Prey fish communities across the Great Lakes continue to change, although the direction and magnitude of those changes are not consistent across the lakes. The metrics used to categorize prey fish status in this and previous periods are based on elements that are common among each of the lake’s Fish Community Objectives and include diversity and the relative role of native species in the prey fish communities. The diversity index categorized three of lakes as ‘fair’, while Superior and Erie were ‘good’ (Table 1). The short term trend, from the previous period (2008-2010) to the current period (2011-2014) found diversity in Erie and Superior to be unchanging, but the other three lakes to be ‘deteriorating’, resulting in an overall trend categorization of ‘undetermined’ (Table 1). The long term diversity trend suggested Lakes Superior and Erie have the most diverse prey communities although the index for those prey fish have been quite variable over time (Figure 1). In Lake Huron, where non-native alewife have substantially declined, the diversity index has also declined. The continued dominance of alewife in Lake Ontario (96% of the prey fish biomass) resulted in the lowest diversity index value (Figure 1). The proportion of native species within the community was judged as ‘good’ in Lakes Superior and Huron, ‘fair’ in Michigan and Erie and ‘poor’ in Ontario (Table 2). The short term trend was improving in in all lakes except Michigan (‘deteriorating’) and Ontario (‘unchanging’), resulting in an overall short term trend of ‘undetermined’ (Table 2). Over the current period, Lake Superior consistently had the highest proportion native prey fish (87%) while Lake Ontario had the lowest (1%) (Figure 2). Lake Michigan’s percent native has declined as round goby increase and comprises a greater proportion of the community. Native prey fish make up 51% of Lake Erie, although basin-specific values differed (Figure 2). Most notably, native species in Lake Huron comprised less than 10% of the community in 1970, but since alewife have declined, now represent nearly 80% of the community (Figure 2). Prey fish data are most consistent for in-lake populations, which are reported here; data from connecting channels was not consistently available across the basin. Abundance was not used to judge prey fish status since successful, basin-wide management actions, including mineral nutrient input reductions and piscivore restoration, both inherently reduce prey fish abundance. However, recent abundance trends as they relate to predator prey balance are referenced, such as in Lakes Michigan and Huron where piscivore stocking is being reduced to lower predation demand on prey fish populations and maintain sport fisheries.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Sate of the Great Lakes 2017 Technical Report","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"Environment and Climate Change Canada and the U.S. Environmental Protection Agency","usgsCitation":"Weidel, B., and Dunlop, E., 2017, Sub-indicator: Prey fish, 9 p.","productDescription":"9 p.","startPage":"254","endPage":"262","ipdsId":"IP-071538","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":352690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":352660,"type":{"id":15,"text":"Index Page"},"url":"https://binational.net/wp-content/uploads/2017/09/SOGL_2017_Technical_Report-EN.pdf"}],"country":"Canada, United States","otherGeospatial":"Great Lakes","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee8ebe4b0da30c1bfc4ce","contributors":{"authors":[{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":731406,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunlop, Erin","contributorId":102377,"corporation":false,"usgs":true,"family":"Dunlop","given":"Erin","affiliations":[],"preferred":false,"id":731407,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70192816,"text":"70192816 - 2017 - Effects of topographic data quality on estimates of shallow slope stability using different regolith depth models","interactions":[],"lastModifiedDate":"2018-02-26T13:16:51","indexId":"70192816","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Effects of topographic data quality on estimates of shallow slope stability using different regolith depth models","docAbstract":"Thickness of colluvium or regolith overlying bedrock or other consolidated materials is a major factor in determining stability of unconsolidated earth materials on steep slopes. Many efforts to model spatially distributed slope stability, for example to assess susceptibility to shallow landslides, have relied on estimates of constant thickness, constant depth, or simple models of thickness (or depth) based on slope and other topographic variables. Assumptions of constant depth or thickness rarely give satisfactory results. Geomorphologists have devised a number of different models to represent the spatial variability of regolith depth and applied them to various settings. I have applied some of these models that can be implemented numerically to different study areas with different types of terrain and tested the results against available depth measurements and landslide inventories. The areas include crystalline rocks of the Colorado Front Range, and gently dipping sedimentary rocks of the Oregon Coast Range. Model performance varies with model, terrain type, and with quality of the input topographic data. Steps in contour-derived 10-m digital elevation models (DEMs) introduce significant errors into the predicted distribution of regolith and landslides. Scan lines, facets, and other artifacts further degrade DEMs and model predictions. Resampling to a lower grid-cell resolution can mitigate effects of facets in lidar DEMs of areas where dense forest severely limits ground returns. Due to its higher accuracy and ability to penetrate vegetation, lidar-derived topography produces more realistic distributions of cover and potential landslides than conventional photogrammetrically derived topographic data.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Landslides: Putting Experience, Knowledge and Emerging Technologies into Practice--Proceedings of the 3rd North American Symposium on Landslides: Association of Environmental and Engineering Geologists Special Publication 27","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Association of Environmental and Engineering Geologists","usgsCitation":"Baum, R.L., 2017, Effects of topographic data quality on estimates of shallow slope stability using different regolith depth models, in Landslides: Putting Experience, Knowledge and Emerging Technologies into Practice--Proceedings of the 3rd North American Symposium on Landslides: Association of Environmental and Engineering Geologists Special Publication 27, p. 807-818.","productDescription":"12 p.","startPage":"807","endPage":"818","ipdsId":"IP-085830","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":352031,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee8ebe4b0da30c1bfc4e6","contributors":{"authors":[{"text":"Baum, Rex L. 0000-0001-5337-1970 baum@usgs.gov","orcid":"https://orcid.org/0000-0001-5337-1970","contributorId":1288,"corporation":false,"usgs":true,"family":"Baum","given":"Rex","email":"baum@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":717052,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70192891,"text":"70192891 - 2017 - What can volunteer angler tagging data tell us about the status of the Giant Trevally (ulua aukea) Caranx ignobilis fishery in Hawaii: revisiting data collected during Hawaii’s Ulua and Papio Tagging Project 2000-2016","interactions":[],"lastModifiedDate":"2018-01-26T11:52:21","indexId":"70192891","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"FWS/CSS-126-2017","title":"What can volunteer angler tagging data tell us about the status of the Giant Trevally (ulua aukea) Caranx ignobilis fishery in Hawaii: revisiting data collected during Hawaii’s Ulua and Papio Tagging Project 2000-2016","docAbstract":"Giant Trevally (ulua aukea) Caranx ignobilis is one of the most highly prized and frequently
targeted nearshore species. However, there is very little information on its current status in
Hawaiian waters. This study uses mark-recapture data collected as part of recreational angler
tagging program conducted by the Hawaii Department of Land and Natural Resources-Division
of Aquatic Resources during 2000-2012. Mark-recapture data were used to estimate von
Bertalanffy growth curve parameters and survivorship. Growth curves generated from the markrecapture
data suggested that Giant Trevally from the main Hawaiian Islands may be growing
faster and reach a smaller maximum size than individuals in the Northwest Hawaiian Islands, but
there are a number of issues rendering this conclusion uncertain. The survivorship of Giant
Trevally was positively associated with age, in part due to ontogenetic habitat shifts that result in
older fish moving to offshore habitats where they are less vulnerable to anglers. When compared
to stock assessments performed using commercial landings data and fisheries-independent visual
surveys, the mark-recapture data produced similar estimates for the average length of exploited
fish, a metric highly negatively correlated to fishing mortality. These results emphasize the need
for additional information on the biology of Giant Trevally in Hawaiian waters and suggest that
the data collected from this recreational angler tagging program may be useful to generate
reliable estimates of mortality for stock assessment purposes.
