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 - 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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":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","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":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","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":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","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.
Great Lakes coastal wetlands (GLCW) have been severely degraded by anthropogenic activity over the last several decades despite their critical role in fish production. Many Great Lakes fish species use coastal wetland habitats for spawning, feeding, shelter, and nurseries throughout the year. The goal of our study was to compare GLCW fish community composition in the spring, summer, and fall months and investigate how water quality relates to fish diversity, the presence of functional groups, and juvenile fish diets. We summarized fish data collected from GLCW across the basin and used the coastal wetland monitoring program’s water quality-land use indicator to quantify water quality. Basin-wide, we found taxonomic and functional group differences in community composition among three sampling seasons, as well as across the range of water quality. Water quality was positively associated with the abundance of small cyprinids and the relative abundance of some habitat and reproductive specialists. Seasonal differences were also observed for many of these functional groups, with more temperature- and pollution-sensitive fishes captured in the spring and more nest-spawning fishes captured in the summer and fall. In our diet study, we found that age-0 fish primarily consumed zooplankton in the fall, whereas age-1 fish primarily consumed macroinvertebrates in the spring. Moreover, wetland quality was positively associated with trichopteran prey abundance. We concluded that taxonomic and functional composition of fish communities in GLCW vary markedly with respect to water quality and season. Thus, a full understanding of communities across a gradient of quality requires multi-season sampling.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s11273-022-09862-8","usgsCitation":"Diller, S., Harrison, A., Kowalski, K., Brady, V., Ciborowski, J., Cooper, M.J., Dumke, J., Gathman, J., Ruetz, C., Uzarski, D.G., Wilcox, D., and Schaeffer, J., 2022, Influences of seasonality and habitat quality on Great Lakes coastal wetland fish community composition and diets: Wetland Ecology and Management, v. 30, p. 439-460, https://doi.org/10.1007/s11273-022-09862-8.","productDescription":"22 p.","startPage":"439","endPage":"460","ipdsId":"IP-133178","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":486155,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.98042758143248,\n 48.00533202110063\n ],\n [\n -92.4544017806511,\n 47.09186420788265\n ],\n [\n -90.93931418529223,\n 46.82009820546638\n ],\n [\n -88.15934346347329,\n 46.49921317133217\n ],\n [\n -87.75820768115408,\n 41.72932138108676\n ],\n [\n -81.47679465253952,\n 41.26802908107109\n ],\n [\n -75.73140554858799,\n 43.76282170300337\n ],\n [\n -82.16775874431909,\n 43.47029804432211\n ],\n [\n -82.73294354635479,\n 45.83385483728805\n ],\n [\n -87.90812366646838,\n 48.31652223525934\n ],\n [\n -89.98042758143248,\n 48.00533202110063\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"30","noUsgsAuthors":false,"publicationDate":"2022-05-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Diller, Sara 0000-0003-1502-0074","orcid":"https://orcid.org/0000-0003-1502-0074","contributorId":223495,"corporation":false,"usgs":true,"family":"Diller","given":"Sara","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":937411,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harrison, Anna M.","contributorId":355448,"corporation":false,"usgs":false,"family":"Harrison","given":"Anna M.","affiliations":[{"id":13588,"text":"Central Michigan University","active":true,"usgs":false}],"preferred":false,"id":937412,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kowalski, Kurt P. 0000-0002-8424-4701 kkowalski@usgs.gov","orcid":"https://orcid.org/0000-0002-8424-4701","contributorId":3768,"corporation":false,"usgs":true,"family":"Kowalski","given":"Kurt P.","email":"kkowalski@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":937413,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brady, Valerie J.","contributorId":355450,"corporation":false,"usgs":false,"family":"Brady","given":"Valerie J.","affiliations":[{"id":18006,"text":"University of Minnesota Duluth","active":true,"usgs":false}],"preferred":false,"id":937414,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ciborowski, Jan J.H.","contributorId":355452,"corporation":false,"usgs":false,"family":"Ciborowski","given":"Jan J.H.","affiliations":[{"id":48871,"text":"University of Windsor","active":true,"usgs":false}],"preferred":false,"id":937415,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cooper, Matthew J.","contributorId":211007,"corporation":false,"usgs":false,"family":"Cooper","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":38169,"text":"University of Southamton, UK","active":true,"usgs":false}],"preferred":false,"id":937416,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dumke, Joshua D.","contributorId":355453,"corporation":false,"usgs":false,"family":"Dumke","given":"Joshua D.","affiliations":[{"id":18006,"text":"University of Minnesota Duluth","active":true,"usgs":false}],"preferred":false,"id":937417,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gathman, Joseph P.","contributorId":172904,"corporation":false,"usgs":false,"family":"Gathman","given":"Joseph P.","affiliations":[],"preferred":false,"id":937418,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ruetz, Carl R. III","contributorId":355456,"corporation":false,"usgs":false,"family":"Ruetz","given":"Carl R. III","affiliations":[{"id":15305,"text":"Grand Valley State University","active":true,"usgs":false}],"preferred":false,"id":937419,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Uzarski, Donald G.","contributorId":211821,"corporation":false,"usgs":false,"family":"Uzarski","given":"Donald","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":937420,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wilcox, Douglas A.","contributorId":244846,"corporation":false,"usgs":false,"family":"Wilcox","given":"Douglas A.","affiliations":[{"id":48999,"text":"Department of Environmental Science and Ecology, The College at Brockport – State University of New York, Brockport, NY","active":true,"usgs":false}],"preferred":false,"id":937421,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Schaeffer, Jeffrey S","contributorId":355459,"corporation":false,"usgs":false,"family":"Schaeffer","given":"Jeffrey