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At least 901 records · Page 50Linked to original sources
USGS1998

Occurrence of pesticides in shallow groundwater of the United States: initial results from the National Water-Quality Assessment program

The first phase of intensive data collection for the National Water-Quality Assessment (NAWQA) was completed during 1993−1995 in 20 major hydrologic basins of the United States. Groundwater land-use studies, designed to sample recently recharged groundwater (generally within 10 years) beneath specific land-use and hydrogeologic settings, are a major component of the groundwater quality as sessment for NAWQA. Pesticide results from the 41 land-use studies conducted during 1993−1995 indicate that pesticides were commonly detected in shallow groundwater, having been found at 54.4% of the 1034 sites sampled in agricultural and urban settings across the United States. Pesticide concentrations were generally low, with over 95% of the detections at concentrations less than 1 μg/L. Of the 46 pesticide compounds examined, 39 were detected. The compounds detected most frequently were atrazine (38.2%), deethylatrazine (34.2%), simazine (18.0%), metolachlor (14.6%), and prometon (13.9%). Statistically significant relations were observed between frequencies of detection and the use, mobility, and persistence of these compounds. Pesticides were commonly detected in both agricultural (56.4%; 813 sites) and urban (46.6%; 221 sites) settings. Frequent detections of pesticides in urban areas indicate that, as is the case with agricultural pesticide use in agricultural areas, urban and suburban pesticide use significantly contribute to pesticide occurrence in shallow groundwater. Although pesticides were detected in groundwater sampled in urban areas and all nine of the agricultural land-use categories examined, significant variations in occurrence were observed among these categories. Maximum contaminant levels (MCLs) established by the U.S. Environmental Protection Agency for drinking water were exceeded for only one pesticide (atrazine, 3 μg/L) at a single location. However, MCLs have been established for only 25 of the 46 pesticide compounds examined, do not cover pesticide degradates, and, at present, do not take into account additive or synergistic effects of combinations of pesticide compounds or potential effects on nearby aquatic ecosystems.

Environmental Science & Technology↗
USGS2015

Characterization of the putatively introduced red alga Acrochaetium secundatum (Acrochaetiales, Rhodophyta) growing epizoically on the pelage of southern sea otters ( Enhydra lutris nereis )

Ecological associations between epibionts (organisms that live on the surface of another living organism) and vertebrates have been documented in both marine and terrestrial environments, and may be opportunistic, commensal, or symbiotic (Lewin et al. 1981, Holmes 1985, Allen et al. 1993, Bledsoe et al. 2006, Pfaller et al. 2008, Suutari et al. 2010). Although epibiont proliferation is frequently reported on slow-moving, sparsely haired organisms such as manatees and sloths, reports from densely furred, highly mobile mammals are much less common. There are reports of epizoic algae for several species of pinnipeds (Kenyon and Rice 1959, Scheffer 1962, Baldridge 1977, Allen et al. 1993), which rely to varying degrees on both pelage and blubber for thermoregulation, but the phenomenon has not been widely described. Scheffer (1962) noted that red algae was fairly common on the pelage of northern fur seals (Callorhinus ursinus), pinnipeds for which fur likely makes a comparatively high contribution to thermoregulation (Donohue et al. 2000). For species with pelage that plays a critical role of thermal insulation, it seems implausible that an epibiont would persist on healthy individuals that devote significant energy resources toward grooming and actively maintaining their coat. Biological characteristics of epibiont settlement and attachment, and physiological requirements of epizoic species play key roles in their successful colonization and potential host impacts. To investigate this relationship, we explore a novel discovery of an epizoic alga from southern sea otters, including describing algal development on sea otter hair and molecular identification of the algae.

Marine Mammal Science↗
USGS2020

Proposed species extinction target fails to capture the diversity in biodiversity

We believe the 20 species extinction metric is a retrograde proposal, which does not adequately consider the lessons learnt from the 2020 Aichi Biodiversity Targets. Whilst having a single simple overarching target is appealing, we believe a positively-framed target will garner support, rather than one that aims to, at best, limit negative impacts. The Convention on Biological Diversity’s zero draft states that future targets should be clear, consistent and SMART (Specific, Measurable, Achievable, Relevant and Timely). Extinction is problematic as a standalone target: it can take decades to demonstrate and therefore cannot be measured over a relevant time-period, and is biased towards terrestrial vertebrates. The proposal is not scalable across nations, nor is it equitable,one of the key aspirations of the zero draft. Many industrialised countries are unlikely to find the targets challenging because their most vulnerable species have largely gone extinct; tropical species-rich countries, where much biodiversity is yet to be catalogued, will find the targets demanding and unachievable in the short- or medium-term. Despite the authors’ statement to the contrary, species extinction is not necessarily relevant to other aspects of biodiversity, such as ecosystems or genetic diversity. A species may be reduced to a small fraction of its former extent without going extinct. However, its ecosystem will be altered, and its contribution to ecosystem functions and the socio-economic benefits it provided will be lost. The focus on extinction is not novel and has not been particularly successful to date, as demonstrated by the decline of emblematic species such as rhinoceroses. Alternatively, composite indicators can be used to capture biodiversity’s three fundamental components (ecosystems, species and genetic diversity). In conclusion, we cannot support a target that fails to represent the diversity in biodiversity and, in the authors’ words, could be met despite “wholesale and damaging changes to life on Earth.”

Science↗
USGS2012

Paenibacillus thiaminolyticus is not the cause of thiamine deficiency impeding lake trout ( Salvelinus namaycush ) recruitment in the Great Lakes

Thiamine (vitamin B 1 ) deficiency is a global concern affecting wildlife, livestock, and humans. In Great Lakes salmonines, thiamine deficiency causes embryo mortality and is an impediment to restoration of native lake trout ( Salvelinus namaycush ) stocks. Thiamine deficiency in fish may result from a diet of prey with high levels of thiaminase I. The discoveries that the bacterial species Paenibacillus thiaminolyticus produces thiaminase I, is found in viscera of thiaminase-containing prey fish, and causes mortality when fed to lake trout in the laboratory provided circumstantial evidence implicating P. thiaminolyticus . This study quantified the contribution of P. thiaminolyticus to the total thiaminase I activity in multiple trophic levels of Great Lakes food webs. Unexpectedly, no relationship between thiaminase activity and either the amount of P. thiaminolyticus thiaminase I protein or the abundance of P. thiaminolyticus cells was found. These results demonstrate that P. thiaminolyticus is not the primary source of thiaminase activity affecting Great Lakes salmonines and calls into question the long-standing assumption that P. thiaminolyticus is the source of thiaminase in other wild and domestic animals.

