Identification and protection of water bodies used by anadromous species are critical in light of increasing threats to fish populations, yet often challenging given budgetary and logistical limitations. Noninvasive, rapid‐assessment, sampling techniques may reduce costs and effort while increasing species detection efficiencies. We used an intrinsic potential (IP) habitat model to identify high‐quality rearing habitats for Chinook Salmon Oncorhynchus tshawytscha and select sites to sample throughout the Chena River basin, Alaska, for juvenile occupancy using an environmental DNA (eDNA) approach. Water samples were collected from 75 tributary sites in 2014 and 2015. The presence of Chinook Salmon DNA in water samples was assessed using a species‐specific quantitative PCR (qPCR) assay. The IP model predicted over 900 stream kilometers in the basin to support high‐quality (IP ≥ 0.75) rearing habitat. Occupancy estimation based on eDNA samples indicated that 80% and 56% of previously unsampled sites classified as high or low IP (IP < 0.75), respectively, were occupied. The probability of detection (p) of Chinook Salmon DNA from three replicate water samples was high (p = 0.76) but varied with drainage area (km2). A power analysis indicated high power to detect proportional changes in occupancy based on parameter values estimated from eDNA occupancy models, although power curves were not symmetrical around zero, indicating greater power to detect positive than negative proportional changes in occupancy. Overall, the combination of IP habitat modeling and occupancy estimation provided a useful, rapid‐assessment method to predict and subsequently quantify the distribution of juvenile salmon in previously unsampled tributary habitats. Additionally, these methods are flexible and can be modified for application to other species and in other locations, which may contribute towards improved population monitoring and management.
","language":"English","publisher":"Wiley","doi":"10.1002/nafm.10014","usgsCitation":"Matter, A., Falke, J.A., Lopez, J.A., and Savereide, J.W., 2018, A rapid assessment method to estimate the distribution of juvenile Chinook Salmon in tributary habitats using eDNA and occupancy estimation: North American Journal of Fisheries Management, v. 38, no. 1, p. 223-236, https://doi.org/10.1002/nafm.10014.","productDescription":"14 p.","startPage":"223","endPage":"236","ipdsId":"IP-082148","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":354275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Chena River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -152.34741210937497,\n 62.935234870604695\n ],\n [\n -143.2177734375,\n 62.935234870604695\n ],\n [\n -143.2177734375,\n 66.08491099733617\n ],\n [\n -152.34741210937497,\n 66.08491099733617\n ],\n [\n -152.34741210937497,\n 62.935234870604695\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"38","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-11","publicationStatus":"PW","scienceBaseUri":"5afee6b9e4b0da30c1bfbd66","contributors":{"authors":[{"text":"Matter, A.","contributorId":68879,"corporation":false,"usgs":true,"family":"Matter","given":"A.","email":"","affiliations":[],"preferred":false,"id":735707,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":735390,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lopez, J. Andres","contributorId":14306,"corporation":false,"usgs":true,"family":"Lopez","given":"J.","email":"","middleInitial":"Andres","affiliations":[],"preferred":false,"id":735708,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Savereide, James W.","contributorId":204591,"corporation":false,"usgs":false,"family":"Savereide","given":"James","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":735709,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197108,"text":"70197108 - 2018 - Occupancy modeling of Parnassius clodius butterfly populations in Grand Teton National Park, Wyoming","interactions":[],"lastModifiedDate":"2018-05-29T13:24:26","indexId":"70197108","displayToPublicDate":"2018-05-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2356,"text":"Journal of Insect Conservation","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Occupancy modeling of Parnassius clodius butterfly populations in Grand Teton National Park, Wyoming","title":"Occupancy modeling of Parnassius clodius butterfly populations in Grand Teton National Park, Wyoming","docAbstract":"Estimating occupancy patterns and identifying vegetation characteristics that influence the presence of butterfly species are essential approaches needed for determining how habitat changes may affect butterfly populations in the future. The montane butterfly species, Parnassius clodius, was investigated to identify patterns of occupancy relating to habitat variables in Grand Teton National Park and Bridger-Teton National Forest, Wyoming, United States. A series of presence–absence surveys were conducted in 2013 in 41 mesic to xeric montane meadows that were considered suitable habitat for P. clodius during their flight season (June–July) to estimate occupancy (ψ) and detection probability (p). According to the null constant parameter model, P. clodius had high occupancy of ψ = 0.78 ± 0.07 SE and detection probability of p = 0.75 ± 0.04 SE. In models testing covariates, the most important habitat indicator for the occupancy of P. clodius was a strong negative association with big sagebrush (Artemisia tridentata; β = − 21.39 ± 21.10 SE) and lupine (Lupinus spp.; β = − 20.03 ± 21.24 SE). While P. clodius was found at a high proportion of meadows surveyed, the presence of A. tridentata may limit their distribution within montane meadows at a landscape scale because A. tridentata dominates a large percentage of the montane meadows in our study area. Future climate scenarios predicted for high elevations globally could cause habitat shifts and put populations of P. clodius and similar non-migratory butterfly populations at risk.
","language":"English","publisher":"Springer","doi":"10.1007/s10841-018-0060-1","usgsCitation":"Szcodronski, K., Debinski, D.M., and Klaver, R.W., 2018, Occupancy modeling of Parnassius clodius butterfly populations in Grand Teton National Park, Wyoming: Journal of Insect Conservation, v. 22, no. 2, p. 267-276, https://doi.org/10.1007/s10841-018-0060-1.","productDescription":"10 p.","startPage":"267","endPage":"276","ipdsId":"IP-091833","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468755,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10841-018-0060-1","text":"Publisher Index Page"},{"id":354260,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Grand Teton National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.94818115234375,\n 43.560491112629286\n ],\n [\n -110.3466796875,\n 43.560491112629286\n ],\n [\n -110.3466796875,\n 44.12702800650004\n ],\n [\n -110.94818115234375,\n 44.12702800650004\n ],\n [\n -110.94818115234375,\n 43.560491112629286\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-03","publicationStatus":"PW","scienceBaseUri":"5afee6b7e4b0da30c1bfbd58","contributors":{"authors":[{"text":"Szcodronski, Kimberly E.","contributorId":199591,"corporation":false,"usgs":false,"family":"Szcodronski","given":"Kimberly E.","affiliations":[],"preferred":false,"id":735669,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Debinski, Diane M.","contributorId":25361,"corporation":false,"usgs":true,"family":"Debinski","given":"Diane","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":735670,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":735618,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197081,"text":"70197081 - 2018 - Ecological neighborhoods as a framework for umbrella species selection","interactions":[],"lastModifiedDate":"2018-05-17T09:51:54","indexId":"70197081","displayToPublicDate":"2018-05-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Ecological neighborhoods as a framework for umbrella species selection","docAbstract":"Umbrella species are typically chosen because they are expected to confer protection for other species assumed to have similar ecological requirements. Despite its popularity and substantial history, the value of the umbrella species concept has come into question because umbrella species chosen using heuristic methods, such as body or home range size, are not acting as adequate proxies for the metrics of interest: species richness or population abundance in a multi-species community for which protection is sought. How species associate with habitat across ecological scales has important implications for understanding population size and species richness, and therefore may be a better proxy for choosing an umbrella species. We determined the spatial scales of ecological neighborhoods important for predicting abundance of 8 potential umbrella species breeding in Nebraska using Bayesian latent indicator scale selection in N-mixture models accounting for imperfect detection. We compare the conservation value measured as collective avian abundance under different umbrella species selected following commonly used criteria and selected based on identifying spatial land cover characteristics within ecological neighborhoods that maximize collective abundance. Using traditional criteria to select an umbrella species resulted in sub-maximal expected collective abundance in 86% of cases compared to selecting an umbrella species based on land cover characteristics that maximized collective abundance directly. We conclude that directly assessing the expected quantitative outcomes, rather than ecological proxies, is likely the most efficient method to maximize the potential for conservation success under the umbrella species concept.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2018.04.026","usgsCitation":"Stuber, E.F., and Fontaine, J.J., 2018, Ecological neighborhoods as a framework for umbrella species selection: Biological Conservation, v. 223, p. 112-119, https://doi.org/10.1016/j.biocon.2018.04.026.","productDescription":"8 p.","startPage":"112","endPage":"119","ipdsId":"IP-088708","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":354228,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"223","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6bbe4b0da30c1bfbd7a","contributors":{"authors":[{"text":"Stuber, Erica F.","contributorId":198581,"corporation":false,"usgs":false,"family":"Stuber","given":"Erica","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":735503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fontaine, Joseph J. 0000-0002-7639-9156 jfontaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7639-9156","contributorId":3820,"corporation":false,"usgs":true,"family":"Fontaine","given":"Joseph","email":"jfontaine@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":735502,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70198025,"text":"70198025 - 2018 - Crowding affects health, growth, and behavior in headstart pens for Agassiz's desert tortoise","interactions":[],"lastModifiedDate":"2018-07-16T11:19:51","indexId":"70198025","displayToPublicDate":"2018-05-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1210,"text":"Chelonian Conservation and Biology","active":true,"publicationSubtype":{"id":10}},"title":"Crowding affects health, growth, and behavior in headstart pens for Agassiz's desert tortoise","docAbstract":"Worldwide, scientists have headstarted threatened and endangered reptiles to augment depleted populations. Not all efforts have been successful. For the threatened Agassiz's desert tortoise (Gopherus agassizii), one challenge to recovery is poor recruitment of juveniles into adult populations, and this is being addressed through headstart programs. We evaluated 8 cohorts of juvenile desert tortoises from 1 to 8 yrs old in a headstart program at Edwards Air Force Base, California, for health, behavior, and growth. We also examined capacities of the headstart pens. Of 148 juveniles evaluated for health, 99.3% were below a prime condition index; 14.9% were lethargic and unresponsive; 59.5% had protruding spinal columns and associated concave scutes; 29.1% had evidence of ant bites; and 14.2% had moderate to severe injuries to limbs or shell. Lifetime growth rates for juveniles 1–8 yrs of age were approximately two times less than growth rates reported for wild populations. Tortoises in older cohorts had higher growth rates, and models indicated that high density in pens and burrow sharing negatively affected growth rates. Densities of tortoises in pens (205–2042/ha) were 350–3500 times higher than the average density recorded in the wild (< 1/ha) for tortoises of similar sizes. The predominant forage species available to juveniles were alien annual grasses, which are nutritionally inadequate for growth. We conclude that the headstart pens were of inadequate size, likely contained too few shelters, and lacked the necessary biomass of preferred forbs to sustain the existing population. Additional factors to consider for future reptilian headstart pens include vegetative cover, food sources, soil seed banks, and soil composition.
