The Line Islands volcanic chain in the central Pacific Ocean exhibits many characteristics of a hotspot-generated seamount chain; however, the lack of a predictable age progression has stymied previous models for the origin of this feature. We combined plate-tectonic reconstructions with seamount age dates and available geochemistry to develop a new model that involves multiple melt regions and multiple melt delivery styles to explain the spatial and temporal history of the Line Islands system. Our model identifies a new melt source region (Larson melt region at ~17°S, ~125°W) that contributed to the formation of the Line Islands, as well as the Mid-Pacific Mountains and possibly the Pukapuka Ridge.
In recent decades, feral horse (Equus caballus; horse) populations increased in sagebrush (Artimesia spp.) ecosystems, especially within the Great Basin, to the point of exceeding maximum appropriate management levels (AMLmax), which were set by land administrators to balance resource use by feral horses, livestock, and wildlife. Concomitantly, greater sage-grouse (Centrocercus urophasianus; sage-grouse) are sagebrush obligates that have experienced population declines within these same arid environments as a result of steady and continued loss of seasonal habitats. Although a strong body of research indicates that overabundant populations of horses degrade sagebrush ecosystems, empirical evidence linking horse abundance to sage-grouse population dynamics is missing. Within a Bayesian framework, we employed state-space models to estimate population rate of change (λ) using 15 years (2005–2019) of count surveys of male sage-grouse at traditional breeding grounds (i.e., leks) as a function of horse abundance relative to AMLmax and other environmental covariates (e.g., wildfire, precipitation, % sagebrush cover). Additionally, we employed a post hoc impact-control design to validate existing AMLmax values as related to sage-grouse population responses, and to help control for environmental stochasticity and broad-scale oscillations in sage-grouse abundance. On average, for every 50% increase in horse abundance over AMLmax, our model predicted an annual decline in sage-grouse abundance by 2.6%. Horse abundance at or below AMLmax coincided with sage-grouse λ estimates that were consistent with trends at non-horse areas elsewhere in the study region. Thus, AMLmax, as a whole, appeared to be set adequately in preventing adverse effects to sage-grouse populations. Results indicated 76%, 97%, and >99% probability of sage-grouse population decline relative to controls when horse numbers are 2, 2.5, and ≥3 times over AMLmax, respectively. As of 2019, horse herds exceeded AMLmax in Nevada, USA, by >4 times on average across all horse management areas. If feral horse populations continue to grow at current rates unabated, model projections indicate sage-grouse populations will be reduced within horse-occupied areas by >70.0% by 2034 (15-year projection), on average compared to 21.2% estimated for control sites. A monitoring framework that improves on estimating horse abundance and identifying responses of sage-grouse and other key indicator species (plant and animal) would be beneficial to guide management decisions that promote co-occurrence of horses with sensitive wildlife and livestock within landscapes subjected to multiple uses. Published 2021. This article is a U.S. Government work and is in the public domain in the USA. The Journal of Wildlife Management published by Wiley Periodicals LLC on behalf of The Wildlife Society.
Following rapid decompression in the conduit of a volcano, magma breaks into ash- to block-sized fragments, powering explosive sub-Plinian and Plinian eruptions that may generate destructive pyroclastic falls and flows. It is thus crucial to assess how magma breaks up into fragments. This task is difficult, however, because of the subterranean nature of the entire process and because the original size of pristine fragments is modified by secondary fragmentation and expansion. New textural observations of sub-Plinian and Plinian pumice lapilli reveal that some primary products of magma fragmentation survive by sintering together within seconds of magma break-up. Their size distributions reflect the energetics of fragmentation, consistent with products of rapid decompression experiments. Pumice aggregates thus offer a unique window into the previously inaccessible primary fragmentation process and could be used to determine the potential energy of fragmentation.
This response is offered to the critique by Gard et al. (2021) of our meta-analysis of polychlorinated biphenyl (PCB)-induced toxicity data in fish (Berninger and Tillitt 2019). Gard et al. (2021) offered numerous comments, the most substantive suggesting that 1) we should have added no-observable–adverse effect residue (NOAER) data from additional studies and all data points from selected studies, and 2) the uncertainty of aggregating data from different PCB mixtures, different species, and different life stages is too great based on a limited data set. The additional studies Gard et al. suggested either were not designed to produce toxicological data, had experimental design issues, were confounded by co-contaminants, or did not contain paired exposure–effects data and as such were not appropriate to add to the data set. Lowest-observable–adverse effect residue (LOAER) values were selected for our analysis because they represent population sensitivities from the central portions of a frequency distribution (the linear portion of dose–response curves). As a consequence, there is less uncertainty in these input data (LOAER values) and greater confidence that they accurately represent the response of fish populations tested. Modeling NOAER values is in the extrapolation portion of a dose–response relationship and subject to enhanced uncertainty. The Gard et al. (2021) critique ignores this fundamental principle of toxicology and adds/deletes data points from our data set without clear selection criteria, which artificially enhances the uncertainty of their models that ultimately are not useful. We reject the premise that it is better to use individual study data as opposed to aggregation of PCB-induced toxicity thresholds in fish.
","language":"English","publisher":"Society for Environmental Toxicology and Chemistry (SETAC)","doi":"10.1002/etc.5074","usgsCitation":"Berninger, J., and Tillitt, D.E., 2021, Response to Gard et al.'s (2021) Comments on the Critical Review “Polychlorinated Biphenyl Tissue-Concentration Thresholds for Survival, Growth, and Reproduction in Fish”: Environmental Toxicology and Chemistry, v. 8, no. 40, p. 2098-2109, https://doi.org/10.1002/etc.5074.","productDescription":"12 p.","startPage":"2098","endPage":"2109","ipdsId":"IP-127386","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":498904,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.5074","text":"Publisher Index Page"},{"id":387596,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"40","noUsgsAuthors":false,"publicationDate":"2021-08-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Berninger, Jason P.","contributorId":173602,"corporation":false,"usgs":false,"family":"Berninger","given":"Jason P.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":820064,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tillitt, Donald E. 0000-0002-8278-3955 dtillitt@usgs.gov","orcid":"https://orcid.org/0000-0002-8278-3955","contributorId":1875,"corporation":false,"usgs":true,"family":"Tillitt","given":"Donald","email":"dtillitt@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":820065,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70255193,"text":"70255193 - 2021 - Habitat selection by wolves and mountain lions during summer in western Montana","interactions":[],"lastModifiedDate":"2024-06-17T12:16:31.493985","indexId":"70255193","displayToPublicDate":"2021-07-22T07:13:58","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Habitat selection by wolves and mountain lions during summer in western Montana","docAbstract":"In the Northern Rockies of the United States, predators like wolves (Canis lupus) and mountain lions (Puma concolor) have been implicated in fluctuations or declines in populations of game species like elk (Cervus canadensis) and mule deer (Odocoileus hemionus). In particular, local distributions of these predators may affect ungulate behavior, use of space, and dynamics. Our goal was to develop generalizable predictions of habitat selection by wolves and mountain lions across western Montana. We hypothesized both predator species would select habitat that maximized their chances of encountering and killing ungulates and that minimized their chances of encountering humans. We assessed habitat selection by these predators during summer using within-home range (3rd order) resource selection functions (RSFs) in multiple study areas throughout western Montana, and tested how generalizable RSF predictions were by applying them to out-of-sample telemetry data from separate study areas. Selection for vegetation cover-types varied substantially among wolves in different study areas. Nonetheless, our predictions of 3rd order selection by wolves were highly generalizable across different study areas. Wolves consistently selected simple topography where ungulate prey may be more susceptible to their cursorial hunting mode. Topographic features may serve as better proxies of predation risk by wolves than vegetation cover-types. Predictions of mountain lion distribution were less generalizable. Use of rugged terrain by mountain lions varied across ecosystem-types, likely because mountain lions targeted the habitats of different prey species in each study area. Our findings suggest that features that facilitate the hunting mode of a predator (i.e. simple topography for cursorial predators and hiding cover for stalking predators) may be more generalizable predictors of their habitat selection than features associated with local prey densities.
