Remotely sensed evapotranspiration (ET) data offer strong potential to support data-driven approaches for sustainable water management. However, practitioners require robust and rigorous accuracy assessments of such data. The OpenET system, which includes an ensemble of six remote sensing models, was developed to increase access to field-scale (30 m) ET data for the contiguous United States. Here we compare OpenET outputs against data from 152 in situ stations, primarily eddy covariance flux towers, deployed across the contiguous United States. Mean absolute error at cropland sites for the OpenET ensemble value is 15.8 mm per month (17% of mean observed ET), mean bias error is −5.3 mm per month (6%) and r2 is 0.9. Results for shrublands and forested sites show higher inter-model variability and lower accuracy relative to croplands. High accuracy and multi-model convergence across croplands demonstrate the utility of a model ensemble approach, and enhance confidence among ET data practitioners, including the agricultural water resource management community.
Larval lampreys are filter feeders that live for several years burrowed in fine sediments in freshwater streams. Stream side channels and edges, where larval lampreys gather, are vulnerable to natural and human-caused dewatering. Water level reductions can strand and kill thousands of larval lampreys, in part because many remain burrowed until their habitats are exposed, at which point larvae must emerge and attempt to move over dewatered substrate to locate wetted habitat. Dewatering for restoration efforts or seasonal closures of irrigation canals can be done slowly to reduce lamprey strandings, but in some settings, mechanisms are lacking to control the dewatering rate. Phased dewatering, where water level is reduced in stages separated by periods of static water level, could provide options when dewatering rate cannot be tightly controlled. To guide this phased approach, information is needed on the movement capability of larval lampreys. We examined larval lamprey (Entosphenus tridentatus and Lampetra spp.) movement distance and rate over dewatered substrate at shoreline slopes of 1%, 5%, 10% and 20% in a laboratory setting and modelled results using gamma regression models. Model results suggest both movement distance and movement rate increased with increasing slope and increasing larval length. We used the models to predict minimum distances and rates that 90%, 75% and 50% of medium-sized (75 mm) lampreys would move over dewatered substrates on slopes of 1%–20%. The models predicted that 50% of larvae could move distances of ≥31 cm at rates of ≥0.7 mm/s on a 1% slope and distances of ≥502 cm at rates of ≥8.6 mm/s on a 20% slope. We present an example scenario of how information on larval movement capabilities and shoreline slope could guide phased dewatering events to limit impacts to lampreys.
Intraspecific resource partitioning may play a critical role in how predators optimize prey selection. The Black-footed Ferret (Mustela nigripes; henceforth, ferret) is a highly specialized predator of prairie dogs (Cynomys spp.; henceforth, PDs). Adult ferrets are sexually dimorphic and PDs are of similar size making them a difficult prey item. PD young are born 6 to 8 weeks prior to births of ferrets, producing a crop of smaller prey items during a period when energetic needs of female ferrets are highest. We asked whether relatively small female ferrets select small PDs as prey. We examined survival rates from early to late summer for large and small black-tailed PDs (Cynomys ludovicianus) in Montana and South Dakota as a function of their distance to adult male and female ferrets using capture–mark–recapture of PDs and simultaneous summer monitoring of ferret locations. Survival of small PDs (<600 g) was low when a female ferret was nearby, but distance to nearest female ferret did not affect survival of large PDs. Distance to the nearest male ferret did not influence survival regardless of PD size. Reduced competition from males for a critical food resource needed by females rearing young would benefit fitness of both sexes. If female ferrets depend on young PDs during their reproductive period, existing habitat models may substantially overestimate ferret carrying capacity.
","language":"English","publisher":"American Society of Mammalogists","doi":"10.1093/jmammal/gyad132","usgsCitation":"Biggins, D.E., Eads, D.A., Ramakrishnan, S., Goldberg, A., Eads, S., Hardin, J., and Konkel, D., 2024, Prey selection by black-footed ferrets (Mustela nigripes): Implications for intersexual resource partitioning and conservation: Journal of Mammalogy, v. 105, no. 2, p. 221-229, https://doi.org/10.1093/jmammal/gyad132.","productDescription":"9 p.","startPage":"221","endPage":"229","ipdsId":"IP-138897","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":440714,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1093/jmammal/gyad132","text":"Publisher Index Page"},{"id":435061,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CWW8GZ","text":"USGS data release","linkHelpText":"Data on black-tailed prairie dog body mass, distance to nearest male and female black-footed ferret, distance to nearest American badger, and reencounter from early to late summer 2005 (Montana) and 2009 (South Dakota)"},{"id":427842,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"105","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Biggins, Dean E. 0000-0003-2078-671X bigginsd@usgs.gov","orcid":"https://orcid.org/0000-0003-2078-671X","contributorId":2522,"corporation":false,"usgs":true,"family":"Biggins","given":"Dean","email":"bigginsd@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":898998,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eads, David A. 0000-0002-4247-017X deads@usgs.gov","orcid":"https://orcid.org/0000-0002-4247-017X","contributorId":173639,"corporation":false,"usgs":true,"family":"Eads","given":"David","email":"deads@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":898999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramakrishnan, Shantini","contributorId":265765,"corporation":false,"usgs":false,"family":"Ramakrishnan","given":"Shantini","affiliations":[{"id":54787,"text":"Denver Zoological Foundation","active":true,"usgs":false}],"preferred":false,"id":899000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goldberg, Amanda R.","contributorId":288043,"corporation":false,"usgs":false,"family":"Goldberg","given":"Amanda R.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":899001,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eads, Samantha L.","contributorId":332613,"corporation":false,"usgs":false,"family":"Eads","given":"Samantha L.","affiliations":[{"id":13693,"text":"University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":899002,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hardin, Joanna","contributorId":335653,"corporation":false,"usgs":false,"family":"Hardin","given":"Joanna","email":"","affiliations":[],"preferred":false,"id":899003,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Konkel, Darla","contributorId":335654,"corporation":false,"usgs":false,"family":"Konkel","given":"Darla","email":"","affiliations":[],"preferred":false,"id":899004,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70250968,"text":"70250968 - 2024 - Saltwater intrusion and sea level rise threatens U.S. rural coastal landscapes and communities","interactions":[],"lastModifiedDate":"2024-01-25T14:59:54.182525","indexId":"70250968","displayToPublicDate":"2024-01-13T07:04:58","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":815,"text":"Anthropocene","active":true,"publicationSubtype":{"id":10}},"title":"Saltwater intrusion and sea level rise threatens U.S. rural coastal landscapes and communities","docAbstract":"The United States (U.S.) coastal plain is subject to rising sea levels, land subsidence, more severe coastal storms, and more intense droughts. These changes lead to inputs of marine salts into freshwater-dependent coastal systems, creating saltwater intrusion. The penetration of salinity into the coastal interior is exacerbated by groundwater extraction and the high density of agricultural canals and ditches throughout much of the rural U.S. landscape. Together saltwater intrusion and sea level rise (SWISLR) create substantial changes to the social-ecological systems situated along the coastal plain. Many scholars and practitioners are engaged in studying and managing SWISLR impacts on social, economic, and ecological systems. However, most efforts are localized and disconnected, despite a widespread desire to understand this common threat. In addition to variable rates of sea level rise across the U.S. outer coastal plain, differences in geomorphic setting, water resources infrastructure and management, and climate extremes are resulting in different patterns of saltwater intrusion. Understanding both the absolute magnitude of this rapid environmental change, and the causes and consequences for its spatial and temporal variation presents an opportunity to build new mechanistic models to link directional climate change to temporally and spatially dynamic socio-environmental impacts. The diverse trajectories of change offer rich opportunities to test and refine modern theories of ecosystem state change in systems with exceptionally strong socioecological feedbacks.