S","affiliations":[{"id":56209,"text":"Tennessee Tech University","active":true,"usgs":false}],"preferred":false,"id":937422,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70256691,"text":"70256691 - 2022 - Long-term assessments are critical to determining persistence and shoreline protection from oyster reef nature-based coastal defenses","interactions":[],"lastModifiedDate":"2024-08-02T13:36:28.334711","indexId":"70256691","displayToPublicDate":"2022-05-20T11:23:33","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1454,"text":"Ecological Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Long-term assessments are critical to determining persistence and shoreline protection from oyster reef nature-based coastal defenses","docAbstract":"Nature-based coastal defense using bivalve reefs provides a potentially self-sustaining approach for regions facing high coastal land loss, relative sea level rise and increasing frequency and intensity of storms. Success of such nature-based coastal defense depends on the reef-building species' life history, habitat requirements, and ability to thrive through short-term and longer-term environmental variation, yet few projects have reported on outcomes beyond the first few years. In coastal Louisiana, USA, Crassostrea virginica (oyster) is an ecosystem engineer, creating self-sustaining, vertically accreting reefs that also provide ecosystem services. Here, we examine the short (< 3 years) and medium (> 10 years) term outcomes of experimental reefs constructed in 2009 for nature-based coastal defense in a Louisiana, USA estuarine lake. Oyster reef density, demography, along with adjacent salt marsh, and shoreline movement were compared at six fringing shoreline reefs and paired reference sites over the first three years post-construction (2009–2011), and a decade later (2019–2020). Oyster density measured in 2019–2020 (< 60 ind m−2) was less than 10% of density measured during 2009–2011 (> 1000 ind m−2). This density difference largely reflected a lack of new recruits and small oysters (< 75 mm shell height) in later samples, with adult oyster densities similar between 2011, 2019 and 2020. Lack of smaller oysters in recent sampling likely reflected the impact of multiple extended low salinity events in this region in recent years, including the record-breaking low salinity in 2019. No differences in shoreline characteristics were detected in marsh vegetation, soil properties or nutrient concentrations between reef and reference sites during early and later years. Similarly, shoreline erosion at both reef and reference sites immediately post-construction, and 10 years later, was high (~1 m y−1) indicating a lack of shoreline protection from these reefs. These findings highlight the need to consider both current and future conditions, including the effect of extreme years, when implementing nature-based coastal defense. On the other hand, the persistence of reproductive-sized oysters on the reef 10 years post creation, indicate reef resilience and potential for reef development and shoreline benefits, should better site conditions return in future years. Determining restoration success within variable and dynamic environments requires frequent monitoring which is required to understand responses to short and longer-term environmental variation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2022.106603","usgsCitation":"La Peyre, M., Leblanc Buie, S.C., Rossi, R., and Roberts, B.J., 2022, Long-term assessments are critical to determining persistence and shoreline protection from oyster reef nature-based coastal defenses: Ecological Engineering, v. 178, 106603, 11 p., https://doi.org/10.1016/j.ecoleng.2022.106603.","productDescription":"106603, 11 p.","ipdsId":"IP-134425","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":432046,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Sister Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.00387573242188,\n 29.161455709145933\n ],\n [\n -90.80680847167969,\n 29.161455709145933\n ],\n [\n -90.80680847167969,\n 29.280110436303417\n ],\n [\n -91.00387573242188,\n 29.280110436303417\n ],\n [\n -91.00387573242188,\n 29.161455709145933\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"178","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908668,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leblanc Buie, Sarah Catherine","contributorId":341595,"corporation":false,"usgs":false,"family":"Leblanc Buie","given":"Sarah","email":"","middleInitial":"Catherine","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":908669,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rossi, Ryann","contributorId":341596,"corporation":false,"usgs":false,"family":"Rossi","given":"Ryann","email":"","affiliations":[{"id":12699,"text":"Louisiana Universities Marine Consortium","active":true,"usgs":false}],"preferred":false,"id":908670,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roberts, Brian J.","contributorId":341597,"corporation":false,"usgs":false,"family":"Roberts","given":"Brian","email":"","middleInitial":"J.","affiliations":[{"id":12699,"text":"Louisiana Universities Marine Consortium","active":true,"usgs":false}],"preferred":false,"id":908671,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70254233,"text":"70254233 - 2022 - The protectiveness of aquatic life criteria for threatened or endangered aquatic species: Cadmium in California","interactions":[],"lastModifiedDate":"2024-05-14T14:29:04.843582","indexId":"70254233","displayToPublicDate":"2022-05-20T10:28:28","publicationYear":"2022","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":17779,"text":"OSF Preprints","active":true,"publicationSubtype":{"id":32}},"title":"The protectiveness of aquatic life criteria for threatened or endangered aquatic species: Cadmium in California","docAbstract":"In the United States, conflicts can arise between the processes to derive aquatic life criteria (ALC) for chemicals under the Clean Water Act (CWA) and the evaluation procedures used in Endangered Species Act (ESA) consultations on the protectiveness of those criteria for protected species. This paper examines the roots of, and possible reconciliation of, one longstanding conflict over cadmium aquatic life criteria in California. This case study includes 1) an overview of occurrences of cadmium in the aquatic environment, 2) factors affecting toxicity of cadmium to aquatic life, 3) a contrast between the analytical procedures of CWA aquatic life criteria derivation and ESA consultation, 4) quantitative estimates of no-effect concentrations of cadmium for 44 ESA listed species in comparison with updated aquatic life criteria, and 5) concludes with suggestions to update California’s aquatic life criteria for cadmium that would be more protective of sensitive ESA listed species.
