Conservation translocations are an important conservation tool commonly employed to augment declining or reestablish extirpated populations. One goal of augmentation is to increase genetic diversity and reduce the risk of inbreeding depression (i.e., genetic rescue). However, introducing individuals from significantly diverged populations risks disrupting coadapted traits and reducing local fitness (i.e., outbreeding depression). Genetic data are increasingly more accessible for wildlife species and can provide unique insight regarding the presence and retention of introduced genetic variation from augmentation as an indicator of effectiveness and adaptive similarity as an indicator of source and recipient population suitability. We used 2 genetic data sets to evaluate augmentation of isolated populations of greater sage-grouse (Centrocercus urophasianus) in the northwestern region of the species range (Washington, USA) and to retrospectively evaluate adaptive divergence among source and recipient populations. We developed 2 statistical models for microsatellite data to evaluate augmentation outcomes. We used one model to predict genetic diversity after augmentation and compared these predictions with observations of genetic change. We used the second model to quantify the amount of observed reproduction attributed to transplants (proof of population integration). We also characterized genome-wide adaptive divergence among source and recipient populations. Observed genetic diversity (HO = 0.65) was higher in the recipient population than predicted had no augmentation occurred (HO = 0.58) but less than what was predicted by our model (HO = 0.75). The amount of shared genetic variation between the 2 geographically isolated resident populations increased, which is evidence of periodic gene flow previously assumed to be rare. Among candidate adaptive genes associated with elevated fixation index (FST) (143 genes) or local environmental variables (97 and 157 genes for each genotype–environment association method, respectively), we found clusters of genes with related functions that may influence the ability of transplants to use local resources and navigate unfamiliar environments and their reproductive potential, all possible reasons for low genetic retention from augmentation.
Bathymetric and velocimetric data were collected by the U.S. Geological Survey, in cooperation with the Missouri Department of Transportation, near nine bridges at eight highway crossings of the Missouri River between Kansas City and St. Louis, Missouri, from May 19 to 26, 2021. A multibeam echosounder mapping system was used to obtain channel-bed elevations for river reaches about 1,640 to 1,840 feet (ft) longitudinally and generally extending laterally across the active channel from bank to bank during low to moderate flood-flow conditions. These surveys provided channel geometry and hydraulic conditions at the time of the surveys and provided characteristics of scour holes that may be useful in developing or verifying predictive guidelines or equations for computing potential scour depth. These data also may be useful to the Missouri Department of Transportation as a low to moderate flood-flow assessment of the bridges for stability and integrity issues with respect to bridge scour during floods.
Bathymetric data were collected around every in-channel pier. Scour holes were present at most piers for which bathymetry could be obtained, except those on banks or surrounded by riprap. Occasionally, scour holes were minor and difficult to discern from nearby dunes and ripples. All the bridge sites in this study were previously surveyed and documented in previous studies. Comparisons between bathymetric surfaces from the previous surveys and those of the current (2021) study do not indicate any consistent correlation between channel-bed elevations and streamflow conditions. The average difference between the bathymetric surfaces varied from 1.59 ft higher to 0.95 ft lower in 2021 than 2017, which corresponds to a gain of 100,200 cubic yards and a loss of 55,800 cubic yards, respectively. The average difference between the bathymetric surfaces varied from 2.74 ft higher to 3.05 ft lower in 2021 than 2013, which corresponds to a gain of 111,500 cubic yards and a loss of 169,200 cubic yards, respectively. The average difference between the bathymetric surfaces varied from 4.52 ft higher to 1.38 ft lower in 2021 than 2011, which corresponds to a gain of 221,100 cubic yards and a loss of 90,300 cubic yards, respectively. The most substantial overall net gain was 221,100 cubic yards between 2011 and 2021 at structures L0550 and A4497 at Jefferson City (site 20). The large net gain likely results from a combination of the mitigation of the scour holes near pier 4 of both bridges and the substantially lower flow in 2021 than in 2011. Alternatively, the most substantial overall net loss was 169,200 cubic yards between 2013 and 2021 at structure A6288 at Hermann (site 21), despite comparable streamflows.
Pier size, nose shape, and skew to approach flow had a substantial effect on the size of the scour hole observed at a given pier. Larger and deeper scour holes were present at piers with wide or blunt noses caused by exposed footings or caissons. When a pier was skewed to primary approach flow, the scour hole was generally deeper and larger than at a similar pier without skew; furthermore, the shape of the scour hole near skewed piers in this study generally was longer and deeper on the side with impinging flow. At structure A6288 at Hermann (site 21), the scour hole near pier 5 was difficult to discern from nearby dunes and ripples, whereas the upstream edge of the footing was visible at pier 4, which likely contributes to the larger scour hole near that pier; the top of the footing may blunt the horseshoe vortex at pier 5, but the exposed front of the footing may exacerbate the vortex at pier 4.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20245021","collaboration":"Prepared in cooperation with Missouri Department of Transportation","usgsCitation":"Huizinga, R.J., 2024, Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River between Kansas City and St. Louis, Missouri, May 19–26, 2021: U.S. Geological Survey Scientific Investigations Report 2024–5021, 101 p., https://doi.org/10.3133/sir20245021.","productDescription":"Report: xi, 101 p.; Data Release; Dataset","numberOfPages":"118","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-137677","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":492017,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116213.htm","linkFileType":{"id":5,"text":"html"}},{"id":427309,"rank":7,"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":427308,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ULGQ4W","text":"USGS data release","linkHelpText":"Bathymetry and velocity data from surveys at highway bridges crossing the Missouri River between Kansas City and St. Louis, Missouri, May 19–26, 2021 (ver. 2.0, August 2023)"},{"id":427306,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245021/full"},{"id":427302,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5021/coverthb.jpg"},{"id":427303,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5021/sir20245021.pdf","text":"Report","size":"34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024–5021"},{"id":427304,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5021/sir20245021.XML"},{"id":427305,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5021/images/"}],"country":"United States","state":"Missouri","otherGeospatial":"Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.99927657337038,\n 39.617338148546736\n ],\n [\n -94.99927657337038,\n 38.11188192313625\n ],\n [\n -89.92359297962084,\n 38.11188192313625\n ],\n [\n -89.92359297962084,\n 39.617338148546736\n ],\n [\n -94.99927657337038,\n 39.617338148546736\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Linear fuel breaks are being implemented to moderate fire behavior and improve wildfire containment in semiarid landscapes such as the sagebrush steppe of North America, where extensive losses in perennial vegetation and ecosystem functioning are resulting from invasion by exotic annual grasses (EAGs) that foster large and recurrent wildfires. However, fuel-break construction can also pose EAG invasion risks, which must be weighed against the intended fire-moderation benefits of the treatments. We investigated how shrub reductions (mowing, cutting), pre-emergent EAG-herbicides, and/or drill seedings of fire-resistant perennial bunchgrasses (PBGs) recently applied to create a large fuel-break system affected native and exotic plant abundances and their associated fuel loading and predicted fire behavior.
