Sub-centennial oxygen (δ18O) isotopes of ostracod and authigenic calcite from Squanga Lake provides evidence of hydroclimatic extremes and a series of post-glacial climate system reorganizations for the interior region of northwest Canada. Authigenic calcite δ18O values range from −16‰ to −21‰ and are presently similar to modern lake water and annual precipitation values. Ostracod δ18O record near identical trends with calcite, offset by +1.7 ± 0.6‰. At 11 ka BP (kaBP = thousands of years before 1950), higher δ18O values reflect decreased precipitation−evaporation (P−E) balance from residual ice sheet influences on moisture availability. A trend to lower δ18O values until ∼8 ka BP reflects a shift to wetter conditions, and reorganization of atmospheric circulation. The last millennium and modern era are relatively dry, though not as dry as the early Holocene extreme. North Pacific climate dynamics remained an important driver of P−E balance in northwest Canada throughout the Holocene.
Life-history tradeoffs are common across taxa, but growth-survival tradeoffs—usually enhancing survival at a cost to growth—are less frequently investigated. Increased salinity (NaCl) is a prevalent anthropogenic disturbance that may cause a growth-survival tradeoff for larval amphibians. Although physiological mechanisms mediating tradeoffs are seldom investigated, hormones are prime candidates. Corticosterone (CORT) is a steroid hormone that independently influences survival and growth and may provide mechanistic insight into growth-survival tradeoffs. We conducted a 24-day experiment to test effects of salinity (<32–4000 mg/L) on growth, development, survival, CORT responses, and tradeoffs among traits of larval Northern Leopard Frogs (Rana pipiens). We also experimentally suppressed CORT signaling to determine whether CORT signaling mediates effects of salinity and a growth-survival tradeoff. Increased salinity reduced survival, growth, and development. Suppressing CORT signaling in conjunction with salinity reduced survival further but also attenuated the negative effects of salinity on growth, development, and water content. CORT of control larvae increased or was stable with growth and development but decreased with growth and development for those exposed to salinity. Therefore, salinity dysregulated CORT physiology. Across all treatments, larvae that survived had higher CORT than larvae that died. By manipulating CORT signaling, we provide strong evidence that CORT physiology mediates the outcome of a growth-survival tradeoff and enhances survival. To our knowledge, this is the first study to concomitantly measure tradeoffs between growth and survival and experimentally link these changes to CORT physiology. Identifying mechanistic links between stressors and fitness-related outcomes is critical to enhance our understanding of tradeoffs.
As the most remote archipelago in the world, the Hawaiian Islands are home to a highly endemic and disharmonic biota that has fascinated biologists for centuries. Forests are the dominant terrestrial biome in Hawai‘i, spanning complex, heterogeneous climates across substrates that vary tremendously in age, soil structure, and nutrient availability. Species richness is low in Hawaiian forests compared to other tropical forests, as a consequence of dispersal limitation from continents and adaptive radiations in only some lineages, and forests are dominated by the widespread Metrosideros species complex. Low species richness provides a relatively tractable model system for studies of community assembly, local adaptation, and species interactions. Moreover, Hawaiian forests provide insights into predicted patterns of evolution on islands, revealing that while some evidence supports “island syndromes,” there are exceptions to them all. For example, Hawaiian plants are not as a whole less defended against herbivores, less dispersible, more conservative in resource use, or more slow-growing than their continental relatives. Clearly, more work is needed to understand the drivers, sources, and constraints on phenotypic variation among Hawaiian species, including both widespread and rare species, and to understand the role of this variation for ecological and evolutionary processes, which will further contribute to conservation of this unique biota. Today, Hawaiian forests are among the most threatened globally. Resource management failures – the proliferation of non-native species in particular – have led to devastating declines in native taxa and resulted in dominance by novel species assemblages. Conservation and restoration of Hawaiian forests now rely on managing threats including climate change, ongoing species introductions, novel pathogens, lost mutualists, and altered ecosystem dynamics through the use of diverse tools and strategies grounded in basic ecological, evolutionary, and biocultural principles. The future of Hawaiian forests thus depends on the synthesis of ecological and evolutionary research, which will continue to inform future conservation and restoration practices.
Carnivore conservation and management are global research priorities focused on reversing population declines of imperiled species and identifying more effective and humane management of generalist carnivores with thriving populations. Nonlethal methods to mitigate conflict are increasingly used to advance conservation objectives; however, there is limited knowledge about the effectiveness of many nonlethal methods. We tested a nonlethal tool (fladry), that serves as a barrier to deter wolves Canis lupus and coyotes Canis latrans, for its efficacy at preventing coyotes from using prairie dog Cynomys ludovicianus colonies, the primary prey for critically endangered black-footed ferrets Mustela nigripes. We used camera trap data and an occupancy approach to evaluate the tool’s efficacy. We measured coyote response to fladry at both a coarse monthly scale (via use, attraction and avoidance probabilities) and a fine scale (via daily activity). Overall, use of areas inside exclosures declined by 60% after 60 days of fladry application and coyotes avoided some previously used areas both within and outside exclosures. Interestingly, coyotes were attracted to previously unused areas surrounding exclosures and increased activity around the periphery of fladry exclosures by 170% immediately after fladry installation, suggesting coyotes actively explored these areas and may have responded to fladry in a way that is counterintuitive to management expectations. Occupancy models provided more robust evaluation of fladry and revealed important behavioral responses relative to other common evaluation techniques (i.e. time until first detected crossing). Our results have implications for future development and evaluation of nonlethal tools for carnivore conservation and management globally.
