Recent large-scale spatial products have been developed to assess wetland position in the tidal frame, but nationwide comparisons and validations are missing for these products. Wetland position within the tidal frame is a commonly used characteristic to compare wetlands across biogeomorphic gradients and factors heavily into wetland vulnerability models. We utilize a dataset of 365 surface elevation table stations across the conterminous USA containing ground-surveyed tidal datum and elevation data to validate two gridded, conterminous USA–wide relative tidal elevation products. We identified substantial differences between our ground-surveyed dataset and the gridded products, with the Gulf coast exhibiting the greatest error (p < 0.0001, n = 140). Error in relative tidal elevation products varied by coast, tidal range, and latitude. These differences in errors indicate that gridded relative tidal elevation products may be more accurate in coastal wetlands with larger tidal ranges (> 30 cm) and are less accurate in freshwater wetlands near the coast. This paper makes advances in understanding why relative tidal elevation differences occur among national datasets and identifies areas of future work that could support more robust vulnerability models.
Salinity, or total dissolved solids (TDS), of the Colorado River affects agricultural, municipal, and industrial water users and is an important concern in the Western United States. In the Paradox Valley of southwestern Colorado, natural discharge of sodium-chloride brine to the Dolores River from the underlying core of a salt-valley anticline accounts for about 6 percent of the salinity load to the Colorado River. Formation of the Paradox Valley began during the Miocene, and subsequent erosion exposed the Pennsylvania Paradox Formation in the core of the anticline where a cap rock, collapse features, breccia, and sodium-chloride saturated brine developed at the top of the exposed salt diapir. The discharge of brine to the Dolores River is affected by these dissolution features, along with seasonal hydrologic conditions and density-dependent flow between older dense brine and the younger fresh groundwater in the overlying alluvial aquifer. To reduce TDS concentrations in the Dolores River through the Paradox Valley, the Bureau of Reclamation has pumped brine from a series of shallow wells adjacent to the river since July 1996. The pumped brine is collected and piped to a deep disposal well where it is injected into the Mississippian Leadville Limestone at a depth of about 4,570-meters below land surface. The pumping and injection operation is collectively known as the Paradox Valley Unit (PVU), and by 2015, the PVU had substantially reduced TDS concentrations in the Dolores River by about 70 percent. Since 2019, injection-pressure limits and related seismic activity have constrained deep-well injection and thus brine pumping at the PVU.
In cooperation with the Bureau of Reclamation, the U.S. Geological Survey developed a MODFLOW-6 three-dimensional, variable-density groundwater flow and TDS transport model of the Paradox Valley to evaluate the effects of PVU pumping operations on brine discharge to the Dolores River and to guide additional research. The finite-difference model grid consists of 76 rows and 48 columns oriented from northwest to southeast in alignment with valley topography and groundwater-flow directions in the near-surface freshwater alluvial aquifer. A 7-layer hydrogeologic framework was developed from existing datasets to represent the alluvial aquifer, cap rock, collapse breccia, and groundwater flow and TDS transport from the underlying Paradox Formation salt to the Dolores River. The model represents a 33-year transient calibration period from 1987 through 2020 that includes pre-PVU conditions from 1987 through June 1996 and post-PVU conditions from July 1996 through 2020. A 1,000-year simulation of groundwater flow and coupled TDS transport computed the initial conditions for the subsequent 33-year transient simulation. Observations of precipitation, streamflow, evaporation, agricultural land use, and PVU brine pumping rates were used to specify appropriate boundary conditions to the model representing time-varying recharge, tributary streamflow, groundwater underflow, evapotranspiration (ET), and PVU pumping. Values for average monthly streamflow and TDS concentration at the upstream streamgage, the Dolores River at Bedrock (USGS streamgage 09169500), were specified as model input where the Dolores River enters Paradox Valley. Observed pumping from the PVU, water levels and TDS concentrations in groundwater, and streamflow and estimated TDS concentrations at the downstream streamgage, the Dolores River near Bedrock (USGS streamgage 09171100), were calibration targets that constrained the manual calibration of model parameters representing aquifer hydraulic conductivity, storage, streambed conductance, recharge, and (ET).
Two primary model-calibration targets were the match between observed and simulated TDS mass flux from PVU pumping wells and the match between estimated and simulated TDS mass flux to the Dolores River. The simulated TDS mass withdrawn by pumping wells is calculated by the model as the product of the assigned pumping rate and simulated groundwater TDS concentrations. Because actual pumping rates were assigned as simulated values, the total simulated PVU pumping for the 33-year calibration is within 0.5 percent of the observed values. However, simulated concentrations and thus mass flux of TDS withdrawn by the PVU pumping wells were consistently about 26 percent less than observed values for all the simulated time periods (33-year simulation, pre-PVU, and post-PVU). The representation of brine inflow was explored through additional modeling to evaluate the effect of the simulated brine source on groundwater TDS concentrations. Results indicated that a saturated-salt constant-flux brine source best replicated the magnitude and transient pattern observed for TDS mass flux from PVU pumping wells.
The simulated TDS mass flux to the Dolores River is compared to estimates based on observed streamflow and specific conductance (SC) data for the downstream streamgage. The calibrated model provided a close fit of simulated to measured streamflow at the downstream streamgage, and the calibrated model fit to estimated TDS concentrations at the downstream streamgage was reasonable. The greatest differences between simulated and estimated values occurred during drought periods from June 2000 to March 2003, May 2012 to June 2013, and October 2013 to October 2014, when simulated TDS concentrations in the river were greater than estimated concentrations. In general, simulated TDS mass flux to the river for the pre-PVU period is in good agreement with estimated values (2-percent difference), but the model overestimated TDS mass flux to the river by about 41 percent during the post-PVU period. The model uncertainty with respect to TDS mass flux to the river indicates other processes or model parameters not well represented by the model are affecting the system, especially during drought. During model calibration, the most sensitive parameters were identified as vertical hydraulic conductivity of the alluvial aquifer, conductance of the Dolores River streambed, ET extinction depth and rate, and recharge rate.
Five 5-year scenarios of conditions for 2021–25 were simulated to assist evaluation of alternative strategies to manage the discharge of brine into the Dolores River. The first scenario simulates no PVU pumping and serves as a base case for comparison to the other scenarios. Two scenarios simulate the effects of varying withdrawal timing at an annual rate about one-third less than during 2010 through 2018. During high-flow spring snowmelt runoff periods when brine discharge is naturally minimized, PVU pumping does not substantially affect salinity in the Dolores River, and comparison of these two scenarios indicates that scheduling brine withdrawals during times of low river stage is nearly as effective at reducing TDS mass flux to the river as pumping brine year-round. Cessation of pumping during periods of high river stage may be advantageous for system maintenance, brine injection, and seismic-risk reduction. The fourth scenario tested the effect of reducing irrigation-return flow on brine discharge and predicted a slight reduction of TDS mass flux to the Dolores River, but not as great a reduction as that of using the PVU to remove brine. The fifth scenario simulated 5 years of drought conditions without PVU pumping and indicates brine discharge during drought about 15 percent greater than during average hydrologic conditions. Results from scenario 5 are consistent with the calibrated model results and indicate that aquifer properties and ET processes and parameters may be affecting simulation results during drought.