Great Lakes↗
USGS1992

Map showing sediment isopachs in the deep-sea basins of the Pacific continental margin, Point Conception to Point Loma

The U.S. Geological Survey conducted a series of cruises, EEZSCAN 84 (EEZ-SCAN 84 Scientific Staff, 1986), to collect reconnaissance data on the newly proclaimed Exclusive Economic Zone (EEZ), the area out to 200 nautical miles from the coastline of the United States. The cruises systematically surveyed the entire conterminous United States west coast EEZ using the Geological Long-Range Inclined Asdic (GLORIA) side-scan sonar, a 160-in 3 airgun seismic-reflection profiler, a 3.5-kHz high-resolution seismic-reflection profiler, a 10-kHz echo sounder, and a proton-precession magnetometer. The nominal trackline spacing throughout the survey was 30 km. Derivative maps of sediment thickness (I-2089-A, I-2090-A, I-2091-A) and depth to basement (I-2089-B, I-2090-B, I-2091-B) in the basins of the west coast EEZ were compiled from both the sonar-image dala and the deep-penetration seismic data obtained on these cruises. Only EEZ-SCAN 84 data were used for the map compilations because available data from other cruises in this region are sparsely located, have poor navigational control, or were obtained with seismic systems that were not powerful enough to resolve oceanic basement. For this map series, sediment thickness and depth to basement were determined only in the deep-ocean basin regions because the seismic system used on the EEZ-SCAN 84 cruises could not resolve oceanic basement beneath the thick sediments of the continental slope. All the data used to compile the maps are presented in the "Atlas of the Exclusive Economic Zone, Western Conterminous United States" (EEZ-SCAN 84 Scientific Staff, 1986). Basement Outcrops GLORIA imagery was used to locate areas of basement outcrop throughout the region. Where possible, sediment thickness on and immediately adjacent to basement outcrops was measured from seismic data. Where there was no bathymetric or seismic control, a seamount peak was assumed to have no sediment cover. A pattern is used on the map to indicate all basement outcrops. Data Reduction Acoustic basement in the basins, invariably oceanic Layer 2, was observed on all of the seismic records. One-way traveltime was measured from the sea floor to acoustic basement. Because the trackline spacing of about 30 km is relatively large compared to the data density along track, we chose to measure the sediment thickness every 0.5 hour or at an interval of approximately 7.5 km. Water depth was measured with a 10-kHz profiler. Depth to basement was calculated using the sea surface as the zero datum and adding the corrected water depth (Carter, 1980) to the sediment thickness. Acoustic travel times were converted to depths by first calculating a regression equation from the interval velocity versus depth data of Connard and others (1984). Their data base comprises a compilation of all available Deep Sea Drilling Project data plus wide-angle refraction data, which were collected in Cascadia Basin west of Oregon and represents the best data set available for the United States west coast EEZ. The regression equation was integrated to determine sediment thickness as a function of one-way traveltime . The resulting equation is z = 1400t + 0 .5t 2 where z is sediment thickness in meters, and t is one-way traveltime in seconds. Sediment thicknesses calculated using this equation were compared to values calculated from the general equation of Carlson and others (1986). Values for sediment thickness calculated by the two equations differed by no greater than 10 percent throughout the range of travel times. Bathymetry The bathymetry is from Chase and others (1981). The bathymetric data were compiled from a variety of sources, and data quality is inconsistent. Because of differences in navigational precision and density of coverage, the bathymetric contours of a feature may be at a different location than the corresponding isopleths derived from the EEZ-SCAN 84 data, or a feature may not be indicated on the bathymetry at all. These situations occur because either the feature is poorly located in the bathymetric data set or, especially in the outer EEZ, the bathymetric data are too sparse to have defined the existence of a feature. Acknowledgments Topographic digital data bases were corrected and verified by Christina Lief. Gerald Evenden developed the computer software system MAPGEN, used to compose this map. Reviews, suggestions, and technical contributions from Edward C. Escowitz and Florence Wong and advice about cartographic design from Will Stettner substantially improved the quality of this map. References Cited Carlson, R.L., Gangi, A.F., and Snow, K.R., 1986, Empirical reflection-traveltime/ depth and velocity/depth functions for the deep-sea sediment column: Journal of Geophysical Research, v. 91, no. B8, p. 8249-8266. Carter, D.J.T., 1980, Echo-sounding correction tables: Taunton, United Kingdom, Hydrographic Department, Ministry of Defence, 150 p. Chase, T.E., Wilde, Pat, Normark, W.R, Miller, C.P., Seekins, B.A., and Young, J.D., 1981, Offshore topography of the Western United States between 32° and 49° North latitudes: U.S. Geological Survey Open-File Report 81-443, scale 1:864,518 at 38° latitude, 2 sheets. Connard, G., Couch, R., Keeling , K., Roy, J., and Troseth, S., 1984, Abyssal plain and continental net-objective sedimentary thicknesses, in Kulm, L.D., and others, eds., Western North America continental margin and adjacent ocean floor off Oregon and Washington, Atlas 1 of Regional Atlas Series, Ocean Margin Drilling Program: Woods Hole, Mass., Marine Science International, sheet 7. EEZ-SCAN 84 Scientific Staff, 1986, Atlas of the Exclusive Economic Zone, Western Conterminous United States: U.S. Geological Survey Miscellaneous Investigations Series I-1792, scale 1:500,000, 152 p. index map for I-2089-A See Also "U.S. Pacific West Coast Field Activities" (Paskevich and others, 2011; http://pubs.usgs.gov/of/2010/1332/htmldocs/pc/pc_overview.html). Paskevich, V.F., Wong, F.L., O?Malley, J.J., Stevenson, A.J., and Gutmacher, C.E., 2011, GLORIA sidescan-sonar imagery for parts of the U.S. Exclusive Economic Zone and adjacent areas: U.S. Geological Survey Open-File Report 2010?1332, available at http://pubs.usgs.gov/of/2010/1332/.

IMAP↗
USGS1992

Map showing depth to basement in the deep-sea basins of the Pacific continental margin, Point Conception to Point Loma

