Transcriptomic data has demonstrated utility to advance the study of physiological diversity and organisms’ responses to environmental stressors. However, a lack of genomic resources and challenges associated with collecting high-quality RNA can limit its application for many wild populations. Minimally invasive blood sampling combined with de novo transcriptomic approaches has great potential to alleviate these barriers. Here, we advance these goals for marine turtles by generating high quality de novo blood transcriptome assemblies to characterize functional diversity and compare global transcriptional profiles between tissues, species, and foraging aggregations.
We generated high quality blood transcriptome assemblies for hawksbill (Eretmochelys imbricata), loggerhead (Caretta caretta), green (Chelonia mydas), and leatherback (Dermochelys coriacea) turtles. The functional diversity in assembled blood transcriptomes was comparable to those from more traditionally sampled tissues. A total of 31.3% of orthogroups identified were present in all four species, representing a core set of conserved genes expressed in blood and shared across marine turtle species. We observed strong species-specific expression of these genes, as well as distinct transcriptomic profiles between green turtle foraging aggregations that inhabit areas of greater or lesser anthropogenic disturbance.
Obtaining global gene expression data through non-lethal, minimally invasive sampling can greatly expand the applications of RNA-sequencing in protected long-lived species such as marine turtles. The distinct differences in gene expression signatures between species and foraging aggregations provide insight into the functional genomics underlying the diversity in this ancient vertebrate lineage. The transcriptomic resources generated here can be used in further studies examining the evolutionary ecology and anthropogenic impacts on marine turtles.
","language":"English","publisher":"Springer Nature","doi":"10.1186/s12864-021-07656-5","usgsCitation":"Banjeree, S.M., Adkins Stoll, J., Allen, C.D., Lynch, J., Harris, H.S., Kenyon, L., Connon, R.E., Sterling, E.J., Naro-Maciel, E., McFadden, K., Lamont, M., Benge, J., Fernandez, N.B., Seminoff, J.A., Benson, S., Lewison, R.L., Eguchi, T., Summers, T.M., Hapdei, J.R., Rice, M.R., Martin, S., Jones, T., Dutton, P., Balazs, G., and Komoroske, L.M., 2021, Species and population specific gene expression in blood transcriptomes of marine turtles: BMC Genomics, v. 22, 346, 16 p., https://doi.org/10.1186/s12864-021-07656-5.","productDescription":"346, 16 p.","ipdsId":"IP-122805","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":452271,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s12864-021-07656-5","text":"Publisher Index 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Although many PM case studies have been published, few efforts have sought to systematically describe and understand dominant PM processes or establish best practices for PM. As a first step, we have reviewed a random sample of environmental PM case study articles (n = 60) using a novel PM process evaluation instrument. We found that significant work likely remains for PM to fully support participatory and integrated planning processes. While PM reports systematically address knowledge integration and learning, they often neglect the facilitation of a multi-value perspective within a democratic process, and the integration across organizations within a governance system. If not reported, we suspect these aspects are also neglected in practice. We conclude with key research and practice issues for improving PM as an approach for real-world participatory planning and governance.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2021.105073","usgsCitation":"Hedelin, B., Gray, S., Woehlke, S., BenDor, T., Singer, A., Jordan, R., Zellner, M., Giabbanelli, P., Glynn, P., Jenni, K., Jetter, A., Kolgani, N., Laursen, B., Leong, K.M., Schmitt Olabisi, L., and Sterling, E., 2021, What's left before participatory modeling can fully support real-world environmental planning processes: A case study review: Environmental Modelling & Software, v. 143, 105073, 15 p., https://doi.org/10.1016/j.envsoft.2021.105073.","productDescription":"105073, 15 p.","ipdsId":"IP-129309","costCenters":[],"links":[{"id":452273,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2021.105073","text":"Publisher Index Page"},{"id":389153,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"143","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hedelin, B.","contributorId":265685,"corporation":false,"usgs":false,"family":"Hedelin","given":"B.","affiliations":[],"preferred":false,"id":823192,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gray, S.","contributorId":265686,"corporation":false,"usgs":false,"family":"Gray","given":"S.","email":"","affiliations":[],"preferred":false,"id":823193,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woehlke, S.","contributorId":265687,"corporation":false,"usgs":false,"family":"Woehlke","given":"S.","email":"","affiliations":[],"preferred":false,"id":823194,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"BenDor, T. 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Despite known socio-environmental effects of EAG there remains a need to enhance monitoring capabilities for better informing conservation and management practices. Here, we integrate field observations, remote sensing and climate data with machine-learning techniques to estimate and assess patterns of historical (1985–2019; R2 = 0.86 ± 0.05; MAE = 6.7 ± 1.4%), present (2020), and future (2025–2040) EAG abundance (30-m) across much of the western United States. Trend analysis revealed that ∼8% and 1% of the landscape experienced significant rises and declines in historical EAG cover, respectively, with hotspots of invasion generally occurring near roads and along low-to-mid elevation gradients with warmer and drier conditions. Accurate simulations of the response of EAG to changing environmental conditions, disturbances and management treatments indicate that ecosystem resistance to invasion is largely controlled by long-term EAG abundance (surrogate for seed bank), time since and frequency of wildfire, and plant community interactions. Ecological thresholds associated with enhanced probabilities of wildfire occurrence and invasion rates indicate that relatively little (10%) EAG cover is needed to heighten these risks. Climate change is expected to push 8% of the landscape across invasion thresholds by 2040, impacting 6% of existing sage-grouse habitat, and we identify where fuel breaks may be placed to reduce wildfire risks and invasion. Spatially detailed, timely, and accurate depictions of past, present, and future EAG abundance are vital for the protection of life and property and the continued stewardship of sagebrush ecosystems.
