Deeper flows through bedrock in mountain watersheds could be important, but lack of data to characterize bedrock properties limits understanding. To address data scarcity, we combine a previously published integrated hydrologic model of a snow‐dominated, headwater basin of the Colorado River with a new method for dating baseflow age using dissolved gas tracers SF6, CFC‐113, N2, and Ar. The original flow model predicts the majority of groundwater flow through shallow alluvium (<8 m) sitting on top of less permeable bedrock. The water moves too quickly and is unable to reproduce observed SF6 concentrations. To match gas data, bedrock permeability is increased to allow a larger fraction of deeper and older groundwater flow (median 112 m). The updated hydrologic model indicates interannual variability in baseflow age (3–12 years) is controlled by the volume of seasonal interflow and tightly coupled to snow accumulation and monsoon rain. Deeper groundwater flow remains stable (11.7 ± 0.7 years) as a function mean historical recharge to bedrock hydraulic conductivity (R/K). A sensitivity analysis suggests that increasing bedrock K effectively moves this alpine basin away from its original conceptualization of hyperlocalized groundwater flow (high R/K) with groundwater age insensitive to changes in water inputs. Instead, this basin is situated close to the precipitation threshold defining recharge controlled groundwater flow conditions (low R/K) in which groundwater age increases with small reductions in precipitation. Work stresses the need to explore alternative methods characterizing bedrock properties in mountain basins to better quantify deeper groundwater flow and predict their hydrologic response to change.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020WR028161","usgsCitation":"Carroll, R.W., Manning, A.H., Niswonger, R.G., Marchetti, D.W., and Williams, K.H., 2020, Baseflow age distributions and depth of active groundwater flow in a snow‐dominated mountain headwater basin: Water Resources Research, v. 56, no. 12, e2020WR028161, 19 p., https://doi.org/10.1029/2020WR028161.","productDescription":"e2020WR028161, 19 p.","ipdsId":"IP-115011","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":454804,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020wr028161","text":"Publisher Index Page"},{"id":384624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.039306640625,\n 37.00255267215955\n ],\n [\n -106.138916015625,\n 37.00255267215955\n ],\n [\n -106.138916015625,\n 40.98819156349393\n ],\n [\n -109.039306640625,\n 40.98819156349393\n ],\n [\n -109.039306640625,\n 37.00255267215955\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"12","noUsgsAuthors":false,"publicationDate":"2020-12-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Carroll, Rosemary W.H. 0000-0002-9302-8074","orcid":"https://orcid.org/0000-0002-9302-8074","contributorId":178784,"corporation":false,"usgs":false,"family":"Carroll","given":"Rosemary","email":"","middleInitial":"W.H.","affiliations":[],"preferred":false,"id":812816,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manning, Andrew H. 0000-0002-6404-1237 amanning@usgs.gov","orcid":"https://orcid.org/0000-0002-6404-1237","contributorId":1305,"corporation":false,"usgs":true,"family":"Manning","given":"Andrew","email":"amanning@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":812817,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Niswonger, Richard G. 0000-0001-6397-2403 rniswon@usgs.gov","orcid":"https://orcid.org/0000-0001-6397-2403","contributorId":197892,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard","email":"rniswon@usgs.gov","middleInitial":"G.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":812818,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marchetti, David W 0000-0002-1246-0798","orcid":"https://orcid.org/0000-0002-1246-0798","contributorId":255716,"corporation":false,"usgs":false,"family":"Marchetti","given":"David","email":"","middleInitial":"W","affiliations":[{"id":38118,"text":"Western Colorado University","active":true,"usgs":false}],"preferred":false,"id":812819,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Williams, Kenneth H. 0000-0002-3568-1155","orcid":"https://orcid.org/0000-0002-3568-1155","contributorId":176791,"corporation":false,"usgs":false,"family":"Williams","given":"Kenneth","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":812820,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70220896,"text":"70220896 - 2020 - Seabird synthesis","interactions":[],"lastModifiedDate":"2021-06-01T19:35:28.963466","indexId":"70220896","displayToPublicDate":"2020-11-17T14:27:37","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Seabird synthesis","docAbstract":"Overall, the status of seabirds was fair to good in the WGOA in 2020, with limited data available from Middleton Island, Cook Inlet, and the Kodiak Archipelago (Figure 63). Colony attendance remains low in some populations compared to historic levels, and some colonies were newly abandoned. However, when birds did arrive to breed, reproductive success generally appeared fair to good for fish-eating, surface-feeding birds and fish-eating, diving birds. There was spatial variability in colony attendance and reproductive success, with Middleton Island birds performing more strongly than Kodiak Island or Cook Inlet. Middleton Island populations from both these groups experienced their strongest breeding seasons since the marine heatwave began in 2014, suggesting an increase in the availability of small schooling fish in that region of WGOA. No large-scale mortality event was recorded based on monthly beach surveys in the WGOA. This year’s integrated approach to reporting seabird status is less comparable to previous Ecosystem Status Reports, as the Alaska Maritime National Wildlife Refuge’s seabird reproductive success time series were not updated, due to COVID-19 related survey cancellations.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Ecosystem status report 2020 Gulf of Alaska","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"NOAA","usgsCitation":"Arimitsu, M.L., Burgess, H.K., Corcoran, R., Hatch, S., Jones, T., Lindsey, J., Marsteller, C.E., Piatt, J., and Schoen, S.K., 2020, Seabird synthesis, chap. of Ecosystem status report 2020 Gulf of Alaska, p. 121-128.","productDescription":"8 p.","startPage":"121","endPage":"128","ipdsId":"IP-123184","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":386071,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":386016,"type":{"id":15,"text":"Index Page"},"url":"https://archive.fisheries.noaa.gov/afsc/refm/stocks/plan_team/2020/GOAecosys.pdf"}],"country":"United States","state":"Alaska","otherGeospatial":"Cook Inlet, Gulf of Alaska. Kodiak Archipelago, Middleton Island,","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.6103515625,\n 56.255557451930585\n ],\n [\n -147.63427734375,\n 56.255557451930585\n ],\n [\n -147.63427734375,\n 61.845782829572485\n ],\n [\n -155.6103515625,\n 61.845782829572485\n ],\n [\n -155.6103515625,\n 56.255557451930585\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 marimitsu@usgs.gov","orcid":"https://orcid.org/0000-0001-6982-2238","contributorId":140501,"corporation":false,"usgs":true,"family":"Arimitsu","given":"Mayumi","email":"marimitsu@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":816640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burgess, Hillary K.","contributorId":220053,"corporation":false,"usgs":false,"family":"Burgess","given":"Hillary","email":"","middleInitial":"K.","affiliations":[{"id":40123,"text":"School of Aquatic and Fishery Sciences, University of Washington, Seattle, Washington, United States of America","active":true,"usgs":false}],"preferred":false,"id":816727,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Corcoran, Robin","contributorId":242629,"corporation":false,"usgs":false,"family":"Corcoran","given":"Robin","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":816728,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hatch, Scott","contributorId":258853,"corporation":false,"usgs":false,"family":"Hatch","given":"Scott","affiliations":[{"id":52319,"text":"ISRC","active":true,"usgs":false}],"preferred":false,"id":816729,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jones, Tim","contributorId":149501,"corporation":false,"usgs":false,"family":"Jones","given":"Tim","affiliations":[{"id":17757,"text":"U.S. Fish and Wildlife Service, Atlantic Coast Joint Venture","active":true,"usgs":false}],"preferred":false,"id":816730,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lindsey, Jackie","contributorId":203501,"corporation":false,"usgs":false,"family":"Lindsey","given":"Jackie","email":"","affiliations":[{"id":36637,"text":"Moss Landing Marine Laboratories, 8272 Moss Landing Road, Moss Landing, CA 95039 USA","active":true,"usgs":false}],"preferred":false,"id":816731,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Marsteller, Caitlin Elizabeth 0000-0002-2430-0708","orcid":"https://orcid.org/0000-0002-2430-0708","contributorId":251784,"corporation":false,"usgs":true,"family":"Marsteller","given":"Caitlin","email":"","middleInitial":"Elizabeth","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":816642,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Piatt, John F. 0000-0002-4417-5748","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":244053,"corporation":false,"usgs":true,"family":"Piatt","given":"John F.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":816641,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schoen, Sarah K. 0000-0002-5685-5185 sschoen@usgs.gov","orcid":"https://orcid.org/0000-0002-5685-5185","contributorId":5136,"corporation":false,"usgs":true,"family":"Schoen","given":"Sarah","email":"sschoen@usgs.gov","middleInitial":"K.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":816643,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70216405,"text":"ofr20201123 - 2020 - Field comparison of five in situ turbidity sensors","interactions":[],"lastModifiedDate":"2020-11-19T15:03:44.391711","indexId":"ofr20201123","displayToPublicDate":"2020-11-17T10:45:04","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1123","displayTitle":"Field Comparison of Five In Situ Turbidity Sensors","title":"Field comparison of five in situ turbidity sensors","docAbstract":"Five commercially available turbidity sensors were field tested by the U.S. Geological Survey Hydrologic Instrumentation Facility for accuracy and data comparability. The tested sensors were the Xylem EXO (EXO), the Hach Solitax sc (Solitax), the In Situ Aqua TROLL sensor installed onto a TROLL 600 sonde (TROLL 600), the Campbell Scientific OBS501 (OBS501), and the Observator ANALITE NEP–5000 (NEP–5000). The sensors were deployed at Pearl River at National Space Technology Laboratories Station, Mississippi (U.S. Geological Survey site 02492620), and were serviced weekly. In addition to the five in situ turbidity sensors, corresponding discrete samples were collected and analyzed during the evaluation on a calibrated Hach 2100N benchtop turbidimeter. The OBS501 malfunctioned early in the evaluation and eventually failed, resulting in few data from the sensor.