","language":"English","publisher":"Chelonian Research Foundation","doi":"10.2744/CCB-1248.1","usgsCitation":"Mack, J.S., Schneider, H.E., and Berry, K.H., 2018, Crowding affects health, growth, and behavior in headstart pens for Agassiz's desert tortoise: Chelonian Conservation and Biology, v. 17, no. 1, p. 14-26, https://doi.org/10.2744/CCB-1248.1.","productDescription":"13 p.","startPage":"14","endPage":"26","ipdsId":"IP-052914","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":495032,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2744/ccb-1248.1","text":"Publisher Index Page"},{"id":355549,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Los Angeles","otherGeospatial":"Edwards Air Force Base","volume":"17","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e584e4b060350a15d1c2","contributors":{"authors":[{"text":"Mack, Jeremy S. jmack@usgs.gov","contributorId":3851,"corporation":false,"usgs":true,"family":"Mack","given":"Jeremy","email":"jmack@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":739720,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schneider, Heather E. 0000-0002-1230-8892","orcid":"https://orcid.org/0000-0002-1230-8892","contributorId":206165,"corporation":false,"usgs":false,"family":"Schneider","given":"Heather","email":"","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":739721,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berry, Kristin H. 0000-0003-1591-8394 kristin_berry@usgs.gov","orcid":"https://orcid.org/0000-0003-1591-8394","contributorId":437,"corporation":false,"usgs":true,"family":"Berry","given":"Kristin","email":"kristin_berry@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":739688,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197087,"text":"70197087 - 2018 - Estimating distribution and connectivity of recolonizing American marten in the northeastern United States using expert elicitation techniques","interactions":[],"lastModifiedDate":"2019-01-28T09:34:55","indexId":"70197087","displayToPublicDate":"2018-05-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":774,"text":"Animal Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Estimating distribution and connectivity of recolonizing American marten in the northeastern United States using expert elicitation techniques","docAbstract":"The American marten Martes americana is a species of conservation concern in the northeastern United States due to widespread declines from over‐harvesting and habitat loss. Little information exists on current marten distribution and how landscape characteristics shape patterns of occupancy across the region, which could help develop effective recovery strategies. The rarity of marten and lack of historical distribution records are also problematic for region‐wide conservation planning. Expert opinion can provide a source of information for estimating species–landscape relationships and is especially useful when empirical data are sparse. We created a survey to elicit expert opinion and build a model that describes marten occupancy in the northeastern United States as a function of landscape conditions. We elicited opinions from 18 marten experts that included wildlife managers, trappers and researchers. Each expert estimated occupancy probability at 30 sites in their geographic region of expertise. We, then, fit the response data with a set of 58 models that incorporated the effects of covariates related to forest characteristics, climate, anthropogenic impacts and competition at two spatial scales (1.5 and 5 km radii), and used model selection techniques to determine the best model in the set. Three top models had strong empirical support, which we model averaged based on AIC weights. The final model included effects of five covariates at the 5‐km scale: percent canopy cover (positive), percent spruce‐fir land cover (positive), winter temperature (negative), elevation (positive) and road density (negative). A receiver operating characteristic curve indicated that the model performed well based on recent occurrence records. We mapped distribution across the region and used circuit theory to estimate movement corridors between isolated core populations. The results demonstrate the effectiveness of expert‐opinion data at modeling occupancy for rare species and provide tools for planning marten recovery in the northeastern United States.
","language":"English","publisher":"Zoological Society of London","doi":"10.1111/acv.12417","usgsCitation":"Aylward, C., Murdoch, J., Donovan, T.M., Kilpatrick, C., Bernier, C., and Katz, J., 2018, Estimating distribution and connectivity of recolonizing American marten in the northeastern United States using expert elicitation techniques: Animal Conservation, v. 21, no. 6, p. 483-495, https://doi.org/10.1111/acv.12417.","productDescription":"13 p.","startPage":"483","endPage":"495","ipdsId":"IP-090408","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":354225,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-16","publicationStatus":"PW","scienceBaseUri":"5afee6bae4b0da30c1bfbd74","contributors":{"authors":[{"text":"Aylward, C.M.","contributorId":204950,"corporation":false,"usgs":false,"family":"Aylward","given":"C.M.","email":"","affiliations":[],"preferred":false,"id":735540,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murdoch, J.D.","contributorId":204951,"corporation":false,"usgs":false,"family":"Murdoch","given":"J.D.","email":"","affiliations":[],"preferred":false,"id":735541,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Donovan, Therese M. 0000-0001-8124-9251 tdonovan@usgs.gov","orcid":"https://orcid.org/0000-0001-8124-9251","contributorId":204296,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":735528,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kilpatrick, C.W.","contributorId":24188,"corporation":false,"usgs":true,"family":"Kilpatrick","given":"C.W.","email":"","affiliations":[],"preferred":false,"id":735542,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bernier, C.","contributorId":204952,"corporation":false,"usgs":false,"family":"Bernier","given":"C.","email":"","affiliations":[],"preferred":false,"id":735543,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Katz, J.","contributorId":204953,"corporation":false,"usgs":false,"family":"Katz","given":"J.","email":"","affiliations":[],"preferred":false,"id":735544,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197085,"text":"70197085 - 2018 - Assessing rockfall susceptibility in steep and overhanging slopes using three-dimensional analysis of failure mechanisms","interactions":[],"lastModifiedDate":"2018-05-16T16:11:40","indexId":"70197085","displayToPublicDate":"2018-05-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2604,"text":"Landslides","active":true,"publicationSubtype":{"id":10}},"title":"Assessing rockfall susceptibility in steep and overhanging slopes using three-dimensional analysis of failure mechanisms","docAbstract":"Rockfalls strongly influence the evolution of steep rocky landscapes and represent a significant hazard in mountainous areas. Defining the most probable future rockfall source areas is of primary importance for both geomorphological investigations and hazard assessment. Thus, a need exists to understand which areas of a steep cliff are more likely to be affected by a rockfall. An important analytical gap exists between regional rockfall susceptibility studies and block-specific geomechanical calculations. Here we present methods for quantifying rockfall susceptibility at the cliff scale, which is suitable for sub-regional hazard assessment (hundreds to thousands of square meters). Our methods use three-dimensional point clouds acquired by terrestrial laser scanning to quantify the fracture patterns and compute failure mechanisms for planar, wedge, and toppling failures on vertical and overhanging rock walls. As a part of this work, we developed a rockfall susceptibility index for each type of failure mechanism according to the interaction between the discontinuities and the local cliff orientation. The susceptibility for slope parallel exfoliation-type failures, which are generally hard to identify, is partly captured by planar and toppling susceptibility indexes. We tested the methods for detecting the most susceptible rockfall source areas on two famously steep landscapes, Yosemite Valley (California, USA) and the Drus in the Mont-Blanc massif (France). Our rockfall susceptibility models show good correspondence with active rockfall sources. The methods offer new tools for investigating rockfall hazard and improving our understanding of rockfall processes.
","language":"English","publisher":"Springer","doi":"10.1007/s10346-017-0911-y","usgsCitation":"Matasci, B., Stock, G.M., Jaboyedoff, M., Carrea, D., Collins, B.D., Guerin, A., Matasci, G., and Ravanel, L., 2018, Assessing rockfall susceptibility in steep and overhanging slopes using three-dimensional analysis of failure mechanisms: Landslides, v. 15, no. 5, p. 859-878, https://doi.org/10.1007/s10346-017-0911-y.","productDescription":"20 p.","startPage":"859","endPage":"878","ipdsId":"IP-088131","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":487233,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://sde.hal.science/hal-01778413","text":"External Repository"},{"id":354227,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-09","publicationStatus":"PW","scienceBaseUri":"5afee6bbe4b0da30c1bfbd78","contributors":{"authors":[{"text":"Matasci, Battista","contributorId":204938,"corporation":false,"usgs":false,"family":"Matasci","given":"Battista","email":"","affiliations":[{"id":37010,"text":"University of Lausanne, Switzerland","active":true,"usgs":false}],"preferred":false,"id":735512,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stock, Greg M.","contributorId":202873,"corporation":false,"usgs":false,"family":"Stock","given":"Greg","email":"","middleInitial":"M.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":735513,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jaboyedoff, Michael","contributorId":204939,"corporation":false,"usgs":false,"family":"Jaboyedoff","given":"Michael","email":"","affiliations":[{"id":37010,"text":"University of Lausanne, Switzerland","active":true,"usgs":false}],"preferred":false,"id":735514,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carrea, Dario","contributorId":204940,"corporation":false,"usgs":false,"family":"Carrea","given":"Dario","email":"","affiliations":[{"id":37010,"text":"University of Lausanne, Switzerland","active":true,"usgs":false}],"preferred":false,"id":735515,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Collins, Brian D. 0000-0003-4881-5359 bcollins@usgs.gov","orcid":"https://orcid.org/0000-0003-4881-5359","contributorId":149278,"corporation":false,"usgs":true,"family":"Collins","given":"Brian","email":"bcollins@usgs.gov","middleInitial":"D.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":735511,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Guerin, Antoine","contributorId":204941,"corporation":false,"usgs":false,"family":"Guerin","given":"Antoine","email":"","affiliations":[{"id":37010,"text":"University of Lausanne, Switzerland","active":true,"usgs":false}],"preferred":false,"id":735516,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Matasci, G.","contributorId":204942,"corporation":false,"usgs":false,"family":"Matasci","given":"G.","email":"","affiliations":[{"id":37010,"text":"University of Lausanne, Switzerland","active":true,"usgs":false}],"preferred":false,"id":735517,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ravanel, L.","contributorId":204943,"corporation":false,"usgs":false,"family":"Ravanel","given":"L.","email":"","affiliations":[{"id":37011,"text":"University of Savoie, Chambery, France","active":true,"usgs":false}],"preferred":false,"id":735518,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70197088,"text":"70197088 - 2018 - Fall and winter microhabitat use and suitability for spring chinook salmon parr in a U.S. Pacific Northwest River","interactions":[],"lastModifiedDate":"2018-05-17T09:56:33","indexId":"70197088","displayToPublicDate":"2018-05-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Fall and winter microhabitat use and suitability for spring chinook salmon parr in a U.S. Pacific Northwest River","docAbstract":"Habitat degradation has been implicated as a primary threat to Pacific salmon Oncorhynchus spp. Habitat restoration and conservation are key toward stemming population declines; however, winter microhabitat use and suitability knowledge are lacking for small juvenile salmonids. Our objective was to characterize microhabitat use and suitability for spring Chinook Salmon Oncorhynchus tshawytscha parr during fall and winter. Using radiotelemetry techniques during October–February (2009–2011), we identified fall and winter microhabitat use by spring Chinook Salmon parr in Catherine Creek, northeastern Oregon. Tagged fish occupied two distinct gradient reaches (moderate and low). Using a mixed‐effects logistic regression resource selection function (RSF) model, we found evidence that microhabitat use was similar between free‐flowing and surface ice conditions. However, habitat use shifted between seasons; most notably, there was greater use of silt substrate and areas farther from the bank during winter. Between gradients, microhabitat use differed with greater use of large wood (LW) and submerged aquatic vegetation in the low‐gradient reach. Using a Bayesian RSF approach, we developed gradient‐specific habitat suitability criteria. Throughout the study area, deep depths and slow currents were most suitable, with the exception of the low‐gradient reach where moderate depths were optimal. Near‐cover coarse and fine substrates were most suitable in the moderate‐ and low‐gradient reaches, respectively. Near‐bank LW was most suitable throughout the study area. Multivariate principal component analyses (PCA) indicated co‐occurring deep depths supporting slow currents near cover were intensively occupied in the moderate‐gradient reach. In the low‐gradient reach, PCA indicated co‐occurring moderate depths, slow currents, and near‐bank cover were most frequently occupied. Our study identified suitable and interrelated microhabitat combinations that can guide habitat restoration for fall migrant and overwintering Chinook Salmon parr in Catherine Creek and potentially the Pacific Northwest.
