Sequoia sempervirens (coast redwood) tree rings have the potential to annually resolve late-Holocene earthquakes on the northern San Andreas Fault based on direct (e.g., physical damage) and indirect (e.g., co-seismic environmental change) impacts, but scarcity of suitable samples and challenges crossdating this long-lived species have limited progress. More precise dating of the pre-1906 (penultimate) earthquake can improve hazard assessment and understanding of rupture segmentation. We target old trees (maximum >815 yr) along the North Coast section of the fault (increment cores via rope-climbing, 11 living trees; plunge cuts, 23 stumps) and employ complementary disturbance detection methods including radial-growth averaging (tree- and series-level), cataloging anatomical indicators (e.g., traumatic resin ducts, TRD), and dating structural components (e.g., reiterated trunks, leans). Multi-centennial ring-width chronologies at Fort Ross (1569−2023) and Gualala (1397−2023) promote continued study with incomplete crossdating limiting utilization of some series. Growth pulses (reductions, releases) and TRD dispersed across the record reflect dynamic environments that obfuscate detection of earthquake signals. The 1906 earthquake did not leave strong signatures on most trees, and when it did, within-tree response varied from normal presentation to discoloration, TRD, and missing rings. Synchrony of indicators at both locations identified 1678−1680 (6 of 15 trees) and 1698−1700 (8 of 16 trees) as the strongest disturbances among dated rings in the time range of the penultimate earthquake, peaking at 1698 (15.7 % of possible growth and anatomical indicators), but the triggering mechanisms for these events are unknown.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.qsa.2025.100283","usgsCitation":"Carroll, A.L., Philibosian, B.E., Sillett, S., Antoine, M., and Kozaci, Ö., 2025, Dendroseismological investigation of redwood trees along the North Coast section of the San Andreas Fault: Quaternary Science Advances, v. 18, 100283, 19 p., https://doi.org/10.1016/j.qsa.2025.100283.","productDescription":"100283, 19 p.","ipdsId":"IP-173541","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":489166,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.qsa.2025.100283","text":"Publisher Index Page"},{"id":486168,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"northern San Andreas Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.83814092270626,\n 38.92679649622329\n ],\n [\n -121.46229105607921,\n 35.267427833783145\n ],\n [\n -120.77467242000347,\n 35.50061264805049\n ],\n [\n -121.62057934578094,\n 36.93729771345596\n ],\n [\n -123.19764758041177,\n 39.037877559747045\n ],\n [\n -123.83814092270626,\n 38.92679649622329\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Carroll, Allyson L.","contributorId":171539,"corporation":false,"usgs":false,"family":"Carroll","given":"Allyson","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":937544,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Philibosian, Belle E. 0000-0003-3138-4716","orcid":"https://orcid.org/0000-0003-3138-4716","contributorId":206110,"corporation":false,"usgs":true,"family":"Philibosian","given":"Belle","email":"","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":937545,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sillett, Stephen C. 0000-0002-7147-759X","orcid":"https://orcid.org/0000-0002-7147-759X","contributorId":355531,"corporation":false,"usgs":false,"family":"Sillett","given":"Stephen C.","affiliations":[{"id":63943,"text":"Cal Poly Humboldt","active":true,"usgs":false}],"preferred":false,"id":937546,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Antoine, Marie E. 0009-0004-1771-1519","orcid":"https://orcid.org/0009-0004-1771-1519","contributorId":355534,"corporation":false,"usgs":false,"family":"Antoine","given":"Marie E.","affiliations":[{"id":63943,"text":"Cal Poly Humboldt","active":true,"usgs":false}],"preferred":false,"id":937547,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kozaci, Özgür 0000-0001-9439-0190","orcid":"https://orcid.org/0000-0001-9439-0190","contributorId":355536,"corporation":false,"usgs":false,"family":"Kozaci","given":"Özgür","affiliations":[{"id":39608,"text":"Pacific Gas & Electric Company","active":true,"usgs":false}],"preferred":false,"id":937548,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70271374,"text":"70271374 - 2025 - Global methane budget 2000-2020","interactions":[],"lastModifiedDate":"2025-09-10T14:32:19.040545","indexId":"70271374","displayToPublicDate":"2025-05-09T09:24:33","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1426,"text":"Earth System Science Data","active":true,"publicationSubtype":{"id":10}},"title":"Global methane budget 2000-2020","docAbstract":"Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. CH4 is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2), and both emissions and atmospheric concentrations of CH4 have continued to increase since 2007 after a temporary pause. The relative importance of CH4 emissions compared to those of CO2 for temperature change is related to its shorter atmospheric lifetime, stronger radiative effect, and acceleration in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in quantifying the factors responsible for the observed atmospheric growth rate arise from diverse, geographically overlapping CH4 sources and from the uncertain magnitude and temporal change in the destruction of CH4 by short-lived and highly variable hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to improve, synthesise, and update the global CH4 budget regularly and to stimulate new research on the methane cycle. Following Saunois et al. (2016, 2020), we present here the third version of the living review paper dedicated to the decadal CH4 budget, integrating results of top-down CH4 emission estimates (based on in situ and Greenhouse Gases Observing SATellite (GOSAT) atmospheric observations and an ensemble of atmospheric inverse-model results) and bottom-up estimates (based on process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). We present a budget for the most recent 2010–2019 calendar decade (the latest period for which full data sets are available), for the previous decade of 2000–2009 and for the year 2020.
The revision of the bottom-up budget in this 2025 edition benefits from important progress in estimating inland freshwater emissions, with better counting of emissions from lakes and ponds, reservoirs, and streams and rivers. This budget also reduces double counting across freshwater and wetland emissions and, for the first time, includes an estimate of the potential double counting that may exist (average of 23 Tg CH4 yr−1). Bottom-up approaches show that the combined wetland and inland freshwater emissions average 248 [159–369] Tg CH4 yr−1 for the 2010–2019 decade. Natural fluxes are perturbed by human activities through climate, eutrophication, and land use. In this budget, we also estimate, for the first time, this anthropogenic component contributing to wetland and inland freshwater emissions. Newly available gridded products also allowed us to derive an almost complete latitudinal and regional budget based on bottom-up approaches.
For the 2010–2019 decade, global CH4 emissions are estimated by atmospheric inversions (top-down) to be 575 Tg CH4 yr−1 (range 553–586, corresponding to the minimum and maximum estimates of the model ensemble). Of this amount, 369 Tg CH4 yr−1 or ∼ 65 % is attributed to direct anthropogenic sources in the fossil, agriculture, and waste and anthropogenic biomass burning (range 350–391 Tg CH4 yr−1 or 63 %–68 %). For the 2000–2009 period, the atmospheric inversions give a slightly lower total emission than for 2010–2019, by 32 Tg CH4 yr−1 (range 9–40). The 2020 emission rate is the highest of the period and reaches 608 Tg CH4 yr−1 (range 581–627), which is 12 % higher than the average emissions in the 2000s. Since 2012, global direct anthropogenic CH4 emission trends have been tracking scenarios that assume no or minimal climate mitigation policies proposed by the Intergovernmental Panel on Climate Change (shared socio-economic pathways SSP5 and SSP3). Bottom-up methods suggest 16 % (94 Tg CH4 yr−1) larger global emissions (669 Tg CH4 yr−1, range 512–849) than top-down inversion methods for the 2010–2019 period. The discrepancy between the bottom-up and the top-down budgets has been greatly reduced compared to the previous differences (167 and 156 Tg CH4 yr−1 in Saunois et al. (2016, 2020) respectively), and for the first time uncertainties in bottom-up and top-down budgets overlap. Although differences have been reduced between inversions and bottom-up, the most important source of uncertainty in the global CH4 budget is still attributable to natural emissions, especially those from wetlands and inland freshwaters.
The tropospheric loss of methane, as the main contributor to methane lifetime, has been estimated at 563 [510–663] Tg CH4 yr−1 based on chemistry–climate models. These values are slightly larger than for 2000–2009 due to the impact of the rise in atmospheric methane and remaining large uncertainty (∼ 25 %). The total sink of CH4 is estimated at 633 [507–796] Tg CH4 yr−1 by the bottom-up approaches and at 554 [550–567] Tg CH4 yr−1 by top-down approaches. However, most of the top-down models use the same OH distribution, which introduces less uncertainty to the global budget than is likely justified.
For 2010–2019, agriculture and waste contributed an estimated 228 [213–242] Tg CH4 yr−1 in the top-down budget and 211 [195–231] Tg CH4 yr−1 in the bottom-up budget. Fossil fuel emissions contributed 115 [100–124] Tg CH4 yr−1 in the top-down budget and 120 [117–125] Tg CH4 yr−1 in the bottom-up budget. Biomass and biofuel burning contributed 27 [26–27] Tg CH4 yr−1 in the top-down budget and 28 [21–39] Tg CH4 yr−1 in the bottom-up budget.
