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Watch lists of invasive species that threaten a particular land management unit are useful tools because they can draw attention to invasive species at the very early stages of invasion when early detection and rapid response efforts are often most successful. However, watch lists typically rely on the subjective selection of invasive species by experts or on the use of spotty occurrence records. Further, incomplete records of invasive plant occurrences bias these watch lists towards the inclusion of invasive plant species that may already be present in a land management unit, because the occurrences have not been formally integrated into publicly accessible biodiversity databases. However, these problems may be overcome by an iterative approach that guides more complete detection and compilation of invasive plant species records within land management units. To address issues from unobserved or unrecorded occurrences, we combined predicted suitable habitat from species distribution models and aggregated invasive plant occurrence records to develop ranked watch lists of 146 priority invasive plant species on >4000 land management units from five different administrative types within the United States. Based on this analysis, we determined that on average 84% of priority invasive plants with suitable habitat within a given land management unit were as yet unobserved, and that 41% of those were ‘doorstep species’ – found within 50 miles of the unit boundary yet not detected within the unit. Two case studies, developed in collaboration with staff at U.S. Fish and Wildlife Service Refuges, showed that by combining both habitat suitability models and invasive plant occurrence records, we could identify additional problematic invasive plants that had been previously overlooked. Model-based watch lists of ‘doorstep species’ are useful tools because they can objectively alert land managers to threats from invasive plants with high likelihood of establishment.

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Jennifer","contributorId":302096,"corporation":false,"usgs":false,"family":"Sieraki","given":"Jennifer","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":863474,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Simpson, Annie 0000-0001-8338-5134","orcid":"https://orcid.org/0000-0001-8338-5134","contributorId":206062,"corporation":false,"usgs":true,"family":"Simpson","given":"Annie","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":863475,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wenick, Jess","contributorId":302097,"corporation":false,"usgs":false,"family":"Wenick","given":"Jess","email":"","affiliations":[{"id":27594,"text":"Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":863476,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Young, Nicholas","contributorId":279993,"corporation":false,"usgs":false,"family":"Young","given":"Nicholas","affiliations":[{"id":7230,"text":"Natural Resource Ecology Laboratory, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":863477,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Sofaer, Helen 0000-0002-9450-5223","orcid":"https://orcid.org/0000-0002-9450-5223","contributorId":216681,"corporation":false,"usgs":true,"family":"Sofaer","given":"Helen","email":"","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":863478,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70239837,"text":"70239837 - 2023 - Trends in tree cover change over three decades related to interannual climate variability and wildfire in California","interactions":[],"lastModifiedDate":"2023-01-23T13:25:40.635476","indexId":"70239837","displayToPublicDate":"2023-01-19T07:22:08","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Trends in tree cover change over three decades related to interannual climate variability and wildfire in California","docAbstract":"

The U.S. State of California has experienced frequent drought events, hotter temperatures and other disruptions to the climate system whose effects on ecosystems have been widely reported in recent decades. Studies primarily confined to specific vegetation communities or species, individual drought incidents, or analysis over a relatively short intervals, has limited our understanding of the broad-scale effects on tree cover and the spatiotemporal variability of effects across broader regions. We focused analysis on multi-annual land cover and land surface change to assess patterns and trends in tree cover loss in tree-dominated Californian ecoregions from 1986 to 2019. The top three years of total tree cover loss for the state were 2018 (1901 km2), 2015 (1556 km2), and 2008 (1549 km2). Overall, annual tree cover loss had upward trends. Tree cover loss rapidly surged later in the study period and was apparently driven by climate stress and wildfires. Underlying geographic variability was apparent in both non-fire and fire-related tree cover loss that sharply increased during hotter multi-year droughts. The increasingly hotter and drier climate conditions were associated with significant increases in fire-induced mortality. Our findings indicate that a possible effect of future hotter and drier climate would lead to further tree cover loss, thereby endangering California's ecosystem goods and services. Geographic variability in tree cover trends indicates that ecoregion-specific mitigation and adaptation strategies would be useful to conserve the region's forest resources. Such strategies may benefit from consideration of historical disturbances, ecoregion's sensitivity to disturbance types, as well as potential ecoregion-specific climate-vegetation-fire feedbacks.

","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/acad15","usgsCitation":"Dwomoh, F.K., Auch, R.F., Brown, J.F., and Tollerud, H.J., 2023, Trends in tree cover change over three decades related to interannual climate variability and wildfire in California: Environmental Research Letters, v. 18, 024007, 15 p., https://doi.org/10.1088/1748-9326/acad15.","productDescription":"024007, 15 p.","ipdsId":"IP-143768","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":444767,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/acad15","text":"Publisher Index Page"},{"id":412213,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"18","noUsgsAuthors":false,"publicationDate":"2023-01-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Dwomoh, Francis K 0000-0002-5054-2276","orcid":"https://orcid.org/0000-0002-5054-2276","contributorId":260864,"corporation":false,"usgs":false,"family":"Dwomoh","given":"Francis","email":"","middleInitial":"K","affiliations":[{"id":52693,"text":"ASRC Federal","active":true,"usgs":false}],"preferred":false,"id":862094,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Auch, Roger F. 0000-0002-5382-5044 auch@usgs.gov","orcid":"https://orcid.org/0000-0002-5382-5044","contributorId":667,"corporation":false,"usgs":true,"family":"Auch","given":"Roger","email":"auch@usgs.gov","middleInitial":"F.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":862095,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":176609,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":862096,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tollerud, Heather J. 0000-0001-9507-4456","orcid":"https://orcid.org/0000-0001-9507-4456","contributorId":210820,"corporation":false,"usgs":true,"family":"Tollerud","given":"Heather","email":"","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":862097,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70242891,"text":"70242891 - 2023 - Climate change hotspots and implications for the global subsea telecommunications network","interactions":[],"lastModifiedDate":"2023-04-21T12:04:18.566776","indexId":"70242891","displayToPublicDate":"2023-01-19T07:02:58","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":14252,"text":"Earth Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Climate change hotspots and implications for the global subsea telecommunications network","docAbstract":"

A global network of subsea telecommunications cables underpins our daily lives, enabling >95% of global digital data transfer, $trillions/day in financial trading, and providing critical communications links, particularly to remote, low-income countries. Despite their importance, subsea cables and their landing stations are vulnerable to damage by natural hazards, including storm surges, waves, cyclones, earthquakes, floods, volcanic eruptions, submarine landslides and ice scour. However, the likelihood or recurrence interval of many of these types of events will likely change under future projected climate change scenarios, compounded by sea-level rise; potentially increasing hazard severity, creating previously unanticipated hazards, or hazards may shift to new locations during the 20–30-year operational life of cable systems. To date, no study has assessed the wide-reaching impacts of future climate change on subsea cables and landing stations on a global scale. Here, for the first time we synthesize the current evidence base, based on published peer-reviewed datasets, to fill this crucial knowledge gap, specifically to assess how and where future climate change is likely to impact subsea cables and their shore-based infrastructure. We find that ocean conditions are highly likely to change on a global basis as a result of climate change, but the feedbacks and links between climate change, natural processes and human activities are often complicated, resulting in a high degree of geographic variability. We identify climate change ‘hotspots’ (regions and locations likely to experience the greatest impacts) but find that not all areas will be affected in the same manner, nor synchronously by the same processes. We conclude that cable routes should carefully consider locally-variable drivers of hazard frequency and magnitude. Consideration should be given both to instantaneous events (e.g. landslides, tropical cyclones) as well as longer-term, sustained impacts (e.g. seabed currents that circulate even in deep water). Multiple factors can combine to increase the risk posed to subsea cables, hence a holistic approach is essential to assess the compounded effects of both natural processes and human activities in the future.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.earscirev.2022.104296","usgsCitation":"Clare, M., Yeo, I., Bricheno, L., Askenov, Y., Browning, J., Haigh, I., Wahl, T., Hunter, J.A., Sams, C., Chaytor, J., Bett, B., and Carter, L., 2023, Climate change hotspots and implications for the global subsea telecommunications network: Earth Science Reviews, v. 237, 104296, 22 p., https://doi.org/10.1016/j.earscirev.2022.104296.","productDescription":"104296, 22 p.","ipdsId":"IP-145171","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":444770,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.earscirev.2022.104296","text":"Publisher Index Page"},{"id":416116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"237","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Clare, M.A.","contributorId":238168,"corporation":false,"usgs":false,"family":"Clare","given":"M.A.","email":"","affiliations":[{"id":39676,"text":"National Oceanography Centre, Southampton, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":870116,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yeo, I.A.","contributorId":304305,"corporation":false,"usgs":false,"family":"Yeo","given":"I.A.","email":"","affiliations":[{"id":13459,"text":"National Oceanography Centre, UK","active":true,"usgs":false}],"preferred":false,"id":870117,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bricheno, L.","contributorId":292902,"corporation":false,"usgs":false,"family":"Bricheno","given":"L.","email":"","affiliations":[{"id":63059,"text":"National Oceanographic Center (NOC), Liverpool, UK.","active":true,"usgs":false}],"preferred":false,"id":870118,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Askenov, Y","contributorId":304307,"corporation":false,"usgs":false,"family":"Askenov","given":"Y","email":"","affiliations":[{"id":13459,"text":"National Oceanography Centre, UK","active":true,"usgs":false}],"preferred":false,"id":870119,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Browning, J.","contributorId":207617,"corporation":false,"usgs":false,"family":"Browning","given":"J.","email":"","affiliations":[{"id":37580,"text":"University College London Earth Sciences, UK","active":true,"usgs":false}],"preferred":false,"id":870120,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Haigh, I.D.","contributorId":304309,"corporation":false,"usgs":false,"family":"Haigh","given":"I.D.","email":"","affiliations":[{"id":33401,"text":"University of Southampton, UK","active":true,"usgs":false}],"preferred":false,"id":870121,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wahl, T.","contributorId":292908,"corporation":false,"usgs":false,"family":"Wahl","given":"T.","affiliations":[{"id":63065,"text":"Univeristy of Central Florida (UCF), Orlando, Florida US.","active":true,"usgs":false}],"preferred":false,"id":870122,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hunter, J. A.","contributorId":203579,"corporation":false,"usgs":false,"family":"Hunter","given":"J.","email":"","middleInitial":"A.","affiliations":[{"id":7219,"text":"Natural Resources Canada","active":true,"usgs":false}],"preferred":false,"id":870123,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sams, C.","contributorId":304311,"corporation":false,"usgs":false,"family":"Sams","given":"C.","email":"","affiliations":[{"id":13459,"text":"National Oceanography Centre, UK","active":true,"usgs":false}],"preferred":false,"id":870124,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Chaytor, Jason 0000-0001-8135-8677 jchaytor@usgs.gov","orcid":"https://orcid.org/0000-0001-8135-8677","contributorId":140095,"corporation":false,"usgs":true,"family":"Chaytor","given":"Jason","email":"jchaytor@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":870125,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Bett, B.J.","contributorId":304312,"corporation":false,"usgs":false,"family":"Bett","given":"B.J.","affiliations":[{"id":13459,"text":"National Oceanography Centre, UK","active":true,"usgs":false}],"preferred":false,"id":870126,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Carter, L.","contributorId":304315,"corporation":false,"usgs":false,"family":"Carter","given":"L.","affiliations":[{"id":34109,"text":"Victoria University of Wellington, New Zealand","active":true,"usgs":false}],"preferred":false,"id":870127,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70240151,"text":"70240151 - 2023 - A model of transmissivity and hydraulic conductivity from electrical resistivity distribution derived from airborne electromagnetic surveys of the Mississippi River Valley Alluvial Aquifer, Midwest USA","interactions":[],"lastModifiedDate":"2023-03-31T15:16:16.810474","indexId":"70240151","displayToPublicDate":"2023-01-19T06:50:27","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"A model of transmissivity and hydraulic conductivity from electrical resistivity distribution derived from airborne electromagnetic surveys of the Mississippi River Valley Alluvial Aquifer, Midwest USA","docAbstract":"