","language":"English","publisher":"Wiley","doi":"10.1002/tafs.10011","usgsCitation":"Favrot, S.D., Jonasson, B.C., and Peterson, J., 2018, Fall and winter microhabitat use and suitability for spring chinook salmon parr in a U.S. Pacific Northwest River: Transactions of the American Fisheries Society, v. 147, no. 1, p. 151-170, https://doi.org/10.1002/tafs.10011.","productDescription":"20 p.","startPage":"151","endPage":"170","ipdsId":"IP-090878","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":354224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Catherine Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.191162109375,\n 44.315987905196906\n ],\n [\n -117.147216796875,\n 44.56699093657141\n ],\n [\n -116.83959960937499,\n 44.94924926661153\n ],\n [\n -116.45507812500001,\n 45.644768217751924\n ],\n [\n -116.52099609375,\n 45.744526980468436\n ],\n [\n -116.69677734375,\n 45.75985868785574\n ],\n [\n -116.96044921875,\n 45.98932892799953\n ],\n [\n -118.970947265625,\n 45.99696161820381\n ],\n [\n -119.13574218749999,\n 45.94351068030587\n ],\n [\n -119.388427734375,\n 45.93587062119052\n ],\n [\n -119.564208984375,\n 45.920587344733654\n ],\n [\n -119.981689453125,\n 45.82114340079471\n ],\n [\n -120.52001953124999,\n 45.68315803253308\n ],\n [\n -120.62988281249999,\n 45.73685954736049\n ],\n [\n -121.17919921875001,\n 45.62172169252446\n ],\n [\n -121.11328124999999,\n 43.01268088642034\n ],\n [\n -117.02636718749999,\n 43.04480541304369\n ],\n [\n -117.04833984375001,\n 43.8186748554532\n ],\n [\n -116.94946289062499,\n 43.88997537383687\n ],\n [\n -116.94946289062499,\n 43.96119063892024\n ],\n [\n -116.96044921875,\n 44.07969327425713\n ],\n [\n -116.87255859374999,\n 44.15068115978094\n ],\n [\n -116.96044921875,\n 44.22945656830167\n ],\n [\n -117.191162109375,\n 44.315987905196906\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"147","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-26","publicationStatus":"PW","scienceBaseUri":"5afee6bae4b0da30c1bfbd72","contributors":{"authors":[{"text":"Favrot, Scott D.","contributorId":171445,"corporation":false,"usgs":false,"family":"Favrot","given":"Scott","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":735538,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jonasson, Brian C.","contributorId":204949,"corporation":false,"usgs":false,"family":"Jonasson","given":"Brian","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":735539,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, James T. 0000-0002-7709-8590 james_peterson@usgs.gov","orcid":"https://orcid.org/0000-0002-7709-8590","contributorId":2111,"corporation":false,"usgs":true,"family":"Peterson","given":"James","email":"james_peterson@usgs.gov","middleInitial":"T.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":735529,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197077,"text":"70197077 - 2018 - Imidacloprid sorption and transport in cropland, grass buffer and riparian buffer soils","interactions":[],"lastModifiedDate":"2018-05-17T09:48:09","indexId":"70197077","displayToPublicDate":"2018-05-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3674,"text":"Vadose Zone Journal","active":true,"publicationSubtype":{"id":10}},"title":"Imidacloprid sorption and transport in cropland, grass buffer and riparian buffer soils","docAbstract":"An understanding of neonicotinoid sorption and transport in soil is critical for determining and mitigating environmental risk associated with the most widely used class of insecticides. The objective of this study was to evaluate mobility and transport of the neonicotinoid imidacloprid (ICD) in soils collected from cropland, grass vegetative buffer strip (VBS), and riparian VBS soils. Soils were collected at six randomly chosen sites within grids that encompassed all three land uses. Single-point equilibrium batch sorption experiments were conducted using radio-labeled (14C) ICD to determine solid–solution partition coefficients (Kd). Column experiments were conducted using soils collected from the three vegetation treatments at one site by packing soil into glass columns. Water flow was characterized by applying Br− as a nonreactive tracer. A single pulse of 14C-ICD was then applied, and ICD leaching was monitored for up to 45 d. Bromide and ICD breakthrough curves for each column were simulated using CXTFIT and HYDRUS-1D models. Sorption results indicated that ICD sorbs more strongly to riparian VBS (Kd = 22.6 L kg−1) than crop (Kd = 11.3 L kg−1) soils. Soil organic C was the strongest predictor of ICD sorption (p < 0.0001). The column transport study found mean peak concentrations of ICD at 5.83, 10.84, and 23.8 pore volumes for crop, grass VBS, and riparian VBS soils, respectively. HYDRUS-1D results indicated that the two-site, one-rate linear reversible model best described results of the breakthrough curves, indicating the complexity of ICD sorption and demonstrating its mobility in soil. Greater sorption and longer retention by the grass and riparian VBS soils than the cropland soil suggests that VBS may be a viable means to mitigate ICD loss from agroecosystems, thereby preventing ICD transport into surface water, groundwater, or drinking water resources.
