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  • PANGAEA  (46)
  • Springer Nature  (5)
  • Wiley  (4)
  • Blackwell Publishing Ltd
  • 2020-2024  (56)
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  • 1
    Publication Date: 2024-03-22
    Description: Soil fauna drives crucial processes of energy and nutrient cycling in agricultural systems, and influences the quality of crops and pest incidence. Soil tillage is the most influential agricultural manipulation of soil structure, and has a profound influence on soil biology and its provision of ecosystem services. The objective of this study was to quantify through meta‐analyses the effects of reducing tillage intensity on density and diversity of soil micro‐ and mesofaunal communities, and how these effects vary among different pedoclimatic conditions and interact with concurrent management practices. We present the results of a global meta‐analysis of available literature data on the effects of different tillage intensities on taxonomic and functional groups of soil micro‐ and mesofauna. We collected paired observations (conventional vs. reduced forms of tillage/no‐tillage) from 133 studies across 33 countries. Our results show that reduced tillage intensity or no‐tillage increases the total density of springtails (+35%), mites (+23%), and enchytraeids (+37%) compared to more intense tillage methods. The meta‐analyses for different nematode feeding groups, life‐forms of springtails, and taxonomic mite groups showed higher densities under reduced forms of tillage compared to conventional tillage on omnivorous nematodes (+53%), epedaphic (+81%) and hemiedaphic (+84%) springtails, oribatid (+43%) and mesostigmatid (+57%) mites. Furthermore, the effects of reduced forms of tillage on soil micro‐ and mesofauna varied with depth, climate and soil texture, as well as with tillage method, tillage frequency, concurrent fertilisation, and herbicide application. Our findings suggest that reducing tillage intensity can have positive effects on the density of micro‐ and mesofaunal communities in areas subjected to long‐term intensive cultivation practices. Our results will be useful to support decision making on the management of soil faunal communities and will facilitate modelling efforts of soil biology in global agroecosystems. HIGHLIGHTS Global meta‐analysis to estimate the effect of reducing tillage intensity on micro‐ and mesofauna Reduced tillage or no‐tillage has positive effects on springtail, mite and enchytraeid density Effects vary among nematode feeding groups, springtail life forms and mite suborders Effects vary with texture, climate and depth and depend on the tillage method and frequency
    Description: Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347
    Description: https://doi.org/10.20387/bonares-eh0f-hj28
    Keywords: ddc:631.4 ; agricultural land use ; conservation agriculture ; conventional agriculture ; soil biodiversity ; soil cultivation
    Language: English
    Type: doc-type:article
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  • 2
    Publication Date: 2023-03-29
    Description: Tap waters were collected from major metropolitan areas of the western United States. Tap waters were sampled between 2012-2015 from seven metropolitan areas: Los Angeles-Long Beach-Santa Ana (CA), Phoenix-Mesa-Glendale (AZ), Salt Lake City (UT), San Diego-Carlsbad-San Marcos (CA), San Francisco-Oakland-Fremont (CA), San Jose-Sunnyvale-Santa Clara (CA), and Riverside-San Bernardino-Ontario (CA). These areas represent some of the most populous in the US and employ a diversity of water management practices. Here hydrogen (d2H) and oxygen (d18O) isotope values along with strontium isotope ratios (87Sr/86Sr) and element abundances were measured. d2H and d18O of 2039 tap waters were measured following Tipple et al., 2017 (Water Research, 119, 212-224). 87Sr/86Sr and elemental compositions of 820 and 806 waters were analyzed following Tipple et al., 2018 (Scientific Reports, 8, 2224), respectively. The purpose of these data was to assess spatial, temporal, and climatic dynamics in isotope and elemental geochemistry of tap waters. We found that the isotope and elemental geochemistry of tap waters corresponded to the water sources (e.g., transported water, local surface water, groundwater, etc.) and management practices (e.g., storage in open reservoirs, mixing, etc.) for discrete areas within the larger metropolitan areas.
