Coastal flooding affects low-lying communities worldwide and is expected to increase with climate change, especially along reef-lined coasts, where wave-driven flooding is particularly prevalent. However, current regional modeling approaches are either insufficient or too computationally expensive to accurately assess risks in these complex environments. This study introduces and validates an improved computationally efficient and physics-based approach to compute dynamic wave-driven regional flooding on reef-lined coasts. We coupled a simplified-physics flood model (SFINCS) with a one-dimensional wave transformation model (XBeach-1D). To assess the performance of the proposed approach, we compared its results with results from a fully resolving two-dimensional wave transformation model (XBeach-2D). We applied this approach for a range of storms and sea-level rise scenarios for two contrasting reef-lined coastal geomorphologies: one low relief area and one high relief area. Our findings reveal that SFINCS coupled with XBeach-1D generates flood extents comparable to those produced by XBeach-2D, with a hit rate of 92%. However, this method tends to underpredict the flood extent of weaker, high-frequency storms and overpredict stronger, low-frequency storms. Across scenarios, our approach overpredicted the mean flood water depth, with a positive bias of 7 cm and root mean square difference of 15 cm. Offering approximately 100 times greater computational efficiency than its two-dimensional XBeach counterpart, this flood modeling technique is recommended for wave-driven flood modeling in scenarios with high computational demands, such as modeling numerous scenarios or undertaking detailed regional-scale modeling.
Groundwater development, mainly for large-scale irrigation, has increased substantially in the Harney Basin of southeastern Oregon since 2010. Concurrently, some areas of the basin experienced groundwater-level declines of more than 100 feet, and some shallow wells have gone dry. The Oregon Water Resources Department has limited new groundwater development in the basin until an improved understanding of the groundwater-flow system is available. The groundwater resources report by Gingerich and others (2022, U.S. Geological Survey Scientific Investigations Report 2021–5103, https://doi.org/10.3133/sir20215103) provides that understanding. This report describes the development of a numerical groundwater-flow model that can be used as a tool to help improve that understanding. The Harney Basin Groundwater Model was developed using the finite-difference groundwater-modeling software U.S. Geological Survey modular finite-difference groundwater-flow model (MODFLOW 6) and associated Python pre- and post-processing routines. The groundwater model encompasses the entire 5,240-square-mile Harney Basin and adjacent areas and is calibrated to the hydrologic conditions from 1930 to 2018. The model has a uniform grid consisting of 78,064 nearly square cells, each covering 2,005 by 2,007 feet (about 92 acres) and has 10 layers (780,640 total cells) representing the vertical distribution of hydrogeologic units. The results from the calibrated model simulations indicate that groundwater pumpage exceeded recharge since about the mid-1980s, resulting in an estimated net cumulative depletion of groundwater storage (discharge minus recharge) of about 840,000 acre-feet and also indicated declines in groundwater evapotranspiration and spring and stream discharge. Model simulations show as much as 100 feet of groundwater-level decline in some areas and more than 40 feet of decline in widespread areas in recent decades. Model simulations are consistent with field observations of groundwater levels through time.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245017","collaboration":"Prepared in cooperation with the Oregon Water Resources Department","usgsCitation":"Gingerich, S.B., Boschmann, D.E., Grondin, G.H., and Schibel, H.J., 2024, Groundwater model of the Harney Basin, southeastern Oregon: U.S. Geological Survey Scientific Investigations Report 2024–5017, 104 p., https://doi.org/10.3133/sir20245017.","productDescription":"Report: xii, 104 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-152081","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":499430,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116178.htm","linkFileType":{"id":5,"text":"html"}},{"id":426855,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5017/sir20245017.jpg"},{"id":426856,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5017/sir20245017.pdf","text":"Report","size":"47.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5017"},{"id":426869,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OEKEIO","text":"USGS data release","description":"USGS data release","linkHelpText":"MODFLOW 6 model used to simulate groundwater flow in the Harney Basin, southeastern Oregon"},{"id":426859,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5017/sir20245017.XML"},{"id":426858,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5017/images"}],"country":"United States","state":"Oregon","otherGeospatial":"Harney Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.44430319880412,\n 44.965776942074626\n ],\n [\n -121.44430319880412,\n 42.262073209475204\n ],\n [\n -117.31344382380401,\n 42.262073209475204\n ],\n [\n -117.31344382380401,\n 44.965776942074626\n ],\n [\n -121.44430319880412,\n 44.965776942074626\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
601 SW 2nd Avenue, Suite 1950
Portland, OR 97204
Observed links between parasites, such as ticks, and climate change have aroused concern for human health, wildlife population dynamics, and broader ecosystem effects. The one-host life history of the winter tick (Dermacentor albipictus) links each annual cohort to environmental conditions during three specific time periods when they are predictably vulnerable: spring detachment from hosts, summer larval stage, and fall questing for hosts. We used mixed-effects generalized linear models to investigate the drivers of tick loads carried by moose (Alces alces) relative to these time periods and across 750 moose, 10 years, and 16 study areas in the western United States. We tested for the effects of biotic factors (moose density, shared winter range, vegetation, migratory behavior) and weather conditions (temperature, snow, humidity) during each seasonal period when ticks are vulnerable and off-host. We found that warm climatic regions, warm seasonal periods across multiple partitions of the annual tick life cycle, and warm years relative to long-term averages each contributed to increased tick loads. We also found important effects of snow and other biotic factors such as host density and vegetation. Tick loads in the western United States were, on average, lower than those where tick-related die-offs in moose populations have occurred recently, but loads carried by some individuals may be sufficient to cause mortality. Lastly, we found interannual variation in tick loads to be most correlated with spring snowpack, suggesting this environmental component may have the highest potential to induce change in tick load dynamics in the immediate future of this region.
The Babouri-Figuil Basin (BFB) is a frontier basin for petroleum in Cameroon. It belongs to the series of Cretaceous rift basins of the West and Central Rift System (WCARS), the origin of which is related to the opening of the South Atlantic. Within the same rift system, commercial hydrocarbon accumulations have been discovered in Chad, Sudan, Niger and, more recently, in Nigeria (Gongola Basin). The study of the geology of the BFB just recently received considerable attention, mainly because of its presumed hydrocarbon potential. In the pursuit of researching possible petroleum systems in the BFB, the current study provides a first look into the characterization of source and reservoir rock and its integration into a 2D lithostratigraphic model. The study was solely based on outcrop samples. Black shale and massive claystone are good to excellent hydrocarbon source rocks [e.g., up to 38 wt% total organic carbon (TOC), up to 943 mg/g hydrogen index, up to 85 m thickness, up to 20–30 km lateral extension], with moderate to high values of extractable organic matter (e.g., >10,000 ppm). Calcareous claystone, on the other hand, are poor source rocks [e.g., <0.20 wt% TOC]. The samples are thermally immature, except for those located close to volcanic intrusion at Golombe that have reached the threshold for oil generation (Tmax >435 °C, production index >0.1). The petrographic analysis of sandstone revealed that they are fine-grained to coarse-grained, poorly to moderately sorted, texturally and compositionally immature to submature, subarkosic to arkosic arenites. The main diagenetic processes that affected sandstones are as follows: moderate to intense compaction characterized by the development of long, concavo-convex, and sutured contacts between grains; cementation through calcite, iron oxide, and quartz cements; alteration of mica and feldspar grains; partial to complete dissolution of feldspar, mica, amphibole grains, and calcite cement; and the replacement of feldspar and mica grains by clay minerals. Alteration and dissolution increase the porosity of sandstone through the creation of secondary pores. However, mechanical compaction through the development of a pseudomatrix and cementation as pore-filling materials have significantly reduced the quality of sandstone beds as conventional petroleum reservoirs. Hence, the best reservoir-quality sandstones in the basin are generally located in the upper portion of the basin in terms of its lithostratigraphic model. They are the cleanest sandstones with the smallest amount of cement and the lowest ductile grain content (pseudomatrix), with a thickness that varies from 3 m to 120 m and a lateral extension of 20 km. The lithostratigraphic model of the basin is characterized by an extensive lacustrine environment that provided a thick sequence of organic-rich formations; sand deposited as extensive reservoirs sandwiched between shale/claystone beds; the development of stratigraphic traps through lateral facies change; and the widespread deposition of lacustrine and floodplain claystone that provide regional seals. The similarities between the Babouri-Figuil Basin and proven petroleum systems in other WCARS rift basins suggest that the basin may host at least one petroleum system where actively generating source rocks are present.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2024.104491","usgsCitation":"Gaspard, M., Hatcherian, J.J., Hackley, P.C., Bessong, M., Bapowa, C., Pougue, H., and Meying, A., 2024, Novel insights about petroleum systems from source and reservoir rock characterization, Cretaceous Deposits, Babouri-Figuil Basin, Northern Cameroon: International Journal of Coal Geology, v. 285, 104491, 21 p., https://doi.org/10.1016/j.coal.2024.104491.","productDescription":"104491, 21 p.","ipdsId":"IP-158392","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":427402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Cameroon","otherGeospatial":"Babouri-Figuil Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 13.666,\n 9.85\n ],\n [\n 13.666,\n 9.633\n ],\n [\n 14.033,\n 9.633\n ],\n [\n 14.033,\n 9.85\n ],\n [\n 13.666,\n 9.85\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"285","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gaspard, Manga","contributorId":335306,"corporation":false,"usgs":false,"family":"Gaspard","given":"Manga","email":"","affiliations":[],"preferred":false,"id":898040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hatcherian, Javin J. 0000-0001-9151-6798 jhatcherian@usgs.gov","orcid":"https://orcid.org/0000-0001-9151-6798","contributorId":195770,"corporation":false,"usgs":true,"family":"Hatcherian","given":"Javin","email":"jhatcherian@usgs.gov","middleInitial":"J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":898041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":898039,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bessong, Moise","contributorId":335307,"corporation":false,"usgs":false,"family":"Bessong","given":"Moise","email":"","affiliations":[],"preferred":false,"id":898042,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bapowa, Carole","contributorId":335308,"corporation":false,"usgs":false,"family":"Bapowa","given":"Carole","email":"","affiliations":[],"preferred":false,"id":898043,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pougue, Henry","contributorId":335309,"corporation":false,"usgs":false,"family":"Pougue","given":"Henry","email":"","affiliations":[],"preferred":false,"id":898044,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meying, Arsene","contributorId":335311,"corporation":false,"usgs":false,"family":"Meying","given":"Arsene","email":"","affiliations":[],"preferred":false,"id":898045,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70261502,"text":"70261502 - 2024 - Changes in landscape and climate in Mexico and Texas reveal small effects on migratory habitat of monarch butterflies (Danaus plexippus)","interactions":[],"lastModifiedDate":"2024-12-13T14:14:04.429932","indexId":"70261502","displayToPublicDate":"2024-03-20T08:19:36","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Changes in landscape and climate in Mexico and Texas reveal small effects on migratory habitat of monarch butterflies (Danaus plexippus)","docAbstract":"The decline of the iconic monarch butterfly (Danaus plexippus) in North America has motivated research on the impacts of land use and land cover (LULC) change and climate variability on monarch habitat and population dynamics. We investigated spring and fall trends in LULC, milkweed and nectar resources over a 20-year period, and ~ 30 years of climate variables in Mexico and Texas, U.S. This region supports spring breeding, and spring and fall migration during the annual life cycle of the monarch. We estimated a − 2.9% decline in milkweed in Texas, but little to no change in Mexico. Fall and spring nectar resources declined < 1% in both study extents. Vegetation greenness increased in the fall and spring in Mexico while the other climate variables did not change in both Mexico and Texas. Monarch habitat in Mexico and Texas appears relatively more intact than in the midwestern, agricultural landscapes of the U.S. Given the relatively modest observed changes in nectar and milkweed, the relatively stable climate conditions, and increased vegetation greenness in Mexico, it seems unlikely that habitat loss (quantity or quality) in Mexico and Texas has caused large declines in population size or survival during migration.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-024-56693-z","usgsCitation":"Diffendorfer, J., Botello, F., Drummond, M.A., Ancona, Z.H., Corro, L.M., Thogmartin, W.E., Ibsen, P.C., Moreno-Sanchez, R., Lukens, L., and Sanchez-Cordero, V., 2024, Changes in landscape and climate in Mexico and Texas reveal small effects on migratory habitat of monarch butterflies (Danaus plexippus): Scientific Reports, v. 14, 6703, 13 p., https://doi.org/10.1038/s41598-024-56693-z.","productDescription":"6703, 13 p.","ipdsId":"IP-158913","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":467022,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-024-56693-z","text":"Publisher Index Page"},{"id":465063,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -98.8951121415543,\n 33.52250910960224\n ],\n [\n -98.8951121415543,\n 18.97741303295362\n ],\n [\n -93.69183868960087,\n 18.97741303295362\n ],\n [\n -93.69183868960087,\n 33.52250910960224\n ],\n [\n -98.8951121415543,\n 33.52250910960224\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","noUsgsAuthors":false,"publicationDate":"2024-03-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":920822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Botello, Francisco","contributorId":335190,"corporation":false,"usgs":false,"family":"Botello","given":"Francisco","email":"","affiliations":[{"id":36218,"text":"UNAM Mexico City","active":true,"usgs":false}],"preferred":false,"id":920823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drummond, Mark A. 0000-0001-7420-3503 madrummond@usgs.gov","orcid":"https://orcid.org/0000-0001-7420-3503","contributorId":3053,"corporation":false,"usgs":true,"family":"Drummond","given":"Mark","email":"madrummond@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":920824,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ancona, Zachary H. 0000-0001-5430-0218 zancona@usgs.gov","orcid":"https://orcid.org/0000-0001-5430-0218","contributorId":5578,"corporation":false,"usgs":true,"family":"Ancona","given":"Zachary","email":"zancona@usgs.gov","middleInitial":"H.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":920825,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Corro, Lucila Marie 0000-0001-5718-6713","orcid":"https://orcid.org/0000-0001-5718-6713","contributorId":335192,"corporation":false,"usgs":true,"family":"Corro","given":"Lucila","email":"","middleInitial":"Marie","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":920826,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":920827,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ibsen, Peter Christian 0000-0002-3436-9100","orcid":"https://orcid.org/0000-0002-3436-9100","contributorId":260735,"corporation":false,"usgs":true,"family":"Ibsen","given":"Peter","email":"","middleInitial":"Christian","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":920828,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Moreno-Sanchez, Rafael","contributorId":347104,"corporation":false,"usgs":false,"family":"Moreno-Sanchez","given":"Rafael","affiliations":[{"id":40160,"text":"UC Denver","active":true,"usgs":false}],"preferred":false,"id":920829,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lukens, Laura","contributorId":347105,"corporation":false,"usgs":false,"family":"Lukens","given":"Laura","affiliations":[{"id":83072,"text":"Monarch Joint Venture/Colorado State University","active":true,"usgs":false}],"preferred":false,"id":920830,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sanchez-Cordero, Victor","contributorId":347106,"corporation":false,"usgs":false,"family":"Sanchez-Cordero","given":"Victor","affiliations":[{"id":36218,"text":"UNAM Mexico City","active":true,"usgs":false}],"preferred":false,"id":920831,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70252087,"text":"sir20235134 - 2024 - Characterizing future streamflows in Massachusetts using stochastic modeling—A pilot study","interactions":[],"lastModifiedDate":"2026-01-30T19:34:44.108239","indexId":"sir20235134","displayToPublicDate":"2024-03-19T12:20:00","publicationYear":"2024","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":"2023-5134","displayTitle":"Characterizing Future Streamflows in Massachusetts Using Stochastic Modeling—A Pilot Study","title":"Characterizing future streamflows in Massachusetts using stochastic modeling—A pilot study","docAbstract":"Communities throughout Massachusetts face the potential effects of climate change, ranging from more extreme rainfall to more pronounced and frequent droughts. Understanding the effects of climate change on hydrology is important to State and community officials to evaluate the potential effects on infrastructure and water systems. To better understand the effects of climate change on hydrology, the U.S. Geological Survey, in partnership with Cornell University and Tufts University, conducted a study in cooperation with the Massachusetts Executive Office of Energy and Environmental Affairs to develop tools for projecting 21st-century climate and hydrologic characteristics in Massachusetts.
