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    A new isolation device for shortening gene flow distance in small-scale transgenic maize breeding

    The GM maize material used was the GM insect-resistant maize variety (line) GIF, and the maize was a yellow grain strain provided by the Lai Jinsheng Teacher Laboratory of China Agricultural University. The conventional maize variety Meiyu 11 with white kernels was selected as the pollen receptor of GM maize. The inheritance of the seed (kernel) color can be considered to be a single gene, with one pair of alleles (yellow vs. white). The yellow allele is dominant, and the white allele is recessive. The experimental site was sown at the base of the agricultural GM environmental safety assessment of the Institute of Tropical Biotechnology, Chinese Academy of Tropical Agricultural Sciences, Wujitangxia Village, Maihao Town, Wenchang City, Hainan Province (110° 45′ 44″ E, 19° 32′ 14″ N). Transgenic insect-resistant maize was sown three times, once every other week, so that the pollination period of GM maize overlapped with the silking period of the non-GM maize. Artificial on-demand sowing with three seeds per hole and a 4–5 cm sowing depth was adopted.
    Field experiments were carried out during two seasons in 2016–2017 and 2017–2018. In the first planting season of 2016–2017, the farthest investigated distance of flow frequency was 60 m (Fig. 1A, Table 1). According to the results from the first investigation, the frequency of gene flow in the eight directions beyond 30 m was very low, almost zero (Table 1). Thus, in 2017–2018, the farthest investigated distance of flow frequency was adjusted to 30 m. In the second planting season, the total area was approximately 14,000 m2 (Fig. 1B, Table 2). As in Hainan off-season reproduction regions the work of breeding research institutes is particularly intensive, it is generally difficult to meet conventional isolation conditions. At the same time, this area also provided a reference for regions around the world that need close isolation. Therefore, we added bagging measures in the treatment areas during the maize tassel pollination period in the second planting season in order to further reduce the flow frequency.
    Figure 1

    Design of the experimental area. (A) In the period of 2016–2017, the design of the experimental area included one control area (A) and one isolation area (B). The dimensions of control area A and isolation area B in the figure are the same. (B) In the period from 2017 to 2018, the design of the experimental area included one control area (D) and three isolation areas (A, B and C). The solid line represents the isolation area, and the dashed line represents the control area without isolation devices. A1–A8 and B1–B8 in (A) and A1–A8, B1–B8, C1–C8 and D1–D8 in (B) represent eight directions of NE, N, NW, W, SW, S, SE and E, respectively. The dimensions of control area D and isolation areas A, B and C in the figure are the same. The blue numbers represent the size of the experimental areas. The green arrows represent the main wind direction during flowering.

    Full size image

    In the first year of the experiment, control and treatment areas were set up. The area of the control region was 10,000 m2 (100 m × 100 m). A 100 m2 (10 m × 10 m) plot was designated in the center for GM insect-resistant maize, and non-GM maize was planted around this central area. The treatment area with isolation measures was 10,000 m2 (100 m × 100 m). A 100 m2 (10 m × 10 m) plot was designated in the center for GM insect-resistant maize, and non-GM maize was planted around this area. Colored steel plates were used as an isolation measure. The isolation height was 4 m.
    A colored steel plate was the isolation material used in these experiments (Fig. 2). Colored steel plates and steel plates are two different materials. At present, there are many colors of colored steel plates. As for which color was used in our isolation experiments, there was no strict requirement, only a desire to match with the surrounding environment. Colored steel plates have the advantages of having both an organic polymer and a steel plate, and many organic polymers have good colorability, formability, corrosion resistance, decoration and high-strength. This combines with the workability of a steel plate, which can be easily finished by stamping, cutting, bending, deep drawing, and other processing to form virtually any shape. This makes the products made of colored steel plates have excellent practicability, decoration, processing and durability.
    Figure 2

    Isolation device for natural ecological risk control of GM maize. (A) Schematic of the isolation device; (B) partial diagram of the isolation device; (C) sectional view of figure (B); (D) structural detail diagram of the square card; 1: rectangular steel frame, 1.1: steel frame wall, 1.1a: horizontal steel rod, 1.1b: vertical steel rod, 2: inclined support rod, 3: colored steel plate, 4: door for entry and exit, 5: hot-dip galvanized steel frame. 6: structure of the square card, 6.1: screw.

    Full size image

    When maize was harvested after ripening, the investigated directions of control plots were NE, N, NW, W, SW, S, SE and E, labeled with A1–A8, respectively, and those of the isolation plots were labeled with B1–B8, respectively. The location of GM insect-resistant maize from 1 m, 3 m, 5 m, 10 m, 15 m, 20 m, 30 m, 40 m, 50 m and 60 m was investigated along these eight directions. The farthest investigation distances for NE, NW, SW and SE were 60 m, and other directions were 40 m. Ten maize plants were harvested randomly at each point (the first ear). Plants were marked in the order of P1, P2, P3, … P10, dried and stored for further testing. The total number of kernels harvested per corn ear was recorded.
    In the second year of the experiment, one control and three treatments were set up. The control plot and the three treatment areas with isolation measures covered an area of 3500 m2 (50 m × 70 m). A 100 m2 (10 m × 10 m) plot was designated in the center of the plot to plant GM maize, and non-GM maize was planted around this central area. Colored steel plates were used as an isolation measure. Bagging of tassels of transgenic maize plants was performed during the pollination period. No bagging was conducted in the control area.
    When the maize was harvested after ripening, the investigated directions of control plots were NE, N, NW, W, SW, S, SE and E, labeled D1, D2, D3, D4, D5, D6, D7 and D8, respectively. Isolation area A was marked A1, A2, A3, A4, A5, A6, A7 and A8 along the same eight directions. Isolation areas B and C were marked with B1, B2, B3, B4, B5, B6, B7 and B8, and C1, C2, C3, C4, C5, C6, C7 and C8, respectively. The location of GM insect-resistant maize from 1 m, 3 m, 5 m, 10 m, 15 m, 20 m and 30 m was investigated along these eight directions. The farthest investigation distances for NE, NW, SW and SE were 30 m, and the farthest investigation distances for N, W, S and E were 20 m. Ten maize plants were harvested randomly at each point (the first ear). Plants were marked in the order of P1, P2, P3, … P10, dried and stored for further testing. The total number of kernels harvested per corn ear was recorded.
    The endosperm was identified by dominant and recessive traits. According to the number of endosperm traits of GM insect-resistant maize harvested at different directions and distances from GM insect-resistant maize, the pollen transmission distance and outcrossing rate of GM insect-resistant maize were then determined. This method can only be applied to dominant endosperm traits such as yellow or non-waxy grains.
    The outcrossing rate was calculated according to formula (1):

    $$ P = frac{N}{T} times 100, $$
    (1)

