Remotely sensed differenced normalized burn ratios (DNBR) provide an index of fire severity across the footprint of a fire. We asked whether this index was useful for explaining patterns of bird occurrence within fire adapted xeric pine-oak forests of the southern Appalachian Mountains.
We evaluated the use of DNBR indices for linking ecosystem process with patterns of bird occurrence. We compared field-based and remotely sensed fire severity indices and used each to develop occupancy models for six bird species to identify patterns of bird occurrence following fire.
We identified and sampled 228 points within fires that recently burned within Great Smoky Mountains National Park. We performed avian point counts and field-assessed fire severity at each bird census point. We also used Landsat™ imagery acquired before and after each fire to quantify fire severity using DNBR. We used non-parametric methods to quantify agreement between fire severity indices, and evaluated single season occupancy models incorporating fire severity summarized at different spatial scales.
Agreement between field-derived and remotely sensed measures of fire severity was influenced by vegetation type. Although occurrence models using field-derived indices of fire severity outperformed those using DNBR, summarizing DNBR at multiple spatial scales provided additional insights into patterns of occurrence associated with different sized patches of high severity fire.
DNBR is useful for linking the effects of fire severity to patterns of bird occurrence, and informing how high severity fire shapes patterns of bird species occurrence on the landscape.
Freshwater fishes utilising seasonally available habitats within annual migratory circuits time movements out of such habitats with changing hydrology, although individual attributes of fish may also mediate the behavioural response to environmental conditions. We tagged juvenile Arctic grayling in a seasonally flowing stream on the Arctic Coastal Plain in Alaska and recorded migration timing towards overwintering habitat. We examined the relationship between individual migration date, and fork length (FL) and body condition index (BCI) for fish tagged in June, July and August in three separate models. Larger fish migrated earlier; however, only the August model suggested a significant relationship with BCI. In this model, 42% of variability in migration timing was explained by FL and BCI, and fish in better condition were predicted to migrate earlier than those in poor condition. Here, the majority (33%) of variability was captured by FL with an additional 9% attributable to BCI. We also noted strong seasonal trends in BCI reflecting overwinter mass loss and subsequent growth within the study area. These results are interpreted in the context of size and energetic state-specific risks of overwinter starvation and mortality (which can be very high in the Arctic), which may influence individuals at greater risk to extend summer foraging in a risky, yet prey rich, habitat. Our research provides further evidence that heterogeneity among individuals within a population can influence migratory behaviour and identifies potential risks to late season migrants in Arctic beaded stream habitats influenced by climate change and petroleum development.
","language":"English","publisher":"John Wiley & Sons","doi":"10.1111/eff.12199","usgsCitation":"Heim, K.C., Wipfli, M.S., Whitman, M.S., and Seitz, A.C., 2016, Body size and condition influence migration timing of juvenile Arctic grayling: Ecology of Freshwater Fish, v. 25, no. 1, p. 156-166, https://doi.org/10.1111/eff.12199.","productDescription":"11 p.","startPage":"156","endPage":"166","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059954","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":318041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Ublutuoch River","volume":"25","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-07","publicationStatus":"PW","scienceBaseUri":"56c44829e4b0946c652116c7","contributors":{"authors":[{"text":"Heim, Kurt C.","contributorId":138832,"corporation":false,"usgs":false,"family":"Heim","given":"Kurt","email":"","middleInitial":"C.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":620311,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":619794,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Whitman, Matthew S.","contributorId":67961,"corporation":false,"usgs":false,"family":"Whitman","given":"Matthew","email":"","middleInitial":"S.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":620312,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seitz, Andrew C.","contributorId":156324,"corporation":false,"usgs":true,"family":"Seitz","given":"Andrew","email":"","middleInitial":"C.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":620313,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70206069,"text":"70206069 - 2016 - Integrating geological archives and climate models for the mid-Pliocene warm period","interactions":[],"lastModifiedDate":"2019-10-22T06:42:44","indexId":"70206069","displayToPublicDate":"2016-02-16T09:19:13","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Integrating geological archives and climate models for the mid-Pliocene warm period","docAbstract":"The mid-Pliocene Warm Period (mPWP) offers an opportunity to understand a warmer-than-present world and assess the predictive ability of numerical climate models. Environmental reconstruction and climate modelling are crucial for understanding the mPWP, and the synergy of these two, often disparate, fields has proven essential in confirming features of the past and in turn building confidence in projections of the future. The continual development of methodologies to better facilitate environmental synthesis and data/model comparison is essential, with recent work demonstrating that time-specific (time-slice) syntheses represent the next logical step in exploring climate change during the mPWP and realizing its potential as a test bed for understanding future climate change.
Wildlife conservation is losing ground in the U.S. for many reasons. The net effect is declines in species and habitat. To address this trend, the wildlife conservation institution (i.e., all customs, practices, organizations and agencies, policies, and laws with respect to wildlife) must adapt to contemporary social–ecological conditions. Adaptation could be supported by clear guidelines reflecting contemporary expectations for wildlife governance. We combine elements of public trust thinking and good governance to produce a broad set of wildlife governance principles. These principles represent guidance for ecologically and socially responsible wildlife conservation. They address persistent, systemic problems and, if adopted, will bring the institution into line with modern expectations for governance of public natural resources. Implementation will require changes in values, objectives, and processes of the wildlife conservation institution. These changes may be difficult, but promise improved wildlife conservation outcomes and increased support for conservation. We introduce challenges and opportunities associated with the principles, and encourage dialogue about them among scientists, practitioners, and other leaders in U.S. wildlife conservation. The principles alone will not change the course of conservation for the better, but may be necessary for such change to occur.
","language":"English","publisher":"Blackwell Pub.","doi":"10.1111/conl.12211","usgsCitation":"Decker, D.J., Smith, C., Forstchen, A., Hare, D., Pomeranz, E., Doyle-Capitman, C., Schuler, K., and Organ, J.F., 2016, Governance principles for wildlife conservation in the 21st century: Conservation Letters, v. 9, no. 4, p. 290-295, https://doi.org/10.1111/conl.12211.","productDescription":"6 p.","startPage":"290","endPage":"295","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064488","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":471235,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/conl.12211","text":"Publisher Index Page"},{"id":318052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-27","publicationStatus":"PW","scienceBaseUri":"56c4482be4b0946c652116e1","contributors":{"authors":[{"text":"Decker, Daniel J.","contributorId":166906,"corporation":false,"usgs":false,"family":"Decker","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":620317,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Christian","contributorId":95065,"corporation":false,"usgs":true,"family":"Smith","given":"Christian","affiliations":[],"preferred":false,"id":620318,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Forstchen, Ann","contributorId":166904,"corporation":false,"usgs":false,"family":"Forstchen","given":"Ann","email":"","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":620319,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hare, Darragh","contributorId":166905,"corporation":false,"usgs":false,"family":"Hare","given":"Darragh","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":620320,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pomeranz, Emily","contributorId":166907,"corporation":false,"usgs":false,"family":"Pomeranz","given":"Emily","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":620321,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Doyle-Capitman, Catherine","contributorId":166908,"corporation":false,"usgs":false,"family":"Doyle-Capitman","given":"Catherine","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":620322,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schuler, Krysten","contributorId":53735,"corporation":false,"usgs":true,"family":"Schuler","given":"Krysten","affiliations":[],"preferred":false,"id":620323,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Organ, John F. 0000-0002-0959-0639 jorgan@usgs.gov","orcid":"https://orcid.org/0000-0002-0959-0639","contributorId":152568,"corporation":false,"usgs":true,"family":"Organ","given":"John","email":"jorgan@usgs.gov","middleInitial":"F.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":620324,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70173989,"text":"70173989 - 2016 - Chesapeake Bay recovery and factors affecting trends: Long-termmonitoring, indicators, and insights","interactions":[],"lastModifiedDate":"2017-01-12T11:29:42","indexId":"70173989","displayToPublicDate":"2016-02-16T02:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5094,"text":"Regional Studies in Marine Science","onlineIssn":"2352-4855","active":true,"publicationSubtype":{"id":10}},"title":"Chesapeake Bay recovery and factors affecting trends: Long-termmonitoring, indicators, and insights","docAbstract":"Monitoring the outcome of restoration efforts is the only way to identify the status of a recovery and the most effective management strategies. In this paper, we discuss Chesapeake Bay and watershed recovery and factors influencing water quality trends. For over 30 years, the Chesapeake Bay Program Partnership’s long-term tidal and watershed water quality monitoring networks have measured physical, chemical and biological parameters throughout the bay and its surrounding watershed underpinning an adaptive management process to drive ecosystem recovery. There are many natural and anthropogenic factors operating and interacting to affect the watershed and bay water quality recovery responses to management actions. Across habitats and indicators, the bay and its watershed continue to express a diverse spatial and temporal fabric of multiscale conditions, stressors and trends that show a range of health conditions and impairments, as well as evidence of progress and degradation. Recurrent independent reviews of the monitoring program have driven a culture of continued adaptation of the monitoring networks to reflect ever evolving management information needs. The adherence to bay and watershed-wide consistent monitoring protocols provides monitoring data supporting analyses and development of scientific syntheses that underpin indicator and model development, regulatory assessments, targeting of management actions, evaluation of management effectiveness, and directing of priorities and policies.