A stochastic weather generator was developed to project future climatic characteristics for Massachusetts. The stochastic weather generator estimates daily precipitation, minimum temperature, and maximum temperature for 17 warming scenarios (from 0 to 8 degrees Celsius, in 0.5-degree increments). To project future hydrologic characteristics, the stochastic weather generator output data were input to the Precipitation-Watershed Modeling System deterministic watershed model for the Squannacook River watershed, which is the watershed selected as the pilot study location for investigating future hydrologic characteristics. Hydrologic data output from the deterministic watershed model were then input to a stochastic watershed model developed for this study to correct model errors (model errors are often observed in the output from deterministic models at the high- and low-flow extremes). The output from the stochastic watershed model was then used to characterize hydrology for the 17 warming scenarios. For the Squannacook River watershed, the results project more extreme flood and low streamflows under the warming scenarios.
Output from the tools allows the characterization of future streamflows for the years 2030, 2050, 2070, and 2090, which expands our understanding of 21st-century climatic and hydrologic risk in Massachusetts. These tools could improve Federal, State, and community officials’ ability to mitigate the effects of climate change over the next several decades.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235134","collaboration":"Prepared in cooperation with the Massachusetts Executive Office of Energy and Environmental Affairs","usgsCitation":"Olson, S.A., Shabestanipour, G., Lamontagne, J., and Steinschneider, S., 2024, Characterizing future streamflows in Massachusetts using stochastic modeling—A pilot study: U.S. Geological Survey Scientific Investigations Report 2023–5134, 19 p., https://doi.org/10.3133/sir20235134.","productDescription":"Report: v, 19 p.; Data Release","numberOfPages":"19","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-149673","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":499396,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116176.htm","linkFileType":{"id":5,"text":"html"}},{"id":426599,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JHB2X2","text":"USGS data release","linkHelpText":"Data for a pilot study characterizing future climate and hydrology in Massachusetts"},{"id":426597,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5134/sir20235134.XML","description":"SIR 2023-5134 XML"},{"id":426596,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235134/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5134 HTML"},{"id":426595,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5134/sir20235134.pdf","text":"Report","size":"1.67 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5134 PDF"},{"id":426594,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5134/coverthb.jpg"},{"id":426598,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5134/images/"}],"country":"United States","state":"Massachusetts","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-70.827398,41.602067],[-70.823735,41.598569],[-70.820918,41.587673],[-70.821001,41.587268],[-70.821743,41.583656],[-70.82191,41.582841],[-70.830087,41.585385],[-70.837632,41.595374],[-70.838147,41.596056],[-70.838452,41.59646],[-70.834529,41.60261],[-70.832044,41.606504],[-70.831802,41.606272],[-70.828025,41.602666],[-70.827398,41.602067]]],[[[-70.59628,41.471905],[-70.57485,41.468259],[-70.567356,41.471208],[-70.56328,41.469127],[-70.553277,41.452955],[-70.552943,41.443394],[-70.555588,41.430882],[-70.553096,41.423952],[-70.547567,41.415831],[-70.538301,41.409241],[-70.528581,41.4051],[-70.517584,41.403769],[-70.506984,41.400242],[-70.502372,41.392005],[-70.501306,41.385391],[-70.498959,41.384339],[-70.490758,41.383634],[-70.484503,41.38629],[-70.472604,41.399128],[-70.473035,41.408757],[-70.470788,41.412875],[-70.463833,41.419145],[-70.450431,41.420703],[-70.446233,41.39648],[-70.449268,41.380422],[-70.448262,41.353651],[-70.451084,41.348161],[-70.496162,41.346452],[-70.538294,41.348958],[-70.599157,41.349272],[-70.709826,41.341723],[-70.733253,41.336226],[-70.747541,41.329952],[-70.764188,41.318706],[-70.768015,41.311959],[-70.766166,41.308962],[-70.768687,41.303702],[-70.775665,41.300982],[-70.802083,41.314207],[-70.819415,41.327212],[-70.838777,41.347209],[-70.833802,41.353386],[-70.812309,41.355745],[-70.800289,41.3538],[-70.783291,41.347829],[-70.774974,41.349176],[-70.768901,41.353246],[-70.729225,41.397728],[-70.724366,41.398942],[-70.712432,41.40885],[-70.711493,41.41546],[-70.701378,41.430925],[-70.686881,41.441334],[-70.64933,41.461068],[-70.603555,41.482384],[-70.598444,41.481151],[-70.59628,41.471905]]],[[[-70.092142,41.297741],[-70.082072,41.299093],[-70.062565,41.308726],[-70.046088,41.321651],[-70.031332,41.339332],[-70.028805,41.359919],[-70.030924,41.367453],[-70.035162,41.372161],[-70.038458,41.376399],[-70.045586,41.383598],[-70.049564,41.3879],[-70.049053,41.391702],[-70.033514,41.385816],[-70.018446,41.36863],[-69.960277,41.278731],[-69.960181,41.264546],[-69.964422,41.25457],[-69.965725,41.252466],[-69.975,41.247392],[-70.001586,41.239353],[-70.015225,41.237964],[-70.052807,41.242685],[-70.083239,41.2444],[-70.096967,41.24085],[-70.118669,41.242351],[-70.170681,41.255881],[-70.237175,41.282724],[-70.256164,41.288123],[-70.266776,41.294453],[-70.273478,41.301528],[-70.275526,41.310464],[-70.260632,41.310092],[-70.249276,41.305623],[-70.244435,41.303203],[-70.240153,41.295384],[-70.229541,41.290171],[-70.20869,41.290171],[-70.196304,41.294612],[-70.12446,41.293851],[-70.092142,41.297741]]],[[[-73.022903,42.741133],[-72.930261,42.73916],[-72.809113,42.736581],[-72.458519,42.726853],[-72.285954,42.721631],[-72.282981,42.721557],[-72.124526,42.717636],[-71.981402,42.713294],[-71.928811,42.712234],[-71.898716,42.71142],[-71.745817,42.707287],[-71.636214,42.704888],[-71.631814,42.704788],[-71.542533,42.702672],[-71.351874,42.698154],[-71.330206,42.69719],[-71.294205,42.69699],[-71.278929,42.711258],[-71.267905,42.72589],[-71.255605,42.736389],[-71.25518,42.73665],[-71.245504,42.742589],[-71.233404,42.745489],[-71.223904,42.746689],[-71.208302,42.743314],[-71.208227,42.743294],[-71.208137,42.743273],[-71.181803,42.73759],[-71.186104,42.790689],[-71.174403,42.801589],[-71.167703,42.807389],[-71.165603,42.808689],[-71.149703,42.815489],[-71.132503,42.821389],[-71.116048,42.817751],[-71.064201,42.806289],[-71.053601,42.833089],[-71.047501,42.844089],[-71.044401,42.848789],[-71.031201,42.859089],[-70.9665,42.868989],[-70.949199,42.876089],[-70.931699,42.884189],[-70.930799,42.884589],[-70.927629,42.885326],[-70.914899,42.886589],[-70.914886,42.886564],[-70.902768,42.88653],[-70.886136,42.88261],[-70.848625,42.860939],[-70.837376,42.864996],[-70.830795,42.868918],[-70.821769,42.87188],[-70.817296,42.87229],[-70.817731,42.850613],[-70.80522,42.781798],[-70.792867,42.747118],[-70.772267,42.711064],[-70.770453,42.704824],[-70.778552,42.69852],[-70.778671,42.693622],[-70.764421,42.68565],[-70.748752,42.683878],[-70.744427,42.682092],[-70.72982,42.669602],[-70.728845,42.663877],[-70.689402,42.653319],[-70.682594,42.654525],[-70.681594,42.662342],[-70.663548,42.677603],[-70.645101,42.689423],[-70.630077,42.692699],[-70.620031,42.688006],[-70.622864,42.67599],[-70.623815,42.665481],[-70.622791,42.660873],[-70.61482,42.65765],[-70.595474,42.660336],[-70.591742,42.648508],[-70.591469,42.639821],[-70.594014,42.63503],[-70.605611,42.634898],[-70.61842,42.62864],[-70.635635,42.600243],[-70.654727,42.582234],[-70.664887,42.580436],[-70.668022,42.581732],[-70.668115,42.585361],[-70.668488,42.589643],[-70.670442,42.592249],[-70.672583,42.594296],[-70.675747,42.594669],[-70.678819,42.594389],[-70.681428,42.593173],[-70.684502,42.588858],[-70.698574,42.577393],[-70.729688,42.57151],[-70.737044,42.576863],[-70.757283,42.570455],[-70.804091,42.561595],[-70.815391,42.554195],[-70.823291,42.551495],[-70.848492,42.550195],[-70.871382,42.546404],[-70.872357,42.542952],[-70.866279,42.522617],[-70.859751,42.520441],[-70.857125,42.521492],[-70.842091,42.519495],[-70.831091,42.503596],[-70.835991,42.490496],[-70.841591,42.487596],[-70.847391,42.491496],[-70.857791,42.490296],[-70.879692,42.478796],[-70.886493,42.470197],[-70.887992,42.467096],[-70.887292,42.464896],[-70.894292,42.460896],[-70.908092,42.466896],[-70.917693,42.467996],[-70.921993,42.466696],[-70.934993,42.457896],[-70.934264,42.444646],[-70.933155,42.437833],[-70.928226,42.430986],[-70.913192,42.427697],[-70.908392,42.425197],[-70.901992,42.420297],[-70.905692,42.416197],[-70.936393,42.418097],[-70.943295,42.436248],[-70.943612,42.452092],[-70.94702,42.456236],[-70.96047,42.446166],[-70.960647,42.443787],[-70.960835,42.441272],[-70.982994,42.423996],[-70.987694,42.416696],[-70.990595,42.407098],[-70.989195,42.402598],[-70.985068,42.402041],[-70.983426,42.396246],[-70.980336,42.391513],[-70.972706,42.389968],[-70.970195,42.388036],[-70.97174,42.387071],[-70.972513,42.385042],[-70.972706,42.381759],[-70.972223,42.377316],[-70.960798,42.360648],[-70.953292,42.349698],[-70.953022,42.343973],[-70.963578,42.34686],[-70.972418,42.353875],[-70.974897,42.355843],[-70.979927,42.356382],[-70.982282,42.35592],[-70.998253,42.352788],[-71.006877,42.347039],[-71.010146,42.339234],[-71.011804,42.335274],[-71.01568,42.326019],[-71.013165,42.315419],[-71.005399,42.307196],[-71.000948,42.302483],[-71.006158,42.28811],[-71.0049,42.28272],[-70.996097,42.271222],[-70.98909,42.267449],[-70.967351,42.268168],[-70.948971,42.272505],[-70.945547,42.269081],[-70.935886,42.264189],[-70.923169,42.263211],[-70.910941,42.265412],[-70.906302,42.271636],[-70.896267,42.2851],[-70.895778,42.292436],[-70.897123,42.29586],[-70.915588,42.302463],[-70.91749,42.305686],[-70.907556,42.307889],[-70.882764,42.30886],[-70.881242,42.300663],[-70.870873,42.285668],[-70.861807,42.275965],[-70.851093,42.26827],[-70.831075,42.267424],[-70.824661,42.265935],[-70.811742,42.262935],[-70.788724,42.25392],[-70.780722,42.251792],[-70.770964,42.249197],[-70.764757,42.244062],[-70.754488,42.228673],[-70.74723,42.221816],[-70.73056,42.21094],[-70.722269,42.207959],[-70.718707,42.184853],[-70.714301,42.168783],[-70.706264,42.163137],[-70.685315,42.133025],[-70.663931,42.108336],[-70.640169,42.088633],[-70.63848,42.081579],[-70.647349,42.076331],[-70.64819,42.068441],[-70.643208,42.050821],[-70.644337,42.045895],[-70.650874,42.046247],[-70.66936,42.037116],[-70.671666,42.02139],[-70.667512,42.01232],[-70.670934,42.007786],[-70.678798,42.00551],[-70.686798,42.012764],[-70.695809,42.013346],[-70.712204,42.007586],[-70.710034,41.999544],[-70.698981,41.987103],[-70.662476,41.960592],[-70.651673,41.958701],[-70.648365,41.961672],[-70.631251,41.950475],[-70.623513,41.943273],[-70.616491,41.940204],[-70.608166,41.940701],[-70.598078,41.947772],[-70.583572,41.950007],[-70.552941,41.929641],[-70.546386,41.916751],[-70.54741,41.911934],[-70.545949,41.907158],[-70.532084,41.889568],[-70.525567,41.85873],[-70.535487,41.839381],[-70.542065,41.831263],[-70.543168,41.824446],[-70.54103,41.815754],[-70.537289,41.810859],[-70.532656,41.804796],[-70.517411,41.790953],[-70.494048,41.773883],[-70.471552,41.761563],[-70.412476,41.744397],[-70.375341,41.738779],[-70.290957,41.734312],[-70.275203,41.726143],[-70.272289,41.721346],[-70.263654,41.714115],[-70.259205,41.713954],[-70.23485,41.733733],[-70.216073,41.742981],[-70.189254,41.751982],[-70.182076,41.750885],[-70.141533,41.760072],[-70.121978,41.758841],[-70.096061,41.766549],[-70.064314,41.772845],[-70.024734,41.787364],[-70.008462,41.800786],[-70.003842,41.80852],[-70.004486,41.838826],[-70.009013,41.876625],[-70.000188,41.886938],[-70.002922,41.890315],[-70.012154,41.891656],[-70.024335,41.89882],[-70.025553,41.911699],[-70.030537,41.929154],[-70.044995,41.930049],[-70.054464,41.927366],[-70.065671,41.911658],[-70.065723,41.899641],[-70.065372,41.887702],[-70.064084,41.878924],[-70.066002,41.877011],[-70.067566,41.877793],[-70.070889,41.882973],[-70.073039,41.899783],[-70.074006,41.93865],[-70.077421,41.985497],[-70.083775,42.012041],[-70.089578,42.024896],[-70.095595,42.032832],[-70.10806,42.043601],[-70.123043,42.051668],[-70.148294,42.06195],[-70.155415,42.062409],[-70.169781,42.059736],[-70.178468,42.05642],[-70.186816,42.05045],[-70.194456,42.03947],[-70.195345,42.034163],[-70.193074,42.027576],[-70.186295,42.021308],[-70.186708,42.019904],[-70.190834,42.020028],[-70.196693,42.022429],[-70.208016,42.03073],[-70.218701,42.045848],[-70.233256,42.057714],[-70.238875,42.060479],[-70.24354,42.060569],[-70.245385,42.063733],[-70.238087,42.072878],[-70.225626,42.078601],[-70.206899,42.0819],[-70.189305,42.082337],[-70.160166,42.078628],[-70.115968,42.067638],[-70.082624,42.054657],[-70.058531,42.040363],[-70.033501,42.017736],[-70.011898,41.98972],[-69.986085,41.949597],[-69.968598,41.9117],[-69.945314,41.845222],[-69.935952,41.809422],[-69.928652,41.74125],[-69.928261,41.6917],[-69.933114,41.670014],[-69.947599,41.645394],[-69.951169,41.640799],[-69.958272,41.639429],[-69.963234,41.633794],[-69.967869,41.627503],[-69.976478,41.603664],[-69.982768,41.581812],[-69.988215,41.554704],[-69.998071,41.54365],[-70.004136,41.54212],[-70.011504,41.542924],[-70.014456,41.545