Populations of the green turtle (Chelonia mydas), a mega-herbivore that consumes seagrasses, are recovering worldwide. Understanding green turtle adaptations to herbivory and responses to changes in seagrass availability will be critical to interpreting plant–herbivore interactions as green turtle populations continue to rebound. Ingesta particle size and diet composition of two green turtle foraging aggregations (Bermuda, 32.3° N, 64.8° W; U.S. Virgin Islands [USVI], 17.8° N, 64.6° W) in the Northwest Atlantic (NWA) were evaluated to assess the prevalence of herbivory across foraging sites and life stages, determine if there is an optimum ingesta particle size, and evaluate green turtle responses to changes in seagrass availability. Both aggregations were herbivorous (> 90% seagrass/algae) across size classes (straight carapace length, SCL). Ingesta particle size (mean ± SD) did not differ between Bermuda (2.6 ± 1.4 cm) and the USVI (2.3 ± 1.2 cm). Of seagrass leaves ingested, 20–30% were 1.7 cm in length, indicating a potential optimum for maximizing digestion rates. Turtle size (SCL) had a significant effect on particle size in Bermuda (p = 0.01, R2 = 0.16) (35.1 ± 9.9 cm SCL) but not in the USVI aggregation, which was comprised of larger turtles (49.0 ± 6.1 cm SCL). In Bermuda, there was no apparent response to the declines in seagrass availability. Ingesta particle size and volume of seagrass leaves did not decline from 2015 to 2019, nor was there an increase in volume of seagrass roots and rhizomes. These results indicate herbivory is prevalent across size classes at two NWA foraging sites and ingesta particle size has important implications for optimizing the green turtle grazing strategy and facilitating ontogenetic diet shifts to herbivory in juveniles. Ingesta particle size is a valuable tool for assessing green turtle responses to seagrass declines that should be interpreted within the context of population demographics.
Lakes and other surface fresh waterbodies provide drinking water, recreational and economic opportunities, food, and other critical support for humans, aquatic life, and ecosystem health. Lakes are also productive ecosystems that provide habitats and influence global cycles. Chlorophyll concentration provides a common metric of water quality, and is frequently used as a proxy for lake trophic state. Here, we document the generation and distribution of the complete MEdium Resolution Imaging Spectrometer (MERIS; Appendix A provides a complete list of abbreviations) radiometric time series for over 2300 satellite resolvable inland bodies of water across the contiguous United States (CONUS) and more than 5,000 in Alaska. This contribution greatly increases the ease of use of satellite remote sensing data for inland water quality monitoring, as well as highlights new horizons in inland water remote sensing algorithm development. We evaluate the performance of satellite remote sensing Cyanobacteria Index (CI)-based chlorophyll algorithms, the retrievals for which provide surrogate estimates of phytoplankton concentrations in cyanobacteria dominated lakes. Our analysis quantifies the algorithms' abilities to assess lake trophic state across the CONUS. As a case study, we apply a bootstrapping approach to derive a new CI-to-chlorophyll relationship, ChlBS, which performs relatively well with a multiplicative bias of 1.11 (11%) and mean absolute error of 1.60 (60%). While the primary contribution of this work is the distribution of the MERIS radiometric timeseries, we provide this case study as a roadmap for future stakeholders' algorithm development activities, as well as a tool to assess the strengths and weaknesses of applying a single algorithm across CONUS.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2021.112685","usgsCitation":"Seegers, B., Werdell, P., Vandermeulen, R., Salls, W., Stumpf, R., Schaeffer, B., Owens, T., Bailey, S., Scott, J., and Loftin, K.A., 2021, Satellites for long-term monitoring of inland U.S. lakes: The MERIS time series and application for chlorophyll-a: Remote Sensing of the Environment, v. 266, 112685, 14 p., https://doi.org/10.1016/j.rse.2021.112685.","productDescription":"112685, 14 p.","ipdsId":"IP-129074","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":450699,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2021.112685","text":"Publisher Index Page"},{"id":392623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska, Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.42675781249999,\n 43.229195113965005\n ],\n [\n -89.2529296875,\n 43.229195113965005\n ],\n [\n -89.2529296875,\n 49.15296965617042\n ],\n [\n -97.42675781249999,\n 49.15296965617042\n ],\n [\n -97.42675781249999,\n 43.229195113965005\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -130.078125,\n 53.74871079689897\n ],\n [\n -128.32031249999997,\n 55.677584411089526\n ],\n [\n -134.82421875,\n 60.75915950226991\n ],\n [\n -139.5703125,\n 61.438767493682825\n ],\n [\n -140.09765625,\n 69.71810669906763\n ],\n [\n -156.09375,\n 71.85622888185527\n ],\n [\n -166.2890625,\n 68.84766505841037\n ],\n [\n -167.6953125,\n 65.29346780107583\n ],\n [\n -166.2890625,\n 59.44507509904714\n ],\n [\n -161.89453125,\n 54.36775852406841\n ],\n [\n -153.80859375,\n 55.87531083569679\n ],\n [\n -145.01953124999997,\n 59.80063426102869\n ],\n [\n -134.47265625,\n 55.07836723201515\n ],\n [\n -132.36328125,\n 51.83577752045248\n ],\n [\n -131.1328125,\n 52.05249047600099\n ],\n [\n -130.078125,\n 53.74871079689897\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"266","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Seegers, Bridget","contributorId":269867,"corporation":false,"usgs":false,"family":"Seegers","given":"Bridget","affiliations":[{"id":37453,"text":"National Aeronautics and Space Administration","active":true,"usgs":false}],"preferred":false,"id":828030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Werdell, P. Jeremy","contributorId":269868,"corporation":false,"usgs":false,"family":"Werdell","given":"P. Jeremy","affiliations":[{"id":37453,"text":"National Aeronautics and Space Administration","active":true,"usgs":false}],"preferred":false,"id":828031,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vandermeulen, Ryan","contributorId":269869,"corporation":false,"usgs":false,"family":"Vandermeulen","given":"Ryan","email":"","affiliations":[{"id":37453,"text":"National Aeronautics and Space Administration","active":true,"usgs":false}],"preferred":false,"id":828032,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Salls, Wilson","contributorId":269870,"corporation":false,"usgs":false,"family":"Salls","given":"Wilson","affiliations":[{"id":35215,"text":"Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":828033,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stumpf, Richard","contributorId":269871,"corporation":false,"usgs":false,"family":"Stumpf","given":"Richard","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":828034,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schaeffer, Blake","contributorId":269872,"corporation":false,"usgs":false,"family":"Schaeffer","given":"Blake","affiliations":[{"id":35215,"text":"Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":828035,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Owens, Tommy","contributorId":269873,"corporation":false,"usgs":false,"family":"Owens","given":"Tommy","email":"","affiliations":[{"id":37453,"text":"National Aeronautics and Space Administration","active":true,"usgs":false}],"preferred":false,"id":828036,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bailey, Sean","contributorId":269874,"corporation":false,"usgs":false,"family":"Bailey","given":"Sean","affiliations":[{"id":37453,"text":"National Aeronautics and Space Administration","active":true,"usgs":false}],"preferred":false,"id":828037,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Scott, Joel","contributorId":269875,"corporation":false,"usgs":false,"family":"Scott","given":"Joel","email":"","affiliations":[{"id":37453,"text":"National Aeronautics and Space Administration","active":true,"usgs":false}],"preferred":false,"id":828038,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Loftin, Keith A. 0000-0001-5291-876X","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":221964,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":828039,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70224434,"text":"sir20215095 - 2021 - Discharge and dissolved-solids characteristics of Blacks Fork above Smiths Fork, Wyoming, April 2018 through September 2019","interactions":[],"lastModifiedDate":"2021-09-24T03:06:17.53203","indexId":"sir20215095","displayToPublicDate":"2021-09-23T22:04:41","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5095","displayTitle":"Discharge and Dissolved-Solids Characteristics of Blacks Fork above Smiths Fork, Wyoming, April 2018 through September 2019","title":"Discharge and dissolved-solids characteristics of Blacks Fork above Smiths Fork, Wyoming, April 2018 through September 2019","docAbstract":"The Colorado River Basin Salinity Control Forum was formed in 1973 to coordinate salinity control efforts among the States in the Colorado River Basin, including Wyoming. The Colorado River Salinity Control Act of 1974 (Public Law 93–320) authorized “the construction, operation, and maintenance of certain works in the Colorado River Basin to control the salinity of water delivered to users in the United States and Mexico.” Water-quality standards for salinity in the lower Colorado River Basin were adopted in 1975. To help meet these standards, the Bureau of Reclamation, Natural Resource Conservation Service, and States within the Colorado River Basin have implemented salinity control projects that focus on reducing salt loading associated with irrigated agriculture by improving water delivery systems and water management practices. The term salinity is synonymous with dissolved solids in this report.
The Bureau of Reclamation, in conjunction with the Colorado River Basin Salinity Control Forum, was interested in determining the contribution of dissolved solids from Blacks Fork above Smiths Fork to the Colorado River and initiated a study of Blacks Fork above Smiths Fork in 2018. In early 2018, the U.S. Geological Survey installed a streamgage at the most downstream location on the Blacks Fork, upstream from the convergence with Smiths Fork, to characterize the stream. The Blacks Fork above Smiths Fork, near Lyman, Wyoming, streamgage (U.S. Geological Survey identifier 09219200) was operated from April 4, 2018, through September 30, 2019, collecting continuous stream stage and specific-conductance data, from which continuous discharge, dissolved-solids concentrations, and dissolved-solids loads were calculated. Seven sites were selected on Blacks Fork and a tributary to describe a snapshot of the discharge and dissolved-solids characteristics. These sites were sampled during July, August, and September 2018 and June, July, August, and September 2019 report.