","language":"English","publisher":"Zoological Society of London","doi":"10.1111/acv.12726","usgsCitation":"Windell, R., Bailey, L., Young, J.K., Livieri, T.M., Eads, D.A., and Breck, S., 2021, Improving evaluation of nonlethal tools for carnivore management and conservation: Evaluating fladry to protect an endangered species from a generalist mesocarnivore: Animal Conservation, v. 25, no. 1, p. 125-136, https://doi.org/10.1111/acv.12726.","productDescription":"12 p.","startPage":"125","endPage":"136","ipdsId":"IP-117480","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":396347,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","otherGeospatial":"Badlands National Park, Buffalo Gap National Grasslands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n 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]\n}","volume":"25","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-08-07","publicationStatus":"PW","contributors":{"editors":[{"text":"Penteriani, Vincenzo","contributorId":280007,"corporation":false,"usgs":false,"family":"Penteriani","given":"Vincenzo","email":"","affiliations":[],"preferred":false,"id":835841,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Ordiz, Andrés","contributorId":280008,"corporation":false,"usgs":false,"family":"Ordiz","given":"Andrés","affiliations":[],"preferred":false,"id":835842,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Windell, Rebecca","contributorId":279885,"corporation":false,"usgs":false,"family":"Windell","given":"Rebecca","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":835692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bailey, Larissa L.","contributorId":229353,"corporation":false,"usgs":false,"family":"Bailey","given":"Larissa L.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":835693,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Julie K.","contributorId":196299,"corporation":false,"usgs":false,"family":"Young","given":"Julie","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":835694,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Livieri, Travis M.","contributorId":198977,"corporation":false,"usgs":false,"family":"Livieri","given":"Travis","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":835695,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eads, David A. 0000-0002-4247-017X deads@usgs.gov","orcid":"https://orcid.org/0000-0002-4247-017X","contributorId":173639,"corporation":false,"usgs":true,"family":"Eads","given":"David","email":"deads@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":835696,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Breck, Stewart","contributorId":199403,"corporation":false,"usgs":false,"family":"Breck","given":"Stewart","affiliations":[],"preferred":false,"id":835697,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70223880,"text":"70223880 - 2021 - Evaluating the migration mortality hypothesis using monarch tagging data","interactions":[],"lastModifiedDate":"2021-09-14T11:35:01.272469","indexId":"70223880","displayToPublicDate":"2021-08-07T08:39:45","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the migration mortality hypothesis using monarch tagging data","docAbstract":"The decline in the eastern North American population of the monarch butterfly population since the late 1990s has been attributed to the loss of milkweed during the summer breeding season and the consequent reduction in the size of the summer population that migrates to central Mexico to overwinter (milkweed limitation hypothesis). However, in some studies the size of the summer population was not found to decline and was not correlated with the size of the overwintering population. The authors of these studies concluded that milkweed limitation could not explain the overwintering population decline. They hypothesized that increased mortality during fall migration was responsible (migration mortality hypothesis). We used data from the long-term monarch tagging program, managed by Monarch Watch, to examine three predictions of the migration mortality hypothesis: (1) that the summer population size is not correlated with the overwintering population size, (2) that migration success is the main determinant of overwintering population size, and (3) that migration success has declined over the last two decades. As an index of the summer population size, we used the number of wild-caught migrating individuals tagged in the U.S. Midwest from 1998 to 2015. As an index of migration success we used the recovery rate of Midwest tagged individuals in Mexico. With regard to the three predictions: (1) the number of tagged individuals in the Midwest, explained 74% of the variation in the size of the overwintering population. Other measures of summer population size were also correlated with overwintering population size. Thus, there is no disconnection between late summer and winter population sizes. (2) Migration success was not significantly correlated with overwintering population size, and (3) migration success did not decrease during this period. Migration success was correlated with the level of greenness of the area in the southern U.S. used for nectar by migrating butterflies. Thus, the main determinant of yearly variation in overwintering population size is summer population size with migration success being a minor determinant. Consequently, increasing milkweed habitat, which has the potential of increasing the summer monarch population, is the conservation measure that will have the greatest impact.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2020.00264","usgsCitation":"Taylor, O.R., Pleasants, J., Grundel, R., Pecoraro, S., Lovett, J.P., and Ryan, A., 2021, Evaluating the migration mortality hypothesis using monarch tagging data: Frontiers in Ecology and Evolution, v. 8, 264, 13 p., https://doi.org/10.3389/fevo.2020.00264.","productDescription":"264, 13 p.","ipdsId":"IP-106646","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":451254,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2020.00264","text":"Publisher Index Page"},{"id":389143,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.0,\n 40\n ],\n [\n -60.0,\n 40\n ],\n [\n -60.00,\n 50.0\n ],\n [\n -100.0,\n 50.0\n ],\n [\n -100.0,\n 40\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","noUsgsAuthors":false,"publicationDate":"2020-08-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Taylor, Orley R.","contributorId":168617,"corporation":false,"usgs":false,"family":"Taylor","given":"Orley","email":"","middleInitial":"R.","affiliations":[{"id":25342,"text":"Department of Ecology and Evolutionary Biology, University of Kansas","active":true,"usgs":false}],"preferred":false,"id":823073,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pleasants, John M.","contributorId":168616,"corporation":false,"usgs":false,"family":"Pleasants","given":"John M.","affiliations":[{"id":25341,"text":"Department of Ecology, Evolution, and Organismal Biology, Iowa State University","active":true,"usgs":false}],"preferred":false,"id":823074,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grundel, Ralph 0000-0002-2949-7087 rgrundel@usgs.gov","orcid":"https://orcid.org/0000-0002-2949-7087","contributorId":2444,"corporation":false,"usgs":true,"family":"Grundel","given":"Ralph","email":"rgrundel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":823075,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pecoraro, Samuel 0000-0002-3435-649X","orcid":"https://orcid.org/0000-0002-3435-649X","contributorId":221137,"corporation":false,"usgs":true,"family":"Pecoraro","given":"Samuel","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":823076,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lovett, James P.","contributorId":265598,"corporation":false,"usgs":false,"family":"Lovett","given":"James","email":"","middleInitial":"P.","affiliations":[{"id":6773,"text":"University of Kansas","active":true,"usgs":false}],"preferred":false,"id":823077,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ryan, Ann","contributorId":265599,"corporation":false,"usgs":false,"family":"Ryan","given":"Ann","email":"","affiliations":[{"id":6773,"text":"University of Kansas","active":true,"usgs":false}],"preferred":false,"id":823078,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70232203,"text":"70232203 - 2021 - Diet composition of Fishers (Pekania pennanti) reintroduced on the Olympic Peninsula, Washington","interactions":[],"lastModifiedDate":"2022-06-13T16:16:46.791335","indexId":"70232203","displayToPublicDate":"2021-08-06T11:05:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2901,"text":"Northwestern Naturalist","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Diet composition of Fishers (Pekania pennanti) reintroduced on the Olympic Peninsula, Washington","title":"Diet composition of Fishers (Pekania pennanti) reintroduced on the Olympic Peninsula, Washington","docAbstract":"Knowledge of diet composition can inform management strategies and efforts to recover endangered carnivore populations in vacant portions of their historic ranges. One such species, the Fisher (Pekania pennanti), was extirpated in Washington State prior to any formal documentation of its food habits in the coastal coniferous forests of western Washington. Fisher recovery efforts in Washington, based on translocating Fishers from extant populations, have been ongoing since 2008, beginning with the release of 90 Fishers on Washington's Olympic Peninsula from 2008 to 2010. We collected fecal samples or digestive tracts from 13 Fishers opportunistically on the Olympic Peninsula from 2009 through 2013. Subsequently, we identified the species composition of each sample's contents to determine the primary foods consumed by the reintroduced Fishers. Fisher diets were diverse and dominated by mammalian prey. Contents of feces and digestive tracts of Fishers were composed primarily of Snowshoe Hare (Lepus americanus) remains, followed by lesser proportions of Mountain Beavers (Aplodontia rufa), Northern Flying Squirrels (Glaucomys sabrinus), Douglas Squirrels (Tamiasciurus douglasii), Southern Red-backed Voles (Myodes gapperi), shrews (Sorex spp.), and unidentified ungulate species. The diet of Fishers comprised species that occur across a wide range of land uses and management prescriptions, including previously logged forests and mature forests that have been set aside for retention of old-growth forest characteristics. Additional study of prey abundance and Fisher foraging behaviors related to structural habitat characteristics across a gradient of land uses would provide useful insights for enhancing the effectiveness of conservation efforts to benefit Fishers in Pacific Northwest coastal forests.
