{"pageNumber":"90","pageRowStart":"2225","pageSize":"25","recordCount":40769,"records":[{"id":70252048,"text":"70252048 - 2024 - A framework to facilitate development and testing of image-based river velocimetry algorithms","interactions":[],"lastModifiedDate":"2025-02-04T14:19:00.286693","indexId":"70252048","displayToPublicDate":"2024-01-24T10:03:47","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"A framework to facilitate development and testing of image-based river velocimetry algorithms","docAbstract":"<p><span>Image-based methods have compelling, demonstrated potential for characterizing flow fields in rivers, but algorithms like particle image velocimetry (PIV) must be further tested and improved to enable more effective use of these techniques. This paper presents a framework designed for this exact purpose: Simulating Hydraulics and Images for Velocimetry Evaluation and Refinement (SHIVER). The approach involves coupling a hydrodynamic model with a synthetic particle generator to advect particles between frames, as dictated by local velocity vectors and thus construct a plausible image sequence specific to the reach of interest. The resulting time series can then be used as input to a velocimetry algorithm to compare image-derived estimates with known (modelled) velocities to perform an exhaustive, spatially distributed accuracy assessment. As an example application of SHIVER, we examined the effects of interrogation area (IA) size, frame rate, flow velocity, and image sequence duration on the performance of a standard PIV algorithm. This analysis indicated that image-derived velocities were generally in close agreement with those from the flow model (root mean square error &lt;10% and mean bias &lt;3%), except when small IAs were coupled with low frame rates. Velocity estimates were most accurate for the lowest modelled discharge ( <i>R</i><sup>2</sup></span>=0.97<span>&nbsp;at baseflow) and became less reliable as the mean flow velocity increased ( <i>R</i></span><sup>2</sup>=0.92<span>&nbsp;for an intermediate discharge and <i>R</i><sup>2</sup></span>=0.86<span>&nbsp;at bankfull). Accuracy was essentially independent of image sequence duration, implying that long occupations might not be necessary. Errors were concentrated along channel margins, where PIV-based velocities tended to be greater than those from the flow model. Small IAs led to underpredictions of velocity, while larger IAs led to overpredictions. SHIVER is highly modular and could be updated to make use of different hydrodynamic models or image simulators. The framework could also facilitate more thorough sensitivity analyses and comparison of various velocimetry algorithms.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/esp.5772","usgsCitation":"Legleiter, C.J., and Kinzel, P.J., 2024, A framework to facilitate development and testing of image-based river velocimetry algorithms: Earth Surface Processes and Landforms, v. 49, no. 4, p. 1361-1382, https://doi.org/10.1002/esp.5772.","productDescription":"22 p.; Data Release","startPage":"1361","endPage":"1382","ipdsId":"IP-155622","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":435057,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C19Z0S","text":"USGS data release","linkHelpText":"Hydrodynamic model output and image simulation code for evaluating image-based river velocimetry from a case study on the Sacramento River near Glenn, California"},{"id":426555,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":481611,"rank":3,"type":{"id":42,"text":"Open Access USGS Document"},"url":"https://pubs.usgs.gov/ja/70252048/70252048.pdf","text":"USGS accepted manuscript","size":"2.85 MB","linkFileType":{"id":1,"text":"pdf"},"description":"USGS accepted manuscript"}],"volume":"49","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-01-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":896387,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":896388,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70253131,"text":"70253131 - 2024 - Macroscale controls determine the recovery of river ecosystem productivity following flood disturbances","interactions":[],"lastModifiedDate":"2024-04-19T12:21:26.738112","indexId":"70253131","displayToPublicDate":"2024-01-24T07:19:27","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Macroscale controls determine the recovery of river ecosystem productivity following flood disturbances","docAbstract":"<div>River ecosystems rely on varied flows, including regular floods, to provide food and habitat for aquatic organisms. However, flows of freshwater are becoming increasingly managed for irrigation, industry, and other human activities, and the frequency of floods is changing. Our study used time-series data of photosynthesis from 143 rivers across the United States and developed a modeling framework to examine how algae, the base of most riverine food webs, recovered following scouring disturbance during floods. We found that algae in wider rivers recovered more quickly following disturbance (e.g., removal from the bottom) but that the flow thresholds at which algae is disturbed are likely more strongly influenced by site-specific characteristics.</div>","language":"English","publisher":"Proceedings of the National Academy of Sciences of the United States of America","doi":"10.1073/pnas.2307065121","usgsCitation":"Lowman, H., Shriver, R.K., Hall, R.O., Harvey, J., Savoy, P., Yackulic, C., and Blaszczak, J., 2024, Macroscale controls determine the recovery of river ecosystem productivity following flood disturbances: Proceedings of the National Academy of Sciences, v. 121, no. 5, e2307065121, https://doi.org/10.1073/pnas.2307065121.","productDescription":"e2307065121","ipdsId":"IP-155408","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":440632,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1073/pnas.2307065121","text":"External Repository"},{"id":427945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","issue":"5","noUsgsAuthors":false,"publicationDate":"2024-01-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Lowman, Heili","contributorId":335690,"corporation":false,"usgs":false,"family":"Lowman","given":"Heili","email":"","affiliations":[{"id":80470,"text":"Department of Natural Resources and Environmental Science, University of Nevada Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":899225,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shriver, Robert K.","contributorId":335691,"corporation":false,"usgs":false,"family":"Shriver","given":"Robert","email":"","middleInitial":"K.","affiliations":[{"id":68642,"text":"Flathead Lake Biological Station, University of Montana, Polson, MT","active":true,"usgs":false}],"preferred":false,"id":899226,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hall, Robert O. Jr.","contributorId":203473,"corporation":false,"usgs":false,"family":"Hall","given":"Robert","suffix":"Jr.","email":"","middleInitial":"O.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":899227,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harvey, Judson 0000-0002-2654-9873","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":219104,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":899228,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Savoy, Philip 0000-0002-6075-837X","orcid":"https://orcid.org/0000-0002-6075-837X","contributorId":300288,"corporation":false,"usgs":true,"family":"Savoy","given":"Philip","email":"","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":899229,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":899230,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Blaszczak, Joanna R.","contributorId":335692,"corporation":false,"usgs":false,"family":"Blaszczak","given":"Joanna R.","affiliations":[{"id":80470,"text":"Department of Natural Resources and Environmental Science, University of Nevada Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":899231,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70251161,"text":"70251161 - 2024 - Examining the effect of physicochemical and meteorological variables on water quality indicators of harmful algal blooms in a shallow hypereutrophic lake using machine learning techniques","interactions":[],"lastModifiedDate":"2024-03-12T13:21:07.21717","indexId":"70251161","displayToPublicDate":"2024-01-24T07:10:47","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Examining the effect of physicochemical and meteorological variables on water quality indicators of harmful algal blooms in a shallow hypereutrophic lake using machine learning techniques","docAbstract":"<div id=\"abstractBox\" class=\"article_abstract-content hlFld-Abstract\"><p class=\"articleBody_abstractText\">Two independent machine learning techniques, boosted regression trees and artificial neural networks, were used to examine the physicochemical and meteorological variables that affect the seasonal growth and decline of harmful algal blooms (HABs) in a shallow, hypereutrophic lake in southern Oregon. High temporal resolution data collected at four monitoring locations were aggregated into daily timesteps to create two response variables: (1) daily maximum pH (pH<sub>max</sub>), representing HAB growth, and (2) daily minimum dissolved oxygen (DO<sub>min</sub>), representing HAB decline. Predictors included meteorological and physical data, estimates of external phosphorus loading, and previous-year average nutrient concentrations, and excluded HAB biomass and internal phosphorus loading. The predictors that captured seasonal changes in both pH<sub>max</sub><span>&nbsp;</span>and DO<sub>min</sub><span>&nbsp;</span>were temperature, inflows, lake-surface elevation, and external phosphorus loading, while short-term changes were captured by measures of stratification, temperature, and wind speed. The pH<sub>max</sub><span>&nbsp;</span>models had similar fits with leave-one-year-out cross-validation (LOYO-CV)<span>&nbsp;</span><i>R</i><sup>2</sup><span>&nbsp;</span>values of 0.2–0.43 (median = 0.40). The DO<sub>min</sub><span>&nbsp;</span>models for the deeper locations had LOYO-CV<span>&nbsp;</span><i>R</i><sup>2</sup><span>&nbsp;</span>values of 0.27–0.43 compared to 0.1–0.25 for the shallower locations. Model performance was affected by variability due to patchiness of HABs, measurement uncertainty, and advection.</p></div>","language":"English","publisher":"American Chemical Society","doi":"10.1021/acsestwater.3c00299","usgsCitation":"Wherry, S., and Schenk, L.N., 2024, Examining the effect of physicochemical and meteorological variables on water quality indicators of harmful algal blooms in a shallow hypereutrophic lake using machine learning techniques: Water, v. 4, no. 3, p. 1073-1082, https://doi.org/10.1021/acsestwater.3c00299.","productDescription":"10 p.; Data Release","startPage":"1073","endPage":"1082","ipdsId":"IP-135772","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":440637,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acsestwater.3c00299","text":"Publisher Index Page"},{"id":435058,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P971MB6W","text":"USGS data release","linkHelpText":"Input and results from boosted regression tree and artificial neural network models that predict daily maximum pH and daily minimum dissolved oxygen in Upper Klamath Lake, 2005-2019"},{"id":424951,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-01-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Wherry, Susan 0000-0002-6749-8697 swherry@usgs.gov","orcid":"https://orcid.org/0000-0002-6749-8697","contributorId":140159,"corporation":false,"usgs":true,"family":"Wherry","given":"Susan","email":"swherry@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":893307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schenk, Liam N. 0000-0002-2491-0813 lschenk@usgs.gov","orcid":"https://orcid.org/0000-0002-2491-0813","contributorId":4273,"corporation":false,"usgs":true,"family":"Schenk","given":"Liam","email":"lschenk@usgs.gov","middleInitial":"N.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":893308,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70251170,"text":"70251170 - 2024 - Identifying indicators of polar bear population status","interactions":[],"lastModifiedDate":"2024-01-25T13:05:16.278419","indexId":"70251170","displayToPublicDate":"2024-01-24T07:04:30","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Identifying indicators of polar bear population status","docAbstract":"<div id=\"ab015\" class=\"abstract author\"><div id=\"as015\"><p id=\"sp0015\">Monitoring trends in large mammal populations is a fundamental component of wildlife management and conservation. However, direct estimates of population size and vital rates of large mammals can be logistically challenging and expensive. Indicators that reflect trends in abundance, therefore, can be valuable tools for supporting population monitoring. Polar bears have a relatively simple life history such that a few key variables may be effective indicators for tracking changes in body condition and recruitment that affect abundance. Direct estimates of polar bear abundance are difficult to obtain due to their large home ranges in remote Arctic habitats. Changes in abundance associated with environmental conditions appear to affect polar bears largely via effects on female body condition which influence reproduction and cub survival (i.e., recruitment). Loss of sea ice habitat is further limiting researcher access for population monitoring creating a need for alternative approaches. Here we used relationships established from eight years (2008–2017) of data collected on 439 polar bears in the Chukchi Sea, to transform previously published individual-based relationships with annually available sea ice, atmospheric circulation, and prey body condition variables to predict annual mean body condition and recruitment during 2018–2022. Although annual sample sizes were limited for verifying predicted body condition and recruitment via techniques such as cross-validation, in most cases predicted annual means were closely correlated with observed means for 2008–2017. Summer sea ice and prey body condition remained within or increased relative to levels observed during 2008–2017 and predicted polar bear body condition and recruitment during 2018–2022 were largely within or above observed annual means during 2008–2017. A lack of trend in environmental and ecological variables or polar bear body condition and recruitment metrics during 2008–2022 is suggestive that the Chukchi Sea polar bear population was likely stable during this time. Our results provide support for developing models that predict important population parameters of large mammals based on environmental and ecological indicators. Given that trend information is lacking for 10 of the 19 recognized polar bear populations and is outdated for others, the use of environmental and ecological indicators may be particularly useful for augmenting direct estimates of polar bear vital rates in between periods of data collection. Although demographic assessments for polar bears have primarily focused on correlations with sea ice availability, our study and others highlight that prey health is also an important indicator of polar bear population status.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2024.111638","usgsCitation":"Rode, K.D., Wilson, R., Crawford, J.A., and Quakenbush, L.T., 2024, Identifying indicators of polar bear population status: Ecological Indicators, v. 159, 111638, 12 p., https://doi.org/10.1016/j.ecolind.2024.111638.","productDescription":"111638, 12 p.","ipdsId":"IP-154752","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":440640,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2024.111638","text":"Publisher Index Page"},{"id":424948,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"159","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":893334,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Ryan R. ","contributorId":222456,"corporation":false,"usgs":false,"family":"Wilson","given":"Ryan R. ","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":893335,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crawford, Justin A.","contributorId":214225,"corporation":false,"usgs":false,"family":"Crawford","given":"Justin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":893336,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quakenbush, Lori T.","contributorId":192737,"corporation":false,"usgs":false,"family":"Quakenbush","given":"Lori","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":893337,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70251268,"text":"70251268 - 2024 - Multiple lines of evidence point to pesticides as stressors affecting invertebrate communities in small streams in five United States regions","interactions":[],"lastModifiedDate":"2024-02-07T17:30:55.287424","indexId":"70251268","displayToPublicDate":"2024-01-24T06:38:05","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Multiple lines of evidence point to pesticides as stressors affecting invertebrate communities in small streams in five United States regions","docAbstract":"<div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0040\">Multistressor studies were performed in five regions of the United States to assess the role of pesticides as stressors affecting invertebrate communities in wadable streams. Pesticides and other chemical and physical stressors were measured in 75 to 99 streams per region for 4&nbsp;weeks, after which invertebrate communities were surveyed (435 total sites). Pesticides were sampled weekly in filtered water, and once in bed sediment. The role of pesticides as a stressor to invertebrate communities was assessed by evaluating multiple lines of evidence: toxicity predictions based on measured pesticide concentrations, multivariate models and other statistical analyses, and previously published mesocosm experiments. Toxicity predictions using benchmarks and species sensitivity distributions and statistical correlations suggested that pesticides were present at high enough concentrations to adversely affect invertebrate communities at the regional scale. Two undirected techniques—boosted regression tree models and distance-based linear models—identified which pesticides were predictors of (respectively) invertebrate metrics and community composition. To put insecticides in context with known, influential covariates of invertebrate response, generalized additive models were used to identify which individual pesticide(s) were important predictors of invertebrate community condition in each region, after accounting for natural covariates. Four insecticides were identified as stressors to invertebrate communities at the regional scale: bifenthrin, chlordane, fipronil and its degradates, and imidacloprid. Fipronil was particularly important in the Southeast region, and imidacloprid, bifenthrin, and chlordane were important in multiple regions. For imidacloprid, bifenthrin, and fipronil, toxicity predictions were supported by mesocosm experiments that demonstrated adverse effects on naïve aquatic communities when dosed under controlled conditions. These multiple lines of evidence do not prove causality—which is challenging in the field under multistressor conditions—but they make a strong case for the role of insecticides as stressors adversely affecting invertebrate communities in streams within the five sampled regions.