Conservation and management of spatially structured populations is challenging because solutions must consider where individuals are located, but also differential individual space use as a result of landscape heterogeneity. A recent extension of spatial capture–recapture (SCR) models, the ecological distance model, uses spatial encounter histories of individuals (e.g., a record of where individuals are detected across space, often sequenced over multiple sampling occasions), to estimate the relationship between space use and characteristics of a landscape, allowing simultaneous estimation of both local densities of individuals across space and connectivity at the scale of individual movement. We developed two model-based estimators derived from the SCR ecological distance model to quantify connectivity over a continuous surface: (1) potential connectivity—a metric of the connectivity of areas based on resistance to individual movement; and (2) density-weighted connectivity (DWC)—potential connectivity weighted by estimated density. Estimates of potential connectivity and DWC can provide spatial representations of areas that are most important for the conservation of threatened species, or management of abundant populations (i.e., areas with high density and landscape connectivity), and thus generate predictions that have great potential to inform conservation and management actions. We used a simulation study with a stationary trap design across a range of landscape resistance scenarios to evaluate how well our model estimates resistance, potential connectivity, and DWC. Correlation between true and estimated potential connectivity was high, and there was positive correlation and high spatial accuracy between estimated DWC and true DWC. We applied our approach to data collected from a population of black bears in New York, and found that forested areas represented low levels of resistance for black bears. We demonstrate that formal inference about measures of landscape connectivity can be achieved from standard methods of studying animal populations which yield individual encounter history data such as camera trapping. Resulting biological parameters including resistance, potential connectivity, and DWC estimate the spatial distribution and connectivity of the population within a statistical framework, and we outline applications to many possible conservation and management problems.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1623","usgsCitation":"Morin, D.J., Fuller, A.K., Royle, J., and Sutherland, C., 2017, Model-based estimators of density and connectivity to inform conservation of spatially structured populations: Ecosphere, v. 8, no. 1, p. 1-16, https://doi.org/10.1002/ecs2.1623.","productDescription":"e01623; 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-075226","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":470168,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1623","text":"Publisher Index Page"},{"id":348721,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-19","publicationStatus":"PW","scienceBaseUri":"5a60fc3de4b06e28e9c23bee","contributors":{"authors":[{"text":"Morin, Dana J.","contributorId":200306,"corporation":false,"usgs":false,"family":"Morin","given":"Dana","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":721855,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719733,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139623,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":719734,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sutherland, Chris","contributorId":150670,"corporation":false,"usgs":false,"family":"Sutherland","given":"Chris","affiliations":[],"preferred":false,"id":721856,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70192567,"text":"70192567 - 2017 - Fish assemblages","interactions":[],"lastModifiedDate":"2018-01-26T14:20:55","indexId":"70192567","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Fish assemblages","docAbstract":"Methods to sample fishes in stream ecosystems and to analyze the raw data, focusing primarily on assemblage-level (all fish species combined) analyses, are presented in this chapter. We begin with guidance on sample site selection, permitting for fish collection, and information-gathering steps to be completed prior to conducting fieldwork. Basic sampling methods (visual surveying, electrofishing, and seining) are presented with specific instructions for estimating population sizes via visual, capture-recapture, and depletion surveys, in addition to new guidance on environmental DNA (eDNA) methods. Steps to process fish specimens in the field including the use of anesthesia and preservation of whole specimens or tissue samples (for genetic or stable isotope analysis) are also presented. Data analysis methods include characterization of size-structure within populations, estimation of species richness and diversity, and application of fish functional traits. We conclude with three advanced topics in assemblage-level analysis: multidimensional scaling (MDS), ecological networks, and loop analysis.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Methods in stream ecology, 3rd Edition","language":"English","publisher":"Academic Press","doi":"10.1016/B978-0-12-416558-8.00016-0","isbn":"9780124165588","usgsCitation":"McGarvey, D.J., Falke, J.A., Li, H.W., and Li, J., 2017, Fish assemblages, chap. of Methods in stream ecology, 3rd Edition, p. 321-353, https://doi.org/10.1016/B978-0-12-416558-8.00016-0.","productDescription":"33 p.","startPage":"321","endPage":"353","ipdsId":"IP-070364","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":350703,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a6c4c95e4b06e28e9cabb04","contributors":{"editors":[{"text":"Hauer, F. Richard","contributorId":189116,"corporation":false,"usgs":false,"family":"Hauer","given":"F.","email":"","middleInitial":"Richard","affiliations":[],"preferred":false,"id":725976,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Lamberti, G. A.","contributorId":44229,"corporation":false,"usgs":false,"family":"Lamberti","given":"G.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":725977,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"McGarvey, Daniel J.","contributorId":201505,"corporation":false,"usgs":false,"family":"McGarvey","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":725973,"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":716229,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Li, Hiram W.","contributorId":18724,"corporation":false,"usgs":true,"family":"Li","given":"Hiram","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":725974,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Li, Judith","contributorId":74622,"corporation":false,"usgs":true,"family":"Li","given":"Judith","email":"","affiliations":[],"preferred":false,"id":725975,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70192642,"text":"70192642 - 2017 - Reconstruction of spatio-temporal temperature from sparse historical records using robust probabilistic principal component regression","interactions":[],"lastModifiedDate":"2017-11-07T14:44:39","indexId":"70192642","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5542,"text":"Advances in Statistical Climatology, Meteorology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Reconstruction of spatio-temporal temperature from sparse historical records using robust probabilistic principal component regression","docAbstract":"Scientific records of temperature and precipitation have been kept for several hundred years, but for many areas, only a shorter record exists. To understand climate change, there is a need for rigorous statistical reconstructions of the paleoclimate using proxy data. Paleoclimate proxy data are often sparse, noisy, indirect measurements of the climate process of interest, making each proxy uniquely challenging to model statistically. We reconstruct spatially explicit temperature surfaces from sparse and noisy measurements recorded at historical United States military forts and other observer stations from 1820 to 1894. One common method for reconstructing the paleoclimate from proxy data is principal component regression (PCR). With PCR, one learns a statistical relationship between the paleoclimate proxy data and a set of climate observations that are used as patterns for potential reconstruction scenarios. We explore PCR in a Bayesian hierarchical framework, extending classical PCR in a variety of ways. First, we model the latent principal components probabilistically, accounting for measurement error in the observational data. Next, we extend our method to better accommodate outliers that occur in the proxy data. Finally, we explore alternatives to the truncation of lower-order principal components using different regularization techniques. One fundamental challenge in paleoclimate reconstruction efforts is the lack of out-of-sample data for predictive validation. Cross-validation is of potential value, but is computationally expensive and potentially sensitive to outliers in sparse data scenarios. To overcome the limitations that a lack of out-of-sample records presents, we test our methods using a simulation study, applying proper scoring rules including a computationally efficient approximation to leave-one-out cross-validation using the log score to validate model performance. The result of our analysis is a spatially explicit reconstruction of spatio-temporal temperature from a very sparse historical record.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/ascmo-3-1-2017","usgsCitation":"Tipton, J., Hooten, M., and Goring, S., 2017, Reconstruction of spatio-temporal temperature from sparse historical records using robust probabilistic principal component regression: Advances in Statistical Climatology, Meteorology and Oceanography, v. 3, p. 1-16, https://doi.org/10.5194/ascmo-3-1-2017.","productDescription":"16 p.","startPage":"1","endPage":"16","ipdsId":"IP-076974","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470165,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/ascmo-3-1-2017","text":"Publisher Index Page"},{"id":348403,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-27","publicationStatus":"PW","scienceBaseUri":"5a07e953e4b09af898c8cc0f","contributors":{"authors":[{"text":"Tipton, John","contributorId":166999,"corporation":false,"usgs":false,"family":"Tipton","given":"John","affiliations":[],"preferred":false,"id":716635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":716634,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goring, Simon","contributorId":167180,"corporation":false,"usgs":false,"family":"Goring","given":"Simon","affiliations":[],"preferred":false,"id":716636,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70193673,"text":"70193673 - 2017 - Beaver colony density trends on the Chequamegon-Nicolet National Forest, 1987 – 2013","interactions":[],"lastModifiedDate":"2017-11-13T13:48:55","indexId":"70193673","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","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":"Beaver colony density trends on the Chequamegon-Nicolet National Forest, 1987 – 2013","docAbstract":"The North American beaver (Castor canadensis) is a managed species in the United States. In northern Wisconsin, as part of the state-wide beaver management program, the Chequamegon-Nicolet National Forest removes beavers from targeted trout streams on U.S. Forest Service lands. However, the success of this management program has not been evaluated. Targeted removals comprise only 3% of the annual beaver harvest, a level of effort that may not affect the beaver population. We used colony location data along Forest streams from 1987–2013 (Nicolet, northeast Wisconsin) and 1997–2013 (Chequamegon, northwest Wisconsin) to assess trends in beaver colony density on targeted trout streams compared to non-targeted streams. On the Chequamegon, colony density on non-targeted trout and non-trout streams did not change over time, while colony density on targeted trout streams declined and then stabilized. On the Nicolet, beaver colony density decreased on both non-targeted streams and targeted trout streams. However, colony density on targeted trout streams declined faster. The impact of targeted trapping was similar across the two sides of the Forest (60% reduction relative to non-targeted trout streams). Exploratory analyses of weather influences found that very dry conditions and severe winters were associated with transient reductions in beaver colony density on non-targeted streams on both sides of the Forest. Our findings may help land management agencies weigh more finely calibrated beaver control measures against continued large-scale removal programs.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0170099","usgsCitation":"Ribic, C., Donner, D.M., Beck, A.J., Rugg, D.J., Reinecke, S., and Eklund, D., 2017, Beaver colony density trends on the Chequamegon-Nicolet National Forest, 1987 – 2013: PLoS ONE, v. 12, no. 1, p. 1-15, https://doi.org/10.1371/journal.pone.0170099.","productDescription":"e0170099; 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-066625","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":461807,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0170099","text":"Publisher Index Page"},{"id":348705,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Chequamegon-Nicolet National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.5,\n 45\n ],\n [\n -88.505859375,\n 45\n ],\n [\n -88.505859375,\n 46.81133924039194\n ],\n [\n -91.5,\n 46.81133924039194\n ],\n [\n -91.5,\n 45\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-12","publicationStatus":"PW","scienceBaseUri":"5a60fc3de4b06e28e9c23beb","contributors":{"authors":[{"text":"Ribic, Christine 0000-0003-2583-1778 caribic@usgs.gov","orcid":"https://orcid.org/0000-0003-2583-1778","contributorId":147952,"corporation":false,"usgs":true,"family":"Ribic","given":"Christine","email":"caribic@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":719849,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Donner, Deahn M.","contributorId":171823,"corporation":false,"usgs":false,"family":"Donner","given":"Deahn","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":721833,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beck, Albert J.","contributorId":200078,"corporation":false,"usgs":false,"family":"Beck","given":"Albert","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":721834,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rugg, David J.","contributorId":171931,"corporation":false,"usgs":false,"family":"Rugg","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":721835,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reinecke, Sue","contributorId":200301,"corporation":false,"usgs":false,"family":"Reinecke","given":"Sue","email":"","affiliations":[],"preferred":false,"id":721836,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eklund, Dan","contributorId":200080,"corporation":false,"usgs":false,"family":"Eklund","given":"Dan","email":"","affiliations":[],"preferred":false,"id":721837,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70192455,"text":"70192455 - 2017 - Modeling waterfowl habitat selection in the Central Valley of California to better understand the spatial relationship between commercial poultry and waterfowl","interactions":[],"lastModifiedDate":"2019-06-04T08:40:19","indexId":"70192455","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Modeling waterfowl habitat selection in the Central Valley of California to better understand the spatial relationship between commercial poultry and waterfowl","docAbstract":"Wildlife researchers frequently study resource and habitat selection of wildlife to understand their potential habitat requirements and to conserve their populations. Understanding wildlife spatial-temporal distributions related to habitat have other applications such as to model interfaces between wildlife and domestic food animals in order to mitigate disease transmission to food animals. The highly pathogenic avian influenza (HPAI) virus represents a significant risk to the poultry industry. The Central Valley of California offers a unique geographical confluence of commercial poultry and wild waterfowl, which are thought to be a key reservoir of avian influenza (AI). Therefore, understanding spatio-temporal distributions of waterfowl could improve our understanding of potential risk of HPAI exposure from a commercial poultry perspective. Using existing radio-telemetry data on waterfowl (U.S. Geological Survey) in combination with habitat and vegetation data based on Geographic Information Systems (GIS), we are developing GIS-based statistical models that predict the probability of waterfowl presence (Habitat Suitability Mapping). Near-real-time application can be developed using recent habitat data derived from Landsat imagery (acquired by satellites and publicly available through the U.S. Geological Survey) to predict temporally- and spatially-varying distributions of waterfowl in the Central Valley. These results could be used to provide decision support for the poultry industry in addressing potential risk of HPAI exposure related to waterfowl proximity.