    where P is the outcrossing rate percentage (%), N is the number of corn kernels containing exogenous genes (the number of the yellow seeds) per ear of corn in units of granules, and T is the total grains (the number of the yellow seeds and white seeds) per ear in units of granules. The outcrossing rates of exogenous genes in different directions and distances were determined, and then the pollen flow distance was determined.
    As descriptive statistics, the arithmetic mean as well the standard deviation of outcrossing rates were calculated. The outcrossing rate at each point (1 m, 3 m, 5 m, … 60 m) in the experiment was the mean of the outcrossing rate (P1, P2, P3, … P10) of 10 corn plants at that point.
    Details of the isolation device for gene flow risk control of GM maize
    The isolation device for gene flow risk control of GM maize, as shown in Fig. 2, comprises a rectangular steel frame (1). The rectangular steel frame 1 was composed of four steel frame walls (1.1), each of which was composed of multiple horizontal steel poles (1.1a) and vertical steel poles (1.1b). Each vertical steel pole was fixed 20–30 cm deep in the soil, and the angle between the inclined support pole (2) and the vertical steel pole was 30°–45°. The vertical steel pole of the four steel frame walls intersected the horizontal steel pole of the top. There were eight inclined supporting poles at the intersection of the vertical steel pole at the four corners of the rectangular steel frame and the horizontal steel pole at the top of the rectangular steel frame, and one inclined supporting pole was fixed through the square card structure (6). The four-sided steel frame wall of the rectangular steel frame was equipped with a colored steel plate (3), and one side of the isolation device was provided with an entry and exit (4). Horizontal steel bars at the top of the rectangular steel frame were provided with a hot-dip galvanized steel frame (5). The hot-dip supporting steel frame was a quadrilateral, and the four corners of the hot-dip supporting steel frame were fixed in the middle of the horizontal steel pole through the hoop. The clamp structure (6) included a side opening and a hollow rectangular frame. The top of the inclined support rod was obliquely inserted into the square clamp structure and fixed on the vertical steel rod through a screw (6.1). The dimensions of the steel rod and the inclined supporting rod were 6000 mm in length, 40 mm in diameter and 2 mm in thickness, and the colored steel plate was 0.425 mm in thickness. The size of the device and the number of inclined supporting rods were determined according to the actual situation in the field. More

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    Dynamics of localised nitrogen supply and relevance for root growth of Vicia faba (‘Fuego’) and Hordeum vulgare (‘Marthe’) in soil

    1.
    Forde, B. & Lorenzo, H. The nutritional control of root development. Plant Soil 232, 51–68. https://doi.org/10.1023/A:1010329902165 (2001).
    CAS  Article  Google Scholar 
    2.
    Hodge, A. The plastic plant: root responses to heterogeneous supplies of nutrients. New Phytol. 162, 9–24. https://doi.org/10.1111/j.1469-8137.2004.01015.x (2004).
    Article  Google Scholar 

    3.
    Robinson, D. Tansley review no 73. The responses of plants to non-uniform supplies of nutrients. New Phytol. 127, 635–674 (1994).
    CAS  Article  Google Scholar 

    4.
    Yu, P., White, P. J., Hochholdinger, F. & Li, C. Phenotypic plasticity of the maize root system in response to heterogeneous nitrogen availability. Planta 240, 667–678. https://doi.org/10.1007/s00425-014-2150-y (2014).
    CAS  Article  PubMed  Google Scholar 

    5.
    Osmont, K. S., Sibout, R. & Hardtke, C. S. Hidden branches: developments in root system architecture. Annu. Rev. Plant Biol. 58, 93–113. https://doi.org/10.1146/annurev.arplant.58.032806.104006 (2007).
    CAS  Article  PubMed  Google Scholar 

    6.
    Ahmed, S. et al. Imaging the interaction of roots and phosphate fertiliser granules using 4D X-ray tomography. Plant Soil 401, 125–134. https://doi.org/10.1007/s11104-015-2425-5 (2016).
    CAS  Article  Google Scholar 

    7.
    Drew, M. & Saker, L. Nutrient supply and the growth of the seminal root system in barley III. Compensatory increases in growth of lateral roots, and in rates of phosphate uptake, in response to a localized supply of phosphate. J. Exp. Bot. 29, 435–451 (1978).
    CAS  Article  Google Scholar 

    8.
    Flavel, R. J., Guppy, C. N., Tighe, M. K., Watt, M. & Young, I. M. Quantifying the response of wheat (Triticum aestivum L.) root system architecture to phosphorus in an Oxisol. Plant Soil 385, 303–310. https://doi.org/10.1007/s11104-014-2191-9 (2014).
    CAS  Article  Google Scholar 

    9.
    Nacry, P., Bouguyon, E. & Gojon, A. Nitrogen acquisition by roots: physiological and developmental mechanisms ensuring plant adaptation to a fluctuating resource. Plant Soil 370, 1–29. https://doi.org/10.1007/s11104-013-1645-9 (2013).
    CAS  Article  Google Scholar 

    10.
    Bloom, A. J., Frensch, J. & Taylor, A. R. Influence of inorganic nitrogen and pH on the elongation of maize seminal roots. Ann. Bot. 97, 867–873. https://doi.org/10.1093/aob/mcj605 (2006).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    11.
    Bloom, A. J., Jackson, L. E. & Smart, D. R. Root-growth as a function of ammonium and nitrate in the root zone. Plant Cell Environ. 16, 199–206. https://doi.org/10.1111/j.1365-3040.1993.tb00861.x (1993).
    CAS  Article  Google Scholar 

    12.
    Caba, J. M., Centeno, M. L., Fernandez, B., Gresshoff, P. M. & Ligero, F. Inoculation and nitrate alter phytohormone levels in soybean roots: differences between a supernodulating mutant and the wild type. Planta 211, 98–104. https://doi.org/10.1007/s004250000265 (2000).
    CAS  Article  PubMed  Google Scholar 

    13.
    Gerendás, J. & Sattelmacher, B. Influence of nitrogen form and concentration on growth and ionic balance of tomato (Lycopersicon esculentum) and potato (Solanum tuberosum). In Plant nutrition—physiology and applications (ed. van Beusichem, M. L.) 33–37 (Springer, Berlin, 1990).
    Google Scholar 

    14.
    Granato, T. C. & Raper, C. D. Jr. Proliferation of maize (Zea mays L.) roots in response to localized supply of nitrate. J. Exp. Bot. 40, 263–275. https://doi.org/10.1093/jxb/40.2.263 (1989).
    CAS  Article  PubMed  Google Scholar 

    15.
    Maizlish, N., Fritton, D. & Kendall, W. Root morphology and early development of maize at varying levels of nitrogen 1. Agron. J. 72, 25–31 (1980).
    CAS  Article  Google Scholar 

    16.
    Ogawa, S., Valencia, M. O., Ishitani, M. & Selvaraj, M. G. Root system architecture variation in response to different NH4+ concentrations and its association with nitrogen-deficient tolerance traits in rice. Acta Physiol. Plant. 36, 2361–2372. https://doi.org/10.1007/s11738-014-1609-6 (2014).
    CAS  Article  Google Scholar 

    17.
    Sattelmacher, B. & Thoms, K. Root growth and 14C-translocation into the roots of maize (Zea mays L.) as influenced by local nitrate supply. J. Plant Nutr. Soil Sci. 152, 7–10 (1989).
    CAS  Google Scholar 

    18.
    Schortemeyer, M., Feil, B. & Stamp, P. Root morphology and nitrogen uptake of maize simultaneously supplied with ammonium and nitrate in a split-root system. Ann. Bot. 72, 107–115. https://doi.org/10.1006/anbo.1993.1087 (1993).
    CAS  Article  Google Scholar 

    19.
    Thoms, K. & Sattelmacher, B. Influence of nitrate placement on morphology and physiology of maize (Zea mays) root systems. In Plant nutrition—physiology and applications (ed van Beusichem, M. L.) 29–32 (Springer, Berlin, 1990).
    Google Scholar 

    20.
    Tian, Q., Chen, F., Liu, J., Zhang, F. & Mi, G. Inhibition of maize root growth by high nitrate supply is correlated with reduced IAA levels in roots. J. Plant Physiol. 165, 942–951. https://doi.org/10.1016/j.jplph.2007.02.011 (2008).
    CAS  Article  PubMed  Google Scholar 

