{"pageNumber":"169","pageRowStart":"4200","pageSize":"25","recordCount":40783,"records":[{"id":70233403,"text":"70233403 - 2022 - Processes and mechanisms of coastal woody-plant mortality","interactions":[],"lastModifiedDate":"2022-09-15T14:17:06.01715","indexId":"70233403","displayToPublicDate":"2022-06-11T08:24:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Processes and mechanisms of coastal woody-plant mortality","docAbstract":"

Observations of woody plant mortality in coastal ecosystems are globally widespread, but the overarching processes and underlying mechanisms are poorly understood. This knowledge deficiency, combined with rapidly changing water levels, storm surges, atmospheric CO2, and vapor pressure deficit, creates large predictive uncertainty regarding how coastal ecosystems will respond to global change. Here we synthesize the literature on the mechanisms that underlie coastal woody-plant mortality, with the goal of producing a testable hypothesis framework. The key emergent mechanisms underlying mortality include hypoxic, osmotic, and ionic-driven reductions in whole-plant hydraulic conductance and photosynthesis that ultimately drive the coupled processes of hydraulic failure and carbon starvation. The relative importance of these processes in driving mortality, their order of progression, and their degree of coupling depends on the characteristics of the anomalous water exposure, on topographic effects, and on taxa-specific variation in traits and trait acclimation. Greater inundation exposure could accelerate mortality globally; however, the interaction of changing inundation exposure with elevated CO2, drought, and rising vapor pressure deficit could influence mortality likelihood. Models of coastal forests that incorporate the frequency and duration of inundation, the role of climatic drivers, and the processes of hydraulic failure and carbon starvation can yield improved estimates of inundation-induced woody-plant mortality.

","language":"English","publisher":"Wiley","doi":"10.1111/gcb.16297","usgsCitation":"McDowell, N.G., Ball, M., Bond-Lamberty, B., Kirwan, M.L., Krauss, K., Megonigal, J.P., Mencuccini, M., Ward, N.D., Weintraub, M., and Bailey, V., 2022, Processes and mechanisms of coastal woody-plant mortality: Global Change Biology, v. 28, no. 20, p. 5881-5900, https://doi.org/10.1111/gcb.16297.","productDescription":"20 p.","startPage":"5881","endPage":"5900","ipdsId":"IP-138484","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":447473,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/gcb.16297","text":"External Repository"},{"id":404111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"20","noUsgsAuthors":false,"publicationDate":"2022-07-29","publicationStatus":"PW","contributors":{"authors":[{"text":"McDowell, Nate G.","contributorId":207743,"corporation":false,"usgs":false,"family":"McDowell","given":"Nate","email":"","middleInitial":"G.","affiliations":[{"id":37622,"text":"Earth Systems Science Division, Pacific Northwest National Laboratory","active":true,"usgs":false}],"preferred":false,"id":847019,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ball, Marilyn","contributorId":293463,"corporation":false,"usgs":false,"family":"Ball","given":"Marilyn","affiliations":[{"id":16807,"text":"Australian National University","active":true,"usgs":false}],"preferred":false,"id":847020,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bond-Lamberty, Ben","contributorId":224752,"corporation":false,"usgs":false,"family":"Bond-Lamberty","given":"Ben","email":"","affiliations":[{"id":40935,"text":"Joint Global Research Institute, Maryland","active":true,"usgs":false}],"preferred":false,"id":847021,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kirwan, Matthew L.","contributorId":191373,"corporation":false,"usgs":false,"family":"Kirwan","given":"Matthew","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":847022,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krauss, Ken 0000-0003-2195-0729","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":221936,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":847023,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Megonigal, J. Patrick","contributorId":288317,"corporation":false,"usgs":false,"family":"Megonigal","given":"J.","email":"","middleInitial":"Patrick","affiliations":[{"id":13510,"text":"Smithsonian Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":847024,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mencuccini, Maurizio","contributorId":199454,"corporation":false,"usgs":false,"family":"Mencuccini","given":"Maurizio","email":"","affiliations":[],"preferred":false,"id":847025,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ward, Nicholas D.","contributorId":293465,"corporation":false,"usgs":false,"family":"Ward","given":"Nicholas","email":"","middleInitial":"D.","affiliations":[{"id":40277,"text":"U.S. Department of Energy","active":true,"usgs":false}],"preferred":false,"id":847026,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Weintraub, Michael N.","contributorId":293467,"corporation":false,"usgs":false,"family":"Weintraub","given":"Michael N.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":847027,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bailey, Vanessa","contributorId":224753,"corporation":false,"usgs":false,"family":"Bailey","given":"Vanessa","email":"","affiliations":[{"id":38914,"text":"Pacific Northwest National Laboratory","active":true,"usgs":false}],"preferred":false,"id":847028,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70246521,"text":"70246521 - 2022 - U-Pb and fission-track data from zircon and apatite resolve latest- and post-Alleghanian thermal histories along the Fall Line of the Atlantic margin of the southeastern United States","interactions":[],"lastModifiedDate":"2023-07-07T12:21:17.568399","indexId":"70246521","displayToPublicDate":"2022-06-10T07:18:14","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"U-Pb and fission-track data from zircon and apatite resolve latest- and post-Alleghanian thermal histories along the Fall Line of the Atlantic margin of the southeastern United States","docAbstract":"

Although the Atlantic continental margin of the eastern United States is an archetypal passive margin, episodes of rejuvenation following continental breakup are increasingly well documented. To better constrain this history of rejuvenation along the southern portion of this continental margin, we present zircon U-Pb (ZUPb) age, zircon fission-track (ZFT) age, apatite U-Pb (AUPb) age, and apatite fission-track (AFT) age and length data from six bedrock samples. The samples were collected along the boundary between the exposed Appalachian hinterland (Piedmont province) and the updip limit of passive margin strata (Coastal Plain province). The samples were collected from central Virginia southward to the South Carolina–Georgia border. ZUPb age distributions are generally consistent with geologic mapping in each of the sample areas. The AUPb data are highly discordant owing to high common-Pb abundances, but for two plutons at the northern and southern ends of the sample area, they define a discordia regression line that indicates substantial Permo-Triassic exhumation-driven cooling. ZFT age distributions are highly dispersed but define central values ranging from Permian to Jurassic. AFT data mostly appear to define a singular underlying cooling age, generally approximately Jurassic or Early Cretaceous. Apatite fission tracks are moderately long (mean lengths in the range of ~13.5 µm), however track lengths for one sample in central North Carolina are shorter (~12.5 µm). To interpret the post-breakup thermal history, we present inverse models of time-temperature history for the five plutonic samples. The models show a history of (1) rapid cooling (>10 °C/m.y.) from deep-crustal to near-surface temperatures by the Triassic, (2) hundreds of degrees of Triassic reheating, (3) Jurassic–Early Cretaceous cooling (at rates of 1–10 °C/m.y.), and (4) slow Late Cretaceous–Cenozoic cooling (~1 °C/m.y.). An additional suite of forward models is presented to further evaluate the magnitude of maximum Triassic reheating at one sample site that is particularly well constrained by thermal maturity data. The model results and geologic reasoning suggest that the inverse models may overestimate Triassic paleotemperatures but that other aspects of the inverse modeling are robust. Overall, this thermal history can be reconciled with several aspects of the lithostratigraphy of distal parts of the continental margin, including the lack of Jurassic–earliest Cretaceous strata beneath the southern Atlantic coastal plain and Cretaceous–Cenozoic grain-size trends.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02447.1","usgsCitation":"Craddock, W.H., O'Sullivan, P., and McAleer, R.J., 2022, U-Pb and fission-track data from zircon and apatite resolve latest- and post-Alleghanian thermal histories along the Fall Line of the Atlantic margin of the southeastern United States: Geosphere, v. 18, no. 4, p. 1330-1353, https://doi.org/10.1130/GES02447.1.","productDescription":"24 p.","startPage":"1330","endPage":"1353","ipdsId":"IP-127916","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":447476,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02447.1","text":"Publisher Index Page"},{"id":418744,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.06589631767767,\n 40.62761013989578\n ],\n [\n -76.81264623503682,\n 40.32689154960596\n ],\n [\n -79.40430771293059,\n 40.02563596082908\n ],\n [\n -81.51277806782672,\n 38.76941324786962\n ],\n [\n -83.62124842272343,\n 36.33152035458974\n ],\n [\n -84.63155713444466,\n 33.778910284254295\n ],\n [\n -83.84088075135841,\n 32.7874625650833\n ],\n [\n -82.1277485880051,\n 31.4481799351054\n ],\n [\n -80.32676349319762,\n 31.672755039272587\n ],\n [\n -77.51546968666938,\n 33.22949605942023\n ],\n [\n -75.14344053741085,\n 35.02409793894682\n ],\n [\n -73.12282311396812,\n 37.10613979176382\n ],\n [\n -73.47423483978443,\n 39.24678773255735\n ],\n [\n -76.06589631767767,\n 40.62761013989578\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Craddock, William H. 0000-0002-4181-4735 wcraddock@usgs.gov","orcid":"https://orcid.org/0000-0002-4181-4735","contributorId":3411,"corporation":false,"usgs":true,"family":"Craddock","given":"William","email":"wcraddock@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":877037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O'Sullivan, Paul","contributorId":257903,"corporation":false,"usgs":false,"family":"O'Sullivan","given":"Paul","affiliations":[{"id":51089,"text":"Geosep Services","active":true,"usgs":false}],"preferred":false,"id":877038,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":877039,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70238498,"text":"70238498 - 2022 - Targeting sagebrush (Artemisia spp.) restoration following wildfire with Greater Sage-Grouse (Centrocercus urophasianus) nest selection and survival models","interactions":[],"lastModifiedDate":"2022-11-28T12:19:06.34769","indexId":"70238498","displayToPublicDate":"2022-06-10T06:15:49","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Targeting sagebrush (Artemisia spp.) restoration following wildfire with Greater Sage-Grouse (Centrocercus urophasianus) nest selection and survival models","docAbstract":"

Unprecedented conservation efforts for sagebrush (Artemisia spp.) ecosystems across the western United States have been catalyzed by risks from escalated wildfire activity that reduces habitat for sagebrush-obligate species such as Greater Sage-Grouse (Centrocercus urophasianus). However, post-fire restoration is challenged by spatial variation in ecosystem processes influencing resilience to disturbance and resistance to non-native invasive species, and spatial and temporal lags between slower sagebrush recovery processes and faster demographic responses of sage-grouse to loss of important habitat. Decision-support frameworks that account for these factors can help users strategically apply restoration efforts by predicting short and long-term ecological benefits of actions. Here, we developed a framework that strategically targets burned areas for restoration actions (e.g., seeding or planting sagebrush) that have the greatest potential to positively benefit sage-grouse populations through time. Specifically, we estimated sagebrush recovery following wildfire and risk of non-native annual grass invasion under four scenarios: passive recovery, grazing exclusion, active restoration with seeding, and active restoration with seedling transplants. We then applied spatial predictions of integrated nest site selection and survival models before wildfire, immediately following wildfire, and at 30 and 50 years post-wildfire based on each restoration scenario and measured changes in habitat. Application of this framework coupled with strategic planting designs aimed at developing patches of nesting habitat may help increase operational resilience for fire-impacted sagebrush ecosystems.

","language":"English","publisher":"Springer Nature","doi":"10.1007/s00267-022-01649-0","usgsCitation":"Roth, C.L., O’Neil, S.T., Coates, P.S., Ricca, M.A., Pyke, D.A., Aldridge, C.L., Heinrichs, J.A., Espinosa, S.P., and Delehanty, D.J., 2022, Targeting sagebrush (Artemisia spp.) restoration following wildfire with Greater Sage-Grouse (Centrocercus urophasianus) nest selection and survival models: Environmental Management, v. 70, p. 288-306, https://doi.org/10.1007/s00267-022-01649-0.","productDescription":"19 p.","startPage":"288","endPage":"306","ipdsId":"IP-123159","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":447481,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00267-022-01649-0","text":"Publisher Index Page"},{"id":435809,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96K6X05","text":"USGS data release","linkHelpText":"Sagebrush Restoration Following Fire Disturbance in the Virginia Mountains, Nevada (2018)"},{"id":409662,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"70","noUsgsAuthors":false,"publicationDate":"2022-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Roth, Cali L. 0000-0001-9077-2765 croth@usgs.gov","orcid":"https://orcid.org/0000-0001-9077-2765","contributorId":174422,"corporation":false,"usgs":true,"family":"Roth","given":"Cali","email":"croth@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":857639,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Neil, Shawn T. 0000-0002-0899-5220","orcid":"https://orcid.org/0000-0002-0899-5220","contributorId":206589,"corporation":false,"usgs":true,"family":"O’Neil","given":"Shawn","email":"","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857640,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857641,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ricca, Mark A. 0000-0003-1576-513X mark_ricca@usgs.gov","orcid":"https://orcid.org/0000-0003-1576-513X","contributorId":139103,"corporation":false,"usgs":true,"family":"Ricca","given":"Mark","email":"mark_ricca@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857642,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":857643,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":857644,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Heinrichs, Julie A. 0000-0001-7733-5034 jheinrichs@usgs.gov","orcid":"https://orcid.org/0000-0001-7733-5034","contributorId":193742,"corporation":false,"usgs":true,"family":"Heinrichs","given":"Julie","email":"jheinrichs@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":857645,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Espinosa, Shawn P.","contributorId":195583,"corporation":false,"usgs":false,"family":"Espinosa","given":"Shawn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":857646,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Delehanty, David J.","contributorId":195584,"corporation":false,"usgs":false,"family":"Delehanty","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":857647,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70262475,"text":"70262475 - 2022 - The occupancy-abundance relationship and sampling designs using occupancy to monitor populations of Asian bears","interactions":[],"lastModifiedDate":"2025-01-22T15:30:34.089451","indexId":"70262475","displayToPublicDate":"2022-06-10T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"The occupancy-abundance relationship and sampling designs using occupancy to monitor populations of Asian bears","docAbstract":"

