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This study investigated the effect of the combined use of sodium caseinate (CAS), commercial phosphatidylcholine (PC), and modified PCs on the physical and oxidative stability of 70% fish oil-in-water emulsions. Caffeic acid was covalently attached to both modified PCs (PCs originated from soy and eggs) in order to increase the antioxidant activity of PCs and investigate the advantage of bringing the antioxidant activity to the close proximity of the oil-water interface. Results showed that oxidative stability was improved when part of the PC was substituted with modified soy PC or egg PC. Emulsions containing a low concentration of modified PCs (10 wt.% of total PC) resulted in a prooxidative effect on the formation of hydroperoxides compared to emulsions with free caffeic acid. On the other hand, a decrease in the formation of volatile oxidation products was observed for emulsions containing higher levels of modified PCs (60 wt.% of total PC) compared to the emulsions with free caffeic acid added at its equivalent concentration. Increased concentrations of modified PCs provided better oxidative stability in high-fat emulsions, independent of the modified PC type. Moreover, when oxidation was initiated by producing singlet oxygen near a single oil droplet using a focused laser, fluorescence imaging showed that the oxidation did not propagate from one oil droplet to another oil droplet.

The scale of the Deepwater Horizon disaster was and is unprecedented: geographic extent, pollutant amount, countermeasure scope, and of most relevance to this Research Topic issue, range of ecotypes affected. These ecotypes include coastal/nearshore, continental shelf, deep benthic, and open-ocean domains, the last of which is the subject of this synthesis. The open-ocean ecotype comprises ~90% of the volume of the Gulf of Mexico. The exact percentage of this ecotype contaminated with toxins is unknown due to its three-dimensional nature and dynamics, but estimates suggest that the footprint encompassed most of its eastern half. Further, interactions between the water column and the deep benthos may be persistent, making this synthesis one of time (a decade) rather than event conclusion. Here we examine key elements of the open-ocean ecosystem, with emphasis on vulnerability and resilience. Of paramount importance relative to the Gulf nearshore and shelf ecotypes, pre-disaster baseline data were lacking for most of the fauna. In such cases, inferences were drawn from post-disaster assessments. Both phytoplankton and mesozooplankton vulnerabilities were quite high, but resilience appeared equally so. The phytoplankton situation was a bit more complex in that toxin-imposed reductions may have been offset by nutrient injection via high freshwater discharge in 2010. Intermediate trophic levels exhibited population-level depressions, ostensibly due to high vulnerability and low resilience. Apex predator impacts were variable. Certain large epipelagic fishes may have avoided the highest concentrations of hydrocarbons/dispersant, and thus larval abundances returned to pre-disaster levels of variability and abundance within a few years after a steep initial decline. Oceanic cetaceans, particularly shallow-diving stenellid dolphins, did not appear to avoid oiled waters and exhibited strong declines in the northern Gulf. Given that population declines of many open-ocean taxa

The scale of the Deepwater Horizon disaster was and is unprecedented: geographic extent, pollutant amount, countermeasure scope, and of most relevance to this Research Topic issue, range of ecotypes affected. These ecotypes include coastal/nearshore, continental shelf, deep benthic, and open-ocean domains, the last of which is the subject of this synthesis. The open-ocean ecotype comprises ~90% of the volume of the Gulf of Mexico. The exact percentage of this ecotype contaminated with toxins is unknown due to its three-dimensional nature and dynamics, but estimates suggest that the footprint encompassed most of its eastern half. Further, interactions between the water column and the deep benthos may be persistent, making this synthesis one of time (a decade) rather than event conclusion. Here we examine key elements of the open-ocean ecosystem, with emphasis on vulnerability and resilience. Of paramount importance relative to the Gulf nearshore and shelf ecotypes, pre-disaster baseline data were lacking for most of the fauna. In such cases, inferences were drawn from post-disaster assessments. Both phytoplankton and mesozooplankton vulnerabilities were quite high, but resilience appeared equally so. The phytoplankton situation was a bit more complex in that toxin-imposed reductions may have been offset by nutrient injection via high freshwater discharge in 2010. Intermediate trophic levels exhibited population-level depressions, ostensibly due to high vulnerability and low resilience. Apex predator impacts were variable. Certain large epipelagic fishes may have avoided the highest concentrations of hydrocarbons/dispersant, and thus larval abundances returned to pre-disaster levels of variability and abundance within a few years after a steep initial decline. Oceanic cetaceans, particularly shallow-diving stenellid dolphins, did not appear to avoid oiled waters and exhibited strong declines in the northern Gulf. Given that population declines of many open-ocean taxa

© The Author(s), 2018. This is the author's version of the work and is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Science of The Total Environment 640-641 (2018): 1148-1156, doi:10.1016/j.scitotenv.2018.05.235., Salt marshes are important coastal environments that provide key ecological services. As sea level rise has accelerated globally, concerns about the ability of salt marshes to survive submergence are increasing. Previous estimates of likely survival of salt marshes were based on ratios of sea level rise to marsh platform accretion. Here we took advantage of an unusual, long-term (1979-2015), spatially detailed comparison of changes in a representative New England salt marsh to provide an empirical estimate of habitat losses based on actual measurements. We show prominent changes in habitat mosaic within the marsh, consistent and coincident with increased submergence and coastal erosion. Model results suggest that at current rates of sea level rise, marsh platform accretion, habitat loss, and with the limitation of the widespread “coastal squeeze”, the entire ecosystem might disappear by the beginning of the next century, a fate that might be likely for many salt marshes elsewhere., Ivan Valiela and Elizabeth Elmstrom were supported by Woods Hole Sea Grant, NOAA grant no. NA14OAR4170074. Javier Lloret was supported by a Rosenthal Postdoctoral Fellowship Award from the Marine Biological Laboratory, and by a Northeast Climate Science Center Fellowship. Tynan Bowyer was supported by a Metcalf Research Fellowship of the University of Chicago. David Remsen was supported by MBL Cox and Bernstein funds., 2020-06-07