    21.
    Gruber, B. D., Giehl, R. F., Friedel, S. & von Wiren, N. Plasticity of the Arabidopsis root system under nutrient deficiencies. Plant Physiol. 163, 161–179. https://doi.org/10.1104/pp.113.218453 (2013).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    22.
    Lima, J. E., Kojima, S., Takahashi, H. & von Wiren, N. Ammonium triggers lateral root branching in Arabidopsis in an AMMONIUM TRANSPORTER1;3-dependent manner. Plant Cell 22, 3621–3633. https://doi.org/10.1105/tpc.110.076216 (2010).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    23.
    Remans, T. et al. The Arabidopsis NRT1.1 transporter participates in the signaling pathway triggering root colonization of nitrate-rich patches. Proc. Natl. Acad. Sci. U. S. A. 103, 19206–19211. https://doi.org/10.1073/pnas.0605275103 (2006).
    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

    24.
    Zhang, H. & Forde, B. G. An Arabidopsis MADS box gene that controls nutrient-induced changes in root architecture. Science 279, 407–409. https://doi.org/10.1126/science.279.5349.407 (1998).
    ADS  CAS  Article  PubMed  Google Scholar 

    25.
    Zhang, H., Jennings, A., Barlow, P. W. & Forde, B. G. Dual pathways for regulation of root branching by nitrate. Proc. Natl. Acad. Sci. U.S.A. 96, 6529–6534. https://doi.org/10.1073/pnas.96.11.6529 (1999).
    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

    26.
    Drew, M. Comparison of the effects of a localised supply of phosphate, nitrate, ammonium and potassium on the growth of the seminal root system, and the shoot, in barley. New Phytol. 75, 479–490 (1975).
    CAS  Article  Google Scholar 

    27.
    Drew, M. & Saker, L. Nutrient Supply and the Growth of the Seminal Root System in Barley II. Localized, compensatory increases in lateral root growth and rates of nitrate uptake when nitrate supply is restricted to only part of the root system. J. Exp. Bot. 26, 79–90 (1975).
    CAS  Article  Google Scholar 

    28.
    Drew, M., Saker, L. & Ashley, T. Nutrient supply and the growth of the seminal root system in barley I. The effect of nitrate concentration on the growth of axes and laterals. J. Exp. Bot. 24, 1189–1202 (1973).
    CAS  Article  Google Scholar 

    29.
    Beeckman, F., Motte, H. & Beeckman, T. Nitrification in agricultural soils: impact, actors and mitigation. Curr. Opin. Biotechnol. 50, 166–173. https://doi.org/10.1016/j.copbio.2018.01.014 (2018).
    CAS  Article  PubMed  Google Scholar 

    30.
    Heil, J., Vereecken, H. & Bruggemann, N. A review of chemical reactions of nitrification intermediates and their role in nitrogen cycling and nitrogen trace gas formation in soil. Eur. J. Soil Sci. 67, 23–39. https://doi.org/10.1111/ejss.12306 (2016).
    CAS  Article  Google Scholar 

    31.
    Blume, H.-P. et al. Scheffer/Schachtschabel Soil Science (Springer, Berlin, 2015).
    Google Scholar 

    32.
    Nieder, R., Benbi, D. K. & Scherer, H. W. Fixation and defixation of ammonium in soils: a review. Biol. Fertil. Soils 47, 1–14. https://doi.org/10.1007/s00374-010-0506-4 (2011).
    CAS  Article  Google Scholar 

    33.
    Nommik, H. & Vahtras, K. Retention and fixation of ammonium and ammonia in soils. In Nitrogen in Agricultural Soils 22, (ed. Stevenson, F. J.) 123–171 (Wiley, Madison, Wisconsin, USA, 1982).
    Google Scholar 

    34.
    Morris, E. C. et al. Shaping 3D root system architecture. Curr. Biol. 27, R919–R930. https://doi.org/10.1016/j.cub.2017.06.043 (2017).
    CAS  Article  PubMed  Google Scholar 

    35.
    Anghinoni, I. & Barber, S. A. Corn root-growth and nitrogen uptake as affected by ammonium placement. Agron. J. 80, 799–802. https://doi.org/10.2134/agronj1988.00021962008000050021x (1988).
    Article  Google Scholar 

    36.
    Anghinoni, I., Magalhaes, J. R. & Barber, S. A. Enzyme-activity, nitrogen uptake and corn growth as affected by ammonium concentration in soil solution. J. Plant Nutr. 11, 131–144. https://doi.org/10.1080/01904168809363791 (1988).
    CAS  Article  Google Scholar 

    37.
    Pan, W. L., Madsen, I. J., Bolton, R. P., Graves, L. & Sistrunk, T. Ammonia/ammonium toxicity root symptoms induced by inorganic and organic fertilizers and placement. Agron. J. 108, 2485–2492. https://doi.org/10.2134/agronj2016.02.0122 (2016).
    CAS  Article  Google Scholar 

    38.
    Xu, L. et al. Nitrogen transformation and plant growth in response to different urea-application methods and the addition of DMPP. J. Plant Nutr. Soil Sci. 177, 271–277. https://doi.org/10.1002/jpln.201100390 (2014).
    CAS  Article  Google Scholar 

    39.
    Zhang, J. C. & Barber, S. A. Corn root distribution between ammonium fertilized and unfertilized soil. Commun. Soil Sci. Plant Anal. 24, 411–419. https://doi.org/10.1080/00103629309368811 (1993).
    Article  Google Scholar 

    40.
    Maestre, F. T. & Reynolds, J. F. Small-scale spatial heterogeneity in the vertical distribution of soil nutrients has limited effects on the growth and development of Prosopis glandulosa seedlings. Plant Ecol. 183, 65–75. https://doi.org/10.1007/s11258-005-9007-1 (2006).
    Article  Google Scholar 

    41.
    Rabbi, S. M., Guppy, C., Flavel, R., Tighe, M. & Young, I. Root plasticity not evident in N-enriched soil volumes for wheat (Triticum aestivum L.) and Barley (Hordeum vulgare L.) varieties. Commun. Soil Sci. Plant Anal. 48, 2002–2012 (2017).
    CAS  Article  Google Scholar 

    42.
    Van Vuuren, M., Robinson, D. & Griffiths, B. Nutrient inflow and root proliferation during the exploitation of a temporally and spatially discrete source of nitrogen in soil. Plant Soil 178, 185–192 (1996).
    Article  Google Scholar 

    43.
    Hodge, A., Robinson, D., Griffiths, B. S. & Fitter, A. H. Why plants bother: root proliferation results in increased nitrogen capture from an organic patch when two grasses compete. Plant Cell Environ. 22, 811–820. https://doi.org/10.1046/j.1365-3040.1999.00454.x (1999).
    Article  Google Scholar 

    44.
    Hodge, A., Stewart, J., Robinson, D., Griffiths, B. S. & Fitter, A. H. Root proliferation, soil fauna and plant nitrogen capture from nutrient-rich patches in soil. New Phytol. 139, 479–494. https://doi.org/10.1046/j.1469-8137.1998.00216.x (1998).
    Article  Google Scholar 

    45.
    Hodge, A., Stewart, J., Robinson, D., Griffiths, B. S. & Fitter, A. H. Plant, soil fauna and microbial responses to N-rich organic patches of contrasting temporal availability. Soil Biol. Biochem. 31, 1517–1530. https://doi.org/10.1016/S0038-0717(99)00070-X (1999).
    CAS  Article  Google Scholar 

    46.
    Li, H. B. et al. Root morphological responses to localized nutrient supply differ among crop species with contrasting root traits. Plant Soil 376, 151–163. https://doi.org/10.1007/s11104-013-1965-9 (2014).
    CAS  Article  Google Scholar 

    47.
    Abalos, D., Sanz-Cobena, A., Misselbrook, T. & Vallejo, A. Effectiveness of urease inhibition on the abatement of ammonia, nitrous oxide and nitric oxide emissions in a non-irrigated Mediterranean barley field. Chemosphere 89, 310–318. https://doi.org/10.1016/j.chemosphere.2012.04.043 (2012).
    ADS  CAS  Article  PubMed  Google Scholar 