</p></div></div><div id=\"ab0010\" class=\"abstract graphical\" lang=\"en\"><br></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2023.169634","usgsCitation":"Nowell, L.H., Moran, P.W., Waite, I.R., Schmidt, T., Bradley, P., Mahler, B.J., and Van Metre, P., 2024, Multiple lines of evidence point to pesticides as stressors affecting invertebrate communities in small streams in five United States regions: Science of the Total Environment, v. 915, 169634, 19 p., https://doi.org/10.1016/j.scitotenv.2023.169634.","productDescription":"169634, 19 p.","ipdsId":"IP-133858","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":440644,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2023.169634","text":"Publisher Index Page"},{"id":425211,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -70.34093824090904,\n              45.96731982755614\n            ],\n            [\n              -80.84386792840942,\n              45.96731982755614\n            ],\n            [\n              -80.84386792840942,\n              41.36128542179111\n            ],\n            [\n              -70.34093824090904,\n              41.36128542179111\n            ],\n            [\n              -70.34093824090904,\n              45.96731982755614\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -80.99233772961507,\n              37.25579760233164\n            ],\n            [\n              -80.99233772961507,\n              44.61324664080104\n            ],\n            [\n              -98.26284554211517,\n              44.61324664080104\n            ],\n            [\n              -98.26284554211517,\n              37.25579760233164\n            ],\n            [\n              -80.99233772961507,\n              37.25579760233164\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -124.21510791138498,\n              42.504659813608754\n            ],\n            [\n              -119.73794381696277,\n              42.504659813608754\n            ],\n            [\n              -119.73794381696277,\n              49.0242512761713\n            ],\n            [\n              -124.21510791138498,\n              49.0242512761713\n            ],\n            [\n              -124.21510791138498,\n              42.504659813608754\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -124.53965220089417,\n              40.68005247321099\n            ],\n            [\n              -124.53965220089417,\n              33.005079792847866\n            ],\n            [\n              -116.48075683093388,\n              33.005079792847866\n            ],\n            [\n              -116.48075683093388,\n              40.68005247321099\n            ],\n            [\n              -124.53965220089417,\n              40.68005247321099\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -86.59958657168067,\n              32.245671596530244\n            ],\n            [\n              -77.15684048162615,\n              32.245671596530244\n            ],\n            [\n              -77.15684048162615,\n              38.79755456911414\n            ],\n            [\n              -86.59958657168067,\n              38.79755456911414\n            ],\n            [\n              -86.59958657168067,\n              32.245671596530244\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"915","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nowell, Lisa H. 0000-0001-5417-7264 lhnowell@usgs.gov","orcid":"https://orcid.org/0000-0001-5417-7264","contributorId":490,"corporation":false,"usgs":true,"family":"Nowell","given":"Lisa","email":"lhnowell@usgs.gov","middleInitial":"H.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":893776,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moran, Patrick W. 0000-0002-2002-3539 pwmoran@usgs.gov","orcid":"https://orcid.org/0000-0002-2002-3539","contributorId":489,"corporation":false,"usgs":true,"family":"Moran","given":"Patrick","email":"pwmoran@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":893777,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waite, Ian R. 0000-0003-1681-6955 iwaite@usgs.gov","orcid":"https://orcid.org/0000-0003-1681-6955","contributorId":616,"corporation":false,"usgs":true,"family":"Waite","given":"Ian","email":"iwaite@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":893778,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmidt, Travis S. 0000-0003-1400-0637 tschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-1400-0637","contributorId":1300,"corporation":false,"usgs":true,"family":"Schmidt","given":"Travis S.","email":"tschmidt@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":893779,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bradley, Paul M. 0000-0001-7522-8606","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":205668,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":893780,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mahler, Barbara J. 0000-0002-9150-9552","orcid":"https://orcid.org/0000-0002-9150-9552","contributorId":333743,"corporation":false,"usgs":false,"family":"Mahler","given":"Barbara","email":"","middleInitial":"J.","affiliations":[{"id":40102,"text":"U.S. Geological Survey, deceased","active":true,"usgs":false}],"preferred":false,"id":893781,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Van Metre, Peter 0000-0001-7564-9814","orcid":"https://orcid.org/0000-0001-7564-9814","contributorId":255624,"corporation":false,"usgs":false,"family":"Van Metre","given":"Peter","affiliations":[{"id":7065,"text":"USGS emeritus","active":true,"usgs":false}],"preferred":false,"id":893782,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70252510,"text":"70252510 - 2024 - A multiscale perspective for improving conservation of Conchos pupfish","interactions":[],"lastModifiedDate":"2024-09-11T16:10:31.575447","indexId":"70252510","displayToPublicDate":"2024-01-23T07:07:24","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":774,"text":"Animal Conservation","active":true,"publicationSubtype":{"id":10}},"title":"A multiscale perspective for improving conservation of Conchos pupfish","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Desert spring systems of the American southwest hold high local fish endemism and are ranked among the most threatened ecosystems in the world. The prioritization of conservation resources to protect species living within these arid landscapes requires knowledge of species abundance and distribution. The plight of Conchos pupfish (<i>Cyprinodon eximius</i>) is representative of freshwater fishes the world over, including population extirpations caused by human poisoning of streams and reservoir construction, to the extent that the species was once considered extinct in the USA. We developed a distance-sampling framework to monitor Conchos pupfish abundance and coupled this approach with species distribution modeling to guide conservation actions. Our multiscale approach included surveying abundances within 5-m transects at three reaches of the Devils River, where the last known USA populations persist. We combined this fine-scale analysis with species distribution modeling for stream segments across the range of the species in Mexico and USA. Modeling revealed Conchos pupfish abundance among transects was negatively correlated with current velocity and detection was negatively correlated with water depth. Estimated abundance at a reach where the species was previously reintroduced was greater than other reaches combined in November 2019, lowest in March 2021 when reach water levels were very low, then equivalent with other reaches by October 2021 after water returned to the reach. Modeled Conchos pupfish distribution illustrated a high probability of occurrence on the periphery of the species' overall range within Texas, USA and broadly across Chihuahua, Mexico, where proposed protected areas might benefit the species. Our study provides conservation guidance by establishing (1) baseline and trajectory values for abundance, (2) transect locations where abundances might be managed within existing protected areas, (3) reaches where high abundances could be used for future repatriation, and (4) stream segments where future surveys might be conducted to assess conservation opportunities.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/acv.12930","usgsCitation":"Elkins, L.C., Acre, M.R., Bean, M.G., Robertson, S.M., Smith, R., and Perkin, J., 2024, A multiscale perspective for improving conservation of Conchos pupfish: Animal Conservation, v. 27, no. 4, p. 538-553, https://doi.org/10.1111/acv.12930.","productDescription":"16 p.","startPage":"538","endPage":"553","ipdsId":"IP-147079","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":440649,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/acv.12930","text":"Publisher Index Page"},{"id":427140,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-01-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Elkins, Lindsey C.","contributorId":335067,"corporation":false,"usgs":false,"family":"Elkins","given":"Lindsey","email":"","middleInitial":"C.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":897359,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Acre, Matthew Ross 0000-0002-5417-9523","orcid":"https://orcid.org/0000-0002-5417-9523","contributorId":268034,"corporation":false,"usgs":true,"family":"Acre","given":"Matthew","email":"","middleInitial":"Ross","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":897360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bean, Megan G.","contributorId":335068,"corporation":false,"usgs":false,"family":"Bean","given":"Megan","email":"","middleInitial":"G.","affiliations":[{"id":27442,"text":"Texas parks and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":897361,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robertson, Sarah M.","contributorId":335069,"corporation":false,"usgs":false,"family":"Robertson","given":"Sarah","email":"","middleInitial":"M.","affiliations":[{"id":27442,"text":"Texas parks and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":897362,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Ryan 0000-0002-3747-6868","orcid":"https://orcid.org/0000-0002-3747-6868","contributorId":333943,"corporation":false,"usgs":false,"family":"Smith","given":"Ryan","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":897363,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Perkin, Joshuah S.","contributorId":238286,"corporation":false,"usgs":false,"family":"Perkin","given":"Joshuah S.","affiliations":[{"id":47708,"text":"Department of Wildlife and Fisheries Sciences, Texas A&M University, College Station, TX","active":true,"usgs":false}],"preferred":false,"id":897364,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70251144,"text":"70251144 - 2024 - Evaluating density-weighted connectivity of black bears (Ursus americanus) in Glacier National Park with spatial capture–recapture models","interactions":[],"lastModifiedDate":"2024-01-24T12:39:21.64194","indexId":"70251144","displayToPublicDate":"2024-01-23T06:37:15","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating density-weighted connectivity of black bears (Ursus americanus) in Glacier National Park with spatial capture–recapture models","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Background</h3><p>Improved understanding of wildlife population connectivity among protected area networks can support effective planning for the persistence of wildlife populations in the face of land use and climate change. Common approaches to estimating connectivity often rely on small samples of individuals without considering the spatial structure of populations, leading to limited understanding of how individual movement links to demography and population connectivity. Recently developed spatial&nbsp;capture-recapture (SCR) models provide a framework to formally connect inference about individual movement, connectivity, and population density, but few studies have applied this approach to empirical data to support connectivity planning.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Methods</h3><p>We used mark-recapture data collected from 924 genetic detections of 598 American black bears (<i>Ursus americanus</i>) in 2004 with SCR ecological distance models to simultaneously estimate density, landscape resistance to movement, and population connectivity in Glacier National Park northwest Montana, USA. We estimated density and movement parameters separately for males and females and used model estimates to calculate predicted density-weighted connectivity surfaces.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results</h3><p>Model results indicated that landscape structure influences black bear density and space use in Glacier. The mean density estimate was 16.08 bears/100&nbsp;km<sup>2</sup><span>&nbsp;</span>(95% CI 12.52–20.6) for females and 9.27 bears/100&nbsp;km<sup>2</sup><span>&nbsp;</span>(95% CI 7.70–11.14) for males. Density increased with forest cover for both sexes. For male black bears, density decreased at higher grizzly bear (<i>Ursus arctos</i>) densities. Drainages, valley bottoms, and riparian vegetation decreased estimates of landscape resistance to movement for male and female bears. For males, forest cover also decreased estimated resistance to movement, but a transportation corridor bisecting the study area strongly increased resistance to movement presenting a barrier to connectivity.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusions</h3><p>Density-weighed connectivity surfaces highlighted areas important for population connectivity that were distinct from areas with high potential connectivity. For black bears in Glacier and surrounding landscapes, consideration of both vegetation and valley topography could inform the placement of underpasses along the transportation corridor in areas characterized by both high population density and potential connectivity. Our study demonstrates that the SCR ecological distance model can provide biologically realistic, spatially explicit predictions to support movement connectivity planning across large landscapes.