Information concerning the availability, use, and quality of water in Grant Parish, Louisiana, is critical for proper water-supply management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. In 2014, about 5.43 million gallons per day (Mgal/d) of water were withdrawn in Grant Parish, including about 2.39 Mgal/d from groundwater sources and 3.03 Mgal/d from surface-water sources. Withdrawals for public-supply use accounted for 71 percent (3.84 Mgal/d) of the total water withdrawn. Withdrawals for agricultural use, composed of general irrigation and livestock uses, accounted for 24 percent (1.28 Mgal/d) of the total water withdrawn. Other categories of use included industrial and rural domestic. Water-use data collected at 5-year intervals from 1960 to 2010 and again in 2014 indicated that water withdrawals peaked in 1960.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203064","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"Murphy, C.J., and White, V.E., 2021, Water resources of Grant Parish, Louisiana: U.S. Geological Survey Fact Sheet 2020–3064, 6 p., https://doi.org/10.3133/fs20203064.","productDescription":"Report: 6 p.; Data Release","numberOfPages":"6","onlineOnly":"N","ipdsId":"IP-103348","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":387262,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3064/coverthb.jpg"},{"id":387263,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3064/fs20203064.pdf","text":"Report","size":"1.04 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 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Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
3535 S. Sherwood Forest Blvd., Suite 120
Baton Rouge, LA 70816
The interface between lotic and lentic ecosystems is often a zone of intense metabolic activity, as primary production in streams and rivers can be light limited whereas nutrients often limit primary production in lake ecosystems. Our objective was to model the influence that rivermouths (the lotic-lentic interface) could have on the loads of soluble reactive phosphorus (SRP) and dissolved inorganic nitrogen (N) passing from the tributary to the nearshore zone of a lake. To achieve this objective, we modeled the combined role of water column nutrient transformation rates with sediment nutrient flux rates. For sensitivity analysis, we picked plausible parameter ranges based on values previously measured in the Fox rivermouth (a tributary to Lake Michigan). Sensitivity analysis of the model demonstrated that overall the importance of water column processing rates increases with increasing nutrient concentration and discharge. We then applied the model to the Fox rivermouth, simulating the change in nutrients on four dates where all of the necessary parameters had been estimated. This modeling suggests that the Fox rivermouth is often a net sink for SRP and source for ammonia (NH4), with water column processing driving SRP removal and both water column and sediment flux driving NH4 dynamics. Removal of SRP in the water column means conversion to particulate and/or organic P, and those P pools are generally considered to be less bioavailable than SRP, so it may be that rivermouths disconnect upstream sources of nutrients from nearshore food webs. These results demonstrate that the interface zone between lotic and lentic systems has the potential to substantially alter the load and character of nutrients as river waters pass through rivermouths to adjacent nearshore areas.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10533-021-00821-8","usgsCitation":"Larson, J.H., Evans, M.A., Fitzpatrick, F., Frost, P., Xenopoulos, M., James, W.F., and Reneau, P., 2021, Benthic and planktonic inorganic nutrient processing rates at the interface between a river and lake: Biogeochemistry, v. 155, p. 189-203, https://doi.org/10.1007/s10533-021-00821-8.","productDescription":"15 p.","startPage":"189","endPage":"203","ipdsId":"IP-118338","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":436267,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PNDSXR","text":"USGS data release","linkHelpText":"Code associated with analysis and modeling of benthic and pelagic inorganic nutrient processing rates at the interface between a river and lake"},{"id":388171,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"155","noUsgsAuthors":false,"publicationDate":"2021-07-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":821513,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, Mary Anne 0000-0002-1627-7210 maevans@usgs.gov","orcid":"https://orcid.org/0000-0002-1627-7210","contributorId":149358,"corporation":false,"usgs":true,"family":"Evans","given":"Mary","email":"maevans@usgs.gov","middleInitial":"Anne","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":821514,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fitzpatrick, Faith A. 0000-0002-9748-7075","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":209612,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":821515,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frost, Paul C.","contributorId":138622,"corporation":false,"usgs":false,"family":"Frost","given":"Paul C.","affiliations":[{"id":12467,"text":"Department of Biology, Trent University, Peterborough, ON CA","active":true,"usgs":false}],"preferred":false,"id":821516,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xenopoulos, Marguerite A.","contributorId":138623,"corporation":false,"usgs":false,"family":"Xenopoulos","given":"Marguerite A.","affiliations":[{"id":12467,"text":"Department of Biology, Trent University, Peterborough, ON CA","active":true,"usgs":false}],"preferred":false,"id":821517,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"James, William F.","contributorId":213265,"corporation":false,"usgs":false,"family":"James","given":"William","email":"","middleInitial":"F.","affiliations":[{"id":38729,"text":"University of Wisconsin-Stout","active":true,"usgs":false}],"preferred":false,"id":821518,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reneau, Paul C. 0000-0002-1335-7573","orcid":"https://orcid.org/0000-0002-1335-7573","contributorId":220311,"corporation":false,"usgs":true,"family":"Reneau","given":"Paul C.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":821519,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70229384,"text":"70229384 - 2021 - Translocation, survival, and recovery of Kansas-banded Canada geese","interactions":[],"lastModifiedDate":"2022-03-04T16:08:57.776602","indexId":"70229384","displayToPublicDate":"2021-07-20T09:52:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Translocation, survival, and recovery of Kansas-banded Canada geese","docAbstract":"Temperate-breeding, or resident, Canada geese were once extirpated in Kansas, USA, but currently provide abundant viewing and hunting opportunities. Kansas Department of Wildlife, Parks, and Tourism (KDWPT) began reintroducing geese in 1980 with a goal of re-establishing a breeding population. Successful reintroductions led to translocating flocks to regions with no previous records of nesting geese; however, KDWPT continues to translocate individuals from nuisance flocks in urban areas to rural reservoirs to reduce human conflicts with urban geese. Our goal was to determine the effects of such translocations on survival and recovery of adult, sub-adult, and juvenile temperate-breeding Canada geese. We used Brownie dead-recovery models in Program MARK to compare survival and recovery probabilities between translocated and nontranslocated (normal wild) Kansas-banded Canada geese for 2012–2017. Model-estimated annual survival differed between status (normal wild Ŝ = 0.761, 95% CI 0.734–0.785; translocated Ŝ = 0.598, 95% CI 0.528–0.665). Recovery probability differed between normal and translocated adults (normal wild ḟ = 0.074, 95% CI = 0.069–0.078; translocated ḟ = 0.138, 95% CI = 0.120–0.158) and juveniles (normal wild ḟ = 0.067, 95% CI = 0.059–0.075; translocated ḟ = 0.250, 95% CI = 0.199–0.310). Recovery probability did not differ between status in the sub-adult age class (normal wild ḟ = 0.126, 95% CI = 0.115–0.137; translocated ḟ = 0.090, 95% CI = 0.055–0.144). Translocation is a viable management option to successfully reduce survival and increase recovery probability of urban nuisance geese in Kansas.
