Rangeland managers need tools to control invasive annual grasses, particularly following wildfire. We assessed responses of native and invasive/exotic grasses to the MB906 soil amendment containing live cultures of a purportedly weed-suppressive strain of the bacterium Pseudomonas fluorescens (“WSB”). MB906 was applied alone and in combination with the pre-emergent herbicide imazapic on >3000 ha across three sagebrush-steppe landscapes burned several months prior. Replicate plots of each treatment type were established and plant cover was measured in the following three years. Cover of invasive-annual grasses (“IAG”) was not responsive to MB906 when all IAG species were considered (“IAG-All”). However, MB906 led to a 54% reduction in the IAG's that were previously reported to be controlled by WSB (“IAG-Target”) in the second year following application (IAG-Target = cheatgrass, Bromus tectorum and medusahead, Taeniatherum caput-medusae; IAG-All also includes Vulpia myuros and Bromus arvensis). MB906 reduced the effectiveness of co-applied imazapic: Imazapic alone reduced IAG-All by 83% and 68% in years 1 and 2, respectively, while imazapic+MB906 reduced IAG-All by 48% and 38% in years 1 and 2, respectively, across all landscapes, and a similar response pattern was observed for IAG-Target. Perennial grass cover was unaffected by the treatments except where it increased 4-fold in response to imazapic applied at a high rate (0.140 kg a.i. ha−1) in one of the landscapes. Tank mixing MB906 and herbicide may have lessened the biological activity of the herbicide by altering the pH or mineral content of the spray solution or by direct metabolism of the herbicide by the bacteria. These results do not provide strong support for MB906 as a tool for annual grass control, though they suggest further investigation may be warranted.
Most state and provincial fish and wildlife agencies have access to important information about patterns in sportsperson participation through their license databases. Using transaction data from Nebraska Game and Parks Commission's electronic hunting and fishing license system, we tracked license purchases of Nebraska, USA, resident license holders in 2010 through 2017. We categorized sportspersons by gender and yearly purchases as hunting only (Hunter), fishing only (Angler), a combination of hunting and fishing (Hunter–Angler), or no purchases (Inactive). The probability of movement among active sportsperson groups was limited and varied little based on initial group participation. The Angler group had the greatest probability of an individual transitioning to the Inactive group (females = 0.39; males = 0.33). The Hunter–Angler group had the greatest probability of an individual remaining within the same group (females = 0.65; males = 0.76). There was a relatively low probability of an individual in the Hunter group moving to the Angler group and vice versa (≤0.02). The sportsperson population is dynamic and understanding patterns of sportsperson participation is important for the future of fish and wildlife management in North America. Using data readily available to most fish and wildlife agencies has the potential to significantly improve our understanding of hunter and angler participation and aid management agencies and conservation organizations in the development of more effective strategies for managing sportspersons. © 2020 The Wildlife Society.
Background
Biological controls with predators of larval mosquito vectors have historically focused almost exclusively on insectivorous animals, with few studies examining predatory plants as potential larvacidal agents. In this study, we experimentally evaluate a generalist plant predator of North America, Utricularia macrorhiza, the common bladderwort, and evaluate its larvacidal efficiency for the mosquito vectors Aedes aegypti and Aedes albopictus in no-choice, laboratory experiments. We sought to determine first, whether U. macrorhiza is a competent predator of container-breeding mosquitoes, and second, its predation efficiency for early and late instar larvae of each mosquito species.
Methods
Newly hatched, first instar Aedes albopictus and Aedes aegypti larvae were separately exposed in cohorts of 10 to field collected U. macrorhiza cuttings. Data on development time and larval survival were collected on a daily basis to ascertain the effectiveness of U. macrorhiza as a larval predator. Survival models were used to assess differences in larval survival between cohorts that were exposed to U. macrorhiza and those that were not. A permutation analysis was used to investigate whether storing U. macrorhiza in laboratory conditions for extended periods of time (1 month vs. 6 months) affected its predation efficiency.
Results
Our results indicated a 100% and 95% reduction of survival of Ae. aegypti and Ae. albopictus larvae respectively, in the presence of U. macrorhiza relative to controls within five days, with peak larvacidal efficiency in plant cuttings from ponds collected in August. Utricularia macrorhiza cuttings, which were prey-deprived, and maintained in laboratory conditions for 6 months were more effective larval predators than cuttings, which were maintained prey-free for 1 month.
Conclusions
Due to the combination of high predation efficiency and the unique biological feature of facultative predation, we suggest that U. macrorhiza warrants further development as a method for larval mosquito control.
No abstract available.
","language":"English","publisher":"PNAS","doi":"10.1073/pnas.2000713117","usgsCitation":"Geremia, C., Merkle, J., White, P.J., and Kauffman, M., 2020, Reply to Craine: Bison redefine what it means to move to find food: PNAS - Proceedings of the National Academy of Sciences of the United States of America, v. 117, no. 17, 2 p., https://doi.org/10.1073/pnas.2000713117.","productDescription":"2 p.","ipdsId":"IP-118446","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":457010,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7196808","text":"Publisher Index Page"},{"id":396741,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"117","issue":"17","noUsgsAuthors":false,"publicationDate":"2020-04-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Geremia, Chris","contributorId":167003,"corporation":false,"usgs":false,"family":"Geremia","given":"Chris","email":"","affiliations":[],"preferred":false,"id":837107,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Merkle, Jerod A.","contributorId":287300,"corporation":false,"usgs":false,"family":"Merkle","given":"Jerod A.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":837106,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"White, P. J.","contributorId":287825,"corporation":false,"usgs":false,"family":"White","given":"P.","email":"","middleInitial":"J.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":837105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":202921,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":837108,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70209199,"text":"sim3455 - 2020 - Potentiometric surface and hydrologic conditions of the South Coast aquifer, Santa Isabel area, Puerto Rico, March–April, 2014","interactions":[],"lastModifiedDate":"2020-05-07T10:45:27.668534","indexId":"sim3455","displayToPublicDate":"2020-04-21T06:42:53","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3455","displayTitle":"Potentiometric Surface and Hydrologic Conditions of the South Coast Aquifer, Santa Isabel Area, Puerto Rico, March–April, 2014","title":"Potentiometric surface and hydrologic conditions of the South Coast aquifer, Santa Isabel area, Puerto Rico, March–April, 2014","docAbstract":"A potentiometric surface map of the South Coast aquifer near Santa Isabel, Puerto Rico, was created from data collected during a synoptic survey of groundwater levels at 55 wells from March 31 to April 17, 2014. Measured groundwater level values ranged from −22.8 to 185.4 feet above mean sea level. During the study period, cumulative rainfall of 0.65 inch was recorded in the study area. Measurements of instantaneous streamflow at 15 locations in streams and irrigation canals, and locations of irrigation ponds, provide additional information about the hydrologic setting. Results of the study indicate a cone of depression was present near the center and eastern parts of the Santa Isabel area of southern Puerto Rico, and a small, deeper cone of depression existed west of Santa Isabel and Rio Coamo. These cones of depression represent areas where the potentiometric surface was below mean sea level. The long-term persistence of such conditions could result in seawater intrusion and an increase in concentrations of total dissolved solids within the South Coast aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3455","collaboration":"Prepared in cooperation with the Puerto Rico Department of Natural and Environmental Resources","usgsCitation":"Ramos, F.A., and Santiago, A.A., 2020, Potentiometric surface and hydrologic conditions of the South Coast aquifer, Santa Isabel area, Puerto Rico, March–April, 2014: U.S. Geological Survey Scientific Investigations Map 3455, 4 p., 1 sheet, https://doi.org/10.3133/sim3455.","productDescription":"Pamphlet: vi, 4 p.; Sheet: 35.68 inches x 28.17 inches; Data Release","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-064406","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":374025,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NS0STQ","text":"USGS data release","linkHelpText":"Data and shapefiles for the potentiometric surface of the South Coast aquifer and hydrologic conditions in the Santa Isabel area, Puerto Rico, March–April 2014"},{"id":374019,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3455/coverthb.jpg"},{"id":374021,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3455/sim3455.pdf","text":"Pamphlet","size":"350 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3455 Pamphlet"},{"id":374022,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3455/sim3455_sheet.pdf","text":"Sheet 1—","size":"4.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3455 Sheet","linkHelpText":"Potentiometric Surface and Hydrologic Conditions of the South Coast Aquifer, Santa Isabel Area, Puerto Rico, March–April, 2014"}],"country":"United States","state":"Puerto Rico","otherGeospatial":"Santa Isabel Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.4779281616211,\n 17.932682319509986\n ],\n [\n -66.29854202270508,\n 17.932682319509986\n ],\n [\n -66.29854202270508,\n 18.029995361346103\n ],\n [\n -66.4779281616211,\n 18.029995361346103\n ],\n [\n -66.4779281616211,\n 17.932682319509986\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