</p>","language":"English","publisher":"Springer Nature","doi":"10.1186/s40462-023-00445-7","usgsCitation":"Carroll, S.L., Schmidt, G.M., Waller, J.S., and Graves, T., 2024, Evaluating density-weighted connectivity of black bears (Ursus americanus) in Glacier National Park with spatial capture–recapture models: Movement Ecology, v. 12, 8, 18 p., https://doi.org/10.1186/s40462-023-00445-7.","productDescription":"8, 18 p.","ipdsId":"IP-152033","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":440652,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-023-00445-7","text":"Publisher Index Page"},{"id":424846,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -115.27217583291136,\n              49.293498450490404\n            ],\n            [\n              -115.27217583291136,\n              47.6179024821721\n            ],\n            [\n              -112.5475664579116,\n              47.6179024821721\n            ],\n            [\n              -112.5475664579116,\n              49.293498450490404\n            ],\n            [\n              -115.27217583291136,\n              49.293498450490404\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2024-01-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Carroll, Sarah L","contributorId":300618,"corporation":false,"usgs":false,"family":"Carroll","given":"Sarah","email":"","middleInitial":"L","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":893258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmidt, Greta M","contributorId":300615,"corporation":false,"usgs":false,"family":"Schmidt","given":"Greta","email":"","middleInitial":"M","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":893259,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waller, John S.","contributorId":167055,"corporation":false,"usgs":false,"family":"Waller","given":"John","email":"","middleInitial":"S.","affiliations":[{"id":16272,"text":"National Park Service, Glacier National Park, West Glacier, MT","active":true,"usgs":false}],"preferred":false,"id":893260,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":893261,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70251503,"text":"70251503 - 2024 - Sicklefin Chub (Macrhybopsis meeki) and Sturgeon Chub (M. gelida) temporal and spatial patterns from extant population monitoring and habitat data spanning 23 Years","interactions":[],"lastModifiedDate":"2024-02-14T12:41:57.260543","indexId":"70251503","displayToPublicDate":"2024-01-23T06:34:48","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6476,"text":"Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Sicklefin Chub (Macrhybopsis meeki) and Sturgeon Chub (M. gelida) temporal and spatial patterns from extant population monitoring and habitat data spanning 23 Years","docAbstract":"<div class=\"html-p\">Sicklefin (<span class=\"html-italic\">Macrhybopsis meeki</span>) and sturgeon chub (<span class=\"html-italic\">M. gelida</span>) historically occurred throughout the Missouri River (MR), in some tributaries, and Mississippi River downstream of the MR. They have been species of U.S. state-level conservation concern and U.S. Endangered Species Act listing candidates since the 1990s. We applied analytical approaches from occupancy modeling to correlation to monitoring data spanning 23 years to assess relationships between occupancy and time, space, environmental factors, habitat, and other species. Sicklefin chub occupancy appeared higher in the early to mid-2000s and mid-to-late 2010s. A potential decline in occupancy occurred for sturgeon chub in the mid-to-late 2010s. Spatially, chub occupancy was depressed for 159 to 438 km downstream of MR dams. Among macrohabitats, inside bends had relatively high occupancy for both species; secondary connected channels had relatively high values for sturgeon chub. Co-occurrence was likely between sicklefin and sturgeon chub and between chubs and shovelnose sturgeon (<span class=\"html-italic\">Scaphirhybchus platorybchus</span>) and channel catfish (<span class=\"html-italic\">Ictalurus punctatus</span>). The observed co-occurrence of chubs and pallid sturgeon (<span class=\"html-italic\">Scaphirhynchus albus</span>; PS) was potentially higher than expected for adult PS. For juvenile PS, co-occurrence was lower than expected in the Lower MR and potentially higher than expected in the Upper MR, warranting future research. Results from this research suggest management for the improvement of sicklefin and sturgeon chub populations may benefit other MR fish populations.</div>","language":"English","publisher":"MDPI","doi":"10.3390/fishes9020043","usgsCitation":"Wildhaber, M.L., West, B.M., Bennett, K.R., May, J.H., Albers, J.L., and Green, N., 2024, Sicklefin Chub (Macrhybopsis meeki) and Sturgeon Chub (M. gelida) temporal and spatial patterns from extant population monitoring and habitat data spanning 23 Years: Fishes, v. 9, no. 2, 43, 31 p., https://doi.org/10.3390/fishes9020043.","productDescription":"43, 31 p.","ipdsId":"IP-158360","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":440655,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fishes9020043","text":"Publisher Index Page"},{"id":435059,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AB7UI4","text":"USGS data release","linkHelpText":"Occupancy model coefficients and observed co-occurrence simulations for sicklefin chub, sturgeon chub, and associated fishes in the Missouri River"},{"id":425643,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -106.18276498651836,\n              48.74166246322022\n            ],\n            [\n              -106.18276498651836,\n              37.22153406979474\n            ],\n            [\n              -88.78042123651797,\n              37.22153406979474\n            ],\n            [\n              -88.78042123651797,\n              48.74166246322022\n            ],\n            [\n              -106.18276498651836,\n              48.74166246322022\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"9","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-01-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":894748,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"West, Benjamin M 0000-0001-8355-0013","orcid":"https://orcid.org/0000-0001-8355-0013","contributorId":298588,"corporation":false,"usgs":true,"family":"West","given":"Benjamin","email":"","middleInitial":"M","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":894749,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennett, Kendell Ray 0000-0001-6081-7002","orcid":"https://orcid.org/0000-0001-6081-7002","contributorId":334116,"corporation":false,"usgs":true,"family":"Bennett","given":"Kendell","email":"","middleInitial":"Ray","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":894750,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"May, Jack Howard 0000-0001-7660-3308","orcid":"https://orcid.org/0000-0001-7660-3308","contributorId":334117,"corporation":false,"usgs":true,"family":"May","given":"Jack","email":"","middleInitial":"Howard","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":894751,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Albers, Janice L. 0000-0002-6312-8269 jalbers@usgs.gov","orcid":"https://orcid.org/0000-0002-6312-8269","contributorId":3972,"corporation":false,"usgs":true,"family":"Albers","given":"Janice","email":"jalbers@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":894752,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Green, Nicholas S.","contributorId":301918,"corporation":false,"usgs":false,"family":"Green","given":"Nicholas S.","affiliations":[{"id":65362,"text":"Kennesaw State University","active":true,"usgs":false}],"preferred":false,"id":894753,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70251139,"text":"70251139 - 2024 - Evaluating spatial coverage of the greater sage-grouse umbrella to conserve sagebrush-dependent species biodiversity within the Wyoming basins","interactions":[],"lastModifiedDate":"2024-01-24T12:57:44.164829","indexId":"70251139","displayToPublicDate":"2024-01-22T06:55:31","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2596,"text":"Land","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating spatial coverage of the greater sage-grouse umbrella to conserve sagebrush-dependent species biodiversity within the Wyoming basins","docAbstract":"<div class=\"html-p\">Biodiversity is threatened due to land-use change, overexploitation, pollution, and anthropogenic climate change, altering ecosystem functioning around the globe. Protecting areas rich in biodiversity is often difficult without fully understanding and mapping species’ ecological niche requirements. As a result, the umbrella species concept is often applied, whereby conservation of a surrogate species is used to indirectly protect species that occupy similar ecological communities. One such species is the greater sage-grouse (<span class=\"html-italic\">Centrocercus urophasianus</span>), which has been used as an umbrella to conserve other species within the sagebrush (<span class=\"html-italic\">Artemisia</span><span>&nbsp;</span>spp.) ecosystem. Sagebrush-steppe ecosystems within the United States have experienced drastic loss, fragmentation, and degradation of remaining habitat, threatening sagebrush-dependent fauna, resulting in west-wide conservation efforts to protect sage-grouse habitats, and presumably other sagebrush wildlife. We evaluated the effectiveness of the greater sage-grouse umbrella to conserve biodiversity using data-driven spatial occupancy and abundance models for seven sagebrush-dependent (obligate or associated) species across the greater Wyoming Basins Ecoregional Assessment (WBEA) area (345,300 km<sup>2</sup>) and assessed overlap with predicted sage-grouse occurrence. Predicted sage-grouse habitat from empirical models only partially (39–58%) captured habitats identified by predicted occurrence models for three sagebrush-obligate songbirds and 60% of biodiversity hotspots (richness of 4–6 species). Sage-grouse priority areas for conservation only captured 59% of model-predicted sage-grouse habitat, and only slightly fewer (56%) biodiversity hotspots. We suggest that the greater sage-grouse habitats may be partially effective as an umbrella for the conservation of sagebrush-dependent species within the sagebrush biome, and management actions aiming to conserve biodiversity should directly consider the explicit mapping of resource requirements for other taxonomic groups.</div>","language":"English","publisher":"MDPI","doi":"10.3390/land13010123","usgsCitation":"Aldridge, C.L., Saher, D., Heinrichs, J., Monroe, A., Leu, M., and Hanser, S.E., 2024, Evaluating spatial coverage of the greater sage-grouse umbrella to conserve sagebrush-dependent species biodiversity within the Wyoming basins: Land, v. 13, no. 1, 123, 22 p., https://doi.org/10.3390/land13010123.","productDescription":"123, 22 p.","ipdsId":"IP-129190","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":440660,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/land13010123","text":"Publisher Index Page"},{"id":424850,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -112.95934067669556,\n              46.4660838376702\n            ],\n            [\n              -112.95934067669556,\n              38.40822699632798\n            ],\n            [\n              -106.32359848919579,\n              38.40822699632798\n            ],\n            [\n              -106.32359848919579,\n              46.4660838376702\n            ],\n            [\n              -112.95934067669556,\n              46.4660838376702\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"13","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-01-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":893244,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Saher, D. Joanne 0000-0002-2452-2570","orcid":"https://orcid.org/0000-0002-2452-2570","contributorId":288928,"corporation":false,"usgs":false,"family":"Saher","given":"D. Joanne","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":893245,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heinrichs, Julie A. 0000-0001-7733-5034","orcid":"https://orcid.org/0000-0001-7733-5034","contributorId":240888,"corporation":false,"usgs":false,"family":"Heinrichs","given":"Julie A.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":893246,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Monroe, Adrian P. 0000-0003-0934-8225 amonroe@usgs.gov","orcid":"https://orcid.org/0000-0003-0934-8225","contributorId":152209,"corporation":false,"usgs":true,"family":"Monroe","given":"Adrian P.","email":"amonroe@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":893247,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Leu, Matthias 0000-0002-4290-7212","orcid":"https://orcid.org/0000-0002-4290-7212","contributorId":194938,"corporation":false,"usgs":false,"family":"Leu","given":"Matthias","email":"","affiliations":[],"preferred":false,"id":893248,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hanser, Steve E. 0000-0002-4430-2073 shanser@usgs.gov","orcid":"https://orcid.org/0000-0002-4430-2073","contributorId":152523,"corporation":false,"usgs":true,"family":"Hanser","given":"Steve","email":"shanser@usgs.gov","middleInitial":"E.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":893249,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70251108,"text":"70251108 - 2024 - The economics of decarbonizing Costa Rica's agriculture, forestry and other land uses sectors","interactions":[],"lastModifiedDate":"2024-01-23T12:58:03.361697","indexId":"70251108","displayToPublicDate":"2024-01-22T06:55:18","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1453,"text":"Ecological Economics","active":true,"publicationSubtype":{"id":10}},"title":"The economics of decarbonizing Costa Rica's agriculture, forestry and other land uses sectors","docAbstract":"<p>In 2018, Costa Rica demonstrated its commitment to the Paris Agreement and published its Decarbonization Plan for achieving zero net emissions by the year 2050. We evaluate the impacts of the country's strategy for decarbonizing its Agriculture, Forestry and Other Land Uses (AFOLU) sectors by coupling the Integrated Economic-Environmental Modeling framework with high-resolution spatial land use-land cover change and ecosystem services modeling (IEEM+ESM). Our results show that decarbonization of AFOLU would simultaneously enhance carbon storage, water purification, water regulation and erosion mitigation ecosystem services. Moreover, the positive cumulative wealth impact of decarbonization would be approximately US$7.27 billion by 2050 while lifting an additional 3810 individuals out of poverty. From a public investment perspective, decarbonization would have a fiscally neutral impact with the economic benefits sufficient in magnitude to off-set policy implementation costs and generate economic returns of over US$852 million when changes in natural capital stocks and environmental quality are considered. This application to Costa Rica is the first integrated economy-wide analysis of a growing number of decarbonization plans globally. The IEEM+ESM approach provides an integrated framework for analyzing decarbonization plans and can be used to refine AFOLU mitigation strategies to capitalize on synergies and minimize negative trade-offs across the three dimensions of wealth and sustainable economic development, namely economy, society and the environment.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolecon.2024.108115","usgsCitation":"Banerjee, O., Cicowiez, M., Vargas, R., Molina-Perez, E., Bagstad, K.J., and Malek, Z., 2024, The economics of decarbonizing Costa Rica's agriculture, forestry and other land uses sectors: Ecological Economics, v. 218, 108115, 15 p., https://doi.org/10.1016/j.ecolecon.2024.108115.","productDescription":"108115, 15 p.","ipdsId":"IP-146533","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":486947,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://research.vu.nl/en/publications/982c7ba2-e757-4767-b936-64ab57cabf27","text":"External Repository"},{"id":424738,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Costa Rica","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-82.96578,8.22503],[-83.50844,8.44693],[-83.71147,8.65684],[-83.59631,8.83044],[-83.63264,9.05139],[-83.90989,9.2908],[-84.3034,9.48735],[-84.64764,9.61554],[-84.71335,9.90805],[-84.97566,10.08672],[-84.91137,9.79599],[-85.11092,9.55704],[-85.33949,9.83454],[-85.66079,9.93335],[-85.79744,10.13489],[-85.79171,10.43934],[-85.65931,10.75433],[-85.94173,10.89528],[-85.71254,11.08844],[-85.56185,11.21712],[-84.903,10.9523],[-84.67307,11.08266],[-84.35593,10.99923],[-84.19018,10.79345],[-83.89505,10.72684],[-83.65561,10.93876],[-83.40232,10.39544],[-83.01568,9.99298],[-82.5462,9.56613],[-82.93289,9.47681],[-82.92715,9.07433],[-82.71918,8.92571],[-82.86866,8.80727],[-82.82977,8.6263],[-82.91318,8.42352],[-82.96578,8.22503]]]},\"properties\":{\"name\":\"Costa Rica\"}}]}","volume":"218","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Banerjee, Onil","contributorId":224437,"corporation":false,"usgs":false,"family":"Banerjee","given":"Onil","email":"","affiliations":[{"id":40887,"text":"Inter-American Development Bank","active":true,"usgs":false}],"preferred":false,"id":893151,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cicowiez, Martin","contributorId":299650,"corporation":false,"usgs":false,"family":"Cicowiez","given":"Martin","email":"","affiliations":[{"id":40888,"text":"Universidad Nacional de la Plata","active":true,"usgs":false}],"preferred":false,"id":893152,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vargas, Renato 0000-0002-2302-1141","orcid":"https://orcid.org/0000-0002-2302-1141","contributorId":299655,"corporation":false,"usgs":false,"family":"Vargas","given":"Renato","email":"","affiliations":[{"id":64919,"text":"CHW Research","active":true,"usgs":false}],"preferred":false,"id":893153,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Molina-Perez, Edmundo 0000-0003-0774-3205","orcid":"https://orcid.org/0000-0003-0774-3205","contributorId":333577,"corporation":false,"usgs":false,"family":"Molina-Perez","given":"Edmundo","email":"","affiliations":[{"id":79938,"text":"Instituto Tecnológico de Monterrey","active":true,"usgs":false}],"preferred":false,"id":893154,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":893155,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Malek, Ziga 0000-0002-6981-6708","orcid":"https://orcid.org/0000-0002-6981-6708","contributorId":299652,"corporation":false,"usgs":false,"family":"Malek","given":"Ziga","email":"","affiliations":[{"id":64916,"text":"Vrije Univeriteit Amsterdam","active":true,"usgs":false}],"preferred":false,"id":893156,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70251093,"text":"70251093 - 2024 - Identifying and constraining marsh-type transitions in response to increasing erosion over the past century","interactions":[],"lastModifiedDate":"2025-05-13T15:59:57.107562","indexId":"70251093","displayToPublicDate":"2024-01-22T06:39:44","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Identifying and constraining marsh-type transitions in response to increasing erosion over the past century","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Marsh environments, characterized by their flora and fauna, change laterally in response to shoreline erosion, water levels and inundation, and anthropogenic activities. The Grand Bay coastal system (USA) has undergone multiple large-scale geomorphic and hydrologic changes resulting in altered sediment supply, depositional patterns, and degraded barrier islands, leaving wetland salt marshes vulnerable to increased wave activity. Two shore-perpendicular transect sites, one along a low-activity shoreline and the other in a high activity area of the same bay-marsh complex, were sampled to investigate how the marshes within 50 m of the modern shoreline have responded to different levels of increased wave activity over the past century. Surface sediments graded finer and more organic with increased distance from the shoreline while cores generally exhibited a coarsening upwards grain-size trend; all cores contained multiple large sedimentological shifts.