In heavily EAG-invaded areas, herbicides reduced EAG and total herbaceous cover without affecting PBGs for 2–3 years and reduced predicted fire behavior for 1 year (from the Fuel Characteristic Classification System). However, surviving post-herbicide EAG cover was still > 30%, which was sufficient fuel to exceed the conventional 1.2-m-flame length (FL) threshold for attempting wildfire suppression with hand tools. In less invaded shrubland, shrub reduction treatments largely reduced shrub cover and height by ~ half without increasing EAGs, but then redistributed the wood to ground level and increased total herbaceous cover. Herbicides and/or drill seeding after shrub reductions did not affect EAG cover, although drill seedings increased PBG cover and exotic forbs (e.g., Russian thistle). Fire behavior was predicted to be moderated in only one of the many yearly observations of the various shrub-reduction treatment combinations. Over all treatments and years, FLs were predicted to exceed 1.2 m in 13% of simulations under average (11 km h−1) or high (47 km h−1) wind speed conditions and exceed the 3.4-m threshold for uncontrollable fire in 11% of simulations under high-wind speeds only.
Predicted fire-moderation benefits over the first 4 years of fuel break implementation were modest and variable, but, generally, increases in EAGs and their associated fire risks were not observed. Nonetheless, ancillary evidence from shrublands would suggest that treatment-induced shifts from shrub to herbaceous fuel dominance are expected to improve conditions for active fire suppression in ways not readily represented in available fire models.
","language":"English","publisher":"Springer","doi":"10.1186/s42408-024-00266-y","usgsCitation":"Germino, M., Price, S.J., and Prichard, S.J., 2024, Vegetation, fuels, and fire-behavior responses to linear fuel-break treatments in and around burned sagebrush steppe: Are we breaking the grass-fire cycle?: Fire Ecology, v. 20, 34, 22 p., https://doi.org/10.1186/s42408-024-00266-y.","productDescription":"34, 22 p.","ipdsId":"IP-151706","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":439967,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s42408-024-00266-y","text":"Publisher Index Page"},{"id":427399,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Oregon","county":"Malheur County, Oweyhee County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.18415929326468,\n 43.38571891396131\n ],\n [\n -117.13095734549842,\n 42.9558610868508\n ],\n [\n -116.38745503351532,\n 42.9558610868508\n ],\n [\n -116.38187715866083,\n 43.33636726730849\n ],\n [\n -116.41762481804064,\n 43.619435037758784\n ],\n [\n -117.19933831765053,\n 43.65567830784602\n ],\n [\n -117.18415929326468,\n 43.38571891396131\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"20","noUsgsAuthors":false,"publicationDate":"2024-04-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Germino, Matthew J. 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":251901,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":898155,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Price, Samuel J. 0000-0003-4172-4139","orcid":"https://orcid.org/0000-0003-4172-4139","contributorId":297001,"corporation":false,"usgs":true,"family":"Price","given":"Samuel","email":"","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":898156,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prichard, Susan J","contributorId":305447,"corporation":false,"usgs":false,"family":"Prichard","given":"Susan","email":"","middleInitial":"J","affiliations":[],"preferred":false,"id":898157,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70252698,"text":"70252698 - 2024 - Comparing modern identification methods for wild bees: Metabarcoding and image-based morphological taxonomic assignment","interactions":[],"lastModifiedDate":"2024-04-03T12:19:45.209981","indexId":"70252698","displayToPublicDate":"2024-04-02T07:18:21","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Comparing modern identification methods for wild bees: Metabarcoding and image-based morphological taxonomic assignment","docAbstract":"With the decline of bee populations worldwide, studies determining current wild bee distributions and diversity are increasingly important. Wild bee identification is often completed by experienced taxonomists or by genetic analysis. The current study was designed to compare two methods of identification including: (1) morphological identification by experienced taxonomists using images of field-collected wild bees and (2) genetic analysis of composite bee legs (multiple taxa) using metabarcoding. Bees were collected from conservation grasslands in eastern Iowa in summer 2019 and identified to the lowest taxonomic unit using both methods. Sanger sequencing of individual wild bee legs was used as a positive control for metabarcoding. Morphological identification of bees using images resulted in 36 unique taxa among 22 genera, and >80% of Bombus specimens were identified to species. Metabarcoding was limited to genus-level assignments among 18 genera but resolved some morphologically similar genera. Metabarcoding did not consistently detect all genera in the composite samples, including kleptoparasitic bees. Sanger sequencing showed similar presence or absence detection results as metabarcoding but provided species-level identifications for cryptic species (i.e., Lasioglossum). Genus-specific detections were more frequent with morphological identification than metabarcoding, but certain genera such as Ceratina and Halictus were identified equally well with metabarcoding and morphology. Genera with proportionately less tissue in a composite sample were less likely to be detected using metabarcoding. Image-based methods were limited by image quality and visible morphological features, while genetic methods were limited by databases, primers, and amplification at target loci. This study shows how an image-based identification method compares with genetic techniques, and how in combination, the methods provide valuable genus- and species-level information for wild bees while preserving tissue for other analyses. These methods could be improved and transferred to a field setting to advance our understanding of wild bee distributions and to expedite conservation research.
The release of over 4500 Gt (gigatonnes) of carbon at the Paleocene–Eocene boundary provides the closest geological analog to modern anthropogenic CO2 emissions. The cause(s) of and responses to the resulting Paleocene–Eocene Thermal Maximum (PETM) and attendant carbon isotopic excursion (CIE) remain enigmatic and intriguing despite over 30 years of intense study. CIE records from the deep sea are generally thin due to its short duration and slow sedimentation rates, and they are truncated due to corrosive bottom waters dissolving carbonate sediments. In contrast, PETM coastal plain sections along the US mid-Atlantic margin are thick, generally having an expanded record of the CIE. Drilling here presents an opportunity to study the PETM onset to a level of detail that could transform our understanding of this important event. Previous drilling in this region provided important insights, but existing cores are either depleted or contain stratigraphic gaps. New core material is needed for well-resolved marine climate records. To plan new drilling, members of the international scientific community attended a multi-staged, hybrid scientific drilling workshop in 2022 designed to maximize not only scientifically and demographically diverse participation but also to protect participants' health and safety during the global pandemic and to reduce our carbon footprint. The resulting plan identified 10 sites for drill holes that would penetrate the Cretaceous–Paleogene (K–Pg) boundary, targeting the pre-onset excursion (POE), the CIE onset, the rapidly deposited Marlboro Clay that records a very thick CIE body, and other Eocene hyperthermals. The workshop participants developed several primary scientific objectives related to investigating the nature and the cause(s) of the CIE onset as well as the biotic effects of the PETM on the paleoshelf. Additional objectives focus on the evidence for widespread wildfires and changes in the hydrological cycle, shelf morphology, and sea level during the PETM as well as the desire to study both underlying K–Pg sediments and overlying post-Eocene records of extreme hyperthermal climate events. All objectives address our overarching research question: what was the Earth system response to a rapid carbon cycle perturbation?
Globally, coastal communities experience flood hazards that are projected to worsen from climate change and sea level rise. The 100-year floodplain or record flood are commonly used to identify risk areas for planning purposes. Remote communities often lack measured flood elevations and require innovative approaches to estimate flood elevations. This study employs observation-based methods to estimate the record flood elevation in Alaska communities and compares results to elevation models, infrastructure locations, and sea level rise projections. In 46 analyzed communities, 22% of structures are located within the record floodplain. With sea level rise projections, this estimate increases to 30–37% of structures by 2100 if structures remain in the same location. Flood exposure is highest in western Alaska. Sea level rise projections suggest northern Alaska will see similar flood exposure levels by 2100 as currently experienced in western Alaska. This evaluation of record flood height, category, and history can be incorporated into hazard planning documents, providing more context for coastal flood exposure than previously existed for Alaska. This basic flood exposure method is transferable to other areas with similar mapping challenges. Identifying current and projected hazardous zones is essential to avoid unintentional development in floodplains and improve long-term safety.
