The presence of vitrinite in sedimentary rocks of post-Silurian age allows its reflectance to be used to estimate the thermal maturation of organic matter in petroleum systems. Increasing reflectance of vitrinite, which is primarily driven by aromaticity, depends primarily on the time and temperature attributes of its evolutionary pathway. This study evaluated carbonaceous shales proximal to coal measures and coal samples via isothermal hydrous pyrolysis (HP) to compare differences in the maturation pathways of vitrinite. Sample residues were analysed via vitrinite reflectance (VRo), geochemical screening tests (organic carbon and programmed temperature pyrolysis), and infrared spectroscopy. The study included samples from Indian and North American basins, to observe differences in vitrinite evolution with respect to enclosing mineral matrix, starting degree of aromaticity, organic matter types, stratigraphic age, and depositional environment. The organic content of HP residues shows an intuitive response to the thermal stress of HP, e.g., a general depletion of total organic carbon (TOC) content, pyrolyzate (S2), and hydrogen index with increasing HP temperature. Infrared proxies including C-factor and CH2/CH3 generally decrease with increasing thermal maturity indicating loss of O via CO2 generation and the thermal cracking of aliphatic organic matter. Tmax, production index (PI), and VRo show intuitive increasing values with respect to HP temperature. The least mature sample (0.48 ± 0.05% VRo) generally experienced the maximum change in these parameters during maturation, whereas the most mature sample (0.99 ± 0.06% VRo) generally showed the least change. This observation is consistent with higher kinetic barriers to reaction in more aromatic vitrinite which contains higher bond dissociation energies. Devolatilization of vitrinite during HP causes formation of gas evacuation vacuoles and contraction cracks in the vitrinite grains of both coal and carbonaceous shale. Similarities in vitrinite response to HP between coal and carbonaceous shale suggest that thermal evolution of the vitrinite maceral is principally controlled by inherent rate-limiting kinetic parameters related to its molecular structure. Whereas, the stratigraphic age, sedimentary environment, surrounding organic matter, lithology, and catalysis by mineral composition have less effect. To further improve our understanding of vitrinite aromatization and kinetic parameters, future studies of vitrinite reflectance thermal evolution with temperature should include coal and carbonaceous shale from the same stratigraphic section and extant woody tissue from modern vascular plants.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2022.104044","usgsCitation":"Mishra, D.K., Hackley, P.C., Jubb, A., Sanders, M.M., Agrawal, S., and Varma, A.K., 2022, Maturation study of vitrinite in carbonaceous shales and coals: Insights from hydrous pyrolysis: International Journal of Coal Geology, v. 259, 104044, 13 p., https://doi.org/10.1016/j.coal.2022.104044.","productDescription":"104044, 13 p.","ipdsId":"IP-138029","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":408530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"259","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mishra, Divya K.","contributorId":290218,"corporation":false,"usgs":false,"family":"Mishra","given":"Divya","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":855038,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":855039,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jubb, Aaron M. 0000-0001-6875-1079","orcid":"https://orcid.org/0000-0001-6875-1079","contributorId":201978,"corporation":false,"usgs":true,"family":"Jubb","given":"Aaron M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":855040,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sanders, Margaret M. 0000-0003-3505-874X","orcid":"https://orcid.org/0000-0003-3505-874X","contributorId":248709,"corporation":false,"usgs":true,"family":"Sanders","given":"Margaret","email":"","middleInitial":"M.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":855041,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Agrawal, Shailesh","contributorId":261453,"corporation":false,"usgs":false,"family":"Agrawal","given":"Shailesh","email":"","affiliations":[],"preferred":false,"id":855042,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Varma, Atul K.","contributorId":290219,"corporation":false,"usgs":false,"family":"Varma","given":"Atul","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":855043,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70254718,"text":"70254718 - 2022 - Reproductive indices and observations of mass ovarian follicular atresia in hatchery-origin pallid sturgeon","interactions":[],"lastModifiedDate":"2024-06-10T16:05:35.788952","indexId":"70254718","displayToPublicDate":"2022-06-17T10:59:15","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2166,"text":"Journal of Applied Ichthyology","active":true,"publicationSubtype":{"id":10}},"title":"Reproductive indices and observations of mass ovarian follicular atresia in hatchery-origin pallid sturgeon","docAbstract":"The Pallid Sturgeon (Scaphirhynchus albus) Conservation Propagation and Stocking Program began stocking in the Missouri River above Fort Peck Reservoir in 1998 with 1997-year-class pallid sturgeon. Within the 1997-year class, all hatchery-origin pallid sturgeon females that reached reproductive maturation by 2016 underwent mass ovarian follicular atresia. Using combined historical and contemporary data, we described the spawning periodicity for female and male pallid sturgeon, characterized age- and size-at-first spawning, and evaluated what proportion of females experience mass ovarian follicular atresia during the first and subsequent reproductive cycles. Pallid sturgeon reached their first reproductive cycle at older ages and larger sizes than described for other populations. Females were functionally and physiologically capable of spawning at 21 years and males at 15 years. Immature pallid sturgeon as old as 20 years were documented. We found that more female pallid sturgeon underwent mass ovarian follicular atresia during the presumed-first reproductive cycle or known-first reproductive cycle than females during subsequent reproductive cycles (62.5% compared to 33.3%) indicating that effects related to reproductive maturation may be occurring. Nonetheless, mass ovarian follicular atresia appears to also occur for reasons not related to reproductive maturation. Females had biennial reproductive cycles, and males had annual and biennial reproductive cycles. Population models should account for females undergoing mass ovarian follicular atresia in their first reproductive cycle and subsequent cycles thereby increasing the age at first-successful spawning and reducing the estimated size of the spawning stock.
