The Science Data Management Branch (SDM) of the U.S. Geological Survey (USGS) provides data management expertise and leadership and develops guidance and tools to support the USGS in providing the nation with reliable scientific information on the basis of which to describe the Earth. The SDM suite of tools supports the USGS Data Management Lifecycle by facilitating quality assurance, description, curation, and publishing of the Bureau's scientific data. The SDM suite of tools includes the USGS Data Management Website, USGS Science Data Catalog, Digital Object Identifier Tool, ScienceBase, ScienceBase Data Release Tool, Metadata Wizard, and Online Metadata Editor.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203041","usgsCitation":"Hutchison, V.B., Liford, A.N., McClees-Funinan, Ricardo, Zolly, Lisa, Ignizio, D.A., Langseth, M.L., Serna, B.S., Sellers, E.A., Hsu, Leslie, Norkin, Tamar, McNiff, Marcia, Donovan, G.C., 2020, USGS enterprise tools for efficient and effective management of science data: U.S. Geological Survey Fact Sheet 2020–3041, 2 p., https://doi.org/10.3133/fs20203041.","productDescription":"4 p.","onlineOnly":"Y","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":378676,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3041/coverthb.jpg"},{"id":378677,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3041/fs20203041.pdf","text":"Report","size":"2.42 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020-3041"}],"contact":"Director, Science Analytics and Synthesis
U.S. Geological Survey
108 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Soft sediment deformation structures are common in fine-grained pyroclastic deposits and are often taken, along with other characteristics, to indicate that deposits were emplaced in a wet and cohesive state. At Ubehebe Crater (Death Valley, California, USA), deposits were emplaced by multiple explosions, both directly from pyroclastic surges and by rapid remobilization of fresh, fine-ash-rich deposits off steep slopes as local granular flows. With the exception of the soft sediment deformation structures themselves, there is no evidence of wet deposition. We conclude that deformation was a result of destabilization of fresh, fine-grained deposits with elevated pore-gas pressure and dry cohesive forces. Soft sediment deformation alone is not sufficient to determine whether parent pyroclastic surges contained liquid water and caused wet deposition of strata.
During winter 2017–18 coastal areas of New England were impacted by the January 4, and March 2–4, 2018, nor’easters. The U.S. Geological Survey (USGS), under an interagency agreement with the Federal Emergency Management Agency (FEMA), collected total water level data (the combination of tide, storm surge, wave runup and setup, and freshwater input) using the North American Vertical Datum of 1988 (NAVD 88) from high-water marks and continuous water-level sensors, to better understand the areal extent, timing, and impact of coastal flooding from strong storms.
During the January 4, 2018, nor’easter the National Oceanic and Atmospheric Administration (NOAA) Boston, Massachusetts, tide gage recorded the highest total water level on record of 9.66 ft. During the March 2–4, 2018, nor’easter, the Boston tide gage recorded its third highest total water level on record of 9.16 ft.
After the January and March 2018 nor’easter storms, the USGS deployed field teams that identified and flagged high-water marks along the coastlines of eastern Massachusetts in January and from Portland, Maine, south to the Connecticut-New York State border in March. In preparation for the approach of the March 2018 nor’easter, the USGS deployed 35 temporary water-level sensors along the coastline of New England to collect total water level data during the storm. Total water level data were also collected at 28 tide gages and 14 coastal streamgages (affected tidally or by tidal backwater during coastal storms) in New England during both nor’easters.
Total water level elevations at 71 high-water marks collected after the January 2018 nor’easter in coastal areas of eastern Massachusetts ranged from 5.8 to 15.1 feet (ft), with an average elevation of 9.4 ft and a median elevation of 9.6 ft. Total water level elevations at 10 tide gages and 7 coastal streamgages from Portland to Cape Cod Bay ranged from 4.8 to 11.2 ft, with an average of 9.1 ft and a median of 9.6 ft. Following the March 2018 nor’easter, 111 high-water marks were collected along the New England coastline. Of the 111 high-water marks, 100 were along the eastern coastline of New England from Portland to Cape Cod and had elevations that ranged from 5.3 to 15.1 ft, with an average of 8.9 ft and a median of 8.6 ft. The remaining 11 high-water marks along the southern coastline of New England in Connecticut, Rhode Island, and Massachusetts had elevations that ranged from 3.1 to 7.5 ft, with an average of 4.3 ft and a median of 4.9 ft. Total water level elevations for 19 USGS temporary water-level sensors from Portland to Cape Cod Bay ranged from 6.2 to 10.4 ft, with an average of 8.4 ft and a median of 8.7 ft. Total water level elevations at 10 tide gages and 6 coastal streamgages from Portland to Cape Cod Bay ranged from 7.8 to 10.8 ft, with an average of 9.1 ft and a median of 9.2 ft.
There were 10 tide gages and 5 coastal streamgages with data from both nor’easters from Portland to Cape Cod Bay; for the January nor’easter, the average and median elevations were about 0.3 and 0.5 ft higher, respectively, than for the March nor’easter. At the 52 high-water mark locations with data for both nor’easters in Massachusetts, the average and median elevations were 0.1 and 0.4 ft higher, respectively, for the January nor’easter than for the March nor’easter.
At 10 tide gages along the coastline from Portland to Cape Cod Bay, the observed peak total water level elevations for the January nor’easter ranged from 1.6 to 3.7 ft higher than the concurrent predicted elevations, with an average of 2.8 ft and a median of 3.0 ft higher. For the March nor’easter, the observed peak total water level elevations ranged from 1.8 to 4.0 ft higher than the concurrent predicted elevations, with an average of 2.7 ft and a median of 3.0 ft higher. This is approximately the amount of storm surge that was experienced during the highest tides of the two nor’easters along the coastline from Portland to Cape Cod Bay.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205048","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Bent, G.C., and Taylor, N.J., 2020, Total water level data from the January and March 2018 nor’easters for coastal areas of New England: U.S. Geological Survey Scientific Investigations Report 2020–5048, 47 p., https://doi.org/10.3133/sir20205048.","productDescription":"Report: vii, 47 p.; 2 Data Releases","numberOfPages":"47","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-108335","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":378670,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://stn.wim.usgs.gov/FEV/#NoreasterofMarch2018","linkFileType":{"id":5,"text":"html"},"linkHelpText":"- Flood Event Viewer, March 2018 nor’easter"},{"id":378666,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5048/coverthb.jpg"},{"id":378669,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://stn.wim.usgs.gov/FEV/#NoreasterJanuary2018","linkFileType":{"id":5,"text":"html"},"linkHelpText":"- Flood Event Viewer, January 2018 nor’easter"},{"id":378667,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5048/sir20205048.pdf","text":"Report","size":"4.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5048"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.86279296875,\n 44.80132682904856\n ],\n [\n -67.203369140625,\n 45.213003555993964\n ],\n [\n -67.32421875,\n 45.120052841530544\n ],\n [\n -67.412109375,\n 45.282617057517406\n ],\n [\n -67.423095703125,\n 45.606352077118316\n ],\n [\n -67.752685546875,\n 45.72152152227954\n ],\n [\n -67.796630859375,\n 47.092565552235705\n ],\n [\n -68.31298828125,\n 47.368594345213374\n ],\n [\n -68.92822265625,\n 47.21956811231547\n ],\n [\n -69.027099609375,\n 47.42065432071318\n ],\n [\n -69.2138671875,\n 47.45780853075031\n ],\n [\n -70.048828125,\n 46.70973594407157\n ],\n [\n -70.279541015625,\n 46.17983040759436\n ],\n [\n -70.455322265625,\n 45.71385093029221\n ],\n [\n -70.77392578125,\n 45.4524242413431\n ],\n [\n -71.015625,\n 45.298075138707965\n ],\n [\n -71.290283203125,\n 45.298075138707965\n ],\n [\n -71.510009765625,\n 44.99588261816546\n ],\n [\n -71.619873046875,\n 44.55133484083592\n ],\n [\n -72.015380859375,\n 44.33956524809713\n ],\n [\n -72.45483398437499,\n 43.42100882994726\n ],\n [\n -72.53173828125,\n 42.90011265525328\n ],\n [\n -72.4658203125,\n 42.76314586689492\n ],\n [\n -73.27880859375,\n 42.771211138625894\n ],\n [\n -73.509521484375,\n 42.09822241118974\n ],\n [\n -73.54248046875,\n 41.31082388091818\n ],\n [\n -73.740234375,\n 41.07935114946899\n ],\n [\n -73.641357421875,\n 41.00477542222947\n ],\n [\n -72.861328125,\n 41.253032440653186\n ],\n [\n -72.059326171875,\n 41.20345619205131\n ],\n [\n -70.345458984375,\n 41.30257109430557\n ],\n [\n -69.971923828125,\n 41.178653972331674\n ],\n [\n -69.80712890625,\n 41.236511201246216\n ],\n [\n -69.93896484375,\n 42.04113400940807\n ],\n [\n -70.57617187499999,\n 42.73894375124377\n ],\n [\n -69.98291015625,\n 43.6599240747891\n ],\n [\n -66.97265625,\n 44.645208223744035\n ],\n [\n -66.86279296875,\n 44.80132682904856\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Mercury (Hg) has been a contaminant of concern for several decades in South Florida, particularly in the Florida Everglades. The transport and bioavailability of Hg in aquatic systems is intimately linked to dissolved organic carbon (DOC). In aquatic systems, Hg can be converted to methylmercury (MeHg), which is the form of Hg that bioaccumulates in food webs. The bioaccumulation of MeHg poses significant health risks to wildlife and humans. Fish consumption advisories triggered by elevated Hg levels first appeared in the 1980s in South Florida. Multiple structures regulate freshwater distribution to Everglades National Park, including S-12D. This report summarizes seasonal and annual concentration and load data from late September 2013 to April 2017 for the total of (1) filter-passing total mercury (FTHg), (2) filter-passing methylmercury (FMeHg), (3) particulate total mercury (PTHg), (4) particulate methylmercury (PMeHg) and, (5) DOC discharged through control structure S-12D. The loads of Hg fractions and DOC at control structure S-12D were determined by pairing discharge data with constituent concentrations estimated by empirical models based on surrogate in situ water-quality measurements.
Calculated concentrations of DOC ranged from 12.8 milligrams per liter (mg/L) to 27.9 mg/L with a mean of 18.8 mg/L during the study period. Annual loads of DOC ranged from 3,950 tons in 2015 to 10,900 tons in 2016. DOC loads increased linearly with an increase in flow, and the highest monthly DOC load of 1,630 tons was observed in February 2016.
Calculated concentrations of FTHg ranged from 0.35 to 1.55 nanograms per liter (ng/L) with a mean of 0.85 ng/L during the study period. Calculated concentrations of FMeHg ranged from 0.06 ng/L to 0.24 ng/L with a mean of 0.14 ng/L during the study period. Generally, FTHg and FMeHg concentrations were lower during periods of decreased flow and higher during periods of increased flow. Calculated PTHg concentrations ranged from 0.09 ng/L to 4.19 ng/L with a mean of 0.58 ng/L during the study period. Calculated PMeHg concentrations ranged from below the limit of detection <0.01 ng/L to 0.29 ng/L with a mean of 0.03 ng/L during the study period.
Loads of Hg were often zero or lowest from November to May, owing to the lack of flow or low-flow conditions. FTHg and FMeHg loads increased linearly with an increase in flow and typically were highest from June to October. During periods of increasing flow or following changes in gate operations, PTHg and PMeHg constituted a greater percentage of the total Hg load. Annual loads of total Hg (filter-passing and particulate) ranged from 254 grams in 2015 to 658 grams in 2016. FTHg was the predominant contributor to the total Hg load. Information presented herein provides the first assessment of DOC and Hg loads to Everglades National Park through control structure S-12D using continuous in situ measurements of discharge and constituent surrogates and compares the surrogate model approach to loads calculated from monthly sampling. Analysis of calculated and observed loads demonstrates the significance of flow data on calculating constituent loads.
Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Peak ground velocity (PGV) is a commonly used parameter in earthquake ground‐motion models (GMMs) and hazard analyses, because it is closely related to structural damage and felt ground shaking, and is typically measured on broadband seismometers. Here, we demonstrate that strainmeters, which directly measure in situ strain in the bulk rock, can easily be related to ground velocity by a factor of bulk shear‐wave velocity and, thus, can be used to measure strain‐estimated PGV. We demonstrate the parity of velocity to strain utilizing data from borehole strainmeters deployed along the plate boundaries of the west coast of the United States for nine recent
High precision triple oxygen isotope measurements of carbonates can better constrain temperatures and oxygen isotope compositions of seawater through geologic time than 18O/16O measurements alone, but lack of a definitive calibration has hindered progress. In this study, we fluorinated both carbonate and water samples to measure quantitatively the triple oxygen isotope composition of each phase. We compared the oxygen isotope fractionation between carbonate and water for different carbonate materials: calcite synthesized with and without carbonic anhydrase, abiogenic calcite from Devils Hole, and extant biogenic calcite and aragonite of marine origin. We found similar 1000lnα18Occ-wt values for all materials and combined the results with the high temperature experimental data of O'Neil et al. (1969), resulting in the following fractionation equation (T in Kelvins)
Biological conservation often requires an understanding of how environmental conditions affect species occurrence and detection probabilities. We used a hierarchical framework to evaluate these effects for several Appalachian stream fish species of conservation concern: Chrosomus cumberlandensis (BSD; blackside dace), Etheostoma sagitta (CAD; Cumberland arrow darter), and Etheostoma spilotum (KAD; Kentucky arrow darter). Etheostoma susanae (Cumberland darter) also is present in the study area but was too rare to model in this analysis. In this study, conducted by the U.S. Geological Survey in cooperation with the U.S. Fish and Wildlife Service, fish and habitat data were collected from 205 randomly selected stream sites in the upper Cumberland and Kentucky River Basins (120 and 85 sites, respectively) of Kentucky and Tennessee. Sites were sampled with 10 spatial replicates (2 meter x 5 meter electrofishing zones) to enable estimation of detection probabilities and environmental effects. The best models (that is, lowest Akaike information criterion scores) showed the effects of agriculture (negative) on occurrence of BSD and stream conductivity (negative) on occurrence of CAD and KAD. These effects were statistically more important than measures of basin area, elevation, and substrate size. Conductivity and agriculture showed nonlinear effects on species occurrence, and effects of conductivity were more precise above 400 microsiemens per centimeter than below this threshold. Models incorporated detection-level effects of electrofishing time (positive), flow velocity (negative), sand substrate (positive), and gravel/cobble substrate (negative). Models accounting for detection of BSD estimated occupancy rates similar to the observed proportion of occupied sites (0.10), but the best-supported models for CAD and KAD increased expected occupancy by about 4 percent for each species (from 0.17 to 0.21 for CAD and from 0.07 to 0.11 for KAD). Results of this study provide new inferences for modeling stream fish occurrence and detection processes and highlight the importance of continued monitoring and assessment of rare fish species in Appalachian headwater streams.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201100","collaboration":"Prepared in cooperation with U.S. Fish and Wildlife Service","usgsCitation":"Hitt, N.P., Rogers, K.M., Kessler, K., and Macmillan, H., 2020, Modeling occupancy of rare stream fish species in the upper Cumberland and Kentucky River Basins: U.S. Geological Survey Open-File Report 2020–1100, 22 p., https://doi.org/10.3133/ofr20201100.","productDescription":"vi, 22 p.","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-118746","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":378605,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1100/ofr20201100.pdf","text":"Report","size":"2.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1100"},{"id":378604,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1100/coverthb.jpg"}],"country":"United States","state":"Kentucky, Tennessee, Virginia","otherGeospatial":"Cumberland River basin, Kentucky River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.1875,\n 35.88905007936091\n ],\n [\n -81.39770507812499,\n 35.88905007936091\n ],\n [\n -81.39770507812499,\n 38.77121637244273\n ],\n [\n -87.1875,\n 38.77121637244273\n ],\n [\n -87.1875,\n 35.88905007936091\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
Streamflow data and statistics are vitally important for proper protection and management of the water quality and water quantity of Alabama streams. Such data and statistics are generally available at U.S. Geological Survey streamflow-gaging stations, also referred to as streamgages or stations, but are often needed at ungaged stream locations. To address this need, the U.S. Geological Survey, in cooperation with numerous Alabama State agencies and organizations, developed regional regression equations for estimating selected low-flow frequency statistics and mean annual flow for ungaged locations on streams in Alabama that are not substantially affected by tides, regulation, diversions, or other anthropogenic influences. A small percentage of the streamgages included in this study experience zero flows during certain periods; thus, the final low-flow frequency regression equations were developed by using weighted left-censored regression analyses to analyze the flow data in an unbiased manner, with weights based on number of years of record.