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.rsma.2015.11.010","usgsCitation":"Tango, P.J., and Batiuk, R.A., 2016, Chesapeake Bay recovery and factors affecting trends: Long-termmonitoring, indicators, and insights: Regional Studies in Marine Science, v. 4, p. 12-20, https://doi.org/10.1016/j.rsma.2015.11.010.","productDescription":"9 p.","startPage":"12","endPage":"20","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067020","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":324139,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, Virginia","otherGeospatial":"Watershed includes New York, Pennsylvania, Virginia, West Virginia, Delaware, and Maryland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.9427490234375,\n 36.85764758564407\n ],\n [\n -76.9427490234375,\n 39.66914219401813\n ],\n [\n -75.465087890625,\n 39.66914219401813\n ],\n [\n -75.465087890625,\n 36.85764758564407\n ],\n [\n -76.9427490234375,\n 36.85764758564407\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576a6533e4b07657d1a11d2c","contributors":{"authors":[{"text":"Tango, Peter J. pjtango@usgs.gov","contributorId":4088,"corporation":false,"usgs":true,"family":"Tango","given":"Peter","email":"pjtango@usgs.gov","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640045,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Batiuk, Richard A.","contributorId":8368,"corporation":false,"usgs":true,"family":"Batiuk","given":"Richard","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":640046,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70168721,"text":"70168721 - 2016 - Nutrients in the nexus","interactions":[],"lastModifiedDate":"2018-02-21T15:09:51","indexId":"70168721","displayToPublicDate":"2016-02-15T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5058,"text":"Journal of Environmental Studies and Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Nutrients in the nexus","docAbstract":"Synthetic nitrogen (N) fertilizer has enabled modern agriculture to greatly improve human nutrition during the twentieth century, but it has also created unintended human health and environmental pollution challenges for the twenty-first century. Averaged globally, about half of the fertilizer-N applied to farms is removed with the crops, while the other half remains in the soil or is lost from farmers’ fields, resulting in water and air pollution. As human population continues to grow and food security improves in the developing world, the dual development goals of producing more nutritious food with low pollution will require both technological and socio-economic innovations in agriculture. Two case studies presented here, one in sub-Saharan Africa and the other in Midwestern United States, demonstrate how management of nutrients, water, and energy is inextricably linked in both small-scale and large-scale food production, and that science-based solutions to improve the efficiency of nutrient use can optimize food production while minimizing pollution. To achieve the needed large increases in nutrient use efficiency, however, technological developments must be accompanied by policies that recognize the complex economic and social factors affecting farmer decision-making and national policy priorities. Farmers need access to affordable nutrient supplies and support information, and the costs of improving efficiencies and avoiding pollution may need to be shared by society through innovative policies. Success will require interdisciplinary partnerships across public and private sectors, including farmers, private sector crop advisors, commodity supply chains, government agencies, university research and extension, and consumers.
","language":"English","publisher":"Springer US","doi":"10.1007/s13412-016-0364-y","usgsCitation":"Davidson, E.A., DuBose, R., Ferguson, R.B., Palm, C., Osmond, D.L., and Baron, J., 2016, Nutrients in the nexus: Journal of Environmental Studies and Sciences, v. 6, no. 1, p. 25-38, https://doi.org/10.1007/s13412-016-0364-y.","productDescription":"14 p.","startPage":"25","endPage":"38","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070397","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":471236,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s13412-016-0364-y","text":"Publisher Index Page"},{"id":323951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-15","publicationStatus":"PW","scienceBaseUri":"576913dfe4b07657d19ff1fa","contributors":{"authors":[{"text":"Davidson, Eric A.","contributorId":7983,"corporation":false,"usgs":true,"family":"Davidson","given":"Eric","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":621391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DuBose, Rachel rldubose@ua.edu","contributorId":167204,"corporation":false,"usgs":false,"family":"DuBose","given":"Rachel","email":"rldubose@ua.edu","affiliations":[{"id":37195,"text":"The University of Alabama","active":true,"usgs":false},{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":true,"id":621392,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ferguson, Richard B.","contributorId":167205,"corporation":false,"usgs":false,"family":"Ferguson","given":"Richard","email":"","middleInitial":"B.","affiliations":[{"id":12505,"text":"University of Nebraska - Lincoln","active":true,"usgs":false}],"preferred":false,"id":621393,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Palm, Cheryl","contributorId":167206,"corporation":false,"usgs":false,"family":"Palm","given":"Cheryl","email":"","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":621394,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Osmond, Deanna L.","contributorId":167207,"corporation":false,"usgs":false,"family":"Osmond","given":"Deanna","email":"","middleInitial":"L.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":621395,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baron, Jill S. 0000-0002-5902-6251 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":174080,"corporation":false,"usgs":true,"family":"Baron","given":"Jill S.","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":621390,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70169998,"text":"70169998 - 2016 - Wetland tree transpiration modified by river-floodplain connectivity","interactions":[],"lastModifiedDate":"2016-08-03T13:10:03","indexId":"70169998","displayToPublicDate":"2016-02-15T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2319,"text":"Journal of Geophysical Research G: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Wetland tree transpiration modified by river-floodplain connectivity","docAbstract":"Hydrologic connectivity provisions water and nutrient subsidies to floodplain wetlands and may be particularly important in floodplains with seasonal water deficits through its effects on soil moisture. In this study, we measured sapflow in 26 trees of two dominant floodplain forest species (Celtis laevigata and Quercus lyrata) at two hydrologically distinct sites in the lower White River floodplain in Arkansas, USA. Our objective was to investigate how connectivity-driven water table variations affected water use, an indicator of tree function. Meteorological variables (photosynthetically active radiation and vapor pressure deficit) were the dominant controls over water use at both sites; however, water table variations explained some site differences. At the wetter site, highest sapflow rates were during a late-season overbank flooding event, and no flood stress was apparent. At the drier site, sapflow decreased as the water table receded. The late-season flood pulse that resulted in flooding at the wetter site did not affect the water table at the drier site; accordingly, higher water use was not observed at the drier site. The species generally associated with wetter conditions (Q. lyrata) was more positively responsive to the flood pulse. Flood water subsidy lengthened the effective growing season, demonstrating ecological implications of hydrologic connectivity for alleviating water deficits that otherwise reduce function in this humid floodplain wetland.
","language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1002/2015JG003208","usgsCitation":"Allen, S.T., Krauss, K.W., Cochran, J.W., King, S.L., and Keim, R., 2016, Wetland tree transpiration modified by river-floodplain connectivity: Journal of Geophysical Research G: Biogeosciences, v. 121, no. 3, p. 753-766, https://doi.org/10.1002/2015JG003208.","productDescription":"14 p.","startPage":"753","endPage":"766","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068177","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471237,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jg003208","text":"Publisher Index Page"},{"id":319709,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","otherGeospatial":"Dale Bumpers White River 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This study examined the effects of two alternative land use-change development scenarios in the Puget Sound region of Washington State on natural capital stocks and ES flows. Land-use change model outputs served as inputs to five ES models developed using the Artificial Intelligence for Ecosystem Services (ARIES) platform. While natural capital stocks declined under managed (1.3–5.8%) and unmanaged (2.8–11.8%) development scenarios, ES flows increased by 18.5–56% and 23.2–55.7%, respectively. Human development of natural landscapes reduced their capacity for service provision, while simultaneously adding beneficiaries, particularly along the urban fringe. Using global and local Moran’s I, we identified three distinct patterns of change in ES due to projected landuse change. For services with location-dependent beneficiaries – open space proximity, viewsheds, and flood regulation – urbanization led to increased clustering and hot-spot intensities. ES flows were greatest in the managed land-use change scenario for open space proximity and flood regulation, and in the unmanaged land-use change scenario for viewsheds—a consequence of the differing ES flow mechanisms underpinning these services. We observed a third pattern – general declines in service provision – for carbon storage and sediment retention, where beneficiaries in our analysis were not location dependent. Contrary to past authors’ finding of ES declines under urbanization, a more nuanced analysis that maps and quantifies ES provision, beneficiaries, and flows better identifies gains and losses for specific ES beneficiaries as urban areas expand.