","language":"English","publisher":"Wiley","doi":"10.1111/jai.14339","usgsCitation":"Cox, T., Guy, C.S., Holmquist, L., and Webb, M., 2022, Reproductive indices and observations of mass ovarian follicular atresia in hatchery-origin pallid sturgeon: Journal of Applied Ichthyology, v. 38, p. 391-402, https://doi.org/10.1111/jai.14339.","productDescription":"12 p.","startPage":"391","endPage":"402","ipdsId":"IP-137205","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":447396,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jai.14339","text":"Publisher Index Page"},{"id":429772,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","noUsgsAuthors":false,"publicationDate":"2022-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Cox, Tanner L.","contributorId":337305,"corporation":false,"usgs":false,"family":"Cox","given":"Tanner L.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":902340,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902341,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holmquist, Luke M.","contributorId":337306,"corporation":false,"usgs":false,"family":"Holmquist","given":"Luke M.","affiliations":[{"id":37431,"text":"Montana Fish, Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":902342,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Webb, Molly A. H.","contributorId":337308,"corporation":false,"usgs":false,"family":"Webb","given":"Molly A. H.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":902343,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70232218,"text":"sir20215143 - 2022 - Application of a soil-water-balance model to estimate annual groundwater recharge for Long Island, New York, 1900–2019","interactions":[],"lastModifiedDate":"2026-04-08T16:38:21.182332","indexId":"sir20215143","displayToPublicDate":"2022-06-17T10:44:25","publicationYear":"2022","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":"2021-5143","displayTitle":"Application of a Soil-Water-Balance Model to Estimate Annual Groundwater Recharge for Long Island, New York, 1900–2019","title":"Application of a soil-water-balance model to estimate annual groundwater recharge for Long Island, New York, 1900–2019","docAbstract":"A soil-water-balance (SWB) model was developed for Long Island, New York, to estimate the potential amount of annual groundwater recharge to the Long Island aquifer system from 1900 to 2019. The SWB model program is a computer code based on a modified Thornthwaite-Mather SWB approach and uses spatially and temporally distributed meteorological, land-cover, and soil properties as input to compute potential daily groundwater recharge. Simulated outputs indicate that island-wide potential groundwater recharge trends, as a percentage of precipitation, have increased approximately 3 percent during the 120-year period. The simulated results account for both climatic and land-cover changes that have occurred during the period. A change from undeveloped (forested land cover) to low- and medium-density residential land cover or land use increased potential groundwater recharge because of a decrease in evapotranspiration. During the 30-year period from 1900 to 1930, the simulated potential average groundwater recharge rate on Long Island was estimated to be 18.50 inches per year (in/yr), or a total of 1,243 million gallons per day, during the 30-year period from 1985 to 2015, the simulated potential average groundwater recharge rate estimate increased to 20.73 in/yr (a total of around 1,393 million gallons per day).
During the 1900–2019 simulation period, the potential average annual groundwater recharge rate was about 19.24 in/yr. The data for that period included values for a 3-year meteorological drought from 1963 to 1965, where the mean precipitation was about 26.5 percent lower than the long-term average of 46.7 in/yr, and the potential groundwater recharge rate was about 12.3 in/yr. During a 3-year wet period from 1982 to 1984, where mean precipitation was about 19.6 percent higher than the long-term average, the estimated potential groundwater recharge rate was about 26.8 in/yr.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215143","usgsCitation":"Finkelstein, J.S., Monti, J., Jr., Masterson, J.P., and Walter, D.A., 2022, Application of a soil-water-balance model to estimate annual groundwater recharge for Long Island, New York, 1900–2019: U.S. Geological Survey Scientific Investigations Report 2021–5143, 25 p., https://doi.org/10.3133/sir20215143.","productDescription":"Report: v, 25 p.; 2 Data Releases","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-103053","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":435800,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93Z8Y8L","text":"USGS data release","linkHelpText":"Soil-water-balance model archive for Long Island, NY, 1900-2019"},{"id":402201,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V2NMUB","text":"USGS data release","linkHelpText":"Soil-water-balance groundwater recharge model results for Long Island, NY, 1900-2019"},{"id":402197,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5143/coverthb.jpg"},{"id":402196,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5143/sir20215143.pdf","text":"Report","size":"5.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5143"},{"id":402199,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5143/images/"},{"id":402217,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20215143/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":402198,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5143/sir20215143.XML"},{"id":402200,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94OLK6Z","text":"USGS data release","linkHelpText":"Soil-water-balance model archive for Long Island, NY, 1900-2019"},{"id":502287,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113197.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New York","otherGeospatial":"Long Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.036865234375,\n 40.55554790286311\n ],\n [\n -73.1744384765625,\n 40.56806745430726\n ],\n [\n -71.795654296875,\n 41.03378713521864\n ],\n [\n -72.2186279296875,\n 41.21998578493921\n ],\n [\n -72.6800537109375,\n 41.02135510866602\n ],\n [\n -73.10302734375,\n 40.98819156349393\n ],\n [\n -73.2513427734375,\n 40.93426521177941\n ],\n [\n -73.5369873046875,\n 40.95501133048621\n ],\n [\n -73.7896728515625,\n 40.8595252289932\n ],\n [\n -73.93798828125,\n 40.763901280945866\n ],\n [\n -74.036865234375,\n 40.66397287638688\n ],\n [\n -74.036865234375,\n 40.55554790286311\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
In densely populated coastal areas with sea-level rise (SLR), protecting the shorelines against erosion due to the wave impact is crucial. Along with many engineered structures like seawalls and breakwaters, there are also green structures like constructed oyster reefs (CORs) that can not only attenuate the incident waves but also grow and maintain pace with SLR. However, there is a lack of data and understanding of the long-term wave attenuation capacity of the living shoreline structures under SLR. In this study, we used the phase-resolving Boussinesq model, FUNWAVE-TVD, to examine the hydrodynamics including wave height and wave-induced currents around the CORs in the Gandys Beach living shoreline project area in the upper Delaware Bay, United States. Waves were measured at six locations (offshore to onshore, with and without CORs) in the Gandys Beach living shoreline project area for two winter months, during which four nor’easters occurred. We selected three cases that represent prevailing wind, wave, and tide conditions to examine the fine spatial and temporal changes in wave height and current velocity by the construction of the reefs. Wave heights and wave energy spectra generated from FUNWAVE-TVD were then validated with field observations. It is found that FUNWAVE-TVD is capable of simulating waves and associated hydrodynamic processes that interact with CORs. The model results show that wave attenuation rates vary with the incident wave properties and water depth, and wave-induced circulation patterns are affected by the CORs. The wave attenuation capacity of CORs over the next 100 years was simulated with the incorporation of the oyster reef optimal growth zone. Our study found that sustainable wave attenuation capacity can only be achieved when suitable habitat for COR is provided, thus it can vertically grow with SLR. Suitable habitat includes optimal intertidal inundation duration, current velocity for larval transport and settlement, on-reef oyster survival and growth, and other environmental conditions including salinity, temperature, and nutrient availability. Furthermore, the model results suggest that it would take CORs approximately 9 years after construction to reach and maintain the maximum wave attenuation capacity in sustainable living shorelines.