Designing a population monitoring program for Asian bears presents challenges associated with their low densities and detectability, generally large home ranges, and logistical or resource constraints. The use of an occupancy-based method to monitor bear populations can be appropriate under certain conditions given the mechanistic relationship between occupancy and abundance. The form of the occupancy–abundance relationship is dependent on species-specific characteristics such as home range size and population density, as well as study area size. To assess the statistical power of tests to detect population change of Asian bears, we conducted a study using a range of scenarios by simulating spatially explicit individual-based capture-recapture data from a demographically open model. Simulations assessed the power to detect changes in population density via changes in site-level occupancy or abundance through time, estimated using a standard occupancy model or a Royle-Nichols model, both with point detectors (representing camera traps). We used IUCN Red List criteria as a guide in selection of two population decline scenarios (20% and 50%), but we chose a shorter time horizon (10 years = 1 bear generation), meaning that declines were steeper than used for IUCN criteria (3 generations). Our simulations detected population declines of 50% with high power (>0.80) and low false positive rates (FPR: incorrectly detecting a decline) (<0.10) when detectors were spaced at > 0.67 times the home range diameter (home-range spacing ratio: HRSR, a measure of spatial correlation), such that bears would tend to overlap no more than two detectors. There was high (0.85) correlation between realized occupancy and N in these scenarios. The FPR increased as the HRSR decreased because of spatial correlation in the occupancy process induced when individual home ranges overlap multiple detectors. The mean statistical power to detect more gradual population declines (20% in 10 years) with HRSR > 0.67 was low for occupancy models 0.22 (maximum power 0.67) and Royle-Nichols models (0.24; maximum power 0.67), suggesting that declines of this magnitude may not be described reliably with 10 years of monitoring. Our results demonstrated that under many realistic scenarios that we explored, false positive rates were unacceptably high. We highlight that when designing occupancy studies, the spacing between point detectors be at least 0.67 times the diameter of the home range size of the larger sex (e.g., males) when the assumptions of the spatial capture-recapture model used for simulation are met.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2022.e02075","usgsCitation":"Fuller, A.K., Augustine, B., Morin, D., Pigeon, K., Boulanger, J., Lee, D., Bisi, F., and Garshelis, D., 2022, The occupancy-abundance relationship and sampling designs using occupancy to monitor populations of Asian bears: Global Ecology and Conservation, v. 35, e02075, 18 p., https://doi.org/10.1016/j.gecco.2022.e02075.","productDescription":"e02075, 18 p.","ipdsId":"IP-135705","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481083,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2022.e02075","text":"Publisher Index Page"},{"id":480920,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":924297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Augustine, Ben C.","contributorId":349417,"corporation":false,"usgs":false,"family":"Augustine","given":"Ben C.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":924298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morin, Dana J.","contributorId":349419,"corporation":false,"usgs":false,"family":"Morin","given":"Dana J.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":924299,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pigeon, Karine","contributorId":349420,"corporation":false,"usgs":false,"family":"Pigeon","given":"Karine","affiliations":[{"id":83340,"text":"IUCN SSC Bear Specialist Group","active":true,"usgs":false}],"preferred":false,"id":924300,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boulanger, John","contributorId":349422,"corporation":false,"usgs":false,"family":"Boulanger","given":"John","affiliations":[{"id":83347,"text":"Integrated Ecological Research","active":true,"usgs":false}],"preferred":false,"id":924301,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lee, David C.","contributorId":349424,"corporation":false,"usgs":false,"family":"Lee","given":"David C.","affiliations":[{"id":83348,"text":"University of South Wales","active":true,"usgs":false}],"preferred":false,"id":924302,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bisi, Francesco","contributorId":349429,"corporation":false,"usgs":false,"family":"Bisi","given":"Francesco","affiliations":[{"id":83482,"text":"University of Insubria","active":true,"usgs":false}],"preferred":false,"id":924303,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Garshelis, David L.","contributorId":349431,"corporation":false,"usgs":false,"family":"Garshelis","given":"David L.","affiliations":[{"id":83484,"text":"IUCN SSC Bear Specialist Group.","active":true,"usgs":false}],"preferred":false,"id":924304,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70232247,"text":"70232247 - 2022 - Turbidity and estimated phosphorus retention in a reconnected Lake Erie coastal wetland","interactions":[],"lastModifiedDate":"2022-06-17T14:15:00.422295","indexId":"70232247","displayToPublicDate":"2022-06-09T09:05:19","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Turbidity and estimated phosphorus retention in a reconnected Lake Erie coastal wetland","docAbstract":"

Nearly all of the wetlands in the coastal zone of Lake Erie have been degraded or destroyed since the 1860s, and most of those that remain are separated from their watersheds by earthen dikes. Hydrologic isolation of these wetlands disrupts ecosystem benefits typical to Great Lakes coastal wetlands, particularly the ability to trap sediments and retain nutrients when inundated by runoff and lake water. High-frequency measurements of turbidity and discharge were taken in 2013 and 2014 to observe turbidity and water flow dynamics to estimate total phosphorus flux of a hydrologically reconnected diked wetland pool in the Crane Creek-Lake Erie wetland complex. Modeled estimates suggest the reconnected pool retained 8% of the total phosphorus loading in 2013 and 10% in 2014, which included short periods of phosphorus export to Lake Erie. Water flowing out of the wetland generally had lower turbidity than inflowing water, but flux in and out of the pool varied seasonally and was linked to changes in lake-levels, seiche dynamics, and weather conditions. More frequent storms, higher winds, and stronger seiches in the spring and fall created turbidity patterns that suggest more phosphorus retention than in summer or winter. Estimates suggest that phosphorus was released during the summer when higher lake levels and the absence of frequent storms, larger short-term seiche oscillations, and potentially soil oxygen availability were driving flux dynamics. This study demonstrated that reestablishing lake hydrology through reconnection of wetland pools can reduce loading and alter timing of delivery of total phosphorus to Lake Erie.

","language":"English","publisher":"MDPI","doi":"10.3390/w14121853","usgsCitation":"Carter, G., Kowalski, K., and Eggleston, M., 2022, Turbidity and estimated phosphorus retention in a reconnected Lake Erie coastal wetland: Water, v. 14, no. 2, 1853, 12 p., https://doi.org/10.3390/w14121853.","productDescription":"1853, 12 p.","ipdsId":"IP-110303","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":447485,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w14121853","text":"Publisher Index Page"},{"id":435812,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71V5C3B","text":"USGS data release","linkHelpText":"Total phosphorus and water flux at a restored hydrologic connection at Ottawa National Wildlife Refuge in 2013 and 2014"},{"id":402325,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Crane Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.24014663696289,\n 41.59772934193236\n ],\n [\n -83.17886352539062,\n 41.59772934193236\n ],\n [\n -83.17886352539062,\n 41.64764694964725\n ],\n [\n -83.24014663696289,\n 41.64764694964725\n ],\n [\n -83.24014663696289,\n 41.59772934193236\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-06-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Carter, Glenn 0000-0001-6630-7513","orcid":"https://orcid.org/0000-0001-6630-7513","contributorId":292490,"corporation":false,"usgs":false,"family":"Carter","given":"Glenn","email":"","affiliations":[],"preferred":false,"id":844792,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kowalski, Kurt P. 0000-0002-8424-4701 kkowalski@usgs.gov","orcid":"https://orcid.org/0000-0002-8424-4701","contributorId":3768,"corporation":false,"usgs":true,"family":"Kowalski","given":"Kurt P.","email":"kkowalski@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":844793,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eggleston, Michael 0000-0003-1068-3290","orcid":"https://orcid.org/0000-0003-1068-3290","contributorId":204833,"corporation":false,"usgs":true,"family":"Eggleston","given":"Michael","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":844794,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70236280,"text":"70236280 - 2022 - Tree rings reveal unmatched 2nd century drought in the Colorado River Basin","interactions":[],"lastModifiedDate":"2022-08-31T14:13:13.360127","indexId":"70236280","displayToPublicDate":"2022-06-09T09:01:34","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Tree rings reveal unmatched 2nd century drought in the Colorado River Basin","docAbstract":"The ongoing 22 year drought in the Upper Colorado River Basin (UCRB) has been extremely severe, even in the context of the longest available tree-ring reconstruction of annual flow at Lees Ferry, Arizona, dating back to 762 CE. While many southwestern drought assessments have been limited to the past 1200 years, longer paleorecords of moisture variability do exist for the UCRB. Here, gridded drought-atlas data in the UCRB domain along with naturalized streamflow data from the instrumental period (1906–2021) are used in a K nearest neighbor (KNN) nonparametric algorithm to develop a streamflow reconstruction for the Lees Ferry gage starting in 1 CE. The reconstruction reveals a 2nd century drought unmatched in severity by the current drought or by well-documented medieval period droughts in the UCRB. Although data are sparse, analysis of individual long tree ring records and other paleoclimatic data also support the occurrence of an exceptional 2nd century drought.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022GL098781","usgsCitation":"Gangopadhyay, S., Woodhouse, C., McCabe, G.J., Routson, C.C., and Meko, D., 2022, Tree rings reveal unmatched 2nd century drought in the Colorado River Basin: Geophysical Research Letters, v. 49, no. 11, e2022GL098781, 10 p., https://doi.org/10.1029/2022GL098781.","productDescription":"e2022GL098781, 10 p.","ipdsId":"IP-139459","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":447488,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022gl098781","text":"Publisher Index Page"},{"id":405995,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","otherGeospatial":"upper Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.03857421875,\n 36.38591277287651\n ],\n [\n -111.181640625,\n 36.58024660149866\n ],\n [\n -110.25878906249999,\n 36.36822190085111\n ],\n [\n -109.9072265625,\n 35.88905007936091\n ],\n [\n -108.8525390625,\n 35.782170703266075\n ],\n [\n -107.51220703125,\n 35.67514743608467\n ],\n [\n -106.74316406249999,\n 36.56260003738545\n ],\n [\n -106.34765625,\n 37.07271048132943\n ],\n [\n -106.5673828125,\n 37.64903402157866\n ],\n [\n -106.12792968749999,\n 38.048091067457236\n ],\n [\n -106.083984375,\n 39.07890809706475\n ],\n [\n -105.0732421875,\n 39.825413103424786\n ],\n [\n -105.35888671875,\n 40.96330795307353\n ],\n [\n -107.11669921875,\n 42.342305278572816\n ],\n [\n -110.32470703125,\n 43.29320031385282\n ],\n [\n -110.6982421875,\n 43.56447158721811\n ],\n [\n -110.91796875,\n 41.75492216766298\n ],\n [\n -111.1376953125,\n 41.393294288784865\n ],\n [\n -111.4013671875,\n 41.09591205639546\n ],\n [\n -111.884765625,\n 39.90973623453719\n ],\n [\n -112.19238281249999,\n 38.66835610151506\n ],\n [\n -112.3681640625,\n 37.21283151445594\n ],\n [\n -112.39013671875,\n 36.65079252503471\n ],\n [\n -112.03857421875,\n 36.38591277287651\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-06-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Gangopadhyay, Subhrendu 0000-0003-3864-8251","orcid":"https://orcid.org/0000-0003-3864-8251","contributorId":173439,"corporation":false,"usgs":false,"family":"Gangopadhyay","given":"Subhrendu","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":850421,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woodhouse, Connie 0000-0003-0545-9753","orcid":"https://orcid.org/0000-0003-0545-9753","contributorId":296028,"corporation":false,"usgs":false,"family":"Woodhouse","given":"Connie","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":850422,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":200854,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory","email":"gmccabe@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":850423,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Routson, Cody C. 0000-0001-8694-7809","orcid":"https://orcid.org/0000-0001-8694-7809","contributorId":187600,"corporation":false,"usgs":false,"family":"Routson","given":"Cody","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":850424,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meko, David 0000-0002-5171-2724","orcid":"https://orcid.org/0000-0002-5171-2724","contributorId":296029,"corporation":false,"usgs":false,"family":"Meko","given":"David","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":850425,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70263077,"text":"70263077 - 2022 - Biodiversity underpins fisheries resilience to exploitation in the Amazon River basin.","interactions":[],"lastModifiedDate":"2025-01-29T15:10:32.880127","indexId":"70263077","displayToPublicDate":"2022-06-08T08:55:39","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18342,"text":"Proceedings of the Royal Society B, Biological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Biodiversity underpins fisheries resilience to exploitation in the Amazon River basin.","docAbstract":"

Inland fisheries feed greater than 150 million people globally, yet their status is rarely assessed due to their socio-ecological complexity and pervasive lack of data. Here, we leverage an unprecedented landings time series from the Amazon, Earth's largest river basin, together with theoretical food web models to examine (i) taxonomic and trait-based signatures of exploitation in inland fish landings and (ii) implications of changing biodiversity for fisheries resilience. In both landings time series and theory, we find that multi-species exploitation of diverse inland fisheries results in a hump-shaped landings evenness curve. Along this trajectory, abundant and large species are sequentially replaced with faster growing and smaller species. Further theoretical analysis indicates that harvests can be maintained for a period of time but that continued biodiversity depletion reduces the pool of compensating species and consequently diminishes fisheries resilience. Critically, higher fisheries biodiversity can delay fishery collapse. Although existing landings data provide an incomplete snapshot of long-term dynamics, our results suggest that multi-species exploitation is affecting freshwater biodiversity and eroding fisheries resilience in the Amazon. More broadly, we conclude that trends in landings evenness could characterize multi-species fisheries development and aid in assessing their sustainability.

