{"pageNumber":"60","pageRowStart":"1475","pageSize":"25","recordCount":41028,"records":[{"id":70262208,"text":"70262208 - 2024 - Effects of exploitation and emigration on apparent survival of Walleye in Lake Sharpe, South Dakota","interactions":[],"lastModifiedDate":"2025-01-15T17:14:02.527341","indexId":"70262208","displayToPublicDate":"2024-12-12T11:08:25","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Effects of exploitation and emigration on apparent survival of Walleye in Lake Sharpe, South Dakota","docAbstract":"

Objective

In 2017, we began a 5-year mark–recapture study to estimate apparent survival of Walleye Sander vitreus and angler exploitation in Lake Sharpe, South Dakota, and inform management strategies for this fishery. The study revealed substantial downstream emigration of Walleye; therefore, we also examined the influence of emigration on apparent mortality.

Methods

We estimated Walleye apparent survival using the Seber parameterization of the dead recovery model. In our models, we included factors influencing voluntary fish release, as well as harvest restrictions, tagging location, and year. We used a multistate Markov model to estimate emigration in relation to Walleye total length, sex, and tagging location, as well as annual reservoir discharge. The exploitation and emigration estimates informed our interpretations of annual Walleye apparent survival.

Result

Apparent survival patterns were explained by an interaction between Walleye length and a minimum harvest length restriction. Apparent survival was lower during July and August, when the minimum harvest length limit was suspended, and results suggest that anglers were willing to release preferred sizes (≥508 mm) when able to harvest smaller (<381 mm) Walleye. Annual apparent survival, exploitation, and emigration estimates ranged between 15% and 47%, 8% and 25%, and 11% and 28%, respectively. Emigration was influenced by tagging location and annual discharge: increasing with proximity to Big Bend dam and during high annual flows. Although years with high exploitation or emigration corresponded to years with low apparent survival, estimates did not explain the magnitude of mortality or emigration indicated by survival models.

Conclusion

Our results revealed that harvest–release decisions by Walleye anglers in Lake Sharpe are primarily influenced by regulations, although exploitation was not a significant source of mortality. Annual patterns in apparent survival indicate high mortality or emigration. Continued investigations into immigration and emigration and sources of mortality of Lake Sharpe Walleye are warranted to better inform management strategies for the fishery.

","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.11062","usgsCitation":"Sacco, L., Fincel, M., Goble, C., Davis, T., and Chipps, S.R., 2024, Effects of exploitation and emigration on apparent survival of Walleye in Lake Sharpe, South Dakota: North American Journal of Fisheries Management, v. 44, no. 6, p. 1476-1488, https://doi.org/10.1002/nafm.11062.","productDescription":"13 p.","startPage":"1476","endPage":"1488","ipdsId":"IP-164462","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":466436,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","otherGeospatial":"Lake Sharpe","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -99.41153996325842,\n 43.9674070613043\n ],\n [\n -99.32356353814174,\n 44.129014653643964\n ],\n [\n -99.70482491930754,\n 44.269188072036656\n ],\n [\n -100.31093666510779,\n 44.38108649572871\n ],\n [\n -100.36959106966292,\n 44.31117145363751\n ],\n [\n -100.0274333861817,\n 44.16408728385727\n ],\n [\n -99.9296748431607,\n 44.06582609926022\n ],\n [\n -99.60706175871532,\n 44.044754224429255\n ],\n [\n -99.41153996325842,\n 43.9674070613043\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Sacco, Laurel H.","contributorId":348515,"corporation":false,"usgs":false,"family":"Sacco","given":"Laurel H.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":923505,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fincel, Mark J.","contributorId":348516,"corporation":false,"usgs":false,"family":"Fincel","given":"Mark J.","affiliations":[{"id":83369,"text":"South Dakota Game, Fish, and Parks","active":true,"usgs":false}],"preferred":false,"id":923506,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goble, Cameron W.","contributorId":348517,"corporation":false,"usgs":false,"family":"Goble","given":"Cameron W.","affiliations":[{"id":83369,"text":"South Dakota Game, Fish, and Parks","active":true,"usgs":false}],"preferred":false,"id":923507,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Tanner","contributorId":348518,"corporation":false,"usgs":false,"family":"Davis","given":"Tanner","affiliations":[{"id":83369,"text":"South Dakota Game, Fish, and Parks","active":true,"usgs":false}],"preferred":false,"id":923508,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923509,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70265979,"text":"70265979 - 2024 - Presence-absence surveys yield spatially imprecise information about nesting sites of an endangered, forest-nesting seabird","interactions":[],"lastModifiedDate":"2025-04-22T15:39:50.491324","indexId":"70265979","displayToPublicDate":"2024-12-12T10:33:48","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Presence-absence surveys yield spatially imprecise information about nesting sites of an endangered, forest-nesting seabird","docAbstract":"

Presence-absence surveys are frequently used to monitor populations of rare and elusive species. Such data may also be used as a proxy for breeding activity, but links between presence-absence data and higher-order processes must be validated to determine their reliability. The Marbled Murrelet (Brachyramphus marmoratus) is a threatened seabird that nests in older-aged forests along the Pacific Coast. Its nests are exceptionally difficult to find, so we tested whether presence-absence surveys can help identify nesting sites. Between 2018 and 2022 we located 17 trees containing active murrelet nests in the Oregon Coast Range (USA) and 38 trees that purportedly contained no active nests (26 in occupied murrelet stands and 12 in unoccupied stands). Observers surveyed within 200 m of focal trees using standard presence-absence surveys, and we modeled the effects of site status (active nest or control) and distance from the focal tree on probability of recording murrelets. We never detected murrelets in unoccupied control sites. We found some evidence that the probability of recording presence was higher at active nesting sites (0.81, 95% CI: 0.71, 0.88) than at occupied control sites (0.71, 95% CI: 0.64, 0.78) although a null model had similar support. The probability of recording murrelet breeding behaviors in nesting and occupied control sites was 0.20 (95% CI: 0.14, 0.27) regardless of distance to a known active nest. These results suggest that presence-absence surveys may be useful for identifying plausible murrelet nesting habitat, but they are ineffective for identifying active nesting sites. Moreover, we estimated that 20 repeated surveys at a point in space are required to reasonably conclude there are no active nesting sites within 200 m. These findings serve as an important reminder of the limitations that can come with relying on presence-absence data alone to identify breeding sites.

","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0315531","usgsCitation":"Spurgeon, J.J., Adrean, L., Nelson, S., Betts, M., Roby, D., and Rivers, J., 2024, Presence-absence surveys yield spatially imprecise information about nesting sites of an endangered, forest-nesting seabird: PLoS ONE, v. 19, no. 12, e0315531, 13 p., https://doi.org/10.1371/journal.pone.0315531.","productDescription":"e0315531, 13 p.","ipdsId":"IP-167025","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":488480,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0315531","text":"Publisher Index Page"},{"id":484839,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.5,\n 45.6\n ],\n [\n -124.1,\n 45.6\n ],\n [\n -124.1,\n 43.9\n ],\n [\n -123.5,\n 43.9\n ],\n [\n -123.5,\n 45.6\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"19","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Spurgeon, Jonathan J. 0000-0002-6888-5867","orcid":"https://orcid.org/0000-0002-6888-5867","contributorId":304259,"corporation":false,"usgs":true,"family":"Spurgeon","given":"Jonathan","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":934230,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adrean, Lindsay J.","contributorId":353648,"corporation":false,"usgs":false,"family":"Adrean","given":"Lindsay J.","affiliations":[{"id":17929,"text":"American Bird Conservancy","active":true,"usgs":false}],"preferred":false,"id":934231,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nelson, S. Kim","contributorId":353649,"corporation":false,"usgs":false,"family":"Nelson","given":"S. Kim","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":934232,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Betts, Matthew G.","contributorId":353650,"corporation":false,"usgs":false,"family":"Betts","given":"Matthew G.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":934233,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roby, Daniel D.","contributorId":353651,"corporation":false,"usgs":false,"family":"Roby","given":"Daniel D.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":934234,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rivers, James W.","contributorId":353652,"corporation":false,"usgs":false,"family":"Rivers","given":"James W.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":934235,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70262779,"text":"70262779 - 2024 - Using camera traps to estimate site occupancy of invasive Argentine Black and White Tegus (Salvator merianae) in South Florida","interactions":[],"lastModifiedDate":"2025-01-22T15:37:00.008611","indexId":"70262779","displayToPublicDate":"2024-12-10T09:33:01","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3444,"text":"Southeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Using camera traps to estimate site occupancy of invasive Argentine Black and White Tegus (Salvator merianae) in South Florida","docAbstract":"

The introduction of nonnative species is a leading cause of biodiversity loss. Many invasive species are cryptic or elusive in nature and therefore often evade detection, complicating their management. Occupancy modeling can reveal the presence and spread of invasive species over time and therefore has important management implications. Camera traps can be used to estimate occupancy, or the proportion of sites that are occupied by a target species. During a 4-year study (2016–2020), we used camera traps both with and without lures to detect the presence of invasive Salvator merianae (Argentine Black and White Tegu) at sites in Miami-Dade County, FL. Our results from a multi-season occupancy model revealed that a quadratic effect of ordinal day was the best predictor of detection, with a peak in June, while occupancy was correlated with distance to landscape features that may facilitate tegu movement. We did not detect any large-scale changes in occupancy over the course of our study. We also discovered that the use of lures with camera traps did not impact detection, indicating fewer resources would be required from invasive species managers for effective monitoring. Understanding the factors that impact occupancy and detection probabilities can inform surveillance and removal efforts, leading to more efficient management strategies.