The Salton Trough (southeastern California, USA) is the northernmost transtensional stepover of the Gulf of California oblique-divergent plate boundary and is also where the southern terminus of the San Andreas fault occurs. Until recently, the distribution of active faults in and around the Salton Sea and their displacement histories were largely unknown. Subbottom CHIRP (compressed high-intensity radar pulse) surveys in the Salton Sea are used to develop a seismic facies model for ancient Lake Cahuilla deposits, a detailed map of submerged active faults, and reconstructed fault displacement histories during the late Holocene. We observe as many as fourteen Lake Cahuilla sequences in the Salton Sea (last ~3 k.y.) and develop a chronostratigraphic framework for the last six sequences (last ~1200 yr) by integrating CHIRP data and cone penetrometer logs with radiocarbon-dated stratigraphy at an onshore paleoseismic site. The Salton Sea contains northern and southern subbasins that appear to be separated by a tectonic hinge zone, and a subsidence signal across hinge-zone faults of 6–9 mm/yr (since ca. A.D. 940) increases toward the south to >15 mm/yr. The faults mapped to the south of the hinge zone appear to accommodate transtension within the San Andreas–Imperial fault stepover. We identify 8–15 distinct growth events across hinge-zone faults, meaning growth occurred at least once every 100 yr since Lake Cahuilla sedimentation began. Several faults offset the top of the most recent Lake Cahuilla highstand deposits, and at least two faults have offset the Salton Sea flood deposits. Active faults and folds were also mapped to a limited extent within the northern subbasin and display growth, but their kinematics and rupture histories require further study. The broad distribution of active faulting suggests that strain between the San Andreas, San Jacinto, and Imperial faults is highly distributed, thus discrepancies between geologic and geodetic slip-rate estimates from these major fault systems are to be expected.
Empirical evidence demonstrates that lakes and reservoirs are warming across the globe. Consequently, there is an increased need to project future changes in lake thermal structure and resulting changes in lake biogeochemistry in order to plan for the likely impacts. Previous studies of the impacts of climate change on lakes have often relied on a single model forced with limited scenario-driven projections of future climate for a relatively small number of lakes. As a result, our understanding of the effects of climate change on lakes is fragmentary, based on scattered studies using different data sources and modelling protocols, and mainly focused on individual lakes or lake regions. This has precluded identification of the main impacts of climate change on lakes at global and regional scales and has likely contributed to the lack of lake water quality considerations in policy-relevant documents, such as the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC). Here, we describe a simulation protocol developed by the Lake Sector of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) for simulating climate change impacts on lakes using an ensemble of lake models and climate change scenarios for ISIMIP phases 2 and 3. The protocol prescribes lake simulations driven by climate forcing from gridded observations and different Earth system models under various representative greenhouse gas concentration pathways (RCPs), all consistently bias-corrected on a 0.5∘ × 0.5∘ global grid. In ISIMIP phase 2, 11 lake models were forced with these data to project the thermal structure of 62 well-studied lakes where data were available for calibration under historical conditions, and using uncalibrated models for 17 500 lakes defined for all global grid cells containing lakes. In ISIMIP phase 3, this approach was expanded to consider more lakes, more models, and more processes. The ISIMIP Lake Sector is the largest international effort to project future water temperature, thermal structure, and ice phenology of lakes at local and global scales and paves the way for future simulations of the impacts of climate change on water quality and biogeochemistry in lakes.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/gmd-15-4597-2022","usgsCitation":"Golub, M., Thiery, W., Marce, R., Pierson, D., Vanderkelen, I., Mercado-Bettin, D., Woolway, R., Grant, L., Jennings, E., Kraemer, B., Schewe, J., Zhao, F., Frieler, K., Mengel, M., Bogomolov, V.Y., Bouffard, D., Cote, M., Couture, R., Debolskiy, A.V., Droppers, B., Gal, G., Guo, M., Janssen, A.B., Kirillin, G., Ladwig, R., Magee, M., Moore, T., Perroud, M., Piccolroaz, S., Raaman Vinnea, L., Schmid, M., Shatwell, T., Stepanenko, V.M., Tan, Z., Woodward, B., Yao, H., Adrian, R., Allan, M., Anneville, O., Arvola, L., Atkins, K., Boegman, L., Carey, C.C., Christianson, K., de Eyto, E., DeGasperi, C.L., Grechushnikova, M., Hejzlar, J., Joehnk, K., Jones, I.D., Laas, A., MacKay, E.B., Mammarella, I., Markensten, H., McBride, C.G., Özkundakci, D., Potes, M., Rinke, K., Robertson, D., Rusak, J.A., Salgado, R., van der Linden, L., Verburg, P., Wain, D., Ward, N.K., Wollrab, S., and Zdorovennova, G., 2022, A framework for ensemble modelling of climate change impacts on lakes worldwide: The ISIMIP lake sector.: Geoscientific Model Development, v. 15, p. 4297-4623, https://doi.org/10.5194/gmd-15-4597-2022.","productDescription":"27 p.","startPage":"4297","endPage":"4623","ipdsId":"IP-136556","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":447420,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-15-4597-2022","text":"Publisher Index Page"},{"id":407955,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","noUsgsAuthors":false,"publicationDate":"2022-06-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Golub, Malgorzata","contributorId":297257,"corporation":false,"usgs":false,"family":"Golub","given":"Malgorzata","email":"","affiliations":[{"id":35850,"text":"Uppsala University, Sweden","active":true,"usgs":false}],"preferred":false,"id":853719,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thiery, Wim","contributorId":223158,"corporation":false,"usgs":false,"family":"Thiery","given":"Wim","email":"","affiliations":[],"preferred":false,"id":853720,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marce, Rafael","contributorId":297259,"corporation":false,"usgs":false,"family":"Marce","given":"Rafael","email":"","affiliations":[{"id":64329,"text":"Catalan Institute for Water Research (ICRA), Girona, Spain","active":true,"usgs":false}],"preferred":false,"id":853721,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pierson, Don","contributorId":194465,"corporation":false,"usgs":false,"family":"Pierson","given":"Don","email":"","affiliations":[],"preferred":false,"id":853722,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vanderkelen, Inne","contributorId":297260,"corporation":false,"usgs":false,"family":"Vanderkelen","given":"Inne","email":"","affiliations":[{"id":64331,"text":"Vrije Universiteit Brussel, Department of Hydrology and Hydraulic Engineering, Brussels, Belgium","active":true,"usgs":false}],"preferred":false,"id":853723,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mercado-Bettin, Daniel","contributorId":297261,"corporation":false,"usgs":false,"family":"Mercado-Bettin","given":"Daniel","affiliations":[{"id":64329,"text":"Catalan Institute for Water Research (ICRA), Girona, Spain","active":true,"usgs":false}],"preferred":false,"id":853724,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Woolway, R. 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recording units, although cost-effective, provides imperfect knowledge about species presence. Summertime bat acoustic surveys in North America exemplify the challenges with characterizing sources of uncertainty: observation error, inability to census populations, and natural stochastic variation. Statistical uncertainty, if not considered thoroughly, hampers determining rare species presence accurately and/or estimating rangewide status and trends with suitable precision. Bat acoustic data are processed using an automated workflow in which proprietary or open-source algorithms assign a species label to each recorded high-frequency echolocation sequence. A false-negative occurs, if a species is actually present but not recorded and/or all recordings from the species are of such poor quality that a correct species identity cannot be assigned to any observation. False positives for a focal species are a direct result of the presence and incorrect identification of a recording from another species. We compare four analytical approaches in terms of parameter estimation and their resulting (in)correct decisions regarding species presence or absence using realistic data-generating scenarios for bat acoustic data within a simulation study. The current standard for deciding species presence or absence uses a multinomial likelihood-ratio test p value (maximum likelihood estimate [MLE]-metric) that accounts for known species misidentifications, but not imperfect detection and only returns a binary outcome (evidence of presence or not). We found that the MLE-metric had estimated median correct decisions less than 60% for presence and greater than 85% for absence. Alternatively, a multispecies count detection model was equivalent to or better than the MLE-metric for correct claims of rare species presence or absence using the posterior probability a species was present at a site and, importantly, provided unbiased estimates of relative activity and probability of occurrence, creating opportunities for reducing posterior uncertainty through the inclusion of meaningful covariates. Single-species occupancy models with and without false-positive detections removed were insufficient for determining local presence because of substantially biased occurrence and detection probabilities. We propose solutions to potential barriers for integrating local, short-term and rangewide, long-term acoustic surveys within a cohesive statistical framework that facilitates determining local species presence with uncertainty concurrent with estimating species–environment relationships.
