Since the 1990s, cosmogenic nuclides have revolutionized the study of Earth surface processes, particularly the understanding of rates and dates. These nuclides, including 3He, 10Be, 14C, 21Ne, 26Al, and 36Cl, enable dating of landforms and the measurement of erosion rates both at the scale of drainage basins and at specific locations on Earth's surface. Cosmogenic nuclides are produced at low rates (several to hundreds of atoms per gram per year) by the interaction of cosmic rays with elements both in the atmosphere and in surficial materials, including in rock and soil. Measuring nuclide concentrations requires elemental separation from source geologic material followed by counting of atoms using sensitive accelerator mass spectrometers. Because nuclide production rates have been quantified, the measured concentration of these nuclides can be interpreted as a near-surface residence time. Here, we review the systematics of commonly used cosmogenic nuclides, describe how they are extracted and measured, and then present case studies focusing on the most commonly measured cosmogenic nuclide, 10Be. We present common applications such as dating surface features, including moraines and outcrops shaped by glaciation, the use of cosmogenic nuclides for inferring tectonic and erosion processes in drainage basins, and the use of these nuclides to trace sediment sources in drainage basins. When multiple nuclides are measured in one sample, they can be used to model burial and exposure histories in stratigraphic sections. We conclude by exploring what the future might bring in terms of measurements and applications.
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Monitoring strategies vary greatly depending on several factors such as the activity of the individual volcano, access, available personnel, and funding.
Certain geodetic monitoring methods, such as Electronic Distance Measurements, are inexpensive but require that scientists be dangerously close to active areas. Other techniques, such as telemetered geodetic measurements (Electronic Tiltmeters and Global Navigation Satellite System), or deformation images from Interferometric Synthetic Aperture Radar, can be collected remotely and with less risk. Observed surface deformation can be fit to the predictions of mathematical source models to obtain quantitative estimates of their parameters (e.g., location, depth, volume change and more). Combined deformation and gravity change measurements can be used to infer the density of subsurface intrusions and better constrain the source of unrest.
To be effective, geodetic monitoring must be done before, during, and after eruptions and must be integrated with other monitoring techniques (e.g., seismology, geochemistry, physical volcanology, remote sensing). It requires the long-term commitment of time and resources.
Done effectively, geodetic monitoring not only can provide timely warnings of escalating volcano hazards but may also lead to improved understanding of how volcanoes work. Even when a volcano is not active, monitoring generates baseline information against which changes in volcano behavior can be compared. Preserving the integrity and accessibility of geodetic data archives is thus essential if future volcanologists are to benefit from the decades-long records of geodetic data gathered by volcano observatories.
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Deposition of the sediments occurred on a marine epeiric ramp that spanned much of the North American continent through most of the Paleozoic. The Upper Midwest region experienced dramatic changes in sea level over geologic time, resulting in the observed sequence of interbedded carbonate and clastic rocks. The greatest degree of karst development occurs within (1) the Lower Ordovician Prairie du Chien Group below the Sauk-Tippecanoe (Knox) unconformity, (2) the Upper Ordovician Galena Group, (3) the Middle and Upper Devonian Wapsipinicon and Cedar Valley Groups, and (4) the Middle Mississippian Mammoth Cave Group and correlative formations. Uplift and exposure of the rocks likely occurred in the Permian, with some later deposition of Cretaceous terrestrial sediments atop the marine strata. Nearly all the Cenozoic sedimentary units were removed by ice sheets during the Pleistocene; however, pockets of Cretaceous sediments persist on the margins of the Driftless Area, a region of the Upper Mississippi River Valley that remained largely free of ice during the last ice age.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Caves and Karst of the Upper Midwest, USA","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-54633-5_1","usgsCitation":"Doctor, D.H., and Alexander, E.C., 2021, Karst geology of the Upper Midwest, USA, chap. of Caves and Karst of the Upper Midwest, USA, 21 p., https://doi.org/10.1007/978-3-030-54633-5_1.","productDescription":"21 p.","ipdsId":"IP-118559","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":383150,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2020-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":810072,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alexander, E. Calvin Jr.","contributorId":173840,"corporation":false,"usgs":false,"family":"Alexander","given":"E.","suffix":"Jr.","email":"","middleInitial":"Calvin","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":810073,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70225626,"text":"70225626 - 2021 - USGS Illinois River Monitoring and Evaluation","interactions":[],"lastModifiedDate":"2024-03-21T16:44:51.356134","indexId":"70225626","displayToPublicDate":"2020-12-01T11:42:15","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":9543,"text":"Interim Summary Report","active":true,"publicationSubtype":{"id":3}},"title":"USGS Illinois River Monitoring and Evaluation","docAbstract":"No abstract available.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"2020 Interim summary report: Asian carp monitoring and response plan","largerWorkSubtype":{"id":3,"text":"Organization Series"},"language":"English","publisher":"Asian Carp Regional Coordinating Committee","usgsCitation":"Harrison, T.J., Hop, K.D., Hlavacek, E., and Knights, B.C., 2021, USGS Illinois River Monitoring and Evaluation: Interim Summary Report, 4 p.","productDescription":"4 p.","startPage":"119","endPage":"122","ipdsId":"IP-128304","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":426840,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":391073,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://invasivecarp.us/PlansReports.html"}],"country":"United States","state":"Illinois","otherGeospatial":"Illinois River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.44907719485067,\n 41.985997476890276\n ],\n [\n -91.5027377363265,\n 41.985997476890276\n ],\n [\n -91.5027377363265,\n 38.48676442684382\n ],\n [\n -87.44907719485067,\n 38.48676442684382\n ],\n [\n -87.44907719485067,\n 41.985997476890276\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harrison, Travis J. 0000-0002-9195-738X","orcid":"https://orcid.org/0000-0002-9195-738X","contributorId":213966,"corporation":false,"usgs":true,"family":"Harrison","given":"Travis","email":"","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":825982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hop, Kevin D. 0000-0002-9928-4773 khop@usgs.gov","orcid":"https://orcid.org/0000-0002-9928-4773","contributorId":1438,"corporation":false,"usgs":true,"family":"Hop","given":"Kevin","email":"khop@usgs.gov","middleInitial":"D.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":825983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hlavacek, Enrika 0000-0002-9872-2305 ehlavacek@usgs.gov","orcid":"https://orcid.org/0000-0002-9872-2305","contributorId":149114,"corporation":false,"usgs":true,"family":"Hlavacek","given":"Enrika","email":"ehlavacek@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":825984,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knights, Brent C. 0000-0001-8526-8468 bknights@usgs.gov","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":2906,"corporation":false,"usgs":true,"family":"Knights","given":"Brent","email":"bknights@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":897033,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70219582,"text":"70219582 - 2021 - Interactive PHREEQ-N-AMDTreat water-quality modeling tools to evaluate performance and design of treatment systems for acid mine drainage","interactions":[],"lastModifiedDate":"2021-04-15T12:53:09.492694","indexId":"70219582","displayToPublicDate":"2020-12-01T07:52:18","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Interactive PHREEQ-N-AMDTreat water-quality modeling tools to evaluate performance and design of treatment systems for acid mine drainage","docAbstract":"The PHREEQ-N-AMDTreat aqueous geochemical modeling tools described herein simulate changes in pH and solute concentrations resulting from passive and active treatment of acidic or alkaline mine drainage (AMD). The “user-friendly” interactive tools, which are publicly available software, utilize PHREEQC equilibrium aqueous and surface speciation models and kinetics models for O2 ingassing and CO2 outgassing, iron and manganese oxidation and precipitation, limestone dissolution, and organic carbon oxidation combined with reduction of nitrate, sulfate, and ferric iron. Reactions with synthetic caustic chemicals (CaO, Ca(OH)2, NaOH, Na2CO3) or oxidizing agents (H2O2) also may be simulated separately or combined with sequential kinetic steps. A user interface facilitates input of water chemistry data for one or two (mixed) influent AMD solutions and adjustment of kinetic variables. Graphical and tabular output indicates the changes in pH, metals and other solute concentrations, total dissolved solids, and specific conductance of treated effluent plus the cumulative quantity of precipitated solids as a function of retention time or the amount of caustic agent added. By adjusting kinetic variables or chemical dosing, the effects of independent or sequential treatment steps that have different retention time (volume/flow rate), aeration rate, quantities of reactive solids, and temperature can be simulated for the specified influent quality. The size (land area) of a treatment system can then be estimated using reaction time estimates (volume for a corresponding treatment step is the product of reaction time and flow rate; area is volume divided by depth). Given the estimated system size, the AMDTreat cost-analysis model may be used to compute approximate costs for installation (capital) and annual operations and maintenance. Thus, various passive and/or active treatment strategies can be identified that could potentially achieve the desired effluent quality, but require different land area, equipment, and costs for construction and operation.