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P.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":621121,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mosby, David","contributorId":32063,"corporation":false,"usgs":true,"family":"Mosby","given":"David","affiliations":[],"preferred":false,"id":621122,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rattner, Barnett A. 0000-0003-3676-2843 brattner@usgs.gov","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":4142,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett","email":"brattner@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":621123,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Scheckel, Kirk G.","contributorId":167121,"corporation":false,"usgs":false,"family":"Scheckel","given":"Kirk","email":"","middleInitial":"G.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":621124,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sprague, Dan dsprague@usgs.gov","contributorId":4484,"corporation":false,"usgs":true,"family":"Sprague","given":"Dan","email":"dsprague@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":621125,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Weber, John","contributorId":78440,"corporation":false,"usgs":true,"family":"Weber","given":"John","affiliations":[],"preferred":false,"id":621126,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70168437,"text":"70168437 - 2016 - The link between volcanism and plutonism in epizonal magma systems; high-precision U–Pb zircon geochronology from the Organ Mountains caldera and batholith, New Mexico","interactions":[],"lastModifiedDate":"2016-02-12T14:00:32","indexId":"70168437","displayToPublicDate":"2016-02-12T15:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1336,"text":"Contributions to Mineralogy and Petrology","active":true,"publicationSubtype":{"id":10}},"title":"The link between volcanism and plutonism in epizonal magma systems; high-precision U–Pb zircon geochronology from the Organ Mountains caldera and batholith, New Mexico","docAbstract":"The Organ Mountains caldera and batholith expose the volcanic and epizonal plutonic record of an Eocene caldera complex. The caldera and batholith are well exposed, and extensive previous mapping and geochemical analyses have suggested a clear link between the volcanic and plutonic sections, making this an ideal location to study magmatic processes associated with caldera volcanism. Here we present high-precision thermal ionization mass spectrometry U–Pb zircon dates from throughout the caldera and batholith, and use these dates to test and improve existing petrogenetic models. The new dates indicate that Eocene volcanic and plutonic rocks in the Organ Mountains formed from ~44 to 34 Ma. The three largest caldera-related tuff units yielded weighted mean 206Pb/238U dates of 36.441 ± 0.020 Ma (Cueva Tuff), 36.259 ± 0.016 Ma (Achenback Park tuff), and 36.215 ± 0.016 Ma (Squaw Mountain tuff). An alkali feldspar granite, which is chemically similar to the erupted tuffs, yielded a synchronous weighted mean 206Pb/238U date of 36.259 ± 0.021 Ma. Weighted mean 206Pb/238U dates from the larger volume syenitic phase of the underlying Organ Needle pluton range from 36.130 ± 0.031 to 36.071 ± 0.012 Ma, and the youngest sample is 144 ± 20 to 188 ± 20 ka younger than the Squaw Mountain and Achenback Park tuffs, respectively. Younger plutonism in the batholith continued through at least 34.051 ± 0.029 Ma. We propose that the Achenback Park tuff, Squaw Mountain tuff, alkali feldspar granite and Organ Needle pluton formed from a single, long-lived magma chamber/mush zone. Early silicic magmas generated by partial melting of the lower crust rose to form an epizonal magma chamber. Underplating of the resulting mush zone led to partial melting and generation of a high-silica alkali feldspar granite cap, which erupted to form the tuffs. The deeper parts of the chamber underwent continued recharge and crystallization for 144 ± 20 ka after the final eruption. Calculated magmatic fluxes for the Organ Needle pluton range from 0.0006 to 0.0030 km3/year, in agreement with estimates from other well-studied plutons. The petrogenetic evolution proposed here may be common to many small-volume silicic volcanic systems.
","language":"English","publisher":"Springer","doi":"10.1007/s00410-015-1208-6","usgsCitation":"Rioux, M., Farmer, L., Bowring, S., Wooton, K.M., Amato, J.M., Coleman, D.S., and Verplanck, P.L., 2016, The link between volcanism and plutonism in epizonal magma systems; high-precision U–Pb zircon geochronology from the Organ Mountains caldera and batholith, New Mexico: Contributions to Mineralogy and Petrology, v. 171, no. 13, 22 p., https://doi.org/10.1007/s00410-015-1208-6.","productDescription":"22 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070760","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":471239,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1721.1/105197","text":"External Repository"},{"id":318007,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Organ Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.38174438476562,\n 31.786551553613972\n ],\n [\n -107.38174438476562,\n 32.186073305250275\n ],\n [\n -106.89147949218749,\n 32.186073305250275\n ],\n [\n -106.89147949218749,\n 31.786551553613972\n ],\n [\n -107.38174438476562,\n 31.786551553613972\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"171","issue":"13","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-21","publicationStatus":"PW","scienceBaseUri":"56bf0239e4b06458514b3133","contributors":{"authors":[{"text":"Rioux, Matthew","contributorId":166814,"corporation":false,"usgs":false,"family":"Rioux","given":"Matthew","email":"","affiliations":[{"id":24531,"text":"Earth Research Institute, University of California, Santa Barbara, CA, 93106, USA","active":true,"usgs":false}],"preferred":false,"id":620129,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farmer, Lang","contributorId":40301,"corporation":false,"usgs":true,"family":"Farmer","given":"Lang","email":"","affiliations":[],"preferred":false,"id":620130,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowring, Samuel","contributorId":149750,"corporation":false,"usgs":false,"family":"Bowring","given":"Samuel","email":"","affiliations":[{"id":17812,"text":"Dept. of Earth and Planetary Sciences, Massachusetts Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":620131,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wooton, Kathleen M.","contributorId":166815,"corporation":false,"usgs":false,"family":"Wooton","given":"Kathleen","email":"","middleInitial":"M.","affiliations":[{"id":24532,"text":"Department of Geological Sciences, University of North Carolina, Chapel Hill, NC 27599, USA","active":true,"usgs":false}],"preferred":false,"id":620132,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Amato, Jeffrey M.","contributorId":67317,"corporation":false,"usgs":true,"family":"Amato","given":"Jeffrey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":620133,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Coleman, Drew S.","contributorId":71442,"corporation":false,"usgs":true,"family":"Coleman","given":"Drew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":620134,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Verplanck, Philip L. 0000-0002-3653-6419 plv@usgs.gov","orcid":"https://orcid.org/0000-0002-3653-6419","contributorId":728,"corporation":false,"usgs":true,"family":"Verplanck","given":"Philip","email":"plv@usgs.gov","middleInitial":"L.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":620128,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70168399,"text":"70168399 - 2016 - Seasonal flows of international British Columbia-Alaska rivers: The nonlinear influence of ocean-atmosphere circulation patterns","interactions":[],"lastModifiedDate":"2016-02-15T11:25:31","indexId":"70168399","displayToPublicDate":"2016-02-12T14:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":664,"text":"Advances in Water Resources","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal flows of international British Columbia-Alaska rivers: The nonlinear influence of ocean-atmosphere circulation patterns","docAbstract":"The northern portion of the Pacific coastal temperate rainforest (PCTR) is one of the least anthropogenically modified regions on earth and remains in many respects a frontier area to science. Rivers crossing the northern PCTR, which is also an international boundary region between British Columbia, Canada and Alaska, USA, deliver large freshwater and biogeochemical fluxes to the Gulf of Alaska and establish linkages between coastal and continental ecosystems. We evaluate interannual flow variability in three transboundary PCTR watersheds in response to El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Arctic Oscillation (AO), and North Pacific Gyre Oscillation (NPGO). Historical hydroclimatic datasets from both Canada and the USA are analyzed using an up-to-date methodological suite accommodating both seasonally transient and highly nonlinear teleconnections. We find that streamflow teleconnections occur over particular seasonal windows reflecting the intersection of specific atmospheric and terrestrial hydrologic processes. The strongest signal is a snowmelt-driven flow timing shift resulting from ENSO- and PDO-associated temperature anomalies. Autumn rainfall runoff is also modulated by these climate modes, and a glacier-mediated teleconnection contributes to a late-summer ENSO-flow association. Teleconnections between AO and freshet flows reflect corresponding temperature and precipitation anomalies. A coherent NPGO signal is not clearly evident in streamflow. Linear and monotonically nonlinear teleconnections were widely identified, with less evidence for the parabolic effects that can play an important role elsewhere. The streamflow teleconnections did not vary greatly between hydrometric stations, presumably reflecting broad similarities in watershed characteristics. These results establish a regional foundation for both transboundary water management and studies of long-term hydroclimatic and environmental change.