{"pageNumber":"99","pageRowStart":"2450","pageSize":"25","recordCount":40782,"records":[{"id":70252921,"text":"70252921 - 2023 - Sea-ice conditions predict polar bear land use around military installations in Alaska","interactions":[],"lastModifiedDate":"2024-04-11T12:06:38.792532","indexId":"70252921","displayToPublicDate":"2023-12-29T07:02:27","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1914,"text":"Human-Wildlife Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Sea-ice conditions predict polar bear land use around military installations in Alaska","docAbstract":"

Polar bears (Ursus maritimus) are threatened by sea-ice loss due to climate change, which is concurrently opening the Arctic to natural resource extraction and a broader scope of national security responsibilities. Mitigating the risk of human–bear conflicts is an emerging challenge as many polar bears spend longer ice-free summers on land where they have limited access to food and come into more frequent contact with people. We investigated a suite of physical and ecological variables that influence the timing of polar bear arrival on, and departure from, land using remote-sensing data on sea-ice extent and satellite telemetry data from 72 radio-collared adult female polar bears from 1986 to 2015. Analyses encompassed the coastline of the Southern Beaufort Sea north of Alaska, USA, and focused on zones within a 35-km radius (mean daily travel distance of a polar bear) of 5 military installations. Sea ice in the Southern Beaufort Sea retreated approximately 1 month earlier in spring, and reformed 1 month later in fall, in 2015 compared to 1979. In generalized linear mixed models, the most important predictors of polar bear arrival and departure were the dates of sea-ice breakup and formation, respectively, in localized marine areas surrounding each military zone. Region-wide sea-ice conditions also influenced land use, although to a lesser extent. We found that polar bears spent longer periods on land in the military zones compared to outside the zones, which may reflect increased land use in areas with human activity and potential attractants (noting that some military installations were in proximity to other human settlements). Our results demonstrate that the timing of polar bear land use in northern Alaska is influenced by sea-ice conditions on multiple spatial scales. This information can be used to predict and manage the presence of polar bears around military installations and other places of interest.

","language":"English","publisher":"Berryman Institute","doi":"10.26077/39a8-fb75","usgsCitation":"Regehr, E.V., Laidre, K.L., Atwood, T.C., Stern, H., and Cohen, B.R., 2023, Sea-ice conditions predict polar bear land use around military installations in Alaska: Human-Wildlife Interactions, v. 17, no. 1, 5, 16 p., https://doi.org/10.26077/39a8-fb75.","productDescription":"5, 16 p.","ipdsId":"IP-132810","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":427697,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -159.03676165597616,\n 72.4217331977608\n ],\n [\n -159.03676165597616,\n 67.87487435242491\n ],\n [\n -140.5797304059763,\n 67.87487435242491\n ],\n [\n -140.5797304059763,\n 72.4217331977608\n ],\n [\n -159.03676165597616,\n 72.4217331977608\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Regehr, Eric V. 0000-0003-4487-3105","orcid":"https://orcid.org/0000-0003-4487-3105","contributorId":66364,"corporation":false,"usgs":false,"family":"Regehr","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":898658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Laidre, Kristin L.","contributorId":191798,"corporation":false,"usgs":false,"family":"Laidre","given":"Kristin","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":898659,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":898660,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stern, Harry","contributorId":192065,"corporation":false,"usgs":false,"family":"Stern","given":"Harry","email":"","affiliations":[],"preferred":false,"id":898661,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cohen, Benjamin R.","contributorId":35629,"corporation":false,"usgs":true,"family":"Cohen","given":"Benjamin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":898680,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70250751,"text":"70250751 - 2023 - Climate impacts to inland fishes: Shifting research topics over time","interactions":[],"lastModifiedDate":"2024-01-03T12:57:58.64162","indexId":"70250751","displayToPublicDate":"2023-12-29T06:54:20","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16703,"text":"PLOS Climate","active":true,"publicationSubtype":{"id":10}},"title":"Climate impacts to inland fishes: Shifting research topics over time","docAbstract":"

Climate change remains a primary threat to inland fishes and fisheries. Using topic modeling to examine trends and relationships across 36 years of scientific literature on documented and projected climate impacts to inland fish, we identify ten representative topics within this body of literature: assemblages, climate scenarios, distribution, climate drivers, population growth, invasive species, populations, phenology, physiology, and reproduction. These topics are largely similar to the output from artificial intelligence application (i.e., ChatGPT) search prompts, but with some key differences. The field of climate impacts on fish has seen dramatic growth since the mid-2000s with increasing popularity of topics related to drivers, assemblages, and phenology. The topics were generally well-dispersed with little overlap of common words, apart from phenology and reproduction which were closely clustered. Pairwise comparisons between topics revealed potential gaps in the literature including between reproduction and distribution and between physiology and phenology. A better understanding of these relationships can help capitalize on existing literature to inform conservation and sustainable management of inland fishes with a changing climate.

","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pclm.0000326","usgsCitation":"Lynch, A., DiSanto, A., Olden, J., Chu, C., Paukert, C., Gundermann, D., Lang, M., Zhang, R., and Krabbenhoft, T.J., 2023, Climate impacts to inland fishes: Shifting research topics over time: PLOS Climate, v. 2, no. 12, e0000326, 17 p., https://doi.org/10.1371/journal.pclm.0000326.","productDescription":"e0000326, 17 p.","ipdsId":"IP-147108","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":441340,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pclm.0000326","text":"Publisher Index Page"},{"id":424064,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Lynch, Abigail 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":216203,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":891263,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DiSanto, Andrew","contributorId":302728,"corporation":false,"usgs":false,"family":"DiSanto","given":"Andrew","email":"","affiliations":[{"id":25492,"text":"University of Virginia","active":true,"usgs":false}],"preferred":false,"id":891264,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olden, Julian D.","contributorId":202893,"corporation":false,"usgs":false,"family":"Olden","given":"Julian D.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":891265,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chu, Cindy","contributorId":176496,"corporation":false,"usgs":false,"family":"Chu","given":"Cindy","email":"","affiliations":[],"preferred":false,"id":891266,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paukert, Craig 0000-0002-9369-8545","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":268045,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":891267,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gundermann, Daria","contributorId":302727,"corporation":false,"usgs":false,"family":"Gundermann","given":"Daria","email":"","affiliations":[{"id":25492,"text":"University of Virginia","active":true,"usgs":false}],"preferred":false,"id":891268,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lang, Mitchel","contributorId":302726,"corporation":false,"usgs":false,"family":"Lang","given":"Mitchel","email":"","affiliations":[{"id":25492,"text":"University of Virginia","active":true,"usgs":false}],"preferred":false,"id":891269,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zhang, Ray","contributorId":302725,"corporation":false,"usgs":false,"family":"Zhang","given":"Ray","email":"","affiliations":[{"id":12909,"text":"George Mason University","active":true,"usgs":false}],"preferred":false,"id":891270,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Krabbenhoft, Trevor J.","contributorId":176498,"corporation":false,"usgs":false,"family":"Krabbenhoft","given":"Trevor","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":891271,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70254076,"text":"70254076 - 2023 - Gap analysis: A proposed methodology to describe and map historical and contemporary populations and habitats","interactions":[],"lastModifiedDate":"2024-05-06T11:53:54.050606","indexId":"70254076","displayToPublicDate":"2023-12-29T06:50:25","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Gap analysis: A proposed methodology to describe and map historical and contemporary populations and habitats","docAbstract":"This is a methodology paper that describes an approach for modeling and mapping historical and contemporary spawning areas for coregonine fishes in the Laurentian Great Lakes. Coregonines are a family of native whitefishes and ciscoes that are now greatly reduced or extirpated, but once served important roles for both the food web and society. This method can illustrate where habitats once existed and where they are today - critical information for restoration and conservation actions.","language":"English","publisher":"Great Lakes Ciscoes","collaboration":"University of Michigan; U.S. Fish and Wildlife Service; Fisheries and Oceans Canada; Chippewas of Nawash Unceded First Nation; Michigan Department of Natural Resources; The Nature Conservancy; Ontario Ministry of Northern Development, Mines, Natural Resources and Forestry; National Oceanic and Atmospheric Administration; Sault Ste Marie Tribe of Chippewa Indians","usgsCitation":"Brant, C., Alofs, K., Castiglione, C., Doka, S.E., Duncan, A.T., Fielder, D., Herbert, M., Liskauskus, A., Rutherford, E.S., Smith, J., Tingley, R.W., Treska, T., Turschak, T., Chu, C., and Esselman, P., 2023, Gap analysis: A proposed methodology to describe and map historical and contemporary populations and habitats, 30 p.","productDescription":"30 p.","ipdsId":"IP-159962","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":428430,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":428413,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.greatlakesciscoes.org/wp-content/uploads/2024/03/gap-analysis_methods.pdf"}],"country":"Canada, United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.43805183601008,\n 50.368037610701975\n ],\n [\n -93.43805183601008,\n 40.34002127489302\n ],\n [\n -75.0689112110101,\n 40.34002127489302\n ],\n [\n -75.0689112110101,\n 50.368037610701975\n ],\n [\n -93.43805183601008,\n 50.368037610701975\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n 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Resources","active":true,"usgs":false}],"preferred":false,"id":900151,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Herbert, Matthew","contributorId":275306,"corporation":false,"usgs":false,"family":"Herbert","given":"Matthew","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":900152,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Liskauskus, Arunas","contributorId":336501,"corporation":false,"usgs":false,"family":"Liskauskus","given":"Arunas","email":"","affiliations":[{"id":65742,"text":"Ontario Ministry of Northern Development, Mines, Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":900153,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rutherford, Edward S.","contributorId":175426,"corporation":false,"usgs":false,"family":"Rutherford","given":"Edward","email":"","middleInitial":"S.","affiliations":[{"id":12789,"text":"NOAA Great Lakes Environmental Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":900154,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Smith, Jason","contributorId":215444,"corporation":false,"usgs":false,"family":"Smith","given":"Jason","affiliations":[{"id":39249,"text":"Little Traverse Band of Odawa Indians","active":true,"usgs":false}],"preferred":false,"id":900155,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Tingley, Ralph W. III 0000-0002-1689-2133","orcid":"https://orcid.org/0000-0002-1689-2133","contributorId":189812,"corporation":false,"usgs":true,"family":"Tingley","given":"Ralph","suffix":"III","email":"","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":900156,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Treska, Ted","contributorId":141105,"corporation":false,"usgs":false,"family":"Treska","given":"Ted","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":900157,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Turschak, Ted","contributorId":336504,"corporation":false,"usgs":false,"family":"Turschak","given":"Ted","email":"","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":900158,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Chu, Cindy","contributorId":176496,"corporation":false,"usgs":false,"family":"Chu","given":"Cindy","email":"","affiliations":[],"preferred":false,"id":900159,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Esselman, Peter C. 0000-0002-0085-903X","orcid":"https://orcid.org/0000-0002-0085-903X","contributorId":204291,"corporation":false,"usgs":true,"family":"Esselman","given":"Peter C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":900160,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70255630,"text":"70255630 - 2023 - Lactation performance in polar bears is associated with fasting time and energetic state","interactions":[],"lastModifiedDate":"2024-06-27T11:49:41.460591","indexId":"70255630","displayToPublicDate":"2023-12-29T06:43:29","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2663,"text":"Marine Ecology Progress Series","active":true,"publicationSubtype":{"id":10}},"title":"Lactation performance in polar bears is associated with fasting time and energetic state","docAbstract":"

Females must continually make resource allocation decisions because of fitness trade-offs between self-maintenance and investment in current offspring, yet factors underpinning these decisions are unresolved. Polar bears Ursus maritimus face considerable allocation challenges when seasonal sea-ice melt precludes access to prey for several months, and females rely solely on energy stores to cover their own energetic needs and provision offspring. We tested how female polar bears regulate lactation during onshore fasting (i.e. capital breeding) and determined the consequences of moderated lactation for females and cubs. Overall, milk energy declined, and lactation was more likely to cease with longer time fasting. Lactation was partially mediated by maternal energetic state and depended on litter characteristics. Milk energy declined more sharply with fasting time (~2.6 times more strongly) in females with 2 offspring compared to those with 1. Females with cubs-of-the-year produced higher energy milk than those with yearlings, and their milk energy also increased more strongly with maternal energy density. Milk energy declines benefited females via reduced depletion of maternal energy reserves, but cub growth decreased. Altered lactation investment likely has consequences for both female survival and the fate of offspring, which could scale up to influence population dynamics. Given that Arctic warming means polar bears across much of their range will experience longer periods without access to primary prey, our results underscore how lactation will likely become increasingly compromised.