    Keywords: drought; elemental composition; hydrogen; hydrology; Oxygen; Strontium
    Type: Dataset
    Format: application/zip, 3 datasets
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  • 3
    Publication Date: 2023-03-29
    Keywords: Area/locality; Arizona_tap_water; California_tap_water; DATE/TIME; drought; elemental composition; Event label; hydrogen; hydrology; LATITUDE; Location; LONGITUDE; One-time_collection_tap_water; Oxygen; Salt_Lake_Valley_tap_water; Sample ID; Strontium; United States of America; Water sample; WS; δ18O, water; δ18O, water, standard deviation; δ Deuterium, water; δ Deuterium, water, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 11414 data points
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  • 4
    Publication Date: 2023-03-29
    Keywords: Area/locality; Arizona_tap_water; California_tap_water; DATE/TIME; drought; elemental composition; Event label; hydrogen; hydrology; LATITUDE; Location; LONGITUDE; One-time_collection_tap_water; Oxygen; Salt_Lake_Valley_tap_water; Sample ID; Strontium; Strontium-87/Strontium-86 ratio; Strontium-87/Strontium-86 ratio, standard deviation; United States of America; Water sample; WS
    Type: Dataset
    Format: text/tab-separated-values, 3286 data points
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  • 5
    Publication Date: 2023-03-29
    Keywords: Aluminium; Antimony; Area/locality; Arizona_tap_water; Arsenic; Barium; Beryllium; Boron; Cadmium; Caesium; Calcium; California_tap_water; Cerium; Chromium; Cobalt; Copper; DATE/TIME; drought; elemental composition; Europium; Event label; hydrogen; hydrology; Iron; Lanthanum; LATITUDE; Lead; Lithium; Location; LONGITUDE; Magnesium; Manganese; Molybdenum; Neodymium; Nickel; One-time_collection_tap_water; Oxygen; Potassium; Salt_Lake_Valley_tap_water; Sample ID; Scandium; Selenium; Sodium; Strontium; Thorium; United States of America; Uranium; Vanadium; Water sample; WS; Yttrium; Zinc
    Type: Dataset
    Format: text/tab-separated-values, 16295 data points
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  • 6
    Publication Date: 2023-05-24
    Description: Hair samples were collected throughout the United States, with particular focus on major metropolitan areas of the western United States. Hair samples were collected in 2004 as well as between 2013-2015. Here hydrogen (d2H) and oxygen (d18O) isotope values along with strontium isotope ratios (87Sr/86Sr) and element abundances were measured. d2H and d18O values, 87Sr/86Sr, and elemental compositions of 560, 385 and 306 hair samples were analyzed following Tipple et al., 2018 (Scientific Reports, 8, 2224), respectively. The purpose of these data was to assess geospatial variations in isotope and elemental geochemistry of human hair. We found that the isotope and elemental geochemistry of human hair largely corresponded to the geochemistry of drinking and bathing water, which in turn varied by water source and management practice. These data provide a foundation to reconstruct human movements using the geochemistry of modern or ancient human hair.
    Keywords: anthropogenic tracers; provenance analysis; stable isotope analysis; strontium isotopes; trace element; water chemistry; water isotopes; water management
    Type: Dataset
    Format: application/zip, 3 datasets
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  • 7
    Publication Date: 2023-05-24
    Keywords: anthropogenic tracers; Area/locality; Arizona_1156; Arizona_1161; Arizona_1197; Arizona_1199; Arizona_570; Arizona_577; Arizona_579; Arizona_585; Arizona_602; Arizona_611; Arizona_625; Arizona_630; Arizona_635; Arizona_640; Arizona_661; Arizona_677; Arizona_678; California_1280; California_1287; California_198; California_200; California_201; California_202; California_205; California_208; California_470; California_473; California_480; California_485; California_487; California_491; California_495; California_542; California_549; California_561; California_562; California_563; California_564; California_731; California_733; California_738; California_756; California_772; California_779; California_781; California_785; California_798; California_808; California_839; California_840; California_853; California_855; California_858; California_862; California_872; California_879; California_882; California_883; California_884; California_885; California_887; California_888; California_889; California_898; California_901; California_904; California_909; California_913; California_914; California_917; DATE/TIME; Event