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.advwatres.2015.10.007","usgsCitation":"Fleming, S.W., Hood, E., Dalhke, H., and O’Neel, S., 2016, Seasonal flows of international British Columbia-Alaska rivers: The nonlinear influence of ocean-atmosphere circulation patterns: Advances in Water Resources, v. 87, p. 42-55, https://doi.org/10.1016/j.advwatres.2015.10.007.","productDescription":"14 p.","startPage":"42","endPage":"55","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068958","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":471241,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.escholarship.org/uc/item/7pg1n1rj","text":"External Repository"},{"id":317991,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska, British Columbia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -140,\n 55\n ],\n [\n -140,\n 60\n ],\n [\n -125,\n 60\n ],\n [\n -125,\n 55\n ],\n [\n -140,\n 55\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"87","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56bf0231e4b06458514b310f","contributors":{"authors":[{"text":"Fleming, Sean W.","contributorId":140495,"corporation":false,"usgs":false,"family":"Fleming","given":"Sean","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":619941,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hood, Eran","contributorId":106802,"corporation":false,"usgs":false,"family":"Hood","given":"Eran","affiliations":[],"preferred":false,"id":619942,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dalhke, Helen","contributorId":166741,"corporation":false,"usgs":false,"family":"Dalhke","given":"Helen","email":"","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":619943,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Neel, Shad 0000-0002-9185-0144 soneel@usgs.gov","orcid":"https://orcid.org/0000-0002-9185-0144","contributorId":166740,"corporation":false,"usgs":true,"family":"O’Neel","given":"Shad","email":"soneel@usgs.gov","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":619940,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70169052,"text":"70169052 - 2016 - Sex-specific energetics of Pacific walruses (Odobenus rosmarus divergens) during the nursing interval","interactions":[],"lastModifiedDate":"2018-06-16T17:49:13","indexId":"70169052","displayToPublicDate":"2016-02-12T14:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3075,"text":"Physiological and Biochemical Zoology","active":true,"publicationSubtype":{"id":10}},"title":"Sex-specific energetics of Pacific walruses (Odobenus rosmarus divergens) during the nursing interval","docAbstract":"Habitat use and activity patterns of Pacific walruses (Odobenus rosmarus divergens) have changed with climate-induced reductions in sea ice. Increases in the time active in water could result in negative energy balance, precluding females from sustaining lactation, which could impact population demographics. Little is known about lactation costs in walruses. We examined the energetics of 0–2-yr-old walrus calves by using Bayesian hierarchical models based on longitudinal husbandry records of growth (n = 6 females and 7 males) and caloric intake (n = 5 females and 6 males) as a proxy for maternal lactation costs. Males and females had similar growth patterns; mean mass increased from 68 kg at birth to 301 kg by 2 yr. Females had a 2,000 kcal kg−1 higher mass storage (growth) cost than males; females typically synthesize and deposit greater amounts of adipose, which is more energy dense than lean tissue. In contrast, males had higher metabolic (basal and activity) costs, ranging from 600 to 1,800 kcal d−1 greater than similarly sized females; males are typically leaner, and muscle is more metabolically active than adipose. Yet total daily energy requirements (storage plus metabolic components) were similar across sexes, summing to approximately 190,000 kcal over the first month postpartum. Based on these estimates and assuming that 8,103 kcal is recovered from 1 kg of mass loss in adult female walruses, suckling calves could deplete 23 kg of their mother’s body mass over the first month after parturition if none of the lactation costs is met through ingested prey.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Physiological and Biochemical Zoology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"University of Chicago Press","publisherLocation":"Chicago, IL","doi":"10.1086/685454","usgsCitation":"Noren, S.R., Udevitz, M.S., and Jay, C.V., 2016, Sex-specific energetics of Pacific walruses (Odobenus rosmarus divergens) during the nursing interval: Physiological and Biochemical Zoology, v. 89, no. 2, p. 93-109, https://doi.org/10.1086/685454.","productDescription":"17 p.","startPage":"93","endPage":"109","numberOfPages":"17","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063740","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":318848,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56e7e0c3e4b0f59b85d6ab05","contributors":{"authors":[{"text":"Noren, Shawn R.","contributorId":127697,"corporation":false,"usgs":false,"family":"Noren","given":"Shawn","email":"","middleInitial":"R.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":622688,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Udevitz, Mark S. 0000-0003-4659-138X mudevitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4659-138X","contributorId":3189,"corporation":false,"usgs":true,"family":"Udevitz","given":"Mark","email":"mudevitz@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":622687,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jay, Chadwick V. 0000-0002-9559-2189 cjay@usgs.gov","orcid":"https://orcid.org/0000-0002-9559-2189","contributorId":192736,"corporation":false,"usgs":true,"family":"Jay","given":"Chadwick","email":"cjay@usgs.gov","middleInitial":"V.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":622689,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70162708,"text":"tm6A54 - 2016 - T-COMP — A suite of programs for extracting transmissivity from MODFLOW models","interactions":[],"lastModifiedDate":"2022-04-26T18:48:27.528677","indexId":"tm6A54","displayToPublicDate":"2016-02-12T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-A54","title":"T-COMP — A suite of programs for extracting transmissivity from MODFLOW models","docAbstract":"Simulated transmissivities are constrained poorly by assigning permissible ranges of hydraulic conductivities from aquifer-test results to hydrogeologic units in groundwater-flow models. These wide ranges are derived from interpretations of many aquifer tests that are categorized by hydrogeologic unit. Uncertainty is added where contributing thicknesses differ between field estimates and numerical models. Wide ranges of hydraulic conductivities and discordant thicknesses result in simulated transmissivities that frequently are much greater than aquifer-test results. Multiple orders of magnitude differences frequently occur between simulated and observed transmissivities where observed transmissivities are less than 1,000 feet squared per day.
Transmissivity observations from individual aquifer tests can constrain model calibration as head and flow observations do. This approach is superior to diluting aquifer-test results into generalized ranges of hydraulic conductivities. Observed and simulated transmissivities can be compared directly with T-COMP, a suite of three FORTRAN programs. Transmissivity observations require that simulated hydraulic conductivities and thicknesses in the volume investigated by an aquifer test be extracted and integrated into a simulated transmissivity. Transmissivities of MODFLOW model cells are sampled within the volume affected by an aquifer test as defined by a well-specific, radial-flow model of each aquifer test. Sampled transmissivities of model cells are averaged within a layer and summed across layers. Accuracy of the approach was tested with hypothetical, multiple-aquifer models where specified transmissivities ranged between 250 and 20,000 feet squared per day. More than 90 percent of simulated transmissivities were within a factor of 2 of specified transmissivities.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: Groundwater in Book 6: Modeling Techniques","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6A54","collaboration":"Prepared in cooperation with the U.S. Department of Energy, National Nuclear Security Administration, Nevada Site Office, Office of Environmental Management, under Interagency Agreement, DE-NA0001654/DE-AI52-12NA30865","usgsCitation":"Halford, K.J., 2016, T-COMP — A suite of programs for extracting transmissivity from MODFLOW models: U.S. Geological Survey Techniques and Methods, book 6, chap. A54, 17 p., https://dx.doi.org/10.3133/tm6A54.","productDescription":"Report: vii, 17 p.; 5 Appendixes","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-071244","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":399691,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_103962.htm"},{"id":317977,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/06/a54/tm6a54_appendixe_Verification.zip","text":"Appendix E","description":"Appendix E","linkHelpText":"Results from T-COMP Verification"},{"id":317976,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/06/a54/tm6a54_appendixd_Regional-SiteCOMPARE.zip","text":"Appendix D","description":"Appendix D","linkHelpText":"T-COMP_Compare–A Workbook for Comparing Simulated Transmissivities Sampled with T-COMP to Specified Values"},{"id":317975,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/06/a54/tm6a54_appendixc_Codes_T-COMP.v1.00.zip","text":"Appendix C","description":"Appendix C","linkHelpText":"Source Codes for T-COMP Programs"},{"id":317974,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/06/a54/tm6a54_appendixb_T-COMP.v.1.00.zip","text":"Appendix B","description":"Appendix B","linkHelpText":"T-COMP Programs, Pre-Processing Tools, and an Example"},{"id":317973,"rank":2,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/06/a54/tm6a54_appendixa_AquiferTests+PDFs.zip","text":"Appendix A","description":"Appendix A","linkHelpText":"Aquifer Tests and Comparisons between Probability Distributions of Transmissivities from Hydraulic-Conductivity Limits and Aquifer-Test Results"},{"id":317978,"rank":7,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/06/a54/coverthb.jpg"},{"id":317972,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/a54/tm6A54.pdf","text":"Report","size":"1.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM6-A54 Report PDF"}],"country":"United States","state":"Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.6667,\n 36.6417\n ],\n [\n -115.9333,\n 36.6417\n ],\n [\n -115.9333,\n 37.3667\n ],\n [\n -116.6667,\n 37.3667\n ],\n [\n -116.6667,\n 36.6417\n ]\n ]\n ]\n }\n }\n ]\n}","publicComments":"This report is Chapter 54 of Section A: Groundwater in Book 6: Modeling Techniques.","contact":"Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Rd.