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the Sixty-Sixth Western Poultry Disease Conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Sixty-Sixth Western Poultry Disease Conference","conferenceDate":"March 20-22, 2017","conferenceLocation":"Sacramento, California","language":"English","publisher":"Western Poutlry Disease Conference","usgsCitation":"Matchett, E., Casazza, M.L., Fleskes, J.P., Kelman, T., Cadena, M., and Pitesky, M., 2017, Modeling waterfowl habitat selection in the Central Valley of California to better understand the spatial relationship between commercial poultry and waterfowl, in Proceedings of the Sixty-Sixth Western Poultry Disease Conference, Sacramento, California, March 20-22, 2017, p. 118-120.","productDescription":"3 p.","startPage":"118","endPage":"120","ipdsId":"IP-083273","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":352033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":364313,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://aaap.memberclicks.net/wpdc-proceedings"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee8f7e4b0da30c1bfc4f0","contributors":{"authors":[{"text":"Matchett, Elliott 0000-0001-5095-2884 ematchett@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-2884","contributorId":5541,"corporation":false,"usgs":true,"family":"Matchett","given":"Elliott","email":"ematchett@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":715916,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":715915,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fleskes, Joseph P. 0000-0001-5388-6675 joe_fleskes@usgs.gov","orcid":"https://orcid.org/0000-0001-5388-6675","contributorId":177154,"corporation":false,"usgs":true,"family":"Fleskes","given":"Joseph","email":"joe_fleskes@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":715917,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelman, T.","contributorId":198390,"corporation":false,"usgs":false,"family":"Kelman","given":"T.","email":"","affiliations":[],"preferred":false,"id":715918,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cadena, M.","contributorId":198391,"corporation":false,"usgs":false,"family":"Cadena","given":"M.","email":"","affiliations":[],"preferred":false,"id":715919,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pitesky, M.","contributorId":198392,"corporation":false,"usgs":false,"family":"Pitesky","given":"M.","affiliations":[],"preferred":false,"id":715920,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70193167,"text":"70193167 - 2017 - Validation of daily increments periodicity in otoliths of spotted gar","interactions":[],"lastModifiedDate":"2017-11-20T15:37:49","indexId":"70193167","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3909,"text":"Journal of the Southeastern Association of Fish and Wildlife Agencies","active":true,"publicationSubtype":{"id":10}},"title":"Validation of daily increments periodicity in otoliths of spotted gar","docAbstract":"Accurate age and growth information is essential in successful management of fish populations and for understanding early life history. We validated daily increment deposition, including the timing of first ring formation, for spotted gar (Lepisosteus oculatus) through 127 days post hatch. Fry were produced from hatchery-spawned specimens, and up to 10 individuals per week were sacrificed and their otoliths (sagitta, lapillus, and asteriscus) removed for daily age estimation. Daily age estimates for all three otolith pairs were significantly related to known age. The strongest relationships existed for measurements from the sagitta (r2 = 0.98) and the lapillus (r2 = 0.99) with asteriscus (r2 = 0.95) the lowest. All age prediction models resulted in a slope near unity, indicating that ring deposition occurred approximately daily. Initiation of ring formation varied among otolith types, with deposition beginning 3, 7, and 9 days for the sagitta, lapillus, and asteriscus, respectively. Results of this study suggested that otoliths are useful to estimate daily age of spotted gar juveniles; these data may be used to back calculate hatch dates, estimate early growth rates, and correlate with environmental factor that influence spawning in wild populations. is early life history information will be valuable in better understanding the ecology of this species.
","language":"English","publisher":"Southeastern Association of Fish and Wildlife Agencies","usgsCitation":"Snow, R.A., Long, J.M., and Frenette, B.D., 2017, Validation of daily increments periodicity in otoliths of spotted gar: Journal of the Southeastern Association of Fish and Wildlife Agencies, v. 4, p. 60-65.","productDescription":"6 p.","startPage":"60","endPage":"65","ipdsId":"IP-077724","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":349158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":349157,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.seafwa.org/publications/journal/?id=402080"}],"volume":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fc3de4b06e28e9c23bf9","contributors":{"authors":[{"text":"Snow, Richard A.","contributorId":176213,"corporation":false,"usgs":false,"family":"Snow","given":"Richard","email":"","middleInitial":"A.","affiliations":[{"id":27443,"text":"Oklahoma Department of Wildlife Conservation","active":true,"usgs":false}],"preferred":false,"id":722924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":718115,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frenette, Bryan D.","contributorId":200628,"corporation":false,"usgs":false,"family":"Frenette","given":"Bryan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":722925,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70193237,"text":"70193237 - 2017 - Spatial demographic models to inform conservation planning of golden eagles in renewable energy landscapes","interactions":[],"lastModifiedDate":"2017-11-22T17:05:17","indexId":"70193237","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"title":"Spatial demographic models to inform conservation planning of golden eagles in renewable energy landscapes","docAbstract":"Spatial demographic models can help guide monitoring and management activities targeting at-risk species, even in cases where baseline data are lacking. Here, we provide an example of how site-specific changes in land use and anthropogenic stressors can be incorporated into a spatial demographic model to investigate effects on population dynamics of Golden Eagles (Aquila chrysaetos). Our study focused on a population of Golden Eagles exposed to risks associated with rapid increases in renewable energy development in southern California, U.S.A. We developed a spatially explicit, individual-based simulation model that integrated empirical data on demography of Golden Eagles with spatial data on the arrangement of nesting habitats, prey resources, and planned renewable energy development sites. Our model permitted simulated eagles of different stage-classes to disperse, establish home ranges, acquire prey resources, prospect for breeding sites, and reproduce. The distribution of nesting habitats, prey resources, and threats within each individual's home range influenced movement, reproduction, and survival. We used our model to explore potential effects of alternative disturbance scenarios, and proposed conservation strategies, on the future distribution and abundance of Golden Eagles in the study region. Results from our simulations suggest that probable increases in mortality associated with renewable energy infrastructure (e.g., collisions with wind turbines and vehicles, electrocution on power poles) could have negative consequences for population trajectories, but that site-specific conservation actions could reduce the magnitude of negative effects. Our study demonstrates the use of a flexible and expandable modeling framework to incorporate spatially dependent processes when determining relative effects of proposed management options to Golden Eagles and their habitats.
","language":"English","publisher":"The Raptor Research Foundation","doi":"10.3356/JRR-16-77.1","usgsCitation":"Wiens, J.D., Schumaker, N.H., Inman, R.D., Esque, T., Longshore, K.M., and Nussear, K.E., 2017, Spatial demographic models to inform conservation planning of golden eagles in renewable energy landscapes: Journal of Raptor Research, v. 51, no. 3, p. 234-257, https://doi.org/10.3356/JRR-16-77.1.","productDescription":"24 p.","startPage":"234","endPage":"257","ipdsId":"IP-079327","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":470164,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3356/jrr-16-77.1","text":"Publisher Index Page"},{"id":347904,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","volume":"51","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f98bbae4b0531197afa004","contributors":{"authors":[{"text":"Wiens, J. 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Biomass of total catch per hectare has decreased 75 percent since 2013. Declines were observed across all functional groups, but most notable was the decline of Emerald Shiner, which decreased from 25.3 kg/ha in spring 2013 to <0.01 kg/ha by autumn 2013. The four primary predator species – Walleye, Yellow Perch, White Perch, and White Bass – all decreased from 2013 to 2015. In 2016, White Bass and Yellow Perch (all lifestages combined) continued to decline, while Walleye and White Perch (all ages combined) increased slightly from 5.6 kg/ha and 3.4 kg/ha to 9.0 kg/ha and 5.0 kg/ha, respectively (autumn catches). Despite decreasing trends in biomass, there was little change in biodiversity. Declines in forage biomass, i.e. Emerald Shiner and age-0 White Perch, resulted in an increased mean trophic level of catches. Forage fish to piscivore ratios reflected marked shifts in species composition toward greater forage in 2014 and 2016.
","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Bodamer Scarbro, B.L., Kraus, R.T., Kocovsky, P., and Vandergoot, C., 2017, Fisheries research and monitoring activities of the Lake Erie Biological Station, 2016.","ipdsId":"IP-084961","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":352813,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -78.83042561866203,\n 42.83947998725651\n ],\n [\n -79.05419559710549,\n 42.84445044266204\n ],\n [\n -79.34723947607836,\n 42.867505439860906\n ],\n [\n -79.63042902700818,\n 42.82979611449315\n ],\n [\n -80.19300640647401,\n 42.78683833970689\n ],\n [\n -80.48946185253618,\n 42.56830684920794\n ],\n [\n -80.75505536977545,\n 42.63058927982553\n ],\n [\n -81.2649125281849,\n 42.65947723113632\n ],\n [\n -81.68254937098362,\n 42.473095041315446\n ],\n [\n -81.94779341039089,\n 42.28566242550343\n ],\n [\n -82.45261137533379,\n 42.096617816981166\n ],\n [\n -82.50875433470178,\n 41.97702258755987\n ],\n [\n -82.6129085481856,\n 42.05303192857255\n ],\n [\n -82.96796357699394,\n 41.990378987810516\n ],\n [\n -83.11885623553695,\n 42.06549924415452\n ],\n [\n -83.11015681923705,\n 42.20201225480912\n ],\n [\n -83.20183479728604,\n 42.17539076035257\n ],\n [\n -83.24447886978825,\n 42.02138217144653\n ],\n [\n -83.29964209129852,\n 41.9183418231263\n ],\n [\n -83.46689589644896,\n 41.71125094657418\n ],\n [\n -83.17885165327081,\n 41.629872982739954\n ],\n [\n -82.94864727645425,\n 41.530145155769816\n ],\n [\n -82.94754108395134,\n 41.46190281418288\n ],\n [\n -82.68519761720665,\n 41.430232650244335\n ],\n [\n -82.45731725777486,\n 41.38919538555325\n ],\n [\n -82.18488329829222,\n 41.44165749902834\n ],\n [\n -82.00315923989179,\n 41.50180730835157\n ],\n [\n -81.76429181925941,\n 41.46784487565424\n ],\n [\n -81.43346949978508,\n 41.65468891025833\n ],\n [\n -81.07814633503381,\n 41.806259431479276\n ],\n [\n -80.6642163266489,\n 41.91355784022605\n ],\n [\n -80.08467398415922,\n 42.10240274001927\n ],\n [\n -79.65015538905237,\n 42.30010672051813\n ],\n [\n -79.23498337452526,\n 42.488602008238786\n ],\n [\n -78.83042561866203,\n 42.83947998725651\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee8f8e4b0da30c1bfc500","contributors":{"authors":[{"text":"Bodamer Scarbro, Betsy L. 0000-0002-9022-7027 bbodamerscarbro@usgs.gov","orcid":"https://orcid.org/0000-0002-9022-7027","contributorId":5857,"corporation":false,"usgs":true,"family":"Bodamer Scarbro","given":"Betsy","email":"bbodamerscarbro@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":688356,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kraus, Richard T. 0000-0003-4494-1841 rkraus@usgs.gov","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":2609,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","email":"rkraus@usgs.gov","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":688357,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kocovsky, Patrick 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":150837,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":688358,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vandergoot, Christopher 0000-0003-4128-3329 cvandergoot@usgs.gov","orcid":"https://orcid.org/0000-0003-4128-3329","contributorId":178356,"corporation":false,"usgs":true,"family":"Vandergoot","given":"Christopher","email":"cvandergoot@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":688359,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70181775,"text":"70181775 - 2017 - Detecting spatial regimes in ecosystems","interactions":[],"lastModifiedDate":"2017-02-14T10:28:26","indexId":"70181775","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Detecting spatial regimes in ecosystems","docAbstract":"Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory-based method, on both terrestrial and aquatic animal data (U.S. Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps and multivariate analyses such as nMDS and cluster analysis. We successfully detected spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change.
