Salt marshes respond to sea-level rise through a series of complex and dynamic bio-physical feedbacks. In this study, we found that sea-level rise triggered salt marsh habitat restructuring, with the associated vegetation changes enhancing salt marsh elevation resilience. A continuous record of marsh elevation relative to sea level that includes reconstruction of high-resolution, sub-decadal, marsh elevation over the past century, coupled with a lower-resolution 1500-year record, revealed that relative sea-level rose 1.5 ± 0.4 m, following local glacial isostatic adjustment (1.2 mm/yr). As sea-level rise has rapidly accelerated, the high marsh zone dropped 11 cm within the tidal frame since 1932, leading to greater inundation and a shift to flood- and salt-tolerant low marsh species. Once the marsh platform fell to the elevation favored by low-marsh Spartina alterniflora, the elevation stabilized relative to sea level. Currently low marsh accretion keeps pace with sea-level rise, while present day high marsh zones that have not transitioned to low marsh have a vertical accretion deficit. Greater biomass productivity, and an expanding subsurface accommodation space favorable for salt marsh organic matter preservation, provide a positive feed-back between sea-level rise and marsh platform elevation. Carbon storage was 46 ± 28 g C/m2/yr from 550 to 1800 CE, increasing to 129 ± 50 g C/m2/yr in the last decade. Enhanced carbon storage is controlled by vertical accretion rates, rather than soil carbon density, and is a direct response to anthropogenic eustatic sea-level rise, ultimately providing a negative feedback on climate warming.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2018.11.003","usgsCitation":"Gonneea Eagle, M., Maio, C.V., Kroeger, K.D., Hawkes, A.D., Mora, J., Sullivan, R., Madsen, S., Buzard, R., Cahill, N., and Donnelly, J.P., 2019, Salt marsh ecosystem restructuring enhances elevation resilience and carbon storage during accelerating relative sea-level rise: Estuarine, Coastal and Shelf Science, v. 217, p. 56-68, https://doi.org/10.1016/j.ecss.2018.11.003.","productDescription":"13 p.","startPage":"56","endPage":"68","ipdsId":"IP-102548","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468022,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecss.2018.11.003","text":"Publisher Index Page"},{"id":360503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.58698654174805,\n 41.542377051288376\n ],\n [\n -70.48965454101562,\n 41.542377051288376\n ],\n [\n -70.48965454101562,\n 41.58245119860674\n ],\n [\n -70.58698654174805,\n 41.58245119860674\n ],\n [\n -70.58698654174805,\n 41.542377051288376\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"217","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c1a152de4b0708288c2350b","contributors":{"authors":[{"text":"Gonneea Eagle, Meagan 0000-0001-5072-2755 mgonneea@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-2755","contributorId":174590,"corporation":false,"usgs":true,"family":"Gonneea Eagle","given":"Meagan","email":"mgonneea@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":754541,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maio, Christopher V.","contributorId":208635,"corporation":false,"usgs":false,"family":"Maio","given":"Christopher","email":"","middleInitial":"V.","affiliations":[{"id":37850,"text":"University of Alaska Fairbanks, Fairbanks, Alaska, UNITED STATES","active":true,"usgs":false}],"preferred":false,"id":754542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":754543,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hawkes, Andrea D.","contributorId":192811,"corporation":false,"usgs":false,"family":"Hawkes","given":"Andrea","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":754544,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mora, Jordan","contributorId":208060,"corporation":false,"usgs":false,"family":"Mora","given":"Jordan","email":"","affiliations":[{"id":37699,"text":"Waquoit Bay National Estuarine Research Reserve, Waquoit, Mass","active":true,"usgs":false}],"preferred":false,"id":754545,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sullivan, Richard","contributorId":211625,"corporation":false,"usgs":false,"family":"Sullivan","given":"Richard","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":754546,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Madsen, Stephanie","contributorId":211626,"corporation":false,"usgs":false,"family":"Madsen","given":"Stephanie","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":754547,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Buzard, Richard M.","contributorId":208627,"corporation":false,"usgs":false,"family":"Buzard","given":"Richard M.","affiliations":[{"id":37850,"text":"University of Alaska Fairbanks, Fairbanks, Alaska, UNITED STATES","active":true,"usgs":false}],"preferred":false,"id":754548,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cahill, Niamh","contributorId":150754,"corporation":false,"usgs":false,"family":"Cahill","given":"Niamh","email":"","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false},{"id":18091,"text":"University College Dublin","active":true,"usgs":false}],"preferred":false,"id":754549,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Donnelly, Jeffrey P.","contributorId":192783,"corporation":false,"usgs":false,"family":"Donnelly","given":"Jeffrey","email":"","middleInitial":"P.","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false}],"preferred":false,"id":754550,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70203775,"text":"70203775 - 2019 - Evaluating consumptive and nonconsumptive predator effects on prey density using field times series data","interactions":[],"lastModifiedDate":"2019-06-12T08:55:18","indexId":"70203775","displayToPublicDate":"2018-12-18T09:48:49","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating consumptive and nonconsumptive predator effects on prey density using field times series data","docAbstract":"Determining the degree to which predation affects prey abundance in natural communities constitutes a key goal of ecological research. Predators can affect prey through both consumptive effects (CEs) and nonconsumptive effects (NCEs), although the contributions of each mechanism to the density of prey populations remain largely hypothetical in most systems. Common statistical methods applied to time series data cannot elucidate the mechanisms responsible for hypothesized predator effects on prey density (e.g., differentiate CEs from NCEs), nor provide parameters for predictive models. State space models (SSMs) applied to time series data offer a way to meet these goals. Here, we employ SSMs to assess effects of an invasive predatory zooplankter, Bythotrephes longimanus, on an important prey species, Daphnia mendotae, in Lake Michigan. We fit mechanistic models in a SSM framework to seasonal time series (1994-2012) using a recently developed, maximum likelihood-based optimization method, iterated filtering, which can overcome challenges in ecological data (e.g. nonlinearities, measurement error, and irregular sampling intervals). Our results indicate that B. longimanus strongly influences D. mendotae dynamics, with mean annual peak densities of B. longimanus observed in Lake Michigan estimated to cause a 61% reduction in D. mendotae population growth rate and a 59% reduction in peak biomass density. Further, the observed B. longimanus effect is most consistent with an NCE via reduced birth rates. The SSM approach also provided estimates for key biological parameters (e.g., demographic rates) and the contribution of dynamic stochasticity and measurement error. Our study therefore provides evidence derived directly from survey data that the invasive zooplankter B. longimanus is affecting zooplankton demographics and offer parameter estimates needed to inform predictive models that explore the effect of B. longimanus under different scenarios such as climate change.","language":"English","publisher":"ESA","doi":"10.1002/ecy.2583","usgsCitation":"Marino, J.A., Peacor, S.D., Bunnell, D., Vanderploeg, H.A., Pothoven, S.A., Elgin, A.K., Bence, J., Jiao, J., and Ionides, E.L., 2019, Evaluating consumptive and nonconsumptive predator effects on prey density using field times series data: Ecology, v. 100, no. 3, Article e02583, 14 p., https://doi.org/10.1002/ecy.2583.","productDescription":"Article e02583, 14 p.","ipdsId":"IP-096682","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":488820,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/2027.42/148243","text":"External Repository"},{"id":364584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"100","issue":"3","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Marino, John A.","contributorId":216168,"corporation":false,"usgs":false,"family":"Marino","given":"John","email":"","middleInitial":"A.","affiliations":[{"id":17862,"text":"Bradley University","active":true,"usgs":false}],"preferred":false,"id":764074,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peacor, Scott D.","contributorId":216169,"corporation":false,"usgs":false,"family":"Peacor","given":"Scott","email":"","middleInitial":"D.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":764075,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bunnell, David 0000-0003-3521-7747 dbunnell@usgs.gov","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":216167,"corporation":false,"usgs":true,"family":"Bunnell","given":"David","email":"dbunnell@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":764073,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vanderploeg, Henry A.","contributorId":195891,"corporation":false,"usgs":false,"family":"Vanderploeg","given":"Henry","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":764076,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pothoven, Steven A.","contributorId":92998,"corporation":false,"usgs":false,"family":"Pothoven","given":"Steven","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":764077,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elgin, Ashley K.","contributorId":216170,"corporation":false,"usgs":false,"family":"Elgin","given":"Ashley","email":"","middleInitial":"K.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":764078,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bence, James R.","contributorId":95026,"corporation":false,"usgs":false,"family":"Bence","given":"James R.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":764079,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jiao, J.","contributorId":216171,"corporation":false,"usgs":false,"family":"Jiao","given":"J.","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":764080,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ionides, Edward L.","contributorId":216172,"corporation":false,"usgs":false,"family":"Ionides","given":"Edward","email":"","middleInitial":"L.","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":764081,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70206271,"text":"70206271 - 2019 - On the contribution of waves to total coastal water level changes in the context of sea level rise: a response to Melet, et al. (2018)","interactions":[],"lastModifiedDate":"2019-10-29T08:28:48","indexId":"70206271","displayToPublicDate":"2018-12-18T08:28:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1246,"text":"Climate Change","onlineIssn":"1573-1480","printIssn":"0165-0009","active":true,"publicationSubtype":{"id":10}},"title":"On the contribution of waves to total coastal water level changes in the context of sea level rise: a response to Melet, et al. (2018)","docAbstract":"Response to Melet, A., Meyssignac, B., Almar, R. & Le Cozannet, G. Under-estimated wave contribution to coastal sea-level rise. Nat. Clim. Change 8, 234–239 (2018).\n\nIn a recent paper, Melet et al.1 claim that the contribution of wind-waves to coastal sea-level rise has been under-estimated. Although we agree with the overall premise that coastal wind-wave dynamics are important when assessing the full coastal impacts of sea-level rise, we argue that the paper is misleading.\n\nIncreasing development such as roads and houses will alter future landscapes and result in biological, social, and economic trade-offs. Managing development requires information on the public’s acceptability of development and understanding which factors shape acceptability. In this study, we examined three questions: 1) What is the public’s acceptability of development? 2) Is acceptability of development influenced by wildlife information? and 3) Is the maximum amount of acceptable development influenced by views about wildlife, involvement in outdoor recreation, and demographic factors? We conducted a visual-preference survey of 9,000 households in Vermont, USA that asked about acceptable levels of development, acceptability of wildlife, involvement in recreation, and individual and town demographics. The survey response rate was 44%. Maximum acceptable condition (MAC) for development was 41 houses/km2 and not meaningfully influenced by broader consequences of development on seven common wildlife species. MAC was influenced by views on individual species, including bear and coyote, but not by other species such as deer, fox, and bobcat. Respondents with a positive attitude toward bear favored less development, whereas the opposite relationship existed for coyote. Similarly, MAC was negatively influenced by involvement in birding and hunting, but not by other common recreational activities. Among demographic factors, respondents that were younger and not born in Vermont were more accepting of development. Population density also positively influenced development acceptability. Results provide measures of the public’s acceptability of development that can help guide decision-making about development, wildlife, and recreation management.