The Paradox Valley groundwater model provides a reasonable overall match to observed conditions in the Dolores River. The model is useful for evaluating relative differences between brine management scenarios to inform PVU operational decisions and to identify gaps in data and process understanding. Representation of the brine source, hydraulic-conductivity parameters, and recharge and ET processes were identified as potential areas for additional field and modeling research. Additional research in the Paradox Valley might include field-data collection that provides additional information on the hydrogeologic framework, groundwater levels, groundwater TDS concentrations, stream characteristics, and aquifer properties. Additional modeling efforts could benefit from applying advanced tools for model development, calibration, and visualization including parameter-estimation and sensitivity analysis. Statistical evaluation of known model uncertainties such as hydraulic conductivity, streambed conductance, representations of the brine source, recharge, and ET could improve the match between simulated and estimated TDS mass flux from PVU pumping wells and to the Dolores River further informing model predictions and system understanding for the Paradox Valley.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245038","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Heywood, C.E., Paschke, S.S., Mast, M.A., and Watts, K.R., 2024, Simulation of groundwater flow and brine discharge to the Dolores River in the Paradox Valley, Montrose County, Colorado: U.S. Geological Survey Scientific Investigations Report 2024–5038, 47 p., https://doi.org/10.3133/sir20245038.","productDescription":"Report: viii, 47 p.; Data Release; 3 Databases","onlineOnly":"Y","ipdsId":"IP-130109","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":432768,"rank":6,"type":{"id":9,"text":"Database"},"url":"https://waterdata.usgs.gov/monitoring-location/09171100/all-graphs/#period=P7D","text":"USGS database site information —","linkHelpText":"USGS 09171100 Dolores River near Bedrock, CO, in USGS water data for the Nation: U.S. Geological Survey National Water Information System"},{"id":432764,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS database—","linkHelpText":"USGS water data for the Nation: U.S. Geological Survey National Water Information System"},{"id":432759,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5038/coverthb.jpg"},{"id":432763,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZW0FH5","text":"USGS data release","linkHelpText":"MODFLOW-6 model of variable-density groundwater flow and brine discharge to the Dolores River in the Paradox Valley, Colorado"},{"id":432766,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://waterdata.usgs.gov/monitoring-location/09169500/all-graphs/#period=P7D","text":"USGS database site information —","linkHelpText":"USGS 09169500 Dolores River at Bedrock, CO, in USGS water data for the Nation: U.S. Geological Survey National Water Information System"},{"id":432760,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5038/sir20245038.pdf","text":"Report","size":"9.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5038"},{"id":499462,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117219.htm","linkFileType":{"id":5,"text":"html"}},{"id":432769,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235094","text":"Hydrogeologic Conceptual Model of Groundwater Occurrence and Brine Discharge to the Dolores River in the Paradox Valley, Montrose County, Colorado"}],"country":"United States","state":"Colorado","county":"Montrose County","otherGeospatial":"Paradox Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.10372373203981,\n 38.51805273423872\n ],\n [\n -109.10372373203981,\n 38.1119253984173\n ],\n [\n -108.49529764389875,\n 38.1119253984173\n ],\n [\n -108.49529764389875,\n 38.51805273423872\n ],\n [\n -109.10372373203981,\n 38.51805273423872\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
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Salinity, or total dissolved solids (TDS), of the Colorado River is a major concern in the southwestern United States where the river provides water to about 40 million people for municipal and industrial use and is used to irrigate about 5.5 million acres of land. Much of the salinity in the Colorado River Basin is derived from natural interactions of surface water and groundwater with various geologic materials (rocks, soils, and alluvial deposits). The Dolores River in southwest Colorado is a major tributary of the Colorado River that historically accounts for about 6 percent of the salinity load to the Upper Colorado River Basin with the Paradox Valley being the primary source of salinity to the Dolores River. The Paradox Valley, one of several salt-anticline valleys in the region, is a fault-bounded topographic basin aligned with and exposing an underlying salt-anticline core. Salt deposits in the Pennsylvanian Paradox Formation of the Hermosa Group form an elongated salt diapir oriented northwest to southeast that is up to 12,000 feet (ft) thick beneath the present valley floor. Surface erosion, groundwater circulation, and weathering during Tertiary and Quaternary valley formation contributed to development of a cap rock, collapse features, breccia, and brine at the top of the exposed salt diapir. Today (2023), brine occurring in the brecciated cap rock and underlying salt deposits is in hydraulic connection with an overlying freshwater alluvial aquifer, and depending on seasonal river stage and hydrologic conditions, the brine discharges to the Dolores River causing the observed increase in salinity as the river crosses the Paradox Valley.
To reduce salinity concentrations in the Dolores River, the Bureau of Reclamation (Reclamation) operates the Paradox Valley Unit (PVU). The PVU project consists of nine shallow brine pumping wells near the Dolores River and one deep disposal well where the brine is injected for disposal. When operational, the PVU pumping wells extract brine from the base of the alluvial aquifer that is piped and injected into a deep disposal well about 3 miles southwest of the PVU. The PVU became fully operational July 1, 1996, and by 2015, operation of the PVU had reduced salinity concentrations in the Dolores River by as much as 70 percent compared to pre-PVU conditions. In response to a 4.5 magnitude earthquake, injection operations, and thus PVU pumping, were ceased from March 2019 to June 2022. A trial period of PVU operation began in June 2022 with a reduced injection rate, and thus PVU pumping rate, of about two-thirds capacity to gather additional information and guide future operational decisions.
In cooperation with Reclamation, the U.S. Geological Survey (USGS) developed this report to present the current (2023) understanding of groundwater and brine occurrence and discharge to the Dolores River in the Paradox Valley. Results from the compilation of spatial datasets, groundwater sampling and age dating, and aquifer tests are presented to provide improved understanding of the Paradox Valley hydrogeology, to supply datasets for a numerical groundwater-flow and brine-transport model, and to support future operations of the PVU. The hydrogeologic data provided herein, along with the most recent loading analysis for the Dolores River in the Paradox Valley, and a previous conceptual model for brine discharge to the river are used to present a conceptual understanding of groundwater occurrence in the Paradox Valley.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235094","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Paschke, S.S., Mast, M.A., Gardner, P.M., Newman, C.P., and Watts, K.R., 2024, Hydrogeologic conceptual model of groundwater occurrence and brine discharge to the Dolores River in the Paradox Valley, Montrose County, Colorado: U.S. Geological Survey Scientific Investigations Report 2023–5094, 58 p., https://doi.org/10.3133/sir20235094.","productDescription":"Report: x, 54 p.; 2 Data Releases; Database","onlineOnly":"Y","ipdsId":"IP-125569","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":432678,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20245038","text":"Simulation of Groundwater Flow and Brine Discharge to the Dolores River in the Paradox Valley, Montrose County, Colorado"},{"id":432677,"rank":6,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS database—","linkHelpText":"USGS water data for the nation: U.S. Geological Survey National Water Information System database"},{"id":432676,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CJQDDU","text":"USGS data release","linkHelpText":"Geospatial datasets developed for a hydrogeologic conceptual model of brine discharge to the Dolores River, Paradox Valley, Colorado"},{"id":432675,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NV5U6F","text":"USGS data release","linkHelpText":"Water-level and pumping data, water-level models, and estimated hydraulic properties for the Paradox Valley alluvial aquifer in Montrose County, Colorado, 2013"},{"id":432674,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FMWX2J","text":"USGS data release","linkHelpText":"Recharge temperatures and groundwater-age models for the Paradox Valley alluvial aquifer, 2011, Colorado"},{"id":432669,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5094/sir20235094.pdf","text":"Report","size":"9.23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5094"},{"id":499380,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117218.htm","linkFileType":{"id":5,"text":"html"}},{"id":432668,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5094/coverthb.jpg"}],"country":"United States","state":"Colorado","county":"Montrose County","otherGeospatial":"Paradox Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.23469392755278,\n 38.62004006715256\n ],\n [\n -109.23469392755278,\n 38.0400613431201\n ],\n [\n -108.48695698861,\n 38.0400613431201\n ],\n [\n -108.48695698861,\n 38.62004006715256\n ],\n [\n -109.23469392755278,\n 38.62004006715256\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
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Long-term wildlife research and monitoring programs strive to maintain consistent data collections and analytical methods. Incorporating new techniques is important but can render data sets incongruent and limit their potential to discern trends in demographic parameters. Integrated population models (IPMs) can address these limitations by combining data sources that may span different periods into a unified statistical framework while providing a holistic view of population dynamics. We developed an IPM in a Bayesian framework for grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem. We coupled demographic data with multiple, independent population count data to link annual changes in abundance with vital rates over 4 decades (1983–2023). Abundance increased threefold from an estimated 270 individuals in 1984 to 1030 individuals in 2023. Parameter estimates indicated survival of bears ≥2 years of age was high, contributing to robust population growth during the 1980s (λ = 1.023 [50 % interquartile range = 0.993–1.082]) and 1990s (λ = 1.064 [1.023–1.103]). A slowing of population growth started around 2000 (2000s: λ = 1.030 [0.989–1.068]) and continued into the 2010s (λ = 1.021 [0.985–1.057]), due primarily to reductions in survival of bears <2 years of age. These findings corroborate previous research that identified density-dependent effects as a likely cause. The IPM framework provided greater certainty and understanding regarding the dynamic demographic characteristics of the population and serves as a powerful monitoring tool for this long-lived species. Implementation of the IPM allows timely dissemination of demographic data to help inform adaptive management strategies and policy decisions necessary for the continued management and conservation of this population. This robust and flexible monitoring system allows scientists to investigate the effects of a changing ecosystem on population dynamics, incorporate new data sources and statistical models, and respond to changes in monitoring needs for the population. We highlight the efficacy of the IPM in estimating and tracking demographic parameters for a long-lived species, while accommodating shifts in monitoring techniques and data collections typical of long-term wildlife conservation programs worldwide.