","language":"English","publisher":"The Royal Society","doi":"10.1098/rspb.2022.0726","usgsCitation":"Heilpern, S., Sethi, S., Barthem, R., da Silva Batista, V., Doria, C.R., Duponchelle, F., Garcia Vasquez, A., Goulding, M., Isaac, V., Naeem, S., and Flecker, A., 2022, Biodiversity underpins fisheries resilience to exploitation in the Amazon River basin.: Proceedings of the Royal Society B, Biological Sciences, v. 289, no. 1976, 20220726, 10 p., https://doi.org/10.1098/rspb.2022.0726.","productDescription":"20220726, 10 p.","ipdsId":"IP-117938","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":487601,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://archimer.ifremer.fr/doc/00776/88847/","text":"External Repository"},{"id":481448,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil, Peru","otherGeospatial":"Amazon River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -63.313226573988004,\n 2.0612813356318185\n ],\n [\n -69.56203866644994,\n -0.014204318512454961\n ],\n [\n -75.92570575301421,\n -4.378615486744579\n ],\n [\n -74.45715869209243,\n -11.37283711742269\n ],\n [\n -68.58854564799162,\n -14.624571352339885\n ],\n [\n -56.626853677433644,\n -11.79116453472244\n ],\n [\n -51.789283587896364,\n -5.789272637136122\n ],\n [\n -45.633273589919156,\n -0.6212788606292179\n ],\n [\n -49.98030189640525,\n 2.344463983995297\n ],\n [\n -63.313226573988004,\n 2.0612813356318185\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"289","issue":"1976","noUsgsAuthors":false,"publicationDate":"2022-06-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Heilpern, Sebastian A.","contributorId":350166,"corporation":false,"usgs":false,"family":"Heilpern","given":"Sebastian A.","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":925457,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sethi, Suresh 0000-0002-0053-1827 ssethi@usgs.gov","orcid":"https://orcid.org/0000-0002-0053-1827","contributorId":191424,"corporation":false,"usgs":true,"family":"Sethi","given":"Suresh","email":"ssethi@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":925456,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barthem, Ronaldo B.","contributorId":350167,"corporation":false,"usgs":false,"family":"Barthem","given":"Ronaldo B.","affiliations":[{"id":83689,"text":"Museu Paraense Emilio Goeldi","active":true,"usgs":false}],"preferred":false,"id":925458,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"da Silva Batista, 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Vasquez","given":"Aurea","affiliations":[{"id":83694,"text":"Evolution et Domestication de l’Ichtyofaune Amazonienne","active":true,"usgs":false}],"preferred":false,"id":925462,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Goulding, Michael","contributorId":350174,"corporation":false,"usgs":false,"family":"Goulding","given":"Michael","affiliations":[{"id":13272,"text":"Wildlife Conservation Society","active":true,"usgs":false}],"preferred":false,"id":925463,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Isaac, Victoria","contributorId":350175,"corporation":false,"usgs":false,"family":"Isaac","given":"Victoria","affiliations":[{"id":83695,"text":"Núcleo de Ecologia Aquática e Pesca da Amazônia","active":true,"usgs":false}],"preferred":false,"id":925464,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Naeem, Shahid","contributorId":287018,"corporation":false,"usgs":false,"family":"Naeem","given":"Shahid","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":925527,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Flecker, Alexander S.","contributorId":350176,"corporation":false,"usgs":false,"family":"Flecker","given":"Alexander S.","affiliations":[{"id":13272,"text":"Wildlife Conservation Society","active":true,"usgs":false}],"preferred":false,"id":925465,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70232111,"text":"ofr20221051 - 2022 - Assessment of mercury in sediments and waters of Grubers Grove Bay, Wisconsin","interactions":[],"lastModifiedDate":"2026-03-27T20:22:54.13031","indexId":"ofr20221051","displayToPublicDate":"2022-06-07T15:08:34","publicationYear":"2022","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":"2022-1051","displayTitle":"Assessment of Mercury in Sediments and Waters of Grubers Grove Bay, Wisconsin","title":"Assessment of mercury in sediments and waters of Grubers Grove Bay, Wisconsin","docAbstract":"

Mercury is a global contaminant that can be detrimental to wildlife and human health. Anthropogenic emissions and point sources are primarily responsible for elevated mercury concentrations in sediments and waters. Mercury can physically move and chemically transform in the environment, resulting in biomagnification of mercury, in the form of methylmercury, in the food web and causing elevated mercury concentrations in upper trophic levels. The ability to measure total mercury concentrations in the environment has existed for several decades and makes it possible to detect hotspots that might exist because of ongoing or previous anthropogenic activity. However, recent (within the past 15 years) developments in mass spectrometry have made it possible to complete low level stable isotope analysis allowing for the determination of mercury sources—natural and anthropogenic—in the environment through “fingerprinting.” Grubers Grove Bay in Lake Wisconsin, the focus area of this study, was determined to have elevated mercury levels even after multiple remediation efforts, resulting in its listing on the Federal list of impaired waters pursuant to the Clean Water Act. Adjacent to the bay is the former Badger Army Ammunition Plant, which manufactured ammunition for the U.S. Army during the early and middle 20th century, after which it was put on standby before being fully decommissioned. This study assesses mercury concentrations in the sediments and suspended particulate matter of Grubers Grove Bay, Wiegands Bay, and upstream sites, and in adjacent soils on the former Badger Army Ammunition Plant site. This study confirmed that mercury contamination exists in the sediments of Grubers Grove Bay even after dredging attempts by the U.S. Army. Additionally, using isotope ratios and a two-endmember mixing model, it was determined that soil from within Badger Army Ammunition Plant’s former site contributed a substantial amount of mercury to the bay. This result was supported by an observed gradient of high to low mercury concentrations from the innermost (nearest Badger Army Ammunition Plant) to the outermost (farthest from Badger Army Ammunition Plant) part of the bay.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221051","collaboration":"Prepared in cooperation with U.S. Army Environmental Command","usgsCitation":"Routhier, E.J., Janssen, S.E., Tate, M.T., Ogorek, J.M., DeWild, J.F., and Krabbenhoft, D.P., 2022, Assessment of mercury in sediments and waters of Grubers Grove Bay, Wisconsin: U.S. Geological Survey Open-File Report 2022–1051, 20 p., https://doi.org/10.3133/ofr20221051.","productDescription":"Report: vii, 20 p.; Data release","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-133343","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501779,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113162.htm","linkFileType":{"id":5,"text":"html"}},{"id":401822,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P990MFHU","text":"USGS data release","linkHelpText":"Gruber's Grove Bay mercury site assessment"},{"id":401821,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1051/images"},{"id":401819,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1051/ofr20221051.pdf","text":"Report","size":"2.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1051"},{"id":401818,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1051/coverthb.jpg"},{"id":401820,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1051/ofr20221051.XML"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Grubers Grove Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.74800109863281,\n 43.32467816302811\n ],\n [\n -89.64569091796874,\n 43.32467816302811\n ],\n [\n -89.64569091796874,\n 43.393572674883146\n ],\n [\n -89.74800109863281,\n 43.393572674883146\n ],\n [\n -89.74800109863281,\n 43.32467816302811\n ]\n ]\n ]\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":15,"text":"Madison PSC"},"publishedDate":"2022-06-07","noUsgsAuthors":false,"publicationDate":"2022-06-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Routhier, Evan J. 0000-0002-0147-9186","orcid":"https://orcid.org/0000-0002-0147-9186","contributorId":292294,"corporation":false,"usgs":false,"family":"Routhier","given":"Evan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":844236,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Janssen, Sarah E. 0000-0003-4432-3154","orcid":"https://orcid.org/0000-0003-4432-3154","contributorId":210991,"corporation":false,"usgs":true,"family":"Janssen","given":"Sarah E.","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":844237,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tate, Michael T. 0000-0003-1525-1219 mttate@usgs.gov","orcid":"https://orcid.org/0000-0003-1525-1219","contributorId":3144,"corporation":false,"usgs":true,"family":"Tate","given":"Michael T.","email":"mttate@usgs.gov","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":844238,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ogorek, Jacob M. 0000-0002-6327-0740 jmogorek@usgs.gov","orcid":"https://orcid.org/0000-0002-6327-0740","contributorId":4960,"corporation":false,"usgs":true,"family":"Ogorek","given":"Jacob","email":"jmogorek@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"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":844239,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeWild, John F. 0000-0003-4097-2798 jfdewild@usgs.gov","orcid":"https://orcid.org/0000-0003-4097-2798","contributorId":2525,"corporation":false,"usgs":true,"family":"DeWild","given":"John","email":"jfdewild@usgs.gov","middleInitial":"F.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844240,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844241,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70232234,"text":"70232234 - 2022 - Decadal-scale phenology and seasonal climate drivers of migratory baleen whales in a rapidly warming marine ecosystem","interactions":[],"lastModifiedDate":"2022-08-02T14:40:28.06704","indexId":"70232234","displayToPublicDate":"2022-06-07T09:04:18","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Decadal-scale phenology and seasonal climate drivers of migratory baleen whales in a rapidly warming marine ecosystem","docAbstract":"

Species' response to rapid climate change can be measured through shifts in timing of recurring biological events, known as phenology. The Gulf of Maine is one of the most rapidly warming regions of the ocean, and thus an ideal system to study phenological and biological responses to climate change. A better understanding of climate-induced changes in phenology is needed to effectively and adaptively manage human-wildlife conflicts. Using data from a 20+ year marine mammal observation program, we tested the hypothesis that the phenology of large whale habitat use in Cape Cod Bay has changed and is related to regional-scale shifts in the thermal onset of spring. We used a multi-season occupancy model to measure phenological shifts and evaluate trends in the date of peak habitat use for North Atlantic right (Eubalaena glacialis), humpback (Megaptera novaeangliae), and fin (Balaenoptera physalus) whales. The date of peak habitat use shifted by +18.1 days (0.90 days/year) for right whales and +19.1 days (0.96 days/year) for humpback whales. We then evaluated interannual variability in peak habitat use relative to thermal spring transition dates (STD), and hypothesized that right whales, as planktivorous specialist feeders, would exhibit a stronger response to thermal phenology than fin and humpback whales, which are more generalist piscivorous feeders. There was a significant negative effect of western region STD on right whale habitat use, and a significant positive effect of eastern region STD on fin whale habitat use indicating differential responses to spatial seasonal conditions. Protections for threatened and endangered whales have been designed to align with expected phenology of habitat use. Our results show that whales are becoming mismatched with static seasonal management measures through shifts in their timing of habitat use, and they suggest that effective management strategies may need to alter protections as species adapt to climate change.

","language":"English","publisher":"Wiley","doi":"10.1111/gcb.16225","usgsCitation":"Pendleton, D., Tingley, M., Ganley, L., Friedland, K., Mayo, C., Brown, M., McKenna, B., Jordaan, A., and Staudinger, M., 2022, Decadal-scale phenology and seasonal climate drivers of migratory baleen whales in a rapidly warming marine ecosystem: Global Change Biology, v. 28, no. 16, p. 4989-5005, https://doi.org/10.1111/gcb.16225.","productDescription":"17 p.","startPage":"4989","endPage":"5005","ipdsId":"IP-135322","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":447501,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/gcb.16225","text":"External Repository"},{"id":402267,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.6640625,\n 41.72213058512578\n ],\n [\n -70.02685546875,\n 41.72213058512578\n ],\n [\n -70.02685546875,\n 42.261049162113856\n ],\n [\n -70.6640625,\n 42.261049162113856\n ],\n [\n -70.6640625,\n 41.72213058512578\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"16","noUsgsAuthors":false,"publicationDate":"2022-06-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Pendleton, Dan","contributorId":292480,"corporation":false,"usgs":false,"family":"Pendleton","given":"Dan","email":"","affiliations":[{"id":48127,"text":"Anderson Cabot Center for Marine Life","active":true,"usgs":false}],"preferred":false,"id":844744,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tingley, Morgan","contributorId":292481,"corporation":false,"usgs":false,"family":"Tingley","given":"Morgan","affiliations":[],"preferred":false,"id":844745,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganley, Laura","contributorId":292482,"corporation":false,"usgs":false,"family":"Ganley","given":"Laura","email":"","affiliations":[],"preferred":false,"id":844746,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Friedland, Kevin","contributorId":292483,"corporation":false,"usgs":false,"family":"Friedland","given":"Kevin","affiliations":[],"preferred":false,"id":844747,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mayo, Charlie","contributorId":292484,"corporation":false,"usgs":false,"family":"Mayo","given":"Charlie","email":"","affiliations":[],"preferred":false,"id":844748,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brown, Moria","contributorId":292485,"corporation":false,"usgs":false,"family":"Brown","given":"Moria","email":"","affiliations":[],"preferred":false,"id":844749,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McKenna, Brigid","contributorId":292486,"corporation":false,"usgs":false,"family":"McKenna","given":"Brigid","email":"","affiliations":[],"preferred":false,"id":844750,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jordaan, Adrian","contributorId":292487,"corporation":false,"usgs":false,"family":"Jordaan","given":"Adrian","affiliations":[],"preferred":false,"id":844751,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Staudinger, Michelle 0000-0002-4535-2005","orcid":"https://orcid.org/0000-0002-4535-2005","contributorId":205971,"corporation":false,"usgs":true,"family":"Staudinger","given":"Michelle","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":844752,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70232334,"text":"70232334 - 2022 - The Pliocene-to-present course of the Tennessee River","interactions":[],"lastModifiedDate":"2022-11-16T16:55:58.712626","indexId":"70232334","displayToPublicDate":"2022-06-07T07:24:56","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2309,"text":"Journal of Geology","active":true,"publicationSubtype":{"id":10}},"title":"The Pliocene-to-present course of the Tennessee River","docAbstract":"

The Tennessee River, a primary drainage of the southern Appalachians and significant sediment source for the Gulf of Mexico, is generally considered to be the product of captures that rerouted the river from a more direct gulfward course. Sedimentary and genetic evidence indicates that a paleo-Tennessee flowed into the Mobile Basin through the late Miocene, although alternate models propose other redirections of the river. We constrain the river course’s age by dating terraces near Pickwick, Tennessee, with cosmogenic 26Al/10Be isochron burial dating. We find that the river’s present path dates to at least the early Pliocene.

