We describe a collection of aquatic and wetland habitats in an inland landscape, and their occurrence within a terrestrial matrix, as a “freshwater ecosystem mosaic” (FEM). Aquatic and wetland habitats in any FEM can vary widely, from permanently ponded lakes, to ephemerally ponded wetlands, to groundwater‐fed springs, to flowing rivers and streams. The terrestrial matrix can also vary, including in its influence on flows of energy, materials, and organisms among ecosystems. Biota occurring in a specific region are adapted to the unique opportunities and challenges presented by spatial and temporal patterns of habitat types inherent to each FEM. To persist in any given landscape, most species move to recolonize habitats and maintain mixtures of genetic materials. Species also connect habitats through time if they possess needed morphological, physiological, or behavioral traits to persist in a habitat through periods of unfavorable environmental conditions. By examining key spatial and temporal patterns underlying FEMs, and species‐specific adaptations to these patterns, a better understanding of the structural and functional connectivity of a landscape can be obtained. Fully including aquatic, wetland, and terrestrial habitats in FEMs facilitates adoption of the next generation of individual‐based models that integrate the principles of population, community, and ecosystem ecology.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12683","usgsCitation":"Mushet, D.M., Alexander, L.C., Bennet, M., Schofield, K., Christensen, J.R., Ali, G., Pollard, A.I., Fritz, K.M., and Lang, M., 2018, Differing modes of biotic connectivity within freshwater ecosystem mosaics: Journal of the American Water Resources Association, v. 55, no. 2, p. 307-317, https://doi.org/10.1111/1752-1688.12683.","productDescription":"11 p.","startPage":"307","endPage":"317","ipdsId":"IP-093523","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":468461,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12683","text":"Publisher Index Page"},{"id":356967,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-24","publicationStatus":"PW","scienceBaseUri":"5b98a26de4b0702d0e842ea8","contributors":{"authors":[{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":743895,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alexander, Laurie C.","contributorId":196285,"corporation":false,"usgs":false,"family":"Alexander","given":"Laurie","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":743896,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennet, Micah","contributorId":207475,"corporation":false,"usgs":false,"family":"Bennet","given":"Micah","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":743897,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schofield, Kate","contributorId":203960,"corporation":false,"usgs":false,"family":"Schofield","given":"Kate","affiliations":[{"id":36774,"text":"USEPA NCEA","active":true,"usgs":false}],"preferred":false,"id":743898,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Christensen, Jay R.","contributorId":179361,"corporation":false,"usgs":false,"family":"Christensen","given":"Jay","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":743900,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ali, Genevieve","contributorId":204052,"corporation":false,"usgs":false,"family":"Ali","given":"Genevieve","affiliations":[{"id":16603,"text":"University of Manitoba","active":true,"usgs":false}],"preferred":false,"id":743901,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pollard, Amina I.","contributorId":203965,"corporation":false,"usgs":false,"family":"Pollard","given":"Amina","email":"","middleInitial":"I.","affiliations":[{"id":36775,"text":"USEPA, Office of Water","active":true,"usgs":false}],"preferred":false,"id":743899,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fritz, Ken M. 0000-0002-3831-2531","orcid":"https://orcid.org/0000-0002-3831-2531","contributorId":203959,"corporation":false,"usgs":false,"family":"Fritz","given":"Ken","email":"","middleInitial":"M.","affiliations":[{"id":36773,"text":"USEPA NERL","active":true,"usgs":false}],"preferred":false,"id":743902,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lang, Megan","contributorId":156431,"corporation":false,"usgs":false,"family":"Lang","given":"Megan","affiliations":[{"id":7261,"text":"Department of Geographical Sciences, University of Maryland, College Park, MD, 20742","active":true,"usgs":false}],"preferred":false,"id":743903,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70198617,"text":"ofr20181131 - 2018 - Research to improve ShakeAlert earthquake early warning products and their utility","interactions":[],"lastModifiedDate":"2018-08-31T09:32:14","indexId":"ofr20181131","displayToPublicDate":"2018-08-30T14:20:57","publicationYear":"2018","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":"2018-1131","title":"Research to improve ShakeAlert earthquake early warning products and their utility","docAbstract":"Earthquake early warning (EEW) is the rapid detection of an earthquake and issuance of an alert or notification to people and vulnerable systems likely to experience potentially damaging ground shaking. The level of ground shaking that is considered damaging is defined by the specific application; for example, manufacturing equipment may experience damage at a lower intensity ground shaking than would cause damage to a building. Along the West Coast of the United States, the warning times for ground shaking could range as high as tens of seconds for moderate levels of ground shaking, or potentially longer, if a lower ground-shaking threshold is used to issue alerts. However, it is not always possible to provide advance warning of ground shaking, particularly for locations close to an earthquake that are most likely to experience very strong ground shaking. EEW alerts may be useful to individuals who can use a few seconds to move to a safe zone and to electromechanical systems that can take automatic actions to reduce damage and injuries. An EEW system, ShakeAlert, has been under development in the United States since 2006. Federal and State governments, as well as the private sector, are now investing in the ShakeAlert prototype system that will, when completed, become an operational public system for the West Coast of the United States.
While the current prototype is delivering alerts to test users, improvements to the accuracy, timeliness, and utility of the alerts are needed. For this reason, it is essential that the ShakeAlert system be continuously improved through targeted research, involving not only the current ShakeAlert partner organizations, but also the broader scientific, engineering, and emergencyresponse communities. To this end, this report describes the opportunities for improvement that can be addressed through research and development over the next 5 years.
Our recommendations are organized into four areas: (1) understand EEW capabilities and user needs, (2) make alerts as fast and accurate as possible, (3) ensure reliability when it counts, and (4) explore the use of new instrumentation.
The first challenge is to understand EEW capabilities and user needs. EEW must deliver actionable information to people and to automated systems to mitigate short- and longterm impacts of damaging ground shaking, so development of EEW must be motivated by the needs of users. Within this challenge, we must study the technical capabilities and limitations of EEW in general, and the ShakeAlert system specifically. This includes development of performance metrics that assess the timeliness and accuracy of alerts to understand the value and utility of the ShakeAlert EEW product(s) for various user groups, including different industry sectors, emergency-management agencies, and the public. Research is needed to define the alerting choices that maximize the utility of the system for users and to determine what the available communication pathways are for providing timely alert information. Additionally, we engage users to assess how alerts will be used by different sectors to mitigate losses and to inform EEW product design. Further, social-science research is needed to develop alert messaging, including what relevant prior and follow-up information are required, to ensure effective use of alerts.
The second challenge is to make alerts as fast and as accurate as possible. The timeliness and accuracy of an EEW alert is important because it will set in motion a series of actions and downstream products. An EEW alert will trigger notification across emergency-alert systems and across multiple communication channels to populations in impacted regions. The EEW alert region may grow as the earthquake fault-rupture length increases, and the EEW system’s characterization of it, evolves. We must continue research into new or improved seismic and geodetic waveform-processing methods necessary to rapidly characterize the expected ground shaking and associated uncertainties. It is important to thoroughly evaluate whether new methods improve alerts through more accurate ground-motion estimates and (or) reduced latencies (that is, longer warning times). New methods could include tracking the extent of a large rupture in real time (known as finite-fault algorithms) and ground-motionbased EEW algorithms. Additionally, ground motion predictions could be optimized for each earthquake as the earthquake fault rupture progresses by using, for example, event terms to shift ground-motion curves for more (or less) energetic ruptures.
The third challenge is to ensure reliability when it counts. This challenge requires us to explore approaches that assess the expected performance of ShakeAlert across the range of earthquake magnitudes, locations, and depths that may occur within the alerting region. Large, damaging earthquakes and their associated aftershock sequences matter most for hazard and for EEW, but these large-earthquake sequences occur infrequently. We expect ShakeAlert to respond robustly to these large-earthquake sequences despite potentially long periods of relative seismic quiescence in the intervening years, and in spite of inevitable communication challenges that arise during and after a large earthquake. We must develop methods to utilize the broadest available datasets to test EEW performance, including ground-motion data recorded in other parts of the world. The observational period for large, damaging earthquakes in any particular region has been short in comparison to estimated large-earthquake recurrence times. Ground-motion records for very large, damaging western United States events and major aftershock sequences do not yet exist, nor do data exist for all potential sources of noise and spurious signals that ShakeAlert must be “tuned” to reject. In addition, robust synthetic data could provide the flexibility to test a wider range of earthquake magnitude, tectonic-setting, and noise scenarios than are covered by existing observational data. Synthetic ground-motion data must be thoroughly vetted against records of smaller magnitude earthquakes to ensure that they accurately capture both the onset and the amplitude of the ground shaking.
The final challenge is to explore the use of new instrumentation. The development of EEW around the world to date has focused on the use of high-quality, scientific-grade seismic and geodetic instrumentation. The use of additional types of instrumentation or information may also improve EEW products by filling gaps in sensor coverage in countries that already have dense seismic networks or enable EEW in countries without such networks. We must keep up with these developments and continuously assess their value in supplementing existing EEW systems, such as ShakeAlert, or enabling EEW where such systems do not exist. Such developments include low-cost instrumentation with microelectromechanical system (MEMS) sensors and global positioning system (GPS)/global navigation satellite system (GNSS) antennas embedded in low-cost consumer electronics, sea-floor seismometers, geodetic instrumentation deployed along the Cascadia and Alaska megathrust margins of western North America, and borehole strainmeters that are already deployed across the region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181131","usgsCitation":"Cochran, E.S., Aagaard, B.T., Allen, R.M., Andrews, J., Baltay, A.S., Barbour, A.J., Bodin, P., Brooks, B.A., Chung, A., Crowell, B.W., Given, D.D., Hanks, T.C., Hartog, J.R., Hauksson, E., Heaton, T.H., McBride, S., Meier, M-A., Melgar, D., Minson, S.E., Murray, J.R., Strauss, J.A., and Toomey, D., 2018, Research to improve ShakeAlert earthquake early warning products and their utility: U.S. Geological Survey Open-File Report 2018–1131, 17 p., https://doi.org/10.3133/ofr20181131.","productDescription":"iv, 17 p.","onlineOnly":"Y","ipdsId":"IP-098968","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":356971,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1131/coverthb.jpg"},{"id":356972,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1131/ofr20181131.pdf","text":"Report","size":"600 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2018-1131"}],"contact":"Earthquake Science Center-Pasadena Field Office