<span>&nbsp;</span><sup>210</sup>Pb-based mass accumulation rates over the last two decades were greater than the long-term (centurial) average at each site with the fastest accumulation rates of 7.81 ± 1.58 and 7.79 ± 1.63 kg/m<sup>2</sup>/year at the sites nearest the shoreline. A shoreline change analysis of three time-slices (1848–2017, 1957–2017, 2016–2017) shows increased erosion at both sites since 1848 with modern rates of −0.95 and −0.88 m/year. Downcore sedimentology, mass accumulation rates, and shoreline change rates paired with foraminiferal biofacies and identification of local estuarine indicator species,<span>&nbsp;</span><i>Paratrochammina simplissima</i>, aided in identifying paleo marsh types, their relative proximity to the shoreline, and sediment provenance. The high-energy marsh site transitioned from middle marsh to low marsh in the 1960s, and the low-energy marsh site transitioned later, at the end of the twentieth and early twenty-first century, due to its more protected location. Marsh type transition corresponds chronologically with the coarsening upwards grain-size trend observed and the degradation of Grand Batture Island; since its submergence, signatures of multiple storm event have been preserved downcore.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s12237-023-01320-9","usgsCitation":"Ellis, A.M., Smith, C., Smith, K., and Jacobs, J.A., 2024, Identifying and constraining marsh-type transitions in response to increasing erosion over the past century: Estuaries and Coasts, v. 47, p. 701-723, https://doi.org/10.1007/s12237-023-01320-9.","productDescription":"23 p.","startPage":"701","endPage":"723","ipdsId":"IP-139224","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":440666,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-023-01320-9","text":"Publisher Index Page"},{"id":424735,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -88.55887042293745,\n              30.413358534481205\n            ],\n            [\n              -88.55887042293745,\n              30.2776597547238\n            ],\n            [\n              -88.36935626278142,\n              30.2776597547238\n            ],\n            [\n              -88.36935626278142,\n              30.413358534481205\n            ],\n            [\n              -88.55887042293745,\n              30.413358534481205\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"47","noUsgsAuthors":false,"publicationDate":"2024-01-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Ellis, Alisha M. 0000-0002-1785-020X aellis@usgs.gov","orcid":"https://orcid.org/0000-0002-1785-020X","contributorId":192957,"corporation":false,"usgs":true,"family":"Ellis","given":"Alisha","email":"aellis@usgs.gov","middleInitial":"M.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":893068,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Christopher G. 0000-0002-8075-4763","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":218439,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":893069,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Kathryn E.L. 0000-0002-7521-7875 kelsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-7521-7875","contributorId":173264,"corporation":false,"usgs":true,"family":"Smith","given":"Kathryn","email":"kelsmith@usgs.gov","middleInitial":"E.L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":893070,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jacobs, Jessica A. 0000-0001-5611-2093","orcid":"https://orcid.org/0000-0001-5611-2093","contributorId":333551,"corporation":false,"usgs":true,"family":"Jacobs","given":"Jessica","email":"","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":893071,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70250940,"text":"70250940 - 2024 - Recent increases in annual, seasonal, and extreme methane fluxes driven by changes in climate and vegetation in boreal and temperate wetland ecosystems","interactions":[],"lastModifiedDate":"2024-01-24T16:29:35.838861","indexId":"70250940","displayToPublicDate":"2024-01-21T10:28:42","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Recent increases in annual, seasonal, and extreme methane fluxes driven by changes in climate and vegetation in boreal and temperate wetland ecosystems","docAbstract":"<p><span>Climate warming is expected to increase global methane (CH</span><sub>4</sub><span>) emissions from wetland ecosystems. Although in&nbsp;situ eddy covariance (EC) measurements at ecosystem scales can potentially detect CH</span><sub>4</sub><span>&nbsp;flux changes, most EC systems have only a few years of data collected, so temporal trends in CH</span><sub>4</sub><span>&nbsp;remain uncertain. Here, we use established drivers to hindcast changes in CH</span><sub>4</sub><span>&nbsp;fluxes (FCH</span><sub>4</sub><span>) since the early 1980s. We trained a machine learning (ML) model on CH</span><sub>4</sub><span>&nbsp;flux measurements from 22 [methane-producing sites] in wetland, upland, and lake sites of the FLUXNET-CH</span><sub>4</sub><span>&nbsp;database with at least two full years of measurements across temperate and boreal biomes. The gradient boosting decision tree ML model then hindcasted daily FCH</span><sub>4</sub><span>&nbsp;over 1981–2018 using meteorological reanalysis data. We found that, mainly driven by rising temperature, half of the sites (</span><i>n</i><span> = 11) showed significant increases in annual, seasonal, and extreme FCH</span><sub>4</sub><span>, with increases in FCH</span><sub>4</sub><span>&nbsp;of ca. 10% or higher found in the fall from 1981–1989 to 2010–2018. The annual trends were driven by increases during summer and fall, particularly at high-CH</span><sub>4</sub><span>-emitting fen sites dominated by aerenchymatous plants. We also found that the distribution of days of extremely high FCH</span><sub>4</sub><span>&nbsp;(defined according to the 95th percentile of the daily FCH</span><sub>4</sub><span>&nbsp;values over a reference period) have become more frequent during the last four decades and currently account for 10–40% of the total seasonal fluxes. The share of extreme FCH</span><sub>4</sub><span>&nbsp;days in the total seasonal fluxes was greatest in winter for boreal/taiga sites and in spring for temperate sites, which highlights the increasing importance of the non-growing seasons in annual budgets. Our results shed light on the effects of climate warming on wetlands, which appears to be extending the CH</span><sub>4</sub><span>&nbsp;emission seasons and boosting extreme emissions.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.17131","usgsCitation":"Feron, S., Malhotra, A., Bansal, S., Fluet-Chouinard, E., McNicol, G., Knox, S., Delwiche, K., Cordero, R., Ouyang, Z., Zhang, Z., Poulter, B., and Jackson, R., 2024, Recent increases in annual, seasonal, and extreme methane fluxes driven by changes in climate and vegetation in boreal and temperate wetland ecosystems: Global Change Biology, v. 30, no. 1, e17131, 18 p., https://doi.org/10.1111/gcb.17131.","productDescription":"e17131, 18 p.","ipdsId":"IP-158799","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":440670,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.17131","text":"Publisher Index Page"},{"id":424864,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-01-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Feron, Sarah","contributorId":330045,"corporation":false,"usgs":false,"family":"Feron","given":"Sarah","affiliations":[{"id":78774,"text":"University of Groningen, Netherlands","active":true,"usgs":false}],"preferred":false,"id":892305,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malhotra, Avni","contributorId":330047,"corporation":false,"usgs":false,"family":"Malhotra","given":"Avni","affiliations":[{"id":37399,"text":"University of Zurich, Switzerland","active":true,"usgs":false}],"preferred":false,"id":892306,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bansal, Sheel 0000-0003-1233-1707 sbansal@usgs.gov","orcid":"https://orcid.org/0000-0003-1233-1707","contributorId":167295,"corporation":false,"usgs":true,"family":"Bansal","given":"Sheel","email":"sbansal@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":892307,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fluet-Chouinard, Etienne","contributorId":217392,"corporation":false,"usgs":false,"family":"Fluet-Chouinard","given":"Etienne","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":892308,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McNicol, Gavin 0000-0002-6655-8045","orcid":"https://orcid.org/0000-0002-6655-8045","contributorId":260536,"corporation":false,"usgs":false,"family":"McNicol","given":"Gavin","email":"","affiliations":[],"preferred":false,"id":892309,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knox, Sarah 0000-0003-2255-5835","orcid":"https://orcid.org/0000-0003-2255-5835","contributorId":167493,"corporation":false,"usgs":false,"family":"Knox","given":"Sarah","affiliations":[{"id":24725,"text":"Ecosystem Science Division, Department of Environmental Science","active":true,"usgs":false}],"preferred":false,"id":892310,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Delwiche, Kyle","contributorId":330044,"corporation":false,"usgs":false,"family":"Delwiche","given":"Kyle","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":892311,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cordero, Raul","contributorId":333264,"corporation":false,"usgs":false,"family":"Cordero","given":"Raul","email":"","affiliations":[],"preferred":false,"id":892312,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ouyang, Zutao","contributorId":260556,"corporation":false,"usgs":false,"family":"Ouyang","given":"Zutao","email":"","affiliations":[],"preferred":false,"id":892313,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Zhang, Zhen 0000-0003-0899-1139","orcid":"https://orcid.org/0000-0003-0899-1139","contributorId":149173,"corporation":false,"usgs":false,"family":"Zhang","given":"Zhen","email":"","affiliations":[],"preferred":false,"id":892314,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Poulter, Benjamin","contributorId":330088,"corporation":false,"usgs":false,"family":"Poulter","given":"Benjamin","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":892315,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jackson, Robert B.","contributorId":330089,"corporation":false,"usgs":false,"family":"Jackson","given":"Robert B.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":892316,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70251189,"text":"70251189 - 2024 - Modeling the response of an endangered rabbit population to RHDV2 and vaccination","interactions":[],"lastModifiedDate":"2024-02-26T16:10:41.674522","indexId":"70251189","displayToPublicDate":"2024-01-21T06:52:21","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the response of an endangered rabbit population to RHDV2 and vaccination","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Rabbit hemorrhagic disease virus 2 (RHDV2), recently detected in the western United States, has the potential to cause mass mortality events in wild rabbit and hare populations. Currently, few management strategies exist other than vaccination. We developed a spatially explicit model of RHDV2 for a population of riparian brush rabbits (<i>Sylvilagus bachmani riparius</i>), a subspecies of brush rabbit classified as endangered in the United States, on a subsection of the San Joaquin River National Wildlife Refuge. The goal of our model was to provide guidance regarding vaccination strategies for an endangered rabbit species. Our model predicts that increased interactions between rabbits (a proxy for landscape connectivity) and disease transmission rates among susceptible hosts (individual brush rabbits and conspecifics) have the greatest influence on the outcome of a potential vaccination campaign. Our model projects that across a range of parameter estimates (given an RHDV2 incursion), the median estimated population size with a 0%–10% vaccination rate after 1 year is 538 rabbits (95% Confidence Interval [C.I.] 69–1235), approximately 36% of the expected size of the study population of 1470 rabbits without an RHDV2 introduction. With a 10%–20%, 20%–30%, or 30%–40% vaccination rate, the median estimated population size increased to 628 rabbits (95% C.I. 130–1298), 723 rabbits (95% C.I. 198–1317), and 774 rabbits (95% C.I. 228–1410), respectively. These estimates represent 43%, 49%, and 53% of the expected population size without an RHDV2 introduction. Overall, a 1% increase in vaccination rate was associated with a six rabbit (95% C.I. 5–7) increase in total remaining population size. This result is dependent on assumptions regarding environmental transmission, home range size (and contact rates of rabbits). Given the relatively short lifespan of rabbits and the potential need for boosters, vaccination programs are most likely to be successful for small target populations where relatively high vaccination rates can be maintained.</p></div></div>","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/csp2.13072","usgsCitation":"Russell, R., Dusek, R.J., Prevost, S., Clifford, D.L., Moriarty, M., and Takahashi, F., 2024, Modeling the response of an endangered rabbit population to RHDV2 and vaccination: Conservation Science and Practice, v. 6, no. 2, e13072, 13 p., https://doi.org/10.1111/csp2.13072.","productDescription":"e13072, 13 p.","ipdsId":"IP-147761","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":440673,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.13072","text":"Publisher Index Page"},{"id":425015,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Joaquin River National Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -121.62025610096535,\n              37.8714544164978\n            ],\n            [\n              -121.62025610096535,\n              37.44731447957429\n            ],\n            [\n              -120.77127456488822,\n              37.44731447957429\n            ],\n            [\n              -120.77127456488822,\n              37.8714544164978\n            ],\n            [\n              -121.62025610096535,\n              37.8714544164978\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"6","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-01-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Russell, Robin 0000-0001-8726-7303","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":333621,"corporation":false,"usgs":false,"family":"Russell","given":"Robin","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":893401,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dusek, Robert J. 0000-0001-6177-7479 rdusek@usgs.gov","orcid":"https://orcid.org/0000-0001-6177-7479","contributorId":174374,"corporation":false,"usgs":true,"family":"Dusek","given":"Robert","email":"rdusek@usgs.gov","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":893402,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prevost, Stephanie","contributorId":333622,"corporation":false,"usgs":false,"family":"Prevost","given":"Stephanie","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":893403,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clifford, Deana L.","contributorId":333623,"corporation":false,"usgs":false,"family":"Clifford","given":"Deana","email":"","middleInitial":"L.","affiliations":[{"id":6952,"text":"California Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":893404,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moriarty, Megan","contributorId":333624,"corporation":false,"usgs":false,"family":"Moriarty","given":"Megan","affiliations":[{"id":6952,"text":"California Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":893405,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Takahashi, Fumika","contributorId":333625,"corporation":false,"usgs":false,"family":"Takahashi","given":"Fumika","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":893406,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70251492,"text":"70251492 - 2024 - Dynamic modeling of coastal compound flooding hazards due to tides, extratropical storms, waves, and sea-level rise: A case study in the Salish Sea, Washington (USA)","interactions":[],"lastModifiedDate":"2024-02-13T15:05:07.531397","indexId":"70251492","displayToPublicDate":"2024-01-20T08:57:58","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Dynamic modeling of coastal compound flooding hazards due to tides, extratropical storms, waves, and sea-level rise: A case study in the Salish Sea, Washington (USA)","docAbstract":"<p><span>The Puget Sound Coastal Storm Modeling System (PS-CoSMoS) is a tool designed to dynamically downscale future climate scenarios (i.e., projected changes in wind and pressure fields and temperature) to compute regional water levels, waves, and compound flooding over large geographic areas (100 s of kilometers) at high spatial resolutions (1 m) pertinent to coastal hazard assessments and planning. This research focuses on advancing robust and computationally efficient approaches to resolving the coastal compound flooding components for complex, estuary environments and their application to the Puget Sound region of Washington State (USA) and the greater Salish Sea. The modeling system provides coastal planners with projections of storm hazards and flood exposure for recurring flood events, spanning the annual to 1-percent annual chance of flooding, necessary to manage public safety and the prioritization and cost-efficient protection of critical infrastructure and valued ecosystems. The tool is applied and validated for Whatcom County, Washington, and includes a cross-shore profile model (XBeach) and overland flooding model (SFINCS) and is nested in a regional tide–surge model and wave model. Despite uncertainties in boundary conditions, hindcast simulations performed with the coupled model system accurately identified areas that were flooded during a recent storm in 2018. Flood hazards and risks are expected to increase exponentially as the sea level rises in the study area of 210 km of shoreline. With 1 m of sea-level rise, annual flood extents are projected to increase from 13 to 33 km</span><sup>2</sup><span>&nbsp;(5 and 13% of low-lying Whatcom County) and flood risk (defined in USD) is projected to increase fifteenfold (from 14 to USD 206 million). PS-CoSMoS, like its prior iteration in California (CoSMoS), provides valuable coastal hazard projections to help communities plan for the impacts of sea-level rise and storms.