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2024.e03133","usgsCitation":"Gould, M.J., Clapp, J., Haroldson, M.A., Costello, C., Nowak, J.J., Martin, H., Ebinger, M., Bjornlie, D., Thompson, D., Dellinger, J.A., Mumma, M., Lukacs, P., and van Manen, F.T., 2024, A unified approach to long-term population monitoring of grizzly bears in the Greater Yellowstone Ecosystem: Global Ecology and Conservation, v. 54, e03133, 16 p., https://doi.org/10.1016/j.gecco.2024.e03133.","productDescription":"e03133, 16 p.","ipdsId":"IP-166249","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":466961,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2024.e03133","text":"Publisher Index Page"},{"id":432938,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Greater Yellowstone Ecosystem","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.19553511360566,\n 45.48126054576713\n ],\n [\n -112.23427309687703,\n 44.53619573717927\n ],\n [\n -110.92847041406486,\n 43.38122138835186\n ],\n [\n -109.24643599937531,\n 43.18040812667567\n ],\n [\n -109.13267230664917,\n 45.518110186630736\n ],\n [\n -112.19553511360566,\n 45.48126054576713\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"54","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gould, Matthew J.","contributorId":201504,"corporation":false,"usgs":false,"family":"Gould","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":911000,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clapp, Justin","contributorId":256932,"corporation":false,"usgs":false,"family":"Clapp","given":"Justin","email":"","affiliations":[{"id":36596,"text":"Wyoming Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":911001,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haroldson, Mark A. 0000-0002-7457-7676 mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":911002,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Costello, Cecily M.","contributorId":145510,"corporation":false,"usgs":false,"family":"Costello","given":"Cecily M.","affiliations":[{"id":5117,"text":"University of Montana, College of Forestry and Conservation, University Hall, Room 309, Missoula, MT 59812, USA","active":true,"usgs":false}],"preferred":false,"id":911003,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nowak, J. Joshua","contributorId":171707,"corporation":false,"usgs":false,"family":"Nowak","given":"J.","email":"","middleInitial":"Joshua","affiliations":[],"preferred":false,"id":911004,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Martin, Hans","contributorId":331216,"corporation":false,"usgs":false,"family":"Martin","given":"Hans","email":"","affiliations":[{"id":79153,"text":"Univ. of Minnesota, St. Paul, MN","active":true,"usgs":false}],"preferred":false,"id":911005,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ebinger, Michael","contributorId":300973,"corporation":false,"usgs":false,"family":"Ebinger","given":"Michael","affiliations":[{"id":35211,"text":"Montana Department of Fish, Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":911006,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bjornlie, Daniel D.","contributorId":145512,"corporation":false,"usgs":false,"family":"Bjornlie","given":"Daniel D.","affiliations":[{"id":16140,"text":"Wyoming Game & Fish Department, Large Carnivore Section, Lander, Wyoming 82520, USA","active":true,"usgs":false}],"preferred":false,"id":911007,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Thompson, Daniel","contributorId":225736,"corporation":false,"usgs":false,"family":"Thompson","given":"Daniel","affiliations":[{"id":13584,"text":"Natural Resources Canada, Canadian Forest Service","active":true,"usgs":false}],"preferred":false,"id":911008,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dellinger, Justin A.","contributorId":190532,"corporation":false,"usgs":false,"family":"Dellinger","given":"Justin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":911009,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mumma, Matthew A.","contributorId":202351,"corporation":false,"usgs":false,"family":"Mumma","given":"Matthew","middleInitial":"A.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":911010,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lukacs, Paul","contributorId":189208,"corporation":false,"usgs":false,"family":"Lukacs","given":"Paul","affiliations":[],"preferred":false,"id":911011,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":911012,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70259350,"text":"70259350 - 2024 - Skill assessment of a total water level and coastal change forecast during the landfall of a hurricane","interactions":[],"lastModifiedDate":"2024-10-04T14:11:40.777116","indexId":"70259350","displayToPublicDate":"2024-08-19T09:07:37","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Skill assessment of a total water level and coastal change forecast during the landfall of a hurricane","docAbstract":"The Total Water Level and Coastal Change Forecast (TWL&CC Forecast) provides coastal communities with 6-day notice of potential elevated water levels and coastal change (i.e., dune erosion, overwash, or inundation) on sandy beaches that threatens safety, infrastructure, or resources. This continuously operating model provides hourly information for select regions along U.S. Gulf of Mexico and Atlantic Ocean coastlines. The objective of this work is to assess the skill of forecasts during a period of elevated water levels along the coasts of North Carolina (NC) and South Carolina, USA caused by Hurricane Isaias in August 2020, using a combination of observations and model hindcasts. Water levels and waves were observed throughout the storm at three locations near Wrightsville Beach, NC, which provided information to assess forecast skill; a wave buoy offshore, a tide gage at a local pier, and a pressure sensor deployed at the pier. In addition to observations, the non-hydrostatic phase-resolving model SWASH (Simulating WAves till SHore) was forced with hourly wave energy spectra derived from a coupled Delft3D-SWAN simulation during the peak of Isaias, to complement observations by computing nearshore wave height and wave-induced setup and runup at the shoreline. During the storm peak, SWASH-simulated water levels at the sensor position were comparable to those at the maximum landward extent (bias = −0.05 m; gain = 0.26; r2 = 0.99), suggesting that observations at the USGS sensor location were a useful proxy for total water level (TWL; sum of tide, surge and wave runup) at the shoreline that are predicted by the TWL&CC Forecast. The TWL forecast at Wrightsville Beach was consistent with observations from the USGS sensor (bias = −0.38 m and −0.74 m, scatter index = 0.22 and 0.28 for the two forecast model grids considered, respectively; weighted regression considering model uncertainty explained 95 percent of variability in observed TWL). Observed TWL was within the confidence interval of the TWL&CC Forecast for the 5 h at the storm peak. Forecast mean water levels (MWL; sum of tide, surge and wave setup) and tide gage observations were also consistent (bias = 0.07 m and 0.02 m for the forecast model grids; scatter index = 0.46; r2 = 0.80). Forecast MWL at the storm peak was within 0.06 m of the observed MWL from the tide gage for both sites. In the region where Isaias made landfall, eight additional pressure sensors were compared to the peak TWL forecast (bias = 0.14 m; scatter index = 0.18). Forecast TWL explained 90 percent of observed variability in TWL when considering uncertainty of the forecast with a weighted regression. The results demonstrate that wave-driven water levels contributed a significant portion of the forecast TWL during Isaias (52 percent during the three peak hours of the storm), and that TWL were represented using the forecast model. Mean absolute error of the coastal change forecast and observed overwash is 0.4 and 0.14 for the two forecast model grids considered. The skill demonstrated by this computationally efficient method indicates that the forecasting system can provide fast and reliable predictions of TWL across hundreds of km of coastline at sub-km resolution, days to hours in advance of when storms threaten coastal regions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coastaleng.2024.104590","usgsCitation":"Birchler, J.J., Palmsten, M.L., Doran, K., Karwandyar, S., Pardun, J.M., Oades, E.M., Mulligan, R.P., and Whitehead-Zimmers, E.S., 2024, Skill assessment of a total water level and coastal change forecast during the landfall of a hurricane: Coastal Engineering, v. 193, 104590, 19 p., https://doi.org/10.1016/j.coastaleng.2024.104590.","productDescription":"104590, 19 p.","ipdsId":"IP-154794","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466962,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coastaleng.2024.104590","text":"Publisher Index Page"},{"id":462596,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"193","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Birchler, Justin J. 0000-0002-0379-2192 jbirchler@usgs.gov","orcid":"https://orcid.org/0000-0002-0379-2192","contributorId":169117,"corporation":false,"usgs":true,"family":"Birchler","given":"Justin","email":"jbirchler@usgs.gov","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":915007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palmsten, Margaret L. 0000-0002-6424-2338","orcid":"https://orcid.org/0000-0002-6424-2338","contributorId":239955,"corporation":false,"usgs":true,"family":"Palmsten","given":"Margaret","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":915008,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doran, Kara S. 0000-0001-8050-5727","orcid":"https://orcid.org/0000-0001-8050-5727","contributorId":292448,"corporation":false,"usgs":true,"family":"Doran","given":"Kara S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":915009,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Karwandyar, Sharifa 0000-0002-1531-2360","orcid":"https://orcid.org/0000-0002-1531-2360","contributorId":343816,"corporation":false,"usgs":false,"family":"Karwandyar","given":"Sharifa","email":"","affiliations":[{"id":82201,"text":"Department of Earth Sciences, Binghamton University","active":true,"usgs":false}],"preferred":false,"id":915010,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pardun, Joshua Michael 0000-0003-4633-3970","orcid":"https://orcid.org/0000-0003-4633-3970","contributorId":335148,"corporation":false,"usgs":true,"family":"Pardun","given":"Joshua","email":"","middleInitial":"Michael","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":915011,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Oades, Elora M.","contributorId":343817,"corporation":false,"usgs":false,"family":"Oades","given":"Elora","email":"","middleInitial":"M.","affiliations":[{"id":82202,"text":"Department of Civil Engineering, Queen’s University","active":true,"usgs":false}],"preferred":false,"id":915012,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mulligan, Ryan P.","contributorId":194423,"corporation":false,"usgs":false,"family":"Mulligan","given":"Ryan","email":"","middleInitial":"P.","affiliations":[{"id":35723,"text":"Queen's University - Kingston, Ontario","active":true,"usgs":false}],"preferred":false,"id":915013,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Whitehead-Zimmers, Eli Sawyer 0000-0002-8925-3498","orcid":"https://orcid.org/0000-0002-8925-3498","contributorId":339930,"corporation":false,"usgs":true,"family":"Whitehead-Zimmers","given":"Eli","email":"","middleInitial":"Sawyer","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":915014,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70259302,"text":"70259302 - 2024 - Crystal resorption as a driver for mush maturation: An experimental investigation","interactions":[],"lastModifiedDate":"2024-10-03T13:53:03.53727","indexId":"70259302","displayToPublicDate":"2024-08-19T08:47:13","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2420,"text":"Journal of Petrology","active":true,"publicationSubtype":{"id":10}},"title":"Crystal resorption as a driver for mush maturation: An experimental investigation","docAbstract":"The thermal state of a magma reservoir controls its physical and rheological properties: at storage temperatures close to the liquidus, magmas are dominated by melt and therefore mobile, while at lower temperatures, magmas are stored as a rheologically locked crystal network with interstitial melt (crystal mush). Throughout the lifetime of a magmatic system, temperature fluctuations drive transitions between mush-dominated and melt-dominated conditions. For example, magma underplating or magma recharge into a crystal mush supplies heat, leading to mush disaggregation and an increase in melt fraction via crystal resorption, before subsequent cooling reinstates a crystal mush via crystal accumulation and recrystallisation. Here, we examine the textural effects of such temperature-driven mush reprocessing cycles on the crystal cargo. We conducted high-P-T resorption experiments during which we nucleated, grew, resorbed, and recrystallised plagioclase crystals in a rhyolitic melt, imposing temperature fluctuations typical for plumbing systems in intermediate arc volcanoes (20–40 °C). The experiments reproduce common resorption textures and show that plagioclase dissolution irreversibly reduces 3D crystal aspect ratios, leading to more equant shapes. Comparison of our experimental results with morphologies of resorbed and unresorbed plagioclase crystals from Mount St. Helens (MSH) (USA) reveals a consistent trend in natural rocks: unresorbed plagioclase crystals (found in MSH dacite, basalt and quenched magmatic inclusions [QMIs]) have tabular shapes, while plagioclase crystals with one or more resorption horizons (found in MSH dacite, QMIs, and mush inclusions) show more equant shapes. Plagioclase crystals showing pervasive resorption (found in the dacite and mush inclusions) have even lower aspect ratios. We therefore suggest that crystal mush maturation results in progressively more equant crystal shapes: the shapes of plagioclase crystals in a magma reservoir will become less tabular every time they are remobilised and resorbed. This has implications for magma rheology and, ultimately, eruptibility, as crystal shape controls the maximum packing fraction and permeability of a crystal mush. We hypothesise that a mature mush with more equant crystals due to multiple resorption–recrystallisation events will be more readily remobilised than an immature mush comprising unresorbed, tabular crystals. This implies that volcanic behaviour and pre-eruptive magmatic timescales may vary systematically during thermal maturation of a crustal magmatic system, with large eruptions due to rapid wholesale remobilisation of mushy reservoirs being more likely in thermally mature systems.