River managers strive to use the best available science to sustain biodiversity and ecosystem function. To achieve this goal requires consideration of processes at different scales. Metacommunity theory describes how multiple species from different communities potentially interact with local-scale environmental drivers to influence population dynamics and community structure. However, this body of knowledge has only rarely been used to inform management practices for river ecosystems. In this article, we present a conceptual model outlining how the metacommunity processes of local niche sorting and dispersal can influence the outcomes of management interventions and provide a series of specific recommendations for applying these ideas as well as research needs. In all cases, we identify situations where traditional approaches to riverine management could be enhanced by incorporating an understanding of metacommunity dynamics. A common theme is developing guidelines for assessing the metacommunity context of a site or region, evaluating how that context may affect the desired outcome, and incorporating that understanding into the planning process and methods used. To maximize the effectiveness of management activities, scientists, and resource managers should update the toolbox of approaches to riverine management to reflect theoretical advances in metacommunity ecology.
","language":"English","publisher":"Wiley","doi":"10.1002/wat2.1557","usgsCitation":"Patrick, C.J., Anderson, K.E., Brown, B.L., Hawkins, C.P., Metcalfe, A.N., Saffarinia, P., Siqueira, T., Swan, C.M., Tonkin, J.D., and Yuan, L.L., 2021, The application of metacommunity theory to the management of riverine ecosystems: WIREs Water, v. 8, no. 6, e1557, 21 p., https://doi.org/10.1002/wat2.1557.","productDescription":"e1557, 21 p.","ipdsId":"IP-119036","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":450888,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wat2.1557","text":"Publisher Index Page"},{"id":389050,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-09-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Patrick, Christopher J.","contributorId":199778,"corporation":false,"usgs":false,"family":"Patrick","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":822932,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Kurt E.","contributorId":265545,"corporation":false,"usgs":false,"family":"Anderson","given":"Kurt","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":822933,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Brown L.","contributorId":265546,"corporation":false,"usgs":false,"family":"Brown","given":"Brown","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":822934,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hawkins, Charles P.","contributorId":198331,"corporation":false,"usgs":false,"family":"Hawkins","given":"Charles","email":"","middleInitial":"P.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":822935,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Metcalfe, Anya N. 0000-0002-6286-4889 ametcalfe@usgs.gov","orcid":"https://orcid.org/0000-0002-6286-4889","contributorId":5271,"corporation":false,"usgs":true,"family":"Metcalfe","given":"Anya","email":"ametcalfe@usgs.gov","middleInitial":"N.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":822936,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Saffarinia, Parsa","contributorId":265547,"corporation":false,"usgs":false,"family":"Saffarinia","given":"Parsa","email":"","affiliations":[],"preferred":false,"id":822937,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Siqueira, Tadeu","contributorId":265548,"corporation":false,"usgs":false,"family":"Siqueira","given":"Tadeu","email":"","affiliations":[],"preferred":false,"id":822938,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Swan, Christopher M.","contributorId":265549,"corporation":false,"usgs":false,"family":"Swan","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":822939,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tonkin, Jonathan D.","contributorId":260624,"corporation":false,"usgs":false,"family":"Tonkin","given":"Jonathan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":822940,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Yuan, Lester L.","contributorId":198316,"corporation":false,"usgs":false,"family":"Yuan","given":"Lester","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":822941,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70223780,"text":"fs20213046 - 2021 - Streamflow—Water year 2020","interactions":[],"lastModifiedDate":"2021-09-08T11:46:34.780751","indexId":"fs20213046","displayToPublicDate":"2021-09-07T19:14:29","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-3046","displayTitle":"Streamflow—Water Year 2020","title":"Streamflow—Water year 2020","docAbstract":"The maps and graphs in this summary describe national streamflow conditions for water year 2020 (October 1, 2019, to September 30, 2020) in the context of streamflow ranks relative to the 91-year period of water years 1930–2020. Annual runoff in the Nation’s rivers and streams during water year 2020 (11.10 inches) was higher than the long-term (1930–2020) mean annual runoff of 9.40 inches for the contiguous United States. Nationwide, the 2020 streamflow ranked the 10th highest out of the 91 years.
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Scant availability of streamflow data can impede the utility of streamflow as a variable in ecological models of aquatic and terrestrial species, especially when studying small streams in watersheds that lack streamgages. Streamflow data at fine resolution and broad extent were needed by collaborators for ecological research on small streams in several ungaged watersheds of southwestern Wyoming, where streamflow data are sparse.
To improve the utility of sparse streamflow data to ecological research in ungaged watersheds, we developed a machine learning approach in R for modeling spatially and temporally continuous monthly streamflow from 2012 through 2017 in three semiarid montane-steppe watersheds (with drainage areas of 26–55 square miles and mean elevations of 8,031–8,455 feet) on the Wyoming Range in the upper Green River Basin. A machine learning streamflow (MLFLOW) model was calibrated and validated with 971 discrete streamflow observations and 24 static and dynamic predictor variables derived from geospatial and time series data on climatic, physiographic, and anthropogenic characteristics affecting streamflow. The predictor variables were temporally and spatially conditioned to amplify the relation of predictor variables to monthly streamflow.
The MLFLOW model had satisfactory agreement between observed and predicted streamflow (coefficient of determination [R2]=0.80, Nash-Sutcliffe efficiency [NSE]=0.79, NSE with log-transformed data [logNSE]=0.82, and percent bias [PBIAS]=0.7 percent). NSE and logNSE indicated the MLFLOW model performed equally well for high and low flows, and PBIAS indicated the MLFLOW model did not overpredict or underpredict monthly streamflow. Streamflow predictions seemed to well represent the annual hydrograph within the study area during the study period.
The most important variables (statistically important in the MLFLOW model) for explaining monthly streamflow were temporally and spatially conditioned dynamic climatic variables, mostly precipitation and snow water equivalent. Importance of the static and dynamic variables did not differ substantially among the three watersheds but differed considerably among the 6 years. Monthly streamflow increased with increasing precipitation, snow water equivalent, and drainage area but decreased with increasing forest cover, elevation, evapotranspiration, and temperature.
The MLFLOW model was most sensitive to selection of dynamic climatic variables. Unconditioned dynamic climatic variables alone explained 54 percent of the variance (R2=0.54) in monthly streamflow, whereas adding static physiographic and anthropogenic variables only explained 12 percent more of the variance (R2=0.66). Also, spatial conditioning of all variables together with temporal conditioning of dynamic variables increased the variance explained in the MLFLOW model by another 14 percent (R2=0.80). The MLFLOW model also had greater sensitivity to temporal than to spatial differences in the data. For the MLFLOW model trained with observations from all watersheds and years or for models trained with observations from all except one watershed or 1 year left out sequentially, performance was better in testing on observations from each watershed than from each year separately. Also, performance was better for models fitted to fewer sites than to fewer months of observations.
