Ungulates commonly select habitat with higher forage biomass and or nutritional quality to improve body condition and fitness. However, predation risk can alter ungulate habitat selection and foraging behavior and may affect their nutritional condition. Ungulates often choose areas with lower predation risk, sometimes sacrificing higher quality forage. This forage–predation risk trade-off can be important for life history strategies and influences individual nutritional condition and population vital rates. We used GPS collar data from adult female mule deer (Odocoileus hemionus) and mountain lions (Puma concolor) to model mule deer habitat selection in relation to forage conditions, stalking cover and predation risk from mountain lions to determine if a forage-predation risk trade-off existed for mule deer in central New Mexico. We also examined mountain lion kill sites and mule deer foraging locations to assess trade-offs at a finer scale. Forage biomass and protein content were inversely correlated with horizontal visibility, hence associated with higher stalking cover for mountain lions, suggesting a forage-predation risk trade-off for mule deer. Mule deer habitat selection was influenced by forage biomass and protein content at the landscape and within home range spatial scales, with forage protein being related to habitat selection during spring and summer and forage biomass during winter. However, mule deer selection for areas with better foraging conditions was constrained by landscape-scale encounter risk for mountain lions, such that increasing encounter risk was associated with diminished selection for areas with better foraging conditions. Mule deer also selected for areas with higher visibility when mountain lion predation risk was higher. Mountain lion kill sites were best explained by decreasing horizontal visibility and available forage protein, suggesting that deer may be selecting for forage quality at the cost of predation risk. A site was 1.5 times more likely to be a kill site with each 1-meter decrease in visibility (i.e., increased stalking cover). Mule deer selection of foraging sites was related to increased forage biomass, further supporting the potential for a trade-off scenario. Mule deer utilized spatio-temporal strategies and risk-conditional behavior to reduce predation risk, and at times selected suboptimal foraging areas with lower predation risk.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2024.1121439","usgsCitation":"Cain, J.W., Kay, J.H., Liley, S.G., and Gedir, J.V., 2024, Mule deer (Odocoileus hemionus) resource selection: Trade-offs between forage and predation risk: Frontiers in Ecology and Evolution, v. 12, 1121439, 17 p., https://doi.org/10.3389/fevo.2024.1121439.","productDescription":"1121439, 17 p.","ipdsId":"IP-148026","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":439940,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2024.1121439","text":"Publisher Index Page"},{"id":429764,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Cibola National Forest, Gallinas Mountains area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.59348062065897,\n 34.340783560738174\n ],\n [\n -107.59348062065897,\n 34.265500399112824\n ],\n [\n -107.493643710218,\n 34.265500399112824\n ],\n [\n -107.493643710218,\n 34.340783560738174\n ],\n [\n -107.59348062065897,\n 34.340783560738174\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2024-04-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902776,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kay, Jacob H.","contributorId":337909,"corporation":false,"usgs":false,"family":"Kay","given":"Jacob","email":"","middleInitial":"H.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":902777,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liley, Stewart G.","contributorId":337910,"corporation":false,"usgs":false,"family":"Liley","given":"Stewart","email":"","middleInitial":"G.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":902778,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gedir, Jay V.","contributorId":337911,"corporation":false,"usgs":false,"family":"Gedir","given":"Jay","email":"","middleInitial":"V.","affiliations":[{"id":24672,"text":"New Mexico Department of Game and Fish","active":true,"usgs":false}],"preferred":false,"id":902779,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70252794,"text":"70252794 - 2024 - Evaluating the potential for efficient, UAS-based reach-scale mapping of river channel bathymetry from multispectral images","interactions":[],"lastModifiedDate":"2024-04-05T15:19:37.198461","indexId":"70252794","displayToPublicDate":"2024-04-04T10:14:30","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17157,"text":"Frontiers in Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the potential for efficient, UAS-based reach-scale mapping of river channel bathymetry from multispectral images","docAbstract":"Introduction: Information on spatial patterns of water depth in river channels is valuable for numerous applications, but such data can be difficult to obtain via traditional field methods. Ongoing developments in remote sensing technology have enabled various image-based approaches for mapping river bathymetry; this study evaluated the potential to retrieve depth from multispectral images acquired by an uncrewed aircraft system (UAS).
Methods: More specifically, we produced depth maps for a 4 km reach of a clear-flowing, relatively shallow river using an established spectrally based algorithm, Optimal Band Ratio Analysis. To assess accuracy, we compared image-derived estimates to direct measurements of water depth. The field data were collected by wading and from a boat equipped with an echo sounder and used to survey cross sections and a longitudinal profile. We partitioned our study area along the Sacramento River, California, USA, into three distinct sub-reaches and acquired a separate image for each one. In addition to the typical, self-contained, per-image depth retrieval workflow, we also explored the possibility of exporting a relationship between depth and reflectance calibrated using data from one site to the other two sub-reaches. Moreover, we evaluated whether sampling configurations progressively more sparse than our full field survey could still provide sufficient calibration data for developing robust depth retrieval models.
Results: Our results indicate that under favorable environmental conditions like those observed on the Sacramento River during low flow, accurate, precise depth maps can be derived from images acquired by UAS, not only within a sub-reach but also across multiple, adjacent sub-reaches of the same river.
