Mangrove is one of the most productive and sensitive ecosystems in the world. Due to the complexity and specificity of mangrove habitat, the development of mangrove is regulated by several factors. Species distribution models (SDMs) are effective tools to identify the potential habitats for establishing and regenerating the ecosystem. Such models usually include exclusively environmental factors. Nevertheless, recent studies have challenged this notion and highlight the importance of including biotic interactions. Both factors are necessary for a mechanistic understanding of the mangrove distribution in order to promote the protection and restoration of mangroves. Thus, we present a novel approach of combining environmental factors and interactions with salt marsh for projecting mangrove distributions at the global level and within latitudinal zones. To test the salt marsh interaction, we fit the MaxEnt model with two predicting sets: (1) environments only and (2) environments + salt marsh interaction index (SII). We found that both sets of models had good predictive ability, although the SII improved model performance slightly. Potential distribution areas of mangrove decrease with latitudes, and are controlled by biotic and abiotic factors. Temperature, precipitation and wind speed are generally critical at both global scale and ecotones along latitudes. SII is important on global scale, with a contribution of 5.9%, ranking 6th, and is particularly critical in the 10–30°S and 20–30°N zone. Interactions with salt marsh, including facilitation and competition, are shown to affect the distribution of mangroves at the zone of coastal ecotone, especially in the latitudinal range from 10° - 30°. The contribution of SII to mangrove distribution increases with latitudes due to the difference in the adaptive capacity of salt marsh plants and mangroves to environments. Totally, this study identified and quantified the effects of salt marsh on mangrove distribution by establishing the SII. The results not only facilitate to establish a more accurate mangrove distribution map, but also improve the efficiency of mangrove restoration by considering the salt marsh interaction in the mangrove management projects. In addition, the method of incorporating biotic interaction into SDMs through establish the biotic interaction index has contributed to the development of SDMs.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2023.119892","usgsCitation":"Cui, L., DeAngelis, D., Berger, U., Cao, M., Zhang, Y., Zhang, X., and Jiang, J., 2024, Global potential distribution of mangroves: Taking into account salt marsh interactions along latitudinal gradients: Journal of Environmental Management, v. 351, 119892, 13 p., https://doi.org/10.1016/j.jenvman.2023.119892.","productDescription":"119892, 13 p.","ipdsId":"IP-142484","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":424944,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"351","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cui, Lina","contributorId":333612,"corporation":false,"usgs":false,"family":"Cui","given":"Lina","email":"","affiliations":[{"id":79946,"text":"Nanjing Forestry University","active":true,"usgs":false}],"preferred":false,"id":893338,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeAngelis, Don 0000-0002-1570-4057","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":221357,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Don","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":893339,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berger, Uta","contributorId":224016,"corporation":false,"usgs":false,"family":"Berger","given":"Uta","affiliations":[{"id":40811,"text":"TU Dresden, Institute of Forest Growth and Computer Science, Germany","active":true,"usgs":false}],"preferred":false,"id":893340,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cao, Minmin","contributorId":333613,"corporation":false,"usgs":false,"family":"Cao","given":"Minmin","email":"","affiliations":[{"id":79946,"text":"Nanjing Forestry University","active":true,"usgs":false}],"preferred":false,"id":893341,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhang, Yaqi","contributorId":333614,"corporation":false,"usgs":false,"family":"Zhang","given":"Yaqi","email":"","affiliations":[{"id":79946,"text":"Nanjing Forestry University","active":true,"usgs":false}],"preferred":false,"id":893342,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zhang, Xiaomin","contributorId":333615,"corporation":false,"usgs":false,"family":"Zhang","given":"Xiaomin","email":"","affiliations":[{"id":79948,"text":"Zhejiang Academy of Forestry","active":true,"usgs":false}],"preferred":false,"id":893343,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jiang, Jiang","contributorId":191968,"corporation":false,"usgs":false,"family":"Jiang","given":"Jiang","email":"","affiliations":[],"preferred":false,"id":893344,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70251342,"text":"70251342 - 2024 - Identifying conditions where reed canarygrass (Phalaris arundinacea) functions as a driver of forest loss in the Upper Mississippi River floodplain under different hydrological scenarios","interactions":[],"lastModifiedDate":"2024-02-06T13:19:35.568516","indexId":"70251342","displayToPublicDate":"2024-01-02T07:15:42","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3751,"text":"Wetlands Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Identifying conditions where reed canarygrass (Phalaris arundinacea) functions as a driver of forest loss in the Upper Mississippi River floodplain under different hydrological scenarios","docAbstract":"Most of the world’s river-floodplain ecosystems are simultaneously undergoing modifications to their hydrological regimes and experiencing species invasions, making it unclear whether invasive species are the main drivers of ecosystem change or simply responding to changes in the hydrological regime.
We simulated patterns of forest recruitment and succession in a 2500-ha portion of the Upper Mississippi River floodplain with and without removal of invasive Phalaris arundinacea and under two different future 100-year hydrological scenarios: a future maintaining the average flooding conditions of the past 40 years (random) and a future that projects an observed upward 40-year trend in flooding conditions forward (trending). By comparing scenarios that included Phalaris removal and ones that did not, we were able to identify the conditions where Phalaris was the main driver of forest loss vs. the conditions where hydrology was the main driver of forest loss. Areas where Phalaris was the main driver of forest loss had mean annual flood inundation durations that were similar to areas that did not lose forest cover (60–90 growing season days), while areas where flooding was the main driver of forest loss had longer mean inundation durations (102–124 growing season days). In comparison to the random hydrology scenario, the trending scenario produced a decrease in the area over which Phalaris was identified as the main driver of forest loss and an increase in the area over which flood inundation was identified as the main driver of forest loss. Thus, if the observed trends in flooding continue, our model projects an increase in the area over which eradicating Phalaris is unlikely to result in the maintenance of forest cover. We used the Resist-Accept-Direct (RAD) framework to discuss potential management options to resist changes and maintain forest cover where Phalaris is likely to be the main driver of forest loss and to accept or direct changes in areas where forest loss is likely driven by hydrological change.
Many animals follow annual cycles wherein physiology and behavior change seasonally. Hibernating mammals undergo one of the most drastic seasonal alterations of physiology and behavior, the timing of which can have significant fitness consequences. The environmental cues regulating these profound phenotypic changes will heavily influence whether hibernators acclimate and ultimately adapt to climate change. Hence, identifying the cues and proximate mechanisms responsible for hibernation termination timing is critical. Northern Idaho ground squirrels (Urocitellus brunneus)—a rare, endemic species threatened with extinction—exhibit substantial variation in hibernation termination phenology, but it is unclear what causes this variation. We attached geolocators to free-ranging squirrels to test the hypothesis that squirrels assess surface conditions in spring before deciding whether to terminate seasonal heterothermy or reenter torpor. Northern Idaho ground squirrels frequently reentered torpor following a brief initial emergence from hibernacula and were more likely to do so earlier in spring or when challenged by residual snowpack. Female squirrels reentered torpor when confronted with relatively shallow snowpack upon emergence, whereas male squirrels reentered torpor in response to deeper spring snowpack. This novel behavior was previously assumed to be physiologically constrained in male ground squirrels by testosterone production required for spermatogenesis and activated by the circannual clock. Assessing surface conditions to decide when to terminate hibernation may help buffer these threatened squirrels against climate change. Documenting the extent to which other hibernators can facultatively alter emergence timing by reentering torpor after emergence will help identify which species are most likely to persist under climate change.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/729775","usgsCitation":"Allison, A.Z., Conway, C.J., Morris, A.E., Goldberg, A., Lohr, K., Richards, R., and Almack, J., 2024, Hit snooze: An imperiled hibernator assesses spring snow conditions to decide whether to terminate hibernation or reenter torpor: Ecological and Evolutionary Physiology, v. 97, no. 1, p. 53-63, https://doi.org/10.1086/729775.","productDescription":"11 p.","startPage":"53","endPage":"63","ipdsId":"IP-155349","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":430130,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Allison, Austin Z.T.","contributorId":339231,"corporation":false,"usgs":false,"family":"Allison","given":"Austin","email":"","middleInitial":"Z.T.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":903878,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903879,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morris, Alice E","contributorId":339157,"corporation":false,"usgs":false,"family":"Morris","given":"Alice","email":"","middleInitial":"E","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":903880,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goldberg, Amanda R.","contributorId":265814,"corporation":false,"usgs":false,"family":"Goldberg","given":"Amanda R.","affiliations":[{"id":54806,"text":"iu","active":true,"usgs":false}],"preferred":false,"id":903881,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lohr, Kristin","contributorId":127012,"corporation":false,"usgs":false,"family":"Lohr","given":"Kristin","affiliations":[{"id":6764,"text":"Idaho Department of Fish and Game, Nampa, Idaho","active":true,"usgs":false}],"preferred":false,"id":903883,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Richards, Russell","contributorId":339244,"corporation":false,"usgs":false,"family":"Richards","given":"Russell","email":"","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":903884,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Almack, Jon","contributorId":339247,"corporation":false,"usgs":false,"family":"Almack","given":"Jon","email":"","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":903885,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70259275,"text":"70259275 - 2024 - Ecology of Lake Erie - Chemistry, plankton & planktivory: A synthesis","interactions":[],"lastModifiedDate":"2024-10-03T13:31:43.005985","indexId":"70259275","displayToPublicDate":"2024-01-01T08:28:10","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18728,"text":"Aquatic Ecosystem Health and Management","active":true,"publicationSubtype":{"id":10}},"title":"Ecology of Lake Erie - Chemistry, plankton & planktivory: A synthesis","docAbstract":"As with other large lake ecosystems worldwide, Lake Erie can be considered a moving target for management, owing to physicochemical and biological changes brought on by anthropogenic change, both planned (e.g. nutrient and fisheries management) and unplanned (e.g. climate change, invasive species, modified land-use activities). These changes have challenged efforts to conserve biodiversity, sustain exploitable resources, and maintain the integrity of services valued by society both within the Lake Erie basin and (Fraker et al., 2022; Fussell et al., 2016; Sinclair et al., 2021; Sinclair et al., 2023) and outside of it (Allan et al., 2013; Jenny et al., 2020; Sterner et al., 2017). Some of these changes and their ramifications for management were documented in the first of four AEHM special issues devoted to the Lake Erie ecosystem (the fourth issue of 2023, volume 26, issue 4; see overview by Ludsin et al., 2023). That special issue focused explicitly on nutrient inputs and availability in Lake Erie and the lower food web, including planktonic and benthic microbial (including cyanobacteria), algal, and invasive dreissenid mussel communities. Similar to the previous Lake Erie special issue, this second one has focused on documenting the state of the lake, providing ecological understanding that could potentially benefit management. While some overlap in topics exists between issues, the studies conducted herein were completely independent of those previous investigations and offer unique insights. Specifically, the contributions to this current issue center on: 1) dynamics of water chemistry in Lake Erie’s central basin (i.e. bottom hypoxia; Ackerman et al., 2024) and western basin (i.e. mercury; Starr et al., 2024); 2) changes in primary producer biomass (Lesht et al., 2024), cyanotoxins (i.e. microcystin; Zastepa et al., 2024), and water quality (e.g. water clarity and dissolved nutrients; Howell et al., 2024); and 3) larval fish foraging (i.e. Lake Whitefish; Coregonus clupeaformis; Amidon et al., 2024) and community structure and phenology (DeBruyne et al., 2024). Below we summarize the major findings of these papers and offer a synthetic perspective on the value of this research for understanding the state of Lake Erie and enhancing management.