Maintaining the integrity and health of aquatic ecosystems is critical to sustaining the many valued services that they provide society. Unfortunately, achieving this goal has proven challenging in most of the world's large ecosystems owing to rampant environmental change caused by human-driven stress, including accelerating climate change, pollution of waterways, habitat modification and destruction, and the continued spread of non-native species (He and Silliman, 2019; Jenny et al., 2020; Smith et al., 2015; Steffen et al., 2007). These stressors, which can also include purposeful management actions (e.g. nutrient and fisheries management), are presenting a grave challenge globally to efforts aimed at securing a sustainable future for nature, society, and the economy.
","language":"English","publisher":"Scholarly Publishing Collective","doi":"10.14321/aehm.027.02.108","usgsCitation":"Ludsin, S., Carlson, A.K., Duncan, A., Febria, C., Hartig, J., Kellogg, W., Minns, C., Munawar, M., Nolan, S., Van der Knaap, M., Verhamme, E., and Williams, K., 2024, The Ecosystem Approach in the 21st century: Guiding science and management – A synthesis: Aquatic Ecosystem Health & Management, v. 27, no. 2, p. 108-116, https://doi.org/10.14321/aehm.027.02.108.","productDescription":"9 p.","startPage":"108","endPage":"116","ipdsId":"IP-163794","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":500797,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12927115/","text":"External Repository"},{"id":480834,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-04-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Ludsin, S.A.","contributorId":349662,"corporation":false,"usgs":false,"family":"Ludsin","given":"S.A.","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":924550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlson, Andrew Kenneth 0000-0002-6681-0853","orcid":"https://orcid.org/0000-0002-6681-0853","contributorId":340581,"corporation":false,"usgs":true,"family":"Carlson","given":"Andrew","email":"","middleInitial":"Kenneth","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":924551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duncan, A.T.","contributorId":349726,"corporation":false,"usgs":false,"family":"Duncan","given":"A.T.","affiliations":[],"preferred":false,"id":924667,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Febria, C.M.","contributorId":349665,"corporation":false,"usgs":false,"family":"Febria","given":"C.M.","affiliations":[{"id":83499,"text":"Traditional Territories of the Three Fires Confederacy of First Nations – Ojibway, Odawa and Potawatomi","active":true,"usgs":false}],"preferred":false,"id":924552,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hartig, J.H.","contributorId":349666,"corporation":false,"usgs":false,"family":"Hartig","given":"J.H.","affiliations":[{"id":48871,"text":"University of Windsor","active":true,"usgs":false}],"preferred":false,"id":924553,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kellogg, W.A.","contributorId":349667,"corporation":false,"usgs":false,"family":"Kellogg","given":"W.A.","affiliations":[{"id":18143,"text":"Cleveland State University","active":true,"usgs":false}],"preferred":false,"id":924554,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Minns, C.K.","contributorId":349668,"corporation":false,"usgs":false,"family":"Minns","given":"C.K.","affiliations":[{"id":7044,"text":"University of Toronto","active":true,"usgs":false}],"preferred":false,"id":924555,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Munawar, M.","contributorId":349669,"corporation":false,"usgs":false,"family":"Munawar","given":"M.","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":924556,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Nolan, S.","contributorId":349670,"corporation":false,"usgs":false,"family":"Nolan","given":"S.","affiliations":[{"id":48871,"text":"University of Windsor","active":true,"usgs":false}],"preferred":false,"id":924557,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Van der Knaap, M.","contributorId":349671,"corporation":false,"usgs":false,"family":"Van der Knaap","given":"M.","affiliations":[{"id":83502,"text":"University of Liège","active":true,"usgs":false}],"preferred":false,"id":924558,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Verhamme, E.M.","contributorId":349672,"corporation":false,"usgs":false,"family":"Verhamme","given":"E.M.","affiliations":[{"id":83503,"text":"LimnoTech, Inc.","active":true,"usgs":false}],"preferred":false,"id":924559,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Williams, K.C.","contributorId":349673,"corporation":false,"usgs":false,"family":"Williams","given":"K.C.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":924560,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70255026,"text":"70255026 - 2024 - Estimating migration timing and abundance in partial migratory systems by integrating continuous antenna detections with physical captures","interactions":[],"lastModifiedDate":"2024-07-15T15:13:06.675879","indexId":"70255026","displayToPublicDate":"2024-04-01T08:31:53","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Estimating migration timing and abundance in partial migratory systems by integrating continuous antenna detections with physical captures","docAbstract":"This paper describes development of a nitrate decision support tool for groundwater wells (GW-NDST) that combines nitrate leaching and groundwater lag-times to compute well concentrations. The GW-NDST uses output from support models that simulate leached nitrate, groundwater age distributions, and nitrate reduction rates. The support models are linked through convolution to simulate nitrate transport to wells. Spatially distributed parameters were adjusted through calibration to 34,255 nitrate sample targets. Prediction uncertainty is illustrated via Monte Carlo realizations informed during calibration. Over 78% of target concentrations were within the simulated range of results from 450 realizations. An example forecasting scenario illustrates that a range of feasible outcomes exist and should be considered when interpreting forecasts for decision making. Uncertainty in forecasting is unavoidable; the intent of characterizing uncertainty in the GW-NDST is to facilitate decision making by increasing insight into the response of nitrate contamination to physical and chemical processes.
Predicting the potential distribution of a non-native species can assist management efforts to mitigate impacts on recipient ecosystems. However, such predictions are lacking for marine species, such as the non-native regal demoiselle, Neopomacentrus cyanomos, that is currently expanding its distribution in the western Atlantic. We used correlative species distribution models with three common algorithms to predict suitable habitat for N. cyanomos in the region. We compared models developed using native, non-native, and global occurrences to differentiate drivers across separate ranges using a suite of 12 environmental characteristics. While final models included an ensemble of variables, the majority ranked the combined effect of temperature variables as a key predictor correlated with the distribution of N. cyanomos. Habitat suitability increased as water temperatures increased beyond 16 °C and where annual thermal ranges were greater than 10 °C at the shallowest depth with substrate within a study cell (~ 9.2 km2 resolution). Habitat suitability also increased where maximum surface temperatures were greater than 27 °C. In the non-native range, the proportion of reef available in each cell was another important variable increasing the suitable habitat for N. cyanomos. Our models predicted high habitat suitability for N. cyanomos throughout the Greater Caribbean, in higher latitudes along North and South American Atlantic coasts, in the eastern Pacific Ocean, and highlights key areas where managers can monitor and target potential removal efforts. The distribution of this non-native species is likely to continue expanding throughout the region with little known about potential implications on native communities.
