123.71835,48.158713],[-123.702743,48.166783],[-123.651408,48.156952],[-123.628819,48.139279],[-123.590839,48.134949],[-123.551131,48.151382],[-123.507235,48.131807],[-123.440128,48.142014],[-123.441972,48.124259],[-123.424668,48.118065],[-123.332699,48.11297],[-123.288265,48.121036],[-123.239129,48.118217],[-123.1644,48.165894],[-123.133445,48.177276],[-123.143229,48.156633],[-123.116479,48.150208],[-123.06621,48.120469],[-123.038727,48.081138],[-122.979413,48.09594],[-122.929095,48.096244],[-122.917942,48.091535],[-122.927975,48.06665],[-122.877641,48.047025],[-122.849273,48.053808],[-122.878255,48.076072],[-122.882013,48.100779],[-122.876282,48.110877],[-122.833173,48.134406],[-122.760448,48.14324],[-122.748911,48.117026],[-122.778466,48.106135],[-122.801399,48.087561],[-122.766648,48.04429],[-122.74229,48.049324],[-122.739271,48.069153],[-122.747389,48.070795],[-122.733257,48.091232],[-122.68724,48.101662],[-122.69222,48.087081],[-122.682264,48.042723],[-122.668942,48.032026],[-122.669868,48.017217],[-122.686898,48.008305],[-122.70184,48.016106],[-122.723374,48.008095],[-122.718082,47.987739],[-122.701294,47.972979],[-122.6788,47.96793],[-122.68445,47.939593],[-122.657722,47.931156],[-122.651063,47.920985],[-122.655085,47.905058],[-122.646494,47.894771],[-122.610341,47.887343],[-122.63636,47.866186],[-122.69376,47.868002],[-122.681602,47.850405],[-122.683742,47.838773],[-122.748061,47.800546],[-122.758498,47.746036],[-122.781682,47.70392],[-122.811929,47.679861],[-122.832139,47.695511],[-122.790619,47.792597],[-122.812616,47.840029],[-122.820178,47.835904],[-122.815027,47.807493],[-122.845612,47.777474],[-122.880462,47.720643],[-122.896524,47.674838],[-122.97244,47.6149],[-123.106486,47.45817],[-123.15598,47.355745],[-123.140169,47.347496],[-123.111298,47.362619],[-123.120234,47.39149],[-122.967284,47.585685],[-122.917103,47.620743],[-122.856611,47.649615],[-122.804498,47.653363],[-122.754186,47.671612],[-122.740159,47.736228],[-122.722686,47.748827],[-122.714801,47.768176],[-122.690562,47.778372],[-122.682015,47.800882],[-122.623192,47.836199],[-122.608105,47.856728],[-122.573672,47.857582],[-122.588235,47.912923],[-122.616701,47.925139],[-122.617022,47.938987],[-122.603861,47.940478],[-122.592184,47.922519],[-122.549072,47.919072],[-122.527593,47.905882],[-122.513986,47.880807],[-122.506122,47.831745],[-122.482529,47.815511],[-122.495458,47.786692],[-122.471402,47.765965],[-122.470333,47.757109],[-122.471844,47.749819],[-122.488491,47.743605],[-122.554454,47.745704],[-122.543161,47.710941],[-122.53094,47.704814],[-122.511196,47.708715],[-122.504604,47.699136],[-122.518277,47.65132],[-122.493205,47.635122],[-122.49824,47.598242],[-122.479089,47.583654],[-122.518367,47.57408],[-122.543118,47.556326],[-122.546611,47.52355],[-122.52305,47.524],[-122.494882,47.510265],[-122.530514,47.469041],[-122.531889,47.428827],[-122.551136,47.394456],[-122.537044,47.375896],[-122.575985,47.32642],[-122.547521,47.285344],[-122.578211,47.254804],[-122.589454,47.227618],[-122.611464,47.2181],[-122.668571,47.270449],[-122.697378,47.283969],[-122.671256,47.343774],[-122.632463,47.376394],[-122.671486,47.366876],[-122.725738,47.33047],[-122.749621,47.276408],[-122.641802,47.205013],[-122.673925,47.174675],[-122.691771,47.141958],[-122.711997,47.127681],[-122.771619,47.167109],[-122.832799,47.243412],[-122.816633,47.276457],[-122.799025,47.289306],[-122.796646,47.341654],[-122.803688,47.355071],[-122.821868,47.363069],[-122.822344,47.319763],[-122.863732,47.270221],[-122.856171,47.233788],[-122.838298,47.208353],[-122.85994,47.165574],[-122.814238,47.179482],[-122.775056,47.123114],[-122.721437,47.103179],[-122.67813,47.103866],[-122.650634,47.132738],[-122.631987,47.140589],[-122.614855,47.169143],[-122.590829,47.178107],[-122.561957,47.244099],[-122.527586,47.291531],[-122.547747,47.316403],[-122.533338,47.31662],[-122.4442,47.266723],[-122.429605,47.269707],[-122.409199,47.288556],[-122.444635,47.300421],[-122.443008,47.306333],[-122.423535,47.319121],[-122.324833,47.348521],[-122.328434,47.400621],[-122.348035,47.415921],[-122.355135,47.441921],[-122.383136,47.450521],[-122.368036,47.459221],[-122.361336,47.481421],[-122.396538,47.51522],[-122.398338,47.55012],[-122.421139,47.57602],[-122.387139,47.59572],[-122.370167,47.583087],[-122.342937,47.59122],[-122.339513,47.599113],[-122.367819,47.624213],[-122.414645,47.639766],[-122.429841,47.658919],[-122.38044,47.709119],[-122.37314,47.729219],[-122.380241,47.758519],[-122.396422,47.777927],[-122.394944,47.803318],[-122.33595,47.852306],[-122.328546,47.897917],[-122.311927,47.923703],[-122.307048,47.949117],[-122.249007,47.959507],[-122.230046,47.970917],[-122.224979,48.016626],[-122.231761,48.029876],[-122.281087,48.049793],[-122.326119,48.092877],[-122.343241,48.097631],[-122.363842,48.12393],[-122.370253,48.164809],[-122.362044,48.187568],[-122.395499,48.228551],[-122.433767,48.23655],[-122.449605,48.232598],[-122.449513,48.214736],[-122.442051,48.20935],[-122.478535,48.188087],[-122.479008,48.175703],[-122.442383,48.130841],[-122.379481,48.087384],[-122.358375,48.056133],[-122.377114,48.057568],[-122.400692,48.085255],[-122.4675,48.130353],[-122.489986,48.120617],[-122.512031,48.133931],[-122.53722,48.183745],[-122.530996,48.249821],[-122.503786,48.257045],[-122.480925,48.251706],[-122.463962,48.270541],[-122.406516,48.25183],[-122.371693,48.287839],[-122.408718,48.326413],[-122.442678,48.337934],[-122.475529,48.359912],[-122.507437,48.364666],[-122.533452,48.383409],[-122.539449,48.39719],[-122.554536,48.40604],[-122.558403,48.426758],[-122.551221,48.439465],[-122.557298,48.444438],[-122.575254,48.443333],[-122.581607,48.429244],[-122.61448,48.41488],[-122.649839,48.408526],[-122.674158,48.424726],[-122.678928,48.439466],[-122.654844,48.454087],[-122.657753,48.47294],[-122.689121,48.476849],[-122.700603,48.457632],[-122.712322,48.464143],[-122.712981,48.47879],[-122.701644,48.497622],[-122.684521,48.509123],[-122.671386,48.50398],[-122.606961,48.522152],[-122.598469,48.512169],[-122.568071,48.50821],[-122.537355,48.466749],[-122.500721,48.460887],[-122.471832,48.470724],[-122.498463,48.556206],[-122.504428,48.564775],[-122.534719,48.574246],[-122.495904,48.575927],[-122.478431,48.559303],[-122.44456,48.570115],[-122.425271,48.599522],[-122.500308,48.656163],[-122.519172,48.713095],[-122.490401,48.751128],[-122.535803,48.776128],[-122.567498,48.779185],[-122.596844,48.771492],[-122.637146,48.735708],[-122.612562,48.714932],[-122.605733,48.701066],[-122.615169,48.693839],[-122.630422,48.696625],[-122.673472,48.733082],[-122.646777,48.785011],[-122.693683,48.804475],[-122.699303,48.789063],[-122.709815,48.786205],[-122.717073,48.84719],[-122.793175,48.892927],[-122.751289,48.911239],[-122.746596,48.930731],[-122.766096,48.941955],[-122.787539,48.931702],[-122.821631,48.941369],[-122.817226,48.95597],[-122.774276,48.991038],[-122.756318,48.996881],[-122.75802,49.002357],[-117.032351,48.999188],[-117.042623,47.761223],[-117.039813,46.425425],[-117.034696,46.418318],[-117.062748,46.353624],[-117.023844,46.335976],[-117.020663,46.314793],[-116.986688,46.296662],[-116.991134,46.276342],[-116.966742,46.256923],[-116.955264,46.23088],[-116.965841,46.203417],[-116.92187,46.167808],[-116.950276,46.123464],[-116.955263,46.102237],[-116.982479,46.089389],[-116.978938,46.080007],[-116.957372,46.075449],[-116.942656,46.061],[-116.915989,45.995413]]],[[[-122.519535,48.288314],[-122.551793,48.281512],[-122.584086,48.297987],[-122.618466,48.294159],[-122.626757,48.288991],[-122.620748,48.282961],[-122.623779,48.269431],[-122.652639,48.265081],[-122.66921,48.240614],[-122.668385,48.223967],[-122.628352,48.222467],[-122.588138,48.18594],[-122.558205,48.119579],[-122.571853,48.102143],[-122.54512,48.05255],[-122.513994,48.059077],[-122.511081,48.075301],[-122.525422,48.096537],[-122.513276,48.097538],[-122.491104,48.094242],[-122.431266,48.045001],[-122.376259,48.034457],[-122.373263,48.000791],[-122.353611,47.981433],[-122.349597,47.958796],[-122.358812,47.93742],[-122.376837,47.923703],[-122.380497,47.904023],[-122.431035,47.914732],[-122.445519,47.930226],[-122.44076,47.951845],[-122.446682,47.963155],[-122.47266,47.988449],[-122.501257,47.987089],[-122.521219,47.972997],[-122.546824,47.967215],[-122.552053,47.973644],[-122.542924,47.996404],[-122.58178,48.010386],[-122.607342,48.030992],[-122.593621,48.0472],[-122.614028,48.072788],[-122.598301,48.110616],[-122.609568,48.15186],[-122.633167,48.163281],[-122.677337,48.154587],[-122.693084,48.181509],[-122.770045,48.224395],[-122.72259,48.304268],[-122.673731,48.354683],[-122.664928,48.374823],[-122.664659,48.401508],[-122.634991,48.404244],[-122.637892,48.395681],[-122.60198,48.409907],[-122.595351,48.3972],[-122.585038,48.395166],[-122.585162,48.353304],[-122.551334,48.342138],[-122.506568,48.310041],[-122.505828,48.297677],[-122.519535,48.288314]]],[[[-122.474684,47.511068],[-122.452399,47.503471],[-122.460027,47.48686],[-122.433385,47.46643],[-122.439415,47.458633],[-122.437656,47.407424],[-122.373628,47.388718],[-122.437809,47.365606],[-122.453997,47.343337],[-122.469702,47.344623],[-122.493122,47.330253],[-122.51885,47.33332],[-122.528128,47.345542],[-122.517797,47.368678],[-122.526733,47.398581],[-122.514703,47.414048],[-122.513328,47.449106],[-122.497862,47.475915],[-122.482739,47.483133],[-122.474684,47.511068]]],[[[-122.695907,48.737273],[-122.663259,48.697077],[-122.618225,48.670721],[-122.609576,48.645018],[-122.635299,48.651846],[-122.673538,48.680809],[-122.691795,48.711498],[-122.718833,48.716818],[-122.722262,48.731624],[-122.715709,48.748672],[-122.695907,48.737273]]],[[[-123.035393,49.002154],[-123.021459,48.977299],[-123.028091,48.973943],[-123.083834,48.976139],[-123.090546,49.001976],[-123.035393,49.002154]]],[[[-122.800217,48.60169],[-122.801096,48.585425],[-122.770349,48.558106],[-122.788503,48.530393],[-122.777467,48.517799],[-122.779124,48.508911],[-122.817912,48.483888],[-122.81973,48.458843],[-122.803521,48.428748],[-122.812208,48.422326],[-122.874135,48.418196],[-122.893646,48.422655],[-122.889016,48.435947],[-122.928004,48.439966],[-122.91646,48.453263],[-122.926901,48.460874],[-122.962009,48.451161],[-123.039156,48.460003],[-123.067675,48.479497],[-123.119451,48.492576],[-123.163234,48.529544],[-123.16147,48.547618],[-123.176266,48.562131],[-123.173061,48.579086],[-123.197754,48.586216],[-123.203026,48.596178],[-123.178425,48.622115],[-123.107362,48.622451],[-123.098462,48.612834],[-123.101552,48.59782],[-123.074611,48.591816],[-123.048403,48.569216],[-122.987296,48.561895],[-122.995026,48.578162],[-123.016647,48.580244],[-123.034101,48.591767],[-123.023433,48.599477],[-123.04653,48.61149],[-123.048652,48.621002],[-122.949116,48.693398],[-122.942367,48.706723],[-122.894599,48.71503],[-122.743049,48.661991],[-122.809622,48.619035],[-122.800217,48.60169]]],[[[-123.197953,48.68466],[-123.14799,48.668001],[-123.106165,48.633473],[-123.134956,48.63724],[-123.237148,48.683466],[-123.236567,48.68895],[-123.212892,48.689713],[-123.197953,48.68466]]],[[[-123.025486,48.717966],[-123.007511,48.718863],[-123.005086,48.694342],[-123.021215,48.681416],[-123.042337,48.675663],[-123.03636,48.69008],[-123.070427,48.699971],[-123.040179,48.717296],[-123.025486,48.717966]]],[[[-122.649405,48.588457],[-122.578856,48.54813],[-122.572967,48.529028],[-122.599948,48.536904],[-122.635738,48.526021],[-122.649256,48.528769],[-122.654342,48.537956],[-122.649405,48.588457]]],[[[-122.714512,48.60878],[-122.670638,48.568812],[-122.68944,48.543903],[-122.722407,48.540606],[-122.73944,48.573893],[-122.739898,48.583949],[-122.714512,48.60878]]],[[[-122.699266,48.621115],[-122.674173,48.629944],[-122.657016,48.609891],[-122.676796,48.610055],[-122.699266,48.621115]]],[[[-122.334524,48.018916],[-122.321721,48.019977],[-122.303455,48.005603],[-122.334524,48.018916]]]]},\"properties\":{\"name\":\"Oregon\",\"nation\":\"USA \"}}]}","volume":"13","issue":"9","noUsgsAuthors":false,"publicationDate":"2022-09-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Hostetter, Nathan J. 0000-0001-6075-2157 nhostetter@usgs.gov","orcid":"https://orcid.org/0000-0001-6075-2157","contributorId":198843,"corporation":false,"usgs":true,"family":"Hostetter","given":"Nathan","email":"nhostetter@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":908624,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Payton, Q.","contributorId":341565,"corporation":false,"usgs":false,"family":"Payton","given":"Q.","email":"","affiliations":[{"id":39334,"text":"Real Time Research","active":true,"usgs":false}],"preferred":false,"id":908625,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roby, D.D.","contributorId":341566,"corporation":false,"usgs":false,"family":"Roby","given":"D.D.","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":908626,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collis, K.","contributorId":341567,"corporation":false,"usgs":false,"family":"Collis","given":"K.","affiliations":[{"id":39334,"text":"Real Time Research","active":true,"usgs":false}],"preferred":false,"id":908627,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Evans, A.F.","contributorId":341568,"corporation":false,"usgs":false,"family":"Evans","given":"A.F.","affiliations":[{"id":39334,"text":"Real Time Research","active":true,"usgs":false}],"preferred":false,"id":908628,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70236388,"text":"70236388 - 2022 - Characterization of vegetated and ponded wetlands with implications towards coastal wetland marsh collapse","interactions":[],"lastModifiedDate":"2023-06-08T14:54:19.254192","indexId":"70236388","displayToPublicDate":"2022-09-05T10:14:05","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1198,"text":"Catena","active":true,"publicationSubtype":{"id":10}},"title":"Characterization of vegetated and ponded wetlands with