The management of North American waterfowl is predicated on long-term, continental scale banding implemented prior to the hunting season (i.e., July–September) and subsequent reporting of bands recovered by hunters. However, single-season banding and encounter operations have a number of characteristics that limit their application to estimating demographic rates and evaluating hypothesized limiting factors throughout the annual cycle. We designed and implemented a 2-season banding program for American black ducks (Anas rubripes), mallards (A. platyrhynchos), and hybrids in eastern North America to evaluate potential application to annual life cycle conservation and sport harvest management. We assessed model fit and compared estimates of annual survival among data types (i.e., pre-hunting season only [July–September], post-hunting season only [January–March], and 2-season [pre- and post-hunting season]) to evaluate model assumptions and potential application to population modeling and management. There was generally high agreement between estimates of annual survival derived using 2-season and pre-season only data for all age and sex cohorts. Estimates of annual survival derived from post-season banding data only were consistently higher for adult females and juveniles of both sexes. We found patterns of seasonal survival varied by species, age, and to a lesser extent, sex. Hunter recovered birds exhibited similar spatial distributions regardless of banding season suggesting banded samples were from the same population. In contrast, Goodness-Of-Fit tests suggest this assumption was statistically violated in some regions and years. We conclude that estimates of seasonal and annual survival for black ducks and mallards based on the 2-season banding program are valid and accurate based on model fit statistics, similarity in survival estimates across data and models, and similarities in the distribution of recoveries. The 2-season program provides greater precision and insight into the survival process and will improve the ability of researchers and managers to test competing hypotheses regarding population regulation resulting in more effective management.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2425","usgsCitation":"Devers, P.K., Emmet, R., Boomer, G.S., Zimmerman, G.S., and Royle, J., 2021, Evaluation of a two-season banding program to estimate and model migratory bird survival: Ecological Applications, v. 31, no. 7, e02425, 18 p., https://doi.org/10.1002/eap.2425.","productDescription":"e02425, 18 p.","ipdsId":"IP-127019","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":387503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-08-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Devers, Patrick K.","contributorId":261406,"corporation":false,"usgs":false,"family":"Devers","given":"Patrick","email":"","middleInitial":"K.","affiliations":[{"id":7199,"text":"US FWS","active":true,"usgs":false}],"preferred":false,"id":819981,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Emmet, Robert L.","contributorId":261407,"corporation":false,"usgs":false,"family":"Emmet","given":"Robert L.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":819982,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boomer, G. Scott 0000-0001-5854-3604","orcid":"https://orcid.org/0000-0001-5854-3604","contributorId":261408,"corporation":false,"usgs":false,"family":"Boomer","given":"G.","email":"","middleInitial":"Scott","affiliations":[{"id":7199,"text":"US FWS","active":true,"usgs":false}],"preferred":true,"id":819983,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zimmerman, Guthrie S.","contributorId":261410,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Guthrie","email":"","middleInitial":"S.","affiliations":[{"id":7199,"text":"US FWS","active":true,"usgs":false}],"preferred":false,"id":819984,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":3504,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":819985,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70226499,"text":"70226499 - 2021 - Is the grass always greener? Land surface phenology reveals differences in peak and season-long vegetation productivity responses to climate and management","interactions":[],"lastModifiedDate":"2021-11-22T13:10:05.542882","indexId":"70226499","displayToPublicDate":"2021-07-22T07:04:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Is the grass always greener? Land surface phenology reveals differences in peak and season-long vegetation productivity responses to climate and management","docAbstract":"Vegetation phenology—the seasonal timing and duration of vegetative phases—is controlled by spatiotemporally variable contributions of climatic and environmental factors plus additional potential influence from human management. We used land surface phenology derived from the Advanced Very High Resolution Radiometer and climate data to examine variability in vegetation productivity and phenological dates from 1989 to 2014 in the U.S. Northwestern Plains, a region with notable spatial heterogeneity in climate, vegetation, and land use. We first analyzed interannual trends in six phenological measures as a baseline. We then demonstrated how including annual-resolution predictors can provide more nuanced insights into measures of phenology between plant communities and across the ecoregion. Across the study area, higher annual precipitation increased both peak and season-long productivity. In contrast, higher mean annual temperatures tended to increase peak productivity but for the majority of the study area decreased season-long productivity. Annual precipitation and temperature had strong explanatory power for productivity-related phenology measures but predicted date-based measures poorly. We found that relationships between climate and phenology varied across the region and among plant communities and that factors such as recovery from disturbance and anthropogenic management also contributed in certain regions. In sum, phenological measures did not respond ubiquitously nor covary in their responses. Nonclimatic dynamics can decouple phenology from climate; therefore, analyses including only interannual trends should not assume climate alone drives patterns. For example, models of areas exhibiting greening or browning should account for climate, anthropogenic influence, and natural disturbances. Investigating multiple aspects of phenology to describe growing-season dynamics provides a richer understanding of spatiotemporal patterns that can be used for predicting ecosystem responses to future climates and land-use change. Such understanding allows for clearer interpretation of results for conservation, wildlife, and land management.
More than 250 landslides were triggered across the eastern volcanic islands of Chuuk State in the Federated States of Micronesia by torrential rainfall from tropical storm Chata’an on July 2, 2002. Landslides triggered during nearly 20 inches of rainfall in less than 24 hours caused 43 fatalities and the destruction or damage of 231 structures, including homes, schools, community centers, and medical dispensaries. Landslides also buried roads, crops, and water supplies. The landslides ranged in volume from a few cubic meters to more than 1 million cubic meters. Most of the failures began as slumps and transformed into debris flows, some of which traveled several hundred meters across coastal flatlands into populated areas. A landslide-inventory map produced after the storm shows that the island of Tonoas had the largest area affected by landslides, although the islands of Weno, Fefan, Etten, Uman, Siis, Udot, Eot, and Fanapanges also had significant landslides. Based on observations since the storm, we estimate the continuing hazard from landslides triggered by Chata’an to be relatively low. However, tropical storms and typhoons similar to Chata’an frequently develop in Micronesia and are likely to affect the islands of Chuuk in the future.
To assess the landslide hazard from future tropical storms, we produced a hazard map that identifies landslide-source areas of high, moderate, and low hazard. This map can be used to identify relatively safe areas for relocating structures or establishing areas where people could gather for shelter in relative safety during future typhoons or tropical storms similar to Chata’an.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20041348","productDescription":"Report: 22 p.; 2 Plates: 35.71 x 40.02 inches","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":387302,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2004/1348/ofr20041348_plate1_Revision.pdf","text":"Plate 1","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2004-1348 Plate 1","linkHelpText":"Landslide Inventory Map of Chuuk Islands Affected by Typhoon Chata'an"},{"id":182255,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2004/1348/coverthb.jpg"},{"id":387301,"rank":2,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2004/1348/versionHist.txt","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2004-1348 version history"},{"id":387300,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2004/1348/ofr20041348_pamphlet_Revision.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2004-1348 Pamphlet"},{"id":387303,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2004/1348/ofr20041348_plate2_Revision.pdf","text":"Plate 2","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2004-1348 Plate 2","linkHelpText":"Debris-Flow Hazard Map of Chuuk Islands Affected by Typhoon Chata’an"},{"id":391875,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_69259.htm"}],"country":"Federated States of Micronesia","state":"Chuuk State","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 151.675,\n 7.2789\n ],\n [\n 151.9022,\n 7.2789\n ],\n [\n 151.9022,\n 7.4689\n ],\n [\n 151.675,\n 7.4689\n ],\n [\n 151.675,\n 7.2789\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: July 21, 2021","contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, Mail Stop 966
Denver, CO 80225
Autumn and winter Santa Ana wind (SAW)–driven wildfires play a substantial role in area burned and societal losses in southern California. Temperature during the event and antecedent precipitation in the week or month prior play a minor role in determining area burned. Burning is dependent on wind intensity and number of human-ignited fires. Over 75% of all SAW events generate no fires; rather, fires during a SAW event are dependent on a fire being ignited. Models explained 40 to 50% of area burned, with number of ignitions being the strongest variable. One hundred percent of SAW fires were human caused, and in the past decade, powerline failures have been the dominant cause. Future fire losses can be reduced by greater emphasis on maintenance of utility lines and attention to planning urban growth in ways that reduce the potential for powerline ignitions.