For agricultural areas facing water scarcity, sustainable water use policy relies on irrigation information that is timely and at a high resolution, but existing publicly available water use data are often insufficient for monitoring compliance or understanding the influence of policy on individual farmer decisions. This study attempts to fill this data gap by using remote sensing to map annual irrigation quantity at the field-scale within the central Ogallala aquifer region of the United States. We compiled in situ annual irrigation volume data at the field scale in the Republican River Basin of Colorado for 2015–2018 and at the Public Land Survey System (PLSS) section scale in western Kansas for 2000–2016, which served as reference data in random forest models that relied on Landsat-based actual evapotranspiration from the Operational Simplified Surface Energy Balance model (SSEBop) along with maps of irrigated area, Landsat spectral indices, climate, soils, and derived hydrologic variables. The models explained 87% of the variability in irrigation volume in Colorado and 75% in Kansas, but accuracy declined when transferring the models in spatial cross-validation (Colorado R2 =0.81; Kansas R2 =0.51) and temporal cross-validation (Colorado R2 =0.82; Kansas R2 =0.68). Predicted annual totals of irrigation volume in western Kansas had a mean absolute error of 11.9%, which was slightly higher than the average annual change of 11%. Use of predicted irrigation maps also lead to an underestimated effect size for a water use restriction policy in Kansas. These results indicate that field- and section-scale irrigation can be mapped with reasonable accuracy within a region and time period that has adequate sample data, but that methods may need to be improved for applying the models more broadly in areas that lack extensive in situ irrigation data to support further research on water use and aid in structuring policy.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.agwat.2022.107764","usgsCitation":"Filippelli, S.S., Sloggy, M.R., Vogeler, J.C., Manning, D.T., Goemans, C., and Senay, G.B., 2022, Remote sensing of field-scale irrigation withdrawals in the central Ogallala aquifer region: Agricultural Water Management, v. 271, 107764, 15 p., https://doi.org/10.1016/j.agwat.2022.107764.","productDescription":"107764, 15 p.","ipdsId":"IP-137832","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":488115,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.agwat.2022.107764","text":"Publisher Index Page"},{"id":428798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado Kansas","otherGeospatial":"Ogallala aquifer, Republican River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -102.00825131829713,\n 36.98969791337646\n ],\n [\n -97.51352205922755,\n 36.9837502608661\n ],\n [\n -97.3406085961385,\n 38.44391430535899\n ],\n [\n -98.0932074623356,\n 38.87773029390084\n ],\n [\n -99.65122819650178,\n 39.098871590431884\n ],\n [\n -99.26469253047271,\n 40.0142028593921\n ],\n [\n -102.06717715371995,\n 40.032435593038315\n ],\n [\n -102.11261804171953,\n 40.992555768008174\n ],\n [\n -104.06597899342937,\n 40.93187765306061\n ],\n [\n -104.48051561524214,\n 39.43819239944247\n ],\n [\n -103.69918549158801,\n 38.5715258326463\n ],\n [\n -102.64452864991789,\n 38.27521479596666\n ],\n [\n -102.4653590264147,\n 36.967066532161525\n ],\n [\n -102.00825131829713,\n 36.98969791337646\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"271","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Filippelli, Steven S 0000-0001-7291-0888","orcid":"https://orcid.org/0000-0001-7291-0888","contributorId":336733,"corporation":false,"usgs":false,"family":"Filippelli","given":"Steven","email":"","middleInitial":"S","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":900929,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sloggy, Matthew R 0000-0001-5129-0755","orcid":"https://orcid.org/0000-0001-5129-0755","contributorId":336734,"corporation":false,"usgs":false,"family":"Sloggy","given":"Matthew","email":"","middleInitial":"R","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":900930,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vogeler, Jody C.","contributorId":264796,"corporation":false,"usgs":false,"family":"Vogeler","given":"Jody","email":"","middleInitial":"C.","affiliations":[{"id":54555,"text":"umn","active":true,"usgs":false}],"preferred":false,"id":900931,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Manning, Dale T 0000-0001-6465-5530","orcid":"https://orcid.org/0000-0001-6465-5530","contributorId":336735,"corporation":false,"usgs":false,"family":"Manning","given":"Dale","email":"","middleInitial":"T","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":900932,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goemans, Christopher 0000-0003-4930-4278","orcid":"https://orcid.org/0000-0003-4930-4278","contributorId":336736,"corporation":false,"usgs":false,"family":"Goemans","given":"Christopher","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":900933,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":900934,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70232182,"text":"ofr20221050 - 2022 - Implementation plan of the National Cooperative Geologic Mapping Program strategy — Appalachian Piedmont and Blue Ridge Provinces","interactions":[],"lastModifiedDate":"2022-09-27T13:49:52.6265","indexId":"ofr20221050","displayToPublicDate":"2022-06-14T17:20:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1050","displayTitle":"Implementation Plan of the National Cooperative Geologic Mapping Program Strategy — Appalachian Piedmont and Blue Ridge Provinces","title":"Implementation plan of the National Cooperative Geologic Mapping Program strategy — Appalachian Piedmont and Blue Ridge Provinces","docAbstract":"The National Cooperative Geologic Mapping Program is publishing a strategic plan titled “Renewing the National Cooperative Geologic Mapping Program as the Nation’s Authoritative Source for Modern Geologic Knowledge.” The plan provides a vision, mission, and goals for the program for the years 2020–30:
Director, Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 21092
Agent-based methods allow for defining simple rules that generate complex group behaviors. The governing rules of such models are typically set a priori, and parameters are tuned from observed behavior trajectories. Instead of making simplifying assumptions across all anticipated scenarios, inverse reinforcement learning provides inference on the short-term (local) rules governing long-term behavior policies by using properties of a Markov decision process. We use the computationally efficient linearly-solvable Markov decision process to learn the local rules governing collective movement for a simulation of the selfpropelled-particle (SPP) model and a data application for a captive guppy population. The estimation of the behavioral decision costs is done in a Bayesian framework with basis function smoothing. We recover the true costs in the SPP simulation and find the guppies value collective movement more than targeted movement toward shelter.