label; HHS; Human hair sample; LATITUDE; Location ID; LONGITUDE; One-time_collection_1349; One-time_collection_1350; One-time_collection_1352; One-time_collection_1353; One-time_collection_1354; One-time_collection_1355; One-time_collection_1356; One-time_collection_1357; One-time_collection_1358; One-time_collection_1359; One-time_collection_1360; One-time_collection_1361; One-time_collection_1363; One-time_collection_1364; One-time_collection_1365; One-time_collection_1366; One-time_collection_1367; One-time_collection_1368; One-time_collection_1369; One-time_collection_1370; One-time_collection_1371; One-time_collection_1372; One-time_collection_1373; One-time_collection_1374; One-time_collection_1375; One-time_collection_1376; One-time_collection_1377; One-time_collection_1378; One-time_collection_1379; One-time_collection_1380; One-time_collection_1381; One-time_collection_1382; One-time_collection_1383; One-time_collection_1384; One-time_collection_1386; One-time_collection_1388; One-time_collection_1389; One-time_collection_1390; One-time_collection_1392; One-time_collection_1393; One-time_collection_1395; One-time_collection_1396; One-time_collection_1397; One-time_collection_1398; One-time_collection_1400; One-time_collection_1401; One-time_collection_1402; One-time_collection_1403; One-time_collection_1404; One-time_collection_1405; One-time_collection_1406; One-time_collection_1407; One-time_collection_1408; One-time_collection_1409; One-time_collection_1410; One-time_collection_1411; One-time_collection_1412; One-time_collection_1413; One-time_collection_1415; One-time_collection_1416; One-time_collection_1417; One-time_collection_1418; One-time_collection_1419; One-time_collection_1420; One-time_collection_1421; One-time_collection_1422; provenance analysis; Salt_Lake_Valley_1000; Salt_Lake_Valley_1001; Salt_Lake_Valley_1002; Salt_Lake_Valley_1003; Salt_Lake_Valley_1004; Salt_Lake_Valley_1005; Salt_Lake_Valley_1006; Salt_Lake_Valley_1007; Salt_Lake_Valley_1008; Salt_Lake_Valley_1009; Salt_Lake_Valley_1010; Salt_Lake_Valley_1011; Salt_Lake_Valley_1012; Salt_Lake_Valley_1013; Salt_Lake_Valley_1014; Salt_Lake_Valley_1015; Salt_Lake_Valley_1016; Salt_Lake_Valley_1017; Salt_Lake_Valley_1018; Salt_Lake_Valley_1019; Salt_Lake_Valley_248; Salt_Lake_Valley_249; Salt_Lake_Valley_250; Salt_Lake_Valley_251; Salt_Lake_Valley_341; Salt_Lake_Valley_342; Salt_Lake_Valley_382; Salt_Lake_Valley_396; Salt_Lake_Valley_413; Salt_Lake_Valley_420; Salt_Lake_Valley_421; Salt_Lake_Valley_432; Salt_Lake_Valley_448; Salt_Lake_Valley_996; Salt_Lake_Valley_997; Salt_Lake_Valley_998; Salt_Lake_Valley_999; Sample ID; stable isotope analysis; strontium isotopes; TC/EA-IRMS; trace element; United States; water chemistry; water isotopes; water management; Year of observation; δ18O; δ18O, standard deviation; δ Deuterium; δ Deuterium, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 3134 data points
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  • 8
    Publication Date: 2023-05-24
    Keywords: Aluminium; anthropogenic tracers; Antimony; Area/locality; Arizona_1156; Arizona_1161; Arizona_1197; Arizona_1199; Arizona_570; Arizona_577; Arizona_579; Arizona_585; Arizona_602; Arizona_611; Arizona_625; Arizona_630; Arizona_635; Arizona_640; Arizona_661; Arizona_677; Arizona_678; Arsenic; Barium; Beryllium; Boron; Cadmium; Caesium; Calcium; California_198; California_200; California_201; California_202; California_205; California_208; California_470; California_473; California_480; California_485; California_487; California_491; California_495; California_542; California_549; California_561; California_562; California_563; California_564; California_731; California_733; California_738; California_756; California_772; California_779; California_781; California_785; California_872; California_879; California_882; California_883; California_884; California_885; California_887; California_888; California_889; California_898; California_901; California_904; California_909; California_913; California_914; California_917; Cerium; Chromium; Cobalt; Copper; DATE/TIME; Europium; Event