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\"}}]}","volume":"130","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Odom, William Elijah 0000-0001-8577-5056","orcid":"https://orcid.org/0000-0001-8577-5056","contributorId":292616,"corporation":false,"usgs":true,"family":"Odom","given":"William","email":"","middleInitial":"Elijah","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":845280,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Granger, Darryl E.","contributorId":191610,"corporation":false,"usgs":false,"family":"Granger","given":"Darryl","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":845281,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70236869,"text":"70236869 - 2022 - Grassy–herbaceous land moderates regional climate effects on honey bee colonies in the Northcentral US","interactions":[],"lastModifiedDate":"2022-09-21T14:04:20.834365","indexId":"70236869","displayToPublicDate":"2022-06-07T07:19:41","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Grassy–herbaceous land moderates regional climate effects on honey bee colonies in the Northcentral US","docAbstract":"

The lack of seasonally sustained floral resources (i.e. pollen and nectar) is considered a primary global threat to pollinator health. However, the ability to predict the abundance of flowering resources for pollinators based upon climate, weather, and land cover is difficult due to insufficient monitoring over adequate spatial and temporal scales. Here we use spatiotemporally distributed honey bee hive scales that continuously measure hive weights as a standardized method to assess nectar intake. We analyze late summer colony weight gain as the response variable in a random forest regression model to determine the importance of climate, weather, and land cover on honey bee colony productivity. Our random forest model predicted resource acquisition by honey bee colonies with 71% accuracy, highlighting the detrimental effects of warm, wet regions in the Northcentral United States on nectar intake, as well as the detrimental effect of years with high growing degree day accumulation. Our model also predicted that grassy–herbaceous natural land had a positive effect on the summer nectar flow and that large areas of natural grassy–herbaceous land around apiaries can moderate the detrimental effects of warm, wet climates. These patterns characterize multi-scale ecological processes that constrain the quantity and quality of pollinator nutritional resources. That is, broad climate conditions constrain regional floral communities, while land use and weather act to further modify the quantity and quality of pollinator nutritional resources. Observing such broad-scale trends demonstrates the potential for utilizing hive scales to monitor the effects of climate change on landscape-level floral resources for pollinators. The interaction of climate and land use also present an opportunity to manage for climate-resilient landscapes that support pollinators through abundant floral resources under climate change.

","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/ac7063","usgsCitation":"Quinlan, G., Sponsler, D.B., Gaines-Day, H., McMinn-Sauder, H., Otto, C., Smart, A., Colin, T., Gratton, C., Isaacs, R., Johnson, R., Milbrath, M.O., and Grozinger, C.M., 2022, Grassy–herbaceous land moderates regional climate effects on honey bee colonies in the Northcentral US: Environmental Research Letters, v. 17, 064036, 11 p., https://doi.org/10.1088/1748-9326/ac7063.","productDescription":"064036, 11 p.","ipdsId":"IP-139777","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":447509,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ac7063","text":"Publisher Index Page"},{"id":407134,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Minnesota, North Dakota, Ohio, Pennsylvania, South Dakota, 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Wisconsin","active":true,"usgs":false}],"preferred":false,"id":852422,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McMinn-Sauder, Harper","contributorId":296755,"corporation":false,"usgs":false,"family":"McMinn-Sauder","given":"Harper","email":"","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":852423,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":852424,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smart, Autumn","contributorId":287583,"corporation":false,"usgs":false,"family":"Smart","given":"Autumn","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":852425,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Colin, Theotime","contributorId":296880,"corporation":false,"usgs":false,"family":"Colin","given":"Theotime","email":"","affiliations":[],"preferred":false,"id":852632,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gratton, Claudio","contributorId":296881,"corporation":false,"usgs":false,"family":"Gratton","given":"Claudio","email":"","affiliations":[],"preferred":false,"id":852633,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Isaacs, Rufus","contributorId":287577,"corporation":false,"usgs":false,"family":"Isaacs","given":"Rufus","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":852634,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Johnson, Reed","contributorId":296882,"corporation":false,"usgs":false,"family":"Johnson","given":"Reed","email":"","affiliations":[],"preferred":false,"id":852635,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Milbrath, Meghan O.","contributorId":296883,"corporation":false,"usgs":false,"family":"Milbrath","given":"Meghan","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":852636,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Grozinger, Christina M.","contributorId":214374,"corporation":false,"usgs":false,"family":"Grozinger","given":"Christina","email":"","middleInitial":"M.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":852426,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70234203,"text":"70234203 - 2022 - Ephemeral stream network extraction from lidar-derived elevation and topographic attributes in urban and forested landscapes","interactions":[],"lastModifiedDate":"2022-08-12T16:57:52.070812","indexId":"70234203","displayToPublicDate":"2022-06-07T06:33:25","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Ephemeral stream network extraction from lidar-derived elevation and topographic attributes in urban and forested landscapes","docAbstract":"

Under-representations of headwater channels in digital stream networks can result in uncertainty in the magnitude of headwater habitat loss, stream burial, and watershed function. Increased availability of high-resolution (<2 m) elevation data makes the delineation of headwater channels more attainable. In this study, elevation data derived from light detection and ranging was used to predict ephemeral stream networks across a forested and urban watershed in the Maryland Piedmont USA. A method was developed using topographic openness (TO) and wetness index to remotely predict the extent of stream networks. Predicted networks were compared against a comprehensive field survey of the ephemeral network in each watershed to evaluate performance. Comparisons were also made to the U.S. Geological Survey National Hydrography Dataset (NHD) and a flow accumulation approach where a single drainage area threshold defined channel initiation. Although the NHD and flow accumulation methods resulted in low commission errors, omission errors were highest in these networks. The TO-based networks detected a larger number of ephemeral channels, but with higher commission error. Small ephemeral channels with less defined banks or originating at groundwater seeps were difficult to detect in all methods. Comparisons between forested and urban watersheds also highlight the difficulty of identifying headwater channels using topographic attributes in human-modified landscapes.

","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.13012","usgsCitation":"Metes, M.J., Jones, D.K., Baker, M.E., Miller, A.J., Hogan, D.M., Loperfido, J., and Hopkins, K.G., 2022, Ephemeral stream network extraction from lidar-derived elevation and topographic attributes in urban and forested landscapes: Journal of the American Water Resources Association, v. 58, no. 4, p. 547-565, https://doi.org/10.1111/1752-1688.13012.","productDescription":"19 p.","startPage":"547","endPage":"565","ipdsId":"IP-109164","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":447514,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/11603/25141","text":"External Repository"},{"id":404741,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Piedmont region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.3,\n 39.2333\n ],\n [\n -77.25,\n 39.2333\n ],\n [\n -77.25,\n 39.2833\n ],\n [\n -77.3,\n 39.2833\n ],\n [\n -77.3,\n 39.2333\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"58","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-06-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Metes, Marina J. 0000-0002-6797-9837","orcid":"https://orcid.org/0000-0002-6797-9837","contributorId":204835,"corporation":false,"usgs":true,"family":"Metes","given":"Marina","middleInitial":"J.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":848166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Daniel K. 0000-0003-0724-8001 dkjones@usgs.gov","orcid":"https://orcid.org/0000-0003-0724-8001","contributorId":4959,"corporation":false,"usgs":true,"family":"Jones","given":"Daniel","email":"dkjones@usgs.gov","middleInitial":"K.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":848167,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baker, Matthew E.","contributorId":149189,"corporation":false,"usgs":false,"family":"Baker","given":"Matthew","email":"","middleInitial":"E.","affiliations":[{"id":17665,"text":"Department of Geography and Environmental Systems, University of Maryland, Baltimore County, Baltimore, Maryland, US","active":true,"usgs":false}],"preferred":false,"id":848168,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Andrew J.","contributorId":207595,"corporation":false,"usgs":false,"family":"Miller","given":"Andrew","email":"","middleInitial":"J.","affiliations":[{"id":15309,"text":"University of Maryland Baltimore County","active":true,"usgs":false}],"preferred":false,"id":848169,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hogan, Dianna M. 0000-0003-1492-4514 dhogan@usgs.gov","orcid":"https://orcid.org/0000-0003-1492-4514","contributorId":131137,"corporation":false,"usgs":true,"family":"Hogan","given":"Dianna","email":"dhogan@usgs.gov","middleInitial":"M.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":848170,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loperfido, J.V.","contributorId":294508,"corporation":false,"usgs":false,"family":"Loperfido","given":"J.V.","affiliations":[{"id":63581,"text":"Stormwater and GIS Services Division of the Public Works Department, City of Durham, NC","active":true,"usgs":false}],"preferred":false,"id":848171,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hopkins, Kristina G. 0000-0003-1699-9384 khopkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1699-9384","contributorId":195604,"corporation":false,"usgs":true,"family":"Hopkins","given":"Kristina","email":"khopkins@usgs.gov","middleInitial":"G.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":848172,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70232109,"text":"sir20225006 - 2022 - Tracking heat in the Willamette River system, Oregon","interactions":[],"lastModifiedDate":"2026-04-08T17:12:43.533209","indexId":"sir20225006","displayToPublicDate":"2022-06-06T14:10:06","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5006","displayTitle":"Tracking Heat in the Willamette River System, Oregon","title":"Tracking heat in the Willamette River system, Oregon","docAbstract":"

The Willamette River Basin in northwestern Oregon is home to several cold-water fish species whose habitat has been altered by the Willamette Valley Project, a system of 13 dams and reservoirs operated by the U.S. Army Corps of Engineers. Water-resource managers use a variety of flow- and temperature-management strategies to ameliorate the effects of upstream Willamette Valley Project dams on the habitat and viability of these anadromous and native fish. In this study, new capabilities were added to the CE-QUAL-W2 two-dimensional flow and water-quality model to inform those flow- and temperature-management strategies by tracking the quantities and ages of water and heat from individual upstream sources to downstream locations in the Willamette River system. Specifically, the fraction of water and heat attributable to upstream dam releases or other water inputs, and the fraction of heat sourced from environmental heat fluxes across the water and sediment surfaces, were tracked and quantified in the river at all locations and times simulated by the model. Applying the updated CE-QUAL-W2 models to the Willamette River system for the months of March through October in the years 2011 (cool and wet), 2015 (hot and dry), and 2016 (warm and somewhat dry) demonstrated that the influence of upstream dam releases on downstream water temperature diminished within a few days as water moved downstream. At sites that are roughly two or more days of travel from upstream dams (Albany and downstream), the July–August fraction of riverine heat content that could be tracked back to upstream dam releases typically diminished to less than 20 percent, despite the fact that roughly 50 percent of July–August streamflow could be attributed to upstream dam releases at the same sites. In contrast, the fraction of riverine heat content that could be attributed to environmental energy fluxes continued to increase with downstream distance, from about 59 to 67 percent at Albany during July–August to 62 to 73 percent at Keizer and 68 to 79 percent at Newberg.

At locations sufficiently far downstream, upstream dam releases affect water temperature mainly through a decrease in travel time (less time for environmental heat fluxes to warm the river during summer) and an increase in thermal mass (more water to dilute and buffer incoming heat fluxes) rather than through the simple transport of heat content (water temperature) released from the dams. This concept was explored not only for the baseline conditions that occurred in March–October of 2011, 2015, and 2016, but also for a hypothetical high-flow release during August 2016 and an actual high-flow release during August 2017. In these high-flow releases, an extra 2,500 cubic feet per second (roughly) was released from Dexter Dam on the Middle Fork Willamette River, and downstream effects were measured (2017, actual) and simulated (2016, hypothetical). Results of the simulations were consistent with insights gained from the baseline conditions, such that temperature changes caused by flow augmentation were substantial in upstream reaches (measured cooling of about 1.5 °C near Harrisburg [43 miles downstream] and Albany [84 miles downstream] in 2017, and cooling of about 0.5 °C near Albany in 2016) and diminished farther downstream, but still measurable (more than a few tenths of a degree Celsius) even at Newberg, which is about 154 miles downstream. The direct downstream effects of dam releases on the river heat content attributable to those releases were increased by the hypothetical flow augmentation, with increases of 20 percent at Harrisburg and 12 percent at Keizer. Even with a decreased influence of environmental energy fluxes on river heat content, however, the fraction of heat content attributable to such fluxes was still more than 50 percent at and downstream of Albany and more than 70 percent at Newberg, where the river temperature was less affected by upstream dam-release temperatures and instead was affected primarily by a decreased travel time and increased thermal mass.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225006","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Portland District","usgsCitation":"Rounds, S.A., and Stratton Garvin, L.E., 2022, Tracking heat in the Willamette River system, Oregon: U.S. Geological Survey Scientific Investigations Report 2022–5006, 47 p., https://doi.org/10.3133/sir20225006.","productDescription":"Report: vii, 47 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-119740","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":401781,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P908DXKH","text":"USGS data release","description":"USGS data release","linkHelpText":"CE-QUAL-W2 models for the Willamette River and major tributaries below U.S. Army Corps of Engineers dams—2011, 2015, and 2016: U.S. Geological Survey data release, https://doi.org/10.5066/P908DXKH."},{"id":401780,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5006/sir20225006.pdf","text":"Report","size":"5.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5006"},{"id":401779,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5006/coverthb.jpg"},{"id":401783,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225035","text":"SIR 2022-5035 —","description":"SIR 2022-5035","linkHelpText":"The thermal landscape of the Willamette River—Patterns and controls on stream temperature and implications for flow management and cold-water salmonids"},{"id":401782,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221017","text":"OFR 2022-1017 —","description":"OFR 2022-1017","linkHelpText":"Updates to models of streamflow and water temperature for 2011, 2015, and 2016 in rivers of the Willamette River Basin, Oregon"},{"id":401784,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225034","text":"SIR 2022-5034 —","description":"SIR 2022-5034","linkHelpText":"Assessment of habitat availability for juvenile Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) in the Willamette River, Oregon"},{"id":401870,"rank":8,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5006/sir20225006.XML"},{"id":401869,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5006/images"},{"id":502294,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113159.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.67858886718747,\n 43.572431747409695\n ],\n [\n -121.44836425781247,\n 43.572431747409695\n ],\n [\n -121.44836425781247,\n 45.7905094675247\n ],\n [\n -123.67858886718747,\n 45.7905094675247\n ],\n [\n -123.67858886718747,\n 43.572431747409695\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201