Discharge at the Blacks Fork above Smiths Fork, near Lyman, Wyo., streamgage (09219200) from April through September in 2018 was lower and less variable than during the same period in 2019. The mean daily (mean of the daily means) discharge during those 6 months in 2018 (15.1 cubic feet per second [ft3/s]) was about one-tenth of the discharge during the same period in 2019 (152 ft3/s). The cumulative monthly discharge during April through September in 2018 was 5,360 acre-feet, about one-tenth of the discharge during the same period in 2019 which was 54,700 acre-feet. Similar differences in discharge between the 2018 and 2019 periods also are noted at other Blacks Fork streamgages in the area.
Continuous specific conductance data and the statistical relation between specific conductance and dissolved-solids concentrations were used to calculate the daily mean dissolved-solids concentrations. Dissolved solids often have an inverse relation with discharge because higher discharges typically have a diluting effect that lowers the dissolved-solids concentrations. In general, when discharges at the Blacks Fork above Smiths Fork streamgage (09219200) are higher, dissolved-solids concentrations are generally lower. However, the high dissolved-solids concentrations that are measured during high discharges indicate that the system has natural variability and the dissolved-solids concentrations are determined by more factors than just discharge. The mean daily dissolved-solids concentration during April through September 2018 was 1,630 milligrams per liter and during the same period in 2019 was 1,100 milligrams per liter.
Dissolved-solids loads were calculated as the product of the discharge and dissolved-solids concentration. The daily mean dissolved-solids loads during 2018 were typically lower than during 2019. This result is primarily because the discharge was much lower in 2018 than in 2019. Therefore, although the daily mean dissolved-solids concentrations tended to be higher in 2018, the substantially higher discharges in 2019 had more of an effect on the dissolved-solids loads than the dissolved-solids concentrations.
The cumulative dissolved-solids load at the Blacks Fork above Smiths Fork, near Lyman, Wyo., streamgage (09219200) during the 18-month study was 81,200 tons, with a mean daily load of 149 tons per day. During the 6-month period from April through September 2018, the cumulative dissolved-solids load at the streamgage was estimated to be 8,740 tons and, during the same 6 months in 2019, the cumulative dissolved-solids load was estimated to be 60,900 tons. During the fall and winter between the two periods, the cumulative dissolved-solids load was 11,600 tons.
Discharge and dissolved-solids concentrations from samples collected during the synoptic sampling events were highly variable among most sites during most synoptic sampling events and also highly variable at most sites among different sampling events. The two sites upstream from the tributary input from Threemile Creek had lower dissolved-solids concentrations than sites including and downstream from the tributary. Sites including and downstream from the tributary had similar values and variability of dissolved-solids loads, with the exception of the farthest downstream site at the Blacks Fork above Smiths Fork, near Lyman, Wyo., streamgage (09219200) that tended to have larger dissolved-solids loads and higher variability among synoptic sampling events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215095","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Eddy-Miller, C.A., Wheeler, J.D., Law, R.M., and Moran, S.W., 2021, Discharge and dissolved-solids characteristics of Blacks Fork above Smiths Fork, Wyoming, April 2018 through September 2019: U.S. Geological Survey Scientific Investigations Report 2021–5095, 32 p., https://doi.org/10.3133/sir20215095.","productDescription":"vii, 32 p.","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-125542","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":389699,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5095/sir20215095.xml","size":"220 kB","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2021–5095 xml"},{"id":389653,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5095/sir20215095.pdf","text":"Report","size":"2.04 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5095"},{"id":389652,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5095/coverthb3.jpg"}],"contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
521 Progress Circle, Suite 6
Cheyenne, WY 82007
Surface-water and groundwater resources in the Big Lost River Basin of south-central Idaho are extensively interconnected; this interchange affects and is affected by water-resource management for irrigated agriculture and other uses in the basin. Concerns from water users regarding declining groundwater levels, declining streamflows, and drought helped motivate an updated evaluation of water resources in the Big Lost River Basin. The hydrogeologic framework presented in this report provides a conceptual basis for understanding groundwater resources in the Big Lost River Basin and comprises three major parts: (1) conceptual description of four hydrogeologic units, (2) development of a three-dimensional hydrogeologic framework model representing the spatial distribution of the hydrogeologic units, and (3) a description of groundwater occurrence and movement. This hydrogeologic framework represents the first of three planned reports describing water resources in the Big Lost River Basin; subsequent reports are intended to present a groundwater budget for the basin and to describe the results of a series of events measuring gains to and losses from streamflow in the Big Lost River. This report was prepared by the U.S. Geological Survey in cooperation with the Idaho Department of Water Resources.
The Big Lost River Basin has four hydrogeologic units. First, the Quaternary unconsolidated sediments unit comprises the basin-fill alluvial aquifer and generally is used within 250 feet of the land surface. The Quaternary unconsolidated sediments unit is spatially heterogeneous, with locally confining conditions in some areas, and is the most heavily used hydrogeologic unit in the basin. Second, the Paleozoic sedimentary rocks unit, composed primarily of carbonates with some siliciclastic rocks, represents the major bedrock aquifer and contributes subsurface recharge at the margins of the alluvial aquifer. Third, the Tertiary volcanic rocks unit, composed primarily of andesite and dacite with lesser tuff, is locally important to water production, particularly in faulted and fractured zones. The Paleozoic sedimentary rocks hydrogeologic unit occurs at the valley margins and underlies tributaries throughout the basin, whereas the Tertiary volcanic rocks hydrogeologic unit primarily occurs in uplands in the western one-half of the basin. Fourth, the Quaternary basalt rocks unit consists of multiple basalt flows that are interbedded with the Quaternary unconsolidated sediments unit in the southern end of the Big Lost River Basin and contains at least three water-bearing zones. Insights gained from this updated hydrogeologic framework will help inform current water-resource management in the Big Lost River Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215078A","collaboration":"Prepared in cooperation with the Idaho Department of Water Resources","usgsCitation":"Zinsser, L.M., 2021, Hydrogeologic framework of the Big Lost River Basin, south-central Idaho, chap. A of Zinsser, L.M., ed., Characterization of water resources in the Big Lost River Basin, south-central Idaho: U.S. Geological Survey Scientific Investigations Report 2021–5078–A, 42 p., https://doi.org/10.3133/sir20215078A.","productDescription":"Report: viii, 42 p.; Appendix; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-125228","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":396956,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5078/a/sir20215078A.XML"},{"id":396955,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5078/a/images"},{"id":389624,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P911S9LF","text":"USGS data release","description":"USGS data release","linkHelpText":"Hydrogeologic framework of the Big Lost River Basin, south-central Idaho—Hydrogeologic framework model and well data"},{"id":389623,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5078/a/sir20215078A_app1.pdf","text":"Appendix 1","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5078A Appendix 1"},{"id":389622,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5078/a/sir20215078A.pdf","text":"Report","size":"8.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5078A"},{"id":389621,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5078/a/coverthb.jpg"},{"id":409279,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2021/5078/a/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2021-5078A Version History"}],"country":"United States","state":"Idaho","otherGeospatial":"Big Lost River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.169921875,\n 43.229195113965005\n ],\n [\n -112.2802734375,\n 43.229195113965005\n ],\n [\n -112.2802734375,\n 44.15068115978094\n ],\n [\n -114.169921875,\n 44.15068115978094\n ],\n [\n -114.169921875,\n 43.229195113965005\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702-4520
The Earth Resources Observation and Science (EROS) Center is the largest facility of its kind within the U.S. Geological Survey. As both a science and data center, EROS serves a unique and critical role in shaping our understanding of a changing planet.
EROS opened its doors in 1973 as a receiving station, data archive, and data distribution hub for the USGS Landsat series of Earth observing satellites. In the nearly five decades since, EROS has grown into a globally recognized leader in land change science.
Warming of lake surface waters has become a concern to limnologists and water managers because air temperatures, which directly affect near-surface water temperatures, are projected to increase in Wisconsin (WICCI 2011) as well as globally (IPCC 2018). This projected increase is in addition to the changes in air temperatures that have already occurred in recent decades(WICCI 2011, NOAA 2017).The deleterious effects of increased temperatures in lake surface waters have been extensively reviewed (e.g., Blenckner 2005, Keller 2007, Adrian et al. 2009, George 2010). Briefly, the exceedance of thermal preferences or tolerances of aquatic biota can cause altered food webs and loss of biodiversity in lakes (DeStasio et al. 1996, Chu et al. 2005, Graham and Harrod 2009, Woodward et al. 2010, Comte et al. 2013). Warmer surface water temperature scan result in stronger and longer thermal stratification in deep lakes(Robertson and Ragotzkie1990, Hondzo and Stefan 1993, Livingstone 2003, Butcher et al. 2015). This process in turn can cause the duration and extent of hypolimnetic anoxia to increase, thus reducing hypolimnetic refugia needed for cold-and cool-water fish (De Stasio et al. 1996, Magnuson et al. 1997, Jeppesen et al. 2012, Missaghi et al. 2017). Longer duration of hypolimnetic anoxia can enhance eutrophication because of more internal loading of phosphorus from bottom sediments (Blenckner et al. 2002, North et al. 2014). Of particular concern, warmer water temperatures favor the growth of toxic cyanobacteria in eutrophic systems (Paerl and Huisman 2008, Wagner and Adrian 2009, Kosten et al. 2012).Another effect of warmer lake surface temperatures is increased evaporation that can result in lower water levels(Spence et al. 2013, Gronewold and Stow 2014).