","language":"English","publisher":"Wiley","doi":"10.1111/ele.12709","usgsCitation":"Sundstrom, S.M., Eason, T., Nelson, R.J., Angeler, D., Barichievy, C., Garmestani, A.S., Graham, N.A., Granholm, D., Gunderson, L., Knutson, M., Nash, K.L., Spanbauer, T., Stow, C., and Allen, C.R., 2017, Detecting spatial regimes in ecosystems: Ecology Letters, v. 20, no. 1, p. 19-32, https://doi.org/10.1111/ele.12709.","productDescription":"14 p.","startPage":"19","endPage":"32","ipdsId":"IP-079617","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":461805,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/ele.12709","text":"External Repository"},{"id":335306,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-20","publicationStatus":"PW","scienceBaseUri":"58a2d3b6e4b0c82512869a05","chorus":{"doi":"10.1111/ele.12709","url":"http://dx.doi.org/10.1111/ele.12709","publisher":"Wiley-Blackwell","authors":"Sundstrom Shana M., Eason Tarsha, Nelson R. John, Angeler David G., Barichievy Chris, Garmestani Ahjond S., Graham Nicholas A.J., Granholm Dean, Gunderson Lance, Knutson Melinda, Nash Kirsty L., Spanbauer Trisha, Stow Craig A., Allen Craig R.","journalName":"Ecology Letters","publicationDate":"12/20/2016","auditedOn":"12/27/2016","publiclyAccessibleDate":"12/20/2016"},"contributors":{"authors":[{"text":"Sundstrom, Shana M.","contributorId":7159,"corporation":false,"usgs":true,"family":"Sundstrom","given":"Shana","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":668483,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eason, Tarsha","contributorId":82220,"corporation":false,"usgs":true,"family":"Eason","given":"Tarsha","email":"","affiliations":[],"preferred":false,"id":668503,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nelson, R. John","contributorId":98215,"corporation":false,"usgs":true,"family":"Nelson","given":"R.","email":"","middleInitial":"John","affiliations":[],"preferred":false,"id":668504,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Angeler, David G.","contributorId":25027,"corporation":false,"usgs":true,"family":"Angeler","given":"David G.","affiliations":[],"preferred":false,"id":668505,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barichievy, Chris","contributorId":17119,"corporation":false,"usgs":true,"family":"Barichievy","given":"Chris","email":"","affiliations":[],"preferred":false,"id":668506,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Garmestani, Ahjond S.","contributorId":77285,"corporation":false,"usgs":true,"family":"Garmestani","given":"Ahjond","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":668507,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Graham, Nicholas A.J.","contributorId":101990,"corporation":false,"usgs":true,"family":"Graham","given":"Nicholas","email":"","middleInitial":"A.J.","affiliations":[],"preferred":false,"id":668508,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Granholm, Dean","contributorId":85087,"corporation":false,"usgs":true,"family":"Granholm","given":"Dean","email":"","affiliations":[],"preferred":false,"id":668509,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gunderson, Lance","contributorId":30797,"corporation":false,"usgs":true,"family":"Gunderson","given":"Lance","affiliations":[],"preferred":false,"id":668510,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Knutson, Melinda","contributorId":27929,"corporation":false,"usgs":true,"family":"Knutson","given":"Melinda","affiliations":[],"preferred":false,"id":668511,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Nash, Kirsty L.","contributorId":40897,"corporation":false,"usgs":true,"family":"Nash","given":"Kirsty","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":668512,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Spanbauer, Trisha","contributorId":146435,"corporation":false,"usgs":false,"family":"Spanbauer","given":"Trisha","email":"","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":668513,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Stow, Craig A.","contributorId":49733,"corporation":false,"usgs":true,"family":"Stow","given":"Craig A.","affiliations":[],"preferred":false,"id":668514,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"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":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":668515,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70193025,"text":"70193025 - 2017 - Hydrochemical determination of source water contributions to Lake Lungo and Lake Ripasottile (central Italy)","interactions":[],"lastModifiedDate":"2017-11-12T11:35:55","indexId":"70193025","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5530,"text":"Journal of Limnology","onlineIssn":"1723-8633","active":true,"publicationSubtype":{"id":10}},"title":"Hydrochemical determination of source water contributions to Lake Lungo and Lake Ripasottile (central Italy)","docAbstract":"Lake Lungo and Lake Ripasottile are two shallow (4-5 m) lakes located in the Rieti Basin, central Italy, that have been described previously as surface outcroppings of the groundwater table. In this work, the two lakes as well as springs and rivers that represent their potential source waters are characterized physio-chemically and isotopically, using a combination of environmental tracers. Temperature and pH were measured and water samples were analyzed for alkalinity, major ion concentration, and stable isotope (δ2H, δ18O, δ13C of dissolved inorganic carbon, and δ34S and δ18O of sulfate) composition. Chemical data were also investigated in terms of local meteorological data (air temperature, precipitation) to determine the sensitivity of lake parameters to changes in the surrounding environment. Groundwater represented by samples taken from Santa Susanna Spring was shown to be distinct with SO42- and Mg2+ content of 270 and 29 mg/L, respectively, and heavy sulfate isotopic composition(δ34S=15.2 ‰ and δ18O=10‰). Outflow from the Santa Susanna Spring enters Lake Ripasottile via a canal and both spring and lake water exhibits the same chemical distinctions and comparatively low seasonal variability. Major ion concentrations in Lake Lungo are similar to the Vicenna Riara Spring and are interpreted to represent the groundwater locally recharged within the plain. The δ13CDIC exhibit the same groupings as the other chemical parameters, providing supporting evidence of the source relationships. Lake Lungo exhibited exceptional ranges of δ13CDIC (±5 ‰) and δ2H, δ18O (±5 ‰ and ±7 ‰, respectively), attributed to sensitivity to seasonal changes. The hydrochemistry results, particularly major ion data, highlight how the two lakes, though geographically and morphologically similar, represent distinct hydrochemical facies. These data also show a different response in each lake to temperature and precipitation patterns in the basin that may be attributed to lake water retention time. The sensitivity of each lake to meteorological patterns can be used to understand the potential effects from long-term climate variability.","language":"English","publisher":"PAGEPress Scientific Publications","publisherLocation":"Pavia, Italy","doi":"10.4081/jlimnol.2016.1576","usgsCitation":"Archer, C., Noble, P., Kreamer, D., Piscopo, V., Petitta, M., Rosen, M.R., Poulson, S.R., Piovesan, G., and Mensing, S., 2017, Hydrochemical determination of source water contributions to Lake Lungo and Lake Ripasottile (central Italy): Journal of Limnology, v. 76, no. 2, p. 326-342, https://doi.org/10.4081/jlimnol.2016.1576.","productDescription":"17 p.","startPage":"326","endPage":"342","ipdsId":"IP-079585","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"links":[{"id":470178,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4081/jlimnol.2016.1576","text":"Publisher Index Page"},{"id":348621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy","otherGeospatial":"Lake Lungo, Lake Ripasottile","volume":"76","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-21","publicationStatus":"PW","scienceBaseUri":"5a096bb1e4b09af898c94149","contributors":{"authors":[{"text":"Archer, Claire","contributorId":198952,"corporation":false,"usgs":false,"family":"Archer","given":"Claire","email":"","affiliations":[{"id":33648,"text":"Department of Geological Sciences and Engineering, University of Nevada","active":true,"usgs":false}],"preferred":false,"id":717688,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noble, Paula","contributorId":198953,"corporation":false,"usgs":false,"family":"Noble","given":"Paula","affiliations":[{"id":33648,"text":"Department of Geological Sciences and Engineering, University of Nevada","active":true,"usgs":false}],"preferred":false,"id":717689,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kreamer, David","contributorId":198954,"corporation":false,"usgs":false,"family":"Kreamer","given":"David","email":"","affiliations":[{"id":30777,"text":"Department of Geoscience, University of Nevada","active":true,"usgs":false}],"preferred":false,"id":717690,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Piscopo, Vincenzo","contributorId":198955,"corporation":false,"usgs":false,"family":"Piscopo","given":"Vincenzo","email":"","affiliations":[{"id":35390,"text":"Tuscia University","active":true,"usgs":false}],"preferred":false,"id":717691,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Petitta, Marco","contributorId":198956,"corporation":false,"usgs":false,"family":"Petitta","given":"Marco","email":"","affiliations":[{"id":35391,"text":"Sapienza University of Rome","active":true,"usgs":false}],"preferred":false,"id":717692,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rosen, Michael R. 0000-0003-3991-0522 mrosen@usgs.gov","orcid":"https://orcid.org/0000-0003-3991-0522","contributorId":495,"corporation":false,"usgs":true,"family":"Rosen","given":"Michael","email":"mrosen@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":717687,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Poulson, Simon R.","contributorId":187411,"corporation":false,"usgs":false,"family":"Poulson","given":"Simon","email":"","middleInitial":"R.","affiliations":[{"id":33648,"text":"Department of Geological Sciences and Engineering, University of Nevada","active":true,"usgs":false}],"preferred":false,"id":717693,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Piovesan, Gianluca","contributorId":198957,"corporation":false,"usgs":false,"family":"Piovesan","given":"Gianluca","email":"","affiliations":[{"id":35390,"text":"Tuscia University","active":true,"usgs":false}],"preferred":false,"id":717694,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mensing, Scott","contributorId":198958,"corporation":false,"usgs":false,"family":"Mensing","given":"Scott","affiliations":[{"id":33212,"text":"Department of Geography, University of NV","active":true,"usgs":false}],"preferred":false,"id":717695,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70179824,"text":"70179824 - 2017 - New techniques to measure cliff change from historical oblique aerial photographs and structure-from-motion photogrammetry","interactions":[],"lastModifiedDate":"2017-01-19T10:18:05","indexId":"70179824","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"New techniques to measure cliff change from historical oblique aerial photographs and structure-from-motion photogrammetry","docAbstract":"Oblique aerial photograph surveys are commonly used to document coastal landscapes. Here it is shown that adequate overlap may exist in these photographic records to develop topographic models with Structure-from-Motion (SfM) photogrammetric techniques. Using photographs of Fort Funston, California, from the California Coastal Records Project, imagery were combined with ground control points in a four-dimensional analysis that produced topographic point clouds of the study area’s cliffs for 5 years spanning 2002 to 2010. Uncertainty was assessed by comparing point clouds with airborne LIDAR data, and these uncertainties were related to the number and spatial distribution of ground control points used in the SfM analyses. With six or more ground control points, the root mean squared errors between the SfM and LIDAR data were less than 0.30 m (minimum 1⁄4 0.18 m), and the mean systematic error was less than 0.10 m. The SfM results had several benefits over traditional airborne LIDAR in that they included point coverage on vertical- to-overhanging sections of the cliff and resulted in 10–100 times greater point densities. Time series of the SfM results revealed topographic changes, including landslides, rock falls, and the erosion of landslide talus along the Fort Funston beach. Thus, it was concluded