Rhabdoviridae is a large family of negative-sense (-) RNA viruses that includes important pathogens of ray-finned fish and marine mammals. As for all viruses, the taxonomic assignment of rhabdoviruses occurs through a process implemented by the International Committee on Taxonomy of Viruses (ICTV). A recent revision of taxonomy conducted in conjunction with the ICTV Rhabdoviridae Study Group has resulted in the establishment of three new subfamilies (Alpharhabdovirinae, Betarhabdovirinae, and Gammarhabdovirinae) within the Rhabdoviridae, as well as three new genera (Cetarhavirus, Siniperhavirus, and Scophrhavirus) and seven new species for viruses infecting fish or marine mammals. All rhabdovirus species have also now been named or renamed to comply with the binomial format adopted by the ICTV in 2021, comprising the genus name followed by a species epithet. Phylogenetic analyses of L protein (RNA-dependent RNA polymerase) sequences of (-) RNA viruses indicate that members of the genus Novirhabdovirus (subfamily Gammarhabdovirinae) do not cluster within the Rhabdoviridae, suggesting the need for a review of their current classification.
","language":"English","publisher":"MDPI","doi":"10.3390/ani12111363","usgsCitation":"Walker, P., Bigarre, L., Kurath, G., Dacheux, L., and Pallandre, L., 2022, Revised taxonomy of rhabdoviruses infecting fish and marine mammals: Animals, v. 12, no. 11, 1363, 16 p., https://doi.org/10.3390/ani12111363.","productDescription":"1363, 16 p.","ipdsId":"IP-140596","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":447667,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/ani12111363","text":"Publisher Index Page"},{"id":405067,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-05-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Walker, Peter J.","contributorId":294712,"corporation":false,"usgs":false,"family":"Walker","given":"Peter J.","affiliations":[{"id":63630,"text":"School of Chemistry and Molecular Biosciences, The University of Queensland, St Lucia, Queensland, 4067, AUSTRALIA","active":true,"usgs":false}],"preferred":false,"id":848752,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bigarre, Laurent","contributorId":294713,"corporation":false,"usgs":false,"family":"Bigarre","given":"Laurent","email":"","affiliations":[{"id":63631,"text":"ANSES, Laboratory of Ploufragan-Plouzané-Niort, Technopole Brest Iroise, 29280 Plouzané, FRANCE","active":true,"usgs":false}],"preferred":false,"id":848753,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kurath, Gael 0000-0003-3294-560X","orcid":"https://orcid.org/0000-0003-3294-560X","contributorId":220175,"corporation":false,"usgs":true,"family":"Kurath","given":"Gael","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":848754,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dacheux, Laurent","contributorId":294714,"corporation":false,"usgs":false,"family":"Dacheux","given":"Laurent","email":"","affiliations":[{"id":63632,"text":"Institut Pasteur, Unit of Lyssavirus Epidemiology and Neuropathology, 28 rue docteur Roux, 757240 Paris, FRANCE","active":true,"usgs":false}],"preferred":false,"id":848755,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pallandre, Laurane","contributorId":294715,"corporation":false,"usgs":false,"family":"Pallandre","given":"Laurane","email":"","affiliations":[{"id":63631,"text":"ANSES, Laboratory of Ploufragan-Plouzané-Niort, Technopole Brest Iroise, 29280 Plouzané, FRANCE","active":true,"usgs":false}],"preferred":false,"id":848756,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70231714,"text":"sir20225044 - 2022 - Potential effects of out-of-basin groundwater transfers on spring discharge, base flow, and groundwater storage pertaining to the Rush Springs aquifer in and near the Caddo Nation of Oklahoma Tribal jurisdictional area, western Oklahoma","interactions":[],"lastModifiedDate":"2026-04-09T17:38:39.55543","indexId":"sir20225044","displayToPublicDate":"2022-05-25T11:41:54","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5044","displayTitle":"Potential Effects of Out-of-Basin Groundwater Transfers on Spring Discharge, Base Flow, and Groundwater Storage Pertaining to the Rush Springs Aquifer In and Near the Caddo Nation of Oklahoma Tribal Jurisdictional Area, Western Oklahoma","title":"Potential effects of out-of-basin groundwater transfers on spring discharge, base flow, and groundwater storage pertaining to the Rush Springs aquifer in and near the Caddo Nation of Oklahoma Tribal jurisdictional area, western Oklahoma","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the Caddo Nation of Oklahoma and Bureau of Indian Affairs, assessed four groundwater-withdrawal scenarios and their potential effects on the Rush Springs aquifer in and near the Caddo Nation of Oklahoma Tribal jurisdictional area in western Oklahoma. Increases in industrial and public water supply needs have led to increased development of water resources within the Rush Springs aquifer. As new areas within the aquifer are developed, increased water withdrawals may result in decreases in available groundwater resources and conflicts among water users.
For this study, a previously published numerical groundwater-flow model of the Rush Springs aquifer was modified to simulate the potential effects of four groundwater withdrawal scenarios. For the previously published calibrated model, groundwater flow was simulated from 1979 through 2015. In this study, groundwater flow simulations were extended through 2035. The period from 2016 through 2035 is referred to as the “20-year projection.” Four groundwater withdrawal scenarios starting in 2007 and continuing through 2035 were evaluated. Scenario 1 simulated no groundwater withdrawals; scenario 2 simulated no withdrawals allocated for out-of-basin water-use transfers; scenario 3 simulated withdrawals based on reported withdrawals during the 2007–15 simulation period and compounded annual increases in groundwater use during the subsequent 20-year projection; and scenario 4 simulated maximum permitted withdrawals for allocation to out-of-basin water-use transfers. Out-of-basin water transfers were classified as withdrawals that are not returned back to the aquifer.
At the springs of interest, changes in water-level altitudes in response to different groundwater withdrawal scenarios were simulated by comparing the results from different model cells. Between 2007 and 2015, scenarios 2–4 yielded similar simulated water-level altitudes in the model cells containing springs of interest, with water-level altitudes decreasing to below the land surface altitude at 13 of the total 25 springs of interest, whereas under scenario 1 there were only two model cells containing springs of interest where the simulated water-level altitudes of a spring decreased to below land surface altitude. For the 20-year projection, water-level altitudes at springs simulated in model cells in scenarios 2–4 decreased to below land surface altitude for 13 of the total 25 model cells containing springs of interest, whereas under scenario 1 there were only two model cells containing springs of interest where the simulated water-level altitudes of a spring decreased to below land surface altitude.
The potential effects of groundwater withdrawals were evaluated by comparing changes in groundwater storage between the four scenarios. The 2007–15 groundwater withdrawal scenarios were used to simulate the potential effects of groundwater withdrawal rates on groundwater storage of the Rush Springs aquifer. The simulated groundwater storage change in the Rush Springs aquifer ranged from an increase of 2.8 percent for scenario 1 to an increase of 1.0 percent for scenario 4. Projected 20-year groundwater withdrawal scenarios were used to simulate the potential effects of selected groundwater withdrawal rates on groundwater storage of the Rush Springs aquifer. Simulated groundwater storage changes ranged from a decrease of 0.5 percent for scenario 1 to a decrease of 0.7 percent for scenario 4.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225044","collaboration":"Prepared in cooperation with the Caddo Nation of Oklahoma and Bureau of Indian Affairs","usgsCitation":"Labriola, L.G., Russell, C.A., and Ellis, J.H., 2022, Potential effects of out-of-basin groundwater transfers on spring discharge, base flow, and groundwater storage pertaining to the Rush Springs aquifer in and near the Caddo Nation of Oklahoma Tribal jurisdictional area, western Oklahoma: U.S. Geological Survey Scientific Investigations Report 2022–5044, 32 p., https://doi.org/10.3133/sir20225044.","productDescription":"Report: vii, 32 p.; Data Release; Dataset","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-128617","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":400914,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92DYE98","text":"USGS data release","linkHelpText":"MODFLOW-NWT model used to simulate the potential effects of out-of-basin transfers for the Rush Springs aquifer in the Caddo Nation of Oklahoma Tribal jurisdictional area, western Oklahoma"},{"id":400911,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5044/sir20225044.pdf","text":"Report","size":"12.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5044"},{"id":400910,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5044/coverthb.jpg"},{"id":400915,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":502399,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113068.htm","linkFileType":{"id":5,"text":"html"}},{"id":401055,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225044/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":400913,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5044/images"},{"id":400912,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5044/sir20225044.XML"}],"country":"United States","state":"Oklahoma","otherGeospatial":"Rush Springs Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.767578125,\n 34.45221847282654\n ],\n [\n -98.5693359375,\n 36.491973470593685\n ],\n [\n -99.66796875,\n 35.817813158696616\n ],\n [\n -99.0966796875,\n 35.137879119634185\n ],\n [\n -98.61328125,\n 34.488447837809304\n ],\n [\n -97.6904296875,\n 34.34343606848294\n ],\n [\n -96.767578125,\n 34.45221847282654\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754-4501
Climate change will continue to be an important consideration for conservation practitioners. However, uncertainty in identifying appropriate management strategies, particularly for understudied species and regions, constrains the implementation of science-based solutions and adaptation strategies. Here, we share a decision-path approach to reduce uncertainty in climate change responses of inland fishes to inform conservation and adaptation planning. With the Fish and Climate Change database (FiCli), a comprehensive, online, public database of peer-reviewed literature on documented and projected climate impacts to inland fishes, users can identify relevant studies and associated management recommendations via geographic regions, response types (i.e., fish assemblage dynamics, demographic, distributional, evolutionary, phenological), fish taxa, and traits (e.g., thermal guilds, feeding type, parental care, habitat type) and use a suite of summary tools to make more informed decisions. For both data-rich and data-poor scenarios, we demonstrate that this approach can reduce uncertainty in understanding climate change responses. Using thermal sensitivity as an example, we also establish the utility of FiCli database to address other user-defined, management-relevant questions via supplementary analyses. This decision-path approach can be applied to rapid assessments, management decisions, and policy development and may serve as a model for other conservation decision-making processes.