Discussion: Moreover, our findings imply that the level of effort invested in obtaining field data for calibration could be significantly reduced. In aggregate, this investigation suggests that UAS-based remote sensing could facilitate highly efficient, cost-effective, operational mapping of river bathymetry at the reach scale in clear-flowing streams.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/frsen.2024.1305991","usgsCitation":"Legleiter, C.J., and Harrison, L.R., 2024, Evaluating the potential for efficient, UAS-based reach-scale mapping of river channel bathymetry from multispectral images: Frontiers in Remote Sensing, v. 5, 1305991, 16 p., https://doi.org/10.3389/frsen.2024.1305991.","productDescription":"1305991, 16 p.","ipdsId":"IP-156864","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":439943,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/frsen.2024.1305991","text":"Publisher Index Page"},{"id":434995,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KEXVAR","text":"USGS data release","linkHelpText":"Multispectral images and field measurements of water depth from the Sacramento River near Glenn, California, acquired September 14-16, 2021"},{"id":427518,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.5,\n 40\n ],\n [\n -122.5,\n 39\n ],\n [\n -121.75,\n 39\n ],\n [\n -121.75,\n 40\n ],\n [\n -122.5,\n 40\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"5","noUsgsAuthors":false,"publicationDate":"2024-04-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":898242,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harrison, Lee R.","contributorId":174322,"corporation":false,"usgs":false,"family":"Harrison","given":"Lee","email":"","middleInitial":"R.","affiliations":[{"id":6710,"text":"University of California, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":898243,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70252803,"text":"70252803 - 2024 - Apparent non-double-couple components as artifacts of moment tensor inversion","interactions":[],"lastModifiedDate":"2024-04-05T15:09:16.834651","indexId":"70252803","displayToPublicDate":"2024-04-04T10:05:07","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17454,"text":"Seismica","active":true,"publicationSubtype":{"id":10}},"title":"Apparent non-double-couple components as artifacts of moment tensor inversion","docAbstract":"Compilations of earthquake moment tensors from global and regional catalogs find pervasive non-double-couple (NDC) components with a mean deviation from a double-couple (DC) source of around 20%. Their distributions vary only slightly with magnitude, faulting mechanism, or geologic environments. This consistency suggests that for most earthquakes, especially smaller ones whose rupture processes are expected to be simpler, the NDC components are largely artifacts of the moment tensor inversion procedure. This possibility is also supported by the fact that NDC components for individual earthquakes with Mw<6.5 are only weakly correlated between catalogs. We explore this possibility by generating synthetic seismograms for the double-couple components of earthquakes around the world using one Earth model and inverting them with a different Earth model. To match the waveforms with a different Earth model, the inversion changes the mechanisms to include a substantial NDC component while largely preserving the fault geometry (DC component). The resulting NDC components have a size and distribution similar to those reported for the earthquakes in the Global Centroid Moment Tensor (GCMT) catalog. The fact that numerical experiments replicate general features of the pervasive NDC components reported in moment tensor catalogs implies that these components are largely artifacts of the inversions not adequately accounting for the effects of laterally varying Earth structure.
","language":"English","publisher":"Seismica","doi":"10.26443/seismica.v3i1.1157","usgsCitation":"Rosler, B., Stein, S., Ringler, A.T., and Vackar, J., 2024, Apparent non-double-couple components as artifacts of moment tensor inversion: Seismica, v. 3, no. 1, 1157, 11 p., https://doi.org/10.26443/seismica.v3i1.1157.","productDescription":"1157, 11 p.","ipdsId":"IP-140079","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":439944,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.26443/seismica.v3i1.1157","text":"Publisher Index Page"},{"id":427517,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-04-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Rosler, Boris","contributorId":335403,"corporation":false,"usgs":false,"family":"Rosler","given":"Boris","email":"","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":898273,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stein, Seth","contributorId":263457,"corporation":false,"usgs":false,"family":"Stein","given":"Seth","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":898274,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":3946,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":898275,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vackar, Jiri","contributorId":335404,"corporation":false,"usgs":false,"family":"Vackar","given":"Jiri","email":"","affiliations":[{"id":80396,"text":"The Czech Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":898276,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70252873,"text":"70252873 - 2024 - Preliminary implications of viscoelastic ray theory for anelastic seismic tomography models","interactions":[],"lastModifiedDate":"2024-06-03T14:58:44.548945","indexId":"70252873","displayToPublicDate":"2024-04-04T07:02:30","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Preliminary implications of viscoelastic ray theory for anelastic seismic tomography models","docAbstract":"The recent developments in general viscoelastic ray theory provide a rigorous mathematical framework for anelastic seismic tomography. They provide closed‐form solutions of forward ray‐tracing and simple inverse problems for anelastic horizontal and spherical layered media with material gradients. They provide ray‐tracing computation algorithms valid for all angles of incidence that account for changes in wave speed, attenuation, and trajectory of anelastic P and S body waves induced by anelastic boundaries. They account for theoretical predictions that seismic waves refract as inhomogeneous waves across anelastic boundaries for all angles of incidence, which in turn accounts for energy carried by plane waves along seismic boundaries at head wave critical angles and wide‐angle refracted (WAR) ray paths that are not predicted by elastic models. Exact viscoelastic ray‐tracing numerical results for various models provide examples that illustrate the effects of anelastic boundaries on the travel times and amplitudes of seismic waves. They show the effects are strongly dependent on angle of incidence. For near‐critical and wide angles of incidence the anelastic effects on travel times and amplitudes can be large and are not explained by elastic ray theory, but the effects on travel times can be relatively small and difficult to distinguish from those for elastic media for pre‐near‐critical angles of incidence. The results for some models indicate that reflected anelastic WAR waves may be observable at the surface and possibly account for some prominent seismic arrivals not explained by elasticity. These preliminary results suggest that the application of exact viscoelastic ray‐tracing computation algorithms to exploration and teleseismic data sets can reveal new insights regarding the properties and distribution of anelastic materials in the Earth.
From 2018 through 2020, the U.S. Geological Survey, in cooperation with the Air Force Civil Engineering Center, conducted an integrated study of the Fountain Creek alluvial aquifer located near Colorado Springs, Colorado. The objective of the study was to characterize hydrologic conditions for the alluvial aquifer pertinent to the potential for transport of solutes. Specific goals of this report were to characterize the groundwater hydrology of the area, to quantify groundwater and surface-water interactions, to estimate hydraulic properties of the aquifer using aquifer testing, and to complete numerical simulations of groundwater flow.
Synoptic groundwater-level elevation measurements completed throughout this study, and as part of other U.S. Geological Survey programs between 1994 and 2020, indicate groundwater-level elevations fluctuate on annual and interannual timeframes. Groundwater-level fluctuations likely were caused by temporally variable groundwater recharge and discharge components in the area, with many wells showing maximum groundwater-level elevations during the winter months (November through March). From an interannual perspective, groundwater-level fluctuations appear to have reached maximum values during 2000 to 2003, decreased during 2003 to 2006, and remained relatively constant since that time, with the exception of several wells which have displayed rising groundwater-level elevations since 2018. Spatial evaluation of groundwater-level elevations indicates groundwater flow is generally from northeast to southwest within the vicinity of several alluvial paleochannels occurring along the northeastern margin of the aquifer. Within the center of the aquifer along Fountain Creek, groundwater flow is generally from north to south, approximately paralleling surface-water flow. To quantitatively understand the potential effect of groundwater recharge and groundwater pumping on fluctuations in groundwater-level elevation, a statistical transfer-function-noise model was applied. Results of the statistical model indicate throughout most of the aquifer, fluctuations were primarily the result of recharge seasonality. In the main stem of the aquifer where groundwater pumping wells were more concentrated, however, groundwater-level elevation fluctuations were also attributable to groundwater pumping through time.