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/w16020346","usgsCitation":"Nederhoff, K., Crosby, S.C., vanArendonk, N.R., Grossman, E.E., Tehranirad, B., Leijnse, T., Klessens, W., and Barnard, P.L., 2024, Dynamic modeling of coastal compound flooding hazards due to tides, extratropical storms, waves, and sea-level rise: A case study in the Salish Sea, Washington (USA): Water, v. 16, no. 2, 346, 23 p., https://doi.org/10.3390/w16020346.","productDescription":"346, 23 p.","ipdsId":"IP-147555","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":440676,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w16020346","text":"Publisher Index Page"},{"id":425606,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","county":"Whatcom County","otherGeospatial":"Salish Sea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -123.1,\n              49.1\n            ],\n            [\n              -123.1,\n              48.6\n            ],\n            [\n              -122.4,\n              48.6\n            ],\n            [\n              -122.4,\n              49.1\n            ],\n            [\n              -123.1,\n              49.1\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"16","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-01-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Nederhoff, Kees 0000-0003-0552-3428","orcid":"https://orcid.org/0000-0003-0552-3428","contributorId":334091,"corporation":false,"usgs":false,"family":"Nederhoff","given":"Kees","affiliations":[{"id":39963,"text":"Deltares-USA","active":true,"usgs":false}],"preferred":true,"id":894711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crosby, Sean C. 0000-0002-1499-6836","orcid":"https://orcid.org/0000-0002-1499-6836","contributorId":219466,"corporation":false,"usgs":false,"family":"Crosby","given":"Sean","email":"","middleInitial":"C.","affiliations":[{"id":40000,"text":"Contractor, USGS","active":true,"usgs":false}],"preferred":false,"id":894712,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"vanArendonk, Nathan R. 0000-0003-3911-995X","orcid":"https://orcid.org/0000-0003-3911-995X","contributorId":219469,"corporation":false,"usgs":false,"family":"vanArendonk","given":"Nathan","email":"","middleInitial":"R.","affiliations":[{"id":12723,"text":"Western Washington University","active":true,"usgs":false}],"preferred":false,"id":894713,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grossman, Eric E. 0000-0003-0269-6307 egrossman@usgs.gov","orcid":"https://orcid.org/0000-0003-0269-6307","contributorId":196610,"corporation":false,"usgs":true,"family":"Grossman","given":"Eric","email":"egrossman@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":894714,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tehranirad, Babak 0000-0002-1634-9165","orcid":"https://orcid.org/0000-0002-1634-9165","contributorId":299107,"corporation":false,"usgs":false,"family":"Tehranirad","given":"Babak","affiliations":[{"id":64774,"text":"contracted to USGS PCMSC","active":true,"usgs":false}],"preferred":false,"id":894715,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leijnse, T.","contributorId":334101,"corporation":false,"usgs":false,"family":"Leijnse","given":"T.","email":"","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":894716,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Klessens, W.","contributorId":334103,"corporation":false,"usgs":false,"family":"Klessens","given":"W.","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":894717,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":140982,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":894718,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70263933,"text":"70263933 - 2024 - Linking avian malaria parasitemia estimates from quantitative PCR and microscopy reveals new infection patterns in Hawai'i","interactions":[],"lastModifiedDate":"2025-02-28T15:45:57.891687","indexId":"70263933","displayToPublicDate":"2024-01-19T09:41:54","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2024,"text":"International Journal for Parasitology","active":true,"publicationSubtype":{"id":10}},"title":"Linking avian malaria parasitemia estimates from quantitative PCR and microscopy reveals new infection patterns in Hawai'i","docAbstract":"<p><i>Plasmodium</i><span>&nbsp;parasites infect thousands of species and provide an exceptional system for studying host-pathogen dynamics, especially for multi-host pathogens. However, understanding these interactions requires an accurate assay of infection. Assessing&nbsp;</span><i>Plasmodium</i><span>&nbsp;infections using microscopy on blood smears often misses infections with low parasitemias (the fractions of cells infected), and biases in malaria prevalence estimates will differ among hosts that differ in mean parasitemias. We examined&nbsp;</span><i>Plasmodium relictum</i><span>&nbsp;infection and parasitemia using both microscopy of blood smears and quantitative polymerase chain reaction (qPCR) on 299 samples from multiple bird species in Hawai'i and fit models to predict parasitemias from qPCR cycle threshold (Ct) values. We used these models to quantify the extent to which microscopy underestimated infection prevalence and to more accurately estimate infection patterns for each species for a large historical study done by microscopy. We found that most qPCR-positive wild-caught birds in Hawaii had low parasitemias (Ct scores ≥35), which were rarely detected by microscopy. The fraction of infections missed by microscopy differed substantially among eight species due to differences in species’ parasitemia levels. Infection prevalence was likely 4–5-fold higher than previous microscopy estimates for three introduced species, including&nbsp;</span><i>Zosterops japonicus</i><span>, Hawaii’s most abundant forest bird, which had low average parasitemias. In contrast, prevalence was likely only 1.5–2.3-fold higher than previous estimates for&nbsp;</span><i>Himatione sanguinea</i><span>&nbsp;and&nbsp;</span><i>Chlorodrepanis virens</i><span>, two native species with high average parasitemias. Our results indicate that relative patterns of infection among species differ substantially from those observed in previous microscopy studies, and that differences depend on variation in parasitemias among species. Although microscopy of blood smears is useful for estimating the frequency of different&nbsp;</span><i>Plasmodium</i><span>&nbsp;stages and host attributes, more sensitive quantitative methods, including qPCR, are needed to accurately estimate and compare infection prevalence among host species.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijpara.2023.10.001","usgsCitation":"Seidi, C., Ferreira, F.C., Parise, K., Paxton, K.L., Paxton, E.H., Atkinson, C., Fleischer, R., Foster, J., and Kipatrick, A., 2024, Linking avian malaria parasitemia estimates from quantitative PCR and microscopy reveals new infection patterns in Hawai'i: International Journal for Parasitology, v. 54, no. 2, p. 123-130, https://doi.org/10.1016/j.ijpara.2023.10.001.","productDescription":"8 p.","startPage":"123","endPage":"130","ipdsId":"IP-155137","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":489967,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ijpara.2023.10.001","text":"Publisher Index Page"},{"id":482641,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70251160,"text":"70251160 - 2024 - Temporal variability in irrigated land and climate influences on salinity loading across the Upper Colorado River Basin, 1986-2017","interactions":[],"lastModifiedDate":"2024-01-25T12:55:51.096512","indexId":"70251160","displayToPublicDate":"2024-01-19T06:52:26","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Temporal variability in irrigated land and climate influences on salinity loading across the Upper Colorado River Basin, 1986-2017","docAbstract":"<div class=\"article-text wd-jnl-art-abstract cf\"><p>Freshwater salinization is a growing global concern impacting human and ecosystem needs with impacts to water availability for human and ecological uses. In the Upper Colorado River Basin (UCRB), dissolved solids in streams compound ongoing water supply challenges to further limit water availability and cause economic damages. Much effort has been dedicated to understanding dissolved solid sources, transport, and management in the region, yet temporal variability in loading from key sources such as irrigated lands and the influence of climate on dissolved solids loading remains unknown. Quantifying the contributions and temporal variability of dissolved solids loads from irrigated lands may benefit salinity management efforts. This study applies a time-varying (dynamic) modeling approach to predict annual dissolved solids loads across the UCRB from 1986 through 2017. Between 66% and 82% of the total accumulated dissolved solids load in the basin is from groundwater (storage and baseflow). Our findings link climate, irrigation, and groundwater, and confirm large storage contributions that have declined slightly with time. Dissolved solids loads increase during wet periods and decrease during dry periods, although the relative contributions of different sources vary little with time. Irrigation enhances loading efficiency relative to unirrigated areas through runoff and groundwater, and can locally be a major source of dissolved solids where irrigation occurs. Results indicate that loads from irrigated areas increase when irrigated area and/or water available for runoff increase. Increased regional aridification over the study period may have contributed to decreasing stream salinity through both quicker surface runoff and lagged groundwater storage processes. Study results may be relevant to salinity management in arid environments where water availability is limited and where irrigation influences salinity loading to streams.</p></div>","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/ad18dd","usgsCitation":"Miller, O.L., Putman, A.L., Smith, R.A., Schwarz, G.E., Hess, M.D., McDonnell, M.C., and Jones, D.K., 2024, Temporal variability in irrigated land and climate influences on salinity loading across the Upper Colorado River Basin, 1986-2017: Environmental Research Letters, v. 19, no. 2, 024008, 14 p., https://doi.org/10.1088/1748-9326/ad18dd.","productDescription":"024008, 14 p.","ipdsId":"IP-147816","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":440686,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ad18dd","text":"Publisher Index Page"},{"id":424946,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -113.17543892334504,\n              43.880984170983\n            ],\n            [\n              -113.17543892334504,\n              34.505329700284875\n            ],\n            [\n              -104.86977486084497,\n              34.505329700284875\n            ],\n            [\n              -104.86977486084497,\n              43.880984170983\n            ],\n            [\n              -113.17543892334504,\n              43.880984170983\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"19","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-01-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Olivia L. 0000-0002-8846-7048","orcid":"https://orcid.org/0000-0002-8846-7048","contributorId":216556,"corporation":false,"usgs":true,"family":"Miller","given":"Olivia","email":"","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":893300,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Putman, Annie L. 0000-0002-9424-1707","orcid":"https://orcid.org/0000-0002-9424-1707","contributorId":225134,"corporation":false,"usgs":true,"family":"Putman","given":"Annie","email":"","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":893301,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Richard A. 0000-0003-2117-2269 rsmith1@usgs.gov","orcid":"https://orcid.org/0000-0003-2117-2269","contributorId":580,"corporation":false,"usgs":true,"family":"Smith","given":"Richard","email":"rsmith1@usgs.gov","middleInitial":"A.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":893302,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schwarz, Gregory E. 0000-0002-9239-4566 gschwarz@usgs.gov","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":213621,"corporation":false,"usgs":true,"family":"Schwarz","given":"Gregory","email":"gschwarz@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":893303,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hess, Michael D. 0000-0002-9958-9163","orcid":"https://orcid.org/0000-0002-9958-9163","contributorId":216504,"corporation":false,"usgs":true,"family":"Hess","given":"Michael","email":"","middleInitial":"D.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":893304,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McDonnell, Morgan C. 0000-0001-6946-9286","orcid":"https://orcid.org/0000-0001-6946-9286","contributorId":296906,"corporation":false,"usgs":true,"family":"McDonnell","given":"Morgan","email":"","middleInitial":"C.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":893305,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jones, Daniel K. 0000-0003-0724-8001 dkjones@usgs.gov","orcid":"https://orcid.org/0000-0003-0724-8001","contributorId":4959,"corporation":false,"usgs":true,"family":"Jones","given":"Daniel","email":"dkjones@usgs.gov","middleInitial":"K.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":893306,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70250850,"text":"ofr20231081 - 2024 - Water-level change from a multiple-well aquifer test in volcanic rocks, Umatilla Indian Reservation near Mission, northeastern Oregon, 2016","interactions":[],"lastModifiedDate":"2026-01-28T17:35:11.290065","indexId":"ofr20231081","displayToPublicDate":"2024-01-18T15:29:15","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1081","displayTitle":"Water-Level Change from a Multiple-Well Aquifer Test in Volcanic Rocks, Umatilla Indian Reservation near Mission, Northeastern Oregon, 2016","title":"Water-level change from a multiple-well aquifer test in volcanic rocks, Umatilla Indian Reservation near Mission, northeastern Oregon, 2016","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the Confederated Tribes of the Umatilla Indian Reservation (CTUIR), (1) estimated water-level change from a multiple-well aquifer test centered on CTUIR well number 422 and (2) evaluated hydraulic connections between the pumping and observation wells on the Umatilla Indian Reservation near Mission, northeastern Oregon to improve the understanding of aquifer characteristics and hydrologic flow boundaries. Water-level changes, or pumping responses, were determined by distinguishing the pumping signal from environmental fluctuations in groundwater levels using analytical water-level models. The pumping well produces water from basalt units from a depth of 450 to 1,057 feet below land surface and was intermittently pumped during February 1–April 18, 2016. Water-level responses to pumping were estimated in the pumping well and in seven observation wells within 4 miles (mi) of the pumping well. The observation wells are open to basalt and some observation wells are either separated from the pumping well by faults and other structural features, within structural zones, or adjacent to structural features. Pumping responses at the observation wells were classified as detected in two wells, ambiguous in one well, and not detected in four wells. Observation-well open-interval elevations overlapped with the pumping-well open interval in both wells with detected pumping responses. Observation wells with detections are 1.8 mi east of the pumping well and across a fault, and 1.4 mi south of the pumping well. The pumping response was classified as ambiguous in an observation well located 1.4 mi west of the pumping well, where the dip of the basalt unit steepens, and adjacent to the Agency syncline. Pumping responses were not detected in observation wells within 0.3 mi of the pumping well where observation-well open-interval elevations are above the top of the pumping well open interval. Analysis of pumping responses indicates (1) a more permeable zone of basalt is adjacent to the lower portion of the pumping-well open interval and extends eastward, (2) basalt adjacent to the upper portion of the pumping-well open-interval is less permeable than the lower portion or separated from the lower portion by a less permeable zone, and (or) (3) a less permeable zone limits vertical hydraulic connectivity between the pumping well and the overlying basalt.