Many species of wildlife alter their daily activity patterns in response to co-occurring species as well as the surrounding environment. Often smaller or subordinate species alter their activity patterns to avoid being active at the same time as larger, dominant species to avoid agonistic interactions. Human development can complicate interspecies interactions, as not all wildlife respond to human activity in the same manner. While some species may change the timing of their activity to avoid being active when humans are, others may be unaffected or may benefit from being active at the same time as humans to reduce predation risk or competition. To further explore these patterns, we used data from a coordinated national camera-trapping program (Snapshot USA) to explore how the activity patterns and temporal activity overlap of a suite of seven widely co-occurring mammalian mesocarnivores varied along a gradient of human development. Our focal species ranged in size from the large and often dominant coyote (Canis latrans) to the much smaller and subordinate Virginia opossum (Didelphis virginiana). Some species changed their activity based on surrounding human development. Coyotes were most active at night in areas of high and medium human development. Red fox (Vulpes vulpes) were more active at dusk in areas of high development relative to areas of low or medium development. However, because most species were primarily nocturnal regardless of human development, temporal activity overlap was high between all species. Only opossum and raccoon (Procyon lotor) showed changes in activity overlap with high overlap in areas of low development compared to areas of moderate development. Although we found that coyotes and red fox altered their activity patterns in response to human development, our results showed that competitive and predatory pressures between these seven widespread generalist species were insufficient to cause them to substantially alter their activity patterns.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0288477","usgsCitation":"McTigue, L., Lassiter, E.V., Shaw, M., Johansson, E., Wilson, K., and DeGregorio, B.A., 2024, Does daily activity overlap of seven mesocarnivores vary based on human development?: PLoS ONE, v. 19, no. 1, e0288477, 12 p., https://doi.org/10.1371/journal.pone.0288477.","productDescription":"e0288477, 12 p.","ipdsId":"IP-147648","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":440736,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0288477","text":"Publisher Index Page"},{"id":432154,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-01-11","publicationStatus":"PW","contributors":{"authors":[{"text":"McTigue, Leah","contributorId":310420,"corporation":false,"usgs":false,"family":"McTigue","given":"Leah","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":907438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lassiter, Ellery V.","contributorId":340666,"corporation":false,"usgs":false,"family":"Lassiter","given":"Ellery","email":"","middleInitial":"V.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":907439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shaw, Mike","contributorId":340667,"corporation":false,"usgs":false,"family":"Shaw","given":"Mike","email":"","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":907440,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johansson, Emily","contributorId":340668,"corporation":false,"usgs":false,"family":"Johansson","given":"Emily","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":907441,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, Ken","contributorId":340670,"corporation":false,"usgs":false,"family":"Wilson","given":"Ken","email":"","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":907442,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"DeGregorio, Brett Alexander 0000-0002-5273-049X","orcid":"https://orcid.org/0000-0002-5273-049X","contributorId":243214,"corporation":false,"usgs":true,"family":"DeGregorio","given":"Brett","email":"","middleInitial":"Alexander","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907443,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70250941,"text":"70250941 - 2024 - Pollen in polar ice implies eastern Canadian forest dynamics diverged from climate after European settlement","interactions":[],"lastModifiedDate":"2024-01-13T15:01:35.535688","indexId":"70250941","displayToPublicDate":"2024-01-11T08:59:21","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Pollen in polar ice implies eastern Canadian forest dynamics diverged from climate after European settlement","docAbstract":"Rapid warming and human exploitation threaten boreal forests. Understanding links among vegetation, climate, and people in this vast biome requires highly resolved long-term records that integrate regional inputs. We developed an 850-year pollen-based record of supraregional vegetation change using a southern Greenland ice core and atmospheric modeling that identified the boreal and mixed-conifer forests of eastern Canada as the dominant pollen source regions. Conifer pollen increased ∼1400 CE at the onset of the cooler and drier Little Ice Age. A subsequent decline began ∼1650 CE and a statistically significant pollen change after 1760 CE suggests ecological consequences of the Little Ice Age cooling and initial human exploitation that persisted until recent decades. These supraregional changes are broadly consistent with local records and demonstrate intensification of human impacts on northern forests, suggesting a shift from a climate-modulated to an increasingly human-controlled system during recent centuries.
Bivalves such as oysters and clams have been farmed in intertidal zones across the Puget Sound region of the Salish Sea for thousands of years. The variety of gear types used on bivalve farms creates complex vertical structure and attachment points for aquatic epiphytes and invertebrates which increases habitat structural complexity, but may alter eelgrass cover in areas where bivalve farms and eelgrass meadows overlap. Eelgrass meadows are highly productive and ecologically foundational nearshore habitats that provide valuable ecosystem services including the provision of nursery, refuge, and foraging habitat. Aquaculture has been a key feature of the environment in the Puget Sound for millennia, however, little is known about how well aquaculture practices are integrated into the system, and what services they provide to mobile species assemblages relative to unfarmed eelgrass meadows. We used stable isotope mixing models to estimate, for several species of nearshore fish and crab in two areas of North Puget Sound, Washington, the percent diet originating from either a natural bottom habitat (eelgrass meadows), farm habitat (oyster farms), or pelagic planktonic sources. Our results indicate that several species of nearshore fish such as surf perch and staghorn sculpin derive a significant proportion of their diets from farm areas, while crabs derive most of their diets from eelgrass habitat, and stickleback derive a significant proportion of their diets from planktonic sources. The results indicate that foraging habitat uses are species specific, and that several species that spatially overlap bivalve farms obtained a large percentage of their diets from adjacent bivalve farm habitat.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2023.1282225","usgsCitation":"Veggerby, K., Scheuerell, M.D., Sanderson, B., and Kiffney, P.M., 2024, Stable isotopes reveal intertidal fish and crabs use bivalve farms as foraging habitat in Puget Sound, Washington: Frontiers in Marine Science, v. 10, 1282225, 10 p., https://doi.org/10.3389/fmars.2023.1282225.","productDescription":"1282225, 10 p.","ipdsId":"IP-159006","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":440747,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2023.1282225","text":"Publisher Index Page"},{"id":429893,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.21054728999565,\n 48.854704403819\n ],\n [\n -122.82069064713903,\n 48.854704403819\n ],\n [\n -122.82069064713903,\n 47.27641993330366\n ],\n [\n -122.21054728999565,\n 47.27641993330366\n ],\n [\n -122.21054728999565,\n 48.854704403819\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2024-01-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Veggerby, Karl","contributorId":338024,"corporation":false,"usgs":false,"family":"Veggerby","given":"Karl","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":902906,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":902907,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sanderson, Beth","contributorId":338027,"corporation":false,"usgs":false,"family":"Sanderson","given":"Beth","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":902908,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kiffney, Peter M.","contributorId":338029,"corporation":false,"usgs":false,"family":"Kiffney","given":"Peter","middleInitial":"M.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":902909,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70250855,"text":"70250855 - 2024 - Comparing single and multiple objective constrained optimization algorithms for tuning a groundwater remediation system","interactions":[],"lastModifiedDate":"2024-01-10T16:31:29.928959","indexId":"70250855","displayToPublicDate":"2024-01-10T10:10:04","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7164,"text":"Environmental Modelling & Software","active":true,"publicationSubtype":{"id":10}},"title":"Comparing single and multiple objective constrained optimization algorithms for tuning a groundwater remediation system","docAbstract":"Groundwater flow and particle tracking models are critical tools to simulate the natural system, contaminant fate and transport, and effects of remediation. Constrained optimization uses models to systematically explore the interplay between remedial design and contaminant fate, considering uncertainty. Sequential Linear Programming (SLP) provides a design alternative addressing a single goal (e.g. maximum hydraulic containment, maximum mass removal). Multi-objective algorithms like Nondominated Sorting Genetic Algorithm (NSGA-II) explore the tradeoffs among such objectives and more (e.g. cost, public-supply well contamination). We explore both approaches at a contaminated site in Long Island, New York USA. We compare the algorithms and ramifications on results. NSGA-II explores, at additional computational cost, explicit tradeoffs among multiple objectives, providing additional insights relative to SLP. The NGSA-II algorithm allows for graphical consideration of three objectives. SLP decision variables often settle at predetermined bounds. Bounds assignment thus differs from parameter estimation; bounds must be acceptable rather than safeguards.