Carson City, NV 89701
http://nevada.usgs.gov/water/
In 2012, the U.S. Geological Survey completed an assessment of undiscovered, technically recoverable oil and gas resources in three source rocks of the Alaska North Slope, including the lower part of the Jurassic to Lower Cretaceous Kingak Shale. In order to identify organic shale potential in the absence of a robust geochemical dataset from the lower Kingak Shale, we introduce two quantitative parameters, $\\Delta DT_\\bar{x}$ and $\\Delta DT_z$, estimated from wireline logs from exploration wells and based in part on the commonly used delta-log resistivity ($\\Delta \\text{ }log\\text{ }R$) technique. Calculation of $\\Delta DT_\\bar{x}$ and $\\Delta DT_z$ is intended to produce objective parameters that may be proportional to the quality and volume, respectively, of potential source rocks penetrated by a well and can be used as mapping parameters to convey the spatial distribution of source-rock potential. Both the $\\Delta DT_\\bar{x}$ and $\\Delta DT_z$ mapping parameters show increased source-rock potential from north to south across the North Slope, with the largest values at the toe of clinoforms in the lower Kingak Shale. Because thermal maturity is not considered in the calculation of $\\Delta DT_\\bar{x}$ or $\\Delta DT_z$, total organic carbon values for individual wells cannot be calculated on the basis of $\\Delta DT_\\bar{x}$ or $\\Delta DT_z$ alone. Therefore, the $\\Delta DT_\\bar{x}$ and $\\Delta DT_z$ mapping parameters should be viewed as first-step reconnaissance tools for identifying source-rock potential.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165001","usgsCitation":"Rouse, W.A., and Houseknecht, D.W., 2016, Modified method for estimating petroleum source-rock potential using wireline logs, with application to the Kingak Shale, Alaska North Slope: U.S. Geological Survey Scientific Investigations Report 2016–5001, 40 p., https://dx.doi.org/10.3133/sir20165001.","productDescription":"v, 40 p.","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-061129","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":316733,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5001/coverthb.jpg"},{"id":316734,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5001/sir20165001.pdf","text":"Report","size":"5.46 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5001"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -166.81640625,\n 66.51326044311188\n ],\n [\n -166.81640625,\n 71.35706654962706\n ],\n [\n -140.80078125,\n 71.35706654962706\n ],\n [\n -140.80078125,\n 66.51326044311188\n ],\n [\n -166.81640625,\n 66.51326044311188\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Energy Resources Program
U.S. Geological Survey
12201 Sunrise Valley Drive
National Center, MS 913
Reston, VA 20192
703–648–6470
http://energy.usgs.gov/
The model presented in this report is a spreadsheet-based model using Visual Basic for Applications within Microsoft Excel (http://dx.doi.org/10.5066/F7057D0Z) prepared in cooperation with the U.S. Army Corps of Engineers and U.S. Fish and Wildlife Service. It uses the same model structure and, initially, parameters as used by Wildhaber and others (2015) for pallid sturgeon. The difference between the model structure used for this report and that used by Wildhaber and others (2015) is that variance is not partitioned. For the model of this report, all variance is applied at the iteration and time-step levels of the model. Wildhaber and others (2015) partition variance into parameter variance (uncertainty about the value of a parameter itself) applied at the iteration level and temporal variance (uncertainty caused by random environmental fluctuations with time) applied at the time-step level. They included implicit individual variance (uncertainty caused by differences between individuals) within the time-step level.
The interface developed for the model of this report is designed to allow the user the flexibility to change population model structure and parameter values and uncertainty separately for every component of the model. This flexibility makes the modeling tool potentially applicable to any fish species; however, the flexibility inherent in this modeling tool makes it possible for the user to obtain spurious outputs. The value and reliability of the model outputs are only as good as the model inputs. Using this modeling tool with improper or inaccurate parameter values, or for species for which the structure of the model is inappropriate, could lead to untenable management decisions. By facilitating fish population modeling, this modeling tool allows the user to evaluate a range of management options and implications. The goal of this modeling tool is to be a user-friendly modeling tool for developing fish population models useful to natural resource managers to inform their decision-making processes; however, as with all population models, caution is needed, and a full understanding of the limitations of a model and the veracity of user-supplied parameters should always be considered when using such model output in the management of any species.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161009","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers and U.S. Fish and Wildlife Service","usgsCitation":"Moran, E.H., Wildhaber, M.L., Green, N.S., and Albers, J.L., 2016, Visual basic, Excel-based fish population modeling tool—The pallid sturgeon example: U.S. Geological Survey Open-File Report 2016–1009, 20 p., https://dx.doi.org/10.3133/ofr20161009.","productDescription":"vi, 20 p.","numberOfPages":"29","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066994","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":316871,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1009/coverthb.jpg"},{"id":316872,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1009/ofr20161009.pdf","text":"Report","size":"17.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1009"},{"id":316917,"rank":3,"type":{"id":4,"text":"Application Site"},"url":"https://dx.doi.org/10.5066/F7057D0Z","text":"http://dx.doi.org/10.5066/F7057D0Z","description":"Microsoft Visual Basic for Applications"}],"contact":"Director, Columbia Environmental Research Center
U.S. Geological Survey
4200 New Haven Road
Columbia, MO 65201-8709
The cold and clear water conditions present below many large dams create ideal conditions for the development of economically important salmonid fisheries. Many of these tailwater fisheries have experienced declines in the abundance and condition of large trout species, yet the causes of these declines remain uncertain. Here, we develop, assess, and apply a drift-foraging bioenergetics model to identify the factors limiting rainbow trout (Oncorhynchus mykiss) growth in a large tailwater. We explored the relative importance of temperature, prey quantity, and prey size by constructing scenarios where these variables, both singly and in combination, were altered. Predicted growth matched empirical mass-at-age estimates, particularly for younger ages, demonstrating that the model accurately describes how current temperature and prey conditions interact to determine rainbow trout growth. Modeling scenarios that artificially inflated prey size and abundance demonstrate that rainbow trout growth is limited by the scarcity of large prey items and overall prey availability. For example, shifting 10% of the prey biomass to the 13 mm (large) length class, without increasing overall prey biomass, increased lifetime maximum mass of rainbow trout by 88%. Additionally, warmer temperatures resulted in lower predicted growth at current and lower levels of prey availability; however, growth was similar across all temperatures at higher levels of prey availability. Climate change will likely alter flow and temperature regimes in large rivers with corresponding changes to invertebrate prey resources used by fish. Broader application of drift-foraging bioenergetics models to build a mechanistic understanding of how changes to habitat conditions and prey resources affect growth of salmonids will benefit management of tailwater fisheries.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2015-0268","usgsCitation":"Dodrill, M.J., Yackulic, C.B., Kennedy, T.A., and Haye, J.W., 2016, Prey size and availability limits maximum size of rainbow trout in a large tailwater: insights from a drift-foraging bioenergetics model: Canadian Journal of Fisheries and Aquatic Sciences, v. 73, no. 5, p. 759-772, https://doi.org/10.1139/cjfas-2015-0268.","productDescription":"14 p.","startPage":"759","endPage":"772","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065511","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":317928,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Lees Ferry, Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.62452697753906,\n 36.82632511529419\n ],\n [\n -111.62452697753906,\n 36.86204269508728\n ],\n [\n -111.5939712524414,\n 36.86204269508728\n ],\n [\n -111.5939712524414,\n 36.82632511529419\n ],\n [\n -111.62452697753906,\n 36.82632511529419\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"73","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56bdb0b1e4b06458514aeeae","contributors":{"authors":[{"text":"Dodrill, Michael J. 0000-0002-7038-7170 mdodrill@usgs.gov","orcid":"https://orcid.org/0000-0002-7038-7170","contributorId":5468,"corporation":false,"usgs":true,"family":"Dodrill","given":"Michael","email":"mdodrill@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":619783,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":619784,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kennedy, Theodore A. tkennedy@usgs.gov","contributorId":166704,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore","email":"tkennedy@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":619785,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haye, John W","contributorId":166705,"corporation":false,"usgs":false,"family":"Haye","given":"John","email":"","middleInitial":"W","affiliations":[{"id":24493,"text":"Cawthron Institute, Nelson, New Zealand","active":true,"usgs":false}],"preferred":false,"id":619786,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168375,"text":"70168375 - 2016 - Identification of lake trout Salvelinus namaycush spawning habitat in northern Lake Huron using high-resolution satellite imagery","interactions":[],"lastModifiedDate":"2016-02-11T09:14:43","indexId":"70168375","displayToPublicDate":"2016-02-11T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Identification of lake trout Salvelinus namaycush spawning habitat in northern Lake Huron using high-resolution satellite imagery","docAbstract":"The availability and quality of spawning habitat may limit lake trout recovery in the Great Lakes, but little is known about the location and characteristics of current spawning habitats. Current methods used to identify lake trout spawning locations are time- and labor-intensive and spatially limited. Due to the observation that some lake trout spawning