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Samantha N.","contributorId":349763,"corporation":false,"usgs":false,"family":"Smith","given":"Samantha N.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":924745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Melissa A.","contributorId":57701,"corporation":false,"usgs":false,"family":"Miller","given":"Melissa","email":"","middleInitial":"A.","affiliations":[{"id":39007,"text":"CA Dept of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":924746,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waddle, Hardin 0000-0003-1940-2133","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":201976,"corporation":false,"usgs":true,"family":"Waddle","given":"Hardin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":924747,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cooke, Sarah","contributorId":349766,"corporation":false,"usgs":false,"family":"Cooke","given":"Sarah","affiliations":[{"id":83510,"text":"Environmental Resources Management","active":true,"usgs":false}],"preferred":false,"id":924748,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":924749,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Currylow, Andrea 0000-0003-1631-8964","orcid":"https://orcid.org/0000-0003-1631-8964","contributorId":212747,"corporation":false,"usgs":true,"family":"Currylow","given":"Andrea","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":924750,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Donmoyer, Kevin","contributorId":316354,"corporation":false,"usgs":false,"family":"Donmoyer","given":"Kevin","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":924751,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mazzotti, Frank J.","contributorId":12358,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank J.","affiliations":[{"id":12604,"text":"Department of Wildlife Ecology and Conservation, Fort Lauderdale Research and Education Center, 3205 College Avenue, University of Florida, Davie, FL 33314, USA","active":true,"usgs":false}],"preferred":false,"id":924752,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70261973,"text":"70261973 - 2024 - Using life history traits to assess climate change vulnerability in understudied species","interactions":[],"lastModifiedDate":"2025-01-07T15:35:26.120248","indexId":"70261973","displayToPublicDate":"2024-12-10T09:22:39","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":19878,"text":"Integrative Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Using life history traits to assess climate change vulnerability in understudied species","docAbstract":"

Climate change is a primary threat to biodiversity, but for many species, we still lack information required to assess their relative vulnerability to changes. Climate change vulnerability assessment (CCVA) is a widely used technique to rank relative vulnerability to climate change based on species characteristics, such as their distributions, habitat associations, environmental tolerances, and life-history traits. However, for species that we expect are vulnerable to climate change yet are understudied, like many amphibians, we often lack information required to construct CCVAs using existing methods. We used the CCVA framework to construct trait-based models based on life history theory, using empirical evidence of traits and distributions that reflected sensitivity of amphibians to environmental perturbation. We performed CCVAs for amphibians in 7 states in the north-central USA, focusing on 31 aquatic-breeding species listed as species of greatest conservation need by at least 1 state. Because detailed information on habitat requirements is unavailable for most amphibian species, we used species distributions and information on traits expected to influence vulnerability to a drying climate (e.g., clutch size and habitat breadth). We scored species vulnerability based on changes projected for mid-century (2040−2069) from 2 climate models representing “least-dry” and “most-dry” scenarios for the region. Species characteristics useful for discriminating vulnerability in our models included small range size, small clutch size, inflexible diel activity patterns, and smaller habitat breadth. When projected climate scenarios included a mix of drier and wetter conditions in the future, the exposure of a species to drying conditions was most important to relative rankings. When the scenario was universally drier, species characteristics were more important to relative rankings. Using information typically available even for understudied species and a range of climate projections, our results highlight the potential of using life history traits as indicators of relative climate vulnerability. The commonalities we identified provide a framework that can be used to assess other understudied species threatened by climate change.

","language":"English","publisher":"Wiley","doi":"10.1002/inc3.77","usgsCitation":"Hinderer, R., Hossack, B., and Eby, L., 2024, Using life history traits to assess climate change vulnerability in understudied species: Integrative Conservation, v. 3, no. 4, p. 368-381, https://doi.org/10.1002/inc3.77.","productDescription":"14 p.","startPage":"368","endPage":"381","ipdsId":"IP-157243","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":466720,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/inc3.77","text":"Publisher Index Page"},{"id":465753,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Kansas, Montana, Nebraska, North Dakota, South Dakota, 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\"}}]}","volume":"3","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-12-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Hinderer, Ross K","contributorId":347816,"corporation":false,"usgs":false,"family":"Hinderer","given":"Ross K","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":922504,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hossack, Blake R. 0000-0001-7456-9564","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":229347,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":922505,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eby, Lisa A","contributorId":251751,"corporation":false,"usgs":false,"family":"Eby","given":"Lisa A","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":922506,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70274652,"text":"70274652 - 2024 - New York State climate impacts assessment chapter 05: Ecosystems","interactions":[],"lastModifiedDate":"2026-04-02T15:19:38.585958","indexId":"70274652","displayToPublicDate":"2024-12-09T09:57:57","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":801,"text":"Annals of the New York Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"New York State climate impacts assessment chapter 05: Ecosystems","docAbstract":"

The people of New York have long benefited from the state's diversity of ecosystems, which range from coastal shorelines and wetlands to extensive forests and mountaintop alpine habitat, and from lakes and rivers to greenspaces in heavily populated urban areas. These ecosystems provide key services such as food, water, forest products, flood prevention, carbon storage, climate moderation, recreational opportunities, and other cultural services. This chapter examines how changes in climatic conditions across the state are affecting different types of ecosystems and the services they provide, and considers likely future impacts of projected climate change. The chapter emphasizes how climate change is increasing the vulnerability of ecosystems to existing stressors, such as habitat fragmentation and invasive species, and highlights opportunities for New Yorkers to adapt and build resilience.

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York\",\"nation\":\"USA \"}}]}","volume":"1542","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Hess, Sheila","contributorId":369172,"corporation":false,"usgs":false,"family":"Hess","given":"Sheila","affiliations":[{"id":87729,"text":"CC Environment and Planning","active":true,"usgs":false}],"preferred":false,"id":958568,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":958569,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boudinot, Garrett","contributorId":369177,"corporation":false,"usgs":false,"family":"Boudinot","given":"Garrett","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":958570,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown-Lima, Carrie","contributorId":236893,"corporation":false,"usgs":false,"family":"Brown-Lima","given":"Carrie","email":"","affiliations":[],"preferred":false,"id":958571,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Corwin, Jason","contributorId":369181,"corporation":false,"usgs":false,"family":"Corwin","given":"Jason","affiliations":[{"id":37334,"text":"University at Buffalo","active":true,"usgs":false}],"preferred":false,"id":958572,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Foppert, John","contributorId":369182,"corporation":false,"usgs":false,"family":"Foppert","given":"John","affiliations":[{"id":39895,"text":"Paul Smith's College","active":true,"usgs":false}],"preferred":false,"id":958573,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Robinson, George","contributorId":140346,"corporation":false,"usgs":false,"family":"Robinson","given":"George","email":"","affiliations":[{"id":13465,"text":"Assoc. Professor, State University of New York at Albany","active":true,"usgs":false}],"preferred":false,"id":958574,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rose, Kevin C.","contributorId":174809,"corporation":false,"usgs":false,"family":"Rose","given":"Kevin","email":"","middleInitial":"C.","affiliations":[{"id":12656,"text":"Rensselaer Polytechnic Institute","active":true,"usgs":false}],"preferred":false,"id":958575,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schlesinger, Matthew D.","contributorId":342842,"corporation":false,"usgs":false,"family":"Schlesinger","given":"Matthew D.","affiliations":[{"id":61506,"text":"New York Natural Heritage Program","active":true,"usgs":false}],"preferred":false,"id":958576,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Shuford, Rebecca","contributorId":369187,"corporation":false,"usgs":false,"family":"Shuford","given":"Rebecca","affiliations":[{"id":56145,"text":"New York Sea Grant","active":true,"usgs":false}],"preferred":false,"id":958577,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Stevens, Amanda","contributorId":369214,"corporation":false,"usgs":false,"family":"Stevens","given":"Amanda","affiliations":[],"preferred":false,"id":958608,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70266447,"text":"70266447 - 2024 - Retention of T‐bar anchor tags by adult steelhead during their upstream migration","interactions":[],"lastModifiedDate":"2025-05-07T15:42:02.23731","indexId":"70266447","displayToPublicDate":"2024-12-08T08:35:07","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Retention of T‐bar anchor tags by adult steelhead during their upstream migration","docAbstract":"

Objective:

T-bar anchor tags can be used to obtain recapture data from anglers, directly estimate exploitation, and evaluate population dynamics. Unfortunately, their use by biologists to study anadromous salmonid fisheries is limited. Two hurdles to adoption include the functional difficulty of tagging large anadromous salmonids using conventional tagging equipment and a lack of information on tag loss by large anadromous salmonids and how it changes over time. As such, our objectives were to (1) describe a T-bar anchor tagging system modified to study adult steelhead Oncorhynchus mykiss (i.e., anadromous Rainbow Trout) and (2) present an instantaneous tag loss model for steelhead that allows estimation of tag loss over time.

Methods: First, we developed a modified tagging system by tagging hatchery-obtained steelhead carcasses and live, resident Rainbow Trout >500 mm using a variety of hardware and tag dimensions. Next, we double-tagged adult steelhead captured at the Lower Granite Dam adult fish trap, Washington, USA. We then used data from 182 recaptured steelhead to fit an instantaneous tag loss model. Last, we investigated whether steelhead tag loss was related to body length.

Result: Tag loss was generally low within the time period under study (i.e., up to 221 days between release and recapture). The estimated probability of tag loss was 0.034 at release, 0.044 at one month, and 0.113 at eight months. We failed to detect significant differences in tag loss parameters between two subsets of small (<720 mm) and large (≥720 mm) steelhead.

Conclusion: T-bar anchor tags are useful external tags for studying adult steelhead during their upstream migration. Because anglers can be used to provide recapture data, T-bar anchor tags may be particularly useful where angler effort is high or direct estimation of fishery exploitation is desired.

","language":"English","publisher":"Oxford Academic","doi":"10.1002/nafm.11055","usgsCitation":"Voss, N.S., McCormick, J., Lubenau, W., Bowersox, B.J., Copeland, T., and Quist, M.C., 2024, Retention of T‐bar anchor tags by adult steelhead during their upstream migration: North American Journal of Fisheries Management, v. 44, no. 6, p. 1385-1391, https://doi.org/10.1002/nafm.11055.","productDescription":"7 p.","startPage":"1385","endPage":"1391","ipdsId":"IP-162952","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":485509,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Lower Granite Dam, Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.7515022516423,\n 47.195723484659\n ],\n [\n -119.7515022516423,\n 46.04149363558699\n ],\n [\n -117.09892399655794,\n 46.04149363558699\n ],\n [\n -117.09892399655794,\n 47.195723484659\n ],\n [\n -119.7515022516423,\n 47.195723484659\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Voss, Nicholas S.","contributorId":300117,"corporation":false,"usgs":false,"family":"Voss","given":"Nicholas","email":"","middleInitial":"S.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":935996,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCormick, Joshua L.","contributorId":354615,"corporation":false,"usgs":false,"family":"McCormick","given":"Joshua L.","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":935997,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lubenau, William J.","contributorId":354616,"corporation":false,"usgs":false,"family":"Lubenau","given":"William J.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":935998,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bowersox, Brett J.","contributorId":265299,"corporation":false,"usgs":false,"family":"Bowersox","given":"Brett","email":"","middleInitial":"J.","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":935999,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Copeland, Timothy","contributorId":265301,"corporation":false,"usgs":false,"family":"Copeland","given":"Timothy","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":936000,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":936001,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70262028,"text":"70262028 - 2024 - Using remote sensing to identify habitat for wintering Henslow's Sparrows (Centronyx henslowii)","interactions":[],"lastModifiedDate":"2025-01-10T16:25:20.923883","indexId":"70262028","displayToPublicDate":"2024-12-06T10:17:51","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7509,"text":"The Wilson Journal of Ornithology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Using remote sensing to identify habitat for wintering Henslow's Sparrows (Centronyx henslowii)","title":"Using remote sensing to identify habitat for wintering Henslow's Sparrows (Centronyx henslowii)","docAbstract":"

The Henslow's Sparrow (Centronyx henslowii) is a grassland bird species that overwinters in the southeastern United States and is a species of conservation concern due to population declines primarily caused by habitat loss. Henslow's Sparrows often overwinter in marginal habitats, such as powerline rights-of-way (ROWs), clear cuts, and field edges that provide some of their desired habitat characteristics, such as low-to-no tree cover and a diverse herbaceous understory. Using remote sensing methods, we evaluated the habitat characteristics of Henslow's Sparrow–occupied ROWs in southeastern Georgia. We calculated 22 satellite imagery metrics from Sentinel 2-L2 10 m resolution imagery, including single-pixel variables (e.g., Enhanced Vegetation Index, EVI) as well as “image texture” metrics that represent spatial heterogeneity. Using Random Forest models, we evaluated whether satellite imagery metrics could be used to discriminate between Henslow's Sparrow used areas (delineated from telemetry data) and surrounding available areas. Satellite imagery metrics were successful in predicting habitat characteristics in the ROWs (as evaluated by out-of-bag error and 3 goodness-of-fit tests), with image texture metrics performing better than single-pixel metrics. Image texture metrics were 9 of the top 10 most important predictors of habitat use in the best performing model that had a 500 m available buffer around use areas (out-of-bag error rate 21.21%). The most important image texture metric, cluster shade, was positively correlated with tree cover; Henslow's Sparrows were more likely to use areas with intermediate levels of cluster shade. From our results, we concluded that image texture metrics derived from 10 m satellite imagery could be used to predict sites that have suitable overwintering habitat for Henslow's Sparrows, but only at coarse resolutions and broader extents (hundreds of meters to kilometers). Therefore, this tool could be used to identify other ROWs (and possibly non-ROWs) with habitat that may support this and other declining grassland species.