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2024.105952","usgsCitation":"Fienen, M., Corson-Dosch, N., Jahn, K., and White, J., 2024, Comparing single and multiple objective constrained optimization algorithms for tuning a groundwater remediation system: Environmental Modelling & Software, v. 173, 105952, 12 p., https://doi.org/10.1016/j.envsoft.2024.105952.","productDescription":"105952, 12 p.","ipdsId":"IP-154816","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":467038,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2024.105952","text":"Publisher Index Page"},{"id":424282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Navy Grumman Groundwater Plume site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.51175816259176,\n 40.65126946756959\n ],\n [\n -73.42534399670191,\n 40.68206493506739\n ],\n [\n -73.45886673346936,\n 40.78790400347398\n ],\n [\n -73.57470641274439,\n 40.76505702193873\n ],\n [\n -73.51175816259176,\n 40.65126946756959\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"173","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corson-Dosch, Nicholas 0000-0002-6776-6241","orcid":"https://orcid.org/0000-0002-6776-6241","contributorId":202630,"corporation":false,"usgs":true,"family":"Corson-Dosch","given":"Nicholas","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jahn, Kalle 0000-0002-4976-0137","orcid":"https://orcid.org/0000-0002-4976-0137","contributorId":333053,"corporation":false,"usgs":true,"family":"Jahn","given":"Kalle","email":"","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891803,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"White, Jeremy T. 0000-0002-4950-1469","orcid":"https://orcid.org/0000-0002-4950-1469","contributorId":248830,"corporation":false,"usgs":false,"family":"White","given":"Jeremy T.","affiliations":[{"id":50032,"text":"GNS New Zealand","active":true,"usgs":false}],"preferred":false,"id":891804,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70251041,"text":"70251041 - 2024 - Polar paleoenvironmental perspectives on modern climate change","interactions":[],"lastModifiedDate":"2024-04-23T20:58:59.199767","indexId":"70251041","displayToPublicDate":"2024-01-10T06:22:51","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16703,"text":"PLOS Climate","active":true,"publicationSubtype":{"id":10}},"title":"Polar paleoenvironmental perspectives on modern climate change","docAbstract":"In today’s rapidly changing climate, society needs a better understanding of climate impacts on sea level, ice sheets and glaciers, sea ice, ocean circulation, ecosystems, biodiversity, and other aspects of planet Earth. Paleoenvironmental records provide a unique and invaluable source of insight into these complex issues, and place recent observations into a broader historical context. This essay discusses why paleoclimate reconstructions from polar regions provide critical information to help anticipate possible future climate impacts. By highlighting some key research examples, this essay explains the value of expanding proxy-based research in Arctic/Antarctic regions, and makes a case for paying greater attention to the lessons already distilled from it.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pclm.0000333","usgsCitation":"Gemery, L., and Lopez-Quiros, A., 2024, Polar paleoenvironmental perspectives on modern climate change: PLOS Climate, v. 3, no. 1, e0000333, 4 p., https://doi.org/10.1371/journal.pclm.0000333.","productDescription":"e0000333, 4 p.","ipdsId":"IP-159914","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":440753,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pclm.0000333","text":"Publisher Index Page"},{"id":424601,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-01-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Gemery, Laura 0000-0003-1966-8732 lgemery@usgs.gov","orcid":"https://orcid.org/0000-0003-1966-8732","contributorId":5402,"corporation":false,"usgs":true,"family":"Gemery","given":"Laura","email":"lgemery@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":892855,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lopez-Quiros, Adrian 0000-0002-7522-2834","orcid":"https://orcid.org/0000-0002-7522-2834","contributorId":333476,"corporation":false,"usgs":false,"family":"Lopez-Quiros","given":"Adrian","email":"","affiliations":[],"preferred":false,"id":892856,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70250904,"text":"70250904 - 2024 - Machine learning approaches to identify lithium concentration in petroleum produced waters","interactions":[],"lastModifiedDate":"2024-10-07T16:06:46.920365","indexId":"70250904","displayToPublicDate":"2024-01-09T08:18:01","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5502,"text":"Mineral Economics","onlineIssn":"2191-2211","printIssn":"2191-2203","active":true,"publicationSubtype":{"id":10}},"title":"Machine learning approaches to identify lithium concentration in petroleum produced waters","docAbstract":"Prices for battery-grade lithium have increased substantially since 2020, which is propelling the search for additional sources of this important element. Battery-grade lithium is predominately recovered from continental brines. Most crude oil and natural gas wells recover briny formation water, which may represent an additional source. Chemical analysis of these waters has been shown to indicate the presence of varying concentrations of lithium and related elements. This paper briefly reviews developments and literature supporting the presence of lithium in petroleum reservoir brines. It also describes the coverage and distribution of lithium data analyses in the United States Geological Survey National Produced Waters Geochemical Database (PWGD). It then addresses the question as to whether a lithium concentration can be accurately predicted using constituents of ion chemistry in produced brines from specific geologic formations. Four machine learning algorithms are employed to classify the commercial potential of lithium in oil field brines using data from oil wells recovering formation water from the Smackover Formation. The calibrated classification models are further applied to new (out-of-sample) data from the Marcellus Formation in the Appalachian Basin. Among the approaches considered, the predictive performance and wider applicability of the gradient boosted tree and the deep neural network models are determined to be the most promising. Finally, we discuss how the calibrated models could be applied to assure the quality of the data reported from chemical laboratory analysis and for imputation when lithium values are missing.
","language":"English","publisher":"Springer","doi":"10.1007/s13563-023-00409-8","usgsCitation":"Attanasi, E., Coburn, T., and Freeman, P., 2024, Machine learning approaches to identify lithium concentration in petroleum produced waters: Mineral Economics, v. 37, p. 477-497, https://doi.org/10.1007/s13563-023-00409-8.","productDescription":"21 p.","startPage":"477","endPage":"497","ipdsId":"IP-144611","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":424326,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","noUsgsAuthors":false,"publicationDate":"2024-01-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Attanasi, Emil 0000-0001-6845-7160 attanasi@usgs.gov","orcid":"https://orcid.org/0000-0001-6845-7160","contributorId":1809,"corporation":false,"usgs":true,"family":"Attanasi","given":"Emil","email":"attanasi@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":891987,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coburn, Timothy","contributorId":333122,"corporation":false,"usgs":false,"family":"Coburn","given":"Timothy","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":891988,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Freeman, Philip A. 0000-0002-0863-7431","orcid":"https://orcid.org/0000-0002-0863-7431","contributorId":206294,"corporation":false,"usgs":true,"family":"Freeman","given":"Philip A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":891989,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70250889,"text":"70250889 - 2024 - Mafic alkaline magmatism and rare earth element mineralization in the Mojave Desert, California: The Bobcat Hills connection to Mountain Pass","interactions":[],"lastModifiedDate":"2024-01-23T00:49:19.129501","indexId":"70250889","displayToPublicDate":"2024-01-09T07:36:36","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Mafic alkaline magmatism and rare earth element mineralization in the Mojave Desert, California: The Bobcat Hills connection to Mountain Pass","docAbstract":"Occurrences of alkaline and carbonatite rocks with high concentrations of rare earth elements (REE) are a defining feature of Precambrian geology in the Mojave Desert of southeastern California. The most economically important occurrence is the carbonatite stock at Mountain Pass, which constitutes the largest REE deposit in the United States. A central scientific goal is to understand the genesis of the carbonatite ore body in the context of widespread REE-rich igneous activity. A swarm of mafic alkaline (shonkinite) dikes has been mapped and sampled at Bobcat Hills, 65 km southeast of the Mountain Pass mine. Whole-rock geochemistry and zircon geochronology demonstrate a clear affinity to the ca. 1.4 Ga Mountain Pass intrusive system. Bobcat Hills dikes have comparably high REE concentrations (La ∼1,000× chondritic) and an error-weighted mean 207Pb/206Pb zircon crystallization age of 1,426 ± 2 Ma (2σ). Unlike the alkaline intrusions at Mountain Pass, which have abundant inherited zircon from Paleoproterozoic basement rocks and crustally influenced oxygen isotope compositions (δ18Ozircon = 6.5–7.5‰), the Bobcat Hills dikes lack any evidence of crustal assimilation and have oxygen isotope values that overlap a mantle range (Bobcat Hills average δ18Ozircon = 5.6 ± 0.3‰). The dikes were a high-temperature, early center of mafic alkaline magmatism in the Mojave Desert that serve as a snapshot of melt generation from a spatially extensive, metasomatized mantle source. We propose that modification of the crust over many tens of Myr at Mountain Pass created an environment that favored crustal assimilation and enabled ascent of late-stage, REE-rich carbonatite magmas.