Three-dimensional evaluation of the aquifer geometry near Fountain Creek was combined with synoptic streamflow measurement and accounting of stream gains and losses to evaluate groundwater and surface-water interactions in the study area. Streamflow gain or loss calculations indicate Fountain Creek both gains from and loses flow to the alluvial aquifer, and gaining or losing reaches of the stream may be partially controlled by the depth to bedrock near the stream. Reaches with streamflow gains tend to coincide with areas where the estimated depth to bedrock is decreasing, meaning the alluvial aquifer is likely thinning in these areas and groundwater-flow paths may be converging and discharging groundwater to the stream. Losing reaches tended to coincide with locally greater depth to bedrock where the alluvial aquifer is likely thicker and has greater storage potential for surface water lost from Fountain Creek.
Results of aquifer testing indicate hydraulic conductivity, estimated from slug tests and single-well pumping tests, ranged from 0.32 to 1,410 feet per day (ft/d) and 4.13 to 664 ft/d, respectively. These results are similar to the range of values from previous aquifer tests in the study area. Hydraulic conductivities from aquifer testing for this study were generally greater than the estimates of previous slug tests and had a mean value less than the estimates from previous pumping tests. Spatial evaluation of aquifer testing results indicates hydraulic conductivity tends to be greater in the main stem of the alluvial aquifer and lower in paleochannels upgradient from the main stem of the aquifer. The spatial variation in hydraulic conductivity may be attributed to the geomorphologic processes that formed the alluvial aquifer. Compacted sediment in the paleochannels has not been potentially transported sufficient distance to cause grain-size sorting, resulting in a poorly sorted deposit and lower hydraulic conductivities. In the central portion of the alluvial aquifer, near Fountain Creek, the sediments have been transported farther from their source areas and are likely better sorted, removing finer grained sediments that would cause lower hydraulic conductivity.
A numerical groundwater-flow model was calibrated for the Fountain Creek alluvial aquifer for 2000–19 to simulate water-budget components, groundwater-flow directions, and groundwater-flow paths. The model simulated precipitation recharge, groundwater and surface-water interactions, evapotranspiration, high-volume groundwater pumping by pumping wells, and external inflows and outflows occurring along the boundaries of the alluvial aquifer. Model calibration was completed using manual and automated approaches, the latter of which assisted in quantifying model results sensitivity to input parameters. The calibrated model corresponds well with groundwater-level elevation observations, with a mean residual (observed minus simulated groundwater-level elevation) equal to −0.60 feet. Simulated groundwater base flow to streams was typically within 10 percent of base flow estimated by independent methods. Groundwater and surface-water interactions represented the largest water-budget components of the aquifer, with the second largest groundwater discharge component coming from pumping wells. Groundwater and surface-water interactions represent both the largest gain and loss terms in the water budget, because these interactions differ spatially, meaning in some areas of the model domain groundwater is being recharged by streams, whereas in other areas, groundwater is discharged to streams. Estimates of advective groundwater-flow paths indicate pumping wells may capture groundwater recharged from losing streams and groundwater that flows into the main stem of the alluvial aquifer from paleochannels.
Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, Colorado 80225
Flood-flow estimates were computed at over 5,000 Federal Emergency Management Agency (FEMA) flood insurance study (FIS) flow locations across Pennsylvania for the 1-percent annual exceedance probability flood event (1-percent AEP). Depending on a point of interest’s proximity to a streamgage, weighting techniques may be applied to obtain flood-flow estimates for ungaged flow locations using observed peak-flow data from a nearby streamgage. Following the U.S. Geological Survey’s (USGS) published guidance, stream segments were identified where the drainage-area ratio method could be leveraged. Using updated regional regression equations and recently published flood-flow estimates at USGS streamgage locations following USGS Bulletin 17C guidelines, weighted and transferred flood flows were computed, where appropriate. For locations not applicable for the drainage-area ratio method, regression equations were used to compute flood-flow estimates. These flood-flow estimates were then compared to FEMA FIS 1-percent AEP flood-flow estimates. Percentage-difference values were computed for 3,599 FIS flow locations determined to be suitable for analysis, finding that USGS-derived flood-flow estimates were consistently lower than FEMA FIS flood-flow estimates with a statewide median percentage difference of −10.1 percent. The dataset was normally distributed with a standard deviation of 45.7 percent. Allegheny County was found to have 74 FIS flow locations with percentage-difference values greater than or equal to 67 percent or less than or equal to −67 percent. The flood-flow region in which Allegheny County is contained, Region 2, had a median percentage-difference value of −39 percent. Although removed from the final analysis, flow locations with drainage-area values above the recommended threshold for regression-based estimation (about 1,000 square miles [mi2]) were observed to have consistently higher percentage-difference values; a reminder of the limitations of use for regression-based flood-flow estimates. This report, the comparisons within, and a companion data release are intended to serve as tools to FEMA in assisting with the ongoing assessment of FIS flow locations across Pennsylvania.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235133","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Weaver, M.R., Stuckey, M.H., Colgin, J.E., and Roland, M.A., 2024, Estimation and comparison of 1-percent annual exceedance probability flood flows at Federal Emergency Management Agency flood insurance study flow locations across Pennsylvania: U.S. Geological Survey Scientific Investigations Report 2023–5133, 33 p., https://doi.org/10.3133/sir20235133.","productDescription":"Report: viii, 33 p.; Data Release","numberOfPages":"33","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-151288","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":427275,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FG2MF2","text":"USGS data release","linkHelpText":"USGS-derived 1-percent 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\"}}]}","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road,
New Cumberland, PA 17070
Mapping benthic habitats with bathymetric, acoustic, and spectral data requires georeferenced ground-truth information about habitat types and characteristics. New technologies like autonomous underwater vehicles (AUVs) collect tens of thousands of images per mission making image-based ground truthing particularly attractive. Two types of machine learning (ML) models, random forest (RF) and deep neural network (DNN), were tested to determine whether ML models could serve as an accurate substitute for manual classification of AUV images for substrate type interpretation. RF models were trained to predict substrate class as a function of texture, edge, and intensity metrics (i.e., features) calculated for each image. Models were tested using a manually classified image dataset with 9-, 6-, and 2-class schemes based on the Coastal and Marine Ecological Classification Standard (CMECS). Results suggest that both RF and DNN models achieve comparable accuracies, with the 9-class models being least accurate (~73–78%) and the 2-class models being the most accurate (~95–96%). However, the DNN models were more efficient to train and apply because they did not require feature estimation before training or classification. Integrating ML models into benthic habitat mapping process can improve our ability to efficiently and accurately ground-truth large areas of benthic habitat using AUV or similar images.
