Land use in Panama has changed dramatically with ongoing deforestation and conversion to cropland and cattle pastures, potentially altering the soil properties that drive the hydrological processes of infiltration and overland flow. We compared plot-scale overland flow generation between hillslopes in forested and actively cattle-grazed watersheds in Central Panama. Soil physical and hydraulic properties, soil moisture and overland flow data were measured along hillslopes of each land-use type. Soil characteristics and rainfall data were input into a simple, 1-D representative model, HYDRUS-1D, to simulate overland flow that we used to make inferences about overland flow response at forest and pasture sites. Runoff ratios (overland flow/rainfall) were generally higher at the pasture site, although no overall trends were observed between rainfall characteristics and runoff ratios across the two land uses at the plot scale. Saturated hydraulic conductivity (Ks) and bulk density were different between the forest and pasture sites (p < 10−4). Simulating overland flow in HYDRUS-1D produced more outputs similar to the overland flow recorded at the pasture site than the forest site. Results from our study indicate that, at the plot scale, Hortonian overland flow is the main driver for overland flow generation at the pasture site during storms with high-rainfall totals. We infer that the combination of a leaf litter layer and the activation of shallow preferential flow paths resulting in shallow saturation-excess overland flow are likely the main drivers for plot scale overland flow generation at the forest site. Results from this study contribute to the broader understanding of the delivery of freshwater to streams, which will become increasingly important in the tropics considering freshwater resource scarcity and changing storm intensities.
The prediction of wave runup, as well as its components, time-averaged setup and the time-varying swash, is a key element of coastal storm hazard assessments, as wave runup controls the transitions between morphodynamic response types such as dune erosion and overwash, and the potential for flooding by wave overtopping. While theoretically able to simulate the dominant low-frequency swash, previous studies using the infragravity-wave–resolving model XBeach (XBSB) have shown an underestimation of the observed swash variance and wave runup, which was in part related to the absence of incident-band swash motions in the model. Here, we use an incident-band wave-resolving, non-hydrostatic version of the XBeach model (XBNH) to simulate wave runup observed during the SandyDuck '97 experiment on an intermediate–reflective sandy beach. The results show that the XBNH model describes wave runup and the individual setup and swash components well. We subsequently examine differences in wave runup prediction between the XBSB and XBNH models and find that the XBNH model is a better predictor of wave runup than XBSB for this beach, which is due to better predictions of both the incident-band and infragravity-band swash. For a range of beach states from reflective to dissipative it is shown that incident-band swash is underestimated by XBSB relative to XBNH, in particular for reflective conditions. Infragravity-band swash is shown to be lower in XBSB than XBNH for most conditions, including dissipative conditions for which the mean difference is 16% of the deep water wave height. The difference in infragravity-band swash in XBNH relative to XBSB is shown to mainly be the result of processes occurring outside the swash zone, but approximately 15% of the difference is caused by explicitly resolving incident-band wave motions within the swash zone, such as swash-swash interactions, which inherently cannot be simulated by wave-averaged models.
Characterizing pre- and post-fire fuels remains a key challenge for estimating biomass consumption and carbon emissions from wildfires. Airborne laser scanning (ALS) data have demonstrated effectiveness for estimating canopy, and to a lesser degree, surface fuel components at fine-scale (i.e., 30 m) across landscapes. Using pre- and post-fire ALS data and corresponding field data, this study estimated consumption of canopy fuel (ΔCF), understory fuel (ΔUF), total fuel (ΔTF), and canopy bulk density (ΔCBD) for the 2012 Pole Creek fire in Oregon, USA (10,760 ha), and portions of the 2011 Las Conchas fire in New Mexico, USA (4,934 ha). Additionally, the feasibility of predicting fuel consumption was tested using separate pre- and post-fire models (PrePost), models combining all pre- and post-fire data (Pooled), and models using all data from both fires (Global). Estimates of ΔTF were then compared to fire radiative energy (FRE, units: MJ) derived from Fire Radiative Power (FRP, units: MW) observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA Terra and Aqua satellites to mechanistically derive a biomass combustion coefficient (BCC, units: kg MJ−1). The PrePost and Pooled approaches yielded similar results at Las Conchas, but at Pole Creek insufficient pre-fire field data resulted in erroneous fuel consumption estimates outside the fire perimeter using the PrePost models. These results demonstrated that pre-fire field data were less important for these models than having field data which represent the full range of fuel conditions likely to exist across the landscape. Estimated total biomass consumed for the PrePost, Pooled, and Global models were 226 Gg, 224 Gg, and 224 Gg at Las Conchas, and 581 Gg, 713 Gg, and 552 Gg at Pole Creek. Comparisons between estimated ΔTF and FRE yielded an average BCC for both fires of 0.367 (s.d. ± 0.049) kg MJ−1 based on pixels with at least five MODIS observations. Both higher MODIS observations per pixel and accounting for canopy occlusion of FRE improved the relationship between ΔTF and MODIS-FRE. This study suggested a practical modelling approach for future efforts using only post-fire field observations and quantified a landscape-scale relationship between MODIS-derived FRE and fine-scale fuel consumption consistent with prior experiments.
The Everglades Depth Estimation Network (EDEN) is an integrated network of water-level gages, interpolation models that estimate daily water-level data at ungaged locations, and applications that generate derived hydrologic data across the freshwater part of the Greater Everglades landscape. Version 3 (V3) of the EDEN interpolation surface-water model is the most recent update, replacing the version 2 (V2) model released in 2011.
The primary revision for the V3 model is the switch to the R programming language to create a more efficient and portable EDEN code relative to V2, without reliance on proprietary software. Using R, the interpolation script runs over 10 times faster and is more easily updated, for example, to accommodate changes in the gage network or to incorporate R software updates. Additional revisions made for the V3 model include updates to the interpolation model, the gage network, and groundwater-level estimations. The EDEN model domain in the Greater Everglades and Big Cypress National Preserve is divided into subdomains that are based on hydrologic boundaries. In the V3 model, the number of subdomains was increased from five to eight, which allows hydrologic boundaries, such as levees and canals, to be better represented in the interpolation scheme. Five pseudogages were added to constrain the water-level surface at subdomain boundaries. Changes made to the water-level gage network between the implementation of the V2 and V3 models are incorporated, and groundwater-level estimations are added, which are important information for hydrologic and ecological studies.
Summary model performance statistics indicate similar accuracy in water-level surfaces generated by the V3 and V2 models, with a root mean square error of 4.78 centimeters for both interpolation models against independent water-level measurements. Providing stability and continuity for the EDEN user community, the V3 model closely replicates the V2 model, with a root mean square difference of 3.87 centimeters for interpolated surfaces from April 1, 2014, to March 31, 2018. The additional groundwater levels provide a realistic estimate of the saturated groundwater surface continuous with the surface-water surface for Water Conservation Areas 2A and 2B from 2000 to 2011. This continuous surface is a more accurate estimation of the spatial distribution of water in the hydrologic system than before, providing needed information for ecological studies in areas where depth to water table affects habitats. Development of the EDEN V3 model advances the tools available to scientists and resource managers for guiding large-scale field operations, describing hydrologic changes, and supporting biological and ecological assessments.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205083","collaboration":"USGS Greater Everglades Priority Ecosystems Science ProgramDirector, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
The effects of climate on plant species ranges are well appreciated, but the effects of other processes, such as fire, on plant species distribution are less well understood. We used a dataset of 561 plots 0.1 ha in size located throughout Yosemite National Park, in the Sierra Nevada of California, USA, to determine the joint effects of fire and climate on woody plant species. We analyzed the effect of climate (annual actual evapotranspiration [AET], climatic water deficit [Deficit]) and fire characteristics (occurrence [BURN] for all plots, fire return interval departure [FRID] for unburned plots, and severity of the most severe fire [dNBR]) on the distribution of woody plant species.
