This study focuses on characterizing the contributions of key terrestrial pathways that deliver dissolved organic carbon (DOC) to streams during hydrological events and on elucidating factors governing variation in water and DOC fluxes from these pathways. We made high-frequency measurements of discharge, specific conductance (SC), and fluorescent dissolved organic matter (FDOM) during 221 events recorded over 2 years within four Vermont (USA) watersheds that range in area from 0.4 to 139 km2. Using the SC measurements, together with statistical information on discharge, we separated the event hydrographs into contributions from three terrestrial pathways, which we refer to as riparian quickflow, subsurface quickflow, and slow-flow groundwater. The pathway discharges were used as input to a mixing model that closely approximated sub-hourly streamwater DOC concentrations as measured with the FDOM sensors. Subsurface quickflow, comprised of pre-event water, was the leading contributor to streamwater DOC fluxes, while riparian quickflow, comprised of event water, was the second-leading contributor to streamwater DOC fluxes, despite comprising the smallest proportion of streamflow yield among the three end-member pathways. Fixed-effects regression analysis revealed that the relationship between DOC fluxes from the end-member pathways and event magnitude was consistent across the four watersheds. This analysis also showed that DOC fluxes from the quickflow pathways increased significantly with temperature and varied inversely, but weakly, with catchment antecedent wetness. We believe that our approach, which leverages in-stream sensors that enable high-frequency measurements over extended periods, may be applicable for evaluating controls on DOC export from other watersheds within and beyond our study region.
Carbon dioxide emissions from active subaerial volcanoes represent 20–50% of the annual global volcanic CO2 flux (Barry et al., 2014). Passive degassing of carbon from the flanks of volcanoes, and the associated accumulation of dissolved inorganic carbon (DIC) within nearby groundwater, also represents a potentially important, yet poorly constrained flux of carbon to the surface (Werner et al., 2019). Here we investigate sources and sinks of DIC in groundwaters in the Lassen Peak region of California. Specifically, we report and interpret the relative abundance and isotopic composition of helium (3He, 4He) and carbon (12C, 13C, 14C) in 37 groundwater samples, from 24 distinct wells, collected between 20 and 60 km from Lassen Peak. Measured groundwater samples have air-corrected 3He/4He values between 0.19 and 7.44 RA (where RA = air 3He/4He = 1.39 × 10−6), all in excess of the radiogenic production value (~0.05 RA), indicating pervasive mantle-derived helium additions to the groundwater system in the Lassen Peak region. Stable carbon isotope ratios of DIC (δ13C) vary between −12.6 and − 27.7‰ (vs. VPDB). Measured groundwater DIC/3He values fall in the range of 2.2 × 1010 to 1.1 × 1012. Using helium and carbon isotope data, we explore several conceptual models to estimate surface carbon contributions and to differentiate between DIC derived from soil CO2 versus DIC derived from external (slab and mantle) carbon sources. Specifically, if we use 14C to identify soil-derived DIC (assuming decadal-to-centennial groundwater ages and a soil CO2 14C activity equal to that of the atmosphere), we calculate that a hypothetical external carbon source would have an apparent δ13C signature between −10.3 and − 59.3‰ (vs. Vienna Pee Dee Belemnite (VPDB)) and an apparent C/3He between 7.0 × 109 and 1.0 × 1012. These apparent δ13C and C/3He values are substantially isotopically lighter than and greater than canonical MORB values, respectively. We suggest that >95% of any external (non-soil-derived) DIC in groundwater must thus be non-mantle in origin (i.e., slab derived or assimilated organic carbon). We further investigate possible sources of external DIC to groundwater using two idealized conceptual approaches: a pure (unfractionated) source mixing model (after Sano and Marty, 1995) and a scenario that invokes fractionation due to calcite precipitation. Because the former model requires carbon contributions from an organic source component with unrealistically low δ13C (~ − 60‰), we suggest that the second scenario is more plausible. Importantly, however, we caution that all conceptual models are dependent on assumptions about initial 14C activity. Thus, we cannot rule out the possibility that the true fraction of non-surface-derived DIC in these samples is lower or negligible, despite the pervasive mantle-derived He isotope signatures throughout the region. Following the 14C approach to deconvolving sources of DIC, we determine that the maximum passive carbon flux could be up to ~2.2 × 106 kg/yr, which is lower than previous magmatic carbon flux estimates from the Lassen region (Rose and Davisson, 1996). We find that the passive dissolved carbon flux could represent a maximum of ~4–18% of the total Lassen geothermal CO2 degassing flux (estimated to be ~3.5 × 107 kg/yr Rose and Davisson, 1996; Gerlach et al., 2008), which is still more than an order of magnitude smaller than soil gas CO2 flux estimates (7.3–11 × 107 kg/yr) for nearby volcanoes (Sorey et al., 1998; Gerlach et al., 1999; Evans et al., 2002; Werner et al., 2014). We conclude that passive dissolved carbon fluxes should be combined with geothermal fluxes and soil gas fluxes to obtain a complete picture of volcanic carbon emissions globally. Our approach highlights the utility of measuring helium isotopes in concert with the full suite of noble gas abundances, tritium, δ13C and 14C, which when interpreted together can be used to better elucidate the various sources of DIC in groundwater.
Information about past ecosystem dynamics and human activities is stored in the ice of Colle Gnifetti glacier in the Swiss Alps. Adverse climatic intervals incurred crop failures and famines and triggered reestablishment of forest vegetation but also societal resilience through innovation. Historical documents and lake sediments record these changes at local—regional scales but often struggle to comprehensively document continental-scale impacts on ecosystems. Here, we provide unique multiproxy evidence of broad-scale ecosystem, land use, and climate dynamics over the past millennium from a Colle Gnifetti microfossil and oxygen isotope record. Microfossil data indicate that before 1750 CE forests and fallow land rapidly replaced crop cultivation during historically documented societal crises caused by climate shifts and epidemics. Subsequently, with technology and the introduction of more resilient crops, European societies adapted to the Little Ice Age cold period, but resource overexploitation and industrialization led to new regional to global-scale environmental challenges.
For the past ∼12 years the Pacific Northwest Seismic Network has been automatically detecting and locating tectonic tremor across the Cascadia subduction zone, resulting in a catalog of more than 500,000 tremor epicenters to date, which has served as a valuable resource for tremor and slip research. This manuscript presents an updated methodology for routine tremor detection in Cascadia and a new catalog of over 180,000 tremor epicenters including amplitudes detected along the subduction zone margin from 2017 to 2021. The events are detected via cross-correlation of continuous vertical envelope data of 128 stations from northern California to northern Vancouver Island. The modified approach results in less scatter and a 55% increase in detected epicenters than previously observed, as well as a newly identified tremor source offset updip from the main tremor and slip region at the southern edge of the subduction zone. Radiated seismic energy in the 1.5–5 Hz band is used to assign epicenters an energy magnitude (MeL), which is calibrated to the ML of local earthquakes. Southern Cascadia is most active, but the highest tremor energy rates occur in northern Cascadia. Tremor in central Cascadia is systematically weaker and less frequent. Individual epicenter magnitudes range from ∼0.5–2 and spatiotemporally cluster into 1,060 swarms with cumulative MeL ranging from ∼0.8 to 3.7. The swarms reflect underlying slow slip events and occur with an earthquake-like energy distribution with a b value ∼1. Tremor epicenters, however, follow a tapered Gutenberg-Richter distribution with high b values, suggesting individual tremor bursts and their constituent low-frequency earthquakes are fault-dimension limited.