","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.3659","usgsCitation":"Malanchuk, J.B., Ross, B., Haukos, D.A., Bidrowski, T.F., and Schultheis, R., 2021, Translocation, survival, and recovery of Kansas-banded Canada geese: Ecosphere, v. 12, no. 7, p. 1-11, https://doi.org/10.1002/ecs2.3659.","productDescription":"e03659, 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-124602","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":489060,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3659","text":"Publisher Index Page"},{"id":396754,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Boomer","contributorId":287969,"corporation":false,"usgs":false,"family":"Malanchuk","given":"J.","email":"","middleInitial":"Boomer","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":837240,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ross, Beth 0000-0001-5634-4951 bross@usgs.gov","orcid":"https://orcid.org/0000-0001-5634-4951","contributorId":199242,"corporation":false,"usgs":true,"family":"Ross","given":"Beth","email":"bross@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":837239,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":837238,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bidrowski, Thomas F.","contributorId":287970,"corporation":false,"usgs":false,"family":"Bidrowski","given":"Thomas","email":"","middleInitial":"F.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":837241,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schultheis, Richard","contributorId":287971,"corporation":false,"usgs":false,"family":"Schultheis","given":"Richard","email":"","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":837242,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70222354,"text":"70222354 - 2021 - Response of forage plants to alteration of temperature and spring thaw date: Implications for geese in a warming Arctic","interactions":[],"lastModifiedDate":"2021-07-22T13:54:40.090154","indexId":"70222354","displayToPublicDate":"2021-07-20T08:48:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Response of forage plants to alteration of temperature and spring thaw date: Implications for geese in a warming Arctic","docAbstract":"Changes in summer temperatures in Arctic Alaska have led to longer and warmer growing seasons over the last three decades. Corresponding with these changes in climate, the abundance and distributions of geese have increased and expanded over the same period. We used an experimental approach to assess the response of goose forage plants to simulated environmental change. We subjected Carex subspathacea, a preferred goose forage growing on the Arctic Coastal Plain (ACP) of Alaska, to manipulations of temperature and timing of spring thaw to measure potential effects in terms of plant nitrogen concentration, aboveground biomass, and total nitrogen availability. Carex subspathacea responded to warming in a dynamic fashion. Increases in temperature led to decreases in leaf nitrogen concentration but increases in aboveground biomass. The increase in biomass was stronger than the decline in nitrogen concentration such that total nitrogen availability was increased with temperature for the first 35–40 d of the season. Grazing removal accounted for only minimal offtake of biomass, and we found no indication that grazing maintained elevated levels of nitrogen concentration longer in the season as reported in other studies. Based on demonstrated relationships in the literature between forage nitrogen concentrations and gosling growth rates, we conclude that there is currently abundant high-quality forage available across the ACP. This finding fits with recent evidence of high gosling growth rates and increasing trends in goose abundance on the ACP. Our results suggest that with climate warming of a few degrees, nitrogen concentration of forage may decrease, but forage biomass and total nitrogen availability will increase. Our data suggest that nitrogen concentration will not fall below the minimum threshold required by geese in the near future. As such, we suggest that there is currently no bottom-up limitation to goose numbers on the ACP.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3627","usgsCitation":"Flint, P.L., and Meixell, B.W., 2021, Response of forage plants to alteration of temperature and spring thaw date: Implications for geese in a warming Arctic: Ecosphere, v. 12, no. 7, e03627, 17 p., https://doi.org/10.1002/ecs2.3627.","productDescription":"e03627, 17 p.","ipdsId":"IP-121569","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":489092,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3627","text":"Publisher Index Page"},{"id":436268,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WMFBVN","text":"USGS data release","linkHelpText":"Vegetation and Temperature Data, Smith River Estuary, Alaska, 2011-2013"},{"id":387378,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Smith River Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -153.358154296875,\n 70.84929093589197\n ],\n [\n -153.0965423583984,\n 70.84929093589197\n ],\n [\n -153.0965423583984,\n 70.92281373736292\n ],\n [\n -153.358154296875,\n 70.92281373736292\n ],\n [\n -153.358154296875,\n 70.84929093589197\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-07-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Flint, Paul L. 0000-0002-8758-6993 pflint@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-6993","contributorId":3284,"corporation":false,"usgs":true,"family":"Flint","given":"Paul","email":"pflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":819732,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meixell, Brandt W. 0000-0002-6738-0349 bmeixell@usgs.gov","orcid":"https://orcid.org/0000-0002-6738-0349","contributorId":138716,"corporation":false,"usgs":true,"family":"Meixell","given":"Brandt","email":"bmeixell@usgs.gov","middleInitial":"W.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":819733,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70228875,"text":"70228875 - 2021 - Do lake-specific characteristics mediate the temporal relationship between walleye growth and warming water temperatures?","interactions":[],"lastModifiedDate":"2022-02-23T15:01:39.001939","indexId":"70228875","displayToPublicDate":"2021-07-20T08:37:05","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6455,"text":"Canadian Journal Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Do lake-specific characteristics mediate the temporal relationship between walleye growth and warming water temperatures?","docAbstract":"Walleye (Sander vitreus) population declines have been linked to climate change, but it is unclear how the growth of this cool-water species may be affected by warming water temperatures. Because warming rates vary among lakes, it is uncertain whether lake characteristics may mediate the temperature effects on walleye growth or may vary as a result of differences in lake habitat or productivity. In this study, we (i) quantified walleye annual growth from 1983 to 2015 in 61 lakes in midwestern United States; (ii) estimated the relationship between annual early life growth (ω; mm·year–1) and water growing degree days (GDD); and (iii) identified lake characteristics affecting loge(ω)–GDD relationships. On average, ω estimates significantly increased with increasing GDD; however, this relationship varied in direction and magnitude among lakes. We estimated an 84% posterior probability of a negative effect of water clarity on the loge(ω)–GDD relationship, suggesting that water clarity may mediate the effect of warming water temperatures by affecting the magnitude and direction of the loge(ω)–GDD relationship. Our results provide insights into the conservation of cool-water species in a changing environment and identify lakes characteristics in which walleye growth may be more resilient to climate change.
","language":"English","doi":"10.1139/cjfas-2020-0169","usgsCitation":". Massie, D., Hansen, G., Li, Y., Sass, G., and Wagner, T., 2021, Do lake-specific characteristics mediate the temporal relationship between walleye growth and warming water temperatures?: Canadian Journal Fisheries and Aquatic Sciences, v. 78, no. 7, p. 913-923, https://doi.org/10.1139/cjfas-2020-0169.","productDescription":"11 p.","startPage":"913","endPage":"923","ipdsId":"IP-118834","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":396339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.20703125,\n 44.59046718130883\n ],\n [\n -87.6708984375,\n 44.59046718130883\n ],\n [\n -87.6708984375,\n 48.07807894349862\n ],\n [\n -97.20703125,\n 48.07807894349862\n ],\n [\n -97.20703125,\n 44.59046718130883\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":". Massie, Danielle L","contributorId":279942,"corporation":false,"usgs":false,"family":". Massie","given":"Danielle L","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":835754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hansen, Gretchen J. A.","contributorId":279944,"corporation":false,"usgs":false,"family":"Hansen","given":"Gretchen J. A.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":835755,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Li, Yan","contributorId":279947,"corporation":false,"usgs":false,"family":"Li","given":"Yan","affiliations":[{"id":56680,"text":"North Carolina Division of Marine Fisheries","active":true,"usgs":false}],"preferred":false,"id":835756,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sass, Greg G.","contributorId":279948,"corporation":false,"usgs":false,"family":"Sass","given":"Greg G.","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":835757,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":835753,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70225161,"text":"70225161 - 2021 - Direct and delayed mortality of Ceriodaphnia dubia and rainbow trout following time-varying acute exposures to zinc","interactions":[],"lastModifiedDate":"2021-10-18T10:34:42.921445","indexId":"70225161","displayToPublicDate":"2021-07-20T08:15:26","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Direct and delayed mortality of Ceriodaphnia dubia and rainbow trout following time-varying acute exposures to zinc","docAbstract":"The potential for delayed mortality following short-term episodic pollution events was evaluated by exposing cladocerans (Ceriodaphnia dubia) and rainbow trout (Oncorhynchus mykiss) to zinc (Zn) in various 1- to 48-h and 1- to 96-h exposures, respectively, followed by transferring the exposed organisms to clean water for up to 47 h for C. dubia and up to 95 h for trout for additional observation. For C. dubia, 1-h exposures of up to 3790 µg Zn/L never resulted in mortality during the actual Zn exposures, but by 48 h, a 1-h exposure to 114 µg/L, a concentration similar to the present US national water quality acute criterion for the test water conditions, ultimately killed 70% of C. dubia. With C. dubia, the speed of action of Zn toxicity was faster for intermediate concentrations than for the highest concentrations tested. For rainbow trout, pronounced delayed mortalities by 96 h only occurred following ≥8-h exposures. For both species, ultimate mortalities from Zn exposures ≤8 h mostly presented as delayed mortalities, whereas for exposures ≥24 h, almost all ultimate mortalities presented during the actual exposure periods. With Zn, risks of delayed mortality following exposures to all concentrations tested were much greater for the more sensitive, small-bodied invertebrate (C. dubia) than for the less sensitive, larger-bodied fish (rainbow trout). These results, along with previous studies, show that delayed mortality is an important consideration in evaluating risks to aquatic organisms from brief, episodic exposures to some substances. Environ Toxicol Chem 2021;40:2484–2498. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA.
Anoxygenic photosynthesis by phototrophic sulfur bacteria is prevalent in microbial mat ecosystems and in restricted, highly stratified aquatic environments. This limited distribution reflects their simultaneous requirements for an anoxic habitat, reduced sulfur to supply electrons for carbon fixation, and an appropriate light regime. Although these conditions were often satisfied in ancient seas, as shown by the distinctive carotenoid and chlorophyll pigments preserved in geological samples going back as far as 1.65 billion y, we can find no record of these organisms growing in today’s generally well-ventilated oceans. An array of carotenoids in sediments from the Namibian shelf suggests that green sulfur bacteria, despite their sensitivity to oxygen, can proliferate during episodic toxic gas eruptions in the Benguela Upwelling System.
The collapse of a volcanic flank can be destructive and deadly. Hydrothermal alteration is common to volcanoes worldwide and is thought to promote volcano instability by decreasing rock strength. However, some laboratory studies have shown that not all alteration reduces rock strength. Our new laboratory data for altered rhyodacites from Chaos Crags (Lassen volcanic center, California, USA) show that pore- and crack-filling mineral precipitation can reduce porosity and permeability and increase strength, Young's modulus, and cohesion. A significant reduction in permeability, by as much as four orders of magnitude, will inhibit fluid circulation and create zones of high pore fluid pressure. We explored the consequences of pore fluid pressurization on volcano stability using large-scale numerical modeling. Upscaled physical and mechanical properties for hydrothermally altered rocks were used as input parameters in our modeling. Results show that a high-pore-pressure zone within a volcano increases volcano deformation and that increasing the size of this zone increases the observed deformation. Hydrothermal alteration associated with mineral precipitation, and increases to rock strength, can therefore promote pore pressurization and volcano deformation, increasing the likelihood of volcano spreading, flank collapses, and phreatic/phreatomagmatic explosions. We conclude that porosity-decreasing alteration, explored here, and porosity-increasing alteration can both promote volcano instability and collapse, but by different mechanisms. Hydrothermal alteration should therefore be monitored at volcanoes worldwide and incorporated into hazard assessments.
We will investigate fish health factors that may be contributing to the failed recovery of Pacific herring populations in Prince William Sound. Field samples will provide infection and disease prevalence data from Prince William Sound and Sitka Sound to inform the age structured assessment (ASA) model, serological data will indicate the prior exposure history and future susceptibility of herring to viral hemorrhagic septicemia virus (VHSV), and diet information will provide insights into the unusually high prevalence of Ichthyophonus that occurs in juvenile herring from Cordova Harbor. Laboratory studies will validate the newly developed plaque neutralization assay as a quantifiable measure of herd immunity against VHS, provide further understanding of disease cofactors including salinity, and investigate possible routes of transmission for Ichthyophonus. Information from the field and laboratory studies will be integrated into the current ASA model and inform a novel ASA-type model that is based on the immune status of herring age cohorts.