","language":"English","publisher":"Wiley","doi":"10.1111/csp2.12724","usgsCitation":"Lynch, A., Myers, B., Wong, J.P., Chu, C., Tingley, R.W., Falke, J.A., Kwak, T.J., Paukert, C.P., and Krabbenhoft, T.J., 2022, Reducing uncertainty in climate change responses of inland fishes: A decision-path approach: Conservation Science and Practice, v. 4, no. 7, e12724, 15 p., https://doi.org/10.1111/csp2.12724.","productDescription":"e12724, 15 p.","ipdsId":"IP-123065","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":447669,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.12724","text":"Publisher Index Page"},{"id":435839,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F6HA3M","text":"USGS data release","linkHelpText":"FiCli: Fish and Climate Change Database (2021 Update)"},{"id":403898,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"7","noUsgsAuthors":false,"publicationDate":"2022-05-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Lynch, Abigail 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":220490,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":846721,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Myers, Bonnie 0000-0002-3170-2633","orcid":"https://orcid.org/0000-0002-3170-2633","contributorId":219702,"corporation":false,"usgs":true,"family":"Myers","given":"Bonnie","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":846722,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wong, Jesse P.","contributorId":264850,"corporation":false,"usgs":false,"family":"Wong","given":"Jesse","email":"","middleInitial":"P.","affiliations":[{"id":12909,"text":"George Mason University","active":true,"usgs":false}],"preferred":false,"id":846723,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chu, Cindy","contributorId":176496,"corporation":false,"usgs":false,"family":"Chu","given":"Cindy","email":"","affiliations":[],"preferred":false,"id":846724,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tingley, Ralph W. III 0000-0002-1689-2133","orcid":"https://orcid.org/0000-0002-1689-2133","contributorId":189812,"corporation":false,"usgs":true,"family":"Tingley","given":"Ralph","suffix":"III","email":"","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":846725,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":846726,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kwak, Thomas J. 0000-0002-0616-137X tkwak@usgs.gov","orcid":"https://orcid.org/0000-0002-0616-137X","contributorId":834,"corporation":false,"usgs":true,"family":"Kwak","given":"Thomas","email":"tkwak@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":846727,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Paukert, Craig P. 0000-0002-9369-8545","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":245524,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","middleInitial":"P.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":846728,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Krabbenhoft, Trevor J.","contributorId":176498,"corporation":false,"usgs":false,"family":"Krabbenhoft","given":"Trevor","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":846729,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70240114,"text":"70240114 - 2022 - Association of antler asymmetry with hoof disease in elk","interactions":[],"lastModifiedDate":"2023-01-27T13:18:18.965479","indexId":"70240114","displayToPublicDate":"2022-05-25T07:16:02","publicationYear":"2022","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":"Association of antler asymmetry with hoof disease in elk","docAbstract":"Treponeme-associated hoof disease (TAHD) is an emergent disease of elk (Cervus canadensis) in the Pacific West of the United States. Although lesions are usually restricted to the feet, anecdotal reports suggested increased prevalence of abnormal antlers in affected elk. We used hunter harvest reports for 1,688 adult male elk harvested in southwestern Washington, USA, during 2016-2018, to evaluate anecdotal reports. We used Akaike's Information Criterion to compare 18 logistic regression models describing the prevalence of asymmetrical antlers, indicated by unequal antler point counts. Our leading model (84% of model weight) described additive effects of TAHD (odds ratio = 1.91; 95% CI = [1.49, 2.44]) and maximum number of antler points. Confidence intervals overlapped zero for all other parameters, which described ecotypic, geographic, and age-related effects. Effects of physical injury on antler development have been described elsewhere; however, injuries leading to instances of antler deformity do not have population-level management implications. In contrast, we describe effects of a transmissible disease that was reported by hunters in >35% of adult male elk and was associated with an increase of ≥16 percentage points in the prevalence of gross asymmetry. Unequal point counts are quite common in elk with otherwise typical antlers and seem unlikely to attract public notice or be attributed to hoof lesions; thus, we suspect our results and anecdotal reports reflect more prominent deformities that are important to stakeholders who enjoy hunting and wildlife viewing.
Ribbed mussels, Geukensia demissa, are marsh fauna that are used in coastal management and restoration due to the ecosystem services they provide. Ribbed mussel restoration efforts may be improved with a greater understanding of the environmental drivers of ribbed mussel distribution at multiple spatial scales to predict areas where restoration could be successful. This study sought to estimate the effects of within-marsh (4 m) and landscape (500 m) factors on ribbed mussel distribution. Ribbed mussel densities were surveyed at 11 sites along the coast of Georgia, USA, and overlaid with spatial data for within-marsh factors (elevation, distance to marsh features, slope) as well as landscape factors (percent cover by subtidal creek, forest, and development within a 500-m radius). The distribution model was then validated using three previously unsurveyed marshes and explained 55% of the variance in ribbed mussel abundance. Ribbed mussel abundances and occupancy were most sensitive to changes in within-marsh factors (elevation and distance to subtidal creeks, bodies of water inundated during the full tidal cycle) but were also sensitive to landscape features (percent landcover of forests and development). The highest ribbed mussel densities were found in mid-elevation areas (~ 0.7 m NAVD88), far from subtidal creeks, and in marshes surrounded with forest and development. These results contrast with distributions in the northeastern USA, where ribbed mussels are distributed along subtidal creek banks. This work suggests that restoration may be most effective when focused on appropriate elevations and at locations away from the marsh-creek ecotone.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s12237-022-01090-w","usgsCitation":"Annis, W., Hunter, E.A., and Carroll, J., 2022, Within-marsh and landscape features structure ribbed mussel distribution in Georgia, USA, marshes: Estuaries and Coasts, v. 45, p. 2660-2674, https://doi.org/10.1007/s12237-022-01090-w.","productDescription":"15 p.","startPage":"2660","endPage":"2674","ipdsId":"IP-132397","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481086,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1007/s12237-022-01090-w","text":"External Repository"},{"id":480947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.27652817835495,\n 32.30818582903797\n ],\n [\n -82.27652817835495,\n 31.035143348707706\n ],\n [\n -80.80318017426605,\n 31.035143348707706\n ],\n [\n -80.80318017426605,\n 32.30818582903797\n ],\n [\n -82.27652817835495,\n 32.30818582903797\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"45","noUsgsAuthors":false,"publicationDate":"2022-05-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Annis, William K.","contributorId":348800,"corporation":false,"usgs":false,"family":"Annis","given":"William K.","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":923780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunter, Elizabeth Ann 0000-0003-4710-167X","orcid":"https://orcid.org/0000-0003-4710-167X","contributorId":288535,"corporation":false,"usgs":true,"family":"Hunter","given":"Elizabeth","email":"","middleInitial":"Ann","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923781,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carroll, John M.","contributorId":348801,"corporation":false,"usgs":false,"family":"Carroll","given":"John M.","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":923782,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70231693,"text":"ofr20221028 - 2022 - Underwater videographic observations of domesticated Delta smelt in field enclosures","interactions":[],"lastModifiedDate":"2022-05-25T11:05:58.013536","indexId":"ofr20221028","displayToPublicDate":"2022-05-24T12:57:03","publicationYear":"2022","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":"2022-1028","displayTitle":"Underwater Videographic Observations of Domesticated Delta Smelt in Field Enclosures","title":"Underwater videographic observations of domesticated Delta smelt in field enclosures","docAbstract":"The delta smelt (Hypomesus transpacificus) is a small, euryhaline fish species endemic to the Sacramento–San Joaquin Delta; it is protected under the U.S. and California Endangered Species Acts, and because of declines in population abundance, the delta smelt may be vulnerable to extinction. The California Department of Water Resources (DWR) is conducting studies to test the viability of using domesticated fish to supplement the wild population of delta smelt. These studies have focused on examining the health and survival of domesticated delta smelt placed inside enclosures (circular cages that are approximately 1.5 meters tall by 1 meter in diameter) into the wild. We completed two parts within this study using underwater cameras inside the enclosures to observe fish behavior and their responses to certain stimuli. In both parts of the study, delta smelt behaviors were broadly categorized into two basic categories: (1) normal and (2) alarm. Normal behavior was characterized as calm, non-polarized, and docile swimming behavior. Alarm behavior was characterized by sudden and rapid darting, polarized frantic swimming activity, and tighter schooling polarization of individuals.