The equations developed include the annual minimum 1- and 7-day average streamflows with a 10-year recurrence interval (referred to as the 1Q10 and 7Q10 flows), the annual minimum 7-day average streamflow with a 2-year recurrence interval (referred to as the 7Q2 flow), and the mean annual flow using data from 174 streamgages from Alabama and surrounding States. For the 1Q10, 7Q2, and 7Q10 low-flow frequency statistics, the regional regression equations are functions of drainage area, streamflow-variability index, mean annual precipitation, and percentage of the drainage basin located in the Piedmont and Southeastern Plains ecoregions. The mean annual flow regression equation is a function of drainage area, mean annual precipitation, and percentage of the drainage basin located in the Southeastern Plains ecoregion. For the mean annual flow regression equation, the average standard error of estimate was 11.2 percent. For the selected low-flow frequency equations, the average standard errors of estimate ranged from 18.1 to 38.8 percent.
The regional regression equations developed from this investigation have been incorporated into the U.S. Geological Survey StreamStats application for Alabama. StreamStats (https://streamstats.usgs.gov/ss/) is a web-based geographic information system application that delineates drainage basins at selected stream locations and then generates the needed basin characteristics for available regional regression equations. Along with the low-flow frequency equations developed in this investigation, the StreamStats application also has regional regression equations for estimating flood-frequency statistics at locations on rural and urban streams in Alabama.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205099","collaboration":"Prepared in cooperation with Alabama Power; Alabama Farmers Federation; Alabama Association of Conservation Districts; Alabama Association of Resource Conservation and Development Councils; Alabama Department of Agriculture and Industries; Alabama Department of Conservation and Natural Resources— Wildlife and Freshwater Fisheries Division; Alabama Department of Economic and Community Affairs—Office of Water Resources; Alabama Department of Environmental Management; Alabama Soil and Water Conservation Committee; Choctawhatchee, Pea and Yellow Rivers Watershed Management Authority; Geological Survey of Alabama; and The University of Alabama—Alabama Water Institute","usgsCitation":"Feaster, T.D., Kolb, K.R., Painter, J.A., and Clark, J.M., 2020, Methods for estimating selected low-flow frequency statistics and mean annual flow for ungaged locations on streams in Alabama (ver. 1.1, November 20, 2020): U.S. Geological Survey Scientific Investigations Report 2020–5099, 21 p., https://doi.org/10.3133/sir20205099.","productDescription":"Report: vii, 21 p.; Appendixes: 4; Data Release; Version History","numberOfPages":"34","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-114774","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":378594,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P994UFS7","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Supporting data for estimating selected low-flow frequency statistics and mean annual flow for ungaged locations on streams in Alabama"},{"id":380616,"rank":8,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2020/5099/versionHist.txt","text":"Version History","size":"1.47 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2020–5099 Version History"},{"id":378593,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5099/sir20205099_appendix2.xlsx","text":"Appendix 2","size":"49.6 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5099 Appendix 2","linkHelpText":"— U.S. Geological Survey streamgages and independent and dependent variables used in the low-flow frequency and mean annual flow regression analyses for ungaged locations on streams in Alabama"},{"id":378592,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5099/sir20205099_appendix2.csv","text":"Appendix 2","size":"27.6 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020–5099 Appendix 2","linkHelpText":"— U.S. Geological Survey streamgages and independent and dependent variables used in the low-flow frequency and mean annual flow regression analyses for ungaged locations on streams in Alabama"},{"id":378832,"rank":6,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5099/coverthb3.jpg"},{"id":378591,"rank":2,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5099/sir20205099_appendix1.xlsx","text":"Appendix 1","size":"18.1 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5099 Appendix 1","linkHelpText":"— U.S. Geological Survey streamgages that were excluded from the regional regression analysis for estimating selected low-flow frequency statistics and mean annual flow for ungaged locations in Alabama"},{"id":378833,"rank":7,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5099/sir20205099.pdf","text":"Report","size":"3.54 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5099"},{"id":378590,"rank":1,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5099/sir20205099_appendix1.csv","text":"Appendix 1","size":"12.7 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020–5099 Appendix 1","linkHelpText":"— U.S. Geological Survey streamgages that were excluded from the regional regression analysis for estimating selected low-flow frequency statistics and mean annual flow for ungaged locations in Alabama"}],"country":"United States","state":"Alabama","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-87.984916,35.005881],[-87.851886,35.005656],[-87.671405,35.003537],[-87.391314,35.002374],[-86.972613,34.99461],[-86.862147,34.991956],[-86.676726,34.99207],[-86.528485,34.990677],[-86.467798,34.990692],[-86.397203,34.99166],[-85.824411,34.988142],[-85.605165,34.984678],[-85.595191,34.924331],[-85.561416,34.750079],[-85.534327,34.625082],[-85.527261,34.588683],[-85.517074,34.542598],[-85.51393,34.525192],[-85.47045,34.328239],[-85.42947,34.125096],[-85.428222,34.114397],[-85.406748,34.002314],[-85.377426,33.856047],[-85.357402,33.750104],[-85.304439,33.482884],[-85.232378,33.108077],[-85.188741,32.889727],[-85.18474,32.870527],[-85.184131,32.870525],[-85.184914,32.868944],[-85.1844,32.861317],[-85.179353,32.855269],[-85.177127,32.853895],[-85.165569,32.85209],[-85.163427,32.851431],[-85.161615,32.849948],[-85.159638,32.844018],[-85.159474,32.839735],[-85.164651,32.834791],[-85.168342,32.828516],[-85.168644,32.814246],[-85.167939,32.811612],[-85.162137,32.804237],[-85.151913,32.794104],[-85.134676,32.782166],[-85.132186,32.778897],[-85.13203,32.776718],[-85.13312,32.773449],[-85.136544,32.769402],[-85.138412,32.764576],[-85.138879,32.760062],[-85.138101,32.753836],[-85.136077,32.749633],[-85.132186,32.74652],[-85.124092,32.741694],[-85.1202,32.737647],[-85.119577,32.734223],[-85.119733,32.72644],[-85.122738,32.715727],[-85.117037,32.692033],[-85.114737,32.685634],[-85.112637,32.683434],[-85.104037,32.679634],[-85.093536,32.669734],[-85.088483,32.657758],[-85.089736,32.655635],[-85.09457,32.652443],[-85.097952,32.645474],[-85.098259,32.642708],[-85.09662,32.638199],[-85.088934,32.635432],[-85.086167,32.633177],[-85.086065,32.631435],[-85.087192,32.628463],[-85.088627,32.626619],[-85.088319,32.623032],[-85.087294,32.62047],[-85.08224,32.616264],[-85.080768,32.610152],[-85.080288,32.603577],[-85.076399,32.594665],[-85.067535,32.579546],[-85.022509,32.542923],[-85.020237,32.534748],[-85.015805,32.528428],[-85.013788,32.526108],[-85.008396,32.524876],[-85.0071,32.523868],[-85.001532,32.514741],[-84.998332,32.494142],[-84.996732,32.492342],[-84.994831,32.486042],[-84.995231,32.475242],[-84.998231,32.469842],[-84.998031,32.461743],[-84.995331,32.453243],[-84.993531,32.450743],[-84.983831,32.445643],[-84.971831,32.442843],[-84.967031,32.435343],[-84.96303,32.424244],[-84.96343,32.422544],[-84.97183,32.416244],[-84.979431,32.412244],[-84.981098,32.402833],[-84.97752,32.39687],[-84.976767,32.392648],[-84.979028,32.38918],[-84.980385,32.385561],[-84.978739,32.376271],[-84.980084,32.373347],[-84.982949,32.371387],[-84.983552,32.368371],[-84.983466,32.363186],[-84.986778,32.359058],[-85.004582,32.345196],[-85.008096,32.336677],[-85.007103,32.328362],[-85.001874,32.322015],[-84.989514,32.319316],[-84.93868,32.300708],[-84.9338,32.29826],[-84.922872,32.285333],[-84.911127,32.276949],[-84.904023,32.273749],[-84.893959,32.265846],[-84.890894,32.261504],[-84.891131,32.25961],[-84.892315,32.258189],[-84.901549,32.255584],[-84.904087,32.250838],[-84.907227,32.24905],[-84.912488,32.247463],[-84.913249,32.24529],[-84.912727,32.24335],[-84.916327,32.236551],[-84.920627,32.233951],[-84.922627,32.231751],[-84.923527,32.229751],[-84.922927,32.224751],[-84.925427,32.221551],[-84.930127,32.219051],[-84.939328,32.217951],[-84.948995,32.217849],[-84.957057,32.21671],[-84.958985,32.215571],[-84.965733,32.208823],[-84.966784,32.206895],[-84.966928,32.204451],[-84.965032,32.200585],[-84.964944,32.19892],[-84.965032,32.196642],[-84.966828,32.193952],[-84.995929,32.184852],[-85.008531,32.181903],[-85.011267,32.180493],[-85.026583,32.166104],[-85.033989,32.156348],[-85.045593,32.143758],[-85.058749,32.136018],[-85.061144,32.134065],[-85.06206,32.132486],[-85.06154,32.129673],[-85.05918,32.125153],[-85.055045,32.113671],[-85.053777,32.107684],[-85.04955,32.095362],[-85.047063,32.090433],[-85.047063,32.087389],[-85.04774,32.084908],[-85.053232,32.080604],[-85.055813,32.074439],[-85.054084,32.07021],[-85.054179,32.067985],[-85.05683,32.059755],[-85.05663,32.054155],[-85.05883,32.046656],[-85.05803,32.043756],[-85.055333,32.04058],[-85.054839,32.038814],[-85.054627,32.036694],[-85.056464,32.031819],[-85.056253,32.028336],[-85.053214,32.024189],[-85.053214,32.021576],[-85.054768,32.017407],[-85.053815,32.013502],[-85.055075,32.010714],[-85.063441,32.00414],[-85.064544,32.002489],[-85.06803,31.993357],[-85.06833,31.986757],[-85.07093,31.981658],[-85.06993,31.978358],[-85.066829,31.974758],[-85.065929,31.971158],[-85.067829,31.967358],[-85.07023,31.965658],[-85.07393,31.964158],[-85.08323,31.962458],[-85.08573,31.960758],[-85.08673,31.959158],[-85.08683,31.957758],[-85.08243,31.945358],[-85.07893,31.941459],[-85.07893,31.940159],[-85.08473,31.937359],[-85.08643,31.935959],[-85.09183,31.928859],[-85.09953,31.925259],[-85.10133,31.918659],[-85.10243,31.917359],[-85.10913,31.914359],[-85.113131,31.911859],[-85.112731,31.909859],[-85.10983,31.90806],[-85.10803,31.90516],[-85.11133,31.89936],[-85.11063,31.89686],[-85.11203,31.89476],[-85.114031,31.89336],[-85.117031,31.89286],[-85.132931,31.89306],[-85.134131,31.89216],[-85.133731,31.88956],[-85.129331,31.88246],[-85.128431,31.87756],[-85.133731,31.870061],[-85.135831,31.862461],[-85.140131,31.858761],[-85.140731,31.857461],[-85.140231,31.855261],[-85.138031,31.851262],[-85.137731,31.845861],[-85.138331,31.844161],[-85.141331,31.841061],[-85.141831,31.839261],[-85.139231,31.834161],[-85.135931,31.830462],[-85.133631,31.826062],[-85.131331,31.817562],[-85.131531,31.813062],[-85.132931,31.808062],[-85.132831,31.798862],[-85.132231,31.795162],[-85.132931,31.792363],[-85.137131,31.788363],[-85.141931,31.781963],[-85.140431,31.779663],[-85.12633,31.768863],[-85.12523,31.767063],[-85.12563,31.764463],[-85.129231,31.758663],[-85.12393,31.747564],[-85.11893,31.732664],[-85.12223,31.722764],[-85.12573,31.718864],[-85.12653,31.716764],[-85.12683,31.708965],[-85.12553,31.694965],[-85.12233,31.691265],[-85.11393,31.686865],[-85.11263,31.685165],[-85.10943,31.677465],[-85.092429,31.659966],[-85.083545,31.656071],[-85.082013,31.65473],[-85.080864,31.652336],[-85.085173,31.644101],[-85.085365,31.642186],[-85.084503,31.639026],[-85.080029,31.636867],[-85.073829,31.629567],[-85.067628,31.625267],[-85.059534,31.621717],[-85.058169,31.620227],[-85.057527,31.616883],[-85.060418,31.611271],[-85.060552,31.608224],[-85.059696,31.607262],[-85.057314,31.606713],[-85.055976,31.605178],[-85.058109,31.593343],[-85.05844,31.58369],[-85.055417,31.578696],[-85.055284,31.577092],[-85.057719,31.573062],[-85.05796,31.57084],[-85.052931,31.56289],[-85.050838,31.555551],[-85.045698,31.548707],[-85.042547,31.545953],[-85.041305,31.540987],[-85.041813,31.537754],[-85.042983,31.5352],[-85.047196,31.528671],[-85.048263,31.526012],[-85.047649,31.523751],[-85.044556,31.520908],[-85.044986,31.51823],[-85.052951,31.506518],[-85.058923,31.495989],[-85.062105,31.488017],[-85.065687,31.484122],[-85.071621,31.468384],[-85.069268,31.453472],[-85.066703,31.447286],[-85.065955,31.442979],[-85.065875,31.430586],[-85.06697,31.428594],[-85.068546,31.427311],[-85.072898,31.426477],[-85.074762,31.424879],[-85.076746,31.415971],[-85.079818,31.411732],[-85.079978,31.410472],[-85.077387,31.402844],[-85.077626,31.39888],[-85.080403,31.393932],[-85.082431,31.38454],[-85.092167,31.364576],[-85.092619,31.357474],[-85.091791,31.355207],[-85.09099,31.354428],[-85.087413,31.354428],[-85.085918,31.353146],[-85.087063,31.340317],[-85.08781,31.337981],[-85.089411,31.336033],[-85.088983,31.334292],[-85.084152,31.328313],[-85.083776,31.31821],[-85.087404,31.311223],[-85.087695,31.304053],[-85.089774,31.295026],[-85.09316,31.289688],[-85.099107,31.284165],[-85.110309,31.281733],[-85.112762,31.280037],[-85.114601,31.277333],[-85.114548,31.276302],[-85.112546,31.274378],[-85.111905,31.272477],[-85.111983,31.267987],[-85.113261,31.264343],[-85.112352,31.25958],[-85.109149,31.254609