that SfM photogrammetric techniques with historical oblique photographs allow for the extraction of useful quantitative information for mapping coastal topography and measuring coastal change. The new techniques presented here are likely applicable to many photograph collections and problems in the earth sciences.","language":"English","publisher":"BioOne, Coastal education and research foundation","doi":"10.2112/JCOASTRES-D-16-00095.1","collaboration":"Olympic National Park; California Coastal Records Project","usgsCitation":"Warrick, J.A., Ritchie, A., Adelman, G., Adelman, K., and Limber, P.W., 2017, New techniques to measure cliff change from historical oblique aerial photographs and structure-from-motion photogrammetry: Journal of Coastal Research, v. 33, no. 1, p. 39-55, https://doi.org/10.2112/JCOASTRES-D-16-00095.1.","productDescription":"17 p. ","startPage":"39","endPage":"55","ipdsId":"IP-075270","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470181,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2112/jcoastres-d-16-00095.1","text":"Publisher Index Page"},{"id":333423,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5881ded3e4b01192927d9f7b","contributors":{"authors":[{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":658843,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ritchie, Andy","contributorId":178426,"corporation":false,"usgs":false,"family":"Ritchie","given":"Andy","email":"","affiliations":[],"preferred":false,"id":658844,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adelman, Gabrielle","contributorId":178427,"corporation":false,"usgs":false,"family":"Adelman","given":"Gabrielle","email":"","affiliations":[],"preferred":false,"id":658845,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adelman, Ken","contributorId":178428,"corporation":false,"usgs":false,"family":"Adelman","given":"Ken","email":"","affiliations":[],"preferred":false,"id":658846,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Limber, Patrick W. 0000-0002-8207-3750 plimber@usgs.gov","orcid":"https://orcid.org/0000-0002-8207-3750","contributorId":5773,"corporation":false,"usgs":true,"family":"Limber","given":"Patrick","email":"plimber@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":658847,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70189500,"text":"70189500 - 2017 - Relative contributions of copper oxide nanoparticles and dissolved copper to Cu uptake kinetics of Gulf killifish (Fundulus grandis) embryos","interactions":[],"lastModifiedDate":"2017-07-13T16:27:55","indexId":"70189500","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Relative contributions of copper oxide nanoparticles and dissolved copper to Cu uptake kinetics of Gulf killifish (Fundulus grandis) embryos","title":"Relative contributions of copper oxide nanoparticles and dissolved copper to Cu uptake kinetics of Gulf killifish (Fundulus grandis) embryos","docAbstract":"The toxicity of soluble metal-based nanomaterials may be due to the uptake of metals in both dissolved and nanoparticulate forms, but the relative contributions of these different forms to overall metal uptake rates under environmental conditions are not quantitatively defined. Here, we investigated the linkage between the dissolution rates of copper(II) oxide (CuO) nanoparticles (NPs) and their bioavailability to Gulf killifish (Fundulus grandis) embryos, with the aim of quantitatively delineating the relative contributions of nanoparticulate and dissolved species for Cu uptake. Gulf killifish embryos were exposed to dissolved Cu and CuO NP mixtures comprising a range of pH values (6.3–7.5) and three types of natural organic matter (NOM) isolates at various concentrations (0.1–10 mg-C L–1), resulting in a wide range of CuO NP dissolution rates that subsequently influenced Cu uptake. First-order dissolution rate constants of CuO NPs increased with increasing NOM concentration and for NOM isolates with higher aromaticity, as indicated by specific ultraviolet absorbance (SUVA), while Cu uptake rate constants of both dissolved Cu and CuO NP decreased with NOM concentration and aromaticity. As a result, the relative contribution of dissolved Cu and nanoparticulate CuO species for the overall Cu uptake rate was insensitive to NOM type or concentration but largely determined by the percentage of CuO that dissolved. These findings highlight SUVA and aromaticity as key NOM properties affecting the dissolution kinetics and bioavailability of soluble metal-based nanomaterials in organic-rich waters. These properties could be used in the incorporation of dissolution kinetics into predictive models for environmental risks of nanomaterials.
","language":"English","publisher":"ACS","doi":"10.1021/acs.est.6b04672","usgsCitation":"Jiang, C., Castellon, B.T., Matson, C., Aiken, G.R., and Hsu-Kim, H., 2017, Relative contributions of copper oxide nanoparticles and dissolved copper to Cu uptake kinetics of Gulf killifish (Fundulus grandis) embryos: Environmental Science & Technology, v. 51, no. 3, p. 1395-1404, https://doi.org/10.1021/acs.est.6b04672.","productDescription":"10 p.","startPage":"1395","endPage":"1404","ipdsId":"IP-080135","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343831,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"3","noUsgsAuthors":false,"publicationDate":"2017-01-27","publicationStatus":"PW","scienceBaseUri":"596886a0e4b0d1f9f05f5992","contributors":{"authors":[{"text":"Jiang, Chuanjia","contributorId":194659,"corporation":false,"usgs":false,"family":"Jiang","given":"Chuanjia","email":"","affiliations":[],"preferred":false,"id":704919,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Castellon, Benjamin T.","contributorId":194660,"corporation":false,"usgs":false,"family":"Castellon","given":"Benjamin","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":704920,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Matson, Cole W.","contributorId":141222,"corporation":false,"usgs":false,"family":"Matson","given":"Cole W.","affiliations":[{"id":13716,"text":"Baylor University","active":true,"usgs":false}],"preferred":false,"id":704921,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":704922,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hsu-Kim, Heileen","contributorId":49041,"corporation":false,"usgs":false,"family":"Hsu-Kim","given":"Heileen","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":704923,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70192516,"text":"70192516 - 2017 - Impacts of mesquite distribution on seasonal space use of lesser prairie-chickens","interactions":[],"lastModifiedDate":"2017-10-26T13:45:42","indexId":"70192516","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Impacts of mesquite distribution on seasonal space use of lesser prairie-chickens","docAbstract":"Loss of native grasslands by anthropogenic disturbances has reduced availability and connectivity of habitat for many grassland species. A primary threat to contiguous grasslands is the encroachment of woody vegetation, which is spurred by disturbances that take on many forms from energy development, fire suppression, and grazing. These disturbances are exacerbated by natural- and human-driven cycles of changes in climate punctuated by drought and desertification conditions. Encroachment of honey mesquite (Prosopis glandulosa) into the prairies of southeastern New Mexico has potentially limited habitat for numerous grassland species, including lesser prairie-chickens (Tympanuchus pallidicinctus). To determine the magnitude of impacts of distribution of mesquite and how lesser prairie-chickens respond to mesquite presence on the landscape in southeastern New Mexico, we evaluated seasonal space use of lesser prairie-chickens in the breeding and nonbreeding seasons. We derived several remotely sensed spatial metrics to characterize the distribution of mesquite. We then used these data to create population-level resource utilization functions and predict intensity of use of lesser prairie-chickens across our study area. Home ranges were smaller in the breeding season compared with the nonbreeding season; however, habitat use was similar across seasons. During both seasons, lesser prairie-chickens used areas closer to leks and largely avoided areas with mesquite. Relative to the breeding season, during the nonbreeding season habitat use suggested a marginal increase in mesquite within areas of low intensity of use, yet aversion to mesquite was strong in areas of medium to high intensity of use. To our knowledge, our study is the first to demonstrate a negative behavioral response by lesser prairie-chickens to woody encroachment in native grasslands. To mitigate one of the possible limiting factors for lesser prairie-chickens, we suggest future conservation strategies be employed by land managersto reduce mesquite abundance in the southern portion of their current range.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2016.09.006","usgsCitation":"Boggie, M.A., Strong, C.R., Lusk, D., Carleton, S.A., Gould, W., Howard, R.L., Nichols, C.T., Falkowski, M.J., and Hagen, C.A., 2017, Impacts of mesquite distribution on seasonal space use of lesser prairie-chickens: Rangeland Ecology and Management, v. 70, no. 1, p. 68-77, https://doi.org/10.1016/j.rama.2016.09.006.","productDescription":"10 p.","startPage":"68","endPage":"77","ipdsId":"IP-073814","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470250,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2016.09.006","text":"Publisher Index Page"},{"id":347478,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","county":"Chaves County, Lea 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T.","contributorId":193024,"corporation":false,"usgs":false,"family":"Nichols","given":"Clay","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":716415,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Falkowski, Michael J.","contributorId":198547,"corporation":false,"usgs":false,"family":"Falkowski","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":716416,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hagen, Christian A.","contributorId":177795,"corporation":false,"usgs":false,"family":"Hagen","given":"Christian","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":716417,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70187204,"text":"70187204 - 2017 - Accurate aging of juvenile salmonids using fork lengths","interactions":[],"lastModifiedDate":"2017-04-26T12:54:27","indexId":"70187204","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"Accurate aging of juvenile salmonids using fork lengths","docAbstract":"Juvenile salmon life history strategies, survival, and habitat interactions may vary by age cohort. However, aging individual juvenile fish using scale reading is time consuming and can be error prone. Fork length data are routinely measured while sampling juvenile salmonids. We explore the performance of aging juvenile fish based solely on fork length data, using finite Gaussian mixture models to describe multimodal size distributions and estimate optimal age-discriminating length thresholds. Fork length-based ages are compared against a validation set of juvenile coho salmon, Oncorynchus kisutch, aged by scales. Results for juvenile coho salmon indicate greater than 95% accuracy can be achieved by aging fish using length thresholds estimated from mixture models. Highest accuracy is achieved when aged fish are compared to length thresholds generated from samples from the same drainage, time of year, and habitat type (lentic versus lotic), although relatively high aging accuracy can still be achieved when thresholds are extrapolated to fish from populations in different years or drainages. Fork length-based aging thresholds are applicable for taxa for which multiple age cohorts coexist sympatrically. Where applicable, the method of aging individual fish is relatively quick to implement and can avoid ager interpretation bias common in scale-based aging.