The Katahdin Woods and Waters National Monument, located in the forests of central Maine, is a newly (2016) established unit for the National Park Service. To better understand the condition of lands within the monument and inform management planning, Katahdin Woods and Waters National Monument resource managers wanted better information of the vegetation present within the monument. To meet this need, scientists at the U.S. Geological Survey Upper Midwest Environmental Sciences Center worked with ecologists at the Maine Natural Areas Program to catalog and map the vegetation of the Seboeis Unit of the monument. This report details this process, provides results of the survey and mapping efforts, presents results in the form of a vegetation map for the Seboeis Unit, and provides vegetation descriptions and a dichotomous key for the entire Katahdin Woods and Waters National Monument.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225078","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Strassman, A.C., Hop, K.D., Sattler, S.R., Schlawin, J., and Cameron, D., 2022, Vegetation map for the Seboeis Unit of Katahdin Woods and Waters National Monument: U.S. Geological Survey Scientific Investigations Report 2022–5078, 73 p., https://doi.org/10.3133/sir20225078.","productDescription":"Report: x, 73 p.; Data Releases","numberOfPages":"88","onlineOnly":"Y","ipdsId":"IP-130383","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":407273,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93HGWGB","text":"USGS data release","linkHelpText":"Vegetation map for the Seboeis Unit of Katahdin Woods and Waters National Monument (vector and tabular data)"},{"id":407272,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5078/images"},{"id":407267,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5078/coverthb.jpg"},{"id":407269,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5078/sir20225078.pdf","text":"Report","size":"19.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5078"},{"id":407270,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5078/sir20225078.XML"},{"id":409229,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BW6YWP","text":"USGS data release","linkHelpText":"2019 Katahdin Woods and Waters National Monument 4-band imagery products"}],"country":"United States","state":"Maine","otherGeospatial":"Seboeis Unit of Katahdin Woods and Waters National Monument","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -68.82465497885659,\n 46.12747294389601\n ],\n [\n -68.82465497885659,\n 45.82583589711629\n ],\n [\n -68.51101993751016,\n 45.82583589711629\n ],\n [\n -68.51101993751016,\n 46.12747294389601\n ],\n [\n -68.82465497885659,\n 46.12747294389601\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54603
Drylands represent more than 41% of the global land surface and are at degradation risk due to land use and climate change. Developing strategies to mitigate degradation and restore drylands in the face of these threats requires an understanding of how drylands are shaped by not only soils and climate, but also geology and geomorphology. However, few studies have completed such a comprehensive analysis that relates spatial variation in plant communities to all aspects of the geologic–geomorphic–edaphic–plant–climate system. The focus of this study is the Colorado Plateau, a high-elevation dryland in the southwestern United States, which is particularly sensitive to future change due to climate vulnerability and increasing land-use pressure. Here, we examined 135 long-term vegetation-monitoring sites in three national parks and characterized connections between geology, geomorphology, soils, climate, and dryland plant communities. To first understand the geologic and geomorphic influences on soil formation and characteristics, we explore associations between soil pedons, bedrock geology, and geomorphology. Then, we characterize principal axes of variation in plant communities and ascertain controls and linkages between components of the edaphic–geomorphic system and plant community ordinations. Geologic and geomorphic substrate exerted controls on important properties of the soil profile, particularly depth, water-holding capacity, rockiness, salinity, and fine sands. Ordination identified five distinct plant communities and three primary axes of variation, representing gradients of woody- to herbaceous-dominated communities (Axis 1), saline scrublands to C3 grasslands (Axis 2), and annual to perennial communities (Axis 3). Geology, geomorphology, and soil explained a large proportion of variation in Axis 1 (74%), while climate variables largely explained Axis 2 (68%), and Axis 3 was not well explained by the random forest models. The variables identified as most influential to each axis were, respectively: (1) soil depth; (2) aridity, lithology, and soil salinity; and (3) temperature and precipitation. We posit that Axis 3 represents a land degradation gradient due to historic grazing, likely exacerbated by dry conditions. Results provide a novel framework that links the geologic and geomorphic evolution of landscapes, with the distribution of soils and plant communities that can guide ecosystem management, exemplifying an approach applicable to drylands globally.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4273","usgsCitation":"Duniway, M.C., Benson, C., Nauman, T.W., Knight, A.C., Bradford, J., Munson, S.M., Witwicki, D.L., Livensperger, C., Van Scoyoc, M.W., Fisk, T.T., Thoma, D., and Miller, M.E., 2022, Geologic, geomorphic, and edaphic underpinnings of dryland ecosystems: Colorado Plateau landscapes in a changing world: Ecosphere, v. 13, no. 11, e4273, 27 p., https://doi.org/10.1002/ecs2.4273.","productDescription":"e4273, 27 p.","ipdsId":"IP-135505","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":488760,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4273","text":"Publisher Index Page"},{"id":435625,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92Z8NDP","text":"USGS data release","linkHelpText":"Soil, geologic, geomorphic, climate, and vegetation data from long-term monitoring plots (2009 - 2018) in Arches, Canyonlands, and Capitol Reef National Parks, Utah, USA"},{"id":410697,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","otherGeospatial":"Colorado Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.63689444724997,\n 36.734805586098716\n ],\n [\n -108.00129122959586,\n 36.72595486884292\n ],\n [\n -107.41606847690218,\n 37.63008491281205\n ],\n [\n -107.57066880734789,\n 38.70708139014661\n ],\n [\n -107.76120496171856,\n 39.973850096503895\n ],\n [\n -108.78556565774403,\n 40.46292505503848\n ],\n [\n -110.23348660705287,\n 40.36792094423029\n ],\n [\n -111.02839675350845,\n 39.403592925523014\n ],\n [\n -111.43291910676305,\n 38.05141646696123\n ],\n [\n -112.77571792678364,\n 37.21069090791468\n ],\n [\n -112.28678230930984,\n 36.79511547655869\n ],\n [\n -111.63689444724997,\n 36.734805586098716\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":859388,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Benson, Christopher","contributorId":296064,"corporation":false,"usgs":false,"family":"Benson","given":"Christopher","email":"","affiliations":[{"id":63978,"text":"formerly) US Geological Survey, Southwest Biological Science Center, Moab, UT","active":true,"usgs":false}],"preferred":false,"id":859389,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nauman, Travis W. 0000-0001-8004-0608 tnauman@usgs.gov","orcid":"https://orcid.org/0000-0001-8004-0608","contributorId":169241,"corporation":false,"usgs":true,"family":"Nauman","given":"Travis","email":"tnauman@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":859390,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knight, Anna C. 0000-0002-9455-2855","orcid":"https://orcid.org/0000-0002-9455-2855","contributorId":255113,"corporation":false,"usgs":true,"family":"Knight","given":"Anna","email":"","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":859391,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":859392,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":859393,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Witwicki, Dana L.","contributorId":207763,"corporation":false,"usgs":false,"family":"Witwicki","given":"Dana","email":"","middleInitial":"L.","affiliations":[{"id":37628,"text":"National Park Service Inventory and Monitoring Program, P.O. Box 848, Moab, UT 84532, USA","active":true,"usgs":false}],"preferred":false,"id":859394,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Livensperger, Carolyn","contributorId":260927,"corporation":false,"usgs":false,"family":"Livensperger","given":"Carolyn","email":"","affiliations":[{"id":52723,"text":"National Park Service, Capitol Reef National Park, 52 Headquarters Dr., Torrey UT 84775","active":true,"usgs":false}],"preferred":false,"id":859395,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Van Scoyoc, Matthew W. 0000-0001-6821-4476","orcid":"https://orcid.org/0000-0001-6821-4476","contributorId":290213,"corporation":false,"usgs":false,"family":"Van Scoyoc","given":"Matthew","email":"","middleInitial":"W.","affiliations":[{"id":62383,"text":"Southeast Utah Group, National Park Service, Moab, UT","active":true,"usgs":false}],"preferred":false,"id":859396,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Fisk, Terry T","contributorId":289096,"corporation":false,"usgs":false,"family":"Fisk","given":"Terry","email":"","middleInitial":"T","affiliations":[{"id":62042,"text":"Water Resources Division, National Park Service","active":true,"usgs":false}],"preferred":false,"id":859397,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Thoma, David","contributorId":265911,"corporation":false,"usgs":false,"family":"Thoma","given":"David","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":859398,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Miller, Mark E.","contributorId":91580,"corporation":false,"usgs":false,"family":"Miller","given":"Mark","email":"","middleInitial":"E.","affiliations":[{"id":6959,"text":"National Park Service Southeast Utah Group","active":true,"usgs":false}],"preferred":false,"id":859399,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70238582,"text":"70238582 - 2022 - Mapping 2-D bedload rates throughout a sand-bed river reach from high-resolution acoustical surveys of migrating bedforms","interactions":[],"lastModifiedDate":"2022-11-30T12:53:57.31331","indexId":"70238582","displayToPublicDate":"2022-11-08T06:50:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Mapping 2-D bedload rates throughout a sand-bed river reach from high-resolution acoustical surveys of migrating bedforms","docAbstract":"This paper introduces a method for determining spatially-distributed, 2-D bedload rates using repeat, high-resolution surveys of the bed topography. As opposed to existing methods, bedform parameters and bedload rates are computed from bed elevation profiles interpolated along the local bedform velocities. The bedform velocity fields are computed applying Large-Scale Particle Image Velocimetry, initially developed for surface velocity measurements, to pairs of successive Digital Elevation Models (DEMs). The bathymetry data are interpolated along the direction of each bedform velocity and the mean height of the closest bedform is computed. The dune shape factor is also evaluated along each bedform direction of travel. The local bedload fluxes can be computed by multiplying the bedform velocity by its mean height averaged over the successive two DEMs, and they can be time-averaged over a series of DEM pairs. This method is applied to a high-resolution acoustical survey of an approximately 300 m long by 40 m wide reach of the Colorado River in Grand Canyon upstream from Diamond Creek, USA. The repeat period was about 6–10 min and bed elevation was interpolated every 0.25 m. The obtained results provide insight to the spatial and temporal variability of bedload rates, bedform parameters and bedload fluxes through cross-sections. The method can be applied to other repeated acoustical surveys of river reaches provided that the space and time resolutions are high enough to capture the local movement of bedforms.