],[-85.102472,31.23786],[-85.098844,31.232524],[-85.096763,31.225651],[-85.098707,31.219511],[-85.098704,31.211286],[-85.106963,31.202693],[-85.108133,31.195637],[-85.107516,31.186451],[-85.106503,31.185305],[-85.104424,31.18565],[-85.102052,31.184734],[-85.098507,31.180153],[-85.100207,31.16549],[-85.092106,31.160293],[-85.083582,31.15963],[-85.077801,31.157889],[-85.076628,31.156927],[-85.070181,31.14868],[-85.064028,31.142495],[-85.06243,31.139518],[-85.061072,31.134225],[-85.054677,31.120818],[-85.052867,31.119489],[-85.050178,31.118916],[-85.035615,31.108192],[-85.032832,31.10057],[-85.029736,31.096163],[-85.026068,31.08418],[-85.028573,31.074583],[-85.018148,31.059253],[-85.012642,31.055402],[-85.011392,31.053546],[-85.008816,31.045573],[-85.009409,31.032378],[-85.005051,31.024701],[-85.004549,31.01918],[-84.999428,31.013843],[-84.999626,31.009079],[-85.001366,31.005044],[-85.002368,31.000682],[-85.243632,31.000884],[-85.498272,30.996928],[-85.749619,30.995292],[-85.749932,30.994837],[-85.998643,30.99287],[-86.035039,30.99332],[-86.116918,30.992917],[-86.238335,30.99437],[-86.289247,30.993798],[-86.36927,30.994477],[-86.49995,30.99334],[-86.512834,30.9937],[-86.519938,30.993245],[-86.563436,30.995223],[-86.706261,30.994703],[-86.725379,30.996872],[-86.74524,30.99629],[-86.830497,30.997401],[-86.92781,30.997704],[-87.039989,30.999594],[-87.053737,30.999131],[-87.118873,30.999427],[-87.124969,30.998802],[-87.140755,30.999532],[-87.237685,30.996393],[-87.25498,30.998285],[-87.301567,30.998434],[-87.458658,30.998386],[-87.51952,30.997586],[-87.598928,30.997457],[-87.599172,30.995722],[-87.596722,30.98761],[-87.593395,30.982959],[-87.592676,30.98014],[-87.594164,30.977572],[-87.594111,30.976335],[-87.589187,30.964464],[-87.592055,30.951492],[-87.59689,30.941131],[-87.598299,30.938793],[-87.600691,30.937074],[-87.602684,30.934277],[-87.607811,30.92449],[-87.6102,30.916628],[-87.611847,30.914541],[-87.614209,30.908536],[-87.616013,30.901453],[-87.620715,30.89893],[-87.622203,30.897508],[-87.622519,30.89368],[-87.620922,30.889923],[-87.620788,30.887494],[-87.622062,30.885408],[-87.6244,30.884696],[-87.629454,30.880115],[-87.634938,30.865886],[-87.628245,30.860131],[-87.626228,30.857127],[-87.62538,30.854355],[-87.627323,30.847961],[-87.626075,30.846494],[-87.624137,30.845713],[-87.617281,30.840353],[-87.615367,30.837031],[-87.615923,30.834693],[-87.605776,30.831304],[-87.60163,30.82514],[-87.600486,30.820627],[-87.594297,30.816984],[-87.58787,30.815037],[-87.581869,30.812403],[-87.576849,30.808163],[-87.572043,30.800532],[-87.56814,30.799088],[-87.564209,30.796246],[-87.560068,30.792258],[-87.559484,30.790447],[-87.554838,30.787125],[-87.552051,30.786254],[-87.545044,30.778666],[-87.545364,30.774105],[-87.54616,30.77202],[-87.536528,30.761383],[-87.535416,30.75476],[-87.535365,30.749775],[-87.532607,30.743489],[-87.523613,30.738306],[-87.511729,30.733535],[-87.505153,30.726313],[-87.502317,30.72159],[-87.497515,30.720123],[-87.487036,30.7185],[-87.481225,30.716508],[-87.479819,30.71495],[-87.479579,30.712865],[-87.474429,30.706586],[-87.470397,30.705281],[-87.467717,30.701683],[-87.466338,30.700835],[-87.456948,30.69756],[-87.451404,30.699806],[-87.44358,30.694604],[-87.439814,30.690479],[-87.436021,30.688668],[-87.430372,30.688645],[-87.424883,30.683374],[-87.419527,30.679981],[-87.412739,30.678055],[-87.406958,30.675165],[-87.406561,30.674019],[-87.407118,30.671796],[-87.405874,30.666616],[-87.400707,30.657148],[-87.397262,30.654351],[-87.396177,30.650454],[-87.397185,30.648117],[-87.393588,30.63088],[-87.393775,30.627006],[-87.395659,30.623372],[-87.39643,30.617734],[-87.39643,30.616909],[-87.395026,30.615281],[-87.397308,30.608728],[-87.39927,30.605611],[-87.404597,30.603389],[-87.406558,30.599928],[-87.408736,30.583701],[-87.412712,30.573227],[-87.414513,30.573456],[-87.416261,30.572448],[-87.418354,30.570043],[-87.418513,30.569561],[-87.416951,30.568003],[-87.41666,30.566306],[-87.418647,30.561837],[-87.422408,30.560439],[-87.423362,30.561425],[-87.426037,30.560073],[-87.427891,30.554159],[-87.431441,30.550263],[-87.43544,30.54914],[-87.446586,30.527068],[-87.446427,30.520306],[-87.444944,30.514943],[-87.445182,30.51398],[-87.446499,30.513569],[-87.447782,30.511913],[-87.447702,30.510458],[-87.444714,30.507494],[-87.44322,30.506782],[-87.43969,30.506649],[-87.431178,30.495795],[-87.430578,30.491096],[-87.432978,30.484896],[-87.435578,30.480496],[-87.434678,30.479196],[-87.431578,30.477696],[-87.430578,30.476596],[-87.429578,30.470596],[-87.425078,30.465596],[-87.414677,30.457296],[-87.407877,30.456396],[-87.404677,30.452897],[-87.399877,30.450997],[-87.396877,30.450597],[-87.391976,30.451597],[-87.381176,30.450097],[-87.370768,30.446865],[-87.36868,30.444631],[-87.366939,30.44048],[-87.366591,30.436648],[-87.368191,30.433407],[-87.371169,30.43049],[-87.386376,30.420497],[-87.395676,30.417597],[-87.403477,30.410198],[-87.408877,30.408798],[-87.419177,30.410198],[-87.422677,30.410098],[-87.426177,30.409198],[-87.429578,30.406498],[-87.431778,30.403198],[-87.434278,30.397498],[-87.437278,30.395898],[-87.440678,30.391498],[-87.440878,30.386698],[-87.438678,30.382098],[-87.438678,30.380798],[-87.441823,30.376304],[-87.449078,30.370399],[-87.451378,30.367199],[-87.451978,30.360299],[-87.450962,30.346262],[-87.452278,30.344099],[-87.459978,30.3363],[-87.462978,30.334],[-87.464878,30.3333],[-87.475579,30.3314],[-87.491879,30.3309],[-87.49998,30.328957],[-87.502572,30.327405],[-87.504701,30.324039],[-87.505943,30.319396],[-87.50578,30.3125],[-87.50468,30.308901],[-87.50278,30.307301],[-87.494879,30.305001],[-87.483679,30.304801],[-87.481879,30.306001],[-87.475879,30.3079],[-87.462978,30.3078],[-87.459578,30.3083],[-87.455578,30.3102],[-87.450078,30.3111],[-87.452378,30.300201],[-87.49998,30.287901],[-87.51838,30.283901],[-87.518324,30.280435],[-87.544533,30.275659],[-87.558097,30.274437],[-87.581362,30.269257],[-87.656888,30.249709],[-87.73553,30.240679],[-87.80056,30.229365],[-87.838462,30.227185],[-87.926119,30.230373],[-87.962253,30.229522],[-87.999996,30.225753],[-88.014572,30.222366],[-88.028401,30.221132],[-88.029272,30.222714],[-88.023991,30.23039],[-87.966847,30.235618],[-87.948979,30.256564],[-87.936041,30.261469],[-87.918247,30.253308],[-87.913762,30.247837],[-87.90046,30.241531],[-87.893201,30.239237],[-87.879343,30.23859],[-87.860085,30.240289],[-87.817743,30.254292],[-87.802087,30.253054],[-87.78775,30.254244],[-87.766626,30.262353],[-87.755263,30.277292],[-87.755516,30.291217],[-87.772758,30.311701],[-87.796717,30.324198],[-87.809266,30.332702],[-87.82988,30.353809],[-87.837239,30.369324],[-87.845132,30.377446],[-87.853806,30.378481],[-87.865017,30.38345],[-87.906343,30.40938],[-87.908908,30.41424],[-87.914136,30.446144],[-87.920031,30.470645],[-87.924211,30.4761],[-87.931902,30.4811],[-87.933355,30.487357],[-87.911141,30.525848],[-87.905343,30.537566],[-87.901711,30.550879],[-87.904168,30.565985],[-87.907891,30.573114],[-87.911431,30.576261],[-87.914956,30.585893],[-87.91253,30.615795],[-87.919346,30.63606],[-87.93107,30.652694],[-87.936717,30.657432],[-87.955989,30.658862],[-87.981196,30.67509],[-88.008396,30.684956],[-88.012444,30.68319],[-88.022076,30.673873],[-88.026706,30.66149],[-88.034588,30.653715],[-88.044339,30.652568],[-88.061998,30.644891],[-88.059598,30.619091],[-88.053998,30.612491],[-88.064898,30.588292],[-88.074898,30.578892],[-88.085493,30.563258],[-88.081617,30.546317],[-88.082792,30.528713],[-88.090734,30.52357],[-88.100874,30.50975],[-88.103768,30.500903],[-88.102988,30.493029],[-88.096867,30.471053],[-88.100646,30.46122],[-88.106437,30.452738],[-88.10407,30.4273],[-88.107274,30.377246],[-88.115432,30.35657],[-88.124611,30.341623],[-88.128052,30.338509],[-88.136173,30.320729],[-88.155775,30.327184],[-88.171967,30.324679],[-88.191542,30.317002],[-88.195664,30.321242],[-88.198361,30.338819],[-88.196353,30.343586],[-88.188532,30.345053],[-88.188527,30.348124],[-88.200065,30.362378],[-88.204495,30.362102],[-88.260695,30.382381],[-88.282635,30.382876],[-88.290649,30.370741],[-88.311608,30.368908],[-88.316525,30.369985],[-88.319599,30.380334],[-88.332277,30.38844],[-88.341345,30.38947],[-88.364022,30.388006],[-88.374671,30.385608],[-88.395023,30.369425],[-88.403547,30.5331],[-88.407462,30.631653],[-88.41863,30.866528],[-88.419562,30.875186],[-88.438211,31.231252],[-88.43878,31.252654],[-88.451045,31.459448],[-88.451575,31.481533],[-88.459478,31.621652],[-88.464425,31.697881],[-88.465107,31.722312],[-88.473227,31.893856],[-88.43865,32.172806],[-88.428278,32.250143],[-88.413819,32.373922],[-88.4125,32.380025],[-88.403789,32.44977],[-88.373338,32.711825],[-88.368349,32.747656],[-88.354292,32.87513],[-88.330934,33.073125],[-88.317135,33.184123],[-88.315235,33.203323],[-88.312535,33.220923],[-88.277421,33.512436],[-88.267148,33.591989],[-88.254622,33.69578],[-88.252257,33.719568],[-88.244142,33.781673],[-88.243025,33.79568],[-88.240054,33.810879],[-88.210741,34.029199],[-88.190678,34.190123],[-88.18762,34.204778],[-88.186667,34.220952],[-88.165634,34.383102],[-88.156292,34.463214],[-88.134263,34.62266],[-88.118407,34.724292],[-88.116418,34.746303],[-88.10756,34.811628],[-88.097888,34.892202],[-88.099999,34.894095],[-88.125038,34.902227],[-88.136692,34.907592],[-88.146335,34.914374],[-88.154617,34.922392],[-88.161594,34.933456],[-88.176106,34.962519],[-88.179973,34.967466],[-88.187429,34.974909],[-88.198811,34.991192],[-88.202959,35.008028],[-87.984916,35.005881]]],[[[-88.124658,30.28364],[-88.086812,30.259864],[-88.074854,30.249119],[-88.075856,30.246139],[-88.078786,30.245039],[-88.109432,30.242097],[-88.120151,30.246149],[-88.137083,30.249179],[-88.166569,30.249255],[-88.20854,30.244807],[-88.280571,30.230274],[-88.304773,30.228031],[-88.313323,30.230024],[-88.310025,30.233233],[-88.299705,30.231812],[-88.280781,30.233781],[-88.25837,30.239595],[-88.224615,30.245559],[-88.17335,30.252418],[-88.158303,30.252393],[-88.141143,30.255024],[-88.130631,30.262125],[-88.124722,30.273541],[-88.124658,30.28364]]]]},\"properties\":{\"name\":\"Alabama\",\"nation\":\"USA \"}}]}","edition":"Version 1.0: September 21, 2020; Version 1.1: September 29, 2020; Version 1.2: November 20, 2020","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, Tennessee 37211
The Clean Water Act (CWA) requires States to identify waters that are impaired for designated uses. These waters are published through a State’s §303(d) list. The CWA also requires that a total maximum daily load (TMDL) be completed for each water body to calculate the maximum amount of contaminants that can be present in that water body and still meet water-quality standards. The Mississippi Department of Environmental Quality (MDEQ) uses a statewide monitoring and assessment strategy to collect benthic macroinvertebrate community data to assess the health of streams and rivers and to identify impaired waters. Waters that are found to be impaired based on the macroinvertebrate community data are listed on the Mississippi §303(d) list, and the cause of impairment is listed as “biological impairment.” Although the CWA requires TMDLs to be developed for applicable contaminants identified in the §303(d) list, TMDLs cannot be computed for stream reaches in Mississippi listed for biological impairment because the actual stressors causing the impairment have not yet been determined. The MDEQ and other water-resource managers in Mississippi require a framework for stressor identification in biologically impaired streams and rivers. This report is organized to (1) provide a general overview of biological impairment and stressor identification in stream ecosystems and (2) provide a detailed framework for stressor identification of Mississippi streams that are biologically impaired. The intent is for the framework to reduce subjectivity, provide consistency, and allow for adaptation as the science evolves. The stressor identification framework for Mississippi involves six key steps:
Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
There is an active debate regarding the influence that climate has on the risk of armed conflict, which stems from challenges in assembling unbiased datasets, competing hypotheses on the mechanisms of climate influence, and the difficulty of disentangling direct and indirect climate effects. We use gridded historical non-state conflict records, satellite data, and land surface models in a structural equation modeling approach to uncover the direct and indirect effects of climate on violent conflicts in Africa and the Middle East (ME). We show that climate–conflict linkages in these regions are more complex than previously suggested, with multiple mechanisms at work. Warm temperatures and low rainfall direct effects on conflict risk were stronger than indirect effects through food and water supplies. Warming increases the risk of violence in Africa but unexpectedly decreases this risk in the ME. Furthermore, at the country level, warming decreases the risk of violence in most West African countries. Overall, we find a non-linear response of conflict to warming across countries that depends on the local temperature conditions. We further show that magnitude and sign of the effects largely depend on the scale of analysis and geographical context. These results imply that extreme caution should be exerted when attempting to explain or project local climate–conflict relationships based on a single, generalized theory.