The greatest utility of the modeling approach is the ease of use and the speed of processing input data, running the model, and interpreting the model output, whereas the greatest limitation is the need for spatially and temporally representative streamflow observations to drive the model. Although familiarity with R is necessary, only a working knowledge of hydrology (for selecting appropriate predictor variables and evaluating the quality of streamflow observations) and a rudimentary understanding of machine learning models are needed. Therefore, this modeling approach is practicable for other scientists who work with water but who are not hydrologists.
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3162 Bozeman Avenue
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The restoration of coastal habitats, particularly coral reefs, can reduce risks by decreasing the exposure of coastal communities to flooding hazards. In the United States, the protective services provided by coral reefs were recently assessed in social and economic terms, with the annual protection provided by U.S. coral reefs off the coasts of the State of Florida and the Commonwealth of Puerto Rico estimated to be more than 9,800 people and $859 million (2010 U.S. dollars). Hurricanes Irma and Maria in 2017 caused widespread damage to coral reefs in the State of Florida and the Commonwealth of Puerto Rico. Here we combine engineering, ecologic, geospatial, social, and economic data and tools to provide a rigorous valuation of where potential coral reef restoration could decrease the hazard faced by Florida and Puerto Rico’s reef-fronted coastal communities. The three restoration scenarios considered: (1) Ecological restoration, ‘E25’, which assumes planting 0.25-meter (m)-high corals on a (cross-shore) 25-m-wide reef; (2) Structural plus ecological, ‘S25’, which assumes emplacing a 1.00-m high structure with 0.25-m high corals on top on a 25 m wide reef; and (3) structural plus ecological, ‘S05’, which assumes emplacing a 1.00-m high structure with 0.25-m high corals on top on a 5 m wide reef. Planted corals are assumed to increase hydrodynamic roughness, thereby dissipating incident wave energy and decreasing flooding potential. We used a standardized approach to ‘place’ potential restoration projects throughout the whole (linear) extent of reefs bordering Florida and Puerto Rico to identify where coral reef restoration could be useful for meeting flood reduction benefits. We always sited potential restoration projects within the existing distribution of reefs even though many sites were far (kilometers [km]) offshore and some sites were relatively deep (up to 7 m depth). We followed risk-based valuation approaches to map flood zones at 10-square-meter resolution along all 980 km of Florida and Puerto’s Rico reef-lined shorelines for the three potential coral reef restoration scenarios and compare them to the flood zones without coral reef restoration. We quantified the potential coastal flood risk reduction provided by coral reef restoration using the latest information from the U.S. Census Bureau, Federal Emergency Management Agency, and Bureau of Economic Analysis for return-interval storm events. Using the damages associated with each storm probability, we also calculate the change in annual expected damages, a measure of the annual protection gained because of coral reef restoration. We found that the benefits of reef restoration off Florida and Puerto Rico are spatially highly variable. In most areas, we found little or no benefit from reef restoration (for example, restoration sites were far offshore or deep). However, there were a number of key areas where reef restoration could have substantial benefits for flood risk reduction. In particular, we estimated the protection gained by Florida and Puerto Rico’s coral reefs from coral reef restoration to result in:
Thus, the annual value of flood risk reduction provided by potential coral reef restoration in Florida and Puerto Rico is more than 3,100 people and $272.9 million (2010 U.S. dollars) in economic activity. These data provide stakeholders and decision makers with a spatially explicit, rigorous valuation of how, where, and when potential coral reef restoration in Florida and Puerto Rico can increase critical coastal storm flood reduction benefits. These results help identify areas where reef management, recovery, and restoration could potentially help reduce the risk to, and increase the resiliency of, Florida and Puerto Rico’s coastal communities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211054","collaboration":"Prepared in cooperation with the University of California, Santa Cruz","usgsCitation":"Storlazzi, C.D., Reguero, B.G., Cumming, K.A., Cole, A.D., Shope, J.B., Gaido L., C., Viehman, T.S., Nickel, B.A., and Beck, M.W., 2021, Rigorously valuing the coastal hazard risks reduction provided by potential coral reef restoration in Florida and Puerto Rico: U.S. Geological Survey Open-File Report 2021–1054, 35 p., https://doi.org/10.3133/ofr20211054.","productDescription":"Report: vi, 35 p.; Data Release","numberOfPages":"35","onlineOnly":"Y","ipdsId":"IP-125062","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":386211,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1054/covrthb.jpg"},{"id":386212,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1054/ofr20211054.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":386214,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZQKZR9","linkHelpText":"Projected flooding extents and depths based on 10-, 50-, 100-, and 500-year wave-energy return periods for the State of Florida, the Commonwealth of Puerto Rico, and the Territory of the U.S. Virgin Islands for current and potentially restored coral reefs"},{"id":386215,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211055","text":"Open-File Report 2021-1055","linkHelpText":"- Rigorously Valuing the Impact of Projected Coral Reef Degradation on Coastal Hazard Risk in Florida"},{"id":386216,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211056","text":"Open-File Report 2021-1056","linkHelpText":"- Rigorously Valuing the Impact of Hurricanes Irma and Maria on Coastal Hazard Risk in Florida and Puerto Rico"}],"country":"United States","state":"Florida","otherGeospatial":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.79345703125,\n 27.401032392938866\n ],\n [\n -80.716552734375,\n 26.82407078047018\n ],\n [\n -80.68359375,\n 26.352497858154024\n ],\n [\n -80.74951171875,\n 25.671235828577043\n ],\n [\n -80.650634765625,\n 25.3241665257384\n ],\n [\n -80.88134765625,\n 24.886436490787712\n ],\n [\n -81.2548828125,\n 24.73685348477069\n ],\n [\n -81.27685546875,\n 24.607069137709683\n ],\n [\n -80.771484375,\n 24.726874870506972\n ],\n [\n -80.22216796875,\n 25.16517336866393\n ],\n [\n -80.101318359375,\n 25.671235828577043\n ],\n [\n -79.94750976562499,\n 26.322960198925365\n ],\n [\n -80.00244140625,\n 26.941659545381516\n ],\n [\n -80.277099609375,\n 27.44004046509707\n ],\n [\n -80.79345703125,\n 27.401032392938866\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.390380859375,\n 18.594188856740413\n ],\n [\n -66.7529296875,\n 18.70869162255995\n ],\n [\n -67.08251953125,\n 18.729501999072138\n ],\n [\n -67.32421875,\n 18.510865709091377\n ],\n [\n -67.401123046875,\n 18.25021997706561\n ],\n [\n -67.30224609375,\n 17.916022703877665\n ],\n [\n -66.895751953125,\n 17.853290114098012\n ],\n [\n -66.42333984375,\n 17.8742034396575\n ],\n [\n -65.885009765625,\n 17.821915515968854\n ],\n [\n -65.467529296875,\n 17.926475979176438\n ],\n [\n -65.32470703125,\n 18.218916080017465\n ],\n [\n -65.511474609375,\n 18.46918890441719\n ],\n [\n -66.390380859375,\n 18.594188856740413\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Coastal and Marine Science Center