","tableOfContents":"","publishedDate":"2022-06-06","noUsgsAuthors":false,"publicationDate":"2022-06-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844225,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stratton Garvin, Laurel E. 0000-0001-8567-8619 lstratton@usgs.gov","orcid":"https://orcid.org/0000-0001-8567-8619","contributorId":270182,"corporation":false,"usgs":true,"family":"Stratton Garvin","given":"Laurel","email":"lstratton@usgs.gov","middleInitial":"E.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844226,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70232108,"text":"sir20225035 - 2022 - The thermal landscape of the Willamette River—Patterns and controls on stream temperature and implications for flow management and cold-water salmonids","interactions":[],"lastModifiedDate":"2026-04-09T17:21:11.420138","indexId":"sir20225035","displayToPublicDate":"2022-06-06T13:31:56","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5035","displayTitle":"The Thermal Landscape of the Willamette River—Patterns and Controls on Stream Temperature and Implications for Flow Management and Cold-Water Salmonids","title":"The thermal landscape of the Willamette River—Patterns and controls on stream temperature and implications for flow management and cold-water salmonids","docAbstract":"

Water temperature is a primary control on the health, diversity, abundance, and distribution of aquatic species, but thermal degradation resulting from anthropogenic influences on rivers is a challenge to threatened species worldwide. In the Willamette River Basin, northwestern Oregon, spring-run Chinook salmon (Oncorhynchus tshawytscha) and winter-run steelhead (O. mykiss) are formerly abundant cold-water-adapted species that are now protected under the Endangered Species Act. Among the challenges to the health of cold-water salmonids in the Willamette River Basin, disruptions in the seasonal patterns of stream temperature imposed by 13 large, multipurpose dams on tributaries to the Willamette River, as well as temperatures routinely in excess of regulatory limits in the Willamette River Basin, are contributing factors. To better understand controls on stream temperature, the sensitivity of stream temperature to flow augmentation as a management tool for suppressing high temperatures, and the implications for threatened salmonids, this study used a two-dimensional hydrodynamic and water-quality model (CE-QUAL-W2) to investigate spatial and temporal patterns of stream temperature in the Willamette River Basin. This study focused on the upper 160.4 river miles of the Willamette River from the confluence of the Middle Fork and Coast Fork Willamette Rivers (river mile 187.2) to Willamette Falls (river mile 26.8), three representative climate years (2011, a cool and wet year; 2015, an extremely hot and dry year; and 2016, a moderately hot and dry year), and a series of flow-augmentation scenarios. Model results show that the Willamette River upstream from Willamette Falls is divisible into four characteristic “thermal reaches” with similar thermal patterns, depending on tributary input, warming rate, and the timing of thermal response. In general, the Willamette River warms downstream during spring and summer, but patterns are complex, influenced by tributary inflows, and seasonally variable. Except in cool wet years (as illustrated by 2011), modeling suggests that adversely warm conditions for spring-run Chinook salmon are extensive from June or July through August. The thermal influence of flow augmentation from dam storage on four tributaries with U.S. Army Corps of Engineers dams varies spatially along the Willamette River, seasonally, and in magnitude, depending on a range of factors like distance from the Willamette River, the temperature of dam outflow, and the thermal template of tributary reaches controlling stream temperature adjustment to environmental heat fluxes. Modeling suggests that targeted flow management (via augmentation from dam storage) can reduce the extent and duration of thermally stressful conditions for Chinook salmon for short periods, but modeling suggests that flow augmentation is limited in its ability to fundamentally alter the “thermal landscape” (the entire range of temperature variation in a river system over space and time) of the Willamette River. While this research provides general insights into the thermal landscape of the Willamette River and its sensitivity to flow management, additional investigation into the thermal landscape of tributaries downstream from U.S. Army Corps of Engineers dams, as well as the thermal management of reservoirs, storage availability, and dam outflows, would be necessary to target specific management actions for supporting specified rearing or migration conditions for spring-run Chinook salmon and other cold-water-adapted species in the Willamette River Basin.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225035","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Portland District","usgsCitation":"Stratton Garvin, L.E., and Rounds, S.A., 2022, The thermal landscape of the Willamette River—Patterns and controls on stream temperature and implications for flow management and cold-water salmonids: U.S. Geological Survey Scientific Investigations Report 2022–5035, 43 p., https://doi.org/10.3133/sir20225035.","productDescription":"Report: vi, 43 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-126305","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":401868,"rank":8,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5035/sir20225035.XML"},{"id":401867,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5035/images"},{"id":401763,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5035/coverthb.jpg"},{"id":401769,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225034","text":"SIR 2022-5034 —","description":"SIR 2022-5034","linkHelpText":"Assessment of habitat availability for juvenile Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) in the Willamette River, Oregon"},{"id":401768,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221017","text":"OFR 2022-1017 —","description":"OFR 2022-1017","linkHelpText":"Updates to models of streamflow and water temperature for 2011, 2015, and 2016 in rivers of the Willamette River Basin, Oregon"},{"id":401765,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P908DXKH","text":"USGS data release","description":"USGS data release","linkHelpText":"CE-QUAL-W2 models for the Willamette River and major tributaries below U.S. Army Corps of Engineers dams—2011, 2015, and 2016"},{"id":401764,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5035/sir20225035.pdf","text":"Report","size":"5.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5035"},{"id":502391,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113158.htm","linkFileType":{"id":5,"text":"html"}},{"id":401767,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225006","text":"SIR 2022-5006 —","description":"SIR 2022-5006","linkHelpText":"Tracking heat in the Willamette River system, Oregon"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.67858886718747,\n 43.572431747409695\n ],\n [\n -121.44836425781247,\n 43.572431747409695\n ],\n [\n -121.44836425781247,\n 45.7905094675247\n ],\n [\n -123.67858886718747,\n 45.7905094675247\n ],\n [\n -123.67858886718747,\n 43.572431747409695\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201

","tableOfContents":"","publishedDate":"2022-06-06","noUsgsAuthors":false,"publicationDate":"2022-06-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Stratton Garvin, Laurel E. 0000-0001-8567-8619 lstratton@usgs.gov","orcid":"https://orcid.org/0000-0001-8567-8619","contributorId":270182,"corporation":false,"usgs":true,"family":"Stratton Garvin","given":"Laurel","email":"lstratton@usgs.gov","middleInitial":"E.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844223,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844224,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70232107,"text":"sir20225034 - 2022 - Assessment of habitat availability for juvenile Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) in the Willamette River, Oregon","interactions":[],"lastModifiedDate":"2022-06-07T11:16:08.029566","indexId":"sir20225034","displayToPublicDate":"2022-06-06T12:46:54","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5034","displayTitle":"Assessment of Habitat Availability for Juvenile Chinook Salmon (Oncorhynchus tshawytscha) and Steelhead (O. mykiss) in the Willamette River, Oregon","title":"Assessment of habitat availability for juvenile Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) in the Willamette River, Oregon","docAbstract":"

The Willamette River, Oregon, is home to two salmonid species listed as threatened under the Endangered Species Act, Upper WIllamette River spring Chinook salmon (Oncorhynchus tshawytscha) and Upper Willamette River winter steelhead (O. mykiss). Streamflow in the Willamette River is regulated by upstream dams, 13 of which are operated by the U.S. Army Corps of Engineers (USACE) as part of the Willamette Valley Project. In 2008, these dams were determined to have a deleterious effect on Endangered Species Act-listed salmonids, resulting in USACE taking actions to mitigate those effects. Mitigation actions included setting seasonal streamflow targets at various locations along the river to improve survival and migration of juvenile salmonids. Although these targets were established with the best available information at the time, recent data and models have advanced understanding of Willamette River bathymetric, hydraulic, and thermal conditions, allowing for a more robust analysis of the effect of streamflow on downstream habitat. This study integrates those recent advances to build high-resolution models of usable habitat for juvenile Chinook salmon and steelhead to assess variation in spatial and seasonal patterns of habitat availability. Specifically, this study develops detailed maps of habitat availability for juvenile Chinook salmon and steelhead for two size classes (fry and pre-smolt). Habitat availability is modeled in a three-step process whereby (1) two-dimensional hydraulic models are paired with literature-supplied data on habitat preferences to create spatially explicit maps of rearing habitats for a wide range of streamflows; (2) reach-specific relations between streamflow and habitat area are developed and paired with streamgage records to create habitat time series for 2011, 2015, and 2016, which reflect “cool and wet,” “hot and dry,” and “warm but average precipitation” conditions, respectively; (3) temperature models are coupled with literature-based thermal thresholds to determine time periods and locations along the river corridor when rearing habitat has optimal, harmful, or lethal temperature conditions; (4) finally, habitat availability is summarized at several spatial scales to characterize longitudinal and seasonal patterns.

Findings show that modeled area of rearing habitat for Chinook salmon and steelhead responds non-uniformly to streamflow, where habitat in some reaches of the Willamette River consistently increase with additional streamflow, while in other reaches, habitat area decreases when streamflows increase from low to moderate flows. Modeled differences in flow-habitat relations are primarily explained by local geomorphology in each reach and resulting hydraulic conditions that arise with different streamflows. These are most pronounced when comparing laterally active, multi-channel reaches upstream from Corvallis with downstream reaches that are laterally stable with single-channel planforms. The reaches upstream from Corvallis generally have more habitat available per unit stream distance than downstream reaches, but all reaches display greatest amounts of habitat at the highest streamflows. Finally, results show that warm water temperature in summer greatly decreases the utility of habitat available to the focal species, particularly downstream from Corvallis. Together, these findings serve to inform flow management by characterizing spatial and seasonal patterns of habitat availability for juvenile spring Chinook salmon and winter steelhead and provide a quantitative assessment of the effects of streamflow on rearing habitat.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225034","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"White, J.S., Peterson, J.T., Stratton Garvin, L.E., Kock, T.J., and Wallick, J.R., 2022, Assessment of habitat availability for juvenile Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) in the Willamette River, Oregon: U.S. Geological Survey Scientific Investigations Report 2022–5034, 44 p., https://doi.org/10.3133/sir20225034.","productDescription":"viii, 44 p.","onlineOnly":"Y","ipdsId":"IP-130018","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":401758,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5034/coverthb.jpg"},{"id":401759,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5034/sir20225034.pdf","text":"Report","size":"13.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5034"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.40942382812501,\n 44.05995928349327\n ],\n [\n -122.2943115234375,\n 44.05995928349327\n ],\n [\n -122.2943115234375,\n 45.66780526567164\n ],\n [\n -123.40942382812501,\n 45.66780526567164\n ],\n [\n -123.40942382812501,\n 44.05995928349327\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201

","tableOfContents":"","publishedDate":"2022-06-06","noUsgsAuthors":false,"publicationDate":"2022-06-06","publicationStatus":"PW","contributors":{"authors":[{"text":"White, James S. 0000-0002-7255-3785 jameswhite@usgs.gov","orcid":"https://orcid.org/0000-0002-7255-3785","contributorId":290253,"corporation":false,"usgs":false,"family":"White","given":"James","email":"jameswhite@usgs.gov","middleInitial":"S.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":844218,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, James T. 0000-0002-7709-8590","orcid":"https://orcid.org/0000-0002-7709-8590","contributorId":204948,"corporation":false,"usgs":false,"family":"Peterson","given":"James","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":844219,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stratton Garvin, Laurel E. 0000-0001-8567-8619 lstratton@usgs.gov","orcid":"https://orcid.org/0000-0001-8567-8619","contributorId":270182,"corporation":false,"usgs":true,"family":"Stratton Garvin","given":"Laurel","email":"lstratton@usgs.gov","middleInitial":"E.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844220,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kock, Tobias J. 0000-0001-8976-0230 tkock@usgs.gov","orcid":"https://orcid.org/0000-0001-8976-0230","contributorId":3038,"corporation":false,"usgs":true,"family":"Kock","given":"Tobias","email":"tkock@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":844221,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wallick, J. Rose 0000-0002-9392-272X rosewall@usgs.gov","orcid":"https://orcid.org/0000-0002-9392-272X","contributorId":3583,"corporation":false,"usgs":true,"family":"Wallick","given":"J. Rose","email":"rosewall@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844222,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70232106,"text":"ofr20221017 - 2022 - Updates to models of streamflow and water temperature for 2011, 2015, and 2016 in rivers of the Willamette River Basin, Oregon","interactions":[],"lastModifiedDate":"2026-03-27T19:55:47.696889","indexId":"ofr20221017","displayToPublicDate":"2022-06-06T12:07:08","publicationYear":"2022","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":"2022-1017","displayTitle":"Updates to Models of Streamflow and Water Temperature for 2011, 2015, and 2016 in Rivers of the Willamette River Basin, Oregon","title":"Updates to models of streamflow and water temperature for 2011, 2015, and 2016 in rivers of the Willamette River Basin, Oregon","docAbstract":"

Mechanistic river models capable of simulating hydrodynamics and stream temperature are valuable tools for investigating thermal conditions and their relation to streamflow in river basins where upstream water storage and management decisions have an important influence on river reaches with threatened fish populations. In the Willamette River Basin in northwestern Oregon, a two-dimensional, hydrodynamic water-quality model (CE‑QUAL‑W2) has been used to investigate the downstream effects of dam operations and other anthropogenic influences on stream temperature. By simulating the managed releases of water and various temperatures from the large Willamette Valley Project dams upstream of the modeling domain, these models can be used to investigate riverine temperature conditions and their relation to streamflow to determine where and when conditions are most challenging for threatened fish populations and how dam operations and flow management can affect and optimize thermal conditions in the river.