The first part of the study took place in a semi-controlled agricultural pond on the campus of the University of California, Davis. At this agricultural pond, we developed methods of observation and documented how fish behaved in response to enclosure disturbances associated with routine cleaning and service that is required during extended field deployments of the enclosures. We observed that delta smelt behavior changed from normal to alarm at the onset of an enclosure service and from alarm to normal within about 2 minutes after the service ended.
The second part of the study was completed in cooperation with the DWR. In October 2019, DWR deployed three enclosures in the Sacramento River near Rio Vista, California. To monitor survival rate of delta smelt, DWR permitted us to deploy cameras in one enclosure to document the frequency and duration of alarm behaviors exhibited by delta smelt and the frequency, duration, and intensity of three types of disturbances: (1) noise generated from passing boats, (2) noise generated from the enclosure moving in response to wave energy, and (3) vertical movements of the enclosure generated from wave energy. Alarm behaviors averaged about 2 minutes in duration and occurred most frequently during the evening compared to midday or morning. Each disturbance variable exhibited substantial variability in duration and intensity and occurred least frequently during the morning and evening compared to midday. Alarm behaviors appeared to be most associated with high intensity enclosure noises and vertical movements; however, limited replicate samples prohibited developing a statistical relation. Alarm behaviors did not directly contribute to injury or mortality of individual delta smelt; however, indirect or sublethal effects of alarm behaviors were not examined.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221028","collaboration":"Prepared in cooperation with California Department of Water Resources","programNote":"Water Availability and Use Science Program","usgsCitation":"Enos, E., Patton, O., and Feyrer, F., 2022, Underwater videographic observations of domesticated Delta smelt in field enclosures: U.S. Geological Survey Open-File Report 2022–1028, 17 p., https://doi.org/10.3133/ofr20221028.","productDescription":"Report: vii, 17 p.; Data Release","numberOfPages":"17","onlineOnly":"Y","ipdsId":"IP-120423","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":401000,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221028/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"Open-File Report 2022-1028"},{"id":400874,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CY39ZG","text":"Underwater videographic observations of cultured Delta Smelt in field enclosures—Video clips and summary data","description":"Enos, E.R., Patton, O.J., and Feyrer, F.V., 2020, Underwater videographic observations of cultured Delta Smelt in field enclosures—Video clips and summary data: U.S. Geological Survey data release, https://doi.org/10.5066/P9CY39ZG."},{"id":400873,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1028/images"},{"id":400872,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1028/ofr20221028.xml"},{"id":400870,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1028/covrthb.jpg"},{"id":400871,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1028/ofr20221028.pdf","text":"Report","size":"8.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2022-1028"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.1514892578125,\n 37.896530447543\n ],\n [\n -120.311279296875,\n 37.896530447543\n ],\n [\n -120.311279296875,\n 39.01064750994083\n ],\n [\n -122.1514892578125,\n 39.01064750994083\n ],\n [\n -122.1514892578125,\n 37.896530447543\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
The retreat of Barry Glacier has contributed to the destabilization of slopes in Barry Arm, creating the possibility that a landslide could rapidly enter the fjord and trigger a tsunami.
The U.S. Geological Survey (USGS) recently released a report documenting potential tsunami wave heights in the event of a large, fast-moving landslide at the Barry Arm fiord near Prince William Sound, Alaska (Barnhart and others, 2021). This new work shows that the largest plausible wave height is smaller than initial estimates published in Dai and others (2020), but waves still represent a substantial hazard to the people who live, work, and recreate in Prince William Sound. Thus, it is important that residents and visitors remain informed about this hazard and prepare accordingly.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20223020","usgsCitation":"Macías, M.A., Barnhart, K.R., Staley, D.M., 2022, New model of the Barry Arm landslide in Alaska reveals potential tsunami wave heights of 2 meters, values much lower than previously estimated: U.S. Geological Survey Fact Sheet 2022–3020, 2 p., https://doi.org/10.3133/fs20223020.","productDescription":"2 p.","onlineOnly":"Y","ipdsId":"IP-132586","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":501486,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113066.htm","linkFileType":{"id":5,"text":"html"}},{"id":400821,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3020/images"},{"id":400820,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2022/3020/fs20223020.xml"},{"id":400817,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3020/coverthb.jpg"},{"id":400818,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3020/fs20223020.pdf","text":"Report","size":"2.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3020"},{"id":400819,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211071","linkHelpText":"Preliminary Assessment of the Wave Generating Potential from Landslides at Barry Arm, Prince William Sound, Alaska"}],"country":"United States","state":"Alaska","otherGeospatial":"Barry Arm landslide","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -148.27423095703125,\n 61.09348761017874\n ],\n [\n -148.08883666992188,\n 61.09348761017874\n ],\n [\n -148.08883666992188,\n 61.194228075714236\n ],\n [\n -148.27423095703125,\n 61.194228075714236\n ],\n [\n -148.27423095703125,\n 61.09348761017874\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
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Focal mechanisms, which reflect the sense of slip in earthquakes, provide important constraints for understanding crustal tectonics and earthquake source physics, including the interactions among earthquakes during mainshock–aftershock sequences or seismic swarms. Focal mechanisms of small (magnitude ≲3.5) earthquakes are usually determined by first‐motion P‐wave polarities, sometimes supplemented by the ratio of S‐wave to P‐wave amplitudes (S/P). However, focal mechanisms of such events can be difficult to reliably constrain, particularly with sparse recording networks or very small magnitude events. Here, we describe a method for deriving S/P amplitude ratios from P/P and S/S amplitude ratios measured on single seismic components between pairs of nearby events, as is often performed during correlation‐based earthquake detection and relocation. These measurements can be transformed into relative S/P amplitude ratios, or they can be combined with a smaller number of traditional S/P amplitude ratios to provide a single‐channel estimation of full S/P ratios, even for low signal‐to‐noise‐ratio events not routinely cataloged and not amenable to traditional S/P ratio processing. This approach has the potential to greatly expand the applicability of S/P amplitude ratios, providing additional constraints for focal mechanisms of small earthquakes, particularly for spatially concentrated seismicity sequences.
The Everglades in south Florida supply fresh drinking water for more than 7 million people, host a National Park, and are classified as a Ramsar wetland of international distinction. Predicting trajectories of water flow and water storage changes in the future is important to managing the Congressionally authorized restoration of the Everglades. Here we describe the needed data sources and analysis approaches to build the inputs for biophysically based modeling that can protect water and ecological resources in the face of changing water management and climate conditions. A biophysical approach to modeling overland flow in the Everglades can help predict future outcomes for ecological habitat, water storage during droughts, and water conveyance during floods. The needed data include measurements of vegetation stem architecture, microtopography, and landscape pattern metrics. Stem architecture measurements present the opportunity to estimate flow roughness of distinct vegetation communities based on hydraulic principles. At a larger scale, the microtopography and the connectivity of the sloughs between ridges offer a way to quantify the effects of flow blockage and tortuous flow paths on overland flow. Combined with theory these data provide the capacity to simulate overland flow in both the historical, pre-drainage Everglades as well as in the present-day managed Everglades. Also provided are the hydrologic data, e.g., water slopes, water depths and overland flow velocities, that can be used to verify a biophysical model. Ultimately, the purpose is to anticipate how changing flow and water depth will interact with evolving vegetation and landscape conditions to influence future water availability for society and for the ecosystem, both in the Everglades and in other low-gradient floodplains.