Quantifiable estimates of predator–prey interactions and relationships in aquatic habitats are difficult to obtain and rare, especially when individuals cannot be readily observed. To overcome this observational impediment, imaging sonar was used to assess the cooccurrence of predator‐size fish and juvenile salmonids, Oncorhynchus spp., at the entrance to a floating surface collector (FSC) in the forebay of North Fork Dam on the Clackamas River, Oregon (USA). Imaging sonar can be used to transform active sound waves into visual data, making it possible to obtain continuous underwater observations on the presence and interspecific interactions between predator‐size fish and prey (juvenile salmonids). Hourly counts of smolt‐size fish tracks, diel phase, water clarity and river discharge were used as covariates within a zero‐inflated Poisson model to determine how these factors may influence the number of predators in front of the FSC. Both the number of smolt‐size fish tracks and diel phase had the strongest effects on the number of predator‐size fish tracks, with more predator‐size fish tracks observed during the daytime, and as the number of smolt‐size fish tracks increased. Additionally, the presence of predator‐size fish may affect the abundance and direction of travel of juvenile salmonids, as fewer smolt‐size fish were observed when predators were present, and a greater proportion of smolt‐size fish were observed travelling away from the FSC when predator‐size fish were present. This study provides estimates of predator and prey fish abundance in the vicinity of surface collection systems at moderate‐sized hydropower projects and could help resource managers better understand mechanisms that can influence the survival and passage behaviour of juvenile salmonids using surface collection structures at dams.
","language":"English","publisher":"Wiley","doi":"10.1111/fme.12465","usgsCitation":"Smith, C.D., Plumb, J., Adams, N.S., and Wyatt, G.J., 2021, Predator and prey events at the entrance of a surface‐oriented fish collector at North Fork Dam, Oregon: Fisheries Management and Ecology, v. 28, no. 2, p. 172-182, https://doi.org/10.1111/fme.12465.","productDescription":"11 p.","startPage":"172","endPage":"182","ipdsId":"IP-097283","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":384347,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","city":"Estacada","otherGeospatial":"North Fork Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.38632202148438,\n 45.273920035433605\n ],\n [\n -122.27645874023438,\n 45.273920035433605\n ],\n [\n -122.27645874023438,\n 45.319323121350145\n ],\n [\n -122.38632202148438,\n 45.319323121350145\n ],\n [\n -122.38632202148438,\n 45.273920035433605\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Collin D. 0000-0003-4184-5686 cdsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-4184-5686","contributorId":3111,"corporation":false,"usgs":true,"family":"Smith","given":"Collin","email":"cdsmith@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":811722,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plumb, John M. 0000-0003-4255-1612","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":220178,"corporation":false,"usgs":true,"family":"Plumb","given":"John","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":811723,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Noah S. 0000-0002-8354-0293 nadams@usgs.gov","orcid":"https://orcid.org/0000-0002-8354-0293","contributorId":3521,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","email":"nadams@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":811724,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wyatt, Garth J","contributorId":214904,"corporation":false,"usgs":false,"family":"Wyatt","given":"Garth","email":"","middleInitial":"J","affiliations":[{"id":39135,"text":"Portland General Electric, 33831 Faraday Rd., Estacada, Oregon 97023","active":true,"usgs":false}],"preferred":false,"id":811725,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217365,"text":"70217365 - 2021 - Climate and Ecological Disturbance Analysis of Engelmann spruce and Douglas fir in the Greater Yellowstone Ecosystem","interactions":[],"lastModifiedDate":"2021-01-20T13:53:14.893644","indexId":"70217365","displayToPublicDate":"2020-11-30T07:51:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7512,"text":"Trees, Forests, and People","active":true,"publicationSubtype":{"id":10}},"title":"Climate and Ecological Disturbance Analysis of Engelmann spruce and Douglas fir in the Greater Yellowstone Ecosystem","docAbstract":"The effects of anthropogenic climate change are apparent in the Greater Yellowstone Ecosystem (GYE), USA, with forest die-off, insect outbreaks, and wildfires impacting forest ecosystems. A long-term perspective would enable assessment of the historical range of variability in forest ecosystems and better determination of recent forest dynamics and historical thresholds. The objectives of this study were to (1) develop tree-ring chronologies for Engelmann spruce and Douglas fir growing at the study location, (2) correlate the annual ring widths of each species to monthly climate variables, (3) examine the instrumental climate data for regimes shifts in the mean state of variables, and (4) determine when ecological disturbances occurred through a quantification of growth releases. Finally, we discuss both climate-growth relationships and growth releases in the context of climate regime shifts and known forest disturbances. Engelmann spruce and Douglas fir showed some similar climate responses using moving correlation analysis including negative correlations between ring width and June – August current year temperature and previous growing season temperature. Regime shift analysis indicated significant (p < 0.05) shifts in minimum and maximum GYE temperature in the latter half of the 20th century. Disturbance analysis indicated that both tree species responded to wildfire and insect outbreak events with growth releases in up to 25% of the trees. Disentangling the influence of climate regime shifts and forest disturbances on the climate-growth relationships can be difficult because climate and forest disturbances are intricately linked. Our evidence indicates that regime shifts in monthly climate variables and forest disturbances as recorded by growth releases can influence the ring width response to climate over time. Trees are key to providing a long-term perspective on climate and ecological health across the GYE because they integrate both climate and ecology in their annual ring widths.
Rocky reef habitats in lacustrine systems constitute important areas for lithophilic‐spawning fishes. Interstitial spaces created by the structure of rocky reefs form microenvironments where incubating embryos and juvenile fish are potentially protected from predators and physical displacement. However, if interstitial spaces are filled or blocked by sediment or biofouling, the reef structure may lose these benefits. Common practices to restore reef habitat include augmentation of existing reef structures or construction of new reefs, though these practices can be costly. We explored an alternative approach for reef remediation. In 2018, we developed two benthic sled cleaning devices that used either propulsion or pressurized water jets and were towed behind a small vessel to clean reefs. We used the devices to clean two impaired natural rocky reefs in Saginaw Bay, Lake Huron. We indexed effectiveness of cleaning by measured changes in substrate relative hardness before and after cleaning. A biological response to reef cleaning was also measured by egg deposition of fall (Lake Whitefish Coregonus clupeaformis) and spring (Walleye Sander vitreus) lithophilic spawners. We found that our propulsion cleaning device was more effective in increasing substrate relative hardness than was the water jet device, although this was not consistent among all study locations. We also found that egg deposition on study plots was variable, but in general, egg deposition was highest on study plots that had the greatest increases in relative hardness post‐cleaning. The practicality of cleaning devices is likely related to the magnitude of site‐specific degradation. Our results indicate that the use of these or similar devices can potentially increase the quality of spawning habitat by displacing sediments that have deposited on reef structures.