","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/aba97d","usgsCitation":"Helman, D., Zaitchik, B., and Funk, C., 2020, Climate has contrasting direct and indirect effects on armed conflicts: Environmental Research Letters, v. 15, 104017, 12 p., https://doi.org/10.1088/1748-9326/aba97d.","productDescription":"104017, 12 p.","ipdsId":"IP-118530","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":455254,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/aba97d","text":"Publisher Index Page"},{"id":421737,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Africa, Middle East","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 19.94002207269733,\n -35.32488342223352\n ],\n [\n 22.30264497339894,\n -34.38790227386746\n ],\n [\n 23.468701613015384,\n -34.330881771106974\n ],\n [\n 24.692322260589634,\n -34.751812137152\n ],\n [\n 25.47740578859498,\n -34.205335553030366\n ],\n [\n 27.089639833842824,\n -33.933450403461386\n ],\n [\n 30.31986500109366,\n -31.23266766081391\n ],\n [\n 31.409895929342156,\n -29.645782996774948\n ],\n [\n 32.442018454769226,\n -28.706434295573864\n ],\n [\n 32.72807344689858,\n -27.67931853909235\n ],\n [\n 33.155428254383054,\n -26.651406714444256\n ],\n [\n 32.964823872325525,\n -25.964783617688084\n ],\n [\n 33.36331786114664,\n -25.571591912195487\n ],\n [\n 35.30713427567525,\n -24.914957583828226\n ],\n [\n 35.7979865007984,\n -23.94228074653921\n ],\n [\n 35.56379587404922,\n -21.75202362871562\n ],\n [\n 34.98380900973302,\n -20.21315923083297\n ],\n [\n 36.16787890081994,\n -19.058565142399104\n ],\n [\n 37.30379075659283,\n -18.141952374921246\n ],\n [\n 39.1570740642473,\n -17.136174010148267\n ],\n [\n 39.99171120001961,\n -16.660159360781748\n ],\n [\n 41.0682242251053,\n -14.963137368247516\n ],\n [\n 40.95578814573199,\n -13.91617034975775\n ],\n [\n 40.68453706291359,\n -11.32197128679266\n ],\n [\n 40.82399150919409,\n -10.408136406171039\n ],\n [\n 40.03587112306394,\n -9.687811393028198\n ],\n [\n 39.55135019679557,\n -8.351337185416625\n ],\n [\n 39.70380063000681,\n -7.759102760228316\n ],\n [\n 39.73448940774267,\n -6.525054669026602\n ],\n [\n 39.108079787535786,\n -6.107967406327589\n ],\n [\n 39.58097469277854,\n -4.84409176173132\n ],\n [\n 40.645240587098044,\n -2.8934219320360484\n ],\n [\n 41.88104116114013,\n -1.7828720395986863\n ],\n [\n 42.846321495888816,\n -0.3763238115751619\n ],\n [\n 44.6130426870549,\n 1.3337215653189958\n ],\n [\n 48.167052639206986,\n 4.331183120159068\n ],\n [\n 49.16834408109261,\n 6.010175574347983\n ],\n [\n 49.42171285060266,\n 6.820690067213022\n ],\n [\n 51.083092435806776,\n 9.331346786378674\n ],\n [\n 51.09186634984317,\n 9.964581280048904\n ],\n [\n 51.417978742067675,\n 10.409874729051978\n ],\n [\n 51.31740456005497,\n 11.946309528735128\n ],\n [\n 50.548027068333795,\n 12.137707830146951\n ],\n [\n 49.13115248025372,\n 11.620849558146801\n ],\n [\n 48.044004416821025,\n 11.620341939366227\n ],\n [\n 46.640305966378634,\n 11.172645312261139\n ],\n [\n 45.6818821835611,\n 11.173783061015001\n ],\n [\n 44.85771617549028,\n 10.664201285177285\n ],\n [\n 43.95570367871929,\n 10.92136306896731\n ],\n [\n 43.53468006805409,\n 12.337634188787533\n ],\n [\n 44.63249654579258,\n 12.462945550291067\n ],\n [\n 45.40715123624611,\n 12.460688162723486\n ],\n [\n 46.04516814467573,\n 12.9778695647599\n ],\n [\n 47.33441277143854,\n 13.236184533556226\n ],\n [\n 48.17434313101157,\n 13.69291801706241\n ],\n [\n 48.95159269475579,\n 13.693508689099573\n ],\n [\n 49.54353187819419,\n 14.483368364319986\n ],\n [\n 52.45048439205132,\n 15.294511212433378\n ],\n [\n 52.67672307262052,\n 16.03490718608431\n ],\n [\n 53.97539917620773,\n 16.590787557432222\n ],\n [\n 55.272295868559354,\n 16.744951146495865\n ],\n [\n 55.60119165612468,\n 17.575779323711444\n ],\n [\n 56.6505841850888,\n 17.734185659254948\n ],\n [\n 56.931023537253225,\n 18.580063447731078\n ],\n [\n 57.786190745158905,\n 18.67100789892801\n ],\n [\n 58.24612568829491,\n 19.68177200664104\n ],\n [\n 60.05265769556499,\n 22.328874054809575\n ],\n [\n 59.337662396660875,\n 23.00313362347829\n ],\n [\n 58.94891701312804,\n 23.986998500345578\n ],\n [\n 58.04717527908926,\n 23.945071379533317\n ],\n [\n 56.97287717626412,\n 24.327036972197277\n ],\n [\n 56.71482214696678,\n 25.002770135748136\n ],\n [\n 56.68322249986562,\n 26.382416748239436\n ],\n [\n 57.17070063245964,\n 25.59202815779247\n ],\n [\n 58.676121965719545,\n 25.225301577550084\n ],\n [\n 60.214965777158795,\n 25.159043398298465\n ],\n [\n 61.81891703028106,\n 24.767972487897396\n ],\n [\n 62.06419745864346,\n 25.89377886559474\n ],\n [\n 62.54067746803244,\n 26.27630135813702\n ],\n [\n 63.37132411744548,\n 26.475048050041366\n ],\n [\n 63.49612844788092,\n 27.348828650266924\n ],\n [\n 62.864819284375955,\n 27.34096287864965\n ],\n [\n 62.97969816227203,\n 28.46757179346359\n ],\n [\n 61.610289880664425,\n 28.946334314400005\n ],\n [\n 61.21617986516833,\n 29.756316129172163\n ],\n [\n 62.04507760662807,\n 30.78418231967639\n ],\n [\n 61.93880371125405,\n 31.609208653404238\n ],\n [\n 61.123694990545374,\n 31.657926463567577\n ],\n [\n 60.96416884310321,\n 33.19690540096326\n ],\n [\n 61.24098250005892,\n 33.65587172991026\n ],\n [\n 60.68014446739852,\n 34.100832237512975\n ],\n [\n 61.37778893601188,\n 35.295360732125076\n ],\n [\n 61.42207731796037,\n 37.16683418899123\n ],\n [\n 59.89938705101014,\n 37.14022532000317\n ],\n [\n 59.51311279139691,\n 37.81264159068715\n ],\n [\n 58.28141382660314,\n 37.852410555981976\n ],\n [\n 57.21082727514343,\n 38.44368272519014\n ],\n [\n 56.39825870656907,\n 38.28079136970368\n ],\n [\n 55.298477434057475,\n 38.313317401679086\n ],\n [\n 54.57054653381368,\n 37.66364651342535\n ],\n [\n 53.547115540902894,\n 37.277070008177446\n ],\n [\n 51.781381433329074,\n 36.78092615924875\n ],\n [\n 50.91881542810725,\n 37.14932110461429\n ],\n [\n 50.383758326423674,\n 37.53717473832667\n ],\n [\n 49.503701446808805,\n 37.83819954101962\n ],\n [\n 49.30554386715613,\n 38.53293744782087\n ],\n [\n 48.50445778069138,\n 38.74481923680315\n ],\n [\n 48.670294001732174,\n 39.57611903098851\n ],\n [\n 47.92223140258733,\n 40.1514552021095\n ],\n [\n 46.945529847290146,\n 39.50178038686741\n ],\n [\n 46.01830650523786,\n 38.978879982075654\n ],\n [\n 45.053554643285395,\n 39.80684483156452\n ],\n [\n 44.046760246680805,\n 40.43839356036679\n ],\n [\n 43.6249079503404,\n 41.106282629695045\n ],\n [\n 42.90323498588239,\n 41.75742402643124\n ],\n [\n 41.62252422329453,\n 41.66106401841387\n ],\n [\n 40.512535562924626,\n 41.42315765777036\n ],\n [\n 38.6650001027339,\n 41.24966415988362\n ],\n [\n 36.99350664605652,\n 41.445497150750185\n ],\n [\n 35.02930845574272,\n 42.207667080024464\n ],\n [\n 33.56682880457808,\n 42.37623650280301\n ],\n [\n 31.318427802977567,\n 41.7206235446414\n ],\n [\n 29.39188872358997,\n 41.37795096106814\n ],\n [\n 28.56826873786889,\n 41.14026093111161\n ],\n [\n 28.396234086451443,\n 40.60947947162197\n ],\n [\n 26.254566715084906,\n 40.54275800010683\n ],\n [\n 25.882843639873442,\n 39.799245920506024\n ],\n [\n 25.887913087032643,\n 38.43972809993258\n ],\n [\n 26.947493151003442,\n 37.10752875019402\n ],\n [\n 27.61471613216355,\n 36.45476489724595\n ],\n [\n 28.34965784789358,\n 36.37715629556908\n ],\n [\n 29.54455029450554,\n 35.692177580691606\n ],\n [\n 30.836693031864314,\n 36.138278105735054\n ],\n [\n 30.873544966309566,\n 36.58100171191616\n ],\n [\n 31.925076685025573,\n 36.24909711716805\n ],\n [\n 32.2101683223855,\n 35.57000610985477\n ],\n [\n 33.88641135517119,\n 36.00103050916614\n ],\n [\n 34.48801248649673,\n 36.391697693009476\n ],\n [\n 35.1923638846518,\n 36.21766024321968\n ],\n [\n 35.61631206049725,\n 34.85032826925669\n ],\n [\n 34.9077577942376,\n 33.343016135696075\n ],\n [\n 33.85416096751965,\n 31.759127544513035\n ],\n [\n 32.992768512281316,\n 31.292459779952807\n ],\n [\n 31.614985174930297,\n 32.105974456923875\n ],\n [\n 29.930963130519643,\n 31.635972223053315\n ],\n [\n 29.158984028978352,\n 31.01903074894362\n ],\n [\n 26.2216581093258,\n 31.7729641047508\n ],\n [\n 25.000377009242527,\n 32.245144600005375\n ],\n [\n 23.668070582513053,\n 32.459049388251685\n ],\n [\n 23.107657278439206,\n 32.96310058108104\n ],\n [\n 21.71014199823574,\n 33.160093933566145\n ],\n [\n 20.356047800860523,\n 32.95949696493204\n ],\n [\n 19.584714390664317,\n 32.2639768519892\n ],\n [\n 19.864982553329867,\n 31.297194007786544\n ],\n [\n 19.342823701795226,\n 30.582453064390947\n ],\n [\n 17.68092498748905,\n 31.266332818296476\n ],\n [\n 15.766257974669543,\n 31.497325770750436\n ],\n [\n 15.377378044184866,\n 32.45124800379622\n ],\n [\n 14.212745856800694,\n 32.99377918214702\n ],\n [\n 13.32152862524373,\n 33.08202328537372\n ],\n [\n 12.501487804749786,\n 33.03818943776618\n ],\n [\n 11.544926845602248,\n 33.55041764627683\n ],\n [\n 10.954014014126585,\n 34.115646508353834\n ],\n [\n 11.345642166618262,\n 35.10895420032685\n ],\n [\n 11.278560909331077,\n 35.67119111696948\n ],\n [\n 10.825375047128091,\n 36.29958742867444\n ],\n [\n 11.61312074284092,\n 36.98275267728964\n ],\n [\n 10.522554215425231,\n 37.241550688727884\n ],\n [\n 9.423193926467349,\n 37.61839781163684\n ],\n [\n 8.4884317037816,\n 37.17115159009515\n ],\n [\n 7.073296668578905,\n 37.27513161742192\n ],\n [\n 6.047737850605785,\n 37.31389837883957\n ],\n [\n 5.276827848278572,\n 37.03898075772244\n ],\n [\n 4.073845993270254,\n 37.247363941086746\n ],\n [\n 2.5790799165311284,\n 37.05286137068833\n ],\n [\n 1.2480316850837312,\n 36.789076681780486\n ],\n [\n -0.2795062688409473,\n 36.18079147002422\n ],\n [\n -1.7217935146900913,\n 35.56033258029477\n ],\n [\n -3.2851598807577034,\n 35.61268920609956\n ],\n [\n -4.792928187930954,\n 35.65549395688895\n ],\n [\n -5.064638297821176,\n 36.14250870710457\n ],\n [\n -6.248043120678176,\n 36.078974129038045\n ],\n [\n -6.975427609276721,\n 34.76271045321012\n ],\n [\n -7.152261425878123,\n 34.02836027763891\n ],\n [\n -8.301117576813539,\n 33.422168861304314\n ],\n [\n -9.665120800556991,\n 32.57250703196394\n ],\n [\n -10.36961142568714,\n 31.08326757350268\n ],\n [\n -10.093527325382155,\n 30.207854050117106\n ],\n [\n -10.629954374444338,\n 29.45605367499725\n ],\n [\n -11.858859915495714,\n 28.633033316001857\n ],\n [\n -13.075118224637947,\n 28.058097398022824\n ],\n [\n -13.76809763143325,\n 27.320557856957095\n ],\n [\n -14.816534801366316,\n 26.521870854700396\n ],\n [\n -15.26967065297913,\n 25.21858691556828\n ],\n [\n -16.09298474615491,\n 24.50612419859428\n ],\n [\n -16.605997558877988,\n 22.671841776392156\n ],\n [\n -17.410322929648714,\n 21.41829790875559\n ],\n [\n -16.935567854651595,\n 20.59995314703903\n ],\n [\n -16.865759261109872,\n 18.774919038122547\n ],\n [\n -16.375957722580864,\n 18.116805467033657\n ],\n [\n -16.825961508379294,\n 16.317347684829784\n ],\n [\n -17.45936414868504,\n 15.178174380805189\n ],\n [\n -17.762905594481452,\n 14.444729004234475\n ],\n [\n -16.904893689215044,\n 13.629903294993056\n ],\n [\n -16.933361637958257,\n 12.262956157784984\n ],\n [\n -15.506519704614504,\n 11.167491550263065\n ],\n [\n -14.884312807147694,\n 10.554476535543671\n ],\n [\n -13.679193966620744,\n 9.396228604594228\n ],\n [\n -13.859657496174549,\n 8.489187319238738\n ],\n [\n -13.05355127512297,\n 7.378748796875939\n ],\n [\n -11.65490647421612,\n 6.686294751047711\n ],\n [\n -10.15144224734101,\n 5.547793384340608\n ],\n [\n -8.552580036790857,\n 4.535765683638658\n ],\n [\n -7.699655854116173,\n 4.124938378509327\n ],\n [\n -6.1389257194393565,\n 4.699576789748775\n ],\n [\n -4.535099988874862,\n 4.813994698476506\n ],\n [\n -3.0106101645667707,\n 4.723716232552675\n ],\n [\n -2.063701591863719,\n 4.359819347000155\n ],\n [\n 0.010361784833548882,\n 5.333318277144826\n ],\n [\n 1.7651823251995893,\n 5.840774898417777\n ],\n [\n 3.082502393172831,\n 6.085657070063661\n ],\n [\n 4.214292065000251,\n 6.136606605002143\n ],\n [\n 4.780549333638646,\n 5.560975393781888\n ],\n [\n 5.2221471675146915,\n 4.666473001409017\n ],\n [\n 5.855927567883015,\n 4.016187270465224\n ],\n [\n 8.088030342845116,\n 4.2083774456593375\n ],\n [\n 9.252088619549625,\n 3.716064402211316\n ],\n [\n 9.58182380603995,\n 3.056803832373973\n ],\n [\n 9.202192248128881,\n 2.0988566332550818\n ],\n [\n 9.095228604303003,\n 0.658594388998381\n ],\n [\n 8.917642763773301,\n -0.19726839314429867\n ],\n [\n 8.284982036640486,\n -0.9726443999896048\n ],\n [\n 9.311970805338035,\n -2.4849817092955817\n ],\n [\n 11.268358153066401,\n -4.431013661657801\n ],\n [\n 11.719430669021932,\n -5.495105262588822\n ],\n [\n 11.840542000923335,\n -6.506908742229598\n ],\n [\n 12.884346780100202,\n -8.101428588501165\n ],\n [\n 12.754365300012893,\n -9.296474933781354\n ],\n [\n 13.46048418043722,\n -10.866551299090006\n ],\n [\n 13.152217764969976,\n -12.243749352883853\n ],\n [\n 12.428221243589377,\n -13.125665018289908\n ],\n [\n 11.890403365497434,\n -15.062987053908046\n ],\n [\n 11.576175248454291,\n -15.649012548238545\n ],\n [\n 11.564546845073892,\n -16.78455618126023\n ],\n [\n 11.491770137096353,\n -17.922241729574267\n ],\n [\n 12.76647104316288,\n -20.13775946567617\n ],\n [\n 13.187626316108805,\n -20.88142419784087\n ],\n [\n 14.143181823756208,\n -22.438806833278306\n ],\n [\n 14.107589454253343,\n -23.99313504309056\n ],\n [\n 14.458435365294719,\n -24.95871930175535\n ],\n [\n 14.657531358340634,\n -26.337386083308687\n ],\n [\n 15.326220102219764,\n -28.059682790972857\n ],\n [\n 16.360424012635548,\n -28.914601919225525\n ],\n [\n 16.543091422097206,\n -29.80826293490204\n ],\n [\n 17.656055886512377,\n -31.757689842805576\n ],\n [\n 17.75363502546861,\n -32.47808237790934\n ],\n [\n 17.267364332028592,\n -32.925799257079035\n ],\n [\n 18.147380983915525,\n -34.24219803258757\n ],\n [\n 19.94002207269733,\n -35.32488342223352\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 47.41038492915342,\n -25.412155860912122\n ],\n [\n 48.38282385089997,\n -21.971869332281315\n ],\n [\n 48.91388175094784,\n -20.339791135720503\n ],\n [\n 49.75751024249058,\n -18.216495300819062\n ],\n [\n 49.815255750033174,\n -17.283316959635556\n ],\n [\n 50.77182451637913,\n -15.4702338353691\n ],\n [\n 50.376592163779776,\n -14.602426820736113\n ],\n [\n 50.30364952478146,\n -13.353352668404426\n ],\n [\n 49.78741300935263,\n -12.480121286716567\n ],\n [\n 49.27457238513867,\n -11.601771506392296\n ],\n [\n 48.510430008336186,\n -12.360398683659355\n ],\n [\n 47.7426346547245,\n -13.488173017251313\n ],\n [\n 47.096048997235926,\n -14.79585957296085\n ],\n [\n 45.99513132651262,\n -15.345688646969919\n ],\n [\n 44.23221922094211,\n -16.00091658609189\n ],\n [\n 44.01886129326675,\n -16.806416772301375\n ],\n [\n 43.605860367154065,\n -17.545232273330967\n ],\n [\n 44.14170720964151,\n -19.67824957989835\n ],\n [\n 43.559015359683485,\n -21.04742153496828\n ],\n [\n 42.9857172115363,\n -21.792994252760565\n ],\n [\n 43.31473647785114,\n -23.57690504550159\n ],\n [\n 43.453752956471476,\n -24.99149037491543\n ],\n [\n 44.32817214255897,\n -25.77970280511022\n ],\n [\n 45.29701935262412,\n -26.179352727463474\n ],\n [\n 46.43446808688989,\n -25.537552078419807\n ],\n [\n 47.41038492915342,\n -25.412155860912122\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2020-09-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Helman, David","contributorId":330683,"corporation":false,"usgs":false,"family":"Helman","given":"David","affiliations":[{"id":37540,"text":"John Hopkins University","active":true,"usgs":false}],"preferred":false,"id":885582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zaitchik, Benjamin F.","contributorId":330684,"corporation":false,"usgs":false,"family":"Zaitchik","given":"Benjamin F.","affiliations":[{"id":37540,"text":"John Hopkins University","active":true,"usgs":false}],"preferred":false,"id":885583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Funk, Chris 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":167070,"corporation":false,"usgs":true,"family":"Funk","given":"Chris","email":"cfunk@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":885584,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70223247,"text":"70223247 - 2020 - Temporal and spatial changes in Myotis lucifugus acoustic activity before and after white-nose syndrome on Fort Drum Army Installation, New York, USA","interactions":[],"lastModifiedDate":"2021-08-19T16:47:04.818752","indexId":"70223247","displayToPublicDate":"2020-09-20T11:42:49","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":629,"text":"Acta Chiropterologica","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Temporal and spatial changes in Myotis lucifugus acoustic activity before and after white-nose syndrome on Fort Drum Army Installation, New York, USA","title":"Temporal and spatial changes in Myotis lucifugus acoustic activity before and after white-nose syndrome on Fort Drum Army Installation, New York, USA","docAbstract":"Changes to bat distribution and habitat associations at the local to sub-landscape scale in the post white-nose syndrome (WNS) environment have received little attention to date despite being critical information for managers. To better understand the spatial nature of bat population declines, we modelled both activity patterns and occupancy from acoustic surveys for the Myotis lucifugus (little brown bat) on Fort Drum Military Installation in New York, USA over 15 summers (2003–2017) that span the pre-WNS, WNS-advent (2008) and post-WNS periods, using a set of generalized linear mixed models and geospatial analysis. Our best supported model indicated significant differences between years with significant declines in activity post-WNS. M. lucifugus activity was most closely associated with woody wetland habitats over the study period, however, the spatial patterns of high activity areas were variable over years, with the areal extent of these high activity areas decreasing post-WNS. Our best supported occupancy model varied by year. However, the null occupancy model [Ψ(.)] was either competing (within 2 ΔAIC units) or was the best supported model. Meaning that none of our environmental variables seemed to impact occupancy, and when they did, these differences were not significant. There was high disagreement between our relative activity models and predictions compared to our occupancy models, suggesting that geographic spatial scale and the resolution of the data impacts model outcome. Our results indicate that continued acoustic monitoring of bat species in the Northeast to assess ongoing temporal and spatial changes in habitat associations and to provide direction for future mist-netting studies should rely more on relative activity as the metric of choice rather than site occupancy.