The U.S. Geological Survey conducted a series of cruises, EEZSCAN 84 (EEZ-SCAN 84 Scientific Staff, 1986), to collect reconnaissance data on the newly proclaimed Exclusive Economic Zone (EEZ), the area out to 200 nautical miles from the coastline of the United States. The cruises systematically surveyed the entire conterminous United States west coast EEZ using the Geological Long-Range Inclined Asdic (GLORIA) side-scan sonar, a 160-in 3 airgun seismic-reflection profiler, a 3.5-kHz high-resolution seismic-reflection profiler, a 10-kHz echo sounder, and a proton-precession magnetometer. The nominal trackline spacing throughout the survey was 30 km. Derivative maps of sediment thickness (I-2089-A, I-2090-A, I-2091-A) and depth to basement (I-2089-B, I-2090-B, I-2091-B) in the basins of the west coast EEZ were compiled from both the sonar-image dala and the deep-penetration seismic data obtained on these cruises. Only EEZ-SCAN 84 data were used for the map compilations because available data from other cruises in this region are sparsely located, have poor navigational control, or were obtained with seismic systems that were not powerful enough to resolve oceanic basement. For this map series, sediment thickness and depth to basement were determined only in the deep-ocean basin regions because the seismic system used on the EEZ-SCAN 84 cruises could not resolve oceanic basement beneath the thick sediments of the continental slope. All the data used to compile the maps are presented in the "Atlas of the Exclusive Economic Zone, Western Conterminous United States" (EEZ-SCAN 84 Scientific Staff, 1986). Basement Outcrops GLORIA imagery was used to locate areas of basement outcrop throughout the region. Where possible, sediment thickness on and immediately adjacent to basement outcrops was measured from seismic data. Where there was no bathymetric or seismic control, a seamount peak was assumed to have no sediment cover. A pattern is used on the map to indicate all basement outcrops. Data Reduction Acoustic basement in the basins, invariably oceanic Layer 2, was observed on all of the seismic records. One-way traveltime was measured from the sea floor to acoustic basement. Because the trackline spacing of about 30 km is relatively large compared to the data density along track, we chose to measure the sediment thickness every 0.5 hour or at an interval of approximately 7.5 km. Water depth was measured with a 10-kHz profiler. Depth to basement was calculated using the sea surface as the zero datum and adding the corrected water depth (Carter, 1980) to the sediment thickness. Acoustic travel times were converted to depths by first calculating a regression equation from the interval velocity versus depth data of Connard and others (1984). Their data base comprises a compilation of all available Deep Sea Drilling Project data plus wide-angle refraction data, which were collected in Cascadia Basin west of Oregon and represents the best data set available for the United States west coast EEZ. The regression equation was integrated to determine sediment thickness as a function of one-way traveltime . The resulting equation is z = 1400t + 0 .5t 2 where z is sediment thickness in meters, and t is one-way traveltime in seconds. Sediment thicknesses calculated using this equation were compared to values calculated from the general equation of Carlson and others (1986). Values for sediment thickness calculated by the two equations differed by no greater than 10 percent throughout the range of travel times. Bathymetry The bathymetry is from Chase and others (1981). The bathymetric data were compiled from a variety of sources, and data quality is inconsistent. Because of differences in navigational precision and density of coverage, the bathymetric contours of a feature may be at a different location than the corresponding isopleths derived from the EEZ-SCAN 84 data, or a feature may not be indicated on the bathymetry at all. These situations occur because either the feature is poorly located in the bathymetric data set or, especially in the outer EEZ, the bathymetric data are too sparse to have defined the existence of a feature. Acknowledgments Topographic digital data bases were corrected and verified by Christina Lief. Gerald Evenden developed the computer software system MAPGEN, used to compose this map. Reviews, suggestions, and technical contributions from Edward C. Escowitz and Florence Wong and advice about cartographic design from Will Stettner substantially improved the quality of this map. References Cited Carlson, R.L., Gangi, A.F., and Snow, K.R., 1986, Empirical reflection-traveltime/ depth and velocity/depth functions for the deep-sea sediment column: Journal of Geophysical Research, v. 91, no. B8, p. 8249-8266. Carter, D.J.T., 1980, Echo-sounding correction tables: Taunton, United Kingdom, Hydrographic Department, Ministry of Defence, 150 p. Chase, T.E., Wilde, Pat, Normark, W.R, Miller, C.P., Seekins, B.A., and Young, J.D., 1981, Offshore topography of the Western United States between 32° and 49° North latitudes: U.S. Geological Survey Open-File Report 81-443, scale 1:864,518 at 38° latitude, 2 sheets. Connard, G., Couch, R., Keeling , K., Roy, J., and Troseth, S., 1984, Abyssal plain and continental net-objective sedimentary thicknesses, in Kulm, L.D., and others, eds., Western North America continental margin and adjacent ocean floor off Oregon and Washington, Atlas 1 of Regional Atlas Series, Ocean Margin Drilling Program: Woods Hole, Mass., Marine Science International, sheet 7. EEZ-SCAN 84 Scientific Staff, 1986, Atlas of the Exclusive Economic Zone, Western Conterminous United States: U.S. Geological Survey Miscellaneous Investigations Series I-1792, scale 1:500,000, 152 p. index map for I-2089-A See Also "U.S. Pacific West Coast Field Activities" (Paskevich and others, 2011; http://pubs.usgs.gov/of/2010/1332/htmldocs/pc/pc_overview.html). Paskevich, V.F., Wong, F.L., O?Malley, J.J., Stevenson, A.J., and Gutmacher, C.E., 2011, GLORIA sidescan-sonar imagery for parts of the U.S. Exclusive Economic Zone and adjacent areas: U.S. Geological Survey Open-File Report 2010?1332, available at http://pubs.usgs.gov/of/2010/1332/.

IMAP↗
USGS1993

Map showing sediment isopachs in the deep-sea basins of the Pacific continental margin, Cape Mendocino to Point Conception