2885 Mission St.
Santa Cruz, CA 95060
The degradation of coastal habitats, particularly coral reefs, raises risks by increasing the exposure of coastal communities to flooding hazards. In the United States, the physical protective services provided by coral reefs were recently assessed, in social and economic terms, with the annual protection provided by U.S. coral reefs off the coast of the State of Florida estimated to be more than 5,600 people and $675 million (2010 U.S. dollars). Degradation of coral reef ecosystems over the past several decades and during tropical storm events has caused regional-scale erosion of the shallow seafloor that serves as a protective barrier against coastal hazards along Southeast Florida, increasing risks to coastal populations. Here we combine engineering, ecologic, geospatial, social, and economic data and tools to provide a rigorous valuation of the increased hazard faced by Florida’s reef-fronted coastal communities because of the projected degradation of its adjacent coral reefs. We followed risk-based valuation approaches to map flood zones at 10-square-meter resolution along all 430 kilometers of Florida’s reef-lined shorelines for both the current and projected future coral reef conditions. We quantified the coastal flood risk increase caused by coral reef degradation using the latest information from the U.S. Census Bureau, Federal Emergency Management Agency, and Bureau of Economic Analysis for return-interval storm events. Using the damages associated with each storm probability, we also calculated the change in annual expected damages, a measure of the annual protection lost because of projected coral reef degradation. We found that degradation of the coral reefs off Florida increases future risks significantly. In particular, we estimated the protection lost by Florida’s coral reefs from projected coral reef degradation will result in:
Thus, the annual value of increased flood risk caused by the projected degradation of Florida’s coral reefs is more than 7,300 people and $823.6 million (2010 U.S. dollars). These data provide stakeholders and decision makers with a spatially explicit, rigorous valuation of how, where, and when degradation of Florida’s coral reefs will decrease critical coastal storm flood reduction benefits. These results help identify areas where reef management, recovery, and restoration could potentially help reduce the risk to, and increase the resiliency of, Florida’s coastal communities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211055","collaboration":"Prepared in cooperation with the University of California, Santa Cruz","usgsCitation":"Storlazzi, C.D., Reguero, B.G., Yates, K.K., Cumming, K.A., Cole, A.D., Shope, J.B., Gaido L., C., Zawada, D.G., Arsenault, S.R., Fehr, Z.W., Nickel, B.A., and Beck, M.W., 2021, Rigorously valuing the impact of projected coral reef degradation on coastal hazard risk in Florida: U.S. Geological Survey Open-File Report 2021–1055, 27 p., https://doi.org/10.3133/ofr20211055.","productDescription":"Report: vi, 27 p.; Data Release","numberOfPages":"27","onlineOnly":"Y","ipdsId":"IP-125063","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":386221,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211054","text":"Open-File Report 2021-1054","linkHelpText":"- Rigorously Valuing the Potential Coastal Hazard Risk Reduction Provided by Coral Reef Restoration in Florida and Puerto Rico"},{"id":386222,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211056","text":"Open-File Report 2021-1056","linkHelpText":"- Rigorously Valuing the Impact of Hurricanes Irma and Maria on Coastal Hazard Risk in Florida and Puerto Rico"},{"id":386220,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D9LDEP","linkHelpText":"Projected flooding extents and depths based on 10-, 50-, 100-, and 500-year wave-energy return periods for the State of Florida with and without projected coral reef degradation"},{"id":386218,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1055/covrthb.jpg"},{"id":386219,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1055/ofr20211055.pdf","text":"Report","size":"6.5 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.79345703125,\n 27.401032392938866\n ],\n [\n -80.716552734375,\n 26.82407078047018\n ],\n [\n -80.68359375,\n 26.352497858154024\n ],\n [\n -80.74951171875,\n 25.671235828577043\n ],\n [\n -80.650634765625,\n 25.3241665257384\n ],\n [\n -80.88134765625,\n 24.886436490787712\n ],\n [\n -81.2548828125,\n 24.73685348477069\n ],\n [\n -81.27685546875,\n 24.607069137709683\n ],\n [\n -80.771484375,\n 24.726874870506972\n ],\n [\n -80.22216796875,\n 25.16517336866393\n ],\n [\n -80.101318359375,\n 25.671235828577043\n ],\n [\n -79.94750976562499,\n 26.322960198925365\n ],\n [\n -80.00244140625,\n 26.941659545381516\n ],\n [\n -80.277099609375,\n 27.44004046509707\n ],\n [\n -80.79345703125,\n 27.401032392938866\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Coastal and Marine Science Center