534],[-70.016584,41.550772],[-70.015059,41.553037],[-70.010644,41.552692],[-70.00153,41.561953],[-69.994357,41.576846],[-69.987192,41.608579],[-69.973035,41.641046],[-69.973153,41.646963],[-69.975719,41.653738],[-69.996359,41.667184],[-70.007011,41.671579],[-70.014211,41.671971],[-70.029346,41.667744],[-70.055523,41.664843],[-70.089238,41.662813],[-70.140877,41.650423],[-70.158621,41.650438],[-70.191061,41.645259],[-70.245867,41.628479],[-70.25621,41.620698],[-70.25542,41.617541],[-70.259601,41.610863],[-70.265424,41.609333],[-70.267587,41.610912],[-70.269687,41.617775],[-70.26913,41.625742],[-70.274522,41.632927],[-70.28132,41.635125],[-70.29062,41.635196],[-70.321588,41.630508],[-70.329924,41.634578],[-70.338067,41.636338],[-70.351634,41.634687],[-70.360352,41.631069],[-70.364892,41.626721],[-70.364744,41.623671],[-70.369854,41.615888],[-70.379151,41.611361],[-70.400581,41.606382],[-70.408535,41.607345],[-70.437246,41.605329],[-70.445289,41.591815],[-70.461278,41.57182],[-70.476256,41.558502],[-70.485571,41.554244],[-70.493244,41.552044],[-70.522327,41.548965],[-70.559689,41.54833],[-70.611081,41.542989],[-70.633607,41.538254],[-70.643627,41.532357],[-70.654104,41.519025],[-70.663856,41.514031],[-70.669518,41.513339],[-70.675379,41.512623],[-70.705181,41.496677],[-70.734306,41.486335],[-70.757171,41.469917],[-70.756481,41.465977],[-70.760863,41.460947],[-70.79027,41.446339],[-70.817478,41.445562],[-70.835867,41.441877],[-70.857528,41.425767],[-70.866946,41.422378],[-70.902763,41.421061],[-70.928197,41.415781],[-70.937282,41.411618],[-70.948431,41.409193],[-70.951045,41.411777],[-70.949861,41.415323],[-70.928165,41.431265],[-70.923698,41.430716],[-70.918983,41.4253],[-70.91164,41.424484],[-70.906011,41.425708],[-70.883247,41.432239],[-70.855265,41.448892],[-70.828546,41.456448],[-70.802186,41.460864],[-70.787769,41.474609],[-70.775268,41.477465],[-70.753905,41.492256],[-70.745053,41.500966],[-70.6948,41.52564],[-70.658659,41.543385],[-70.654302,41.549926],[-70.655365,41.557498],[-70.653899,41.56516],[-70.64878,41.56987],[-70.642748,41.572385],[-70.640948,41.577325],[-70.64204,41.583066],[-70.652449,41.60521],[-70.651986,41.610184],[-70.640003,41.624616],[-70.645251,41.633547],[-70.652614,41.637829],[-70.650419,41.644202],[-70.638695,41.649427],[-70.637632,41.654573],[-70.646308,41.678433],[-70.649285,41.680943],[-70.661475,41.681756],[-70.645962,41.693794],[-70.62544,41.698691],[-70.623652,41.707398],[-70.626529,41.712995],[-70.642914,41.71841],[-70.644641,41.71898],[-70.651093,41.715715],[-70.656596,41.715401],[-70.670453,41.721912],[-70.708193,41.730959],[-70.718739,41.73574],[-70.726331,41.732731],[-70.728933,41.723433],[-70.721302,41.712968],[-70.717451,41.69398],[-70.719575,41.685002],[-70.729395,41.68814],[-70.744396,41.696967],[-70.755347,41.694326],[-70.761481,41.676808],[-70.76236,41.667735],[-70.758198,41.661225],[-70.757622,41.654265],[-70.765463,41.641575],[-70.769318,41.641145],[-70.773654,41.645033],[-70.775798,41.649145],[-70.776709,41.650756],[-70.809118,41.656437],[-70.813286,41.65567],[-70.815729,41.652796],[-70.816351,41.645995],[-70.804664,41.641157],[-70.800215,41.631753],[-70.801063,41.629513],[-70.810279,41.624873],[-70.835296,41.624532],[-70.843177,41.628487],[-70.843522,41.62866],[-70.843528,41.628663],[-70.844165,41.628983],[-70.852518,41.626919],[-70.855031,41.624283],[-70.855162,41.624145],[-70.854232,41.618429],[-70.854211,41.618302],[-70.853445,41.613592],[-70.850181,41.593529],[-70.85222,41.589223],[-70.852488,41.588658],[-70.852551,41.588526],[-70.853121,41.587321],[-70.85324,41.587332],[-70.857239,41.587705],[-70.862852,41.600678],[-70.862998,41.601014],[-70.863486,41.602143],[-70.868501,41.613733],[-70.868904,41.614664],[-70.86836,41.622664],[-70.869624,41.625608],[-70.872665,41.627816],[-70.87904,41.629777],[-70.887643,41.632422],[-70.889209,41.632904],[-70.88926,41.632875],[-70.889594,41.632685],[-70.904513,41.624205],[-70.905765,41.623494],[-70.913202,41.619266],[-70.904522,41.610361],[-70.899981,41.593504],[-70.901381,41.592504],[-70.910814,41.595506],[-70.916581,41.607483],[-70.920074,41.61081],[-70.927172,41.611253],[-70.929722,41.609479],[-70.93,41.600441],[-70.927393,41.594064],[-70.931338,41.5842],[-70.937978,41.577416],[-70.941588,41.581034],[-70.946911,41.581089],[-70.948797,41.579038],[-70.9473,41.573659],[-70.93783,41.565239],[-70.931545,41.540169],[-70.941785,41.540121],[-70.979225,41.530427],[-70.983354,41.520616],[-71.003275,41.511912],[-71.019354,41.508857],[-71.035514,41.499047],[-71.058418,41.505967],[-71.085663,41.509292],[-71.12057,41.497448],[-71.1224,41.522156],[-71.131312,41.592308],[-71.131618,41.593918],[-71.137492,41.602561],[-71.138599,41.60347],[-71.140588,41.605102],[-71.14091,41.607405],[-71.141509,41.616076],[-71.140468,41.623893],[-71.135688,41.628402],[-71.134484,41.641198],[-71.134478,41.641262],[-71.13267,41.658744],[-71.132888,41.660102],[-71.134688,41.660502],[-71.135188,41.660502],[-71.14587,41.662795],[-71.153989,41.664102],[-71.17609,41.668102],[-71.17609,41.668502],[-71.17599,41.671402],[-71.18129,41.672502],[-71.191175,41.674292],[-71.191178,41.674216],[-71.194384,41.674803],[-71.19564,41.67509],[-71.224798,41.710498],[-71.225709,41.711603],[-71.261392,41.752301],[-71.31779,41.776099],[-71.317795,41.776101],[-71.327896,41.780501],[-71.329396,41.7826],[-71.329296,41.7868],[-71.332196,41.7923],[-71.333896,41.7945],[-71.335797,41.7948],[-71.339297,41.7963],[-71.340697,41.7983],[-71.340797,41.8002],[-71.339297,41.8044],[-71.339297,41.8065],[-71.338897,41.8083],[-71.339197,41.809],[-71.347197,41.8231],[-71.344897,41.828],[-71.339597,41.832],[-71.337597,41.8337],[-71.335197,41.8355],[-71.341797,41.8437],[-71.342198,41.8448],[-71.333997,41.8623],[-71.340798,41.8816],[-71.339298,41.893399],[-71.339298,41.893599],[-71.338698,41.898399],[-71.352699,41.896699],[-71.354699,41.896499],[-71.362499,41.895599],[-71.364699,41.895399],[-71.365399,41.895299],[-71.370999,41.894599],[-71.373799,41.894399],[-71.3766,41.893999],[-71.3817,41.893199],[-71.3817,41.922699],[-71.3816,41.922899],[-71.381401,41.964799],[-71.381501,41.966699],[-71.381466,41.984998],[-71.381401,42.018798],[-71.458104,42.017762],[-71.498258,42.01722],[-71.499905,42.017198],[-71.500905,42.017098],[-71.527306,42.015098],[-71.527606,42.014998],[-71.559439,42.014342],[-71.576908,42.014098],[-71.76601,42.009745],[-71.799242,42.008065],[-71.80065,42.023569],[-71.89078,42.024368],[-71.987326,42.02688],[-72.063496,42.027347],[-72.102162,42.028899],[-72.135687,42.030245],[-72.135715,42.030245],[-72.249523,42.031626],[-72.317148,42.031907],[-72.45668,42.033999],[-72.509192,42.034217],[-72.528131,42.034295],[-72.573231,42.030141],[-72.582332,42.024695],[-72.590233,42.024695],[-72.606933,42.024995],[-72.607933,42.030795],[-72.643134,42.032395],[-72.695927,42.036788],[-72.714134,42.036608],[-72.755838,42.036195],[-72.757538,42.033295],[-72.753538,42.032095],[-72.751738,42.030195],[-72.754038,42.025395],[-72.757467,42.020947],[-72.758151,42.020865],[-72.760558,42.021846],[-72.762151,42.021527],[-72.76231,42.019775],[-72.761354,42.018183],[-72.759738,42.016995],[-72.761238,42.014595],[-72.763238,42.012795],[-72.763265,42.009742],[-72.766139,42.007695],[-72.766739,42.002995],[-72.774757,42.002129],[-72.816741,41.997595],[-72.813541,42.036494],[-72.847142,42.036894],[-72.863619,42.037709],[-72.863733,42.03771],[-72.999549,42.038653],[-73.008745,42.03886],[-73.053254,42.039861],[-73.127276,42.041964],[-73.229798,42.044877],[-73.231056,42.044945],[-73.293097,42.04694],[-73.29442,42.046984],[-73.432812,42.050587],[-73.487314,42.049638],[-73.496879,42.049675],[-73.508142,42.086257],[-73.352527,42.510002],[-73.264957,42.74594],[-73.022903,42.741133]]]]},\"properties\":{\"name\":\"Massachusetts\",\"nation\":\"USA \"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Human populations have utilized heavy metals and persistent organic pollutants for their physiochemical properties in industrial, agricultural, and consumer goods for decades. Limited knowledge on their persistence and toxicological effects has resulted in organisms being exposed to some of the most problematic compounds ever generated by humans. Although overlap in exposure paradigms exists for historical and emerging contaminants, the different physiochemical properties, sources into the environment, and bioactivity of contaminants of emerging concern (CECs) have highlighted the importance of characterizing their risk to aquatic wildlife under chronic low-dose exposure scenarios. This chapter defines the fundamental terminology associated with characterizing the exposure paradigm in ecological risk assessment. The different sources and fate, routes of exposure, and biotransformation of common contaminants are covered using model chemicals to emphasize important factors that affect their partitioning among different environmental matrices. Finally, this chapter concludes with a discussion about bioaccumulation models and an example of how two similar CECs demonstrate different clearance rates and bioaccumulation potentials in fish.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Aquatic ecotoxicology","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-031-53130-9_8","usgsCitation":"Saari, G.N., Siddiqui, S., and Brander, S.M., 2024, Partitioning of chemicals in aquatic organisms, chap. of Aquatic ecotoxicology, p. 115-130, https://doi.org/10.1007/978-3-031-53130-9_8.","productDescription":"16 p.","startPage":"115","endPage":"130","ipdsId":"IP-146203","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":433696,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2024-03-19","publicationStatus":"PW","contributors":{"editors":[{"text":"Siddiqui, Samreen","contributorId":298402,"corporation":false,"usgs":false,"family":"Siddiqui","given":"Samreen","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":912940,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Brander, Susanne M.","contributorId":187546,"corporation":false,"usgs":false,"family":"Brander","given":"Susanne","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":912941,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Saari, Gavin N. 0000-0002-3593-5127 gsaari@usgs.gov","orcid":"https://orcid.org/0000-0002-3593-5127","contributorId":289203,"corporation":false,"usgs":true,"family":"Saari","given":"Gavin","email":"gsaari@usgs.gov","middleInitial":"N.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":912888,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siddiqui, Samreen","contributorId":298402,"corporation":false,"usgs":false,"family":"Siddiqui","given":"Samreen","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":912889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brander, Susanne M.","contributorId":187546,"corporation":false,"usgs":false,"family":"Brander","given":"Susanne","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":912890,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70252168,"text":"ofr20241011 - 2024 - Summary of Creepmeter Data from 1980 to 2020—Measurements Spanning the Hayward, Calaveras, and San Andreas Faults in Northern and Central California","interactions":[],"lastModifiedDate":"2026-01-28T18:05:08.13879","indexId":"ofr20241011","displayToPublicDate":"2024-03-18T11:51:10","publicationYear":"2024","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":"2024-1011","displayTitle":"Summary of Creepmeter Data from 1980 to 2020—Measurements Spanning the Hayward, Calaveras, and San Andreas Faults in Northern and Central California","title":"Summary of Creepmeter Data from 1980 to 2020—Measurements Spanning the Hayward, Calaveras, and San Andreas Faults in Northern and Central California","docAbstract":"This report is an update to the presentation by Schulz (1989) introducing potential users to the creepmeter data collected between the publication of Schulz’s report and mid-2020. The creepmeter network monitors aseismic, surface slip at various locations on the Hayward, Calaveras, and San Andreas Faults in northern and central California. There are different designs of creepmeters and these are briefly described. For a majority of the creepmeters, these data are automatically sent to the U.S. Geological Survey (USGS) offices where they are stored and processed. In addition, for most of the creepmeters, occasional manual measurements are made and these are compared with digitally recorded data. For some sites, the comparisons indicated degradation of the electronic sensor and consequently corrections are made to the digital data. The largest transient deformation is that which followed the 2004, M6, Parkfield earthquake. Various functions found in the literature that have been used to model postseismic slip were tested with the observed postseismic behavior seen on the creepmeters in the vicinity of Parkfield, California. No single function adequately fit all the data from these Parkfield instruments. This report is a discussion and analysis of data from creepmeters deployed by the USGS. The discussion primarily focuses on instruments that are currently operating in 2020 or have operated quite recently but are no longer in service.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241011","usgsCitation":"Langbein, J., Bilham, R.G., Snyder, H.A., and Ericksen, T., 2024, Summary of Creepmeter Data from 1980 to 2020—Measurements Spanning the Hayward, Calaveras, and San Andreas Faults in Northern and Central California: U.S. Geological Survey Report 2024–1011, 110 p., https://doi.org/10.3133/ofr20241011.","productDescription":"vi, 110 p.","numberOfPages":"110","onlineOnly":"Y","ipdsId":"IP-143918","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":499206,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116172.htm","linkFileType":{"id":5,"text":"html"}},{"id":426750,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1011/ofr20241011.pdf","text":"Report","size":"60 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":426749,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1011/covrthb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.83784784258054,\n 37.99394764431494\n ],\n [\n -122.83784784258054,\n 34.52234572819374\n ],\n [\n -119.36616815508066,\n 34.52234572819374\n ],\n [\n -119.36616815508066,\n 37.99394764431494\n ],\n [\n -122.83784784258054,\n 37.99394764431494\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Earthquake Science Center