Biological invasions represent an important and unique case of ecological transformation that can strongly influence species and entire ecosystems. Challenges in managing invasions arise on multiple fronts, ranging from diverse and often divergent values associated with native and introduced species, logistical constraints, and transformation via other change agents (e.g., climate and land-use change). We address biological invasions considering the Resist-Accept-Direct (RAD) framework for addressing ecological transformation. Because RAD is focused on decisions, we address both social and ecological factors that influence preferences for decision alternatives. We address social factors first as these can constrain the range of alternatives considered in an ecological context. Next, we address ecological dynamics by modeling trajectories from RAD alternatives in a two-species scenario involving impacts of introduced brook trout (Salvelinus fontinalis) on native bull trout (S. confluentus). Results reveal that decision alternatives aligned with each of the major components of RAD can produce positive outcomes. In a management context, these findings highlight the value of investing in early engagement to fully identify decision alternatives, formalizing models of system dynamics to understand ecological trajectories, and applying this knowledge to set the stage for longer term efforts to address biological invasions.
Many turtle species have temperature-dependent sex determination (TSD), raising the prospect that climate change could impact population dynamics by altering sex ratios. Understanding how climate change will affect populations of animals with TSD requires a reliable and minimally invasive method of identifying the sexes of young individuals. This determination is challenging in many turtles, which often lack conspicuous external sexual dimorphism until years after hatching. Here, we explore four alternatives for sexing three age classes of captive-reared young gopher tortoises (Gopherus polyphemus), a terrestrial turtle of conservation concern native to the southeastern United States: (1) naive testosterone levels, (2) testosterone levels following a follicle stimulating hormone (FSH) challenge, (3) linear morphological measurements, and (4) geometric morphometrics. Unlike some other turtle species, male and female neonatal gopher tortoises have overlapping naive testosterone concentration distributions, justifying more complicated methods. We found that sex of neonates (<7 days old) is best predicted by a “random forest” machine learning model with naive testosterone levels and morphological measurements (8% out-of-bag error). Sex of hatchlings (4–8 months old) was predicted with 11% error using a simple threshold on naive testosterone levels, or with 4% error using a simple threshold on post-FSH testosterone levels. Sex of juveniles (approximately 3.5 years old) was perfectly predicted using a simple threshold on naive testosterone levels. Sexing hatchlings at >4 months of age is the easiest and most reliable non-surgical method for sex identification. Given access to a rearing facility and equipment to perform hormone assays, these methods have the potential to supplant laparoscopic surgery as the method of choice for sexing young gopher tortoises.
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Kevin J.","contributorId":348329,"corporation":false,"usgs":false,"family":"Loope","given":"Kevin J.","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":923369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rostal, David C.","contributorId":348330,"corporation":false,"usgs":false,"family":"Rostal","given":"David C.","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":923370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walden, Margarete A.","contributorId":348331,"corporation":false,"usgs":false,"family":"Walden","given":"Margarete A.","affiliations":[{"id":83335,"text":"University of Nevada–Reno","active":true,"usgs":false}],"preferred":false,"id":923371,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shoemaker, Kevin T.","contributorId":348332,"corporation":false,"usgs":false,"family":"Shoemaker","given":"Kevin T.","affiliations":[{"id":83335,"text":"University of Nevada–Reno","active":true,"usgs":false}],"preferred":false,"id":923372,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hunter, Elizabeth Ann 0000-0003-4710-167X","orcid":"https://orcid.org/0000-0003-4710-167X","contributorId":288535,"corporation":false,"usgs":true,"family":"Hunter","given":"Elizabeth","email":"","middleInitial":"Ann","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923373,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70232202,"text":"70232202 - 2022 - How do accuracy and model agreement vary with versioning, scale, and landscape heterogeneity for satellite-derived vegetation maps in sagebrush steppe?","interactions":[],"lastModifiedDate":"2022-06-14T13:08:00.238472","indexId":"70232202","displayToPublicDate":"2022-06-13T11:00:15","publicationYear":"2022","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":"How do accuracy and model agreement vary with versioning, scale, and landscape heterogeneity for satellite-derived vegetation maps in sagebrush steppe?","docAbstract":"Maps of the distribution and abundance of dominant plants derived from satellite data are essential for ecological research and management, particularly in the vast semiarid shrub-steppe. Appropriate application of these maps requires an understanding of model accuracy and precision, and how it might vary across space, time, and different vegetation types. For a 113 k Ha burn area, we compared modeled maps of different vegetation cover types created from satellite data to ‘benchmark” models based on intensive field sampling (~1500-2000 plots resampled annually for 5 years) for three new satellite-derived models: USDA Rangeland Analysis Platform (RAP), the USGS Rangeland Condition Monitoring Assessment and Projection (RCMAP), and USGS fractional estimate of exotic annual grass cover (USGS-fractional-EAG). We assessed out-of-sample point accuracy and asked if and how accuracy changed each year due to vegetation shifts, new images, and model improvements (i.e. model versions). We also assessed how map agreement between satellite-based and field-based models changed with scale of application, topography, and time since fire.
