The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, assessed statistical relations between hydraulic properties of streams at approximate bankfull conditions for different ecological regions (ecoregions) in Texas. Data from more than 103,000 records of measured discharge and ancillary hydraulic properties were assembled from summaries of discharge measurements for 424 U.S. Geological Survey streamgages in Texas. The data were subsequently subsetted at each streamgage for a streamgage-specific discharge interval centered on the estimated median annual peak discharge (0.5 annual exceedance probability) obtained from previously published regional regression equations in Texas in conjunction with the streamgage-specific sample median annual peak discharge for the period of record for each streamgage. Discharge measurements at gaged locations representing bankfull conditions (approximated from a discharge interval centered on the estimated median annual peak discharge at a given site) and associated watershed properties were subjected to rigorous statistical analysis. For most discharge measurements (where discharge is symbolically represented as Q), the following hydraulic properties are available: cross-section area (A), water-surface top width (B), and reported mean velocity (V). Statewide summary statistics were computed by using these four hydraulic properties (Q, A, B, and V) and the following five watershed properties: (1) watershed area (contributing drainage area), (2) a multiple of main-channel slope (1,000 times main-channel slope), (3) mean annual precipitation, (4) drainage density, and (5) sinuosity ratio. From the initial set of 424 streamgages, summary statistics were computed for 372 selected streamgages in Texas and constitute the subsetted measurements dataset described in this report. Eight of the 10 ecoregions in Texas are represented in the statewide summary statistics.
The resulting statistical relations, expressed as regression equations, can be used to estimate cross-section area, water-surface top width, discharge, and mean velocity of streams in different Texas ecoregions, at approximate bankfull conditions. In the regression equations, watershed properties were the independent variables for applicable watersheds, and predictions from the equations might be useful for estimating the four hydraulic properties at ungaged or unmonitored locations from selected characteristics measured at both the ungaged locations and gaged locations.
Four regression equations to estimate the four hydraulic properties were identified as the preferred equations from this study. The four preferred equations use watershed area, mean annual precipitation, and aggregated ecoregion (treated as a categorical variable) to estimate the hydraulic properties, and justification is provided for this preference. For the four equations, the proportions of variance explained by the regression equations as measured by Nash-Sutcliffe efficiency are about 71 percent for cross-section area, 36 percent for top width, 76 percent for discharge, and 25 percent for mean velocity. Residual standard error (RSEs) of the regression equations are 0.252 log10 square feet for cross-section area, 0.319 log10 feet for top width, 0.247 log10 cubic feet per second for discharge, and 0.190 log10 feet per second for mean velocity, and the corresponding standard deviations of response are 0.465 log10 square feet, 0.397 log10 feet, 0.507 log10 cubic feet per second, and 0.220 log10 feet per second, respectively. The residual standard errors are less than the standard deviations as anticipated but show that the uncertainty reduction (percent change) for cross-section area is about −46 percent, about −20 percent for top width, about −51 percent for discharge, and about −14 percent for mean velocity.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205086","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Asquith, W.H., Gordon, J.D., and Wallace, D.S., 2020, Regional regression equations for estimation of four hydraulic properties of streams at approximate bankfull conditions for different ecoregions in Texas: U.S. Geological Survey Scientific Investigations Report 2020–5086, 45 p., https://doi.org/10.3133/sir20205086.","productDescription":"Report: vi, 45 p.; Companion File","numberOfPages":"54","onlineOnly":"Y","ipdsId":"IP-081456","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":436735,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96WY938","text":"USGS data release","linkHelpText":"Source code in R for creation of regional regression equations for estimation of four 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\"}}]}","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
Ice wedge degradation is a widespread occurrence across the circumpolar Arctic causing extreme spatial heterogeneity in water distribution, vegetation, and energy balance across landscapes. These heterogeneities influence carbon dioxide (CO2) and methane (CH4) fluxes, yet there is little understanding of how they effect change in landscape‐level carbon (C) gas flux over time. We measured CO2 and CH4 fluxes in an area undergoing ice wedge degradation near Prudhoe Bay, Alaska, and combined with repeat imagery analysis to estimate seasonal landscape‐level C flux response to geomorphic change. Net CO2 and CH4 emissions changed by −25% and +42%, respectively, resulting in a 14% increase in seasonal CO2‐C equivalent emissions over 69 years as ice wedge degradation formed water‐filled troughs. The dynamic ice wedge degradation/stabilization process can cause significant changes in CO2 and CH4 fluxes over time, and the integration of this process is important to forecasting landscape‐level C fluxes in permafrost regions abundant in ice wedges.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020GL089894","usgsCitation":"Wickland, K.P., Jorgenson, M., Koch, J.C., Kanevskiy, M.Z., and Striegl, R.G., 2020, Carbon dioxide and methane flux in a dynamic Arctic tundra landscape: Decadal‐scale impacts of ice wedge degradation and stabilization: Geophysical Research Letters, v. 47, no. 22, e2020GL089894, 10 p., https://doi.org/10.1029/2020GL089894.","productDescription":"e2020GL089894, 10 p.","ipdsId":"IP-120601","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":380783,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Prudhoe Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -148.73428344726562,\n 70.00180966478055\n ],\n [\n -147.8704833984375,\n 70.00180966478055\n ],\n [\n -147.8704833984375,\n 70.35709062721314\n ],\n [\n -148.73428344726562,\n 70.35709062721314\n ],\n [\n -148.73428344726562,\n 70.00180966478055\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"22","noUsgsAuthors":false,"publicationDate":"2020-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Wickland, Kimberly P. 0000-0002-6400-0590 kpwick@usgs.gov","orcid":"https://orcid.org/0000-0002-6400-0590","contributorId":1835,"corporation":false,"usgs":true,"family":"Wickland","given":"Kimberly","email":"kpwick@usgs.gov","middleInitial":"P.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":805612,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jorgenson, M.Torre 0000-0002-9834-8851","orcid":"https://orcid.org/0000-0002-9834-8851","contributorId":245200,"corporation":false,"usgs":false,"family":"Jorgenson","given":"M.Torre","affiliations":[{"id":13506,"text":"Alaska Ecoscience","active":true,"usgs":false}],"preferred":false,"id":805613,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":805614,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kanevskiy, Mikhail Z.","contributorId":199153,"corporation":false,"usgs":false,"family":"Kanevskiy","given":"Mikhail","email":"","middleInitial":"Z.","affiliations":[],"preferred":false,"id":805615,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":805616,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227004,"text":"70227004 - 2020 - Vegetation management on private forestland can increase avian species richness and abundance","interactions":[],"lastModifiedDate":"2021-12-27T14:37:29.778561","indexId":"70227004","displayToPublicDate":"2020-11-02T08:33:34","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9101,"text":"Ornithological Applications","printIssn":"0010-5422","active":true,"publicationSubtype":{"id":10}},"title":"Vegetation management on private forestland can increase avian species richness and abundance","docAbstract":"Conservation efforts on private lands are important for biodiversity conservation. On private lands in South Carolina, in the southeastern United States, forestry management practices (prescribed burning, thinning, herbicide application) are used to improve upland pine habitat for wildlife and timber harvest and are incentivized through U.S. Department of Agriculture Farm Bill cost-share programs. Because many forest-dependent avian species have habitat requirements created primarily through forest management, data are needed on the effectiveness of these management activities. We studied privately owned loblolly pine (Pinus taeda) stands in the South Carolina Piedmont region. Our objective was to understand how management practices influence avian species richness and abundance at local (forest stand) and landscape levels in relatively small stands (average ~28 ha). We surveyed 49 forest stands during 2 bird breeding seasons with traditional point counts and vegetation surveys. We evaluated the effects of management on pine stand characteristics, avian species richness, and abundance of state-designated bird species of concern. Repeated burning and thinning shifted stand conditions to open pine woodlands with reduced basal area and herbaceous understories. Stands with lower basal area supported greater avian species richness. Some species increased in abundance in response to active management (e.g., Brown-headed Nuthatch [Sitta pusilla] and Indigo Bunting [Passerina cyanea]), but relationships varied. Some species responded positively to increases in forest quantity at a landscape scale (1–5 km; e.g., Northern Bobwhite [Colinus virginianus]). We found species-rich avian communities and species of conservation concern on working timber lands, indicating that incentivized forest management on private lands can provide valuable habitat for wildlife.