label; HHS; Human hair sample; ICP-MS; Iron; Lanthanum; LATITUDE; Lead; Lithium; Location ID; LONGITUDE; Magnesium; Manganese; Molybdenum; Neodymium; Nickel; Potassium; provenance analysis; Salt_Lake_Valley_1000; Salt_Lake_Valley_1001; Salt_Lake_Valley_1002; Salt_Lake_Valley_1003; Salt_Lake_Valley_1004; Salt_Lake_Valley_1005; Salt_Lake_Valley_1006; Salt_Lake_Valley_1007; Salt_Lake_Valley_1008; Salt_Lake_Valley_1009; Salt_Lake_Valley_1010; Salt_Lake_Valley_1011; Salt_Lake_Valley_1012; Salt_Lake_Valley_1013; Salt_Lake_Valley_1014; Salt_Lake_Valley_1015; Salt_Lake_Valley_1016; Salt_Lake_Valley_1017; Salt_Lake_Valley_1018; Salt_Lake_Valley_1019; Salt_Lake_Valley_248; Salt_Lake_Valley_249; Salt_Lake_Valley_250; Salt_Lake_Valley_251; Salt_Lake_Valley_342; Salt_Lake_Valley_413; Salt_Lake_Valley_421; Salt_Lake_Valley_432; Salt_Lake_Valley_996; Salt_Lake_Valley_997; Salt_Lake_Valley_998; Salt_Lake_Valley_999; Sample ID; Selenium; Sodium; stable isotope analysis; Strontium; strontium isotopes; Thorium; trace element; United States; Uranium; Vanadium; water chemistry; water isotopes; water management; Year of observation; Yttrium; Zinc
    Type: Dataset
    Format: text/tab-separated-values, 5779 data points
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  • 9
    Publication Date: 2023-05-24
    Keywords: anthropogenic tracers; Area/locality; Arizona_1156; Arizona_1161; Arizona_1197; Arizona_1199; Arizona_570; Arizona_577; Arizona_579; Arizona_585; Arizona_602; Arizona_611; Arizona_625; Arizona_630; Arizona_635; Arizona_640; Arizona_661; Arizona_677; Arizona_678; California_198; California_200; California_201; California_202; California_205; California_208; California_470; California_473; California_480; California_485; California_487; California_491; California_495; California_542; California_549; California_561; California_562; California_563; California_564; California_731; California_733; California_738; California_756; California_772; California_779; California_781; California_785; California_872; California_879; California_882; California_883; California_884; California_885; California_887; California_888; California_889; California_898; California_901; California_904; California_909; California_913; California_914; California_917; DATE/TIME; Event label; HHS; Human hair sample; LATITUDE; Location ID; LONGITUDE; MC-ICP-MS; One-time_collection_1349; One-time_collection_1350; One-time_collection_1352; One-time_collection_1354; One-time_collection_1355; One-time_collection_1357; One-time_collection_1358; One-time_collection_1359; One-time_collection_1360; One-time_collection_1361; One-time_collection_1363; One-time_collection_1364; One-time_collection_1365; One-time_collection_1366; One-time_collection_1367; One-time_collection_1368; One-time_collection_1369; One-time_collection_1370; One-time_collection_1371; One-time_collection_1372; One-time_collection_1373; One-time_collection_1374; One-time_collection_1375; One-time_collection_1376; One-time_collection_1377; One-time_collection_1378; One-time_collection_1379; One-time_collection_1380; One-time_collection_1381; One-time_collection_1382; One-time_collection_1383; One-time_collection_1386; One-time_collection_1389; One-time_collection_1390; One-time_collection_1395; One-time_collection_1396; One-time_collection_1397; One-time_collection_1401; One-time_collection_1403; One-time_collection_1404; One-time_collection_1405; One-time_collection_1406; One-time_collection_1407; One-time_collection_1408; One-time_collection_1409; One-time_collection_1410; One-time_collection_1411; One-time_collection_1412; One-time_collection_1413; One-time_collection_1415; One-time_collection_1416; One-time_collection_1417; One-time_collection_1418; One-time_collection_1419; One-time_collection_1420; provenance