We identify five major priorities for improving the CH4 budget: (i) producing a global, high-resolution map of water-saturated soils and inundated areas emitting CH4 based on a robust classification of different types of emitting ecosystems; (ii) further development of process-based models for inland-water emissions; (iii) intensification of CH4 observations at local (e.g. FLUXNET-CH4 measurements, urban-scale monitoring, satellite imagery with pointing capabilities) to regional scales (surface networks and global remote sensing measurements from satellites) to constrain both bottom-up models and atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) integration of 3D variational inversion systems using isotopic and/or co-emitted species such as ethane as well as information in the bottom-up inventories on anthropogenic super-emitters detected by remote sensing (mainly oil and gas sector but also coal, agriculture, and landfills) to improve source partitioning.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/essd-17-1873-2025","usgsCitation":"Saunois, M., Martinez, A., Poulter, B., Zhang, Z., Raymond, P.A., Regnier, P., Canadell, J.G., Jackson, R.B., Patra, P.K., Bousquet, P., Ciais, P., Dlugokencky, E.J., Lan, X., Allen, G.H., Bastviken, D., Beerling, D.J., Belikov, D., Blake, D.R., Castaldi, S., Crippa, M., Deemer, B., Dennison, F., Etiope, G., Gedney, N., Höglund-Isaksson, L., Holgerson, M.A., Hopcroft, P.O., Hugelius, G., Ito, A., Jain, A.K., Janardanan, R., Johnson, M.S., Kleinen, T., Krummel, P.B., Lauerwald, R., Li, T., Liu, X., McDonald, K.C., Melton, J.R., Mühle, J., Müller, J., Murguia-Flores, F., Niwa, Y., Noce, S., Pan, S., Parker, R.J., Peng, C., Ramonet, M., Riley, W.J., Rocher-Ros, G., Rosentreter, J.A., Sasakawa, M., Segers, A., Smith, S.J., Stanley, E.H., Thanwerdas, J., Tian, H., Tsuruta, A., Tubiello, F.N., Weber, T.S., van der Werf, G.R., Worthy, D.E., Xi, Y., Yoshida, Y., Zhang, W., Zheng, B., Zhu, Q., Zhu, Q., and Zhuang, Q., 2025, Global methane budget 2000-2020: Earth System Science Data, v. 17, no. 5, p. 1873-1958, https://doi.org/10.5194/essd-17-1873-2025.","productDescription":"86 p.","startPage":"1873","endPage":"1958","ipdsId":"IP-163722","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":497355,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/essd-12-1561-2020","text":"Publisher Index Page"},{"id":495276,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Saunois, Marielle","contributorId":217394,"corporation":false,"usgs":false,"family":"Saunois","given":"Marielle","email":"","affiliations":[{"id":39615,"text":"Universite 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Small waterbody conservation has been supported by different stakeholders aiming at improving water quality, enhancing floodwater storage, and supporting migratory bird breeding habitat. Conservation agencies are using hydrological and biological monitoring, modeling, and mapping to adaptively manage small waterbodies in the face of stressors such as invasive species and climate change. As remote sensing estimates of small waterbody surface water extent have become easier to access, understanding the capabilities and limitations of using remote sensing, especially in areas lacking surface water monitoring, is important for conservation decision making. Here, we used in situ monitoring and process-based hydrological modeling to explore remote sensing accuracy, especially related to waterbody size, emergent aquatic vegetation cover, and climatic conditions. Overall, we found that the accuracy of satellite and aerial imagery surface water mapping approaches vastly decreased for waterbodies smaller than 2 ha. We also found emergent vegetation could be masking surface water in waterbodies larger than 2 ha and that accuracy of some remote sensing estimates may decrease during wetter climatic periods. These results indicate that sensors commonly used for surface water applications alone may not be able to accurately detect small waterbody surface water, which supports the need for combining monitoring and modeling to understand how small waterbodies may respond to future changes in climate and land use.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2025.113525","usgsCitation":"McKenna, O.P., Lothspeich, A., Vacek, S., MacDonald, D., Eash, J., Vanderhoof, M.K., McCulloch, E., Ross, C., Sabrina, S., and Knight, J., 2025, Small waterbodies of large conservation concern: Towards an integrated approach to more accurately measuring surface water dynamics: Ecological Indicators, v. 175, 113525, 13 p., https://doi.org/10.1016/j.ecolind.2025.113525.","productDescription":"113525, 13 p.","ipdsId":"IP-156979","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":488103,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2025.113525","text":"Publisher Index Page"},{"id":486573,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Nelson Lake Waterfowl Protection Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.298889,\n 45.492\n ],\n [\n -95.298889,\n 45.4889\n ],\n [\n -95.295,\n 45.4889\n ],\n [\n -95.295,\n 45.492\n ],\n [\n -95.298889,\n 45.492\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"175","noUsgsAuthors":false,"publicationDate":"2025-05-09","publicationStatus":"PW","contributors":{"authors":[{"text":"McKenna, Owen P. 0000-0002-5937-9436 omckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-5937-9436","contributorId":198598,"corporation":false,"usgs":true,"family":"McKenna","given":"Owen","email":"omckenna@usgs.gov","middleInitial":"P.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":938404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lothspeich, Audrey Claire 0000-0002-5460-6142","orcid":"https://orcid.org/0000-0002-5460-6142","contributorId":355935,"corporation":false,"usgs":true,"family":"Lothspeich","given":"Audrey Claire","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":938405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vacek, Sara","contributorId":178445,"corporation":false,"usgs":false,"family":"Vacek","given":"Sara","email":"","affiliations":[],"preferred":false,"id":938406,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"MacDonald, Dawn","contributorId":355936,"corporation":false,"usgs":false,"family":"MacDonald","given":"Dawn","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":938407,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eash, Josh D.","contributorId":267175,"corporation":false,"usgs":false,"family":"Eash","given":"Josh D.","affiliations":[{"id":55428,"text":"U.S. Fish and Wildlife Service, 5600 American Blvd. W., Bloomington, MN","active":true,"usgs":false}],"preferred":false,"id":938408,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - 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However, if there are only a few samples within each region, then the map should be smoothed in an appropriate way to mitigate the problems that arise from having only a few samples. A smoothing algorithm based on a Bayesian hierarchical model is developed and presented in this report. This algorithm has several features that make it especially suitable for mapping earth science data: it can account for measurements that are censored, it can process multiple datasets with different measurement errors and different censoring thresholds, and it can calculate the uncertainty in any statistic that is mapped. The algorithm is demonstrated by mapping gold concentrations that are measured in streambed sediments in the Taylor Mountains quadrangle in southwestern Alaska.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section C: Computer programs in Book 7: Bayesian Mapping of Regionally Grouped, Sparse, Univariate Earth Science Data","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/tm7C29","programNote":"Mineral Resources Program","usgsCitation":"Ellefsen, K.J., Wang, B., and Goldman, M.A., 2025, Bayesian mapping of regionally grouped, sparse, univariate earth science data: U.S. Geological Survey Techniques and Methods, book 7, chap. C29, 20 p., https://doi.org/10.3133/tm7C29.","productDescription":"iv, 20 p.","onlineOnly":"Y","ipdsId":"IP-148248","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":485233,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/07/c29/coverthb2.jpg"},{"id":485714,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/tm7C29/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"T and M 7C29"},{"id":485567,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/07/c29/tm7c29.xml"},{"id":485566,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/07/c29/images"},{"id":485235,"rank":3,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P14X4CKG","text":"USGS software release","linkHelpText":"Software for Bayesian mapping of regionally grouped, sparse, univariate earth science data (program BMRGSU)"},{"id":485234,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/07/c29/tm7c29.pdf","text":"Report","size":"9.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"T and M 7C29"}],"country":"United States","state":"Alaska","otherGeospatial":"Taylor Mountains quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -159,\n 61\n ],\n [\n -159,\n 60\n ],\n [\n -156,\n 60\n ],\n [\n -156,\n 61\n ],\n [\n -159,\n 61\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, Mail Stop 973
Denver, CO 80225
Emerging wildlife pathogens often display geographic variability due to landscape heterogeneity. Modeling approaches capable of learning complex, non-linear spatial dynamics of diseases are needed to rigorously assess and mitigate the effects of pathogens on wildlife health and biodiversity. We propose a novel machine learning (ML)-guided approach that leverages prior physical knowledge of ecological systems, using partial differential equations. We present our approach, taking advantage of the universal function approximation property of neural networks for flexible representation of the underlying dynamics of the geographic spread and growth of wildlife diseases. We demonstrate the benefits of our approach by comparing its forecasting power with commonly used methods and highlighting the obtained insights on disease dynamics. Additionally, we show the theoretical guarantees for the approximation error of our model. We illustrate the implementation of our ML-guided approach using data from white-nose syndrome (WNS) outbreaks in bat populations across the US. WNS is an infectious fungal disease responsible for significant declines in bat populations. Our results on WNS are useful for disease surveillance and bat conservation efforts. Our methods can be broadly used to assess the effects of environmental and anthropogenic drivers impacting wildlife health and biodiversity.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/eds.2025.3","usgsCitation":"Reyes, J., Oh, G., McGahan, I., Ma, T., Russell, R., Walsh, D.P., and Zhu, J., 2025, Learning complex spatial dynamics of wildlife diseases with machine learning-guided partial differential equations: Environmental Data Science, v. 4, e28, 23 p., https://doi.org/10.1017/eds.2025.3.","productDescription":"e28, 23 p.","ipdsId":"IP-160182","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":490167,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/eds.2025.3","text":"Publisher Index Page"},{"id":489410,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","noUsgsAuthors":false,"publicationDate":"2025-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Reyes, Juan Francisco Mandujano","contributorId":356170,"corporation":false,"usgs":false,"family":"Reyes","given":"Juan Francisco Mandujano","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":938920,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oh, Gina","contributorId":333634,"corporation":false,"usgs":false,"family":"Oh","given":"Gina","email":"","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":938921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGahan, Ian","contributorId":333637,"corporation":false,"usgs":false,"family":"McGahan","given":"Ian","email":"","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":938922,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ma, Ting Fung","contributorId":356257,"corporation":false,"usgs":false,"family":"Ma","given":"Ting Fung","affiliations":[{"id":37804,"text":"University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":938923,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Russell, Robin 0000-0001-8726-7303","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":333621,"corporation":false,"usgs":false,"family":"Russell","given":"Robin","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":938924,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Walsh, Daniel P. 0000-0002-7772-2445","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":219539,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":938925,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zhu, Jun","contributorId":356177,"corporation":false,"usgs":false,"family":"Zhu","given":"Jun","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":938926,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70266550,"text":"70266550 - 2025 - A partner-driven decision support model to inform the reintroduction of bull trout","interactions":[],"lastModifiedDate":"2025-05-09T15:23:24.336355","indexId":"70266550","displayToPublicDate":"2025-05-08T10:13:24","publicationYear":"2025","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":"A partner-driven decision support model to inform the reintroduction of bull trout","docAbstract":"Assessments of species reintroductions involve a series of complex decisions that include human perspectives and ecological contexts. Here, we present a reintroduction assessment involving bull trout (Salvelinus confluentus) using a structured decision-making process. We approached this assessment by engaging partners representing public utilities, government agencies, and Tribes with shared interests in a potential reintroduction. These individuals identified objectives, decision alternatives, and ecological scenarios that were incorporated into a co-produced simulation-based model of potential reintroduction outcomes. The model included mathematical representations of habitat availability, life history expression, and assumptions regarding constraints on potential bull trout populations. Within each recipient stream, partners chose to explore a wide range of decision alternatives and simulated scenarios affecting reintroduction success. Results suggested that 1) reintroductions using eggs or adults were most optimal, 2) adding more individuals resulted in diminishing returns, 3) access to migratory habitat could improve success, and 4) the diversity of opportunities for life history expression led to improved reintroduction opportunities. In addition, modeled scenarios indicated some recipient streams consistently produced lower abundance of reintroduced bull trout. This work contributes a novel example to a growing portfolio of reintroduction assessments that may inform future conservation for bull trout and many other species facing similar challenges.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0323427","usgsCitation":"Benjamin, J.R., Neibauer, J., Anthony, H., Vazquez, J., Rawhouser, A., and Dunham, J., 2025, A partner-driven decision support model to inform the reintroduction of bull trout: PLoS ONE, v. 20, no. 5, e0323427, 17 p., https://doi.org/10.1371/journal.pone.0323427.","productDescription":"e0323427, 17 p.","ipdsId":"IP-172949","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":490112,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0323427","text":"Publisher Index Page"},{"id":485650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Lake Chelan watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.49036241599774,\n 48.04634063295097\n ],\n [\n -120.37067822007936,\n 48.16552254778642\n ],\n [\n -120.75794320314404,\n 48.538515779248854\n ],\n [\n -120.80213597240349,\n 48.5303354671282\n ],\n [\n -121.11319724267128,\n 48.54549059352783\n ],\n [\n -121.18989609066836,\n 48.38742171862049\n ],\n [\n -121.0025710146728,\n 48.255137103181255\n ],\n [\n -120.49036241599774,\n 48.04634063295097\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"20","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Benjamin, Joseph R. 0000-0003-3733-6838 jbenjamin@usgs.gov","orcid":"https://orcid.org/0000-0003-3733-6838","contributorId":3999,"corporation":false,"usgs":true,"family":"Benjamin","given":"Joseph","email":"jbenjamin@usgs.gov","middleInitial":"R.