During this study, the four remaining sensors (minus the OBS501) changed similarly throughout the field test; however, sensor data from the EXO consistently demonstrated lower results than the Solitax, TROLL 600, and NEP–5000, possibly because of the variation in raw signal processing among manufacturers. Results from a single factor analysis of variance test and a Tukey Honestly Significant Difference test verified the low bias observed in the EXO data and indicated there was a significant difference between the EXO data and data from the Solitax, TROLL 600, and NEP–5000 but an insignificant difference among the data when the Solitax, TROLL 600, and NEP–5000 were compared to each other.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201123","usgsCitation":"Snazelle, T.T., 2020, Field comparison of five in situ turbidity sensors: U.S. Geological Survey Open-File Report 2020–1123, 15 p., https://doi.org/10.3133/ofr20201123.","productDescription":"Report: iv, 15 p.; Data Release; Dataset","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-103944","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":380549,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1123/ofr20201123.pdf","text":"Report","size":"3.94 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1123"},{"id":380548,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1123/coverthb.jpg"},{"id":380550,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KDERG6","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Turbidity data collected by five in situ sensors at USGS site 02492620 Pearl River at NSTL station, Mississippi, from November 2017 to January 2018"},{"id":380551,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"}],"country":"United States","state":"Mississippi","otherGeospatial":"National Space Technology Laboratories Station","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.0274658203125,\n 30.211608223816906\n ],\n [\n -89.28314208984375,\n 30.211608223816906\n ],\n [\n -89.28314208984375,\n 30.41078179084589\n ],\n [\n -90.0274658203125,\n 30.41078179084589\n ],\n [\n -90.0274658203125,\n 30.211608223816906\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"U.S. Geological Survey
Water Mission Area
12201 Sunrise Valley Drive
Reston, VA 20192
The movement patterns of birds across a landscape are often highly variable and influenced by complex interactions between individuals and environments. Because periods of movement can be marked by high mortality, especially among juvenile birds, understanding these patterns may be vital for the conservation of many bird species. However, these patterns can be challenging to quantify. We used radio‐telemetry to document the movement patterns of ‘Akohekohe (Palmeria dolei), an endangered Hawaiian Honeycreeper endemic to Maui Island, Hawai'i. This species is believed to be highly susceptible to mosquito‐transmitted avian malaria (Plasmodium relictum) and only breeds in high‐elevation wet forests on the windward side of east Maui (> 1715 m) that serve as mosquito‐free refugia. Over a 2‐yr period (2013–2014), we used radio‐telemetry and resightings of color‐banded birds to track the movements of juveniles (N = 11) and adults (N = 24) and quantified home ranges with minimum convex polygons (MCP) and 95% fixed kernels (KHR). Movement patterns and home range sizes of adult and juvenile ‘Akohekohe were significantly different, with adults having relatively small home ranges (0.57 ha, MCP; 1.09 ha, KHR) and juveniles moving greater distances and having larger home ranges (25.02 ha, MCP; 90.56 ha, KHR). Only juveniles moved into lower‐elevation forests that can support mosquito populations, at least seasonally. The absence of adults in this transitional malaria zone suggests that adult ‘Akohekohe cannot maintain long‐term home ranges in areas with an increased risk of malaria infection. In addition, the long‐distance movements of juveniles during the post‐fledging, pre‐breeding period likely increases their risk of contracting avian malaria and could be a key factor limiting the population of this species.
The U.S. Geological Survey monitored dissolved nitrate plus nitrite as nitrogen (N) and dissolved organic carbon (DOC) concentrations and calculated loads of these constituents at the W.P. Franklin Lock and Dam (S-79) from April 2014 to December 2017. Flows from Lake Okeechobee controlled by S-77, S-78 and S-79 affect water quality in the downstream Caloosahatchee River Estuary, where increased nutrients and dissolved organic matter are of concern. Numerous algal blooms have occurred in the Caloosahatchee River and downstream estuaries in recent years (2005–18) and are often attributed to eutrophication. Dissolved nitrate plus nitrite as N (hereafter, referred to as nitrate) data were collected at 15-minute intervals using a submersible ultraviolet optical nitrate sensor. The instrument data were corrected for interferences, as determined by the relation between instrument measurements and 20 concurrent laboratory values. A surrogate model, based on 36 concurrent measurements of DOC, fluorescence of chromophoric dissolved organic matter, and specific conductance, was developed to calculate DOC at 15-minute intervals.
Mean and median calculated nitrate concentrations for the study period (2014–17) were both 0.21 milligram per liter (mg/L). Monthly mean nitrate concentrations ranged from 0.04 mg/L in April 2017 to 0.48 mg/L in November 2015. Monthly mean nitrate concentrations and the proportion of water that was attributed to Lake Okeechobee discharge, released through S-79, were weakly correlated and indicate that the nitrate concentrations typically decreased as the percentage of water released from the lake increased. Annual nitrate loads were 278 metric tons in 2015, 782 metric tons in 2016, and 525 metric tons in 2017. Monthly mean nitrate loads ranged from 1.2 metric tons in April 2017 to 171.3 metric tons in February 2016. Nitrate loads increased linearly with an increase in flow and typically increased during the wet season, May to October. Monthly loads of nitrate were strongly correlated with flow at S-77 and S-79.