","language":"English","publisher":"Soil Science Society of America","doi":"10.2136/vzj2017.07.0139","usgsCitation":"Satkowski, L.E., Goyne, K.W., Anderson, S., Lerch, R.N., Allen, C.R., and Snow, D.D., 2018, Imidacloprid sorption and transport in cropland, grass buffer and riparian buffer soils: Vadose Zone Journal, v. 17, no. 1, p. 1-12, https://doi.org/10.2136/vzj2017.07.0139.","productDescription":"12 p.","startPage":"1","endPage":"12","ipdsId":"IP-087113","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468760,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2136/vzj2017.07.0139","text":"Publisher Index Page"},{"id":354233,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-12","publicationStatus":"PW","scienceBaseUri":"5afee6bbe4b0da30c1bfbd80","contributors":{"authors":[{"text":"Satkowski, Laura E.","contributorId":204930,"corporation":false,"usgs":false,"family":"Satkowski","given":"Laura","email":"","middleInitial":"E.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":735491,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goyne, Keith W.","contributorId":204931,"corporation":false,"usgs":false,"family":"Goyne","given":"Keith","email":"","middleInitial":"W.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":735492,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Stephen H.","contributorId":204932,"corporation":false,"usgs":false,"family":"Anderson","given":"Stephen H.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":735493,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lerch, Robert N.","contributorId":204933,"corporation":false,"usgs":false,"family":"Lerch","given":"Robert","email":"","middleInitial":"N.","affiliations":[{"id":37009,"text":"USDA Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":735494,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":735490,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Snow, Daniel D.","contributorId":204934,"corporation":false,"usgs":false,"family":"Snow","given":"Daniel","email":"","middleInitial":"D.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":735495,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70198754,"text":"70198754 - 2018 - A guide to Bayesian model checking for ecologists","interactions":[],"lastModifiedDate":"2018-11-14T09:32:56","indexId":"70198754","displayToPublicDate":"2018-05-15T09:51:01","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1459,"text":"Ecological Monographs","active":true,"publicationSubtype":{"id":10}},"title":"A guide to Bayesian model checking for ecologists","docAbstract":"Checking that models adequately represent data is an essential component of applied statistical inference. Ecologists increasingly use hierarchical Bayesian statistical models in their research. The appeal of this modeling paradigm is undeniable, as researchers can build and fit models that embody complex ecological processes while simultaneously accounting for observation error. However, ecologists tend to be less focused on checking model assumptions and assessing potential lack of fit when applying Bayesian methods than when applying more traditional modes of inference such as maximum likelihood. There are also multiple ways of assessing the fit of Bayesian models, each of which has strengths and weaknesses. For instance, Bayesian P values are relatively easy to compute, but are well known to be conservative, producing P values biased toward 0.5. Alternatively, lesser known approaches to model checking, such as prior predictive checks, cross‐validation probability integral transforms, and pivot discrepancy measures may produce more accurate characterizations of goodness‐of‐fit but are not as well known to ecologists. In addition, a suite of visual and targeted diagnostics can be used to examine violations of different model assumptions and lack of fit at different levels of the modeling hierarchy, and to check for residual temporal or spatial autocorrelation. In this review, we synthesize existing literature to guide ecologists through the many available options for Bayesian model checking. We illustrate methods and procedures with several ecological case studies including (1) analysis of simulated spatiotemporal count data, (2) N‐mixture models for estimating abundance of sea otters from an aircraft, and (3) hidden Markov modeling to describe attendance patterns of California sea lion mothers on a rookery. We find that commonly used procedures based on posterior predictive P values detect extreme model inadequacy, but often do not detect more subtle cases of lack of fit. Tests based on cross‐validation and pivot discrepancy measures (including the “sampled predictive P value”) appear to be better suited to model checking and to have better overall statistical performance. We conclude that model checking is necessary to ensure that scientific inference is well founded. As an essential component of scientific discovery, it should accompany most Bayesian analyses presented in the literature.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecm.1314","usgsCitation":"Conn, P.B., Johnson, D., Williams, P.J., Melin, S.R., and Hooten, M., 2018, A guide to Bayesian model checking for ecologists: Ecological Monographs, v. 88, no. 4, p. 526-542, https://doi.org/10.1002/ecm.1314.","productDescription":"17 p.","startPage":"526","endPage":"542","ipdsId":"IP-091408","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":356616,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"88","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-14","publicationStatus":"PW","scienceBaseUri":"5b98a2c6e4b0702d0e842fe2","contributors":{"authors":[{"text":"Conn, Paul B.","contributorId":87440,"corporation":false,"usgs":true,"family":"Conn","given":"Paul","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":743048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Devin S.","contributorId":47524,"corporation":false,"usgs":true,"family":"Johnson","given":"Devin S.","affiliations":[],"preferred":false,"id":743049,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, Perry J.","contributorId":169058,"corporation":false,"usgs":false,"family":"Williams","given":"Perry","email":"","middleInitial":"J.","affiliations":[{"id":25400,"text":"U.S. Fish and Wildlife Service, Big Oaks National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":743050,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Melin, Sharon R.","contributorId":147080,"corporation":false,"usgs":false,"family":"Melin","given":"Sharon","email":"","middleInitial":"R.","affiliations":[{"id":6578,"text":"National Marine Fisheries Service, Seattle, WA 98112, USA","active":true,"usgs":false}],"preferred":false,"id":743051,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":742853,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70190581,"text":"sir20175100 - 2018 - Preliminary synthesis and assessment of environmental flows in the middle Verde River watershed, Arizona","interactions":[],"lastModifiedDate":"2019-05-15T09:24:27","indexId":"sir20175100","displayToPublicDate":"2018-05-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5100","title":"Preliminary synthesis and assessment of environmental flows in the middle Verde River watershed, Arizona","docAbstract":"A 3-year study was undertaken to evaluate the suitability of the available modeling tools for characterizing environmental flows in the middle Verde River watershed of central Arizona, describe riparian vegetation throughout the watershed, and estimate sediment mobilization in the river. Existing data on fish and macroinvertebrates were analyzed in relation to basin characteristics, flow regimes, and microhabitat, and a pilot study was conducted that sampled fish and macroinvertebrates and the microhabitats in which they were found. The sampling for the pilot study took place at five different locations in the middle Verde River watershed. This report presents the results of this 3-year study.
The Northern Arizona Groundwater Flow Model (NARGFM) was found to be capable of predicting long-term changes caused by alteration of regional recharge (such as may result from climate variability) and groundwater pumping in gaining, losing, and dry reaches of the major streams in the middle Verde River watershed. Over the period 1910 to 2006, the model simulated an increase in dry reaches, a small increase in reaches losing discharge to the groundwater aquifer, and a concurrent decrease in reaches gaining discharge from groundwater. Although evaluations of the suitability of using the NARGFM and Basin Characteristic Model to characterize various streamflow intervals showed that smallerscale basin monthly runoff could be estimated adequately at locations of interest, monthly stream-flow estimates were found unsatisfactory for determining environmental flows.
Orthoimagery and Moderate Resolution Imaging Spectroradiometer data were used to quantify stream and riparian vegetation properties related to biotic habitat. The relative abundance of riparian vegetation varied along the main channel of the Verde River. As would be expected, more upland plant species and fewer lowland species were found in the upper-middle section compared to the lower-middle section, and vice-versa. Vegetation changes within the upper-middle and lower-middle reaches are related to differences in climate and hydrology. In general, the riparian vegetation of the middle Verde River watershed is that of a healthy ecosystem’s mixed age, mixed patch structure, likely a result of the mostly unaltered disturbance regime.
The frequency of in-river hydrogeomorphic features (pool, riffle, run) varied along the middle Verde River channel. There was a greater abundance of riffle habitat in the upper-middle reach; the lower-middle reach included more pool habitat. The Oak Creek tributary was more homogenous in geomorphic stream habitat composition than West Clear Creek, where runs dominated the upper reaches and pools dominated many of the lower reaches.
On the basis of the period of record and discharges recorded at 15-minute intervals, five flows were found to reach the gravel-transport threshold. Sediment mobilization computed with flows averaged over daily time steps yielded just three flows that reached the gravel-transport threshold, and monthly averaged flows yielded none. In the middle Verde River watershed, 15-minute data should be used when possible to evaluate sediment transport in the river system.
Data from more than 300 fish surveys conducted from 1992 to 2011 were analyzed using two schemes, one that divided the river into five reaches based on basin characteristics, and a second that divided the river into five reaches based on degree of flow alteration (specifically, diversions). Fish community metrics and assemblage data were used to analyze patterns of species composition and abundance in the two approaches. Overall, native and non-native species were regularly interacting and probably competing for similar resources. Fish abundances were also analyzed in response to floods and other flow metrics. Although the data are limited, native fish abundances increased more rapidly than non-native fish abundances in response to large floods. The basin-characteristic reach analysis showed native fish in greater abundance in the upper-middle reaches of the Verde River watershed and generally decreasing with downstream distance. The median relative abundance of native fish decreased by 50 percent from reach 1 to reach 5. Using the reach scheme based on degree of flow alteration, nondiverted reaches were found to have a greater abundance of native fish than diverted reaches. In heavily diverted reaches, non-native species outnumbered native species.
Fish metrics and stream-flow metrics for the 30, 90, and 365-day periods before collection were computed and the results analyzed statistically. Only abundance of all fish species was associated with the 30-day flow metrics. The 90-day flow metrics were generally positively associated with fish metrics, whereas the 365-day flow metrics had more negative correlations. In particular, significant relations were found between fish metrics and the magnitude and frequency of high flows, including maximum monthly flow, median annual number of high-flow events, and median annual maximum streamflow. Native sucker (Catostomidae) populations tended to decrease in periods of extended base flow, and fish in the non-native sunfish family (Centrarchidae) decreased in periods of flashy, high magnitude flows.
A pilot study surveyed fish at five locations in the upper part of the middle Verde River watershed as a means to measure microhabitat availability and quantify native and non-native fish use of that available microhabitat. Results indicated that native and non-native species exhibit some clear differences in microhabitat use. Although at least some native and non-native fish were found in each velocity, depth, and substrate category, preferential microhabitat use was common. On a percentage basis, non-native species had a strong preference for slow-moving and deeper water with silt and sand substrate, with a secondary preference for faster moving and very shallow water and a coarse gravel substrate. Native species showed a general preference for somewhat faster, moderate depth water over coarse gravel and had no clear secondary preference.
Macroinvertebrate-variables index period, high-flow year, and collection location (upper-middle Verde River, lowermiddle Verde River, or Verde River tributaries) were found to be important explanatory variables in differentiating among community metrics. Overall richness (number of unique taxa), Shannon’s diversity index, and the percent of the most dominant taxa were all highly correlated, but their response to each macroinvertebrate variable was different. The percentage of mayfly (order Ephemeroptera) taxa was significantly higher in Oak Creek and the upper-middle and lower-middle Verde River reaches, locations which have higher flows and more urbanization than other reaches. When community metrics were related to hydrologic metrics, caddisfly (order Trichoptera) populations appeared to increase and mayfly populations to decrease in response to less flashy and more stable streamflows. Conversely, caddisfly populations appeared to decrease and mayfly populations to increase in response to greater flow variability.