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Constructed rock reefs have been used to remediate spawning habitat for Lake Sturgeon (Acipenser fulvescens) and other lithophilic spawning fishes in the St. Clair-Detroit River System, North America. Early projects used a cross-channel design and species-specific metrics (e.g., proximity to historical spawning locations) to guide reef placement. However, the Middle Channel Reefs and portions of other early projects were compromised by fine sediment accumulation. Therefore, geomorphological criteria were considered in siting reefs constructed after 2013 to avoid sediment sources and improve the likelihood of successful reef function. To evaluate the effectiveness of the revised placement process, we quantified physical maturation of constructed reefs using annual side-scan and down-looking sonar surveys beginning in 2014 and underwater video surveys beginning in 2015. Reef areas and hardness were measured from sonar surveys and underwater video was used to quantify surficial sediment composition. Size and hardness of reefs developed using geomorphological criteria decreased with time, but at rates slower than what was observed at the Middle Channel Reefs. Sediment composition of the reefs remained similar through 2017 and prevalence of reef rock was high, except at Hart's Light Reef, where dreissenid mussel shells composed 32% of the surficial substrate by age three. However, accumulation of fine sediments was documented at all reefs in 2018. Despite using geomorphic criteria to identify areas most suitable for reef construction, reef sediment composition has changed, and future reef restoration projects could benefit by incorporating methods for maintenance, in addition to using geomorphic criteria, to identify restoration sites.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2020.105837","usgsCitation":"Fischer, J., Roseman, E., Mayer, C., and Wills, T., 2020, If you build it and they come, will they stay? Maturation of constructed fish spawning reefs in the St. Clair-Detroit River System: Ecological Engineering, v. 150, 105837, 13 p., https://doi.org/10.1016/j.ecoleng.2020.105837.","productDescription":"105837, 13 p.","ipdsId":"IP-106280","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":377216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Michigan, Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.5018310546875,\n 42.524748042348165\n ],\n [\n -82.3040771484375,\n 43.0287452513488\n ],\n [\n -82.584228515625,\n 43.03677585761058\n ],\n [\n -82.6611328125,\n 42.62587560259137\n ],\n [\n -82.69958496093749,\n 42.476148570254516\n ],\n [\n -82.5018310546875,\n 42.524748042348165\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.8424072265625,\n 42.313877566161864\n ],\n [\n -82.8753662109375,\n 42.407234661551875\n ],\n [\n -83.0950927734375,\n 42.370720143531976\n ],\n [\n -83.2049560546875,\n 42.224449701009725\n ],\n [\n -83.243408203125,\n 42.049292638686836\n ],\n [\n -83.2159423828125,\n 41.983994270935625\n ],\n [\n -83.0291748046875,\n 42.037054301883806\n ],\n [\n -83.03466796874999,\n 42.21224516288584\n ],\n [\n -83.023681640625,\n 42.293564192170095\n ],\n [\n -82.8424072265625,\n 42.313877566161864\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"150","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fischer, Jason 0000-0001-7226-6500 jfischer@usgs.gov","orcid":"https://orcid.org/0000-0001-7226-6500","contributorId":200339,"corporation":false,"usgs":true,"family":"Fischer","given":"Jason","email":"jfischer@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":795244,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roseman, Edward F. 0000-0002-5315-9838","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":217909,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":795245,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mayer, Christine","contributorId":237769,"corporation":false,"usgs":false,"family":"Mayer","given":"Christine","affiliations":[{"id":47604,"text":"University of Toledo, Lake Erie Center","active":true,"usgs":false}],"preferred":false,"id":795246,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wills, Todd","contributorId":237770,"corporation":false,"usgs":false,"family":"Wills","given":"Todd","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":795247,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70209640,"text":"fs20203022 - 2020 - Nature’s Notebook-A tool for recording the timing of seasonal activity of plants and animals","interactions":[],"lastModifiedDate":"2020-04-21T14:25:37.241199","indexId":"fs20203022","displayToPublicDate":"2020-04-20T13:15:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3022","displayTitle":"Nature’s Notebook—A Tool for Recording the Timing of Seasonal Activity of Plants and Animals","title":"Nature’s Notebook-A tool for recording the timing of seasonal activity of plants and animals","docAbstract":"Nature's Notebook is a customizable program used by individual observers and Federal Government partners to document patterns in phenology—the timing of seasonal activity of plants and animals over the course of the calendar year. The USA National Phenology Network (USA-NPN) established Nature's Notebook in 2009 to create a standard approach for collecting phenology data on plants and animals across the country. Currently, about half of the data are submitted by independent backyard observers at individual sites and half are submitted by groups of participants as part of a Local Phenology Program. With support from the U.S. Geological Survey, the USA-NPN collects, organizes, and shares data on phenology. This information aids decision making, scientific discovery, and the development of a broader understanding of phenology.
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Near-field remote sensing of surface velocity and river discharge (discharge) were measured using coherent, continuous wave Doppler and pulsed radars. Traditional streamgaging requires sensors be deployed in the water column; however, near-field remote sensing has the potential to transform streamgaging operations through non-contact methods in the U.S. Geological Survey (USGS) and other agencies around the world. To differentiate from satellite or high-altitude platforms, near-field remote sensing is conducted from fixed platforms such as bridges and cable stays. Radar gages were collocated with 10 USGS streamgages in river reaches of varying hydrologic and hydraulic characteristics, where basin size ranged from 381 to 66,200 square kilometers. Radar-derived mean-channel (mean) velocity and discharge were computed using the probability concept and were compared to conventional instantaneous measurements and time series. To test the efficacy of near-field methods, radars were deployed for extended periods of time to capture a range of hydraulic conditions and environmental factors. During the operational phase, continuous time series of surface velocity, radar-derived discharge, and stage-discharge were recorded, computed, and transmitted contemporaneously and continuously in real time every 5 to 15 min. Minimum and maximum surface velocities ranged from 0.30 to 3.84 m per second (m/s); minimum and maximum radar-derived discharges ranged from 0.17 to 4890 cubic meters per second (m3/s); and minimum and maximum stage-discharge ranged from 0.12 to 4950 m3/s. Comparisons between radar and stage-discharge time series were evaluated using goodness-of-fit statistics, which provided a measure of the utility of the probability concept to compute discharge from a singular surface velocity and cross-sectional area relative to conventional methods. Mean velocity and discharge data indicate that velocity radars are highly correlated with conventional methods and are a viable near-field remote sensing technology that can be operationalized to deliver real-time surface velocity, mean velocity, and discharge.