","language":"English","publisher":"Exxon Valdez Oil Spill Trustee Council (EVOSTC)","usgsCitation":"Hershberger, P., and Purcell, M.K., 2021, Herring Disease Program - Annual Project Report 2012011-E, February 1, 2010-January 31, 2021, 26 p.","productDescription":"26 p.","ipdsId":"IP-127098","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":387460,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":387451,"type":{"id":15,"text":"Index Page"},"url":"https://evostc.state.ak.us/restoration-projects/project-search/hrm-program-herring-disease-program-ii-20120111-e/"}],"country":"United States","state":"Alaska","otherGeospatial":"Prince William Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -149.56787109375,\n 59.567723306212955\n ],\n [\n -144.33837890625,\n 59.567723306212955\n ],\n [\n -144.33837890625,\n 61.41775026352097\n ],\n [\n -149.56787109375,\n 61.41775026352097\n ],\n [\n -149.56787109375,\n 59.567723306212955\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hershberger, Paul 0000-0002-2261-7760","orcid":"https://orcid.org/0000-0002-2261-7760","contributorId":203322,"corporation":false,"usgs":true,"family":"Hershberger","given":"Paul","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":819957,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Purcell, Maureen K. 0000-0003-0154-8433 mpurcell@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8433","contributorId":168475,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen","email":"mpurcell@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":819958,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70222135,"text":"70222135 - 2021 - Cyprosulfamide: Analysis of the herbicide safener and two of its degradates in surface water and groundwater from the Midwestern United States","interactions":[],"lastModifiedDate":"2021-08-18T11:38:48.072637","indexId":"70222135","displayToPublicDate":"2021-07-20T06:45:37","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9105,"text":"ACS Agricultural Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Cyprosulfamide: Analysis of the herbicide safener and two of its degradates in surface water and groundwater from the Midwestern United States","docAbstract":"Herbicide safeners are commonly included in herbicide formulations to selectively protect crops from herbicide toxicity but are poorly understood in terms of their environmental occurrence and fate. This study established an analytical method for a newer safener, cyprosulfamide, and two of its degradates, cyprosulfamide desmethyl and N-cyclopropyl-4-sulfamoylbenzamide, in water via solid-phase extraction and liquid chromatography with tandem mass spectroscopy. To evaluate the potential for off-field transport and transformation of cyprosulfamide, the method was used to analyze groundwater and surface water samples collected near cornfields in the midwestern United States where cyprosulfamide had been applied. All three compounds were detected in surface water samples (N = 34); N-cyclopropyl-4-sulfamoylbenzamide was most frequently detected (56%), followed by cyprosulfamide (25%) and cyprosulfamide desmethyl (19%). Maximum concentrations ranged from 22.0 to 5185.9 ng/L, with the highest concentrations and detection rates during the growing season. None of our target analytes were detected in groundwater.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acsagscitech.1c00050","usgsCitation":"McFadden, M.E., and Hladik, M.L., 2021, Cyprosulfamide: Analysis of the herbicide safener and two of its degradates in surface water and groundwater from the Midwestern United States: ACS Agricultural Science and Technology, v. 1, no. 4, p. 355-361, https://doi.org/10.1021/acsagscitech.1c00050.","productDescription":"7 p.","startPage":"355","endPage":"361","ipdsId":"IP-126164","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":387319,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.119140625,\n 37.020098201368114\n ],\n [\n -80.15625,\n 37.020098201368114\n ],\n [\n -80.15625,\n 49.15296965617042\n ],\n [\n -97.119140625,\n 49.15296965617042\n ],\n [\n -97.119140625,\n 37.020098201368114\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"1","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-07-20","publicationStatus":"PW","contributors":{"authors":[{"text":"McFadden, Monica E 0000-0002-8589-9638","orcid":"https://orcid.org/0000-0002-8589-9638","contributorId":261268,"corporation":false,"usgs":false,"family":"McFadden","given":"Monica","email":"","middleInitial":"E","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":819624,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":205314,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819625,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70222363,"text":"70222363 - 2021 - Conservation implications of spatiotemporal variation in the terrestrial ecology of Western spadefoots","interactions":[],"lastModifiedDate":"2021-08-17T14:59:39.589595","indexId":"70222363","displayToPublicDate":"2021-07-19T09:37:34","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Conservation implications of spatiotemporal variation in the terrestrial ecology of Western spadefoots","docAbstract":"Conservation of species reliant on ephemeral resources can be especially challenging in the face of a changing climate. Western spadefoots (Spea hammondii) are small burrowing anurans that breed in ephemeral pools, but adults spend the majority of their lives underground in adjacent terrestrial habitat. Western spadefoots are of conservation concern throughout their range because of habitat loss, but little is known about the activity patterns and ecology of their terrestrial life stage. We conducted a radio-telemetry study of adult western spadefoots at 2 sites in southern California, USA, from December 2018 to November 2019 to characterize their survival, behavior, and movements from breeding through aestivation to refine conservation and management for the species. Western spadefoot survival varied seasonally, with risk of mortality higher in the active season than during aestivation. The probability of movement between successive observations was higher during the winter and spring and when atmospheric moisture was high and soil water content at 10-cm depth was low. The amount of rain between observations had the strongest effect on the probability of movement between observations; for every 20 mm of rainfall between observations, western spadefoots were 2.4 times more likely to move. When movements occurred, movement rates were highest when both relative humidity and soil water content at 10-cm depth were high. The conditions under which western spadefoots were likely active on the surface, likely to have moved, and moved at the highest rates are conditions that reduce the risk of desiccation of surface-active spadefoots. Western spadefoot home range areas varied between study sites and were mostly <1 ha, although 1 individual's home range area was >6 ha. Western spadefoots rapidly dispersed from the breeding pools, and asymptotic distances from the breeding pool were generally reached by June. The asymptotic distance from the breeding pool varied between sites, with the 95th percentile of the posterior predictive distribution reaching 486 m at 1 site and 187 m at the other. Western spadefoots did not select most habitat components disproportionately to their availability, but at Crystal Cove State Park, they avoided most evaluated vegetation types (graminoids, forbs, and shrubs). Spatial variation was evident in most evaluated western spadefoot behaviors; context-dependent behavior suggests that site-specific management is likely necessary for western spadefoots. Furthermore, comparison with an earlier study of western spadefoots at Crystal Cove State Park indicated substantial temporal variation in western spadefoot behavior. Therefore, basing management decisions on short-term studies might fail to meet conservation objectives. Better understanding the influences of spatial context and climatic variation on western spadefoot behavior will improve conservation efforts for this species.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22095","usgsCitation":"Halstead, B., Baumberger, K.L., Backlin, A.R., Kleeman, P.M., Wong, M.N., Gallegos, E., Rose, J.P., and Fisher, R.N., 2021, Conservation implications of spatiotemporal variation in the terrestrial ecology of Western spadefoots: Journal of Wildlife Management, v. 85, no. 7, p. 1377-1393, https://doi.org/10.1002/jwmg.22095.","productDescription":"17 p.","startPage":"1377","endPage":"1393","ipdsId":"IP-125223","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":489101,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22095","text":"Publisher Index Page"},{"id":436269,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P912W368","text":"USGS data release","linkHelpText":"Western Spadefoot Habitat Selection Based on Radio Telemetry in Orange County, California 2019"},{"id":387396,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Orange County","otherGeospatial":"Crystal Cove State Park, Limestone Canyon Regional Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.70314216613768,\n 33.6988507346491\n ],\n [\n -117.65378952026366,\n 33.6988507346491\n ],\n [\n -117.65378952026366,\n 33.732620149421436\n ],\n [\n -117.70314216613768,\n 33.732620149421436\n ],\n [\n -117.70314216613768,\n 33.6988507346491\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.80364990234375,\n 33.555701234563486\n ],\n [\n -117.78099060058595,\n 33.57687060377715\n ],\n [\n -117.79163360595703,\n 33.58945533558725\n ],\n [\n -117.81635284423827,\n 33.5651422701066\n ],\n [\n -117.81703948974608,\n 33.560278835227706\n ],\n [\n -117.80364990234375,\n 33.555701234563486\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"85","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-07-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":819756,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baumberger, Katherine L. 0000-0002-2150-6372 kbaumberger@usgs.gov","orcid":"https://orcid.org/0000-0002-2150-6372","contributorId":225260,"corporation":false,"usgs":true,"family":"Baumberger","given":"Katherine","email":"kbaumberger@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":819757,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Backlin, Adam R. 0000-0001-5618-8426 abacklin@usgs.gov","orcid":"https://orcid.org/0000-0001-5618-8426","contributorId":3802,"corporation":false,"usgs":true,"family":"Backlin","given":"Adam","email":"abacklin@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":819758,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kleeman, Patrick M. 0000-0001-6567-3239 pkleeman@usgs.gov","orcid":"https://orcid.org/0000-0001-6567-3239","contributorId":3948,"corporation":false,"usgs":true,"family":"Kleeman","given":"Patrick","email":"pkleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":819759,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wong, Monique Nicole 0000-0001-7038-321X","orcid":"https://orcid.org/0000-0001-7038-321X","contributorId":261323,"corporation":false,"usgs":true,"family":"Wong","given":"Monique","email":"","middleInitial":"Nicole","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":819760,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gallegos, Elizabeth 0000-0002-8402-2631 egallegos@usgs.gov","orcid":"https://orcid.org/0000-0002-8402-2631","contributorId":1528,"corporation":false,"usgs":true,"family":"Gallegos","given":"Elizabeth","email":"egallegos@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":819761,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":199339,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan","email":"jprose@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":819762,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":819763,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70222509,"text":"70222509 - 2021 - Miocene neritic benthic foraminiferal community dynamics, Calvert Cliffs, Maryland, USA: Species pool, patterns and processes","interactions":[],"lastModifiedDate":"2021-08-02T14:45:47.370559","indexId":"70222509","displayToPublicDate":"2021-07-19T09:37:12","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3000,"text":"Palaios","active":true,"publicationSubtype":{"id":10}},"title":"Miocene neritic benthic foraminiferal community dynamics, Calvert Cliffs, Maryland, USA: Species pool, patterns and processes","docAbstract":"The presence/absence and abundance of benthic foraminifera in successive discrete beds (Shattuck “zones”) of the Miocene Calvert and Choptank formations, exposed at the Calvert Cliffs, Maryland, USA, allows for investigation of community dynamics over space and time. The stratigraphic distribution of benthic foraminifera is documented and interpreted in the context of sea-level change, sequence stratigraphy, and the previously published distribution of mollusks. Neritic benthic foraminiferal communities of four sea-level cycles over ∼4 million years of the middle Miocene, encompassing the Miocene Climatic Optimum and the succeeding middle Miocene Climate Transition, are dominated by the same abundant species. They differ in the varying abundance of common species that occur throughout most of the studied section and in the different rare species that appear and disappear. Transgressive systems tracts (TSTs) have higher species diversity than highstand systems tracts (HSTs) but much lower density of specimens. In contrast to some previous research, all beds in the studied section are interpreted as being from the inner part of a broad, low gradient shelf and were deposited at water depths of less than ∼50 m. It is suggested that species are recruited from a regional species pool of propagules throughout the duration of TSTs. Recruitment is curtailed during highstands leading to lower diversity in the HSTs.