Red Knots (Calidris canutus rufa) stop at Delaware Bay during northward migration to feed on eggs of horseshoe crabs (Limulus polyphemus). The northward migration of C. c. rufa coincides with the spawning of horseshoe crabs whose eggs are the perfect food for a migrating Red Knot (Karpanty et al. 2006, Haramis et al. 2007). Horseshoe crabs are therefore an important food resource for Red Knots as well as other shorebirds at Delaware Bay.
Horseshoe crabs have been harvested since at least 1990 for use as bait in American eel (Anguilla rostrata) and whelk (Busycon) fisheries (Kreamer and Michels 2009). In the late 1990s and early 2000s the number of Red Knots found at Delaware Bay declined dramatically from ~50,000 to ~13,000 (Niles et al. 2008). At the same time the number of horseshoe crabs harvested also declined and avian conservation biologists hypothesized that unregulated harvest of horseshoe crabs from Delaware Bay in the 1990s prevented sufficient refueling during stopover for successful migration to the breeding grounds, nesting, and survival for the remainder of the annual cycle (McGowan et al. 2011).
The harvest of horseshoe crabs in the Delaware Bay region has been managed by the Atlantic States Marine Fisheries Commission (ASMFC) since 2012 using an Adaptive Resource Management (ARM) framework (McGowan et al. 2015b). The ARM framework was designed to constrain the harvest so that number of spawning crabs would not limit the number of Red Knots stopping at Delaware Bay during migration. This management framework to achieve multiple objectives requires an estimate each year of both the crab population and the Red Knot stopover population size to inform harvest recommendations (McGowan et al. 2015a). We have estimated the stopover population size using mark-resight data on individually-marked birds and a Jolly-Seber model for open populations since 2011.
","language":"English","publisher":"Atlantic States Marine Fisheries Commission","usgsCitation":"Lyons, J.E., 2021, Red knot stopover population size and migration ecology at Delaware Bay, USA, 2021, 21 p.","productDescription":"21 p.","ipdsId":"IP-135416","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":427147,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":398095,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://dnrec.delaware.gov/fish-wildlife/conservation/shorebirds/research/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Delaware, New Jersey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.09403509407363,\n 38.74026331013363\n ],\n [\n -74.92922524720622,\n 38.95518554423097\n ],\n [\n -74.86023507875021,\n 39.17242937484494\n ],\n [\n -75.47348102058082,\n 39.53695640590777\n ],\n [\n -75.45818237996806,\n 39.725833415896574\n ],\n [\n -75.62300710583959,\n 39.7375634879601\n ],\n [\n -75.68813576821344,\n 39.5812414619472\n ],\n [\n -75.61529784001694,\n 39.40677166373757\n ],\n [\n -75.46198775359684,\n 39.16648631014266\n ],\n [\n -75.34700185696957,\n 38.90151720709986\n ],\n [\n -75.09403509407363,\n 38.74026331013363\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":222844,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":839581,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70224547,"text":"70224547 - 2021 - SiteOpt: An open-source R-package for site selection and portfolio optimization","interactions":[],"lastModifiedDate":"2021-11-16T15:45:42.56053","indexId":"70224547","displayToPublicDate":"2021-09-22T08:35:08","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1445,"text":"Ecography","active":true,"publicationSubtype":{"id":10}},"title":"SiteOpt: An open-source R-package for site selection and portfolio optimization","docAbstract":"Conservation planning involves identifying and selecting actions to best achieve objectives for managing natural, social and cultural resources. Conservation problems are often high dimensional when specified as combinatorial or portfolio problems and when multiple competing objectives are considered at varying spatial and temporal scales. Although analytical techniques such as modern portfolio theory (MPT) have been developed to address these complex problems, open source computational platforms for executing these approaches are not readily available. We present a user-friendly R-package called SiteOpt for optimization of binary decisions while explicitly considering environmental or economic uncertainty and the risk tolerance of decision makers. We illustrate the package with spatially-explicit site selection problems (i.e. spatial conservation planning), including an option for divestment (i.e. selling assets), when accounting for future uncertainties in designing conservation areas. The tool is applicable to both spatial and non-spatial problems, such as budget allocation or species selection. Constraints for spatial design and spatial dependencies (e.g. connectivity among sites) can also be specified in SiteOpt. Users can optimize site selection based on two competing objectives by solving for the Nash bargaining solution. Importantly, by quantifying uncertainty and asset spatial correlation, a measure of risk can be included as one such objective to be traded off against portfolio benefits. Thus, SiteOpt can be used to explicitly manage risk in portfolio-based spatial optimization. This tool facilitates decisions in a variety of problem settings, including reserve selection, invasive species management, allocation of law enforcement activities for conservation, budget allocation and asset selection under uncertainty and risk.