U.S. Geological Survey
350 N. Akron Rd.
Moffett Field, CA 94035
A massive bloom of the raphidophyte Heterosigma akashiwo occurred in summer 2022 in San Francisco Bay, causing widespread ecological impacts including events of low dissolved oxygen and mass fish kills. The rapidly evolving bloom required equally rapid management response, leading to the use of near-real-time image analysis of chlorophyll from the Ocean and Land Colour Instrument (OLCI) aboard Sentinel-3. Standard algorithms failed to adequately capture the bloom, signifying a need to refine a two-band algorithm developed for coastal and inland waters that relates the red-edge part of the remote sensing reflectance spectrum to chlorophyll. While the bloom was the initial motivation for optimizing this algorithm, an extensive dataset of in-water validation measurements from both bloom and non-bloom periods was used to evaluate performance over a range of concentrations and community composition. The modified red-edge algorithm with a simplified atmospheric correction scheme outperformed existing standard products across diverse conditions, and given the modest computational requirements, was found suitable for operational use and near-real-time product generation. The final version of the algorithm successfully minimizes error for non-bloom periods when chlorophyll a is typically <30 mg m−3, while also capturing bloom periods of >100 mg m−3 chlorophyll a.
","language":"English","publisher":"MDPI","doi":"10.3390/rs16061103","usgsCitation":"Kudela, R.M., Senn, D.B., Richardson, E.T., Bouma-Gregson, K., Bergamaschi, B.A., and Sim, L., 2024, Evaluation and refinement of chlorophyll-a algorithms for high-biomass blooms in San Francisco Bay (USA): Remote Sensing, v. 16, no. 6, 1103, 15 p., https://doi.org/10.3390/rs16061103.","productDescription":"1103, 15 p.","ipdsId":"IP-160723","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":440089,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs16061103","text":"Publisher Index Page"},{"id":435018,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GXJHZ3","text":"USGS data release","linkHelpText":"Assessing spatial variability of nutrients, phytoplankton, and related water-quality constituents in the San Francisco Bay, California: 2021-2022 High-resolution mapping surveys"},{"id":427314,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.07594813067364,\n 37.409521554962424\n ],\n [\n -122.01459141030173,\n 37.543473010939294\n ],\n [\n -122.3138751078345,\n 37.9439399615851\n ],\n [\n -122.2371288097209,\n 38.076947981745235\n ],\n [\n -122.4289707157553,\n 38.1493978144897\n ],\n [\n -122.49802549540809,\n 38.08298835733879\n ],\n [\n -122.5286656402067,\n 37.93788689033987\n ],\n [\n -122.4673236665621,\n 37.792501512759955\n ],\n [\n -122.35216906140471,\n 37.610380642182776\n ],\n [\n -122.07594813067364,\n 37.409521554962424\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-03-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Kudela, Raphael M.","contributorId":205181,"corporation":false,"usgs":false,"family":"Kudela","given":"Raphael","email":"","middleInitial":"M.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":897798,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senn, David B.","contributorId":205182,"corporation":false,"usgs":false,"family":"Senn","given":"David","email":"","middleInitial":"B.","affiliations":[{"id":12703,"text":"San Francisco Estuary Institute","active":true,"usgs":false}],"preferred":false,"id":897799,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richardson, Emily T. 0000-0003-2696-8266","orcid":"https://orcid.org/0000-0003-2696-8266","contributorId":304430,"corporation":false,"usgs":true,"family":"Richardson","given":"Emily","email":"","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":897800,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bouma-Gregson, Keith 0000-0002-0304-6034","orcid":"https://orcid.org/0000-0002-0304-6034","contributorId":311235,"corporation":false,"usgs":true,"family":"Bouma-Gregson","given":"Keith","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":897801,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":897802,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sim, Lawrence","contributorId":168731,"corporation":false,"usgs":false,"family":"Sim","given":"Lawrence","email":"","affiliations":[{"id":12703,"text":"San Francisco Estuary Institute","active":true,"usgs":false}],"preferred":false,"id":897803,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70252252,"text":"70252252 - 2024 - New diagnostic assessment of MCMC algorithm effectiveness, efficiency, reliability, and controllability","interactions":[],"lastModifiedDate":"2024-03-26T15:03:05.007788","indexId":"70252252","displayToPublicDate":"2024-03-18T06:42:07","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17179,"text":"IEEE Access","active":true,"publicationSubtype":{"id":10}},"title":"New diagnostic assessment of MCMC algorithm effectiveness, efficiency, reliability, and controllability","docAbstract":"Predator species can indirectly affect prey species through the cost of anti-predator behavior responses, which may involve shifts in occupancy, space use, or movement. Quantifying the various strategies implemented by prey species to avoid adverse interactions with predators can lead to a better understanding of potential population-level repercussions. Therefore, the purpose of this study was to examine predator–prey interactions by quantifying the effect of predator species presence on detection rates of prey species, using coyotes (Canis latrans) and white-tailed deer (Odocoileus virginianus) in Central Appalachian forests of the eastern United States as a model predator–prey system. To test two competing hypotheses related to interspecific interactions, we modeled species detections from 319 camera traps with a two-species occupancy model that incorporated a continuous-time detection process. We found that white-tailed deer occupancy was independent of coyote occupancy, but white-tailed deer were more frequently detectable and had greater detection intensity at sites where coyotes were present, regardless of vegetation-related covariates. In addition, white-tailed deer detection rates at sites with coyotes were highest when presumed forage availability was relatively low. These findings suggest that white-tailed deer may be exhibiting an active avoidance behavioral response to predators by increasing movement rates when coyotes are present in an area, perhaps due to reactive evasive maneuvers and/or proactive attempts to reduce adverse encounters with them. Concurrently, coyotes could be occupying sites with higher white-tailed deer densities. Because white-tailed deer did not exhibit significant shifts in daily activity patterns based on coyote occupancy, we further suggest that white-tailed deer in our study system generally do not use temporal partitioning as their primary strategy for avoiding encounters with coyotes. Overall, our study implements a recently developed analytical approach for modeling multi-species occupancy from camera traps and provides novel ecological insight into the complex relationships between predator and prey species.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.11149","usgsCitation":"Clipp, H.L., Pesi, S.M., Miller, M.L., Gigliotti, L., Skelly, B.P., and Rota, C., 2024, White-tailed deer detection rates increase when coyotes are present: Ecology and Evolution, v. 14, no. 3, e11149, 13 pp., https://doi.org/10.1002/ece3.11149.","productDescription":"e11149, 13 pp.","ipdsId":"IP-157302","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":440105,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.11149","text":"Publisher Index Page"},{"id":433571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.4877790212181,\n 39.94978819373756\n ],\n [\n -82.01878727948417,\n 39.01317775882444\n ],\n [\n -82.58830516880357,\n 38.2047845680037\n ],\n [\n -79.5468825034643,\n 37.66652638635898\n ],\n [\n -77.96682473836029,\n 39.5141262945331\n ],\n [\n -76.37907636338417,\n 40.11338027059526\n ],\n [\n -77.28462588707731,\n 41.09189702989761\n ],\n [\n -80.4877790212181,\n 39.94978819373756\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Clipp, Hannah L.","contributorId":342785,"corporation":false,"usgs":false,"family":"Clipp","given":"Hannah","email":"","middleInitial":"L.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":910392,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pesi, Sarah M.","contributorId":342786,"corporation":false,"usgs":false,"family":"Pesi","given":"Sarah","email":"","middleInitial":"M.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":910393,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Madison L.","contributorId":342787,"corporation":false,"usgs":false,"family":"Miller","given":"Madison","email":"","middleInitial":"L.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":910394,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gigliotti, Laura C. 0000-0002-6390-4133","orcid":"https://orcid.org/0000-0002-6390-4133","contributorId":200327,"corporation":false,"usgs":false,"family":"Gigliotti","given":"Laura C.","affiliations":[],"preferred":false,"id":910395,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Skelly, Brett P.","contributorId":342789,"corporation":false,"usgs":false,"family":"Skelly","given":"Brett","email":"","middleInitial":"P.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":910396,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rota, Christopher T.","contributorId":342791,"corporation":false,"usgs":false,"family":"Rota","given":"Christopher T.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":910397,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70252441,"text":"70252441 - 2024 - Data-driven adjustments for combined use of NGA-East hard-rock ground motion and site amplification models","interactions":[],"lastModifiedDate":"2024-05-07T14:35:47.184916","indexId":"70252441","displayToPublicDate":"2024-03-17T08:31:39","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Data-driven adjustments for combined use of NGA-East hard-rock ground motion and site amplification models","docAbstract":"Model development in the Next Generation Attenuation-East (NGA-East) project included two components developed concurrently and independently: (1) earthquake ground-motion models (GMMs) that predict the median and aleatory variability of various intensity measures conditioned on magnitude and distance, derived for a reference hard-rock site condition with an average shear-wave velocity in the upper 30 m (VS30) = 3000 m/s; and (2) a site amplification model that modifies intensity measures for softer site conditions. We investigate whether these models, when used in tandem, are compatible with ground-motion recordings in central and eastern North America (CENA) using an expanded version of the NGA-East database that includes new events from November 2011 (end date of NGA-East data curation) to April 2022. Following this expansion, the data set has 187 events, 2096 sites, and 16,272 three-component recordings, although the magnitude range remains limited (∼4 to 5.8). We compute residuals using 17 NGA-East GMMs and three data selection criteria that reflect within-CENA regional variations in ground-motion attributes. Mixed-effects regression of the residuals reveals a persistent pattern in which ground motions are overpredicted at short periods (0.01–0.6 s, including peak ground acceleration (PGA)) and underpredicted at longer periods. These misfits are regionally variable, with the Texas–Oklahoma–Kansas region having larger absolute misfits than other parts of CENA. Two factors potentially influencing these misfits are (1) differences in the site amplification models used to adjust the data to the reference condition during NGA-East GMM development relative to CENA amplification models applied since the 2018 National Seismic Hazard Model (NSHM), and (2) potential bias in simulation-based factors used to adjust ground motions from the hard-rock reference condition to a VS30 = 760 m/s condition. We provide adjustment factors and their epistemic uncertainties and discuss implications for applications.