","language":"English","publisher":"SEPM Society for Sedimentary Geology","doi":"10.2110/palo.2020.069","usgsCitation":"Culver, S.J., Sutton, S., Mallinson, D.J., Buzas, M.A., Robinson, M., and Dowsett, H., 2021, Miocene neritic benthic foraminiferal community dynamics, Calvert Cliffs, Maryland, USA: Species pool, patterns and processes: Palaios, v. 36, no. 7, p. 247-259, https://doi.org/10.2110/palo.2020.069.","productDescription":"13 p.","startPage":"247","endPage":"259","ipdsId":"IP-122997","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":387628,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Calvert Cliffs","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.5966796875,\n 38.315801006824984\n ],\n [\n -76.365966796875,\n 38.315801006824984\n ],\n [\n -76.365966796875,\n 38.89530825492018\n ],\n [\n -76.5966796875,\n 38.89530825492018\n ],\n [\n -76.5966796875,\n 38.315801006824984\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-07-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Culver, Stephen J.","contributorId":198984,"corporation":false,"usgs":false,"family":"Culver","given":"Stephen","email":"","middleInitial":"J.","affiliations":[{"id":27911,"text":"East Carolina University Greenville, North Carolina,USA","active":true,"usgs":false}],"preferred":false,"id":820359,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sutton, Seth R","contributorId":261662,"corporation":false,"usgs":false,"family":"Sutton","given":"Seth R","affiliations":[{"id":36317,"text":"East Carolina University","active":true,"usgs":false}],"preferred":false,"id":820360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mallinson, David J.","contributorId":198986,"corporation":false,"usgs":false,"family":"Mallinson","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":27911,"text":"East Carolina University Greenville, North Carolina,USA","active":true,"usgs":false}],"preferred":false,"id":820361,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buzas, Martin A","contributorId":261663,"corporation":false,"usgs":false,"family":"Buzas","given":"Martin","email":"","middleInitial":"A","affiliations":[{"id":36606,"text":"Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":820362,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robinson, Marci M. 0000-0002-9200-4097","orcid":"https://orcid.org/0000-0002-9200-4097","contributorId":261664,"corporation":false,"usgs":true,"family":"Robinson","given":"Marci M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":820363,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dowsett, Harry J. 0000-0003-1983-7524","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":261665,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":820364,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70227749,"text":"70227749 - 2021 - Spatial and temporal variation in length-weight relationships of age-0 Scaphirhynchus sturgeon in the lower Missouri River","interactions":[],"lastModifiedDate":"2022-01-28T15:28:49.002502","indexId":"70227749","displayToPublicDate":"2021-07-19T09:05:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":737,"text":"American Midland Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal variation in length-weight relationships of age-0 Scaphirhynchus sturgeon in the lower Missouri River","docAbstract":"Length-weight relationships can be useful tools for assessing fish condition. We developed these equations (W = aLb) for wild-caught age-0 (4.1–12.0 cm) Scaphirhynchus sturgeon from eight reaches spanning over 750 river km of the lower Missouri River from 2014 to 2017. We used nonlinear modeling to estimate the constant (a) and exponent (b) of the LW equation for each reach to assess potential spatial differences. We also assessed long-term temporal effects by estimating these parameters by year at Lexington reach, which is located in the middle of our sampling area and was the only reach sampled all 4 y. Constant and exponent estimates from linearized regressions varied by reach and were inversely related during the spatial analyses. Similarly, parameter estimates were also inversely related and varied among years during the temporal analysis at Lexington. To account for the relationship between constant and exponent values, we used predicted weights at 2 cm increments (4.1–12.0 cm) for the spatial analysis (by reach) and for the temporal analysis (by year). During the 2014 and 2015 spatial analyses, weights varied by size but were usually higher in Lexington and Glasgow, which were the furthest upstream reaches sampled during those years. During 2016 and 2017, Lexington was the furthest downstream reach sampled but did not consistently yield relatively high predicted weights. Temporal analysis at Lexington yielded higher predicted weights for 2014–2015 compared to 2016–2017 for higher size categories (10- and 12-cm). In general our results suggest differences in body condition among reaches and years in the lower Missouri River. Further research is needed to identify the specific mechanisms driving spatial and temporal L-W relationship differences observed and to determine if differences in predicted body conditions affect long-term survival and recruitment of age-0 Scaphirhynchus sturgeon. Currently, factors influencing age-0 Scaphirhynchus sturgeon condition and growth are unknown and this work serves to highlight knowledge gaps regarding factors influencing Scaphirhynchus sturgeon recruitment.