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/petrology/egae088","usgsCitation":"Mangler, M.F., Humphreys, M.C., Iveson, A.A., Cooper, K.M., Clynne, M.A., Lindoo, A., Brooker, R.A., and Wadsworth, F.B., 2024, Crystal resorption as a driver for mush maturation: An experimental investigation: Journal of Petrology, v. 65, no. 9, egae088, 23 p., https://doi.org/10.1093/petrology/egae088.","productDescription":"egae088, 23 p.","ipdsId":"IP-160202","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":466963,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/petrology/egae088","text":"Publisher Index Page"},{"id":462532,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.31914874888618,\n 46.31454908454265\n ],\n [\n -122.31914874888618,\n 46.087541612133066\n ],\n [\n -122.05239446980664,\n 46.087541612133066\n ],\n [\n -122.05239446980664,\n 46.31454908454265\n ],\n [\n -122.31914874888618,\n 46.31454908454265\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"65","issue":"9","noUsgsAuthors":false,"publicationDate":"2024-08-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Mangler, Martin F.","contributorId":344829,"corporation":false,"usgs":false,"family":"Mangler","given":"Martin","email":"","middleInitial":"F.","affiliations":[{"id":37954,"text":"University of Durham","active":true,"usgs":false}],"preferred":false,"id":914838,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Humphreys, Madeleine C.S.","contributorId":344830,"corporation":false,"usgs":false,"family":"Humphreys","given":"Madeleine","email":"","middleInitial":"C.S.","affiliations":[{"id":37954,"text":"University of Durham","active":true,"usgs":false}],"preferred":false,"id":914839,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iveson, Alexander A.","contributorId":344831,"corporation":false,"usgs":false,"family":"Iveson","given":"Alexander","email":"","middleInitial":"A.","affiliations":[{"id":37954,"text":"University of Durham","active":true,"usgs":false}],"preferred":false,"id":914840,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cooper, Kari M.","contributorId":32814,"corporation":false,"usgs":true,"family":"Cooper","given":"Kari","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":914841,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clynne, Michael A. 0000-0002-4220-2968 mclynne@usgs.gov","orcid":"https://orcid.org/0000-0002-4220-2968","contributorId":2032,"corporation":false,"usgs":true,"family":"Clynne","given":"Michael","email":"mclynne@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":914842,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lindoo, Amanda","contributorId":344833,"corporation":false,"usgs":false,"family":"Lindoo","given":"Amanda","email":"","affiliations":[{"id":37954,"text":"University of Durham","active":true,"usgs":false}],"preferred":false,"id":914843,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brooker, Richard A.","contributorId":344834,"corporation":false,"usgs":false,"family":"Brooker","given":"Richard","email":"","middleInitial":"A.","affiliations":[{"id":37322,"text":"University of Bristol","active":true,"usgs":false}],"preferred":false,"id":914844,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wadsworth, Fabian B.","contributorId":344835,"corporation":false,"usgs":false,"family":"Wadsworth","given":"Fabian","email":"","middleInitial":"B.","affiliations":[{"id":37954,"text":"University of Durham","active":true,"usgs":false}],"preferred":false,"id":914845,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70263708,"text":"70263708 - 2024 - Combined high rates of alternative breeding strategies unexpectedly found among populations of a solitary nesting raptor","interactions":[],"lastModifiedDate":"2025-02-20T15:11:38.678929","indexId":"70263708","displayToPublicDate":"2024-08-19T08:02:32","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Combined high rates of alternative breeding strategies unexpectedly found among populations of a solitary nesting raptor","docAbstract":"Social monogamy is the prevalent mating system in birds, but alternative strategies of extra-pair paternity (EPP) and conspecific brood parasitism (CBP) occur in many species. Raptors are virtually absent in discussions of broad taxonomic reviews regarding EPP and CBP likely because these strategies are mostly absent or at low frequency; CBP is unreported in solitary nesting raptors. In contrast, we found high frequencies of EPP (16%–31%) and CBP (15%–26%) nests among three populations of Cooper's Hawks (Accipiter cooperii) across the northern breeding range of this solitary nesting, socially monogamous species. EPP and CBP combined occurred in 42%–46% of all nests among populations and hence unexpectedly were nearly equivalent to proportions of genetically monogamous nests. Select covariates failed to predict presence of EPP and CBP in part because virtually all extra-pair adults were uncaught and likely were floaters. We found no support for the hypothesis that territorial females traded copulations for food to maximize energy intake for increased production. Our unique discoveries enhance knowledge of the extent and diversity of alternative breeding strategies among groups of avian and other animal species.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.70190","usgsCitation":"Rosenfield, R., Sonsthagen, S.A., Stout, W., Driscoll, T., Stewart, A., Frater, P., and Talbot, S., 2024, Combined high rates of alternative breeding strategies unexpectedly found among populations of a solitary nesting raptor: Ecology and Evolution, v. 14, no. 8, e70190, 9 p., https://doi.org/10.1002/ece3.70190.","productDescription":"e70190, 9 p.","ipdsId":"IP-149699","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":489767,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.70190","text":"Publisher Index Page"},{"id":482262,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"North Dakota, Wisconsin","otherGeospatial":"British Columbia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.66224579513528,\n 49.37114703992023\n ],\n [\n -125.48971420547437,\n 48.284658555794834\n ],\n [\n -121.31263679596735,\n 48.60975116618848\n ],\n [\n -116.37609510458793,\n 48.68924899033392\n ],\n [\n -107.02814048290524,\n 48.85432609532998\n ],\n [\n -96.76874442980454,\n 47.85799909171628\n ],\n [\n -92.81284802493039,\n 47.91251881339643\n ],\n [\n -89.69747094218953,\n 44.8122732296117\n ],\n [\n -87.86765163336594,\n 44.56188562271629\n ],\n [\n -89.14175605692945,\n 45.72958527706788\n ],\n [\n -90.69478565475457,\n 47.96759369541124\n ],\n [\n -107.17242393479384,\n 49.61248906532754\n ],\n [\n -124.66224579513528,\n 49.37114703992023\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"8","noUsgsAuthors":false,"publicationDate":"2024-08-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Rosenfield, Robert N.","contributorId":351110,"corporation":false,"usgs":false,"family":"Rosenfield","given":"Robert N.","affiliations":[{"id":17717,"text":"University of Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":927909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874 ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":927910,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stout, William E.","contributorId":351111,"corporation":false,"usgs":false,"family":"Stout","given":"William E.","affiliations":[{"id":83921,"text":"Oconomowoc","active":true,"usgs":false}],"preferred":false,"id":927911,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Driscoll, Timothy G.","contributorId":351112,"corporation":false,"usgs":false,"family":"Driscoll","given":"Timothy G.","affiliations":[{"id":13256,"text":"Urban Raptor Research Project","active":true,"usgs":false}],"preferred":false,"id":927912,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stewart, Andrew C.","contributorId":351113,"corporation":false,"usgs":false,"family":"Stewart","given":"Andrew C.","affiliations":[{"id":83922,"text":"Cobble Hill, British Columbia, Canada","active":true,"usgs":false}],"preferred":false,"id":927913,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Frater, Paul N.","contributorId":351114,"corporation":false,"usgs":false,"family":"Frater","given":"Paul N.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":927914,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Talbot, Sandra L.","contributorId":351115,"corporation":false,"usgs":false,"family":"Talbot","given":"Sandra L.","affiliations":[{"id":83923,"text":"Northwestern Institute of Art and Science","active":true,"usgs":false}],"preferred":false,"id":927915,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70259413,"text":"70259413 - 2024 - Predicting the effects of solar energy development on plants and wildlife in the Desert Southwest, United States","interactions":[],"lastModifiedDate":"2024-10-07T11:46:49.220695","indexId":"70259413","displayToPublicDate":"2024-08-19T06:45:12","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18738,"text":"Renewable & Sustainable Energy Reviews (RSER)","active":true,"publicationSubtype":{"id":10}},"title":"Predicting the effects of solar energy development on plants and wildlife in the Desert Southwest, United States","docAbstract":"With the intensity and frequency of wildfires increasing rapidly, the need to study the ecological effects of these wildfires is also growing. An understudied aspect of fire ecology is the effect fires have on parasite–host interactions, including ectoparasites that might be pathogen vectors. Although some studies have examined the impacts of fire on ticks, studies on other ectoparasites, including pathogen vectors, are rare. To help address this knowledge gap, we examined the abiotic and biotic factors that predict the likelihood and extent of parasitism of deer mice (Peromyscus maniculatus) by fleas within a landscape of unburned and recovering burned (>9 yr postfire) mixed conifer forests. We sampled 227 individual deer mice across 27 sites within the Jemez Mountains of northern New Mexico in 2022 and quantified measures of parasitism by fleas (primarily Aetheca wagneri). These sites were distributed in both unburned areas (n = 15) and recovering burned areas (n = 12), with the latter derived from 2 large fires, the Las Conchas fire (2011) and the Thompson Ridge fire (2013). Using these data, we tested for differences in prevalence, mean abundance, and mean intensity of fleas on deer mice, focusing on the predictive importance of host sex and fire history. We also created generalized linear mixed-effects models to investigate the best host and environmental predictors of parasitism by fleas. Approximately a decade postfire, we found minimal evidence to suggest that fire history influenced either the presence or intensity of fleas on deer mice. Rather, at the current forest-regeneration stage, the extent of parasitism by fleas was best predicted by measures of host sex, body condition, and the trapline's ability to accumulate water, as measured through topography. As host body condition increased, the probability of males being parasitized increased, whereas the opposite pattern was seen for females. Male mice also had significantly greater flea loads. Among potential abiotic predictors, the topographic wetness index or compound topographic index (a proxy for soil moisture) was positively related to flea intensity, suggesting larger flea populations in burrows with higher relative humidity. In summary, although fire may potentially have short-term impacts on the likelihood and extent of host parasitism by fleas, in this recovering study system, host characteristics and topographic wetness index are the primary predictors of parasitism by fleas.