","language":"English","publisher":"Wiley","doi":"10.1111/ecog.05717","usgsCitation":"Saghand, P.G., Haider, Z., Charkhgard, H., Eaton, M.J., Martin, J., Yurek, S., and Udell, B.J., 2021, SiteOpt: An open-source R-package for site selection and portfolio optimization: Ecography, v. 44, no. 11, p. 1678-1685, https://doi.org/10.1111/ecog.05717.","productDescription":"8 p.","startPage":"1678","endPage":"1685","ipdsId":"IP-119211","costCenters":[{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":450726,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ecog.05717","text":"Publisher Index Page"},{"id":436191,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9S4QV7T","text":"USGS data release","linkHelpText":"Data from SiteOpt: an Open-source R-package for Site Selection and Portfolio Optimization"},{"id":389806,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"11","noUsgsAuthors":false,"publicationDate":"2021-09-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Saghand, Payman G","contributorId":266005,"corporation":false,"usgs":false,"family":"Saghand","given":"Payman","email":"","middleInitial":"G","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":824023,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haider, Zulqarnain","contributorId":216714,"corporation":false,"usgs":false,"family":"Haider","given":"Zulqarnain","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":824024,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Charkhgard, Hadi","contributorId":216710,"corporation":false,"usgs":false,"family":"Charkhgard","given":"Hadi","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":824025,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eaton, Mitchell J. 0000-0001-7324-6333","orcid":"https://orcid.org/0000-0001-7324-6333","contributorId":213526,"corporation":false,"usgs":true,"family":"Eaton","given":"Mitchell","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":824026,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Martin, Julien 0000-0002-7375-129X","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":218445,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":824027,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yurek, Simeon 0000-0002-6209-7915","orcid":"https://orcid.org/0000-0002-6209-7915","contributorId":216738,"corporation":false,"usgs":true,"family":"Yurek","given":"Simeon","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":824028,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Udell, Bradley J. 0000-0001-5225-4959","orcid":"https://orcid.org/0000-0001-5225-4959","contributorId":223440,"corporation":false,"usgs":false,"family":"Udell","given":"Bradley","email":"","middleInitial":"J.","affiliations":[{"id":40715,"text":"Wildlife Ecology and Conservation Department, University of Florida, Gainesville, FL","active":true,"usgs":false}],"preferred":false,"id":824029,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70226497,"text":"70226497 - 2021 - Frequency distribution","interactions":[],"lastModifiedDate":"2021-11-22T14:23:44.401647","indexId":"70226497","displayToPublicDate":"2021-09-22T08:20:57","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Frequency distribution","docAbstract":"Given a numerical dataset, a frequency distribution is a summary displaying fluctuations of an attribute within the range of values. In contrast to an analytical probability distribution, a frequency distribution always deals with empirically observed values (Everitt and Skondall 2010). In general, the larger the number of values, the more useful is the frequency distribution relative to listing all values. Today, multiple software packages allow easy display of a frequency distribution.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of mathematical geosciences","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","doi":"10.1007/978-3-030-26050-7","usgsCitation":"Olea, R., 2021, Frequency distribution, chap. of Encyclopedia of mathematical geosciences, HTML Document, https://doi.org/10.1007/978-3-030-26050-7.","productDescription":"HTML Document","ipdsId":"IP-122768","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":498722,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://pure.qub.ac.uk/en/publications/fce9c7cb-69b5-4b16-9f9a-f81c0c89e272","text":"External Repository"},{"id":391979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":224285,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":827107,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70224321,"text":"70224321 - 2021 - Drought resistance and resilience: The role of soil moisture–plant interactions and legacies in a dryland ecosystem","interactions":[],"lastModifiedDate":"2021-09-22T12:22:40.018062","indexId":"70224321","displayToPublicDate":"2021-09-22T07:18:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Drought resistance and resilience: The role of soil moisture–plant interactions and legacies in a dryland ecosystem","docAbstract":"Bee conservation is a topic of global concern, particularly in agroecosystems where their contribution to crop pollination is highly valued. Over a decade ago, bees and other pollinators were made a priority of the Conservation Reserve Program (CRP), a U.S. federal program that pays land owners to establish a conservation cover, typically grassland, on environmentally sensitive farmland. Despite large financial investment in this program, few studies have measured the benefit of CRP to bees, particularly in complex agroecosystems with abundant alternative forage. To determine if CRP land seeded with pollinator-attractive native flowers and/or introduced legumes provides distinct floral composition that attracts more foraging bees than non-CRP habitats, we compared CRP land to paired non-CRP fields and roadsides at 31 sites in Michigan, U.S.A.. We found CRP land had unique floral species community composition, higher floral abundance, greater species richness, more native floral species, and greater inflorescence coverage. Greater inflorescence coverage on CRP land was associated with a greater abundance of both honey bees and wild bees than either non-CRP fields or roadsides, as was native flower abundance for wild bees. Showy native plant species were important forage resources on CRP land: Monarda fistulosa was the most foraged upon species by both honey bees and wild bees, and goldenrod species were important late-summer forage resources for honey bees. These findings demonstrate the benefit of managing CRP land with herbaceous seed mixes to create dense, showy, native plant communities that provide summer-long resources to both bee groups. Insights from this study could be used to enhance the composition of future conservation program investments and management of non-CRP land to benefit pollinators.
Preferential sampling is a form of data collection that may significantly distort the histogram and the semivariogram of spatially correlated data. Typical situations are a higher sampling density at high-valued areas favorable for mining, and highly contaminated areas in need of environmental remediation. Multiple statistical procedures are devoted to obtaining representative statistics, whose magnitudes should be close to the respective population values. This paper proposes a resampling method that can compensate for preferential sampling of spatially correlated data without using declustering weights. The application of the method herein generates a dataset of median estimates of quantiles of multiple stratified resamples that is free of preferential sampling. The methodology is illustrated with two examples. The first one involves values actually measured in the field and has the advantage of representing a real scenario of spatial fluctuations and preferential sampling. A second dataset is synthetic and has the main benefit of a priori knowledge of the underlying spatial distribution, thus allowing a satisfactory evaluation of the results against the known baseline. Access to computer code is offered for practical application of the method.
The Smallmouth Bass (Micropterus dolomieu; SMB) is a widely distributed black bass species, but the southwestern edge of the species range within the Interior Highlands contains some of the most divergent ecotypes. The Neosho subspecies (M. d. velox) inhabits tributaries of the Arkansas River within the Ozark Mountains and a second lineage is reported from drainages of the Ouachita Mountains. We sought to develop a single nucleotide polymorphism (SNP) panel to (1) diagnose hybridization with sympatric Spotted Bass (Micropterus punctulatus; SPB) and non-native Northern SMB (M. d. dolomieu) stocked in the region, and (2) delineate population structure within the ranges of the Neosho and Ouachita SMB lineages. We obtained 76 individual SMB samples from across their range but concentrated within the Interior Highlands (n = 50). We also included 3 SPB to allow for hybrid detection and 3 Shoal Bass (Micropterus cataractae) as an outgroup. Phylogenetic trees constructed with the generated SNP data corroborated the existence of at least three major lineages of SMB (Northern, Neosho, and Ouachita), each containing varying degrees of differentiation among major drainages. Simulation analyses revealed that chosen SNPs had high power (> 0.9) to assign SMB × SPB hybrid categories and similarly high power (> 0.8) for Northern SMB × Interior Highlands SMB hybrids. Clustering methods delineated major inter-basin population structure within the native ranges of Neosho and Ouachita SMB with chosen SNPs. Anticipated uses of the resulting 192-loci SNP panel include conservation planning, fisheries management assessments, and ecological investigations of the Neosho and Ouachita SMB lineages.