A root cause of conflict is the different levels of biological organization that are the focus of CWA and ESA procedures. The CWA ALC are intended to protect diverse ecosystems by protecting at least 95% of the species richness in communities, allowing that it is acceptable for some species in the residual most sensitive 5% of the community richness to be harmed or even locally extirpated so long as they are not societally important species. The ESA is charged with minimizing harm to individual organisms and disallows increasing risk of extinction or impeding recovery of protected species. With cadmium in California, these procedures converge because some of the most sensitive species to cadmium happen to be surrogates for protected species (acute responses of steelhead/rainbow trout, Oncorhynchus mykiss, and chronic responses of threespine stickleback, Gasterosteus aculeatus). The present review concludes that while the superseded 1996 cadmium criteria versions would not be fully protective for up to half of the 44 ESA listed aquatic species in California, the updated 2016 versions would be more protective. Still, the review shows that the updated acute criteria would only fully protect the less sensitive half of the distribution of data for steelhead/rainbow trout sensitivity to cadmium, and the chronic criterion still would not protect the listed threespine stickleback. With a data rich species such as rainbow trout, instead of defining acute criteria using a central tendency statistic such as the geometric mean of multiple test responses, using a lower statistic such as the 10th percentile would ensure that the vast majority of a sensitive, protected species (and all less sensitive species) would be protected. Available data for the stickleback indicate it may be highly sensitive to cadmium, but no threshold can be derived from existing data. Additional testing with cadmium and stickleback would be needed to suggest an alternative, quantitative approach.
","language":"English","publisher":"OSF Preprints","doi":"10.31219/osf.io/d3tpe","usgsCitation":"Mebane, C.A., 2022, The protectiveness of aquatic life criteria for threatened or endangered aquatic species: Cadmium in California: OSF Preprints, https://doi.org/10.31219/osf.io/d3tpe.","productDescription":"44 p.","numberOfPages":"44","ipdsId":"IP-137876","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":447697,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.31219/osf.io/d3tpe","text":"External Repository"},{"id":428689,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":900691,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70231754,"text":"70231754 - 2022 - A critical review of bioaccumulation and biotransformation of organic chemicals in birds","interactions":[],"lastModifiedDate":"2022-05-25T15:29:48.479448","indexId":"70231754","displayToPublicDate":"2022-05-20T10:20:01","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5344,"text":"Reviews of Environmental Contamination and Toxicology","active":true,"publicationSubtype":{"id":10}},"title":"A critical review of bioaccumulation and biotransformation of organic chemicals in birds","docAbstract":"A literature review of bioaccumulation and biotransformation of organic chemicals in birds was undertaken, aiming to support scoping and prioritization of future research. The objectives were to characterize available bioaccumulation/biotransformation data, identify knowledge gaps, determine how extant data can be used, and explore the strategy and steps forward. An intermediate approach balanced between expediency and rigor was taken given the vastness of the literature. Following a critical review of > 500 peer-reviewed studies, > 25,000 data entries and 2 million information bytes were compiled on > 700 organic compounds for ~ 320 wild species and 60 domestic breeds of birds. These data were organized into themed databases on bioaccumulation and biotransformation, field survey, microsomal enzyme activity, metabolic pathway, and bird taxonomy and diet. Significant data gaps were identified in all databases at multiple levels. Biotransformation characterization was largely fragmented over metabolite/pathway identification and characterization of enzyme activity or biotransformation kinetics. Limited biotransformation kinetic data constrained development of an avian biotransformation model. A substantial shortage of in vivo biotransformation kinetics has been observed as most reported rate constants were derived in vitro. No metric comprehensively captured all key contaminant classes or chemical groups to support broad-scope modeling of bioaccumulation or biotransformation. However, metrics such as biota-feed accumulation factor, maximum transfer factor, and total elimination rate constant were more readily usable for modeling or benchmarking than other reviewed parameters. Analysis demonstrated the lack of bioaccumulation/biotransformation characterization of shorebirds, seabirds, and raptors. In the study of bioaccumulation and biotransformation of organic chemicals in birds, this review revealed the need for greater chemical and avian species diversity, chemical measurements in environmental media, basic biometrics and exposure conditions, multiple tissues/matrices sampling, and further exploration on biotransformation. Limitations of classical bioaccumulation metrics and current research strategies used in bird studies were also discussed. Forward-looking research strategies were proposed: adopting a chemical roadmap for future investigations, integrating existing biomonitoring data, gap-filling with non-testing approaches, improving data reporting practices, expanding field sampling scopes, bridging existing models and theories, exploring biotransformation via avian genomics, and establishing an online data repository.
