Deep-water coral reefs are found worldwide and harbor biodiversity levels that are comparable to their shallow-water counterparts. However, the genetic diversity and population structure of deep-water species remain poorly explored, and historical taxonomical issues still need to be resolved. Here we used microsatellite markers as well as ultraconserved elements (UCE) and exons to shed light on the population structure, genetic diversity, and phylogenetic position of the genus Madrepora, which contains M. oculata, one of the most widespread scleractinian species. Population structure of 107 samples from three Southwestern Atlantic sedimentary basins revealed the occurrence of a cryptic species, herein named M. piresae sp. nov. (authored by Kitahara, Capel and Zilberberg), which can be found in sympatry with M. oculata. Phylogeny reconstructions based on 134 UCEs and exon regions corroborated the population genetic data, with the recovery of two well-supported groups, and reinforced the polyphyly of the family Oculinidae. In order to better accommodate the genus Madrepora, while reducing taxonomical confusion associated with the name Madreporidae, we propose the monogeneric family Bathyporidae fam. nov. (authored by Kitahara, Capel, Zilberberg and Cairns). Our findings advance the knowledge on the widespread deep-water genus Madrepora, resolve a long-standing question regarding the phylogenetic position of the genus, and highlight the need of a worldwide review of the genus.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ympev.2023.107994","usgsCitation":"Capel, K.C., Zilberberg, C., Carpes, R.M., Morrison, C., Vaga, C.F., Quattrini, A., Quek, R.Z., Huang, D., Cairns, S.D., and Kitahara, M.V., 2024, How long have we been mistaken? Multi-tools shedding light into the systematics of the widespread deep-water genus Madrepora Linnaeus, 1758 (Scleractinia): Molecular Phylogenetics and Evolution, v. 191, 107994, 10 p., https://doi.org/10.1016/j.ympev.2023.107994.","productDescription":"107994, 10 p.","ipdsId":"IP-154239","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":425471,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"191","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Capel, Katia C. C.","contributorId":333882,"corporation":false,"usgs":false,"family":"Capel","given":"Katia","email":"","middleInitial":"C. C.","affiliations":[{"id":79999,"text":"Center for Marine Biology, São Paulo University, São Sebastião, São Paulo, Brazil","active":true,"usgs":false}],"preferred":false,"id":894214,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zilberberg, Carla","contributorId":333883,"corporation":false,"usgs":false,"family":"Zilberberg","given":"Carla","email":"","affiliations":[{"id":80000,"text":"Department of Zoology, Institute of Biodiversity and Sustainability – Nupem, Federal University of Rio de Janeiro, Macaé, Rio de Janeiro, Brazil","active":true,"usgs":false}],"preferred":false,"id":894215,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carpes, Raphael M.","contributorId":333884,"corporation":false,"usgs":false,"family":"Carpes","given":"Raphael","email":"","middleInitial":"M.","affiliations":[{"id":80000,"text":"Department of Zoology, Institute of Biodiversity and Sustainability – Nupem, Federal University of Rio de Janeiro, Macaé, Rio de Janeiro, Brazil","active":true,"usgs":false}],"preferred":false,"id":894216,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morrison, Cheryl 0000-0001-9425-691X cmorrison@usgs.gov","orcid":"https://orcid.org/0000-0001-9425-691X","contributorId":202644,"corporation":false,"usgs":true,"family":"Morrison","given":"Cheryl","email":"cmorrison@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":894217,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vaga, Claudia F.","contributorId":333885,"corporation":false,"usgs":false,"family":"Vaga","given":"Claudia","email":"","middleInitial":"F.","affiliations":[{"id":80002,"text":"Center for Marine Biology, São Paulo University, São Sebastião, São Paulo, Brazil; Graduate Program in Zoology, Department of Zoology, Institute of Biosciences, University of São Paulo, São Paulo, Brazil","active":true,"usgs":false}],"preferred":false,"id":894218,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Quattrini, Andrea M.","contributorId":333886,"corporation":false,"usgs":false,"family":"Quattrini","given":"Andrea M.","affiliations":[{"id":80003,"text":"Department of Invertebrate Zoology, Smithsonian Institution, Washington DC, United States of America","active":true,"usgs":false}],"preferred":false,"id":894219,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Quek, Randolph Z. B.","contributorId":333887,"corporation":false,"usgs":false,"family":"Quek","given":"Randolph","email":"","middleInitial":"Z. B.","affiliations":[{"id":80004,"text":"Department of Biological Sciences, National University of Singapore, Singapore","active":true,"usgs":false}],"preferred":false,"id":894220,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Huang, Danwei","contributorId":333888,"corporation":false,"usgs":false,"family":"Huang","given":"Danwei","email":"","affiliations":[{"id":80005,"text":"Department of Biological Sciences, National University of Singapore, Singapore; Lee Kong Chian Natural History Museum, National University of Singapore, Singapore","active":true,"usgs":false}],"preferred":false,"id":894221,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cairns, Stephen D.","contributorId":333889,"corporation":false,"usgs":false,"family":"Cairns","given":"Stephen","email":"","middleInitial":"D.","affiliations":[{"id":80003,"text":"Department of Invertebrate Zoology, Smithsonian Institution, Washington DC, United States of America","active":true,"usgs":false}],"preferred":false,"id":894222,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kitahara, Marcelo V.","contributorId":333890,"corporation":false,"usgs":false,"family":"Kitahara","given":"Marcelo","email":"","middleInitial":"V.","affiliations":[{"id":80006,"text":"Center for Marine Biology, São Paulo University; Graduate Program in Zoology, Department of Zoology, Institute of Biosciences, University of São Paulo; Department of Invertebrate Zoology, Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":894223,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70250692,"text":"70250692 - 2024 - Usurpation and brooding of Least Tern (Sternula antillarum) chicks by Common Terns (Sterna hirundo)","interactions":[],"lastModifiedDate":"2023-12-27T12:45:06.135111","indexId":"70250692","displayToPublicDate":"2023-12-23T06:43:37","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"Usurpation and brooding of Least Tern (Sternula antillarum) chicks by Common Terns (Sterna hirundo)","docAbstract":"We present the 2023 U.S. Geological Survey time‐independent earthquake rupture forecast for the conterminous United States, which gives authoritative estimates of the magnitude, location, and time‐averaged frequency of potentially damaging earthquakes throughout the region. In addition to updating virtually all model components, a major focus has been to provide a better representation of epistemic uncertainties. For example, we have improved the representation of multifault ruptures, both in terms of allowing more and less fault connectivity than in the previous models, and in sweeping over a broader range of viable models. An unprecedented level of diagnostic information has been provided for assessing the model, and the development was overseen by a 19‐member participatory review panel. Although we believe the new model embodies significant improvements and represents the best available science, we also discuss potential model limitations, including the applicability of logic tree branch weights with respect different types of hazard and risk metrics. Future improvements are also discussed, with deformation model enhancements being particularly worthy of pursuit, as well as better representation of sampling errors in the gridded seismicity components. We also plan to add time‐dependent components, and assess implications with a wider range of hazard and risk metrics.
Riparian plant species can differ in their responses to streamflow variation in ways that strongly influence the composition and functioning of riparian plant communities. Quantifying these differences and the potential asymmetry of responses to low- versus high-flow phases of stream fluctuations is important for predicting and managing vegetation responses to variation in flow regimes. We measured the physiological response of two riparian plant species with different habitat preferences to an experimental flow that progressed from a low-flow to high-flow phase. Schedonorous arundinaceus, a hydric grass growing in near-channel habitat, exhibited significant and biologically substantial declines in stem water potential (SWP) during the low-flow phase of the experiment and a saturating increase in leaf relative water content (LRWC) during the high-flow phase. These patterns are consistent with cavitation risk in response to low-flow anomalies and saturating responses to high-flow anomalies in this hydric species. Pluchea sericea, a mesic shrub growing at intermediate elevations above the channel, exhibited a decrease in LRWC during the low-flow phase and an increase in SWP during the high-flow phase. These patterns are consistent with protection from stem cavitation risk during drought through leaf dehydration and opportunistic increases in water status in response to high-flow anomalies in this mesic species. The asymmetrical responses of both species to low- versus high-flow phases demonstrate unique physiological responses to flow anomalies of contrasting directions attributable to species habitat preferences and functional strategies that can be used by managers to predict non-linear vegetation responses to flow variation.