","language":"English","publisher":"Springer Link","doi":"10.1007/s12686-020-01170-8","usgsCitation":"Long, J.M., Taylor, A.T., and Buonaccorsi, V., 2021, A conservation-oriented SNP panel for Smallmouth Bass (Micropterus dolomieu), with emphasis on Interior Highlands lineages: Conservation Genetics Resources, v. 13, p. 47-59, https://doi.org/10.1007/s12686-020-01170-8.","productDescription":"13 p.","startPage":"47","endPage":"59","ipdsId":"IP-115509","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395780,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Missouri, Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.8447265625,\n 33.358061612778876\n ],\n [\n -91.0986328125,\n 33.358061612778876\n ],\n [\n -91.0986328125,\n 37.405073750176925\n ],\n [\n -95.8447265625,\n 37.405073750176925\n ],\n [\n -95.8447265625,\n 33.358061612778876\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2020-09-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834205,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, A. T.","contributorId":275351,"corporation":false,"usgs":false,"family":"Taylor","given":"A.","email":"","middleInitial":"T.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":834206,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buonaccorsi, V.","contributorId":275670,"corporation":false,"usgs":false,"family":"Buonaccorsi","given":"V.","email":"","affiliations":[{"id":56875,"text":"The Center for Aquaculture Technologies","active":true,"usgs":false}],"preferred":false,"id":834207,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70263065,"text":"70263065 - 2021 - Scale growth rates and scale circulus deposition rates of marine-stage Atlantic salmon Salmo salar raised under semi-natural conditions","interactions":[],"lastModifiedDate":"2025-01-29T16:33:18.150509","indexId":"70263065","displayToPublicDate":"2021-09-21T10:25:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":20060,"text":"Journal of Northwest Atlantic Fishery Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Scale growth rates and scale circulus deposition rates of marine-stage Atlantic salmon Salmo salar raised under semi-natural conditions","title":"Scale growth rates and scale circulus deposition rates of marine-stage Atlantic salmon Salmo salar raised under semi-natural conditions","docAbstract":"Scale circuli yield valuable information about the life history, age, and growth of a fish. However, because circuli formation is influenced by somatic growth, the rate at which circuli are formed and the factors influencing these rates must be taken into account for the given life stage of the study species. Scales were collected from Atlantic salmon raised in marine net pens off of the coast of Maine in order to characterize the formation of scale circuli and the growth of scales during the ocean phase, and to relate circulus deposition and scale growth rate to water temperature. Fish were sampled 13 times over a period of 25 months. Neither circulus deposition rate nor growth rate were constant through time and the same trend held when circulus deposition and growth were related to thermal experience. Both rates decreased over the course of the study, presumably related to the fish reaching sexual maturity. The results of this study indicate that the pattern of circulus deposition and scale growth of Atlantic salmon vary greatly during the early marine phase, and this dynamic should be taken into account when assessing growth, especially over short time periods.
","language":"English","publisher":"Northwest Atlantic Fisheries Organization","doi":"10.2960/J.v52.m733","usgsCitation":"Peterson, E., Sheehan, T., and Zydlewski, J.D., 2021, Scale growth rates and scale circulus deposition rates of marine-stage Atlantic salmon Salmo salar raised under semi-natural conditions: Journal of Northwest Atlantic Fishery Science, v. 52, p. 19-27, https://doi.org/10.2960/J.v52.m733.","productDescription":"9 p.","startPage":"19","endPage":"27","ipdsId":"IP-110206","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":489762,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2960/j.v52.m733","text":"Publisher Index Page"},{"id":481464,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","state":"Newfoundland","otherGeospatial":"Placentia Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -53.5,\n 47.5\n ],\n [\n -54.5,\n 47.5\n ],\n [\n -54.5,\n 46.667\n ],\n [\n -53.5,\n 46.667\n ],\n [\n -53.5,\n 47.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"52","noUsgsAuthors":false,"publicationDate":"2021-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Peterson, Erin","contributorId":287522,"corporation":false,"usgs":false,"family":"Peterson","given":"Erin","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":925429,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sheehan, Timothy F.","contributorId":272581,"corporation":false,"usgs":false,"family":"Sheehan","given":"Timothy F.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":925430,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":925428,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227095,"text":"70227095 - 2021 - White-nose Syndrome and environmental correlates to landscape-scale bat presence","interactions":[],"lastModifiedDate":"2021-12-29T14:40:46.904017","indexId":"70227095","displayToPublicDate":"2021-09-21T08:35:06","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"White-nose Syndrome and environmental correlates to landscape-scale bat presence","docAbstract":"Over the past 13 years, White-nose Syndrome (WNS) has caused North American bat population declines and shifted community structure towards species less or unaffected by the disease. Mist-netting, acoustic surveys, and cave count data have been used to document changes in bat presence and activity through site-specific, pre- and post-WNS studies. Management and survey guidance often must be applied at a combined landscape and site-specific scale. Our objective was to explore the relationships among WNS impact, influence of available hibernacula, and environmental factors for the nightly presence of 3 WNS-affected bats: the Indiana bat (Myotis sodalis), northern long-eared bat (M. septentrionalis), and big brown bat (Eptesicus fuscus). We used recordings from 10 acoustic monitoring study areas, each with 3 survey locations across the states of Virginia, West Virginia, Ohio and Kentucky to assess changes in nightly bat presence during the summer of 2017. There were significant positive and negative correlates of broad land-cover categories for presence of all 3 bat species. Our findings also corroborated trends in abundance and distribution patterns found in prior, smaller-scale studies, supporting the relevance of land cover categories in a large-scale acoustic monitoring framework. We observed a negative association between WNS impact-years and nightly northern long-eared bat presence, but low occurrence and patchy distribution reduced our ability to infer strong relationships. Big brown bat presence showed a significant positive relationship with WNS occurrence on the landscape, providing evidence that big brown bats are maintaining populations after years of exposure. Indiana bats were the least-documented species, limiting the strength of our conclusions, but we did observe significant temporal patterns in nightly presence, with higher probabilities of presence earlier in the summer. Our results show the potential efficacy of using a WNS impact metric to predict summer bat presence, inform current U.S. Fish and Wildlife Service acoustic monitoring guidelines, and highlight which environmental variables are relevant for large-scale acoustic monitoring.
Identifying migration routes and fall stopover sites of Cinnamon Teal (Spatula cyanoptera septentrionalium) can provide a spatial guide to management and conservation efforts, and address vulnerabilities in wetland networks that support migratory waterbirds. Using high spatiotemporal resolution GPS-GSM transmitters, we analyzed 61 fall migration tracks across western North America during our three-year study (2017–2019). We marked Cinnamon Teal primarily during spring/summer in important breeding and molting regions across seven states (California, Oregon, Washington, Idaho, Utah, Colorado, and Nevada). We assessed fall migration routes and timing, detected 186 fall stopover sites, and identified specific North American ecoregions where sites were located. We classified underlying land cover for each stopover site and measured habitat selection for 12 land cover types within each ecoregion. Cinnamon Teal selected a variety of flooded habitats including natural, riparian, tidal, and managed wetlands; wet agriculture (including irrigation ditches, flooded fields, and stock ponds); wastewater sites; and golf and urban ponds. Wet agriculture was the most used habitat type (29.8% of stopover locations), and over 72% of stopover locations were on private land. Relatively scarce habitats such as wastewater ponds, tidal marsh, and golf and urban ponds were highly selected in specific ecoregions. In contrast, dry non-habitat across all ecoregions, and dry agriculture in the Cold Deserts and Mediterranean California ecoregions, was consistently avoided. Resources used by Cinnamon Teal often reflected wetland availability across the west and emphasize their adaptability to dynamic resource conditions in arid landscapes. Our results provide much needed information on spatial and temporal resource use by Cinnamon Teal during migration and indicate important wetland habitats for migrating waterfowl in the western United States.