Concerns have been raised regarding the practice of exposing fish to air during catch-and-release (C&R) angling. The purpose of this study was to evaluate the effects of air exposure on short- and long-term survival and progeny production of Yellowstone Cutthroat Trout Oncorhynchus clarkii bouvieri. Prespawn adults were sampled at a weir during upstream migration in 2016 and 2017, exposed to a simulated angling event of 102 s, and then exposed to air for a randomly selected duration of 0, 30, or 60 s. An additional control group was added during 2017 in which fish were not exposed to simulated angling or air. In total, 1,519 fish were sampled in 2016, and 744 fish were sampled in 2017. Additionally, age-0 fish (2016: n = 2,924; 2017: n = 1,492) were collected to evaluate the effects of air exposure on the production of progeny. No effect of angling itself or of angling and air exposure was observed on short-term (≤60 d posttreatment) or long-term (>1 year posttreatment) survival of adults, with one exception. During 2016, fish that had been air exposed for 60 s had a statistically higher short-term survival rate than fish that received no air exposure. Air exposure had no effect on the proportion of fish that successfully spawned. Regression analysis revealed that neither angling nor air exposure affected progeny production. Considering that much of the literature, as well as this study, reports little to no influence of air exposure on salmonid mortality or reproductive success, it seems highly unlikely that air exposure of less than 60 s during C&R angling would have negative population-level effects.
The glacial aquifer system, which is a collection of aquifers within Quaternary sediments in the glaciated conterminous United States, is a principal aquifer that supplies groundwater that serves about 42 million people and accounts for about 5 percent of the Nation’s drinking water. This aquifer system (the area of maximum glacial advance) underlies parts of 25 States and covers 1.87×106 square kilometers. A hydrogeologic framework is presented that divides the glaciated United States into 17 distinct hydrogeologic terranes using a geologic approach based on previous mapping. Each hydrogeologic terrane contains Quaternary sediment that is derived from a common depositional history and can be characterized by similar texture and thickness. Characteristics of Quaternary sediments are described using attributes computed from a lithologic database of well logs compiled from 24 States (excluding Kentucky). The hydrogeologic framework presents a nationwide picture of the glacial aquifer system and provides generalizations concerning the nature of aquifers within it (for example, whether the aquifers are shallow or deep, and unconfined or confined). In this way insights can be gained from understanding the similarities and differences in distinct parts of the glacial aquifer system and how they relate to water use and quality and to aquifer vulnerability.
Delineation of hydrogeologic terranes was based on an interpretation of existing geologic mapping of Quaternary sediments and the thickness of unconsolidated material. Overall thickness of Quaternary sediment was used to qualitatively rank the generalized complexity of the hydrogeologic framework in each terrane: “lower” complexity (assigned a terrane code 1), “moderate” complexity (terrane code 2), and “higher” complexity (terrane code 3). Letter designations appended to the terrane codes (for example, 1A, 1B, or 1C) differentiate terranes of similar complexity. Two unique areas, where thick, stratified, coarse-grained sediment dominates, were assigned terrane code 4.
Elements of this hydrogeologic framework include a glacial environments and surficial sediments geodatabase, which includes lithologic, geomorphic, and stratigraphic characterization of Quaternary sediments based on previous mapping; a gridded database of sediment and aquifer characteristics computed from lithologic logs obtained from water-well driller records; a water-use database with information on public-water supply systems and sources of groundwater; and estimated recharge computed from a geologically based soil-water balance model. A generalized map of the bedrock geology based on previous State-level mapping is included as well.
Quaternary sediment in the glaciated United States includes glacial, postglacial (Holocene) and nonglacial sediments. At land surface, 60 percent of the glacial sediment is till. Large areas of outwash and ice contact sediments are extensive throughout the Midwest but generally are confined to valleys in the Northeast and the Northwest. Lacustrine sediments were deposited in proglacial lakes adjacent to the present Great Lakes and in glacial Lake Agassiz in the eastern Dakotas and northwestern Minnesota. The median thickness of Quaternary sediment ranges from 6 to 45 meters across the 17 hydrogeologic terranes, but the maximum thickness is more than 500 meters in some areas. Quaternary sediments generally contain less than 10 percent coarse material; the median range is near zero percent under till to about 50 percent under ice contact and outwash sediments. About 80 percent of the coarse material lies within 25 to 40 meters of land surface.
In most of the glaciated United States, there is a small likelihood of penetrating an aquifer-material interval containing coarse material at least 3 meters thick. A single aquifer-material interval was recorded in about 44 percent of lithologic logs, whereas about 11 percent of the logs penetrated multiple intervals. About 44 percent of water wells in the lithologic database are completed in Quaternary sediment, and many of these Quaternary water wells (42 percent) are confined by at least 7.5 meters of fine materials. About 33 percent of these Quaternary water wells are unconfined—the remainder are where only thin layers (less than 3 meters) of coarse material are present. The median depths of Quaternary water wells range from 13 to 40 meters among the 17 hydrogeologic terranes.
Recharge ranges from more than 400 millimeters per year in the Northeast to 11 millimeters or less per year in the Dakotas and Montana (median value of 136 millimeters per year). Annual groundwater withdrawals compiled by county range on an areal basis from less than 1 to 370 millimeters per year, and the mean is 7.4 millimeters per year. About 36 percent of the withdrawals are for public-water supply, of which 70 percent are derived from Quaternary sediments. Groundwater withdrawals are less than 10 percent of recharge throughout most of the glaciated conterminous United States but are a larger proportion of recharge near urban areas in the Northeast and the Midwest, and in counties throughout drier parts of the Midwest.
The salient characteristics of the 17 hydrogeologic terranes are presented through maps and a set of descriptive plots to facilitate visual comparisons between selected sediment and aquifer characteristics. The thickness of Quaternary sediment generally increases from the lower complexity terranes through the higher complexity terranes, consistent with their delineation. Median proportions of coarse material in Quaternary sediment and depths to aquifer-material intervals are highly variable (less than 10 to 50 percent, and 0 to 30 meters, respectively). Median thicknesses of aquifer-material intervals generally fall within a narrow range (10 to 20 meters), except in two terranes that contain thick coarse-grained sediment (30 to 35 meters). The source of water in wells varies from mostly bedrock wells in the lower complexity terranes to mostly Quaternary wells in the higher complexity terranes where the sediment is thickest. A tree diagram compiled from a hierarchical cluster analysis of a matrix composed of metrics based on sediment and aquifer characteristics, and the distribution of water wells in each terrane, indicates some groups of terranes that can be treated as comparable when analyzing groundwater flow and quality.