sites are relatively clean of overlaying algae compared to areas not used for spawning, we suspected that spawning sites could be identified using satellite imagery. Satellite imagery collected just before and after the spawning season in 2013 was used to assess whether lake trout spawning habitat could be identified based on its spectral characteristics. Results indicated that Pléiades high-resolution multispectral satellite imagery can be successfully used to estimate algal coverage of substrates and temporal changes in algal coverage, and that models developed from processed imagery can be used to identify potential lake trout spawning sites based on comparison of sites where lake trout eggs were and were not observed after spawning. Satellite imagery is a potential new tool for identifying lake trout spawning habitat at large scales in shallow nearshore areas of the Great Lakes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2015.11.011","usgsCitation":"Grimm, A.G., Brooks, C., Binder, T., Riley, S.C., Farha, S., Shuchman, R.A., and Krueger, C., 2016, Identification of lake trout Salvelinus namaycush spawning habitat in northern Lake Huron using high-resolution satellite imagery: Journal of Great Lakes Research, v. 42, no. 1, p. 127-135, https://doi.org/10.1016/j.jglr.2015.11.011.","productDescription":"9 p.","startPage":"127","endPage":"135","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069823","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":317927,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Huron","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.2486572265625,\n 45.805828539928356\n ],\n [\n -84.2486572265625,\n 46.31658418182218\n ],\n [\n -83.2379150390625,\n 46.31658418182218\n ],\n [\n -83.2379150390625,\n 45.805828539928356\n ],\n [\n -84.2486572265625,\n 45.805828539928356\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56bdb0ace4b06458514aeeaa","contributors":{"authors":[{"text":"Grimm, Amanda G.","contributorId":150482,"corporation":false,"usgs":false,"family":"Grimm","given":"Amanda","email":"","middleInitial":"G.","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":619829,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brooks, Colin N.","contributorId":103961,"corporation":false,"usgs":true,"family":"Brooks","given":"Colin N.","affiliations":[],"preferred":false,"id":619830,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Binder, Thomas R.","contributorId":21093,"corporation":false,"usgs":true,"family":"Binder","given":"Thomas R.","affiliations":[],"preferred":false,"id":619831,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Riley, Stephen C. 0000-0002-8968-8416 sriley@usgs.gov","orcid":"https://orcid.org/0000-0002-8968-8416","contributorId":2661,"corporation":false,"usgs":true,"family":"Riley","given":"Stephen","email":"sriley@usgs.gov","middleInitial":"C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":619828,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Farha, Steve A. 0000-0001-9953-6996 sfarha@usgs.gov","orcid":"https://orcid.org/0000-0001-9953-6996","contributorId":5170,"corporation":false,"usgs":true,"family":"Farha","given":"Steve A.","email":"sfarha@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":619832,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shuchman, Robert A.","contributorId":150483,"corporation":false,"usgs":false,"family":"Shuchman","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":619833,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Krueger, Charles C.","contributorId":73131,"corporation":false,"usgs":true,"family":"Krueger","given":"Charles C.","affiliations":[],"preferred":false,"id":619834,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70168342,"text":"70168342 - 2016 - Wide-area estimates of evapotranspiration by red gum (Eucalyptus camaldulensis) and associated vegetation in the Murray-Darling River Basin, Australia","interactions":[],"lastModifiedDate":"2016-04-21T10:59:08","indexId":"70168342","displayToPublicDate":"2016-02-10T13:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Wide-area estimates of evapotranspiration by red gum (Eucalyptus camaldulensis) and associated vegetation in the Murray-Darling River Basin, Australia","docAbstract":"Floodplain red gum forests (Eucalyptus camaldulensis plus associated grasses, reeds and sedges) are sites of high biodiversity in otherwise arid regions of southeastern Australia. They depend on periodic floods from rivers, but dams and diversions have reduced flood frequencies and volumes, leading to deterioration of trees and associated biota. There is a need to determine their water requirements so environmental flows can be administered to maintain or restore the forests. Their water requirements include the frequency and extent of overbank flooding, which recharges the floodplain soils with water, as well as the actual amount of water consumed in evapotranspiration (ET). We estimated the flooding requirements and ET for a 38 134 ha area of red gum forest fed by the Murrumbidgee River in Yanga National Park, New South Wales. ET was estimated by three methods: sap flux sensors placed in individual trees; a remote sensing method based on the Enhanced Vegetation Index from MODIS satellite imagery and a water balance method based on differences between river flows into and out of the forest. The methods gave comparable estimates yet covered different spatial and temporal scales. We estimated flood frequency and volume requirements by comparing Normalized Difference Vegetation Index values from Landsat images with flood history from 1995 to 2014, which included both wet periods and dry periods. ET during wet years is about 50% of potential ET but is much less in dry years because of the trees' ability to control stomatal conductance. Based on our analyses plus other studies, red gum trees at this location require environmental flows of 2000 GL yr−1 every other year, with peak flows of 20 000 ML d−1, to produce flooding sufficient to keep them in good condition. However, only about 120–200 GL yr−1 of river water is consumed in ET, with the remainder flowing out of the forest where it enters the Murray River system.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.10734","usgsCitation":"Nagler, P.L., Doody, T.M., Glenn, E.P., Jarchow, C.J., Barreto-Munoz, A., and Didan, K., 2016, Wide-area estimates of evapotranspiration by red gum (Eucalyptus camaldulensis) and associated vegetation in the Murray-Darling River Basin, Australia: Hydrological Processes, v. 30, no. 9, p. 1376-1387, https://doi.org/10.1002/hyp.10734.","productDescription":"12 p.","startPage":"1376","endPage":"1387","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064981","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":317918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","otherGeospatial":"Murray-Darling River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 143.4814453125,\n -34.73032697882121\n ],\n [\n 143.4814453125,\n -34.31394984163212\n ],\n [\n 144.35623168945312,\n -34.31394984163212\n ],\n [\n 144.35623168945312,\n -34.73032697882121\n ],\n [\n 143.4814453125,\n -34.73032697882121\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-29","publicationStatus":"PW","scienceBaseUri":"56bc5f35e4b08d617f660028","contributors":{"authors":[{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":619773,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doody, Tanya M.","contributorId":138691,"corporation":false,"usgs":false,"family":"Doody","given":"Tanya","email":"","middleInitial":"M.","affiliations":[{"id":12494,"text":"CSIRO Land and Water, Australia","active":true,"usgs":false}],"preferred":false,"id":619774,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glenn, Edward P.","contributorId":19289,"corporation":false,"usgs":true,"family":"Glenn","given":"Edward","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":619775,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jarchow, Christopher J. 0000-0002-0424-4104 cjarchow@usgs.gov","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":5813,"corporation":false,"usgs":true,"family":"Jarchow","given":"Christopher","email":"cjarchow@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":619776,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barreto-Munoz, Armando","contributorId":131000,"corporation":false,"usgs":false,"family":"Barreto-Munoz","given":"Armando","email":"","affiliations":[{"id":7204,"text":"University of Arizona, Electrical and Computer Engineering","active":true,"usgs":false}],"preferred":false,"id":619777,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Didan, Kamel","contributorId":130999,"corporation":false,"usgs":false,"family":"Didan","given":"Kamel","email":"","affiliations":[{"id":7204,"text":"University of Arizona, Electrical and Computer Engineering","active":true,"usgs":false}],"preferred":false,"id":619778,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70168332,"text":"70168332 - 2016 - Extensive dispersal of Roanoke logperch (Percina rex) inferred from genetic marker data","interactions":[],"lastModifiedDate":"2016-02-10T11:06:44","indexId":"70168332","displayToPublicDate":"2016-02-10T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Extensive dispersal of Roanoke logperch (Percina rex) inferred from genetic marker data","docAbstract":"The dispersal ecology of most stream fishes is poorly characterised, complicating conservation efforts for these species. We used microsatellite DNA marker data to characterise dispersal patterns and effective population size (Ne) for a population of Roanoke logperchPercina rex, an endangered darter (Percidae). Juveniles and candidate parents were sampled for 2 years at sites throughout the Roanoke River watershed. Dispersal was inferred via genetic assignment tests (ATs), pedigree reconstruction (PR) and estimation of lifetime dispersal distance under a genetic isolation-by-distance model. Estimates of Ne varied from 105 to 1218 individuals, depending on the estimation method. Based on PR, polygamy was frequent in parents of both sexes, with individuals spawning with an average of 2.4 mates. The sample contained 61 half-sibling pairs, but only one parent–offspring pair and no full-sib pairs, which limited our ability to discriminate natal dispersal of juveniles from breeding dispersal of their parents between spawning events. Nonetheless, all methods indicated extensive dispersal. The AT indicated unrestricted dispersal among sites ≤15 km apart, while siblings inferred by the PR were captured an average of 14 km and up to 55 km apart. Model-based estimates of median lifetime dispersal distance (6–24 km, depending on assumptions) bracketed AT and PR estimates, indicating that widely dispersed individuals do, on average, contribute to gene flow. Extensive dispersal of P. rex suggests that darters and other small benthic stream fishes may be unexpectedly mobile. Monitoring and management activities for such populations should encompass entire watersheds to fully capture population dynamics.