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Franke College of Forestry and Conservation University of Montana, Missoula","active":true,"usgs":false}],"preferred":false,"id":840915,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Parajuli, Sujan 0000-0002-1652-3063","orcid":"https://orcid.org/0000-0002-1652-3063","contributorId":222684,"corporation":false,"usgs":true,"family":"Parajuli","given":"Sujan","email":"","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":840916,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wu, Zhuoting 0000-0001-7393-1832 zwu@usgs.gov","orcid":"https://orcid.org/0000-0001-7393-1832","contributorId":4953,"corporation":false,"usgs":true,"family":"Wu","given":"Zhuoting","email":"zwu@usgs.gov","affiliations":[{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":840917,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70220443,"text":"70220443 - 2021 - Trophic transfer efficiency in the Lake Superior food web: Assessing the impacts of non-native species","interactions":[],"lastModifiedDate":"2021-08-03T16:11:08.337078","indexId":"70220443","displayToPublicDate":"2021-05-13T08:05:48","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Trophic transfer efficiency in the Lake Superior food web: Assessing the impacts of non-native species","docAbstract":"Ecosystem-based management relies on understanding how perturbations influence ecosystem structure and function (e.g., invasive species, exploitation, abiotic changes). However, data on unimpacted systems are scarce; therefore, we often rely on impacted systems to make inferences about ‘natural states.’ Among the Laurentian Great Lakes, Lake Superior provides a unique case study to address non-native species impacts because the food web is dominated by native species. Additionally, Lake Superior is both vertically (benthic versus pelagic) and horizontally (nearshore versus offshore) structured by depth, providing an opportunity to compare the function of these sub-food webs. We developed an updated Lake Superior EcoPath model using data from the 2005/2006 lake-wide multi-agency surveys covering multiple trophic levels. We then compared trophic transfer efficiency (TTE) to previously published EcoPath models. Finally, we compared ecosystem function of the 2005/2006 ecosystem to that with non-native linkages removed and compared native versus non-native species-specific approximations of TTE and trophic flow. Lake Superior was relatively efficient (TTE = 0.14) compared to systems reported in a global review (average TTE = 0.09), and the microbial loop was highly efficient (TTE > 0.20). Non-native species represented a very small proportion (<0.01%) of total biomass and were generally more efficient and had higher trophic flow compared to native species. Our results provide valuable insight into the importance of the microbial loop and represent a baseline estimate of non-native species impacts on Lake Superior. Finally, this work is a starting point for further model development to predict future changes in the Lake Superior ecosystem.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2021.04.010","usgsCitation":"Mathias, B.G., Hrabik, T.R., Hoffman, J.C., Gorman, O., Seider, M., Sierszen, M.E., Vinson, M., Yule, D.L., and Yurista, P.M., 2021, Trophic transfer efficiency in the Lake Superior food web: Assessing the impacts of non-native species: Journal of Great Lakes Research, v. 47, no. 4, p. 1146-1158, https://doi.org/10.1016/j.jglr.2021.04.010.","productDescription":"13 p.","startPage":"1146","endPage":"1158","ipdsId":"IP-115192","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":452278,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9067395","text":"External Repository"},{"id":436366,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9W93YXH","text":"USGS data release","linkHelpText":"Compilation of Data for Parameterization of an Ecopath Model of Lake Superior at the Beginning of the 21st Century (2001-2016)"},{"id":385642,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.63671874999997,\n 46.195042108660154\n ],\n [\n -83.84765624999997,\n 46.195042108660154\n ],\n [\n -83.84765624999997,\n 49.83798245308484\n ],\n [\n -92.63671874999997,\n 49.83798245308484\n ],\n [\n -92.63671874999997,\n 46.195042108660154\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mathias, Bryan G.","contributorId":240743,"corporation":false,"usgs":false,"family":"Mathias","given":"Bryan","email":"","middleInitial":"G.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":815547,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hrabik, Thomas R.","contributorId":35614,"corporation":false,"usgs":false,"family":"Hrabik","given":"Thomas","email":"","middleInitial":"R.","affiliations":[{"id":6915,"text":"University of Minnesota - Duluth","active":true,"usgs":false}],"preferred":false,"id":815548,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoffman, Joel C.","contributorId":84244,"corporation":false,"usgs":false,"family":"Hoffman","given":"Joel","email":"","middleInitial":"C.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":815549,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gorman, Owen 0000-0003-0451-110X","orcid":"https://orcid.org/0000-0003-0451-110X","contributorId":216889,"corporation":false,"usgs":true,"family":"Gorman","given":"Owen","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":815550,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Seider, Michael J.","contributorId":258016,"corporation":false,"usgs":false,"family":"Seider","given":"Michael J.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":815551,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sierszen, Michael E.","contributorId":63320,"corporation":false,"usgs":false,"family":"Sierszen","given":"Michael","email":"","middleInitial":"E.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":815552,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vinson, Mark R. 0000-0001-5256-9539 mvinson@usgs.gov","orcid":"https://orcid.org/0000-0001-5256-9539","contributorId":3800,"corporation":false,"usgs":true,"family":"Vinson","given":"Mark","email":"mvinson@usgs.gov","middleInitial":"R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":815553,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yule, Daniel L. 0000-0002-0117-5115","orcid":"https://orcid.org/0000-0002-0117-5115","contributorId":248693,"corporation":false,"usgs":true,"family":"Yule","given":"Daniel","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":815554,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yurista, Peder M.","contributorId":127358,"corporation":false,"usgs":false,"family":"Yurista","given":"Peder","email":"","middleInitial":"M.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":815555,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70220492,"text":"70220492 - 2021 - Biogeography and ecology of Ostracoda in the U.S. northern Bering, Chukchi, and Beaufort Seas","interactions":[],"lastModifiedDate":"2021-05-17T12:47:37.844807","indexId":"70220492","displayToPublicDate":"2021-05-13T07:39:46","publicationYear":"2021","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":"Biogeography and ecology of Ostracoda in the U.S. northern Bering, Chukchi, and Beaufort Seas","docAbstract":"Ostracoda (bivalved Crustacea) comprise a significant part of the benthic meiofauna in the Pacific-Arctic region, including more than 50 species, many with identifiable ecological tolerances. These species hold potential as useful indicators of past and future ecosystem changes. In this study, we examined benthic ostracodes from nearly 300 surface sediment samples, >34,000 specimens, from three regions—the northern Bering, Chukchi and Beaufort Seas—to establish species’ ecology and distribution. Samples were collected during various sampling programs from 1970 through 2018 on the continental shelves at 20 to ~100m water depth. Ordination analyses using species’ relative frequencies identified six species, Normanicythere leioderma, Sarsicytheridea bradii, Paracyprideis pseudopunctillata, Semicytherura complanata, Schizocythere ikeyai, and Munseyella mananensis, as having diagnostic habitat ranges in bottom water temperatures, salinities, sediment substrates and/or food sources. Species relative abundances and distributions can be used to infer past bottom environmental conditions in sediment archives for paleo-reconstructions and to characterize potential changes in Pacific-Arctic ecosystems in future sampling studies. Statistical analyses further showed ostracode assemblages grouped by the summer water masses influencing the area. Offshore-to-nearshore transects of samples across different water masses showed that complex water mass characteristics, such as bottom temperature, productivity, as well as sediment texture, influenced the relative frequencies of ostracode species over small spatial scales. On the larger biogeographic scale, synoptic ordination analyses showed dominant species—N. leioderma (Bering Sea), P. pseudopunctillata (offshore Chukchi and Beaufort Seas), and S. bradii (all regions)—remained fairly constant over recent decades. However, during 2013–2018, northern Pacific species M. mananensis and S. ikeyai increased in abundance by small but significant proportions in the Chukchi Sea region compared to earlier years. It is yet unclear if these assemblage changes signify a meiofaunal response to changing water mass properties and if this trend will continue in the future. Our new ecological data on ostracode species and biogeography suggest these hypotheses can be tested with future benthic monitoring efforts.