","language":"English","publisher":"Sage Journals","doi":"10.1177/87552930241231825","usgsCitation":"Ramos-Sepulveda, M.E., Stewart, J.P., Parker, G.A., Moschetti, M.P., Thompson, E.M., Brandenberg, S.J., Hashash, Y.M., and Rathje, E., 2024, Data-driven adjustments for combined use of NGA-East hard-rock ground motion and site amplification models: Earthquake Spectra, v. 40, no. 2, p. 1132-1157, https://doi.org/10.1177/87552930241231825.","productDescription":"26 p.","startPage":"1132","endPage":"1157","ipdsId":"IP-153071","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":440108,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/87552930241231825","text":"Publisher Index Page"},{"id":426964,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas, Oklahoma, Texas","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-102.04224,36.993083],[-102.051744,40.003078],[-95.30829,39.999998],[-95.302507,39.984357],[-95.250254,39.948644],[-95.204428,39.938949],[-95.201935,39.904053],[-95.149657,39.905948],[-95.128166,39.874165],[-95.081534,39.861718],[-95.042142,39.864805],[-95.013152,39.899953],[-94.95154,39.900533],[-94.929574,39.888754],[-94.939767,39.85193],[-94.916918,39.836138],[-94.886933,39.833098],[-94.875944,39.813294],[-94.890292,39.791626],[-94.925605,39.789754],[-94.935782,39.778906],[-94.906244,39.759418],[-94.865243,39.770094],[-94.862943,39.742994],[-94.899316,39.724042],[-94.944741,39.744377],[-94.965318,39.739065],[-94.971317,39.68641],[-95.024595,39.668485],[-95.053367,39.630347],[-95.049277,39.589583],[-95.069315,39.576218],[-95.103228,39.577783],[-95.113077,39.559133],[-95.109304,39.542285],[-95.052177,39.499996],[-95.04078,39.466387],[-94.982144,39.440552],[-94.972952,39.421705],[-94.947864,39.408604],[-94.942039,39.389499],[-94.92311,39.384492],[-94.894979,39.393565],[-94.880979,39.383899],[-94.88136,39.370383],[-94.910641,39.348335],[-94.905329,39.311952],[-94.887056,39.28648],[-94.831471,39.256273],[-94.825663,39.241729],[-94.834896,39.223842],[-94.823791,39.209874],[-94.781518,39.206146],[-94.763138,39.179903],[-94.741938,39.170203],[-94.680336,39.184303],[-94.663835,39.179103],[-94.662435,39.157603],[-94.596033,39.157703],[-94.589933,39.140403],[-94.607354,39.113444],[-94.611908,38.609272],[-94.617919,36.499414],[-94.431822,35.397652],[-94.485875,33.637867],[-94.448637,33.642766],[-94.461129,33.625415],[-94.452961,33.616986],[-94.471152,33.601588],[-94.430039,33.591124],[-94.413155,33.569368],[-94.379649,33.580607],[-94.380091,33.568943],[-94.399227,33.559903],[-94.386086,33.544923],[-94.355945,33.54318],[-94.345513,33.567313],[-94.32366,33.549835],[-94.309582,33.551673],[-94.287025,33.58241],[-94.280849,33.577187],[-94.290901,33.558872],[-94.27909,33.557026],[-94.240179,33.589536],[-94.251569,33.558188],[-94.226392,33.552912],[-94.208078,33.566911],[-94.196395,33.555123],[-94.192483,33.570425],[-94.216141,33.576392],[-94.214431,33.583187],[-94.194465,33.582886],[-94.183913,33.594682],[-94.162266,33.588906],[-94.156782,33.575749],[-94.14216,33.58139],[-94.151257,33.571793],[-94.136864,33.571],[-94.128658,33.550952],[-94.119902,33.566999],[-94.082641,33.575492],[-94.055663,33.561887],[-94.073744,33.558285],[-94.069092,33.553406],[-94.04345,33.552253],[-94.041833,31.992402],[-94.018664,31.990843],[-93.971712,31.920384],[-93.938002,31.906917],[-93.927672,31.891497],[-93.901173,31.885958],[-93.874822,31.840611],[-93.874761,31.821661],[-93.839951,31.798597],[-93.822598,31.773559],[-93.830647,31.745811],[-93.802452,31.693186],[-93.826462,31.666919],[-93.816838,31.622509],[-93.838057,31.606795],[-93.834924,31.586211],[-93.798087,31.534044],[-93.746826,31.526008],[-93.726736,31.5116],[-93.749476,31.46869],[-93.70093,31.437784],[-93.704879,31.410881],[-93.674117,31.397681],[-93.664665,31.357698],[-93.687851,31.309835],[-93.642516,31.269508],[-93.620343,31.271025],[-93.600308,31.176158],[-93.588503,31.165581],[-93.552649,31.185575],[-93.531744,31.180817],[-93.551693,31.097258],[-93.52301,31.065241],[-93.531219,31.051678],[-93.516943,31.032584],[-93.539526,31.008498],[-93.562626,31.005995],[-93.571906,30.987614],[-93.526245,30.939411],[-93.567788,30.888302],[-93.553626,30.83514],[-93.561666,30.807739],[-93.584265,30.796663],[-93.592828,30.763986],[-93.619129,30.742002],[-93.609544,30.723139],[-93.629904,30.67994],[-93.654971,30.670184],[-93.6831,30.640763],[-93.681235,30.596102],[-93.712454,30.588479],[-93.727844,30.57407],[-93.729195,30.544842],[-93.740253,30.539569],[-93.714322,30.518562],[-93.716678,30.494006],[-93.697828,30.443838],[-93.702665,30.429947],[-93.757654,30.390423],[-93.765822,30.333318],[-93.706608,30.281187],[-93.705519,30.244185],[-93.720946,30.209852],[-93.688212,30.141376],[-93.698276,30.138608],[-93.702436,30.112721],[-93.732485,30.088914],[-93.699396,30.05925],[-93.720805,30.053043],[-93.739734,30.023987],[-93.786935,29.99058],[-93.838374,29.882855],[-93.927992,29.80964],[-93.926504,29.78956],[-93.893862,29.767289],[-93.891637,29.744618],[-93.873941,29.73777],[-93.837971,29.690619],[-93.852868,29.675885],[-94.001406,29.681486],[-94.132577,29.646217],[-94.631084,29.451464],[-94.694158,29.415632],[-94.731047,29.369141],[-94.778691,29.361483],[-94.783131,29.375642],[-94.706365,29.436805],[-94.681541,29.471389],[-94.608557,29.483345],[-94.594211,29.492127],[-94.591407,29.513858],[-94.566674,29.531988],[-94.532348,29.5178],[-94.495025,29.525031],[-94.503429,29.54325],[-94.522421,29.545672],[-94.553988,29.573882],[-94.740699,29.525858],[-94.779674,29.530533],[-94.78954,29.546494],[-94.755237,29.562782],[-94.708741,29.625226],[-94.693154,29.694453],[-94.695317,29.723052],[-94.735271,29.785433],[-94.816085,29.75671],[-94.851108,29.721373],[-94.872551,29.67125],[-94.893107,29.661336],[-94.921318,29.658178],[-94.936089,29.692704],[-94.965963,29.70033],[-95.013777,29.644322],[-95.013623,29.62979],[-94.984831,29.604361],[-95.016889,29.548303],[-94.981916,29.511141],[-94.909898,29.49691],[-94.930861,29.450504],[-94.8908,29.433432],[-94.893994,29.30817],[-94.921593,29.281556],[-94.952526,29.290122],[-95.099101,29.173529],[-95.151925,29.151162],[-95.16525,29.113566],[-95.136221,29.084537],[-94.879239,29.285839],[-94.824953,29.306005],[-94.822307,29.344254],[-94.810696,29.353435],[-94.784895,29.335535],[-94.72253,29.331446],[-95.081773,29.111222],[-95.125134,29.067321],[-95.238924,28.988644],[-95.38239,28.866348],[-95.439594,28.859022],[-95.812504,28.664942],[-96.220376,28.491966],[-96.371117,28.397661],[-96.378616,28.383909],[-96.37596,28.401682],[-96.335119,28.437795],[-96.223825,28.495067],[-96.21505,28.509679],[-95.98616,28.606319],[-95.978526,28.650594],[-95.996338,28.658736],[-96.006516,28.648049],[-96.047737,28.649067],[-96.228909,28.580873],[-96.233998,28.596649],[-96.212624,28.622604],[-96.230944,28.641433],[-96.19125,28.69436],[-96.222802,28.698431],[-96.287942,28.683164],[-96.304227,28.671459],[-96.303718,28.644996],[-96.373439,28.626675],[-96.487943,28.569677],[-96.485907,28.607845],[-96.510844,28.61497],[-96.497612,28.625148],[-96.499648,28.635835],[-96.563262,28.644487],[-96.572931,28.667897],[-96.561226,28.696395],[-96.584091,28.722798],[-96.645867,28.710457],[-96.664534,28.696904],[-96.635018,28.668914],[-96.634,28.654665],[-96.61059,28.638889],[-96.622804,28.622095],[-96.611099,28.585962],[-96.565297,28.5824],[-96.561226,28.570695],[-96.526111,28.557972],[-96.505755,28.525911],[-96.419749,28.467387],[-96.403973,28.44245],[-96.59176,28.357462],[-96.672677,28.335579],[-96.705247,28.348811],[-96.700158,28.369676],[-96.710336,28.406827],[-96.768352,28.410389],[-96.790235,28.383926],[-96.791761,28.31217],[-96.809573,28.290287],[-96.787181,28.255681],[-96.800413,28.224128],[-96.934765,28.123873],[-97.007539,28.136087],[-97.027014,28.148408],[-97.021303,28.1841],[-97.037008,28.185528],[-97.153601,28.13318],[-97.214039,28.087494],[-97.21535,28.076575],[-97.176444,28.059892],[-97.137421,28.057037],[-97.025693,28.11216],[-97.035528,28.084688],[-97.025859,28.041939],[-97.129168,27.919801],[-97.186709,27.825453],[-97.225176,27.825723],[-97.250797,27.876035],[-97.272253,27.881427],[-97.325097,27.867893],[-97.379042,27.837867],[-97.393291,27.782905],[-97.368355,27.741683],[-97.316446,27.712676],[-97.253955,27.696696],[-97.296598,27.613947],[-97.294054,27.5941],[-97.321535,27.571199],[-97.401942,27.335574],[-97.420263,27.317254],[-97.482859,27.297915],[-97.508304,27.275014],[-97.532223,27.278577],[-97.546981,27.290791],[-97.498126,27.308602],[-97.502706,27.322343],[-97.483877,27.338628],[-97.48693,27.358984],[-97.501688,27.366618],[-97.609068,27.285193],[-97.63146,27.28621],[-97.640111,27.270943],[-97.628916,27.242953],[-97.54291,27.229213],[-97.42408,27.264073],[-97.443673,27.116235],[-97.461739,27.095624],[-97.480569,27.102494],[-97.495836,27.094098],[-97.493291,27.078067],[-97.477515,27.066108],[-97.48693,27.057711],[-97.486676,27.03481],[-97.473444,27.02285],[-97.478533,26.999186],[-97.536803,26.999695],[-97.555378,26.99028],[-97.555378,26.93888],[-97.540874,26.90631],[-97.563266,26.842188],[-97.509831,26.803511],[-97.484385,26.763562],[-97.471663,26.758727],[-97.445708,26.609362],[-97.416955,26.553637],[-97.430696,26.506563],[-97.42637,26.484425],[-97.441383,26.455418],[-97.411612,26.447275],[-97.42179,26.417249],[-97.406014,26.409107],[-97.395072,26.417249],[-97.369627,26.394603],[-97.388965,26.36585],[-97.391001,26.332262],[-97.358176,26.356435],[-97.330441,26.350582],[-97.352833,26.318521],[-97.343927,26.267376],[-97.311866,26.273737],[-97.307031,26.253126],[-97.32128,26.228699],[-97.296598,26.200709],[-97.306776,26.159487],[-97.282094,26.120301],[-97.295072,26.108342],[-97.270898,26.086459],[-97.199651,26.077044],[-97.195071,26.04193],[-97.224842,26.027426],[-97.219244,25.996128],[-97.208557,25.991802],[-97.167208,26.007069],[-97.162628,26.023482],[-97.18273,26.053126],[-97.152009,26.062108],[-97.146294,25.955606],[-97.156608,25.949022],[-97.178362,25.962114],[-97.229226,25.958753],[-97.248033,25.948097],[-97.276707,25.952147],[-97.277163,25.935438],[-97.350398,25.925241],[-97.37443,25.907444],[-97.360082,25.868874],[-97.372864,25.840117],[-97.422636,25.840378],[-97.445113,25.850026],[-97.454727,25.879337],[-97.521762,25.886458],[-97.546421,25.934077],[-97.582565,25.937857],[-97.583044,25.955443],[-97.598043,25.957556],[-97.649176,26.021499],[-97.758838,26.032131],[-97.789823,26.04246],[-97.801344,26.060017],[-97.860504,26.052918],[-97.88653,26.066339],[-97.93542,26.052688],[-97.950095,26.061828],[-97.967358,26.051718],[-97.981335,26.067182],[-98.028759,26.06647],[-98.039239,26.041275],[-98.070021,26.047992],[-98.084755,26.070808],[-98.091038,26.059169],[-98.105505,26.067537],[-98.146622,26.049412],[-98.177897,26.074672],[-98.197046,26.056153],[-98.220673,26.076467],[-98.248806,26.073101],[-98.264514,26.085507],[-98.277218,26.098802],[-98.265698,26.12037],[-98.296195,26.120321],[-98.302979,26.11005],[-98.323828,26.121249],[-98.335204,26.137617],[-98.336837,26.166432],[-98.354645,26.15304],[-98.386694,26.157872],[-98.404433,26.182564],[-98.442536,26.199151],[-98.450976,26.219904],[-98.496684,26.212853],[-98.543852,26.234492],[-98.576188,26.235221],[-98.585184,26.254429],[-98.599154,26.257612],[-98.669397,26.23632],[-98.681167,26.26271],[-98.707451,26.272152],[-98.711233,26.289687],[-98.745272,26.303096],[-98.749054,26.321662],[-98.789822,26.331575],[-98.807348,26.369421],[-98.890965,26.357569],[-98.921277,26.381426],[-98.937556,26.376093],[-98.967587,26.398266],[-99.008003,26.395459],[-99.039107,26.412947],[-99.082002,26.39651],[-99.113808,26.434002],[-99.091635,26.476977],[-99.105031,26.500335],[-99.127782,26.525199],[-99.170704,26.540316],[-99.178064,26.620547],[-99.200522,26.656443],[-99.208907,26.724761],[-99.240023,26.745851],[-99.242444,26.788262],[-99.268613,26.843213],[-99.295146,26.86544],[-99.316753,26.865831],[-99.3289,26.879761],[-99.324684,26.915973],[-99.379149,26.93449],[-99.393748,26.96073],[-99.378435,26.980034],[-99.415476,27.01724],[-99.42938,27.010833],[-99.446524,27.023008],[-99.452316,27.062669],[-99.429209,27.090982],[-99.442123,27.106839],[-99.430581,27.126612],[-99.439971,27.151072],[-99.426348,27.176262],[-99.432795,27.209693],[-99.445238,27.223341],[-99.441549,27.24992],[-99.463309,27.268437],[-99.48791,27.260721],[-99.496615,27.271708],[-99.487513,27.29024],[-99.494604,27.303542],[-99.536443,27.312538],[-99.504837,27.338289],[-99.507779,27.354247],[-99.487521,27.412396],[-99.495104,27.451518],[-99.480419,27.481596],[-99.497519,27.500496],[-99.52582,27.496696],[-99.515978,27.572131],[-99.55495,27.614454],[-99.585148,27.606398],[-99.578099,27.619196],[-