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231081","collaboration":"Prepared in cooperation with Confederated Tribes of the Umatilla Indian Reservation","usgsCitation":"Garcia, C.A., Kennedy, J.J., and Ely, K., 2024, Water-level change from a multiple-well aquifer test in volcanic rocks, Umatilla Indian Reservation near Mission, northeastern Oregon, 2016: U.S. Geological Survey Open-File Report 2023–1081, 16 p., https://doi.org/10.3133/ofr20231081.","productDescription":"Report: vii, 16 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-149402","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":499191,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115942.htm","linkFileType":{"id":5,"text":"html"}},{"id":424231,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1081/ofr20231081.XML"},{"id":424229,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q1122I","text":"USGS data release","description":"USGS data release","linkHelpText":"Multiple-well aquifer-test data and results, Umatilla Indian Reservation near Mission, northeastern Oregon"},{"id":424228,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231081/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1081"},{"id":424227,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1081/ofr20231081.pdf","text":"Report","size":"3.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1081"},{"id":424230,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1081/images"},{"id":424226,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1081/ofr20231081.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Umatilla Indian Reservation","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -118.5,\n              45.44\n            ],\n            [\n              -118.5,\n              45.36\n            ],\n            [\n              -118.36,\n              45.36\n            ],\n            [\n              -118.36,\n              45.44\n            ],\n            [\n              -118.5,\n              45.44\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_or@usgs.gov\" data-mce-href=\"mailto:dc_or@usgs.gov\">Director</a> , <a href=\"https://www.usgs.gov/centers/oregon-water-science-center\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/oregon-water-science-center\">Oregon Water Science Center</a><br>U.S. Geological Survey<br>601 SW 2nd Avenue, Suite 1950<br>Portland, OR 97204</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Description of Monitoring Network</li><li>Hydrogeology</li><li>Data Collection</li><li>Later-Level Modeling and Pumping Response</li><li>Estimation</li><li>Summary</li><li>References Cited</li></ul>","publishedDate":"2024-01-18","noUsgsAuthors":false,"publicationDate":"2024-01-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Garcia, C. Amanda 0000-0003-3776-3565 cgarcia@usgs.gov","orcid":"https://orcid.org/0000-0003-3776-3565","contributorId":1899,"corporation":false,"usgs":true,"family":"Garcia","given":"C.","email":"cgarcia@usgs.gov","middleInitial":"Amanda","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennedy, Joseph J. 0000-0002-6608-2366","orcid":"https://orcid.org/0000-0002-6608-2366","contributorId":333051,"corporation":false,"usgs":false,"family":"Kennedy","given":"Joseph J.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":891782,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ely, Kate","contributorId":192464,"corporation":false,"usgs":false,"family":"Ely","given":"Kate","affiliations":[{"id":13345,"text":"Confederated Tribes of the Umatilla Indian Reservation","active":true,"usgs":false}],"preferred":false,"id":891783,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70254146,"text":"70254146 - 2024 - Constraining magma storage conditions of the Toba magmatic system: A plagioclase and amphibole perspective","interactions":[],"lastModifiedDate":"2024-05-09T12:11:44.614027","indexId":"70254146","displayToPublicDate":"2024-01-18T07:09:18","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1336,"text":"Contributions to Mineralogy and Petrology","active":true,"publicationSubtype":{"id":10}},"title":"Constraining magma storage conditions of the Toba magmatic system: A plagioclase and amphibole perspective","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Silicic magma reservoirs are responsible for producing the largest explosive eruptions in the geologic record. Petrologic and geochronological data provide evidence for these systems spending substantial periods of time (10<sup>4</sup>–10<sup>5</sup>&nbsp;yrs) within the upper crust prior to eruption; however, the long-term thermochemical evolution of these systems is not fully understood, as existing petrologic data make it challenging to quantify the time interval a magmatic system has spent at certain temperatures, or its “thermal history”. Here, we investigate the 74&nbsp;ka Youngest Toba Tuff (YTT), one of the largest explosive eruptions in the geologic record, to better constrain the long-term thermal evolution of its magmatic system. We combine forward models of Sr diffusion in plagioclase and hornblende, mineral thermometry, and pre-existing trace-element evolution models to quantify the thermochemical evolution of the YTT magmatic system. We find that plagioclase crystals record decades to centuries of storage at temperatures<span>&nbsp;</span><span id=\"MathJax-Element-1-Frame\" class=\"MathJax_SVG\"></span>750&nbsp;<span id=\"MathJax-Element-2-Frame\" class=\"MathJax_SVG\"></span>C, while hornblende records up to 6200&nbsp;years at the same temperatures. Hornblende crystallizes at temperatures around 820&nbsp;<span id=\"MathJax-Element-3-Frame\" class=\"MathJax_SVG\"></span>C and adjusting our diffusion modeling to this temperature results in no more than 900&nbsp;years at initial crystallization conditions. Combined with previous trace-element modeling work, these results indicate that although there was chemical diversity for long durations in the YTT magma system sufficient to produce unique composition eruptive products, the entire system was experiencing a relatively similar thermal history that did not allow for large bodies of eruptible magma to be present for long periods (<span id=\"MathJax-Element-4-Frame\" class=\"MathJax_SVG\"></span><span>&nbsp;</span>10<sup>2</sup>–10<sup>3</sup>&nbsp;years). Rather, we suggest that magmas within the YTT magmatic system were stored for long durations at thermal conditions where they were uneruptible and only remobilized within a few centuries prior to eruption.</p></div></div>","language":"English","publisher":"Springer Nature","doi":"10.1007/s00410-023-02089-7","usgsCitation":"Lubbers, J.E., Kent, A.J., and de Silva, S., 2024, Constraining magma storage conditions of the Toba magmatic system: A plagioclase and amphibole perspective: Contributions to Mineralogy and Petrology, v. 179, 12, 15 p., https://doi.org/10.1007/s00410-023-02089-7.","productDescription":"12, 15 p.","ipdsId":"IP-157051","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":428586,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Indonesia","otherGeospatial":"Sumatra","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              97.90796819323884,\n              3.4920463781608646\n            ],\n            [\n              97.90796819323884,\n              1.7800567155424005\n            ],\n            [\n              99.90747991198981,\n              1.7800567155424005\n            ],\n            [\n              99.90747991198981,\n              3.4920463781608646\n            ],\n            [\n              97.90796819323884,\n              3.4920463781608646\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"179","noUsgsAuthors":false,"publicationDate":"2024-01-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Lubbers, Jordan Edward 0000-0002-3566-5091","orcid":"https://orcid.org/0000-0002-3566-5091","contributorId":330466,"corporation":false,"usgs":true,"family":"Lubbers","given":"Jordan","email":"","middleInitial":"Edward","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":900422,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kent, Adam J.R.","contributorId":292680,"corporation":false,"usgs":false,"family":"Kent","given":"Adam","email":"","middleInitial":"J.R.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":900423,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"de Silva, Shanaka","contributorId":206802,"corporation":false,"usgs":false,"family":"de Silva","given":"Shanaka","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":900424,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70251364,"text":"70251364 - 2024 - Intrinsic and extrinsic regulation of water clarity in a large, floodplain-river ecosystem","interactions":[],"lastModifiedDate":"2024-04-23T15:15:32.981503","indexId":"70251364","displayToPublicDate":"2024-01-18T06:37:44","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Intrinsic and extrinsic regulation of water clarity in a large, floodplain-river ecosystem","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Ecosystem processes in rivers are thought to be controlled more by extrinsic than intrinsic factors, that is, the result of processes that occur upstream or within their watersheds. However, large floodplain rivers have a diverse assemblage of aquatic areas spanning gradients of connectivity with the main channel and internal controls may at times regulate long-term dynamics. When and where internal controls are important has not been widely explored in rivers. The Upper Mississippi River System (UMRS) provides a unique opportunity to assess regulation of ecosystem processes in a large floodplain river as water clarity has increased in several reaches over the last two decades. To better understand when and where intrinsic variables (for example<i>,</i><span>&nbsp;</span>aquatic vegetation and common carp) and extrinsic variables (for example<i>,</i><span>&nbsp;</span>upstream main channel total suspended solids (TSS) concentration and discharge) regulate water clarity, we describe 24-year trends of TSS in six study reaches of the UMRS. We evaluated the degree to which trends were shared across aquatic areas within each study reach and identified potential drivers of long-term TSS dynamics. Results varied across and within UMRS reaches, but common carp abundance was the strongest predictor in nearly all study reaches. Several models indicated associations with both intrinsic and extrinsic factors, and the marginal model<span>&nbsp;</span><i>r</i><sup>2</sup><span>&nbsp;</span>values (0.26–0.61) suggest that additional environmental factors may have influenced water clarity. Knowledge of the degree to which intrinsic and extrinsic processes regulate water clarity is important for understanding and managing large, floodplain rivers worldwide.</p></div></div>","language":"English","publisher":"Springer Nature","doi":"10.1007/s10021-023-00895-5","usgsCitation":"Carhart, A., Drake, D.C., Fischer, J.R., Houser, J.N., Jankowski, K.J., Kalas, J.E., and Lund, E.M., 2024, Intrinsic and extrinsic regulation of water clarity in a large, floodplain-river ecosystem: Ecosystems, v. 27, p. 395-413, https://doi.org/10.1007/s10021-023-00895-5.","productDescription":"19 p.","startPage":"395","endPage":"413","ipdsId":"IP-154464","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":425462,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -92.4556475999726,\n              44.11793587169143\n            ],\n            [\n              -92.4556475999726,\n              39.2309522838064\n            ],\n            [\n              -89.46736634997285,\n              39.2309522838064\n            ],\n            [\n              -89.46736634997285,\n              44.11793587169143\n            ],\n            [\n              -92.4556475999726,\n              44.11793587169143\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"27","noUsgsAuthors":false,"publicationDate":"2024-01-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Carhart, Alicia 0000-0002-9977-8124","orcid":"https://orcid.org/0000-0002-9977-8124","contributorId":223884,"corporation":false,"usgs":false,"family":"Carhart","given":"Alicia","email":"","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":894275,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Drake, Deanne C.","contributorId":207846,"corporation":false,"usgs":false,"family":"Drake","given":"Deanne","email":"","middleInitial":"C.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":894276,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fischer, James R.","contributorId":333909,"corporation":false,"usgs":false,"family":"Fischer","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":894277,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Houser, Jeffrey N. 0000-0003-3295-3132 jhouser@usgs.gov","orcid":"https://orcid.org/0000-0003-3295-3132","contributorId":2769,"corporation":false,"usgs":true,"family":"Houser","given":"Jeffrey","email":"jhouser@usgs.gov","middleInitial":"N.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":894278,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jankowski, Kathi Jo 0000-0002-3292-4182","orcid":"https://orcid.org/0000-0002-3292-4182","contributorId":207429,"corporation":false,"usgs":true,"family":"Jankowski","given":"Kathi","email":"","middleInitial":"Jo","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":894279,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kalas, John E.","contributorId":333910,"corporation":false,"usgs":false,"family":"Kalas","given":"John","email":"","middleInitial":"E.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":894280,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lund, Eric M.","contributorId":291763,"corporation":false,"usgs":false,"family":"Lund","given":"Eric","email":"","middleInitial":"M.","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":894281,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70263628,"text":"70263628 - 2024 - The 1886 Charleston, South Carolina, earthquake: Intensities and ground motions","interactions":[],"lastModifiedDate":"2025-02-19T16:18:40.303665","indexId":"70263628","displayToPublicDate":"2024-01-17T10:14:41","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"The 1886 Charleston, South Carolina, earthquake: Intensities and ground motions","docAbstract":"<p><span>The 1 September 1886 Charleston, South Carolina, earthquake was one of the largest preinstrumental earthquakes in eastern North America for which extensive contemporaneous observations were documented. The distribution of shaking was mapped shortly after the earthquake, and reconsidered by several authors in the late twentieth century, but has not been reconsidered with a modern appreciation for issues associated with macroseismic data interpretation. Detailed contemporary accounts have also never been used to map the distribution of numerical shaking intensities in the near field. In this study we reconsider macroseismic data from far‐field accounts as well as detailed accounts of damage in the near field, estimating modified Mercalli intensity values at 1297 locations including over 200 definite “not felt” reports that delineate the overall felt extent. We compare the results to the suite of ground‐motion models for eastern North America selected by the National Seismic Hazard Model, using a recently proposed mainshock rupture model and an average site condition for the locations at which intensities are estimated. The comparison supports the moment magnitude estimate, 7.3, from a recently proposed rupture model (</span><a class=\"link link-ref xref-bibr\" data-modal-source-id=\"rf7\">Bilham and Hough, 2023</a><span>). A ShakeMap constrained by model predictions and estimated intensities further illustrates this consistency, which we show is insensitive to rupture model details. Given the uncertainty of calibration relations for magnitudes close to 7, the overall intensity distribution provides a good characterization of shaking but cannot improve the independent moment magnitude estimate. We also identify a previously unrecognized early large aftershock that occurred 9–10&nbsp;min after the mainshock, for which we estimate magnitude ∼5.6.