Cyclic climatic and glacial fluctuations of the Late Quaternary produced a dynamic biogeographic history for high latitudes. To refine our understanding of this history in northwestern North America, we explored geographic structure in a wide-ranging carnivore, the wolverine (Gulo gulo). We examined genetic variation in populations across mainland Alaska, coastal Southeast Alaska, and mainland western Canada using nuclear microsatellite genotypes and sequence data from the mitochondrial DNA (mtDNA) control region and Cytochrome b (Cytb) gene. Data from maternally inherited mtDNA reflect stable populations in Northwest Alaska, suggesting the region harbored wolverine populations since at least the Last Glacial Maximum (LGM; 21 Kya), consistent with their persistence in the fossil record of Beringia. Populations in Southeast Alaska are characterized by minimal divergence, with no genetic signature of long-term refugial persistence (consistent with the lack of pre-Holocene fossil records there). The Kenai Peninsula population exhibits mixed signatures depending on marker type: mtDNA data indicate stability (i.e., historical persistence) and include a private haplotype, whereas biparentally inherited microsatellites exhibit relatively low variation and a lack of private alleles consistent with a more recent Holocene colonization of the peninsula. Our genetic work is largely consistent with the early 20th century taxonomic hypothesis that wolverines on the Kenai Peninsula belong to a distinct subspecies. Our finding of significant genetic differentiation of wolverines inhabiting the Kenai Peninsula, coupled with the peninsula’s burgeoning human population and the wolverine’s known sensitivity to anthropogenic impacts, provides valuable foundational data that can be used to inform conservation and management prescriptions for wolverines inhabiting these landscapes.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/jmammal/gyab045","usgsCitation":"Krejsa, D.M., Talbot, S.L., Sage, G.K., Sonsthagen, S.A., Jung, T.S., Magoun, A., and Cook, J.A., 2021, Dynamic landscapes in northwestern North America structured populations of wolverines (Gulo gulo): Journal of Mammology, v. 102, no. 3, p. 891-908, https://doi.org/10.1093/jmammal/gyab045.","productDescription":"18 p.","startPage":"891","endPage":"908","ipdsId":"IP-117178","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":452282,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyab045","text":"Publisher Index Page"},{"id":436367,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P908DV91","text":"USGS data release","linkHelpText":"Genetic Data from Wolverine (Gulo gulo) of North America"},{"id":386135,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Russia, United States","state":"Alaska, British Columbia, Northwest Territories, Nunavit, Yukon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -173.583984375,\n 64.28275952823394\n ],\n [\n -169.7607421875,\n 64.28275952823394\n ],\n [\n -169.7607421875,\n 67.13582938531948\n ],\n [\n -173.583984375,\n 67.13582938531948\n ],\n [\n -173.583984375,\n 64.28275952823394\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.908203125,\n 68.23682270936281\n ],\n [\n -111.181640625,\n 67.97463396204759\n ],\n [\n -120.234375,\n 69.80930869552193\n ],\n [\n -128.14453125,\n 70.67088107015755\n ],\n [\n 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ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":814570,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jung, Thomas S","contributorId":257552,"corporation":false,"usgs":false,"family":"Jung","given":"Thomas","email":"","middleInitial":"S","affiliations":[{"id":33063,"text":"Yukon Department of Environment","active":true,"usgs":false}],"preferred":false,"id":814571,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Magoun, Audrey J","contributorId":257553,"corporation":false,"usgs":false,"family":"Magoun","given":"Audrey J","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":814572,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cook, Joseph A.","contributorId":8323,"corporation":false,"usgs":false,"family":"Cook","given":"Joseph","email":"","middleInitial":"A.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":814573,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70221058,"text":"70221058 - 2021 - Intensity of grass invasion negatively correlated with population density and age structure of an endangered dune plant across its range","interactions":[],"lastModifiedDate":"2021-08-03T16:15:41.13252","indexId":"70221058","displayToPublicDate":"2021-05-12T10:44:59","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Intensity of grass invasion negatively correlated with population density and age structure of an endangered dune plant across its range","docAbstract":"Invasive species are a global threat to ecosystem biodiversity and function; non-native grass invasion has been particularly problematic in sparsely vegetated ecosystems such as open dunes. Native plant population responses to invasion, however, are infrequently translated to landscape scales, limiting the effectiveness of these data for addressing conservation issues. We quantified population density, total population size, and age class distribution of the federally-endangered plant species Antioch Dunes evening primrose (Oenothera deltoides subsp. howellii), at sites along a non-native grass invasion gradient in California, USA. We then scaled relationships between invasion and plant density across the species’ range using spatial models and remote sensing data. Adult and juvenile O. deltoides subsp. howellii densities were more than 10 times higher in non-invaded areas (grids with 10% total plant cover) when compared to highly-invaded areas (grids with 80% total plant cover). The ratio of O. deltoides subsp. howellii juveniles to adults decreased to less than 1 at 54% total cover, highlighting sensitivity of the regeneration niche to invasion. Spatial models mapped hotspots of O. deltoides subsp. howellii abundance and population structure across the landscape at sub-meter scales. Scaling the impacts of increasing invasion on plant species of conservation concern holds promise when coupled with remote sensing approaches, especially in naturally low-cover ecosystems where readily available metrics (e.g., Normalized Difference Vegetation Index) can be used to quantify invasion. These spatial models inform how future invasive species management may influence population size and spatial distribution of species of conservation concern.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10530-021-02516-5","usgsCitation":"Jones, S., Kennedy, A., Freeman, C.M., and Thorne, K., 2021, Intensity of grass invasion negatively correlated with population density and age structure of an endangered dune plant across its range: Biological Invasions, v. 23, p. 2451-2471, https://doi.org/10.1007/s10530-021-02516-5.","productDescription":"21 p.","startPage":"2451","endPage":"2471","ipdsId":"IP-126563","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":436368,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PRVA0M","text":"USGS data release","linkHelpText":"Antioch Dunes evening primrose (Oenothera deltoides subsp. howellii) juvenile and adult abundance across the known range, California, USA (2019)"},{"id":386030,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Antioch","otherGeospatial":"San Francisco Bay-Delta region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.92729949951172,\n 37.998597644907385\n ],\n [\n -121.6691207885742,\n 37.998597644907385\n ],\n [\n -121.6691207885742,\n 38.089174937729794\n ],\n [\n -121.92729949951172,\n 38.089174937729794\n ],\n [\n -121.92729949951172,\n 37.998597644907385\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","noUsgsAuthors":false,"publicationDate":"2021-05-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Scott 0000-0002-1056-3785","orcid":"https://orcid.org/0000-0002-1056-3785","contributorId":215602,"corporation":false,"usgs":true,"family":"Jones","given":"Scott","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":816666,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennedy, Anna 0000-0002-6530-7498","orcid":"https://orcid.org/0000-0002-6530-7498","contributorId":259164,"corporation":false,"usgs":true,"family":"Kennedy","given":"Anna","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":816667,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Freeman, Chase M. 0000-0003-4211-6709 cfreeman@usgs.gov","orcid":"https://orcid.org/0000-0003-4211-6709","contributorId":150052,"corporation":false,"usgs":true,"family":"Freeman","given":"Chase","email":"cfreeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":816668,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":816669,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70225649,"text":"70225649 - 2021 - Cross-ecosystem fluxes of pesticides from prairie wetlands mediated by aquatic insect emergence: Implications for terrestrial insectivores","interactions":[],"lastModifiedDate":"2021-10-29T14:20:46.124622","indexId":"70225649","displayToPublicDate":"2021-05-12T09:10:57","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Cross-ecosystem fluxes of pesticides from prairie wetlands mediated by aquatic insect emergence: Implications for terrestrial insectivores","docAbstract":"Contaminants alter the quantity and quality of insect prey available to terrestrial insectivores. In agricultural regions, the quantity of aquatic insects emerging from freshwaters can be impacted by insecticides originating from surrounding croplands. We hypothesized that, in such regions, adult aquatic insects could