","language":"English","publisher":"Earth and Space Science Open Archive","doi":"10.1002/essoar.10511451.1","usgsCitation":"Harvey, J., and Choi, J., 2022, Biophysical methods and data analysis for simulating overland flow in the Everglades: ESSOAr, 51 p., https://doi.org/10.1002/essoar.10511451.1.","productDescription":"51 p.","ipdsId":"IP-140509","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":447677,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/essoar.10511451.1","text":"External Repository"},{"id":435841,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DQYB1O","text":"USGS data release","linkHelpText":"Biophysical Data for Simulating Overland Flow in the Everglades"},{"id":408968,"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 -82.07811851388726,\n 26.46536235501027\n ],\n [\n -82.07811851388726,\n 24.821342005916392\n ],\n [\n -79.90282554513692,\n 24.821342005916392\n ],\n [\n -79.90282554513692,\n 26.46536235501027\n ],\n [\n -82.07811851388726,\n 26.46536235501027\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harvey, Judson 0000-0002-2654-9873","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":219104,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":856291,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Choi, Jay 0000-0003-1276-481X jchoi@usgs.gov","orcid":"https://orcid.org/0000-0003-1276-481X","contributorId":219096,"corporation":false,"usgs":true,"family":"Choi","given":"Jay","email":"jchoi@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":856292,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70232278,"text":"70232278 - 2022 - The importance of lake emergent aquatic vegetation for estimating Arctic-boreal methane emissions","interactions":[],"lastModifiedDate":"2022-06-27T13:34:20.25476","indexId":"70232278","displayToPublicDate":"2022-05-23T18:24:27","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"The importance of lake emergent aquatic vegetation for estimating Arctic-boreal methane emissions","docAbstract":"Areas of lakes that support emergent aquatic vegetation emit disproportionately more methane than open water but are under-represented in upscaled estimates of lake greenhouse gas emissions. These shallow areas are typically less than ∼1.5 m deep and can be detected with synthetic aperture radar (SAR). To assess the importance of lake emergent vegetation (LEV) zones to landscape-scale methane emissions, we combine airborne SAR mapping with field measurements of vegetated and open-water methane flux. First, we use Uninhabited Aerial Vehicle SAR data from the NASA Arctic-Boreal Vulnerability Experiment to map LEV in 4,572 lakes across four Arctic-boreal study areas and find it comprises ∼16% of lake area, exceeding previous estimates, and exhibiting strong regional differences (averaging 59 [50–68]%, 22 [20–25]%, 1.0 [0.8–1.2]%, and 7.0 [5.0–12]% of lake areas in the Peace-Athabasca Delta, Yukon Flats, and northern and southern Canadian Shield, respectively). Next, we account for these vegetated areas through a simple upscaling exercise using paired methane fluxes from regions of open water and LEV. After excluding vegetated areas that could be accounted for as wetlands, we find that inclusion of LEV increases overall lake emissions by 21 [18–25]% relative to estimates that do not differentiate lake zones. While LEV zones are proportionately greater in small lakes, this relationship is weak and varies regionally, underscoring the need for methane-relevant remote sensing measurements of lake zones and a consistent criterion for distinguishing wetlands. Finally, Arctic-boreal lake methane upscaling estimates can be improved with more measurements from all lake zones.
","language":"English","publisher":"Wiley","doi":"10.1029/2021JG006635","usgsCitation":"Kyzivat, E.D., Smith, L., Garcia-Tigreros, F., Huang, C., Wang, C., Langhorst, T., Fayne, J.V., Harlan, M., Ishitsuka, Y., Feng, D., Dolan, W., Pitcher, L.H., Wickland, K., Dornblaser, M., Striegl, R.G., Pavelsky, T.M., Butman, D.E., and Gleason, C.J., 2022, The importance of lake emergent aquatic vegetation for estimating Arctic-boreal methane emissions: Journal of Geophysical Research: Biogeosciences, v. 127, e2021, 23 p., https://doi.org/10.1029/2021JG006635.","productDescription":"e2021, 23 p.","ipdsId":"IP-135368","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":447679,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021jg006635","text":"Publisher Index Page"},{"id":402450,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -147.83203125,\n 66.31986144668052\n ],\n [\n -143.7890625,\n 66.31986144668052\n ],\n [\n -143.7890625,\n 66.94727435155409\n ],\n [\n -147.83203125,\n 66.94727435155409\n ],\n [\n -147.83203125,\n 66.31986144668052\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.5986328125,\n 63.6949869286095\n ],\n [\n -111.73095703125,\n 63.6949869286095\n ],\n [\n -111.73095703125,\n 65.22910188319217\n ],\n [\n -113.5986328125,\n 65.22910188319217\n ],\n [\n -113.5986328125,\n 63.6949869286095\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.400390625,\n 62.298581128718226\n ],\n [\n -114.345703125,\n 62.298581128718226\n ],\n [\n -114.345703125,\n 62.865168668923125\n ],\n [\n -115.400390625,\n 62.865168668923125\n ],\n [\n -115.400390625,\n 62.298581128718226\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.8408203125,\n 58.459228692360625\n ],\n [\n -110.89599609375,\n 58.459228692360625\n ],\n [\n -110.89599609375,\n 59.16466752496466\n ],\n [\n -111.8408203125,\n 59.16466752496466\n ],\n [\n -111.8408203125,\n 58.459228692360625\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"127","noUsgsAuthors":false,"publicationDate":"2022-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Kyzivat, Ethan D.","contributorId":292525,"corporation":false,"usgs":false,"family":"Kyzivat","given":"Ethan","email":"","middleInitial":"D.","affiliations":[{"id":16929,"text":"Brown University","active":true,"usgs":false}],"preferred":false,"id":844970,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Laurence C.","contributorId":169004,"corporation":false,"usgs":false,"family":"Smith","given":"Laurence C.","affiliations":[{"id":13022,"text":"Department of Geography, University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":844971,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Garcia-Tigreros, Fenix 0000-0001-8694-9046","orcid":"https://orcid.org/0000-0001-8694-9046","contributorId":194744,"corporation":false,"usgs":false,"family":"Garcia-Tigreros","given":"Fenix","email":"","affiliations":[],"preferred":false,"id":844972,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huang, Chang","contributorId":292526,"corporation":false,"usgs":false,"family":"Huang","given":"Chang","email":"","affiliations":[{"id":16929,"text":"Brown University","active":true,"usgs":false}],"preferred":false,"id":844973,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Chao","contributorId":292527,"corporation":false,"usgs":false,"family":"Wang","given":"Chao","email":"","affiliations":[{"id":27517,"text":"University of North Carolina - Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":844974,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Langhorst, Theodore","contributorId":292528,"corporation":false,"usgs":false,"family":"Langhorst","given":"Theodore","email":"","affiliations":[{"id":27517,"text":"University of North Carolina - Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":844975,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fayne, Jessica V.","contributorId":292529,"corporation":false,"usgs":false,"family":"Fayne","given":"Jessica","email":"","middleInitial":"V.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":844976,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Harlan, Merritt E.","contributorId":292530,"corporation":false,"usgs":false,"family":"Harlan","given":"Merritt E.","affiliations":[{"id":62930,"text":"UMass-Amherst","active":true,"usgs":false}],"preferred":false,"id":844977,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ishitsuka, Yuta","contributorId":292531,"corporation":false,"usgs":false,"family":"Ishitsuka","given":"Yuta","email":"","affiliations":[{"id":62930,"text":"UMass-Amherst","active":true,"usgs":false}],"preferred":false,"id":844978,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Feng, Dongmei","contributorId":219349,"corporation":false,"usgs":false,"family":"Feng","given":"Dongmei","email":"","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":844979,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Dolan, Wayana 0000-0001-8405-4302","orcid":"https://orcid.org/0000-0001-8405-4302","contributorId":265350,"corporation":false,"usgs":false,"family":"Dolan","given":"Wayana","email":"","affiliations":[{"id":27051,"text":"University of North Carolina at Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":844980,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Pitcher, Lincoln H.","contributorId":169006,"corporation":false,"usgs":false,"family":"Pitcher","given":"Lincoln","email":"","middleInitial":"H.","affiliations":[{"id":13022,"text":"Department of Geography, University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":844981,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Wickland, Kimberly 0000-0002-6400-0590","orcid":"https://orcid.org/0000-0002-6400-0590","contributorId":208471,"corporation":false,"usgs":true,"family":"Wickland","given":"Kimberly","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":844982,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Dornblaser, Mark 0000-0002-6298-3757","orcid":"https://orcid.org/0000-0002-6298-3757","contributorId":220741,"corporation":false,"usgs":true,"family":"Dornblaser","given":"Mark","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":844983,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":844984,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Pavelsky, Tamlin M.","contributorId":258838,"corporation":false,"usgs":false,"family":"Pavelsky","given":"Tamlin","email":"","middleInitial":"M.","affiliations":[{"id":52312,"text":"Department of Geological Sciences, University of North Carolina, Chapel Hill, North Carolina, USA","active":true,"usgs":false}],"preferred":false,"id":844985,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Butman, David E.","contributorId":145535,"corporation":false,"usgs":false,"family":"Butman","given":"David","email":"","middleInitial":"E.","affiliations":[{"id":16142,"text":"School of Environmental and Forest Sciences & Environmental Engineering, University of Washington, Seattle","active":true,"usgs":false}],"preferred":false,"id":844986,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Gleason, Colin J.","contributorId":169003,"corporation":false,"usgs":false,"family":"Gleason","given":"Colin","email":"","middleInitial":"J.","affiliations":[{"id":13022,"text":"Department of Geography, University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":844987,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70237019,"text":"70237019 - 2022 - Teams, networks, and networks of networks advancing our understanding and conservation of inland waters","interactions":[],"lastModifiedDate":"2022-09-27T18:26:23.163194","indexId":"70237019","displayToPublicDate":"2022-05-23T12:57:32","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Teams, networks, and networks of networks advancing our understanding and conservation of inland waters","docAbstract":"Networks are defined as groups of interconnected people and things, and by this definition, networks play a major role in the science of inland waters. In this article, we bring the latest social network research to understand and improve inland waters science and conservation outcomes. What we found is that relationships matter.