{"pageNumber":"240","pageRowStart":"5975","pageSize":"25","recordCount":40783,"records":[{"id":70218264,"text":"70218264 - 2021 - Field evaluation of a compact, polarizing topo‐bathymetric lidar across a range of river conditions","interactions":[],"lastModifiedDate":"2021-05-13T15:54:16.338045","indexId":"70218264","displayToPublicDate":"2021-01-27T07:12:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Field evaluation of a compact, polarizing topo‐bathymetric lidar across a range of river conditions","docAbstract":"

This paper summarizes field trials to evaluate the performance of a prototype compact topo‐bathymetric lidar sensor for surveying rivers. The sensor uses a novel polarization technique to distinguish between laser returns from the water surface and streambed and its size and weight permit deployment from a small unmanned aerial system (sUAS) or a boat. Field testing was designed to identify the range of operational conditions under which the sensor can provide accurate information on river depths. For accuracy assessment, conventional, field‐based depth measurements were collected by wading and sonar. Additionally, optical properties of the rivers were measured in situ. Wading and lidar bathymetry comparisons in relatively shallow channels yielded observed versus predicted (OP) regression R2 values ranging from 0.60 to 0.97. A comparison between sonar and lidar bathymetry in a deeper river resulted in an OP R2 of 0.72. Absorption and attenuation coefficients at the 532 nm wavelength of the lidar were recorded in the field and the highest values of these inherent optical properties were at sites with the highest turbidity and highest concentrations of colored dissolved organic matter, chlorophyll, and suspended sediment. At these sites, which included both sand and gravel/cobble beds, the point density of riverbed returns was not uniform, with areas of sparse coverage occurring primarily in deeper water. However, submerged objects and slopes could be resolved in the lidar point clouds.

","language":"English","publisher":"Wiley","doi":"10.1002/rra.3771","usgsCitation":"Kinzel, P.J., Legleiter, C.J., and Grams, P.E., 2021, Field evaluation of a compact, polarizing topo‐bathymetric lidar across a range of river conditions: River Research and Applications, v. 37, no. 4, p. 531-534, https://doi.org/10.1002/rra.3771.","productDescription":"3 p.","startPage":"531","endPage":"534","ipdsId":"IP-123278","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":453697,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.3771","text":"Publisher Index Page"},{"id":436543,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96K0QI4","text":"USGS data release","linkHelpText":"UAS-based remotely sensed data and field measurements from the Blue River and Colorado River, near Kremmling, Colorado, October 17-18, 2018"},{"id":436542,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O9ONXF","text":"USGS data release","linkHelpText":"Remotely sensed bathymetry and field measurements from the Colorado River near Lees Ferry, Arizona, September 23, 2019"},{"id":436541,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91TZXPZ","text":"USGS data release","linkHelpText":"UAS-based remotely sensed bathymetry and field measurements from the Colorado River, near Parshall Colorado, June 13, 2019"},{"id":383589,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado","otherGeospatial":"Lees Ferry, Kremmling, Parshall","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.64306640625,\n 36.81808022778526\n ],\n [\n -111.1376953125,\n 36.81808022778526\n ],\n [\n -111.1376953125,\n 37.081475648860525\n ],\n [\n -111.64306640625,\n 37.081475648860525\n ],\n [\n -111.64306640625,\n 36.81808022778526\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.52618408203125,\n 39.926588421909436\n ],\n [\n -106.08673095703125,\n 39.926588421909436\n ],\n [\n -106.08673095703125,\n 40.13899044275822\n ],\n [\n -106.52618408203125,\n 40.13899044275822\n ],\n [\n -106.52618408203125,\n 39.926588421909436\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-01-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810770,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":810771,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grams, Paul E. 0000-0002-0873-0708","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":216115,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":810772,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70217656,"text":"ofr20201151 - 2021 - Modeling Least Bell’s Vireo habitat suitability in current and historic ranges in California","interactions":[],"lastModifiedDate":"2021-01-27T12:54:14.460569","indexId":"ofr20201151","displayToPublicDate":"2021-01-26T15:54:25","publicationYear":"2021","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":"2020-1151","displayTitle":"Modeling Least Bell’s Vireo Habitat Suitability in Current and Historic Ranges in California","title":"Modeling Least Bell’s Vireo habitat suitability in current and historic ranges in California","docAbstract":"

We developed a habitat suitability model for the federally endangered Least Bell’s Vireo (Vireo bellii pusillus) across its current and historic range in California. The vireo disappeared from most of its range by the 1980s, remaining only in southern California and northern Baja California, Mexico. This decline was due to habitat loss and introduction of brood parasitic brown-headed cowbirds (Molothrus ater) into California in the late 1800s. Habitat protection and management since the mid-1980s increased southern California vireo populations with small numbers of birds recently expanding back into the historic range. The vireo habitat model will help meet the U.S. Fish and Wildlife Service recovery objectives by distinguishing specific areas to survey for new occurrences; characterizing important vireo-habitat relationships; and identifying areas for habitat management. We constructed models based on the vireo’s current range to predict suitable habitat in the historic range, which differs substantially in environmental conditions. We used the partitioned Mahalanobis D2 modeling technique designed to predict habitat suitability in areas not included in a sample of species locations and under novel conditions. We constructed alternative models with different combinations of environmental variables hypothesized to be important components of vireo habitat. We selected a set of best performing models to predict suitable habitat for a riparian vegetation grid buffered 500 meters across California. Most models for southern California did not predict suitable habitat in the historic range. The top performing model has an area under the curve value of 0.93. It is a simple model and discriminated among riparian habitats, with only 6 percent predicted as suitable. On average, suitable vireo habitat had more than 60-percent riparian vegetation and flat land at the 150-meter scale, little-to-no slope, and was within 130 meters of water.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201151","collaboration":"Wildlife Program","usgsCitation":"Preston, K.L., Kus, B.E., and Perkins, E., 2021, Modeling Least Bell’s Vireo habitat suitability in current and historic ranges in California: U.S. Geological Survey Open-File Report 2020–1151, 44 p., https://doi.org/10.3133/ofr20201151.","productDescription":"Report: vii, 44 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-123538","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":382648,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1151/coverthb.jpg"},{"id":382649,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1151/ofr20201151.pdf","text":"Report","size":"15.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1151"},{"id":382650,"rank":3,"type":{"id":30,"text":"Data 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\"}}]}","contact":"

Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819

","tableOfContents":"","publishedDate":"2021-01-26","noUsgsAuthors":false,"publicationDate":"2021-01-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Preston, Kristine L. 0000-0002-6958-1128 kpreston@usgs.gov","orcid":"https://orcid.org/0000-0002-6958-1128","contributorId":207765,"corporation":false,"usgs":true,"family":"Preston","given":"Kristine","email":"kpreston@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":809152,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kus, Barbara E. 0000-0002-3679-3044 barbara_kus@usgs.gov","orcid":"https://orcid.org/0000-0002-3679-3044","contributorId":3026,"corporation":false,"usgs":true,"family":"Kus","given":"Barbara E.","email":"barbara_kus@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":809153,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perkins, Emily 0000-0002-6286-3480 eperkins@usgs.gov","orcid":"https://orcid.org/0000-0002-6286-3480","contributorId":140442,"corporation":false,"usgs":true,"family":"Perkins","given":"Emily","email":"eperkins@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":809154,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70218175,"text":"70218175 - 2021 - Native American fire management at an ancient wildland–urban interface in the Southwest United States","interactions":[],"lastModifiedDate":"2021-02-15T15:43:28.004603","indexId":"70218175","displayToPublicDate":"2021-01-26T09:38:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Native American fire management at an ancient wildland–urban interface in the Southwest United States","docAbstract":"

The intersection of expanding human development and wildland landscapes—the “wildland–urban interface” or WUI—is one of the most vexing contexts for fire management because it involves complex interacting systems of people and nature. Here, we document the dynamism and stability of an ancient WUI that was apparently sustainable for more than 500 y. We combine ethnography, archaeology, paleoecology, and ecological modeling to infer intensive wood and fire use by Native American ancestors of Jemez Pueblo and the consequences on fire size, fire–climate relationships, and fire intensity. Initial settlement of northern New Mexico by Jemez farmers increased fire activity within an already dynamic landscape that experienced frequent fires. Wood harvesting for domestic fuel and architectural uses and abundant, small, patchy fires created a landscape that burned often but only rarely burned extensively. Depopulation of the forested landscape due to Spanish colonial impacts resulted in a rebound of fuels accompanied by the return of widely spreading, frequent surface fires. The sequence of more than 500 y of perennial small fires and wood collecting followed by frequent “free-range” wildland surface fires made the landscape resistant to extreme fire behavior, even when climate was conducive and surface fires were large. The ancient Jemez WUI offers an alternative model for fire management in modern WUI in the western United States, and possibly other settings where local management of woody fuels through use (domestic wood collecting) coupled with small prescribed fires may make these communities both self-reliant and more resilient to wildfire hazards.

","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2018733118","usgsCitation":"Roos, C., Swetnam, T.W., Ferguson, T.J., Liebmann, M.J., Loehman, R.A., Welch, J., Margolis, E.Q., Guiterman, C.H., Hockaday, W., Aiuvalasit, M., Battillo, J., Farella, J., and Kiahtipes, C., 2021, Native American fire management at an ancient wildland–urban interface in the Southwest United States: Proceedings of the National Academy of Sciences, v. 4, no. 118, e2018733118, 11 p., https://doi.org/10.1073/pnas.2018733118.","productDescription":"e2018733118, 11 p.","ipdsId":"IP-122927","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":453702,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2018733118","text":"Publisher Index Page"},{"id":383270,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.9404296875,\n 31.353636941500987\n ],\n [\n -108.19335937499999,\n 31.39115752282472\n ],\n [\n -108.10546875,\n 31.728167146023935\n ],\n [\n -102.919921875,\n 32.0639555946604\n ],\n [\n -103.02978515625,\n 37.16031654673677\n ],\n [\n -114.12597656249999,\n 37.125286284966805\n ],\n [\n -114.169921875,\n 35.94243575255426\n ],\n [\n -114.7412109375,\n 36.12012758978146\n ],\n [\n -114.41162109375,\n 34.470335121217474\n ],\n [\n -114.5654296875,\n 33.61461929233378\n ],\n [\n -114.58740234375,\n 33.119150226768866\n ],\n [\n -114.7412109375,\n 32.54681317351514\n ],\n [\n -111.15966796875,\n 31.372399104880525\n ],\n [\n -108.9404296875,\n 31.353636941500987\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","issue":"118","noUsgsAuthors":false,"publicationDate":"2021-01-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Roos, Christopher","contributorId":251699,"corporation":false,"usgs":false,"family":"Roos","given":"Christopher","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":810341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swetnam, Thomas W.","contributorId":191872,"corporation":false,"usgs":false,"family":"Swetnam","given":"Thomas","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":810342,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ferguson, T. J.","contributorId":251700,"corporation":false,"usgs":false,"family":"Ferguson","given":"T.","email":"","middleInitial":"J.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":810343,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Liebmann, Matthew J.","contributorId":179334,"corporation":false,"usgs":false,"family":"Liebmann","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":810344,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loehman, Rachel A. 0000-0001-7680-1865 rloehman@usgs.gov","orcid":"https://orcid.org/0000-0001-7680-1865","contributorId":187605,"corporation":false,"usgs":true,"family":"Loehman","given":"Rachel","email":"rloehman@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":false,"id":810345,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Welch, John","contributorId":251701,"corporation":false,"usgs":false,"family":"Welch","given":"John","email":"","affiliations":[{"id":36678,"text":"Simon Fraser University","active":true,"usgs":false}],"preferred":false,"id":810346,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Margolis, Ellis Q. 0000-0002-0595-9005 emargolis@usgs.gov","orcid":"https://orcid.org/0000-0002-0595-9005","contributorId":173538,"corporation":false,"usgs":true,"family":"Margolis","given":"Ellis","email":"emargolis@usgs.gov","middleInitial":"Q.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":810347,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Guiterman, Christopher H.","contributorId":190553,"corporation":false,"usgs":false,"family":"Guiterman","given":"Christopher","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":810348,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hockaday, William","contributorId":251702,"corporation":false,"usgs":false,"family":"Hockaday","given":"William","email":"","affiliations":[{"id":13716,"text":"Baylor University","active":true,"usgs":false}],"preferred":false,"id":810349,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Aiuvalasit, Michael","contributorId":251703,"corporation":false,"usgs":false,"family":"Aiuvalasit","given":"Michael","email":"","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":810350,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Battillo, Jenna","contributorId":251704,"corporation":false,"usgs":false,"family":"Battillo","given":"Jenna","email":"","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":810351,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Farella, Joshua","contributorId":179332,"corporation":false,"usgs":false,"family":"Farella","given":"Joshua","email":"","affiliations":[],"preferred":false,"id":810352,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Kiahtipes, Christopher","contributorId":251705,"corporation":false,"usgs":false,"family":"Kiahtipes","given":"Christopher","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":810353,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70218727,"text":"70218727 - 2021 - Vegetation monitoring optimization with normalized difference vegetation index and evapotranspiration using remote sensing measurements and land surface models over East Africa","interactions":[],"lastModifiedDate":"2021-03-09T13:46:15.225469","indexId":"70218727","displayToPublicDate":"2021-01-26T07:38:54","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7749,"text":"Frontiers in Climate","active":true,"publicationSubtype":{"id":10}},"title":"Vegetation monitoring optimization with normalized difference vegetation index and evapotranspiration using remote sensing measurements and land surface models over East Africa","docAbstract":"

The majority of people in East Africa rely on the agro-pastoral system for their livelihood, which is highly vulnerable to droughts and flooding. Agro-pastoral droughts are endemic to the region and are considered the main natural hazard that contributes to food insecurity. Drought begins with rainfall deficit, gradually leading to soil moisture deficit, higher land surface temperature, and finally impacts to vegetation growth. Therefore, monitoring vegetation conditions is essential in understanding the progression of drought, potential effects on food security, and providing early warning information needed for drought mitigation decisions. Because vegetation processes couple the land and atmosphere, monitoring of vegetation conditions requires consideration of both water provision and demand. While there is consensus in using either the Normalized Difference Vegetation Index (NDVI) or evapotranspiration (ET) for vegetation monitoring, a comprehensive assessment optimizing the use of both has not yet been done. Moreover, the evaluation methods for understanding the relationships between NDVI and ET for vegetation monitoring are also limited. Taking these gaps into account we have developed a framework to optimize vegetation monitoring using both NDVI and ET by identifying where they perform the best by using triple collocation and cross-correlation methods. We estimated the random error structure in Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI; ET from the Operational Simplified Surface Energy Balance (SSEBop) model; and ET from land surface models (LSMs). LSM ET and SSEBop ET have been found to be better indicators for vegetation monitoring during extreme drought events, while NDVI could provide better information on vegetation condition during wetter than normal conditions. The random error structures of these variables suggest that LSM ET is most likely to provide important information for vegetation monitoring over low and high ends of the vegetation fraction areas. Over moderate vegetative areas, any of these variables could provide important vegetation information for drought characterization and food security assessments. While this study provides a framework for optimizing vegetation monitoring for drought and food security assessments over East Africa, the framework can be adopted to optimize vegetation monitoring over any other drought and food insecure region of the world.