Wind-waves have an important role in Earth system dynamics through air–sea interactions and are key drivers of coastal and offshore hydro-morphodynamics that affect communities, ecosystems, infrastructure and operations. In this Review, we outline historical and projected changes in the wind-wave climate over the world’s oceans, and their impacts. Historical trend analysis is challenging owing to the presence of temporal inhomogeneities from increased numbers and types of assimilated data. Nevertheless, there is general agreement over a consistent historical increase in mean wave height of 1–3 cm yr−1 in the Southern and Arctic Oceans, with extremes increasing by >10 cm yr−1 for the latter. By 2100, mean wave height is projected to rise by 5–10% in the Southern Ocean and eastern tropical South Pacific, and by >100% in the Arctic Ocean. By contrast, reductions in mean wave height up to 10% are expected in the North Atlantic and North Pacific, with regional variability and uncertainty for changes in extremes. Differences between 1.5 °C and warmer worlds reveal the potential benefit of limiting anthropogenic warming. Resolving global-scale climate change impacts on coastal processes and atmospheric–ocean–wave interactions requires a step-up in observational and modeling capabilities, including enhanced spatiotemporal resolution and coverage of observations, more homogeneous data products, multidisciplinary model improvement, and better sampling of uncertainty with larger ensembles.
Fieldwork is a critical tool for scientific research, particularly in applied disciplines. Yet fieldwork is often unsafe, especially for members of historically marginalized groups and people whose presence in scientific spaces threatens traditional hierarchies of power, authority, and legitimacy. Research is needed to identify interventions that prevent sexual harassment and assault from occurring in the first place. We conducted a quasi-experiment assessing the impacts of a 90-min interactive training on field-based staff in a United States state government agency. We hypothesized that the knowledge-based interventions, social modeling, and mastery experiences included in the training would increase participants’ sexual harassment and assault prevention knowledge, self-efficacy, behavioural intention, and behaviour after the training compared to a control group of their peers. Treatment–control and pre-post training survey data indicate that the training increased participants’ sexual harassment and assault prevention knowledge and prevention self-efficacy, and, to a lesser extent, behavioural intention. These increases persisted several months after the training for knowledge and self-efficacy. While we did not detect differences in the effect of the training for different groups, interestingly, post-hoc tests indicated that women and members of underrepresented racial groups generally scored lower compared to male and white respondents, suggesting that these groups self-assess their own capabilities differently. Finally, participants’ likelihood to report incidents increased after the training but institutional reports remained low, emphasizing the importance of efforts to transform reporting systems and develop better methods to measure bystander actions. These results support the utility of a peer-led interactive intervention for improving workplace culture and safety in scientific fieldwork settings.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-023-49203-0","usgsCitation":"Cronin, M.R., Zavaleta, E.S., Beltran, R.S., Esparza, M., Payne, A., Termin, V., Thompson, J., and Jones, M.S., 2024, Testing the effectiveness of interactive training on sexual harassment and assault in field science: Scientific Reports, v. 14, 523, 18 p., https://doi.org/10.1038/s41598-023-49203-0.","productDescription":"523, 18 p.","ipdsId":"IP-159122","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":440762,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-023-49203-0","text":"Publisher Index Page"},{"id":430050,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","noUsgsAuthors":false,"publicationDate":"2024-01-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Cronin, Melissa R.","contributorId":338415,"corporation":false,"usgs":false,"family":"Cronin","given":"Melissa","email":"","middleInitial":"R.","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":903256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zavaleta, Erika S.","contributorId":338416,"corporation":false,"usgs":false,"family":"Zavaleta","given":"Erika","email":"","middleInitial":"S.","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":903257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beltran, Roxanne S.","contributorId":338418,"corporation":false,"usgs":false,"family":"Beltran","given":"Roxanne","email":"","middleInitial":"S.","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":903258,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esparza, Melanie","contributorId":338421,"corporation":false,"usgs":false,"family":"Esparza","given":"Melanie","email":"","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":903259,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Payne, Allison","contributorId":338424,"corporation":false,"usgs":false,"family":"Payne","given":"Allison","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":903260,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Termin, Valerie","contributorId":338429,"corporation":false,"usgs":false,"family":"Termin","given":"Valerie","email":"","affiliations":[{"id":81126,"text":"California Department of Fish & Wildlife","active":true,"usgs":false}],"preferred":false,"id":903261,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thompson, Joseph","contributorId":338431,"corporation":false,"usgs":false,"family":"Thompson","given":"Joseph","email":"","affiliations":[{"id":81127,"text":"Los Angeles County Department of Public Health","active":true,"usgs":false}],"preferred":false,"id":903262,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jones, Megan Siobhan 0000-0002-4284-3650","orcid":"https://orcid.org/0000-0002-4284-3650","contributorId":294651,"corporation":false,"usgs":true,"family":"Jones","given":"Megan","email":"","middleInitial":"Siobhan","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903263,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70250830,"text":"ofr20231098 - 2024 - Developing and implementing an International Macroseismic Scale (IMS) for earthquake engineering, earthquake science, and rapid damage assessment","interactions":[],"lastModifiedDate":"2024-01-09T16:15:18.237937","indexId":"ofr20231098","displayToPublicDate":"2024-01-08T16:00:00","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":"2023-1098","displayTitle":"Developing and Implementing an International Macroseismic Scale (IMS) for Earthquake Engineering, Earthquake Science, and Rapid Damage Assessment","title":"Developing and implementing an International Macroseismic Scale (IMS) for earthquake engineering, earthquake science, and rapid damage assessment","docAbstract":"Macroseismic observations and analysis connect our collective seismological past with the present and the present to the future by facilitating hazard estimates and communicating the effects of ground shaking to a wide variety of audiences across the ages. Invaluable ground shaking and building damage information is gained through standardized, systematic approaches for assigning intensities and, importantly, sharing and archiving those assignments in a reproducible form. The applications for these assignments are far reaching. Traditional macroseismic surveys provide vital constraints on critical aspects of earthquakes and their effects on society, whereas internet-based macroseismic datasets are extremely valuable for real-time earthquake situational awareness, and they contribute to later engineering loss and risk analyses. These important applications of macroseismic observations would be helped by revisiting traditional macroseismic surveys for modern environments, standardizing internet-based collection strategies, and ensuring compatibility between traditional and internet-based approaches of macroseismic data collection.
Even with best practices, we have identified several limitations with modern macroseismic data collection approaches, particularly from the U.S. Geological Survey's perspective. First, whereas crowdsourced, internet-based intensities such as “Did You Feel It?” are robust and definitive for lower intensities, they are poorly defined above intensity VII, where damage observations may require expert knowledge of each building’s structural system.
