Long‐term standardized monitoring programs are fundamental to assessing how fish populations respond to anthropogenic stressors. Standardized monitoring programs may need to adopt new methods to adapt to rapid environmental changes that are associated with a changing climate. In the upper Yellowstone River, Montana, biologists have used a standardized, mark–recapture monitoring protocol to annually estimate the abundance of trout since 1978 to assess population status and trends. However, within the past two decades, climate change has caused changes in discharge timing that have prevented standardized monitoring from occurring annually.
We investigated the feasibility of using two analytical methods, N‐mixture models and mean capture probability, for estimating the abundance of three trout species in the upper Yellowstone River using the historical long‐term data set; these methods allow abundance to be estimated when a mark–recapture estimate cannot be obtained due to hydrologic conditions.
When compared with abundance estimates from mark–recapture methods, N‐mixture models most often resulted in negatively biased abundance estimates, whereas mean capture probability analyses resulted in positively biased abundance estimates. Additionally, N‐mixture models produced negatively biased estimates when tested against true abundance values from simulated data sets. The bias in the N‐mixture model estimates was caused by poor model fit and variation in capture probability. The bias in the mean capture probability estimates was caused by heterogeneity in capture probability, likely caused by variable environmental conditions, which were not accounted for in the models.
N‐mixture models and mean capture probability are not viable alternatives for estimating abundance in the upper Yellowstone River. Thus, exploring additional adaptations to sampling methodologies and analytical approaches, including models that require individually marked fish, will be valuable for this system. Climate change will undoubtedly necessitate changes to standardized sampling methods throughout the world; thus, developing alternative sampling and analytical methods will be important for maintaining the utility of long‐term data sets.
","language":"English","publisher":"Oxford Academic","doi":"10.1002/nafm.11026","usgsCitation":"Briggs, M., Glassic, H.C., Guy, C.S., Opitz, S., Rotella, J., and Schmetterling, D., 2024, Adapting standardized trout monitoring to a changing climate for the upper Yellowstone River, Montana, USA: North American Journal of Fisheries Management, v. 44, no. 5, p. 947-961, https://doi.org/10.1002/nafm.11026.","productDescription":"15 p.","startPage":"947","endPage":"961","ipdsId":"IP-172896","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":488961,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.11026","text":"Publisher Index Page"},{"id":486239,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"upper Yellowstone River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.27790695947738,\n 45.77750283140904\n ],\n [\n -111.27790695947738,\n 45.00210734009434\n ],\n [\n -110.23435146225052,\n 45.00210734009434\n ],\n [\n -110.23435146225052,\n 45.77750283140904\n ],\n [\n -111.27790695947738,\n 45.77750283140904\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"5","noUsgsAuthors":false,"publicationDate":"2024-08-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Briggs, Michelle A.","contributorId":355621,"corporation":false,"usgs":false,"family":"Briggs","given":"Michelle A.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":937791,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glassic, Hayley Corrine 0000-0001-6839-1026","orcid":"https://orcid.org/0000-0001-6839-1026","contributorId":305858,"corporation":false,"usgs":true,"family":"Glassic","given":"Hayley","email":"","middleInitial":"Corrine","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":937792,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":937793,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Opitz, Scott T.","contributorId":355622,"corporation":false,"usgs":false,"family":"Opitz","given":"Scott T.","affiliations":[{"id":37431,"text":"Montana Fish, Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":937794,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rotella, Jay J.","contributorId":355623,"corporation":false,"usgs":false,"family":"Rotella","given":"Jay J.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":937795,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schmetterling, David A.","contributorId":355624,"corporation":false,"usgs":false,"family":"Schmetterling","given":"David A.","affiliations":[{"id":37431,"text":"Montana Fish, Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":937796,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70264248,"text":"70264248 - 2024 - Onset of aftershocks: Constraints on the Rate-and-State model","interactions":[],"lastModifiedDate":"2025-03-10T14:39:45.261636","indexId":"70264248","displayToPublicDate":"2024-10-01T09:39:12","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Onset of aftershocks: Constraints on the Rate-and-State model","docAbstract":"Aftershock rates typically decay with time t after the mainshock according to the Omori–Utsu law, R(t)=K(c+t)−p, with parameters K, c, and p. The rate‐and‐state (RS) model, which is currently the most popular physics‐based seismicity model, also predicts an Omori–Utsu decay with p = 1 and a c‐value that depends on the size of the coseismic stress change. Because the mainshock‐induced stresses strongly vary in space, the c‐value should vary accordingly. Short‐time aftershock incompleteness (STAI) in earthquake catalogs has prevented a detailed test of this prediction so far, but the newly developed a‐positive method for reconstructing the true earthquake rate now allows its testing. Using previously published slip models, we calculate the coseismic stress changes for the six largest mainshocks in Southern California in recent decades and estimate the maximum shear as a scalar proxy of the coseismic stress tensor. Aftershock rates reconstructed for events in different stress ranges show that the rates follow a power law with p = 1 independent of stress with no clear sign of a c‐value. The onset of the power‐law decay is abrupt and more delayed in areas with smaller stress changes. The observations do not necessarily contradict the RS model, as STAI limits the resolution for early aftershocks, and the RS model can reproduce the observations for specific Aσ values. However, the observations lead to strong constraints, namely Aσ<10 kPa and a power‐law decay of the background rate with distance to the fault, with exponent 2.7.