U.S. Geological Survey
525 South Wilson Ave.
Pasadena, CA 91106-3212
Great megathrust earthquakes arise from the sudden release of energy accumulated during centuries of interseismic plate convergence. The moment deficit (energy available for future earthquakes) is commonly inferred by integrating the rate of interseismic plate locking over the time since the previous great earthquake. But accurate integration requires knowledge of how interseismic plate locking changes decades after earthquakes, measurements not available for most great earthquakes. Here we reconstruct the post-earthquake history of plate locking at Guafo Island, above the seismogenic zone of the giant 1960 (Mw = 9.5) Chile earthquake, through forward modeling of land-level changes inferred from aerial imagery (since 1974) and measured by GPS (since 1994). We find that interseismic locking increased to ~70% in the decade following the 1960 earthquake and then gradually to 100% by 2005. Our findings illustrate the transient evolution of plate locking in Chile, and suggest a similarly complex evolution elsewhere, with implications for the time- and magnitude-dependent probability of future events.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41467-018-05989-6","usgsCitation":"Melnick, D., Li, S., Moreno, M., Cisternas, M., Jara-Munoz, J., Wesson, R.L., Nelson, A.R., Baez, J.C., and Deng, Z., 2018, Back to full interseismic plate locking decades after the giant 1960 Chile earthquake: Nature Communications, v. 9, Article number: 3527; 10 p., https://doi.org/10.1038/s41467-018-05989-6.","productDescription":"Article number: 3527; 10 p.","ipdsId":"IP-098182","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":468462,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-018-05989-6","text":"Publisher Index Page"},{"id":357100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76,\n -48\n ],\n [\n -72,\n -48\n ],\n [\n -72,\n -36\n ],\n [\n -76,\n -36\n ],\n [\n -76,\n -48\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-30","publicationStatus":"PW","scienceBaseUri":"5b98a26de4b0702d0e842eae","contributors":{"authors":[{"text":"Melnick, Daniel","contributorId":195525,"corporation":false,"usgs":false,"family":"Melnick","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":744310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Shaoyang","contributorId":207597,"corporation":false,"usgs":false,"family":"Li","given":"Shaoyang","email":"","affiliations":[],"preferred":false,"id":744311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moreno, Marcos","contributorId":195527,"corporation":false,"usgs":false,"family":"Moreno","given":"Marcos","email":"","affiliations":[],"preferred":false,"id":744312,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cisternas, Macro","contributorId":198898,"corporation":false,"usgs":false,"family":"Cisternas","given":"Macro","email":"","affiliations":[{"id":34895,"text":"Pontificia Universidad Catolica de Valparaiso","active":true,"usgs":false}],"preferred":false,"id":744313,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jara-Munoz, Julius","contributorId":207598,"corporation":false,"usgs":false,"family":"Jara-Munoz","given":"Julius","email":"","affiliations":[],"preferred":false,"id":744314,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wesson, Robert L. 0000-0003-2702-0012 rwesson@usgs.gov","orcid":"https://orcid.org/0000-0003-2702-0012","contributorId":850,"corporation":false,"usgs":true,"family":"Wesson","given":"Robert","email":"rwesson@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":744315,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nelson, Alan R. 0000-0001-7117-7098 anelson@usgs.gov","orcid":"https://orcid.org/0000-0001-7117-7098","contributorId":812,"corporation":false,"usgs":true,"family":"Nelson","given":"Alan","email":"anelson@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":744316,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Baez, Juan Carlos","contributorId":207599,"corporation":false,"usgs":false,"family":"Baez","given":"Juan","email":"","middleInitial":"Carlos","affiliations":[],"preferred":false,"id":744317,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Deng, Zhiguo","contributorId":207600,"corporation":false,"usgs":false,"family":"Deng","given":"Zhiguo","email":"","affiliations":[],"preferred":false,"id":744318,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70199062,"text":"70199062 - 2018 - Ancient convergent losses of Paraoxonase 1 yield potential risks for modern marine mammals","interactions":[],"lastModifiedDate":"2018-08-30T10:53:58","indexId":"70199062","displayToPublicDate":"2018-08-30T10:53:54","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Ancient convergent losses of Paraoxonase 1 yield potential risks for modern marine mammals","title":"Ancient convergent losses of Paraoxonase 1 yield potential risks for modern marine mammals","docAbstract":"Mammals diversified by colonizing drastically different environments, with each transition yielding numerous molecular changes, including losses of protein function. Though not initially deleterious, these losses could subsequently carry deleterious pleiotropic consequences. We have used phylogenetic methods to identify convergent functional losses across independent marine mammal lineages. In one extreme case, Paraoxonase 1 (PON1) accrued lesions in all marine lineages, while remaining intact in all terrestrial mammals. These lesions coincide with PON1 enzymatic activity loss in marine species’ blood plasma. This convergent loss is likely explained by parallel shifts in marine ancestors’ lipid metabolism and/or bloodstream oxidative environment affecting PON1’s role in fatty acid oxidation. PON1 loss also eliminates marine mammals’ main defense against neurotoxicity from specific man-made organophosphorus compounds, implying potential risks in modern environments.
Numerous contaminants of emerging concern (CECs) typically occur in urban rivers. Wastewater effluents are a major source of many CECs. Urban runoff (stormwater) is a major urban water budget component and may constitute another major CEC pathway. Yet, stormwater-based CEC field studies are rare. This research investigated 384 CECs in 36 stormwater samples in Minneapolis-St. Paul, Minnesota, USA. Nine sampling sites included three large stormwater conveyances (pipes) and three paired iron-enhanced sand filters (IESFs; untreated inlets and treated outlets). The 123 detected compounds included commercial-consumer compounds, veterinary and human pharmaceuticals, lifestyle and personal care compounds, pesticides, and others. Thirty-one CECs were detected in ≥50% of samples. Individual samples contained a median of 35 targeted CECs (range: 18–54). Overall, median concentrations were ≥10 ng/L for 25 CECs and ≥100 ng/L for 9 CECs. Ranked, hierarchical linear modeling indicated significant seasonal- and site type-based concentration variability for 53 and 30 CECs, respectively, with observed patterns corresponding to CEC type, source, usage, and seasonal hydrology. A primarily warm-weather, diffuse, runoff-based profile included many herbicides. A second profile encompassed winter and/or late summer samples enriched with some recalcitrant, hydrophobic compounds (e.g., PAHs), especially at pipes, suggesting conservative, less runoff-dependent sources (e.g., sediments). A third profile, indicative of mixed conservative/non-runoff, runoff, and/or atmospheric sources and transport that collectively affect a variety of conditions, included various fungicides, lifestyle, non-prescription, and commercial-consumer CECs. Generally, pipe sites had large, diverse land-use catchments, and showed more frequent detections of diverse CECs, but often at lower concentrations; while untreated sites (with smaller, more residential-catchments) demonstrated greater detections of “pseudo-persistent” and other ubiquitous or residentially-associated CECs. Although untreated stormwater transports an array of CECs to receiving waters, IESF treatment significantly removed concentrations of 14 (29%) of the 48 most detected CECs; for these, median removal efficiencies were 26%–100%. Efficient removal of some hydrophobic (e.g., PAHs, bisphenol A) and polar-hydrophilic (e.g., caffeine, nicotine) compounds indicated particulate-bound contaminant filtration and for certain dissolved contaminants, sorption.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2018.08.020","usgsCitation":"Fairbairn, D.J., Elliott, S.M., Kiesling, R.L., Schoenfuss, H.L., Ferrey, M.L., and Westerhoff, B., 2018, Contaminants of emerging concern in urban stormwater: Spatiotemporal patterns and removal by iron-enhanced sand filters (IESFs): Water Research, v. 145, p. 332-345, https://doi.org/10.1016/j.watres.2018.08.020.","productDescription":"14 p.","startPage":"332","endPage":"345","ipdsId":"IP-094557","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":356946,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","city":"Minneapolis, St. Paul","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.44696044921875,\n 44.859275967357476\n ],\n [\n -92.95944213867186,\n 44.859275967357476\n ],\n [\n -92.95944213867186,\n 45.08661163034925\n ],\n [\n -93.44696044921875,\n 45.08661163034925\n ],\n [\n -93.44696044921875,\n 44.859275967357476\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"145","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a26ee4b0702d0e842eb4","contributors":{"authors":[{"text":"Fairbairn, David J.","contributorId":207455,"corporation":false,"usgs":false,"family":"Fairbairn","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":13330,"text":"Minnesota Pollution Control Agency","active":true,"usgs":false}],"preferred":false,"id":743862,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elliott, Sarah M. 0000-0002-1414-3024 selliott@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-3024","contributorId":1472,"corporation":false,"usgs":true,"family":"Elliott","given":"Sarah","email":"selliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":743861,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kiesling, Richard L. 0000-0002-3017-1826 kiesling@usgs.gov","orcid":"https://orcid.org/0000-0002-3017-1826","contributorId":1837,"corporation":false,"usgs":true,"family":"Kiesling","given":"Richard","email":"kiesling@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":743863,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schoenfuss, Heiko L.","contributorId":76409,"corporation":false,"usgs":false,"family":"Schoenfuss","given":"Heiko","email":"","middleInitial":"L.","affiliations":[{"id":13317,"text":"Saint Cloud State University","active":true,"usgs":false}],"preferred":false,"id":743864,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ferrey, Mark L.","contributorId":207457,"corporation":false,"usgs":false,"family":"Ferrey","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":13330,"text":"Minnesota Pollution Control Agency","active":true,"usgs":false}],"preferred":false,"id":743865,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Westerhoff, Benjamin J.","contributorId":207458,"corporation":false,"usgs":false,"family":"Westerhoff","given":"Benjamin J.","affiliations":[{"id":20306,"text":"St. Cloud State University","active":true,"usgs":false}],"preferred":false,"id":743866,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70198999,"text":"70198999 - 2018 - Elevated aeolian sediment transport on the Colorado Plateau, USA: The role of grazing, vehicle disturbance, and increasing aridity","interactions":[],"lastModifiedDate":"2018-11-14T09:27:13","indexId":"70198999","displayToPublicDate":"2018-08-29T16:05:09","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Elevated aeolian sediment transport on the Colorado Plateau, USA: The role of grazing, vehicle disturbance, and increasing aridity","docAbstract":"Dryland wind transport of sediment can accelerate soil erosion, degrade air quality, mobilize dunes, decrease water supply, and damage infrastructure. We measured aeolian sediment horizontal mass flux (q) at 100 cm height using passive aspirated sediment traps to better understand q variability on the Colorado Plateau. Measured q‘hot spots’ rival the highest ever recorded including 7,460 g m−2 day−1 in an off‐highway vehicle (OHV) area, but were more commonly 50‐2,000 g m−2 day−1. Overall mean q on rangeland sites was 5.14 g m−2 day−1, considerably lower than areas with concentrated livestock use (9‐19 g m−2 day−1), OHV use (414 g m−2 day−1), and downwind of unpaved roads (13.14 g m−2 day−1), but were higher than areas with minimal soil disturbance (1.60 g m−2 day−1). Rangeland q increased with increasing annual temperature, increased winds, and decreasing precipitation. Spatial modeling suggests that ~92‐93% of regional q occurs in rangelands versus ~7‐8% along unpaved roads. Four of the five largest road qvalues (n=33) measured were along roads used primarily for oil or gas wells. Our findings indicate that predicted future mega‐droughts will increase q disproportionately in disturbed rangelands, and potentially further compromise air quality, hydrologic cycles, and other ecosystem services.