Clumped isotope paleothermometry using pedogenic carbonates is a powerful tool for investigating past climate changes. However, location-specific seasonal patterns of precipitation and soil moisture cause systematic biases in the temperatures they record, hampering comparison of data across large areas or differing climate states. To account for biases, more systematic studies of carbonate forming processes are needed. We measured modern soil temperatures within the San Luis Valley of the Rocky Mountains and compared them to paleotemperatures determined using clumped isotopes. For Holocene-age samples, clumped isotope results indicate carbonate accumulated at a range of temperatures with site averages similar to the annual mean. Paleotemperatures for late Pleistocene-age samples (ranging 19–72 ka in age) yielded site averages only 2°C lower, despite evidence that annual temperatures during glacial periods were 5–9°C colder than modern. We use a 1D numerical model of soil physics to support the idea that differences in hydrologic conditions in interglacial versus glacial periods promote differences in the seasonal distribution of soil carbonate accumulation. Model simulations of modern (Holocene) conditions suggest that soil drying under low soil pCO2 favors year-round carbonate accumulation in this region but peaking during post-monsoon soil drying. During a “glacial” simulation with lowered temperatures and added snowpack, more carbonate accumulation shifted to the summer season. These experiments show that changing hydrologic regimes could change the seasonality of carbonate accumulation, which in this study blunts the use of clumped isotopes to quantify glacial-interglacial temperature changes. This highlights the importance of understanding seasonal biases of climate proxies for accurate paleoenvironmental reconstruction.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023GC011221","usgsCitation":"Hudson, A.M., Kelson, J.R., Paces, J., Ruleman, C.A., Huntington, K.W., and Schauer, A.J., 2024, Clumped isotopes record a glacial-interglacial shift in seasonality of soil carbonate accumulation in the San Luis Valley, southern Rocky Mountains, USA: Geochemistry, Geophysics, Geosystems, v. 25, no. 4, e2023GC011221, 23 p., https://doi.org/10.1029/2023GC011221.","productDescription":"e2023GC011221, 23 p.","ipdsId":"IP-114357","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":440002,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023gc011221","text":"Publisher Index Page"},{"id":435011,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TJF3PZ","text":"USGS data release","linkHelpText":"Isotopic, geochronologic and soil temperature data for Holocene and late Pleistocene soil carbonates of the San Luis Valley, Colorado and New Mexico, USA"},{"id":427311,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, new Mexico","otherGeospatial":"San Luis Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107,\n 38.5\n ],\n [\n -107,\n 35.5\n ],\n [\n -105,\n 35.5\n ],\n [\n -105,\n 38.5\n ],\n [\n -107,\n 38.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"25","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-03-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Hudson, Adam M. 0000-0002-3387-9838 ahudson@usgs.gov","orcid":"https://orcid.org/0000-0002-3387-9838","contributorId":195419,"corporation":false,"usgs":true,"family":"Hudson","given":"Adam","email":"ahudson@usgs.gov","middleInitial":"M.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":897780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelson, Julia R.","contributorId":335224,"corporation":false,"usgs":false,"family":"Kelson","given":"Julia","email":"","middleInitial":"R.","affiliations":[{"id":80344,"text":"Department of Geosciences, University of Michigan, Ann Arbor, MI, USA, Department of Earth and Atmospheric Sciences, Indiana University, Indianapolis, Indiana, USA","active":true,"usgs":false}],"preferred":false,"id":897781,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paces, James B. 0000-0002-9809-8493","orcid":"https://orcid.org/0000-0002-9809-8493","contributorId":118216,"corporation":false,"usgs":true,"family":"Paces","given":"James B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":897782,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruleman, Chester A. 0000-0002-1503-4591 cruleman@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-4591","contributorId":1264,"corporation":false,"usgs":true,"family":"Ruleman","given":"Chester","email":"cruleman@usgs.gov","middleInitial":"A.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":897783,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huntington, Katharine W.","contributorId":195423,"corporation":false,"usgs":false,"family":"Huntington","given":"Katharine","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":897784,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schauer, Andrew J.","contributorId":140713,"corporation":false,"usgs":false,"family":"Schauer","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":897785,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70252668,"text":"70252668 - 2024 - Timing and source of recharge to the Columbia River Basalt groundwater system in northeastern Oregon","interactions":[],"lastModifiedDate":"2024-09-11T16:11:18.161455","indexId":"70252668","displayToPublicDate":"2024-03-30T06:44:42","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Timing and source of recharge to the Columbia River Basalt groundwater system in northeastern Oregon","docAbstract":"Recharge to and flow within the Columbia River Basalt Group (CRBG) groundwater flow system of northeastern Oregon were characterized using isotopic, gas, and age-tracer samples from wells completed in basalt, springs, and stream base flow. Most groundwater samples were late-Pleistocene to early-Holocene; median age of well samples was 11,100 years. The relation between mean groundwater age and completed well depth across the eastern portion of the study area was similar despite differences in precipitation, topographic position, incision, thickness of the sedimentary overburden, and CRBG geologic unit. However, the lateral continuity in groundwater age was disrupted across large regional fault zones indicating these structures are substantial impediments to groundwater flow from the high-precipitation uplands to adjacent lower-precipitation and lower-elevation portions of the study area. Recharge rates calculated from the age-depth relations were <3 mm/yr and independent of the modern precipitation gradient across the study area. The age-constrained recharge rates to the CRBG groundwater system are considerably smaller than previously published estimates and highlight the uncertainty of prevailing models used to estimate recharge to the CRBG groundwater system across the Columbia Plateau in Oregon and Washington. Age tracer and isotopic evidence indicate recharge to the CRBG groundwater system is an exceedingly slow and localized process.
Eight springs and seeps at Fort Irwin National Training Center were described and categorized by their general characteristics, discharge, geophysical properties, and water quality between 2015 and 2017. The data collected establish a modern (2017) baseline of hydrologic conditions at the springs. Two types of springs were identified: (1) precipitation-fed upland springs (Cave, Desert King, Devouge, No Name, and Panther Springs) and (2) groundwater discharge-fed basin springs (Garlic, Bitter, and Jack Springs). Comparison of electrical resistivity tomography data collected at groundwater basin springs from 2015 to 2017 indicated that spring discharge and connection to the underlying groundwater system is highly focused, although the springs themselves appear diffuse and are spread out over a large area.
Spring discharge was consistently less than reported by Thompson (1929), except at Garlic Spring where discharges and vegetation have increased in recent years. Multiple discrete flume and seepage meter measurements taken between October 2015 and April 2016 indicated that discharge changed predictably on diurnal and seasonal timescales in response to evapotranspiration. These preliminary results and the lush vegetation noted at some of the springs, particularly at Bitter, Garlic, and Jack Springs, indicated plant evapotranspiration accounts for a substantial part of the discharge from these springs.