","language":"English","doi":"10.3389/fclim.2021.589981","usgsCitation":"Pervez, S., McNally, A., Arsenault, K., Budde, M., and Rowland, J., 2021, Vegetation monitoring optimization with normalized difference vegetation index and evapotranspiration using remote sensing measurements and land surface models over East Africa: Frontiers in Climate, v. 3, 589981, 15 p., https://doi.org/10.3389/fclim.2021.589981.","productDescription":"589981, 15 p.","ipdsId":"IP-120378","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":453711,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fclim.2021.589981","text":"Publisher Index Page"},{"id":384242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Burundi, Djibouti, Eritrea, Ethiopia, Kenya, Rwanda, Somalia, Somaliland, South Sudan, Sudan, Uganda, United Republic of Tanzania","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[41.58513,-1.68325],[40.88477,-2.08255],[40.63785,-2.49979],[40.26304,-2.57309],[40.12119,-3.27768],[39.80006,-3.68116],[39.60489,-4.34653],[39.20222,-4.67677],[38.74054,-5.90895],[38.79977,-6.47566],[39.44,-6.84],[39.47,-7.1],[39.19469,-7.7039],[39.25203,-8.00781],[39.18652,-8.48551],[39.53574,-9.11237],[39.9496,-10.0984],[40.31659,-10.3171],[39.521,-10.89688],[38.42756,-11.2852],[37.82764,-11.26879],[37.47129,-11.56876],[36.77515,-11.59454],[36.51408,-11.72094],[35.3124,-11.43915],[34.55999,-11.52002],[34.28,-10.16],[33.94084,-9.69367],[33.73972,-9.41715],[32.75938,-9.2306],[32.19186,-8.93036],[31.55635,-8.76205],[31.15775,-8.59458],[30.74,-8.34],[30.2,-7.08],[29.62,-6.52],[29.41999,-5.94],[29.51999,-5.41998],[29.34,-4.49998],[29.27638,-3.29391],[29.02493,-2.83926],[29.11748,-2.29221],[29.25483,-2.21511],[29.29189,-1.62006],[29.57947,-1.34131],[29.58784,-0.58741],[29.8195,-0.2053],[29.87578,0.59738],[30.08615,1.06231],[30.46851,1.58381],[30.85267,1.8494],[31.17415,2.20447],[30.77332,2.33989],[30.83385,3.50917],[29.95349,4.1737],[29.716,4.6008],[29.15908,4.38927],[28.69668,4.45508],[28.42899,4.28715],[27.97998,4.40841],[27.37423,5.23394],[27.21341,5.55095],[26.46591,5.94672],[26.21342,6.5466],[25.79665,6.97932],[25.12413,7.50009],[25.11493,7.8251],[24.56737,8.22919],[23.88698,8.61973],[23.80581,8.66632],[23.45901,8.95429],[23.39478,9.26507],[23.55725,9.68122],[23.5543,10.08926],[22.97754,10.71446],[22.86417,11.1424],[22.87622,11.38461],[22.50869,11.67936],[22.49762,12.26024],[22.28801,12.64605],[21.93681,12.58818],[22.03759,12.95546],[22.29658,13.37232],[22.18329,13.78648],[22.51202,14.09318],[22.30351,14.32682],[22.56795,14.94429],[23.02459,15.68072],[23.88689,15.61084],[23.83766,19.58047],[23.85,20],[25,20.00304],[25,22],[29.02,22],[32.9,22],[36.86623,22],[37.18872,21.01885],[36.96941,20.83744],[37.1147,19.80796],[37.48179,18.61409],[37.86276,18.36786],[38.41009,17.99831],[38.99062,16.84063],[39.26611,15.92272],[39.81429,15.43565],[41.17927,14.49108],[41.73495,13.92104],[42.27683,13.34399],[42.58958,13.00042],[43.08123,12.69964],[43.31785,12.39015],[43.28638,11.97493],[42.71587,11.73564],[43.1453,11.46204],[43.47066,11.27771],[43.66667,10.86417],[44.1178,10.44554],[44.61426,10.44221],[45.55694,10.69803],[46.6454,10.81655],[47.52566,11.12723],[48.0216,11.19306],[48.37878,11.37548],[48.94819976077792,11.410619368129069],[48.9482,11.41062],[49.26776,11.43033],[49.72862,11.5789],[50.25878,11.67957],[50.73202,12.0219],[51.1112,12.02464],[51.13387,11.74815],[51.04153,11.16651],[51.04531,10.6409],[50.83418,10.27972],[50.55239,9.19874],[50.07092,8.08173],[49.4527,6.80466],[48.59455,5.33911],[47.74079,4.2194],[46.56476,2.85529],[45.56399,2.04576],[44.06815,1.05283],[43.13597,0.2922],[42.04157,-0.91916],[41.81095,-1.44647],[41.58513,-1.68325]],[[33.96339,9.46429],[33.97498,8.68456],[33.96162,9.58358],[33.96339,9.46429]],[[46.948339803464556,7.996880071332679],[46.94834,7.99688],[47.78942,8.003],[46.948339803464556,7.996880071332679]],[[36.85509,4.44786],[38.12091,3.59861],[38.43697,3.58851],[38.12092,3.59861],[36.85509,4.44786]]]},\"properties\":{\"name\":\"Kenya\"}}]}","volume":"3","noUsgsAuthors":false,"publicationDate":"2021-01-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Pervez, Shahriar 0000-0003-3417-1871 shahriar.pervez.ctr@usgs.gov","orcid":"https://orcid.org/0000-0003-3417-1871","contributorId":174568,"corporation":false,"usgs":true,"family":"Pervez","given":"Shahriar","email":"shahriar.pervez.ctr@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":811541,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McNally, Amy","contributorId":254957,"corporation":false,"usgs":false,"family":"McNally","given":"Amy","affiliations":[{"id":48664,"text":"USAID","active":true,"usgs":false}],"preferred":false,"id":811542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arsenault, Kristi","contributorId":254958,"corporation":false,"usgs":false,"family":"Arsenault","given":"Kristi","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":811543,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Budde, Michael 0000-0002-9098-2751 mbudde@usgs.gov","orcid":"https://orcid.org/0000-0002-9098-2751","contributorId":166756,"corporation":false,"usgs":true,"family":"Budde","given":"Michael","email":"mbudde@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":811544,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rowland, James 0000-0003-4837-3511 rowland@usgs.gov","orcid":"https://orcid.org/0000-0003-4837-3511","contributorId":145846,"corporation":false,"usgs":true,"family":"Rowland","given":"James","email":"rowland@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":811545,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70218696,"text":"70218696 - 2021 - Paleoseismic trenching reveals late quaternary kinematics of the Leech River Fault: Implications for forearc strain accumulation in Northern Cascadia","interactions":[],"lastModifiedDate":"2021-04-08T15:06:15.66963","indexId":"70218696","displayToPublicDate":"2021-01-26T07:21:39","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Paleoseismic trenching reveals late quaternary kinematics of the Leech River Fault: Implications for forearc strain accumulation in Northern Cascadia","docAbstract":"

New paleoseismic trenching indicates late Quaternary oblique right‐lateral slip on the Leech River fault, southern Vancouver Island, Canada, and constrains permanent forearc deformation in northern Cascadia. A south‐to‐north reduction in northward Global Navigation Satellite System velocities and seismicity across the Olympic Mountains, Strait of Juan de Fuca (JDF), and the southern Strait of Georgia, has been used as evidence for permanent north–south crustal shortening via thrust faulting between a northward migrating southern forearc and rigid northern backstop in southwestern Canada. However, previous paleoseismic studies indicating late Quaternary oblique right‐lateral slip on west‐northwest‐striking forearc faults north of the Olympic Mountains and in the southern Strait of Georgia are more consistent with forearc deformation models that invoke oroclinal bending and(or) westward extrusion of the Olympic Mountains. To help evaluate strain further north across the Strait of JDF, we present the results from two new paleoseismic trenches excavated across the Leech River fault. In the easternmost Good Hope trench, we document a vertical fault zone and a broad anticline deforming glacial till. Comparison of till clast orientations in faulted and undeformed glacial till shows evidence for postdeposition faulted till clast rotation, indicating strike‐slip shear. The orientation of opening mode fissuring during surface rupture is consistent with right‐lateral slip and the published regional SHmax\">SHmaxSHmax directions. Vertical separation and the formation of scarp‐derived colluvium along one fault also indicate a dip‐slip component. Radiocarbon charcoal dating within offset glacial till and scarp‐derived colluvium suggest a single surface rupturing earthquake at 9.4±3.4  ka\">9.4±3.4  ka9.4±3.4  ka⁠. The oblique right‐lateral slip sense inferred in the Good Hope trench is consistent with slip kinematics observed on other regional west‐northwest‐striking faults and indicates that these structures do not accommodate significant north–south shortening via thrust faulting.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120200204","usgsCitation":"Harrichhausen, N., Morell, K.D., Regalla, C., Bennett, S.E., Leonard, L.J., Lynch, E.M., and Nissen, E., 2021, Paleoseismic trenching reveals late quaternary kinematics of the Leech River Fault: Implications for forearc strain accumulation in Northern Cascadia: Bulletin of the Seismological Society of America, v. 111, no. 2, p. 1110-1138, https://doi.org/10.1785/0120200204.","productDescription":"29 p.","startPage":"1110","endPage":"1138","ipdsId":"IP-119823","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":384060,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","state":"Washington","otherGeospatial":"Vancouver Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.82391357421874,\n 48.08725331988952\n ],\n [\n -122.54974365234374,\n 48.08725331988952\n ],\n [\n -122.54974365234374,\n 48.70908786918211\n ],\n [\n -124.82391357421874,\n 48.70908786918211\n ],\n [\n -124.82391357421874,\n 48.08725331988952\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"111","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-01-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Harrichhausen, Nicolas 0000-0001-8953-4292","orcid":"https://orcid.org/0000-0001-8953-4292","contributorId":254359,"corporation":false,"usgs":false,"family":"Harrichhausen","given":"Nicolas","email":"","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":811408,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morell, Kristin D. 0000-0001-8464-3553","orcid":"https://orcid.org/0000-0001-8464-3553","contributorId":254360,"corporation":false,"usgs":false,"family":"Morell","given":"Kristin","email":"","middleInitial":"D.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":811409,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Regalla, Christine 0000-0003-2975-8336","orcid":"https://orcid.org/0000-0003-2975-8336","contributorId":254361,"corporation":false,"usgs":false,"family":"Regalla","given":"Christine","email":"","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":811410,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bennett, Scott E.K. 0000-0002-9772-4122 sekbennett@usgs.gov","orcid":"https://orcid.org/0000-0002-9772-4122","contributorId":5340,"corporation":false,"usgs":true,"family":"Bennett","given":"Scott","email":"sekbennett@usgs.gov","middleInitial":"E.K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":811411,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Leonard, Lucinda J. 0000-0002-6492-7660","orcid":"https://orcid.org/0000-0002-6492-7660","contributorId":254362,"corporation":false,"usgs":false,"family":"Leonard","given":"Lucinda","email":"","middleInitial":"J.","affiliations":[{"id":16829,"text":"University of Victoria","active":true,"usgs":false}],"preferred":false,"id":811412,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lynch, Emerson M. 0000-0003-1419-1373","orcid":"https://orcid.org/0000-0003-1419-1373","contributorId":254363,"corporation":false,"usgs":false,"family":"Lynch","given":"Emerson","email":"","middleInitial":"M.","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":811413,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nissen, Edwin 0000-0002-0406-2706","orcid":"https://orcid.org/0000-0002-0406-2706","contributorId":244221,"corporation":false,"usgs":false,"family":"Nissen","given":"Edwin","email":"","affiliations":[{"id":48865,"text":"University of Victoria; Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":811414,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70221891,"text":"70221891 - 2021 - Extending the capture map concept to estimate discrete and risk-based streamflow depletion potential","interactions":[],"lastModifiedDate":"2021-07-13T18:46:07.15415","indexId":"70221891","displayToPublicDate":"2021-01-25T13:44:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Extending the capture map concept to estimate discrete and risk-based streamflow depletion potential","docAbstract":"

A popular and contemporary use of numerical groundwater models is to estimate the discrete relation between groundwater extraction and surface-water/groundwater exchange. Previously, the concept of a “capture map” has been put forward as a means to effectively summarize this relation for decision-making consumption. While capture maps have enjoyed success in the environmental simulation industry, they are deterministic, ignoring uncertainty in the underlying model. Furthermore, capture maps are not typically calculated in a manner that facilitates analysis of varying combinations of extraction locations and/or reaches. That is, they are typically constructed with focus on a single reach or group of reaches. The former of these limitations is important for conveying risk to decision makers and stakeholders, while the latter is important for decision-making support related to surface-water management, where future foci may include reaches that were not the focus of the original capture analysis. Herein, we use the concept of a response matrix to generalize the theory of the capture-map approach to estimate spatially discrete streamflow depletion potential. We also use first-order, second-moment uncertainty estimation techniques with the concept of “risk shifting” to place capture maps and streamflow depletion potential in a stochastic, risk-based framework. Our approach is demonstrated for an integrated groundwater/surface-water model of the lower San Antonio River, Texas, USA.