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/condor/duaa048","usgsCitation":"Wood, J., Tegeler, A., and Ross, B., 2020, Vegetation management on private forestland can increase avian species richness and abundance: Ornithological Applications, v. 122, no. 4, duaa048, 16 p., https://doi.org/10.1093/condor/duaa048.","productDescription":"duaa048, 16 p.","ipdsId":"IP-106496","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":454896,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/condor/duaa048","text":"Publisher Index Page"},{"id":393413,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South 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Carolina\",\"nation\":\"USA \"}}]}","volume":"122","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-08-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, J.M.","contributorId":270361,"corporation":false,"usgs":false,"family":"Wood","given":"J.M.","email":"","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":829149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tegeler, A.K.","contributorId":270363,"corporation":false,"usgs":false,"family":"Tegeler","given":"A.K.","email":"","affiliations":[{"id":56153,"text":"2South Carolina Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":829150,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ross, Beth 0000-0001-5634-4951 bross@usgs.gov","orcid":"https://orcid.org/0000-0001-5634-4951","contributorId":199242,"corporation":false,"usgs":true,"family":"Ross","given":"Beth","email":"bross@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":829151,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70215885,"text":"ofr20201115 - 2020 - Southern (California) sea otter population status and trends at San Nicolas Island, 2017–2020","interactions":[],"lastModifiedDate":"2020-11-03T12:47:24.250221","indexId":"ofr20201115","displayToPublicDate":"2020-11-02T08:26:49","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1115","displayTitle":"Southern (California) Sea Otter Population Status and Trends at San Nicolas Island, 2017–2020","title":"Southern (California) sea otter population status and trends at San Nicolas Island, 2017–2020","docAbstract":"The southern sea otter (Enhydra lutris nereis) population at San Nicolas Island, California, has been monitored annually since the translocation of 140 sea otters to the island was completed in 1990. Monitoring efforts have varied in frequency and type across years. In 2017, the U.S. Navy and the U.S. Fish and Wildlife Service initiated a sea otter monitoring and research plan to determine the effects of military readiness activities on the growth or decline of the southern sea otter population at San Nicolas Island. The monitoring program, at its basic level, includes quarterly seasonal surveys of population abundance, distribution, and foraging activity. From 2017 to 2020, we measured a 22-percent per annum increase in population abundance (95-percent confidence interval =11–34 percent) with 114 total individuals as of February 2020. Coinciding with recent population growth, the sea otter distribution, which previously tended to concentrate on the west side, appears to have shifted toward an expansion of use in the north and especially greater seasonal use in the north and south during winter and spring. Foraging data were collected on a total of 2,675 foraging dives in 167 foraging bouts, and the majority of identified prey on successful dives (n=1,335) were sea urchins (940) followed by snails (240) and crabs (78). Small numbers of lobsters (26), octopus (16), and abalone (5) also were identified. Estimates of energy intake rates averaged 17.3 kilocalories per minute (95-percent confidence interval =15.6–19.0 kilocalories per minute) and suggest possible variations across years and seasons, but confidence intervals based on specific years of data were relatively wide. In addition to abundance, trends, distribution, and forage energy intake across seasons and years, these replicated surveys provide information on the precision of data achieved by quarterly survey effort. We used precision estimates and conducted simulation analyses to assess the power of detecting 10-percent or greater decreases in population growth rates and how this power is likely to change with years of observation, survey effort, and the size of decrease. These results can be useful to the planning of future monitoring and research of sea otters at San Nicolas Island.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201115","collaboration":"Wildlife ProgramDirector, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Anticoagulant rodenticides (ARs) are commonly used to control rodent pests. However, worldwide, their use is associated with secondary and tertiary poisoning of nontarget species, especially predatory and scavenging birds. No medical device can rapidly test for AR exposure of avian wildlife. Prothrombin time (PT) is a useful biomarker for AR exposure, and multiple commercially available point-of-care (POC) devices measure PT of humans, and domestic and companion mammals. We evaluated the potential of one commercially available POC device, the Coag-Sense® PT/INR Monitoring System, to rapidly detect AR exposure of living birds of prey. The Coag-Sense device delivered repeatable PT measurements on avian blood samples collected from four species of raptors trapped during migration (Intraclass Correlation Coefficient > 0.9; overall intra-sample variation CV: 5.7%). However, PT measurements reported by the Coag-Sense system from 81 ferruginous hawk (Buteo regalis) nestlings were not correlated to those measured by a one-stage laboratory avian PT assay (r = − 0.017, p = 0.88). Although precise, the lack of agreement in PT estimates from the Coag-Sense device and the laboratory assay indicates that this device is not suitable for detecting potential AR exposure of birds of prey. The lack of suitability may be related to the use of a mammalian reagent in the clotting reaction, suggesting that the device may perform better in testing mammalian wildlife
The coupled biophysical interactions between submerged aquatic vegetation (SAV), hydrodynamics (currents and waves), sediment dynamics, and nutrient cycling have long been of interest in estuarine environments. Recent observational studies have addressed feedbacks between SAV meadows and their role in modifying current velocity, sedimentation, and nutrient cycling. To represent these dynamic processes in a numerical model, the presence of SAV and its effect on hydrodynamics (currents and waves) and sediment dynamics was incorporated into the open-source Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) model. In this study, we extend the COAWST modeling framework to account for dynamic changes of SAV and associated epiphyte biomass. Modeled SAV biomass is represented as a function of temperature, light, and nutrient availability. The modeled SAV community exchanges nutrients, detritus, dissolved inorganic carbon, and dissolved oxygen with the water-column biogeochemistry model. The dynamic simulation of SAV biomass allows the plants to both respond to and cause changes in the water column and sediment bed properties, hydrodynamics, and sediment transport (i.e., a two-way feedback). We demonstrate the behavior of these modeled processes through application to an idealized domain and then apply the model to a eutrophic harbor where SAV dieback is a result of anthropogenic nitrate loading and eutrophication. These cases demonstrate an advance in the deterministic modeling of coupled biophysical processes and will further our understanding of future ecosystem change.