","language":"English","publisher":"Springer Link","doi":"10.1007/s44169-021-00007-1","usgsCitation":"Kuo, D.T., Rattner, B.A., Marteinson, S.C., Letcher, R.J., Fernie, K.J., Treu, G., Deutsch, M., Johnson, M.S., Deglin, S., and Embry, M., 2022, A critical review of bioaccumulation and biotransformation of organic chemicals in birds: Reviews of Environmental Contamination and Toxicology, v. 260, 6, 22 p., https://doi.org/10.1007/s44169-021-00007-1.","productDescription":"6, 22 p.","ipdsId":"IP-125200","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":447701,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s44169-021-00007-1","text":"Publisher Index Page"},{"id":401051,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"260","noUsgsAuthors":false,"publicationDate":"2022-05-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Kuo, Dave T. F.","contributorId":292043,"corporation":false,"usgs":false,"family":"Kuo","given":"Dave","email":"","middleInitial":"T. F.","affiliations":[{"id":62810,"text":"City University of Hong Kong","active":true,"usgs":false}],"preferred":false,"id":843691,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rattner, Barnett A. 0000-0003-3676-2843 brattner@usgs.gov","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":4142,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett","email":"brattner@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":843713,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marteinson, Sarah C.","contributorId":292044,"corporation":false,"usgs":false,"family":"Marteinson","given":"Sarah","email":"","middleInitial":"C.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":843714,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Letcher, Robert J.","contributorId":176209,"corporation":false,"usgs":false,"family":"Letcher","given":"Robert","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":843715,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fernie, Kim J.","contributorId":211241,"corporation":false,"usgs":false,"family":"Fernie","given":"Kim","email":"","middleInitial":"J.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":843716,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Treu, Gabriele","contributorId":218385,"corporation":false,"usgs":false,"family":"Treu","given":"Gabriele","email":"","affiliations":[{"id":39836,"text":"Leibniz Institute for Zoo and Wildlife Research","active":true,"usgs":false}],"preferred":false,"id":843717,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Deutsch, Markus","contributorId":292048,"corporation":false,"usgs":false,"family":"Deutsch","given":"Markus","email":"","affiliations":[{"id":62812,"text":"Umweltbundesamt","active":true,"usgs":false}],"preferred":false,"id":843718,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johnson, Mark S.","contributorId":86058,"corporation":false,"usgs":true,"family":"Johnson","given":"Mark","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":843719,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Deglin, Sandrine","contributorId":292050,"corporation":false,"usgs":false,"family":"Deglin","given":"Sandrine","email":"","affiliations":[{"id":62814,"text":"Health and Environmental Science Institutue","active":true,"usgs":false}],"preferred":false,"id":843720,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Embry, Michelle","contributorId":176356,"corporation":false,"usgs":false,"family":"Embry","given":"Michelle","email":"","affiliations":[],"preferred":false,"id":843721,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70257011,"text":"70257011 - 2022 - Effects of prescribed fire on prenesting movements of wild turkeys in Arkansas","interactions":[],"lastModifiedDate":"2024-09-05T15:36:51.76754","indexId":"70257011","displayToPublicDate":"2022-05-20T10:17:30","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Effects of prescribed fire on prenesting movements of wild turkeys in Arkansas","docAbstract":"The restoration of historic disturbance regimes is an increasingly common management strategy to conserve disturbance-dependent communities and species, and enhance resilience of ecosystems to climate change or plant and animal invasions. However, the reintroduction of frequent and wide-scale disturbance may have unexpected consequences on species that are accustomed to an environment absent of frequent disturbance. Implementation of frequent prescribed fire for community restoration has coincided with population declines of eastern wild turkeys (Meleagris gallopavo silvestris) in the Ozark Highlands of Arkansas. We investigated whether there was evidence of linkage between wild turkey movement behavior and habitat use and the widespread use of prescribed fire that began in 2002 and continued through the end of our study in 2013. We fitted 67 female wild turkeys with satellite transmitters in 2012 and 2013 on the White Rock Ecosystem Restoration Area to estimate annual and seasonal home ranges and examine pre-nesting habitat use at multiple spatial scales. Home range was larger for adults in 2013 (4,750 ha, SE = 946.2, n = 12) than in 2012 (2,703 ha, SE = 283.4, n = 19). Mean pre-nesting ranges for adults were 1,633 ha (SE = 238.9, n = 23) in 2012 and 1,118 ha (SE = 158.8, n = 18) in 2013, smaller than those of sub-adults, 1,761 ha (SE = 581.2, n = 3) in 2012 and 5,576 ha (SE = 2260, n = 8) in 2013. Habitat selection analyses for the pre-nesting period indicated that wild turkeys used locations with more variability in canopy cover and vegetation height and in smaller patch sizes than expected based on availability. However, female wild turkeys selected nesting cover that had more variability in canopy cover and vegetation height but in larger patches. Differences in sub-adults and adult home and seasonal ranges suggest that other factors such as density dependence or social hierarchy could be driving movements as opposed to prescribed fire application. Wild turkey females selected variable vegetation structure during the pre-nesting and nesting periods with characteristics that could be a result of frequent prescribed fire or forest succession. However, we documented no direct evidence these characteristics or other aspects of the prescribed fire program were causing wild turkey population declines.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.1264","usgsCitation":"Pittman, H., and Krementz, D.G., 2022, Effects of prescribed fire on prenesting movements of wild turkeys in Arkansas: Wildlife Society Bulletin, v. 46, no. 2, e1264, 14 p., https://doi.org/10.1002/wsb.1264.","productDescription":"e1264, 14 p.","ipdsId":"IP-077113","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":433507,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","otherGeospatial":"Boston Mountain Ranger District of the Ozark‐St. Francis, National Forest, White Rock Ecosystem Restoration Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.15913371190965,\n 35.85873194814944\n ],\n [\n -94.15913371190965,\n 35.46671910080133\n ],\n [\n -93.6126286148777,\n 35.46671910080133\n ],\n [\n -93.6126286148777,\n 35.85873194814944\n ],\n [\n -94.15913371190965,\n 35.85873194814944\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"46","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-05-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Pittman, H.T.","contributorId":341911,"corporation":false,"usgs":false,"family":"Pittman","given":"H.T.","email":"","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":909138,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krementz, David G. 0000-0002-5661-4541 dkrementz@usgs.gov","orcid":"https://orcid.org/0000-0002-5661-4541","contributorId":2827,"corporation":false,"usgs":true,"family":"Krementz","given":"David","email":"dkrementz@usgs.gov","middleInitial":"G.