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.4457","usgsCitation":"Nauman, T.W., Duniway, M.C., Webb, N.P., and Belnap, J., 2018, Elevated aeolian sediment transport on the Colorado Plateau, USA: The role of grazing, vehicle disturbance, and increasing aridity: Earth Surface Processes and Landforms, v. 43, no. 14, p. 2897-2914, https://doi.org/10.1002/esp.4457.","productDescription":"18 p.","startPage":"2897","endPage":"2914","ipdsId":"IP-091070","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":356937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Colorado Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.23406982421875,\n 37.76202988573211\n ],\n [\n -109.05853271484374,\n 37.76202988573211\n ],\n [\n -109.05853271484374,\n 39.37889504706486\n ],\n [\n -110.23406982421875,\n 39.37889504706486\n ],\n [\n -110.23406982421875,\n 37.76202988573211\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"14","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-13","publicationStatus":"PW","scienceBaseUri":"5b98a26ee4b0702d0e842eb8","contributors":{"authors":[{"text":"Nauman, Travis W. 0000-0001-8004-0608 tnauman@usgs.gov","orcid":"https://orcid.org/0000-0001-8004-0608","contributorId":169241,"corporation":false,"usgs":true,"family":"Nauman","given":"Travis","email":"tnauman@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":743714,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":743715,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webb, Nichloas P.","contributorId":207393,"corporation":false,"usgs":false,"family":"Webb","given":"Nichloas","email":"","middleInitial":"P.","affiliations":[{"id":37528,"text":"USDA-ARS Jornada Experimental Range, PO Box 30003, MSC 3JER, NMSU, Las Cruces, NM 88003, USA","active":true,"usgs":false}],"preferred":false,"id":743717,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":743716,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70200889,"text":"70200889 - 2018 - Using United States Geological Survey stream gages to predict flow and temperature conditions to maintain freshwater mussel habitat","interactions":[],"lastModifiedDate":"2018-11-14T15:22:08","indexId":"70200889","displayToPublicDate":"2018-08-29T15:23:25","publicationYear":"2018","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":"Using United States Geological Survey stream gages to predict flow and temperature conditions to maintain freshwater mussel habitat","docAbstract":"Habitat conditions necessary to support freshwater mussels can be difficult to characterize and predict, particularly for rare or endangered species such as the federally endangered dwarf wedgemussel, Alasmidonta heterodon. In this study, we evaluate flow and temperature conditions in three areas of the mainstem Delaware River known to consistently support A. heterodon, and we develop predictive models using the U.S. Geological Survey (USGS) stream gages and thermal stations in order to identify conditions under which habitat alteration could threaten the species. Flow and temperature prediction models based on nearby existing USGS gage and thermal stations were predictive for all three sites. Both discharge prediction and water depth profile models indicate one location (Site 3) was the most vulnerable to low‐flow conditions as it requires the highest discharge rate (26.3 cms) at the USGS Callicoon gage to maintain both the full wetted perimeter (Pfull) and minimal wetted perimeter (Pmin) and prevent occlusion of areas that contain A. heterodon. Flow management targets aimed at protecting Site 3 should also protect Sites 1 and 2. Although analyses indicated significant benthic habitat available in all three sites even under low discharge rates, specific mussel locations could be vulnerable to dewatering and thermal stress if only Pmin values were maintained. Results indicate the magnitude of site temperature deviations from thermal stations varied by site and river temperature. In general, our results suggest that existing temperature and stream gage infrastructure may be used predictively to evaluate the effects of different flow targets on mainstem Delaware River A. heterodon habitat.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3326","usgsCitation":"Cole, J.C., Townsend, P.A., Eshleman, K.N., St. John White, B., Galbraith, H.S., and Lellis, W.A., 2018, Using United States Geological Survey stream gages to predict flow and temperature conditions to maintain freshwater mussel habitat: River Research and Applications, v. 34, no. 8, p. 977-992, https://doi.org/10.1002/rra.3326.","productDescription":"15 p.","startPage":"977","endPage":"992","ipdsId":"IP-086457","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":437774,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7WS8S6V","text":"USGS data release","linkHelpText":"Site bathymetry, water temperature and rating curve 2004 and 2005 data for 3 sites in the Delaware River mainstem"},{"id":359432,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Delaware River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.5255126953125,\n 41.3500103516271\n ],\n [\n -74.5477294921875,\n 41.3500103516271\n ],\n [\n -74.5477294921875,\n 42.429538632268276\n ],\n [\n -75.5255126953125,\n 42.429538632268276\n ],\n [\n -75.5255126953125,\n 41.3500103516271\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"8","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-29","publicationStatus":"PW","scienceBaseUri":"5bed4274e4b0b3fc5cf91c8e","contributors":{"authors":[{"text":"Cole, Jeffrey C. 0000-0002-2477-7231 jccole@usgs.gov","orcid":"https://orcid.org/0000-0002-2477-7231","contributorId":5585,"corporation":false,"usgs":true,"family":"Cole","given":"Jeffrey","email":"jccole@usgs.gov","middleInitial":"C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":751069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Townsend, Phillip A. 0000-0001-7003-8774","orcid":"https://orcid.org/0000-0001-7003-8774","contributorId":210594,"corporation":false,"usgs":false,"family":"Townsend","given":"Phillip","email":"","middleInitial":"A.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":751070,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eshleman, Keith N.","contributorId":210596,"corporation":false,"usgs":false,"family":"Eshleman","given":"Keith","email":"","middleInitial":"N.","affiliations":[{"id":37215,"text":"University of Maryland Center for Environmental Science","active":true,"usgs":false}],"preferred":false,"id":751071,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"St. John White, Barbara 0000-0001-8131-0534 bwhite@usgs.gov","orcid":"https://orcid.org/0000-0001-8131-0534","contributorId":141183,"corporation":false,"usgs":false,"family":"St. John White","given":"Barbara","email":"bwhite@usgs.gov","affiliations":[],"preferred":false,"id":751072,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Galbraith, Heather S. 0000-0003-3704-3517","orcid":"https://orcid.org/0000-0003-3704-3517","contributorId":204518,"corporation":false,"usgs":true,"family":"Galbraith","given":"Heather","email":"","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":751073,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lellis, William A. 0000-0001-7806-2904 wlellis@usgs.gov","orcid":"https://orcid.org/0000-0001-7806-2904","contributorId":2369,"corporation":false,"usgs":true,"family":"Lellis","given":"William","email":"wlellis@usgs.gov","middleInitial":"A.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":751074,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70199020,"text":"70199020 - 2018 - Sensitivity of mangrove range limits to climate variability","interactions":[],"lastModifiedDate":"2018-08-29T15:22:30","indexId":"70199020","displayToPublicDate":"2018-08-29T15:22:07","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1839,"text":"Global Ecology and Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Sensitivity of mangrove range limits to climate variability","docAbstract":"Aim
Correlative distribution models have been used to identify potential climatic controls of mangrove range limits, but there is still uncertainty about the relative importance of these factors across different regions. To provide insights into the strength of climatic control of different mangrove range limits, we tested whether temporal variability in mangrove abundance increases near range limits and whether this variability is correlated with climatic factors thought to control large‐scale mangrove distributions.
Location
North and South America.
Time period
1984–2011.
Major taxa studied
Avicennia germinans, Avicennia schuaeriana, Rhizophora mangle, Laguncularia racemosa.
Methods
We characterized temporal variability in the enhanced vegetation index (EVI) at mangrove range limits using Landsat satellite imagery collected between 1984–2011. We characterized greening trends at each range limit, examined variability in EVI along latitudinal gradients near each range limit, and assessed correlations between changes in EVI and temperature and precipitation.
Results
Spatial variability in mean EVI was generally correlated with temperature and precipitation, but the relationships were region specific. Greening trends were most pronounced at range limits in eastern North America. In these regions variability in EVI increased toward the range limit and was sensitive to climatic factors. In contrast, EVI at range limits on the Pacific coast of North America and both coasts of South America was relatively stable and less sensitive to climatic variability.
Main conclusions
Our results suggest that range limits in eastern North America are strongly controlled by climate factors. Mangrove expansion in response to future warming is expected to be rapid in regions that are highly sensitive to climate variability (e.g. eastern North America), but the response in other range limits (e.g. South America) is likely to be more complex and modulated by additional factors such as dispersal limitation, habitat constraints, and/or changing climatic means rather than just extremes.
Zebra mussels (Dreissena polymorpha, Pallas, 1771) are an aquatic invasive species in the
United States, and new infestations of zebra mussels can rapidly expand into dense colonies. Zebra
mussels were first reported in Marion Lake, Dakota County, Minnesota, in September 2017, and
surveys indicated the infestation was likely isolated near a public boat access. A 2.4-hectare area
containing the known zebra mussel infestation was enclosed and treated by area resource managers for
9 days with EarthTec QZ (target concentration: 0.5 milligrams per liter as copper), a copper-based
molluscicide, to eradicate the zebra mussels. Researchers led an onsite bioassay to provide an estimate
of the treatment efficacy within the enclosure. The bioassay was conducted in a mobile assay trailer that
received a continuous flow of treated lake water. Bioassay tanks (n=9; 350 liters) within the trailer were
stocked with zebra mussels (25 mussels per containment bag; 7 bags per tank) collected from White
Bear Lake, Ramsey County, Minn. Mortality in the treated bioassay tanks reached a mean of 99 percent
(95-percent confidence interval: 98–100 percent), there were no mortalities in the control tanks.