© The Author(s), 2018. This is the author's version of the work and is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Science of The Total Environment 640-641 (2018): 1148-1156, doi:10.1016/j.scitotenv.2018.05.235., Salt marshes are important coastal environments that provide key ecological services. As sea level rise has accelerated globally, concerns about the ability of salt marshes to survive submergence are increasing. Previous estimates of likely survival of salt marshes were based on ratios of sea level rise to marsh platform accretion. Here we took advantage of an unusual, long-term (1979-2015), spatially detailed comparison of changes in a representative New England salt marsh to provide an empirical estimate of habitat losses based on actual measurements. We show prominent changes in habitat mosaic within the marsh, consistent and coincident with increased submergence and coastal erosion. Model results suggest that at current rates of sea level rise, marsh platform accretion, habitat loss, and with the limitation of the widespread “coastal squeeze”, the entire ecosystem might disappear by the beginning of the next century, a fate that might be likely for many salt marshes elsewhere., Ivan Valiela and Elizabeth Elmstrom were supported by Woods Hole Sea Grant, NOAA grant no. NA14OAR4170074. Javier Lloret was supported by a Rosenthal Postdoctoral Fellowship Award from the Marine Biological Laboratory, and by a Northeast Climate Science Center Fellowship. Tynan Bowyer was supported by a Metcalf Research Fellowship of the University of Chicago. David Remsen was supported by MBL Cox and Bernstein funds., 2020-06-07

© The Author(s), 2018. This is the author's version of the work and is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Science of The Total Environment 640-641 (2018): 1148-1156, doi:10.1016/j.scitotenv.2018.05.235., Salt marshes are important coastal environments that provide key ecological services. As sea level rise has accelerated globally, concerns about the ability of salt marshes to survive submergence are increasing. Previous estimates of likely survival of salt marshes were based on ratios of sea level rise to marsh platform accretion. Here we took advantage of an unusual, long-term (1979-2015), spatially detailed comparison of changes in a representative New England salt marsh to provide an empirical estimate of habitat losses based on actual measurements. We show prominent changes in habitat mosaic within the marsh, consistent and coincident with increased submergence and coastal erosion. Model results suggest that at current rates of sea level rise, marsh platform accretion, habitat loss, and with the limitation of the widespread “coastal squeeze”, the entire ecosystem might disappear by the beginning of the next century, a fate that might be likely for many salt marshes elsewhere., Ivan Valiela and Elizabeth Elmstrom were supported by Woods Hole Sea Grant, NOAA grant no. NA14OAR4170074. Javier Lloret was supported by a Rosenthal Postdoctoral Fellowship Award from the Marine Biological Laboratory, and by a Northeast Climate Science Center Fellowship. Tynan Bowyer was supported by a Metcalf Research Fellowship of the University of Chicago. David Remsen was supported by MBL Cox and Bernstein funds., 2020-06-07

© The Author(s), 2018. This is the author's version of the work and is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Science of The Total Environment 640-641 (2018): 1148-1156, doi:10.1016/j.scitotenv.2018.05.235., Salt marshes are important coastal environments that provide key ecological services. As sea level rise has accelerated globally, concerns about the ability of salt marshes to survive submergence are increasing. Previous estimates of likely survival of salt marshes were based on ratios of sea level rise to marsh platform accretion. Here we took advantage of an unusual, long-term (1979-2015), spatially detailed comparison of changes in a representative New England salt marsh to provide an empirical estimate of habitat losses based on actual measurements. We show prominent changes in habitat mosaic within the marsh, consistent and coincident with increased submergence and coastal erosion. Model results suggest that at current rates of sea level rise, marsh platform accretion, habitat loss, and with the limitation of the widespread “coastal squeeze”, the entire ecosystem might disappear by the beginning of the next century, a fate that might be likely for many salt marshes elsewhere., Ivan Valiela and Elizabeth Elmstrom were supported by Woods Hole Sea Grant, NOAA grant no. NA14OAR4170074. Javier Lloret was supported by a Rosenthal Postdoctoral Fellowship Award from the Marine Biological Laboratory, and by a Northeast Climate Science Center Fellowship. Tynan Bowyer was supported by a Metcalf Research Fellowship of the University of Chicago. David Remsen was supported by MBL Cox and Bernstein funds., 2020-06-07

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Remote Sensing 9 (2017): 1020, doi:10.3390/rs9101020., The vulnerability of coastal systems to hazards such as storms and sea-level rise is typically characterized using a combination of ground and manned airborne systems that have limited spatial or temporal scales. Structure-from-motion (SfM) photogrammetry applied to imagery acquired by unmanned aerial systems (UAS) offers a rapid and inexpensive means to produce high-resolution topographic and visual reflectance datasets that rival existing lidar and imagery standards. Here, we use SfM to produce an elevation point cloud, an orthomosaic, and a digital elevation model (DEM) from data collected by UAS at a beach and wetland site in Massachusetts, USA. We apply existing methods to (a) determine the position of shorelines and foredunes using a feature extraction routine developed for lidar point clouds and (b) map land cover from the rasterized surfaces using a supervised classification routine. In both analyses, we experimentally vary the input datasets to understand the benefits and limitations of UAS-SfM for coastal vulnerability assessment. We find that (a) geomorphic features are extracted from the SfM point cloud with near-continuous coverage and sub-meter precision, better than was possible from a recent lidar dataset covering the same area; and (b) land cover classification is greatly improved by including topographic data with visual reflectance, but changes to resolution (when <50 cm) have little influence on the classification accuracy., This project was funded by the U.S. Geological Survey (USGS) Coastal and Marine Geology Program and the Department of the Interior Northeast Climate Science Center.