","language":"English","publisher":"MDPI","doi":"10.3390/rs16071264","usgsCitation":"Geisz, J.K., Wernette, P., and Esselman, P., 2024, Classification of lakebed geologic substrate in autonomously collected benthic imagery using machine learning: Remote Sensing, v. 16, no. 7, 1264, 29 p., https://doi.org/10.3390/rs16071264.","productDescription":"1264, 29 p.","ipdsId":"IP-152592","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":439948,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs16071264","text":"Publisher Index Page"},{"id":434996,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9N32CV7","text":"USGS data release","linkHelpText":"Autonomously Collected Benthic Imagery for Substrate Prediction, Lake Michigan 2020-2021"},{"id":433724,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.90204822016032,\n 42.674502983776904\n ],\n [\n -87.65489307014272,\n 42.76669269166209\n ],\n [\n -86.26871023108912,\n 45.83189647310439\n ],\n [\n -86.71489901589742,\n 45.86861211740754\n ],\n [\n -87.71542062998205,\n 44.51147169699496\n ],\n [\n -88.08342598535049,\n 43.233909567544146\n ],\n [\n -87.90204822016032,\n 42.674502983776904\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.61587060463187,\n 45.628545449737345\n ],\n [\n -84.87703701182424,\n 45.79764011104598\n ],\n [\n -85.13854737456055,\n 45.75496839185476\n ],\n [\n -85.7086983940175,\n 44.97892485981876\n ],\n [\n -85.62680073631381,\n 44.81109395544547\n ],\n [\n -84.61587060463187,\n 45.628545449737345\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"7","noUsgsAuthors":false,"publicationDate":"2024-04-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Geisz, Joseph K. 0000-0001-6783-7057","orcid":"https://orcid.org/0000-0001-6783-7057","contributorId":342270,"corporation":false,"usgs":false,"family":"Geisz","given":"Joseph","email":"","middleInitial":"K.","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":912943,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wernette, Phillipe Alan 0000-0002-8902-5575","orcid":"https://orcid.org/0000-0002-8902-5575","contributorId":259274,"corporation":false,"usgs":true,"family":"Wernette","given":"Phillipe Alan","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":912944,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Esselman, Peter C. 0000-0002-0085-903X","orcid":"https://orcid.org/0000-0002-0085-903X","contributorId":204291,"corporation":false,"usgs":true,"family":"Esselman","given":"Peter C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":912945,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70252786,"text":"70252786 - 2024 - Deep learning workflow to support in-flight processing of digital aerial imagery for wildlife population surveys","interactions":[],"lastModifiedDate":"2024-04-05T14:33:25.164806","indexId":"70252786","displayToPublicDate":"2024-04-03T09:27:19","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":"Deep learning workflow to support in-flight processing of digital aerial imagery for wildlife population surveys","docAbstract":"Deep learning shows promise for automating detection and classification of wildlife from digital aerial imagery to support cost-efficient remote sensing solutions for wildlife population monitoring. To support in-flight orthorectification and machine learning processing to detect and classify wildlife from imagery in near real-time, we evaluated deep learning methods that address hardware limitations and the need for processing efficiencies to support the envisioned in-flight workflow. We developed an annotated dataset for a suite of marine birds from high-resolution digital aerial imagery collected over open water environments to train the models. The proposed 3-stage workflow for automated, in-flight data processing includes: 1) image filtering based on the probability of any bird occurrence, 2) bird instance detection, and 3) bird instance classification. For image filtering, we compared the performance of a binary classifier with Mask Region-based Convolutional Neural Network (Mask R-CNN) as a means of sub-setting large volumes of imagery based on the probability of at least one bird occurrence in an image. On both the validation and test datasets, the binary classifier achieved higher performance than Mask R-CNN for predicting bird occurrence at the image-level. We recommend the binary classifier over Mask R-CNN for workflow first-stage filtering. For bird instance detection, we leveraged Mask R-CNN as our detection framework and proposed an iterative refinement method to bootstrap our predicted detections from loose ground-truth annotations. We also discuss future work to address the taxonomic classification phase of the envisioned workflow.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0288121","usgsCitation":"Ke, T., Yu, S.X., Koneff, M.D., Fronczak, D.L., Fara, L., Harrison, T., Landolt, K.L., Hlavacek, E., Lubinski, B.R., and White, T., 2024, Deep learning workflow to support in-flight processing of digital aerial imagery for wildlife population surveys: PLoS ONE, v. 19, no. 4, e0288121, 19 p., https://doi.org/10.1371/journal.pone.0288121.","productDescription":"e0288121, 19 p.","ipdsId":"IP-154866","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":439949,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0288121","text":"Publisher Index Page"},{"id":434997,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CBZQV1","text":"USGS data release","linkHelpText":"Code, imagery, and annotations for training a deep learning model to detect wildlife in aerial imagery"},{"id":427513,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts, Wisconsin","county":"Manitowoc County","otherGeospatial":"Lake Michigan, Nantucket Shoals area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.86205441323496,\n 44.34056668991383\n ],\n [\n -87.86205441323496,\n 43.85488754500619\n ],\n [\n -87.2738483494078,\n 43.85488754500619\n ],\n [\n -87.2738483494078,\n 44.34056668991383\n ],\n [\n -87.86205441323496,\n 44.34056668991383\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -69.86598676810571,\n 41.22419472396538\n ],\n [\n -69.86598676810571,\n 41.64346958731832\n ],\n [\n -70.45153895220938,\n 41.64346958731832\n ],\n 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D.","contributorId":191128,"corporation":false,"usgs":false,"family":"Koneff","given":"Mark","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":898212,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fronczak, David L.","contributorId":191560,"corporation":false,"usgs":false,"family":"Fronczak","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":898213,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fara, Luke J. 0000-0002-1143-4395","orcid":"https://orcid.org/0000-0002-1143-4395","contributorId":202973,"corporation":false,"usgs":true,"family":"Fara","given":"Luke J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":898214,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Harrison, Travis 0000-0002-9195-738X","orcid":"https://orcid.org/0000-0002-9195-738X","contributorId":335378,"corporation":false,"usgs":false,"family":"Harrison","given":"Travis","affiliations":[{"id":80387,"text":"Upper Midwest Environmental Sciences Center, Former Employee","active":true,"usgs":false}],"preferred":false,"id":898215,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Landolt, Kyle Lawrence 