","language":"English","publisher":"Wiley","doi":"10.1111/gwat.13080","usgsCitation":"White, J.T., Foster, L.K., and Fienen, M., 2021, Extending the capture map concept to estimate discrete and risk-based streamflow depletion potential: Groundwater, v. 59, no. 4, p. 571-580, https://doi.org/10.1111/gwat.13080.","productDescription":"10 p.","startPage":"571","endPage":"580","ipdsId":"IP-120491","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":436548,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AB2MIL","text":"USGS data release","linkHelpText":"MODFLOW-NWT model for extending the capture map concept to estimate discrete and risk-based streamflow depletion potential"},{"id":387161,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-03-10","publicationStatus":"PW","contributors":{"authors":[{"text":"White, Jeremy T. 0000-0002-4950-1469 jwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-4950-1469","contributorId":167708,"corporation":false,"usgs":true,"family":"White","given":"Jeremy","email":"jwhite@usgs.gov","middleInitial":"T.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819223,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foster, Linzy K. 0000-0002-7373-7017","orcid":"https://orcid.org/0000-0002-7373-7017","contributorId":259186,"corporation":false,"usgs":true,"family":"Foster","given":"Linzy","email":"","middleInitial":"K.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819224,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819225,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70247394,"text":"70247394 - 2021 - Constraints on the geometry of the subducted Gorda Plate with converted phases generated by local earthquakes","interactions":[],"lastModifiedDate":"2023-08-02T14:59:28.02689","indexId":"70247394","displayToPublicDate":"2021-01-25T09:54:44","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7501,"text":"JGR Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Constraints on the geometry of the subducted Gorda Plate with converted phases generated by local earthquakes","docAbstract":"

The largest slip in great megathrust earthquakes often occurs in the 10–30 km depth range, yet seismic imaging of the material properties in this region has proven difficult. We utilize a dense onshore-offshore passive seismic dataset from the southernmost Cascadia subduction zone where seismicity in the mantle of the subducted Gorda Plate produces S-to-P and P-to-S conversions generated within a few km of the plate interface. These conversions typically occur in the 10–20 km depth range at either the top or bottom of a ∼5 km thick layer with a high Vp/Vs that we infer to be primarily the subducted crust. We use their arrival times and amplitudes to infer the location of the top and bottom of the subducted crust as well as the velocity contrasts across these discontinuities. Comparing with both the Slab1.0 and the updated Slab2 interface models, the Slab2 model is generally consistent with the converted phases, while the Slab1.0 model is 1–2 km deeper in the 2–20 km depth range and ∼6–8 km too deep in the 10–20 km depth range between 40.25°N and 40.4°N. Comparing the amplitudes of the converted phases to synthetics for simplified velocity structures, the amplitude of the converted phases requires models containing a ∼5 km thick zone with at least a ∼10%–20% reduction in S wave velocity. Thus, the plate boundary is likely contained within or at the top of this low velocity zone, which potentially indicates a significant porosity and fluid content within the seismogenic zone.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB019962","usgsCitation":"Gong, J., and McGuire, J., 2021, Constraints on the geometry of the subducted Gorda Plate with converted phases generated by local earthquakes: JGR Solid Earth, v. 126, no. 2, e2020JB019962, 23 p., https://doi.org/10.1029/2020JB019962.","productDescription":"e2020JB019962, 23 p.","ipdsId":"IP-114309","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":453718,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2020jb019962","text":"External Repository"},{"id":419501,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Gorda Plate","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -125.5,\n 41\n ],\n [\n -125.5,\n 40\n ],\n [\n -124,\n 40\n ],\n [\n -124,\n 41\n ],\n [\n -125.5,\n 41\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"126","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-02-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Gong, Jianhua","contributorId":317847,"corporation":false,"usgs":false,"family":"Gong","given":"Jianhua","email":"","affiliations":[{"id":34004,"text":"Scripps Institute of Oceanography","active":true,"usgs":false}],"preferred":false,"id":879445,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, Jeffrey J. 0000-0001-9235-2166","orcid":"https://orcid.org/0000-0001-9235-2166","contributorId":219786,"corporation":false,"usgs":true,"family":"McGuire","given":"Jeffrey J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":879446,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70217636,"text":"70217636 - 2021 - Human activities and weather drive contact rates of wintering elk","interactions":[],"lastModifiedDate":"2021-03-05T21:27:54.234412","indexId":"70217636","displayToPublicDate":"2021-01-25T07:08:25","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":"Human activities and weather drive contact rates of wintering elk","docAbstract":"
  1. Wildlife aggregation patterns can influence disease transmission. However, limited research evaluates the influence of anthropogenic and natural factors on aggregation. Many managers would like to reduce wildlife contact rates, driven by aggregation, to limit disease transmission. We develop a novel analytical framework to quantify how management activities such as supplemental feeding and hunting versus weather drive contact rates while accounting for correlated contacts. We apply the framework to the National Elk Refuge (NER), Wyoming, USA, where the probable arrival of chronic wasting disease (CWD) has magnified concerns.
  2. We used a daily proximity index to measure contact rates among 68 global positioning system collared elk from 2016 to 2019. We modelled contact rates as a function of abiotic weather‐related effects, anthropogenic effects and aggregation from the prior day. The winter of 2017–2018 had greater natural forage availability and little snow, which led to a rare non‐feeding year on the NER and provided a unique opportunity to evaluate the effect of feeding on contact rates relative to other conditions.
  3. Supplemental feeding was the strongest predictor of aggregation, and contact rates were 2.6 times larger while feeding occurred compared to the baseline rate (0.34 and 0.13, respectively). Snow‐covered area was the second strongest predictor of contact rates highlighting the importance of abiotic factors to elk aggregation, but this effect had half the strength of feeding. These results are the first to show, even in animals that congregate naturally, how greatly supplemental feeding amplifies aggregation. Contact rates were also 23% lower during times when elk hunting was active (0.10) compared to the baseline.
  4. Synthesis and applications. Supplemental feeding increased contacts between elk well above the natural effects of weather, even after accounting for correlated movement expected in wintering ungulates. Similarly, differences in hunting season timing with adjacent areas led to an increase in contacts, suggesting an additional management option for reducing aggregation. The analytical framework presented supports the evaluation of temporally varying management actions that influence aggregation broadly and can be easily implemented whether the interest in changing aggregation is related to reduction of disease transmission, human–wildlife conflict or inter‐species competition.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.13818","usgsCitation":"Janousek, W.M., Graves, T., Berman, E., Chong, G.W., Cole, E.K., Dewey, S., Johnston, A.N., and Cross, P., 2021, Human activities and weather drive contact rates of wintering elk: Journal of Applied Ecology, v. 58, no. 3, p. 667-676, https://doi.org/10.1111/1365-2664.13818.","productDescription":"10 p.","startPage":"667","endPage":"676","ipdsId":"IP-117805","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":453726,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.13818","text":"Publisher Index Page"},{"id":436549,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QF62CQ","text":"USGS data release","linkHelpText":"Daily 30-m fractional snow covered area and summary stats for the National Elk Refuge, Wyoming from 2015 to 2020"},{"id":382579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"National Elk Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.78956604003905,\n 43.483815720045435\n ],\n [\n -110.54374694824219,\n 43.483815720045435\n ],\n [\n -110.54374694824219,\n 43.64054754952543\n ],\n [\n -110.78956604003905,\n 43.64054754952543\n ],\n [\n -110.78956604003905,\n 43.483815720045435\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"58","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-01-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Janousek, William Michael 0000-0003-3978-1775","orcid":"https://orcid.org/0000-0003-3978-1775","contributorId":237980,"corporation":false,"usgs":true,"family":"Janousek","given":"William","email":"","middleInitial":"Michael","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":809051,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":809050,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berman, Ethan 0000-0001-6112-6211","orcid":"https://orcid.org/0000-0001-6112-6211","contributorId":248405,"corporation":false,"usgs":false,"family":"Berman","given":"Ethan","affiliations":[],"preferred":false,"id":809052,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chong, Geneva W. 0000-0003-3883-5153 geneva_chong@usgs.gov","orcid":"https://orcid.org/0000-0003-3883-5153","contributorId":419,"corporation":false,"usgs":true,"family":"Chong","given":"Geneva","email":"geneva_chong@usgs.gov","middleInitial":"W.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":809053,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cole, Eric K 0000-0002-2229-5853","orcid":"https://orcid.org/0000-0002-2229-5853","contributorId":248406,"corporation":false,"usgs":false,"family":"Cole","given":"Eric","email":"","middleInitial":"K","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":809054,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dewey, Sarah","contributorId":145757,"corporation":false,"usgs":false,"family":"Dewey","given":"Sarah","affiliations":[{"id":16229,"text":"National Park Service, Grand Teton National Park, PO Drawer 170, Moose, WY 83012 USA","active":true,"usgs":false}],"preferred":false,"id":809055,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnston, Aaron N. 0000-0003-4659-0504","orcid":"https://orcid.org/0000-0003-4659-0504","contributorId":201768,"corporation":false,"usgs":true,"family":"Johnston","given":"Aaron","email":"","middleInitial":"N.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":809056,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cross, Paul C. 0000-0001-8045-5213","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":204814,"corporation":false,"usgs":true,"family":"Cross","given":"Paul C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":809057,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70224619,"text":"70224619 - 2021 - A reporting format for leaf-level gas exchange data and metadata","interactions":[],"lastModifiedDate":"2021-09-30T13:30:08.09724","indexId":"70224619","displayToPublicDate":"2021-01-24T08:15:20","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1457,"text":"Ecological Informatics","active":true,"publicationSubtype":{"id":10}},"title":"A reporting format for leaf-level gas exchange data and metadata","docAbstract":"

Leaf-level gas exchange data support the mechanistic understanding of plant fluxes of carbon and water. These fluxes inform our understanding of ecosystem function, are an important constraint on parameterization of terrestrial biosphere models, are necessary to understand the response of plants to global environmental change, and are integral to efforts to improve crop production. Collection of these data using gas analyzers can be both technically challenging and time consuming, and individual studies generally focus on a small range of species, restricted time periods, or limited geographic regions. The high value of these data is exemplified by the many publications that reuse and synthesize gas exchange data, however the lack of metadata and data reporting conventions make full and efficient use of these data difficult. Here we propose a reporting format for leaf-level gas exchange data and metadata to provide guidance to data contributors on how to store data in repositories to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets. For data users, the reporting format will better allow data repositories to optimize data search and extraction, and more readily integrate similar data into harmonized synthesis products. The reporting format specifies data table variable naming and unit conventions, as well as metadata characterizing experimental conditions and protocols. For common data types that were the focus of this initial version of the reporting format, i.e., survey measurements, dark respiration, carbon dioxide and light response curves, and parameters derived from those measurements, we took a further step of defining required additional data and metadata that would maximize the potential reuse of those data types. To aid data contributors and the development of data ingest tools by data repositories we provided a translation table comparing the outputs of common gas exchange instruments. Extensive consultation with data collectors, data users, instrument manufacturers, and data scientists was undertaken in order to ensure that the reporting format met community needs. The reporting format presented here is intended to form a foundation for future development that will incorporate additional data types and variables as gas exchange systems and measurement approaches advance in the future. The reporting format is published in the U.S. Department of Energy's ESS-DIVE data repository, with documentation and future development efforts being maintained in a version control system.

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The sea and land change elevation spatially and temporally from a multitude of processes, so it is necessary to constrain the movement of both to evaluate how coastlines will evolve and how those evolving coastlines will impact the natural and built environment over time. We combine land movement observations from global navigation satellite systems (GNSSs), leveling of geodetic monuments, and tide gauge records with a tectonic model of the Cascadia subduction zone to constrain absolute rates of vertical land movement in coastal Washington. We infer rates of vertical land movement in areas lacking direct observations by interpolating high-quality land movement observations and a discretely sampled interseismic locking model. Here we present a model of absolute vertical land movement that is combined with sea level rise estimates to inform local relative sea level projections on a community-scale. The most rapid vertical uplift (~3.5 mm/year) of the land is found across the northwest Olympic Peninsula, which currently outpaces sea level rise. Conversely, some areas, including a stretch of the northern Pacific Ocean coast from La Push to Kalaloch and the southern Puget Sound, are found to be subsiding at 0.5–1.0 mm/year, exacerbating the rate of relative sea level rise and thereby increasing the vulnerability of coastal communities.