This guide is intended to provide managers, decision makers, and other practitioners with advice on conducting a rapid assessment of the social dimensions of drought. Findings from a rapid assessment can provide key social context that may aid in decision making, such as when preparing a drought plan, allocating local drought resilience funding, or gathering the support of local agencies and organizations for collective action related to drought mitigation.
Part I—In the introduction to Part I, we describe the unique problems associated with drought—particularly its slow onset and long duration, which make it difficult to define drought—and highlight five major types of drought (see Box 1). We introduce a few social dimensions of drought (such as economic and institutional perspectives), demonstrate how these dimensions can be interrelated, and describe a few of the modern challenges (such as transformational change and cascading risks) that practitioners face.
We also provide background on the rapid assessment method, first describing it as a “snapshot” of the social landscape, then providing some key advantages of the method (it can be quicker and cheaper than more in-depth methods), and lastly describing how secondary data and other methods can help overcome some of the disadvantages of rapid assessments.
Then, after summarizing the process of developing this guide, we outline the process of using the guide. Importantly, we compare the guide to a travel guide, which provides many different types of information and is best approached with specific interests in mind. Ultimately, we hope for this guide to be malleable enough that it can be helpful to researchers and practitioners in many different contexts, using many different research methods. Related to how to use the guide, we characterize the type of person who might be motivated to use this guide. We also specify key qualifications for a researcher conducting a rapid assessment, drawing particular attention to training on ethical considerations.
We sketch out key considerations when choosing social dimensions of drought to focus on, and the type of data used for analysis. First, it is important to note that in this guide we provide nine important social dimensions of drought, but this is by no means a comprehensive list, and a researcher may find that other dimensions better fit their local context. Second, we provide some pros and cons to a narrow (focusing on just a few dimensions or at a smaller scale) versus broad research focus. Lastly, we describe the pros and cons of using primary versus secondary data (one strategy is to use both, sequentially) and qualitative versus quantitative data.
Ultimately, Part I of this guide functions as an exploration of the various decisions a researcher will make when designing a rapid assessment. These decisions will inform the type of findings and other outcomes that result from the rapid assessment.
Part II—Part II of this guide introduces nine key social dimensions of drought: defining the problem of drought, individual perceptions, social relationships, technology, economics and livelihoods, water governance, decision making, information, and social vulnerability. Each section provides background and key considerations related to a particular dimension, as well as ideas for how to explore the dimension via a rapid assessment.
Part III—Part III of this guide provides two hypothetical examples of how one might use this guide to aid the practitioner in implementing the lessons learned here. In the first example, a watershed group uses two dimensions, defining the problem of drought and social relationships, to inform a community meeting about protecting fisheries from drought. In the second example, a resource manager uses the economics and livelihoods and social vulnerability dimensions to inform the development of a livestock grazing drought management plan.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm17A1","usgsCitation":"Clifford, K.R., Goolsby, J.B., Cravens, A.E., and Cooper, A.E., 2022, Rapidly assessing social characteristics of drought preparedness and decision making: A guide for practitioners: U.S. Geological Survey Techniques and Methods 17-A1, 41 p., https://doi.org/10.3133/tm17A1.","productDescription":"vii, 41 p.","onlineOnly":"Y","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":409066,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/17/a1/tm17a1.xml"},{"id":409065,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/17/a1/images"},{"id":409061,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/17/a1/coverthb.jpg"},{"id":409062,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/17/a1/tm17a1.pdf","text":"Report","size":"1.47 MB","linkFileType":{"id":1,"text":"pdf"},"description":"T and M 17-A1"}],"contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
Habitat selection involves a series of decisions that are arguably the most important decisions that animals make and these decisions occur at multiple hierarchical spatial scales. Colonial-nesting birds face a unique challenge when selecting a nest site because each bird’s choices are severely constrained by other birds within their breeding colony. Individuals must seek out optimum nesting locations within the constraint of the colony’s geographic location. We investigated how water depth and proximity to open water affected 4th-order nest-site selection of Western and Clark’s Grebes (Aechmophorus occidentalis, Aechmophorus clarkii), colonial nesting waterbirds that have declined in abundance across their range. We used an orthomosiac that we created from ~ 500 aerial drone images of a large breeding colony to construct a Resource Selection Function to describe microhabitat features that influence nest-site placement within the colony footprint. Grebes preferred to nest in portions of the colony with intermediate water depths (40-80 cm during nest construction) and they preferred to nest in portions of the colony furthest from open water. Understanding how individual birds make use of available microhabitat features within the footprint of their breeding colony can help inform conservation efforts of colonial-nesting birds, particularly for species that nest in wetland habitats whose water levels are managed for human use.