Documenting responses of biotic assemblages to coal-mining impacts is crucial to informing regulatory and reclamation actions. However, attributing biotic patterns to specific stressors is difficult given the dearth of preimpact studies and prevalence of confounding factors. Analysing species distributions and abundances, especially stratified by species traits, provides insights into how assemblage composition shifts occur. We evaluated stream habitats and fish assemblages along a mining intensity gradient in 83 headwater (2nd- and 3rd-order) streams of the upper Clinch and Powell river basins in Virginia. Our multivariate gradient (MINE.PC1) was based on percentages of watershed area covered by surface mine, underground mine and valley fill to represent spatial variance in mining intensity. MINE.PC1 was positively correlated with conductivity and percentage of substrate as cobble. Forty fish-assemblage metrics were analysed via boosted regression trees to assess assemblage responses to mining intensity, while accounting for environmental variation and spatial structure among sites. Conductivity and MINE.PC1 were strongly negatively related to occurrences of Fantail Darter (Etheostoma flabellare) and sculpin (Cottus) spp. Several taxonomic, trophic and reproductive metrics of assemblage composition responded strongly to mining intensity or its instream correlates. For example, coal mining favoured omnivore-herbivores, but inhibited invertivores, simple lithophils and nonsimple nonlithophils. We revealed distinct negative and positive responses to mining-related stressors, which suggest changes to macroinvertebrate prey availability and/or contaminant loads contribute to fish extirpations in coalfield streams. Future assessments of mining impacts on fish assemblages could be more instructive by including characterisations of physicochemical stressors and regionally calibrated biotic metrics with demonstrated sensitivity to mining.
","language":"English","publisher":"Wiley","doi":"10.1111/eff.12588","usgsCitation":"Martin, Z.P., Angermeier, P.L., Ciparis, S., and Orth, D., 2021, Coal-mining intensity influences species and trait distributions of stream fishes in two Central Appalachian watersheds: Ecology of Freshwater Fish, v. 30, no. 3, p. 347-365, https://doi.org/10.1111/eff.12588.","productDescription":"19 p.","startPage":"347","endPage":"365","ipdsId":"IP-113479","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":454189,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/eff.12588","text":"External Repository"},{"id":396022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Powell River, upper Clinch River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.71630859375,\n 37.153749608429415\n ],\n [\n -82.03765869140625,\n 37.470498470798724\n ],\n [\n -82.89459228515624,\n 36.96306042436515\n ],\n [\n -83.6444091796875,\n 36.61773216000592\n ],\n [\n -82.694091796875,\n 36.602299135790446\n ],\n [\n -81.71630859375,\n 37.153749608429415\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-11-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Martin, Zachary P. 0000-0001-5779-3548 zmartin@usgs.gov","orcid":"https://orcid.org/0000-0001-5779-3548","contributorId":279461,"corporation":false,"usgs":false,"family":"Martin","given":"Zachary","email":"zmartin@usgs.gov","middleInitial":"P.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":834958,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angermeier, Paul L. 0000-0003-2864-170X biota@usgs.gov","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":166679,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834957,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ciparis, Serena","contributorId":279464,"corporation":false,"usgs":false,"family":"Ciparis","given":"Serena","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":834959,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Orth, Donald J.","contributorId":279468,"corporation":false,"usgs":false,"family":"Orth","given":"Donald J.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":834960,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216762,"text":"70216762 - 2021 - Characterizing patterns of genomic variation in the threatened Utah prairie dog: Implications for conservation and management","interactions":[],"lastModifiedDate":"2021-05-14T11:49:09.559193","indexId":"70216762","displayToPublicDate":"2020-11-29T08:40:12","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1601,"text":"Evolutionary Applications","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing patterns of genomic variation in the threatened Utah prairie dog: Implications for conservation and management","docAbstract":"Utah prairie dogs (Cynomys parvidens) are federally threatened due to eradication campaigns, habitat destruction, and outbreaks of plague. Today, Utah prairie dogs exist in small, isolated populations, making them less demographically stable and more susceptible to erosion of genetic variation by genetic drift. We characterized patterns of genetic structure at neutral and putatively adaptive loci in order to evaluate the relative effects of genetic drift and local adaptation on population divergence. We sampled individuals across the Utah prairie dog species range and generated 2,955 single nucleotide polymorphisms (SNPs) using double digest restriction site associated DNA sequencing (ddRAD). Genetic diversity was lower in low elevation sites compared to high elevation sites. Population divergence was high among sites and followed an isolation‐by‐distance (IBD) model. Our results indicate that genetic drift plays a substantial role in the population divergence of the Utah prairie dog, and colonies would likely benefit from translocation of individuals between recovery units, which are characterized by distinct elevations, despite the detection of environmental associations with outlier loci. By understanding the processes that shape genetic structure, better informed decisions can be made with respect to the management of threatened species to ensure that adaptation is not stymied.
Local adaptation can drive diversification of closely related species across environmental gradients and promote convergence of distantly related taxa that experience similar conditions. We examined a potential case of adaptation to novel visual environments in a species flock (Great Lakes salmonids, genus Coregonus) using a new amplicon genotyping protocol on the Oxford Nanopore Flongle and MinION. We sequenced five visual opsin genes for individuals of C. artedi, C. hoyi, C. kiyi, and C. zenithicus. Comparisons revealed species-specific differences in a key spectral tuning amino acid in rhodopsin (Tyr261Phe substitution), suggesting local adaptation of C. kiyi to the blue-shifted depths of Lake Superior. Ancestral state reconstruction demonstrates that parallel evolution and “toggling” at this amino acid residue has occurred several times across the fish tree of life, resulting in identical changes to the visual systems of distantly related taxa across replicated environmental gradients. Our results suggest that ecological differences and local adaptation to distinct visual environments are strong drivers of both evolutionary parallelism and diversification.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/gbe/evaa237","usgsCitation":"Eaton, K., Bernal, M., Backenstose, N., Yule, D., and Krabbenhoft, T.J., 2021, Nanopore amplicon sequencing reveals molecular convergence and local adaptation of rhodopsin in Great Lakes salmonids: Genome Biology and Evolution, v. 13, no. 2, evaa237, 8 p., https://doi.org/10.1093/gbe/evaa237.","productDescription":"evaa237, 8 p.","ipdsId":"IP-120367","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":454193,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gbe/evaa237","text":"Publisher Index Page"},{"id":381029,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.19921875,\n 46.875213396722685\n ],\n [\n -84.92431640625,\n 48.10743118848039\n ],\n [\n -85.7373046875,\n 48.10743118848039\n ],\n [\n -86.50634765625,\n 48.93693495409401\n ],\n [\n -88.24218749999999,\n 49.06666839558117\n ],\n [\n -89.6044921875,\n 48.48748647988415\n ],\n [\n -90.06591796875,\n 47.989921667414194\n ],\n [\n -92.4169921875,\n 46.800059446787316\n ],\n [\n -91.95556640625,\n 46.649436163350245\n ],\n [\n -91.0546875,\n 46.78501604269254\n ],\n [\n -90.966796875,\n 46.51351558059737\n ],\n [\n -90.15380859375,\n 46.483264729155586\n ],\n [\n -88.06640625,\n 47.3834738721015\n ],\n [\n -88.61572265625,\n 46.9502622421856\n ],\n [\n -88.52783203125,\n 46.58906908309182\n ],\n [\n -88.11035156249999,\n 46.830133640447386\n ],\n [\n -87.25341796875,\n 46.42271253466717\n ],\n [\n -86.572265625,\n 46.28622391806706\n ],\n [\n -84.19921875,\n 46.875213396722685\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-11-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Eaton, Katherine","contributorId":245464,"corporation":false,"usgs":false,"family":"Eaton","given":"Katherine","affiliations":[{"id":40126,"text":"University of Buffalo","active":true,"usgs":false}],"preferred":false,"id":806238,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernal, Moises","contributorId":245465,"corporation":false,"usgs":false,"family":"Bernal","given":"Moises","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":806239,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Backenstose, Nathan","contributorId":245466,"corporation":false,"usgs":false,"family":"Backenstose","given":"Nathan","affiliations":[{"id":40126,"text":"University of Buffalo","active":true,"usgs":false}],"preferred":false,"id":806240,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yule, Daniel 0000-0002-0117-5115 dyule@usgs.gov","orcid":"https://orcid.org/0000-0002-0117-5115","contributorId":139532,"corporation":false,"usgs":true,"family":"Yule","given":"Daniel","email":"dyule@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":806241,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krabbenhoft, Trevor J.","contributorId":176498,"corporation":false,"usgs":false,"family":"Krabbenhoft","given":"Trevor","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":806242,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70221833,"text":"70221833 - 2021 - Drivers and projections of ice phenology in mountain lakes in the western United States","interactions":[],"lastModifiedDate":"2021-07-09T18:35:41.337556","indexId":"70221833","displayToPublicDate":"2020-11-27T13:24:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Drivers and projections of ice phenology in mountain lakes in the western United States","docAbstract":"Climate change is causing rapid warming and altered precipitation patterns in mountain watersheds, both of which influence the timing of ice breakup in mountain lakes. To enable predictions of ice breakup in the future, we analyzed a dataset of mountain lake ice breakup dates derived from remote sensing and historical downscaled climate data. We evaluated drivers of ice breakup, constructed a predictive statistical model, and developed projections of mountain lake ice breakup date with global climate models. Using Random Forest analysis, we determined that winter and spring cumulative snow fraction (portion of precipitation falling as snow) and air temperature are the strongest predictors of ice breakup on mountain lakes. Interactions between precipitation, cumulative winter air temperature and lake surface area indicate that shifts in air temperature and precipitation affect smaller lakes (< 2 km2) more than larger lakes (> 2–10 km2). A linear mixed effects model (RMSE of 18 d), applied with an ensemble of 15 global climate models, projected that end-of-century ice breakup in mountain lakes will be earlier by 25 ± 4 and 61 ± 5 (mean ± SE) days for representative concentration pathways 4.5 and 8.5, respectively.