","language":"English","publisher":"MDPI","doi":"10.3390/w13030281","usgsCitation":"Newton, T., Weldon, R.J., Miller, I.M., Schmidt, D., Morgan, H., Mauger, G.S., and Grossman, E., 2021, An assessment of vertical land movement to support coastal hazards planning in Washington state: Water (MDPI), v. 13, no. 3, 18 p., https://doi.org/10.3390/w13030281.","productDescription":"18 p.","ipdsId":"IP-124927","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":453737,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w13030281","text":"Publisher Index Page"},{"id":383609,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Seattle area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.26660156249999,\n 48.980216985374994\n ],\n [\n -123.24462890625,\n 48.268569112964336\n ],\n [\n -124.73876953125,\n 48.50204750525715\n ],\n [\n -124.892578125,\n 46.875213396722685\n ],\n [\n -122.9150390625,\n 46.76996843356982\n ],\n [\n -121.06933593749999,\n 47.17477833929903\n ],\n [\n -121.17919921875001,\n 48.705462895790546\n ],\n [\n -121.1572265625,\n 49.05227025601607\n ],\n [\n -123.26660156249999,\n 48.980216985374994\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-01-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Newton, Tyler","contributorId":252548,"corporation":false,"usgs":false,"family":"Newton","given":"Tyler","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":810903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weldon, Ray J.","contributorId":175463,"corporation":false,"usgs":false,"family":"Weldon","given":"Ray","email":"","middleInitial":"J.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":810910,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Ian M. 0000-0002-3289-6337","orcid":"https://orcid.org/0000-0002-3289-6337","contributorId":41951,"corporation":false,"usgs":false,"family":"Miller","given":"Ian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":810911,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmidt, David","contributorId":7596,"corporation":false,"usgs":true,"family":"Schmidt","given":"David","affiliations":[],"preferred":false,"id":810912,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morgan, Harriet","contributorId":252550,"corporation":false,"usgs":false,"family":"Morgan","given":"Harriet","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":810913,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grossman, Eric 0000-0003-3911-995X egrossman@usgs.gov","orcid":"https://orcid.org/0000-0003-3911-995X","contributorId":252549,"corporation":false,"usgs":true,"family":"Grossman","given":"Eric","email":"egrossman@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":810904,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mauger, Guillaume S.","contributorId":138608,"corporation":false,"usgs":false,"family":"Mauger","given":"Guillaume","email":"","middleInitial":"S.","affiliations":[{"id":12463,"text":"Climate Impacts Group, College of the Environment, University of Washington","active":true,"usgs":false}],"preferred":false,"id":810914,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70217708,"text":"70217708 - 2021 - In vitro effects-based method and water quality screening model for use in pre- and post-distribution treated waters","interactions":[],"lastModifiedDate":"2021-02-17T22:08:26.656546","indexId":"70217708","displayToPublicDate":"2021-01-23T07:19:33","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"In vitro effects-based method and water quality screening model for use in pre- and post-distribution treated waters","docAbstract":"

Recent urban public water supply contamination events emphasize the importance of screening treated drinking water quality after distribution. In vitro bioassays, when run concurrently with analytical chemistry methods, are effective tools to evaluating the efficacy of water treatment processes and water quality. We tested 49 water samples representing the Chicago Department of Water Management service areas for estrogen, (anti)androgen, glucocorticoid receptor-activating contaminants and cytotoxicity. We present a tiered screening approach suitable to samples with anticipated low-level activity and initially tested all extracts for statistically identifiable endocrine activity; performing a secondary dilution-response analysis to determine sample EC50 and biological equivalency values (BioEq). Estrogenic activity was detected in untreated Lake Michigan intake water samples using mammalian (5/49; median: 0.21 ng E2Eq/L) and yeast cell (5/49; 1.78 ng E2Eq/L) bioassays. A highly sensitive (anti)androgenic activity bioassay was applied for the first time to water quality screening and androgenic activity was detected in untreated intake and treated pre-distribution samples (4/49; 0.93 ng DHTEq/L). No activity was identified above method detection limits in the yeast androgenic, mammalian anti-androgenic, and both glucocorticoid bioassays. Known estrogen receptor agonists were detected using HPLC/MS-MS (estrone: 0.72-1.4 ng/L; 17α-estradiol: 1.3-1.5 ng/L; 17β-estradiol: 1.4 ng/L; equol: 8.8 ng/L), however occurrence did not correlate with estrogenic bioassay results. Many studies have applied bioassays to water quality monitoring using only relatively small samples sets often collected from surface and/or wastewater effluent. However, to realistically adapt these tools to treated water quality monitoring, water quality managers must have the capacity to screen potentially hundreds of samples in short timeframes. Therefore, we provided a tiered screening model that increased sample screening speed, without sacrificing statistical stringency, and detected estrogenic and androgenic activity only in pre-distribution Chicago area samples.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.144750","usgsCitation":"Medlock-Kakaley, E., Cardon, M.C., Evans, N., Iwanowicz, L., Allen, J.M., Wagner, E., Bokenkamp, K., Richardson, S.D., Plewa, M.J., Bradley, P., Romanok, K., Kolpin, D., Conley, J.M., Gray, L.E., Hartig, P.C., and Wilson, V.S., 2021, In vitro effects-based method and water quality screening model for use in pre- and post-distribution treated waters: Science of the Total Environment, v. 768, 144750, 10 p., https://doi.org/10.1016/j.scitotenv.2020.144750.","productDescription":"144750, 10 p.","ipdsId":"IP-117278","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science 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Aim

Populations of cold‐adapted species at the trailing edges of geographic ranges are particularly vulnerable to the negative effects of climate change from the combination of exposure to warm temperatures and high sensitivity to heat. Many of these species are predicted to decline under future climate scenarios, but they could persist if they can adapt to warming climates either physiologically or behaviourally. We aim to understand local variation in contemporary habitat use and use this information to identify signs of adaptive capacity. We focus on moose (Alces alces), a charismatic species of conservation and public interest.

Location

The northeastern United States, along the trailing edge of the moose geographic range in North America.

Methods

We compiled data on occurrences and habitat use of moose from remote cameras and GPS collars across the northeastern United States. We use these data to build habitat suitability models at local and regional spatial scales and then to predict future habitat suitability under climate change. We also use fine‐scale GPS data to model relationships between habitat use and temperature on a daily temporal scale and to predict future habitat use.

Results

We find that habitat suitability for moose will decline under a range of climate change scenarios. However, moose across the region differ in their use of climatic and habitat space, indicating that they could exhibit adaptive capacity. We also find evidence for behavioural responses to weather, where moose increase their use of forested wetland habitats in warmer places and/or times.

Main conclusionsOur results suggest that there will be significant shifts in moose distribution due to climate change. However, if there is spatial variation in thermal tolerance, trailing‐edge populations could adapt to climate change. We highlight that prioritizing certain habitats for conservation (i.e., thermal refuges) could be crucial for this adaptation.

","language":"English","publisher":"Wiley","doi":"10.1111/ddi.13223","usgsCitation":"Teitelbaum, C.S., Siren, A., Coffel, E., Foster, J., Frair, J.L., Hinton, J.W., Horton, R.W., Kramer, D.W., Lesk, C., Raymond, C., Wattles, D., Zeller, K., and Morelli, T.L., 2021, Habitat use as indicator of adaptive capacity to climate change: Diversity and Distributions, v. 27, no. 4, p. 655-667, https://doi.org/10.1111/ddi.13223.","productDescription":"13 p.","startPage":"655","endPage":"667","ipdsId":"IP-122889","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":453743,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.13223","text":"Publisher Index Page"},{"id":384405,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York, Vermont, New Hampshire, Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.498046875,\n 42.682435398386204\n ],\n [\n -70.7080078125,\n 42.682435398386204\n ],\n [\n -70.7080078125,\n 44.902577996288876\n ],\n [\n -75.498046875,\n 44.902577996288876\n ],\n [\n -75.498046875,\n 42.682435398386204\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-01-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Teitelbaum, Claire S. 0000-0001-5646-3184","orcid":"https://orcid.org/0000-0001-5646-3184","contributorId":255382,"corporation":false,"usgs":false,"family":"Teitelbaum","given":"Claire","email":"","middleInitial":"S.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":812277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siren, Alexej P. K.","contributorId":236810,"corporation":false,"usgs":false,"family":"Siren","given":"Alexej P. 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Remote sensing satellite Earth Observing Systems (EOS) provide a variety of products for monitoring Earth surface processes at varying spatial and spectral resolutions. Combining information from high and medium spatial resolution images is valuable for monitoring ground cover and vegetation status in cropland, grassland, forests, and other natural settings. However, coupling information from different EOS requires compensating for atmospheric and view angle effects before integrating comparable surface reflectance (SR) values. The objectives of this study were i) to assess how different atmospheric constituents affect the atmospheric correction results in Sentinel-2 and WorldView-3 imagery, ii) to establish a relationship with field spectra measurements, and iii) to develop an empirical approach to ensure that SR values extracted from different EOS can be normalized for use in monitoring vegetation and land cover status. We compared surface reflectance values derived from Sentinel-2 images corrected with Sen2Cor, MODTRAN or FLAASH atmospheric correction approaches for the visible-to-near infrared regions. Additionally, this information was compared to SR values extracted from WorldView-3 imagery acquired from the same dates and location (Central Spain) and corrected with MODTRAN and FLAASH approaches. Assessment of the atmospheric correction was conducted by comparing satellite image SR with ground-truth spectra acquired with a FieldSpec hand-held spectroradiometer. The results emphasized the importance of using common atmospheric parameters collected from ancillary data sources (i.e. MODIS Atmosphere & Land products) to ensure a reliable SR comparison. When compared to field-collected spectral data, SR from corrected Sentinel-2 push-broom imagery showed a reliable match (<4% difference in the visible bands and <0.52% difference in the near infrared bands). However, SR imagery from the pointable WorldView-3 instrument showed significant deviation, likely resulting from the effects of steep off-nadir acquisition angles (24.6° to 39.1°) combined with surface anisotropy. The magnitude and sign of the deviation in SR differed depending on the vegetation type, wavelength and sun-surface-sensor geometry. Therefore, it was necessary to account for angular effects to ensure reliable comparisons of imagery from the different EOS. In this study, an empirical angular correction approach was developed based on calibrating each WorldView-3 band against the ground-truth spectra. This correction allowed for the accurate signal normalization of WorldView-3 and Sentinel-2 imagery SR in the visible-to-near infrared regions.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.isprsjprs.2021.01.009","usgsCitation":"Pancorbo, J., Lamb, B.T., Quemada, M., Hively, W.D., Gonzalez-Fernandez, I., and Molina, I., 2021, Sentinel-2 and WorldView-3 atmospheric correction and signal normalization based on ground-truth spectroradiometric measurements: ISPRS Journal of Photogrammetry and Remote Sensing, v. 173, p. 166-180, https://doi.org/10.1016/j.isprsjprs.2021.01.009.","productDescription":"15 p.","startPage":"166","endPage":"180","ipdsId":"IP-119231","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":382917,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Spain","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-9.03482,41.88057],[-8.98443,42.59278],[-9.39288,43.02662],[-7.97819,43.74834],[-6.75449,43.56791],[-5.41189,43.57424],[-4.34784,43.40345],[-3.51753,43.4559],[-1.90135,43.4228],[-1.50277,43.03401],[0.33805,42.57955],[0.70159,42.79573],[1.82679,42.34338],[2.986,42.47302],[3.03948,41.89212],[2.09184,41.22609],[0.81052,41.01473],[0.72133,40.67832],[0.10669,40.12393],[-0.27871,39.30998],[0.11129,38.73851],[-0.46712,38.29237],[-0.68339,37.64235],[-1.43838,37.44306],[-2.14645,36.67414],[-3.41578,36.6589],[-4.3689,36.67784],[-4.99522,36.32471],[-5.37716,35.94685],[-5.86643,36.02982],[-6.23669,36.36768],[-6.52019,36.94291],[-7.45373,37.09779],[-7.53711,37.4289],[-7.16651,37.80389],[-7.02928,38.07576],[-7.37409,38.37306],[-7.09804,39.03007],[-7.49863,39.62957],[-7.06659,39.71189],[-7.02641,40.18452],[-6.86402,40.33087],[-6.85113,41.11108],[-6.38909,41.38182],[-6.66861,41.88339],[-7.25131,41.91835],[-7.42251,41.79207],[-8.01317,41.79089],[-8.26386,42.28047],[-8.67195,42.13469],[-9.03482,41.88057]]]},\"properties\":{\"name\":\"Spain\"}}]}","volume":"173","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pancorbo, J.L.","contributorId":248756,"corporation":false,"usgs":false,"family":"Pancorbo","given":"J.L.","email":"","affiliations":[{"id":50014,"text":"Universidad Politécnica de Madrid, CEIGRAM","active":true,"usgs":false}],"preferred":false,"id":809791,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lamb, Brian T.","contributorId":211092,"corporation":false,"usgs":false,"family":"Lamb","given":"Brian","email":"","middleInitial":"T.","affiliations":[{"id":38178,"text":"City College of New York","active":true,"usgs":false}],"preferred":false,"id":809792,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Quemada, Miguel","contributorId":211094,"corporation":false,"usgs":false,"family":"Quemada","given":"Miguel","email":"","affiliations":[{"id":38180,"text":"School of Agricultural Engineering and CEIGRAM, Technical University of Madrid","active":true,"usgs":false}],"preferred":false,"id":809793,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hively, W. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":210993,"corporation":false,"usgs":true,"family":"Hively","given":"W.","email":"","middleInitial":"Dean","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":809794,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gonzalez-Fernandez, I.","contributorId":248757,"corporation":false,"usgs":false,"family":"Gonzalez-Fernandez","given":"I.","email":"","affiliations":[{"id":50017,"text":"Ecotoxicology of Air Pollution, CIEMAT","active":true,"usgs":false}],"preferred":false,"id":809795,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Molina, Inigo","contributorId":248758,"corporation":false,"usgs":false,"family":"Molina","given":"Inigo","email":"","affiliations":[{"id":50014,"text":"Universidad Politécnica de Madrid, CEIGRAM","active":true,"usgs":false}],"preferred":false,"id":809796,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70228526,"text":"70228526 - 2021 - Could ecological release buffer suppression efforts for non-native lake trout (Salvelinus namaycush) in Yellowstone Lake, Yellowstone National Park?","interactions":[],"lastModifiedDate":"2022-02-14T19:18:25.968825","indexId":"70228526","displayToPublicDate":"2021-01-22T12:59:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Could ecological release buffer suppression efforts for non-native lake trout (,I>Salvelinus namaycush in Yellowstone Lake, Yellowstone National Park?","title":"Could ecological release buffer suppression efforts for non-native lake trout (Salvelinus namaycush) in Yellowstone Lake, Yellowstone National Park?","docAbstract":"

Yellowstone Lake in Yellowstone National Park, USA, has the longest ongoing suppression program for non-native lake trout (Salvelinus namaycush) in the western USA. Harvest data from the suppression program, along with data from an assessment program initiated in 2011, was used to estimate lake trout abundance and mortality rates. Abundance and biomass estimates were used to estimate stock–recruitment dynamics, which were inputs to a simulation model forecasting responses to continued suppression. Abundance increased during 1998–2012 when total annual mortality exceeded 0.59 and declined thereafter. The fishing mortality rate required to reduce abundance was 67% greater than predicted by models that used prerecruit survival estimates from the lake trout’s native range. Prerecruit survival in Yellowstone Lake was estimated at four to six times greater than native range survival rates. Simulated abundance continued to decline if recent suppression efforts were maintained. High prerecruit survival in Yellowstone Lake likely illustrates ecological release for an invasive species in an ecosystem containing few predators or competitors and demonstrates the potential pitfalls of assuming equal demographic rates for native and non-native populations.