","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.abh2262","usgsCitation":"Keeley, J., Guzman-Morales, J., Gershunov, A., Syphard, A.D., Cayan, D., Pierce, D.W., Flannigan, M., and Brown, T.J., 2021, Ignitions explain more than climate or weather in driving Santa Ana Wind fires: Science Advances, v. 7, no. 30, eabh2262, 10 p., https://doi.org/10.1126/sciadv.abh2262.","productDescription":"eabh2262, 10 p.","ipdsId":"IP-126058","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":451452,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1126/sciadv.abh2262","text":"External Repository"},{"id":387395,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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David W","contributorId":261327,"corporation":false,"usgs":false,"family":"Pierce","given":"David","email":"","middleInitial":"W","affiliations":[{"id":52819,"text":"Climate, Atmospheric Science and Physical Oceanography Division, Scripps Institution of Oceanography, University of California, San Diego, San Diego, CA 92093, USA","active":true,"usgs":false}],"preferred":false,"id":819772,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Flannigan, Michael","contributorId":261328,"corporation":false,"usgs":false,"family":"Flannigan","given":"Michael","affiliations":[{"id":52822,"text":"Department of Renewable Resources, University of Alberta, Edmonton, Alberta T6G 2H1, Canada","active":true,"usgs":false}],"preferred":false,"id":819773,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brown, Tim J","contributorId":261329,"corporation":false,"usgs":false,"family":"Brown","given":"Tim","email":"","middleInitial":"J","affiliations":[{"id":52823,"text":"Western Regional Climate Center, Desert Research Institute, Reno, NV 89512, USA","active":true,"usgs":false}],"preferred":false,"id":819774,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70223244,"text":"70223244 - 2021 - Benthic and planktonic inorganic nutrient processing rates at the interface between a river and lake","interactions":[],"lastModifiedDate":"2021-08-19T16:50:06.649243","indexId":"70223244","displayToPublicDate":"2021-07-20T11:47:37","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Benthic and planktonic inorganic nutrient processing rates at the interface between a river and lake","docAbstract":"The interface between lotic and lentic ecosystems is often a zone of intense metabolic activity, as primary production in streams and rivers can be light limited whereas nutrients often limit primary production in lake ecosystems. Our objective was to model the influence that rivermouths (the lotic-lentic interface) could have on the loads of soluble reactive phosphorus (SRP) and dissolved inorganic nitrogen (N) passing from the tributary to the nearshore zone of a lake. To achieve this objective, we modeled the combined role of water column nutrient transformation rates with sediment nutrient flux rates. For sensitivity analysis, we picked plausible parameter ranges based on values previously measured in the Fox rivermouth (a tributary to Lake Michigan). Sensitivity analysis of the model demonstrated that overall the importance of water column processing rates increases with increasing nutrient concentration and discharge. We then applied the model to the Fox rivermouth, simulating the change in nutrients on four dates where all of the necessary parameters had been estimated. This modeling suggests that the Fox rivermouth is often a net sink for SRP and source for ammonia (NH4), with water column processing driving SRP removal and both water column and sediment flux driving NH4 dynamics. Removal of SRP in the water column means conversion to particulate and/or organic P, and those P pools are generally considered to be less bioavailable than SRP, so it may be that rivermouths disconnect upstream sources of nutrients from nearshore food webs. These results demonstrate that the interface zone between lotic and lentic systems has the potential to substantially alter the load and character of nutrients as river waters pass through rivermouths to adjacent nearshore areas.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10533-021-00821-8","usgsCitation":"Larson, J.H., Evans, M.A., Fitzpatrick, F., Frost, P., Xenopoulos, M., James, W.F., and Reneau, P., 2021, Benthic and planktonic inorganic nutrient processing rates at the interface between a river and lake: Biogeochemistry, v. 155, p. 189-203, https://doi.org/10.1007/s10533-021-00821-8.","productDescription":"15 p.","startPage":"189","endPage":"203","ipdsId":"IP-118338","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":436267,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PNDSXR","text":"USGS data release","linkHelpText":"Code associated with analysis and modeling of benthic and pelagic inorganic nutrient processing rates at the interface between a river and lake"},{"id":388171,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"155","noUsgsAuthors":false,"publicationDate":"2021-07-20","publicationStatus":"PW","contributors":{"authors":[{"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":821513,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, Mary Anne 0000-0002-1627-7210 maevans@usgs.gov","orcid":"https://orcid.org/0000-0002-1627-7210","contributorId":149358,"corporation":false,"usgs":true,"family":"Evans","given":"Mary","email":"maevans@usgs.gov","middleInitial":"Anne","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":821514,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fitzpatrick, Faith A. 0000-0002-9748-7075","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":209612,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":821515,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frost, Paul C.","contributorId":138622,"corporation":false,"usgs":false,"family":"Frost","given":"Paul C.","affiliations":[{"id":12467,"text":"Department of Biology, Trent University, Peterborough, ON CA","active":true,"usgs":false}],"preferred":false,"id":821516,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xenopoulos, Marguerite A.","contributorId":138623,"corporation":false,"usgs":false,"family":"Xenopoulos","given":"Marguerite A.","affiliations":[{"id":12467,"text":"Department of Biology, Trent University, Peterborough, ON CA","active":true,"usgs":false}],"preferred":false,"id":821517,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"James, William F.","contributorId":213265,"corporation":false,"usgs":false,"family":"James","given":"William","email":"","middleInitial":"F.","affiliations":[{"id":38729,"text":"University of Wisconsin-Stout","active":true,"usgs":false}],"preferred":false,"id":821518,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reneau, Paul C. 0000-0002-1335-7573","orcid":"https://orcid.org/0000-0002-1335-7573","contributorId":220311,"corporation":false,"usgs":true,"family":"Reneau","given":"Paul C.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":821519,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70229384,"text":"70229384 - 2021 - Translocation, survival, and recovery of Kansas-banded Canada geese","interactions":[],"lastModifiedDate":"2022-03-04T16:08:57.776602","indexId":"70229384","displayToPublicDate":"2021-07-20T09:52:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Translocation, survival, and recovery of Kansas-banded Canada geese","docAbstract":"Temperate-breeding, or resident, Canada geese were once extirpated in Kansas, USA, but currently provide abundant viewing and hunting opportunities. Kansas Department of Wildlife, Parks, and Tourism (KDWPT) began reintroducing geese in 1980 with a goal of re-establishing a breeding population. Successful reintroductions led to translocating flocks to regions with no previous records of nesting geese; however, KDWPT continues to translocate individuals from nuisance flocks in urban areas to rural reservoirs to reduce human conflicts with urban geese. Our goal was to determine the effects of such translocations on survival and recovery of adult, sub-adult, and juvenile temperate-breeding Canada geese. We used Brownie dead-recovery models in Program MARK to compare survival and recovery probabilities between translocated and nontranslocated (normal wild) Kansas-banded Canada geese for 2012–2017. Model-estimated annual survival differed between status (normal wild Ŝ = 0.761, 95% CI 0.734–0.785; translocated Ŝ = 0.598, 95% CI 0.528–0.665). Recovery probability differed between normal and translocated adults (normal wild ḟ = 0.074, 95% CI = 0.069–0.078; translocated ḟ = 0.138, 95% CI = 0.120–0.158) and juveniles (normal wild ḟ = 0.067, 95% CI = 0.059–0.075; translocated ḟ = 0.250, 95% CI = 0.199–0.310). Recovery probability did not differ between status in the sub-adult age class (normal wild ḟ = 0.126, 95% CI = 0.115–0.137; translocated ḟ = 0.090, 95% CI = 0.055–0.144). Translocation is a viable management option to successfully reduce survival and increase recovery probability of urban nuisance geese in Kansas.
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Boomer","contributorId":287969,"corporation":false,"usgs":false,"family":"Malanchuk","given":"J.","email":"","middleInitial":"Boomer","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":837240,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ross, Beth 0000-0001-5634-4951 bross@usgs.gov","orcid":"https://orcid.org/0000-0001-5634-4951","contributorId":199242,"corporation":false,"usgs":true,"family":"Ross","given":"Beth","email":"bross@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":837239,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":837238,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bidrowski, Thomas F.","contributorId":287970,"corporation":false,"usgs":false,"family":"Bidrowski","given":"Thomas","email":"","middleInitial":"F.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":837241,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schultheis, Richard","contributorId":287971,"corporation":false,"usgs":false,"family":"Schultheis","given":"Richard","email":"","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":837242,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70259284,"text":"70259284 - 2021 - Hydrothermal alteration can result in pore pressurization and volcano instability","interactions":[],"lastModifiedDate":"2024-10-03T12:20:50.607266","indexId":"70259284","displayToPublicDate":"2021-07-20T07:19:41","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Hydrothermal alteration can result in pore pressurization and volcano instability","docAbstract":"The collapse of a volcanic flank can be destructive and deadly. Hydrothermal alteration is common to volcanoes worldwide and is thought to promote volcano instability by decreasing rock strength. However, some laboratory studies have shown that not all alteration reduces rock strength. Our new laboratory data for altered rhyodacites from Chaos Crags (Lassen volcanic center, California, USA) show that pore- and crack-filling mineral precipitation can reduce porosity and permeability and increase strength, Young's modulus, and cohesion. A significant reduction in permeability, by as much as four orders of magnitude, will inhibit fluid circulation and create zones of high pore fluid pressure. We explored the consequences of pore fluid pressurization on volcano stability using large-scale numerical modeling. Upscaled physical and mechanical properties for hydrothermally altered rocks were used as input parameters in our modeling. Results show that a high-pore-pressure zone within a volcano increases volcano deformation and that increasing the size of this zone increases the observed deformation. Hydrothermal alteration associated with mineral precipitation, and increases to rock strength, can therefore promote pore pressurization and volcano deformation, increasing the likelihood of volcano spreading, flank collapses, and phreatic/phreatomagmatic explosions. We conclude that porosity-decreasing alteration, explored here, and porosity-increasing alteration can both promote volcano instability and collapse, but by different mechanisms. Hydrothermal alteration should therefore be monitored at volcanoes worldwide and incorporated into hazard assessments.