","language":"English","publisher":"Society for Northwestern Vertebrate Biology","doi":"10.1898/NWN20-08","usgsCitation":"Happe, P.J., Pace, S.H., Prugh, L., Jenkins, K., Lewis, J.C., and Hagar, J., 2021, Diet composition of Fishers (Pekania pennanti) reintroduced on the Olympic Peninsula, Washington: Northwestern Naturalist, v. 102, no. 2, p. 97-108, https://doi.org/10.1898/NWN20-08.","productDescription":"12 p.","startPage":"97","endPage":"108","ipdsId":"IP-117708","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":402099,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Olympic Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.21142578125,\n 46.98774725646568\n ],\n [\n -124.21691894531249,\n 46.90899838277448\n ],\n [\n -123.8653564453125,\n 46.95776134668866\n ],\n [\n -122.947998046875,\n 47.040182144806664\n ],\n [\n -122.7117919921875,\n 47.11873795272715\n ],\n [\n -122.4755859375,\n 47.297859249409825\n ],\n [\n -122.34924316406251,\n 47.39834920035926\n ],\n [\n -122.4041748046875,\n 47.431803338643334\n ],\n [\n -122.44262695312501,\n 47.56170075451973\n ],\n [\n -122.4810791015625,\n 47.70976154266637\n ],\n [\n -122.44262695312501,\n 47.73932336136857\n ],\n [\n -122.4920654296875,\n 47.916342040161155\n ],\n [\n -122.59643554687499,\n 47.964180715412276\n ],\n [\n -122.65686035156249,\n 48.09275716032736\n ],\n [\n -122.7557373046875,\n 48.17707562779612\n ],\n [\n -122.90954589843749,\n 48.12943437745315\n ],\n [\n -123.01391601562499,\n 48.122101028190805\n ],\n [\n -123.12927246093751,\n 48.188063481211415\n ],\n [\n -123.32702636718749,\n 48.151428143221224\n ],\n [\n -123.662109375,\n 48.19538740833338\n ],\n [\n -124.0191650390625,\n 48.213692646648035\n ],\n [\n -124.57946777343751,\n 48.40732607972984\n ],\n [\n -124.7552490234375,\n 48.42920055556841\n ],\n [\n -124.76623535156251,\n 48.17707562779612\n ],\n [\n -124.67285156250001,\n 47.87214396888731\n ],\n [\n -124.46960449218751,\n 47.73562905149295\n ],\n [\n -124.354248046875,\n 47.33510005753559\n ],\n [\n -124.2279052734375,\n 47.19717795172789\n ],\n [\n -124.21142578125,\n 46.98774725646568\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"102","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Happe, Patricia J.","contributorId":50983,"corporation":false,"usgs":false,"family":"Happe","given":"Patricia","email":"","middleInitial":"J.","affiliations":[{"id":16133,"text":"National Park Service, Olympic National Park","active":true,"usgs":false}],"preferred":false,"id":844584,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pace, Shelby H.","contributorId":292446,"corporation":false,"usgs":false,"family":"Pace","given":"Shelby","email":"","middleInitial":"H.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":844599,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prugh, Laura R.","contributorId":257957,"corporation":false,"usgs":false,"family":"Prugh","given":"Laura R.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":844600,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jenkins, Kurt 0000-0003-1415-6607","orcid":"https://orcid.org/0000-0003-1415-6607","contributorId":221472,"corporation":false,"usgs":true,"family":"Jenkins","given":"Kurt","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":844585,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lewis, Jeffrey C.","contributorId":141090,"corporation":false,"usgs":false,"family":"Lewis","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[{"id":13674,"text":"WDFW","active":true,"usgs":false}],"preferred":false,"id":844601,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hagar, Joan 0000-0002-3044-6607 joan_hagar@usgs.gov","orcid":"https://orcid.org/0000-0002-3044-6607","contributorId":3369,"corporation":false,"usgs":true,"family":"Hagar","given":"Joan","email":"joan_hagar@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":844602,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70230796,"text":"70230796 - 2021 - Comparing geometric differences between Landsat Collection 1 to Collection 2 level-1 products","interactions":[],"lastModifiedDate":"2022-04-26T15:52:18.27322","indexId":"70230796","displayToPublicDate":"2021-08-06T10:47:56","publicationYear":"2021","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Comparing geometric differences between Landsat Collection 1 to Collection 2 level-1 products","docAbstract":"In late 2020 the U.S. Geological Survey (USGS) began the distribution of Landsat products associated with their collection 2 reprocessing of the archive. Several changes were implemented within the Landsat Product Generation System (LPGS) and the calibration parameters applied to the Landsat imagery for the collection 2 processing. When comparing between collection 1 and collection 2 products, radiometric and geometric differences will be present. One of the most substantial changes between the two collections was an adjustment to the ground control which made the control more accurate from an absolute and relative perspective. Some of the other changes associated with collection 2 processing were to the Digital Elevation Model (DEM) used in terrain correction, the Thermal Infrared Sensor (TIRS) relative gains, TIRS absolute calibration, Operational Land Imagery (OLI) absolute gain model, OLI relative gain, and OLI bias calculation to name a few. Although these changes also have an effect on the differences between the product associated with these two collections, the change in the ground control, although typically less than one 30-meter multispectral pixel in magnitude, will have the largest effect on the differences between the products. This change in ground control is also a spatially dynamic change that although is low in spatial frequency, is nonlinear and is not a change that can be modeled on a global or even on a local Worldwide Reference System-2 (WRS-2) path and row scale. The effects of these ground control changes will be discussed and demonstrated within this paper along with examples showing their effect on specific datasets. This paper demonstrates some of these geometric differences associated with the ground control through both the registration statistics created during product generation and through an example comparison of a set of collection 1 and collection 2 products.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings volume 11829, Earth Observing Systems XXVI","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SPIE Optical Engineering + Applications","conferenceDate":"Aug 1-5, 2021","conferenceLocation":"San Diego, CA","language":"English","doi":"10.1117/12.2596204","usgsCitation":"Choate, M.J., Rengarajan, R., Micijevic, E., and Lubke, M., 2021, Comparing geometric differences between Landsat Collection 1 to Collection 2 level-1 products, in Proceedings volume 11829, Earth Observing Systems XXVI, v. 11829, San Diego, CA, Aug 1-5, 2021, 118290H, 11 p., https://doi.org/10.1117/12.2596204.","productDescription":"118290H, 11 p.","ipdsId":"IP-131285","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":399676,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11829","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Choate, Michael J. 0000-0002-8101-4994","orcid":"https://orcid.org/0000-0002-8101-4994","contributorId":216866,"corporation":false,"usgs":true,"family":"Choate","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":841371,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rengarajan, Rajagopalan 0000-0003-1860-7110","orcid":"https://orcid.org/0000-0003-1860-7110","contributorId":242014,"corporation":false,"usgs":false,"family":"Rengarajan","given":"Rajagopalan","affiliations":[{"id":48475,"text":"KBR, Contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":841372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Micijevic, Esad 0000-0002-3828-9239","orcid":"https://orcid.org/0000-0002-3828-9239","contributorId":290334,"corporation":false,"usgs":false,"family":"Micijevic","given":"Esad","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":false,"id":841374,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lubke, Mark 0000-0002-7257-2337","orcid":"https://orcid.org/0000-0002-7257-2337","contributorId":261911,"corporation":false,"usgs":false,"family":"Lubke","given":"Mark","email":"","affiliations":[{"id":53079,"text":"KBR, contractor to U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":841373,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70222614,"text":"70222614 - 2021 - Preliminary assessment of the geometric improvements to the Landsat Collection-2 archive","interactions":[],"lastModifiedDate":"2021-08-10T11:33:12.694196","indexId":"70222614","displayToPublicDate":"2021-08-06T09:10:55","publicationYear":"2021","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Preliminary assessment of the geometric improvements to the Landsat Collection-2 archive","docAbstract":"The U.S. Geological Survey (USGS) has completed processing of the historical Landsat archive to Collection-2 as of December of 2020 and has released it to the public. As part of Collection-2, several geometric changes have been implemented, including changes to the ground control points (GCPs) and elevation datasets. These datasets are used as a geometric reference for all missions. In addition, mission specific improvements were included in Collection-2, such as improvements to the precision correction algorithms and updates of the calibration parameters. This paper discusses a preliminary analysis of a comparison between the Collection-1 and Collection-2 products of the entire Landsat archive. Compared to the Level 1 products in Collection-1, the number of Tier-1 precision- and terrain-corrected (L1TP) Level 1 products in Collection-2 increased by 6.26% across all sensors. Landsat 8 products showed an increase of Tier-1 L1TP products by 5.33%; Landsat 7 products showed an increase of Tier-1 products by 6.94%; and Landsat 5 and Landsat 4 Thematic Mapper (TM) products showed an increase of Tier-1 products by 9.35%. The geometric accuracy of the Tier-1 terrain corrected products also improved by 2 meters or more.