2885 Mission St.
Santa Cruz, CA 95060
The degradation of coastal habitats, particularly coral reefs, raises risks by increasing the exposure of coastal communities to flooding hazards. In the United States, the physical protective services provided by coral reefs were recently assessed in social and economic terms, with the annual protection provided by U.S. coral reefs off the coasts of the State of Florida and the Commonwealth of Puerto Rico estimated to be more than 9,800 people and $859 million (2010 U.S. dollars). Hurricanes Irma and Maria in 2017 caused widespread damage to coral reefs in the State of Florida and the Commonwealth of Puerto Rico. These damages were measured in post-storm surveys of reefs and assessed in terms of their impact on reef condition and height, which are critical parameters for evaluating the coastal defense benefits of reefs. We combined engineering, ecologic, geospatial, social, and economic data and tools to value the increased risks in Florida and Puerto Rico from hurricane-induced damages to their adjacent coral reefs. We followed risk-based valuation approaches to map flooding at 10-square-meter resolution along all 980 kilometers of Florida and Puerto Rico’s reef-lined shorelines considering reef condition before (undamaged) and after (damaged) the 2017 hurricanes. We quantified the coastal flood risk increase caused by the hurricane-induced damage to the coral reefs using the latest information from the U.S. Census Bureau, Federal Emergency Management Agency, and Bureau of Economic Analysis for return-interval storm events. Using the damages associated with each storm probability, we also calculated the change in annual expected damages, a measure of the annual protection lost because of the reef damage caused by the 2017 hurricanes. We found that the damages to the coral reefs off Florida and Puerto Rico from Hurricanes Irma and Maria increased future risks significantly. In particular, we estimated the protection lost by Florida and Puerto Rico’s coral reefs from the 2017 hurricanes to result in:
Thus, the annual value of increased flood risk caused by the damage to Florida and Puerto Rico’s coral reefs from hurricanes in 2017 is more than 4,300 people and $181.5 mil-lion (2010 U.S. dollars) in economic impacts. These data provide stakeholders and decision makers with a spatially explicit, rigorous valuation of how, where, and when the damage from the 2017 hurricanes decreased critical coastal storm flood reduction benefits to Florida and Puerto Rico’s coral reefs. These results help identify areas where reef management, recovery, and restoration could potentially help reduce the risk to, and increase the resiliency of, Florida and Puerto Rico’s coastal communities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211056","collaboration":"Prepared in cooperation with the University of California, Santa Cruz and the National Oceanic and Atmospheric Administration","usgsCitation":"Storlazzi, C.D., Reguero, B.G., Viehman, T.S., Cumming, K.A., Cole, A.D., Shope, J.B., Groves, S.H., Gaido L., C., Nickel, B.A., and Beck, M.W., 2021, Rigorously valuing the impact of Hurricanes Irma and Maria on coastal hazard risks in Florida and Puerto Rico: U.S. Geological Survey Open-File Report 2021–1056, 29 p., https://doi.org/10.3133/ofr20211056.","productDescription":"Report: v, 29 p.; Data Release","numberOfPages":"29","onlineOnly":"Y","ipdsId":"IP-125064","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":386227,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EHOBKO","linkHelpText":"Projected flooding extents and depths based on 10-, 50-, 100-, and 500-year wave-energy return periods for the State of Florida and the Commonwealth of Puerto Rico before and after Hurricanes Irma and Maria due to the storms' damage to the coral reefs"},{"id":386229,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211055","text":"Open-File Report 2021-1055","linkHelpText":"- Rigorously Valuing the Impact of Projected Coral Reef Degradation on Coastal Hazard Risk in Florida"},{"id":386225,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1056/covrthb.jpg"},{"id":386226,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1056/ofr20211056.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":386228,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211054","text":"Open-File Report 2021-1054","linkHelpText":"- Rigorously Valuing the Potential Coastal Hazard Risk Reduction Provided by Coral Reef Restoration in Florida and Puerto Rico"}],"country":"United States","state":"Florida","otherGeospatial":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.79345703125,\n 27.401032392938866\n ],\n [\n -80.716552734375,\n 26.82407078047018\n ],\n [\n -80.68359375,\n 26.352497858154024\n ],\n [\n -80.74951171875,\n 25.671235828577043\n ],\n [\n -80.650634765625,\n 25.3241665257384\n ],\n [\n -80.88134765625,\n 24.886436490787712\n ],\n [\n -81.2548828125,\n 24.73685348477069\n ],\n [\n -81.27685546875,\n 24.607069137709683\n ],\n [\n -80.771484375,\n 24.726874870506972\n ],\n [\n -80.22216796875,\n 25.16517336866393\n ],\n [\n -80.101318359375,\n 25.671235828577043\n ],\n [\n -79.94750976562499,\n 26.322960198925365\n ],\n [\n -80.00244140625,\n 26.941659545381516\n ],\n [\n -80.277099609375,\n 27.44004046509707\n ],\n [\n -80.79345703125,\n 27.401032392938866\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.368408203125,\n 18.542116654448996\n ],\n [\n -66.961669921875,\n 18.646245142670608\n ],\n [\n -67.269287109375,\n 18.552532366385577\n ],\n [\n -67.357177734375,\n 18.198043686762652\n ],\n [\n -67.236328125,\n 17.916022703877665\n ],\n [\n -66.59912109375,\n 17.832374329567518\n ],\n [\n -65.643310546875,\n 17.95783210227242\n ],\n [\n -65.291748046875,\n 18.22935133838668\n ],\n [\n -65.54443359375,\n 18.500447458475094\n ],\n [\n -66.368408203125,\n 18.542116654448996\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Coastal and Marine Science Center
2885 Mission St.
Santa Cruz, CA 95060
Interactions between neighboring plants are critical for biodiversity maintenance in plant populations and communities. Intraspecific trait variation and genome duplication are common in plant species and can drive eco-evolutionary dynamics through genotype-mediated plant–plant interactions. However, few studies have examined how species-wide intraspecific variation may alter interactions between neighboring plants. We investigate how subspecies and ploidy variation in a genetically diverse species, big sagebrush (Artemisia tridentata), can alter the demographic outcomes of plant interactions. Using a replicated, long-term common garden experiment that represents range-wide diversity of A. tridentata, we ask how intraspecific variation, environment, and stand age mediate neighbor effects on plant growth and survival. Spatially explicit models revealed that ploidy variation and subspecies identity can mediate plant–plant interactions but that the effect size varied in time and across experimental sites. We found that demographic impacts of neighbor effects were strongest during early stages of stand development and in sites with greater growth rates. Within subspecies, tetraploid populations showed greater tolerance to neighbor crowding compared to their diploid variants. Our findings provide evidence that intraspecific variation related to genome size and subspecies identity impacts spatial demography in a genetically diverse plant species. Accounting for intraspecific variation in studies of conspecific density dependence will improve our understanding of how local populations will respond to novel genotypes and biotic interaction regimes. As introduction of novel genotypes into local populations becomes more common, quantifying demographic processes in genetically diverse populations will help predict long-term consequences of plant–plant interactions.