also act as vectors of pesticide transfer to terrestrial food webs. To estimate insect-mediated pesticide flux from wetlands embedded in an important agricultural landscape, semipermanetly and temporarily ponded wetlands were surveyed in cropland and grassland landscapes across a natural salinity gradient in the Prairie Pothole Region of North Dakota (USA) during the bird breeding season in 2015 and 2016 (n = 14 and 15 wetlands, respectively). Current-use pesticides, including the herbicide atrazine and the insecticides bifenthrin and imidacloprid, were detected in newly emerged insects. Pesticide detections were similar in insects emerging from agricultural and grassland wetlands. Biomass of emerging aquatic insects decreased 43%, and insect-mediated pesticide flux increased 50% along the observed gradient in concentrations of insecticides in emerging aquatic insects (from 3 to 577 ng total insecticide g–1 insect). Overall, adult aquatic insects were estimated to transfer between 2 and 180 µg total pesticide wetland–1 d–1 to the terrestrial ecosystem. In one of the 2 study years, biomass of emerging adult aquatic insects was also 73% lower from agricultural than grassland wetlands and was dependent on salinity. Our results suggest that accumulated insecticides reduce the availability of adult aquatic insect prey for insectivores and potentially increase insectivore exposure to insect-borne pesticides. Adult aquatic insects retain pesticides across metamorphosis and may expose insectivores living near both agricultural and grassland wetlands to dietary sources of toxic chemicals.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/etc.5111","usgsCitation":"Kraus, J.M., Kuivila, K., Hladik, M.L., Shook, N., Mushet, D., Dowdy, K., and Harrington, R., 2021, Cross-ecosystem fluxes of pesticides from prairie wetlands mediated by aquatic insect emergence: Implications for terrestrial insectivores: Environmental Toxicology and Chemistry, v. 40, no. 8, p. 2282-2296, https://doi.org/10.1002/etc.5111.","productDescription":"15 p.","startPage":"2282","endPage":"2296","ipdsId":"IP-103658","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":436369,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P971S7IV","text":"USGS data release","linkHelpText":"Adult aquatic insect emergence, insect pesticide concentrations and water chemistry of wetlands in the Prairie Pothole Region, North Dakota, USA, 2015-16"},{"id":391164,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alberta, Iowa, Manitoba, Minnesota, Montana, North Dakota, Saskatchewan, South Dakota","otherGeospatial":"Prairie Potholes region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.8564453125,\n 41.44272637767212\n ],\n [\n -93.6474609375,\n 44.809121700077355\n ],\n [\n -96.3720703125,\n 47.100044694025215\n ],\n [\n -98.26171875,\n 47.724544549099676\n ],\n [\n -98.7451171875,\n 50.3454604086048\n ],\n [\n -101.07421875,\n 51.890053935216926\n ],\n [\n -105.6005859375,\n 52.802761415419674\n ],\n [\n -112.763671875,\n 54.265224078605684\n ],\n [\n -115.4443359375,\n 54.87660665410869\n ],\n [\n -115.8837890625,\n 53.461890432859114\n ],\n [\n -114.12597656249999,\n 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Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":826056,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kuivila, Kathryn 0000-0001-7940-489X kkuivila@usgs.gov","orcid":"https://orcid.org/0000-0001-7940-489X","contributorId":190790,"corporation":false,"usgs":true,"family":"Kuivila","given":"Kathryn","email":"kkuivila@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826057,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":203857,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826058,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shook, Neil","contributorId":268174,"corporation":false,"usgs":false,"family":"Shook","given":"Neil","email":"","affiliations":[{"id":55580,"text":"5U.S. Fish and Wildlife Survey, Chase Lake Prairie Project Office, 5924 19th Street SE, Woodworth, ND","active":true,"usgs":false}],"preferred":false,"id":826059,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mushet, David M. 0000-0002-5910-2744","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":248468,"corporation":false,"usgs":true,"family":"Mushet","given":"David M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":826060,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dowdy, Kelen","contributorId":268175,"corporation":false,"usgs":false,"family":"Dowdy","given":"Kelen","email":"","affiliations":[{"id":55581,"text":"City of Greeley Water Resources, 1001 11th Avenue #200, Greeley, CO","active":true,"usgs":false}],"preferred":false,"id":826061,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harrington, Rachel","contributorId":268176,"corporation":false,"usgs":false,"family":"Harrington","given":"Rachel","affiliations":[{"id":55583,"text":"U.S. Environmental Protection Agency, Region 8, 1595 Wynkoop St., Denver, CO","active":true,"usgs":false}],"preferred":false,"id":826062,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70222453,"text":"70222453 - 2021 - Quick and dirty (and accurate) 3-D paleoseismic trench models using coded scale bars","interactions":[],"lastModifiedDate":"2021-11-01T15:38:15.192062","indexId":"70222453","displayToPublicDate":"2021-05-12T08:43:23","publicationYear":"2021","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":"Quick and dirty (and accurate) 3-D paleoseismic trench models using coded scale bars","docAbstract":"Structure‐from‐motion (SfM) modeling has dramatically increased the speed of generating geometrically accurate orthophoto mosaics of paleoseismic trenches, but some aspects of this technique remain time and labor intensive. Model accuracy relies on control points to establish scale, reduce distortion, and orient 3D models. Traditional SfM methods use total station or Global Navigation Satellite System (GNSS) surveys to constrain models, but collecting control points along a vertical trench wall is often inhibited by poor line of sight to the survey sensor or limited sky view and requires many hours in the field and office. We used physical scale bars printed with coded targets to constrain SfM models of a dusty, 46‐m‐long trench excavation across the Teton fault (Wyoming, U.S.A.). We present a workflow for generating quick and accurate 3D SfM models and orthophoto mosaics and compare the effectiveness of using scale bar, GNSS, and total‐station control in the models. Our results show that the scale bar model deviates from total station survey points by an average of 3.1 cm (maximum of 5.3 cm). In addition, the scale‐bar model only deviates an average of 1.7 cm (maximum 3.5 cm) when compared to the best model alternative, the SfM model controlled by the total station survey. Scale bars eliminate several hours needed to collect and incorporate control points from total station or GNSS surveys and significantly simplify the workflow, at the cost of slightly increased 3D model and orthophoto mosaic error. Our results further suggest that trench models can be constrained with at least four physical scale bars, but using five to six physical scale bars provides redundant control for field deployment and model optimization. The scale bar method for paleoseismic trenches proves to be portable and fast, minimizes the need for specialized survey equipment, and maintains model accuracy needed for mapping trench walls.
Algal and cyanobacterial blooms can foul water systems, inhibit recreation, and produce cyanotoxins, which can be toxic to humans, domestic animals, and wildlife. Blooms that recur yearly present a special challenge, in that chronic effects of most cyanotoxins are unknown. To better understand cyanotoxin timing, possible environmental triggers, and inter-relations among taxa and toxins in bloom communities, recurring cyanobacterial blooms were investigated at three recreational sites in Kabetogama Lake in Voyageurs National Park from 2016-2019. Results indicated that peak neurotoxin concentrations occurred before peak microcystin concentrations and that toxin-forming cyanobacteria were present before visible blooms, which is a serious human health concern. Two cyanotoxin mixture models (MIX) and two microcystin (MC) models were developed using near-real-time environmental variables and additional comprehensive variables based on laboratory analyses. Comprehensive models explained more variability than the environmental models and neither MIX model was a better fit than the MC models. However, the MIX models produced no false negatives, indicating that all observations above human-health regulatory guidelines were simulated by the MIX models. The results show that a model based on a cyanotoxin mixture is more protective of human health than a model based on microcystin alone. In 2019, 7 of 19 toxins were detected in various mixtures. The potential toxin producing cyanobacteria, Microcystis, was significantly correlated with microcystin-YR, while Pseudanabaena sp. and Synechococcus sp. were negatively correlated to several toxins. Jaccard and Sorenson indices indicated strong same-day similarities among the three bloom communities. Nitrogen-fixing cyanobacteria were present at every site, and when combined with internal loading of phosphorus, might explain similarities among sites, and why seasonal differences, even in samples from the same site, were stronger. Information from this dissertation adds to the body of work on recurring blooms and under-studied toxins and toxin mixtures, providing a better understanding of future research options for freshwater cyanotoxins in and outside of Voyageurs National Park.