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Remote Sensing 9 (2017): 1020, doi:10.3390/rs9101020., The vulnerability of coastal systems to hazards such as storms and sea-level rise is typically characterized using a combination of ground and manned airborne systems that have limited spatial or temporal scales. Structure-from-motion (SfM) photogrammetry applied to imagery acquired by unmanned aerial systems (UAS) offers a rapid and inexpensive means to produce high-resolution topographic and visual reflectance datasets that rival existing lidar and imagery standards. Here, we use SfM to produce an elevation point cloud, an orthomosaic, and a digital elevation model (DEM) from data collected by UAS at a beach and wetland site in Massachusetts, USA. We apply existing methods to (a) determine the position of shorelines and foredunes using a feature extraction routine developed for lidar point clouds and (b) map land cover from the rasterized surfaces using a supervised classification routine. In both analyses, we experimentally vary the input datasets to understand the benefits and limitations of UAS-SfM for coastal vulnerability assessment. We find that (a) geomorphic features are extracted from the SfM point cloud with near-continuous coverage and sub-meter precision, better than was possible from a recent lidar dataset covering the same area; and (b) land cover classification is greatly improved by including topographic data with visual reflectance, but changes to resolution (when <50 cm) have little influence on the classification accuracy., This project was funded by the U.S. Geological Survey (USGS) Coastal and Marine Geology Program and the Department of the Interior Northeast Climate Science Center.

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Remote Sensing 9 (2017): 1020, doi:10.3390/rs9101020., The vulnerability of coastal systems to hazards such as storms and sea-level rise is typically characterized using a combination of ground and manned airborne systems that have limited spatial or temporal scales. Structure-from-motion (SfM) photogrammetry applied to imagery acquired by unmanned aerial systems (UAS) offers a rapid and inexpensive means to produce high-resolution topographic and visual reflectance datasets that rival existing lidar and imagery standards. Here, we use SfM to produce an elevation point cloud, an orthomosaic, and a digital elevation model (DEM) from data collected by UAS at a beach and wetland site in Massachusetts, USA. We apply existing methods to (a) determine the position of shorelines and foredunes using a feature extraction routine developed for lidar point clouds and (b) map land cover from the rasterized surfaces using a supervised classification routine. In both analyses, we experimentally vary the input datasets to understand the benefits and limitations of UAS-SfM for coastal vulnerability assessment. We find that (a) geomorphic features are extracted from the SfM point cloud with near-continuous coverage and sub-meter precision, better than was possible from a recent lidar dataset covering the same area; and (b) land cover classification is greatly improved by including topographic data with visual reflectance, but changes to resolution (when <50 cm) have little influence on the classification accuracy., This project was funded by the U.S. Geological Survey (USGS) Coastal and Marine Geology Program and the Department of the Interior Northeast Climate Science Center.

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Remote Sensing 9 (2017): 1020, doi:10.3390/rs9101020., The vulnerability of coastal systems to hazards such as storms and sea-level rise is typically characterized using a combination of ground and manned airborne systems that have limited spatial or temporal scales. Structure-from-motion (SfM) photogrammetry applied to imagery acquired by unmanned aerial systems (UAS) offers a rapid and inexpensive means to produce high-resolution topographic and visual reflectance datasets that rival existing lidar and imagery standards. Here, we use SfM to produce an elevation point cloud, an orthomosaic, and a digital elevation model (DEM) from data collected by UAS at a beach and wetland site in Massachusetts, USA. We apply existing methods to (a) determine the position of shorelines and foredunes using a feature extraction routine developed for lidar point clouds and (b) map land cover from the rasterized surfaces using a supervised classification routine. In both analyses, we experimentally vary the input datasets to understand the benefits and limitations of UAS-SfM for coastal vulnerability assessment. We find that (a) geomorphic features are extracted from the SfM point cloud with near-continuous coverage and sub-meter precision, better than was possible from a recent lidar dataset covering the same area; and (b) land cover classification is greatly improved by including topographic data with visual reflectance, but changes to resolution (when <50 cm) have little influence on the classification accuracy., This project was funded by the U.S. Geological Survey (USGS) Coastal and Marine Geology Program and the Department of the Interior Northeast Climate Science Center.

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Remote Sensing 9 (2017): 1020, doi:10.3390/rs9101020., The vulnerability of coastal systems to hazards such as storms and sea-level rise is typically characterized using a combination of ground and manned airborne systems that have limited spatial or temporal scales. Structure-from-motion (SfM) photogrammetry applied to imagery acquired by unmanned aerial systems (UAS) offers a rapid and inexpensive means to produce high-resolution topographic and visual reflectance datasets that rival existing lidar and imagery standards. Here, we use SfM to produce an elevation point cloud, an orthomosaic, and a digital elevation model (DEM) from data collected by UAS at a beach and wetland site in Massachusetts, USA. We apply existing methods to (a) determine the position of shorelines and foredunes using a feature extraction routine developed for lidar point clouds and (b) map land cover from the rasterized surfaces using a supervised classification routine. In both analyses, we experimentally vary the input datasets to understand the benefits and limitations of UAS-SfM for coastal vulnerability assessment. We find that (a) geomorphic features are extracted from the SfM point cloud with near-continuous coverage and sub-meter precision, better than was possible from a recent lidar dataset covering the same area; and (b) land cover classification is greatly improved by including topographic data with visual reflectance, but changes to resolution (when <50 cm) have little influence on the classification accuracy., This project was funded by the U.S. Geological Survey (USGS) Coastal and Marine Geology Program and the Department of the Interior Northeast Climate Science Center.

