{"pageNumber":"44","pageRowStart":"1075","pageSize":"25","recordCount":184582,"records":[{"id":70271501,"text":"70271501 - 2025 - A compilation pipeline for wildlife tracking datasets collected from ground-based and satellite-based telemetry transmission devices","interactions":[],"lastModifiedDate":"2025-09-18T15:27:18.163987","indexId":"70271501","displayToPublicDate":"2025-08-19T10:22:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1457,"text":"Ecological Informatics","active":true,"publicationSubtype":{"id":10}},"title":"A compilation pipeline for wildlife tracking datasets collected from ground-based and satellite-based telemetry transmission devices","docAbstract":"<p><span>Wildlife&nbsp;conservation planning&nbsp;increasingly requires collaboration and integration of research from discrete studies spanning large&nbsp;geographic areas. Tracking datasets are essential for analyzing animal movements and species distributions in relation to environmental conditions and combining them can enable powerful analyses to further aid planning efforts. However, combining datasets necessitates addressing variation in study designs, tracking methodologies, location uncertainty, and data attributes. We outline a compilation pipeline to integrate ground-based and satellite-based&nbsp;telemetry&nbsp;tracking datasets, motivated from our work with greater sage-grouse (</span><i>Centrocercus urophasianus</i><span>), a highly imperiled species of western North America. Our objective was to create a database with a standardized set of attributes to facilitate filtering locations for spatial analyses. Our pipeline phases are: (1) dataset pre-processing, (2) formatting individual datasets to a common template, (3) dataset binding, (4) error checking, and (5) filtering. Our pipeline includes additional functionality to identify coordinates from recurrently visited locations (e.g., nest sites), which may be of special interest. The final compiled sage-grouse database included nearly 5 million locations collected from 53 datasets and over 19,000 birds tracked from 1980 to 2022, including over 11,000 nest locations. Our error checks flagged 3.9&nbsp;% of locations as likely errors, predominantly collected from satellite-based&nbsp;telemetry&nbsp;transmissions. We demonstrate the ability of our pipeline to identify nest locations and flag erroneous locations by applying it to simulated tracking datasets. Overall, our workflow offers a transferable approach for researchers aiming to standardize wildlife telemetry datasets and conduct ecological analyses for both individual studies and large-scale collaborations.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoinf.2025.103220","collaboration":"Bureau of Land Management","usgsCitation":"Wann, G.T., Whipple, A.L., O’Donnell, M.S., and Aldridge, C.L., 2025, A compilation pipeline for wildlife tracking datasets collected from ground-based and satellite-based telemetry transmission devices: Ecological Informatics, v. 90, 103220, 11 p., https://doi.org/10.1016/j.ecoinf.2025.103220.","productDescription":"103220, 11 p.","ipdsId":"IP-174162","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":495748,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoinf.2025.103220","text":"Publisher Index Page"},{"id":495714,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Colorado, Idaho, Montana, Nevada, North Dakota, Oregon, South Dakota, Utah, Washington, Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -118.33602266473824,\n              36.14719079486781\n            ],\n            [\n              -110.55053462488866,\n              37.206242788039134\n            ],\n            [\n              -105.89746256645961,\n              40.02501095984442\n            ],\n            [\n              -102.5194136320973,\n              44.82182818739983\n            ],\n            [\n              -106.52465821457994,\n              48.378668867318794\n            ],\n            [\n              -106.59044740699102,\n              48.95429657658073\n            ],\n            [\n              -121.6328973274124,\n              48.97073706473478\n            ],\n            [\n              -122.65581494478303,\n              41.23928046174427\n            ],\n            [\n              -118.33602266473824,\n              36.14719079486781\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"90","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wann, Gregory T. 0000-0001-9076-7819 wanng@usgs.gov","orcid":"https://orcid.org/0000-0001-9076-7819","contributorId":3855,"corporation":false,"usgs":true,"family":"Wann","given":"Gregory","email":"wanng@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":948970,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whipple, Ashley L. 0000-0002-0304-7643","orcid":"https://orcid.org/0000-0002-0304-7643","contributorId":300552,"corporation":false,"usgs":true,"family":"Whipple","given":"Ashley","email":"","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":948971,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":140876,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":948972,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":948973,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70272727,"text":"70272727 - 2025 - Assessing policy effectiveness trends in nonindigenous aquatic species introduction in the Ohio River basin","interactions":[],"lastModifiedDate":"2025-12-05T15:58:38.264512","indexId":"70272727","displayToPublicDate":"2025-08-19T09:52:20","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Assessing policy effectiveness trends in nonindigenous aquatic species introduction in the Ohio River basin","docAbstract":"Aquatic invasive species (AIS) create costly, detrimental effects when established. Recognition of this in the United States reached a threshold in 1990 with the federal passage of the Nonindigenous Aquatic Nuisance Prevention and Control Act. This act created six regional panels, the national Aquatic Nuisance Species Task Force, and incentivized state-level AIS planning. The management of the Ohio River basin fell under the Mississippi River Basin Panel and the state-led Mississippi Interstate Cooperative Resource Association, which developed a joint action plan in 2010 to prevent, contain, and manage AIS. All Ohio River basin states besides West Virginia created aquatic nuisance species plans between 1999 and 2021. This study aims to utilize the best available data, the USGS Nonindigenous Aquatic Species (NAS) database, to examine how legislative and planning milestones have influenced the rate of new AIS arrivals and the spread of existing and new AIS. Arrival and spread of AIS were assessed at the HUC-8 scale (8-digit hydrological unit code) along the Ohio, Wabash, Cumberland, Alleghany, Monongahela, and Tennessee rivers. A near-linear increase in new AIS across all rivers was determined. Most AIS species (35–55%) did not spread beyond the HUC they were first detected in, while less than 10% spread to all HUCs in a river. The findings indicate no clear correlation between legislative and planning milestones and changes in AIS spread. More work could help to fill data gaps in detecting and monitoring AIS through coordinated local and regional programs, as expanding the quality and quantity of data collection efforts can improve understanding of AIS dynamics, assessments of management effectiveness, and inform future policy. Future work could expand the analysis to evaluate the effectiveness of policy and planning programs in reducing AIS, considering the variability in on-the-ground approaches and spread prevention efforts across states.","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre","doi":"10.3391/mbi.2025.16.4.04","usgsCitation":"Clasgens, A.N., Murry, B.A., Zipp, K., Arantes, C.C., and Neilson, M., 2025, Assessing policy effectiveness trends in nonindigenous aquatic species introduction in the Ohio River basin: Management of Biological Invasions, v. 16, no. 4, p. 943-959, https://doi.org/10.3391/mbi.2025.16.4.04.","productDescription":"17 p.","startPage":"943","endPage":"959","ipdsId":"IP-167017","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":497391,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2025.16.4.04","text":"Publisher Index Page"},{"id":497141,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Georgia, Illinois, Indiana, Kentucky, Mississippi, New York, Ohio, Pennsylvania, Tennessee, West Virginia","otherGeospatial":"Ohio River drainage","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -77.86189828374268,\n              41.77677411774701\n            ],\n            [\n              -78.63164005664989,\n              42.413236850225616\n            ],\n            [\n              -80.3205619541407,\n              41.52394031593266\n            ],\n            [\n              -81.68440343936543,\n              39.99520322262126\n            ],\n            [\n              -83.73626351948025,\n              40.91179316865117\n            ],\n            [\n              -85.75377241079076,\n              41.00045122078683\n            ],\n            [\n              -87.29259028984461,\n              40.42166367952521\n            ],\n            [\n              -88.54389544444282,\n              39.58671971059428\n            ],\n            [\n              -89.34400773501363,\n              38.01283806367644\n            ],\n            [\n              -89.61987832634247,\n              37.407427236343395\n            ],\n            [\n              -89.33088690734974,\n              35.30445704462397\n            ],\n            [\n              -88.08870098862076,\n              34.22161459059926\n            ],\n            [\n              -86.40862152775846,\n              34.1696767386851\n            ],\n            [\n              -82.7983151924422,\n              35.87757326220134\n            ],\n            [\n              -81.42706279554102,\n              36.962278650385485\n            ],\n  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0000-0003-3142-1628","orcid":"https://orcid.org/0000-0003-3142-1628","contributorId":363327,"corporation":false,"usgs":false,"family":"Murry","given":"Brent","middleInitial":"A.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":951455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zipp, Kaylyn 0009-0008-0621-8285","orcid":"https://orcid.org/0009-0008-0621-8285","contributorId":363330,"corporation":false,"usgs":false,"family":"Zipp","given":"Kaylyn","affiliations":[{"id":25572,"text":"University of Maine, Orono","active":true,"usgs":false}],"preferred":false,"id":951456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arantes, Caroline C. 0000-0002-9752-1499","orcid":"https://orcid.org/0000-0002-9752-1499","contributorId":363331,"corporation":false,"usgs":false,"family":"Arantes","given":"Caroline","middleInitial":"C.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":951457,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Neilson, Matthew 0000-0002-5139-5677","orcid":"https://orcid.org/0000-0002-5139-5677","contributorId":214507,"corporation":false,"usgs":true,"family":"Neilson","given":"Matthew","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":951458,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70270458,"text":"70270458 - 2025 - Improved prediction of postfire debris flows through rainfall anomaly maps","interactions":[],"lastModifiedDate":"2025-08-20T14:53:20.297849","indexId":"70270458","displayToPublicDate":"2025-08-19T09:48:24","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Improved prediction of postfire debris flows through rainfall anomaly maps","docAbstract":"<p><span>Predicting where runoff-generated debris flows might occur during rainfall on steep, recently burned terrain is challenging. Studies of mass-movement processes in unburned areas indicate that event locations are well-predicted by rainfall anomaly,&nbsp;</span><i>R*</i><span>, in which peak observed rainfall is normalized by local rainfall climatology. Here, we use remote and field methods to map debris flows triggered within the 2020 Dolan Fire burn area in coastal California, demonstrate that a short-duration&nbsp;</span><i>R*</i><span>&nbsp;metric predicts debris-flow occurrence more effectively than absolute peak intensity or longer-duration rainfall metrics, and show that incorporating an&nbsp;</span><i>R*</i><span>&nbsp;criterion into an existing debris-flow likelihood model can reduce false positive predictions and improve accuracy. We test&nbsp;</span><i>R</i><span>* at three other climatically distinct fires in California, demonstrating its utility for mapping likely debris-flow locations in different climates. We also consider how&nbsp;</span><i>R*</i><span>&nbsp;can benefit postfire debris-flow prediction given recent increases in climatological variability within individual burn perimeters.