","language":"English","publisher":"Springer Link","doi":"10.1007/s13157-022-01602-1","usgsCitation":"Lachman, D.A., Conway, C.J., Vierling, K.T., Matthews, T., and Mack, D., 2022, Drones and bathymetry show the importance of optimal water depth for nest placement within breeding colonies of Western and Clark’s grebes: Wetlands, v. 42, 110, 10 p., https://doi.org/10.1007/s13157-022-01602-1.","productDescription":"110, 10 p.","ipdsId":"IP-132937","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":429886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","county":"Valley County","otherGeospatial":"Cascade Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.20273923505505,\n 44.769058037542806\n ],\n [\n -116.20273923505505,\n 44.47495390440537\n ],\n [\n -116.01258023679465,\n 44.47495390440537\n ],\n [\n -116.01258023679465,\n 44.769058037542806\n ],\n [\n -116.20273923505505,\n 44.769058037542806\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"42","noUsgsAuthors":false,"publicationDate":"2022-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Lachman, Deo A.","contributorId":338149,"corporation":false,"usgs":false,"family":"Lachman","given":"Deo","email":"","middleInitial":"A.","affiliations":[{"id":81087,"text":"University of Idaho, Department of Fish and Wildlife Sciences","active":true,"usgs":false}],"preferred":false,"id":902975,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902976,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vierling, Kerri T.","contributorId":338150,"corporation":false,"usgs":false,"family":"Vierling","given":"Kerri","email":"","middleInitial":"T.","affiliations":[{"id":81087,"text":"University of Idaho, Department of Fish and Wildlife Sciences","active":true,"usgs":false}],"preferred":false,"id":902977,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matthews, Ty","contributorId":338151,"corporation":false,"usgs":false,"family":"Matthews","given":"Ty","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":902978,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mack, Diane Evans","contributorId":338152,"corporation":false,"usgs":false,"family":"Mack","given":"Diane Evans","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":902979,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70242697,"text":"70242697 - 2022 - Stream corridor and upland sources of fluvial sediment and phosphorus from a mixed urban-agricultural tributary to the Great Lakes","interactions":[],"lastModifiedDate":"2023-04-13T12:18:36.893973","indexId":"70242697","displayToPublicDate":"2022-11-06T07:13:22","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Stream corridor and upland sources of fluvial sediment and phosphorus from a mixed urban-agricultural tributary to the Great Lakes","docAbstract":"Like many impaired Great Lakes tributaries, Apple Creek, Wisconsin (119 km2) has Total Maximum Daily Load (TMDL) targets for reducing suspended sediment and total phosphorus by 51.2 % and 64.2 %, respectively. From August 2017 - October 2018, a stream sediment budget and fingerprinting integrated study was conducted to quantify upland and stream corridor sources of suspended sediment and sediment-bound phosphorus. Phosphorus concentrations varied among source groups and fluvial sediments, with higher concentrations among suspended sediment and cropland soils. Eroding streambanks identified in the stream corridor sediment budget accounted for 100 % of the TMDL Soil and Water Assessment Tool (SWAT) suspended sediment load but only 20 % of the total phosphorus load. Fine-grained streambed sediment equated to approximately-three years of modeled suspended sediment load but only one third of total phosphorus load. The two primary sources of fine-grained streambed sediment were streambanks and cropland, with relative streambank contributions increasing with downstream direction and watershed area. The relative proportion of suspended sediment varied by season and streamflow; however, cropland and streambank erosion accounted for 54 % and 23 % of the suspended sediment when weighted by of the proportion for representative streamflow. Urban land was a source in the upper watershed, but the signature was sequestered by a mid-watershed detention basin. Contributions from construction sites were higher in the fall 2018, likely corresponding to increased activity following a wet spring. These integrated techniques helped describe sources, transport, and sinks of fluvial sediment and phosphorus throughout the watershed at a range of spatial and temporal scales.
Across the Pacific Northwest, there are many examples of artificial structures created to allow passage of upstream-migrating salmon over natural barriers. We studied upstream passage across three structures installed in 1989 to allow passage of salmon over Lake Creek Falls, a series of three natural waterfalls at the outlet of Triangle Lake on Lake Creek, in the central Oregon Coast Range (lat 123.57508°; long 44.15735°). To track upstream passage by adult coho salmon (Oncorhynchus kisutch), 87 fish were tagged using gastrically implanted radio tags. Tracking was accomplished with a series of stationary receivers installed to detect crossings at each of three structures—over Lake Creek Falls using two upstream Denil-type ladders and a bypass downstream constructed to mimic a natural side channel. Tracking spanned the upstream migration and spawn timing for adult coho salmon in the basin and extended from October 2019 to February 2020. A total of 15 coho salmon (17 percent) were tagged in October, 30 coho salmon (35 percent) were tagged in November, and 42 coho salmon (48 percent) were tagged in December. Later-than-normal precipitation and associated low discharge delayed upstream migrations. Accordingly, most fish arrived late in the season (late November and December) and in sudden flushes with the erratic rain events. Fish that were tagged earlier were more likely to cross all three ladders, with more than 93 percent of fish tagged in October compared to 46.7 and 19.0 percent of November and December fish passing, respectively. The decline in passage rate could be attributed to the overlapping influences of stream discharge and advanced stage of maturation (lower energy reserves) of fish later in the season. Near the end of the study, both fish that crossed and fish obstructed by barriers were observed in tributaries known to be used for spawning by coho salmon. Without a much longer-term study involving many more fish than the current study, more intensive tracking, and coverage of different flow years, firm conclusions are difficult to draw regarding the overall influences of the passage structures on the likelihood of upstream passage by adult coho salmon. However, substantial numbers of fish are capable of crossing during certain conditions. The population-level consequences of the barriers on spawning distribution and the production of coho salmon in the watershed are not clear. Additional empirical study or population modeling could be used to address this question in more detail.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221083","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Fischer, R.B., Dunham, J., Scheidt, N., Hansen, A.C., and Heaston, E.D., 2022, Passage of adult coho salmon (Oncorhynchus kisutch) over Lake Creek Falls, Oregon, 2019: U.S. Geological Survey Open-File Report 2022–1083, 19 p., https://doi.org/10.3133/ofr20221083.","productDescription":"vii, 19 p.","onlineOnly":"Y","ipdsId":"IP-130393","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":409177,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1083/coverthb.jpg"},{"id":409181,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1083/ofr20221083.XML"},{"id":409180,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1083/images"},{"id":409179,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221083/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1083"},{"id":409178,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1083/ofr20221083.pdf","text":"Report","size":"21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1083"}],"country":"United States","state":"Oregon","otherGeospatial":"Lake Creek Falls","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.61844237310005,\n 44.17170307975459\n ],\n [\n -123.61844237310005,\n 44.131057340436286\n ],\n [\n -123.5593908594283,\n 44.131057340436286\n ],\n [\n -123.5593908594283,\n 44.17170307975459\n ],\n [\n -123.61844237310005,\n 44.17170307975459\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
777 NW 9th Street, Suite 400
Corvallis, OR 97330
The purpose of the Upper Klamath Basin Groundwater Flow Model (UKBGFM) is to simulate groundwater conditions in the Upper Klamath Basin under historical and predevelopment conditions. The UKBGFM quantifies estimates of and changes in groundwater levels, storage, pumping, drainage flow to tile drains, evapotranspiration, and flow between the Upper Klamath Basin and neighboring basins. The quantifications of base flow to streams and seepage to and from lakes and reservoirs can be used as inputs to the RiverWare Mass Balance Model (Zagona and others, 2001), a companion model being developed as part of the Klamath Natural Flow Study (KNFS).