","largerWorkTitle":"SPIE proceedings volume 11829, earth observing systems XXVI","language":"English","publisher":"SPIE","doi":"10.1117/12.2596200","usgsCitation":"Lubke, M., Rengarajan, R., and Choate, M.J., 2021, Preliminary assessment of the geometric improvements to the Landsat Collection-2 archive, in SPIE proceedings volume 11829, earth observing systems XXVI, v. 11829, 1182901, 14 p., https://doi.org/10.1117/12.2596200.","productDescription":"1182901, 14 p.","ipdsId":"IP-131181","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":387782,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11829","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lubke, Mark 0000-0002-7257-2337","orcid":"https://orcid.org/0000-0002-7257-2337","contributorId":261911,"corporation":false,"usgs":false,"family":"Lubke","given":"Mark","email":"","affiliations":[{"id":53079,"text":"KBR, contractor to U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":820758,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rengarajan, Rajagopalan 0000-0003-1860-7110","orcid":"https://orcid.org/0000-0003-1860-7110","contributorId":242014,"corporation":false,"usgs":false,"family":"Rengarajan","given":"Rajagopalan","affiliations":[{"id":48475,"text":"KBR, Contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":820759,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Choate, Michael J. 0000-0002-8101-4994","orcid":"https://orcid.org/0000-0002-8101-4994","contributorId":216866,"corporation":false,"usgs":true,"family":"Choate","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":820760,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70225549,"text":"70225549 - 2021 - Climate change and other factors influencing the saguaro cactus","interactions":[],"lastModifiedDate":"2021-10-22T13:27:33.684305","indexId":"70225549","displayToPublicDate":"2021-08-06T08:27:08","publicationYear":"2021","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":9539,"text":"Intermountain Park Science","active":true,"publicationSubtype":{"id":30}},"title":"Climate change and other factors influencing the saguaro cactus","docAbstract":"The saguaro cacti (Carnegiea gigantea [Engelm.] Britton & Rose) is one of the world’s most iconic plants and a symbol of the desert Southwest. It is the namesake of Saguaro National Park, which was created (initially as a national monument) in 1933 to study, interpret, and protect the “giant cactus” and other unique Sonoran Desert species. Research on saguaros over the past century has revealed much about the plant’s growth, reproduction, population dynamics, and use by people and wildlife. Young saguaros grow very slowly, not reaching reproductive age until they are 35–65 years old. They produce white flowers that open at night during April through June, followed by large red fruits that are consumed by many desert animals. The saguaro fruit is also a traditional food source for the Tohono O’odham people, and the harvest of the saguaro fruit is a very important part of their culture (Bruhn 1971). Mature saguaros produce thousands of seeds each year, but establishment is episodic in that seedlings survive only during favorable periods with several consecutive years of cooler, wetter weather (Steenbergh and Lowe 1977).
","language":"English","publisher":"National Park Service","usgsCitation":"Swann, D., Winkler, D.E., Conver, J.L., and Foley, T., 2021, Climate change and other factors influencing the saguaro cactus: Intermountain Park Science, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-108877","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":390817,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":390801,"type":{"id":15,"text":"Index Page"},"url":"https://www.nps.gov/articles/000/climate-change-and-other-factors-influencing-the-saguaro-cactus.htm"}],"country":"United States","state":"Arizona","otherGeospatial":"Saguaro National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.25476837158203,\n 32.24416711645735\n ],\n [\n -111.06834411621094,\n 32.24416711645735\n ],\n [\n -111.06834411621094,\n 32.35821324969215\n ],\n [\n -111.25476837158203,\n 32.35821324969215\n ],\n [\n -111.25476837158203,\n 32.24416711645735\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Swann, Don E.","contributorId":267908,"corporation":false,"usgs":false,"family":"Swann","given":"Don E.","affiliations":[{"id":55529,"text":"Biologist, Saguaro National Park, 3693 South Old Spanish Trail, AZ (520) 360-7261 Don_Swann@nps.gov","active":true,"usgs":false}],"preferred":false,"id":825545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Winkler, Daniel E. 0000-0003-4825-9073","orcid":"https://orcid.org/0000-0003-4825-9073","contributorId":206786,"corporation":false,"usgs":true,"family":"Winkler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":825546,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conver, Joshua L.","contributorId":267924,"corporation":false,"usgs":false,"family":"Conver","given":"Joshua","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":825547,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Foley, Theresa","contributorId":267925,"corporation":false,"usgs":false,"family":"Foley","given":"Theresa","email":"","affiliations":[],"preferred":false,"id":825548,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70226639,"text":"70226639 - 2021 - Brown treesnake mortality after aerial application of toxic baits","interactions":[],"lastModifiedDate":"2021-12-01T13:31:25.091333","indexId":"70226639","displayToPublicDate":"2021-08-06T07:29:21","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Brown treesnake mortality after aerial application of toxic baits","docAbstract":"Quantitative evaluation of control tools for managing invasive species is necessary to assess overall effectiveness and individual variation in treatment susceptibility. Invasive brown treesnakes (Boiga irregularis) on Guam have caused severe ecological and economic effects, pose a risk of accidental introduction to other islands, and are the greatest impediment to the reestablishment of extirpated native fauna. An aerial delivery system for rodent-based toxic baits can reduce brown treesnake abundance and heterogeneity among individuals may influence bait attraction or toxicant susceptibility. Previous baiting trials have either been simulated aerial treatments or relied on slightly different bait capsule compositions and the results of aerial delivery of toxic baits under operational conditions may not be directly comparable. We monitored 30 radio-tagged adult snakes (990–1,265 mm snout-vent length) during an aerial baiting operation in a 55-ha area using transmitters equipped with accelerometers and receivers programed to display a status code indicating mortality if a snake failed to move for >24 hours. We used known-fate models to estimate mortality and evaluate a priori hypotheses explaining differences in mortality based on size, sex, and treatment effects. Eleven radio-tagged snakes died in the aerial baiting treatment period (0.37, 95% CI = 0.21–0.55) and no individuals (0.00, 95% CI = 0.00–0.04) died during the non-treatment period. Our data provide strong evidence for an additive size-based treatment effect on mortality, with smaller adults (0.59, 95% CI = 0.35–0.80) exhibiting higher mortality than larger snakes (0.14, 95% CI = 0.02–0.37) but did not support a sex effect on mortality. The high mortality of snakes during the treatment period indicates that aerial baiting can reduce brown treesnake abundance, but further refinement or use in combination with other removal tools may be necessary to overcome size-based differences in susceptibility and achieve eradication.
Stormwater discharges from municipalities are regulated by provisions in the Clean Water Act of 1972 to protect the Nation’s water resources from harmful pollutants. In 2014, the Kansas Department of Health and Environment issued new stormwater discharge permits for 17 municipalities in Johnson County, Kansas, in the northeastern part of the State. The county is largely suburban and has 20 municipalities within 22 watersheds. Municipalities in Johnson County are required to implement stormwater management programs that reduce discharges of pollutants, protect water quality, and satisfy applicable water-quality regulations.