","language":"English","publisher":"Wisconsin Department of Natural Resources","usgsCitation":"Lathrop, R.C., and Robertson, D., 2021, Long-term epilimnetic temperature trends in Lake Mendota and Trout Lake, Wisconsin, 10 p.","productDescription":"10 p.","ipdsId":"IP-131835","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":406606,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":398289,"type":{"id":15,"text":"Index Page"},"url":"https://wicci.wisc.edu/water-resources-working-group/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wisconsin","otherGeospatial":"Lake Mendota, Trout Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.3657112121582,\n 43.103740264387625\n ],\n [\n -89.37326431274414,\n 43.113264831709394\n ],\n [\n -89.38064575195311,\n 43.11489388557451\n ],\n [\n -89.37583923339844,\n 43.12379026073815\n ],\n [\n -89.38339233398438,\n 43.13055565187361\n ],\n [\n -89.39798355102539,\n 43.12830060463496\n ],\n [\n -89.40845489501953,\n 43.130931484996964\n ],\n [\n -89.40879821777344,\n 43.140451820450636\n ],\n [\n -89.40982818603516,\n 43.14220540479065\n ],\n [\n -89.40605163574219,\n 43.14746585603295\n ],\n [\n -89.40519332885742,\n 43.15097257204435\n ],\n [\n -89.40502166748047,\n 43.152851087148385\n ],\n [\n -89.4093132019043,\n 43.15322678324046\n ],\n [\n -89.41017150878906,\n 43.15047162493179\n ],\n [\n -89.40948486328125,\n 43.147215368619335\n ],\n [\n -89.41841125488281,\n 43.145962916154375\n ],\n [\n -89.42527770996094,\n 43.14182964095191\n ],\n [\n -89.43145751953125,\n 43.13494022794606\n ],\n [\n -89.44107055664062,\n 43.120908478032554\n ],\n [\n -89.44931030273438,\n 43.115395124193334\n ],\n [\n -89.45411682128906,\n 43.11025723372219\n ],\n [\n -89.46149826049805,\n 43.11013191393195\n ],\n [\n -89.46836471557617,\n 43.10812676239141\n ],\n [\n -89.46853637695312,\n 43.109755953021676\n ],\n [\n -89.483642578125,\n 43.10562023059227\n ],\n [\n -89.48484420776367,\n 43.10236158581175\n ],\n [\n -89.48312759399414,\n 43.09308603205923\n ],\n [\n -89.4729995727539,\n 43.08669260282566\n ],\n [\n -89.4729995727539,\n 43.084185193502705\n ],\n [\n -89.46647644042967,\n 43.08105078752353\n ],\n [\n -89.45549011230469,\n 43.08142692470809\n ],\n [\n -89.43145751953125,\n 43.091957828335666\n ],\n [\n -89.4232177734375,\n 43.08619112917161\n ],\n [\n -89.41909790039062,\n 43.086817970597735\n ],\n [\n -89.42665100097656,\n 43.084812055455174\n ],\n [\n -89.4261360168457,\n 43.08117616684163\n ],\n [\n -89.42218780517578,\n 43.07779083519471\n ],\n [\n -89.41841125488281,\n 43.07866853173014\n ],\n [\n -89.40811157226562,\n 43.07779083519471\n ],\n [\n -89.39523696899414,\n 43.0770385138722\n ],\n [\n -89.3818473815918,\n 43.081552303256444\n ],\n [\n -89.37686920166016,\n 43.086817970597735\n ],\n [\n -89.37360763549805,\n 43.09170711357466\n ],\n [\n -89.36931610107422,\n 43.096345170514745\n ],\n [\n -89.37068939208984,\n 43.09784932976191\n ],\n [\n -89.36811447143555,\n 43.103865597264054\n ],\n [\n -89.3657112121582,\n 43.103740264387625\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.64672088623047,\n 46.06489382954517\n ],\n [\n -89.6590805053711,\n 46.079422858644335\n ],\n [\n -89.67041015625,\n 46.078232098524595\n ],\n [\n -89.66938018798827,\n 46.073468801073744\n ],\n [\n -89.67727661132811,\n 46.06632308397751\n ],\n [\n -89.67487335205078,\n 46.063583647141385\n ],\n [\n -89.66920852661133,\n 46.06066540185297\n ],\n [\n -89.67598915100098,\n 46.05774700231395\n ],\n [\n -89.67787742614746,\n 46.0548880123878\n ],\n [\n -89.68053817749023,\n 46.05381585300414\n ],\n [\n -89.67959403991698,\n 46.052743672805086\n ],\n [\n -89.67641830444336,\n 46.052445841277944\n ],\n [\n -89.67547416687012,\n 46.0502418380586\n ],\n [\n -89.67332839965819,\n 46.0500035621722\n ],\n [\n -89.67169761657713,\n 46.048514314593234\n ],\n [\n -89.6736717224121,\n 46.048454743854876\n ],\n [\n -89.6736717224121,\n 46.047561175070236\n ],\n [\n -89.67942237854004,\n 46.04672716449607\n ],\n [\n -89.68268394470215,\n 46.04327184368698\n ],\n [\n -89.6825122833252,\n 46.04184199254818\n ],\n [\n -89.69066619873047,\n 46.037969293215895\n ],\n [\n -89.69873428344727,\n 46.03790971110604\n ],\n [\n -89.70379829406738,\n 46.03671805541736\n ],\n [\n -89.70388412475586,\n 46.029686763759436\n ],\n [\n -89.70268249511719,\n 46.02789900460852\n ],\n [\n -89.70010757446289,\n 46.02706469721667\n ],\n [\n -89.69924926757812,\n 46.02670713305107\n ],\n [\n -89.70070838928223,\n 46.02593240275772\n ],\n [\n -89.70002174377441,\n 46.024740488797164\n ],\n [\n -89.69959259033203,\n 46.02229698483673\n ],\n [\n -89.69916343688965,\n 46.02128379298403\n ],\n [\n -89.70002174377441,\n 46.01955536402927\n ],\n [\n -89.69916343688965,\n 46.01848251888057\n ],\n [\n -89.69633102416991,\n 46.01800569213273\n ],\n [\n -89.69281196594238,\n 46.01675400235616\n ],\n [\n -89.69109535217284,\n 46.01717123542982\n ],\n [\n -89.68972206115723,\n 46.018840136243064\n ],\n [\n -89.68414306640625,\n 46.01919775129263\n ],\n [\n -89.681396484375,\n 46.018959341516585\n ],\n [\n -89.67676162719727,\n 46.01669439737435\n ],\n [\n -89.6770191192627,\n 46.01562149671552\n ],\n [\n -89.67504501342773,\n 46.01335641585366\n ],\n [\n -89.67092514038086,\n 46.012879544903214\n ],\n [\n -89.66663360595703,\n 46.01466778976556\n ],\n [\n -89.66380119323729,\n 46.018244106020624\n ],\n [\n -89.66242790222168,\n 46.02033018369074\n ],\n [\n -89.66079711914062,\n 46.01985337287631\n ],\n [\n -89.66028213500977,\n 46.01729044430121\n ],\n [\n -89.6608829498291,\n 46.01669439737435\n ],\n [\n -89.66122627258301,\n 46.015979132581386\n ],\n [\n -89.65882301330566,\n 46.01520425194874\n ],\n [\n -89.65624809265135,\n 46.01651558204347\n ],\n [\n -89.65487480163574,\n 46.02098579184671\n ],\n [\n -89.65581893920898,\n 46.022952569670835\n ],\n [\n -89.65384483337402,\n 46.0314744650882\n ],\n [\n -89.65229988098143,\n 46.03356004355776\n ],\n [\n -89.65152740478516,\n 46.04106747439689\n ],\n [\n -89.64998245239256,\n 46.04392717975828\n ],\n [\n -89.65547561645508,\n 46.047084599141165\n ],\n [\n -89.66045379638672,\n 46.047442031473445\n ],\n [\n -89.66543197631835,\n 46.045476125024614\n ],\n [\n -89.66989517211914,\n 46.04476123260601\n ],\n [\n -89.67264175415039,\n 46.04684630963474\n ],\n [\n -89.67023849487305,\n 46.047620746772246\n ],\n [\n -89.66835021972656,\n 46.0472037435089\n ],\n [\n -89.66774940490721,\n 46.0472037435089\n ],\n [\n -89.66800689697266,\n 46.04809731807564\n ],\n [\n -89.6663761138916,\n 46.048514314593234\n ],\n [\n -89.66500282287598,\n 46.050897091446004\n ],\n [\n -89.66242790222168,\n 46.05071838674764\n ],\n [\n -89.65178489685059,\n 46.056674898437706\n ],\n [\n -89.64672088623047,\n 46.0625712121688\n ],\n [\n -89.64672088623047,\n 46.06489382954517\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lathrop, Richard C","contributorId":172075,"corporation":false,"usgs":false,"family":"Lathrop","given":"Richard","email":"","middleInitial":"C","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":839930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robertson, Dale M. 0000-0001-6799-0596","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":217258,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":839931,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70240963,"text":"70240963 - 2021 - Zirconium-bearing accessory minerals in UK Paleogene granites: Textural, compositional, and paragenetic relationships","interactions":[],"lastModifiedDate":"2023-03-02T16:41:52.991683","indexId":"70240963","displayToPublicDate":"2021-09-23T10:35:50","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1593,"text":"European Journal of Mineralogy","active":true,"publicationSubtype":{"id":10}},"title":"Zirconium-bearing accessory minerals in UK Paleogene granites: Textural, compositional, and paragenetic relationships","docAbstract":"The mineral occurrences, parageneses, textures, and compositions of Zr-bearing accessory minerals in a suite of UK Paleogene granites from Scotland and Northern Ireland are described. Baddeleyite, zirconolite, and zircon, in that sequence, formed in hornblende + biotite granites (type 1) and hedenbergite–fayalite granites (type 2). The peralkaline microgranite (type 3) of Ailsa Craig contains zircon, dalyite, a eudialyte-group mineral, a fibrous phase which is possibly lemoynite, and Zr-bearing aegirine. Hydrothermal zircon is also present in all three granite types and documents the transition from a silicate-melt environment to an incompatible element-rich aqueous-dominated fluid. No textures indicative of inherited zircon were observed. The minerals crystallized in stages from magmatic through late-magmatic to hydrothermal. The zirconolite and eudialyte-group mineral are notably Y+REE-rich (REE signifies rare earth element). The crystallization sequence of the minerals may have been related to the activities of Si and Ca, to melt peralkalinity, and to local disequilibrium.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/ejm-33-537-2021","usgsCitation":"Belkin, H.E., and MacDonald, R., 2021, Zirconium-bearing accessory minerals in UK Paleogene granites: Textural, compositional, and paragenetic relationships: European Journal of Mineralogy, v. 37, p. 537-570, https://doi.org/10.5194/ejm-33-537-2021.","productDescription":"34 p.","startPage":"537","endPage":"570","ipdsId":"IP-124385","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":450702,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/ejm-33-537-2021","text":"Publisher Index Page"},{"id":413625,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Northern Ireland, Scotland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -4.371029936775869,\n 57.27175687671797\n ],\n [\n -7.259167863003029,\n 57.27175687671797\n ],\n [\n -7.259167863003029,\n 54.061864482791236\n ],\n [\n -4.371029936775869,\n 54.061864482791236\n ],\n [\n -4.371029936775869,\n 57.27175687671797\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"37","noUsgsAuthors":false,"publicationDate":"2021-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Belkin, Harvey E. 0000-0001-7879-6529 hbelkin@usgs.gov","orcid":"https://orcid.org/0000-0001-7879-6529","contributorId":581,"corporation":false,"usgs":true,"family":"Belkin","given":"Harvey","email":"hbelkin@usgs.gov","middleInitial":"E.