implications towards coastal wetland marsh collapse","docAbstract":"Coastal wetlands provide numerous ecosystem services; yet these ecosystems are increasingly vulnerable to climate change stressors, especially excessive flooding from sea-level rise and storm events. This study highlights the important contribution of vegetation belowground biomass to marsh stability and identifies loss of vegetation as a critical driver of marsh collapse. We investigated the shear strength of salt marshes and unvegetated interior ponds using a modified cone penetrometer along a chronosequence of wetland marsh collapse (0 to 21 + years following pond formation) to characterize changes in the structural integrity of the marsh soil. Following conversion from vegetated marsh to open water pond, the surficial soils experienced a dramatic loss in shear strength resulting from the loss of vegetation and compaction of soil pore space. The Cone Penetrometer Testing (CPT) data indicate that higher shear strength in the surficial layers of the vegetated marsh sites were never recovered, up to 21 + years following marsh collapse. Coupled with significant elevation loss from marsh collapse, additional sea-level rise, deep subsidence, and reduced sedimentation may contribute to conditions that can exceed critical flooding thresholds, making recovery from marsh collapse difficult or impossible. Therefore, characterizing mechanisms and thresholds of marsh collapse are critical for identifying those coastal marshes that are vulnerable to collapse before conversion from vegetated marsh to open water occurs.","language":"English","publisher":"Elsevier","doi":"10.1016/j.catena.2022.106547","usgsCitation":"Cadigan, J.A., Jafari, N., Stagg, C., Laurenzano, C., Harris, B.D., Meselhe, A.E., Dugas, J., and Couvillion, B., 2022, Characterization of vegetated and ponded wetlands with implications towards coastal wetland marsh collapse: Catena, v. 218, 106547, 9 p.; Data Release, https://doi.org/10.1016/j.catena.2022.106547.","productDescription":"106547, 9 p.; Data Release","ipdsId":"IP-123995","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":446532,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.catena.2022.106547","text":"Publisher Index Page"},{"id":406222,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417830,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EW3N0D"}],"country":"United States","state":"Louisiana","city":"Port Sulphur","otherGeospatial":"Gulf of Mexico, Mississippi River Deltaic Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.98626708984375,\n 29.3067588581613\n ],\n [\n -89.48501586914062,\n 29.3067588581613\n ],\n [\n -89.48501586914062,\n 29.54956657394792\n ],\n [\n -89.98626708984375,\n 29.54956657394792\n ],\n [\n -89.98626708984375,\n 29.3067588581613\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"218","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cadigan, Jack A. 0000-0002-1200-8275","orcid":"https://orcid.org/0000-0002-1200-8275","contributorId":296178,"corporation":false,"usgs":false,"family":"Cadigan","given":"Jack","email":"","middleInitial":"A.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":850851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jafari, Navid H.","contributorId":214730,"corporation":false,"usgs":false,"family":"Jafari","given":"Navid H.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":850852,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stagg, Camille 0000-0002-1125-7253","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":220330,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":850853,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Laurenzano, Claudia 0000-0003-1406-8658","orcid":"https://orcid.org/0000-0003-1406-8658","contributorId":215853,"corporation":false,"usgs":false,"family":"Laurenzano","given":"Claudia","affiliations":[{"id":25340,"text":"Cherokee Nation Technologies","active":true,"usgs":false}],"preferred":false,"id":850854,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harris, Brian D. 0000-0001-5771-1880","orcid":"https://orcid.org/0000-0001-5771-1880","contributorId":296180,"corporation":false,"usgs":false,"family":"Harris","given":"Brian","email":"","middleInitial":"D.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":850855,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meselhe, Amina E.","contributorId":296186,"corporation":false,"usgs":false,"family":"Meselhe","given":"Amina","email":"","middleInitial":"E.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":850856,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dugas, Jason 0000-0001-6094-7560","orcid":"https://orcid.org/0000-0001-6094-7560","contributorId":205300,"corporation":false,"usgs":true,"family":"Dugas","given":"Jason","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":850857,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Couvillion, Brady 0000-0001-5323-1687","orcid":"https://orcid.org/0000-0001-5323-1687","contributorId":222810,"corporation":false,"usgs":true,"family":"Couvillion","given":"Brady","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":850858,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70236363,"text":"70236363 - 2022 - Balancing future renewable energy infrastructure siting and associated habitat loss for migrating whooping cranes","interactions":[],"lastModifiedDate":"2022-09-05T13:24:05.252457","indexId":"70236363","displayToPublicDate":"2022-09-05T08:18:29","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Balancing future renewable energy infrastructure siting and associated habitat loss for migrating whooping cranes","docAbstract":"The expansion of human infrastructure has contributed to novel risks and disturbance regimes in most ecosystems, leading to considerable uncertainty about how species will respond to altered landscapes. A recent assessment revealed that whooping cranes (Grus americana), an endangered migratory waterbird species, avoid wind-energy infrastructure during migration. However, uncertainties regarding collective impacts of other types of human infrastructure, such as power lines on migration, variable drought conditions, and continued construction of wind energy infrastructure may compromise ongoing recovery efforts for whooping cranes. Droughts are increasing in frequency and severity throughout the whooping crane migration corridor, and the impacts of drought on stopover habitat use are largely unknown. Moreover, decision-based analyses are increasingly advocated to guide recovery planning for endangered species, yet applications remain rare. Using GPS locations from 57 whooping cranes from 2010 through 2016 in the United States Great Plains, we assessed habitat selection and avoidance of potential disturbances during migration relative to drought conditions, and we used these results in an optimization analysis to select potential sites for new wind energy developments that minimize relative habitat loss for whooping cranes and maximize wind energy potential. Drought occurrence and severity varied spatially and temporally across the migration corridor during our study period. Whooping cranes rarely used areas <5 km from human settlements and wind energy infrastructure under both drought and non-drought conditions, and <2 km from power lines during non-drought conditions, with the lowest likelihood of use near wind energy infrastructure. Whooping cranes differed in their selection of wetland and cropland land cover types depending on drought or non-drought conditions. We identified scenarios for wind energy expansion across the migration corridor and in select states, which are robust to uncertain drought conditions, where future loss of highly selected stopover habitats could be minimized under a common strategy. Our approach was to estimate functional habitat loss while integrating current disturbances, potential future disturbances, and uncertainty in drought conditions. Therefore, dynamic models describing potential costs associated with risk-averse behaviors resulting from future developments can inform proactive conservation before population impacts occur.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2022.931260","usgsCitation":"Ellis, K.S., Pearse, A.T., Brandt, D.A., Bidwell, M., Harrell, W.C., Butler, M.J., and Post van der Burg, M., 2022, Balancing future renewable energy infrastructure siting and associated habitat loss for migrating whooping cranes: Frontiers in Ecology and Evolution, v. 10, 931260, 17 p., https://doi.org/10.3389/fevo.2022.931260.","productDescription":"931260, 17 p.","ipdsId":"IP-138784","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":446538,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2022.931260","text":"Publisher Index Page"},{"id":435701,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P902I4WO","text":"USGS data release","linkHelpText":"Whooping crane migration habitat selection disturbance data and maps"},{"id":406216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas, Montana, Nebraska, North Dakota, South Dakota, Oklahoma, Texas","otherGeospatial":"Great Plains","volume":"10","noUsgsAuthors":false,"publicationDate":"2022-08-12","publicationStatus":"PW","contributors":{"editors":[{"text":"Hamilton, Diana","contributorId":296218,"corporation":false,"usgs":false,"family":"Hamilton","given":"Diana","email":"","affiliations":[{"id":12803,"text":"Mount Allison University","active":true,"usgs":false}],"preferred":false,"id":850888,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Ellis, Kristen S. 0000-0003-2759-3670","orcid":"https://orcid.org/0000-0003-2759-3670","contributorId":251877,"corporation":false,"usgs":true,"family":"Ellis","given":"Kristen","email":"","middleInitial":"S.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":850802,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":850803,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brandt, David A. 0000-0001-9786-307X dbrandt@usgs.gov","orcid":"https://orcid.org/0000-0001-9786-307X","contributorId":149929,"corporation":false,"usgs":true,"family":"Brandt","given":"David","email":"dbrandt@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":850804,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bidwell, Mark T.","contributorId":139204,"corporation":false,"usgs":false,"family":"Bidwell","given":"Mark T.","affiliations":[{"id":12696,"text":"Environmental Canada","active":true,"usgs":false}],"preferred":false,"id":850805,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harrell, Wade C.","contributorId":147143,"corporation":false,"usgs":false,"family":"Harrell","given":"Wade","email":"","middleInitial":"C.","affiliations":[{"id":16793,"text":"USFWS, Ecological Services, Austwell, TX","active":true,"usgs":false}],"preferred":false,"id":850806,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Butler, Matthew J.","contributorId":296149,"corporation":false,"usgs":false,"family":"Butler","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":850807,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Post van der Burg, Max 0000-0002-3943-4194","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":216013,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":850808,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70236497,"text":"70236497 - 2022 - Predictive models of selective cattle use of large, burned landscapes in semiarid sagebrush-steppe","interactions":[],"lastModifiedDate":"2022-09-09T12:14:02.910302","indexId":"70236497","displayToPublicDate":"2022-09-05T07:10:56","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Predictive models of selective cattle use of large, burned landscapes in semiarid sagebrush-steppe","docAbstract":"The fire-exotic annual grass cycle is a severe threat to shrub-steppe rangelands, and a greater understanding of how livestock grazing relates to the problem is needed to guide effective management interventions. Grazing effects vary throughout shrub-steppe rangelands because livestock are selective in their use within pastures. Thus, knowing where cattle are located and concentrate their use in a postfire landscape is important for enhancing plant community resiliency to disturbance and resistance to exotic annual grass invasion. We asked how the distribution and intensity of cattle use varied across 113 000 ha of recently burned, environmentally varied shrub-steppe. Generalized linear mixed effects models were used to determine the relationship of cattle dung (presence/absence and counts), which was recorded during the third to fifth postfire year (after grazing deferment) on 1166 (531-m2) plots, to water sources, burn severity, grass cover, and topographic predictors. Our distribution and intensity of use models revealed similar relationships between cattle use and landscape predictors. Cattle use was greater in areas that were flatter and closer to water and that had moderate burn severity and less heat load and ruggedness. Slope had the strongest effect on cattle use of the predictors. The probability of cattle being present decreased by 10% for every 5° increase in slope until slope exceeded 15°, and then the effect of slope weakened. Despite moderate slopes
Pest management professionals will require a diverse, adaptive abatement toolbox to combat advanced challenges from disease vector and nuisance insect populations. Designed for post-application longevity, insecticidal paints offer extended residual effects on targeted insect pest populations; a measured understanding of active ingredient bioavailability over time is valuable to fully assess treatment efficacy and potential environmental risks. This study was initiated because a nuisance net-spinning caddisfly, Smicridea fasciatella, is lowering the quality of life for riverfront residents at the type locality.