Mean and median calculated DOC concentrations for the study period were 18.3 mg/L and 18.9 mg/L, respectively. Monthly mean DOC concentrations ranged from 12.6 mg/L in May 2017 to 21.5 mg/L in September 2015. Generally, DOC concentrations were lower during the dry season months (November to April) and higher during the wet season months. Monthly mean DOC concentrations were moderately correlated with monthly mean flow volumes at S-79. There was a strong correlation between monthly mean DOC concentrations and the proportion of water released at S-79 that can be attributed directly to Lake Okeechobee, indicating that contributions between Moore Haven Lock and Dam (S-77) and S-79 have a higher DOC concentration than water released from Lake Okeechobee. Monthly mean nitrate concentrations and monthly mean DOC concentrations were strongly correlated. Annual loads of DOC were 23,960 metric tons in 2015 and 65,610 metric tons in 2016 (2014 and 2017 data were incomplete). Monthly loads of DOC ranged from 284 metric tons in May 2017 to 15,122 metric tons in September 2017, the latter corresponding to the effects from Hurricane Irma. Monthly loads of DOC were strongly correlated with flow at S-77 and S-79.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201094","collaboration":"USGS Greater Everglades Priority Ecosystem Science Program","usgsCitation":"Booth, A., 2020, Measured and calculated nitrate and dissolved organic carbon concentrations and loads at the W.P. Franklin Lock and Dam, S-79, south Florida, 2014-17: U.S. Geological Survey Open-File Report 2020-1094, 37 p., https://doi.org/10.3133/ofr20201094.","productDescription":"Report: vi, 37 p.; Data Release","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-091619","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":380478,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1094/coverthb.jpg"},{"id":380479,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1094/ofr20201094.pdf","text":"Report","size":"3.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1094"},{"id":380480,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V4ZGWU","text":"USGS data release","linkHelpText":"Calculated carbon concentrations, Franklin Lock and Dam (S-79) southern Florida, 2014-2017"}],"country":"United States","state":"Florida","otherGeospatial":"W.P. Franklin Lock and Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.7437744140625,\n 26.701452590314368\n ],\n [\n -81.47735595703125,\n 26.701452590314368\n ],\n [\n -81.47735595703125,\n 26.74683674289727\n ],\n [\n -81.7437744140625,\n 26.74683674289727\n ],\n [\n -81.7437744140625,\n 26.701452590314368\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Many canyon‐bound rivers have been dammed and downstream flow and water temperatures modified. Climate change is expected to cause lower storage in reservoirs and warmer release temperatures, which may further alter downstream flow and thermal regimes. To anticipate potential future changes, we first need to understand the dominant heat transfer mechanisms in canyon‐bound river systems. Towards this end, we adapt a dynamic process‐based river routing and temperature model to account for complex shading and radiation characteristics found in canyon‐bound rivers. We apply the model to a 362 km segment of the Colorado River in Grand Canyon National Park, USA to simulate temperature over an 18‐year period. Extensive temperature and flow datasets from within the canyon were used to assess model performance. At the most downstream gaging location, root mean square errors of hourly flow routing and temperature predictions were 11.5 m3/s and 0.93 °C, respectively. We found that heat fluxes controlling temperatures were highly variable over space and time, primarily due to shortwave radiation dynamics and hydropeaking flow conditions. Additionally, the large differences between air and water temperature during summer periods resulted in high sensible and latent heat fluxes. Sensitivity analyses indicate that reservoir release temperatures are most influential above the RM88 gage (141 kilometers below Glen Canyon Dam), while a combination of discharge, shortwave radiation, and air temperature become more important farther downstream. This study illustrates the importance of understanding the spatial and temporal variability of topographic shading when predicting water temperatures in canyon‐bound rivers.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020WR027566","usgsCitation":"Mihalevich, B.A., Neilson, B., Buahin, C.A., Yackulic, C., and Schmidt, J.C., 2020, Water temperature controls for regulated canyon-bound rivers: Water Resources Research, v. 56, e2020WR027566, 24 p., https://doi.org/10.1029/2020WR027566.","productDescription":"e2020WR027566, 24 p.","ipdsId":"IP-117871","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":381103,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Colorado River, Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.961181640625,\n 35.639441068973944\n ],\n [\n -111.29150390625,\n 35.639441068973944\n ],\n [\n -111.29150390625,\n 36.923547681089296\n ],\n [\n -113.961181640625,\n 36.923547681089296\n ],\n [\n -113.961181640625,\n 35.639441068973944\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","noUsgsAuthors":false,"publicationDate":"2020-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Mihalevich, Bryce A.","contributorId":245512,"corporation":false,"usgs":false,"family":"Mihalevich","given":"Bryce","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":806340,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neilson, Bethany","contributorId":178798,"corporation":false,"usgs":false,"family":"Neilson","given":"Bethany","affiliations":[],"preferred":false,"id":806341,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buahin, Caleb A.","contributorId":245514,"corporation":false,"usgs":false,"family":"Buahin","given":"Caleb","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":806342,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":806343,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmidt, John C.","contributorId":207751,"corporation":false,"usgs":false,"family":"Schmidt","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":37627,"text":"Department of Watershed Sciences, Utah State University, Logan, UT, USA","active":true,"usgs":false}],"preferred":false,"id":806344,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228678,"text":"70228678 - 2020 - Increased typhoon activity in the Pacific deep tropics driven by Little Ice Age circulation changes","interactions":[],"lastModifiedDate":"2022-02-16T15:34:39.786634","indexId":"70228678","displayToPublicDate":"2020-11-16T08:57:14","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Increased typhoon activity in the Pacific deep tropics driven by Little Ice Age circulation changes","docAbstract":"The instrumental record reveals that tropical cyclone activity is sensitive to oceanic and atmospheric variability on inter-annual and decadal scales. However, our understanding of the influence of climate on tropical cyclone behaviour is restricted by the short historical record and the sparseness of prehistorical reconstructions, particularly in the western North Pacific, where coastal communities suffer loss of life and livelihood from typhoons annually. Here, to explore past regional typhoon dynamics, we reconstruct three millennia of deep tropical North Pacific cyclogenesis. Combined with existing records, our reconstruction demonstrates that low-baseline typhoon activity prior to 1350 CE was followed by an interval of frequent storms during the Little Ice Age. This pattern, concurrent with hydroclimate proxy variability, suggests a centennial-scale link between Pacific hydroclimate and tropical cyclone climatology. An ensemble of global climate models demonstrates a migration of the Pacific Walker circulation and variability in two Pacific climate modes during the Little Ice Age, which probably contributed to enhanced tropical cyclone activity in the tropical western North Pacific. In the next century, projected changes to the Pacific Walker circulation and expansion of the tropics will invert these Little Ice Age hydroclimate trends, potentially reducing typhoon activity in the deep tropical Pacific.
","language":"English","publisher":"Nature Publications","doi":"10.1038/s41561-020-00656-2","usgsCitation":"Bramante, J.F., Ford, M., Kench, P., Ashton, A., Toomey, M., Sullivan, R., Karnauskas, K., Ummenhofer, C.C., and Donnelly, J.P., 2020, Increased typhoon activity in the Pacific deep tropics driven by Little Ice Age circulation changes: Nature Geoscience, v. 13, p. 806-811, https://doi.org/10.1038/s41561-020-00656-2.","productDescription":"6 p.","startPage":"806","endPage":"811","ipdsId":"IP-120405","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":467271,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/26505","text":"External Repository"},{"id":396015,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"South Pacific Ocean","volume":"13","noUsgsAuthors":false,"publicationDate":"2020-11-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Bramante, James F","contributorId":245127,"corporation":false,"usgs":false,"family":"Bramante","given":"James","email":"","middleInitial":"F","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":835005,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ford, Murray","contributorId":224308,"corporation":false,"usgs":false,"family":"Ford","given":"Murray","email":"","affiliations":[{"id":40855,"text":"UA","active":true,"usgs":false}],"preferred":false,"id":835006,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kench, Paul","contributorId":248315,"corporation":false,"usgs":false,"family":"Kench","given":"Paul","email":"","affiliations":[{"id":49849,"text":"Simon Frazier U.","active":true,"usgs":false}],"preferred":false,"id":835007,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ashton, Andrew","contributorId":184098,"corporation":false,"usgs":false,"family":"Ashton","given":"Andrew","affiliations":[],"preferred":false,"id":835008,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Toomey, Michael 0000-0003-0167-9273 mtoomey@usgs.gov","orcid":"https://orcid.org/0000-0003-0167-9273","contributorId":184097,"corporation":false,"usgs":true,"family":"Toomey","given":"Michael","email":"mtoomey@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":835009,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sullivan, Richard","contributorId":211625,"corporation":false,"usgs":false,"family":"Sullivan","given":"Richard","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":835010,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Karnauskas, Kristopher","contributorId":279498,"corporation":false,"usgs":false,"family":"Karnauskas","given":"Kristopher","email":"","affiliations":[{"id":36627,"text":"University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":835011,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ummenhofer, Caroline C. 0000-0002-9163-3967","orcid":"https://orcid.org/0000-0002-9163-3967","contributorId":223139,"corporation":false,"usgs":false,"family":"Ummenhofer","given":"Caroline","email":"","middleInitial":"C.","affiliations":[{"id":40678,"text":"University of New South Wales; Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":835012,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Donnelly, Jeffrey P.","contributorId":192783,"corporation":false,"usgs":false,"family":"Donnelly","given":"Jeffrey","email":"","middleInitial":"P.","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false}],"preferred":false,"id":835013,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70216704,"text":"70216704 - 2020 - Along-margin variations in breakup volcanism at the Eastern North American Margin","interactions":[],"lastModifiedDate":"2020-12-01T13:29:05.858719","indexId":"70216704","displayToPublicDate":"2020-11-16T07:22:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Along-margin variations in breakup volcanism at the Eastern North American Margin","docAbstract":"We model the magnetic signature of rift-related volcanism to understand the distribution and volumeofmagmatic activity that occurred during the breakup of Pangaea and early Atlantic opening at the Eastern North American Margin (ENAM).Along-strike variations in the amplitude and character of the prominent East Coast Magnetic Anomaly (ECMA) suggest that the emplacement of the volcanic layers producing this anomaly similarly varied along the margin. We use three-dimensional magnetic forward modeling constrained by seismic interpretationsto identify along-margin variations in volcanic thickness and width that can explain the observed amplitude and character of the ECMA. Our model results suggest that the ECMA is produced by a combination of both first-order (~600-1000 km)and second-order (~50-31100 km) magmatic segmentation. The first-order magmatic segmentation could have resulted from preexisting variations in crustal thickness and rheology developed during the tectonic amalgamation of Pangaea. The second-order magmatic segmentation developed during continental breakup and likely influenced the segmentation and transform fault spacing of the initial, and modern, Mid-Atlantic Ridge. These variations in magmatism showhow extension and thermal weakening was distributed at the ENAM during continental breakup and how this breakup magmatism was related to both previous and subsequent Wilson Cycle stages.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB020040","usgsCitation":"Greene, J., Tominaga, M., and Miller, N.C., 2020, Along-margin variations in breakup volcanism at the Eastern North American Margin: Journal of Geophysical Research, v. 125, no. 12, e2020JB020040, https://doi.org/10.1029/2020JB020040.","productDescription":"e2020JB020040","ipdsId":"IP-123067","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454811,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2020jb020040","text":"External Repository"},{"id":380905,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"East Coast of United States, Atlantic Ocean","geographicExtents":"{ \"type\": \"FeatureCollection\",\n\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.5859375,\n 32.24997445586331\n ],\n [\n -67.8515625,\n 32.24997445586331\n ],\n [\n -67.8515625,\n 44.08758502824516\n ],\n [\n -75.5859375,\n 44.08758502824516\n ],\n [\n -75.5859375,\n 32.24997445586331\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"125","issue":"12","noUsgsAuthors":false,"publicationDate":"2020-11-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Greene, John A. 0000-0002-4310-602X","orcid":"https://orcid.org/0000-0002-4310-602X","contributorId":200999,"corporation":false,"usgs":false,"family":"Greene","given":"John A.","affiliations":[],"preferred":false,"id":805943,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tominaga, Masako 0000-0002-1169-4146","orcid":"https://orcid.org/0000-0002-1169-4146","contributorId":200937,"corporation":false,"usgs":false,"family":"Tominaga","given":"Masako","email":"","affiliations":[],"preferred":false,"id":805944,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Nathaniel C. 0000-0003-3271-2929 ncmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-3271-2929","contributorId":174592,"corporation":false,"usgs":true,"family":"Miller","given":"Nathaniel","email":"ncmiller@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":805945,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70216429,"text":"70216429 - 2020 - Cortisol is an osmoregulatory and glucose-regulating hormone in Atlantic sturgeon, a basal ray-finned fish","interactions":[],"lastModifiedDate":"2020-11-18T13:08:33.014524","indexId":"70216429","displayToPublicDate":"2020-11-16T07:06:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2275,"text":"Journal of Experimental Biology","active":true,"publicationSubtype":{"id":10}},"title":"Cortisol is an osmoregulatory and glucose-regulating hormone in Atlantic sturgeon, a basal ray-finned fish","docAbstract":"Our current understanding of the hormonal control of ion regulation in aquatic vertebrates comes primarily from studies on teleost fishes, with relatively little information on more basal fishes. We investigated the role of cortisol in regulating seawater tolerance and its underlying mechanisms in an anadromous chondrostean, the Atlantic sturgeon (Acipenser oxyrinchus). Exposure of freshwater-reared Atlantic sturgeon to seawater (25 ppt) resulted in transient (1–3 day) increases in plasma chloride, cortisol and glucose levels and long-term (6–14 day) increases in the abundance of gill Na+/K+/2Cl− cotransporter (NKCC), which plays a critical role in salt secretion in teleosts. The abundance of gill V-type H+-ATPase, which is thought to play a role in ion uptake in fishes, decreased after exposure to seawater. Gill Na+/K+-ATPase activity did not increase in 25 ppt seawater, but did increase in fish gradually acclimated to 30 ppt. Treatment of Atlantic sturgeon in freshwater with exogenous cortisol resulted in dose-dependent increases in cortisol, glucose and gill NKCC and H+-ATPase abundance. Our results indicate that cortisol has an important role in regulating mechanisms for ion secretion and uptake in sturgeon and provide support for the hypothesis that control of osmoregulation and glucose by corticosteroids is a basal trait of jawed vertebrates.
The salinity structure in an estuary is controlled by time‐dependent mixing processes. However, the locations and temporal variability of where significant mixing occurs is not well‐understood. Here we utilize a tracer variance approach to demonstrate the spatial and temporal structure of salinity mixing in the Hudson River Estuary. We run a 4‐month hydrodynamic simulation of the tides, currents, and salinity that captures the spring‐neap tidal variability as well as wind‐driven and freshwater flow events. On a spring‐neap time scale, salinity variance dissipation (mixing) occurs predominantly during the transition from neap to spring tides. On a tidal time scale, 60% of the salinity variance dissipation occurs during ebb tides and 40% during flood tides. Spatially, mixing during ebbs occurs primarily where lateral bottom salinity fronts intersect the bed at the transition from the main channel to adjacent shoals. During ebbs, these lateral fronts form seaward of constrictions located at multiple locations along the estuary. During floods, mixing is generated by a shear layer elevated in the water column at the top of the mixed bottom boundary layer, where variations in the along channel density gradients locally enhance the baroclinic pressure gradient leading to stronger vertical shear and more mixing. For both ebb and flood, the mixing occurs at the location of overlap of strong vertical stratification and eddy diffusivity, not at the maximum of either of those quantities. This understanding lends a new insight to the spatial and time dependence of the estuarine salinity structure.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JC016096","usgsCitation":"Warner, J., Geyer, W.R., Ralston, D.K., and Kalra, T., 2020, Using tracer variance decay to quantify variability of salinity mixing in the Hudson River Estuary: Journal of Geophysical Research, Oceans, v. 125, no. 12, e2020JC016096, 18 p., https://doi.org/10.1029/2020JC016096.","productDescription":"e2020JC016096, 18 p.","ipdsId":"IP-117991","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454821,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020jc016096","text":"Publisher Index Page"},{"id":382091,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Hudson River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.03137207031247,\n 40.551374198715166\n ],\n [\n -73.74023437499999,\n 40.551374198715166\n ],\n [\n -73.74023437499999,\n 42.90413649491736\n ],\n [\n -74.03137207031247,\n 42.90413649491736\n ],\n [\n -74.03137207031247,\n 40.551374198715166\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"125","issue":"12","noUsgsAuthors":false,"publicationDate":"2020-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":807929,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Geyer, W Rockwill 0000-0001-9030-1744","orcid":"https://orcid.org/0000-0001-9030-1744","contributorId":247570,"corporation":false,"usgs":false,"family":"Geyer","given":"W","email":"","middleInitial":"Rockwill","affiliations":[{"id":49582,"text":"Woods Hole Oceanographic Institution, Applied Ocean Physics and Engineering Department, MS #11, Woods Hole, MA,","active":true,"usgs":false}],"preferred":false,"id":807930,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ralston, David K. 0000-0002-0774-3101","orcid":"https://orcid.org/0000-0002-0774-3101","contributorId":195909,"corporation":false,"usgs":false,"family":"Ralston","given":"David","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":807931,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kalra, Tarandeep S. 0000-0001-5468-248X tkalra@usgs.gov","orcid":"https://orcid.org/0000-0001-5468-248X","contributorId":178820,"corporation":false,"usgs":true,"family":"Kalra","given":"Tarandeep S.","email":"tkalra@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":807932,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216487,"text":"70216487 - 2020 - Stable isotope dynamics of herbivorous reef fishes and their ectoparasites","interactions":[],"lastModifiedDate":"2020-11-23T14:24:50.172104","indexId":"70216487","displayToPublicDate":"2020-11-14T08:18:24","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"Stable isotope dynamics of herbivorous reef fishes and their ectoparasites","docAbstract":"Acanthurids (surgeonfishes) are an abundant and diverse group of herbivorous fishes on coral reefs. While their contribution to trophic linkages and dynamics in coral reef systems has received considerable attention, the role of linkages involving their parasites has not. As both consumers of fish tissue and prey to microcarnivores, external parasites may play a significant role in trophic transfer between primary consumers (and hence their predominantly algae-based diet) and the broader coral reef community. Stable isotope analysis is a common tool for studying trophic linkages which can be used for studies involving parasites. We examined the stable isotope ecology (13C and 15N) of copepod (Caligus atromaculatus) and monogenean (Neobenedenia sp.) ectoparasites collected from two species of Caribbean acanthurids (Acanthurus coeruleus and Acanthurus bahianus). There were significant intraspecific differences in isotope discrimination factors between parasites collected from the two different host species as well as interspecific differences between parasites collected from the same host species. Discrimination factors for 15N were consistently positive but varied in magnitude depending on host and parasite species and were slightly lower than what would be expected for consumers. The 13C discrimination factors for both monogeneans and copepods collected from A. coeruleus were consistently positive but were negative for copepods collected from A. bahianus. These findings emphasize the complexity of the stable isotope trophic interactions occurring between parasites and their hosts, highlighting the value of these types of host-parasite isotopic studies.