","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lno.11656","usgsCitation":"Caldwell, T.J., Chandra, S., Albright, T., Harpold, A., Dills, T., Greenberg, J., Sadro, S., and Dettinger, M.D., 2021, Drivers and projections of ice phenology in mountain lakes in the western United States: Limnology and Oceanography, v. 66, no. 3, p. 995-1008, https://doi.org/10.1002/lno.11656.","productDescription":"14 p.","startPage":"995","endPage":"1008","ipdsId":"IP-104573","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":454196,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.11656","text":"Publisher Index Page"},{"id":387042,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Oregon, Washington","otherGeospatial":"Cascade Mountains, northern Rocky Mountains, Sierra Nevada Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.136474609375,\n 48.07807894349862\n ],\n [\n -116.378173828125,\n 49.001843917978526\n ],\n [\n -119.36645507812499,\n 49.001843917978526\n ],\n [\n -119.20166015625,\n 48.52388120259336\n ],\n [\n -117.191162109375,\n 47.66538735632654\n ],\n [\n -116.42211914062499,\n 47.65058757118734\n ],\n [\n -116.114501953125,\n 47.71715357016648\n ],\n [\n -116.136474609375,\n 48.07807894349862\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.76171875,\n 46.475699386607516\n ],\n [\n -119.84985351562499,\n 48.96579381461063\n ],\n [\n -121.78344726562499,\n 49.01625665778159\n ],\n [\n -122.1240234375,\n 47.04766864046083\n ],\n [\n -122.58544921875,\n 45.506346901083425\n ],\n [\n -123.1787109375,\n 42.73087427928485\n ],\n [\n -122.54150390625,\n 42.04113400940807\n ],\n [\n -122.27783203125,\n 41.1290213474951\n ],\n [\n -120.87158203125,\n 41.393294288784865\n ],\n [\n -120.9814453125,\n 42.08191667830631\n ],\n [\n -121.62963867187499,\n 43.98491011404692\n ],\n [\n -121.14624023437499,\n 45.18978009667531\n ],\n [\n -120.76171875,\n 46.475699386607516\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.45507812500001,\n 36.19109202182454\n ],\n [\n -119.794921875,\n 39.01064750994083\n ],\n [\n -120.498046875,\n 40.49709237269567\n ],\n [\n -120.52001953124999,\n 40.94671366508002\n ],\n [\n -121.6845703125,\n 40.56389453066509\n ],\n [\n -120.73974609374999,\n 38.47939467327645\n ],\n [\n -118.23486328125,\n 35.47856499535729\n ],\n [\n -116.87255859374999,\n 35.65729624809628\n ],\n [\n -116.45507812500001,\n 36.19109202182454\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"66","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Caldwell, Timothy J","contributorId":146463,"corporation":false,"usgs":false,"family":"Caldwell","given":"Timothy","email":"","middleInitial":"J","affiliations":[{"id":16704,"text":"University of Nevada - Reno","active":true,"usgs":false}],"preferred":false,"id":818862,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chandra, Sudeep 0000-0002-9297-8211","orcid":"https://orcid.org/0000-0002-9297-8211","contributorId":224786,"corporation":false,"usgs":false,"family":"Chandra","given":"Sudeep","email":"","affiliations":[{"id":32871,"text":"University of Nevada at Reno","active":true,"usgs":false}],"preferred":false,"id":818863,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Albright, Thomas","contributorId":260809,"corporation":false,"usgs":false,"family":"Albright","given":"Thomas","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":818864,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harpold, Adrian","contributorId":207118,"corporation":false,"usgs":false,"family":"Harpold","given":"Adrian","affiliations":[{"id":37455,"text":"University of Nevada","active":true,"usgs":false}],"preferred":false,"id":818865,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dills, Thomas","contributorId":260810,"corporation":false,"usgs":false,"family":"Dills","given":"Thomas","email":"","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":818866,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Greenberg, Jonathan","contributorId":260811,"corporation":false,"usgs":false,"family":"Greenberg","given":"Jonathan","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":818867,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sadro, Steven 0000-0002-6416-3840","orcid":"https://orcid.org/0000-0002-6416-3840","contributorId":139662,"corporation":false,"usgs":false,"family":"Sadro","given":"Steven","email":"","affiliations":[{"id":12871,"text":"Marine Science Institute, University of California, Santa Barbara, CA, USA","active":true,"usgs":false}],"preferred":false,"id":818868,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dettinger, Michael D. 0000-0002-7509-7332 mddettin@usgs.gov","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":149896,"corporation":false,"usgs":true,"family":"Dettinger","given":"Michael","email":"mddettin@usgs.gov","middleInitial":"D.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":818869,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70227121,"text":"70227121 - 2021 - Terrestrial wildlife in the post-mined Appalachian landscape: Status and opportunities","interactions":[],"lastModifiedDate":"2022-01-03T15:42:46.650199","indexId":"70227121","displayToPublicDate":"2020-11-26T10:52:13","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Terrestrial wildlife in the post-mined Appalachian landscape: Status and opportunities","docAbstract":"Coal mining is an anthropogenic stressor that has impacted terrestrial and semi-aquatic wildlife in the Appalachian Plateau since European settlement. Creation of grassland and early-successional habitats resulting from mining in a forested landscape has resulted in novel, non-analog habitat conditions. Depending on the taxa, the extent of mining on the landscape, and reclamation practices, effects have ranged across a gradient of negative to positive. Forest-obligate species such as woodland salamanders and forest-interior birds or those that depend on aquatic systems in their life cycle have been most impacted. Others, such as grassland and early-successional bird species have responded favorably. Some bat species, as an unintended consequence, use legacy deep mines as winter hibernacula in a region with limited karst geology. Recolonization of impacted wildlife often depends on life strategies and species’ vagility, but also on altered or arrested successional processes on the post-surface mine landscape. Many wildlife species will benefit from Forest Reclamation Approach practices going forward. In the future, managers will be faced with decisions about reforestation versus maintaining open habitats depending on the conservation need of species. Lastly, the post-mined landscape currently is the focal point for a regional effort to restore elk (Cervus canadensis) in the Appalachians.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Appalachia's coal-mined landscapes","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer Nature","doi":"10.1007/978-3-030-57780-3_6","usgsCitation":"Lituma, C.M., Cox, J., Spear, S.F., Edwards, J.W., De La Cruz, J.L., Muller, L.I., and Ford, W., 2021, Terrestrial wildlife in the post-mined Appalachian landscape: Status and opportunities, chap. of Appalachia's coal-mined landscapes, p. 135-166, https://doi.org/10.1007/978-3-030-57780-3_6.","productDescription":"32 p.","startPage":"135","endPage":"166","ipdsId":"IP-119718","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":488353,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10919/104692","text":"External Repository"},{"id":393655,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Appalachian Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.15625,\n 36.66841891894786\n ],\n [\n -75.05859375,\n 41.244772343082076\n ],\n [\n -73.36669921875,\n 43.004647127794435\n ],\n [\n -72.1142578125,\n 44.008620115415354\n ],\n [\n -74.44335937499999,\n 44.74673324024678\n ],\n [\n -81.9580078125,\n 38.496593518947584\n ],\n [\n -80.15625,\n 36.66841891894786\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2020-11-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Lituma, Christopher M.","contributorId":270668,"corporation":false,"usgs":false,"family":"Lituma","given":"Christopher","email":"","middleInitial":"M.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":829720,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cox, John J.","contributorId":140196,"corporation":false,"usgs":false,"family":"Cox","given":"John J.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":829721,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spear, Stephen F.","contributorId":120450,"corporation":false,"usgs":true,"family":"Spear","given":"Stephen","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":829722,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Edwards, John W.","contributorId":270671,"corporation":false,"usgs":false,"family":"Edwards","given":"John","email":"","middleInitial":"W.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":829723,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"De La Cruz, Jesse L.","contributorId":270672,"corporation":false,"usgs":false,"family":"De La Cruz","given":"Jesse","email":"","middleInitial":"L.