We present updated inversion‐based fault‐system solutions for the 2023 update to the National Seismic Hazard Model (NSHM23), standardizing earthquake rate model calculations on crustal faults across the western United States. We build upon the inversion methodology used in the Third Uniform California Earthquake Rupture Forecast (UCERF3) to solve for time‐independent rates of earthquakes in an interconnected fault system. The updated model explicitly maps out a wide range of fault recurrence and segmentation behavior (epistemic uncertainty), more completely exploring the solution space of viable models beyond those of UCERF3. We also improve the simulated annealing implementation, greatly increasing computational efficiency (and thus inversion convergence), and introduce an adaptive constraint weight calculation algorithm that helps to mediate between competing constraints. Hazard calculations show that ingredient changes (especially fault and deformation models) are the primary driver of hazard changes between NSHM23 and UCERF3. Updates to the inversion methodology are also consequential near faults in which the slip rate in UCERF3 was poorly fit or was satisfied primarily using large multifault ruptures that are now restricted by explicit b‐value and segmentation constraints.
Baseline information about declining North American shorebird populations is essential to determine the effects of global warming at low-lying coastal areas of the Arctic and subarctic, where numerous taxa breed, and to assess population recovery throughout their range. We estimated population sizes on the Yukon-Kuskokwim Delta in western Alaska on the eastern edge of the Bering Sea. We conducted ground-based surveys during 2015 and 2016 at 589 randomly selected plots from an area of 35,769 km2. We used stratified random sampling in 8 physiographic strata and corrected population estimates using detection ratios derived from double sampling on a subset of plots. We detected 11,110 breeding individuals of 21 taxa. Western Sandpiper (Calidris mauri), Red-necked Phalarope (Phalaropus lobatus), Dunlin (subspecies C. alpina pacifica), and Wilson’s Snipe (Gallinago delicata) were the most abundant taxa. We estimated that ~6.9 million individual shorebirds were breeding on the entire Yukon-Kuskokwim Delta in 2015 and 2016. Our surveys of this region provided robust population estimates (CVs ≤ 0.35) for 14 species. Our results indicate that the Yukon-Kuskokwim Delta supports a large proportion of North America’s breeding populations of the Pacific Golden-Plover (Pluvialis fulva), the western population of a Whimbrel subspecies (Numenius phaeopus hudsonicus), a Bar-tailed Godwit subspecies (Limosa lapponica baueri), Black Turnstone (Arenaria melanocephala), a Dunlin subspecies (Calidris alpina pacifica), and Western Sandpiper. Our study highlights the importance to breeding shorebirds of this relatively pristine but climatically sensitive deltaic system. Estuaries and deltaic systems worldwide are rapidly being degraded by anthropogenic activities. Our population estimates can be used to refine prior North American population estimates, determine effects of global warming, and evaluate conservation success by measuring population change over time.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/ornithapp/duad066","usgsCitation":"Lyons, J.E., Brown, S.C., Saalfeld, S., Johnson, J.A., Andres, B.A., Sowl, K.M., Gill, R.E., McCaffery, B.J., Kidd, L., McGarvey, M., Winn, B., Gates, H., Granfors, D.A., and Lanctot, R., 2024, Alaska's climate sensitive Yukon-Kuskokwim Delta supports seven million Arctic-breeding shorebirds, including the majority of six North American populations: Ornithological Applications, v. 126, no. 2, duad066, 14 p., https://doi.org/10.1093/ornithapp/duad066.","productDescription":"duad066, 14 p.","ipdsId":"IP-152991","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":440867,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ornithapp/duad066","text":"Publisher Index Page"},{"id":423900,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon–Kuskokwim coastal lowlands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -164.3286930983152,\n 63.39057476280905\n ],\n [\n -166.60703050643983,\n 61.37078951015633\n ],\n [\n -164.4372054832038,\n 59.715009537551424\n ],\n [\n -159.20751145416725,\n 59.836857513445096\n ],\n [\n -159.20751145416725,\n 63.40083870657119\n ],\n [\n -164.3286930983152,\n 63.39057476280905\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"126","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":222844,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":891006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Stephen C.","contributorId":38457,"corporation":false,"usgs":false,"family":"Brown","given":"Stephen","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":891007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Saalfeld, Sarah T.","contributorId":41721,"corporation":false,"usgs":true,"family":"Saalfeld","given":"Sarah T.","affiliations":[],"preferred":false,"id":891008,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, James A.","contributorId":199284,"corporation":false,"usgs":false,"family":"Johnson","given":"James","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":891009,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Andres, Brad A.","contributorId":68811,"corporation":false,"usgs":true,"family":"Andres","given":"Brad","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":891010,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sowl, Kristine M.","contributorId":60372,"corporation":false,"usgs":false,"family":"Sowl","given":"Kristine","email":"","middleInitial":"M.","affiliations":[{"id":12598,"text":"Izembek National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":891011,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gill, Robert E. 0000-0002-1414-0587 rgill@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-0587","contributorId":332825,"corporation":false,"usgs":true,"family":"Gill","given":"Robert","email":"rgill@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":891012,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McCaffery, Brian J.","contributorId":37617,"corporation":false,"usgs":true,"family":"McCaffery","given":"Brian","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":891013,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kidd, Lindall","contributorId":332827,"corporation":false,"usgs":false,"family":"Kidd","given":"Lindall","email":"","affiliations":[{"id":79655,"text":"BirdLife Australia","active":true,"usgs":false}],"preferred":false,"id":891014,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McGarvey, Metta","contributorId":332828,"corporation":false,"usgs":false,"family":"McGarvey","given":"Metta","email":"","affiliations":[{"id":79653,"text":"Manomet, Inc.","active":true,"usgs":false}],"preferred":false,"id":891015,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Winn, Brad","contributorId":332829,"corporation":false,"usgs":false,"family":"Winn","given":"Brad","affiliations":[{"id":79653,"text":"Manomet, Inc.","active":true,"usgs":false}],"preferred":false,"id":891016,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Gates, H. River","contributorId":84256,"corporation":false,"usgs":true,"family":"Gates","given":"H. River","affiliations":[],"preferred":false,"id":891017,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Granfors, Diane A.","contributorId":174567,"corporation":false,"usgs":false,"family":"Granfors","given":"Diane","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":891018,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Lanctot, Richard B.","contributorId":77879,"corporation":false,"usgs":false,"family":"Lanctot","given":"Richard B.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":891019,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70250651,"text":"70250651 - 2024 - Trophic ecology of juvenile lean and siscowet lake charr (Salvelinus namaycush) in Lake Superior: Assessing for potential competition","interactions":[],"lastModifiedDate":"2024-01-04T15:00:11.731237","indexId":"70250651","displayToPublicDate":"2023-12-21T07:12:18","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Trophic ecology of juvenile lean and siscowet lake charr (Salvelinus namaycush) in Lake Superior: Assessing for potential competition","title":"Trophic ecology of juvenile lean and siscowet lake charr (Salvelinus namaycush) in Lake Superior: Assessing for potential competition","docAbstract":"Current pollinator survey methods exhibit bias, require highly-trained practitioners, and are difficult to scale to large sample sizes. High-throughput sequencing of terrestrial eDNA could provide a complementary tool for studying pollinator communities, but eDNA methods have not been extensively evaluated. We conducted metagenetic analysis of whole arthropod community eDNA from 20 flower and seven honey bee-collected pollen samples and compared eDNA-derived data with traditional netting-based surveys of the pollinator communities present during sampling. We focused our analysis on Anthophila (bees) and detected eight bee genera belonging to four families across COI, 16S, and 28S markers. Results varied considerably by marker and eDNA substrate. Detected bee genera were plausible for the study system and about 43 percent of total bee genera were detected with both eDNA and net-based surveys, though netting resulted in more detections across a wider diversity of genera. Data from sequenced controls suggest that eDNA identifications were unlikely to have resulted from cross-contamination. Our results demonstrate that bee communities can be documented with eDNA techniques and that the choice of marker and substrate substantially influences detection. Future improvements to our methods are required, but eDNA surveys appear well-suited to characterize diverse pollinator communities and provide novel sampling perspectives within plant-pollinator networks. Future efforts should focus on improving the selection of markers available for pollinator eDNA metagenetics, addressing taxonomic gaps within reference sequence databases and optimizing sampling and eDNA isolation protocols. We anticipate that such improvements are highly feasible and that eDNA will be a useful tool to those who study pollinators and plant-pollinator interactions.