We tested the efficacy and potential mobility of a transfluthrin-based paint (a.i. 0.50%), comparing the impacts of UV exposure and substrate texture over time. Direct UV exposure decreased efficacy (β ± S.E. = 0.008 ± 0.001, P < 0.001) and a coarse texture maintained greater efficacy (β ± S.E. = −3.7 ± 1.3, P = 0.004) over time. Notably, the coarse texture + indirect UV treatment maintained 100% mortality after 240 days. UV exposure and substrate texture did not have a significant impact on leachate concentrations over time, and successive immersion tests indicated a two-phase emission pattern. Bioaccumulation increased with time on the cuticle of dead adult S. fasciatella; after 24 h of direct exposure the concentration of transfluthrin was 25.3 ± 0.9 ng/caddisfly with a maximum concentration of 345 ng/caddisfly after 7 days.
Our predictions were validated with measured, time-dependent impacts on efficacy, leachability, and bioaccumulation. Because of the mobility of active ingredient in the environment, insecticidal paints merit low-impact protocols to improve public health outcomes and environmental safety. © 2022 Society of Chemical Industry.
","language":"English","publisher":"Wiley","doi":"10.1002/ps.7163","usgsCitation":"Cavallaro, M.C., Sanders, C., and Hladik, M.L., 2022, Measured efficacy, bioaccumulation, and leaching of a transfluthrin-based insecticidal paint: A case study with a nuisance, nonbiting aquatic insect: Pest Management Science, v. 78, no. 12, p. 5413-5422, https://doi.org/10.1002/ps.7163.","productDescription":"10 p.","startPage":"5413","endPage":"5422","ipdsId":"IP-142496","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":407124,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"78","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-09-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Cavallaro, Michael C.","contributorId":296789,"corporation":false,"usgs":false,"family":"Cavallaro","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":64177,"text":"Bullhead City Pest Abatement District","active":true,"usgs":false}],"preferred":false,"id":852487,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sanders, Corey 0000-0001-7743-6396","orcid":"https://orcid.org/0000-0001-7743-6396","contributorId":204711,"corporation":false,"usgs":true,"family":"Sanders","given":"Corey","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":852488,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":203857,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":852489,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70236194,"text":"sir20225080 - 2022 - Water-level and recoverable water in storage changes, High Plains aquifer, predevelopment to 2017 and 2015–17","interactions":[],"lastModifiedDate":"2022-09-02T14:00:26.433161","indexId":"sir20225080","displayToPublicDate":"2022-09-02T07:50:04","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5080","displayTitle":"Water-Level and Recoverable Water in Storage Changes, High Plains Aquifer, Predevelopment to 2017 and 2015–17","title":"Water-level and recoverable water in storage changes, High Plains aquifer, predevelopment to 2017 and 2015–17","docAbstract":"The High Plains aquifer underlies 111.8 million acres (about 175,000 square miles) in parts of eight States—Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming. Water-level declines began in parts of the High Plains aquifer soon after the beginning of substantial groundwater irrigation (about 1950). This report presents water-level changes and change in recoverable water in storage in the High Plains aquifer from predevelopment (about 1950) to 2017 and from 2015 to 2017.
Water-level changes from predevelopment to 2017, by well, ranged from a rise of 84 feet to a decline of 262 feet; the range for 99 percent of the wells was from a rise of 39 feet to a decline of 200 feet. Water-level changes from 2015 to 2017, by well, ranged from a rise of 41 feet to a decline of 21 feet; the range for 99 percent of the wells was from a rise of 14 feet to a decline of 10 feet. The area-weighted, average water-level changes in the aquifer were an overall decline of 16.8 feet from predevelopment to 2017 and a rise of 0.1 foot from 2015 to 2017. Total recoverable water in storage in the aquifer in 2017 was about 2.91 billion acre-feet, which was a decline of about 291.8 million acre-feet since predevelopment and a rise of 0.1 million acre-feet from 2015 to 2017.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225080","programNote":"Groundwater and Streamflow Information Program","usgsCitation":"McGuire, V.L., and Strauch, K.R., 2022, Water-level and recoverable water in storage changes, High Plains aquifer, predevelopment to 2017 and 2015–17: U.S. Geological Survey Scientific Investigations Report 2022–5080, 15 p., https://doi.org/10.3133/sir20225080.","productDescription":"Report: vi, 15 p.; Data Release; Dataset","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-106333","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":405912,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5080/sir20225080.pdf","text":"Report","size":"5.31 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5080"},{"id":405911,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5080/coverthb.jpg"},{"id":405915,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":405914,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5080/images"},{"id":405913,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5080/sir20225080.XML"},{"id":405916,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YN7PY3","text":"USGS data release","linkHelpText":"Data from maps of water-level changes in the High Plains aquifer in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming, predevelopment (about 1950) to 2017 and 2015–17"}],"country":"United States","state":"Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, Wyoming","otherGeospatial":"High Plains aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.4912109375,\n 33.32134852669881\n ],\n [\n -102.216796875,\n 32.24997445586331\n ],\n [\n -100.45898437499999,\n 34.52466147177172\n ],\n [\n -99.6240234375,\n 36.06686213257888\n ],\n [\n -99.6240234375,\n 38.09998264736481\n ],\n [\n -97.20703125,\n 40.74725696280421\n ],\n [\n -97.119140625,\n 42.293564192170095\n ],\n [\n -98.9208984375,\n 42.87596410238256\n ],\n [\n -101.7333984375,\n 43.77109381775651\n ],\n [\n -103.22753906249999,\n 42.90816007196054\n ],\n [\n -105.0732421875,\n 42.52069952914966\n ],\n [\n -105.908203125,\n 42.293564192170095\n ],\n [\n -105.8203125,\n 41.07935114946899\n ],\n [\n -104.150390625,\n 40.97989806962013\n ],\n [\n -104.7216796875,\n 39.50404070558415\n ],\n [\n -104.67773437499999,\n 38.30718056188316\n ],\n [\n -103.1396484375,\n 38.20365531807149\n ],\n [\n -103.974609375,\n 37.23032838760387\n ],\n [\n -103.88671875,\n 35.496456056584165\n ],\n [\n -104.1064453125,\n 34.95799531086792\n ],\n [\n -103.4912109375,\n 33.32134852669881\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
Spatial data about the bathymetry, habitat characteristics, underlying geology, and other features of the ocean and inland seas are essential for decision-making. Marine research and management organizations use these data to help ensure safe navigation, promote sustainable fisheries, extract energy, and protect marine habitats in the coastal and ocean waters of the U.S. Exclusive Economic Zone (EEZ) and Laurentian Great Lakes. Many of these organizations may have overlapping or shared mapping interests without knowing it.
In a multi-jurisdictional planning environment, it can be challenging and cumbersome to determine where other entities have shared or overlapping mapping interests, especially across a transnational region such as the Great Lakes. State and provincial governments, federal governments, academia, tribes and First Nations, and other stakeholders from both the U.S. and Canada all have mapping interests across Great Lakes waters. Identifying and communicating target geographies for new data collection that are shared among multiple organizations can both help to avoid redundancy of new mapping efforts, and create opportunities for greater efficiency through collaboration.
To address this issue, a spatial priorities study was conducted using a geospatial tool developed by the National Ocean Services National Centers for Coastal and Ocean Science (NCCOS). The tool provided an easy-to-use online interface in which programs can identify their priorities in a simple and straightforward way. This study asked representatives of Great Lakes management and science organizations to identify the areas for which they needed maps of lakebed features on a near-term, mid-term, and long-term timeframe, and why. Then, the responses were analyzed and overlaid to determine areas of shared mapping need and opportunity and to determine the types of map products needed.
The analysis revealed high interest among multiple organizations in discrete geographies including the Minnesota and Wisconsin shoreline from Duluth to the eastern extent of the Bayfield Peninsula, Green Bay in Lake Michigan, and the southern coastlines of Lake Erie and Lake Ontario, the St. Marys River, and the northern Lake Superior coastal waters near Grand Portage, MN. Lower priority mapping interest were distributed widely across all lakes, but tended to be concentrated in nearshore areas (<30 m depth).
The analysis also indicated that the top mapping justifications were Habitat/biota/natural area, Benthic exploration, Commercial and recreational fishing, and Scientific research. The top desired map product types were Elevation, Substrate/sub-bottom geologic characterization, and Habitat map/characterization, although participants on some lakes noted other less prevalent product types.
Following from previously conducted NOAA and non-NOAA Federal spatial prioritization exercises, the results of this regional focus can help mapping organizations better understand how their priorities align with the needs of regional organizations, allow for more efficient coordination and funding, and enable partners to leverage assets and resources to fill their most pressing data and information gaps across Great Lakes waters. The U.S. Mapping Coordination Site hosts the results of this study and other spatial prioritization studies. Through this website, one can interact with the study results along with recent and planned mapping efforts.