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2016.09.012","usgsCitation":"Sethi, S., Gerken, J., and Ashline, J., 2017, Accurate aging of juvenile salmonids using fork lengths: Fisheries Research, v. 185, p. 161-168, https://doi.org/10.1016/j.fishres.2016.09.012.","productDescription":"8 p.","startPage":"161","endPage":"168","ipdsId":"IP-077073","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":470171,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.fishres.2016.09.012","text":"Publisher Index Page"},{"id":340459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"185","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5901b1bae4b0c2e071a99b92","contributors":{"authors":[{"text":"Sethi, Suresh 0000-0002-0053-1827 ssethi@usgs.gov","orcid":"https://orcid.org/0000-0002-0053-1827","contributorId":191424,"corporation":false,"usgs":true,"family":"Sethi","given":"Suresh","email":"ssethi@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gerken, Jonathon","contributorId":191437,"corporation":false,"usgs":false,"family":"Gerken","given":"Jonathon","email":"","affiliations":[],"preferred":false,"id":693046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ashline, Joshua","contributorId":191438,"corporation":false,"usgs":false,"family":"Ashline","given":"Joshua","email":"","affiliations":[],"preferred":false,"id":693047,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70186169,"text":"70186169 - 2017 - Summer habitat selection by Dall’s sheep in Wrangell-St. Elias National Park and Preserve, Alaska","interactions":[],"lastModifiedDate":"2017-03-30T15:13:22","indexId":"70186169","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2373,"text":"Journal of Mammalogy","onlineIssn":"1545-1542","printIssn":"0022-2372","active":true,"publicationSubtype":{"id":10}},"title":"Summer habitat selection by Dall’s sheep in Wrangell-St. Elias National Park and Preserve, Alaska","docAbstract":"Sexual segregation occurs frequently in sexually dimorphic species, and it may be influenced by differential habitat requirements between sexes or by social or evolutionary mechanisms that maintain separation of sexes regardless of habitat selection. Understanding the degree of sex-specific habitat specialization is important for management of wildlife populations and the design of monitoring and research programs. Using mid-summer aerial survey data for Dall’s sheep (Ovis dalli dalli) in southern Alaska during 1983–2011, we assessed differences in summer habitat selection by sex and reproductive status at the landscape scale in Wrangell-St. Elias National Park and Preserve (WRST). Males and females were highly segregated socially, as were females with and without young. Resource selection function (RSF) models containing rugged terrain, intermediate values of the normalized difference vegetation index (NDVI), and open landcover types best explained resource selection by each sex, female reproductive classes, and all sheep combined. For male and all female models, most coefficients were similar, suggesting little difference in summer habitat selection between sexes at the landscape scale. A combined RSF model therefore may be used to predict the relative probability of resource selection by Dall’s sheep in WRST regardless of sex or reproductive status.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/jmammal/gyw135","usgsCitation":"Roffler, G.H., Adams, L., and Hebblewhite, M., 2017, Summer habitat selection by Dall’s sheep in Wrangell-St. Elias National Park and Preserve, Alaska: Journal of Mammalogy, v. 98, no. 1, p. 94-105, https://doi.org/10.1093/jmammal/gyw135.","productDescription":"12 p.","startPage":"94","endPage":"105","ipdsId":"IP-060082","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":470170,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyw135","text":"Publisher Index Page"},{"id":338838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"98","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-17","publicationStatus":"PW","scienceBaseUri":"58de194fe4b02ff32c699ca1","chorus":{"doi":"10.1093/jmammal/gyw135","url":"http://dx.doi.org/10.1093/jmammal/gyw135","publisher":"Oxford University Press (OUP)","authors":"Roffler Gretchen H., Adams Layne G., Hebblewhite Mark","journalName":"Journal of Mammalogy","publicationDate":"9/17/2016"},"contributors":{"authors":[{"text":"Roffler, Gretchen H. groffler@usgs.gov","contributorId":1946,"corporation":false,"usgs":true,"family":"Roffler","given":"Gretchen","email":"groffler@usgs.gov","middleInitial":"H.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":687742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Layne G. 0000-0001-6212-2896 ladams@usgs.gov","orcid":"https://orcid.org/0000-0001-6212-2896","contributorId":2776,"corporation":false,"usgs":true,"family":"Adams","given":"Layne G.","email":"ladams@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":687741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hebblewhite, Mark","contributorId":190188,"corporation":false,"usgs":false,"family":"Hebblewhite","given":"Mark","email":"","affiliations":[],"preferred":false,"id":687743,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70191835,"text":"70191835 - 2017 - The history of late holocene surface-faulting earthquakes on the central segments of the Wasatch fault zone, Utah","interactions":[],"lastModifiedDate":"2018-02-15T11:13:15","indexId":"70191835","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"The history of late holocene surface-faulting earthquakes on the central segments of the Wasatch fault zone, Utah","docAbstract":"The Wasatch fault (WFZ)—Utah’s longest and most active normal fault—forms a prominent eastern boundary to the Basin and Range Province in northern Utah. To provide paleoseismic data for a Wasatch Front regional earthquake forecast, we synthesized paleoseismic data to define the timing and displacements of late Holocene surface-faulting earthquakes on the central five segments of the WFZ. Our analysis yields revised histories of large (M ~7) surface-faulting earthquakes on the segments, as well as estimates of earthquake recurrence and vertical slip rate. We constrain the timing of four to six earthquakes on each of the central segments, which together yields a history of at least 24 surface-faulting earthquakes since ~6 ka. Using earthquake data for each segment, inter-event recurrence intervals range from about 0.6 to 2.5 kyr, and have a mean of 1.2 kyr. Mean recurrence, based on closed seismic intervals, is ~1.1–1.3 kyr per segment, and when combined with mean vertical displacements per segment of 1.7–2.6 m, yield mean vertical slip rates of 1.3–2.0 mm/yr per segment. These data refine the late Holocene behavior of the central WFZ; however, a significant source of uncertainty is whether structural complexities that define the segments of the WFZ act as hard barriers to ruptures propagating along the fault. Thus, we evaluate fault rupture models including both single-segment and multi-segment ruptures, and define 3–17-km-wide spatial uncertainties in the segment boundaries. These alternative rupture models and segment-boundary zones honor the WFZ paleoseismic data, take into account the spatial and temporal limitations of paleoseismic data, and allow for complex ruptures such as partial-segment and spillover ruptures. Our data and analyses improve our understanding of the complexities in normal-faulting earthquake behavior and provide geological inputs for regional earthquake-probability and seismic hazard assessments.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geology and resources of the Wasatch: Back to front, Utah Geological Association Publication 46","language":"English","publisher":"Utah Geological Association","usgsCitation":"DuRoss, C., Personius, S., Olig, S.S., Crone, A.J., Hylland, M.D., Lund, W.R., and Schwartz, D.P., 2017, The history of late holocene surface-faulting earthquakes on the central segments of the Wasatch fault zone, Utah, chap. of Geology and resources of the Wasatch: Back to front, Utah Geological Association Publication 46, v. 46, p. 1-51.","productDescription":"51 p.","startPage":"1","endPage":"51","ipdsId":"IP-083722","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":351656,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":351655,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.mapstore.utah.gov/uga46.html"}],"volume":"46","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee8f8e4b0da30c1bfc4fa","contributors":{"authors":[{"text":"DuRoss, Christopher 0000-0002-6963-7451 cduross@usgs.gov","orcid":"https://orcid.org/0000-0002-6963-7451","contributorId":152321,"corporation":false,"usgs":true,"family":"DuRoss","given":"Christopher","email":"cduross@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":713293,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Personius, Stephen 0000-0001-8347-7370 personius@usgs.gov","orcid":"https://orcid.org/0000-0001-8347-7370","contributorId":150055,"corporation":false,"usgs":true,"family":"Personius","given":"Stephen","email":"personius@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":713294,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olig, Susan S","contributorId":197357,"corporation":false,"usgs":false,"family":"Olig","given":"Susan","email":"","middleInitial":"S","affiliations":[],"preferred":false,"id":713295,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crone, Anthony J. 0000-0002-3006-406X crone@usgs.gov","orcid":"https://orcid.org/0000-0002-3006-406X","contributorId":790,"corporation":false,"usgs":true,"family":"Crone","given":"Anthony","email":"crone@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":713296,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hylland, Michael D.","contributorId":195214,"corporation":false,"usgs":false,"family":"Hylland","given":"Michael","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":713297,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lund, William R.","contributorId":197358,"corporation":false,"usgs":false,"family":"Lund","given":"William","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":713298,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schwartz, David P. 0000-0001-5193-9200 dschwartz@usgs.gov","orcid":"https://orcid.org/0000-0001-5193-9200","contributorId":1940,"corporation":false,"usgs":true,"family":"Schwartz","given":"David","email":"dschwartz@usgs.gov","middleInitial":"P.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":713299,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70195830,"text":"70195830 - 2017 - Understanding the past to interpret the future: Comparison of simulated groundwater recharge in the upper Colorado River basin (USA) using observed and general-circulation-model historical climate data","interactions":[],"lastModifiedDate":"2020-12-10T13:20:04.696686","indexId":"70195830","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Understanding the past to interpret the future: Comparison of simulated groundwater recharge in the upper Colorado River basin (USA) using observed and general-circulation-model historical climate data","docAbstract":"In evaluating potential impacts of climate change on water resources, water managers seek to understand how future conditions may differ from the recent past. Studies of climate impacts on groundwater recharge often compare simulated recharge from future and historical time periods on an average monthly or overall average annual basis, or compare average recharge from future decades to that from a single recent decade. Baseline historical recharge estimates, which are compared with future conditions, are often from simulations using observed historical climate data. Comparison of average monthly results, average annual results, or even averaging over selected historical decades, may mask the true variability in historical results and lead to misinterpretation of future conditions. Comparison of future recharge results simulated using general circulation model (GCM) climate data to recharge results simulated using actual historical climate data may also result in an incomplete understanding of the likelihood of future changes. In this study, groundwater recharge is estimated in the upper Colorado River basin, USA, using a distributed-parameter soil-water balance groundwater recharge model for the period 1951–2010. Recharge simulations are performed using precipitation, maximum temperature, and minimum temperature data from observed climate data and from 97 CMIP5 (Coupled Model Intercomparison Project, phase 5) projections. Results indicate that average monthly and average annual simulated recharge are similar using observed and GCM climate data. However, 10-year moving-average recharge results show substantial differences between observed and simulated climate data, particularly during period 1970–2000, with much greater variability seen for results using observed climate data.