","language":"English","publisher":"Wilson Ornithological Society","doi":"10.1676/23-00049","usgsCitation":"Moore, S., Dwire, A., Prebyl, T., Schneider, T., and Hunter, E.A., 2024, Using remote sensing to identify habitat for wintering Henslow's Sparrows (Centronyx henslowii): The Wilson Journal of Ornithology, v. 136, no. 4, p. 436-447, https://doi.org/10.1676/23-00049.","productDescription":"12 p.","startPage":"436","endPage":"447","ipdsId":"IP-154594","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":465994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Moody Forest Wildlife Management Area, Townsend Wildlife Management Area, Paulks Pasture Wildlife Management Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.57525588321172,\n 32.48251517887438\n ],\n [\n -82.66578654540206,\n 31.015534685580576\n ],\n [\n -81.36949067181612,\n 30.978771137717928\n ],\n [\n -80.93094224410345,\n 32.04324987692853\n ],\n [\n -82.57525588321172,\n 32.48251517887438\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"136","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, Sierra A.","contributorId":347927,"corporation":false,"usgs":false,"family":"Moore","given":"Sierra A.","affiliations":[{"id":81880,"text":"Department of Fish and Wildlife Conservation","active":true,"usgs":false}],"preferred":false,"id":922751,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dwire, Abigail W.","contributorId":347929,"corporation":false,"usgs":false,"family":"Dwire","given":"Abigail W.","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":922752,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prebyl, Thomas J.","contributorId":347930,"corporation":false,"usgs":false,"family":"Prebyl","given":"Thomas J.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":922753,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schneider, Todd M.","contributorId":347932,"corporation":false,"usgs":false,"family":"Schneider","given":"Todd M.","affiliations":[{"id":36378,"text":"Georgia Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":922754,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hunter, Elizabeth Ann 0000-0003-4710-167X","orcid":"https://orcid.org/0000-0003-4710-167X","contributorId":288535,"corporation":false,"usgs":true,"family":"Hunter","given":"Elizabeth","email":"","middleInitial":"Ann","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":922755,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70264044,"text":"70264044 - 2024 - Structured decision-making workshop: Chronic wasting disease management in free-ranging cervids in Massachusetts","interactions":[],"lastModifiedDate":"2025-03-05T16:27:26.437342","indexId":"70264044","displayToPublicDate":"2024-12-06T10:17:30","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"FWS/CSS-161-2024","title":"Structured decision-making workshop: Chronic wasting disease management in free-ranging cervids in Massachusetts","docAbstract":"

This document describes the results of a 2.5-day rapid decision prototype workshop that evaluated management activities for chronic wasting disease (CWD) in Massachusetts (MA) that were either proactive (i.e., actions taken prior to CWD arrival/detection) or reactive (i.e., actions taken after CWD arrival/detection). The workshop was led by members of the Wildlife Section of the MA Division of Fisheries and Wildlife (hereafter referred to as MassWildlife) and included a group of agency communications specialists and district managers. U. S. Geological Survey staff and a volunteer acted as decision facilitators and led the analysis of the decision.

Chronic wasting disease is an always fatal neurological disease that has spread across much of North America and threatens the health of deer populations in locations where it occurs (reviewed by Escobar et al. 2020). CWD can spread into new areas via two general mechanisms: (1) natural spread (e.g., dispersal of CWD-infected male white-tailed deer [Odocoileus virginianus]), and (2) anthropogenic spread (e.g., CWD spread facilitated by human intervention; Leiss et al. 2017, Escobar et al. 2020). Once CWD arrives in a state, natural resources agencies spend eight times more on CWD than agencies with no known cases; to cover these new CWD-related management activities, the natural resources agencies are typically forced to reallocate money from existing conservation priorities (Chiavacci, 2022). As of May 2024, there were 34 U.S. states and five Canadian provinces that had detected CWD positive free-ranging and/or captive animals in the family Cervidae (collectively referred to as ‘cervid’ hereafter), and the number of new states/provinces that are detecting CWD for the first time continues to grow (U. S. Geological Survey, May 2024). As of February 2024, the closest CWD positive state to MA with CWD detected in free-ranging white-tailed deer is Pennsylvania. To date, there have been no detections of CWD in MA, but testing has been limited in MA since 2012. The growing number of CWD positive states suggests that there may be increasing risk of CWD entering and establishing in MA as the number of CWD cases increases across North America.

According to a 2023 survey of hunters in MA conducted by MassWildlife, 68% of hunters were concerned about CWD entering MA, and 88% of respondents said that it was at least moderately important to keep CWD out of MA; these survey results indicate that most hunters may support CWD risk reduction actions (Martin Feehan, Massachusetts Division of Fisheries and Wildlife, oral communication, 12 Feb 2024). In addition, 23.1% of responding deer hunters in MA have hunted for cervids in CWD-positive states/provinces in the last five years (not including states/provinces that have been able to successfully eradicate CWD following a positive detection). Participants of the survey were also asked, “how many deer have you harvested that tested positive for CWD?”. A total of three respondents said that they had one deer test positive for CWD, which, when extended to the whole population of MA deer hunters, results in an estimated 32 CWD positive deer harvested in CWD-positive states and imported into MA in the last five years. When asked about how they transport harvested deer from out of state into MA, the three participants indicated either “already processed & packaged” or “not applicable.” Note, that in MA, it is a violation of regulation to import whole carcasses or high-risk parts (e.g., head, brain, spinal tissues, bones) of any member of the Cervidae family (wild or captive) from a state/province that has detected CWD; it is legal to bring in deboned meat, cleaned skull caps, hides without the head, or a fixed taxidermy mount (Massachusetts Division of Fisheries and Wildlife, 2024a).

To date, testing for CWD has been limited in MA since 2012. However, the data collected from the 2023 MA hunter survey suggests that there is a real risk of CWD being imported by a MA resident who has hunted in a CWD positive state. Therefore, given the higher costs of CWD management post arrival, the potential natural spread of CWD from nearby states, and the risk of CWD introduction via humanmediated cervid movement, MassWildlife is motivated to take actions that minimize the risk of CWD introduction and spread in MA with the ultimate goal of managing thriving wildlife populations and maximizing hunter and general public satisfaction, which are both parts of the MassWildlife mission.

A 2.5-day rapid prototyping structured decision making workshop was held with MassWildlife staff to develop a decision framework for CWD management in MA. During the workshop, we defined the context and extent of CWD management activities in MA. Next, we identified four fundamental objectives that help achieve the mission of MassWildlife and that address stakeholder concerns. The fundamental objectives included: (1) maximizing hunter satisfaction and participation, (2) maximizing public satisfaction (non-consumptive), (3) maximizing health and sustainability of cervids, and (4) maximizing the efficiency of CWD management. Then, we generated a list of five alternatives (i.e., strategies) that varied the intensity of proactive and reactive actions. The five strategies were: (1) minimal proactive and minimal reactive actions, (2) intermediate proactive and intermediate reactive actions, (3) intensive proactive and intermediate reactive actions, (4) minimal proactive and intensive reactive actions, and (5) intensive proactive and intensive reactive actions. Lastly, we estimated the performance of each strategy on the fundamental objectives and assessed the overall performance of strategies relative to one another. We did so by first estimating the consequences of each alternative strategy on fundamental objectives using expert elicitation, and then, we elicited objective weights from MassWildlife staff to incorporate the relative importance of different fundamental objectives.

Given that it is unknown when CWD will arrive in MA, we evaluated the performance of alternative strategies against fundamental objectives given three distinct scenarios for time to arrival of CWD: introduction in 2.5, 7.5, or 10+ years. The preliminary results of the rapid prototype indicate that the performance of the CWD management strategies that we evaluated depends on when CWD first arrives in MA. If CWD were to arrive in 2.5 or 7.5 years from now (February, 2024), then the ‘minimal proactive and minimal reactive’ strategy performs the best on both the deer population and cost fundamental objectives (fundamental objectives 3 & 4), but the ‘intensive proactive and intensive reactive’ strategy performs best on both of the human dimensions fundamental objectives (fundamental objectives 1 & 2) as well as the minimize CWD prevalence objective (also related to fundamental objective 3). We also found that public trust is likely to remain high across all five alternative strategies if CWD arrives after year 10, but public trust decreases if CWD arrives in year 2.5 or 7.5. After incorporating objective weights, we found that in scenarios where CWD arrives in the near-term (in years 2.5 or 7.5), an intermediate strategy (e.g., ‘intermediate proactive and intermediate reactive’ or ‘intensive proactive and intermediate reactive’) performed best, and the ‘minimal proactive and intensive reactive’ strategy performed worst. Conversely, if CWD were to arrive after 10 years, then the ‘minimal proactive and minimal reactive’ and ‘minimal proactive and intensive reactive’ strategies performed best. Collectively, these results suggest that the decision on which alternative strategy to employ is sensitive to when CWD arrives in MA. Following the discussion of the preliminary results, we identified the following four next steps. First, we discussed how a more detailed communications plan is needed and would likely alter the performance estimates of the alternative strategies on fundamental objectives 1 & 2, which were hunter and public satisfaction, respectively. The development of the communication plan would likely be easier once the alternative actions have been identified along with the audience and message. Second, a surveillance plan could be a useful tool to inform CWD management. Surveillance for CWD was performed in MA annually from 2002 to 2012 (n = 4,356 wild white-tailed deer and moose [Alces alces] samples). Limited surveillance was conducted from 2013 to 2022; and in 2023, 242 wild samples were collected. It is not clear whether MA needs a robust or minimal surveillance plan (e.g., is a minimal surveillance plan enough to detect the pathogen at the threshold that would trigger action?), or what type of invasion event the surveillance plan should target (e.g., natural vs anthropogenic spread events). The use of decision trees and a formal risk assessment may help answer these questions. Third, some of the elicited estimates from experts during this rapid prototype could be replaced with empirical data. Lastly, given that the decision was sensitive to when CWD arrived in MA and a surveillance plan would rely on the mode of introduction, forecasting and predicting the CWD invasion front and/or the likelihood of different incursion events across MA would provide valuable insights. 