Second, in the United States, we use the Modified Mercalli Intensity (MMI) Scale, which is consistent with—yet inferior to—the more recently developed European Macroseismic Scale (EMS–98; Grünthal and others, 1998). Similarly, New Zealand uses the New Zealand MMI Scale (Dowrick and others, 2008), which lacks detail on how to assign intensities above MMI VIII. The EMS–98 fundamentally advanced the science of macroseismic intensity assignment by requiring quantitative assessments at each location through consistent application on statistical ranges of well-defined damage grades to building-specific vulnerability classes. Lastly, the United States and New Zealand no longer have professionals dedicated to conducting traditional macroseismic field surveys, so a strategy is needed for allowing postearthquake building inspectors and insurance loss assessors to contribute to intensity assignments.
The goals of our International Macroseismic Scale workshop were thus twofold. First, harmonize the MMI Scale with EMS–98 for the United States and New Zealand—which share several similar building types—by considering those structures and associated damage grades that are not well represented in the current EMS–98 building vulnerability class table. Second, begin to formalize the process of augmenting EMS–98 with new regional building classes and damage grades toward the development of a macroseismic scale that can be used globally, beyond the United States and New Zealand. Such an effort necessarily requires reviewing and expanding the original EMS–98 explanatory documents and consideration of any required revisions. We can build on the shoulders of giants in that a few of the original EMS–98 developers and experts participated in and were integral to our workshop. Their background and guidance were key in moving forward toward an international scale.
We agreed that additional building vulnerability classes, damage grades, and written and pictorial descriptions are necessary and ideally accompanied by a detailed paper trail for other nations to follow. If we can improve the macroseismic assignment process in both nations, we can also aim to refine the process of collecting postearthquake impact data, a boon to many engineering and financial concerns.
The benefits of a truly International Macroseismic Scale are considerable for both the engineering and seismology communities. A modern macroseismic scale requires more deliberate archival damage data collection, motivating more consistent and accessible postevent datasets that would have applications beyond the specific event. Applying field-collected building damage data toward macroseismic assignments would allow for increased coordination between engineering reconnaissance teams and local inspectors in collecting such data for official purposes. In addition, rapid and consistent intensity assignments globally would enable more accurate ShakeMaps—and thus improved earthquake engineering and geotechnical forensics, loss and risk estimates, and correlations between macroseismic intensity and ground motion parameters.
A brief summary of the Powell Center IMS workshop was published by Wald and others (2023) in the magazine Eos. This Open-File Report describes the workshop, its discussions, and its outcomes in detail. In summarizing the workshop, we have added important background material and reflections for proper context.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20231098","usgsCitation":"Wald, D.J., Goded, T., Hortacsu, A., and Loos, S.C., 2024, Developing and implementing an International Macroseismic Scale (IMS) for earthquake engineering, earthquake science, and rapid damage assessment: U.S. Geological Survey Open-File Report 2023–1098, 55 p., https://doi.org/10.3133/ofr20231098.","productDescription":"viii, 55 p.","onlineOnly":"Y","ipdsId":"IP-149203","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":424198,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1098/images"},{"id":424196,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1098/ofr20231098.pdf","text":"Report","size":"7.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1098"},{"id":424195,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1098/coverthb.jpg"},{"id":424207,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231098/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1098"},{"id":424199,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1098/ofr20231098.xml"}],"contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, Mail Stop 966
Denver, CO 80225
Urban stream restoration requires a quantitative understanding of hydromodification to provide a scientific basis for establishing, prioritizing, and monitoring stream quality improvement goals. A study by the U.S. Geological Survey, in cooperation with the Johnson County Urban stream restoration benefits from a quantitative understanding of hydromodification to provide a scientific basis for establishing, prioritizing, and monitoring stream quality improvement goals. A study by the U.S. Geological Survey, in cooperation with the Johnson County Stormwater Management Program, began in 2017 to assess streamflow conditions at U.S. Geological Survey streamgages along Indian and Kill Creeks in Johnson County, Kansas. These streams represent the most urban (Indian Creek) and least urban (Kill Creek) drainage basins in the county. The assessment used 40 streamflow indicators to characterize streamflow conditions for both streams and quantify the degree of hydromodification for Indian Creek. The 40 streamflow indicators consisted of 35 commonly used indicators for characterizing streamflow, 2 less common seasonality indicators, and 3 other indicators based on duration curves, runoff hydrographs, and streamflow percentile classes. The indicators represented five key components of the natural streamflow regime: magnitude, frequency, duration, timing, and rate of change. As part of the study, indicators were evaluated as to general utility for characterizing streamflow conditions, quantifying hydromodification, and assessing the effectiveness of implemented management practices intended to restore urban streams. Results identifying indicators that serve these purposes could be applied more generally to other streams in Johnson County to assess hydromodification and potential restoration opportunities. Although the same set of streamflow indicators may not apply to other regions, methods and results presented in this report provide guidance, techniques, and perspective for future related or similar studies elsewhere, particularly those designed to quantify hydromodification of urban streams and monitor the effectiveness of restoration efforts.
Compared to Kill Creek, which, for the purposes of this study, was considered representative of a least disturbed rural reference condition, Indian Creek hydrology was determined to be substantially modified because of urbanization. Of the 35 streamflow indicators evaluated, 19 indicated a generally consistent and substantial difference between the 2 streams. Hydromodification of Indian Creek was characterized by larger annual mean and monthly mean streamflows (and, thus, larger streamflow volumes), larger low streamflows of shorter duration, larger high streamflows with increased frequency and shorter duration, faster rise and fall rates, and decreased seasonality of high and low streamflows. For the two seasonality indicators, seasonality of high and low streamflows decreased. Duration curves, runoff event hydrographs, and streamflow percentile classes also indicated differences between the two streams for specific ranges of streamflow.
Indicators that were useful in identifying generally consistent and substantial differences between the two streams, and therefore demonstrating they collectively or individually may be indicators of hydromodification, included annual median and mean flows; monthly mean flows for February, July, August, September, October, November, and December; all the minimum mean flow indictors (1-day, 3-day, 7-day, 30-day, and 90-day); annual number and mean magnitude of peak flows; some of the flow pulse indicators; and rise and fall rates. Indicators determined to be marginally useful or not useful for identifying consistent and substantial streamflow differences between streams included the flashiness indicators Richards-Baker flashiness index and the fraction of the year the daily mean flow is greater than the annual mean flow, which was not expected.