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0000-0001-7313-9298","orcid":"https://orcid.org/0000-0001-7313-9298","contributorId":225685,"corporation":false,"usgs":true,"family":"Holnbeck","given":"Stephen","email":"","middleInitial":"R.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791973,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lotspeich, R. Russell 0000-0002-5572-9064 rlotspei@usgs.gov","orcid":"https://orcid.org/0000-0002-5572-9064","contributorId":3388,"corporation":false,"usgs":true,"family":"Lotspeich","given":"R.","email":"rlotspei@usgs.gov","middleInitial":"Russell","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":false,"id":791974,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Laveau, Christopher 0000-0002-4009-1889","orcid":"https://orcid.org/0000-0002-4009-1889","contributorId":206046,"corporation":false,"usgs":true,"family":"Laveau","given":"Christopher","email":"","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791975,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Moramarco, Tommaso 0000-0002-9870-1694","orcid":"https://orcid.org/0000-0002-9870-1694","contributorId":225686,"corporation":false,"usgs":false,"family":"Moramarco","given":"Tommaso","email":"","affiliations":[{"id":41180,"text":"IRPI-Consiglio Nazionale delle Ricerche","active":true,"usgs":false}],"preferred":false,"id":791976,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Jones, Mark E. 0000-0002-9242-1528","orcid":"https://orcid.org/0000-0002-9242-1528","contributorId":225687,"corporation":false,"usgs":true,"family":"Jones","given":"Mark","email":"","middleInitial":"E.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791977,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Gourley, Jonathan J 0000-0001-7363-3755","orcid":"https://orcid.org/0000-0001-7363-3755","contributorId":225540,"corporation":false,"usgs":false,"family":"Gourley","given":"Jonathan","email":"","middleInitial":"J","affiliations":[{"id":41158,"text":"NOAA/OAR/National Severe Storms Laboratory, Norman, OK, USA 73072","active":true,"usgs":false}],"preferred":false,"id":791978,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wasielewski, Danny","contributorId":225688,"corporation":false,"usgs":false,"family":"Wasielewski","given":"Danny","affiliations":[{"id":41181,"text":"NOAA National Severe Storms Laboratory","active":true,"usgs":false}],"preferred":false,"id":791979,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70210282,"text":"70210282 - 2020 - Biofilms provide new insight into pesticide occurrence in streams and links to aquatic ecological communities","interactions":[],"lastModifiedDate":"2020-05-29T15:28:16.294568","indexId":"70210282","displayToPublicDate":"2020-04-20T10:19:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Biofilms provide new insight into pesticide occurrence in streams and links to aquatic ecological communities","docAbstract":"Streambed sediment is commonly analyzed to assess occurrence of hydrophobic pesticides and risks to aquatic communities. However, stream biofilms also have the potential to accumulate pesticides and may be consumed by aquatic organisms. To better characterize risks to aquatic life, the U.S. Geological Survey Regional Stream Quality Assessment measured 93 current-use and 3 legacy pesticides in bed sediment and biofilm from 54 small streams in California across a range of land-use settings. On average, 4 times as many current-use pesticides were detected in biofilm at a site (median of 2) as in sediment (median of 0.5). Of 31 current-use pesticides detected, 20 were detected more frequently in biofilm than sediment and 10 equally frequently. Pyrethroids as a class were the most potentially toxic to benthic invertebrates, and of the nine pyrethroids detected, seven occurred more frequently in biofilm than sediment. We constructive General Additive Models to investigate relations between pesticides and six metrics of benthic community structure. Pesticides in biofilm improved fit in four of the six models, and pesticides in sediment improved fit in two. The results indicate that sampling of stream biofilms can complement bed-sediment sampling by identifying more current-use pesticides present and better estimating ecological risks.","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.9b07430","usgsCitation":"Mahler, B., Schmidt, T., Nowell, L.H., Qi, S.L., Van Metre, P.C., Hladik, M.L., Carlisle, D.M., Munn, M., and May, J., 2020, Biofilms provide new insight into pesticide occurrence in streams and links to aquatic ecological communities: Environmental Science & Technology, v. 54, no. 9, p. 5509-5519, https://doi.org/10.1021/acs.est.9b07430.","productDescription":"11 p.","startPage":"5509","endPage":"5519","ipdsId":"IP-114380","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":437021,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YYD8DI","text":"USGS data release","linkHelpText":"Concentrations of pesticides associated with streambed sediment and biofilm in California streams, 2017"},{"id":375146,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.520263671875,\n 34.34343606848294\n ],\n [\n -118.5205078125,\n 34.813803317113155\n ],\n [\n -120.684814453125,\n 37.21283151445594\n ],\n [\n -121.56372070312499,\n 38.487994609214795\n ],\n [\n -122.025146484375,\n 39.027718840211605\n ],\n [\n -123.53027343749999,\n 38.75408327579141\n ],\n [\n -122.64038085937499,\n 37.32648861334206\n ],\n [\n -121.95922851562501,\n 36.29741818650811\n ],\n [\n -120.69580078125001,\n 34.89494244739732\n ],\n [\n -120.62988281249999,\n 34.50655662164561\n ],\n [\n -119.520263671875,\n 34.34343606848294\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"9","noUsgsAuthors":false,"publicationDate":"2020-04-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Mahler, Barbara 0000-0002-9150-9552 bjmahler@usgs.gov","orcid":"https://orcid.org/0000-0002-9150-9552","contributorId":1249,"corporation":false,"usgs":true,"family":"Mahler","given":"Barbara","email":"bjmahler@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - 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Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":789940,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Munn, Mark D. 0000-0002-7154-7252","orcid":"https://orcid.org/0000-0002-7154-7252","contributorId":205360,"corporation":false,"usgs":true,"family":"Munn","given":"Mark D.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":789941,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"May, Jason 0000-0002-5699-2112","orcid":"https://orcid.org/0000-0002-5699-2112","contributorId":224991,"corporation":false,"usgs":false,"family":"May","given":"Jason","affiliations":[{"id":41015,"text":"Deceased (ex-USGS)","active":true,"usgs":false}],"preferred":false,"id":789937,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70210970,"text":"70210970 - 2020 - Subduction megathrust heterogeneity characterized from 3D seismic data","interactions":[],"lastModifiedDate":"2020-07-08T15:21:30.577495","indexId":"70210970","displayToPublicDate":"2020-04-20T10:13:50","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Subduction megathrust heterogeneity characterized from 3D seismic data","docAbstract":"Megathrust roughness and structural complexity are thought to be controls on earthquake slip at subduction zones because they result in heterogeneity in shear strength and resolved stress. However, because active megathrust faults are difficult to observe, the causes and scales of complexity are largely unknown. Here we measured the in situ properties of the megathrust of the Middle America subduction zone in a three-dimensional seismic reflection volume to determine how fault properties vary. We quantify spatial variability in the megathrust roughness, overburden and rock physical properties. Heterogeneity in the megathrust roughness exists at length scales of a few kilometres because the megathrust is dissected by active lower-plate normal faults, which offset the megathrust and renewed fault roughness. Spatial variations in the rock physical properties at the plate interface are characterized by correlation length scales of hundreds of metres. Frontal prism taper, historical seismicity and the variation in earthquake stress drop values local to the megathrust are all affected by the heterogeneity at these length scales. Both geometric and rheological complexities may therefore control the mechanical behaviour of the subduction plate interface, which includes earthquake rupture characteristics.