","language":"English","publisher":"University of Notre Dame","doi":"10.1674/0003-0031-186.1.106","usgsCitation":"Gonzalez, A., Long, J.M., Gosch, N.J., Civiello, A., Gemeinhardt, T., and Hall, J.R., 2021, Spatial and temporal variation in length-weight relationships of age-0 Scaphirhynchus sturgeon in the lower Missouri River: American Midland Naturalist, v. 186, no. 1, p. 106-121, https://doi.org/10.1674/0003-0031-186.1.106.","productDescription":"17 p.","startPage":"106","endPage":"121","ipdsId":"IP-108837","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395050,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Kansas, Missouri, Nebraska","otherGeospatial":"Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.8277587890625,\n 42.79540065303723\n ],\n [\n -97.294921875,\n 42.80346172417078\n ],\n [\n -96.668701171875,\n 42.46399280017058\n ],\n [\n -96.25671386718749,\n 41.80817277478235\n ],\n [\n -96.1578369140625,\n 41.33970040774419\n ],\n [\n -95.965576171875,\n 40.622291783092706\n ],\n [\n -95.570068359375,\n 40.04443758460856\n ],\n [\n -95.020751953125,\n 39.76632525654491\n ],\n [\n -95.2679443359375,\n 39.58029027440865\n ],\n [\n -94.8944091796875,\n 39.13006024213511\n ],\n [\n -94.449462890625,\n 39.0533181067413\n ],\n [\n -94.273681640625,\n 39.14710270770074\n ],\n [\n -94.0814208984375,\n 39.031986028740086\n ],\n [\n -93.1256103515625,\n 39.257778150283364\n ],\n [\n -92.999267578125,\n 39.18117526158749\n ],\n [\n -93.03771972656249,\n 39.00637903337455\n ],\n [\n -92.61474609375,\n 38.852542390364235\n ],\n [\n -92.4005126953125,\n 38.59540719940386\n ],\n [\n -92.01599121093749,\n 38.453588708941375\n ],\n [\n -91.746826171875,\n 38.62116234642254\n ],\n [\n -91.3568115234375,\n 38.62545397209084\n ],\n [\n -90.90087890624999,\n 38.46219172306828\n ],\n [\n -90.252685546875,\n 38.77978137804918\n ],\n [\n -90.0933837890625,\n 38.81403111409755\n ],\n [\n -90.06591796875,\n 38.950865400919994\n ],\n [\n -90.406494140625,\n 38.93377552819722\n ],\n [\n -90.94482421875,\n 38.68122173079789\n ],\n [\n -91.351318359375,\n 38.81403111409755\n ],\n [\n -91.7852783203125,\n 38.80118939192329\n ],\n [\n -92.0599365234375,\n 38.646908247760706\n ],\n [\n -92.252197265625,\n 38.732661120482334\n ],\n [\n -92.373046875,\n 38.94232097947902\n ],\n [\n -92.801513671875,\n 39.11727568585598\n ],\n [\n -92.7685546875,\n 39.26203141523749\n ],\n [\n -93.1585693359375,\n 39.54217596171196\n ],\n [\n -93.416748046875,\n 39.37252570201878\n ],\n [\n -94.053955078125,\n 39.257778150283364\n ],\n [\n -94.273681640625,\n 39.342794408952365\n ],\n [\n -94.5098876953125,\n 39.24501680713314\n ],\n [\n -94.757080078125,\n 39.287545585410435\n ],\n [\n -94.9603271484375,\n 39.5633531658293\n ],\n [\n -94.76806640624999,\n 39.78321267821705\n ],\n [\n -94.8834228515625,\n 39.985538414809746\n ],\n [\n -95.086669921875,\n 39.977120098439634\n ],\n [\n -95.2899169921875,\n 40.12009038025332\n ],\n [\n -95.635986328125,\n 40.693134153308065\n ],\n [\n -95.7843017578125,\n 41.352072144512924\n ],\n [\n -95.9271240234375,\n 41.83682786072714\n ],\n [\n -96.35009765625,\n 42.55712670332118\n ],\n [\n -97.13012695312499,\n 42.94436044696629\n ],\n [\n -97.9156494140625,\n 42.96848221128033\n ],\n [\n -97.8277587890625,\n 42.79540065303723\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"186","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gonzalez, A.","contributorId":272273,"corporation":false,"usgs":false,"family":"Gonzalez","given":"A.","email":"","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":832028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":832029,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gosch, N. J. C.","contributorId":272518,"corporation":false,"usgs":false,"family":"Gosch","given":"N.","email":"","middleInitial":"J. C.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":832030,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Civiello, A. P.","contributorId":272519,"corporation":false,"usgs":false,"family":"Civiello","given":"A. P.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":832031,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gemeinhardt, T.R.","contributorId":272520,"corporation":false,"usgs":false,"family":"Gemeinhardt","given":"T.R.","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":832032,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hall, J. R.","contributorId":272561,"corporation":false,"usgs":false,"family":"Hall","given":"J.","email":"","middleInitial":"R.","affiliations":[{"id":17640,"text":"Nebraska Game and Parks Commission","active":true,"usgs":false}],"preferred":false,"id":832141,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70223114,"text":"70223114 - 2021 - Incorporation of non-native species in the diets of cisco (Coregonus artedi) from eastern Lake Ontario","interactions":[],"lastModifiedDate":"2021-08-11T12:50:04.835719","indexId":"70223114","displayToPublicDate":"2021-07-19T07:46:40","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Incorporation of non-native species in the diets of cisco (Coregonus artedi) from eastern Lake Ontario","docAbstract":"Cisco Coregonus artedi was once an important native fish in Lake Ontario; however, after multiple population crashes, the cisco stock has yet to recover to historic abundances. Rehabilitation of cisco in Lake Ontario is a fish community management objective, but the extent to which recent non-native species and pelagic food web changes have influenced cisco is not well understood. We described cisco diets in contemporary Lake Ontario following the addition and spread of non-native zooplankton species. We collected 618 cisco and processed 178 for full diet analysis in eastern Lake Ontario using mid-water trawls and bottom-set gill nets from 2016 to 2020. We found that Lake Ontario cisco were mostly zooplanktivorous, and non-native zooplankton dominated their diet during July and September. Cisco smaller than 300 mm had a more diverse diet including both native and non-native zooplankton, while cisco larger than 300 mm fed almost exclusively on non-native predatory cladocerans Bythotrephes longimanus and Cercopagis pengoi (98.9% consumed prey dry mass). We also found fish eggs, presumed to be of coregonine origin in 75% of non-empty December-collected cisco diets, suggesting eggs subsidize cisco diets when available. Juvenile round goby Neogobius melanostomus, alewife Alosa pseudoharengus and rainbow smelt Osmerus mordax were found in 2% of all analyzed non-empty stomachs. Lake Ontario cisco diet appears to be more similar to zooplanktivorous Lake Superior cisco than Lake Michigan where piscivory is prevalent. Lake Ontario cisco diets reflected zooplankton community changes indicating that non-native predatory cladocerans are now an important energy source supporting this native species.
Seismic interferometry is widely applied to retrieve wavefields propagating between receivers. Another version of seismic interferometry, called inter-source interferometry, uses the principles of seismic reciprocity and expands interferometric applications to retrieve waves that propagate between two seismic sources. Previous studies of inter-source interferometry usually involve surface-wave and coda-wave estimations. We use inter-source interferometry to estimate the P-waves propagating between two sources rather than the estimation of surface waves and coda waves. We show that the recovered arrival times are dependent on the accuracy of the earthquake catalog of the two sources. Using inter-source interferometry, one can recover the waveform of the direct body waves and potentially reconstruct the waveform of coda waves, depending on the source-receiver geometry. The retrieval of these waveforms is accurate only when the wavefield is sampled with approximately 4 receivers per wavelength in the stationary phase zone. We show that using only receivers inside the stationary phase region for inter-source interferometry introduces the phase error of approximately 0.3 radians. In our study, we show an example of the P-wavefield reconstruction between two earthquakes using the seismic records from an array along San Andreas Fault. The retrieved P waves give a qualitative estimation of the thickness of the low-velocity zone of San Andreas Fault of approximately 4 km.
We present a regression model for estimating mean August baseflow per square kilometer of drainage area to help resource managers assess relative amounts of baseflow in Maine streams with Atlantic Salmon habitat. The model was derived from mean August baseflows computed at 31 USGS streamflow gages in Maine. We use an ordinary least squares regression model to estimate mean August baseflow per unit drainage area from two explanatory variables: percentage of the basin underlain by sand and gravel aquifers and mean July precipitation in the basin. This model provides the ability to estimate mean August baseflow in cubic meters per second per square kilometer of basin area on user-selected, ungaged sites throughout Maine south of 46° 21′55″ N latitude. The model has an adjusted R2 of 0.78 and a mean 95% prediction interval of plus or minus 0.002 cubic meters per second per square kilometer. A map of the Narraguagus watershed in eastern coastal Maine shows reaches color coded by relative amounts of baseflow predicted by the model as an example of how this method could be applied throughout Maine. The map can be used to identify reaches with relatively higher amounts of baseflow during summer low flows for habitat conservation and restoration work. These areas have the potential to be high-quality habitat for Atlantic salmon and other cold-water fish because baseflows are known to moderate stream temperatures in summer low-flow periods.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3835","usgsCitation":"Lombard, P.J., Dudley, R., Collins, M.J., Saunders, R., and Atkinson, E., 2021, Model estimated baseflow for streams with endangered Atlantic Salmon in Maine, USA: River Research and Applications, v. 37, no. 9, p. 1254-1264, https://doi.org/10.1002/rra.3835.","productDescription":"11 p.","startPage":"1254","endPage":"1264","ipdsId":"IP-124443","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":451480,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.3835","text":"Publisher Index Page"},{"id":436271,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KRSNU7","text":"USGS data release","linkHelpText":"Spatial Coverage for Estimated Baseflow for Streams Containing Endangered Atlantic Salmon in Maine, USA (version 1.1, June 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\"}}]}","volume":"37","issue":"9","noUsgsAuthors":false,"publicationDate":"2021-07-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Lombard, Pamela J. 0000-0002-0983-1906","orcid":"https://orcid.org/0000-0002-0983-1906","contributorId":203509,"corporation":false,"usgs":true,"family":"Lombard","given":"Pamela","email":"","middleInitial":"J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819723,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dudley, Robert W. 0000-0002-0934-0568","orcid":"https://orcid.org/0000-0002-0934-0568","contributorId":220211,"corporation":false,"usgs":true,"family":"Dudley","given":"Robert W.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819724,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collins, Matthias J. 0000-0003-4238-2038","orcid":"https://orcid.org/0000-0003-4238-2038","contributorId":196365,"corporation":false,"usgs":false,"family":"Collins","given":"Matthias","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":819725,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saunders, Rory","contributorId":261311,"corporation":false,"usgs":false,"family":"Saunders","given":"Rory","email":"","affiliations":[{"id":52809,"text":"NOAA, National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":819726,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Atkinson, Ernie","contributorId":261312,"corporation":false,"usgs":false,"family":"Atkinson","given":"Ernie","email":"","affiliations":[{"id":52810,"text":"Maine Department of Marine Resources, Division of Sea-run Fisheries","active":true,"usgs":false}],"preferred":false,"id":819727,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70222387,"text":"70222387 - 2021 - Experimental evaluation of spatial capture–recapture study design","interactions":[],"lastModifiedDate":"2021-10-06T15:34:25.246554","indexId":"70222387","displayToPublicDate":"2021-07-18T07:24:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Experimental evaluation of spatial capture–recapture study design","docAbstract":"A principal challenge impeding strong inference in analyses of wild populations is the lack of robust and long-term data sets. Recent advancements in analytical tools used in wildlife science may increase our ability to integrate smaller data sets and enhance the statistical power of population estimates. One such advancement, the development of spatial capture–recapture (SCR) methods, explicitly accounts for differences in spatial study designs, making it possible to equate multiple study designs in one analysis. SCR has been shown to be robust to variation in design as long as minimal sampling guidance is adhered to. However, these expectations are based on simulation and have yet to be evaluated in wild populations. Here we conduct a rigorously designed field experiment by manipulating the arrangement of artificial cover objects (ACOs) used to collect data on red-backed salamanders (Plethodon cinereus) to empirically evaluate the effects of design configuration on inference made using SCR. Our results suggest that, using SCR, estimates of space use and detectability are sensitive to study design configuration, namely the spacing and extent of the array, and that caution is warranted when assigning biological interpretation to these parameters. However, estimates of population density remain robust to design except when the configuration of detectors grossly violates existing recommendations.