0000-0002-6738-8586","orcid":"https://orcid.org/0000-0002-6738-8586","contributorId":298782,"corporation":false,"usgs":true,"family":"Landolt","given":"Kyle","email":"","middleInitial":"Lawrence","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":898216,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hlavacek, Enrika 0000-0002-9872-2305","orcid":"https://orcid.org/0000-0002-9872-2305","contributorId":297184,"corporation":false,"usgs":false,"family":"Hlavacek","given":"Enrika","affiliations":[{"id":48800,"text":"Former USGS, UMESC employee","active":true,"usgs":false}],"preferred":false,"id":898217,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lubinski, Brian R.","contributorId":177523,"corporation":false,"usgs":false,"family":"Lubinski","given":"Brian","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":898218,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"White, Timothy","contributorId":236917,"corporation":false,"usgs":false,"family":"White","given":"Timothy","email":"","affiliations":[{"id":20318,"text":"Bureau of Ocean Energy Management","active":true,"usgs":false}],"preferred":true,"id":898219,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70252763,"text":"70252763 - 2024 - Propensity score matching mitigates risk of faulty inferences in observational studies of effectiveness of restoration trials","interactions":[],"lastModifiedDate":"2024-05-20T15:29:15.542173","indexId":"70252763","displayToPublicDate":"2024-04-03T09:13:24","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Propensity score matching mitigates risk of faulty inferences in observational studies of effectiveness of restoration trials","docAbstract":"While the recent incursion of highly pathogenic avian influenza into North America has resulted in notable losses to the commercial poultry industry, the mechanism by which virus enters commercial poultry houses is still not understood. One theorized mechanism is that waterfowl shed virus into the environment surrounding poultry farms, such as into retention ponds, and is then transmitted into poultry houses via bridge species. Little is known about if and when wild waterfowl use these retention ponds, leading to uncertainty regarding the potential significance of this interface. To quantify the use of retention ponds on commercial poultry farms by wild waterfowl, we surveyed 12 such ponds across Somerset and Dorchester counties, Maryland, USA. This region was chosen due to the high level of poultry production and its importance for migratory waterfowl. Surveys consisted of recording waterfowl visible on the retention ponds from public roadways at least once per week from 20 September 2022–31 March 2023. Throughout the course of this study, we observed a total of nine species of waterfowl using retention ponds on commercial poultry farms at nine of 12 sites. The number of waterfowl observed at retention ponds varied notably throughout the course of our survey period, with values generally following trends of fall migration within each species indicating that resident birds were not the only individuals to utilize these habitats. Additionally, waterfowl use was highest at sites with little vegetation immediately surrounding the pond, and lowest when ponds were surrounded by trees. Our data suggest that retention ponds on commercial poultry farms present a notable interface for waterfowl to introduce avian influenza viruses to farm sites. However, additional testing and surveys could provide further insight into whether it may be possible to reduce the use of these habitats by wild waterfowl through vegetative management as preliminarily reported here.
","language":"English","publisher":"Hindawi","doi":"10.1155/2024/3022927","usgsCitation":"Sullivan, J.D., McDonough, A., Lescure, L., and Prosser, D., 2024, Identifying an understudied interface: Preliminary evaluation of the use of retention ponds on commercial poultry farms by wild waterfowl: Transboundary and Emerging Diseases, v. 2024, 3022927, 9 p., https://doi.org/10.1155/2024/3022927.","productDescription":"3022927, 9 p.","ipdsId":"IP-156554","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":439953,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1155/2024/3022927","text":"Publisher Index Page"},{"id":434998,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U7QISZ","text":"USGS data release","linkHelpText":"Data describing the use of retention ponds on commercial poultry facilities on Delmarva by wild waterfowl"},{"id":427619,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2024","noUsgsAuthors":false,"publicationDate":"2024-04-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Sullivan, Jeffery D. 0000-0002-9242-2432","orcid":"https://orcid.org/0000-0002-9242-2432","contributorId":265822,"corporation":false,"usgs":true,"family":"Sullivan","given":"Jeffery","email":"","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":898427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McDonough, Ayla","contributorId":332811,"corporation":false,"usgs":false,"family":"McDonough","given":"Ayla","email":"","affiliations":[{"id":78934,"text":"Akima","active":true,"usgs":false}],"preferred":false,"id":898428,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lescure, Lauren","contributorId":335066,"corporation":false,"usgs":false,"family":"Lescure","given":"Lauren","affiliations":[{"id":27609,"text":"Contractor to USGS","active":true,"usgs":false}],"preferred":false,"id":898429,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prosser, Diann 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":217931,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":898430,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70253057,"text":"70253057 - 2024 - Quantifying and evaluating strategies to decrease carbon dioxide emissions generated from tourism to Yellowstone National Park","interactions":[],"lastModifiedDate":"2024-04-18T12:11:12.119066","indexId":"70253057","displayToPublicDate":"2024-04-03T07:08:14","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16703,"text":"PLOS Climate","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying and evaluating strategies to decrease carbon dioxide emissions generated from tourism to Yellowstone National Park","docAbstract":"The tourism industry needs strategies to reduce emissions and hasten the achievement of global carbon dioxide (CO2) emission reduction targets. Using a case study approach, we estimated CO2 emissions related to park tourism in Yellowstone National Park (USA) generated from transit to and from the park, transit within the park, accommodations, and park operations. Results indicate tourism to Yellowstone National Park produces an estimated 1.03 megaton (1.03 billion kg) of CO2-equivalent emissions annually, with an average of 479 kg CO2 per visitor. Almost 90% of these emissions were attributable to transit to and from the destination, while 5% were from transit within the park, 4% from overnight accommodations, and about 1% from other park operations (e.g., visitor centers, museums, shops, restaurants, etc.). Visitors who fly only made up about 35% of all visitors, but produced 72% of the emissions related to transit to and from the park. Future scenarios that alter transit to and from the park can reduce emissions the most; this includes a greater proportion of local or regional visitors, fewer visitors flying, and increased fuel efficiency of vehicles. The method developed in this work, and applied specifically to Yellowstone National Park, can be adopted elsewhere and used to help decision makers evaluate the effectiveness of potential emission reduction strategies.