Six locations along the Verde River were sampled for macroinvertebrates as part of a pilot study associated with this report—(1) below Granite Creek, (2) near Campbell Ranch, (3) at the U.S. Geological Survey Paulden gage, (4) at the Perkinsville Bridge, (5) at the USGS Clarkdale gage, and (6) near the Reitz Ranch property. A nonmetric multidimensional scaling ordination of macroinvertebrate assemblages showed that the Verde River below Granite Creek site was different from the five other sites and that the Perkinsville Bridge and near Reitz Ranch samples had similar community structure. The near Campbell Ranch and Paulden gage locations had similar microhabitat characteristics, with the exception of riparian cover, yet the assemblage structure was very different. The different community composition at Verde River below Granite Creek was likely due to it having the smallest substrate sizes, lowest velocities, shallowest depths, and most riparian cover of the six sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175100","collaboration":"Prepared in cooperation with The Nature Conservancy and Salt River Project","usgsCitation":"Paretti, N.V., Brasher, A.M.D., Pearlstein, S.L., Skow, D.M., Gungle, Bruce, and Garner, B.D., 2018, Preliminary synthesis and assessment of environmental flows in the middle Verde River watershed, Arizona: U.S. Geological Survey Scientific Investigations Report 2017–5100, 104 p., https://doi.org/10.3133/sir20175100.","productDescription":"Report: xii; 104 p.; 3 Tables","numberOfPages":"120","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-084364","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":354141,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5100/sir20175100_table14.csv","text":"Table 14","size":"5 KB","linkFileType":{"id":7,"text":"csv"},"description":"Scientific Investigation Report 2017-5100 Table 12"},{"id":354142,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5100/sir20175100_tables12_14.xlsx","text":"Table 12 and 14","size":"25 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Scientific Investigation Report 2017-5100 Table 12 and 14 Excel file"},{"id":354139,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5100/sir20175100.pdf","text":"Report","size":"17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Scientific Investigation Report 2017-5100"},{"id":354138,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5100/coverthb.jpg"},{"id":354140,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5100/sir20175100_table12.csv","text":"Table 12","size":"5 KB","linkFileType":{"id":7,"text":"csv"},"description":"Scientific Investigation Report 2017-5100 Table 12"}],"country":"United States","state":"Arizona","otherGeospatial":"Verde River Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.5,\n 34.5\n ],\n [\n -112.5,\n 34.5\n ],\n [\n -112.5,\n 35.5\n ],\n [\n -111.5,\n 35.5\n ],\n [\n -111.5,\n 34.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Predictions of the projected changes in species distributions and potential adaptation action benefits can help guide conservation actions. There is substantial uncertainty in projecting species distributions into an unknown future, however, which can undermine confidence in predictions or misdirect conservation actions if not properly considered. Recent studies have shown that the selection of alternative climate metrics describing very different climatic aspects (e.g., mean air temperature vs. mean precipitation) can be a substantial source of projection uncertainty. It is unclear, however, how much projection uncertainty might stem from selecting among highly correlated, ecologically similar climate metrics (e.g., maximum temperature in July, maximum 30‐day temperature) describing the same climatic aspect (e.g., maximum temperatures) known to limit a species’ distribution. It is also unclear how projection uncertainty might propagate into predictions of the potential benefits of adaptation actions that might lessen climate change effects. We provide probabilistic measures of climate change vulnerability, adaptation action benefits, and related uncertainty stemming from the selection of four maximum temperature metrics for brook trout (Salvelinus fontinalis), a cold‐water salmonid of conservation concern in the eastern United States. Projected losses in suitable stream length varied by as much as 20% among alternative maximum temperature metrics for mid‐century climate projections, which was similar to variation among three climate models. Similarly, the regional average predicted increase in brook trout occurrence probability under an adaptation action scenario of full riparian forest restoration varied by as much as .2 among metrics. Our use of Bayesian inference provides probabilistic measures of vulnerability and adaptation action benefits for individual stream reaches that properly address statistical uncertainty and can help guide conservation actions. Our study demonstrates that even relatively small differences in the definitions of climate metrics can result in very different projections and reveal high uncertainty in predicted climate change effects.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.14101","usgsCitation":"DeWeber, J.T., and Wagner, T., 2018, Probabilistic measures of climate change vulnerability, adaptation action benefits, and related uncertainty from maximum temperature metric selection: Global Change Biology, v. 24, no. 6, p. 2735-2748, https://doi.org/10.1111/gcb.14101.","productDescription":"14 p.","startPage":"2735","endPage":"2748","ipdsId":"IP-090617","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468761,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.14101","text":"Publisher Index Page"},{"id":354199,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-27","publicationStatus":"PW","scienceBaseUri":"5afee6bce4b0da30c1bfbd88","contributors":{"authors":[{"text":"DeWeber, Jefferson T.","contributorId":199675,"corporation":false,"usgs":false,"family":"DeWeber","given":"Jefferson","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":735454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":735167,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70197047,"text":"70197047 - 2018 - Carboniferous climate teleconnections archived in coupled bioapatite δ18OPO4 and 87Sr/86Sr records from the epicontinental Donets Basin, Ukraine","interactions":[],"lastModifiedDate":"2018-05-15T15:58:06","indexId":"70197047","displayToPublicDate":"2018-05-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Carboniferous climate teleconnections archived in coupled bioapatite δ18OPO4 and 87Sr/86Sr records from the epicontinental Donets Basin, Ukraine","title":"Carboniferous climate teleconnections archived in coupled bioapatite δ18OPO4 and 87Sr/86Sr records from the epicontinental Donets Basin, Ukraine","docAbstract":"Reconstructions of paleo-seawater chemistry are largely inferred from biogenic records of epicontinental seas. Recent studies provide considerable evidence for large-scale spatial and temporal variability in the environmental dynamics of these semi-restricted seas that leads to the decoupling of epicontinental isotopic records from those of the open ocean. We present conodont apatite δ18OPO4 and 87Sr/86Sr records spanning 24 Myr of the late Mississippian through Pennsylvanian derived from the U–Pb calibrated cyclothemic succession of the Donets Basin, eastern Ukraine. On a 2 to 6 Myr-scale, systematic fluctuations in bioapatite δ18OPO4 and 87Sr/86Sr broadly follow major shifts in the Donets onlap–offlap history and inferred regional climate, but are distinct from contemporaneous more open-water δ18OPO4 and global seawater Sr isotope trends.
A −1 to −6‰ offset in Donets δ18OPO4 values from those of more open-water conodonts and greater temporal variability in δ18OPO4 and 87Sr/86Sr records are interpreted to primarily record climatically driven changes in local environmental processes in the Donets sea. Systematic isotopic shifts associated with Myr-scale sea-level fluctuations, however, indicate an extrabasinal driver. We propose a mechanistic link to glacioeustasy through a teleconnection between high-latitude ice changes and atmospheric pCO2 and regional monsoonal circulation in the Donets region. Inferred large-magnitude changes in Donets seawater salinity and temperature, not archived in the more open-water or global contemporaneous records, indicate a modification of the global climate signal in the epicontinental sea through amplification or dampening of the climate signal by local and regional environmental processes. This finding of global climate change filtered through local processes has implications for the use of conodont δ18OPO4 and 87Sr/86Sr values as proxies of paleo-seawater composition, mean temperature, and glacioeustasy.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2018.03.051","usgsCitation":"Montanez, I.P., Osleger, D.J., Chen, J., Wortham, B.E., Stamm, R.G., Nemyrovska, T.I., Griffin, J.M., Poletaev, V.I., and Wardlaw, B.R., 2018, Carboniferous climate teleconnections archived in coupled bioapatite δ18OPO4 and 87Sr/86Sr records from the epicontinental Donets Basin, Ukraine: Earth and Planetary Science Letters, v. 492, p. 89-101, https://doi.org/10.1016/j.epsl.2018.03.051.","productDescription":"13 p.","startPage":"89","endPage":"101","ipdsId":"IP-090058","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":468762,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2018.03.051","text":"Publisher Index Page"},{"id":354190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Ukraine","otherGeospatial":"Donets Basin","volume":"492","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6bbe4b0da30c1bfbd82","contributors":{"authors":[{"text":"Montanez, Isabel P.","contributorId":204886,"corporation":false,"usgs":false,"family":"Montanez","given":"Isabel","email":"","middleInitial":"P.","affiliations":[{"id":37004,"text":"Department of Earth and Planetary Sciences, University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":735365,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Osleger, Dillon J.","contributorId":204887,"corporation":false,"usgs":false,"family":"Osleger","given":"Dillon","email":"","middleInitial":"J.","affiliations":[{"id":37004,"text":"Department of Earth and Planetary Sciences, University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":735366,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chen, J.-H.","contributorId":203812,"corporation":false,"usgs":false,"family":"Chen","given":"J.-H.","email":"","affiliations":[{"id":36211,"text":"GFDL/NOAA","active":true,"usgs":false}],"preferred":false,"id":735367,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wortham, Barbara E.","contributorId":204904,"corporation":false,"usgs":false,"family":"Wortham","given":"Barbara","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":735419,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stamm, Robert G. 0000-0001-9141-5364","orcid":"https://orcid.org/0000-0001-9141-5364","contributorId":204885,"corporation":false,"usgs":true,"family":"Stamm","given":"Robert","email":"","middleInitial":"G.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":735364,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nemyrovska, Tamara I.","contributorId":204888,"corporation":false,"usgs":false,"family":"Nemyrovska","given":"Tamara","email":"","middleInitial":"I.","affiliations":[{"id":37005,"text":"Department of Paleontology and Stratigraphy, Institute of Geological Science, Ukrainian Academy of Sciences, Kiev, Ukraine","active":true,"usgs":false}],"preferred":false,"id":735368,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Griffin, Julie M.","contributorId":204889,"corporation":false,"usgs":false,"family":"Griffin","given":"Julie","email":"","middleInitial":"M.","affiliations":[{"id":37004,"text":"Department of Earth and Planetary Sciences, University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":735369,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Poletaev, Vladislav I.","contributorId":204890,"corporation":false,"usgs":false,"family":"Poletaev","given":"Vladislav","email":"","middleInitial":"I.","affiliations":[{"id":37005,"text":"Department of Paleontology and Stratigraphy, Institute of Geological Science, Ukrainian Academy of Sciences, Kiev, Ukraine","active":true,"usgs":false}],"preferred":false,"id":735370,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wardlaw, Bruce R. bwardlaw@usgs.gov","contributorId":266,"corporation":false,"usgs":true,"family":"Wardlaw","given":"Bruce","email":"bwardlaw@usgs.gov","middleInitial":"R.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":735371,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70196888,"text":"70196888 - 2018 - Respiratory disease, behavior, and survival of mountain goat kids","interactions":[],"lastModifiedDate":"2018-07-23T13:00:20","indexId":"70196888","displayToPublicDate":"2018-05-14T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Respiratory disease, behavior, and survival of mountain goat kids","docAbstract":"Bacterial pneumonia is a threat to bighorn sheep (Ovis canadensis) populations. Bighorn sheep in the East Humboldt Mountain Range (EHR), Nevada, USA, experienced a pneumonia epizootic in 2009–2010. Testing of mountain goats (Oreamnos americanus) that were captured or found dead on this range during and after the epizootic detected bacteria commonly associated with bighorn sheep pneumonia die‐offs. Additionally, in years subsequent to the bighorn sheep epizootic, the mountain goat population had low kid:adult ratios, a common outcome for bighorn sheep populations that have experienced a pneumonia epizootic. We hypothesized that pneumonia was present and negatively affecting mountain goat kids in the EHR. From June–August 2013–2015, we attempted to observe mountain goat kids with marked adult females in the EHR at least once per week to document signs of respiratory disease; identify associations between respiratory disease, activity levels, and subsequent disappearance (i.e., death); and estimate weekly survival. Each time we observed a kid with a marked adult female, we recorded any signs of respiratory disease and collected behavior data that we fit to a 3‐state discrete hidden Markov model (HMM) to predict a kid's state (active vs. sedentary) and its probability of disappearing. We first observed clinical signs of respiratory disease in kids in late July–early August each summer. We observed 8 of 31 kids with marked adult females with signs of respiratory disease on 13 occasions. On 11 of these occasions, the HMM predicted that kids were in the sedentary state, which was associated with increased probability of subsequent death. We estimated overall probability of kid survival from June–August to be 0.19 (95% CI = 0.08–0.38), which was lower than has been reported in other mountain goat populations. We concluded that respiratory disease was present in the mountain goat kids in the EHR and negatively affected their activity levels and survival. Our results raise concerns about potential effects of pneumonia to mountain goat populations and the potential for disease transmission between mountain goats and bighorn sheep where the species are sympatric.