However, a predictive model produced for timely delivery to area resource managers indicated zebra
mussel mortality within the treated enclosure may have been as low as 85 percent. Onsite bioassays are
a viable and important tool for treatment evaluation particularly in newly infested waterbodies with low
zebra mussel densities.
Director, Upper Midwest Environmental Science Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54602
An understanding of riverine water-quality dynamics in regional mixed-land use watersheds is the foundation for advances in landscape biogeochemistry and informed land management. A differential implementation of the statistical/process-based model SPAtially Referenced Regressions on Watershed attributes (SPARROW; Smith et al., https://doi.org/10.1029/97wr02171) is proposed to empirically relate a regional pattern of changes in flow-normalized constituent flux, over a multiyear period, to contemporaneous changes in spatially referenced explanatory variables. In a pilot application, the differential model, called Spatiotemporal Watershed Accumulation of Net effects (SWAN), is used to explore factors influencing changes in flow-normalized flux of total nitrogen over the period 1990–2010 at 43 sites in the nontidal Chesapeake Bay watershed. A seven-parameter model explains 80% of the transformed variability in independently estimated flux changes, indicating that storage effects having characteristic time scales greater than 20 years had a small influence, relative to changes in inputs, on regional water-quality response. Results suggest that 1990–2010 changes in total-nitrogen flux are largely the outcome of increased nonpoint-source pollution associated with urban and suburban development, modulated to the point of negation by terrestrial losses stemming from widespread increases in air temperature and precipitation. The loss mechanism is qualitatively consistent with denitrification; however, increases in aboveground biomass, agricultural nitrogen exports, or hydrologic flushing are also plausible contributors. Although qualified by a small sample size and constraints on explanatory data availability, the pilot suggests that SWAN is a promising approach for broadening scientific understanding of factors driving regional water-quality change and for supporting evidence-based land-management decisions.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2017WR022403","usgsCitation":"Chanat, J.G., and Yang, G., 2018, Exploring drivers of regional water-quality change using differential spatially referenced regression – A pilot study in the Chesapeake Bay watershed: Water Resources Research, v. 54, no. 10, p. 8120-8145, https://doi.org/10.1029/2017WR022403.","productDescription":"26 p.","startPage":"8120","endPage":"8145","ipdsId":"IP-093045","costCenters":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"links":[{"id":468466,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017wr022403","text":"Publisher Index Page"},{"id":390388,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n 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-75.882568359375,\n 37.42252593456307\n ],\n [\n -75.618896484375,\n 37.640334898059486\n ],\n [\n -75.509033203125,\n 37.82280243352756\n ],\n [\n -75.38818359375,\n 38.013476231041935\n ],\n [\n -75.16845703124999,\n 38.272688535980976\n ],\n [\n -75.1904296875,\n 38.41916639395372\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"10","noUsgsAuthors":false,"publicationDate":"2018-10-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Chanat, Jeffrey G. 0000-0002-3629-7307 jchanat@usgs.gov","orcid":"https://orcid.org/0000-0002-3629-7307","contributorId":5062,"corporation":false,"usgs":true,"family":"Chanat","given":"Jeffrey","email":"jchanat@usgs.gov","middleInitial":"G.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824897,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yang, Guoxiang 0000-0001-5587-3683","orcid":"https://orcid.org/0000-0001-5587-3683","contributorId":267279,"corporation":false,"usgs":false,"family":"Yang","given":"Guoxiang","affiliations":[{"id":55459,"text":"NSA Contractor to USGS VA and WV WSC","active":true,"usgs":false}],"preferred":false,"id":824898,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70198358,"text":"ofr20181123 - 2018 - Effects of proposed navigation channel improvements on sediment transport in Mobile Harbor, Alabama","interactions":[],"lastModifiedDate":"2018-08-29T14:58:16","indexId":"ofr20181123","displayToPublicDate":"2018-08-29T08:30:00","publicationYear":"2018","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":"2018-1123","title":"Effects of proposed navigation channel improvements on sediment transport in Mobile Harbor, Alabama","docAbstract":"A Delft3D model was developed to evaluate the potential effects of proposed navigation
channel deepening and widening in Mobile Harbor, Alabama. The model performance was
assessed through comparisons of modeled and observed data of water levels, velocities, and bed
level changes; the model captured hydrodynamic and sediment transport patterns in the study
area with skill. The validated model was used to simulate changes in sediment transport for existing
conditions and with the proposed modifications to the navigational channel (with-project),
with and without accounting for 0.5 meter (m) of sea level rise (SLR). Each scenario was simulated
for 1 year with a wave climatology representative of the year 2010 as well as for 10 years
with a longer-term wave climatology spanning from 1988 to 2016. Bed level differences for the
existing and with-project 2010 simulations were minimal, ranging from −0.11 to 0.11 m offshore
of Pelican Island and −0.81 to 0.22 m offshore of the Fort Morgan Peninsula. For the simulations
accounting for 0.5 m of SLR, differences in bed levels from −0.20 to 0.32 m near Pelican
Island and −0.38 to 0.34 m offshore of the Fort Morgan Peninsula. The proposed modifications
reduced the channel shoaling volume by 4.77 and 8.09 percent for the 2010 simulations without
and with 0.5 m of SLR, respectively. For the 10-year simulations, bed level differences for the
existing and with-project simulations ranged from −3.17 to 3.94 m for the simulation without
SLR and −1.92 to 1.47 m for the simulation with 0.5 m of SLR. The with-project condition reduced
the entrance channel shoaling volume by 5.54 percent for the simulation without SLR and
14.98 percent for the simulation with 0.5 m of SLR.
Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
The epicenter of the 16 July 1936
Conceptual and numerical models were developed to understand and simulate monthly flow-weighted dissolved-solids concentrations in the Colorado River at Imperial Dam. The ability to simulate dissolved-solids concentrations at this location will help the Bureau of Reclamation satisfy the binational agreement on the volume and salinity of Colorado River water delivered to Mexico. A robust spatial- and temporal-resolution dataset that consists of river discharge and dissolved-solids concentration and load information between January 1990 and September 2016 for 10 sites on canals, drains, tributaries, and the main stem of the Colorado River between Hoover and Imperial Dams was generated. Daily mean dissolved-solids concentrations were estimated and monthly mean dissolved-solids loads were computed for each site. Spatial and temporal load patterns, and historical and current controls on loads and concentrations, were analyzed in order to develop a conceptual model of dissolved-solids transport between Hoover and Imperial Dams. Two numerical models describing the relations between dissolved-solids concentrations and components controlling dissolved-solids concentrations and loads were developed, calibrated, and verified.
Between January 1990 and September 2016, there was a 98.8-million-acre-feet loss of water and a 57.0-million-ton loss of dissolved-solids load from the Colorado River between Hoover and Imperial Dams. Between Hoover and Parker Dams, about 69.0 million acre-feet of water was lost and 51.1 million tons of dissolved solids were lost; between Parker and Imperial Dams, about 29.8 million acre-feet of water was lost and 5.9 million tons of dissolved solids were lost. Water was removed from the river at a relatively consistent rate over the 25-year study period through water transfers to California and Arizona, evapotranspiration from crop irrigation, transpiration processes of riparian vegetation, and evaporation from the river main stem. Dissolved solids were removed from the river between Hoover and Parker Dams at a relatively constant rate through water transfers to California and Arizona, and water pumped from the river for irrigation within the Mohave Valley. A small amount of dissolved solids are gained by the river from inflow from the Bill Williams River. Between Parker and Imperial Dams, however, dissolved solids were not removed from the river at a consistent rate over the study period. Dissolved solids were generally removed from the river from 1990 to 2012, then gained by the river from 2012 to 2015, and then removed from the river from 2015 through 2016. Dissolved solids are assumed to be removed from the river and accumulated within the floodplain sediments and aquifers during irrigation processes; some dissolved solids may also be removed from the river through uptake by crops and riparian vegetation. Dissolved solids accumulated on the landscape and in the floodplain aquifer during irrigation are transported to the river during periods when the hydraulic gradient between the floodplain aquifer and the river is increased, causing a gain in dissolved solids in the river. Dissolved-solids gains in the river occur during periods of relatively low river discharge, such as during the winter months and during drier climatic conditions.
Two numerical models were developed and coefficients were estimated by using data from a May 2008-September 2016 calibration period. One model simulates concentrations at Imperial Dam based on the Colorado River system downstream from Parker Dam, and the other model simulates concentrations at Imperial Dam based on the Colorado River system downstream from Hoover Dam. Both models simulated monthly flow-weighted concentrations of dissolved solids for the Colorado River at Imperial Dam, which corresponded well with observed concentrations for the entire study period. The models are more sensitive to input variables of monthly discharge of the Colorado River below Parker Dam and monthly flow-weighted dissolved-solids concentrations of the Colorado River below Hoover Dam and Parker Dam than to the rate of change in concentration with respect to time and the combined discharge of the Colorado River Indian Reservation Main Canal and the Palo Verde Canal. The calibrated models can be used to run scenarios of future monthly flow-weighted dissolved-solids concentrations in the Colorado River at Imperial Dam. Although the models are expected to provide concentration estimates within 18 milligrams per liter (Parker Dam to Imperial Dam model) to 22 milligrams per liter (Hoover Dam to Imperial Dam model), 95 percent of the time, the error of future scenarios increases as uncertainty in the estimated future input variables increases.
Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
While the influence of antecedent conditions on watershed function is widely recognized under typical hydrologic regimes, gaps remain in the context of extreme climate events (ECEs). ECEs are those events that far exceed seasonal norms of intensity, duration, or impact upon the physical environment or ecosystem. In this synthesis, we discuss the role of source availability and hydrologic connectivity on antecedent conditions and propose a conceptual framework to characterize system response to ECEs at the watershed scale. We present four case studies in detail that span a range of types of antecedent conditions and type of ECE to highlight important controls and feedbacks. Because ECEs have the potential to export large amounts of water and materials, their occurrence in sequence can disproportionately amplify the response. In fact, multiple events may not be considered extreme in isolation, but when they occur in close sequence they may lead to extreme responses in terms of both supply and transport capacity. Therefore, to advance our understanding of these complexities, we need continued development of a mechanistic understanding of how antecedent conditions set the stage for ECE response across multiple regions and climates, particularly since monitoring of these rare events is costly and difficult to obtain. Through focused monitoring of critical ecosystems during rare events we will also be able to extend and validate modeling studies. Cross-regional comparisons are also needed to define characteristics of resilient systems. These monitoring, modeling, and synthesis efforts are more critical than ever in light of changing climate regimes, intensification of human modifications of the landscape, and the disproportionate impact of ECEs in highly populated regions.