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","language":"English","publisher":"American Fisheries Society","doi":"10.1002/fsh.11157","usgsCitation":"Kerkhove, A., Trudeau, A., Jensen, O., Isermann, D.A., Dombrowski, P., Latimer, A., and Feiner, Z., 2024, Understanding the role of recreational angling technology in angler expectations of catch, trip catch, and angler satisfaction: Fisheries Magazine, v. 49, no. 10, p. 463-474, https://doi.org/10.1002/fsh.11157.","productDescription":"12 p.","startPage":"463","endPage":"474","ipdsId":"IP-158366","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481058,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/fsh.11157","text":"Publisher Index Page"},{"id":480748,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","county":"Dane County, Vilas 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","language":"English","publisher":"U.S. Geological Survey","usgsCitation":"Rossos, K., 2024, Fall 2024: Watermarks New England Water Science Center Newsletter, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-171574","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":465623,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://cms.usgs.gov/watermarks-new-england-wsc-newsletters/watermarks-newsletter-fall-2024"},{"id":465624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rossos, Katrina 0000-0002-3819-4344","orcid":"https://orcid.org/0000-0002-3819-4344","contributorId":331723,"corporation":false,"usgs":true,"family":"Rossos","given":"Katrina","email":"","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922291,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70259749,"text":"70259749 - 2024 - Special flora and vegetation of Indiana Dunes National Park","interactions":[],"lastModifiedDate":"2024-10-23T12:24:15.097251","indexId":"70259749","displayToPublicDate":"2024-10-01T07:20:11","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":273,"text":"Natural Resource Report","active":false,"publicationSubtype":{"id":4}},"seriesNumber":"NPS/INDU/NRR—2024/262","title":"Special flora and vegetation of Indiana Dunes National Park","docAbstract":"No abstract available.
","language":"English","publisher":"National Park Service","doi":"10.36967/2302417","usgsCitation":"Pavlovic, N., Plampin, B., Tonkovich, G.S., and Hamilla, D.R., 2024, Special flora and vegetation of Indiana Dunes National Park: Natural Resource Report NPS/INDU/NRR—2024/262, xxvii, 771 p., https://doi.org/10.36967/2302417.","productDescription":"xxvii, 771 p.","startPage":"802","ipdsId":"IP-069641","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":463119,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Indiana","otherGeospatial":"Dunes National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.14259682399684,\n 41.64975697846441\n ],\n [\n -87.12126914485442,\n 41.630763565962894\n ],\n [\n -87.09722021804414,\n 41.60920060097345\n ],\n [\n -87.04638795765823,\n 41.5948273396551\n ],\n [\n -86.93033845468838,\n 41.630254643981544\n ],\n [\n -86.88982018901976,\n 41.65899026034268\n ],\n [\n -86.89049275682176,\n 41.69951612637291\n ],\n [\n -86.91725614199466,\n 41.72158907366915\n ],\n [\n -87.14259682399684,\n 41.64975697846441\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pavlovic, Noel B. 0000-0002-2335-2274","orcid":"https://orcid.org/0000-0002-2335-2274","contributorId":266174,"corporation":false,"usgs":true,"family":"Pavlovic","given":"Noel B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":916588,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plampin, Barbara","contributorId":345432,"corporation":false,"usgs":false,"family":"Plampin","given":"Barbara","email":"","affiliations":[{"id":82581,"text":"Botanist","active":true,"usgs":false}],"preferred":false,"id":916589,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tonkovich, Gayle S.","contributorId":345433,"corporation":false,"usgs":false,"family":"Tonkovich","given":"Gayle","email":"","middleInitial":"S.","affiliations":[{"id":82582,"text":"Northwest Indiana Restoration Monitoring Inventory, Department of Biology, Indiana University","active":true,"usgs":false}],"preferred":false,"id":916611,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hamilla, David R.","contributorId":345439,"corporation":false,"usgs":false,"family":"Hamilla","given":"David","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":916612,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70259320,"text":"70259320 - 2024 - Preliminary observations of the April 5th, 2024, Mw4.8 New Jersey earthquake","interactions":[],"lastModifiedDate":"2024-10-04T11:54:34.426806","indexId":"70259320","displayToPublicDate":"2024-10-01T06:52:32","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10542,"text":"The Seismic Record","active":true,"publicationSubtype":{"id":10}},"title":"Preliminary observations of the April 5th, 2024, Mw4.8 New Jersey earthquake","docAbstract":"On 5 April 2024, 10:23 a.m. local time, a moment magnitude 4.8 earthquake struck Tewksbury Township, New Jersey, about 65 km west of New York City. Millions of people from Virginia to Maine and beyond felt the ground shaking, resulting in the largest number (>180,000) of U.S. Geological Survey (USGS) “Did You Feel It?” reports of any earthquake. A team deployed by the Geotechnical Extreme Events Reconnaissance Association and the National Institute of Standards and Technology documented structural and nonstructural damage, including substantial damage to a historic masonry building in Lebanon, New Jersey. The USGS National Earthquake Information Center reported a focal depth of about 5 km, consistent with a lack of signal in Interferometric Synthetic Aperture Radar data. The focal mechanism solution is strike slip with a substantial thrust component. Neither mechanism’s nodal plane is parallel to the primary northeast trend of geologic discontinuities and mapped faults in the region, including the Ramapo fault. However, many of the relocated aftershocks, for which locations were augmented by temporary seismic deployments, form a cluster that parallels the general northeast trend of the faults. The aftershocks lie near the Tewksbury fault, north of the Ramapo fault.