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.3502","usgsCitation":"Zaiats, A., Germino, M., Serpe, M.D., Richardson, B., and Caughlin, T., 2021, Intraspecific variation mediates density dependence in a genetically diverse plant species: Ecology, v. 102, no. 11, e03502, 11 p., https://doi.org/10.1002/ecy.3502.","productDescription":"e03502, 11 p.","ipdsId":"IP-122281","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":388887,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Utah","city":"Ephraim, Majors Flat, Orchard","otherGeospatial":"Great Basin Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.861572265625,\n 43.46886761482925\n ],\n [\n -114.04907226562499,\n 41.9921602333763\n ],\n [\n -114.06005859375,\n 37.00255267215955\n ],\n [\n -113.148193359375,\n 37.59682400108367\n ],\n [\n -112.06054687499999,\n 39.39375459224348\n ],\n [\n -111.64306640625,\n 40.10328591293439\n ],\n [\n -111.90673828125,\n 40.83874913796459\n ],\n [\n -112.071533203125,\n 42.00032514831621\n ],\n [\n -115.8837890625,\n 43.492782808225\n ],\n [\n -116.861572265625,\n 43.46886761482925\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"102","issue":"11","noUsgsAuthors":false,"publicationDate":"2021-09-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Zaiats, Andrii","contributorId":257073,"corporation":false,"usgs":false,"family":"Zaiats","given":"Andrii","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":822590,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Germino, Matthew J. 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":251901,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":822591,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Serpe, Marcelo D.","contributorId":257074,"corporation":false,"usgs":false,"family":"Serpe","given":"Marcelo","email":"","middleInitial":"D.","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":822592,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Richardson, Bryce 0000-0001-9521-4367","orcid":"https://orcid.org/0000-0001-9521-4367","contributorId":195702,"corporation":false,"usgs":false,"family":"Richardson","given":"Bryce","email":"","affiliations":[],"preferred":false,"id":822593,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Caughlin, Trevor 0000-0001-6752-2055","orcid":"https://orcid.org/0000-0001-6752-2055","contributorId":256964,"corporation":false,"usgs":false,"family":"Caughlin","given":"Trevor","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":822594,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70223771,"text":"70223771 - 2021 - Pedigree accumulation analysis: Combining methods from community ecology and population genetics for breeding adult estimation","interactions":[],"lastModifiedDate":"2021-12-10T16:43:01.819527","indexId":"70223771","displayToPublicDate":"2021-09-07T10:51:14","publicationYear":"2021","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":"Pedigree accumulation analysis: Combining methods from community ecology and population genetics for breeding adult estimation","docAbstract":"The basic stratigraphic and structural framework of Mount Diablo is described using a revised geologic map, gravity data, and aeromagnetic data. The mountain is made up of two distinct stratigraphic assemblages representing different depocenters that were juxtaposed by ~20 km of late Pliocene and Quaternary right-lateral offset on the Greenville-Diablo-Concord fault. Both assemblages are composed of Cretaceous and Cenozoic strata overlying a compound basement made up of the Franciscan and Great Valley complexes. The rocks are folded and faulted by late Neogene and Quaternary compressional structures related to both regional plate-boundary–normal compression and a restraining step in the strike-slip fault system. The core of the mountain is made up of uplifted basement rocks. Late Neogene and Quaternary deformation is overprinted on Paleogene extensional deformation that is evidenced at Mount Diablo by significant attenuation in the basement rocks and by an uptilted stepped graben structure on the northeast flank. Retrodeformation of the northeast flank suggests that late Early to early Late Cretaceous strata may have been deposited against and across a steeply west-dipping basement escarpment. The location of the mountain today was a depocenter through the Late Cretaceous and Paleogene and received shallow-marine deposits periodically into the late Miocene. Uplift of the mountain itself happened mostly in the Quaternary.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Regional geology of Mount Diablo, California: Its tectonic evolution on the North America plate boundary","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2021.1217(01)","usgsCitation":"Graymer, R., and Langenheim, V., 2021, Geologic framework of Mount Diablo, California, chap. of Regional geology of Mount Diablo, California: Its tectonic evolution on the North America plate boundary, v. 217, p. 1-34, https://doi.org/10.1130/2021.1217(01).","productDescription":"34 p.","startPage":"1","endPage":"34","ipdsId":"IP-113894","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":450894,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/figure/Supplemental_Material_Geologic_framework_of_Mount_Diablo_California/15148989","text":"External Repository"},{"id":388591,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mount Diablo","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.025146484375,\n 37.7897092979573\n ],\n [\n -121.80198669433592,\n 37.7897092979573\n ],\n [\n -121.80198669433592,\n 37.92632597629602\n ],\n [\n -122.025146484375,\n 37.92632597629602\n ],\n [\n -122.025146484375,\n 37.7897092979573\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"217","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Graymer, Russell 0000-0003-4910-5682","orcid":"https://orcid.org/0000-0003-4910-5682","contributorId":207816,"corporation":false,"usgs":true,"family":"Graymer","given":"Russell","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":822042,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Langenheim, Victoria 0000-0003-2170-5213","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":206990,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria","affiliations":[],"preferred":true,"id":822043,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70229777,"text":"70229777 - 2021 - Integrating socioecological suitability with human-wildlife conflict risk: Case study for translocation of a large ungulate","interactions":[],"lastModifiedDate":"2022-03-17T15:32:45.548565","indexId":"70229777","displayToPublicDate":"2021-09-07T10:17:25","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Integrating socioecological suitability with human-wildlife conflict risk: Case study for translocation of a large ungulate","docAbstract":"We develop a self‐consistent scaling model relating magnitude Mw to surface rupture length (LE), surface displacement DE, and rupture width WE, for strike‐slip faults. Knowledge of the long‐term fault‐slip rate SF improves magnitude estimates. Data are collected for 55 ground‐rupturing strike‐slip earthquakes that have geological estimates of LE, DE, and SF, and geophysical estimates of WE. We begin with the model of Anderson et al. (2017), which uses a closed form equation for the seismic moment of a surface‐rupturing strike‐slip fault of arbitrary aspect ratio and given stress drop, ΔτC. Using WE estimates does not improve Mw estimates. However, measurements of DE plus the relationship between ΔτC and surface slip provide an alternate approach to study WE. A grid of plausible stress drop and width pairs were used to predict displacement and earthquake magnitude. A likelihood function was computed from within the uncertainty ranges of the corresponding observed Mw and DE values. After maximizing likelihoods over earthquakes in length bins, we found the most likely values of WE for constant stress drop; these depend on the rupture length. The best‐fitting model has the surprising form WE∝logLE—a gentle increase in width with rupture length. Residuals from this model are convincingly correlated to the fault‐slip rate and also show a weak correlation with the crustal thickness. The resulting model thus supports a constant stress drop for ruptures of all lengths, consistent with teleseismic observation. The approach can be extended to test other observable factors that might improve the predictability of magnitude from a mapped fault for seismic hazard analyses.