","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2019-0306","usgsCitation":"Syslo, J.M., Brenden, T., Guy, C.S., Koel, T.M., Bigelow, P., Doepke, P.D., Arnold, J., and Brian D. Ertel, 2021, Could ecological release buffer suppression efforts for non-native lake trout (Salvelinus namaycush) in Yellowstone Lake, Yellowstone National Park?: Canadian Journal of Fisheries and Aquatic Sciences, v. 77, no. 6, p. 1010-1025, https://doi.org/10.1139/cjfas-2019-0306.","productDescription":"16 p.","startPage":"1010","endPage":"1025","ipdsId":"IP-112126","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":501016,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/99788","text":"External Repository"},{"id":395909,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone Lake, Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.654296875,\n 44.27273816279087\n ],\n [\n -110.1983642578125,\n 44.27273816279087\n ],\n [\n -110.1983642578125,\n 44.574817404670306\n ],\n [\n -110.654296875,\n 44.574817404670306\n ],\n [\n -110.654296875,\n 44.27273816279087\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"77","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Syslo, John M.","contributorId":276045,"corporation":false,"usgs":false,"family":"Syslo","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":36244,"text":"MSU","active":true,"usgs":false}],"preferred":false,"id":834517,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brenden, Travis O.","contributorId":276046,"corporation":false,"usgs":false,"family":"Brenden","given":"Travis O.","affiliations":[{"id":36244,"text":"MSU","active":true,"usgs":false}],"preferred":false,"id":834518,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":834516,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koel, Todd M","contributorId":276047,"corporation":false,"usgs":false,"family":"Koel","given":"Todd","email":"","middleInitial":"M","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":834519,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bigelow, Patricia E.","contributorId":276048,"corporation":false,"usgs":false,"family":"Bigelow","given":"Patricia E.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":834520,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Doepke, Philip D","contributorId":276049,"corporation":false,"usgs":false,"family":"Doepke","given":"Philip","email":"","middleInitial":"D","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":834521,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Arnold, Jeffrey L.","contributorId":276050,"corporation":false,"usgs":false,"family":"Arnold","given":"Jeffrey L.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":834522,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brian D. Ertel","contributorId":276051,"corporation":false,"usgs":false,"family":"Brian D. Ertel","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":834523,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70213169,"text":"70213169 - 2021 - The history of surface-elevation paradigms in mangrove biogeomorphology","interactions":[],"lastModifiedDate":"2021-01-25T17:52:59.973859","indexId":"70213169","displayToPublicDate":"2021-01-22T11:49:20","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"7","title":"The history of surface-elevation paradigms in mangrove biogeomorphology","docAbstract":"

Positioned in the intertidal zone, mangrove forests are a key model ecosystem with which to observe and test biogeomorphological concepts. Understanding how mangroves interact with their intertidal environment, particularly tidal inundation, is important if we are to assess their vulnerability or resilience to accelerated sea-level rise. While various biogeomorphological processes are now well studied in mangroves, these are not new concepts, and researchers often do not adequately describe their historical origins. This chapter discusses the historical context of two key paradigms in mangrove biogeomorphology: (1) the distribution of mangroves across the intertidal zone is controlled primarily by tidal inundation and (2) mangroves can adjust their elevation relative to the tidal frame through a combination of minerogenic and biogenic processes. The first paradigm had been noted as early as 350 BC, and studied quantitatively since at least the 1920s in Malaysia. The concept of “Inundation Classes” introduced at that time is still used by mangrove restoration practitioners today. The second paradigm has its roots in debates over whether mangroves are “land builders” or “land consolidators” in the early 20th century, and our view of this paradigm is strongly influenced by the geomorphic setting in which we work. It is important for us to understand the historical underpinnings of mangrove science and how they have shaped the paradigms that we use today. At a time when the mangrove research field is rapidly expanding, it is also important to acknowledge the intellectual contribution of researchers upon which we build today's science.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Dynamic sedimentary environments of mangrove coasts","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-816437-2.00007-0","usgsCitation":"Friess, D., and McKee, K.L., 2021, The history of surface-elevation paradigms in mangrove biogeomorphology, chap. 7 of Dynamic sedimentary environments of mangrove coasts, p. 179-198, https://doi.org/10.1016/B978-0-12-816437-2.00007-0.","productDescription":"20 p.","startPage":"179","endPage":"198","ipdsId":"IP-099892","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":382563,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Friess, Daniel A.","contributorId":35454,"corporation":false,"usgs":false,"family":"Friess","given":"Daniel A.","affiliations":[{"id":25407,"text":"Department of Geography, National University of Singapore","active":true,"usgs":false}],"preferred":false,"id":798485,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKee, Karen L. 0000-0001-7042-670X mckeek@usgs.gov","orcid":"https://orcid.org/0000-0001-7042-670X","contributorId":704,"corporation":false,"usgs":true,"family":"McKee","given":"Karen","email":"mckeek@usgs.gov","middleInitial":"L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":798486,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70227706,"text":"70227706 - 2021 - Drivers of site fidelity in ungulates","interactions":[],"lastModifiedDate":"2022-01-27T14:48:07.844313","indexId":"70227706","displayToPublicDate":"2021-01-22T08:31:48","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Drivers of site fidelity in ungulates","docAbstract":"
  1. While the tendency to return to previously visited locations—termed ‘site fidelity’—is common in animals, the cause of this behaviour is not well understood. One hypothesis is that site fidelity is shaped by an animal's environment, such that animals living in landscapes with predictable resources have stronger site fidelity. Site fidelity may also be conditional on the success of animals’ recent visits to that location, and it may become stronger with age as the animal accumulates experience in their landscape. Finally, differences between species, such as the way memory shapes site attractiveness, may interact with environmental drivers to modulate the strength of site fidelity.
  2. We compared inter-year site fidelity in 669 individuals across eight ungulate species fitted with GPS collars and occupying a range of environmental conditions in North America and Africa. We used a distance-based index of site fidelity and tested hypothesized drivers of site fidelity using linear mixed effects models, while accounting for variation in annual range size.
  3. Mule deer Odocoileus hemionus and moose Alces alces exhibited relatively strong site fidelity, while wildebeest Connochaetes taurinus and barren-ground caribou Rangifer tarandus granti had relatively weak fidelity. Site fidelity was strongest in predictable landscapes where vegetative greening occurred at regular intervals over time (i.e. high temporal contingency). Species differed in their response to spatial heterogeneity in greenness (i.e. spatial constancy). Site fidelity varied seasonally in some species, but remained constant over time in others. Elk employed a ‘win-stay, lose-switch’ strategy, in which successful resource tracking in the springtime resulted in strong site fidelity the following spring. Site fidelity did not vary with age in any species tested.
  4. Our results provide support for the environmental hypothesis, particularly that regularity in vegetative phenology shapes the strength of site fidelity at the inter-annual scale. Large unexplained differences in site fidelity suggest that other factors, possibly species-specific differences in attraction to known sites, contribute to variation in the expression of this behaviour.
  5. Understanding drivers of variation in site fidelity across groups of organisms living in different environments provides important behavioural context for predicting how animals will respond to environmental change.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2656.13425","usgsCitation":"Morrison, T., Merkle, J.A., Hopcraft, J., Aikens, E.O., Beck, J., Boone, R., Courtemanch, A.B., Dwinnell, S.P., Fairbanks, W.S., Griffith, B., Middleton, A.D., Monteith, K.L., Oates, B., Riotte-Lambert, L., Sawyer, H., Smith, K.T., Stabach, J.A., Taylor, K.L., and Kauffman, M., 2021, Drivers of site fidelity in ungulates: Journal of Animal Ecology, v. 90, no. 4, p. 955-966, https://doi.org/10.1111/1365-2656.13425.","productDescription":"12 p.","startPage":"955","endPage":"966","ipdsId":"IP-076551","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":453752,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2656.13425","text":"Publisher Index Page"},{"id":394967,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"90","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-02-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Morrison, Thomas A.","contributorId":272238,"corporation":false,"usgs":false,"family":"Morrison","given":"Thomas A.","affiliations":[{"id":56374,"text":"ug","active":true,"usgs":false}],"preferred":false,"id":831844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Merkle, Jerod A.","contributorId":272239,"corporation":false,"usgs":false,"family":"Merkle","given":"Jerod","email":"","middleInitial":"A.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":831845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hopcraft, J. Grant C.","contributorId":272240,"corporation":false,"usgs":false,"family":"Hopcraft","given":"J. Grant C.","affiliations":[{"id":56374,"text":"ug","active":true,"usgs":false}],"preferred":false,"id":831846,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aikens, Ellen O.","contributorId":272241,"corporation":false,"usgs":false,"family":"Aikens","given":"Ellen","email":"","middleInitial":"O.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":831847,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beck, Jeffrey","contributorId":272242,"corporation":false,"usgs":false,"family":"Beck","given":"Jeffrey","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":831848,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boone, Randall","contributorId":121404,"corporation":false,"usgs":true,"family":"Boone","given":"Randall","email":"","affiliations":[],"preferred":false,"id":831953,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Courtemanch, Alyson B.","contributorId":198651,"corporation":false,"usgs":false,"family":"Courtemanch","given":"Alyson","email":"","middleInitial":"B.","affiliations":[{"id":35682,"text":"Wyoming Game and Fish Department, Jackson, WY","active":true,"usgs":false}],"preferred":false,"id":831954,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dwinnell, Samantha P.","contributorId":270427,"corporation":false,"usgs":false,"family":"Dwinnell","given":"Samantha","email":"","middleInitial":"P.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":831955,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fairbanks, W. Sue","contributorId":145758,"corporation":false,"usgs":false,"family":"Fairbanks","given":"W.","email":"","middleInitial":"Sue","affiliations":[{"id":16230,"text":"Department of Natural Resource Ecology and Management, Iowa State University, 339 Science Hall II, Ames, Iowa 50011","active":true,"usgs":false}],"preferred":false,"id":831956,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Griffith, Brad 0000-0001-8698-6859","orcid":"https://orcid.org/0000-0001-8698-6859","contributorId":82571,"corporation":false,"usgs":true,"family":"Griffith","given":"Brad","email":"","affiliations":[{"id":108,"text":"Alaska Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":true,"id":831957,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Middleton, Arthur D.","contributorId":264420,"corporation":false,"usgs":false,"family":"Middleton","given":"Arthur","email":"","middleInitial":"D.","affiliations":[{"id":54468,"text":"uc","active":true,"usgs":false}],"preferred":true,"id":831958,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Monteith, Kevin L.","contributorId":83400,"corporation":false,"usgs":true,"family":"Monteith","given":"Kevin","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":831959,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Oates, Brendan","contributorId":200235,"corporation":false,"usgs":false,"family":"Oates","given":"Brendan","affiliations":[],"preferred":false,"id":831960,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Riotte-Lambert, Louise","contributorId":272336,"corporation":false,"usgs":false,"family":"Riotte-Lambert","given":"Louise","email":"","affiliations":[],"preferred":false,"id":831961,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Sawyer, Hall","contributorId":39930,"corporation":false,"usgs":false,"family":"Sawyer","given":"Hall","affiliations":[],"preferred":false,"id":831962,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Smith, Kurt T.","contributorId":204975,"corporation":false,"usgs":false,"family":"Smith","given":"Kurt","email":"","middleInitial":"T.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":831963,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Stabach, Jared A.","contributorId":272337,"corporation":false,"usgs":false,"family":"Stabach","given":"Jared","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":831964,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Taylor, Kaitlyn L.","contributorId":272342,"corporation":false,"usgs":false,"family":"Taylor","given":"Kaitlyn","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":831965,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":202921,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":831843,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70218774,"text":"70218774 - 2021 - Onshore flow characteristics of the 1755 CE Lisbon tsunami: Linking forward and inverse numerical modeling","interactions":[],"lastModifiedDate":"2021-03-11T13:40:37.333947","indexId":"70218774","displayToPublicDate":"2021-01-22T07:38:20","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Onshore flow characteristics of the 1755 CE Lisbon tsunami: Linking forward and inverse numerical modeling","docAbstract":"

The 1755 CE Lisbon earthquake triggered the largest historical tsunami ever impacting the Atlantic coasts of Europe. Despite recent efforts to better understand this event, there are still unanswered questions about the location of its epicenter and whether physical and historical evidences are in agreement.

Inverse modeling using tsunami sediments can be applied to quantify onshore flow characteristics. Forward numerical modeling is also a powerful tool capable of simulating tsunami hydrodynamics and the induced sediment transport. This work presents novel results from a combination of inverse and forward modeling to assess tsunami characteristics onshore. The study site is located on the Portuguese southern coast, at the Salgados lowland where inverse modeling was performed using TsuSedMod (Jaffe and Gelfenbaum, 2007) based on data retrieved from sediment samples. Forward modeling, including tsunami generation and propagation, was performed using the FLOW module of Delft3D suite model. Onshore topography was corrected for the 1755 CE scenario based on extensive tsunami sedimentary deposit thickness data. The tsunami source was chosen based on recent results from the authors that pointed to a good correlation between modeled and field tsunami data for the Marques de Pombal Fault (MPF), Horseshoe Fault (HSF) and a hypothetical scenario represented by a simple combination between Gorringe Bank and Horseshoe Fault (Scenario 1 - SC1).