Of 43 species that were present on at least two plots, 38 species occurred on five or more plots. Of those 38 species, models for the distribution of 13 species (34%) were significantly improved by including the variable for fire occurrence (BURN). Models for the distribution of 10 species (26%) were significantly improved by including FRID, and two species (5%) were improved by including dNBR. Species for which distribution models were improved by inclusion of fire variables included some of the most areally extensive woody plants. Species and ecological zones were aligned along an AET-Deficit gradient from cool and moist to hot and dry conditions.
In fire-frequent ecosystems, such as those in most of western North America, species distribution models were improved by including variables related to fire. Models for changing species distributions would also be improved by considering potential changes to the fire regime.
","language":"English","publisher":"Springer","doi":"10.1186/s42408-020-00079-9","usgsCitation":"van Wagtendonk, J., Moore, P., Yee, J.L., and Lutz, J.A., 2020, The distribution of woody species in relation to climate and fire in Yosemite National Park, California, USA: Fire Ecology, v. 16, 22, 23 p., https://doi.org/10.1186/s42408-020-00079-9.","productDescription":"22, 23 p.","ipdsId":"IP-117438","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":455198,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s42408-020-00079-9","text":"Publisher Index Page"},{"id":379026,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yosemite National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.13549804687501,\n 36.94989178681327\n ],\n [\n -118.24584960937499,\n 36.94989178681327\n ],\n [\n -118.24584960937499,\n 38.272688535980976\n ],\n [\n -120.13549804687501,\n 38.272688535980976\n ],\n [\n -120.13549804687501,\n 36.94989178681327\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","noUsgsAuthors":false,"publicationDate":"2020-09-29","publicationStatus":"PW","contributors":{"authors":[{"text":"van Wagtendonk, Jan W.","contributorId":189573,"corporation":false,"usgs":false,"family":"van Wagtendonk","given":"Jan W.","affiliations":[],"preferred":false,"id":800466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Peggy E","contributorId":242603,"corporation":false,"usgs":false,"family":"Moore","given":"Peggy E","affiliations":[{"id":48478,"text":"retired USGS WERC employee","active":true,"usgs":false}],"preferred":false,"id":800467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yee, Julie L. 0000-0003-1782-157X julie_yee@usgs.gov","orcid":"https://orcid.org/0000-0003-1782-157X","contributorId":3246,"corporation":false,"usgs":true,"family":"Yee","given":"Julie","email":"julie_yee@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":800468,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lutz, James A.","contributorId":139178,"corporation":false,"usgs":false,"family":"Lutz","given":"James","email":"","middleInitial":"A.","affiliations":[{"id":12682,"text":"Utah State University, Logan, UT","active":true,"usgs":false}],"preferred":false,"id":800469,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70221555,"text":"70221555 - 2020 - Timescale methods for simplifying, understanding and modeling biophysical and water quality processes in coastal aquatic ecosystems: A review","interactions":[],"lastModifiedDate":"2021-06-23T12:39:32.793452","indexId":"70221555","displayToPublicDate":"2020-09-29T06:49:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Timescale methods for simplifying, understanding and modeling biophysical and water quality processes in coastal aquatic ecosystems: A review","docAbstract":"In this article, we describe the use of diagnostic timescales as simple tools for illuminating how aquatic ecosystems work, with a focus on coastal systems such as estuaries, lagoons, tidal rivers, reefs, deltas, gulfs, and continental shelves. Intending this as a tutorial as well as a review, we discuss relevant fundamental concepts (e.g., Lagrangian and Eulerian perspectives and methods, parcels, particles, and tracers), and describe many of the most commonly used diagnostic timescales and definitions. Citing field-based, model-based, and simple algebraic methods, we describe how physical timescales (e.g., residence time, flushing time, age, transit time) and biogeochemical timescales (e.g., for growth, decay, uptake, turnover, or consumption) are estimated and implemented (sometimes together) to illuminate coupled physical-biogeochemical systems. Multiple application examples are then provided to demonstrate how timescales have proven useful in simplifying, understanding, and modeling complex coastal aquatic systems. We discuss timescales from the perspective of “holism”, the degree of process richness incorporated into them, and the value of clarity in defining timescales used and in describing how they were estimated. Our objective is to provide context, new applications and methodological ideas and, for those new to timescale methods, a starting place for implementing them in their own work.
","language":"English","publisher":"MDPI","doi":"10.3390/w12102717","usgsCitation":"Lucas, L., and Deleersnijder, E., 2020, Timescale methods for simplifying, understanding and modeling biophysical and water quality processes in coastal aquatic ecosystems: A review: Water, v. 12, no. 10, 2717, 65 p., https://doi.org/10.3390/w12102717.","productDescription":"2717, 65 p.","ipdsId":"IP-119708","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":455205,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w12102717","text":"Publisher Index Page"},{"id":386640,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-09-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Lucas, Lisa 0000-0001-7797-5517 llucas@usgs.gov","orcid":"https://orcid.org/0000-0001-7797-5517","contributorId":260498,"corporation":false,"usgs":true,"family":"Lucas","given":"Lisa","email":"llucas@usgs.gov","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":818032,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Deleersnijder, Eric 0000-0003-0346-9667","orcid":"https://orcid.org/0000-0003-0346-9667","contributorId":260499,"corporation":false,"usgs":false,"family":"Deleersnijder","given":"Eric","email":"","affiliations":[{"id":52602,"text":"Université catholique de Louvain, Institute of Mechanics, Materials and Civil Engineering (IMMC) & Earth and Life Institute (ELI), Louvain-la-Neuve, Belgium","active":true,"usgs":false}],"preferred":false,"id":818033,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70218208,"text":"70218208 - 2020 - Comparing simulations of umbrella-cloud growth and ash transport with observations from Pinatubo, Kelud, and Calbuco volcanoes","interactions":[],"lastModifiedDate":"2021-02-19T20:33:29.170078","indexId":"70218208","displayToPublicDate":"2020-09-27T14:28:03","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5634,"text":"Atmosphere","active":true,"publicationSubtype":{"id":10}},"title":"Comparing simulations of umbrella-cloud growth and ash transport with observations from Pinatubo, Kelud, and Calbuco volcanoes","docAbstract":"The largest explosive volcanic eruptions produce umbrella clouds that drive ash radially outward, enlarging the area that impacts aviation and ground-based communities. Models must consider the effects of umbrella spreading when forecasting hazards from these eruptions. In this paper we test a version of the advection–dispersion model Ash3d that considers umbrella spreading by comparing its simulations with observations from three well-documented umbrella-forming eruptions: (1) the 15 June 1991 eruption of Pinatubo (Philippines); (2) the 13 February 2014 eruption of Kelud (Indonesia); and (3) phase 2 of the 22–23 April 2015 eruption of Calbuco (Chile). In volume, these eruptions ranged from several cubic kilometers dense-rock equivalent (DRE) for Pinatubo to about one tenth for Calbuco. In mass eruption rate (MER), they ranged from 108–109 kg s−1 at Pinatubo to 9–16 × 106 kg s−1 at Calbuco. For each case we ran simulations that considered umbrella growth and ones that did not. All umbrella-cloud simulations produced a cloud whose area was within ~25% of the observed cloud by the end of the eruption. By the eruption end, the simulated areas of the Pinatubo, Kelud, and Calbuco clouds were 851, 53.2, and 100 × 103 km2 respectively. These areas were 2.2, 2.2, and 1.5 times the areas calculated in simulations that ignored umbrella growth. For Pinatubo and Kelud, the umbrella simulations provided better agreement with the observed cloud area than the non-umbrella simulations. Each of these simulations extended 24 h from the eruption start. After the eruption ended, the difference in cloud area (umbrella minus non-umbrella) at Pinatubo persisted for many hours; at Kelud it diminished and became negative after 14 h and at Calbuco it became negative after ~23 h. The negative differences were inferred to result from the fact that non-umbrella simulations distributed ash over a wider vertical extent in the plume, and that wind shear spread the cloud out in multiple directions. Thus, for some smaller eruptions, wind shear can produce a larger cloud than might be produced by umbrella spreading alone.