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-016-1481-0","usgsCitation":"Tillman, F., Gangopadhyay, S., and Pruitt, T., 2017, Understanding the past to interpret the future: Comparison of simulated groundwater recharge in the upper Colorado River basin (USA) using observed and general-circulation-model historical climate data: Hydrogeology Journal, v. 25, no. 2, p. 347-358, https://doi.org/10.1007/s10040-016-1481-0.","productDescription":"12 p.","startPage":"347","endPage":"358","ipdsId":"IP-076138","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":352218,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Colorado River basin","volume":"25","issue":"2","noUsgsAuthors":false,"publicationDate":"2016-10-19","publicationStatus":"PW","scienceBaseUri":"5afee8ebe4b0da30c1bfc4d8","contributors":{"authors":[{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":1629,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred D.","email":"ftillman@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":false,"id":730201,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gangopadhyay, Subhrendu 0000-0003-3864-8251","orcid":"https://orcid.org/0000-0003-3864-8251","contributorId":173439,"corporation":false,"usgs":false,"family":"Gangopadhyay","given":"Subhrendu","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":730202,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pruitt, Tom 0000-0002-3543-1324","orcid":"https://orcid.org/0000-0002-3543-1324","contributorId":173440,"corporation":false,"usgs":false,"family":"Pruitt","given":"Tom","email":"","affiliations":[{"id":27228,"text":"Reclamation","active":true,"usgs":false}],"preferred":false,"id":730203,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70192833,"text":"70192833 - 2017 - Thumbnail‐based questionnaires for the rapid and efficient collection of macroseismic data from global earthquakes","interactions":[],"lastModifiedDate":"2017-10-30T16:19:05","indexId":"70192833","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Thumbnail‐based questionnaires for the rapid and efficient collection of macroseismic data from global earthquakes","docAbstract":"The collection of earthquake testimonies (i.e., qualitative descriptions of felt shaking) is essential for macroseismic studies (i.e., studies gathering information on how strongly an earthquake was felt in different places), and when done rapidly and systematically, improves situational awareness and in turn can contribute to efficient emergency response. In this study, we present advances made in the collection of testimonies following earthquakes around the world using a thumbnail‐based questionnaire implemented on the European‐Mediterranean Seismological Centre (EMSC) smartphone app and its website compatible for mobile devices. In both instances, the questionnaire consists of a selection of thumbnails, each representing an intensity level of the European Macroseismic Scale 1998. We find that testimonies are collected faster, and in larger numbers, by way of thumbnail‐based questionnaires than by more traditional online questionnaires. Responses were received from all seismically active regions of our planet, suggesting that thumbnails overcome language barriers. We also observed that the app is not sufficient on its own, because the websites are the main source of testimonies when an earthquake strikes a region for the first time in a while; it is only for subsequent shocks that the app is widely used. Notably though, the speed of the collection of testimonies increases significantly when the app is used. We find that automated EMSC intensities as assigned by user‐specified thumbnails are, on average, well correlated with “Did You Feel It?” (DYFI) responses and with the three independently and manually derived macroseismic datasets, but there is a tendency for EMSC to be biased low with respect to DYFI at moderate and large intensities. We address this by proposing a simple adjustment that will be verified in future earthquakes.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220160120","usgsCitation":"Bossu, R., Landes, M., Roussel, F., Steed, R., Mazet-Roux, G., Martin, S.S., and Hough, S.E., 2017, Thumbnail‐based questionnaires for the rapid and efficient collection of macroseismic data from global earthquakes: Seismological Research Letters, v. 88, no. 1, p. 72-81, https://doi.org/10.1785/0220160120.","productDescription":"10 p.","startPage":"72","endPage":"81","ipdsId":"IP-079649","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":470167,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1785/0220160120","text":"External Repository"},{"id":347752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"88","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-26","publicationStatus":"PW","scienceBaseUri":"59f83a3ae4b063d5d30980f7","contributors":{"authors":[{"text":"Bossu, Remy","contributorId":198780,"corporation":false,"usgs":false,"family":"Bossu","given":"Remy","email":"","affiliations":[],"preferred":false,"id":717115,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Landes, Matthieu","contributorId":198781,"corporation":false,"usgs":false,"family":"Landes","given":"Matthieu","email":"","affiliations":[],"preferred":false,"id":717116,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roussel, Frederic","contributorId":198782,"corporation":false,"usgs":false,"family":"Roussel","given":"Frederic","email":"","affiliations":[],"preferred":false,"id":717117,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Steed, Robert","contributorId":198783,"corporation":false,"usgs":false,"family":"Steed","given":"Robert","email":"","affiliations":[],"preferred":false,"id":717118,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mazet-Roux, Gilles","contributorId":198784,"corporation":false,"usgs":false,"family":"Mazet-Roux","given":"Gilles","email":"","affiliations":[],"preferred":false,"id":717119,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Martin, Stacey S.","contributorId":140021,"corporation":false,"usgs":false,"family":"Martin","given":"Stacey","email":"","middleInitial":"S.","affiliations":[{"id":5110,"text":"Earth Observatory of Singapore, Nanyang Technological University","active":true,"usgs":false}],"preferred":false,"id":717120,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hough, Susan E. 0000-0002-5980-2986 hough@usgs.gov","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":587,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"hough@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":717114,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70189831,"text":"70189831 - 2017 - Using structural damage statistics to derive macroseismic intensity within the Kathmandu valley for the 2015 M7.8 Gorkha, Nepal earthquake","interactions":[],"lastModifiedDate":"2018-03-27T11:19:18","indexId":"70189831","displayToPublicDate":"2016-12-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3525,"text":"Tectonophysics","active":true,"publicationSubtype":{"id":10}},"title":"Using structural damage statistics to derive macroseismic intensity within the Kathmandu valley for the 2015 M7.8 Gorkha, Nepal earthquake","docAbstract":"We make and analyze structural damage observations from within the Kathmandu valley following the 2015 M7.8 Gorkha, Nepal earthquake to derive macroseismic intensities at several locations including some located near ground motion recording sites. The macroseismic intensity estimates supplement the limited strong ground motion data in order to characterize the damage statistics. This augmentation allows for direct comparisons between ground motion amplitudes and structural damage characteristics and ultimately produces a more constrained ground shaking hazard map for the Gorkha earthquake. For systematic assessments, we focused on damage to three specific building categories: (a) low/mid-rise reinforced concrete frames with infill brick walls, (b) unreinforced brick masonry bearing walls with reinforced concrete slabs, and (c) unreinforced brick masonry bearing walls with partial timber framing. Evaluating dozens of photos of each construction type, assigning each building in the study sample to a European Macroseismic Scale (EMS)-98 Vulnerability Class based upon its structural characteristics, and then individually assigning an EMS-98 Damage Grade to each building allows a statistically derived estimate of macroseismic intensity for each of nine study areas in and around the Kathmandu valley. This analysis concludes that EMS-98 macroseismic intensities for the study areas from the Gorkha mainshock typically were in the VII–IX range. The intensity assignment process described is more rigorous than the informal approach of assigning intensities based upon anecdotal media or first-person accounts of felt-reports, shaking, and their interpretation of damage. Detailed EMS-98 macroseismic assessments in urban areas are critical for quantifying relations between shaking and damage as well as for calibrating loss estimates. We show that the macroseismic assignments made herein result in fatality estimates consistent with the overall and district-wide reported values.","language":"English","publisher":"Elsevier","doi":"10.1016/j.tecto.2016.08.002","usgsCitation":"McGowan, S., Jaiswal, K.S., and Wald, D.J., 2017, Using structural damage statistics to derive macroseismic intensity within the Kathmandu valley for the 2015 M7.8 Gorkha, Nepal earthquake: Tectonophysics, v. 714-715, p. 158-172, https://doi.org/10.1016/j.tecto.2016.08.002.","productDescription":"15 p.","startPage":"158","endPage":"172","ipdsId":"IP-078944","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":470183,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.tecto.2016.08.002","text":"Publisher Index Page"},{"id":344402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Nepal","otherGeospatial":"Kathmandu Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 84.715576171875,\n 27.176469131898898\n ],\n [\n 86.0888671875,\n 27.176469131898898\n ],\n [\n 86.0888671875,\n 27.97499795326776\n ],\n [\n 84.715576171875,\n 27.97499795326776\n ],\n [\n 84.715576171875,\n 27.176469131898898\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"714-715","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"597afba6e4b0a38ca2750b5e","contributors":{"authors":[{"text":"McGowan, Sean","contributorId":195190,"corporation":false,"usgs":false,"family":"McGowan","given":"Sean","affiliations":[],"preferred":false,"id":706492,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":706493,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":706494,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70179304,"text":"70179304 - 2017 - Challenges with secondary use of multi-source water-quality data in the United States","interactions":[],"lastModifiedDate":"2017-01-03T10:15:39","indexId":"70179304","displayToPublicDate":"2016-12-28T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Challenges with secondary use of multi-source water-quality data in the United States","docAbstract":"Combining water-quality data from multiple sources can help counterbalance diminishing resources for stream monitoring in the United States and lead to important regional and national insights that would not otherwise be possible. Individual monitoring organizations understand their own data very well, but issues can arise when their data are combined with data from other organizations that have used different methods for reporting the same common metadata elements. Such use of multi-source data is termed “secondary use”—the use of data beyond the original intent determined by the organization that collected the data. In this study, we surveyed more than 25 million nutrient records collected by 488 organizations in the United States since 1899 to identify major inconsistencies in metadata elements that limit the secondary use of multi-source data. Nearly 14.5 million of these records had missing or ambiguous information for one or more key metadata elements, including (in decreasing order of records affected) sample fraction, chemical form, parameter name, units of measurement, precise numerical value, and remark codes. As a result, metadata harmonization to make secondary use of these multi-source data will be time consuming, expensive, and inexact. Different data users may make different assumptions about the same ambiguous data, potentially resulting in different conclusions about important environmental issues. The value of these ambiguous data is estimated at \\$US12 billion, a substantial collective investment by water-resource organizations in the United States. By comparison, the value of unambiguous data is estimated at \\$US8.2 billion. The ambiguous data could be preserved for uses beyond the original intent by developing and implementing standardized metadata practices for future and legacy water-quality data throughout the United States.