","language":"English","publisher":"Museum and Institute of Zoology PAS","doi":"10.3161/15081109ACC2020.22.1.011","usgsCitation":"Ford, W., Nocera, T., Silvis, A., and Dobony, C.A., 2020, Temporal and spatial changes in Myotis lucifugus acoustic activity before and after white-nose syndrome on Fort Drum Army Installation, New York, USA: Acta Chiropterologica, v. 22, no. 1, p. 121-134, https://doi.org/10.3161/15081109ACC2020.22.1.011.","productDescription":"14 p.","startPage":"121","endPage":"134","ipdsId":"IP-101094","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":455261,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10919/102442","text":"External Repository"},{"id":388164,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fort Drum Army Installation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.574951171875,\n 44.006644643819655\n ],\n [\n -75.36895751953125,\n 44.188112606916484\n ],\n [\n -75.56121826171875,\n 44.268804788566165\n ],\n [\n -75.8660888671875,\n 44.05403780323783\n ],\n [\n -75.75897216796875,\n 43.98688630934305\n ],\n [\n -75.574951171875,\n 44.006644643819655\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":821520,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nocera, Tomás","contributorId":264425,"corporation":false,"usgs":false,"family":"Nocera","given":"Tomás","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":821521,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Silvis, Alexander","contributorId":264426,"corporation":false,"usgs":false,"family":"Silvis","given":"Alexander","affiliations":[{"id":54472,"text":"RES Inc.","active":true,"usgs":false}],"preferred":false,"id":821522,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dobony, Christopher A.","contributorId":264428,"corporation":false,"usgs":false,"family":"Dobony","given":"Christopher","email":"","middleInitial":"A.","affiliations":[{"id":54473,"text":"Fort Drum Military Installation","active":true,"usgs":false}],"preferred":false,"id":821523,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228508,"text":"70228508 - 2020 - A demographic projection model to support conservation decision making for an endangered snake with limited monitoring data","interactions":[],"lastModifiedDate":"2022-02-11T15:35:55.593402","indexId":"70228508","displayToPublicDate":"2020-09-20T09:28:56","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":774,"text":"Animal Conservation","active":true,"publicationSubtype":{"id":10}},"title":"A demographic projection model to support conservation decision making for an endangered snake with limited monitoring data","docAbstract":"Conservation planning for rare and threatened species is often made more difficult by a lack of research and monitoring data. In such cases, managers may rely on qualitative assessments of species risk that lack explicit acknowledgement of uncertainty. Snakes are a group of conservation concern that are also notoriously difficult to monitor. Here, we demonstrate a quantitative population projection for a data-deficient species, the Puerto Rican boa (Chilabothrus inornatus) using expert knowledge and published information about species life history and threats to persistence. Using this model, we simulated population dynamics over 30 years under four scenarios of future urbanization and found that there was an increased probability of population decline as urbanization rates increased. We conduct a sensitivity analysis to evaluate the sensitivity of outcomes to model inputs, a practice that may also be useful in recovery planning. The sensitivity analyses also provide insight into how the future trajectories would change if the elicited demographic rates are incorrect. Even when data are sparse, quantitative methods can often be used to produce rigorous and reproducible estimates of future status with quantifiable uncertainty.
","language":"English","publisher":"Wiley","doi":"10.1111/acv.12641","usgsCitation":"Tucker, A.M., McGowan, C.P., Mulero Oliveras, E., Angeli, N., and Zegarra, J., 2020, A demographic projection model to support conservation decision making for an endangered snake with limited monitoring data: Animal Conservation, v. 24, no. 2, p. 291-301, https://doi.org/10.1111/acv.12641.","productDescription":"11 p.","startPage":"291","endPage":"301","ipdsId":"IP-117213","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-65.3277,18.295843],[-65.337451,18.308308],[-65.327318,18.323666],[-65.342068,18.34529],[-65.335701,18.349535],[-65.329334,18.341955],[-65.321754,18.338316],[-65.309833,18.337973],[-65.304409,18.332054],[-65.298328,18.330529],[-65.255933,18.342117],[-65.221568,18.320959],[-65.222853,18.310464],[-65.249857,18.296691],[-65.260282,18.290823],[-65.283269,18.280214],[-65.3277,18.295843]]],[[[-67.89174,18.11397],[-67.887099,18.112574],[-67.87643,18.114157],[-67.869804,18.118851],[-67.861548,18.122144],[-67.848245,18.10832],[-67.843202,18.094858],[-67.843615,18.085099],[-67.845293,18.081938],[-67.853098,18.078195],[-67.865598,18.06544],[-67.871462,18.0578],[-67.895921,18.052342],[-67.904431,18.05913],[-67.918778,18.063116],[-67.927841,18.068572],[-67.940799,18.079716],[-67.934479,18.111306],[-67.932185,18.113221],[-67.91088,18.119668],[-67.89174,18.11397]]],[[[-65.308717,18.145172],[-65.302295,18.141089],[-65.294896,18.14283],[-65.287962,18.148097],[-65.275165,18.13443],[-65.276214,18.131936],[-65.283248,18.132999],[-65.296036,18.12799],[-65.322794,18.126589],[-65.327184,18.124106],[-65.338506,18.112439],[-65.342037,18.11138],[-65.350493,18.111914],[-65.364733,18.120377],[-65.397837,18.110873],[-65.399791,18.108832],[-65.411767,18.106211],[-65.423765,18.097764],[-65.426311,18.093749],[-65.45138,18.086096],[-65.45681,18.087778],[-65.465849,18.087715],[-65.468768,18.092643],[-65.47979,18.096352],[-65.507265,18.091646],[-65.524209,18.081977],[-65.542087,18.081177],[-65.558646,18.08566],[-65.569305,18.091616],[-65.570628,18.097325],[-65.57686,18.103224],[-65.575579,18.115669],[-65.546199,18.119329],[-65.511712,18.13284],[-65.489829,18.135912],[-65.46791,18.143767],[-65.437058,18.15766],[-65.399517,18.161935],[-65.371373,18.157517],[-65.334289,18.147761],[-65.313476,18.144296],[-65.308717,18.145172]]],[[[-66.438813,18.485713],[-66.420921,18.488639],[-66.410344,18.489886],[-66.394287,18.489748],[-66.377286,18.488044],[-66.37282,18.487726],[-66.349647,18.486335],[-66.337728,18.48562],[-66.315477,18.474724],[-66.31503,18.47468],[-66.291225,18.472347],[-66.283675,18.472203],[-66.276599,18.478129],[-66.269799,18.480281],[-66.258015,18.476906],[-66.251547,18.472464],[-66.241797,18.46874],[-66.220148,18.466],[-66.199032,18.466163],[-66.192664,18.466212],[-66.183886,18.460506],[-66.179218,18.455305],[-66.172315,18.451462],[-66.159796,18.451706],[-66.153037,18.454457],[-66.14395,18.459761],[-66.139572,18.462317],[-66.139451,18.462387],[-66.139443,18.462315],[-66.138532,18.453305],[-66.133085,18.445881],[-66.127938,18.444632],[-66.125198,18.451209],[-66.124284,18.456324],[-66.123188,18.45943],[-66.123343,18.460363],[-66.125015,18.470435],[-66.118338,18.469581],[-66.092098,18.466535],[-66.083254,18.462022],[-66.073987,18.4581],[-66.043272,18.453655],[-66.03944,18.454441],[-66.036559,18.450216],[-66.036491,18.450117],[-66.023221,18.443875],[-66.006523,18.444347],[-65.99718,18.449895],[-65.992935,18.457489],[-65.992793,18.458102],[-65.992349,18.460024],[-65.99079,18.460419],[-65.958492,18.451354],[-65.92567,18.444881],[-65.916843,18.444619],[-65.907756,18.446893],[-65.904988,18.450926],[-65.878683,18.438322],[-65.838825,18.431865],[-65.831476,18.426849],[-65.828457,18.423543],[-65.816691,18.410663],[-65.794556,18.402845],[-65.787666,18.402544],[-65.774937,18.413951],[-65.77053,18.41294],[-65.769749,18.409473],[-65.771695,18.406277],[-65.750455,18.385208],[-65.750179,18.38505],[-65.742154,18.380459],[-65.733567,18.382211],[-65.699069,18.368156],[-65.669636,18.362102],[-65.668845,18.361939],[-65.634431,18.369835],[-65.627246,18.376436],[-65.626527,18.381728],[-65.624975,18.386553],[-65.622761,18.387771],[-65.618229,18.386496],[-65.614891,18.382473],[-65.619068,18.367755],[-65.628198,18.353711],[-65.63419,18.338965],[-65.628047,18.328252],[-65.626456,18.298982],[-65.634389,18.292349],[-65.635826,18.288271],[-65.634893,18.283923],[-65.630833,18.264989],[-65.623111,18.248012],[-65.597618,18.234289],[-65.589947,18.228225],[-65.593795,18.224059],[-65.615981,18.227389],[-65.626731,18.235484],[-65.638181,18.229121],[-65.637565,18.224444],[-65.628414,18.205149],[-65.635281,18.199975],[-65.639688,18.205656],[-65.662185,18.207018],[-65.664127,18.207136],[-65.690749,18.19499],[-65.694515,18.187011],[-65.691021,18.178998],[-65.695856,18.179324],[-65.710895,18.186963],[-65.712533,18.189146],[-65.717999,18.190176],[-65.728471,18.185588],[-65.734664,18.180368],[-65.738834,18.174066],[-65.739125,18.173453],[-65.743632,18.163957],[-65.758728,18.156601],[-65.766919,18.148424],[-65.777584,18.129239],[-65.796711,18.083746],[-65.796289,18.079835],[-65.794686,18.078607],[-65.795028,18.073561],[-65.796711,18.069842],[-65.801831,18.058527],[-65.809174,18.056818],[-65.817107,18.063378],[-65.825848,18.057482],[-65.83109,18.050664],[-65.834274,18.038988],[-65.832429,18.014916],[-65.839591,18.015077],[-65.850913,18.011954],[-65.870335,18.006597],[-65.875122,18.002826],[-65.884937,17.988521],[-65.896102,17.99026],[-65.905319,17.983974],[-65.910537,17.981855],[-65.924738,17.976087],[-65.976611,17.967669],[-65.98455,17.969411],[-65.985358,17.971854],[-65.995185,17.978989],[-66.007731,17.980541],[-66.017308,17.979583],[-66.019539,17.978354],[-66.024,17.975896],[-66.046585,17.954853],[-66.049033,17.954561],[-66.058217,17.959238],[-66.068678,17.966335],[-66.069979,17.966357],[-66.08141,17.966552],[-66.116194,17.949141],[-66.127009,17.946953],[-66.140661,17.94102],[-66.147912,17.933963],[-66.155387,17.929406],[-66.159742,17.928613],[-66.161232,17.931747],[-66.175626,17.933565],[-66.186914,17.935363],[-66.189726,17.933936],[-66.200174,17.929515],[-66.206961,17.932268],[-66.213374,17.944614],[-66.202655,17.944753],[-66.185554,17.940997],[-66.179548,17.943727],[-66.174839,17.948214],[-66.176814,17.950438],[-66.206207,17.96305],[-66.206807,17.963307],[-66.215355,17.959376],[-66.218081,17.95729],[-66.231519,17.943912],[-66.229181,17.934651],[-66.232013,17.931154],[-66.252737,17.934574],[-66.260684,17.936083],[-66.270905,17.947098],[-66.275651,17.94826],[-66.290782,17.946491],[-66.297679,17.959148],[-66.31695,17.976683],[-66.323659,17.978536],[-66.338152,17.976492],[-66.33839,17.976458],[-66.362511,17.968231],[-66.365098,17.964832],[-66.368777,17.957717],[-66.371591,17.951469],[-66.385059,17.939004],[-66.391227,17.945819],[-66.398945,17.950925],[-66.412131,17.957286],[-66.445481,17.979379],[-66.450368,17.983226],[-66.454888,17.986784],[-66.461342,17.990273],[-66.491396,17.990262],[-66.510143,17.985618],[-66.540537,17.975476],[-66.583233,17.961229],[-66.589658,17.969386],[-66.594392,17.970682],[-66.605035,17.969015],[-66.623788,17.98105],[-66.631944,17.982746],[-66.645651,17.98026],[-66.657797,17.974605],[-66.664391,17.968259],[-66.672819,17.966451],[-66.699115,17.977568],[-66.709856,17.982109],[-66.713394,17.987763],[-66.716957,17.990344],[-66.731118,17.991658],[-66.746248,17.990349],[-66.750427,17.995443],[-66.753964,17.99959],[-66.755341,18.001203],[-66.764491,18.006317],[-66.770307,18.005955],[-66.799656,17.99245],[-66.806866,17.983786],[-66.807924,17.979606],[-66.806903,17.976046],[-66.805683,17.975052],[-66.795106,17.977438],[-66.789302,17.980793],[-66.784953,17.978326],[-66.787245,17.972914],[-66.80827,17.965635],[-66.8224,17.954499],[-66.838584,17.949931],[-66.852288,17.955004],[-66.856474,17.956553],[-66.859471,17.954316],[-66.862545,17.952022],[-66.871697,17.952707],[-66.88344,17.952526],[-66.899639,17.948298],[-66.904585,17.950527],[-66.906532,17.955356],[-66.906276,17.963368],[-66.924529,17.972808],[-66.928651,17.970204],[-66.930414,17.963127],[-66.916127,17.959102],[-66.909483,17.952559],[-66.909359,17.94988],[-66.912522,17.947446],[-66.930313,17.943389],[-66.932636,17.939998],[-66.931581,17.9369],[-66.919298,17.932062],[-66.923826,17.926923],[-66.927261,17.926875],[-66.959998,17.940216],[-66.980516,17.951648],[-66.98105,17.952505],[-66.982669,17.9551],[-66.982206,17.961192],[-66.987287,17.970663],[-66.996738,17.972899],[-67.003972,17.970799],[-67.014744,17.968468],[-67.024522,17.970722],[-67.062478,17.973819],[-67.076534,17.967759],[-67.089827,17.951418],[-67.101468,17.946621],[-67.109985,17.945806],[-67.109986,17.945806],[-67.128251,17.948153],[-67.133733,17.951919],[-67.167031,17.963073],[-67.178566,17.964792],[-67.183508,17.962706],[-67.188717,17.950989],[-67.187474,17.946252],[-67.183694,17.937982],[-67.183457,17.931135],[-67.194785,17.932826],[-67.196924,17.935651],[-67.197273,17.937461],[-67.197517,17.941514],[-67.197668,17.943549],[-67.198988,17.94782],[-67.200973,17.949896],[-67.210034,17.953595],[-67.212101,17.956027],[-67.21433,17.962436],[-67.215271,17.983464],[-67.211973,17.992993],[-67.207694,17.998019],[-67.177893,18.008882],[-67.174299,18.011149],[-67.172397,18.014906],[-67.172138,18.021422],[-67.173761,18.024548],[-67.193269,18.03185],[-67.209887,18.035439],[-67.196694,18.066491],[-67.190656,18.064269],[-67.184589,18.06775],[-67.183938,18.069914],[-67.186465,18.074195],[-67.192999,18.076877],[-67.198212,18.076828],[-67.199314,18.091135],[-67.19529,18.096149],[-67.183921,18.103683],[-67.182182,18.108507],[-67.176554,18.151046],[-67.178618,18.159318],[-67.180822,18.168055],[-67.180701,18.168182],[-67.155185,18.195001],[-67.152665,18.203493],[-67.158001,18.216719],[-67.173,18.230666],[-67.175429,18.248008],[-67.187843,18.266671],[-67.187873,18.266874],[-67.189971,18.281015],[-67.196056,18.290443],[-67.209963,18.294974],[-67.225403,18.296648],[-67.226081,18.296722],[-67.235137,18.299935],[-67.267484,18.353149],[-67.27135,18.362329],[-67.268259,18.366989],[-67.260671,18.370197],[-67.23909,18.375318],[-67.226744,18.378247],[-67.216998,18.382078],[-67.202167,18.389908],[-67.160144,18.415587],[-67.159608,18.415915],[-67.156599,18.418983],[-67.155245,18.424401],[-67.156619,18.439562],[-67.161746,18.453462],[-67.169011,18.466352],[-67.169016,18.478488],[-67.164144,18.487396],[-67.14283,18.505485],[-67.138249,18.507776],[-67.125655,18.511706],[-67.103468,18.514523],[-67.093752,18.515757],[-67.07929,18.513256],[-67.020276,18.510603],[-66.988958,18.497724],[-66.95954,18.489878],[-66.957733,18.489129],[-66.957517,18.489171],[-66.944636,18.491693],[-66.906872,18.483556],[-66.90143,18.484552],[-66.867386,18.490785],[-66.849673,18.490745],[-66.83694,18.487659],[-66.836635,18.487701],[-66.79932,18.492775],[-66.780311,18.491411],[-66.764893,18.484097],[-66.749301,18.476701],[-66.742067,18.474681],[-66.733986,18.473457],[-66.710743,18.472611],[-66.683719,18.481367],[-66.679876,18.484944],[-66.664364,18.487809],[-66.645839,18.488777],[-66.624618,18.494199],[-66.586778,18.484948],[-66.584074,18.484287],[-66.565241,18.485523],[-66.562916,18.48845],[-66.563485,18.490512],[-66.558503,18.489987],[-66.53484,18.481253],[-66.533487,18.481663],[-66.529476,18.482877],[-66.511609,18.476848],[-66.470292,18.46907],[-66.456486,18.46892],[-66.449184,18.470991],[-66.441852,18.479751],[-66.439961,18.485525],[-66.438813,18.485713]]]]},\"properties\":{\"name\":\"Puerto Rico\",\"nation\":\"USA \"}}]}","volume":"24","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-09-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Tucker, A. M.","contributorId":276002,"corporation":false,"usgs":false,"family":"Tucker","given":"A.","email":"","middleInitial":"M.","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":834463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":167162,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor","email":"cmcgowan@usgs.gov","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":834464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mulero Oliveras, E.","contributorId":276003,"corporation":false,"usgs":false,"family":"Mulero Oliveras","given":"E.","email":"","affiliations":[{"id":38462,"text":"University of Puerto Rico","active":true,"usgs":false}],"preferred":false,"id":834465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Angeli, N.F.","contributorId":276004,"corporation":false,"usgs":false,"family":"Angeli","given":"N.F.","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":834466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zegarra, J.P.","contributorId":242909,"corporation":false,"usgs":false,"family":"Zegarra","given":"J.P.","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":834467,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70216752,"text":"70216752 - 2020 - Ultra‐high‐resolution mapping of biocrusts with Unmanned Aerial Systems","interactions":[],"lastModifiedDate":"2021-01-19T16:11:50.809644","indexId":"70216752","displayToPublicDate":"2020-09-19T10:14:41","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5347,"text":"Remote Sensing in Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Ultra‐high‐resolution mapping of biocrusts with Unmanned Aerial Systems","docAbstract":"Biological soil crusts (biocrusts) occur in drylands globally where they support ecosystem functioning by increasing soil stability, reducing dust emissions and modifying soil resource availability (e.g. water, nutrients). Determining biocrust condition and extent across landscapes continues to present considerable challenges to scientists and land managers. Biocrusts grow in patches, cover vast expanses of rugged terrain and are vulnerable to physical disturbance associated with ground‐based mapping techniques. As such, remote sensing offers promising opportunities to map and monitor biocrusts. While satellite‐based remote sensing has been used to detect biocrusts at relatively large spatial scales, few studies have used high‐resolution imagery from Unmanned Aerial Systems (UAS) to map fine‐scale patterns of biocrusts. We collected sub‐centimeter, true color 3‐band imagery at 10 plots in sagebrush and pinyon‐juniper woodland communities in a semiarid ecosystem in the southwestern US and used object‐based image analysis (OBIA) to segment and classify the imagery into maps of light and dark biocrusts, bare soil, rock and various vegetation covers. We used field data to validate the classifications and assessed the spatial distribution and configuration of different classes using fragmentation metrics. Map accuracies ranged from 46 to 77% (average 65%) and were higher in pinyon‐juniper (average 70%) versus sagebrush (average 60%) plots. Biocrust classes showed generally high accuracies at both pinyon‐juniper plots (average dark crust = 70%; light crust = 80%) and sagebrush plots (average dark crust = 69%; light crust = 77%). Point cloud density, sun elevation and spectral confusion between vegetation cover explained some differences in accuracy across plots. Spatial analyses of classified maps showed that biocrust patches in pinyon‐juniper plots were generally larger, more aggregated and contiguous than in sagebrush plots. Pinyon‐juniper plots also had greater patch richness and a lower Shannon evenness index than sagebrush plots, suggesting greater soil cover heterogeneity in this plant community type.