The U.S. Geological Survey conducted a series of cruises, EEZSCAN 84 (EEZ-SCAN 84 Scientific Staff, 1986), to collect reconnaissance data on the newly proclaimed Exclusive Economic Zone (EEZ), the area out to 200 nautical miles from the coastline of the United States. The cruises systematically surveyed the entire conterminous United States west coast EEZ using the Geological Long-Range Inclined Asdic (GLORIA) side-scan sonar, a 160-in 3 airgun seismic-reflection profiler, a 3.5-kHz high-resolution seismic-reflection profiler, a 10-kHz echo sounder, and a proton-precession magnetometer. The nominal trackline spacing throughout the survey was 30 km. Derivative maps of sediment thickness (I-2089-A, I-2090-A, I-2091-A) and depth to basement (I-2089-B, I-2090-B, I-2091-B) in the basins of the west coast EEZ were compiled from both the sonar-image dala and the deep-penetration seismic data obtained on these cruises. Only EEZ-SCAN 84 data were used for the map compilations because available data from other cruises in this region are sparsely located, have poor navigational control, or were obtained with seismic systems that were not powerful enough to resolve oceanic basement. For this map series, sediment thickness and depth to basement were determined only in the deep-ocean basin regions because the seismic system used on the EEZ-SCAN 84 cruises could not resolve oceanic basement beneath the thick sediments of the continental slope. All the data used to compile the maps are presented in the "Atlas of the Exclusive Economic Zone, Western Conterminous United States" (EEZ-SCAN 84 Scientific Staff, 1986). Basement Outcrops GLORIA imagery was used to locate areas of basement outcrop throughout the region. Where possible, sediment thickness on and immediately adjacent to basement outcrops was measured from seismic data. Where there was no bathymetric or seismic control, a seamount peak was assumed to have no sediment cover. A pattern is used on the map to indicate all basement outcrops. Data Reduction Acoustic basement in the basins, invariably oceanic Layer 2, was observed on all of the seismic records. One-way traveltime was measured from the sea floor to acoustic basement. Because the trackline spacing of about 30 km is relatively large compared to the data density along track, we chose to measure the sediment thickness every 0.5 hour or at an interval of approximately 7.5 km. Water depth was measured with a 10-kHz profiler. Depth to basement was calculated using the sea surface as the zero datum and adding the corrected water depth (Carter, 1980) to the sediment thickness. Acoustic travel times were converted to depths by first calculating a regression equation from the interval velocity versus depth data of Connard and others (1984). Their data base comprises a compilation of all available Deep Sea Drilling Project data plus wide-angle refraction data, which were collected in Cascadia Basin west of Oregon and represents the best data set available for the United States west coast EEZ. The regression equation was integrated to determine sediment thickness as a function of one-way traveltime . The resulting equation is z = 1400t + 0 .5t 2 where z is sediment thickness in meters, and t is one-way traveltime in seconds. Sediment thicknesses calculated using this equation were compared to values calculated from the general equation of Carlson and others (1986). Values for sediment thickness calculated by the two equations differed by no greater than 10 percent throughout the range of travel times. Bathymetry The bathymetry is from Chase and others (1981). The bathymetric data were compiled from a variety of sources, and data quality is inconsistent. Because of differences in navigational precision and density of coverage, the bathymetric contours of a feature may be at a different location than the corresponding isopleths derived from the EEZ-SCAN 84 data, or a feature may not be indicated on the bathymetry at all. These situations occur because either the feature is poorly located in the bathymetric data set or, especially in the outer EEZ, the bathymetric data are too sparse to have defined the existence of a feature. Acknowledgments Topographic digital data bases were corrected and verified by Christina Lief. Gerald Evenden developed the computer software system MAPGEN, used to compose this map. Reviews, suggestions, and technical contributions from Edward C. Escowitz and Florence Wong and advice about cartographic design from Will Stettner substantially improved the quality of this map. References Cited Carlson, R.L., Gangi, A.F., and Snow, K.R., 1986, Empirical reflection-traveltime/ depth and velocity/depth functions for the deep-sea sediment column: Journal of Geophysical Research, v. 91, no. B8, p. 8249-8266. Carter, D.J.T., 1980, Echo-sounding correction tables: Taunton, United Kingdom, Hydrographic Department, Ministry of Defence, 150 p. Chase, T.E., Wilde, Pat, Normark, W.R, Miller, C.P., Seekins, B.A., and Young, J.D., 1981, Offshore topography of the Western United States between 32° and 49° North latitudes: U.S. Geological Survey Open-File Report 81-443, scale 1:864,518 at 38° latitude, 2 sheets. Connard, G., Couch, R., Keeling , K., Roy, J., and Troseth, S., 1984, Abyssal plain and continental net-objective sedimentary thicknesses, in Kulm, L.D., and others, eds., Western North America continental margin and adjacent ocean floor off Oregon and Washington, Atlas 1 of Regional Atlas Series, Ocean Margin Drilling Program: Woods Hole, Mass., Marine Science International, sheet 7. EEZ-SCAN 84 Scientific Staff, 1986, Atlas of the Exclusive Economic Zone, Western Conterminous United States: U.S. Geological Survey Miscellaneous Investigations Series I-1792, scale 1:500,000, 152 p. See Also "U.S. Pacific West Coast Field Activities" (Paskevich and others, 2011; http://pubs.usgs.gov/of/2010/1332/htmldocs/pc/pc_overview.html). Paskevich, V.F., Wong, F.L., O?Malley, J.J., Stevenson, A.J., and Gutmacher, C.E., 2011, GLORIA sidescan-sonar imagery for parts of the U.S. Exclusive Economic Zone and adjacent areas: U.S. Geological Survey Open-File Report 2010?1332, available at http://pubs.usgs.gov/of/2010/1332/.

IMAP↗
USGS1993

Map showing depth to basement in the deep-sea basins of the Pacific continental margin, Cape Mendocino to Point Conception

The U.S. Geological Survey conducted a series of cruises, EEZSCAN 84 (EEZ-SCAN 84 Scientific Staff, 1986), to collect reconnaissance data on the newly proclaimed Exclusive Economic Zone (EEZ), the area out to 200 nautical miles from the coastline of the United States. The cruises systematically surveyed the entire conterminous United States west coast EEZ using the Geological Long-Range Inclined Asdic (GLORIA) side-scan sonar, a 160-in 3 airgun seismic-reflection profiler, a 3.5-kHz high-resolution seismic-reflection profiler, a 10-kHz echo sounder, and a proton-precession magnetometer. The nominal trackline spacing throughout the survey was 30 km. Derivative maps of sediment thickness (I-2089-A, I-2090-A, I-2091-A) and depth to basement (I-2089-B, I-2090-B, I-2091-B) in the basins of the west coast EEZ were compiled from both the sonar-image dala and the deep-penetration seismic data obtained on these cruises. Only EEZ-SCAN 84 data were used for the map compilations because available data from other cruises in this region are sparsely located, have poor navigational control, or were obtained with seismic systems that were not powerful enough to resolve oceanic basement. For this map series, sediment thickness and depth to basement were determined only in the deep-ocean basin regions because the seismic system used on the EEZ-SCAN 84 cruises could not resolve oceanic basement beneath the thick sediments of the continental slope. All the data used to compile the maps are presented in the "Atlas of the Exclusive Economic Zone, Western Conterminous United States" (EEZ-SCAN 84 Scientific Staff, 1986). Basement Outcrops GLORIA imagery was used to locate areas of basement outcrop throughout the region. Where possible, sediment thickness on and immediately adjacent to basement outcrops was measured from seismic data. Where there was no bathymetric or seismic control, a seamount peak was assumed to have no sediment cover. A pattern is used on the map to indicate all basement outcrops. Data Reduction Acoustic basement in the basins, invariably oceanic Layer 2, was observed on all of the seismic records. One-way traveltime was measured from the sea floor to acoustic basement. Because the trackline spacing of about 30 km is relatively large compared to the data density along track, we chose to measure the sediment thickness every 0.5 hour or at an interval of approximately 7.5 km. Water depth was measured with a 10-kHz profiler. Depth to basement was calculated using the sea surface as the zero datum and adding the corrected water depth (Carter, 1980) to the sediment thickness. Acoustic travel times were converted to depths by first calculating a regression equation from the interval velocity versus depth data of Connard and others (1984). Their data base comprises a compilation of all available Deep Sea Drilling Project data plus wide-angle refraction data, which were collected in Cascadia Basin west of Oregon and represents the best data set available for the United States west coast EEZ. The regression equation was integrated to determine sediment thickness as a function of one-way traveltime . The resulting equation is z = 1400t + 0 .5t 2 where z is sediment thickness in meters, and t is one-way traveltime in seconds. Sediment thicknesses calculated using this equation were compared to values calculated from the general equation of Carlson and others (1986). Values for sediment thickness calculated by the two equations differed by no greater than 10 percent throughout the range of travel times. Bathymetry The bathymetry is from Chase and others (1981). The bathymetric data were compiled from a variety of sources, and data quality is inconsistent. Because of differences in navigational precision and density of coverage, the bathymetric contours of a feature may be at a different location than the corresponding isopleths derived from the EEZ-SCAN 84 data, or a feature may not be indicated on the bathymetry at all. These situations occur because either the feature is poorly located in the bathymetric data set or, especially in the outer EEZ, the bathymetric data are too sparse to have defined the existence of a feature. Acknowledgments Topographic digital data bases were corrected and verified by Christina Lief. Gerald Evenden developed the computer software system MAPGEN, used to compose this map. Reviews, suggestions, and technical contributions from Edward C. Escowitz and Florence Wong and advice about cartographic design from Will Stettner substantially improved the quality of this map. References Cited Carlson, R.L., Gangi, A.F., and Snow, K.R., 1986, Empirical reflection-traveltime/ depth and velocity/depth functions for the deep-sea sediment column: Journal of Geophysical Research, v. 91, no. B8, p. 8249-8266. Carter, D.J.T., 1980, Echo-sounding correction tables: Taunton, United Kingdom, Hydrographic Department, Ministry of Defence, 150 p. Chase, T.E., Wilde, Pat, Normark, W.R, Miller, C.P., Seekins, B.A., and Young, J.D., 1981, Offshore topography of the Western United States between 32° and 49° North latitudes: U.S. Geological Survey Open-File Report 81-443, scale 1:864,518 at 38° latitude, 2 sheets. Connard, G., Couch, R., Keeling , K., Roy, J., and Troseth, S., 1984, Abyssal plain and continental net-objective sedimentary thicknesses, in Kulm, L.D., and others, eds., Western North America continental margin and adjacent ocean floor off Oregon and Washington, Atlas 1 of Regional Atlas Series, Ocean Margin Drilling Program: Woods Hole, Mass., Marine Science International, sheet 7. EEZ-SCAN 84 Scientific Staff, 1986, Atlas of the Exclusive Economic Zone, Western Conterminous United States: U.S. Geological Survey Miscellaneous Investigations Series I-1792, scale 1:500,000, 152 p. See Also "U.S. Pacific West Coast Field Activities" (Paskevich and others, 2011; http://pubs.usgs.gov/of/2010/1332/htmldocs/pc/pc_overview.html). Paskevich, V.F., Wong, F.L., O?Malley, J.J., Stevenson, A.J., and Gutmacher, C.E., 2011, GLORIA sidescan-sonar imagery for parts of the U.S. Exclusive Economic Zone and adjacent areas: U.S. Geological Survey Open-File Report 2010?1332, available at http://pubs.usgs.gov/of/2010/1332/.