","language":"English","publisher":"BioOne","doi":"10.1645/23-45","usgsCitation":"Padilla, C., Martin, J., Cain, J.W., and Gompper, M., 2024, Abiotic and demographic drivers of flea parasitism on deer mice in a recovering mixed-conifer forest a decade postfire: Journal of Parasitology, v. 110, no. 4, p. 375-385, https://doi.org/10.1645/23-45.","productDescription":"11 p.","startPage":"375","endPage":"385","ipdsId":"IP-153592","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":485844,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Jemez Ranger District of Santa Fe National Forest, Valles Caldera National Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.30445858820687,\n 36.653454747968524\n ],\n [\n -107.30445858820687,\n 35.654968715553636\n ],\n [\n -105.9993414935517,\n 35.654968715553636\n ],\n [\n -105.9993414935517,\n 36.653454747968524\n ],\n [\n -107.30445858820687,\n 36.653454747968524\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"110","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Padilla, Colton J.","contributorId":353982,"corporation":false,"usgs":false,"family":"Padilla","given":"Colton J.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":936849,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Jessica T.","contributorId":355088,"corporation":false,"usgs":false,"family":"Martin","given":"Jessica T.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":936850,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cain, James W. 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Due to the prolonged time required to reach maturity, estimates of tree maturation size remain unavailable and we lack a global view on the generality and the shape of this trade-off. Using seed production from five continents, we estimate tree maturation sizes for 486 tree pecies spanning tropical to boreal climates. Results show that a species’ maturation size increases with maximum size, but in a non-proportional way: the largest species begin reproduction at smaller sizes than would be expected if maturation size were simply proportional to maximum size. Furthermore, the decrease in relative maturation size is steepest in cold climates. 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systems past and present. However, timescale differences of water isotope inputs to proxy systems and the signal embedded in long paleorecords often
confound translation to observed hydroclimatic metrics. Here, a unique 20-year dataset of meteorology, hydrology, and the isotopic composition of
weekly meteoric and surface water samples (δ18O, δ2 H) are combined with paleoclimate δ18O data from tree-ring cellulose and lake carbonate to better
understand proxy signals of Upper Colorado river basin drought. Annual tree-ring cellulose δ18O from Picea engelmannii growing within a glacier-fed creek
and a spring discharge area were used to derive annual source water δ18O using a cellulose source-water isotope model. Comparisons with the monitoring
record indicates that tree-ring cellulose δ18O tracks variations in wet and dry hydroclimatic extremes. Source water isotopes are shown to reflect the
hydroclimate of the current year and some number of previous years as an effective moisture-discharge proxy rather than a precipitation isotope proxy.
Results contextualize Holocene lake carbonate δ18O data. The contemporary-to-paleo comparison identifies changes in seasonal precipitation extremes
during recent millennia and several earlier arid and monsoon-dominated Holocene periods that exceed the arid maximum of the calibration period.
Broad infestations of invasive, non-native vegetation have transformed wetlands around the world. Ludwigia hexapetala is a widespread, amphibious invasive plant with a creeping growth habit in open water and an erect growth habit in terrestrial habitats. In the upper San Francisco Estuary of California, L. hexapetala is increasingly terrestrializing into marshes and this expansion may be facilitated by allelopathy. We conducted the first field-based study on L. hexapetala allelopathy to determine whether (1) three allelochemicals known to be exuded by L. hexapetala are expressed in situ, (2) the allelochemicals are detectable in leaves, soil, and water, and (3) allelopathic expression varies by season, salinity, and growth habit (open water “patch” vs. terrestrial marsh “interface” locations). Water, soil, and L. hexapetala leaves were collected in two freshwater sites and two oligohaline sites in the upper San Francisco Estuary in summer 2021, fall 2021, and spring 2022. Myricitrin and quercitrin, known allelochemicals, and salipurposid, a newly identified polyphenol, were detected in water, soil, and leaves. There were significant differences in allelochemical concentrations under fresh versus oligohaline conditions in water and soil, but not leaves. All three allelochemicals generally had higher concentrations in patch versus interface locations, suggesting that L. hexapetala allelopathy plays a greater competitive role in open water than terrestrial habitats. Leaf concentrations of each allelochemical varied seasonally; however, both myricitrin and salipurposid had heightened concentrations in spring. These results suggest that herbicide application in early spring may be most effective in controlling L. hexapetala terrestrialization from open water to marshes.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-024-03412-4","usgsCitation":"Drexler, J.Z., Gross, M., Hladik, M.L., Morrison, B., and Hestir, E., 2024, In situ allelopathic expression by the invasive amphibious plant, Ludwigia hexapetala (water primrose) across habitat types, seasons, and salinities: Biological Invasions, v. 26, p. 3811-3828, https://doi.org/10.1007/s10530-024-03412-4.","productDescription":"18 p.","startPage":"3811","endPage":"3828","ipdsId":"IP-160888","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":432937,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.89839069902723,\n 38.06121335326662\n ],\n [\n -120.11889157934385,\n 36.328833706314626\n ],\n [\n -119.45382625178553,\n 37.03516328439403\n ],\n [\n -121.50294770892147,\n 40.68679922497094\n ],\n [\n -122.32978568372388,\n 40.63907726889312\n ],\n [\n -122.2668740986846,\n 39.26816562329512\n ],\n [\n -121.89839069902723,\n 38.06121335326662\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"26","noUsgsAuthors":false,"publicationDate":"2024-08-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":167492,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith","email":"jdrexler@usgs.gov","middleInitial":"Z.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":910993,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gross, Michael 0000-0002-2433-166X","orcid":"https://orcid.org/0000-0002-2433-166X","contributorId":343411,"corporation":false,"usgs":false,"family":"Gross","given":"Michael","affiliations":[{"id":81579,"text":"California Department of Food and Agriculture","active":true,"usgs":false}],"preferred":false,"id":910994,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":221087,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":910995,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morrison, Bailey 0000-0001-5824-8605","orcid":"https://orcid.org/0000-0001-5824-8605","contributorId":343414,"corporation":false,"usgs":false,"family":"Morrison","given":"Bailey","email":"","affiliations":[{"id":54780,"text":"UC Merced","active":true,"usgs":false}],"preferred":false,"id":910996,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hestir, Erin","contributorId":343417,"corporation":false,"usgs":false,"family":"Hestir","given":"Erin","affiliations":[{"id":54780,"text":"UC Merced","active":true,"usgs":false}],"preferred":false,"id":910997,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70258722,"text":"70258722 - 2024 - Global assessment of aquatic Isoëtes species ecology","interactions":[],"lastModifiedDate":"2024-09-25T12:06:12.189538","indexId":"70258722","displayToPublicDate":"2024-08-17T07:00:12","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Global assessment of aquatic Isoëtes species ecology","docAbstract":"A Decree of the Supreme Court of the United States, entered June 7, 1954 (New Jersey v. New York, 347 U.S. 995), established the position of Delaware River Master within the U.S. Geological Survey. In addition, the Decree authorizes the diversion of water from the Delaware River Basin and requires compensating releases from certain reservoirs owned by New York City be made under the supervision and direction of the River Master. The Decree stipulates that the River Master provide reports to the Court, not less frequently than annually. This report is the 64th annual report of the River Master of the Delaware River. The report covers the 2017 River Master report year, from December 1, 2016, to November 30, 2017.