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":829724,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Muller, Lisa I.","contributorId":270673,"corporation":false,"usgs":false,"family":"Muller","given":"Lisa","email":"","middleInitial":"I.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":829725,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. 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The precision of density estimates depends fundamentally on the number and spatial configuration of traps. Despite this knowledge, existing sampling design recommendations are heuristic and their performance remains untested for most practical applications. To address this issue, we propose a genetic algorithm that minimizes any sensible, criteria‐based objective function to produce near‐optimal sampling designs. To motivate the idea of optimality, we compare the performance of designs optimized using three model‐based criteria related to the probability of capture. We use simulation to show that these designs out‐perform those based on existing recommendations in terms of bias, precision, and accuracy in the estimation of population size. Our approach, available as a function in the R package oSCR, allows conservation practitioners and researchers to generate customized and improved sampling designs for wildlife monitoring.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.3262","usgsCitation":"Dupont, G., Royle, J.A., Nawaz, M., and Sutherland, C., 2021, Optimal sampling design for spatial capture‐recapture: Ecology, v. 102, no. 3, e03262, https://doi.org/10.1002/ecy.3262.","productDescription":"e03262","ipdsId":"IP-118217","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":454202,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ecy.3262","text":"External Repository"},{"id":380979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"102","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-02-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Dupont, Gates","contributorId":245387,"corporation":false,"usgs":false,"family":"Dupont","given":"Gates","email":"","affiliations":[{"id":49179,"text":"University of Massachusetts-Amherst","active":true,"usgs":false}],"preferred":false,"id":806101,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":806102,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nawaz, Muhammad Ali","contributorId":245388,"corporation":false,"usgs":false,"family":"Nawaz","given":"Muhammad Ali","affiliations":[{"id":49180,"text":"Snow Leopard Trust","active":true,"usgs":false}],"preferred":false,"id":806103,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sutherland, Chris","contributorId":245389,"corporation":false,"usgs":false,"family":"Sutherland","given":"Chris","affiliations":[{"id":49181,"text":"Univ. Massachusetts-Amherst","active":true,"usgs":false}],"preferred":false,"id":806104,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217180,"text":"70217180 - 2021 - Is there enough water? How bearish and bullish outlooks are linked to decision-maker perspectives on environmental flows","interactions":[],"lastModifiedDate":"2021-01-11T14:32:11.466282","indexId":"70217180","displayToPublicDate":"2020-11-26T08:27:56","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Is there enough water? How bearish and bullish outlooks are linked to decision-maker perspectives on environmental flows","docAbstract":"Policies that mandate environmental flows (e-flows) can be powerful tools for freshwater conservation, but implementation of these policies faces many hurdles. To better understand these challenges, we explored two key questions: (1) What additional data are needed to implement e-flows? and (2) What are the major socio-political barriers to implementing e-flows? We surveyed water and natural resource decision makers in the semi-arid Red River basin, Texas-Oklahoma, USA, and used social network analysis to analyze their communication patterns. Most respondents agreed that e-flows can provide important benefits and identified the same data needs. However, respondents sharply in their beliefs on other issues, and a clustering analysis revealed two distinct groups of decision makers. One cluster of decision makers tended to be bearish, or pessimistic, and believed that: current flow conditions are not adequate, there are many serious socio-political barriers to implementation, water conflicts will likely increase in the future, and climate change is likely to exacerbate these issues. The other cluster of respondents was bullish, or optimistic: they foresaw fewer future water conflicts and fewer socio-political barriers to implementation. Despite these differences, both clusters largely identified the same data needs and barriers to e-flows implementation. Our social network analysis revealed that the frequency of communication between clusters was not significantly different than the frequency of communication within clusters. Overall, our results suggest that the different perspectives of decision-makers could complicate efforts to implement e-flows and proactively plan for climate change. However, there are opportunities for collaboration on addressing common data needs and barriers to implementation. Overall, our study provides a key socio-environmental perspective on e-flows implementation from a semi-arid and socio-politically complex river basin and contextualizes the many challenges facing e-flows implementation in river basins globally.
Freshwater mussels of the order Unionida are a widely distributed taxon that are important in maintaining freshwater ecosystems and are also highly imperiled throughout the world. Monitoring of mussel populations with environmental DNA (eDNA) is an attractive alternative to traditional methods because it is noninvasive and requires less labor and taxonomic knowledge from field personnel. We developed eDNA metabarcoding assays specific to freshwater mussels and tested them at six sites in the Clinch River, located in the southeastern United States. Our objective was to determine the utility of eDNA metabarcoding for future monitoring of mussel populations and restoration efforts in this watershed. Two metabarcoding assays that target the mitochondrial DNA regions of the cytochrome c oxidase subunit I (COI) and NADH dehydrogenase subunit (ND1) genes were developed and tested. Our assays appear to be order specific, amplifying members from the two families found in North America, Unionidae and Margaritiferidae, while not amplifying nontarget fish or other bivalve species. From the field collected samples, our assays together detected 19 species, eight of which are listed as federally endangered. The assays also detected 42%, 58%, and 54% of the species identified by recent quantitative visual mussel surveys at three sampling sites. Increased sampling effort by processing a greater water volume or number of samples will likely increase species detections. These eDNA metabarcoding assays may enable enhanced monitoring of freshwater mussel assemblages and subsequently inform conservation efforts.
Occupancy methods propelled the quantitative study of species distributions forward by separating the observation process, or the imperfect detectability of species, from the ecological processes of interest governing species distributions. Occupancy studies come at a cost, however: the collection of additional data to account for nondetections at sites where the species is present. The most common occupancy designs (repeated measures designs) require repeat visits to sites or the use of multiple observers or detection methods. Time‐to‐detection methods have been identified as a potentially efficient alternative, requiring only one visit to each site by a single observer. A comparison of time‐to‐detection methods to repeated measures designs for visual encounter surveys would allow researchers to evaluate whether time‐to‐detection methods might be appropriate for their study system and can inform optimal survey design. We collected time‐to‐detection data during two different repeated measures design occupancy surveys for four amphibians and compared the performance of time‐to‐detection methods to the other designs using the location (potential bias) and precision of posterior distributions for occurrence parameters. We further used results of time‐to‐detection surveys to optimize survey design. Time‐to‐detection methods performed best for species that are widespread and have high detection probabilities and rates, but performed less well for cryptic species with lower probability of occurrence or whose detection was strongly affected by survey conditions. In all cases single surveys were most efficient in terms of person‐hours expended, but under some conditions the survey duration required to achieve high detection probabilities would be prohibitively long for a single survey. Regardless of occupancy survey design, time‐to‐detection methods provide important information that can be used to optimize surveys, allowing researchers and resource managers to efficiently achieve monitoring and conservation goals. Collecting time‐to‐detection data while conducting repeated measures occupancy surveys requires only small modifications to field methods but could have large benefits in terms of time spent surveying in the long‐term.