Results from inverse model show tsunami onshore average speed varying from 7.3 up to 9.3 m/s and shear velocities from 0.52 up to 0.66 m/s. Forward modeling results show a wide variation according to the seismic source and tsunami onshore velocities can range from around 7 m/s when considering MPF to even an absence of inundation (SC1). The good agreement between both modeling approaches estimating tsunami velocity confirms the potential of numerical modeling coupled with geological records to improve the understanding of historical events.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2021.106432","usgsCitation":"Bosnic, I., Costa, P.J., Dourado, F., La Selle, S., and Gelfenbaum, G.R., 2021, Onshore flow characteristics of the 1755 CE Lisbon tsunami: Linking forward and inverse numerical modeling: Marine Geology, v. 434, 106432, 6 p., https://doi.org/10.1016/j.margeo.2021.106432.","productDescription":"106432, 6 p.","ipdsId":"IP-124318","costCenters":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":384303,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Portugal","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-9.03482,41.88057],[-8.67195,42.13469],[-8.26386,42.28047],[-8.01317,41.79089],[-7.42251,41.79207],[-7.25131,41.91835],[-6.66861,41.88339],[-6.38909,41.38182],[-6.85113,41.11108],[-6.86402,40.33087],[-7.02641,40.18452],[-7.06659,39.71189],[-7.49863,39.62957],[-7.09804,39.03007],[-7.37409,38.37306],[-7.02928,38.07576],[-7.16651,37.80389],[-7.53711,37.4289],[-7.45373,37.09779],[-7.85561,36.83827],[-8.38282,36.97888],[-8.89886,36.86881],[-8.7461,37.65135],[-8.84,38.26624],[-9.28746,38.35849],[-9.52657,38.73743],[-9.44699,39.39207],[-9.04831,39.75509],[-8.97735,40.15931],[-8.76868,40.76064],[-8.79085,41.18433],[-8.99079,41.54346],[-9.03482,41.88057]]]},\"properties\":{\"name\":\"Portugal\"}}]}","volume":"434","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bosnic, Ivana 0000-0003-3977-6116","orcid":"https://orcid.org/0000-0003-3977-6116","contributorId":255091,"corporation":false,"usgs":false,"family":"Bosnic","given":"Ivana","email":"","affiliations":[{"id":51417,"text":"Instituto Dom Luiz","active":true,"usgs":false}],"preferred":false,"id":811781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Costa, Pedro JM 0000-0001-6573-0539","orcid":"https://orcid.org/0000-0001-6573-0539","contributorId":255092,"corporation":false,"usgs":false,"family":"Costa","given":"Pedro","email":"","middleInitial":"JM","affiliations":[{"id":51417,"text":"Instituto Dom Luiz","active":true,"usgs":false}],"preferred":false,"id":811782,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dourado, Francisco 0000-0002-0872-9715","orcid":"https://orcid.org/0000-0002-0872-9715","contributorId":255093,"corporation":false,"usgs":false,"family":"Dourado","given":"Francisco","email":"","affiliations":[{"id":51419,"text":"Rio de Janeiro State University","active":true,"usgs":false}],"preferred":false,"id":811783,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"La Selle, SeanPaul 0000-0002-4500-7885 slaselle@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-7885","contributorId":181565,"corporation":false,"usgs":true,"family":"La Selle","given":"SeanPaul","email":"slaselle@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":811784,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gelfenbaum, Guy R. 0000-0003-1291-6107 ggelfenbaum@usgs.gov","orcid":"https://orcid.org/0000-0003-1291-6107","contributorId":742,"corporation":false,"usgs":true,"family":"Gelfenbaum","given":"Guy","email":"ggelfenbaum@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":811785,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228921,"text":"70228921 - 2021 - Morphology and composition of Goldeye (Hiodontidae; Hiodon alosoides) otoliths","interactions":[],"lastModifiedDate":"2022-02-25T12:05:39.356088","indexId":"70228921","displayToPublicDate":"2021-01-21T14:41:13","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2394,"text":"Journal of Morphology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Morphology and composition of Goldeye (Hiodontidae; Hiodon alosoides) otoliths","title":"Morphology and composition of Goldeye (Hiodontidae; Hiodon alosoides) otoliths","docAbstract":"

We provide up-to-date morphological and compositional data on otoliths of the osteoglossomorph Goldeye (Hiodon alosoides). Using computed tomography (CT) X-ray, we documented the location of each of the three pairs of otoliths (lapilli, sagittae, and asterisci) in relation to the swim bladder, which extended forward in close proximity to the sagittae and asterisci. The lappili were the largest otoliths in terms of surface area and volume, but the sagittae were highly modified, appearing spiral in shape when viewed dorsally, with a surface area to volume ratio more than double that of the lapilli. Using scanning electron microscopy, the surface of each otolith was viewable in great detail, and small otoconia (~10.5 μm diameter) were observed on each, but were most numerous on the sagittae. On scanning electron micrographs, the sagittae appeared to be bi-lobed, with asymmetrical lobes each oriented in the same general direction. Using neutron and X-ray diffraction methods, we found three polymorphs of calcium carbonate crystals (aragonite, vaterite, and calcite), sometimes all within the same otolith. However, in general, lapilli and sagittae were composed predominately of aragonite whereas asterisci were composed chiefly of vaterite. With these results, we provide information on a unique species, whose inclusion in future studies would benefit our understanding of fish hearing, fish evolution, and fisheries ecology.

","language":"English","publisher":"Wiley","doi":"10.1002/jmor.21324","usgsCitation":"Long, J.M., Snow, R., Pracheil, B., and Chakaoumakous, B.C., 2021, Morphology and composition of Goldeye (Hiodontidae; Hiodon alosoides) otoliths: Journal of Morphology, v. 282, no. 4, p. 511-519, https://doi.org/10.1002/jmor.21324.","productDescription":"9 p.","startPage":"511","endPage":"519","ipdsId":"IP-119139","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":453755,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1767877","text":"External Repository"},{"id":396454,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"282","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":835905,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Snow, Richard A.","contributorId":280026,"corporation":false,"usgs":false,"family":"Snow","given":"Richard A.","affiliations":[{"id":57412,"text":"2. Oklahoma Department of Wildlife Conservation","active":true,"usgs":false}],"preferred":false,"id":835906,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pracheil, Brenda M.","contributorId":280027,"corporation":false,"usgs":false,"family":"Pracheil","given":"Brenda M.","affiliations":[{"id":37070,"text":"Oak Ridge National Laboratory","active":true,"usgs":false}],"preferred":false,"id":835907,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chakaoumakous, Bryan C.","contributorId":280028,"corporation":false,"usgs":false,"family":"Chakaoumakous","given":"Bryan","email":"","middleInitial":"C.","affiliations":[{"id":37070,"text":"Oak Ridge National Laboratory","active":true,"usgs":false}],"preferred":false,"id":835908,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217752,"text":"70217752 - 2021 - Predictors of invertebrate biomass and rate of advancement of invertebrate phenology across eight sites in the North American Arctic","interactions":[],"lastModifiedDate":"2023-03-27T16:57:30.693028","indexId":"70217752","displayToPublicDate":"2021-01-21T10:33:44","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3093,"text":"Polar Biology","active":true,"publicationSubtype":{"id":10}},"title":"Predictors of invertebrate biomass and rate of advancement of invertebrate phenology across eight sites in the North American Arctic","docAbstract":"

Average annual temperatures in the Arctic increased by 2–3 °C during the second half of the twentieth century. Because shorebirds initiate northward migration to Arctic nesting sites based on cues at distant wintering grounds, climate-driven changes in the phenology of Arctic invertebrates may lead to a mismatch between the nutritional demands of shorebirds and the invertebrate prey essential for egg formation and subsequent chick survival. To explore the environmental drivers affecting invertebrate availability, we modeled the biomass of invertebrates captured in modified Malaise-pitfall traps over three summers at eight Arctic Shorebird Demographics Network sites as a function of accumulated degree-days and other weather variables. To assess climate-driven changes in invertebrate phenology, we used data from the nearest long-term weather stations to hindcast invertebrate availability over 63 summers, 1950–2012. Our results confirmed the importance of both accumulated and daily temperatures as predictors of invertebrate availability while also showing that wind speed negatively affected invertebrate availability at the majority of sites. Additionally, our results suggest that seasonal prey availability for Arctic shorebirds is occurring earlier and that the potential for trophic mismatch is greatest at the northernmost sites, where hindcast invertebrate phenology advanced by approximately 1–2.5 days per decade. Phenological mismatch could have long-term population-level effects on shorebird species that are unable to adjust their breeding schedules to the increasingly earlier invertebrate phenologies.

","language":"English","publisher":"Springer Link","doi":"10.1007/s00300-020-02781-5","usgsCitation":"Shaftel, R., Rinella, D.J., Kwon, E., Brown, S.C., Gates, H., Kendall, S., Lank, D.B., Liebezeit, J.R., Payer, D.C., Rausch, J., Saalfeld, S., Sandercock, B., Smith, P., Ward, D.H., and Lanctot, R., 2021, Predictors of invertebrate biomass and rate of advancement of invertebrate phenology across eight sites in the North American Arctic: Polar Biology, v. 44, p. 237-257, https://doi.org/10.1007/s00300-020-02781-5.","productDescription":"21 p.","startPage":"237","endPage":"257","ipdsId":"IP-114811","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":453760,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00300-020-02781-5","text":"Publisher Index Page"},{"id":382855,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska, Newfoundland, Northwest Territories","otherGeospatial":"North American Arctic","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -159.9609375,\n 64.32087157990324\n ],\n [\n -158.73046875,\n 66.72254132270653\n ],\n [\n -163.125,\n 68.33437594128185\n ],\n [\n -151.34765625,\n 68.39918004344189\n ],\n [\n -132.5390625,\n 66.99884379185184\n ],\n [\n -123.57421875,\n 68.52823492039876\n ],\n [\n -124.8046875,\n 70.90226826757711\n ],\n [\n -135.35156249999997,\n 69.96043926902489\n ],\n [\n -151.171875,\n 71.85622888185527\n ],\n [\n -165.05859375,\n 71.35706654962706\n ],\n [\n -169.98046875,\n 65.2198939361321\n ],\n [\n -159.9609375,\n 64.32087157990324\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -56.25,\n 46.31658418182218\n ],\n [\n -52.734375,\n 46.31658418182218\n ],\n [\n -52.734375,\n 49.724479188712984\n ],\n [\n -56.25,\n 49.724479188712984\n ],\n [\n -56.25,\n 46.31658418182218\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","noUsgsAuthors":false,"publicationDate":"2021-01-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Shaftel, Rebecca 0000-0002-4789-4211","orcid":"https://orcid.org/0000-0002-4789-4211","contributorId":248594,"corporation":false,"usgs":false,"family":"Shaftel","given":"Rebecca","email":"","affiliations":[{"id":37194,"text":"University of Alaska Anchorage","active":true,"usgs":false}],"preferred":false,"id":809530,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rinella, Daniel J.","contributorId":69048,"corporation":false,"usgs":true,"family":"Rinella","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":809531,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kwon, Eunbi","contributorId":169349,"corporation":false,"usgs":false,"family":"Kwon","given":"Eunbi","email":"","affiliations":[],"preferred":false,"id":809532,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Stephen C.","contributorId":38457,"corporation":false,"usgs":false,"family":"Brown","given":"Stephen","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":809533,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gates, H. River","contributorId":84256,"corporation":false,"usgs":true,"family":"Gates","given":"H. River","affiliations":[],"preferred":false,"id":809534,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kendall, Steve","contributorId":213517,"corporation":false,"usgs":false,"family":"Kendall","given":"Steve","affiliations":[],"preferred":false,"id":809535,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lank, David B.","contributorId":42533,"corporation":false,"usgs":false,"family":"Lank","given":"David","email":"","middleInitial":"B.","affiliations":[{"id":29801,"text":"Department of Biological Sciences, Simon Fraser University, Burnaby, BC","active":true,"usgs":false}],"preferred":false,"id":809536,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Liebezeit, Joseph R.","contributorId":127693,"corporation":false,"usgs":false,"family":"Liebezeit","given":"Joseph","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":809537,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Payer, David C.","contributorId":7495,"corporation":false,"usgs":false,"family":"Payer","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":809538,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rausch, Jennie","contributorId":203672,"corporation":false,"usgs":false,"family":"Rausch","given":"Jennie","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":809539,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Saalfeld, Sarah T.","contributorId":41721,"corporation":false,"usgs":true,"family":"Saalfeld","given":"Sarah T.","affiliations":[],"preferred":false,"id":809540,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sandercock, Brett K.","contributorId":223926,"corporation":false,"usgs":false,"family":"Sandercock","given":"Brett K.","affiliations":[],"preferred":false,"id":809541,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Smith, Paul A.","contributorId":73477,"corporation":false,"usgs":true,"family":"Smith","given":"Paul A.","affiliations":[],"preferred":false,"id":809542,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Ward, David H. 0000-0002-5242-2526 dward@usgs.gov","orcid":"https://orcid.org/0000-0002-5242-2526","contributorId":3247,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dward@usgs.gov","middleInitial":"H.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":809543,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Lanctot, Richard B.","contributorId":77879,"corporation":false,"usgs":false,"family":"Lanctot","given":"Richard B.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":809544,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70237877,"text":"70237877 - 2021 - Evaluating the use of marine protected areas by endangered species: A habitat selection approach","interactions":[],"lastModifiedDate":"2023-04-14T16:55:05.946982","indexId":"70237877","displayToPublicDate":"2021-01-21T09:18:23","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9977,"text":"Ecological Solutions and Evidence","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the use of marine protected areas by endangered species: A habitat selection approach","docAbstract":"

1. Optimizing the design of marine protected area (MPA) networks for the conservation of migratory marine species and their habitats involves a suite of important considerations, such as appropriate scale requirements and the distribution of anthropogenic impacts. Often, a fundamental component of the conservation planning process is delineating areas of high use or high biodiversity within a region of interest.