© The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in ZooKeys 550 (2016): 207–223, doi:10.3897/zookeys.550.9546., Scientific names serve to label biodiversity information: information related to species. Names, and their underlying taxonomic definitions, however, are unstable and ambiguous. This negatively impacts the utility of names as identifiers and as effective indexing tools in biological informatics where names are commonly utilized for searching, retrieving and integrating information about species. Semiotics provides a general model for describing the relationship between taxon names and taxon concepts. It distinguishes syntactics, which governs relationships among names, from semantics, which represents the relations between those labels and the taxa to which they refer. In the semiotic context, changes in semantics (i.e., taxonomic circumscription) do not consistently result in a corresponding and reflective change in syntax. Further, when syntactic changes do occur, they may be in response to semantic changes or in response to syntactic rules. This lack of consistency in the cardinal relationship between names and taxa places limits on how scientific names may be used in biological informatics in initially anchoring, and in the subsequent retrieval and integration, of relevant biodiversity information. Precision and recall are two measures of relevance. In biological taxonomy, recall is negatively impacted by changes or ambiguity in syntax while precision is negatively impacted when there are changes or ambiguity in semantics. Because changes in syntax are not correlated with changes in semantics, scientific names may be used, singly or conflated into synonymous sets, to improve recall in pattern recognition or search and retrieval. Names cannot be used, however, to improve precision. This is because changes in syntax do not uniquely identify changes in circumscription. These observations place limits on the utility of scientific names within biological informatics applications that rely on names as identifiers for taxa. Taxonomic systems and services used to organi

© The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in ZooKeys 550 (2016): 207–223, doi:10.3897/zookeys.550.9546., Scientific names serve to label biodiversity information: information related to species. Names, and their underlying taxonomic definitions, however, are unstable and ambiguous. This negatively impacts the utility of names as identifiers and as effective indexing tools in biological informatics where names are commonly utilized for searching, retrieving and integrating information about species. Semiotics provides a general model for describing the relationship between taxon names and taxon concepts. It distinguishes syntactics, which governs relationships among names, from semantics, which represents the relations between those labels and the taxa to which they refer. In the semiotic context, changes in semantics (i.e., taxonomic circumscription) do not consistently result in a corresponding and reflective change in syntax. Further, when syntactic changes do occur, they may be in response to semantic changes or in response to syntactic rules. This lack of consistency in the cardinal relationship between names and taxa places limits on how scientific names may be used in biological informatics in initially anchoring, and in the subsequent retrieval and integration, of relevant biodiversity information. Precision and recall are two measures of relevance. In biological taxonomy, recall is negatively impacted by changes or ambiguity in syntax while precision is negatively impacted when there are changes or ambiguity in semantics. Because changes in syntax are not correlated with changes in semantics, scientific names may be used, singly or conflated into synonymous sets, to improve recall in pattern recognition or search and retrieval. Names cannot be used, however, to improve precision. This is because changes in syntax do not uniquely identify changes in circumscription. These observations place limits on the utility of scientific names within biological informatics applications that rely on names as identifiers for taxa. Taxonomic systems and services used to organi

© The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in ZooKeys 550 (2016): 207–223, doi:10.3897/zookeys.550.9546., Scientific names serve to label biodiversity information: information related to species. Names, and their underlying taxonomic definitions, however, are unstable and ambiguous. This negatively impacts the utility of names as identifiers and as effective indexing tools in biological informatics where names are commonly utilized for searching, retrieving and integrating information about species. Semiotics provides a general model for describing the relationship between taxon names and taxon concepts. It distinguishes syntactics, which governs relationships among names, from semantics, which represents the relations between those labels and the taxa to which they refer. In the semiotic context, changes in semantics (i.e., taxonomic circumscription) do not consistently result in a corresponding and reflective change in syntax. Further, when syntactic changes do occur, they may be in response to semantic changes or in response to syntactic rules. This lack of consistency in the cardinal relationship between names and taxa places limits on how scientific names may be used in biological informatics in initially anchoring, and in the subsequent retrieval and integration, of relevant biodiversity information. Precision and recall are two measures of relevance. In biological taxonomy, recall is negatively impacted by changes or ambiguity in syntax while precision is negatively impacted when there are changes or ambiguity in semantics. Because changes in syntax are not correlated with changes in semantics, scientific names may be used, singly or conflated into synonymous sets, to improve recall in pattern recognition or search and retrieval. Names cannot be used, however, to improve precision. This is because changes in syntax do not uniquely identify changes in circumscription. These observations place limits on the utility of scientific names within biological informatics applications that rely on names as identifiers for taxa. Taxonomic systems and services used to organi

© The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in BMC Research Notes 7 (2014): 79, doi:10.1186/1756-0500-7-79., As biological disciplines extend into the ‘big data’ world, they will need a names-based infrastructure to index and interconnect distributed data. The infrastructure must have access to all names of all organisms if it is to manage all information. Those who compile lists of species hold different views as to the intellectual property rights that apply to the lists. This creates uncertainty that impedes the development of a much-needed infrastructure for sharing biological data in the digital world. The laws in the United States of America and European Union are consistent with the position that scientific names of organisms and their compilation in checklists, classifications or taxonomic revisions are not subject to copyright. Compilations of names, such as classifications or checklists, are not creative in the sense of copyright law. Many content providers desire credit for their efforts. A ‘blue list’ identifies elements of checklists, classifications and monographs to which intellectual property rights do not apply. To promote sharing, authors of taxonomic content, compilers, intermediaries, and aggregators should receive citable recognition for their contributions, with the greatest recognition being given to the originating authors. Mechanisms for achieving this are discussed.

© The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in BMC Research Notes 7 (2014): 79, doi:10.1186/1756-0500-7-79., As biological disciplines extend into the ‘big data’ world, they will need a names-based infrastructure to index and interconnect distributed data. The infrastructure must have access to all names of all organisms if it is to manage all information. Those who compile lists of species hold different views as to the intellectual property rights that apply to the lists. This creates uncertainty that impedes the development of a much-needed infrastructure for sharing biological data in the digital world. The laws in the United States of America and European Union are consistent with the position that scientific names of organisms and their compilation in checklists, classifications or taxonomic revisions are not subject to copyright. Compilations of names, such as classifications or checklists, are not creative in the sense of copyright law. Many content providers desire credit for their efforts. A ‘blue list’ identifies elements of checklists, classifications and monographs to which intellectual property rights do not apply. To promote sharing, authors of taxonomic content, compilers, intermediaries, and aggregators should receive citable recognition for their contributions, with the greatest recognition being given to the originating authors. Mechanisms for achieving this are discussed.