Municipalities are challenged by the need to restore stream quality in urbanized areas where options are limited because of existing development. Understanding hydromodification effects and implications for stream quality can help managers plan urban development that minimizes degradation of stream quality and provides insights for implementing effective management practices. Streamflow indicators identified in this report can be used to guide urban stream restoration. In particular, the most useful indicators could form the basis of numeric criteria for restoration goals aimed at achieving or progressing toward more natural streamflow conditions—and, by extension, more healthy ecosystems—by characterizing flow conditions, quantifying hydromodification, establishing stream-restoration goals, and monitoring progress toward achieving those goals as management practices are implemented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235063","collaboration":"Prepared in cooperation with the Johnson County Stormwater Management Program","usgsCitation":"Rasmussen, T.J., Juracek, K.E., Eslick, P.J., Eng, K., and Kellenberger, L.J., 2024, Streamflow characterization and hydromodification, Indian and Kill Creek Basins, Johnson County, Kansas, 1985–2018: U.S. Geological Survey Scientific Investigations Report 2023–5063, 44 p., https://doi.org/10.3133/sir20235063.","productDescription":"Report: v, 44 p.; 1 Appendix; 2 Tables; Dataset","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-114771","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":424135,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5063/sir20235063.XML"},{"id":424140,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5063/downloads/sir20235063_table3.1.xlsx","text":"Table 3.1","size":"112 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":424139,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5063/downloads/sir20235063_table2.1.csv","text":"Table 2.1","size":"10.5 kB","linkFileType":{"id":7,"text":"csv"}},{"id":424133,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5063/coverthb.jpg"},{"id":424134,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5063/sir20235063.pdf","text":"Report","size":"12.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5063"},{"id":499323,"rank":12,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115947.htm","linkFileType":{"id":5,"text":"html"}},{"id":424143,"rank":11,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235063/full"},{"id":424142,"rank":10,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":424136,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5063/images/"},{"id":424137,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5063/downloads/sir20235063_appendix1.pdf","text":"Appendix 1","size":"606 kB","linkFileType":{"id":1,"text":"pdf"}},{"id":424138,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5063/downloads/sir20235063_table2.1.xlsx","text":"Table 2.1","size":"40.8 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":424141,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5063/downloads/sir20235063_table3.1.csv","text":"Table 3.1","size":"51.4 kB","linkFileType":{"id":7,"text":"csv"}}],"country":"United States","state":"Kansas","county":"Johnson County","otherGeospatial":"Indian and Kill Creek Basins","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-94.6075,39.0437],[-94.6075,39.0399],[-94.6082,38.8463],[-94.6084,38.8341],[-94.6102,38.7376],[-95.0572,38.7395],[-95.0558,38.9816],[-95.0477,38.9778],[-95.0383,38.9771],[-95.0312,38.9773],[-95.0292,38.9813],[-95.0271,38.9881],[-95.0249,38.9962],[-95.0189,38.9987],[-95.0135,38.9991],[-95.0077,38.998],[-94.9946,38.9976],[-94.9899,38.997],[-94.9841,38.995],[-94.9789,38.9926],[-94.9755,38.9885],[-94.9704,38.9851],[-94.9645,38.9832],[-94.9575,38.982],[-94.9527,38.9828],[-94.9479,38.9845],[-94.9448,38.9871],[-94.9423,38.9898],[-94.9386,38.9933],[-94.9367,38.9964],[-94.9335,38.9995],[-94.9264,38.9998],[-94.9217,38.9996],[-94.9176,38.9977],[-94.9209,38.9919],[-94.923,38.9856],[-94.9207,38.9837],[-94.9164,38.9859],[-94.9115,38.9889],[-94.9078,38.9924],[-94.9014,39.0022],[-94.8989,39.0053],[-94.8945,39.0102],[-94.8919,39.0155],[-94.891,39.021],[-94.8875,39.0313],[-94.8824,39.0379],[-94.8768,39.0441],[-94.8681,39.052],[-94.8631,39.0564],[-94.8488,39.0578],[-94.8318,39.0546],[-94.8131,39.0486],[-94.8038,39.0456],[-94.7197,39.0435],[-94.6693,39.0433],[-94.6075,39.0437]]]},\"properties\":{\"name\":\"Johnson\",\"state\":\"KS\"}}]}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049
Hidden Markov Models (HMMs) are often used to model multi-state capture-recapture data in ecology. However, a variety of HMM modeling approaches and software exist, including both maximum likelihood and Bayesian methods. The diversity of these methods obscures the underlying HMM and can exaggerate minor differences in parameterization.
In this paper, we describe a general framework for modelling multi-state capture-recapture data via HMMs using both maximum likelihood and Bayesian methods. We then apply an HMM to invasive silver carp telemetry data from the Illinois River and compare the results estimated by both methods.
Our analysis demonstrates disadvantages of relying on a single approach and highlights insights obtained from implementing both methods together. While both methods often struggled to converge, our results show biologically informative priors for Bayesian methods and initial values for maximum likelihood methods can guide convergence toward realistic solutions. Incorporating prior knowledge of the system can successfully constrain estimation to biologically realistic movement and detection probabilities when dealing with sparse data.
Biologically unrealistic estimates may be a sign of poor model convergence. In contrast, consistent convergence behavior across approaches can increase the credibility of a model. Estimates of movement probabilities can strongly influence the predicted population dynamics of a system. Therefore, thoroughly assessing results from HMMs is important when evaluating potential management strategies, particularly for invasive species.
","language":"English","publisher":"Springer","doi":"10.1186/s40462-023-00434-w","usgsCitation":"Labuzzetta, C.J., Coulter, A.A., and Erickson, R.A., 2024, Comparing maximum likelihood and Bayesian methods for fitting hidden Markov models to multi-state capture-recapture data of invasive carp in the Illinois River: Ecology Movement, v. 12, 2, 15 p., https://doi.org/10.1186/s40462-023-00434-w.","productDescription":"2, 15 p.","ipdsId":"IP-150787","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":440773,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-023-00434-w","text":"Publisher Index Page"},{"id":426962,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","otherGeospatial":"Illinois River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.0589176022094,\n 38.26712368948924\n ],\n [\n -87.45540197720929,\n 38.26712368948924\n ],\n [\n -87.45540197720929,\n 42.10926577184944\n ],\n [\n -91.0589176022094,\n 42.10926577184944\n ],\n [\n -91.0589176022094,\n 38.26712368948924\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2024-01-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Labuzzetta, Charles J. 0000-0002-6027-0120","orcid":"https://orcid.org/0000-0002-6027-0120","contributorId":332055,"corporation":false,"usgs":true,"family":"Labuzzetta","given":"Charles","email":"","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":897153,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coulter, Alison A.","contributorId":90992,"corporation":false,"usgs":false,"family":"Coulter","given":"Alison","email":"","middleInitial":"A.","affiliations":[{"id":26877,"text":"Southern Illinois University, Carbondale, IL","active":true,"usgs":false},{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":897154,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":897155,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70250932,"text":"70250932 - 2024 - Subsurface redox interactions regulate ebullitive methane flux in heterogeneous Mississippi River deltaic wetland","interactions":[],"lastModifiedDate":"2024-01-13T15:05:43.092673","indexId":"70250932","displayToPublicDate":"2024-01-07T09:03:34","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5407,"text":"Journal of Advances in Modeling Earth Systems","active":true,"publicationSubtype":{"id":10}},"title":"Subsurface redox interactions regulate ebullitive methane flux in heterogeneous Mississippi River deltaic wetland","docAbstract":"As interfaces connecting terrestrial and ocean ecosystems, coastal wetlands develop temporally and spatially complex redox conditions, which drive uncertainties in greenhouse gas emission as well as the total carbon budget of the coastal ecosystem. To evaluate the role of complex redox reactions in methane emission from coastal wetlands, a coupled reactive-transport model was configured to represent subsurface biogeochemical cycles of carbon, nitrogen, and sulfur, along with production and transport of multiple gas species through diffusion and ebullition. This model study was conducted at multiple sites along a salinity gradient in the Barataria Basin at the Mississippi River Deltaic Plain. Over a freshwater to saline gradient, simulated total flux of methane was primarily controlled by its subsurface production and consumption, which were determined by redox reactions directly (e.g., methanogenesis, methanotrophy) and indirectly (e.g., competition with sulfate reduction) under aerobic and/or anaerobic conditions. At fine spatiotemporal scales, surface methane fluxes were also strongly dependent on transport processes, with episodic ebullitive fluxes leading to higher spatial and temporal variability compared to the gradient-driven diffusion flux. Ebullitive methane fluxes were determined by methane fraction in total ebullitive gas and the frequency of ebullitive events, both of which varied with subsurface methane concentrations and other gas species. Although ebullition thresholds are constrained by local physical factors, this study indicates that redox interactions not only determine gas composition in ebullitive fluxes but can also regulate ebullition frequency through gas production.