","language":"English","publisher":"Michigan State University Press","doi":"10.14321/aehm.027.01.116","usgsCitation":"Ludsin, S., Munawar, M., DeBruyne, R.L., Howell, E.T., Tyson, J., and Watkins, J.M., 2024, Ecology of Lake Erie - Chemistry, plankton & planktivory: A synthesis: Aquatic Ecosystem Health and Management, v. 27, no. 1, p. 116-124, https://doi.org/10.14321/aehm.027.01.116.","productDescription":"9 p.","startPage":"116","endPage":"124","ipdsId":"IP-163615","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":462529,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -78.90437674926393,\n 42.88573072124271\n ],\n [\n -79.52141499356523,\n 42.87769210959476\n ],\n [\n -80.22678399206747,\n 42.79281581499302\n ],\n [\n -80.51880625151767,\n 42.57814946253396\n ],\n [\n -81.02026663661093,\n 42.67543230196293\n ],\n [\n -81.30128454543694,\n 42.67543535756306\n ],\n [\n -81.53822853578485,\n 42.56596464399709\n ],\n [\n -81.9019334399238,\n 42.33014170165541\n ],\n [\n -81.95153424579222,\n 42.26492779780335\n ],\n [\n -82.12236039987853,\n 42.236375180224144\n ],\n [\n -82.45298532777961,\n 42.08524033767702\n ],\n [\n -82.5191058069868,\n 41.92964634487325\n ],\n [\n -82.61828632462084,\n 42.04024072452731\n ],\n [\n -82.91034362126736,\n 41.987015817617134\n ],\n [\n -83.11972864041921,\n 42.077062926530004\n ],\n [\n -83.10317152070901,\n 42.24453450962994\n ],\n [\n -83.29610139408294,\n 41.9419412108324\n ],\n [\n -83.3622121286252,\n 41.92964573816295\n ],\n [\n -83.51644448225035,\n 41.69555451568095\n ],\n [\n -82.9488535420495,\n 41.41103910261083\n ],\n [\n -82.71193183972241,\n 41.41929329585025\n ],\n [\n -82.47491670465367,\n 41.35733064230888\n ],\n [\n -81.99008606791249,\n 41.477110666960954\n ],\n [\n -81.70899983775189,\n 41.46067864477564\n ],\n [\n -81.25720217469238,\n 41.736707291689584\n ],\n [\n -80.6842102922714,\n 41.88460348122109\n ],\n [\n -79.96258495960994,\n 42.16700280222196\n ],\n [\n -79.42295622097835,\n 42.38302164176207\n ],\n [\n -79.37861904307078,\n 42.4440510296389\n ],\n [\n -79.15795348814065,\n 42.52534601120243\n ],\n [\n -79.00930804606551,\n 42.69563463834368\n ],\n [\n -78.83853732874603,\n 42.76038448982763\n ],\n [\n -78.84931646792415,\n 42.86956831700121\n ],\n [\n -78.90437674926393,\n 42.88573072124271\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"27","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-01-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Ludsin, Stuart A.","contributorId":270532,"corporation":false,"usgs":false,"family":"Ludsin","given":"Stuart A.","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":914751,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munawar, Mohiuddin","contributorId":344801,"corporation":false,"usgs":false,"family":"Munawar","given":"Mohiuddin","email":"","affiliations":[{"id":13015,"text":"Department of Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":914752,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeBruyne, Robin L. 0000-0002-9232-7937 rdebruyne@usgs.gov","orcid":"https://orcid.org/0000-0002-9232-7937","contributorId":4936,"corporation":false,"usgs":true,"family":"DeBruyne","given":"Robin","email":"rdebruyne@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":914753,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Howell, E. Todd","contributorId":344802,"corporation":false,"usgs":false,"family":"Howell","given":"E.","email":"","middleInitial":"Todd","affiliations":[{"id":82411,"text":"Ontario Ministry of the Environment, Conservation, and Parks","active":true,"usgs":false}],"preferred":false,"id":914754,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tyson, Jeffrey","contributorId":344803,"corporation":false,"usgs":false,"family":"Tyson","given":"Jeffrey","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":914755,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Watkins, James M.","contributorId":189286,"corporation":false,"usgs":false,"family":"Watkins","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":914756,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70250749,"text":"70250749 - 2024 - Modular compositional learning improves 1D hydrodynamic lake model performance by merging process-based modeling with deep learning","interactions":[],"lastModifiedDate":"2024-01-02T12:32:07.209065","indexId":"70250749","displayToPublicDate":"2023-12-28T06:30:40","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5407,"text":"Journal of Advances in Modeling Earth Systems","active":true,"publicationSubtype":{"id":10}},"title":"Modular compositional learning improves 1D hydrodynamic lake model performance by merging process-based modeling with deep learning","docAbstract":"Hybrid Knowledge-Guided Machine Learning (KGML) models, which are deep learning models that utilize scientific theory and process-based model simulations, have shown improved performance over their process-based counterparts for the simulation of water temperature and hydrodynamics. We highlight the modular compositional learning (MCL) methodology as a novel design choice for the development of hybrid KGML models in which the model is decomposed into modular sub-components that can be process-based models and/or deep learning models. We develop a hybrid MCL model that integrates a deep learning model into a modularized, process-based model. To achieve this, we first train individual deep learning models with the output of the process-based models. In a second step, we fine-tune one deep learning model with observed field data. In this study, we replaced process-based calculations of vertical diffusive transport with deep learning. Finally, this fine-tuned deep learning model is integrated into the process-based model, creating the hybrid MCL model with improved overall projections for water temperature dynamics compared to the original process-based model. We further compare the performance of the hybrid MCL model with the process-based model and two alternative deep learning models and highlight how the hybrid MCL model has the best performance for projecting water temperature, Schmidt stability, buoyancy frequency, and depths of different isotherms. Modular compositional learning can be applied to existing modularized, process-based model structures to make the projections more robust and improve model performance by letting deep learning estimate uncertain process calculations.
The Red Shiner Cyprinella lutrensis is one of the most prolific and ecologically destructive invasive fish species in the southwestern United States. The production and release of YY individuals as Trojan sex chromosome carriers can theoretically eradicate invasive fish populations by eventually eliminating phenotypic females.
The YY individuals are typically produced through hormonally induced sex reversals and selective breeding of subsequently feminized males. We tested three dosages of estradiol-17β (E2)-treated diets (50, 100, and 150 mg of E2 per kg of diet) administered to sexually immature Red Shiner for various durations to determine their effectiveness at feminizing Red Shiner cohorts. Survival, growth, and gonadal development were assessed for each treatment.
All E2 treatments had minimal, if any, detrimental effects on the growth and gonadal development of Red Shiner. The 50-mg dosage lasting from 2 to 120 days posthatch achieved a 100% feminization rate while using the lowest amount of E2; therefore, this dosage and treatment interval are recommended when attempting Red Shiner feminization under these rearing conditions. Feminization of males allowed for the spawning of neofemales (FXY) with wild-type males (MXY), which resulted in the first putative YY Red Shiner. The YY verification crosses (n = 20) resulted in predominately male offspring (189 males/191 offspring) except for (1) an intersex individual from an MYY × FXX cross with two previtellogenic oocytes in its testis and (2) a single female that may have resulted from an inbred cross between an XY male and a YY female or from an unknown autosomal or environmental effect on sexual phenotype.