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":865503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"MacDonald, Ray","contributorId":9704,"corporation":false,"usgs":true,"family":"MacDonald","given":"Ray","email":"","affiliations":[],"preferred":false,"id":865504,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70224408,"text":"sir20215071 - 2021 - Origin of unconsolidated Quaternary deposits at Harriet Point near Redoubt Volcano, Alaska","interactions":[],"lastModifiedDate":"2021-09-23T16:53:40.644109","indexId":"sir20215071","displayToPublicDate":"2021-09-23T09:25:43","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5071","displayTitle":"Origin of Unconsolidated Quaternary Deposits at Harriet Point near Redoubt Volcano, Alaska","title":"Origin of unconsolidated Quaternary deposits at Harriet Point near Redoubt Volcano, Alaska","docAbstract":"Unconsolidated boulder-rich diamicton units exposed in sea cliffs at Harriet Point southeast of Redoubt Volcano were evaluated to better understand their provenance relative to the late Quaternary eruptive history of the volcano. A previous study concluded that deposits at Harriet Point were emplaced by a large volcanic landslide originating on the southeast flank of Redoubt Volcano (Begét and Nye, 1994). Field-based analysis of the stratigraphy and sedimentology of the Harriet Point deposits and numerical simulations of the volcanic landslide area of inundation indicate that none of the deposits are volcanogenic. All of the unconsolidated boulder-rich diamicton units at Harriet Point are glacial in origin and can be reconciled using the presently available model for late Quaternary glaciation of Cook Inlet.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215071","usgsCitation":"Waythomas, C.F., 2021, Origin of unconsolidated Quaternary deposits at Harriet Point near Redoubt Volcano, Alaska: U.S. Geological Survey Scientific Investigations Report 2021-5071, 14 p., https://doi.org/10.3133/sir20215071.","productDescription":"iv, 14 p.","numberOfPages":"14","onlineOnly":"Y","ipdsId":"IP-116798","costCenters":[{"id":121,"text":"Alaska Volcano Observatory","active":false,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":389648,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5071/sir20215071.pdf","text":"Report","size":"9.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":389649,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5071/covrthb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Harriet Point, Redoubt Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -152.94067382812497,\n 60.303144396154856\n ],\n [\n -152.14279174804688,\n 60.303144396154856\n ],\n [\n -152.14279174804688,\n 60.5923622983958\n ],\n [\n -152.94067382812497,\n 60.5923622983958\n ],\n [\n -152.94067382812497,\n 60.303144396154856\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Alaska Volcano Observatory
U.S. Geological Survey
4210 University Drive
Anchorage, AK 99508
The Harney Basin is a closed river basin in southeastern Oregon. Surface water in the basin is used for a variety of social, economic, and ecological benefits. While some surface water uses compete with one another, others are complementary or jointly produce multiple beneficial outcomes. The objective of this study is to conduct an economic assessment of surface water in the basin as it relates to wet meadow pasture production and outdoor recreation. Given the complex interactions between surface water management on public and private land and the various goods and services that are derived from adequate water resources, an economic assessment of surface water management can be used to assist future decision making in the basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211087","usgsCitation":"Bair, L.S., Flyr, M., and Huber, C., 2021, Economic assessment of surface water in the Harney Basin, Oregon: U.S. Geological Survey Open-File Report 2021-1087, 43 p., https://doi.org/10.3133/ofr20211087.","productDescription":"vii, 43 p.","numberOfPages":"43","onlineOnly":"Y","ipdsId":"IP-122032","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":389611,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1087/covrthb.jpg"},{"id":389612,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1087/ofr20211087.pdf","text":"Report","size":"16 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Oregon","otherGeospatial":"Harney Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.05859375,\n 42.24478535602799\n ],\n [\n -117.454833984375,\n 42.24478535602799\n ],\n [\n -117.454833984375,\n 44.38669150215206\n ],\n [\n -120.05859375,\n 44.38669150215206\n ],\n [\n -120.05859375,\n 42.24478535602799\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"This paper considers mutualistic interactions between two consumers, in which one consumer can consume a resource only by exchange of service for service with the other. By rigorous analysis on the one-resource and two-consumer model with Holling-type I response, we show periodic oscillations and tri-stability in the mutualism system: when their initial densities decrease, the consumers' interaction outcomes would change from coexistence in periodic oscillation, to persistence at a steady state, and to extinction. Under certain conditions, we also show two types of bi-stability in the system: the consumers would change from coexisting in periodic oscillation (resp. at a steady state) to going to extinction when their initial densities decrease. Then we analyze a modified system with Holling-type II response. Based on theoretical analysis and numerical computation, we show that there also exist tri-stability and two types of bi-stability in this system. Moreover, it is shown that varying the degree of obligation can lead to transition of interaction outcomes between coexistence in periodic oscillation (resp. at a steady state) and extinction of both consumers. These results are important in understanding complexity in mutualism.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jmaa.2021.125672","usgsCitation":"Wang, Y., Wu, H., and DeAngelis, D.L., 2021, Periodic oscillation and tri-stability in mutualism systems with two consumers: Journal of Mathematical Analysis and Applications, v. 506, no. 2, 125672, https://doi.org/10.1016/j.jmaa.2021.125672.","productDescription":"125672","ipdsId":"IP-131197","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":408694,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"506","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Yuanshi","contributorId":207814,"corporation":false,"usgs":false,"family":"Wang","given":"Yuanshi","email":"","affiliations":[{"id":37637,"text":"School of Mathematics and Computational Science Sun Yat-sen University","active":true,"usgs":false}],"preferred":false,"id":855730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wu, Hong","contributorId":207815,"corporation":false,"usgs":false,"family":"Wu","given":"Hong","email":"","affiliations":[{"id":37637,"text":"School of Mathematics and Computational Science Sun Yat-sen University","active":true,"usgs":false}],"preferred":false,"id":855731,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":148065,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":855732,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70224528,"text":"70224528 - 2021 - Survival and abundance of polar bears in Alaska’s Beaufort Sea, 2001–2016","interactions":[],"lastModifiedDate":"2021-11-01T16:02:45.091989","indexId":"70224528","displayToPublicDate":"2021-09-23T08:38:20","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Survival and abundance of polar bears in Alaska’s Beaufort Sea, 2001–2016","docAbstract":"The Arctic Ocean is undergoing rapid transformation toward a seasonally ice-free ecosystem. As ice-adapted apex predators, polar bears (Ursus maritimus) are challenged to cope with ongoing habitat degradation and changes in their prey base driven by food-web response to climate warming. Knowledge of polar bear response to environmental change is necessary to understand ecosystem dynamics and inform conservation decisions. In the southern Beaufort Sea (SBS) of Alaska and western Canada, sea ice extent has declined since satellite observations began in 1979 and available evidence suggests that the carrying capacity of the SBS for polar bears has trended lower for nearly two decades. In this study, we investigated the population dynamics of polar bears in Alaska's SBS from 2001 to 2016 using a multistate Cormack–Jolly–Seber mark–recapture model. States were defined as geographic regions, and we used location data from mark–recapture observations and satellite-telemetered bears to model transitions between states and thereby explain heterogeneity in recapture probabilities. Our results corroborate prior findings that the SBS subpopulation experienced low survival from 2003 to 2006. Survival improved modestly from 2006 to 2008 and afterward rebounded to comparatively high levels for the remainder of the study, except in 2012. Abundance moved in concert with survival throughout the study period, declining substantially from 2003 and 2006 and afterward fluctuating with lower variation around an average of 565 bears (95% Bayesian credible interval [340, 920]) through 2015. Even though abundance was comparatively stable and without sustained trend from 2006 to 2015, polar bears in the Alaska SBS were less abundant over that period than at any time since passage of the U.S. Marine Mammal Protection Act. The potential for recovery is likely limited by the degree of habitat degradation the subpopulation has experienced, and future reductions in carrying capacity are expected given current projections for continued climate warming.