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21470","usgsCitation":"Blanchong, J.A., Anderson, C.A., Clark, N.J., Klaver, R.W., Plummer, P.J., Cox, M., Mcadoo, C., and Wolff, P.L., 2018, Respiratory disease, behavior, and survival of mountain goat kids: Journal of Wildlife Management, v. 82, no. 6, p. 1243-1251, https://doi.org/10.1002/jwmg.21470.","productDescription":"9 p.","startPage":"1243","endPage":"1251","ipdsId":"IP-094396","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":487211,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lib.dr.iastate.edu/nrem_pubs/276","text":"External Repository"},{"id":354147,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"82","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-25","publicationStatus":"PW","scienceBaseUri":"5afee6bee4b0da30c1bfbd96","contributors":{"authors":[{"text":"Blanchong, Julie A.","contributorId":6030,"corporation":false,"usgs":false,"family":"Blanchong","given":"Julie","email":"","middleInitial":"A.","affiliations":[{"id":13018,"text":"Department of Forest and Wildlife Ecology, University of Wisconsin, Madison","active":true,"usgs":false}],"preferred":false,"id":735235,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Christopher A.","contributorId":204866,"corporation":false,"usgs":false,"family":"Anderson","given":"Christopher","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":735236,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Nicholas J.","contributorId":204867,"corporation":false,"usgs":false,"family":"Clark","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":16755,"text":"University of Queensland, Australia","active":true,"usgs":false}],"preferred":false,"id":735237,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":734914,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Plummer, Paul J.","contributorId":204868,"corporation":false,"usgs":false,"family":"Plummer","given":"Paul","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":735238,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cox, Mike","contributorId":198457,"corporation":false,"usgs":false,"family":"Cox","given":"Mike","email":"","affiliations":[],"preferred":false,"id":735239,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mcadoo, Caleb","contributorId":204869,"corporation":false,"usgs":false,"family":"Mcadoo","given":"Caleb","email":"","affiliations":[],"preferred":false,"id":735240,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wolff, Peregrine L.","contributorId":69865,"corporation":false,"usgs":true,"family":"Wolff","given":"Peregrine","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":735241,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70196975,"text":"sim3388 - 2018 - Surficial geologic map of the Dillingham quadrangle, southwestern Alaska","interactions":[],"lastModifiedDate":"2018-05-16T10:06:12","indexId":"sim3388","displayToPublicDate":"2018-05-14T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3388","title":"Surficial geologic map of the Dillingham quadrangle, southwestern Alaska","docAbstract":"Director,
Alaska Science Center
U.S. Geological Survey
4230 University Drive
Anchorage, Alaska 99508
The ability to model freshwater stream habitat and species distributions is limited by the spatially sparse flow data available from long-term gauging stations. Flow data beyond the immediate vicinity of gauging stations would enhance our ability to explore and characterize hydrologic habitat suitability. The southeastern USA supports high aquatic biodiversity, but threats, such as landuse alteration, climate change, conflicting water-resource demands, and pollution, have led to the imperilment and legal protection of many species. The ability to distinguish suitable from unsuitable habitat conditions, including hydrologic suitability, is a key criterion for successful conservation and restoration of aquatic species. We used the example of the critically endangered Tar River Spinymussel (Parvaspina steinstansana) and associated species to demonstrate the value of modeled flow data (WaterFALL™) to generate novel insights into population structure and testable hypotheses regarding hydrologic suitability. With ordination models, we: 1) identified all catchments with potentially suitable hydrology, 2) identified 2 distinct hydrologic environments occupied by the Tar River Spinymussel, and 3) estimated greater hydrological habitat niche breadth of assumed surrogate species associates at the catchment scale. Our findings provide the first demonstrated application of complete, continuous, regional modeled hydrologic data to freshwater mussel distribution and management. This research highlights the utility of modeling and data-mining methods to facilitate further exploration and application of such modeled environmental conditions to inform aquatic species management. We conclude that such an approach can support landscape-scale management decisions that require spatial information at fine resolution (e.g., enhanced National Hydrology Dataset catchments) and broad extent (e.g., multiple river basins).
","language":"English","publisher":"The University of Chicago Press","doi":"10.1086/697947","usgsCitation":"Drew, C.A., Eddy, M., Kwak, T.J., Cope, W., and Augspurger, T., 2018, Hydrologic characteristics of freshwater mussel habitat: novel insights from modeled flows: Freshwater Science, v. 37, no. 2, p. 343-356, https://doi.org/10.1086/697947.","productDescription":"14 p.","startPage":"343","endPage":"356","ipdsId":"IP-095471","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":354148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","volume":"37","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6bee4b0da30c1bfbd94","contributors":{"authors":[{"text":"Drew, C. Ashton","contributorId":140953,"corporation":false,"usgs":false,"family":"Drew","given":"C.","email":"","middleInitial":"Ashton","affiliations":[],"preferred":false,"id":735242,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eddy, Michele","contributorId":198941,"corporation":false,"usgs":false,"family":"Eddy","given":"Michele","email":"","affiliations":[],"preferred":false,"id":735243,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kwak, Thomas J. 0000-0002-0616-137X tkwak@usgs.gov","orcid":"https://orcid.org/0000-0002-0616-137X","contributorId":834,"corporation":false,"usgs":true,"family":"Kwak","given":"Thomas","email":"tkwak@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":734915,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cope, W. Gregory","contributorId":70353,"corporation":false,"usgs":true,"family":"Cope","given":"W. Gregory","affiliations":[],"preferred":false,"id":735244,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Augspurger, Tom","contributorId":189894,"corporation":false,"usgs":false,"family":"Augspurger","given":"Tom","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":735245,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196883,"text":"70196883 - 2018 - Landscape‐level patterns in fawn survival across North America","interactions":[],"lastModifiedDate":"2018-07-03T11:19:38","indexId":"70196883","displayToPublicDate":"2018-05-14T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Landscape‐level patterns in fawn survival across North America","docAbstract":"A landscape‐level meta‐analysis approach to examining early survival of ungulates may elucidate patterns in survival not evident from individual studies. Despite numerous efforts, the relationship between fawn survival and habitat characteristics remains unclear and there has been no attempt to examine trends in survival across landscape types with adequate replication. In 2015–2016, we radiomarked 98 white‐tailed deer (Odocoileus virginianus) fawns in 2 study areas in Pennsylvania. By using a meta‐analysis approach, we compared fawn survival estimates from across North America using published data from 29 populations in 16 states to identify patterns in survival and cause‐specific mortality related to landscape characteristics, predator communities, and deer population density. We modeled fawn survival relative to percentage of agricultural land cover and deer density. Estimated average survival to 3–6 months of age was 0.414 ± 0.062 (SE) in contiguous forest landscapes (no agriculture) and for every 10% increase in land area in agriculture, fawn survival increased 0.049 ± 0.014. We classified cause‐specific mortality as human‐caused, natural (excluding predation), and predation according to agriculturally dominated, forested, and mixed (i.e., both agricultural and forest cover) landscapes. Predation was the greatest source of mortality in all landscapes. Landscapes with mixed forest and agricultural cover had greater proportions and rates of human‐caused mortalities, and lower proportions and rates of mortality due to predators, when compared to forested landscapes. Proportion and rate of natural deaths did not differ among landscapes. We failed to detect any relationship between fawn survival and deer density. The results highlight the need to consider multiple spatial scales when accounting for factors that influence fawn survival. Furthermore, variation in mortality sources and rates among landscapes indicate the potential for altered landscape mosaics to influence fawn survival rates. Wildlife managers can use the meta‐analysis to identify factors that will facilitate comparisons of results among studies and advance a better understanding of patterns in fawn survival.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21456","usgsCitation":"Gingery, T.M., Diefenbach, D.R., Wallingford, B.D., and Rosenberry, C.S., 2018, Landscape‐level patterns in fawn survival across North America: Journal of Wildlife Management, v. 82, no. 5, p. 1003-1013, https://doi.org/10.1002/jwmg.21456.","productDescription":"11 p.","startPage":"1003","endPage":"1013","ipdsId":"IP-092016","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":354144,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"82","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-06","publicationStatus":"PW","scienceBaseUri":"5afee6bfe4b0da30c1bfbd9a","contributors":{"authors":[{"text":"Gingery, Tess M.","contributorId":204865,"corporation":false,"usgs":false,"family":"Gingery","given":"Tess","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":735227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diefenbach, Duane R. 0000-0001-5111-1147 drd11@usgs.gov","orcid":"https://orcid.org/0000-0001-5111-1147","contributorId":5235,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Duane","email":"drd11@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":734904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wallingford, Bret D.","contributorId":171632,"corporation":false,"usgs":false,"family":"Wallingford","given":"Bret","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":735228,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rosenberry, Christopher S.","contributorId":171633,"corporation":false,"usgs":false,"family":"Rosenberry","given":"Christopher","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":735229,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70272980,"text":"70272980 - 2018 - Application and comparison of the MODIS-Derived Enhanced Vegetation Index (EVI) to VIIRS, Landsat 5 TM, and Landsat 8 OLI platforms: A case study in the arid Colorado River Delta, Mexico","interactions":[],"lastModifiedDate":"2025-12-11T16:57:04.855099","indexId":"70272980","displayToPublicDate":"2018-05-13T10:52:11","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3380,"text":"Sensors","active":true,"publicationSubtype":{"id":10}},"title":"Application and comparison of the MODIS-Derived Enhanced Vegetation Index (EVI) to VIIRS, Landsat 5 TM, and Landsat 8 OLI platforms: A case study in the arid Colorado River Delta, Mexico","docAbstract":"The Enhanced Vegetation Index (EVI) is a key Earth science parameter used to assess vegetation, originally developed and calibrated for the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra and Aqua satellites. With the impending decommissioning of the MODIS sensors by the year 2020/2022, alternative platforms will need to be used to estimate EVI. We compared Landsat 5 (2000–2011), 8 (2013–2016) and the Visible Infrared Imaging Radiometer Suite (VIIRS; 2013–2016) to MODIS EVI (2000–2016) over a 420,083-ha area of the arid lower Colorado River Delta in Mexico. Over large areas with mixed land cover or agricultural fields, we found high correspondence between Landsat and MODIS EVI (R2 = 0.93 for the entire area studied and 0.97 for agricultural fields), but the relationship was weak over bare soil (R2 = 0.27) and riparian vegetation (R2 = 0.48). The correlation between MODIS and Landsat EVI was higher over large, homogeneous areas and was generally lower in narrow riparian areas. VIIRS and MODIS EVI were highly similar (R2 = 0.99 for the entire area studied) and did not show the same decrease in performance in smaller, narrower regions as Landsat. Landsat and VIIRS provide EVI estimates of similar quality and characteristics to MODIS, but scale, seasonality and land cover type(s) should be considered before implementing Landsat EVI in a particular area.