Vegetation and biological soil crust (biocrust) cover can have a stabilizing effect on dunes by fixing sediment in-place and increasing surface roughness, thus limiting dune mobility, sediment transport, and erosion. These biological effects influence rates of aeolian activity and thus surficial changes, though variability in wind and sediment supply may obscure these topographic effects. In this study, we compare monthly measures of sediment transport and decadal estimates of dune mobility to repeat topographic changes measured as a net volume change in sediment storage (difference in volume between all positive and negative topographic changes) and total volume change (absolute summed volume of all positive and negative changes) for areas of bare, vegetated, and biocrusted sand within a dunefield with limited sediment supply and unimodal winds. We found that monthly net volume changes normalized by area were similar between bare sand and sand with at least 20 % vegetation cover. However, total volume change was significantly greater for bare sand and correlated with monthly sediment flux estimates (R2 = 0.46), though the relationship was significantly improved by including monthly changes in surface roughness (R2 = 0.8). Longer-term decadal trends in topographic change showed larger total volume changes with the greatest decreases in vegetation canopy cover. Additionally, decadal total volume changes strongly correlated with estimates of dune mobility (R2 = 0.99). We also found that increased total volume changes did not necessarily signal increased net volume changes for all land cover types. Specifically, increases in total volume change for bare sand resulted in near equal or lower net volume changes, as both positive (deposition) and negative (erosion) change increased with sediment transport. Conversely, less mobile land covers, such as biocrust covered sand, increased in erosion without significant increases in total volume change, demonstrating that more stable surfaces might exhibit a larger topographic change imbalance than mobile sediment surfaces under the same conditions. This study highlights the importance of considering multiple measures of topographic change for interpreting sediment mobility, transport, and availability. Additionally, we hypothesize a novel framework for remote sensing-based empirical studies aimed at interpreting aeolian landscape evolution resulting from climate change effects on weather as well as biological controls such as vegetation and biocrusts.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2023.109021","usgsCitation":"Caster, J., Sankey, J., Sankey, T.T., Kasprak, A., Bowker, M., and Joyal, T., 2024, Do topographic changes tell us about variability in aeolian sediment transport and dune mobility? Analysis of monthly to decadal surface changes in a partially vegetated and biocrust covered dunefield: Geomorphology, v. 447, 109021, 16 p., https://doi.org/10.1016/j.geomorph.2023.109021.","productDescription":"109021, 16 p.","ipdsId":"IP-156570","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":435071,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UW0LR4","text":"USGS data release","linkHelpText":"Compilation of topographic data, aerial imagery, and land cover classification, collected between 1984 to 2021 for an aeolian dune field near Lees Ferry, AZ"},{"id":424129,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","volume":"447","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Caster, Joshua 0000-0002-2858-1228 jcaster@usgs.gov","orcid":"https://orcid.org/0000-0002-2858-1228","contributorId":199033,"corporation":false,"usgs":true,"family":"Caster","given":"Joshua","email":"jcaster@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":891537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sankey, Joel B. 0000-0003-3150-4992","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":261248,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":891538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sankey, Temuulen Ts.","contributorId":332965,"corporation":false,"usgs":false,"family":"Sankey","given":"Temuulen","email":"","middleInitial":"Ts.","affiliations":[{"id":79706,"text":"Northern Arizona University, School of Informatics, Computing and Cyber Systems, Flagstaff, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":891539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kasprak, Alan 0000-0001-8184-6128","orcid":"https://orcid.org/0000-0001-8184-6128","contributorId":245742,"corporation":false,"usgs":false,"family":"Kasprak","given":"Alan","affiliations":[{"id":49307,"text":"Current: Utah State University. Former: Southwest Biological Science Center, Grand Canyon Monitoring and Research Center, U.S. Geological Survey, Flagstaff, AZ 86001, USA","active":true,"usgs":false}],"preferred":false,"id":891540,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bowker, Matthew A.","contributorId":240683,"corporation":false,"usgs":false,"family":"Bowker","given":"Matthew A.","affiliations":[],"preferred":false,"id":891541,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Joyal, Taylor","contributorId":265766,"corporation":false,"usgs":false,"family":"Joyal","given":"Taylor","email":"","affiliations":[{"id":54788,"text":"Northern Arizona University, School of Earth and Sustainability, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":891542,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70253022,"text":"70253022 - 2024 - Environmental DNA as a tool for better understanding the distribution, abundance, and health of Atlantic and Pacific salmon","interactions":[],"lastModifiedDate":"2024-04-17T11:50:20.755724","indexId":"70253022","displayToPublicDate":"2023-12-21T06:46:28","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5686,"text":"Fisheries Magazine","active":true,"publicationSubtype":{"id":10}},"title":"Environmental DNA as a tool for better understanding the distribution, abundance, and health of Atlantic and Pacific salmon","docAbstract":"The development and application of approaches to detect and quantify environmental DNA (eDNA) have potential to improve our understanding of the distribution, abundance, and health of Atlantic Salmon Salmo salar and Pacific salmon Oncorhynchus spp. Here, we review 61 articles focusing on eDNA applications pertaining to salmon occupying natural habitat and aquaculture facilities in the context of advances, opportunities, and challenges. Given recent advances, eDNA now serves as a useful tool for detecting Atlantic Salmon and Pacific salmon and understanding threats to the health of fish and their habitats. Opportunities exist to apply sensitive and minimally invasive eDNA approaches to detect fish and assess fish habitat, assess range expansions of salmon and salmon pathogens, and detect invasive species that may threaten salmon health and abundance. Near real-time eDNA detection and quantification approaches to inform fisheries management may be on the horizon. Challenges limiting the widespread application of eDNA approaches for informing salmon management include accounting for the many factors affecting detection and quantification of eDNA, limits of data for deriving inference, and expense. Through continued development and refinement, eDNA approaches are anticipated to become increasingly available to, and utilized by, managers of Atlantic Salmon and Pacific salmon fisheries.