","language":"English","publisher":"Springer","doi":"10.1007/s10533-018-0482-6","usgsCitation":"McMillan, S.K., Wilson, H.F., Tague, C.L., Hanes, D.M., Inamdar, S., Karwan, D.L., Loecke, T., Morrison, J., Murphy, S.F., and Vidon, P., 2018, Before the storm: Antecedent conditions as regulators of hydrologic and biogeochemical response to extreme climate events: Biogeochemistry, v. 141, no. 3, p. 487-501, https://doi.org/10.1007/s10533-018-0482-6.","productDescription":"15 p.","startPage":"487","endPage":"501","ipdsId":"IP-092162","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":356841,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"141","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-16","publicationStatus":"PW","scienceBaseUri":"5b98a271e4b0702d0e842ed6","contributors":{"authors":[{"text":"McMillan, Sara K.","contributorId":207309,"corporation":false,"usgs":false,"family":"McMillan","given":"Sara","email":"","middleInitial":"K.","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":743514,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Henry F.","contributorId":207310,"corporation":false,"usgs":false,"family":"Wilson","given":"Henry","email":"","middleInitial":"F.","affiliations":[{"id":24491,"text":"Agriculture and Agri-Food Canada","active":true,"usgs":false}],"preferred":false,"id":743515,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tague, Christina L.","contributorId":207311,"corporation":false,"usgs":false,"family":"Tague","given":"Christina","email":"","middleInitial":"L.","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":743516,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanes, Daniel M.","contributorId":207312,"corporation":false,"usgs":false,"family":"Hanes","given":"Daniel","email":"","middleInitial":"M.","affiliations":[{"id":37518,"text":"St. Louis University","active":true,"usgs":false}],"preferred":false,"id":743517,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Inamdar, Shreeram","contributorId":177337,"corporation":false,"usgs":false,"family":"Inamdar","given":"Shreeram","affiliations":[],"preferred":false,"id":743518,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Karwan, Diana L.","contributorId":207315,"corporation":false,"usgs":false,"family":"Karwan","given":"Diana","email":"","middleInitial":"L.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":743522,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Loecke, Terry","contributorId":207313,"corporation":false,"usgs":false,"family":"Loecke","given":"Terry","email":"","affiliations":[{"id":6773,"text":"University of Kansas","active":true,"usgs":false}],"preferred":false,"id":743519,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morrison, Jonathan 0000-0002-1756-4609","orcid":"https://orcid.org/0000-0002-1756-4609","contributorId":203255,"corporation":false,"usgs":true,"family":"Morrison","given":"Jonathan","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":743520,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":743513,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Vidon, Philippe","contributorId":207314,"corporation":false,"usgs":false,"family":"Vidon","given":"Philippe","email":"","affiliations":[{"id":37519,"text":"SUNY College of Environmental Science and Forestry","active":true,"usgs":false}],"preferred":false,"id":743521,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70198988,"text":"70198988 - 2018 - Input data processing tools for the integrated hydrologic model GSFLOW","interactions":[],"lastModifiedDate":"2018-08-28T13:25:31","indexId":"70198988","displayToPublicDate":"2018-08-28T13:25:28","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Input data processing tools for the integrated hydrologic model GSFLOW","docAbstract":"Integrated hydrologic modeling (IHM) encompasses a vast number of processes and specifications, variable in time and space, and development of models can be arduous. Model input construction techniques have not been formalized or made easily reproducible. Creating the input files for integrated hydrologic models requires complex GIS processing of raster and vector datasets from various sources. Developing stream network topology that is consistent with the model grid-scale digital elevation model (DEM) is important for robust simulation of surface water and groundwater exchanges. Distribution of meteorological data over the model domain is difficult in complex terrain at the model-grid scale, but is necessary for realistic simulations. As model development requires extensive GIS and computer programming expertise, the use of IHMs has mostly been limited to research groups with available financial, human, and technical resources. Here we present a series of open-source Python scripts that are combined with ESRI ArcGIS to provide a formalized technique for the parameterization and development of inputs for the readily available IHM called GSFLOW. This Python toolkit automates many of the necessary and laborious processes of parameterization, including stream network development, land coverages, and meteorological distribution over the model domain. The final products of the toolkit are PRMS ready Parameter Files, along with several input parameters for a MODFLOW model, including input for the Streamflow Routing Package. A demonstration of the toolkit is provided to illustrate its capabilities.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2018.07.020","usgsCitation":"Gardner, M.A., Morton, C.G., Huntington, J., Niswonger, R., and Henson, W.R., 2018, Input data processing tools for the integrated hydrologic model GSFLOW: Environmental Modelling and Software, v. 109, p. 41-53, https://doi.org/10.1016/j.envsoft.2018.07.020.","productDescription":"13 p.","startPage":"41","endPage":"53","ipdsId":"IP-092325","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":468469,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2018.07.020","text":"Publisher Index Page"},{"id":356840,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"109","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a272e4b0702d0e842ed8","contributors":{"authors":[{"text":"Gardner, Murphy A. 0000-0002-3951-6667","orcid":"https://orcid.org/0000-0002-3951-6667","contributorId":207374,"corporation":false,"usgs":true,"family":"Gardner","given":"Murphy","email":"","middleInitial":"A.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":743645,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morton, Charles G.","contributorId":207375,"corporation":false,"usgs":false,"family":"Morton","given":"Charles","email":"","middleInitial":"G.","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":743652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huntington, Justin L.","contributorId":31279,"corporation":false,"usgs":true,"family":"Huntington","given":"Justin L.","affiliations":[],"preferred":false,"id":743653,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Niswonger, Richard G. 0000-0001-6397-2403 rniswon@usgs.gov","orcid":"https://orcid.org/0000-0001-6397-2403","contributorId":2833,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard G.","email":"rniswon@usgs.gov","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":false,"id":743654,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Henson, Wesley R. 0000-0003-4962-5565 whenson@usgs.gov","orcid":"https://orcid.org/0000-0003-4962-5565","contributorId":384,"corporation":false,"usgs":true,"family":"Henson","given":"Wesley","email":"whenson@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":743655,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198947,"text":"70198947 - 2018 - Twelve questions for the participatory modeling community","interactions":[],"lastModifiedDate":"2018-09-10T10:52:04","indexId":"70198947","displayToPublicDate":"2018-08-28T13:20:44","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5053,"text":"Earth's Future","active":true,"publicationSubtype":{"id":10}},"title":"Twelve questions for the participatory modeling community","docAbstract":"Participatory modeling engages the implicit and explicit knowledge of stakeholders to create formalized and shared representations of reality and has evolved into a field of study as well as a practice. Participatory modeling researchers and practitioners who focus specifically on environmental resources met at the National Socio‐Environmental Synthesis Center (SESYNC) in Annapolis, Maryland, over the course of 2 years to discuss the state of the field and future directions for participatory modeling. What follows is a description of 12 overarching groups of questions that could guide future inquiry.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018EF000841","usgsCitation":"Jordan, R., Gray, S., Zellner, M., Glynn, P.D., Voinov, A., Hedelin, B., Sterling, E.J., Leong, K., Olabisi, L.S., Hubacek, K., Bommel, P., BenDor, T.K., Jetter, A.J., Laursen, B., Singer, A., Giabbanelli, P.J., Kolagani, N., Carrera, L., Jenni, K., Prell, C., and National Socio-Environmental Synthesis Center Participatory Modeling Pursuit Working Group, 2018, Twelve questions for the participatory modeling community: Earth's Future, v. 6, no. 8, p. 1046-1057, https://doi.org/10.1029/2018EF000841.","productDescription":"12 p.","startPage":"1046","endPage":"1057","ipdsId":"IP-097317","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":468470,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018ef000841","text":"Publisher Index Page"},{"id":356839,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"8","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-03","publicationStatus":"PW","scienceBaseUri":"5b98a272e4b0702d0e842eda","contributors":{"authors":[{"text":"Jordan, Rebecca","contributorId":201914,"corporation":false,"usgs":false,"family":"Jordan","given":"Rebecca","email":"","affiliations":[{"id":36292,"text":"Rutgers University, Human Ecology & Ecology, Evolution and Natural Resources School of Environmental and Biological Sciences, 59 Lipman Drive, New Brunswick, NJ 08901","active":true,"usgs":false}],"preferred":false,"id":743524,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gray, Steven","contributorId":201912,"corporation":false,"usgs":false,"family":"Gray","given":"Steven","email":"","affiliations":[{"id":36290,"text":"Michigan State University, Department of Community Sustainability, Natural Resource Building 480 Wilson Road Room 151, East Lansing, MI 48824","active":true,"usgs":false}],"preferred":false,"id":743525,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zellner, Moira","contributorId":201924,"corporation":false,"usgs":false,"family":"Zellner","given":"Moira","affiliations":[{"id":36300,"text":"University of Illinois at Chicago, Department of Urban Planning & Policy and Institute for Environmental Science and Policy. 412 S. Peoria St., MC 348, Chicago, IL 60607","active":true,"usgs":false}],"preferred":false,"id":743526,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glynn, Pierre D. 0000-0001-8804-7003 pglynn@usgs.gov","orcid":"https://orcid.org/0000-0001-8804-7003","contributorId":2141,"corporation":false,"usgs":true,"family":"Glynn","given":"Pierre","email":"pglynn@usgs.gov","middleInitial":"D.