Groundwater-flow models require the spatial distribution of the hydraulic conductivity parameter. One approach to defining this spatial distribution in groundwater-flow model grids is to map the electrical resistivity distribution by airborne electromagnetic (AEM) survey and establish a petrophysical relation between mean resistivity calculated as a nonlinear function of the resistivity layering and thicknesses of the layers and aquifer transmissivity compiled from historical aquifer tests completed within the AEM survey area. The petrophysical relation is used to transform AEM resistivity to transmissivity and to hydraulic conductivity over areas where the saturated thickness of the aquifer is known. The US Geological Survey applied this approach to a gain better understanding of the aquifer properties of the Mississippi River Valley alluvial aquifer. Alluvial-aquifer transmissivity data, compiled from 160 historical aquifer tests in the Mississippi Alluvial Plain (MAP), were correlated to mean resistivity calculated from 16,816 line-kilometers (km) of inverted resistivity soundings produced from a frequency-domain AEM survey of 95,000 km2 of the MAP. Correlated data were used to define petrophysical relations between transmissivity and mean resistivity by omitting from the correlations the aquifer-test and AEM sounding data that were separated by distances greater than 1 km and manually calibrating the relation coefficients to slug-test data. The petrophysical relation yielding the minimum residual error between simulated and slug-test data was applied to 2,364 line-km of AEM soundings in the 1,000-km2 Shellmound (Mississippi) study area to calculate hydraulic property distributions of the alluvial aquifer for use in future groundwater-flow models.

","language":"English","publisher":"Springer","doi":"10.1007/s10040-022-02590-6","usgsCitation":"Ikard, S., Minsley, B.J., Rigby, J.R., and Kress, W., 2023, A model of transmissivity and hydraulic conductivity from electrical resistivity distribution derived from airborne electromagnetic surveys of the Mississippi River Valley Alluvial Aquifer, Midwest USA: Hydrogeology Journal, v. 31, p. 313-334, https://doi.org/10.1007/s10040-022-02590-6.","productDescription":"22 p.","startPage":"313","endPage":"334","ipdsId":"IP-131404","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":444772,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10040-022-02590-6","text":"Publisher Index Page"},{"id":435495,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZBFXI5","text":"USGS data release","linkHelpText":"Historical (1940–2006) and recent (2019–20) aquifer slug test datasets used to model transmissivity and hydraulic conductivity of the Mississippi River Valley alluvial aquifer from recent (2018–20) airborne electromagnetic (AEM) survey data"},{"id":412493,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mississippi River Valley Alluvial Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.75162112363195,\n 32.09494813471724\n ],\n [\n -86.77759567445979,\n 32.09494813471724\n ],\n [\n -86.77759567445979,\n 38.26438477290091\n ],\n [\n -92.75162112363195,\n 38.26438477290091\n ],\n [\n -92.75162112363195,\n 32.09494813471724\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"31","noUsgsAuthors":false,"publicationDate":"2023-01-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Ikard, Scott 0000-0002-8304-4935","orcid":"https://orcid.org/0000-0002-8304-4935","contributorId":201775,"corporation":false,"usgs":true,"family":"Ikard","given":"Scott","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862774,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Minsley, Burke J. 0000-0003-1689-1306","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":248573,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"","middleInitial":"J.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":862775,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rigby, James R. 0000-0002-5611-6307","orcid":"https://orcid.org/0000-0002-5611-6307","contributorId":260894,"corporation":false,"usgs":true,"family":"Rigby","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862776,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kress, Wade 0000-0002-6833-028X","orcid":"https://orcid.org/0000-0002-6833-028X","contributorId":203539,"corporation":false,"usgs":true,"family":"Kress","given":"Wade","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862777,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70241146,"text":"70241146 - 2023 - Plant community predictions support the potential for big sagebrush range expansion adjacent to the leading edge","interactions":[],"lastModifiedDate":"2023-03-13T11:44:20.641768","indexId":"70241146","displayToPublicDate":"2023-01-19T06:42:15","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3242,"text":"Regional Environmental Change","active":true,"publicationSubtype":{"id":10}},"title":"Plant community predictions support the potential for big sagebrush range expansion adjacent to the leading edge","docAbstract":"

Big sagebrush ecosystems are widespread across drylands of western North America and provide numerous services, but the abundance of these ecosystems has declined substantially and the future of these ecosystems is uncertain. As a result, characterizing potential areas for expansion of these ecosystems is important. Species distribution models of the big sagebrush suggest areas of increasing climatic habitat suitability at northern latitudes under climate change scenarios. This implies the formation of a leading edge during a future big sagebrush range expansion. Such an expansion requires that current nearby range margin big sagebrush populations are stable and serve as future seed sources. Our goal was to quantify the impacts of future climate conditions on the plant community composition and biomass in the in range margin big sagebrush plant communities adjacent to the leading edge. We did this using an individual-based soil water and plant growth simulation model, STEPWAT2. We assessed community dynamics throughout the twenty-first century using 13 climate models under two representative concentration pathways to capture the variability among projections. Our results show minimal overall change in plant community composition and little change in biomass, suggesting that range margin big sagebrush plant communities adjacent to the leading edge will remain stable to serve as essential dispersal sources for future range expansion, assuming no other relevant changes such as changes in disturbance regimes. These assessments of plant community responses to shifts in climate and characterization of variability in future projections will help inform conservation planning and management of the big sagebrush ecosystem.

","language":"English","publisher":"Springer","doi":"10.1007/s10113-022-01999-9","usgsCitation":"Martyn, T., Palmquist, K., Bradford, J., Schlaepfer, D.R., and Lauenroth, W., 2023, Plant community predictions support the potential for big sagebrush range expansion adjacent to the leading edge: Regional Environmental Change, v. 23, 27, 12 p., https://doi.org/10.1007/s10113-022-01999-9.","productDescription":"27, 12 p.","ipdsId":"IP-146920","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":414005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -125.54030283521868,\n 49.526621871576566\n ],\n [\n -125.54030283521868,\n 28.895094929809844\n ],\n [\n -101.38064109224445,\n 28.895094929809844\n ],\n [\n -101.38064109224445,\n 49.526621871576566\n ],\n [\n -125.54030283521868,\n 49.526621871576566\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"23","noUsgsAuthors":false,"publicationDate":"2023-01-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Martyn, T.","contributorId":303016,"corporation":false,"usgs":false,"family":"Martyn","given":"T.","affiliations":[{"id":65608,"text":"Yale School of the Environment, Yale University, 195 Prospect Street, New Haven, CT, 06511, USA","active":true,"usgs":false}],"preferred":false,"id":866273,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palmquist, K.","contributorId":303017,"corporation":false,"usgs":false,"family":"Palmquist","given":"K.","email":"","affiliations":[{"id":65609,"text":"Department of Biological Sciences, Marshall University, 1 John Marshall Drive, Huntington, WV, 25755, USA","active":true,"usgs":false}],"preferred":false,"id":866274,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":866275,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schlaepfer, Daniel Rodolphe 0000-0001-9973-2065","orcid":"https://orcid.org/0000-0001-9973-2065","contributorId":225569,"corporation":false,"usgs":true,"family":"Schlaepfer","given":"Daniel","email":"","middleInitial":"Rodolphe","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":866276,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lauenroth, W.K.","contributorId":192984,"corporation":false,"usgs":false,"family":"Lauenroth","given":"W.K.","email":"","affiliations":[],"preferred":false,"id":866277,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70239849,"text":"70239849 - 2023 - Identifying building locations in the wildland–urban interface before and after fires with convolutional neural networks","interactions":[],"lastModifiedDate":"2023-05-01T15:44:23.6532","indexId":"70239849","displayToPublicDate":"2023-01-19T06:28:12","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Identifying building locations in the wildland–urban interface before and after fires with convolutional neural networks","docAbstract":"

Background: Wildland–urban interface (WUI) maps identify areas with wildfire risk, but they are often outdated owing to the lack of building data. Convolutional neural networks (CNNs) can extract building locations from remote sensing data, but their accuracy in WUI areas is unknown. Additionally, CNNs are computationally intensive and technically complex, making them challenging for end-users, such as those who use or create WUI maps, to apply.

Aims: We identified buildings pre- and post-wildfire and estimated building destruction for three California wildfires: Camp, Tubbs and Woolsey.

Methods: We evaluated a CNN-based building dataset and a CNN model from a separate commercial vendor to detect buildings from high-resolution imagery. This dataset and model represent to end-users the state of the art of what is readily available for potential WUI mapping.

Key results: We found moderate accuracies for the building dataset and the CNN model and a severe underestimation of buildings and their destruction rates where trees occluded buildings. The CNN model performed best post-fire with accuracies ≥73%.

Conclusions: Existing CNNs may be used with moderate accuracy for identifying individual buildings post-fire and mapping the extent of the WUI. The implications are, however, that CNNs are too inaccurate for post-fire damage assessments or building counts in the WUI.

","language":"English","publisher":"CSIRO","doi":"10.1071/WF22181","usgsCitation":"Kasraee, N.K., Hawbaker, T., and Radeloff, V., 2023, Identifying building locations in the wildland–urban interface before and after fires with convolutional neural networks: International Journal of Wildland Fire, v. 32, no. 4, p. 610-621, https://doi.org/10.1071/WF22181.","productDescription":"12 p.","startPage":"610","endPage":"621","ipdsId":"IP-141304","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":435496,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VWV2IO","text":"USGS data release","linkHelpText":"Building locations identified before and after the Camp, Tubbs, and Woolsey wildfires"},{"id":412207,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-01-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Kasraee, Neda K.","contributorId":301130,"corporation":false,"usgs":false,"family":"Kasraee","given":"Neda","email":"","middleInitial":"K.","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":862137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":862138,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Radeloff, Volker C.","contributorId":294405,"corporation":false,"usgs":false,"family":"Radeloff","given":"Volker C.","affiliations":[{"id":34113,"text":"University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":862139,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70256633,"text":"70256633 - 2023 - A perched culvert and natural obstructions limit fish dispersal in an intermittent prairie stream","interactions":[],"lastModifiedDate":"2024-08-27T16:35:17.58428","indexId":"70256633","displayToPublicDate":"2023-01-18T11:22:33","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"A perched culvert and natural obstructions limit fish dispersal in an intermittent prairie stream","docAbstract":"

Poorly constructed road crossings block upstream movement of fish into stream reaches that provide critical habitat or connect isolated populations. Although removing these barriers is often a conservation priority, quantifying fish passage following removal has not been well studied, particularly in intermittent streams. In this study, we sought to understand how barriers influence the dispersal of fishes in intermittent prairie streams. We used passive integrated transponder tags and antenna stations to quantify fish movement of 3 prairie-stream fishes (Central Stoneroller Campostoma anomalum [Rafinesque, 1820], Southern Redbelly Dace Chrosomus erythrogaster [Rafinesque, 1820], and Creek Chub Semotilis atromaculatus [Mitchill, 1818]) through a road crossing in an intermittent prairie stream for 3 y before and 3 y after removing a perched culvert. We verified that no upstream fish movement occurred through the culvert, despite large aggregations of tagged fish in the intermittent reach below the culvert. In contrast, tagged individuals of all 3 species were detected above the road crossing in each of the 3 y following removal. We also tracked the recovery of these species, plus the Orangethroat Darter Etheostoma spectabile (Agassiz, 1854), following a severe drought in 2018 in 2 spring-fed tributary reaches, 1 without a downstream barrier and 1 with the removed downstream culvert. Surveys of the tributary reaches showed rapid recovery of fish densities following drought in the tributary without a downstream barrier. However, recovery at the site above the removed culvert appeared to be limited by a natural waterfall. Our observations suggest barrier removal allowed access to spawning habitat within the intermittent reach immediately upstream of the site, but other obstacles or shear distance to perennial spring-fed tributary reaches also limited recolonization following severe drought. Increased connectivity between perennial and intermittent reaches in prairie streams likely benefits fishes by increasing their resilience following disturbance and providing habitat during critical life stages.