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":909137,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70231755,"text":"70231755 - 2022 - Assessing climate change impacts on Pacific salmon using bioenergetics and spatiotemporal explicit river temperature predictions under varying riparian conditions","interactions":[],"lastModifiedDate":"2022-05-25T15:00:58.75195","indexId":"70231755","displayToPublicDate":"2022-05-20T09:56:36","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Assessing climate change impacts on Pacific salmon using bioenergetics and spatiotemporal explicit river temperature predictions under varying riparian conditions","docAbstract":"Pacific salmon and trout populations are affected by timber harvest, the removal and alteration of riparian vegetation, and the resulting physical changes to water quality, temperature, and associated delivery of high-quality terrestrial prey. Juvenile salmon and trout growth, a key predictor of survival, is poorly understood in the context of current and future (climate-change mediated) conditions, with resource managers needing information on how land use will impact future river conditions for these commercially and culturally important species. We used the Heat Source water temperature modeling framework to develop a spatiotemporal model to assess how riparian canopy and vegetation preservation and addition could influence river temperatures under future climate predictions in a coastal river fed by a moraine-dammed lake: the Quinault River in Washington State. The model predicted higher water temperatures under future carbon emission projections, representative concentration pathway (RCP) 4.5 and 8.5, with varying magnitude based on different riparian vegetation scenarios. We used the daily average temperature output from these scenarios to predict potential juvenile fish growth using the Wisconsin bioenergetics model. A combination of riparian vegetation removal and continued high carbon emissions resulted in a predicted seven-day average daily maximum temperature (7DADM) increase of 1.7°C in the lower river by 2080; increases in riparian shading mitigate this 7DADM increase to only 0.9°C. Under the current thermal regime, bioenergetics modeling predicts juvenile fish lose weight in the lower river; this loss of potential growth worsens by an average of 20–83% in the lower river by 2080, increasing with the loss of riparian shading. This study assess the impact of riparian vegetation management on future thermal habitat for Pacific salmon and trout under warming climates and provide a useful spatially explicit modeling framework that managers can use to make decisions regarding riparian vegetation management and its mechanistic impact to water temperature and rearing juvenile fish.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0266871","usgsCitation":"Spanjer, A.R., Gendaszek, A.S., Wulfkuhle, E.J., Black, R.W., and Jaeger, K.L., 2022, Assessing climate change impacts on Pacific salmon using bioenergetics and spatiotemporal explicit river temperature predictions under varying riparian conditions: PLoS ONE, v. 17, no. 5, e0266871, 25 p., https://doi.org/10.1371/journal.pone.0266871.","productDescription":"e0266871, 25 p.","ipdsId":"IP-119800","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":447705,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0266871","text":"Publisher Index Page"},{"id":435843,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XGI6GS","text":"USGS data release","linkHelpText":"Quinault River water temperature and salmon bioenergetics model data"},{"id":435842,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GSX4QE","text":"USGS data release","linkHelpText":"Water temperature and riparian vegetation survey data for the lower Quinault River, WA for select periods in 2018 and 2019"},{"id":401045,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Lake Quinault, Quinault River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.31854248046875,\n 47.292270864380086\n ],\n [\n -123.82553100585936,\n 47.292270864380086\n ],\n [\n -123.82553100585936,\n 47.50421439972969\n ],\n [\n -124.31854248046875,\n 47.50421439972969\n ],\n [\n -124.31854248046875,\n 47.292270864380086\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-05-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Spanjer, Andrew R. 0000-0002-7288-2722 aspanjer@usgs.gov","orcid":"https://orcid.org/0000-0002-7288-2722","contributorId":150395,"corporation":false,"usgs":true,"family":"Spanjer","given":"Andrew","email":"aspanjer@usgs.gov","middleInitial":"R.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":843701,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gendaszek, Andrew S. 0000-0002-2373-8986 agendasz@usgs.gov","orcid":"https://orcid.org/0000-0002-2373-8986","contributorId":3509,"corporation":false,"usgs":true,"family":"Gendaszek","given":"Andrew","email":"agendasz@usgs.gov","middleInitial":"S.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":843702,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wulfkuhle, Elyse J.","contributorId":207132,"corporation":false,"usgs":false,"family":"Wulfkuhle","given":"Elyse","email":"","middleInitial":"J.","affiliations":[{"id":37427,"text":"Quinault Indian Tribe","active":true,"usgs":false}],"preferred":false,"id":843703,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Black, Robert W. 0000-0002-4748-8213 rwblack@usgs.gov","orcid":"https://orcid.org/0000-0002-4748-8213","contributorId":1820,"corporation":false,"usgs":true,"family":"Black","given":"Robert","email":"rwblack@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":843704,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jaeger, Kristin L. 0000-0002-1209-8506","orcid":"https://orcid.org/0000-0002-1209-8506","contributorId":206935,"corporation":false,"usgs":true,"family":"Jaeger","given":"Kristin","middleInitial":"L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":843705,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70231812,"text":"70231812 - 2022 - Nearshore bathymetric changes along the Alaska Beaufort Sea coast and possible physical drivers","interactions":[],"lastModifiedDate":"2022-05-27T13:29:13.252547","indexId":"70231812","displayToPublicDate":"2022-05-20T08:24:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"title":"Nearshore bathymetric changes along the Alaska Beaufort Sea coast and possible physical drivers","docAbstract":"Erosion rates along Alaska's Beaufort Sea coast, among the highest in the world, are negatively impacting communities, industrial and military infrastructure, and wildlife