Weather, climate, and climate change all effect outdoor recreation and tourism, and will continue to cause a multitude of effects as the climate warms. We conduct a systematic literature review to better understand how weather, climate, and climate change affect outdoor recreation and nature-based tourism across the United States. We specifically explore how the effects differ by recreational activity, and how visitors and supply-side tourism operators perceive these effects and risks. The 82 papers reviewed show the complex ways in which weather, climate, and climate change may affect outdoor recreation, with common themes being an extended season to participate in warm-weather activities, a shorter season to participate in snow-dependent activities, and larger negative effects to activities that depend on somewhat consistent precipitation levels (e.g., snow-based recreation, water-based recreation, fishing). Nature-based tourists perceive a variety of climate change effects on tourism, and some recreationists have already changed their behavior as a result of climate change. Nature-based tourism suppliers are already noticing a wide variety of climate change effects, including shifts in seasonality of specific activities and visitation overall. Collectively, this review provides insights into our current understanding of climate change and outdoor recreation and opportunities for future research.
Declines in bumble bee species range and abundances are documented across multiple continents and have prompted the need for research to aid species recovery and conservation. The rusty patched bumble bee (Bombus affinis) is the first federally listed bumble bee species in North America. We conducted a range-wide population genetics study of B. affinis from across all extant conservation units to inform conservation efforts. To understand the species’ vulnerability and help establish recovery targets, we examined population structure, patterns of genetic diversity, and population differentiation. Additionally, we conducted a site-level analysis of colony abundance to inform prioritizing areas for conservation, translocation, and other recovery actions. We find substantial evidence of population structuring along an east-to-west gradient. Putative populations show evidence of isolation by distance, high inbreeding coefficients, and a range-wide male diploidy rate of ~15%. Our results suggest the Appalachians represent a genetically distinct cluster with high levels of private alleles and substantial differentiation from the rest of the extant range. Site-level analyses suggest low colony abundance estimates for B. affinis compared to similar datasets of stable, co-occurring species. These results lend genetic support to trends from observational studies, suggesting that B. affinis has undergone a recent decline and exhibit substantial spatial structure. The low colony abundances observed here suggest caution in overinterpreting the stability of populations even where B. affinis is reliably detected interannually. These results help delineate informed management units, provide context for the potential risks of translocation programs, and help set clear recovery targets for this and other threatened bumble bee species.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/jisesa/ieae041","usgsCitation":"Mola, J., Pearse, I.S., Boone, M., Evans, E., Hepner, M.J., Jean, R., Kochanski, J., Nordmeyer, C., Runquist, E., Smith, T.A., Strange, J., Watson, J., and Koch, J.B., 2024, Range-wide genetic analysis of an endangered bumble bee (Bombus affinis, Hymenoptera: Apidae) reveals population structure, isolation by distance, and low colony abundance: Journal of Insect Science, v. 24, no. 2, 19, 12 p., https://doi.org/10.1093/jisesa/ieae041.","productDescription":"19, 12 p.","ipdsId":"IP-160165","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":439960,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jisesa/ieae041","text":"Publisher Index Page"},{"id":434999,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13CHTK8","text":"USGS data release","linkHelpText":"Population genetic analysis of the rusty patched bumble bee in extant locations in 2022"},{"id":427779,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Illinois, Indiana, Kentucky, Michigan, Minnesota, Ohio, Virginia, Wisconsin, West 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\"}}]}","volume":"24","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-04-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Mola, John","contributorId":335435,"corporation":false,"usgs":false,"family":"Mola","given":"John","affiliations":[{"id":80402,"text":"Colorado State U","active":true,"usgs":false}],"preferred":false,"id":898842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearse, Ian S. 0000-0001-7098-0495","orcid":"https://orcid.org/0000-0001-7098-0495","contributorId":216680,"corporation":false,"usgs":true,"family":"Pearse","given":"Ian","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":898843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boone, Michelle","contributorId":335436,"corporation":false,"usgs":false,"family":"Boone","given":"Michelle","affiliations":[{"id":40035,"text":"U Minnesota","active":true,"usgs":false}],"preferred":false,"id":898844,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Evans, Elaine","contributorId":335437,"corporation":false,"usgs":false,"family":"Evans","given":"Elaine","email":"","affiliations":[{"id":40035,"text":"U Minnesota","active":true,"usgs":false}],"preferred":false,"id":898845,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hepner, Mark J.","contributorId":335438,"corporation":false,"usgs":false,"family":"Hepner","given":"Mark","middleInitial":"J.","affiliations":[{"id":80404,"text":"Metamophecology","active":true,"usgs":false}],"preferred":false,"id":898846,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jean, Robert","contributorId":335439,"corporation":false,"usgs":false,"family":"Jean","given":"Robert","affiliations":[{"id":80405,"text":"ESI","active":true,"usgs":false}],"preferred":false,"id":898847,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kochanski, Jade 0000-0001-8693-2404","orcid":"https://orcid.org/0000-0001-8693-2404","contributorId":270193,"corporation":false,"usgs":false,"family":"Kochanski","given":"Jade","email":"","affiliations":[{"id":34113,"text":"University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":898848,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nordmeyer, Cade","contributorId":335612,"corporation":false,"usgs":false,"family":"Nordmeyer","given":"Cade","email":"","affiliations":[{"id":79104,"text":"Minnesota Zoo","active":true,"usgs":false}],"preferred":false,"id":898849,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Runquist, Eric","contributorId":335614,"corporation":false,"usgs":false,"family":"Runquist","given":"Eric","email":"","affiliations":[{"id":80447,"text":"9. U.S. Fish and Wildlife Service, Minnesota-Wisconsin Ecological Services Field Office","active":true,"usgs":false}],"preferred":false,"id":898850,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Smith, Tamara A.","contributorId":257977,"corporation":false,"usgs":false,"family":"Smith","given":"Tamara","email":"","middleInitial":"A.