The original models were initially developed to simulate conditions in spring–autumn of 2001 and 2002. This report documents (1) the upgrade of the river models to CE‑QUAL‑W2 version 4.2 and (2) the update of those models to simulate conditions that occurred from March through October of 2011, 2015, and 2016. These years were selected to represent a range of climatic and hydrologic conditions in the Willamette River Basin, including a “cool, wet” year (2011), a “hot, dry” year (2015), and a “normal” year (2016). Six submodels comprise the modeling system updated in this report; each submodel can be run independently or run with the others as a system. These models include the Coast Fork and Middle Fork Willamette River submodel, which includes the Coast Fork and Middle Fork Willamette Rivers, the Row River, and Fall Creek; the McKenzie River submodel, which includes the South Fork McKenzie River downstream of Cougar Dam and the McKenzie River from its confluence with the South Fork McKenzie River to its mouth; the South Santiam River submodel, which comprises the South Santiam River from Foster Dam to the Santiam River; the North Santiam and Santiam River submodel, which includes the Santiam River and the North Santiam River downstream of Big Cliff Dam; the Upper Willamette River submodel, which includes the Willamette River from Eugene to Salem; and the Middle Willamette River submodel, which includes the Willamette River from Salem to Willamette Falls near Oregon City.

The models included in this report were originally developed, calibrated, and documented by other researchers. As part of the model updates described here, some model parameters were adjusted to improve stability and decrease runtime. Boundary conditions including meteorological, hydrologic, and thermal parameters were developed and updated for model years 2011, 2015, and 2016. In many cases, the data sources used to drive the 2001 and 2002 models were no longer available, which required the use of new data sources, the determination of a proxy record, or the development of appropriate estimation techniques. Goodness-of-fit statistics for the updated models show a good model fit, with the models simulating subdaily water temperatures at most comparable locations with a mean absolute error of generally less than 1 °C and often nearing 0.5 °C, depending on the individual submodel, and a reasonably low bias. The subdaily mean error for the South Santiam River submodel produced the highest bias of any of the submodels. Goodness-of-fit statistics indicate that the results may be biased cool (ranging from -0.43 °C in 2016 to -0.80 °C in 2011 for subdaily results), but the only water temperature data available for comparison on the South Santiam River is itself estimated, and those estimates are known to be too high in summer. Depending on future modeling needs, that submodel may warrant further refinement, along with additional data collection to properly define and minimize any model bias.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221017","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Portland District","usgsCitation":"Stratton Garvin, L.E., Rounds, S.A., and Buccola, N.L., 2022, Updates to models of streamflow and water temperature for 2011, 2015, and 2016 in rivers of the Willamette River Basin, Oregon: U.S. Geological Survey Open-File Report 2022–1017, 73 p., https://doi.org/10.3133/ofr20221017.","productDescription":"Report: x, 73 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-119723","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":401872,"rank":8,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1017/ofr20221017.XML"},{"id":401871,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1017/images"},{"id":401815,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225035","text":"SIR 2022-5035 —","linkHelpText":"The thermal landscape of the Willamette River—Patterns and controls on stream temperature and implications for flow management and cold-water salmonids"},{"id":401814,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225034","text":"SIR 2022-5034 —","linkHelpText":"Assessment of habitat availability for juvenile Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss) in the Willamette River, Oregon"},{"id":501762,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113157.htm","linkFileType":{"id":5,"text":"html"}},{"id":401754,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1017/coverthb.jpg"},{"id":401755,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1017/ofr20221017.pdf","text":"Report","size":"10.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1017"},{"id":401756,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P908DXKH","text":"USGS data release","description":"USGS data release","linkHelpText":"CE-QUAL-W2 models for the Willamette River and major tributaries below U.S. Army Corps of Engineers dams—2011, 2015, and 2016"},{"id":401813,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225006","text":"SIR 2022-5006 —","linkHelpText":"Tracking heat in the Willamette River system, Oregon"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.134765625,\n 42.779275360241904\n ],\n [\n -120.673828125,\n 42.779275360241904\n ],\n [\n -120.673828125,\n 45.9511496866914\n ],\n [\n -123.134765625,\n 45.9511496866914\n ],\n [\n -123.134765625,\n 42.779275360241904\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201

","tableOfContents":"","publishedDate":"2022-06-06","noUsgsAuthors":false,"publicationDate":"2022-06-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Stratton Garvin, Laurel E. 0000-0001-8567-8619 lstratton@usgs.gov","orcid":"https://orcid.org/0000-0001-8567-8619","contributorId":270182,"corporation":false,"usgs":true,"family":"Stratton Garvin","given":"Laurel","email":"lstratton@usgs.gov","middleInitial":"E.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844215,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buccola, Norman L. 0000-0002-9590-2458 nbuccola@usgs.gov","orcid":"https://orcid.org/0000-0002-9590-2458","contributorId":139096,"corporation":false,"usgs":true,"family":"Buccola","given":"Norman","email":"nbuccola@usgs.gov","middleInitial":"L.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844217,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70232187,"text":"70232187 - 2022 - Maize yield forecasts for Sub-Saharan Africa using Earth Observation data and machine learning","interactions":[],"lastModifiedDate":"2022-06-10T11:47:56.19594","indexId":"70232187","displayToPublicDate":"2022-06-06T06:44:49","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5055,"text":"Global Food Security","active":true,"publicationSubtype":{"id":10}},"title":"Maize yield forecasts for Sub-Saharan Africa using Earth Observation data and machine learning","docAbstract":"

Food insecurity continues to grow in Sub-Saharan Africa (SSA). In 2019, chronically malnourished people numbered nearly 240 million, or 20% of the population in SSA. Globally, numerous efforts have been made to anticipate potential droughts, crop conditions, and food shortages in order to improve early warning and risk management for food insecurity. To support this goal, we develop an Earth Observation (EO) and machine-learning-based operational, subnational maize yield forecast system and evaluate its out-of-sample forecast skills during the growing seasons for Kenya, Somalia, Malawi, and Burkina Faso. In general, forecast skills improve substantially during the vegetative growth period (VP) and gradually during the reproductive development period (RP). Thus, mid-season assessment can provide effective early warning months before harvest. Skillful forecasts (Nash Sutcliffe Efficiency (NSE) > 0.6 and Mean Absolute Percentage Error (MAPE) < 20%) appear approximately two dekads after the VP; for example, skillful forecasts appear in May in Kenya and Somalia, January in Malawi, and July in Burkina Faso. During model development, effective EO features are also identified, such as precipitation and available water during VP, and dry days and extreme temperatures in early VP. Compared to monthly standard EO features, sub-monthly (dekadal), non-standard, and serial EO features significantly improve forecast skills by ＋ 0.3 NSE and -10% of MAPE, demonstrating the ability to precisely and effectively capture favorable or detrimental crop development conditions. Finally, skillful forecasts and practical utility are demonstrated in the recent normal and dry years in each region. Overall, the developed yield forecasting system can provide skillful predictions during the growing season, supporting regional and international agricultural decision-making processes, including informing food-security planning and management, thereby helping to mitigate food shortages caused by unfavorable climate conditions.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.gfs.2022.100643","usgsCitation":"Lee, D., Davenport, F., Shukla, S., Husak, G., Funk, W., Harrison, L., McNally, A., Budde, M., Rowland, J., and Verdin, J., 2022, Maize yield forecasts for Sub-Saharan Africa using Earth Observation data and machine learning: Global Food Security, v. 33, 100643, 30 p., https://doi.org/10.1016/j.gfs.2022.100643.","productDescription":"100643, 30 p.","ipdsId":"IP-136632","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":447531,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gfs.2022.100643","text":"Publisher Index Page"},{"id":402055,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Burkina Faso, Kenya, Malawi, Somalia","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[41.58513,-1.68325],[40.88477,-2.08255],[40.63785,-2.49979],[40.26304,-2.57309],[40.12119,-3.27768],[39.80006,-3.68116],[39.60489,-4.34653],[39.20222,-4.67677],[37.7669,-3.67712],[37.69869,-3.09699],[34.07262,-1.05982],[33.90371,-0.95],[33.89357,0.10981],[34.18,0.515],[34.6721,1.17694],[35.03599,1.90584],[34.59607,3.05374],[34.47913,3.5556],[34.005,4.24988],[34.6202,4.84712],[35.29801,5.506],[35.81745,5.33823],[35.81745,4.77697],[36.15908,4.44786],[36.85509,4.44786],[38.12091,3.59861],[38.43697,3.58851],[38.67114,3.61607],[38.89251,3.50074],[39.55938,3.42206],[39.85494,3.83879],[40.76848,4.25702],[41.1718,3.91909],[41.85508,3.91891],[42.12861,4.23413],[42.76967,4.25259],[43.66087,4.95755],[44.9636,5.00162],[47.78942,8.003],[48.48674,8.83763],[48.93813,9.45175],[48.93823,9.9735],[48.93849,10.98233],[48.94201,11.39427],[48.9482,11.41062],[49.26776,11.43033],[49.72862,11.5789],[50.25878,11.67957],[50.73202,12.0219],[51.1112,12.02464],[51.13387,11.74815],[51.04153,11.16651],[51.04531,10.6409],[50.83418,10.27972],[50.55239,9.19874],[50.07092,8.08173],[49.4527,6.80466],[48.59455,5.33911],[47.74079,4.2194],[46.56476,2.85529],[45.56399,2.04576],[44.06815,1.05283],[43.13597,0.2922],[42.04157,-0.91916],[41.81095,-1.44647],[41.58513,-1.68325]]],[[[-2.8275,9.64246],[-3.5119,9.90033],[-3.98045,9.86234],[-4.33025,9.61083],[-4.77988,9.82198],[-4.95465,10.15271],[-5.40434,10.37074],[-5.47056,10.95127],[-5.19784,11.37515],[-5.22094,11.71386],[-4.42717,12.54265],[-4.28041,13.22844],[-4.00639,13.47249],[-3.5228,13.33766],[-3.10371,13.54127],[-2.96769,13.79815],[-2.19182,14.24642],[-2.00104,14.55901],[-1.06636,14.97382],[-0.51585,15.11616],[-0.26626,14.92431],[0.37489,14.92891],[0.29565,14.44423],[0.42993,13.98873],[0.99305,13.33575],[1.0241,12.85183],[2.17711,12.62502],[2.15447,11.94015],[1.93599,11.64115],[1.44718,11.54772],[1.24347,11.11051],[0.89956,10.99734],[0.0238,11.01868],[-0.4387,11.09834],[-0.76158,10.93693],[-1.20336,11.00982],[-2.94041,10.96269],[-2.9639,10.39533],[-2.8275,9.64246]]],[[[34.55999,-11.52002],[34.28001,-12.28003],[34.55999,-13.58],[34.90715,-13.56542],[35.26796,-13.88783],[35.68685,-14.61105],[35.7719,-15.89686],[35.33906,-16.10744],[35.03381,-16.8013],[34.38129,-16.18356],[34.30729,-15.47864],[34.51767,-15.01371],[34.45963,-14.61301],[34.06483,-14.35995],[33.7897,-14.45183],[33.21402,-13.97186],[32.68817,-13.71286],[32.99176,-12.78387],[33.30642,-12.43578],[33.11429,-11.6072],[33.31531,-10.79655],[33.48569,-10.52556],[33.23139,-9.67672],[32.75938,-9.2306],[33.73973,-9.41715],[33.94084,-9.69367],[34.28001,-10.16],[34.55999,-11.52002]]]]},\"properties\":{\"name\":\"Kenya\"}}]}","volume":"33","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lee, 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Chris 0000-0002-9254-6718","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":189580,"corporation":false,"usgs":false,"family":"Funk","given":"W. 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Temperate-breeding Canada Goose (Branta canadensis maxima) abundance has increased to previously unrecorded levels, providing social, ecological, and economic value. However, there are also costs associated with abundant Canada Geese. Although hunter harvest is a valued, sustainable use of Canada Geese, the adaptability of geese to urban areas may result in lower susceptibility of geese to hunters, potentially reducing the contribution of hunter harvest to conflict reduction. Our goal was to compare movement of geese marked in urban and rural areas to assess efficacy of hunter harvest in managing urban goose populations. We marked 71 adult female Canada Geese during brood-rearing with GPS-GSM transmitters in urban (n = 45) and rural (n = 26) locations in Iowa, USA to monitor movement during the 2018-19 and 2019-20 Mississippi Flyway goose hunting season frameworks. We estimated the mean proportion of locations each group was available for hunter harvest and examined factors affecting home range areas using generalized linear mixed models. Additionally, we estimated habitat selection of urban- and rural-marked geese using a step-selection analysis. Urban geese had a lower proportion of locations in areas available to hunters (0.07 [95% CI: 0.04-0.13]) than rural geese (0.56 [95% CI: 0.34-0.76]), but median home range area was similar for each group and decreased in size from autumn to late winter. Canada Geese marked in urban areas were more likely to select developed areas and less likely to select wetlands than rural geese, and they had high selection of agricultural fields within city limits during goose hunting seasons. Although Canada Geese breeding in urban areas may be less available for hunter harvest, movement data show when and where opportunity exists to increase harvest susceptibility. Canada Goose management could require actions in addition to hunter harvest to achieve goals in urban areas.