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":743523,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Voinov, Alexey","contributorId":191330,"corporation":false,"usgs":false,"family":"Voinov","given":"Alexey","affiliations":[],"preferred":false,"id":743527,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hedelin, Beatrice","contributorId":201917,"corporation":false,"usgs":false,"family":"Hedelin","given":"Beatrice","email":"","affiliations":[{"id":36295,"text":"Karlstad University, Centre for Climate and Safety, Department of Environmental and Life Sciences, SE-651 88 Karlstad, Sweden","active":true,"usgs":false}],"preferred":false,"id":743528,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sterling, Eleanor J.","contributorId":145439,"corporation":false,"usgs":false,"family":"Sterling","given":"Eleanor","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":743529,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Leong, Kirsten","contributorId":207317,"corporation":false,"usgs":false,"family":"Leong","given":"Kirsten","affiliations":[{"id":37520,"text":"NOAA Fisheries, Pacific Islands Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":743530,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Olabisi, Laura 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Bethany","contributorId":201920,"corporation":false,"usgs":false,"family":"Laursen","given":"Bethany","affiliations":[{"id":36298,"text":"Michigan State University, Departments of Community Sustainability and Philosophy, Natural Resource Building 480 Wilson Road Room 151, East Lansing, MI 48824","active":true,"usgs":false}],"preferred":false,"id":743536,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Singer, Alison","contributorId":201923,"corporation":false,"usgs":false,"family":"Singer","given":"Alison","email":"","affiliations":[{"id":36290,"text":"Michigan State University, Department of Community Sustainability, Natural Resource Building 480 Wilson Road Room 151, East Lansing, MI 48824","active":true,"usgs":false}],"preferred":false,"id":743537,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Giabbanelli, Philippe J.","contributorId":207321,"corporation":false,"usgs":false,"family":"Giabbanelli","given":"Philippe","email":"","middleInitial":"J.","affiliations":[{"id":37524,"text":"Department of Computer Science, Northern Illinois University","active":true,"usgs":false}],"preferred":false,"id":743538,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Kolagani, Nagesh","contributorId":191331,"corporation":false,"usgs":false,"family":"Kolagani","given":"Nagesh","email":"","affiliations":[],"preferred":false,"id":743539,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Carrera, Laura Basco","contributorId":207322,"corporation":false,"usgs":false,"family":"Carrera","given":"Laura Basco","affiliations":[{"id":37525,"text":"Unit Water Resource and Delta Management Deltares","active":true,"usgs":false}],"preferred":false,"id":743540,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Jenni, Karen","contributorId":207323,"corporation":false,"usgs":true,"family":"Jenni","given":"Karen","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":743541,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Prell, Christina","contributorId":201921,"corporation":false,"usgs":false,"family":"Prell","given":"Christina","email":"","affiliations":[{"id":36299,"text":"University of Maryland, Department of Sociology, 2112 Parren Mitchell Art-Sociology Building, 3834 Campus Drive, College Park, MD 20742","active":true,"usgs":false}],"preferred":false,"id":743650,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"National Socio-Environmental Synthesis Center Participatory Modeling Pursuit Working Group","contributorId":207376,"corporation":true,"usgs":false,"organization":"National Socio-Environmental Synthesis Center Participatory Modeling Pursuit Working Group","id":743651,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}} ,{"id":70198948,"text":"70198948 - 2018 - Designing a protected area to safeguard imperiled species from urbanization","interactions":[],"lastModifiedDate":"2019-01-28T09:25:34","indexId":"70198948","displayToPublicDate":"2018-08-28T13:12:21","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Designing a protected area to safeguard imperiled species from urbanization","docAbstract":"Reserve design is a process that can address ecological, social, and political factors to identify parcels of land needed to sustain wildlife populations and other natural resources. Acquisition of parcels for a large terrestrial reserve is difficult because it typically occurs over a long timeframe and thus invokes consideration of future conditions such as climate and urbanization changes. In central Florida, a new protected area, the Everglades Headwaters National Wildlife Refuge, has been authorized by the United States Government. The new refuge will host important threatened and endangered species and habitats, as well as be located to allow for species adaptation from climate change impacts. For this study we combined habitat objectives defined by the U.S. Fish and Wildlife Service and projections from two urbanization models to provide guidance for Everglades Headwaters National Wildlife Refuge design. We used Marxan with Zones to find near-optimal solutions for protecting explicit amounts of five target habitats. We identified parcels for inclusion into the reserve design that the model allocated among two zones representing different methods of protection: fee-simple purchase (up to 20,234 hectares authorized by the United States government), and conservation easement agreements (up to 40,469 hectares authorized). As expected, for all scenarios we found an increase in costs as the proportion of fee-simple purchases was increased, reflecting the lesser cost of easements, but the number of parcels required for protection differed little among scenarios. The two urbanization models showed considerable agreement over which habitat patches were not forecast to be developed, and showed some agreement over which parcels might be developed. The U.S. Fish and Wildlife Service may benefit from focusing on parcels that are selected frequently by our analyses under both urban scenarios because these parcels are more likely to be in areas where urbanization threats and demand for land is reduced. The reserve designs we generated met U.S. Fish and Wildlife Service habitat goals within fee and easement zone restrictions, and we found reserve configurations that fell well below the mandated size limit.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/072017-JFWM-060","usgsCitation":"Romanach, S.S., Stith, B., and Johnson, F.A., 2018, Designing a protected area to safeguard imperiled species from urbanization: Journal of Fish and Wildlife Management, v. 9, no. 2, p. 446-458, https://doi.org/10.3996/072017-JFWM-060.","productDescription":"13 p.","startPage":"446","endPage":"458","ipdsId":"IP-088649","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":460861,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/072017-jfwm-060","text":"Publisher Index Page"},{"id":356837,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.75750732421875,\n 27.23753666659069\n ],\n [\n -80.80169677734375,\n 27.23753666659069\n ],\n [\n -80.80169677734375,\n 28.29954416560909\n ],\n [\n -81.75750732421875,\n 28.29954416560909\n ],\n [\n -81.75750732421875,\n 27.23753666659069\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"2","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-14","publicationStatus":"PW","scienceBaseUri":"5b98a272e4b0702d0e842edc","contributors":{"authors":[{"text":"Romanach, Stephanie S. 0000-0003-0271-7825 sromanach@usgs.gov","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":140419,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","email":"sromanach@usgs.gov","middleInitial":"S.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":743543,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stith, Bradley","contributorId":175419,"corporation":false,"usgs":false,"family":"Stith","given":"Bradley","affiliations":[{"id":12876,"text":"Cherokee Nation Technology Solutions","active":true,"usgs":false}],"preferred":false,"id":743545,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Fred A. 0000-0002-5854-3695 fjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":2773,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred","email":"fjohnson@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":743544,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70198959,"text":"70198959 - 2018 - Life history characteristics may be as important as climate projections for defining range shifts: An example for common tree species in the intermountain western US","interactions":[],"lastModifiedDate":"2018-11-21T15:19:41","indexId":"70198959","displayToPublicDate":"2018-08-28T13:03:58","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Life history characteristics may be as important as climate projections for defining range shifts: An example for common tree species in the intermountain western US","docAbstract":"Aim
Predictions of future suitable habitat for plant species with climate change are known to be affected by uncertainty associated with statistical approaches, climate models and occurrence records. However, life history characteristics related to dispersal and establishment processes as well as sensitivity to barriers created by land‐use may also play important roles in shaping future distributions with climate change. We compared the uncertainty in predicted distributions associated with climate projections to uncertainty associated with species interactions related to dispersal and establishment and land‐use barriers with four common animal‐dispersed tree species in pinyon–juniper woodlands in the western United States, a region experiencing increasing fragmentation due to land‐use.
Location
Western USA.
Methods
We compared the effects of life history characteristics related to species interactions (long‐distance dispersal and facilitation), land‐use fragmentation and variation in climate projections on species distributions with climate change using a simulation model. We evaluated the impacts of these factors on three characteristics of species distributions, area occupied, range size, and distance between patches, across four 30‐year intervals centred on 2020, 2040, 2060 and 2080.
Results
We found that uncertainty associated with climate projections and the potential effects of facilitation on establishment had the greatest impact in distribution characteristics. The effects of all factors varied by species, despite their overlapping initial distributions and relatively similar dispersal traits, highlighting the impact of life history characteristics on model outcomes.
Main conclusions
These results suggest that assessments of species future range shifts and vulnerability to climate change should incorporate land‐use barriers and life history traits related to dispersal and establishment, particularly for species with strong facilitative interactions.