We paired mercury (Hg) concentrations in dragonfly larvae with water chemistry in 29 U.S. national parks to highlight how ecological and biogeochemical context (habitat, dissolved organic carbon [DOC]) influence drivers of Hg bioaccumulation. Although prior studies have defined influences of biogeochemical variables on Hg production and bioaccumulation, it has been challenging to determine their influence across diverse habitats, regions, or biogeochemical conditions within a single study. We compared global (i.e., all sites), habitat-specific, and DOC-class models to illuminate how these controls on biotic Hg vary. Although the suite of important biogeochemical factors across all sites (e.g., aqueous Hg, DOC, sulfate [SO42−], and pH) was consistent with general findings in the literature, contrasting the restricted models revealed more nuanced controls on biosentinel Hg. Comparing habitats, aqueous (filtered) total mercury (THg) and SO42− were important in lentic systems whereas aqueous (filtered) methylmercury (MeHg), DOC, pH, and SO42− were important in lotic and wetland systems. The ability to identify important variables varied among habitats, with less certainty in lentic (model weight (W) = 0.05) than lotic (W = 0.11) or wetland habitats (W = 0.23), suggesting that biogeochemical drivers of bioaccumulation are more variable, or obscured by other aspects of Hg cycling, in these habitats. Results revealed a contrast in the importance of aqueous MeHg versus aqueous THg between DOC-classes: in low-DOC sites (<8.5 mg/L), availability of upstream inputs of MeHg appeared more important for bioaccumulation; in high-DOC sites (>8.5 mg/L) THg was more important, suggesting a link to in-situ controls on bioavailability of Hg for MeHg production. Mercury bioaccumulation (indicated by bioaccumulation factor) was more efficient in low DOC-class sites, likely due to reduced partitioning of aqueous MeHg to DOC. Together, findings highlight substantial variation in the drivers of Hg bioaccumulation and suggest consideration of these factors in natural resource management and decision-making.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2023.169396","usgsCitation":"Nelson, S.J., Willacker, J., Eagles-Smith, C., Flanagan Pritz, C.M., Chen, C.Y., Klemmer, A.J., and Krabbenhoft, D.P., 2024, Habitat and dissolved organic carbon modulate variation in the biogeochemical drivers of mercury bioaccumulation in dragonfly larvae at the national scale: Science of the Total Environment, v. 912, 169396, https://doi.org/10.1016/j.scitotenv.2023.169396.","productDescription":"169396","ipdsId":"IP-159769","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":425714,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"912","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nelson, Sarah J.","contributorId":167269,"corporation":false,"usgs":false,"family":"Nelson","given":"Sarah","email":"","middleInitial":"J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":894958,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Willacker, James 0000-0002-6286-5224","orcid":"https://orcid.org/0000-0002-6286-5224","contributorId":207883,"corporation":false,"usgs":true,"family":"Willacker","given":"James","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":894959,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":221745,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":894960,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flanagan Pritz, Colleen M 0000-0002-0466-2103","orcid":"https://orcid.org/0000-0002-0466-2103","contributorId":299600,"corporation":false,"usgs":false,"family":"Flanagan Pritz","given":"Colleen","email":"","middleInitial":"M","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":894961,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chen, Celia Y.","contributorId":145630,"corporation":false,"usgs":false,"family":"Chen","given":"Celia","email":"","middleInitial":"Y.","affiliations":[{"id":16179,"text":"Dartmouth College, Hanover NH","active":true,"usgs":false}],"preferred":false,"id":894962,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Klemmer, Amanda J","contributorId":219891,"corporation":false,"usgs":false,"family":"Klemmer","given":"Amanda","email":"","middleInitial":"J","affiliations":[],"preferred":false,"id":894963,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":894964,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70251142,"text":"70251142 - 2024 - Assessing microplastics contamination in unviable loggerhead sea turtle eggs","interactions":[],"lastModifiedDate":"2024-01-24T12:42:58.730912","indexId":"70251142","displayToPublicDate":"2023-12-21T06:40:23","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":"Assessing microplastics contamination in unviable loggerhead sea turtle eggs","docAbstract":"Sea turtles, in comparison with marine mammals, sea birds, and fishes, are the most affected by microplastics in terms of number of individuals impacted and concentration within each organism. The ubiquitous nature and persistence of microplastics in the environment further compromises sea turtles as many species are currently vulnerable, endangered, or critically endangered. The objective of this study was to quantify microplastic contamination in unviable loggerhead sea turtle eggs (Caretta caretta). Eggs were collected from seven locations along the northwest coast of Florida. A total of 70 nests and 350 eggs were examined. Microplastics (n = 510) were found in undeveloped loggerhead sea turtle eggs across all seven sites, suggesting that maternal transference and/or exchange between the internal and external environment were possible. The frequency found was 7.29 ± 1.83 microplastic pieces per nest and 1.46 ± 0.01 per egg. Microplastics were categorized based on color, shape, size, and type of polymer. The predominant color of microplastics were blue/green (n = 236), shape was fibers (n = 369), and length was 10–300 μm (n = 191). Identified fragments, films, beads and one foam (n = 187) had the most common area of 1–10 μm2 (n = 45). Micro-Fourier Transform Infrared (μ-FTIR) spectroscopy analysis demonstrated that polyethylene (11 %) and polystyrene (7 %) were the main polymer types. For the first time microplastics were found in unviable, undeveloped loggerhead sea turtle eggs collected in northwest Florida. This work provides insight into the distribution patterns of microplastic pollutants in loggerhead sea turtle eggs and may extend to other species worldwide.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2023.169434","usgsCitation":"Curl, L.F., Hurst, S.A., Pomory, C.M., Lamont, M., and Janosik, A.M., 2024, Assessing microplastics contamination in unviable loggerhead sea turtle eggs: Science of the Total Environment, v. 912, 169434, 11 p., https://doi.org/10.1016/j.scitotenv.2023.169434.","productDescription":"169434, 11 p.","ipdsId":"IP-157840","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":424847,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.52215071903645,\n 30.711556366152337\n ],\n [\n -87.52215071903645,\n 29.380201094936183\n ],\n [\n -84.55584212528632,\n 29.380201094936183\n ],\n [\n -84.55584212528632,\n 30.711556366152337\n ],\n [\n -87.52215071903645,\n 30.711556366152337\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"912","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Curl, Lindsay F.","contributorId":333594,"corporation":false,"usgs":false,"family":"Curl","given":"Lindsay","email":"","middleInitial":"F.","affiliations":[{"id":16703,"text":"University of West Florida","active":true,"usgs":false}],"preferred":false,"id":893250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hurst, Samantha A.","contributorId":333595,"corporation":false,"usgs":false,"family":"Hurst","given":"Samantha","email":"","middleInitial":"A.","affiliations":[{"id":16703,"text":"University of West Florida","active":true,"usgs":false}],"preferred":false,"id":893251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pomory, Christopher M.","contributorId":333596,"corporation":false,"usgs":false,"family":"Pomory","given":"Christopher","email":"","middleInitial":"M.","affiliations":[{"id":16703,"text":"University of West Florida","active":true,"usgs":false}],"preferred":false,"id":893252,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lamont, Margaret 0000-0001-7520-6669","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":222403,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":893253,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Janosik, Alexis M.","contributorId":333597,"corporation":false,"usgs":false,"family":"Janosik","given":"Alexis","email":"","middleInitial":"M.","affiliations":[{"id":16703,"text":"University of West Florida","active":true,"usgs":false}],"preferred":false,"id":893254,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70250846,"text":"70250846 - 2024 - Using an open-source tool to develop a three-dimensional hydrogeologic framework of the Kobo Valley, Ethiopia","interactions":[],"lastModifiedDate":"2024-01-09T16:47:27.725312","indexId":"70250846","displayToPublicDate":"2023-12-20T10:36:40","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1816,"text":"Geosciences","active":true,"publicationSubtype":{"id":10}},"title":"Using an open-source tool to develop a three-dimensional hydrogeologic framework of the Kobo Valley, Ethiopia","docAbstract":"Groundwater resource management requires understanding the groundwater basin’s hydrogeology and would be improved with the development of a three-dimensional hydrogeologic framework model (HFM). A wide range of methods and software exist to quantify the extent, structure, and properties of geologic systems. However, most geologic software is proprietary and cost-prohibitive for use in developing countries. GemPy is a Python-based, open-source (no-cost) tool for generating three-dimensional geological models. This study uses available data and GemPy to develop the Kobo Valley Hydrogeologic Framework Model (KV-HFM), a three-dimensional HFM for Kobo Valley in northern Ethiopia, which is part of the East African Rift System. The KV-HFM is a conceptual model that comprises the hydrostratigraphy, structural features, and hydraulic properties of the Kobo Valley groundwater system. The limited data described the extent and altitude of the hydrostratigraphic units using the GemPy implicit potential–field interpolation. The KV-HFM showed the existence of an east-to-west, structural-based groundwater divide composed of volcanic rock and clay. This divide splits the catchment into two groundwater systems with limited interconnected flow. This study illustrates the use of open-source software for developing an HFM using sparse, existing geologic data.