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":936553,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neibauer, Judith","contributorId":354836,"corporation":false,"usgs":false,"family":"Neibauer","given":"Judith","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":936554,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anthony, Hugh","contributorId":354839,"corporation":false,"usgs":false,"family":"Anthony","given":"Hugh","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":936555,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vazquez, Jose","contributorId":354841,"corporation":false,"usgs":false,"family":"Vazquez","given":"Jose","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":936556,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rawhouser, Ashley","contributorId":243429,"corporation":false,"usgs":false,"family":"Rawhouser","given":"Ashley","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":936557,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dunham, Jason 0000-0002-6268-0633","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":220078,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":936558,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70266306,"text":"70266306 - 2025 - Variability in hydrologic response to wildfire between snow zones in forested headwaters","interactions":[],"lastModifiedDate":"2025-05-15T15:08:04.001368","indexId":"70266306","displayToPublicDate":"2025-05-08T10:02:28","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Variability in hydrologic response to wildfire between snow zones in forested headwaters","docAbstract":"Rising temperatures and shifting fire regimes in the western United States are pushing fires upslope into areas of deep winter snowpack, where we have little knowledge of the likely hydrologic impacts of wildfire. We quantified differences in the timing and magnitude of stormflow responses to summer rainstorms among six catchments of varying levels of burn severity and seasonal snowpack cover for years 1–3 after the 2020 Cameron Peak fire. Our objectives were to (1) examine whether responsiveness, magnitude, and timing of stormflow responses to rainfall vary between burned and unburned catchments and between snow zones, and (2) identify the factors that affect these responses. We evaluated whether differences in storm hydrograph peak flow, total flow, stage rise, and lag to peak time differed by snow zone and burn category using generalised linear models. Additional predictors in these models are the maximum 60-min rainfall intensity for each storm, the cumulative potential water deficit prior to the storm, and the year post-fire. These models showed that the high snow zone (HSZ) has higher total stormflow than the low snow zone (LSZ), likely due to the higher soil moisture content in that area. In both snow zones, the biggest driver of the magnitude of the stormflow response was MI60. Burn category did not have a clear impact on stormflow response in the HSZ, but it did impact stage rise at the severely burned catchment in the LSZ. This was the only site that had widespread overland flow post-fire. These results demonstrate that the stormflow responses to fire vary between snow zones, indicating a need to account for elevation and snow persistence in post-fire risk assessments.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70151","usgsCitation":"Miller, Q., Barnard, D.M., Sears, M., Hammond, J., and Kampf, S., 2025, Variability in hydrologic response to wildfire between snow zones in forested headwaters: Hydrological Processes, v. 39, no. 5, e70151, 16 p., https://doi.org/10.1002/hyp.70151.","productDescription":"e70151, 16 p.","ipdsId":"IP-172047","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":490124,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.70151","text":"Publisher Index Page"},{"id":485996,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106,\n 41\n ],\n [\n -106,\n 40.333\n ],\n [\n -105,\n 40.333\n ],\n [\n -105,\n 41\n ],\n [\n -106,\n 41\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"39","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Quinn","contributorId":354373,"corporation":false,"usgs":false,"family":"Miller","given":"Quinn","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":935514,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnard, David M 0000-0003-1877-3151","orcid":"https://orcid.org/0000-0003-1877-3151","contributorId":222833,"corporation":false,"usgs":false,"family":"Barnard","given":"David","email":"","middleInitial":"M","affiliations":[{"id":18168,"text":"USDA ARS","active":true,"usgs":false}],"preferred":false,"id":935515,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sears, Megan","contributorId":354374,"corporation":false,"usgs":false,"family":"Sears","given":"Megan","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":935516,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":935517,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kampf, Stephanie","contributorId":346221,"corporation":false,"usgs":false,"family":"Kampf","given":"Stephanie","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":935518,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70267309,"text":"70267309 - 2025 - Leveraging detection uncertainty to estimate Renibacterium salmoninarum infection status among multiple tissues and assays","interactions":[],"lastModifiedDate":"2025-05-20T16:55:57.977539","indexId":"70267309","displayToPublicDate":"2025-05-08T09:45:45","publicationYear":"2025","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":"Leveraging detection uncertainty to estimate Renibacterium salmoninarum infection status among multiple tissues and assays","docAbstract":"Effective disease surveillance relies on accurate pathogen testing and robust prevalence estimates. Diagnostic specificity (DSp), the probability that an uninfected animal tests negative, is high when false positives are low. Diagnostic sensitivity (DSe) is the probability an infected animal tests positive; higher DSe means fewer false negatives. However, sensitivity and false negatives are harder to estimate without a \"gold standard\", an assay that can detect between 90 - 100% of true positive infections. Occupancy estimation of infection prevalence offers one solution by allowing for imperfect detection of the pathogen. Testing potentially infected tissues multiple times allows for the use of a Bayesian multistate occupancy model to estimate the probability of pathogen infection in tissues [Formula: see text] and detection probabilities [Formula: see text] for different assays. Using [Formula: see text] and [Formula: see text] from the posterior distribution, the conditional probability of detecting the pathogen can be modeled, allowing for the calculation of DSe. Renibacterium salmoninarum is a bacterial pathogen causing bacterial kidney disease among salmonid species and was the model pathogen we used to train our model. The current testing standard for salmonids combines initial screening for antibodies using direct fluorescent antibody test (DFAT) with polymerase chain reaction (PCR) confirmation to detect R. salmoninarum. However, detection of R. salmoninarum still varies between species, tissues, and assays. Here, a multi-state occupancy model was used to estimate detection probability among individual and dual kidney/liver infections with DFAT and qPCR in fish with an unknown infection status. Both assays produced false negatives, but qPCR had fewer than DFAT and a higher DSe. Infection state was often misclassified, but multiple surveys per individual or combining tissues for testing improved DSe for both assays.
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R.","contributorId":355584,"corporation":false,"usgs":false,"family":"Fetherman","given":"Eric R.","affiliations":[{"id":39887,"text":"Colorado Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":937689,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huyvaert, Kathryn P.","contributorId":355585,"corporation":false,"usgs":false,"family":"Huyvaert","given":"Kathryn P.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":937690,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drennan, John D.","contributorId":355587,"corporation":false,"usgs":false,"family":"Drennan","given":"John D.","affiliations":[{"id":39887,"text":"Colorado Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":937691,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brock, Rebecca E.","contributorId":355589,"corporation":false,"usgs":false,"family":"Brock","given":"Rebecca E.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":937692,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yeatts, Brooke","contributorId":355591,"corporation":false,"usgs":false,"family":"Yeatts","given":"Brooke","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":937693,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Winkelman, Dana L. 0000-0002-5247-0114 danaw@usgs.gov","orcid":"https://orcid.org/0000-0002-5247-0114","contributorId":4141,"corporation":false,"usgs":true,"family":"Winkelman","given":"Dana","email":"danaw@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":937694,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70269669,"text":"70269669 - 2025 - Ultrasonic deterrents provide no additional benefit over curtailment in reducing bat fatalities at an Ohio wind energy facility","interactions":[],"lastModifiedDate":"2025-07-29T14:36:03.820212","indexId":"70269669","displayToPublicDate":"2025-05-08T09:27:14","publicationYear":"2025","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":"Ultrasonic deterrents provide no additional benefit over curtailment in reducing bat fatalities at an Ohio wind energy facility","docAbstract":"Wind energy is important for achieving net-zero greenhouse gas emissions but also contributes to global bat mortality. Current strategies to minimize bat mortality due to collision with wind-turbine blades fall broadly into two categories: curtailment (limiting turbine operation during high-risk periods) and deterrence (discouraging bat activity near turbines). Recently, there has been interest in combining these strategies to achieve greater reductions in bat fatalities than either strategy might achieve in isolation. To investigate the effectiveness of combining curtailment with ultrasonic deterrent minimization strategies, we deployed six ultrasonic deterrents at nacelle height on 16 experimental turbines at Avangrid Renewables’ Blue Creek Wind Energy Facility. We rotated between four conditions (normal operations, curtailment only, deterrent only, curtailment and deterrent) randomly assigned to four wind turbines each night between 15 June and 3 October 2017. We found that bat mortality at wind turbines was independent of wind speed. The effectiveness of ultrasonic acoustic deterrents varied between high-frequency-calling species (eastern red bats) and low-frequency-calling species (hoary bats, silver-haired bats, and big brown bats). When deterrents were active, mortality was twice as high for eastern red bats compared to the control. Conversely, deterrents had a weak dampening effect on bat mortality for low-frequency species. We found no additive effects on mortality reduction for turbines operating both curtailment and deterrents compared to either approach in isolation. Our findings suggest that ultrasonic acoustic deterrents may not be effective for both high and low frequency echolocating bats. The increase in fatalities of eastern red bats is alarming and underscores the importance of considering site- and species-specific effects of minimization solutions.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0318451","usgsCitation":"Clerc, J., Huso, M., Schirmacher, M.R., Whitby, M.D., and Hein, C.D., 2025, Ultrasonic deterrents provide no additional benefit over curtailment in reducing bat fatalities at an Ohio wind energy facility: PLoS ONE, v. 20, no. 5, e0318451, 16 p., https://doi.org/10.1371/journal.pone.0318451.","productDescription":"e0318451, 16 p.","ipdsId":"IP-169209","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":493320,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0318451","text":"Publisher Index Page"},{"id":493094,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","county":"Paulding County, Van Wert County","otherGeospatial":"Blue Creek Wind Energy Facility","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.7984601140799,\n 41.01667721426381\n ],\n [\n -84.79663300607753,\n 40.89732795018247\n ],\n [\n -84.50522800681905,\n 40.89802092865145\n ],\n [\n -84.50431462783759,\n 41.0173716521324\n ],\n [\n -84.7984601140799,\n 41.01667721426381\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"20","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Clerc, Jeffrey 0000-0002-3331-9507","orcid":"https://orcid.org/0000-0002-3331-9507","contributorId":348189,"corporation":false,"usgs":false,"family":"Clerc","given":"Jeffrey","affiliations":[{"id":33782,"text":"National Renewable Energy Laboratory","active":true,"usgs":false}],"preferred":false,"id":944346,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huso, Manuela 0000-0003-4687-6625 mhuso@usgs.gov","orcid":"https://orcid.org/0000-0003-4687-6625","contributorId":223969,"corporation":false,"usgs":true,"family":"Huso","given":"Manuela","email":"mhuso@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":944347,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schirmacher, Michael R.","contributorId":76635,"corporation":false,"usgs":false,"family":"Schirmacher","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":12591,"text":"Bat Conservation International","active":true,"usgs":false}],"preferred":false,"id":944348,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whitby, Michael D. 0000-0002-0694-3830","orcid":"https://orcid.org/0000-0002-0694-3830","contributorId":345180,"corporation":false,"usgs":false,"family":"Whitby","given":"Michael","email":"","middleInitial":"D.","affiliations":[{"id":82508,"text":"Bat Conservation International, 500 N Capital of Texas Highway, Austin, TX, 78746 USA","active":true,"usgs":false}],"preferred":false,"id":944349,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hein, Cris D.","contributorId":73910,"corporation":false,"usgs":false,"family":"Hein","given":"Cris","email":"","middleInitial":"D.","affiliations":[{"id":12591,"text":"Bat Conservation International","active":true,"usgs":false}],"preferred":false,"id":944350,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70266525,"text":"70266525 - 2025 - Marginalizing time in habitat selection and species distribution models improves inference","interactions":[],"lastModifiedDate":"2025-05-09T15:11:57.95249","indexId":"70266525","displayToPublicDate":"2025-05-08T08:01:21","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Marginalizing time in habitat selection and species distribution models improves inference","docAbstract":"Aim
Recent methodological advances for studying how animals move and use space with telemetry data have focused on fine-scale, more mechanistic inference. However, in many cases, researchers and managers remain interested in larger scale questions regarding species distribution and habitat use across study areas, landscapes, or seasonal ranges. Point processes offer a unified framework for many methods applied in studies of species distribution and resource selection; however, challenges remain in terms of dealing with temporal autocorrelation common in many types of telemetry data collected from animal locations.