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.8139","usgsCitation":"Bromaghin, J.F., Douglas, D.C., Durner, G.M., Simac, K.S., and Atwood, T.C., 2021, Survival and abundance of polar bears in Alaska’s Beaufort Sea, 2001–2016: Ecology and Evolution, v. 11, no. 20, p. 14250-14267, https://doi.org/10.1002/ece3.8139.","productDescription":"18 p.","startPage":"14250","endPage":"14267","ipdsId":"IP-125254","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":450707,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ece3.8139","text":"External Repository"},{"id":389724,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska","otherGeospatial":"Beaufort Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -166.2890625,\n 68.23682270936281\n ],\n [\n -156.4453125,\n 71.24435551310674\n ],\n [\n -140.9765625,\n 69.59589006237648\n ],\n [\n -141.15234374999997,\n 76.24781659441473\n ],\n [\n -166.55273437499997,\n 76.03731657616542\n ],\n [\n -166.2890625,\n 68.23682270936281\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"20","noUsgsAuthors":false,"publicationDate":"2021-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Bromaghin, Jeffrey F. 0000-0002-7209-9500 jbromaghin@usgs.gov","orcid":"https://orcid.org/0000-0002-7209-9500","contributorId":139899,"corporation":false,"usgs":true,"family":"Bromaghin","given":"Jeffrey","email":"jbromaghin@usgs.gov","middleInitial":"F.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":823891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":823892,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Durner, George M. 0000-0002-3370-1191 gdurner@usgs.gov","orcid":"https://orcid.org/0000-0002-3370-1191","contributorId":3576,"corporation":false,"usgs":true,"family":"Durner","given":"George","email":"gdurner@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":823893,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Simac, Kristin S. 0000-0002-4072-1940 ksimac@usgs.gov","orcid":"https://orcid.org/0000-0002-4072-1940","contributorId":131096,"corporation":false,"usgs":true,"family":"Simac","given":"Kristin","email":"ksimac@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":823894,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":823895,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228980,"text":"70228980 - 2021 - Modelling presence versus abundance for invasive species risk assessment","interactions":[],"lastModifiedDate":"2022-02-25T14:26:41.787468","indexId":"70228980","displayToPublicDate":"2021-09-23T08:22:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Modelling presence versus abundance for invasive species risk assessment","docAbstract":"Invasive species prevention and management can be guided by comparisons of invasion risk across space and among species. Species distribution models are widely used to assess invasion risk and typically estimate suitability for species presence. However, suitability for presence may not capture patterns of abundance and impact. We asked how models estimating suitability for presence versus suitability for abundance aligned in their implications for risk assessment.
Western United States.
We developed ensembles of species distribution models for presence and for abundance for four invasive plants. We visualized the distribution of presence and abundance in environmental and geographic space and compared model outputs using criteria relevant for decision-making: a comparison of risk across management units for each species, and a ranking of risk among species for each management unit.
We found good overall agreement between models of presence versus abundance in the relative risk across management units and among species. However, the area predicted to be suitable for invasive species presence was often substantially higher than the area predicted to be suitable for abundance, especially within uninvaded management units.
Models of suitability for invasive species presence and abundance yielded similar assessments of relative risk in comparisons across space and species. In addition, we found patterns of presence and abundance in environmental space can guide modelling decisions and model interpretation. Suitability for abundance can improve relative risk assessment when abundance locations occupy a well-defined subset of the environmental space corresponding to presence. Where abundance locations occur throughout this environmental space, as was particularly striking for Taeniatherum caput-medusae, suitability for presence may better reflect risk of ongoing population increases and spread. This species is at risk of becoming abundant across a substantial portion of the western United States.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.13414","usgsCitation":"Jarnevich, C.S., Sofaer, H., and Engelstad, P., 2021, Modelling presence versus abundance for invasive species risk assessment: Diversity and Distributions, v. 27, no. 12, p. 2454-2464, https://doi.org/10.1111/ddi.13414.","productDescription":"11 p.","startPage":"2454","endPage":"2464","ipdsId":"IP-123563","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":450709,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.13414","text":"Publisher Index Page"},{"id":436188,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MVEPP4","text":"USGS data release","linkHelpText":"Presence and abundance data and models for four invasive plant species"},{"id":396476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":836066,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sofaer, Helen R. 0000-0002-9450-5223","orcid":"https://orcid.org/0000-0002-9450-5223","contributorId":216681,"corporation":false,"usgs":true,"family":"Sofaer","given":"Helen","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":836067,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Engelstad, Peder","contributorId":238758,"corporation":false,"usgs":false,"family":"Engelstad","given":"Peder","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":836068,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70224629,"text":"70224629 - 2021 - Natural history of a bighorn sheep pneumonia epizootic: Source of infection, course of disease, and pathogen clearance","interactions":[],"lastModifiedDate":"2021-11-16T15:49:41.376419","indexId":"70224629","displayToPublicDate":"2021-09-23T08:21:55","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Natural history of a bighorn sheep pneumonia epizootic: Source of infection, course of disease, and pathogen clearance","docAbstract":"A respiratory disease epizootic at the National Bison Range (NBR) in Montana in 2016–2017 caused an 85% decline in the bighorn sheep population, documented by observations of its unmarked but individually identifiable members, the subjects of an ongoing long-term study. The index case was likely one of a small group of young bighorn sheep on a short-term exploratory foray in early summer of 2016. Disease subsequently spread through the population, with peak mortality in September and October and continuing signs of respiratory disease and sporadic mortality of all age classes through early July 2017. Body condition scores and clinical signs suggested that the disease affected ewe groups before rams, although by the end of the epizootic, ram mortality (90% of 71) exceeded ewe mortality (79% of 84). Microbiological sampling 10 years to 3 months prior to the epizootic had documented no evidence of infection or exposure to Mycoplasma ovipneumoniae at NBR, but during the epizootic, a single genetic strain of M. ovipneumoniae was detected in affected animals. Retrospective screening of domestic sheep flocks near the NBR identified the same genetic strain in one flock, presumptively the source of the epizootic infection. Evidence of fatal lamb pneumonia was observed during the first two lambing seasons following the epizootic but was absent during the third season following the death of the last identified M. ovipneumoniae carrier ewe. Monitoring of life-history traits prior to the epizootic provided no evidence that environmentally and/or demographically induced nutritional or other stress contributed to the epizootic. Furthermore, the epizootic occurred despite proactive management actions undertaken to reduce risk of disease and increase resilience in this population. This closely observed bighorn sheep epizootic uniquely illustrates the natural history of the disease including the (presumptive) source of spillover, course, severity, and eventual pathogen clearance.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.8166","usgsCitation":"Besser, T., Cassirer, E.F., Lisk, A., Nelson, D., Manlove, K.R., Cross, P., and Hogg, J.T., 2021, Natural history of a bighorn sheep pneumonia epizootic: Source of infection, course of disease, and pathogen clearance: Ecology and Evolution, v. 11, no. 21, p. 14366-14382, https://doi.org/10.1002/ece3.8166.","productDescription":"17 p.","startPage":"14366","endPage":"14382","ipdsId":"IP-126913","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":450711,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.8166","text":"Publisher Index Page"},{"id":390113,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"National Bison Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.51873779296875,\n 47.148633511301426\n ],\n [\n -113.93646240234375,\n 47.148633511301426\n ],\n [\n -113.93646240234375,\n 47.57837853860192\n ],\n [\n -114.51873779296875,\n 47.57837853860192\n ],\n [\n -114.51873779296875,\n 47.148633511301426\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"21","noUsgsAuthors":false,"publicationDate":"2021-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Besser, T. E.","contributorId":266154,"corporation":false,"usgs":false,"family":"Besser","given":"T. E.