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Different theoretical frameworks have been invoked to guide the study of virus evolution. Three of the more prominent ones are (i) the evolution of virulence, (ii) life history theory, and (iii) the generalism–specialism dichotomy. All involve purported tradeoffs between traits that define the evolvability and constraint of virus-associated phenotypes. However, as popular as these frameworks are, there is a surprising paucity of direct laboratory tests of the frameworks that support their utility as broadly applicable theoretical pillars that can guide our understanding of disease evolution. In this study, we conduct a meta-analysis of direct experimental evidence for these three frameworks across several widely studied virus–host systems: plant viruses, fungal viruses, animal viruses, and bacteriophages. We extracted 60 datasets from 28 studies and found a range of relationships between traits in different analysis categories (e.g., frameworks, virus–host systems). Our work demonstrates that direct evidence for relationships between traits is highly idiosyncratic and specific to the host–virus system and theoretical framework. Consequently, scientists researching viral pathogens from different taxonomic groups might reconsider their allegiance to these canons as the basis for expectation, explanation, or prediction. Future efforts could benefit from consistent definitions, and from developing frameworks that are compatible with the evidence and apply to particular biological and ecological contexts.

","language":"English","publisher":"Oxford Academic","doi":"10.1093/ve/veae105","usgsCitation":"Kabengele, K., Turner, W.C., Turner, P., and Ogbunugafor, C., 2024, A meta-analysis highlights the idiosyncratic nature of tradeoffs in laboratory models of virus evolution: Virus Evolution, v. 10, no. 1, veae105, 13 p., https://doi.org/10.1093/ve/veae105.","productDescription":"veae105, 13 p.","ipdsId":"IP-158849","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":466723,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ve/veae105","text":"Publisher Index Page"},{"id":465990,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-12-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Kabengele, Ketty","contributorId":347923,"corporation":false,"usgs":false,"family":"Kabengele","given":"Ketty","affiliations":[{"id":37550,"text":"Yale University","active":true,"usgs":false}],"preferred":false,"id":922747,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Turner, Wendy Christine 0000-0002-0302-1646","orcid":"https://orcid.org/0000-0002-0302-1646","contributorId":287053,"corporation":false,"usgs":true,"family":"Turner","given":"Wendy","email":"","middleInitial":"Christine","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":922749,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Turner, Paul E.","contributorId":348136,"corporation":false,"usgs":false,"family":"Turner","given":"Paul E.","affiliations":[],"preferred":false,"id":922748,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ogbunugafor, C. Brandon","contributorId":347925,"corporation":false,"usgs":false,"family":"Ogbunugafor","given":"C. Brandon","affiliations":[{"id":37550,"text":"Yale University","active":true,"usgs":false}],"preferred":false,"id":922750,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70262778,"text":"70262778 - 2024 - Rock sample photogrammetry","interactions":[],"lastModifiedDate":"2026-03-02T15:54:48.581032","indexId":"70262778","displayToPublicDate":"2024-12-05T09:26:13","publicationYear":"2024","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19901,"text":"Protocols.io","active":true,"publicationSubtype":{"id":32}},"title":"Rock sample photogrammetry","docAbstract":"

This step-by-step protocol describes the photogrammetry process used by the U.S. Geological Survey Spokane Imaging Lab (SPIMG) lab to create 3D models of geologic samples. Steps related to photographing small objects are applicable to photogrammetry in general, however, SPIMG-specific steps involving lab hardware and software may not be.

","language":"English","publisher":"Protocols.io","doi":"10.17504/protocols.io.kqdg3xy67g25/v1","usgsCitation":"Evart, L., 2024, Rock sample photogrammetry: Protocols.io, https://doi.org/10.17504/protocols.io.kqdg3xy67g25/v1.","productDescription":"HTML Document","ipdsId":"IP-171668","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":480921,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":489122,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.17504/protocols.io.kqdg3xy67g25/v1","text":"Publisher Index Page"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Evart, Lucas Leonidus 0000-0002-3442-0922","orcid":"https://orcid.org/0000-0002-3442-0922","contributorId":302525,"corporation":false,"usgs":true,"family":"Evart","given":"Lucas Leonidus","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":924744,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70262438,"text":"70262438 - 2024 - Abundance-mediated species interactions","interactions":[],"lastModifiedDate":"2025-01-22T15:12:17.729427","indexId":"70262438","displayToPublicDate":"2024-12-05T08:07:25","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Abundance-mediated species interactions","docAbstract":"

Species interactions shape biodiversity patterns, community assemblage, and the dynamics of wildlife populations. Ecological theory posits that the strength of interspecific interactions is fundamentally underpinned by the population sizes of the involved species. Nonetheless, prevalent approaches for modeling species interactions predominantly center around occupancy states. Here, we use simulations to illuminate the inadequacies of modeling species interactions solely as a function of occupancy, as is common practice in ecology. We demonstrate erroneous inference into species interactions due to error in parameter estimates when considering species occupancy alone. To address this critical issue, we propose, develop, and demonstrate an abundance-mediated interaction framework designed explicitly for modeling species interactions involving two or more species from detection/non-detection data. We present Markov chain Monte Carlo (MCMC) samplers tailored for diverse ecological scenarios, including intraguild predation, disease- or predator-mediated competition, and trophic cascades. Illustrating the practical implications of our approach, we compare inference from modeling the interactions in a three-species network involving coyotes (Canis latrans), fishers (Pekania pennanti), and American marten (Martes americana) in North America as a function of occupancy states and as a function of abundance. When modeling interactions as a function of abundance rather than occupancy, we uncover previously unidentified interactions. Our study emphasizes that accounting for abundance-mediated interactions rather than simple co-occurrence patterns can fundamentally alter our comprehension of system dynamics. Through an empirical case study and comprehensive simulations, we demonstrate the importance of accounting for abundance when modeling species interactions, and we present a statistical framework equipped with MCMC samplers to achieve this paradigm shift in ecological research.

","language":"English","publisher":"Wiley","doi":"10.1002/ecy.4468","usgsCitation":"Twining, J., Augustine, B., Royle, A., and Fuller, A.K., 2024, Abundance-mediated species interactions: Ecology, v. 106, no. 1, e4468, 20 p., https://doi.org/10.1002/ecy.4468.","productDescription":"e4468, 20 p.","ipdsId":"IP-161645","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481047,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.4468","text":"Publisher Index Page"},{"id":480918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"106","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-12-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Twining, Joshua P.","contributorId":349314,"corporation":false,"usgs":false,"family":"Twining","given":"Joshua P.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":924215,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Augustine, Ben 0000-0001-6935-6361","orcid":"https://orcid.org/0000-0001-6935-6361","contributorId":245736,"corporation":false,"usgs":true,"family":"Augustine","given":"Ben","email":"","affiliations":[{"id":49304,"text":"Department of Natural Resources, Cornell University","active":true,"usgs":false}],"preferred":false,"id":924216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":924217,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":924218,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70276497,"text":"70276497 - 2024 - Real-time lava flow forecasting during the 2022 Mauna Loa eruption response","interactions":[],"lastModifiedDate":"2026-06-08T14:54:09.718676","indexId":"70276497","displayToPublicDate":"2024-12-05T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Real-time lava flow forecasting during the 2022 Mauna Loa eruption response","docAbstract":"

On November 27, 2022, Mauna Loa (Hawai‘i) erupted for the first time in 38 years, initially producing lava flows that covered the floor of its summit caldera, Moku‘āweoweo. Over the first 12 h following the summit eruption, four main fissures opened on Mauna Loa’s Northeast Rift Zone, with “fissure 3” quickly becoming the dominant source of lava flows. For the next 12 days, fissure 3 produced a 19-km-long lava flow to the north, crossing the Mauna Loa Weather Observatory access road and coming within 2.8 km of inundating the Daniel K. Inouye Highway (Saddle Road). Within 40 min of fissure 3 opening, inundation modeling efforts had begun. For the duration of the eruption, the computational fluid dynamics model Lava2d was run in real time, using flow front locations and other field observations to make sequential forecast improvements, eventually producing a set of models which accurately predicted the routing and arrival times of lava from fissure 3. These models were used to inform timing estimates of possible future inundation of the Saddle Road. As the eruption progressed, almost 4000 Lava2d models were made using high-performance computing resources, providing critical information on uncertainty in multi-week forecasts. To our knowledge, this was the first ever real-time physics-based ensemble lava flow modeling and forecasting effort. Here, we present a chronology of these real-time efforts, focusing on the successes and limitations of this approach.

","language":"English","publisher":"Springer Nature","doi":"10.1007/s00445-024-01783-z","usgsCitation":"Hyman, D., Dietterich, H., Gallant, E., Lynn, K.J., Zoeller, M.H., Patrick, M.R., Kauahikaua, J., Trusdell, F., Hon, K., Denlinger, R.P., Foks, N., Lee, R.L., Falgout, J.T., and Gordon, J.M., 2024, Real-time lava flow forecasting during the 2022 Mauna Loa eruption response: Bulletin of Volcanology, v. 87, 3, 18 p., https://doi.org/10.1007/s00445-024-01783-z.","productDescription":"3, 18 p.","ipdsId":"IP-168086","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":505468,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-024-01783-z","text":"Publisher Index Page"},{"id":505153,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mauna Loa","geographicExtents":"{\n 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0000-0002-9607-7584","orcid":"https://orcid.org/0000-0002-9607-7584","contributorId":351609,"corporation":false,"usgs":true,"family":"Hyman","given":"David Matthew","affiliations":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":962510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dietterich, Hannah R. 0000-0001-7898-4343","orcid":"https://orcid.org/0000-0001-7898-4343","contributorId":212771,"corporation":false,"usgs":true,"family":"Dietterich","given":"Hannah R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":962511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gallant, Elisabeth 0000-0001-6841-3694","orcid":"https://orcid.org/0000-0001-6841-3694","contributorId":339872,"corporation":false,"usgs":false,"family":"Gallant","given":"Elisabeth","affiliations":[{"id":81292,"text":"University of Hawaiʻi at 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Leon 0000-0002-4907-3679","orcid":"https://orcid.org/0000-0002-4907-3679","contributorId":239959,"corporation":false,"usgs":false,"family":"Foks","given":"N. Leon","affiliations":[{"id":48073,"text":"Apogee Engineering, LLC; Contracted to USGS","active":true,"usgs":false}],"preferred":false,"id":962520,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lee, R. 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The Europa Imaging System (EIS) consists of a Narrow-Angle Camera (NAC) and a Wide-Angle Camera (WAC) that are designed to work together to address high-priority science objectives regarding Europa’s geology, composition, and the nature of its ice shell. EIS accommodates variable geometry and illumination during rapid, low-altitude flybys with both framing and pushbroom imaging capability using rapid-readout, 8-megapixel (4k × 2k) detectors. Color observations are acquired using pushbroom imaging with up to six broadband filters. The data processing units (DPUs) perform digital time delay integration (TDI) to enhance signal-to-noise ratios and use readout strategies to measure and correct spacecraft jitter. The NAC has a 2.3° × 1.2° field of view (FOV) with a 10-μrad instantaneous FOV (IFOV), thus achieving 0.5-m pixel scale over a swath that is 2 km wide and several km long from a range of 50 km. The NAC is mounted on a 2-axis gimbal, ±30° cross- and along-track, that enables independent targeting and near-global (≥90%) mapping of Europa at ≤100-m pixel scale (to date, only ∼15% of Europa has been imaged at ≤900 m/pixel), as well as stereo imaging from as close as 50-km altitude to generate digital terrain models (DTMs) with ≤4-m ground sample distance (GSD) and ≤0.5-m vertical precision. The NAC will also perform observations at long range to search for potential erupting plumes, achieving 10-km pixel scale at a distance of one million kilometers. The WAC has a 48° × 24° FOV with a 218-μrad IFOV, achieving 11-m pixel scale at the center of a 44-km-wide swath from a range of 50 km, and generating DTMs with 32-m GSD and ≤4-m vertical precision. The WAC is designed to acquire three-line pushbroom stereo and color swaths along flyby ground-tracks.