We will investigate fish health factors that may be contributing to the failed recovery of Pacific herring populations in Prince William Sound. Field samples will provide infection and disease prevalence data from Prince William Sound and Sitka Sound to inform the age structured assessment (ASA) model, serological data will indicate the prior exposure history and future susceptibility of herring to viral hemorrhagic septicemia virus (VHSV), and diet information will provide insights into the unusually high prevalence of Ichthyophonus that occurs in juvenile herring from Cordova Harbor. Laboratory studies will validate the newly developed plaque neutralization assay as a quantifiable measure of herd immunity against VHS, provide further understanding of disease cofactors including salinity, and investigate possible routes of transmission for Ichthyophonus. Information from the field and laboratory studies will be integrated into the current ASA model and inform a novel ASA-type model that is based on the immune status of herring age cohorts.
","language":"English","publisher":"Exxon Valdez Oil Spill Trustee Council (EVOSTC)","usgsCitation":"Hershberger, P., and Purcell, M.K., 2021, Herring Disease Program - Annual Project Report 2012011-E, February 1, 2010-January 31, 2021, 26 p.","productDescription":"26 p.","ipdsId":"IP-127098","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":387460,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":387451,"type":{"id":15,"text":"Index Page"},"url":"https://evostc.state.ak.us/restoration-projects/project-search/hrm-program-herring-disease-program-ii-20120111-e/"}],"country":"United States","state":"Alaska","otherGeospatial":"Prince William Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -149.56787109375,\n 59.567723306212955\n ],\n [\n -144.33837890625,\n 59.567723306212955\n ],\n [\n -144.33837890625,\n 61.41775026352097\n ],\n [\n -149.56787109375,\n 61.41775026352097\n ],\n [\n -149.56787109375,\n 59.567723306212955\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hershberger, Paul 0000-0002-2261-7760","orcid":"https://orcid.org/0000-0002-2261-7760","contributorId":203322,"corporation":false,"usgs":true,"family":"Hershberger","given":"Paul","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":819957,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Purcell, Maureen K. 0000-0003-0154-8433 mpurcell@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8433","contributorId":168475,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen","email":"mpurcell@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":819958,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70227749,"text":"70227749 - 2021 - Spatial and temporal variation in length-weight relationships of age-0 Scaphirhynchus sturgeon in the lower Missouri River","interactions":[],"lastModifiedDate":"2022-01-28T15:28:49.002502","indexId":"70227749","displayToPublicDate":"2021-07-19T09:05:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":737,"text":"American Midland Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal variation in length-weight relationships of age-0 Scaphirhynchus sturgeon in the lower Missouri River","docAbstract":"Length-weight relationships can be useful tools for assessing fish condition. We developed these equations (W = aLb) for wild-caught age-0 (4.1–12.0 cm) Scaphirhynchus sturgeon from eight reaches spanning over 750 river km of the lower Missouri River from 2014 to 2017. We used nonlinear modeling to estimate the constant (a) and exponent (b) of the LW equation for each reach to assess potential spatial differences. We also assessed long-term temporal effects by estimating these parameters by year at Lexington reach, which is located in the middle of our sampling area and was the only reach sampled all 4 y. Constant and exponent estimates from linearized regressions varied by reach and were inversely related during the spatial analyses. Similarly, parameter estimates were also inversely related and varied among years during the temporal analysis at Lexington. To account for the relationship between constant and exponent values, we used predicted weights at 2 cm increments (4.1–12.0 cm) for the spatial analysis (by reach) and for the temporal analysis (by year). During the 2014 and 2015 spatial analyses, weights varied by size but were usually higher in Lexington and Glasgow, which were the furthest upstream reaches sampled during those years. During 2016 and 2017, Lexington was the furthest downstream reach sampled but did not consistently yield relatively high predicted weights. Temporal analysis at Lexington yielded higher predicted weights for 2014–2015 compared to 2016–2017 for higher size categories (10- and 12-cm). In general our results suggest differences in body condition among reaches and years in the lower Missouri River. Further research is needed to identify the specific mechanisms driving spatial and temporal L-W relationship differences observed and to determine if differences in predicted body conditions affect long-term survival and recruitment of age-0 Scaphirhynchus sturgeon. Currently, factors influencing age-0 Scaphirhynchus sturgeon condition and growth are unknown and this work serves to highlight knowledge gaps regarding factors influencing Scaphirhynchus sturgeon recruitment.
","language":"English","publisher":"University of Notre Dame","doi":"10.1674/0003-0031-186.1.106","usgsCitation":"Gonzalez, A., Long, J.M., Gosch, N.J., Civiello, A., Gemeinhardt, T., and Hall, J.R., 2021, Spatial and temporal variation in length-weight relationships of age-0 Scaphirhynchus sturgeon in the lower Missouri River: American Midland Naturalist, v. 186, no. 1, p. 106-121, https://doi.org/10.1674/0003-0031-186.1.106.","productDescription":"17 p.","startPage":"106","endPage":"121","ipdsId":"IP-108837","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395050,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Kansas, Missouri, Nebraska","otherGeospatial":"Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.8277587890625,\n 42.79540065303723\n ],\n [\n -97.294921875,\n 42.80346172417078\n ],\n [\n -96.668701171875,\n 42.46399280017058\n ],\n [\n -96.25671386718749,\n 41.80817277478235\n ],\n [\n -96.1578369140625,\n 41.33970040774419\n ],\n [\n -95.965576171875,\n 40.622291783092706\n ],\n [\n -95.570068359375,\n 40.04443758460856\n ],\n [\n -95.020751953125,\n 39.76632525654491\n ],\n [\n -95.2679443359375,\n 39.58029027440865\n ],\n [\n -94.8944091796875,\n 39.13006024213511\n ],\n [\n -94.449462890625,\n 39.0533181067413\n ],\n [\n -94.273681640625,\n 39.14710270770074\n ],\n [\n -94.0814208984375,\n 39.031986028740086\n ],\n [\n -93.1256103515625,\n 39.257778150283364\n ],\n [\n -92.999267578125,\n 39.18117526158749\n ],\n [\n -93.03771972656249,\n 39.00637903337455\n ],\n [\n -92.61474609375,\n 38.852542390364235\n ],\n [\n -92.4005126953125,\n 38.59540719940386\n ],\n [\n -92.01599121093749,\n 38.453588708941375\n ],\n [\n -91.746826171875,\n 38.62116234642254\n ],\n [\n -91.3568115234375,\n 38.62545397209084\n ],\n [\n -90.90087890624999,\n 38.46219172306828\n ],\n [\n -90.252685546875,\n 38.77978137804918\n ],\n [\n -90.0933837890625,\n 38.81403111409755\n ],\n [\n -90.06591796875,\n 38.950865400919994\n ],\n [\n -90.406494140625,\n 38.93377552819722\n ],\n [\n -90.94482421875,\n 38.68122173079789\n ],\n [\n -91.351318359375,\n 38.81403111409755\n ],\n [\n -91.7852783203125,\n 38.80118939192329\n ],\n [\n -92.0599365234375,\n 38.646908247760706\n ],\n [\n -92.252197265625,\n 38.732661120482334\n ],\n [\n -92.373046875,\n 38.94232097947902\n ],\n [\n -92.801513671875,\n 39.11727568585598\n ],\n [\n -92.7685546875,\n 39.26203141523749\n ],\n [\n -93.1585693359375,\n 39.54217596171196\n ],\n [\n -93.416748046875,\n 39.37252570201878\n ],\n [\n -94.053955078125,\n 39.257778150283364\n ],\n [\n -94.273681640625,\n 39.342794408952365\n ],\n [\n -94.5098876953125,\n 39.24501680713314\n ],\n [\n -94.757080078125,\n 39.287545585410435\n ],\n [\n -94.9603271484375,\n 39.5633531658293\n ],\n [\n -94.76806640624999,\n 39.78321267821705\n ],\n [\n -94.8834228515625,\n 39.985538414809746\n ],\n [\n -95.086669921875,\n 39.977120098439634\n ],\n [\n -95.2899169921875,\n 40.12009038025332\n ],\n [\n -95.635986328125,\n 40.693134153308065\n ],\n [\n -95.7843017578125,\n 41.352072144512924\n ],\n [\n -95.9271240234375,\n 41.83682786072714\n ],\n [\n -96.35009765625,\n 42.55712670332118\n ],\n [\n -97.13012695312499,\n 42.94436044696629\n ],\n [\n -97.9156494140625,\n 42.96848221128033\n ],\n [\n -97.8277587890625,\n 42.79540065303723\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"186","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gonzalez, A.","contributorId":272273,"corporation":false,"usgs":false,"family":"Gonzalez","given":"A.","email":"","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":832028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":832029,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gosch, N. J. C.","contributorId":272518,"corporation":false,"usgs":false,"family":"Gosch","given":"N.","email":"","middleInitial":"J. C.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":832030,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Civiello, A. P.","contributorId":272519,"corporation":false,"usgs":false,"family":"Civiello","given":"A. P.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":832031,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gemeinhardt, T.R.","contributorId":272520,"corporation":false,"usgs":false,"family":"Gemeinhardt","given":"T.R.","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":832032,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hall, J. R.","contributorId":272561,"corporation":false,"usgs":false,"family":"Hall","given":"J.","email":"","middleInitial":"R.","affiliations":[{"id":17640,"text":"Nebraska Game and Parks Commission","active":true,"usgs":false}],"preferred":false,"id":832141,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70222350,"text":"70222350 - 2021 - Model estimated baseflow for streams with endangered Atlantic Salmon in Maine, USA","interactions":[],"lastModifiedDate":"2021-11-16T15:32:29.208233","indexId":"70222350","displayToPublicDate":"2021-07-18T09:08:05","publicationYear":"2021","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":"Model estimated baseflow for streams with endangered Atlantic Salmon in Maine, USA","docAbstract":"We present a regression model for estimating mean August baseflow per square kilometer of drainage area to help resource managers assess relative amounts of baseflow in Maine streams with Atlantic Salmon habitat. The model was derived from mean August baseflows computed at 31 USGS streamflow gages in Maine. We use an ordinary least squares regression model to estimate mean August baseflow per unit drainage area from two explanatory variables: percentage of the basin underlain by sand and gravel aquifers and mean July precipitation in the basin. This model provides the ability to estimate mean August baseflow in cubic meters per second per square kilometer of basin area on user-selected, ungaged sites throughout Maine south of 46° 21′55″ N latitude. The model has an adjusted R2 of 0.78 and a mean 95% prediction interval of plus or minus 0.002 cubic meters per second per square kilometer. A map of the Narraguagus watershed in eastern coastal Maine shows reaches color coded by relative amounts of baseflow predicted by the model as an example of how this method could be applied throughout Maine. The map can be used to identify reaches with relatively higher amounts of baseflow during summer low flows for habitat conservation and restoration work. These areas have the potential to be high-quality habitat for Atlantic salmon and other cold-water fish because baseflows are known to moderate stream temperatures in summer low-flow periods.