The quality of water ranges from fresh in precipitation-fed upland springs (Cave, Desert King, Devouge, and Panther Springs) to slightly saline (Garlic and Jack Springs) and moderately saline (Bitter Spring) in groundwater-fed discharge springs. Nitrate concentrations from water at most of the springs were less than 3 milligrams per liter, except for samples from Devouge and Desert King Springs and one sample from Jack Spring. An analysis of delta nitrogen-15 in nitrate (δ15N-NO3) and delta oxygen-18 in nitrate (δ18O-NO3) indicates high nitrate concentrations in excess of the U.S. Environmental Protection Agency maximum contaminant level at Jack Spring and Desert King Spring resulting from the dissolution of nitrate-bearing caliche deposits; nitrate concentrations at Devouge Spring are a result of algal growth within the spring, and the source of nitrate concentrations in Garlic Spring are consistent with a treated wastewater origin from Langford Valley-Irwin subbasin upgradient. The source of water in upland springs, indicated by values of delta oxygen-18 (δ18O) and delta deuterium (δD) are consistent with recharge from winter precipitation. In groundwater basin springs, values of δ18O and δD are consistent with groundwater sampled from nearby wells. Summer monsoonal precipitation appears to contribute little water to spring flow. Most springs contain low levels of tritium and appear to be primarily older (pre-1950s) groundwater. Groundwater basin springs with detectable tritium may result from occasional streamflow in nearby washes. These springs could be susceptible to decreases in flow during extended dry periods when the localized recharge may be reduced due to the loss of focused recharge through nearby washes.
Groundwater samples from Garlic and Bitter Springs contained arsenic concentrations above the U.S. Environmental Protection Agency maximum contaminant level. Groundwater samples from all springs, except Cave, Desert King, and Devouge Springs, exceeded the State of California maximum contaminant level for fluoride. Garlic Spring was the only sampled spring that contained vanadium concentrations that exceeded the State of California notification level. Only a single water sample from Jack Spring contained uranium at a concentration that exceeded the U.S. Environmental Protection Agency maximum contaminant level.
Many other constituents of concern were analyzed, including those from anthropogenic sources that may be a result of military activities. Most of these constituents were not detected above their respective reporting levels in spring water; only 15 were detected in spring waters. Diesel and gasoline degradants, many of which also occur naturally, were the most commonly detected compounds. Several other organic compounds, primarily solvents or their degradants, were detected in groundwater basin springs. These constituents, in order of decreasing detection frequency, were carbon disulfide; perchlorate; mercury; acetone; methylnaphthalene; toluene; methyl ethyl ketone; cyanide; and styrene; 4-iso-propyl-toluene; isopropylbenzene; methyl salicylate; and phenol. Except for Garlic Spring, which is affected by discharges of treated wastewater, the quality of water from most springs appears to be relatively unaffected by activities at the Fort Irwin National Training Center.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235142","collaboration":"Prepared in cooperation with the U.S. Army Fort Irwin National Training Center","programNote":"Water Availability and Use Science Program","usgsCitation":"Densmore, J.N., Thayer, D.C., Dick, M.C., Swarzenski, P.W., Ball, L.B., Rosecrans, C.Z., and Johnson, C., 2024, Evaluation of the characteristics, discharge, and water quality of selected springs at Fort Irwin National Training Center, San Bernardino County, California: U.S. Geological Survey Scientific Investigations Report 2023–5142, 87 p., https://doi.org/10.3133/sir20235142.","productDescription":"Report: xii, 87 p.; 2 Data Releases","numberOfPages":"87","onlineOnly":"Y","ipdsId":"IP-098665","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":426854,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P901E9C2","text":"USGS Data Release","description":"Mesmer, R.D., Dick, M.C., and Densmore, J.N., 2024, Temperature and discharge data of selected springs at Fort Irwin National Training Center, San Bernardino County, California: U.S. Geological Survey data release, available at https://doi.org/10.5066/P901E9C2.","linkHelpText":"Temperature and discharge data of selected springs at Fort Irwin National Training Center, San Bernardino County, California"},{"id":499404,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116216.htm","linkFileType":{"id":5,"text":"html"}},{"id":426868,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5142/images"},{"id":426867,"rank":6,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5142/covrthb.jpg"},{"id":426866,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235142/full"},{"id":426865,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5142/sir20235142.xml"},{"id":426864,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5142/sir20235142.pdf","text":"Report","size":"25.9 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":426853,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77W6BF0","text":"USGS Data Release","description":"Thayer, D.C., Ball, L.B., Densmore, J.N., Swarzenski, P.W., and Johnson, C., 2018, Electrical resistivity tomography data at Fort Irwin National Training Center, San Bernardino County, California, 2015 and 2017: U.S. Geological Survey data release, available at https://doi.org/10.5066/F77W6BF0.","linkHelpText":"Electrical resistivity tomography data at Fort Irwin National Training Center, San Bernardino County, California, 2015 and 2017"}],"country":"United States","state":"California","otherGeospatial":"Fort Irwin National Training Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.65077467771744,\n 36.01045506303355\n ],\n [\n -117.65077467771744,\n 34.68622540325404\n ],\n [\n -115.49481045780325,\n 34.68622540325404\n ],\n [\n -115.49481045780325,\n 36.01045506303355\n ],\n [\n -117.65077467771744,\n 36.01045506303355\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
The Arizona Toad (Anaxyrus microscaphus) is restricted to riverine corridors and adjacent uplands in the arid southwestern United States. As with numerous amphibians worldwide, populations are declining and face various known or suspected threats, from disease to habitat modification resulting from climate change. The Arizona Toad has been petitioned to be listed under the U.S. Endangered Species Act and was considered “warranted but precluded” citing the need for additional information – particularly regarding natural history (e.g., connectivity and dispersal ability). The objectives of this study were to characterize population structure and genetic diversity across the species’ range. We used reduced-representation genomic sequencing to genotype 3,601 single nucleotide polymorphisms in 99 Arizona Toads from ten drainages across its range. Multiple analytical methods revealed two distinct genetic groups bisected by the Colorado River; one in the northwestern portion of the range in southwestern Utah and eastern Nevada and the other in the southeastern portion of the range in central and eastern Arizona and New Mexico. We also found subtle substructure within both groups, particularly in central Arizona where toads at lower elevations were less connected than those at higher elevations. The northern and southern parts of the Arizona Toad range are not well connected genetically and could be managed as separate units. Further, these data could be used to identify source populations for assisted migration or translocations to support small or potentially declining populations.