","language":"English","publisher":"Nature","doi":"10.1038/s41561-020-0562-9","usgsCitation":"Kirkpatrick, J.D., Edwards, J.H., Verdecchia, A., Kluesner, J.W., Harrington, R.M., and Silver, E., 2020, Subduction megathrust heterogeneity characterized from 3D seismic data: Nature Geoscience, v. 13, p. 369-374, https://doi.org/10.1038/s41561-020-0562-9.","productDescription":"6 p.","startPage":"369","endPage":"374","ipdsId":"IP-106884","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467292,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.mcgill.ca/concern/articles/pc289q07k","text":"External Repository"},{"id":376202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Costa Rica","otherGeospatial":"Central America megathrust, Pacific Ocean","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.68212890625,\n 8.222363866437243\n ],\n [\n -83.77349853515625,\n 8.222363866437243\n ],\n [\n -83.77349853515625,\n 9.584500864717143\n ],\n [\n -86.68212890625,\n 9.584500864717143\n ],\n [\n -86.68212890625,\n 8.222363866437243\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2020-04-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Kirkpatrick, James D.","contributorId":202603,"corporation":false,"usgs":false,"family":"Kirkpatrick","given":"James","email":"","middleInitial":"D.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":792312,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edwards, Joel H.","contributorId":202599,"corporation":false,"usgs":false,"family":"Edwards","given":"Joel","email":"","middleInitial":"H.","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":792313,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Verdecchia, Alessandro","contributorId":228863,"corporation":false,"usgs":false,"family":"Verdecchia","given":"Alessandro","email":"","affiliations":[{"id":41521,"text":"Ruhr-Universität Bochum","active":true,"usgs":false}],"preferred":false,"id":792314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kluesner, Jared W. 0000-0003-1701-8832 jkluesner@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-8832","contributorId":201261,"corporation":false,"usgs":true,"family":"Kluesner","given":"Jared","email":"jkluesner@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":792315,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harrington, Rebecca M.","contributorId":146633,"corporation":false,"usgs":false,"family":"Harrington","given":"Rebecca","email":"","middleInitial":"M.","affiliations":[{"id":16736,"text":"Dept. of Earth and Planetary Sci,.McGill Univ., Montreal, Quebec","active":true,"usgs":false}],"preferred":false,"id":792316,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Silver, Eli","contributorId":173114,"corporation":false,"usgs":false,"family":"Silver","given":"Eli","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":792317,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70210161,"text":"70210161 - 2020 - The Landsat Burned Area algorithm and products for the conterminous United States","interactions":[],"lastModifiedDate":"2022-04-14T19:23:11.991912","indexId":"70210161","displayToPublicDate":"2020-04-20T10:12:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"The Landsat Burned Area algorithm and products for the conterminous United States","docAbstract":"Complete and accurate burned area map data are needed to document spatial and temporal patterns of fires, to quantify their drivers, and to assess the impacts on human and natural systems. In this study, we developed the Landsat Burned Area (BA) algorithm, an update from the Landsat Burned Area Essential Climate Variable (BAECV) algorithm. Here, we present the BA algorithm and products, changes relative to the BAECV algorithm and products, and updated validation metrics. We also present spatial and temporal patterns of burned area across the conterminous U.S., how burned area varies in relation to the number of operational Landsat sensors, and a comparison with other burned area datasets, including the BAECV, Monitoring Trends in Burn Severity (MTBS), GeoMAC, and Moderate Resolution Imaging Spectroradiometer (MODIS) MCD64A1.006 data. The BA algorithm identifies burned areas in analysis ready data (ARD) time-series of Landsat imagery from 1984 through 2018 using machine learning, thresholding, and image segmentation. Validation with reference data from high-resolution commercial satellite imagery resulted in omission and commission error rates averaging 19% and 41%, respectively. In comparison, validation with Landsat reference data had omission and commission error rates averaging 40% and 28%, respectively when burned areas in cultivated crops and pasture/hay land-cover types were excluded. Both validation tests documented lower commission error rates relative to the BAECV products. The amount of burned area detected varies not only in response to climate but also with the number of operational sensors and scenes collected. The combined amount of burned area detected by multiple sensors was larger than from any individual sensor, but there was no significant difference between individual sensors. Therefore, we used BA products from individual sensors to assess trends over time and all available sensors to compare with other existing BA products. From 1984 through 2018, annual burned area averaged 30,000 km2, ranged between 14,000 km2 in 1991 and 46,500 km2 in 2012, and increased over time at a rate of 356 km2/year. Compared to existing burned area products, the new Landsat BA products identified 29% more burned area than the BAECV products (1984–2015), 183% more than the MTBS/GeoMAC products (1984–2018), and 56% more than the MCD64A1.006 products (2003–2018). The products had similar patterns of year-to-year variability; the R2 values of linear regressions between annual burned area were >0.70 with the BAECV products and the MTBS/GeoMAC products, but somewhat lower for the MCD64A1.006 product (R2 = 0.66). The BA products are routinely produced as new Landsat data are collected and provide a unique data source to monitor and assess the spatial and temporal patterns and the impacts of fire.","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2020.111801","usgsCitation":"Hawbaker, T., Vanderhoof, M.K., Schmidt, G.L., Beal, Y.G., Picotte, J.J., Takacs, J., Falgout, J.T., and Dwyer, J.L., 2020, The Landsat Burned Area algorithm and products for the conterminous United States: Remote Sensing of Environment, v. 244, 111801, 24 p., https://doi.org/10.1016/j.rse.2020.111801.","productDescription":"111801, 24 p.","ipdsId":"IP-111890","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central 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mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":789349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmidt, Gail L. 0000-0002-9684-8158 gschmidt@usgs.gov","orcid":"https://orcid.org/0000-0002-9684-8158","contributorId":3475,"corporation":false,"usgs":true,"family":"Schmidt","given":"Gail","email":"gschmidt@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":789350,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beal, Yen-Ju G. 0000-0002-5538-5687 ygbeal@usgs.gov","orcid":"https://orcid.org/0000-0002-5538-5687","contributorId":5328,"corporation":false,"usgs":true,"family":"Beal","given":"Yen-Ju","email":"ygbeal@usgs.gov","middleInitial":"G.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":789463,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Picotte, Joshua J. 0000-0002-4021-4623 jpicotte@usgs.gov","orcid":"https://orcid.org/0000-0002-4021-4623","contributorId":4626,"corporation":false,"usgs":true,"family":"Picotte","given":"Joshua","email":"jpicotte@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":789352,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Takacs, Joshua 0000-0003-1509-5498 jdtakacs@usgs.gov","orcid":"https://orcid.org/0000-0003-1509-5498","contributorId":194380,"corporation":false,"usgs":true,"family":"Takacs","given":"Joshua","email":"jdtakacs@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":789353,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Falgout, Jeff T. 0000-0002-7108-477X jfalgout@usgs.gov","orcid":"https://orcid.org/0000-0002-7108-477X","contributorId":4957,"corporation":false,"usgs":true,"family":"Falgout","given":"Jeff","email":"jfalgout@usgs.gov","middleInitial":"T.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":789354,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dwyer, John L. 0000-0002-8281-0896 dwyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8281-0896","contributorId":3481,"corporation":false,"usgs":true,"family":"Dwyer","given":"John","email":"dwyer@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":789355,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70214062,"text":"70214062 - 2020 - Localized outbreaks of coral disease on Arabian reefs are linked to extreme temperatures and environmental stressors","interactions":[],"lastModifiedDate":"2020-09-22T14:52:08.334936","indexId":"70214062","displayToPublicDate":"2020-04-20T09:44:45","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1338,"text":"Coral Reefs","active":true,"publicationSubtype":{"id":10}},"title":"Localized outbreaks of coral disease on Arabian reefs are linked to extreme temperatures and environmental stressors","docAbstract":"The Arabian Peninsula borders the hottest reefs in the world, and corals living in these extreme environments can provide insight into the effects of warming on coral health and disease. Here, we examined coral reef health at 17 sites across three regions along the northeastern Arabian Peninsula (Persian Gulf, Strait of Hormuz and Oman Sea) representing a gradient of environmental conditions. The Persian Gulf has extreme seasonal fluctuations in temperature and chronic hypersalinity, whereas the other two regions experience more moderate conditions. Field surveys identified 13 coral diseases including tissue loss diseases of unknown etiology (white syndromes) in Porites, Platygyra, Dipsastraea, Cyphastrea, Acropora and Goniopora; growth anomalies in Porites, Platygyra and Dipsastraea; black band disease in Platygyra, Dipsastraea, Acropora, Echinopora and Pavona; bleached patches in Porites and Goniopora and a disease unique to this region, yellow-banded tissue loss in Porites. The most widespread diseases were Platygyra growth anomalies (52.9% of all surveys), Acropora white syndrome (47.1%) and Porites bleached patches (35.3%). We found a number of diseases not yet reported in this region and found differential disease susceptibility among coral taxa. Disease prevalence was higher on reefs within the Persian Gulf (avg. 2.05%) as compared to reefs within the Strait of Hormuz (0.46%) or Oman Sea (0.25%). A high number of localized disease outbreaks (8 of 17 sites) were found, especially within the Persian Gulf (5 of 8 sites). Across all regions, the majority of variation in disease prevalence (82.2%) was associated with the extreme temperature range experienced by these corals combined with measures of organic pollution and proximity to shore. Thermal stress is known to drive a number of coral diseases, and thus, this region provides a platform to study disease at the edge of corals’ thermal range.