","language":"English","publisher":"University of Chicago Press","doi":"10.1086/723046","usgsCitation":"Gido, K., Hedden, S.C., Bruckerhoff, L.A., Pennock, C.A., Hedden, C.K., Hopper, G.W., Renner, E.A., Johnson, E., and Postlethwait, B.J., 2023, A perched culvert and natural obstructions limit fish dispersal in an intermittent prairie stream: Freshwater Science, v. 42, no. 1, p. 33-43, https://doi.org/10.1086/723046.","productDescription":"11 p.","startPage":"33","endPage":"43","ipdsId":"IP-137178","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":499917,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.lsu.edu/agrnr_pubs/367","text":"External Repository"},{"id":433206,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","otherGeospatial":"Kings Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.64135743121071,\n 39.14759412347976\n ],\n [\n -96.64135743121071,\n 39.00078060209594\n ],\n [\n -96.44964269955051,\n 39.00078060209594\n ],\n [\n -96.44964269955051,\n 39.14759412347976\n ],\n [\n -96.64135743121071,\n 39.14759412347976\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"42","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gido, Keith B.","contributorId":341429,"corporation":false,"usgs":false,"family":"Gido","given":"Keith B.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":908404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hedden, Skyler C.","contributorId":341430,"corporation":false,"usgs":false,"family":"Hedden","given":"Skyler","email":"","middleInitial":"C.","affiliations":[{"id":38831,"text":"Arizona Department of Game and Fish","active":true,"usgs":false}],"preferred":false,"id":908405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bruckerhoff, Lindsey Ann 0000-0002-9523-4808","orcid":"https://orcid.org/0000-0002-9523-4808","contributorId":292594,"corporation":false,"usgs":true,"family":"Bruckerhoff","given":"Lindsey","email":"","middleInitial":"Ann","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908406,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pennock, Casey A.","contributorId":341431,"corporation":false,"usgs":false,"family":"Pennock","given":"Casey","email":"","middleInitial":"A.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":908407,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hedden, Crosby K.","contributorId":341432,"corporation":false,"usgs":false,"family":"Hedden","given":"Crosby","email":"","middleInitial":"K.","affiliations":[{"id":38831,"text":"Arizona Department of Game and Fish","active":true,"usgs":false}],"preferred":false,"id":908408,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hopper, Garrett W.","contributorId":341433,"corporation":false,"usgs":false,"family":"Hopper","given":"Garrett","email":"","middleInitial":"W.","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":908409,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Renner, Elizabeth A.","contributorId":341434,"corporation":false,"usgs":false,"family":"Renner","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":908410,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johnson, Eric R.","contributorId":341435,"corporation":false,"usgs":false,"family":"Johnson","given":"Eric R.","affiliations":[{"id":81737,"text":"Wildlife and Avian Programs","active":true,"usgs":false}],"preferred":false,"id":908411,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Postlethwait, Ben J.","contributorId":341436,"corporation":false,"usgs":false,"family":"Postlethwait","given":"Ben","email":"","middleInitial":"J.","affiliations":[{"id":81737,"text":"Wildlife and Avian Programs","active":true,"usgs":false}],"preferred":false,"id":908412,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70239039,"text":"70239039 - 2023 - Addressing a potential weakness in indices of predation, herbivory, and parasitism","interactions":[],"lastModifiedDate":"2023-04-12T13:29:13.910564","indexId":"70239039","displayToPublicDate":"2023-01-18T11:14:25","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3103,"text":"Population Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Addressing a potential weakness in indices of predation, herbivory, and parasitism","docAbstract":"

Quantification of predation, herbivory, and parasitism is critical to understanding the dynamics and trophic interactions of populations in an ecosystem. Such quantification can be challenging if the availability or consumption of the taxa are difficult to assess. Sometimes the consumption of a single prey, forage, or host is used as an overall index of the predation, herbivory, or parasitism for a population of interest. Occasionally, human-manipulated baits are used to derive similar indices. However, all such indices are susceptible to influence by variation in the abundance of the preferred taxon relative to other taxa as the result of preference switching. In this article, I describe a test for preference switching (and an adjustment, if detected) that does not require availability and consumption of the prey (forage, or host) to be measured on the same scale. The ability to detect and adjust for preference switching in such situations may advance the understanding of biological preference in taxa not previously studied in this respect.

","language":"English","publisher":"The Ecological Society of Japan","doi":"10.1002/1438-390X.12147","usgsCitation":"Adams, J.V., 2023, Addressing a potential weakness in indices of predation, herbivory, and parasitism: Population Ecology, v. 65, no. 2, p. 133-144, https://doi.org/10.1002/1438-390X.12147.","productDescription":"12 p.","startPage":"133","endPage":"144","ipdsId":"IP-141116","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":498871,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/1438-390x.12147","text":"Publisher Index Page"},{"id":412372,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"65","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-01-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Adams, Jean V. 0000-0002-9101-068X jvadams@usgs.gov","orcid":"https://orcid.org/0000-0002-9101-068X","contributorId":3140,"corporation":false,"usgs":true,"family":"Adams","given":"Jean","email":"jvadams@usgs.gov","middleInitial":"V.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":859801,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70240290,"text":"70240290 - 2023 - Drivers of survival of translocated tortoises","interactions":[],"lastModifiedDate":"2023-02-03T14:52:44.17437","indexId":"70240290","displayToPublicDate":"2023-01-18T08:43:40","publicationYear":"2023","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":"Drivers of survival of translocated tortoises","docAbstract":"

Translocation of animals, especially for threatened and endangered species, is a currently popular but very challenging activity. We translocated 158 adult Agassiz's desert tortoises (Gopherus agassizii), a threatened species, from the National Training Center, Fort Irwin, in the central Mojave Desert in California, USA, to 4 plots as part of a long-distance, hard-release, mitigation-driven translocation to prevent deaths from planned military maneuvers. We monitored demographic and behavioral variables of tortoises fitted with radio-transmitters from 2008 to 2018. By the end of the project, 17.72% of tortoises were alive, 65.82% were dead, 15.19% were missing, and 1.27% were removed from the study because they returned to Fort Irwin. Mortality was high during the first 3 years: >50% of the released animals died, primarily from predation. Thereafter, mortality declined but remained high. After 10.5 years, survival was highest, 37.50% (15/40), on the plot closest to original home sites, whereas from 2.56% to 23.68% remained alive on the other 3 release plots. Surviving tortoises settled early, repeatedly using locations where they constructed burrows, compared with tortoises that died or disappeared. Models of behavioral and other variables indicated that numbers of repeatedly used locations (burrows) were a driver of survival throughout the study, although plot location, size and sex of tortoises, and distance traveled were contributors, especially during early years. Because >50% mortality occurred, we considered this translocation unsuccessful. The study area appeared to be an ecological sink with historical and current anthropogenic uses contributing to habitat degradation and a decline in both the resident and released tortoises. Our findings will benefit design and selection of future translocation areas.

","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22352","usgsCitation":"Mack, J., and Berry, K.H., 2023, Drivers of survival of translocated tortoises: Journal of Wildlife Management, v. 87, e22352, 27 p, https://doi.org/10.1002/jwmg.22352.","productDescription":"e22352, 27 p","ipdsId":"IP-144211","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":444783,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22352","text":"Publisher Index Page"},{"id":435497,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9USRU0T","text":"USGS data release","linkHelpText":"Demographic and Movement Data for Adult Desert Tortoises Translocated from Fort Irwin, 2008-2018"},{"id":412671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Fort Irwin National Training Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.35309032036193,\n 35.83722728738816\n ],\n [\n -117.35309032036193,\n 35.1178564871942\n ],\n [\n -116.11268639625317,\n 35.1178564871942\n ],\n [\n -116.11268639625317,\n 35.83722728738816\n ],\n [\n -117.35309032036193,\n 35.83722728738816\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"87","noUsgsAuthors":false,"publicationDate":"2023-01-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Mack, Jeremy S 0000-0002-3394-8493","orcid":"https://orcid.org/0000-0002-3394-8493","contributorId":206166,"corporation":false,"usgs":false,"family":"Mack","given":"Jeremy S","affiliations":[{"id":37269,"text":"Crater Lake National Park (formerly USGS - WERC)","active":true,"usgs":false}],"preferred":false,"id":863258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berry, Kristin H. 0000-0003-1591-8394 kristin_berry@usgs.gov","orcid":"https://orcid.org/0000-0003-1591-8394","contributorId":437,"corporation":false,"usgs":true,"family":"Berry","given":"Kristin","email":"kristin_berry@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863259,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70249747,"text":"70249747 - 2023 - A field test of R package GPSeqClus: For establishing animal location clusters","interactions":[],"lastModifiedDate":"2023-10-26T12:15:31.229011","indexId":"70249747","displayToPublicDate":"2023-01-18T07:13:22","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9977,"text":"Ecological Solutions and Evidence","active":true,"publicationSubtype":{"id":10}},"title":"A field test of R package GPSeqClus: For establishing animal location clusters","docAbstract":"
  1. The ability to track animals with Global Positioning System (GPS) collars opened an enormous potential for studying animal movements and behaviour in their natural environment. One such endeavour is to identify clusters of GPS locations as a way to estimate predator kill rate. Clapp et al. (2021) developed an R package (GPSeqClus) to assess a location dataset based on user-defined parameters to identify clusters and their characteristics. These characteristics can then help to distinguish resting-site clusters from kill sites of their large (>50 kg) prey.
  2. We identified location clusters of an adult male wolf Canis lupus on Ellesmere Island, Nunavut, Canada in July 2009 and tracked him until he died in April 2010. Identifying location clusters was challenging because the collar only obtained two GPS locations per day (12 h apart). In July 2010, we searched 30 of 52 location-clusters we identified as kill/scavenge sites and found 17 of them as such, given they had muskox Ovibos moschatus or caribou Rangifer tarandus pearyi remains nearby. We also documented five wolf rendezvous sites, two den sites, and the wolf's death site to total 60 location-clusters in all.
  3. We used a two-step process in testing the R Package GPSeqClus (hereafter GPSeqClus): (1) compare the number of clusters our method discerned with the number identified by the new algorithm, and (2) compare the number of biologically significant clusters (e.g. den sites, kill/feeding sites) we found with the number the new algorithm located. We made these tests with GPSeqClus by varying the search radius, number of days at a site, and minimum number of locations required for a cluster.
  4. GPSeqClus compared well to our technique, with the best sub-algorithm among the 25 we tested only missing three of our identified clusters and yielding six additional clusters. GPSeqClus identified 16 of the 17 confirmed sites of remains, all wolf home sites, and the wolf's carcass site. Identifying clusters using a 500-m search radius, a 1.5-day window, and a minimum of two GPS locations per cluster was suitable for a coarse GPS acquisition rate of two locations per day when prey are large, such as muskox or caribou.
  5. Given that GPSeqClus performed well with our coarse location dataset, we expect it will also perform even better with a collar acquiring more than two locations per day. Having a field-tested utility such as GPSeqClus will enhance carnivore predation studies elsewhere.
","language":"English","publisher":"British Ecological Society","doi":"10.1002/2688-8319.12204","usgsCitation":"Cluff, H.D., and Mech, L.D., 2023, A field test of R package GPSeqClus: For establishing animal location clusters: Ecological Solutions and Evidence, v. 4, no. 1, e12204, 9 p., https://doi.org/10.1002/2688-8319.12204.","productDescription":"e12204, 9 p.","ipdsId":"IP-136647","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":444784,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2688-8319.12204","text":"Publisher Index Page"},{"id":422133,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-01-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Cluff, H. Dean","contributorId":53210,"corporation":false,"usgs":true,"family":"Cluff","given":"H.","email":"","middleInitial":"Dean","affiliations":[],"preferred":false,"id":886942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mech, L. David 0000-0003-3944-7769 david_mech@usgs.gov","orcid":"https://orcid.org/0000-0003-3944-7769","contributorId":2518,"corporation":false,"usgs":true,"family":"Mech","given":"L.","email":"david_mech@usgs.gov","middleInitial":"David","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":886920,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70239772,"text":"70239772 - 2023 - Incorporating temperature into seepage loss estimates for a large unlined irrigation canal","interactions":[],"lastModifiedDate":"2025-05-14T17:36:22.285243","indexId":"70239772","displayToPublicDate":"2023-01-18T06:52:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Incorporating temperature into seepage loss estimates for a large unlined irrigation canal","docAbstract":"