Innovation
Space–time point processes (STPPs) have a unique property, in that marginalising time offers a connection between individual animal movement and broader point processes, yet this property has seen little attention in both statistical and applied research. In this paper, we first present some of the details of this marginalisation property and methods for applying marginalised STPPs (mSTTPs) to autocorrelated telemetry data and then apply a mSTTP in a case study on the summer space use and habitat selection of female caribou (Rangifer tarandus) in Denali National Park and Preserve, Alaska.
Main Conclusions
The case study demonstrated that an mSTPP approach can improve inference over other commonly used methods in terms of its ability to account for temporal autocorrelation and offers greater precision in parameter estimates and improved predictions of space use. As this method fits conveniently into the existing point process frameworks, it offers a practical solution to dealing with temporal autocorrelation inherent to many types of telemetry data when research questions center around broader scale patterns of animal habitat selection and space use.
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","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20253021","programNote":"National and Global Petroleum Assessment","usgsCitation":"Burke, L.A., Paxton, S.T., Kinney, S.A., Gianoutsos, N.J., Dubiel, R.F., Pitman, J.K., Schenk, C.J., Mercier, T.J., Le, P.A., and Leathers-Miller, H.M., 2025, Assessment of undiscovered oil and gas resources in the Lower Cretaceous Hosston and Travis Peak Formations, U.S. Gulf Coast, 2024: U.S. Geological Survey Fact Sheet 2025–3021, 4 p., https://doi.org/10.3133/fs20253021.","productDescription":"Report: 4 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-170167","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":485851,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118567.htm","linkFileType":{"id":5,"text":"html"}},{"id":485513,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3021/fs20253021.xml"},{"id":485512,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3021/images"},{"id":485342,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1JPWRAY","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project-Gulf Coast Mesozoic Province, Lower Cretaceous Travis Peak and Hosston Formations: Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables"},{"id":485561,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20253021/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2025-3021"},{"id":485340,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3021/fs20253021.pdf","text":"Report","size":"2.89 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3021"},{"id":485339,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3021/coverthb.jpg"}],"country":"United States","state":"Alabama, Arkansas, Georgia, Louisiana, Mississippi, Texas","otherGeospatial":"Gulf Coast area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -101,\n 33.75\n ],\n [\n -101,\n 25.99278122819011\n ],\n [\n -80.66288679220173,\n 25.99278122819011\n ],\n [\n -80.66288679220173,\n 33.75\n ],\n [\n -101,\n 33.75\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Wetland and permafrost soils contain some of Earth's largest reservoirs of organic carbon, and these stores are threatened by rapid warming across the Arctic. Nearly half of northern wetlands are affected by permafrost. As these ecosystems warm, the cycling of dissolved organic matter (DOM) and the opportunities for microbial degradation are changing. This is particularly evident as the relationship between wetland and permafrost DOM dynamics evolves, especially with the introduction of permafrost-derived DOM into wetland environments. Thus, understanding the interplay of DOM composition and microbial communities from wetlands and permafrost is critical to predicting the impact of released carbon on global carbon cycling. As little is understood about the interactions between wetland active layer and permafrost-derived sources as they intermingle, we conducted experimental bioincubations of mixtures of DOM and microbial communities from two fen wetland depths (shallow: 0–15 cm, and deep: 15–30 cm) and two ages of permafrost soil (Holocene and Pleistocene). We found that the source of microbial inoculum was not a significant driver of dissolved organic carbon (DOC) degradation across treatments; rather, DOM source and specifically, DOM molecular composition, controlled the rate of DOC loss over 100 days of bioincubations. DOC loss across all treatments was negatively correlated with modified aromaticity index, O/C, and the relative abundance of condensed aromatic and polyphenolic formula, and positively correlated with H/C and the relative abundance of aliphatic and peptide-like formula. Pleistocene permafrost-derived DOC exhibited ∼70% loss during the bioincubation driven by its initial molecular-level composition, highlighting its high bioavailability irrespective of microbial source.
","language":"English","publisher":"Wiley","doi":"10.1029/2024JG008445","usgsCitation":"Starr, S., Wickland, K., Kellerman, A.M., McKenna, A.M., Kurek, M., Miller, A., Karsaras, A., Douglas, T.A., Mackelprang, R., Shade, A., and Spencer, R., 2025, Organic matter composition versus microbial source: Controls on carbon loss from fen wetland and permafrost soils: JGR Biogeosciences, v. 130, no. 5, e2024JG008445, 17 p., https://doi.org/10.1029/2024JG008445.","productDescription":"e2024JG008445, 17 p.","ipdsId":"IP-162667","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":488194,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024jg008445","text":"Publisher Index Page"},{"id":485821,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Fairbanks","otherGeospatial":"Big Trail Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -147.87084295958078,\n 64.9276059180502\n ],\n [\n -147.87084295958078,\n 64.9051043539906\n ],\n [\n -147.7757330370365,\n 64.9051043539906\n ],\n [\n -147.7757330370365,\n 64.9276059180502\n ],\n [\n -147.87084295958078,\n 64.9276059180502\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"130","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Starr, Sommer F.","contributorId":355129,"corporation":false,"usgs":false,"family":"Starr","given":"Sommer F.","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":936901,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wickland, Kimberly 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University","active":true,"usgs":false}],"preferred":false,"id":936907,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Douglas, Thomas A. 0000-0003-1314-1905","orcid":"https://orcid.org/0000-0003-1314-1905","contributorId":64553,"corporation":false,"usgs":false,"family":"Douglas","given":"Thomas","email":"","middleInitial":"A.","affiliations":[{"id":33087,"text":"Cold Regions Research and Engineering Laboratory","active":true,"usgs":false}],"preferred":true,"id":936908,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mackelprang, Rachel","contributorId":200882,"corporation":false,"usgs":false,"family":"Mackelprang","given":"Rachel","email":"","affiliations":[{"id":7080,"text":"California State University, Northridge","active":true,"usgs":false}],"preferred":false,"id":936909,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Shade, Ashley L.","contributorId":355140,"corporation":false,"usgs":false,"family":"Shade","given":"Ashley 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margin-spanning megasplay fault at the Cascadia Subduction Zone","docAbstract":"It has been previously proposed that a megasplay fault within the Cascadia accretionary wedge, spanning from offshore Vancouver Island to Oregon, has the potential to slip during a future Cascadia subduction zone earthquake. This hypothetical fault has major implications for tsunami size and arrival times and is included in disaster-planning scenarios currently in use in the region. This hypothesis is evaluated in this study using CASIE21 deep-penetrating and U.S. Geological Survey high-resolution seismic reflection profiles. We map changes in wedge structural style and seismic character to identify the inner-outer wedge transition zone where a megasplay fault has been previously hypothesized to exist and evaluate evidence for active faulting within this zone. Our results indicate that there is not an active, through-going megasplay fault in Cascadia, but instead, the structure and activity of faulting at the inner-outer wedge transition zone is highly variable and segmented along strike, consistent with the segmentation of other physical and mechanical properties in Cascadia. Wedge sedimentation, plate dip, and subducting topography are proposed to play a major role in controlling megasplay fault development and evolution. Incorporating updated megasplay fault location, geometry, and activity into modeling of Cascadia earthquakes and tsunamis could help better constrain associated hazards.