Resource allocation for land acquisition is a common multi-objective problem that involves complex trade-offs. The National Wildlife Refuge System (NWRS) of the U.S. Fish and Wildlife Service currently uses the Targeted Resource Acquisition Comparison Tool (TRACT) to allocate funds from the Migratory Bird Conservation Fund (MBCF; established through the Migratory Bird Hunting and Conservation Act of 1934) for land acquisition based on cost-benefit analysis, regional priority rankings of candidate land parcels available for acquisition, and the overall biological contribution to duck population objectives. However, current policy encourages decision makers to consider societal and economic benefits of lands acquired, in addition to their biological benefits to waterfowl. These decisions about portfolio elements (i.e. individual land parcels) require an analysis of the difficult trade-offs among multiple objectives. In the last decade the application of multi-criteria decision analysis (MCDA) methods has been instrumental in aiding decision makers with complex multi-objective decisions. In this study, we present an alternative approach to developing land acquisition portfolios using MCDA and Modern Portfolio Theory (MPT). We describe the development of a portfolio decision analysis tool using constrained optimization for land acquisition decisions by the NWRS. We outline the decision framework, describe development of the prototype tool in Microsoft Excel, and test the results of the tool using land parcels submitted as candidates for MBCF funding in 2019. Our results indicate that the constrained optimization outperformed the traditional TRACT method and ad hoc portfolios developed using current NWRS criteria.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2420","usgsCitation":"Krainyk, A., Lyons, J., Rice, M.B., Fowler, K., Soulliere, G.J., Brasher, M.G., Humburg, D.D., and Coluccy, J.M., 2021, Multicriteria decisions and portfolio analysis: Land acquisition for biological and social objectives: Ecological Applications, v. 31, no. 2, e02420, 46 p., https://doi.org/10.1002/eap.2420.","productDescription":"e02420, 46 p.","ipdsId":"IP-108367","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":387464,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-08-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Krainyk, Anastasia Ihorvina 0000-0002-3100-9011","orcid":"https://orcid.org/0000-0002-3100-9011","contributorId":261353,"corporation":false,"usgs":true,"family":"Krainyk","given":"Anastasia Ihorvina","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":819915,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":261354,"corporation":false,"usgs":true,"family":"Lyons","given":"James E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":819916,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rice, Mindy B.","contributorId":214399,"corporation":false,"usgs":false,"family":"Rice","given":"Mindy","email":"","middleInitial":"B.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":819917,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fowler, Kenneth A.","contributorId":261355,"corporation":false,"usgs":false,"family":"Fowler","given":"Kenneth A.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":819918,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Soulliere, Gregory J.","contributorId":172329,"corporation":false,"usgs":false,"family":"Soulliere","given":"Gregory","email":"","middleInitial":"J.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":819919,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brasher, Michael G.","contributorId":214393,"corporation":false,"usgs":false,"family":"Brasher","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":36215,"text":"Ducks Unlimited","active":true,"usgs":false}],"preferred":false,"id":819920,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Humburg, Dale D.","contributorId":79357,"corporation":false,"usgs":false,"family":"Humburg","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":13073,"text":"Ducks Unlimited, Inc.","active":true,"usgs":false}],"preferred":false,"id":819921,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Coluccy, John M.","contributorId":214395,"corporation":false,"usgs":false,"family":"Coluccy","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":36215,"text":"Ducks Unlimited","active":true,"usgs":false}],"preferred":false,"id":819922,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70222346,"text":"70222346 - 2021 - The Chesapeake Bay program modeling system: Overview and recommendations for future development","interactions":[],"lastModifiedDate":"2021-07-22T14:30:50.592821","indexId":"70222346","displayToPublicDate":"2021-07-17T09:14:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"The Chesapeake Bay program modeling system: Overview and recommendations for future development","docAbstract":"The Chesapeake Bay is the largest, most productive, and most biologically diverse estuary in the continental United States providing crucial habitat and natural resources for culturally and economically important species. Pressures from human population growth and associated development and agricultural intensification have led to excessive nutrient and sediment inputs entering the Bay, negatively affecting the health of the Bay ecosystem and the economic services it provides. The Chesapeake Bay Program (CBP) is a unique program formally created in 1983 as a multi-stakeholder partnership to guide and foster restoration of the Chesapeake Bay and its watershed. Since its inception, the CBP Partnership has been developing, updating, and applying a complex linked modeling system of watershed, airshed, and estuary models as a planning tool to inform strategic management decisions and Bay restoration efforts. This paper provides a description of the 2017 CBP Modeling System and the higher trophic level models developed by the NOAA Chesapeake Bay Office, along with specific recommendations that emerged from a 2018 workshop designed to inform future model development. Recommendations highlight the need for simulation of watershed inputs, conditions, processes, and practices at higher resolution to provide improved information to guide local nutrient and sediment management plans. More explicit and extensive modeling of connectivity between watershed landforms and estuary sub-areas, estuarine hydrodynamics, watershed and estuarine water quality, the estuarine-watershed socioecological system, and living resources will be important to broaden and improve characterization of responses to targeted nutrient and sediment load reductions. Finally, the value and importance of maintaining effective collaborations among jurisdictional managers, scientists, modelers, support staff, and stakeholder communities is emphasized. An open collaborative and transparent process has been a key element of successes to date and is vitally important as the CBP Partnership moves forward with modeling system improvements that help stakeholders evolve new knowledge, improve management strategies, and better communicate outcomes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2021.109635","usgsCitation":"Hood, R., Shenk, G.W., Dixon, R.L., Smith, S.M., Ball, W.P., Bash, J., Batiuk, R., Boomer, K., Brady, D.C., Cerco, C., Claggett, P., de Mutsert, K., Easton, Z.M., Elmore, A., Friedrichs, M.A., Harris, L.A., Ihde, T.F., Lacher, I., Li, L., Linker, L.C., Miller, A., Moriarty, J., Noe, G.E., Onyullo, G., Rose, K.A., Skalak, K., Tian, R., Veith, T.L., Wainger, L.A., Weller, D.E., and Zhang, Y.J., 2021, The Chesapeake Bay program modeling system: Overview and recommendations for future development: Ecological Modelling, v. 456, 109635, 28 p., https://doi.org/10.1016/j.ecolmodel.2021.109635.","productDescription":"109635, 28 p.","ipdsId":"IP-129202","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience 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M.","affiliations":[{"id":40564,"text":"Virginia Institute of Marine Science, William & Mary","active":true,"usgs":false}],"preferred":false,"id":819705,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Harris, Lora A.","contributorId":202883,"corporation":false,"usgs":false,"family":"Harris","given":"Lora","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":819706,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Ihde, Thomas F.","contributorId":261321,"corporation":false,"usgs":false,"family":"Ihde","given":"Thomas","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":819707,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Lacher, Iara","contributorId":147432,"corporation":false,"usgs":false,"family":"Lacher","given":"Iara","email":"","affiliations":[],"preferred":false,"id":819708,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Li, Li","contributorId":261322,"corporation":false,"usgs":false,"family":"Li","given":"Li","affiliations":[],"preferred":false,"id":819709,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Linker, Lewis C. 0000-0002-3456-3659","orcid":"https://orcid.org/0000-0002-3456-3659","contributorId":252964,"corporation":false,"usgs":false,"family":"Linker","given":"Lewis","email":"","middleInitial":"C.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":819710,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Miller, Andrew","contributorId":200717,"corporation":false,"usgs":false,"family":"Miller","given":"Andrew","affiliations":[],"preferred":false,"id":819711,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Moriarty, Julia 0000-0003-1087-6180","orcid":"https://orcid.org/0000-0003-1087-6180","contributorId":261307,"corporation":false,"usgs":false,"family":"Moriarty","given":"Julia","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":819712,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":436,"text":"National Research Program - 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2021 - Supporting cost-effective watershed management strategies for Chesapeake Bay using a modeling and optimization framework","interactions":[],"lastModifiedDate":"2021-10-11T12:37:34.100588","indexId":"70224975","displayToPublicDate":"2021-07-17T07:30:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7164,"text":"Environmental Modelling & Software","active":true,"publicationSubtype":{"id":10}},"title":"Supporting cost-effective watershed management strategies for Chesapeake Bay using a modeling and optimization framework","docAbstract":"Extensive efforts to adaptively manage nutrient pollution rely on Chesapeake Bay Program's (Phase 6) Watershed Model, called Chesapeake Assessment Scenario Tool (CAST), which helps decision-makers plan and track implementation of Best Management Practices (BMPs). We describe mathematical characteristics of CAST and develop a constrained nonlinear BMP-subset model, software, and visualization framework. This represents the first publicly available optimization framework for exploring least-cost strategies of pollutant load control for the United States' largest estuary. The optimization identifies implementation options for a BMP subset modeled with load reduction effectiveness factors, and the web interface facilitates interactive exploration of >30,000 solutions organized by objective, nutrient control level, and for ~200 counties. We assess framework performance and demonstrate modeled cost improvements when comparing optimization-suggested proposals with proposals inspired by jurisdiction plans. Stakeholder feedback highlights the framework's current utility for investigating cost-effective tradeoffs and its usefulness as a foundation for future analysis of restoration strategies.