analysis; Salt_Lake_Valley_1000; Salt_Lake_Valley_1001; Salt_Lake_Valley_1002; Salt_Lake_Valley_1003; Salt_Lake_Valley_1004; Salt_Lake_Valley_1005; Salt_Lake_Valley_1006; Salt_Lake_Valley_1007; Salt_Lake_Valley_1008; Salt_Lake_Valley_1009; Salt_Lake_Valley_1010; Salt_Lake_Valley_1011; Salt_Lake_Valley_1012; Salt_Lake_Valley_1013; Salt_Lake_Valley_1014; Salt_Lake_Valley_1015; Salt_Lake_Valley_1016; Salt_Lake_Valley_1017; Salt_Lake_Valley_1018; Salt_Lake_Valley_1019; Salt_Lake_Valley_248; Salt_Lake_Valley_249; Salt_Lake_Valley_250; Salt_Lake_Valley_251; Salt_Lake_Valley_342; Salt_Lake_Valley_413; Salt_Lake_Valley_421; Salt_Lake_Valley_432; Salt_Lake_Valley_996; Salt_Lake_Valley_997; Salt_Lake_Valley_998; Salt_Lake_Valley_999; Sample ID; stable isotope analysis; Strontium-87/Strontium-86 ratio; Strontium-87/Strontium-86 ratio, standard deviation; strontium isotopes; trace element; United States; water chemistry; water isotopes; water management; Year of observation
    Type: Dataset
    Format: text/tab-separated-values, 1655 data points
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  • 10
    Publication Date: 2023-07-06
    Description: The SOAP voyage examined air-sea interactions over the productive waters of the Chatham Rise, east of New Zealand onboard the RV Tangaroa (New Zealand National Institute of Water and Atmospheric Research, Wellington) from February 12 to March 7 (Law et al., 2017: doi:10.5194/acp-17-13645-2017). 23 seawater samples were collected throughout the voyage for the purpose of generating nascent SSA. Seawater samples were collected from the ocean surface during workboat operations (approximately 10 cm depth) or from the mixed layer (3 - 12 m depth, always less than the measured mixed layer depth) or deep water samples. Surface samples were collected in prewashed 5L PTFE bottles, subsurface measurements were colected in Niskin bottles onboard a CTD rosette. Nascent SSA was generated in-situ in a 0.45 m3 cylindrical polytetrafluoroethylene chamber housing four sintered glass filters with porosities between 16 and 250 μm (Cravigan et al., 2019: https://doi.org/10.5194/acp-2019-797). Dried and filtered compressed air was passed through the glass filters at a flow rate of 15.5 ± 3 L/min and resulting SSA was sampled from the headspace of the chamber. The volatility and hygroscopicity of nascent SSA was determined with a volatility and hygroscopicity tandem differential mobility analyser (VH-TDMA) (Johnson et al., 2004: doi:10.1016/j.jaerosci.2003.10.008, 2008: doi:10.1016/j.jaerosci.2008.05.005). A diffusion drier was used to dry the sample flow to 20 ± 5 % RH prior to characterisation by the VH-TDMA. The VH-TDMA used two TSI 3010 condensation particle counters. The aerosol sample flow rate for each scanning mobility particle sizer was 1 L/min, resulting in a total inlet flow of 2 L/min, the sheath flow for the pre-DMA, V-DMA and H-DMA were 11, 6 and 6 L/min, respectively. The dependence of HGF on RH at ambient temperature was measured for one water sample (workboat 9) to provide the deliquescence relative humidity (DRH). All VH-TDMA data were inverted using the TDMAinv algorithm (Gysel et al., 2009: doi:10.1016/j.jaerosci.2008.07.013). The seawater chlorophyll-a concentration was measured by filtering 2 litres of sample water onto GF/F Whatman filters, with immediate freezing in liquid nitrogen and subsequent analysis within 3 months of collection. Filters were ground and chlorophyll-a extracted in 90 % acetone with concentration determined by a calibrated fluorometer (Perkin-Elmer), with an analytical precision of 0.001 mg/m3 (Law et al., 2011: doi:10.1016/j.dsr2.2010.10.018).
    Keywords: aerosols; ccn; Chatham Rise; DATE/TIME; Depth, description; FTIR; functional groups; Humidity, relative; Humidity, relative, maximum; Humidity, relative, minimum; Hygroscopic growth factor; Hygroscopic growth factor, raw counts; hygroscopicity; IBA; ion beam; Particle, geometric median diameter; PTFE bottle, 5L; sea spray; SOAP; SOAP (Surface Ocean Aerosol Production); SSA; TAN1203; Tangaroa; TDMA; Temperature, water; volatility; Volatility-Hygroscopicity Tandem Differential Mobility Analyser (VH-TDMA); WB9
    Type: Dataset
    Format: text/tab-separated-values, 42292 data points
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