NOAA intends to update their spatial priorities on a three- to five-year basis. Future studies should strive to expand participation of federal agencies, state and local governments, federally-recognized tribes, academia, and private industry (among other stakeholders) to seek out ocean mapping partnerships in conjunction with the National Ocean Mapping, Exploration and Characterization (NOMEC) goals map once, use many times.”
","language":"English","publisher":"National Oceanic and Atmospheric Administration","doi":"10.25923/4dzh-wh46","usgsCitation":"Gouws, K., Chappell, A., Westington, M., Yung, C., Esselman, P., Brinks, L., Kearns, T., Zhang, X., Buja, K., and Krumwiede, B., 2022, Great Lakes spatial priorities study: NOAA Technical Memorandum NOS CS 51, viii, 40 p., https://doi.org/10.25923/4dzh-wh46.","productDescription":"viii, 40 p.","ipdsId":"IP-132029","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":407519,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.91552734375,\n 44.28453670601888\n ],\n [\n -76.4813232421875,\n 44.319918120477425\n ],\n [\n -77.113037109375,\n 44.01652134387754\n ],\n [\n -77.640380859375,\n 44.08758502824516\n ],\n [\n -79.2938232421875,\n 43.8503744993026\n ],\n [\n -79.9090576171875,\n 43.30119623257966\n ],\n [\n -79.2718505859375,\n 43.153101551466385\n ],\n [\n -78.6236572265625,\n 43.32517767999296\n ],\n [\n -77.431640625,\n 43.213183300738876\n ],\n [\n -76.871337890625,\n 43.22519255488632\n ],\n [\n -76.102294921875,\n 43.56845179881218\n ],\n [\n -75.91552734375,\n 44.28453670601888\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.870849609375,\n 42.75104599038353\n ],\n [\n -78.8763427734375,\n 42.896088552971065\n ],\n [\n -79.5025634765625,\n 42.88803956056295\n ],\n [\n -80.2386474609375,\n 42.79540065303723\n ],\n [\n -80.5517578125,\n 42.61374895431491\n ],\n [\n -81.2933349609375,\n 42.69051116998238\n ],\n [\n -82.1722412109375,\n 42.24071874922666\n ],\n [\n -82.55126953124999,\n 42.05745022024682\n ],\n [\n -82.803955078125,\n 42.05337156043361\n ],\n [\n -82.99621582031249,\n 42.049292638686836\n ],\n [\n -83.1060791015625,\n 42.13082130188811\n ],\n [\n -83.22143554687499,\n 42.14304156290942\n ],\n [\n -83.5345458984375,\n 41.693424216151314\n ],\n [\n -83.353271484375,\n 41.623655390686395\n ],\n [\n -83.111572265625,\n 41.566141964768384\n ],\n [\n -83.0401611328125,\n 41.43860847395721\n ],\n [\n -82.913818359375,\n 41.376808565702355\n ],\n [\n -82.79296874999999,\n 41.430371882652814\n ],\n [\n -82.44140625,\n 41.36444153054222\n ],\n [\n -81.9964599609375,\n 41.47977575214487\n ],\n [\n -81.650390625,\n 41.47566020027821\n ],\n [\n -81.1669921875,\n 41.734429390721\n ],\n [\n -79.73876953125,\n 42.20817645934742\n ],\n [\n -78.9312744140625,\n 42.63799988907408\n ],\n [\n -78.870849609375,\n 42.75104599038353\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.45263671875,\n 45.182036837015886\n ],\n [\n -80.870361328125,\n 44.5435052132082\n ],\n [\n -80.760498046875,\n 44.66083904265621\n ],\n [\n -80.1123046875,\n 44.402391829093915\n ],\n [\n -79.94750976562499,\n 44.41024041296011\n ],\n [\n -79.903564453125,\n 44.77013681219717\n ],\n [\n -79.69482421875,\n 44.69989765840318\n ],\n [\n -79.716796875,\n 44.91813929958515\n ],\n [\n -80.67260742187499,\n 45.96642454131025\n ],\n [\n -81.8701171875,\n 46.17983040759436\n ],\n [\n -84.00146484374999,\n 46.38483322349276\n ],\n [\n -84.26513671875,\n 46.27863122156088\n ],\n [\n -84.100341796875,\n 46.03510927947334\n ],\n [\n -84.803466796875,\n 46.09609080214316\n ],\n [\n -84.715576171875,\n 45.729191061299915\n ],\n [\n -84.26513671875,\n 45.61403741135093\n ],\n [\n -83.682861328125,\n 45.31352900692258\n ],\n [\n -83.441162109375,\n 45.1742925240767\n ],\n [\n -83.46313476562499,\n 45.01141864227728\n ],\n [\n -83.309326171875,\n 44.80132682904856\n ],\n [\n -83.441162109375,\n 44.32384807250689\n ],\n [\n -83.583984375,\n 44.29240108529005\n ],\n [\n -83.671875,\n 44.04811573082351\n ],\n [\n -83.880615234375,\n 44.000717834282774\n ],\n [\n -84.00146484374999,\n 43.77902662160831\n ],\n [\n -83.95751953125,\n 43.6599240747891\n ],\n [\n -83.660888671875,\n 43.56447158721811\n ],\n [\n -83.22143554687499,\n 43.94537239244209\n ],\n [\n -82.913818359375,\n 44.02442151965934\n ],\n [\n -82.781982421875,\n 43.96119063892024\n ],\n [\n -82.540283203125,\n 43.11702412135048\n ],\n [\n -82.408447265625,\n 42.97250158602597\n ],\n [\n -81.9140625,\n 43.13306116240612\n ],\n [\n -81.67236328125,\n 43.46886761482925\n ],\n [\n -81.727294921875,\n 44.040218713142146\n ],\n [\n -81.595458984375,\n 44.268804788566165\n ],\n [\n -81.221923828125,\n 44.62175409623324\n ],\n [\n -81.45263671875,\n 45.182036837015886\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.20947265625,\n 41.623655390686395\n ],\n [\n -86.220703125,\n 42.21224516288584\n ],\n [\n -86.15478515625,\n 42.956422511073335\n ],\n [\n -86.46240234375,\n 43.691707903073805\n ],\n [\n -85.97900390625,\n 44.84029065139799\n ],\n [\n -85.62744140625,\n 45.02695045318546\n ],\n [\n -85.517578125,\n 44.69989765840318\n ],\n [\n -85.0341796875,\n 44.98034238084973\n ],\n [\n -85.25390625,\n 45.259422036351694\n ],\n [\n -84.83642578125,\n 45.42929873257377\n ],\n [\n -85.10009765625,\n 45.55252525134013\n ],\n [\n -84.79248046875,\n 45.79816953017265\n ],\n [\n -84.7705078125,\n 46.01222384063236\n ],\n [\n -85.49560546875,\n 46.14939437647686\n ],\n [\n -86.24267578125,\n 45.99696161820381\n ],\n [\n -86.50634765625,\n 45.81348649679973\n ],\n [\n -86.59423828125,\n 45.920587344733654\n ],\n [\n -86.85791015625,\n 45.81348649679973\n ],\n [\n -87.0556640625,\n 45.84410779560204\n ],\n [\n -87.29736328125,\n 45.61403741135093\n ],\n [\n -88.08837890625,\n 44.653024159812\n ],\n [\n -87.978515625,\n 44.465151013519616\n ],\n [\n -87.5830078125,\n 44.715513732021336\n ],\n [\n -87.12158203125,\n 45.1510532655634\n ],\n [\n -87.5390625,\n 44.5278427984555\n ],\n [\n -87.78076171875,\n 43.8186748554532\n ],\n [\n -88.00048828124999,\n 42.924251753870685\n ],\n [\n -87.82470703125,\n 42.00032514831621\n ],\n [\n -87.20947265625,\n 41.623655390686395\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.22119140625,\n 46.5739667965278\n ],\n [\n -84.39697265625,\n 46.694667307773116\n ],\n [\n -84.287109375,\n 46.9052455464292\n ],\n [\n -84.70458984375,\n 47.025206001585396\n ],\n [\n -84.52880859375,\n 47.27922900257082\n ],\n [\n -84.88037109375,\n 47.62097541515849\n ],\n [\n -84.79248046875,\n 48.004625021133904\n ],\n [\n -85.8251953125,\n 48.019324184801185\n ],\n [\n -86.5283203125,\n 48.80686346108517\n ],\n [\n -88.154296875,\n 49.03786794532644\n ],\n [\n -88.5498046875,\n 48.879167148960214\n ],\n [\n -88.79150390625,\n 48.531157010976706\n ],\n [\n -89.20898437499999,\n 48.61838518688487\n ],\n [\n -89.4287109375,\n 48.16608541901253\n ],\n [\n -90.59326171875,\n 47.76886840424207\n ],\n [\n -92.21923828124999,\n 46.73986059969267\n ],\n [\n -91.845703125,\n 46.604167162931844\n ],\n [\n -90.9228515625,\n 46.89023157359399\n ],\n [\n -91.0546875,\n 46.5739667965278\n ],\n [\n -90.72509765625,\n 46.558860303117164\n ],\n [\n -90.3076171875,\n 46.51351558059737\n ],\n [\n -89.80224609374999,\n 46.70973594407157\n ],\n [\n -89.18701171875,\n 46.830133640447386\n ],\n [\n -88.65966796875,\n 47.12995075666307\n ],\n [\n -87.91259765625,\n 47.41322033016902\n ],\n [\n -88.2861328125,\n 47.204642388766935\n ],\n [\n -88.52783203125,\n 46.89023157359399\n ],\n [\n -88.4619140625,\n 46.70973594407157\n ],\n [\n -88.13232421875,\n 46.81509864599243\n ],\n [\n -87.69287109375,\n 46.649436163350245\n ],\n [\n -87.34130859375,\n 46.42271253466717\n ],\n [\n -87.0556640625,\n 46.49839225859763\n ],\n [\n -86.81396484375,\n 46.37725420510028\n ],\n [\n -86.59423828125,\n 46.37725420510028\n ],\n [\n -86.17675781249999,\n 46.58906908309182\n ],\n [\n -85.6494140625,\n 46.604167162931844\n ],\n [\n -85.166015625,\n 46.7549166192819\n ],\n [\n -85.10009765625,\n 46.46813299215554\n ],\n [\n -84.79248046875,\n 46.37725420510028\n ],\n [\n -84.22119140625,\n 46.5739667965278\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gouws, Karen","contributorId":297003,"corporation":false,"usgs":false,"family":"Gouws","given":"Karen","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":853075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chappell, Ashley","contributorId":297005,"corporation":false,"usgs":false,"family":"Chappell","given":"Ashley","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":853076,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Westington, Meredith","contributorId":297007,"corporation":false,"usgs":false,"family":"Westington","given":"Meredith","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":853077,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yung, Cathleen","contributorId":297009,"corporation":false,"usgs":false,"family":"Yung","given":"Cathleen","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":853078,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Esselman, Peter C. 0000-0002-0085-903X","orcid":"https://orcid.org/0000-0002-0085-903X","contributorId":204291,"corporation":false,"usgs":true,"family":"Esselman","given":"Peter C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":853079,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brinks, Linden","contributorId":297011,"corporation":false,"usgs":false,"family":"Brinks","given":"Linden","email":"","affiliations":[{"id":64275,"text":"GLOS","active":true,"usgs":false}],"preferred":false,"id":853080,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kearns, Timothy","contributorId":242948,"corporation":false,"usgs":false,"family":"Kearns","given":"Timothy","email":"","affiliations":[],"preferred":false,"id":853198,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zhang, Xiaofan","contributorId":297012,"corporation":false,"usgs":false,"family":"Zhang","given":"Xiaofan","email":"","affiliations":[{"id":64275,"text":"GLOS","active":true,"usgs":false}],"preferred":false,"id":853081,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Krumwiede, Brandon","contributorId":297013,"corporation":false,"usgs":false,"family":"Krumwiede","given":"Brandon","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":853082,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Buja, Ken","contributorId":297014,"corporation":false,"usgs":false,"family":"Buja","given":"Ken","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":853083,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70256750,"text":"70256750 - 2022 - Seasonal context of bristly cave crayfish Cambarus setosus habitat use and life history","interactions":[],"lastModifiedDate":"2024-09-04T15:39:26.083626","indexId":"70256750","displayToPublicDate":"2022-09-01T10:33:33","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2201,"text":"Journal of Cave and Karst Studies","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal context of bristly cave crayfish Cambarus setosus habitat use and life history","docAbstract":"Cave crayfishes are important members of groundwater communities, but many cave crayfishes are threatened or endangered. Unfortunately, we lack basic life history and ecological data that are needed for developing conservation plans for most cave crayfishes, especially the role of seasonal and annual fluctuations in structuring populations. Therefore, we determined the seasonal life history and habitat use of Cambarus setosus in Smallin Civil War Cave, Christian County, Missouri, United States. We conducted visual crayfish surveys over a 400 m section of the cave from 2006 to 2019. We used multinomial logit, multiple linear regression, and logistic regression models to estimate crayfish substrate, water depth, and water velocity use, respectively. All models included sex, carapace length, season, distance into the cave, and interactions between all variables and sex as predictor terms. We also used t-tests to assess morphometric differences between male and female crayfish. Six mark-recapture events (2010 to 2019) were used to estimate population sizes using a nil-recapture model. We attempted to age eight individuals using gastric mill bands, but annual bands were not discernable. We found reproductively active males during all seasons. We captured one ovigerous female during the spring, though ovigerous females were observed during show cave tours during spring, summer, and autumn. Male C. setosus were more likely to use homogenous and heterogeneous rock substrates and shallower and calmer water when compared to females; however, these relationships varied based on distance into the cave and season. Females sampled were significantly larger than males, and males regenerated chelae more often. Minimum population size estimates ranged from 9 to 159 individuals and indicated the population was relatively stable. Our data provide both a baseline population estimate for comparison with future studies and valuable trait information that is often lacking but useful for developing conservation efforts.