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":824438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cassirer, E. Frances","contributorId":198303,"corporation":false,"usgs":false,"family":"Cassirer","given":"E.","email":"","middleInitial":"Frances","affiliations":[],"preferred":false,"id":824439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lisk, Amy","contributorId":266155,"corporation":false,"usgs":false,"family":"Lisk","given":"Amy","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":824440,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, Danielle","contributorId":266156,"corporation":false,"usgs":false,"family":"Nelson","given":"Danielle","email":"","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":824441,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Manlove, Kezia R.","contributorId":198305,"corporation":false,"usgs":false,"family":"Manlove","given":"Kezia","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":824442,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cross, Paul C. 0000-0001-8045-5213","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":204814,"corporation":false,"usgs":true,"family":"Cross","given":"Paul C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":824443,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hogg, John T.","contributorId":245903,"corporation":false,"usgs":false,"family":"Hogg","given":"John","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":824444,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70224529,"text":"70224529 - 2021 - Evidence for humans in North America during the Last Glacial Maximum","interactions":[],"lastModifiedDate":"2021-09-24T13:39:08.628097","indexId":"70224529","displayToPublicDate":"2021-09-23T08:19:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for humans in North America during the Last Glacial Maximum","docAbstract":"Archaeologists and researchers in allied fields have long sought to understand human colonization of North America. When, how, and from where did people migrate, and what were the consequences of their arrival for the established fauna and landscape are enduring questions. Here, we present evidence from excavated surfaces of in situ human footprints from White Sands National Park (New Mexico, USA), where multiple human footprints are stratigraphically constrained and bracketed by seed layers that yield calibrated ages between ~23 and 21 ka. These findings confirm the presence of humans in North America during the Last Glacial Maximum, adding evidence to the antiquity of human colonization of the Americas, and provide a temporal range extension for the co-existence of early inhabitants and Pleistocene megafauna.","language":"English","doi":"10.1126/science.abg7586","usgsCitation":"Bennett, M.R., Bustos, D., Pigati, J.S., Springer, K.B., Urban, T.M., Holliday, V.T., Reynolds, S.C., Budka, M., Honke, J.S., Hudson, A.M., Fenerty, B., Connelly, C., Martinez, P., Santucci, V.L., and Odess, D., 2021, Evidence for humans in North America during the Last Glacial Maximum: Science, p. 1528-1531, https://doi.org/10.1126/science.abg7586.","productDescription":"4 p.","startPage":"1528","endPage":"1531","ipdsId":"IP-125967","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":450714,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://eprints.bournemouth.ac.uk/36202/7/science_manuscript_WHSA_rev3_17Aug21.pdf","text":"External Repository"},{"id":436190,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ABZEM9","text":"USGS data release","linkHelpText":"Data release for Evidence of humans in North America during the Last Glacial Maximum"},{"id":389708,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"White Sands National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.49734497070312,\n 32.62434010409917\n ],\n [\n -106.12792968749999,\n 32.62434010409917\n ],\n [\n -106.12792968749999,\n 32.90495631913751\n ],\n [\n -106.49734497070312,\n 32.90495631913751\n ],\n [\n -106.49734497070312,\n 32.62434010409917\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bennett, Matthew R.","contributorId":265968,"corporation":false,"usgs":false,"family":"Bennett","given":"Matthew","email":"","middleInitial":"R.","affiliations":[{"id":54847,"text":"Bournemouth University, U.K.","active":true,"usgs":false}],"preferred":false,"id":823896,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bustos, David","contributorId":265969,"corporation":false,"usgs":false,"family":"Bustos","given":"David","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":823897,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pigati, Jeffrey S. 0000-0001-5843-6219 jpigati@usgs.gov","orcid":"https://orcid.org/0000-0001-5843-6219","contributorId":201167,"corporation":false,"usgs":true,"family":"Pigati","given":"Jeffrey","email":"jpigati@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":823898,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Springer, Kathleen B. 0000-0002-2404-0264 kspringer@usgs.gov","orcid":"https://orcid.org/0000-0002-2404-0264","contributorId":149826,"corporation":false,"usgs":true,"family":"Springer","given":"Kathleen","email":"kspringer@usgs.gov","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":823899,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Urban, Thomas. M.","contributorId":265970,"corporation":false,"usgs":false,"family":"Urban","given":"Thomas.","email":"","middleInitial":"M.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":823900,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Holliday, Vance T.","contributorId":265971,"corporation":false,"usgs":false,"family":"Holliday","given":"Vance","email":"","middleInitial":"T.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":823901,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reynolds, Sally C.","contributorId":265972,"corporation":false,"usgs":false,"family":"Reynolds","given":"Sally","email":"","middleInitial":"C.","affiliations":[{"id":54847,"text":"Bournemouth University, U.K.","active":true,"usgs":false}],"preferred":false,"id":823902,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Budka, Marcin","contributorId":265973,"corporation":false,"usgs":false,"family":"Budka","given":"Marcin","email":"","affiliations":[{"id":54847,"text":"Bournemouth University, U.K.","active":true,"usgs":false}],"preferred":false,"id":823903,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Honke, Jeffrey S. 0000-0003-4357-9297 jhonke@usgs.gov","orcid":"https://orcid.org/0000-0003-4357-9297","contributorId":201389,"corporation":false,"usgs":true,"family":"Honke","given":"Jeffrey","email":"jhonke@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":823904,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hudson, Adam M. 0000-0002-3387-9838 ahudson@usgs.gov","orcid":"https://orcid.org/0000-0002-3387-9838","contributorId":195419,"corporation":false,"usgs":true,"family":"Hudson","given":"Adam","email":"ahudson@usgs.gov","middleInitial":"M.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":823905,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Fenerty, Brendan","contributorId":261639,"corporation":false,"usgs":false,"family":"Fenerty","given":"Brendan","email":"","affiliations":[{"id":52636,"text":"Department of Geosciences, University of Arizona, Tucson, AZ","active":true,"usgs":false}],"preferred":false,"id":823906,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Connelly, Clare","contributorId":265974,"corporation":false,"usgs":false,"family":"Connelly","given":"Clare","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":823907,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Martinez, Patrick J.","contributorId":239661,"corporation":false,"usgs":false,"family":"Martinez","given":"Patrick J.","affiliations":[{"id":47955,"text":"Colorado Division of Wildlife, retired; USFWS, retired","active":true,"usgs":false}],"preferred":false,"id":823908,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Santucci, Vincent L.","contributorId":192886,"corporation":false,"usgs":false,"family":"Santucci","given":"Vincent","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":823909,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Odess, Daniel","contributorId":265975,"corporation":false,"usgs":false,"family":"Odess","given":"Daniel","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":823910,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70230404,"text":"70230404 - 2021 - Informing future condition scenario planning for habitat specialists of the imperiled pine rockland ecosystem of South Florida","interactions":[],"lastModifiedDate":"2022-04-12T13:20:09.477273","indexId":"70230404","displayToPublicDate":"2021-09-23T08:12:11","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":7504,"text":"Final Report","active":true,"publicationSubtype":{"id":1}},"title":"Informing future condition scenario planning for habitat specialists of the imperiled pine rockland ecosystem of South Florida","docAbstract":"This project evaluated habitat conditions for two species found in the imperiled pine rockland ecosystem—the Rim Rock Crowned Snake (Tantilla oolitica) and the Key Ring-Necked Snake (Diadophis punctatus acricus). The Rim Rock Crowned Snake historically occurred in eastern Miami-Dade County (hereafter, mainland) as well as throughout the Florida Keys, whereas the Key Ring-Necked Snake occurs only in lower Florida Keys (Enge et al. 2004; Mays and Enge 2016). Both species are very elusive, small (< 20 cm in length) and primarily fossorial. Pine rockland habitat is rapidly disappearing in South Florida, with < 3 percent of its original extent remaining. Saltwater intrusion from hurricanes and sea-level rise (SLR), and human development pose the greatest threats to the longevity of this ecosystem which, in turn, places species that are endemic to this unique habitat at risk of extinction.
The Rim Rock Crowned Snake and the Key Ringed-Necked Snake are being considered for listing by the U.S. Fish and Wildlife Service (USFWS). To aid the agency’s decision, it must be able to forecast species’ responses to potential future environmental conditions, as well as to different conservation and management actions. Yet, the information needed to complete these forecasts—such as population trends, life history traits, habitat use, and future land use and climate conditions—is often lacking for most rare species. This is especially problematic for assessments of species resiliency to changes in climate and land use.
When these types of data are lacking, information on habitat quality can be used to help determine how a species will respond to change. First, this project gathered current and historical records for both species from various sources such as museum specimens, inventories, and other personal account. Then, we identified potential future changes in habitat that could result from different management actions, such as habitat acquisition or restoration, and environmental conditions, such as changes in the frequency and intensity of tropical storms and rates of SLR. Researchers then explored the potential impacts of these habitat condition changes on the Rim Rock Crowned Snake and Key Ring-Necked Snake.
This information can be used by the USFWS to help make decisions about the need to protect these species under the Endangered Species Act and could inform the conservation, management, and recovery of other at-risk species found in the pine rockland ecosystem. This work supports the Secretary of Interior’s priority to create a conservation stewardship legacy by using science to identify best practices to manage land and water resource and adapt to changes in the environment.