The Paleocene-Eocene Thermal Maximum (PETM), the most well-studied transient hyperthermal event in Earth history, is characterized by prominent and dynamic changes in global marine ecosystems. Understanding such biotic responses provides valuable insights into future scenarios in the face of anthropogenic warming. However, evidence of the PETM biotic responses is largely biased towards deep-sea records, whereas shallow-marine evidence remains scarce and elusive. Here we investigate a shallow-marine microfaunal record from Maryland, eastern United States, to comprehensively document the shallow-marine biotic response to the PETM. We applied birth-death modeling to estimate the local diversity dynamics, combined with evaluation of time-variable preservation artifacts. We discovered strong increase of species disappearance and appearance predating the onset and at the final recovery phase of the PETM, respectively. Our paleoecological analyses indicate that bathymetric habitat compression due to extreme warmth and oxygen minimum zone expansion caused shallow-marine benthic species extirpation and ecosystem perturbation during the PETM; and that rapid recovery and diversification followed the PETM disaster, thus contributing new understanding to the shallow-marine biotic changes in a broad context of global warming.
Surface effects of sea-level rise (SLR) in permafrost regions are obvious where increasingly iceless seas erode and inundate coastlines. SLR also drives saltwater intrusion, but subsurface impacts on permafrost-bound coastlines are unseen and unclear due to limited field data and the absence of models that include salinity-dependent groundwater flow with solute exclusion and freeze-thaw dynamics. Here, we develop a numerical model with the aforementioned processes to investigate climate change impacts on coastal permafrost. We find that SLR drives lateral permafrost thaw due to depressed freezing temperatures from saltwater intrusion, whereas warming drives top-down thaw. Under high SLR and low warming scenarios, thaw driven by SLR exceeds warming-driven thaw when normalized to the influenced surface area. Results highlight an overlooked feedback mechanism between SLR and permafrost thaw with potential implications for coastal infrastructure, ocean-aquifer interactions, and carbon mobilization.
Storm-driven nutrient loading from tributaries can fuel eutrophication in nearshore and open water areas of lentic ecosystems. However, nutrient processing in river-to-lake transitional zones can substantially alter the amount and composition of nutrients transported to lakes from upstream surface waters. We measured the removal of nutrients and dissolved organic carbon (DOC) from the water column in the Fox rivermouth (Green Bay, Lake Michigan) to evaluate the response of rivermouth plankton to episodic nutrient enrichment. Light and dark water column incubations (8–12 hr) were conducted on four occasions from April through September to measure changes in dissolved nitrogen (N), phosphorus (P), and DOC concentrations in three locations along the Fox rivermouth. Two incubation experiments were conducted on consecutive days, (a) under ambient nutrient concentrations, and (b) under experimentally enriched N and P concentrations. Spatial and temporal variation was observed in nutrient uptake rates, but light incubations consistently had higher nutrient uptake rates than dark incubations. Nutrient enrichment increased total dissolved P and total dissolved N uptake and DOC release in light incubations, but only increased total dissolved P uptake in dark incubations. Moreover, nutrient uptake ratios (N:P) decreased from ambient to nutrient enriched conditions and indicated preferential P uptake by phytoplankton communities in light conditions. Our study substantiates that rivermouths can process nutrients bound for downstream ecosystems and demonstrates the potential of plankton communities to dynamically increase net uptake rates in response to episodic nutrient enrichment.
The ShBOQ-1 geochemical reference material is relevant to studies of the organic geochemistry and mineralogy of petroleum source rocks containing high concentrations of carbonate minerals and organic sulfur-rich, oil-prone marine organic matter. ShBOQ-1 is geochemically and mineralogically similar to the lower part of the Upper Cretaceous Eagle Ford Shale.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213048","usgsCitation":"Birdwell, J.E., and Wilson, S.A., 2021, Geochemical and mineralogical properties of Boquillas Shale geochemical reference material ShBOQ-1:U.S. Geological Survey Fact Sheet 2021–3048, 4 p., https://doi.org/10.3133/fs20213048.","productDescription":"Report: 4 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-123902","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":389380,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2021/3048/coverthb.jpg"},{"id":389381,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2021/3048/fs20213048.pdf","text":"Report","size":"1.53 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2021-3048"},{"id":389382,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D6D1KG","text":"USGS data release","linkHelpText":"Results from geochemical and mineralogical characterization of Boquillas Shale geochemical reference material ShBOQ-1"}],"contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Avian populations must mount effective immune responses upon exposure to environmental stressors such as avian influenza and xenobiotics. Although multiple immune assays have been tested and applied to various avian species, antibody-mediated immune responses in non-model avian species are not commonly reported due to the lack of commercially available species-specific antibodies. The objectives of the present study were to advance methods for studying wild bird immune responses and to apply these to the evaluation of cytological responses after exposure of American kestrels, Falco sparverius, to a commercial flame retardant mixture containing isopropylated triarylphosphate isomers (ITP). Hatchlings were gavaged daily with safflower oil or 1.5 ug/g bw/day of ITP suspended in safflower oil, then bled on days 9, 17, and 21. The ITP treatment group (n = 18) and a subset of controls (Poly I:C treatment group; n = 10) were injected on days 9 and 15 with a synthetic analog of viral double-stranded RNA, polyinosinic:polycytidylic acid (Poly I:C), a toll-like receptor ligand and synthetic viral mimic, and responses compared to a sham injected control group (n = 8). The hypotheses tested whether kestrels showed immunological differences among treatment groups, genetic sex, and/or white blood cell (WBC) subpopulation type over time. A flow cytometry (FCM) gating strategy categorized heterophils (H), lymphocytes (L), and monocytes (M) and their proportions, and measured relative fluorescence in response to anti-chicken CD4 binding. Fluorescent cell surfaces and some granular/vacuolar inclusions were visualized by epifluorescence microscopy. A fourth subpopulation with higher levels of granularity than M but less than H became increasingly apparent with time and was gated along with the H subpopulation; its frequency of occurrence was lowest in the ITP group (P = 0.0023). The percentages of cells differed among treatment groups, days, and sexes (P = 0.0001). For both sexes, percentages of H and L were higher than M in control and Poly I:C. In the ITP group, L percentages were higher than H and M (P = 0.0457), and H and L were higher than M on days 9 and 21 (P = 0.0001). The ratios of H:L and H:WBC, indicators of robust immunity, were also higher on days 9 and 21 than on 17 (P = 0.0079). For each sex, the highest levels of activity measured by FCM geometric means (GEO) of fluorescence (indicative of antibody binding) were observed on day 9 (P = 0.0001 female, and P = 0.0011 male) in H over both L and M (P < 0.0001 for each). In males, GEO of the Poly I:C group was higher than that of the ITP group (P = 0.0374), with no difference observed among females over all days. By using a FCM algorithm for population comparisons of fluorescence to investigate binding within H, the T(x) scores indicated higher fluorescence in control and Poly I:C groups over ITP (P = 0.0001). Unlike chickens, Gallus gallus, which express CD4 primarily on L, kestrels bound the commercial antibody primarily within the gated H subpopulation, suggesting an immunophenotypic difference between taxa, despite a ~60% identity of Falco CD4 amino acid sequences with chicken CD4. The emergent cell subset within the gated H presented dendritic-like cell (DLC) morphological and functional properties, apparently serving as an effector cell. This study adds interpretive context to ecological investigations of infection and of potential immunomodulation by emerging compounds, whereby the early innate responses are mediated by the various cell subsets serving as useful quantitative markers of immunological condition. Data showed that dietary exposure to ITP was immunosuppressive for male and female kestrels over the course of the experiment, reducing DLC frequency compared to the Poly I:C controls. Heterophils and DLC were important in facilitating innate immunological responses.