Accuracy and map agreement varied considerably among the vegetation types and across time and space (r2 ranging from 0 to 0.53), and some of the variability was predictable. All models tended to over or underestimate cover when field-measured cover was relatively low or high, respectively, i.e. a “false moderating effect”. Accuracy was greater and improved with newer versions of RAP (+0.05 to 0.29 r2) compared to RCMAP and USGS fractional model estimates, and in some cases was greater than field-based models. Variability in map agreement tended to decrease with larger areas sampled (particularly in areas >12 km), and this scale dependency was more evident in RAP and USGS-fractional-EAG models. Creating a “fair” basis for comparison of spatial models of low-statured semiarid vegetation derived from satellite compared to field data is not trivial because scaling the field data to the scale of large satellite pixels (or downscaling satellite-based models to field scale) requires modeling and associated model uncertainty. Accuracy can vary considerably and understanding the variation can help guide application of the models to the appropriate time, place, and variables.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2022.108935","usgsCitation":"Applestein, C., and Germino, M., 2022, How do accuracy and model agreement vary with versioning, scale, and landscape heterogeneity for satellite-derived vegetation maps in sagebrush steppe?: Ecological Indicators, v. 139, 108935, 11 p., https://doi.org/10.1016/j.ecolind.2022.108935.","productDescription":"108935, 11 p.","ipdsId":"IP-138386","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":447436,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2022.108935","text":"Publisher Index Page"},{"id":435803,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P8G8XM","text":"USGS data release","linkHelpText":"Modelled functional group vegetation cover from 2016 to 2020 on the Soda Wildfire"},{"id":402095,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.05883789062501,\n 42.391008609205045\n ],\n [\n -114.730224609375,\n 42.391008609205045\n ],\n [\n -114.730224609375,\n 45.44471679159555\n ],\n [\n -119.05883789062501,\n 45.44471679159555\n ],\n [\n -119.05883789062501,\n 42.391008609205045\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"139","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Applestein, Cara 0000-0002-7923-8526","orcid":"https://orcid.org/0000-0002-7923-8526","contributorId":205748,"corporation":false,"usgs":true,"family":"Applestein","given":"Cara","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":844582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Germino, Matthew J. 0000-0001-6326-7579 mgermino@usgs.gov","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":152582,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","email":"mgermino@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":844583,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70232200,"text":"70232200 - 2022 - Thirteen novel ideas and underutilized resources to support progress towards a range-wide American eel stock assessment","interactions":[],"lastModifiedDate":"2022-09-15T14:08:12.517171","indexId":"70232200","displayToPublicDate":"2022-06-13T10:49:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1659,"text":"Fisheries Management and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Thirteen novel ideas and underutilized resources to support progress towards a range-wide American eel stock assessment","docAbstract":"A robust assessment of the American eel (Anguilla rostrata) stock, required to guide conservation efforts, is challenged by the species’ vast range, high variability in demographic parameters and data inadequacies. Novel ideas and underutilised resources that may assist both analytic assessments and spatially oriented modelling include (1) species and environmental databases; (2) mining of data from scattered sources; (3) infilling of data gaps by spatial analysis; (4) age estimation from measurements of DNA methylation; evaluation of eel abundance by (5) larval, (6) glass-bottom boat, (7) net enclosure and (8) eDNA surveys; (9) accounting for dam-induced habitat increases in eel watercourse modelling; (10) spatially oriented modelling with and without temporal components; (11) geographically nested modelling of glass eel recruitment; (12) spawner per recruit modelling and (13) life cycle modelling to examine larval allocation effects. Eel biologists are too few to gather the required assessment data across all of the species’ range. Public posting of electrofishing and eDNA metabarcoding data sets and the use of machine learning techniques to comprehensively inventory small dams will help meet some data needs. These approaches address only a small proportion of the assessment challenges that face American eels. Worldwide collaboration amongst Anguilla scientists is a key enabler of progress towards stock assessment goals.
","language":"English","publisher":"Wiley","doi":"10.1111/fme.12572","usgsCitation":"Cairns, D., Benchetrit, J., Bernatchez, L., Bornarel, V., Casselman, J., Castonguay, M., Charsley, A., Dorrow, M., Drouineau, H., Frankowski, J., Haro, A., Hoyle, S., Knickle, D.C., Koops, M.A., Poirier, L.A., Thorson, J.T., Young, J.A., and Zhu, X., 2022, Thirteen novel ideas and underutilized resources to support progress towards a range-wide American eel stock assessment: Fisheries Management and Ecology, v. 29, no. 5, p. 516-541, https://doi.org/10.1111/fme.12572.","productDescription":"26 p.","startPage":"516","endPage":"541","ipdsId":"IP-135604","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":447439,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/fme.12572","text":"Publisher Index 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Best subsets regression analysis was used to develop linear regression models that quantify relations among five categories of hydrologic explanatory metrics (i.e., duration, frequency, magnitude, rate-of-change, and timing) computed from streamgage records and six categories of biological response metrics (i.e., composition, habitat, life history, reproductive, tolerance, trophic) computed from fish community samples, as well as fish-based indices of biotic integrity (FIBI) scores and FIBI scores normalized to the an impairment threshold of the corresponding stream class (FIBI_BCG4). Three hydrologic datasets were used to examine rRelations between altered hydrology and fish community responses were examined at three different temporal scalesusing three hydrologic datasets that represented periods of record, long-term changes, and short-term changes to flow regimes in streams of Minnesota.","language":"English","publisher":"Springer","doi":"10.1186/s13717-022-00383-z","usgsCitation":"Ziegeweid, J.R., Johnson, G.D., Krall, A.L., Fitzpatrick, K., and Levin, S., 2022, Quantifying relations between altered hydrology and fish community responses for streams in Minnesota: Ecological Processes, v. 11, 41, 25 p., https://doi.org/10.1186/s13717-022-00383-z.","productDescription":"41, 25 p.","ipdsId":"IP-125704","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":447443,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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\"}}]}","volume":"11","noUsgsAuthors":false,"publicationDate":"2022-06-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Ziegeweid, Jeffrey R. 0000-0001-7797-3044 jrziege@usgs.gov","orcid":"https://orcid.org/0000-0001-7797-3044","contributorId":4166,"corporation":false,"usgs":true,"family":"Ziegeweid","given":"Jeffrey","email":"jrziege@usgs.gov","middleInitial":"R.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Gregory D.","contributorId":201568,"corporation":false,"usgs":false,"family":"Johnson","given":"Gregory","email":"","middleInitial":"D.","affiliations":[{"id":13330,"text":"Minnesota Pollution Control Agency","active":true,"usgs":false}],"preferred":false,"id":844552,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krall, Aliesha L. 0000-0003-2521-5043 adiekoff@usgs.gov","orcid":"https://orcid.org/0000-0003-2521-5043","contributorId":176545,"corporation":false,"usgs":true,"family":"Krall","given":"Aliesha","email":"adiekoff@usgs.gov","middleInitial":"L.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844553,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fitzpatrick, Kara","contributorId":292426,"corporation":false,"usgs":false,"family":"Fitzpatrick","given":"Kara","email":"","affiliations":[{"id":13330,"text":"Minnesota Pollution Control Agency","active":true,"usgs":false}],"preferred":false,"id":844554,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Levin, Sara B. 0000-0002-2448-3129","orcid":"https://orcid.org/0000-0002-2448-3129","contributorId":209947,"corporation":false,"usgs":true,"family":"Levin","given":"Sara B.