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025GL114791","usgsCitation":"Cavagnaro, D.B., McCoy, S.W., Thomas, M.A., Kostelnik, J., and Lindsay, D.N., 2025, Improved prediction of postfire debris flows through rainfall anomaly maps: Geophysical Research Letters, v. 52, no. 16, e2025GL114791, 12 p., https://doi.org/10.1029/2025GL114791.","productDescription":"e2025GL114791, 12 p.","ipdsId":"IP-170042","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":494967,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13ZGR6F","text":"USGS data release","linkHelpText":"Inventory of fluvial erosion and debris-flow activity following the 2020 Dolan Fire, California"},{"id":494458,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025gl114791","text":"Publisher Index Page"},{"id":494344,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Callifornia","county":"Monterey County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -121.7,\n              36.2\n            ],\n            [\n              -121.7,\n              35.9\n            ],\n            [\n              -121.3,\n              35.9\n            ],\n            [\n              -121.3,\n              36.2\n            ],\n            [\n              -121.7,\n              36.2\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"52","issue":"16","noUsgsAuthors":false,"publicationDate":"2025-08-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Cavagnaro, David B.","contributorId":359920,"corporation":false,"usgs":false,"family":"Cavagnaro","given":"David","middleInitial":"B.","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":946432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCoy, Scott W.","contributorId":359922,"corporation":false,"usgs":false,"family":"McCoy","given":"Scott","middleInitial":"W.","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":946433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomas, Matthew A. 0000-0002-9828-5539 matthewthomas@usgs.gov","orcid":"https://orcid.org/0000-0002-9828-5539","contributorId":200616,"corporation":false,"usgs":true,"family":"Thomas","given":"Matthew","email":"matthewthomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":946434,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kostelnik, Jaime 0000-0002-1817-5461","orcid":"https://orcid.org/0000-0002-1817-5461","contributorId":300717,"corporation":false,"usgs":true,"family":"Kostelnik","given":"Jaime","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":946435,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindsay, Donald N.","contributorId":359924,"corporation":false,"usgs":false,"family":"Lindsay","given":"Donald","middleInitial":"N.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":946436,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70270862,"text":"70270862 - 2025 - Estimating the hypothetical endowment of critical minerals and other commodities in porphyry copper mine waste in the Four Corners states, USA","interactions":[],"lastModifiedDate":"2025-08-26T14:17:35.326171","indexId":"70270862","displayToPublicDate":"2025-08-19T09:14:15","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Estimating the hypothetical endowment of critical minerals and other commodities in porphyry copper mine waste in the Four Corners states, USA","docAbstract":"<p>Society is fundamentally dependent upon commodities that are used in end-use products for the aerospace, defense, energy, telecommunication, and transportation sectors, resulting in centuries of mining to supply these commodities and materials. Waste from these mining operations can remain on the landscape indefinitely, but there is a lack of national understanding of the distribution and scale of such waste features. The renewable energy transition will continue to increase demand for critical minerals and will result in increasing volumes of mine waste on the Earth’s surface. Reprocessing mine waste can reduce environmental risks and recover needed commodities to match growing demand for societal growth. Therefore, understanding the approximate abundance of commodities that may be available for recovery within mine waste features can be an important piece of domestic critical mineral supply. </p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geologic Mapping Forum 24/25 abstracts","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Minnesota Geological Survey","usgsCitation":"Gaynor, S.P., Karl, N., Helfrich, A., Smith, A.F., and Mauk, J.L., 2025, Estimating the hypothetical endowment of critical minerals and other commodities in porphyry copper mine waste in the Four Corners states, USA, <i>in</i> Geologic Mapping Forum 24/25 abstracts, p. 56-57.","productDescription":"2 p.","startPage":"56","endPage":"57","ipdsId":"IP-177494","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science 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Water quality parameters described include surface (above pycnocline) total nitrogen (TN), surface total phosphorus (TP), surface water temperature (WTEMP), spring (March-May) and summer (July-September) surface chlorophyll a, summer bottom (below pycnocline) dissolved oxygen (DO) concentrations, and Secchi disk depth (a measure of water clarity). Results for annual bottom TP, bottom TN, surface ortho-phosphate (PO4), surface dissolved inorganic nitrogen (DIN), surface total suspended solids (TSS), and summer surface DO concentrations are provided in Appendix B. Drivers discussed include physiographic watershed characteristics, changes in TN, TP, and sediment loads from the watershed to tidal waters, expected effects of changing land use, and implementation of nutrient management and natural resource conservation practices. Factors internal to estuarine waters that also play a role as drivers are described including biogeochemical processes, physical forces such as wind driven mixing of the water column and increase in rainfall intensity and volume, and biological factors such as phytoplankton biomass and the presence of submerged aquatic vegetation. Continuing to track water quality response and investigating these influencing factors are important steps to understanding water quality patterns and changes in the Potomac River. The intended audiences for this report include, but are not limited to, 1) technical managers within jurisdictions who are looking at tidal water quality data and trying to understand why patterns are occurring, 2) local watershed organizations that are trying to understand these analyses and working to connect them to their local area(s), and 3) federal, state, and academic researchers. Figure 1 presents a conceptual model highlighting these intended audiences. Our goal is for the Tributary Summary documents to be sources of readily available background for change over time in tidal water quality observed with monitoring data. The intended purpose of the Tributary Summary documents is to help answer questions related to water quality, show how landscape factors drive water quality change over time, provide support for management decisions that may alter water quality trends and living resources conditions, and highlight where there may be information or knowledge gaps.","language":"English","publisher":"Chesapeake Bay Program","usgsCitation":"Sullivan, B.M., Gootman, K., Gunnerson, A., Betts, S., Duran, G., Johnson, C., Mason, C.A., Perry, E., Bhatt, G., Keisman, J.L., Webber, J.S., Harcum, J., Lane, M., Devereux, O., Zhang, Q., Murphy, R., Renee Karrh, Butler, T., and Wei, Z., 2025, Potomac Tributary Summary: A summary of trends in tidal water quality and associated factors, 1985 - 2022, 88 p.","productDescription":"88 p.","ipdsId":"IP-173187","costCenters":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science 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Qian","contributorId":331417,"corporation":false,"usgs":false,"family":"Zhang","given":"Qian","affiliations":[{"id":79204,"text":"UMCES","active":true,"usgs":false}],"preferred":false,"id":946629,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Murphy, Rebecca","contributorId":331418,"corporation":false,"usgs":false,"family":"Murphy","given":"Rebecca","affiliations":[{"id":79204,"text":"UMCES","active":true,"usgs":false}],"preferred":false,"id":946630,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Renee Karrh","contributorId":359985,"corporation":false,"usgs":false,"family":"Renee Karrh","affiliations":[{"id":33964,"text":"Maryland Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":946631,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Butler, Thomas","contributorId":219625,"corporation":false,"usgs":false,"family":"Butler","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":946632,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Wei, Zhaoying","contributorId":245828,"corporation":false,"usgs":false,"family":"Wei","given":"Zhaoying","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":946633,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}}
,{"id":70270880,"text":"70270880 - 2025 - Shifts in suitability of pinyon-juniper communities: A climate adaptation framework for range-wide management of arid woodland resources","interactions":[],"lastModifiedDate":"2025-08-26T15:40:42.066035","indexId":"70270880","displayToPublicDate":"2025-08-19T08:35:22","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":22182,"text":"Forest Ecology & Management","active":true,"publicationSubtype":{"id":10}},"title":"Shifts in suitability of pinyon-juniper communities: A climate adaptation framework for range-wide management of arid woodland resources","docAbstract":"<p><span>Pinyon-juniper (PJ) woodlands are a diverse ecosystem type providing a wealth of ecosystem services across western North America. Managing PJ woodlands in the 21st century entails balancing multiple conservation objectives, and resource managers and policy-makers working to sustain PJ woodlands need spatially explicit information about current PJ woodland conditions and how they may be impacted in coming decades in the context of wildfire risk and changing climate. Here, we address knowledge gaps and provide information that improves the long-term value of conservation and restoration actions in PJ woodlands. To this end, we merged projections of future environmental suitability for nine PJ species with wildfire risk and locations of mature and old-growth (MOG) woodlands to assess spatial variation in PJ woodlands with differing threats and management opportunities. We identified potential climate refugia with enduring high community suitability and low burn probability (3 % of study area</span><u>)</u><span>&nbsp;that may persist with relatively little management. We found promising locations of PJ-MOG forest type with high future suitability (12 % of areas) that could be prioritized for fire risk reduction to maintain high-value woodlands. Despite a 38 % mean community suitability decline under future climate conditions, some locations (7 % of areas) may act as climate refugia where future climate conditions can support current PJ woodland composition and structure. We conclude by demonstrating how this information can be integrated into a conceptual framework to help prioritize conservation and climate adaptation in PJ woodlands.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2025.123075","collaboration":"Bureau of Land Management","usgsCitation":"Noel, A.R., Schlaepfer, D.R., Barrett, I.P., Duniway, M.C., Norris, J.R., Domschke, C.T., Butterfield, B.J., Swan, M.C., Hartwig, K., Crist, M.R., and Bradford, J.B., 2025, Shifts in suitability of pinyon-juniper communities: A climate adaptation framework for range-wide management of arid woodland resources: Forest Ecology & Management, v. 596, 123075, 13 p., https://doi.org/10.1016/j.foreco.2025.123075.","productDescription":"123075, 13 p.","ipdsId":"IP-178751","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":495061,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2025.123075","text":"Publisher Index Page"},{"id":494906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Mexico, United States","otherGeospatial":"western North America","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -127.50770240912789,\n              51.26451527851455\n            ],\n            [\n              -125.5179241133188,\n              37.61802033493834\n            ],\n            [\n              -108.45616956845282,\n              17.905986456648336\n            ],\n            [\n              -100.63114638813056,\n              19.804450355914284\n            ],\n            [\n              -96.68217379668386,\n              49.16349814350793\n            ],\n         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0000-0001-9973-2065","orcid":"https://orcid.org/0000-0001-9973-2065","contributorId":225569,"corporation":false,"usgs":true,"family":"Schlaepfer","given":"Daniel","email":"","middleInitial":"Rodolphe","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":947276,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barrett, Ian P.","contributorId":360597,"corporation":false,"usgs":false,"family":"Barrett","given":"Ian","middleInitial":"P.","affiliations":[{"id":86049,"text":"Bureau of Land Management, National Interagency Fire Center, Boise ID","active":true,"usgs":false}],"preferred":false,"id":947277,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duniway, Michael C. 0000-0002-9643-2785 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OR","active":true,"usgs":false}],"preferred":false,"id":947280,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Butterfield, Brad J.","contributorId":360599,"corporation":false,"usgs":false,"family":"Butterfield","given":"Brad","middleInitial":"J.","affiliations":[{"id":86053,"text":"Department of Biological Sciences, Northern Arizona University, PO Box 5640 Flagstaff, Arizona 86011 USA","active":true,"usgs":false}],"preferred":false,"id":947281,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Swan, Megan C.","contributorId":360600,"corporation":false,"usgs":false,"family":"Swan","given":"Megan","middleInitial":"C.","affiliations":[{"id":86054,"text":"National Park Service, Southern Colorado Plateau Network, 930 N Switzer Canyon Dr Suite 200, Flagstaff, AZ, 86011 USA","active":true,"usgs":false}],"preferred":false,"id":947282,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hartwig, Kim","contributorId":292169,"corporation":false,"usgs":false,"family":"Hartwig","given":"Kim","affiliations":[],"preferred":false,"id":947283,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Crist, Michelle R.","contributorId":360601,"corporation":false,"usgs":false,"family":"Crist","given":"Michelle","middleInitial":"R.","affiliations":[{"id":86049,"text":"Bureau of Land Management, National Interagency Fire Center, Boise ID","active":true,"usgs":false}],"preferred":false,"id":947284,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":222784,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":947285,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70270887,"text":"70270887 - 2025 - Revisiting an enigma on California's north coast: The Mw6.5 Fickle Hill earthquake of 21 December 1954","interactions":[],"lastModifiedDate":"2025-12-01T16:27:30.70546","indexId":"70270887","displayToPublicDate":"2025-08-19T08:16:21","publicationYear":"2025","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":"Revisiting an enigma on California's north coast: The Mw6.5 Fickle Hill earthquake of 21 December 1954","docAbstract":"<p><span>Many earthquakes occur along the North Coast of California in the vicinity of the Mendocino Triple Junction (MTJ), where the Pacific, Gorda, and North American (NA) plates meet, and on the adjacent plate boundaries. The MTJ marks the nexus of the Mendocino and San Andreas faults with the Cascadia subduction zone (CSZ). Historically, most large earthquakes around the MTJ have been within the offshore Gorda plate and its subducted portion beneath the NA plate. North of the MTJ, active faults mapped in the NA plate are part of the CSZ fold‐and‐thrust belt. Although some events have been detected in the NA plate, no large historic events have been associated with mapped surface faults. The 21 December 1954 <i>M</i><sub>w</sub></span><span>&nbsp;6.5 earthquake in Humboldt County is one possible exception. Using published data from catalogs and articles, unpublished data from Berkeley’s archives, and&nbsp;</span><i>S</i><span>‐</span><i>P</i><span>&nbsp;times interpreted from two U.S. Coast and Geodetic Survey (USCGS) accelerometers, we determine a probability cloud for the earthquake’s hypocenter using NonLinLoc. The highest probability location lies beneath Fickle Hill just east of the city of Arcata, California, at 40.87°&nbsp;N, 124.03°&nbsp;W, and ∼11&nbsp;km depth. Using&nbsp;</span><i>P</i><span>‐wave polarities from Berkeley stations and the digitized waveforms from the accelerometers, we find that the focal mechanism most consistent with the data indicates thrust movement with strike, dip, and rake of 350°, 10°, and 90°, respectively, at a depth of 14&nbsp;km. Given the depth uncertainties of both this event and the megathrust, this implies that the earthquake most likely took place on the subduction interface rather than on the mapped faults in the Mad River fault zone that trend 322° and dip to the northeast. The revisited intensity in the epicentral region also supports a location beneath Fickle Hill to the east of the city of Arcata, California.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120250080","usgsCitation":"Hellweg, M., Lee, T.A., Dreger, D.S., Lomax, A., Hagos, L., Haddabi, H., McPherson, R.C., Dengler, L., Hough, S.E., and Patton, J.R., 2025, Revisiting an enigma on California's north coast: The Mw6.5 Fickle Hill earthquake of 21 December 1954: Bulletin of the Seismological Society of America, v. 115, no. 6, p. 2623-2639, https://doi.org/10.1785/0120250080.","productDescription":"17 p.","startPage":"2623","endPage":"2639","ipdsId":"IP-177949","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":494901,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Nevada, Oregon, Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -124.23082743259238,\n              46.45369999658712\n            ],\n            [\n              -124.94108692827174,\n              41.87317683684783\n            ],\n            [\n              -124.0036946792876,\n              37.27396300370703\n            ],\n            [\n              -120.72594459506794,\n              33.05110616586563\n            ],\n            [\n              -116.56731665360127,\n              33.7291335831041\n            ],\n            [\n              -116.56731665360127,\n              46.45369999658712\n            ],\n            [\n              -124.23082743259238,\n              46.45369999658712\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  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Survey","active":true,"usgs":false}],"preferred":false,"id":947299,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McPherson, Robert C.","contributorId":350346,"corporation":false,"usgs":false,"family":"McPherson","given":"Robert","middleInitial":"C.","affiliations":[{"id":83721,"text":"Cal Poly Humboldt Univ.","active":true,"usgs":false}],"preferred":false,"id":947300,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dengler, Lori","contributorId":197374,"corporation":false,"usgs":false,"family":"Dengler","given":"Lori","affiliations":[],"preferred":false,"id":947301,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hough, Susan E. 0000-0002-5980-2986","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":263442,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science 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,{"id":70271353,"text":"70271353 - 2025 - Evaluation of daily stream temperature predictions (1979-2021) across the contiguous United States using a spatiotemporal aware machine learning algorithm","interactions":[],"lastModifiedDate":"2025-09-10T14:57:19.895523","indexId":"70271353","displayToPublicDate":"2025-08-19T07:53:02","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7164,"text":"Environmental Modelling & Software","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of daily stream temperature predictions (1979-2021) across the contiguous United States using a spatiotemporal aware machine learning algorithm","docAbstract":"<p><span>Stream temperature controls a variety of physical and biological processes that affect ecosystems, human health, and economic activities. We used 42 years (1979–2021) of data to predict daily summary statistics of stream temperature across &gt;50,000 stream reaches in the contiguous United States using a recurrent graph convolution network. We comprehensively documented the performance – both across all reaches and by stream type (e.g., reservoir or groundwater influence) – as a baseline for future improvement. The model showed reach-level RMSE of &lt;2&nbsp;°C with 90&nbsp;% prediction intervals that contain 90.7&nbsp;% of observations. We also assessed how the model captured variability in ecologically relevant metrics (e.g., R</span><sup>2</sup><span>&nbsp;for annual 7-day maximum&nbsp;=&nbsp;0.76; R</span><sup>2</sup><span>&nbsp;for days exceeding 25&nbsp;°C&nbsp;=&nbsp;0.75). This model does not outperform state-of-the-art machine learning efforts (e.g., RMSE ≤1.5&nbsp;°C) due to a limited input set but does provide the most spatially complete modeling to date to support water availability assessments.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2025.106655","usgsCitation":"Diaz, J.A., Oliver, S.K., and Gorski, G., 2025, Evaluation of daily stream temperature predictions (1979-2021) across the contiguous United States using a spatiotemporal aware machine learning algorithm: Environmental Modelling & Software, v. 193, 106655, 16 p., https://doi.org/10.1016/j.envsoft.2025.106655.","productDescription":"106655, 16 p.","ipdsId":"IP-178555","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":495393,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2025.106655","text":"Publisher Index Page"},{"id":495279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"contiguous United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n              ],\n              [\n                -94.32914,\n                48.67074\n              ],\n              [\n                -93.63087,\n                48.60926\n              ],\n              [\n                -92.61,\n                48.45\n              ],\n              [\n                -91.64,\n                48.14\n              ],\n              [\n                -90.83,\n                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,{"id":70271129,"text":"70271129 - 2025 - Avian influenza spillover into poultry: Environmental influences and biosecurity protections","interactions":[],"lastModifiedDate":"2025-08-28T14:54:17.55377","indexId":"70271129","displayToPublicDate":"2025-08-19T07:47:16","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":22340,"text":"One Health","active":true,"publicationSubtype":{"id":10}},"title":"Avian influenza spillover into poultry: Environmental influences and biosecurity protections","docAbstract":"With the continued spread of highly pathogenic avian influenza (HPAI), understanding the complex dynamics of virus transfer at the wild – agriculture interface is paramount. Spillover events (i.e., virus transfer from wild birds into poultry) are related to proximity to infected wild bird populations and environmental conditions. By accounting for such dynamics, we can take a combined approach to assess the impacts of biosecurity measures implemented at poultry farms while simultaneously accounting for their local risk levels. We implemented a Bayesian joint-likelihood logistic regression for the Continental U.S. comparing models of spatiotemporal risk according to land use, weather, and predicted waterfowl distributions followed by integrating a farm-level case-control questionnaire dataset focused on identifying trends in HPAI spillover risk associated with a farm's biosecurity practices. We found that estimates of waterfowl abundance, along with mean precipitation and temperature during winter, were most correlated with spatiotemporal HPAI risk. Additionally, we identified multiple biosecurity practices associated with reduced risk to HPAI, where the strongest relationships were related to litter decontamination treatments, vehicle wash stations, and avoiding shared dead-bird disposal sites with other farms. This model broadly guides surveillance of HPAI in wild and domestic populations, identifying when and where we are most likely to see increased instances of the virus while also providing insights into how poultry farms can better protect themselves from risk.","language":"English","publisher":"Elsevier","doi":"10.1016/j.onehlt.2025.101172","usgsCitation":"Gonnerman, M.B., Mullinax, J., Fox, A., Patyk, K.A., Fields, V., McCool, M., Torchetti, M.K., Lantz, K., Sullivan, J.D., and Prosser, D.J., 2025, Avian influenza spillover into poultry: Environmental influences and biosecurity protections: One Health, v. 21, 101172, 9 p., https://doi.org/10.1016/j.onehlt.2025.101172.","productDescription":"101172, 9 p.","ipdsId":"IP-178496","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":495069,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.onehlt.2025.101172","text":"Publisher Index Page"},{"id":495002,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"contiguous United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n              ],\n              [\n                -94.32914,\n                48.67074\n              ],\n              [\n                -93.63087,\n                48.60926\n              ],\n              [\n                -92.61,\n                48.45\n              ],\n              [\n                -91.64,\n                48.14\n              ],\n              [\n                -90.83,\n                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Resource managers need to understand stream and river condition and how these conditions are changing over time to determine whether regional long-term restoration and conservation goals are being met. The objective of this report was to document the spatial and temporal variability of conditions for seven indicators of river and stream health across the nontidal Chesapeake Bay watershed. The framework for the U.S. Geological Survey’s Nontidal Network (NTN), a network of more than 100 nutrient and suspended sediment monitoring locations, was extended to assess conditions for six additional indicators of stream health: temperature, salinity, toxic contaminants, streamflow, hydromorphology, and biological aquatic communities. For each indicator, the latest available data from multiple sources were compiled and harmonized, and key metrics were identified to describe indicator conditions across space and time. A status condition was defined for each indicator to describe overall spatial variability in recent condition, and trend analyses were used to describe changes in each indicator metric over time. The analysis revealed clear differences in spatial and temporal data coverage across the seven indicators, so individual indicator trend analyses were not constrained to a common time interval. However, a status snapshot was conducted across all indicators for the 2015–17 period to simultaneously explore spatial variability across all indicators. The status snapshot highlighted general degraded conditions across multiple indicators in large metropolitan regions, such as the Baltimore–Washington, D.C., metropolitan area. Regression analysis between indicator status metrics and major land cover for the sites suggest urbanization as a potential driver of degraded conditions for many of the indicator metrics, including total phosphorus, salinity, temperature, high-flow frequency, and metrics of habitat and biological assemblage quality. A final analysis exploring the spatial representation of each indicator network showed that some indicator monitoring networks did not cover certain settings, such as small watersheds. These results provided an initial assessment of stream health status and trends and will continue to be leveraged to describe conditions across the Chesapeake Bay watershed to help inform local and regional management decisions. These results also highlighted the need for improved coordination among monitoring organizations to support long-term multi-indicator monitoring and assessment.