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envint.2021.106779","usgsCitation":"Jenkins, J., Baudoin, B.A., Johnson, D., Fernie, K.J., Stapelton, H.M., and Karouna-Renier, N., 2021, Establishment of baseline cytology metrics in nestling American kestrels (Falco sparverius): Immunomodulatory effects of the flame retardant isopropylated triarylphosphate isomers: Environment International, v. 157, 106779, 15 p.; Data Release, https://doi.org/10.1016/j.envint.2021.106779.","productDescription":"106779, 15 p.; Data Release","ipdsId":"IP-116785","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":450748,"rank":4,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envint.2021.106779","text":"Publisher Index Page"},{"id":436196,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P7ZTMU","text":"USGS data release","linkHelpText":"Laboratory analysis assessing immune response after flame retardant exposure in American kestrels, Falco sparverius, through 21 days post-hatch"},{"id":436195,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SGX37F","text":"USGS data release","linkHelpText":"Discerning innate immunity in American kestrels, Falco sparverius, through 21 days post-hatch"},{"id":390889,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417862,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/p9sgx37f"}],"volume":"157","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jenkins, Jill 0000-0002-5087-0894","orcid":"https://orcid.org/0000-0002-5087-0894","contributorId":206575,"corporation":false,"usgs":true,"family":"Jenkins","given":"Jill","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":825642,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baudoin, Brooke A 0000-0003-2874-1604","orcid":"https://orcid.org/0000-0003-2874-1604","contributorId":267938,"corporation":false,"usgs":true,"family":"Baudoin","given":"Brooke","email":"","middleInitial":"A","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":825643,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Darren 0000-0002-0502-6045","orcid":"https://orcid.org/0000-0002-0502-6045","contributorId":203921,"corporation":false,"usgs":true,"family":"Johnson","given":"Darren","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":825644,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fernie, Kim J.","contributorId":211241,"corporation":false,"usgs":false,"family":"Fernie","given":"Kim","email":"","middleInitial":"J.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":825645,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stapelton, Heather M. 0000-0002-9995-6517","orcid":"https://orcid.org/0000-0002-9995-6517","contributorId":267940,"corporation":false,"usgs":false,"family":"Stapelton","given":"Heather","email":"","middleInitial":"M.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":825646,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Karouna-Renier, Natalie 0000-0001-7127-033X nkarouna@usgs.gov","orcid":"https://orcid.org/0000-0001-7127-033X","contributorId":200983,"corporation":false,"usgs":true,"family":"Karouna-Renier","given":"Natalie","email":"nkarouna@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":825647,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70224957,"text":"70224957 - 2021 - Integrating regional and local monitoring data and assessment tools to evaluate habitat conditions and inform river restoration","interactions":[],"lastModifiedDate":"2021-10-11T15:55:41.405172","indexId":"70224957","displayToPublicDate":"2021-09-20T10:49:47","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Integrating regional and local monitoring data and assessment tools to evaluate habitat conditions and inform river restoration","docAbstract":"RRestoring degraded rivers requires initial assessment of the fluvial landscape to identify stressors and riverine features that can be enhanced. We associated local-scale river habitat data collected using standardized national monitoring tools with modeled regional water temperature and flow data on mid-sized northwest U.S. rivers (30–60 m wide). We grouped these rivers according to quartiles of their modeled mean August water temperature and examined their physical habitat structure and flow. We then used principal components analysis to summarize the variation in several dimensions of physical habitat. We also compared local conditions in the Priest River, a river targeted for restoration of native salmonid habitat in northern Idaho, with those in other rivers of the region to infer potential drivers controlling water temperature. The warmest rivers had physical structure and fluvial characteristics typical of thermally degraded rivers, whereas the coldest rivers had higher mean summer flows and greater channel planform complexity. The Priest River sites had approximately twice as many deep residual pools (>50, >75, and >100 cm) and incision that averaged approximately twice that in the coldest rivers. Percentage fines and natural cover in the Priest were also more typical of the higher-temperature river groups. We found generally low instream cover and low levels of large wood both across the region and within the Priest River. Our approach enabled us to consider the local habitat conditions of a river in the context of other similarly sized rivers in the surrounding region. Understanding this context is important for identifying potential influences on river water temperature within the focal basin and for defining attainable goals for management and restoration of thermal and habitat conditions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2021.108213","usgsCitation":"Mejia, F.H., Connor, J.M., Kaufmann, P.R., Torgersen, C.E., Berntsen, E.K., and Andersen, T., 2021, Integrating regional and local monitoring data and assessment tools to evaluate habitat conditions and inform river restoration: Ecological Indicators, no. 131, 108213, 14 p., https://doi.org/10.1016/j.ecolind.2021.108213.","productDescription":"108213, 14 p.","ipdsId":"IP-119748","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":450752,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2021.108213","text":"Publisher Index Page"},{"id":390391,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Washington","otherGeospatial":"Priest River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.158203125,\n 48.191725575618726\n ],\n [\n -116.861572265625,\n 48.191725575618726\n ],\n [\n -116.861572265625,\n 48.49840764096433\n ],\n [\n -117.158203125,\n 48.49840764096433\n ],\n [\n -117.158203125,\n 48.191725575618726\n ]\n ]\n ]\n }\n }\n ]\n}","issue":"131","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mejia, Francine H. 0000-0003-4447-231X","orcid":"https://orcid.org/0000-0003-4447-231X","contributorId":214345,"corporation":false,"usgs":true,"family":"Mejia","given":"Francine","email":"","middleInitial":"H.