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120230224","usgsCitation":"Hough, S.E., and Bilham, R., 2024, The 1886 Charleston, South Carolina, earthquake: Intensities and ground motions: Bulletin of the Seismological Society of America, v. 114, no. 3, p. 1658-1679, https://doi.org/10.1785/0120230224.","productDescription":"22 p.","startPage":"1658","endPage":"1679","ipdsId":"IP-157642","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482222,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Carolina","city":"Charleston","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -80.5,\n              33.3\n            ],\n            [\n              -80.5,\n              32.65\n            ],\n            [\n              -79.9,\n              32.65\n            ],\n            [\n              -79.9,\n              33.3\n            ],\n            [\n              -80.5,\n              33.3\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"114","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-01-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Hough, Susan E. 0000-0002-5980-2986 hough@usgs.gov","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":587,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"hough@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927605,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bilham, Roger","contributorId":225117,"corporation":false,"usgs":false,"family":"Bilham","given":"Roger","affiliations":[{"id":13693,"text":"University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":927606,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70268354,"text":"70268354 - 2024 - Tropical forests and global change: Biogeochemical responses and opportunities for cross-site comparisons, an organized INSPIRE session at the 108th Annual Meeting, Ecological Society of America, Portland, Oregon, USA, August 2023","interactions":[],"lastModifiedDate":"2026-02-10T18:08:46.837428","indexId":"70268354","displayToPublicDate":"2024-01-17T09:42:37","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2863,"text":"New Phytologist","active":true,"publicationSubtype":{"id":10}},"title":"Tropical forests and global change: Biogeochemical responses and opportunities for cross-site comparisons, an organized INSPIRE session at the 108th Annual Meeting, Ecological Society of America, Portland, Oregon, USA, August 2023","docAbstract":"<p><span>Tropical forests play a critical role in the global carbon (C) cycle. These ecosystems maintain the highest rates of net primary production (NPP) on Earth (Hengl&nbsp;</span><i>et&nbsp;al</i><span>.,&nbsp;</span><span><a id=\"#nph19511-bib-0014_R_d6461774e632\" class=\"bibLink tab-link\" href=\"https://nph.onlinelibrary.wiley.com/doi/10.1111/nph.19511#nph19511-bib-0014\" data-tab=\"pane-pcw-references\" data-mce-href=\"https://nph.onlinelibrary.wiley.com/doi/10.1111/nph.19511#nph19511-bib-0014\">2017</a></span><span>), contain&nbsp;</span><i>c</i><span>. 30% of terrestrial C stocks (Jobbagy &amp; Jackson,&nbsp;</span><span><a id=\"#nph19511-bib-0020_R_d6461774e637\" class=\"bibLink tab-link\" href=\"https://nph.onlinelibrary.wiley.com/doi/10.1111/nph.19511#nph19511-bib-0020\" data-tab=\"pane-pcw-references\" data-mce-href=\"https://nph.onlinelibrary.wiley.com/doi/10.1111/nph.19511#nph19511-bib-0020\">2000</a></span><span>), and have some of the largest stores of fine-root biomass globally (Jackson&nbsp;</span><i>et&nbsp;al</i><span>.,&nbsp;</span><span><a id=\"#nph19511-bib-0019_R_d6461774e643\" class=\"bibLink tab-link\" href=\"https://nph.onlinelibrary.wiley.com/doi/10.1111/nph.19511#nph19511-bib-0019\" data-tab=\"pane-pcw-references\" data-mce-href=\"https://nph.onlinelibrary.wiley.com/doi/10.1111/nph.19511#nph19511-bib-0019\">1996</a></span><span>), as well as higher fine-root production and turnover rates compared with other biomes (Cusack&nbsp;</span><i>et&nbsp;al</i><span>.,&nbsp;</span><span><a id=\"#nph19511-bib-0007_R_d6461774e648\" class=\"bibLink tab-link\" href=\"https://nph.onlinelibrary.wiley.com/doi/10.1111/nph.19511#nph19511-bib-0007\" data-tab=\"pane-pcw-references\" data-mce-href=\"https://nph.onlinelibrary.wiley.com/doi/10.1111/nph.19511#nph19511-bib-0007\">2021</a></span><span>). Tropical forest responses to projected warming, altered rainfall regimes, and elevated CO</span><sub>2</sub><span>&nbsp;concentrations (IPCC,&nbsp;</span><span><a id=\"#nph19511-bib-0018_R_d6461774e653\" class=\"bibLink tab-link\" href=\"https://nph.onlinelibrary.wiley.com/doi/10.1111/nph.19511#nph19511-bib-0018\" data-tab=\"pane-pcw-references\" data-mce-href=\"https://nph.onlinelibrary.wiley.com/doi/10.1111/nph.19511#nph19511-bib-0018\">2021</a></span><span>) are likely to be different from other ecosystems because of their unique characteristics (Box&nbsp;</span><a class=\"featureLink scrollableLink\" title=\"Link to feature\" href=\"https://nph.onlinelibrary.wiley.com/doi/10.1111/nph.19511#nph19511-fea-0001\" data-mce-href=\"https://nph.onlinelibrary.wiley.com/doi/10.1111/nph.19511#nph19511-fea-0001\">1</a><span>), making targeted research and model development important for understanding tropical forest–climate feedbacks. There is now a critical mass of long-term global change field experiments and modeling efforts in tropical forests, yet thus far there has been little synthesis, cross-site comparison, or multi-site standardized experimentation among tropical forests to help us understand how these biomes are changing. An organized INSPIRE session at the 108</span><sup>th</sup><span>&nbsp;Annual Meeting of the Ecological Society of America set out to tackle just this. Speakers covered large-scale tropical forest field experiments and modeling efforts, with an emphasis on changes in ecosystem biogeochemistry under warming, drying, elevated atmospheric CO</span><sub>2</sub><span>, and changing nutrient status. In this Meeting report, we provide an overview of the large-scale global change experiments presented and highlight the main objectives and opportunities for tropical forest research that emerged, including cross-site comparisons and integration with ecosystem-scale models (Fig.&nbsp;</span><a href=\"https://nph.onlinelibrary.wiley.com/doi/10.1111/nph.19511#nph19511-fig-0001\" data-mce-href=\"https://nph.onlinelibrary.wiley.com/doi/10.1111/nph.19511#nph19511-fig-0001\">1</a><span>).</span></p>","language":"English","publisher":"New Phytologist Foundation","doi":"10.1111/nph.19511","usgsCitation":"Cusack, D.F., Reed, S., Andersen, K., Cinoğlu, D., Craig, M., Dietterich, L.H., Hogan, J., Holmes, J.A., Nottingham, A.T., Ostertag, R., Soper, F.M., Wood, T.E., and Wong, M., 2024, Tropical forests and global change: Biogeochemical responses and opportunities for cross-site comparisons, an organized INSPIRE session at the 108th Annual Meeting, Ecological Society of America, Portland, Oregon, USA, August 2023: New Phytologist, v. 241, no. 5, p. 1922-1926, https://doi.org/10.1111/nph.19511.","productDescription":"5 p.","startPage":"1922","endPage":"1926","ipdsId":"IP-158781","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":491102,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":491496,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/nph.19511","text":"External Repository"}],"volume":"241","issue":"5","noUsgsAuthors":false,"publicationDate":"2024-01-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Cusack, Daniela F. 0000-0003-4681-7449","orcid":"https://orcid.org/0000-0003-4681-7449","contributorId":245300,"corporation":false,"usgs":false,"family":"Cusack","given":"Daniela","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":941049,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":941050,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Andersen, Kelly M.","contributorId":357282,"corporation":false,"usgs":false,"family":"Andersen","given":"Kelly M.","affiliations":[{"id":85392,"text":"College of Science, Nanyang Technological University, Singapore","active":true,"usgs":false}],"preferred":false,"id":941051,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cinoğlu, Damla","contributorId":332640,"corporation":false,"usgs":false,"family":"Cinoğlu","given":"Damla","affiliations":[{"id":79539,"text":"The University of Texas at Austin, 2415 Speedway #C0930, Austin, TX 78712, USA","active":true,"usgs":false}],"preferred":false,"id":941052,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Craig, Matthew E.","contributorId":357283,"corporation":false,"usgs":false,"family":"Craig","given":"Matthew E.","affiliations":[{"id":85394,"text":"Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37830 USA","active":true,"usgs":false}],"preferred":false,"id":941053,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dietterich, Lee H.","contributorId":333170,"corporation":false,"usgs":false,"family":"Dietterich","given":"Lee","email":"","middleInitial":"H.","affiliations":[{"id":79766,"text":"Department of Ecosystem Science and Sustainability, Colorado State University, Fort Collins, CO 80523; US Army Engineer Research and Development Center, Environmental Laboratory, Vicksburg, MS 39180","active":true,"usgs":false}],"preferred":false,"id":941054,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hogan, J.A.","contributorId":357284,"corporation":false,"usgs":false,"family":"Hogan","given":"J.A.","affiliations":[{"id":85395,"text":"USDA Forest Service International Institute of Tropical Forestry, Río Piedras, PR 00926 USA","active":true,"usgs":false}],"preferred":false,"id":941055,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Holmes, Jennifer A.","contributorId":178159,"corporation":false,"usgs":false,"family":"Holmes","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":941056,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Nottingham, Andrew T.","contributorId":266049,"corporation":false,"usgs":false,"family":"Nottingham","given":"Andrew","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":941057,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ostertag, Rebecca","contributorId":197840,"corporation":false,"usgs":false,"family":"Ostertag","given":"Rebecca","email":"","affiliations":[],"preferred":false,"id":941058,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Soper, Fiona M.","contributorId":207085,"corporation":false,"usgs":false,"family":"Soper","given":"Fiona","email":"","middleInitial":"M.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":941059,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wood, Tana E.","contributorId":202372,"corporation":false,"usgs":false,"family":"Wood","given":"Tana","email":"","middleInitial":"E.","affiliations":[{"id":36399,"text":"International Institute of Tropical Forestry, USDA Forest Service, Rio Piedras, PR","active":true,"usgs":false}],"preferred":false,"id":941060,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Wong, Michelle Y.","contributorId":357285,"corporation":false,"usgs":false,"family":"Wong","given":"Michelle Y.","affiliations":[{"id":85396,"text":"Department of Ecology and Evolutionary Biology; Yale University, New Haven, CT 06511","active":true,"usgs":false}],"preferred":false,"id":941061,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70250915,"text":"ofr20231095 - 2024 - A machine learning tool for design of behavioral fish barriers in the Sacramento-San Joaquin River Delta","interactions":[],"lastModifiedDate":"2024-12-03T19:40:06.138265","indexId":"ofr20231095","displayToPublicDate":"2024-01-16T13:57:36","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1095","displayTitle":"A Machine Learning Tool for Design of Behavioral Fish Barriers in the Sacramento-San Joaquin River Delta","title":"A machine learning tool for design of behavioral fish barriers in the Sacramento-San Joaquin River Delta","docAbstract":"<h1>Executive Summary</h1><p>Survival of out-migrating juvenile salmonids (<i>Oncorhynchus</i> spp.) through the Sacramento-San Joaquin River Delta averages less than 33 percent, depending on water flow through the delta, and is partially governed by the distribution of fish among three Sacramento River distributaries: Sutter, Steamboat, and Georgiana sloughs. Behavioral altering structures in the junctions of the distributaries can effectively increase entrainment into favorable routes, thereby increasing through-delta (Verona to Chips Island, California) survival. The effectiveness of these structures, hence forth called “behavioral barriers,” are dependent on shape, length, location, barrier type, and water velocity, which is governed by Sacramento River discharge (hereinafter referred to as “flow”).</p><p>We developed a machine learning tool to optimize behavioral barrier designs at up to three junctions within the Sacramento-San Joaquin Delta for improving through-delta survival of juvenile winter-run Chinook salmon (<i>Oncorhynchus tshawytscha</i>). This barrier optimization tool (BOT) works by evolving barrier solutions in one to three junctions by repeatedly simulating survival of populations of Sacramento River origin fish as they pass through the Delta. Over approximately 6,000 simulations per junction, the BOT converges on barrier designs that result in the greatest average survival given simulated environmental conditions. Survival at each iteration of the model is simulated using a modified version of the salmon travel time and routing simulation (STARS) model. In the BOT, STARS is modified by replacing probabilistic route determinations with an individual based model (IBM) that simulates fish behavior to predict the entrainment rates in each junction. The IBM allows the flexibility to explore how entrainment changes with evolving barrier designs. We used juvenile winter-run-sized Chinook salmon catch data collected at Knights Landing from 1997 to 2011 to create realistic arrival and spatial distributions of simulated fish within the BOT that varied among water years (hereafter years). We demonstrated the capabilities of the BOT by comparing optimized barrier solutions and their resulting simulated improvement in survival among three scenarios that differed in the number of junctions with barriers (Georgiana Slough, Steamboat Slough, or both) and the barrier operational period (early: November 1–March 15, or late: January 1–April 30). In this initial demonstration of the BOT we only considered a bioacoustic fish fence (BAFF) at Georgiana Slough and a floating fish guidance structure (FFGS) at Steamboat Slough.</p><p>The increase in simulated through-delta fish survival ranged from 1.0 to 6.3 percent among the optimized barrier designs. The most effective Georgiana Slough barrier design predicted improved survival by 6.3 percent and was chosen by the California Department of Water Resources (DWR) as the Georgiana Slough salmon migratory barrier planned for operation annually from 2023 to 2030 at Georgiana Slough in response to the 2020 California Department of Fish and Wildlife’s (CDFW) Incidental Take Permit Minimization Measure 8.9.1 (California Department of Fish and Wildlife [CDFW], 2020). When barriers were simulated in both junctions, the percentages of simulated winter-run Chinook salmon interacting with a barrier at Steamboat or Georgiana sloughs were 95 percent given the early operational period and 48 percent given the late operational period. When barriers were simulated at both sloughs, the optimal barrier at Steamboat Slough effectively routed fish into the Sacramento River. This is because the Georgiana Slough barrier reduced routing into Georgiana Slough where survival is low, which resulted in higher survival for fish routed down the Sacramento River at Steamboat Slough than fish routed down Steamboat Slough. Whereas when no barrier was simulated at Georgiana Slough, the optimized barrier at Steamboat Slough routed fish into Steamboat Slough. This is because survival was higher through Steamboat Slough than the Sacramento River and Georgiana Slough combined. The greatest improvement in survival (6.3 percent) was predicted over the earlier operational period with only a barrier at Georgiana Slough.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231095","collaboration":"Prepared in cooperation with the California Department of Water Resources","usgsCitation":"Swyers, N.M., Blake, A., Stumpner, P., Burau, J.R., Burdick, S.M., and Anwar, M.S., 2024, A machine learning tool for design of behavioral fish barriers in the Sacramento-San Joaquin River Delta: U.S. Geological Survey Open-File Report 2023–1095, 38 p., https://doi.org/10.3133/ofr20231095.","productDescription":"ix, 38 p.","onlineOnly":"Y","ipdsId":"IP-151594","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":424660,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231095/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1095"},{"id":424362,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1095/images"},{"id":424363,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1095/ofr20231095.XML"},{"id":424359,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1095/ofr20231095.jpg"},{"id":424360,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1095/ofr20231095.pdf","text":"Report","size":"9.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1095"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin River Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n       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,{"id":70250959,"text":"ofr20231087 - 2024 - Physics to fish—Understanding the factors that create and sustain native fish habitat in the San Francisco Estuary","interactions":[],"lastModifiedDate":"2026-01-28T17:42:49.415587","indexId":"ofr20231087","displayToPublicDate":"2024-01-16T08:06:53","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1087","displayTitle":"Physics to Fish: Understanding the Factors that Create and Sustain Native Fish Habitat in the San Francisco Estuary","title":"Physics to fish—Understanding the factors that create and sustain native fish habitat in the San Francisco Estuary","docAbstract":"<h1>Executive Summary</h1><p>The Bureau of Reclamation (Reclamation) operates the Central Valley Project (CVP), one of the nation’s largest water projects. Reclamation has an ongoing need to improve the scientific basis for adaptive management of the CVP and, by extension, joint operations with California’s State Water Project. The U.S. Geological Survey (USGS) works cooperatively with the Bureau of Reclamation to provide scientific support for the management of Reclamation’s CVP project. Major habitat restoration efforts and a new water-diversion point are planned to benefit delta smelt (<i>Hypomesus transpacificus</i>) and other species of concern while ensuring the reliability of water supply. In addition, various flow actions and management activities have been identified as possible methods to increase populations of delta smelt and salmonid (<i>Oncorhynchus</i> spp.) runs of concern. The overarching goal of this cooperative project was to provide Reclamation with the scientific information needed to evaluate the efficacy of ongoing and future adaptive management actions and to improve the scientific basis for more flexible CVP operations that would achieve water-supply reliability and fish protection. The research and monitoring described in this report comprises the period 2015–19 and focuses on management issues related to native fish species of concern, especially delta smelt. Conserving the delta smelt population while providing a reliable water supply is a primary management and policy issue in California.