© The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in BMC Research Notes 7 (2014): 79, doi:10.1186/1756-0500-7-79., As biological disciplines extend into the ‘big data’ world, they will need a names-based infrastructure to index and interconnect distributed data. The infrastructure must have access to all names of all organisms if it is to manage all information. Those who compile lists of species hold different views as to the intellectual property rights that apply to the lists. This creates uncertainty that impedes the development of a much-needed infrastructure for sharing biological data in the digital world. The laws in the United States of America and European Union are consistent with the position that scientific names of organisms and their compilation in checklists, classifications or taxonomic revisions are not subject to copyright. Compilations of names, such as classifications or checklists, are not creative in the sense of copyright law. Many content providers desire credit for their efforts. A ‘blue list’ identifies elements of checklists, classifications and monographs to which intellectual property rights do not apply. To promote sharing, authors of taxonomic content, compilers, intermediaries, and aggregators should receive citable recognition for their contributions, with the greatest recognition being given to the originating authors. Mechanisms for achieving this are discussed.

The paper describes a pilot project to convert a conventional floristic checklist, written in a standard word processing program, into structured data in the Darwin Core Archive format. After peer-review and editorial acceptance, the final revised version of the checklist was converted into Darwin Core Archive by means of regular expressions and published thereafter in both human-readable form as traditional botanical publication and Darwin Core Archive data files. The data were published and indexed through the Global Biodiversity Information Facility (GBIF) Integrated Publishing Toolkit (IPT) and significant portions of the text of the paper were used to describe the metadata on IPT. After publication, the data will become available through the GBIF infrastructure and can be re-used on their own or collated with other data.

The concept of semantic tagging and its potential for semantic enhancements to taxonomic papers is outlined and illustrated by four exemplar papers published in the present issue of ZooKeys. The four papers were created in different ways: (i) written in Microsoft Word and submitted as non-tagged manuscript (doi: 10.3897/zookeys.50.504); (ii) generated from Scratchpads and submitted as XMLtagged manuscripts (doi: 10.3897/zookeys.50.505 and doi: 10.3897/zookeys.50.506); (iii) generated from an author’s database (doi: 10.3897/zookeys.50.485) and submitted as XML-tagged manuscript. XML tagging and semantic enhancements were implemented during the editorial process of ZooKeys using the Pensoft Mark Up Tool (PMT), specially designed for this purpose. The XML schema used was TaxPub, an extension to the Document Type Definitions (DTD) of the US National Library of Medicine Journal Archiving and Interchange Tag Suite (NLM). The following innovative methods of tagging, layout, publishing and disseminating the content were tested and implemented within the ZooKeys editorial workflow: (1) highly automated, fi ne-grained XML tagging based on TaxPub; (2) final XML output of the paper validated against the NLM DTD for archiving in PubMedCentral; (3) bibliographic metadata embedded in the PDF through XMP (Extensible Metadata Platform); (4) PDF uploaded after publication to the Biodiversity Heritage Library (BHL); (5) taxon treatments supplied through XML to Plazi; (6) semantically enhanced HTML version of the paper encompassing numerous internal and external links and linkouts, such as: (i) vizualisation of main tag elements within the text (e.g., taxon names, taxon treatments, localities, etc.); (ii) internal cross-linking between paper sections, citations, references, tables, and figures; (iii) mapping of localities listed in the whole paper or within separate taxon treatments; (v) taxon names autotagged, dynamically mapped and linked through the Pensoft Taxon Profile (PTP) to la

Author Posting. © The Author(s), 2010. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Trends in Ecology & Evolution 25 (2010): 686-691, doi:10.1016/j.tree.2010.09.004., Those who seek answers to big, broad questions about biology, especially questions emphasizing the organism (taxonomy, evolution, ecology), will soon benefit from an emerging names-based infrastructure. It will draw on the almost universal association of organism names with biological information to index and interconnect information distributed across the Internet. The result will be a virtual data commons, expanding as further data are shared, allowing biology to become more of a “big science”. Informatics devices will exploit this ‘big new biology’, revitalizing comparative biology with a broad perspective to reveal previously inaccessible trends and discontinuities, so helping us to reveal unfamiliar biological truths. Here, we review the first components of this freely available, participatory, and semantic Global Names Architecture., DJP thanks the NSF for support through the Data Conservancy project and the Alfred P. Sloan and John D. and Catherine T. MacArthur foundations for their support.

Author Posting. © The Author(s), 2010. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Trends in Ecology & Evolution 25 (2010): 686-691, doi:10.1016/j.tree.2010.09.004., Those who seek answers to big, broad questions about biology, especially questions emphasizing the organism (taxonomy, evolution, ecology), will soon benefit from an emerging names-based infrastructure. It will draw on the almost universal association of organism names with biological information to index and interconnect information distributed across the Internet. The result will be a virtual data commons, expanding as further data are shared, allowing biology to become more of a “big science”. Informatics devices will exploit this ‘big new biology’, revitalizing comparative biology with a broad perspective to reveal previously inaccessible trends and discontinuities, so helping us to reveal unfamiliar biological truths. Here, we review the first components of this freely available, participatory, and semantic Global Names Architecture., DJP thanks the NSF for support through the Data Conservancy project and the Alfred P. Sloan and John D. and Catherine T. MacArthur foundations for their support.

Author Posting. © The Author(s), 2010. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Trends in Ecology & Evolution 25 (2010): 686-691, doi:10.1016/j.tree.2010.09.004., Those who seek answers to big, broad questions about biology, especially questions emphasizing the organism (taxonomy, evolution, ecology), will soon benefit from an emerging names-based infrastructure. It will draw on the almost universal association of organism names with biological information to index and interconnect information distributed across the Internet. The result will be a virtual data commons, expanding as further data are shared, allowing biology to become more of a “big science”. Informatics devices will exploit this ‘big new biology’, revitalizing comparative biology with a broad perspective to reveal previously inaccessible trends and discontinuities, so helping us to reveal unfamiliar biological truths. Here, we review the first components of this freely available, participatory, and semantic Global Names Architecture., DJP thanks the NSF for support through the Data Conservancy project and the Alfred P. Sloan and John D. and Catherine T. MacArthur foundations for their support.