The combination of climate change and altered disturbance regimes is directly and indirectly affecting plant communities by mediating competitive interactions, resulting in shifts in species composition and abundance. Dryland plant communities, defined by low soil water availability and highly variable climatic regimes, are particularly vulnerable to climatic changes that exceed their historical range of variability. Individual‐based simulation models can be important tools to quantify the impacts of climate change, altered disturbance regimes, and their interaction on demographic and community‐level responses because they represent competitive interactions between individuals and individual responses to fluctuating environmental conditions. Here, we introduce STEPWAT2, an individual plant‐based simulation model for exploring the joint influence of climate change and disturbance regimes on dryland ecohydrology and plant community composition. STEPWAT2 utilizes a process‐based soil water model (SOILWAT2) to simulate available soil water in multiple soil layers, which plant individuals compete for based on the temporal matching of water and active root distributions with depth. This representation of resource utilization makes STEPWAT2 particularly useful for understanding how changes in soil moisture and altered disturbance regimes will concurrently impact demographic and community‐level responses in drylands. Our goals are threefold: (1) to describe the core modules and functions within STEPWAT2 (model description), (2) to validate STEPWAT2 model output using field data from big sagebrush plant communities (model validation), and (3) to highlight the usefulness of STEPWAT2 as a modeling framework for examining the impacts of climate change and disturbance regimes on dryland plant communities under future conditions (model application). To address goals 2 and 3, we focus on 15 sites that span the spatial extent of big sagebrush plant communities in the western United States. For goal 3, we quantify how climate change, fire, and grazing can interact to influence plant functional type biomass and composition. We use big sagebrush‐dominated plant communities to demonstrate the functionality of STEPWAT2, as these communities are among the most widespread dryland ecosystems in North America.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2394","usgsCitation":"Palmquist, K.A., Bradford, J.B., Martin, T.E., Schlaepfer, D., and Lauenroth, W.K., 2018, STEPWAT2: An individual‐based model for exploring the impact of climate and disturbance on dryland plant communities: Ecosphere, v. 9, no. 8, p. 1-23, https://doi.org/10.1002/ecs2.2394.","productDescription":"e02394; 23 p.","startPage":"1","endPage":"23","ipdsId":"IP-095177","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468472,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2394","text":"Publisher Index Page"},{"id":356834,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-22","publicationStatus":"PW","scienceBaseUri":"5b98a272e4b0702d0e842ee2","contributors":{"authors":[{"text":"Palmquist, Kyle A.","contributorId":169517,"corporation":false,"usgs":false,"family":"Palmquist","given":"Kyle","email":"","middleInitial":"A.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":743612,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":743614,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin, Trace E.","contributorId":138852,"corporation":false,"usgs":false,"family":"Martin","given":"Trace","email":"","middleInitial":"E.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":743615,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schlaepfer, Daniel R.","contributorId":105189,"corporation":false,"usgs":false,"family":"Schlaepfer","given":"Daniel R.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":743616,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lauenroth, William K.","contributorId":80982,"corporation":false,"usgs":false,"family":"Lauenroth","given":"William","email":"","middleInitial":"K.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":743613,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198966,"text":"70198966 - 2018 - Increasing connectivity between metapopulation ecology and landscape ecology","interactions":[],"lastModifiedDate":"2018-08-28T10:15:45","indexId":"70198966","displayToPublicDate":"2018-08-27T20:41:41","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Increasing connectivity between metapopulation ecology and landscape ecology","docAbstract":"Metapopulation ecology and landscape ecology aim to understand how spatial structure influences ecological processes, yet these disciplines address the problem using fundamentally different modeling approaches. Metapopulation models describe how the spatial distribution of patches affects colonization and extinction, but often do not account for the heterogeneity in the landscape between patches. Models in landscape ecology use detailed descriptions of landscape structure, but often without considering colonization and extinction dynamics. We present a novel spatially explicit modeling framework for narrowing the divide between these disciplines to advance understanding of the effects of landscape structure on metapopulation dynamics. Unlike previous efforts, this framework allows for statistical inference on landscape resistance to colonization using empirical data. We demonstrate the approach using 11 yr of data on a threatened amphibian in a desert ecosystem. Occupancy data for Lithobates chiricahuensis (Chiricahua leopard frog) were collected on the Buenos Aires National Wildlife Refuge (BANWR), Arizona, USA from 2007 to 2017 following a reintroduction in 2003. Results indicated that colonization dynamics were influenced by both patch characteristics and landscape structure. Landscape resistance increased with increasing elevation and distance to the nearest streambed. Colonization rate was also influenced by patch quality, with semi‐permanent and permanent ponds contributing substantially more to the colonization of neighboring ponds relative to intermittent ponds. Ponds that only hold water intermittently also had the highest extinction rate. Our modeling framework can be widely applied to understand metapopulation dynamics in complex landscapes, particularly in systems in which the environment between habitat patches influences the colonization process
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.2189","usgsCitation":"Howell, P., Muths, E.L., Hossack, B., Sigafus, B., and Chandler, R., 2018, Increasing connectivity between metapopulation ecology and landscape ecology: Ecology, v. 99, no. 5, p. 1119-1128, https://doi.org/10.1002/ecy.2189.","productDescription":"10 p.","startPage":"1119","endPage":"1128","ipdsId":"IP-073405","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468474,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.2189","text":"Publisher Index Page"},{"id":356817,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"99","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-25","publicationStatus":"PW","scienceBaseUri":"5b98a273e4b0702d0e842ee4","contributors":{"authors":[{"text":"Howell, Paige E.","contributorId":173495,"corporation":false,"usgs":false,"family":"Howell","given":"Paige E.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":743617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":743618,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hossack, Blake 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":207343,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":743619,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sigafus, Brent","contributorId":207344,"corporation":false,"usgs":true,"family":"Sigafus","given":"Brent","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":743620,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chandler, Richard rchandler@usgs.gov","contributorId":2511,"corporation":false,"usgs":true,"family":"Chandler","given":"Richard","email":"rchandler@usgs.gov","affiliations":[{"id":13266,"text":"Warnell School of Forestry and Natural Resources, The University of Georgia","active":true,"usgs":false}],"preferred":false,"id":743621,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198922,"text":"70198922 - 2018 - Effects of urbanization, and habitat composition on site occupancy of two snake species using regional monitoring data from southern California","interactions":[],"lastModifiedDate":"2018-10-04T13:21:21","indexId":"70198922","displayToPublicDate":"2018-08-27T14:22:32","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Effects of urbanization, and habitat composition on site occupancy of two snake species using regional monitoring data from southern California","docAbstract":"Detection data from a regional, reptile-monitoring program conducted by the U.S. Geological Survey were analyzed to understand the effects of urbanization and habitat composition on site occupancy of the coachwhip (Masticophis flagellum) and striped racer (M. lateralis) in coastal southern California. Likelihood-based occupancy models indicated striped racers responded to habitat composition, favoring scrub-dominated sites. Coachwhips also responded to habitat composition, favoring open habitats. However, unlike racers, coachwhip spatial population dynamics were strongly associated with the fragmentation and isolation of natural areas caused by urbanization. The odds of coachwhips occupying a site were 64 times greater in large connected areas than the most urbanized and fragmented sites. For coachwhips within urbanized and fragmented sites, the odds of extinction were 10 times greater and odds of colonization were five times lower than in large connected sites. Observed differences between both species in habitat use and specificity are supported by telemetry studies and corroborate existing knowledge of historical patterns of occurrence within the region. Movement data on the coachwhip and striped racer indicate the coachwhip is a wider-ranging species with a greater propensity to encounter roads and other edge environments. Collectively, the results suggest there is widespread loss of the coachwhip from the region, and that long-term persistence of remaining populations is dependent on metapopulation dynamics. The substantially different response of the two species to land-use change serves as a caution against the casual use of closely related species as surrogates in the development of species-specific conservation plans.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2018.e00427","usgsCitation":"Mitrovich, M.J., Diffendorfer, J., Brehme, C.S., and Fisher, R.N., 2018, Effects of urbanization, and habitat composition on site occupancy of two snake species using regional monitoring data from southern California: Global Ecology and Conservation, v. 15, p. 1-10, https://doi.org/10.1016/j.gecco.2018.e00427.","productDescription":"10 p.","startPage":"1","endPage":"10","ipdsId":"IP-100913","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468477,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2018.e00427","text":"Publisher Index Page"},{"id":437778,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9N958Z8","text":"USGS data release","linkHelpText":"Masticophis occupancy in southern California, 1995-2000"},{"id":356798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","volume":"15","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a273e4b0702d0e842eee","contributors":{"authors":[{"text":"Mitrovich, Milan J. 0000-0001-6053-1143","orcid":"https://orcid.org/0000-0001-6053-1143","contributorId":207272,"corporation":false,"usgs":false,"family":"Mitrovich","given":"Milan","email":"","middleInitial":"J.","affiliations":[{"id":37506,"text":"San Diego State University; former USGS employee","active":true,"usgs":false}],"preferred":false,"id":743441,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":743442,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brehme, Cheryl S. 0000-0001-8904-3354 cbrehme@usgs.gov","orcid":"https://orcid.org/0000-0001-8904-3354","contributorId":3419,"corporation":false,"usgs":true,"family":"Brehme","given":"Cheryl","email":"cbrehme@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":743443,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":743440,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70198919,"text":"70198919 - 2018 - Quantifying functional connectivity: The role of breeding habitat, abundance, and landscape features on range‐wide gene flow in sage‐grouse","interactions":[],"lastModifiedDate":"2018-08-27T14:05:24","indexId":"70198919","displayToPublicDate":"2018-08-27T14:05:20","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1601,"text":"Evolutionary Applications","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying functional connectivity: The role of breeding habitat, abundance, and landscape features on range‐wide gene flow in sage‐grouse","docAbstract":"Functional connectivity, quantified using landscape genetics, can inform conservation through the identification of factors linking genetic structure to landscape mechanisms. We used breeding habitat metrics, landscape attributes, and indices of grouse abundance, to compare fit between structural connectivity and genetic differentiation within five long‐established Sage‐Grouse Management Zones (MZ) I‐V using microsatellite genotypes from 6,844 greater sage‐grouse (Centrocercus urophasianus) collected across their 10.7 million‐km2 range. We estimated structural connectivity using a circuit theory‐based approach where we built resistance surfaces using thresholds dividing the landscape into “habitat” and “nonhabitat” and nodes were clusters of sage‐grouse leks (where feather samples were collected using noninvasive techniques). As hypothesized, MZ‐specific habitat metrics were the best predictors of differentiation. To our surprise, inclusion of grouse abundance‐corrected indices did not greatly improve model fit in most MZs. Functional connectivity of breeding habitat was reduced when probability of lek occurrence dropped below 0.25 (MZs I, IV) and 0.5 (II), thresholds lower than those previously identified as required for the formation of breeding leks, which suggests that individuals are willing to travel through undesirable habitat. The individual MZ landscape results suggested terrain roughness and steepness shaped functional connectivity across all MZs. Across respective MZs, sagebrush availability (<10%–30%; II, IV, V), tree canopy cover (>10%; I, II, IV), and cultivation (>25%; I, II, IV, V) each reduced movement beyond their respective thresholds. Model validations confirmed variation in predictive ability across MZs with top resistance surfaces better predicting gene flow than geographic distance alone, especially in cases of low and high differentiation among lek groups. The resultant resistance maps we produced spatially depict the strength and redundancy of range‐wide gene flow and can help direct conservation actions to maintain and restore functional connectivity for sage‐grouse.