","language":"English","publisher":"International Association on Water Pollution Research","publisherLocation":"Amsterdam","doi":"10.1016/j.watres.2016.12.024","usgsCitation":"Sprague, L.A., Oelsner, G.P., and Argue, D.M., 2017, Challenges with secondary use of multi-source water-quality data in the United States: Water Research, v. 110, p. 252-261, https://doi.org/10.1016/j.watres.2016.12.024.","productDescription":"10 p.","startPage":"252","endPage":"261","ipdsId":"IP-078333","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":470186,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watres.2016.12.024","text":"Publisher Index Page"},{"id":332569,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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goelsner@usgs.gov","orcid":"https://orcid.org/0000-0001-9329-7357","contributorId":4440,"corporation":false,"usgs":true,"family":"Oelsner","given":"Gretchen","email":"goelsner@usgs.gov","middleInitial":"P.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":656682,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Argue, Denise M. 0000-0002-1096-5362 dmargue@usgs.gov","orcid":"https://orcid.org/0000-0002-1096-5362","contributorId":2636,"corporation":false,"usgs":true,"family":"Argue","given":"Denise","email":"dmargue@usgs.gov","middleInitial":"M.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":656683,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70179284,"text":"70179284 - 2017 - The practice of prediction: What can ecologists learn from applied, ecology-related fields?","interactions":[],"lastModifiedDate":"2017-12-11T14:01:21","indexId":"70179284","displayToPublicDate":"2016-12-27T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1452,"text":"Ecological Complexity","active":true,"publicationSubtype":{"id":10}},"title":"The practice of prediction: What can ecologists learn from applied, ecology-related fields?","docAbstract":"The pervasive influence of human induced global environmental change affects biodiversity across the globe, and there is great uncertainty as to how the biosphere will react on short and longer time scales. To adapt to what the future holds and to manage the impacts of global change, scientists need to predict the expected effects with some confidence and communicate these predictions to policy makers. However, recent reviews found that we currently lack a clear understanding of how predictable ecology is, with views seeing it as mostly unpredictable to potentially predictable, at least over short time frames. However, in applied, ecology-related fields predictions are more commonly formulated and reported, as well as evaluated in hindsight, potentially allowing one to define baselines of predictive proficiency in these fields. We searched the literature for representative case studies in these fields and collected information about modeling approaches, target variables of prediction, predictive proficiency achieved, as well as the availability of data to parameterize predictive models. We find that some fields such as epidemiology achieve high predictive proficiency, but even in the more predictive fields proficiency is evaluated in different ways. Both phenomenological and mechanistic approaches are used in most fields, but differences are often small, with no clear superiority of one approach over the other. Data availability is limiting in most fields, with long-term studies being rare and detailed data for parameterizing mechanistic models being in short supply. We suggest that ecologists adopt a more rigorous approach to report and assess predictive proficiency, and embrace the challenges of real world decision making to strengthen the practice of prediction in ecology.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecocom.2016.12.005","usgsCitation":"Pennekamp, F., Adamson, M., Petchey, O.L., Poggiale, J., Aguiar, M., Kooi, B.W., Botkin, D.B., and DeAngelis, D.L., 2017, The practice of prediction: What can ecologists learn from applied, ecology-related fields?: Ecological Complexity, v. 32, no. B, p. 156-167, https://doi.org/10.1016/j.ecocom.2016.12.005.","productDescription":"12 p.","startPage":"156","endPage":"167","onlineOnly":"Y","ipdsId":"IP-074291","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":470187,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5167/uzh-134675","text":"Publisher Index Page"},{"id":332565,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"B","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5864dd4de4b0cd2dabe7c1c9","contributors":{"authors":[{"text":"Pennekamp, Frank","contributorId":177677,"corporation":false,"usgs":false,"family":"Pennekamp","given":"Frank","email":"","affiliations":[],"preferred":false,"id":656646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adamson, Matthew","contributorId":177678,"corporation":false,"usgs":false,"family":"Adamson","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":656647,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Petchey, Owen L","contributorId":177679,"corporation":false,"usgs":false,"family":"Petchey","given":"Owen","email":"","middleInitial":"L","affiliations":[],"preferred":false,"id":656648,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Poggiale, Jean-Christophe","contributorId":177680,"corporation":false,"usgs":false,"family":"Poggiale","given":"Jean-Christophe","email":"","affiliations":[],"preferred":false,"id":656649,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aguiar, Maira","contributorId":177681,"corporation":false,"usgs":false,"family":"Aguiar","given":"Maira","email":"","affiliations":[],"preferred":false,"id":656650,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kooi, Bob W.","contributorId":152069,"corporation":false,"usgs":false,"family":"Kooi","given":"Bob","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":656651,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Botkin, Daniel B.","contributorId":90917,"corporation":false,"usgs":false,"family":"Botkin","given":"Daniel","email":"","middleInitial":"B.","affiliations":[{"id":13532,"text":"Department of Biology, University of Miami","active":true,"usgs":false}],"preferred":false,"id":656652,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":148065,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":656645,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70179183,"text":"70179183 - 2017 - Spatiotemporal patterns of duck nest density and predation risk: a multi-scale analysis of 18 years and more than 10,000 nests","interactions":[],"lastModifiedDate":"2017-07-01T17:13:33","indexId":"70179183","displayToPublicDate":"2016-12-21T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2939,"text":"Oikos","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal patterns of duck nest density and predation risk: a multi-scale analysis of 18 years and more than 10,000 nests","docAbstract":"Many avian species are behaviorally-plastic in selecting nest sites, and may shift to new locations or habitats following an unsuccessful breeding attempt. If there is predictable spatial variation in predation risk, the process of many individuals using prior experience to adaptively change nest sites may scale up to create shifting patterns of nest density at a population level. We used 18 years of waterfowl nesting data to assess whether there were areas of consistently high or low predation risk, and whether low-risk areas increased, and high-risk areas decreased in nest density the following year. We created kernel density maps of successful and unsuccessful nests in consecutive years and found no correlation in predation risk and no evidence for adaptive shifts, although nest density was correlated between years. We also examined between-year correlations in nest density and nest success at three smaller spatial scales: individual nesting fields (10–28 ha), 16-ha grid cells and 4-ha grid cells. Here, results were similar across all scales: we found no evidence for year-to-year correlation in nest success but found strong evidence that nest density was correlated between years, and areas of high nest success increased in nest density the following year. Prior research in this system has demonstrated that areas of high nest density have higher nest success, and taken together, our results suggest that ducks may adaptively select nest sites based on the local density of conspecifics, rather than the physical location of last year's nest. In unpredictable environments, current cues, such as the presence of active conspecific nests, may be especially useful in selecting nest sites. The cues birds use to select breeding locations and successfully avoid predators deserve continued attention, especially in systems of conservation concern.
","language":"English","publisher":"Wiley","doi":"10.1111/oik.03728","usgsCitation":"Ringelman, K.M., Eadie, J.M., Ackerman, J., Sih, A., Loughman, D.L., Yarris, G., Oldenburger, S.L., and McLandress, M.R., 2017, Spatiotemporal patterns of duck nest density and predation risk: a multi-scale analysis of 18 years and more than 10,000 nests: Oikos, v. 126, no. 3, p. 332-338, https://doi.org/10.1111/oik.03728.","productDescription":"7 p.","startPage":"332","endPage":"338","ipdsId":"IP-056863","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":332409,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"126","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-13","publicationStatus":"PW","scienceBaseUri":"585ba2e9e4b01224f329b96c","contributors":{"authors":[{"text":"Ringelman, Kevin M.","contributorId":95806,"corporation":false,"usgs":true,"family":"Ringelman","given":"Kevin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":656327,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eadie, John M.","contributorId":65219,"corporation":false,"usgs":false,"family":"Eadie","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":7082,"text":"University of California - Davis","active":true,"usgs":false}],"preferred":false,"id":656328,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":656329,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sih, Andrew","contributorId":177597,"corporation":false,"usgs":false,"family":"Sih","given":"Andrew","email":"","affiliations":[],"preferred":false,"id":656330,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loughman, Daniel L.","contributorId":167556,"corporation":false,"usgs":false,"family":"Loughman","given":"Daniel","email":"","middleInitial":"L.","affiliations":[{"id":24747,"text":"California Waterfowl Association","active":true,"usgs":false}],"preferred":false,"id":656331,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yarris, Gregory S.","contributorId":115361,"corporation":false,"usgs":true,"family":"Yarris","given":"Gregory S.","affiliations":[],"preferred":false,"id":656332,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Oldenburger, Shaun L.","contributorId":177598,"corporation":false,"usgs":false,"family":"Oldenburger","given":"Shaun","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":656333,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McLandress, M. Robert","contributorId":177599,"corporation":false,"usgs":false,"family":"McLandress","given":"M.","email":"","middleInitial":"Robert","affiliations":[],"preferred":false,"id":656334,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ]}