","language":"English","publisher":"National Speleological Society","doi":"10.4311/2021LSC0110","usgsCitation":"Mouser, J., Ashley, D., Zenter, D., and Brewer, S.K., 2022, Seasonal context of bristly cave crayfish Cambarus setosus habitat use and life history: Journal of Cave and Karst Studies, v. 84, no. 3, p. 85-95, https://doi.org/10.4311/2021LSC0110.","productDescription":"11 p.","startPage":"85","endPage":"95","ipdsId":"IP-127872","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":446569,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://doi.org/10.4311/2021lsc0110","text":"Publisher Index Page"},{"id":433451,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","county":"Christian County","otherGeospatial":"Smallin Civil War Cave","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.18894102326013,\n 37.05222350256189\n ],\n [\n -93.18894102326013,\n 37.04918995811687\n ],\n [\n -93.18586955215672,\n 37.04918995811687\n ],\n [\n -93.18586955215672,\n 37.05222350256189\n ],\n [\n -93.18894102326013,\n 37.05222350256189\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"84","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mouser, J.B.","contributorId":244447,"corporation":false,"usgs":false,"family":"Mouser","given":"J.B.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":908855,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ashley, D.C.","contributorId":244487,"corporation":false,"usgs":false,"family":"Ashley","given":"D.C.","email":"","affiliations":[{"id":48915,"text":"Missouri Western State University","active":true,"usgs":false}],"preferred":false,"id":908856,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zenter, D.L.","contributorId":341751,"corporation":false,"usgs":false,"family":"Zenter","given":"D.L.","email":"","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":908857,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":908858,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70233185,"text":"70233185 - 2022 - Basis for technical guidance to evaluate evapotranspiration covers","interactions":[],"lastModifiedDate":"2022-12-12T15:58:40.79318","indexId":"70233185","displayToPublicDate":"2022-09-01T09:55:22","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesNumber":"NUREG/CR-7297","title":"Basis for technical guidance to evaluate evapotranspiration covers","docAbstract":"This report provides technical guidance to evaluate evapotranspiration (ET) cover design criteria with emphasis on applications to long-term disposal sites such as Uranium Mill Tailings Radiation Control Act of 1978 (UMTRCA) sites. Water balance covers, also known as ET covers, reduce percolation by storing precipitation then allowing vegetation to cycle it back to the atmosphere. For long-term (over 200 years) waste isolation, ET covers may provide significant benefits over conventional, resistive covers that rely on engineered components, such as compacted clay barriers and geomembranes, to divert precipitation. UMTRCA covers were designed to impede and attenuate radioactive radon-222 gas flux from the underlying tailings, while minimizing percolation of any contaminants to groundwater. Such covers have implicit regulatory compliance post-construction. Alternative cover systems, such as ET covers, must explicitly meet some anticipated performance, and demonstrate beneficial use. While all engineered structures will change over time, an ET cover evolves with nature rather than resisting it, which may perpetuate a more reliable waste isolation system. For example, UMTRCA sites must provide safe and environmentally sound disposal, long-term stabilization, and control of uranium mill tailings and remain effective for up to 1,000 years, to the extent reasonably achievable, and, in any case, for at least 200 years. UMTRCA covers rely on the engineered properties to meet regulatory requirements during and immediately after construction. Subsequent compliance is implicit in the design. The design of an ET cover is far more dependent on mesoscale meteorology, native vegetation, and edaphic soil properties which are site-specific. Therefore, the design and anticipated performance of an ET cover must be demonstrated through a combination of modeling, natural analogues and pilot studies, and then verified with monitoring data. There is no single ET cover design that can likely meet performance standards across different climates, available soils, and vegetation. The technical information presented in this report reviews guidelines and performance criteria commonly used for ET covers at municipal waste facilities and the consideration factors of such covers to meet the regulatory requirements at long-term disposal sites.","language":"English","publisher":"U.S. Nuclear Regulatory Commission","usgsCitation":"Caldwell, T., Huntington, J., Davies, G.E., Tabatabai, S., and Fuhrmann, M., 2022, Basis for technical guidance to evaluate evapotranspiration covers, 127 p.","productDescription":"127 p.","ipdsId":"IP-120445","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":410286,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":403886,"type":{"id":15,"text":"Index Page"},"url":"https://www.nrc.gov/reading-rm/doc-collections/nuregs/contract/cr7297/index.html"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Caldwell, Todd 0000-0003-4068-0648","orcid":"https://orcid.org/0000-0003-4068-0648","contributorId":217924,"corporation":false,"usgs":true,"family":"Caldwell","given":"Todd","email":"","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":846716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huntington, Jena 0000-0002-9291-1404","orcid":"https://orcid.org/0000-0002-9291-1404","contributorId":204033,"corporation":false,"usgs":true,"family":"Huntington","given":"Jena","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":846717,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davies, Gwendolyn Elizabeth 0000-0003-1538-8610","orcid":"https://orcid.org/0000-0003-1538-8610","contributorId":293203,"corporation":false,"usgs":true,"family":"Davies","given":"Gwendolyn","email":"","middleInitial":"Elizabeth","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":846718,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tabatabai, S.","contributorId":293205,"corporation":false,"usgs":false,"family":"Tabatabai","given":"S.","affiliations":[{"id":12536,"text":"U.S. Nuclear Regulatory Commission","active":true,"usgs":false}],"preferred":false,"id":846719,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuhrmann, M.","contributorId":138800,"corporation":false,"usgs":false,"family":"Fuhrmann","given":"M.","affiliations":[{"id":12528,"text":"US Nuclear Regulatory Commission","active":true,"usgs":false}],"preferred":false,"id":846720,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237260,"text":"70237260 - 2022 - Little bugs, big data, and Colorado River adaptive management: Preliminary findings from the ongoing bug flow experiment at Glen Canyon Dam","interactions":[],"lastModifiedDate":"2025-03-14T15:11:55.173887","indexId":"70237260","displayToPublicDate":"2022-09-01T09:22:40","publicationYear":"2022","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":8569,"text":"Boatman's Quarterly Review","active":true,"publicationSubtype":{"id":30}},"title":"Little bugs, big data, and Colorado River adaptive management: Preliminary findings from the ongoing bug flow experiment at Glen Canyon Dam","docAbstract":"The undammed Colorado River in Grand Canyon was characterized by spring snow-melt floods that sometimes exceeded 100,000 cubic feet per second (cfs). These were followed by occasional flash floods during summer monsoons, then by low flows from fall through early spring (Figure 1; Topping and others, 2003). This seasonally variable flow regime carried huge loads of sediment and was an important driver of natural processes that sustained the Colorado River ecosystem. For instance, high turbidity associated with this flow regime likely restricted algal growth to the river’s edge or shallow cobble habitats, similar to other desert rivers. Aquatic invertebrate assemblages were probably diverse and adapted to these variable conditions (Vinson, 2001; Haden and others, 2003). Native fishes were likely opportunistic feeders, consuming ants, seeds, and other terrestrial resources during times of flooding and switching to aquatic-derived resources like algae and aquatic invertebrates at other times (Minckley, 1991; Behn and Baxter, 2019). Regulation of the Colorado River by Glen Canyon Dam in 1963 eliminated the annual snowmelt floods, it sharply increased base flows by more than 50 percent, and dramatically increased within-day fluctuations in discharge for hydropower production (the ‘daily tides’ of the river, Figure 1 and 2; Topping and others, 2003). Glen Canyon Dam also changed other aspects of the river’s physical template, particularly temperature, sediment, and nutrient regimes. These changes to the physical template of the river led to fundamental changes in the natural processes that the sustain Colorado River ecosystem. For example, algae are common throughout the river during periods of clear water and represent the foundation of aquatic food webs (Stevens and others, 1997; Cross and others 2013). Many types of aquatic insects have disappeared or become rare, particularly sensitive groups such as mayflies, stoneflies, and caddisflies (Kennedy and others, 2016). Because aquatic insect assemblages in the Colorado River in Grand Canyon are neither diverse nor productive, food webs are simplified and inherently unstable, limiting populations of hungry fish (Cross and others 2013; Korman and others 2021).