","language":"English","publisher":"Springer","doi":"10.1007/s10592-024-01606-w","usgsCitation":"Oyler-McCance, S.J., Ryan, M.J., Sullivan, B.K., Fike, J., Cornman, R.S., Giermakowski, J.T., Zimmerman, S.J., Harrow, R.L., Hedwell, S., Hossack, B., Latella, I., Lovish, R.E., Siefken, S., Sigafus, B., and Muths, E., 2024, Genetic Connectivity in the Arizona toad (Anaxyrus microscaphus): implications for conservation of a stream dwelling amphibian in the arid Southwestern U.S.: Conservation Genetics, v. 25, p. 835-848, https://doi.org/10.1007/s10592-024-01606-w.","productDescription":"14 p.","startPage":"835","endPage":"848","ipdsId":"IP-154561","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":440011,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10592-024-01606-w","text":"Publisher Index Page"},{"id":427560,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Nevada, New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.0000406770512,\n 38.468528390736736\n ],\n [\n -118.0000406770512,\n 30.615684527609147\n ],\n [\n -106.80078434694725,\n 30.615684527609147\n ],\n [\n -106.80078434694725,\n 38.468528390736736\n ],\n [\n -118.0000406770512,\n 38.468528390736736\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"25","noUsgsAuthors":false,"publicationDate":"2024-03-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":898325,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ryan, Mason J.","contributorId":266045,"corporation":false,"usgs":false,"family":"Ryan","given":"Mason","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":898326,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sullivan, Brian K.","contributorId":177225,"corporation":false,"usgs":false,"family":"Sullivan","given":"Brian","email":"","middleInitial":"K.","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":898327,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fike, Jennifer A. 0000-0001-8797-7823","orcid":"https://orcid.org/0000-0001-8797-7823","contributorId":207268,"corporation":false,"usgs":true,"family":"Fike","given":"Jennifer A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":898328,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cornman, Robert S. 0000-0001-9511-2192 rcornman@usgs.gov","orcid":"https://orcid.org/0000-0001-9511-2192","contributorId":5356,"corporation":false,"usgs":true,"family":"Cornman","given":"Robert","email":"rcornman@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":898329,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Giermakowski, J. T.","contributorId":335421,"corporation":false,"usgs":false,"family":"Giermakowski","given":"J.","email":"","middleInitial":"T.","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":898330,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zimmerman, Shawna J 0000-0003-3394-6102 szimmerman@usgs.gov","orcid":"https://orcid.org/0000-0003-3394-6102","contributorId":238076,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Shawna","email":"szimmerman@usgs.gov","middleInitial":"J","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":898331,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Harrow, R. L.","contributorId":335422,"corporation":false,"usgs":false,"family":"Harrow","given":"R.","email":"","middleInitial":"L.","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":898332,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hedwell, S.J.","contributorId":335423,"corporation":false,"usgs":false,"family":"Hedwell","given":"S.J.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":898333,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hossack, Blake R. 0000-0001-7456-9564","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":229347,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":898334,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Latella, I. M.","contributorId":335424,"corporation":false,"usgs":false,"family":"Latella","given":"I. M.","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":898335,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lovish, R. E.","contributorId":335425,"corporation":false,"usgs":false,"family":"Lovish","given":"R.","email":"","middleInitial":"E.","affiliations":[{"id":80401,"text":"Naval Facilities Engineering Systems Command Southwest","active":true,"usgs":false}],"preferred":false,"id":898336,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Siefken, S.","contributorId":335427,"corporation":false,"usgs":false,"family":"Siefken","given":"S.","affiliations":[{"id":65571,"text":"Utah Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":898337,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Sigafus, Brent H. 0000-0002-7422-8927","orcid":"https://orcid.org/0000-0002-7422-8927","contributorId":264740,"corporation":false,"usgs":true,"family":"Sigafus","given":"Brent H.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":898338,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Muths, Erin L. 0000-0002-5498-3132","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":245922,"corporation":false,"usgs":true,"family":"Muths","given":"Erin L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":898339,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70251912,"text":"70251912 - 2024 - Summary of the discussions during 2023 SSA topical meeting on “Future Directions for Physics-Based Ground Motion Modeling”","interactions":[],"lastModifiedDate":"2026-03-25T16:02:49.42664","indexId":"70251912","displayToPublicDate":"2024-03-29T11:01:26","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Summary of the discussions during 2023 SSA topical meeting on “Future Directions for Physics-Based Ground Motion Modeling”","docAbstract":"The Seismological Society of America (SSA) topical conference, Future Directions for Physics‐Based Ground Motion Modeling, was held in Vancouver, Canada, on 10–13 October 2023, co‐sponsored by the Seismological Society of Japan and co‐chaired by Annemarie Baltay of the U.S. Geological Survey and Hiroshi Kawase of Kyoto University. This meeting brought together many researchers and practitioners interested in modeling, observing, and utilizing ground‐motion models (GMMs). Scientists gathered to discuss complex kinematic and dynamic rupture simulation approaches, empirical representations of the earthquake source, site and path effects, physical modeling of the recording site, challenges for model extrapolation, and overall prediction accuracy and simulation validation. The four‐day meeting included many posters as well as oral presentations, with each session followed by lively discussion sections, upon which we report here.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220240084","usgsCitation":"Kawase, H., and Baltay Sundstrom, A.S., 2024, Summary of the discussions during 2023 SSA topical meeting on “Future Directions for Physics-Based Ground Motion Modeling”: Seismological Research Letters, v. 95, no. 3, p. 2026-2030, https://doi.org/10.1785/0220240084.","productDescription":"5 p.","startPage":"2026","endPage":"2030","ipdsId":"IP-163467","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":501503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"95","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-03-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Kawase, Hiroshi","contributorId":267868,"corporation":false,"usgs":false,"family":"Kawase","given":"Hiroshi","email":"","affiliations":[{"id":36662,"text":"Kyoto University","active":true,"usgs":false}],"preferred":false,"id":896049,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baltay, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":896050,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70252670,"text":"70252670 - 2024 - Post-wildfire debris flows","interactions":[],"lastModifiedDate":"2024-04-02T15:03:04.719071","indexId":"70252670","displayToPublicDate":"2024-03-29T10:00:07","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Post-wildfire debris flows","docAbstract":"Post-wildfire debris flows pose severe hazards to communities and infrastructure near and within recently burned mountainous terrain. Intense heat of wildfires changes the runoff characteristics of a watershed by combusting the vegetative canopy, litter, and duff, introducing ash into the soil and creating water repellant soils. Following wildfire, rainfall on bare ground is less able to infiltrate into the fire-altered soils and overland flow is less impeded by vegetation. Rainfall runoff in recently burned areas can erode hillslopes owing to the removal of soil binding organic matter near the soil surface by fire. In channels, loose, dry-ravel deposits composed of sand and gravel are readily entrained by concentrated runoff in channels. Entrainment of soil on hillslopes and in channels bulks up the sediment concentration of the rainfall runoff to generate debris flows capable of transporting boulders and large woody debris. Post-wildfire debris flows can be triggered by rainfall conditions that would typically produce little runoff during unburned conditions. The primary rainfall trigger for post-wildfire debris flows is high intensity rainfall during short duration convective rainstorms or periods of high rainfall intensity embedded within a long-duration frontal storm. Numerous observations of debris flows triggered by storms lasting less than an hour following periods of little to no rainfall indicate that antecedent rainfall is not a requirement for initiation of post-wildfire debris flows. Post-wildfire