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/gmd-13-5211-2020","usgsCitation":"Kalra, T., Ganju, N., and Testa, J.M., 2020, Development of a submerged aquatic vegetation growth model in the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST v3.4) model: Geoscientific Model Development, v. 13, no. 11, p. 5211-5228, https://doi.org/10.5194/gmd-13-5211-2020.","productDescription":"18 p.","startPage":"5211","endPage":"5228","ipdsId":"IP-102944","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454901,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-13-5211-2020","text":"Publisher Index Page"},{"id":380185,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-11-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Kalra, Tarandeep S. 0000-0001-5468-248X tkalra@usgs.gov","orcid":"https://orcid.org/0000-0001-5468-248X","contributorId":178820,"corporation":false,"usgs":true,"family":"Kalra","given":"Tarandeep S.","email":"tkalra@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":804107,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":804108,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Testa, Jeremy M.","contributorId":244524,"corporation":false,"usgs":false,"family":"Testa","given":"Jeremy","email":"","middleInitial":"M.","affiliations":[{"id":37215,"text":"University of Maryland Center for Environmental Science","active":true,"usgs":false}],"preferred":false,"id":804109,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70216069,"text":"70216069 - 2020 - Seasonality of biological and physical systems as indicators of climatic variation and change","interactions":[],"lastModifiedDate":"2024-05-16T15:21:12.860978","indexId":"70216069","displayToPublicDate":"2020-11-02T07:25:14","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1252,"text":"Climatic Change","active":true,"publicationSubtype":{"id":10}},"title":"Seasonality of biological and physical systems as indicators of climatic variation and change","docAbstract":"Evidence-based responses to climate change by society require operational and sustained information including biophysical indicator systems that provide up-to-date measures of trends and patterns against historical baselines. Two key components linking anthropogenic climate change to impacts on socio-ecological systems are the periodic inter- and intra-annual variations in physical climate systems (seasonality) and in plant and animal life cycles (phenology). We describe a set of national indicators that reflect sub-seasonal to seasonal drivers and responses of terrestrial physical and biological systems to climate change and variability at the national scale. Proposed indicators and metrics include seasonality of surface climate conditions (e.g., frost and freeze dates and durations), seasonality of freeze/thaw in freshwater systems (e.g., timing of stream runoff and durations of lake/river ice), seasonality in ecosystem disturbances (e.g., wildfire season timing and duration), seasonality in vegetated land surfaces (e.g., green-up and brown-down of landscapes), and seasonality of organismal life-history stages (e.g., timings of bird migration). Recommended indicators have strong linkages to variable and changing climates, include abiotic and biotic responses and feedback mechanisms, and are sufficiently simple to facilitate communication to broad audiences and stakeholders interested in understanding and adapting to climate change.
The COVID-19 pandemic has led to environmental recovery in some ecosystems from a global “anthropause,” yet such evidence for natural resources with extraction or production value (e.g., fisheries) is limited. This brief report provides a data-driven global snapshot of expert-perceived impacts of COVID-19 on inland fisheries. We distributed an online survey assessing perceptions of inland fishery pressures in June and July 2020 to basin-level inland fishery experts (i.e., identified by the Food and Agriculture Organization of the United Nations across the global North and South); 437 respondents from 79 countries addressed 93 unique hydrological basins, accounting for 82.1% of global inland fish catch. Based on the responses analyzed against extrinsic fish catch and human development index data, pandemic impacts on inland fisheries 1) add gradation to the largely positive environmental narrative of the global pandemic and 2) identify that basins of higher provisioning value are perceived to experience greater fishery pressures but may have limited compensatory capacity to mitigate COVID-19 impacts along with negative pressures already present.
","language":"English","publisher":"PNAS","doi":"10.1073/pnas.2014016117","usgsCitation":"Stokes, G.L., Lynch, A., Lowe, B.S., Funge-Smith, S., Valbo-Jorgensen, J., and Smidt, S.J., 2020, COVID-19 pandemic impacts on global inland fisheries: PNAS, v. 117, no. 47, p. 29419-29421, https://doi.org/10.1073/pnas.2014016117.","productDescription":"3 p.","startPage":"29419","endPage":"29421","ipdsId":"IP-120698","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":454904,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2014016117","text":"Publisher Index Page"},{"id":381214,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"117","issue":"47","noUsgsAuthors":false,"publicationDate":"2020-11-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Stokes, Gretchen L. 0000-0003-4202-6527","orcid":"https://orcid.org/0000-0003-4202-6527","contributorId":245640,"corporation":false,"usgs":false,"family":"Stokes","given":"Gretchen","email":"","middleInitial":"L.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":806705,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lynch, Abigail J. 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":220490,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","middleInitial":"J.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":806691,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lowe, Benjamin S. 0000-0002-1879-254X","orcid":"https://orcid.org/0000-0002-1879-254X","contributorId":245641,"corporation":false,"usgs":false,"family":"Lowe","given":"Benjamin","email":"","middleInitial":"S.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":806706,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Funge-Smith, Simon 0000-0001-9974-5333","orcid":"https://orcid.org/0000-0001-9974-5333","contributorId":245642,"corporation":false,"usgs":false,"family":"Funge-Smith","given":"Simon","email":"","affiliations":[{"id":32888,"text":"Food and Agriculture organization of the United Nations","active":true,"usgs":false}],"preferred":false,"id":806707,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Valbo-Jorgensen, John 0000-0002-1992-5682","orcid":"https://orcid.org/0000-0002-1992-5682","contributorId":220485,"corporation":false,"usgs":false,"family":"Valbo-Jorgensen","given":"John","affiliations":[{"id":32888,"text":"Food and Agriculture organization of the United Nations","active":true,"usgs":false}],"preferred":false,"id":806708,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smidt, Samuel J. 0000-0001-7728-2083","orcid":"https://orcid.org/0000-0001-7728-2083","contributorId":192816,"corporation":false,"usgs":false,"family":"Smidt","given":"Samuel","email":"","middleInitial":"J.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":806709,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70237973,"text":"70237973 - 2020 - High-frequency data reveal deicing salts drive elevated specific conductance and chloride along with pervasive and frequent exceedances of the U.S. Environmental Protection Agency aquatic life criteria for chloride in urban streams","interactions":[],"lastModifiedDate":"2022-11-02T11:44:45.440534","indexId":"70237973","displayToPublicDate":"2020-11-02T06:43:13","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"High-frequency data reveal deicing salts drive elevated specific conductance and chloride along with pervasive and frequent exceedances of the U.S. Environmental Protection Agency aquatic life criteria for chloride in urban streams","docAbstract":"Increasing specific conductance (SC) and chloride concentrations [Cl] negatively affect many stream ecosystems. We characterized spatial variability in SC, [Cl], and exceedances of Environmental Protection Agency [Cl] criteria using nearly 30 million high-frequency observations (2–15 min intervals) for SC and modeled [Cl] from 93 sites across three regions in the eastern United States: Southeast, Mid-Atlantic, and New England. SC and [Cl] increase substantially from south to north and within regions with impervious surface cover (ISC). In the Southeast, [Cl] weakly correlates with ISC, no [Cl] exceedances occur, and [Cl] concentrations are constant with time. In the Mid-Atlantic and New England, [Cl] and [Cl] exceedances strongly correlate with ISC. [Cl] criteria are frequently exceeded at sites with greater than 9–10% ISC and median [Cl] higher than 30–80 mg/L. Tens to hundreds of [Cl] exceedances observed annually at most of these sites help explain previous research where stream ecosystems showed changes at (primarily nonwinter) [Cl] as low as 30–40 mg/L. Mid-Atlantic chronic [Cl] exceedances occur primarily in December–March. In New England, exceedances are common in nonwinter months. [Cl] is increasing at nearly all Mid-Atlantic and New England sites with the largest increases at sites with higher [Cl].