","language":"English","publisher":"MDPI","doi":"10.3390/d12110429","usgsCitation":"Jenkins, W., Demopoulos, A., Nicholson, M.C., and Sikkel, P.C., 2020, Stable isotope dynamics of herbivorous reef fishes and their ectoparasites: Diversity, v. 12, no. 11, 429, 20 p., https://doi.org/10.3390/d12110429.","productDescription":"429, 20 p.","ipdsId":"IP-121817","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":454824,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d12110429","text":"Publisher Index Page"},{"id":436718,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QE4FW6","text":"USGS data release","linkHelpText":"Stable isotope dynamics of herbivorous reef fishes and their ectoparasites: 2012, 2013, 2018"},{"id":380682,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"British Virgin Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -65.06858825683594,\n 18.281518235308905\n ],\n [\n -64.63050842285156,\n 18.281518235308905\n ],\n [\n -64.63050842285156,\n 18.405351676442407\n ],\n [\n -65.06858825683594,\n 18.405351676442407\n ],\n [\n -65.06858825683594,\n 18.281518235308905\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Jenkins, William 0000-0001-5133-2628 wjenkins@usgs.gov","orcid":"https://orcid.org/0000-0001-5133-2628","contributorId":206535,"corporation":false,"usgs":true,"family":"Jenkins","given":"William","email":"wjenkins@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":805391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Demopoulos, Amanda 0000-0003-2096-4694","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":219234,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":805392,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nicholson, Matthew C.","contributorId":169813,"corporation":false,"usgs":false,"family":"Nicholson","given":"Matthew","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":805393,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sikkel, Paul C.","contributorId":140403,"corporation":false,"usgs":false,"family":"Sikkel","given":"Paul","email":"","middleInitial":"C.","affiliations":[{"id":13476,"text":"Arkansas State University, State University, AR","active":true,"usgs":false}],"preferred":false,"id":805394,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216172,"text":"sir20205109 - 2020 - Reducing leaf litter contributions of phosphorus and nitrogen to urban stormwater through municipal leaf collection and street cleaning practices","interactions":[],"lastModifiedDate":"2020-11-13T21:31:12.15837","indexId":"sir20205109","displayToPublicDate":"2020-11-13T14:32:36","publicationYear":"2020","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":"2020-5109","displayTitle":"Reducing Leaf Litter Contributions of Phosphorus and Nitrogen to Urban Stormwater through Municipal Leaf Collection and Street Cleaning Practices","title":"Reducing leaf litter contributions of phosphorus and nitrogen to urban stormwater through municipal leaf collection and street cleaning practices","docAbstract":"As the boundaries of urban land use continue to expand, environmental managers are looking for innovative ways to reduce export of nutrients from urban sources. Municipal services such as leaf collection and street cleaning have the potential to reduce nutrient pollution at its source while continuing to offer services valued by residents. This study characterized reductions of total and dissolved forms of phosphorus and nitrogen in stormwater runoff from paired catchments, testing the method and frequency of municipal leaf collection and street cleaning programs.
Overall, the performance of municipal programs was related to the frequency and not the form of treatment. Catchments receiving a weekly street cleaning by a regenerative-air street cleaner had the highest reduction in phosphorus load, ranging from 65 to 71 percent (probability value [p] is less than 0.05) for total phosphorus and 57 to 70 percent (p is less than 0.05) for dissolved phosphorus, regardless of leaf collection method or frequency. Reduction in nitrogen load was generally mixed, with many of the catchments showing no statistically significant changes after treatment. In general, nutrient concentrations, and subsequent percent reduction of nutrient loads, were positively correlated with street tree canopy. Collection of only leaf piles, leaving streets unswept, showed no significant reduction in loads of total or dissolved phosphorus and an 83 percent increase in load of total nitrogen. The majority of nutrient concentrations were in the dissolved fraction making source control through leaf collection and street cleaning more effective at reducing the amount of dissolved nutrients in stormwater runoff than structural practices such as wet detention ponds. Based on the results of this study, municipal leaf management programs would be most effective with weekly street cleaning in areas of high street tree canopy, whereas the method and frequency of leaf pile collection is of less importance to the mitigation of nutrients in stormwater runoff.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205109","collaboration":"Prepared in cooperation with the Wisconsin Department of Natural Resources, the City of Madison, Fund for Lake Michigan, Yahara Watershed Improvement Network, Dane County Land and Water Resources, Clean Lakes Alliance, League of Wisconsin Municipalities, and DuPage River Salt Creek Workgroup","usgsCitation":"Selbig, W.R., Buer, N.H., Bannerman, R.T., and Gaebler, P., 2020, Reducing leaf litter contributions of phosphorus and nitrogen to urban stormwater through municipal leaf collection and street cleaning practices: U.S. Geological Survey Scientific Investigations Report 5109, 17 p., https://doi.org/10.3133/sir20205109.","productDescription":"Report: iv, 17 p.; Appendix; Data Release","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-116819","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":380292,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93L2WM1","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Stormwater-quality data in the control and test catchments during the calibration and treatment phase of a leaf collection study in Madison, Fond du Lac, and Oshkosh, Wisconsin, from September 2016 through November 2019"},{"id":380291,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5109/sir20205109_appendix_1.pdf","text":"Appendix 1","size":"1.67 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5109 Appendix 1","linkHelpText":"— Paired-Basin Nutrient Loads in the Control and Test Catchments During Calibration and Treatment Phases"},{"id":380289,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5109/coverthb.jpg"},{"id":380290,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5109/sir20205109.pdf","text":"Report","size":"2.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5109"}],"country":"United States","state":"Wisconsin","city":"Fond du Lac, Madison, Oshkosh","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.49462890625,\n 42.98154421882687\n ],\n [\n -89.27490234375,\n 42.98154421882687\n ],\n [\n -89.27490234375,\n 43.1405770781429\n ],\n [\n -89.49462890625,\n 43.1405770781429\n ],\n [\n -89.49462890625,\n 42.98154421882687\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.505859375,\n 43.71354951931429\n ],\n [\n -88.37814331054688,\n 43.71354951931429\n ],\n [\n -88.37814331054688,\n 43.804800966308385\n ],\n [\n -88.505859375,\n 43.804800966308385\n ],\n [\n -88.505859375,\n 43.71354951931429\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.61160278320312,\n 43.95822503841972\n ],\n [\n -88.50723266601562,\n 43.95822503841972\n ],\n [\n -88.50723266601562,\n 44.050089820756796\n ],\n [\n -88.61160278320312,\n 44.050089820756796\n ],\n [\n -88.61160278320312,\n 43.95822503841972\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
The U.S. Geological Survey, in cooperation with the Connecticut Department of Public Health, conducted a study to determine the presence of arsenic and uranium in private drinking water wells in Connecticut. Samples were collected during 2013–18 from wells completed in 115 geologic units, with 2,433 samples analyzed for arsenic and 2,191 samples analyzed for uranium. The study concluded four major findings.
Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
Given the importance of crayfish in stream ecosystems, gaining insight into the role of stream permanence in maintaining predator–prey interactions is critical. Our objectives were to determine the influence of stream permanence and season on crayfish predation and assess the role of stream permanence and crayfish density on the presence of predators, while accounting for imperfect detection. We conducted surveys of crayfish density, mammalian scat, and environmental variables within 10 intermittent and 10 permanent streams in the Ozark Highlands. We used occupancy modeling to assess the relationship between predator presence, crayfish density, and environmental variables. Stream permanence did not play a role in determining relative frequency of occurrence or percent volume of crayfish prey in mammalian diets. However, percent volume and relative frequency of crayfish prey found in scats differed by season, with both highest in spring and summer. The relative frequency and percent volume of fish prey showed a significant interaction of season by stream permanence, which may be the first instance of this observation. Procyon lotor (Raccoon) had the highest detection probability (p = 0.39), whereas Neovison vison (American Mink; p = 0.15) and Lontra canadensis (River Otter; p = 0.03) had low detection probabilities. Further study into predator–prey interactions in the context of hydrology, particularly when related to imperiled groups like freshwater crayfishes, is needed since climate change is expected to alter hydrologic patterns.
No abstract available.
","language":"English","publisher":"Wiley","doi":"10.1002/lob.10411","usgsCitation":"Meyer, M.F., and Zwart, J.A., 2020, Virtual summit: Incorporating data science and open science in aquatic research: Limnology and Oceanography Bulletin, v. 29, no. 4, p. 144-146, https://doi.org/10.1002/lob.10411.","productDescription":"3 p.","startPage":"144","endPage":"146","ipdsId":"IP-122703","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":454829,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lob.10411","text":"Publisher Index Page"},{"id":420063,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-11-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Meyer, Michael F. 0000-0002-8034-9434","orcid":"https://orcid.org/0000-0002-8034-9434","contributorId":244065,"corporation":false,"usgs":false,"family":"Meyer","given":"Michael","email":"","middleInitial":"F.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":880911,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":880912,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216418,"text":"70216418 - 2020 - Improving the ability to include freshwater wetland plants in process-based models","interactions":[],"lastModifiedDate":"2020-11-18T00:14:07.890099","indexId":"70216418","displayToPublicDate":"2020-11-12T11:27:18","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2456,"text":"Journal of Soil and Water Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Improving the ability to include freshwater wetland plants in process-based models","docAbstract":"Considerable effort and resources have been placed into conservation programs designed to reduce or alleviate negative environmental effects of crop production and into evaluation of the benefits of these programs. Wetlands are an important source of ecosystem services, but modeling wetland plants is an emerging science. To date, wetland plant growth has not been explicitly accounted for in ecosystem service models that quantify conservation program effects. As part of an effort to more accurately simulate wetland plants within process-based models, we expanded upon plant growth data collected in an earlier effort with additional sampling at two of four previously sampled areas, and included a fifth sampling site. We then used data from the five sites spanning five years as wetland plant parameters at both the species and functional group levels for the Agricultural Land Management Alternative with Numerical Assessment Criteria (ALMANAC) model. In addition to individual species, modelers are interested in functional groups representing a collection of species because it is unrealistic to model every species occurring in an ecosystem. ALMANAC simulations were completed at three sites for both individual wetland plant species and functional groups. At each site, simulated plant yields were within 1 Mg ha–1 (±7%) of measured values (r2 = 0.99). Multisite species simulated yields were within 37% of measured values (r2 = 0.95). Functional groups performed as well as individual species simulations. Functional group simulated yields were within 1 Mg ha–1 (±5%) of measured yields. Plant growth is a major component of these wetland ecosystems, and ALMANAC verified wetland plant parameters support more accurate assessments of conservation programs and practices on the influence of wetland ecosystems embedded within agricultural fields. The improved plant parameters we provide here will be transferred to other process-based models that focus on other ecosystem components such as soil and water effects, facilitating wetland evaluations across the United States and elsewhere.
The relationship between people and wildfire has always been paradoxical: fire is an essential ecological process and management tool, but can also be detrimental to life and property. Consequently, fire regimes have been modified throughout history through both intentional burning to promote benefits and active suppression to reduce risks. Reintroducing fire and its benefits back into the Sky Island mountains of the United States-Mexico borderlands has the potential to reduce adverse effects of altered fire regimes and build resilient ecosystems and human communities. To help guide regional fire restoration, we describe the frequency and severity of recent fires over a 32-year period (1985-2017) across a vast binational region in the United States-Mexico borderlands and assess variation in fire frequency and severity across climate gradients and in relation to vegetation and land tenure classes. We synthesize relevant literature on historical fire regimes within 9 major vegetation types and assess how observed contemporary fire characteristics vary from expectations based on historical patterns. Less than 28% of the study area burned during the observation period, excluding vegetation types in warmer climates that are not adapted to fire (eg, Desertscrub and Thornscrub). Average severity of recent fires was low despite some extreme outliers in cooler, wetter environments. Midway along regional temperature and precipitation gradients, approximately 64% of Pine-Oak Forests burned at least once, with fire frequencies that mainly corresponded to historical expectations on private lands in Mexico but less so on communal lands, suggesting the influence of land management. Fire frequency was higher than historical expectations in extremely cool and wet environments that support forest types such as Spruce-Fir, indicating threats to these systems possibly attributable to drought and other factors. In contrast, fires were absent or infrequent across large areas of Woodlands (~73% unburned) and Grasslands (~88% unburned) due possibly to overgrazing, which reduces abundance and continuity of fine fuels needed to carry fire. Our findings provide a new depiction of fire regimes in the Sky Islands that can help inform fire management, restoration, and regional conservation planning, fostered by local and traditional knowledge and collaboration among landowners and managers.
","language":"English","publisher":"Sage Journals","doi":"10.1177/1178622120969191","usgsCitation":"Villarreal, M.L., Iniguez, J.M., Flesch, A.D., Sanderlin, J.S., Cortes Montano, C., Conrad, C.R., and Haire, S.L., 2020, Contemporary fire regimes provide a critical perspective on restoration needs in the Mexico-United States borderlands: Air, Soil and Water Research, v. 13, p. 1-18, https://doi.org/10.1177/1178622120969191.","productDescription":"18 p.","startPage":"1","endPage":"18","ipdsId":"IP-117669","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":454834,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/1178622120969191","text":"Publisher Index Page"},{"id":436720,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99S0I9W","text":"USGS data release","linkHelpText":"Differenced Normalized Burn Ratio (dNBR) data of wildfires in the Sky Island Mountains of the southwestern US and northern Mexico from 2011-2017"},{"id":380988,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Arizona, Sonora","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.796875,\n 29.036960648558267\n ],\n [\n -108.984375,\n 29.036960648558267\n ],\n [\n -108.984375,\n 33.54139466898275\n ],\n [\n -111.796875,\n 33.54139466898275\n ],\n [\n -111.796875,\n 29.036960648558267\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2020-11-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":806073,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iniguez, Jose M. 0000-0002-4566-1297","orcid":"https://orcid.org/0000-0002-4566-1297","contributorId":213972,"corporation":false,"usgs":false,"family":"Iniguez","given":"Jose","email":"","middleInitial":"M.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":806074,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flesch, Aaron D. 0000-0003-3434-0778","orcid":"https://orcid.org/0000-0003-3434-0778","contributorId":245372,"corporation":false,"usgs":false,"family":"Flesch","given":"Aaron","email":"","middleInitial":"D.","affiliations":[{"id":49169,"text":"School of Natural Resources and the Environment and The Desert Laboratory on Tumamoc Hill, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":806075,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sanderlin, Jamie S. 0000-0001-8651-9804","orcid":"https://orcid.org/0000-0001-8651-9804","contributorId":245373,"corporation":false,"usgs":false,"family":"Sanderlin","given":"Jamie","email":"","middleInitial":"S.","affiliations":[{"id":49171,"text":"US Forest Service, Rocky Mountain Research Station, Flagstaff, Arizona","active":true,"usgs":false}],"preferred":false,"id":806076,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cortes Montano, Citlali 0000-0002-1916-1985","orcid":"https://orcid.org/0000-0002-1916-1985","contributorId":213973,"corporation":false,"usgs":false,"family":"Cortes Montano","given":"Citlali","email":"","affiliations":[{"id":38945,"text":"Universidad Juárez del Estado de Durango","active":true,"usgs":false}],"preferred":false,"id":806077,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Conrad, Caroline Rose 0000-0002-0496-8081","orcid":"https://orcid.org/0000-0002-0496-8081","contributorId":236945,"corporation":false,"usgs":true,"family":"Conrad","given":"Caroline","email":"","middleInitial":"Rose","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":806078,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Haire, Sandra L. 0000-0002-5356-7567","orcid":"https://orcid.org/0000-0002-5356-7567","contributorId":213971,"corporation":false,"usgs":false,"family":"Haire","given":"Sandra","email":"","middleInitial":"L.","affiliations":[{"id":32362,"text":"Haire Laboratory for Landscape Ecology","active":true,"usgs":false}],"preferred":false,"id":806079,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70216182,"text":"sir20205101 - 2020 - Ungulate migrations of the western United States, Volume 1","interactions":[],"lastModifiedDate":"2025-02-25T15:42:29.878133","indexId":"sir20205101","displayToPublicDate":"2020-11-12T09:50:00","publicationYear":"2020","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":"2020-5101","displayTitle":"Ungulate Migrations of the Western United States, Volume 1","title":"Ungulate migrations of the western United States, Volume 1","docAbstract":"Across the western United States, many ungulate herds must migrate seasonally to access resources and avoid harsh winter conditions. Because these migration paths cover vast landscapes (in other words migration distances up to 150 miles [241 kilometers]), they are increasingly threatened by roads, fencing, subdivisions, and other development. Over the last decade, many new tracking studies have been conducted on migratory herds, and analytical methods have been developed that allow for population-level corridors and stopovers to be mapped and prioritized. In 2018, the U.S. Geological Survey assembled a Corridor Mapping Team to provide technical assistance to western states working to map bison, elk, moose, mule deer, and pronghorn migrations using existing Global Positioning System data. Led by the Wyoming Cooperative Fish and Wildlife Research Unit, the team consists of federal scientists, university researchers, and biologists and analysts from participating state agencies.