","language":"English","publisher":"InterResearch","doi":"10.3354/meps14382","usgsCitation":"Archer, L.C., Atkinson, S.N., Pagano, A.M., Penk, S.R., and Molnar, P.K., 2023, Lactation performance in polar bears is associated with fasting time and energetic state: Marine Ecology Progress Series, v. 720, p. 175-189, https://doi.org/10.3354/meps14382.","productDescription":"15 p.","startPage":"175","endPage":"189","ipdsId":"IP-148832","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":441350,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/meps14382","text":"Publisher Index Page"},{"id":430561,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"720","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Archer, Louise C. 0000-0002-1983-3825","orcid":"https://orcid.org/0000-0002-1983-3825","contributorId":312474,"corporation":false,"usgs":false,"family":"Archer","given":"Louise","email":"","middleInitial":"C.","affiliations":[{"id":67687,"text":"University of Toronto Scarborough","active":true,"usgs":false}],"preferred":false,"id":904991,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Atkinson, Stephen N.","contributorId":12365,"corporation":false,"usgs":false,"family":"Atkinson","given":"Stephen","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":904992,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pagano, Anthony M. 0000-0003-2176-0909 apagano@usgs.gov","orcid":"https://orcid.org/0000-0003-2176-0909","contributorId":3884,"corporation":false,"usgs":true,"family":"Pagano","given":"Anthony","email":"apagano@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":904993,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Penk, Stephanie R. 0000-0002-8027-4372","orcid":"https://orcid.org/0000-0002-8027-4372","contributorId":312472,"corporation":false,"usgs":false,"family":"Penk","given":"Stephanie","email":"","middleInitial":"R.","affiliations":[{"id":67687,"text":"University of Toronto Scarborough","active":true,"usgs":false}],"preferred":false,"id":904994,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Molnar, Peter K.","contributorId":339736,"corporation":false,"usgs":false,"family":"Molnar","given":"Peter","email":"","middleInitial":"K.","affiliations":[{"id":67687,"text":"University of Toronto Scarborough","active":true,"usgs":false}],"preferred":false,"id":904995,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70250981,"text":"70250981 - 2023 - Visitor use and activities detected using trail cameras at forest restoration sites","interactions":[],"lastModifiedDate":"2024-01-17T12:42:49.676866","indexId":"70250981","displayToPublicDate":"2023-12-29T06:41:35","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1462,"text":"Ecological Restoration","active":true,"publicationSubtype":{"id":10}},"title":"Visitor use and activities detected using trail cameras at forest restoration sites","docAbstract":"

We used trail cameras to monitor human visits and activities at two sites in northeast Indiana being restored to bottomland hardwood forests. These sites, managed as nature preserves, are close to cities, where trails and parking lots have been added for ease of access. In this study, trail cameras were successfully used to capture visitation rates and activity types. The two sites had median visitor use rates of 1 and 13 visitors per day. Across both sites, “parking lot use only” (62%), hikers (30.2%), and bicyclists (5%) accounted for more than 97% of site visits. Overall, most weekday visitor-time occurred during daylight hours, peaking at lunch and evening. Mean total number of daily visitors was higher during weekends; however, total daily visitor-time did not vary between days of the week. Michaelis-Menten rarefaction models of sampling efficiency across the study’s four camera stations suggest sampling duration of 27 to 55 days to accurately estimate mean daily visitor counts and 3 to 40 days to detect half the maximal numbers of observed activities. Study estimates of visitation provide land managers with information for accommodating visitor use activities on the restored sites and offer inputs for cultural ecosystem services assessments and associated economic analyses.

","language":"English","publisher":"University of Wisconsin Press","doi":"10.3368/er.41.4.199","usgsCitation":"Albers, J.L., Wildhaber, M.L., Green, N., Struckhoff, M., and Hooper, M.J., 2023, Visitor use and activities detected using trail cameras at forest restoration sites: Ecological Restoration, v. 41, no. 4, p. 199-212, https://doi.org/10.3368/er.41.4.199.","productDescription":"14 p.","startPage":"199","endPage":"212","ipdsId":"IP-144951","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":441352,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3368/er.41.4.199","text":"Publisher Index Page"},{"id":424484,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Albers, Janice L. 0000-0002-6312-8269 jalbers@usgs.gov","orcid":"https://orcid.org/0000-0002-6312-8269","contributorId":3972,"corporation":false,"usgs":true,"family":"Albers","given":"Janice","email":"jalbers@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":892642,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":892643,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Green, Nicholas S.","contributorId":301918,"corporation":false,"usgs":false,"family":"Green","given":"Nicholas S.","affiliations":[{"id":65362,"text":"Kennesaw State University","active":true,"usgs":false}],"preferred":false,"id":892644,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Struckhoff, Matthew 0000-0002-4911-9956","orcid":"https://orcid.org/0000-0002-4911-9956","contributorId":201512,"corporation":false,"usgs":true,"family":"Struckhoff","given":"Matthew","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":892645,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hooper, Michael J. 0000-0002-4161-8961 mhooper@usgs.gov","orcid":"https://orcid.org/0000-0002-4161-8961","contributorId":3251,"corporation":false,"usgs":true,"family":"Hooper","given":"Michael","email":"mhooper@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":892646,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70250702,"text":"sir20235117 - 2023 - Prediction of the probability of elevated nitrate concentrations at groundwater depths used for drinking-water supply in the Puget Sound basin, Washington, 2004–19","interactions":[],"lastModifiedDate":"2026-03-13T15:36:53.605706","indexId":"sir20235117","displayToPublicDate":"2023-12-28T11:33:39","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5117","displayTitle":"Prediction of the Probability of Elevated Nitrate Concentrations at Groundwater Depths Used for Drinking-Water Supply in the Puget Sound Basin, Washington, 2004–19","title":"Prediction of the probability of elevated nitrate concentrations at groundwater depths used for drinking-water supply in the Puget Sound basin, Washington, 2004–19","docAbstract":"

The Puget Sound basin encompasses the 13,700-square-mile area that drains to the Puget Sound and the adjacent marine waters of Washington State. Well more than 4 million people live within the basin, with numbers continuing to increase, who rely on the basin’s natural resources including groundwater. The Puget Sound Partnership was created by a Washington State statute to implement a science-based recovery of the Puget Sound to help address impacts to these resources. As part of the recovery, the partnership developed the Puget Sound Vital Signs as measures of ecosystem health that guide the assessment of progress toward Puget Sound recovery goals. The Puget Sound Partnership Leadership Council adopted a Drinking Water Vital Sign associated with human health and quality of life, recognizing certain indicators as integral to the sustainability of Puget Sound recovery efforts. One such Vital Sign indicator was the vulnerability of groundwater throughout the aquifers of the Puget Sound basin to elevated nitrate concentrations as defined by the probability of exceeding 2 milligrams/liter (mg/L) at a specific location and well depth. The U.S. Geological Survey (USGS) led the effort to characterize groundwater vulnerability. For this study, groundwater vulnerability refers to a probability with which a contaminant applied at or near the land surface can migrate to the aquifer of interest for a given set of land-use practices. Nitrate concentration data were selected for evaluation because elevated nitrate concentrations are typically caused by anthropogenic activities and have been associated with deleterious impacts on human health.

To identify groundwater vulnerability to elevated nitrate concentrations, logistic regression was used to relate anthropogenic (human associated) and natural variables to the occurrence of elevated nitrate concentrations in untreated groundwater from large public water supply system wells found within the Washington State Department of Health Sentry database. Variables that were analyzed included well depth, soil hydraulic conductivity, precipitation, population density, fertilizer application amounts, and land-use types. Statistically significant models that predicted the probabilities of groundwater nitrate concentrations greater than 2 mg/L based on the predictor variables were created for the time periods 2000–04, 2005–09, 2010–14, and 2015–19. For all time periods, well depth and a measure of the abundance of urban and agricultural land over or near the well consistently helped explain the vulnerability of the well to elevated nitrate concentrations defined as a probability of exceeding 2 mg/L of nitrate. Precipitation and (or) soil hydraulic conductivity were also important predictor variables in the models.

The models for each time period were used to create maps of groundwater vulnerability at 150- and 300-foot depths throughout the Puget Sound basin. As expected, the most vulnerable locations were associated with shallower well depths and increased agriculture and urban land cover. Across all four time periods, groundwater vulnerability throughout the Puget Sound was low, with probabilities of exceeding 2 mg/L concentrations of nitrate at depths at 150 and 300 feet typically less than 50 percent. Results also found a slight decrease in probabilities of elevated nitrate concentrations throughout the basin over time. More specifically, additional statistical tests found that groundwater with probabilities of less than about 60 percent declined from 2000 to 2019 and represented more than 75 percent of the modeled Puget Sound basin aquifer. Wells with greater than 60 percent probability increased over the same time period but represented only about 25 percent of the aquifer. The maps and statistical analysis presented in the study provide valuable and informative evaluation of the vulnerability of groundwater in the Puget Sound basin to elevated nitrate concentrations. The probability maps do not represent measured nitrate concentrations in groundwater, but rather they present the probability that nitrate concentrations exceed 2 mg/L. The models and predictions from this study are a viable indicator for the Puget Sound Partnership’s Healthy Human Population—Drinking Water Vital Sign. The logistic regression modeling approach presented here benefits water managers by allowing them to assess temporal trends in a range of probabilities, explore vulnerability changes as new regional land cover and anthropogenic data are generated, and distinguish vulnerabilities at different depths within the aquifer.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235117","collaboration":"Prepared in cooperation with Puget Sound Partnership","usgsCitation":"Black, R.W., Wright, E.E., Bright, V.A.L., and Headman, A.O., 2023, Prediction of the probability of elevated nitrate concentrations at groundwater depths used for drinking-water supply in the Puget Sound basin, Washington, 2004–19: U.S. Geological Survey Scientific Investigations Report 2023–5117, 40 p., https://doi.org/10.3133/sir20235117.","productDescription":"Report: vi, 40 p.; Data Release","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-135130","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":424530,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5117/images"},{"id":424531,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5117/sir20235117.XML"},{"id":423904,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5117/covrthb.jpg"},{"id":423905,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5117/sir20235117.pdf","text":"Report","size":"16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5117"},{"id":501157,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115891.htm","linkFileType":{"id":5,"text":"html"}},{"id":423906,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TOWGYM","text":"USGS Data Release","description":"Wright, E.E., Bright, V.A.L., Black, R.W., and Headman, A.O., 2022, Index of vulnerability for elevated nitrates in groundwater in the Puget Sound Basin, Washington, 2000–2019: U.S. Geological Survey data release, https://doi.org/10.5066/P9TOWGYM.","linkHelpText":"Index of vulnerability for elevated nitrates in groundwater in the Puget Sound Basin, Washington, 2000–2019"},{"id":424529,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235117/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5117"}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.38747179984844,\n 49.222164372548065\n ],\n [\n -124.38747179984844,\n 46.31382574682385\n ],\n [\n -120.38844836234833,\n 46.31382574682385\n ],\n [\n -120.38844836234833,\n 49.222164372548065\n ],\n [\n -124.38747179984844,\n 49.222164372548065\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, 
Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402

","tableOfContents":"","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2023-12-28","noUsgsAuthors":false,"publicationDate":"2023-12-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Black, Robert W. 0000-0002-4748-8213 rwblack@usgs.gov","orcid":"https://orcid.org/0000-0002-4748-8213","contributorId":1820,"corporation":false,"usgs":true,"family":"Black","given":"Robert","email":"rwblack@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891034,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Elise E. 0000-0001-7460-9730","orcid":"https://orcid.org/0000-0001-7460-9730","contributorId":302876,"corporation":false,"usgs":true,"family":"Wright","given":"Elise","email":"","middleInitial":"E.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891035,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bright, Valerie A.L. 0000-0002-7627-8004","orcid":"https://orcid.org/0000-0002-7627-8004","contributorId":294970,"corporation":false,"usgs":true,"family":"Bright","given":"Valerie","email":"","middleInitial":"A.L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891036,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Headman, Alexander O. 0000-0003-0034-3970 aheadman@usgs.gov","orcid":"https://orcid.org/0000-0003-0034-3970","contributorId":196986,"corporation":false,"usgs":true,"family":"Headman","given":"Alexander","email":"aheadman@usgs.gov","middleInitial":"O.","affiliations":[],"preferred":true,"id":891037,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70250734,"text":"70250734 - 2023 - Water, water everywhere, but every drop unique: Emerging challenges in the science to understand the role of contaminants in management of drinking water supplies","interactions":[],"lastModifiedDate":"2024-05-30T15:38:49.77242","indexId":"70250734","displayToPublicDate":"2023-12-28T06:32:43","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16135,"text":"GeoHealth","active":true,"publicationSubtype":{"id":10}},"title":"Water, water everywhere, but every drop unique: Emerging challenges in the science to understand the role of contaminants in management of drinking water supplies","docAbstract":"