Between December 2020 and April 2023, the COVID-19 Scenario Modeling Hub (SMH) generated operational multi-month projections of COVID-19 burden in the US to guide pandemic planning and decision-making in the context of high uncertainty. This effort was born out of an attempt to coordinate, synthesize and effectively use the unprecedented amount of predictive modeling that emerged throughout the COVID-19 pandemic. Here we describe the history of this massive collective research effort, the process of convening and maintaining an open modeling hub active over multiple years, and attempt to provide a blueprint for future efforts. We detail the process of generating 17 rounds of scenarios and projections at different stages of the COVID-19 pandemic, and disseminating results to the public health community and lay public. We also highlight how SMH was expanded to generate influenza projections during the 2022–23 season. We identify key impacts of SMH results on public health and draw lessons to improve future collaborative modeling efforts, research on scenario projections, and the interface between models and policy.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epidem.2023.100738","usgsCitation":"Loo, S.L., Howerton, E., Contamin, L., Smith, C.P., Borchering, R.K., Mullany, L.C., Bents, S., Carcelen, E., Jung, S., Bogich, T.L., van Panhuis, W., Kerr, J., Espino, J., Yan, K., Hochheiser, H., Runge, M.C., Shea, K., Lessler, J., Viboud, C., and Truelove, S., 2024, The US COVID-19 and Influenza Scenario Modeling Hubs: Delivering long-term projections to guide policy: Epidemics, v. 46, 100738, 10 p., https://doi.org/10.1016/j.epidem.2023.100738.","productDescription":"100738, 10 p.","ipdsId":"IP-158025","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":489978,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epidem.2023.100738","text":"Publisher Index 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0000-0002-7607-8248","orcid":"https://orcid.org/0000-0002-7607-8248","contributorId":193646,"corporation":false,"usgs":false,"family":"Shea","given":"Katriona","email":"","affiliations":[],"preferred":false,"id":929854,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Lessler, Justin","contributorId":258042,"corporation":false,"usgs":false,"family":"Lessler","given":"Justin","email":"","affiliations":[{"id":36717,"text":"Johns Hopkins University","active":true,"usgs":false}],"preferred":false,"id":929855,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Viboud, Cécile","contributorId":351985,"corporation":false,"usgs":false,"family":"Viboud","given":"Cécile","affiliations":[{"id":52216,"text":"National Institutes of Health Fogarty International Center","active":true,"usgs":false}],"preferred":false,"id":929856,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Truelove, Shaun","contributorId":258037,"corporation":false,"usgs":false,"family":"Truelove","given":"Shaun","email":"","affiliations":[{"id":36717,"text":"Johns Hopkins University","active":true,"usgs":false}],"preferred":false,"id":929857,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}} ,{"id":70250867,"text":"70250867 - 2024 - Planning hydrological restoration of coastal wetlands: Key model considerations and solutions","interactions":[],"lastModifiedDate":"2024-01-25T14:55:29.470908","indexId":"70250867","displayToPublicDate":"2024-01-06T09:21:40","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Planning hydrological restoration of coastal wetlands: Key model considerations and solutions","docAbstract":"The hydrological restoration of coastal wetlands is an emerging approach for mitigating and adapting to climate change and enhancing ecosystem services such as improved water quality and biodiversity. This paper synthesises current knowledge on selecting appropriate modelling approaches for hydrological restoration projects. The selection of a modelling approach is based on project-specific factors, such as costs, risks, and uncertainties, and aligns with the overall project objectives. We provide guidance on model selection, emphasising the use of simpler and less expensive modelling approaches when appropriate, and identifying situations when models may not be required for project managers to make informed decisions. This paper recognises and supports the widespread use of hydrological restoration in coastal wetlands by bridging the gap between hydrological science and restoration practices. It underscores the significance of project objectives, budget, and available data and offers decision-making frameworks, such as decision trees, to aid in matching modelling methods with specific project outcomes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2024.169881","usgsCitation":"Twomey, A., Nunez, K., Carr, J., Crooks, S., Friess, D., Glamore, W., Orr, M., Reef, R., Rogers, K., Waltham, N., and Lovelock, C.E., 2024, Planning hydrological restoration of coastal wetlands: Key model considerations and solutions: Science of the Total Environment, v. 915, 169881, 16 p., https://doi.org/10.1016/j.scitotenv.2024.169881.","productDescription":"169881, 16 p.","ipdsId":"IP-156710","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":440785,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2024.169881","text":"Publisher Index Page"},{"id":424276,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"915","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Twomey, Alice","contributorId":333063,"corporation":false,"usgs":false,"family":"Twomey","given":"Alice","email":"","affiliations":[{"id":13335,"text":"The University of Queensland","active":true,"usgs":false}],"preferred":false,"id":891826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nunez, Karinna","contributorId":333064,"corporation":false,"usgs":false,"family":"Nunez","given":"Karinna","email":"","affiliations":[{"id":6708,"text":"Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":891827,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carr, Joel A. 0000-0002-9164-4156 jcarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9164-4156","contributorId":168645,"corporation":false,"usgs":true,"family":"Carr","given":"Joel A.","email":"jcarr@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":891828,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crooks, Steve","contributorId":333065,"corporation":false,"usgs":false,"family":"Crooks","given":"Steve","affiliations":[{"id":38182,"text":"Silvestrum Climate Associates","active":true,"usgs":false}],"preferred":false,"id":891829,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Friess, Daniel A.","contributorId":35454,"corporation":false,"usgs":false,"family":"Friess","given":"Daniel A.","affiliations":[{"id":25407,"text":"Department of Geography, National University of Singapore","active":true,"usgs":false}],"preferred":false,"id":891830,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Glamore, William","contributorId":333067,"corporation":false,"usgs":false,"family":"Glamore","given":"William","email":"","affiliations":[{"id":27304,"text":"University of New South Wales","active":true,"usgs":false}],"preferred":false,"id":891831,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Orr, Michelle","contributorId":197537,"corporation":false,"usgs":false,"family":"Orr","given":"Michelle","email":"","affiliations":[],"preferred":false,"id":891832,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Reef, Ruth","contributorId":298614,"corporation":false,"usgs":false,"family":"Reef","given":"Ruth","affiliations":[{"id":64623,"text":"Monash University, Australia","active":true,"usgs":false}],"preferred":false,"id":891833,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rogers, Kerrylee","contributorId":64151,"corporation":false,"usgs":false,"family":"Rogers","given":"Kerrylee","email":"","affiliations":[{"id":16754,"text":"University of Wollongong, Australia","active":true,"usgs":false}],"preferred":false,"id":891834,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Waltham, Nathan","contributorId":333070,"corporation":false,"usgs":false,"family":"Waltham","given":"Nathan","email":"","affiliations":[{"id":40403,"text":"James Cook University","active":true,"usgs":false}],"preferred":false,"id":891835,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lovelock, Catherine E.","contributorId":215562,"corporation":false,"usgs":false,"family":"Lovelock","given":"Catherine","email":"","middleInitial":"E.","affiliations":[{"id":39280,"text":"School of Biological Sciences, The University of Queensland","active":true,"usgs":false}],"preferred":false,"id":891836,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70252011,"text":"70252011 - 2024 - Complex landslide patterns explained by local intra-unit variability of stratigraphy and structure: Case study in the Tyee Formation, Oregon, USA","interactions":[],"lastModifiedDate":"2024-03-11T12:18:44.85142","indexId":"70252011","displayToPublicDate":"2024-01-06T07:15:17","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1517,"text":"Engineering Geology","active":true,"publicationSubtype":{"id":10}},"title":"Complex landslide patterns explained by local intra-unit variability of stratigraphy and structure: Case study in the Tyee Formation, Oregon, USA","docAbstract":"Lithology and geologic structure are important controls on landslide susceptibility and are incorporated into many regional landslide hazard models. Typically, metrics for mapped geologic units are used as model input variables and a single set of values for material strength are assumed, regardless of spatial heterogeneities that may exist within a map unit. Here we describe how differences in bedding thickness, grain size, inferred uniaxial compressive strength, and bedding dip control the inherent susceptibility of slopes to deep-seated failure within a single mapped geologic unit - the Tyee Formation