","language":"English","publisher":"Springer","doi":"10.1007/s00338-020-01928-4","usgsCitation":"Aeby, G.S., Howells, E., Work, T.M., Abrego, D., Williams, G.J., Wedding, L.M., Caldwell, J.M., Moritsch, M.M., and Burt, J., 2020, Localized outbreaks of coral disease on Arabian reefs are linked to extreme temperatures and environmental stressors: Coral Reefs, v. 39, p. 829-846, https://doi.org/10.1007/s00338-020-01928-4.","productDescription":"18 p.","startPage":"829","endPage":"846","ipdsId":"IP-117756","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":457021,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00338-020-01928-4","text":"Publisher Index Page"},{"id":378662,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Oman, United Arab Emirates","otherGeospatial":"Gulf of Oman, Persian Gulf, Strait of Hormuz","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 51.8115234375,\n 23.765236889758672\n ],\n [\n 56.953125,\n 23.765236889758672\n ],\n [\n 56.953125,\n 26.667095801104814\n ],\n [\n 51.8115234375,\n 26.667095801104814\n ],\n [\n 51.8115234375,\n 23.765236889758672\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","noUsgsAuthors":false,"publicationDate":"2020-04-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Aeby, Greta S.","contributorId":64783,"corporation":false,"usgs":false,"family":"Aeby","given":"Greta","email":"","middleInitial":"S.","affiliations":[{"id":13394,"text":"Hawai‘i Institute of Marine Biology","active":true,"usgs":false}],"preferred":false,"id":799354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Howells, Emily","contributorId":225444,"corporation":false,"usgs":false,"family":"Howells","given":"Emily","email":"","affiliations":[{"id":41112,"text":"Center for Genomics and Systems Biology, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates","active":true,"usgs":false}],"preferred":false,"id":799355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Work, Thierry M. 0000-0002-4426-9090 thierry_work@usgs.gov","orcid":"https://orcid.org/0000-0002-4426-9090","contributorId":1187,"corporation":false,"usgs":true,"family":"Work","given":"Thierry","email":"thierry_work@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":799356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Abrego, David","contributorId":225447,"corporation":false,"usgs":false,"family":"Abrego","given":"David","email":"","affiliations":[{"id":41113,"text":"Department of Natural Science and Public Health, Zayed University, Abu Dhabi, United Arab Emirates","active":true,"usgs":false}],"preferred":false,"id":799357,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Williams, Gareth J.","contributorId":47898,"corporation":false,"usgs":true,"family":"Williams","given":"Gareth","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":799358,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wedding, Lisa M.","contributorId":241019,"corporation":false,"usgs":false,"family":"Wedding","given":"Lisa","email":"","middleInitial":"M.","affiliations":[{"id":25447,"text":"University of Oxford","active":true,"usgs":false}],"preferred":false,"id":799359,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Caldwell, Jamie M.","contributorId":241020,"corporation":false,"usgs":false,"family":"Caldwell","given":"Jamie","email":"","middleInitial":"M.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":799360,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Moritsch, Monica M","contributorId":149980,"corporation":false,"usgs":false,"family":"Moritsch","given":"Monica","email":"","middleInitial":"M","affiliations":[{"id":17873,"text":"Department of Ecology and Evolutionary Biology, University of California, Santa Cruz CA 95060","active":true,"usgs":false}],"preferred":false,"id":799361,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Burt, John","contributorId":225446,"corporation":false,"usgs":false,"family":"Burt","given":"John","email":"","affiliations":[{"id":41112,"text":"Center for Genomics and Systems Biology, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates","active":true,"usgs":false}],"preferred":false,"id":799362,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70210710,"text":"70210710 - 2020 - Acoustic Sediment Estimation Toolbox (ASET): A software package for calibrating and processing TRDI ADCP data to compute suspended-sediment transport in sandy rivers","interactions":[],"lastModifiedDate":"2020-06-18T14:36:43.859337","indexId":"70210710","displayToPublicDate":"2020-04-20T09:30:06","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1315,"text":"Computers & Geosciences","printIssn":"0098-3004","active":true,"publicationSubtype":{"id":10}},"title":"Acoustic Sediment Estimation Toolbox (ASET): A software package for calibrating and processing TRDI ADCP data to compute suspended-sediment transport in sandy rivers","docAbstract":"Quantifying suspended-sediment transport is critical for a variety of disciplines related to the management of water resources. However, the number of gauging stations and monitoring networks in most rivers around the world is insufficient to improve understanding of river dynamics and support water resource management decisions. This is mainly due to the high operational costs and intensive labor involved in traditional sediment measurement techniques, especially in sand bed rivers where coarse material varies spatially in the river cross section. Recently, the acoustic surrogate method has received attention as a potentially accurate surrogate technology for estimating suspended-sediment concentrations. In addition, the acoustic surrogate method, through use of acoustic Doppler current profilers (ADCPs), has the advantage of being able to simultaneously measure the flow velocity field and cross-sectional area when moving-boat measurements are performed. In spite of the important advances made in the implementation of this technique, there are no widely-available, free tools for processing the ADCP acoustic signal cross section measurements which include options to extrapolate velocity and sediment in unmeasured ADCP zones and develop calibrations with physical samples. This paper presents a new software called Acoustic Sediment Estimation Toolbox (ASET), which enables the user to develop a calibration between the acoustic signal collected with a down-looking Teledyne RD Instruments ADCP and sediment concentrations determined using traditional sediment sampling techniques. Moreover, ASET software uses dynamic ADCP measurements to estimate the total suspended-sediment transport through a river cross section. The theoretical framework and data processing routines applied by each module in ASET are presented. Finally, a comparison is made between the results obtained by ASET and by traditional methodologies for computing suspended-sediment transport in a large river system (Paraná River, Argentina).","language":"English","publisher":"Elsevier","doi":"10.1016/j.cageo.2020.104499","usgsCitation":"Dominguez Ruben, L.G., Szupiany, R., Latosinski, F., Lopez Weibel, C., Wood, M.S., and Boldt, J.A., 2020, Acoustic Sediment Estimation Toolbox (ASET): A software package for calibrating and processing TRDI ADCP data to compute suspended-sediment transport in sandy rivers: Computers & Geosciences, v. 140, https://doi.org/10.1016/j.cageo.2020.104499.","productDescription":"104499, 13 p.","startPage":"Article 104499","ipdsId":"IP-102073","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":375680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Argentina","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-65.5,-55.2],[-66.45,-55.25],[-66.95992,-54.89681],[-67.56244,-54.87001],[-68.63335,-54.8695],[-68.63401,-52.63637],[-68.25,-53.1],[-67.75,-53.85],[-66.45,-54.45],[-65.05,-54.7],[-65.5,-55.2]]],[[[-64.96489,-22.07586],[-64.37702,-22.79809],[-63.98684,-21.99364],[-62.84647,-22.03499],[-62.68506,-22.24903],[-60.84656,-23.88071],[-60.02897,-24.0328],[-58.80713,-24.77146],[-57.77722,-25.16234],[-57.63366,-25.60366],[-58.61817,-27.12372],[-57.60976,-27.3959],[-56.4867,-27.5485],[-55.69585,-27.38784],[-54.78879,-26.62179],[-54.62529,-25.73926],[-54.13005,-25.54764],[-53.62835,-26.12487],[-53.64874,-26.92347],[-54.49073,-27.47476],[-55.16229,-27.88192],[-56.2909,-28.85276],[-57.62513,-30.21629],[-57.87494,-31.01656],[-58.14244,-32.0445],[-58.13265,-33.04057],[-58.34961,-33.26319],[-58.42707,-33.90945],[-58.49544,-34.43149],[-57.22583,-35.28803],[-57.36236,-35.97739],[-56.73749,-36.41313],[-56.78829,-36.90157],[-57.74916,-38.18387],[-59.23186,-38.72022],[-61.23745,-38.92842],[-62.33596,-38.82771],[-62.12576,-39.4241],[-62.33053,-40.17259],[-62.14599,-40.6769],[-62.7458,-41.02876],[-63.77049,-41.16679],[-64.73209,-40.80268],[-65.11804,-41.06431],[-64.97856,-42.058],[-64.30341,-42.35902],[-63.75595,-42.04369],[-63.45806,-42.56314],[-64.3788,-42.87356],[-65.1818,-43.49538],[-65.32882,-44.50137],[-65.56527,-45.03679],[-66.50997,-45.03963],[-67.29379,-45.5519],[-67.58055,-46.30177],[-66.59707,-47.03392],[-65.64103,-47.23613],[-65.98509,-48.13329],[-67.16618,-48.69734],[-67.81609,-49.86967],[-68.72875,-50.26422],[-69.13854,-50.73251],[-68.81556,-51.7711],[-68.14999,-52.34998],[-68.57155,-52.29944],[-69.49836,-52.14276],[-71.9148,-52.00902],[-72.3294,-51.42596],[-72.30997,-50.67701],[-72.97575,-50.74145],[-73.32805,-50.37879],[-73.41544,-49.31844],[-72.64825,-48.87862],[-72.33116,-48.24424],[-72.44736,-47.73853],[-71.91726,-46.88484],[-71.55201,-45.56073],[-71.65932,-44.97369],[-71.22278,-44.78424],[-71.3298,-44.40752],[-71.79362,-44.20717],[-71.46406,-43.78761],[-71.91542,-43.40856],[-72.1489,-42.25489],[-71.7468,-42.05139],[-71.91573,-40.83234],[-71.68076,-39.80816],[-71.41352,-38.91602],[-70.81466,-38.553],[-71.11863,-37.57683],[-71.12188,-36.65812],[-70.36477,-36.00509],[-70.38805,-35.16969],[-69.81731,-34.19357],[-69.81478,-33.27389],[-70.0744,-33.09121],[-70.53507,-31.36501],[-69.91901,-30.33634],[-70.01355,-29.36792],[-69.65613,-28.45914],[-69.00123,-27.52121],[-68.29554,-26.89934],[-68.5948,-26.50691],[-68.386,-26.18502],[-68.41765,-24.51855],[-67.32844,-24.0253],[-66.98523,-22.98635],[-67.10667,-22.73592],[-66.27334,-21.83231],[-64.96489,-22.07586]]]]},\"properties\":{\"name\":\"Argentina\"}}]}","volume":"140","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dominguez