The concept of semantic tagging and its potential for semantic enhancements to taxonomic papers is outlined and illustrated by four exemplar papers published in the present issue of ZooKeys. The four papers were created in different ways: (i) written in Microsoft Word and submitted as non-tagged manuscript (doi: 10.3897/zookeys.50.504); (ii) generated from Scratchpads and submitted as XMLtagged manuscripts (doi: 10.3897/zookeys.50.505 and doi: 10.3897/zookeys.50.506); (iii) generated from an author’s database (doi: 10.3897/zookeys.50.485) and submitted as XML-tagged manuscript. XML tagging and semantic enhancements were implemented during the editorial process of ZooKeys using the Pensoft Mark Up Tool (PMT), specially designed for this purpose. The XML schema used was TaxPub, an extension to the Document Type Definitions (DTD) of the US National Library of Medicine Journal Archiving and Interchange Tag Suite (NLM). The following innovative methods of tagging, layout, publishing and disseminating the content were tested and implemented within the ZooKeys editorial workflow: (1) highly automated, fi ne-grained XML tagging based on TaxPub; (2) final XML output of the paper validated against the NLM DTD for archiving in PubMedCentral; (3) bibliographic metadata embedded in the PDF through XMP (Extensible Metadata Platform); (4) PDF uploaded after publication to the Biodiversity Heritage Library (BHL); (5) taxon treatments supplied through XML to Plazi; (6) semantically enhanced HTML version of the paper encompassing numerous internal and external links and linkouts, such as: (i) vizualisation of main tag elements within the text (e.g., taxon names, taxon treatments, localities, etc.); (ii) internal cross-linking between paper sections, citations, references, tables, and figures; (iii) mapping of localities listed in the whole paper or within separate taxon treatments; (v) taxon names autotagged, dynamically mapped and linked through the Pensoft Taxon Profile (PTP) to la

Background Increasing the quantity and quality of data is a key goal of biodiversity informatics, leading to increased fitness for use in scientific research and beyond. This goal is impeded by a legacy of geographic locality descriptions associated with biodiversity records that are often heterogeneous and not in a map-ready format. The biodiversity informatics community has developed best practices and tools that provide the means to do retrospective georeferencing (e.g., the BioGeomancer toolkit), a process that converts heterogeneous descriptions into geographic coordinates and a measurement of spatial uncertainty. Even with these methods and tools, data publishers are faced with the immensely time-consuming task of vetting georeferenced localities. Furthermore, it is likely that overlap in georeferencing effort is occurring across data publishers. Solutions are needed that help publishers more effectively georeference their records, verify their quality, and eliminate the duplication of effort across publishers. Results We have developed a tool called BioGeoBIF, which incorporates the high throughput and standardized georeferencing methods of BioGeomancer into a beginning-to-end workflow. Custodians who publish their data to the Global Biodiversity Information Facility (GBIF) can use this system to improve the quantity and quality of their georeferences. BioGeoBIF harvests records directly from the publishers' access points, georeferences the records using the BioGeomancer web-service, and makes results available to data managers for inclusion at the source. Using a web-based, password-protected, group management system for each data publisher, we leave data ownership, management, and vetting responsibilities with the managers and collaborators of each data set. We also minimize the georeferencing task, by combining and storing unique textual localities from all registered data access points, and dynamically linking that information to the password pro

Background Increasing the quantity and quality of data is a key goal of biodiversity informatics, leading to increased fitness for use in scientific research and beyond. This goal is impeded by a legacy of geographic locality descriptions associated with biodiversity records that are often heterogeneous and not in a map-ready format. The biodiversity informatics community has developed best practices and tools that provide the means to do retrospective georeferencing (e.g., the BioGeomancer toolkit), a process that converts heterogeneous descriptions into geographic coordinates and a measurement of spatial uncertainty. Even with these methods and tools, data publishers are faced with the immensely time-consuming task of vetting georeferenced localities. Furthermore, it is likely that overlap in georeferencing effort is occurring across data publishers. Solutions are needed that help publishers more effectively georeference their records, verify their quality, and eliminate the duplication of effort across publishers. Results We have developed a tool called BioGeoBIF, which incorporates the high throughput and standardized georeferencing methods of BioGeomancer into a beginning-to-end workflow. Custodians who publish their data to the Global Biodiversity Information Facility (GBIF) can use this system to improve the quantity and quality of their georeferences. BioGeoBIF harvests records directly from the publishers' access points, georeferences the records using the BioGeomancer web-service, and makes results available to data managers for inclusion at the source. Using a web-based, password-protected, group management system for each data publisher, we leave data ownership, management, and vetting responsibilities with the managers and collaborators of each data set. We also minimize the georeferencing task, by combining and storing unique textual localities from all registered data access points, and dynamically linking that information to the password pro

© 2007 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The definitive version was published in Bioinformatics 23 (2007): 1434-1436, doi:10.1093/bioinformatics/btm109., Web content syndication through standard formats such as RSS and ATOM has become an increasingly popular mechanism for publishers, news sources, and blogs to disseminate regularly updated content. These standardized syndication formats deliver content directly to the subscriber, allowing them to locally aggregate content from a variety of sources instead of having to find the information on multiple websites. The uBioRSS application is a "taxonomically intelligent" service customized for the biological sciences. It aggregates syndicated content from academic publishers and science news feeds, then uses a taxonomic name entity recognition algorithm to identify and index taxonomic names within those data streams. The resulting name index is cross-referenced to current global taxonomic datasets to provide context for browsing the publications by taxonomic group. This process, called taxonomic indexing, draws upon services developed specifically for biological sciences, collectively referred to as "taxonomic intelligence." Such value-added enhancements can provide biologists with accelerated and improved access to current biological content.