","language":"English","publisher":"MDPI","doi":"10.3390/geosciences14010003","usgsCitation":"Mekonen, S.S., Boyce, S.E., Mohammed, A.K., and Disse, M., 2024, Using an open-source tool to develop a three-dimensional hydrogeologic framework of the Kobo Valley, Ethiopia: Geosciences, v. 14, no. 1, 3, 27 p., https://doi.org/10.3390/geosciences14010003.","productDescription":"3, 27 p.","ipdsId":"IP-133573","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":440882,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/geosciences14010003","text":"Publisher Index Page"},{"id":424222,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Ethiopia","otherGeospatial":"Afar Depression, Kobo Valley catchment","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 39.3,\n 12.4\n ],\n [\n 39.3,\n 11.9\n ],\n [\n 39.8333,\n 11.9\n ],\n [\n 39.8333,\n 12.4\n ],\n [\n 39.3,\n 12.4\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Mekonen, Sisay Simachew","contributorId":333048,"corporation":false,"usgs":false,"family":"Mekonen","given":"Sisay","email":"","middleInitial":"Simachew","affiliations":[{"id":79717,"text":"Hydrology and River Basin Management Department, Technical University of Munich","active":true,"usgs":false}],"preferred":false,"id":891768,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyce, Scott E. 0000-0003-0626-9492 seboyce@usgs.gov","orcid":"https://orcid.org/0000-0003-0626-9492","contributorId":4766,"corporation":false,"usgs":true,"family":"Boyce","given":"Scott","email":"seboyce@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891769,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mohammed, Abdella K.","contributorId":333049,"corporation":false,"usgs":false,"family":"Mohammed","given":"Abdella","email":"","middleInitial":"K.","affiliations":[{"id":79718,"text":"Hydraulic and Water Resources Engineering, Arba Minch University","active":true,"usgs":false}],"preferred":false,"id":891770,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Disse, Markus","contributorId":333050,"corporation":false,"usgs":false,"family":"Disse","given":"Markus","email":"","affiliations":[{"id":79717,"text":"Hydrology and River Basin Management Department, Technical University of Munich","active":true,"usgs":false}],"preferred":false,"id":891771,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70250834,"text":"70250834 - 2024 - Mapping development preferences on the perceived value of ecosystem services and land use conflict and compatibility in Greater Kuala Lumpur","interactions":[],"lastModifiedDate":"2024-01-09T16:35:13.370126","indexId":"70250834","displayToPublicDate":"2023-12-20T10:35:01","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10078,"text":"Urban Forestry & Urban Greening","active":true,"publicationSubtype":{"id":10}},"title":"Mapping development preferences on the perceived value of ecosystem services and land use conflict and compatibility in Greater Kuala Lumpur","docAbstract":"Rapid and unplanned development can diminish the social values for ecosystem services associated with urban landscapes. Tropical Global South cities, such as Greater Kuala Lumpur (GKL), Malaysia, that are highly biodiverse, are particularly vulnerable to the fragmentation and loss of natural ecosystems. This study investigates the social values for ecosystem services in GKL, a rapidly urbanising metropolitan area in Southeast Asia and presents the novel application of the SolVES (Social Values for Ecosystem Services) tool to an urban area. A public participatory GIS (PPGIS) survey was conducted to assess residents’ development preferences and perceived distribution of social values. The study revealed two groups of respondents, using cluster analysis, each with unique development preferences - a group favouring both green and grey developments and another favouring green development but strongly opposing grey development. The two groups differed statistically in their sociodemographic characteristics, and also how they mapped different social values. Our spatial analysis of their preferences towards future urban expansion in GKL highlighted locations where there is potential for land-use conflict. For example, the favour-balanced-development group tended to value built areas over green spaces. These findings support the need to consider residents’ preferences and socioecological traits through greater public engagement in urban landscape management.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ufug.2023.128183","usgsCitation":"Lourdes, K.T., Gibbins, C.N., Sherrouse, B.C., Semmens, D., Hamel, P., Sanusi, R., Azhar, B., Diffendorfer, J., and Lechner, A.M., 2024, Mapping development preferences on the perceived value of ecosystem services and land use conflict and compatibility in Greater Kuala Lumpur: Urban Forestry & Urban Greening, v. 92, 128183, 14 p., https://doi.org/10.1016/j.ufug.2023.128183.","productDescription":"128183, 14 p.","ipdsId":"IP-142664","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":440885,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ufug.2023.128183","text":"Publisher Index Page"},{"id":424221,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Malaysia","otherGeospatial":"Greater Kuala Lumpur","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 102,\n 3.5\n ],\n [\n 101.166667,\n 3.5\n ],\n [\n 101.166667,\n 2.5\n ],\n [\n 102,\n 2.5\n ],\n [\n 102,\n 3.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"92","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lourdes, Karen T.","contributorId":333035,"corporation":false,"usgs":false,"family":"Lourdes","given":"Karen","email":"","middleInitial":"T.","affiliations":[{"id":79714,"text":"University of Nottingham Malaysia","active":true,"usgs":false}],"preferred":false,"id":891722,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gibbins, Chris N.","contributorId":333036,"corporation":false,"usgs":false,"family":"Gibbins","given":"Chris","email":"","middleInitial":"N.","affiliations":[{"id":79714,"text":"University of Nottingham Malaysia","active":true,"usgs":false}],"preferred":false,"id":891723,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherrouse, Benson C. 0000-0002-5102-5895 bcsherrouse@usgs.gov","orcid":"https://orcid.org/0000-0002-5102-5895","contributorId":2445,"corporation":false,"usgs":true,"family":"Sherrouse","given":"Benson","email":"bcsherrouse@usgs.gov","middleInitial":"C.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":891724,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Semmens, Darius J. 0000-0001-7924-6529","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":64201,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":891725,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hamel, Perrine","contributorId":146253,"corporation":false,"usgs":false,"family":"Hamel","given":"Perrine","email":"","affiliations":[{"id":16647,"text":"Natural Capital Project, Stanford University, 371 Serra Mall, Stanford, CA 94305","active":true,"usgs":false}],"preferred":false,"id":891726,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sanusi, Ruzana","contributorId":333037,"corporation":false,"usgs":false,"family":"Sanusi","given":"Ruzana","email":"","affiliations":[{"id":61553,"text":"University Putra Malaysia","active":true,"usgs":false}],"preferred":false,"id":891727,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Azhar, Badrul","contributorId":333038,"corporation":false,"usgs":false,"family":"Azhar","given":"Badrul","email":"","affiliations":[{"id":61553,"text":"University Putra Malaysia","active":true,"usgs":false}],"preferred":false,"id":891728,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Diffendorfer, Jay 0000-0003-1093-6948","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":11930,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"Jay","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":891729,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lechner, Alex M.","contributorId":333039,"corporation":false,"usgs":false,"family":"Lechner","given":"Alex","email":"","middleInitial":"M.","affiliations":[{"id":79714,"text":"University of Nottingham Malaysia","active":true,"usgs":false}],"preferred":false,"id":891730,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70250901,"text":"70250901 - 2024 - The magmatic origin of the Columbia River Gorge, USA","interactions":[],"lastModifiedDate":"2024-01-11T14:30:15.316981","indexId":"70250901","displayToPublicDate":"2023-12-20T08:26:02","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"The magmatic origin of the Columbia River Gorge, USA","docAbstract":"Our newly acquired and recently published map, geochronologic, and compositional data for early intermediate-composition central volcanoes in the northeastern San Juan Mountains provide insights about the broad magmatic precursors to the large continental-arc ignimbrite flare-up in the mid-Cenozoic Southern Rocky Mountain volcanic field (SRMVF). Initial volcanism migrated from central Colorado to northern New Mexico ca. 40–29 Ma, as part of a more regional trend of southward-progressing mid-Cenozoic magmatism in the U.S. segment of the North American Cordillera. Within the San Juan locus, which represents the largest preserved erosional remnant of the SRMVF and site of most intense eruptive activity, new 40Ar/39Ar and U-Pb zircon ages show that eruptions at many individual edifices began nearly concurrently, at ca. 35 Ma, with peak activity at 34–32 Ma. Broadly similar precursor effusive volcanism characterizes other major loci of continental-arc ignimbrite magmatism along the western American cordilleras, but none of these sites records early volcanism as voluminous, spatially widespread, well exposed, or compositionally diverse as the San Juan locus in Colorado.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02691.1","usgsCitation":"Lipman, P.W., Zimmerer, M.J., and Gilmer, A.K., 2024, Precursors to a continental-arc ignimbrite flare-up: Early central volcanoes of the San Juan Mountains, Colorado, USA: Geosphere, v. 20, no. 1, p. 23-73, https://doi.org/10.1130/GES02691.1.","productDescription":"51 p.","startPage":"23","endPage":"73","ipdsId":"IP-155437","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467044,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02691.1","text":"Publisher Index Page"},{"id":462995,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"San Juan Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108.68165761517949,\n 39.59682872691155\n ],\n [\n -108.68165761517949,\n 36.71205671615208\n ],\n [\n -104.3200844779584,\n 36.71205671615208\n ],\n [\n -104.3200844779584,\n 39.59682872691155\n ],\n [\n -108.68165761517949,\n 39.59682872691155\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"20","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-12-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Lipman, Peter W. 0000-0001-9175-6118","orcid":"https://orcid.org/0000-0001-9175-6118","contributorId":203612,"corporation":false,"usgs":true,"family":"Lipman","given":"Peter","email":"","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":916126,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zimmerer, Matthew J.","contributorId":191162,"corporation":false,"usgs":false,"family":"Zimmerer","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":916127,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gilmer, Amy K. 0000-0001-5038-8136","orcid":"https://orcid.org/0000-0001-5038-8136","contributorId":218307,"corporation":false,"usgs":true,"family":"Gilmer","given":"Amy","email":"","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":916128,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70250627,"text":"70250627 - 2024 - Legacy sediment as a potential source of orthophosphate: Preliminary conceptual and geochemical models for the Susquehanna River, Chesapeake Bay watershed, USA","interactions":[],"lastModifiedDate":"2023-12-21T12:59:23.83208","indexId":"70250627","displayToPublicDate":"2023-12-20T06:56:07","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":"Legacy sediment as a potential source of orthophosphate: Preliminary conceptual and geochemical models for the Susquehanna River, Chesapeake Bay watershed, USA","docAbstract":"Nutrient pollution from agriculture and urban areas plus acid mine drainage (AMD) from legacy coal mines are primary causes of water-quality impairment in the Susquehanna River, which is the predominant source of freshwater and nutrients entering the Chesapeake Bay. Recent increases in the delivery of dissolved orthophosphate (PO4) from the river to the bay may be linked to long-term increases in pH, decreased acidity of precipitation, and decreased acidity, iron, and aluminum loading from widespread AMD. Since the 1950s, baseline pH increased from ~6.5 to ~8 in the West Branch and “North Branch” of the Susquehanna River, which drain bituminous and anthracite coalfields of Pennsylvania. A current baseline pH of ~8 and daily maxima exceeding 9 have been documented along the lower Susquehanna River. In response to improved river quality, bioavailable PO4 now may be released into solution from legacy sediment that has filled major impoundments in lower reaches of the river. At typical pH (5–8) of natural water, aqueous PO4 species tend to be adsorbed by hydrous iron, aluminum, and manganese oxides that coat soil and sediment particles; however, PO4 may be substantially desorbed at pH >8. We created a geochemical model that simulates equilibrium aqueous/solid distributions of PO4 as pH and other solution characteristics change. Considering current conditions in the lower Susquehanna River, the model demonstrates potential for extensive release of adsorbed PO4 at pH >8. Empirical data from laboratory experiments corroborate model results. The transfer of PO4 into the water column may increase algae growth, which removes CO2 and drives pH to higher values, facilitating additional PO4 release and exacerbating the potential for harmful algal blooms. Thus, legacy sediment is a currently unquantified source of PO4 that warrants consideration by resource managers and programs collaborating to reduce phosphorus loads to the bay and similar settings worldwide.