Ruben, Lucas Gerardo","contributorId":225404,"corporation":false,"usgs":false,"family":"Dominguez Ruben","given":"Lucas","email":"","middleInitial":"Gerardo","affiliations":[{"id":41098,"text":"Littoral National University, Argentina","active":true,"usgs":false}],"preferred":false,"id":791058,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Szupiany, Ricardo","contributorId":225405,"corporation":false,"usgs":false,"family":"Szupiany","given":"Ricardo","affiliations":[{"id":41098,"text":"Littoral National University, Argentina","active":true,"usgs":false}],"preferred":false,"id":791059,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Latosinski, Francisco","contributorId":225406,"corporation":false,"usgs":false,"family":"Latosinski","given":"Francisco","affiliations":[{"id":41099,"text":"National Scientific and Technical Research Council, Argentina","active":true,"usgs":false}],"preferred":false,"id":791060,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lopez Weibel, Cecilia","contributorId":225407,"corporation":false,"usgs":false,"family":"Lopez Weibel","given":"Cecilia","affiliations":[{"id":32938,"text":"Littoral National University","active":true,"usgs":false}],"preferred":false,"id":791061,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wood, Molly S. 0000-0002-5184-8306 mswood@usgs.gov","orcid":"https://orcid.org/0000-0002-5184-8306","contributorId":788,"corporation":false,"usgs":true,"family":"Wood","given":"Molly","email":"mswood@usgs.gov","middleInitial":"S.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":791062,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boldt, Justin A. 0000-0002-0771-3658","orcid":"https://orcid.org/0000-0002-0771-3658","contributorId":207849,"corporation":false,"usgs":true,"family":"Boldt","given":"Justin","email":"","middleInitial":"A.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791063,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70228074,"text":"70228074 - 2020 - Identifying candidate reference reaches to assess the physical and biological integrity of wadeable streams in different ecoregions and among stream sizes","interactions":[],"lastModifiedDate":"2022-02-16T14:39:39.755202","indexId":"70228074","displayToPublicDate":"2020-04-20T08:32:06","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Identifying candidate reference reaches to assess the physical and biological integrity of wadeable streams in different ecoregions and among stream sizes","docAbstract":"Efforts to quantify disturbances to aquatic systems often use landscape-level metrics, presumably linked to ecological integrity, but fewer studies have directly linked ecological integrity to instream habitat, and applied these results to unsampled stream reaches throughout a landscape. We developed a flexible, quantitative approach that characterizes stream impairment across a landscape and identifies least-disturbed stream reaches to serve as benchmarks for high quality physical habitat and ecological integrity. Fish and macroinvertebrate community characteristics, reach-level physical habitat and water quality metrics were summarized in 891 wadeable stream reaches across two ecoregions in Missouri, USA. The influence of reach and water-quality characteristics as well as landscape-level variables on 7 fish and 3 macroinvertebrate community biological indicator metrics was then modeled using boosted regression trees (BRTs). On average, reach-level models explained more variance (25 and 27% in the two ecoregions examined) in biotic metrics than landscape-level models (18% and 20%). Abiotic and biotic associations differed among ecoregions and stream sizes, however, reach-level habitat (e.g., bankfull width/depth ratio, channel incision height) and water quality (e.g., dissolved oxygen, total chlorophyll) were consistently top predictors. At the landscape scale, fish richness in the agriculturally dominated ecoregion increased with decreased fragmentation/flow modification, while invertebrate metrics responded to agricultural disturbances. Invertebrate metrics in the forested ecoregion showed community degradation apparent with crop coverage as low as 8-10% of the riparian zone, while urban impairment was best detected using invertebrate indicators of biotic integrity and measures of fish trophic ecology. Relationships among landscape-scale variables and reach characteristics identified as top predictors in BRTs also highlighted potential mechanistic relationships among landscape, habitat, and measures of ecological integrity. Using the results of the landscape-level models, estimates for overall ecological integrity were predicted for over 28,000 stream reaches throughout Missouri, and a total of 1,423 candidate reference reaches were identified. The objective approach to characterizing stream impairment developed in this study offers specific advantages, including a reach and landscape-level evaluation of human disturbance as well as an inductive, multi-metric determination of ecological integrity.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2019.105966","usgsCitation":"Paukert, C.P., Kleeklamp, E.R., and Tingley, R.W., 2020, Identifying candidate reference reaches to assess the physical and biological integrity of wadeable streams in different ecoregions and among stream sizes: Ecological Indicators, v. 111, 105966, 15 p., https://doi.org/10.1016/j.ecolind.2019.105966.","productDescription":"105966, 15 p.","ipdsId":"IP-097233","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395344,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"111","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"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":833017,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kleeklamp, Ethan R.","contributorId":274478,"corporation":false,"usgs":false,"family":"Kleeklamp","given":"Ethan","email":"","middleInitial":"R.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":833018,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tingley, Ralph William 0000-0002-1689-2133","orcid":"https://orcid.org/0000-0002-1689-2133","contributorId":258043,"corporation":false,"usgs":true,"family":"Tingley","given":"Ralph","email":"","middleInitial":"William","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":833062,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70222531,"text":"70222531 - 2020 - Hydrologically induced deformation in Long Valley Caldera and adjacent Sierra Nevada","interactions":[],"lastModifiedDate":"2021-08-03T12:45:57.564571","indexId":"70222531","displayToPublicDate":"2020-04-20T07:43:24","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologically induced deformation in Long Valley Caldera and adjacent Sierra Nevada","docAbstract":"Vertical and horizontal components of GNSS displacements in the Long Valley Caldera and adjacent Sierra Nevada range show a clear correlation with hydrological trends at both multiyear and seasonal time scales. We observe a clear vertical and horizontal seasonal deformation pattern primarily attributable to the solid earth response to hydrological surface loading at large-to-regional (Sierra Nevada range) scales. Several GNSS sites, located at the eastern edge of the Sierra Nevada along the southwestern rim of Long Valley Caldera, also show significant horizontal deformation that cannot be explained by elastic deformation from surface loading. Due to the location of these sites and the strong correlation between their horizontal displacements and spring discharge, we hypothesize that this deformation reflects poroelastic processes related to snowmelt runoff water infiltrating into the Sierra Nevada slopes around Long Valley Caldera. Interestingly, this is also an area where water infiltrates to feed the local hydrothermal system, and where snowmelt-induced earthquake swarms have been recently detected.