Aquifer-material intervals indicated on maps prepared from the lithologic logs, including unconfined and confined conditions, correlate well with aquifer systems delineated on state maps for Illinois, Indiana, and North Dakota. The large scale of the study limits the resolution at which the maps can be interpreted, however, and alluvial units are not mapped correctly for some valleys in the Northeast and the Northwest. Lithologic logs used in the study are biased toward shallow depths because not all logs penetrate the entire thickness of Quaternary sediment, but this bias should not limit the utility of the sediment and aquifer descriptions because shallow depths are commonly exploited for water supply. The hydrogeologic framework will support ongoing studies of groundwater flow and quality in the U.S. Geological Survey National Water Quality Assessment program for the glaciated United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185091","usgsCitation":"Yager, R.M., Kauffman, L.J., Soller, D.R., Haj, A.E., Heisig, P.M., Buchwald, C.A., Westenbroek, S.M., and Reddy, J.E., 2019, Characterization and occurrence of confined and unconfined aquifers in Quaternary sediments in the glaciated conterminous United States (ver. 1.1, February 2019): U.S. Geological Survey Scientific Investigations Report 2018–5091, 90 p., https://doi.org/10.3133/sir20185091.","productDescription":"Report: ix, 90 p.; Interactive Leaflet maps; Data releases","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-081249","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":359750,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71R6PQG","text":"USGS data release","description":"USGS data release","linkHelpText":"Databases used to develop a hydrogeologic framework for Quaternary sediments in the glaciated conterminous United States"},{"id":359748,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/ds1090","text":"Data Series 1090","linkHelpText":"- Hydrogeologic Framework for Characterization and Occurrence of Confined and Unconfined Aquifers in Quaternary Sediments in the Glaciated Conterminous United States—A Digital Map Compilation and Database"},{"id":359747,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7HH6J8X","text":"USGS data release","description":"USGS data release","linkHelpText":"Digital products from a hydrogeologic framework for Quaternary sediments within the glaciated conterminous United States"},{"id":359745,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5091/coverthb2.jpg"},{"id":359749,"rank":6,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sir/2018/5091/sir20185091_index.html","linkFileType":{"id":5,"text":"html"},"linkHelpText":"- Index page for oversized, interactive Leaflet maps"},{"id":359746,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5091/sir20185091.pdf","text":"Report","size":"17.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5091"},{"id":361089,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2018/5091/versionHist.txt","size":"1.27 KB","linkFileType":{"id":2,"text":"txt"}}],"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 -124.969069883,\n 35.090811167\n ],\n [\n -65.343237884,\n 35.090811167\n ],\n [\n -65.343237884,\n 50.932504994\n ],\n [\n -124.969069883,\n 50.932504994\n ],\n [\n -124.969069883,\n 35.090811167\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: February 2019; Version 1.0: December 2018","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street
Iowa City, IA 52240
Competition between microbial sulfate reduction and methanogenesis drives cycling of fossil carbon and generation of CH4 in sedimentary basins. However, little is understood about the fundamental relationship between subsurface aqueous geochemistry and microbiology that drives these processes. Here we relate elemental and isotopic geochemistry of coal-associated water and gas to the microbial community composition from wells in two different coal beds across CH4 and SO42− gradients (Powder River Basin, Montana, USA). Areas with high CH4 concentrations generally have higher alkalinity and δ13C-DIC values, little to no SO42−, and greater conversion of coal-biodegradable organics to CH4 (based on δ13C-CH4and δ13C-CO2 values). Wells with SO42− concentrations from 2 to 10 mM had bacterial populations dominated by several different sulfate-reducing bacteria and archaea that were mostly novel and unclassified. In contrast, in wells with SO42− concentrations <1 mM, the sequences were dominated by presumptive syntrophic bacteria as well as archaeal Methanosarcinales and Methanomicrobiales. The presence of sequences indicative of these bacteria in low SO42− methanogenic wells may suggest a syntrophic role in coal biodegradation and/or the generation of methanogenic substrates from intermediate organic compounds. Archaeal sequences were observed in all sampled zones, with an enrichment of sequences indicative of methanogens in low SO42− zones and unclassified sequences in high SO42− zones. However, sequences indicative of Methanomassiliicoccales were enriched in intermediate SO42− zones and suggest tolerance to SO42− and/or alternative metabolisms in the presence of SO42−. Moreover, sequences indicative of methylotrophic methanogens were more prevalent in an intermediate SO42− and CH4 well and results suggest an important role for methylotrophic methanogens in critical zone transitions. The presented results demonstrate in situ changes in bacterial and archaeal population distributions along a SO42− gradient associated with recalcitrant, organic carbon that is biodegraded and converted to CO2 and/or CH4.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2018.11.009","usgsCitation":"Schweitzer, H., Ritter, D., McIntosh, J., Barnhart, E.P., Cunningham, A.B., Vinson, D., Orem, W.H., and Fields, M.W., 2019, Changes in microbial communities and associated water and gas geochemistry across a sulfate gradient in coal beds: Powder River Basin, USA: Geochimica et Cosmochimica Acta, v. 245, p. 495-513, https://doi.org/10.1016/j.gca.2018.11.009.","productDescription":"19 p.","startPage":"495","endPage":"513","ipdsId":"IP-094442","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":468025,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gca.2018.11.009","text":"Publisher Index Page"},{"id":360261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Powder River Basin","volume":"245","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c137dc8e4b006c4f8514856","contributors":{"authors":[{"text":"Schweitzer, Hannah","contributorId":211468,"corporation":false,"usgs":false,"family":"Schweitzer","given":"Hannah","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":754144,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ritter, Daniel","contributorId":211473,"corporation":false,"usgs":false,"family":"Ritter","given":"Daniel","affiliations":[],"preferred":false,"id":754145,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McIntosh, Jennifer","contributorId":100059,"corporation":false,"usgs":true,"family":"McIntosh","given":"Jennifer","affiliations":[],"preferred":false,"id":754146,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnhart, Elliott P. 0000-0002-8788-8393","orcid":"https://orcid.org/0000-0002-8788-8393","contributorId":203225,"corporation":false,"usgs":true,"family":"Barnhart","given":"Elliott","middleInitial":"P.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":754143,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cunningham, Alfred B.","contributorId":172389,"corporation":false,"usgs":false,"family":"Cunningham","given":"Alfred","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":754147,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vinson, David","contributorId":211474,"corporation":false,"usgs":false,"family":"Vinson","given":"David","affiliations":[],"preferred":false,"id":754148,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Orem, William H. 0000-0003-4990-0539 borem@usgs.gov","orcid":"https://orcid.org/0000-0003-4990-0539","contributorId":577,"corporation":false,"usgs":true,"family":"Orem","given":"William","email":"borem@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":754149,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fields, Matthew W.","contributorId":172391,"corporation":false,"usgs":false,"family":"Fields","given":"Matthew","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":754150,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70227822,"text":"70227822 - 2019 - Spatial organization of fish diversity in a species-rich basin","interactions":[],"lastModifiedDate":"2022-02-01T19:18:48.099253","indexId":"70227822","displayToPublicDate":"2018-12-13T14:18:22","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Spatial organization of fish diversity in a species-rich basin","docAbstract":"Many abiotic and biotic environmental characteristics in river basins show spatial gradients from river source to main stem. We examined the spatial organization of fish within the Duck River Basin to document patterns in diversity that could help guide conservation strategies relevant to controlling the detrimental effects of basin development. In all, over 0.33 million fishes representing 145 species and 18 families, including 9 non-native species, were collected in 207 samples distributed throughout the basin. Main stem sites with large catchment areas supported more fish diversity than smaller sites in tributaries. Moreover, rare species were most common in the main stem and ubiquitous species in tributaries. The spatial organization of species assemblages was mostly nested, as assemblages appeared to disassemble in an upstream direction from main stem sites and confluences. These findings suggest that fish conservation efforts might emphasize main stem segments and confluences that support higher biodiversity including the rare species often most in need of protection. The main stem can support the populations needed to recolonize tributaries and rescue populations that might periodically go extinct after droughts or other major disturbances. In tributaries, conservation of species assemblages may focus on managing between-patch connectivity via corridor maintenance or creation.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3392","usgsCitation":"Miranda, L.E., Kilgore, K.J., and Slack, W., 2019, Spatial organization of fish diversity in a species-rich basin: River Research and Applications, v. 35, no. 2, p. 188-196, https://doi.org/10.1002/rra.3392.","productDescription":"9 p.","startPage":"188","endPage":"196","ipdsId":"IP-098959","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468026,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.3392","text":"Publisher Index Page"},{"id":395230,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","otherGeospatial":"Duck River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.95379638671874,\n 35.36217605914681\n ],\n [\n -86.0504150390625,\n 35.36217605914681\n ],\n [\n -86.0504150390625,\n 36.089060460282006\n ],\n [\n -87.95379638671874,\n 36.089060460282006\n ],\n [\n -87.95379638671874,\n 35.36217605914681\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"2","noUsgsAuthors":false,"publicationDate":"2018-12-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":832371,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kilgore, Kenneth J.","contributorId":272892,"corporation":false,"usgs":false,"family":"Kilgore","given":"Kenneth","email":"","middleInitial":"J.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":832372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Slack, William T.","contributorId":272893,"corporation":false,"usgs":false,"family":"Slack","given":"William T.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":832373,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70201138,"text":"sim3423 - 2019 - Delineation of selected lithologic units using airborne electromagnetic data near Cedar Rapids, Iowa","interactions":[],"lastModifiedDate":"2019-02-08T12:22:20","indexId":"sim3423","displayToPublicDate":"2018-12-12T13:38:43","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3423","displayTitle":"Delineation of Selected Lithologic Units Using Airborne Electromagnetic Data near Cedar Rapids, Iowa","title":"Delineation of selected lithologic units using airborne electromagnetic data near Cedar Rapids, Iowa","docAbstract":"The U.S. Geological Survey, in cooperation with the City of Cedar Rapids, began a study in 2013 to better understand the effects of drought stress on the Cedar River alluvial aquifer. After an evaluation of the existing groundwater-flow models for the alluvial aquifer, a plan was begun to construct an updated groundwater-flow model capable of evaluating the effect of prolonged drought and increased demand. As part of the effort to update the existing groundwater-flow model, data were collected during an airborne electromagnetic (AEM) survey in May 2017. The study area for the AEM survey encompasses about 53 square kilometers of the Cedar River Basin, west of Cedar Rapids, Iowa, and includes a 19-kilometer reach of the Cedar River. The AEM survey of the Cedar River alluvial aquifer and adjacent areas was completed to characterize the subsurface geology of the area to refine a lithologic framework. The collected AEM data were postprocessed by numerical inversion using the program EM1DFM to produce subsurface apparent resistivity cross sections. Changes observed in resistivity profile values with depth were used to infer lithologic changes and delineate three of the four lithologic units designated in the lithologic framework for this area: alluvial deposits, glacial till, and bedrock; hereafter referred to as the “lithologic framework.” The fourth unit, composed of surficial eolian sediments, was not delineated in these profiles because these units are thin and discontinuous and are not reliably distinguishable from flood plain alluvial deposits. For the purposes of delineating lithologic units using the AEM data, bedrock was assumed to be the lowest unit in a profile, glacial till was deposited on a bedrock surface, and alluvium was deposited on erosional till or bedrock surfaces.