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255072","usgsCitation":"Boyle, L.J., Austin, S.H., Cashman, M.J., Clifton, Z.J., Clune, J.W., Colgin, J.E., Elliott, K.E.M., Fanelli, R.M., Foss, E.P., Hitt, N.P., Hittle, E.A., Howe, C.M., Majcher, E.H., Maloney, K.O., Mason, C.A., Metes, M.J., Moyer, D.L., Needham, T.P., Rogers, K.M., Thompson, J.J., Yang, G., and Zimmerman, T.M., 2025, Tracking status and trends in seven key indicators of river and stream condition in the Chesapeake Bay watershed: U.S. Geological Survey Scientific Investigations Report 2025–5072, 104 p., https://doi.org/10.3133/sir20255072.","productDescription":"Report: x, 104 p.; Data 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          [\n              -75.1904296875,\n              38.41916639395372\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_va@usgs.gov\" data-mce-href=\"mailto:dc_va@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/virginia-and-west-virginia-water-science-center\" data-mce-href=\"https://www.usgs.gov/centers/virginia-and-west-virginia-water-science-center\">Virginia and West Virginia Water Science Center</a><br>U.S. Geological Survey<br>1730 East Parham Road<br>Richmond, Virginia 23228</p>","tableOfContents":"<ul><li>Abstract</li><li>1. Introduction</li><li>2. Status and Trends Methods, Analyses, and Results</li><li>3. Summary</li><li>Acknowledgements</li><li>References Cited</li><li>Appendix 1. Stream Salinity Supplemental Information</li><li>Appendix 2. Stream Toxic Contaminants Supplemental Information</li><li>Appendix 3. Stream Hydromorphology Supplemental Information</li><li>Appendix 4. Status Snapshot</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2025-08-18","noUsgsAuthors":false,"publicationDate":"2025-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Boyle, Lindsey J. 0009-0007-8825-5700","orcid":"https://orcid.org/0009-0007-8825-5700","contributorId":359737,"corporation":false,"usgs":false,"family":"Boyle","given":"Lindsey","middleInitial":"J.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":946092,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Austin, Samuel H. 0000-0001-5626-023X saustin@usgs.gov","orcid":"https://orcid.org/0000-0001-5626-023X","contributorId":153,"corporation":false,"usgs":true,"family":"Austin","given":"Samuel","email":"saustin@usgs.gov","middleInitial":"H.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center 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,{"id":70271913,"text":"70271913 - 2025 - Cryptic CAM photosynthesis in Joshua tree (Yucca brevifolia, Y. jaegeriana)","interactions":[],"lastModifiedDate":"2025-12-01T16:45:08.446207","indexId":"70271913","displayToPublicDate":"2025-08-18T10:32:30","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2863,"text":"New Phytologist","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Cryptic CAM photosynthesis in Joshua tree (<i>Yucca brevifolia, Y. jaegeriana</i>)","title":"Cryptic CAM photosynthesis in Joshua tree (Yucca brevifolia, Y. jaegeriana)","docAbstract":"<ul class=\"unordered-list\"><li>Joshua trees are long-lived perennial monocots native to the Mojave Desert in North America. Composed of two species,<span>&nbsp;</span><i>Yucca brevifolia</i><span>&nbsp;</span>and<span>&nbsp;</span><i>Y. jaegeriana</i><span>&nbsp;</span>(Asparagaceae), Joshua trees are imperiled by climate change, with decreases in suitable habitat predicted under future climate change scenarios. Relatively little is understood about the ecophysiology of Joshua trees across their range, including the extent to which populations are locally adapted or phenotypically plastic to environmental stress.</li><li>Plants in our common gardens showed evidence of Crassulacean acid metabolism photosynthesis (CAM) in a pilot experiment, despite no prior report of this photosynthetic pathway in these species. We further studied the variation and strength of CAM within a single common garden, measuring seedlings representing populations across the range of the two species.</li><li>A combination of physiology and transcriptomic data showed low levels of CAM that varied across populations but were unrelated to home environmental conditions. Gene expression confirmed CAM activity and further suggested differences in carbon and nitrogen metabolism between<span>&nbsp;</span><i>Y. brevifolia</i><span>&nbsp;</span>and<span>&nbsp;</span><i>Y. jaegeriana.</i></li><li>Together the results suggest greater physiological diversity between these species than initially expected, particularly at the seedling stage, with implications for future survival of Joshua trees under a warming climate.</li></ul>","language":"English","publisher":"New Phytologist Foundation","doi":"10.1111/nph.70437","usgsCitation":"Heyduk, K., Scoles-Sciulla, S.J., Hennessy, B., Czymmek, M., McAssey, E.V., Kane, C., Kim, G.Y., Sogunle, I., Heublein, L., Sriram, D., MacNeill, B., Hren, M.T., Esque, T.C., Yoder, J.B., McKain, M.R., Smith, C.I., and DeFalco, L., 2025, Cryptic CAM photosynthesis in Joshua tree (Yucca brevifolia, Y. jaegeriana): New Phytologist, v. 248, no. 5, p. 2583-2598, https://doi.org/10.1111/nph.70437.","productDescription":"14 p.","startPage":"2583","endPage":"2598","ipdsId":"IP-173093","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":496157,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/nph.70437","text":"Publisher Index Page"},{"id":496015,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"248","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Heyduk, Karolina","contributorId":361735,"corporation":false,"usgs":false,"family":"Heyduk","given":"Karolina","affiliations":[{"id":86340,"text":"University of Connecticut; University of Hawai'i","active":true,"usgs":false}],"preferred":false,"id":949346,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scoles-Sciulla, Sara J. 0000-0003-1693-5030 sscoles@usgs.gov","orcid":"https://orcid.org/0000-0003-1693-5030","contributorId":2614,"corporation":false,"usgs":true,"family":"Scoles-Sciulla","given":"Sara","email":"sscoles@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":949347,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hennessy, Bridget","contributorId":361736,"corporation":false,"usgs":false,"family":"Hennessy","given":"Bridget","affiliations":[{"id":86341,"text":"Chicago Botanical Garden","active":true,"usgs":false}],"preferred":false,"id":949348,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Czymmek, Madeline","contributorId":361737,"corporation":false,"usgs":false,"family":"Czymmek","given":"Madeline","affiliations":[{"id":86341,"text":"Chicago Botanical Garden","active":true,"usgs":false}],"preferred":false,"id":949349,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McAssey, Edward V.","contributorId":361738,"corporation":false,"usgs":false,"family":"McAssey","given":"Edward","middleInitial":"V.","affiliations":[{"id":86340,"text":"University of Connecticut; University of Hawai'i","active":true,"usgs":false}],"preferred":false,"id":949350,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kane, Chase","contributorId":361739,"corporation":false,"usgs":false,"family":"Kane","given":"Chase","affiliations":[{"id":35760,"text":"University of Hawai'i","active":true,"usgs":false}],"preferred":false,"id":949351,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kim, G. 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,{"id":70271174,"text":"70271174 - 2025 - Regional differentiation in somatic growth and maturation attributes for loggerhead sea turtles (Caretta caretta) in the Northwest Atlantic","interactions":[],"lastModifiedDate":"2025-09-02T15:48:41.689007","indexId":"70271174","displayToPublicDate":"2025-08-18T08:41:18","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2660,"text":"Marine Biology","active":true,"publicationSubtype":{"id":10}},"title":"Regional differentiation in somatic growth and maturation attributes for loggerhead sea turtles (Caretta caretta) in the Northwest Atlantic","docAbstract":"<p><span>The ages and sizes at which organisms mature have significant implications for lifetime reproductive success. For species at risk of extinction, such as sea turtles, these attributes can ultimately impact probability of population persistence. Within the Northwest Atlantic Ocean, the broader loggerhead sea turtle (</span><i>Caretta caretta</i><span>) population comprises management units both along the US Gulf of America (formerly Gulf of Mexico) and Atlantic coasts. Although age, growth, and maturation have been more intensively studied along the US Atlantic, data specific to the Gulf of America have remained sparse. To address this data gap, we conducted skeletal growth mark analysis (skeletochronology) for 123 humerus bones collected from loggerheads found dead in the US Gulf of America from 1998 to 2021. We compared resulting age, growth, and maturation data with information from studies of US Atlantic coast loggerheads for similar size and year ranges, using the exact same skeletochronology methods, as well as with Gulf of America mark-recapture growth data. Results indicate that Gulf of America loggerheads exhibit significantly faster juvenile somatic growth. In addition, sizes at maturation were substantially smaller, corresponding with mean estimates of age at maturation 7.5 to 15&nbsp;years earlier than US Atlantic counterparts. Finally, the maximum observed Gulf of America adult age estimate was 42.5&nbsp;years, considerably less than the highest US Atlantic estimate of 77.0&nbsp;years. These detailed data offer insights into regional variability in somatic growth dynamics and characteristics associated with maturation, which in turn can impact relative reproductive contributions and, ultimately, population trajectories.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1007/s00227-025-04684-7","usgsCitation":"Avens, L., Lamont, M., Foley, A.M., Higgins, B.M., Howell, L.N., Lovewell, G., Shaver, D.J., Stacy, B.A., Walker, J.S., Clark, J.M., Wallace, A.A., and Vander Zanden, H.B., 2025, Regional differentiation in somatic growth and maturation attributes for loggerhead sea turtles (Caretta caretta) in the Northwest Atlantic: Marine Biology, v. 172, 149, 18 p., https://doi.org/10.1007/s00227-025-04684-7.","productDescription":"149, 18 p.","ipdsId":"IP-174852","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research 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,{"id":70270631,"text":"70270631 - 2025 - Landscape changes elevate the risk of avian influenza virus diversification and emergence in the East Asian–Australasian Flyway","interactions":[],"lastModifiedDate":"2025-08-21T16:12:27.780843","indexId":"70270631","displayToPublicDate":"2025-08-18T08:27:04","publicationYear":"2025","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":"Landscape changes elevate the risk of avian influenza virus diversification and emergence in the East Asian–Australasian Flyway","docAbstract":"<p><span>Highly pathogenic avian influenza viruses (HPAIV) persistently threaten wild waterfowl, domestic poultry, and public health. The East Asian–Australasian Flyway plays a crucial role in HPAIV dynamics due to its large populations of migratory waterfowl and poultry. Over recent decades, this flyway has undergone substantial landscape changes, including both losses and gains of waterfowl habitats. These changes can affect waterfowl distributions, increase contact with poultry, and consequently alter ecological conditions that favor avian influenza virus (AIV) evolution. However, limited research has assessed these likely impacts. Here, we integrated empirical data and an individual-based model to simulate AIV transmission in migratory waterfowl and domestic poultry, including wild-to-poultry spillover and reassortment dynamics in poultry, across landscapes representing the years 2000 and 2015. We used the reassortment incidence as a proxy for ecological and transmission conditions that support viral diversification and the emergence of novel subtypes. Our simulations show that landscape change reshaped the waterfowl distribution, facilitated bird aggregation at improved habitats, increased coinfection, and raised reassortment rate by 1,593%, indicating a substantially higher potential for viral diversification and emergence. Model-generated risk maps show expanded and increased reassortment risk in southeastern China, the Yellow River Basin, and northeastern China. These findings suggest the importance of landscape change as a driver of potential AIV diversification and subtype emergence. This underscores the need for interdisciplinary approaches that integrate landscape dynamics, host movement, and viral evolution to better assess and mitigate future risk.