Habitat selection is a critical aspect of a species' ecology, requiring complex decision-making that is both hierarchical and scale-dependent, since factors that influence selection may be nested or unequal across scales. Elk (Cervus canadensis) ranged widely across diverse ecoregions in North America prior to European settlement and subsequent eastern extirpation. Most habitat selection studies have occurred within their contemporary western range, even after eastern reintroductions began. As habitat selection can vary by geographic location, available cover, season, and diel period, it is important to understand how a non-migratory, reintroduced population in northern Wisconsin, USA, is limited by the lack of variation in topography, elevation, and vegetation. We tested scale-dependent habitat selection on 79 adult elk from 2017 to 2020 using resource selection functions across temporal (i.e., seasonal) and spatial scales (i.e., landscape and home range). We found that selection varied both spatially and temporally, and elk selected areas with the greatest potential to influence fitness at larger scales, meaning elk selected areas closer to escape cover and further from “risky” features (e.g., annual wolf territory centers, county roads, and highways). We found stronger avoidance of annual wolf territory centers during spring, suggesting elk were selecting safer habitats during calving season. Elk selected habitats with less canopy cover across both spatial scales and all seasons, suggesting that elk selected areas with better access to forage as early seral stage stands have greater forage biomass than closed-canopy forests and direct solar radiation to provide warmth in the cooler seasons. This study provides insight into the complexity of hierarchical decision-making, such as how risky habitat features and land cover type influence habitat selection differently across seasons and spatial scales, influencing the decision-making of elk. Scale-dependent behavior is crucial to understand within specific geographic regions, as these decisions scale up to influence population dynamics.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.70346","usgsCitation":"Merems, J., Brose, A., Tack, J., Crimmins, S.M., and Van Deelen, T., 2024, Scale-dependence in elk habitat selection for a reintroduced population in Wisconsin, USA: Ecology and Evolution, v. 14, no. 10, e70346, 13 p., https://doi.org/10.1002/ece3.70346.","productDescription":"e70346, 13 p.","ipdsId":"IP-151404","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":488270,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.70346","text":"Publisher Index Page"},{"id":485840,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Chequamegon-Nicolet National Forest, Flambeau River State Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.44038392352694,\n 46.55749714177122\n ],\n [\n -91.44038392352694,\n 45.89642997708481\n ],\n [\n -90.69624903990778,\n 45.89642997708481\n ],\n [\n -90.69624903990778,\n 46.55749714177122\n ],\n [\n -91.44038392352694,\n 46.55749714177122\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"10","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Merems, Jennifer L.","contributorId":354971,"corporation":false,"usgs":false,"family":"Merems","given":"Jennifer L.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":936740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brose, Anna L.","contributorId":354972,"corporation":false,"usgs":false,"family":"Brose","given":"Anna L.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":936741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tack, Jennifer Price","contributorId":354973,"corporation":false,"usgs":false,"family":"Tack","given":"Jennifer Price","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":936742,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crimmins, Shawn M. 0000-0001-6229-5543 scrimmins@usgs.gov","orcid":"https://orcid.org/0000-0001-6229-5543","contributorId":5498,"corporation":false,"usgs":true,"family":"Crimmins","given":"Shawn","email":"scrimmins@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":936743,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Van Deelen, Timothy R.","contributorId":354974,"corporation":false,"usgs":false,"family":"Van Deelen","given":"Timothy R.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":936744,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70266769,"text":"70266769 - 2024 - Adapting standardized trout monitoring to a changing climate for the upper Yellowstone River, Montana, USA","interactions":[],"lastModifiedDate":"2025-05-13T15:43:28.159582","indexId":"70266769","displayToPublicDate":"2024-10-01T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Adapting standardized trout monitoring to a changing climate for the upper Yellowstone River, Montana, USA","docAbstract":"Objective
Long-term standardized monitoring programs are fundamental to assessing how fish populations respond to anthropogenic stressors. Standardized monitoring programs may need to adopt new methods to adapt to rapid environmental changes associated with a changing climate. In the upper Yellowstone River, Montana, biologists have used a standardized, mark-recapture monitoring protocol to annually estimate the abundance of trout since 1978 to assess population status and trends. However, within the last two decades, climate change has caused changes in discharge timing that have prevented standardized monitoring from occurring annually.