In 2015, the U.S. Geological Survey, in cooperation with the Johnson County Stormwater Management Program, began a 4-year monitoring program designed to meet new stormwater monitoring requirements for some municipalities in Johnson County. Additional data were collected to evaluate the usefulness of continuous water-quality monitoring and different sampling methods in assessing changes in water quality. Twelve of the 22 watersheds in the county were within the sampling network for this project.
Discrete water-quality samples were collected at 25 stream sites and 2 lake sites using passive, grab, and equal-width increment sampling methods. Samples at all sites were analyzed for nutrients, Escherichia coli bacteria, total suspended solids, and suspended-sediment concentration. Ninety-nine percent of storm-event samples and 98 percent of low-flow samples were less than the Kansas Surface Water Quality Standard for nitrate plus nitrite. Eight percent of storm-event samples and 100 percent of low-flow samples were less than the total suspended solids screening value of 50 milligrams per liter. Passive samples generally had higher concentrations when compared to equal-width increment and grab samples, and grab samples and equal-width increment samples generally had similar concentrations.
Continuous water-quality data were collected at one site. Ordinary least squares regression analysis was used to relate continuous (15-minute) water-quality sensor measurements to discretely sampled constituent concentrations at one site.
Numerous factors affect water quality in urban runoff. Urban areas have many possible contaminant sources, including municipal and industrial wastewater discharges, stormwater runoff from impervious surfaces, and failing infrastructure. A better understanding of these factors can inform future monitoring efforts, leading to datasets that are representative of storm runoff and can be used to detect differences between sites and over time.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215041","collaboration":"Prepared in cooperation with the Johnson County Stormwater Management Program","usgsCitation":"Leiker, B.M., Rasmussen, T.J., Eslick-Huff, P.J., and Painter, C.C., 2021, Assessment of water-quality constituents monitored for total maximum daily loads in Johnson County, Kansas, January 2015 through December 2018: U.S. Geological Survey Scientific Investigations Report 2021–5041, 45 p., https://doi.org/10.3133/sir20215041.","productDescription":"Report: viii, 45 p.; Appendixes: 62 p.; Data Release","numberOfPages":"58","onlineOnly":"Y","ipdsId":"IP-119343","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":387659,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91397BC","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water-quality and preceding precipitation data for low-flow and storm-event samples collected in Johnson County, Kansas, from January 2015 through November 2018"},{"id":387657,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5041/sir20215041.pdf","text":"Report","size":"3.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5041"},{"id":387656,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5041/coverthb.jpg"},{"id":387658,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5041/sir20215041_appendixes_2to6.pdf","text":"Appendixes 2–6","size":"2.27 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5041 Appendixes"}],"country":"United States","state":"Kansas","county":"Johnson County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-94.6075,39.0437],[-94.6075,39.0399],[-94.6082,38.8463],[-94.6084,38.8341],[-94.6102,38.7376],[-95.0572,38.7395],[-95.0558,38.9816],[-95.0477,38.9778],[-95.0383,38.9771],[-95.0312,38.9773],[-95.0292,38.9813],[-95.0271,38.9881],[-95.0249,38.9962],[-95.0189,38.9987],[-95.0135,38.9991],[-95.0077,38.998],[-94.9946,38.9976],[-94.9899,38.997],[-94.9841,38.995],[-94.9789,38.9926],[-94.9755,38.9885],[-94.9704,38.9851],[-94.9645,38.9832],[-94.9575,38.982],[-94.9527,38.9828],[-94.9479,38.9845],[-94.9448,38.9871],[-94.9423,38.9898],[-94.9386,38.9933],[-94.9367,38.9964],[-94.9335,38.9995],[-94.9264,38.9998],[-94.9217,38.9996],[-94.9176,38.9977],[-94.9209,38.9919],[-94.923,38.9856],[-94.9207,38.9837],[-94.9164,38.9859],[-94.9115,38.9889],[-94.9078,38.9924],[-94.9014,39.0022],[-94.8989,39.0053],[-94.8945,39.0102],[-94.8919,39.0155],[-94.891,39.021],[-94.8875,39.0313],[-94.8824,39.0379],[-94.8768,39.0441],[-94.8681,39.052],[-94.8631,39.0564],[-94.8488,39.0578],[-94.8318,39.0546],[-94.8131,39.0486],[-94.8038,39.0456],[-94.7197,39.0435],[-94.6693,39.0433],[-94.6075,39.0437]]]},\"properties\":{\"name\":\"Johnson\",\"state\":\"KS\"}}]}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049
Blind reverse faults are challenging to detect, and earthquake records can be elusive because deep fault slip does not break the surface along readily recognized scarps. The blind Reelfoot fault in the New Madrid seismic zone in the central United States has been the subject of extensive prior investigation; however, the extent of slip at the southern portion of the fault remains unconstrained. In this study, we use lidar to map terraces and lacustrine landforms in the Obion River valley and investigate apparent broad folding resulting from slip on the buried Reelfoot fault. We compare remote surface mapping results with three auger boreholes in the ∼24 ka Finley terrace and interpret apparent warping as due to tectonic folding and not stratigraphic thickening. We combine our results with historical records of coseismic lake formation that indicate surface deformation dammed the Obion River in the 1812 CE earthquake. Older terraces (deposited at least 35–55 ka) record progressive fold scarps ≥1, ≥2, and ≥8 m high indicating a long record of earthquakes predating the existing paleoseismic record. Broad, distributed folding above the Reelfoot fault into the Obion River valley is consistent with a deep active fault tip along the southern reaches of the fault. Our analyses indicate the entire length of the fault (≥70 km) is capable of rupture and is more consistent with longer rupture scenarios.
Private lands provide key habitat for imperiled species and are core components of function protected area networks; yet, their incorporation into national and regional conservation planning has been challenging. Identifying locations where private landowners are likely to participate in conservation initiatives can help avoid conflict and clarify trade-offs between ecological benefits and sociopolitical costs. Empirical, spatially explicit assessment of the factors associated with conservation on private land is an emerging tool for identifying future conservation opportunities. However, most data on private land conservation are voluntarily reported and incomplete, which complicates these assessments. We used a novel application of occupancy models to analyze the occurrence of conservation easements on private land. We compared multiple formulations of occupancy models with a logistic regression model to predict the locations of conservation easements based on a spatially explicit social-ecological systems framework. We combined a simulation experiment with a case study of easement data in Idaho and Montana (United States) to illustrate the utility of the occupancy framework for modeling conservation on private land. Occupancy models that explicitly accounted for variation in reporting produced estimates of predictors that were substantially less biased than estimates produced by logistic regression under all simulated conditions. Occupancy models produced estimates for the 6 predictors we evaluated in our case study that were larger in magnitude, but less certain than those produced by logistic regression. These results suggest that occupancy models result in qualitatively different inferences regarding the effects of predictors on conservation easement occurrence than logistic regression and highlight the importance of integrating variable and incomplete reporting of participation in empirical analysis of conservation initiatives. Failure to do so can lead to emphasizing the wrong social, institutional, and environmental factors that enable conservation and underestimating conservation opportunities in landscapes where social norms or institutional constraints inhibit reporting.