The remote, inaccessible location of many rivers in Alaska creates a compelling need for remote sensing approaches to streamflow monitoring. Motivated by this objective, we evaluated the potential to infer flow velocities from optical image sequences acquired from a helicopter deployed above two large, sediment-laden rivers. Rather than artificial seeding, we used an ensemble correlation particle image velocimetry (PIV) algorithm to track the movement of boil vortices that upwell suspended sediment and produce a visible contrast at the water surface. This study introduced a general, modular workflow for image preparation (stabilization and geo-referencing), preprocessing (filtering and contrast enhancement), analysis (PIV), and postprocessing (scaling PIV output and assessing accuracy via comparison to field measurements). Applying this method to images acquired with a digital mapping camera and an inexpensive video camera highlighted the importance of image enhancement and the need to resample the data to an appropriate, coarser pixel size and a lower frame rate. We also developed a Parameter Optimization for PIV (POP) framework to guide selection of the interrogation area (IA) and frame rate for a particular application. POP results indicated that the performance of the PIV algorithm was highly robust and that relatively large IAs (64–320 pixels) and modest frame rates (0.5–2 Hz) yielded strong agreement (
The distribution and relative abundance of Westslope Cutthroat Trout (WCT) Oncorhynchus clarkii lewisi in relation to habitat characteristics remain unknown across large portions of the species’ range. The goals of this research were to provide a foundational understanding of WCT distribution and relative abundance related to habitat characteristics in tributaries of the St. Maries River, Idaho—a highly altered watershed. The basin drains an area of approximately 1,863 km2 and has a longitudinal elevation difference of about 207 m. Backpack electrofishing and habitat assessments were conducted at 68 reaches in 35 different tributaries of the St. Maries River in 2017 and 2018. Habitat was measured at small (reach-level) and large (watershed-level) scales. A total of 652 WCT was sampled from 52 of 68 total reaches. Habitat characteristics varied by age-class, but most WCT were estimated to be age 0 and age 1. Logistic regression models indicated that the presence of age-0 WCT was positively related to stream gradient and elevation, but negatively related to water temperature, road density, fine substrate, stream depth, and the presence of Brook Trout (BKT) Salvelinus fontinalis. The relative abundance of age-0 WCT was positively associated with road density and inversely related to wetted width, canopy cover, and elevation. The presence of age-1 and older (age-1+) WCT was positively related to gradient, canopy cover, and elevation, but negatively associated with road density, temperature, stream depth, and the presence of BKT. Relative abundance of age-1+WCT was positively associated with gradient, large substrate, canopy cover, and road density. Conversely, the relative abundance of age-1+WCT was inversely related to wetted width and elevation. This research indicates that WCT populations can persist in response to altered landscapes when suitable habitat exists. However, unmitigated threats, such as nonnative species competition (e.g., BKT), hybridization with Rainbow Trout O. mykiss, habitat loss, and habitat fragmentation, pose persistent complications to WCT abundance in locations where populations appear robust but their actual abundance is unknown.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10450","usgsCitation":"Heckel, J.W., Quist, M.C., Watkins, C.J., and Dux, A.M., 2020, Distribution and abundance of Westslope Cutthroat Trout in relation to habitat characteristics at multiple spatial scales: North American Journal of Fisheries Management, v. 40, no. 4, p. 893-909, https://doi.org/10.1002/nafm.10450.","productDescription":"17 p,","startPage":"893","endPage":"909","ipdsId":"IP-107683","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":393744,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"St. Maries River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.707763671875,\n 46.878968335076856\n ],\n [\n -115.631103515625,\n 46.878968335076856\n ],\n [\n -115.631103515625,\n 47.372314620566925\n ],\n [\n -116.707763671875,\n 47.372314620566925\n ],\n [\n -116.707763671875,\n 46.878968335076856\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-04-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Heckel, John W","contributorId":270716,"corporation":false,"usgs":false,"family":"Heckel","given":"John","email":"","middleInitial":"W","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":829822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":829821,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Watkins, Carson J.","contributorId":171708,"corporation":false,"usgs":false,"family":"Watkins","given":"Carson","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":829823,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dux, Andrew M.","contributorId":212798,"corporation":false,"usgs":false,"family":"Dux","given":"Andrew","email":"","middleInitial":"M.","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":829824,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70211836,"text":"70211836 - 2020 - Using value of information to prioritize research needs for migratory bird management under climate change: A case study using federal land acquisition in the United States","interactions":[],"lastModifiedDate":"2020-08-07T20:52:19.472499","indexId":"70211836","displayToPublicDate":"2020-04-17T15:49:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1023,"text":"Biological Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Using value of information to prioritize research needs for migratory bird management under climate change: A case study using federal land acquisition in the United States","docAbstract":"In response to global habitat loss, many governmental and non‐governmental organizations have implemented land acquisition programs to protect critical habitats permanently for priority species. The ability of these protected areas to meet future management objectives may be compromised if the effects of climate change are not considered in acquisition decisions. Unfortunately, the effects of climate change on ecological systems are complex and plagued by uncertainty, making it difficult for organizations to prioritize research needs to improve decision‐making. Herein, we demonstrate the use of qualitative value of information analysis to identify and prioritize which sources of uncertainty should be reduced to improve land acquisition decisions to protect migratory birds in the face of climate change. The qualitative value of information analysis process involves four steps: (i ) articulating alternative hypotheses; (ii ) determining the magnitude of uncertainty regarding each hypothesis; (iii ) evaluating the relevance of each hypothesis to acquisition decision‐making; and (iv ) assessing the feasibility of reducing the uncertainty surrounding each hypothesis through research and monitoring. We demonstrate this approach using the objectives of 3 U.S. federal land acquisition programs that focus on migratory bird management. We used a comprehensive literature review, expert elicitation, and professional judgement to evaluate 11 hypotheses about the effect of climate change on migratory birds. Based on our results, we provide a list of priorities for future research and monitoring to reduce uncertainty and improve land acquisition decisions for the programs considered in our case study. Reducing uncertainty about how climate change will influence the spatial distribution of priority species and biotic homogenization were identified as the highest priorities for future research due to both the value of this information for improving land acquisition decisions and the feasibility of reducing uncertainty through research and monitoring. Research on how changes in precipitation patterns and winter severity will influence migratory bird abundance is also expected to benefit land acquisition decisions. By contrast, hypotheses about phenology and migration distance were identified as low priorities for research. By providing a rigorous and transparent approach to prioritizing research, we demonstrate that qualitative value of information is a valuable tool for prioritizing research and improving management decisions in other complex, high‐uncertainty cases where traditional quantitative value of information analysis is not possible. Given the inherent complexity of ecological systems under climate change, and the difficulty of identifying management‐relevant research priorities, we expect this approach to have wide applications within the field of natural resource management.
","language":"English","publisher":"Wiley","doi":"10.1111/brv.12602","usgsCitation":"Rushing, C.S., Rubenstein, M.A., Lyons, J.E., and Runge, M.C., 2020, Using value of information to prioritize research needs for migratory bird management under climate change: A case study using federal land acquisition in the United States: Biological Reviews, v. 95, no. 4, p. 1109-1130, https://doi.org/10.1111/brv.12602.","productDescription":"22 p.","startPage":"1109","endPage":"1130","ipdsId":"IP-111311","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":377204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"95","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Rushing, Clark S","contributorId":237020,"corporation":false,"usgs":false,"family":"Rushing","given":"Clark","email":"","middleInitial":"S","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":795310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rubenstein, Madeleine A. 0000-0001-8569-781X mrubenstein@usgs.gov","orcid":"https://orcid.org/0000-0001-8569-781X","contributorId":203206,"corporation":false,"usgs":true,"family":"Rubenstein","given":"Madeleine","email":"mrubenstein@usgs.gov","middleInitial":"A.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":795311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":222844,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":795312,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":795313,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70205557,"text":"sim3440 - 2020 - Bedrock geologic map of the Mount Ascutney 7.5- x 15-minute quadrangle, Windsor County, Vermont, and Sullivan County, New Hampshire","interactions":[],"lastModifiedDate":"2020-04-30T13:49:33.821916","indexId":"sim3440","displayToPublicDate":"2020-04-17T15:35:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3440","displayTitle":"Bedrock Geologic Map of the Mount Ascutney 7.5- x 15-Minute Quadrangle, Windsor County, Vermont, and Sullivan County, New Hampshire","title":"Bedrock geologic map of the Mount Ascutney 7.5- x 15-minute quadrangle, Windsor County, Vermont, and Sullivan County, New Hampshire","docAbstract":"The bedrock geology of the Mount Ascutney 7.5- x 15-minute quadrangle consists of highly deformed and metamorphosed Mesoproterozoic through Devonian metasedimentary and meta-igneous rocks intruded by rocks of the Mesozoic White Mountain Igneous Suite. In the west, Mesoproterozoic gneisses of the Mount Holly Complex are the oldest rocks and form the northeastern flank of the Chester dome. The allochthonous Cambrian through Ordovician rocks include the Moretown and Cram Hill Formations and the North River Igneous Suite; these rocks structurally overlie the Chester dome along the Keyes Mountain thrust fault. Silurian and Devonian metasedimentary and metavolcanic rocks of the Connecticut Valley trough (CVT) unconformably overlie the pre-Silurian rocks. The easternmost extent of the CVT in New Hampshire is exposed in the Meriden antiform. Ordovician to Silurian and Devonian metasedimentary rocks of the Bronson Hill anticlinorium structurally overlie the CVT along the Monroe thrust fault. The oldest part of the Bronson Hill anticlinorium, called the Bronson Hill arc, consists of Ordovician metamorphosed volcanic, plutonic, and sedimentary rocks of the Ammonoosuc Volcanics, the Partridge Formation, and the Oliverian Plutonic Suite. The rocks of the Bronson Hill arc may be partly correlative with the pre-Silurian rocks above the Chester dome and are exposed in two fault-bounded structural belts (Cornish City and Claremont belts) and in the Sugar River dome. Collectively, these belts form the regional Orfordville anticlinorium, Hardscrabble synclinorium, and the western part of the broader Bronson Hill anticlinorium in western New Hampshire. Silurian to Devonian metasedimentary rocks of the Clough Quartzite, and Fitch and Littleton Formations unconformably overlie the rocks of the Bronson Hill arc. Devonian granitic and pegmatitic dikes and sills of the New Hampshire Plutonic Suite intruded previously deformed rocks. Post-tectonic Cretaceous plutonic and volcanic rocks of the Ascutney Mountain Intrusive Complex underlie Mount Ascutney. Because of the historically significant scientific research, and its prominence in the landscape, Mount Ascutney is commonly regarded as Vermont’s most famous volcano.