habitat. Decreasing maximal winter ice extent and increasing summer open water duration and extent in the Beaufort Sea may be making the coast more vulnerable to destructive storm waves than during recent, colder, icier decades. Previous studies of Beaufort Sea coastal change have been limited to subaerial analyses of the shoreline. Here we describe nearshore seafloor change by comparing post-World War II (WWII) (1945-53) bathymetry data to recently acquired (1985–2018) bathymetry data and relate the observed seafloor change to adjacent shoreline change near Utqiagvik, within Stefansson Sound, and immediately west of Barter Island and Kaktovik. Within the Utqiagvik region, seabed erosion was generally highest (>1.0 m of loss) offshore of Point Barrow and along the eastern end of the Tapkaluk Islands, while there were lesser amounts of deposition (<0.5 m of gain) within the protected waters of Elson Lagoon. Sedimentation was generally highest offshore of Point Barrow, in a region of converging currents, and on the landward side of the barrier islands and spits fronting Elson Lagoon, which is likely related to a regional trend of westerly sediment transport and landward migration of the barrier islands. Within Stefansson Sound, perhaps the most notable changes from post-WWII bathymetry data compared to recent data are a switch from mixed, low erosion and deposition in 1997 to low deposition (<0.5 m) in 2018 east of the Boulder Patch, a switch from low erosion in 1997 to neutral depth change in 2018 in the channel between the north and south Boulder Patch areas, and higher deposition from 1997 to 2018 landward of the rapidly retreating barrier islands along the Sound's northern border. At Barter Island, high erosion near north-facing shorelines and high deposition near west-facing shorelines generally matched shoreline changes. One of our goals is to identify possible processes responsible for the depth changes we quantified. Using simple metrics that relate sediment characteristics with modeled waves and non-wave induced currents, we show that sediment resuspension and transport by both wave and non-wave driven currents likely contribute to the overall patterns of change within the ∼13 m isobath along the open coast, and that the influence of wave action affecting sediment transport is expanding seaward.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2022.104745","usgsCitation":"Zimmermann, M., Erikson, L.H., Gibbs, A.E., Prescott, M., Escarzaga, S.M., Tweedie, C.E., Kasper, J., and Duvoy, P.X., 2022, Nearshore bathymetric changes along the Alaska Beaufort Sea coast and possible physical drivers: Continental Shelf Research, v. 242, 104745, 15 p., https://doi.org/10.1016/j.csr.2022.104745.","productDescription":"104745, 15 p.","ipdsId":"IP-132441","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":447707,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2022.104745","text":"Publisher Index Page"},{"id":401293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beaufort Sea coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -164.00390625,\n 69.33383491964828\n ],\n [\n -140.9326171875,\n 69.33383491964828\n ],\n [\n -140.9326171875,\n 72.39570570653261\n ],\n [\n -164.00390625,\n 72.39570570653261\n ],\n [\n -164.00390625,\n 69.33383491964828\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"242","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zimmermann, Mark 0000-0002-5786-3814","orcid":"https://orcid.org/0000-0002-5786-3814","contributorId":200380,"corporation":false,"usgs":false,"family":"Zimmermann","given":"Mark","email":"","affiliations":[],"preferred":false,"id":843888,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":843889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gibbs, Ann E. 0000-0002-0883-3774 agibbs@usgs.gov","orcid":"https://orcid.org/0000-0002-0883-3774","contributorId":2644,"corporation":false,"usgs":true,"family":"Gibbs","given":"Ann","email":"agibbs@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":843890,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prescott, Megan M.","contributorId":292137,"corporation":false,"usgs":false,"family":"Prescott","given":"Megan M.","affiliations":[{"id":62835,"text":"Lynker Technologies, Under contract to Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":843891,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Escarzaga, Stephen M.","contributorId":279732,"corporation":false,"usgs":false,"family":"Escarzaga","given":"Stephen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":843892,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tweedie, Craig E.","contributorId":200176,"corporation":false,"usgs":false,"family":"Tweedie","given":"Craig","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":843893,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kasper, Jeremy L. 0000-0003-0975-6114","orcid":"https://orcid.org/0000-0003-0975-6114","contributorId":208630,"corporation":false,"usgs":false,"family":"Kasper","given":"Jeremy L.","affiliations":[{"id":37850,"text":"University of Alaska Fairbanks, Fairbanks, Alaska, UNITED STATES","active":true,"usgs":false}],"preferred":false,"id":843894,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Duvoy, Paul X.","contributorId":292138,"corporation":false,"usgs":false,"family":"Duvoy","given":"Paul","email":"","middleInitial":"X.","affiliations":[{"id":62836,"text":"Institute of Northern Engineering, University of Alaska Fairbanks, Fairbanks, AK, USA","active":true,"usgs":false}],"preferred":false,"id":843895,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70233420,"text":"70233420 - 2022 - Comparison of indices to infer population dynamics of black brant","interactions":[],"lastModifiedDate":"2023-01-18T15:57:57.880082","indexId":"70233420","displayToPublicDate":"2022-05-20T07:54:12","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of indices to infer population dynamics of black brant","docAbstract":"To aid managers in assessing status of Pacific black brant Branta bernicla nigricans (hereafter brant), I examined pre-existing long-term data series from summer, fall staging, and wintering areas to infer overall population processes and assessed the utility of the various data sources. Variation in demographic parameters measured in subarctic and Arctic locations suggests some form of metapopulation structure likely exists for brant. I used serial autocorrelation coefficients to assess the ability of various indices to track population processes. Based on this approach, the Lincoln–Petersen estimator and the fall aerial survey estimate partitioned using age ratios of staging brant at Izembek Lagoon, Alaska, appear to be the best indicators. However, these two indexes show different trends for the overall brant population. The Lincoln–Petersen estimates showed biologically implausible changes in size among sequential years, whereas the fall Izembek index did not. Annual estimates of survival and productivity fit the patterns of annual variation in the fall Izembek index better than the Lincoln–Petersen estimates. I conclude that the fall age–partitioned Izembek Lagoon index appears to be the best for tracking population processes in brant.