2. However, basing conservation strategies off merely the number of individuals in an ecosystem is outdated and potentially subject to arbitrary thresholds. To be effective at protecting marine megafauna, MPAs would ideally encompass habitats used by focal species. Through satellite-tracking studies, evidence of whether species actually use protected areas is emerging.

3. Here, we present a multispecies perspective on habitat selection within existing MPAs throughout the Floridian ecoregion, which encompasses coastal Florida and the Gulf of Mexico. Using an 11-year satellite-tracking dataset on 235 marine turtles, we used integrated step selection analysis to quantify the effects of sea turtle behavioural state (identified by a switching state-space model), protected area status, chlorophyll and bathymetry on habitat selection.

4. Our results show that sea turtles do select for existing protected areas, specifically multi-use zones, while controlling for the effects of depth and primary productivity. However, our analysis revealed that turtles showed no selection for the no-take zones within MPAs, during either transiting or foraging.

5. These findings contribute to the existing literature base of MPA use for highly mobile, imperilled species and could inform management of existing MPAs or changes to zoning, specifically multi-use to no-take. Our use of a robust spatial modelling framework to evaluate habitat selection relative to MPAs could be incorporated into conservation planning to build MPA networks designed to accommodate migratory species.

","language":"English","publisher":"Wiley","doi":"10.1002/2688-8319.12035","usgsCitation":"Roberts, K.E., Smith, B., Burkholder, D.A., and Hart, K., 2021, Evaluating the use of marine protected areas by endangered species: A habitat selection approach: Ecological Solutions and Evidence, v. 2, no. 1, e12035, 10 p.; Data Release, https://doi.org/10.1002/2688-8319.12035.","productDescription":"e12035, 10 p.; Data Release","ipdsId":"IP-116564","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":453762,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2688-8319.12035","text":"Publisher Index Page"},{"id":408857,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":415792,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UZU4GG","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.55389682044014,\n 26.141125121136838\n ],\n [\n -82.55389682044014,\n 24.4670519782689\n ],\n [\n -79.75556154192874,\n 24.4670519782689\n ],\n [\n -79.75556154192874,\n 26.141125121136838\n ],\n [\n -82.55389682044014,\n 26.141125121136838\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-01-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Roberts, Kelsey E. 0000-0001-8422-632X","orcid":"https://orcid.org/0000-0001-8422-632X","contributorId":296892,"corporation":false,"usgs":true,"family":"Roberts","given":"Kelsey","email":"","middleInitial":"E.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":856057,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Brian J. 0000-0002-0531-0492","orcid":"https://orcid.org/0000-0002-0531-0492","contributorId":139672,"corporation":false,"usgs":false,"family":"Smith","given":"Brian J.","affiliations":[{"id":12876,"text":"Cherokee Nation Technology Solutions","active":true,"usgs":false}],"preferred":false,"id":856058,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burkholder, Derek A. 0000-0001-6315-6932","orcid":"https://orcid.org/0000-0001-6315-6932","contributorId":289783,"corporation":false,"usgs":false,"family":"Burkholder","given":"Derek","email":"","middleInitial":"A.","affiliations":[{"id":62249,"text":"Halmos College of Natural Sciences and Oceanography, Department of Marine and Environmental Science, Nova Southeastern University","active":true,"usgs":false}],"preferred":false,"id":856059,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":220333,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":856060,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217613,"text":"70217613 - 2021 - Valleys of fire: Historical fire regimes of forest-grassland ecotones across the montane landscape of the Valles Caldera National Preserve, New Mexico, USA","interactions":[],"lastModifiedDate":"2021-02-04T14:25:19.390912","indexId":"70217613","displayToPublicDate":"2021-01-21T08:40:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Valleys of fire: Historical fire regimes of forest-grassland ecotones across the montane landscape of the Valles Caldera National Preserve, New Mexico, USA","docAbstract":"

Context

Montane grasslands and forest-grassland ecotones are unique and dynamic components of many landscapes, but the processes that regulate their dynamics are difficult to observe over ecologically relevant time spans.

Objectives

We aimed to demonstrate the efficacy of using grassland-forest ecotone trees to reconstruct spatial and temporal properties of the historical fire regime in a complex landscape of montane forests and adjacent grasslands.

Methods

We sampled and crossdated fire-scarred trees along ecotones and compared variations in historical fire occurrence within and among nine adjoining valle basins in a 10,158 ha landscape. We analyzed fire year extensiveness, climate regulation, and the occurrence of consecutive fire years.

Results

The resulting tree-ring record covers 1240–2005 AD, with 296 trees recording 125 replicated fire years during the analysis period 1601–1902 AD. Mean fire intervals for all events recorded on two or more trees ranged from 4.7 to 13.6 years in individual valles, and a mean of 2.4 ± 1.7 (SD) years at the landscape scale. Between 1660 and 1902, extensive fires occurring in six or more valles occurred 15 times, on average at ~ 17-year intervals; 29 moderately widespread fires (3–5 valles) occurred during this period, at 8.7 year intervals on average. Widespread events occurred in years with a significantly lower Palmer Drought Severity Index (PDSI) preceded by years of significantly positive PDSI, indicating conditions favorable for fine fuel production. Spatial reconstruction of fire extent revealed multiple occurrences of consecutive-year fires burning non-overlapping areas, associated with persistent low PDSI anomalies preceded by positive conditions in antecedent years.

Conclusions

A landscape spatiotemporal approach to reconstructing fire regimes of montane forest-grassland complexes provides a valuable baseline for guiding prescribed and natural fire management at large spatial scales.

","language":"English","publisher":"Springer","doi":"10.1007/s10980-020-01101-w","usgsCitation":"Dewar, J.J., Falk, D.A., Swetnam, T.W., Baisan, C.H., Allen, C.D., Parmenter, R.R., and Margolis, E.Q., 2021, Valleys of fire: Historical fire regimes of forest-grassland ecotones across the montane landscape of the Valles Caldera National Preserve, New Mexico, USA: Landscape Ecology, v. 36, p. 331-352, https://doi.org/10.1007/s10980-020-01101-w.","productDescription":"22 p.","startPage":"331","endPage":"352","ipdsId":"IP-099759","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":382540,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Valles Caldera National Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.67861938476562,\n 35.79553849799263\n ],\n [\n -106.33804321289061,\n 35.79553849799263\n ],\n [\n -106.33804321289061,\n 36.01800375871416\n ],\n [\n -106.67861938476562,\n 36.01800375871416\n ],\n [\n -106.67861938476562,\n 35.79553849799263\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","noUsgsAuthors":false,"publicationDate":"2021-01-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Dewar, J. J.","contributorId":248334,"corporation":false,"usgs":false,"family":"Dewar","given":"J.","email":"","middleInitial":"J.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":808897,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falk, Donald A.","contributorId":197570,"corporation":false,"usgs":false,"family":"Falk","given":"Donald","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":808898,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swetnam, T. W.","contributorId":248335,"corporation":false,"usgs":false,"family":"Swetnam","given":"T.","email":"","middleInitial":"W.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":808899,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baisan, C. H.","contributorId":248336,"corporation":false,"usgs":false,"family":"Baisan","given":"C.","email":"","middleInitial":"H.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":808900,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allen, Craig D. 0000-0002-8777-5989 craig_allen@usgs.gov","orcid":"https://orcid.org/0000-0002-8777-5989","contributorId":2597,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"craig_allen@usgs.gov","middleInitial":"D.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":808901,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Parmenter, R. R.","contributorId":248337,"corporation":false,"usgs":false,"family":"Parmenter","given":"R.","email":"","middleInitial":"R.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":808902,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Margolis, Ellis Q. 0000-0002-0595-9005 emargolis@usgs.gov","orcid":"https://orcid.org/0000-0002-0595-9005","contributorId":173538,"corporation":false,"usgs":true,"family":"Margolis","given":"Ellis","email":"emargolis@usgs.gov","middleInitial":"Q.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":808903,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70218659,"text":"70218659 - 2021 - A metapopulation model of social group dynamics and disease applied to Yellowstone wolves","interactions":[],"lastModifiedDate":"2021-03-04T13:44:08.699721","indexId":"70218659","displayToPublicDate":"2021-01-21T07:42:12","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"A metapopulation model of social group dynamics and disease applied to Yellowstone wolves","docAbstract":"

The population structure of social species has important consequences for both their demography and transmission of their pathogens. We develop a metapopulation model that tracks two key components of a species’ social system: average group size and number of groups within a population. While the model is general, we parameterize it to mimic the dynamics of the Yellowstone wolf population and two associated pathogens: sarcoptic mange and canine distemper. In the initial absence of disease, we show that group size is mainly determined by the birth and death rates and the rates at which groups fission to form new groups. The total number of groups is determined by rates of fission and fusion, as well as environmental resources and rates of intergroup aggression. Incorporating pathogens into the models reduces the size of the host population, predominantly by reducing the number of social groups. Average group size responds in more subtle ways: infected groups decrease in size, but uninfected groups may increase when disease reduces the number of groups and thereby reduces intraspecific aggression. Our modeling approach allows for easy calculation of prevalence at multiple scales (within group, across groups, and population level), illustrating that aggregate population-level prevalence can be misleading for group-living species. The model structure is general, can be applied to other social species, and allows for a dynamic assessment of how pathogens can affect social structure and vice versa.

","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2020023118","usgsCitation":"Brandell, E.E., Dobson, A.P., Hudson, P., Cross, P., and Smith, D., 2021, A metapopulation model of social group dynamics and disease applied to Yellowstone wolves: Proceedings of the National Academy of Sciences, v. 118, no. 10, e2020023118, 10 p., https://doi.org/10.1073/pnas.2020023118.","productDescription":"e2020023118, 10 p.","ipdsId":"IP-108918","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":453766,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7958402","text":"Publisher Index Page"},{"id":383818,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"118","issue":"10","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Brandell, Ellen E.","contributorId":253140,"corporation":false,"usgs":false,"family":"Brandell","given":"Ellen","email":"","middleInitial":"E.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":811296,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dobson, A P 0000-0002-9678-1694","orcid":"https://orcid.org/0000-0002-9678-1694","contributorId":253143,"corporation":false,"usgs":false,"family":"Dobson","given":"A","email":"","middleInitial":"P","affiliations":[{"id":6644,"text":"Princeton University","active":true,"usgs":false}],"preferred":false,"id":811297,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hudson, Peter J.","contributorId":253146,"corporation":false,"usgs":false,"family":"Hudson","given":"Peter J.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":811299,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cross, Paul C. 0000-0001-8045-5213","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":204814,"corporation":false,"usgs":true,"family":"Cross","given":"Paul C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":811298,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Douglas W.","contributorId":179181,"corporation":false,"usgs":false,"family":"Smith","given":"Douglas W.","affiliations":[],"preferred":false,"id":811300,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70224333,"text":"70224333 - 2021 - Precipitation characteristics and land cover control wet season runoff source and rainfall partitioning in three humid tropical catchments in central Panama","interactions":[],"lastModifiedDate":"2021-09-23T12:31:07.32711","indexId":"70224333","displayToPublicDate":"2021-01-21T07:29:19","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Precipitation characteristics and land cover control wet season runoff source and rainfall partitioning in three humid tropical catchments in central Panama","docAbstract":"

Mechanisms of runoff generation in the humid tropics are poorly understood, particularly in the context of land-use/land cover change. This study analyzed the results of 124 storm hydrographs from three humid tropical catchments of markedly different vegetation cover and land-use history in central Panama during the 2017 wet season: actively grazed pasture, young secondary succession, and near-mature forest. We used electrical conductivity to separate baseflow (old water) from storm-event water (new-water). In all three land covers, new-water dominated storm runoff generation in 44% of the sampled storm events, indicating the dominance of fast shallow flow paths in the landscape. Activation of these flow paths was found to depend on a combination of maximum rainfall intensity and total storm rainfall, which, in turn, relates to markedly contrasting hydrograph separation results among land covers. Relationships between these rainfall characteristics and storm runoff generation were nonlinear, producing a threshold response with the exceedance of specific rainfall volumes and/or intensities. The pastoral catchment delivered order of magnitude more new-water during storm events than the two forested catchments. Although new-water contributed minimally (<10%) to total wet season runoff in the forested catchments, 43% of runoff generation in the pasture came from five large rainfall events where a threshold response produced substantial increases in total runoff and new-runoff efficiency. Based on our results, we propose a conceptual model of hydrologic flow paths in humid tropical systems that can explain previously observed disparities in seasonal storage and runoff with respect to land use/land cover.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020WR028058","usgsCitation":"Birch, A.L., Stallard, R., and Barnard, H.R., 2021, Precipitation characteristics and land cover control wet season runoff source and rainfall partitioning in three humid tropical catchments in central Panama: Water Resources Research, v. 57, no. 2, e2020WR028058, 19 p., https://doi.org/10.1029/2020WR028058.","productDescription":"e2020WR028058, 19 p.","ipdsId":"IP-121670","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":453769,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020wr028058","text":"Publisher Index Page"},{"id":389642,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Panama","otherGeospatial":"Agua Salud Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.299072265625,\n 8.890498870150504\n ],\n [\n -79.29931640625,\n 8.890498870150504\n ],\n [\n -79.29931640625,\n 9.486990162235656\n ],\n [\n -80.299072265625,\n 9.486990162235656\n ],\n [\n -80.299072265625,\n 8.890498870150504\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Birch, Andrew L.","contributorId":257522,"corporation":false,"usgs":false,"family":"Birch","given":"Andrew","email":"","middleInitial":"L.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":823784,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stallard, Robert 0000-0001-8209-7608","orcid":"https://orcid.org/0000-0001-8209-7608","contributorId":215272,"corporation":false,"usgs":true,"family":"Stallard","given":"Robert","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":823785,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnard, Holly R.","contributorId":257523,"corporation":false,"usgs":false,"family":"Barnard","given":"Holly","email":"","middleInitial":"R.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":823786,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70217635,"text":"70217635 - 2021 - Space matters: Host spatial structure and the dynamics of plague transmission","interactions":[],"lastModifiedDate":"2021-02-22T16:51:58.782522","indexId":"70217635","displayToPublicDate":"2021-01-21T07:10:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Space matters: Host spatial structure and the dynamics of plague transmission","docAbstract":"