Quantifying seepage losses from unlined irrigation canals is necessary to improve water use and conservation. The use of heat as a tracer is widely used in quantifying seepage rates across the sediment–water interface. In this study, field observations and two-dimensional numerical models were used to simulate seepage losses during the 2018 and 2019 irrigation season in the Truckee Canal system. Nineteen transects were instrumented with temperature probes and stage recording devices for inverse modeling to derive seepage flux and volumetric losses over the 39 km length of canal. The numerical models for each transect were calibrated and validated using the two-year dataset. Soil zones and observation data were used in each numerical model to help guide calibration of vertical and lateral heat and fluid fluxes. Model simulations were used to derive multivariable regression equations that consider stage, temperature, and hydraulic gradient. The results demonstrate the value of long-term datasets that illustrate the seasonality of groundwater levels, siltation, stage, and temperature on seepage rates. Seepage rates estimated by the numerical models range from 0.16 to 4.6 m3/d m−1. Total annual volumetric losses estimated for 2018 and 2019 were 1.6 × 10-2 to 1.2 × 10-2 km3, respectively. The seepage losses estimated by this study account for 32 % to 41 % of the inflow volumes. Regression models were able to reproduce seepage time-series simulated by the numerical models reasonably well. In arid environments, water diverted into irrigation canals may be influenced by seasonal variations in temperature sufficient to influence the water accounting of conveyed surface flows.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2023.129117","usgsCitation":"Naranjo, R.C., Smith, D., and Lindenbach, E.J., 2023, Incorporating temperature into seepage loss estimates for a large unlined irrigation canal: Journal of Hydrology, v. 617, no. C, 129117, 15 p.; Data Release, https://doi.org/10.1016/j.jhydrol.2023.129117.","productDescription":"129117, 15 p.; Data Release","ipdsId":"IP-096517","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":412069,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":435498,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P971LB6C","text":"USGS data release","linkHelpText":"Supplemental data and documentation of VS2DH seepage models: Incorporating temperature into seepage loss estimates for a large irrigation canal"}],"country":"United States","state":"Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.6447610565691,\n 39.4835481422399\n ],\n [\n -119.6447610565691,\n 38.96460925429065\n ],\n [\n -118.63993876134998,\n 38.96460925429065\n ],\n [\n -118.63993876134998,\n 39.4835481422399\n ],\n [\n -119.6447610565691,\n 39.4835481422399\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"617","issue":"C","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Naranjo, Ramon C. 0000-0003-4469-6831 rnaranjo@usgs.gov","orcid":"https://orcid.org/0000-0003-4469-6831","contributorId":3391,"corporation":false,"usgs":true,"family":"Naranjo","given":"Ramon","email":"rnaranjo@usgs.gov","middleInitial":"C.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861853,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, David 0000-0002-9543-800X","orcid":"https://orcid.org/0000-0002-9543-800X","contributorId":169280,"corporation":false,"usgs":true,"family":"Smith","given":"David","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861906,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lindenbach, Evan J.","contributorId":263642,"corporation":false,"usgs":false,"family":"Lindenbach","given":"Evan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":861907,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70239766,"text":"70239766 - 2023 - Comparison of traditional and geometric morphometrics using Lake Huron ciscoes of the Coregonus artedi complex","interactions":[],"lastModifiedDate":"2023-05-25T15:38:17.243989","indexId":"70239766","displayToPublicDate":"2023-01-18T06:50:23","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of traditional and geometric morphometrics using Lake Huron ciscoes of the Coregonus artedi complex","docAbstract":"

Here we determine how traditional morphometrics (TM) compares with geometric morphometrics (GM) in discriminating among morphologies of four forms of ciscoes of the Coregonus artedi complex collected from Lake Huron. One of the forms comprised two groups of the same deepwater cisco separated by capture depth, whereas the other three forms were shallow-water ciscoes. Our three groups of shallow-water ciscoes were better separated (3% versus 19% overlap) in Principle Component Analysis (PCA) with TM data than with GM data incorporating semilandmarks (evenly spaced nonhomologous landmarks used to bridge between widely separated homologous landmarks). Our two deepwater cisco groups, comprising a putatively single form collected from different depths, separated more in PCAs with GM data (33% overlap) than in PCAs with TM data (66% overlap), an anomaly caused by greater decompression of the swimbladder and deformation of the body wall in the group captured at greater depths. Separation of the two deepwater cisco groups captured at different depths was not affected by the removal of semilandmarks. Assignment of forms using canonical variate analysis (CVA) accurately assigned 86% of individuals using TM data, 98% of individuals using GM data incorporating semilandmarks, and 100% of individuals using GM data without semilandmarks. However, we considered assignments from the same form of deepwater cisco into separate groups as misassignments resulting from different capture depths, which reduced the accuracy of assignments with GM data to 66% with semilandmarks. Our study implies that TM will continue to have an important role in morphological discrimination within Coregonus and other fishes similarly shaped.

","language":"English","publisher":"Wiley","doi":"10.1002/tafs.10403","usgsCitation":"Martin, B.E., O’Malley, B., Eshenroder, R.E., Kao, Y., Olds, C., O’Brien, T.P., and Davis, C.L., 2023, Comparison of traditional and geometric morphometrics using Lake Huron ciscoes of the Coregonus artedi complex: Transactions of the American Fisheries Society, v. 152, no. 3, p. 296-309, https://doi.org/10.1002/tafs.10403.","productDescription":"14 p.","startPage":"296","endPage":"309","ipdsId":"IP-143472","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":498958,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10403","text":"Publisher Index Page"},{"id":412068,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Huron","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n 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Wisconsin","active":true,"usgs":false}],"preferred":false,"id":861807,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Malley, Brian 0000-0001-5035-3080 bomalley@usgs.gov","orcid":"https://orcid.org/0000-0001-5035-3080","contributorId":216560,"corporation":false,"usgs":true,"family":"O’Malley","given":"Brian","email":"bomalley@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":861808,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eshenroder, Randy E","contributorId":301032,"corporation":false,"usgs":false,"family":"Eshenroder","given":"Randy","email":"","middleInitial":"E","affiliations":[{"id":65273,"text":"GLFC","active":true,"usgs":false}],"preferred":false,"id":861809,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kao, Yu-Chun 0000-0001-5552-909X ykao@usgs.gov","orcid":"https://orcid.org/0000-0001-5552-909X","contributorId":192240,"corporation":false,"usgs":true,"family":"Kao","given":"Yu-Chun","email":"ykao@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":861810,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olds, Chris","contributorId":218041,"corporation":false,"usgs":false,"family":"Olds","given":"Chris","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":861811,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Brien, Timothy P. 0000-0003-4502-5204 tiobrien@usgs.gov","orcid":"https://orcid.org/0000-0003-4502-5204","contributorId":2662,"corporation":false,"usgs":true,"family":"O’Brien","given":"Timothy","email":"tiobrien@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":861812,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Davis, Chris L.","contributorId":264659,"corporation":false,"usgs":false,"family":"Davis","given":"Chris","email":"","middleInitial":"L.","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":861813,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70239872,"text":"70239872 - 2023 - Structured decision making to prioritize regional bird monitoring needs","interactions":[],"lastModifiedDate":"2023-06-09T15:05:52.668523","indexId":"70239872","displayToPublicDate":"2023-01-18T06:39:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13279,"text":"INFORMS Journal on Applied Analytics","active":true,"publicationSubtype":{"id":10}},"title":"Structured decision making to prioritize regional bird monitoring needs","docAbstract":"

Conservation planning for large ecosystems has multiple benefits but is often challenging to implement because of the multiple jurisdictions, species, and habitats involved. In addition, decision making at large spatial scales can be hampered because many approaches do not explicitly incorporate potentially competing values and concerns of stakeholders. After the Deepwater Horizon oil spill, establishing baselines was challenging because of (1) variation in study designs, (2) inconsistent use of explicit objectives and hypotheses, (3) inconsistent use of standardized monitoring protocols, and (4) variation in spatial and temporal scope associated with avian monitoring projects before the spill. Herein, we show how the Gulf of Mexico Avian Monitoring Network members used structured decision making to identify bird monitoring priorities. We used multiple tools and techniques to clearly define the problem and stakeholder objectives and to identify bird monitoring priorities at the scale of the entire northern Gulf of Mexico region. Although our example is specific to the northern Gulf of Mexico, this approach provides an example of how stakeholder values can be incorporated into the coordination process of broad-scale monitoring programs to address management, restoration, and scientific questions in other ecosystems and for other taxa.