","language":"English","publisher":"MDPI","doi":"10.3390/atmos11101038","usgsCitation":"Mastin, L.G., and Van Eaton, A.R., 2020, Comparing simulations of umbrella-cloud growth and ash transport with observations from Pinatubo, Kelud, and Calbuco volcanoes: Atmosphere, v. 11, no. 10, 1038, 21 p., https://doi.org/10.3390/atmos11101038.","productDescription":"1038, 21 p.","ipdsId":"IP-121394","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":455211,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/atmos11101038","text":"Publisher Index Page"},{"id":436777,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NPYCRH","text":"USGS data release","linkHelpText":"Observations and model simulations of umbrella-cloud growth during eruptions of Mount Pinatubo (Philippines, June 15, 1991), Kelud Volcano (Indonesia, February 14, 2014), and Calbuco Volcano (Chile, April 22-23, 2015)"},{"id":383397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile, Indonesia, Philippines","otherGeospatial":"Calbuco volcano, Kelud volcano, Pinatubo volcano","volume":"11","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-09-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Mastin, Larry G. 0000-0002-4795-1992 lgmastin@usgs.gov","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":555,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"lgmastin@usgs.gov","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":810426,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Eaton, Alexa R. 0000-0001-6646-4594 avaneaton@usgs.gov","orcid":"https://orcid.org/0000-0001-6646-4594","contributorId":184079,"corporation":false,"usgs":true,"family":"Van Eaton","given":"Alexa","email":"avaneaton@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":810427,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70217181,"text":"70217181 - 2020 - Effects of dewatering on behavior, distribution, and abundance of larval lampreys","interactions":[],"lastModifiedDate":"2021-01-11T14:43:47.441892","indexId":"70217181","displayToPublicDate":"2020-09-27T08:34:52","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Effects of dewatering on behavior, distribution, and abundance of larval lampreys","docAbstract":"Anthropogenic dewatering of aquatic habitats can cause stranding and mortality of burrowed larval lampreys; however, the effects of dewatering have not been quantified. We assessed: (a) changes in spatial distribution, abundance, and emergence of larvae dewatered at Leaburg Reservoir (OR); (b) emergence and mortality of larvae dewatered in a laboratory; and (c) bias, precision, and interpretation of field results by simulation and modeling of laboratory results. In the field, we examined the distribution, abundance (by N‐mixture model), and density of larvae by electrofishing at randomly selected sites before dewatering and after refill, and assessed the emergence rate by observation and excavation during dewatering. Due to dewatering in the field, about 42% of larvae emerged and spatial distribution changed toward sites dewatered less than 20 hours. Estimated average density decreased from 10.8 larvae/m2 before dewatering to 2.3 larvae/m2 after refilling, suggesting that abundance declined by 79%; simulation suggested this decline ranged 71–84% (interquartile range). In the laboratory, we examined the emergence and mortality rates of larvae dewatered 0–48 hrs. The emergence rate in the laboratory was similar to that in the field. Mortality rate increased with hours dewatered and was higher for emerged than burrowed larvae. Laboratory estimates of mortality rate predicted a 61% decline in abundance if only burrowed larvae survived and a 54% decline if both burrowed and emerged larvae survived. Abundance declines in the field could be from mortality (e.g., desiccation, predation) and relocation to watered habitat. Our results indicate dewatering can substantially affect spatial distribution and abundance of larval lampreys in freshwater ecosystems.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3730","usgsCitation":"Harris, J.E., Skalicky, J.J., Liedtke, T.L., Weiland, L.K., Clemens, B.J., and Gray, A.E., 2020, Effects of dewatering on behavior, distribution, and abundance of larval lampreys: River Research and Applications, v. 36, no. 10, p. 2001-2012, https://doi.org/10.1002/rra.3730.","productDescription":"12 p.","startPage":"2001","endPage":"2012","ipdsId":"IP-119069","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":382054,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Leaburg Reservoir, McKenzie River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.068603515625,\n 43.75522505306928\n ],\n [\n -121.36596679687499,\n 43.75522505306928\n ],\n [\n -121.36596679687499,\n 45.706179285330855\n ],\n [\n -124.068603515625,\n 45.706179285330855\n ],\n [\n -124.068603515625,\n 43.75522505306928\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-09-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Harris, Julianne E. 0000-0003-1343-5911","orcid":"https://orcid.org/0000-0003-1343-5911","contributorId":247527,"corporation":false,"usgs":false,"family":"Harris","given":"Julianne","email":"","middleInitial":"E.","affiliations":[{"id":49569,"text":"U.S. Fish and Wildlife Service, Columbia River Fish and Wildlife Conservation Office, 1211 SE Cardinal Court, Suite 100, Vancouver, Washington 98683","active":true,"usgs":false}],"preferred":false,"id":807857,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Skalicky, Joseph J. 0000-0002-6467-5037","orcid":"https://orcid.org/0000-0002-6467-5037","contributorId":247528,"corporation":false,"usgs":false,"family":"Skalicky","given":"Joseph","email":"","middleInitial":"J.","affiliations":[{"id":49569,"text":"U.S. Fish and Wildlife Service, Columbia River Fish and Wildlife Conservation Office, 1211 SE Cardinal Court, Suite 100, Vancouver, Washington 98683","active":true,"usgs":false}],"preferred":false,"id":807858,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liedtke, Theresa L. 0000-0001-6063-9867 tliedtke@usgs.gov","orcid":"https://orcid.org/0000-0001-6063-9867","contributorId":2999,"corporation":false,"usgs":true,"family":"Liedtke","given":"Theresa","email":"tliedtke@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":807859,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weiland, Lisa K. 0000-0002-9729-4062 lweiland@usgs.gov","orcid":"https://orcid.org/0000-0002-9729-4062","contributorId":3565,"corporation":false,"usgs":true,"family":"Weiland","given":"Lisa","email":"lweiland@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":807860,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clemens, Benjamin J.","contributorId":195098,"corporation":false,"usgs":false,"family":"Clemens","given":"Benjamin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":807861,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gray, Ann E.","contributorId":195113,"corporation":false,"usgs":false,"family":"Gray","given":"Ann","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":807862,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70214530,"text":"70214530 - 2020 - Modeling soil porewater salinity in mangrove forests (Everglades, Florida, USA) impacted by hydrological restoration and a warming climate","interactions":[],"lastModifiedDate":"2020-09-30T14:56:14.381095","indexId":"70214530","displayToPublicDate":"2020-09-26T09:49:06","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Modeling soil porewater salinity in mangrove forests (Everglades, Florida, USA) impacted by hydrological restoration and