More progeny tests with inbred and outbred crosses should be conducted to determine the prevalence of female offspring from YY individuals and how this may impact an eradication strategy featuring releases of YY Red Shiner.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/naaq.10314","usgsCitation":"Teal, C.N., Schill, D., Bauder, J.M., Fogelson, S.B., Fitzsimmons, K., Stewart, W., Culver, M., and Bonar, S.A., 2024, The effects of estradiol-17β on the sex reversal, survival, and growth of Red Shiner and its use in the development of YY individuals: North American Journal of Aquaculture, v. 86, no. 1, p. 110-129, https://doi.org/10.1002/naaq.10314.","productDescription":"20 p.","startPage":"110","endPage":"129","ipdsId":"IP-155076","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":498669,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10150/670656","text":"External Repository"},{"id":429775,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-12-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Teal, Chad N.","contributorId":337952,"corporation":false,"usgs":false,"family":"Teal","given":"Chad","email":"","middleInitial":"N.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":902800,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schill, Daniel J.","contributorId":337953,"corporation":false,"usgs":false,"family":"Schill","given":"Daniel J.","affiliations":[{"id":61802,"text":"Fisheries Management Solutions","active":true,"usgs":false}],"preferred":false,"id":902801,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bauder, Javan Mathias 0000-0002-2055-5324","orcid":"https://orcid.org/0000-0002-2055-5324","contributorId":337814,"corporation":false,"usgs":true,"family":"Bauder","given":"Javan","email":"","middleInitial":"Mathias","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902802,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fogelson, Susan B.","contributorId":337954,"corporation":false,"usgs":false,"family":"Fogelson","given":"Susan","email":"","middleInitial":"B.","affiliations":[{"id":61804,"text":"Fishhead Labs","active":true,"usgs":false}],"preferred":false,"id":902803,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fitzsimmons, Kevin","contributorId":337955,"corporation":false,"usgs":false,"family":"Fitzsimmons","given":"Kevin","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":902804,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stewart, William T.","contributorId":337956,"corporation":false,"usgs":false,"family":"Stewart","given":"William T.","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":902805,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Culver, Melanie 0000-0001-5380-3059 mculver@usgs.gov","orcid":"https://orcid.org/0000-0001-5380-3059","contributorId":197693,"corporation":false,"usgs":true,"family":"Culver","given":"Melanie","email":"mculver@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":902806,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bonar, Scott A. 0000-0003-3532-4067 sbonar@usgs.gov","orcid":"https://orcid.org/0000-0003-3532-4067","contributorId":3712,"corporation":false,"usgs":true,"family":"Bonar","given":"Scott","email":"sbonar@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902807,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70251352,"text":"70251352 - 2024 - How long have we been mistaken? Multi-tools shedding light into the systematics of the widespread deep-water genus Madrepora Linnaeus, 1758 (Scleractinia)","interactions":[],"lastModifiedDate":"2024-02-07T15:05:56.570052","indexId":"70251352","displayToPublicDate":"2023-12-23T08:41:38","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2779,"text":"Molecular Phylogenetics and Evolution","active":true,"publicationSubtype":{"id":10}},"displayTitle":"How long have we been mistaken? Multi-tools shedding light into the systematics of the widespread deep-water genus Madrepora Linnaeus, 1758 (Scleractinia)","title":"How long have we been mistaken? Multi-tools shedding light into the systematics of the widespread deep-water genus Madrepora Linnaeus, 1758 (Scleractinia)","docAbstract":"Deep-water coral reefs are found worldwide and harbor biodiversity levels that are comparable to their shallow-water counterparts. However, the genetic diversity and population structure of deep-water species remain poorly explored, and historical taxonomical issues still need to be resolved. Here we used microsatellite markers as well as ultraconserved elements (UCE) and exons to shed light on the population structure, genetic diversity, and phylogenetic position of the genus Madrepora, which contains M. oculata, one of the most widespread scleractinian species. Population structure of 107 samples from three Southwestern Atlantic sedimentary basins revealed the occurrence of a cryptic species, herein named M. piresae sp. nov. (authored by Kitahara, Capel and Zilberberg), which can be found in sympatry with M. oculata. Phylogeny reconstructions based on 134 UCEs and exon regions corroborated the population genetic data, with the recovery of two well-supported groups, and reinforced the polyphyly of the family Oculinidae. In order to better accommodate the genus Madrepora, while reducing taxonomical confusion associated with the name Madreporidae, we propose the monogeneric family Bathyporidae fam. nov. (authored by Kitahara, Capel, Zilberberg and Cairns). Our findings advance the knowledge on the widespread deep-water genus Madrepora, resolve a long-standing question regarding the phylogenetic position of the genus, and highlight the need of a worldwide review of the genus.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ympev.2023.107994","usgsCitation":"Capel, K.C., Zilberberg, C., Carpes, R.M., Morrison, C., Vaga, C.F., Quattrini, A., Quek, R.Z., Huang, D., Cairns, S.D., and Kitahara, M.V., 2024, How long have we been mistaken? Multi-tools shedding light into the systematics of the widespread deep-water genus Madrepora Linnaeus, 1758 (Scleractinia): Molecular Phylogenetics and Evolution, v. 191, 107994, 10 p., https://doi.org/10.1016/j.ympev.2023.107994.","productDescription":"107994, 10 p.","ipdsId":"IP-154239","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":425471,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"191","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Capel, Katia C. C.","contributorId":333882,"corporation":false,"usgs":false,"family":"Capel","given":"Katia","email":"","middleInitial":"C. C.","affiliations":[{"id":79999,"text":"Center for Marine Biology, São Paulo University, São Sebastião, São Paulo, Brazil","active":true,"usgs":false}],"preferred":false,"id":894214,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zilberberg, Carla","contributorId":333883,"corporation":false,"usgs":false,"family":"Zilberberg","given":"Carla","email":"","affiliations":[{"id":80000,"text":"Department of Zoology, Institute of Biodiversity and Sustainability – Nupem, Federal University of Rio de Janeiro, Macaé, Rio de Janeiro, Brazil","active":true,"usgs":false}],"preferred":false,"id":894215,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carpes, Raphael M.","contributorId":333884,"corporation":false,"usgs":false,"family":"Carpes","given":"Raphael","email":"","middleInitial":"M.","affiliations":[{"id":80000,"text":"Department of Zoology, Institute of Biodiversity and Sustainability – Nupem, Federal University of Rio de Janeiro, Macaé, Rio de Janeiro, Brazil","active":true,"usgs":false}],"preferred":false,"id":894216,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morrison, Cheryl 0000-0001-9425-691X cmorrison@usgs.gov","orcid":"https://orcid.org/0000-0001-9425-691X","contributorId":202644,"corporation":false,"usgs":true,"family":"Morrison","given":"Cheryl","email":"cmorrison@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":894217,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vaga, Claudia F.","contributorId":333885,"corporation":false,"usgs":false,"family":"Vaga","given":"Claudia","email":"","middleInitial":"F.","affiliations":[{"id":80002,"text":"Center for Marine Biology, São Paulo University, São Sebastião, São Paulo, Brazil; Graduate Program in Zoology, Department of Zoology, Institute of Biosciences, University of São Paulo, São Paulo, Brazil","active":true,"usgs":false}],"preferred":false,"id":894218,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Quattrini, Andrea M.","contributorId":333886,"corporation":false,"usgs":false,"family":"Quattrini","given":"Andrea M.","affiliations":[{"id":80003,"text":"Department of Invertebrate Zoology, Smithsonian Institution, Washington DC, United States of America","active":true,"usgs":false}],"preferred":false,"id":894219,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Quek, Randolph Z. B.","contributorId":333887,"corporation":false,"usgs":false,"family":"Quek","given":"Randolph","email":"","middleInitial":"Z. B.","affiliations":[{"id":80004,"text":"Department of Biological Sciences, National University of Singapore, Singapore","active":true,"usgs":false}],"preferred":false,"id":894220,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Huang, Danwei","contributorId":333888,"corporation":false,"usgs":false,"family":"Huang","given":"Danwei","email":"","affiliations":[{"id":80005,"text":"Department of Biological Sciences, National University of Singapore, Singapore; Lee Kong Chian Natural History Museum, National University of Singapore, Singapore","active":true,"usgs":false}],"preferred":false,"id":894221,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cairns, Stephen D.","contributorId":333889,"corporation":false,"usgs":false,"family":"Cairns","given":"Stephen","email":"","middleInitial":"D.","affiliations":[{"id":80003,"text":"Department of Invertebrate Zoology, Smithsonian Institution, Washington DC, United States of America","active":true,"usgs":false}],"preferred":false,"id":894222,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kitahara, Marcelo V.","contributorId":333890,"corporation":false,"usgs":false,"family":"Kitahara","given":"Marcelo","email":"","middleInitial":"V.","affiliations":[{"id":80006,"text":"Center for Marine Biology, São Paulo University; Graduate Program in Zoology, Department of Zoology, Institute of Biosciences, University of São Paulo; Department of Invertebrate Zoology, Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":894223,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70251142,"text":"70251142 - 2024 - Assessing microplastics contamination in unviable loggerhead sea turtle eggs","interactions":[],"lastModifiedDate":"2024-01-24T12:42:58.730912","indexId":"70251142","displayToPublicDate":"2023-12-21T06:40:23","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Assessing microplastics contamination in unviable loggerhead sea turtle eggs","docAbstract":"Sea turtles, in comparison with marine mammals, sea birds, and fishes, are the most affected by microplastics in terms of number of individuals impacted and concentration within each organism. The ubiquitous nature and persistence of microplastics in the environment further compromises sea turtles as many species are currently vulnerable, endangered, or critically endangered. The objective of this study was to quantify microplastic contamination in unviable loggerhead sea turtle eggs (Caretta caretta). Eggs were collected from seven locations along the northwest coast of Florida. A total of 70 nests and 350 eggs were examined. Microplastics (n = 510) were found in undeveloped loggerhead sea turtle eggs across all seven sites, suggesting that maternal transference and/or exchange between the internal and external environment were possible. The frequency found was 7.29 ± 1.83 microplastic pieces per nest and 1.46 ± 0.01 per egg. Microplastics were categorized based on color, shape, size, and type of polymer. The predominant color of microplastics were blue/green (n = 236), shape was fibers (n = 369), and length was 10–300 μm (n = 191). Identified fragments, films, beads and one foam (n = 187) had the most common area of 1–10 μm2 (n = 45). Micro-Fourier Transform Infrared (μ-FTIR) spectroscopy analysis demonstrated that polyethylene (11 %) and polystyrene (7 %) were the main polymer types. For the first time microplastics were found in unviable, undeveloped loggerhead sea turtle eggs collected in northwest Florida. This work provides insight into the distribution patterns of microplastic pollutants in loggerhead sea turtle eggs and may extend to other species worldwide.