© 2007 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The definitive version was published in Bioinformatics 23 (2007): 1434-1436, doi:10.1093/bioinformatics/btm109., Web content syndication through standard formats such as RSS and ATOM has become an increasingly popular mechanism for publishers, news sources, and blogs to disseminate regularly updated content. These standardized syndication formats deliver content directly to the subscriber, allowing them to locally aggregate content from a variety of sources instead of having to find the information on multiple websites. The uBioRSS application is a "taxonomically intelligent" service customized for the biological sciences. It aggregates syndicated content from academic publishers and science news feeds, then uses a taxonomic name entity recognition algorithm to identify and index taxonomic names within those data streams. The resulting name index is cross-referenced to current global taxonomic datasets to provide context for browsing the publications by taxonomic group. This process, called taxonomic indexing, draws upon services developed specifically for biological sciences, collectively referred to as "taxonomic intelligence." Such value-added enhancements can provide biologists with accelerated and improved access to current biological content.

© 2007 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The definitive version was published in Bioinformatics 23 (2007): 1434-1436, doi:10.1093/bioinformatics/btm109., Web content syndication through standard formats such as RSS and ATOM has become an increasingly popular mechanism for publishers, news sources, and blogs to disseminate regularly updated content. These standardized syndication formats deliver content directly to the subscriber, allowing them to locally aggregate content from a variety of sources instead of having to find the information on multiple websites. The uBioRSS application is a "taxonomically intelligent" service customized for the biological sciences. It aggregates syndicated content from academic publishers and science news feeds, then uses a taxonomic name entity recognition algorithm to identify and index taxonomic names within those data streams. The resulting name index is cross-referenced to current global taxonomic datasets to provide context for browsing the publications by taxonomic group. This process, called taxonomic indexing, draws upon services developed specifically for biological sciences, collectively referred to as "taxonomic intelligence." Such value-added enhancements can provide biologists with accelerated and improved access to current biological content.

© 2007 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The definitive version was published in Bioinformatics 23 (2007): 1434-1436, doi:10.1093/bioinformatics/btm109., Web content syndication through standard formats such as RSS and ATOM has become an increasingly popular mechanism for publishers, news sources, and blogs to disseminate regularly updated content. These standardized syndication formats deliver content directly to the subscriber, allowing them to locally aggregate content from a variety of sources instead of having to find the information on multiple websites. The uBioRSS application is a "taxonomically intelligent" service customized for the biological sciences. It aggregates syndicated content from academic publishers and science news feeds, then uses a taxonomic name entity recognition algorithm to identify and index taxonomic names within those data streams. The resulting name index is cross-referenced to current global taxonomic datasets to provide context for browsing the publications by taxonomic group. This process, called taxonomic indexing, draws upon services developed specifically for biological sciences, collectively referred to as "taxonomic intelligence." Such value-added enhancements can provide biologists with accelerated and improved access to current biological content.

© 2007 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The definitive version was published in Bioinformatics 23 (2007): 1434-1436, doi:10.1093/bioinformatics/btm109., Web content syndication through standard formats such as RSS and ATOM has become an increasingly popular mechanism for publishers, news sources, and blogs to disseminate regularly updated content. These standardized syndication formats deliver content directly to the subscriber, allowing them to locally aggregate content from a variety of sources instead of having to find the information on multiple websites. The uBioRSS application is a "taxonomically intelligent" service customized for the biological sciences. It aggregates syndicated content from academic publishers and science news feeds, then uses a taxonomic name entity recognition algorithm to identify and index taxonomic names within those data streams. The resulting name index is cross-referenced to current global taxonomic datasets to provide context for browsing the publications by taxonomic group. This process, called taxonomic indexing, draws upon services developed specifically for biological sciences, collectively referred to as "taxonomic intelligence." Such value-added enhancements can provide biologists with accelerated and improved access to current biological content.

Author Posting. © Society of Systematic Biologists, 2006. This article is posted here by permission of Society of Systematic Biologists for personal use, not for redistribution. The definitive version was published in Systematic Biology 55 (2006): 367-373, doi: 10.1080/10635150500541680., Taxonomic indexing refers to a new array of taxonomically intelligent network services that use nomenclatural principles and elements of expert taxonomic knowledge to manage information about organisms. Taxonomic indexing was introduced to help manage the increasing amounts of digital information about biology. It has been designed to form a near basal layer in a layered cyberinfrastructure that deals with biological information. Taxonomic Indexing accommodates the special problems of using names of organisms to index biological material. It links alternative names for the same entity (reconciliation), and distinguishes between uses of the same name for different entities (disambiguation), and names are placed within an indefinite number of hierarchical schemes. In order to access all information on all organisms, Taxonomic indexing must be able to call on a registry of all names in all forms for all organisms. NameBank has been developed to meet that need. Taxonomic indexing is an area of informatics that overlaps with taxonomy, is dependent on the expert input of taxonomists, and reveals the relevance of the discipline to a wide audience.

Author Posting. © Marine Biological Laboratory , 2006. This article is posted here by permission of Marine Biological Laboratory for personal use, not for redistribution. The definitive version was published in Biological Bulletin 210 (2006): 18-24., Given the current trends, it seems inevitable that all biological documents will eventually exist in a digital format and be distributed across the internet. New network services and tools need to be developed to increase retrieval rates for documents and to refine data recovery. Biological data have traditionally been well managed using taxonomic principles. As part of a larger initiative to build an array of names-based network services that emulate taxonomic principles for managing biological information, we undertook the digitization of a major taxonomic reference text, Nomenclator Zoologicus. The process involved replicating the text to a high level of fidelity, parsing the content for inclusion within a database, developing tools to enable expert input into the product, and integrating the metadata and factual content within taxonomic network services. The result is a high-quality and freely available web application (http://uio.mbl.edu/NomenclatorZoologicus/) capable of being exploited in an array of biological informatics services., This work was supported with funding from the Andrew W. Mellon Foundation and GBIF.