a warming climate","docAbstract":"Hydrology is a critical driver controlling mangrove wetlands structural and functional attributes at different spatial and temporal scales. Yet, human activities have negatively affected hydrology, causing mangrove diebacks and coverage loss worldwide. In fact, the assessment of mangrove water budgets, impacted by natural and human disturbances, is limited due to a lack of long-term data and information that hinders our understanding of how changes in hydroperiod and salinity control mangrove productivity and spatial distribution. In this study, we implemented a mass balance-based hydrological model (RHYMAN) that explicitly considers groundwater discharge in the Shark River estuary (SRE, southwestern Everglades) located in a karstic geomorphic setting and influenced by regional hydrological restoration. We used long-term hydroperiod and porewater salinity (PWS) datasets obtained from 2004 to 2016 for model calibration and validation and to determine spatiotemporal variability in water levels and PWS at three riverine mangrove sites (downstream, SRS-6; midstream, SRS-5; upstream, SRS-4) along SRE. Model results agree with a distinct PWS pattern along the estuarine salinity gradient where the highest PWS occurs at SRS-6 (mean: 25, range: 22–30 ppt), followed by SRS-5 (17, 14–25 ppt) and SRS-4 (5, 3–13 ppt). A commensurate increase in PWS over a thirteen-year period indicates a long-term reduction in freshwater inflow coupled with sea-level rise (SLR). Increasing freshwater scenario simulation results show a significant reduction (17–27%) in PWS along the estuary in contrast with a high SLR scenario when salinity increases up to 1.1 to 2.5 times that of control values. Model results show that freshwater inflow and SLR are key drivers controlling mangrove wetlands PWS in this karstic coastal region. Given its relatively simple structure, this mass balance-based hydrological model could be used in other environmental settings to evaluate potential habitat and regime shifts due to changes in hydrology and PWS under regional hydrological restoration management.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2020.109292","usgsCitation":"Zhao, X., Rivera-Monroy, V.H., Wang, H., Xue, Z., Tsai, C., Willson, C.S., Castañeda-Moya, E., and Twilley, R.R., 2020, Modeling soil porewater salinity in mangrove forests (Everglades, Florida, USA) impacted by hydrological restoration and a warming climate: Ecological Modelling, v. 436, 109292, 18 p., https://doi.org/10.1016/j.ecolmodel.2020.109292.","productDescription":"109292, 18 p.","ipdsId":"IP-117526","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":455213,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://repository.lsu.edu/civil_engineering_pubs/1184","text":"Publisher Index Page"},{"id":378913,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.9085693359375,\n 25.06072125231416\n ],\n [\n -80.3814697265625,\n 25.06072125231416\n ],\n [\n -80.3814697265625,\n 26.48532391504829\n ],\n [\n -81.9085693359375,\n 26.48532391504829\n ],\n [\n -81.9085693359375,\n 25.06072125231416\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"436","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zhao, Xiaochen","contributorId":219696,"corporation":false,"usgs":false,"family":"Zhao","given":"Xiaochen","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":799834,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rivera-Monroy, Victor H. 0000-0003-2804-4139","orcid":"https://orcid.org/0000-0003-2804-4139","contributorId":200322,"corporation":false,"usgs":false,"family":"Rivera-Monroy","given":"Victor","email":"","middleInitial":"H.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":799835,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Hongqing 0000-0002-2977-7732","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":219641,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":799836,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xue, Zuo 0000-0003-4018-0248","orcid":"https://orcid.org/0000-0003-4018-0248","contributorId":241655,"corporation":false,"usgs":false,"family":"Xue","given":"Zuo","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":799837,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tsai, Cheng-Feng","contributorId":241949,"corporation":false,"usgs":false,"family":"Tsai","given":"Cheng-Feng","email":"","affiliations":[],"preferred":false,"id":799838,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Willson, C. S.","contributorId":90440,"corporation":false,"usgs":false,"family":"Willson","given":"C.","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":799839,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Castañeda-Moya, E. 0000-0001-7759-4351","orcid":"https://orcid.org/0000-0001-7759-4351","contributorId":241657,"corporation":false,"usgs":false,"family":"Castañeda-Moya","given":"E.","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":799840,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Twilley, Robert R.","contributorId":34585,"corporation":false,"usgs":false,"family":"Twilley","given":"Robert","email":"","middleInitial":"R.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":799841,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70216488,"text":"70216488 - 2020 - Sea‐level rise will drive divergent sediment transport patterns on fore reefs and reef flats, potentially causing erosion on atoll islands","interactions":[],"lastModifiedDate":"2020-11-23T14:12:16.975375","indexId":"70216488","displayToPublicDate":"2020-09-25T07:58:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7358,"text":"Journal of Geophysical Research – Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Sea‐level rise will drive divergent sediment transport patterns on fore reefs and reef flats, potentially causing erosion on atoll islands","docAbstract":"Atoll reef islands primarily consist of unconsolidated sediment, and their ocean‐facing shorelines are maintained by sediment produced and transported across their reefs. Changes in incident waves can alter cross‐shore sediment exchange and, thus, affect the sediment budget and morphology of atoll reef islands. Here we investigate the influence of sea level rise and projected wave climate change on wave characteristics and cross‐shore sediment transport across an atoll reef at Kwajalein Island, Republic of the Marshall Islands. Using a phase‐resolving model, we quantify the influence on sediment transport of quantities not well captured by wave‐averaged models, namely, wave asymmetry and skewness and flow acceleration. Model results suggest that for current reef geometry, sea level, and wave climate, potential bedload transport is directed onshore, decreases from the fore reef to the beach, and is sensitive to the influence of flow acceleration. We find that a projected 12% decrease in annual wave energy by 2100 CE has negligible influence on reef flat hydrodynamics. However, 0.5–2.0 m of sea level rise increases wave heights, skewness, and shear stress on the reef flat and decreases wave skewness and shear stress on the fore reef. These hydrodynamic changes decrease potential sediment inputs onshore from the fore reef where coral production is greatest but increase potential cross‐reef sediment transport from the outer reef flat to the beach. Assuming sediment production on the fore reef remains constant or decreases due to increasing ocean temperatures and acidification, these processes have the potential to decrease net sediment delivery to atoll islands, causing erosion.