IMAP↗
USGS1993

Map showing sediment isopachs in the deep-sea basins of the Pacific Continental Margin, Strait of Juan de Fuca to Cape Mendocino

The U.S. Geological Survey conducted a series of cruises, EEZSCAN 84 (EEZ-SCAN 84 Scientific Staff, 1986), to collect reconnaissance data on the newly proclaimed Exclusive Economic Zone (EEZ), the area out to 200 nautical miles from the coastline of the United States. The cruises systematically surveyed the entire conterminous United States west coast EEZ using the Geological Long-Range Inclined Asdic (GLORIA) side-scan sonar, a 160-in 3 airgun seismic-reflection profiler, a 3.5-kHz high-resolution seismic-reflection profiler, a 10-kHz echo sounder, and a proton-precession magnetometer. The nominal trackline spacing throughout the survey was 30 km. Derivative maps of sediment thickness (I-2089-A, I-2090-A, I-2091-A) and depth to basement (I-2089-B, I-2090-B, I-2091-B) in the basins of the west coast EEZ were compiled from both the sonar-image dala and the deep-penetration seismic data obtained on these cruises. Only EEZ-SCAN 84 data were used for the map compilations because available data from other cruises in this region are sparsely located, have poor navigational control, or were obtained with seismic systems that were not powerful enough to resolve oceanic basement. For this map series, sediment thickness and depth to basement were determined only in the deep-ocean basin regions because the seismic system used on the EEZ-SCAN 84 cruises could not resolve oceanic basement beneath the thick sediments of the continental slope. All the data used to compile the maps are presented in the "Atlas of the Exclusive Economic Zone, Western Conterminous United States" (EEZ-SCAN 84 Scientific Staff, 1986). Basement Outcrops GLORIA imagery was used to locate areas of basement outcrop throughout the region. Where possible, sediment thickness on and immediately adjacent to basement outcrops was measured from seismic data. Where there was no bathymetric or seismic control, a seamount peak was assumed to have no sediment cover. A pattern is used on the map to indicate all basement outcrops. Data Reduction Acoustic basement in the basins, invariably oceanic Layer 2, was observed on all of the seismic records. One-way traveltime was measured from the sea floor to acoustic basement. Because the trackline spacing of about 30 km is relatively large compared to the data density along track, we chose to measure the sediment thickness every 0.5 hour or at an interval of approximately 7.5 km. Water depth was measured with a 10-kHz profiler. Depth to basement was calculated using the sea surface as the zero datum and adding the corrected water depth (Carter, 1980) to the sediment thickness. Acoustic travel times were converted to depths by first calculating a regression equation from the interval velocity versus depth data of Connard and others (1984). Their data base comprises a compilation of all available Deep Sea Drilling Project data plus wide-angle refraction data, which were collected in Cascadia Basin west of Oregon and represents the best data set available for the United States west coast EEZ. The regression equation was integrated to determine sediment thickness as a function of one-way traveltime . The resulting equation is z = 1400t + 0 .5t 2 where z is sediment thickness in meters, and t is one-way traveltime in seconds. Sediment thicknesses calculated using this equation were compared to values calculated from the general equation of Carlson and others (1986). Values for sediment thickness calculated by the two equations differed by no greater than 10 percent throughout the range of travel times. Bathymetry The bathymetry is from Chase and others (1981). The bathymetric data were compiled from a variety of sources, and data quality is inconsistent. Because of differences in navigational precision and density of coverage, the bathymetric contours of a feature may be at a different location than the corresponding isopleths derived from the EEZ-SCAN 84 data, or a feature may not be indicated on the bathymetry at all. These situations occur because either the feature is poorly located in the bathymetric data set or, especially in the outer EEZ, the bathymetric data are too sparse to have defined the existence of a feature. Acknowledgments Topographic digital data bases were corrected and verified by Christina Lief. Gerald Evenden developed the computer software system MAPGEN, used to compose this map. Reviews, suggestions, and technical contributions from Edward C. Escowitz and Florence Wong and advice about cartographic design from Will Stettner substantially improved the quality of this map. References Cited Carlson, R.L., Gangi, A.F., and Snow, K.R., 1986, Empirical reflection-traveltime/ depth and velocity/depth functions for the deep-sea sediment column: Journal of Geophysical Research, v. 91, no. B8, p. 8249-8266. Carter, D.J.T., 1980, Echo-sounding correction tables: Taunton, United Kingdom, Hydrographic Department, Ministry of Defence, 150 p. Chase, T.E., Wilde, Pat, Normark, W.R, Miller, C.P., Seekins, B.A., and Young, J.D., 1981, Offshore topography of the Western United States between 32° and 49° North latitudes: U.S. Geological Survey Open-File Report 81-443, scale 1:864,518 at 38° latitude, 2 sheets. Connard, G., Couch, R., Keeling , K., Roy, J., and Troseth, S., 1984, Abyssal plain and continental net-objective sedimentary thicknesses, in Kulm, L.D., and others, eds., Western North America continental margin and adjacent ocean floor off Oregon and Washington, Atlas 1 of Regional Atlas Series, Ocean Margin Drilling Program: Woods Hole, Mass., Marine Science International, sheet 7. EEZ-SCAN 84 Scientific Staff, 1986, Atlas of the Exclusive Economic Zone, Western Conterminous United States: U.S. Geological Survey Miscellaneous Investigations Series I-1792, scale 1:500,000, 152 p. See Also "U.S. Pacific West Coast Field Activities" (Paskevich and others, 2011; http://pubs.usgs.gov/of/2010/1332/htmldocs/pc/pc_overview.html). Paskevich, V.F., Wong, F.L., O?Malley, J.J., Stevenson, A.J., and Gutmacher, C.E., 2011, GLORIA sidescan-sonar imagery for parts of the U.S. Exclusive Economic Zone and adjacent areas: U.S. Geological Survey Open-File Report 2010?1332, available at http://pubs.usgs.gov/of/2010/1332/.