Biological soil crusts (biocrusts) are communities predominately comprised of lichens, bryophytes, fungi, algae, and cyanobacteria that form at the soil surface in dryland ecosystems worldwide. Biocrusts can influence the vascular plant community by altering surface hydrology, nutrient cycling, and the availability of microsites suitable for germination. Fire frequency has increased in many dryland systems, but the potential impacts of fire on biocrust-plant interactions remains unclear. Our study explores how biocrusts and the heating associated with fire affect plant growth across five North American desert sites: the Chihuahuan, Colorado Plateau, Great Basin, Mojave, and Sonoran. Using field-collected biocrusts and mineral soil samples from each of these five deserts, we investigated soil biogeochemical differences and the implications of soil heating and biocrust cover on greenhouse grown Elymus elymoides plants. Results showed plant biomass and leaf production were largely determined by the desert where soils originated, and that the soils collected from the Great Basin site, whether heated or not, were generally higher in nutrients and distinct from the other North American desert sites. In contrast, the Chihuahuan site was lower in nutrients and plant biomass growth compared with the other desert sites. In the short term, biocrusts and heating did not significantly affect the biogeochemical profile of individual desert site soils. However, biocrusts and soil heating positively influenced plant growth, and the combination of these factors influenced plants more strongly than either factor considered separately. These findings highlight the importance of biocrusts in mediating resources and suggest additional mechanisms through which fire may alter or accentuate dynamics between biocrusts and vascular plants.
The fresh groundwater system at Fire Island National Seashore in New York is one of the natural resources that is most vulnerable to climate change; the various federally listed threatened or endangered species that live on Fire Island, including the piping plover, roseate tern shorebird, and seabeach amaranth may be affected by changes in the groundwater system. The U.S. Geological Survey, in cooperation with the National Park Service, developed a three-dimensional groundwater-flow model to simulate climate-change-related changes in depth to the water table and depth to freshwater/saltwater interfaces on Fire Island. An existing SEAWAT three-dimensional variable-density groundwater flow and transport model was converted to a MODFLOW–NWT three-dimensional finite-difference groundwater model with the Seawater Intrusion (SWI2) package and recalibrated using the UCODE_2005 automatic calibration software. The simulated groundwater divide was found to be skewed strongly toward the ocean shore in response to the modeled wave setup and tidal pumping overheight.
Effects of climate change include sea-level rise and changes in groundwater recharge rates. Sea-level rise scenarios included specified uniform steady states at 0.2-, 0.4-, and 0.6-meter increases above the 2015 level, applied to the existing topography. A high-recharge scenario was created by increasing 2015 recharge rates by 10 percent. Under all scenarios except the low-recharge scenario, the depth to the water table and the thickness of the unsaturated zone decreased. The thickness of the freshwater lens decreased under every scenario. Resulting maps were generated on a 25-meter grid and indicate changes in areas where natural resources may be vulnerable because of projected climate changes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205117","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Misut, P.E., and Dressler, S., 2021, Simulation of water-table and freshwater/saltwater interface response to climate-change-driven sea-level rise and changes in recharge at Fire Island National Seashore, New York: U.S. Geological Survey Scientific Investigations Report 2020–5117, 47 p., https://doi.org/10.3133/sir20205117.","productDescription":"Report: vii, 47 p.; Data Release","numberOfPages":"47","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-082635","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":387031,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95TBIMW","text":"USGS data release","linkHelpText":"MODFLOW-NWT model used to simulate water-table and freshwater/saltwater interface response to climate-change-driven sea-level rise and changes in recharge at the Fire Island National Seashore, New York"},{"id":387039,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20205104","text":"Scientific Investigations Report 2020–5104","linkHelpText":"- Simulated Effects of Sea-Level Rise on the Shallow, Fresh Groundwater System of Assateague Island, Maryland and Virginia"},{"id":387038,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20205080","text":"Scientific Investigations Report 2020–5080","linkHelpText":"- Simulation of Water-Table Response to Sea-Level Rise and Change in Recharge, Sandy Hook Unit, Gateway National Recreation Area, New Jersey"},{"id":387030,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5117/sir20205117.pdf","text":"Report","size":"21.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5117"},{"id":387029,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5117/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island National Seashore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.31314086914062,\n 40.614994915836924\n ],\n [\n -73.2513427734375,\n 40.612909950230936\n ],\n [\n -73.06869506835938,\n 40.65563874006118\n ],\n [\n -72.84072875976562,\n 40.730608477796636\n ],\n [\n -72.75146484374999,\n 40.763901280945866\n ],\n [\n -72.76931762695312,\n 40.77534183237267\n ],\n [\n -72.83798217773438,\n 40.74725696280421\n ],\n [\n -72.96157836914061,\n 40.72228267283148\n ],\n [\n -73.08792114257812,\n 40.66918118282895\n ],\n [\n -73.2403564453125,\n 40.637925243274374\n ],\n [\n -73.30215454101562,\n 40.63375667842965\n ],\n [\n -73.32687377929688,\n 40.62020704520565\n ],\n [\n -73.31314086914062,\n 40.614994915836924\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
The Sandy Hook Unit, Gateway National Recreation Area (hereafter Sandy Hook) in New Jersey is a 10-kilometer-long spit visited by thousands of people each year who take advantage of the historical and natural resources and recreational opportunities. The historical and natural resources are threatened by global climate change, including sea-level rise (SLR), changes in precipitation and groundwater recharge, and changes in the frequency and severity of coastal storms. Fresh groundwater resources are important to the ecosystems of Sandy Hook. The Bayside Holly Forest, one of only two known old-growth American holly (Ilex opaca) maritime forests, is particularly vulnerable to global climate change because of the proximity of the water table to land surface in low-lying areas and the potential for saltwater intrusion and inundation.
The shallow groundwater-flow system on Sandy Hook is dominated by recharge from precipitation, fresh groundwater discharge to evapotranspiration (ET), discharge to surface seeps, and submarine groundwater discharge (groundwater discharging directly to the ocean). A three-dimensional groundwater-flow model that simulates the shallow groundwater-flow system and interaction with surrounding saltwater boundaries was constructed to simulate multi-density groundwater flow, treating the freshwater/saltwater transition zone as a sharp interface that represents the half-seawater surface.
Groundwater-flow simulations completed for this study include a Baseline scenario, three SLR scenarios (0.2, 0.4, and 0.6 meter [m]), two Recharge scenarios—a 10-percent Increased Recharge scenario and a 10-percent Decreased Recharge scenario—and a scenario with 0.6 m of SLR and 10-percent increase in recharge. The Recharge scenarios indicate the system is not sensitive to a 10-percent increase or decrease in recharge from the Baseline scenario. In the SLR scenarios, SLR causes the water table to rise, resulting in increased fresh groundwater discharge to ET and seeps, and reduced submarine discharge compared to the Baseline scenario. The increased discharge to ET and seeps causes the magnitude of water-table rise to be less than that of SLR, which in turn causes the thickness of the freshwater lens to thin, reducing the depth to the half-seawater surface. Water-table rise associated with SLR diminishes the thickness of the unsaturated zone; comparing the Baseline and the 0.6-m SLR scenarios, the area where the simulated water table is above land surface increases by 50.6 hectares, from about 0.9 to 7.4 percent of the land area of Sandy Hook. Areas where the simulated water table is above land surface are likely to be emergent wetlands and contain freshwater if they are tens of meters or more from the shoreline. The steady-state simulations indicate that the percentage of land where the half-seawater surface is less than 9 m below the water table increases from about 2.5 percent (20 hectares) to about 9 percent (74 hectares) with 0.6 m of SLR. In low-lying areas close to the Sandy Hook Bay shoreline, the half-seawater surface is simulated to be as much as 20 m closer to the water table with SLR of 0.6 m. Transient salinization, if any, of shallow groundwater from increased frequency or severity of storm-driven inundation is not included in the analysis.