","language":"English","publisher":"InForms","doi":"10.1287/inte.2022.1154","usgsCitation":"Fournier, A., Wilson, R., Gleason, J.S., Adams, E.M., Brush, J.M., Cooper, R.J., DeMaso, S.J., Driscoll, M., Frederick, P.C., Jodice, P.G., Ottinger, M.A., Reeves, D.B., Seymour, M.A., Sharuga, S.M., Tirpak, J., Vermillion, W.G., Zenzal, T.J., Lyons, J.E., and Woodrey, M.S., 2023, Structured decision making to prioritize regional bird monitoring needs: INFORMS Journal on Applied Analytics, v. 53, no. 3, p. 207-217, https://doi.org/10.1287/inte.2022.1154.","productDescription":"11 p.","startPage":"207","endPage":"217","ipdsId":"IP-102745","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":412274,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fournier, Auriel M. V.","contributorId":176535,"corporation":false,"usgs":false,"family":"Fournier","given":"Auriel M. V.","affiliations":[],"preferred":false,"id":862219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, R. Randy","contributorId":288965,"corporation":false,"usgs":false,"family":"Wilson","given":"R. Randy","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":862221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gleason, Jeffrey S.","contributorId":264218,"corporation":false,"usgs":false,"family":"Gleason","given":"Jeffrey","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":862222,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, Evan M.","contributorId":139994,"corporation":false,"usgs":false,"family":"Adams","given":"Evan","email":"","middleInitial":"M.","affiliations":[{"id":6928,"text":"BioDiversity Research Institute, Gorham, ME 04038","active":true,"usgs":false}],"preferred":false,"id":862223,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brush, Janell M.","contributorId":264219,"corporation":false,"usgs":false,"family":"Brush","given":"Janell","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":862224,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cooper, Robert J.","contributorId":99245,"corporation":false,"usgs":false,"family":"Cooper","given":"Robert","email":"","middleInitial":"J.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":862225,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"DeMaso, Stephen J.","contributorId":86938,"corporation":false,"usgs":false,"family":"DeMaso","given":"Stephen","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":862226,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Driscoll, Melanie J. L.","contributorId":301147,"corporation":false,"usgs":false,"family":"Driscoll","given":"Melanie J. L.","affiliations":[{"id":65318,"text":"Baton Rouge, LA","active":true,"usgs":false}],"preferred":false,"id":862227,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Frederick, Peter C.","contributorId":215042,"corporation":false,"usgs":false,"family":"Frederick","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":39161,"text":"Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, Florida, United States of America","active":true,"usgs":false}],"preferred":false,"id":862228,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":219852,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":862229,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ottinger, Mary Ann","contributorId":26422,"corporation":false,"usgs":false,"family":"Ottinger","given":"Mary","email":"","middleInitial":"Ann","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":862296,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Reeves, David B.","contributorId":181809,"corporation":false,"usgs":false,"family":"Reeves","given":"David","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":862230,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Seymour, Michael A.","contributorId":38886,"corporation":false,"usgs":false,"family":"Seymour","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":862231,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Sharuga, Stephanie M.","contributorId":301148,"corporation":false,"usgs":false,"family":"Sharuga","given":"Stephanie","email":"","middleInitial":"M.","affiliations":[{"id":65319,"text":"Genwest Systems","active":true,"usgs":false}],"preferred":false,"id":862232,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Tirpak, John M.","contributorId":197496,"corporation":false,"usgs":false,"family":"Tirpak","given":"John M.","affiliations":[],"preferred":false,"id":862233,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Vermillion, William G.","contributorId":301149,"corporation":false,"usgs":false,"family":"Vermillion","given":"William","email":"","middleInitial":"G.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":862234,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Zenzal, Theodore J. Jr. 0000-0001-7342-1373","orcid":"https://orcid.org/0000-0001-7342-1373","contributorId":224399,"corporation":false,"usgs":true,"family":"Zenzal","given":"Theodore","suffix":"Jr.","email":"","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":862235,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Lyons, James E.","contributorId":301146,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":862220,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Woodrey, Mark S.","contributorId":259212,"corporation":false,"usgs":false,"family":"Woodrey","given":"Mark","email":"","middleInitial":"S.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":862236,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70239823,"text":"70239823 - 2023 - Beyond presence mapping: Predicting fractional cover of non-native vegetation in Sentinel-2 imagery using an ensemble of MaxEnt models","interactions":[],"lastModifiedDate":"2023-09-06T16:04:00.742929","indexId":"70239823","displayToPublicDate":"2023-01-17T09:12:01","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5347,"text":"Remote Sensing in Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Beyond presence mapping: Predicting fractional cover of non-native vegetation in Sentinel-2 imagery using an ensemble of MaxEnt models","docAbstract":"

Non-native species maps are important tools for understanding and managing biological invasions. We demonstrate a novel approach to extend presence modeling to map fractional cover (FC) of non-native yellow sweet clover Melilotus officinalis in the Northern Great Plains, USA. We used ensembles of MaxEnt models to map FC across landscapes from satellite imagery trained from regional aerial imagery that was trained by local unmanned aerial vehicle (UAV) imagery. Clover cover from field surveys and classified UAV imagery were nearly identical (n = 22, R2 = 0.99). Two classified UAV images provided training data to map clover presence with MaxEnt and National Agricultural Imagery Program (NAIP) aerial imagery. We binned cover predictions from NAIP imagery within each Sentinel-2 pixel into eight cover classes to create pure (100%) and FC (20%–95%) training data and modeled each class separately using MaxEnt and Sentinel-2 imagery. We mapped pure clover with one classification threshold and compared its performance to 15 candidate maps that included FC predictions outside pure predictions. Each FC map represented alternative combinations of five MaxEnt thresholds and three approaches to assign cover to pixels with multiple predictions from the FC ensemble. Evaluations of performance with independent datasets revealed maps including FC corresponded to field (n = 32, R2 range: 0.39–0.68) and UAV (n = 20, R2 range: 0.61–0.84) data better than pure clover maps (R2 = 0.15 and 0.31, respectively). Overall, the pure clover map predicted 3.2% cover, whereas the three best performing FC maps predicted 6.6%–8.0% cover. Including FC predictions increased accuracy and cover predictions which can improve ecological understanding of invasions. Our method allows efficient FC mapping for vegetative species discernible in UAV imagery and may be especially useful for mapping rare, irruptive or patchily distributed species with poor representation in field data, which challenges landscape-level mapping.

","language":"English","publisher":"Wiley","doi":"10.1002/rse2.325","usgsCitation":"Preston, T.M., Johnston, A.N., Ebenhoch, K.G., and Diehl, R.H., 2023, Beyond presence mapping: Predicting fractional cover of non-native vegetation in Sentinel-2 imagery using an ensemble of MaxEnt models: Remote Sensing in Ecology and Conservation, v. 9, no. 4, p. 512-526, https://doi.org/10.1002/rse2.325.","productDescription":"15 p.","startPage":"512","endPage":"526","ipdsId":"IP-135782","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":444792,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rse2.325","text":"Publisher Index Page"},{"id":435499,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91X4EPQ","text":"USGS data release","linkHelpText":"Fractional cover estimates of sweet clover derived from UAV, aerial, and Sentinel-2 imagery for central Montana and northwest South Dakota, 2019"},{"id":412216,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, South Dakota","county":"Butte County, Harding County, Musselshell 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Todd M. 0000-0002-8812-9233","orcid":"https://orcid.org/0000-0002-8812-9233","contributorId":204676,"corporation":false,"usgs":true,"family":"Preston","given":"Todd","email":"","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":862047,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnston, Aaron N. 0000-0003-4659-0504","orcid":"https://orcid.org/0000-0003-4659-0504","contributorId":201768,"corporation":false,"usgs":true,"family":"Johnston","given":"Aaron","email":"","middleInitial":"N.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":862048,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ebenhoch, Kyle Gregory 0000-0001-7046-5557","orcid":"https://orcid.org/0000-0001-7046-5557","contributorId":299946,"corporation":false,"usgs":true,"family":"Ebenhoch","given":"Kyle","email":"","middleInitial":"Gregory","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":862049,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Diehl, Robert H. 0000-0001-9141-1734 rhdiehl@usgs.gov","orcid":"https://orcid.org/0000-0001-9141-1734","contributorId":3396,"corporation":false,"usgs":true,"family":"Diehl","given":"Robert","email":"rhdiehl@usgs.gov","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":862050,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70240165,"text":"70240165 - 2023 - Moving Aircraft River Velocimetry (MARV): Framework and proof-of-concept on the Tanana River","interactions":[],"lastModifiedDate":"2023-01-31T13:13:29.009178","indexId":"70240165","displayToPublicDate":"2023-01-17T07:11:28","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Moving Aircraft River Velocimetry (MARV): Framework and proof-of-concept on the Tanana River","docAbstract":"