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\"}}]}","volume":"17","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Luukkonen, Benjamin Z.","contributorId":348730,"corporation":false,"usgs":false,"family":"Luukkonen","given":"Benjamin Z.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":923723,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923724,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones III, Orrin E.","contributorId":348731,"corporation":false,"usgs":false,"family":"Jones III","given":"Orrin E.","affiliations":[{"id":24495,"text":"Iowa Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":923725,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70236537,"text":"70236537 - 2022 - Evidence of alternative trophic pathways for fish consumers in a large river system in the face of invasion","interactions":[],"lastModifiedDate":"2022-09-09T12:08:10.245228","indexId":"70236537","displayToPublicDate":"2022-06-05T07:06:10","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Evidence of alternative trophic pathways for fish consumers in a large river system in the face of invasion","docAbstract":"

Large rivers are susceptible to anthropogenic alteration, which can result in drastic changes to their functional ecology. We evaluated spatial–temporal changes in the functional fish communities of the Upper Mississippi River System (UMRS) using data from six study reaches. Species were classified into one of 14 feeding guilds and mass per unit effort (MPUE) was then calculated for each feeding guild annually per gear type. MPUE was standardized using the multigear mean standardization method (MGMS) and log-transformed. Both ANOSIM and Chi-square tests were used to determine differences in MPUE among reaches. We then estimated functional diversity by calculating the number of functional groups (N), Margalef's d, Pielou's J′, Shannon's Diversity, and Simpson's Diversity Index. An AR(1) time series model was used to investigate proportional changes in each guild over 25 years. To evaluate the effect of invasive Carp species in invaded reaches, a Chow test was applied to observations between 2000 and 2005. Analyses revealed differences in the functional fish community among reaches. We found differences in functional diversity metrics among study reaches, but there was little evidence that this differed between invaded and non-invaded reaches. Results determined that invertivore/detritivores have been consistently declining system-wide, with few groups showing a net change. There was also little evidence that invasion altered the proportion of any functional guild. Evaluating the spatial–temporal patterns of functional communities is beneficial to understanding the resilience of a system and can provide further insight into its trophic needs when considering future restoration initiatives.

","language":"English","publisher":"Wiley","doi":"10.1002/rra.3992","usgsCitation":"Gatto, J.V., Ickes, B., and Chick, J.H., 2022, Evidence of alternative trophic pathways for fish consumers in a large river system in the face of invasion: River Research and Applications, v. 38, no. 7, p. 1321-1332, https://doi.org/10.1002/rra.3992.","productDescription":"12 p.","startPage":"1321","endPage":"1332","ipdsId":"IP-133926","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":447539,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.3992","text":"Publisher Index Page"},{"id":406441,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"7","noUsgsAuthors":false,"publicationDate":"2022-06-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Gatto, John V. 0000-0002-9793-0997","orcid":"https://orcid.org/0000-0002-9793-0997","contributorId":296376,"corporation":false,"usgs":false,"family":"Gatto","given":"John","email":"","middleInitial":"V.","affiliations":[{"id":36894,"text":"Illinois Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":851341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ickes, Brian 0000-0001-5622-3842 bickes@usgs.gov","orcid":"https://orcid.org/0000-0001-5622-3842","contributorId":2925,"corporation":false,"usgs":true,"family":"Ickes","given":"Brian","email":"bickes@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":851342,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chick, John H.","contributorId":229508,"corporation":false,"usgs":false,"family":"Chick","given":"John","email":"","middleInitial":"H.","affiliations":[{"id":36894,"text":"Illinois Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":851343,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70237904,"text":"70237904 - 2022 - A three-dimensional Lagrangian particle tracking model for predicting transport of eggs of rheophilic-spawning carps in turbulent rivers","interactions":[],"lastModifiedDate":"2022-10-31T12:20:46.232586","indexId":"70237904","displayToPublicDate":"2022-06-04T07:19:04","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"A three-dimensional Lagrangian particle tracking model for predicting transport of eggs of rheophilic-spawning carps in turbulent rivers","docAbstract":"

Grass carp, bighead carp, and silver carp spawn in flowing water. Their eggs, and then larvae, develop while drifting. Hydraulic conditions and water temperature control spawning locations, egg survival, and the downstream distance traveled before the hatched larvae can swim for low velocity nursery habitats. Existing egg drift models simulate the fluvial transport of carp eggs but have limitations in capturing the effect of localized turbulence on egg transport due to inadequate dimensions of hydrodynamics and/or empirical parameterization of river dispersion. We present a three-dimensional Lagrangian particle tracking model that uses fully resolved river hydrodynamics and a continuous random walk algorithm driven by local turbulent kinetic energy and its dissipation rate. We incorporate a new set of equations to compute evolving egg characteristics with fully resolved 3-D hydrodynamics. To demonstrate the performance of the model, we conducted a case study in an eight-kilometer reach of the Missouri River at the discharge of approximately 25% daily flow exceedance. Three-dimensional river hydrodynamics was modeled, calibrated, and evaluated with measurement data. Egg drift was modeled and compared using fully three-dimensional, depth-averaged two-dimensional, and zone-averaged one-dimensional hydrodynamics. The comparison shows a generally good agreement among models of downstream egg transport due to advection but a different dispersion pattern of eggs in the river, as a result of turbulent diffusion and shear induced dispersion.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2022.110035","usgsCitation":"Li, G., Wang, B., Elliott, C.M., Call, B., Chapman, D., and Jacobson, R., 2022, A three-dimensional Lagrangian particle tracking model for predicting transport of eggs of rheophilic-spawning carps in turbulent rivers: Ecological Modelling, v. 470, https://doi.org/10.1016/j.ecolmodel.2022.110035.","productDescription":"110035, 16 p.","startPage":"110035","ipdsId":"IP-136512","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":447545,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2022.110035","text":"Publisher Index Page"},{"id":435825,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X5M3WH","text":"USGS data release","linkHelpText":"Field Data and Models of the Missouri River at Sheepnose Bend, near Lexington, Missouri, 2019-2021"},{"id":408882,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"470","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Li, Geng","contributorId":298636,"corporation":false,"usgs":false,"family":"Li","given":"Geng","email":"","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":856141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Bin","contributorId":298637,"corporation":false,"usgs":false,"family":"Wang","given":"Bin","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":856142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elliott, Caroline M. 0000-0002-9190-7462 celliott@usgs.gov","orcid":"https://orcid.org/0000-0002-9190-7462","contributorId":2380,"corporation":false,"usgs":true,"family":"Elliott","given":"Caroline","email":"celliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":856143,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Call, Bruce 0000-0001-9064-2231","orcid":"https://orcid.org/0000-0001-9064-2231","contributorId":217707,"corporation":false,"usgs":true,"family":"Call","given":"Bruce","email":"","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":856144,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chapman, Duane","contributorId":298640,"corporation":false,"usgs":false,"family":"Chapman","given":"Duane","affiliations":[{"id":64637,"text":"Former USGS Columbia Environmental Research Center Employee","active":true,"usgs":false}],"preferred":false,"id":856145,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jacobson, R. B. 0000-0002-8368-2064","orcid":"https://orcid.org/0000-0002-8368-2064","contributorId":92614,"corporation":false,"usgs":true,"family":"Jacobson","given":"R. B.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":856140,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70232136,"text":"70232136 - 2022 - Multi-stage soil-hydraulic recovery and limited ravel accumulations following the 2017 Nuns and Tubbs wildfires in Northern California","interactions":[],"lastModifiedDate":"2022-07-08T13:45:20.841908","indexId":"70232136","displayToPublicDate":"2022-06-04T06:51:33","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5739,"text":"Journal of Geophysical Research: Earth Surface","onlineIssn":"2169-9011","active":true,"publicationSubtype":{"id":10}},"title":"Multi-stage soil-hydraulic recovery and limited ravel accumulations following the 2017 Nuns and Tubbs wildfires in Northern California","docAbstract":"

Wildfire can impact soil-hydraulic properties by reducing saturated hydraulic conductivity and sorptivity, making recently burned landscapes prone to debris flows and flash floods. The post-fire hazard window can range from years to decades. In Northern California, where wildfire frequency is steadily increasing, the impact and soil-hydraulic recovery from wildfires is unknown. Following the October 2017 Nuns and Tubbs fires in the Northern Bay Area of California, we established 41 monitoring sites for repeat tension-disc infiltrometer measurements of field-saturated hydraulic conductivity (Kfs) over 3.5 years. Our site arrays, which encompass grasslands, chaparral, and oak and conifer forests across a range in lithology, show a marked decrease in Kfs following the wildfires and a swift partial recovery following the initial post-fire rainy season. Our time series reveals a complex path to soil-hydraulic recovery marked by distinct seasonal stages. Analysis of changing Kfs, sorptivity, and infiltration model residuals collectively suggests that these stages are related to transitions between soil-hydraulic processes like structural soil sealing from rainsplash, thermal cracking of bare soil, and vegetation regrowth. While soil infiltration rates were strongly impacted by the 2017 fires, dry ravel estimates are an order of magnitude less for similar slopes than the 2009 Station fire in the San Gabriel mountains of Southern California, suggesting that limited ravel flux may insufficiently load channels for debris flows that initiate from within-channel failure. Our analysis suggests that burned landscapes in the Northern Bay Area of California may experience rapid soil-hydraulic recovery and limited pathways toward post-fire debris flow initiation.

","language":"English","publisher":"Wiley","doi":"10.1029/2022JF006591","usgsCitation":"Perkins, J.P., Diaz, C., Corbett, S.C., Cerovski-Darriau, C., Stock, J.D., Prancevic, J.P., Micheli, L., and Jasperse, J., 2022, Multi-stage soil-hydraulic recovery and limited ravel accumulations following the 2017 Nuns and Tubbs wildfires in Northern California: Journal of Geophysical Research: Earth Surface, v. 127, no. 6, e2022JF006591, 19 p., https://doi.org/10.1029/2022JF006591.","productDescription":"e2022JF006591, 19 p.","ipdsId":"IP-136584","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":447547,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022jf006591","text":"Publisher Index Page"},{"id":435827,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J5BTSN","text":"USGS data release","linkHelpText":"Field-saturated hydraulic conductivity time series and sediment accumulations following the 2017 Nuns and Tubbs wildfires, Napa and Sonoma Counties, CA, USA"},{"id":401914,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Pepperwood Preserve, Sugarloaf Ridge State Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.61016845703124,\n 38.37773029803778\n ],\n [\n -122.47901916503906,\n 38.37773029803778\n ],\n [\n -122.47901916503906,\n 38.501967316378895\n ],\n [\n -122.61016845703124,\n 38.501967316378895\n ],\n [\n -122.61016845703124,\n 38.37773029803778\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.7777099609375,\n 38.49954915714596\n ],\n [\n -122.65033721923827,\n 38.49954915714596\n ],\n [\n -122.65033721923827,\n 38.61123697842133\n ],\n [\n -122.7777099609375,\n 38.61123697842133\n ],\n [\n -122.7777099609375,\n 38.49954915714596\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"127","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-06-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Perkins, Jonathan P. 0000-0002-6113-338X","orcid":"https://orcid.org/0000-0002-6113-338X","contributorId":237053,"corporation":false,"usgs":true,"family":"Perkins","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":844314,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diaz, Carlos","contributorId":292327,"corporation":false,"usgs":false,"family":"Diaz","given":"Carlos","email":"","affiliations":[{"id":17863,"text":"Sonoma County Water Agency","active":true,"usgs":false}],"preferred":false,"id":844315,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Corbett, Skye C. 0000-0003-3277-1021 scorbett@usgs.gov","orcid":"https://orcid.org/0000-0003-3277-1021","contributorId":200617,"corporation":false,"usgs":true,"family":"Corbett","given":"Skye","email":"scorbett@usgs.gov","middleInitial":"C.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":844316,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cerovski-Darriau, Corina 0000-0002-0543-0902","orcid":"https://orcid.org/0000-0002-0543-0902","contributorId":221159,"corporation":false,"usgs":true,"family":"Cerovski-Darriau","given":"Corina","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":844320,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stock, Jonathan D. 0000-0001-8565-3577 jstock@usgs.gov","orcid":"https://orcid.org/0000-0001-8565-3577","contributorId":3648,"corporation":false,"usgs":true,"family":"Stock","given":"Jonathan","email":"jstock@usgs.gov","middleInitial":"D.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":844317,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Prancevic, Jeffrey Paul 0000-0003-1890-7551","orcid":"https://orcid.org/0000-0003-1890-7551","contributorId":292330,"corporation":false,"usgs":true,"family":"Prancevic","given":"Jeffrey","email":"","middleInitial":"Paul","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":844321,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Micheli, Lisa","contributorId":292329,"corporation":false,"usgs":false,"family":"Micheli","given":"Lisa","email":"","affiliations":[{"id":37798,"text":"Pepperwood Preserve","active":true,"usgs":false}],"preferred":false,"id":844319,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jasperse, Jay","contributorId":168661,"corporation":false,"usgs":false,"family":"Jasperse","given":"Jay","affiliations":[{"id":17863,"text":"Sonoma County Water Agency","active":true,"usgs":false}],"preferred":false,"id":844318,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70232132,"text":"70232132 - 2022 - Petrogenesis and rare earth element mineralization of the Elk Creek carbonatite, Nebraska, USA","interactions":[],"lastModifiedDate":"2022-06-08T11:50:52.591025","indexId":"70232132","displayToPublicDate":"2022-06-04T06:48:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2954,"text":"Ore Geology Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Petrogenesis and rare earth element mineralization of the Elk Creek carbonatite, Nebraska, USA","docAbstract":"