In its first year, the team has worked to develop standardized analytical and computational methods and a workflow applicable to datasets typically collected by state agencies. In 2019, the team completed analyses necessary to map corridors, stopovers, routes and winter ranges in Arizona, Idaho, Nevada, Utah, and Wyoming. A total of 26 corridors, 16 migration routes, 25 stopovers, and 9 winter ranges were mapped across these states and are included in this report. This report and associated data release provide the means for the habitats required for migration to be taken into account by state and federal transportation officials, land and wildlife managers, planners, and other conservationists working to maintain big-game migration in the western states.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205101","issn":"2328-031X; 2328-0328","isbn":"978-1-4113-4379-5","usgsCitation":"Kauffman, M.J., Copeland, H.E., Berg, J., Bergen, S., Cole, E., Cuzzocreo, M., Dewey, S., Fattebert, J., Gagnon, Gelzer, E., Geremia, C., Graves, T., Hersey, K., Hurley, M., Kaiser, J., Meacham, J., Merkle, J., Middleton, A., Nuñez, T., Oates, B., Olson, D., Olson, L., Sawyer, H., Schroeder, C., Sprague, S., Steingisser, A., Thonhoff, M., 2020, Ungulate migrations of the western United States, Volume 1 (ver. 1.1, December 2023): U.S. Geological Survey Scientific Investigations Report 2020–5101, 119 p., https://doi.org/10.3133/sir20205101.","productDescription":"Report: xiv, 119 p.; Data Release","onlineOnly":"N","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":482390,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20245006","text":"Ungulate Migrations of the Western United States, Volume 4"},{"id":423443,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2020/5101/versionHist.txt","size":"1.0 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2020-5101 version history"},{"id":380307,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5101/sir20205101.pdf","text":"Report","size":"34.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5101"},{"id":482391,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20245111","text":"Ungulate Migrations of the Western United States, Volume 5"},{"id":482389,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225088","text":"Ungulate Migrations of the Western United States, Volume 3"},{"id":482388,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225008","text":"Ungulate Migrations of the Western United States, Volume 2"},{"id":380308,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O2YM6I","text":"USGS data release","description":"USGS data release","linkHelpText":"Ungulate Migrations of the Western United States, Volume 1"},{"id":380306,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5101/coverthb2.jpg"}],"country":"Canada, Mexico, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -126.03515625,\n 22.51255695405145\n ],\n [\n -95.361328125,\n 22.51255695405145\n ],\n [\n -95.361328125,\n 53.225768435790194\n ],\n [\n -126.03515625,\n 53.225768435790194\n ],\n [\n -126.03515625,\n 22.51255695405145\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Verion 1.1: December 203; Version 1.0: November 2020","contact":"Associate Director, Ecosystems Mission Area
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Reston, VA 20192
Groundwater is a critical resource in the Grand Canyon region, supplying nearly all water needs for residents and millions of visitors. Additionally, groundwater discharging at hundreds of spring locations in and near Grand Canyon supports important ecosystems in this mostly arid environment. The security of groundwater supplies is of critical importance for both people and ecosystems in the region and the potential for changes to groundwater systems from projected climate change is a cause for concern. In this study, we analyze recent historical and projected precipitation and temperature data for the Grand Canyon region. Projected climate scenarios are then used in Soil Water Balance groundwater infiltration simulations to understand the state-of-the-science on projected changes to groundwater resources in the area. Historical climate data from 1896 through 2019 indicate multi-decadal cyclical patterns in both precipitation and temperature for most of the time period. Since the 1970s, however, a significant rising trend in temperature is observed in the area. All 10-year periods since 1993 are characterized by both below average precipitation and above average temperature. Downscaled and bias-corrected precipitation and temperature output from 97 CMIP5 global climate models for the water-year 2020–2099 time period indicate projected precipitation patterns similar to recent historical (water-year 1951–2015) data. Projected temperature for the Grand Canyon area, however, is expected to rise by as much as 3.4 °C by the end of the century, relative to the recent historical average. Integrating the effects of projected precipitation and temperature changes on groundwater infiltration, simulation results indicate that > 76% of future decades will experience average potential groundwater infiltration less than that of the recent historical period.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-020-76743-6","usgsCitation":"Tillman, F.D., Gangopadhyay, S., and Pruitt, T., 2020, Recent and projected precipitation and temperature changes in the Grand Canyon area with implications for groundwater resources: Scientific Reports, v. 10, 19740, 11 p., https://doi.org/10.1038/s41598-020-76743-6.","productDescription":"19740, 11 p.","ipdsId":"IP-117188","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":454837,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-020-76743-6","text":"Publisher Index Page"},{"id":381030,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Utah","otherGeospatial":"Colorado Plateau, Grand Canyon, Kaibab Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.97216796875,\n 35.60371874069731\n ],\n [\n -109.53369140625,\n 35.60371874069731\n ],\n [\n -109.53369140625,\n 38.35888785866677\n ],\n [\n -113.97216796875,\n 38.35888785866677\n ],\n [\n -113.97216796875,\n 35.60371874069731\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2020-11-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":147809,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred","email":"ftillman@usgs.gov","middleInitial":"D.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806235,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gangopadhyay, Subhrendu 0000-0003-3864-8251","orcid":"https://orcid.org/0000-0003-3864-8251","contributorId":173439,"corporation":false,"usgs":false,"family":"Gangopadhyay","given":"Subhrendu","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":806236,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pruitt, Tom 0000-0002-3543-1324","orcid":"https://orcid.org/0000-0002-3543-1324","contributorId":173440,"corporation":false,"usgs":false,"family":"Pruitt","given":"Tom","email":"","affiliations":[{"id":27228,"text":"Reclamation","active":true,"usgs":false}],"preferred":false,"id":806237,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70248052,"text":"70248052 - 2020 - Using remote sensing products to predict recovery of vegetation across space and time following energy development","interactions":[],"lastModifiedDate":"2024-05-16T15:37:39.154563","indexId":"70248052","displayToPublicDate":"2020-11-12T09:16:58","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Using remote sensing products to predict recovery of vegetation across space and time following energy development","docAbstract":"Using localized studies to understand how ecosystems recover can create uncertainty in recovery predictions across landscapes. Large archives of remote sensing data offer opportunities for quantifying the spatial and temporal factors influencing recovery at broad scales and predicting recovery. For example, energy production is a widespread and expanding land use among many semi-arid ecosystems of the Western United States dominated by sagebrush (Artemisia spp.), a keystone species providing a variety of ecological services. With remotely-sensed (Landsat) estimates of vegetation cover collected every 2–5 years from southwestern Wyoming, USA, over nearly three decades (1985–2015), we modeled changes in sagebrush cover on 375 former oil and gas well pads in response to weather and site-level conditions. We then used modeled relationships to predict recovery time across the landscape as an indicator of resilience for vegetation after well pad disturbances, where faster recovery indicates a greater capacity to recover when similarly disturbed. We found the rate of change in sagebrush cover generally increased with moisture and temperature, particularly at higher elevations. Rate of change in sagebrush cover also increased and decreased with greater percent sand and larger well pads, respectively. We predicted 21% of the landscape would recover to pre-disturbance conditions within 60 years, whereas other areas may require >100 years for recovery. These predictions and maps could inform future restoration efforts as they reflect resilience. This approach also is applicable to other disturbance types (e.g., fires and vegetation removal treatments) across landscapes, which can further improve conservation efforts by characterizing past conditions and monitoring trends in subsequent years.