IMAP↗
USGS1993

Map showing depth to basement in the deep-sea basins of the Pacific continental margin, Strait of Juan de Fuca to Cape Mendocino

The U.S. Geological Survey conducted a series of cruises, EEZSCAN 84 (EEZ-SCAN 84 Scientific Staff, 1986), to collect reconnaissance data on the newly proclaimed Exclusive Economic Zone (EEZ), the area out to 200 nautical miles from the coastline of the United States. The cruises systematically surveyed the entire conterminous United States west coast EEZ using the Geological Long-Range Inclined Asdic (GLORIA) side-scan sonar, a 160-in 3 airgun seismic-reflection profiler, a 3.5-kHz high-resolution seismic-reflection profiler, a 10-kHz echo sounder, and a proton-precession magnetometer. The nominal trackline spacing throughout the survey was 30 km. Derivative maps of sediment thickness (I-2089-A, I-2090-A, I-2091-A) and depth to basement (I-2089-B, I-2090-B, I-2091-B) in the basins of the west coast EEZ were compiled from both the sonar-image dala and the deep-penetration seismic data obtained on these cruises. Only EEZ-SCAN 84 data were used for the map compilations because available data from other cruises in this region are sparsely located, have poor navigational control, or were obtained with seismic systems that were not powerful enough to resolve oceanic basement. For this map series, sediment thickness and depth to basement were determined only in the deep-ocean basin regions because the seismic system used on the EEZ-SCAN 84 cruises could not resolve oceanic basement beneath the thick sediments of the continental slope. All the data used to compile the maps are presented in the "Atlas of the Exclusive Economic Zone, Western Conterminous United States" (EEZ-SCAN 84 Scientific Staff, 1986). Basement Outcrops GLORIA imagery was used to locate areas of basement outcrop throughout the region. Where possible, sediment thickness on and immediately adjacent to basement outcrops was measured from seismic data. Where there was no bathymetric or seismic control, a seamount peak was assumed to have no sediment cover. A pattern is used on the map to indicate all basement outcrops. Data Reduction Acoustic basement in the basins, invariably oceanic Layer 2, was observed on all of the seismic records. One-way traveltime was measured from the sea floor to acoustic basement. Because the trackline spacing of about 30 km is relatively large compared to the data density along track, we chose to measure the sediment thickness every 0.5 hour or at an interval of approximately 7.5 km. Water depth was measured with a 10-kHz profiler. Depth to basement was calculated using the sea surface as the zero datum and adding the corrected water depth (Carter, 1980) to the sediment thickness. Acoustic travel times were converted to depths by first calculating a regression equation from the interval velocity versus depth data of Connard and others (1984). Their data base comprises a compilation of all available Deep Sea Drilling Project data plus wide-angle refraction data, which were collected in Cascadia Basin west of Oregon and represents the best data set available for the United States west coast EEZ. The regression equation was integrated to determine sediment thickness as a function of one-way traveltime . The resulting equation is z = 1400t + 0 .5t 2 where z is sediment thickness in meters, and t is one-way traveltime in seconds. Sediment thicknesses calculated using this equation were compared to values calculated from the general equation of Carlson and others (1986). Values for sediment thickness calculated by the two equations differed by no greater than 10 percent throughout the range of travel times. Bathymetry The bathymetry is from Chase and others (1981). The bathymetric data were compiled from a variety of sources, and data quality is inconsistent. Because of differences in navigational precision and density of coverage, the bathymetric contours of a feature may be at a different location than the corresponding isopleths derived from the EEZ-SCAN 84 data, or a feature may not be indicated on the bathymetry at all. These situations occur because either the feature is poorly located in the bathymetric data set or, especially in the outer EEZ, the bathymetric data are too sparse to have defined the existence of a feature. Acknowledgments Topographic digital data bases were corrected and verified by Christina Lief. Gerald Evenden developed the computer software system MAPGEN, used to compose this map. Reviews, suggestions, and technical contributions from Edward C. Escowitz and Florence Wong and advice about cartographic design from Will Stettner substantially improved the quality of this map. References Cited Carlson, R.L., Gangi, A.F., and Snow, K.R., 1986, Empirical reflection-traveltime/ depth and velocity/depth functions for the deep-sea sediment column: Journal of Geophysical Research, v. 91, no. B8, p. 8249-8266. Carter, D.J.T., 1980, Echo-sounding correction tables: Taunton, United Kingdom, Hydrographic Department, Ministry of Defence, 150 p. Chase, T.E., Wilde, Pat, Normark, W.R, Miller, C.P., Seekins, B.A., and Young, J.D., 1981, Offshore topography of the Western United States between 32° and 49° North latitudes: U.S. Geological Survey Open-File Report 81-443, scale 1:864,518 at 38° latitude, 2 sheets. Connard, G., Couch, R., Keeling , K., Roy, J., and Troseth, S., 1984, Abyssal plain and continental net-objective sedimentary thicknesses, in Kulm, L.D., and others, eds., Western North America continental margin and adjacent ocean floor off Oregon and Washington, Atlas 1 of Regional Atlas Series, Ocean Margin Drilling Program: Woods Hole, Mass., Marine Science International, sheet 7. EEZ-SCAN 84 Scientific Staff, 1986, Atlas of the Exclusive Economic Zone, Western Conterminous United States: U.S. Geological Survey Miscellaneous Investigations Series I-1792, scale 1:500,000, 152 p. See Also "U.S. Pacific West Coast Field Activities" (Paskevich and others, 2011; http://pubs.usgs.gov/of/2010/1332/htmldocs/pc/pc_overview.html). Paskevich, V.F., Wong, F.L., O?Malley, J.J., Stevenson, A.J., and Gutmacher, C.E., 2011, GLORIA sidescan-sonar imagery for parts of the U.S. Exclusive Economic Zone and adjacent areas: U.S. Geological Survey Open-File Report 2010?1332, available at http://pubs.usgs.gov/of/2010/1332/.