Methods
We investigated the feasibility of using two analytical methods, N-mixture models and mean capture probability, for estimating the abundance of three trout species in the upper Yellowstone River; these methods allow abundance to be estimated when a mark-recapture estimate cannot be obtained due to hydrologic conditions.
Result
When compared to abundance estimates from mark-recapture methods, N-mixture models most often resulted in negatively biased abundance estimates while mean capture probability analyses resulted in positively biased abundance estimates. Additionally, N-mixture models produced negatively biased estimates compared to true abundance values from simulated datasets. Bias in N-mixture model estimates was caused by poor model fit and variation in capture probability. Bias in mean capture probability estimates was caused by heterogeneity in capture probability that was not accounted for in the models.
Conclusion
N-mixture models and mean capture probability are not viable alternatives for estimating abundance in the upper Yellowstone River. Thus, exploring additional adaptations to sampling methodologies and analytical approaches, including models that require individually marked fish, will be valuable for this system. Climate change will undoubtedly necessitate changes to standardized sampling methods throughout the world; thus, developing alternative sampling and analytical methods will be important for maintaining long-term datasets.
","language":"English","publisher":"Oxford Academic","doi":"10.1002/nafm.11026","usgsCitation":"Briggs, M., Glassic, H.C., Guy, C.S., Opitz, S., Rotella, J., and Schmetterling, D., 2024, Adapting standardized trout monitoring to a changing climate for the upper Yellowstone River, Montana, USA: North American Journal of Fisheries Management, v. 44, no. 5, p. 947-961, https://doi.org/10.1002/nafm.11026.","productDescription":"15 p.","startPage":"947","endPage":"961","ipdsId":"IP-160733","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":488197,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.11026","text":"Publisher Index Page"},{"id":485823,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"upper Yellowstone River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.25391301846597,\n 45.79233815794254\n ],\n [\n -111.25391301846597,\n 45.00638613042193\n ],\n [\n -110.01308523101437,\n 45.00638613042193\n ],\n [\n -110.01308523101437,\n 45.79233815794254\n ],\n [\n -111.25391301846597,\n 45.79233815794254\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"5","noUsgsAuthors":false,"publicationDate":"2024-08-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Briggs, Michelle A.","contributorId":354954,"corporation":false,"usgs":false,"family":"Briggs","given":"Michelle A.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":936730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glassic, Hayley Corrine 0000-0001-6839-1026","orcid":"https://orcid.org/0000-0001-6839-1026","contributorId":305858,"corporation":false,"usgs":true,"family":"Glassic","given":"Hayley","email":"","middleInitial":"Corrine","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":936731,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true}],"preferred":true,"id":936732,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Opitz, Scott T.","contributorId":354955,"corporation":false,"usgs":false,"family":"Opitz","given":"Scott T.","affiliations":[{"id":61825,"text":"Montana Fish","active":true,"usgs":false}],"preferred":false,"id":936733,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rotella, Jay J.","contributorId":354956,"corporation":false,"usgs":false,"family":"Rotella","given":"Jay J.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":936734,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schmetterling, David A.","contributorId":354957,"corporation":false,"usgs":false,"family":"Schmetterling","given":"David A.","affiliations":[{"id":61825,"text":"Montana Fish","active":true,"usgs":false}],"preferred":false,"id":936735,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70257226,"text":"70257226 - 2024 - Synopsis of basin-scale 3D framework modeling at the USGS Mapping Program","interactions":[],"lastModifiedDate":"2026-04-10T16:33:10.651244","indexId":"70257226","displayToPublicDate":"2024-09-30T10:30:40","publicationYear":"2024","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Synopsis of basin-scale 3D framework modeling at the USGS Mapping Program","docAbstract":"No abstract available.