","language":"English","publisher":"McGill University Libraries","doi":"10.26443/seismica.v2i4.1477","usgsCitation":"Lucas, M.C., Ledeczi, A., Tobin, H., Carbotte, S.M., Watt, J., Han, S., Boston, B., and Jiang, D., 2025, No evidence for an active margin-spanning megasplay fault at the Cascadia Subduction Zone: Seismica, v. 2, no. 4, 1477, 28 p., https://doi.org/10.26443/seismica.v2i4.1477.","productDescription":"1477, 28 p.","ipdsId":"IP-171867","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":488293,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.26443/seismica.v2i4.1477","text":"Publisher Index Page"},{"id":485645,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British Columbia, Oregon, Washington","otherGeospatial":"Cascadia subduction zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -129.8333,\n 49.5\n ],\n [\n -129.8333,\n 42\n ],\n [\n -123,\n 42\n ],\n [\n -123,\n 49.5\n ],\n [\n -129.8333,\n 49.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-05-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Lucas, Madeleine C.","contributorId":263451,"corporation":false,"usgs":false,"family":"Lucas","given":"Madeleine","email":"","middleInitial":"C.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":936468,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ledeczi, Anna M.","contributorId":354806,"corporation":false,"usgs":false,"family":"Ledeczi","given":"Anna M.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":936469,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tobin, Harold J.","contributorId":354808,"corporation":false,"usgs":false,"family":"Tobin","given":"Harold J.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":936470,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carbotte, Suzanne M.","contributorId":339692,"corporation":false,"usgs":false,"family":"Carbotte","given":"Suzanne","email":"","middleInitial":"M.","affiliations":[{"id":28041,"text":"Lamont-Doherty Earth Observatory, Columbia University","active":true,"usgs":false}],"preferred":false,"id":936471,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Watt, Janet 0000-0002-4759-3814","orcid":"https://orcid.org/0000-0002-4759-3814","contributorId":221271,"corporation":false,"usgs":true,"family":"Watt","given":"Janet","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":936472,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Han, Shuoshuo","contributorId":339693,"corporation":false,"usgs":false,"family":"Han","given":"Shuoshuo","email":"","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":936473,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Boston, Brian","contributorId":252937,"corporation":false,"usgs":false,"family":"Boston","given":"Brian","email":"","affiliations":[{"id":40272,"text":"Japan Agency for Marine-Earth Science and Technology","active":true,"usgs":false}],"preferred":false,"id":936474,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jiang, D.","contributorId":354811,"corporation":false,"usgs":false,"family":"Jiang","given":"D.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":936475,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70267968,"text":"70267968 - 2025 - Climate-driven deoxygenation of lakes alters the nutrient-toxin profile of a food fish","interactions":[],"lastModifiedDate":"2025-06-10T14:08:35.740802","indexId":"70267968","displayToPublicDate":"2025-05-07T08:59:20","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21817,"text":"Ecotoxicology and Public Health","active":true,"publicationSubtype":{"id":10}},"title":"Climate-driven deoxygenation of lakes alters the nutrient-toxin profile of a food fish","docAbstract":"Climate change is rapidly altering fisheries supporting aquatic ecosystems. The implications for food security depend not only on harvest biomass but also concentrations of nutrients and toxins in fish. Using brook trout from Adirondack lakes (New York, USA), we tested whether ongoing lake deoxygenation trends will affect fish muscle omega-3 fatty acids, selenium, and mercury concentrations. Across space (16 lakes: 1 year) and time (6 years: 1 lake), anoxia decreased selenium and was associated with elevated fish mercury, with no effect on omega-3 content. Because selenium may mitigate some end points of mercury toxicity, highly variable Se:Hg molar ratios (0.70–35.79) in neighboring lakes may have health risk implications. For fish consumers, ongoing lake deoxygenation under climate change could potentially reduce selenium intake while enhancing mercury exposure. Simultaneous alteration of beneficial compounds and toxins by environmental change complicates the development of fish consumption advisories to safeguard public health in a warming world.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.5c01032","usgsCitation":"Jane, S.F., Heilpern, S., Brenna, J., Detmer, T.M., Driscoll, C., Eagles-Smith, C., Giri, S.K., Glahn, R., Jirka, K., Kim, J., Montesdeoca, M., Olson, C.I., Park, H., Randall, E.A., and McIntyre, P.B., 2025, Climate-driven deoxygenation of lakes alters the nutrient-toxin profile of a food fish: Ecotoxicology and Public Health, v. 59, no. 19, p. 9486-9496, https://doi.org/10.1021/acs.est.5c01032.","productDescription":"11 p.","startPage":"9486","endPage":"9496","ipdsId":"IP-164745","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":490305,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Adirondack lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.7,\n 43.71\n ],\n [\n -74.98,\n 43.71\n ],\n [\n -74.98,\n 43.42\n ],\n [\n -74.7,\n 43.42\n ],\n [\n -74.7,\n 43.71\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"59","issue":"19","noUsgsAuthors":false,"publicationDate":"2025-05-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Jane, Stephen F.","contributorId":191442,"corporation":false,"usgs":false,"family":"Jane","given":"Stephen","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":939809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heilpern, Sebastian A.","contributorId":287013,"corporation":false,"usgs":false,"family":"Heilpern","given":"Sebastian A.","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":939810,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brenna, J. 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This article goes beyond the physical damage imposed by the catastrophe to discuss the effects of the earthquakes on the operations of women-owned businesses. The mixed-method study with entrepreneurs belonging to a women’s business association operating in a moderately disrupted part of the region explores their struggles and recovery expectations. Thirty-five questionnaires were analyzed to identify the reasons for business closure, challenges, and needs faced in the post-disaster period and their recovery strategies. In addition, 23 entrepreneurs participated in roundtable discussions to provide a broader context to their responses to survey topics as well as lessons learned. Across both the survey and roundtables, while many respondents reported minor physical damage to their building, they also experienced financial and personal challenges from disruption to equipment, infrastructure, services, supply chains, institutional decisions, employee well-being, and customer base. Many used their business resources and personal savings to assist employees and others in the community. The women entrepreneurs often felt their recovery needs were ignored by government and private relief organizations and encountered barriers to receiving assistance from public and private institutions. Organizing together as women in business, even informally, provided mutual support during the crisis and recovery periods and catalyzed their role in support of their communities. The results illuminate functional community recovery as a balance of recovery of built infrastructure functionality and recovery of the broader social and economic fabric of the community.
","language":"English","publisher":"Sage","doi":"10.1177/87552930251330921","usgsCitation":"Orhan, E., Wein, A., Kroll, C., and Fung, J., 2025, Lessons in business recovery following the 2023 Kahramanmaraş earthquake sequence, Türkiye informed by women entrepreneurs: Earthquake Spectra, v. 41, no. 3, p. 1910-1940, https://doi.org/10.1177/87552930251330921.","productDescription":"31 p.","startPage":"1910","endPage":"1940","ipdsId":"IP-166964","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":494904,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Turkey","otherGeospatial":"southern Turkey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 34.331004781765444,\n 37.920957650366006\n ],\n [\n 34.331004781765444,\n 36.747538006336825\n ],\n [\n 40.125738345242354,\n 36.747538006336825\n ],\n [\n 40.125738345242354,\n 37.920957650366006\n ],\n [\n 34.331004781765444,\n 37.920957650366006\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"41","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-05-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Orhan, Ezgi","contributorId":360575,"corporation":false,"usgs":false,"family":"Orhan","given":"Ezgi","affiliations":[{"id":86042,"text":"Cankaya University, Turkiye","active":true,"usgs":false}],"preferred":false,"id":947222,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wein, Anne 0000-0002-5516-3697 awein@usgs.gov","orcid":"https://orcid.org/0000-0002-5516-3697","contributorId":589,"corporation":false,"usgs":true,"family":"Wein","given":"Anne","email":"awein@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":947223,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kroll, Cynthia","contributorId":360576,"corporation":false,"usgs":false,"family":"Kroll","given":"Cynthia","affiliations":[{"id":66280,"text":"Cynthia Kroll Consulting","active":true,"usgs":false}],"preferred":false,"id":947224,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fung, Juan","contributorId":360577,"corporation":false,"usgs":false,"family":"Fung","given":"Juan","affiliations":[{"id":25356,"text":"National Institute of Standards and Technology","active":true,"usgs":false}],"preferred":false,"id":947225,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70267683,"text":"70267683 - 2025 - Interpreting a sudden population decline in a long-lived species (Malaclemys terrapin rhizophorarum)","interactions":[],"lastModifiedDate":"2025-05-29T15:03:15.907361","indexId":"70267683","displayToPublicDate":"2025-05-07T07:57:28","publicationYear":"2025","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":"Interpreting a sudden population decline in a long-lived species (Malaclemys terrapin rhizophorarum)","docAbstract":"Long-term ecological studies are critical for providing insight into population dynamics and detecting population declines, particularly for species of conservation concern. However, spatiotemporal variation and logistical challenges make the identification of sudden population declines difficult. We conducted an in-water capture-mark-recapture study of mangrove diamond-backed terrapins (Malaclemys terrapin rhizophorarum) within Big Sable Creek, in Everglades National Park, Florida. We used an 18-year dataset (2001 to 2019) incorporating year, sex, hurricane occurrence, and sampling effort to estimate survival using Cormack–Jolly–Seber (CJS) models in Program Mark. Annual survivorship estimates were high from 2001 to 2003 for both sexes (91%–96%) and variable from 2006 to 2014 (77%–92%). Beginning in 2015, survival estimates exhibited a steeper decline (females: 65%, males 75%), and dropped to below 36% by 2018. Because the driver of this apparent population decline is unknown, we created a population projection matrix and used model-estimated annual survival to simulate annual terrapin population size. We then generated competing scenarios of low survival at various age classes to attempt to reproduce a simulated decline mirroring what we observed from our capture data. A scenario of low adult survival (75%–85%) from 2012 to 2018, possibly in conjunction with no reproduction after 2010, provides estimates of abundance that appear to match simulated annual population size and may indicate that adult emigration/human removal or a drastic drop in recruitment could be responsible for the apparent decline in survival. We explore reasons for this apparent decline and highlight difficulties common to long-term studies that may influence how declines are interpreted.
","language":"English","publisher":"British Ecological Society","doi":"10.1002/ece3.71347","usgsCitation":"Guzy, J.C., Smith, B., Denton, M., Cherkiss, M., Roche, D., Crowder, A., and Hart, K., 2025, Interpreting a sudden population decline in a long-lived species (Malaclemys terrapin rhizophorarum): Ecology and Evolution, v. 15, no. 5, e71347, 16 p., https://doi.org/10.1002/ece3.71347.","productDescription":"e71347, 16 p.","ipdsId":"IP-168394","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":488447,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.71347","text":"Publisher Index Page"},{"id":486731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Cape Sable, Everglades National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.29674951955056,\n 25.648529217591914\n ],\n [\n -81.29674951955056,\n 25.09922085696259\n ],\n [\n -80.79518175403075,\n 25.09922085696259\n ],\n [\n -80.79518175403075,\n 25.648529217591914\n ],\n [\n -81.29674951955056,\n 25.648529217591914\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Guzy, Jacquelyn C. 0000-0003-2648-398X","orcid":"https://orcid.org/0000-0003-2648-398X","contributorId":288520,"corporation":false,"usgs":true,"family":"Guzy","given":"Jacquelyn","email":"","middleInitial":"C.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":938536,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Brian J. 0000-0002-0531-0492","orcid":"https://orcid.org/0000-0002-0531-0492","contributorId":139672,"corporation":false,"usgs":false,"family":"Smith","given":"Brian J.","affiliations":[{"id":12876,"text":"Cherokee Nation Technology Solutions","active":true,"usgs":false}],"preferred":false,"id":938537,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Denton, Mathew 0000-0002-1024-3722","orcid":"https://orcid.org/0000-0002-1024-3722","contributorId":210504,"corporation":false,"usgs":true,"family":"Denton","given":"Mathew","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":938538,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cherkiss, Michael 0000-0002-7802-6791","orcid":"https://orcid.org/0000-0002-7802-6791","contributorId":218466,"corporation":false,"usgs":true,"family":"Cherkiss","given":"Michael","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":938539,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roche, David 0000-0002-3329-2746 droche@usgs.gov","orcid":"https://orcid.org/0000-0002-3329-2746","contributorId":204332,"corporation":false,"usgs":true,"family":"Roche","given":"David","email":"droche@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":13165,"text":"Nova Southeastern University","active":true,"usgs":false}],"preferred":true,"id":938540,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crowder, Andrew G.","contributorId":355985,"corporation":false,"usgs":false,"family":"Crowder","given":"Andrew G.","affiliations":[{"id":84891,"text":"Xylem Analytics","active":true,"usgs":false}],"preferred":false,"id":938541,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":218324,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":938542,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70266883,"text":"70266883 - 2025 - Long-term patterns in growth of White Sturgeon in the Sacramento-San Joaquin River basin, California.","interactions":[],"lastModifiedDate":"2025-05-15T13:11:35.40062","indexId":"70266883","displayToPublicDate":"2025-05-06T09:26:29","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18328,"text":"Frontiers in Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Long-term patterns in growth of White Sturgeon in the Sacramento-San Joaquin River basin, California.","docAbstract":"Introduction: The Sacramento-San Joaquin River system (SSJ) of California includes both riverine, delta, and estuarine habitats and is among the most modified aquatic ecosystems in the United States. Water development projects in the system are associated with declines of many native species, including White Sturgeon Acipenser transmontanus.