Information on velocity fields in rivers is critical for designing infrastructure, modeling contaminant transport, and assessing habitat. Although non-contact approaches to measuring flow velocity are well established, these methods assume a stationary imaging platform. This study eliminates this constraint by introducing a framework for moving aircraft river velocimetry (MARV). The workflow takes as input images acquired from an airplane and involves orthorectification, frame overlap analysis, image enhancement, particle image velocimetry (PIV), and aggregation of the resulting velocity vectors onto a prediction grid. We also use new metrics to quantify the agreement between image-derived and field-measured velocity vectors in terms of both orientation and magnitude. The potential of MARV was evaluated using data from two Alaskan rivers: a large, highly turbid channel and its smaller, clearer tributary. Sediment boil vortices on the mainstem provided natural features trackable via PIV and estimated velocities corresponded closely with field measurements (R2 up to 0.911). We compared an exhaustive approach that evaluates overlap for all frame combinations to a simpler rolling window implementation and found that the more efficient algorithm did not compromise accuracy. Sensitivity analysis suggested that the method was robust to window parameterization. Comparing PIV output from different flying heights and imaging systems indicated that larger pixels led to higher accuracy and that a more advanced dual-camera system provided superior performance. Results from the tributary were less encouraging, presumably due to a lack of trackable features in visible images. Testing across a range of rivers is needed to assess the generality of MARV.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022WR033822","usgsCitation":"Legleiter, C.J., Kinzel, P.J., Laker, M., and Conaway, J., 2023, Moving Aircraft River Velocimetry (MARV): Framework and proof-of-concept on the Tanana River: Water Resources Research, v. 59, no. 2, e2022WR033822, 29 p., https://doi.org/10.1029/2022WR033822.","productDescription":"e2022WR033822, 29 p.","ipdsId":"IP-145891","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":488772,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022wr033822","text":"Publisher Index Page"},{"id":435500,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P968OENT","text":"USGS data release","linkHelpText":"Digital orthophotos and field measurements of flow velocity from the Tanana and Nenana Rivers, Alaska, from August 2021 (ver. 2.0, June 2024)"},{"id":412495,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-01-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":862816,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862817,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Laker, Mark","contributorId":298315,"corporation":false,"usgs":false,"family":"Laker","given":"Mark","email":"","affiliations":[{"id":64530,"text":"U.S. Fish and Wildlife Service, Kenai National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":862818,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conaway, Jeff 0000-0002-3036-592X","orcid":"https://orcid.org/0000-0002-3036-592X","contributorId":214226,"corporation":false,"usgs":true,"family":"Conaway","given":"Jeff","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":862819,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70241042,"text":"70241042 - 2023 - The San Francisco Estuary, USA as a reference section for an Anthropocene series","interactions":[],"lastModifiedDate":"2023-05-12T14:55:36.358251","indexId":"70241042","displayToPublicDate":"2023-01-17T06:57:16","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13447,"text":"The Anthropocene Review","active":true,"publicationSubtype":{"id":10}},"title":"The San Francisco Estuary, USA as a reference section for an Anthropocene series","docAbstract":"
A San Francisco Estuary core was analysed at high resolution to assess its component stratigraphic signatures of the Anthropocene in the form of non-native species, Hg, spheroidal carbonaceous particles, δ13Corg, δ15N, radiogenic materials, and heavy metals. Time series analysis of the core using Ti data provides a chronology to depth 167 cm into the 1960s. Below this, to depth 230 cm, the lowermost part of the core may extend to the 1950s or potentially a little earlier. The earliest anthropogenic marker recorded in the core is the excursion in Hg (beginning at 190 cm) which may denote the early 1960s and is the closest stratigraphic marker in the core to the proposed mid-20th century timing for the onset of the Anthropocene. Biostratigraphical signatures of non-native species arriving in the 1970s–1980s are widespread key markers and are significant tools for the correlation of Anthropocene deposits across the estuary. The absence of signals that indicate pre-1950s deposits precludes the use of the core to mark the Holocene–Anthropocene boundary. However, the core provides an important reference section to demonstrate the palaeontological distinctiveness of Anthropocene series deposits.
","language":"English","publisher":"Sage Publications","doi":"10.1177/20530196221147607","usgsCitation":"Himson, S.J., Williams, M., Zalasiewicz, J., Waters, C.N., McGann, M., England, R., Jaffe, B.E., Boom, A., Holmes, R., Sampson, S., Pye, C., Berrio, J.C., Tyrrell, G., Wilkinson, I.P., Rose, N., Gaca, P., and Cundy, A., 2023, The San Francisco Estuary, USA as a reference section for an Anthropocene series: The Anthropocene Review, v. 10, no. 1, p. 87-115, https://doi.org/10.1177/20530196221147607.","productDescription":"29 p.","startPage":"87","endPage":"115","ipdsId":"IP-143287","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":444795,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/20530196221147607","text":"Publisher Index 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Andrew","contributorId":302914,"corporation":false,"usgs":false,"family":"Cundy","given":"Andrew","affiliations":[{"id":65579,"text":"Ocean and Earth Science, National Oceanography Centre Southampton, UK","active":true,"usgs":false}],"preferred":false,"id":865821,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70248758,"text":"70248758 - 2023 - A multimodal data fusion and deep learning framework for large-scale wildfire surface fuel mapping","interactions":[],"lastModifiedDate":"2023-09-20T11:50:04.288946","indexId":"70248758","displayToPublicDate":"2023-01-17T06:44:20","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5678,"text":"Fire","active":true,"publicationSubtype":{"id":10}},"title":"A multimodal data fusion and deep learning framework for large-scale wildfire surface fuel mapping","docAbstract":"
Accurate estimation of fuels is essential for wildland fire simulations as well as decision-making related to land management. Numerous research efforts have leveraged remote sensing and machine learning for classifying land cover and mapping forest vegetation species. In most cases that focused on surface fuel mapping, the spatial scale of interest was smaller than a few hundred square kilometers; thus, many small-scale site-specific models had to be created to cover the landscape at the national scale. The present work aims to develop a large-scale surface fuel identification model using a custom deep learning framework that can ingest multimodal data. Specifically, we use deep learning to extract information from multispectral signatures, high-resolution imagery, and biophysical climate and terrain data in a way that facilitates their end-to-end training on labeled data. A multi-layer neural network is used with spectral and biophysical data, and a convolutional neural network backbone is used to extract the visual features from high-resolution imagery. A Monte Carlo dropout mechanism was also devised to create a stochastic ensemble of models that can capture classification uncertainties while boosting the prediction performance. To train the system as a proof-of-concept, fuel pseudo-labels were created by a random geospatial sampling of existing fuel maps across California. Application results on independent test sets showed promising fuel identification performance with an overall accuracy ranging from 55% to 75%, depending on the level of granularity of the included fuel types. As expected, including the rare—and possibly less consequential—fuel types reduced the accuracy. On the other hand, the addition of high-resolution imagery improved classification performance at all levels.
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0000-0003-1992-6033","orcid":"https://orcid.org/0000-0003-1992-6033","contributorId":329857,"corporation":false,"usgs":false,"family":"Ebrahimian","given":"Hamed","email":"","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":883474,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Taciroglu, Erugrul 0000-0001-9618-1210","orcid":"https://orcid.org/0000-0001-9618-1210","contributorId":329858,"corporation":false,"usgs":false,"family":"Taciroglu","given":"Erugrul","email":"","affiliations":[{"id":33607,"text":"University of California Los Angeles","active":true,"usgs":false}],"preferred":false,"id":883475,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70240732,"text":"70240732 - 2023 - High resolution SnowModel simulations reveal future elevation-dependent snow loss and earlier, flashier surface water input for the Upper Colorado River Basin","interactions":[],"lastModifiedDate":"2023-02-17T12:48:22.792443","indexId":"70240732","displayToPublicDate":"2023-01-17T06:40:31","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5053,"text":"Earth's Future","active":true,"publicationSubtype":{"id":10}},"title":"High resolution SnowModel simulations reveal future elevation-dependent snow loss and earlier, flashier surface water input for the Upper Colorado River Basin","docAbstract":"

Continued climate warming is reducing seasonal snowpacks in the western United States, where >50% of historical water supplies were snowmelt-derived. In the Upper Colorado River Basin, declining snow water equivalent (SWE) and altered surface water input (SWI, rainfall and snowmelt available to enter the soil) timing and magnitude affect streamflow generation and water availability. To adapt effectively to future conditions, we need to understand current spatiotemporal distributions of SWE and SWI and how they may change in future decades. We developed 100-m SnowModel simulations for water years 2001–2013 and two scenarios: control (CTL) and pseudo-global-warming (PGW). The PGW fraction of precipitation falling as snow was lower relative to CTL, except for November–April at high elevations. PGW peak SWE was lower for low (−45%) and mid elevations (−14%), while the date of peak SWE was uniformly earlier in the year for all elevations (17–23 days). Currently unmonitored high elevation snow represented a greater fraction of total PGW SWE. PGW peak daily SWI was higher for all elevations (30%–42%), while the dates of SWI peaks and centroids were earlier in the year for all elevations under PGW. PGW displayed elevated winter SWI, lower summer SWI, and changes in spring SWI timing were elevation-dependent. Although PGW peak SWI was elevated and earlier compared to CTL, SWI was more evenly distributed throughout the year for PGW. These simulated shifts in the timing and magnitude of SWE and SWI have broad implications for water management in dry, snow-dominated regions.

","language":"English","publisher":"Wiley","doi":"10.1029/2022EF003092","usgsCitation":"Hammond, J., Sexstone, G., Putman, A.L., Barnhart, T., Rey, D., Driscoll, J.M., Liston, G., Rasmussen, K.L., McGrath, D., Fassnacht, S.R., and Kampf, S.K., 2023, High resolution SnowModel simulations reveal future elevation-dependent snow loss and earlier, flashier surface water input for the Upper Colorado River Basin: Earth's Future, v. 11, no. 2, e2022EF003092, 23 p., https://doi.org/10.1029/2022EF003092.","productDescription":"e2022EF003092, 23 p.","ipdsId":"IP-134961","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":444801,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022ef003092","text":"Publisher Index Page"},{"id":413164,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.09822592354452,\n 40.405754404337216\n ],\n [\n -109.09822592354452,\n 37.57258792388836\n ],\n [\n -104.96912907559856,\n 37.57258792388836\n ],\n [\n -104.96912907559856,\n 40.405754404337216\n ],\n [\n -109.09822592354452,\n 40.405754404337216\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-01-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864569,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sexstone, Graham A. 0000-0001-8913-0546","orcid":"https://orcid.org/0000-0001-8913-0546","contributorId":203850,"corporation":false,"usgs":true,"family":"Sexstone","given":"Graham A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864570,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Putman, Annie L. 0000-0002-9424-1707","orcid":"https://orcid.org/0000-0002-9424-1707","contributorId":225134,"corporation":false,"usgs":true,"family":"Putman","given":"Annie","email":"","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864571,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnhart, Theodore B. 0000-0002-9682-3217","orcid":"https://orcid.org/0000-0002-9682-3217","contributorId":202558,"corporation":false,"usgs":true,"family":"Barnhart","given":"Theodore B.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864572,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rey, David M. 0000-0003-2629-365X","orcid":"https://orcid.org/0000-0003-2629-365X","contributorId":211848,"corporation":false,"usgs":true,"family":"Rey","given":"David M.","affiliations":[{"id":37277,"text":"WMA - 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2023 - Green turtle movements in the Gulf of Mexico: Tracking reveals new migration corridor and habitat use suggestive of MPA expansion","interactions":[],"lastModifiedDate":"2023-03-28T15:07:15.603791","indexId":"70239932","displayToPublicDate":"2023-01-17T06:36:19","publicationYear":"2023","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":"Green turtle movements in the Gulf of Mexico: Tracking reveals new migration corridor and habitat use suggestive of MPA expansion","docAbstract":"

Globally, Marine Protected Areas are an important tool in the conservation of large marine vertebrates. Recent studies have highlighted the use of protected areas by imperiled green turtles (Chelonia mydas) in the southern Gulf of Mexico. To identify and characterize inter-nesting, migratory, and foraging areas for green turtles that nest in the northern Gulf of Mexico, we deployed 14 satellite tags on 13 individual green turtles after nesting in Northwest Florida. We used switching state-space modeling to highlight turtle use in the Florida Keys National Marine Sanctuary and in habitat outside of protected areas such as near Cape Sable, Florida and off the Yucatán Peninsula, Mexico. Turtles were tracked for 21–217 days and migrated for a mean of 22 days. Five individuals used stopover sites during migration; these sites were in areas of dense seagrass habitat, often within boundaries of existing Aquatic Preserves. Turtles established mean foraging home ranges of 118.0 km2 (50% kernel density estimate) with foraging centroids that were 0.33–7.3 km apart. The area off Cape Sable, Florida, which lies outside of currently protected area boundaries, appears to be a hotspot for green turtles that nest throughout the Gulf of Mexico. While protected areas in the Gulf of Mexico are used by this subset of nesting green turtles, several key sites remain unprotected. These findings are relevant when considering expansion of currently protected areas and in defining critical habitat for this species.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2023.e02380","usgsCitation":"Lamont, M., Benscoter, A., and Hart, K., 2023, Green turtle movements in the Gulf of Mexico: Tracking reveals new migration corridor and habitat use suggestive of MPA expansion: Global Ecology and Conservation, v. 42, e02380, 11 p.; Data Release, https://doi.org/10.1016/j.gecco.2023.e02380.","productDescription":"e02380, 11 p.; Data Release","ipdsId":"IP-140257","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":444803,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2023.e02380","text":"Publisher Index Page"},{"id":412351,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":414821,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V4TIUB","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.0345726788432,\n 30.719126261397776\n ],\n [\n -87.0345726788432,\n 23.243613583999505\n ],\n [\n -80.23880542030703,\n 23.243613583999505\n ],\n [\n -80.23880542030703,\n 30.719126261397776\n ],\n [\n -87.0345726788432,\n 30.719126261397776\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"42","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lamont, Margaret 0000-0001-7520-6669","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":222403,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":862427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Benscoter, Allison 0000-0003-4205-3808","orcid":"https://orcid.org/0000-0003-4205-3808","contributorId":216194,"corporation":false,"usgs":true,"family":"Benscoter","given":"Allison","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":862428,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":218455,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":862429,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70239912,"text":"70239912 - 2023 - Juxtaposition of intensive agriculture, vulnerable aquifers, and mixed chemical/microbial exposures in private-well tapwater in northeast Iowa","interactions":[],"lastModifiedDate":"2023-01-25T12:39:26.054546","indexId":"70239912","displayToPublicDate":"2023-01-17T06:35:44","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13280,"text":"Environmental Science and Technology: Water","active":true,"publicationSubtype":{"id":10}},"title":"Juxtaposition of intensive agriculture, vulnerable aquifers, and mixed chemical/microbial exposures in private-well tapwater in northeast Iowa","docAbstract":"