The protection and management of water resources continues to be challenged by multiple and ongoing factors such as shifts in demographic, social, economic, and public health requirements. Physical limitations placed on access to potable supplies include natural and human-caused factors such as aquifer depletion, aging infrastructure, saltwater intrusion, floods, and drought. These factors, although varying in magnitude, spatial extent, and timing, can exacerbate the potential for contaminants of concern (CECs) to be present in sources of drinking water, infrastructure, premise plumbing and associated tap water. This monograph examines how current and emerging scientific efforts and technologies increase our understanding of the range of CECs and drinking water issues facing current and future populations. It is not intended to be read in one sitting, but is instead a starting point for scientists wanting to learn more about the issues surrounding CECs. This text discusses the topical evolution CECs over time (Section 1), improvements in measuring chemical and microbial CECs, through both analysis of concentration and toxicity (Section 2) and modeling CEC exposure and fate (Section 3), forms of treatment effective at removing chemical and microbial CECs (Section 4), and potential for human health impacts from exposure to CECs (Section 5). The paper concludes with how changes to water quantity, both scarcity and surpluses, could affect water quality (Section 6). Taken together, these sections document the past 25 years of CEC research and the regulatory response to these contaminants, the current work to identify and monitor CECs and mitigate exposure, and the challenges facing the future.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022GH000716","usgsCitation":"Glassmeyer, S., Burns, E., Focazio, M.J., Furlong, E., Gribble, M.O., Jahne, M., Keely, S., Kenicutt, A., Kolpin, D., Medlock Kakaley, E., and Pfaller, S., 2023, Water, water everywhere, but every drop unique: Emerging challenges in the science to understand the role of contaminants in management of drinking water supplies: GeoHealth, v. 7, no. 12, e2022GH000716, 76 p., https://doi.org/10.1029/2022GH000716.","productDescription":"e2022GH000716, 76 p.","ipdsId":"IP-134856","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":441358,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022gh000716","text":"Publisher Index Page"},{"id":424050,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Glassmeyer, S.T.","contributorId":302031,"corporation":false,"usgs":false,"family":"Glassmeyer","given":"S.T.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":891174,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, E.E.","contributorId":332863,"corporation":false,"usgs":false,"family":"Burns","given":"E.E.","email":"","affiliations":[{"id":79666,"text":"Personal Care Products Council","active":true,"usgs":false}],"preferred":false,"id":891175,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Focazio, Michael J. 0000-0003-0967-5576 mfocazio@usgs.gov","orcid":"https://orcid.org/0000-0003-0967-5576","contributorId":1276,"corporation":false,"usgs":true,"family":"Focazio","given":"Michael","email":"mfocazio@usgs.gov","middleInitial":"J.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":891176,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Furlong, Edward 0000-0002-7305-4603","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":213730,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":891177,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gribble, Matthew O.","contributorId":255548,"corporation":false,"usgs":false,"family":"Gribble","given":"Matthew","email":"","middleInitial":"O.","affiliations":[{"id":40432,"text":"Emory University","active":true,"usgs":false}],"preferred":false,"id":891178,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jahne, M.A.","contributorId":332865,"corporation":false,"usgs":false,"family":"Jahne","given":"M.A.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":891179,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Keely, S.P.","contributorId":332866,"corporation":false,"usgs":false,"family":"Keely","given":"S.P.","email":"","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":891180,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kenicutt, A.R.","contributorId":332867,"corporation":false,"usgs":false,"family":"Kenicutt","given":"A.R.","email":"","affiliations":[{"id":79668,"text":"York College of PA","active":true,"usgs":false}],"preferred":false,"id":891181,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891182,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Medlock Kakaley, E.K.","contributorId":332868,"corporation":false,"usgs":false,"family":"Medlock Kakaley","given":"E.K.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":891183,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Pfaller, S.L.","contributorId":332869,"corporation":false,"usgs":false,"family":"Pfaller","given":"S.L.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":891184,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70256511,"text":"70256511 - 2023 - Ectoparasitism and energy infrastructure limit survival of preadult Golden Eagles in the Southern Great Plains","interactions":[],"lastModifiedDate":"2024-08-12T16:23:18.994532","indexId":"70256511","displayToPublicDate":"2023-12-27T11:09:35","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"title":"Ectoparasitism and energy infrastructure limit survival of preadult Golden Eagles in the Southern Great Plains","docAbstract":"

Much of the US Southern Great Plains (SGP) continues to undergo intensive energy development that could affect the region's Golden Eagles (Aquila chrysaetos), yet the species' population status there is unknown. During 2011–2020, we used satellite telemetry to assess annual survival rates and causes of mortality among 40 preadult (<3 yr of age) Golden Eagles in the SGP; 29 were monitored beginning at the late nestling stage and 11 immigrated into the SGP from western regions. For comparison we monitored 15 preadult Golden Eagles from nests in the Central Great Plains (CGP), where energy development was less extensive. We estimated survival rates by using a multi-state model in a Bayesian framework that accounted for probabilities of causes of death. Mean annual survival in the SGP during the preadult period was 0.060, versus 0.512 in the CGP and ∼0.7–0.9 reported elsewhere in the coterminous western USA. Mexican chicken bugs (Haematosiphon inodorus) were implicated in deaths of at least seven Golden Eagles during the ∼2-wk late nestling stage and in two deaths <3 mo after fledging. Energy infrastructure especially electrocutions accounted for 12 (57.1%) of 21 deaths of post-fledged preadults. Seven of 11 immigrant eagles died. Overall, probabilities of death of a Golden Eagle during the preadult period in the SGP due to Mexican chicken bugs and to electrocution were both 0.345. We estimated that the SGP population may be declining 9% annually due to poor recruitment; mitigation of underlying factors should be a priority for managing Golden Eagles in the western USA.

","language":"English","publisher":"Raptor Research Foundation","doi":"10.3356/JRR-21-72","usgsCitation":"Murphy, R.K., Millsap, B.A., Stahlecker, D.W., Boal, C.W., Smith, B.W., Mullican, S.D., and Borgman, C.C., 2023, Ectoparasitism and energy infrastructure limit survival of preadult Golden Eagles in the Southern Great Plains: Journal of Raptor Research, v. 57, no. 4, p. 505-521, https://doi.org/10.3356/JRR-21-72.","productDescription":"17 p.","startPage":"505","endPage":"521","ipdsId":"IP-134885","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":441361,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3356/jrr-21-72","text":"Publisher Index Page"},{"id":432490,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Kansas, New Mexico, Oklahoma, Texas","otherGeospatial":"Southern Great Plains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.72793700699765,\n 38.81212221224669\n ],\n [\n -105.72793700699765,\n 30.814517878279688\n ],\n [\n -100.1803240398034,\n 30.814517878279688\n ],\n [\n -100.1803240398034,\n 38.81212221224669\n ],\n [\n -105.72793700699765,\n 38.81212221224669\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"57","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Robert K.","contributorId":67643,"corporation":false,"usgs":false,"family":"Murphy","given":"Robert","email":"","middleInitial":"K.","affiliations":[{"id":56253,"text":"Eagle Environmental, Inc","active":true,"usgs":false}],"preferred":false,"id":907745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Millsap, Brian A.","contributorId":75841,"corporation":false,"usgs":true,"family":"Millsap","given":"Brian","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":907746,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stahlecker, Dale W.","contributorId":305748,"corporation":false,"usgs":false,"family":"Stahlecker","given":"Dale","email":"","middleInitial":"W.","affiliations":[{"id":66288,"text":"Eagle Environmental Inc","active":true,"usgs":false}],"preferred":false,"id":907747,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":907748,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Brian W.","contributorId":199748,"corporation":false,"usgs":false,"family":"Smith","given":"Brian","email":"","middleInitial":"W.","affiliations":[{"id":17821,"text":"U.S. Fish and Wildlife Service, Division of Migratory Birds","active":true,"usgs":false}],"preferred":false,"id":907749,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mullican, Shea D.","contributorId":340972,"corporation":false,"usgs":false,"family":"Mullican","given":"Shea","email":"","middleInitial":"D.","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":907750,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Borgman, Corrie C.","contributorId":340973,"corporation":false,"usgs":false,"family":"Borgman","given":"Corrie","email":"","middleInitial":"C.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":907751,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70257327,"text":"70257327 - 2023 - Declining American Goshawk (Accipiter atricapillus) nest site habitat suitability in a timber production landscape: Effects of abiotic, biotic, and forest management factors","interactions":[],"lastModifiedDate":"2024-08-28T16:09:16.379927","indexId":"70257327","displayToPublicDate":"2023-12-27T10:52:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Declining American Goshawk (Accipiter atricapillus) nest site habitat suitability in a timber production landscape: Effects of abiotic, biotic, and forest management factors","title":"Declining American Goshawk (Accipiter atricapillus) nest site habitat suitability in a timber production landscape: Effects of abiotic, biotic, and forest management factors","docAbstract":"

Conservation of the American Goshawk (Accipiter atricapillus; hereafter goshawk) has been contentious in relation to forest management. Higher quality goshawk nesting habitat is generally considered to consist of contiguous tracts of mature forest, due to goshawks' large home ranges, territoriality, and food requirements. The large trees of mature forest have the greatest economic value to timber companies. We used long-term (1965–2019) data from 281 goshawk nest site locations in the Black Hills National Forest (BHNF), South Dakota, and Wyoming, USA, to evaluate (1) abiotic and biotic factors associated with goshawk nest site habitat suitability (hereafter habitat suitability); (2) changes in habitat suitability over time; and (3) the effect of anthropogenic activities and natural disturbances on habitat suitability. We evaluated forest attributes across five spatial scales relevant to goshawks, used information-theoretic methods to rank and select models, and assessed the predictive capability of the best-approximating models using the concordance statistic. The best-approximating model had excellent predictive capability (concordance = 0.821). Forest attributes at the 12-ha scale were a better predictor of goshawk habitat suitability than covariates evaluated at the point or >12-ha scales, indicating the importance of managing goshawk habitat beyond the nest tree, but within the nest stand. Goshawk habitat suitability was positively related to mean percent canopy cover and median canopy base height, and negatively related to variability in canopy base height within 12 ha of the location. As mean percent canopy cover within 12 ha of a location increased, goshawk habitat suitability increased more slowly in burned compared to unburned areas. Commercial thinning treatments were more likely to occur in closed canopy forest that already had a higher likelihood of goshawk nesting, and we documented a positive relationship between habitat suitability and the interaction of canopy cover with commercial thinning. Goshawk habitat suitability was negatively related to slope and distance to drainage bottoms, and positively related to distance to ridges, which may be related to microclimatic factors. Our results indicate goshawk habitat suitability decreased across the BHNF over the past three decades and much high-quality nesting habitat was lost during this period due to a combination of unsustainable timber harvest and natural disturbances. Minimizing forest management activities that decrease canopy cover and canopy base height, and increase variability in canopy base height in areas of high- and medium-quality goshawk habitat are likely to slow the loss of higher-quality habitat and allow development of future nesting habitat. In addition to informing management, this study demonstrates the value of using existing long-term legacy datasets in conjunction with time series of remotely sensed habitat attributes to evaluate changes in habitat suitability for raptors in heavily managed landscapes with extensive natural disturbances.

","language":"English","publisher":"The Raptor Research Foundation, Inc.","doi":"10.3356/JRR-22-116","usgsCitation":"Bruggeman, J., Kennedy, P., Andersen, D.E., Deisch, S., and Dowd Stukel, E., 2023, Declining American Goshawk (Accipiter atricapillus) nest site habitat suitability in a timber production landscape: Effects of abiotic, biotic, and forest management factors: Journal of Raptor Research, v. 57, no. 4, p. 595-616, https://doi.org/10.3356/JRR-22-116.","productDescription":"22 p.","startPage":"595","endPage":"616","ipdsId":"IP-131063","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":433252,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota, Wyoming","otherGeospatial":"Black Hills National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -103.43693855745735,\n 43.356145430824284\n ],\n [\n -103.2453110990768,\n 43.65127660509563\n ],\n [\n -103.28799233163049,\n 44.184936790000336\n ],\n [\n -103.5682101102287,\n 44.47034928011246\n ],\n [\n -104.02419632305251,\n 44.568539246903015\n ],\n [\n -104.35190822302025,\n 44.83186690058787\n ],\n [\n -104.60789383129,\n 44.58876639683757\n ],\n [\n -104.61727412202488,\n 44.439874040779614\n ],\n [\n -104.32767875182326,\n 44.24995062651524\n ],\n [\n -104.05715060176854,\n 44.1638696947999\n ],\n [\n -104.03414949657513,\n 43.9000787982707\n ],\n [\n -103.98071548762339,\n 43.5157370272095\n ],\n [\n -103.75626279313133,\n 43.3596577295468\n ],\n [\n -103.43693855745735,\n 43.356145430824284\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"57","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bruggeman, Jason E.","contributorId":342294,"corporation":false,"usgs":false,"family":"Bruggeman","given":"Jason E.","affiliations":[{"id":81853,"text":"Beartooth Wildlife Research LLC","active":true,"usgs":false}],"preferred":false,"id":909974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennedy, Patricia L.","contributorId":342295,"corporation":false,"usgs":false,"family":"Kennedy","given":"Patricia L.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":909975,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Andersen, David E. 0000-0001-9535-3404 dea@usgs.gov","orcid":"https://orcid.org/0000-0001-9535-3404","contributorId":199408,"corporation":false,"usgs":true,"family":"Andersen","given":"David","email":"dea@usgs.gov","middleInitial":"E.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":909973,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Deisch, Shelly","contributorId":342296,"corporation":false,"usgs":false,"family":"Deisch","given":"Shelly","email":"","affiliations":[{"id":56698,"text":"South Dakota Department of Game, Fish, and Parks","active":true,"usgs":false}],"preferred":false,"id":909976,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dowd Stukel, Eileen","contributorId":342297,"corporation":false,"usgs":false,"family":"Dowd Stukel","given":"Eileen","email":"","affiliations":[{"id":56698,"text":"South Dakota Department of Game, Fish, and Parks","active":true,"usgs":false}],"preferred":false,"id":909977,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70243946,"text":"sir20235051 - 2023 - Automated construction of Streamflow-Routing networks for MODFLOW—Application in the Mississippi Embayment region","interactions":[],"lastModifiedDate":"2023-12-23T14:28:31.061588","indexId":"sir20235051","displayToPublicDate":"2023-12-22T15:44:25","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5051","displayTitle":"Automated Construction of Streamflow-Routing Networks for MODFLOW—Application in the Mississippi Embayment Region","title":"Automated construction of Streamflow-Routing networks for MODFLOW—Application in the Mississippi Embayment region","docAbstract":"