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]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Spangler, Leland R. 0000-0002-2223-7047","orcid":"https://orcid.org/0000-0002-2223-7047","contributorId":295310,"corporation":false,"usgs":true,"family":"Spangler","given":"Leland","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":909734,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70259803,"text":"70259803 - 2024 - Effects of recent wildfires on giant sequoia groves were anomalous at millennial timescales: a response to Hanson et al.","interactions":[],"lastModifiedDate":"2024-10-25T15:30:37.48096","indexId":"70259803","displayToPublicDate":"2024-09-30T10:23:34","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1636,"text":"Fire Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Effects of recent wildfires on giant sequoia groves were anomalous at millennial timescales: a response to Hanson et al.","docAbstract":"The giant sequoia (Sequoiadendron giganteum [Lindley] Buchholz) of California’s Sierra Nevada recently suffered historically unprecedented wildfires that killed an estimated 13–19% of seed-bearing sequoias across their native range. Hanson et al. recently sought to characterize post-fire reproduction in two severely burned sequoia groves, but their two papers (1) inaccurately portrayed sequoia fire ecology, (2) had methodological flaws, and (3) without supporting evidence, questioned efforts to prevent large, stand-replacing wildfires and to plant sequoia seedlings in areas of low post-fire regeneration.
Our analyses and literature review contradict many of Hanson et al.’s claims and implications. First, evidence indicates that preceding the recent wildfires, large, contiguous areas (>10 to >100 ha) of fire severe enough to kill most sequoias had been absent for at least a millennium, and probably much longer. The ancient sequoia fire regime was instead overwhelmingly dominated by surface fires in which most forest area burned at low or moderate severity interspersed with small forest gaps (hundredths of a hectare to a few hectares) created by local patches of higher-severity fire, within which most mature sequoias survived and most successful reproduction occurred. Prescribed fires have typically mimicked ancient fires and induced adequate sequoia regeneration. In contrast, in some extensive areas where recent wildfires killed most (or all) mature sequoias, regeneration has been well below historical levels, threatening a net loss of sequoia grove area. Methodologically, Hanson et al. reported sixfold greater post-fire sequoia seedling densities than others who sampled the same area; our assessments suggest their higher densities may have largely resulted from plot-placement bias. Finally, Hanson et al.’s comparisons of median seedling densities were inappropriate.
Hanson et al. questioned efforts to prevent large, high-severity wildfires in sequoia groves but did not acknowledge (1) that past fires sustained sequoia reproduction without the deaths of large fractions of mature sequoias, (2) the anomalous effects of recent wildfires, and (3) the acute conservation threat of losing large fractions of seed-bearing sequoias. Hanson et al.’s further implication, made without supporting evidence, that decisions to plant sequoia seedlings may be unwarranted ignores research showing that recent post-wildfire regeneration has often been well below historical levels.
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Despite regulatory efforts to mitigate risk, non-target wildlife may be unintentionally exposed to ARs through various trophic pathways, and depending on dose, exposure can result in adverse effects and mortality. Second-generation ARs (SGARs) are mixtures of cis- and trans-diastereoisomers (each including two stereoisomers) that exhibit similar in vitro inhibitory potency for vitamin K epoxide reductase in rodent microsomal assay systems. Some diastereoisomers and hence some individual stereoisomers are preferentially metabolized in vivo, resulting in residue patterns in exposed target rodents that differ from the bait formulations. Use of less persistent but equally potent SGAR stereoisomers in baits results in lower tissue residues in target rodents, which in turn constitutes lower risk when consumed by non-target wildlife. The toxicity of two brodifacoum formulations with stereoisomers having markedly different elimination half-lives in rats (Formulation A containing the two least persistent stereoisomers, and Formulation B containing the most persistent stereoisomer) were tested in a 7-day dietary feeding trial with American kestrels. Based on previous kestrel studies using commercially available brodifacoum, Formulations A and B were each provided at three dietary concentrations (0.05, 0.1 and 0.5 µg/g diet, 4 kestrels/dose level) predicted to cause a range of toxicity. Compared to unexposed controls, all kestrels that ingested 0.5 µg/g diet of the longer-lived Formulation B exhibited extreme coagulopathy. In contrast, the 0.5 µg/g diet of the shorter-lived Formulation A yielded only a modest lengthening of clotting time in just 1 of the 4 exposed kestrels. These findings support the notion that SGAR baits enriched with less persistent stereoisomers may pose lower hazard and ultimately risk to non-target wildlife.
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The U.S. Geological Survey visited 28 of these lakes and impoundments at 14 single and multiple waterbody systems to evaluate their appropriateness for characterizing drought. The data collection and computation methods at each system were then reviewed and checked for consistency. The types of historical monthly data available varied by system and included water surface elevation, depth of water below the spillway, volume, or reservoir capacity (percent full). For this analysis, water surface elevations and reservoir capacities were converted to volumes to assess the interannual variability in lake volumes. As a second level of assessment, analysis was also done on water surface elevation variability. Systems that did not have enough differentiation in monthly values between lake volume or water surface elevations to clearly demarcate drought levels were identified as unsuitable for use in the drought index for that month. This report discusses the limitations of using the reviewed lakes and impoundments as a drought index, as well as a list of best practices for data collection techniques to improve the confidence and reliability of the data collected.