","language":"English","publisher":"Grand Canyon River Guides Association","usgsCitation":"Kennedy, T., Metcalfe, A., Deemer, B., Ford, M., Szydlo, C.M., Yackulic, C., and Muehlbauer, J., 2022, Little bugs, big data, and Colorado River adaptive management: Preliminary findings from the ongoing bug flow experiment at Glen Canyon Dam: Boatman's Quarterly Review, v. 35, no. 3, p. 26-31.","productDescription":"6 p.","startPage":"26","endPage":"31","ipdsId":"IP-143763","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":483348,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.gcrg.org/bqr"},{"id":407960,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Glen Canyon Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.48968696594237,\n 36.93095788125762\n ],\n [\n -111.47878646850586,\n 36.93095788125762\n ],\n [\n -111.47878646850586,\n 36.94021961852396\n ],\n [\n -111.48968696594237,\n 36.94021961852396\n ],\n [\n -111.48968696594237,\n 36.93095788125762\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kennedy, Theodore 0000-0003-3477-3629","orcid":"https://orcid.org/0000-0003-3477-3629","contributorId":221741,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853868,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Metcalfe, Anya 0000-0002-6286-4889","orcid":"https://orcid.org/0000-0002-6286-4889","contributorId":221738,"corporation":false,"usgs":true,"family":"Metcalfe","given":"Anya","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853869,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deemer, Bridget R. 0000-0002-5845-1002 bdeemer@usgs.gov","orcid":"https://orcid.org/0000-0002-5845-1002","contributorId":198160,"corporation":false,"usgs":true,"family":"Deemer","given":"Bridget","email":"bdeemer@usgs.gov","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853870,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ford, Morgan 0000-0001-5104-9566","orcid":"https://orcid.org/0000-0001-5104-9566","contributorId":221740,"corporation":false,"usgs":true,"family":"Ford","given":"Morgan","email":"","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853871,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Szydlo, Cheyenne Maxime 0000-0003-4818-2395","orcid":"https://orcid.org/0000-0003-4818-2395","contributorId":297340,"corporation":false,"usgs":true,"family":"Szydlo","given":"Cheyenne","email":"","middleInitial":"Maxime","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853872,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853873,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Muehlbauer, Jeffrey 0000-0003-1808-580X","orcid":"https://orcid.org/0000-0003-1808-580X","contributorId":221739,"corporation":false,"usgs":true,"family":"Muehlbauer","given":"Jeffrey","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853874,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70256644,"text":"70256644 - 2022 - Seabird vulnerability to oil: Exposure potential, sensitivity, and uncertainty in the northern Gulf of Mexico","interactions":[],"lastModifiedDate":"2024-08-29T14:09:34.922004","indexId":"70256644","displayToPublicDate":"2022-09-01T09:02:56","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Seabird vulnerability to oil: Exposure potential, sensitivity, and uncertainty in the northern Gulf of Mexico","docAbstract":"The northern Gulf of Mexico (nGoM) is a globally important region for oil extraction and supports a diverse assemblage of marine birds. Due to their frequent contact with surface waters, diverse foraging strategies, and the ease with which oil adheres to feathers, seabirds are particularly susceptible to hydrocarbon contamination. Given the chronic and acute exposure of seabirds to oiling and a lack of studies that focus on the exposure of seabirds to oiling in sub-tropical and tropical regions, a greater understanding of the vulnerability of seabirds to oil in the nGoM appears warranted. We present an oil vulnerability index for seabirds in the nGoM tailored to the current state of knowledge using new, spatiotemporally expensive vessel-based seabird observations. We use information on the exposure and sensitivity of seabirds to oil to rank seabird vulnerability. Exposure variables characterized the potential to encounter oil and gas (O&G). Sensitivity variables characterized the potential impact of seabirds interacting with O&G and are related to life history and productivity. We also incorporated uncertainty in each variable, identifying data gaps. We found that the percent of seabirds’ habitat defined as highly suitable within 10 km of an O&G platform ranged from 0%-65% among 24 species. Though O&G platforms only overlap with 15% of highly suitable seabird habitat, overlap occurs in areas of moderate to high vulnerability of seabirds, particularly along the shelf-slope. Productivity-associated sensitivity variables were primarily responsible for creating the gradient in vulnerability scores and had greater uncertainty than exposure variables. Highly vulnerable species (e.g., Northern gannet (Morus bassanus)) tended to have high exposure to the water surface via foraging behaviors (e.g., plunge-diving), older age at first breeding, and an extended incubating and fledging period compared to less vulnerable species (e.g., Pomarine jaeger (Stercorarius pomarinus)). Uncertainty related to productivity could be reduced through at-colony monitoring. Strategic seabird satellite tagging could help target monitoring efforts to colonies known to use the nGoM, and continued vessel-based observations could improve habitat characterization. As offshore energy development in the nGoM continues, managers and researchers could use these vulnerability ranks to identify information gaps to prioritize research and focal species.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2022.880750","usgsCitation":"Michael, P.E., Hixson, K.M., Haney, J., Satge, Y., Gleason, J., and Jodice, P.G., 2022, Seabird vulnerability to oil: Exposure potential, sensitivity, and uncertainty in the northern Gulf of Mexico: Frontiers in Marine Science, v. 9, 880750, 20 p., https://doi.org/10.3389/fmars.2022.880750.","productDescription":"880750, 20 p.","ipdsId":"IP-136731","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":446580,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2022.880750","text":"Publisher Index Page"},{"id":433301,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"northern Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.65064732144825,\n 24.16865530700734\n ],\n [\n -80.74028091647656,\n 24.49674089923498\n ],\n [\n -80.6110475132637,\n 25.375716312633244\n ],\n [\n -82.48124501487644,\n 27.87595132514076\n ],\n [\n -82.50401354053463,\n 28.975470074471573\n ],\n [\n -84.01377542803263,\n 30.278116834370664\n ],\n [\n -85.21105352771927,\n 29.813919882762193\n ],\n [\n -86.41030861654544,\n 30.53771106924384\n ],\n [\n -88.05949534476994,\n 30.614388650912403\n ],\n [\n -89.250977846713,\n 30.128789114669402\n ],\n [\n -88.84045762268858,\n 28.94436305824601\n ],\n [\n -90.45644421555457,\n 29.213975074748845\n ],\n [\n -91.6391457751865,\n 29.567867845383958\n ],\n [\n -92.61153919455367,\n 29.52398569897167\n ],\n [\n -94.15861129214014,\n 29.615060750195013\n ],\n [\n -95.85111266718562,\n 28.497269906948034\n ],\n [\n -97.05244440317941,\n 27.930797727982196\n ],\n [\n -97.4997935110664,\n 26.841188159759383\n ],\n [\n -97.23172322974906,\n 26.093166420472286\n ],\n [\n -86.07549373074224,\n 26.17610757333493\n ],\n [\n -85.31650372657558,\n 24.614391708025977\n ],\n [\n -83.65064732144825,\n 24.16865530700734\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2022-09-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Michael, Pamela E.","contributorId":341457,"corporation":false,"usgs":false,"family":"Michael","given":"Pamela","email":"","middleInitial":"E.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":908453,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hixson, K. M.","contributorId":341458,"corporation":false,"usgs":false,"family":"Hixson","given":"K.","email":"","middleInitial":"M.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":908454,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haney, J.C.","contributorId":288019,"corporation":false,"usgs":false,"family":"Haney","given":"J.C.","email":"","affiliations":[{"id":61685,"text":"Terra Mar Applied Sciences","active":true,"usgs":false}],"preferred":false,"id":908455,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Satge, Y.G.","contributorId":279816,"corporation":false,"usgs":false,"family":"Satge","given":"Y.G.","email":"","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":908456,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gleason, J.S.","contributorId":288017,"corporation":false,"usgs":false,"family":"Gleason","given":"J.S.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":908457,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":219852,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908458,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70236514,"text":"70236514 - 2022 - Geochemical studies of the Green River Formation in the Piceance Basin, Colorado: I. Major, minor, and trace elements","interactions":[],"lastModifiedDate":"2022-09-09T13:32:07.905743","indexId":"70236514","displayToPublicDate":"2022-09-01T08:22:11","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Geochemical studies of the Green River Formation in the Piceance Basin, Colorado: I. Major, minor, and trace elements","docAbstract":"The Eocene Green River Formation contains the largest oil shale deposits in the world and is a welldocumented example of a lacustrine depositional system. In addition, mineral resources associated with oil shale in the Piceance Basin nahcolite [NaHCO3] and dawsonite [NaAl(CO3)(OH)2)] are of current and potential economic value, respectively. Detailed geochemical analysis across the basin can aid in the understanding of the depositional environment, sedimentary processes, and water-chemistry evolution in this system. Quantitative geochemical data for Green River oil shale from the Piceance Basin of Colorado were collected by inductively coupled plasma optical emission spectroscopy and mass spectrometry as part of this study. The basin margin is represented by samples from exposures at Douglas Pass (Garfield County) and the basin center area is characterized by core samples from two drilled wells: the Shell 23X-2 and John Savage 24-1 (Rio Blanco County). Major elements and groups of elements are used as proxies for clastic influx (Si, Al, K, Ti), carbonate deposition (Ca, Mg), salinity (Na), paleo-productivity (P), and redox state (Fe, S), respectively. Minor and trace elements reinforce observations based on major elements, including Rb, Zr, Nb for clastic influx and Mn, Sr for carbonate. Trace elements are used to characterize redox conditions (As, Mo, U, V, Co, Ni, Cu, Zn) and salinity (Rb/K, B/Ga). Chemical distinctions between the basin margin and the basin center, in terms of these components and total organic carbon concentrations, support the model of a permanently stratified lake through most of the depositional interval. A primary purpose of the study was to conduct more extensive sampling to confirm conclusions of a previous reconnaissance study. Geochemical data from this study indicates elevated Na around the basin margin occurring earlier than in the deeper basin. Early in the history of Lake Uinta, the salinity may have been elevated first in the shallower marginal waters, due to increased evaporation, which then led to elevated salinity in the basin center through transport of saline density currents. Other indicators of salinity (Rb/K, B/Ga) do not track Na content in intervals where clay minerals are absent due to diagenetic alteration under hypersaline conditions but may be used to indicate the salinities at which authigenic Na-bearing minerals begin to form. Most Na-rich samples show high proportions of clastic constituents (Si, Al, K, Ti) compared to conventional carbonate constituents (Ca, Mg). Redox-sensitive period IV transition metal elements (V, Co, Ni, Cu, Zn) show only local occurrence of significant enrichment relative to average shale abundances. Analysis of Fe/Al ratios for this dataset suggests that the depletion of these elements may be related to source rocks depleted in mafic constituents, with apparent redox-related enrichments subdued by this effect. The basin margin samples reflect generally oxic bottom waters, with some intervals deposited under more reducing, possibly dysoxic to anoxic conditions. The basin center results indicate more reducing conditions, with Mo and U enrichment factors suggesting operation of a particulate shuttle mechanism that scavenged Mo on Fe/Mn-oxyhydroxides that redissolved at depth, with Mo precipitating along with sulfides and/or organic matter at or near the sediment/water interface.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The lacustrine Green River Formation: Hydrocarbon potential and Eocene climate record","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Utah Geological Association","doi":"10.31711/ugap.v50i.114","usgsCitation":"Boak, J., Wu, T., and Birdwell, J.E., 2022, Geochemical studies of the Green River Formation in the Piceance Basin, Colorado: I. Major, minor, and trace elements, chap. of The lacustrine Green River Formation: Hydrocarbon potential and Eocene climate record, v. 50, p. 266-297, https://doi.org/10.31711/ugap.v50i.114.","productDescription":"32 p.","startPage":"266","endPage":"297","ipdsId":"IP-127516","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":446590,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.31711/ugap.v50i.114","text":"Publisher Index Page"},{"id":435705,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q5VOQB","text":"USGS data release","linkHelpText":"Geochemical data for the Green River Formation in the Piceance Basin, Colorado: Major and trace element concentrations and total organic carbon content"},{"id":406448,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Green River Formation, Piceance Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.1439208984375,\n 39.48284540453334\n ],\n [\n -107.8692626953125,\n 39.64799732373418\n ],\n [\n -107.91320800781249,\n 40.027614437486655\n ],\n [\n -108.2647705078125,\n 40.17467622056341\n ],\n [\n -108.6492919921875,\n 40.069664523297774\n ],\n [\n -108.7811279296875,\n 39.88023492849342\n ],\n [\n -108.5394287109375,\n 39.6437675734185\n ],\n [\n -108.1439208984375,\n 39.48284540453334\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"50","noUsgsAuthors":false,"publicationDate":"2022-09-01","publicationStatus":"PW","contributors":{"editors":[{"text":"Hurst, C. J.","contributorId":206942,"corporation":false,"usgs":false,"family":"Hurst","given":"C.