of Oregon, USA. The Tyee, which covers over 15,000 km2 and underlies much of the Oregon Coast Range, comprises gently folded alternating beds of sandstone and siltstone deposited as turbidites, forming a 2-km thick Eocene submarine fan which has been uplifted and exhumed through the Cenozoic. Deep-seated landslides are widespread in the Tyee, but form a complex spatial pattern such that landslide density ranges from 0 to 24% of the total landscape area. These slides are often extensive and sufficiently deep to reduce local hillslope gradients, resulting in a strong negative correlation between landslide density and mean local slope. Mean annual precipitation and predicted strong ground motions from Cascadia earthquake scenarios also fail to explain the spatial distribution of deep-seated landslides. Consequently, landslide stability models, which are strongly influenced by landscape slope, pore-water pressure, and seismic acceleration, yield landslide susceptibility maps which are broadly anti-correlated with mapped deep-seated landslide density. Through a multivariable linear regression model, we show that much of the variance in deep-seated landslide density can be explained by variability of intra-unit stratigraphic and structural characteristics, which we measure at 128 sites across two study areas totaling ∼3000 km2. Our results suggest bedding dip is only weakly correlated to landslide density, but strongly influences landslide failure style. Subtle increases in bedding dip, even in the gently folded Tyee Formation, result in a substantially higher likelihood of a landslide being cataclinal, or parallel to bedding. Overall, we find a slight majority of landslides fail within these cataclinal slopes, and that these landslides tend to be larger than non-cataclinal landslides. We also show that the lithological and structural properties that influence landslide susceptibility are distinct for these two populations of landslides. Our results demonstrate how localized, intra-unit, geologic variability can exert strong control on landslide susceptibility and failure style. This suggests that in some locations, landslide hazard models could be significantly improved by incorporating detailed, spatially variable, geologic properties rather than relying solely on generalized geologic map units.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.enggeo.2023.107387","usgsCitation":"LaHusen, S.R., and Grant, A.R., 2024, Complex landslide patterns explained by local intra-unit variability of stratigraphy and structure: Case study in the Tyee Formation, Oregon, USA: Engineering Geology, v. 329, 107387, 14 p., https://doi.org/10.1016/j.enggeo.2023.107387.","productDescription":"107387, 14 p.","ipdsId":"IP-146959","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":440788,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.enggeo.2023.107387","text":"Publisher Index Page"},{"id":426489,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Tyee Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -125.10474453625554,\n 42.47204971687748\n ],\n [\n -121.72095547375605,\n 42.47204971687748\n ],\n [\n -121.72095547375605,\n 45.35210028381104\n ],\n [\n -125.10474453625554,\n 45.35210028381104\n ],\n [\n -125.10474453625554,\n 42.47204971687748\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"329","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"LaHusen, Sean Richard 0000-0003-4246-4439","orcid":"https://orcid.org/0000-0003-4246-4439","contributorId":294677,"corporation":false,"usgs":true,"family":"LaHusen","given":"Sean","email":"","middleInitial":"Richard","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":896262,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grant, Alex R. 0000-0002-5096-4305","orcid":"https://orcid.org/0000-0002-5096-4305","contributorId":219066,"corporation":false,"usgs":true,"family":"Grant","given":"Alex","middleInitial":"R.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":896263,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70250949,"text":"70250949 - 2024 - Environmental and geographical factors influence the occurrence and abundance of the southern house mosquito, Culex quinquefasciatus, in Hawai‘i","interactions":[],"lastModifiedDate":"2024-01-13T15:15:09.210779","indexId":"70250949","displayToPublicDate":"2024-01-05T09:11:23","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":"Environmental and geographical factors influence the occurrence and abundance of the southern house mosquito, Culex quinquefasciatus, in Hawai‘i","docAbstract":"Hawaiian honeycreepers, a group of endemic Hawaiian forest birds, are being threatened by avian malaria, a non-native disease that is driving honeycreepers populations to extinction. Avian malaria is caused by the parasite Plasmodium relictum, which is transmitted by the invasive mosquito Culex quinquefasciatus. Environmental and geographical factors play an important role in shaping mosquito-borne disease transmission dynamics through their influence on the distribution and abundance of mosquitoes. We assessed the effects of environmental (temperature, precipitation), geographic (site, elevation, distance to anthropogenic features), and trap type (CDC light trap, CDC gravid trap) factors on mosquito occurrence and abundance. Occurrence was analyzed using classification and regression tree models (CART) and generalized linear models (GLM); abundance (count data) was analyzed using generalized linear mixed models (GLMMs). Models predicted highest mosquito occurrence at mid-elevation sites and between July and November. Occurrence increased with temperature and precipitation up to 580 mm. For abundance, the best model was a zero-inflated negative-binomial model that indicated higher abundance of mosquitoes at mid-elevation sites and peak abundance between August and October. Estimation of occurrence and abundance as well as understanding the factors that influence them are key for mosquito control, which may reduce the risk of forest bird extinction.
Proterozoic rocks exposed in the southwestern U.S.A. represent one of the best examples of crustal growth by arc-related magmatism and accretionary orogenesis. Within the Southwest the 1.8–1.7 Ga Yavapai Province is widely regarded as a classic example of juvenile arc crust, however 1.8–2.5 Ga inherited zircon and Nd and Hf model ages have been recognized near Gunnison in central Colorado. These data have led to questions regarding the extent and nature of pre-1.8 Ga crustal material and the genesis of the Yavapai Province. We present evidence for a geochemically distinct, spatially restricted crustal block underlain by pre-1.8 Ga crust material (referred to here as the Gunnison block) in central to western Colorado within the Yavapai Province. The Gunnison block is characterized by 1.8–1.9 and 2.4–2.6 Ga inherited zircon, Pb isotopic systematics (μ = 9.8 ± 0.1, κ = 3.7 ± 0.1) elevated relative to 1.8 Ga depleted mantle values, 1.8–2.5 Ga Nd and Hf model ages, and a distinct pressure-temperature-time history. The geochemical data are consistent with mixing between juvenile 1.8 Ga and pre-1.8 Ga sources. The older crustal component is most similar to the isotopically enriched Mojave Province of eastern California and western Arizona, suggesting greater similarities between these provinces than previously recognized. Monazite and xenotime petrochronology indicate ca. 1.75–1.74, 1.72–1.69, 1.67, and 1.47–1.38 Ga tectono-metamorphic events. These data suggest that the Gunnison block accreted to other components of the Yavapai Province outboard of Laurentia at 1.75–1.74 Ga. The composite Yavapai Province was accreted to the margin of Laurentia during the 1.72–1.69 Ga Yavapai orogeny. Later overprinting is associated with the ∼1.68–1.60 Ga Mazatzal and ∼1.47–1.37 Ga Picuris orogenies. Identification of distinct crustal terranes within the Yavapai Province supports models involving multiple arcs and back-arcs that were progressively assembled prior to their accretion to Laurentia, perhaps akin to the present-day Banda Sea in Indonesia.
Accurate estimation and monitoring of wildlife population trends is foundational to evidence-based conservation. Here, we use hierarchical modelling to estimate population trends for six species of management interest (coyotes; red foxes, white-tailed deer, gray foxes; eastern wild turkey, and bobcats) while accounting for observation error from a long-term camera trap survey conducted across the State of New York. We were able to detect population level trends in occurrence and abundance and produce spatially explicit predictions for all six species using a combination of single-species occupancy models and Royle-Nichols models. Coyote (mean λ = 1.22, 95 % CI = 0.85–1.82) and red fox (mean λ = 1.17, 95 % CI = 0.95–1.46) populations were widely distributed with stable populations across the sampling period from 2014 to 2021. White-tailed deer populations were highly abundant and displayed an increasing population trend (mean λ = 1.85, 95 % CI = 1.54–2.10). Eastern wild turkey occupancy remained low across the state despite displaying a slight increase in occupancy over the sampling period (mean ψ = 0.16, 95 % CI = 0.07–0.25). Gray fox occupancy was also low (mean ψ = 0.22, 95 % CI = 0.12–0.29), consistent with growing concerns over the species across North America. Despite recent recoveries elsewhere, bobcat populations in New York State displayed very low occupancy (mean ψ = 0.07, 95 % CI = 0.02–0.12), highlighting the necessity of monitoring to inform conservation action. We provide empirically supported management implications for each species and demonstrate the efficacy of long-term camera trapping to provide robust evidence on population trends while accounting for imperfect detections, over scales meaningful to species management and conservation.