Mercury (Hg) is a global pollutant that affects aquatic biota in otherwise pristine settings such as the Adirondack region of New York State. Bioaccumulation of Hg is especially problematic in sensitive landscapes, where inorganic mercury from atmospheric deposition is readily converted, via natural processes, to methylmercury (MeHg), the toxic form that is taken up and biomagnified in aquatic food webs. There is great interest in monitoring MeHg in aquatic biota across these sensitive regions to evaluate responses to changes in Hg emissions. Aquatic insects, such as dragonfly larvae, have great potential as MeHg “biosentinels,” but currently are not widely used for this purpose. An important practical consideration in the use of aquatic insects for MeHg biomonitoring is whether total mercury (THg) is a suitable surrogate for MeHg, which is much more technically challenging and expensive to analyze than is THg. The objective of this project was to assess the suitability of THg as a surrogate for MeHg in stream-dwelling insects. Specifically, existing data on immature aquatic insects from nine Adirondack streams were used to characterize MeHg to THg ratios (i.e., MeHg%), and variation in these ratios (e.g., among sites, seasons, taxa) in predator and primary consumer insects, examine how well THg in different groups tracks measured stream water MeHg (i.e., filtered MeHg; FMeHg), and explore the influence of trophic position (indicated by nitrogen stable isotopes; δ15N) on the observed MeHg% patterns.
Three broad insect feeding groups were included in this analysis: predators, shredders, and scrapers. Predators had the highest MeHg% (median 94%), and MeHg% did not differ significantly among any of the taxa considered: stoneflies, damselflies, and three families of dragonflies (darners, common skimmers, and clubtails). Darners and common skimmers, the most numerous and abundant predators, were combined for further analyses. Site medians for these “selected dragonflies” were all at least 90% (summer-fall collections) and MeHg% did not differ significantly among sites. The correlation between FMeHg and THg in selected dragonflies was nearly as strong as that of FMeHg and dragonfly MeHg. In contrast, median MeHg% in shredders (northern caddisflies) and scrapers (flathead mayflies), which are both primary consumers, was lower overall (medians 52% and 35%, respectively), more variable, and less-well representative of FMeHg than predators. Stable isotope results indicate that variation in feeding position is an important influence on some of the MeHg% patterns observed in this study. This study’s findings suggest that THg is likely to be a suitable surrogate for MeHg in predatory aquatic insects from Adirondack streams, but do not support the use of THg in primary consumers for regional MeHg monitoring.
","language":"English","publisher":"New York State Energy Research and Development Authority","usgsCitation":"Riva-Murray, K., 2020, Ratios of methylmercury to total mercury in predator and primary consumer insects from Adirondack streams in New York State: Summary Report 20-32, vi, 15 p.","productDescription":"vi, 15 p.","ipdsId":"IP-103615","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":382274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":382272,"type":{"id":15,"text":"Index Page"},"url":"https://www.nyserda.ny.gov/About/Publications/Research-and-Development-Technical-Reports/Environmental-Research-and-Development-Technical-Reports#eco"}],"country":"United States","state":"New York","otherGeospatial":"Adirondack region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.805908203125,\n 44.02442151965934\n ],\n [\n -73.85009765625,\n 44.02442151965934\n ],\n [\n -73.85009765625,\n 44.5435052132082\n ],\n [\n -74.805908203125,\n 44.5435052132082\n ],\n [\n -74.805908203125,\n 44.02442151965934\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Riva-Murray, Karen 0000-0001-6683-2238 krmurray@usgs.gov","orcid":"https://orcid.org/0000-0001-6683-2238","contributorId":2984,"corporation":false,"usgs":true,"family":"Riva-Murray","given":"Karen","email":"krmurray@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808421,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70216557,"text":"70216557 - 2020 - Mixotrophic iron-oxidizing Thiomonas isolates from an acid mine drainage-affected creek","interactions":[],"lastModifiedDate":"2020-11-25T16:12:04.955826","indexId":"70216557","displayToPublicDate":"2020-11-01T09:41:22","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":850,"text":"Applied and Environmental Microbiology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Mixotrophic iron-oxidizing Thiomonas isolates from an acid mine drainage-affected creek","title":"Mixotrophic iron-oxidizing Thiomonas isolates from an acid mine drainage-affected creek","docAbstract":"Natural attenuation of heavy metals occurs via coupled microbial iron cycling and metal precipitation in creeks impacted by acid mine drainage (AMD). Here, we describe the isolation, characterization, and genomic sequencing of two iron-oxidizing bacteria (FeOB) species: Thiomonas ferrovorans FB-6 and Thiomonas metallidurans FB-Cd, isolated from slightly acidic (pH 6.3), Fe-rich, AMD-impacted creek sediments. These strains precipitated amorphous iron oxides, lepidocrocite, goethite, and magnetite or maghemite and grew at a pH optimum of 5.5. While Thiomonas spp. are known as mixotrophic sulfur oxidizers and As oxidizers, the FB strains oxidized Fe, which suggests they can efficiently remove Fe and other metals via coprecipitation. Previous evidence for Thiomonas sp. Fe oxidation is largely ambiguous, possibly because of difficulty demonstrating Fe oxidation in heterotrophic/mixotrophic organisms. Therefore, we also conducted a genomic analysis to identify genetic mechanisms of Fe oxidation, other metal transformations, and additional adaptations, comparing the two FB strain genomes with 12 other Thiomonas genomes. The FB strains fall within a relatively novel group of Thiomonas strains that includes another strain (b6) with solid evidence of Fe oxidation. Most Thiomonas isolates, including the FB strains, have the putative iron oxidation gene cyc2, but only the two FB strains possess the putative Fe oxidase genes mtoAB. The two FB strain genomes contain the highest numbers of strain-specific gene clusters, greatly increasing the known Thiomonas genetic potential. Our results revealed that the FB strains are two distinct novel species of Thiomonas with the genetic potential for bioremediation of AMD via iron oxidation.