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3835","usgsCitation":"Lombard, P.J., Dudley, R., Collins, M.J., Saunders, R., and Atkinson, E., 2021, Model estimated baseflow for streams with endangered Atlantic Salmon in Maine, USA: River Research and Applications, v. 37, no. 9, p. 1254-1264, https://doi.org/10.1002/rra.3835.","productDescription":"11 p.","startPage":"1254","endPage":"1264","ipdsId":"IP-124443","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":451480,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.3835","text":"Publisher Index Page"},{"id":436271,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KRSNU7","text":"USGS data release","linkHelpText":"Spatial Coverage for Estimated Baseflow for Streams Containing Endangered Atlantic Salmon in Maine, USA (version 1.1, June 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\"}}]}","volume":"37","issue":"9","noUsgsAuthors":false,"publicationDate":"2021-07-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Lombard, Pamela J. 0000-0002-0983-1906","orcid":"https://orcid.org/0000-0002-0983-1906","contributorId":203509,"corporation":false,"usgs":true,"family":"Lombard","given":"Pamela","email":"","middleInitial":"J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819723,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dudley, Robert W. 0000-0002-0934-0568","orcid":"https://orcid.org/0000-0002-0934-0568","contributorId":220211,"corporation":false,"usgs":true,"family":"Dudley","given":"Robert W.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819724,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collins, Matthias J. 0000-0003-4238-2038","orcid":"https://orcid.org/0000-0003-4238-2038","contributorId":196365,"corporation":false,"usgs":false,"family":"Collins","given":"Matthias","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":819725,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saunders, Rory","contributorId":261311,"corporation":false,"usgs":false,"family":"Saunders","given":"Rory","email":"","affiliations":[{"id":52809,"text":"NOAA, National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":819726,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Atkinson, Ernie","contributorId":261312,"corporation":false,"usgs":false,"family":"Atkinson","given":"Ernie","email":"","affiliations":[{"id":52810,"text":"Maine Department of Marine Resources, Division of Sea-run Fisheries","active":true,"usgs":false}],"preferred":false,"id":819727,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70222389,"text":"70222389 - 2021 - Multicriteria decisions and portfolio analysis: Land acquisition for biological and social objectives","interactions":[],"lastModifiedDate":"2021-10-06T15:35:26.925959","indexId":"70222389","displayToPublicDate":"2021-07-18T07:22:34","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Multicriteria decisions and portfolio analysis: Land acquisition for biological and social objectives","docAbstract":"Resource allocation for land acquisition is a common multi-objective problem that involves complex trade-offs. The National Wildlife Refuge System (NWRS) of the U.S. Fish and Wildlife Service currently uses the Targeted Resource Acquisition Comparison Tool (TRACT) to allocate funds from the Migratory Bird Conservation Fund (MBCF; established through the Migratory Bird Hunting and Conservation Act of 1934) for land acquisition based on cost-benefit analysis, regional priority rankings of candidate land parcels available for acquisition, and the overall biological contribution to duck population objectives. However, current policy encourages decision makers to consider societal and economic benefits of lands acquired, in addition to their biological benefits to waterfowl. These decisions about portfolio elements (i.e. individual land parcels) require an analysis of the difficult trade-offs among multiple objectives. In the last decade the application of multi-criteria decision analysis (MCDA) methods has been instrumental in aiding decision makers with complex multi-objective decisions. In this study, we present an alternative approach to developing land acquisition portfolios using MCDA and Modern Portfolio Theory (MPT). We describe the development of a portfolio decision analysis tool using constrained optimization for land acquisition decisions by the NWRS. We outline the decision framework, describe development of the prototype tool in Microsoft Excel, and test the results of the tool using land parcels submitted as candidates for MBCF funding in 2019. Our results indicate that the constrained optimization outperformed the traditional TRACT method and ad hoc portfolios developed using current NWRS criteria.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2420","usgsCitation":"Krainyk, A., Lyons, J., Rice, M.B., Fowler, K., Soulliere, G.J., Brasher, M.G., Humburg, D.D., and Coluccy, J.M., 2021, Multicriteria decisions and portfolio analysis: Land acquisition for biological and social objectives: Ecological Applications, v. 31, no. 2, e02420, 46 p., https://doi.org/10.1002/eap.2420.","productDescription":"e02420, 46 p.","ipdsId":"IP-108367","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":387464,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-08-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Krainyk, Anastasia Ihorvina 0000-0002-3100-9011","orcid":"https://orcid.org/0000-0002-3100-9011","contributorId":261353,"corporation":false,"usgs":true,"family":"Krainyk","given":"Anastasia Ihorvina","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":819915,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":261354,"corporation":false,"usgs":true,"family":"Lyons","given":"James E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":819916,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rice, Mindy B.","contributorId":214399,"corporation":false,"usgs":false,"family":"Rice","given":"Mindy","email":"","middleInitial":"B.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":819917,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fowler, Kenneth A.","contributorId":261355,"corporation":false,"usgs":false,"family":"Fowler","given":"Kenneth A.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":819918,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Soulliere, Gregory J.","contributorId":172329,"corporation":false,"usgs":false,"family":"Soulliere","given":"Gregory","email":"","middleInitial":"J.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":819919,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brasher, Michael G.","contributorId":214393,"corporation":false,"usgs":false,"family":"Brasher","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":36215,"text":"Ducks Unlimited","active":true,"usgs":false}],"preferred":false,"id":819920,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Humburg, Dale D.","contributorId":79357,"corporation":false,"usgs":false,"family":"Humburg","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":13073,"text":"Ducks Unlimited, Inc.","active":true,"usgs":false}],"preferred":false,"id":819921,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Coluccy, John M.","contributorId":214395,"corporation":false,"usgs":false,"family":"Coluccy","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":36215,"text":"Ducks Unlimited","active":true,"usgs":false}],"preferred":false,"id":819922,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70222346,"text":"70222346 - 2021 - The Chesapeake Bay program modeling system: Overview and recommendations for future development","interactions":[],"lastModifiedDate":"2021-07-22T14:30:50.592821","indexId":"70222346","displayToPublicDate":"2021-07-17T09:14:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"The Chesapeake Bay program modeling system: Overview and recommendations for future development","docAbstract":"The Chesapeake Bay is the largest, most productive, and most biologically diverse estuary in the continental United States providing crucial habitat and natural resources for culturally and economically important species. Pressures from human population growth and associated development and agricultural intensification have led to excessive nutrient and sediment inputs entering the Bay, negatively affecting the health of the Bay ecosystem and the economic services it provides. The Chesapeake Bay Program (CBP) is a unique program formally created in 1983 as a multi-stakeholder partnership to guide and foster restoration of the Chesapeake Bay and its watershed. Since its inception, the CBP Partnership has been developing, updating, and applying a complex linked modeling system of watershed, airshed, and estuary models as a planning tool to inform strategic management decisions and Bay restoration efforts. This paper provides a description of the 2017 CBP Modeling System and the higher trophic level models developed by the NOAA Chesapeake Bay Office, along with specific recommendations that emerged from a 2018 workshop designed to inform future model development. Recommendations highlight the need for simulation of watershed inputs, conditions, processes, and practices at higher resolution to provide improved information to guide local nutrient and sediment management plans. More explicit and extensive modeling of connectivity between watershed landforms and estuary sub-areas, estuarine hydrodynamics, watershed and estuarine water quality, the estuarine-watershed socioecological system, and living resources will be important to broaden and improve characterization of responses to targeted nutrient and sediment load reductions. Finally, the value and importance of maintaining effective collaborations among jurisdictional managers, scientists, modelers, support staff, and stakeholder communities is emphasized. An open collaborative and transparent process has been a key element of successes to date and is vitally important as the CBP Partnership moves forward with modeling system improvements that help stakeholders evolve new knowledge, improve management strategies, and better communicate outcomes.