    48.
    Slangen, J. H. G. & Kerkhoff, P. Nitrification inhibitors in agriculture and horticulture—a literature-review. Fertil. Res. 5, 1–76. https://doi.org/10.1007/Bf01049492 (1984).
    CAS  Article  Google Scholar 

    49.
    Zaman, M., Zaman, S., Nguyen, M. L., Smith, T. J. & Nawaz, S. The effect of urease and nitrification inhibitors on ammonia and nitrous oxide emissions from simulated urine patches in pastoral system: a two-year study. Sci. Tot. Environ. 465, 97–106. https://doi.org/10.1016/j.scitotenv.2013.01.014 (2013).
    CAS  Article  Google Scholar 

    50.
    Metzner, R. et al. Direct comparison of MRI and X-ray CT technologies for 3D imaging of root systems in soil: potential and challenges for root trait quantification. Plant Methods 11, 17. https://doi.org/10.1186/s13007-015-0060-z (2015).
    Article  PubMed  PubMed Central  Google Scholar 

    51.
    Beuters, P., Scherer, H. W., Spott, O. & Vetterlein, D. Impact of potassium on plant uptake of non-exchangeable NH4+-N. Plant Soil 387, 37–47. https://doi.org/10.1007/s11104-014-2275-6 (2014).
    CAS  Article  Google Scholar 

    52.
    Vetterlein, D., Kuhn, T., Kaiser, K. & Jahn, R. Illite transformation and potassium release upon changes in composition of the rhizophere soil solution. Plant Soil 371, 267–279. https://doi.org/10.1007/s11104-013-1680-6 (2013).
    CAS  Article  Google Scholar 

    53.
    VDLUFA, M. Band 1. Die Untersuchung von Böden (VDLUFA-Verlag, Darmstad, 1991) ((in German)).
    Google Scholar 

    54.
    Koebernick, N. et al. In situ visualization and quantification of three-dimensional root system architecture and growth using X-ray computed tomography. Vadose Zone J. https://doi.org/10.2136/vzj2014.03.0024 (2014).
    Article  Google Scholar 

    55.
    Blaser, S. R. G. A., Schlüter, S. & Vetterlein, D. How much is too much?-Influence of X-ray dose on root growth of faba bean (Vicia faba) and barley (Hordeum vulgare). PLoS ONE 13, e0193669. https://doi.org/10.1371/journal.pone.0193669 (2018).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    56.
    Schlüter, S., Blaser, S. R. G. A., Weber, M., Schmidt, V. & Vetterlein, D. Quantification of root growth patterns from the soil perspective via root distance models. Front. Plant Sci. 9, 1084. https://doi.org/10.3389/fpls.2018.01084 (2018).
    Article  PubMed  PubMed Central  Google Scholar 

    57.
    Flavel, R. J. et al. Non-destructive quantification of cereal roots in soil using high-resolution X-ray tomography. J. Exp. Bot. 63, 2503–2511. https://doi.org/10.1093/jxb/err421 (2012).
    CAS  Article  PubMed  Google Scholar 

    58.
    Doube, M. et al. BoneJ: free and extensible bone image analysis in ImageJ. Bone 47, 1076–1079. https://doi.org/10.1016/j.bone.2010.08.023 (2010).
    Article  PubMed  PubMed Central  Google Scholar 

    59.
    Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682. https://doi.org/10.1038/nmeth.2019 (2012).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    60.
    Kirschke, T., Spott, O. & Vetterlein, D. Impact of urease and nitrification inhibitor on NH4+ and NO3− dynamic in soil after urea spring application under field conditions evaluated by soil extraction and soil solution sampling. J. Plant Nutr. Soil Sci. 182, 441–450. https://doi.org/10.1002/jpln.201800513 (2019).
    CAS  Article  Google Scholar 

    61.
    61Bergmann, W. Farbatlas Ernährungsstörungen bei Kulturpflanzen: visuelle und analytische Diagnose. (1986).

    62.
    Bennett, W. F., Pesek, J. & Hanway, J. J. Effect of nitrate and ammonium on growth of corn in nutrient solution sand culture. Agron. J. 56, 342–345 (1964).
    CAS  Article  Google Scholar 

    63.
    Magalhaes, J. R. & Wilcox, G. E. Tomato growth and nutrient-uptake patterns as influenced by nitrogen form and light-intensity. J. Plant Nutr. 6, 941–956. https://doi.org/10.1080/01904168309363157 (1983).
    CAS  Article  Google Scholar 

    64.
    Ganmore-Neumann, R. & Kafkafi, U. root temperature and percentage NO3−/NH4+ effect on tomato plant development I. Morphology and growth 1. Agron. J. 72, 758–761 (1980).
    CAS  Article  Google Scholar 

    65.
    Einsmann, J. C., Jones, R. H., Pu, M. & Mitchell, R. J. Nutrient foraging traits in 10 co-occurring plant species of contrasting life forms. J. Ecol. 87, 609–619. https://doi.org/10.1046/j.1365-2745.1999.00376.x (1999).
    Article  Google Scholar 

    66.
    Gao, W., Blaser, S. R. G. A., Schluter, S., Shen, J. B. & Vetterlein, D. Effect of localised phosphorus application on root growth and soil nutrient dynamics in situ—comparison of maize (Zea mays) and faba bean (Vicia faba) at the seedling stage. Plant Soil 441, 469–483. https://doi.org/10.1007/s11104-019-04138-2 (2019).
    CAS  Article  Google Scholar 

    67.
    Britto, D. T. & Kronzucker, H. J. NH4+ toxicity in higher plants: a critical review. J. Plant Physiol. 159, 567–584. https://doi.org/10.1078/0176-1617-0774 (2002).
    CAS  Article  Google Scholar 

    68.
    Adjel, F., Bouzerzour, H. & Benmahammed, A. Salt stress effects on seed germination and seedling growth of barley (Hordeum vulgare L.) Genotypes. J. Agric. Sustain. 3, 223–237 (2013).
    Google Scholar 

    69.
    Ahmed, A. K., Tawfik, K. & Abd El-Gawad, Z. Tolerance of seven faba bean varieties to drought and salt stresses. Res. J. Agric. Biol. Sci. 4, 175–186 (2008).
    Google Scholar 

    70.
    Link, W. et al. Genotypic variation for drought tolerance in Vicia faba. Plant Breed. 118, 477–483. https://doi.org/10.1046/j.1439-0523.1999.00412.x (1999).
    Article  Google Scholar 

    71.
    Varshney, R. K. et al. Genome wide association analyses for drought tolerance related traits in barley (Hordeum vulgare L.). Field Crops Res. 126, 171–180. https://doi.org/10.1016/j.fcr.2011.10.008 (2012).
    Article  Google Scholar 

    72.
    Wilcox, G. E., Magalhaes, J. R. & Silva, F. L. I. M. Ammonium and nitrate concentrations as factors in tomato growth and nutrient-uptake. J. Plant Nutr. 8, 989–998. https://doi.org/10.1080/01904168509363401 (1985).
    Article  Google Scholar 

    73.
    Elamin, O. M. & Wilcox, G. E. Nitrogen form ratio influence on muskmelon growth, composition, and manganese toxicity. J. Am. Soc. Hortic. Sci. 111, 320–322 (1986).
    Google Scholar 

    74.
    Handa, S., Warren, H. L., Huber, D. M. & Tsai, C. Y. Nitrogen nutrition and seedling development of normal and opaque-2 maize genotypes. Can. J. Plant Sci. 64, 885–894. https://doi.org/10.4141/cjps84-121 (1984).
    CAS  Article  Google Scholar  More