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2023.169434","usgsCitation":"Curl, L.F., Hurst, S.A., Pomory, C.M., Lamont, M., and Janosik, A.M., 2024, Assessing microplastics contamination in unviable loggerhead sea turtle eggs: Science of the Total Environment, v. 912, 169434, 11 p., https://doi.org/10.1016/j.scitotenv.2023.169434.","productDescription":"169434, 11 p.","ipdsId":"IP-157840","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":424847,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.52215071903645,\n 30.711556366152337\n ],\n [\n -87.52215071903645,\n 29.380201094936183\n ],\n [\n -84.55584212528632,\n 29.380201094936183\n ],\n [\n -84.55584212528632,\n 30.711556366152337\n ],\n [\n -87.52215071903645,\n 30.711556366152337\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"912","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Curl, Lindsay F.","contributorId":333594,"corporation":false,"usgs":false,"family":"Curl","given":"Lindsay","email":"","middleInitial":"F.","affiliations":[{"id":16703,"text":"University of West Florida","active":true,"usgs":false}],"preferred":false,"id":893250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hurst, Samantha A.","contributorId":333595,"corporation":false,"usgs":false,"family":"Hurst","given":"Samantha","email":"","middleInitial":"A.","affiliations":[{"id":16703,"text":"University of West Florida","active":true,"usgs":false}],"preferred":false,"id":893251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pomory, Christopher M.","contributorId":333596,"corporation":false,"usgs":false,"family":"Pomory","given":"Christopher","email":"","middleInitial":"M.","affiliations":[{"id":16703,"text":"University of West Florida","active":true,"usgs":false}],"preferred":false,"id":893252,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lamont, Margaret 0000-0001-7520-6669","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":222403,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":893253,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Janosik, Alexis M.","contributorId":333597,"corporation":false,"usgs":false,"family":"Janosik","given":"Alexis","email":"","middleInitial":"M.","affiliations":[{"id":16703,"text":"University of West Florida","active":true,"usgs":false}],"preferred":false,"id":893254,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70250615,"text":"70250615 - 2024 - Non-native Rhizophora mangle as sinks for coastal contamination on Moloka'i, Hawai'i","interactions":[],"lastModifiedDate":"2023-12-20T12:58:34.273857","indexId":"70250615","displayToPublicDate":"2023-12-19T06:55:54","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17112,"text":"Environmental Advances","active":true,"publicationSubtype":{"id":10}},"title":"Non-native Rhizophora mangle as sinks for coastal contamination on Moloka'i, Hawai'i","docAbstract":"Coastal mangrove forests provide a suite of environmental services, including sequestration of anthropogenic contamination. Yet, research lags on the environmental fate and potential human health risks of mangrove-sequestered contaminants in the context of mangrove removal for development and range shifts due to climate change. To address this, we conducted a study on Moloka'i, Hawai'i, comparing microplastic and pesticide contamination in coastal compartments both at areas modified by non-native red mangroves (Rhizophora mangle) and unmodified, open coastline. Sediment, porewater, and mangrove plant tissues were collected to quantify microplastic and pesticide concentrations across ecosystem type. Average microplastics were similar between mangrove (8.89 items/kg) and non-mangrove areas (9.01 items/kg) in sediment and porewater, but mangrove roots were a substantial reservoir of microplastics (2004 items/kg). Additionally, there was a strong relationship between proximity to urban development and microplastics detected. Six pesticides were detected, most commonly the insecticide bifenthrin, found in most sediment samples (11.3 ng/g), all root samples (243.3 ng/g), and one propagule sample (8.60 ng/g). Other pesticides detected with appreciable concentrations include the neonicotinoid insecticide imidacloprid and the legacy insecticide transformation product, p,p’-DDE. The other detections, all at concentrations < 1 ng/g, were p,p’-DDT, trifluralin, and permethrin. The high concentrations of bifenthrin in roots compared to lower concentrations detected in sediment suggest that mangrove roots strongly accumulate some pesticides, indicating mangrove roots as a sink for organic contaminants. Study methods could be applied to other Hawaiian Islands and other locations where mangroves have been introduced to further examine the observed trends. Additional information is needed to investigate the fate and cycling of pesticides and microplastics adhered to mangrove roots, to better inform non-native mangrove removal efforts on Moloka'i and elsewhere.
An assumption of biotelemetry is that animal performance is unaffected by the tagging process and tag burden, yet this assumption is often untested or not thoroughly explored. Our objective was to explore how transmitter implantation procedures influenced Atlantic Salmon Salmo salar smolt survival and migratory performance.
We monitored radio-tagged smolts, first in the hatchery and then in a river with a receiver array. We assessed survival and in-river performance in relation to surgeon, surgery duration, processing order, and fish size.
Mortality was 13.3% during an 8-day hatchery-observation but was higher for fish processed by one of two experienced surgeons (25% vs. 2%). Mortality peaked three days post-surgery and was higher for smaller fish and fish tagged during morning tagging sessions (compared to afternoons). The size effect changed over time, being greatest during the first two days post-surgery, and continuing thereafter at a diminished level. Fish performance once released into a river also differed between surgeons (migration initiation 66% vs. 82%; and to-lake migration success 22% vs 43%), and consistent with hatchery observations, fish tagged in the morning by one surgeon performed poorly once released.
We highlight immediate and lingering effects of surgical procedures on smolt survival that, if not accounted for, could bias inferences about the study population. Researchers should anticipate tagger effects during study design to ensure potential tagger effects (i.e., surgeon, order tagged, conditions during tagging) are balanced across study groups of interest. Testing for a fixed tagger effect in analyses may not always be adequate because a tagger effect may covary with processing order and fish size and may change over time.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10986","usgsCitation":"Heim, K., Withers, J.L., and Castro-Santos, T., 2024, Tagger effects in aquatic telemetry: Short-term and delayed impacts of surgery in Atlantic salmon smolts: North American Journal of Fisheries Management, v. 44, no. 2, p. 262-275, https://doi.org/10.1002/nafm.10986.","productDescription":"14 p.","startPage":"262","endPage":"275","ipdsId":"IP-154942","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":440909,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.10986","text":"Publisher Index Page"},{"id":424052,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-12-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Heim, Kurt C.","contributorId":264533,"corporation":false,"usgs":false,"family":"Heim","given":"Kurt C.","affiliations":[{"id":48645,"text":"umt","active":true,"usgs":false}],"preferred":false,"id":891196,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Withers, Jonah L.","contributorId":265471,"corporation":false,"usgs":false,"family":"Withers","given":"Jonah","email":"","middleInitial":"L.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":891197,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Castro-Santos, Theodore 0000-0003-2575-9120","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":315433,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":891198,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70251815,"text":"70251815 - 2024 - Numbers of wildlife fatalities at renewable energy facilities in a targeted development region","interactions":[],"lastModifiedDate":"2024-02-29T15:01:41.057961","indexId":"70251815","displayToPublicDate":"2023-12-15T08:30:47","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Numbers of wildlife fatalities at renewable energy facilities in a targeted development region","docAbstract":"Increased interest in renewable energy has fostered development of wind and solar energy facilities globally. However, energy development sometimes has negative environmental impacts, such as wildlife fatalities. Efforts by regional land managers to balance energy potential while minimizing fatality risk currently rely on datasets that are aggregated at continental, but not regional scales, that focus on single species, or that implement meta-analyses that inappropriately use inferential statistics. We compiled and summarized fatality data from 87 reports for solar and wind facilities in the Mojave and Sonoran Deserts region of southern California within the Desert Renewable Energy Conservation Plan area. Our goal was to evaluate potential temporal and guild-specific patterns in fatalities, especially for priority species of conservation concern. We also aimed to provide a perspective on approaches interpreting these types of data, given inherent limitations in how they were collected. Mourning doves (Zenaida macroura), Chukar (Alectoris chukar) and California Quail (Callipepla californica), and passerines (Passeriformes), accounted for the most commonly reported fatalities. However, our aggregated count data were derived from raw, uncorrected totals, and thus reflect an absolute minimum number of fatalities for the monitored period. Additionally, patterns in the raw data suggested that many species commonly documented as fatalities (e.g., waterbirds and other nocturnal migrants, bats) are rarely counted during typical pre-construction use surveys. This may explain the more commonly observed mismatch between pre-construction risk assessment and actual fatalities. Our work may serve to guide design of future scientific research to address temporal and spatial patterns in fatalities and to apply rigorous guild-specific survey methodologies to estimate populations at risk from renewable energy development.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0295552","usgsCitation":"Conkling, T., Fesnock, A.L., and Katzner, T., 2024, Numbers of wildlife fatalities at renewable energy facilities in a targeted development region: PLoS ONE, v. 18, no. 12, e0295552, 15 p., https://doi.org/10.1371/journal.pone.0295552.","productDescription":"e0295552, 15 p.","ipdsId":"IP-142188","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":440915,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0295552","text":"Publisher Index Page"},{"id":426127,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.41388196440452,\n 32.63301172668308\n ],\n [\n -114.71231156077859,\n 32.71521061573718\n ],\n [\n -114.41844327520268,\n 34.121883375452825\n ],\n [\n -115.258371375603,\n 35.51347324917859\n ],\n [\n -116.44620706269673,\n 36.348306541123236\n ],\n [\n -120.9361068529251,\n 35.49816148699837\n ],\n [\n -117.83770190615772,\n 34.11965094145391\n ],\n [\n -116.41388196440452,\n 32.63301172668308\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Conkling, Tara 0000-0003-1926-8106","orcid":"https://orcid.org/0000-0003-1926-8106","contributorId":217915,"corporation":false,"usgs":true,"family":"Conkling","given":"Tara","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":895658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fesnock, Amy L.","contributorId":334447,"corporation":false,"usgs":false,"family":"Fesnock","given":"Amy","email":"","middleInitial":"L.","affiliations":[{"id":80149,"text":"Desert District Office, U.S. Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":895659,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":895660,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70251028,"text":"70251028 - 2024 - Elevated temperature and nutrients lead to increased N2O emissions from salt marsh soils from cold and warm climates","interactions":[],"lastModifiedDate":"2024-02-07T17:24:27.301889","indexId":"70251028","displayToPublicDate":"2023-12-14T07:08:31","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Elevated temperature and nutrients lead to increased N2O emissions from salt marsh soils from cold and warm climates","title":"Elevated temperature and nutrients lead to increased N2O emissions from salt marsh soils from cold and warm climates","docAbstract":"Salt marshes can attenuate nutrient pollution and store large amounts of ‘blue carbon’ in their soils, however, the value of sequestered carbon may be partially offset by nitrous oxide (N2O) emissions. Global climate and land use changes result in higher temperatures and inputs of reactive nitrogen (Nr) into coastal zones. Here, we investigated the combined effects of elevated temperature (ambient + 5℃) and Nr (double ambient concentrations) on nitrogen processing in marsh soils from two climatic regions (Quebec, Canada and Louisiana, U.S.) with two vegetation types, Sporobolus alterniflorus (= Spartina alterniflora) and Sporobolus pumilus (= Spartina patens), using 24-h laboratory incubation experiments. Potential N2O fluxes increased from minor sinks to major sources following elevated treatments across all four marsh sites. One day of potential N2O emissions under elevated treatments (representing either long-term sea surface warming or short-term ocean heatwaves effects on coastal marsh soil temperatures alongside pulses of N loading) offset 15–60% of the potential annual ambient N2O sink, depending on marsh site and vegetation type. Rates of potential denitrification were generally higher in high latitude than in low latitude marsh soils under ambient treatments, with low ratios of N2O:N2 indicating complete denitrification in high latitude marsh soils. Under elevated temperature and Nr treatments, potential denitrification was lower in high latitude soil but higher in low latitude soil as compared to ambient conditions, with incomplete denitrification observed except in Louisiana S. pumilus. Overall, our findings suggest that a combined increase in temperature and Nr has the potential to reduce salt marsh greenhouse gas (GHG) sinks under future global change scenarios.