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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Regional invasive species & climate change research to practice paper","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"University of Massachusetts Amherst","doi":"10.7275/hd7v-h449","usgsCitation":"Buonaiuto, D., Barker Plotkin, A., Bois, S., Brincka, M., Colberg, E., Colleran, B., and Morelli, T.L., 2024, Where there's a when there's a way. Shifting phenology & windows of opportunity for control, in Regional invasive species & climate change research to practice paper, 2 p., https://doi.org/10.7275/hd7v-h449.","productDescription":"2 p.","ipdsId":"IP-167302","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":486064,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2024-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Buonaiuto, Dan","contributorId":355377,"corporation":false,"usgs":false,"family":"Buonaiuto","given":"Dan","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":937184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barker Plotkin, Audrey","contributorId":292378,"corporation":false,"usgs":false,"family":"Barker Plotkin","given":"Audrey","email":"","affiliations":[{"id":37315,"text":"Harvard","active":true,"usgs":false}],"preferred":false,"id":937185,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bois, Sarah","contributorId":355378,"corporation":false,"usgs":false,"family":"Bois","given":"Sarah","affiliations":[{"id":84736,"text":"Linda Loring Nature Foundation","active":true,"usgs":false}],"preferred":false,"id":937186,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brincka, Matthew","contributorId":355380,"corporation":false,"usgs":false,"family":"Brincka","given":"Matthew","affiliations":[{"id":84737,"text":"New York State Parks","active":true,"usgs":false}],"preferred":false,"id":937187,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Colberg, Eva","contributorId":355381,"corporation":false,"usgs":false,"family":"Colberg","given":"Eva","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":937188,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Colleran, Brian","contributorId":355383,"corporation":false,"usgs":false,"family":"Colleran","given":"Brian","affiliations":[],"preferred":false,"id":937189,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":937190,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70261523,"text":"70261523 - 2024 - Studies to assess natural resource recovery and evaluate monitoring methods for restored bottomland hardwood forests","interactions":[],"lastModifiedDate":"2024-12-13T15:14:44.595886","indexId":"70261523","displayToPublicDate":"2024-09-30T09:10:02","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2006,"text":"Integrated Environmental Assessment and Management","active":true,"publicationSubtype":{"id":10}},"title":"Studies to assess natural resource recovery and evaluate monitoring methods for restored bottomland hardwood forests","docAbstract":"The Natural Resource Damage Assessment and Restoration process assesses natural resource injury due to oil or chemical spills and calculates the damages to compensate the public for those injuries. Ecological restoration provides a means for recovering resources injured or lost due to contamination from oil or chemical spills by restoring the injured site after remediation, or acquiring or reconstructing equivalent resources off site to replace those lost due to the spill. In the case of restored forests, once restoration is implemented, monitoring of forest ecology helps keep recovery on track, with the maturation of forest vegetation, recovered soil conditions, and development of microbial, fungal, and faunal communities, necessary for ecologically functioning forests. This series of papers focuses on applying methods for monitoring restoration progress in forest vegetation and soils, and amphibian, avian, and mammalian communities, assessing strengths and weaknesses of different methods, and evaluating levels of effort needed to obtain accurate indications of forest ecological condition.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry (SETAC)","doi":"10.1002/ieam.4996","usgsCitation":"Hooper, M.J., Struckhoff, M., Isanhart, J.P., Albers, J.L., Grabner, K., Green, N., Kunz, B.K., McDonald, M.V., and West, B.M., 2024, Studies to assess natural resource recovery and evaluate monitoring methods for restored bottomland hardwood forests: Integrated Environmental Assessment and Management, v. 20, no. 6, p. 1912-1916, https://doi.org/10.1002/ieam.4996.","productDescription":"5 p.","startPage":"1912","endPage":"1916","ipdsId":"IP-170053","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":466889,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ieam.4996","text":"Publisher Index Page"},{"id":465111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-11-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Hooper, Michael J.","contributorId":344824,"corporation":false,"usgs":false,"family":"Hooper","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":78382,"text":"formerly Columbia Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":920885,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Struckhoff, Matthew 0000-0002-4911-9956","orcid":"https://orcid.org/0000-0002-4911-9956","contributorId":201512,"corporation":false,"usgs":true,"family":"Struckhoff","given":"Matthew","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":920886,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Isanhart, John P.","contributorId":201904,"corporation":false,"usgs":false,"family":"Isanhart","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":36287,"text":"USDOI Office of Restoration and Damage Assessment, Denver, CO","active":true,"usgs":false}],"preferred":false,"id":920887,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Albers, Janice L. 0000-0002-6312-8269 