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,{"id":70261537,"text":"70261537 - 2024 - Salt marsh habitats and diamondback terrapins in a rapidly changing climate: A review","interactions":[],"lastModifiedDate":"2024-12-13T15:25:17.597572","indexId":"70261537","displayToPublicDate":"2024-12-04T08:14:02","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Salt marsh habitats and diamondback terrapins in a rapidly changing climate: A review","docAbstract":"

The impacts associated with global climate change (e.g., sea-level rise, tropical storms, and warming temperatures) are expected to alter predator–prey interactions, foundation species, and plant community structure in coastal ecosystems. While the complex dynamics of these habitats have been examined under future climate predictions, few ecosystem models incorporate influences from fauna, such as the diamondback terrapin, the only estuarine turtle native to North America. This review examines the impacts of climate change on diamondback terrapins (Malaclemys terrapin) and the role that terrapins play as higher trophic level predators and keystone species in driving the dynamics of these ecosystems. We also review the potential implications of changes to terrapin populations on coastal ecosystems as a conservation challenge and suggest solutions to advance our understanding of those complex systems. Because of their role as a keystone and area-sensitive species that helps maintain healthy coastal habitats by foraging on herbivorous periwinkle snails, alterations to terrapin life history from climate change are expected, which could have significant impacts to the conservation of coastal habitats. Life history alterations could occur due to individual stressors, such as warming temperatures altering terrapin sex ratios. However, because of the complexity of these coastal systems, these stressors could also act additively or synergistically. Inclusion of faunal taxa such as the diamondback terrapin in modeling efforts examining climate change impacts to coastal ecosystems would better represent the complexity of these habitats thereby providing a more comprehensive evaluation of the entire ecosystem, resulting in more effective conservation strategies.

","language":"English","publisher":"Springer Nature","doi":"10.1007/s12237-024-01466-0","usgsCitation":"Lamont, M.M., Osland, M.J., and Baustian, M., 2024, Salt marsh habitats and diamondback terrapins in a rapidly changing climate: A review: Estuaries and Coasts, v. 48, no. 1, 33, 14 p., https://doi.org/10.1007/s12237-024-01466-0.","productDescription":"33, 14 p.","ipdsId":"IP-167295","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":466727,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-024-01466-0","text":"Publisher Index Page"},{"id":465112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.99312483251897,\n 43.35029876340829\n ],\n [\n -103.6065024224903,\n 43.35029876340829\n ],\n [\n -103.6065024224903,\n 25.935704461203755\n ],\n [\n -73.99312483251897,\n 25.935704461203755\n ],\n [\n -73.99312483251897,\n 43.35029876340829\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"48","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-12-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Lamont, Margaret M. 0000-0001-7520-6669 mlamont@usgs.gov","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":4525,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","email":"mlamont@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":920918,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Osland, Michael J. 0000-0001-9902-8692 mosland@usgs.gov","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":3080,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","email":"mosland@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":920919,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baustian, Melissa M.","contributorId":189569,"corporation":false,"usgs":false,"family":"Baustian","given":"Melissa M.","affiliations":[],"preferred":false,"id":920920,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70261248,"text":"sir20245115 - 2024 - Flood-inundation maps for the Cuyahoga River at Jaite, Ohio, 2024","interactions":[],"lastModifiedDate":"2025-12-22T21:00:37.290202","indexId":"sir20245115","displayToPublicDate":"2024-12-04T06:45:00","publicationYear":"2024","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":"2024-5115","displayTitle":"Flood-Inundation Maps for the Cuyahoga River at Jaite, Ohio, 2024","title":"Flood-inundation maps for the Cuyahoga River at Jaite, Ohio, 2024","docAbstract":"

Digital flood-inundation maps for a nearly 6-mile reach of the Cuyahoga River at Jaite, Ohio, were created by the U.S. Geological Survey (USGS) in cooperation with the Northeast Ohio Regional Sewer District Board of Trustees. The maps depict estimates of the extent and depth of flooding corresponding to selected water levels (stages) at USGS streamgage 04206425 on the Cuyahoga River at Jaite, Ohio.

Water-surface profiles were computed for the stream reach by using a one-dimensional steady-state step-backwater model. The hydraulic model was calibrated to the current USGS streamgage data and then used to compute 15 water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from 6 to 20 feet, which correspond to below “action stage” to “major flood stage” as reported by the National Weather Service. The simulated water-surface profiles were then used with a geographic information system digital elevation model derived from light detection and ranging data to delineate the areas flooded at each stage.

These maps, along with current stage data from the USGS streamgage and forecasted high-flow stages from the National Weather Service, can provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for postflood recovery efforts.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245115","collaboration":"Prepared in cooperation with the Northeast Ohio Regional Sewer District Board of Trustees","usgsCitation":"Whitehead, M.T., and Ostheimer, C.J., 2024, Flood-inundation maps for the Cuyahoga River at Jaite, Ohio, 2024: U.S. Geological Survey Scientific Investigations Report 2024–5115, 12 p., https://doi.org/10.3133/sir20245115.","productDescription":"Report: vi, 12 p.; 1 Data Release","numberOfPages":"12","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-158402","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":497897,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118059.htm","linkFileType":{"id":5,"text":"html"}},{"id":464690,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O3MYQ0","text":"USGS data release","linkHelpText":"Geospatial datasets and hydraulic model for flood-inundation maps of Cuyahoga River at Jaite, Ohio"},{"id":464689,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5115/images/"},{"id":464688,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5115/sir20245115.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2024-5115 XML"},{"id":464685,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5115/coverthb.jpg"},{"id":464686,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5115/sir20245115.pdf","text":"Report","size":"3.08 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5115 PDF"},{"id":464687,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245115/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5115 HTML"}],"country":"United States","state":"Ohio","city":"Jaite","otherGeospatial":"Cuyahoga River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.6,\n 41.3167\n ],\n [\n -81.6,\n 41.25\n ],\n [\n -81.5,\n 41.25\n ],\n [\n -81.5,\n 41.3167\n ],\n [\n -81.6,\n 41.3167\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Blvd, Suite 100
Columbus, OH 43229

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2024-12-04","noUsgsAuthors":false,"publicationDate":"2024-12-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Whitehead, Matthew T. 0000-0002-4888-2597 mtwhiteh@usgs.gov","orcid":"https://orcid.org/0000-0002-4888-2597","contributorId":218036,"corporation":false,"usgs":true,"family":"Whitehead","given":"Matthew T.","email":"mtwhiteh@usgs.gov","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":920110,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ostheimer, Chad J. 0000-0002-4528-8867","orcid":"https://orcid.org/0000-0002-4528-8867","contributorId":213950,"corporation":false,"usgs":true,"family":"Ostheimer","given":"Chad","email":"","middleInitial":"J.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":920111,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70270827,"text":"70270827 - 2024 - Increasing soil water drought in response to altered precipitation timing across the western United States","interactions":[],"lastModifiedDate":"2025-08-25T14:50:40.293404","indexId":"70270827","displayToPublicDate":"2024-12-04T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Increasing soil water drought in response to altered precipitation timing across the western United States","docAbstract":"

Recent trends of rising temperatures and longer droughts between precipitation events are impacting water-limited dryland ecosystems in the western United States. Although ecosystem drought response depends directly on soil moisture, trends in soil moisture (e.g., edaphic drought) remain more poorly explored than precipitation (e.g., meteorological drought), representing an important knowledge gap. Here, we applied the SOILWAT2 ecosystem water balance model to quantify long-term trends of soil moisture and edaphic drought using observed daily weather from 1976 to 2019 at 337 stations across the western United States. We assessed edaphic drought for different plant community types (grass dominated vs. shrub dominated), and explored variations with soil depth and texture. The duration of the longest edaphic drought in a given year increased by 1.5 ± 0.2 days/decade for grassy and 1.7 ± 0.2 days/decade for woody vegetation. Importantly, these trends in edaphic drought were consistent with but greater in magnitude compared with meteorological drought indicating more severe water stress for both plants and ecosystems. The correlation between meteorological drought and edaphic drought was greater under woody vegetation (0.45) compared with grass (0.34) and greater at surface soil depths (0–20 cm; 0.46) compared with the deeper soil (20–100 cm; 0.34). Among soil textures, the correlation between meteorological and edaphic drought was highest on sandy soils and lowest on finer textured silty soils. Using the biogeographic domains (eight western NEON domains), we found that the Pacific Northwest, Pacific Southwest, and Desert Southwest exhibited the strongest increases in edaphic drought through time, but lower correlation between meteorological and edaphic droughts. These findings characterize strong but variable connections between edaphic drought and meteorological drought across the western United States and demonstrate the critical influences of vegetation type, soil depth, and soil properties in mediating the magnitude and spatial distribution of edaphic drought.

","language":"English","publisher":"Wiley","doi":"10.1002/eco.2749","usgsCitation":"Zhang, F., Biederman, J.A., Schlaepfer, D.R., Bradford, J.B., Reed, S.C., and Smith, W.K., 2024, Increasing soil water drought in response to altered precipitation timing across the western United States: Ecohydrology, v. 18, no. 2, e2749, 12 p., https://doi.org/10.1002/eco.2749.","productDescription":"e2749, 12 p.","ipdsId":"IP-163653","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":498230,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eco.2749","text":"Publisher Index Page"},{"id":494732,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"western United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -125.86807902477261,\n 49.588522649130624\n ],\n [\n -125.36941038239132,\n 41.02167216747373\n ],\n [\n -122.62525956962213,\n 32.782718887450514\n ],\n [\n -101.22796660251535,\n 31.03128157801875\n ],\n [\n -101.22796660251535,\n 49.588522649130624\n ],\n [\n -125.86807902477261,\n 49.588522649130624\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-12-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Zhang, Fangyue","contributorId":266007,"corporation":false,"usgs":false,"family":"Zhang","given":"Fangyue","email":"","affiliations":[{"id":54855,"text":"USDA Agricultural Research Service Southwest Watershed Research Center, Tucson, Arizona 85719 ; School of Natural Resources and the Environment, University of Arizona, Tucson, Arizona 85721","active":true,"usgs":false}],"preferred":false,"id":947146,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Biederman, Joel A.","contributorId":360505,"corporation":false,"usgs":false,"family":"Biederman","given":"Joel","middleInitial":"A.","affiliations":[{"id":86023,"text":"USDA Agricultural Research Service Southwest Watershed Research Center, Tucson, AZ 85719, USA","active":true,"usgs":false}],"preferred":false,"id":947147,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schlaepfer, Daniel Rodolphe 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":947148,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":947149,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":217604,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":947150,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, William K.","contributorId":360506,"corporation":false,"usgs":false,"family":"Smith","given":"William","middleInitial":"K.","affiliations":[{"id":86024,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ 85721, USA","active":true,"usgs":false}],"preferred":false,"id":947151,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70261232,"text":"ofr20241071 - 2024 - Using the horizontal-to-vertical spectral ratio method to estimate thickness of the Barry Arm landslide, Prince William Sound, Alaska","interactions":[],"lastModifiedDate":"2025-12-22T20:41:07.836719","indexId":"ofr20241071","displayToPublicDate":"2024-12-03T13:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-1071","displayTitle":"Using the Horizontal-to-Vertical Spectral Ratio Method to Estimate Thickness of the Barry Arm Landslide, Prince William Sound, Alaska","title":"Using the horizontal-to-vertical spectral ratio method to estimate thickness of the Barry Arm landslide, Prince William Sound, Alaska","docAbstract":"