Development and evaluation of models for tectonic evolution in the Cascadia forearc require understanding of along-strike heterogeneity of strain distribution, uplift, and upper-plate characteristics. Here, we investigated the Neogene geologic record of the Klamath Mountains province in southernmost Cascadia and obtained apatite (U-Th)/He (AHe) thermochronology of Mesozoic plutons, Neogene graben sediment thickness, detrital zircon records from Neogene grabens, gravity and magnetic data, and kinematic analysis of faults. We documented three aspects of Neogene tectonics: early Miocene and younger rock exhumation, development of topographic relief sufficient to isolate Neogene graben-filling sediments from sources outside of the Klamath Mountains, and initiation of mid-Miocene or younger right-lateral and reverse faulting. Key findings are: (1) 10 new apatite AHe mean cooling ages from the Canyon Creek and Granite Peak plutons in the Trinity Alps range from 24.7 ± 2.1 Ma to 15.7 ± 2.1 Ma. Inverse thermal modeling of these data and published apatite fission-track ages indicate the most rapid rock cooling between ca. 25 and 15 Ma. One new AHe mean cooling age (26.7 ± 3.2 Ma) from the Ironside Mountain batholith 40 km west of the Trinity Alps, combined with previously published AHe ages, suggests geographically widespread latest Oligocene to Miocene cooling in the southern Klamath Mountains province. (2) AHe ages of 39.4 ± 5.1 Ma on the downthrown side and 22.7 ± 3.0 Ma on the upthrown side of the Browns Meadow fault suggest early Miocene to younger fault activity. (3) U-Pb detrital zircon ages (n = 862) and Lu-Hf isotope geochemistry from Miocene Weaverville Formation sediments in the Weaverville, Lowden Ranch, Hayfork, and Hyampom grabens south and southwest of the Trinity Alps can be traced to entirely Klamath Mountains sources; they suggest the south-central Klamath Mountains had, by the middle Miocene, sufficient relief to isolate these grabens from more distal sediment sources. (4) Two Miocene detrital zircon U-Pb ages of 10.6 ± 0.4 Ma and 16.7 ± 0.2 Ma from the Lowden Ranch graben show that the maximum depositional age of the upper Weaverville Formation here is younger than previously recognized. (5) A prominent steep-sided negative gravity anomaly associated with the Hayfork graben shows that both the north and south margins are fault-controlled, and inversion of gravity data suggests basin fill is between 1 km and 1.9 km thick. Abrupt elevation changes of basin fill-to-bedrock contacts reported in well logs record E-side-up and right-lateral faulting at the eastern end of the Hayfork graben. A NE-striking gravity gradient separates the main graben on the west from a narrower, thinner basin to the east, supporting this interpretation. (6) Of fset of both the base of the Weaverville Formation and the cataclasite-capped La Grange fault surface by a fault on the southwest margin of the Weaverville basin documents 200 m of reverse and 1500 m of right-lateral strike-slip motion on this structure, here named the Democrat Gulch fault; folded and steeply dipping strata adjacent to the fault confirm that faulting postdated deposition of the Weaverville Formation.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02612.1","usgsCitation":"Michalak, M.J., Cashman, S.M., Langenheim, V., Team, T.C., and Christensen, D.J., 2024, Neogene faulting, basin development, and relief generation in the southern Klamath Mountains (USA): Geosphere, v. 20, no. 1, p. 237-266, https://doi.org/10.1130/GES02612.1.","productDescription":"30 p.","startPage":"237","endPage":"266","ipdsId":"IP-144540","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":440927,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02612.1","text":"Publisher Index Page"},{"id":425101,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Southern Klamath Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -125.98917316134096,\n 44.02774490532599\n ],\n [\n -125.98917316134096,\n 38.79194801722443\n ],\n [\n -120.47403644259101,\n 38.79194801722443\n ],\n [\n -120.47403644259101,\n 44.02774490532599\n ],\n [\n -125.98917316134096,\n 44.02774490532599\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"20","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-12-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Michalak, Melanie J.","contributorId":317978,"corporation":false,"usgs":false,"family":"Michalak","given":"Melanie","email":"","middleInitial":"J.","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":893555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cashman, Susan M.","contributorId":333685,"corporation":false,"usgs":false,"family":"Cashman","given":"Susan","email":"","middleInitial":"M.","affiliations":[{"id":63943,"text":"Cal Poly Humboldt","active":true,"usgs":false}],"preferred":false,"id":893556,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langenheim, Victoria 0000-0003-2170-5213","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":217113,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":893557,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Team, Taylor C.","contributorId":333686,"corporation":false,"usgs":false,"family":"Team","given":"Taylor","email":"","middleInitial":"C.","affiliations":[{"id":63943,"text":"Cal Poly Humboldt","active":true,"usgs":false}],"preferred":false,"id":893558,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Christensen, Dana J.","contributorId":333687,"corporation":false,"usgs":false,"family":"Christensen","given":"Dana","email":"","middleInitial":"J.","affiliations":[{"id":63943,"text":"Cal Poly Humboldt","active":true,"usgs":false}],"preferred":false,"id":893559,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70251168,"text":"70251168 - 2024 - Relative effectiveness of a radionuclide (210Pb), surface elevation table (SET), and LiDAR at monitoring mangrove forest surface elevation change","interactions":[],"lastModifiedDate":"2024-08-26T14:28:23.578119","indexId":"70251168","displayToPublicDate":"2023-12-12T07:05:57","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Relative effectiveness of a radionuclide (210Pb), surface elevation table (SET), and LiDAR at monitoring mangrove forest surface elevation change","docAbstract":"Sea-level rise (SLR) is one of the greatest future threats to mangrove forests. Mangroves have kept up with or paced past SLR by maintaining their forest floor elevation relative to sea level through root growth, sedimentation, and peat development. Monitoring surface elevation change (SEC) or accretion rates allows us to understand mangrove response to SLR and prioritizes resilient ecosystems for conservation or vulnerable ecosystems for restoration. We compared three methods to measure SEC and accretion in mangrove forests: 210Pb, surface elevation tables (SETs), and a terrestrial light detection and ranging system (compact biomass LiDAR—CBL). Lead-210 accretion rates were not significantly different than SET SEC rates and differences between the two methods (− 2 to 2 mm/year) were within the error of our measurements. Lead-210 only measures accretion in the upper meter of sediment and cannot capture deeper subsurface processes (e.g., subsidence, compaction) that SETs can. The lack of differences suggests the following: (1) surface processes in the active root zone are influencing forest floor elevation more than subsurface processes, (2) subsurface processes were not large enough to effect elevation, or (3) the SETs were not installed deep enough to capture subsurface processes. CBL SEC rates did not differ significantly from SET SEC rates. The larger spatial scale of the CBL scans resulted in significantly different SEC rates from some of the plots. This was due to the CBL measuring areas missed by the SET. The greater number of points measured by CBL (~ 30,000 vs 36) increased precision and lowered standard error. The traditional SET/rSET method is currently 3–10 × cheaper than the 210Pb or CBL method, respectively, and can accurately track changes in forest floor elevation. Costs of the use of LiDAR are likely to decrease in the future with the advent of newer and more cost-effective technology.
Reintroductions are one means of managing species distributions, but the feasibility of such efforts is uncertain. Here we consider reintroduction for threatened bull trout (Salvelinus confluentus) that currently occupy a small fraction of historically occupied habitats in the upper Klamath River basin owing to climate warming and human modifications of ecosystems. We engaged stakeholders across multiple organizations to co-produce a decision support model that estimated the potential of reintroduction to establish new populations and persistence of donor populations. Stakeholders identified recipient and donor populations, strategy (e.g., artificial propagation, translocation), number of individuals, and life stage of bull trout. The most optimal decision for reintroduction was artificial propagation of 10,000 fry into Annie Creek. This strategy may have negative consequences on donor populations, with the exception of Sun Creek, which was resilient to simulated removal of bull trout. Donor populations and recipient streams identified as most feasible were generally consistent across all of these scenarios. During model development, however, an unexpected and intense wildfire affected half of the streams considered and may have dramatically impacted donor populations. With models in hand from the initial feasibility assessment, we adapted them to further evaluate the potential of supplementation following this massive disturbance. Overall, results of this study indicate the value of developing co-produced tools that can be rapidly adapted to evaluate the consequences of whole-system transformations in near-real-time assessments.