</span></p>","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2503427122","usgsCitation":"Yin, S., Zhang, C., Teitelbaum, C.S., Si, Y., Zhang, G., Wang, X., Mao, D., Huangh, Z.Y., de Boer, W.F., Takekawa, J., Prosser, D.J., and Xiao, X., 2025, Landscape changes elevate the risk of avian influenza virus diversification and emergence in the East Asian–Australasian Flyway: Proceedings of the National Academy of Sciences, v. 122, no. 34, e2503427122, 9 p., https://doi.org/10.1073/pnas.2503427122.","productDescription":"e2503427122, 9 p.","ipdsId":"IP-176107","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":494467,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2503427122","text":"Publisher Index Page"},{"id":494397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China, Korea, Mongolia, Russia","otherGeospatial":"East Asian–Australasian Flyway","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              75,\n              20\n            ],\n            [\n              175,\n              20\n            ],\n            [\n              175,\n              75\n            ],\n            [\n              75,\n              75\n            ],\n            [\n              75,\n              20\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"122","issue":"34","noUsgsAuthors":false,"publicationDate":"2025-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Yin, Shenglai","contributorId":223544,"corporation":false,"usgs":false,"family":"Yin","given":"Shenglai","email":"","affiliations":[{"id":37803,"text":"Wageningen University","active":true,"usgs":false}],"preferred":false,"id":946706,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Chenchen","contributorId":360042,"corporation":false,"usgs":false,"family":"Zhang","given":"Chenchen","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":946707,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teitelbaum, Claire Stewart 0000-0001-5646-3184","orcid":"https://orcid.org/0000-0001-5646-3184","contributorId":295336,"corporation":false,"usgs":true,"family":"Teitelbaum","given":"Claire","email":"","middleInitial":"Stewart","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":946708,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Si, Yali","contributorId":223542,"corporation":false,"usgs":false,"family":"Si","given":"Yali","email":"","affiliations":[{"id":40738,"text":"Tsinghua University","active":true,"usgs":false}],"preferred":false,"id":946709,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhang, Geli","contributorId":206235,"corporation":false,"usgs":false,"family":"Zhang","given":"Geli","email":"","affiliations":[],"preferred":false,"id":946710,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, Xinxin","contributorId":304701,"corporation":false,"usgs":false,"family":"Wang","given":"Xinxin","email":"","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":946711,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mao, Dehua","contributorId":360045,"corporation":false,"usgs":false,"family":"Mao","given":"Dehua","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":946712,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Huangh, Zheng Y.X.","contributorId":360047,"corporation":false,"usgs":false,"family":"Huangh","given":"Zheng","middleInitial":"Y.X.","affiliations":[{"id":79946,"text":"Nanjing Forestry University","active":true,"usgs":false}],"preferred":false,"id":946713,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"de Boer, Willem Frederik","contributorId":360049,"corporation":false,"usgs":false,"family":"de Boer","given":"Willem","middleInitial":"Frederik","affiliations":[{"id":37803,"text":"Wageningen University","active":true,"usgs":false}],"preferred":false,"id":946714,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Takekawa, John","contributorId":330942,"corporation":false,"usgs":false,"family":"Takekawa","given":"John","affiliations":[{"id":32931,"text":"USGS - 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,{"id":70270422,"text":"70270422 - 2025 - Integrating hunter dynamics and waterfowl dynamics to inform harvest management","interactions":[],"lastModifiedDate":"2025-08-19T13:52:50.613209","indexId":"70270422","displayToPublicDate":"2025-08-17T08:50:39","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Integrating hunter dynamics and waterfowl dynamics to inform harvest management","docAbstract":"<p><span>The successful conservation and management of North American waterfowl relies upon an adaptive harvest management framework that accounts for changes in the system state and critical uncertainties related to the dynamics of waterfowl populations and habitats. Increasing recognition of the importance of the human dimensions of the harvest process, particularly those related to hunters, has motivated calls for the integration of social objectives into waterfowl conservation programs and decision making. We introduce a framework for modeling the dynamics of hunter populations and behavior alongside those of waterfowl populations. Using Bayesian estimation, we fit a dynamic state space model to observational data from the Mid-Continent mallard (</span><i>Anas platyrhynchos</i><span>) system over a 20-year period and estimated parameter values for the relative effects of a set of hypothesized drivers of hunter recruitment, retention, reactivation, participation, and success rates. We then made projections across 3 future scenarios to examine the continuation of current trends, the potential effects of a shift to a moderate regulatory framework as informed by expert elicitation, and increased hunter recruitment to maintain a stable hunter population. We found that a theoretical stable state exists for Mid-Continent mallard and hunter populations but that the influence of broader sociocultural shifts and increasing hunter mortality from an aging base pose significant challenges for efforts to stabilize the ongoing decline of active hunter numbers, even under favorable regulatory conditions. This modeling framework and results from it can be used to inform decision processes in the management of game populations that seek to include social objectives and assess the potential trade-offs of prioritizing across social and ecological objectives. We emphasize the need for focused human dimensions expertise throughout the process of fully integrating goals for waterfowl populations, habitats, and people in waterfowl conservation.</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70084","usgsCitation":"Berl, R.E., Devers, P.K., Boomer, G.S., and Runge, M., 2025, Integrating hunter dynamics and waterfowl dynamics to inform harvest management: Journal of Wildlife Management, no. Online First, https://doi.org/10.1002/jwmg.70084.","ipdsId":"IP-177503","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":498234,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.70084","text":"Publisher Index Page"},{"id":494296,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"issue":"Online First","noUsgsAuthors":false,"publicationDate":"2025-08-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Berl, Richard Eugene Waggaman 0000-0002-4154-1319","orcid":"https://orcid.org/0000-0002-4154-1319","contributorId":336851,"corporation":false,"usgs":true,"family":"Berl","given":"Richard","email":"","middleInitial":"Eugene Waggaman","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":946388,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Devers, Patrick K. 0000-0002-5281-6875","orcid":"https://orcid.org/0000-0002-5281-6875","contributorId":359900,"corporation":false,"usgs":false,"family":"Devers","given":"Patrick","middleInitial":"K.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":946389,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boomer, G. Scott 0000-0001-5854-3604","orcid":"https://orcid.org/0000-0001-5854-3604","contributorId":261408,"corporation":false,"usgs":false,"family":"Boomer","given":"G.","email":"","middleInitial":"Scott","affiliations":[{"id":7199,"text":"US FWS","active":true,"usgs":false}],"preferred":true,"id":946390,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":214737,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":946391,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70272650,"text":"70272650 - 2025 - Economic costs of invasive carps in the United States: Case study and management implications","interactions":[],"lastModifiedDate":"2025-12-03T15:39:53.981745","indexId":"70272650","displayToPublicDate":"2025-08-16T09:43:32","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Economic costs of invasive carps in the United States: Case study and management implications","docAbstract":"<p><span>Biological invasions can have far-reaching impacts and incur enormous monetary costs. Economic considerations play an important role in management decision-making. We used the invasion of U.S. waterways by silver (</span><i>Hypophthalmichthys molitrix</i><span>) and bighead (</span><i>H. nobilis</i><span>) carp as a case study of the costs of aquatic invasive species. Although these carps are well-known invaders, published reports on their economic costs are lacking. Our study included market values for commercial fisheries, non-market values for recreational fisheries, and management costs. Our results showed that by 2020, U.S. federal and state agencies had spent nearly $592 million in cumulative management costs. A difference-in-difference model testing for the effect of invasive carp on commercial harvest in invaded versus uninvaded reaches of the Mississippi and Illinois Rivers showed no statistical significance. A benefit transfer analysis of invasion effects on total economic value of recreational fishing, an important ecosystem service, in a heavily invaded section of the Illinois River estimated a total loss of more than $10 million over 10&nbsp;years. While there are other known impacts on ecosystem services, including alteration of aquatic food webs, plankton communities, and native fish communities, these could not be quantified in economic terms in our analysis.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10530-025-03647-9","usgsCitation":"Brown, E., Snapp, J.W., Huber, C., Caudill, J., and Grigelis, P.E., 2025, Economic costs of invasive carps in the United States: Case study and management implications: Biological Invasions, v. 27, no. 9, 191, 21 p., https://doi.org/10.1007/s10530-025-03647-9.","productDescription":"191, 21 p.","ipdsId":"IP-177332","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":497097,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10530-025-03647-9","text":"Publisher Index Page"},{"id":496984,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"conterminous United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n              ],\n              [\n                -94.32914,\n                48.67074\n              ],\n              [\n                -93.63087,\n                48.60926\n              ],\n              [\n                -92.61,\n                48.45\n              ],\n              [\n                -91.64,\n                48.14\n              ],\n              [\n                -90.83,\n            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]\n}","volume":"27","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-08-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Brown, Ellie 0000-0001-7798-830X ebrown@usgs.gov","orcid":"https://orcid.org/0000-0001-7798-830X","contributorId":200491,"corporation":false,"usgs":true,"family":"Brown","given":"Ellie","email":"ebrown@usgs.gov","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":false,"id":951168,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Snapp, Joseph W.","contributorId":363146,"corporation":false,"usgs":false,"family":"Snapp","given":"Joseph","middleInitial":"W.","affiliations":[{"id":37487,"text":"formerly USGS","active":true,"usgs":false}],"preferred":false,"id":951169,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huber, Christopher","contributorId":363148,"corporation":false,"usgs":false,"family":"Huber","given":"Christopher","affiliations":[{"id":86628,"text":"NPS, formerly USGS","active":true,"usgs":false}],"preferred":false,"id":951170,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caudill, James","contributorId":363149,"corporation":false,"usgs":false,"family":"Caudill","given":"James","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":951171,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grigelis, Peter E.","contributorId":363150,"corporation":false,"usgs":false,"family":"Grigelis","given":"Peter","middleInitial":"E.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":951172,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70270821,"text":"70270821 - 2025 - Evaluating the performance of multiple precipitation datasets over the transboundary Ili River Basin between China and Kazakhstan","interactions":[],"lastModifiedDate":"2025-08-25T15:21:07.451208","indexId":"70270821","displayToPublicDate":"2025-08-16T08:15:07","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3504,"text":"Sustainability","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the performance of multiple precipitation datasets over the transboundary Ili River Basin between China and Kazakhstan","docAbstract":"<p><span>The Ili River Basin is characterized by complex topography and diverse climatic zones with limited in situ observations. This study evaluates the performance of six widely used precipitation datasets, CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data), ERA5_Land (European Centre for Medium-Range Weather Forecasts—ECMWF Reanalysis 5_Land), GPCC (Global Precipitation Climatology Centre), IMERG (Integrated Multi-satellite Retrievals for GPM), PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks), and TerraClimate, against ground-based data from 2001 to 2023. The evaluation is conducted across multiple spatial scales and temporal resolutions. At the basin scale, most datasets exhibit strong correlations with in situ observations across all temporal scales (r &gt; 0.7), except for PERSIANN, which demonstrates a relatively weaker performance during summer and winter (r &lt; 0.6). All datasets except ERA5_ Land show low annual and monthly bias (&lt;5%), although larger errors are observed during summer, particularly for IMERG and PERSIANN. Dataset performance generally declines with increasing elevation. Basin-wide gridded evaluations reveal distinct spatial variations across all elevation zones, with CHIRPS showing the strongest ability to capture orographic precipitation gradients throughout the basin. All datasets correctly identified 2008 as a drought year and 2016 as a wet year, even though the magnitude and spatial resolution of the anomalies varied among them. These findings highlight the importance of selecting precipitation datasets that are suited to the complex topographic and climatic characteristics of transboundary basins. Our study provides valuable insights for improving hydrological modeling and can be used for water sustainability and flood–drought mitigation support activities in the Ili River Basin.