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844555,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70232196,"text":"70232196 - 2022 - Spectral mixture analysis for surveillance of harmful algal blooms (SMASH): A field-, laboratory-, and satellite-based approach to identifying cyanobacteria genera from remotely sensed data","interactions":[],"lastModifiedDate":"2022-06-13T15:44:24.981546","indexId":"70232196","displayToPublicDate":"2022-06-13T10:31:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Spectral mixture analysis for surveillance of harmful algal blooms (SMASH): A field-, laboratory-, and satellite-based approach to identifying cyanobacteria genera from remotely sensed data","docAbstract":"Algal blooms around the world are increasing in frequency and severity, often with the possibility of adverse effects on human and ecosystem health. The health and economic impacts associated with harmful algal blooms, or HABs, provide compelling rationale for developing new methods for monitoring these events via remote sensing. Although concentrations of chlorophyll-a and key pigments like phycocyanin are routinely estimated from satellite images and used to infer algal or cyanobacterial cell counts, current methods are unable to provide information on the taxonomic composition of a bloom. This study introduced a new approach capable of differentiating among genera based on their reflectance characteristics: Spectral Mixture Analysis for Surveillance of HABs, or SMASH. The foundation of SMASH is a multiple endmember spectral mixture analysis (MESMA) algorithm that takes a library of cyanobacteria endmembers and a hyperspectral image as input and estimates the fractional abundance of each genus, plus water, on a per-pixel basis. Importantly, we assume that the water column consists of only pure water and cyanobacteria, implying that our linear spectral unmixing models do not account for other optically active constituents such as suspended sediment and colored dissolved organic matter (CDOM). We used reflectance spectra for 12 genera measured under a microscope to populate an algal spectral library and applied the SMASH workflow to satellite images from four waterbodies across the United States. Normalized spectral separability scores indicated that the 12 genera were distinct from one another and the MESMA algorithm reproduced known input fractions for simulated mixtures that included all pairwise combinations of genera and water. We used Upper Klamath Lake as an example to illustrate data products generated via SMASH: maps of the normalized difference chlorophyll index and cyanobacterial index, a MESMA-based classification of algal genera, fraction images for each endmember, and a root mean square error (RMSE) image that summarizes uncertainty. For Upper Klamath Lake, these outputs highlighted a complex algal bloom featuring several genera, primarily Aphanizomenon, and intricate spatial patterns associated with gyres. The maximum RMSE constraint imposed on the MESMA algorithm provided a means of avoiding false positive detection of genera not present in a waterbody but must not be set so low as to leave much of an image unclassified in cases where genera included in the library are present. Comparison of endmember fractions with relative biovolumes calculated from field samples indicated that taxonomic information from SMASH was consistent with field observations. For example, the algorithm successfully identified Microcystis in Owasco Lake but avoided misclassifying Asterionella, a genus not yet included in our library, in Detroit Lake. This proof-of-concept investigation demonstrates the potential of SMASH to enhance our understanding of algal blooms, particularly with respect to their spatial and temporal dynamics.
Habitat-suitability indices (HSI) have been employed in restoration to identify optimal sites for planting native species. Often, HSI are based on abiotic variables and do not include biotic interactions, even though similar abiotic conditions can favor both native and nonnative species. Biotic interactions such as competition may be especially important in invader-dominated habitats because invasive species often have fast growth rates and can exploit resources quickly. In this study, we test the utility of an HSI of microtopography derived from airborne LiDAR to predict post-disturbance recovery and native planting success in native shrub-dominated and nonnative, invasive grass-dominated dryland habitats in Hawaiʻi. The HSI uses high-resolution digital terrain models to classify sites' microtopography as high, medium, or low suitability, based on wind exposure and topographic position. We used a split-plot before-after-control-impact design to implement a disturbance experiment within native shrub (Dodonaea viscosa) and nonnative, invasive grass (Cenchrus clandestinus)-dominated ecosystems across three microtopography categories. In contrast to previous studies using the same HSI, we found that microtopography was a poor predictor of pre-disturbance conditions for soil nutrients, organic matter content, or foliar C:N, within both Dodonaea and Cenchrus vegetation types. In invader-dominated Cenchrus plots, microtopography helped predict cover, but not as expected (i.e., highest cover would be in high-suitability plots): D. viscosa had the greatest cover in low-suitability and C. clandestinus had the greatest cover in medium-suitability plots. Similarly, in native-dominated Dodonaea plots, microtopography was a poor predictor of D. viscosa, C. clandestinus, and total plant cover. Although we found some evidence that microtopography helped inform post-disturbance plant recovery of D. viscosa and total plant cover, vegetation type was a more important predictor. Important for considering the success of plantings, percent cover of D. viscosa decreased while percent cover of C. clandestinus increased within both vegetation types 20 months after disturbance. Our results are evidence that HSIs based on topographic features may prove most useful for choosing planting sites in harsh habitats or those already dominated by native species. In more productive habitats, competition from resident species may offset any benefits gained from “better” suitability sites.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2690","usgsCitation":"Yelenik, S.G., Rose, E., Cordell, S., Victoria, M., and Kellner, J.R., 2022, The role of microtopography and resident species in post-disturbance recovery of arid habitats in Hawaiʻi: Ecological Applications, v. 32, e2690, 18 p., https://doi.org/10.1002/eap.2690.","productDescription":"e2690, 18 p.","ipdsId":"IP-080159","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":447453,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2690","text":"Publisher Index Page"},{"id":419497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Army Pohakuloa Training Area, Keʻamuku maneuver area, Hawaii Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.75116384910783,\n 19.925062000236125\n ],\n [\n -155.7454528828605,\n 19.776779210079724\n ],\n [\n -155.6101203582919,\n 19.781480563216192\n ],\n [\n -155.65866357139447,\n 19.937813032695132\n ],\n [\n -155.75116384910783,\n 19.925062000236125\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"32","noUsgsAuthors":false,"publicationDate":"2022-08-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Yelenik, Stephanie G. 0000-0002-9011-0769 syelenik@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-0769","contributorId":5251,"corporation":false,"usgs":true,"family":"Yelenik","given":"Stephanie","email":"syelenik@usgs.gov","middleInitial":"G.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":879447,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rose, Eli 0000-0003-0958-9491 etrose@usgs.gov","orcid":"https://orcid.org/0000-0003-0958-9491","contributorId":194190,"corporation":false,"usgs":true,"family":"Rose","given":"Eli","email":"etrose@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":879448,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cordell, Susan","contributorId":197818,"corporation":false,"usgs":false,"family":"Cordell","given":"Susan","email":"","affiliations":[],"preferred":false,"id":879449,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Victoria, Michelle","contributorId":317848,"corporation":false,"usgs":false,"family":"Victoria","given":"Michelle","email":"","affiliations":[{"id":69168,"text":"Pacific Internship Programs for Exploring Science, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":879450,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kellner, James R.","contributorId":172034,"corporation":false,"usgs":false,"family":"Kellner","given":"James","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":879451,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70232415,"text":"70232415 - 2022 - Analysis of surface water trends for the conterminous United States using MODIS satellite data, 2003–2019","interactions":[],"lastModifiedDate":"2022-07-01T12:26:23.085105","indexId":"70232415","displayToPublicDate":"2022-06-13T07:24:13","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Analysis of surface water trends for the conterminous United States using MODIS satellite data, 2003–2019","docAbstract":"Satellite imagery is commonly used to map surface water extents over time, but many approaches yield discontinuous records resulting from cloud obstruction or image archive gaps. We applied the Dynamic Surface Water Extent (DSWE) model to downscaled (250-m) daily Moderate Resolution Imaging Spectroradiometer (MODIS) data in Google Earth Engine to generate monthly surface water maps for the conterminous United States (US) from 2003 through 2019. The aggregation of daily observations to monthly maps of maximum water extent produced records with diminished cloud and cloud shadow effects across most of the country. We used the continuous monthly record to analyze spatiotemporal surface water trends stratified within Environmental Protection Agency Ecoregions. Although not all ecoregion trends were significant (p < 0.05), results indicate that much of the western and eastern US underwent a decline in surface water over the 17-year period, while many ecoregions in the Great Plains had positive trends. Trends were also generated from monthly streamgage discharge records and compared to surface water trends from the same ecoregion. These approaches agreed on the directionality of trend detected for 54 of 85 ecoregions, particularly across the Great Plains and portions of the western US, whereas trends were not congruent in select western deserts, the Great Lakes region, and the southeastern US. By describing the geographic distribution of surface water over time and comparing these records to instrumented discharge data across the conterminous US, our findings demonstrate the efficacy of using satellite imagery to monitor surface water dynamics and supplement traditional instrumented monitoring.