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/cobi.13673","usgsCitation":"Williamson, M., Dickson, B., Hooten, M., Graves, R., Lubell, M., and Schwartz, M., 2021, Improving inferences about private land conservation by accounting for incomplete reporting: Conservation Biology, v. 35, no. 4, p. 1174-1185, https://doi.org/10.1111/cobi.13673.","productDescription":"12 p.","startPage":"1174","endPage":"1185","ipdsId":"IP-113790","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":482903,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, 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\"}}]}","volume":"35","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-03-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Williamson, Matthew A.","contributorId":351796,"corporation":false,"usgs":false,"family":"Williamson","given":"Matthew A.","affiliations":[{"id":84047,"text":"bsu","active":true,"usgs":false}],"preferred":false,"id":929510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dickson, Brett G.","contributorId":351797,"corporation":false,"usgs":false,"family":"Dickson","given":"Brett G.","affiliations":[{"id":62994,"text":"CSP","active":true,"usgs":false}],"preferred":false,"id":929511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hooten, Mevin","contributorId":18254,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","affiliations":[],"preferred":false,"id":929695,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graves, Rose A.","contributorId":351798,"corporation":false,"usgs":false,"family":"Graves","given":"Rose A.","affiliations":[{"id":33811,"text":"TNC","active":true,"usgs":false}],"preferred":false,"id":929512,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lubell, Mark N.","contributorId":351799,"corporation":false,"usgs":false,"family":"Lubell","given":"Mark N.","affiliations":[{"id":54468,"text":"uc","active":true,"usgs":false}],"preferred":false,"id":929513,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schwartz, Mark W.","contributorId":351800,"corporation":false,"usgs":false,"family":"Schwartz","given":"Mark W.","affiliations":[{"id":54468,"text":"uc","active":true,"usgs":false}],"preferred":false,"id":929514,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70222458,"text":"ofr20211073 - 2021 - Reconnaissance study of the major and trace element content of bauxite deposits in the Arkansas bauxite region, Saline and Pulaski Counties, central Arkansas","interactions":[],"lastModifiedDate":"2021-08-06T21:38:29.620031","indexId":"ofr20211073","displayToPublicDate":"2021-08-05T15:00:00","publicationYear":"2021","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":"2021-1073","displayTitle":"Reconnaissance Study of the Major and Trace Element Content of Bauxite Deposits in the Arkansas Bauxite Region, Saline and Pulaski Counties, Central Arkansas","title":"Reconnaissance study of the major and trace element content of bauxite deposits in the Arkansas bauxite region, Saline and Pulaski Counties, central Arkansas","docAbstract":"The Arkansas bauxite district, which comprises about 275 square miles (710 square kilometers) of central Arkansas, produced an order of magnitude more bauxite and alumina than the other bauxite districts in the United States combined. Bauxite was mined in the region continuously from 1898 to 1982. These bauxites are laterite deposits, formed from intensive in-place weathering of the exposed surface of the Granite Mountain pluton, a Late Cretaceous batholith composed mainly of nepheline syenite and lesser amounts of syenite. Nepheline syenite was the aluminum source for the bauxite and clay deposits that blanket the pluton. The early Eocene continental sedimentary rocks that contain and overlie the bauxite deposits indicate that central Arkansas had a warm tropical environment during bauxite formation.
Bauxite ores are the principal sources of aluminum. Some of the global bauxite deposits have been found to contain co-occurring metals that have essential applications in modern technologies. For example, bauxite is the largest global source of gallium (Ga), used in semiconductors, which is recovered as a byproduct of processing bauxite to recover alumina. Other critical metal commodities within some bauxites that reportedly have potential for byproduct recovery include niobium (Nb), scandium (Sc), and rare earth elements (REEs). Currently (2021), the United States is wholly dependent on imports for its supplies of bauxite for processing to produce alumina. The United States is also dependent on foreign sources of gallium, niobium, and scandium, as well for most of its domestic requirements of REEs.
For these reasons, samples were collected from Arkansas bauxite deposits, associated clays, mill residue wastes (respectively referred to as red muds and black sands), and the parent nepheline syenite to determine their elemental content, with a particular focus on gallium, niobium, scandium, and REEs. Each sample was analyzed for 60 elements; these data and the methods used are published as a U.S. Geological Survey data release.
The results indicate that, of the critical metals in bauxites, gallium is a potential byproduct from the central Arkansas bauxite deposits. The highest gallium concentrations occur in the raw bauxite ore, with an average concentration of 76 parts per million (ppm). Gallium partitions with alumina (the product) rather than into mine waste residues. Results indicate an average niobium content of 662 ppm in the Arkansas bauxite ores. Niobium progressively increases in concentration from parent syenite (247 ppm) to clays (315 ppm) and further from bauxite (662 ppm) to processed residues (1,075 ppm). Low concentrations of scandium were found in all samples, averaging 10 ppm or less in the parent rock (syenite), bauxite, clays, and processing residues. Modest concentrations of the light and heavy REEs were found in samples of bauxite ores, bauxitic clays and interbedded clays, syenite, and the residues of ore. The highest REE values were found in processed residues, with average concentrations of 613 ppm total light REEs and 130 ppm total heavy REEs. These concentrations suggest that additional processing to recover REEs is unlikely to be economic in the foreseeable future.
Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS 973
Denver, CO 80225
Animal movement is a complex phenomenon where individual movement patterns can be influenced by a variety of factors including the animal’s current activity, available terrain and habitat, and locations of other animals. Motivated by modeling grizzly bear movement in the Greater Yellowstone Ecosystem, this article presents an agent-based model represented in a state-space framework for collective animal movement. The novel contribution of this work is a collective animal movement model that captures interactions between animals that can trigger changes in movement patterns, such as when a dominant grizzly bear may cause another subordinate bear to temporarily leave an area. The modeling framework enables learning different movement patterns through a state-space representation with particle-MCMC methods for fully Bayesian model fitting and the prediction of future animal movement behaviors.
Researchers most often focus on individual toxicants when identifying effective chemical control agents for aquatic invasive species; however, toxicant mixtures may elicit synergistic effects. Synergistic effects may decrease required concentrations and shorten exposure durations for treatments. We investigated four toxicants (EarthTec QZ, Clam-Trol CT-2, niclosamide, and potassium chloride) that have been considered to control invasive zebra mussels (Dreissena polymorpha Pallas, 1771). We determined the toxicity of binary mixtures for five different mixture ratios to adult mussels. We compared our observations to predictions made with concentration addition and independent action paradigms, as based on the dose-response relationships of each individual toxicant. We calculated the model deviation ratio for each combination at the LC50 and LC90 and identified three possible interactions: synergy, antagonism, and additivity. We found that mixtures of niclosamide and Clam-Trol CT-2 were the most synergistic while mixtures that included potassium chloride were largely additive to antagonistic. The use of synergistic combinations has potential to decrease the overall volume and concentration of individual toxicants required for dreissenid mussel treatments, thereby decreasing cost.
The Gulf of Maine has recently experienced its warmest 5-year period (2015–2020) in the instrumental record. This warming was associated with a decline in the signature subarctic zooplankton species, Calanus finmarchicus. The temperature changes have also led to impacts on commercial species such as Atlantic cod (Gadus morhua) and American lobster (Homarus americanus) and protected species including Atlantic puffins (Fratercula arctica) and northern right whales (Eubalaena glacialis). The recent period also saw a decline in Atlantic herring (Clupea harengus) recruitment and an increase in novel harmful algal species, although these have not been attributed to the recent warming. Here, we use an ensemble of numerical ocean models to characterize expected ocean conditions in the middle of this century. Under the high CO2 emissions scenario (RCP8.5), the average temperature in the Gulf of Maine is expected to increase 1.1°C to 2.4°C relative to the 1976–2005 average. Surface salinity is expected to decrease, leading to enhanced water column stratification. These physical changes are likely to lead to additional declines in subarctic species including C. finmarchicus, American lobster, and Atlantic cod and an increase in temperate species. The ecosystem changes have already impacted human communities through altered delivery of ecosystem services derived from the marine environment. Continued warming is expected to lead to a loss of heritage, changes in culture, and the necessity for adaptation.