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120210113","usgsCitation":"Anderson, J.G., Biasi, G., Angster, S.J., and Wesnousky, S., 2021, Improved scaling relationships for seismic moment and average slip of strike-slip earthquakes incorporating fault slip rate, fault width and stress drop: Bulletin of the Seismological Society of America, v. 111, no. 5, p. 2379-2392, https://doi.org/10.1785/0120210113.","productDescription":"14 p.","startPage":"2379","endPage":"2392","ipdsId":"IP-117223","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482645,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"111","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-09-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, John G.","contributorId":140379,"corporation":false,"usgs":false,"family":"Anderson","given":"John","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":929142,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Biasi, Glenn 0000-0003-0940-5488 gbiasi@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-5488","contributorId":195946,"corporation":false,"usgs":true,"family":"Biasi","given":"Glenn","email":"gbiasi@usgs.gov","affiliations":[],"preferred":true,"id":929143,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Angster, Stephen J. 0000-0001-9250-8415","orcid":"https://orcid.org/0000-0001-9250-8415","contributorId":225610,"corporation":false,"usgs":true,"family":"Angster","given":"Stephen","email":"","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":929144,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wesnousky, Stephen G.","contributorId":351624,"corporation":false,"usgs":false,"family":"Wesnousky","given":"Stephen G.","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":929145,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70223483,"text":"sim3470 - 2021 - Geologic map of Olympus Mons caldera, Mars","interactions":[],"lastModifiedDate":"2023-03-20T18:13:31.216229","indexId":"sim3470","displayToPublicDate":"2021-09-07T10:02:40","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3470","displayTitle":"Geologic Map of Olympus Mons Caldera, Mars","title":"Geologic map of Olympus Mons caldera, Mars","docAbstract":"The Mars volcano, Olympus Mons, is probably the best known extraterrestrial volcano. The summit forms a nested caldera with six overlapping collapse pits that collectively measure ~65 x ~80 kilometers (km). Numerous wrinkle ridges and graben occur on the caldera floor, and topographic data indicate >1.2 km of elevation change since the formation of the floor as a series of lava lakes. The paths of lava flows on the south and southeast flanks do not conform to present-day topography. Mapping at a scale of 1:200,000 shows that the summit area displays a complex volcanic history that has numerous similarities to terrestrial shield volcanoes. Pangboche crater is a large (~10-km-diameter) crater of impact origin that lies on the south flank of the caldera and, because of the elevation and lack of volatiles, it displays numerous features more similar to fresh lunar craters than to impact craters on Mars.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3470","collaboration":"Prepared for the National Aeronautics and Space Administration","usgsCitation":"Mouginis-Mark, P.J., 2021, Geologic map of Olympus Mons caldera, Mars: U.S. Geological Survey Scientific Investigations Map 3470, 6 p., 1 sheet, scale 1:200,000, https://doi.org/10.3133/sim3470.","productDescription":"Report: iv, 6 p.; Metadata; Read Me; 1 Sheet: 38.06 x 40.11 inches","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-107079","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":436209,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95C2UHD","text":"USGS data release","linkHelpText":"Interactive Map: USGS SIM 3470 Geologic Map of Olympus Mons Caldera, Mars"},{"id":388840,"rank":7,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3470/sim3470_gis_files.zip","text":"SIM 3470 GIS Files","size":"260 MB","linkFileType":{"id":6,"text":"zip"}},{"id":388595,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3470/sim3470_sheet.pdf","size":"11 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":388596,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3470/sim3470_metadata.txt","size":"20 KB","linkFileType":{"id":2,"text":"txt"}},{"id":388592,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3470/covrthb.jpg"},{"id":388593,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3470/sim3470_pamphlet.pdf","text":"Pamphlet to Accompany Map Sheet","size":"1 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":388594,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3470/sim3470_readme.docx","text":"Read Me","size":"25 KB docx"},{"id":405427,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.5066/P95C2UHD","text":"Interactive map","description":"Mouginis-Mark, P.J., 2021, Geologic map of Olympus Mons caldera, Mars: U.S. Geological Survey Scientific Investigations Map 3470, 6 p., 1 sheet, scale 1:200,000, https://doi.org/10.3133/sim3470.","linkHelpText":"- Geologic Map of Olympus Mons Caldera, Mars, 1:200K. Mouginis-Mark (2021)"},{"id":388598,"rank":6,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3470/sim3470_metadata.xml","size":"20 KB","linkFileType":{"id":8,"text":"xml"}}],"contact":"Contact Astrogeology Research Program staff
Astrogeology Science Center
U.S. Geological Survey
2255 N. Gemini Dr.
Flagstaff, AZ 86001
Sea ducks exhibit complex movement patterns throughout their annual cycle; most species use distinct molting and staging sites during migration and disjunct breeding and wintering sites. Although research on black scoters (Melanitta americana) has investigated movements and habitat selection during winter, little is known about their annual-cycle movements. We used satellite telemetry to identify individual variation in migratory routes and breeding areas for black scoters wintering along the Atlantic Coast, to assess migratory connectivity among wintering, staging, breeding, and molt sites, and to examine effects of breeding site attendance on movement patterns and phenology. Black scoters occupied wintering areas from Canadian Maritime provinces to the southeastern United States. Males used an average of 2.5 distinct winter areas compared to 1.1 areas for females, and within-winter movements averaged 1,256 km/individual. Individuals used an average of 2.1 staging sites during the 45-day pre-breeding migration period, and almost all were detected in the Gulf of St. Lawrence. Males spent less time at breeding sites and departed them earlier than females. During post-breeding migration, females took approximately 25 fewer days than males to migrate from breeding sites to molt and staging sites, and then wintering areas. Most individuals used molt sites in James and Hudson bays before migrating directly to coastal wintering sites, which took approximately 11 days and covered 1,524 km. Males tended to arrive at wintering areas 10 days earlier than females. Individuals wintering near one another did not breed closer together than expected by chance, suggesting weak spatial structuring of the Atlantic population. Females exhibited greater fidelity (4.5 km) to previously used breeding sites compared to males (60 km). A substantial number of birds bred west of Hudson Bay in the Barrenlands, suggesting this area is used more widely than believed previously. Hudson and James bays provided key habitat for black scoters that winter along the Atlantic Coast, with most individuals residing for >30% of their annual cycle in these bays. Relative to other species of sea duck along the Atlantic Coast, the Atlantic population of black scoter is more dispersed and mobile during winter but is more concentrated during migration. These results could have implications for future survey efforts designed to assess population trends of black scoters.