Sequoia Scientific’s LISST-ABS is a submersible acoustic instrument that measures the acoustic backscatter sensor (ABS) concentration at a point within a river, stream, or creek. Compared to traditional physical methods for measuring suspended-sediment concentration (SSC), sediment surrogates like the LISST-ABS offer continuous data that can be calibrated with physical SSC samples. Data were collected at 10 U.S. Geological Survey streamflow-gaging stations between January 10, 2016, and February 21, 2018, across the contiguous United States to test the accuracy and effectiveness of using the LISST-ABS as a surrogate for measuring the concentration of suspended sediment in a dynamic fluvial system. Correlation coefficients (Pearson’s r values) relating the ABS concentration and SSC from physical samples ranged from r = 0.718 to r = 0.956 at the 10 stations with the mean percentage of fines (percentage of the sediment less than 62.5 microns in diameter) ranging from 65 to 100 percent (with minimum and maximum values of 18 and 100 percent, respectively). The LISST-ABS instruments used in this field evaluation were factory-calibrated to accurately determine SSC for grains in the diameter range of 75–90 microns. Note that the sensor responds to grains of arbitrary sizes, but the accuracy varies at sizes other than this calibration size. For operational use, regression models could be determined for the ABS concentrations and SSC values or the instrument could be recalibrated to sediments for each fluvial environment. However, such calibrations were beyond the scope of this report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201096","collaboration":"Federal Interagency Sedimentation Project and Observing Systems Division","usgsCitation":"Manaster, A.E., Straub, T.D., Wood, M.S., Bell, J.M., Dombroski, D.E., and Curran, C.A., 2020, Field evaluation of the Sequoia Scientific LISST-ABS acoustic backscatter sediment sensor: U.S. Geological Survey Open-File Report 2020–1096, 26 p., https://doi.org/10.3133/ofr20201096.","productDescription":"Report: v, 26 p.; Data Release","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-116096","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":378643,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1096/coverthb.jpg"},{"id":378644,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1096/ofr20201096.pdf","text":"Report","size":"3.04 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1096"},{"id":378645,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LROJE4","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data for field evaluation of the Sequoia Scientific LISST-ABS acoustic backscatter sediment sensor"}],"contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
Migration is a period of high activity and exposure during which risks and energetic demand on individuals may be greater than during nonmigratory periods. Stopover locations can help mitigate these threats by providing supplemental energy en route to the animal’s end destination. Effective conservation of migratory species therefore requires an understanding of use of space that provides resources to migratory animals at stopover sites. We conducted a radio-telemetry study of a short-distance migrant, the American Woodcock (Scolopax minor), at an important stopover site, the Cape May Peninsula, New Jersey. Our objectives were to describe land-cover types used by American Woodcock and evaluate home range habitat selection for individuals that stopover during fall migration and those that choose to overwinter. We radio-marked 271 individuals and collected 1,949 locations from these birds (0–21 points individual–1) over 4 yr (2010 to 2013) to inform resource selection functions of land-cover types and other landscape characteristics by this species. We evaluated these relationships at multiple spatial extents for (1) birds known to have ultimately left the peninsula (presumed migrants), and (2) birds known to have remained on the peninsula into the winter (presumed winter residents). We found that migrants selected deciduous wetland forest, agriculture, mixed shrub, coniferous wetland forest, and coniferous shrub, while wintering residents selected deciduous wetland forest, coniferous shrub, and deciduous shrub. We used these results to develop predictive models of potential habitat: 7.80% of the peninsula was predicted to be potential stopover habitat for American Woodcock (95% classification accuracy) and 4.96% of the peninsula was predicted to be potential wintering habitat (85% classification accuracy). Our study is the first to report habitat relationships for migratory American Woodcock in the coastal U.S. and provides important spatial tools for local and regional managers to support migratory and winter resident woodcock populations into the future.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/condor/duaa046","usgsCitation":"Allen, B.L., McAuley, D., and Blomberg, E.J., 2020, Migratory status determines resource selection by American Woodcock at an important fall stopover, Cape May, New Jersey: The Condor, duaa046, 16 p., https://doi.org/10.1093/condor/duaa046.","productDescription":"duaa046, 16 p.","ipdsId":"IP-092164","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":436781,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7R49PZ2","text":"USGS data release","linkHelpText":"Multiscale resource selection by American Woodcock (Scolopax minor) during fall migration at Cape May, New Jersey"},{"id":379018,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Cape May","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.6024169921875,\n 38.852542390364235\n ],\n [\n -74.06982421875,\n 38.852542390364235\n ],\n [\n -74.06982421875,\n 39.51675478434244\n ],\n [\n -75.6024169921875,\n 39.51675478434244\n ],\n [\n -75.6024169921875,\n 38.852542390364235\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2020-09-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Allen, Brian L.","contributorId":171560,"corporation":false,"usgs":false,"family":"Allen","given":"Brian","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":800447,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McAuley, Daniel 0000-0003-3674-6392 dmcauley@usgs.gov","orcid":"https://orcid.org/0000-0003-3674-6392","contributorId":215182,"corporation":false,"usgs":true,"family":"McAuley","given":"Daniel","email":"dmcauley@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":800448,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blomberg, Erik J.","contributorId":17543,"corporation":false,"usgs":false,"family":"Blomberg","given":"Erik","email":"","middleInitial":"J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":800449,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70214091,"text":"sim3461 - 2020 - Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas","interactions":[{"subject":{"id":70214091,"text":"sim3461 - 2020 - Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas","indexId":"sim3461","publicationYear":"2020","noYear":false,"displayTitle":"Geologic Framework and Hydrostratigraphy of the Edwards and Trinity Aquifers Within Northern Medina County, Texas","title":"Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas"},"predicate":"SUPERSEDED_BY","object":{"id":70258397,"text":"sim3526 - 2024 - Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas","indexId":"sim3526","publicationYear":"2024","noYear":false,"title":"Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas"},"id":1}],"supersededBy":{"id":70258397,"text":"sim3526 - 2024 - Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas","indexId":"sim3526","publicationYear":"2024","noYear":false,"title":"Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas"},"lastModifiedDate":"2024-09-20T17:56:40.050301","indexId":"sim3461","displayToPublicDate":"2020-09-24T08:37:02","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3461","displayTitle":"Geologic Framework and Hydrostratigraphy of the Edwards and Trinity Aquifers Within Northern Medina County, Texas","title":"Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas","docAbstract":"The karstic Edwards and Trinity aquifers are classified as major sources of water in south-central Texas by the Texas Water Development Board. During 2018–20 the U.S. Geological Survey, in cooperation with the Edwards Aquifer Authority, mapped and described the geologic framework and hydrostratigraphy of the rocks composing the Edwards and Trinity aquifers in northern Medina County from field observations of the surficial expressions of the rocks. The thicknesses of the mapped lithostratigraphic members and hydrostratigraphic units were also estimated from field observations.
The Cretaceous-age rocks (listed in ascending order) in the study area are part of the Trinity Group (lower and upper members of the Glen Rose Limestone), Edwards Group (Kainer Formation [and its stratigraphic equivalent, the Fort Terrett Formation] and Person Formation), Devils River Limestone, Washita Group (Georgetown Formation, Del Rio Clay, and Buda Limestone), Eagle Ford Group, Austin Group, Taylor Group, and Late Cretaceous igneous intrusive rocks. The groups and formations are composed primarily of relatively thick layers of clays, shales, and limestone. The igneous rocks are coarse-grained ultramafic in composition.
The principal structural feature in northern Medina County is the Balcones fault zone, which is the result of late Oligocene and early Miocene extensional faulting and fracturing resulting from the eastern Edwards Plateau uplift. In the Balcones fault zone, most of the faults in the study area are high-angle to vertical, en echelon, normal faults that are predominately downthrown to the southeast.