Increasing demand for river water now conflicts with an increasing desire to maintain riparian ecosystems. Efficiently managing river flows for riparian vegetation requires an understanding of the time scale of flow effects, but this information is limited by the absence of long-term studies of vegetation change in response to flow variation. To investigate the influence of short- and long-term flow variability and dam operation on riparian vegetation, we determined the occurrence of 107 plant species in 133 permanent plots of known inundating discharge along the Gunnison River in Colorado on five different occasions between 1990 and 2013. Individual species moved up and down the gradient of inundating discharge coincident with increases and decreases in mean annual flow, and the correlations between flow and species occurrence were strongest when flows were weighted by time before vegetation sampling with a median half-life of 1.5 years. Some tall, rhizomatous, perennial species, however, responded to flows on a longer time scale. Logistic regression of species occurrence showed a significant relation with inundation duration for 70 out of 107 species. Plot species richness and total vegetative cover decreased in association with desiccation at low inundation durations and with fluvial disturbance at high inundation durations. Within-plot similarity in species occurrence between years decreased strongly with increasing inundation duration. Moderate inundation durations were dominated by tall, rhizomatous, perennial herbs, including invasive Phalaris arundinacea (reed canary grass). Over the 23-year study period, species richness declined, and the proportion of rhizomatous perennials increased, consistent with the hypothesis that decreases in flow peaks and increases in low flows caused by flow regulation have decreased establishment opportunities for disturbance-dependent species. In summary, annual-scale changes in vegetation were strongly influenced by flow variation, and decadal-scale changes were influenced by decreases in fluvial disturbance from upstream flow regulation beginning decades prior to the onset of this study.
Many wildlife species are threatened in Asia, including the five species of terrestrial bears (Asiatic black, Ursus thibetanus; brown, U. arctos; sloth, Melursus ursinus; sun, Helarctos malayanus; giant panda, Ailuropoda melanoleuca): many populations of these bears are thought to be declining or imperiled by small population size. Here our aim is to document how population assessments have been conducted for bears in Asia. We searched the literature and identified 102 studies published during 1999–2021 that investigated the status of an Asian bear population; these occurred in 24 of the 32 bear range countries in Asia. At the most basic level, 11% of studies verified presence of bears in places where they were not known to exist. The most common objective (53% of papers) was a distribution map, often derived from presence locations in a habitat-based model. Occupancy studies (15%) used temporal (time stamps on images from cameras) or spatial (transect segments) replicates, but tended to focus on “use”, so detector spacing was sometimes not appropriate for occupancy. Purported population indices, such as sign density or camera trap encounter rates, were reported in 16% of studies. One third of studies provided a population estimate, but only 10 studies in two decades used a rigorous method (e.g., mark–recapture). Sign surveys and interviews were the most common methods for determining bear presence, and local interviews were heavily relied upon for assessing population trend. Camera trapping has become increasingly prevalent, but only one study obtained a population estimate using photographs to distinguish natural individual markings. Only three studies used hair traps to obtain DNA-based population estimates, and three other studies obtained population estimates from DNA in scats. Just three studies quantitatively measured change in population size or occupancy over time, and none of these showed a decline. Unique rangewide sign surveys of giant pandas showed significant geographic expansion. The opinions of experts and local people, now heavily relied upon for population assessments, are not reliable or sensitive enough for monitoring. Quantitative population assessments are desirable to direct conservation actions toward the most perilous situations, and provide a means to gauge the effectiveness of conservation actions. This paper demonstrates the paucity of rigorous monitoring of Asian bears, and leads off a series of papers that propose improved methods for assessing distribution, occupancy, and density
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2022 - Predicting near-term effects of climate change on nitrogen transport to Chesapeake Bay","interactions":[],"lastModifiedDate":"2022-08-15T13:54:09.728265","indexId":"70232212","displayToPublicDate":"2022-06-12T09:12:01","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Predicting near-term effects of climate change on nitrogen transport to Chesapeake Bay","docAbstract":"Understanding effects of climate change on nitrogen fate and transport in the environment is critical to nutrient management. We used climate projections within a previously calibrated spatially referenced regression (SPARROW) model to predict effects of expected climate change over 1995 through 2025 on total nitrogen fluxes to Chesapeake Bay and in watershed streams. Assuming nitrogen inputs and other watershed conditions remain at 2012 levels, effects of increasing temperature, runoff, streamflow, and stream velocity expected between 1995 and 2025 will include an estimated net 6.5% decline in annual nitrogen delivery to the bay from its watershed. This predicted decline is attributable to declines in the delivery of nitrogen from upland nonpoint sources to streams due to predicted warmer temperatures. Such temperature-driven declines in the delivery of nitrogen to streams more than offset predicted increased delivery to and within streams due to increased runoff and streamflow and may be attributable to increasing rates of denitrification or ammonia volatilization or to changes in plant phenology. Predicted climate-driven declines in nitrogen flux are generally similar across the watershed but vary slightly among major nonpoint source sectors and tributary watersheds. Nitrogen contributions to the bay from point sources are not affected by temperature-driven changes in delivery from uplands and are therefore predicted to increase slightly between 1995 and 2025.
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