In humid regions with dense stream networks, surface water exerts a fundamental control on the water levels and flow directions of shallow groundwater. Understanding interactions between groundwater and surface water is critical for managing groundwater resources and groundwater-dependent ecosystems. Representing streams in groundwater models has historically been arduous and error prone. In recent years, however, all the information needed to numerically describe stream boundary conditions for a model area has become readily available online, as have robust open-source software tools for translating that information to a model grid. The SFRmaker Python package leverages geospatial capabilities in the scientific Python ecosystem to robustly automate the production of input to the Streamflow-Routing (SFR) Package of MODFLOW from the National Hydrography Dataset Plus or other hydrography data. This report documents an application of SFRmaker to automate production of SFR Package input for groundwater models within the Mississippi Embayment Regional Aquifer Study area. SFR Package input was developed in three steps: (1) preprocessing to develop a single set of grid-independent flowlines from National Hydrography Dataset Plus version 2 data; (2) setting up the SFR package from the preprocessed flowlines, and (3) correcting streambed top elevations after an initial model run. Separating the hydrography preprocessing from the construction of SFR Package input was advantageous in that it minimized the need to repeat computationally expensive geoprocessing (thereby speeding model construction) and also allowed for the curation of a single set of grid-independent SFR input data that can be used for any MODFLOW model within the study area.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235051","usgsCitation":"Leaf, A.T., 2023, Automated construction of Streamflow-Routing networks for MODFLOW—Application in the Mississippi Embayment region: U.S. Geological Survey Scientific Investigations Report 2023–5051, 28 p., https://doi.org/10.3133/sir20235051.","productDescription":"Report: vii, 28 p.; 4 Data Releases; Dataset","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-105069","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":417495,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P971LPOB","text":"USGS data release","linkHelpText":"MODFLOW–6 models of the Mississippi embayment (MERAS 3) and Mississippi Delta"},{"id":417456,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CXDIPL","text":"USGS data release","linkHelpText":"Datasets used to map the potentiometric surface, Mississippi River Valley alluvial aquifer, spring 2020"},{"id":423683,"rank":12,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235100","text":"SIR 2023–5100","linkHelpText":"—Simulating groundwater flow in the Mississippi Alluvial Plain with a focus on the Mississippi Delta"},{"id":417488,"rank":8,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5051/images"},{"id":417481,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5051/sir20235051.XML","text":"Report","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2023–5051"},{"id":417457,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":423682,"rank":11,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235080","text":"SIR 2023–5080","linkHelpText":"—Updated estimates of water budget components for the Mississippi embayment region using a Soil-Water-Balance model, 2000–2020"},{"id":417455,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P84B24","text":"USGS data release","linkHelpText":"National-scale grid to support regional groundwater availability studies and a national hydrogeologic database"},{"id":423152,"rank":10,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235051/full"},{"id":417450,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5051/coverthb2.jpg"},{"id":417454,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WQPRFB","text":"USGS data release","linkHelpText":"Waterborne resistivity inverted models, Mississippi Alluvial Plain, 2016–2018"},{"id":417451,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5051/sir20235051.pdf","text":"Report","size":"46.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5051"}],"country":"United States","otherGeospatial":"Mississippi Embayment Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.88995719655937,\n 28.910338985045087\n ],\n [\n -85.96905875905937,\n 28.910338985045087\n ],\n [\n -85.96905875905937,\n 37.74314338343309\n ],\n [\n -94.88995719655937,\n 37.74314338343309\n ],\n [\n -94.88995719655937,\n 28.910338985045087\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-12-22","noUsgsAuthors":false,"publicationDate":"2023-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Leaf, Andrew T. 0000-0001-8784-4924 aleaf@usgs.gov","orcid":"https://orcid.org/0000-0001-8784-4924","contributorId":5156,"corporation":false,"usgs":true,"family":"Leaf","given":"Andrew","email":"aleaf@usgs.gov","middleInitial":"T.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":873850,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70250336,"text":"sir20235100 - 2023 - Simulating groundwater flow in the Mississippi Alluvial Plain with a focus on the Mississippi Delta","interactions":[],"lastModifiedDate":"2026-03-13T15:20:23.277736","indexId":"sir20235100","displayToPublicDate":"2023-12-22T15:26:20","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5100","displayTitle":"Simulating Groundwater Flow in the Mississippi Alluvial Plain with a Focus on the Mississippi Delta","title":"Simulating groundwater flow in the Mississippi Alluvial Plain with a focus on the Mississippi Delta","docAbstract":"

The Mississippi Alluvial Plain has become one of the most important agricultural regions in the United States but relies heavily on groundwater for irrigation. On average, more than 12 billion gallons are withdrawn daily from the Mississippi River Valley alluvial aquifer. Declining groundwater levels, especially in the Delta region of northwest Mississippi and the Cache and Grand Prairie regions of eastern Arkansas, have led to concerns about future sustainability. The U.S. Geological Survey Mississippi Alluvial Plain Project is focused on quantifying the groundwater system in the alluvial plain and the response of groundwater resources to future development. A key objective of the project is to provide updated groundwater flow models supported by extensive data collection and analyses. MODFLOW 6, PEST++, and several open-source python packages were used to develop a simplified, faster running version of the Mississippi Embayment Regional Aquifer Study model that can provide boundary conditions for local inset models, including the Mississippi Delta model described in this report. An automated workflow was used for model construction, history matching, and development of baseline future climate scenarios. The models incorporate information from a Soil-Water-Balance code simulation of the terrestrial water balance, metering-based estimates of water use from thousands of wells, measured and estimated streamflow and stages, and the largest airborne electromagnetic survey flown to date in the United States. Baseline scenarios for the Mississippi Delta under potential future climates were constructed using recharge, surface runoff and irrigation pumping forcings from a future version of the Soil-Water-Balance model, driven by downscaled temperature and precipitation output from 10 general circulation model simulations, including high and moderate carbon emissions pathways.

Results indicate a complex water balance that varies in time and space in terms of the terrestrial recharge, stream leakage, and regional groundwater flow components, which are affected by seasonal forcings, human activity, and alluvial geomorphology. The general circulation model outputs indicate a continued rise in average temperatures but no clear precipitation trend. Increased crop water demand is anticipated from the higher temperatures, resulting in increased irrigation withdrawals to sustain current levels of irrigated agriculture. Simulated drawdowns in groundwater levels at the mid-21st century vary greatly. Under moderate or wet climate scenarios, and in parts of the aquifer that are well connected to surface water, little to no additional drawdown is anticipated. Under dry or warm scenarios, drawdowns of as much as 10 meters or more are possible in parts of the aquifer that are relatively disconnected from surface water. Under dry or warm scenarios, the portion of the Delta with greater than 60 feet of saturated thickness could be reduced from near 100 percent currently (2018) to 80–90 percent by mid-century. Future simulations with the model could include alternative management scenarios to identify options for improving groundwater sustainability. The automated model construction workflows are designed to facilitate regular updating, making this a “living” framework that the Mississippi Department of Environmental Quality and other stakeholders can use for adaptive management going forward.

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Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-12-22","noUsgsAuthors":false,"publicationDate":"2023-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Leaf, Andrew T. 0000-0001-8784-4924 aleaf@usgs.gov","orcid":"https://orcid.org/0000-0001-8784-4924","contributorId":5156,"corporation":false,"usgs":true,"family":"Leaf","given":"Andrew","email":"aleaf@usgs.gov","middleInitial":"T.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":889494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duncan, Leslie L. 0000-0002-5938-5721","orcid":"https://orcid.org/0000-0002-5938-5721","contributorId":204004,"corporation":false,"usgs":true,"family":"Duncan","given":"Leslie","email":"","middleInitial":"L.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":889495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haugh, Connor J. 0000-0002-5204-8271","orcid":"https://orcid.org/0000-0002-5204-8271","contributorId":219945,"corporation":false,"usgs":true,"family":"Haugh","given":"Connor J.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":889496,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunt, Randall J. 0000-0001-6465-9304","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":16118,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":889497,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rigby, James R. 0000-0002-5611-6307","orcid":"https://orcid.org/0000-0002-5611-6307","contributorId":260894,"corporation":false,"usgs":true,"family":"Rigby","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":889498,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70250314,"text":"sir20235080 - 2023 - Updated estimates of water budget components for the Mississippi Embayment Region using a soil-water-balance model, 2000–2020","interactions":[],"lastModifiedDate":"2026-03-12T20:54:31.140336","indexId":"sir20235080","displayToPublicDate":"2023-12-22T15:17:09","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5080","displayTitle":"Updated Estimates of Water Budget Components for the Mississippi Embayment Region Using a Soil-Water-Balance Model, 2000–2020","title":"Updated estimates of water budget components for the Mississippi Embayment Region using a soil-water-balance model, 2000–2020","docAbstract":"

A Soil-Water-Balance (SWB) model for the Mississippi embayment region in Arkansas, Tennessee, Mississippi, and Louisiana was constructed and calibrated to gain insight into potential recharge patterns for the Mississippi River Valley alluvial aquifer, which has had substantial drawdown under intense pumping stress over the last several decades. An analysis of the net infiltration term from the SWB model combined with newly gathered airborne electromagnetic geophysical data on the surficial sediments in a calibrated modular three-dimensional finite-difference (MODFLOW 6) groundwater flow model of one area in the alluvial plain found that the distribution of net infiltration was significantly different from the recharge that gets to the water table through the complicated silt and clay stratigraphy of the unsaturated zone. The net infiltration of water through the rooting zone as simulated by SWB ranges from 5.7 to 12.3 inches per year in the alluvial plain part of the model domain, and is fairly evenly distributed within local areas. Recharge to the underlying aquifer is less and is much more focused in particular zones where the connectivity through the upper layers of the unsaturated zone above the water table is greater, indicating possible horizontal flow and perched water table conditions in the unsaturated zone. Runoff and net infiltration together account for 32 percent of the incoming precipitation overall and somewhat higher percentages in the alluvial plain area on an annual basis. These terms are much higher in the fall and winter than in the summer. Actual evapotranspiration accounts for between 62 and 72 percent on average of the annual precipitation but dominates all other terms in the summer months. Without irrigation, summertime net infiltration and runoff would be near zero in the crop-dominated alluvial plain area. The SWB model reproduced reported irrigation rates for corn, soybeans, rice, and cotton on an annual basis fairly well. The SWB model for the Mississippi embayment region was calibrated using more than 15,000 observations representing four parts of the calculated water budget: actual evapotranspiration, surface runoff, net infiltration, and irrigation. Using a Monte Carlo approach to determine the uncertainty in the model results stemming from the uncertainty in the model parameters used in the calibration, the uncertainty in the annual actual evapotranspiration values was around 5 percent, whereas the uncertainty in the irrigation, net infiltration, and runoff was around 20 percent.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235080","programNote":"Water Availability and Use Science Program","usgsCitation":"Nielsen, M.G., and Westenbroek, S.M., 2023, Updated estimates of water budget components for the Mississippi embayment region using a Soil-Water-Balance model, 2000–2020: U.S. Geological Survey Scientific Investigations Report 2023–5080, 58 p., https://doi.org/10.3133/sir20235080","productDescription":"Report: vii, 58 p.; Data Release; Dataset","numberOfPages":"72","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-132665","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501044,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115885.htm","linkFileType":{"id":5,"text":"html"}},{"id":423679,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235051","text":"SIR 2023–5051","linkHelpText":"— Automated construction of Streamflow-Routing networks for MODFLOW—Application in the Mississippi Embayment region"},{"id":423678,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235100","text":"SIR 2023–5100","linkHelpText":"—Simulating groundwater flow in the Mississippi Alluvial Plain with a focus on the Mississippi Delta"},{"id":423159,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235080/full"},{"id":423153,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5080/coverthb.jpg"},{"id":423155,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5080/sir20235080.XML"},{"id":423154,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5080/sir20235080.pdf","text":"Report","size":"14.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5080"},{"id":423156,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5080/images/"},{"id":423158,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":423157,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97KK17G","text":"USGS data release","linkHelpText":"Model archive and output files for net infiltration, runoff, and irrigation water use for the Mississippi Embayment Regional Aquifer System, 2000 to 2020, simulated with the Soil-Water-Balance model"}],"country":"United States","otherGeospatial":"Mississippi Embayment Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.12089542031869,\n 28.886284478842654\n ],\n [\n -86.65019229531852,\n 28.886284478842654\n ],\n [\n -86.65019229531852,\n 37.89501192204163\n ],\n [\n -94.12089542031869,\n 37.89501192204163\n ],\n [\n -94.12089542031869,\n 28.886284478842654\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-12-22","noUsgsAuthors":false,"publicationDate":"2023-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Nielsen, Martha G. 0000-0003-3038-9400 mnielsen@usgs.gov","orcid":"https://orcid.org/0000-0003-3038-9400","contributorId":4169,"corporation":false,"usgs":true,"family":"Nielsen","given":"Martha","email":"mnielsen@usgs.gov","middleInitial":"G.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":889419,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Westenbroek, Stephen, M. 0000-0002-6284-8643","orcid":"https://orcid.org/0000-0002-6284-8643","contributorId":206429,"corporation":false,"usgs":true,"family":"Westenbroek","given":"Stephen, M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":889420,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70250566,"text":"cir1516 - 2023 - Integrated science strategy for assessing and monitoring water availability and migratory birds for terminal lakes across the Great Basin, United States","interactions":[],"lastModifiedDate":"2025-08-07T21:10:28.947951","indexId":"cir1516","displayToPublicDate":"2023-12-22T07:00:34","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1516","displayTitle":"Integrated Science Strategy for Assessing and Monitoring Water Availability and Migratory Birds for Terminal Lakes Across the Great Basin, United States","title":"Integrated science strategy for assessing and monitoring water availability and migratory birds for terminal lakes across the Great Basin, United States","docAbstract":"

Executive Summary

In 2022, the U.S. Geological Survey (USGS) established the Saline Lake Ecosystems Integrated Water Availability Assessment (IWAAs) to monitor and assess the hydrology of terminal lakes in the Great Basin and the migratory birds and other wildlife dependent on those habitats. Scientists from across the USGS (with specialties in water quantity, water quality, limnology, avian biology, data science, landscape ecology, and science communication) formed the Saline Lake Ecosystems IWAAs Team. The team has developed this regional strategic science plan to guide data collection and assessment activities at terminal lakes in the Great Basin.