Natural resources on Sandy Hook, particularly the Bayside Holly Forest, may be adversely affected by the rising water table associated with SLR. Freshwater emergent wetlands may increase in area at the expense of other ecosystem assemblages occurring in or on the edges of low-lying enclosed depressions. Cultural resources close to the water table, such as existing basements of structures, may be adversely affected.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205080","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Carleton, G.B., Charles, E.G., Fiore, A.R., and Winston, R.B., 2021, Simulation of water-table response to sea-level rise and change in recharge, Sandy Hook unit, Gateway National Recreation Area, New Jersey: U.S. Geological Survey Scientific Investigations Report 2020–5080, 91 p., https://doi.org/10.3133/sir20205080.","productDescription":"Report: ix, 91 p.; Data Release","numberOfPages":"91","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-081081","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":387036,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20205117","text":"Scientific Investigations Report 2020–5117","linkHelpText":"- Simulation of Water-Table and Freshwater/Saltwater Interface Response to Climate-Change-Driven Sea-Level Rise and Changes in Recharge at Fire Island National Seashore, New York"},{"id":387037,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20205104","text":"Scientific Investigations Report 2020–5104","linkHelpText":"- Simulated Effects of Sea-Level Rise on the Shallow, Fresh Groundwater System of Assateague Island, Maryland and Virginia"},{"id":387032,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BP018M","text":"USGS data release","linkHelpText":"MODFLOW-2005 with SWI2 used to evaluate the water-table response to sea-level rise and change in recharge, Sandy Hook Unit, Gateway National Recreation Area, New Jersey"},{"id":387033,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5080/coverthb.jpg"},{"id":387034,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5080/sir20205080.pdf","text":"Report","size":"19.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5080"}],"country":"United States","state":"New Jersey","otherGeospatial":"Gateway National Recreation Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.04716491699219,\n 40.39467254512293\n ],\n [\n -73.95927429199219,\n 40.39467254512293\n ],\n [\n -73.95927429199219,\n 40.49239284038429\n ],\n [\n -74.04716491699219,\n 40.49239284038429\n ],\n [\n -74.04716491699219,\n 40.39467254512293\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike
Lawrenceville, NJ 08648
Wetlands along upper estuaries are characterized by dynamic transitions between forested and herbaceous communities (marsh) as salinity, hydroperiod, and nutrients change. The importance of belowground net primary productivity (BNPP) associated with fine and coarse root growth also changes but remains the dominant component of overall productivity in these important blue carbon wetlands. Appropriate BNPP assessment techniques to use in various tidal wetlands are not well-defined, and could make a difference in BNPP estimation. We hypothesized that different BNPP techniques applied among tidal wetlands differ in estimation of BNPP and possibly also correlate differently with porewater nutrient concentrations. We compare 6-month and 12-month root ingrowth, serial soil coring techniques utilizing two different calculations, and a mass balance approach (TBCA, Total Belowground Carbon Allocation) among four tidal wetland types along each of two river systems transitioning from freshwater forest to marsh. Median values of BNPP were 266 to 2946 g/m2/year among all techniques used, with lower BNPP estimation from root ingrowth cores and TBCA (266–416 g/m2/year), and higher BNPP estimation from serial coring of standing crop root biomass (using Smalley and Max-Min calculation methods) (2336–2946 g/m2/year). Root turnover (or longevity) to a soil depth of 30 cm was 2.2/year (1.3 years), 2.7/year (1.1 years), 4.5/year (0.9 years), and 1.2/year (2.6 years), respectively, for Upper Forest, Middle Forest, Lower Forest, and Marsh. Marsh had greater root biomass and BNPP, with slower root turnover (greater root longevity) versus forested wetlands. Soil porewater concentrations of NH3 and reactive phosphorus stimulated BNPP in the marsh when assessed with short-deployment BNPP techniques, indicating that pulses of mineralized nutrients may stimulate BNPP to facilitate marsh replacement of forested wetlands. Overall, ingrowth techniques appeared to represent forested wetland BNPP adequately, while serial coring may be necessary to represent herbaceous plant BNPP from rhizomes as marshes replace forested wetlands.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0253554","usgsCitation":"From, A., Krauss, K., Noe, G.E., Cormier, N., Stagg, C., Moss, R., and Whitbeck, J.L., 2021, Belowground productivity varies by assessment technique, vegetation type, and nutrient availability in tidal freshwater forested wetlands transitioning to marsh: PLoS ONE, v. 16, no. 7, e0253554, 24 p.; Data Release, https://doi.org/10.1371/journal.pone.0253554.","productDescription":"e0253554, 24 p.; Data Release","ipdsId":"IP-125248","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":451492,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0253554","text":"Publisher Index Page"},{"id":395155,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417856,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GZ421B"}],"country":"United States","state":"Georgia, South Carolina","otherGeospatial":"Sampit River, Savannah River, Waccamaw River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.97816467285156,\n 32.05639055725355\n ],\n [\n -80.96717834472656,\n 32.09130089401913\n ],\n [\n -81.00837707519531,\n 32.118638011730695\n ],\n [\n -81.04888916015625,\n 32.108751062791974\n ],\n [\n -81.1175537109375,\n 32.171544054655016\n ],\n [\n -81.13815307617188,\n 32.227904590766364\n ],\n [\n -81.18827819824219,\n 32.20815332547324\n ],\n [\n -81.15943908691406,\n 32.130268345320815\n ],\n [\n -81.12442016601561,\n 32.076174718029634\n ],\n [\n -81.02142333984375,\n 32.06861069132688\n ],\n [\n -80.97816467285156,\n 32.05639055725355\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.01573181152344,\n 33.614047465781894\n ],\n [\n -79.18876647949219,\n 33.62719851659249\n ],\n [\n -79.33021545410156,\n 33.351179088043494\n ],\n [\n -79.34600830078125,\n 33.26797224977847\n ],\n [\n -79.21760559082031,\n 33.247301699949205\n ],\n [\n -79.13795471191406,\n 33.44060944370356\n ],\n [\n -79.01573181152344,\n 33.614047465781894\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-07-16","publicationStatus":"PW","contributors":{"authors":[{"text":"From, Andrew 0000-0002-6543-2627","orcid":"https://orcid.org/0000-0002-6543-2627","contributorId":221929,"corporation":false,"usgs":true,"family":"From","given":"Andrew","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":832187,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krauss, Ken 0000-0003-2195-0729","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":207009,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":832188,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":436,"text":"National Research Program - 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2021 - Global-scale changes to extreme ocean wave events due to anthropogenic warming","interactions":[],"lastModifiedDate":"2021-08-19T15:19:20.697385","indexId":"70223280","displayToPublicDate":"2021-07-16T10:14:41","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Global-scale changes to extreme ocean wave events due to anthropogenic warming","docAbstract":"Extreme surface ocean waves are often primary drivers of coastal flooding and erosion over various time scales. Hence, understanding future changes in extreme wave events owing to global warming is of socio-economic and environmental significance. However, our current knowledge of potential changes in high-frequency (defined here as having return periods of less than 1 year) extreme wave events are largely unknown, despite being strongly linked to coastal hazards across time scales relevant to coastal management. Here, we present global climate-modeling evidence, based on the most comprehensive multi-method, multi-model wave ensemble, of projected changes in a core set of extreme wave indices describing high-frequency, extra-tropical storm-driven waves. We find changes in high-frequency extreme wave events of up to ∼50%–100% under RCP8.5 high-emission scenario; which is nearly double the expected changes for RCP4.5 scenario, when globally integrated. The projected changes exhibit strong inter-hemispheric asymmetry, with strong increases in extreme wave activity across the tropics and high latitudes of the Southern Hemisphere region, and a widespread decrease across most of the Northern Hemisphere. We find that the patterns of projected increase across these extreme wave events over the Southern Hemisphere region resemble their historical response to the positive anomaly of the Southern Annular Mode. Our findings highlight that many countries with low-adaptive capacity are likely to face increasing exposure to much more frequent extreme wave events in the future.
","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/ac1013","usgsCitation":"Morim, J., Vitousek, S., Hemer, M., Reguero, B., Erikson, L.H., Casas-Prat, M., Wang, X.L., Semedo, A., Mori, N., Shimura, T., Mentaschi, L., and Timmerman, B., 2021, Global-scale changes to extreme ocean wave events due to anthropogenic warming: Environmental Research Letters, v. 16, no. 7, 074056, 10 p., https://doi.org/10.1088/1748-9326/ac1013.","productDescription":"074056, 10 p.","ipdsId":"IP-116482","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":451497,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ac1013","text":"Publisher Index Page"},{"id":388151,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-07-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Morim, Joao","contributorId":264483,"corporation":false,"usgs":false,"family":"Morim","given":"Joao","email":"","affiliations":[{"id":7117,"text":"Griffith University","active":true,"usgs":false}],"preferred":false,"id":821581,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vitousek, Sean 0000-0002-3369-4673 svitousek@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-4673","contributorId":149065,"corporation":false,"usgs":true,"family":"Vitousek","given":"Sean","email":"svitousek@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":821582,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hemer, Mark","contributorId":264484,"corporation":false,"usgs":false,"family":"Hemer","given":"Mark","email":"","affiliations":[{"id":36909,"text":"CSIRO","active":true,"usgs":false}],"preferred":false,"id":821583,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reguero, Borja","contributorId":264485,"corporation":false,"usgs":false,"family":"Reguero","given":"Borja","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":821584,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":821585,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Casas-Prat, Merce","contributorId":264487,"corporation":false,"usgs":false,"family":"Casas-Prat","given":"Merce","email":"","affiliations":[{"id":54478,"text":"Environment and Climate Change Canada,","active":true,"usgs":false}],"preferred":false,"id":821586,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wang, Xiaolan L.","contributorId":264488,"corporation":false,"usgs":false,"family":"Wang","given":"Xiaolan","email":"","middleInitial":"L.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":821587,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Semedo, Alvaro","contributorId":264491,"corporation":false,"usgs":false,"family":"Semedo","given":"Alvaro","affiliations":[{"id":54479,"text":"IHE-Delft","active":true,"usgs":false}],"preferred":false,"id":821588,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mori, Nobuhito","contributorId":264492,"corporation":false,"usgs":false,"family":"Mori","given":"Nobuhito","affiliations":[{"id":36662,"text":"Kyoto University","active":true,"usgs":false}],"preferred":false,"id":821589,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Shimura, Tomoya","contributorId":264493,"corporation":false,"usgs":false,"family":"Shimura","given":"Tomoya","email":"","affiliations":[{"id":36662,"text":"Kyoto University","active":true,"usgs":false}],"preferred":false,"id":821590,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mentaschi, Lorenzo","contributorId":264494,"corporation":false,"usgs":false,"family":"Mentaschi","given":"Lorenzo","email":"","affiliations":[{"id":54481,"text":"European Commission","active":true,"usgs":false}],"preferred":false,"id":821591,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Timmerman, Ben","contributorId":264495,"corporation":false,"usgs":false,"family":"Timmerman","given":"Ben","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":821592,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ]}