","language":"English","publisher":"American Society for Microbiology","doi":"10.1128/AEM.01424-20","usgsCitation":"Akob, D., Hallenbeck, M., Beulig, F., Fabisch, M., Kusel, K., Keffer, J.L., Woyke, T., Shapiro, N., Lapidus, A., Klenk, H., and Chan, C., 2020, Mixotrophic iron-oxidizing Thiomonas isolates from an acid mine drainage-affected creek: Applied and Environmental Microbiology, v. 86, no. 24, e01424-20, 18 p., https://doi.org/10.1128/AEM.01424-20.","productDescription":"e01424-20, 18 p.","ipdsId":"IP-118414","costCenters":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":454911,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7688216","text":"External Repository"},{"id":380785,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Germany","state":"Thuringia","otherGeospatial":"Ronneburg uranium mining district","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 11.854248046875,\n 50.65294336725709\n ],\n [\n 12.32666015625,\n 50.65294336725709\n ],\n [\n 12.32666015625,\n 50.972264889367494\n ],\n [\n 11.854248046875,\n 50.972264889367494\n ],\n [\n 11.854248046875,\n 50.65294336725709\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"86","issue":"24","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Liu, Shuang-Jiang","contributorId":245233,"corporation":false,"usgs":false,"family":"Liu","given":"Shuang-Jiang","email":"","affiliations":[],"preferred":false,"id":805654,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Akob, Denise M. 0000-0003-1534-3025","orcid":"https://orcid.org/0000-0003-1534-3025","contributorId":204701,"corporation":false,"usgs":true,"family":"Akob","given":"Denise M.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":805596,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hallenbeck, Michelle","contributorId":245191,"corporation":false,"usgs":false,"family":"Hallenbeck","given":"Michelle","email":"","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":805597,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beulig, Felix","contributorId":245192,"corporation":false,"usgs":false,"family":"Beulig","given":"Felix","affiliations":[{"id":40121,"text":"Friedrich Schiller University Jena","active":true,"usgs":false}],"preferred":false,"id":805598,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fabisch, Maria","contributorId":191122,"corporation":false,"usgs":false,"family":"Fabisch","given":"Maria","email":"","affiliations":[],"preferred":false,"id":805599,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kusel, Kirsten","contributorId":171802,"corporation":false,"usgs":false,"family":"Kusel","given":"Kirsten","email":"","affiliations":[{"id":26947,"text":"Friedrich Schiller University, Germany","active":true,"usgs":false}],"preferred":false,"id":805600,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Keffer, Jessica L","contributorId":245193,"corporation":false,"usgs":false,"family":"Keffer","given":"Jessica","email":"","middleInitial":"L","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":805601,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Woyke, Tanja","contributorId":220021,"corporation":false,"usgs":false,"family":"Woyke","given":"Tanja","email":"","affiliations":[{"id":40122,"text":"DOE JGI","active":true,"usgs":false}],"preferred":false,"id":805602,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Shapiro, Nicole","contributorId":220023,"corporation":false,"usgs":false,"family":"Shapiro","given":"Nicole","email":"","affiliations":[{"id":40122,"text":"DOE JGI","active":true,"usgs":false}],"preferred":false,"id":805603,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lapidus, Alla","contributorId":220024,"corporation":false,"usgs":false,"family":"Lapidus","given":"Alla","email":"","affiliations":[{"id":40122,"text":"DOE JGI","active":true,"usgs":false}],"preferred":false,"id":805604,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Klenk, Hans-Peter","contributorId":220025,"corporation":false,"usgs":false,"family":"Klenk","given":"Hans-Peter","email":"","affiliations":[{"id":33636,"text":"Newcastle University","active":true,"usgs":false}],"preferred":false,"id":805605,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Chan, Clara","contributorId":245195,"corporation":false,"usgs":false,"family":"Chan","given":"Clara","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":805606,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70227617,"text":"70227617 - 2020 - Winter versus summer habitat selection in a threatened ground squirrel","interactions":[],"lastModifiedDate":"2022-01-21T15:53:54.569335","indexId":"70227617","displayToPublicDate":"2020-11-01T09:38:01","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Winter versus summer habitat selection in a threatened ground squirrel","docAbstract":"Hibernation is a strategy many species employ to survive periods of thermal stress or resource shortage (e.g., harsh thermal conditions, food limitations) and habitat requirements of hibernating species may differ between summer (the active season) and winter (during hibernation). Accounting for seasonal differences in habitat affinities will help ensure that management actions are more beneficial and land-use policies are more appropriate. The northern Idaho ground squirrel (Urocitellus brunneus) is a federally listed threatened species that is in decline and hibernates for approximately 8 months per year. We collared northern Idaho ground squirrels in Adams County, Idaho from 2013–2017. The majority of northern Idaho ground squirrels we collared selected hibernacula outside of the areas they used during the active season. Furthermore, habitat features of hibernacula locations differed from habitat features of active-season areas. Hibernacula locations had greater canopy closure compared to active-season locations (36.9% and 7.0% canopy closure, respectively) and hibernaculum habitat features (particularly distance to nearest log) influenced overwinter survival. Our results suggest that recovery efforts for northern Idaho ground squirrels should include protection and management for the full range of habitat conditions used throughout summer and winter. More broadly, we emphasize the need to identify and protect habitat during all seasons because habitat requirements can differ substantially during different portions of an animal's annual cycle and effective conservation will require management of year-round habitat needs.
This chapter comprises the following sections: names, taxonomy, subspecies and distribution, descriptive notes, habitat, movements and home range, activity patterns, feeding ecology, reproduction and growth, behavior, parasites and diseases, status in the wild, and status in captivity.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Bears of the world: Ecology, conservation and management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Cambridge University Press","doi":"10.1017/9781108692571.014","usgsCitation":"Haroldson, M.A., Clapham, M., Costello, C., Gunther, K.A., Kendall, K., Miller, S., Pigeon, K., Proctor, M.F., Rode, K.D., Servheen, C., Stenhouse, G., and van Manen, F.T., 2020, Brown Bear (Ursus arctos; North America), chap. 13 of Bears of the world: Ecology, conservation and management, p. 162-195, https://doi.org/10.1017/9781108692571.014.","productDescription":"34 p.","startPage":"162","endPage":"195","ipdsId":"IP-108729","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":382058,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": 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mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":807863,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clapham, Melanie","contributorId":247529,"corporation":false,"usgs":false,"family":"Clapham","given":"Melanie","email":"","affiliations":[{"id":49570,"text":"University of Victoria, Victoria, British Columbia","active":true,"usgs":false}],"preferred":false,"id":807864,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Costello, Cecily M.","contributorId":145510,"corporation":false,"usgs":false,"family":"Costello","given":"Cecily M.","affiliations":[{"id":5117,"text":"University of Montana, College of Forestry and Conservation, University Hall, Room 309, Missoula, MT 59812, USA","active":true,"usgs":false}],"preferred":false,"id":807865,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gunther, Kerry A.","contributorId":190246,"corporation":false,"usgs":false,"family":"Gunther","given":"Kerry","email":"","middleInitial":"A.","affiliations":[{"id":5130,"text":"Bear Management Office, Yellowstone National Park, WY 82190, USA","active":true,"usgs":false}],"preferred":false,"id":807866,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kendall, Kate 0000-0002-4831-2287","orcid":"https://orcid.org/0000-0002-4831-2287","contributorId":247530,"corporation":false,"usgs":false,"family":"Kendall","given":"Kate","affiliations":[{"id":49571,"text":"Ursine Ecological","active":true,"usgs":false}],"preferred":false,"id":807867,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Sterling","contributorId":247531,"corporation":false,"usgs":false,"family":"Miller","given":"Sterling","affiliations":[{"id":49572,"text":"Dunrovin Ranch and Research, LLC.","active":true,"usgs":false}],"preferred":false,"id":807868,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pigeon, Karine","contributorId":247532,"corporation":false,"usgs":false,"family":"Pigeon","given":"Karine","email":"","affiliations":[{"id":49573,"text":"fRi Research, Alberta","active":true,"usgs":false}],"preferred":false,"id":807869,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Proctor, Michael F.","contributorId":150939,"corporation":false,"usgs":false,"family":"Proctor","given":"Michael","email":"","middleInitial":"F.","affiliations":[{"id":18147,"text":"Birchdale Ecological","active":true,"usgs":false}],"preferred":false,"id":807870,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":807871,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Servheen, Christopher","contributorId":124584,"corporation":false,"usgs":false,"family":"Servheen","given":"Christopher","email":"","affiliations":[{"id":5128,"text":"U.S. Fish and Wildlife Service, University of