jalbers@usgs.gov","orcid":"https://orcid.org/0000-0002-6312-8269","contributorId":3972,"corporation":false,"usgs":true,"family":"Albers","given":"Janice","email":"jalbers@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":920888,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grabner, Keith 0000-0003-0788-7751 kgrabner@usgs.gov","orcid":"https://orcid.org/0000-0003-0788-7751","contributorId":217705,"corporation":false,"usgs":true,"family":"Grabner","given":"Keith","email":"kgrabner@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":920889,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Green, Nicholas S.","contributorId":301918,"corporation":false,"usgs":false,"family":"Green","given":"Nicholas S.","affiliations":[{"id":65362,"text":"Kennesaw State University","active":true,"usgs":false}],"preferred":false,"id":920890,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kunz, Bethany K. 0000-0002-7193-9336 bkunz@usgs.gov","orcid":"https://orcid.org/0000-0002-7193-9336","contributorId":3798,"corporation":false,"usgs":true,"family":"Kunz","given":"Bethany","email":"bkunz@usgs.gov","middleInitial":"K.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":920891,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McDonald, M. Victoria","contributorId":344823,"corporation":false,"usgs":false,"family":"McDonald","given":"M.","email":"","middleInitial":"Victoria","affiliations":[{"id":16964,"text":"University of Central Arkansas","active":true,"usgs":false}],"preferred":false,"id":920892,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"West, Benjamin M 0000-0001-8355-0013","orcid":"https://orcid.org/0000-0001-8355-0013","contributorId":298588,"corporation":false,"usgs":true,"family":"West","given":"Benjamin","email":"","middleInitial":"M","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":920893,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70259545,"text":"70259545 - 2024 - Statistical analysis of Lake Tahoe secchi depth data","interactions":[],"lastModifiedDate":"2024-10-11T13:57:27.121649","indexId":"70259545","displayToPublicDate":"2024-09-30T08:52:09","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Statistical analysis of Lake Tahoe secchi depth data","docAbstract":"Secchi depth measurements in Lake Tahoe have been collected at a Long-Term Profile (LTP) monitoring site since 1968. 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","language":"English","publisher":"Tahoe Science Advisory Council","usgsCitation":"Naranjo, R.C., 2024, Statistical analysis of Lake Tahoe secchi depth data, 16 p.","productDescription":"16 p.","ipdsId":"IP-168331","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":462818,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.tahoesciencecouncil.org/project-list","linkFileType":{"id":5,"text":"html"}},{"id":462826,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Lake Tahoe","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.11446470824197,\n 39.21366571450457\n ],\n [\n -120.16965242081064,\n 39.102249370483676\n ],\n [\n -120.08208791686843,\n 38.932606385440636\n ],\n [\n -119.94227904502787,\n 38.933750744029425\n ],\n [\n -119.93050566634669,\n 39.25014399290501\n ],\n [\n -120.0666353573491,\n 39.24444253042536\n ],\n [\n -120.11446470824197,\n 39.21366571450457\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Naranjo, Ramon C. 0000-0003-4469-6831 rnaranjo@usgs.gov","orcid":"https://orcid.org/0000-0003-4469-6831","contributorId":3391,"corporation":false,"usgs":true,"family":"Naranjo","given":"Ramon","email":"rnaranjo@usgs.gov","middleInitial":"C.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":915688,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70259407,"text":"70259407 - 2024 - Microplastic and associated black particles from road-tire wear: Implications for radiative effects across the cryosphere and in the atmosphere","interactions":[],"lastModifiedDate":"2024-10-07T11:57:36.115271","indexId":"70259407","displayToPublicDate":"2024-09-30T06:55:46","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18737,"text":"JGR - Atmospheres","active":true,"publicationSubtype":{"id":10}},"title":"Microplastic and associated black particles from road-tire wear: Implications for radiative effects across the cryosphere and in the atmosphere","docAbstract":"The environmental effects of airborne micro- and nano-size plastic particles are poorly understood. Microscopy and chemical analyses of atmospherically deposited particles on snow surfaces at high elevation (2,865–3,690 m) in the Upper Colorado River basin (UCRB; Colorado Rocky Mountains) revealed the presence of black substances intimately associated with microplastic fibers, particles interpreted to have originated as tire matter. Identical and similar particles occur in shredded tires and road-surface samples. The substance responsible for the black color of all tires is carbon black, a graphitic light-absorbing tire additive produced by hydrocarbon combustion that homogeneously permeates the mixture of tire polymers and other additives. Such black tire matter may thus exert radiative effects closely similar to those of black carbon. The presence in snow of many organic compound types common to tires, measured by two-dimensional gas chromatography, suggests that atmospherically deposited black road-tire-wear matter is among the light-absorbing particulates that advance the onset and rate of snow melt in the UCRB. The mass of road-tire-wear particles shed from vehicles may be estimated by multiplying measured amounts of eroded tire-per-distance traveled by vehicular distances. Under a combination of measurements and assumptions about the amounts and radiative properties of atmospheric tire-wear particles, the radiative effects of these particles might add about 10%–30% to those effects from black carbon, an estimate ripe for revision. On regional and global scales, the amounts and effects of emitted and deposited tire-wear matter likely vary by factors of geographic source, transport pathway, and depositional setting.