Although carbonatites are the primary source of the world’s rare earth elements (REEs), the processes responsible for ore-grade REE enrichment in carbonatites are still poorly understood. In this study, we present a petrologic, geochemical, and isotopic evaluation of the Elk Creek carbonatite in southeast Nebraska to constrain the origin of REE mineralization. The Elk Creek carbonatite is a multilithologic carbonatite comprised of an early apatite-dolomite carbonatite, a middle/heavy REE-enriched magnetite-dolomite carbonatite, and a late-stage light REE-enriched, barite-dolomite carbonatite, as well as a suite of breccias. Neodymium, strontium, and carbon isotopic data from the early apatite-dolomite carbonatite, εNd(T) = 2.3 to 3.4, 87Sr/86Sr(i) = 0.702704 to 0.702857, and δ13C = −3.3 to −3.4, indicate that the parental magma and REEs were derived from the mantle, and textural and chemical data suggest that hydrothermal processes played an important role in reaching ore-grade enrichment. Higher initial 87Sr/86Sr values (∼0.7041) of REE-mineralized lithologies are evidence that these fluids were derived, in part, from meteoric water that interacted with the country rock. Modeling of the C-O isotopic data reveals that some of the isotopic variation results from closed-system Rayleigh fractionation of an evolving carbonatitic magma between 300 and 500 °C, but an excursion to heavier δ18O is likely the result of interaction with H2O-CO2-fluids at temperatures from 400 to 100 °C. Hydrothermal dolomite has higher 87Sr/86Sr values than early-formed magmatic dolomite, consistent with metasomatism by fluids derived, in part, from a more radiogenic source such as the Precambrian-age wall rock. Rare earth element mineralization occurs primarily in fine-grained, cavity filling minerals including monazite, bastnäsite, parisite, and synchysite along with barite, dolomite, quartz, and iron oxides. We interpret the LREE enrichment at Elk Creek to be the product of hydrothermal fluids derived from the evolving carbonatite magma and fluids from the wall rock. The REEs likely became enriched in late-stage fluids from the evolving magma as well as being remobilization by the dissolution of earlier formed minerals. Middle/heavy REE-enrichment in the magnetite-dolomite carbonatite is hosted in hydrothermal dolomite and is attributed to variations in the composition of hydrothermal fluids.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.oregeorev.2022.104953","usgsCitation":"Verplanck, P., Farmer, G.L., Kettler, R.M., Lowers, H.A., Johnson, C.A., Koenig, A.E., and Blessington, M.J., 2022, Petrogenesis and rare earth element mineralization of the Elk Creek carbonatite, Nebraska, USA: Ore Geology Reviews, v. 146, 104953, 19 p., https://doi.org/10.1016/j.oregeorev.2022.104953.","productDescription":"104953, 19 p.","ipdsId":"IP-137353","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":447551,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.oregeorev.2022.104953","text":"Publisher Index Page"},{"id":401913,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Populations of amphibians that breed in isolated, ephemeral wetlands may be particularly sensitive to breeding and recruitment rates, which can be influenced by dynamic and difficult-to-predict extrinsic factors. The gopher frog Rana capito is a declining species currently proposed for listing under the U.S. Endangered Species Act, as well as one of many pond-breeding amphibians of conservation concern in the southeastern United States. To represent gopher frog breeding dynamics, we applied an occupancy modeling framework that integrated multiple data sets collected across the species' range to 1) estimate the influence of climate, habitat, and other factors on wetland-specific seasonal breeding probabilities; and 2) use those estimates to characterize seasonal, annual, and regional breeding patterns over a 10-y period. Breeding probability at a wetland was positively influenced by seasonal precipitation (Standardized Precipitation Index) and negatively influenced by fish presence. We found some evidence that the amount of suitable habitat surrounding a wetland was positively correlated with breeding probability during drought conditions. The percentage of sampled wetlands (N = 192) predicted to have breeding varied seasonally, annually, and regionally across the study. Within-year temporal patterns of breeding differed across the range: in most locations north of Florida, peaks of breeding occurred in winter and spring months; whereas breeding was more dispersed throughout the year in Florida. Peaks of breeding across the 10-y period often occurred during or in the season following high rainfall events (e.g., hurricanes). These results have direct applications for site-level management that aims to increase successful breeding opportunities of gopher frogs and other associated pond-breeding amphibians, including monitoring protocol and intensity, removal of fish, and improving terrestrial habitat conditions surrounding wetlands (e.g., via tree or shrub removal and prescribed fire). The results also have implications for better-informed management through the closer alignment of breeding activity monitoring with predicted seasonal peaks. Furthermore, estimates of breeding frequency can be incorporated into population viability analyses to inform forthcoming assessments of extinction risk and designation of the species' conservation status by the U.S. Fish and Wildlife Service.

","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-21-076","usgsCitation":"Crawford, B., Farmer, A.L., Enge, K.M., Greene, A.H., Diaz, L., Maerz, J., and Moore, C.T., 2022, Breeding dynamics of gopher frog metapopulations over 10 years: Journal of Fish and Wildlife Management, v. 13, no. 2, p. 422-436, https://doi.org/10.3996/JFWM-21-076.","productDescription":"15 p.","startPage":"422","endPage":"436","ipdsId":"IP-132970","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":447552,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-21-076","text":"Publisher Index Page"},{"id":433319,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, Georgia, North Carolina, South Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.37623620146309,\n 35.01905610973961\n ],\n [\n -79.58387829875939,\n 35.765474175904856\n ],\n [\n -84.05790907036402,\n 32.71553184084284\n ],\n [\n -86.95743456481551,\n 31.313371252353505\n ],\n [\n -87.97753689244945,\n 31.255714516567366\n ],\n [\n -87.90062766475464,\n 30.410921928153\n ],\n [\n -87.59693089405745,\n 30.192182652668805\n ],\n [\n -86.47166028094222,\n 30.256647398203384\n ],\n [\n -85.28363865323925,\n 29.70795105375852\n ],\n [\n -84.92300860524551,\n 29.589227662420754\n ],\n [\n -84.08074545620036,\n 30.02565465245405\n ],\n [\n -83.15740795176218,\n 29.317339522650897\n ],\n [\n -82.63768115979533,\n 28.69410108060019\n ],\n [\n -82.92151914429557,\n 27.84487915072812\n ],\n [\n -82.2486913639156,\n 26.57820345742978\n ],\n [\n -80.14666967814253,\n 27.38909651326503\n ],\n [\n -81.36572255738787,\n 30.46066646132182\n ],\n [\n -80.96075675824606,\n 31.903583611808543\n ],\n [\n -79.10275245779792,\n 33.184671689061005\n ],\n [\n -78.85784463476865,\n 33.722973799123594\n ],\n [\n -77.88573955862327,\n 33.91871952883908\n ],\n [\n -76.37623620146309,\n 35.01905610973961\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-06-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Crawford, Brian A.","contributorId":341519,"corporation":false,"usgs":false,"family":"Crawford","given":"Brian A.","affiliations":[{"id":81748,"text":"Georgia Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":908553,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farmer, Anna L.","contributorId":341520,"corporation":false,"usgs":false,"family":"Farmer","given":"Anna","email":"","middleInitial":"L.","affiliations":[{"id":36335,"text":"Fish and Wildlife Research Institute","active":true,"usgs":false}],"preferred":false,"id":908554,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Enge, Kevin M","contributorId":177669,"corporation":false,"usgs":false,"family":"Enge","given":"Kevin","email":"","middleInitial":"M","affiliations":[],"preferred":false,"id":908555,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Greene, Aubrey Heupel","contributorId":341522,"corporation":false,"usgs":false,"family":"Greene","given":"Aubrey","email":"","middleInitial":"Heupel","affiliations":[{"id":36335,"text":"Fish and Wildlife Research Institute","active":true,"usgs":false}],"preferred":false,"id":908556,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Diaz, Lauren","contributorId":341523,"corporation":false,"usgs":false,"family":"Diaz","given":"Lauren","email":"","affiliations":[{"id":36335,"text":"Fish and Wildlife Research Institute","active":true,"usgs":false}],"preferred":false,"id":908557,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Maerz, John C.","contributorId":341524,"corporation":false,"usgs":false,"family":"Maerz","given":"John C.","affiliations":[{"id":81749,"text":"Warnell School of Forestry and Natural Resources","active":true,"usgs":false}],"preferred":false,"id":908558,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moore, Clinton T. 0000-0002-6053-2880 cmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-6053-2880","contributorId":3643,"corporation":false,"usgs":true,"family":"Moore","given":"Clinton","email":"cmoore@usgs.gov","middleInitial":"T.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908559,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70231909,"text":"70231909 - 2022 - Biogeography of freshwater mussels (Bivalvia: Unionida) in Texas and implications on conservation biology","interactions":[],"lastModifiedDate":"2022-07-08T13:38:13.520477","indexId":"70231909","displayToPublicDate":"2022-06-03T08:43:05","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Biogeography of freshwater mussels (Bivalvia: Unionida) in Texas and implications on conservation biology","docAbstract":"

Aim

Biogeography seeks to identify and explain the spatial distributions of species and has become an important tool used by conservationists to protect and manage aquatic organisms. Texas, located in the southwestern United States, is home to 52 species of freshwater mussels, 9 of which are endemic to Texas and 7 that are endemic to Texas and neighboring states or countries. There have been two major attempts to classify this fauna into biogeographical provinces; however, both efforts relied on limited distribution information and outdated taxonomy. To address both issues, we set out to delineate biogeographic provinces for freshwater mussels in Texas by using a comprehensive distributional dataset of >28,000 records and molecular information.

Location

Southwestern United States.

Methods

We compiled community and molecular data for 48 of the 52 freshwater mussel species that occur in Texas. We performed algorithmic hierarchal cluster analysis (HCA) and nonmetric multidimensional scaling (NMDS) based on Euclidean distance to identify biogeographic groupings. We conducted a similar analysis using molecular sequence data for our target species.

Results

Based on the results from community and molecular data, we identified seven biogeographic provinces for freshwater mussels in Texas: Great Plains, Mississippi Embayment, Sabine-Neches, Trinity-San Jacinto, Central Texas, Rio Grande and Coastal. However, the Coastal and Great Plains provinces were not included in our analysis and were recognized based on previous work.

Main conclusions

Our approach integrating community and molecular datasets provides a comprehensive assessment of the biogeography of freshwater mussels in Texas, which serves as a model for future biogeographic studies. Our findings also shed light on the ecological, evolutionary and geologic processes shaping freshwater mussel communities in Texas, which is important for the conservation of remaining biodiversity in the state.

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\"}}]}","volume":"28","issue":"7","noUsgsAuthors":false,"publicationDate":"2022-05-30","publicationStatus":"PW","contributors":{"authors":[{"text":"de Moulpied, Michael 0000-0002-4007-7550","orcid":"https://orcid.org/0000-0002-4007-7550","contributorId":292219,"corporation":false,"usgs":false,"family":"de Moulpied","given":"Michael","email":"","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":844093,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Chase H. 0000-0002-1499-0311","orcid":"https://orcid.org/0000-0002-1499-0311","contributorId":225140,"corporation":false,"usgs":false,"family":"Smith","given":"Chase","email":"","middleInitial":"H.","affiliations":[{"id":13716,"text":"Baylor University","active":true,"usgs":false}],"preferred":false,"id":844094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robertson, Clint 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R.","contributorId":202530,"corporation":false,"usgs":false,"family":"Randklev","given":"Charles","email":"","middleInitial":"R.","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":844098,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70231907,"text":"70231907 - 2022 - Structured decision making to rank North American Wetland Conservation Act proposals within joint venture regions","interactions":[],"lastModifiedDate":"2023-01-18T15:51:07.526101","indexId":"70231907","displayToPublicDate":"2022-06-03T08:32:14","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Structured decision making to rank North American Wetland Conservation Act proposals within joint venture regions","docAbstract":"

The North American Wetlands Conservation Act (16 U.S.C. 4401-4412) provided funding and administration for wetland management and conservation projects. The North American Wetland Conservation Fund, enabled in 1989 with the Act, provides financial resources. Resource allocation decisions are based, in part, on regional experts, particularly migratory bird Joint Ventures (JVs) (i.e., partnerships for cooperative planning and coordinated management of the continent’s waterfowl populations and habitats). The JVs evaluate funding proposals submitted with their respective regions each year and make funding recommendations to decision makers. Proposal evaluation procedures differ among JVs, however, it could be helpful to consider a transparent, repeatable, and data-driven framework for prioritization within regions. We used structured decision making and linear additive value models for ranking proposals within JV regions. We used two JVs as case studies and constructed two different value models using JV-specific objectives and weights. The framework was developed through a collaborative process with JV staff and stakeholders. Models were written in Microsoft Excel. To test these models, we used six NAWCA proposals submitted to the Upper Mississippi / Great Lakes Joint Venture in 2016 and seven proposals submitted to the Gulf Coast Joint Venture in 2017. We compared proposal ranks assigned by the value model to ranks assigned by each JV’s management board. Ranks assigned by the value model differed from ranks assigned by the board for the Upper Mississippi / Great Lakes Joint Venture, but not for the Gulf Coast Joint Venture. However, ranks from the value model could change markedly with different objective weights and value functions. The weighted linear value model was beneficial for ranking NAWCA proposals because it allows JVs to treat the ranking as a multiple objective problem and tailor the ranking to their specific regional concerns. We believe a structured decision making approach could be adapted by JV staff to facilitate a systematic and transparent process for proposal ranking by their management boards.

","language":"English","publisher":"U. S. 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