\n\nDifferent teams and networks have different objectives and lifespans. Consider this: Data collection networks may persist for decades, whereas knowledge-generating teams may exist only for months. The structure of connections in a network determines how easily information or resources can flow or pass through a network, which then influences the ability of the network to accomplish work like creating and applying new knowledge, integrating knowledge across fields, or coordinating collective action.\n\nWhen independent networks designed around different purposes become connected to achieve new goals, a network of networks is formed, where each layer is a unique network defined by social, geographic, and temporal boundaries and distinct types of connections. This structure has a lot of potential for transformative work, but is especially susceptible to failure if one of the cross-network connections fails.\n\nFrom the smallest of inland waters research teams to the largest, multi-institutional, international collaborations, an understanding of how the connections between people are created and maintained can be used to set up conditions for success.","largerWorkTitle":"Encyclopedia of inland waters","language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-819166-8.00054-2","usgsCitation":"Read, E., Cross, J., Herman-Mercer, N.M., Oliver, S.K., and O’Reilly, C.M., 2022, Teams, networks, and networks of networks advancing our understanding and conservation of inland waters, chap. of Encyclopedia of inland waters, v. 4, p. 607-624, https://doi.org/10.1016/B978-0-12-819166-8.00054-2.","productDescription":"18 p.","startPage":"607","endPage":"624","ipdsId":"IP-126937","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":407456,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","edition":"2nd","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Tockner, Klement","contributorId":224174,"corporation":false,"usgs":false,"family":"Tockner","given":"Klement","email":"","affiliations":[{"id":40838,"text":"FWF Austrian Science Fund","active":true,"usgs":false}],"preferred":false,"id":853141,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Mehner, Thomas","contributorId":272917,"corporation":false,"usgs":false,"family":"Mehner","given":"Thomas","email":"","affiliations":[{"id":38332,"text":"Leibniz-Institute of Freshwater Ecology and Inland Fisheries","active":true,"usgs":false}],"preferred":false,"id":853142,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Read, Emily 0000-0002-9617-9433 eread@usgs.gov","orcid":"https://orcid.org/0000-0002-9617-9433","contributorId":190110,"corporation":false,"usgs":true,"family":"Read","given":"Emily","email":"eread@usgs.gov","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":853096,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cross, Jennifer 0000-0002-5582-4192","orcid":"https://orcid.org/0000-0002-5582-4192","contributorId":297016,"corporation":false,"usgs":false,"family":"Cross","given":"Jennifer","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":853097,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herman-Mercer, Nicole M. 0000-0001-5933-4978 nhmercer@usgs.gov","orcid":"https://orcid.org/0000-0001-5933-4978","contributorId":3927,"corporation":false,"usgs":true,"family":"Herman-Mercer","given":"Nicole","email":"nhmercer@usgs.gov","middleInitial":"M.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":853098,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":853099,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O’Reilly, Catherine M.","contributorId":150334,"corporation":false,"usgs":false,"family":"O’Reilly","given":"Catherine","email":"","middleInitial":"M.","affiliations":[{"id":18004,"text":"Illinois State University","active":true,"usgs":false}],"preferred":false,"id":853100,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70247281,"text":"70247281 - 2022 - Measurement and variability of lake metabolism","interactions":[],"lastModifiedDate":"2023-07-26T14:37:33.211427","indexId":"70247281","displayToPublicDate":"2022-05-23T09:35:06","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Measurement and variability of lake metabolism","docAbstract":"Aim: The aim of this article is to provide an overview of what contributes to lake metabolism, a brief overview of methods for estimating lake metabolism, and drivers of metabolism variability within and across lakes.
Main concepts covered: In this article, we describe the key drivers of within and across lake variability in metabolism including lake morphometry, nutrients, light availability, temperature, and organic matter and how these drivers shape lake metabolic patterns across Earth's biomes.
Conclusion/Outlook: We end the article with how interacting factors influence lake metabolic rates and how recent and future global changes may influence lake metabolism patterns.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of Inland Waters","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-819166-8.00029-3","usgsCitation":"Zwart, J.A., and Brighenti, L.S., 2022, Measurement and variability of lake metabolism, chap. of Encyclopedia of Inland Waters, v. 2, p. 163-173, https://doi.org/10.1016/B978-0-12-819166-8.00029-3.","productDescription":"11 p.","startPage":"163","endPage":"173","ipdsId":"IP-120390","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":419351,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","edition":"Second Edition","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brighenti, Ludmila S","contributorId":317713,"corporation":false,"usgs":false,"family":"Brighenti","given":"Ludmila","email":"","middleInitial":"S","affiliations":[{"id":69135,"text":"Universidade do Estado de Minas Gerais","active":true,"usgs":false}],"preferred":false,"id":879104,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70237245,"text":"70237245 - 2022 - Hydrological cycle and water budgets","interactions":[],"lastModifiedDate":"2022-10-05T14:33:45.429244","indexId":"70237245","displayToPublicDate":"2022-05-23T09:28:40","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Hydrological cycle and water budgets","docAbstract":"In this chapter, we describe the hydrological cycle and each of its components (pools). The hydrological cycle is important to the transport and cycling of nutrients and energy. Quantifying the various components of the hydrological cycle, referred to as constructing water budget for a defined area, is an important framework for wise and equitable water management. The hydrological cycle has changed as the result of human activity affecting specific components of the water budget and the movement of water between the components. Water budgets are provided for two defined areas: the earth as a whole and the watershed of a small inland lake.
Given a specific area with well-defined boundaries, constructing a water budget consists of quantifying the amount and relationships among inflow, outflow, and change in storage within a defined area of the hydrological cycle, water budgets relevant to inland waters and aquatic ecosystems, and how the hydrological cycle and water budgets have been affected by anthropogenic modifications.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of inland waters","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-819166-8.00008-6","usgsCitation":"Robertson, D., Perlman, H.A., and Narisimhan, T.N., 2022, Hydrological cycle and water budgets, chap. of Encyclopedia of inland waters, p. 19-27, https://doi.org/10.1016/B978-0-12-819166-8.00008-6.","productDescription":"9 p.","startPage":"19","endPage":"27","ipdsId":"IP-121572","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":407961,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Second Edition","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Robertson, Dale M. 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":853822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perlman, Howard A. 0000-0002-2392-0737","orcid":"https://orcid.org/0000-0002-2392-0737","contributorId":297327,"corporation":false,"usgs":true,"family":"Perlman","given":"Howard","email":"","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":853823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Narisimhan, T. N.","contributorId":297329,"corporation":false,"usgs":false,"family":"Narisimhan","given":"T.","email":"","middleInitial":"N.","affiliations":[{"id":33770,"text":"University of California at Berkeley","active":true,"usgs":false}],"preferred":false,"id":853824,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70238776,"text":"70238776 - 2022 - Worldwide wetland loss and conservation of biodiversity and ecosystem services","interactions":[],"lastModifiedDate":"2022-12-12T15:15:10.893711","indexId":"70238776","displayToPublicDate":"2022-05-23T09:12:32","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Worldwide wetland loss and conservation of biodiversity and ecosystem services","docAbstract":"Aim: Best strategies for future conservation and management to address global and regional trends in wetland loss and degradation are assessed in this article.
Main concepts covered: Direct drivers of wetland loss and change include land drainage and filling, hydrologic alteration, degradation from pollutants and sediments, and conversion to agriculture, urban and industrial usage. Estimates of global wetland loss are as high as 87% since 1700 CE. All regions of the world have lost wetland area. The designation of wetland protected area reduces disturbance by humans and supports the conservation of biodiversity and habitat. Protected areas have been designated by local, state, or federal entities, NGOs (e.g., Nature Conservancy), and the Ramsar Convention on Wetlands. Protected wetlands have great value for human society. For example, wetlands such as peatland and swamp store carbon that would otherwise be released as greenhouse gases to the atmosphere. A case study of the Keoladeo National Park, Rajasthan, India underscores the importance of maintaining water supply to maintain aquatic vegetation in protected wetlands.