IMAP↗
USGS2023

Estuarine salinity extremes: Using the Coastal Salinity Index to quantify the role of droughts, floods, hurricanes, and freshwater flow alteration

In the face of accelerating climate change, advancing understanding of how extreme climatic events influence estuarine salinities can help to inform resource management. Extreme salinities driven by droughts, hurricanes, floods, and freshwater flow alterations can lead to ecological transformations in estuarine ecosystems. Here, we applied the Coastal Salinity Index (CSI; Conrads and Darby 2017) to 22 years (1998–2020) of salinity data in a Louisiana estuary (Barataria Estuary, USA) to elucidate the impacts of extreme events on estuarine salinities. The CSI is an index to quantify salinity patterns at a specific location through long-term averages and deviations from historical average conditions. We calculated and compared CSI values for four stations distributed along an estuarine salinity gradient. We identified 10 events between 1998 and 2020 that produced extreme salinities, including two droughts, four hurricanes, three floods, and one freshwater diversion. The droughts of 2000 and 2006 caused surface water salinities to increase substantially throughout the estuary. The effects of hurricanes were highly variable, with some storms leading to elevated salinities throughout the entire estuary (e.g., Hurricanes Katrina and Rita in 2005), whereas other storms led to elevated salinities for some but not all stations (e.g., Hurricanes Gustav and Ike in 2008 or Hurricane Isaac in 2012). The opening of a freshwater river diversion in 2010 contributed to fresher conditions throughout the estuary and appeared to reduce or eliminate the increases in salinity that normally occur during the summer, although these effects were short-lived. Mississippi River floods in 2008, 2011, and 2019 reduced salinities throughout the estuary, but the effects were most pronounced in the lower estuary compared to the upper estuary. Collectively, our results advance understanding of the influence of extreme events on estuarine salinity regimes. Our analyses also highlight the value of the CSI for identifying periods with extreme salinities (i.e., extreme high or low salinities) via calculations that place salinity levels within and across estuaries within a historical context.

Louisiana↗
USGS2024

Nitrate exposure from drinking water and dietary sources among Iowa farmers using private wells

Nitrate levels are increasing in water resources across the United States and nitrate ingestion from drinking water has been associated with adverse health risks in epidemiologic studies at levels below the maximum contaminant level (MCL). In contrast, dietary nitrate ingestion has generally been associated with beneficial health effects. Few studies have characterized the contribution of both drinking water and dietary sources to nitrate exposure. The Agricultural Health Study is a prospective cohort of farmers and their spouses in Iowa and North Carolina. In 2018–2019, we assessed nitrate exposure for 47 farmers who used private wells for their drinking water and lived in 8 eastern Iowa counties where groundwater is vulnerable to nitrate contamination. Drinking water and dietary intakes were estimated using the National Cancer Institute Automated Self-Administered 24-Hour Dietary Assessment tool. We measured nitrate in tap water and estimated dietary nitrate from a database of food concentrations. Urinary nitrate was measured in first morning void samples in 2018–19 and in archived samples from 2010 to 2017 (minimum time between samples: 2 years; median: 7 years). We used linear regression to evaluate urinary nitrate concentrations in relation to total nitrate, and drinking water and dietary intakes separately. Overall, dietary nitrate contributed the most to total intake (median: 97 %; interquartile range [IQR]: 57–99 %). Among 15 participants (32 %) whose drinking water nitrate concentrations were at/above the U.S. Environmental Protection Agency MCL (10 mg/L NO 3 -N), median intake from water was 44 % (IQR: 26–72 %). Total nitrate intake was the strongest predictor of urinary nitrate concentrations (R 2 = 0.53). Drinking water explained a similar proportion of the variation in nitrate excretion (R 2 = 0.52) as diet (R 2 = 0.47). Our findings demonstrate the importance of both dietary and drinking water intakes as determinants of nitrate excretion.

Iowa↗
USGS1997

Energy sources and ecological role of crayfishes in an Ozark stream: Insights from stable isotopes and gut analysis

Energy sources for the crayfishes Orconectes luteus and O. punctimanus in the Jacks Fork River, Missouri, were quantified using stable isotopes (??13C and ??15N) and gut-content analysis. A dual-isotope mixing model indicated that about two thirds of crayfish production originated from allochthonous carbon sources, and 30-50% of crayfish production was derived from direct consumption of animal matter. Young-of-the-year crayfishes and adult O. luteus were more carnivorous than the larger adult O. punctimanus. Contributions of energy sources determined using the stable isotope mixing model were similar to results of gut-content analysis corrected for differential assimilation of dietary components. Proportions of crayfish production attributed to animal matter by these two methods were four to five times greater than estimates derived from uncorrected gut-content analysis. Unadjusted gut-content analysis overestimated the percentage of crayfish production from feeding directly on detritus. Production-based calculations of crayfish food consumption rates indicated that crayfishes were the dominant consumers of benthic invertebrates, detritus, and algae and may strongly influence lower trophic levels, organic matter processing, and energy flow in this system.

Canadian Journal of Fisheries and Aquatic Sciences↗
USGS2023

Assessing contaminants of emerging concern in the Great Lakes Ecosystem: A decade of method development and practical application

Assessing the ecological risk of contaminants in the field typically involves consideration of a complex mixture of compounds which may or may not be detected via instrumental analyses. Further, there are insufficient data to predict the potential biological effects of many detected compounds, leading to their being characterized as contaminants of emerging concern (CECs). Over the past several years, advances in chemistry, toxicology, and bioinformatics have resulted in a variety of concepts and tools that can enhance the pragmatic assessment of the ecological risk of CECs. The present Focus article describes a 10+- year multiagency effort supported through the U.S. Great Lakes Restoration Initiative to assess the occurrence and implications of CECs in the North American Great Lakes. State-of-the-science methods and models were used to evaluate more than 700 sites in about approximately 200 tributaries across lakes Ontario, Erie, Huron, Michigan, and Superior, sometimes on multiple occasions. Studies featured measurement of up to 500 different target analytes in different environmental matrices, coupled with evaluation of biological effects in resident species, animals from in situ and laboratory exposures, and in vitro systems. Experimental taxa included birds, fish, and a variety of invertebrates, and measured endpoints ranged from molecular to apical responses. Data were integrated and evaluated using a diversity of curated knowledgebases and models with the goal of producing actionable insights for risk assessors and managers charged with evaluating and mitigating the effects of CECs in the Great Lakes. This overview is based on research and data captured in approximately about 90 peer-reviewed journal articles and reports, including approximately about 30 appearing in a virtual issue comprised of highlighted papers published in Environmental Toxicology and Chemistry or Integrated Environmental Assessment and Management . Environ Toxicol Chem 2023;42:2506–2518. © 2023 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Environmental Toxicology and Chemistry↗
USGS2012

High-resolution digital elevation dataset for Crater Lake National Park and vicinity, Oregon, based on LiDAR survey of August-September 2010 and bathymetric survey of July 2000