</p><p>Our approach for this cooperative project is based on the “physics to fish” concept, the idea that high-quality habitat is generated and sustained by the interaction between physical processes and the landscape. These interactions create a template for chemical and biological processes that can change across a variety of spatial and temporal scales. Following this concept, this project (hereafter referred to as “the physics to fish project”) included monitoring and studies of water flows, sediments, water quality, and invertebrate and fish dynamics across a range of spatial and temporal scales and in regions relevant to resource managers tasked with managing water supplies and ecosystem health in the San Francisco Estuary. The intent of this approach was to document the habitat conditions, important processes, and interactions among them that create high-quality habitat for native fishes so that the likely effects of future management actions (for example, habitat restoration) can be objectively assessed at the local (site-specific), regional (within subregions of the estuary), and landscape (across the entire estuary and beyond) scales.</p><p>Hydrodynamically, the upper estuary (landward of Carquinez Strait) is characterized by a fixed volume of tidally exchanged water (for example, tidal prism) that interacts with the existing channel network and bathymetry to create regions with differing hydrodynamics. Our results indicate that careful study of construction or reoperation of existing infrastructure to perform management actions can help (1) improve the accuracy of hydrodynamic models; (2) further understanding of ecological effects; and (3) enhance abilities to predict ecological outcomes. At the local scale, we developed a new concept called the Lagrangian to Eulerian (LE) ratio that can be used as a tool for understanding the importance of various hydrodynamic processes in specific channels or channel networks and for forecasting transport dynamics. Channels with LE ratios&lt;1 in a channel network or in a dead-end slough are hydrodynamically able to develop an exchange zone between two parcels of water that may have different chemical and physical properties. In a dead-end channel, there is a landward region with long residence time (no-exchange zone) and a seaward region with short residence time (high-exchange zone) that are well mixed with seaward waters. At the transition (exchange zone) between the high and no-exchange regions, a gradient will form in water-quality constituents that differ in concentration between the landward and seaward waters.</p><p>Turbidity affects fish habitat and has declined through time in the San Francisco Estuary. Average turbidity across the Sacramento–San Joaquin Delta (hereafter referred to as “the Delta”) is dependent on annual hydrology. In dry years, the region around Cache Slough (known regionally as the “Cache Slough Complex”) in the northern Delta is generally more turbid than Suisun Bay and the lower Sacramento River. When the Yolo By-Pass (known regionally as “Yolo Bypass”), a large flood bypass that runs parallel to the Sacramento River in the northern Delta, is not flooding and river flows are lower, sediment is usually transported into the Cache Slough Complex because flood tides dominate ebb tides, resulting in transport of suspended sediment from seaward areas of the upper estuary into the Cache Slough Complex. These hydrodynamic conditions also favor the formation of turbidity maximums (TMs) in the Cache Slough Complex. The TMs are areas of higher suspended-sediment concentration, providing higher-turbidity habitat favored by some fishes, including delta smelt, and they can also concentrate other constituents, including phytoplankton and organic carbon that can be important in food webs.</p><p>Pelagic primary production by phytoplankton is the basis for Delta food webs supporting pelagic fishes such as delta smelt; however, phytoplankton abundance in the Delta has declined during recent decades. We examined how nutrients, hydrodynamics, and other factors affect phytoplankton blooms. Based on our results, we developed three new concepts of phytoplankton bloom formation in the Delta, each associated with a distinct set of hydrologic conditions. First, productivity cascades highlighted how local processes can contribute to phytoplankton blooms observed at the regional scale. Second, we observed phytoplankton blooms in the upper San Francisco Estuary that were associated with transport out of Yolo By-Pass (transport blooms). Third, we also documented a series of phytoplankton blooms that were in the confluence area at the landward edge of Suisun Bay. The conditions leading to creation of confluence phytoplankton blooms are not yet understood, but the confluence region connects the Cache Slough Complex with Suisun Marsh. Therefore, blooms in this area have the potential to spread to large areas of the Delta.</p><p>At the landscape scale, the distribution of the invasive clams (<i>Potamocorbula amurensis</i> and <i>Corbicula fluminea</i>, hereafter referred to as “<i>Corbicula</i>”) is driven by salinity. At smaller spatial scales, the distribution of either species is sensitive to multiple factors affecting survival and reproduction, complicating efforts to predict distribution and abundance without considering local-scale conditions across the area of interest. In the Cache Slough Complex, the area landward of the exchange zone in regions with LE ratio&lt;1 were characterized by low abundances of <i>Corbicula</i> probably because recruits from seaward areas are not transported past the exchange zone and because there are no landward tributaries with adult <i>Corbicula</i> to provide an upstream source of recruits. <i>Corbicula</i> biomass was highest near or downstream from the exchange zone consistent with <i>Corbicula</i> grazing on phytoplankton produced in the exchange zone or transported from the no-exchange zone. The severity of <i>Corbicula</i> grazing could be reduced by manipulating the hydrodynamic characteristics of waterways; however, the beneficial and harmful effects on the organisms meant to benefit from increased phytoplankton production, including zooplankton and fish species of concern, should be thoroughly examined before manipulating hydrodynamic characteristics.</p><p>The distribution of fishes at the landscape scale is generally driven by the position of the salinity field in the estuary. The physics to fish project compared distributions of fishes at Ryer Island, a tidal wetland in Suisun Bay and a region of variable salinity, with fish distributions at the Cache Slough Complex, a freshwater region. At Ryer Island, there was an absence of freshwater invasive species and an abundance of native species, such as Sacramento splittail (<i>Pogonichthys macrolepidotus</i>), tule perch (<i>Hysterocarpus traskii</i>), and Sacramento pikeminnow (<i>Ptychocheilus grandis</i>). The native species were almost exclusively captured in wetland and nearshore shallow-water habitat regardless of water-quality conditions. In the Cache Slough Complex, our regional scale objective was to elucidate how hydrodynamic-physical habitat interactions drive fish-community structure. Our studies showed that dendritic channel systems were better able to support native species, while intertidal habitats supported those species best able to exploit the transient character of the habitat. Habitats upstream from the exchange zone were especially important in supporting high numbers of native fishes relative to within or downstream from the exchange zone. Many of the native species were associated with tidal marsh in the no-exchange zone. More pelagic-oriented, mobile species, such as Striped Bass (<i>Morone saxatilis</i>), threadfin shad (<i>Dorosoma petenense</i>), and Sacramento pikeminnow, were more affected by water-quality conditions, such as turbidity.</p><p>The physics to fish concept developed in this project provides a framework for designing individual projects and for considering the cumulative effects of multiple projects in a region, using the LE ratio as a guiding metric. The physics to fish concept may also provide a suitable framework for coordinating management actions. Tidal wetlands can function in several ways in the hydrodynamic framework. Relatively small tidal wetlands with short channel networks and with LE ratios&gt;1 are not able to maintain a landward no-exchange zone or an exchange zone. This likely means that any contributions to pelagic food webs would be limited to resources derived from wetland vegetation, which can include dissolved and particulate organic matter (detritus) and populations of consumers that can increase in abundance based on those resources. The fate of the contributed production from these channels depends on the characteristics of the receiving waters seaward of the tidal wetland. If these channels join a large system such as Suisun Bay, then any contribution is likely to be rapidly dispersed in the larger volume; however, the channel junction might provide a focal point for consumers, such as fishes, to congregate and feed on material leaving the wetland on ebb tides before it is dispersed in the larger volume. Fishes might also access these resources by entering the wetland.</p><p>The physics to fish project has established a foundation and several new concepts for understanding how habitat restoration can benefit native fish populations at the local and regional levels. Many of the ideas regarding habitat restoration and channel modifications outlined in this report could help guide management actions that could improve conditions for native fishes at little or no water cost beyond water already dedicated to other management actions. A complete list of products originating from this work is provided in appendix 1.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231087","collaboration":"Prepared in cooperation with the Bureau of Reclamation","programNote":"Water Availability and Use Science Program","usgsCitation":"Brown, L.R., Ayers, D.E., Bergamaschi, B., Burau, J.R., Dailey, E.T., Downing, B., Downing-Kunz, M., Feyrer, F.V., Huntsman, B.M., Kraus, T., Morgan, T., Lacy, J.R., Parchaso, F., Ruhl, C.A., Stumpner, E., Stumpner, P., Thompson, J., and Young, M.J., 2024, Physics to fish—Understanding the factors that create and sustain native fish habitat in the San Francisco Estuary: U.S. Geological Survey Open-File Report 2023–1087, 150 p., https://doi.org/10.3133/ofr20231087.","productDescription":"xiv, 150 p.","numberOfPages":"150","onlineOnly":"Y","ipdsId":"IP-117031","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - 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,{"id":70250972,"text":"70250972 - 2024 - National-scale remotely sensed lake trophic state from 1984 through 2020","interactions":[],"lastModifiedDate":"2024-05-16T15:36:46.875911","indexId":"70250972","displayToPublicDate":"2024-01-16T06:59:19","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"National-scale remotely sensed lake trophic state from 1984 through 2020","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Lake trophic state is a key ecosystem property that integrates a lake’s physical, chemical, and biological processes. Despite the importance of trophic state as a gauge of lake water quality, standardized and machine-readable observations are uncommon. Remote sensing presents an opportunity to detect and analyze lake trophic state with reproducible, robust methods across time and space. We used Landsat surface reflectance data to create the first compendium of annual lake trophic state for 55,662 lakes of at least 10 ha in area throughout the contiguous United States from 1984 through 2020. The dataset was constructed with FAIR data principles (Findable, Accessible, Interoperable, and Reproducible) in mind, where data are publicly available, relational keys from parent datasets are retained, and all data wrangling and modeling routines are scripted for future reuse. Together, this resource offers critical data to address basic and applied research questions about lake water quality at a suite of spatial and temporal scales.</p></div></div>","language":"English","publisher":"Nature","doi":"10.1038/s41597-024-02921-0","usgsCitation":"Meyer, M.F., Topp, S.N., King, T.V., Ladwig, R., Pilla, R.M., Dugan, H.A., Eggleston, J., Hampton, S.E., Leech, D.M., Oleksy, I., Ross, J.C., Ross, M.V., Woolway, R.I., Yang, X., Brousil, M.R., Fickas, K.C., Padowski, J.C., Pollard, A., Ren, J., and Zwart, J.A., 2024, National-scale remotely sensed lake trophic state from 1984 through 2020: Scientific Data, v. 11, 77, 20 p., https://doi.org/10.1038/s41597-024-02921-0.","productDescription":"77, 20 p.","ipdsId":"IP-149039","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":440696,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41597-024-02921-0","text":"Publisher Index Page"},{"id":424487,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2024-01-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Meyer, Michael Frederick 0000-0002-8034-9434 mmeyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8034-9434","contributorId":304191,"corporation":false,"usgs":true,"family":"Meyer","given":"Michael","email":"mmeyer@usgs.gov","middleInitial":"Frederick","affiliations":[{"id":37786,"text":"WMA - 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,{"id":70251863,"text":"70251863 - 2024 - Nanoscale silicate melt textures determine volcanic ash surface chemistry","interactions":[],"lastModifiedDate":"2024-03-04T17:27:58.029986","indexId":"70251863","displayToPublicDate":"2024-01-15T11:25:12","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Nanoscale silicate melt textures determine volcanic ash surface chemistry","docAbstract":"<p><span>Explosive volcanic eruptions produce vast quantities of silicate ash, whose surfaces are subsequently altered during atmospheric transit. These altered surfaces mediate environmental interactions, including atmospheric ice nucleation, and toxic effects in biota. A lack of knowledge of the initial, pre-altered ash surface has required previous studies to assume that the ash surface composition created during magmatic fragmentation is equivalent to the bulk particle assemblage. Here we examine ash particles generated by controlled fragmentation of andesite and find that fragmentation generates ash particles with substantial differences in surface chemistry. We attribute this disparity to observations of nanoscale melt heterogeneities, in which Fe-rich nanophases in the magmatic melt deflect and blunt fractures, thereby focusing fracture propagation within aureoles of single-phase melt formed during diffusion-limited growth of crystals. In this manner, we argue that commonly observed pre-eruptive microtextures caused by disequilibrium crystallisation and/or melt unmixing can modify fracture propagation and generate primary discrepancies in ash surface chemistry, an essential consideration for understanding the cascading consequences of reactive ash surfaces in various environments.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/s41467-024-44712-6","usgsCitation":"Hornby, A., Ayris, P., Damby, D., Diplas, S., Eychenne, J., Kendrick, J.E., Cimarelli, C., Kueppers, U., Scheu, B., Utley, J.E., and Dingwell, D.B., 2024, Nanoscale silicate melt textures determine volcanic ash surface chemistry: Nature Communications, v. 15, 531, 10 p., https://doi.org/10.1038/s41467-024-44712-6.","productDescription":"531, 10 p.","ipdsId":"IP-150779","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":440699,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-024-44712-6","text":"Publisher Index Page"},{"id":426240,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","noUsgsAuthors":false,"publicationDate":"2024-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Hornby, Adrian","contributorId":334524,"corporation":false,"usgs":false,"family":"Hornby","given":"Adrian","email":"","affiliations":[{"id":80162,"text":"Cornell University, USA","active":true,"usgs":false}],"preferred":false,"id":895847,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ayris, Paul M","contributorId":269559,"corporation":false,"usgs":false,"family":"Ayris","given":"Paul M","affiliations":[{"id":36958,"text":"LMU Munich, Germany","active":true,"usgs":false}],"preferred":false,"id":895848,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Damby, David 0000-0002-3238-3961","orcid":"https://orcid.org/0000-0002-3238-3961","contributorId":206614,"corporation":false,"usgs":true,"family":"Damby","given":"David","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":895849,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Diplas, Spyros","contributorId":334525,"corporation":false,"usgs":false,"family":"Diplas","given":"Spyros","email":"","affiliations":[{"id":80164,"text":"SINTEF, Norway","active":true,"usgs":false}],"preferred":false,"id":895850,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eychenne, Julia","contributorId":168818,"corporation":false,"usgs":false,"family":"Eychenne","given":"Julia","email":"","affiliations":[{"id":25364,"text":"Univ. 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