The U.S. Congress requested the USGS to establish the Saline Lake Ecosystems IWAAs in response to historically low water levels at terminal lakes and associated wetlands across the Great Basin. Not all Great Basin terminal lakes have high salinity; however, all terminal lakes occur in endorheic, closed, basins with no surface-water outflow. Low lake levels across the Great Basin are the result of increased water use for agriculture and municipalities, drought conditions, and a warming climate. Great Basin terminal lake water extents have decreased by as much as 90 percent over the last 150 years, and terminal lake wetlands have decreased in area by as much as 47 percent since 1984. Lake elevations and wetland areas are primarily supported by freshwater inputs from snowmelt feeding upgradient rivers, streams, and springs. These freshwater inputs have been severely reduced because of continued and increased surface-water diversions and surface-water capture through groundwater pumping for agriculture, mining, and public supply as well as unprecedented drought conditions and warming temperatures related to climate change.

Water quality, specifically salinity, is highly variable for terminal lakes of the Great Basin, and this variability is a result of the balance between freshwater inflow and evaporation. Variability of salinity at each of the terminal lakes can be affected by lake morphology, hydrogeologic features of the basin, annual variability in weather patterns, and changes in upgradient water use. Hypersaline terminal lakes provide abundant food resources such as brine shrimp and brine flies that support nesting and migrating birds. The density and composition of invertebrates are closely tied to lake salinity. Increased salinity can exceed the tolerance of invertebrates, severely limiting their biomass. In contrast, decreased salinity can lead to altered invertebrate community composition, reducing the abundance of optimal avian prey resources.

Great Basin terminal lake ecosystems, including open-water and adjacent aquatic and terrestrial environments, provide resources necessary to sustain many animal populations throughout the year. Although a variety of taxa use terminal lakes, these ecosystems are of acute importance for the millions of migratory waterbirds (for example, shorebirds, wading birds, and waterfowl) dependent on the network of terminal lakes and their associated wetlands. Migratory birds transiting the Pacific and Central Flyways use Great Basin terminal lake ecosystems throughout the year to feed, nest, and transit between wintering and breeding ranges. As such, successful conservation of birds and their habitats requires coordinated management of water and habitats across the Great Basin network of terminal lakes and wetlands.

The linkages between water availability and ecosystem vulnerability of terminal lakes in the Great Basin are not well understood. The vulnerability of terminal lakes is related to the factors driving change and adaptive capacity of the lake ecosystem. Saline lake ecosystems are vulnerable when changes in water quantity affect ecosystem function. Water quantity affects salinity, which affects food webs and habitat; these linkages can be investigated with water-quality and food web monitoring. Water quantity also affects inundated habitat, which can be quantified through remote sensing. It is necessary to quantify hydroclimatic and water use controls on water availability to terminal lakes to assess the response of the ecosystems. Remotely sensed data can provide a broad-scale and long-term synoptic view of terminal lake hydrologic characteristics, but ground observations are required to interpret changes in water quality and ecological functions. Some terminal lake basins have ongoing monitoring and modeling efforts within the Great Basin (for example, Great Salt Lake, Carson River Basin), yet most monitoring locations are hydrologically upgradient and too far away from lake inflows to provide an accurate assessment of hydrological trends for the lake ecosystems. Other terminal lakes have no long-term hydrological monitoring in their respective watersheds (for example, Lake Abert).

Ecological data collection in the Great Basin is also insufficient to understand how many birds exist on the landscape, how birds use the mosaic of terminal-lake habitats as an interconnected system, and how Great Basin terminal lakes are linked to the larger continental system of the Pacific and Central Flyways. Across agencies and organizations, tracking bird movement, abundance, and diversity is inconsistent, with some lakes having once- or twice-a-year bird survey efforts and a few locations having more intensive ecological data-gathering efforts (for example, Great Salt Lake, Lake Abert). Bridging hydrological and ecological information gaps will improve understanding of the trends in water supply and water quality, habitat availability and usage, and impacts on vulnerable waterbird species, all of which would be used by managers in coordinated conservation of this unique network of terminal-lake habitats.

The terminal lakes of the Great Basin are part of the Basin and Range physiographic province that extends from the Colorado Plateau on the east to the Sierra Nevada on the west, and from the Snake River Plain on the north to the Garlock fault and the Mojave block on the south. The Great Basin is larger than 650,000 square kilometers and encompasses most of the State of Nevada but also extends to western Utah, eastern California, southeastern Idaho, southwestern Wyoming, and southeastern Oregon. The climate is arid to semiarid with a hydrologic regime that is snowmelt dominated, providing as much as 75 percent of total annual runoff for the region. Terminal lakes of the Great Basin occupy the lowest areas of closed (endorheic) drainage basins, such that lake levels and water quality respond rapidly to surface-water inflow. Terminal lakes provide local and regional economic value to the States in the Great Basin, including mineral extraction, aquaculture, public works, and recreational uses. As an example, assessments of Great Salt Lake’s ecological health and economic impact find hemispheric importance for the former and regional importance for the latter. Great Salt Lake creates about 7,000 jobs and $2 billion of economic output per year, most of which would be lost with further declines in lake level.

The objectives of this Science Strategy are threefold: (1) to identify how changing water availability affects the quality, diversity, and abundance of habitats supporting continental waterbird populations; (2) to highlight the scientific monitoring and assessment needs of Great Basin terminal lakes; and (3) to support coordinated management and conservation actions to benefit those ecosystems, migratory birds, and other wildlife. There are long-term hydrological, ecological, and societal challenges associated with terminal lakes ecosystems in the Great Basin. This Science Strategy benefits partners by providing a conceptual model, nested at different spatial extents, that identifies key scientific information needs to inform coordinated implementation of management and conservation plans within and among hydrologic basins to address these complex challenges.

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Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th Street, Suite 400
Corvallis, Oregon 97330

Director, Utah Water Science Center
U.S. Geological Survey
2329 West Orton Circle
Salt Lake City, Utah 84119-2047

","tableOfContents":"","publishedDate":"2023-12-22","noUsgsAuthors":false,"publicationDate":"2023-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Frus, Rebecca J. 0000-0002-2435-7202","orcid":"https://orcid.org/0000-0002-2435-7202","contributorId":206261,"corporation":false,"usgs":true,"family":"Frus","given":"Rebecca","email":"","middleInitial":"J.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":890388,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":890389,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":890390,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eagles-Smith, Collin 0000-0003-1329-5285 ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":215925,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":890391,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herring, Garth 0000-0003-1106-4731 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tmarston@usgs.gov","orcid":"https://orcid.org/0000-0003-1053-4172","contributorId":3272,"corporation":false,"usgs":true,"family":"Marston","given":"Thomas","email":"tmarston@usgs.gov","middleInitial":"M.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":890396,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Morris, Christopher M. 0000-0002-0477-7605 cmmorris@usgs.gov","orcid":"https://orcid.org/0000-0002-0477-7605","contributorId":243176,"corporation":false,"usgs":true,"family":"Morris","given":"Christopher M.","email":"cmmorris@usgs.gov","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":false,"id":890397,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Naranjo, Ramon C. 0000-0003-4469-6831 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Center","active":true,"usgs":true}],"preferred":false,"id":890402,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Reichert, Brian E. 0000-0002-9640-0695","orcid":"https://orcid.org/0000-0002-9640-0695","contributorId":22166,"corporation":false,"usgs":true,"family":"Reichert","given":"Brian","email":"","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":890403,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Rumsey, Christine A. 0000-0001-7536-750X","orcid":"https://orcid.org/0000-0001-7536-750X","contributorId":187588,"corporation":false,"usgs":true,"family":"Rumsey","given":"Christine A.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":false,"id":890404,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Schuster, Rudy 0000-0003-2353-8500 schusterr@usgs.gov","orcid":"https://orcid.org/0000-0003-2353-8500","contributorId":3119,"corporation":false,"usgs":true,"family":"Schuster","given":"Rudy","email":"schusterr@usgs.gov","affiliations":[],"preferred":true,"id":890405,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Smith, Cassandra D. 0000-0003-1088-1772 cassandrasmith@usgs.gov","orcid":"https://orcid.org/0000-0003-1088-1772","contributorId":205220,"corporation":false,"usgs":true,"family":"Smith","given":"Cassandra","email":"cassandrasmith@usgs.gov","middleInitial":"D.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":890406,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70250772,"text":"70250772 - 2023 - Train, inform, borrow, or combine? Approaches to process-guided deep learning for groundwater-influenced stream temperature prediction","interactions":[],"lastModifiedDate":"2024-01-04T12:51:48.498521","indexId":"70250772","displayToPublicDate":"2023-12-22T06:44:56","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Train, inform, borrow, or combine? Approaches to process-guided deep learning for groundwater-influenced stream temperature prediction","docAbstract":"

Although groundwater discharge is a critical stream temperature control process, it is not explicitly represented in many stream temperature models, an omission that may reduce predictive accuracy, hinder management of aquatic habitat, and decrease user confidence. We assessed the performance of a previously-described process-guided deep learning model of stream temperature in the Delaware River Basin (USA). We found lower accuracy (root mean square error [RMSE] of 1.71 versus 1.35°C) and stronger seasonal bias (absolute mean monthly bias of 1.06 vs. 0.68°C) for reaches primarily influenced by deep groundwater as compared to atmospheric conditions. We then tested four approaches for improving groundwater process representation: (a) a custom loss function leveraging the unique patterns of air and water temperature coupling characteristic of different temperature drivers, (b) inclusion of additional groundwater-relevant catchment attributes, (c) incorporation of additional process model outputs, and (d) a composite model. The custom loss function and the additional attributes significantly improved the predictive accuracy in groundwater-dominated reaches (RMSE of 1.37 and 1.26°C) and reduced the seasonal bias (absolute mean monthly bias of 0.44 and 0.48°C), but neither approach could identify holdout groundwater reaches. Variable importance analysis indicates the custom loss function nudges the model to use the existing inputs more efficiently, whereas with the added features the model relies on a broader suite of inputs. This analysis is a substantial step toward more accurately representing groundwater discharge processes in stream temperature models and will improve predictive accuracy and inform habitat management.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023WR035327","usgsCitation":"Barclay, J.R., Topp, S.N., Koenig, L.E., Sleckman, M.J., and Appling, A.P., 2023, Train, inform, borrow, or combine? Approaches to process-guided deep learning for groundwater-influenced stream temperature prediction: Water Resources Research, v. 59, no. 12, e2023WR035327, 19 p., https://doi.org/10.1029/2023WR035327.","productDescription":"e2023WR035327, 19 p.","ipdsId":"IP-150248","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":441375,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023wr035327","text":"Publisher Index Page"},{"id":435108,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KO49OT","text":"USGS data release","linkHelpText":"Model Code, Outputs, and Supporting Data for Approaches to Process-Guided Deep Learning for Groundwater-Influenced Stream Temperature Predictions"},{"id":424108,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Delaware River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.0,\n 38.46095870619746\n ],\n [\n -74.27398526052804,\n 38.46095870619746\n ],\n [\n -74.27398526052804,\n 42.406071951802744\n ],\n [\n -76,\n 42.406071951802744\n ],\n [\n -76,\n 38.46095870619746\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"59","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Barclay, Janet R. 0000-0003-1643-6901 jbarclay@usgs.gov","orcid":"https://orcid.org/0000-0003-1643-6901","contributorId":222437,"corporation":false,"usgs":true,"family":"Barclay","given":"Janet","email":"jbarclay@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891360,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Topp, Simon Nemer 0000-0001-7741-5982","orcid":"https://orcid.org/0000-0001-7741-5982","contributorId":268229,"corporation":false,"usgs":true,"family":"Topp","given":"Simon","email":"","middleInitial":"Nemer","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":891361,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koenig, Lauren Elizabeth 0000-0002-7790-330X","orcid":"https://orcid.org/0000-0002-7790-330X","contributorId":295259,"corporation":false,"usgs":true,"family":"Koenig","given":"Lauren","email":"","middleInitial":"Elizabeth","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":891362,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sleckman, Margaux Jeanne 0000-0002-1843-6932","orcid":"https://orcid.org/0000-0002-1843-6932","contributorId":295257,"corporation":false,"usgs":true,"family":"Sleckman","given":"Margaux","email":"","middleInitial":"Jeanne","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":891363,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":891364,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70252083,"text":"70252083 - 2023 - A decade of death and other dynamics: Deepening perspectives on the diversity and distribution of sea stars and wasting","interactions":[],"lastModifiedDate":"2024-03-13T11:42:12.578809","indexId":"70252083","displayToPublicDate":"2023-12-22T06:41:21","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1014,"text":"Biological Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"A decade of death and other dynamics: Deepening perspectives on the diversity and distribution of sea stars and wasting","docAbstract":"

Mass mortality events provide valuable insight into biological extremes and also ecological interactions more generally. The sea star wasting epidemic that began in 2013 catalyzed study of the microbiome, genetics, population dynamics, and community ecology of several high-profile species inhabiting the northeastern Pacific but exposed a dearth of information on the diversity, distributions, and impacts of sea star wasting for many lesser-known sea stars and a need for integration across scales. Here, we combine datasets from single-site to coast-wide studies, across time lines from weeks to decades, for 65 species. We evaluated the impacts of abiotic characteristics hypothetically associated with sea star wasting (sea surface temperature, pelagic primary productivity, upwelling wind forcing, wave exposure, freshwater runoff) and species characteristics (depth distribution, developmental mode, diet, habitat, reproductive period). We find that the 2010s sea star wasting outbreak clearly affected a little over a dozen species, primarily intertidal and shallow subtidal taxa, causing instantaneous wasting prevalence rates of 5%–80%. Despite the collapse of some populations within weeks, environmental and species variation protracted the outbreak, which lasted 2–3 years from onset until declining to chronic background rates of ∼2% sea star wasting prevalence. Recruitment began immediately in many species, and in general, sea star assemblages trended toward recovery; however, recovery was heterogeneous, and a marine heatwave in 2019 raised concerns of a second decline. The abiotic stressors most associated with the 2010s sea star wasting outbreak were elevated sea surface temperature and low wave exposure, as well as freshwater discharge in the north. However, detailed data speaking directly to the biological, ecological, and environmental cause(s) and consequences of the sea star wasting outbreak remain limited in scope, unavoidably retrospective, and perhaps always indeterminate. Redressing this shortfall for the future will require a broad spectrum of monitoring studies not less than the taxonomically broad cross-scale framework we have modeled in this synthesis.