","language":"English","publisher":"U.S. Bureau of Reclamation","usgsCitation":"Traum, J.A., and Boyce, S.E., 2022, Klamath natural flow study, Upper Klamath Basin groundwater flow model: Fact Sheet, 2 p.","productDescription":"2 p.","ipdsId":"IP-145778","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":418055,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://www.usbr.gov/mp/kbao/docs/04-factsheet-gwmodeling-final.pdf"},{"id":418057,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Upper Klamath basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.54532325728275,\n 42.588031447169925\n ],\n [\n -124.57092240453784,\n 42.588031447169925\n ],\n [\n -124.57092240453784,\n 41.175\n ],\n [\n -121.54532325728275,\n 41.175\n ],\n [\n -121.54532325728275,\n 42.588031447169925\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Traum, Jonathan A. 0000-0002-4787-3680 jtraum@usgs.gov","orcid":"https://orcid.org/0000-0002-4787-3680","contributorId":4780,"corporation":false,"usgs":true,"family":"Traum","given":"Jonathan","email":"jtraum@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856125,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyce, Scott E. 0000-0003-0626-9492 seboyce@usgs.gov","orcid":"https://orcid.org/0000-0003-0626-9492","contributorId":4766,"corporation":false,"usgs":true,"family":"Boyce","given":"Scott","email":"seboyce@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856126,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70237965,"text":"ofr20221078 - 2022 - Abundance of eelgrass (Zostera marina) at key Black Brant (Branta bernicla nigricans) wintering sites along the northern Pacific coast of Baja California, Mexico, 1998–2012","interactions":[],"lastModifiedDate":"2023-09-18T20:02:25.588335","indexId":"ofr20221078","displayToPublicDate":"2022-11-03T07:10:46","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":"2022-1078","displayTitle":"Abundance of Eelgrass (Zostera marina) at Key Black Brant (Branta bernicla nigricans) Wintering Sites Along the Northern Pacific Coast of Baja California, Mexico, 1998–2012","title":"Abundance of eelgrass (Zostera marina) at key Black Brant (Branta bernicla nigricans) wintering sites along the northern Pacific coast of Baja California, Mexico, 1998–2012","docAbstract":"Trends in the abundance and distribution of eelgrass (Zostera marina), the primary winter forage of black brant (Branta bernicla nigricans), was evaluated at three major wintering sites for black brant along the northern Pacific coast of Baja California, Mexico. This region of northwestern Mexico contains significant beds of eelgrass that were showing signs of decline, which may negatively affect the Pacific flyway population of black brant. Embayment-wide surveys of eelgrass were conducted at Bahia San Quintin (BSQ), Laguna Ojo de Liebre (LOL), and Laguna San Ignacio (LSI) between 1998 and 2012 to estimate baselines and trends in the distribution and abundance of this seagrass in Mexico. Eelgrass was the most abundant and frequently encountered seagrass in each site across survey years. Density and aboveground biomass of eelgrass was greater in BSQ than in LOL and LSI while abundance of widgeongrass (Ruppia maritima), a secondary source of food for brant, was greatest in LSI across survey years. Widgeongrass occurred higher in the intertidal zone than did eelgrass in all embayments, and both seagrasses generally shifted to lower water depths along a southward latitudinal gradient. A negative temporal trend in abundance of seagrasses was detected in BSQ that appeared linked to impacts of climate warming and an increase in macroalgae populations. Decreases in abundance of seagrasses were also detected in LOL and LSI, although long-term trends were less certain in LOL. Overall, declines in abundance of eelgrass in Baja California may be influencing the ongoing shift in the winter distribution of brant to areas north of the Mexican border.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221078","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Ward, D.H., 2022, Abundance of eelgrass (Zostera marina) at key Black Brant (Branta bernicla nigricans) wintering sites along the northern Pacific coast of Baja California, Mexico, 1998–2012: U.S. Geological Survey Open-File Report 2022–1078, 15 p., https://doi.org/10.3133/ofr20221078.","productDescription":"Report: vi, 15 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-135227","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":409019,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WEK4JI","text":"USGS data release","description":"USGS data release.","linkHelpText":"Mapping data of eelgrass (Zostera marina) distribution, Alaska and Baja California, Mexico"},{"id":409018,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H4LBP3","text":"USGS data release","description":"USGS data release.","linkHelpText":"Point sampling data for eelgrass (Zostera marina) and widgeongrass (Ruppia maritima) abundance in embayments of the north Pacific coast of Baja California, Mexico, 1998–2012"},{"id":409021,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1078/ofr20221078.XML"},{"id":409020,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1078/images"},{"id":409042,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221004","text":"OFR 2022-1004 —","description":"OFR 2022-1004","linkHelpText":"Spatial extent of seagrasses (Zostera marina and Ruppia maritima) along the central Pacific coast of Baja California, Mexico, 1999–2000"},{"id":409015,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1078/coverthb2.jpg"},{"id":409017,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221078/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1078"},{"id":409016,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1078/ofr20221078.pdf","text":"Report","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1078"}],"country":"Mexico","otherGeospatial":"Baja California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.34490212994275,\n 28.246325178662076\n ],\n [\n -115.34490212994275,\n 26.352495017715754\n ],\n [\n -111.76335916119284,\n 26.352495017715754\n ],\n [\n -111.76335916119284,\n 28.246325178662076\n ],\n [\n -115.34490212994275,\n 28.246325178662076\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
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Recent literature has demonstrated the sensitivity of mayflies to environmental contaminants. However, to date, there are no methods approved by the US Environmental Protection Agency for using sensitive insects like mayflies in whole-effluent toxicity or receiving water toxicity tests. The parthenogenetic mayfly Neocloeon triangulifer has been shown to be amenable to continuous culture in the laboratory, and methods have been described for its use in both acute and chronic toxicity studies. The goal of the present study was to investigate aspects of N. triangulifer testing and culturing methods that might require adjustment so that they are applicable for testing effluents and receiving waters in a short-term exposure. To this end, the influence of organism age, test duration, and test temperature on sensitivity to NaCl as a reference toxicant were tested (concentrations ranging from 182 to 2489 mg/L). Further studies were conducted to assess the utility of commercially available diets and the influence of nutrient amendment of water on organism growth and sensitivity. Seven-day NaCl tests started with less than 24-h-old larvae were similar in sensitivity to 14-day and full life chronic tests, and were much more sensitive than those started with 7-day-old organisms. Reducing test temperature from 25 °C to 22 °C had a minor influence on culture timing, and little impact on sensitivity to NaCl. In other experiments, reconstituted test water supplemented with nutrients to potentially improve in-test food quality had minimal effect on growth at 7 days and did not significantly alter acute sensitivity to NaCl relative to unamended reconstituted water. A suitable commercially available, ready-to-feed diet substitute for cultured diatoms was not found. Testing N. triangulifer in effluents or receiving waters with the methods recommended will complement similar methods for Ceriodaphnia dubia.