Conclusion/outlook: Given the combined stresses of land-use and climate change to wetland protected areas, management of altered wetlands may improve their function. Beneficial management actions can include freshwater remediation of hydrologically-altered floodplains, improved wetland reserve design, assisted migration, and the softening of burning/cutting during drought. A better knowledge of potential of management actions to remediate land-use change will be helpful in addressing protected area management to promote conservation in the future.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of inland waters","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-819166-8.00058-X","usgsCitation":"Middleton, B., 2022, Worldwide wetland loss and conservation of biodiversity and ecosystem services, chap. of Encyclopedia of inland waters, v. 3, p. 288-294, https://doi.org/10.1016/B978-0-12-819166-8.00058-X.","productDescription":"7 p.","startPage":"288","endPage":"294","ipdsId":"IP-118283","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":410283,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Middleton, Beth 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":222689,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":858560,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70243254,"text":"70243254 - 2022 - An introduction to current climate projections and their use in climate impacts research","interactions":[],"lastModifiedDate":"2023-05-05T13:37:14.428567","indexId":"70243254","displayToPublicDate":"2022-05-23T08:28:07","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"1","title":"An introduction to current climate projections and their use in climate impacts research","docAbstract":"Using climate projections to evaluate future climate impacts and their associated risks requires a background knowledge of the nature of climate change, use of climate models to develop future projections, and knowledge of how to address climate scenario uncertainty. This chapter provides an overview of climate and climate change, some of the foundational climate science that underlies current climate change assessments, and a brief introduction to climate models and climate scenario uncertainty. Global projections of temperature and precipitation changes from the recent Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6) and a brief comparison to the prior assessment (AR5) are provided. The main sources of uncertainty in these projections include climate variability, climate model differences and treatment of scientific knowledge gaps, and greenhouse gas (GHG) emissions. When projections are downscaled to local resolution, downscaling is an additional source of uncertainty. These uncertainties can be incorporated in assessments of climate impacts by choosing a range of scenarios that directly address the sources of uncertainty. Evaluating the likelihood of a given climate impact on animal health or management strategies requires consideration of the main sources of climate projection uncertainties. Adaptation requires consideration of global-to-regional contexts of climate changes and impacts, but also adaptive capacity.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Climate change and animal health","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"CRC Press","doi":"10.1201/9781003149774-1","usgsCitation":"Littell, J., 2022, An introduction to current climate projections and their use in climate impacts research, chap. 1 of Climate change and animal health, p. 1-21, https://doi.org/10.1201/9781003149774-1.","productDescription":"21 p.","startPage":"1","endPage":"21","ipdsId":"IP-135325","costCenters":[{"id":49028,"text":"Alaska Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":416757,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Stephen, Craig","contributorId":168939,"corporation":false,"usgs":false,"family":"Stephen","given":"Craig","email":"","affiliations":[],"preferred":false,"id":871855,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Duncan, Colleen G.","contributorId":15512,"corporation":false,"usgs":false,"family":"Duncan","given":"Colleen","email":"","middleInitial":"G.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":871856,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Littell, Jeremy S. 0000-0002-5302-8280","orcid":"https://orcid.org/0000-0002-5302-8280","contributorId":205907,"corporation":false,"usgs":true,"family":"Littell","given":"Jeremy","middleInitial":"S.","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":871684,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70238744,"text":"70238744 - 2022 - Wetlands under global change","interactions":[],"lastModifiedDate":"2022-12-07T13:13:47.960346","indexId":"70238744","displayToPublicDate":"2022-05-23T07:12:50","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Wetlands under global change","docAbstract":"Wetlands are among the ecosystem types most threatened by global change, including both climate change and other anthropogenic factors such as sea level rise, urban development, deforestation, agricultural land use, drainage, levees, tidal flow restrictions, pollution, eutrophication, and fires. Wetlands not only store disproportionate amounts of carbon compared to other terrestrial ecosystems, but they lie at the terrestrial-aquatic interface crucial to understanding landscape and global scale biogeochemical cycles. In this chapter, we focus on the major global change factors affecting wetlands and the responses of different wetland types to those global change factors. Special attention is given to direct responses to increasing atmospheric carbon dioxide levels. Because of their hydrological connections and placement at the terrestrial-aquatic interface, the conservation of wetlands involves accounting for uncertainties related to interacting stressors. While the past decades have seen many important experimental and observational studies of wetland responses to global change factors, large uncertainties remain, especially within tropical regions where even the basic extent of wetland ecosystems is not well documented.
Earthquakes occur as a burst of sudden ground shaking created by the release of accumulated stress along a fault, often influenced by movement of the world’s tectonic plates. Ground shaking from an earthquake can generate additional hazards, including landslides, liquefaction, and tsunami. According to the 2019 “Global Assessment Report on Disaster Risk Reduction”, earthquakes combined with tsunami are the most damaging environmental hazards globally. Impacts of earthquakes and tsunami on people have increased around the world as human development of built infrastructure continues to expand. Adverse earthquake and tsunami impacts can be reduced through strategies including land-use planning, engineering, mitigation and preparedness, emergency planning, warnings, and exercises. The specific disaster risk reduction approaches taken will depend on the country, considering the geography, built environment, and social and cultural contexts. Wherever the location, it is important that such measures are considered and implemented holistically, as singular approaches may not be effective in addressing earthquake and tsunami challenges.
a.
Aim: To demonstrate the societal values of inland fishes through nine services provided by inland fishes. Each service is defined, key stakeholders identified, and threats enumerated. Diverse case studies (geography, taxonomy, fishery-type) provide examples to highlight the societal values around the world.
b.
Main concepts: Nine societal services of inland fishes – 1. Livelihoods and subsistence income; 2. Commercial income; 3. Food and nutrition; 4. Recreational services; 5. Cultural services; 6. Educational and scientific opportunities within fisheries; 7. Biodiversity and ecosystem function; 8. Regulation and indicator of freshwater quality; and 9. Regulation of freshwater quantity and natural flow regimes.
c.
Conclusion/outlook: Inland fishes have immense social, economic, and ecological importance. Freshwater ecosystems face a diverse array of pressures that threaten the fulfillment of societal services. Addressing key knowledge gaps can assist with sustainable management and conservation of these important resources.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The Encyclopedia of Inland Waters","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-819166-8.00030-X","usgsCitation":"Lynch, A., Arthur, R.I., Baigun, C., Claussen, J., Kangur, K., Koning, A.A., Murchie, K.J., Myers, B., Stokes, G.L., Tingley, R.W., and Youn, S., 2022, Societal values of inland fishes, chap. of The Encyclopedia of Inland Waters, v. 4, p. 475-490, https://doi.org/10.1016/B978-0-12-819166-8.00030-X.","productDescription":"16 p.","startPage":"475","endPage":"490","ipdsId":"IP-120829","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":401744,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","edition":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lynch, Abigail J. 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":207361,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","middleInitial":"J.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":844170,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arthur, Robert I.","contributorId":292266,"corporation":false,"usgs":false,"family":"Arthur","given":"Robert","email":"","middleInitial":"I.","affiliations":[{"id":62853,"text":"Woodhill Solutions","active":true,"usgs":false}],"preferred":false,"id":844171,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baigun, Claudio","contributorId":292267,"corporation":false,"usgs":false,"family":"Baigun","given":"Claudio","email":"","affiliations":[{"id":62854,"text":"Institute of Research and Environmental Engineering","active":true,"usgs":false}],"preferred":false,"id":844172,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Claussen, Julie E.","contributorId":292268,"corporation":false,"usgs":false,"family":"Claussen","given":"Julie E.","affiliations":[{"id":47804,"text":"Fisheries Conservation Foundation","active":true,"usgs":false}],"preferred":false,"id":844173,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kangur, Külli","contributorId":292269,"corporation":false,"usgs":false,"family":"Kangur","given":"Külli","affiliations":[{"id":18000,"text":"Estonian University of Life Sciences","active":true,"usgs":false}],"preferred":false,"id":844174,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Koning, Aaron A.","contributorId":292270,"corporation":false,"usgs":false,"family":"Koning","given":"Aaron","email":"","middleInitial":"A.","affiliations":[{"id":16704,"text":"University of Nevada - Reno","active":true,"usgs":false}],"preferred":false,"id":844175,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Murchie, Karen J.","contributorId":292271,"corporation":false,"usgs":false,"family":"Murchie","given":"Karen","email":"","middleInitial":"J.","affiliations":[{"id":39376,"text":"Shedd Aquarium","active":true,"usgs":false}],"preferred":false,"id":844176,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Myers, Bonnie 0000-0002-3170-2633","orcid":"https://orcid.org/0000-0002-3170-2633","contributorId":219702,"corporation":false,"usgs":true,"family":"Myers","given":"Bonnie","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":844177,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stokes, Gretchen L.","contributorId":292272,"corporation":false,"usgs":false,"family":"Stokes","given":"Gretchen","email":"","middleInitial":"L.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":844178,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Tingley, Ralph William 0000-0002-1689-2133","orcid":"https://orcid.org/0000-0002-1689-2133","contributorId":258043,"corporation":false,"usgs":true,"family":"Tingley","given":"Ralph","email":"","middleInitial":"William","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":844179,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Youn, So-Jung","contributorId":292273,"corporation":false,"usgs":false,"family":"Youn","given":"So-Jung","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":844180,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70231692,"text":"fs20223033 - 2022 - Selenium in the Kootenai River Basin, Montana and Idaho, United States, and British Columbia, Canada","interactions":[],"lastModifiedDate":"2026-03-24T21:18:41.523205","indexId":"fs20223033","displayToPublicDate":"2022-05-23T06:58:26","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3033","displayTitle":"Selenium in the Kootenai River Basin, Montana and Idaho, United States, and British Columbia, Canada","title":"Selenium in the Kootenai River Basin, Montana and Idaho, United States, and British Columbia, Canada","docAbstract":"Selenium entering the 90-mile long transboundary Koocanusa Reservoir (also called Lake Koocanusa) in southeastern British Columbia, Canada, and northwestern Montana, United States, has been measured at concentrations above State and Federal water-quality and aquatic life standards. The reservoir is within the international Kootenai (or “Kootenay” in Canada) drainage basin, which contains critical habitat for native fish species and is impounded by Libby Dam 16 miles upstream from Libby, Montana. Since 1984, selenium concentrations have ranged from below detection to greater than 8 micrograms per liter in the Elk River, measured 2.2 miles above its discharge into Koocanusa Reservoir at a British Columbia environmental monitoring station (site 0200016). Selenium is a required micro-nutrient, but elevated concentrations in water bioaccumulate in egg-laying fish and birds, causing various sublethal effects and death. One possible source of selenium in the Kootenai River Basin is the excavation of bedrock in the Elk River Valley to access coal seams for metallurgical steelmaking and coal production. Five open-pit coal mines are operating in this region of southeastern British Columbia that produce about 21 million tons of metallurgical coal annually.