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":851360,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Boak, Jeremy 0000-0003-0251-434X","orcid":"https://orcid.org/0000-0003-0251-434X","contributorId":296328,"corporation":false,"usgs":false,"family":"Boak","given":"Jeremy","email":"","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":851288,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wu, Tengfei 0000-0003-2804-5537","orcid":"https://orcid.org/0000-0003-2804-5537","contributorId":296330,"corporation":false,"usgs":false,"family":"Wu","given":"Tengfei","email":"","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":851289,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":851290,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70251892,"text":"70251892 - 2022 - Changes in aquatic vegetation cover following lock closure on the Illinois Waterway from 2019 – 2021","interactions":[],"lastModifiedDate":"2024-03-05T15:06:25.784988","indexId":"70251892","displayToPublicDate":"2022-09-01T08:18:54","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":17168,"text":"Completion Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"LTRMP-2019AER7","title":"Changes in aquatic vegetation cover following lock closure on the Illinois Waterway from 2019 – 2021","docAbstract":"Over the summer of 2020, the Illinois Waterway was closed to complete maintenance on lock chambers along the Illinois River. This closure restricted inter-pool vessel traffic along the river and potentially changed habitat characteristics for aquatic vegetation establishment and growth. To assess if patterns of vegetation establishment and growth changed during the closure, peak biomass imagery from 2019 (pre closure) and 2021 (post closure) were compared for a vegetation response. This assessment found locations where aquatic vegetation increased and locations where aquatic vegetation decreased. However, due to unforeseen limitations in vegetation and water sampling, a causal reason for observed changed in vegetation could not be established.","language":"English","publisher":"U.S. Army Corps of Engineers’ Upper Mississippi River Restoration Program","usgsCitation":"Strassman, A.C., 2022, Changes in aquatic vegetation cover following lock closure on the Illinois Waterway from 2019 – 2021: Completion Report LTRMP-2019AER7, 44 p.","productDescription":"44 p.","ipdsId":"IP-145368","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":426307,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://umesc.usgs.gov/data_library/ltrmp_other/IWW_Closure_Veg_Change_Co-op_Report_Final_20221201.pdf"},{"id":426318,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","otherGeospatial":"Illinois River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.28788998955925,\n 42.108326944582615\n ],\n [\n -90.7915689421851,\n 42.108326944582615\n ],\n [\n -90.7915689421851,\n 38.76757015391274\n ],\n [\n -87.28788998955925,\n 38.76757015391274\n ],\n [\n -87.28788998955925,\n 42.108326944582615\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Strassman, Andrew C. 0000-0002-9792-7181 astrassman@usgs.gov","orcid":"https://orcid.org/0000-0002-9792-7181","contributorId":4575,"corporation":false,"usgs":true,"family":"Strassman","given":"Andrew","email":"astrassman@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":895948,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70236442,"text":"70236442 - 2022 - Explainable machine learning improves interpretability in the predictive modeling of biological stream conditions in the Chesapeake Bay Watershed, USA","interactions":[],"lastModifiedDate":"2022-09-07T12:10:54.664669","indexId":"70236442","displayToPublicDate":"2022-09-01T07:07:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Explainable machine learning improves interpretability in the predictive modeling of biological stream conditions in the Chesapeake Bay Watershed, USA","docAbstract":"Anthropogenic alterations have resulted in widespread degradation of stream conditions. To aid in stream restoration and management, baseline estimates of conditions and improved explanation of factors driving their degradation are needed. We used random forests to model biological conditions using a benthic macroinvertebrate index of biotic integrity for small, non-tidal streams (upstream area ≤200 km2) in the Chesapeake Bay watershed (CBW) of the mid-Atlantic coast of North America. We utilized several global and local model interpretation tools to improve average and site-specific model inferences, respectively. The model was used to predict condition for 95,867 individual catchments for eight periods (2001, 2004, 2006, 2008, 2011, 2013, 2016, 2019). Predicted conditions were classified as Poor, FairGood, or Uncertain to align with management needs and individual reach lengths and catchment areas were summed by condition class for the CBW for each period. Global permutation and local Shapley importance values indicated percent of forest, development, and agriculture in upstream catchments had strong impacts on predictions. Development and agriculture negatively influenced stream condition for model average (partial dependence [PD] and accumulated local effect [ALE] plots) and local (individual condition expectation and Shapley value plots) levels. Friedman's H-statistic indicated large overall interactions for these three land covers, and bivariate global plots (PD and ALE) supported interactions among agriculture and development. Total stream length and catchment area predicted in FairGood conditions decreased then increased over the 19-years (length/area: 66.6/65.4% in 2001, 66.3/65.2% in 2011, and 66.6/65.4% in 2019). Examination of individual catchment predictions between 2001 and 2019 showed those predicted to have the largest decreases in condition had large increases in development; whereas catchments predicted to exhibit the largest increases in condition showed moderate increases in forest cover. Use of global and local interpretative methods together with watershed-wide and individual catchment predictions support conservation practitioners that need to identify widespread and localized patterns, especially acknowledging that management actions typically take place at individual-reach scales.
The United States National Hydrography Dataset (NHD) is a database of vector features representing the surface water features for the country. The NHD was originally compiled from hydrographic content on U.S. Geological Survey topographic maps but is being updated with higher quality feature representations through flow-routing techniques that derive hydrography from high-resolution elevation data. However, deriving hydrography through flow-routing methods is a complex process that needs to be tailored to different geographic conditions, which can lead to varying solutions. To address this problem, this paper evaluates automated deep learning and its transferability to extract hydrography from interferometric synthetic aperture radar (IfSAR) elevation data spanning a range of geographic conditions in Alaska.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceDate":"August 22-28, 2022","conferenceLocation":"Florence, Italy","language":"English","publisher":"International Society for Photogrammetry and Remote Sensing (ISPRS)","doi":"10.5194/isprs-archives-XLVIII-4-W1-2022-449-2022","usgsCitation":"Stanislawski, L., Shavers, E.J., Duffy, A., Thiem, P.T., Jaroenchai, N., Wang, S., Jiang, Z., Kronenfeld, B.J., and Buttenfield, B.P., 2022, Scaling-up deep learning predictions of hydrography from IfSAR data in Alaska, in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Florence, Italy, August 22-28, 2022, p. 449-456, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-449-2022.","productDescription":"8 p.","startPage":"449","endPage":"456","ipdsId":"IP-143118","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":446603,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/isprs-archives-xlviii-4-w1-2022-449-2022","text":"Publisher Index Page"},{"id":409352,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -157.48017274535448,\n 67.79791394109961\n ],\n [\n -157.48017274535448,\n 66.00582490875226\n ],\n [\n -152.2946258703545,\n 66.00582490875226\n ],\n [\n -152.2946258703545,\n 67.79791394109961\n ],\n [\n -157.48017274535448,\n 67.79791394109961\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2022-08-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Stanislawski, Larry 0000-0002-9437-0576","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":217849,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":857001,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shavers, Ethan J. 0000-0001-9470-5199 eshavers@usgs.gov","orcid":"https://orcid.org/0000-0001-9470-5199","contributorId":206890,"corporation":false,"usgs":true,"family":"Shavers","given":"Ethan","email":"eshavers@usgs.gov","middleInitial":"J.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":857002,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duffy, Alexander 0000-0001-6036-0583","orcid":"https://orcid.org/0000-0001-6036-0583","contributorId":299070,"corporation":false,"usgs":false,"family":"Duffy","given":"Alexander","email":"","affiliations":[{"id":64752,"text":"University of Missouri Science & Technology","active":true,"usgs":false}],"preferred":false,"id":857003,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thiem, Philip T. 0000-0002-3324-2589","orcid":"https://orcid.org/0000-0002-3324-2589","contributorId":287990,"corporation":false,"usgs":true,"family":"Thiem","given":"Philip","email":"","middleInitial":"T.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":857004,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jaroenchai, Nattapon","contributorId":267318,"corporation":false,"usgs":false,"family":"Jaroenchai","given":"Nattapon","email":"","affiliations":[{"id":38021,"text":"University of Illinois Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":857005,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, Shaowen","contributorId":198966,"corporation":false,"usgs":false,"family":"Wang","given":"Shaowen","email":"","affiliations":[],"preferred":false,"id":857006,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jiang, Zhe","contributorId":267317,"corporation":false,"usgs":false,"family":"Jiang","given":"Zhe","email":"","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":857007,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kronenfeld, Barry J. 0000-0002-9518-2462","orcid":"https://orcid.org/0000-0002-9518-2462","contributorId":207104,"corporation":false,"usgs":false,"family":"Kronenfeld","given":"Barry","email":"","middleInitial":"J.","affiliations":[{"id":5043,"text":"Eastern Illinois University","active":true,"usgs":false}],"preferred":false,"id":857008,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Buttenfield, Barbara P. 0000-0001-5961-5809","orcid":"https://orcid.org/0000-0001-5961-5809","contributorId":206887,"corporation":false,"usgs":false,"family":"Buttenfield","given":"Barbara","email":"","middleInitial":"P.","affiliations":[{"id":16144,"text":"University of Colorado-Boulder","active":true,"usgs":false}],"preferred":false,"id":857009,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70236950,"text":"70236950 - 2022 - Upper Rio Grande Basin water-resource status and trends: Focus area study review and synthesis","interactions":[],"lastModifiedDate":"2024-05-16T15:46:58.587708","indexId":"70236950","displayToPublicDate":"2022-08-31T06:58:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12603,"text":"Journal of the American Society of Agricultural and Biological Engineers","active":true,"publicationSubtype":{"id":10}},"title":"Upper Rio Grande Basin water-resource status and trends: Focus area study review and synthesis","docAbstract":"The Upper Rio Grande Basin (URGB) is a critical international water resource under pressure from a myriad of climatic, ecological, infrastructural, water-use, and legal constraints. The objective of this study is to provide a comprehensive assessment of the spatial distribution and temporal trends of selected water-budget components (snow processes, evapotranspiration (ET), streamflow processes, and groundwater storage) using integrated analyses, such as watershed modeling and water availability and use data in the URGB over the past three decades. A spatially distributed snow evolution modeling system simulated snowpack processes over 34 years (1984–2017). It highlighted snow water equivalent declines from -35 to -77 mm/decade with widespread variability across elevation zones and land cover types. Gridded actual ET data from the SSEBop model were developed and tested for the URGB and demonstrated that all land-cover types had significant decreasing trends (1986-2015) ranging from -14 to -80 mm/decade. Conductivity-mass-balance (CMB) hydrograph separation results found that baseflow forms a large component of total streamflow, ranging from 29 to 69% (49% average) of total streamflow at 17 URGB sites upstream of Albuquerque, NM. Three of 4 graphical hydrograph separation methods in the U.S. Geological Survey Groundwater Toolbox were found to be inappropriate for estimating baseflow in the URGB; the most promising method, baseflow index (BFI) Standard, was optimized using CMB data and tested at three URGB sites, with resulting overestimation of 0 to 47%. Simulated changes in groundwater storage were extracted from historical and recent groundwater-flow models of select alluvial basins (San Luis, Española, Middle Rio Grande, and Tularosa-Hueco). In general, decreases in groundwater storage were observed from 1903 to 2013 except for the San Luis alluvial basin (Colorado), where periods of recovery are observed. The PRMS hydrologic model was successfully calibrated for 9 near-native subbasins (Nash-Sutcliffe efficiency 0.47 to 0.85) and parameters translated to the remaining subbasins; compared to simulated near-native flows (with minimal influence of reservoirs or diversions), observed Rio Grande streamgage flows demonstrated reductions of 40% or more for New Mexico and Texas areas of the basin. Significant decreasing trends (1980-2015) in precipitation, snowmelt rate, streamflow, and baseflow were observed at many of the 12 streamgage basins studied, which suggests that the decreasing trends for actual ET may be related to overall decreasing water availability in the basin, with negative implications for agricultural production and groundwater abstraction. Water security concerns arise from our findings of higher fraction precipitation as rain, slower snowmelt rates leading to decreasing streamflow production, and an increasing fraction of baseflow, all of which will affect the timing and magnitude of water available for human needs in the basin.