  • in

    Comparison of gut microbiota in exclusively breast-fed and formula-fed babies: a study of 91 term infants

    We found that in breast-fed group, α diversity remained unchanged before 3 months of age, but increased significantly in 6 months of age. Previously studies have reported that faecal bacterial diversity increases with age, indicating a more complex microbial community over time8,9. Studies have shown that infants who are exclusively breast-fed have lower microbial diversity, compared with formula-fed babies whose gut microbiota is more diverse and similar to older children10,11,12. The difference of gut microbial diversity between breast-fed and formula-fed babies is also reported in animal research in tiger cubs13. We also found that among different groups, α diversity was lower in breast-fed group than formula-fed groups in 40 days of age. In adults, low gut microbial diversity has been linked to diseases in recent studies. In infants, breast milk may be the major determinant of a lower gut microbial diversity, because specific bacteria are selected for degrading particular oligosaccharides in breast milk. The predomination of infant-type Bifidobacteria during breastfeeding results in a low bacterial diversity, but it is beneficial for babies’ health. For example, the infant-type Bifidobacteria has a large impact on the maturation of the immune system, which may help reduce the incidence of infections in children. However, some diseases have been associated with a reduced microbial diversity in early life, such as eczema and asthma, which have been linked to low microbial diversity in 1 week–4 months of age. But the low microbial diversity is not coupled to Bifidobacterium abundance in these studies, and no reports have shown negative impacts of breastfeeding on development of asthma or allergies. The causality of lower diversity to diseases remains to be identified. What’s more, research has suggested that an immature gut microbial community can be “repaired” by introduction of adult-like microbes increasing greatly during introduction of solid foods in 6 months of age, which is within the development window of opportunity. Findings in adults cannot be inferred to infants regarding the association of gut microbial diversity with diseases, since the microbial ecosystem and the immune system of infants are quite different from adults4.
    Bifidobacterium represented the most predominant genus and Enterobacteriaceae the second in all groups at all time-points in our study. Previous study also indicates that all infants have significant levels of Enterobacteriaceae and Bifidobacteriaceae at family level in 2 months of age. The abundance of a single genus usually constitutes the most in family level evaluation. Roger et al. have indicated that Bifidobacterium accounts for 40–60% on average of the total faecal microbiota of a 2-week old new born10. In our study, in 40 days of age, Bifidobacterium accounted for 46.2% in breast-fed group, and 32.2–33.0% in formula-fed groups, which was precisely classified according to feeding types. Bifidobacterium is present in the first few months and decreases as age goes on to almost zero by 18 months old14. Enterobacteriaceae also decreases with time7,8. This is consistent with the European study of 531 infants, which indicates the decrease trend in Bifidobacteriaceae and Enterobacteriaceae species from 6 weeks of age until 4 weeks after solid foods introduction, regardless of differences in feeding patterns15. We found that in breast-fed group, Bifidobacterium decreased from 46.2% in 40 days to 41.4% in 3 months and 29.9% in 6 months of age. In formula-fed groups, after solid foods introduction, Bifidobacterium decreased from 32.2% in 3 months to 31.7% in 6 months of age in formula A group, but increased from 33.0 to 39.0% in formula B group, indicating that different formulas may have different effects on microbiota. In our study, solid foods were introduced from 4 to 6 months of age, so they affected only the last time point in 6 m. We found that in 40 days of age, Bifidobacterium and Bacteroides were significantly higher, while Streptococcus and Enterococcus copy numbers were significantly lower in breast-fed group than they were in formula A-fed group. Lachnospiraceae was lower in breast-fed group than that in formula B-fed group. Veillonella and Clostridioides were lower in breast-fed group than that in formula A and B-fed groups. In 3 months of age there were less Lachnospiraceae and Clostridioides in breast-fed group than formula-fed groups. Other differences of microbiota were shown in Figs. 5 and 6.
    After birth, the most important determinant of infant gut microbial colonization is breastfeeding. Studies have shown that breastfeeding is associated with higher levels of Bifidobacterium1,2,16, which is consistent with our study. The genus Bifidobacterium possesses multiple benefits, such as modulation of the immune system, production of vitamins, remission of atopic dermatitis symptoms in infants and decrease in rotavirus infections and lactose intolerance in children and adults10,17. Bifidobacteria is reported to be associated with diminished risk of allergic diseases18 and excessive weight gain19. Higher level of Bifidobacteria also indicates better immune responses to vaccines20.
    Bacteroides is among several beneficial bacteria in the earlier neonatal phase, which has important and specific functions in the development of mucosal immune system6. The early activation of mucosal immune system may provide human body lifelong protection from health disorders6. Bacteroides is also linked with increased diversity and faster maturation of gut2. Koenig has studied 1 baby for 2.5 years after its birth and found that Bacteroides genus is absent before the introduction of solid foods21. However, Yassour M. et al. have reported that many infants present a significant Bacteroides species in the first 6 months, before the introduction of solid foods, in a longitudinal study of 39 children in their first 3 years of life14. We also found that there was Bacteroides in the first 6 months of life in all groups. Bacteroides was significantly higher in breast-fed infants, ranking third in 40 days (0.095) in breast-fed group, but decreased as time went on to 0.059 in 3 m and 0.039 in 6 m.
    Besides Bacteroides, other health promoting bacteria like Clostridia has been reported to be vital to provide mucosal barrier homeostasis during the neonatal period, which is necessary in the immature intestine6. Formula-fed infants tend to have a more diverse microbial community with increased Clostridia species9,12, which is in accordance with our finding. We also found Veillonella was lower in breast-fed infants than formula-fed ones. Although there is an analysis indicating that Veillonella has been associated with a lower incidence of asthma, it has not taken feeding patterns into consideration22. So more data are needed to clarify the specific roles of certain bacteria with regard to feeding types.
    Studies have shown that breast milk keeps the gut in a condition with a lower abundance of Veillonellaceae, Enterococcaceae, Streptococcaceae9,11,23 and Lachnospiraceae7, which is consistent with our results. Some researchers have indicated that higher level of Streptococcus sp. is seen in patients suffered from type 1 diabetes2. There may be other negative effects of these bacteria, but we still know little about them.
    The subsequent big change in diet is the introduction of solid foods in 4–6 months of age, which is largely associated with changes in infant gut microbiota. A case study has found an increase in Bacteroidetes at phylum level after solid foods are introduced21. They have indicated that Bacteroidetes is specialized in the decomposition of complex plant polysaccharides21, and it is also associated with faster maturation of the intestinal microbial community2. In our study, after solid foods introduction, percentage of Bacteroides at genus level increased in formula A-fed group, from 0.023 to 0.028, but kept almost the same from 0.009 to 0.008 in formula B-fed group. While in breast-fed group, a decreased percentage of Bacteroides was found from 0.059 in 3 m to 0.039 in 6 m. The trends are different according to different feeding patterns. Pannaraj et al. believe that daily breastfeeding as a part of milk intake continues to affect the infant gut microbial composition, even after solid foods introduction8. But in our study, differences in gut microbiota between breast-fed group and formula-fed groups were not seen any more after solid foods were introduced. As for studies of gut microbiota, the taxonomic level of bacteria adopted in research may affect the results. We focused on microbiota mainly at genus level, resulting in certain discrepancies with some other articles at phylum or species level.
    There were significant differences of microbiota between formula A-fed and formula B-fed groups in our study. We found that Pediococcus was less in formula A-fed group than that in formula B-fed group in 40 days. Many research articles have not taken the differences of formulas into consideration, especially retrospective studies. Even breast-fed group is mixed with formulas in some reports. So there must be some inaccuracies of their findings.
    Except for feeding patterns, several factors are associated with the microbiota over the first year of life, which is a key period for the gut colonization, such as the mode of delivery, antibiotic exposure, geographical location, household siblings, and furry pets2,9. During the first days of life, the gut microbiota in infants born by vaginal delivery (VD) is similar to that in maternal vagina and intestinal tract, whereas in infants born by caesarean section delivery (CS) the gut microbiota shares characteristics with that of maternal skin. We noticed that the genera of Bacteroides and Parabacteroides were negatively correlated with CS. This was consistent with findings in many other studies, in which the difference of Bacteroides remains in 4 and 12 months of age7,9, and we also found the negative correlation of Bacteroides with CS existed not only in 40 days but also in 6 months of age. The increased morbidity reported extensively in infants born by CS is likely led by altered early gut colonization partially24. Accumulating data have indicated that antibiotic-mediated gut microbiota turbulence during the vital developmental window in early life period may lead to increased risk for chronic non-infectious diseases in later life24. There is a high detection rate of gut Enterococcus in antibiotic-treated infants in their early postnatal period among 26 infants born in a mean gestational age of 39 weeks25. We also found that the relative abundance of Enterococcus was positively correlated with antibiotics usage. The overgrowth of Enterococcus may be caused by antibiotic selection25.
    In conclusion, by a larger cohort study than before, differences in gut microbiota among infants who were fed exclusively by breast milk or a single kind of formulas were obtained from this study, contributing further to our understanding of early gut microbial colonization, with more solid data than previous studies with mixed feeding patterns. Faecal diversity was lower in breast-fed infants than formula-fed ones in early life period, but increased significantly after solid foods introduction. A low diversity of the gut microbiota in early life appeared to characterize a healthy gut, if caused by breastfeeding, which was different from theories in adults. There were differences in bacterial composition in infants according to different feeding types, and even different formulas had different effects on microbiota, which we could not ignore in future research. This study presented initial data facilitating further research that will help us understand the importance of breastfeeding to gut microbiota in early life period. More