","language":"English","publisher":"University of Chicago Press","doi":"10.1086/727969","usgsCitation":"Dawson, M., Duffin, P., Giakoumis, M., Schiebelhut, L.M., Beas-Luna, R., Bosley, K., Castilho, R., Ewers-Saucedo, C., Gavenus, K., Keller, A., Konar, B., Largier, J.L., Lorda, J., Miner, M., Moritsch, M., Navarette, S., Raimondi, P.T., Traiger, S.B., Turner, M., and Wares, J., 2023, A decade of death and other dynamics: Deepening perspectives on the diversity and distribution of sea stars and wasting: Biological Bulletin, v. 244, no. 3, https://doi.org/10.1086/727969.","ipdsId":"IP-131426","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":441377,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/56754","text":"External 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University of New York","active":true,"usgs":false}],"preferred":false,"id":896552,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schiebelhut, Lauren M","contributorId":295369,"corporation":false,"usgs":false,"family":"Schiebelhut","given":"Lauren","email":"","middleInitial":"M","affiliations":[{"id":54780,"text":"UC Merced","active":true,"usgs":false}],"preferred":false,"id":896553,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beas-Luna, Rodrigo","contributorId":127447,"corporation":false,"usgs":false,"family":"Beas-Luna","given":"Rodrigo","email":"","affiliations":[{"id":6948,"text":"UC Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":896554,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bosley, Keith","contributorId":334802,"corporation":false,"usgs":false,"family":"Bosley","given":"Keith","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":896555,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Castilho, Rita","contributorId":334803,"corporation":false,"usgs":false,"family":"Castilho","given":"Rita","email":"","affiliations":[{"id":80253,"text":"University of Algarve","active":true,"usgs":false}],"preferred":false,"id":896556,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ewers-Saucedo, Christine","contributorId":334804,"corporation":false,"usgs":false,"family":"Ewers-Saucedo","given":"Christine","email":"","affiliations":[{"id":80254,"text":"Zoological Museum Christian-Albrechts University","active":true,"usgs":false}],"preferred":false,"id":896557,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gavenus, Katie","contributorId":334805,"corporation":false,"usgs":false,"family":"Gavenus","given":"Katie","email":"","affiliations":[{"id":80255,"text":"Center for Alaskan Coastal Studies","active":true,"usgs":false}],"preferred":false,"id":896558,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Keller, Aimee","contributorId":334806,"corporation":false,"usgs":false,"family":"Keller","given":"Aimee","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":896559,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Konar, Brenda","contributorId":131034,"corporation":false,"usgs":false,"family":"Konar","given":"Brenda","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":896560,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Largier, John L.","contributorId":175121,"corporation":false,"usgs":false,"family":"Largier","given":"John","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":896561,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Lorda, Julio","contributorId":334807,"corporation":false,"usgs":false,"family":"Lorda","given":"Julio","affiliations":[{"id":34468,"text":"Universidad Autonoma de Baja California","active":true,"usgs":false}],"preferred":false,"id":896562,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Miner, Melissa","contributorId":334808,"corporation":false,"usgs":false,"family":"Miner","given":"Melissa","email":"","affiliations":[{"id":80256,"text":"University of Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":896563,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Moritsch, Monica","contributorId":304091,"corporation":false,"usgs":false,"family":"Moritsch","given":"Monica","affiliations":[{"id":65966,"text":"EDF","active":true,"usgs":false}],"preferred":false,"id":896564,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Navarette, Sergio","contributorId":334809,"corporation":false,"usgs":false,"family":"Navarette","given":"Sergio","email":"","affiliations":[{"id":66274,"text":"Pontifica Universidad Catolica de Chile","active":true,"usgs":false}],"preferred":false,"id":896565,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Raimondi, Peter T.","contributorId":139302,"corporation":false,"usgs":false,"family":"Raimondi","given":"Peter","email":"","middleInitial":"T.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":896566,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Traiger, Sarah Beth 0000-0002-6222-1445","orcid":"https://orcid.org/0000-0002-6222-1445","contributorId":293218,"corporation":false,"usgs":true,"family":"Traiger","given":"Sarah","email":"","middleInitial":"Beth","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":896567,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Turner, Monica","contributorId":193037,"corporation":false,"usgs":false,"family":"Turner","given":"Monica","affiliations":[],"preferred":false,"id":896568,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Wares, John","contributorId":177199,"corporation":false,"usgs":false,"family":"Wares","given":"John","affiliations":[],"preferred":false,"id":896569,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}} ,{"id":70251923,"text":"70251923 - 2023 - Identifying structural priors in a hybrid differentiable model for stream water temperature modeling","interactions":[],"lastModifiedDate":"2024-03-07T13:01:44.619138","indexId":"70251923","displayToPublicDate":"2023-12-21T06:59:39","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Identifying structural priors in a hybrid differentiable model for stream water temperature modeling","docAbstract":"

Although deep learning models for stream temperature (Ts) have recently shown exceptional accuracy, they have limited interpretability and cannot output untrained variables. With hybrid differentiable models, neural networks (NNs) can be connected to physically based equations (called structural priors) to output intermediate variables such as water source fractions (specifying what portion of water is groundwater, subsurface, and surface flow). However, it is unclear if such outputs are physically meaningful when only limited physics is imposed, and if structural priors have enough impacts to be identifiable from data. Here, we tested four alternative structural priors describing basin-scale water temperature memory and instream heat processes in a differentiable stream temperature model where NNs freely estimate the water source fractions. We evaluated models’ abilities to predict Ts and baseflow ratio. The four priors exhibited noticeably different behaviors in these two metrics and their tradeoffs, with some dominating others. Therefore, the better structural priors can be identified. Moreover, testing different priors yielded valuable insights: having a separate shallow subsurface flow component better matches observations, and a recency-weighted averaging of past air temperature for calculating source water temperature resulted in better Ts and baseflow prediction than traditionally employed simple averaging. However, we also highlight the limitations when insufficient physical constraints are implemented: the internal variables (water source fractions) may not be adequately constrained by a single target variable (stream temperature) alone. To ensure the physical significance of the internal fluxes, one can either employ multivariate data for model selection, or include more physical processes in the priors.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023WR034420","usgsCitation":"Rahmani, F., Appling, A.P., Feng, D., Lawson, K., and Shen, C., 2023, Identifying structural priors in a hybrid differentiable model for stream water temperature modeling: Water Resources Research, v. 59, no. 12, e2023WR034420, 21 p., https://doi.org/10.1029/2023WR034420.","productDescription":"e2023WR034420, 21 p.","ipdsId":"IP-148327","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":441379,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023wr034420","text":"Publisher Index Page"},{"id":426426,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Rahmani, Farshid","contributorId":265775,"corporation":false,"usgs":false,"family":"Rahmani","given":"Farshid","email":"","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":896103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":896104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feng, Dapeng 0000-0002-5653-6504","orcid":"https://orcid.org/0000-0002-5653-6504","contributorId":317078,"corporation":false,"usgs":false,"family":"Feng","given":"Dapeng","email":"","affiliations":[{"id":68932,"text":"Civil and Environmental Engineering, The Pennsylvania State University, University Park, PA, USA","active":true,"usgs":false}],"preferred":false,"id":896105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lawson, Kathryn","contributorId":265776,"corporation":false,"usgs":false,"family":"Lawson","given":"Kathryn","affiliations":[{"id":54792,"text":"Civil and Environmental Engineering, Pennsylvania State University, University Park, PA","active":true,"usgs":false}],"preferred":false,"id":896106,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shen, Chaopeng","contributorId":152465,"corporation":false,"usgs":false,"family":"Shen","given":"Chaopeng","email":"","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":896107,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70251950,"text":"70251950 - 2023 - Satellite-derived prefire vegetation predicts variation in field-based invasive annual grass cover after fire","interactions":[],"lastModifiedDate":"2024-03-07T12:47:38.158193","indexId":"70251950","displayToPublicDate":"2023-12-21T06:44:25","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":849,"text":"Applied Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Satellite-derived prefire vegetation predicts variation in field-based invasive annual grass cover after fire","docAbstract":"

Aims

Invasion by annual grasses (IAGs) and concomitant increases in wildfire are impacting many drylands globally, and an understanding of factors that contribute to or detract from community resistance to IAGs is needed to inform postfire restoration interventions. Prefire vegetation condition is often unknown in rangelands but it likely affects variation in postfire invasion resistance across large burned scars. Whether satellite-derived products like the Rangeland Analysis Platform (RAP) can fulfill prefire information needs and be used to parametrize models of fire recovery to inform postfire management of IAGs is a key question.

Methods

We used random forests to ask how IAG abundances in 669 field plots measured in the 2-3 years following megafires in sagebrush steppe rangelands of western USA responded to RAP estimates of annual:perennial prefire vegetation cover, the effects of elevation, heat load, postfire treatments, soil moisture–temperature regimes, and land-agency ratings of ecosystem resistance to invasion and resilience to disturbance.

Results

Postfire IAG cover measured in the field was 22¯% and RAP-estimated prefire annual herbaceous cover was 15.7¯%. The random forest model had an R2 of 0.36 and a root-mean-squared error (RMSE) of 4.41. Elevation, postfire herbicide treatment, and prefire estimates from RAP for the ratio of annual:perennial and shrub cover were the most important predictors of postfire IAG cover. Threshold-like relationships between postfire IAG cover and the predictors indicate that maintaining annual:perennial cover below 0.4 and shrub cover below <10% prior to wildfire would decrease invasion, at low elevations below 1400 m above sea level.

Conclusion

Despite known differences between RAP and field-based estimates of vegetation cover, RAP was still a useful predictor of variation in IAG abundances after fire. IAG management is oftentimes reactive, but our findings indicate impactful roles for more inclusively addressing the exotic annual community, and focusing on prefire maintenance of annual:perennial herbaceous and shrub cover at low elevations.

","language":"English","publisher":"Wiley","doi":"10.1111/avsc.12759","usgsCitation":"Anthony, C.A., Applestein, C., and Germino, M., 2023, Satellite-derived prefire vegetation predicts variation in field-based invasive annual grass cover after fire: Applied Vegetation Science, v. 26, no. 4, e12759, 11 p., https://doi.org/10.1111/avsc.12759.","productDescription":"e12759, 11 p.","ipdsId":"IP-153942","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":426424,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Anthony, Christopher A 0000-0003-0968-224X","orcid":"https://orcid.org/0000-0003-0968-224X","contributorId":334644,"corporation":false,"usgs":false,"family":"Anthony","given":"Christopher","email":"","middleInitial":"A","affiliations":[{"id":80198,"text":"USFWS (current)","active":true,"usgs":false}],"preferred":false,"id":896157,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Applestein, Cara 0000-0002-7923-8526","orcid":"https://orcid.org/0000-0002-7923-8526","contributorId":205748,"corporation":false,"usgs":true,"family":"Applestein","given":"Cara","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":896158,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Germino, Matthew J. 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":251901,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":896159,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70256474,"text":"70256474 - 2023 - Achieving success with RISE: A widely implementable, iterative, structured process for mastering interdisciplinary team science collaborations","interactions":[],"lastModifiedDate":"2024-08-08T10:55:46.557875","indexId":"70256474","displayToPublicDate":"2023-12-20T10:49:34","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"Achieving success with RISE: A widely implementable, iterative, structured process for mastering interdisciplinary team science collaborations","docAbstract":"

Scientific experts from different disciplines often struggle to mesh their specialized perspectives into the shared mindset that is needed to address difficult and persistent environmental, ecological, and societal problems. Many traditional graduate programs provide excellent research and technical skill training. However, these programs often do not teach a systematic way to learn team skills, nor do they offer a protocol for identifying and tackling increasingly integrated interdisciplinary (among disciplines) and transdisciplinary (among researchers and stakeholders) questions. As a result, professionals trained in traditional graduate programs (e.g., current graduate students and employed practitioners) may not have all of the collaborative skills needed to advance solutions to difficult scientific problems. In the present article, we illustrate a tractable, widely implementable structured process called RISE that accelerates the development of these missing skills. The RISE process (Route to Identifying, learning, and practicing interdisciplinary and transdisciplinary team Skills to address difficult Environmental problems) can be used by diverse teams as a tool for research, professional interactions, or training. RISE helps professionals with different expertise learn from each other by repeatedly asking team-developed questions that are tested using an interactive quantitative tool (e.g., agent-based models, machine learning, case studies) applied to a shared problem framework and data set. Outputs from the quantitative tool are then discussed and interpreted as a team, considering all team members’ perspectives, disciplines, and expertise. After this synthesis, RISE is repeated with new questions that the team jointly identified in earlier data interpretation discussions. As a result, individual perspectives, originally informed by disciplinary training, are complemented by a shared understanding of team function and elevated interdisciplinary knowledge.