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2021 - Supporting cost-effective watershed management strategies for Chesapeake Bay using a modeling and optimization framework","interactions":[],"lastModifiedDate":"2021-10-11T12:37:34.100588","indexId":"70224975","displayToPublicDate":"2021-07-17T07:30:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7164,"text":"Environmental Modelling & Software","active":true,"publicationSubtype":{"id":10}},"title":"Supporting cost-effective watershed management strategies for Chesapeake Bay using a modeling and optimization framework","docAbstract":"Extensive efforts to adaptively manage nutrient pollution rely on Chesapeake Bay Program's (Phase 6) Watershed Model, called Chesapeake Assessment Scenario Tool (CAST), which helps decision-makers plan and track implementation of Best Management Practices (BMPs). We describe mathematical characteristics of CAST and develop a constrained nonlinear BMP-subset model, software, and visualization framework. This represents the first publicly available optimization framework for exploring least-cost strategies of pollutant load control for the United States' largest estuary. The optimization identifies implementation options for a BMP subset modeled with load reduction effectiveness factors, and the web interface facilitates interactive exploration of >30,000 solutions organized by objective, nutrient control level, and for ~200 counties. We assess framework performance and demonstrate modeled cost improvements when comparing optimization-suggested proposals with proposals inspired by jurisdiction plans. Stakeholder feedback highlights the framework's current utility for investigating cost-effective tradeoffs and its usefulness as a foundation for future analysis of restoration strategies.
The Sandy Hook Unit, Gateway National Recreation Area (hereafter Sandy Hook) in New Jersey is a 10-kilometer-long spit visited by thousands of people each year who take advantage of the historical and natural resources and recreational opportunities. The historical and natural resources are threatened by global climate change, including sea-level rise (SLR), changes in precipitation and groundwater recharge, and changes in the frequency and severity of coastal storms. Fresh groundwater resources are important to the ecosystems of Sandy Hook. The Bayside Holly Forest, one of only two known old-growth American holly (Ilex opaca) maritime forests, is particularly vulnerable to global climate change because of the proximity of the water table to land surface in low-lying areas and the potential for saltwater intrusion and inundation.
The shallow groundwater-flow system on Sandy Hook is dominated by recharge from precipitation, fresh groundwater discharge to evapotranspiration (ET), discharge to surface seeps, and submarine groundwater discharge (groundwater discharging directly to the ocean). A three-dimensional groundwater-flow model that simulates the shallow groundwater-flow system and interaction with surrounding saltwater boundaries was constructed to simulate multi-density groundwater flow, treating the freshwater/saltwater transition zone as a sharp interface that represents the half-seawater surface.
Groundwater-flow simulations completed for this study include a Baseline scenario, three SLR scenarios (0.2, 0.4, and 0.6 meter [m]), two Recharge scenarios—a 10-percent Increased Recharge scenario and a 10-percent Decreased Recharge scenario—and a scenario with 0.6 m of SLR and 10-percent increase in recharge. The Recharge scenarios indicate the system is not sensitive to a 10-percent increase or decrease in recharge from the Baseline scenario. In the SLR scenarios, SLR causes the water table to rise, resulting in increased fresh groundwater discharge to ET and seeps, and reduced submarine discharge compared to the Baseline scenario. The increased discharge to ET and seeps causes the magnitude of water-table rise to be less than that of SLR, which in turn causes the thickness of the freshwater lens to thin, reducing the depth to the half-seawater surface. Water-table rise associated with SLR diminishes the thickness of the unsaturated zone; comparing the Baseline and the 0.6-m SLR scenarios, the area where the simulated water table is above land surface increases by 50.6 hectares, from about 0.9 to 7.4 percent of the land area of Sandy Hook. Areas where the simulated water table is above land surface are likely to be emergent wetlands and contain freshwater if they are tens of meters or more from the shoreline. The steady-state simulations indicate that the percentage of land where the half-seawater surface is less than 9 m below the water table increases from about 2.5 percent (20 hectares) to about 9 percent (74 hectares) with 0.6 m of SLR. In low-lying areas close to the Sandy Hook Bay shoreline, the half-seawater surface is simulated to be as much as 20 m closer to the water table with SLR of 0.6 m. Transient salinization, if any, of shallow groundwater from increased frequency or severity of storm-driven inundation is not included in the analysis.
Natural resources on Sandy Hook, particularly the Bayside Holly Forest, may be adversely affected by the rising water table associated with SLR. Freshwater emergent wetlands may increase in area at the expense of other ecosystem assemblages occurring in or on the edges of low-lying enclosed depressions. Cultural resources close to the water table, such as existing basements of structures, may be adversely affected.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205080","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Carleton, G.B., Charles, E.G., Fiore, A.R., and Winston, R.B., 2021, Simulation of water-table response to sea-level rise and change in recharge, Sandy Hook unit, Gateway National Recreation Area, New Jersey: U.S. Geological Survey Scientific Investigations Report 2020–5080, 91 p., https://doi.org/10.3133/sir20205080.","productDescription":"Report: ix, 91 p.; Data Release","numberOfPages":"91","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-081081","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":387036,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20205117","text":"Scientific Investigations Report 2020–5117","linkHelpText":"- Simulation of Water-Table and Freshwater/Saltwater Interface Response to Climate-Change-Driven Sea-Level Rise and Changes in Recharge at Fire Island National Seashore, New York"},{"id":387037,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20205104","text":"Scientific Investigations Report 2020–5104","linkHelpText":"- Simulated Effects of Sea-Level Rise on the Shallow, Fresh Groundwater System of Assateague Island, Maryland and Virginia"},{"id":387032,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BP018M","text":"USGS data release","linkHelpText":"MODFLOW-2005 with SWI2 used to evaluate the water-table response to sea-level rise and change in recharge, Sandy Hook Unit, Gateway National Recreation Area, New Jersey"},{"id":387033,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5080/coverthb.jpg"},{"id":387034,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5080/sir20205080.pdf","text":"Report","size":"19.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5080"}],"country":"United States","state":"New Jersey","otherGeospatial":"Gateway National Recreation Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.04716491699219,\n 40.39467254512293\n ],\n [\n -73.95927429199219,\n 40.39467254512293\n ],\n [\n -73.95927429199219,\n 40.49239284038429\n ],\n [\n -74.04716491699219,\n 40.49239284038429\n ],\n [\n -74.04716491699219,\n 40.39467254512293\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike
Lawrenceville, NJ 08648
The fresh groundwater system at Fire Island National Seashore in New York is one of the natural resources that is most vulnerable to climate change; the various federally listed threatened or endangered species that live on Fire Island, including the piping plover, roseate tern shorebird, and seabeach amaranth may be affected by changes in the groundwater system. The U.S. Geological Survey, in cooperation with the National Park Service, developed a three-dimensional groundwater-flow model to simulate climate-change-related changes in depth to the water table and depth to freshwater/saltwater interfaces on Fire Island. An existing SEAWAT three-dimensional variable-density groundwater flow and transport model was converted to a MODFLOW–NWT three-dimensional finite-difference groundwater model with the Seawater Intrusion (SWI2) package and recalibrated using the UCODE_2005 automatic calibration software. The simulated groundwater divide was found to be skewed strongly toward the ocean shore in response to the modeled wave setup and tidal pumping overheight.