In the United States and globally, contaminant exposure in unregulated private-well point-of-use tapwater (TW) is a recognized public-health data gap and an obstacle to both risk-management and homeowner decision making. To help address the lack of data on broad contaminant exposures in private-well TW from hydrologically-vulnerable (alluvial, karst) aquifers in agriculturally-intensive landscapes, samples were collected in 2018–2019 from 47 northeast Iowa farms and analyzed for 35 inorganics, 437 unique organics, 5 in vitro bioassays, and 11 microbial assays. Twenty-six inorganics and 51 organics, dominated by pesticides and related transformation products (35 herbicide-, 5 insecticide-, and 2 fungicide-related), were observed in TW. Heterotrophic bacteria detections were near ubiquitous (94 % of the samples), with detection of total coliform bacteria in 28 % of the samples and growth on at least one putative-pathogen selective media across all TW samples. Health-based hazard index screening levels were exceeded frequently in private-well TW and attributed primarily to inorganics (nitrate, uranium). Results support incorporation of residential treatment systems to protect against contaminant exposure and the need for increased monitoring of rural private-well homes. Continued assessment of unmonitored and unregulated private-supply TW is needed to model contaminant exposures and human-health risks.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2023.161672","usgsCitation":"Bradley, P., Kolpin, D., Thompson, D.A., Romanok, K., Smalling, K., Breitmeyer, S.E., Cardon, M.C., Cwiertny, D.M., Evans, N., Field, R.W., Focazio, M.J., Freeman, L.E., Givens, C.E., Gray, J.L., Hager, G.L., Hladik, M.L., Hoffman, J.N., Jones, R.R., Kanagy, L.K., Lane, R.F., McCleskey, R., Medgyesi, D., Medlock-Kakaley, E., Meppelink, S., Meyer, M., Stavreva, D.A., and Ward, M.H., 2023, Juxtaposition of intensive agriculture, vulnerable aquifers, and mixed chemical/microbial exposures in private-well tapwater in northeast Iowa: Environmental Science and Technology: Water, v. 868, 161672, 11 p., https://doi.org/10.1016/j.scitotenv.2023.161672.","productDescription":"161672, 11 p.","ipdsId":"IP-134194","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":444805,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2023.161672","text":"Publisher Index Page"},{"id":435501,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IYT37H","text":"USGS data release","linkHelpText":"Target-Chemical Concentrations, Exposure Activity Ratios, and Bioassay Results for Assessment of Mixed-Organic/Inorganic Chemical Exposures in Northeast Iowa Private-Well Tapwater, 2018"},{"id":412305,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.12228849222048,\n 42.99050594750622\n ],\n [\n -93.12228849222048,\n 41.09871525515322\n ],\n [\n -89.9156424790619,\n 41.09871525515322\n ],\n [\n -89.9156424790619,\n 42.99050594750622\n ],\n [\n -93.12228849222048,\n 42.99050594750622\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"868","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bradley, Paul M. 0000-0001-7522-8606","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":221226,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul M.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862342,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":205652,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862343,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Darrin A.","contributorId":238107,"corporation":false,"usgs":false,"family":"Thompson","given":"Darrin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":862344,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Romanok, Kristin M. 0000-0002-8472-8765","orcid":"https://orcid.org/0000-0002-8472-8765","contributorId":221227,"corporation":false,"usgs":true,"family":"Romanok","given":"Kristin M.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862345,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862346,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Breitmeyer, Sara E. 0000-0003-0609-1559 sbreitmeyer@usgs.gov","orcid":"https://orcid.org/0000-0003-0609-1559","contributorId":172622,"corporation":false,"usgs":true,"family":"Breitmeyer","given":"Sara","email":"sbreitmeyer@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - 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Land-based sources of groundwater pollution can be a critical threat to coral reefs, and a better understanding of “ridge-to-reef” water movement is required to advance management and coral survival in the Anthropocene. In this study a more complete understanding of the geological, atmospheric, and oceanic drivers behind coastal groundwater exchange on the Kalaupapa peninsula, on Moloka‘i, Hawai‘i, is obtained by analyzing high resolution geochemical and geophysical time-series data. In concert with multiyear water level analyses, a tidally and precipitation-driven groundwater connection between Kauhakō Crater lake and submarine groundwater discharge (SGD) fluxes are demonstrated. Results include an average discharge rate of 190 cm d−1 and the detection of water-flow pathways past cesspools that likely contribute to higher nutrient loading near the SGD sites. This underlines the importance of managing anthropogenic nutrients that enter the shallow freshwater lens such as through cesspools and are consequently discharged via SGD onto coral reef habitats.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2022.114509","usgsCitation":"Oberle, F.K., Cheriton, O.M., Swarzenski, P., Brown, E.K., and Storlazzi, C.D., 2023, Physicochemical coastal groundwater dynamics between Kauhakō Crater lake and Kalaupapa settlement, Moloka‘i, Hawai‘i: Marine Pollution Bulletin, v. 187, 114509, 12 p., https://doi.org/10.1016/j.marpolbul.2022.114509.","productDescription":"114509, 12 p.","ipdsId":"IP-146121","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":435502,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XQAMW8","text":"USGS data release","linkHelpText":"Physicochemical measurements of the coastal aquifer and coastal groundwater discharge on Kalaupapa, Moloka'i, Hawaii"},{"id":411967,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","city":"Kalaupapa","otherGeospatial":"Kauhakō Crater Lake, Kalaupapa Peninsula, Moloka'i","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -156.9876032907954,\n 21.20057697124608\n ],\n [\n -156.9876032907954,\n 21.184169607286606\n ],\n [\n -156.9619419645661,\n 21.184169607286606\n ],\n [\n -156.9619419645661,\n 21.20057697124608\n ],\n [\n -156.9876032907954,\n 21.20057697124608\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"187","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Oberle, Ferdinand K.J. 0000-0001-8871-3619","orcid":"https://orcid.org/0000-0001-8871-3619","contributorId":214402,"corporation":false,"usgs":true,"family":"Oberle","given":"Ferdinand","middleInitial":"K.J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":861701,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cheriton, Olivia M. 0000-0003-3011-9136","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":204459,"corporation":false,"usgs":true,"family":"Cheriton","given":"Olivia","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":861702,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swarzenski, Peter W 0000-0003-0116-0578","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":225227,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter W","affiliations":[],"preferred":true,"id":861703,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Eric K.","contributorId":41956,"corporation":false,"usgs":true,"family":"Brown","given":"Eric","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":861727,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":861728,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70239727,"text":"70239727 - 2023 - Subaqueous clinoforms created by sandy wave-supported gravity flows: Lessons from the central California shelf","interactions":[],"lastModifiedDate":"2023-01-16T19:30:15.171651","indexId":"70239727","displayToPublicDate":"2023-01-16T13:25:26","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Subaqueous clinoforms created by sandy wave-supported gravity flows: Lessons from the central California shelf","docAbstract":"Subaqueous clinoforms are an important yet underappreciated shelf feature. Their origins are typically associated with subaerial deltas but recent work has identified similar features in settings without a significant fluvial source. These other studies have shown that such subaqueous clinoforms, also known as infralittoral prograding wedges (IPWs), are created largely by wave-induced processes. This study uses geophysical, sedimentological, and radiocarbon data to determine the sedimentary characteristics and genesis of a shore-parallel subaqueous clinoform developed far from any significant river on the central California continental shelf; a feature known locally as the Cross Hosgri Slope. Sediment cores through the feature reveal that it is composed of beds with an erosive base, followed by a thin coarsening upward sequence of shelly fine sands transitioning to a fining upward sequence marked by alternating parallel and ripple cross laminated very fine sands. The deposit is often capped by fine silts that are commonly interbedded with thin very fine sand beds. Radiocarbon dating of shells within the cores paired with seismic profiles indicate the subaqueous clinoform initiated progradation ~7 ka, nucleating on an older Younger Dryas relict shoreface. We suggest the CHS was created by winter-storm waves mobilizing sands in water depths up to ~ 70 m that transitioned into wave-supported gravity flows. The wave-supported gravity flows traveled downslope to water depths of up to ~85 m, corresponding to the foot of the subaqueous clinoform. They did not travel beyond this depth as wave influence at these depths is negligible and the shelf slope is insufficient to maintain movement of the load alone. Our work suggests that wave-supported gravity flows can entrain very fine sands and silts and build subaqueous clinoforms, even in the absence of a significant river source. Furthermore, we provide a facies model for sandy wave-supported gravity flow deposits.","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2022.106977","usgsCitation":"Medri, E., Simms, A.R., Kluesner, J., Johnson, S., Nishenko, S., Greene, H.G., and Conrad, J.E., 2023, Subaqueous clinoforms created by sandy wave-supported gravity flows: Lessons from the central California shelf: Marine Geology, v. 456, 106977, 13 p., https://doi.org/10.1016/j.margeo.2022.106977.","productDescription":"106977, 13 p.","ipdsId":"IP-144443","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":444808,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://escholarship.org/uc/item/62t4p940","text":"Publisher Index Page"},{"id":411965,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Pacific Ocean","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.56611710043825,\n 36.61947594158909\n ],\n [\n -123.56611710043825,\n 34.32371030361945\n ],\n [\n -119.09307635415979,\n 34.32371030361945\n ],\n [\n -119.09307635415979,\n 36.61947594158909\n ],\n [\n -123.56611710043825,\n 36.61947594158909\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"456","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Medri, Elisa","contributorId":300974,"corporation":false,"usgs":false,"family":"Medri","given":"Elisa","email":"","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":861657,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simms, Alexander R.","contributorId":52887,"corporation":false,"usgs":true,"family":"Simms","given":"Alexander","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":861658,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kluesner, Jared W. 0000-0003-1701-8832","orcid":"https://orcid.org/0000-0003-1701-8832","contributorId":206367,"corporation":false,"usgs":true,"family":"Kluesner","given":"Jared W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":861659,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Samuel Y. 0000-0001-7972-9977","orcid":"https://orcid.org/0000-0001-7972-9977","contributorId":221270,"corporation":false,"usgs":true,"family":"Johnson","given":"Samuel Y.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":861660,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nishenko, Stuart P.","contributorId":82219,"corporation":false,"usgs":true,"family":"Nishenko","given":"Stuart P.","affiliations":[],"preferred":false,"id":861661,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Greene, H. Gary","contributorId":139063,"corporation":false,"usgs":false,"family":"Greene","given":"H.","email":"","middleInitial":"Gary","affiliations":[{"id":12639,"text":"Moss Landing Marine Labs","active":true,"usgs":false}],"preferred":false,"id":861662,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Conrad, James E. 0000-0001-6655-694X jconrad@usgs.gov","orcid":"https://orcid.org/0000-0001-6655-694X","contributorId":2316,"corporation":false,"usgs":true,"family":"Conrad","given":"James","email":"jconrad@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":861663,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70239723,"text":"70239723 - 2023 - Hydrodynamics and habitat interact to structure fish communities within terminal channels of a tidal freshwater delta","interactions":[],"lastModifiedDate":"2023-01-16T18:55:39.202204","indexId":"70239723","displayToPublicDate":"2023-01-16T12:45:04","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Hydrodynamics and habitat interact to structure fish communities within terminal channels of a tidal freshwater delta","docAbstract":"Terminal channels were historically a common feature of tidal delta ecosystems but have become increasingly rare as landscapes have been modified. Tidal hydrodynamics are a defining feature in tidal terminal channel ecosystems from which native aquatic communities have evolved. However, few studies have explored the relationship between fish community structure and hydrodynamics in these tidal terminal channel ecosystems. We sampled fish communities throughout a network of terminal channels within the northeasternmost region of the San Francisco Estuary to determine the relationship between fish community structure and hydrodynamics within these environments. We collected two years (2017 and 2018) of fish community samples using gill nets and analyzed data using multivariate community analyses and count models. We found metrics of fish diversity and counts of native fishes to be greatest upstream (farthest from tidal influence) of the tidal excursion within terminal channels. Counts of non-native fishes were less affected by this hydrodynamic feature of terminal channels and more tightly correlated to local habitat conditions (e.g., water temperature, depth). Our results suggest that channel hydrodynamics plays a role in structuring fish communities within terminal channels, particularly native fishes. These results indicate that hydrodynamics in tidal delta ecosystems may be able to be altered in ways that benefit native fishes without the cost of water pumping.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4339","usgsCitation":"Huntsman, B., Young, M.J., Feyrer, F.V., Stumpner, P., Brown, L.R., and Burau, J.R., 2023, Hydrodynamics and habitat interact to structure fish communities within terminal channels of a tidal freshwater delta: Ecosphere, v. 14, no. 1, e4339, 18 p., https://doi.org/10.1002/ecs2.4339.","productDescription":"e4339, 18 p.","ipdsId":"IP-139147","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":444812,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4339","text":"Publisher Index Page"},{"id":411962,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Cache Slough Complex, San Francisco Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.69932887248329,\n 38.24856975517184\n ],\n [\n -121.67220637492461,\n 38.24776088323978\n ],\n [\n -121.71752497844034,\n 38.3229474560282\n ],\n [\n -121.80987879924118,\n 38.31217280176293\n ],\n [\n -121.77760646037407,\n 38.28495967449561\n ],\n [\n -121.72713801554991,\n 38.28064774752275\n ],\n [\n -121.69932887248329,\n 38.24856975517184\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Huntsman, Brock 0000-0003-4090-1949","orcid":"https://orcid.org/0000-0003-4090-1949","contributorId":223101,"corporation":false,"usgs":true,"family":"Huntsman","given":"Brock","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Matthew J. 0000-0001-9306-6866 mjyoung@usgs.gov","orcid":"https://orcid.org/0000-0001-9306-6866","contributorId":206255,"corporation":false,"usgs":true,"family":"Young","given":"Matthew","email":"mjyoung@usgs.gov","middleInitial":"J.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feyrer, Frederick V. 0000-0003-1253-2349 ffeyrer@usgs.gov","orcid":"https://orcid.org/0000-0003-1253-2349","contributorId":178379,"corporation":false,"usgs":true,"family":"Feyrer","given":"Frederick","email":"ffeyrer@usgs.gov","middleInitial":"V.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861637,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stumpner, Paul 0000-0002-0933-7895 pstump@usgs.gov","orcid":"https://orcid.org/0000-0002-0933-7895","contributorId":5667,"corporation":false,"usgs":true,"family":"Stumpner","given":"Paul","email":"pstump@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861638,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Larry R. 0000-0001-6702-4531","orcid":"https://orcid.org/0000-0001-6702-4531","contributorId":269405,"corporation":false,"usgs":false,"family":"Brown","given":"Larry","email":"","middleInitial":"R.","affiliations":[{"id":55970,"text":"USGS CAWSC (not in system - posthumous)","active":true,"usgs":false}],"preferred":false,"id":861639,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Burau, Jon R. 0000-0002-5196-5035 jrburau@usgs.gov","orcid":"https://orcid.org/0000-0002-5196-5035","contributorId":1500,"corporation":false,"usgs":true,"family":"Burau","given":"Jon","email":"jrburau@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861640,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70239726,"text":"70239726 - 2023 - Enhancements to population monitoring of Yellowstone grizzly bears","interactions":[],"lastModifiedDate":"2023-01-16T18:08:30.013759","indexId":"70239726","displayToPublicDate":"2023-01-16T12:00:14","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3671,"text":"Ursus","active":true,"publicationSubtype":{"id":10}},"title":"Enhancements to population monitoring of Yellowstone grizzly bears","docAbstract":"