A three-dimensional fence diagram was created as part of the lithologic framework to further define the extent and thickness of the lithologic units near the Cedar River alluvial aquifer. The fence diagram shows a three-dimensional perspective of unit thickness, extent, and orientation of the delineated lithologic framework. A lithologic framework, by design, is intended to represent a simplification of a more complex natural system through data interpolation between known points, which usually are lithologic logs. The resistivity profiles produced from the AEM survey allow for continuous mapping and accurate interpolation of lithology between lithologic logs; however, the apparent resistivity value may reflect several characteristics of subsurface materials including variations in lithology, porosity, water quality, grain sorting, and degree of saturation. In this study, the only variables considered were those related to changes in the subsurface material.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3423","collaboration":"Prepared in cooperation with the City of Cedar Rapids","usgsCitation":"Valder, J.F., Haj, A.E., Bristow, E.L., and Valseth, K.J., 2019, Delineation of selected lithologic units using airborne electromagnetic data near Cedar Rapids, Iowa (ver. 1.1, February 2019): U.S. Geological Survey Scientific Investigations Map 3423, 2 sheets, 9-p. pamphlet, https://doi.org/10.3133/sim3423.","productDescription":"Pamphlet: vi, 9 p.; 2 Sheets: 42.0 x 24.0 inches and 44.0 x 28.0 inches; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-101741","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":361084,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sim/3423/versionHist.txt","text":"Version History","size":"1 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3423 Version History"},{"id":360194,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3423/sim3423_sheet2.pdf","text":"Sheet 2","size":"2.99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3423 Sheet 2"},{"id":360192,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3423/sim3423_pamphlet.pdf","text":"Pamphlet","size":"2.00 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3423 Pamphlet"},{"id":360191,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3423/coverthb2.jpg"},{"id":360193,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3423/sim3423_sheet1.pdf","text":"Sheet 1","size":"7.65 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3423 Sheet 1"},{"id":360208,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BS882S","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Airborne electromagnetic and magnetic survey data and inverted resistivity models, Cedar Rapids, Iowa, May 2017"}],"country":"United States","state":"Iowa","city":"Cedar Rapids","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.8,\n 42\n ],\n [\n -91.7,\n 42\n ],\n [\n -91.7,\n 42.0667\n ],\n [\n -91.8,\n 42.0667\n ],\n [\n -91.8,\n 42\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: February 2019; Version 1.0: December 2018","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
1608 Mountain View Road
Rapid City, SD 57702
Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing salt marsh management decisions at the Bombay Hook National Wildlife Refuge in Delaware. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of eight salt marsh management units within the refuge and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that would be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per salt marsh management unit, that would maximize total management benefits at different cost constraints at the refuge scale. Results indicated that for the objectives and actions considered here, total management benefits would increase consistently up to approximately \\$300,000, but that further expenditures would yield diminishing return on investment. Management actions selected within optimal portfolios at total costs less than \\$300,000 included hydrologic restoration, recontouring adjacent uplands to facilitate marsh migration, and burning the marsh. The prototype presented here provides a framework for decision making at the Bombay Hook National Wildlife Refuge that can be updated as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181160","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Neckles, H.A., Lyons, J.E., Nagel, J.L., Adamowicz, S.C., Mikula, T., Guiteras, S.T., and Mitchell, L.R., 2018, Optimization of salt marsh management at the Bombay Hook National Wildlife Refuge, Delaware, through use of structured decision making (ver. 1.1, May 2019): U.S. Geological Survey Open-File Report 2018–1160, 29 p., https://doi.org/10.3133/ofr20181160.","productDescription":"vi, 29 p.","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-098065","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":360083,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1160/coverthb2.jpg"},{"id":364017,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2018/1160/versionHist.txt","text":"Version History","size":"1.35 KB","linkFileType":{"id":2,"text":"txt"}},{"id":360084,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1160/ofr20181160.pdf","text":"Report","size":"26.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1160"}],"country":"United States","state":"Delaware","otherGeospatial":"Bombay Hook National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.52928924560547,\n 39.18410260153466\n ],\n [\n -75.3885269165039,\n 39.18410260153466\n ],\n [\n -75.3885269165039,\n 39.30667511534216\n ],\n [\n -75.52928924560547,\n 39.30667511534216\n ],\n [\n -75.52928924560547,\n 39.18410260153466\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: May 29, 2019","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road
Laurel, MD 20708
Before the digital era, seismograms were recorded in analog form and read manually by analysts. The digital era represents only about 25% of the total time span of instrumental seismology. Analog data provide important constraints on earthquake processes over the long term, and in some cases are the only data available. The media on which analog data are recorded degrades with time and there is an urgent need for cost‐effective approaches to preserve the information they contain. In this study, we work directly with images by constructing a set of image‐based methods for earthquake processing, rather than pursue the usual approach of converting analog data to vector time series. We demonstrate this approach on one month of continuous Develocorder films from the Rangely earthquake control experiment run by the U.S. Geological Survey (USGS). We scan the films into images and compress these into low‐dimensional feature vectors as input to a classifier that separates earthquakes from noise in a defined feature space. We feed the detected event images into a short‐term average/long‐term average (STA/LTA) picker, a grid‐search associator, and a 2D image correlator to measure both absolute arrival times and relative arrival‐time differences between events. We use these measurements to locate the earthquakes using hypoDD. In the month that we studied, we identified 40 events clustered near the injection wells. In the original study, Raleigh et al. (1976) identified only 32 events during the same period. Scanning without vectorizing analog seismograms represents an attractive approach to archiving these perishable data. We demonstrated that it is possible to carry out precision seismology directly on such images. Our approach has the potential for wide application to analog seismograms.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220180298","usgsCitation":"Wang, K., Ellsworth, W., Beroza, G.C., Williams, G., Zhang, M., Schroeder, D., and Rubinstein, J.L., 2019, Seismology with dark data: Image-based processing of analog records using machine learning for the rangely earthquake control experiment: Seismological Research Letters, v. 90, no. 2A, p. 553-562, https://doi.org/10.1785/0220180298.","productDescription":"10 p.","startPage":"553","endPage":"562","ipdsId":"IP-101838","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":363470,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"90","issue":"2A","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Kaiwen","contributorId":215275,"corporation":false,"usgs":false,"family":"Wang","given":"Kaiwen","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":761970,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellsworth, William L. 0000-0001-8378-4979","orcid":"https://orcid.org/0000-0001-8378-4979","contributorId":194691,"corporation":false,"usgs":true,"family":"Ellsworth","given":"William L.","affiliations":[],"preferred":false,"id":761971,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beroza, Gregory C.","contributorId":191201,"corporation":false,"usgs":false,"family":"Beroza","given":"Gregory","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":761972,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Gordon","contributorId":215276,"corporation":false,"usgs":false,"family":"Williams","given":"Gordon","affiliations":[{"id":37180,"text":"UC Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":761973,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhang, Miao","contributorId":215277,"corporation":false,"usgs":false,"family":"Zhang","given":"Miao","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":761974,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schroeder, Dustin","contributorId":215278,"corporation":false,"usgs":false,"family":"Schroeder","given":"Dustin","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":761975,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rubinstein, Justin L. 0000-0003-1274-6785","orcid":"https://orcid.org/0000-0003-1274-6785","contributorId":206551,"corporation":false,"usgs":true,"family":"Rubinstein","given":"Justin","email":"","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":761969,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70201329,"text":"70201329 - 2019 - A 50-year Sr/Ca time series from an enclosed, shallow-water Guam coral: In situ monitoring and extraction of a temperature trend, annual cycle, and ENSO and PDO signals","interactions":[],"lastModifiedDate":"2019-03-15T12:41:32","indexId":"70201329","displayToPublicDate":"2018-12-11T11:33:30","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"A 50-year Sr/Ca time series from an enclosed, shallow-water Guam coral: In situ monitoring and extraction of a temperature trend, annual cycle, and ENSO and PDO signals","docAbstract":"Located on the northern edge of the West