99.594038,27.638573],[-99.638929,27.626758],[-99.665948,27.635968],[-99.6595,27.645246],[-99.668942,27.659974],[-99.711511,27.658365],[-99.77074,27.732134],[-99.796342,27.735586],[-99.813086,27.773952],[-99.841708,27.766464],[-99.850877,27.793974],[-99.877677,27.799427],[-99.876003,27.837968],[-99.904385,27.875284],[-99.894091,27.89295],[-99.90008,27.912142],[-99.937142,27.940537],[-99.931812,27.980967],[-99.991447,27.99456],[-100.017914,28.064787],[-100.053123,28.08473],[-100.083393,28.144035],[-100.208059,28.190383],[-100.220284,28.23221],[-100.251634,28.236177],[-100.293468,28.278475],[-100.286471,28.312296],[-100.341869,28.384953],[-100.349586,28.402604],[-100.337797,28.44296],[-100.368288,28.477196],[-100.333814,28.499252],[-100.38886,28.515748],[-100.411414,28.551899],[-100.398385,28.584884],[-100.44732,28.609325],[-100.445529,28.637144],[-100.500354,28.66196],[-100.511998,28.705352],[-100.507613,28.740599],[-100.533017,28.76328],[-100.53583,28.805888],[-100.547324,28.825817],[-100.57051,28.826317],[-100.572992,28.848464],[-100.598877,28.875591],[-100.602054,28.901944],[-100.640568,28.914212],[-100.651512,28.943432],[-100.645894,28.986421],[-100.674656,29.099777],[-100.772649,29.168492],[-100.767059,29.195287],[-100.797671,29.246943],[-100.876049,29.279585],[-100.886842,29.307848],[-100.940615,29.333109],[-100.948972,29.347246],[-101.010614,29.368669],[-101.060151,29.458661],[-101.130038,29.47842],[-101.144337,29.473246],[-101.173821,29.514566],[-101.254895,29.520342],[-101.261175,29.536777],[-101.242023,29.592512],[-101.265347,29.607284],[-101.307332,29.587847],[-101.314329,29.595622],[-101.311219,29.648491],[-101.325214,29.657821],[-101.361756,29.657821],[-101.415402,29.756561],[-101.446502,29.755006],[-101.455224,29.771874],[-101.475269,29.780663],[-101.522695,29.759671],[-101.546797,29.796991],[-101.561569,29.794658],[-101.582562,29.771334],[-101.625958,29.771063],[-101.646418,29.754304],[-101.662453,29.77128],[-101.706636,29.762737],[-101.777161,29.789327],[-101.79687,29.782619],[-101.852604,29.801895],[-101.929709,29.789323],[-101.974548,29.810276],[-101.987539,29.801057],[-102.034759,29.804028],[-102.050044,29.78507],[-102.115682,29.79239],[-102.159601,29.814356],[-102.181894,29.846034],[-102.227553,29.843534],[-102.261389,29.853283],[-102.268817,29.867991],[-102.276755,29.862978],[-102.315389,29.87992],[-102.364542,29.845387],[-102.386678,29.76688],[-102.508313,29.783219],[-102.513381,29.76576],[-102.539417,29.751629],[-102.565661,29.761592],[-102.630151,29.734315],[-102.670971,29.741954],[-102.698347,29.695591],[-102.693466,29.676507],[-102.742031,29.632142],[-102.739991,29.599041],[-102.768341,29.594734],[-102.762241,29.579449],[-102.773961,29.573084],[-102.771429,29.548546],[-102.808692,29.522319],[-102.807327,29.494009],[-102.832539,29.433109],[-102.824564,29.399558],[-102.843021,29.357988],[-102.883722,29.348059],[-102.888328,29.291947],[-102.906296,29.260011],[-102.871347,29.241625],[-102.866846,29.225015],[-102.890064,29.208814],[-102.915866,29.215878],[-102.917805,29.190697],[-102.932612,29.194113],[-102.953475,29.176308],[-102.977266,29.186226],[-102.994653,29.17962],[-103.015028,29.12577],[-103.040442,29.099351],[-103.074407,29.088534],[-103.100266,29.0577],[-103.113922,28.988547],[-103.163865,28.972099],[-103.227801,28.991532],[-103.245121,28.98024],[-103.266003,28.990206],[-103.28119,28.982138],[-103.289258,28.999698],[-103.331022,29.021766],[-103.334819,29.039801],[-103.361998,29.018914],[-103.427754,29.042334],[-103.453029,29.067467],[-103.469167,29.069242],[-103.503236,29.11911],[-103.524613,29.120998],[-103.523384,29.133389],[-103.558679,29.154962],[-103.59236,29.15026],[-103.61054,29.165773],[-103.645635,29.159286],[-103.71377,29.185008],[-103.755943,29.225545],[-103.777623,29.232265],[-103.789034,29.257502],[-103.816642,29.270927],[-103.975235,29.296017],[-104.038282,29.320156],[-104.08215,29.345923],[-104.106467,29.373127],[-104.166563,29.399352],[-104.181273,29.426265],[-104.212529,29.452439],[-104.213239,29.47301],[-104.264155,29.514001],[-104.318074,29.527938],[-104.334811,29.519463],[-104.381041,29.543406],[-104.399591,29.572319],[-104.507568,29.639624],[-104.539761,29.676074],[-104.53577,29.687248],[-104.565688,29.770462],[-104.592472,29.810276],[-104.610166,29.819118],[-104.633275,29.870485],[-104.679772,29.924659],[-104.679661,29.975272],[-104.706874,30.050685],[-104.685003,30.085643],[-104.695366,30.13213],[-104.687296,30.179464],[-104.713166,30.237957],[-104.733822,30.261221],[-104.749664,30.26126],[-104.761634,30.301148],[-104.809794,30.334926],[-104.817596,30.365915],[-104.859521,30.390413],[-104.85242,30.418792],[-104.869872,30.458645],[-104.876787,30.511004],[-104.899001,30.5704],[-104.924796,30.604832],[-104.967167,30.608107],[-104.980291,30.62204],[-104.9863,30.661059],[-105.006801,30.686039],[-105.062334,30.686303],[-105.062626,30.698222],[-105.098282,30.718914],[-105.110682,30.743366],[-105.15764,30.754008],[-105.164819,30.772493],[-105.178279,30.772134],[-105.195144,30.792138],[-105.212917,30.785415],[-105.21866,30.801567],[-105.261361,30.798078],[-105.287238,30.822206],[-105.314863,30.816961],[-105.360672,30.847384],[-105.394242,30.852979],[-105.399609,30.888941],[-105.488027,30.943278],[-105.533088,30.984859],[-105.55743,30.990229],[-105.60333,31.082625],[-105.64189,31.098322],[-105.646731,31.113908],[-105.709491,31.136375],[-105.742678,31.164897],[-105.773257,31.166897],[-105.782895,31.197563],[-105.869353,31.288634],[-105.890872,31.290014],[-105.908771,31.312774],[-105.938452,31.318735],[-105.953943,31.364749],[-105.970101,31.365937],[-106.004926,31.392458],[-106.080258,31.398702],[-106.106877,31.421403],[-106.132782,31.425367],[-106.203969,31.465378],[-106.246203,31.541153],[-106.280811,31.562062],[-106.303536,31.620413],[-106.378039,31.72831],[-106.451541,31.764808],[-106.484642,31.747809],[-106.547144,31.807305],[-106.602727,31.825024],[-106.605245,31.845905],[-106.635926,31.866235],[-106.630692,31.886411],[-106.645296,31.894859],[-106.614346,31.918003],[-106.629747,31.92657],[-106.614702,31.956],[-106.622819,31.952891],[-106.619569,31.971578],[-106.638186,31.97682],[-106.618486,32.000495],[-103.064423,32.000518],[-103.064625,32.999899],[-103.043531,34.018014],[-103.041924,36.500439],[-103.002434,36.500397],[-103.002199,37.000104],[-102.04224,36.993083]]],[[[-97.134356,27.896329],[-97.107511,27.890378],[-97.11895,27.884121],[-97.134356,27.896329]]],[[[-97.240849,26.411504],[-97.247619,26.456261],[-97.276425,26.521729],[-97.292399,26.528014],[-97.31073,26.556558],[-97.308635,26.576723],[-97.338489,26.647429],[-97.345822,26.700589],[-97.370438,26.723896],[-97.368343,26.795649],[-97.387459,26.820789],[-97.390078,27.156512],[-97.377508,27.199459],[-97.386674,27.204696],[-97.373318,27.27645],[-97.359963,27.304732],[-97.361796,27.359988],[-97.331157,27.412362],[-97.317277,27.46369],[-97.236882,27.598293],[-97.231383,27.632336],[-97.214099,27.631551],[-97.200743,27.650144],[-97.203474,27.684533],[-97.103326,27.789068],[-97.092851,27.81447],[-97.098874,27.82285],[-97.134489,27.825206],[-97.056713,27.842294],[-96.985745,27.954048],[-96.967807,28.020041],[-96.952618,28.01644],[-96.92643,28.043413],[-96.927085,28.057292],[-96.886233,28.084396],[-96.879424,28.131402],[-96.84538,28.108881],[-96.83003,28.111842],[-96.81042,28.126034],[-96.818656,28.17228],[-96.791958,28.188687],[-96.703838,28.198246],[-96.702659,28.211208],[-96.662462,28.227314],[-96.651856,28.251275],[-96.607992,28.27707],[-96.592934,28.296972],[-96.55326,28.302341],[-96.528906,28.322505],[-96.450998,28.337039],[-96.403206,28.371475],[-96.397846,28.343513],[-96.4137,28.327343],[-96.547774,28.270798],[-96.694666,28.18212],[-96.849624,28.064939],[-96.966996,27.950531],[-97.166682,27.676583],[-97.30447,27.407734],[-97.350398,27.268105],[-97.370941,27.161166],[-97.37913,27.047996],[-97.370731,26.909706],[-97.333028,26.736479],[-97.194644,26.306513],[-97.154271,26.066841],[-97.169842,26.077853],[-97.194458,26.27164],[-97.214885,26.353606],[-97.240849,26.411504]]],[[[-94.886539,29.510724],[-94.894747,29.52697],[-94.878969,29.502674],[-94.886539,29.510724]]]]},\"properties\":{\"name\":\"Kansas\",\"nation\":\"USA \"}}]}","volume":"40","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Ramos-Sepulveda, Maria E.","contributorId":294748,"corporation":false,"usgs":false,"family":"Ramos-Sepulveda","given":"Maria","email":"","middleInitial":"E.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":897170,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stewart, Jonathan P.","contributorId":100110,"corporation":false,"usgs":false,"family":"Stewart","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[{"id":7081,"text":"University of California - Los Angeles","active":true,"usgs":false}],"preferred":false,"id":897171,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parker, Grace Alexandra 0000-0002-9445-2571","orcid":"https://orcid.org/0000-0002-9445-2571","contributorId":237091,"corporation":false,"usgs":true,"family":"Parker","given":"Grace","email":"","middleInitial":"Alexandra","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":897172,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":897173,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":897174,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brandenberg, Scott J.","contributorId":303895,"corporation":false,"usgs":false,"family":"Brandenberg","given":"Scott","email":"","middleInitial":"J.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":897175,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hashash, Youssef M A","contributorId":146595,"corporation":false,"usgs":false,"family":"Hashash","given":"Youssef","email":"","middleInitial":"M A","affiliations":[{"id":15289,"text":"University of Illinois, Ven Te Chow Hydrosystems Laboratory","active":true,"usgs":false}],"preferred":false,"id":897176,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rathje, Ellen 0000-0002-4169-7153","orcid":"https://orcid.org/0000-0002-4169-7153","contributorId":197024,"corporation":false,"usgs":false,"family":"Rathje","given":"Ellen","email":"","affiliations":[],"preferred":false,"id":897177,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70252709,"text":"70252709 - 2024 - Snow-cover remote sensing of conifer tree recovery in high-severity burn patches","interactions":[],"lastModifiedDate":"2024-04-03T12:08:46.291369","indexId":"70252709","displayToPublicDate":"2024-03-16T07:04:11","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Snow-cover remote sensing of conifer tree recovery in high-severity burn patches","docAbstract":"The number of large, high-severity wildfires has been increasing across the western United States over the last several decades. It is not fully understood how changes in the frequency of large, severe wildfires may impact the resilience of conifer forests, due to alterations in regeneration success or failure. Our research investigates 30 years of conifer recovery patterns within 34 high-severity wildfire complexes (1988–1991) of the Northern Rocky Mountains. We evaluate the capability of snow-cover Landsat to characterize conifer tree recolonization of high-severity burn patches. Snow-cover images isolate conifer-specific vegetation signals by diminishing spectral contributions from soil and deciduous vegetation. The presence of conifer regeneration was successfully classified by snow-cover Landsat at >10% canopy cover at 98% accuracy and modeled at 3-year intervals post-fire. Spectral detectability of regenerating conifer vegetation began 11–19 years post-fire, varying across forest types. Thirty years post-fire, 65% of the total high-severity burn area had been recolonized by conifer trees, with differences observed between forest types: 72% of lodgepole pine, 77% of Douglas-fir, and 44% of fir-spruce severely burned areas containing conifer regeneration. Projected recovery timelines to pre-fire conifer vegetation also differed between lodgepole pine (29.5 years), Douglas-fir (36.9 years), and fir-spruce forests (48.7 years), as estimated from snow-cover NDVI trends. Although we generally documented patterns of conifer resilience, we also identified reduced likelihoods of recovery within high-severity burn patches exhibiting greater area-to-perimeter ratios, aridity, south-facing aspects, slopes, and elevation. Snow-cover Landsat imagery was shown to improve the characterization of post-fire forest recovery and may be applied to support forest restoration decision-making following high-severity wildfire.