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":824849,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Connor, Jason M","contributorId":267258,"corporation":false,"usgs":false,"family":"Connor","given":"Jason","email":"","middleInitial":"M","affiliations":[{"id":40867,"text":"Kalispel Tribe Natural Resources Department","active":true,"usgs":false}],"preferred":false,"id":824850,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kaufmann, Phil R","contributorId":267259,"corporation":false,"usgs":false,"family":"Kaufmann","given":"Phil","email":"","middleInitial":"R","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":824851,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Torgersen, Christian E. 0000-0001-8325-2737 ctorgersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":146935,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian","email":"ctorgersen@usgs.gov","middleInitial":"E.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":824852,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Berntsen, Eric K","contributorId":214885,"corporation":false,"usgs":false,"family":"Berntsen","given":"Eric","email":"","middleInitial":"K","affiliations":[{"id":39131,"text":"Kalispel Tribe of Indians","active":true,"usgs":false}],"preferred":false,"id":824853,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Andersen, Todd","contributorId":243418,"corporation":false,"usgs":false,"family":"Andersen","given":"Todd","email":"","affiliations":[{"id":40867,"text":"Kalispel Tribe Natural Resources Department","active":true,"usgs":false}],"preferred":false,"id":824854,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70229187,"text":"70229187 - 2021 - Honey bee (Apis mellifera) colonies benefit from grassland/ pasture while bumble bee (Bombus impatiens) colonies in the same landscapes benefit from non-corn/soybean cropland","interactions":[],"lastModifiedDate":"2022-03-02T16:44:23.45246","indexId":"70229187","displayToPublicDate":"2021-09-20T10:30:41","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Honey bee (Apis mellifera) colonies benefit from grassland/ pasture while bumble bee (Bombus impatiens) colonies in the same landscapes benefit from non-corn/soybean cropland","docAbstract":"Agriculturally important commercially managed pollinators including honey bees (Apis mellifera L., 1758) and bumble bees (Bombus impatiens Cresson, 1863) rely on the surrounding landscape to fulfill their dietary needs. A previous study in Europe demonstrated that managed honey bee foragers and unmanaged native bumble bee foragers are associated with different land uses. However, it is unclear how response to land use compares between managed honey bees and a managed native bumble bee species in the United States, where honey bees are an imported species. Furthermore, to our knowledge, no such direct comparisons of bee responses to land use have been made at the colony level. To better understand how two different social bees respond to variation in land use, we monitored the weights of A. mellifera and B. impatiens colonies placed in 12 apiaries across a range of land use in Michigan, United States in 2017. Bombus impatiens colonies gained more weight and produced more drones when surrounded by diverse agricultural land (i.e., non-corn/soybean cropland such as tree fruits and grapes), while honey bee colonies gained more weight when surrounded by more grassland/pasture land. These findings add to our understanding of how different bee species respond to agricultural landscapes, highlighting the need for further species-specific land use studies to inform tailored land management.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0257701","usgsCitation":"Quinlan, G., Milbrath, M., Otto, C., and Isaacs, R., 2021, Honey bee (Apis mellifera) colonies benefit from grassland/ pasture while bumble bee (Bombus impatiens) colonies in the same landscapes benefit from non-corn/soybean cropland: PLoS ONE, v. 16, no. 9, p. 1-12, https://doi.org/10.1371/journal.pone.0257701.","productDescription":"e0257701, 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-130366","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":450754,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0257701","text":"Publisher Index Page"},{"id":396654,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.05639648437499,\n 41.705728515237524\n ],\n [\n -84.00146484374999,\n 43.32517767999296\n ],\n [\n -86.41845703124999,\n 43.27720532212024\n ],\n [\n -86.253662109375,\n 43.004647127794435\n ],\n [\n -86.2646484375,\n 42.67435857693381\n ],\n [\n -86.319580078125,\n 42.45588764197166\n ],\n [\n -86.517333984375,\n 42.17968819665961\n ],\n [\n -86.671142578125,\n 41.95131994679697\n ],\n [\n -86.934814453125,\n 41.763117447005875\n ],\n [\n -84.825439453125,\n 41.77131167976407\n ],\n [\n -84.825439453125,\n 41.705728515237524\n ],\n [\n -84.05639648437499,\n 41.705728515237524\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"9","noUsgsAuthors":false,"publicationDate":"2021-09-20","publicationStatus":"PW","contributors":{"editors":[{"text":"Dolezal, Adam","contributorId":210716,"corporation":false,"usgs":false,"family":"Dolezal","given":"Adam","email":"","affiliations":[{"id":38135,"text":"Illinois","active":true,"usgs":false}],"preferred":false,"id":836923,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Quinlan, Gabriela","contributorId":287574,"corporation":false,"usgs":false,"family":"Quinlan","given":"Gabriela","email":"","affiliations":[{"id":36244,"text":"MSU","active":true,"usgs":false}],"preferred":false,"id":836895,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milbrath, Megan","contributorId":287575,"corporation":false,"usgs":false,"family":"Milbrath","given":"Megan","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":836896,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":836897,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Isaacs, Rufus","contributorId":287577,"corporation":false,"usgs":false,"family":"Isaacs","given":"Rufus","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":836898,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70224266,"text":"sir20215062 - 2021 - Development of regression equations for the estimation of the magnitude and frequency of floods at rural, unregulated gaged and ungaged streams in Puerto Rico through water year 2017","interactions":[],"lastModifiedDate":"2021-09-21T11:32:14.387182","indexId":"sir20215062","displayToPublicDate":"2021-09-20T09:49:44","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5062","displayTitle":"Development of Regression Equations for the Estimation of the Magnitude and Frequency of Floods at Rural, Unregulated Gaged and Ungaged Streams in Puerto Rico Through Water Year 2017","title":"Development of regression equations for the estimation of the magnitude and frequency of floods at rural, unregulated gaged and ungaged streams in Puerto Rico through water year 2017","docAbstract":"The methods of computation and estimates of the magnitude of flood flows were updated for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent chance exceedance levels for 91 streamgages on the main island of Puerto Rico by using annual peak-flow data through 2017. Since the previous flood frequency study in 1994, the U.S. Geological Survey has collected additional peak flows at additional streamgages, and Puerto Rico has experienced numerous flood events. This updated study was performed using longer annual peak-flow datasets from more stations to provide more representative equations to predict flood flows. Screening criteria for these streamgages included 10 or more years of annual peak-flow data, unregulated flow, and less than 10 percent impervious drainage area.
The magnitude and frequency of floods at selected streamgages in Puerto Rico were estimated using updated methods outlined in Bulletin 17C. The new procedures include a regional skew analysis that incorporates Bayesian regression techniques, the Expected Moments Algorithm to better represent missing record and estimate parameters of the log-Pearson Type III distribution, and the Multiple Grubbs-Beck test for low outlier detection.