Pacific Warm Pool and having a developed economy and modern infrastructure, Guam is well positioned and equipped for obtaining natural records of the west Pacific maritime paleoclimate. This study was a proof of concept to explore whether useful climate proxy records might be obtained from coral at readily accessible, even if geochemically nonoptimal, coastal sites. A 50-year Sr/Ca record (1960–2010) was thus obtained from a shallow-water, near-shore Porites luteacolony at a recreational facility inside Guam's Apra Harbor and compared with local and regional meteorological records, including the El Niño–Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) indices. The accessibility of the site enabled documentation of relevant environmental variables for 16 months (September 2009–December 2010): seawater δ18O, pH, seawater cations, and nitrate. Time series of seawater δ18O, pH, and cations show evidence of freshwater input from direct rainfall and stream discharge into the harbor. An anomalously higher mean and variable concentrations of Ba suggest the presence of river-borne, fine-grained terrigenous sediment. Nevertheless, the Sr/Ca time series reproduces a long-term warming trend seen in historical records of local air temperature and regional sea-surface temperature (SST) and closely tracks the ENSO and PDO indices over the entire 50-year record. The consistency of the results with Guam's historical instrumental records, previous coral δ18O results from Guam obtained by others, and previous Sr/Ca proxy results for SST in similar environments elsewhere demonstrate that accessible near-shore sites—where environmental conditions can be monitored—can produce useful Sr/Ca records of local and regional climate phenomena.
","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/JCOASTRES-D-16-00099.1","usgsCitation":"Bell, T., Lander, M., Jenson, J., Randall, R., Partin, J.W., and Prouty, N.G., 2019, A 50-year Sr/Ca time series from an enclosed, shallow-water Guam coral: In situ monitoring and extraction of a temperature trend, annual cycle, and ENSO and PDO signals: Journal of Coastal Research, v. 35, no. 2, p. 269-286, https://doi.org/10.2112/JCOASTRES-D-16-00099.1.","productDescription":"18 p.","startPage":"269","endPage":"286","ipdsId":"IP-075254","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":360156,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a8e2e4b034bf6a7e4dbb","contributors":{"authors":[{"text":"Bell, Tomoko","contributorId":211310,"corporation":false,"usgs":false,"family":"Bell","given":"Tomoko","email":"","affiliations":[{"id":7267,"text":"University of Tokyo","active":true,"usgs":false}],"preferred":false,"id":753624,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lander, Mark","contributorId":211311,"corporation":false,"usgs":false,"family":"Lander","given":"Mark","affiliations":[{"id":38228,"text":"University of Guam","active":true,"usgs":false}],"preferred":false,"id":753625,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jenson, John","contributorId":211312,"corporation":false,"usgs":false,"family":"Jenson","given":"John","affiliations":[{"id":38228,"text":"University of Guam","active":true,"usgs":false}],"preferred":false,"id":753626,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Randall, Richard","contributorId":211313,"corporation":false,"usgs":false,"family":"Randall","given":"Richard","email":"","affiliations":[{"id":38228,"text":"University of Guam","active":true,"usgs":false}],"preferred":false,"id":753627,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Partin, Judson W.","contributorId":203459,"corporation":false,"usgs":false,"family":"Partin","given":"Judson","email":"","middleInitial":"W.","affiliations":[{"id":36624,"text":"Institute for Geophysics, Jackson School of Geosciences, University of Texas at Austin, J. J. Pickle Research Campus, Building 196, 10100 Burnet Road (R2200), Austin, Texas 78758, USA","active":true,"usgs":false}],"preferred":false,"id":753628,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Prouty, Nancy G. 0000-0002-8922-0688 nprouty@usgs.gov","orcid":"https://orcid.org/0000-0002-8922-0688","contributorId":3350,"corporation":false,"usgs":true,"family":"Prouty","given":"Nancy","email":"nprouty@usgs.gov","middleInitial":"G.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":753623,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70201350,"text":"70201350 - 2019 - Food‐web structure and ecosystem function in the Laurentian Great Lakes—Toward a conceptual model","interactions":[],"lastModifiedDate":"2019-01-28T08:36:06","indexId":"70201350","displayToPublicDate":"2018-12-11T11:00:11","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Food‐web structure and ecosystem function in the Laurentian Great Lakes—Toward a conceptual model","docAbstract":"Avian immunology developed originally by investigating domesticated poultry species (Galliformes), but in recent decades eco-immunological studies of wild bird species have revealed that avian immune systems are more diverse than initially assumed. This study compares six immunological elements in eggs of six species within the same family, the New World blackbirds (Icteridae),whose members differ most notably in two life history parameters, brood parasitism and body size. We measured the maternal immune investment of passive immune components in both yolk and albumen: lysozyme, ovotransferrin, and immunoglobulins (Igs), and LPS-specific Igs. We predicted that brood parasites would have higher levels of immune activity for both innate and adaptive immunity compared with non-brood parasites, and that increased body size could increase microbial exposure of larger animals, resulting in an increase in some adaptive immune responses, such as LPS-specific Igs. We found that brood parasites had significantly higher levels of Igs and lysozyme levels in albumen, but significantly lower levels of Igs in yolk compared with non-brood parasites. Igs in yolk scaled according to body size, with the smallest organisms (the brood parasites) having the lowest levels, and the largest organism (common grackle) having the highest. Our results confirm the findings of other studies of comparative immunity among species in a single taxon that (1) similarities in immune investment cannot be assumed among closely related species and (2) single measures of immune defense cannot be assumed to be indicators of a species’ overall immune strategy, as life history traits can differentially affect immune responses.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/iob/oby011","usgsCitation":"Fassbinder-Orth, C., Igl, L., Hahn, D., Watts, K.M., Wilcoxon, T., and Ramos-Alvarez, K., 2019, Do life history traits influence patterns of maternal immune elements in New World blackbirds (Icteridae)?: Integrative Organismal Biology, v. 1, no. 1, https://doi.org/10.1093/iob/oby011.","productDescription":"oby011, 12 p.","startPage":"1-12","ipdsId":"IP-089571","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468029,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/iob/oby011","text":"Publisher Index Page"},{"id":369081,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota, Puerto Rico, South Dakota","city":"Cabo Rojo","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.1700668334961,\n 18.03652451536251\n ],\n [\n -67.10586547851562,\n 18.03652451536251\n ],\n [\n -67.10586547851562,\n 18.105392315190315\n ],\n [\n -67.1700668334961,\n 18.105392315190315\n ],\n [\n -67.1700668334961,\n 18.03652451536251\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.150390625,\n 42.53689200787315\n ],\n [\n -96.48193359375,\n 42.53689200787315\n ],\n [\n -96.48193359375,\n 49.081062364320736\n ],\n [\n -104.150390625,\n 49.081062364320736\n ],\n [\n -104.150390625,\n 42.53689200787315\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"1","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Fassbinder-Orth, Carol","contributorId":167623,"corporation":false,"usgs":false,"family":"Fassbinder-Orth","given":"Carol","email":"","affiliations":[{"id":24786,"text":"Creighton University, Omaha, NE, 68178, USA","active":true,"usgs":false}],"preferred":false,"id":774934,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Igl, Lawrence D. 0000-0003-0530-7266","orcid":"https://orcid.org/0000-0003-0530-7266","contributorId":214801,"corporation":false,"usgs":true,"family":"Igl","given":"Lawrence D.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":774933,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hahn, D. Caldwell 0000-0002-5242-2059","orcid":"https://orcid.org/0000-0002-5242-2059","contributorId":26055,"corporation":false,"usgs":true,"family":"Hahn","given":"D. Caldwell","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":774932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Watts, Kelsey M.","contributorId":220447,"corporation":false,"usgs":false,"family":"Watts","given":"Kelsey","email":"","middleInitial":"M.","affiliations":[{"id":40171,"text":"Creighton University","active":true,"usgs":false}],"preferred":false,"id":774937,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilcoxon, Travis 0000-0002-9492-8859","orcid":"https://orcid.org/0000-0002-9492-8859","contributorId":220446,"corporation":false,"usgs":false,"family":"Wilcoxon","given":"Travis","email":"","affiliations":[{"id":40170,"text":"Millikin University","active":true,"usgs":false}],"preferred":false,"id":774936,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ramos-Alvarez, Katsi","contributorId":220445,"corporation":false,"usgs":false,"family":"Ramos-Alvarez","given":"Katsi","email":"","affiliations":[{"id":40169,"text":"Departamento de Recursos Naturales y Ambientales de Puerto Rico","active":true,"usgs":false}],"preferred":false,"id":774935,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70217859,"text":"70217859 - 2019 - Beta diversity response to stress severity and heterogeneity in sensitive versus tolerant stream diatoms","interactions":[],"lastModifiedDate":"2021-02-08T13:38:21.190833","indexId":"70217859","displayToPublicDate":"2018-12-11T07:33:23","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Beta diversity response to stress severity and heterogeneity in sensitive versus tolerant stream diatoms","docAbstract":"Severity and heterogeneity of stress are major constraints of beta diversity, but their relative influence is poorly understood. Here, we addressed this question by examining the patterns of beta diversity in stress‐sensitive versus stress‐tolerant stream diatoms and their response to local versus regional factors along gradients of stress severity and heterogeneity.