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":898851,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Strange, Jaime","contributorId":335615,"corporation":false,"usgs":false,"family":"Strange","given":"Jaime","email":"","affiliations":[{"id":80406,"text":"Ohio State","active":true,"usgs":false}],"preferred":false,"id":898852,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Watson, Jay","contributorId":335443,"corporation":false,"usgs":false,"family":"Watson","given":"Jay","email":"","affiliations":[{"id":80407,"text":"Winsconsin DNR","active":true,"usgs":false}],"preferred":false,"id":898853,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Koch, Jonathan B","contributorId":237988,"corporation":false,"usgs":false,"family":"Koch","given":"Jonathan","email":"","middleInitial":"B","affiliations":[{"id":47671,"text":"University of Hawai'i, Hilo","active":true,"usgs":false}],"preferred":false,"id":898854,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70256184,"text":"70256184 - 2024 - The potential influence of genome-wide adaptive divergence on conservation translocation outcome in an isolated greater sage-grouse population","interactions":[],"lastModifiedDate":"2024-07-26T00:07:03.307419","indexId":"70256184","displayToPublicDate":"2024-04-02T19:05:38","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"The potential influence of genome-wide adaptive divergence on conservation translocation outcome in an isolated greater sage-grouse population","docAbstract":"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
A century ago, measuring elevation in tidal wetlands proved difficult, as survey leveling of soft marsh soils relative to a fixed datum was error prone. For 60 years, vertical accretion measures from marker horizons were used as analogs of elevation change. But without a direct measure of elevation, it was not possible to measure the total influence of surface and subsurface processes on elevation. In the 1990s, the surface elevation table (SET) method, which measures the movement of the wetland surface relative to a fixed point beneath the surface (i.e., the SET benchmark base), was combined with the marker horizon method (SET-MH), providing direct, independent, and simultaneous measures of surface accretion and elevation and quantification of surface and shallow subsurface process influences on elevation. SET-MH measures have revealed several fundamental findings about tidal wetland dynamics. First, accretion [A] is often a poor analog for elevation change [E]. From 50–66% of wetlands experience shallow subsidence (A > E), 7–10% shallow expansion (A < E), 7% shrink-swell, and for 24–36% A is an analog for E (A = E). Second, biological processes within the root zone and physical processes within and below the root zone influence elevation change in addition to surface processes. Third, vegetation plays a key role in wetland vertical dynamics. Plants trap sediment and increase resistance to erosion and compaction. Soil organic matter accumulation can lead to shallow expansion, but reduced plant growth can lead to subsidence, and plant death to soil collapse. Fourth, elevation rates are a better indicator of wetland response to sea-level rise than accretion rates because they incorporate subsurface influences on elevation occurring beneath the marker horizon. Fifth, combining elevation trends with relative sea-level rise (RSLR) trends improves estimates of RSLR at the wetland surface (i.e., RSLRwet). Lastly, subsurface process influences are fundamental to a wetland’s response to RSLR and plant community dynamics related to wetland transgression, making the SET-MH method an invaluable tool for understanding coastal wetland elevation dynamics.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-024-01332-z","usgsCitation":"Cahoon, D., 2024, Measuring and interpreting the surface and shallow subsurface process influences on coastal wetland elevation: A review: Estuaries and Coasts, v. 47, p. 1708-1734, https://doi.org/10.1007/s12237-024-01332-z.","productDescription":"27 p.","startPage":"1708","endPage":"1734","ipdsId":"IP-156420","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":427516,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","noUsgsAuthors":false,"publicationDate":"2024-04-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Cahoon, Donald R. 0000-0002-2591-5667","orcid":"https://orcid.org/0000-0002-2591-5667","contributorId":219657,"corporation":false,"usgs":true,"family":"Cahoon","given":"Donald","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":898277,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70252765,"text":"70252765 - 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?","interactions":[],"lastModifiedDate":"2024-04-04T15:06:24.47512","indexId":"70252765","displayToPublicDate":"2024-04-02T09:56:30","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1636,"text":"Fire Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Vegetation, fuels, and fire-behavior responses to linear fuel-break treatments in and around burned sagebrush steppe: Are we breaking the grass-fire cycle?","docAbstract":"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.
Community-type conversions, such as replacement of perennials by exotic annual grasses in semiarid desert communities, are occurring due to plant invasions that often create positive plant–soil feedbacks, which favor invaders and make restoration of native perennials difficult. Exotic annual grass control measures, such as pre-emergent herbicides, can also alter soil ecosystems directly or indirectly (i.e. via the plant community), yet there are few studies on the topic in natural, non-cropped landscapes. We asked how spray treatments applied to soil post-fire with the intention of inhibiting invasive annual grasses (such as Bromus tectorum L.) and releasing existing native perennial grasses affected soil resources, a microbial process, and invertebrates in three climatically varied sagebrush steppe sites. Spray treatments included chemical herbicides (imazapic and rimsulfuron) that strongly affected plant communities and a bioherbicide (Pseudomonas fluorescens strain D7) that did not. Chemical herbicides increased soil mineral nitrogen in proportion to their negative effects on plant cover for 2 years after treatments in all sites and increased soil water and net N mineralization (measured at one site) but did not affect total carbon, nitrogen, or organic matter. Invertebrate responses to herbicides varied by site, and invertebrates increased with chemical herbicides at the highest, wettest site. We show that herbicide treatments can exacerbate pulses of mineral nutrients, which previous studies have shown can weaken ecosystem resistance to invasion. Thus, restoration strategies that increase the likelihood that desired plants can capture mineralized nutrients after herbicide application will likely be more successful.