In the past two decades, Salt Plains National Wildlife Refuge has been increasingly recognized as important habitat for both breeding and migratory shorebirds. North American snowy plovers Charadrius nivosus in particular rely on the nearly 5,000-ha salt flat at Salt Plains National Wildlife Refuge, which thousands use as breeding and stopover habitat. Elsewhere on the Southern Great Plains, decadal declines up to 75% within snowy plover subpopulations have been documented and attributed to vegetation encroachment, increased rates of nest predation, and decreased availability of fresh surface water. Despite many attempts to estimate this species' abundance across the continent, to date, no known attempt at distance sampling of snowy plovers has occurred. To address this paucity of data, we assessed feasibility of distance sampling methods to accurately estimate snowy plover abundance and detectability. Distance sampling surveys (2017–2018) indicated high detection probability (P = 0.80) and the population abundance estimate across the salt flat extrapolated to 3,307 individuals. The distance-sampling population abundance estimate is lower than population abundance estimates determined by two previous studies within the past decade but far greater than 2,105 estimated for a study in 2006. Overall, distance sampling snowy plovers at Salt Plains National Wildlife Refuge proved to be an effective addition to pre-established survey protocols but further investigation is needed to compare accuracy and precision of methods used in this study, annual surveys conducted by Salt Plains National Wildlife Refuge, and other potential snowy plover surveys.
","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-20-041","usgsCitation":"Heath-Acre, K., Conway, W.C., Boal, C.W., Collins, D., Hensley, G., Johnson, W., and Schmidt, P.M., 2021, Detectability and abundance of snowy plovers at Salt Plains National Wildlife Refuge, Oklahoma: Journal of Fish and Wildlife Management, v. 12, no. 1, p. 50-60, https://doi.org/10.3996/JFWM-20-041.","productDescription":"11 p.","startPage":"50","endPage":"60","ipdsId":"IP-119304","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":454211,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-20-041","text":"Publisher Index Page"},{"id":396436,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","otherGeospatial":"Salt Plains National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.30841064453125,\n 36.67172341847759\n ],\n [\n -98.12713623046875,\n 36.67172341847759\n ],\n [\n -98.12713623046875,\n 36.85984517196147\n ],\n [\n -98.30841064453125,\n 36.85984517196147\n ],\n [\n -98.30841064453125,\n 36.67172341847759\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-11-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Heath-Acre, K. M.","contributorId":280036,"corporation":false,"usgs":false,"family":"Heath-Acre","given":"K. M.","affiliations":[{"id":57413,"text":"Texas Tech University Lubbock","active":true,"usgs":false}],"preferred":false,"id":835924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, W. C.","contributorId":280037,"corporation":false,"usgs":false,"family":"Conway","given":"W.","email":"","middleInitial":"C.","affiliations":[{"id":57413,"text":"Texas Tech University Lubbock","active":true,"usgs":false}],"preferred":false,"id":835925,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","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":835926,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collins, D. P.","contributorId":276303,"corporation":false,"usgs":false,"family":"Collins","given":"D. P.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":835927,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hensley, G.","contributorId":280038,"corporation":false,"usgs":false,"family":"Hensley","given":"G.","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":835928,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, W. P.","contributorId":280039,"corporation":false,"usgs":false,"family":"Johnson","given":"W. P.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":835929,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schmidt, P. M.","contributorId":280040,"corporation":false,"usgs":false,"family":"Schmidt","given":"P.","email":"","middleInitial":"M.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":835930,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70224617,"text":"70224617 - 2021 - Warming and microbial uptake influence the fate of added soil carbon across a Hawai'ian weathering gradient","interactions":[],"lastModifiedDate":"2021-09-30T11:45:11.03798","indexId":"70224617","displayToPublicDate":"2020-11-23T06:42:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3416,"text":"Soil Biology and Biochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Warming and microbial uptake influence the fate of added soil carbon across a Hawai'ian weathering gradient","docAbstract":"Tropical forest soils contain some of the largest carbon (C) stocks on Earth, yet the effects of warming on the fate of fresh C entering tropical soils are still poorly understood. This research sought to understand how the fate of fresh C entering soils is influenced by warming, soil weathering status, and C chemistry. We hypothesized that compounds that are quickly incorporated into microbial biomass (i.e., greater C use efficiency [CUE]) subsequently have longer-term (255 days) retention in soil. We also hypothesized that relatively weathered soils with greater sorptive capacity also retain more fresh C in the short and longer-terms, and that C in these soils is more resistant to weathering loss compared with less weathered soils. We tested these hypotheses by adding two 13C-labeled compounds (glucose and glycine) to three tropical forest soils from a weathering gradient in Hawai'i, and then incubating soils at ambient (16 °C), +5 °C, and +10 °C for 255 days. We found that 255-day 13C retention in mineral soil across sites and temperatures was best predicted by two factors: initial retention of 13C in mineral soil and initial microbial 13CUE (Adjusted R2 = 0.78). Carbon compound type influenced 13C initial retention, with greater glucose-13C retention versus glycine-13C retention in mineral soils and microbial biomass, corresponding to greater glucose-13C retention in soil at 255 days. Warming had a negative longer-term effect on the retention of 13C only in the least-weathered soil, supporting our hypothesis. These results show that initial retention of fresh C in soils via mineral sorption and microbial uptake is a strong predictor of longer-term retention, indicating that immediate C losses are a major hurdle for soil C storage. Also, retention of fresh C appears most sensitive to warming in less-weathered tropical soils, supporting the idea that mineral sorption may provide some protections against warming. Understanding the interaction between soil sorptive properties and warming for C cycling could improve predictions of forest-climate feedbacks for tropical regions.