","language":"English","publisher":"Wiley","doi":"10.1002/etc.5463","usgsCitation":"Soucek, D.J., Dickinson, A., and Norberg-King, T.J., 2022, Influence of test method variables on sensitivity of Neocloeon triangulifer to a reference toxicant in short-term, effluent style evaluations: Environmental Toxicology and Chemistry, v. 41, no. 11, p. 2758-2768, https://doi.org/10.1002/etc.5463.","productDescription":"11 p.","startPage":"2758","endPage":"2768","ipdsId":"IP-138022","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":435633,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V2UFL3","text":"USGS data release","linkHelpText":"Survival, and growth of Neocloeon triangulifer under different test conditions in effluent style evaluations"},{"id":412677,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-08-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Soucek, David J. 0000-0002-7741-0193 drieckssoucek@usgs.gov","orcid":"https://orcid.org/0000-0002-7741-0193","contributorId":295408,"corporation":false,"usgs":true,"family":"Soucek","given":"David","email":"drieckssoucek@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":863229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dickinson, Amy","contributorId":224592,"corporation":false,"usgs":false,"family":"Dickinson","given":"Amy","email":"","affiliations":[{"id":40897,"text":"Illinois Natural History Survey, University of Illinois, Urbana-Champaign, IL","active":true,"usgs":false}],"preferred":false,"id":863230,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Norberg-King, Teresa J.","contributorId":175087,"corporation":false,"usgs":false,"family":"Norberg-King","given":"Teresa","email":"","middleInitial":"J.","affiliations":[{"id":13485,"text":"U.S. Environmental Protection Agency, Duluth, MN","active":true,"usgs":false}],"preferred":false,"id":863231,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70240392,"text":"70240392 - 2022 - Invasive species control and management: The sea lamprey story","interactions":[],"lastModifiedDate":"2023-02-07T14:55:10.876653","indexId":"70240392","displayToPublicDate":"2022-11-01T08:41:41","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"10","title":"Invasive species control and management: The sea lamprey story","docAbstract":"Control of invasive species is a critical component of conservation biology given the catastrophic damage that they can cause to the ecosystems they invade. This is particularly evident with sea lamprey (Petromyzon marinus) in the Laurentian Great Lakes. Native to the Atlantic Ocean, the sea lamprey's ability to osmoregulate in fresh water, its wide thermal tolerance, generalist diet, and high fecundity allowed it to rapidly reach pest proportions in the prey-rich Great Lakes once it gained access through shipping canals. The invasion exacerbated declines in Great Lakes fisheries caused by overharvest, culminating in the crash of lake trout (Salvelinus namaycush) and other fish populations. In the last 60 years, however, a highly successful sea lamprey control program has reduced sea lamprey to ∼10% of their peak abundance and has been instrumental in enabling the rehabilitation of the Great Lakes ecosystem. In this chapter, we: (1) discuss the likely vectors of the invasion and the physiological attributes of sea lamprey that enabled them to become established in the Great Lakes; (2) review the two cornerstones of the sea lamprey control program—which relies on a combination of pesticides to eradicate multiple generations of larval sea lamprey in their nursey streams, and in-stream barriers to restrict the upstream migration of spawning lamprey—both of which exploit unique physiological vulnerabilities of sea lamprey; (3) describe how sea lamprey control can adversely affect non-target species and how these can be mitigated; (4) show how physiology-based approaches are improving our understanding of the lethal and sublethal effects of sea lamprey on host fishes; and (5) discuss the future of conservation physiology in sea lamprey control. The prime challenge in the next several decades of the Anthropocene will be to further refine the specificity of control tools while maintaining their efficacy, and to adapt to a warming climate and other anthropogenic activities affecting the Great Lakes and their tributaries.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Fish physiology","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/bs.fp.2022.09.001","usgsCitation":"Wilkie, M.P., Johnson, N.S., and Docker, M.F., 2022, Invasive species control and management: The sea lamprey story, chap. 10 of Fish physiology, v. 39B, p. 489-579, https://doi.org/10.1016/bs.fp.2022.09.001.","productDescription":"91 p.","startPage":"489","endPage":"579","ipdsId":"IP-140668","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":412814,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Erie, Lake Huron, Lake Michigan, Lake Ontario, Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n 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F.","contributorId":195099,"corporation":false,"usgs":false,"family":"Docker","given":"Margaret","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":863650,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70238799,"text":"70238799 - 2022 - New generation hyperspectral sensors DESIS and PRISMA provide improved agricultural crop classifications","interactions":[],"lastModifiedDate":"2022-12-13T14:27:49.816431","indexId":"70238799","displayToPublicDate":"2022-11-01T08:11:28","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5987,"text":"Photogrammetric Engineering & Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"New generation hyperspectral sensors DESIS and PRISMA provide improved agricultural crop classifications","docAbstract":"Using new remote sensing technology to study agricultural crops will support advances in food and water security. The recently launched, new generation spaceborne hyperspectral sensors, German DLR Earth Sensing Imaging Spectrometer (DESIS) and Italian PRecursore IperSpettrale della Missione Applicativa (PRISMA), provide unprecedented data in hundreds of narrow spectral bands for the study of the Earth. Therefore, our overarching goal in this study was to use these data to explore advances that can be made in agricultural research. We selected PRISMA and DESIS images during the 2020 growing season in California's Central Valley to study seven major crops. PRISMA and DESIS images were highly correlated (R 2of 0.9–0.95). Out of the 235 DESIS bands (400–1000 nm) and 238 PRISMA bands (400–2500 nm), 26 (11%) and 45 (19%) bands, respectively, were optimal to study agricultural crops. These optimal bands provided crop type classification accuracies of 83–90%. Hyperspectral vegetation indices to estimate plant pigment content, stress, biomass, moisture, and cellulose/lignin content were also identified.
","language":"English","publisher":"American Society for Photogrammetry and Remote Sensing","doi":"10.14358/PERS.22-00039R2","usgsCitation":"Aneece, I.P., and Thenkabail, P., 2022, New generation hyperspectral sensors DESIS and PRISMA provide improved agricultural crop classifications: Photogrammetric Engineering & Remote Sensing, v. 88, no. 11, p. 715-729, https://doi.org/10.14358/PERS.22-00039R2.","productDescription":"15 p.","startPage":"715","endPage":"729","ipdsId":"IP-137552","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":445966,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14358/pers.22-00039r2","text":"Publisher Index Page"},{"id":435634,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98LO5D4","text":"USGS data release","linkHelpText":"DESIS and PRISMA spectral library of agricultural crops in California's Central Valley in the 2020 Growing Season"},{"id":410361,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121,\n 37.15\n ],\n [\n -121,\n 36.75\n ],\n [\n -120.333,\n 36.75\n ],\n [\n -120.333,\n 37.15\n ],\n [\n -121,\n 37.15\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"88","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Aneece, Itiya P. 0000-0002-1201-5459","orcid":"https://orcid.org/0000-0002-1201-5459","contributorId":208265,"corporation":false,"usgs":true,"family":"Aneece","given":"Itiya","middleInitial":"P.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":858748,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad 0000-0002-2182-8822","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":220239,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":858749,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238033,"text":"70238033 - 2022 - Warming-driven erosion and sediment transport in cold regions","interactions":[],"lastModifiedDate":"2022-12-15T15:17:16.294124","indexId":"70238033","displayToPublicDate":"2022-11-01T07:28:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12813,"text":"Nature--Reviews of Earth and Environment","active":true,"publicationSubtype":{"id":10}},"title":"Warming-driven erosion and sediment transport in cold regions","docAbstract":"Rapid atmospheric warming since the mid-twentieth century has increased temperature-dependent erosion and sediment-transport processes in cold environments, affecting food, energy and water security. In this Review, we summarize landscape changes in cold environments and provide a global inventory of increases in erosion and sediment yield driven by cryosphere degradation. Anthropogenic climate change, deglaciation, and thermokarst disturbances are causing increased sediment mobilization and transport processes in glacierized and periglacierized basins. With continuous cryosphere degradation, sediment transport will continue to increase until reaching a maximum (peak sediment). Thereafter, transport is likely to shift from a temperature-dependent regime toward a rainfall-dependent regime roughly between 2100–2200. The timing of the regime shift would be regulated by changes in meltwater, erosive rainfall and landscape erodibility, and complicated by geomorphic feedbacks and connectivity. Further progress in integrating multisource sediment observations, developing physics-based sediment-transport models, and enhancing interdisciplinary and international scientific collaboration is needed to predict sediment dynamics in a warming world.