","language":"English","publisher":"Wiley","doi":"10.1111/eva.12627","usgsCitation":"Row, J.R., Doherty, K., Cross, T.B., Schwartz, M.K., Oyler-McCance, S.J., Naugle, D.E., Knick, S.T., and Fedy, B., 2018, Quantifying functional connectivity: The role of breeding habitat, abundance, and landscape features on range‐wide gene flow in sage‐grouse: Evolutionary Applications, v. 11, no. 8, p. 1305-1321, https://doi.org/10.1111/eva.12627.","productDescription":"17 p.","startPage":"1305","endPage":"1321","ipdsId":"IP-091293","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468478,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eva.12627","text":"Publisher Index Page"},{"id":437779,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7RB73V0","text":"USGS data release","linkHelpText":"Genetic and functional connectivity data for greater sage-grouse across the species range generated 2005-2015 (ver. 2.0, December 2022)"},{"id":356795,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-12","publicationStatus":"PW","scienceBaseUri":"5b98a273e4b0702d0e842ef0","contributors":{"authors":[{"text":"Row, Jeffery R.","contributorId":178107,"corporation":false,"usgs":false,"family":"Row","given":"Jeffery","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":743427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doherty, Kevin E.","contributorId":177793,"corporation":false,"usgs":false,"family":"Doherty","given":"Kevin E.","affiliations":[],"preferred":false,"id":743428,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cross, Todd B.","contributorId":189267,"corporation":false,"usgs":false,"family":"Cross","given":"Todd","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":743429,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schwartz, Michael K.","contributorId":102326,"corporation":false,"usgs":true,"family":"Schwartz","given":"Michael","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":743430,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":743426,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Naugle, Dave E.","contributorId":207278,"corporation":false,"usgs":false,"family":"Naugle","given":"Dave","email":"","middleInitial":"E.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":743431,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Knick, Steven T. 0000-0003-4025-1704 steve_knick@usgs.gov","orcid":"https://orcid.org/0000-0003-4025-1704","contributorId":159,"corporation":false,"usgs":true,"family":"Knick","given":"Steven","email":"steve_knick@usgs.gov","middleInitial":"T.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":743432,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fedy, Bradley C.","contributorId":40536,"corporation":false,"usgs":true,"family":"Fedy","given":"Bradley C.","affiliations":[],"preferred":false,"id":743433,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70198894,"text":"70198894 - 2018 - Global Modern Charcoal Dataset (GMCD): A tool for exploring proxy-fire linkages and spatial patterns of biomass burning","interactions":[],"lastModifiedDate":"2019-06-03T13:19:34","indexId":"70198894","displayToPublicDate":"2018-08-27T12:35:27","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3217,"text":"Quaternary International","active":true,"publicationSubtype":{"id":10}},"title":"Global Modern Charcoal Dataset (GMCD): A tool for exploring proxy-fire linkages and spatial patterns of biomass burning","docAbstract":"Progresses in reconstructing Earth's history of biomass burning has motivated the development of a modern charcoal dataset covering the last decades through a community-based initiative called the Global Modern Charcoal Dataset (GMCD). As the frequency, intensity and spatial scale of fires are predicted to increase regionally and globally in conjunction with changing climate, anthropogenic activities and land-use patterns, there is an increasing need to further understand, calibrate and interrogate recent and past fire regimes as related to changing fire emissions and changing carbon sources and sinks. Discussions at the PAGES Global Paleofire Working Group workshop 2015, including paleoecologists, numerical modelers, statisticians, paleoclimatologists, archeologists, and anthropologists, identified an urgent need for an open, standardized, quality-controlled and globally representative dataset of modern sedimentary charcoal and other sediment-based fire proxies. This dataset fits into a gap between metrics of biomass burning indicators, current fire regimes and land cover, and carbon emissions inventories. The dataset will enable the calibration of paleofire data with other modern datasets including: data of satellite derived fire occurrence, vegetation patterns and species diversity, land cover change, and a range of sources capturing biochemical cycling. Standardized protocols are presented for collecting and analyzing sediment-based fire proxies, including charcoal, levoglucosan, black carbon, and soot. The GMCD will provide a publicly-accessible repository of modern fire sediment surface samples in all terrestrial ecosystems. Sample collection and contributions to the dataset will be solicited from lacustrine, peat, marine, glacial, or other sediments, from a wide variety of ecosystems and geographic locations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quaint.2017.03.046","usgsCitation":"Hawthorne, D., Courtney Mustaphi, C.J., Aleman, J.C., Blarquez, O., Colombaroli, D., Daniau, A., Marlon, J.R., Power, M., Vanniere, B., Han, Y., Hantson, S., Kehrwald, N.M., Magi, B.I., Yue, X., Carcaillet, C., Marchant, R., Ogunkoya, A., Githumbi, E.N., and Muriuki, R.M., 2018, Global Modern Charcoal Dataset (GMCD): A tool for exploring proxy-fire linkages and spatial patterns of biomass burning: Quaternary International, v. 488, p. 3-17, https://doi.org/10.1016/j.quaint.2017.03.046.","productDescription":"15 p.","startPage":"3","endPage":"17","ipdsId":"IP-085704","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":468480,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quaint.2017.03.046","text":"Publisher Index 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UK","active":true,"usgs":false}],"preferred":false,"id":743295,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aleman, Julie C.","contributorId":168919,"corporation":false,"usgs":false,"family":"Aleman","given":"Julie","email":"","middleInitial":"C.","affiliations":[{"id":25389,"text":"Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA","active":true,"usgs":false}],"preferred":false,"id":743296,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blarquez, Olivier","contributorId":207238,"corporation":false,"usgs":false,"family":"Blarquez","given":"Olivier","email":"","affiliations":[{"id":37492,"text":"Department de Geographie, Universite de Montreal, Montreal, Canada","active":true,"usgs":false}],"preferred":false,"id":743297,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Colombaroli, Daniele 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Bozeman, Montana, USA","active":true,"usgs":false}],"preferred":false,"id":743309,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Githumbi, Esther N.","contributorId":168922,"corporation":false,"usgs":false,"family":"Githumbi","given":"Esther","email":"","middleInitial":"N.","affiliations":[{"id":25391,"text":"York Institute for Tropical Ecosystems, Environment Department, University of York, York, UK","active":true,"usgs":false}],"preferred":false,"id":743310,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Muriuki, Rebecca M.","contributorId":207247,"corporation":false,"usgs":false,"family":"Muriuki","given":"Rebecca","email":"","middleInitial":"M.","affiliations":[{"id":37499,"text":"National Museums of Kenya, Earth Science Department, Paleobotany and Palynology Section, Nairobi, Kenya","active":true,"usgs":false}],"preferred":false,"id":743311,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70220399,"text":"70220399 - 2018 - Tools and methods in participatory modeling: Selecting the right tool for the job","interactions":[],"lastModifiedDate":"2021-05-11T12:01:45.324007","indexId":"70220399","displayToPublicDate":"2018-08-27T06:57:19","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7599,"text":"Environmental Modeling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Tools and methods in participatory modeling: Selecting the right tool for the job","docAbstract":"Various tools and methods are used in participatory modelling, at different stages of the process and for different purposes. The diversity of tools and methods can create challenges for stakeholders and modelers when selecting the ones most appropriate for their projects. We offer a systematic overview, assessment, and categorization of methods to assist modelers and stakeholders with their choices and decisions. Most available literature provides little justification or information on the reasons for the use of particular methods or tools in a given study. In most of the cases, it seems that the prior experience and skills of the modelers had a dominant effect on the selection of the methods used. While we have not found any real evidence of this approach being wrong, we do think that putting more thought into the method selection process and choosing the most appropriate method for the project can produce better results. Based on expert opinion and a survey of modelers engaged in participatory processes, we offer practical guidelines to improve decisions about method selection at different stages of the participatory modeling process.
The Sentinel-2A and Landsat-8 satellites carry on-board moderate resolution multispectral imagers for the purpose of documenting the Earth’s changing surface. Though they are independently built and managed, users will certainly take advantage of the opportunity to have higher temporal coverage by combining the datasets. Thus it is important for the radiometric and geometric calibration of the MultiSpectral Instrument (MSI) and the Operational Land Imager (OLI) to be compatible. Cross-calibration of MSI to OLI has been accomplished using multiple techniques involving the use of pseudo-invariant calibration sites (PICS) using direct comparisons as well as through use of PICS models predicting top-of-atmosphere reflectance. A team from the University of Arizona is acquiring field data under both instruments for vicarious calibration of the sensors. This paper shows that the work done to date by the Landsat and Sentinel-2 calibration teams has resulted in stable radiometric calibration for each instrument and consistency to ~2.5% between the instruments for all the spectral bands that the instruments have in common.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/22797254.2018.1507613","usgsCitation":"Barsi, J., Alhammoud, B., Czapla-Myers, J., Gascon, F., Haque, O., Kaewmanee, M., Leigh, L., and Markham, B., 2018, Sentinel-2A MSI and Landsat-8 OLI radiometric cross comparison over desert sites: European Journal of Remote Sensing, v. 51, no. 1, p. 822-837, https://doi.org/10.1080/22797254.2018.1507613.","productDescription":"16 p.","startPage":"822","endPage":"837","ipdsId":"IP-088432","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":494460,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/22797254.2018.1507613","text":"Publisher Index Page"},{"id":494383,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-08-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Barsi, Julia","contributorId":251781,"corporation":false,"usgs":false,"family":"Barsi","given":"Julia","email":"","affiliations":[{"id":50397,"text":"SSAI","active":true,"usgs":false}],"preferred":false,"id":946725,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alhammoud, Bahjat","contributorId":360058,"corporation":false,"usgs":false,"family":"Alhammoud","given":"Bahjat","affiliations":[{"id":85960,"text":"ARGANS Limited","active":true,"usgs":false}],"preferred":false,"id":946726,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Czapla-Myers, Jeffrey","contributorId":360059,"corporation":false,"usgs":false,"family":"Czapla-Myers","given":"Jeffrey","affiliations":[{"id":85963,"text":"College of Optical Sciences, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":946727,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gascon, Ferran","contributorId":360060,"corporation":false,"usgs":false,"family":"Gascon","given":"Ferran","affiliations":[{"id":85964,"text":"ESA/ESRIN","active":true,"usgs":false}],"preferred":false,"id":946728,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haque, Obaidul 0000-0002-0914-1446 ohaque@usgs.gov","orcid":"https://orcid.org/0000-0002-0914-1446","contributorId":4691,"corporation":false,"usgs":true,"family":"Haque","given":"Obaidul","email":"ohaque@usgs.gov","affiliations":[{"id":40546,"text":"KBR, Contractor to the USGS Earth Resources Observation and Science (EROS) Center","active":true,"usgs":false}],"preferred":true,"id":946729,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kaewmanee, Morakot","contributorId":360061,"corporation":false,"usgs":false,"family":"Kaewmanee","given":"Morakot","affiliations":[{"id":85965,"text":"IP Lab, SDSU","active":true,"usgs":false}],"preferred":false,"id":946730,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Leigh, Larry","contributorId":360062,"corporation":false,"usgs":false,"family":"Leigh","given":"Larry","affiliations":[{"id":85965,"text":"IP Lab, SDSU","active":true,"usgs":false}],"preferred":false,"id":946731,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Markham, Brian","contributorId":360063,"corporation":false,"usgs":false,"family":"Markham","given":"Brian","affiliations":[{"id":79115,"text":"NASA/GSFC","active":true,"usgs":false}],"preferred":false,"id":946732,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ]}