","language":"English","publisher":"North Dakota State University","usgsCitation":"Christensen, V., 2021, Freshwater cyanotoxin mixtures in recurring cyanobacterial blooms in Voyageurs National Park, 221 p.","productDescription":"221 p.","ipdsId":"IP-128041","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":409293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":409284,"type":{"id":15,"text":"Index Page"},"url":"https://www.proquest.com/docview/2547519599","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Minnesota","otherGeospatial":"Kabetogama Lake, Voyageurs National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.7287375311439,\n 48.44384887858732\n ],\n [\n -92.74528481592849,\n 48.46823569471036\n ],\n [\n -92.85651934142741,\n 48.45238559671293\n ],\n [\n -92.80320031267578,\n 48.47311165228035\n ],\n [\n -92.9355785909554,\n 48.46823569471036\n ],\n [\n -93.01371854688433,\n 48.52184546050012\n ],\n [\n -93.05508675884663,\n 48.53280411143439\n ],\n [\n -93.11300225559437,\n 48.51271143988237\n ],\n [\n -93.11759872359,\n 48.48469017375146\n ],\n [\n -93.06703757563596,\n 48.47494001557638\n ],\n [\n -93.06060252044176,\n 48.44628808733975\n ],\n [\n -93.02199218927704,\n 48.431041110668644\n ],\n [\n -92.98062397731476,\n 48.41151830276564\n ],\n [\n -92.95120658214137,\n 48.426161111635196\n ],\n [\n -92.92822424216214,\n 48.42189072806485\n ],\n [\n -92.9034033149849,\n 48.43226103720582\n ],\n [\n -92.86755086461727,\n 48.42189072806485\n ],\n [\n -92.80871607427095,\n 48.410908094197964\n ],\n [\n -92.78113726629607,\n 48.40480560576938\n ],\n [\n -92.7287375311439,\n 48.44384887858732\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Christensen, Victoria 0000-0003-4166-7461","orcid":"https://orcid.org/0000-0003-4166-7461","contributorId":220548,"corporation":false,"usgs":true,"family":"Christensen","given":"Victoria","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856888,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70220886,"text":"70220886 - 2021 - Exploring the factors controlling the error characteristics of the Surface Water and Ocean Topography mission discharge estimates","interactions":[],"lastModifiedDate":"2021-06-30T19:00:04.291567","indexId":"70220886","displayToPublicDate":"2021-05-12T07:16:05","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Exploring the factors controlling the error characteristics of the Surface Water and Ocean Topography mission discharge estimates","docAbstract":"The Surface Water and Ocean Topography (SWOT) satellite mission will measure river width, water surface elevation, and slope for rivers wider than 50-100 m. SWOT observations will enable estimation of river discharge by using simple flow laws such as the Manning-Strickler equation, complementing in-situ streamgages. Several discharge inversion algorithms designed to compute unobserved flow law parameters (e.g. friction coefficient, bathymetry) have been proposed, but to date, a systematic assessment of factors controlling algorithm performance has not been conducted. Here, we assess the performance of the five algorithms that are expected to be used in the construction of the SWOT product. To perform this assessment, we used synthetic SWOT observations created with hydraulic model output corrupted with SWOT-like error. Prior information provided to the algorithms was purposefully limited to an estimate of mean annual flow (MAF), designed to produce a “worst case” benchmark. Prior MAF error was an important control on algorithm performance, but discharge estimates produced by the algorithms are less biased than the MAF; thus, the discharge algorithms improve on the prior. We show for the first time that accuracy and frequency of remote sensing observations are less important than prior bias, hydraulic variability among reaches, and flow law accuracy in governing discharge algorithm performance. The discharge errors and error sensitivities reported herein are a bounding benchmark, representing worst possible expected errors and error sensitivities. This study lays the groundwork to develop predictive power of algorithm performance, and thus map the global distribution of worst-case SWOT discharge accuracy.
Higher spatial and temporal resolutions of remote sensing data are likely to be useful for ecological monitoring efforts. There are many different treatment approaches for the introduced European genotype of Phragmites australis, and adaptive management principles are being integrated in at least some long-term monitoring efforts. In this paper, we investigated how natural color and a smaller set of near-infrared (NIR) images collected with low-cost uncrewed aerial vehicles (UAVs) could help quantify the aboveground effects of management efforts at 20 sites enrolled in the Phragmites Adaptive Management Framework (PAMF) spanning the coastal Laurentian Great Lakes region. We used object-based image analysis and field ground truth data to classify the Phragmites and other cover types present at each of the sites and calculate the percent cover of Phragmites, including whether it was alive or dead, in the UAV images. The mean overall accuracy for our analysis with natural color data was 91.7% using four standardized classes (Live Phragmites, Dead Phragmites, Other Vegetation, Other Non-vegetation). The Live Phragmites class had a mean user’s accuracy of 90.3% and a mean producer’s accuracy of 90.1%, and the Dead Phragmites class had a mean user’s accuracy of 76.5% and a mean producer’s accuracy of 85.2% (not all classes existed at all sites). These results show that UAV-based imaging and object-based classification can be a useful tool to measure the extent of dead and live Phragmites at a series of sites undergoing management. Overall, these results indicate that UAV sensing appears to be a useful tool for identifying the extent of Phragmites at management sites.
","language":"English","publisher":"MDPI","doi":"10.3390/rs13101895","usgsCitation":"Brooks, C.N., Weinstein, C.B., Poley, A.F., Grimm, A.G., Marion, N.P., Bourgeau-Chavez, L., Hansen, D., and Kowalski, K., 2021, Using uncrewed aerial vehicles for identifying the extent of invasive Phragmites australis in treatment areas enrolled in an adaptive management program: Remote Sensing, v. 13, no. 10, 1895, 21 p., https://doi.org/10.3390/rs13101895.","productDescription":"1895, 21 p.","ipdsId":"IP-124814","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":452292,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs13101895","text":"Publisher Index Page"},{"id":436371,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91NICZD","text":"USGS data release","linkHelpText":"Land cover classifications and associated data from treatment areas enrolled in the Phragmites Adaptive Management Framework, 2018"},{"id":386675,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.08837890625,\n 43.03677585761058\n ],\n [\n -87.2314453125,\n 43.03677585761058\n ],\n [\n -87.2314453125,\n 44.465151013519616\n ],\n [\n -88.08837890625,\n 44.465151013519616\n ],\n [\n -88.08837890625,\n 43.03677585761058\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.0234375,\n 43.197167282501276\n ],\n [\n -83.34228515625,\n 43.197167282501276\n ],\n [\n -83.34228515625,\n 44.02442151965934\n ],\n [\n -84.0234375,\n 44.02442151965934\n ],\n [\n -84.0234375,\n 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Here, we present full water column observations at unprecedented resolution from the southwest Puerto Rico insular shelf and slope during Hurricane María, representing a rare set of high-frequency, subsurface, oceanographic observations collected along an island margin during a hurricane. The shelf geometry and orientation relative to the storm acted to stabilize and strengthen stratification. This maintained elevated sea-surface temperatures (SSTs) throughout the storm and led to an estimated 65% greater potential hurricane intensity contribution at this site before eye passage. Coastal cooling did not occur until 11 hours after the eye passage. Our findings present a new framework for how hurricane interaction with insular island margins may generate baroclinic processes that maintain elevated SSTs, thus potentially providing increased energy for the storm.