Land use influences surface water quality, often alleviating stoichiometric constraints on primary production and altering biogeochemical cycling. However, land use effects on nutrient content and potential trace metal accumulation in aquatic plants remain unclear, and high concentrations of metals and altered nutrient ratios could impact the health of herbivores and detritivores. We tested for land use effects on nutrient and trace metal accumulation in a widespread riverine macrophyte, Podostemum ceratophyllum, collected from 91 locations from Georgia to Maine, USA in 2014–2016. We quantified carbon (C), nitrogen (N), phosphorus (P), their molar and mass ratios, N and C stable isotopes, and 17 additional elements in dried plants collected from each location to estimate relationships between plant tissue content and watershed land use, which we quantified as agriculture, forest, and development. Decreasing forest cover was correlated with increasing δ15N, Mg, Mn, and P in Podostemum tissue. Increasing urban development was correlated with increasing δ15N, Mg and P, while increasing agriculture was correlated with a decrease in C: P and the concentrations of multiple metals, along with increases in P, Mg and δ15N. Decreases in ratios of N: P and C:P with increasing agriculture and urban development in the watershed indicate more rapid P storage relative to C and N in plant tissue, and increased resource quality of the plant to consumers in these watersheds. We also observed potentially toxic dietary concentrations of some trace metals (B, Cd, Tl, Zn) in plant tissue which could be related to the plant's natural herbivory defense system or to land use. We conclude that land use influences the elemental composition of P. ceratophyllum, and potentially the quality and toxicity of the plant to herbivores and detritivores in eastern North American rivers.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2024.176118","usgsCitation":"Wood, J., Dietterich, L.H., Leasure, D.R., Jantzi, S., Maddox, T., Wenger, S., Skaggs, J., Rosemond, A.D., and Freeman, M., 2024, Elemental composition and potential toxicity of the riverine macrophyte Podostemum ceratophyllum Michx. reflects land use in eastern North America: Science of the Total Environment, v. 954, 176118, 14 p., https://doi.org/10.1016/j.scitotenv.2024.176118.","productDescription":"176118, 14 p.","ipdsId":"IP-144142","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":490988,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2024.176118","text":"Publisher Index Page"},{"id":465144,"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 -69.54256609727352,\n 43.88143574292508\n ],\n [\n -70.647563027507,\n 44.26997672061174\n ],\n [\n -73.8976845593064,\n 43.177908703325954\n ],\n [\n -74.07002050845693,\n 40.99340531964512\n ],\n [\n -72.05924526688266,\n 41.33951624483788\n ],\n [\n -70.23920091350011,\n 41.51880370179515\n ],\n [\n -69.54256609727352,\n 43.88143574292508\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.53957439072548,\n 37.96935046600281\n ],\n [\n -80.27133242619323,\n 38.11626273373102\n ],\n [\n -85.94943603496614,\n 34.90130349851556\n ],\n [\n -85.30759808373625,\n 33.510279887546815\n ],\n [\n -82.4448300394111,\n 34.00184838830782\n ],\n [\n -77.9718785239481,\n 36.58735830390653\n ],\n [\n -77.87536535646905,\n 37.23153468843074\n ],\n [\n -79.53957439072548,\n 37.96935046600281\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"954","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, James","contributorId":174400,"corporation":false,"usgs":false,"family":"Wood","given":"James","affiliations":[],"preferred":false,"id":921060,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dietterich, Lee H.","contributorId":333170,"corporation":false,"usgs":false,"family":"Dietterich","given":"Lee","email":"","middleInitial":"H.","affiliations":[{"id":79766,"text":"Department of Ecosystem Science and Sustainability, Colorado State University, Fort Collins, CO 80523; US Army Engineer Research and Development Center, Environmental Laboratory, Vicksburg, MS 39180","active":true,"usgs":false}],"preferred":false,"id":921061,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leasure, Douglas R.","contributorId":145643,"corporation":false,"usgs":false,"family":"Leasure","given":"Douglas","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":921062,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jantzi, Sarah","contributorId":347214,"corporation":false,"usgs":false,"family":"Jantzi","given":"Sarah","email":"","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":921063,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maddox, Thomas","contributorId":347217,"corporation":false,"usgs":false,"family":"Maddox","given":"Thomas","email":"","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":921064,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wenger, Seth J.","contributorId":177838,"corporation":false,"usgs":false,"family":"Wenger","given":"Seth J.","affiliations":[],"preferred":false,"id":921065,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Skaggs, Jonathan","contributorId":260315,"corporation":false,"usgs":false,"family":"Skaggs","given":"Jonathan","email":"","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":921066,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rosemond, Amy D.","contributorId":279630,"corporation":false,"usgs":false,"family":"Rosemond","given":"Amy","email":"","middleInitial":"D.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":921067,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":921068,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ]}