Otoliths, also known as ear stones, are small body parts that help fish with hearing and balance. Like tree rings, otoliths form one light and one dark band per year, creating rings. These rings can be measured to understand fish growth. The wider the ring, the greater the growth. In our study, we used otoliths to understand how one fish species—lake trout—responds to rising temperature in the state of Alaska. We found that warmer spring air temperature and earlier lake ice melt were related to faster lake trout growth. This finding is consistent with other studies that link warmer water temperature and earlier lake ice melt to increased plankton in Alaska’s lakes. Together, these findings suggest that climate-driven increases at the bottom of the food web might benefit top predators like lake trout. However, the relationship between warmer temperature and faster growth may not last.
Information used in decision making arises from the structuring of observations and data. The collection, dissemination, and use of information has monetary and non-monetary costs (e.g., competition for attention) and necessitates trade-offs. Understanding the benefits of having information (i.e., the value of information, VOI), including resulting societal outcomes, is useful to information producers/funders and decision makers. Using theory, use cases, and hypotheticals, we describe how information (e.g., geospatial information) is valued and incorporated in decisions and actions related to managing natural resources, environments, and the impacts of natural and anthropogenic hazards. We discuss the nature of information and how it relates to models (conceptual, mental, scientific), beliefs, knowledge, and economic analyses. VOI approaches and behavioral factors that potentially affect information use and value are summarized. Framing of information and VOI through data to decision pathways (DDPs) at first simplifies understanding, then illustrates the benefits of information, and the human and societal challenges encountered in valuing and using it. We present approaches to overcome these challenges. Our transdisciplinary analysis concludes with a summary of critical issues affecting DDPs and VOI, and suggestions for improving both economic analyses and the actionability and use of information.
Previous studies indicate that cyanobacterial harmful algal bloom (cyanoHAB) frequency, extent, and magnitude have increased globally over the past few decades. However, little quantitative capability is available to assess these metrics of cyanoHABs across broad geographic scales and at regular intervals. Here, the spatial extent was quantified from a cyanobacteria algorithm applied to two European Space Agency satellite platforms—the MEdium Resolution Imaging Spectrometer (MERIS) onboard Envisat and the Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3. CyanoHAB spatial extent was defined for each geographic area as the percentage of valid satellite pixels that exhibited cyanobacteria above the detection limit of the satellite sensor. This study quantified cyanoHAB spatial extent for over 2,000 large lakes and reservoirs across the contiguous United States (CONUS) during two time periods: 2008–2011 via MERIS and 2017–2020 via OLCI when cloud-, ice-, and snow-free imagery was available. Approximately 56% of resolvable lakes were glaciated, 13% were headwater, isolated, or terminal lakes, and the rest were primarily drainage lakes. Results were summarized at national-, regional-, state-, and lake-scales, where regions were defined as nine climate regions which represent climatically consistent states. As measured by satellite, changes in national cyanoHAB extent did have a strong increase of 6.9% from 2017 to 2020 (|Kendall’s tau (τ)| = 0.56; gamma (γ) = 2.87 years), but had negligible change (|τ| = 0.03) from 2008 to 2011. Two of the nine regions had moderate (0.3 ≤ |τ| < 0.5) increases in spatial extent from 2017 to 2020, and eight of nine regions had negligible (|τ| < 0.2) change from 2008 to 2011. Twelve states had a strong or moderate increase from 2017 to 2020 (|τ| ≥ 0.3), while only one state had a moderate increase and two states had a moderate decrease from 2008 to 2011. A decrease, or no change, in cyanoHAB spatial extent did not indicate a lack of issues related to cyanoHABs. Sensitivity results of randomly omitted daily CONUS scenes confirm that even with reduced data availability during a short four-year temporal assessment, the direction and strength of the changes in spatial extent remained consistent. We present the first set of national maps of lake cyanoHAB spatial extent across CONUS and demonstrate an approach for quantifying past and future changes at multiple spatial scales. Results presented here provide water quality managers information regarding current cyanoHAB spatial extent and quantify rates of change.
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Jeremy","contributorId":291794,"corporation":false,"usgs":false,"family":"Werdell","given":"P. Jeremy","affiliations":[{"id":37453,"text":"National Aeronautics and Space Administration","active":true,"usgs":false}],"preferred":false,"id":843515,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70232148,"text":"70232148 - 2022 - Tick abundance, diversity and pathogen data collected by the National Ecological Observatory Network","interactions":[],"lastModifiedDate":"2022-06-08T11:39:13.564226","indexId":"70232148","displayToPublicDate":"2022-05-20T06:37:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10930,"text":"Gigabyte","active":true,"publicationSubtype":{"id":10}},"title":"Tick abundance, diversity and pathogen data collected by the National Ecological Observatory Network","docAbstract":"Cases of tick-borne diseases have been steadily increasing in the USA, owing in part to tick range expansion, land cover and associated host population changes, and habitat fragmentation. However, the relative importance of these and other potential drivers remain poorly understood within this complex disease system. Ticks are ectotherms with multi-host lifecycles, which makes them sensitive to changes in the physical environment and the ecological community. Here, we describe data collected by the National Ecological Observatory Network on tick abundance, diversity and pathogen infection. Ticks are collected using drag or flag methods multiple times in a growing season at 46 terrestrial sites across the USA. Ticks are identified and enumerated by a professional taxonomist, and a subset of nymphs are PCR-tested for various tick-borne pathogens. These data will enable multiscale analyses to better understand how drivers of tick dynamics and pathogen prevalence may shift with climate or land-use change.