Regional regression equations were developed to estimate peak-flow statistics at ungaged locations by using selected basin and climatic characteristics as explanatory variables. These variables were determined from digital spatial datasets and geographic information systems by using the most recent data available. Ordinary least-squares regression techniques were used to filter the basin characteristics and determine two separate regions, region 1 (west) and region 2 (east), based on residuals. A generalized least-squares procedure was used to account for cross-correlation of sites and develop the final set of equations that have drainage area as the only explanatory variable. The average standard errors of prediction ranged from 18.7 to 46.7 percent in region 1 and 33.4 to 57.6 percent in region 2 for all annual exceedance probabilities (AEPs) examined. The updated statistics showed a greater accuracy of prediction when compared to those from the previous study using drainage area as the only explanatory variable for all AEPs examined in region 1 and the 0.01 and 0.002 AEP flows for region 2. When compared to equations developed in the previous study that have drainage area, mean annual rainfall, and (or) depth-to-rock as explanatory variables, the updated statistics show a greater accuracy of prediction in region 1 at AEP flows of 0.02 and lower (that is, higher flows). Those developed for region 2 do not show a greater accuracy of prediction for any AEP flows when compared to the equations having multiple explanatory variables in the previous study.
The calculated regression equations, basin characteristics, and at-site statistics will be incorporated into the U.S. Geological Survey web application, StreamStats (https://streamstats.usgs.gov/ss/). This application allows users to select a location on a stream, whether gaged or ungaged, to obtain estimates of basin characteristics and flow statistics.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215062","usgsCitation":"Ryan, P.J., Gotvald, A.J., Hazelbaker, C.L., Veilleux, A.G., and Wagner, D.M., 2021, Development of regression equations for the estimation of the magnitude and frequency of floods at rural, unregulated gaged and ungaged streams in Puerto Rico through water year 2017: U.S. Geological Survey Scientific Investigations Report 2021–5062, 37 p., https://doi.org/10.3133/sir20215062.","productDescription":"Report: v, 37 p.; Appendix Tables: 3; Data Release","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-123614","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":389343,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91XT14B","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data files for the development of regression equations for estimation of the magnitude and frequency of floods at rural, unregulated gaged and ungaged streams in Puerto Rico through water year 2017"},{"id":389335,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5062/coverthb.jpg"},{"id":389336,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5062/sir20215062.pdf","text":"Report","size":"4.38 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5062"},{"id":389337,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5062/sir20215062_appendix_2.1.csv","text":"Appendix Table 2.1 (.csv format)","size":"5.89 kB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"— Streamgages operated by the U.S. Geological Survey (USGS) in Puerto Rico that were used in the regional skew analysis"},{"id":389340,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5062/sir20215062_appendix_1.xlsx","text":"Appendix 1 (.xlsx format)","size":"30.9 kB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"— Streamgages considered for development of regional regression equations in Puerto Rico and details of at-site statistic inputs"},{"id":389338,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5062/sir20215062_appendix_2.1.xlsx","text":"Appendix Table 2.1 (.xlsx format)","size":"19.6 kB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"— Streamgages operated by the U.S. Geological Survey (USGS) in Puerto Rico that were used in the regional skew analysis"},{"id":389339,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5062/sir20215062_appendix_1.csv","text":"Appendix 1 (.csv format)","size":"20.7 kB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"— Streamgages considered for development of regional regression equations in Puerto Rico and details of at-site statistic inputs"},{"id":389341,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5062/sir20215062_appendix_3.csv","text":"Appendix 3 (.csv format)","size":"80.4 kB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"— At-site, regression equation, and weighted magnitude, variance, and prediction intervals of annual exceedance probability floods for select unregulated streamgages in Puerto Rico"},{"id":389342,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5062/sir20215062_appendix_3.xlsx","text":"Appendix 3 (.xlsx format)","size":"134 kB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"— At-site, regression equation, and weighted magnitude, variance, and prediction intervals of annual exceedance probability floods for select unregulated streamgages in Puerto Rico"}],"country":"United States","otherGeospatial":"Puerto 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U.S. Geological Survey
4446 Pet Lane, Suite 108
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Coastal research frequently involves the use of a GIS to analyze large areas for changes in response to major weather events, human action, and other factors. The GIS workflows used to conduct these analyses can be complex and sometimes require multiple days to complete. Long runtimes often exist even on modern high-powered workstations if the GIS software does not use parallel computing techniques, which prevents it from fully utilizing the capabilities of multicore processors. If a GIS application supports a programming interface that allows geoprocessing tools to be called from an external program, then GIS workflows can use parallel functionality embedded in that programming language to divide the load of a large workflow among multiple child processes. In ArcMap and ArcGIS Pro, this technique can be implemented by using the Python programming interface and the multiprocessing module in Python to run geoprocessing tools in child processes. This method was used in the Seafloor Elevation Change Analysis Tool (SECAT), a Python script written for ArcMap and ArcGIS Pro that calculates changes in seafloor elevation over time using two different digital elevation models. Running SECAT with between one and eight child processes on two different datasets improved execution times by at least a factor of 2.4. These results demonstrate that using the Python multiprocessing module can significantly accelerate a variety of time-consuming workflows.
","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/JCOASTRES-D-21-00026.1","usgsCitation":"Zieg, J.A., and Zawada, D., 2021, Improving ESRI ArcGIS performance of coastal and seafloor analysis with the Python multiprocessing module: Journal of Coastal Research, v. 37, no. 6, p. 1288-1293, https://doi.org/10.2112/JCOASTRES-D-21-00026.1.","productDescription":"6 p.","startPage":"1288","endPage":"1293","ipdsId":"IP-117051","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":397108,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zieg, Jonathan Andrew 0000-0002-4590-9328","orcid":"https://orcid.org/0000-0002-4590-9328","contributorId":288476,"corporation":false,"usgs":true,"family":"Zieg","given":"Jonathan","email":"","middleInitial":"Andrew","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":837979,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zawada, David G. 0000-0003-4547-4878 dzawada@usgs.gov","orcid":"https://orcid.org/0000-0003-4547-4878","contributorId":1898,"corporation":false,"usgs":true,"family":"Zawada","given":"David G.","email":"dzawada@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":837980,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70230277,"text":"70230277 - 2021 - Stable isotopes used to infer trophic position of green turtles (Chelonia mydas) from Dry Tortugas National Park, Gulf of Mexico, United States","interactions":[],"lastModifiedDate":"2023-06-09T14:07:06.207792","indexId":"70230277","displayToPublicDate":"2021-09-20T09:00:51","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5094,"text":"Regional Studies in Marine Science","onlineIssn":"2352-4855","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Stable isotopes used to infer trophic position of green turtles (Chelonia mydas) from Dry Tortugas National Park, Gulf of Mexico, United States","title":"Stable isotopes used to infer trophic position of green turtles (Chelonia mydas) from Dry Tortugas National Park, Gulf of Mexico, United States","docAbstract":"Evaluating resource use patterns for imperiled species is critical for understanding what supports their populations. Here we established stable isotope (