Methods: We used White Sturgeon pectoral fin rays collected from 1983 to 2016 throughout the SSJ to assess long-term changes in growth and associations with thermal and hydrological conditions (i.e., temperature, discharge, salinity). Age and growth were estimated from 1,897 White Sturgeon varying in fork length from 25 to 210 cm and from age 0 to 33.
Results: Age structure varied through time with the oldest fish generally sampled during the mid-1980s. Growth of White Sturgeon in 1951–1970 was slower than growth of fish in 1971–1990 and 1991–2012. Growth of White Sturgeon during 1991–2012 was ~10% higher than during other time periods.
Discussion: Little variation in growth was explained by environmental covariates, suggesting that annual growth was likely influenced by factors not measured in our study. Alternatively, population structure and movement behavior of White Sturgeon in the SSJ may be such that the scale (i.e., spatial or temporal) of available habitat covariates was mismatched to the scale at which growth of White Sturgeon responds. Increased growth in recent times may be partly due to density-dependent processes in association with substantial declines in White Sturgeon population abundance over the last several decades. This research provides important information on long-term patterns in growth that contributes to the conservation and management of White Sturgeon in the SSJ and beyond.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/ffwsc.2025.1577065","usgsCitation":"Quist, M.C., Blackburn, S., Ulaski, M., and Jackson, Z., 2025, Long-term patterns in growth of White Sturgeon in the Sacramento-San Joaquin River basin, California.: Frontiers in Freshwater Science, v. 3, 1577065, 10 p., https://doi.org/10.3389/ffwsc.2025.1577065.","productDescription":"1577065, 10 p.","ipdsId":"IP-175717","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":488907,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/ffwsc.2025.1577065","text":"Publisher Index Page"},{"id":485931,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.79850686101548,\n 38.755876798924476\n ],\n [\n -122.64621142922209,\n 38.755876798924476\n ],\n [\n -122.64621142922209,\n 37.31156292678925\n ],\n [\n -120.79850686101548,\n 37.31156292678925\n ],\n [\n -120.79850686101548,\n 38.755876798924476\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"3","noUsgsAuthors":false,"publicationDate":"2025-05-07","publicationStatus":"PW","contributors":{"authors":[{"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":937030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blackburn, Shannon","contributorId":338596,"corporation":false,"usgs":false,"family":"Blackburn","given":"Shannon","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":937031,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ulaski, Marta","contributorId":280108,"corporation":false,"usgs":false,"family":"Ulaski","given":"Marta","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":937032,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, Zachary","contributorId":338597,"corporation":false,"usgs":false,"family":"Jackson","given":"Zachary","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":937033,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70275112,"text":"70275112 - 2025 - Development of a two-stage life cycle model to inform the Trap and Haul Program for Coho salmon in the Lewis River, Washington","interactions":[{"subject":{"id":70275112,"text":"70275112 - 2025 - Development of a two-stage life cycle model to inform the Trap and Haul Program for Coho salmon in the Lewis River, Washington","indexId":"70275112","publicationYear":"2025","noYear":false,"title":"Development of a two-stage life cycle model to inform the Trap and Haul Program for Coho salmon in the Lewis River, Washington"},"predicate":"SUPERSEDED_BY","object":{"id":70275077,"text":"ofr20261004 - 2026 - Development of a two-stage lifecycle model to inform the trap-and-haul program for Oncorhynchus kisutch (coho salmon) in the Lewis River, Washington","indexId":"ofr20261004","publicationYear":"2026","noYear":false,"title":"Development of a two-stage lifecycle model to inform the trap-and-haul program for Oncorhynchus kisutch (coho salmon) in the Lewis River, Washington"},"id":1}],"supersededBy":{"id":70275077,"text":"ofr20261004 - 2026 - Development of a two-stage lifecycle model to inform the trap-and-haul program for Oncorhynchus kisutch (coho salmon) in the Lewis River, Washington","indexId":"ofr20261004","publicationYear":"2026","noYear":false,"title":"Development of a two-stage lifecycle model to inform the trap-and-haul program for Oncorhynchus kisutch (coho salmon) in the Lewis River, Washington"},"lastModifiedDate":"2026-04-22T18:50:14.222897","indexId":"70275112","displayToPublicDate":"2025-05-06T09:17:38","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19846,"text":"BioRxiv","active":true,"publicationSubtype":{"id":32}},"title":"Development of a two-stage life cycle model to inform the Trap and Haul Program for Coho salmon in the Lewis River, Washington","docAbstract":"Restoration of salmon populations in the upper Lewis River Basin depends on a trap-and-haul program owing to the Lewis River Hydroelectric Project (Project) operated by PacifiCorp and Cowlitz PUD (Utilities), which has been a barrier to salmon passage since the 1930s. Thus, sustaining the Coho salmon (Oncorhynchus kisutch) population upstream of the Project currently depends on two fundamental factors: (1) the collection of upstream migrating adult Coho salmon at Merwin Dam, the lower most dam within the Project, and transporting them by truck to spawn above Swift Dam, the upper most dam within the Project; and (2) the collection of out-migrating juvenile Coho salmon at the downstream collection facility at Swift Dam for transport and release below the Project. The reintroduction program began once the downstream collection facility at Swift Dam was commissioned in late-2012 with the first year of transport data being collected in 2013. Over the past decade, the Utilities have been collecting data on juvenile outmigrants and adult fish returns at the dams. The need to construct a life cycle model for Lewis River anadromous fish was identified by the Lewis River Aquatic Technical Subgroup, with the understanding that many years (>15) of data collection are needed to adequately measure the life cycle production of coho salmon. Use of past data to construct models could help inform future data collection and provide a framework that can be updated annually to measure trap and haul program performance within a life cycle context (Note: Data are not currently available from PacifiCorp. Contact organization Chris Karchesky for further information).
Because Coho salmon can live as long as five years, estimating demographic parameters for Coho salmon populations over their life cycle requires at least 10 or more years of data collection. Over the past decade, PacifiCorp has been collecting data on fish collection efficiency and the numbers of adult and juvenile salmon transported around the Lewis River dams, providing sufficient data to formulate a life cycle model that can guide future data collection efforts and provide preliminary information to resource managers The goal of the statistical life cycle model was to estimate annual production and survival during two critical life-stage transitions (1) the freshwater production from escapement of adults released upstream of Swift Dam, and the collection of downstream migrating juveniles at the passage facility at Swift Dam, and (2) the smolt-to-adult survival from the time of collection at Swift Dam to their return as adults. We used the Beverton-Holt stock-recruitment model to estimate juvenile production from the number of spawners. This approach allowed us to test for density dependence at current spawner abundances while estimating annual productivity, defined as the number of juveniles produced per spawner at low spawner abundance. Productivity was then expressed as a function of the number of juveniles collected and transported downstream of the Project. Because juvenile Fish Collection Efficiency (FCE) directly affects the number of juveniles that survive to continue downstream migration, FCE is a primary determinant of fish production. Consequently, the modeling framework is well suited to evaluate the performance of trap and haul programs within a life cycle context.
The objectives of this study were to: (1) gather and collate available data on adult and juvenile Coho salmon at Merwin and Swift dams, (2) quantify adult escapement, juvenile abundance, and the age at outmigration and adult return, (3) describe, formulate, and fit the integrated population model (IPM) to the data, and (4) summarize our findings, identify data gaps, and identify potential opportunities for future studies that could provide information used to improve model estimation and inference. Our key findings were: (1) over and above the number of spawning females, FCE was the primary factor affecting productivity of Coho salmon above Swift Dam, (2) smolt-to-adult return (SAR) rates were relatively high considering that harvest was included in the estimate, averaging about 4.5% and ranging as high as 12.9%, and (3) juvenile capacity upriver of Swift Dam was difficult to estimate due to the limited range in spawning females over the time series of data, suggesting the model may be improved by collecting data at higher spawner abundances. In addition, by including FCE in the model, we estimated that the median pre-collection productivity, defined as the number of juveniles produced per spawner when FCE = 1, was 64 juveniles per spawner. Because this two-stage life cycle model partitions factors that affect fish production in river versus the ocean, the model estimates should help inform fishery managers about the overall role that fish collection at Swift Dam plays in the recovery and sustainability of Lewis River Coho salmon. By providing the model with (1) more years of data, (2) higher numbers of spawning females, and (3) data on age at juvenile migration in relation to age at adult return greater certainty in the estimates of capacity and SAR can be attained. Ultimately, information provided by the model can assist in the evaluation and continued improvement of the current trap and haul program to support anadromous fishes in the Lewis River Basin.
","language":"English","publisher":"BioRxiv","doi":"10.1101/2025.04.30.651546","usgsCitation":"Plumb, J., and Perry, R.W., 2025, Development of a two-stage life cycle model to inform the Trap and Haul Program for Coho salmon in the Lewis River, Washington: BioRxiv, https://doi.org/10.1101/2025.04.30.651546.","productDescription":"34 p.","ipdsId":"IP-178609","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":502905,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":502978,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/2025.04.30.651546","text":"External Repository"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Plumb, John 0000-0003-4255-1612","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":223236,"corporation":false,"usgs":true,"family":"Plumb","given":"John","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":959472,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":959473,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70266492,"text":"70266492 - 2025 - Using long-term ecological datasets to unravel the impacts of short-term meteorological disturbances on phytoplankton communities","interactions":[],"lastModifiedDate":"2025-05-08T14:12:51.567682","indexId":"70266492","displayToPublicDate":"2025-05-06T09:07:04","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Using long-term ecological datasets to unravel the impacts of short-term meteorological disturbances on phytoplankton communities","docAbstract":"Extreme meteorological events such as storms are increasing in frequency and intensity, but our knowledge of their impacts on aquatic ecosystems and emergent system properties is limited. Understanding the ecological impacts of storms on the dynamics of primary producers remains a challenge that needs to be addressed to assess the vulnerability of freshwater ecosystems to extreme weather conditions and climate change.
One promising approach to gain insights into storm impacts on phytoplankton community dynamics is to analyse long-term monitoring datasets. However, such an approach requires disentangling the impacts of short-term meteorological disturbances from the effects of the seasonal trajectories of meteorological conditions. To this end, we applied boosted regression tree models to phytoplankton time series from eight relatively large lakes on four continents, coupled with a procedure adapted to detect and quantify rare events.