","language":"English","publisher":"University of California Press","doi":"10.1525/elementa.2020.00076","usgsCitation":"Pershing, A., Alexander, M.A., Brady, D., Brickman, D., Curchitser, E.N., Diamond, A.W., McClenachan, L., Mills, K., Nichols, O., Pendleton, D., Record, N., Scott, J., Staudinger, M., and Wang, Y., 2021, Climate impacts on the Gulf of Maine ecosystem: A review of observed and expected changes in 2050 from rising temperatures: Elementa: Science of the Anthropocene, v. 9, no. 1, 00076, 18 p., https://doi.org/10.1525/elementa.2020.00076.","productDescription":"00076, 18 p.","ipdsId":"IP-120338","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":451274,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1525/elementa.2020.00076","text":"Publisher Index Page"},{"id":389262,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Maine, Massachusetts, New Brunswick, New Hampshire, Nova Scotia","otherGeospatial":"Gulf of Maine","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -69.67529296875,\n 41.672911819602085\n ],\n [\n -65.72021484375,\n 43.43696596521823\n ],\n [\n -66.09375,\n 44.22945656830167\n ],\n [\n -65.63232421875,\n 44.824708282300236\n ],\n [\n -64.599609375,\n 45.182036837015886\n ],\n [\n -64.775390625,\n 45.5679096098613\n ],\n [\n -66.8408203125,\n 45.07352060670971\n ],\n [\n -66.97265625,\n 44.653024159812\n ],\n [\n -70.3564453125,\n 43.77109381775651\n ],\n [\n -70.77392578125,\n 42.779275360241904\n ],\n [\n -71.21337890625,\n 42.309815415686664\n ],\n [\n -70.51025390625,\n 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C.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":818161,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brickman, David","contributorId":260603,"corporation":false,"usgs":false,"family":"Brickman","given":"David","email":"","affiliations":[{"id":52613,"text":"DFO","active":true,"usgs":false}],"preferred":false,"id":818162,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Curchitser, Enrique N.","contributorId":260604,"corporation":false,"usgs":false,"family":"Curchitser","given":"Enrique","email":"","middleInitial":"N.","affiliations":[{"id":52614,"text":"Rutgers Unv.","active":true,"usgs":false}],"preferred":false,"id":818163,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Diamond, Anthony W.","contributorId":260605,"corporation":false,"usgs":false,"family":"Diamond","given":"Anthony","email":"","middleInitial":"W.","affiliations":[{"id":18889,"text":"University of New 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Daniel","contributorId":260609,"corporation":false,"usgs":false,"family":"Pendleton","given":"Daniel","affiliations":[{"id":48127,"text":"Anderson Cabot Center for Marine Life","active":true,"usgs":false}],"preferred":false,"id":818168,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Record, Nicholas","contributorId":260610,"corporation":false,"usgs":false,"family":"Record","given":"Nicholas","affiliations":[{"id":52615,"text":"Bigelow Lab","active":true,"usgs":false}],"preferred":false,"id":818169,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Scott, James","contributorId":260611,"corporation":false,"usgs":false,"family":"Scott","given":"James","affiliations":[{"id":52616,"text":"CIRES","active":true,"usgs":false}],"preferred":false,"id":818170,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Staudinger, Michelle 0000-0002-4535-2005","orcid":"https://orcid.org/0000-0002-4535-2005","contributorId":206655,"corporation":false,"usgs":true,"family":"Staudinger","given":"Michelle","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":818171,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Wang, Yanjun","contributorId":260612,"corporation":false,"usgs":false,"family":"Wang","given":"Yanjun","email":"","affiliations":[{"id":52613,"text":"DFO","active":true,"usgs":false}],"preferred":false,"id":818172,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70222522,"text":"sir20215055 - 2021 - Groundwater quality and age of secondary bedrock aquifers in the glaciated portion of eastern Nebraska, 2016–18","interactions":[],"lastModifiedDate":"2021-08-05T09:52:41.030548","indexId":"sir20215055","displayToPublicDate":"2021-08-04T08:23:21","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5055","displayTitle":"Groundwater Quality and Age of Secondary Bedrock Aquifers in the Glaciated Portion of Eastern Nebraska, 2016–18","title":"Groundwater quality and age of secondary bedrock aquifers in the glaciated portion of eastern Nebraska, 2016–18","docAbstract":"The Eastern Nebraska Water Resources Assessment (ENWRA) project was initiated in 2006 to assist water managers by developing a hydrogeologic framework and water budget for the glaciated portion of eastern Nebraska. Within the ENWRA area, the primary groundwater sources for municipal, domestic, and irrigation water needs are provided by withdrawals from alluvial, buried paleovalley, and the High Plains aquifer (where present). Generally, other bedrock aquifers are considered a secondary water source. However, in some areas, such as parts of Sarpy and Nemaha Counties, these secondary bedrock aquifers are the only source of water within glaciated upland areas. To improve the understanding of the quality, geochemistry, and age of groundwater from bedrock aquifers, the U.S. Geological Survey (USGS), in cooperation with the ENWRA group, which includes the Lewis and Clark, Lower Elkhorn, Lower Platte North, Lower Platte South, Nemaha, and Papio-Missouri River Natural Resources Districts, designed a study to sample 31 wells completed in the secondary bedrock aquifers and analyze samples for major ions, physical properties, nutrients, stable isotopes, and selected age tracers. Of the 31 samples collected for this report, 22 samples were collected from the Dakota aquifer contained in the Dakota Sandstone, 3 from the Niobrara aquifer contained in the Niobrara Formation of Colorado Group, and 6 from Paleozoic aquifers contained in undifferentiated Paleozoic-age units.
The results of this study indicate that major ion data collected from the Dakota aquifer can be used for assessing the quality, recharge source, and age of groundwater. Calcium bicarbonate dominant samples were characterized as modern or mixed, indicating that, in these areas, groundwater is unconfined and is recharged by precipitation and (or) surface water. If groundwater extraction rates exceed recharge rates, total dissolved solid concentrations may increase as a result of upwelling of groundwater from deeper units or formations, which can adversely affect groundwater quality. Sampling results presented in this report indicate water quality is good, but that groundwater in the Dakota aquifer with calcium bicarbonate water type may be vulnerable to surface contamination. In contrast, groundwater sampled from the Dakota aquifer, having a dominant water type other than calcium bicarbonate, generally has low dissolved oxygen and nitrate concentrations, and higher concentrations of total dissolved solids and trace elements, including iron and strontium. The geochemical characteristics of noncalcium bicarbonate samples from the Dakota aquifer indicated confining conditions and limited groundwater recharge from local precipitation. Apparent groundwater ages estimated from radiocarbon (carbon-14) sampling of noncalcium bicarbonate samples from the Dakota aquifer indicated that the time of groundwater recharge to the Dakota aquifer occurred during Pleistocene time. Depleted stable isotopes results indicate recharge during a colder climate. Groundwater under confined conditions is not easily recharged from precipitation or surface water. Future groundwater-level monitoring in locations where the Dakota aquifer appears to be confined could provide information to evaluate whether groundwater supplies remain sufficient to meet future municipal, domestic, and irrigation needs.