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22125","usgsCitation":"Lamb, J.S., Gilliland, S.G., Savard, J.L., Loring, P.H., McWilliams, S.R., Olsen, G.H., Osenkowski, J.E., Paton, P.W., Perry, M., and Bowman, T.D., 2021, Annual-cycle movements and phenology of black scoters in eastern North America: Journal of Wildlife Management, v. 85, no. 8, p. 1628-1645, https://doi.org/10.1002/jwmg.22125.","productDescription":"18 p.","startPage":"1628","endPage":"1645","ipdsId":"IP-126228","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":489131,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.uri.edu/nrs_facpubs/523","text":"External Repository"},{"id":389808,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Chesapeake Bay, Delaware Bay, Gulf of St 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0000-0003-0358-3240","orcid":"https://orcid.org/0000-0003-0358-3240","contributorId":198059,"corporation":false,"usgs":false,"family":"Lamb","given":"Juliet","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":824006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gilliland, Scott G.","contributorId":225143,"corporation":false,"usgs":false,"family":"Gilliland","given":"Scott","email":"","middleInitial":"G.","affiliations":[{"id":41046,"text":"Canadian Wildlife Service, Environment and Climate Change Canada, Sackville, NB","active":true,"usgs":false}],"preferred":false,"id":824007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Savard, Jean-Pierre L.","contributorId":101776,"corporation":false,"usgs":false,"family":"Savard","given":"Jean-Pierre","email":"","middleInitial":"L.","affiliations":[{"id":6962,"text":"Science and Technology Branch, Environment Canada","active":true,"usgs":false}],"preferred":false,"id":824008,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Loring, Pamela H.","contributorId":266003,"corporation":false,"usgs":false,"family":"Loring","given":"Pamela","email":"","middleInitial":"H.","affiliations":[{"id":54854,"text":"Division of Migratory Birds, U.S. Fish and Wildlife Service, Charlestown, RI 02813, USA","active":true,"usgs":false}],"preferred":false,"id":824010,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McWilliams, Scott R.","contributorId":172328,"corporation":false,"usgs":false,"family":"McWilliams","given":"Scott","email":"","middleInitial":"R.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":824056,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Olsen, Glenn H. 0000-0002-7188-6203","orcid":"https://orcid.org/0000-0002-7188-6203","contributorId":238130,"corporation":false,"usgs":true,"family":"Olsen","given":"Glenn","email":"","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":824012,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Osenkowski, Jason E.","contributorId":225144,"corporation":false,"usgs":false,"family":"Osenkowski","given":"Jason","email":"","middleInitial":"E.","affiliations":[{"id":41047,"text":"Rhode Island Department of Environmental Management, West Kingston, RI","active":true,"usgs":false}],"preferred":false,"id":824011,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Paton, Peter W. C.","contributorId":146616,"corporation":false,"usgs":false,"family":"Paton","given":"Peter","email":"","middleInitial":"W. C.","affiliations":[{"id":6923,"text":"University of Rhode Island, Kingston, RI","active":true,"usgs":false}],"preferred":false,"id":824057,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Perry, Matthew 0000-0001-6452-9534 mperry@usgs.gov","orcid":"https://orcid.org/0000-0001-6452-9534","contributorId":179173,"corporation":false,"usgs":true,"family":"Perry","given":"Matthew","email":"mperry@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":824013,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bowman, Timothy D.","contributorId":80779,"corporation":false,"usgs":false,"family":"Bowman","given":"Timothy","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":824009,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70224585,"text":"70224585 - 2021 - Conservation of northwestern and southwestern pond turtles: Threats, population size estimates, and population viability analysis","interactions":[],"lastModifiedDate":"2021-12-10T17:00:00.435086","indexId":"70224585","displayToPublicDate":"2021-09-07T07:57:11","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Conservation of northwestern and southwestern pond turtles: Threats, population size estimates, and population viability analysis","docAbstract":"Accurate status assessments of long-lived, widely distributed taxa depend on the availability of long-term monitoring data from multiple populations. However, monitoring populations across large temporal and spatial scales is often beyond the scope of any one researcher or research group. Consequently, wildlife managers may be tasked with utilizing limited information from different sources to detect range-wide evidence of population declines and their causes. When assessments need to be made under such constraints, the research and management communities must determine how to extrapolate from variable population data to species-level inferences. Here, using three different approaches, we integrate and analyze data from the peer-reviewed literature and government agency reports to inform conservation for northwestern pond turtles (NPT) Actinemys marmorata and southwestern pond turtles (SPT) Actinemys pallida. Both NPT and SPT are long-lived freshwater turtles distributed along the west coast of the United States and Mexico. Conservation concerns exist for both species; however, SPT may face more severe threats and are thought to exist at lower densities throughout their range than NPT. For each species, we ranked the impacts of 13 potential threats, estimated population sizes, and modeled population viability with and without long-term droughts. Our results suggest that predation of hatchlings by invasive predators, such as American bullfrogs Lithobates catesbeianus and Largemouth Bass Micropterus salmoides, is a high-ranking threat for NPT and SPT. Southwestern pond turtles may also face more severe impacts associated with natural disasters (droughts, wildfires, and floods) than do NPT. Population size estimates from trapping surveys indicate that SPT have smaller population sizes on average than do NPT (P = 0.0003), suggesting they may be at greater risk of local extirpation. Population viability analysis models revealed that long-term droughts are a key environmental parameter; as the frequency of severe droughts increases with climate change, the likelihood of population recovery decreases, especially when census sizes are low. Given current population trends and vulnerability to natural disasters throughout their range, we suggest that conservation and recovery actions first focus on SPT to prevent further population declines.
The field of geospatial analytics and modeling has a long history coinciding with the physical and cultural evolution of humans. This history is analyzed relative to the four scientific paradigms: (1) empirical analysis through description, (2) theoretical explorations using models and generalizations, (3) simulating complex phenomena and (4) data exploration. Correlations among developments in general science and those of the geospatial sciences are explored. Trends identify areas ripe for growth and improvement in the fourth and current paradigm that has been spawned by the big data explosion, such as exposing the ‘black box’ of GeoAI training and generating big geospatial training datasets. Future research should focus on integrating both theory- and data-driven knowledge discovery.