The Adirondack region of New York.
Beta diversity was measured as multivariate dispersion of communities across high stress, low stress, and high + low stress (heterogeneous) environments, encompassing 200 stream samples. Null models were implemented to assess community similarity relative to randomly assembled communities and the importance of local assembly processes versus the regional species pool.
The overall beta diversity was influenced by a combination of severity and heterogeneity of stress, while beta diversity of sensitive species increased with heterogeneity. Beta diversity of tolerant species did not vary with either severity or heterogeneity of stress. Heterogeneity decreased community similarity relative to the null expectation in all groups of species. Stress reduced the importance of local assembly mechanisms for the overall beta diversity and sensitive species beta diversity. In contrast, the importance of local assembly mechanisms increased with stress regarding beta diversity of tolerant species.
Beta diversity responded to both severity and heterogeneity of stress, but turnover along these gradients was mostly driven by sensitive species. The overall beta diversity and beta diversity of sensitive species became more constrained by the depauperate regional species pool, as opposed to local assembly mechanisms. While heterogeneous stress contributed to beta diversity, severe stress suppressed beta diversity through elimination of sensitive species. Therefore, an increase in beta diversity in an environmentally‐stressed region may serve as a forewarning for future loss of sensitive species, should the stress continue to intensify.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.12865","usgsCitation":"Pound, K., Lawrence, G.B., and Passy, S., 2019, Beta diversity response to stress severity and heterogeneity in sensitive versus tolerant stream diatoms: Diversity and Distributions, v. 25, no. 3, p. 374-384, https://doi.org/10.1111/ddi.12865.","productDescription":"11 p.","startPage":"374","endPage":"384","ipdsId":"IP-073100","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":468030,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.12865","text":"Publisher Index Page"},{"id":383086,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Adirondack Park, Black River basin, Oswegatchie River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.3936767578125,\n 43.201171681272456\n ],\n [\n -74.33349609375,\n 43.201171681272456\n ],\n [\n -74.33349609375,\n 44.453388800301774\n ],\n [\n -75.3936767578125,\n 44.453388800301774\n ],\n [\n -75.3936767578125,\n 43.201171681272456\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"25","issue":"3","noUsgsAuthors":false,"publicationDate":"2018-12-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Pound, Katrina L","contributorId":139826,"corporation":false,"usgs":false,"family":"Pound","given":"Katrina L","affiliations":[{"id":13288,"text":"Graduate student, Dept of Biology, Univ of Texas at Arlington","active":true,"usgs":false}],"preferred":false,"id":809943,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":809944,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Passy, Sophia","contributorId":248812,"corporation":false,"usgs":false,"family":"Passy","given":"Sophia","affiliations":[{"id":50025,"text":"Associate Professor, University of Texas at Arlington","active":true,"usgs":false}],"preferred":false,"id":809945,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70201280,"text":"70201280 - 2019 - Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models","interactions":[],"lastModifiedDate":"2018-12-10T12:41:37","indexId":"70201280","displayToPublicDate":"2018-12-10T12:41:32","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models","docAbstract":"Gully erosion susceptibility mapping is a fundamental tool for land-use planning aimed at mitigating land degradation. However, the capabilities of some state-of-the-art data-mining models for developing accurate maps of gully erosion susceptibility have not yet been fully investigated. This study assessed and compared the performance of two different types of data-mining models for accurately mapping gully erosion susceptibility at a regional scale in Chavar, Ilam, Iran. The two methods evaluated were: Certainty Factor (CF), a bivariate statistical model; and Maximum Entropy (ME), an advanced machine learning model. Several geographic and environmental factors that can contribute to gully erosion were considered as predictor variables of gully erosion susceptibility. Based on an existing differential GPS survey inventory of gully erosion, a total of 63 eroded gullies were spatially randomly split in a 70:30 ratio for use in model calibration and validation, respectively. Accuracy assessments completed with the receiver operating characteristic curve method showed that the ME-based regional gully susceptibility map has an area under the curve (AUC) value of 88.6% whereas the CF-based map has an AUC of 81.8%. According to jackknife tests that were used to investigate the relative importance of predictor variables, aspect, distance to river, lithology and land use are the most influential factors for the spatial distribution of gully erosion susceptibility in this region of Iran. The gully erosion susceptibility maps produced in this study could be useful tools for land managers and engineers tasked with road development, urbanization and other future development.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.11.235","usgsCitation":"Azareh, A., Rahmati, O., Rafiei-Sardooi, E., Sankey, J.B., Lee, S., Shahabi, H., and Bin Ahmad, B., 2019, Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models: Science of the Total Environment, v. 655, p. 684-696, https://doi.org/10.1016/j.scitotenv.2018.11.235.","productDescription":"13 p.","startPage":"684","endPage":"696","ipdsId":"IP-091094","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468031,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2018.11.235","text":"Publisher Index Page"},{"id":360103,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Iran","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 46.1667,\n 33.3333\n ],\n [\n 47,\n 33.3333\n ],\n [\n 47,\n 33.8333\n ],\n [\n 46.1667,\n 33.8333\n ],\n [\n 46.1667,\n 33.3333\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"655","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c0f8977e4b0c53ecb2c71de","contributors":{"authors":[{"text":"Azareh, Ali","contributorId":211256,"corporation":false,"usgs":false,"family":"Azareh","given":"Ali","email":"","affiliations":[{"id":38202,"text":"Department of Geography, University of Jiroft, Kerman, Iran","active":true,"usgs":false}],"preferred":false,"id":753469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rahmati, Omid","contributorId":211254,"corporation":false,"usgs":false,"family":"Rahmati","given":"Omid","email":"","affiliations":[{"id":38200,"text":"Department of Watershed Management, Faculty of Agriculture and Natural Resources Management, Lorestan University, Iran","active":true,"usgs":false}],"preferred":false,"id":753467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rafiei-Sardooi, Elham","contributorId":211257,"corporation":false,"usgs":false,"family":"Rafiei-Sardooi","given":"Elham","email":"","affiliations":[{"id":38203,"text":"Faculty of Natural Resources, University of Jiroft, Kerman, Iran","active":true,"usgs":false}],"preferred":false,"id":753470,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":753466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lee, Saro","contributorId":211255,"corporation":false,"usgs":false,"family":"Lee","given":"Saro","email":"","affiliations":[{"id":38201,"text":"Geological Research Division, Korea Institute of Geoscience and Mineral Resources (KIGAM), Daejeon 305350, Korea","active":true,"usgs":false}],"preferred":false,"id":753468,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shahabi, Himan","contributorId":211258,"corporation":false,"usgs":false,"family":"Shahabi","given":"Himan","email":"","affiliations":[{"id":38204,"text":"Department of Geomorphology, Faculty of Natural Resources, University of Kurdistan, Sanandaj, Iran","active":true,"usgs":false}],"preferred":false,"id":753471,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bin Ahmad, Baharin","contributorId":211259,"corporation":false,"usgs":false,"family":"Bin Ahmad","given":"Baharin","email":"","affiliations":[{"id":38205,"text":"Department of Geoinformation, Faculty of Geoinformation and Real Estate, Universiti Teknologi Malaysia (UTM), Malaysia","active":true,"usgs":false}],"preferred":false,"id":753472,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70201281,"text":"70201281 - 2019 - Energetic constraints and the paradox of a diffusing population in a heterogeneous environment","interactions":[],"lastModifiedDate":"2019-01-28T08:37:33","indexId":"70201281","displayToPublicDate":"2018-12-10T12:36:52","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3593,"text":"Theoretical Population Biology","active":true,"publicationSubtype":{"id":10}},"title":"Energetic constraints and the paradox of a diffusing population in a heterogeneous environment","docAbstract":"Previous mathematical analyses have shown that, for certain parameter ranges, a population, described by logistic equations on a set of connected patches, and diffusing among them, can reach a higher equilibrium total population when the local carrying capacities are heterogeneously distributed across patches, than when carrying capacities having the same total sum are homogeneously distributed across the patches. It is shown here that this apparently paradoxical result is explained when the resultant differences in energy inputs to the whole multi-patch system are taken into account. We examine both Pearl–Verhulst and Original Verhulst logistic models and show that, when total input of energy or limiting resource, is constrained to be the same in the homogeneous and heterogeneous cases, the total population in the heterogeneous patches can never reach an asymptotic equilibrium that is greater than the sum of the carrying capacities over the homogeneous patches. We further show that, when the dynamics of the limiting resources are explicitly modeled, as in a chemostat model, the paradoxical result of the logistic models does not occur. These results have implications concerning the use of some ubiquitous equations of population ecology in modeling populations in space.