Hydrostratigraphically, the rocks exposed in the study area (listed in descending order from land surface as they appear in a stratigraphic column) are igneous, the upper confining unit to the Edwards aquifer, the Edwards aquifer, the upper zone of the Trinity aquifer, and the upper part of the middle zone of the Trinity aquifer. The karstic carbonate Edwards and Trinity aquifers developed as a result of their original depositional history, primary and secondary porosity, diagenesis, fracturing, and faulting. These factors have resulted in development of modified porosity, permeability, and transmissivity within and between the aquifers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3461","collaboration":"Prepared in cooperation with the Edwards Aquifer Authority","usgsCitation":"Clark, A.K., Morris, R.E., and Pedraza, D.E., 2020, Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas: U.S. Geological Survey Scientific Investigations Map 3461, 13 p. pamphlet, 1 pl., scale 1:24,000, https://doi.org/10.3133/sim3461.","productDescription":"Report: vi, 13 p.; Sheet: 48 inches x 36 inches; Data Release","numberOfPages":"23","onlineOnly":"N","ipdsId":"IP-112816","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":378661,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HHMBX8","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Geospatial dataset of the geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas, at 1:24,000 scale"},{"id":378659,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3461/sim3461_pamphlet.pdf","text":"Pamphlet","size":"1.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3461 Pamphlet"},{"id":378658,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3461/coverthb1.jpg"},{"id":378660,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3461/sim3461.pdf","text":"Map sheet","size":"30.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3461"}],"country":"United States","state":"Texas","county":"Medina County","otherGeospatial":"Edwards and Trinity Aquifers","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.46609497070312,\n 29.31514119318728\n ],\n [\n -98.79867553710936,\n 29.31514119318728\n ],\n [\n -98.79867553710936,\n 29.6510621496229\n ],\n [\n -99.46609497070312,\n 29.6510621496229\n ],\n [\n -99.46609497070312,\n 29.31514119318728\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
Geomagnetic perturbations (BGEO) related to magnetospheric ultralow frequency (ULF) waves induce electric fields within the conductive Earth—geoelectric fields (EGEO)—that in turn drive geomagnetically induced currents. Though numerous past studies have examined ULF wave BGEO from a space weather perspective, few studies have linked ULF waves with EGEO. Using recently available magnetotelluric impedance and EGEO measurements in the contiguous United States, we explore the relationship between ULF waves and EGEO. We use satellite, ground‐based radar, BGEO, and EGEO measurements in a case study of a plasmaspheric virtual resonance (PVR), demonstrating that the PVR EGEO has significant spatial variation in contrast to a relatively uniform BGEO, consistent with spatially varying Earth conductivity. We further show ULF wave EGEO measurements during two moderate storms of ∼1 V/km. We use both results to highlight the need for more research characterizing ULF wave EGEO.
Mercury (Hg) has been a contaminant of concern for several decades in South Florida, particularly in the Florida Everglades. The transport and bioavailability of Hg in aquatic systems is intimately linked to dissolved organic carbon (DOC). In aquatic systems, Hg can be converted to methylmercury (MeHg), which is the form of Hg that bioaccumulates in food webs. The bioaccumulation of MeHg poses significant health risks to wildlife and humans. Fish consumption advisories triggered by elevated Hg levels first appeared in the 1980s in South Florida. Multiple structures regulate freshwater distribution to Everglades National Park, including S-12D. This report summarizes seasonal and annual concentration and load data from late September 2013 to April 2017 for the total of (1) filter-passing total mercury (FTHg), (2) filter-passing methylmercury (FMeHg), (3) particulate total mercury (PTHg), (4) particulate methylmercury (PMeHg) and, (5) DOC discharged through control structure S-12D. The loads of Hg fractions and DOC at control structure S-12D were determined by pairing discharge data with constituent concentrations estimated by empirical models based on surrogate in situ water-quality measurements.
Calculated concentrations of DOC ranged from 12.8 milligrams per liter (mg/L) to 27.9 mg/L with a mean of 18.8 mg/L during the study period. Annual loads of DOC ranged from 3,950 tons in 2015 to 10,900 tons in 2016. DOC loads increased linearly with an increase in flow, and the highest monthly DOC load of 1,630 tons was observed in February 2016.
Calculated concentrations of FTHg ranged from 0.35 to 1.55 nanograms per liter (ng/L) with a mean of 0.85 ng/L during the study period. Calculated concentrations of FMeHg ranged from 0.06 ng/L to 0.24 ng/L with a mean of 0.14 ng/L during the study period. Generally, FTHg and FMeHg concentrations were lower during periods of decreased flow and higher during periods of increased flow. Calculated PTHg concentrations ranged from 0.09 ng/L to 4.19 ng/L with a mean of 0.58 ng/L during the study period. Calculated PMeHg concentrations ranged from below the limit of detection <0.01 ng/L to 0.29 ng/L with a mean of 0.03 ng/L during the study period.
Loads of Hg were often zero or lowest from November to May, owing to the lack of flow or low-flow conditions. FTHg and FMeHg loads increased linearly with an increase in flow and typically were highest from June to October. During periods of increasing flow or following changes in gate operations, PTHg and PMeHg constituted a greater percentage of the total Hg load. Annual loads of total Hg (filter-passing and particulate) ranged from 254 grams in 2015 to 658 grams in 2016. FTHg was the predominant contributor to the total Hg load. Information presented herein provides the first assessment of DOC and Hg loads to Everglades National Park through control structure S-12D using continuous in situ measurements of discharge and constituent surrogates and compares the surrogate model approach to loads calculated from monthly sampling. Analysis of calculated and observed loads demonstrates the significance of flow data on calculating constituent loads.
Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Peak ground velocity (PGV) is a commonly used parameter in earthquake ground‐motion models (GMMs) and hazard analyses, because it is closely related to structural damage and felt ground shaking, and is typically measured on broadband seismometers. Here, we demonstrate that strainmeters, which directly measure in situ strain in the bulk rock, can easily be related to ground velocity by a factor of bulk shear‐wave velocity and, thus, can be used to measure strain‐estimated PGV. We demonstrate the parity of velocity to strain utilizing data from borehole strainmeters deployed along the plate boundaries of the west coast of the United States for nine recent
Testing how plant restoration influences animal taxonomic and functional diversity can shift restoration projects beyond mainly plant community considerations. We incorporated multi-trophic interactions into restoration by describing an ongoing functional trait-based restoration experiment in Hawaiian lowland tropical wet forest (Liko Nā Pilina Experiment), where litter arthropods are examined from a functional perspective thereby linking plants and higher trophic levels. We hypothesized that (1) communities with greater plant functional trait diversity would have cascading effects through food webs, increasing animal diversity and network complexity, and (2) increases in animal species and network complexity would be stronger for restoration efforts in plant communities with more complementary functional traits than those with more redundant traits. We examined experimental treatments of planted communities with the same species richness but with different plant functional trait profiles based on (1) rates of expected carbon turnover (slow or moderate), and (2) the similarity of their functional trait measurements (redundant or complementary), as determined by functional dispersion calculations. Initial data on arthropod communities and leaf litter decomposition rates revealed linkages between plant functional traits and arthropod community diversity. Overall, we argue that a more comprehensive evaluation of restoration accounts for both functional diversity and the multi-trophic nature of animal and plant communities. Developing restoration projects based on plant functional traits that influence both plant and invertebrate species provides a new paradigm, and the incorporation of both native and non-native (but non-invasive) plants shows promise in restoring ecosystem function in disturbed lowland tropical forests.