Conducting detailed investigations of large landslides is difficult, especially in the subsurface, largely due to environmental factors such as steep slopes, difficult access, and numerous objective hazards. These factors have made it challenging to accurately estimate the depth to the failure surface of the Barry Arm landslide, a large (roughly 108 cubic meters), deep-seated bedrock landslide in Prince William Sound, Alaska, recognized in 2019. The landslide has exhibited accelerated movement in recent years and poses a potential tsunamigenic hazard if rapid failure occurs. Failure surface depth, equivalent to landslide thickness, is a necessary metric for landslide-volume calculations and associated tsunami wave models. In this report, we used seismic noise recorded by a seismometer located on the Barry Arm landslide in Alaska to calculate the horizontal-to-vertical spectral ratio (HVSR) to investigate the site fundamental frequency (f0) and depth of the failure surface. To ensure that observed peak frequencies in the spectral ratio were related to the underlying stratigraphy (and not caused by other noise sources like nearby glaciers, topographic resonance, weather, or human activities), we also calculated HVSRs using earthquake signals, HVSRs at other seismic stations within a 2.5-kilometer radius, and a standard spectral ratio between the landslide station and other sites. We observed multiple peaks in the landslide HVSR curves at 1.5 hertz (Hz), 4–5 Hz, and 7–11 Hz. The frequencies of these peaks were consistent at the landslide site through time and across methods and were dissimilar to those identified at other seismic stations in the area, making it unlikely the peaks were caused by local noise.

Directional HVSRs calculated at 15-degree intervals showed amplification of the higher frequency peaks in the direction parallel to slip, indicating two-dimensional site effects. We used the distinct frequency peaks in the seismic record to develop a 4-layer conceptual model of the landslide wherein the top of the deepest layer represents the primary failure surface, or the boundary between damaged (mobile) and undamaged material. We inverted Rayleigh wave ellipticity curves within this 4-layer configuration with constraints on S-wave velocity and layer thickness based on analogous material properties identified in the literature. This was necessary absent any site-specific subsurface S-wave velocity data. The best-fitting models indicate a mean slope-normal depth to the failure surface of 188 (±9) meters (m), with additional stratigraphic boundaries at 4 and 20 m below ground surface, potentially representing layered motion. These results agree with and improve upon ranges estimated by previous studies and can support future modeling and assessment efforts at Barry Arm.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20241071","programNote":"Landslide Hazards Program","usgsCitation":"Collins, A.L., Allstadt, K.E., and Staley, D.M., 2024, Using the horizontal-to-vertical spectral ratio method to estimate thickness of the Barry Arm landslide, Prince William Sound, Alaska: U.S. Geological Survey Open-File Report 2024–1071, 25 p., https://doi.org/10.3133/ofr20241071.","productDescription":"vii, 25 p.","onlineOnly":"Y","ipdsId":"IP-164227","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":464747,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241071/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1043"},{"id":464705,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1071/ofr20241071.xml"},{"id":464704,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1071/images"},{"id":464670,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1071/ofr20241071.pdf","text":"Report","size":"12.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1071"},{"id":464669,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1071/coverthb.jpg"},{"id":497896,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118058.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Alaska","otherGeospatial":"Barry Arm landslide","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -148.08474908024374,\n 61.17012644718048\n ],\n [\n -148.15558320312988,\n 61.17012644718048\n ],\n [\n -148.1702846248608,\n 61.12691732704323\n ],\n [\n -148.11415192370606,\n 61.12498100886924\n ],\n [\n -148.08474908024374,\n 61.17012644718048\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, Mail Stop 966
Denver, CO 80225

","tableOfContents":"","publishedDate":"2024-12-03","noUsgsAuthors":false,"publicationDate":"2024-12-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Collins, Andrew L. 0000-0003-4751-7333","orcid":"https://orcid.org/0000-0003-4751-7333","contributorId":332093,"corporation":false,"usgs":true,"family":"Collins","given":"Andrew","email":"","middleInitial":"L.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":920004,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allstadt, Kate E. 0000-0003-4977-5248","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":138704,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":920005,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Staley, Dennis M. 0000-0002-2239-3402 dstaley@usgs.gov","orcid":"https://orcid.org/0000-0002-2239-3402","contributorId":4134,"corporation":false,"usgs":true,"family":"Staley","given":"Dennis","email":"dstaley@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":920006,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70261290,"text":"70261290 - 2024 - The dynamics of sea otter prey selection under population growth and expansion","interactions":[],"lastModifiedDate":"2024-12-05T15:09:26.868315","indexId":"70261290","displayToPublicDate":"2024-12-03T09:04:22","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"The dynamics of sea otter prey selection under population growth and expansion","docAbstract":"

Sea otters (Enhydra lutris) were extirpated from much of their range in the North Pacific by the early 1900s but have made a remarkable recovery in Southeast Alaska. Sea otter populations have been particularly successful in Glacier Bay, Alaska, a protected tidewater glacier fjord with a diverse and productive nearshore habitat. Collection of sea otter foraging observations in Glacier Bay began in 1993, along with high-resolution aerial surveys that provide estimates of sea otter abundance and distribution. We integrated these two data sources to investigate how sea otter diet changed in space and time as sea otters established and spread across Glacier Bay. Specifically, we developed a multilevel Bayesian model to capture how sea otter diet at a location (the number, type, and size of prey collected) changed as a function of local cumulative otter abundance and the year in which the location was first occupied. This framework enabled us to estimate the sequence of sea otter prey selection and switching as prey populations responded to sea otter foraging pressure. We found that local sea otter diet changed substantially as the population established, shifting away from large urchins, crabs, and clams to Modiolus mussels and small urchins, and lastly to small clams and Mytilus mussels. We also found that sea otter diet at newly occupied sites changed as otters spread over the main channel and into the arms of Glacier Bay. Further, by 2019, sea otters across the bay were primarily foraging on small prey, regardless of the local occupancy history. The absence of a spatial gradient in the size of prey captured late in the study suggests that feedbacks between the top-down effects of sea otter foraging, sea otter dispersal processes, and local variation in habitat productivity may have homogenized the size structure of available prey across Glacier Bay.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70084","usgsCitation":"Leach, C., Weitzman, B., Bodkin, J., Esler, D., Esslinger, G.G., Kloecker, K.A., Monson, D., Womble, J., and Hooten, M.B., 2024, The dynamics of sea otter prey selection under population growth and expansion: Ecosphere, v. 15, no. 12, e70084, 16 p., https://doi.org/10.1002/ecs2.70084.","productDescription":"e70084, 16 p.","ipdsId":"IP-160898","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":489061,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70084","text":"Publisher Index Page"},{"id":464801,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Glacier Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -136.8,\n 59\n ],\n [\n -136.8,\n 58.4\n ],\n [\n -135.8,\n 58.4\n ],\n [\n -135.8,\n 59\n ],\n [\n -136.8,\n 59\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Leach, Clint","contributorId":167886,"corporation":false,"usgs":false,"family":"Leach","given":"Clint","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":920247,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weitzman, Ben","contributorId":252838,"corporation":false,"usgs":false,"family":"Weitzman","given":"Ben","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":920248,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bodkin, Jim","contributorId":328539,"corporation":false,"usgs":false,"family":"Bodkin","given":"Jim","email":"","affiliations":[{"id":7065,"text":"USGS emeritus","active":true,"usgs":false}],"preferred":false,"id":920249,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esler, Daniel 0000-0001-5501-4555 desler@usgs.gov","orcid":"https://orcid.org/0000-0001-5501-4555","contributorId":5465,"corporation":false,"usgs":true,"family":"Esler","given":"Daniel","email":"desler@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":920250,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Esslinger, George G. 0000-0002-3459-0083 gesslinger@usgs.gov","orcid":"https://orcid.org/0000-0002-3459-0083","contributorId":131009,"corporation":false,"usgs":true,"family":"Esslinger","given":"George","email":"gesslinger@usgs.gov","middleInitial":"G.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":920251,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kloecker, Kimberly A. 0000-0002-2461-968X kkloecker@usgs.gov","orcid":"https://orcid.org/0000-0002-2461-968X","contributorId":3442,"corporation":false,"usgs":true,"family":"Kloecker","given":"Kimberly","email":"kkloecker@usgs.gov","middleInitial":"A.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":920252,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Monson, Daniel 0000-0002-4593-5673 dmonson@usgs.gov","orcid":"https://orcid.org/0000-0002-4593-5673","contributorId":196670,"corporation":false,"usgs":true,"family":"Monson","given":"Daniel","email":"dmonson@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":920253,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Womble, Jamie N.","contributorId":267709,"corporation":false,"usgs":false,"family":"Womble","given":"Jamie N.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":920254,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hooten, Mevin B. 0000-0002-1614-723X","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":292295,"corporation":false,"usgs":false,"family":"Hooten","given":"Mevin","email":"","middleInitial":"B.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":920255,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70262202,"text":"70262202 - 2024 - Monitoring animal populations with cameras using open, multistate, N-mixture models","interactions":[],"lastModifiedDate":"2025-01-15T16:11:49.912007","indexId":"70262202","displayToPublicDate":"2024-12-02T09:06:48","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring animal populations with cameras using open, multistate, N-mixture models","docAbstract":"