In the Greater Yellowstone Ecosystem, counts of female grizzly bears (Ursus arctos) with cubs-of-the-year (females with cubs) from systematic aerial surveys and opportunistic ground sightings are combined with demographic data to derive annual population estimates. We addressed 2 limitations to the monitoring approach. As part of a rule set, a conservative distance of >30 km currently is used as a threshold to assign sightings to unique females with cubs, resulting in underestimation bias. Using telemetry locations of females with cubs collected during 1997–2019, we created 1,000 data sets for each of 5 levels of simulated number of females with cubs, simulated sightings by selecting among these locations, and evaluated the classification performance of alternative distance criteria (12–30 km). Under all scenarios, 12–16-km criteria maximized classification performance and minimized estimation bias; the 16-km criterion was optimal for current conditions and sampling efforts. Our second objective was to test generalized additive models (GAMs) as a flexible trend analysis technique. We simulated 1,000 time series for each of 10 scenarios (10, 15, and 20% decline over periods of 5, 10, and 15 yrs, plus stability), applied GAMs, and assessed metrics associated with the posterior distribution of the instantaneous rate of change. We detected declines among >99.6% of replicates under the 15 and 20% decline scenarios and in 84.7–94.7% of replicates under the 10% decline scenario. From decline onset to first detection, periods ranged from 3.7 (20% decline over 5 yrs) to 11.1 (10% decline over 15 yrs), with 3.9–8.8 years mean duration of detection events. The GAM approach allows detection of directional changes in population trend, including early warning metrics, and stabilization after such changes. Retrospective application of the 16-km distance criterion and GAMs resulted in higher population estimates and growth rates than are reported using current methods.

","language":"English","publisher":"International Association for Bear Research and Management","doi":"10.2192/URSUS-D-22-00002.2","usgsCitation":"van Manen, F.T., Ebinger, M., Costello, C., Bjornlie, D., Clapp, J., Thompson, D., Haroldson, M.A., Frey, K.L., Hendricks, C., Nicholson, J., Gunther, K.A., Wilmot, K.R., Cooley, H., Fortin-Noreus, J., Hnilicka, P., and Tyers, D.B., 2023, Enhancements to population monitoring of Yellowstone grizzly bears: Ursus, v. 33, e17, 19 p., https://doi.org/10.2192/URSUS-D-22-00002.2.","productDescription":"e17, 19 p.","ipdsId":"IP-137270","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":444815,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2192/ursus-d-22-00002.2","text":"Publisher Index Page"},{"id":411958,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Box 168, Yellowstone National Park, WY 82190","active":true,"usgs":false}],"preferred":false,"id":861651,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wilmot, Katharine R.","contributorId":244265,"corporation":false,"usgs":false,"family":"Wilmot","given":"Katharine","email":"","middleInitial":"R.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":861652,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Cooley, Hilary","contributorId":205414,"corporation":false,"usgs":false,"family":"Cooley","given":"Hilary","affiliations":[],"preferred":false,"id":861653,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Fortin-Noreus, Jennifer","contributorId":200746,"corporation":false,"usgs":false,"family":"Fortin-Noreus","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":861654,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Hnilicka, Pat","contributorId":289731,"corporation":false,"usgs":false,"family":"Hnilicka","given":"Pat","affiliations":[],"preferred":false,"id":861655,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Tyers, Daniel B.","contributorId":124587,"corporation":false,"usgs":false,"family":"Tyers","given":"Daniel","email":"","middleInitial":"B.","affiliations":[{"id":5129,"text":"U.S. Forest Service, 2327 University Way, Bozeman, MT 59715, USA","active":true,"usgs":false}],"preferred":false,"id":861656,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70239942,"text":"70239942 - 2023 - Genetic diversity goals and targets have improved, but remain insufficient for clear implementation of the post-2020 global biodiversity framework","interactions":[],"lastModifiedDate":"2025-02-07T16:12:42.07767","indexId":"70239942","displayToPublicDate":"2023-01-16T07:21:09","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Genetic diversity goals and targets have improved, but remain insufficient for clear implementation of the post-2020 global biodiversity framework","docAbstract":"

Genetic diversity among and within populations of all species is necessary for people and nature to survive and thrive in a changing world. Over the past three years, commitments for conserving genetic diversity have become more ambitious and specific under the Convention on Biological Diversity’s (CBD) draft post-2020 global biodiversity framework (GBF). This Perspective article comments on how goals and targets of the GBF have evolved, the improvements that are still needed, lessons learned from this process, and connections between goals and targets and the actions and reporting that will be needed to maintain, protect, manage and monitor genetic diversity. It is possible and necessary that the GBF strives to maintain genetic diversity within and among populations of all species, to restore genetic connectivity, and to develop national genetic conservation strategies, and to report on these using proposed, feasible indicators.

","language":"English","publisher":"Springer Nature","doi":"10.1007/s10592-022-01492-0","usgsCitation":"Hoban, S.M., Bruford, M.W., da Silva, J.M., Funk, W., Frankham, R., Gill, M.J., Grueber, C.E., Heuertz, M., Hunter, M., Kershaw, F., Lacy, R.C., Lees, C., Lopes-Fernandes, M., MacDonald, A.J., Mastretta-Yanes, A., McGowan, P., Meek, M.H., Mergeay, J., Millette, K.L., Mittan-Moreau, C.S., Navarro, L.M., O'Brien, D., Ogden, R., Segelbacher, G., Paz-Vinas, I., Vernesi, C., and Laikre, L., 2023, Genetic diversity goals and targets have improved, but remain insufficient for clear implementation of the post-2020 global biodiversity framework: Conservation Genetics, v. 24, p. 181-191, https://doi.org/10.1007/s10592-022-01492-0.","productDescription":"11 p.","startPage":"181","endPage":"191","ipdsId":"IP-146840","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":444818,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10592-022-01492-0","text":"Publisher Index Page"},{"id":412362,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","noUsgsAuthors":false,"publicationDate":"2023-01-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Hoban, Sean M. 0000-0002-0348-8449","orcid":"https://orcid.org/0000-0002-0348-8449","contributorId":206582,"corporation":false,"usgs":false,"family":"Hoban","given":"Sean","email":"","middleInitial":"M.","affiliations":[{"id":37343,"text":"The Morton Arboretum","active":true,"usgs":false}],"preferred":false,"id":862450,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bruford, Michael W.","contributorId":190769,"corporation":false,"usgs":false,"family":"Bruford","given":"Michael","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":862451,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"da Silva, Jessica M.","contributorId":290139,"corporation":false,"usgs":false,"family":"da Silva","given":"Jessica","email":"","middleInitial":"M.","affiliations":[{"id":62352,"text":"South African National Biodiversity Institute, Kirstenbosch Research Centre, Rhodes Drive, Private Bag X7, 7735 Cape Town, South Africa","active":true,"usgs":false}],"preferred":false,"id":862452,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Funk, W. 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