Pharmaceuticals and personal care products (PPCPs) are frequently detected in marine environments, posing a threat to aquatic organisms. Our previous research demonstrated the occurrence of neuroactive compounds in effluent and sediments from a wastewater treatment plant (WWTP) in a fjord North of Stavanger, the fourth-largest city in Norway. To better understand the influence of PPCP mixtures on fish, Atlantic cod (Gadus morhua) were caged for one month in 3 locations: site 1 (reference), site 2 (WWTP discharge), and site 3 (6.7 km west of discharge). Transcriptomic profiling was conducted in the brains of exposed fish and detection of PPCPs in WWTP effluent and muscle fillets were determined. Caffeine (47.8 ng/L), benzotriazole (10.9 ng/L), N,N-diethyl-meta-toluamide (DEET) (5.6 ng/L), methyl-1H-benzotriazole (5.5 ng/L), trimethoprim (3.4 ng/L), carbamazepine (2.1 ng/L), and nortriptyline (0.4 ng/L) were detected in the WWTP effluent. Octocrylene concentrations were observed in muscle tissue at all sites and ranged from 53 to 193 ng/g. Nervous system function and endocrine system disorders were the top enriched disease and function pathways predicted in male and female fish at site 2, with the top shared canonical pathways involved with estrogen receptor and Sirtuin signaling. At the discharge site, predicted disease and functional responses in female brains were involved in cellular assembly, organization, and function, tissue development, and nervous system development, whereas male brains were involved in connective tissue development, function, and disorders, nervous system development and function, and neurological disease. The top shared canonical pathways in females and males were involved in fatty acid activation and tight junction signaling. This study suggests that pseudopersistent, chronic exposure of native juvenile Atlantic cod from this ecosystem to PPCPs may alter neuroendocrine and neuron development.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2023.169110","usgsCitation":"Magnuson, J.T., Sydnes, M.O., Raeder, E.M., Schlenk, D., and Pampanin, D.M., 2024, Transcriptomic profiles of brains in juvenile Atlantic cod (Gadus morhua) exposed to pharmaceuticals and personal care products from a wastewater treatment plant discharge: Science of the Total Environment, v. 912, 169110, 10 p., https://doi.org/10.1016/j.scitotenv.2023.169110.","productDescription":"169110, 10 p.","ipdsId":"IP-158382","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":424280,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Norway","city":"Stavanger","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 5.189191946629705,\n 59.15422889863524\n ],\n [\n 5.189191946629705,\n 58.93276153443935\n ],\n [\n 5.832419933115403,\n 58.93276153443935\n ],\n [\n 5.832419933115403,\n 59.15422889863524\n ],\n [\n 5.189191946629705,\n 59.15422889863524\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"912","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Magnuson, Jason Tyler 0000-0001-6841-8014","orcid":"https://orcid.org/0000-0001-6841-8014","contributorId":329838,"corporation":false,"usgs":true,"family":"Magnuson","given":"Jason","email":"","middleInitial":"Tyler","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":891876,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sydnes, Magne O.","contributorId":333084,"corporation":false,"usgs":false,"family":"Sydnes","given":"Magne","email":"","middleInitial":"O.","affiliations":[{"id":79723,"text":"University of Stavanger","active":true,"usgs":false}],"preferred":false,"id":891877,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Raeder, Erik Magnus","contributorId":333085,"corporation":false,"usgs":false,"family":"Raeder","given":"Erik","email":"","middleInitial":"Magnus","affiliations":[{"id":40295,"text":"Norwegian University of Life Sciences","active":true,"usgs":false}],"preferred":false,"id":891878,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schlenk, Daniel","contributorId":221106,"corporation":false,"usgs":false,"family":"Schlenk","given":"Daniel","email":"","affiliations":[{"id":12655,"text":"University of California, Riverside","active":true,"usgs":false}],"preferred":false,"id":891879,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pampanin, Daniela M.","contributorId":333086,"corporation":false,"usgs":false,"family":"Pampanin","given":"Daniela","email":"","middleInitial":"M.","affiliations":[{"id":79723,"text":"University of Stavanger","active":true,"usgs":false}],"preferred":false,"id":891880,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70254312,"text":"70254312 - 2024 - Global seismic networks operated by the U.S. Geological Survey","interactions":[],"lastModifiedDate":"2024-05-17T12:06:38.850435","indexId":"70254312","displayToPublicDate":"2023-11-29T07:03:17","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Global seismic networks operated by the U.S. Geological Survey","docAbstract":"The U.S. Geological Survey (USGS) Global Seismographic Network (GSN) Program operates two thirds of the GSN, a network of state‐of‐the‐art, digital seismological and geophysical sensors with digital telecommunications. This network serves as a multiuse scientific facility and a valuable resource for research, education, and monitoring. The other one third of the GSN is funded by the National Science Foundation (NSF), and the operations of this component are overseen by EarthScope. This collaboration between the USGS, EarthScope, and NSF has allowed for the development and operations of the GSN to be a truly multiuse network that provides near real‐time open access data, facilitating fundamental discoveries by the Earth science community, supporting the earthquake hazards mission of the USGS, benefitting tsunami monitoring by the National Oceanic and Atmospheric Administration, and contributing to nuclear test monitoring and treaty verification. In this article, we describe the installation and evolution of the seismic networks operated by the USGS that ultimately led to the USGS portion of the GSN (100 stations under network codes IU, IC, and CU) as they are today and envision technological advances and opportunities to further improve the utility of the network in the future. This article focuses on the USGS‐operated component of the GSN; a companion article on the GSN stations funded by the NSF and operated by the Cecil and Ida Green Institute of Geophysics and Planetary Physics, Scripps Institution of Oceanography, University of California at San Diego by Davis et al. (2023) appears in this volume.
Managers can modify river flow regimes using fish monitoring data to minimize impacts from water management infrastructure. For example, operation of the gate-controlled Delta Cross Channel (DCC) in California can negatively affect the endangered Sacramento River winter-run Chinook Salmon Oncorhynchus tshawytscha. Although guidelines have been developed for DCC operations by using real-time juvenile fish sampling count data, there is uncertainty about how environmental conditions influence fish occupancy and the extent to which those relationships are affected by sampling and identification error.
We evaluated the effect of environmental conditions, imperfect detection, and misidentification error on salmon occupancy by analyzing data using hierarchical multistate occupancy models. A total of 14,147 trawl tows and beach seine hauls were conducted on 1058 sampling days between October and December from 1996 to 2019. During these surveys, 2803 juvenile winter-run Chinook Salmon were identified, and approximately 29% of the sampling days had at least one winter-run juvenile detected.
The probability of misidentifying an individual juvenile winter-run Chinook Salmon in the field was estimated to be 0.056 based on fish identification examinations and genetic sampling. Occupancy varied considerably and was related to flow characteristics, water clarity, weather, time of year, and whether occupancy was detected during the previous sampling day. However, these relationships and their significance changed considerably when accounting for imperfect detection and the probability of misidentifying individual juvenile salmon. Detection was <0.3 under average sampling conditions during a single sample and was influenced by flow, water clarity, site, and volume sampled.
Our modeling results indicate that DCC gate closure decisions could occur on fewer days when imperfect detection and misidentification error are not accounted for. These findings demonstrate the need to account for identification and detection error while using monitoring data to assess factors influencing fish occupancy and inform future management decisions.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10974","usgsCitation":"Kirsch, J., Peterson, J., Duarte, A., Goodman, D., Goodman, A., Hugentobler, S., Meek, M., Perry, R., Smith, L., and Stuart, J., 2024, Imperfect detection and misidentification affect inferences from data informing water operation decisions: North American Journal of Fisheries Management, v. 44, no. 2, p. 335-358, https://doi.org/10.1002/nafm.10974.","productDescription":"24 p.","startPage":"335","endPage":"358","ipdsId":"IP-146813","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":441005,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.10974","text":"Publisher Index Page"},{"id":430148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-11-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Kirsch, Joseph E.","contributorId":338806,"corporation":false,"usgs":false,"family":"Kirsch","given":"Joseph E.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":903618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, James T. 0000-0002-7709-8590 james_peterson@usgs.gov","orcid":"https://orcid.org/0000-0002-7709-8590","contributorId":2111,"corporation":false,"usgs":true,"family":"Peterson","given":"James","email":"james_peterson@usgs.gov","middleInitial":"T.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903619,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duarte, Adam","contributorId":28492,"corporation":false,"usgs":false,"family":"Duarte","given":"Adam","affiliations":[{"id":6960,"text":"Department of Biology, Texas State University","active":true,"usgs":false}],"preferred":false,"id":903620,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goodman, Denise","contributorId":339306,"corporation":false,"usgs":false,"family":"Goodman","given":"Denise","email":"","affiliations":[],"preferred":false,"id":904033,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goodman, Andrew","contributorId":338810,"corporation":false,"usgs":false,"family":"Goodman","given":"Andrew","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":903621,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hugentobler, Sara","contributorId":338812,"corporation":false,"usgs":false,"family":"Hugentobler","given":"Sara","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":903622,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meek, Mariah","contributorId":260835,"corporation":false,"usgs":false,"family":"Meek","given":"Mariah","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":903623,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Perry, Russell W. 0000-0003-4110-8619","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":220177,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":903624,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Smith, Lori","contributorId":338817,"corporation":false,"usgs":false,"family":"Smith","given":"Lori","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":903625,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Stuart, Jeffrey","contributorId":338821,"corporation":false,"usgs":false,"family":"Stuart","given":"Jeffrey","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":903626,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70250145,"text":"70250145 - 2024 - Grizzly bear responses to restrictions of recreation in Yellowstone National Park","interactions":[],"lastModifiedDate":"2024-01-24T17:52:21.656037","indexId":"70250145","displayToPublicDate":"2023-11-20T09:37:56","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Grizzly bear responses to restrictions of recreation in Yellowstone National Park","docAbstract":"Avoiding humans will be more difficult and energetically costly for animals as outdoor recreation increases and people venture farther into wildland areas that provide high-quality habitat for wildlife. Restricting human access can be an attractive management tool to mitigate effects of human recreation activities on wildlife; however, the efficacy of such measures is rarely assessed. In 1982, Yellowstone National Park identified areas important to grizzly bears (Ursus arctos) to help protect critical grizzly bear habitat and reduce the likelihood of human injuries by bears. Referred to as bear management areas (BMAs), human access is restricted in these areas for 2–8 months each year, with timing and type of restrictions varying by area. We examined 2 datasets to evaluate grizzly bear selection of BMAs and differences of bear density in BMAs and non-BMAs. First, we used 17 years of recent global positioning system telemetry data for grizzly bears to assess their selection of BMAs during periods when human access was allowed, and when access was restricted. We used step-selection functions to test the hypothesis that bears spend time in places that allow them to avoid people and select quality food sources. There was support that grizzly bears differentially select for BMAs regardless of whether human access was restricted at the time, compared with areas outside BMAs, and that selection changed with sex and season. Only males during the summer and hyperphagic seasons changed their selection of BMAs based on whether access restrictions were in place, and overall, male bears preferred unrestricted BMAs (BMAs without restrictions in place). Females preferentially selected BMAs regardless of whether the area had access restrictions in place only during the mating season. Individuals varied widely in their preference for BMAs and access restrictions. Bears likely choose to spend time in BMAs based on available food resources rather than restrictions to human access. Supporting this interpretation, our analyses indicated that a greater proportion of BMA in an area was associated with higher densities of grizzly bear. Thus, restrictions to human access likely help reduce the potential for human–bear interactions, accomplishing one of the original objectives for establishing the BMAs.