","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.abf1552","usgsCitation":"Cheriton, O.M., Storlazzi, C.D., Rosenberger, K.J., Sherman, C.E., and Schmidt, W., 2021, Rapid observations of ocean dynamics and stratification along a steep island coast during Hurricane María: Science Advances, v. 7, no. 20, eabf1552, 10 p., https://doi.org/10.1126/sciadv.abf1552.","productDescription":"eabf1552, 10 p.","ipdsId":"IP-111341","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":452294,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.abf1552","text":"Publisher Index Page"},{"id":386110,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"southwestern Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.0880126953125,\n 17.90556881196468\n ],\n [\n -66.7474365234375,\n 17.90556881196468\n ],\n [\n -66.7474365234375,\n 18.109308155101445\n ],\n [\n -67.0880126953125,\n 18.109308155101445\n ],\n [\n -67.0880126953125,\n 17.90556881196468\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"20","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cheriton, Olivia M. 0000-0003-3011-9136","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":204459,"corporation":false,"usgs":true,"family":"Cheriton","given":"Olivia","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":816756,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":816757,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberger, Kurt J. 0000-0002-5185-5776 krosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5185-5776","contributorId":140453,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Kurt","email":"krosenberger@usgs.gov","middleInitial":"J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":816758,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherman, Clark E. 0000-0003-0758-7900","orcid":"https://orcid.org/0000-0003-0758-7900","contributorId":259180,"corporation":false,"usgs":false,"family":"Sherman","given":"Clark","middleInitial":"E.","affiliations":[{"id":34129,"text":"University of Puerto Rico Mayaguez","active":true,"usgs":false}],"preferred":false,"id":816759,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmidt, Wilford 0000-0003-3564-4159","orcid":"https://orcid.org/0000-0003-3564-4159","contributorId":259182,"corporation":false,"usgs":false,"family":"Schmidt","given":"Wilford","email":"","affiliations":[{"id":34129,"text":"University of Puerto Rico Mayaguez","active":true,"usgs":false}],"preferred":false,"id":816760,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70220401,"text":"ofr20211022 - 2021 - Evaporation from Lake Mead and Lake Mohave, Nevada and Arizona, 2010–2019","interactions":[],"lastModifiedDate":"2021-05-12T11:48:04.655661","indexId":"ofr20211022","displayToPublicDate":"2021-05-11T15:05:25","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1022","displayTitle":"Evaporation from Lake Mead and Lake Mohave, Nevada and Arizona, 2010–2019","title":"Evaporation from Lake Mead and Lake Mohave, Nevada and Arizona, 2010–2019","docAbstract":"Evaporation-rate estimates at Lake Mead and Lake Mohave, Nevada and Arizona, were based on eddy covariance and available energy measurements from March 2010 through April 2019 at Lake Mead and May 2013 through April 2019 at Lake Mohave. The continuous data needed to compute monthly evaporation were collected from floating-platform and land-based measurement stations located at each reservoir. Collected data include latent- and sensible-heat fluxes, net radiation, air temperature, wind speed, humidity, and water-temperature profiles. Data collection, analysis methods, and monthly evaporation results for Lake Mead through February 2012 were documented in a U.S. Geological Survey (USGS) Scientific-Investigations Report, 2013–5229. Monthly evaporation and associated datasets for both reservoirs through April 2015 were published in a USGS Data Release (https://doi.org/10.5066/F79C6VG3). Average annual evaporation at Lake Mead was 1,896 millimeters (mm), which is a 10 percent difference from the 1,718 mm average annual evaporation at Lake Mohave; this was primarily due to differences in available energy. Average annual available energy at Lake Mead was 139 watts per square meter (W/m2), which is an 18 percent difference from the 116 W/m2 average annual available energy at Lake Mohave. Differences in available energy are driven by differences in advected heat between Lake Mead and Lake Mohave; advected heat at Lake Mohave is lower due to colder inflows and warmer outflows. Lake Mead monthly evaporation estimates for this study compare reasonably well to the Bureau of Reclamation’s 24-Month Study (24MS) evaporation coefficients, which are based on pioneering studies from the 1950s. Temporal trends in this study indicate that the effects of heat storage at Lake Mead were underestimated in the 24MS, particularly during the fall months when energy was released from the lake. Mean monthly evaporation rates at Lake Mead were greater than Lake Mohave from June through November during the study period. The seasonal pattern of evaporation at Lake Mohave in this study indicates that the effects of available energy were underestimated in the 24MS coefficients for this reservoir, and that evaporation was substantially overestimated from spring through summer
during the study period of 2013 through 2019.
Director,
Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road
Carson City, Nevada 95819
Collection of biological samples for DNA is necessary in a variety of disciplines including disease epidemiology, landscape genetics, and forensics. Quantity and quality of DNA varies depending on the method of collection or media available for collection (e.g., blood, tissue, fecal). Blood is the most common sample collected in vials or on Whatman Flinders Technology Associates (FTA) cards with short- and long-term storage providing adequate DNA for study objectives. The focus of this study was to determine if biological samples stored on Whatman FTA Elute cards were a reasonable alternative to traditional DNA sample collection, storage, and extraction. Tissue, nasal swabs, and ocular fluid were collected from white-tailed deer (Odocoileus virginianus). Tissue samples and nasal swabs acted as a control to compare extraction and DNA suitability for microsatellite analysis for nasal swabs and ocular fluid extracted from FTA Elute cards. We determined that FTA Elute cards improved the extraction time and storage of samples and that nasal swabs and ocular fluid containing pigmented fluid were reasonable alternatives to traditional tissue DNA extractions.
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\"}}]}","volume":"11","noUsgsAuthors":false,"publicationDate":"2021-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Edson, Jessie","contributorId":275594,"corporation":false,"usgs":false,"family":"Edson","given":"Jessie","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":834161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Justin","contributorId":275595,"corporation":false,"usgs":false,"family":"Brown","given":"Justin","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":834162,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, William L.","contributorId":275596,"corporation":false,"usgs":false,"family":"Miller","given":"William L.","affiliations":[{"id":56863,"text":"Calvin 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David 0000-0003-3068-1073","orcid":"https://orcid.org/0000-0003-3068-1073","contributorId":219540,"corporation":false,"usgs":true,"family":"Walter","given":"W. David","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834160,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70223093,"text":"70223093 - 2021 - A renewed philosophy about supplemental sea lamprey controls","interactions":[],"lastModifiedDate":"2022-01-07T15:55:12.877426","indexId":"70223093","displayToPublicDate":"2021-05-11T11:14:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"A renewed philosophy about supplemental sea lamprey controls","docAbstract":"Invasive sea lamprey (Petromyzon marinus) populations in the Laurentian Great Lakes have been reduced by up to 90% through the use of selective pesticides (lampricides) and physical sea lamprey barriers that block spawning migrations. Nevertheless, other control methods are needed to achieve integrated pest management objectives, delay biological resistance, and address societal pressure to reduce pesticide use and restore lotic connectivity through dam removals. Despite decades of research and scientific advances, new control tools that focus on controlling adult and juvenile life stages have been rare because tactics have not been cost-effective alternatives to lampricides and sea lamprey barriers. Here, we propose a renewed philosophy highlighting that new control methods need not be true alternatives to lampricides and sea lamprey barriers (i.e., have similar effectiveness), but instead can be useful as supplemental controls integrated with current methods, especially in places where current methods are less effective due to environmental or societal conditions. Current case studies pairing multiple supplemental controls together on two Lake Huron tributaries, the Black Mallard and Cheboygan Rivers, have shown promise in reducing sea lamprey reproductive success, the scope of lampricide treatments, and ultimately the number of juvenile sea lampreys produced. Additional case studies are planned and will be evaluated within a decade-long adaptive assessment plan.