Climate warming is expected to have substantial impacts on native trout across the Rocky Mountains, but there is little understanding of how these changes affect future distributions of co-occurring native fishes within population strongholds. We used mixed-effects logistic regression to investigate the role of abiotic (e.g., temperature) and biotic factors (bull trout presence, Salvelinus confluentus) on distributions of westslope cutthroat trout (Oncorhynchus clarkii lewisi; WCT) in the North Fork Flathead River, USA and Canada. The probability of WCT presence increased with stream temperature and decreased with channel gradient and bull trout presence, yet the effect of bull trout was reduced with increasing pool densities. Combining this model with spatially explicit stream temperature projections, we predict a 29% increase in suitable habitat under high emissions through 2075, with gains at mid-elevation sites predicted to exceed bull trout thermal tolerances and high-elevation sites expected to become more thermally suitable for WCT. Our study illustrates the importance of considering abiotic and biotic drivers to assess species response to climate change, helping to guide local-scale climate adaptation and management.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2020-0099","usgsCitation":"Heinle, K., Eby, L., Muhlfeld, C.C., Steed, A., Jones, L., D’Angelo, V.S., Whiteley, A.R., and Hubblewhite, M., 2021, Influence of water temperature and biotic interactions on the distribution of westslope cutthroat trout (Oncorhynchus clarkii lewisi) in a population stronghold under climate change: Canadian Journal of Fisheries and Aquatic Sciences, v. 78, no. 4, p. 444-456, https://doi.org/10.1139/cjfas-2020-0099.","productDescription":"13 p.","startPage":"444","endPage":"456","ipdsId":"IP-111700","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":387127,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alberta, British Columbia, Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.9996337890625,\n 47.98256841921405\n ],\n [\n -113.49426269531249,\n 47.97889140226657\n ],\n [\n -113.6700439453125,\n 48.34894812401375\n ],\n [\n -113.895263671875,\n 48.669198799260045\n ],\n [\n -114.730224609375,\n 49.57510247172322\n ],\n [\n -114.993896484375,\n 49.61070993807422\n ],\n [\n -115.103759765625,\n 49.396675075193976\n ],\n [\n -114.4940185546875,\n 48.585692256886624\n ],\n [\n -113.9996337890625,\n 47.98256841921405\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Heinle, Kadie","contributorId":260877,"corporation":false,"usgs":false,"family":"Heinle","given":"Kadie","email":"","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":819032,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eby, Lisa A","contributorId":251751,"corporation":false,"usgs":false,"family":"Eby","given":"Lisa A","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":819033,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":819034,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Steed, Amber","contributorId":124596,"corporation":false,"usgs":false,"family":"Steed","given":"Amber","affiliations":[{"id":5133,"text":"Montana Fish Wildlife and Parks, Kalispell, Montana 59901","active":true,"usgs":false}],"preferred":false,"id":819035,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jones, Leslie","contributorId":260953,"corporation":false,"usgs":false,"family":"Jones","given":"Leslie","affiliations":[],"preferred":false,"id":819200,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"D’Angelo, Vincent S. 0000-0003-1244-8091 vdangelo@usgs.gov","orcid":"https://orcid.org/0000-0003-1244-8091","contributorId":224823,"corporation":false,"usgs":true,"family":"D’Angelo","given":"Vincent","email":"vdangelo@usgs.gov","middleInitial":"S.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":819036,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Whiteley, Andrew R.","contributorId":150155,"corporation":false,"usgs":false,"family":"Whiteley","given":"Andrew","email":"","middleInitial":"R.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":819037,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hubblewhite, Mark","contributorId":260878,"corporation":false,"usgs":false,"family":"Hubblewhite","given":"Mark","email":"","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":819038,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70216733,"text":"70216733 - 2021 - Small mammal responses to wetland restoration in the Greater Everglades ecosystem","interactions":[],"lastModifiedDate":"2021-04-08T14:17:17.479018","indexId":"70216733","displayToPublicDate":"2020-11-22T07:56:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Small mammal responses to wetland restoration in the Greater Everglades ecosystem","docAbstract":"Wetlands have experienced dramatic losses in extent around the world, disrupting ecosystem function, habitat, and biodiversity. In Florida’s Greater Everglades, a massive restoration effort costing billions of dollars and spanning multiple decades is underway. As Everglades restoration is implemented in incremental projects, scientists and planners monitor the outcomes of projects. In this study, we evaluated the progress of a restoration project in the southwestern Everglades. We aimed to determine whether the presence and density of small mammals differed between areas with hydrologic restoration of the ecosystem and areas without restoration. Our three focal species were: marsh rice rat (Oryzomys palustris), hispid cotton rat (Sigmodon hispidus), and cotton mouse (Peromyscus gossypinus). Using spatially explicit capture‐recapture models, we found greater densities of cotton mouse in restored habitat and lower densities of hispid cotton rat in sites with higher water levels. Additionally, we found an increase in the presence of the marsh rice rat in restored areas compared to unrestored, but captures were too low to reliably assess significance. Our study provides evidence that ongoing restoration in the southwestern Everglades is already impacting the small mammal community.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.13332","usgsCitation":"Romanach, S., D’Acunto, L., Chapman, J., and Hanson, M., 2021, Small mammal responses to wetland restoration in the Greater Everglades ecosystem: Restoration Ecology, v. 29, no. 3, e13332, 9 p., https://doi.org/10.1111/rec.13332.","productDescription":"e13332, 9 p.","ipdsId":"IP-114410","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":454216,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/rec.13332","text":"Publisher Index Page"},{"id":436633,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BWA7RD","text":"USGS data release","linkHelpText":"Small mammal captures at the Picayune Strand State Forest, October 2014 - April 2016"},{"id":380947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Greater Everglades area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.97448730468749,\n 25.035838555635017\n ],\n [\n -79.903564453125,\n 25.035838555635017\n ],\n [\n -79.903564453125,\n 26.59343927024179\n ],\n [\n -81.97448730468749,\n 26.59343927024179\n ],\n [\n -81.97448730468749,\n 25.035838555635017\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Romanach, Stephanie 0000-0003-0271-7825","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":220761,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":806009,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D’Acunto, Laura 0000-0001-6227-0143","orcid":"https://orcid.org/0000-0001-6227-0143","contributorId":215343,"corporation":false,"usgs":true,"family":"D’Acunto","given":"Laura","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":806010,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chapman, Julia","contributorId":245353,"corporation":false,"usgs":false,"family":"Chapman","given":"Julia","affiliations":[],"preferred":false,"id":806011,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanson, Matthew R 0000-0002-2859-3878","orcid":"https://orcid.org/0000-0002-2859-3878","contributorId":245354,"corporation":false,"usgs":false,"family":"Hanson","given":"Matthew R","affiliations":[],"preferred":false,"id":806012,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216501,"text":"70216501 - 2021 - A comparison of plant communities in restored, old field, and remnant coastal prairies","interactions":[],"lastModifiedDate":"2021-04-08T14:15:43.570497","indexId":"70216501","displayToPublicDate":"2020-11-22T07:41:05","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of plant communities in restored, old field, and remnant coastal prairies","docAbstract":"Temperate grasslands are experiencing worldwide declines due to habitat conversion. Grassland restoration efforts are employed to compensate for these losses. However, there is a need to better understand the ecological effects of grassland restoration and management practices. We investigated the effects of three different grassland management regimes on plant communities of coastal prairie ecosystems in southwest Louisiana (USA). We compared old fields, prairie remnants, and restored prairies. Coastal prairies are a unique type of grassland historically present across southeast Texas and southwest Louisiana. Old fields represent former coastal prairie habitats allowed to revegetate naturally without active management. Remnant coastal prairies are small, isolated patches of comparatively intact prairie. Restored coastal prairies have been actively restored by planting native coastal prairie vegetation and managed with prescribed burning, mowing, and/or removal of invasive non‐native species. Our work was conducted in 3 old fields, 4 remnants, and 4 restored prairies. Old fields were dominated by non‐native species with low conservation value, whereas remnant prairies were dominated by native species with high conservation value. Remnants had a mean species richness of 75 species per site, which is higher than most other tallgrass prairie ecosystems in North America. Restored sites were dominated by native species with high conservation value, although the composition differed between restored and remnant sites. Collectively, our results: (1) reinforce the importance of identifying and preserving remnant coastal prairies; and (2) show that restoration of degraded coastal prairies is a viable strategy for supporting the persistence of these unique grassland ecosystems.","language":"English","publisher":"Wiley","doi":"10.1111/rec.13325","usgsCitation":"Feher, L., Allain, L., Osland, M., Pigott, E., Reid, C., and Latiolais, N., 2021, A comparison of plant communities in restored, old field, and remnant coastal prairies: Restoration Ecology, v. 29, no. 3, e13325, 11 p., https://doi.org/10.1111/rec.13325.","productDescription":"e13325, 11 p.","ipdsId":"IP-120471","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":380738,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.1253662109375,\n 29.649868677972304\n ],\n [\n -91.7962646484375,\n 29.649868677972304\n ],\n [\n -91.7962646484375,\n 30.92107637538488\n ],\n [\n -94.1253662109375,\n 30.92107637538488\n ],\n [\n -94.1253662109375,\n 29.649868677972304\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Feher, Laura 