The development of models to elucidate the transmission pathways and dynamics of wildlife diseases remains challenging. Sylvatic plague, caused by the bacterium Yersinia pestis (Yp), is an infectious zoonotic disease that primarily affects wild rodents, including prairie dogs (Cynomys spp.) in North America. Proposed transmission pathways for Yp include flea bites, direct contacts between hosts, and environmental reservoirs (e.g. soil, carcasses). We developed a spatially explicit, agent-based model of Yp transmission to explore the effects of alternative transmission pathways, different disease initiation mechanisms (host or fleas), parameter uncertainty, and spatial structure of hosts. A particularly novel aspect of our model was the integration of ecological models with traditional disease models. Specifically, we used estimates from spatial capture-recapture models to generate data-driven spatial distributions, densities, and contact rates to capture the spatial structure of prairie dogs. We simulated ~9 million scenarios across a wide range of parameter values and conducted sensitivity analyses to determine the most influential parameters on the number of flea-days (sum of the mean number of fleas on hosts each day of the simulation), number of newly infected hosts per day, the time to depopulation (<20 prairie dogs remaining), and the proportion of the prairie dog population remaining at the end of the simulation (after 150 days). When including spatial structure, we found the probability of transmission via environmental sources of Yp (i.e. carcasses) had the greatest influence on model results when Yp infection was initiated in prairie dog hosts, rather than in fleas. Conversely, the mechanism of transmission by fleas to prairie dogs had the greatest influence on model results when Yp infection was initiated in fleas (i.e. via introduction by carnivores, a migrant prairie dog, or other mammalian host). Uncertainty in parameter estimates, particularly those related to the transmission pathways of Yp, continue to hamper efforts to realistically model plague dynamics in wild rodents. Our results elucidate the complexity of the flea-plague-prairie dog system and reiterate the importance of research on Yp transmission mechanisms to provide a full understanding of this disease. Our results also emphasize the importance of realistic estimates of spatial structure for exploring transmission dynamics of wildlife diseases and provide a framework for generating a data-driven description of spatial structure.

    ","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2021.109450","usgsCitation":"Russell, R., Walsh, D.P., Samuel, M., Grunnill, M.S., and Rocke, T.E., 2021, Space matters: Host spatial structure and the dynamics of plague transmission: Ecological Modelling, v. 443, 109450, 13 p., https://doi.org/10.1016/j.ecolmodel.2021.109450.","productDescription":"109450, 13 p.","ipdsId":"IP-124148","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":453772,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2021.109450","text":"Publisher Index Page"},{"id":382580,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":383420,"rank":2,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P97AJ6LY"}],"volume":"443","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Russell, Robin E. 0000-0001-8726-7303","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":219536,"corporation":false,"usgs":true,"family":"Russell","given":"Robin E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":809045,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walsh, Daniel P. 0000-0002-7772-2445","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":219539,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":809046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Samuel, Michael D.","contributorId":206351,"corporation":false,"usgs":false,"family":"Samuel","given":"Michael D.","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":809047,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grunnill, Martin S.","contributorId":248404,"corporation":false,"usgs":false,"family":"Grunnill","given":"Martin","email":"","middleInitial":"S.","affiliations":[{"id":49892,"text":"Public Health England","active":true,"usgs":false}],"preferred":false,"id":809048,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":809049,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217434,"text":"sir20205130 - 2021 - Water-quality trends of urban streams in Independence, Missouri, 2005–18","interactions":[],"lastModifiedDate":"2021-01-21T12:48:49.595303","indexId":"sir20205130","displayToPublicDate":"2021-01-20T17:15:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5130","displayTitle":"Water-Quality Trends of Urban Streams in Independence, Missouri, 2005–18","title":"Water-quality trends of urban streams in Independence, Missouri, 2005–18","docAbstract":"

    The U.S. Geological Survey and the city of Independence, Missouri, Water Pollution Control Department has studied the water quality and ecological condition of urban streams within Independence since 2005. Selected physical properties, nutrients, chloride, fecal indicator bacteria (Escherichia coli and total coliform), total dissolved solids, and suspended-sediment concentration data for base-flow and stormflow samples were used to document temporal trends in concentrations and flow-weighted concentrations; and annual loads were computed and investigated for selected nutrients, chloride, and suspended sediment. The six study sites included in this report are located on five urban streams: Rock Creek, a tributary in the city that drains to the Missouri River; three tributaries of the Little Blue River within the city (East Fork Little Blue River, Adair Creek, and Spring Branch Creek); and two sites on the main stem of the Little Blue River (one upstream from the city and one downstream from the three tributaries).

    Many factors such as population, land use, and climate, and combinations of these factors contributed to the significant changes in the concentrations and transport of nutrients, chloride, fecal indicator bacteria, and suspended sediment in the urban streams within Independence. The population of Independence and the amount of developed land in the urban watersheds remained unchanged during the 2005–18 study. Differences were noted in precipitation and in streamflow during the study. Annual precipitation and streamflow were separated into two time periods within the study—period 1 (2006–10), having greater annual streamflow and precipitation, and period 2 (2011–18), having about 30 percent lower annual streamflow and less precipitation. Streamflow was an important factor in the transport of nitrogen, phosphorus, chloride, and suspended sediment from the urban watersheds. Changes in data collection methodology during the study period and improvements to the city stormwater and wastewater infrastructure also could have contributed to some of the trends. Between 2009 and 2015, more than 35 million dollars of improvements were made to stormwater and wastewater infrastructure within the city. These improvements, such as additional sewage overflow holding tanks, removal of septic tanks, and improved and expanded sanitary sewer lines and storm overflows, also could have affected the decreased nutrients and fecal indicator bacteria trends among the urban streams in the study area.

    Models were used for analyzing streamflow-related variability in constituent concentrations and loads to determine if the water quality changed significantly during the study period. Trends in concentration data at four sites were analyzed using a statistical package called R–QWTREND and trends in load data were analyzed at six sites using a statistical package called Weighted Regressions on Time, Discharge, and Season-Kalman filter (WRTDS–K); both developed by the U.S. Geological Survey and publicly available for use.

    Statistically significant trends in flow-weighted nutrient concentrations and loads generally were downward during the study period. The only nutrient compound with a statistically significant upward trend in flow-weighted concentration was dissolved orthophosphate as phosphorus at the Rock Creek site and the upstream site on the Little Blue River. A statistically significant downward trend in annual dissolved ammonia load was identified at the downstream Little Blue River site. A significant upward linear trend in annual orthophosphate as phosphorus load was identified on Adair Creek.

    A statistically significant upward trend in dissolved chloride concentrations was identified at the downstream Little Blue River site. Road salt application near the site during the winter could have resulted in higher concentrated runoff during wet weather conditions. Annual chloride loads significantly decreased in Adair Creek and Spring Branch Creek. The mean annual chloride load transported in the drier (2011–18) period 2 was significantly less than during the wetter (2006–10) period 1, indicating that trends in precipitation runoff are an important factor in trends in annual transport of chloride.

    Statistically significant downward trends in flow-weighted fecal indicator bacteria Escherichia coli (E. coli) population densities were noted for Rock Creek and the down-stream site on the Little Blue River. However, no trend was identified in E. coli population density at the upstream Little Blue River site. The downward trend in E. coli population density at the downstream site could be a result of decreased streamflow and precipitation over the study period, storage of fecal indicator bacteria in the Little Blue River streambed within the study area, die-off of fecal indicator bacteria during travel from upstream to downstream, changes in the sample collection methodology, improvements to the city’s storm-water and wastewater infrastructures, or a combination of these factors.

    The statistically significant downward trend in suspended-sediment concentration identified at the upstream Little Blue River site could be affected by the decreased streamflow and precipitation during the study period, by changes in sampling methods within the study period, and by the decrease in construction and urban land development upstream from the city.

    No statistically significant change was indicated in the annual suspended-sediment load transported from Independence to the Little Blue River during the study period. More than one-half the suspended sediment transported in the Little Blue River originated in the watershed upstream from Independence.

    The Little Blue River and many of its tributaries that drain Independence have been designated as recreational waters classified for whole-body contact class B and secondary contact recreation, and some have been listed as impaired for E. coli by the Missouri Department of Natural Resources from urban runoff and storm sewers. Observations were made among the available E. coli population density data for both Little Blue River sites to further understand water-quality conditions over the study period. Both Little Blue River sites had similar medians and geometric means for the recreational season (April through October) and during the full study period, both of which are greater than the regulatory population density for both recreational classes. The Little Blue River drainage area nearly doubles in size from the upstream to downstream site; therefore, the consistent geometric mean and median of E. coli population densities at the upstream and downstream Little Blue River sites could be primarily due to the larger volume of streamflow creating a dilution effect. Other possible factors could be storage of fecal indicator bacteria in stream bed sediments, die-off of fecal indicator bacteria during transport, improvements to the city’s wastewater and stormwater infrastructure, changes to sampling methodology, or a combination of these factors. Specific sources of the E. coli are currently (2019) unknown.

    ","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205130","collaboration":"Prepared in cooperation with the city of Independence, Missouri, Water Pollution Control Department","usgsCitation":"Barr, M.N., and Kalkhoff, S.J., 2021, Water-quality trends of urban streams in Independence, Missouri, 2005–18: U.S. Geological Survey Scientific Investigations Report 2020–5130, 57 p., https://doi.org/10.3133/sir20205130.","productDescription":"Report: viii, 57 p.; 5 Tables","onlineOnly":"Y","ipdsId":"IP-113987","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":382337,"rank":12,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5130/sir20205130_table3_2.csv","text":"Table 3.2. Annual total phosphorus, chloride, and suspended-sediment loads in the Little Blue River near Lake City, Missouri (site 8)—U.S. Geological Survey site number 06894000. (csv file)","size":"4.0 kB","description":"SIR 2020-5130 Table 3.2 CSV format"},{"id":382336,"rank":11,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5130/sir20205130_table3_2.xlsx","text":"Table 3.2. Annual total phosphorus, chloride, and suspended-sediment loads in the Little Blue River near Lake City, Missouri (site 8)—U.S. Geological Survey site number 06894000.","size":"16.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020-5130 Table 3.2 XLSX format"},{"id":382326,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5130/sir20205130_table1_3.xlsx","text":"Table 1.3. Summary statistics for selected physical properties and chemical constituents at select sites in Independence, Missouri.","size":"20.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020-5130 Table 1.3 XLSX format"},{"id":382324,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5130/coverthb.jpg"},{"id":382325,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5130/sir20205130.pdf","text":"Report","size":"6.21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5130"},{"id":382327,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5130/sir20205130_table1_3.csv","text":"Table 1.3. Summary statistics for selected physical properties and chemical constituents at select sites in Independence, Missouri. (csv file)","size":"12.0 kB","description":"SIR 2020-5130 Table 1.3 CSV format"},{"id":382328,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5130/sir20205130_table2_1.xlsx","text":"Table 2.1. Estimated annual mean concentration, load, and yield for select nitrogen species in urban streams in Independence, Missouri.","size":"28.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020-5130 Table 2.1 XLSX format"},{"id":382329,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5130/sir20205130_table2_1.csv","text":"Table 2.1. Estimated annual mean concentration, load, and yield for select nitrogen species in urban streams in Independence, Missouri. (csv file)","size":"12.0 kB","description":"SIR 2020-5130 Table 2.1 CSV format"},{"id":382330,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5130/sir20205130_table2_2.xlsx","text":"Table 2.2. Estimated annual mean concentration, load, and yield for select phosphorus species, chloride, and suspended sediment in urban streams in Independence, Missouri.","size":"24.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020-5130 Table 2.2 XLSX format"},{"id":382331,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5130/sir20205130_table2_2.csv","text":"Table 2.2. Estimated annual mean concentration, load, and yield for select phosphorus species, chloride, and suspended sediment in urban streams in Independence, Missouri. (csv file)","size":"8.0 kB","description":"SIR 2020-5130 Table 2.2 CSV format"},{"id":382332,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5130/sir20205130_table3_1.xlsx","text":"Table 3.1. Annual total nitrogen, total organic nitrogen, dissolved ammonia, and dissolved nitrate plus nitrite loads in the Little Blue River near Lake City, Missouri (site 8)—U.S.","size":"16.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020-5130 Table 3.1 XLSX format"},{"id":382333,"rank":10,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5130/sir20205130_table3_1.csv","text":"Table 3.1. Annual total nitrogen, total organic nitrogen, dissolved ammonia, and dissolved nitrate plus nitrite loads in the Little Blue River near Lake City, Missouri (site 8)—U.S. (csv file)","size":"4.0 kB","description":"SIR 2020-5130 Table 3.1 CSV format"}],"country":"United States","state":"Missouri","city":"Independence","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.50576782226562,\n 39.029852466679316\n ],\n [\n -94.32037353515625,\n 39.020784109393176\n ],\n [\n -94.32518005371094,\n 39.15349256868936\n ],\n [\n -94.50714111328125,\n 39.14816772482178\n ],\n [\n -94.50576782226562,\n 39.029852466679316\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

    Director, Central Midwest Water Science Center
    U.S. Geological Survey
    1400 Independence Road
    Rolla, MO 65401

    ","tableOfContents":"","publishedDate":"2021-01-20","noUsgsAuthors":false,"publicationDate":"2021-01-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Barr, Miya N. 0000-0002-9961-9190 mnbarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9961-9190","contributorId":3686,"corporation":false,"usgs":true,"family":"Barr","given":"Miya","email":"mnbarr@usgs.gov","middleInitial":"N.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808593,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kalkhoff, Stephen J. 0000-0003-4110-1716 sjkalkho@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-1716","contributorId":1731,"corporation":false,"usgs":true,"family":"Kalkhoff","given":"Stephen","email":"sjkalkho@usgs.gov","middleInitial":"J.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808594,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}