During the report year, precipitation in the upper Delaware River Basin was 47.85 inches or 108 percent of the long-term average. On December 1, 2016, combined useable storage in the New York City reservoirs in the upper Delaware River Basin was 110.115 billion gallons or 40.7 percent of combined storage capacity, the lowest combined storage of the 2017 report year. The reservoirs were at about 100 percent of useable capacity on May 31, 2017. Combined storage remained above 80 percent of combined capacity until September 2017.
A lower basin drought watch issued by the Delaware River Basin Commission in 2016 extended from the beginning of this report year to January 18, 2017. The drought watch was ended on January 18, 2017, due to increased precipitation in December 2016. River Master operations during the year were conducted as stipulated by the Decree and the Flexible Flow Management Programs.
Diversions from the Delaware River Basin by New York City and New Jersey fully complied with the Decree. Reservoir releases were made as directed by the River Master at rates designed to meet the flow objective for the Delaware River at Montague, New Jersey (N.J.), on 52 days during the report year. Interim Excess Release Quantity and conservation releases, designed to relieve thermal stress and protect the fishery and aquatic habitat in the tailwaters of the reservoirs, were made during the report year. Excess Release Quantity and Interim Excess Release Quantity Bank releases were also made during the report year.
The water quality in the Delaware River estuary between the streamgages at Trenton, N.J., and Reedy Island Jetty, Delaware, was monitored at various locations. The data on water temperature, specific conductance, dissolved oxygen, and pH were collected continuously by electronic instruments at four sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241022","isbn":"978-1-4113-4580-5","usgsCitation":"Russell, K.L., Andrews, W.J., DiFrenna, V.J., Norris, J.M., and Mason, R.R., Jr., 2024, Report of the River Master of the Delaware River for the period December 1, 2016–November 30, 2017: U.S. Geological Survey Open-File Report 2024–1022, 109 p., https://doi.org/10.3133/ofr20241022.","productDescription":"xi, 109 p.","numberOfPages":"109","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-153026","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"links":[{"id":499249,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117174.htm","linkFileType":{"id":5,"text":"html"}},{"id":432667,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1022/images/"},{"id":432666,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1022/ofr20241022.XML","description":"OFR 2024-1022 XML"},{"id":432665,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241022/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1022 HTML"},{"id":432664,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1022/ofr20241022.pdf","text":"Report","size":"10.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1022 PDF"},{"id":432663,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1022/coverthb.jpg"}],"country":"United States","state":"New Jersey, New York, Pennsylvania","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76,\n 43\n ],\n [\n -76,\n 39.31354002356349\n ],\n [\n -74,\n 39.31354002356349\n ],\n [\n -74,\n 43\n ],\n [\n -76,\n 43\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Delaware River Master
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The U.S. Geological Survey (USGS)‐operated ShakeAlert® system is the United States West Coast earthquake early warning system (Given et al., 2018). In this study we detail ShakeAlert’s performance during some of the largest events seen by the system thus far. Statewide public alerting using ShakeAlert messages was authorized in California in October 2019. Over the next few years, public alerts were expanded into Oregon and then into Washington (U.S. Geological Survey, 2024). ShakeAlert source results are routinely compared to the USGS Comprehensive Catalog (ComCat; Guy et al., 2015; U.S. Geological Survey, Earthquake Hazards Program, 2017), which contains the earthquake location and magnitude determined using complete waveform data. M 4.5 and larger is the threshold used for public alerting and was deliberately set below the level where damage is likely to compensate for cases where the system underestimates the magnitude. Between 17 October 2019 and 1 September 2023, the ShakeAlert system created 95 events with maximum magnitude estimates of M ≥4.5, the public alerting threshold. 94 of the 95 events were due to real earthquakes. Seven were categorized “false” per ShakeAlert’s internal definition that there was no matching catalog event within 100 km and 30 s of origin time; however, all but one of these were real earthquakes that were poorly located, primarily because they were at the edges of the seismic network. Three detected events were labeled “missed” because they were very poorly located (>100 km location error). In addition, the system did not produce solutions for four ComCat events M ≥4.5 (U.S. Geological Survey, Earthquake Hazards Program, 2017), which were all at the edge of the alerting and network boundaries. The ShakeAlert system has accurately detected the majority of earthquakes that have occurred within the operational region since completing the public rollout, and alerts from the system have been delivered to millions of cell phone users throughout the West Coast.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120230259","usgsCitation":"Lux, A., Smith, D., Böse, M., McGuire, J., Saunders, J., Huynh, M., Stubailo, I., Andrews, J.R., Lotto, G., Crowell, B., Crane, S., Allen, R.M., Given, D.D., Hartog, R., Heaton, T., Husker, A., Marty, J., O'Driscoll, L., Tobin, H.J., McBride, S.K., and Toomey, D., 2024, Status and performance of the ShakeAlert® earthquake early warning system: 2019-2023: Bulletin of the Seismological Society of America, v. 114, no. 6, p. 3041-3062, https://doi.org/10.1785/0120230259.","productDescription":"22 p.","startPage":"3041","endPage":"3062","ipdsId":"IP-158989","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":481878,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, 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2024 - Spatial variability of water temperature within the White River basin, Mount Rainier National Park Washington","interactions":[{"subject":{"id":70257569,"text":"70257569 - 2024 - Spatial variability of water temperature within the White River basin, Mount Rainier National Park Washington","indexId":"70257569","publicationYear":"2024","noYear":false,"title":"Spatial variability of water temperature within the White River basin, Mount Rainier National Park Washington"},"predicate":"SUPERSEDED_BY","object":{"id":70265982,"text":"sir20255029 - 2025 - Spatial stream network modeling of water temperature within the White River Basin, Mount Rainier National Park, Washington","indexId":"sir20255029","publicationYear":"2025","noYear":false,"title":"Spatial stream network modeling of water temperature within the White River Basin, Mount Rainier National Park, Washington"},"id":1}],"supersededBy":{"id":70265982,"text":"sir20255029 - 2025 - Spatial stream network modeling of water temperature within the White River Basin, Mount Rainier National Park, Washington","indexId":"sir20255029","publicationYear":"2025","noYear":false,"title":"Spatial stream network modeling of water temperature within the White River Basin, Mount Rainier National Park, Washington"},"lastModifiedDate":"2025-04-28T15:40:31.008668","indexId":"70257569","displayToPublicDate":"2024-08-16T10:22:40","publicationYear":"2024","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":18346,"text":"EarthArXiv","active":true,"publicationSubtype":{"id":32}},"title":"Spatial variability of water temperature within the White River basin, Mount Rainier National Park Washington","docAbstract":"Water temperature is a primary control on the occurrence and distribution of cold-water species. Rivers draining Mount Rainier in western Washington, including the White River along its northern flank, support several cold-water fish populations, but the spatial distribution of water temperatures, particularly during late-summer base flow between August and September, and the climatic, hydrologic, and physical processes regulating this temperature distribution are not well understood. Spatial stream network (SSN) models, which are generalized linear models that incorporate streamwise spatial autocovariance structures, were fit to mean and seven-day average daily maximum water temperature for August and September for the White River basin located with Mount Rainier National Park. The SSN models were calibrated using water temperature measurements collected between 2010 and 2020. Significant covariates within the best-fit models included the proportion of ice cover and forest cover within the basin, mean August air temperature, the proportion of consolidated geologic units, and snow water equivalent. Statistical models that included spatial autocovariance structures had better predictive performance than those that did not. In addition, models of mean August and September water temperature had better predictive performance than those of seven-day average daily maximum temperature in August and September. Predictions of the spatial distribution of water temperature were similar between August and September with a general warming in the downstream part of main-stem White River compared to cooler water temperatures in the high-elevation headwater streams. Estimated water temperatures for the upper White River model are three to four degrees Celsius warmer for tributaries but one to two degrees cooler for the main stem compared to the regional-scale model. Differences between the upper White River SSN model and the regional-scale SSN model are attributed the upper White River SSN including water temperature observations specific to the upper White River, whereas water temperature observations from lower elevation streams and downstream of the Mount Rainer National Park boundary were used in the regional-scale model.