","language":"English","publisher":"John Wiley & Sons","doi":"10.1111/eff.12177","usgsCitation":"Roberts, J.H., Angermeier, P.L., and Hallerman, E.M., 2016, Extensive dispersal of Roanoke logperch (Percina rex) inferred from genetic marker data: Ecology of Freshwater Fish, v. 25, no. 1, p. 1-16, https://doi.org/10.1111/eff.12177.","productDescription":"16 p.","startPage":"1","endPage":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037298","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":317905,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-08-25","publicationStatus":"PW","scienceBaseUri":"56bc5f30e4b08d617f660010","contributors":{"authors":[{"text":"Roberts, James H.","contributorId":83811,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":619737,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angermeier, Paul L. 0000-0003-2864-170X biota@usgs.gov","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":166679,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":619704,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hallerman, Eric M.","contributorId":40501,"corporation":false,"usgs":true,"family":"Hallerman","given":"Eric","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":619738,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70168333,"text":"70168333 - 2016 - American woodcock migratory connectivity as indicated by hydrogen isotopes","interactions":[],"lastModifiedDate":"2016-03-31T13:08:09","indexId":"70168333","displayToPublicDate":"2016-02-10T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"American woodcock migratory connectivity as indicated by hydrogen isotopes","docAbstract":"To identify factors contributing to the long-term decline of American woodcock, a holistic understanding of range-wide population connectivity throughout the annual cycle is needed. We used band recovery data and isotopic composition of primary (P1) and secondary (S13) feathers to estimate population sources and connectivity among natal, early fall, and winter ranges of hunter-harvested juvenile American woodcock. We used P1 feathers from known-origin pre-fledged woodcock (n = 43) to create a hydrogenδ2Hf isoscape by regressing δ2Hf against expected growing-season precipitation (δ2Hp). Modeled δ2Hp values explained 79% of the variance in P1 δ2Hf values, indicating good model fit for estimating woodcock natal origins. However, a poor relationship (r2 = 0.23) between known-origin, S13 δ2Hf values, and expected δ2Hp values precluded assignment of early fall origins. We applied the δ2Hfisoscape to assign natal origins using P1 feathers from 494 hunter-harvested juvenile woodcock in the United States and Canada during 2010–2011 and 2011–2012 hunting seasons. Overall, 64% of all woodcock origins were assigned to the northernmost (>44°N) portion of both the Central and Eastern Management Regions. In the Eastern Region, assignments were more uniformly distributed along the Atlantic coast, whereas in the Central Region, most woodcock were assigned to origins within and north of the Great Lakes region. We compared our origin assignments to spatial coverage of the annual American woodcock Singing Ground Survey (SGS) and evaluated whether the survey effectively encompasses the entire breeding range. When we removed the inadequately surveyed Softwood shield Bird Conservation Region (BCR) from the northern portion of the SGS area, only 48% of juvenile woodcock originated in areas currently surveyed by the SGS. Of the individuals assigned to the northernmost portions of the breeding range, several were harvested in the southern extent of the wintering range. Based upon this latitudinal winter stratification, we examined whether woodcock employed a leapfrog migration strategy. Using δ2Hf values and band-recovery data, we found some support for this migration strategy hypothesis but not as a singular explanation. The large harvest derivation of individuals from the northernmost portions of the breeding range, and the difference in breeding distributions within each Management Region should be considered in future range-wide conservation and harvest management planning for American woodcock.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.1035","usgsCitation":"Sullins, D.S., Conway, W.C., Haukos, D.A., Hobson, K., Wassenaar, L.I., Comer, C.E., and Hung, I., 2016, American woodcock migratory connectivity as indicated by hydrogen isotopes: Journal of Wildlife Management, v. 80, no. 3, p. 510-526, https://doi.org/10.1002/jwmg.1035.","productDescription":"17 p.","startPage":"510","endPage":"526","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064387","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":317903,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"80","issue":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-12","publicationStatus":"PW","scienceBaseUri":"56bc5f29e4b08d617f65ffd5","contributors":{"authors":[{"text":"Sullins, Daniel S.","contributorId":166689,"corporation":false,"usgs":false,"family":"Sullins","given":"Daniel","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":619731,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Warren C.","contributorId":51550,"corporation":false,"usgs":true,"family":"Conway","given":"Warren","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":619732,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":619705,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hobson, Keith A.","contributorId":47306,"corporation":false,"usgs":true,"family":"Hobson","given":"Keith A.","affiliations":[],"preferred":false,"id":619733,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wassenaar, Leonard I","contributorId":150277,"corporation":false,"usgs":false,"family":"Wassenaar","given":"Leonard","email":"","middleInitial":"I","affiliations":[{"id":17954,"text":"International Atomic Energy Agency, Vienna, Austria","active":true,"usgs":false}],"preferred":false,"id":619734,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Comer, Christopher E.","contributorId":166690,"corporation":false,"usgs":false,"family":"Comer","given":"Christopher","email":"","middleInitial":"E.","affiliations":[{"id":32360,"text":"Stephen F. Austin State University, Nacogdoches, TX","active":true,"usgs":false}],"preferred":false,"id":619735,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hung, I-Kuai","contributorId":166691,"corporation":false,"usgs":false,"family":"Hung","given":"I-Kuai","email":"","affiliations":[],"preferred":false,"id":619736,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70173600,"text":"70173600 - 2016 - Predicting the risk of toxic blooms of golden alga from cell abundance and environmental covariates","interactions":[],"lastModifiedDate":"2016-06-10T14:59:45","indexId":"70173600","displayToPublicDate":"2016-02-09T09:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2622,"text":"Limnology and Oceanography: Methods","active":true,"publicationSubtype":{"id":10}},"title":"Predicting the risk of toxic blooms of golden alga from cell abundance and environmental covariates","docAbstract":"Golden alga (Prymnesium parvum) is a toxic haptophyte that has caused considerable ecological damage to marine and inland aquatic ecosystems worldwide. Studies focused primarily on laboratory cultures have indicated that toxicity is poorly correlated with the abundance of golden alga cells. This relationship, however, has not been rigorously evaluated in the field where environmental conditions are much different. The ability to predict toxicity using readily measured environmental variables and golden alga abundance would allow managers rapid assessments of ichthyotoxicity potential without laboratory bioassay confirmation, which requires additional resources to accomplish. To assess the potential utility of these relationships, several a priori models relating lethal levels of golden alga ichthyotoxicity to golden alga abundance and environmental covariates were constructed. Model parameters were estimated using archived data from four river basins in Texas and New Mexico (Colorado, Brazos, Red, Pecos). Model predictive ability was quantified using cross-validation, sensitivity, and specificity, and the relative ranking of environmental covariate models was determined by Akaike Information Criterion values and Akaike weights. Overall, abundance was a generally good predictor of ichthyotoxicity as cross validation of golden alga abundance-only models ranged from ∼ 80% to ∼ 90% (leave-one-out cross-validation). Environmental covariates improved predictions, especially the ability to predict lethally toxic events (i.e., increased sensitivity), and top-ranked environmental covariate models differed among the four basins. These associations may be useful for monitoring as well as understanding the abiotic factors that influence toxicity during blooms.
","language":"English","publisher":"Wiley","doi":"10.1002/lom3.10048","usgsCitation":"Patino, R., VanLandeghem, M.M., and Denny, S., 2016, Predicting the risk of toxic blooms of golden alga from cell abundance and environmental covariates: Limnology and Oceanography: Methods, v. 13, no. 10, p. 568-586, https://doi.org/10.1002/lom3.10048.","productDescription":"18 p.","startPage":"568","endPage":"586","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053132","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":471255,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lom3.10048","text":"Publisher Index Page"},{"id":323461,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico, Texas","otherGeospatial":"Colorado River Basin, Brazos River Basin, Red River Basin, Pecos River 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Shawn","contributorId":145738,"corporation":false,"usgs":false,"family":"Denny","given":"Shawn","email":"","affiliations":[],"preferred":false,"id":638471,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70164478,"text":"70164478 - 2016 - Aerobic biodegradation potential of endocrine disrupting chemicals in surface-water sediment at Rocky Mountains National Park, USA","interactions":[],"lastModifiedDate":"2018-08-09T12:08:22","indexId":"70164478","displayToPublicDate":"2016-02-08T09:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1529,"text":"Environmental Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Aerobic biodegradation potential of endocrine disrupting chemicals in surface-water sediment at Rocky Mountains National Park, USA","docAbstract":"Endocrine disrupting chemicals (EDC) in surface water and bed sediment threaten the structure and function of aquatic ecosystems. In natural, remote, and protected surface-water environments where contaminant releases are sporadic, contaminant biodegradation is a fundamental driver of exposure concentration, timing, duration, and, thus, EDC ecological risk. Anthropogenic contaminants, including known and suspected EDC, were detected in surface water and sediment collected from 2 streams and 2 lakes in Rocky Mountains National Park (ROMO). The potential for aerobic EDC biodegradation was assessed in collected sediments using 6 14C-radiolabeled model compounds. Aerobic microbial mineralization of natural (estrone and 17β-estradiol) and synthetic (17α-ethinylestradiol) estrogen was significant at all sites. ROMO bed sediment microbial communities also effectively degraded the xenoestrogens, bisphenol-A and 4-nonylphenol. The same sediment samples exhibited little potential for aerobic biodegradation of triclocarban, however, illustrating the need to assess a wider range of contaminant compounds. The current results support recent concerns over the widespread environmental occurrence of carbanalide antibacterials, like triclocarban and triclosan, and suggest that backcountry use of products containing these compounds should be discouraged.