Predation can play an important role in structuring ecological communities, and predator–prey dynamics can be altered following the introduction of new species. An unauthorized introduction of redside shiner (Richardsonius balteatus) into reservoirs in the Upper Skagit River, Washington, USA created concern that a consequent shift in predator–prey dynamics in the reservoirs could reduce recruitment and production of native salmonids in the basin. We estimated predation mortality in Ross Lake on nonnative redside shiner and juvenile native salmonids to evaluate the potential role of predation in regulating these populations and limiting survival of native species of concern. We used bioenergetics modelling and stable isotope analysis combined with directed field measurements of growth, seasonal diet and thermal experience of piscivorous salmonids to quantify their consumption demand on prey fishes to evaluate the relative magnitude of predation mortality on invasive redside shiners and native salmonids. While redside shiner are the dominant prey fish species in Ross Lake, the modest biomass of native salmonids consumed could translate into substantial mortality, the magnitude of which depended on the timing and size at which prey fishes were eaten. This information provides important context for how nonnative species may indirectly impact native species through shared predation (apparent competition) and can inform conservation decisions surrounding nonnative species control, sustainability of native salmonids and introductions of anadromous fishes.
Understanding the response of coastal barriers to future changes in rates of sea level rise, sediment availability, and storm intensity/frequency is essential for coastal planning, including socioeconomic and ecological management. Identifying drivers of past changes in barrier morphology, as well as barrier sensitivity to these forces, is necessary to accomplish this. Using remote sensing, field, and laboratory analyses, we reconstruct the mesoscale (decades–centuries) evolution of central Fire Island, a portion of a 50 km barrier island fronting Long Island, New York, USA. We find that the configuration of the modern beach and foredune at Fire Island is radically different from the system's relict morphostratigraphy. Central Fire Island is comprised of at least three formerly inlet-divided rotational barriers with distinct subaerial beach and dune–ridge systems that were active prior to the mid-19th century. Varying morphologic states reflected in the relict barriers (e.g., progradational and transgressive) contrast with the modern barrier, which is dominated by a tall and nearly continuous foredune and is relatively static, except for erosion and drowning of its fringing marsh. We suggest that this state shift indicates a transition from a regime dominated by inlet-mediated gradients in alongshore sediment availability to one where human impacts exerted greater influence on island evolution from the late 19th century onward. The retention of some geomorphic capital in Fire Island's relict subaerial features combined with its static nature renders the barrier increasingly susceptible to narrowing and passive submergence. This may lead to an abrupt geomorphic state shift in the future, a veiled vulnerability that may also exist in other stabilized barriers.
The Rocky Mountain Population (RMP) of greater sandhill cranes uses a key stopover area, the San Luis Valley (SLV) in Colorado. Parameters of migration phenology can differ between autumn and spring and are affected by weather and environmental factors. We hypothesized that sandhill cranes in the SLV would have a longer stopover duration in autumn than in spring, and that wind assistance, crosswinds, temperature change, barometric air pressure, and surface water area would influence persistence probability. We used data from sandhill cranes fitted with transmitters that spanned autumn and spring, 2015-2022. We used an open robust design mark-recapture model to estimate stopover duration, arrival probability, and persistence probability. We examined the effects of weather and surface water on the persistence probability for 106 sandhill cranes in the SLV. Stopover duration was longer in autumn than in spring and had higher variability across years. Arrival probability to the SLV peaked on 13 October in autumn and 21 February in spring. Persistence probability declined around mid-December in autumn and mid-March in spring. We found that several weather covariates influenced persistence in both seasons. In autumn, sandhill cranes departed the SLV with higher tailwinds, lower crosswinds, and higher surface water availability. In spring, sandhill cranes departed the SLV with lower crosswinds and higher barometric air pressure at the surface and higher wind speeds at altitudes of about 3,000 m. The effect of wind speed was stronger later in the spring. Given the lower variability of arrival and persistence probability and shorter stopover duration in spring compared to autumn, we suspect that RMP sandhill cranes are using a time-minimization strategy during spring. However, given the use of supportive winds and weather conditions ideal for soaring, RMP sandhill cranes appear to be using strategies that save energy in both seasons. Our study identifies the optimal timing of water management and surveys for RMP sandhill cranes and confirms that weather influences their persistence. Understanding differences in migration patterns between seasons and the factors that influence persistence at stopover sites will also be important for anticipating phenological impacts from climate change and land use alterations.
Mountain lakes are sensitive indicators of anthropogenically driven global change, with lake sediment records documenting increased primary production during the twentieth century. Atmospheric nutrient deposition and warming have been attributed to changes in other Western mountain lakes, however, the intensity of these drivers varies. We analyzed a sediment core representing a 270-year record from Santa Fe Lake, New Mexico, to constrain the southern margin of Rocky Mountain lakes and quantify patterns of change in lake biogeochemistry, production, and diatoms since 1750. Lake sediments were dated using 210Pb and analyzed for carbon (C), nitrogen (N), stable isotopes (δ13C, δ15N), diatoms, and phototrophic pigments. The abundance of cyanobacteria, purple sulfur-reducing bacteria, and diatom pigments were elevated during the stable conditions of the Little Ice Age; these phototrophic groups declined in the late 1800s and reached a minimum by 1950. From 1950 to 2020, sediments recorded an increased abundance of cryptophyte, diatom, and chlorophyte groups. The C and N (percentage dry mass) increased after 1950, whereas δ15N and δ13C values declined. Changes since the mid-twentieth century are contemporaneous with warming trends in the Southwest and modest deposition of atmospheric N. Our findings highlight the geographic variability of mountain lake responses to changing environmental conditions.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/15230430.2024.2303810","usgsCitation":"Shampain, A., Baron, J., Leavitt, P.R., and Spaulding, S., 2024, Climatic variability as a principal driver of primary production in the southernmost subalpine Rocky Mountain lake: Arctic, Antarctic, and Alpine Research, v. 56, no. 1, 2303810, 18 p., https://doi.org/10.1080/15230430.2024.2303810.","productDescription":"2303810, 18 p.","ipdsId":"IP-153651","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":440125,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/15230430.2024.2303810","text":"Publisher Index Page"},{"id":427400,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Santa Fe Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.74147810102569,\n 35.85975006476575\n ],\n [\n -106.27,\n 35.85975006476575\n ],\n [\n -106.27,\n 35.66069461088024\n ],\n [\n -105.74147810102569,\n 35.66069461088024\n ],\n [\n -105.74147810102569,\n 35.85975006476575\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"56","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Shampain, Anna 0000-0001-5447-7638","orcid":"https://orcid.org/0000-0001-5447-7638","contributorId":331317,"corporation":false,"usgs":false,"family":"Shampain","given":"Anna","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":898146,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baron, Jill 0000-0002-5902-6251 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":194124,"corporation":false,"usgs":true,"family":"Baron","given":"Jill","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":898147,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leavitt, Peter R.","contributorId":335357,"corporation":false,"usgs":false,"family":"Leavitt","given":"Peter","email":"","middleInitial":"R.","affiliations":[{"id":27547,"text":"University of Regina","active":true,"usgs":false}],"preferred":false,"id":898148,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spaulding, Sarah A. 0000-0002-9787-7743","orcid":"https://orcid.org/0000-0002-9787-7743","contributorId":223186,"corporation":false,"usgs":true,"family":"Spaulding","given":"Sarah","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":898149,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70252676,"text":"70252676 - 2024 - Modeled flooding by tsunamis and a storm versus observed extent of coral erratics on Anegada, British Virgin Islands— Further evidence for a great Caribbean earthquake six centuries ago","interactions":[],"lastModifiedDate":"2024-04-02T14:36:15.942014","indexId":"70252676","displayToPublicDate":"2024-03-14T09:29:59","publicationYear":"2024","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":"Modeled flooding by tsunamis and a storm versus observed extent of coral erratics on Anegada, British Virgin Islands— Further evidence for a great Caribbean earthquake six centuries ago","docAbstract":"Models of near-field tsunamis and an extreme hurricane provide further evidence for a great precolonial earthquake along the Puerto Rico Trench. The models are benchmarked to brain-coral boulders and cobbles on Anegada, 125 km south of the trench. The models are screened by their success in flooding the mapped sites of these erratics, which were emplaced some six centuries ago. Among 25 tsunami scenarios, 19 have megathrust sources and the rest posit normal faulting on the outer rise. The modeled storm, the most extreme of 15 hurricanes of category 5, produces tsunami-like bores from surf beat. In the tsunami scenarios, simulated flow depth is 1 m or more at all the clast sites, and 2 m or more at nearly all, given either a megathrust rupture 255 km long with 7.5 m of dip slip and M8.45, or an outer-rise rupture 130 km long with 11.4 m of dip slip and M8.17. By contrast, many coral clasts lie beyond the reach of simulated flooding from the extreme hurricane. The tsunami screening may underestimate earthquake size by neglecting trees and shrubs that likely impeded both the simulated flows and the observed clasts; and it may overestimate earthquake size by leaving coastal sand barriers intact. The screening results broadly agree with those from previously published tsunami simulations. In either successful scenario, the average recurrence interval spans thousands of years, and flooding on the nearest Caribbean shores begins within a half-hour.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023JB028387","usgsCitation":"Wei, Y., ten Brink, U.S., and Atwater, B.F., 2024, Modeled flooding by tsunamis and a storm versus observed extent of coral erratics on Anegada, British Virgin Islands— Further evidence for a great Caribbean earthquake six centuries ago: JGR Solid Earth, v. 129, no. 3, e2023JB028387, 26 p., https://doi.org/10.1029/2023JB028387.","productDescription":"e2023JB028387, 26 p.","ipdsId":"IP-160030","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":440127,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023jb028387","text":"Publisher Index Page"},{"id":427312,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"British Virgin Islands","otherGeospatial":"Anegada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -64.26970963209003,\n 18.687395079258394\n ],\n [\n -64.27098250709774,\n 18.70548066405327\n ],\n [\n -64.31107821074197,\n 18.74887709066421\n ],\n [\n -64.34353638253225,\n 18.7524941354379\n ],\n [\n -64.41895422673412,\n 18.747371507694695\n ],\n [\n -64.41927244548606,\n 18.73561900967063\n ],\n [\n -64.39986110161998,\n 18.719646355609257\n ],\n [\n -64.35181007008187,\n 18.715426911972713\n ],\n [\n -64.3206243759603,\n 18.713016020229745\n ],\n [\n -64.30407748159904,\n 18.70156264195039\n ],\n [\n -64.280847288407,\n 18.685284968543982\n ],\n [\n -64.26970963209003,\n 18.687395079258394\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"129","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-03-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Wei, Yong","contributorId":242870,"corporation":false,"usgs":false,"family":"Wei","given":"Yong","affiliations":[{"id":48562,"text":"JISAO, University of Washington, WA 98105 USA","active":true,"usgs":false}],"preferred":false,"id":897881,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"ten Brink, Uri S. 0000-0001-6858-3001","orcid":"https://orcid.org/0000-0001-6858-3001","contributorId":201741,"corporation":false,"usgs":true,"family":"ten Brink","given":"Uri","email":"","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":897882,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Atwater, Brian F. 0000-0003-1155-2815","orcid":"https://orcid.org/0000-0003-1155-2815","contributorId":335255,"corporation":false,"usgs":false,"family":"Atwater","given":"Brian","email":"","middleInitial":"F.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":897883,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70255250,"text":"70255250 - 2024 - Incorporating life history diversity in an integrated population model to inform viability analysis","interactions":[],"lastModifiedDate":"2024-06-13T14:29:03.449351","indexId":"70255250","displayToPublicDate":"2024-03-14T09:22:46","publicationYear":"2024","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}},"title":"Incorporating life history diversity in an integrated population model to inform viability analysis","docAbstract":"Life history diversity can significantly affect population dynamics and effects of management actions. For instance, variation in individual responses to environmental variability can reduce extirpation risk to populations, as the portfolio effect dampens temporal variability in abundance. Moreover, differences in habitat use may cause individuals to respond differently to habitat management and climate variability. To explore the role of life history diversity in population trajectories, population models need to incorporate within-population variation. Integrated population modeling (IPM) is a population modeling approach that offers several advantages for sharing information and propagating uncertainty across datasets. In this study, we developed an IPM for an endangered population of Chinook salmon (Oncorhynchus tshawytscha) in the Wenatchee River, Washington, USA, that accounts for diversity in juvenile life histories, spawning location, and return age. Our analysis revealed that diversity in the age of juvenile emigration from natal streams had a portfolio effect, resulting in a 20% reduction in year-to-year variability in adult abundance in population projections. Our population viability analysis suggests that management interventions may be necessary to meet recovery goals, and our model should be useful for simulating the outcomes of proposed actions.