Effects of climate change include sea-level rise and changes in groundwater recharge rates. Sea-level rise scenarios included specified uniform steady states at 0.2-, 0.4-, and 0.6-meter increases above the 2015 level, applied to the existing topography. A high-recharge scenario was created by increasing 2015 recharge rates by 10 percent. Under all scenarios except the low-recharge scenario, the depth to the water table and the thickness of the unsaturated zone decreased. The thickness of the freshwater lens decreased under every scenario. Resulting maps were generated on a 25-meter grid and indicate changes in areas where natural resources may be vulnerable because of projected climate changes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205117","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Misut, P.E., and Dressler, S., 2021, Simulation of water-table and freshwater/saltwater interface response to climate-change-driven sea-level rise and changes in recharge at Fire Island National Seashore, New York: U.S. Geological Survey Scientific Investigations Report 2020–5117, 47 p., https://doi.org/10.3133/sir20205117.","productDescription":"Report: vii, 47 p.; Data Release","numberOfPages":"47","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-082635","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":387031,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95TBIMW","text":"USGS data release","linkHelpText":"MODFLOW-NWT model used to simulate water-table and freshwater/saltwater interface response to climate-change-driven sea-level rise and changes in recharge at the Fire Island National Seashore, New York"},{"id":387039,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20205104","text":"Scientific Investigations Report 2020–5104","linkHelpText":"- Simulated Effects of Sea-Level Rise on the Shallow, Fresh Groundwater System of Assateague Island, Maryland and Virginia"},{"id":387038,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20205080","text":"Scientific Investigations Report 2020–5080","linkHelpText":"- Simulation of Water-Table Response to Sea-Level Rise and Change in Recharge, Sandy Hook Unit, Gateway National Recreation Area, New Jersey"},{"id":387030,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5117/sir20205117.pdf","text":"Report","size":"21.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5117"},{"id":387029,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5117/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island National Seashore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.31314086914062,\n 40.614994915836924\n ],\n [\n -73.2513427734375,\n 40.612909950230936\n ],\n [\n -73.06869506835938,\n 40.65563874006118\n ],\n [\n -72.84072875976562,\n 40.730608477796636\n ],\n [\n -72.75146484374999,\n 40.763901280945866\n ],\n [\n -72.76931762695312,\n 40.77534183237267\n ],\n [\n -72.83798217773438,\n 40.74725696280421\n ],\n [\n -72.96157836914061,\n 40.72228267283148\n ],\n [\n -73.08792114257812,\n 40.66918118282895\n ],\n [\n -73.2403564453125,\n 40.637925243274374\n ],\n [\n -73.30215454101562,\n 40.63375667842965\n ],\n [\n -73.32687377929688,\n 40.62020704520565\n ],\n [\n -73.31314086914062,\n 40.614994915836924\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
Extreme surface ocean waves are often primary drivers of coastal flooding and erosion over various time scales. Hence, understanding future changes in extreme wave events owing to global warming is of socio-economic and environmental significance. However, our current knowledge of potential changes in high-frequency (defined here as having return periods of less than 1 year) extreme wave events are largely unknown, despite being strongly linked to coastal hazards across time scales relevant to coastal management. Here, we present global climate-modeling evidence, based on the most comprehensive multi-method, multi-model wave ensemble, of projected changes in a core set of extreme wave indices describing high-frequency, extra-tropical storm-driven waves. We find changes in high-frequency extreme wave events of up to ∼50%–100% under RCP8.5 high-emission scenario; which is nearly double the expected changes for RCP4.5 scenario, when globally integrated. The projected changes exhibit strong inter-hemispheric asymmetry, with strong increases in extreme wave activity across the tropics and high latitudes of the Southern Hemisphere region, and a widespread decrease across most of the Northern Hemisphere. We find that the patterns of projected increase across these extreme wave events over the Southern Hemisphere region resemble their historical response to the positive anomaly of the Southern Annular Mode. Our findings highlight that many countries with low-adaptive capacity are likely to face increasing exposure to much more frequent extreme wave events in the future.
","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/ac1013","usgsCitation":"Morim, J., Vitousek, S., Hemer, M., Reguero, B., Erikson, L.H., Casas-Prat, M., Wang, X.L., Semedo, A., Mori, N., Shimura, T., Mentaschi, L., and Timmerman, B., 2021, Global-scale changes to extreme ocean wave events due to anthropogenic warming: Environmental Research Letters, v. 16, no. 7, 074056, 10 p., https://doi.org/10.1088/1748-9326/ac1013.","productDescription":"074056, 10 p.","ipdsId":"IP-116482","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":451497,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ac1013","text":"Publisher Index Page"},{"id":388151,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-07-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Morim, Joao","contributorId":264483,"corporation":false,"usgs":false,"family":"Morim","given":"Joao","email":"","affiliations":[{"id":7117,"text":"Griffith University","active":true,"usgs":false}],"preferred":false,"id":821581,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vitousek, Sean 0000-0002-3369-4673 svitousek@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-4673","contributorId":149065,"corporation":false,"usgs":true,"family":"Vitousek","given":"Sean","email":"svitousek@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":821582,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hemer, Mark","contributorId":264484,"corporation":false,"usgs":false,"family":"Hemer","given":"Mark","email":"","affiliations":[{"id":36909,"text":"CSIRO","active":true,"usgs":false}],"preferred":false,"id":821583,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reguero, Borja","contributorId":264485,"corporation":false,"usgs":false,"family":"Reguero","given":"Borja","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":821584,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":821585,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Casas-Prat, Merce","contributorId":264487,"corporation":false,"usgs":false,"family":"Casas-Prat","given":"Merce","email":"","affiliations":[{"id":54478,"text":"Environment and Climate Change Canada,","active":true,"usgs":false}],"preferred":false,"id":821586,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wang, Xiaolan L.","contributorId":264488,"corporation":false,"usgs":false,"family":"Wang","given":"Xiaolan","email":"","middleInitial":"L.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":821587,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Semedo, Alvaro","contributorId":264491,"corporation":false,"usgs":false,"family":"Semedo","given":"Alvaro","affiliations":[{"id":54479,"text":"IHE-Delft","active":true,"usgs":false}],"preferred":false,"id":821588,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mori, Nobuhito","contributorId":264492,"corporation":false,"usgs":false,"family":"Mori","given":"Nobuhito","affiliations":[{"id":36662,"text":"Kyoto University","active":true,"usgs":false}],"preferred":false,"id":821589,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Shimura, Tomoya","contributorId":264493,"corporation":false,"usgs":false,"family":"Shimura","given":"Tomoya","email":"","affiliations":[{"id":36662,"text":"Kyoto University","active":true,"usgs":false}],"preferred":false,"id":821590,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mentaschi, Lorenzo","contributorId":264494,"corporation":false,"usgs":false,"family":"Mentaschi","given":"Lorenzo","email":"","affiliations":[{"id":54481,"text":"European Commission","active":true,"usgs":false}],"preferred":false,"id":821591,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Timmerman, Ben","contributorId":264495,"corporation":false,"usgs":false,"family":"Timmerman","given":"Ben","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":821592,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70222933,"text":"70222933 - 2021 - Regeneration trends along climate gradients in Taxodium distichum forests of the southeastern United States","interactions":[],"lastModifiedDate":"2023-06-09T14:09:27.431715","indexId":"70222933","displayToPublicDate":"2021-07-16T09:23:48","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Regeneration trends along climate gradients in Taxodium distichum forests of the southeastern United States","title":"Regeneration trends along climate gradients in Taxodium distichum forests of the southeastern United States","docAbstract":"The development of relict vegetation at the edges of some ecosystems has taken place particularly in environments where the regeneration of foundational species is declining. As an important stage of regeneration in the Taxodium distichum, this study explored the relationship of cone volume and seed number across environmental gradients in the Mississippi River Alluvial Valley (MRAV) and northern Gulf of Mexico Coast (GOM) in a long-term network of forested wetlands (North American Baldcypress Swamp Network (NABCSN)) from 2007 to 2019. Resembling spheroids, the volumes of Taxodium distichum cones were based on the measured dimensions of the cones collected in swamps across southeastern environmental gradients. Cones with larger volumes also had larger numbers of seeds (r2 = 0.423, F = 113.9, p < 0.0001; Linear regression equation: Seed number per cone = 9.8925223 + 0.8854056* Cone volume cm3). Mean cone volumes were related to water availability with highest volumes in locations with moderate amounts of total annual precipitation (e.g., White River National Wildlife Refuge (NWR) Arkansas, Tensas NWR Louisiana, and Morgan Brake NWR Mississippi), and longer periods of annual percent time of site drawdown. Cone volume was high in 2018 following the 2017 mega-flood in the Mississippi River Alluvial Valley (MRAV) generated by Hurricane Harvey. Mean annual air temperature was not related to cone volume. Along the Gulf Coast, mean cone volume increased from east to west from Florida to Texas. Especially near the edge of the range of T. distichum forests, smaller cones may be related to regeneration failure and lower seed numbers to support regeneration. A better understanding of regeneration constraints can inform managers of the emergence of relict status in these forests.