The McKay’s Bunting (Plectrophenax hyperboreus) is endemic to Alaska, breeds solely on the remote and uninhabited St. Matthew and Hall islands (332 km2) in the central Bering Sea, and is designated as a species of high conservation concern due to its small population size and restricted range. A previous hypothesized population estimate (~2,800—6,000 individuals) was greatly increased (~31,200 individuals) after systematic surveys of the species’ entire breeding range in 2003, establishing McKay’s Bunting as one of the rarest passerines in North America. In 2018, we replicated the 2003 surveys and used density surface models to estimate breeding season densities, distributions, and population change over the intervening time period. Our results indicate that the McKay's Bunting population declined by 38% (95% CI: 27—48%) from ~31,560 to 19,481 individuals since 2003. Spatial model predictions showed no areas with an increase of birds on either St. Matthew or Hall islands but revealed declines across 13% (42 km2) of St. Matthew Island. Declines disproportionately occurred both in marginal habitats with reduced rocky nesting substrate and in high-density hotspots along the coast of St. Matthew Island. The total area occupied by breeding adults decreased by 8%, and high-density hotspots shifted inland from the coast of St. Matthew Island to higher elevations on both islands, the latter potentially responses to exceptionally warm weather and reduced spring snow cover in 2018. Additionally, we observed low numbers of predators and interspecific competitors in 2018 suggesting these did not cause the decline. Our findings indicate that McKay’s Bunting meets international standards for elevating its conservation status from Least Concern to Endangered based on the International Union for Conservation of Nature Red List of Threatened Species ranking criteria. Additional population monitoring and studies to identify the causal mechanisms of the recent population decline of this rare species could assist future population assessments.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ornithapp/duad064","usgsCitation":"Richardson, R.M., Amundson, C.L., Johnson, J.A., Romano, M.D., Taylor, A.R., Fleming, M., and Matsuoka, S.M., 2024, Rapid population decline in McKay's Bunting, an Alaskan endemic, highlights the species’ current status relative to international standards for vulnerable species: Ornithological Applications, v. 126, no. 2, duad064, 12 p., https://doi.org/10.1093/ornithapp/duad064.","productDescription":"duad064, 12 p.","ipdsId":"IP-156671","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":440896,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ornithapp/duad064","text":"Publisher Index Page"},{"id":435072,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94JY2KH","text":"USGS data release","linkHelpText":"Data for Estimating McKay's Bunting (Plectrophenax hyperboreus) Population Change on St. Matthew and Hall Islands, Alaska"},{"id":423862,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Hall Island, St. Matthew Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -172.261171193919,\n 60.283813219091456\n ],\n [\n -172.19823889848468,\n 60.313577467466075\n ],\n [\n -172.38560550534595,\n 60.400588373260575\n ],\n [\n -172.5472270822568,\n 60.39634932448172\n ],\n [\n -172.88334275105373,\n 60.53524320077517\n ],\n [\n -172.8876335893788,\n 60.61534716459596\n ],\n [\n -173.08072048870488,\n 60.7127489098923\n ],\n [\n -173.13364082804736,\n 60.65742694272734\n ],\n [\n -173.05497545875448,\n 60.546497343244624\n ],\n [\n -173.0735690914964,\n 60.49370736988794\n ],\n [\n -172.95628617727795,\n 60.46833761065767\n ],\n [\n -172.7925190827116,\n 60.3796448928919\n ],\n [\n -172.6030069581948,\n 60.31074342132811\n ],\n [\n -172.261171193919,\n 60.283813219091456\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"126","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Richardson, Rachel M. 0000-0001-8501-250X rrichardson@usgs.gov","orcid":"https://orcid.org/0000-0001-8501-250X","contributorId":205918,"corporation":false,"usgs":true,"family":"Richardson","given":"Rachel","email":"rrichardson@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":890693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Amundson, Courtney L.","contributorId":332619,"corporation":false,"usgs":false,"family":"Amundson","given":"Courtney","email":"","middleInitial":"L.","affiliations":[{"id":79516,"text":"Former USGS employee, now with USDA","active":true,"usgs":false}],"preferred":false,"id":890694,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, James A. 0000-0002-2312-0633","orcid":"https://orcid.org/0000-0002-2312-0633","contributorId":299054,"corporation":false,"usgs":false,"family":"Johnson","given":"James","email":"","middleInitial":"A.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":890695,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Romano, Marc D.","contributorId":224656,"corporation":false,"usgs":false,"family":"Romano","given":"Marc","email":"","middleInitial":"D.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":890696,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taylor, Audrey R.","contributorId":10396,"corporation":false,"usgs":false,"family":"Taylor","given":"Audrey","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":890697,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fleming, Michael D.","contributorId":332620,"corporation":false,"usgs":false,"family":"Fleming","given":"Michael D.","affiliations":[{"id":79518,"text":"Images Unlimited","active":true,"usgs":false}],"preferred":false,"id":890698,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Matsuoka, Steven M. 0000-0001-6415-1885 smatsuoka@usgs.gov","orcid":"https://orcid.org/0000-0001-6415-1885","contributorId":184173,"corporation":false,"usgs":true,"family":"Matsuoka","given":"Steven","email":"smatsuoka@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":890699,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70250612,"text":"70250612 - 2024 - The 2022 Chaos Canyon landslide in Colorado: Insights revealed by seismic analysis, field investigations, and remote sensing","interactions":[],"lastModifiedDate":"2024-01-25T14:51:22.947677","indexId":"70250612","displayToPublicDate":"2023-12-19T06:59:31","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2604,"text":"Landslides","active":true,"publicationSubtype":{"id":10}},"title":"The 2022 Chaos Canyon landslide in Colorado: Insights revealed by seismic analysis, field investigations, and remote sensing","docAbstract":"An unusual, high-alpine, rapid debris slide originating in ice-rich debris occurred on June 28, 2022, at 16:33:16 MDT at the head of Chaos Canyon, a formerly glacier-covered valley in Rocky Mountain National Park, CO, USA. In this study, we integrate eyewitness videos and seismic records of the event with meteorological data, field observations, pre- and post-event satellite imagery, and uncrewed aircraft vehicle imagery to characterize the event and future hazards it may pose. Deformation of the eventual slide mass preceded rapid failure by decades, starting in the early to mid-2000s, accelerating in 2018 (the warmest year on record), and reaching ~ 20 m/year in 2021. The main event, which was preceded by smaller sliding episodes earlier that day, had a volume of ~ 2.1 million m3, reached peak velocities of about 5 m/s, slid on a surface up to 80 m deep, and moved up to ~ 245 m downslope in < 2 min. We observed blocks of frozen debris (permafrost) in the landslide deposits. Within ~ 2 weeks, these blocks had melted and became dry, conical debris mounds (molards). We hypothesize that the rapid slide was induced by gradually increasing long-term air temperatures that thawed ice and increased pore pressures. The presence and suspected influence of permafrost on the occurrence of this landslide indicate other slopes in the park, and other moderate-to-low latitude alpine regions may experience similar slope stability issues as temperatures continue to warm.