debris-flow hazard assessment entails estimating probability and magnitude of debris flows in the burned area, estimating debris-flow runout and intensity, and defining rainfall intensity-duration thresholds for debris-flow initiation. In the United States, probability and magnitude is estimated using empirically derived models largely based on data collected in southern California. The models provide maps to identify watersheds and drainage paths where post-wildfire hazards are most pronounced. Rainfall intensity-duration thresholds can be incorporated into flood hazard forecasting tools. Currently, work is underway to identify how to best implement debris-flow runout models in burned areas with efficiency and accuracy. Post-wildfire debris flows have been a long-recognized process in the Transverse Ranges of southern California; however, climate change is driving more frequent wildfires to burn more mountainous terrain throughout the western United States and worldwide. As a result, post-wildfire debris flows are becoming a more common threat in areas where they were once infrequent. As the threat of post-wildfire debris flow expands into new areas, evaluating the hazard becomes challenging because the degree to which wildfire increases debris-flow susceptibility varies from region to region. This chapter summarizes the knowledge to date for evaluating post-wildfire debris-flow susceptibility and hazard assessment. We summarize the characteristics of wildfire burn severity, topography, underlying soil and geology, and rainfall conditions that contribute to making a watershed most likely to produce post-wildfire debris flows. Methods for hazard assessment in the United States and other countries are summarized. We highlight knowledge gaps for how post-wildfire debris-flow susceptibility varies throughout the western United States and worldwide and identify research needs to improve hazard assessment methods in different geographies.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Advances in Debris-flow Science and Practice","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-031-48691-3_11","usgsCitation":"Gartner, J., Kean, J.W., Rengers, F.K., McCoy, S., Oakley, N.S., and Sheridan, G.J., 2024, Post-wildfire debris flows, chap. of Advances in Debris-flow Science and Practice, p. 309-345, https://doi.org/10.1007/978-3-031-48691-3_11.","productDescription":"37 p.","startPage":"309","endPage":"345","ipdsId":"IP-144910","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":427315,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2024-03-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Gartner, Joseph","contributorId":335250,"corporation":false,"usgs":false,"family":"Gartner","given":"Joseph","affiliations":[{"id":78476,"text":"BGC Engineering","active":true,"usgs":false}],"preferred":false,"id":897864,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":897865,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":897866,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCoy, Scott W.","contributorId":267182,"corporation":false,"usgs":false,"family":"McCoy","given":"Scott W.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":897867,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oakley, Nina S.","contributorId":197885,"corporation":false,"usgs":false,"family":"Oakley","given":"Nina","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":897868,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sheridan, Gary J.","contributorId":210293,"corporation":false,"usgs":false,"family":"Sheridan","given":"Gary","email":"","middleInitial":"J.","affiliations":[{"id":13336,"text":"University of Melbourne","active":true,"usgs":false}],"preferred":false,"id":897869,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70261888,"text":"70261888 - 2024 - Lahars: Origins, behavior and hazards","interactions":[],"lastModifiedDate":"2024-12-31T16:01:22.063764","indexId":"70261888","displayToPublicDate":"2024-03-29T09:58:59","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Lahars: Origins, behavior and hazards","docAbstract":"Volcanic debris flows that originate at potentially active volcanoes are called lahars. Lahars are like debris flows in non-volcanic terrain but can most notably differ in origin and size. Primary lahars occur during eruptions and may have novel origins such as turbulent mixing of hot rock moving across ice- and snow-clad volcanoes and eruptions through crater lakes. Lahars range in volume to more than a cubic kilometer (109 m3), with the biggest ones caused by huge deep-seated flank collapses of water-saturated edifice rock. Because they can be so voluminous, can have high water contents, and commonly can be clay rich, these lahars can travel tens to even hundreds of kilometers. Long transport causes evolution of flow types from flood flow to hyperconcentrated flow to debris flow. Lahars capable of traveling far downstream are commonly sufficiently liquefied that they drape valley slopes and leave behind thin deposits as they pass downstream. Only in valley bottoms are lahars likely to emplace thick deposits, and even there the deposits are apt to be much thinner than peak flow depths. Flows with long transport change character with time and distance downstream. Deposits, especially those in valley bottoms, can accrete during intervals that represent a significant proportion of the time it takes the flow to pass (typically minutes). The combination of flows changing character and their progressive accretion imposes distinctive characteristics on their deposits such as normal and inverse grading. Historically, lahars have caused thousands of fatalities and destroyed entire towns. Perhaps the most disastrous known lahar occurred in 1985 at Nevado del Ruiz in Colombia and killed more than 23,000 people. Since that disaster, an increasing awareness of lahar hazards has led to efforts to mitigate them. In recent decades, improved land-use decisions, monitoring and communication have improved hazard responses and saved many lives. Lahar hazard maps and development of lahar inundation models have helped planners and people at risk to better understand the nature of the risk owing to lahars.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Advances in debris-flow science and practice","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-031-48691-3_12","usgsCitation":"Vallance, J.W., 2024, Lahars: Origins, behavior and hazards, chap. of Advances in debris-flow science and practice, p. 347-381, https://doi.org/10.1007/978-3-031-48691-3_12.","productDescription":"35 p.","startPage":"347","endPage":"381","ipdsId":"IP-149909","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":465567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2024-03-29","publicationStatus":"PW","contributors":{"editors":[{"text":"Jakob, Matthias","contributorId":82179,"corporation":false,"usgs":true,"family":"Jakob","given":"Matthias","email":"","affiliations":[],"preferred":false,"id":922171,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"McDougall, Scott","contributorId":194908,"corporation":false,"usgs":false,"family":"McDougall","given":"Scott","email":"","affiliations":[],"preferred":false,"id":922172,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Santi, Paul","contributorId":347682,"corporation":false,"usgs":false,"family":"Santi","given":"Paul","affiliations":[],"preferred":false,"id":922173,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Vallance, James W. 0000-0002-3083-5469 jvallance@usgs.gov","orcid":"https://orcid.org/0000-0002-3083-5469","contributorId":547,"corporation":false,"usgs":true,"family":"Vallance","given":"James","email":"jvallance@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":922161,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70254474,"text":"70254474 - 2024 - Numerical modeling of debris flows: A conceptual assessment","interactions":[],"lastModifiedDate":"2024-05-28T11:49:50.632421","indexId":"70254474","displayToPublicDate":"2024-03-29T06:48:23","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Numerical modeling of debris flows: A conceptual assessment","docAbstract":"Real-world hazard evaluation poses many challenges for the development and application of numerical models of debris flows. In this chapter we provide a conceptual overview of physically based, depth-averaged models designed to simulate debris-flow motion across three-dimensional terrain. When judiciously formulated and applied, these models can provide useful information about anticipated depths, speeds, and extents of debris-flow inundation as well as debris interactions with structures such as levees and dams. Depth-averaged debris-flow models can differ significantly from one another, however. Some of the greatest differences result from simulation of one-phase versus two-phase flow, use of parsimonious versus information-intensive initial and boundary conditions, use of tuning coefficients versus physically measureable parameters, application of dissimilar numerical solution techniques, and variations in computational speed and model accessibility. This overview first addresses these and related attributes of depth-averaged debris-flow models. It then describes model testing and application to hazard evaluation, with a focus on our own model, D-Claw. The overview concludes with a discussion of outstanding challenges for development of improved debris-flow models and suggestions for prospective model users.