An airborne electromagnetic survey west of the Poso Creek oil field, located in the southeastern San Joaquin Valley, California, was flown in October 2016 to improve understanding of the hydrogeologic setting and the distribution of groundwater salinity in the area. The airborne electromagnetic data were used to develop resistivity models of the subsurface, where the mean depth of investigation is about 300 meters below the land surface and thus characterizes parts of the Kern River Formation and overlying sediments. Resistivity models along with water table elevation, historical total dissolved solids measurements of water samples from wells, well lithologic records, borehole geophysical logs, and mapped surface geology were used to develop an understanding of local hydrogeologic controls on resistivity. Interpretation of these data indicate the resistivity structure primarily reflects the general lithologic character and geologic structure of the study area, with more subtle influences from variations in saturation and salinity.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/dr1155","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Zamudio, K.D., Ball, L.B., and Stephens, M.J., 2022, Airborne electromagnetic survey results near the Poso Creek oil field, San Joaquin Valley, California, fall 2016: U.S. Geological Survey Data Report 1155, 55 p., https://doi.org/10.3133/dr1155.","productDescription":"Report: vii, 59 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-131476","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":501206,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113076.htm","linkFileType":{"id":5,"text":"html"}},{"id":400702,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1155/dr1155.xml"},{"id":400701,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1155/images"},{"id":400662,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1155/coverthb.jpg"},{"id":400663,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1155/dr1155.pdf","text":"Report","size":"14.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1155"},{"id":400664,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H9AVZY","text":"USGS data release","linkHelpText":"Airborne electromagnetic and magnetic survey data, southeastern San Joaquin Valley near Cawelo, California, 2016"}],"country":"United States","state":"California","otherGeospatial":"Poso Creek Oil Field, San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.2,\n 35.4667\n ],\n [\n -119.0667,\n 35.4667\n ],\n [\n -119.0667,\n 35.5833\n ],\n [\n -119.2,\n 35.5833\n ],\n [\n -119.2,\n 35.4667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, Mail Stop 973
Denver, CO 80225
Wind has been the dominant agent of landscape modification on Mars for the past ~3 billion years. Among the diversity of features formed by aeolian abrasion on the surface of Mars are periodic bedrock ridges (PBRs), a relatively recently recognized class of erosional bedforms on Mars for which Earth analogues are rare. Gale crater, the field site for NASA’s Mars Science Laboratory Curiosity rover since it landed there in 2012, contains a diverse and extensive record of aeolian deposition and erosion. This study focuses on a series of periodic, linear bedrock ridges that occur within the Fe/Mg-smectite clay-bearing Glen Torridon region of Aeolis Mons (informally Mount Sharp). During Curiosity’s exploration of the Glen Torridon region between sols ~2300-3080, the rover drove through this field of ridges, providing the first opportunity for the in situ observation of these enigmatic erosional features. This study characterizes the Glen Torridon ridges using orbiter and rover data to determine their morphology, spatial distribution, compositional and material properties, and association with other aeolian features in the area. Based on these observations, the Glen Torridon ridges are interpreted to be consistent with an origin as wind-eroded periodic bedrock ridges carved during the most recent exhumation of Mount Sharp into the present-day mound. Although there is evidence for multidirectional winds in the Glen Torridon region based on the orientation of modern ripples, megaripples, TARs and other bedrock indicators, the consistent orientation of the Glen Torridon ridges, coupled with morphologic asymmetries within the ridges, support formation and elongation of the Glen Torridon PBRs forms parallel to a net regional northerly wind direction in and around Gale crater.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JE007096","usgsCitation":"Stack, K.M., Dietrich, W.E., Lamb, M.P., Sullivan, R., Christian, J.R., Newman, C.E., O’Connell-Cooper, C., Sneed, J.W., Day, M.D., Baker, M., Arvidson, R.A., Fedo, C.M., Khan, S., Williams, R., Bennett, K.A., Bryk, A.B., Cofield, S., Edgar, L.A., Fox, V.F., Fraeman, A.A., House, C.H., Rubin, D.M., Sun, V.Z., and Van Beek, J., 2022, Orbital and in-situ investigation of periodic bedrock ridges in Glen Torridon, Gale Crater, Mars: Journal of Geophysical Research E: Planets, v. 127, no. 6, e2021JE007096, 33 p., https://doi.org/10.1029/2021JE007096.","productDescription":"e2021JE007096, 33 p.","ipdsId":"IP-133144","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":447723,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2021je007096","text":"External Repository"},{"id":421607,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gale Crater, Glen Torridon, Mars","volume":"127","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-05-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Stack, K. 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Empirical data on resource selection within the region is limited, likely hindering management of these coastal forests. Our objectives were to determine roosting home range size, selection of day-roost tree species, second- and third-order roosting habitat selection, and to quantify the overall availability of resources in the surrounding landscape. We found core and peripheral roosting home range estimates were large, yet similar to observations from other areas of contiguous forests. Prior to juvenile volancy, female northern long-eared bats appear to select red maple (Acer rubrum), water ash (Fraxinus caroliniana), and loblolly pine (Pinus taeda) as day-roosts, but then use sweetgum (Liquidambar styraciflua), swamp bay (Persea palustris), and water tupelo (Nyssa aquatica) after juvenile volancy. At the second-order spatial scale, roosting home ranges were associated with woody wetlands farther from anthropogenic development and open water. However, within the third-order scale, northern long-eared bats were associated with undeveloped woody wetlands and upland forests, areas containing shorter trees and occurring proximal to open water. Peripheral and core areas were predicted to comprise approximately 20% of the local landscape. Our results show that complex and large tracts of woody wetlands juxtaposed with upland forests in this part of the Coastal Plain may be important for northern long-eared bats locally, results largely consistent with species management efforts in eastern North America.
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