Hydrological and bioclimatic processes that lead to drought may stress plants and wildlife, restructure plant community type and architecture, increase monotypic stands and bare soils, facilitate the invasion of non‐native plant species and accelerate soil erosion. Our study focuses on the impact of a paucity of Colorado River surface flows from the United States (U.S.) to Mexico. We measured change in riparian plant greenness and water use over the past two decades using remotely sensed measurements of vegetation index (VI), evapotranspiration (ET), and a new annualized Phenology Assessment Metric (PAM) for ET. We measure these long‐term (2000‐2019) metrics and their short‐term (2014‐2019) response to an environmental, pulse flow in 2014, as prescribed under Minute 319 of the 1944 Water Treaty between the two nations. In subsequent years, small directed flows were provided to restoration areas under Minute 323. We use 250 m MODIS and 30 m Landsat imagery to evaluate three vegetation indices (NDVI, EVI, EVI2). We select EVI2 to parameterize an optical‐based ET algorithm and test the relationship between ET from Landsat and MODIS by regression approaches. Our analyses show significant decreases in VIs and ET for both the 20‐year and post‐pulse 5‐year periods. Over the last 20 years, EVI Landsat declined 34% (30% by EVIMODIS) and ETLandsat‐EVI declined 38% (27% by ETMODIS‐EVI), overall ca. 1.61 mmd‐1 or 476 mmyr‐1 drop in ET. Over the 5 years since the 2014 pulse flow, EVI Landsat declined 20% (13% by EVIMODIS) and ETLandsat‐EVI declined 23% (4% by ETMODIS‐EVI) with a 0.77 mmd‐1 or a 209 mmyr‐1 5‐year drop in ET. Data and change maps show the pulse flow contributed enough water to slow the rate of loss, but only for the very short‐term (1‐2 years). These findings are critically important as they suggest further deterioration of biodiversity, wildlife habitat and key ecosystem services due to anthropogenic diversions of water in the U.S. and Mexico and from land clearing, fires, and plant‐related drought which affect hydrological processes.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.13911","usgsCitation":"Nagler, P.L., Barreto-Muñoz, A., Chavoshi Borujeni, S., Jarchow, C., Gómez‐Sapiens, M., Nouri, H., Herrmann, S.M., and Didan, K., 2020, Ecohydrological responses to surface flow across borders: Two decades of changes in vegetation greenness and water use in the riparian corridor of the Colorado River Delta: Hydrological Processes, v. 34, no. 25, p. 4851-4883, https://doi.org/10.1002/hyp.13911.","productDescription":"33 p.; Data Release","startPage":"4851","endPage":"4883","ipdsId":"IP-117414","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":378804,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":436784,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98PGDJ1","text":"USGS data release","linkHelpText":"Colorado River Delta Project: A compilation of vegetation indices, phenology assessment metrics, estimates of evapotranspiration and change maps for seven reaches of the delta's 150 km region, for nearly the last two decades"}],"country":"Mexico, United States","otherGeospatial":"Colorado River delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.15869140624999,\n 31.606609719226917\n ],\n [\n -114.521484375,\n 31.606609719226917\n ],\n [\n -114.521484375,\n 32.76880048488168\n ],\n [\n -115.15869140624999,\n 32.76880048488168\n ],\n [\n -115.15869140624999,\n 31.606609719226917\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"25","noUsgsAuthors":false,"publicationDate":"2020-10-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":799708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barreto-Muñoz, Armando","contributorId":239891,"corporation":false,"usgs":false,"family":"Barreto-Muñoz","given":"Armando","affiliations":[{"id":48028,"text":"University of Arizona, Biosystems Engineering, Tucson, AZ, 85721 USA","active":true,"usgs":false}],"preferred":false,"id":799709,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chavoshi Borujeni, Sattar","contributorId":241612,"corporation":false,"usgs":false,"family":"Chavoshi Borujeni","given":"Sattar","email":"","affiliations":[{"id":48363,"text":"Soil Conservation and Watershed Management Research Department, Isfahan Agricultural and Natural Resources Research and Education Centre, AREEO, Isfahan, Iran","active":true,"usgs":false}],"preferred":false,"id":799710,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jarchow, Christopher J. 0000-0002-0424-4104","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":211737,"corporation":false,"usgs":false,"family":"Jarchow","given":"Christopher J.","affiliations":[{"id":38314,"text":"USGS Southwest Biological Science Center, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":799711,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gómez‐Sapiens, Marth M.","contributorId":241615,"corporation":false,"usgs":false,"family":"Gómez‐Sapiens","given":"Marth M.","affiliations":[],"preferred":false,"id":799732,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nouri, Hamideh","contributorId":178847,"corporation":false,"usgs":false,"family":"Nouri","given":"Hamideh","affiliations":[],"preferred":false,"id":799733,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Herrmann, Stefanie M. 0000-0002-4069-2019","orcid":"https://orcid.org/0000-0002-4069-2019","contributorId":20234,"corporation":false,"usgs":true,"family":"Herrmann","given":"Stefanie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":799734,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Didan, Kamel","contributorId":130999,"corporation":false,"usgs":false,"family":"Didan","given":"Kamel","email":"","affiliations":[{"id":7204,"text":"University of Arizona, Electrical and Computer Engineering","active":true,"usgs":false}],"preferred":false,"id":799735,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70224628,"text":"70224628 - 2020 - The influence of soil age on ecosystem structure and function across biomes","interactions":[],"lastModifiedDate":"2021-10-01T13:29:58.920691","indexId":"70224628","displayToPublicDate":"2020-09-18T08:26:28","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"The influence of soil age on ecosystem structure and function across biomes","docAbstract":"The importance of soil age as an ecosystem driver across biomes remains largely unresolved. By combining a cross-biome global field survey, including data for 32 soil, plant, and microbial properties in 16 soil chronosequences, with a global meta-analysis, we show that soil age is a significant ecosystem driver, but only accounts for a relatively small proportion of the cross-biome variation in multiple ecosystem properties. Parent material, climate, vegetation and topography predict, collectively, 24 times more variation in ecosystem properties than soil age alone. Soil age is an important local-scale ecosystem driver; however, environmental context, rather than soil age, determines the rates and trajectories of ecosystem development in structure and function across biomes. Our work provides insights into the natural history of terrestrial ecosystems. We propose that, regardless of soil age, changes in the environmental context, such as those associated with global climatic and land-use changes, will have important long-term impacts on the structure and function of terrestrial ecosystems across biomes.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41467-020-18451-3","usgsCitation":"Delgado-Baquerizo, M., Reich, P.B., Bardgett, R., Eldridge, D.J., Lambers, H., Wardle, D., Reed, S., Plaza, C., Png, G.K., Neuhauser, S., Berhe, A.A., Hart, S., Hu, H., He, J., Bastida, F., Abades, S.R., Alfaro, F.D., Cutler, N.A., Gallardo, A., García-Velázquez, L., Hayes, P.E., Hseu, Z., Perez, C.A., Santos, F., Siebe, C., Trivedi, P., Sullivan, B.W., Weber-Grullon, L., Williams, M., and Fierer, N., 2020, The influence of soil age on ecosystem structure and function across biomes: Nature Communications, v. 11, 4721, 14 p., https://doi.org/10.1038/s41467-020-18451-3.","productDescription":"4721, 14 p.","ipdsId":"IP-117229","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":455286,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-020-18451-3","text":"Publisher Index Page"},{"id":390114,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2020-09-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Delgado-Baquerizo, Manuel","contributorId":214645,"corporation":false,"usgs":false,"family":"Delgado-Baquerizo","given":"Manuel","email":"","affiliations":[{"id":39101,"text":"Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, USA","active":true,"usgs":false}],"preferred":false,"id":824408,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reich, Peter B.","contributorId":202370,"corporation":false,"usgs":false,"family":"Reich","given":"Peter","email":"","middleInitial":"B.","affiliations":[{"id":36398,"text":"Department of Forest Resources, University of Minnesota, St. Paul, MN","active":true,"usgs":false}],"preferred":false,"id":824409,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bardgett, Richard D.","contributorId":266148,"corporation":false,"usgs":false,"family":"Bardgett","given":"Richard D.","affiliations":[{"id":54928,"text":"School of Earth and Environmental Sciences, Michael Smith Building, The University of Manchester, Oxford Road, Manchester M13 9PT, UK","active":true,"usgs":false}],"preferred":false,"id":824410,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eldridge, David J. 0000-0002-2191-486X","orcid":"https://orcid.org/0000-0002-2191-486X","contributorId":207298,"corporation":false,"usgs":false,"family":"Eldridge","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":37514,"text":"Center for Ecosystem Science, University of New South Wales, Sydney, NSW 2052, Australia","active":true,"usgs":false}],"preferred":false,"id":824411,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lambers, Hans","contributorId":266149,"corporation":false,"usgs":false,"family":"Lambers","given":"Hans","affiliations":[{"id":54929,"text":"School of Biological Sciences, The University of Western Australia, 35 Stirling Hwy, Crawley (Perth), WA 6009, Australia","active":true,"usgs":false}],"preferred":false,"id":824412,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wardle, David A.","contributorId":266150,"corporation":false,"usgs":false,"family":"Wardle","given":"David A.","affiliations":[{"id":54930,"text":"Asian School of the Environment, Nanyang Technological University, 50 Nanyang avenue, Singapore 639798","active":true,"usgs":false}],"preferred":false,"id":824413,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":824414,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Plaza, Cesar","contributorId":266151,"corporation":false,"usgs":false,"family":"Plaza","given":"Cesar","email":"","affiliations":[{"id":54931,"text":"Instituto de Ciencias Agrarias, Consejo Superior de Investigaciones Científicas, Serrano 115 bis, 28006, Madrid, Spain","active":true,"usgs":false}],"preferred":false,"id":824415,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Png, Guochen K.","contributorId":266152,"corporation":false,"usgs":false,"family":"Png","given":"Guochen","email":"","middleInitial":"K.","affiliations":[{"id":54928,"text":"School of Earth and Environmental Sciences, Michael Smith Building, The University of Manchester, Oxford Road, Manchester M13 9PT, UK","active":true,"usgs":false}],"preferred":false,"id":824416,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Neuhauser, Sigrid","contributorId":214697,"corporation":false,"usgs":false,"family":"Neuhauser","given":"Sigrid","email":"","affiliations":[],"preferred":false,"id":824417,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Berhe, Asmeret A.","contributorId":214701,"corporation":false,"usgs":false,"family":"Berhe","given":"Asmeret","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":824418,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hart, Stephen C.","contributorId":240757,"corporation":false,"usgs":false,"family":"Hart","given":"Stephen C.","affiliations":[],"preferred":false,"id":824419,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hu, Hang-Wei","contributorId":240759,"corporation":false,"usgs":false,"family":"Hu","given":"Hang-Wei","email":"","affiliations":[],"preferred":false,"id":824420,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"He, Ji-Zheng","contributorId":240758,"corporation":false,"usgs":false,"family":"He","given":"Ji-Zheng","email":"","affiliations":[],"preferred":false,"id":824421,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Bastida, Felipe","contributorId":240755,"corporation":false,"usgs":false,"family":"Bastida","given":"Felipe","email":"","affiliations":[],"preferred":false,"id":824422,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Abades, Sebastian R.","contributorId":214700,"corporation":false,"usgs":false,"family":"Abades","given":"Sebastian","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":824423,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Alfaro, Fernando D.","contributorId":207304,"corporation":false,"usgs":false,"family":"Alfaro","given":"Fernando","email":"","middleInitial":"D.","affiliations":[{"id":37517,"text":"GEMA Center for Genomics, Ecology & Environment, Universidad Mayor, Camino La Piramide 5750, Huechuraba, Santiago, Chile","active":true,"usgs":false}],"preferred":false,"id":824424,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Cutler, Nick A.","contributorId":214703,"corporation":false,"usgs":false,"family":"Cutler","given":"Nick","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":824425,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Gallardo, Antonio","contributorId":266153,"corporation":false,"usgs":false,"family":"Gallardo","given":"Antonio","affiliations":[{"id":54932,"text":"Departamento de Sistemas Físicos, Químicos y Naturales, Universidad Pablo de Olavide, 41013 Sevilla, Spain","active":true,"usgs":false}],"preferred":false,"id":824426,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"García-Velázquez, Laura","contributorId":214699,"corporation":false,"usgs":false,"family":"García-Velázquez","given":"Laura","affiliations":[],"preferred":false,"id":824427,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Hayes, Patrick E.","contributorId":214704,"corporation":false,"usgs":false,"family":"Hayes","given":"Patrick","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":824428,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Hseu, Zeng-Yei","contributorId":214705,"corporation":false,"usgs":false,"family":"Hseu","given":"Zeng-Yei","email":"","affiliations":[],"preferred":false,"id":824429,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Perez, Cecilia A.","contributorId":214708,"corporation":false,"usgs":false,"family":"Perez","given":"Cecilia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":824430,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Santos, Fernanda","contributorId":243276,"corporation":false,"usgs":false,"family":"Santos","given":"Fernanda","affiliations":[],"preferred":false,"id":824431,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Siebe, Christina","contributorId":214710,"corporation":false,"usgs":false,"family":"Siebe","given":"Christina","email":"","affiliations":[],"preferred":false,"id":824432,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Trivedi, Pankaj","contributorId":240760,"corporation":false,"usgs":false,"family":"Trivedi","given":"Pankaj","email":"","affiliations":[],"preferred":false,"id":824433,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Sullivan, Benjamin W.","contributorId":207086,"corporation":false,"usgs":false,"family":"Sullivan","given":"Benjamin","email":"","middleInitial":"W.