The Arctic National Wildlife Refuge is a unique landscape in northern Alaska with limited water resources, substantial biodiversity of rare and threatened species, as well as oil and gas resources. The region has unique hydrology related to perennial springs, and the formation of large aufeis fields—sheets of ice that grow in the river channels where water reaches the surface in the winter and freezes. This work aims to update our understanding of water resources and water quality in the springs, streams, rivers, and lakes of this region, returning to sites sampled by the U.S. Geological Survey in the 1970s. We resampled eight streams, four springs, and six lakes for hydrological metrics, water quality, and macroinvertebrates, and recalculated flood-frequency metrics for rivers using updated data and modern techniques. Aufeis field melt rates were also assessed for the past several decades. Although the available data preclude trend determinations in most cases, our analysis and comparison to the historical sampling indicates an increase in dissolved ions for streams and springs, faster and earlier aufeis melt, and similar macroinvertebrate populations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245008","usgsCitation":"Koch, J.C., Best, H., Baughman, C., Couvillion, C., Carey, M.P., and Conaway, J., 2024, A comparison of contemporary and historical hydrology and water quality in the foothills and coastal plain of the Arctic National Wildlife Refuge, Arctic Slope, northern Alaska: U.S. Geological Survey Scientific Investigations Report 2024–5008, 24 p., https://doi.org/10.3133/sir20245008.","productDescription":"Report: viii, 24 p.; 2 Data Releases; Correction Note","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-151990","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":499422,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116206.htm","linkFileType":{"id":5,"text":"html"}},{"id":498378,"rank":8,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2024/5008/correctionNote.txt","text":"Correction note","size":"1 KB","linkFileType":{"id":2,"text":"txt"}},{"id":430506,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7KK98VP","text":"USGS data release","description":"USGS data release","linkHelpText":"Rasters of observed aufeis deposits within rivers of the 1002 Area based on historical Landsat imagery, 1985-2022"},{"id":430429,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7X34VHM","text":"USGS data release","description":"USGS data release","linkHelpText":"Macroinvertebrates from streams and springs in the 1002 region of the Arctic National Wildlife Refuge, Alaska, 2021"},{"id":427077,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5008/sir20245008.XML"},{"id":427076,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5008/images"},{"id":427075,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245008/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5008"},{"id":427074,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5008/sir20245008.pdf","text":"Report","size":"12.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5008"},{"id":427073,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5008/sir20245008.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -147.35991062435545,\n 70.47943246978403\n ],\n [\n -147.35991062435545,\n 68.94103321326239\n ],\n [\n -141.60307468685548,\n 68.94103321326239\n ],\n [\n -141.60307468685548,\n 70.47943246978403\n ],\n [\n -147.35991062435545,\n 70.47943246978403\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
There is a significant need to develop decision support tools capable of delivering accurate representations of environmental conditions, such as ground and surface water solute concentrations, in a timely and computationally efficient manner. Such tools can be leveraged to assess a large number of potential management strategies for mitigating non-point source pollutants. Here, we assess the effectiveness of the impulse-response emulation approach to approximate process-based groundwater model estimates of solute transport from MODFLOW and MT3D over a wide range of model inputs and parameters, with the goal of assessing where in parameter space the assumptions underlying this emulation approach are valid. The impulse-response emulator was developed using the sensitivity analysis utilities in the PEST++ software suite and is capable of approximating MODFLOW/MT3D estimates of solute transport over a large portion of the parameter space tested, except in cases where the Courant number is above 0.5. Across all runs tested, the highest percent errors were at the plume fronts. These results suggest that the impulse-response approach may be suitable for emulation of solute transport models for a wide range of cases, except when high-resolution outputs are needed, or when very low concentrations at plume edges are of particular interest.
","language":"English","publisher":"Wiley","doi":"10.1111/gwat.13405","usgsCitation":"Heerspink, B.P., Fienen, M., and Reeves, H.W., 2024, Evaluation of an impulse-response emulator for groundwater contaminant transport modeling: Groundwater, v. 62, no. 6, p. 945-956, https://doi.org/10.1111/gwat.13405.","productDescription":"12 p.","startPage":"945","endPage":"956","ipdsId":"IP-153543","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":498231,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.13405","text":"Publisher Index Page"},{"id":429517,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":435013,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13J3TCG","text":"USGS data release","linkHelpText":"Model Archive for an Impulse Response Emulator of Groundwater Contaminant Transport Models"}],"volume":"62","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Heerspink, Brent Porter 0000-0001-7591-5115","orcid":"https://orcid.org/0000-0001-7591-5115","contributorId":337146,"corporation":false,"usgs":true,"family":"Heerspink","given":"Brent","email":"","middleInitial":"Porter","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":902087,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":902088,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reeves, Howard W. 0000-0001-8057-2081 hwreeves@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-2081","contributorId":2307,"corporation":false,"usgs":true,"family":"Reeves","given":"Howard","email":"hwreeves@usgs.gov","middleInitial":"W.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":902089,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70252583,"text":"70252583 - 2024 - Performance-based earthquake early warning for tall buildings","interactions":[],"lastModifiedDate":"2024-05-07T14:38:41.09501","indexId":"70252583","displayToPublicDate":"2024-03-28T06:52:06","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":"Performance-based earthquake early warning for tall buildings","docAbstract":"Point counts (PCs) are widely used in biodiversity surveys but, despite numerous advantages, simple PCs suffer from several problems: detectability, and therefore abundance, is unknown; systematic spatiotemporal variation in detectability yields biased inferences, and unknown survey area prevents formal density estimation and scaling-up to the landscape level. We introduce integrated distance sampling (IDS) models that combine distance sampling (DS) with simple PC or detection/nondetection (DND) data to capitalize on the strengths and mitigate the weaknesses of each data type. Key to IDS models is the view of simple PC and DND data as aggregations of latent DS surveys that observe the same underlying density process. This enables the estimation of separate detection functions, along with distinct covariate effects, for all data types. Additional information from repeat or time-removal surveys, or variable survey duration, enables the separate estimation of the availability and perceptibility components of detectability with DS and PC data. IDS models reconcile spatial and temporal mismatches among data sets and solve the above-mentioned problems of simple PC and DND data. To fit IDS models, we provide JAGS code and the new “IDS()” function in the R package unmarked. Extant citizen-science data generally lack the information necessary to adjust for detection biases, but IDS models address this shortcoming, thus greatly extending the utility and reach of these data. In addition, they enable formal density estimation in hybrid designs, which efficiently combine DS with distance-free, point-based PC or DND surveys. We believe that IDS models have considerable scope in ecology, management, and monitoring.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.4292","usgsCitation":"Kery, M., Royle, A., Hallman, T., Robinson, D., Strebel, N., and Kellner, K.F., 2024, Integrated distance sampling models for simple point counts: Ecology, v. 105, no. 5, e4292, 14 p., https://doi.org/10.1002/ecy.4292.","productDescription":"e4292, 14 p.","ipdsId":"IP-147069","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":492866,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.4292","text":"Publisher Index Page"},{"id":492538,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"105","issue":"5","noUsgsAuthors":false,"publicationDate":"2024-03-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Kery, Marc","contributorId":168361,"corporation":false,"usgs":false,"family":"Kery","given":"Marc","affiliations":[{"id":12551,"text":"Swiss Ornithological Institute, Sempach, Switzerland","active":true,"usgs":false}],"preferred":false,"id":943421,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":943422,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hallman, Tyler","contributorId":358288,"corporation":false,"usgs":false,"family":"Hallman","given":"Tyler","affiliations":[{"id":85597,"text":"Swiss Ornithological Institute; University of Charlotte; Bangor University","active":true,"usgs":false}],"preferred":false,"id":943423,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robinson, Doug","contributorId":358289,"corporation":false,"usgs":false,"family":"Robinson","given":"Doug","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":943424,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Strebel, Nicolas","contributorId":358290,"corporation":false,"usgs":false,"family":"Strebel","given":"Nicolas","affiliations":[{"id":67146,"text":"Swiss Ornithological Institute","active":true,"usgs":false}],"preferred":false,"id":943425,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kellner, Kenneth F.","contributorId":310338,"corporation":false,"usgs":false,"family":"Kellner","given":"Kenneth","email":"","middleInitial":"F.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":943426,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}