Coastal mangrove forests provide a suite of environmental services, including sequestration of anthropogenic contamination. Yet, research lags on the environmental fate and potential human health risks of mangrove-sequestered contaminants in the context of mangrove removal for development and range shifts due to climate change. To address this, we conducted a study on Moloka'i, Hawai'i, comparing microplastic and pesticide contamination in coastal compartments both at areas modified by non-native red mangroves (Rhizophora mangle) and unmodified, open coastline. Sediment, porewater, and mangrove plant tissues were collected to quantify microplastic and pesticide concentrations across ecosystem type. Average microplastics were similar between mangrove (8.89 items/kg) and non-mangrove areas (9.01 items/kg) in sediment and porewater, but mangrove roots were a substantial reservoir of microplastics (2004 items/kg). Additionally, there was a strong relationship between proximity to urban development and microplastics detected. Six pesticides were detected, most commonly the insecticide bifenthrin, found in most sediment samples (11.3 ng/g), all root samples (243.3 ng/g), and one propagule sample (8.60 ng/g). Other pesticides detected with appreciable concentrations include the neonicotinoid insecticide imidacloprid and the legacy insecticide transformation product, p,p’-DDE. The other detections, all at concentrations < 1 ng/g, were p,p’-DDT, trifluralin, and permethrin. The high concentrations of bifenthrin in roots compared to lower concentrations detected in sediment suggest that mangrove roots strongly accumulate some pesticides, indicating mangrove roots as a sink for organic contaminants. Study methods could be applied to other Hawaiian Islands and other locations where mangroves have been introduced to further examine the observed trends. Additional information is needed to investigate the fate and cycling of pesticides and microplastics adhered to mangrove roots, to better inform non-native mangrove removal efforts on Moloka'i and elsewhere.
Rare earth elements and yttrium (REEs) have a wide range of applications in high- and low-carbon technologies. The strategic significance of REEs has grown due to their expanding applications in manufacturing industries and the constrained availability of these essential resources. This research explores the applicability of machine learning models and their uncertainty for assessing the REE potential in coal beds using various coal parameters as inputs. The work focuses on developing a predictive model based on geological variables, excluding considerations related to potential shifts in the commodities market. The Indiana Coal Quality Database was used as the data source. The promising and unpromising indicators derived from the outlook coefficient of samples from the database were used as the REE potential indicator for machine learning classification models. The filter-based approach with bootstrap was used to evaluate the importance of the coal parameters and their prediction uncertainties. Four machine learning methods (linear discriminant analysis (LDA), random forest (RF), support vector machine (SVM), and artificial neural networks (ANN), a data balancing and augmentation approach (Synthetic Minority Over-sampling Technique), and bootstrap resampling techniques were used for building the models and evaluating their prediction capabilities under uncertainty. It was determined that the SVM bootstrap model with ten-times balanced and augmented data provided superior results compared with other models. Finally, stochastic spatial maps of the REE potential within the coal basin were generated using sequential indicator simulation. The spatial maps of the REE potential showed that a 29% area of the Indiana section of the Illinois coal basin has economic potential of REEs, with 90% confidence.
An assumption of biotelemetry is that animal performance is unaffected by the tagging process and tag burden, yet this assumption is often untested or not thoroughly explored. Our objective was to explore how transmitter implantation procedures influenced Atlantic Salmon Salmo salar smolt survival and migratory performance.
We monitored radio-tagged smolts, first in the hatchery and then in a river with a receiver array. We assessed survival and in-river performance in relation to surgeon, surgery duration, processing order, and fish size.
Mortality was 13.3% during an 8-day hatchery-observation but was higher for fish processed by one of two experienced surgeons (25% vs. 2%). Mortality peaked three days post-surgery and was higher for smaller fish and fish tagged during morning tagging sessions (compared to afternoons). The size effect changed over time, being greatest during the first two days post-surgery, and continuing thereafter at a diminished level. Fish performance once released into a river also differed between surgeons (migration initiation 66% vs. 82%; and to-lake migration success 22% vs 43%), and consistent with hatchery observations, fish tagged in the morning by one surgeon performed poorly once released.
We highlight immediate and lingering effects of surgical procedures on smolt survival that, if not accounted for, could bias inferences about the study population. Researchers should anticipate tagger effects during study design to ensure potential tagger effects (i.e., surgeon, order tagged, conditions during tagging) are balanced across study groups of interest. Testing for a fixed tagger effect in analyses may not always be adequate because a tagger effect may covary with processing order and fish size and may change over time.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10986","usgsCitation":"Heim, K., Withers, J.L., and Castro-Santos, T., 2024, Tagger effects in aquatic telemetry: Short-term and delayed impacts of surgery in Atlantic salmon smolts: North American Journal of Fisheries Management, v. 44, no. 2, p. 262-275, https://doi.org/10.1002/nafm.10986.","productDescription":"14 p.","startPage":"262","endPage":"275","ipdsId":"IP-154942","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":440909,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.10986","text":"Publisher Index Page"},{"id":424052,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-12-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Heim, Kurt C.","contributorId":264533,"corporation":false,"usgs":false,"family":"Heim","given":"Kurt C.","affiliations":[{"id":48645,"text":"umt","active":true,"usgs":false}],"preferred":false,"id":891196,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Withers, Jonah L.","contributorId":265471,"corporation":false,"usgs":false,"family":"Withers","given":"Jonah","email":"","middleInitial":"L.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":891197,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Castro-Santos, Theodore 0000-0003-2575-9120","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":315433,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":891198,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70238080,"text":"70238080 - 2024 - Forecasting water levels using machine (deep) learning to complement numerical modelling in the southern Everglades, USA","interactions":[],"lastModifiedDate":"2023-12-21T17:57:32.339716","indexId":"70238080","displayToPublicDate":"2023-12-15T11:51:08","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"7","title":"Forecasting water levels using machine (deep) learning to complement numerical modelling in the southern Everglades, USA","docAbstract":"Water level is an important guide for water resource management and wetland ecosystems, defining one of the most basic processes in hydrology. This research seeks to investigate the possibility of complementing numerical modeling with a Machine Learning (ML) model to forecast daily water levels in the southern Everglades in Florida, USA. An exact analytical solution to water level may not be possible, but using the computational methods afforded by ML, the traditional numerical techniques may be enhanced to generate more robust, scalable predictions. Five locations were chosen for application of the Time-Delayed Neural Network (TDNN) and Long-Short Term Memory Recurrent Neural Network (LSTM-RNN) ML models, which were built to estimate water level with 1, 2, 3, 7 and 10 day forecasts using a simulation step of 1 day. The results showed that rainfall forecasts from weather models could improve water-level forecasts if the accuracy and performance of the weather models can be improved. The ML models presented here improve water-level predictions from a historical hydrologic model for a 24 hour forecast horizon.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Advanced hydroinformatics: Machine learning and optimization for water resources","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Geophysical Union","doi":"10.1002/9781119639268.ch7","usgsCitation":"Forde, C.S., Bhattacharya, B., Solomatine, D., Swain, E., and Aumen, N., 2024, Forecasting water levels using machine (deep) learning to complement numerical modelling in the southern Everglades, USA, chap. 7 of Advanced hydroinformatics: Machine learning and optimization for water resources, p. 177-211, https://doi.org/10.1002/9781119639268.ch7.","productDescription":"35 p.","startPage":"177","endPage":"211","ipdsId":"IP-140554","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":440912,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1002/9781119639268.ch7","text":"Publisher Index Page"},{"id":423841,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.1037093889116,\n 26.92620905192487\n ],\n [\n -81.32930131865726,\n 26.92620905192487\n ],\n [\n -81.32930131865726,\n 25.096697437852114\n ],\n [\n -80.1037093889116,\n 25.096697437852114\n ],\n [\n -80.1037093889116,\n 26.92620905192487\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2023-12-15","publicationStatus":"PW","contributors":{"editors":[{"text":"Corzo Perez, Gerald A.","contributorId":332614,"corporation":false,"usgs":false,"family":"Corzo Perez","given":"Gerald","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":890674,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Solomatine, Dimitri 0000-0003-2031-9871","orcid":"https://orcid.org/0000-0003-2031-9871","contributorId":298962,"corporation":false,"usgs":false,"family":"Solomatine","given":"Dimitri","email":"","affiliations":[{"id":49677,"text":"IHE Delft Institute for Water Education","active":true,"usgs":false}],"preferred":false,"id":890675,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Forde, Courtney S 0000-0003-2084-6698","orcid":"https://orcid.org/0000-0003-2084-6698","contributorId":298960,"corporation":false,"usgs":false,"family":"Forde","given":"Courtney","email":"","middleInitial":"S","affiliations":[{"id":64740,"text":"Caribbean Institute for Meteorology and Hydrology","active":true,"usgs":false}],"preferred":false,"id":856773,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bhattacharya, Biswa 0000-0002-8046-589X","orcid":"https://orcid.org/0000-0002-8046-589X","contributorId":298961,"corporation":false,"usgs":false,"family":"Bhattacharya","given":"Biswa","email":"","affiliations":[{"id":49677,"text":"IHE Delft Institute for Water Education","active":true,"usgs":false}],"preferred":false,"id":856774,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Solomatine, Dimitri 0000-0003-2031-9871","orcid":"https://orcid.org/0000-0003-2031-9871","contributorId":298962,"corporation":false,"usgs":false,"family":"Solomatine","given":"Dimitri","email":"","affiliations":[{"id":49677,"text":"IHE Delft Institute for Water Education","active":true,"usgs":false}],"preferred":false,"id":856775,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swain, Eric 0000-0001-7168-708X","orcid":"https://orcid.org/0000-0001-7168-708X","contributorId":223705,"corporation":false,"usgs":true,"family":"Swain","given":"Eric","affiliations":[{"id":269,"text":"FLWSC-Ft. 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We analyzed a ∼95-years-long instantaneous-discharge record, an extensive sediment-transport record, oblique and aerial photographs, historical channel surveys, and historical stage-discharge rating relations to determine the primary mechanisms responsible for this transformation.