Montana, Missoula, MT 59812","active":true,"usgs":false}],"preferred":false,"id":807872,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Stenhouse, Gordon","contributorId":167054,"corporation":false,"usgs":false,"family":"Stenhouse","given":"Gordon","email":"","affiliations":[{"id":24604,"text":"Foothills Research Institute","active":true,"usgs":false}],"preferred":false,"id":807873,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":807874,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70217183,"text":"70217183 - 2020 - Ecological and social dimensions of sloth bear conservation in Sri Lanka","interactions":[],"lastModifiedDate":"2021-01-12T12:38:09.759517","indexId":"70217183","displayToPublicDate":"2020-11-01T09:22:08","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"28","title":"Ecological and social dimensions of sloth bear conservation in Sri Lanka","docAbstract":"Balancing the needs of humans and wildlife in Sri Lanka presents enormous socioeconomic and conservation challenges. Sloth bears are legally protected, but attacks on humans generate intense fear, which increases the potential for human-caused bear mortality and local extirpation of bears. In this chapter, what is known about the ecology and human dimensions of the sloth bear in a country with a teeming human population and a history of poverty and civil conflict is explored. We also address whether changes in land use in the aftermath of the civil war may have impacted sloth bear distribution and discuss the conservation outlook for bears.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Bears of the world: Ecology, conservation and management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Cambridge University Press","doi":"10.1017/9781108692571.029","usgsCitation":"Ratnayeke, S., and van Manen, F.T., 2020, Ecological and social dimensions of sloth bear conservation in Sri Lanka, chap. 28 of Bears of the world: Ecology, conservation and management, p. 379-386, https://doi.org/10.1017/9781108692571.029.","productDescription":"8 p.","startPage":"379","endPage":"386","ipdsId":"IP-107001","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":454915,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/9781108692571.029","text":"Publisher Index Page"},{"id":382057,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Sri Lanka","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 80.57373046875,\n 9.535748998133627\n ],\n [\n 80.04638671875,\n 9.817329187067783\n ],\n [\n 80.00244140625,\n 9.253936156814463\n ],\n [\n 79.7607421875,\n 8.667918002363121\n ],\n [\n 79.6728515625,\n 6.882800241767556\n ],\n [\n 80.31005859375,\n 5.637852598770866\n ],\n [\n 81.84814453125,\n 6.599130675207247\n ],\n [\n 81.97998046875,\n 7.514980942395872\n ],\n [\n 81.01318359375,\n 9.080400104155315\n ],\n [\n 80.57373046875,\n 9.535748998133627\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ratnayeke, Shyamala","contributorId":203978,"corporation":false,"usgs":false,"family":"Ratnayeke","given":"Shyamala","email":"","affiliations":[{"id":36779,"text":"Department of Biological Sciences, Sunway University, Malaysia","active":true,"usgs":false}],"preferred":false,"id":807875,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":807876,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70222481,"text":"70222481 - 2020 - Wildfire and Earth surface processes","interactions":[],"lastModifiedDate":"2021-08-02T15:49:34.707051","indexId":"70222481","displayToPublicDate":"2020-11-01T08:31:55","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Wildfire and Earth surface processes","docAbstract":"Wildfire is a worldwide phenomenon that is expected to increase in extent and severity in the future, due to fuel accumulations, shifting land management practices, and climate change. It immediately affects the landscape by removing vegetation, depositing ash, influencing water-repellent soil formation, and physically weathering boulders and bedrock. These changes typically lead to increased erosion through sheetwash, rilling, dry ravel, and increased mass movement in the form of floods, debris flow, rockfall, and landslides. These process changes bring about landform changes as hillslopes are lowered and stream channels aggrade or incise at increased rates. Furthermore, development of alluvial fans, debris fans, and talus cones are enhanced. The window of disturbance to the landscape caused by wildfire is typically on the order of 3–4 years, with some effects persisting up to 30 years.
Executive Summary Under the Resources and Ecosystem Sustainability, Tourist Opportunities, and Revived Economies of the Gulf Coast States Act of 2012 (RESTORE Act), the Gulf Coast Ecosystem Restoration Council (RESTORE Council or Council) is required to report on the progress of funded projects and programs. Systematic monitoring of restoration at the project-specific and programmatic-levels (watershed and Gulf of Mexico) enables consistent reporting and gives the public confidence that the restoration investments selected by the RESTORE Council will be evaluated and adaptively managed accordingly. Monitoring information that has been collected at different spatial and temporal scales can be used as the foundation to illustrate progress towards comprehensive ecosystem restoration goals and objectives that promote holistic Gulf of Mexico recovery (see ‘RESTORE Council Background’ at the beginning of this report for additional Council information).
Currently, federal, state and local agencies, universities, private industry, and non-governmental organizations (NGOs) are conducting monitoring activities at various scales around the Gulf of Mexico. In addition, each RESTORE Council-funded project will, at a minimum, perform project-specific monitoring. This collection of monitoring activities was inventoried and coordinated into a network of existing programs by the Council-funded RESTORE Council Monitoring and Assessment Program (CMAP), which will suggest opportunities for efficiencies and collaborative cross-program review of performance with other Gulf ecosystem recovery efforts. CMAP was designed and funded to inventory and integrate existing monitoring efforts, improve discovery and accessibility of existing monitoring data, and ensure the collected information supports management decisions.
The fundamental approach to building the CMAP Gulf of Mexico water quality monitoring, habitat monitoring, and mapping network was to: 1. Adopt, or construct as needed, a comprehensive inventory of existing habitat and water quality observation, monitoring, and mapping programs in the Gulf of Mexico (hereafter referred to as the “Inventory”; NOAA and USGS, 2019a); 2. Evaluate the suitability/applicability of each program and its existing and prospective data for use in restoration activities; 3. Develop a process to use the Inventory to conduct gap assessments; 4. Develop a catalog of baseline assessments conducted in the Gulf of Mexico (NOAA and USGS, 2019b); and 5. Develop a searchable monitoring information portal/database to enable access to collected information and products.
","language":"English","publisher":"National Oceanic and Atmospheric Administration (NOAA)","doi":"10.25923/mrdd-h727","usgsCitation":"Bosch, J., Burkart, H.B., Chivoiu, B., Clark, R., Clement, C., Enwright, N., Giordano, S., Jeffrey, C., Johnson, E., Hart, R., Hile, S.D., Howell, J.S., Laurenzano, C., Lee, M., McCloskey, T., McTigue, T., Meyers, M.B., Miller, K.E., Mize, S., Monaco, M.E., Owen, K., Rebich, R., Rendon, S.H., Robertson, A., Sample, T., Sanks, K.M., Steyer, G., Suir, K., Swarzenski, C.M., and Thurman, H.R., 2020, Council monitoring and assessment program (CMAP): A framework for using the monitoring program inventory to conduct gap assessments for the Gulf of Mexico Region: NOAA Technical Memorandum 284, ii, 55 p., https://doi.org/10.25923/mrdd-h727.","productDescription":"ii, 55 p.","startPage":"55 p.","ipdsId":"IP-119233","costCenters":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research 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,{"id":70216170,"text":"70216170 - 2020 - Wetlands in agricultural landscapes—Significant findings and recent advances from CEAP-Wetlands","interactions":[],"lastModifiedDate":"2020-11-07T15:59:50.088468","indexId":"70216170","displayToPublicDate":"2020-10-31T09:53:53","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2456,"text":"Journal of Soil and Water Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Wetlands in agricultural landscapes—Significant findings and recent advances from CEAP-Wetlands","docAbstract":"The Wetlands Component of the USDA's Conservation Effects Assessment Project (CEAP-Wetlands) is a multi-agency effort advancing science related to quantifying and interpreting effects and effectiveness of conservation practices and programs on ecosystem services provided by wetlands in agricultural landscapes. This special section originated from a symposium held at the 73rd Soil and Water Conservation Society's International Annual Conference in Albuquerque New Mexico, July 29 to August 1, 2018. The symposium was jointly organized by the USDA Natural Resources Conservation Service and the US Geological Survey. To facilitate CEAP-Wetlands efforts, several regional assessments were conducted across the United States. These regional assessments were designed to address science gaps hindering wetland conservation and to develop tools facilitating conservation assessments. Conservation decisions affect not just agricultural wetlands, but also the services that these complex ecosystems provide to society. Papers in this special section of the Journal of Soil and Water Conservation present key findings and recent advances from several CEAP-Wetlands regional assessments and discuss the significant contributions of each assessment to an ever-increasing understanding of wetland ecosystems and their provisioning of ecosystem services. Modeling efforts using the Agricultural Policy and Environmental eXtender (APEX) and other process-based models are an integral component of CEAP-Wetlands. Results of these modeling efforts are also presented, and conservation implications are discussed.