No abstract available.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"2021 Interim summary report: Invasive carp monitoring and response plan","largerWorkSubtype":{"id":3,"text":"Organization Series"},"language":"English","publisher":"Invasive Carp Regional Coordinating Committee","collaboration":"U.S. Army Corps of Engineers (USACE); U.S. Environmental Protection Agency (US EPA); Great Lakes Restoration Initiative (GLRI); Great Lakes Fishery Commission (GLFC)","usgsCitation":"Brey, M.K., Knights, B.C., Stanton, J., Bailey, S., Harrison, T.J., Appel, D., Fritts, A.K., Duncker, J.J., and Jackson, P.R., 2022, USGS Telemetry Project: Interim Summary Report, 4 p.","productDescription":"4 p.","startPage":"44","endPage":"47","ipdsId":"IP-139583","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":411179,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://invasivecarp.us/PlansReports.html","linkFileType":{"id":5,"text":"html"}},{"id":411180,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinios","city":"Chicago","otherGeospatial":"Chicago area waterway system, lower Des Plaines River, upper Illinois River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.43112380718674,\n 42.441954655237765\n ],\n [\n -90.0705596136894,\n 42.441954655237765\n ],\n [\n -90.0705596136894,\n 40.87479938214008\n ],\n [\n -87.43112380718674,\n 40.87479938214008\n ],\n [\n -87.43112380718674,\n 42.441954655237765\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Brey, Marybeth K. 0000-0003-4403-9655 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0000-0002-6225-3703","orcid":"https://orcid.org/0000-0002-6225-3703","contributorId":237371,"corporation":false,"usgs":true,"family":"Stanton","given":"Jessica","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":860342,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bailey, Sean 0000-0003-0361-7914 sbailey@usgs.gov","orcid":"https://orcid.org/0000-0003-0361-7914","contributorId":198515,"corporation":false,"usgs":true,"family":"Bailey","given":"Sean","email":"sbailey@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":860363,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harrison, Travis J. 0000-0002-9195-738X","orcid":"https://orcid.org/0000-0002-9195-738X","contributorId":213966,"corporation":false,"usgs":true,"family":"Harrison","given":"Travis","email":"","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":860346,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Appel, Douglas 0000-0001-8775-1058","orcid":"https://orcid.org/0000-0001-8775-1058","contributorId":268159,"corporation":false,"usgs":true,"family":"Appel","given":"Douglas","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":860343,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fritts, Andrea K. 0000-0003-2142-3339","orcid":"https://orcid.org/0000-0003-2142-3339","contributorId":204594,"corporation":false,"usgs":true,"family":"Fritts","given":"Andrea","email":"","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":860345,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Duncker, James J. 0000-0001-5464-7991 jduncker@usgs.gov","orcid":"https://orcid.org/0000-0001-5464-7991","contributorId":4316,"corporation":false,"usgs":true,"family":"Duncker","given":"James","email":"jduncker@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860344,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jackson, P. Ryan 0000-0002-3154-6108 pjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-3154-6108","contributorId":194529,"corporation":false,"usgs":true,"family":"Jackson","given":"P.","email":"pjackson@usgs.gov","middleInitial":"Ryan","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860341,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70238323,"text":"70238323 - 2022 - Occurrence of a reproducing wild population of Channa aurolineata (Pisces: Channidae) in the Manatee River drainage, Florida","interactions":[],"lastModifiedDate":"2023-03-28T15:31:28.449045","indexId":"70238323","displayToPublicDate":"2022-11-01T06:56:38","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":868,"text":"Aquatic Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Occurrence of a reproducing wild population of Channa aurolineata (Pisces: Channidae) in the Manatee River drainage, Florida","docAbstract":"We report on the discovery of a wild, reproducing population of Channa aurolineata (Pisces: Channidae) in west-central Florida (USA), and first documented occurrence of snakeheads in the Gulf Coast region. Channa aurolineata is a large, predatory fish of the bullseye snakehead “Marulius group” species complex from Asia. Adult and juvenile specimens were captured in June 2020 in a 1.8-hectare pond that connects during high water to a small stream within the Manatee River-Tampa Bay Basin. The pond site is 250-km from the only other wild C. aurolineata population in the USA (present in southeast Florida since ca. 2000) and is considered a separate introduction and not the result of natural dispersal. Morphological and molecular comparisons revealed high overlap between the two Florida populations, evidence humans may have transported fish between sites. To verify identification, we compared Florida samples to C. aurolineata from Thailand and found mtDNA-COI barcode sequences to be identical or to differ by only a single base pair. Life body coloration of Florida samples matched their Asian counterparts, but Florida specimens averaged fewer dorsal fin rays (53.6 vs. 56.0), anal fin rays (34.2 vs 36.1), lateral line scales (65.3 vs. 67.4), and vertebrae (62.1 vs. 64.3), differences implying possible founder effect or sampling bias. Existence of this invasive predator is a concern because of the risk of spread and negative ecological effects, including an observation of terrestrial hunting behavior. In 2020–2021, several hundred C. aurolineata were removed from the pond by nets and electrofishing, and surveys suggested the population had not spread to nearby waters. In May 2021 the pond was treated with rotenone and 48 more specimens were recovered. No additional snakeheads have been sighted since the piscicide operation, although verification of eradication will require monitoring of the watershed.
","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre (REABIC)","doi":"10.3391/ai.2022.17.4.07","usgsCitation":"Nico, L., Neilson, M., Robins, R.H., Pfeiffer, J., Kail, M., Randall, Z.S., and Johnson, E.A., 2022, Occurrence of a reproducing wild population of Channa aurolineata (Pisces: Channidae) in the Manatee River drainage, Florida: Aquatic Invasions, v. 17, no. 4, p. 577-601, https://doi.org/10.3391/ai.2022.17.4.07.","productDescription":"25 p.; Data Release","startPage":"577","endPage":"601","ipdsId":"IP-135993","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":445971,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/ai.2022.17.4.07","text":"Publisher Index Page"},{"id":414829,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J71VWW","linkFileType":{"id":5,"text":"html"}},{"id":409382,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Manatee River drainage","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.69123997431116,\n 27.59323900275288\n ],\n [\n -82.69123997431116,\n 27.368302299325308\n ],\n [\n -82.27542527747138,\n 27.368302299325308\n ],\n [\n -82.27542527747138,\n 27.59323900275288\n ],\n [\n -82.69123997431116,\n 27.59323900275288\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nico, Leo 0000-0002-4488-7737","orcid":"https://orcid.org/0000-0002-4488-7737","contributorId":219308,"corporation":false,"usgs":true,"family":"Nico","given":"Leo","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":857095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neilson, Matthew 0000-0002-5139-5677","orcid":"https://orcid.org/0000-0002-5139-5677","contributorId":213998,"corporation":false,"usgs":true,"family":"Neilson","given":"Matthew","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":857096,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robins, Robert H.","contributorId":292263,"corporation":false,"usgs":false,"family":"Robins","given":"Robert","email":"","middleInitial":"H.","affiliations":[{"id":40459,"text":"Florida Museum, University of Florida","active":true,"usgs":false}],"preferred":false,"id":857097,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pfeiffer, John M.","contributorId":202521,"corporation":false,"usgs":false,"family":"Pfeiffer","given":"John M.","affiliations":[{"id":36469,"text":"Florida Museum of Natural History","active":true,"usgs":false}],"preferred":false,"id":857098,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kail, Matthew","contributorId":299079,"corporation":false,"usgs":false,"family":"Kail","given":"Matthew","affiliations":[],"preferred":false,"id":857099,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Randall, Zachary S. 0000-0001-8973-3304","orcid":"https://orcid.org/0000-0001-8973-3304","contributorId":299081,"corporation":false,"usgs":false,"family":"Randall","given":"Zachary","email":"","middleInitial":"S.","affiliations":[{"id":64761,"text":"Division of Ichthyology, Florida Museum, University of Florida","active":true,"usgs":false}],"preferred":false,"id":857100,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnson, Eric A.","contributorId":80158,"corporation":false,"usgs":false,"family":"Johnson","given":"Eric","email":"","middleInitial":"A.","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":857101,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70262352,"text":"70262352 - 2022 - Seasonal movements and spatial overlap of juvenile and adult lake sturgeon in Lake Champlain","interactions":[],"lastModifiedDate":"2025-01-17T15:36:08.047546","indexId":"70262352","displayToPublicDate":"2022-11-01T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13429,"text":"Transactions of American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal movements and spatial overlap of juvenile and adult lake sturgeon in Lake Champlain","docAbstract":"The