","language":"English","publisher":"Oxford Academic","doi":"10.1093/biosci/biad097","usgsCitation":"Mather, M.E., Granco, G., Bergtold, J., Caldas, M., Heier Stamm, J., Sheshukov, A., Sanderson, M., and Daniels, M., 2023, Achieving success with RISE: A widely implementable, iterative, structured process for mastering interdisciplinary team science collaborations: BioScience, v. 73, no. 12, p. 891-905, https://doi.org/10.1093/biosci/biad097.","productDescription":"15 p.","startPage":"891","endPage":"905","ipdsId":"IP-148659","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":441388,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biosci/biad097","text":"Publisher Index Page"},{"id":432344,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Mather, Martha E. 0000-0003-0827-3006 mather@usgs.gov","orcid":"https://orcid.org/0000-0003-0827-3006","contributorId":340771,"corporation":false,"usgs":true,"family":"Mather","given":"Martha","email":"mather@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Granco, Gabriel","contributorId":340772,"corporation":false,"usgs":false,"family":"Granco","given":"Gabriel","email":"","affiliations":[{"id":66019,"text":"Cal Poly Pomona","active":true,"usgs":false}],"preferred":false,"id":907538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bergtold, Jason","contributorId":340773,"corporation":false,"usgs":false,"family":"Bergtold","given":"Jason","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":907539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caldas, Marcellus","contributorId":340774,"corporation":false,"usgs":false,"family":"Caldas","given":"Marcellus","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":907540,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heier Stamm, Jessica","contributorId":340775,"corporation":false,"usgs":false,"family":"Heier Stamm","given":"Jessica","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":907541,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sheshukov, Aleksey","contributorId":340776,"corporation":false,"usgs":false,"family":"Sheshukov","given":"Aleksey","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":907542,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sanderson, Matthew","contributorId":340777,"corporation":false,"usgs":false,"family":"Sanderson","given":"Matthew","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":907543,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Daniels, Melinda","contributorId":340778,"corporation":false,"usgs":false,"family":"Daniels","given":"Melinda","affiliations":[{"id":37456,"text":"Stroud Water Research Center","active":true,"usgs":false}],"preferred":false,"id":907544,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70250593,"text":"pp1842LL - 2023 - The effects of management practices on grassland birds—Bobolink (Dolichonyx oryzivorus)","interactions":[{"subject":{"id":70250593,"text":"pp1842LL - 2023 - The effects of management practices on grassland birds—Bobolink (Dolichonyx oryzivorus)","indexId":"pp1842LL","publicationYear":"2023","noYear":false,"chapter":"LL","displayTitle":"The Effects of Management Practices on Grassland Birds—Bobolink (Dolichonyx oryzivorus)","title":"The effects of management practices on grassland birds—Bobolink (Dolichonyx oryzivorus)"},"predicate":"IS_PART_OF","object":{"id":70203022,"text":"pp1842 - 2019 - The effects of management practices on grassland birds","indexId":"pp1842","publicationYear":"2019","noYear":false,"title":"The effects of management practices on grassland birds"},"id":1}],"isPartOf":{"id":70203022,"text":"pp1842 - 2019 - The effects of management practices on grassland birds","indexId":"pp1842","publicationYear":"2019","noYear":false,"title":"The effects of management practices on grassland birds"},"lastModifiedDate":"2024-06-26T14:36:14.181107","indexId":"pp1842LL","displayToPublicDate":"2023-12-19T13:44:15","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1842","chapter":"LL","displayTitle":"The Effects of Management Practices on Grassland Birds—Bobolink (Dolichonyx oryzivorus)","title":"The effects of management practices on grassland birds—Bobolink (Dolichonyx oryzivorus)","docAbstract":"

Keys to Bobolink (Dolichonyx oryzivorus) management are providing large areas of suitable habitat (for example, native or tame grasslands of moderate vegetative height and density, low shrub density, and moderate litter and forb cover), and protecting nesting habitat from disturbance during the breeding season. Bobolinks have been reported to use habitats with 10–166 centimeters (cm) average vegetation height, 6–75 cm visual obstruction reading, 17–65 percent grass cover, 3–50 percent forb cover, less than or equal to (≤) 22 percent shrub cover, ≤38 percent bare ground, 5–39 percent litter cover, and ≤9 cm litter depth.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1842LL","usgsCitation":"Shaffer, J.A., Igl, L.D., Johnson, D.H., Sondreal, M.L., Goldade, C.M., Zimmerman, A.L., Wooten, T.L., and Euliss, B.R., 2023, The effects of management practices on grassland birds—Bobolink (Dolichonyx oryzivorus), chap. LL of Johnson, D.H., Igl, L.D., Shaffer, J.A., and DeLong, J.P., eds., The effects of management practices on grassland birds: U.S. Geological Survey Professional Paper 1842, 44 p., https://doi.org/10.3133/pp1842LL.","productDescription":"v, 44 p.","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-097127","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":423745,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1842/ll/coverthb.jpg"},{"id":423746,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1842/ll/pp1842ll.pdf","text":"Report","size":"2.68 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1842–LL"}],"contact":"

Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, North Dakota 58401

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","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-12-19","noUsgsAuthors":false,"publicationDate":"2023-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Shaffer, Jill A. 0000-0003-3172-0708","orcid":"https://orcid.org/0000-0003-3172-0708","contributorId":214803,"corporation":false,"usgs":true,"family":"Shaffer","given":"Jill A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":890488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Igl, Lawrence D. 0000-0003-0530-7266","orcid":"https://orcid.org/0000-0003-0530-7266","contributorId":220514,"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":890489,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Douglas H. 0000-0002-7778-6641","orcid":"https://orcid.org/0000-0002-7778-6641","contributorId":221269,"corporation":false,"usgs":true,"family":"Johnson","given":"Douglas H.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":890490,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sondreal, Marriah L.","contributorId":215631,"corporation":false,"usgs":false,"family":"Sondreal","given":"Marriah","email":"","middleInitial":"L.","affiliations":[{"id":39297,"text":"former U.S. Geological Survey employee","active":true,"usgs":false}],"preferred":false,"id":890491,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goldade, Christopher M.","contributorId":215632,"corporation":false,"usgs":false,"family":"Goldade","given":"Christopher","email":"","middleInitial":"M.","affiliations":[{"id":39297,"text":"former U.S. Geological Survey employee","active":true,"usgs":false}],"preferred":false,"id":890492,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zimmerman, Amy L.","contributorId":217210,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Amy","email":"","middleInitial":"L.","affiliations":[{"id":39297,"text":"former U.S. Geological Survey employee","active":true,"usgs":false}],"preferred":false,"id":890493,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wooten, Travis L.","contributorId":215633,"corporation":false,"usgs":false,"family":"Wooten","given":"Travis","email":"","middleInitial":"L.","affiliations":[{"id":39297,"text":"former U.S. Geological Survey employee","active":true,"usgs":false}],"preferred":false,"id":890494,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Euliss, Betty R.","contributorId":191881,"corporation":false,"usgs":false,"family":"Euliss","given":"Betty","email":"","middleInitial":"R.","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":890495,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70250603,"text":"70250603 - 2023 - Using a coupled integral projection model to investigate interspecific competition during an invasion: An application to silver carp (Hypophthalmichthys molitrix) and gizzard shad (Dorosoma cepedianum)","interactions":[],"lastModifiedDate":"2023-12-19T12:50:26.049418","indexId":"70250603","displayToPublicDate":"2023-12-19T06:32:31","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3824,"text":"Letters in Biomathematics","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Using a coupled integral projection model to investigate interspecific competition during an invasion: An application to silver carp (Hypophthalmichthys molitrix) and gizzard shad (Dorosoma cepedianum)","title":"Using a coupled integral projection model to investigate interspecific competition during an invasion: An application to silver carp (Hypophthalmichthys molitrix) and gizzard shad (Dorosoma cepedianum)","docAbstract":"

As a generalization of stage-based matrix models, integral projection models (IPMs) have been used to describe the size-based dynamics of wildlife and fisheries populations. Although some matrix models have explicitly included species interactions, few IPMs have expanded beyond single species, which limits their ability to describe the competitive dynamics of co-occuring taxa. We present a coupled system of IPMs where intra- and inter-specific competition may reciprocally affect the life-histories of two species. We investigated the potential role that competition has on two overlapping fish species in the upper Mississippi River system: the native gizzard shad (Dorosoma cepedianum) and the invasive silver carp (Hypophthalmichthys molitrix). Numerical simulations of this system indicated that the coupled IPMs could exhibit asymptotic behaviors similar to traditional, non-linear competition models. Specifically, by altering the competition coefficients, we demonstrate this model's ability to detect competitive exclusion, species coexistence, and dual extinction outcomes.

","language":"English","publisher":"Intercollegiate Biomathematics Alliance","usgsCitation":"Peirce, J.P., Sandland, G., Schumann, D., Thompson, H.M., and Erickson, R.A., 2023, Using a coupled integral projection model to investigate interspecific competition during an invasion: An application to silver carp (Hypophthalmichthys molitrix) and gizzard shad (Dorosoma cepedianum): Letters in Biomathematics, v. 10, no. 1, p. 175-184.","productDescription":"10 p.","startPage":"175","endPage":"184","ipdsId":"IP-156781","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":423743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":423740,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://lettersinbiomath.journals.publicknowledgeproject.org/index.php/lib/article/view/645"}],"volume":"10","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peirce, James P 0000-0002-7147-3695","orcid":"https://orcid.org/0000-0002-7147-3695","contributorId":316559,"corporation":false,"usgs":false,"family":"Peirce","given":"James","email":"","middleInitial":"P","affiliations":[{"id":47908,"text":"University of Wisconsin - La Crosse","active":true,"usgs":false}],"preferred":false,"id":890531,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sandland, Gregory","contributorId":332579,"corporation":false,"usgs":false,"family":"Sandland","given":"Gregory","email":"","affiliations":[{"id":12793,"text":"University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":890532,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schumann, David","contributorId":199504,"corporation":false,"usgs":false,"family":"Schumann","given":"David","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":890533,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Hannah Mann 0000-0001-8316-3232","orcid":"https://orcid.org/0000-0001-8316-3232","contributorId":316560,"corporation":false,"usgs":true,"family":"Thompson","given":"Hannah","email":"","middleInitial":"Mann","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":890534,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":890535,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70259695,"text":"70259695 - 2023 - Two-dimensional inverse energy cascade in a laboratory surf zone for varying wave directional spread","interactions":[],"lastModifiedDate":"2024-10-21T11:29:40.817354","indexId":"70259695","displayToPublicDate":"2023-12-19T06:26:39","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3070,"text":"Physics of Fluids","active":true,"publicationSubtype":{"id":10}},"title":"Two-dimensional inverse energy cascade in a laboratory surf zone for varying wave directional spread","docAbstract":"

Surfzone eddies enhance the dispersion and transport of contaminants, bacteria, and larvae across the nearshore, altering coastal water quality and ecosystem health. During directionally spread wave conditions, vertical vortices (horizontal eddies) are injected near the ends of breaking crests. Energy associated with these eddies may be transferred to larger-scale, low-frequency rotational motions through an inverse energy cascade, consistent with two-dimensional turbulence. However, our understanding of the relationships between the wave conditions and the dynamics and energetics of low-frequency surfzone eddies are largely based on numerical modeling. Here, we test these relationships with remotely sensed and in situ observations from large-scale directional wave basin experiments with varying wave conditions over alongshore-uniform barred bathymetry. Surface velocities derived with particle image velocimetry were employed to assess the spatial scales of low-frequency surfzone eddies and compute structure functions with alongshore velocities. Second-order structure functions for directionally spread waves (⁠ 

","language":"English","publisher":"AIP Publishing","doi":"10.1063/5.0169895","usgsCitation":"Baker, C., Moulton, M., Chickadel, C.C., Nuss, E., Palmsten, M.L., and Brodie, K.L., 2023, Two-dimensional inverse energy cascade in a laboratory surf zone for varying wave directional spread: Physics of Fluids, v. 35, 125140, 18 p., https://doi.org/10.1063/5.0169895.","productDescription":"125140, 18 p.","ipdsId":"IP-156274","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467067,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1063/5.0169895","text":"Publisher Index Page"},{"id":463055,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","noUsgsAuthors":false,"publicationDate":"2023-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Baker, Christine","contributorId":305678,"corporation":false,"usgs":false,"family":"Baker","given":"Christine","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":916354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moulton, Melissa","contributorId":194341,"corporation":false,"usgs":false,"family":"Moulton","given":"Melissa","email":"","affiliations":[],"preferred":false,"id":916355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chickadel, C Chris 0000-0002-0770-7725","orcid":"https://orcid.org/0000-0002-0770-7725","contributorId":221998,"corporation":false,"usgs":false,"family":"Chickadel","given":"C","email":"","middleInitial":"Chris","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":916356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nuss, Emma","contributorId":305681,"corporation":false,"usgs":false,"family":"Nuss","given":"Emma","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":916357,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Palmsten, Margaret L. 0000-0002-6424-2338","orcid":"https://orcid.org/0000-0002-6424-2338","contributorId":239955,"corporation":false,"usgs":true,"family":"Palmsten","given":"Margaret","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":916358,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brodie, Katherine L.","contributorId":345330,"corporation":false,"usgs":false,"family":"Brodie","given":"Katherine","email":"","middleInitial":"L.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":916359,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70250567,"text":"ofr20231077 - 2023 - Applying intrinsic potential models to evaluate salmon (Oncorhynchus spp.) introduction into main-stem and tributary habitats upstream from the Skagit River Hydroelectric Project, northern Washington","interactions":[],"lastModifiedDate":"2024-12-03T19:37:33.744214","indexId":"ofr20231077","displayToPublicDate":"2023-12-18T14:53:20","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1077","displayTitle":"Applying Intrinsic Potential Models to Evaluate Salmon (Oncorhynchus spp.) Introduction into Main-Stem and Tributary Habitats Upstream from the Skagit River Hydroelectric Project, Northern Washington","title":"Applying intrinsic potential models to evaluate salmon (Oncorhynchus spp.) introduction into main-stem and tributary habitats upstream from the Skagit River Hydroelectric Project, northern Washington","docAbstract":"