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2019.105872","usgsCitation":"Monroe, A., Aldridge, C.L., O’Donnell, M.S., Manier, D., Homer, C., and Anderson, P.J., 2020, Using remote sensing products to predict recovery of vegetation across space and time following energy development: Ecological Indicators, v. 110, 105872, 15 p.; 2 Data Releases, https://doi.org/10.1016/j.ecolind.2019.105872.","productDescription":"105872, 15 p.; 2 Data Releases","ipdsId":"IP-101503","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":454840,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2019.105872","text":"Publisher Index Page"},{"id":436724,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XV8GH7","text":"USGS data release","linkHelpText":"Predicted (1989-2015) and forecasted (2015-2114) estimates for rate of change and recovery of sagebrush (Artemisia spp.) following energy development in southwestern Wyoming, USA (ver. 2.0, January 2021)"},{"id":436723,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XV8GH7","text":"USGS data release","linkHelpText":"Predicted (1989-2015) and forecasted (2015-2114) estimates for rate of change and recovery of sagebrush (Artemisia spp.) following energy development in southwestern Wyoming, USA (ver. 2.0, January 2021)"},{"id":436722,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DQ5INM","text":"USGS data release","linkHelpText":"Predicted (1989-2015) and forecasted (2015-2114) estimates for rate of change and recovery of sagebrush (Artemisia spp.) following energy development in southwestern Wyoming, USA"},{"id":436721,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DQ5INM","text":"USGS data release","linkHelpText":"Predicted (1989-2015) and forecasted (2015-2114) estimates for rate of change and recovery of sagebrush (Artemisia spp.) following energy development in southwestern Wyoming, USA"},{"id":420410,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.03921100550399,\n 42.92284600849075\n ],\n [\n -111.03921100550399,\n 41.03307775348375\n ],\n [\n -106.02701021455793,\n 41.03307775348375\n ],\n [\n -106.02701021455793,\n 42.92284600849075\n ],\n [\n -111.03921100550399,\n 42.92284600849075\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"110","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Monroe, Adrian P. 0000-0003-0934-8225 amonroe@usgs.gov","orcid":"https://orcid.org/0000-0003-0934-8225","contributorId":152209,"corporation":false,"usgs":true,"family":"Monroe","given":"Adrian P.","email":"amonroe@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":881652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":140876,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881653,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Manier, Daniel 0000-0002-1105-1327","orcid":"https://orcid.org/0000-0002-1105-1327","contributorId":244206,"corporation":false,"usgs":true,"family":"Manier","given":"Daniel","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881654,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Homer, Collin 0000-0003-4755-8135","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":238918,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":881655,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, Patrick J. 0000-0003-2281-389X andersonpj@usgs.gov","orcid":"https://orcid.org/0000-0003-2281-389X","contributorId":3590,"corporation":false,"usgs":true,"family":"Anderson","given":"Patrick","email":"andersonpj@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881656,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70250009,"text":"70250009 - 2020 - Memorial to Waite Osterkamp 1939-2020","interactions":[],"lastModifiedDate":"2023-11-12T14:17:09.611619","indexId":"70250009","displayToPublicDate":"2020-11-12T08:12:37","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17087,"text":"GSA 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","language":"English","publisher":"Geologic Society of America","usgsCitation":"Betancourt, J.L., Gray, J.R., Hupp, C.R., Emmett, W.W., and Toy, T., 2020, Memorial to Waite Osterkamp 1939-2020: GSA Memorial, v. 49, p. 29-33.","productDescription":"5 p.","startPage":"29","endPage":"33","ipdsId":"IP-118401","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":422524,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":422511,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://rock.geosociety.org/net/documents/gsa/memorials/v49/Osterkamp-WR.pdf"}],"volume":"49","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Betancourt, Julio L. 0000-0002-7165-0743 jlbetanc@usgs.gov","orcid":"https://orcid.org/0000-0002-7165-0743","contributorId":3376,"corporation":false,"usgs":true,"family":"Betancourt","given":"Julio","email":"jlbetanc@usgs.gov","middleInitial":"L.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":887975,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gray, John R. 0000-0002-8817-3701 jrgray@usgs.gov","orcid":"https://orcid.org/0000-0002-8817-3701","contributorId":1158,"corporation":false,"usgs":true,"family":"Gray","given":"John","email":"jrgray@usgs.gov","middleInitial":"R.","affiliations":[{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true}],"preferred":true,"id":887988,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hupp, Cliff R. 0000-0003-1853-9197 crhupp@usgs.gov","orcid":"https://orcid.org/0000-0003-1853-9197","contributorId":2344,"corporation":false,"usgs":true,"family":"Hupp","given":"Cliff","email":"crhupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":887989,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Emmett, Wijlliam W.","contributorId":331527,"corporation":false,"usgs":false,"family":"Emmett","given":"Wijlliam","email":"","middleInitial":"W.","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":887978,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Toy, Terry","contributorId":331528,"corporation":false,"usgs":false,"family":"Toy","given":"Terry","email":"","affiliations":[{"id":12651,"text":"University of Denver","active":true,"usgs":false}],"preferred":false,"id":887979,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70216416,"text":"70216416 - 2020 - Leave no trace communication: Effectiveness based on assessments of resource conditions","interactions":[],"lastModifiedDate":"2020-11-17T23:42:48.50792","indexId":"70216416","displayToPublicDate":"2020-11-11T17:35:21","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7356,"text":"Journal of Interpretation Research","active":true,"publicationSubtype":{"id":10}},"title":"Leave no trace communication: Effectiveness based on assessments of resource conditions","docAbstract":"The efficacy of different Leave No Trace (LNT) communication interventions designed to persuade forest visitors to practice low-impact camping behaviors were evaluated. Three depreciative campsite behaviors—littering, tree damage, and surface disposal of human waste—were evaluated by before-and-after resource condition assessments. Three LNT communication interventions were evaluated against a control: (1) an LNT brochure and poster display (non-personal), (2) personal LNT communication by a forest naturalist, and (3) a combination of both non-personal and personal methods. The study population was overnight campers using dispersed road-accessed campsites in Western Maryland’s Green Ridge State Forest. LNT communication successfully improved resource conditions for the targeted depreciative behaviors. For litter and human waste, personal communication by a forest naturalist was effective, but the non-personal method was ineffective. In contrast, tree damage was significantly reduced by both non-personal and personal communication methods. Combining personal and non-personal communication efforts did not result in an increased benefit. The core implication of this study is that several camping resource impacts can be measurably reduced when uniformed staff personally communicate the desired low impact practices.
| Kaua‘i's native forest birds have experienced steep declines since the beginning of systematic surveys in 1981, and declines have accelerated in recent decades. This report details the analysis of the most recent surveys conducted in 2018. Incorporating the new survey results, long-term trends continue to show sharp declines for all native honeycreeper species with the exception of ‘apapane (Himatione sanguinea), which has stable numbers in core areas of its range. Kaua‘i ‘elepaio (Chasiempis sclateri) continued to decline in the outer portions of its range but increased in the core areas of its range. Abundance estimates of forest birds ranged from slightly higher to slightly lower in most species, indicating a relatively stable period from 2012–2018, and a pause from the rapid declines seen in earlier periods. Many native species now exist in very low numbers, and variation in estimates from survey to survey will increase. |