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2021.03.013","usgsCitation":"Siefkes, M.J., Johnson, N.S., and Muir, A.M., 2021, A renewed philosophy about supplemental sea lamprey controls: Journal of Great Lakes Research, v. 47, no. Suppl 1, p. S742-S752, https://doi.org/10.1016/j.jglr.2021.03.013.","productDescription":"11 p.","startPage":"S742","endPage":"S752","ipdsId":"IP-124405","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":452300,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2021.03.013","text":"Publisher Index Page"},{"id":387863,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","issue":"Suppl 1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Siefkes, Michael J.","contributorId":222109,"corporation":false,"usgs":false,"family":"Siefkes","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":820925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":597,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas","email":"njohnson@usgs.gov","middleInitial":"S.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":820926,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muir, Andrew M.","contributorId":176177,"corporation":false,"usgs":false,"family":"Muir","given":"Andrew","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":820927,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227730,"text":"70227730 - 2021 - Managing wildlife at landscape scales","interactions":[],"lastModifiedDate":"2022-01-27T17:06:06.7913","indexId":"70227730","displayToPublicDate":"2021-05-11T11:01:06","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"10","title":"Managing wildlife at landscape scales","docAbstract":"Managing wildlife populations on a landscape is not a new concept to the field of wildlife management. However, a variety of barriers exist to effectively manage wildlife species at landscape scales. For example, competing management objectives for the same population can occur in parts of two adjoining states and 3-4 agencies within a single state may be charged with managing the habitat on which that population depends at varying spatial scales. Moreover, most state and federal agencies have different mandates and implement management actions out of offices that have static administrative or jurisdictional boundaries. Hence, implementing management actions across relatively large spatial extents can be difficult because one manager or one agency field office may have little or no input on the management of habitats or populations for which they do not have administrative responsibility. In contrast, landscape ecologists often focus on actions that ignore those same logistical hurdles. Landscape ecologists and wildlife managers should be aware of such barriers and incorporate these unique challenges and constraints into their research questions, proposed management actions, and policies. Our goal is to identify challenges, constraints, and opportunities to managing wildlife populations at a landscape scale and describe how resource agencies and landscape ecologists can work collaboratively to overcome challenges and constraints. We also explore the potential management challenges created by continuing to manage wildlife populations and habitats based on local-scale approaches to management and decision making. Finally, we provide a case study using the greater sage-grouse as an example of challenges and constraints to managing a species at a landscape scale.","language":"English","publisher":"Johns Hopkins University Press","usgsCitation":"Connelly, J.W., and Conway, C.J., 2021, Managing wildlife at landscape scales, p. 143-157.","productDescription":"15 p.","startPage":"143","endPage":"157","ipdsId":"IP-075833","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":394980,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Connelly, John W.","contributorId":272302,"corporation":false,"usgs":false,"family":"Connelly","given":"John","email":"","middleInitial":"W.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":831943,"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":831942,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70231193,"text":"70231193 - 2021 - Great Lakes harmful algal blooms: Current knowledge gaps","interactions":[],"lastModifiedDate":"2022-05-03T14:10:37.442691","indexId":"70231193","displayToPublicDate":"2021-05-11T09:05:41","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Great Lakes harmful algal blooms: Current knowledge gaps","docAbstract":"Freshwater Harmful Algal Blooms (HABs) pose serious risks throughout the world to drinking water, recreation, and ecosystem health. The Great Lakes, which contain nearly 20% of the world’s available surface freshwater, have been experiencing an increase in HABs since the 1990s. Knowledge gaps relating to HABs remain even after extensive and ongoing research efforts. These knowledge gaps are presented below for the benefit of water resource managers, state and federal agencies, legislators, and others involved in the development of policies to address HABs throughout the Great Lakes.","language":"English","publisher":"Great Lakes Commission","usgsCitation":"Boyer, G.L., Evans, M.A., Maguire, T., Newell, S., Raymond, H., Robertson, D., Stammler, K., Zacharda, N., and Gibbons, K.J., 2021, Great Lakes harmful algal blooms: Current knowledge gaps, 5 p.","productDescription":"5 p.","ipdsId":"IP-127133","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":400052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":400005,"type":{"id":15,"text":"Index Page"},"url":"https://www.glc.org/work/habs/publications"}],"country":"Canada, United States","otherGeospatial":"Great 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0000-0001-6799-0596","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":217258,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":841915,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stammler, Katie","contributorId":291256,"corporation":false,"usgs":false,"family":"Stammler","given":"Katie","email":"","affiliations":[{"id":39523,"text":"Essex Region Conservation Authority","active":true,"usgs":false}],"preferred":false,"id":841916,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zacharda, Nicole","contributorId":291336,"corporation":false,"usgs":false,"family":"Zacharda","given":"Nicole","email":"","affiliations":[],"preferred":false,"id":841918,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gibbons, Kenneth 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Landscape genomics provides an opportunity to assess long-term functional connectivity by relating environmental variables to spatial patterns of genomic variation resulting from generations of movement, dispersal and mating behaviors. Identifying landscape features associated with gene flow at large geographic scales for highly mobile species is becoming increasingly possible due to more accessible genomic approaches, improved analytical methods and enhanced computational power. We characterized the genetic structure and diversity of migratory mule deer Odocoileus hemionus using 4051 single nucleotide polymorphisms in 406 individuals sampled across multiple habitats throughout Wyoming, USA. We then identified environmental variables associated with genomic variation within genetic groups and statewide using a stepwise approach to first evaluate nonlinear relationships of landscape resistance with genetic distances and then use mixed-effects modeling to choose top landscape genomic models. We identified three admixed genetic groups of mule deer and found that environmental variables associated with gene flow varied among genetic groups, revealing scale-dependent and regional variation in functional connectivity. At the statewide scale, more gene flow occurred in areas with low elevation and mixed habitat. In the southern genetic group, more gene flow occurred in areas with low elevation. In the northern genetic group, more gene flow occurred in grassland and forest habitats, while highways and energy infrastructure reduced gene flow. In the western genetic group, the null model of isolation by distance best represented genetic patterns. Overall, our findings highlight the role of different seasonal ranges on mule deer genetic connectivity, and show that anthropogenic features hinder connectivity. This study demonstrates the value of combining a large, genome-wide marker set with recent advances in landscape genomics to evaluate functional connectivity in a wide-ranging migratory species.
Long-distance migrations influence the dynamics of hostpathogen interactions and understanding the role of migratory waterfowl in the spread of the highly pathogenic avian influenza viruses (HPAIV) is important. While wild geese have been associated with outbreak events, disease ecology of closely related species has not been studied to the same extent. The swan goose (Anser cygnoides) and the bar-headed goose (Anser indicus) are congeneric species with distinctly different HPAIV infection records; the former with few and the latter with numerous records. We compared movements of these species, as well as the more distantly related whooper swan (Cygnus cygnus) through their annual migratory cycle to better understand exposure to HPAIV events and how this compares within and between congeneric and noncongeneric species. In spite of their record of fewer infections, swan geese were more likely to come in contact with disease outbreaks than bar-headed geese. We propose two possible explanations: i) frequent prolonged contact with domestic ducks increases innate immunity in swan geese, and/or ii) the stress of high-elevation migration reduces immunity of bar-headed geese. Continued efforts to improve our understanding of species-level pathogen response is critical to assessing disease transmission risk.