","language":"English","publisher":"MDPI","doi":"10.3390/s18051546","usgsCitation":"Jarchow, C., Didan, K., Barreto-Muñoz, A., Nagler, P.L., and Glenn, E., 2018, Application and comparison of the MODIS-Derived Enhanced Vegetation Index (EVI) to VIIRS, Landsat 5 TM, and Landsat 8 OLI platforms: A case study in the arid Colorado River Delta, Mexico: Sensors, v. 18, no. 5, 1546, 17 p., https://doi.org/10.3390/s18051546.","productDescription":"1546, 17 p.","ipdsId":"IP-086846","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":497383,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/s18051546","text":"Publisher Index Page"},{"id":497335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","otherGeospatial":"Colorado River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.39760654188758,\n 32.8908327506181\n ],\n [\n -115.33226880384278,\n 32.8908327506181\n ],\n [\n -115.33226880384278,\n 31.59336803534171\n ],\n [\n -114.39760654188758,\n 31.59336803534171\n ],\n [\n -114.39760654188758,\n 32.8908327506181\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","issue":"5","noUsgsAuthors":false,"publicationDate":"2018-05-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Jarchow, Christopher 0000-0002-0424-4104 cjarchow@usgs.gov","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":196069,"corporation":false,"usgs":true,"family":"Jarchow","given":"Christopher","email":"cjarchow@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":951980,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Didan, Kamel","contributorId":292780,"corporation":false,"usgs":false,"family":"Didan","given":"Kamel","affiliations":[{"id":62999,"text":"Biosystems Engineering, University of Arizona, Tucson, AZ, 85721 USA","active":true,"usgs":false}],"preferred":false,"id":951981,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barreto-Muñoz, Armando","contributorId":239891,"corporation":false,"usgs":false,"family":"Barreto-Muñoz","given":"Armando","affiliations":[{"id":48028,"text":"University of Arizona, Biosystems Engineering, Tucson, AZ, 85721 USA","active":true,"usgs":false}],"preferred":false,"id":951982,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":951983,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Glenn, Edward P.","contributorId":56542,"corporation":false,"usgs":false,"family":"Glenn","given":"Edward P.","affiliations":[{"id":13060,"text":"Department of Soil, Water and Environmental Science, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":951984,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70220422,"text":"70220422 - 2018 - Inferring the absence of an incipient population during a rapid response for an invasive species","interactions":[],"lastModifiedDate":"2021-05-13T11:56:12.67446","indexId":"70220422","displayToPublicDate":"2018-05-13T06:51:49","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Inferring the absence of an incipient population during a rapid response for an invasive species","docAbstract":"Successful eradication of invasives is facilitated by early detection and prompt onset of control. However, realizing or verifying that a colonization has occurred is difficult for cryptic species especially at low population densities. Responding to the capture or unconfirmed sighting of a cryptic invasive species, and the associated effort to determine if it indicates an incipient (small, localized) population or merely a lone colonizer, is costly and cannot continue indefinitely. However, insufficient detection effort risks erroneously concluding the species is not present, allowing the population to increase in size and expand its range. Evidence for an incipient population requires detection of ≥1 individual; its absence, on the other hand, must be inferred probabilistically. We use an actual rapid response incident and species-specific detection estimates tied to a known density to calculate the amount of effort (with non-sequential detections) necessary to assert, with a pre-defined confidence, that invasive brown treesnakes are absent from the search area under a wide range of hypothetical population densities. We illustrate that the amount of effort necessary to declare that a species is absent is substantial and increases with decreased individual detection probability, decreased density, and increased level of desired confidence about its absence. Such survey investment would be justified where the cost savings due to early detection are large. Our Poisson-based model application will allow managers to make informed decisions about how long to continue detection efforts, should no additional detections occur, and suggests that effort to do so is significantly higher than previously thought. While our model application informs how long to search to infer absence of an incipient population of brown treesnakes, the approach is sufficiently general to apply to other invasive species if density-dependent detection estimates are known or reliable surrogate estimates are available.
Vitrinite reflectance (VRo) is a standard petrographic method for assessing thermal maturity (rank) of coal. The vitrinite reflectance technique, however, requires significant petrographic experience, can be time-consuming, and may be biased by analyst subjectivity. Correlations between coal rank and Raman spectral properties are a promising alternative that can supplant some of the limitations inherent in the VRo protocol. The traditional peak-fitting methodologies for quantifying metrics from Raman spectra, however, also suffer from analyst subjectivity that can affect correlations between analyte and spectral properties.
This research combines high-throughput Raman spectroscopy with multivariate analysis (MVA) to create calibration models for the prediction of coal rank though VRo and atomic O/C ratio. MVA techniques eliminate the ambiguous subjectivity prevalent in peak-fitting methods by evaluating the full Raman spectrum, then identifying the integral vibrational modes for constructing accurate models. Partial least squares (PLS) regression models were developed using Raman spectra and VRo values (0.23–5.23%) for 68 geographically diverse coal samples. The calibration set was validated using one-half of the samples to rigorously assess the model’s predictive accuracy. The root mean standard error of prediction was 0.19 for the VRo model and 0.014 for the atomic O/C model. Both models exhibited linear correlations, with coefficients of determination (R2) for the validation set of 0.99 (VRo) and 0.93 (atomic O/C), despite the geographic and rank diversity of the samples. This study demonstrates the applicability and power of using PLS models for the prediction of both the VRo and atomic O/C ratio from Raman spectra. The quantitative MVA protocol contained herein provides a Raman alternative to the VRo industry benchmark for coal rank that is not subject to the limitations and subjectivity of peak-fitting methods.