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.tpb.2018.11.003","usgsCitation":"Wang, Y., and DeAngelis, D.L., 2019, Energetic constraints and the paradox of a diffusing population in a heterogeneous environment: Theoretical Population Biology, v. 125, p. 30-37, https://doi.org/10.1016/j.tpb.2018.11.003.","productDescription":"8 p.","startPage":"30","endPage":"37","ipdsId":"IP-092638","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":460541,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.tpb.2018.11.003","text":"Publisher Index Page"},{"id":360102,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"125","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c0f8979e4b0c53ecb2c71e5","contributors":{"authors":[{"text":"Wang, Yuanshi","contributorId":207814,"corporation":false,"usgs":false,"family":"Wang","given":"Yuanshi","email":"","affiliations":[{"id":37637,"text":"School of Mathematics and Computational Science Sun Yat-sen University","active":true,"usgs":false}],"preferred":false,"id":753474,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":148065,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":753473,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70223253,"text":"70223253 - 2019 - Running on empty: Recharge dynamics from animal movement data","interactions":[],"lastModifiedDate":"2021-08-19T16:21:18.119233","indexId":"70223253","displayToPublicDate":"2018-12-09T11:19:30","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Running on empty: Recharge dynamics from animal movement data","docAbstract":"Vital rates such as survival and recruitment have always been important in the study of population and community ecology. At the individual level, physiological processes such as energetics are critical in understanding biomechanics and movement ecology and also scale up to influence food webs and trophic cascades. Although vital rates and population-level characteristics are tied with individual-level animal movement, most statistical models for telemetry data are not equipped to provide inference about these relationships because they lack the explicit, mechanistic connection to physiological dynamics. We present a framework for modelling telemetry data that explicitly includes an aggregated physiological process associated with decision making and movement in heterogeneous environments. Our framework accommodates a wide range of movement and physiological process specifications. We illustrate a specific model formulation in continuous-time to provide direct inference about gains and losses associated with physiological processes based on movement. Our approach can also be extended to accommodate auxiliary data when available. We demonstrate our model to infer mountain lion (Puma concolor; in Colorado, USA) and African buffalo (Syncerus caffer; in Kruger National Park, South Africa) recharge dynamics.
","language":"English","publisher":"Wiley","doi":"10.1111/ele.13198","usgsCitation":"Hooten, M., Scharf, H.R., and Morales, J.M., 2019, Running on empty: Recharge dynamics from animal movement data: Ecology Letters, v. 22, no. 2, p. 377-389, https://doi.org/10.1111/ele.13198.","productDescription":"13 p.","startPage":"377","endPage":"389","ipdsId":"IP-101207","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468032,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://eprints.gla.ac.uk/277798/","text":"External Repository"},{"id":388161,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"2","noUsgsAuthors":false,"publicationDate":"2018-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":821532,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scharf, Henry R.","contributorId":206652,"corporation":false,"usgs":false,"family":"Scharf","given":"Henry","email":"","middleInitial":"R.","affiliations":[{"id":37371,"text":"Colorado State University, Department of Statistics","active":true,"usgs":false}],"preferred":false,"id":821533,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morales, Juan M.","contributorId":171521,"corporation":false,"usgs":false,"family":"Morales","given":"Juan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":821534,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70201225,"text":"70201225 - 2019 - Coastal wetlands: A synthesis","interactions":[],"lastModifiedDate":"2018-12-07T15:18:55","indexId":"70201225","displayToPublicDate":"2018-12-07T15:18:52","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Coastal wetlands: A synthesis","docAbstract":"This book and this synthesis address the pressing need for better management of coastal wetlands worldwide because these wetlands are disappearing at an alarming rate; in some countries the loss is 70%–80% in the last 50 years. Managing requires understanding. Although our understanding of the functioning of coastal wetland ecosystems has grown rapidly over the past decade, still much remains to be learned and understood. We have gained insight into the roles of geomorphic processes, hydrologic dynamics, biotic feedback, and disturbance agents in creating and molding a variety of coastal wetland ecosystems across climatic gradients. The variety is expressed not so much in the more obvious differences in vegetation cover, but rather how physical processes both facilitate and constrain a diversity of plant and animal communities. At one level, coastal wetlands are the product of tidal forces and freshwater inputs at the margin of continents. At another level, the plants control the water currents in the tidal creeks draining the wetlands by generating a tidal current asymmetry that controls sediment transport and results in a deep tidal creek surrounded by shallow vegetated wetlands. The vegetation also influences the physics of water and sediment through several other processes including biofilms, bioturbation of sediments, the buffeting of currents and waves, organic enrichment of sediments, and the closing of nutrient cycles. Few ecosystems provide us with so many clear examples of such feedback controls. What we do understand about the structure and functioning of coastal wetlands should provide the theoretical underpinnings for effective management in protecting them for their many contributions to ecosystem goods and services. What we do not understand should compel us to focus our attention and energies toward seeking optimal solutions to some of the most perplexing and urgent problems facing natural resource management.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Coastal wetlands: An integrated ecosystem approach","language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-444-63893-9.00001-0","usgsCitation":"Hopkinson, C.S., Wolanski, E., Cahoon, D.R., Perillo, G.M., and Brinson, M.M., 2019, Coastal wetlands: A synthesis, chap. of Coastal wetlands: An integrated ecosystem approach, p. 1-75, https://doi.org/10.1016/B978-0-444-63893-9.00001-0.","productDescription":"75 p.","startPage":"1","endPage":"75","ipdsId":"IP-098675","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":360068,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c0b9570e4b0c53ecb2aca78","contributors":{"editors":[{"text":"Perillo, Gerardo M. E.","contributorId":211190,"corporation":false,"usgs":false,"family":"Perillo","given":"Gerardo","email":"","middleInitial":"M. E.","affiliations":[],"preferred":false,"id":753392,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Wolanski, Eric","contributorId":82186,"corporation":false,"usgs":true,"family":"Wolanski","given":"Eric","affiliations":[],"preferred":false,"id":753393,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Cahoon, Donald R. 0000-0002-2591-5667 dcahoon@usgs.gov","orcid":"https://orcid.org/0000-0002-2591-5667","contributorId":3791,"corporation":false,"usgs":true,"family":"Cahoon","given":"Donald","email":"dcahoon@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":753394,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Hopkinson, Charles S.","contributorId":139745,"corporation":false,"usgs":false,"family":"Hopkinson","given":"Charles","email":"","middleInitial":"S.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":753395,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Hopkinson, Charles S.","contributorId":139745,"corporation":false,"usgs":false,"family":"Hopkinson","given":"Charles","email":"","middleInitial":"S.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":753326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolanski, Eric","contributorId":211163,"corporation":false,"usgs":false,"family":"Wolanski","given":"Eric","email":"","affiliations":[],"preferred":false,"id":753327,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cahoon, Donald R. 0000-0002-2591-5667 dcahoon@usgs.gov","orcid":"https://orcid.org/0000-0002-2591-5667","contributorId":3791,"corporation":false,"usgs":true,"family":"Cahoon","given":"Donald","email":"dcahoon@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":753325,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perillo, Gerardo M. E.","contributorId":211190,"corporation":false,"usgs":false,"family":"Perillo","given":"Gerardo","email":"","middleInitial":"M. E.","affiliations":[],"preferred":false,"id":753329,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brinson, Mark M.","contributorId":211164,"corporation":false,"usgs":false,"family":"Brinson","given":"Mark","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":753328,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70201226,"text":"70201226 - 2019 - Evaluating restored tidal freshwater wetlands","interactions":[],"lastModifiedDate":"2018-12-07T15:16:36","indexId":"70201226","displayToPublicDate":"2018-12-07T15:16:32","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Evaluating restored tidal freshwater wetlands","docAbstract":"As restoration of tidal freshwater wetlands has progressed in North America and Eurasia, research findings have continued to emerge on the postrestoration success of these ecosystems. The most common approaches used to restore tidal freshwater wetlands involve excavation or placement of dredged sediment to restore tidal hydrology compatible with vegetation establishment and managed realignment or diversion, which involves reconnecting former wetlands to tides by breaching dikes or levees. Postconstruction monitoring of tidal freshwater wetland restoration projects commonly includes not only studies of hydrology, soil, and vegetation but also geomorphology, microbial communities, seed banks, fish, birds, and invertebrates. Based on a review of assessment approaches and monitoring studies, we present criteria for evaluating tidal freshwater wetland restoration projects. In a case study, we apply these criteria to evaluate restored tidal freshwater wetlands in the highly urbanized Anacostia River watershed (Washington, DC, USA). We conclude that restoration can create tidal freshwater wetlands worldwide that share some structural or functional aspects with natural systems. Soil organic matter and microbial communities may be the slowest components to develop, and watershed urbanizationimposes strong constraints that prevent development of tidal freshwater wetlands similar to those in rural settings.