","language":"English","publisher":"American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org","doi":"10.13031/ja.14964","usgsCitation":"Douglas-Mankin, K., Rumsey, C., Sexstone, G., Ivahnenko, T.I., Houston, N., Chavarria, S., Senay, G.B., Foster, L.K., Thomas, J., Flickinger, A.K., Galanter, A.E., Moeser, C.D., Welborn, T.L., Pedraza, D.E., Lambert, P., and Johnson, M.S., 2022, Upper Rio Grande Basin water-resource status and trends: Focus area study review and synthesis: Journal of the American Society of Agricultural and Biological Engineers, v. 65, no. 4, p. 881-901, https://doi.org/10.13031/ja.14964.","productDescription":"21 p.","startPage":"881","endPage":"901","ipdsId":"IP-133533","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":446605,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.13031/ja.14964","text":"Publisher Index Page"},{"id":407213,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","otherGeospatial":"Upper Rio Grande Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.7314453125,\n 30.410781790845864\n ],\n [\n -102.21679687500001,\n 30.410781790845864\n ],\n [\n -102.21679687500001,\n 38.30718056188316\n ],\n [\n -109.7314453125,\n 38.30718056188316\n ],\n [\n -109.7314453125,\n 30.410781790845864\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"65","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Douglas-Mankin, Kyle R. 0000-0002-3155-3666","orcid":"https://orcid.org/0000-0002-3155-3666","contributorId":223378,"corporation":false,"usgs":false,"family":"Douglas-Mankin","given":"Kyle R.","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":852780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rumsey, Christine 0000-0001-7536-750X crumsey@usgs.gov","orcid":"https://orcid.org/0000-0001-7536-750X","contributorId":146240,"corporation":false,"usgs":true,"family":"Rumsey","given":"Christine","email":"crumsey@usgs.gov","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":852781,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sexstone, Graham A. 0000-0001-8913-0546","orcid":"https://orcid.org/0000-0001-8913-0546","contributorId":203850,"corporation":false,"usgs":true,"family":"Sexstone","given":"Graham A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":852782,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ivahnenko, Tamara I. 0000-0002-1124-7688 ivahnenk@usgs.gov","orcid":"https://orcid.org/0000-0002-1124-7688","contributorId":2050,"corporation":false,"usgs":true,"family":"Ivahnenko","given":"Tamara","email":"ivahnenk@usgs.gov","middleInitial":"I.","affiliations":[{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":false,"id":852783,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Houston, Natalie 0000-0002-6071-4545","orcid":"https://orcid.org/0000-0002-6071-4545","contributorId":206533,"corporation":false,"usgs":true,"family":"Houston","given":"Natalie","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":852784,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chavarria, Shaleene 0000-0001-8792-1010","orcid":"https://orcid.org/0000-0001-8792-1010","contributorId":222578,"corporation":false,"usgs":true,"family":"Chavarria","given":"Shaleene","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":852785,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":852786,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Foster, Linzy K. 0000-0002-7373-7017","orcid":"https://orcid.org/0000-0002-7373-7017","contributorId":259186,"corporation":false,"usgs":true,"family":"Foster","given":"Linzy","email":"","middleInitial":"K.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":852787,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Thomas, Jonathan V. 0000-0003-0903-9713","orcid":"https://orcid.org/0000-0003-0903-9713","contributorId":217874,"corporation":false,"usgs":true,"family":"Thomas","given":"Jonathan V.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":852788,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Flickinger, Allison K. 0000-0002-8638-2569","orcid":"https://orcid.org/0000-0002-8638-2569","contributorId":223702,"corporation":false,"usgs":true,"family":"Flickinger","given":"Allison","email":"","middleInitial":"K.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":852789,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Galanter, Amy E. 0000-0002-2960-0136","orcid":"https://orcid.org/0000-0002-2960-0136","contributorId":205393,"corporation":false,"usgs":true,"family":"Galanter","given":"Amy","email":"","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":852790,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Moeser, C. David 0000-0003-0154-9110","orcid":"https://orcid.org/0000-0003-0154-9110","contributorId":214563,"corporation":false,"usgs":true,"family":"Moeser","given":"C.","email":"","middleInitial":"David","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":852791,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Welborn, Toby L. 0000-0003-4839-2405 tlwelbor@usgs.gov","orcid":"https://orcid.org/0000-0003-4839-2405","contributorId":2295,"corporation":false,"usgs":true,"family":"Welborn","given":"Toby","email":"tlwelbor@usgs.gov","middleInitial":"L.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":852793,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Pedraza, Diana E. 0000-0003-4483-8094","orcid":"https://orcid.org/0000-0003-4483-8094","contributorId":207782,"corporation":false,"usgs":true,"family":"Pedraza","given":"Diana","email":"","middleInitial":"E.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":852796,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Lambert, Patrick M. 0000-0001-6808-2303","orcid":"https://orcid.org/0000-0001-6808-2303","contributorId":296913,"corporation":false,"usgs":false,"family":"Lambert","given":"Patrick M.","affiliations":[{"id":32931,"text":"USGS - Retired","active":true,"usgs":false}],"preferred":false,"id":852794,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Johnson, Michael Scott 0000-0003-2378-7144 johnsonm@usgs.gov","orcid":"https://orcid.org/0000-0003-2378-7144","contributorId":296914,"corporation":false,"usgs":true,"family":"Johnson","given":"Michael","email":"johnsonm@usgs.gov","middleInitial":"Scott","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":852795,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70236251,"text":"70236251 - 2022 - Going beyond low flows: Streamflow drought deficit and duration illuminate distinct spatiotemporal drought patterns and trends in the U.S. during the last century","interactions":[],"lastModifiedDate":"2022-08-31T11:35:53.919041","indexId":"70236251","displayToPublicDate":"2022-08-30T06:32:22","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":"Going beyond low flows: Streamflow drought deficit and duration illuminate distinct spatiotemporal drought patterns and trends in the U.S. during the last century","docAbstract":"Streamflow drought is a recurring challenge, and understanding spatiotemporal patterns of past droughts is needed to manage future water resources. We examined regional patterns in streamflow drought metrics and compared these metrics to low flow timing and magnitude using long-term daily records for 555 minimally disturbed watersheds. For each streamgage, we calculated streamflow drought duration (number of days) and deficit (flow volume below a specified threshold) for each climate year (April 1–March 31). We identified drought using five thresholds (2%–30%) and two approaches: variable thresholds with unique values for each day of the year, and a fixed threshold based on all period-of-record flows. We then analyzed drought trends using the Mann-Kendall test with persistence adjustment for 1921–2020, 1951–2020, and 1981–2020, and computed correlations between annual streamflow drought metrics and climate metrics using values from a monthly water balance model. Spatial patterns in drought metrics were consistent between variable and fixed approaches, though fixed threshold durations were typically longer and variable threshold deficits larger. High interannual variability in drought duration emerged in the central, interior west, and southwestern U.S., with high deficit variability in the interior west. Drought metrics were weakly correlated with low flow magnitude and timing, providing unique information. Drought duration and deficit increased in the southern and western U.S. for both 1951–2020 and 1981–2020, particularly using fixed thresholds, and paralleled trends in aridity. Projections of continued aridification for the southern and western U.S. may increase drought durations and deficits and intensify water availability impacts.
Unselective fishing involves activities that target the entire assemblage rather than specific fish species, size classes, or trophic levels. This common fishing approach has been in practice for decades in inland waters in China but its implications for biodiversity remain unclear. We addressed this issue by studying fish assemblages in freshwater lakes (five fishing lakes, one reference lake, and a total of 51 sampling sites) between pre- and post-fishing time-periods in Eastern China during 2017–2019. The effects of lake, fishing period, and their interactions on fish abundance, biomass, and diversity indices were assessed. Multivariate analysis was conducted to test for differences in fish assemblages among lakes and between fishing periods. After the implementation of fishing activities, significant reductions in fish species richness, abundance, biomass, and all three life-history strategies (opportunistic, equilibrium, and periodic) were observed in fishing lakes, whereas opposite trends were observed in the reference lake. Compositional similarity of fish assemblages among fishing lakes increased over the three-year monitoring period. Our results suggest that unselective fishing reduces fish diversity and homogenizes fish assemblage structure in lakes. These findings have important implications for protecting both biodiversity and fisheries in inland waters in China and are applicable to other countries or regions that rely on fish as a major food source.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watbs.2022.100055","usgsCitation":"Liu, H., Chen, Y., Gozlan, R., Qu, X., Xia, W., Cheng, F., Wang, L., Paukert, C.P., Olden, J., and Xie, S., 2022, Fish diversity reduction and assemblage structure homogenization in lakes: A case study on unselective fishing in China: Water Biology and Security, v. 1, 100055, 8 p., https://doi.org/10.1016/j.watbs.2022.100055.","productDescription":"100055, 8 p.","ipdsId":"IP-129830","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":446626,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watbs.2022.100055","text":"Publisher Index Page"},{"id":433314,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 115,\n 37\n ],\n [\n 115,\n 32\n ],\n [\n 122,\n 32\n ],\n [\n 122,\n 37\n ],\n [\n 115,\n 37\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Liu, Han","contributorId":341500,"corporation":false,"usgs":false,"family":"Liu","given":"Han","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":908513,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Yushun","contributorId":341501,"corporation":false,"usgs":false,"family":"Chen","given":"Yushun","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":908514,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gozlan, Rodolphe E.","contributorId":341502,"corporation":false,"usgs":false,"family":"Gozlan","given":"Rodolphe E.","affiliations":[{"id":81747,"text":"Université de Montpellier","active":true,"usgs":false}],"preferred":false,"id":908515,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Qu, Xiao","contributorId":341503,"corporation":false,"usgs":false,"family":"Qu","given":"Xiao","email":"","affiliations":[{"id":27775,"text":"University of Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":908516,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xia, Wentong","contributorId":341504,"corporation":false,"usgs":false,"family":"Xia","given":"Wentong","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":908517,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cheng, Fei","contributorId":341505,"corporation":false,"usgs":false,"family":"Cheng","given":"Fei","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":908518,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wang, Lizhu","contributorId":341506,"corporation":false,"usgs":false,"family":"Wang","given":"Lizhu","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":908519,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Paukert, Craig P. 0000-0002-9369-8545","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":245524,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","middleInitial":"P.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":908520,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Olden, Julian D.","contributorId":341507,"corporation":false,"usgs":false,"family":"Olden","given":"Julian D.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":908521,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Xie, Songguang","contributorId":341508,"corporation":false,"usgs":false,"family":"Xie","given":"Songguang","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":908522,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70236305,"text":"70236305 - 2022 - Diminishing Arctic lakes","interactions":[],"lastModifiedDate":"2022-09-01T12:13:35.958674","indexId":"70236305","displayToPublicDate":"2022-08-29T07:12:19","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2841,"text":"Nature Climate Change","onlineIssn":"1758-6798","printIssn":"1758-678X","active":true,"publicationSubtype":{"id":10}},"title":"Diminishing Arctic lakes","docAbstract":"The Arctic is home to the largest surface water fraction of any terrestrial biome, containing thousands of low-lying lakes. Now, it appears that some Arctic lakes are drying due to rising air temperatures and autumn rains, causing permafrost to thaw and water bodies to drain.
Modern ecological and environmental sciences are dominated by observational data. As a result, traditional statistical training often leaves scientists ill-prepared for the data analysis tasks they encounter in their work. Bayesian methods provide a more robust and flexible tool for data analysis, as they enable information from different sources to be brought into the modelling process. Bayesian Applications in Evnironmental and Ecological Studies with R and Stan provides a Bayesian framework for model formulation, parameter estimation, and model evaluation in the context of analyzing environmental and ecological data.
Features:
The book is primarily aimed at graduate students and researchers in the environmental and ecological sciences, as well as environmental management professionals. This is a group of people representing diverse subject matter fields, who could benefit from the potential power and flexibility of Bayesian methods.
","language":"English","publisher":"Chapman and Hall/CRC","doi":"10.1201/9781351018784","usgsCitation":"Qian, S.S., Dufour, M.R., and Alameddine, I., 2022, Bayesian applications in environmental and ecological studies with R and Stan, 415 p., https://doi.org/10.1201/9781351018784.","productDescription":"415 p.","ipdsId":"IP-134860","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":407695,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2022-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Qian, Song S.","contributorId":198934,"corporation":false,"usgs":false,"family":"Qian","given":"Song","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":842387,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dufour, Mark Richard 0000-0001-6930-7666","orcid":"https://orcid.org/0000-0001-6930-7666","contributorId":291450,"corporation":false,"usgs":true,"family":"Dufour","given":"Mark","email":"","middleInitial":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":842388,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alameddine, Ibrahim","contributorId":244836,"corporation":false,"usgs":false,"family":"Alameddine","given":"Ibrahim","affiliations":[{"id":40455,"text":"American University of Beirut","active":true,"usgs":false}],"preferred":false,"id":842389,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}