Overall, the patterns and potential drivers we identified provide important insights into the responses of lakes to short-term meteorological events and highlight differences in the response of phytoplankton communities according to lake morphological characteristics. Our results indicated that deepened thermoclines and lake-specific combinations of drivers describing altered thermal structures caused deviations from the typical trajectories of seasonal phytoplankton succession. For shallow polymictic lakes, shifts in phytoplankton succession also depended on changes in light availability.
Overall, our study highlights the value of long-term monitoring to improve our understanding of phytoplankton sensitivity to short-term meteorological disturbances.
Warming rivers and interactions with non-native species impact salmonid species globally. Understanding how hydroclimatic conditions synergistically and independently interact with non-native species is critical for effectively managing salmonids into the future. We used a 10-year mark–recapture dataset to assess how native Yellowstone cutthroat trout (YCT) Oncorhynchus virginalis bouvieri and non-native brown trout Salmo trutta growth rates and apparent survival were affected by hydroclimatic conditions and (for YCT) the presence of brown trout in a tributary. Growth (YCT) and survival (both species across size classes) were negatively related to warming stream temperatures. Brown trout growth was positively related to increasing daily streamflow variability (a proxy for streamflow), but this variable was not included in the top YCT growth model. Density-dependent effects appeared to be non-existent (growth) or weakly positive (survival). When sympatric with brown trout, YCT displayed worse survival than allopatric YCT across environmental conditions. Broadly, we found native and non-native trout respond to different hydroclimatic conditions that shift with changing climatic conditions, and brown trout represent an additional threat to YCT survival.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2024-0211","usgsCitation":"Heinle, K., Al-Chokhachy, R., Sepulveda, A., and Verhille, C.E., 2025, Native Yellowstone cutthroat trout Oncorhynchus virginalis bouvieri growth and survival in a headwater stream primarily driven by warming stream temperatures, with non-native brown trout Salmo trutta posing an additional threat to survival: Canadian Journal of Fisheries and Aquatic Sciences, v. 82, p. 1-17, https://doi.org/10.1139/cjfas-2024-0211.","productDescription":"17 p.","startPage":"1","endPage":"17","ipdsId":"IP-168237","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":490403,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1WUVM5S","text":"USGS data release","linkHelpText":"Trout mark-recapture and stream temperature and streamflow data from Duck Creek, Montana"},{"id":486636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"East Fork Duck Creek, Henry Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.38754194568855,\n 45.95593917254632\n ],\n [\n -110.38754194568855,\n 45.80046830120395\n ],\n [\n -110.17467211725662,\n 45.80046830120395\n ],\n [\n -110.17467211725662,\n 45.95593917254632\n ],\n [\n -110.38754194568855,\n 45.95593917254632\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2025-04-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Heinle, Kadie B.","contributorId":355955,"corporation":false,"usgs":false,"family":"Heinle","given":"Kadie B.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":938444,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Al-Chokhachy, Robert 0000-0002-2136-5098","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":222450,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":938445,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sepulveda, Adam 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":4187,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":938446,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Verhille, Christine E.","contributorId":174642,"corporation":false,"usgs":false,"family":"Verhille","given":"Christine","email":"","middleInitial":"E.","affiliations":[{"id":13461,"text":"U.C. Davis","active":true,"usgs":false}],"preferred":false,"id":938447,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70266755,"text":"70266755 - 2025 - Horizontal transport of Picture Gorge Basalt magma through the Monument Dike Swarm determined by magnetic fabric","interactions":[],"lastModifiedDate":"2025-05-28T14:59:01.115416","indexId":"70266755","displayToPublicDate":"2025-05-06T08:52:35","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Horizontal transport of Picture Gorge Basalt magma through the Monument Dike Swarm determined by magnetic fabric","docAbstract":"Flood basalts of the mid-Miocene Columbia River Basalt Group (CRBG) cover 210,000 km2 of Washington, Oregon, and Idaho. The source of CRBG melt is debated; widely spaced feeder dike swarms can be projected toward hypothetical sources near the Oregon-Idaho border. In this study, we use anisotropy of magnetic susceptibility (AMS) to track magma flow in the Monument dike swarm (MDS), the feeder dikes of the Picture Gorge Basalt (PGB). This small formation of the main-phase CRBG eruptions allows us to explore in detail the localized dynamics of a large igneous province feeder system, with implications for the larger CRBG picture. We measured the magnetic fabric of 205 oriented paleomagnetic specimens subsampled from 97 samples collected from 15 dikes of the MDS. Thermal demagnetization and hysteresis loops show that the magnetic minerals are a mixture of single domain and multidomain sized titanomagnetites. At three dikes, the paleodepth of sampling was determined to be shallow (<350 m). Magma flowing through dikes has been shown—in most cases— to acquire an anisotropic magnetic fabric with an AMS ellipsoid minimum axis perpendicular to the wall and maximum axis aligned in the direction of flow. Of 15 dikes, 12 show horizontal flow directions in the plane of the dike. Only one dike displayed imbricated fabrics, showing westward flow away from the Oregon-Idaho border. We conclude that magma flow in the MDS was sub-horizontal from a distal source.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024GC012078","usgsCitation":"Avery, M.S., and Pivarunas, A.F., 2025, Horizontal transport of Picture Gorge Basalt magma through the Monument Dike Swarm determined by magnetic fabric: Geochemistry, Geophysics, Geosystems, v. 26, no. 5, e2024GC012078, 15p., https://doi.org/10.1029/2024GC012078.","productDescription":"e2024GC012078, 15p.","ipdsId":"IP-171767","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":490122,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024gc012078","text":"Publisher Index Page"},{"id":485707,"rank":1,"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 -120.25,\n 45\n ],\n [\n -120.25,\n 44\n ],\n [\n -118.5,\n 44\n ],\n [\n -118.5,\n 45\n ],\n [\n -120.25,\n 45\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"26","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Avery, Margaret Susan 0000-0002-8504-7072","orcid":"https://orcid.org/0000-0002-8504-7072","contributorId":329991,"corporation":false,"usgs":true,"family":"Avery","given":"Margaret","email":"","middleInitial":"Susan","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":936691,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pivarunas, Anthony Francis 0000-0002-0003-2059","orcid":"https://orcid.org/0000-0002-0003-2059","contributorId":301014,"corporation":false,"usgs":true,"family":"Pivarunas","given":"Anthony","email":"","middleInitial":"Francis","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":936692,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70268784,"text":"70268784 - 2025 - Factors influencing landslide occurrence in low-relief formerly glaciated landscapes: Landslide inventory and susceptibility analysis in Minnesota, USA","interactions":[],"lastModifiedDate":"2025-07-08T15:50:15.049077","indexId":"70268784","displayToPublicDate":"2025-05-06T08:46:13","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"Factors influencing landslide occurrence in low-relief formerly glaciated landscapes: Landslide inventory and susceptibility analysis in Minnesota, USA","docAbstract":"In landscapes recently impacted by continental glaciation, landslides may occur where topographic relief has been generated by the drainage of glacial lakes and ensuing post-glacial fluvial network development into unconsolidated glacially derived sediments and exhumed bedrock. To investigate linkages among environmental variables, post-glacial landscape development, and landslides, we created a landslide inventory of nearly 10,000 landslides in five regions of the formerly glaciated low-relief state of Minnesota, USA. Multivariate logistic regression indicates the importance of slope angle, lithology, and the development of stream valleys to landslide distribution. Areas underlain by fine-grained glaciolacustrine and nearshore deposits that are incised by streams are particularly prone to shallow (<1-2 m depth) landslides. Landslides also occur in a wide range of glacial and fluvial deposits, and as rockfall in layered Paleozoic sedimentary rocks in central and southern Minnesota and Precambrian igneous and sedimentary rocks in northeastern Minnesota. Although no more than 1-2% of the studied regions are susceptible to landslides, they can pose risk to life and safety, damage infrastructure, and impact water quality. The combination of recently generated low-relief steep slopes, extensive unconsolidated sediments, and layered sedimentary bedrock make this formerly glaciated landscape more susceptible to landslides than current national-scale models indicate.","language":"English","publisher":"Springer Nature","doi":"10.1007/s11069-025-07262-8","usgsCitation":"Triplett, L., Hammer, M.N., DeLong, S.B., Gran, K.B., Jennings, C.E., Engle, Z.T., Bartley, J., Blumentritt, D., Breckenridge, A., Day, S., Kohout, M., Larson, P., McDermott, J., and Richard, E., 2025, Factors influencing landslide occurrence in low-relief formerly glaciated landscapes: Landslide inventory and susceptibility analysis in Minnesota, USA: Natural Hazards, v. 121, p. 11799-11827, https://doi.org/10.1007/s11069-025-07262-8.","productDescription":"29 p.","startPage":"11799","endPage":"11827","ipdsId":"IP-176536","costCenters":[{"id":237,"text":"Earthquake Science 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sdelong@usgs.gov","orcid":"https://orcid.org/0000-0002-0945-2172","contributorId":5240,"corporation":false,"usgs":true,"family":"DeLong","given":"Stephen","email":"sdelong@usgs.gov","middleInitial":"B.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":941944,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gran, Karen B.","contributorId":288093,"corporation":false,"usgs":false,"family":"Gran","given":"Karen","email":"","middleInitial":"B.","affiliations":[{"id":6915,"text":"University of Minnesota - Duluth","active":true,"usgs":false}],"preferred":true,"id":941945,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jennings, Carrie E.","contributorId":288092,"corporation":false,"usgs":false,"family":"Jennings","given":"Carrie","email":"","middleInitial":"E.","affiliations":[],"preferred":true,"id":941946,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Engle, Zachary T. 0000-0002-6412-7727","orcid":"https://orcid.org/0000-0002-6412-7727","contributorId":300814,"corporation":false,"usgs":true,"family":"Engle","given":"Zachary","email":"","middleInitial":"T.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":941947,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bartley, Julie K.","contributorId":353117,"corporation":false,"usgs":false,"family":"Bartley","given":"Julie K.","affiliations":[{"id":84345,"text":"Gustavus Adolphus College","active":true,"usgs":false}],"preferred":false,"id":941948,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Blumentritt, Dylan J.","contributorId":353118,"corporation":false,"usgs":false,"family":"Blumentritt","given":"Dylan J.","affiliations":[{"id":61757,"text":"Winona State University","active":true,"usgs":false}],"preferred":false,"id":941949,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Breckenridge, Andy","contributorId":357609,"corporation":false,"usgs":false,"family":"Breckenridge","given":"Andy","affiliations":[{"id":33516,"text":"University of Wisconsin-Superior","active":true,"usgs":false}],"preferred":false,"id":941950,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Day, Stephanie","contributorId":353120,"corporation":false,"usgs":false,"family":"Day","given":"Stephanie","affiliations":[{"id":12471,"text":"North Dakota State University","active":true,"usgs":false}],"preferred":false,"id":941951,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kohout, Melissa A.","contributorId":353121,"corporation":false,"usgs":false,"family":"Kohout","given":"Melissa A.","affiliations":[{"id":84347,"text":"Mankato State University","active":true,"usgs":false}],"preferred":false,"id":941952,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Larson, Philip H.","contributorId":353122,"corporation":false,"usgs":false,"family":"Larson","given":"Philip H.","affiliations":[{"id":84348,"text":"Minnesota State University Mankato","active":true,"usgs":false}],"preferred":false,"id":941953,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"McDermott, Jeni A.","contributorId":353123,"corporation":false,"usgs":false,"family":"McDermott","given":"Jeni A.","affiliations":[{"id":6748,"text":"University of St. Thomas","active":true,"usgs":false}],"preferred":false,"id":941954,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Richard, Emilie","contributorId":300815,"corporation":false,"usgs":false,"family":"Richard","given":"Emilie","email":"","affiliations":[{"id":18006,"text":"University of Minnesota Duluth","active":true,"usgs":false}],"preferred":false,"id":941955,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70267313,"text":"70267313 - 2025 - Modeling lamprey distribution using flow, geomorphology, and elevation in a terminal lake system","interactions":[],"lastModifiedDate":"2025-06-16T14:01:42.236379","indexId":"70267313","displayToPublicDate":"2025-05-06T08:31:51","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Modeling lamprey distribution using flow, geomorphology, and elevation in a terminal lake system","docAbstract":"Objective
Lampreys are an ecologically important group of fishes. Several species are imperiled and lack key distribution and habitat data. The terminal Goose Lake Basin, U.S.A. is home to two such species, the Goose Lake Lamprey, Entosphenus sp. (formally undescribed), and the Pit-Klamath Brook Lamprey, E. lethophagus. Species distribution models (SDMs) are useful for identifying key habitats; however, SDMs are subject to accuracy impairments caused by scale mismatches and spatial autocorrelation—both exacerbated by the hierarchical structure of dendritic stream networks. Our goal was to relate lamprey presence–absence to ecological drivers and predict the distribution of lampreys across the Goose Lake Basin.