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Coastal wetlands: An integrated ecosystem approach","language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-444-63893-9.00025-3","usgsCitation":"Baldwin, A.H., Hammerschlag, R.S., and Cahoon, D.R., 2019, Evaluating restored tidal freshwater wetlands, chap. of Coastal wetlands: An integrated ecosystem approach, p. 889-912, https://doi.org/10.1016/B978-0-444-63893-9.00025-3.","productDescription":"24 p.","startPage":"889","endPage":"912","ipdsId":"IP-089855","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":360067,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c0b9572e4b0c53ecb2aca7a","contributors":{"editors":[{"text":"Perillo, Gerardo M. E.","contributorId":211190,"corporation":false,"usgs":false,"family":"Perillo","given":"Gerardo","email":"","middleInitial":"M. E.","affiliations":[],"preferred":false,"id":753388,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Wolanski, Eric","contributorId":211163,"corporation":false,"usgs":false,"family":"Wolanski","given":"Eric","email":"","affiliations":[],"preferred":false,"id":753389,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Cahoon, Donald R. 0000-0002-2591-5667 dcahoon@usgs.gov","orcid":"https://orcid.org/0000-0002-2591-5667","contributorId":3791,"corporation":false,"usgs":true,"family":"Cahoon","given":"Donald","email":"dcahoon@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":753390,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Hopkinson, Charles S.","contributorId":139745,"corporation":false,"usgs":false,"family":"Hopkinson","given":"Charles","email":"","middleInitial":"S.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":753391,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Baldwin, Andrew H.","contributorId":11479,"corporation":false,"usgs":true,"family":"Baldwin","given":"Andrew","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":753386,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hammerschlag, Richard S.","contributorId":67206,"corporation":false,"usgs":true,"family":"Hammerschlag","given":"Richard","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":753387,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cahoon, Donald R. 0000-0002-2591-5667 dcahoon@usgs.gov","orcid":"https://orcid.org/0000-0002-2591-5667","contributorId":3791,"corporation":false,"usgs":true,"family":"Cahoon","given":"Donald","email":"dcahoon@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":753330,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70201236,"text":"70201236 - 2019 - Fire changes the spatial distribution and sources of soil organic carbon in a grassland-shrubland transition zone","interactions":[],"lastModifiedDate":"2019-02-21T14:47:10","indexId":"70201236","displayToPublicDate":"2018-12-07T15:01:43","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3089,"text":"Plant and Soil","active":true,"publicationSubtype":{"id":10}},"title":"Fire changes the spatial distribution and sources of soil organic carbon in a grassland-shrubland transition zone","docAbstract":"Aims
In many mixed grass-shrub ecosystems, increased shrub biomass tends to promote overall carbon storage, but the distribution of carbon pools may be complicated by disturbances such as wildfires. We investigated the spatial distribution of surface soil organic carbon (SOC) and its relative contribution from grasses and shrubs after fires in a grass-shrub transition zone in the northern Chihuahuan Desert, USA.
Methods
We used a prescribed fire to create a burned treatment, then collected soil and plant samples. The biogeochemical approaches, geostatistical analyses, and carbon partitioning analyses were used to quantify the SOC and soil δ13C spatial patterns.
Results
Before the prescribed fire, up to 98% of the spatial dependence of SOC was autocorrelated at a distance of 1.91 m, corresponding to the approximate average shrub canopy diameter, but the spatial dependence dropped to 81% at a larger autocorrelation distance (3.74 m) two windy seasons after the fire. C4 grasses and C3 shrubs contributed approximately equal amounts of carbon to the surface SOC pool before the prescribed fire. However, C4 grasses became the dominant source of SOC two windy seasons following the fire. For individual microsites, a substantially increased proportion of SOC was derived from C4 grasses at the shrub microsites following the fire.
Conclusions
The higher proportion of C4 grasses-derived SOC at the shrub microsites post-fire suggests that SOC may have preferred pathways to move among different microsites following fire disturbance. The distinct spatial distribution patterns of δ13C, and the increased contribution of SOC from grasses may be explained by the rapid recovery of grasses following the fire. Overall, our results provide insights into how fire might be used as a management tool to alter soil carbon pools in the context of shrub encroachment.
Results from several long‐term monitoring programs in the western Adirondack Mountains, New York, indicate that acid–base chemistry of headwater streams has remained unchanged or improved only marginally since the 1990s. A paucity of quantitative fishery data, however, limits our understanding of the pre‐acidified communities as well as present‐day impacts of acidification on fish assemblages, which impedes efforts to evaluate temporal trends and biological recovery in streams of the region. Fish communities were characterized at 48 streams (chemistry was assessed at 47 streams) in the western Adirondacks at least once during summer 2014–2016 to assess present‐day effects of acidification on fish assemblages, refine important relations, and identify biological targets and chemical effect thresholds that could help gauge biological recovery across the region. Concentrations of inorganic aluminum (Ali) exceeded chronic and acute toxicity thresholds (1.0 and 2.0 μmol/L) in 21.3% and 8.5%, respectively, of 47 study streams sampled during summer 2014–2016 and in 64.0% and 44.0% of 25 streams sampled during spring 2014–2015. In streams with summer Aliconcentrations less than 1.0 μmol/L, community richness, density, and biomass averaged 2.0 species, 444.2 fish/0.1 ha, and 1,924.4 g/0.1 ha, respectively, whereas density and biomass of Brook Trout Salvelinus fontinalis populations averaged 280.8 fish/0.1 ha and 1,384.0 g/0.1 ha, respectively. These findings identify defensible targets for biological recovery and show that Ali toxicity is not a major concern for fish assemblages in most streams during summer base flow periods but is potentially a serious issue for fish in as many as two‐thirds of streams during spring high flows. Though additional data are needed to address several limitations and information gaps, results from this study provide a sound foundation to gauge biological recovery, detect future effects of climatic stressors, and help ensure that functional stream ecosystems can be sustained or restored in parts of the Adirondacks.
","language":"English","publisher":"Wiley ","doi":"10.1002/tafs.10137","usgsCitation":"Baldigo, B., George, S., Lawrence, G., and Paul, E., 2019, Acidification impacts and goals for gauging recovery of Brook Trout populations and fish communities in streams of the Western Adirondack Mountains, New York, USA: Transactions of the American Fisheries Society, v. 148, no. 2, p. 373-392, https://doi.org/10.1002/tafs.10137.","productDescription":"20 p.","startPage":"373","endPage":"392","ipdsId":"IP-098030","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":468033,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10137","text":"Publisher Index Page"},{"id":362148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.26184082031249,\n 43.59630591596548\n ],\n [\n -73.5150146484375,\n 43.59630591596548\n ],\n [\n -73.5150146484375,\n 44.18220395771566\n ],\n [\n -75.26184082031249,\n 44.18220395771566\n ],\n [\n -75.26184082031249,\n 43.59630591596548\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"148","issue":"2","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Baldigo, Barry","contributorId":214240,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":759427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"George, Scott","contributorId":214241,"corporation":false,"usgs":true,"family":"George","given":"Scott","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":759428,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":214242,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":759429,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paul, Eric","contributorId":214243,"corporation":false,"usgs":false,"family":"Paul","given":"Eric","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":759430,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}