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    Contribution to the reproductive ecology of Notoscopelus resplendens (Richardson, 1845) (Myctophidae) in the Central-Eastern Atlantic

    1.
    Benoit-Bird, K. J. & Au, W. W. L. Energy: Converting from acoustic to biological resource units. J. Acoust. Soc. Am. 111, 2070 (2002).
    ADS  PubMed  Article  Google Scholar 
    2.
    Simard, Y. & Mackas, D. L. Mesoscale aggregations of euphausiid sound scattering layers on the continental shelf of Vancouver Island. Can. J. Fish. Aquat. Sci. 46, 1238–1249 (1989).
    Article  Google Scholar 

    3.
    Ariza, A., Garijo, J. C., Landeira, J. M., Bordes, F. & Hernández-León, S. Migrant biomass and respiratory carbon flux by zooplankton and micronekton in the subtropical northeast Atlantic Ocean (Canary Islands). Prog. Oceanogr. https://doi.org/10.1016/j.pocean.2015.03.003 (2015).
    Article  Google Scholar 

    4.
    Ariza, A. et al. Vertical distribution, composition and migratory patterns of acoustic scattering layers in the Canary Islands. J. Mar. Syst. https://doi.org/10.1016/j.jmarsys.2016.01.004 (2016).
    Article  Google Scholar 

    5.
    Hays, G. C. A review of the adaptive significance and ecosystem consequences of zooplankton diel vertical migrations. Hydrobiologia 503, 163–170 (2003).
    Article  Google Scholar 

    6.
    Yatsu, A., Sassa, C., Moku, M. & Kinoshita, T. Night-time vertical distribution and abundance of small epipelagic and mesopelagic fishes in the upper 100 m layer of the Kuroshio–Oyashio Transition Zone in Spring. Fish. Sci. 71, 1280–1286 (2005).
    CAS  Article  Google Scholar 

    7.
    Olson, R. J. et al. Bioenergetics, Trophic Ecology, and Niche Separation of Tunas. (Advances in Marine Biology, 2016).

    8.
    Hudson, J. M., Steinberg, D. K., Sutton, T. T., Graves, J. E. & Latour, R. J. Myctophid feeding ecology and carbon transport along the northern Mid-Atlantic Ridge. Deep Res. Part I Oceanogr. Res. Pap. https://doi.org/10.1016/j.dsr.2014.07.002 (2014).
    Article  Google Scholar 

    9.
    Guidi, L. et al. A new look at ocean carbon remineralization for estimating deepwater sequestration. Global Biogeochem. Cy. 29, 1044–1059 (2015).
    ADS  CAS  Article  Google Scholar 

    10.
    van Noord, J. E. Diet of five species of the family Myctophidae caught off the Mariana Islands. Ichthyol. Res. 60, 89–92 (2013).
    Article  Google Scholar 

    11.
    Lam, V. & Pauly, D. Mapping the global biomass of mesopelagic fishes. Sea Around Us Proj. Newsl. 30, 4 (2005).
    Google Scholar 

    12.
    Irigoien, X. et al. Large mesopelagic fishes biomass and trophic efficiency in the open ocean. Nat. Commun. 5, 3271 (2014).
    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

    13.
    Hulley, P. A. Results of the research cruises of FRV” Walther Herwig” to South America. LVIII. Family Myctophidae (Osteichthyes, Myctophiformes). Arch. für Fischereiwiss. 31, 1–300 (1981).
    Google Scholar 

    14.
    Hulley, P. A. Myctophidae. In Check-List of the FISHES of the Eastern Tropical Atlantic (CLOFETA) (eds Quero, J. C., Hureau, J. C., Karrer, C., Post, A. & Saldanha, L.) 398–467 (1990).

    15.
    Lubimova, T. G., Shust, K. V. & Popkov, V. V. Specific features in the ecology of Southern Ocean mesopelagic fish of the family Myctophidae. In Biological Resources of the Arctic and Antarctic (Collected Papers) 337 (1987).

    16.
    Catul, V., Gauns, M. & Karuppasamy, P. K. A review on mesopelagic fishes belonging to family Myctophidae. Rev. Fish Biol. Fish. 21, 339–354 (2011).
    Article  Google Scholar 

    17.
    Cherel, Y., Fontaine, C., Richard, P. & Labat, J. P. Isotopic niches and trophic levels of myctophid fishes and their predators in the Southern Ocean. Limnol. Oceanogr. 55, 324–332 (2010).
    ADS  CAS  Article  Google Scholar 

    18.
    Pérez-Rodríguez, A. An Integrative Study to the Functioning of the Flemish Cap Demersal Community (University of Vigo, Vigo, 2012).
    Google Scholar 

    19.
    Battaglia, P. et al. Feeding habits of the Atlantic bluefin tuna, Thunnus thynnus (L. 1758), in the central Mediterranean Sea (Strait of Messina). Helgol. Mar. Res. 67, 97–107 (2013).
    ADS  Article  Google Scholar 

    20.
    Rosas-Luis, R., Villanueva, R. & Sánchez, P. Trophic habits of the Ommastrephid squid Illex coindetii and Todarodes sagittatus in the northwestern Mediterranean Sea. Fish. Res. 152, 21–28 (2014).
    Article  Google Scholar 

    21.
    Hedd, A., Montevecchi, W. A., Davoren, G. K. & Fifield, D. A. Diets and distributions of Leach’s storm-petrel (Oceanodroma leucorhoa) before and after an ecosystem shift in the Northwest Atlantic. Can. J. Zool. 87, 787–801 (2009).
    CAS  Article  Google Scholar 

    22.
    Ohizumi, H., Kuramochi, T., Kubodera, T., Yoshioka, M. & Miyazaki, N. Feeding habits of Dall’s porpoises (Phocoenoides dalli) in the subarctic North Pacific and the Bering Sea basin and the impact of predation on mesopelagic micronekton. Deep Sea Res. Part I Oceanogr. Res. Pap. 50, 593–610 (2003).
    ADS  Article  Google Scholar 

    23.
    Lisovenko, L. A. & Prut’ko, V. G. Reproductive biology of Diaphus suborbitalis (Myctophidae) in the equatorial part of the Indian Ocean. 2. Fecundity and reproductive potential. J. Ichthyol. 27, 1–12 (1987).
    Google Scholar 

    24.
    Shotton, R. Lanternfishes: A potential fishery in the Northern Arabian Sea. Review of the state of world fishery resources: Marine fisheries. FAO Fisheries Circular, (920). (1997).