Author Posting. © Society of Systematic Biologists, 2006. This article is posted here by permission of Society of Systematic Biologists for personal use, not for redistribution. The definitive version was published in Systematic Biology 55 (2006): 367-373, doi: 10.1080/10635150500541680., Taxonomic indexing refers to a new array of taxonomically intelligent network services that use nomenclatural principles and elements of expert taxonomic knowledge to manage information about organisms. Taxonomic indexing was introduced to help manage the increasing amounts of digital information about biology. It has been designed to form a near basal layer in a layered cyberinfrastructure that deals with biological information. Taxonomic Indexing accommodates the special problems of using names of organisms to index biological material. It links alternative names for the same entity (reconciliation), and distinguishes between uses of the same name for different entities (disambiguation), and names are placed within an indefinite number of hierarchical schemes. In order to access all information on all organisms, Taxonomic indexing must be able to call on a registry of all names in all forms for all organisms. NameBank has been developed to meet that need. Taxonomic indexing is an area of informatics that overlaps with taxonomy, is dependent on the expert input of taxonomists, and reveals the relevance of the discipline to a wide audience.

Author Posting. © Society of Systematic Biologists, 2006. This article is posted here by permission of Society of Systematic Biologists for personal use, not for redistribution. The definitive version was published in Systematic Biology 55 (2006): 367-373, doi: 10.1080/10635150500541680., Taxonomic indexing refers to a new array of taxonomically intelligent network services that use nomenclatural principles and elements of expert taxonomic knowledge to manage information about organisms. Taxonomic indexing was introduced to help manage the increasing amounts of digital information about biology. It has been designed to form a near basal layer in a layered cyberinfrastructure that deals with biological information. Taxonomic Indexing accommodates the special problems of using names of organisms to index biological material. It links alternative names for the same entity (reconciliation), and distinguishes between uses of the same name for different entities (disambiguation), and names are placed within an indefinite number of hierarchical schemes. In order to access all information on all organisms, Taxonomic indexing must be able to call on a registry of all names in all forms for all organisms. NameBank has been developed to meet that need. Taxonomic indexing is an area of informatics that overlaps with taxonomy, is dependent on the expert input of taxonomists, and reveals the relevance of the discipline to a wide audience.

Author Posting. © Marine Biological Laboratory , 2006. This article is posted here by permission of Marine Biological Laboratory for personal use, not for redistribution. The definitive version was published in Biological Bulletin 210 (2006): 18-24., Given the current trends, it seems inevitable that all biological documents will eventually exist in a digital format and be distributed across the internet. New network services and tools need to be developed to increase retrieval rates for documents and to refine data recovery. Biological data have traditionally been well managed using taxonomic principles. As part of a larger initiative to build an array of names-based network services that emulate taxonomic principles for managing biological information, we undertook the digitization of a major taxonomic reference text, Nomenclator Zoologicus. The process involved replicating the text to a high level of fidelity, parsing the content for inclusion within a database, developing tools to enable expert input into the product, and integrating the metadata and factual content within taxonomic network services. The result is a high-quality and freely available web application (http://uio.mbl.edu/NomenclatorZoologicus/) capable of being exploited in an array of biological informatics services., This work was supported with funding from the Andrew W. Mellon Foundation and GBIF.

Author Posting. © Society of Systematic Biologists, 2006. This article is posted here by permission of Society of Systematic Biologists for personal use, not for redistribution. The definitive version was published in Systematic Biology 55 (2006): 367-373, doi: 10.1080/10635150500541680., Taxonomic indexing refers to a new array of taxonomically intelligent network services that use nomenclatural principles and elements of expert taxonomic knowledge to manage information about organisms. Taxonomic indexing was introduced to help manage the increasing amounts of digital information about biology. It has been designed to form a near basal layer in a layered cyberinfrastructure that deals with biological information. Taxonomic Indexing accommodates the special problems of using names of organisms to index biological material. It links alternative names for the same entity (reconciliation), and distinguishes between uses of the same name for different entities (disambiguation), and names are placed within an indefinite number of hierarchical schemes. In order to access all information on all organisms, Taxonomic indexing must be able to call on a registry of all names in all forms for all organisms. NameBank has been developed to meet that need. Taxonomic indexing is an area of informatics that overlaps with taxonomy, is dependent on the expert input of taxonomists, and reveals the relevance of the discipline to a wide audience.

Author Posting. © Society of Systematic Biologists, 2006. This article is posted here by permission of Society of Systematic Biologists for personal use, not for redistribution. The definitive version was published in Systematic Biology 55 (2006): 367-373, doi: 10.1080/10635150500541680., Taxonomic indexing refers to a new array of taxonomically intelligent network services that use nomenclatural principles and elements of expert taxonomic knowledge to manage information about organisms. Taxonomic indexing was introduced to help manage the increasing amounts of digital information about biology. It has been designed to form a near basal layer in a layered cyberinfrastructure that deals with biological information. Taxonomic Indexing accommodates the special problems of using names of organisms to index biological material. It links alternative names for the same entity (reconciliation), and distinguishes between uses of the same name for different entities (disambiguation), and names are placed within an indefinite number of hierarchical schemes. In order to access all information on all organisms, Taxonomic indexing must be able to call on a registry of all names in all forms for all organisms. NameBank has been developed to meet that need. Taxonomic indexing is an area of informatics that overlaps with taxonomy, is dependent on the expert input of taxonomists, and reveals the relevance of the discipline to a wide audience.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Material Science and Engineering, 1985., MICROFICHE COPY AVAILABLE IN ARCHIVES AND SCIENCE., Vita., Bibliography: leaves 208-229., by Frank Remsen Field III., Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Material Science and Engineering, 1985., MICROFICHE COPY AVAILABLE IN ARCHIVES AND SCIENCE., Vita., Bibliography: leaves 208-229., by Frank Remsen Field III., Ph.D.

Type I and II methanotrophic bacteria can be cleanly separated by using Percoll buoyant density gradients. This simple and inexpensive method can be used to screen new isolates rapidly for preliminary classification. In addition, Percoll gradients can also be used to enhance standard enrichment techniques for methanotrophs from natural water samples.

Type I and II methanotrophic bacteria can be cleanly separated by using Percoll buoyant density gradients. This simple and inexpensive method can be used to screen new isolates rapidly for preliminary classification. In addition, Percoll gradients can also be used to enhance standard enrichment techniques for methanotrophs from natural water samples.

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