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":824434,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Weber-Grullon, Luis","contributorId":214711,"corporation":false,"usgs":false,"family":"Weber-Grullon","given":"Luis","email":"","affiliations":[],"preferred":false,"id":824435,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Williams, Mark","contributorId":214696,"corporation":false,"usgs":false,"family":"Williams","given":"Mark","affiliations":[],"preferred":false,"id":824436,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Fierer, Noah","contributorId":138711,"corporation":false,"usgs":false,"family":"Fierer","given":"Noah","email":"","affiliations":[{"id":6713,"text":"University of Colorado, Boulder CO","active":true,"usgs":false}],"preferred":false,"id":824437,"contributorType":{"id":1,"text":"Authors"},"rank":30}]}} ,{"id":70213529,"text":"70213529 - 2020 - A new decision support tool for collaborative adaptive vegetation management in northern Great Plains national parks","interactions":[],"lastModifiedDate":"2020-09-18T13:05:44.799112","indexId":"70213529","displayToPublicDate":"2020-09-18T08:04:04","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6665,"text":"Parks Stewardship Forum","active":true,"publicationSubtype":{"id":10}},"title":"A new decision support tool for collaborative adaptive vegetation management in northern Great Plains national parks","docAbstract":"National Park Service (NPS) units in the northern Great Plains (NGP) were established to preserve and interpret the history of America, protect and showcase unusual geology and paleontology, and provide a home for vanishing large wildlife. A unifying feature among these national parks, monuments, and historic sites is mixed-grass prairie, which not only provides background scenery but is the very foundation of many park missions. As recognition of the prairie’s importance to park fundamental resources and values has grown, so too has the realization that invasive plants threaten these values by reducing native species diversity, altering food webs, and marring the visitor experience. Parks manage invasive species despite uncertainties in treatment effectiveness because management cannot wait for research to provide definitive answers. Under these circumstances, adaptive management (AM) is an appropriate approach. In the NGP, we formed a collaborative adaptive vegetation management team to apply AM towards reducing invasive species (with a focus on exotic annual grasses) and improving native vegetation conditions. In our AM framework, the team uses a Bayesian model built from NPS Inventory & Monitoring and Fire Effects monitoring data and experimental results to predict the effects of management actions on park management units, according to those units’ vegetation condition and management history. These predictions inform management decisions, which are then applied.
","language":"English","publisher":"University of California at Berkeley","doi":"10.5070/P536349865","usgsCitation":"Ashton, I.W., Symstad, A., Baldwin, H., Post van der Burg, M., Bekedam, S., Borgman, E., Haar, M., Hogan, T., Rockwood, S., Swanson, D., Thomson, C., and Wienk, C., 2020, A new decision support tool for collaborative adaptive vegetation management in northern Great Plains national parks: Parks Stewardship Forum, v. 3, no. 36, 11 p., https://doi.org/10.5070/P536349865.","productDescription":"11 p.","ipdsId":"IP-115660","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":455290,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5070/p536349865","text":"Publisher Index Page"},{"id":378563,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"36","noUsgsAuthors":false,"publicationDate":"2020-09-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Ashton, Isabel W.","contributorId":240922,"corporation":false,"usgs":false,"family":"Ashton","given":"Isabel","email":"","middleInitial":"W.","affiliations":[{"id":38111,"text":"National Park Service, Rapid City, SD","active":true,"usgs":false}],"preferred":false,"id":799138,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Symstad, Amy 0000-0003-4231-2873 asymstad@usgs.gov","orcid":"https://orcid.org/0000-0003-4231-2873","contributorId":201095,"corporation":false,"usgs":true,"family":"Symstad","given":"Amy","email":"asymstad@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":799139,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baldwin, Heather 0000-0003-1939-5439 baldwinh@usgs.gov","orcid":"https://orcid.org/0000-0003-1939-5439","contributorId":5635,"corporation":false,"usgs":true,"family":"Baldwin","given":"Heather","email":"baldwinh@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":799140,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Post van der Burg, Max 0000-0002-3943-4194 maxpostvanderburg@usgs.gov","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":4947,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","email":"maxpostvanderburg@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":799141,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bekedam, Steven","contributorId":240924,"corporation":false,"usgs":false,"family":"Bekedam","given":"Steven","email":"","affiliations":[{"id":29837,"text":"National Park Service, Yellowstone National Park, WY","active":true,"usgs":false}],"preferred":false,"id":799142,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Borgman, Erin","contributorId":240926,"corporation":false,"usgs":false,"family":"Borgman","given":"Erin","email":"","affiliations":[{"id":48162,"text":"National Park Service, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":799143,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Haar, Milton","contributorId":240927,"corporation":false,"usgs":false,"family":"Haar","given":"Milton","affiliations":[{"id":48163,"text":"National Park Service, Interior, SD","active":true,"usgs":false}],"preferred":false,"id":799144,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hogan, Terri","contributorId":240929,"corporation":false,"usgs":false,"family":"Hogan","given":"Terri","email":"","affiliations":[{"id":48162,"text":"National Park Service, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":799145,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rockwood, Stephanie","contributorId":240930,"corporation":false,"usgs":false,"family":"Rockwood","given":"Stephanie","email":"","affiliations":[{"id":38111,"text":"National Park Service, Rapid City, SD","active":true,"usgs":false}],"preferred":false,"id":799146,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Swanson, Daniel J","contributorId":240932,"corporation":false,"usgs":false,"family":"Swanson","given":"Daniel J","affiliations":[{"id":48165,"text":"National Park Service, Hot Springs, SD","active":true,"usgs":false}],"preferred":false,"id":799147,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Thomson, Carmen","contributorId":240933,"corporation":false,"usgs":false,"family":"Thomson","given":"Carmen","email":"","affiliations":[{"id":48167,"text":"National Park Service, Omaha, NE","active":true,"usgs":false}],"preferred":false,"id":799148,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wienk, Cody","contributorId":240934,"corporation":false,"usgs":false,"family":"Wienk","given":"Cody","affiliations":[{"id":48167,"text":"National Park Service, Omaha, NE","active":true,"usgs":false}],"preferred":false,"id":799149,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70214657,"text":"70214657 - 2020 - Landsat Collection 2 geometric calibration updates","interactions":[],"lastModifiedDate":"2020-10-02T11:59:42.820426","indexId":"70214657","displayToPublicDate":"2020-09-17T12:58:44","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Landsat Collection 2 geometric calibration updates","docAbstract":"The U.S. Geological Survey (USGS) changed the management and delivery of Landsat products to the public in its archive through the implementation of Collections. The Collections process ensures consistent data quality through time and across all the Landsat sensors with a few modifications to the metadata. The consistent data products from Collections are more conducive for applications such as time-series analysis, because the data can be used without a need for sensor-specific geometric or radiometric adjustments. The Collections process also allows for calibration improvements from updated reference sources, model trending, and enhanced algorithms that are grouped together and applied at one time, thus limiting the operational impacts to users. The first collection, Collection-1 was released in 2016, and Collection-2 is expected to be released in 2020. This paper addresses the geometric improvements to the Collection -2 dataset. Geometric improvements in Collection-2 include improvements to the geometric accuracy and interoperability of all Landsat products by implementing the Sentinel 2 Global Reference Image (GRI), improved elevation dataset using NASADEM and other sources of Digital Elevation Model (DEM) for terrain correction, improvements to the precision correction process for Enhanced Thematic Mapper Plus (ETM+) and Thematic Mapper (TM) sensors, changes to the Thermal Infrared Sensor (TIRS) to Operational Land Imager (OLI) alignment estimates, thermal band detector alignments and focal plane adjustments for ETM+, and improvements to the ETM+ sensor to attitude control system (ACS).
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings: Earth observing systems XXV","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Earth Observing Systems XXV","conferenceDate":"Aug 24-Sep 4, 2020","language":"English","publisher":"SPIE","doi":"10.1117/12.2570429","usgsCitation":"Rengarajan, R., Choate, M.J., Storey, J.C., Franks, S., and Micijevic, E., 2020, Landsat Collection 2 geometric calibration updates, in Proceedings: Earth observing systems XXV, v. 11501, Aug 24-Sep 4, 2020, 115010N, 11 p., https://doi.org/10.1117/12.2570429.","productDescription":"115010N, 11 p.","ipdsId":"IP-122667","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":378968,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11501","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rengarajan, R. 0000-0003-1860-7110","orcid":"https://orcid.org/0000-0003-1860-7110","contributorId":56036,"corporation":false,"usgs":true,"family":"Rengarajan","given":"R.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":800336,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Choate, Michael J. 0000-0002-8101-4994","orcid":"https://orcid.org/0000-0002-8101-4994","contributorId":216866,"corporation":false,"usgs":true,"family":"Choate","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":800337,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Storey, James C. 0000-0002-6664-7232 storey@usgs.gov","orcid":"https://orcid.org/0000-0002-6664-7232","contributorId":5333,"corporation":false,"usgs":true,"family":"Storey","given":"James","email":"storey@usgs.gov","middleInitial":"C.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":800436,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Franks, Shannon 0000-0003-1335-5401","orcid":"https://orcid.org/0000-0003-1335-5401","contributorId":93362,"corporation":false,"usgs":true,"family":"Franks","given":"Shannon","affiliations":[],"preferred":false,"id":800437,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Micijevic, Esad 0000-0002-3828-9239 emicijevic@usgs.gov","orcid":"https://orcid.org/0000-0002-3828-9239","contributorId":3075,"corporation":false,"usgs":true,"family":"Micijevic","given":"Esad","email":"emicijevic@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":800438,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70215257,"text":"70215257 - 2020 - Comparability and reproducibility of biomarker ratio values measured by GC-QQQ-MS","interactions":[],"lastModifiedDate":"2020-10-15T13:14:16.860035","indexId":"70215257","displayToPublicDate":"2020-09-17T07:15:34","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2958,"text":"Organic Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Comparability and reproducibility of biomarker ratio values measured by GC-QQQ-MS","docAbstract":"The Norwegian Geochemical Standard North Sea Oil-1 was analyzed by gas chromatography triple quadrupole mass spectrometry (GC-QQQ-MS) on two instruments using independently developed analytical methods. Biomarker ratios determined by GC-QQQ-MS were compared to each other and to previously reported values determined by gas chromatography single quadrupole mass spectrometry (GC-Q-MS) or flame ionization detection (GC-FID). Hopane, sterane, and tricyclic ratio values determined by GC-QQQ-MS in multiple reaction monitoring (MRM) mode are comparable to each other, but their comparability to reported values measured by GC-Q-MS in selected ion monitoring (SIM) mode depends in part on whether the compounds in the ratio have similar or dissimilar mass spectral responses. For example, sterane and hopane stereoisomer thermal maturity ratios measured by GC-QQQ-MS in MRM mode agree with previously reported GC-Q-MS SIM values, but an offset is observed for ratios of rearranged hopanes or steranes to their non-rearranged counterparts. Triaromatic steroid, monoaromatic steroid, phenanthrene, and methylphenanthrene ratios measured by GC-QQQ-MS are comparable to each other and to reported GC-Q-MS SIM values. The carbon preference index is comparable across GC-QQQ-MS measurements and reported GC-FID values, while comparability is more variable for other ratios based on pristane, phytane, and/or n-alkanes. Comparability of variably acquired biomarker data could be enhanced in the future by developing instrument- and ratio-specific correction factors or by modifying GC-QQQ-MS parameters and MRM transitions to more closely reproduce previously reported values.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.orggeochem.2020.104124","usgsCitation":"French, K.L., Leider, A., and Hallmann, C., 2020, Comparability and reproducibility of biomarker ratio values measured by GC-QQQ-MS: Organic Geochemistry, v. 150, 104124, 4 p., https://doi.org/10.1016/j.orggeochem.2020.104124.","productDescription":"104124, 4 p.","ipdsId":"IP-119234","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":455295,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.orggeochem.2020.104124","text":"Publisher Index Page"},{"id":436788,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99ZMFJ5","text":"USGS data release","linkHelpText":"Data Release for "Comparability and reproducibility of biomarker ratio values measured by GC-QQQ-MS""},{"id":379343,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"150","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"French, Katherine L. 0000-0002-0153-8035","orcid":"https://orcid.org/0000-0002-0153-8035","contributorId":205462,"corporation":false,"usgs":true,"family":"French","given":"Katherine","email":"","middleInitial":"L.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":801281,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leider, Arne","contributorId":242996,"corporation":false,"usgs":false,"family":"Leider","given":"Arne","email":"","affiliations":[{"id":48601,"text":"Max-Planck-Institute for Biogeochemistry, Jena, Germany","active":true,"usgs":false}],"preferred":false,"id":801282,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hallmann, Christian","contributorId":242997,"corporation":false,"usgs":false,"family":"Hallmann","given":"Christian","email":"","affiliations":[{"id":48601,"text":"Max-Planck-Institute for Biogeochemistry, Jena, Germany","active":true,"usgs":false}],"preferred":false,"id":801283,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70213277,"text":"sir20205068 - 2020 - Temperature and water-quality diversity and the effects of surface-water connection in off-channel features of the Willamette River, Oregon, 2015–16","interactions":[],"lastModifiedDate":"2020-09-17T16:54:15.231751","indexId":"sir20205068","displayToPublicDate":"2020-09-16T13:50:58","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":"2020-5068","displayTitle":"Temperature and Water-Quality Diversity and the Effects of Surface-Water Connection in Off-Channel Features of the Willamette River, Oregon, 2015–16","title":"Temperature and water-quality diversity and the effects of surface-water connection in off-channel features of the Willamette River, Oregon, 2015–16","docAbstract":"Water-quality conditions (including temperature) in the Willamette River and many of its adjacent off-channel features, such as alcoves and side channels, were monitored between river miles 67 (near Salem, Oregon) and 168 (near Eugene, Oregon) during the summers of 2015 and 2016. One or more parameters (water temperature, dissolved oxygen, pH, specific conductance, and [or] water depth) were continuously measured at sites in the main channel (9 sites in 2015; 5 sites in 2016) and select off-channel features (20 features in 2015; 22 features in 2016). This study was initiated in reaction to the unusually warm, dry weather and resulting low streamflows that occurred in the Pacific Northwest in 2015 and the need for flow managers to understand the effects of streamflow on water-quality conditions in off-channel features of the Willamette River. Field monitoring was focused on documenting water-quality conditions during low summer streamflows and during fluctuations in streamflow, including when side channels became alcoves and reconnected to become side channels again.