    25
    Olivar, M. P. et al. Vertical distribution, diversity and assemblages of mesopelagic fishes in the western Mediterranean. Deep Res. Part I Oceanogr. Res. Pap. 62, 53–69 (2012).
    ADS  Article  Google Scholar 

    26.
    Battaglia, P. et al. Diet of the spothead lanternfish Diaphus metopoclampus (Cocco, 1829) (Pisces: Myctophidae) in the central Mediterranean Sea. Ital. J. Zool. 81, 530–543 (2014).
    CAS  Article  Google Scholar 

    27.
    Lisovenko, L. A. & Prutko, V. G. Reproductive biology of Diaphus suborbitalis (Myctophidae) in the equatorial part of the Indian Ocean. 1. Nature of oogenesis and type of spawning. J. Ichthyol. 26, 619–629 (1986).
    Google Scholar 

    28.
    Dalpadado, P. Reproductive biology of the lanternfish Benthosema pterotum from the Indian Ocean. Mar. Biol. 98, 307–316 (1988).
    Article  Google Scholar 

    29.
    Hussain, S. M. The reproductive biology of the lantern fish Benthosema fibulatum from the northern Arabian Sea. Fish. Res. 13, 381–393 (1992).
    Article  Google Scholar 

    30.
    Gartner, J. V. Patterns of reproduction in the dominant lanternfish species (Pisces: Myctophidae) of the eastern Gulf of Mexico, with a review of reproduction among tropical-subtropical Myctophidae. Bull. Mar. Sci. 52, 721–750 (1993).
    Google Scholar 

    31.
    Gjosaeter, J. Life history and ecology of the myctophid fish Notoscopelus elongatus Kroeyeri from the northeast Atlantic. Ser. Havundersokelser Fisk. Skr. 17, 133–142 (1981).
    Google Scholar 

    32.
    Kawaguchi, K., Mauchline, J. & Mauchline, J. Biology of myctophid fishes (Family Myctophidae) in the rockall trough, Northeastern Atlantic Ocean Biology of Myctophid Fishes (Family Myctophidae) in the Rockall Trough, Northeastern Atlantic Ocean. Biol. Oceanogr. 1, 337–373 (1982).
    Google Scholar 

    33
    Hussain, S. M. & Ali-Khan, J. Fecundity of Benthosema fibulatum and Benhosema pterotum from the northern Arabian sea. Deep Sea Res. Part A Oceanogr. Res. Pap. 34, 1293–1299 (1987).
    ADS  Article  Google Scholar 

    34.
    Young, J. W., Blaber, S. J. M. & Rose, R. Reproductive biology of three species of midwater fishes associated with the continental slope of eastern Tasmania, Australia. Mar. Biol. 95, 323–332 (1987).
    Article  Google Scholar 

    35.
    Prosch, R. M. Reproductive biology and spawning of the myctophid Lampanyctodes hectoris and the sternoptychid Maurolicus muelleri in the Southern Benguela ecosystem. S. Afr. J. Mar. Sci. 10, 241–252 (1991).
    Article  Google Scholar 

    36.
    Clarke, T. A. Fecundity and other aspects of reproductive effort in mesopelagic fishes from the North Central and Equatorial Pacific. Biol. Oceanogr. 3, 147–165 (1984).
    Google Scholar 

    37.
    Flynn, A. J. & Paxton, J. R. Spawning aggregation of the lanternfish Diaphus danae (family Myctophidae) in the north-western Coral Sea and associations with tuna aggregations. Mar. Freshw. Res. 63, 1255–1271 (2012).
    Article  Google Scholar 

    38.
    García-Seoane, E., Bernal, A. & Saborido-Rey, F. Reproductive ecology of the glacier lanternfish Benthosema glaciale. Hydrobiologia 727, 137–149 (2014).
    Article  Google Scholar 

    39.
    Sassa, C., Ohshimo, S., Tanaka, H. & Tsukamoto, Y. Reproductive biology of Benthosema pterotum (Teleostei: Myctophidae) in the shelf region of the East China Sea. J. Mar. Biol. Assoc. UK 94, 423–433 (2014).
    Article  Google Scholar 

    40.
    Sassa, C., Tanaka, H. & Ohshimo, S. Comparative reproductive biology of three dominant myctophids of the genus Diaphus on the slope region of the East China Sea. Deep. Res. Part I Oceanogr. Res. Pap. 115, 145–158 (2016).
    ADS  Article  Google Scholar 

    41.
    Eschmeyer, W. N., Fricke, R. & R, van der L. Catalog of Fishes, electronic version (3 January 2017). San Francisco, CA (California Academy of Sciences). (2018).

    42
    Collins, M. A. et al. Latitudinal and bathymetric patterns in the distribution and abundance of mesopelagic fish in the Scotia Sea. Deep. Res. Part II Top. Stud. Oceanogr. 59–60, 189–198 (2012).
    ADS  Article  Google Scholar 

    43.
    Albikovskaya, L. K. Some aspects of the biology and distribution of glacier lanternfish (Benthosema glaciale) over the slopes of Flemish Cap and eastern Grand Bank. NAFO Sci. Counc. Stud. 12, 37–42 (1988).
    Google Scholar 

    44.
    Nafpaktitis, B. G. Review of the lanternfish genus Notoscopelus (family myctophidae) in the north Atlantic and the Mediterranean. Bulletin of Marine Science vol. 25 (1975).

    45.
    Hulley, P. A. & Paxton, J. R. Myctophiformes—Myctophidae/Neoscopelidae. In FAO Species Identification Guide for Fisheries Purposes: The Living Marine Resources of the Eastern Central Atlantic (eds Carpenter, K.E. & De Angelis, N.) 1922–1923, Rome (2016).

    46.
    Sarmiento-Lezcano, A. N., Triay-Portella, R., Castro, J. J., Rubio-Rodríguez, U. & Pajuelo, J. G. Age-based life-history parameters of the mesopelagic fish Notoscopelus resplendens (Richardson, 1845) in the Central Eastern Atlantic. Fish. Res. https://doi.org/10.1016/j.fishres.2018.03.016 (2018).
    Article  Google Scholar 

    47.
    Sutton, T. T. et al. A global biogeographic classification of the mesopelagic zone. Deep Sea Res. Part I Oceanogr. Res. Pap. https://doi.org/10.1016/j.dsr.2017.05.006 (2017).
    Article  Google Scholar 

    48.
    Moser, H. G. & Ahlstrom, E. H. Myctophidae: lanternfishes. In The Early Stages of Fishes in the California Current Region. Cal. Coop. Ocean. Fish. (CalCOFI). (ed. Moser, H. G.) 387–475 (1996).

    49.
    Bordes, F. et al. Catálogo de especies meso y batipelágicas. Peces, moluscos y crustáceos. Colectadas con arrastre en las Islas Canarias, durante las campañas realizadas a bordo de B/E ‘La Bocaina’. Instituto Canarios de Ciencias Marinas (ICCM), Agencia Canaria de Investig. in 326 (2009).