The bedrock geology was mapped to study the tectonic history of the area and to provide a framework for ongoing characterization of the bedrock of Vermont and New Hampshire. This Scientific Investigations Map of the Mount Ascutney 7.5- x 15-minute quadrangle consists of sheets 1 and 2 as well as a geographic information system (GIS) database that includes bedrock geologic units, faults, outcrops, structural geologic information, geochemistry, and photographs. Sheet 1 of the report includes a bedrock geologic map, a correlation of map units, and a description of map units. Sheet 2 includes a discussion of the geology, references, three cross sections from the geologic map on sheet 1, igneous rock geochemistry results of the main map units from the Mount Ascutney stock, a tectonic map showing major structural features, and a structural domain map showing the orientation and distribution of brittle features.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3440","collaboration":"Prepared in cooperation with the State of Vermont, Vermont Agency of Natural Resources, Vermont Geological Survey; State of New Hampshire, Department of Environmental Services, New Hampshire Geological Survey; and the National Park Service","usgsCitation":"Walsh, G.J., Valley, P.M., Thompson, P.J., Ratcliffe, N.M., Proctor, B.P., and Sicard, K.R., 2020, Bedrock geologic map of the Mount Ascutney 7.5- x 15-minute quadrangle, Windsor County, Vermont, and Sullivan County, New Hampshire (ver. 1.1, April 2020): U.S. Geological Survey Scientific Investigations Map 3440, 2 sheets, scale 1:24,000, https://doi.org/10.3133/sim3440.","productDescription":"2 Sheets: 61.00 x 40.81 inches and 57.00 x 40.50 inches; Read Me; Spatial Data; Metadata; Companion Files","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-090096","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":374082,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sim/3440/versionHist.txt","text":"Version History","size":"2.17 KB","linkFileType":{"id":2,"text":"txt"}},{"id":374079,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3440/coverthb4.jpg"},{"id":374081,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_sheet2.pdf","text":"Sheet 2","size":"27.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":""},{"id":374080,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_sheet1.pdf","text":"Sheet 1","size":"26.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3440"},{"id":374083,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_readme.txt","text":"Read Me","size":"13.1 KB","linkFileType":{"id":2,"text":"txt"}},{"id":374087,"rank":9,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_MountAscutney_openaccess.zip","text":"Open Access","size":"6.09 MB","linkFileType":{"id":6,"text":"zip"}},{"id":374086,"rank":8,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_MountAscutney_metadata.zip","text":"Metadata","size":"366 KB","linkFileType":{"id":6,"text":"zip"}},{"id":374085,"rank":7,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_MountAscutney_database.zip","text":"Database","size":"6.58 MB","linkFileType":{"id":6,"text":"zip"}},{"id":374084,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_MountAscutney_basemap.zip","text":"Base Map","size":"43.7 MB","linkFileType":{"id":6,"text":"zip"}},{"id":374088,"rank":10,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3440/sim3440_MountAscutney_photos.zip","text":"Photos","size":"577 MB","linkFileType":{"id":6,"text":"zip"}}],"country":"United States","state":"New Hampshire, Vermont","county":"Sullivan County, Windsor County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.5,\n 43.375\n ],\n [\n -72.25,\n 43.375\n ],\n [\n -72.25,\n 43.5\n ],\n [\n -72.5,\n 43.5\n ],\n [\n -72.5,\n 43.375\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"","edition":"Version 1.1: April 2020; Version 1.0: April 2020","contact":"Florence Bascom Geoscience Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The Caney Mountain cave crayfish (Orconectes stygocaneyi) is one of North America's rarest crayfish, endemic to one cave in southern Missouri, USA. The species is listed as 'critically imperiled' by Missouri, and 'threatened' by the American Fisheries Society. Previously, only 15 crayfish have been observed in Mud Cave, and only two have been collected (for original species description). We aimed to collect the first natural history data on the species and search adjacent caves and springs for additional populations. Twelve visual searches and supplemental trapping over four years, in all seasons, yielded 69 O. stygocaneyi (including 11 young-of-year) observations and capture of 22 crayfish, including one ovigerous female. Visual searches of nearby caves and springs yielded no O. stygocaneyi records. However, multiple surveys of those caves and springs, using environmental DNA detected the species in one additional cave adjacent to Mud Cave, but only during spring high flow events when the caves may be ephemerally connected. Orconectes stygocaneyi's distribution is among the most restricted of any North American crayfish, and further evaluation of its conservation status designations might be warranted. Long term conservation of O. stygocaneyi would benefit from management practices promoting sustained, unimpacted surface runoff within Mud Cave's recharge area.
","language":"English","publisher":"International Association of Astacology","doi":"10.5869/fc.2020.v25-1.047","usgsCitation":"DiStefano, R., Ashley, D., Brewer, S.K., Mouser, J., and Neimiller, M., 2020, Preliminary investigation of the critically imperiled Caney Mountain cave crayfish Orconectes stygocaneyi Hobbs III, 2001 (Decapoda: Cambaridae) in Missouri, USA: Freshwater Crayfish, v. 25, no. 1, p. 47-57, https://doi.org/10.5869/fc.2020.v25-1.047.","productDescription":"11 p.","startPage":"47","endPage":"57","ipdsId":"IP-113351","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":396037,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Mud Lake","volume":"25","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"DiStefano, Robert J.","contributorId":213268,"corporation":false,"usgs":false,"family":"DiStefano","given":"Robert J.","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":834913,"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":834914,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":834915,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":834916,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Neimiller, M.","contributorId":279385,"corporation":false,"usgs":false,"family":"Neimiller","given":"M.","email":"","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":834917,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70211909,"text":"70211909 - 2020 - Millennial-scale climate and human drivers of environmental change and fire activity in a dry, mixed-conifer forest of northwestern Montana","interactions":[],"lastModifiedDate":"2020-08-11T18:31:53.806671","indexId":"70211909","displayToPublicDate":"2020-04-17T13:25:21","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5860,"text":"Frontiers in Forests and Global Change","active":true,"publicationSubtype":{"id":10}},"title":"Millennial-scale climate and human drivers of environmental change and fire activity in a dry, mixed-conifer forest of northwestern Montana","docAbstract":"Warm summer temperatures and longer fire seasons are promoting larger, and in some cases, more fires that are severe in low- and mid-elevation, dry mixed-conifer forests of the Northern Rocky Mountains (NRM). Long-term historical fire conditions and human influence on past fire activity are not well understood for these topographically and biophysically heterogeneous forests. We developed reconstructions of millennial-scale fire activity, vegetation change, and human presence at Black Lake, a small closed-basin lake on the Flathead Indian Reservation in the Mission Valley, Northwestern Montana, United States. Fossil pollen, charcoal, and biomarkers associated with human presence were used to evaluate the interaction between climate variability, fire activity, vegetation change and human activity for the past 7000 years. Comparisons among multiple proxies suggest climate variability acted as the primary control on fire activity and vegetation change from the early Holocene until the late Holocene when records suggest fire activity and climate variability decoupled. Specific biomarkers (5β-stanols including coprostanol and epi-coprostanol) associated with human presence indicate humans were present within the Black Lake watershed for thousands of years, although the inferred intensity of human presence is highly variable. A strong relationship between climate variability and fire activity during the early and mid-Holocene weakens during the last few thousand years, suggesting possible increased influence of humans in mediating fire activity in recent millennia, and/or a shift in the interaction between the distribution and abundance of woody fuel and fire severity. Human-set fires during the cooler and wetter late Holocene may have been aimed at maintaining important cultural resources associated with the heterogeneous mosaic of mixed conifer forests within the Black Lake watershed. The paleoenvironmental reconstruction at Black Lake corroborates archeological records that show humans were present within the Black Lake watershed for over 7000 years. Further research is needed to evaluate the evidence for this continuous presence and the possible role that people played in shaping fire regimes and vegetation within low- to mid-elevation mixed-conifer ecosystems of the NRM.
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