","language":"English","publisher":"Southeast Climate Adaptation Science Center","usgsCitation":"Walls, S.C., 2021, Informing future condition scenario planning for habitat specialists of the imperiled pine rockland ecosystem of South Florida: Final Report, 18 p.","productDescription":"18 p.","ipdsId":"IP-129367","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":398537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":398518,"type":{"id":15,"text":"Index Page"},"url":"https://secasc.ncsu.edu/science/pine-rocklands/"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.0458984375,\n 24.287026865376436\n ],\n [\n -79.9365234375,\n 24.287026865376436\n ],\n [\n -79.9365234375,\n 26.244156283890756\n ],\n [\n -82.0458984375,\n 26.244156283890756\n ],\n [\n -82.0458984375,\n 24.287026865376436\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Walls, Susan C. 0000-0001-7391-9155 swalls@usgs.gov","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":138952,"corporation":false,"usgs":true,"family":"Walls","given":"Susan","email":"swalls@usgs.gov","middleInitial":"C.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":840331,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70227126,"text":"70227126 - 2021 - Evaluating streamwater dissolved organic carbon dynamics in context of variable flowpath contributions with a tracer-based mixing model","interactions":[],"lastModifiedDate":"2022-01-03T15:32:26.574984","indexId":"70227126","displayToPublicDate":"2021-09-23T08:09:33","publicationYear":"2021","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":"Evaluating streamwater dissolved organic carbon dynamics in context of variable flowpath contributions with a tracer-based mixing model","docAbstract":"This study focuses on characterizing the contributions of key terrestrial pathways that deliver dissolved organic carbon (DOC) to streams during hydrological events and on elucidating factors governing variation in water and DOC fluxes from these pathways. We made high-frequency measurements of discharge, specific conductance (SC), and fluorescent dissolved organic matter (FDOM) during 221 events recorded over 2 years within four Vermont (USA) watersheds that range in area from 0.4 to 139 km2. Using the SC measurements, together with statistical information on discharge, we separated the event hydrographs into contributions from three terrestrial pathways, which we refer to as riparian quickflow, subsurface quickflow, and slow-flow groundwater. The pathway discharges were used as input to a mixing model that closely approximated sub-hourly streamwater DOC concentrations as measured with the FDOM sensors. Subsurface quickflow, comprised of pre-event water, was the leading contributor to streamwater DOC fluxes, while riparian quickflow, comprised of event water, was the second-leading contributor to streamwater DOC fluxes, despite comprising the smallest proportion of streamflow yield among the three end-member pathways. Fixed-effects regression analysis revealed that the relationship between DOC fluxes from the end-member pathways and event magnitude was consistent across the four watersheds. This analysis also showed that DOC fluxes from the quickflow pathways increased significantly with temperature and varied inversely, but weakly, with catchment antecedent wetness. We believe that our approach, which leverages in-stream sensors that enable high-frequency measurements over extended periods, may be applicable for evaluating controls on DOC export from other watersheds within and beyond our study region.
Carbon dioxide emissions from active subaerial volcanoes represent 20–50% of the annual global volcanic CO2 flux (Barry et al., 2014). Passive degassing of carbon from the flanks of volcanoes, and the associated accumulation of dissolved inorganic carbon (DIC) within nearby groundwater, also represents a potentially important, yet poorly constrained flux of carbon to the surface (Werner et al., 2019). Here we investigate sources and sinks of DIC in groundwaters in the Lassen Peak region of California. Specifically, we report and interpret the relative abundance and isotopic composition of helium (3He, 4He) and carbon (12C, 13C, 14C) in 37 groundwater samples, from 24 distinct wells, collected between 20 and 60 km from Lassen Peak. Measured groundwater samples have air-corrected 3He/4He values between 0.19 and 7.44 RA (where RA = air 3He/4He = 1.39 × 10−6), all in excess of the radiogenic production value (~0.05 RA), indicating pervasive mantle-derived helium additions to the groundwater system in the Lassen Peak region. Stable carbon isotope ratios of DIC (δ13C) vary between −12.6 and − 27.7‰ (vs. VPDB). Measured groundwater DIC/3He values fall in the range of 2.2 × 1010 to 1.1 × 1012. Using helium and carbon isotope data, we explore several conceptual models to estimate surface carbon contributions and to differentiate between DIC derived from soil CO2 versus DIC derived from external (slab and mantle) carbon sources. Specifically, if we use 14C to identify soil-derived DIC (assuming decadal-to-centennial groundwater ages and a soil CO2 14C activity equal to that of the atmosphere), we calculate that a hypothetical external carbon source would have an apparent δ13C signature between −10.3 and − 59.3‰ (vs. Vienna Pee Dee Belemnite (VPDB)) and an apparent C/3He between 7.0 × 109 and 1.0 × 1012. These apparent δ13C and C/3He values are substantially isotopically lighter than and greater than canonical MORB values, respectively. We suggest that >95% of any external (non-soil-derived) DIC in groundwater must thus be non-mantle in origin (i.e., slab derived or assimilated organic carbon). We further investigate possible sources of external DIC to groundwater using two idealized conceptual approaches: a pure (unfractionated) source mixing model (after Sano and Marty, 1995) and a scenario that invokes fractionation due to calcite precipitation. Because the former model requires carbon contributions from an organic source component with unrealistically low δ13C (~ − 60‰), we suggest that the second scenario is more plausible. Importantly, however, we caution that all conceptual models are dependent on assumptions about initial 14C activity. Thus, we cannot rule out the possibility that the true fraction of non-surface-derived DIC in these samples is lower or negligible, despite the pervasive mantle-derived He isotope signatures throughout the region. Following the 14C approach to deconvolving sources of DIC, we determine that the maximum passive carbon flux could be up to ~2.2 × 106 kg/yr, which is lower than previous magmatic carbon flux estimates from the Lassen region (Rose and Davisson, 1996). We find that the passive dissolved carbon flux could represent a maximum of ~4–18% of the total Lassen geothermal CO2 degassing flux (estimated to be ~3.5 × 107 kg/yr Rose and Davisson, 1996; Gerlach et al., 2008), which is still more than an order of magnitude smaller than soil gas CO2 flux estimates (7.3–11 × 107 kg/yr) for nearby volcanoes (Sorey et al., 1998; Gerlach et al., 1999; Evans et al., 2002; Werner et al., 2014). We conclude that passive dissolved carbon fluxes should be combined with geothermal fluxes and soil gas fluxes to obtain a complete picture of volcanic carbon emissions globally. Our approach highlights the utility of measuring helium isotopes in concert with the full suite of noble gas abundances, tritium, δ13C and 14C, which when interpreted together can be used to better elucidate the various sources of DIC in groundwater.
Information about past ecosystem dynamics and human activities is stored in the ice of Colle Gnifetti glacier in the Swiss Alps. Adverse climatic intervals incurred crop failures and famines and triggered reestablishment of forest vegetation but also societal resilience through innovation. Historical documents and lake sediments record these changes at local—regional scales but often struggle to comprehensively document continental-scale impacts on ecosystems. Here, we provide unique multiproxy evidence of broad-scale ecosystem, land use, and climate dynamics over the past millennium from a Colle Gnifetti microfossil and oxygen isotope record. Microfossil data indicate that before 1750 CE forests and fallow land rapidly replaced crop cultivation during historically documented societal crises caused by climate shifts and epidemics. Subsequently, with technology and the introduction of more resilient crops, European societies adapted to the Little Ice Age cold period, but resource overexploitation and industrialization led to new regional to global-scale environmental challenges.
For the past ∼12 years the Pacific Northwest Seismic Network has been automatically detecting and locating tectonic tremor across the Cascadia subduction zone, resulting in a catalog of more than 500,000 tremor epicenters to date, which has served as a valuable resource for tremor and slip research. This manuscript presents an updated methodology for routine tremor detection in Cascadia and a new catalog of over 180,000 tremor epicenters including amplitudes detected along the subduction zone margin from 2017 to 2021. The events are detected via cross-correlation of continuous vertical envelope data of 128 stations from northern California to northern Vancouver Island. The modified approach results in less scatter and a 55% increase in detected epicenters than previously observed, as well as a newly identified tremor source offset updip from the main tremor and slip region at the southern edge of the subduction zone. Radiated seismic energy in the 1.5–5 Hz band is used to assign epicenters an energy magnitude (MeL), which is calibrated to the ML of local earthquakes. Southern Cascadia is most active, but the highest tremor energy rates occur in northern Cascadia. Tremor in central Cascadia is systematically weaker and less frequent. Individual epicenter magnitudes range from ∼0.5–2 and spatiotemporally cluster into 1,060 swarms with cumulative MeL ranging from ∼0.8 to 3.7. The swarms reflect underlying slow slip events and occur with an earthquake-like energy distribution with a b value ∼1. Tremor epicenters, however, follow a tapered Gutenberg-Richter distribution with high b values, suggesting individual tremor bursts and their constituent low-frequency earthquakes are fault-dimension limited.
Red Knots (Calidris canutus rufa) stop at Delaware Bay during northward migration to feed on eggs of horseshoe crabs (Limulus polyphemus). The northward migration of C. c. rufa coincides with the spawning of horseshoe crabs whose eggs are the perfect food for a migrating Red Knot (Karpanty et al. 2006, Haramis et al. 2007). Horseshoe crabs are therefore an important food resource for Red Knots as well as other shorebirds at Delaware Bay.