","language":"English","publisher":"EarthArXiv","doi":"10.31223/X5712P","usgsCitation":"Gendaszek, A., Leach, A.C., and Jaeger, K.L., 2024, Spatial variability of water temperature within the White River basin, Mount Rainier National Park Washington: EarthArXiv, https://doi.org/10.31223/X5712P.","productDescription":"33 p.","ipdsId":"IP-166723","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":433007,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":439208,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.31223/x5712p","text":"External Repository"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gendaszek, Andrew S. 0000-0002-2373-8986","orcid":"https://orcid.org/0000-0002-2373-8986","contributorId":343378,"corporation":false,"usgs":false,"family":"Gendaszek","given":"Andrew","middleInitial":"S.","affiliations":[{"id":82076,"text":"King County","active":true,"usgs":false}],"preferred":false,"id":910876,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leach, Anya Clare 0000-0001-7828-8858","orcid":"https://orcid.org/0000-0001-7828-8858","contributorId":339960,"corporation":false,"usgs":true,"family":"Leach","given":"Anya","email":"","middleInitial":"Clare","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":910877,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jaeger, Kristin L. 0000-0002-1209-8506","orcid":"https://orcid.org/0000-0002-1209-8506","contributorId":206935,"corporation":false,"usgs":true,"family":"Jaeger","given":"Kristin","middleInitial":"L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":910878,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70257561,"text":"70257561 - 2024 - Simulated sea level rise in coastal peat oils stimulates mercury methylation","interactions":[],"lastModifiedDate":"2024-09-23T16:20:31.643081","indexId":"70257561","displayToPublicDate":"2024-08-16T08:36:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5615,"text":"ACS Earth and Space Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Simulated sea level rise in coastal peat oils stimulates mercury methylation","docAbstract":"Coastal wetlands are vulnerable to sea level rise with unknown consequences for mercury (Hg) cycling, particularly the potential for exacerbating neurotoxic methylmercury (MeHg) production and bioaccumulation in food webs. Here, the effect of sea level rise on MeHg formation in the Florida Everglades was evaluated by incubating peat cores from a freshwater wetland for 0–20 days in the laboratory at five salinity conditions (0.16–6.0 parts-per-thousand; 0.20–454 mg L–1 sulfate (SO42–)) to simulate the onset of sea level rise within coastal margins. Isotopically enriched inorganic mercury (201Hg(II)) was used to track MeHg formation and peat-porewater partitioning. In all five salinity treatments, porewaters became anoxic within 1 day and became progressively enriched in dissolved organic matter (DOM) of greater aromatic composition over the 20 days compared to ambient conditions. In the four highest salinity treatments, SO42– concentrations decreased and sulfide concentrations increased over time due to microbial dissimilatory SO42– reduction that was concurrent with 201Hg(II) methylation. Importantly, elevated salinity resulted in a greater proportion of produced Me201Hg observed in porewaters as opposed to bound to peat, interpreted to be due to the complexation of MeHg with aromatic DOM released from peat. The findings highlight the potential for enhanced production and mobilization of MeHg in coastal wetlands of the Florida Everglades due to the onset of saltwater intrusion.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acsearthspacechem.4c00124","usgsCitation":"Cook, B.A., Peterson, B.D., Ogorek, J.M., Janssen, S., and Poulin, B., 2024, Simulated sea level rise in coastal peat oils stimulates mercury methylation: ACS Earth and Space Chemistry, v. 8, no. 9, p. 1784-1796, https://doi.org/10.1021/acsearthspacechem.4c00124.","productDescription":"13 p.","startPage":"1784","endPage":"1796","ipdsId":"IP-163692","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":439209,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acsearthspacechem.4c00124","text":"Publisher Index Page"},{"id":432933,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":434914,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P139NMHU","text":"USGS data release","linkHelpText":"Mercury Methylation Assay Along a Salinity Gradient in Coastal Peat Soils in the Florida Everglades"}],"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 -80.26748408478383,\n 26.417153260709895\n ],\n [\n -81.55705618538097,\n 26.417153260709895\n ],\n [\n -81.55705618538097,\n 25.075472168285998\n ],\n [\n -80.26748408478383,\n 25.075472168285998\n ],\n [\n -80.26748408478383,\n 26.417153260709895\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"8","issue":"9","noUsgsAuthors":false,"publicationDate":"2024-08-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Cook, Bryce A.","contributorId":340463,"corporation":false,"usgs":false,"family":"Cook","given":"Bryce","email":"","middleInitial":"A.","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":910839,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, Benjamin D.","contributorId":328487,"corporation":false,"usgs":false,"family":"Peterson","given":"Benjamin","email":"","middleInitial":"D.","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":910840,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ogorek, Jacob M. 0000-0002-6327-0740 jmogorek@usgs.gov","orcid":"https://orcid.org/0000-0002-6327-0740","contributorId":4960,"corporation":false,"usgs":true,"family":"Ogorek","given":"Jacob","email":"jmogorek@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":910841,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Janssen, Sarah E. 0000-0003-4432-3154","orcid":"https://orcid.org/0000-0003-4432-3154","contributorId":210991,"corporation":false,"usgs":true,"family":"Janssen","given":"Sarah E.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":910842,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Poulin, Brett A.","contributorId":328488,"corporation":false,"usgs":false,"family":"Poulin","given":"Brett A.","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":910843,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70257678,"text":"70257678 - 2024 - Trail sustainability broadly defined","interactions":[],"lastModifiedDate":"2024-08-23T13:43:06.541821","indexId":"70257678","displayToPublicDate":"2024-08-16T06:59:51","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5520,"text":"Journal of Outdoor Recreation and Tourism","active":true,"publicationSubtype":{"id":10}},"title":"Trail sustainability broadly defined","docAbstract":"In this paper we provide a concise yet comprehensive examination of the importance and sustainability of trail networks, considering a diverse array of perspectives. Sustainability related to recreation infrastructure elements has been variously defined, with different disciplines often only considering one or two aspects of sustainability. In the context of trail networks, we suggest that there must be an equilibrium or harmony between human uses and the long-term sustainable management of the trail network's infrastructure, its protections of environmental and historic/cultural resources, and provision of diverse socio-economic benefits to visitors and surrounding communities. While trail sustainability has often been narrowly defined as accommodating visitation while minimizing environmental degradation, we emphasize a broader definition that encompasses four interconnected domains: managerial, resource, social, and economic. We suggest that a network of trails cannot be truly sustainable until scientists, land managers, and trail stewards fully consider and effectively address each of these dimensions.
Observations of glacier mass changes are key to understanding the response of glaciers to climate change and related impacts, such as regional runoff, ecosystem changes, and global sea level rise. Spaceborne optical and radar sensors make it possible to quantify glacier elevation changes, and thus multi-annual mass changes, on a regional and global scale. However, estimates from a growing number of studies show a wide range of results with differences often beyond uncertainty bounds. Here, we present the outcome of a community-based inter-comparison experiment using spaceborne optical stereo (ASTER) and synthetic aperture radar interferometry (TanDEM-X) data to estimate elevation changes for defined glaciers and target periods that pose different assessment challenges. Using provided or self-processed digital elevation models (DEMs) for five test sites, 12 research groups provided a total of 97 spaceborne elevation-change datasets using various processing approaches. Validation with airborne data showed that using an ensemble estimate is promising to reduce random errors from different instruments and processing methods but still requires a more comprehensive investigation and correction of systematic errors. We found that scene selection, DEM processing, and co-registration have the biggest impact on the results. Other processing steps, such as treating spatial data voids, differences in survey periods, or radar penetration, can still be important for individual cases. Future research should focus on testing different implementations of individual processing steps (e.g. co-registration) and addressing issues related to temporal corrections, radar penetration, glacier area changes, and density conversion. Finally, there is a clear need for our community to develop best practices, use open, reproducible software, and assess overall uncertainty to enhance inter-comparison and empower physical process insights across glacier elevation-change studies.
The climate change-induced transition from grass-dominated marshes to woody-plant-dominated mangrove forests has the potential to impact the ecosystem goods and services provided by coastal wetlands. To better anticipate and prepare for these impacts, there is a need to advance understanding of future changes in mangrove distribution and coastal wetland vegetation structural properties due to warming winters.
Southeastern United States.
Recent (1981–2010) and future (2071–2100).
Coastal wetland vegetation.
We estimated changes in mangrove distribution and coastal wetland vegetation structure using known climate-ecological relationships, recent climate data for the period 1981–2010, and future projected climate data for the period 2071–2100. We quantified potential changes in mangrove presence, mangrove relative abundance, coastal wetland vegetation height, and coastal wetland vegetation aboveground biomass under two Shared Socio-Economic Pathway scenarios (SSPs; SSP2-4.5 and SSP5-8.5), which correspond to intermediate and high greenhouse gas emissions scenarios, respectively.
Our analyses indicate that mangrove presence and relative abundance will dramatically increase in the northern Gulf of Mexico and the southeast Atlantic coast of the United States, particularly under the high emissions scenario. Because of the higher stature of mangroves relative to salt marsh vegetation, this expansion will cause a transformative change in coastal wetland vegetation height and aboveground biomass in many areas. However, along the arid southern Texas coast, low precipitation and high salinities are expected to constrain mangrove expansion and growth.
Our results show where and to what extent climate change, in the form of winter temperature warming, is projected to enable the transition from shorter, grass-dominated salt marshes to taller, woody plant-dominated mangrove forests in the southeastern United States, with consequent impacts on ecosystem goods and services.