","language":"English","publisher":"Wiley, Inc.","doi":"10.1002/etc.3266","usgsCitation":"Bradley, P.M., Battaglin, W.A., Iwanowicz, L., Clark, J.M., and Journey, C.A., 2016, Aerobic biodegradation potential of endocrine disrupting chemicals in surface-water sediment at Rocky Mountains National Park, USA: Environmental Chemistry, v. 35, no. 5, p. 1087-1096, https://doi.org/10.1002/etc.3266.","productDescription":"10 p.","startPage":"1087","endPage":"1096","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067297","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":316641,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Rocky Mountain National Park","volume":"35","issue":"5","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-20","publicationStatus":"PW","scienceBaseUri":"56b9bc28e4b08d617f63a7df","chorus":{"doi":"10.1002/etc.3266","url":"http://dx.doi.org/10.1002/etc.3266","publisher":"Wiley-Blackwell","authors":"Bradley Paul M., Battaglin William A., Iwanowicz Luke R., Clark Jimmy M., Journey Celeste A.","journalName":"Environmental Toxicology and Chemistry","publicationDate":"3/15/2016","auditedOn":"4/19/2016"},"contributors":{"authors":[{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":597544,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Battaglin, William A. 0000-0001-7287-7096 wbattagl@usgs.gov","orcid":"https://orcid.org/0000-0001-7287-7096","contributorId":1527,"corporation":false,"usgs":true,"family":"Battaglin","given":"William","email":"wbattagl@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":597545,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178 liwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":150383,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R. ","email":"liwanowicz@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":597546,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clark, Jimmy M. 0000-0002-3138-5738 jmclark@usgs.gov","orcid":"https://orcid.org/0000-0002-3138-5738","contributorId":4773,"corporation":false,"usgs":true,"family":"Clark","given":"Jimmy","email":"jmclark@usgs.gov","middleInitial":"M.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":597547,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Journey, Celeste A. 0000-0002-2284-5851 cjourney@usgs.gov","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":2617,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste","email":"cjourney@usgs.gov","middleInitial":"A.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":597548,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70170009,"text":"70170009 - 2016 - Evaluating a portable cylindrical bait trap to capture diamondback terrapins in salt marsh","interactions":[],"lastModifiedDate":"2018-08-09T12:04:48","indexId":"70170009","displayToPublicDate":"2016-02-06T13:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating a portable cylindrical bait trap to capture diamondback terrapins in salt marsh","docAbstract":"Diamondback terrapins (Malaclemys terrapin) are currently in decline across much of their historical range, and demographic data on a regional scale are needed to identify where their populations are at greatest risk. Because terrapins residing in salt marshes are difficult to capture, we designed a cylindrical bait trap (CBT) that could be deployed in shallow tidal waters. From 2003 to 2006, trials were conducted with CBTs in the Chesapeake Bay, Maryland (USA) to determine terrapin sex, size, and age distribution within 3 salt marsh interior habitats—open bays, tidal guts, and broken marshes—using 15 traps/habitat. Analyses based on 791 total captures with CBTs indicate that smaller terrapins, (i.e., adult male and subadult) were more prevalent within the transecting tidal guts and broken marshes, whereas the adult females were more evenly distributed among habitats, including open bays. Subadult females made up the largest percent of catch in the CBTs deployed within the 3 marsh interior habitats. During a 12-day trial in which we compared capture performance of CBTs and modified fyke nets along open shorelines during the nesting season, fyke nets outperformed CBTs by accounting for 95.2% of the 604 terrapin captures. Although the long drift leads of the fyke nets proved more effective for intercepting along-shore travel of adult female terrapins during the nesting season, CBTs provided a more effective means of live-trapping terrapins within the shallow interior marshes.
","language":"English","publisher":"Wildlife Society","publisherLocation":"Washington, D.C.","doi":"10.1002/wsb.610","usgsCitation":"Henry, P.F., Haramis, G., and Day, D.D., 2016, Evaluating a portable cylindrical bait trap to capture diamondback terrapins in salt marsh: Wildlife Society Bulletin, v. 40, no. 1, p. 160-168, https://doi.org/10.1002/wsb.610.","productDescription":"9 p.","startPage":"160","endPage":"168","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060499","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":500067,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/665f61740326408db40866d1177de199","text":"External Repository"},{"id":319727,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Glenn Martin National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.05182647705078,\n 38.017127786121506\n ],\n [\n -76.05182647705078,\n 38.012799997174575\n ],\n [\n -76.05096817016602,\n 38.00928348049952\n ],\n [\n -76.03878021240234,\n 38.00603731538592\n ],\n [\n -76.03689193725586,\n 38.00319680300937\n ],\n [\n -76.0305404663086,\n 38.00157360367438\n ],\n [\n -76.0279655456543,\n 37.99940928200236\n ],\n [\n -76.02161407470703,\n 37.995351006703814\n ],\n [\n -76.01972579956055,\n 37.99251008038448\n ],\n [\n -76.01869583129883,\n 37.990345491241776\n ],\n [\n -76.01285934448242,\n 37.990210202299636\n ],\n [\n -76.0114860534668,\n 37.9881808382286\n ],\n [\n -76.00959777832031,\n 37.98425724185128\n ],\n [\n -76.00753784179688,\n 37.98019812825676\n ],\n [\n -76.00547790527344,\n 37.97843910930459\n ],\n [\n -76.00393295288086,\n 37.97762724018384\n ],\n [\n -76.00255966186523,\n 37.973838398875515\n ],\n [\n -76.00135803222656,\n 37.97167325888967\n ],\n [\n -75.9979248046875,\n 37.96856075828048\n ],\n [\n -75.99294662475586,\n 37.96747811844137\n ],\n [\n -75.9898567199707,\n 37.970049361992054\n ],\n [\n -75.98917007446289,\n 37.97329711986601\n ],\n [\n -75.98814010620117,\n 37.9774919277906\n ],\n [\n -75.98779678344727,\n 37.98060404971996\n ],\n [\n -75.98745346069336,\n 37.982904228934125\n ],\n [\n -75.98487854003906,\n 37.98358073851119\n ],\n [\n -75.9811019897461,\n 37.98398664126368\n ],\n [\n -75.97698211669922,\n 37.98561022982037\n ],\n [\n -75.9759521484375,\n 37.990480779934416\n ],\n [\n -75.97509384155272,\n 37.99724489645483\n ],\n [\n -75.97578048706055,\n 38.00427891593761\n ],\n [\n -75.9785270690918,\n 38.00982449404459\n ],\n [\n -75.97972869873047,\n 38.01307049147015\n ],\n [\n -75.9814453125,\n 38.016451585943095\n ],\n [\n -75.98127365112305,\n 38.020373460133186\n ],\n [\n -75.98299026489256,\n 38.02348376284101\n ],\n [\n -75.98642349243164,\n 38.026458711461245\n ],\n [\n -75.99191665649414,\n 38.0282165788684\n ],\n [\n -75.99552154541016,\n 38.03105612173487\n ],\n [\n -75.99775314331055,\n 38.03457159374112\n ],\n [\n -76.00032806396484,\n 38.037410890266095\n ],\n [\n -76.0066795349121,\n 38.040385273328546\n ],\n [\n -76.01217269897461,\n 38.04173722569343\n ],\n [\n -76.01749420166016,\n 38.042142806535615\n ],\n [\n -76.02367401123047,\n 38.042142806535615\n ],\n [\n -76.02727890014648,\n 38.03984448539368\n ],\n [\n -76.03208541870117,\n 38.037546092117\n ],\n [\n -76.03414535522461,\n 38.03632926647352\n ],\n [\n -76.03860855102539,\n 38.03632926647352\n ],\n [\n -76.04324340820312,\n 38.03430117880767\n ],\n [\n -76.04633331298828,\n 38.031732187147\n ],\n [\n -76.04856491088867,\n 38.02808135979607\n ],\n [\n -76.05096817016602,\n 38.024024671574615\n ],\n [\n -76.05148315429688,\n 38.020373460133186\n ],\n [\n -76.05182647705078,\n 38.017127786121506\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-06","publicationStatus":"PW","scienceBaseUri":"56ff9be4e4b0328dcb7eaaa2","contributors":{"authors":[{"text":"Henry, Paula F. P. 0000-0002-7601-5546 phenry@usgs.gov","orcid":"https://orcid.org/0000-0002-7601-5546","contributorId":4485,"corporation":false,"usgs":true,"family":"Henry","given":"Paula","email":"phenry@usgs.gov","middleInitial":"F. P.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":625871,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haramis, G. Michael mharamis@usgs.gov","contributorId":4001,"corporation":false,"usgs":true,"family":"Haramis","given":"G. 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Distinct forms of chaparral, distinguished by differing species composition, geography, and edaphic characteristics, can cover thousands of hectares with dense vegetation or be restricted to smaller communities identified by the presence of endemic species. To maintain the biodiversity of chaparral, protective land management actions will be required to mitigate the loss due to the impacts of human population growth, development, climate change, and increased fire frequencies.
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