Remote cameras have become a mainstream tool for studying wildlife populations. For species whose developmental stages or states are identifiable in photographs, there are opportunities for tracking population changes and estimating demographic rates. Recent developments in hierarchical models allow for the estimation of ecological states and rates over time for unmarked animals whose states are known. However, this powerful class of models has been underutilized because they are computationally intensive, and model outputs can be difficult to interpret. Here, we use simulation to show how camera data can be analyzed with multistate, Dail-Madsen (hereafter multistate DM) models to estimate abundance, survival, and recruitment. We evaluated four commonly encountered scenarios arising from camera trap data (low and high abundance and 25% and 50% missing data) each with 18 different sample size combinations (camera sites = 40, 250; surveys = 4, 8, and 12; and years = 2, 5, 10) and evaluated the bias and precision of abundance, survival, and recruitment estimates. We also analyzed our empirical camera data on moose (Alces alces) with multistate DM models and compared inference with telemetry studies from the same time and region to assess the accuracy of camera studies to track moose populations. Most scenarios recovered the known parameters from our simulated data with higher accuracy and increased precision for scenarios with more sites, surveys, and/or years. Large amounts of missing data and fewer camera sites, especially at higher abundances, reduced accuracy, and precision of survival and recruitment. Our empirical analysis provided biologically realistic estimates of moose survival and recruitment and recovered the pattern of moose abundance across the region. Multistate DM models can be used for estimating demographic parameters from camera data when developmental states are clearly identifiable. We discuss several avenues for future research and caveats for using multistate DM models for large-scale population monitoring.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.70583","usgsCitation":"Siren, A.P., Hallworth, M.T., Kilborn, J.R., Bernier, C., Fortin, N., Geider, K., Patry, R., Cliche, R.M., Prout, L.S., Gifford, S., Wixsom, S., Morelli, T.L., and Wilson, T.L., 2024, Monitoring animal populations with cameras using open, multistate, N-mixture models: Ecology and Evolution, v. 14, no. 12, e70583, 13 p., https://doi.org/10.1002/ece3.70583.","productDescription":"e70583, 13 p.","ipdsId":"IP-171292","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":466731,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.70583","text":"Publisher Index Page"},{"id":466423,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Hampshire, 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Temuco, Chile","active":true,"usgs":false}],"preferred":false,"id":923484,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bernier, Chris A.","contributorId":348499,"corporation":false,"usgs":false,"family":"Bernier","given":"Chris A.","affiliations":[{"id":39587,"text":"Vermont Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":923485,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fortin, Nicholas L.","contributorId":348500,"corporation":false,"usgs":false,"family":"Fortin","given":"Nicholas L.","affiliations":[{"id":39587,"text":"Vermont Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":923486,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Geider, Katherina D.","contributorId":348501,"corporation":false,"usgs":false,"family":"Geider","given":"Katherina D.","affiliations":[{"id":39587,"text":"Vermont Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":923487,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Patry, Riley K.","contributorId":348502,"corporation":false,"usgs":false,"family":"Patry","given":"Riley K.","affiliations":[{"id":83367,"text":"Dartmouth College Woodlands","active":true,"usgs":false}],"preferred":false,"id":923488,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cliche, Rachel M.","contributorId":331624,"corporation":false,"usgs":false,"family":"Cliche","given":"Rachel","email":"","middleInitial":"M.","affiliations":[{"id":79254,"text":"United States Fish and Wildlife Service, Silvio O. Conte National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":923489,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Prout, Leighlan S.","contributorId":331625,"corporation":false,"usgs":false,"family":"Prout","given":"Leighlan","email":"","middleInitial":"S.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":923490,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gifford, Suzanne J.","contributorId":348504,"corporation":false,"usgs":false,"family":"Gifford","given":"Suzanne J.","affiliations":[{"id":40027,"text":"United States Forest Service","active":true,"usgs":false}],"preferred":false,"id":923491,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wixsom, Scott","contributorId":339522,"corporation":false,"usgs":false,"family":"Wixsom","given":"Scott","affiliations":[{"id":81331,"text":"USDA Green Mountain National Forest","active":true,"usgs":false}],"preferred":false,"id":923492,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":923493,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Wilson, Tammy L. 0000-0002-3672-8277","orcid":"https://orcid.org/0000-0002-3672-8277","contributorId":293684,"corporation":false,"usgs":true,"family":"Wilson","given":"Tammy","email":"","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923494,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70261108,"text":"sir20245073 - 2024 - Assessment of the interconnection between Tampa Bay and the Floridan aquifer system: Historical groundwater data compilation and analysis, 1976–2022","interactions":[],"lastModifiedDate":"2025-12-22T21:06:29.381777","indexId":"sir20245073","displayToPublicDate":"2024-12-02T08:51:01","publicationYear":"2024","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":"2024-5073","displayTitle":"Assessment of the Interconnection Between Tampa Bay and the Floridan Aquifer System: Historical Groundwater Data Compilation and Analysis, 1976–2022","title":"Assessment of the interconnection between Tampa Bay and the Floridan aquifer system: Historical groundwater data compilation and analysis, 1976–2022","docAbstract":"

The U.S. Geological Survey used existing data collected after the last major navigational channel modification in the mid-1980s to investigate groundwater levels and chloride concentrations in wells in the Floridan aquifer system and other aquifers beneath and near Tampa Bay. Tampa Bay is located on the west-central coast of Florida and provides access for commercial shipping. In 2021, the U.S. Army Corps of Engineers began to investigate alternatives to improve the efficiency of the deep-draft navigation channels within Tampa Bay, reduce costs, improve safety, and analyze the implications of modifying navigational channels. The Floridan aquifer system underlies Tampa Bay and is the primary source of public water supply in the region. Modifications to the channels have the potential to expose the Floridan aquifer system to the saltwater in Tampa Bay, with the potential to increase salinity in wells in the region. Other factors affecting the groundwater levels and the location of the freshwater/saltwater interface were also examined, including changes in sea level, groundwater extraction, and variations in climate.

Groundwater levels and well-construction reports were used to identify whether different aquifer units are well-connected. Twelve wells had available data before and after the last major channel modifications, which took place in the 1980s, with six datasets of chloride concentration available in areas along the northern and eastern coastline of Tampa Bay, which is nearest to historical dredging activities. Of these six, Kendall’s τ and p-values indicated increasing trends in chloride concentration for three datasets (TR 11-2, TR 10-2, 51), no trend in chloride concentration for two datasets (TR 9-3, 50), and a decreasing trend in chloride concentration for one dataset (TR 9-1). The upward trends in chloride concentration observed for TR 10-2 and 51 are likely the result of changes in local groundwater withdrawals. Well TR 11-2 had a gradual increasing trend in chloride concentration, fresh groundwater throughout the period of record, and a 3- to 4-foot increase in hydraulic head during the period of record, possibly caused by the construction and control of the Tampa Bypass Canal, resulting in changes to the regional potentiometric surface.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245073","issn":"2328-0328","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Decker, J.D., 2024, Assessment of the interconnection between Tampa Bay and the Floridan aquifer system—Historical groundwater data compilation and analysis, 1976–2022: U.S. Geological Survey Scientific Investigations Report 2024–5073, 95 p., https://doi.org/10.3133/sir20245073.","productDescription":"Report: x, 95 p.; Data Release","numberOfPages":"110","onlineOnly":"Y","ipdsId":"IP-160506","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":464929,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245073/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5073 HTML"},{"id":464447,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://waterdata.usgs.gov/nwis/","text":"USGS water data for the Nation","linkHelpText":"- USGS National Water Information System database"},{"id":464444,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5073/sir20245073.pdf","size":"7.42 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5073"},{"id":464443,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5073/images"},{"id":464442,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5073/coverthb.jpg"},{"id":464624,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5073/sir20245073.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2024-5073 XML"},{"id":497902,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118056.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida","otherGeospatial":"Tampa Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.88462108750781,\n 28.199458304380144\n ],\n [\n -82.88462108750781,\n 27.315234231945368\n ],\n [\n -82.28125819751263,\n 27.315234231945368\n ],\n [\n -82.28125819751263,\n 28.199458304380144\n ],\n [\n -82.88462108750781,\n 28.199458304380144\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559

Contact Us- USGS Publications Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2024-12-02","noUsgsAuthors":false,"publicationDate":"2024-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Decker, Jeremy D. 0000-0002-0700-515X","orcid":"https://orcid.org/0000-0002-0700-515X","contributorId":202857,"corporation":false,"usgs":true,"family":"Decker","given":"Jeremy","email":"","middleInitial":"D.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true},{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":919310,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70256975,"text":"70256975 - 2024 - A partially nonergodic ground-motion model for Fourier amplitude spectra for the San Francisco Bay area, California, USA","interactions":[],"lastModifiedDate":"2026-03-27T19:14:38.860534","indexId":"70256975","displayToPublicDate":"2024-12-01T13:54:15","publicationYear":"2024","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A partially nonergodic ground-motion model for Fourier amplitude spectra for the San Francisco Bay area, California, USA","docAbstract":"

We develop a partially nonergodic ground-motion model (GMM) for Fourier amplitude spectra for the San Francisco Bay Area, California, USA, using the Bayless and Abrahamson (2019) GMM as a reference ergodic GMM and developing location-dependent adjustments to the predicted median and variance. We compile regional ground-motion data from moment magnitude (\uD835\uDC40w) >3 earthquakes occurring during 2000–2022 for which magnitude information is available in the U.S. Geological Survey Comprehensive Catalog (Guy et al., 2015). The data set predominantly consists of records from \uD835\uDC40w3.5–4.5 earthquakes but includes three well-recorded \uD835\uDC40w > 5 events. Ground-motion residuals are evaluated using the time-averaged shear-wave velocity in the top 30 m (\uD835\uDC49S30) from the California-specific map of Thompson et al. (2018) and basin-depth site parameters from the seismic velocity model of Aagaard and Hirakawa (2021). The \uD835\uDC49S30 dependence and basin-depth scaling of the reference ergodic GMM of Bayless and Abrahamson (2019) are evaluated and modified with the updated data set. We compute maps of site adjustments using a varying-coefficient model that considers the spatial correlation structure and uncertainties at each observation location. The spatial covariance model is developed using ground-motion residuals that are standardized by the uncertainty model, which allows for consideration of the aleatory variability in developing the site adjustments. The covariance model is fit considering the means and standard deviations of the site terms at all locations. The use of partially nonergodic median adjustments results in modified variance components of the within-event variability. Due to the low number of large-magnitude earthquakes that control seismic hazard in the data set, we do not modify between-event variance; however, we present adjustments to site-to-site variability for use in partially nonergodic hazard assessments. 

","conferenceTitle":"18th World Conference on Earthquake Engineering","conferenceDate":"June 30-July 5, 2024","conferenceLocation":"Milan, Italy","language":"English","publisher":"International Association for Earthquake Engineering","usgsCitation":"Moschetti, M.P., Thompson, E.M., Peterson, R., Smith, J.A., and Aagaard, B.T., 2024, A partially nonergodic ground-motion model for Fourier amplitude spectra for the San Francisco Bay area, California, USA, 18th World Conference on Earthquake Engineering, Milan, Italy, June 30-July 5, 2024, 12 p.","productDescription":"12 p.","ipdsId":"IP-162025","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":501753,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://proceedings-wcee.org/view.html?id=23629&conference=18WCEE"},{"id":501752,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.5,\n 38.37517483429019\n ],\n [\n -123.5,\n 36.90107315948201\n ],\n [\n -121,\n 36.90107315948201\n ],\n [\n -121,\n 38.37517483429019\n ],\n [\n -123.5,\n 38.37517483429019\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":909047,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":909048,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, Ryan","contributorId":341857,"corporation":false,"usgs":false,"family":"Peterson","given":"Ryan","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":909049,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, James Andrew 0000-0002-5565-9254 jimsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-5565-9254","contributorId":332933,"corporation":false,"usgs":true,"family":"Smith","given":"James","email":"jimsmith@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"preferred":true,"id":909050,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aagaard, Brad T. 0000-0002-8795-9833 baagaard@usgs.gov","orcid":"https://orcid.org/0000-0002-8795-9833","contributorId":192869,"corporation":false,"usgs":true,"family":"Aagaard","given":"Brad","email":"baagaard@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":909051,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70265951,"text":"70265951 - 2024 - Natural resource management confronts the growing scale and severity of ecosystem responses to drought and wildfire","interactions":[],"lastModifiedDate":"2025-04-22T16:57:48.586238","indexId":"70265951","displayToPublicDate":"2024-12-01T11:55:38","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1468,"text":"Ecology and Society","active":true,"publicationSubtype":{"id":10}},"title":"Natural resource management confronts the growing scale and severity of ecosystem responses to drought and wildfire","docAbstract":"

Intensification of drought and wildfire associated with climate change has triggered widespread ecosystem stress and transformation. Natural resource managers are on the frontline of these changes, yet their perspectives on whether management actions match the scale and align with the severity of ecosystem responses to improve outcomes are not well understood. To provide new insight, a new conceptual framework that linked scale and severity was tested by conducting interviews and surveys of staff associated with natural resource management on the Colorado Plateau in the southwestern United States (U.S.), which contains the highest concentration of public lands in the contiguous U.S. Results indicate that drought was experienced more frequently than wildfire, and both stressors were happening at large scales and moderate to abrupt timeframes with a high degree of impact to ecosystems. Ecosystem responses were perceived to increase in severity under future climate change with limited capacity to recover, and a majority of resource managers expressed that they had low control to shape these trajectories. Although management strategies to address drought and wildfire were well recognized, adaptation-specific actions remained unclear or had limited financial and staffing resources to support implementation. Additional effort could help close a growing misalignment between management actions and natural resource responses, including effective science communication, refined information tailored to meet adaptation goals at management-relevant spatiotemporal scales, and opportunities for adaptive management that can proactively address intensification of drought and wildfire.