0000-0002-5983-6190","orcid":"https://orcid.org/0000-0002-5983-6190","contributorId":221894,"corporation":false,"usgs":true,"family":"Feher","given":"Laura","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":805466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allain, Larry 0000-0002-7717-9761","orcid":"https://orcid.org/0000-0002-7717-9761","contributorId":221930,"corporation":false,"usgs":true,"family":"Allain","given":"Larry","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":805467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Osland, Michael 0000-0001-9902-8692","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":222814,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":805468,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pigott, Elisabeth","contributorId":245154,"corporation":false,"usgs":false,"family":"Pigott","given":"Elisabeth","email":"","affiliations":[{"id":49096,"text":"Pigott Consulting at U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":805469,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reid, Christopher","contributorId":198739,"corporation":false,"usgs":false,"family":"Reid","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":805470,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Latiolais, Nicholas","contributorId":245156,"corporation":false,"usgs":false,"family":"Latiolais","given":"Nicholas","email":"","affiliations":[{"id":49098,"text":"Latiolais Consulting at U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":805471,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70216934,"text":"70216934 - 2021 - Evaluation of a roughness length parametrization accounting for wind–wave alignment in a coupled atmosphere–wave model","interactions":[],"lastModifiedDate":"2021-03-05T21:07:22.044536","indexId":"70216934","displayToPublicDate":"2020-11-21T12:54:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7443,"text":"Quarterly Journal of the Royal Meteorological Society","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of a roughness length parametrization accounting for wind–wave alignment in a coupled atmosphere–wave model","docAbstract":"The importance of wind energy as an alternative energy source has increased over the latest years with more focus on offshore winds. A good estimation of the offshore winds is thus of major importance for this industry. Up to now the effect of the wind–wave (mis)alignment has not yet been taken into account in coupled atmosphere–wave models to study the vertical wind profile and power production estimations of offshore wind farms. In this study the roughness length parametrization of Drennan et al. in 2003, and its extension addressing the wind–wave (mis)alignment proposed by Porchetta et al. in 2019, are investigated in the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) model. This study shows that the yearly mean wind estimation at hub height (100 m) is improved by the roughness length parametrization of Porchetta et al. compared to Drennan. This is mainly due to the increased roughness of the former parametrization compare to the latter, even in aligned wind–wave conditions. This difference in roughness is caused by the dataset used to obtain the constants, deep‐water conditions versus mixed offshore conditions. Moreover, the roughness length parametrization of Porchetta et al. performs better in two of three alignment categories. Furthermore, similar model performances are obtained if we exclude the wind directions from the wind shadow zone of the measurement mast or the wind directions from the recently built Alpha Ventus wind farm, which is in close vicinity of the measurement mast. Investigating different wind conditions shows that the new roughness length parametrization of Porchetta et al. performs best for both offshore and onshore winds. Additionally, we show that the coupled model estimations of the vertical wind are only slightly affected by significant wave height estimations. Similar model performances for different accuracies of significant wave height estimations are presented. One exception is the perpendicular alignment category where the new roughness length of Porchetta et al. outperforms the roughness length of Drennan when investigating the wind estimations related to significant wave heights with a higher accuracy. The roughness length parametrization of Porchetta et al. reduced the power production overestimation of the coupled model from 5.7 to 2.8%. We also show that the standalone atmospheric model including the roughness length of Charnock in 1955 has a degraded performance compared to the coupled model including the roughness length parametrization of Porchetta et al. for yearly average wind profiles.
","language":"English","publisher":"Royal Meteorological Society","doi":"10.1002/qj.3948","usgsCitation":"Porchetta, S., Temel, O., Warner, J., Munoz-Esparza, J., Monbaliu, J., van Beeck, J., and van Lipzig, N., 2021, Evaluation of a roughness length parametrization accounting for wind–wave alignment in a coupled atmosphere–wave model: Quarterly Journal of the Royal Meteorological Society, v. 147, no. 735, p. 825-846, https://doi.org/10.1002/qj.3948.","productDescription":"22 p.","startPage":"825","endPage":"846","ipdsId":"IP-117950","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454221,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lirias.kuleuven.be/bitstream/123456789/685815/2/COAWST_QJRMetS_rkul.docx","text":"External Repository"},{"id":381447,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"147","issue":"735","noUsgsAuthors":false,"publicationDate":"2020-12-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Porchetta, Sara","contributorId":245775,"corporation":false,"usgs":false,"family":"Porchetta","given":"Sara","email":"","affiliations":[{"id":49315,"text":"KU Leuven, Department Earth and Environmental Sciences, Leuven, Belgium","active":true,"usgs":false}],"preferred":false,"id":807016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Temel, O.","contributorId":245776,"corporation":false,"usgs":false,"family":"Temel","given":"O.","email":"","affiliations":[{"id":49316,"text":"Royal Observatory of Belgium, Brussels, Belgium","active":true,"usgs":false}],"preferred":false,"id":807017,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":807018,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Munoz-Esparza, J.C.","contributorId":245777,"corporation":false,"usgs":false,"family":"Munoz-Esparza","given":"J.C.","email":"","affiliations":[{"id":16785,"text":"National Center for Atmospheric Research, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":807019,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Monbaliu, J","contributorId":245778,"corporation":false,"usgs":false,"family":"Monbaliu","given":"J","email":"","affiliations":[{"id":49317,"text":"KULeuven, Department of Civil Engineering, Leuven, Belgium","active":true,"usgs":false}],"preferred":false,"id":807020,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"van Beeck, J.","contributorId":245779,"corporation":false,"usgs":false,"family":"van Beeck","given":"J.","email":"","affiliations":[{"id":49319,"text":"KULeuven, Department Earth and Environmental Sciences, Leuven, Belgium","active":true,"usgs":false}],"preferred":false,"id":807021,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"van Lipzig, N.","contributorId":245780,"corporation":false,"usgs":false,"family":"van Lipzig","given":"N.","email":"","affiliations":[{"id":49321,"text":"von Karman Institute for Fluid Dynamics, Sint-Genesius-Rode, Belgium","active":true,"usgs":false}],"preferred":false,"id":807022,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70225590,"text":"70225590 - 2021 - Increasing comparability among coral bleaching experiments","interactions":[],"lastModifiedDate":"2021-10-26T14:31:59.549345","indexId":"70225590","displayToPublicDate":"2020-11-21T09:22:46","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":"Increasing comparability among coral bleaching experiments","docAbstract":"Coral bleaching is the single largest global threat to coral reefs worldwide. Integrating the diverse body of work on coral bleaching is critical to understanding and combating this global problem. Yet investigating the drivers, patterns, and processes of coral bleaching poses a major challenge. A recent review of published experiments revealed a wide range of experimental variables used across studies. Such a wide range of approaches enhances discovery, but without full transparency in the experimental and analytical methods used, can also make comparisons among studies challenging. To increase comparability but not stifle innovation, we propose a common framework for coral bleaching experiments that includes consideration of coral provenance, experimental conditions, and husbandry. For example, reporting the number of genets used, collection site conditions, the experimental temperature offset(s) from the maximum monthly mean (MMM) of the collection site, experimental light conditions, flow, and the feeding regime will greatly facilitate comparability across studies. Similarly, quantifying common response variables of endosymbiont (Symbiodiniaceae) and holobiont phenotypes (i.e., color, chlorophyll, endosymbiont cell density, mortality, and skeletal growth) could further facilitate cross-study comparisons. While no single bleaching experiment can provide the data necessary to determine global coral responses of all corals to current and future ocean warming, linking studies through a common framework as outlined here, would help increase comparability among experiments, facilitate synthetic insights into the causes and underlying mechanisms of coral bleaching, and reveal unique bleaching responses among genets, species, and regions. Such a collaborative framework that fosters transparency in methods used would strengthen comparisons among studies that can help inform coral reef management and facilitate conservation strategies to mitigate coral bleaching worldwide.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2262","usgsCitation":"Grottoli, A., Toonen, R.J., van Woesik, R., Vega Thurber, R., Warner, M.E., McLachlan, R.H., Price, J., Bahr, K.D., Baums, I., Castillo, K., Coffroth, M.A., Cunning, R., Dobson, K., Donahue, M., Hench, J.L., Iglesias-Prieto, R., Kemp, D.W., Kenkel, C.D., Kline, D.I., Kuffner, I.B., Matthews, J., Mayfield, A., Padilla-Gamino, J., Palumbi, S.R., Voolstra, C., Weis, V.M., and Wu, H.C., 2021, Increasing comparability among coral bleaching experiments: Ecological Applications, v. 31, no. 4, e02262, 17 p., https://doi.org/10.1002/eap.2262.","productDescription":"e02262, 17 p.","ipdsId":"IP-114969","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454223,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2262","text":"Publisher Index Page"},{"id":390962,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-05-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Grottoli, Andrea G.","contributorId":267953,"corporation":false,"usgs":false,"family":"Grottoli","given":"Andrea G.","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":825698,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Toonen, R. 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