Water in the main channel of the Willamette River upstream from river mile 50 near Newberg typically is well mixed during summer, with warm water temperatures (greater than 18 degrees Celsius) and high dissolved-oxygen concentrations (often greater than 7.7 milligrams per liter). During low summer flows, a diverse suite of off-channel features exists adjacent to the main channel of the Willamette River. Despite temporal and spatial variability within individual features, comparison of continuous water-temperature data between the main channel and off-channel features indicated that some off-channel features were consistently cooler than the main channel, some were consistently warmer than the main channel, and others frequently fluctuated between warmer or cooler than the main channel. Site-specific characteristics including upstream connection, depth, and presence or absence of aquatic or riparian vegetation were factors that seemed to affect the water quality of a feature.
Results from this study showed a relation between the geomorphology, hydrology, ecology, and water quality of an off-channel feature. Data confirmed that many features that can be classified as cold-water refuges based on water-temperature standards also contained low concentrations of dissolved oxygen that may not be suitable for sensitive fish species. A simplified site classification scheme is proposed that links water-quality conditions in measured off-channel features with site-specific characteristics and summer streamflows. The site classification scheme was extended to create a theoretical process matrix that relates measured water-quality conditions to a list of the processes and site-specific characteristics that could create those conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205068","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Portland District","usgsCitation":"Smith, C.D., Mangano, J.F., and Rounds, S.A., 2020, Temperature and water-quality diversity and the effects of surface-water connection in off-channel features of the Willamette River, Oregon, 2015–16: U.S. Geological Survey Scientific Investigations Report 2020–5068, 70 p., https://doi.org/10.3133/sir20205068.","productDescription":"Report: viii, 70 p.; 3 Data Releases","onlineOnly":"Y","ipdsId":"IP-102289","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":378475,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F73T9FPK","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Continuous temperature measurements to assess upstream connection of off-channel features of the middle and upper Willamette River, Oregon, summer, 2016"},{"id":378473,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VQ315D","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Point measurements of temperature and water quality in main-channel and off-channel features of the Willamette River, 2015 -16"},{"id":378472,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5068/sir20205068.pdf","text":"Report","size":"11.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5068"},{"id":378471,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5068/coverthb.jpg"},{"id":378474,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77M06DV","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water surface elevations recorded by submerged water level loggers in off-channel features of the middle and upper Willamette River, Oregon, summer, 2016"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.46435546875,\n 44.133333\n ],\n [\n -122.43713378906249,\n 44.133333\n ],\n [\n -122.43713378906249,\n 45.216667\n ],\n [\n -123.46435546875,\n 45.216667\n ],\n [\n -123.46435546875,\n 44.133333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Plants and animals undergo certain recurring life-cycle events, such as migrations between summer and winter habitats or the annual blooming of plants. Known as phenology, the timing of these events is very sensitive to changes in climate (and changes in one species’ phenology can impact entire food webs and ecosystems). Shifts in phenology have been described as a “fingerprint” of the temporal and spatial responses of wildlife to climate change impacts. Thus, phenology provides one of the strongest indicators of the adaptive capacity of organisms (or the ability of organisms to cope with future environmental conditions).
In this study, researchers are exploring how the timing and occurrence of a number of highly migratory marine animals is changing due to a series of climatic and ecological shifts. First, using existing long-term historical data series, they will determine the direction and magnitude of how migration, abundance, or other phenological factors have changed for marine mammals, sea turtles, and fishes that migrate into the Gulf of Maine on a seasonal basis. Because marine animals are inherently difficult to detect, the team will apply dynamic occupancy models to evaluate seasonal migration patterns and habitat use across multiple habitats in the Gulf of Maine region. The project team will also synthesize regional information on a key, ecologically-important prey fish, sandlance, whose timing and abundance is a strong predictor of the occurrence and behavior of predator species targeted in this study as well as a range of other regional fish and wildlife of conservation and management concern. Results from this component of the project will identify coastal fish and wildlife species that are relatively more or less able to adapt and thus potentially vulnerable to climate change; determine the likely primary drivers of those changes; and identify data gaps and future monitoring needs. Ultimately, this information will be available and useful for regional coastal management and adaptation decisions that will allow managers to effectively plan for the future.
In a second component of the project, researchers will focus specifically on changes in migration patterns of the endangered North Atlantic right whale. While shifts in the distribution and time of recurring life events are adaptive responses that may help species cope with climate impacts, they can also lead to changes in how species interact with humans. The North Atlantic right whale is one of the most endangered whale species on the planet. In the North Atlantic Ocean, ship strikes and entanglements with commercial fishing gear represent fatal threats to right whales. Recent reports suggest that North Atlantic right whale migration patterns have changed. Many researchers posit that shifts in migration are responsible for recent increases in the overlap between right whales and human activities, especially fishing. To help understand how changes in right whale movements and behaviors may overlap with ship traffic, and thus put the animals at risk of encountering vessels, we will combine right whale habitat models with ship traffic maps. The end result will be a set of maps identifying risk levels.
Power consumption coefficients (PCCs) and dedicated flowmeter records for irrigation wells in three Utah groundwater basins were analyzed to develop a method to better characterize the accuracy of annual groundwater withdrawal estimates. The PCC method has been used by the U.S. Geological Survey in Utah since 1963 as a way to estimate groundwater withdrawal. As a result, most irrigation wells in Utah have historic records consisting of multiple PCCs. Over time, numerous wells have been retrofitted with dedicated flowmeters to more accurately describe groundwater use for irrigation. The combination of historical PCCs and flowmeter data was examined to classify wells as simple, complex, or borderline. The PCCs for each well were statistically analyzed for each period of record to determine the PCC coefficient of variation (CV). Variance, standard deviation, and CV also were calculated for each well, yielding similar results. The CV was selected as the best statistical method for classifying wells. Through field verification and examination of records, CV thresholds were established, allowing wells to be classified as simple, complex, or borderline. This well classification provides information on the uncertainty and best methods for quantifying annual groundwater withdrawals from irrigation wells in a basin.
Annual irrigation groundwater withdrawals in Tooele, Parowan, and Goshen Valleys were calculated by using various combinations of historical PCC records and data from dedicated flowmeters. Differences between annual groundwater withdrawal using the most recent measurements, and historic minimum, maximum, mean, and median PCCs were compared. The smallest percent difference between annual groundwater withdrawal calculated using the most recently measured PCCs, which is the current method for calculating withdrawal in most basins, in Tooele and Parowan Valleys, was 7 and 9 percent respectively, using historical median and mean.
In Goshen Valley, most wells have dedicated flowmeters, and there is a subset of wells that have 2016 power usage data, historical PCC records, and 2016 reported dedicated flowmeter withdrawal. Using this subset of irrigation wells, the smallest percent different between withdrawal from dedicated flowmeters and withdrawal calculated by using other methods was 5 percent (using withdrawal calculated with historical mean PCCs for each well). Annual groundwater withdrawal calculated using the most recently measured PCCs was 9-percent less than dedicated flowmeter reported withdrawal. So, if withdrawal from dedicated flowmeters is as close to reality as possible, then in the case of Goshen Valley, using historical mean PCCs to calculate withdrawal is closer to reality than using the most recently measured PCCs to calculate withdrawal.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201106","collaboration":"Water Availability and Use Science ProgramDirector, Utah Water Science Center
U.S. Geological Survey
2329 West Orton Circle
Salt Lake City, Utah 84119-2047
Motion‐activated wildlife cameras (or “camera traps”) are frequently used to remotely and noninvasively observe animals. The vast number of images collected from camera trap projects has prompted some biologists to employ machine learning algorithms to automatically recognize species in these images, or at least filter‐out images that do not contain animals. These approaches are often limited by model transferability, as a model trained to recognize species from one location might not work as well for the same species in different locations. Furthermore, these methods often require advanced computational skills, making them inaccessible to many biologists. We used 3 million camera trap images from 18 studies in 10 states across the United States of America to train two deep neural networks, one that recognizes 58 species, the “species model,” and one that determines if an image is empty or if it contains an animal, the “empty‐animal model.” Our species model and empty‐animal model had accuracies of 96.8% and 97.3%, respectively. Furthermore, the models performed well on some out‐of‐sample datasets, as the species model had 91% accuracy on species from Canada (accuracy range 36%–91% across all out‐of‐sample datasets) and the empty‐animal model achieved an accuracy of 91%–94% on out‐of‐sample datasets from different continents. Our software addresses some of the limitations of using machine learning to classify images from camera traps. By including many species from several locations, our species model is potentially applicable to many camera trap studies in North America. We also found that our empty‐animal model can facilitate removal of images without animals globally. We provide the trained models in an R package (MLWIC2: Machine Learning for Wildlife Image Classification in R), which contains Shiny Applications that allow scientists with minimal programming experience to use trained models and train new models in six neural network architectures with varying depths.
Spatially distributed populations often rely on large-scale processes for long-term population stability. These processes are driven by individuals moving across the landscape through long-distance dispersal movements. However, as landscapes are continually altered by anthropogenic development, increased fragmentation and avoidance behavior can affect landscape permeability and limit dispersal. Lesser prairie-chickens (Tympanuchus pallidicinctus) are a species of concern that have lost significant portions (>90%) of their historic distribution in the Southern Great Plains of the United States and are currently being impacted by continued anthropogenic development. Using GPS telemetry locations of 346 lesser prairie-chickens across their entire geographic distribution, we identified 184 different long-distance movements that drive population connectivity. We used empirical cumulative distribution functions to create a selection–avoidance–neutral curve and estimated the spatial scale of response to anthropogenic features (i.e., towers and windmills, large transmission and smaller distribution powerlines, oil wells, roads, and fences) during these movements. In addition, we tested for behavioral differences between movement types (e.g., exploratory loops vs. long-distance movements between home ranges) and for regional differences in response among study areas. We found that during long-distance movements, lesser prairie-chickens generally avoided all anthropogenic feature types we tested despite some variation in the reported response distance among study areas. However, they avoided the tallest features (i.e., towers and windmills and transmission powerlines) at much greater distances in comparison with the shorter features in our analysis. Our results show that long-distance movements are likely affected by responses to functional landscape fragmentation through increased development of anthropogenic features in important connectivity zones. As our estimated response distances during long-distance movements varied in comparison with previously reported response distances during other behavioral states (e.g., breeding or nesting), using long-distance or dispersal specific movement data may be more appropriate when asking questions related to connectivity across the landscape.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3202","usgsCitation":"Peterson, J.M., Earl, J.E., Fuhlendorf, S.D., Elmore, D., Haukos, D.A., Tanner, A.M., and Carleton, S., 2020, Estimating response distances of lesser prairie-chickens to anthropogenic features during long-distance movements: Ecosphere, v. 11, no. 9, e03202, 15 p., https://doi.org/10.1002/ecs2.3202.","productDescription":"e03202, 15 p.","ipdsId":"IP-101823","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":455320,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3202","text":"Publisher Index Page"},{"id":388350,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Kansas, New Mexico, Oklahoma, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.94140625,\n 32.32427558887655\n ],\n [\n -98.349609375,\n 32.32427558887655\n ],\n [\n -98.349609375,\n 40.245991504199026\n ],\n [\n -104.94140625,\n 40.245991504199026\n ],\n [\n -104.94140625,\n 32.32427558887655\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"9","noUsgsAuthors":false,"publicationDate":"2020-09-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Peterson, Jacob M.","contributorId":264585,"corporation":false,"usgs":false,"family":"Peterson","given":"Jacob","email":"","middleInitial":"M.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":821703,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Earl, Julia E.","contributorId":264586,"corporation":false,"usgs":false,"family":"Earl","given":"Julia","email":"","middleInitial":"E.","affiliations":[{"id":54510,"text":"ltu","active":true,"usgs":false}],"preferred":false,"id":821704,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fuhlendorf, Samuel D.","contributorId":264587,"corporation":false,"usgs":false,"family":"Fuhlendorf","given":"Samuel","email":"","middleInitial":"D.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":821705,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Elmore, Dwayne","contributorId":264588,"corporation":false,"usgs":false,"family":"Elmore","given":"Dwayne","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":821706,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":821702,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tanner, Ashley M.","contributorId":264589,"corporation":false,"usgs":false,"family":"Tanner","given":"Ashley","email":"","middleInitial":"M.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":821707,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Carleton, Scott A.","contributorId":264590,"corporation":false,"usgs":false,"family":"Carleton","given":"Scott A.","affiliations":[{"id":37461,"text":"fws","active":true,"usgs":false}],"preferred":false,"id":821708,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70248965,"text":"70248965 - 2020 - Scenarios for valuing sample information in natural resources","interactions":[],"lastModifiedDate":"2023-09-27T11:44:33.515534","indexId":"70248965","displayToPublicDate":"2020-09-15T06:43:29","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Scenarios for valuing sample information in natural resources","docAbstract":"We present a high-resolution daily temperature data set, CHIRTS-daily, which is derived by merging the monthly Climate Hazards center InfraRed Temperature with Stations climate record with daily temperatures from version 5 of the European Centre for Medium-Range Weather Forecasts Re-Analysis. We demonstrate that remotely sensed temperature estimates may more closely represent true conditions than those that rely on interpolation, especially in regions with sparse in situ data. By leveraging remotely sensed infrared temperature observations, CHIRTS-daily provides estimates of 2-meter air temperature for 1983–2016 with a footprint covering 60°S-70°N. We describe this data set and perform a series of validations using station observations from two prominent climate data sources. The validations indicate high levels of accuracy, with CHIRTS-daily correlations with observations ranging from 0.7 to 0.9, and very good representation of heat wave trends.
","language":"English","publisher":"Nature Publications","doi":"10.1038/s41597-020-00643-7","usgsCitation":"Verdin, A., Funk, C., Peterson, P., Landsfeld, M., Tuholske, C., and Grace, K., 2020, Development and validation of the CHIRTS-daily quasi-global high-resolution daily temperature data set: Scientific Data, v. 7, 303, 14 p., https://doi.org/10.1038/s41597-020-00643-7.","productDescription":"303, 14 p.","ipdsId":"IP-118171","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":455325,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41597-020-00643-7","text":"Publisher Index Page"},{"id":421817,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","noUsgsAuthors":false,"publicationDate":"2020-09-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Verdin, Andrew","contributorId":145812,"corporation":false,"usgs":false,"family":"Verdin","given":"Andrew","affiliations":[{"id":6713,"text":"University of Colorado, Boulder CO","active":true,"usgs":false}],"preferred":false,"id":885585,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Funk, Chris 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":167070,"corporation":false,"usgs":true,"family":"Funk","given":"Chris","email":"cfunk@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":885586,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, Pete","contributorId":192379,"corporation":false,"usgs":false,"family":"Peterson","given":"Pete","affiliations":[],"preferred":false,"id":885587,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Landsfeld, Martin","contributorId":192380,"corporation":false,"usgs":false,"family":"Landsfeld","given":"Martin","affiliations":[],"preferred":false,"id":885588,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tuholske, Cascade","contributorId":330685,"corporation":false,"usgs":false,"family":"Tuholske","given":"Cascade","email":"","affiliations":[{"id":37180,"text":"UC Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":885589,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grace, Kathryn","contributorId":145815,"corporation":false,"usgs":false,"family":"Grace","given":"Kathryn","email":"","affiliations":[{"id":7215,"text":"University of Utah Dept. of Geography","active":true,"usgs":false}],"preferred":false,"id":885590,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}