Streamflow and nutrient concentration data needed to compute nitrogen and phosphorus loads were compiled from Federal, State, Provincial, and local agency databases and also from selected university databases. The nitrogen and phosphorus loads are necessary inputs to Spatially Referenced Regressions on Watershed Attributes (SPARROW) models. SPARROW models are a way to estimate the distribution, sources, and transport of nutrients in streams throughout the Midcontinental region of Canada and the United States. After screening the data, approximately 1,500 sites sampled by 34 agencies were identified as having suitable data for calculating the long-term mean-annual nutrient loads required for SPARROW model calibration. These final sites represent a wide range in watershed sizes, types of nutrient sources, and land-use and watershed characteristics in the Midcontinental region of Canada and the United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185051","collaboration":"Prepared in cooperation with the International Joint Commission","usgsCitation":"Saad, D.A., Benoy, G.A., and Robertson, D.M., 2018, Estimates of long-term mean-annual nutrient loads considered for use in SPARROW models of the Midcontinental region of Canada and the United States, 2002 base year: U.S. Geological Survey Scientific Investigations Report 2018–5051, 14 p., https://doi.org/10.3133/sir20185051.","productDescription":"Report: vi, 14 p.; Data Release","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-084092","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":353945,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VT1R1K","text":"USGS data release","description":"USGS data release","linkHelpText":"Water-quality and streamflow datasets used for estimating loads considered for use in the 2002 Midcontinent nutrient SPARROW models, United States and Canada, 1970-2012"},{"id":353943,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5051/sir20185051.pdf","text":"Report","size":"8.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5051"},{"id":353931,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5051/coverthb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.32617187499999,\n 49.26780455063753\n ],\n [\n -94.3505859375,\n 42.94033923363181\n ],\n [\n -91.7578125,\n 39.16414104768742\n ],\n [\n -88.9013671875,\n 36.63316209558658\n ],\n [\n -86.572265625,\n 35.17380831799959\n ],\n [\n -81.7822265625,\n 37.82280243352756\n ],\n [\n -79.5849609375,\n 40.17887331434696\n ],\n [\n -77.16796875,\n 42.293564192170095\n ],\n [\n -74.794921875,\n 43.739352079154706\n ],\n [\n -75.6298828125,\n 44.933696389694674\n ],\n [\n -78.44238281249999,\n 45.1510532655634\n ],\n [\n -80.2001953125,\n 46.58906908309182\n ],\n [\n -82.2216796875,\n 47.368594345213374\n ],\n [\n -84.287109375,\n 49.781264058178344\n ],\n [\n -87.2314453125,\n 50.233151832472245\n ],\n [\n -90.52734374999999,\n 50.708634400828224\n ],\n [\n -95.1416015625,\n 50.401515322782366\n ],\n [\n -99.66796875,\n 50.064191736659104\n ],\n [\n -100.986328125,\n 51.45400691005982\n ],\n [\n -103.4912109375,\n 51.536085601784755\n ],\n [\n -102.74414062499999,\n 49.97948776108648\n ],\n [\n -104.32617187499999,\n 49.26780455063753\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
Polar bears (Ursus maritimus) in Alaska use the Arctic National Wildlife Refuge (ANWR) for maternal denning. Pregnant bears den in snow banks for more than 3 months in winter during which they give birth to and nurture young. Denning is one of the most vulnerable times in polar bear life history as the family group cannot simply walk away from a disturbance without jeopardizing survival of newly born cubs. The ANWR includes the “1002 Area”, a region recently opened for oil and gas exploration by the U.S. Department of the Interior (DOI). As a part of its mission, the DOI “… protects and manages the Nation's natural resources …” and is therefore responsible for conserving polar bears and encouraging development of energy potential. Because future industrial activities could overlap habitats used by denning polar bears, identifying these habitats can inform the decisions of resource managers tasked to develop resources and protect polar bears. To help inform these efforts, we qualitatively compared the distribution of denning habitat identified by two different methods: previously published habitat from manual interpretation of aerial photographs, and habitat derived by computer interrogation of interferometric synthetic aperture radar (IfSAR) digital terrain models (DTM). Because photograph-interpreted methods depicted denning habitat as a line and IfSAR-derived methods depicted habitat as a polygon, we assessed agreement between the two methods with distance measurements. We found that 77.5 percent of IfSAR-derived denning habitat (79.6 km2 ; 1.2 percent of the 6,837.0 km2 1002 Area) was within 600 m of photograph-interpreted habitat (3,026.9 km), including 53.9 percent within 200 m. This distribution differed from that of randomly distributed points, as only 49.4 percent of these occurred within 600 m of photograph-interpreted habitat, including 18.3 percent within 200 m. Both methods appear to identify the major physiographic features that polar bears might select for denning. IfSAR-derived methods identified habitat at greater frequency beyond major landscape features such as coastal bluffs, river banks and lakeshores, were more likely to identify isolated pockets of putative denning habitat, and were easier to implement than deriving habitat from photograph-interpretive efforts. However, previous research suggests that photograph-interpretation methods may identify denning habitat more correctly than computer interrogation of IfSAR DTMs. Future work should quantify the distribution of IfSAR-derived denning habitat relative to actual landscape features and polar bear maternal dens in the 1002 Area, and investigate the feasibility of habitat identification from finer grained DTMs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181083","usgsCitation":"Durner, G.M., and Atwood, T.C., 2018, A comparison of photograph-interpreted and IfSAR-derived maps of polar bear denning habitat for the 1002 Area of the Arctic National Wildlife Refuge, Alaska: U.S. Geological Survey Open-File Report 2018–1083, 12 p., https://doi.org/10.3133/ofr20181083.","productDescription":"Report: iv, 12 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-095475","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":354103,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DJ5DXT","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data used to compare photo-interpreted and IfSAR-derived maps of polar bear denning habitat for the 1002 Area of the Arctic National Wildlife Refuge, Alaska, 2006-2016"},{"id":354102,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1083/ofr20181083.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1083"},{"id":354101,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1083/coverthb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -146.5,\n 69.5\n ],\n [\n -142,\n 69.5\n ],\n [\n -142,\n 70.25\n ],\n [\n -146.5,\n 70.25\n ],\n [\n -146.5,\n 69.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4230 University Drive
Anchorage, Alaska 99508
The California Department of Water Resources and Bureau of Reclamation propose new water intake facilities on the Sacramento River in northern California that would convey some of the water for export to areas south of the Sacramento-San Joaquin River Delta (hereinafter referred to as the Delta) through tunnels rather than through the Delta. The collection of water intakes, tunnels, pumping facilities, associated structures, and proposed operations are collectively referred to as California WaterFix. The water intake facilities, hereinafter referred to as the North Delta Diversion (NDD), are proposed to be located on the Sacramento River downstream of the city of Sacramento and upstream of the first major river junction where Sutter Slough branches from the Sacramento River. The NDD can divert a maximum discharge of 9,000 cubic feet per second (ft3 /s) from the Sacramento River, which reduces the amount of Sacramento River inflow into the Delta.
In this report, we conduct four analyses to investigate the effect of the NDD and its proposed operation on survival of juvenile Chinook salmon (Oncorhynchus tshawytscha). All analyses used the results of a Bayesian survival model that allowed us to simulate travel time, migration routing, and survival of juvenile Chinook salmon migrating through the Delta in response to NDD operations, which affected both inflows to the Delta and operation of the Delta Cross Channel (DCC).
For the first analysis, we evaluated the effect of the NDD bypass rules on salmon survival. The NDD bypass rules are a set of operational rule curves designed to provide adaptive levels of fish protection by defining allowable diversion rates as a function of (1) Sacramento River discharge as measured at Freeport, and (2) time of year when endangered runs requiring the most protection are present. We determined that all bypass rule curves except constant low-level pumping (maximum diversion of 900 ft3 /s) could cause a sizeable decrease in survival by as much as 6–10 percentage points. The maximum decrease in survival occurred at an intermediate Sacramento River flow of about 20,000–30,000 ft3 /s. Diversion rates increased rapidly as Sacramento River flows increased from 20,000 ft3 /s to 30,000 ft3 /s, until a maximum diversion rate was reached at 9,000 ft3 /s. Because through-Delta survival increases sharply over this range of Sacramento River flow before beginning to level off with further flow increases, increasing diversion rates over this flow range causes a large decrease in survival relative to no diversion.
For the second analysis, we applied the survival model to 82 years of daily simulated flows under the Proposed Action (PA) and No Action Alternative (NAA). The PA includes operation of the Central Valley Project/State Water Project with implementation of the NDD and its operations prescribed by the NDD bypass rules, whereas the NAA assumes system operations without implementation of the NDD. We also evaluated a “Level 1” (L1) scenario, which was similar to the PA scenario but applied the most protective bypass rule known as Level 1 post-pulse operations. We noted a high probability that survival under the PA scenario was lower than under the NAA scenario, and that travel time was longer under PA relative to NAA in most simulation years. However, the largest survival differences between the PA and NAA scenarios occurred during October–November and May–June. Although bypass rules are less restrictive during these periods, we determined that more frequent use of the DCC under PA led to the largest differences in survival between the two scenarios. Additionally, we noted no difference in median survival decreases between the PA and L1 scenarios, although in some years the L1 scenario had a lower survival decrease than the PA scenario.
For the third analysis, we proposed a quantitative approach for developing NDD rule curves (that is, prescribed diversion flows for given inflows) by using the survival model to identify diversion rates that meet a criterion of a having a small probability of exceeding a given decrease in survival. We examined diversion rates that led to a 10% chance of exceeding a given decrease in survival for a range of absolute and relative decreases in survival. To maintain a given constant level of protection across the range of river flows, our analysis indicated that diversions had to increase at a much slower rate with respect to Sacramento River flow relative to the rule curves defined in the NDD bypass table. Additionally, we determined that diversion rates could be higher than under the bypass table rule curves at river flows less than 20,000 ft3 /s, but diversions had to be less than defined by NDD bypass rules at higher flows.
For the fourth analysis, we simulated the effect of “real-time operations” on salmon survival, where bypass flow rates were determined by the presence of juvenile salmon entering the Delta, as indicated by juvenile salmon catch in a rotary screw trap upstream of the Delta. For this analysis, we evaluated NDD operations as defined by the L1 scenario and an additional scenario (Unlimited Pulse Protection [UPP]) that provided protection to an unlimited number of fish pulses. This analysis indicated that the highest catches occurred during flow pulses when daily survival was high, which caused annual survival to be weighted towards periods of high daily survival, resulting in a high annual survival. We determined that the mean annual survival decreased by 1–4 percentage points, and annual survival decreases were more frequently smaller for the UPP scenario. Additionally, because the UPP scenario protected an unlimited number of fish pulses, decreases in daily survival under the UPP scenario were less than under the L1 scenario.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181078","collaboration":"Prepared in cooperation with National Oceanic and Atmospheric Administration, National Marine Fisheries Service","usgsCitation":"Perry, R.W., and Pope, A.C., 2018, Effects of the proposed California WaterFix North Delta Diversion on survival of juvenile Chinook salmon (Oncorhynchus tshawytscha) in the Sacramento-San Joaquin River Delta, northern California: U.S. Geological Survey Open-File Report 2018-1078, 94 p. plus appendixes,\nhttps://doi.org/10.3133/ofr20181078.","productDescription":"Report: x, 94 p.; 11 Appendixes","numberOfPages":"108","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-095992","costCenters":[{"id":654,"text":"Western Fisheries Research 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-121.33,\n 37.82\n ],\n [\n -121.33,\n 38.5\n ],\n [\n -121.9167,\n 38.5\n ],\n [\n -121.9167,\n 37.82\n ],\n [\n -121.33,\n 37.82\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
Context
Landscape resistance is vital to connectivity modeling and frequently derived from resource selection functions (RSFs). RSFs estimate relative probability of use and tend to focus on understanding habitat preferences during slow, routine animal movements (e.g., foraging). Dispersal and migration, however, can produce rarer, faster movements, in which case models of movement speed rather than resource selection may be more realistic for identifying habitats that facilitate connectivity.
Objective
To compare two connectivity modeling approaches applied to resistance estimated from models of movement rate and resource selection.
Methods
Using movement data from migrating elk, we evaluated continuous time Markov chain (CTMC) and movement-based RSF models (i.e., step selection functions [SSFs]). We applied circuit theory and shortest random path (SRP) algorithms to CTMC, SSF and null (i.e., flat) resistance surfaces to predict corridors between elk seasonal ranges. We evaluated prediction accuracy by comparing model predictions to empirical elk movements.
Results
All connectivity models predicted elk movements well, but models applied to CTMC resistance were more accurate than models applied to SSF and null resistance. Circuit theory models were more accurate on average than SRP models.
Conclusions
CTMC can be more realistic than SSFs for estimating resistance for fast movements, though SSFs may demonstrate some predictive ability when animals also move slowly through corridors (e.g., stopover use during migration). High null model accuracy suggests seasonal range data may also be critical for predicting direct migration routes. For animals that migrate or disperse across large landscapes, we recommend incorporating CTMC into the connectivity modeling toolkit.