High precision triple oxygen isotope measurements of carbonates can better constrain temperatures and oxygen isotope compositions of seawater through geologic time than 18O/16O measurements alone, but lack of a definitive calibration has hindered progress. In this study, we fluorinated both carbonate and water samples to measure quantitatively the triple oxygen isotope composition of each phase. We compared the oxygen isotope fractionation between carbonate and water for different carbonate materials: calcite synthesized with and without carbonic anhydrase, abiogenic calcite from Devils Hole, and extant biogenic calcite and aragonite of marine origin. We found similar 1000lnα18Occ-wt values for all materials and combined the results with the high temperature experimental data of O'Neil et al. (1969), resulting in the following fractionation equation (T in Kelvins)
Biological conservation often requires an understanding of how environmental conditions affect species occurrence and detection probabilities. We used a hierarchical framework to evaluate these effects for several Appalachian stream fish species of conservation concern: Chrosomus cumberlandensis (BSD; blackside dace), Etheostoma sagitta (CAD; Cumberland arrow darter), and Etheostoma spilotum (KAD; Kentucky arrow darter). Etheostoma susanae (Cumberland darter) also is present in the study area but was too rare to model in this analysis. In this study, conducted by the U.S. Geological Survey in cooperation with the U.S. Fish and Wildlife Service, fish and habitat data were collected from 205 randomly selected stream sites in the upper Cumberland and Kentucky River Basins (120 and 85 sites, respectively) of Kentucky and Tennessee. Sites were sampled with 10 spatial replicates (2 meter x 5 meter electrofishing zones) to enable estimation of detection probabilities and environmental effects. The best models (that is, lowest Akaike information criterion scores) showed the effects of agriculture (negative) on occurrence of BSD and stream conductivity (negative) on occurrence of CAD and KAD. These effects were statistically more important than measures of basin area, elevation, and substrate size. Conductivity and agriculture showed nonlinear effects on species occurrence, and effects of conductivity were more precise above 400 microsiemens per centimeter than below this threshold. Models incorporated detection-level effects of electrofishing time (positive), flow velocity (negative), sand substrate (positive), and gravel/cobble substrate (negative). Models accounting for detection of BSD estimated occupancy rates similar to the observed proportion of occupied sites (0.10), but the best-supported models for CAD and KAD increased expected occupancy by about 4 percent for each species (from 0.17 to 0.21 for CAD and from 0.07 to 0.11 for KAD). Results of this study provide new inferences for modeling stream fish occurrence and detection processes and highlight the importance of continued monitoring and assessment of rare fish species in Appalachian headwater streams.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201100","collaboration":"Prepared in cooperation with U.S. Fish and Wildlife Service","usgsCitation":"Hitt, N.P., Rogers, K.M., Kessler, K., and Macmillan, H., 2020, Modeling occupancy of rare stream fish species in the upper Cumberland and Kentucky River Basins: U.S. Geological Survey Open-File Report 2020–1100, 22 p., https://doi.org/10.3133/ofr20201100.","productDescription":"vi, 22 p.","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-118746","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":378605,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1100/ofr20201100.pdf","text":"Report","size":"2.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1100"},{"id":378604,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1100/coverthb.jpg"}],"country":"United States","state":"Kentucky, Tennessee, Virginia","otherGeospatial":"Cumberland River basin, Kentucky River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.1875,\n 35.88905007936091\n ],\n [\n -81.39770507812499,\n 35.88905007936091\n ],\n [\n -81.39770507812499,\n 38.77121637244273\n ],\n [\n -87.1875,\n 38.77121637244273\n ],\n [\n -87.1875,\n 35.88905007936091\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
The Clean Water Act (CWA) requires States to identify waters that are impaired for designated uses. These waters are published through a State’s §303(d) list. The CWA also requires that a total maximum daily load (TMDL) be completed for each water body to calculate the maximum amount of contaminants that can be present in that water body and still meet water-quality standards. The Mississippi Department of Environmental Quality (MDEQ) uses a statewide monitoring and assessment strategy to collect benthic macroinvertebrate community data to assess the health of streams and rivers and to identify impaired waters. Waters that are found to be impaired based on the macroinvertebrate community data are listed on the Mississippi §303(d) list, and the cause of impairment is listed as “biological impairment.” Although the CWA requires TMDLs to be developed for applicable contaminants identified in the §303(d) list, TMDLs cannot be computed for stream reaches in Mississippi listed for biological impairment because the actual stressors causing the impairment have not yet been determined. The MDEQ and other water-resource managers in Mississippi require a framework for stressor identification in biologically impaired streams and rivers. This report is organized to (1) provide a general overview of biological impairment and stressor identification in stream ecosystems and (2) provide a detailed framework for stressor identification of Mississippi streams that are biologically impaired. The intent is for the framework to reduce subjectivity, provide consistency, and allow for adaptation as the science evolves. The stressor identification framework for Mississippi involves six key steps:
Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
There is an active debate regarding the influence that climate has on the risk of armed conflict, which stems from challenges in assembling unbiased datasets, competing hypotheses on the mechanisms of climate influence, and the difficulty of disentangling direct and indirect climate effects. We use gridded historical non-state conflict records, satellite data, and land surface models in a structural equation modeling approach to uncover the direct and indirect effects of climate on violent conflicts in Africa and the Middle East (ME). We show that climate–conflict linkages in these regions are more complex than previously suggested, with multiple mechanisms at work. Warm temperatures and low rainfall direct effects on conflict risk were stronger than indirect effects through food and water supplies. Warming increases the risk of violence in Africa but unexpectedly decreases this risk in the ME. Furthermore, at the country level, warming decreases the risk of violence in most West African countries. Overall, we find a non-linear response of conflict to warming across countries that depends on the local temperature conditions. We further show that magnitude and sign of the effects largely depend on the scale of analysis and geographical context. These results imply that extreme caution should be exerted when attempting to explain or project local climate–conflict relationships based on a single, generalized theory.
","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/aba97d","usgsCitation":"Helman, D., Zaitchik, B., and Funk, C., 2020, Climate has contrasting direct and indirect effects on armed conflicts: Environmental Research Letters, v. 15, 104017, 12 p., https://doi.org/10.1088/1748-9326/aba97d.","productDescription":"104017, 12 p.","ipdsId":"IP-118530","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":455254,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/aba97d","text":"Publisher Index Page"},{"id":421737,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Africa, Middle East","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 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]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2020-09-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Helman, David","contributorId":330683,"corporation":false,"usgs":false,"family":"Helman","given":"David","affiliations":[{"id":37540,"text":"John Hopkins University","active":true,"usgs":false}],"preferred":false,"id":885582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zaitchik, Benjamin F.","contributorId":330684,"corporation":false,"usgs":false,"family":"Zaitchik","given":"Benjamin F.","affiliations":[{"id":37540,"text":"John Hopkins University","active":true,"usgs":false}],"preferred":false,"id":885583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Funk, Chris 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":167070,"corporation":false,"usgs":true,"family":"Funk","given":"Chris","email":"cfunk@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":885584,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70223247,"text":"70223247 - 2020 - Temporal and spatial changes in Myotis lucifugus acoustic activity before and after white-nose syndrome on Fort Drum Army Installation, New York, USA","interactions":[],"lastModifiedDate":"2021-08-19T16:47:04.818752","indexId":"70223247","displayToPublicDate":"2020-09-20T11:42:49","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":629,"text":"Acta Chiropterologica","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Temporal and spatial changes in Myotis lucifugus acoustic activity before and after white-nose syndrome on Fort Drum Army Installation, New York, USA","title":"Temporal and spatial changes in Myotis lucifugus acoustic activity before and after white-nose syndrome on Fort Drum Army Installation, New York, USA","docAbstract":"Changes to bat distribution and habitat associations at the local to sub-landscape scale in the post white-nose syndrome (WNS) environment have received little attention to date despite being critical information for managers. To better understand the spatial nature of bat population declines, we modelled both activity patterns and occupancy from acoustic surveys for the Myotis lucifugus (little brown bat) on Fort Drum Military Installation in New York, USA over 15 summers (2003–2017) that span the pre-WNS, WNS-advent (2008) and post-WNS periods, using a set of generalized linear mixed models and geospatial analysis. Our best supported model indicated significant differences between years with significant declines in activity post-WNS. M. lucifugus activity was most closely associated with woody wetland habitats over the study period, however, the spatial patterns of high activity areas were variable over years, with the areal extent of these high activity areas decreasing post-WNS. Our best supported occupancy model varied by year. However, the null occupancy model [Ψ(.)] was either competing (within 2 ΔAIC units) or was the best supported model. Meaning that none of our environmental variables seemed to impact occupancy, and when they did, these differences were not significant. There was high disagreement between our relative activity models and predictions compared to our occupancy models, suggesting that geographic spatial scale and the resolution of the data impacts model outcome. Our results indicate that continued acoustic monitoring of bat species in the Northeast to assess ongoing temporal and spatial changes in habitat associations and to provide direction for future mist-netting studies should rely more on relative activity as the metric of choice rather than site occupancy.