","language":"English","publisher":"Wiley","doi":"10.1111/jbi.14985","usgsCitation":"Bardou, R., Osland, M., Alemu I, J., Feher, L.C., Harlan, D.P., Scyphers, S.B., Shepard, C., Swinea, S.H., Thorne, K., Andrew, J.E., and Hughes, A.R., 2024, Projected changes in mangrove distribution and vegetation structure under climate change in the southeastern United States: Journal of Biogeography, v. 51, no. 11, p. 2285-2297, https://doi.org/10.1111/jbi.14985.","productDescription":"13 p.","startPage":"2285","endPage":"2297","ipdsId":"IP-159771","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":439211,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jbi.14985","text":"Publisher Index Page"},{"id":433149,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": 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E.","contributorId":343621,"corporation":false,"usgs":false,"family":"Andrew","given":"Jill","email":"","middleInitial":"E.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":911548,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hughes, A. Randall","contributorId":177827,"corporation":false,"usgs":false,"family":"Hughes","given":"A.","email":"","middleInitial":"Randall","affiliations":[],"preferred":false,"id":911549,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70263690,"text":"70263690 - 2024 - The use of conceptual ecological models to identify critical data and uncertainties to support numerical modeling: The northern Gulf of Mexico eastern oyster Crassostrea virginica example","interactions":[],"lastModifiedDate":"2025-02-20T22:09:37.912852","indexId":"70263690","displayToPublicDate":"2024-08-15T16:06:46","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2680,"text":"Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The use of conceptual ecological models to identify critical data and uncertainties to support numerical modeling: The northern Gulf of Mexico eastern oyster Crassostrea virginica example","title":"The use of conceptual ecological models to identify critical data and uncertainties to support numerical modeling: The northern Gulf of Mexico eastern oyster Crassostrea virginica example","docAbstract":"Increasing reliance on numerical simulation models to help inform management and restoration choices benefits from careful consideration of critical early steps in model development. Along the northern coast of the Gulf of Mexico, the eastern oyster Crassostrea virginica fulfills important ecological and economic roles. Using the eastern oyster as an example, we draw on several recent frameworks outlining best practices for model development and application for restoration, conservation, and management.
We identify priority model questions, outline a conceptual ecological model (CEM) to guide numerical model development, and use this framework to identify uncertainties and research needs.
The CEM uses a nested design, identifying explicit vital rates, processes, attributes, and outcomes for the species (oysters), population, and metapopulation (i.e., network of populations) levels in response to drivers of species, population, and metapopulation changes and changing environmental factors. Most management actions related to oyster restoration and harvest affect population attributes directly, but many coastal management actions and changes (i.e., climate change and coastal and water resource engineering) impact environmental factors that alter vital rates and attributes of oysters, populations, and metapopulations.
Investment in studies targeting individual oyster‐ and population‐level multi‐stressor responses (filtration, respiration, growth, and reproduction) and improving hydrodynamic and environmental models targeting drivers that influence metapopulation vital rates and attributes (i.e., connectivity and substrate persistence) would contribute to reducing uncertainties. Development of numerical models covering the entire oyster life cycle and connectivity of populations using hydrodynamic models of current and predicted conditions to provide key abiotic and biotic factors influencing larval movement, recruitment, and on‐reef oyster vital rates would assist in balancing the goals of conservation, restoration, and fisheries management of this foundational estuarine species.
We completed four protocol surveys for Least Bell’s Vireos (Vireo bellii pusillus; hereinafter vireo) during the breeding season, supplemented by weekly territory monitoring visits between April 6 and July 20 at the San Luis Rey Flood Risk Management Project Area (hereinafter Project Area). We identified a total of 136 territorial male vireos; 121 were confirmed as paired, and 4 were confirmed as single males. For the remaining 11 territories, we were unable to confirm breeding status. In 2023, two transient vireos were detected. The vireo population in the Project Area increased by 2 percent from 2022 to 2023. Populations in southern San Diego County also increased (by 6 percent on the Otay River) or were stable (Salt Creek/Wolf Canyon). In contrast, the vireo population at Marine Corps Base Camp Pendleton (MCBCP) and at Marine Corps Air Station decreased by 2 and 10 percent, respectively.
We used an index of treatment (hereinafter Treatment Index) to evaluate the effect of ongoing vegetation clearing on the Project Area vireo population. The Treatment Index measures the cumulative effect of vegetation treatment within a territory by using the percentage area treated weighted by the number of years since treatment. We determined that the Treatment Index for an unoccupied habitat was more than four times higher than that of an occupied habitat, indicating that vireos selected habitats that were less treated in which to settle.
We monitored vireo nests at three general site types: (1) within the flood channel where non-native and native vegetation removal has occurred regularly (hereinafter Channel), (2) three sites near the flood channel where limited non-native and native vegetation removal has occurred (hereinafter Off-channel), and (3) three sites that have been actively restored by planting native vegetation (hereinafter Restoration). Nesting activity was monitored in 84 territories, 4 of which were occupied by single males. Overall, 46 percent of completed nests were successful, and nest success did not differ among the three sites. In 2023, we found that territories in the Channel had greater hatching success per egg compared to Off-channel, but there were no other differences with regard to clutch size, hatching, or fledging success among Channel, Off-channel, and Restoration sites. Overall breeding success and productivity were slightly higher in 2023 than in 2022, with pairs fledging an average±standard deviation of 3.1±2.1 young and 79 percent of pairs fledging at least 1 young.
To investigate if the cumulative years of treatment had an effect on vireo reproductive effort, we looked at the effects of the Treatment Index on reproductive parameters. Results from generalized linear models indicated that treatment did not have an effect on vireo nesting effort (the number of nest attempts) or the number of vireo fledglings per pair produced in 2023. Similarly, we did not detect an effect of Treatment Index on the daily survival rate (DSR) of nests.
Analysis of vegetation data collected at vireo nests from 2006 to 2023 did not reveal an effect of vegetation cover at the nest on DSR. We did find, however, that Channel nests were placed higher in and farther from the edge of the host plant than Off-channel nests. Within sites, we did not detect any differences in vegetation cover between successful and unsuccessful nests.
Red/arroyo willow (Salix laevigata or Salix lasiolepis) and mule fat (Baccharis salicifolia) were the species most commonly selected for nesting by vireos in all three site types. Black willow (Salix gooddingii) and sandbar willow (Salix exigua) also were commonly used. Vireos used a wider variety of species for nesting in Channel and Off-channel sites (10 and 13 species, respectively) compared to Restoration sites (2 species), although there was limited nesting in Restoration sites in 2023.
There were 51 vireos banded before the 2023 breeding season that were resighted and identified at the Project Area in 2023. Two of these vireos were originally banded outside of the Project Area, at the Santa Margarita River on MCBCP. Adult birds of known age ranged from 1 to 7 years old. Between 2006 and 2023, survival of males (66±11 percent) was consistently higher than that of females (60±12 percent). First-year birds from 2006 to 2022 had an average annual survival of 15±5 percent.
First-year dispersal in 2023 averaged 20.2±31.3 kilometers (km), with the longest dispersal (76.3 km) by a female that was recaptured at Wolf Canyon, a tributary to Otay River. From 2007 to 2012, most returning first-year vireos returned to the Project Area, whereas from 2014 to 2016, a greater proportion of returning birds dispersed to areas outside of the Project Area. From 2018 to 2022, the trend shifted, and more first-year vireos returned to the Project Area, except for 2022 when only one out of five first-year vireos returned to the Project Area. This trend continued in 2023: 71 percent of all first-year vireos returned to the Project Area, and 29 percent dispersed to areas outside of the Project Area (San Diego River and Wolf Canyon).
Most of the returning adult male vireos showed strong between-year fidelity to their previous territories. In 2023, 94 percent of males (34/36) occupied a territory that they had defended in 2022 (within 100 meters [m]). In 2023, 33 percent of females (1/3) detected returned to a territory they occupied in 2022. The average between-year movement for returning adult vireos was 0.2±0.9 km. The amount of treatment at adults’ 2022 territories did not affect the distance adults moved to their 2023 territories.
We completed four protocol surveys for the endangered Southwestern Willow Flycatcher (Empidonax traillii extimus; hereinafter flycatcher) at the Project Area between May 15 and July 21, 2023. In 2023, four transient Willow Flycatchers were detected in the Project Area. Two transients were detected in Reach 1, one in Reach 3a, and one in Whelan Mitigation. No resident flycatchers were documented in the Project Area in 2023.
A total of 46 vegetation transects (516 points) were sampled in the Project Area in 2023. There were 71 percent (368/516) of points located in the Channel, and 22 percent (113/516) were in Upper Pond. The remaining 7 percent (35/516) of points were at the Whelan Restoration site. Foliage cover below 1 m was higher at the Channel points and Upper Pond compared to Whelan Restoration. From 1 to 3 m, foliage cover was similar at all 3 sites; however, above 3 m foliage cover was higher in the Channel compared to the Upper Pond and Whelan Restoration sites. Average canopy height was higher in the Channel (5.6±3.8 m) compared to Upper Pond (4.7±2.7 m) and Whelan Restoration (4.0±2.0 m). From 2006 to 2023, total foliage cover declined from 2 to 3 m and above 6 m in the Channel, in contrast to Upper Pond and Whelan Restoration, where little directional change in vegetation cover has occurred and where vegetation cover has largely recovered to 2006 levels. Within the Channel, the steepest declines occurred between 2009 and 2013 and between 2014 and 2016. Since 2016, we observed an increase in foliage cover, largely herbaceous, between 0 and 2 m within the Channel. Although increases were observed at all height classes after 2016, percentage cover has remained below levels measured before 2009.
We sampled vegetation at 45 vireo nests and 45 random plots (territory plots) within territories in the Channel and Upper Pond after the 2023 breeding season. Vireos in the Channel established territories in areas with significantly more cover from 3 to 7 m but less cover below 1 m relative to the available habitat. Within territories, Channel vireos selected nest sites largely at random, but with significantly less foliage cover from 4 to 5 m. Vireos at Upper Pond established territories in areas with significantly more foliage cover below 4 m and from 5 to 6 m relative to available habitat. Within territories, Upper Pond vireos also selected nest sites at random except for a preference for sites with significantly less foliage cover below 1 m.
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