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/su17167418","usgsCitation":"Duisebek, B., Senay, G., Ojima, D.S., Zhang, T., Sagin, J., and Wang, X., 2025, Evaluating the performance of multiple precipitation datasets over the transboundary Ili River Basin between China and Kazakhstan: Sustainability, v. 17, no. 16, 7418, 26 p., https://doi.org/10.3390/su17167418.","productDescription":"7418, 26 p.","ipdsId":"IP-181853","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":495056,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/su17167418","text":"Publisher Index Page"},{"id":494743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China, Kazakhstan","otherGeospatial":"Ili River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              46.71910209135149,\n              50.09770097338648\n            ],\n            [\n              46.71910209135149,\n              44.15010644271524\n            ],\n            [\n              84.48446379774907,\n              44.15010644271524\n            ],\n            [\n              84.48446379774907,\n              50.09770097338648\n            ],\n            [\n              46.71910209135149,\n              50.09770097338648\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"17","issue":"16","noUsgsAuthors":false,"publicationDate":"2025-08-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Duisebek, Baktybek","contributorId":360498,"corporation":false,"usgs":false,"family":"Duisebek","given":"Baktybek","affiliations":[{"id":86016,"text":"Kazakh British Technical University","active":true,"usgs":false}],"preferred":false,"id":947122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":166812,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":947123,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ojima, Dennis S.","contributorId":208511,"corporation":false,"usgs":false,"family":"Ojima","given":"Dennis","email":"","middleInitial":"S.","affiliations":[{"id":37812,"text":"Colorado State University; North Central Climate Science Center","active":true,"usgs":false}],"preferred":false,"id":947124,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhang, Tibin","contributorId":360499,"corporation":false,"usgs":false,"family":"Zhang","given":"Tibin","affiliations":[{"id":86019,"text":"State Key Laboratory of Soil and Water Conservation Science and Engineering, Northwest A&F University","active":true,"usgs":false}],"preferred":false,"id":947125,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sagin, Janay","contributorId":360500,"corporation":false,"usgs":false,"family":"Sagin","given":"Janay","affiliations":[{"id":86016,"text":"Kazakh British Technical University","active":true,"usgs":false}],"preferred":false,"id":947126,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, Xuejiao","contributorId":271179,"corporation":false,"usgs":false,"family":"Wang","given":"Xuejiao","email":"","affiliations":[{"id":12433,"text":"China University of Geosciences","active":true,"usgs":false}],"preferred":false,"id":947127,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70270385,"text":"70270385 - 2025 - RAD (Resist-Accept-Direct) switch points and triggers for adaptation planning","interactions":[],"lastModifiedDate":"2025-08-18T14:13:27.087542","indexId":"70270385","displayToPublicDate":"2025-08-15T09:05:09","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"RAD (Resist-Accept-Direct) switch points and triggers for adaptation planning","docAbstract":"<p><span>Climate change is transforming ecosystems globally. The Resist-Accept-Direct (RAD) framework has gained traction within many natural resource management institutions to help consider the decision space in response to this transformation. Because RAD helps manage for directional change, RAD choices entail considering which RAD pathway to implement and for how long. For example, one may&nbsp;</span><i>accept</i><span>&nbsp;a slowly changing ecosystem, but at a certain point, decide to begin&nbsp;</span><i>resisting</i><span>&nbsp;or&nbsp;</span><i>directing</i><span>&nbsp;the change an ecosystem is experiencing. Alternatively, one may begin&nbsp;</span><i>resisting</i><span>&nbsp;an ecosystem transformation, but ultimately realize resistance is no longer feasible based on cost or efficacy. These choices are challenging and encompass broad domains of cultural, ecological, financial, organizational, public, regulatory, and technological considerations to determine when to switch RAD pathways. We introduce the concepts of RAD switch points and triggers to help support these decision processes. We illustrate these concepts using case studies on walleye (</span><i>Sander vitreus</i><span>) stocking decisions in Wisconsin, wildfire response in the Greater Yellowstone Ecosystem, and bull trout (</span><i>Salvelinus confluentus</i><span>) management in Oregon, USA. Synthesizing across these examples, we delineate key points for decision makers as they (iteratively) reevaluate among the RAD pathways as conditions continue to change.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2025.126419","usgsCitation":"Lynch, A.J., Ashander, J., Ciocco, A., Cravens, A.E., Dassow, C.J., Dee, L.E., Dunham, J., Eaton, M.J., Embke, H., Hennessy, J., Latzka, A., Lawrence, D.J., Littell, J., Miller, B.W., Palasti, L., Runge, M., Sass, G., Shultz, A.D., Siegel, K., Svancara, L.K., Thompson, L., Thurman, L., Valler, J.B., Weiskopf, S.R., and Yocum, H.M., 2025, RAD (Resist-Accept-Direct) switch points and triggers for adaptation planning: Journal of Environmental Management, v. 392, 126419, 13 p., https://doi.org/10.1016/j.jenvman.2025.126419.","productDescription":"126419, 13 p.","ipdsId":"IP-165065","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":494254,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"392","noUsgsAuthors":false,"publicationDate":"2025-08-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Lynch, Abigail J. 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":204271,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","middleInitial":"J.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":946256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ashander, Jaime 0000-0002-1841-4768","orcid":"https://orcid.org/0000-0002-1841-4768","contributorId":294949,"corporation":false,"usgs":true,"family":"Ashander","given":"Jaime","email":"","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":946257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ciocco, Anthony 0000-0002-5849-888X","orcid":"https://orcid.org/0000-0002-5849-888X","contributorId":356914,"corporation":false,"usgs":true,"family":"Ciocco","given":"Anthony","affiliations":[{"id":85276,"text":"NC CASC","active":true,"usgs":false}],"preferred":true,"id":946258,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cravens, Amanda E. 0000-0002-0271-7967 aecravens@usgs.gov","orcid":"https://orcid.org/0000-0002-0271-7967","contributorId":196752,"corporation":false,"usgs":true,"family":"Cravens","given":"Amanda","email":"aecravens@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":946259,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dassow, Colin J.","contributorId":293206,"corporation":false,"usgs":false,"family":"Dassow","given":"Colin","email":"","middleInitial":"J.","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":946260,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dee, Laura E. 0000-0003-0471-1371","orcid":"https://orcid.org/0000-0003-0471-1371","contributorId":213455,"corporation":false,"usgs":false,"family":"Dee","given":"Laura","email":"","middleInitial":"E.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":946261,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dunham, Jason 0000-0002-6268-0633","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":220078,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":946262,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Eaton, Mitchell J. 0000-0001-7324-6333","orcid":"https://orcid.org/0000-0001-7324-6333","contributorId":213526,"corporation":false,"usgs":true,"family":"Eaton","given":"Mitchell","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":946263,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Embke, Holly Susan 0000-0002-9897-7068","orcid":"https://orcid.org/0000-0002-9897-7068","contributorId":358337,"corporation":false,"usgs":true,"family":"Embke","given":"Holly Susan","affiliations":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":946265,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hennessy, Joseph M.","contributorId":199495,"corporation":false,"usgs":false,"family":"Hennessy","given":"Joseph M.","affiliations":[],"preferred":false,"id":946266,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Latzka, Alexander W.","contributorId":348855,"corporation":false,"usgs":false,"family":"Latzka","given":"Alexander W.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":946267,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lawrence, David J","contributorId":242819,"corporation":false,"usgs":false,"family":"Lawrence","given":"David","email":"","middleInitial":"J","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":946268,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Littell, Jeremy S. 0000-0002-5302-8280","orcid":"https://orcid.org/0000-0002-5302-8280","contributorId":205907,"corporation":false,"usgs":true,"family":"Littell","given":"Jeremy","middleInitial":"S.","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":946269,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Miller, Brian W. 0000-0003-1716-1161","orcid":"https://orcid.org/0000-0003-1716-1161","contributorId":196603,"corporation":false,"usgs":true,"family":"Miller","given":"Brian","email":"","middleInitial":"W.","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":946270,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Palasti, Luca","contributorId":359786,"corporation":false,"usgs":false,"family":"Palasti","given":"Luca","affiliations":[{"id":12502,"text":"University of Colorado - Boulder","active":true,"usgs":false}],"preferred":false,"id":946271,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":214737,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":946272,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Sass, Gregory","contributorId":359787,"corporation":false,"usgs":false,"family":"Sass","given":"Gregory","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":946273,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Shultz, Aaron D.","contributorId":303739,"corporation":false,"usgs":false,"family":"Shultz","given":"Aaron","email":"","middleInitial":"D.","affiliations":[{"id":16233,"text":"Great Lakes Indian Fish and Wildlife Commission","active":true,"usgs":false}],"preferred":false,"id":946274,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Siegel, Katherine","contributorId":359788,"corporation":false,"usgs":false,"family":"Siegel","given":"Katherine","affiliations":[{"id":7044,"text":"University of Toronto","active":true,"usgs":false}],"preferred":false,"id":946275,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Svancara, Leona Kay 0009-0007-1936-6079","orcid":"https://orcid.org/0009-0007-1936-6079","contributorId":359789,"corporation":false,"usgs":true,"family":"Svancara","given":"Leona","middleInitial":"Kay","affiliations":[{"id":49226,"text":"Northwest Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":946276,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Thompson, Laura 0000-0002-7884-6001","orcid":"https://orcid.org/0000-0002-7884-6001","contributorId":207364,"corporation":false,"usgs":true,"family":"Thompson","given":"Laura","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":946277,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Thurman, Lindsey 0000-0003-3142-4909","orcid":"https://orcid.org/0000-0003-3142-4909","contributorId":269425,"corporation":false,"usgs":true,"family":"Thurman","given":"Lindsey","email":"","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":946278,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Valler, Jackson Brear 0009-0006-0076-7481","orcid":"https://orcid.org/0009-0006-0076-7481","contributorId":359790,"corporation":false,"usgs":true,"family":"Valler","given":"Jackson","middleInitial":"Brear","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":946279,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Weiskopf, Sarah R. 0000-0002-5933-8191","orcid":"https://orcid.org/0000-0002-5933-8191","contributorId":207699,"corporation":false,"usgs":true,"family":"Weiskopf","given":"Sarah","email":"","middleInitial":"R.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":946280,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Yocum, Heather M. 0000-0002-3754-4330","orcid":"https://orcid.org/0000-0002-3754-4330","contributorId":265513,"corporation":false,"usgs":false,"family":"Yocum","given":"Heather","email":"","middleInitial":"M.","affiliations":[{"id":54706,"text":"Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":946281,"contributorType":{"id":1,"text":"Authors"},"rank":25}]}}