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2021.119485","usgsCitation":"Middleton, B., Lei, T., Villegas, O., and Liu, X., 2021, Regeneration trends along climate gradients in Taxodium distichum forests of the southeastern United States: Forest Ecology and Management, v. 497, 119485, 10 p.; Data Release, https://doi.org/10.1016/j.foreco.2021.119485.","productDescription":"119485, 10 p.; Data Release","ipdsId":"IP-125636","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":387812,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417855,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H7WGM5"}],"country":"United States","state":"Arkansas, Florida, Illinois, Kentucky, Louisiana, Mississippi, Missouri, Tennessee","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.76953125,\n 37.43997405227057\n ],\n [\n -89.9560546875,\n 37.26530995561875\n ],\n [\n -91.4501953125,\n 33.8339199536547\n ],\n [\n -91.62597656249999,\n 31.765537409484374\n ],\n [\n -91.8896484375,\n 30.44867367928756\n ],\n [\n -90.087890625,\n 29.19053283229458\n ],\n [\n -89.384765625,\n 30.06909396443887\n ],\n [\n -90.4833984375,\n 30.44867367928756\n ],\n [\n -89.3408203125,\n 32.84267363195431\n ],\n [\n -88.76953125,\n 37.43997405227057\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.814453125,\n 29.6880527498568\n ],\n [\n -83.6279296875,\n 29.878755346037977\n ],\n [\n -83.671875,\n 30.675715404167743\n ],\n [\n -85.1220703125,\n 30.600093873550072\n ],\n [\n -84.814453125,\n 29.6880527498568\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"497","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Middleton, Beth 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":206922,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":820867,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lei, Ting","contributorId":245022,"corporation":false,"usgs":false,"family":"Lei","given":"Ting","affiliations":[{"id":40912,"text":"Beijing Forestry","active":true,"usgs":false}],"preferred":false,"id":820868,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Villegas, Omag 0000-0003-0169-895X","orcid":"https://orcid.org/0000-0003-0169-895X","contributorId":263439,"corporation":false,"usgs":false,"family":"Villegas","given":"Omag","email":"","affiliations":[{"id":53989,"text":"Universidad Juarez del Estado de Durango, Mexico","active":true,"usgs":false}],"preferred":false,"id":820869,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Liu, Xiaohui","contributorId":263440,"corporation":false,"usgs":false,"family":"Liu","given":"Xiaohui","email":"","affiliations":[{"id":53990,"text":"NE Institute of Geography and Agroecology, Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":820870,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70222057,"text":"tm13B2 - 2021 - A numerical model for the cooling of a lava sill with heat pipe effects","interactions":[],"lastModifiedDate":"2021-07-19T11:39:28.138117","indexId":"tm13B2","displayToPublicDate":"2021-07-16T09:00:07","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"13-B2","displayTitle":"A Numerical Model for the Cooling of a Lava Sill with Heat Pipe Effects","title":"A numerical model for the cooling of a lava sill with heat pipe effects","docAbstract":"Understanding the cooling process of volcanic intrusions into wet sediments is a difficult but important problem, given the presence of extremely large temperature gradients and potentially complex water-magma interactions. This report presents a numerical model to study such interactions, including the effect of heat pipes on the cooling of volcanic intrusions. Udell (1985) has shown that heat pipes may develop in heated saturated granular media under laboratory conditions. In previous work, Baker and others (2015) calculated temperatures in the vicinity of a volcanic sill that intruded into wet sediment, showing an unexpected temperature profile in which peak temperatures remained near constant over a region extending a meter above and below the sill. This is challenging to explain with conduction or convection heating methods but is predicted if the heat transfer is performed primarily by a heat pipe. We have numerically modeled the cooling of a lava sill under similar circumstances, using the experimental findings of Udell (1985) to estimate the characteristics of the heat pipe. We have constructed a model using Microsoft C#.NET, complete with an intuitive graphical user interface. The model is available from the U.S. Geological Survey and is capable of being run on Microsoft Windows 7 and higher with modest hardware. We find that the resulting overall temperature profile has some key similarities to the profile inferred by Baker and others (2015). Future models including more detailed convective heat transfer physics will be necessary to fully reproduce the effects of boiling in sediments.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm13B2","usgsCitation":"Williams, K.E., Dundas, C.M., and Kestay, L.P., 2021, A numerical model for the cooling of a lava sill with heat pipe effects: U.S. Geological Survey Techniques and Methods, book 13, chap. B2, 14 p., https://doi.org/10.3133/tm13B2.","productDescription":"v, 14 p.","numberOfPages":"14","onlineOnly":"Y","ipdsId":"IP-120432","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":387233,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/13/b2/tm13B2_LavaCooling-Heatpipe_executable.zip","text":"Program — LavaCooling-Heatpipe.exe","size":"30 KB","linkFileType":{"id":6,"text":"zip"}},{"id":387194,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/13/b2/tm13B2.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":387193,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/13/b2/covrthb.jpg"}],"contact":"Contact Astrogeology Research Program staff
Astrogeology Science Center
U.S. Geological Survey
2255 N. Gemini Dr.
Flagstaff, AZ 86001
High resolution seafloor mapping shows extraordinary evidence that massive (>300 m thick) icebergs once drifted >5,000 km south along the eastern United States, with >700 iceberg scours now identified south of Cape Hatteras. Here we report on sediment cores collected from several buried scours that show multiple plow marks align with Heinrich Event 3 (H3), ~31,000 years ago. Numerical glacial iceberg simulations indicate that the transport of icebergs to these sites occurs during massive, but short-lived, periods of elevated meltwater discharge. Transport of icebergs to the subtropics, away from deep water formation sites, may explain why H3 was associated with only a modest increase in ice-rafting across the subpolar North Atlantic, and implies a complex relationship between freshwater forcing and climate change. Stratigraphy from subbottom data across the scour marks shows there are additional features that are both older and younger, and may align with other periods of elevated meltwater discharge.
","language":"English","publisher":"Nature","doi":"10.1038/s41467-021-23924-0","usgsCitation":"Condron, A., and Hill, J.C., 2021, Timing of iceberg scours and massive ice-rafting events in the subtropical North Atlantic: Nature Communications, v. 12, 3668, 14 p., https://doi.org/10.1038/s41467-021-23924-0.","productDescription":"3668, 14 p.","ipdsId":"IP-120103","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":451504,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-021-23924-0","text":"Publisher Index Page"},{"id":387321,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Georgia, South Carolina","otherGeospatial":"Atlantic Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.37695312499999,\n 34.88593094075317\n ],\n [\n -77.82714843749999,\n 34.161818161230386\n ],\n [\n -79.365234375,\n 33.137551192346145\n ],\n [\n -81.0791015625,\n 31.653381399664\n ],\n [\n -81.474609375,\n 30.259067203213018\n ],\n [\n -79.6728515625,\n 26.86328062676624\n ],\n [\n -75.76171875,\n 27.916766641249065\n ],\n [\n -73.0810546875,\n 28.92163128242129\n ],\n [\n -71.71875,\n 34.161818161230386\n ],\n [\n -76.37695312499999,\n 34.88593094075317\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2021-06-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Condron, Alan 0000-0002-7337-1713","orcid":"https://orcid.org/0000-0002-7337-1713","contributorId":229547,"corporation":false,"usgs":false,"family":"Condron","given":"Alan","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":819626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hill, Jenna C. 0000-0002-7475-357X","orcid":"https://orcid.org/0000-0002-7475-357X","contributorId":21987,"corporation":false,"usgs":true,"family":"Hill","given":"Jenna","email":"","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":819627,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}