Frequent, large floods dominated the early part of the discharge record between 1926 and 1940. A dramatic ∼30 % decrease in annual mean discharge, and ∼27 % decrease in the mean of the partial-duration flood series occurred in 1941. This decline did not result in widespread channel change but provided an opportunity for vegetation to establish along the channel margins. Widespread channel narrowing began after a second decline in mean and peak discharge in 1956 at which time the channel banks became heavily vegetated. Between 1952 and 2019, the river channel narrowed by 57–59 %. Approximately 2–4 m of bed aggradation occurred at most study sites. As the channel narrowed and became more vegetated, large floods maintained the narrower channel width but did not cause rewidening. Suspended-sediment transport data illustrate the sediment trapping effects of vegetation that lead to channel narrowing; suspended-sand concentrations decline, thereby indicating sediment deposition, as vegetation becomes progressively inundated during floods. Furthermore, dense channel-margin and floodplain vegetation provide increased roughness, resulting in flood-peak attenuation and alteration of hydrograph shape. Vegetation expansion causes positive feedbacks whereby sediment deposition during floods is exacerbated by the roughness and sediment-trapping effects of vegetation leading to further narrowing. These positive feedbacks have reduced sediment delivery to the Little Colorado River downstream. Channel widening is not likely to occur unless there are very large floods that exceed the erosional threshold of the channel-margin vegetation, or unless large-scale vegetation removal efforts are undertaken.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2023.109017","usgsCitation":"Dean, D.J., and Topping, D.J., 2024, The effects of vegetative feedbacks on flood shape, sediment transport, and geomorphic change in a dryland river: Moenkopi Wash, AZ: Geomorphology, v. 447, 109017, 23 p., https://doi.org/10.1016/j.geomorph.2023.109017.","productDescription":"109017, 23 p.","ipdsId":"IP-155199","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":423885,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Moenkopi Wash","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.78862193867995,\n 37.0525531194242\n ],\n [\n -112.71049693867953,\n 37.0525531194242\n ],\n [\n -112.71049693867953,\n 33.3186010895229\n ],\n [\n -107.78862193867995,\n 33.3186010895229\n ],\n [\n -107.78862193867995,\n 37.0525531194242\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"447","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dean, David J. 0000-0003-0203-088X djdean@usgs.gov","orcid":"https://orcid.org/0000-0003-0203-088X","contributorId":131047,"corporation":false,"usgs":true,"family":"Dean","given":"David","email":"djdean@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":890950,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Topping, David J. 0000-0002-2104-4577","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":215068,"corporation":false,"usgs":true,"family":"Topping","given":"David","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":890951,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70251815,"text":"70251815 - 2024 - Numbers of wildlife fatalities at renewable energy facilities in a targeted development region","interactions":[],"lastModifiedDate":"2024-02-29T15:01:41.057961","indexId":"70251815","displayToPublicDate":"2023-12-15T08:30:47","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":"Numbers of wildlife fatalities at renewable energy facilities in a targeted development region","docAbstract":"Increased interest in renewable energy has fostered development of wind and solar energy facilities globally. However, energy development sometimes has negative environmental impacts, such as wildlife fatalities. Efforts by regional land managers to balance energy potential while minimizing fatality risk currently rely on datasets that are aggregated at continental, but not regional scales, that focus on single species, or that implement meta-analyses that inappropriately use inferential statistics. We compiled and summarized fatality data from 87 reports for solar and wind facilities in the Mojave and Sonoran Deserts region of southern California within the Desert Renewable Energy Conservation Plan area. Our goal was to evaluate potential temporal and guild-specific patterns in fatalities, especially for priority species of conservation concern. We also aimed to provide a perspective on approaches interpreting these types of data, given inherent limitations in how they were collected. Mourning doves (Zenaida macroura), Chukar (Alectoris chukar) and California Quail (Callipepla californica), and passerines (Passeriformes), accounted for the most commonly reported fatalities. However, our aggregated count data were derived from raw, uncorrected totals, and thus reflect an absolute minimum number of fatalities for the monitored period. Additionally, patterns in the raw data suggested that many species commonly documented as fatalities (e.g., waterbirds and other nocturnal migrants, bats) are rarely counted during typical pre-construction use surveys. This may explain the more commonly observed mismatch between pre-construction risk assessment and actual fatalities. Our work may serve to guide design of future scientific research to address temporal and spatial patterns in fatalities and to apply rigorous guild-specific survey methodologies to estimate populations at risk from renewable energy development.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0295552","usgsCitation":"Conkling, T., Fesnock, A.L., and Katzner, T., 2024, Numbers of wildlife fatalities at renewable energy facilities in a targeted development region: PLoS ONE, v. 18, no. 12, e0295552, 15 p., https://doi.org/10.1371/journal.pone.0295552.","productDescription":"e0295552, 15 p.","ipdsId":"IP-142188","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":440915,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0295552","text":"Publisher Index Page"},{"id":426127,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.41388196440452,\n 32.63301172668308\n ],\n [\n -114.71231156077859,\n 32.71521061573718\n ],\n [\n -114.41844327520268,\n 34.121883375452825\n ],\n [\n -115.258371375603,\n 35.51347324917859\n ],\n [\n -116.44620706269673,\n 36.348306541123236\n ],\n [\n -120.9361068529251,\n 35.49816148699837\n ],\n [\n -117.83770190615772,\n 34.11965094145391\n ],\n [\n -116.41388196440452,\n 32.63301172668308\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Conkling, Tara 0000-0003-1926-8106","orcid":"https://orcid.org/0000-0003-1926-8106","contributorId":217915,"corporation":false,"usgs":true,"family":"Conkling","given":"Tara","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":895658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fesnock, Amy L.","contributorId":334447,"corporation":false,"usgs":false,"family":"Fesnock","given":"Amy","email":"","middleInitial":"L.","affiliations":[{"id":80149,"text":"Desert District Office, U.S. Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":895659,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":895660,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}