,{"id":70270388,"text":"70270388 - 2025 - Relationships between water quality, stream metabolism, and water stargrass growth in the lower Yakima River, 2018 to 2020","interactions":[],"lastModifiedDate":"2025-08-18T13:32:56.593268","indexId":"70270388","displayToPublicDate":"2025-08-15T08:30:05","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":18346,"text":"EarthArXiv","active":true,"publicationSubtype":{"id":32}},"title":"Relationships between water quality, stream metabolism, and water stargrass growth in the lower Yakima River, 2018 to 2020","docAbstract":"<p><span>Since the early 2000s, water clarity on the lower Yakima River has improved. Changes in best management practices combined with a total maximum daily load for suspended sediment led to these improved conditions. As water clarity improved, so did conditions for aquatic plants; the clearer the water, the better the light penetration, and dramatic increases in plant biomass were observed. In the lower Yakima River, beds of native water stargrass (grass-leaf mud-plantain, Heteranthera dubia) are prolific and can extend bank to bank in some locations. Increased primary productivity can alter local water quality by increasing daily swings of dissolved oxygen (DO) and pH from photosynthesis. In this study, we collected continuous water quality data for 2.5 years at three sites on the lower Yakima River to provide a detailed examination of water quality conditions. These sites were located just below the Prosser Dam (Prosser site, USGS station 12509489), at a long-term USGS streamgage in Benton County (Kiona site, USGS station 12510500), and in West Richland, WA (Van Giesen site; USGS station 12511800). In addition to the continuous water quality data collected, estimates of water stargrass biomass were made through the growing season (June through September) during water years 2018–2020. The main objectives of this study were to document water quality conditions on the lower Yakima River and to analyze if there was a statistical relation between the amount of water stargrass biomass and the observed daily cycles of water quality.</span><br><br><span>During summer, frequent exceedances of established water quality criteria were documented each year during this study. Maximum daily temperatures exceeded 21o C, minimum DO concentrations were below 8 milligrams per liter (mg/L), and maximum pH surpassed 8.5 almost every day from June through August each water year across all three monitoring locations. Water stargrass biomass tended to increase from June through August and September but was ‘reset’ by the following summer likely from high winter and spring streamflows and natural die-off. Results from this study suggest that spring peak discharge and average spring discharge affects late-season water stargrass biomass. In 2018, the highest peak discharge of the study took place, and the August water stargrass biomass values were lower in 2018 than in 2019 and 2020.</span><br><br><span>Seven different water quality metrics were computed for a 7-day and 28-day period prior to each water stargrass sample to examine possible correlations between the plant biomass and water quality. We examined daily maximum temperature, DO minimum, DO range, pH maximum, pH range, mean nitrate, and nitrate range. While there were some statistically significant correlations among the seven water quality metrics and median water stargrass biomass, the correlations were not consistent across all three sites. At the Prosser site, the 7-day average daily maximum pH and average daily pH range showed significant correlations with median water stargrass biomass. At the Kiona site, both the 7-day and 28-day mean nitrate values showed a significant relationship to median water stargrass biomass. At the Van Giesen site, there were no significant correlations between the seven water quality metrics and median water stargrass biomass. However, whole-stream estimates of gross primary productivity at the Kiona site, which incorporate the entire river community, were related to temperature, DO, and pH indicating the whole river community is influencing surface water quality to some extent.</span><br><br><span>Additional data on water stargrass biomass and continuous water quality could help elucidate the complex interactions between growth and water quality. At a minimum, collection of water stargrass biomass data near the end of the growing season (mid to late August) could be added to locations where continuous water quality and streamflow discharge measurements are also being collected. In addition, experimental removal of water stargrass and its effects on local water quality could provide insight into the complex relationships between water stargrass growth and water quality. Finally, further investigations into streamflow and its effects on water stargrass could be improved. Our data showed a qualitative relationship between spring peak discharge, average spring discharge, and August water stargrass biomass, but more data are needed to confirm this. If spring high streamflows are important for late-season biomass, then targeted flow releases from reservoirs in the upper watershed could be used to slow down water stargrass growth during summer months.</span></p>","language":"English","publisher":"EarthArXiv","doi":"10.31223/X5JT8P","usgsCitation":"Sheibley, R.W., Appel, M., and Foreman, J.R., 2025, Relationships between water quality, stream metabolism, and water stargrass growth in the lower Yakima River, 2018 to 2020: EarthArXiv, preprint posted August 15, 2025, https://doi.org/10.31223/X5JT8P.","productDescription":"89 p.","ipdsId":"IP-179498","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":494252,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2025-08-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Sheibley, Rich W. 0000-0003-1627-8536 sheibley@usgs.gov","orcid":"https://orcid.org/0000-0003-1627-8536","contributorId":3044,"corporation":false,"usgs":true,"family":"Sheibley","given":"Rich","email":"sheibley@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":946282,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Appel, Marcella","contributorId":272175,"corporation":false,"usgs":false,"family":"Appel","given":"Marcella","email":"","affiliations":[],"preferred":true,"id":946283,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foreman, James R. 0000-0003-0535-4580 jforeman@usgs.gov","orcid":"https://orcid.org/0000-0003-0535-4580","contributorId":3669,"corporation":false,"usgs":true,"family":"Foreman","given":"James","email":"jforeman@usgs.gov","middleInitial":"R.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":false,"id":946284,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70271317,"text":"70271317 - 2025 - Evapotranspiration terminology and definitions","interactions":[],"lastModifiedDate":"2026-02-10T13:40:04.779874","indexId":"70271317","displayToPublicDate":"2025-08-15T08:12:55","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":22342,"text":"Irrigation and Drainage Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Evapotranspiration terminology and definitions","docAbstract":"<p><span>Evapotranspiration (ET), the combined process of evaporation from soil and plant surfaces and transpiration from plant tissue, plays a pivotal role in the global water and energy balance. Accurately quantifying ET at various spatial scales is important for diverse applications, including irrigation and natural resource management. While efforts to standardize ET methodology have progressed over the last few decades, some confusion and disagreements in terminology persist among communities of researchers and practitioners involved in the measurement, estimation, and simulation of ET. This technical note addresses the historical evolution and standardization of ET terminology, aiming to reduce and mitigate disparities in definitions and usage by advocating for standardized definitions and emphasizing the adoption of reference ET (</span><span>ET<sub>ref</sub></span><span>) terminology to promote consistency and accuracy and to avoid ambiguity. This document provides comprehensive definitions of key terms, including crop (i.e.,&nbsp;vegetation cover) coefficients, consumptive use (CU), actual crop evapotranspiration (</span><span>ET<sub>a</sub></span><span>), and&nbsp;</span><span>ET<sub>ref</sub></span><span>&nbsp;variants for short (grass,&nbsp;</span><span>ET<sub>o</sub></span><span>) and tall (alfalfa,&nbsp;</span><span>ET<sub>r</sub></span><span>) reference crops. Practical discussion on several relevant topics is given: (1)&nbsp;single and dual crop coefficient approaches, (2)&nbsp;applications to nonagricultural vegetation, (3)&nbsp;recommended subscripts for terms, (4)&nbsp;practical guidelines and considerations for&nbsp;</span><span>ET<sub>ref</sub></span><span>&nbsp;calculation, (5)&nbsp;encouragement to replace “potential ET” terminology with better terms, (6)&nbsp;clarification on maximum ET (</span><span>ET<sub>max</sub></span><span>) and maximum crop coefficient (</span><span>K<sub>c max</sub></span><span>) terms, (7)&nbsp;ET products derived from remote sensing, (8)&nbsp;a brief description of the role of ET in water rights, and (9)&nbsp;a figure illustrating the use of the terms defined herein. The conclusion emphasizes the importance of consistent terminology for effective communication among researchers and end-users, which will facilitate the adoption of standardized ET methods and technologies. This technical note was created by the American Society of Civil Engineers, Environmental and Water Resources Institute (ASCE-EWRI), Evapotranspiration in Irrigation and Hydrology Committee, with input and endorsement from other relevant organizations in the United States and internationally. 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,{"id":70270266,"text":"sir20255076A - 2025 - Decision framing overview and performance of management alternatives for bison and elk feedground management at the National Elk Refuge in Jackson, Wyoming","interactions":[{"subject":{"id":70261162,"text":"sir20245119A - 2025 - Decision framing overview and performance of management alternatives for bison and elk feedground management at the National Elk Refuge in Jackson, Wyoming","indexId":"sir20245119A","publicationYear":"2025","noYear":false,"chapter":"A","displayTitle":"Decision Framing Overview and Performance of Management Alternatives for Bison and Elk Feedground Management at the National Elk Refuge in Jackson, Wyoming","title":"Decision framing overview and performance of management alternatives for bison and elk feedground management at the National Elk Refuge in Jackson, Wyoming"},"predicate":"SUPERSEDED_BY","object":{"id":70270266,"text":"sir20255076A - 2025 - Decision framing overview and performance of management alternatives for bison and elk feedground management at the National Elk Refuge in Jackson, Wyoming","indexId":"sir20255076A","publicationYear":"2025","noYear":false,"chapter":"A","title":"Decision framing overview and performance of management alternatives for bison and elk feedground management at the National Elk Refuge in Jackson, Wyoming"},"id":1},{"subject":{"id":70270266,"text":"sir20255076A - 2025 - Decision framing overview and performance of management alternatives for bison and elk feedground management at the National Elk Refuge in Jackson, Wyoming","indexId":"sir20255076A","publicationYear":"2025","noYear":false,"chapter":"A","displayTitle":"Decision Framing Overview and Performance of Management Alternatives for Bison and Elk Feedground Management at the National Elk Refuge in Jackson, Wyoming","title":"Decision framing overview and performance of management alternatives for bison and elk feedground management at the National Elk Refuge in Jackson, Wyoming"},"predicate":"IS_PART_OF","object":{"id":70270249,"text":"sir20255076 - 2025 - Decision analysis in support of the National Elk Refuge bison and elk management plan","indexId":"sir20255076","publicationYear":"2025","noYear":false,"title":"Decision analysis in support of the National Elk Refuge bison and elk management plan"},"id":2}],"isPartOf":{"id":70270249,"text":"sir20255076 - 2025 - Decision analysis in support of the National Elk Refuge bison and elk management plan","indexId":"sir20255076","publicationYear":"2025","noYear":false,"title":"Decision analysis in support of the National Elk Refuge bison and elk management plan"},"lastModifiedDate":"2026-02-03T15:02:22.288635","indexId":"sir20255076A","displayToPublicDate":"2025-08-14T15:50:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5076","chapter":"A","displayTitle":"Decision Framing Overview and Performance of Management Alternatives for Bison and Elk Feedground Management at the National Elk Refuge in Jackson, Wyoming","title":"Decision framing overview and performance of management alternatives for bison and elk feedground management at the National Elk Refuge in Jackson, Wyoming","docAbstract":"<p>This report was developed to evaluate the performance of a set of proposed alternatives for&nbsp;<i>Cervus elaphus canadensis</i>&nbsp;(elk) and&nbsp;<i>Bison bison</i>&nbsp;(bison) management at the National Elk Refuge in Wyoming, U.S.A., and to inform a National Environmental Policy Act Environmental Impact Statement focused on developing the next “Bison and Elk Management Plan” (BEMP). 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Bison and elk provide opportunities for wildlife-related recreation and contribute to the tourism industry in and around Jackson, Wyoming. Over the last century, the Refuge has provisioned supplemental feed to elk and, more recently, bison during winter months to ensure adequate forage and prevent starvation and conflict with private landowners. However, supplemental feeding artificially aggregates animals and can increase rates of disease transmission and localized damage to sensitive habitats near the feeding areas. This report presents analyses and results to support two of the nine management objectives in the next “Bison and Elk Management Plan,” with a particular focus on the social and economic consequences of five management alternatives considered in this study. The alternatives are to continue feeding bison and elk during winter months on the Refuge, stop feeding after CWD is measured at 3 percent prevalence or above in the Jackson elk herd, stop feeding immediately, reduce feeding for five years and then stop feeding, and increase elk harvest for five years and then stop feeding. These alternatives are anticipated to alter bison and elk population and space-use dynamics, with corresponding effects on wildlife-related recreation and tourism, including the number of visitors and sleigh-ride participants on the Refuge, and hunters and outfitters within the Jackson Elk Herd Unit. The performance of each of this study’s alternatives was variable, resulting in overlap in the performance of alternatives on the select objectives over the next 20 years. Generally, visitation-related objectives performed better under the continue feeding alternative, whereas hunting-related objectives performed better under the increase harvest alternative. The results presented here may assist U.S. Fish and Wildlife Service decision makers in balancing social and economic benefits identified in the decision-making process for the “Bison and Elk Management Plan” with other objectives evaluated in this report.