Wind fetch is defined as the unobstructed distance that wind can travel over water in a constant direction. Fetches are limited by landforms surrounding the body of water. Fetch is an important characteristic of open water because longer fetches can result in larger wind-generated waves. The larger waves, in turn, can increase shoreline erosion and sediment resuspension (Rohweder and others 2012). Increases in sediment resuspension lead to increases in water turbidity, which in turn decreases light penetration and, therefore, create conditions less conducive to aquatic plant growth (Giblin and others 2010).
A wind fetch model was developed by David Finlayson, U. S. Geological Survey, Pacific Science Center, while he was a Ph.D. student at the University of Washington (Finlayson 2005). This method calculates effective fetch using the recommended procedure of the Shore Protection Manual (USACE 1984). Scientists at the United States Geological Survey, Upper Midwest Environmental Sciences Center (UMESC) and the United States Army Corps of Engineers (USACE) further refined this model (Rohweder and others 2012) and structured it to operate using the most recent version of the ArcMap Geographic Information System platform (Esri, 2019). At the time the analysis was performed, the version of ArcMap used was 10.7.1. The model refined in 2012 was used for the analyses described in this report.
Using this model, UMESC performed an analysis to model weighted wind fetch for the Upper Mississippi River System (UMRS) corresponding to three separate time periods of land cover spatial data acquisition (1989, 2000, and 2010/2011). The purpose of the analysis was to examine how fetch varies over time and space within the UMRS for potential management applications. For more detailed information on the wind fetch model, examine the USGS Open-File Report by Rohweder and others (2012).
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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Persons, Trevor","contributorId":247703,"corporation":false,"usgs":false,"family":"Persons","given":"Trevor","affiliations":[{"id":49619,"text":"Field Herpetologist, Northern Arizona University, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":808137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Drost, Charles A. 0000-0002-4792-7095 charles_drost@usgs.gov","orcid":"https://orcid.org/0000-0002-4792-7095","contributorId":3151,"corporation":false,"usgs":true,"family":"Drost","given":"Charles","email":"charles_drost@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":808138,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70217097,"text":"70217097 - 2020 - Using hair cortisol to assess physiological stress in Alaska polar bears","interactions":[],"lastModifiedDate":"2025-03-07T15:42:57.149246","indexId":"70217097","displayToPublicDate":"2020-10-31T08:27:38","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":251,"text":"Final Report","active":false,"publicationSubtype":{"id":4}},"title":"Using hair cortisol to assess physiological stress in Alaska polar bears","docAbstract":"The concentration of cortisol in hair (HCC) of polar bears (Ursus maritimus) may provide a retrospective view of physiological stress they experience and a link to their response to environmental change. To understand this relationship, we assayed HCC from polar bears captured in the Alaska Beaufort, Bering and Chukchi seas during 1983–1989 and 2004–2016. Cortisol accumulated in hair through summer and autumn and into the subsequent winter. HCC was similar between adult males and adult females. No difference in HCC across regions suggested all bears responded similarly to the environment. HCC in spring was elevated following years with a high winter Arctic Oscillation index and highly variable wind speed. HCC increased non-linearly with increasing duration of the continental shelf summer open water period up to 50 days and then decreased. HCC of spring samples declined with increasing body size, indicating that the stress response was more active in smaller bears or those in poor body condition. HCC of spring samples was greater and more variable in 2004–2006 than during either 1983–1989 or 2008–2016, and significantly so for females with 1st year cubs and subadult females. Elevated HCC in 2004–2006 coincided with years of reduced survival of southern Beaufort Sea polar bears and suggests that unidentified environmental perturbations impacted Alaska polar bears. Because HCC may be obtained by relatively non-invasive means, it has potential use for assessing polar bear populations that are difficult to study by capturing. Hence, information gained from HCC can inform polar bear conservation, especially on the vulnerability of subadult females and adult females with new cubs, and possible future environmental perturbations impacts on bear physiology.","language":"English","publisher":"Northern Pacific Research Board","usgsCitation":"Durner, G.M., 2020, Using hair cortisol to assess physiological stress in Alaska polar bears: Final Report, 79 p.","productDescription":"79 p.","ipdsId":"IP-123453","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":381912,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://nprb.org/project-search/#metadata/9be4eee1-a9a4-4026-a477-02da9460d0d3/project/files"},{"id":381946,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beaufort Sea, Bering Sea, Chukchi Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -141.1083984375,\n 69.61120561869633\n ],\n [\n -135.17578125,\n 70.40734767606811\n ],\n [\n -140.18554687499997,\n 72.3157853052617\n ],\n [\n -154.3798828125,\n 72.93253803407026\n ],\n [\n -160.576171875,\n 73.18861179538935\n ],\n [\n -162.509765625,\n 73.20131708476698\n ],\n [\n -164.2236328125,\n 72.79008827319015\n ],\n [\n -160.7080078125,\n 71.00265967789278\n ],\n [\n -159.2578125,\n 70.8446726342528\n ],\n [\n -156.8408203125,\n 70.91664110709776\n ],\n [\n -152.0068359375,\n 70.34831755984779\n ],\n [\n -141.1083984375,\n 69.54987728327795\n ],\n [\n -141.1083984375,\n 69.61120561869633\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -168.1787109375,\n 65.6582745198266\n ],\n [\n -164.00390625,\n 66.60067571342496\n ],\n [\n -163.6083984375,\n 67.13582938531948\n ],\n [\n -166.6845703125,\n 68.39918004344189\n ],\n [\n -166.201171875,\n 69.06856318696033\n ],\n [\n -165.05859375,\n 68.95839084822076\n ],\n [\n -163.4765625,\n 69.4421276134176\n ],\n [\n -162.9052734375,\n 70.24460360904779\n ],\n [\n -167.5634765625,\n 70.88788500718185\n ],\n [\n -170.244140625,\n 70.17020068549206\n ],\n [\n -168.1787109375,\n 65.6582745198266\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -171.650390625,\n 63.68524808030715\n ],\n [\n -168.046875,\n 63.11463763252091\n ],\n [\n -167.51953124999997,\n 63.87939001720202\n ],\n [\n -169.541015625,\n 64.4348920430406\n ],\n [\n -171.38671874999997,\n 64.41592147626879\n ],\n [\n -172.3095703125,\n 64.03374392176401\n ],\n [\n -171.650390625,\n 63.68524808030715\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Durner, George M. 0000-0002-3370-1191 gdurner@usgs.gov","orcid":"https://orcid.org/0000-0002-3370-1191","contributorId":3576,"corporation":false,"usgs":true,"family":"Durner","given":"George","email":"gdurner@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":807603,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70268708,"text":"70268708 - 2020 - On the robustness of annual daily precipitation maxima estimates over Monsoon Asia","interactions":[],"lastModifiedDate":"2025-07-07T16:11:01.608215","indexId":"70268708","displayToPublicDate":"2020-10-30T11:09:30","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21978,"text":"Frontiers in Climate Services","active":true,"publicationSubtype":{"id":10}},"title":"On the robustness of annual daily precipitation maxima estimates over Monsoon