Site-specific selenium standards were established for the reservoir in 2020 following collaborative work by the U.S. Geological Survey, Montana Department of Environmental Quality, the British Columbia Ministry of Environment and Climate Change Strategy, the Lake Koocanusa Monitoring and Research Working Group, and the Selenium Technical Subcommittee. The standards of 0.8 microgram per liter for dissolved selenium in the water column and 15.1 milligrams per kilogram dry weight for fish egg (ovary) tissue (in addition to the muscle and wholebody standards) were adopted into Montana State law in 2020 and approved by the U.S. Environmental Protection Agency in 2021.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223033","usgsCitation":"U.S. Geological Survey, 2022, Selenium in the Kootenai River Basin, Montana and Idaho, United States, and British Columbia, Canada: U.S. Geological Survey Fact Sheet 2022–3033, 4 p., https://doi.org/10.3133/fs20223033.","productDescription":"Report: 4 p.; Data Release; 3 Datasets","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-139916","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":400866,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YYVV7R","text":"USGS data release","linkHelpText":"Selenium and mercury in fish tissues from the Kootenai River, Montana and Idaho, 2018–2019"},{"id":400864,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2022/3033/fs20223033.XML"},{"id":400865,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3033/images"},{"id":400862,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3033/coverthb.jpg"},{"id":400863,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3033/fs20223033.pdf","text":"Report","size":"2.65 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3033"},{"id":501490,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113067.htm","linkFileType":{"id":5,"text":"html"}},{"id":400881,"rank":9,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/fs20223033/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":400869,"rank":8,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":400868,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://www.waterqualitydata.us","text":"National Water Quality Monitoring Council database","linkHelpText":"—Water Quality Portal"},{"id":400867,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://kwt.bcwatertool.ca/drainagebasin","text":"British Columbia Ministry of Forests Lands Natural Resource Operations and Rural Development database","linkHelpText":"—BC Water Tool"}],"country":"Canada, United States","state":"British Columbia, Idaho, Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.90551757812499,\n 47.88688085106901\n ],\n [\n -114.54345703125,\n 47.88688085106901\n ],\n [\n -114.54345703125,\n 50.48547354578499\n ],\n [\n -116.90551757812499,\n 50.48547354578499\n ],\n [\n -116.90551757812499,\n 47.88688085106901\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
The spatial ecology of individuals often varies within a population or species. Identifying how individuals in different classes interact with their environment can lead to a better understanding of population responses to human activities and environmental change and improve population estimates. Most inferences about polar bear (Ursus maritimus) spatial ecology are based on data from adult females due to morphological constraints on applying satellite radio collars to other classes of bears. Recent studies, however, have provided limited movement data for adult males and sub-adults of both sexes using ear-mounted and glue-on tags. We evaluated class-specific movements and step selection patterns for polar bears in the Chukchi Sea subpopulation during spring.
We developed hierarchical Bayesian models to evaluate polar bear movement (i.e., step length and directional persistence) and step selection at the scale of 4-day step lengths. We assessed differences in movement and step selection parameters among the three classes of polar bears (i.e., adult males, sub-adults, and adult females without cubs-of-the-year).
Adult males had larger step lengths and less directed movements than adult females. Sub-adult movement parameters did not differ from the other classes but point estimates were most similar to adult females. We did not detect differences among polar bear classes in step selection parameters and parameter estimates were consistent with previous studies.
Our findings support the use of estimated step selection patterns from adult females as a proxy for other classes of polar bears during spring. Conversely, movement analyses indicated that using data from adult females as a proxy for the movements of adult males is likely inappropriate. We recommend that researchers consider whether it is valid to extend inference derived from adult female movements to other classes, based on the questions being asked and the spatial and temporal scope of the data. Because our data were specific to spring, these findings highlight the need to evaluate differences in movement and step selection during other periods of the year, for which data from ear-mounted and glue-on tags are currently lacking.
","language":"English","publisher":"Springer Nature","doi":"10.1186/s40462-022-00326-5","usgsCitation":"Wilson, R., St Martin, M., Regehr, E.V., and Rode, K.D., 2022, Intrapopulation differences in polar bear movement and step selection patterns: Movement Ecology, v. 10, 25, 12 p., https://doi.org/10.1186/s40462-022-00326-5.","productDescription":"25, 12 p.","ipdsId":"IP-135708","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":447686,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-022-00326-5","text":"Publisher Index Page"},{"id":407206,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationDate":"2022-05-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilson, Ryan R. ","contributorId":222456,"corporation":false,"usgs":false,"family":"Wilson","given":"Ryan R. ","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":852744,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"St Martin, Michelle","contributorId":296903,"corporation":false,"usgs":false,"family":"St Martin","given":"Michelle","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":852745,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Regehr, Eric V. 0000-0003-4487-3105","orcid":"https://orcid.org/0000-0003-4487-3105","contributorId":66364,"corporation":false,"usgs":false,"family":"Regehr","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":852746,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":852747,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70252816,"text":"70252816 - 2022 - Environmental drivers of cyanobacterial abundance and cyanotoxin production in backwaters of the Upper Mississippi River","interactions":[],"lastModifiedDate":"2024-04-08T23:47:34.73073","indexId":"70252816","displayToPublicDate":"2022-05-22T08:46:21","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Environmental drivers of cyanobacterial abundance and cyanotoxin production in backwaters of the Upper Mississippi River","docAbstract":"High densities of cyanobacteria in aquatic ecosystems can cause impacts to ecosystem services because they serve as a poor-quality food resource, produce toxins and can indirectly cause a variety of other negative impacts to water quality. There are many hypotheses about the potential environmental drivers of variation in cyanobacterial abundance and toxicity, but these hypotheses have rarely been considered in combination and rarely been examined in large river ecosystems. Here we use monthly data from backwater habitats of the Upper Mississippi River (UMR) to evaluate associations between environmental conditions and cyanobacterial abundance and toxicity (microcystin and anatoxin-a) that would be expected based on several hypotheses. Backwaters in the Mississippi River vary in flushing rate, temperature, turbidity, nutrient availability, water depth and vegetative cover. We find support for hypotheses that suggest physical conditions in backwaters (flushing rate, temperature, turbidity, rooted vegetation cover and water depth) and nutrient availability influence cyanobacterial abundance and toxicity. We then used structural equation modeling to incorporate several hypotheses into a causal modeling framework, which indicated that backwater connectivity (flushing) strongly influences cyanobacterial abundance via the regulation of water temperature, and that nutrient availability strongly influences the presence of microcystin concentrations above our detection limit. Our data suggest that management of backwater connectivity could influence cyanobacterial abundance and toxicity in UMR backwaters. Reconnecting backwaters (via alteration of levees) could serve as a local adaptation to minimize the effects of climate change and excessive nutrient loading.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3987","usgsCitation":"Giblin, S.M., Larson, J.H., and King, J.D., 2022, Environmental drivers of cyanobacterial abundance and cyanotoxin production in backwaters of the Upper Mississippi River: River Research and Applications, v. 38, no. 6, p. 1115-1128, https://doi.org/10.1002/rra.3987.","productDescription":"14 p.","startPage":"1115","endPage":"1128","ipdsId":"IP-134311","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":427556,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United Stares","state":"Wisconsin","otherGeospatial":"Blue Lake, Great River Backwater, Indian Slough, Lizzy Paul's Pond, Mertes Lake, Second Lake, Stoddard Backwater, Trempealeau Wildlife Refuge, Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.7533542542472,\n 44.157127527506105\n ],\n [\n -91.7533542542472,\n 43.58283679178368\n ],\n [\n -90.94310098095912,\n 43.58283679178368\n ],\n [\n -90.94310098095912,\n 44.157127527506105\n ],\n [\n -91.7533542542472,\n 44.157127527506105\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"38","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-05-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Giblin, Shawn M.","contributorId":335419,"corporation":false,"usgs":false,"family":"Giblin","given":"Shawn","email":"","middleInitial":"M.