Crater Lake partially fills the caldera that formed approximately 7,700 years ago during the eruption of a 12,000-foot volcano known as Mount Mazama. The caldera-forming or climactic eruption of Mount Mazama devastated the surrounding landscape, left a thick deposit of pumice and ash in adjacent valleys, and spread a blanket of volcanic ash as far away as southern Canada. Because the Crater Lake region is potentially volcanically active, knowledge of past events is important to understanding hazards from future eruptions. Similarly, because the area is seismically active, documenting and evaluating geologic faults is critical to assessing hazards from earthquakes. As part of the American Recovery and Reinvestment Act (ARRA) of 2009, the U.S. Geological Survey was awarded funding for high-precision airborne LiDAR ( Li ght D etection A nd R anging) data collection at several volcanoes in the Cascade Range through the Oregon LiDAR Consortium, administered by the Oregon Department of Geology and Mineral Industries (DOGAMI). The Oregon LiDAR Consortium contracted with Watershed Sciences, Inc., to conduct the data collection surveys. Collaborating agencies participating with the Oregon LiDAR Consortium for data collection in the Crater Lake region include Crater Lake National Park (National Park Service) and the Federal Highway Administration. In the immediate vicinity of Crater Lake National Park, 798 square kilometers of LiDAR data were collected, providing a digital elevation dataset of the ground surface beneath forest cover with an average resolution of 1.6 laser returns/m 2 and both vertical and horizontal accuracies of ±5 cm. The LiDAR data were mosaicked in this report with bathymetry of the lake floor of Crater Lake, collected in 2000 using high-resolution multibeam sonar in a collaborative effort between the U.S. Geological Survey, Crater Lake National Park, and the Center for Coastal and Ocean Mapping at the University of New Hampshire. The bathymetric survey collected 16 million soundings with a spatial resolution of 2 meters using an EM1002 system owned and operated by C&C Technologies, Inc. The combined LiDAR and bathymetric dataset has a cell size of 1 meter and will contribute to understanding past volcanic events and their deposits, recognizing of faults and volcanic landforms, and quantifying landscape modification during and after the next volcanic eruption at Crater Lake.

Oregon↗
USGS2018

President elect's message

The first morning home the day after I became president of SWS at the annual meeting in Denver, I note the wilting of my garden and the grumpiness of my cats as the dawn of my new reality. The extra hours that I will spend as president of SWS will manifest itself as more cat and garden unhappiness as travel and responsibilities grow. The cats gleefully blast out of the door into the backyard, because they have been cooped up indoors during the Denver meeting. My husband is more supportive than the cats and garden. So far, being the president of SWS recreates for me both the feelings of boundless possibilities I felt when president of my 4-H club when the changing future was in my hands, and of the heavy responsibility of my temporary summer chairmanship of my university department. “I am ready”, I think as I sleepily sip coffee that morning. My observations at the Denver annual meeting led to my realization that SWS is changing in sync with the breakneck speed of the world around us. Importantly, the new Student Section is contributing new insights into all aspects of SWS. Our students are the way forward for SWS, so it is incredibly exciting to witness increasing student involvement. Please, if you are a student and you want to participate in SWS activities, contact me. Other new things emerging at the Denver meeting included the Traditional Ecological Knowledge initiative, which will be an important step in our internationalization efforts. Also related to internationalization, we are linking regional South American and African meetings to SWS section initiatives. Our PCP program is working toward offering certifications to members with training outside of North America, which will be of incredible value to these members. Other great ideas are emerging from the Denver meeting. The chapter presidents and section chairs are creating consortia to foster intra-meeting exchange of ideas. The New Media committee is offering a venue for member-created videos and phone apps. And now, we prepare for the 40th anniversary of SWS in 2020 with the planning of various celebrations as well as special issues on emerging issues in wetland science, and the history of SWS. Much of my year will be spent shepherding these and other SWS activities, which will come together at the next annual meeting in Baltimore (May 28-31, 2019). In this world of electronic communication, the networking time at the annual meetings is precious. Hope to see you in Baltimore. A long time ago, SWS membership information was stored in a shoebox. Despite the substantial changes in our organization since then, I view SWS as a shoebox-full of members that I want to know personally. If you have ideas or concerns in the next year, please contact me: middletonb@usgs.gov Much of my year will be spent shepherding these and other SWS activities, which will come together at the meeting in Baltimore (May 28-31, 2019). In this world of electronic communication, the networking time at the annual meetings is precious.

Wetland Science & Practice↗
USGS2019

The tangled tale of Kīlauea’s 2018 eruption as told by geochemical monitoring

Changes in magma chemistry that affect eruptive behavior occur during many volcanic eruptions, but typical analytical techniques are too slow to contribute to hazard monitoring. We used rapid energy-dispersive X-ray fluorescence analysis to measure diagnostic elements in lava samples within a few hours of collection during the 2018 Kīlauea eruption. The geochemical data provided important information for field crews and civil authorities in advance of changing hazards during the eruption. The appearance of hotter magma was recognized several days before the onset of voluminous eruptions of fast-moving flows that destroyed hundreds of homes. We identified, in near-real time, interactions between older, colder, stored magma – including the unexpected eruption of andesite – and hotter magma delivered during dike emplacement.

Hawaii↗
USGS2020

Spatial variability of phytoplankton in a shallow tidal freshwater system reveals complex controls on abundance and community structure

Estuaries worldwide are undergoing changes to patterns of aquatic productivity because of human activities that alter flow, impact sediment delivery and thus the light field, and contribute nutrients and contaminants like pesticides and metals. These changes can influence phytoplankton communities, which in turn can alter estuarine food webs. We used multiple approaches-including high-resolution water quality mapping, synoptic sampling, productivity and nitrogen uptake rates, Lagrangian parcel tracking, enclosure experiments and bottle incubations-over a short time period to take a “spatial snapshot” of conditions in the northern region of the San Francisco Estuary (California, USA) to examine how environmental drivers like light availability, nutrients, water residence time, and contaminants affect phytoplankton abundance and community attributes like size distribution, taxonomic structure, and nutrient uptake rates. Zones characterized by longer residence time (15–60 days) had higher chlorophyll-a concentrations (9 ± 4 µg L −1 ) and were comprised primarily of small phytoplankton cells (<5 µm, 74 ± 8%), lower ammonium concentrations (1 ± 0.8 µM), higher nitrate uptake rates, and higher rates of potential carbon productivity. Conversely, zones characterized by shorter residence time (1–14 days) had higher ammonium concentration (13 ± 5 µM) and lower chlorophyll-a concentration (5 ± 1 µg L −1 ) with diatoms making up a larger percent contribution. Longer residence time, however, did not result in the accumulation of large (>5 µm) cells considered important to pelagic food webs. Rather, longer residence time zones had a phytoplankton community comprised primarily of small cells, particularly picocyanobacteria that made up 38 ± 17% of the chlorophyll-a – nearly double the concentration seen in shorter residence time zones (22 ± 7% picocyanobacterial of chlorophyll-a). Our results suggest that water residence time in estuaries may have an effect as large or larger than that experimentally demonstrated for light, contaminants, or nutrients.

California↗