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22527","usgsCitation":"Loggers, E., Litt, A.R., van Manen, F.T., Haroldson, M.A., and Gunther, K.A., 2024, Grizzly bear responses to restrictions of recreation in Yellowstone National Park: Journal of Wildlife Management, v. 88, no. 2, e22527, 25 p., https://doi.org/10.1002/jwmg.22527.","productDescription":"e22527, 25 p.","ipdsId":"IP-154494","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":441023,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22527","text":"Publisher Index Page"},{"id":422836,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.10748291015625,\n 44.12702800650004\n ],\n [\n -109.98138427734375,\n 44.1289994645142\n ],\n [\n -109.98687744140624,\n 44.33367180085156\n ],\n [\n -110.03631591796875,\n 44.34152959888481\n ],\n [\n -110.04730224609375,\n 44.3906169787868\n ],\n [\n -110.00885009765625,\n 44.422011314236634\n ],\n [\n -109.98138427734375,\n 44.50825885600572\n ],\n [\n -110.028076171875,\n 44.52196830685208\n ],\n [\n -110.1104736328125,\n 44.50825885600572\n ],\n [\n -110.12969970703125,\n 44.53371669765759\n ],\n [\n -110.07476806640625,\n 44.56503415498704\n ],\n [\n -110.0225830078125,\n 44.58655513209543\n ],\n [\n -109.84954833984375,\n 44.61784415342067\n ],\n [\n -109.80010986328124,\n 44.71161010858431\n ],\n [\n -109.84405517578125,\n 44.75258502192499\n ],\n [\n -109.90997314453125,\n 44.813018740612776\n ],\n [\n -109.9127197265625,\n 44.89868701215517\n ],\n [\n -109.9346923828125,\n 44.97839955494438\n ],\n [\n -109.96490478515625,\n 45.017243565102596\n ],\n [\n -110.00885009765625,\n 45.06770141120143\n ],\n [\n -110.06378173828125,\n 45.05412098425883\n ],\n [\n -110.13519287109374,\n 45.042478050891546\n ],\n [\n -110.69549560546874,\n 45.04053733158769\n ],\n [\n -110.775146484375,\n 45.079339209738094\n ],\n [\n -110.82183837890625,\n 45.06964120886863\n ],\n [\n -110.86578369140625,\n 45.04635929200553\n ],\n [\n -110.89874267578124,\n 45.0502402697946\n ],\n [\n -110.928955078125,\n 45.08127861241874\n ],\n [\n -110.9619140625,\n 45.09679146394738\n ],\n [\n -111.005859375,\n 45.10842333769411\n ],\n [\n -111.0333251953125,\n 45.10260769705975\n ],\n [\n -111.060791015625,\n 45.10066901851988\n ],\n [\n -111.0992431640625,\n 45.11811475546806\n ],\n [\n -111.126708984375,\n 45.120052841530516\n ],\n [\n -111.15966796875,\n 45.089035564831036\n ],\n [\n -111.181640625,\n 45.059941562221226\n ],\n [\n -111.11846923828125,\n 45.01918507438176\n ],\n [\n -111.10748291015625,\n 44.12702800650004\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"88","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Loggers, Elise","contributorId":331713,"corporation":false,"usgs":false,"family":"Loggers","given":"Elise","email":"","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":888556,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Litt, Andrea R.","contributorId":208358,"corporation":false,"usgs":false,"family":"Litt","given":"Andrea","email":"","middleInitial":"R.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":888557,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":888558,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haroldson, Mark A. 0000-0002-7457-7676 mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":888559,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gunther, Kerry A.","contributorId":84621,"corporation":false,"usgs":false,"family":"Gunther","given":"Kerry","email":"","middleInitial":"A.","affiliations":[{"id":5118,"text":"Yellowstone National Park, Yellowstone Center for Resources, Bear Management Office, P.O. Box 168, Yellowstone National Park, WY 82190","active":true,"usgs":false}],"preferred":false,"id":888560,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70254770,"text":"70254770 - 2024 - Genomic insights into isolation of the threatened Florida crested caracara (Caracara plancus)","interactions":[],"lastModifiedDate":"2024-06-07T11:51:38.687513","indexId":"70254770","displayToPublicDate":"2023-10-14T06:47:40","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2333,"text":"Journal of Heredity","active":true,"publicationSubtype":{"id":10}},"title":"Genomic insights into isolation of the threatened Florida crested caracara (Caracara plancus)","docAbstract":"We conducted a population genomic study of the crested caracara (Caracara plancus) using samples (n = 290) collected from individuals in Florida, Texas, and Arizona, United States. Crested caracaras are non-migratory raptors ranging from the southern tip of South America to the southern United States, including a federally protected relict population in Florida long thought to have been isolated since the last ice age. Our objectives were to evaluate genetic diversity and population structure of Florida’s apparently isolated population and to evaluate taxonomic relationships of crested caracaras at the northern edge of their range. Using DNA purified from blood samples, we conducted double-digest restriction site associated DNA sequencing and sequenced the mitochondrial ND2 gene. Analyses of population structure using over 9,000 SNPs suggest that two major clusters are best supported, one cluster including only Florida individuals and the other cluster including Arizona and Texas individuals. Both SNPs and mitochondrial haplotypes reveal the Florida population to be highly differentiated genetically from Arizona and Texas populations, whereas, Arizona and Texas populations are moderately differentiated from each other. The Florida population’s mitochondrial haplotypes form a separate monophyletic group, while Arizona and Texas populations share mitochondrial haplotypes. Results of this study provide substantial genetic evidence that Florida’s crested caracaras have experienced long-term isolation from caracaras in Arizona and Texas and thus, represent a distinct evolutionary lineage possibly warranting distinction as an Evolutionarily Significant Unit (ESU) or subspecies. This study will inform conservation strategies focused on long-term survival of Florida’s distinct, panmictic population.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/jhered/esad057","usgsCitation":"Payne, N., Erwin, J.A., Morrison, J.L., Dwyer, J.F., and Culver, M., 2024, Genomic insights into isolation of the threatened Florida crested caracara (Caracara plancus): Journal of Heredity, v. 115, no. 1, p. 45-56, https://doi.org/10.1093/jhered/esad057.","productDescription":"12 p.","startPage":"45","endPage":"56","ipdsId":"IP-157635","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":498479,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10150/671235","text":"External Repository"},{"id":429624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"115","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-10-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Payne, Natalie","contributorId":287191,"corporation":false,"usgs":false,"family":"Payne","given":"Natalie","email":"","affiliations":[{"id":40855,"text":"UA","active":true,"usgs":false}],"preferred":false,"id":902557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erwin, John A.","contributorId":275259,"corporation":false,"usgs":false,"family":"Erwin","given":"John","email":"","middleInitial":"A.","affiliations":[{"id":40855,"text":"UA","active":true,"usgs":false}],"preferred":false,"id":902558,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morrison, Joan L.","contributorId":169993,"corporation":false,"usgs":false,"family":"Morrison","given":"Joan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":902559,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dwyer, James F.","contributorId":169992,"corporation":false,"usgs":false,"family":"Dwyer","given":"James","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":902560,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Culver, Melanie 0000-0001-5380-3059 mculver@usgs.gov","orcid":"https://orcid.org/0000-0001-5380-3059","contributorId":197693,"corporation":false,"usgs":true,"family":"Culver","given":"Melanie","email":"mculver@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":902561,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70249268,"text":"70249268 - 2024 - Spatial variation in density of American black bears in northern Yellowstone National Park","interactions":[],"lastModifiedDate":"2023-12-04T17:20:03.177492","indexId":"70249268","displayToPublicDate":"2023-10-03T07:29:35","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16872,"text":"The Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Spatial variation in density of American black bears in northern Yellowstone National Park","docAbstract":"The quality and availability of resources are known to influence spatial patterns of animal density. In Yellowstone National Park, relationships between the availability of resources and the distribution of grizzly bears (Ursus arctos) have been explored but have yet to be examined in American black bears (Ursus americanus). We conducted non-invasive genetic sampling during 2017–2018 (mid-May to mid-July) and applied spatially explicit capture-recapture models to estimate density of black bears and examine associations with landscape features. In both years, density estimates were higher in forested vegetation communities, which provide food resources and thermal and security cover preferred by black bears, compared with non-forested areas. In 2017, density also varied by sex, with female densities being higher than males. Based on our estimates, the northern range of Yellowstone National Park supports one of the highest densities of black bears (20 black bears/100 km2) in the northern Rocky Mountains (6–12 black bears/100 km2 in other regions). Given these high densities, black bears could influence other wildlife populations more than previously thought, such as through displacement of sympatric predators from kills. Our study provides the first spatially explicit estimates of density for black bears within an ecosystem that contains the majority of North America's large mammal species. Our density estimates provide a baseline that can be used for future research and management decisions of black bears, including efforts to reduce human–bear conflicts.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.22497","usgsCitation":"Bowersock, N.R., Litt, A.R., Sawaya, M.A., Gunther, K.A., and van Manen, F.T., 2024, Spatial variation in density of American black bears in northern Yellowstone National Park: The Journal of Wildlife Management, v. 88, no. 1, e22497, 16 p., https://doi.org/10.1002/jwmg.22497.","productDescription":"e22497, 16 p.","ipdsId":"IP-152759","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":441146,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22497","text":"Publisher Index Page"},{"id":421535,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.03494952723108,\n 43.72561860928255\n ],\n [\n -106.75486658878216,\n 43.72561860928255\n ],\n [\n -106.75486658878216,\n 45.330355263304455\n ],\n [\n -110.03494952723108,\n 45.330355263304455\n ],\n [\n -110.03494952723108,\n 43.72561860928255\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"88","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-09-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Bowersock, Nathaniel R.","contributorId":268804,"corporation":false,"usgs":false,"family":"Bowersock","given":"Nathaniel","email":"","middleInitial":"R.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":884948,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Litt, Andrea R.","contributorId":208358,"corporation":false,"usgs":false,"family":"Litt","given":"Andrea","email":"","middleInitial":"R.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":884949,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sawaya, Michael A.","contributorId":330440,"corporation":false,"usgs":false,"family":"Sawaya","given":"Michael","email":"","middleInitial":"A.","affiliations":[{"id":78897,"text":"Sinopah Wildlife Research Associates","active":true,"usgs":false}],"preferred":false,"id":884950,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gunther, Kerry A.","contributorId":84621,"corporation":false,"usgs":false,"family":"Gunther","given":"Kerry","email":"","middleInitial":"A.","affiliations":[{"id":5118,"text":"Yellowstone National Park, Yellowstone Center for Resources, Bear Management Office, P.O. Box 168, Yellowstone National Park, WY 82190","active":true,"usgs":false}],"preferred":false,"id":884951,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":884952,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70270074,"text":"70270074 - 2024 - Stochastic simulation of earthquake ground motions for the seismic assessment of monumental masonry structures: Source-based vs site-based approaches","interactions":[],"lastModifiedDate":"2025-08-08T15:17:14.307712","indexId":"70270074","displayToPublicDate":"2023-09-28T10:13:06","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1434,"text":"Earthquake Engineering and Structural Dynamics","active":true,"publicationSubtype":{"id":10}},"title":"Stochastic simulation of earthquake ground motions for the seismic assessment of monumental masonry structures: Source-based vs site-based approaches","docAbstract":"Earthquakes are among the most destructive natural disasters and have resulted in a massive number of fatalities and economic losses all over the world. Simulated ground motion records are valuable, particularly for regions lacking seismic stations or with a limited history of large-magnitude earthquakes. Notably, a significant percentage of monumental masonry buildings are located in regions with limited access to real records; hence, simulated records play a paramount role in their seismic protection. However, few studies have investigated the structural response of heritage buildings via response history analyses to assess the performance of simulated earthquakes against real ones. To accomplish this, this study simulates the recorded time-series of the 9th of July 1998 Faial earthquake in the Azores (Mw = 6.2) at four available stations, using two different simulation approaches, that is, a source-based stochastic finite-fault method and a site-based broadband stochastic method. First, two masonry facades with sidewalls characterized by different slenderness levels are adopted to conduct this research. Moreover, the proposed approach is also applied to an existing monumental structure, that is, São Francisco Church, located at Horta, which was affected by damage during the Faial earthquake. Results demonstrate that both simulation approaches provide similar results in terms of structural response prediction. The proposed framework also demonstrates that a small mismatch in terms of predicted damage patterns can result in a significant relative error in terms of displacement predictions.