","language":"English","publisher":"Museum and Institute of Zoology PAS","doi":"10.3161/15081109ACC2020.22.1.011","usgsCitation":"Ford, W., Nocera, T., Silvis, A., and Dobony, C.A., 2020, Temporal and spatial changes in Myotis lucifugus acoustic activity before and after white-nose syndrome on Fort Drum Army Installation, New York, USA: Acta Chiropterologica, v. 22, no. 1, p. 121-134, https://doi.org/10.3161/15081109ACC2020.22.1.011.","productDescription":"14 p.","startPage":"121","endPage":"134","ipdsId":"IP-101094","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":455261,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10919/102442","text":"External Repository"},{"id":388164,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fort Drum Army Installation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.574951171875,\n 44.006644643819655\n ],\n [\n -75.36895751953125,\n 44.188112606916484\n ],\n [\n -75.56121826171875,\n 44.268804788566165\n ],\n [\n -75.8660888671875,\n 44.05403780323783\n ],\n [\n -75.75897216796875,\n 43.98688630934305\n ],\n [\n -75.574951171875,\n 44.006644643819655\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"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. Mark","email":"wford@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":821520,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nocera, Tomás","contributorId":264425,"corporation":false,"usgs":false,"family":"Nocera","given":"Tomás","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":821521,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Silvis, Alexander","contributorId":264426,"corporation":false,"usgs":false,"family":"Silvis","given":"Alexander","affiliations":[{"id":54472,"text":"RES Inc.","active":true,"usgs":false}],"preferred":false,"id":821522,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dobony, Christopher A.","contributorId":264428,"corporation":false,"usgs":false,"family":"Dobony","given":"Christopher","email":"","middleInitial":"A.","affiliations":[{"id":54473,"text":"Fort Drum Military Installation","active":true,"usgs":false}],"preferred":false,"id":821523,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228508,"text":"70228508 - 2020 - A demographic projection model to support conservation decision making for an endangered snake with limited monitoring data","interactions":[],"lastModifiedDate":"2022-02-11T15:35:55.593402","indexId":"70228508","displayToPublicDate":"2020-09-20T09:28:56","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":774,"text":"Animal Conservation","active":true,"publicationSubtype":{"id":10}},"title":"A demographic projection model to support conservation decision making for an endangered snake with limited monitoring data","docAbstract":"Conservation planning for rare and threatened species is often made more difficult by a lack of research and monitoring data. In such cases, managers may rely on qualitative assessments of species risk that lack explicit acknowledgement of uncertainty. Snakes are a group of conservation concern that are also notoriously difficult to monitor. Here, we demonstrate a quantitative population projection for a data-deficient species, the Puerto Rican boa (Chilabothrus inornatus) using expert knowledge and published information about species life history and threats to persistence. Using this model, we simulated population dynamics over 30 years under four scenarios of future urbanization and found that there was an increased probability of population decline as urbanization rates increased. We conduct a sensitivity analysis to evaluate the sensitivity of outcomes to model inputs, a practice that may also be useful in recovery planning. The sensitivity analyses also provide insight into how the future trajectories would change if the elicited demographic rates are incorrect. Even when data are sparse, quantitative methods can often be used to produce rigorous and reproducible estimates of future status with quantifiable uncertainty.
","language":"English","publisher":"Wiley","doi":"10.1111/acv.12641","usgsCitation":"Tucker, A.M., McGowan, C.P., Mulero Oliveras, E., Angeli, N., and Zegarra, J., 2020, A demographic projection model to support conservation decision making for an endangered snake with limited monitoring data: Animal Conservation, v. 24, no. 2, p. 291-301, https://doi.org/10.1111/acv.12641.","productDescription":"11 p.","startPage":"291","endPage":"301","ipdsId":"IP-117213","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto 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M.","contributorId":276002,"corporation":false,"usgs":false,"family":"Tucker","given":"A.","email":"","middleInitial":"M.","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":834463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":167162,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor","email":"cmcgowan@usgs.gov","middleInitial":"P.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":834464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mulero Oliveras, E.","contributorId":276003,"corporation":false,"usgs":false,"family":"Mulero Oliveras","given":"E.","email":"","affiliations":[{"id":38462,"text":"University of Puerto Rico","active":true,"usgs":false}],"preferred":false,"id":834465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Angeli, N.F.","contributorId":276004,"corporation":false,"usgs":false,"family":"Angeli","given":"N.F.","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":834466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zegarra, J.P.","contributorId":242909,"corporation":false,"usgs":false,"family":"Zegarra","given":"J.P.","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":834467,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70226676,"text":"70226676 - 2020 - Neonicotinoid insecticide concentrations in agricultural wetlands and associations with aquatic invertebrate communities","interactions":[],"lastModifiedDate":"2021-12-03T13:03:38.319596","indexId":"70226676","displayToPublicDate":"2020-09-20T07:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":682,"text":"Agriculture, Ecosystems and Environment","active":true,"publicationSubtype":{"id":10}},"title":"Neonicotinoid insecticide concentrations in agricultural wetlands and associations with aquatic invertebrate communities","docAbstract":"Neonicotinoids are considered a superior insecticide for agricultural pest management, although their impacts on non-target insects is a rising concern. Aside from laboratory and mesocosm studies, limited research has been directed towards the role neonicotinoids may have in structuring aquatic invertebrate communities in field settings. Therefore, we simultaneously collected aquatic invertebrate and surface water samples from 26 wetlands within a highly modified agricultural landscape of Nebraska’s Rainwater Basin during spring 2015. Water samples were tested for six different neonicotinoids, nutrients, and physical properties. Trace levels of clothianidin and imidacloprid were the only neonicotinoids detected, occurring in 85% and 15%, respectively, of wetlands sampled. All measurements for clothianidin and imidacloprid were below chronic toxicity benchmarks set by the United States Environmental Protection Agency. Neonicotinoid concentrations were significantly lower (W26, 0.05 = 42.5) at wetlands with vegetative buffer strips >50 m wide compared to wetlands with vegetative buffers strips <50 m. Although neonicotinoids were below benchmark concentrations proposed by government regulations, a significant negative association between neonicotinoid concentrations and aquatic invertebrate biomass was observed across all wetlands studied (Parameter Estimate = -0.031; SE = 0.014).