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Decision analysis in support of the National Elk Refuge Bison and Elk Management Plan","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255076E","collaboration":"Prepared in cooperation with the National Park Service, U.S. Fish and Wildlife Service, and Wyoming Game and Fish Department","programNote":"Ecosystems Mission Area—Biological Threats & Invasive Species Research Program","usgsCitation":"McEachran, M.C., Don Carlos, A., Cotterill, G.G., Cole, E.K., and Cook, J.D., 2025, Estimating the social and economic consequences of proposed management alternatives at the National Elk Refuge in Jackson, Wyoming, chap. E <i>of</i> Cook, J.D., and Cross, P.C., eds., Decision analysis in support of the National Elk Refuge bison and elk management plan: U.S. Geological Survey Scientific Investigations Report 2025–5076, 11 p., https://doi.org/10.3133/sir20255076E. 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The reintroduced population in and around Jackson, Wyoming has averaged 485 individuals between 2018–2023 and is the subject of a planning process to inform management strategies that will guide the U.S. Fish and Wildlife’s next “Bison and Elk Management Plan” for the National Elk Refuge. This small population may benefit from historical winter-feeding operations on the National Elk Refuge because those operations may increase overwinter survival and limit human-bison conflicts, which are the number of individual bison that engage in nuisance, damaging, or otherwise aggressive behaviors with humans and livestock, that may lead to culling and other sources of mortality (for example, vehicle collisions). To inform the next “Bison and Elk Management Plan,” the U.S. Geological Survey used a population model to evaluate five management alternatives for bison and <i>Cervus elaphus canadensis</i> feedground operations that included continuing the elk and bison feeding program, immediately stopping the feeding program, and three other alternatives that would phase out the feeding program after a period of time. The results indicate that the bison population would be expected to decline over the next 20 years under all alternatives that stop feeding bison on the refuge. Further, this decline would lead to an associated reduction in bison harvest opportunities for resident, nonresident, and Tribal hunters. Finally, human-bison conflicts would also be expected to increase under the no feeding alternatives because bison may venture onto private lands in greater numbers if feed is not provisioned during winter months. In combination, these results suggest that feeding may lead to better outcomes for bison over the next 20 years; however, these effects may be traded off against other downsides of the feedground program, such as increased rates of animal-to-animal contact on feedgrounds that can lead to disease transmission.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Decision analysis in support of the National Elk Refuge Bison and Elk Management Plan","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255076D","collaboration":"Prepared in cooperation with the National Park Service, U.S. Fish and Wildlife Service, and Wyoming Game and Fish Department","programNote":"Ecosystems Mission Area—Biological Threats & Invasive Species Research Program","usgsCitation":"Cook, J.D., McEachran, M.C., Cotterill, G.G., and Cole, E.K., 2025, Bison population dynamics, harvest, and human conflict potential under feedground management alternatives at the National Elk Refuge in Jackson, Wyoming, chap. D <i>of</i> Cook, J.D., and Cross, P.C., eds., Decision analysis in support of the National Elk Refuge bison and elk management plan: U.S. Geological Survey Scientific Investigations Report 2025–5076, 24 p., https://doi.org/10.3133/sir20255076D. 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A resource selection function evaluated measurable attributes of interest to managers, including elk use of private property and sensitive habitat types at monthly timesteps and varying winter conditions. The study area boundaries were created through an expert elicitation process and consist of the Jackson Elk Herd Unit, Grand Teton National Park, the National Elk Refuge, and the northern third of the Fall Creek Elk Herd Unit. For each of the five alternatives, we distributed monthly elk numbers calculated in a concurrent analysis that simulated chronic wasting disease dynamics in this system for 20 years. Measurable attributes representing potential elk use of (1) private property, (2) cattle properties as an index of <i>Brucella abortus</i> risk, and sensitive habitats consisting of (3) <i>Populus tremuloides</i> Michx. (quaking aspen), (4) <i>Populus angustifolia</i> E. James (narrowleaf cottonwood), and (5) <i>Salix</i> L. (willow) in core winter use areas all closely followed the declines of elk abundance projected by the elk chronic wasting disease model. After 20 years, the continue feeding alternative ranked most favorably in terms of limiting elk days on private property and reducing brucellosis risk from elk to cattle because this alternative concentrated elk on the National Elk Refuge and resulted in the lowest elk population sizes. However, other management alternatives, including increase harvest and reduce feeding, tended to limit elk use of sensitive quaking aspen, narrowleaf cottonwood, and willow habitats during winter (December–April).</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Decision analysis in support of the National Elk Refuge Bison and Elk Management Plan","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255076C","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture, National Park Service, U.S. Fish and Wildlife Service, and Wyoming Game and Fish Department","programNote":"Ecosystems Mission Area—Biological Threats & Invasive Species Research Program and the Species Management Research Program","usgsCitation":"Cotterill, G.G., Cross, P.C., Cole, E.K., Cook, J.D., McEachran, M.C., and Graves, T.A., 2025, Evaluating elk distribution and conflict under proposed management alternatives at the National Elk Refuge in Jackson, Wyoming, chap. C <i>of</i> Cook, J.D., and Cross, P.C., eds., Decision analysis in support of the National Elk Refuge bison and elk management plan: U.S. Geological Survey Scientific Investigations Report 2025–5076, 32 p., https://doi.org/10.3133/sir20255076C. [Supersedes USGS Scientific Investigations Report 2024–5119.]","productDescription":"Report: vii, 32 p.; Software Release","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":494123,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5076/c/sir20255076C.XML","description":"SIR 2025-5076 C XML"},{"id":494138,"rank":6,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P1486NQE","text":"USGS software release","linkHelpText":"- Supporting code for—Evaluating elk distribution and conflict under proposed management alternatives at the National Elk Refuge in Jackson, Wyoming (version 2.0)"},{"id":494120,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5076/c/coverthb.jpg"},{"id":494121,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5076/c/sir20255076C.pdf","text":"Report","size":"6.58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5076 C PDF"},{"id":494124,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5076/c/images"},{"id":494122,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255076C/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5076 C HTML"}],"country":"United States","state":"Wyoming","otherGeospatial":"National Elk Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -110.78225266437141,\n              43.46790181387567\n            ],\n            [\n              -110.72445411600302,\n              43.480764457816235\n            ],\n            [\n              -110.70981181708308,\n              43.502568770827935\n            ],\n            [\n              -110.6897749869821,\n              43.51262964481907\n            ],\n            [\n              -110.6628023310768,\n              43.52213004158219\n            ],\n            [\n              -110.64353614828745,\n              43.53665716685947\n            ],\n            [\n              -110.62349931818646,\n              43.55620738705895\n            ],\n            [\n              -110.5972973095928,\n              43.598637460483474\n            ],\n            [\n              -110.59883860421601,\n              43.62653567653447\n            ],\n            [\n              -110.6520132687147,\n              43.62207283164909\n            ],\n            [\n              -110.6897749869821,\n              43.60477617840215\n            ],\n            [\n              -110.73216058911865,\n              43.56458411181504\n            ],\n            [\n              -110.74680288803886,\n              43.517100606095084\n            ],\n            [\n              -110.76067453964718,\n              43.50480466552287\n            ],\n            [\n              -110.78225266437141,\n              43.46790181387567\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Center Director, <a href=\"https://www.usgs.gov/centers/norock\" data-mce-href=\"https://www.usgs.gov/centers/norock\">Northern Rocky Mountain Science Center</a><br>U.S. Geological Survey<br>2327 University Way, Suite 2<br>Bozeman, MT 59715</p><p><a href=\"../contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results</li><li>Summary</li><li>References Cited</li><li>Appendix C1. Core Elk Winter Areas Defined by the Expert Panel</li><li>Appendix C2. Predicted Elk Use of Winter Feedgrounds in the Northern Fall Creek Elk Herd Unit</li><li>Appendix C3. Adjusted Use Predictions for Jackson Elk Attending State Feedgrounds in the Gros Ventre River Drainage or in the Native Winter Range</li><li>Appendix C4. Elk Summer Predictive Maps from the Broad-Scale Resource Selection Function</li><li>Appendix C5. Elk Predictive Maps from the National Elk Refuge Winter Resource Selection Function</li><li>Appendix C6. Near-Term Rankings (5 years) of Measurable Attributes</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2025-08-14","noUsgsAuthors":false,"publicationDate":"2025-08-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Cotterill, Gavin G. 0000-0002-1408-778X","orcid":"https://orcid.org/0000-0002-1408-778X","contributorId":346534,"corporation":false,"usgs":true,"family":"Cotterill","given":"Gavin","middleInitial":"G.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":946084,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cross, Paul C. 0000-0001-8045-5213","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":219533,"corporation":false,"usgs":true,"family":"Cross","given":"Paul C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":946085,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cole, Eric K. 0000-0002-2229-5853 eric_cole@fws.gov","orcid":"https://orcid.org/0000-0002-2229-5853","contributorId":348261,"corporation":false,"usgs":true,"family":"Cole","given":"Eric","email":"eric_cole@fws.gov","middleInitial":"K.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":true,"id":946086,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cook, Jonathan D. 0000-0001-7000-8727","orcid":"https://orcid.org/0000-0001-7000-8727","contributorId":291411,"corporation":false,"usgs":true,"family":"Cook","given":"Jonathan","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":946087,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McEachran, Margaret C. 0000-0002-8390-451X","orcid":"https://orcid.org/0000-0002-8390-451X","contributorId":346535,"corporation":false,"usgs":true,"family":"McEachran","given":"Margaret C.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":946088,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Graves, Tabitha A. 0000-0001-5145-2400 tgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":5898,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha","email":"tgraves@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":946089,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
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The U.S. Geological Survey facilitated a structured decision-making process for the U.S. Fish and Wildlife Service to develop the alternatives and the criteria (performance metrics) for evaluating the alternatives. Chapter A provides scoping details of the report, a summary of the 19 metrics that are used to evaluate the performance of each of 6 alternatives, and methodological details of 2 performance metrics that were not covered in other technical chapters. Chapter B analyzes elk population and chronic wasting disease dynamics under the five initial alternatives. Chapter C evaluates elk space-use based on data collected from global positioning system collars on elk and expert elicitation for scenarios with limited data. Chapter D evaluates bison population dynamics, conflict, and harvest patterns under the five initial alternatives. Chapter E assesses social and economic consequences. Chapter F is newly added to this superseding report and details the analysis and results of a new alternative that was developed after discussion among the lead and cooperating agencies working on the BEMP. The full set of six alternatives are anticipated to have varying affects on bison and elk population abundance and private land use, wildlife-related recreation and tourism, and hunters and outfitters in the region. 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Further, three of the four alternative D scenarios resulted in fewer elk-use days on sensitive aspen, willow, and cottonwood habitat types compared to continuing to feed; the 7 percent CWD trigger scenario resulted in higher elk-use days on cottonwood and willow habitats compared to continued feeding, but fewer elk-use days on aspen habitats. 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