Asia","docAbstract":"Understanding precipitation extremes over Monsoon Asia is vital for water resource management and hazard mitigation, but there are many gaps and uncertainties in observations in this region. To better understand observational uncertainties, this study uses a high-resolution validation dataset to assess the consistency of the representation of annual daily precipitation maxima (Rx1day) over land in 13 observational datasets from the Frequent Rainfall Observations on Grids (FROGS) database. The FROGS datasets are grouped into three categories: in situ-based and satellite-based with and without corrections to rain gauges. We also look at three sub-regions: Japan, India, and the Maritime Continent based on their different station density, orography, and coastal complexity. We find broad similarities in spatial and temporal distributions among in situ-based products over Monsoon Asia. Satellite products with correction to rain gauges show better general agreement and less inter-product spread than their uncorrected counterparts. However, this comparison also reveals strong sub-regional differences that can be explained by the quantity and quality of rain gauges. High consistency in spatial and temporal patterns are observed over Japan, which has a dense station network, while large inter-product spread is found over the Maritime Continent and India, which have sparser station density. We also highlight that while corrected satellite products show improvement compared to uncorrected products in regions of high station density (e.g., Japan) they have mixed success over other regions (e.g., India and the Maritime Continent). In addition, the length of record available at each station can also affect the satellite correction over these poorly sampled regions. Results of the additional comparison between all considered datasets and the sub-regional high resolution dataset remain the same, indicating that the overall quality of the station network has implications for the reliability of the in situ-based products derived and also the satellite products that use a correction to in situ data. Given these uncertainties in observations, there is no single best dataset for assessment of Rx1day in Monsoon Asia. In all cases we recommend users understand how each dataset is produced in order to select the most appropriate product to estimate precipitation extremes to fit their purpose.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fclim.2020.578785","usgsCitation":"Nguyen, P., Bador, M., Alexander, L., Lane, T., and Funk, C., 2020, On the robustness of annual daily precipitation maxima estimates over Monsoon Asia: Frontiers in Climate Services, v. 2, 578785, 19 p., https://doi.org/10.3389/fclim.2020.578785.","productDescription":"578785, 19 p.","ipdsId":"IP-121958","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":492046,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fclim.2020.578785","text":"Publisher Index Page"},{"id":491743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Monsoon Asia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 67.82681208821384,\n 28.08149631086141\n ],\n [\n 67.82681208821384,\n 4.541379126404635\n ],\n [\n 88.69639230102973,\n 4.541379126404635\n ],\n [\n 88.69639230102973,\n 28.08149631086141\n ],\n [\n 67.82681208821384,\n 28.08149631086141\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 148.23729356007158,\n 45.2939171288528\n ],\n [\n 129.57288839651233,\n 45.2939171288528\n ],\n [\n 129.57288839651233,\n 29.638462684082825\n ],\n [\n 148.23729356007158,\n 29.638462684082825\n ],\n [\n 148.23729356007158,\n 45.2939171288528\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 90.4186427916805,\n 10.095537024904786\n ],\n [\n 90.4186427916805,\n -11.16935497577198\n ],\n [\n 155.06835956423896,\n -11.16935497577198\n ],\n [\n 155.06835956423896,\n 10.095537024904786\n ],\n [\n 90.4186427916805,\n 10.095537024904786\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2","noUsgsAuthors":false,"publicationDate":"2020-10-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Nguyen, Phuong-Loan","contributorId":357544,"corporation":false,"usgs":false,"family":"Nguyen","given":"Phuong-Loan","affiliations":[{"id":85452,"text":"ARC Centre of Excellence for Climate Extremes, UNSW Sydney, Sydney, New South Wales, Australia","active":true,"usgs":false}],"preferred":false,"id":941695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bador, Margot","contributorId":223056,"corporation":false,"usgs":false,"family":"Bador","given":"Margot","email":"","affiliations":[{"id":40656,"text":"Climate Change Research Centre, UNSW Sydney","active":true,"usgs":false}],"preferred":false,"id":941696,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alexander, Lisa","contributorId":223054,"corporation":false,"usgs":false,"family":"Alexander","given":"Lisa","email":"","affiliations":[{"id":40656,"text":"Climate Change Research Centre, UNSW Sydney","active":true,"usgs":false}],"preferred":false,"id":941697,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lane, Todd P.","contributorId":357545,"corporation":false,"usgs":false,"family":"Lane","given":"Todd P.","affiliations":[{"id":85454,"text":"2School of Earth Science and ARC Centre of Excellence for Climate Extremes, The University of Melbourne, Melbourne, Victoria, Australia","active":true,"usgs":false}],"preferred":false,"id":941698,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":941699,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227642,"text":"70227642 - 2020 - Characterizing spatiotemporal patterns of crop phenology across North America during 2000–2016 using satellite imagery and agricultural survey data","interactions":[],"lastModifiedDate":"2022-01-24T14:57:06.932262","indexId":"70227642","displayToPublicDate":"2020-10-30T08:48:53","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1958,"text":"ISPRS Journal of Photogrammetry and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing spatiotemporal patterns of crop phenology across North America during 2000–2016 using satellite imagery and agricultural survey data","docAbstract":"Crop phenology represents an integrative indicator of climate change and plays a vital role in terrestrial carbon dynamics and sustainable agricultural development. However, spatiotemporal variations of crop phenology remain unclear at large scales. This knowledge gap has hindered our ability to realistically quantify the biogeochemical dynamics in agroecosystems, predict future climate, and make informed decisions for climate change mitigation and adaptation. In this study, we improved an EVI-curve-based approach and used it to detect spatiotemporal patterns in cropping intensity and five major phenological stages over North America during 2000–2016 using vegetation index in combination with agricultural survey data and other ancillary maps. Our predicted crop phenological stages showed strong linear relationships with the survey-based datasets, with R2, RMSEs, and MAEs in the ranges of 0.35 –0.99, three to ten days, and two to eight days, respectively. During the study period, the planting dates were advanced by 0.60 days/year (p < 0.01), and harvesting dates were delayed by 0.78 days/year (p < 0.01) over North America. A minimum temperature increase by 1 °C caused a 4.26-day planting advance (r = −0.50, p < 0. 01) or a 0.66-day harvest delay (r = 0.10, p < 0.01). While, a higher maximum temperature resulted in a planting advance by 4.48 days/°C (r = −0.62, p < 0.01) or a harvest advance by 2.22 days/°C (r = −0.40, p < 0.01). Our analysis illustrated evident spatiotemporal variations in crop phenology in response to climate change and management practices. The derived crop phenological datasets and cropping intensity maps can be used in regional climate assessments and in developing adaptation strategies.