Increasing stream metal concentrations apparently caused by climate warming have been reported for a small number of mountain watersheds containing hydrothermally altered bedrock with abundant sulfide minerals (mineralized watersheds). Such increases are concerning and could negatively impact downstream ecosystem health, water resources, and mine-site remediation efforts. However, the pervasiveness and typical magnitude of these trends remain uncertain. We aggregated available streamwater chemistry data collected from late summer and fall over the past 40 years for 22 mineralized watersheds throughout the Colorado Rocky Mountains. Temporal trend analysis performed using the Regional Kendall Test indicates significant regional upward trends of ∼2% of the site median per year for sulfate, zinc, and copper concentrations in the 17 streams affected by acid rock drainage (ARD; median pH ≤ 5.5), equivalent to concentrations roughly doubling over the past 30 years. An examination of potential load trends utilizing streamflow data from eight “index gages” located near the sample sites provides strong support for regionally increasing sulfate and metal loads in ARD-affected streams, particularly at higher elevations. Declining streamflows are likely contributing to regionally increasing concentrations, but increasing loads appear to be on average an equal or greater contributor. Comparison of selected site characteristics with site concentration trend magnitudes shows the highest correlation for mean annual air temperature and mean elevation (R2 of 0.42 and 0.35, respectively, with all others being ≤0.14). Future research on climate-driven controlling mechanisms should therefore focus on processes such as melting of frozen ground directly linked to site mean temperature and elevation.
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.
Urban growth and other land-use changes were examined in the Lower Rio Grande Valley and Alluvial Floodplain ecoregions in Texas, along the U.S.-Mexico border. The analysis focused on understanding the types and causes of land change as well as the recovery of natural land-cover types between years 2001 and 2011. The purpose was to develop improved capabilities for understanding land change dynamics in urbanizing ecoregions and to provide data for further analyses. The spatial data, including metadata, allows further exploration and characterization of changes affecting this dynamic region.
Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, Mail Stop 980
Denver, CO 80225
This study examined the abundance and distribution of nutrients and phytoplankton in the tidal aquatic environments of the Sacramento–San Joaquin Delta (Delta) and Suisun Bay, comprising three spatial surveys conducted in May, July, and October of 2018 that used continuous underway high frequency sampling and measurements onboard a high-speed boat to characterize spatial variation across the extent of the Delta. The method used involves simultaneously collecting information about the concentration and spatial distribution of all major nutrient forms with analogous information about the major classes of phytoplankton and associated water-quality conditions. The results showed substantial variation across space and time, providing an unprecedented snapshot of the dynamic environmental processes that shape the ways nutrients interact with and affect aquatic habitats in the Delta.
The purposes of this study were to improve our understanding of how hydrodynamics, landscape features, and aquatic primary productivity interact to drive nutrient cycling and transport in the Delta and to provide insights into the underlying processes most directly responsible for the conditions at the time of this study, and thus into the range of conditions that may be expected following the wide array of prospective future changes to the Delta. One major anticipated change at the time of this study was the planned upgrade to the Sacramento Regional Wastewater Treatment Plant, but the study also informs our understanding of potential effects from other changes to the Delta, such as those caused by other nutrient-management actions, flow actions, large-scale wetland restoration, drought, flood, levee failure, and changes to water management.
Nutrient loading is the primary driver of nutrient concentrations in the Delta, but several other major drivers interact to shape their distribution and effects: geomorphology, hydrodynamics, landscape features, and aquatic productivity. Hydrodynamics affect timescales of transport and dilution of nutrient loads in the Delta. During transit through the system, channel geometry, tidal mixing, and water exports affect hydrodynamics in diverse ways that influence water-residence and transport times, thereby markedly affecting the range of times during which natural internal cycling can alter nutrient concentrations and forms. Channel geometry and location shape tidal energy and river currents into these observed dynamics. Interactions with Delta aquatic landscapes such as herbaceous tidal marsh, submerged aquatic vegetation, and large expanses of intertidal or subtidal sediments (all highly productive landscapes) exert demand on available nutrient supplies but can also simultaneously transform and generate nutrients. Finally, while phytoplankton require nutrients to sustain production and thus are a potential nutrient sink, the amount and form of nutrients also can influence the occurrence of harmful algal blooms (HABs) that adversely affect aquatic organisms as well as affect the occurrence of beneficial algal blooms that result in production of algae that are favorable for imperiled Delta pelagic aquatic food webs.
The surveys revealed a complex mosaic of spatial variation, with nutrient concentrations varying from near zero to well above concentrations considered eutrophic; nutrient concentrations were more often related to the extent of hydrologic transport and mixing than to specific geographic locations or to specific landscape features. Similarly, the surveys identified phytoplankton abundance ranging from near detection to the level of large phytoplankton blooms, with large variation in phytoplankton community composition. Although the study occurred during a period of low bloom activity, phytoplankton productivity appeared to be the strongest potential sink for inorganic nutrients in the Delta, indicating that it is a larger control on nutrient concentrations and distribution than previously understood. Cycling and transformation within the water column only appeared to substantially lower total nutrient concentrations at the longest estimated transport timescales. Contrary to expectations, we did not observe substantial nutrient depletion near landscape-scale features such as open-water habitats, submerged aquatic vegetation beds, extensive wetlands, or exposed sediments, indicating that these habitat types did not act as major sinks for nutrients in the Delta during these surveys. These results indicated that nutrient reduction efforts may have the greatest effect on pelagic phytoplankton productivity in the more productive reaches of the Delta and estuary, but these effects are unlikely to be magnified by changes to nutrient loss within the Delta over conceivable changes in flow conditions, Delta water management actions, or large-scale wetland restoration activities. Nevertheless, local processes were shown to cause substantial loss, and thus integrating of nutrient effects with other indicators of aquatic habitat conditions will help inform planning future actions at specific sites.
Finally, we note that the primary contribution of this study was intended to be the survey data themselves. Aside from the results highlighted in this report, the surveys are a benchmark against which future environmental change may be evaluated, including changes to nutrient management or water exports, drought, large-scale wetland restoration, and climate change. Further, although we highlight some of the main findings from the surveys in this report, the necessarily limited scope precludes examination of many topics for which these surveys may be highly informative. To facilitate the utility of these data to stakeholders, managers, and researchers, we have released the data online (Bergamaschi and others, 2020) and created an online data exploration portal (https://ca.water.usgs.gov/bay-delta/2018-delta-wide-mapping-surveys.html) where users may query the surveys in a variety of ways to test hypotheses, examine relationships, assess spatial trends, and download data. The data exploration portal is intended to be an immersive experience that allows users to gain greater understanding of the complex interactions that shape Delta aquatic environments. This report is intended as a companion to the portal, allowing the reader to challenge and further explore the highlighted findings.
This study was a collaboration between the U.S. Geological Survey and the Delta Regional Monitoring Program, with additional funding provided from U.S. Geological Survey Cooperative Matching Funds Program.
Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819