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2023-0118","usgsCitation":"Sorel, M.H., Jorgensen, J.C., Zabel, R.W., Scheuerell, M.D., Murdoch, A.R., Kamphaus, C.M., and Converse, S.J., 2024, Incorporating life history diversity in an integrated population model to inform viability analysis: Canadian Journal of Fisheries and Aquatic Sciences, v. 81, no. 5, p. 535-548, https://doi.org/10.1139/cjfas-2023-0118.","productDescription":"14 p.","startPage":"535","endPage":"548","ipdsId":"IP-153564","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":440129,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1139/cjfas-2023-0118","text":"External Repository"},{"id":430133,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.65380079789186,\n 48.385800374959246\n ],\n [\n -122.85878973700216,\n 48.35952757767319\n ],\n [\n -122.85878973700216,\n 45.39007143816454\n ],\n [\n -118.65380079789189,\n 45.42475769972472\n ],\n [\n -118.65380079789186,\n 48.385800374959246\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"81","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sorel, Mark H.","contributorId":171739,"corporation":false,"usgs":false,"family":"Sorel","given":"Mark","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":903859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jorgensen, Jeffrey C.","contributorId":339208,"corporation":false,"usgs":false,"family":"Jorgensen","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":903860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zabel, Richard W.","contributorId":272049,"corporation":false,"usgs":false,"family":"Zabel","given":"Richard","email":"","middleInitial":"W.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":903861,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scheuerell, Mark David 0000-0002-8284-1254","orcid":"https://orcid.org/0000-0002-8284-1254","contributorId":288621,"corporation":false,"usgs":true,"family":"Scheuerell","given":"Mark","email":"","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903862,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Murdoch, Andrew R.","contributorId":339213,"corporation":false,"usgs":false,"family":"Murdoch","given":"Andrew","email":"","middleInitial":"R.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":903863,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kamphaus, Cory M.","contributorId":339215,"corporation":false,"usgs":false,"family":"Kamphaus","given":"Cory","email":"","middleInitial":"M.","affiliations":[{"id":39287,"text":"Yakama Nation Fisheries","active":true,"usgs":false}],"preferred":false,"id":903864,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":903865,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70258782,"text":"70258782 - 2024 - Estimating multivariate ecological variables at high spatial resolution using a cost-effective matching algorithm","interactions":[],"lastModifiedDate":"2024-10-03T16:05:53.476234","indexId":"70258782","displayToPublicDate":"2024-03-14T08:41:44","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Estimating multivariate ecological variables at high spatial resolution using a cost-effective matching algorithm","docAbstract":"Simulation models are valuable tools for estimating ecosystem response to environmental conditions and are particularly relevant for investigating climate change impacts. However, because of high computational requirements, models are often applied over a coarse grid of points or for representative locations. Spatial interpolation of model output can be necessary to guide decision-making, yet interpolation is not straightforward because the interpolated values must maintain the covariance structure among variables. We present methods for two key steps for utilizing limited simulations to generate detailed maps of multivariate and time series output. First, we present a method to select an optimal set of simulation sites that maximize the area represented for a given number of sites. Then, we introduce a multivariate matching approach to interpolate simulation results to detailed maps for the represented area. This approach links simulation output to environmentally analogous matched sites according to user-defined criteria. We demonstrate the methods with case studies using output from (1) an individual-based plant simulation model to illustrate site selection, and (2) an ecosystem water balance simulation model to illustrate interpolation. For the site selection case study, we identified 200 simulation sites that represented 96% of a large study area (1.12 × 106 km2) at a ~1-km resolution. For the interpolation case study, we generated ~1-km resolution maps across 4.38 × 106 km2 of drylands in North America from a 10 × 10 km grid of simulated sites. Estimates of interpolation errors using cross validation were low (less than 10% of the range of each variable). Our point selection and interpolation methods, which are available as an easy-to-use R package, provide a means of cost-effectively generating detailed maps of expensive, complex simulation output (e.g., multivariate and time series) at scales relevant for local conservation planning. Our methods are flexible and allow the user to identify relevant matching criteria to balance interpolation uncertainty with areal coverage to enhance inference and decision-making at management-relevant scales across large areas.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4811","usgsCitation":"Renne, R.R., Schlaepfer, D.R., Palmquist, K.A., Lauenroth, W.K., and Bradford, J., 2024, Estimating multivariate ecological variables at high spatial resolution using a cost-effective matching algorithm: Ecosphere, v. 15, no. 3, e4811, 18 p., https://doi.org/10.1002/ecs2.4811.","productDescription":"e4811, 18 p.","ipdsId":"IP-133218","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":467024,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1002/ecs2.4811","text":"Publisher Index Page"},{"id":462276,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-03-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Renne, Rachel R.","contributorId":213935,"corporation":false,"usgs":false,"family":"Renne","given":"Rachel","email":"","middleInitial":"R.","affiliations":[{"id":38934,"text":"School of Forestry and Environmental Studies, Yale University, New Haven, CT 06511, USA","active":true,"usgs":false}],"preferred":false,"id":914056,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schlaepfer, Daniel Rodolphe 0000-0001-9973-2065","orcid":"https://orcid.org/0000-0001-9973-2065","contributorId":225569,"corporation":false,"usgs":true,"family":"Schlaepfer","given":"Daniel","email":"","middleInitial":"Rodolphe","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":914057,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Palmquist, Kyle A.","contributorId":169517,"corporation":false,"usgs":false,"family":"Palmquist","given":"Kyle","email":"","middleInitial":"A.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":914058,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lauenroth, William K.","contributorId":80982,"corporation":false,"usgs":false,"family":"Lauenroth","given":"William","email":"","middleInitial":"K.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":914059,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":914060,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70252498,"text":"70252498 - 2024 - Evaluating water-quality trends in agricultural watersheds prioritized for management-practice implementation","interactions":[],"lastModifiedDate":"2024-04-10T16:05:11.77161","indexId":"70252498","displayToPublicDate":"2024-03-14T06:51:53","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16692,"text":"Journal of the American Water Resources Assocation","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating water-quality trends in agricultural watersheds prioritized for management-practice implementation","docAbstract":"Many agricultural watersheds rely on the voluntary use of management practices (MPs) to reduce nonpoint source nutrient and sediment loads; however, the water-quality effects of MPs are uncertain. We interpreted water-quality responses from as early as 1985 through 2020 in three agricultural Chesapeake Bay watersheds that were prioritized for MP implementation, namely, the Smith Creek (Virginia), Upper Chester River (Maryland), and Conewago Creek (Pennsylvania) watersheds. We synthesized patterns in MPs, climate, land use, and nutrient inputs to better understand factors affecting nutrient and sediment loads. Relations between MPs and expected water-quality improvements were not consistently identifiable. The number of MPs increased in all watersheds since the early 2010s, but most monitored nutrient and sediment loads did not decrease. Nutrient and sediment loads increased or remained stable in Smith Creek and the Upper Chester River. Sediment loads and some nutrient loads decreased in Conewago Creek. In Smith Creek, a 36-year time-series model suggests that changes in manure affected flow-normalized total nitrogen loads. We hypothesize that increases in nutrient applications may overshadow some expected MP effects. MPs might have stemmed further water-quality degradation, but improvements in nutrient loads may rely on reducing manure and fertilizer applications. Our results highlight the importance of assessing MP performance with long-term monitoring-based studies.
StreamStats is a U.S. Geological Survey (USGS) web application that provides streamflow statistics, such as the 1-percent annual exceedance probability peak flow, the mean flow, and the 7-day, 10-year low flow, to the public through a map-based user interface. These statistics are used in many ways, such as in the design of roads, bridges, and other structures; in delineation of floodplains for land-use zoning and setting of insurance rates; for regulatory purposes, such as the permitting of wastewater discharges; and for hydrologic and climate change studies. StreamStats was first developed for Massachusetts and released in 2001. The application provided users with the ability to obtain streamflow statistics computed from data collected at USGS streamgages and to obtain estimates of streamflow statistics for user-selected ungaged sites. Massachusetts StreamStats used geographic information system software and digital mapping to compute drainage-basin characteristics, which were then used in statistical models to estimate streamflow statistics for the user-selected sites. The statistical models were in the form of equations that were developed through a process known as regression analysis. StreamStats was the first known web application with the ability to do interactive geoprocessing.
The utility of Massachusetts StreamStats was instantly apparent, leading the USGS to develop a version of StreamStats that could be implemented nationally. USGS State offices normally were required to develop custom regression equations and prepare local digital mapping data needed for implementing StreamStats for their States. Funding needed to complete this work usually was provided through cooperative agreements between the USGS and State agencies. In 2004, Idaho became the first to be released in the national version of StreamStats. By 2023, 44 States were fully implemented and six were undergoing implementation.
StreamStats has undergone many modifications over the years to keep up with changes to the underlying software and to add functionality. Customized functionality and separate linked StreamStats applications were developed for several States. Meeting the high demand for additions and improvements to StreamStats while also adhering to budgetary constraints has, at times, been challenging. The StreamStats development team has identified numerous additional improvements that could be made to provide better performance and more functionality. The lessons learned from the experience of building and operating StreamStats for nearly 25 years could be relevant to others interested in pursuing efforts of a similar scale.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1514","usgsCitation":"Ries, K.G., III, Steeves, P.A., and McCarthy, P., 2024, StreamStats—A quarter century of delivering web-based geospatial and hydrologic information to the public, and lessons learned: U.S. Geological Survey Circular 1514, 40 p., https://doi.org/10.3133/cir1514.","productDescription":"viii, 40 p.","numberOfPages":"40","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-102663","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":499073,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116170.htm","linkFileType":{"id":5,"text":"html"}},{"id":426017,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1514/cir1514.XML","description":"CIR 1514 XML"},{"id":426018,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/circ/1514/images/"},{"id":426016,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/cir1514/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"CIR 1514 HTML"},{"id":426015,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1514/cir1514.pdf","text":"Report","size":"7.67 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1514 PDF"},{"id":426014,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1514/coverthb.jpg"}],"contact":"National Coordinator, StreamStats
U.S. Geological Survey
1728 Lampman Drive, Suite D
Billings, MT 59102
Alaska’s Arctic coast has some of the highest coastal erosion rates in the world, primarily driven by permafrost thaw and increasing wave energy. In the Arctic, a warming climate is driving sea ice cover to decrease in space and time. A lack of long-term observational wave data along Alaska’s coast challenges the ability of engineers, scientists, and planners to study and address threats and effects from wave-driven erosion and flooding. To overcome the lack of available observational wave data in the nearshore in this study by the U.S. Geological Survey, waves were downscaled with the Simulating WAves Nearshore numerical wave model (SWAN) for the hindcast period of 1979 to 2019 from the United States-Canada border to the Bering Sea utilizing nine model domains. For each domain, the model was forced at the open boundary with 2,500 representative “sea states,” which are likely combinations of significant wave heights, mean wave periods, mean wave directions, and wind speeds and directions. The sea states were obtained from the European Centre for Medium-Range Weather Forecasts “ERA5” dataset for reanalysis of winds and waves using a multivariant maximum-dissimilarity algorithm. The SWAN runs created a downscaled wave database at each grid point, which was used to reconstruct the 40-year time series in the nearshore along the 5- and 10-meter isobaths at locations approximately 400 m apart and corresponding to transects spaced approximately 50 m alongshore, as developed for USGS shoreline-change assessments. Reconstructed time series were compared to observations to validate the numerical model and the downscaled wave database method and showed overall good agreements.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231094","programNote":"Prepared in cooperation with Deltares USA and the University of California, Santa Cruz","usgsCitation":"Engelstad, A.C., Erikson, L.H., Reguero, B.G., Gibbs, A.E., and Nederhoff, K., 2024, Database and time series of nearshore waves along the Alaskan coast from the United States-Canada border to the Bering Sea: U.S. Geological Survey Open-File Report 2023–1094, 23 p., https://doi.org/10.3133/ofr20231094.","productDescription":"Report: v, 23 p.; Data Release","numberOfPages":"23","onlineOnly":"Y","ipdsId":"IP-132323","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":499201,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116169.htm","linkFileType":{"id":5,"text":"html"}},{"id":426586,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231094/full"},{"id":426585,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1094/images"},{"id":426584,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1094/ofr20231094.xml"},{"id":426583,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1094/covrthb.jpg"},{"id":426582,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1094/ofr20231094.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":426581,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P931CSO9","text":"USGS Data Release","description":"Engelstad, A.C., Erikson, L.H., Reguero, B.G., Gibbs, A.E., Nederhoff, K.M., 2024, Nearshore wave time-series along the coast of Alaska computed with a numerical wave model: U.S. Geological Survey data release, https://doi.org/10.5066/P931CSO9.","linkHelpText":"Nearshore wave time-series along the coast of Alaska computed with a numerical wave model"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -168.34514806758992,\n 65.52631288766165\n ],\n [\n -140.04436681759015,\n 65.52631288766165\n ],\n [\n -140.04436681759015,\n 71.42344314984271\n ],\n [\n -168.34514806758992,\n 71.42344314984271\n ],\n [\n -168.34514806758992,\n 65.52631288766165\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St.
Santa Cruz, CA 95060