lake sturgeon Acipenser fulvescens is a large, long-lived, potamodromous species that is widely distributed throughout freshwater systems in the central part of North America. In this study, we used acoustic telemetry to examine seasonal distribution and movement patterns of endangered Lake Sturgeon in Lake Champlain, Vermont. Acoustic tags were implanted in 29 juvenile Lake Sturgeon (453–874 mm TL) and 19 adults (1,215–1,615 mm TL) from the Winooski River and nearby areas of Lake Champlain between 2015 and 2019; tags were detected with 23 passive acoustic receivers deployed in the river and delta area and an additional 34 receivers deployed throughout Lake Champlain. Home range analysis using a lattice-based density estimator indicated that juvenile home range sizes were the same as adult home range sizes in spring and summer but were statistically larger than adult home ranges in winter. Cumulative home range analysis showed that juvenile and adult home ranges overlapped in shallow (<10-m) water in the summer and fall. In winter and spring, cumulative home ranges from juveniles included deepwater sites (>25 m), while adults remained in shallow water near the mouth of their spawning river. Seven juveniles made long-range movements (18–34 km) during the winter and spring months, and 13 juveniles moved back into the lower section of their natal river after overwintering in Lake Champlain. This study is the first to directly compare adult and juvenile Lake Sturgeon distribution, home range size, movements, and habitat use in a large lake system and provides a baseline for further research on the movement ecology of Lake Sturgeon in Lake Champlain.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10378","usgsCitation":"Izzo, L., Zydlewski, G., Marsden, J., and Parrish, D.L., 2022, Seasonal movements and spatial overlap of juvenile and adult lake sturgeon in Lake Champlain: Transactions of American Fisheries Society, v. 151, no. 6, p. 666-681, https://doi.org/10.1002/tafs.10378.","productDescription":"16 p.","startPage":"666","endPage":"681","ipdsId":"IP-140091","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481073,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10378","text":"Publisher Index Page"},{"id":480734,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","otherGeospatial":"Lake Champlain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.36468763012583,\n 44.65163325219339\n ],\n [\n -73.36468763012583,\n 44.396369652793226\n ],\n [\n -73.12430847320215,\n 44.396369652793226\n ],\n [\n -73.12430847320215,\n 44.65163325219339\n ],\n [\n -73.36468763012583,\n 44.65163325219339\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"151","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-09-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Izzo, Lisa K.","contributorId":348951,"corporation":false,"usgs":false,"family":"Izzo","given":"Lisa K.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":923896,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zydlewski, Gayle Barbin","contributorId":348952,"corporation":false,"usgs":false,"family":"Zydlewski","given":"Gayle Barbin","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":923897,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marsden, J. Ellen","contributorId":348955,"corporation":false,"usgs":false,"family":"Marsden","given":"J. Ellen","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":923898,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Parrish, Donna L. 0000-0001-9693-6329 dparrish@usgs.gov","orcid":"https://orcid.org/0000-0001-9693-6329","contributorId":138661,"corporation":false,"usgs":true,"family":"Parrish","given":"Donna","email":"dparrish@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923899,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237988,"text":"70237988 - 2022 - Observed and forecasted changes in land use by polar bears in the Beaufort and Chukchi Seas, 1985–2040","interactions":[],"lastModifiedDate":"2022-11-16T17:25:45.53204","indexId":"70237988","displayToPublicDate":"2022-10-31T06:52:33","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":"Observed and forecasted changes in land use by polar bears in the Beaufort and Chukchi Seas, 1985–2040","docAbstract":"Monitoring changes in the distribution of large carnivores is important for managing human safety and supporting conservation. Throughout much of their range, polar bears (Ursus maritimus) are increasingly using terrestrial habitats in response to Arctic sea ice decline. Their increased presence in coastal areas has implications for bear-human conflict, inter-species interactions, and polar bear health and survival. We examined observed trends in land use over three decades by polar bears in the southern Beaufort Sea (SB) and Chukchi Sea (CS) where bears have traditionally spent most of the year on the sea ice. Using data from 408 adult females fitted with satellite radio-collars, we examined trends in the annual proportion of bears coming onshore (hereafter referred to as “percent of bears”) during the summer for ≥21 days, arrival and departure dates, duration spent onshore and relationships with sea ice metrics. We then estimated future land use through 2040 by extrapolating trends and by combining observed relationships between land use and sea ice with projections of future sea ice from an ensemble of earth system models. The observed percent of bears summering onshore and their duration onshore was correlated with the percent of open water that occurred within their population’s range between July and October. As sea ice declined, the percent of bears summering onshore increased from ~5 to 30% in the SB and ~10 to 50% in the CS and duration onshore increased by >30 days to 60–70 days in both populations. Using a range of greenhouse gas emission scenarios and adjustments for faster than forecasted sea ice loss we estimated that 50-62% of SB and 79-88% of CS bears will spend 90–108 and 110–126 days onshore during summer in the SB and CS, respectively, by 2040. Sea ice projections varied little between greenhouse gas emission scenarios prior to 2040 but diverged thereafter. Observed and forecasted increases in polar bear land occupancy puts more bears in proximity to human activities and settlements for longer durations while extending the lack of access to their primary prey. Because human conflict is one of the primary factors affecting the conservation of large carnivores worldwide, mitigation of bear-human interactions on land will be an increasingly important component of polar bear conservation.
The bedrock geology of the 7.5-minute Crown Point quadrangle consists of deformed and metamorphosed Mesoproterozoic gneisses of the Adirondack Highlands unconformably overlain by weakly deformed lower Paleozoic sedimentary rocks of the Champlain Valley. The Mesoproterozoic rocks occur on the eastern edge of the Adirondack Highlands and represent an extension of the Grenville Province of Laurentia. Granulite facies Mesoproterozoic paragneiss, marble, and amphibolite hosted the emplacement of granitic orthogneiss at approximately 1.18–1.15 giga-annum (Ga, billion years before present). The earliest of four phases of deformation (D1) is characterized by gneissosity, rarely preserved F1 isoclinal folds, and migmatite in the host rocks. Subsequent D2 deformation produced a composite penetrative gneissosity, migmatite, and isoclinal F2 folds. Towards the end of D2, felsic magmatism (including the regionally extensive Lyon Mountain Granite Gneiss, abbreviated “LMG”) spread by penetrative migration as semiconcordant alkali feldspar granite sheets subparallel to S2 into previously deformed lithologies. The LMG crystallized at approximately 1.15 Ga and displays synkinematic F2 folds thus constraining the time of D2 deformation. Exhumation during D3 produced F3 folds exhibited in regional domes and basins, such as the Keeney Mountain synform, local reactivation of the S2 foliation, partial melting, metamorphism, metasomatism, iron ore remobilization, and intrusion of magnetite-bearing pegmatite both as layer-parallel sills and crosscutting dikes. D4 created NE- and NW-trending boudinage, local high-grade ductile shear zones, and crosscutting granitic pegmatite dikes. Kilometer (km)-scale lineaments readily observed in lidar data are Ediacaran mafic dikes and Phanerozoic brittle faults. The Paleozoic rocks are part of the Early Cambrian to Late Ordovician great American carbonate bank on the ancient margin of Laurentia. Cambrian-Ordovician stratigraphy records an approximately 1-km-thick section and a transition from synrift clastics to passive margin peritidal carbonate buildups to gradually deeper water subtidal to shelf carbonates during foreland basin development associated with the Taconic orogeny. The Paleozoic rocks are weakly folded and block faulted. Large areas of the Champlain Valley are covered by undifferentiated glacial deposits, some of which contain mapped landslides. The map also shows waste rock piles and tailings from historical mining operations and large areas of artificial fill.
This study was undertaken to improve our understanding of the bedrock geology in the Adirondack Highlands, establish a modern framework for 1:24,000-scale bedrock geologic mapping in the Adirondacks, provide a context for historical iron mines in the eastern Adirondacks, and update the stratigraphy of the Champlain Valley in New York and Vermont. This Scientific Investigations Map of the Crown Point 7.5-minute quadrangle consists of a map sheet, an explanatory pamphlet, and a geographic information system database that includes bedrock geologic units, faults, outcrops, and structural geologic information. The map sheet includes a bedrock geologic map, a correlation of map units, a description of map units, an explanation of map symbols, three cross sections, and a simplified surficial geologic map that includes lidar percent slope. The explanatory pamphlet includes a discussion of the geology.