Methods
Using a dataset pooling approach, we integrated count and presence–absence data from five surveys and relevant habitat variables from publicly available, geospatial datasets to build logistic regression models. To account for potential mismatches of scale, we compared three sample grains for slope and sinuosity (i.e., stream segment lengths: 250, 500, and 1,000 m), and two scales of elevation (site and watershed). We accounted for spatial autocorrelation by incorporating network-based and Euclidean spatial dependencies using a spatial stream network (SSN) modeling approach. Using the best-fit spatial and non-spatial models, we predicted basin-wide lamprey distribution.
Result
Flow, sinuosity at our largest sample grain (1,000 m), and watershed-scale elevation were positively associated with lamprey presence, whereas slope was negatively associated. The non-spatial model predicted lamprey presence among sinuous, low-gradient streams, whereas the spatial model, which identified Euclidean and flow-connected spatial relationships, predicted contiguous patches with a high probability of occurrence near areas with previously observed presences.
Conclusions
Our study revealed ecological relationships and produced an accurate basinwide SDM. Prediction and inference improved after accounting for spatial relationships across multiple scales. Developing accurate and efficient modeling strategies that incorporate the hierarchical structure inherent to stream ecosystems aids in the management and conservation of native fishes such as lampreys.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/tafafs/vnaf017","usgsCitation":"Dickey, J., Clemens, B.J., Dumelle, M., and Davis, M.J., 2025, Modeling lamprey distribution using flow, geomorphology, and elevation in a terminal lake system: Transactions of the American Fisheries Society, v. 154, no. 3, p. 322-338, https://doi.org/10.1093/tafafs/vnaf017.","productDescription":"17 p.","startPage":"322","endPage":"338","ipdsId":"IP-170580","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":504380,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12180746/","text":"External Repository"},{"id":486248,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"154","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-05-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Dickey, Jacob C.","contributorId":350824,"corporation":false,"usgs":false,"family":"Dickey","given":"Jacob C.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":937699,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clemens, Benjamin J.","contributorId":195098,"corporation":false,"usgs":false,"family":"Clemens","given":"Benjamin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":937700,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dumelle, Michael 0000-0002-3393-5529","orcid":"https://orcid.org/0000-0002-3393-5529","contributorId":355601,"corporation":false,"usgs":false,"family":"Dumelle","given":"Michael","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":937701,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Melanie J. 0000-0003-1734-7177","orcid":"https://orcid.org/0000-0003-1734-7177","contributorId":202773,"corporation":false,"usgs":true,"family":"Davis","given":"Melanie","email":"","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":937702,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70266474,"text":"70266474 - 2025 - Failure to meet the exchangeability assumption in Bayesian multispecies occupancy models: Implications for study design","interactions":[{"subject":{"id":70266474,"text":"70266474 - 2025 - Failure to meet the exchangeability assumption in Bayesian multispecies occupancy models: Implications for study design","indexId":"70266474","publicationYear":"2025","noYear":false,"title":"Failure to meet the exchangeability assumption in Bayesian multispecies occupancy models: Implications for study design"},"predicate":"SUPERSEDED_BY","object":{"id":70272628,"text":"70272628 - 2025 - When do single-species occupancy models outperform multispecies models?","indexId":"70272628","publicationYear":"2025","noYear":false,"title":"When do single-species occupancy models outperform multispecies models?"},"id":1}],"supersededBy":{"id":70272628,"text":"70272628 - 2025 - When do single-species occupancy models outperform multispecies models?","indexId":"70272628","publicationYear":"2025","noYear":false,"title":"When do single-species occupancy models outperform multispecies models?"},"lastModifiedDate":"2025-11-26T14:27:45.5494","indexId":"70266474","displayToPublicDate":"2025-05-06T08:30:40","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19846,"text":"BioRxiv","active":true,"publicationSubtype":{"id":32}},"title":"Failure to meet the exchangeability assumption in Bayesian multispecies occupancy models: Implications for study design","docAbstract":"Bayesian hierarchical models are ubiquitous in ecology. Random effect model structures are often employed that treat individual effects as deviations from larger population-level effects. In this way individuals are assumed to be \"exchangeable\" samples. Ecologists may address this exchangeability assumption intuitively, but might in certain modeling contexts ignore it altogether, including in situations where it may have large implications for study design. Multispecies occupancy models based on detection/non-detection data are an approach that can be utilized by those tasked with monitoring rare and endangered species because most literature suggests that, compared to single species occupancy models, improved parameter estimates are assured. Yet, we illustrate through a power analysis how sampling requirements to detect experimental treatment effects vary tremendously depending on whether the species exchangeability assumption is met. The degree to which species in a community respond similarly to covariates governs the ability to accurately estimate parameters using multispecies occupancy models. Detecting small or moderate changes in occupancy resulting from habitat restoration treatments may be impossible for small datasets (e.g., < 36 sampling locations, each surveyed < 8 times) even with a paired treatment-control design if the exchangeability assumption is violated. By contrast, when the assumption is met, small effects may be confidently estimated with as few as 12 sampling locations (6 pairs) and 6-8 survey events. Often, it may be impossible to know whether the exchangeability assumption is met. The statistical power needed to accurately estimate species-specific effects using detection/non-detection multispecies occupancy models depends on the unknown values of treatment effects and whether responses by species in the community diverge. When the species exchangeability assumption is violated, and at lower levels of sampling effort, multispecies occupancy models may provide worse inference than single species occupancy models.
","language":"English","publisher":"BioRxiv","doi":"10.1101/2025.04.30.651473","usgsCitation":"Cotterill, G.G., Keinath, D.A., and Graves, T., 2025, Failure to meet the exchangeability assumption in Bayesian multispecies occupancy models: Implications for study design: BioRxiv, preprint posted May 06, 2025, https://doi.org/10.1101/2025.04.30.651473.","productDescription":"31 p.","ipdsId":"IP-176524","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":488154,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1101/2025.04.30.651473","text":"Publisher Index Page"},{"id":485549,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2025-05-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Cotterill, Gavin G. 0000-0002-1408-778X","orcid":"https://orcid.org/0000-0002-1408-778X","contributorId":346534,"corporation":false,"usgs":true,"family":"Cotterill","given":"Gavin","middleInitial":"G.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":936157,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keinath, Douglas A.","contributorId":274356,"corporation":false,"usgs":false,"family":"Keinath","given":"Douglas","email":"","middleInitial":"A.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":936158,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":936159,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70266908,"text":"70266908 - 2025 - Relating systematic molecular and textural properties of graptolite pyrolyzed via gold tube hydrous pyrolysis: Implications for thermal proxies in lower Paleozoic marine shales","interactions":[],"lastModifiedDate":"2025-05-15T14:57:48.182492","indexId":"70266908","displayToPublicDate":"2025-05-06T07:52:32","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Relating systematic molecular and textural properties of graptolite pyrolyzed via gold tube hydrous pyrolysis: Implications for thermal proxies in lower Paleozoic marine shales","docAbstract":"A series of gold tube pyrolysis experiments (72 h, 300–550 °C, 50 MPa) conducted on a graptolite-rich lower Paleozoic marine shale generated pyrolysis residues for a comprehensive evaluation of the molecular and structural variability of three types of graptolite periderm. Organic petrology, Raman spectroscopy, and field emission scanning electron microscopy (FE-SEM) with energy dispersive spectroscopy (EDS) were combined to evaluate the thermal evolution process. The three types of graptolite periderm, namely granular, non-granular, and nodular graptolite, were analyzed by Raman spectroscopy wherein point measurements were obtained after the maceral was identified and the location verified by organic petrology. Distinct thermal evolution pathways among non-granular, granular, and nodular graptolite periderms were recorded. The evolution patterns of the Raman parameters, particularly D1 and G bands, highlight the differences in geochemical composition of the graptolite periderm types and the alteration of molecular structure with increasing thermal maturity. Raman parameters D1 (position of the D1 peak), G-FWHM (full width at half maximum of the G peak), and ratios D1-FWHM/G-FWHM (full width at half maximum of the D1 peak ratioed to G-FWHM) and AD1/AG (ratio of D1 and G peak intensities) showed effectiveness in assessing thermal maturity. Bireflectance with increasing gold tube pyrolysis temperature followed a hierarchy: non-granular > granular > nodular, reflecting different molecular alignment intensities. Qualitative FE-SEM evaluation showed that fine-grained mineral inclusions (primarily Fe-sulfide as determined via EDS) were associated with the graptolite populations, with granular graptolite containing greater amounts of coarser-grained (e.g., ∼300–1400 nm) mineral inclusions relative to non-granular and nodular graptolite, which contain finer-grained (e.g., ∼100–200 nm) inclusions difficult to resolve with optical microscopy. These findings are investigated to highlight the mechanisms that drive organic matter evolution within graptolite during thermal maturation, as well as to explore some of the limitations of using spectroscopic parameters as thermal maturity proxies.
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