Horseshoe crabs have been harvested since at least 1990 for use as bait in American eel (Anguilla rostrata) and whelk (Busycon) fisheries (Kreamer and Michels 2009). In the late 1990s and early 2000s the number of Red Knots found at Delaware Bay declined dramatically from ~50,000 to ~13,000 (Niles et al. 2008). At the same time the number of horseshoe crabs harvested also declined and avian conservation biologists hypothesized that unregulated harvest of horseshoe crabs from Delaware Bay in the 1990s prevented sufficient refueling during stopover for successful migration to the breeding grounds, nesting, and survival for the remainder of the annual cycle (McGowan et al. 2011).
The harvest of horseshoe crabs in the Delaware Bay region has been managed by the Atlantic States Marine Fisheries Commission (ASMFC) since 2012 using an Adaptive Resource Management (ARM) framework (McGowan et al. 2015b). The ARM framework was designed to constrain the harvest so that number of spawning crabs would not limit the number of Red Knots stopping at Delaware Bay during migration. This management framework to achieve multiple objectives requires an estimate each year of both the crab population and the Red Knot stopover population size to inform harvest recommendations (McGowan et al. 2015a). We have estimated the stopover population size using mark-resight data on individually-marked birds and a Jolly-Seber model for open populations since 2011.
","language":"English","publisher":"Atlantic States Marine Fisheries Commission","usgsCitation":"Lyons, J.E., 2021, Red knot stopover population size and migration ecology at Delaware Bay, USA, 2021, 21 p.","productDescription":"21 p.","ipdsId":"IP-135416","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":427147,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":398095,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://dnrec.delaware.gov/fish-wildlife/conservation/shorebirds/research/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Delaware, New Jersey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.09403509407363,\n 38.74026331013363\n ],\n [\n -74.92922524720622,\n 38.95518554423097\n ],\n [\n -74.86023507875021,\n 39.17242937484494\n ],\n [\n -75.47348102058082,\n 39.53695640590777\n ],\n [\n -75.45818237996806,\n 39.725833415896574\n ],\n [\n -75.62300710583959,\n 39.7375634879601\n ],\n [\n -75.68813576821344,\n 39.5812414619472\n ],\n [\n -75.61529784001694,\n 39.40677166373757\n ],\n [\n -75.46198775359684,\n 39.16648631014266\n ],\n [\n -75.34700185696957,\n 38.90151720709986\n ],\n [\n -75.09403509407363,\n 38.74026331013363\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":222844,"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":839581,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70224547,"text":"70224547 - 2021 - SiteOpt: An open-source R-package for site selection and portfolio optimization","interactions":[],"lastModifiedDate":"2021-11-16T15:45:42.56053","indexId":"70224547","displayToPublicDate":"2021-09-22T08:35:08","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1445,"text":"Ecography","active":true,"publicationSubtype":{"id":10}},"title":"SiteOpt: An open-source R-package for site selection and portfolio optimization","docAbstract":"Conservation planning involves identifying and selecting actions to best achieve objectives for managing natural, social and cultural resources. Conservation problems are often high dimensional when specified as combinatorial or portfolio problems and when multiple competing objectives are considered at varying spatial and temporal scales. Although analytical techniques such as modern portfolio theory (MPT) have been developed to address these complex problems, open source computational platforms for executing these approaches are not readily available. We present a user-friendly R-package called SiteOpt for optimization of binary decisions while explicitly considering environmental or economic uncertainty and the risk tolerance of decision makers. We illustrate the package with spatially-explicit site selection problems (i.e. spatial conservation planning), including an option for divestment (i.e. selling assets), when accounting for future uncertainties in designing conservation areas. The tool is applicable to both spatial and non-spatial problems, such as budget allocation or species selection. Constraints for spatial design and spatial dependencies (e.g. connectivity among sites) can also be specified in SiteOpt. Users can optimize site selection based on two competing objectives by solving for the Nash bargaining solution. Importantly, by quantifying uncertainty and asset spatial correlation, a measure of risk can be included as one such objective to be traded off against portfolio benefits. Thus, SiteOpt can be used to explicitly manage risk in portfolio-based spatial optimization. This tool facilitates decisions in a variety of problem settings, including reserve selection, invasive species management, allocation of law enforcement activities for conservation, budget allocation and asset selection under uncertainty and risk.
","language":"English","publisher":"Wiley","doi":"10.1111/ecog.05717","usgsCitation":"Saghand, P.G., Haider, Z., Charkhgard, H., Eaton, M.J., Martin, J., Yurek, S., and Udell, B.J., 2021, SiteOpt: An open-source R-package for site selection and portfolio optimization: Ecography, v. 44, no. 11, p. 1678-1685, https://doi.org/10.1111/ecog.05717.","productDescription":"8 p.","startPage":"1678","endPage":"1685","ipdsId":"IP-119211","costCenters":[{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":450726,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ecog.05717","text":"Publisher Index Page"},{"id":436191,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9S4QV7T","text":"USGS data release","linkHelpText":"Data from SiteOpt: an Open-source R-package for Site Selection and Portfolio Optimization"},{"id":389806,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"11","noUsgsAuthors":false,"publicationDate":"2021-09-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Saghand, Payman G","contributorId":266005,"corporation":false,"usgs":false,"family":"Saghand","given":"Payman","email":"","middleInitial":"G","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":824023,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haider, Zulqarnain","contributorId":216714,"corporation":false,"usgs":false,"family":"Haider","given":"Zulqarnain","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":824024,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Charkhgard, Hadi","contributorId":216710,"corporation":false,"usgs":false,"family":"Charkhgard","given":"Hadi","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":824025,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eaton, Mitchell J. 0000-0001-7324-6333","orcid":"https://orcid.org/0000-0001-7324-6333","contributorId":213526,"corporation":false,"usgs":true,"family":"Eaton","given":"Mitchell","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":824026,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Martin, Julien 0000-0002-7375-129X","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":218445,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":824027,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yurek, Simeon 0000-0002-6209-7915","orcid":"https://orcid.org/0000-0002-6209-7915","contributorId":216738,"corporation":false,"usgs":true,"family":"Yurek","given":"Simeon","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":824028,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Udell, Bradley J. 0000-0001-5225-4959","orcid":"https://orcid.org/0000-0001-5225-4959","contributorId":223440,"corporation":false,"usgs":false,"family":"Udell","given":"Bradley","email":"","middleInitial":"J.","affiliations":[{"id":40715,"text":"Wildlife Ecology and Conservation Department, University of Florida, Gainesville, FL","active":true,"usgs":false}],"preferred":false,"id":824029,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70226497,"text":"70226497 - 2021 - Frequency distribution","interactions":[],"lastModifiedDate":"2021-11-22T14:23:44.401647","indexId":"70226497","displayToPublicDate":"2021-09-22T08:20:57","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Frequency distribution","docAbstract":"Given a numerical dataset, a frequency distribution is a summary displaying fluctuations of an attribute within the range of values. In contrast to an analytical probability distribution, a frequency distribution always deals with empirically observed values (Everitt and Skondall 2010). In general, the larger the number of values, the more useful is the frequency distribution relative to listing all values. Today, multiple software packages allow easy display of a frequency distribution.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of mathematical geosciences","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","doi":"10.1007/978-3-030-26050-7","usgsCitation":"Olea, R., 2021, Frequency distribution, chap. of Encyclopedia of mathematical geosciences, HTML Document, https://doi.org/10.1007/978-3-030-26050-7.","productDescription":"HTML Document","ipdsId":"IP-122768","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":498722,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://pure.qub.ac.uk/en/publications/fce9c7cb-69b5-4b16-9f9a-f81c0c89e272","text":"External Repository"},{"id":391979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":224285,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":827107,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70224321,"text":"70224321 - 2021 - Drought resistance and resilience: The role of soil moisture–plant interactions and legacies in a dryland ecosystem","interactions":[],"lastModifiedDate":"2021-09-22T12:22:40.018062","indexId":"70224321","displayToPublicDate":"2021-09-22T07:18:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Drought resistance and resilience: The role of soil moisture–plant interactions and legacies in a dryland ecosystem","docAbstract":"Bee conservation is a topic of global concern, particularly in agroecosystems where their contribution to crop pollination is highly valued. Over a decade ago, bees and other pollinators were made a priority of the Conservation Reserve Program (CRP), a U.S. federal program that pays land owners to establish a conservation cover, typically grassland, on environmentally sensitive farmland. Despite large financial investment in this program, few studies have measured the benefit of CRP to bees, particularly in complex agroecosystems with abundant alternative forage. To determine if CRP land seeded with pollinator-attractive native flowers and/or introduced legumes provides distinct floral composition that attracts more foraging bees than non-CRP habitats, we compared CRP land to paired non-CRP fields and roadsides at 31 sites in Michigan, U.S.A.. We found CRP land had unique floral species community composition, higher floral abundance, greater species richness, more native floral species, and greater inflorescence coverage. Greater inflorescence coverage on CRP land was associated with a greater abundance of both honey bees and wild bees than either non-CRP fields or roadsides, as was native flower abundance for wild bees. Showy native plant species were important forage resources on CRP land: Monarda fistulosa was the most foraged upon species by both honey bees and wild bees, and goldenrod species were important late-summer forage resources for honey bees. These findings demonstrate the benefit of managing CRP land with herbaceous seed mixes to create dense, showy, native plant communities that provide summer-long resources to both bee groups. Insights from this study could be used to enhance the composition of future conservation program investments and management of non-CRP land to benefit pollinators.