The bedrock geologic map on the map sheet is multi-layered and has been designed to enable the user to turn off the surficial map layer to view the concealed bedrock map units.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3491","collaboration":"Prepared in cooperation with the State of Vermont, Vermont Agency of Natural Resources, Vermont Geological Survey, and the State of New York, Department of Education, New York Geological Survey","usgsCitation":"Walsh, G.J., Orndorff, R.C., and McAleer, R.J., 2022, Bedrock geologic map of the Crown Point quadrangle, Essex County, New York, and Addison County, Vermont: U.S. Geological Survey Scientific Investigations Map 3491, 1 sheet, scale 1:24,000, 44-p. pamphlet, https://doi.org/10.3133/sim3491.","productDescription":"Pamphlet: viii, 44 p.; Sheet: 62.00 x 41.00 inches; Base Map; Database; Metadata","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-117525","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":435638,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1FHRNVU","text":"USGS data release","linkHelpText":"Database for the bedrock geologic map of the Crown Point quadrangle, Essex County, New York, and Addison County, Vermont"},{"id":410043,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_sheet1.pdf","size":"178 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":408680,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_metadata.zip","size":"216 KB","linkFileType":{"id":6,"text":"zip"}},{"id":408682,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_basemap.zip","text":"Topographic Spatial Data","size":"119 MB","linkFileType":{"id":6,"text":"zip"}},{"id":408679,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_database.zip","size":"4.40 MB","linkFileType":{"id":6,"text":"zip"}},{"id":408674,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_pamphlet.pdf","text":"Pamphlet","size":"11.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3491"},{"id":408673,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3491/coverthb.jpg"},{"id":501933,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113783.htm","linkFileType":{"id":5,"text":"html"}},{"id":408681,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3491/sim3491_openaccess.zip","text":"Open Access","size":"6.29 MB","linkFileType":{"id":6,"text":"zip"}}],"country":"United States","state":"New York, Vermont","county":"Addison County, Essex County","otherGeospatial":"Crown Point quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.5,\n 44\n ],\n [\n -73.5,\n 43.875\n ],\n [\n -73.375,\n 43.875\n ],\n [\n -73.375,\n 44\n ],\n [\n -73.5,\n 44\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Florence Bascom Geoscience Center
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The Sevier/Toroweap Fault Zone is a major north-south-striking fault located in northern Arizona and southwestern Utah. In partnership with the National Park Service, the U.S. Geological Survey conducted two geophysical controlled-source audio-frequency magnetotelluric (CSAMT) surveys that transected the Sevier/Toroweap Fault Zone at Clay Flat, Utah, a potential pull-apart basin, west of a site of proposed groundwater pumping to evaluate the subsurface hydrogeology. The goal of the surveys was to enhance understanding of the interconnectedness of the Navajo aquifer, the region’s primary groundwater source, across two groundwater basins to the east and west of the fault zone, Water Rights Area (WRA) 81 and WRA 85.
In the Kane County, Utah, area, the Sevier/Toroweap Fault Zone consists of the Sevier section (to the north) and the northern Toroweap section (to the south). Two survey lines totaling 7 kilometers of CSAMT survey data were collected. The CSAMT survey line SV1 transected both the Sevier section and the northern Toroweap section of the fault zone; survey line SV2 transected only the Sevier section. Although offset of the Navajo Sandstone, the main component of the Navajo aquifer, by the Sevier/Toroweap Fault Zone is generally accepted as the geologic reason that the Navajo aquifer is disconnected in the study area, results of the CSAMT surveys suggest that vertical offset of the Navajo Sandstone of the Glen Canyon Group across the Sevier/Toroweap Fault Zone is insufficient to completely disconnect the aquifer in the study area. The effects of faulting on groundwater north and south of the study area, where offset of water-bearing layers may be greater, requires further study. A clearer understanding of groundwater movement across the Sevier /Toroweap Fault Zone will aid water-resource managers in making informed decisions concerning groundwater rights.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225071","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Jones, C.J.R., Robinson, M.J., and Macy, J.P., 2022, Characterization of the Sevier/Toroweap Fault Zone in Kane County, Utah, using controlled-source audio-frequency magnetotelluric (CSAMT) surveys: U.S. Geological Survey Scientific Investigations Report 2022–5071, 14 p., https://doi.org/10.3133/sir20225071.","productDescription":"Report: iv, 14 p.; Data Release","numberOfPages":"14","onlineOnly":"Y","ipdsId":"IP-133730","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":408827,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5071/covrthb.jpg"},{"id":408828,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5071/sir20225071.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":408830,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QF9PFR","text":"Controlled source audio-frequency magnetotellurics (CSAMT) data from the Sevier fault near Red Knoll, Kane County, Utah (ver. 2.0, July 2022)","description":"Robinson, M.J., and Macy, J.P., 2022, Controlled source audio-frequency magnetotellurics (CSAMT) data from the Sevier fault near Red Knoll, Kane County, Utah: U.S. Geological Survey data release, https://doi.org/10.5066/P9QF9PFR."}],"country":"United States","state":"Utah","county":"Kane County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.97309886757559,\n 37.55221820418316\n ],\n [\n -112.97309886757559,\n 37.082590637675466\n ],\n [\n -112.15461742226314,\n 37.082590637675466\n ],\n [\n -112.15461742226314,\n 37.55221820418316\n ],\n [\n -112.97309886757559,\n 37.55221820418316\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
Arizona Water Science Center
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“Blue carbon” wetland vegetation has a limited freshwater requirement. One type, mangroves, utilizes less freshwater during transpiration than adjacent terrestrial ecoregions, equating to only 43% (average) to 57% (potential) of evapotranspiration (
Many coastal ecosystems suffer from eutrophication, algal blooms, and dead zones due to excessive anthropogenic inputs of nitrogen (N) and phosphorus (P). This has led to regional restoration efforts that focus on managing watershed loads of N and P. In Chesapeake Bay, the largest estuary in the United States, dual nutrient reductions of N and P have been pursued since the 1980s. However, it remains unclear whether nutrient limitation – an indicator of restriction of algal growth by supplies of N and P – has changed in the tributaries of Chesapeake Bay following decades of reduction efforts. Toward that end, we analyzed historical data from nutrient-addition bioassay experiments and data from the Chesapeake Bay long-term water-quality monitoring program for six stations in three tidal tributaries (i.e., Patuxent, Potomac, and Choptank Rivers). Classification and regression tree (CART) models were developed using concurrent collections of water-quality parameters for each bioassay monitoring location during 1990-2003, which satisfactorily predicted the bioassay-based measures of nutrient limitation (classification accuracy = 96%). Predictions from the CART models using water-quality monitoring data showed enhanced nutrient limitation over the period of 1985-2020 at four of the six stations, including the downstream station in each of these three tributaries. These results indicate detectable, long-term water-quality improvements in the tidal tributaries. Overall, this research provides a new analytical tool for detecting signs of ecosystem recovery following nutrient reductions. More broadly, the approach can be adapted to other waterbodies with long-term bioassays and water-quality data sets to detect ecosystem recovery.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2022.119099","usgsCitation":"Zhang, Q., Fisher, T., Buchanan, C., Gustafson, A., Karrh, R., Murphy, R.R., Testa, J.M., Tian, R., and Tango, P.J., 2022, Nutrient limitation of phytoplankton in three tributaries of Chesapeake Bay: Detecting responses following nutrient reductions: Water Research, v. 226, 119099, 13 p., https://doi.org/10.1016/j.watres.2022.119099.","productDescription":"119099, 13 p.","ipdsId":"IP-141495","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":446002,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watres.2022.119099","text":"Publisher Index Page"},{"id":408854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, Pennsylvania, Virginia, West 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border wall construction and remediation","docAbstract":"The construction of a wall at the United States-Mexico border is known to impede and deter movement of terrestrial wildlife between the two countries. One such species is the jaguar, in its northernmost range in the borderlands of Arizona and Sonora. We developed an anisotropic cost distance model for jaguar in a binational crossing area of the Madrean Sky Islands at the United States-Mexico border in Southern Arizona as a case study by using previously collected GPS tracking data for jaguars, bioenergetic calculations for pumas, and a digital elevation model. This model describes projected energy expenditure for jaguar to reach key water sources north of the international border. These desert springs and the broader study region provide vital habitat for jaguar conservation and reintroduction efforts in the United States. An emerging impediment to jaguar conservation and reintroduction is border infrastructure including border wall. By comparing walled and un-walled border sections, and three remediation scenarios, we demonstrate that existing border infrastructure significantly increases energy expenditure by jaguars and that some partial remediation scenarios are more beneficial than others. Our results demonstrate opportunities for remediation. Improved understanding of how border infrastructure impacts physiological requirements and resulting impacts to jaguar and other terrestrial wildlife in the United States-Mexico borderlands may inform conservation management.
The U.S. Geological Survey has been working in collaboration with the Massachusetts Department of Environmental Protection on a project to collect water-quality data from the Merrimack River watershed since April 2020. Twelve locations in the Merrimack River watershed are being sampled for nutrients (such as nitrogen), metals (such as aluminum), Escherichia coli bacteria, and other measures.
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U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532