Large magnitude snow avalanches pose a hazard to humans and infrastructure worldwide. Analyzing the spatiotemporal behavior of avalanches and the contributory climate factors is important for understanding historical variability in climate-avalanche relationships as well as improving avalanche forecasting. We used established dendrochronological methods to develop a long-term (1867–2019) regional avalanche chronology for the Rocky Mountains of northwest Montana using tree-rings from 647 trees exhibiting 2134 avalanche-related growth disturbances. We then used principal component analysis and a generalized linear autoregressive moving average model to examine avalanche-climate relationships. Historically, large magnitude regional avalanche years were characterized by stormy winters with positive snowpack anomalies, with avalanche years over recent decades increasingly influenced by warmer temperatures and a shallow snowpack. The amount of snowpack across the region, represented by the first principal component, is shown to be directly related to avalanche probability. Coincident with warming and regional snowpack reductions, a decline of ~ 14% (~ 2% per decade) in overall large magnitude avalanche probability is apparent through the period 1950–2017. As continued climate warming drives further regional snowpack reductions in the study region our results suggest a decreased probability of regional large magnitude avalanche frequency associated with winters characterized by large snowpacks and a potential increase in large magnitude events driven by warming temperatures and spring precipitation.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-021-89547-z","usgsCitation":"Peitzsch, E.H., Pederson, G.T., Birkeland, K.W., Hendrikx, J., and Fagre, D.B., 2021, Climate drivers of large magnitude snow avalanche years in the U.S. northern Rocky Mountains: Scientific Reports, v. 11, 10032, 13 p., https://doi.org/10.1038/s41598-021-89547-z.","productDescription":"10032, 13 p.","ipdsId":"IP-124589","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":452307,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-021-89547-z","text":"Publisher Index Page"},{"id":385581,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.158203125,\n 47.15984001304432\n ],\n [\n -111.22558593749999,\n 47.15984001304432\n ],\n [\n -111.22558593749999,\n 48.951366470947725\n ],\n [\n -117.158203125,\n 48.951366470947725\n ],\n [\n -117.158203125,\n 47.15984001304432\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2021-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Peitzsch, Erich H. 0000-0001-7624-0455","orcid":"https://orcid.org/0000-0001-7624-0455","contributorId":202576,"corporation":false,"usgs":true,"family":"Peitzsch","given":"Erich","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":815449,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":815450,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Birkeland, Karl W.","contributorId":209943,"corporation":false,"usgs":false,"family":"Birkeland","given":"Karl","email":"","middleInitial":"W.","affiliations":[{"id":38033,"text":"U.S.D.A. Forest Service National Avalanche Center, Bozeman, Montana, USA","active":true,"usgs":false}],"preferred":false,"id":815451,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hendrikx, Jordy 0000-0001-6194-3596","orcid":"https://orcid.org/0000-0001-6194-3596","contributorId":140954,"corporation":false,"usgs":false,"family":"Hendrikx","given":"Jordy","email":"","affiliations":[{"id":13628,"text":"Department of Earth Sciences, P.O. Box 173480, Montana State University, Bozeman, MT, USA. 59717.","active":true,"usgs":false}],"preferred":false,"id":815452,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fagre, Daniel B. 0000-0001-8552-9461 dan_fagre@usgs.gov","orcid":"https://orcid.org/0000-0001-8552-9461","contributorId":2036,"corporation":false,"usgs":true,"family":"Fagre","given":"Daniel","email":"dan_fagre@usgs.gov","middleInitial":"B.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":815471,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70231470,"text":"70231470 - 2021 - Principles for collaborative risk communication: Reducing landslide losses in Puerto Rico","interactions":[],"lastModifiedDate":"2023-10-13T18:25:05.745749","indexId":"70231470","displayToPublicDate":"2021-05-11T06:54:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2246,"text":"Journal of Emergency Management","active":true,"publicationSubtype":{"id":10}},"title":"Principles for collaborative risk communication: Reducing landslide losses in Puerto Rico","docAbstract":"Landslides are frequent and damaging natural hazards that threaten the people and the natural and built environments of Puerto Rico. In 2017, more than 70,000 landslides were triggered across the island by heavy rainfall from Hurricane María, prompting requests by local professionals for landslide education and outreach materials. This article describes a novel collaborative risk communication framework that was developed to meet those requests and shaped the creation of a Spanish- and English-language Landslide Guide for Residents of Puerto Rico. Collaborative risk communication is defined here as an iterative process guided by a set of principles for the interdisciplinary coproduction of hazards information and communication products by local and external stakeholders. The process that supports this form of risk communication involves mapping out the risk communication stakeholders in the at-risk or disaster-affected location—in this case Puerto Rico—and collaborating over time to address a shared challenge, such as landslide hazards. The approach described in this article involved the formation of a core team of government and university partners that expanded in membership to conduct collaborative work with an informal network of hazards professionals from diverse sectors in Puerto Rico. The following principles guided this process: cultural competence, ethical engagement, listening, inclusive decision making, empathy, convergence research, nested mentoring, adaptability, and reciprocity. This article contributes to the field of risk communication and emergency management by detailing these principles and the associated process in order to motivate collaborative risk communication efforts in different geographic and cultural contexts. While the work described here focuses on addressing landslides, the principles and process are transferable to other natural, technological, and willful human-caused hazards. They may also serve as a roadmap for future partnerships among government agencies and university researchers to inform the cocreation of science education and outreach tools.
","language":"English","publisher":"Journal of Emergency Management","usgsCitation":"West, J., Davis, L.A., Lugo Bendezu, R., Alvarez Gandia, Y., Hughes, K.S., Godt, J.W., and Peek, L., 2021, Principles for collaborative risk communication: Reducing landslide losses in Puerto Rico: Journal of Emergency Management, v. 19, no. 8, p. 41-61.","productDescription":"21 p.","startPage":"41","endPage":"61","ipdsId":"IP-126215","costCenters":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"links":[{"id":400483,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.wmpllc.org/ojs/index.php/jem/article/view/3044"},{"id":400498,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Puerto 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Stephen","contributorId":218339,"corporation":false,"usgs":false,"family":"Hughes","given":"K.","email":"","middleInitial":"Stephen","affiliations":[{"id":16585,"text":"University of Puerto Rico - Mayaguez","active":true,"usgs":false}],"preferred":false,"id":842725,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Godt, Jonathan W. 0000-0002-8737-2493 jgodt@usgs.gov","orcid":"https://orcid.org/0000-0002-8737-2493","contributorId":1166,"corporation":false,"usgs":true,"family":"Godt","given":"Jonathan","email":"jgodt@usgs.gov","middleInitial":"W.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":842726,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Peek, Lori","contributorId":269659,"corporation":false,"usgs":false,"family":"Peek","given":"Lori","email":"","affiliations":[],"preferred":false,"id":842727,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70227795,"text":"70227795 - 2021 - Gradient self-potential logging in the Rio Grande to identify gaining and losing reaches across the Mesilla Valley","interactions":[],"lastModifiedDate":"2022-01-31T12:42:56.341708","indexId":"70227795","displayToPublicDate":"2021-05-11T06:38:56","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Gradient self-potential logging in the Rio Grande to identify gaining and losing reaches across the Mesilla Valley","docAbstract":"Little information exists on the habitat use and feeding ecology of insectivorous bats in arid ecosystems, especially at and near uranium mines in northern Arizona, within the Grand Canyon watershed. In 2015–2016, we conducted mist-netting, nightly acoustic monitoring (>1 year), and diet analyses of bats, as well as insect sampling, at 2 uranium mines (Pinenut and Arizona 1) with water containment ponds. Because of physical barriers and limited general access to areas within the mine yard, mist-netting was limited to outside of the perimeter fence and away from the containment ponds. Mist-netting also occurred at 2 nearby sites that served as proxies to the mines. Bats captured directly at the mines included one pregnant Antrozous pallidus and 3 adult male Parastrellus hesperus. At the proxy sites, we captured 45 individuals identified as A. pallidus, Corynorhinus townsendii, Eptesicus fuscus, Euderma maculatum, Lasionycteris noctivagans, Myotis californicus, Myotis ciliolabrum, P. hesperus, and Tadarida brasiliensis. The nightly and seasonal presence of bats, as shown through acoustic recordings at each mine, coincided with the seasonal migratory and hibernation behaviors of the bat species. Statistical comparisons of acoustic recordings with precipitation data collected over one year show that seasonal monsoon rains generally had a negative effect on the nightly activity and presence of bats. Diets of P. hesperus from both mines were comprised mostly of coleopterans but also included smaller volumes of Hymenoptera, Hemiptera, Lepidoptera, Diptera, and Neuroptera. The diet of A. pallidus was comprised solely of Coleoptera. Diets of bat species from the proxy sites were characteristic of their known feeding ecology, which ranged from the consumption of soft-bodied insects (e.g., moths) by C. townsendii to the consumption of hard-bodied insects (e.g., beetles) by E. fuscus. Ultimately, the increased knowledge of the natural history of bats through multiple methods of data collection allows for a better understanding of complex arid ecosystems. It also provides resources needed for the management of habitat associated with alternative energy, such as uranium mining.