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":898322,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":898323,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"King, Jeremy D.","contributorId":335420,"corporation":false,"usgs":false,"family":"King","given":"Jeremy","email":"","middleInitial":"D.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":898324,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70232532,"text":"70232532 - 2022 - Cryptic extinction risk in a western Pacific lizard radiation","interactions":[],"lastModifiedDate":"2022-08-02T15:06:39.035711","indexId":"70232532","displayToPublicDate":"2022-05-22T06:37:05","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1006,"text":"Biodiversity and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Cryptic extinction risk in a western Pacific lizard radiation","docAbstract":"Cryptic ecologies, the Wallacean Shortfall of undocumented species’ geographical ranges and the Linnaean Shortfall of undescribed diversity, are all major barriers to conservation assessment. When these factors overlap with drivers of extinction risk, such as insular distributions, the number of threatened species in a region or clade may be underestimated, a situation we term ‘cryptic extinction risk’. The genus Lepidodactylus is a diverse radiation of insular and arboreal geckos that occurs across the western Pacific. Previous work on Lepidodactylus showed evidence of evolutionary displacement around continental fringes, suggesting an inherent vulnerability to extinction from factors such as competition and predation. We sought to (1) comprehensively review status and threats, (2) estimate the number of undescribed species, and (3) estimate extinction risk in data deficient and candidate species, in Lepidodactylus. From our updated IUCN Red List assessment, 60% of the 58 recognized species are threatened (n = 15) or Data Deficient (n = 21), which is higher than reported for most other lizard groups. Species from the smaller and isolated Pacific islands are of greatest conservation concern, with most either threatened or Data Deficient, and all particularly vulnerable to invasive species. We estimated 32 undescribed candidate species and linear modelling predicted that an additional 18 species, among these and the data deficient species, are threatened with extinction. Focusing efforts to resolve the taxonomy and conservation status of key taxa, especially on small islands in the Pacific, is a high priority for conserving this remarkably diverse, yet poorly understood, lizard fauna. Our data highlight how cryptic ecologies and cryptic diversity combine and lead to significant underestimation of extinction risk.
No abstract available.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.3770","usgsCitation":"Converse, S.J., McClintock, B., and Conn, P., 2022, Linking capture–recapture and movement: Ecology, v. 103, no. 10, e3770, 3 p., https://doi.org/10.1002/ecy.3770.","productDescription":"e3770, 3 p.","ipdsId":"IP-135754","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":490655,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.3770","text":"Publisher Index Page"},{"id":489383,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"103","issue":"10","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":938917,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McClintock, Brett T.","contributorId":356249,"corporation":false,"usgs":false,"family":"McClintock","given":"Brett T.","affiliations":[{"id":84944,"text":"Marine Mammal Laboratory","active":true,"usgs":false}],"preferred":false,"id":938918,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conn, Paul B.","contributorId":356250,"corporation":false,"usgs":false,"family":"Conn","given":"Paul B.","affiliations":[{"id":84944,"text":"Marine Mammal Laboratory","active":true,"usgs":false}],"preferred":false,"id":938919,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227789,"text":"70227789 - 2022 - Greenhouse gas balances in coastal ecosystems: Current challenges in “blue carbon” estimation and significance to national greenhouse gas inventories","interactions":[],"lastModifiedDate":"2022-09-12T16:49:50.821961","indexId":"70227789","displayToPublicDate":"2022-05-21T11:39:56","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"12","title":"Greenhouse gas balances in coastal ecosystems: Current challenges in “blue carbon” estimation and significance to national greenhouse gas inventories","docAbstract":"Coastal wetlands are defined herein as inundated, vegetated ecosystems with hydrology, and biogeochemistry influenced by sea levels, at timescales of tides to millennia. Coastal wetlands are necessary components of global greenhouse gas estimation and scenario modeling, both for continental and oceanic mass balances. The carbon pools and fluxes on coastal lands, especially those influenced by tidal drivers and sea level rise, are distinct in their magnitude, rates, and uncertainties. We describe herein the pathways taken for a US scale estimation of blue carbon based on annual timesteps and bottom-up modeling, as appropriate for the first effort to include coastal wetlands in the Intergovernmental Panel on Climate Change (IPCC) guidelines for a National Greenhouse Gas Inventory (NGGI). As such, we summarize multiple efforts to reconcile mapping, modeling, and measurement issues and we report the assumptions we made based on data availability. Provided as requested feedback to the IPCC.
Subsidiary Body for Scientific and Technological Advice (SBSTA) evaluation of guidance criteria, these analyses synergistically point scientists, practitioners, and policy makers toward the greatest uncertainties to address in future assessments: coastal wetland methane emissions and carbon dioxide emissions associated with the fate of eroded soil. This is a story of what was learned in the 2014–2018 NASA Carbon Monitoring System project (https://carbon.nasa.gov/cgi-bin/cms_projects.pl), how it informs “good practice” (IPCC 2006) in reporting coastal wetland emissions and removals, and where it points scientifically toward data needs at different temporal and spatial scales.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","publisherLocation":"Balancing greenhouse gas budgets: Accounting for natural and anthropogenic flows of CO2 and other trace gases","doi":"10.1016/B978-0-12-814952-2.00001-0","usgsCitation":"Windham-Myers, L., Holmquist, J., Kroeger, K.D., and Troxler, T., 2022, Greenhouse gas balances in coastal ecosystems: Current challenges in “blue carbon” estimation and significance to national greenhouse gas inventories, p. 403-425, https://doi.org/10.1016/B978-0-12-814952-2.00001-0.","productDescription":"23 p.","startPage":"403","endPage":"425","ipdsId":"IP-123602","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":406543,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Windham-Myers, Lisamarie 0000-0003-0281-9581 lwindham-myers@usgs.gov","orcid":"https://orcid.org/0000-0003-0281-9581","contributorId":2449,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","email":"lwindham-myers@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":832252,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holmquist, James R.","contributorId":272628,"corporation":false,"usgs":false,"family":"Holmquist","given":"James R.","affiliations":[{"id":13510,"text":"Smithsonian Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":832253,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":832254,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Troxler, Tiffany G.","contributorId":272629,"corporation":false,"usgs":false,"family":"Troxler","given":"Tiffany G.","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":832255,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70233467,"text":"70233467 - 2022 - How beavers are changing Arctic landscapes and Earth’s climate","interactions":[],"lastModifiedDate":"2022-07-21T14:16:06.220539","indexId":"70233467","displayToPublicDate":"2022-05-21T09:10:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9348,"text":"Frontiers for Young Minds","active":true,"publicationSubtype":{"id":10}},"title":"How beavers are changing Arctic landscapes and Earth’s climate","docAbstract":"Beavers build dams that change the way water moves between streams, lakes, and the land. In Alaska, beavers are moving north from the forests into the Arctic tundra. When beavers build dams in the Arctic, they cause frozen soil, called permafrost, to thaw. Scientists are studying how beavers and the thawing of permafrost are impacting streams and rivers in Alaska’s national parks. For example, permafrost thaw from beavers can add harmful substances like mercury to streams. Mercury can be taken up by stream food webs, including fish, which then become unhealthy to eat. Permafrost thaw can also move carbon (from dead plants) to beaver ponds. When this carbon decomposes, it can be released from beaver ponds into the air as greenhouse gases, which cause Earth’s climate to warm. Scientists are trying to keep up with these busy beavers to better understand how they are changing Arctic landscapes and Earth’s climate.