","language":"English","publisher":"Wiley","doi":"10.1002/eqe.4012","usgsCitation":"Karimzadeh, S., Funari, M., Szabó, S., Hussaini, S.M., Rezaeian, S., and Lourenço, P., 2024, Stochastic simulation of earthquake ground motions for the seismic assessment of monumental masonry structures: Source-based vs site-based approaches: Earthquake Engineering and Structural Dynamics, v. 53, no. 1, p. 303-330, https://doi.org/10.1002/eqe.4012.","productDescription":"28 p.","startPage":"303","endPage":"330","ipdsId":"IP-153599","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":494182,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eqe.4012","text":"Publisher Index Page"},{"id":493847,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Azores region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -33.14680988830381,\n 40.82334899248238\n ],\n [\n -33.14680988830381,\n 35.721016488135206\n ],\n [\n -21.995996591249934,\n 35.721016488135206\n ],\n [\n -21.995996591249934,\n 40.82334899248238\n ],\n [\n -33.14680988830381,\n 40.82334899248238\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"53","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-09-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Karimzadeh, Shaghayegh","contributorId":359419,"corporation":false,"usgs":false,"family":"Karimzadeh","given":"Shaghayegh","affiliations":[{"id":85799,"text":"University of Minho, Portugal","active":true,"usgs":false}],"preferred":false,"id":945297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Funari, Marco F.","contributorId":359424,"corporation":false,"usgs":false,"family":"Funari","given":"Marco F.","affiliations":[{"id":85802,"text":"School of Sustainability, Civil and Environmental Engineering, University of Surrey, Guildford, UK.","active":true,"usgs":false}],"preferred":false,"id":945298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Szabó, Simon","contributorId":359425,"corporation":false,"usgs":false,"family":"Szabó","given":"Simon","affiliations":[{"id":85803,"text":"Department of Civil Engineering, University of Minho, Institute for Sustainability and Innovation in Structural Engineering, ARISE, Guimarães, Portugal","active":true,"usgs":false}],"preferred":false,"id":945299,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hussaini, S. 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Sajad","affiliations":[{"id":85803,"text":"Department of Civil Engineering, University of Minho, Institute for Sustainability and Innovation in Structural Engineering, ARISE, Guimarães, Portugal","active":true,"usgs":false}],"preferred":false,"id":945300,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rezaeian, Sanaz 0000-0001-7589-7893","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":238513,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":945301,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lourenço, Paulo B.","contributorId":359427,"corporation":false,"usgs":false,"family":"Lourenço","given":"Paulo B.","affiliations":[{"id":85803,"text":"Department of Civil Engineering, University of Minho, Institute for Sustainability and Innovation in Structural Engineering, ARISE, Guimarães, Portugal","active":true,"usgs":false}],"preferred":false,"id":945302,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70251827,"text":"70251827 - 2024 - A comparison of summer, fall and winter estimates of monarch population size before and after milkweed eradication from crop fields in North America","interactions":[],"lastModifiedDate":"2024-03-01T12:44:57.250606","indexId":"70251827","displayToPublicDate":"2023-09-14T06:40:41","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2003,"text":"Insect Conservation and Diversity","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of summer, fall and winter estimates of monarch population size before and after milkweed eradication from crop fields in North America","docAbstract":"Scenario planning is a powerful approach for assessing restoration outcomes under alternative futures. However, developing plausible scenarios remains daunting in complex systems like ecological communities. Here, we used Bayesian multispecies occupancy modeling to develop scenarios to assess woodland restoration outcomes in afforested communities in seven wildlife management areas in Arkansas, U.S.A. Our objectives were (1) to define plausible woodland restoration and afforestation scenarios by quantifying historic ranges of variation in mean tree cover and tree cover heterogeneity from 1986 to 2021 and (2) to predict changes in bird species richness and occupancy patterns for six species of greatest conservation need under two future scenarios: complete afforestation (100% tree cover) and woodland restoration (based on remotely sensed historic tree cover). Using 35 years of remotely sensed tree cover data and 6 years of bird monitoring data, we developed multispecies occupancy models to predict future bird species richness and occupancy under the complete afforestation and woodland restoration scenarios. Between 1986 and 2021, tree cover increased in all study areas—with one increasing 70%. Under the woodland restoration scenario, avian species richness increased up to 20%, and four of six species of greatest conservation need exhibited gains in occupancy probability. The complete afforestation scenario had negligible effects on richness and occupancy. Overall, we found decreasing tree cover to historic levels prior to widespread afforestation would provide community-level benefits and would do little harm even to forest-dependent species of conservation concern. Applying multispecies occupancy modeling within a scenario planning framework allows for comparing multiscale trade-offs between plausible futures.
The federally endangered Cape Sable seaside sparrow (Ammospiza maritima mirabilis) is endemic to the Greater Everglades ecosystem in southern Florida, inhabiting fragmented marl prairies in six individual subpopulations. The subspecies is threatened by loss of breeding habitat from fire and water management. Genetic information is severely limited for the subspecies but could help inform decisions regarding subpopulation protections and potential translocations for genetic rescue. To provide genetic data and inform management efforts, feather samples were collected across five subpopulations (designated A–E) and protocols were tested to optimize DNA extraction yields. We assessed four mitochondrial DNA markers (N = 36–69) and 12 nuclear microsatellite loci (N = 55) in 108 sparrows. Mitochondrial DNA sequences revealed low haplotype diversity, with NADH dehydrogenase-2 haplotypes matching to most other extant subspecies and to the Atlantic coast subspecies. Nuclear diversity was low compared to other subspecies, but similar across subpopulations. Samples grouped as one population when analyzed by Principal Component Analysis, Bayesian modelling and genetic distance metrics. Limited genetic emigration was detected from one putative migrant. Relatedness was significantly different for sparrows in the most geographically distant subpopulation (A), likely reflecting high self-recruitment and natal site fidelity (P = 0.003). The low to moderate effective population size (NE = 202.4; NE:NC = 0.06) and generation time estimates indicated that unique genetic variation could be lost quickly during stochastic events. The sample sizes were limited, which reduced the power to comprehensively address recent population size reductions and any subsequent loss of genetic diversity.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10592-023-01551-0","usgsCitation":"Beaver, C., Virzi, T., and Hunter, M., 2024, Genetic analysis of federally endangered Cape Sable seaside sparrow subpopulations in the Greater Everglades, USA: Conservation Genetics, v. 25, p. 101-116, https://doi.org/10.1007/s10592-023-01551-0.","productDescription":"16 p.; Data Release","startPage":"101","endPage":"116","ipdsId":"IP-129514","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":441213,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10592-023-01551-0","text":"Publisher Index Page"},{"id":420243,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NYGMI1","linkFileType":{"id":5,"text":"html"}},{"id":420152,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.92502664678194,\n 26.153665277276858\n ],\n [\n -81.92502664678194,\n 24.937300882586968\n ],\n [\n -80.0519651651226,\n 24.937300882586968\n ],\n [\n -80.0519651651226,\n 26.153665277276858\n ],\n [\n -81.92502664678194,\n 26.153665277276858\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"25","noUsgsAuthors":false,"publicationDate":"2023-08-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Beaver, Caitlin 0000-0002-9269-7604","orcid":"https://orcid.org/0000-0002-9269-7604","contributorId":219703,"corporation":false,"usgs":true,"family":"Beaver","given":"Caitlin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":881149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Virzi, Thomas","contributorId":328736,"corporation":false,"usgs":false,"family":"Virzi","given":"Thomas","email":"","affiliations":[{"id":78474,"text":"Conservation InSight","active":true,"usgs":false}],"preferred":false,"id":881150,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunter, Margaret 0000-0002-4760-9302","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":214958,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":881151,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}