From the shores of Jamestown and spreading north, south, and west, the lands that became the State of Virginia were some of the first in North America top experience rapid landscape change from European settlement. Imagery and data from the USGS Landsat series of satellites offer an unparalleled resource for the study, understanding, and preservation of Virginia’s land and water resources. From monitoring the health of water bodies to managing invasive species to planning for a range of climate change effects, the USGS National Land Imaging Program’s stewardship and public delivery of Landsat data have benefitted Virginians in myriad ways.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213050","usgsCitation":"U.S. Geological Survey, 2021, Virginia and Landsat (ver. 1.1, February 2023): U.S. Geological Survey Fact Sheet 2021–3050, 2 p., https://doi.org/10.3133/fs20213050.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-132606","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":413291,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20213050/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":413223,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2021/3050/images"},{"id":413220,"rank":4,"type":{"id":31,"text":"Publication 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U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
With the United Nations Decade on Ecosystem Restoration, restoration of damaged ecosystems is turning into a global movement. Restoration actions that are not based on science and an understanding of ecosystem function can thwart desired restoration outcomes at best and cause further damage to ecosystems at worst. Restoration often includes revegetation using seed. Where we source seed for restoration can make a difference for species establishment, restoration outcomes, and recovery of ecosystem function. However, sourcing seeds of native species, let alone genetically appropriate seed, is not currently possible for many restoration projects. The process of increasing and sourcing suitable seed for restoration includes many steps that need to be addressed typically years before a restoration project is initiated. These steps of seed collection, evaluation and development, field establishment, production, certification and procurement, storage, and finally restoration, need to be considered ideally at a scale larger than individual restoration projects and with research conducted in each step. We describe these steps as implemented in the United States, the challenges therein, and provide suggestions and examples of how groups can make efficient and effective progress toward getting the right seed in the right place at the right time.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.13499","usgsCitation":"Mccormick, M.L., Carr, A.N., Massatti, R., Winkler, D.E., De Angelis, P., and Olwell, P., 2021, How to increase the supply of native seed to improve restoration success: The US native seed development process: Restoration Ecology, v. 29, no. 8, e13499, 9 p., https://doi.org/10.1111/rec.13499.","productDescription":"e13499, 9 p.","ipdsId":"IP-129073","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":450919,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/rec.13499","text":"Publisher Index Page"},{"id":389146,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-09-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Mccormick, Molly Lutisha 0000-0002-4361-7567","orcid":"https://orcid.org/0000-0002-4361-7567","contributorId":265148,"corporation":false,"usgs":true,"family":"Mccormick","given":"Molly","email":"","middleInitial":"Lutisha","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":823085,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carr, Amanda N.","contributorId":265604,"corporation":false,"usgs":false,"family":"Carr","given":"Amanda","email":"","middleInitial":"N.","affiliations":[{"id":54729,"text":"Chicago Botanic Garden, Negaunee Institute for Plant Conservation Science and Action, 1000 Lake Cook Rd, Glencoe, IL 60022","active":true,"usgs":false}],"preferred":false,"id":823086,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Massatti, Robert 0000-0001-5854-5597","orcid":"https://orcid.org/0000-0001-5854-5597","contributorId":207294,"corporation":false,"usgs":true,"family":"Massatti","given":"Robert","email":"","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":823087,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Winkler, Daniel E. 0000-0003-4825-9073","orcid":"https://orcid.org/0000-0003-4825-9073","contributorId":206786,"corporation":false,"usgs":true,"family":"Winkler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":823088,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"De Angelis, Patricia","contributorId":265605,"corporation":false,"usgs":false,"family":"De Angelis","given":"Patricia","email":"","affiliations":[{"id":54730,"text":"U.S. Fish and Wildlife Service, International Affairs, Division of Scientific Authority, 5275 Leesburg Pike, Falls Church, VA 22041-3803","active":true,"usgs":false}],"preferred":false,"id":823089,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Olwell, Peggy","contributorId":213569,"corporation":false,"usgs":false,"family":"Olwell","given":"Peggy","email":"","affiliations":[{"id":38799,"text":"Bureau of Land Management, Washington DC","active":true,"usgs":false}],"preferred":false,"id":823090,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70223790,"text":"70223790 - 2021 - Contemporary and historic dynamics of lake whitefish (Coregonus clupeaformis) eggs, larvae, and juveniles suggest recruitment bottleneck during first growing season","interactions":[],"lastModifiedDate":"2021-09-08T12:51:05.717868","indexId":"70223790","displayToPublicDate":"2021-09-06T07:49:14","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9331,"text":"Annales Zoologici Finnici","active":true,"publicationSubtype":{"id":10}},"title":"Contemporary and historic dynamics of lake whitefish (Coregonus clupeaformis) eggs, larvae, and juveniles suggest recruitment bottleneck during first growing season","docAbstract":"To determine if a survival bottleneck occurs in Lake Erie's lake whitefish (Coregonus clupeaformis) population and explore possible mechanisms responsible, we examined contemporary and historical dynamics of lake whitefish eggs, larvae and juveniles. Widespread spawning and low overwinter egg retention were observed in 2016–2018, however subsequent larval CPUE remained consistent with historical observations when regular recruitment occurred. Highest larval CPUE was consistently observed in nearshore areas 3–11 km from mid-lake spawning locations. Fall age-1 juvenile presence was predicted by fall age-0 catches, indicating the bottleneck occurs during the first growing season. Our results suggest the following: (1) factors limiting recruitment affect survival during or after the pelagic larval stage to fall age-0, and (2) physical and biological processes underlying connectivity between spawning and nearshore nursery habitats may be limiting recruitment. Future research focusing on larval nursery habitat characterization and lake whitefish growth and survival may reveal mechanisms affecting recruitment.
About 14.5 months after the 2018 eruption and summit collapse of Kīlauea Volcano, Hawaiʻi, liquid water started accumulating in the deepened summit crater, forming a lake that attained 51 m depth before rapidly boiling off on December 20, 2020, when an eruption from the crater wall poured lava into the lake. Modeling the growth of the crater lake at Kīlauea summit is important for assessing the potential for explosive volcanism. Our current understanding of the past 2500 years of eruptive activity at Kīlauea suggests a slight dominance of explosive behavior over effusive. The deepened summit crater and presence of the crater lake in 2019 raised renewed concerns about explosive activity. Groundwater models using hydraulic-property data from a nearby drillhole successfully forecast the timing and rate of lake filling. Here we compare the groundwater-model predictions with observational data through the demise of the crater lake, examine the implications for local water-table configuration, consider the potential role of evaporation and recharge (neglected in previous models), and briefly discuss the energetics of the rapid boil-off. This post audit of groundwater-flow models of Kīlauea summit shows that simple models can sometimes be used effectively to simulate complex settings such as volcanoes.
Across portions of the western Great Plains in North America, natural fire has been removed from grassland ecosystems, decreasing vegetation heterogeneity and allowing woody encroachment. The loss of fire has implications for grassland species requiring diverse vegetation patches and structure or patches that have limited occurrence in the absence of fire. The lesser prairie-chicken (Tympanuchus pallidicinctus) is a declining species of prairie-grouse that requires heterogeneous grasslands throughout its life history and fire has been removed from much of its occupied range. Patch-burn grazing is a management strategy that re-establishes the fire-grazing interaction to a grassland system, increasing heterogeneity in vegetation structure and composition. We evaluated the effects of patch-burn grazing on lesser prairie-chicken space use, habitat features, and vegetation selection during a 4-year field study from 2014–2017. Female lesser prairie-chickens selected 1- and 2-year post-fire patches during the lekking season, ≥4-year post-fire patches during the nesting season, and year-of-fire and 1-year post-fire patches during post-nesting and nonbreeding seasons. Vegetation selection during the lekking season was not similar to available vegetation in selected patches, suggesting that lesser prairie-chickens cue in on other factors during the lekking season. During the nesting season, females selected nest sites with greater visual obstruction, which was available in ≥4-year post-fire patches; during the post-nesting season, females selected sites with 15–25% bare ground, which was available in the year-of-fire, 1-year post-fire, and 2-year post-fire patches; and during the nonbreeding season they selected sites with lower visual obstruction, available in the year-of-fire and 1-year post-fire patches. Because lesser prairie-chickens selected all available time-since-fire patches during their life history, patch-burn grazing may be a viable management tool to restore and maintain lesser prairie-chicken habitat on the landscape. © 2021 The Wildlife Society.