For the Niobrara aquifer and Paleozoic aquifers, the dominant water type was not a diagnostic indicator of recharge source, age, and groundwater quality as with the Dakota aquifer. Most likely this is because the host formation was dominated by calcium-carbonate-rich rocks; however, few samples were collected from these aquifers to be able to confirm this interpretation. Samples collected from wells completed in the Niobrara aquifer and Paleozoic aquifers and characterized as calcium sulfate water type have statistically significantly higher concentrations of total dissolved solids compared to other samples from the Niobrara aquifer and Paleozoic aquifers characterized as calcium bicarbonate. Given that six of the nine of samples collected from the Niobrara and Paleozoic aquifers indicated modern recharge, these secondary bedrock aquifers are reliant on precipitation to sustain groundwater levels and may be vulnerable to a multiyear drought. Well yields of the Niobrara and Paleozoic aquifers are dependent on the presence of secondary porosity and these units offer little storage. Samples collected from wells completed in Paleozoic aquifers were the most isotopically enriched and similar to modern precipitation and had the highest concentrations of nitrate, indicating that groundwater is affected by agricultural activities. Future groundwater sampling would be beneficial to characterize groundwater-quality changes within the Niobrara and Paleozoic aquifers over time.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215055","collaboration":"Prepared in cooperation with the Eastern Nebraska Water Resources Assessment","usgsCitation":"Hobza, C.M., and Flynn, A.T., 2021, Groundwater quality and age of secondary bedrock aquifers in the glaciated portion of eastern Nebraska, 2016–18: U.S. Geological Survey Scientific Investigations Report 2021–5055, 42 p., https://doi.org/10.3133/sir20215055.","productDescription":"Report: viii, 42 p.; Dataset","numberOfPages":"54","onlineOnly":"Y","ipdsId":"IP-122775","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":387641,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":387643,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5055/sir20215055.XML","linkFileType":{"id":8,"text":"xml"}},{"id":387642,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5055/images"},{"id":387640,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5055/sir20215055.pdf","text":"Report","size":"2.78 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5055"},{"id":387639,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5055/coverthb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.9541015625,\n 42.779275360241904\n ],\n [\n -97.7783203125,\n 42.261049162113856\n ],\n [\n -97.58056640625,\n 41.52502957323801\n ],\n [\n -97.05322265625,\n 41.07935114946899\n ],\n [\n -96.87744140625,\n 40.64730356252251\n ],\n [\n -96.591796875,\n 39.99395569397331\n ],\n [\n -95.2734375,\n 39.977120098439634\n ],\n [\n -95.49316406249999,\n 40.3130432088809\n ],\n [\n -95.80078125,\n 40.713955826286046\n ],\n [\n -95.91064453125,\n 41.31082388091818\n ],\n [\n -96.13037109375,\n 42.00032514831621\n ],\n [\n -96.5478515625,\n 42.65012181368022\n ],\n [\n -97.0751953125,\n 42.87596410238256\n ],\n [\n -97.822265625,\n 42.89206418807337\n ],\n [\n -97.9541015625,\n 42.779275360241904\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
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Spatiotemporal variation in forage is a primary driver of ungulate behavior, yet little is known about the nutritional components they select, and how selection varies across the growing season with changes in forage quality and quantity. We addressed these uncertainties in barren-ground caribou (Rangifer tarandus), which experience their most important foraging opportunities during the short Arctic summer. Recent declines in Arctic caribou populations have raised concerns about the influence of climate change on summer foraging opportunities, given shifting vegetation conditions and insect harassment, and their potential effects on caribou body condition and demography. We examined Arctic caribou selection of summer forage by pairing locations from females in the Central Arctic Herd of Alaska with spatiotemporal predictions of biomass, digestible nitrogen (DN), and digestible energy (DE). We then assessed selection for these nutritional components across the growing season at landscape and patch scales, and determined whether foraging opportunities were constrained by insect harassment. During early summer, at the landscape scale, caribou selected for intermediate biomass and high DN and DE, following expectations of the forage maturation hypothesis. At the patch scale, however, caribou selected for high values of all forage components, particularly DN, suggesting that protein may be limiting. During late summer, after DN declined below the threshold for protein gain, caribou exhibited a switch at both spatial scales, selecting for higher biomass, likely enabling mass and fat deposition. Mosquito activity strongly altered caribou selection of forage and increased their movement rates, while oestrid fly activity had little influence. Our results demonstrate that early and late summer periods afford Arctic caribou distinct foraging opportunities, as they prioritize quality earlier in the summer and quantity later. Climate change may further constrain caribou access to DN as earlier, warmer Arctic summers may be associated with reduced DN and increased mosquito harassment.
Inland aquatic systems, such as reservoirs, contribute substantially to global methane (CH4) emissions; yet are among the most uncertain components of the total CH4 budget. Reservoirs have received recent attention as they may generate high CH4 fluxes. Improved quantification of these CH4 fluxes, particularly their spatiotemporal distribution, is key to realistically incorporating them in CH4 modeling and budget studies. Here we report on a new global, gridded (0.25° lat × 0.25° lon) study of reservoir CH4 emissions, accounting for new knowledge regarding reservoir areal extent and distribution, and spatiotemporal emission patterns influenced by diurnal variability, temperature-dependent seasonality, satellite-derived freeze-thaw dynamics, and eco-climatic zone. The results of this new data set comprise daily CH4 emissions throughout the full annual cycle and show that reservoirs cover 297 × 103 km2 globally and emit 10.1 Tg CH4 yr−1 (1σ uncertainty range of 7.2–12.9 Tg CH4 yr−1) from diffusive (1.2 Tg CH4 yr−1) and ebullitive (8.9 Tg CH4 yr−1) emission pathways. This analysis of reservoir CH4 emission addresses multiple gaps and uncertainties in previous studies and represents an important contribution to studies of the global CH4 budget. The new data sets and methodologies from this study provide a framework to better understand and model the current and future role of reservoirs in the global CH4 budget and to guide efforts to mitigate reservoir-related CH4 emissions.
Temporal variations of de facto wastewater reuse are relevant to public drinking water systems (PWSs) that obtain water from surface sources. Variations in wastewater discharge flows, streamflow, de facto reuse, and disinfection by-products (DBPs – trihalomethane-4 [THM4] and haloacetic acid-5 [HAA5]) over an 18-year period were examined at 11 PWSs in the Shenandoah River watershed, using more than 25,000 data records, in gaged and ungaged reaches. The relationship of de facto reuse with DBPs by year and quarter at the PWSs was examined. A linear relationship was found between THM4 and de facto reuse on an annual average basis (p = 0.050), as well as in quarters 3 (July – September) (p = 0.032) and 4 (October – December) (p = 0.031). Using a t-test (p < 0.05), the study also showed that there were significant differences in DBP levels for PWSs relative to 1% de facto reuse. This was found for THM4 based on annual average and quarter 1 (January – March) data, and for HAA5 based on quarter 3 data during the period of record.
Slow-moving landslides, often with nearly imperceptible creeping motion, are an important landscape shaper and a dangerous natural hazard across the globe, yet their spatial distribution and geologic controls are still poorly known owing to a paucity of detailed, large-area observations. Here, we use interferometry of L-band satellite radar images to reveal 617 spatially large (4
The Green Mountain State of Vermont is known for its vast swaths of deciduous forest, patches of evergreen, and the Green Mountains that run through its center.
Valuable insight into the forests and landscape features of Vermont can be gleaned from the 50-year historical record of Landsat satellite imagery. The archive is accessible at no cost to researchers, land managers, and the public thanks to the open data policy of the U.S. Geological Survey’s National Land Imaging Program.
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U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192