We assessed habitat suitability for salmonids across selected tributaries upstream from three hydroelectric dams on the upper Skagit River in Whatcom County, northern Washington. We used NetMap, a commercial toolset within the ArcMap geographic information system (GIS), to analyze stream attributes based upon a synthetic stream channel network derived from digital elevation models. The GIS-derived stream attributes—including gradient, bankfull width, valley width index, elevation, and stream flow—allowed us to examine the spatial distribution and relative quality of spawning and rearing habitat for salmonids based on existing intrinsic potential (IP) models. As a first step, we created maps of potential anadromous fish distribution by identifying potential migration barriers within the synthetic stream network. Next, we applied a suite of existing IP models for steelhead, coho, and Chinook salmon (Oncorhynchus mykiss, O. kisutch, and O. tshawytscha, respectively) to estimate low, medium, and high IP habitat for each species. Three different IP models were used for each species, based on species preference curves from populations from coastal Oregon, northern California, Alaska, and western Washington. We found that at least 25 tributaries that were greater than third order and contained habitat with the potential for anadromous fish, totaling about 470 river kilometers in 4,453 synthetic stream reaches averaging about 100 meters (m) in length. The IP of each of these reaches was calculated and placed into low, medium, and high IP categories. For Chinook salmon, the only stream with significantly (in other words, greater than 1 kilometer [km]) high IP reaches was the upper Skagit River upstream from Ross Lake reservoir in Canada, upstream from the third dam in the hydroelectric system. There were differences among the three models evaluated, with the model derived for the lower Skagit River showing more high and medium IP habitat than the other two models that were designed for the Columbia River Basin. For coho salmon, all three models showed similar results favoring medium IP over low and high IP habitat. Of the 3 species examined with existing IP models, steelhead had the most habitat rated as high IP with 19 targeted tributaries showing greater than 1 km of high intrinsic potential habitat.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231077","collaboration":"Prepared in cooperation with Seattle City Light","usgsCitation":"Duda, J.J., and Hardiman, J.M., 2023, Applying intrinsic potential models to evaluate salmon (Oncorhynchus spp.) introduction into main-stem and tributary habitats upstream from the Skagit River Hydroelectric Project, northern Washington: U.S. Geological Survey Open-File Report 2023-1077, 44 p. https://doi.org/10.3133/ofr20231077.","productDescription":"Report: viii, 44 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-147497","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":423653,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1077/ofr20231077.XML"},{"id":423733,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MKQ2UK","text":"USGS data release","description":"USGS data release","linkHelpText":"Upper Skagit River intrinsic potential results"},{"id":423650,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1077/ofr20231077.pdf"},{"id":423649,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1077/ofr20231077.jpg"},{"id":423652,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1077/Images"},{"id":423651,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231077/full"}],"country":"Canada, United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.3,\n 49.3\n ],\n [\n -121.3,\n 48.3\n ],\n [\n -120.3,\n 48.3\n ],\n [\n -120.3,\n 49.3\n ],\n [\n -121.3,\n 49.3\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016

","tableOfContents":"","publishedDate":"2023-12-18","noUsgsAuthors":false,"publicationDate":"2023-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":148954,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":890407,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hardiman, Jill M. 0000-0002-3661-9695 jhardiman@usgs.gov","orcid":"https://orcid.org/0000-0002-3661-9695","contributorId":2672,"corporation":false,"usgs":true,"family":"Hardiman","given":"Jill","email":"jhardiman@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":890408,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70256475,"text":"70256475 - 2023 - The context dependency of fish-habitat associations in separated karst ecoregions","interactions":[],"lastModifiedDate":"2024-08-07T16:04:22.691671","indexId":"70256475","displayToPublicDate":"2023-12-18T10:54:40","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"The context dependency of fish-habitat associations in separated karst ecoregions","docAbstract":"

Fish populations may be isolated via natural conditions in geographically separated ecoregions. Although reconnecting these populations is not a management goal, we need to understand how these populations persist across landscapes to develop meaningful conservation actions, particularly for species occupying sensitive karst ecosystems. Our study objective was to determine the physicochemical factors related to the occurrence of four spring-associated fishes. Arbuckle Uplift and Ozark Highlands ecoregions, USA. We used a hierarchical approach to identify habitat relationships at multiple spatial scales. We collected detection data using snorkeling and seining. We examined the physicochemical relationships related to the detection and occurrence of four spring-associated fishes using occupancy modeling in a Bayesian framework. We found physicochemical relationships that differed and were similar between ecoregions for several fishes. For three species, we found different water temperature relationships between ecoregions. Smallmouth bass were ubiquitous in their use of drainage areas in the Ozark Highlands but only associated with the lower network of the Arbuckle Uplift. There were several mirrored relationships between ecoregions, including an interaction between residual pool depth and water temperature, where sites with deeper pools were more likely to be occupied during warmer water temperatures. There were single-species occurrence relationships with percent vegetation and percent agriculture. Lastly, snorkeling was a more efficient sampling method compared to seining for all fishes. Our results indicate stream temperature mitigation may be possible via the maintenance of key channel morphologies, and we identify shared stressors between ecoregions. Channel mitigation to maintain reaches with deeper pools may be an important strategy for maintaining thermal refugia, particularly when considering climate change. Identifying the mechanistic underpinning of other multiscale ecological relationships would be helpful to discern if some of the different ecoregion relationships represent warning signals or interactions with unmeasured biotic or abiotic factors.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.10701","usgsCitation":"Swedberg, D.A., Mollenhauer, R.M., and Brewer, S.K., 2023, The context dependency of fish-habitat associations in separated karst ecoregions: Ecology and Evolution, v. 13, no. 12, e10701, 18 p., https://doi.org/10.1002/ece3.10701.","productDescription":"e10701, 18 p.","ipdsId":"IP-146272","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":441399,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.10701","text":"Publisher Index Page"},{"id":432361,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.6056935051375,\n 36.99095780343694\n ],\n [\n -95.25818479665297,\n 36.77262795781087\n ],\n [\n -95.51281809235115,\n 35.597221761955254\n ],\n [\n -94.4536118118592,\n 35.530687987028585\n ],\n [\n -94.6056935051375,\n 36.99095780343694\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -97.16528274367352,\n 34.594939532905144\n ],\n [\n -97.44206576958777,\n 33.94434112413069\n ],\n [\n -96.10069816898147,\n 33.94433280692786\n ],\n [\n -96.13328126204877,\n 34.75563707296074\n ],\n [\n -97.16528274367352,\n 34.594939532905144\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Swedberg, Dusty A.","contributorId":340779,"corporation":false,"usgs":false,"family":"Swedberg","given":"Dusty","email":"","middleInitial":"A.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":907545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mollenhauer, Robert M.","contributorId":340780,"corporation":false,"usgs":false,"family":"Mollenhauer","given":"Robert","email":"","middleInitial":"M.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":907546,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":907547,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70254772,"text":"70254772 - 2023 - Forage senescence and disease influence elk pregnancy across the Greater Yellowstone Ecosystem","interactions":[],"lastModifiedDate":"2024-06-07T15:57:01.046173","indexId":"70254772","displayToPublicDate":"2023-12-18T10:45:58","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Forage senescence and disease influence elk pregnancy across the Greater Yellowstone Ecosystem","docAbstract":"

For various temperate ungulate species, recent research has highlighted the potential for spring vegetation phenology (“green-up”) to influence individual condition, with purported benefits to population productivity. However, few studies have been able to measure the benefit on vital rates directly, and fewer still have investigated the comparative influence of other phenological periods on ungulate vital rates. In this study, we tracked phenological changes throughout the duration of the growing season and examined how their timing affected the probability of pregnancy in an ungulate population. We did this for elk (Cervus canadensis) across the Greater Yellowstone Ecosystem (GYE) by sampling 1106 adult females in winter at 25 sites over a 13-year period and assessing sources of variation in pregnancy using a Bayesian hierarchical model. Pregnancy rates were generally high across the GYE (82.4%), and the primary influences on probability of pregnancy were the timing of vegetation senescence (“brown-down”) in autumn and exposure to the reproductive disease brucellosis. Earlier forage brown-down in fall negatively influenced the probability of pregnancy of elk aged 6–9 years by an estimated 17.2% within the range (ca. 32 days) of observed brown-down end dates. While summer habitat quality has been inferred to influence elk pregnancy previously, our findings specify the key influence of foraging conditions later in the seasonal cycle, immediately before the breeding season. The reproductive disease brucellosis was also an important factor, reducing the probability of pregnancy by 12.4% in elk in the 6- to 9-year age class. Because pregnancy was tested before most disease-induced abortions occur, the apparent mechanism for this effect is a prolonged reduction in fertility beyond the period of initial exposure in which fetal mortality is typically expected. Our results prompt greater scrutiny of the combined effects of late-season phenology and disease on reproductive rates and population productivity in temperate ungulates.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4694","usgsCitation":"Bidder, O.R., Connor, T., Morales, J.M., Rickbeil, G.J., Merkle, J., Fuda, R.K., Rogerson, J., Scurlock, B.M., Edwards, W.H., Cole, E., McWhirter, D.E., Courtemanch, A.B., Dewey, S., Kauffman, M., MacNulty, D.R., du Toit, J., Stahler, D., and Middleton, A.D., 2023, Forage senescence and disease influence elk pregnancy across the Greater Yellowstone Ecosystem: Ecosphere, v. 14, e4694, 14 p., https://doi.org/10.1002/ecs2.4694.","productDescription":"e4694, 14 p.","ipdsId":"IP-157765","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":441401,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4694","text":"Publisher Index Page"},{"id":429652,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, 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sources","interactions":[],"lastModifiedDate":"2023-12-28T12:44:48.760618","indexId":"70250712","displayToPublicDate":"2023-12-18T06:36:38","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2321,"text":"Journal of Geophysical Research: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Bayesian hierarchical modeling for probabilistic estimation of tsunami amplitude from far-field earthquake sources","docAbstract":"

Evaluation of tsunami disaster risk for a coastal region requires reliable estimation of tsunami hazard, for example, wave amplitude close to the shore. Observed tsunami data are scarce and have poor spatial coverage, and for this reason probabilistic tsunami hazard analysis (PTHA) traditionally relies on numerical simulation of “synthetic” tsunami generation and propagation toward the coast. Such an approach has been extensively studied in the past and it is widely recognized as an important disaster-risk mitigation tool. PTHA can not only provide less uncertain and spatially coherent hazard estimates in comparison with classical empirical data analysis which is restricted at the tide gauge stations, but also local inundation information. In this paper, we explore a purely statistical alternative to traditional PTHA for evaluation of tsunami amplitude hazard. Here, we use tide gauge measurements of tsunami amplitude along the western United States, specifically California and Oregon, and develop a spatial Bayesian hierarchical model (BHM) to assess tsunami hazard from far-field earthquake sources at various recurrence intervals. The configuration of our model incorporates latent Gaussian fields that utilize information on the distance between tide gauges as well as on the continental shelf width, that is, a covariate linked to potential dissipative effects on wave energy as the tsunami travels over shallow water. Through our BHM, we produce spatially continuous probabilistic maps of far-field tsunami hazard which can aid comprehensive tsunami disaster risk reduction and management.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023JC020002","usgsCitation":"Boumis, G., Geist, E.L., and Lee, D., 2023, Bayesian hierarchical modeling for probabilistic estimation of tsunami amplitude from far-field earthquake sources: Journal of Geophysical Research: Oceans, v. 128, no. 12, e2023JC020002, 16 p., https://doi.org/10.1029/2023JC020002.","productDescription":"e2023JC020002, 16 p.","ipdsId":"IP-151939","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":499265,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023jc020002","text":"Publisher Index Page"},{"id":423956,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.89613542356796,\n 48.497460056867624\n ],\n [\n -126.0601979235679,\n 49.01892139292943\n ],\n [\n -126.0601979235679,\n 44.94434930821649\n ],\n [\n -126.41176042356773,\n 40.75865742539179\n ],\n [\n -125.35707292356773,\n 38.45677055335565\n ],\n [\n -123.24769792356778,\n 34.64558981782825\n ],\n [\n -120.61097917356783,\n 33.0397043679928\n ],\n [\n -118.32582292356796,\n 32.0767084901876\n ],\n [\n -115.33754167356793,\n 32.37411455892672\n ],\n [\n -120.17152604856793,\n 36.78614622387245\n ],\n [\n -122.80824479856787,\n 39.95497361468907\n ],\n [\n -122.80824479856787,\n 43.94038749428063\n ],\n [\n -122.89613542356796,\n 48.497460056867624\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"128","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Boumis, Georgios 0000-0001-7825-5239","orcid":"https://orcid.org/0000-0001-7825-5239","contributorId":332846,"corporation":false,"usgs":false,"family":"Boumis","given":"Georgios","email":"","affiliations":[{"id":79664,"text":"Center for Complex Hydrosystems Research, University of Alabama","active":true,"usgs":false}],"preferred":false,"id":891060,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Geist, Eric L. 0000-0003-0611-1150","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":15543,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":891061,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, Danhyang","contributorId":332847,"corporation":false,"usgs":false,"family":"Lee","given":"Danhyang","email":"","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":891062,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}