","language":"English","publisher":"Resilience Alliance","doi":"10.5751/ES-15517-290417","usgsCitation":"Munson, S.M., Vaughn, A., Petersen, B., Bradford, J., and Duniway, M.C., 2024, Natural resource management confronts the growing scale and severity of ecosystem responses to drought and wildfire: Ecology and Society, v. 29, no. 4, 17, 23 p., https://doi.org/10.5751/ES-15517-290417.","productDescription":"17, 23 p.","ipdsId":"IP-157838","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":488488,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/es-15517-290417","text":"Publisher Index Page"},{"id":484850,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":934144,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vaughn, Anna L.","contributorId":353625,"corporation":false,"usgs":false,"family":"Vaughn","given":"Anna L.","affiliations":[{"id":84447,"text":"Dept. of Geography, Planning and Recreation Program in Sustainable Communities, Northern Arizona University, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":934145,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Petersen, Brian","contributorId":191672,"corporation":false,"usgs":false,"family":"Petersen","given":"Brian","email":"","affiliations":[],"preferred":false,"id":934146,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":934147,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":934148,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70258358,"text":"70258358 - 2024 - Challenges in developing vertical hazard for seismic analysis of concrete dams","interactions":[],"lastModifiedDate":"2026-04-21T16:24:13.096174","indexId":"70258358","displayToPublicDate":"2024-12-01T11:22:09","publicationYear":"2024","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Challenges in developing vertical hazard for seismic analysis of concrete dams","docAbstract":"The seismic response of concrete dams depends on both the horizontal (H) and vertical (V) components of ground motion (GM), and excluding the V components when conducting response history analyses (RHAs) may underestimate the seismic fragility. Although V components of GM time series could be selected to be consistent with the hazard, hazard curves for the V component (or for short, V hazard curves) are rarely available for evaluating such hazard consistency. One of the challenges in developing V hazard curves in the U.S. Geological Survey (USGS) National Seismic Hazard Model (NSHM) is the lack of ground motion models (GMMs) that directly estimate intensity measures (IMs) for the V component of GM. In this study, we compare alternative approaches of developing V hazard curves. Using a case study in California, we compare V hazard curves computed from GMMs for the V component of GM against those from applying GMMs for the V/H ratios and those from selecting multicomponent time series that are consistent with the H hazard. We discuss and invite feedback on issues such as availability of GMMs, applicability of GMMs, and choice of inputs for ground motion selection and modification (GMSM).","conferenceTitle":"18th World Conference on Earthquake Engineering","conferenceDate":"June 30-July 5, 2024","conferenceLocation":"Milan, Italy","language":"English","publisher":"International Association for Earthquake Engineering","usgsCitation":"Kwong, N.S., Rezaeian, S., Makdisi, A.J., and Luco, N., 2024, Challenges in developing vertical hazard for seismic analysis of concrete dams, 18th World Conference on Earthquake Engineering, Milan, Italy, June 30-July 5, 2024, 12 p.","productDescription":"12 p.","ipdsId":"IP-160244","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":503275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":433715,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://proceedings-wcee.org/view.html?id=22755&conference=18WCEE"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kwong, N. Simon 0000-0003-3017-9585","orcid":"https://orcid.org/0000-0003-3017-9585","contributorId":241863,"corporation":false,"usgs":true,"family":"Kwong","given":"N.","email":"","middleInitial":"Simon","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":913035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rezaeian, Sanaz 0000-0001-7589-7893 srezaeian@usgs.gov","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":4395,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","email":"srezaeian@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":913036,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Makdisi, Andrew James 0000-0002-8239-0692","orcid":"https://orcid.org/0000-0002-8239-0692","contributorId":267917,"corporation":false,"usgs":true,"family":"Makdisi","given":"Andrew","email":"","middleInitial":"James","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":913037,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":913038,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70258357,"text":"70258357 - 2024 - Development of USGS NSHMs: Do small changes in hazard imply small changes in risk?","interactions":[],"lastModifiedDate":"2026-04-21T16:20:04.754461","indexId":"70258357","displayToPublicDate":"2024-12-01T11:16:45","publicationYear":"2024","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Development of USGS NSHMs: Do small changes in hazard imply small changes in risk?","docAbstract":"One of the flagship products from the U.S. Geological Survey (USGS) is the National Seismic Hazard Model (NSHM). Since 1976, the NSHM has been periodically updated to reflect newly published earthquake science and provide probabilistic estimates of seismic hazard for the United States. During each update cycle, alternative models are deliberated, analyzed, and documented through logic trees and their corresponding logic tree branch weights. For example, the decision to modify a logic tree branch weight may be influenced by sensitivity analyses of the logic tree branches in their effects on the mean hazard. However, do small changes in traditional measures of hazard imply small changes in risk? In this study, we make use of two update cycles of the USGS NSHMs and a National Bridge Inventory (NBI) from the Federal Highway Administration (FHWA) to explore the preceding question. Specifically, we first identify geographic locations in the conterminous United States in which the change in hazard from one cycle to another is relatively small. Next, we model the seismic risk to highway bridges for these locations and for each update cycle, while simultaneously distinguishing low hazard environments from high hazard environments. These data enable quantitative analysis of how much changes in risk can be expected given small changes in hazard, investigating the importance of risk models in decision-making during development of the USGS NSHMs.","conferenceTitle":"18th World Conference on Earthquake Engineering","conferenceDate":"June 30-July 5, 2024","conferenceLocation":"Milan, Italy","language":"English","publisher":"International Association for Earthquake Engineering","usgsCitation":"Kwong, N.S., and Jaiswal, K.S., 2024, Development of USGS NSHMs: Do small changes in hazard imply small changes in risk?, 18th World Conference on Earthquake Engineering, Milan, Italy, June 30-July 5, 2024, 11 p.","productDescription":"11 p.","ipdsId":"IP-160243","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":503274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":433714,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://proceedings-wcee.org/view.html?id=24719&conference=18WCEE"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kwong, N. Simon 0000-0003-3017-9585","orcid":"https://orcid.org/0000-0003-3017-9585","contributorId":241863,"corporation":false,"usgs":true,"family":"Kwong","given":"N.","email":"","middleInitial":"Simon","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":913033,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":913034,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70271418,"text":"70271418 - 2024 - Geophysical modeling of a possible blind geothermal system near Battle Mountain, NV","interactions":[],"lastModifiedDate":"2025-09-12T16:15:46.534671","indexId":"70271418","displayToPublicDate":"2024-12-01T11:05:15","publicationYear":"2024","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Geophysical modeling of a possible blind geothermal system near Battle Mountain, NV","docAbstract":"The northeastern portion of the Reese River basin in north-central Nevada is the focus of detailed geophysical and geological studies as part of the INGENIOUS project, which aims to identify new, commercially viable hidden geothermal systems in the Great Basin region of the western U.S. This location, herein referred to as Argenta Rise, occupies a broad (~15km wide) left-step between major range-front fault systems along the northwestern edge of the Shoshone Range and Argenta Rim, with numerous ENE-striking intra-basin faults presumably accommodating sinistral-normal oblique slip across the step-over. Four discrete regions have been identified within the study area that have favorable structural settings for hosting a blind hydrothermal system. However, with no definitive or extensive surface manifestations of an active hydrothermal system (e.g., geysers, steam vents, sinter, etc.), detailed geophysical studies are necessary to resolve subsurface geology and structure, and identify zones of enhanced structural complexity that may promote hydrothermal fluid flow. Hence, we collected high-resolution gravity, MT, and rock property data (density, magnetic susceptibility), and analyzed the recently acquired GeoDAWN aeromagnetic data to characterize potential geothermal resources in this region. Using the new geophysical datasets, we jointly modeled gravity and magnetic data along a series of intersecting 2D profiles that integrated information from recent, local-scale fault mapping. Rock property measurements performed on outcrops and hand samples throughout the study area constrained the models. The MT data were used to construct a 3D resistivity model that highlights the location of inferred alteration and fluids in the subsurface. Combined MT and potential field results reveal which structures may be most important for controlling hydrothermal fluid migration, as well as which geologic units may host hydrothermal fluids. Our gravity derived depth to basement surface coincides well with the base of shallow conductive anomalies, suggesting hydrothermal fluids may be confined to basin fill sediments and volcanics. This work supports our development of 3D geophysical and geologic models that are focused along the western flank of the northern Shoshone Range and aids the process of selecting sites for temperature gradient drilling.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Using the Earth to save the Earth","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Geothermal Rising","usgsCitation":"Earney, T.E., Glen, J.M., Peacock, J., Faulds, J., Schermerhorn, W.D., Rea-Downing, G.H., Anderson, J.E., Lindsey, C.R., and Richards, M., 2024, Geophysical modeling of a possible blind geothermal system near Battle Mountain, NV, in Using the Earth to save the Earth, v. 48, p. 1699-1719.","productDescription":"21 p.","startPage":"1699","endPage":"1719","ipdsId":"IP-167246","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science 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James","contributorId":344582,"corporation":false,"usgs":false,"family":"Faulds","given":"James","affiliations":[{"id":82394,"text":"Nevada Bureau of Mines and Geology, University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":948687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schermerhorn, William D. 0000-0002-0167-378X","orcid":"https://orcid.org/0000-0002-0167-378X","contributorId":210081,"corporation":false,"usgs":true,"family":"Schermerhorn","given":"William","email":"","middleInitial":"D.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":948688,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rea-Downing, Grant Harold 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0000-0001-5693-9664","orcid":"https://orcid.org/0000-0001-5693-9664","contributorId":333436,"corporation":false,"usgs":false,"family":"Lindsey","given":"Cary","email":"","middleInitial":"R.","affiliations":[{"id":79883,"text":"USGS for this work (just joined GBCGE at UNR)","active":true,"usgs":false}],"preferred":false,"id":948691,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Richards, Maria 0000-0002-8416-4111","orcid":"https://orcid.org/0000-0002-8416-4111","contributorId":361370,"corporation":false,"usgs":false,"family":"Richards","given":"Maria","affiliations":[{"id":86255,"text":"University of Nevada, Reno, Great Basin Center for Geothermal Energy, Nevada Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":948692,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ]}