    50.
    Bordes Caballero, F. et al. Epi- and mesopelagic fishes, acoustic data, and SST images collected off Lanzarote, Fuerteventura and Gran Canaria, Canary Islands, during cruise ‘La Bocaina 04–97’. In Informes Técnicos del Instituto Canario de Ciencias Marinas. 1–45 (1999).

    51.
    Wienerroither, R. M. Species composition of mesopelagic fishes in the area of the Canary Islands, Eastern Central Atlantic. Informes Técnicos del Instituto Canario de Ciencias Marinas. (2003).

    52.
    Fulton, T. W. The Sovereignty of the Sea: An Historical Account of the Claims of England to the Dominion of the British Seas and of the Evolution of the Territorial Waters, with Special Reference to the Rights of Fishing and the Naval Salute (W. Blackwood, Edinburgh, 1911).
    Google Scholar 

    53.
    Brown-Peterson, N. J., Wyanski, D. M., Saborido-Rey, F., Macewicz, B. J. & Lowerre-Barbieri, S. K. A standardized terminology for describing reproductive development in fishes. Mar. Coast. Fish. 3, 52–70 (2011).
    Article  Google Scholar 

    54.
    Brown-Peterson, N. J., Overstreet, R. M., Lotz, J. M., Franks, J. S. & Burns, K. M. Reproductive biology of cobia, Rachycentron canadum, from coastal waters of the southern United States. Fish. Bull. 99, 15–28 (2001).
    Google Scholar 

    55.
    Luna, L. G. Manual of Histologic Staining Methods of the Armed Forces Institute of Pathology 3rd edn. (McGraw-Hill Book Company, New York, 1968).
    Google Scholar 

    56.
    De Vlaming, V. Oocyte Developmental Pattern and Hormonal Involvement Among Teleosts. (1983).

    57.
    Murua, H. et al. Procedures to estimate fecundity of wild collected marine fish in relation to fish reproductive strategy. J. Northwest Atl. Fish. Sci. 33, 33–54 (2003).
    Article  Google Scholar 

    58.
    Kiesbu, O. S. Oogenesis in cod, Gadus morhua L., studied by light and electron microscopy. J. Fish Biol. 34, 735–745 (1989).
    Article  Google Scholar 

    59.
    Hunter, J. R., Lo, N. C. H. & Leong, J. H. Batch Fecundity in multiple spawning fishes. NOAA Tech. Rep. NMFS 36, 67–77 (1985).
    Google Scholar 

    60.
    R Core Team. R: A Language and Environment for Statistical Computing. (2018).

    61.
    Sassa, C. & Hirota, Y. Seasonal occurrence of mesopelagic fish larvae on the onshore side of the Kuroshio off southern Japan. Deep. Res. Part I 81, 49–61 (2013).
    Article  Google Scholar 

    62.
    QGIS Development Team. QGIS Geographic Information System. Open Source Geospatial Foundation. (2020). https://www.qgis.org/es/site/.

    63.
    Wienerroither, R., Uibleina, F., Bordes, F. & Moreno, T. Composition, distribution, and diversity of pelagic fishes around the Canary Islands, Eastern Central Atlantic. Mar. Biol. Res. 5, 328–344 (2009).
    Article  Google Scholar 

    64.
    Olivar, M. P. et al. Variation in the diel vertical distributions of larvae and transforming stages of oceanic fishes across the tropical and equatorial Atlantic. Prog. Oceanogr. 160, 83–100 (2018).
    ADS  Article  Google Scholar 

    65.
    Clarke, T. A. Sex ratios and sexual differences in size among mesopelagic fishes from the central Pacific Ocean. Mar. Biol. 73, 203–209 (1983).
    Article  Google Scholar 

    66.
    Herring, P. J. The Biology of the Deep Ocean (Oxford University Press, Oxford, 2002).
    Google Scholar 

    67.
    Dalpadado, P. Aspects of the Biology of Benthosema pterotum (Myctophidae) from the Indian Ocean (University of Bergen, Bergen, 1983).
    Google Scholar 

    68.
    Filin, A. A. Growth, size and age composition of the Notoscopelus kroeyerii (Myctophidae). J. Ichthyol. 37, 27–32 (1997).
    Google Scholar 

    69.
    Greely, T. M., Gartner, J. V. J. & Torres, J. J. Age and growth of Electrona antarctica (Pisces: Myctophidae), the dominant mesopelagic fish in the Southern Ocean. Mar. Biol. 133, 145–158 (1999).
    Article  Google Scholar 

    70.
    Hulley, P. A. Myctophidae. In Fishes of the North-eastern Atlantic and the Mediterranean (eds Whitehead, P.J.P. et al.) 429–483 (1986).

    71.
    Kawaguchi, K. & Shimizu, H. Taxonomy and distribution of the lanternfishes, genus Diaphus (Pisces, Myctophidae) in the western Pacific, eastern Indian Oceans and the southeast Asian Seas. Bull. Ocean Res. Inst. Univ. Tokyo 10, 1–145 (1978).
    Google Scholar 

    72.
    Herring, P. J. Sex with the lights on? A review of bioluminescent sexual dimorphism in the sea. J. Mar. Biol. Assoc. UK 87, 829–842 (2007).
    CAS  Article  Google Scholar 

    73.
    Barnes, A. T. & Case, J. F. The luminescence of lanternfish (Myctophidae): Spontaneous activity and responses to mechanical, electrical, and chemical stimulation. J. Exp. Mar. Biol. Ecol. 15, 203–221 (1974).
    Article  Google Scholar 

    74.
    Clarke, T. A. Some aspects of the ecology of lanternfishes (Myctophidae) in the Pacific Ocean near Hawaii. Fish. Bull. 71, 401–434 (1973).
    Google Scholar 

    75.
    Karnella, C. The Ecology of Lanterfishes (Myctophidae) in the Bermuda ‘Ocean Acre’ (George Washington University, Washington, 1983).
    Google Scholar 

    76.
    Sabatés, A. & Masò, M. Effect of a shelf slope front on the spatial distribution of mesopelagic fish larvae in the western Mediterranean. Deep. Res. I(37), 1085–1098 (1990).
    ADS  Article  Google Scholar 

    77.
    Alekseyeva, Y. I. & Alekseyev, F. Y. Some aspects of reproductive biology of the lanternfishes, Myctophum punctatum and Notoscopelus resplendens (Myctophidae), from the eastern tropical Atlantic. J. Ichthyol. 23, 56–63 (1983).
    Google Scholar 

    78.
    Davison, P. C., Checkley, D. M., Koslow, J. A. & Barlow, J. Carbon export mediated by mesopelagic fishes in the northeast Pacific Ocean. Prog. Oceanogr. https://doi.org/10.1016/j.pocean.2013.05.013 (2013).
    Article  Google Scholar  More

  • in

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    Occurrence, distribution, and health risk assessment of quinolone antibiotics in water, sediment, and fish species of Qingshitan reservoir, South China

    1.
    Yu, Z. Y. Analysis of current situation of antibiotic abuse and countermeasures. Econ. Res. Guide. 145(35), 314–315 (2011) (in Chinese).
    ADS  Google Scholar 
    2.
    Adachi, F. et al. Occurrence of fluoroquinolones and fluoroquinolone-resistance genes in the aquatic environment. Sci. Total Environ. 444(444C), 508–514 (2013).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    3.
    Wu, T. T. et al. Investigation of the typical antibiotics in the sediments of the Yongjiang River, Nanning City, South China. China Environ. Sci. 33(2), 336–344 (2013) (in Chinese).
    CAS  Google Scholar 

    4.
    Ruan, Y. F. et al. Distribution characteristics of typical antibiotics in surface water and sediments from freshwater aquaculture water in Tianjin suburban areas, China. J. Agro-Environ. Sci. 30(12), 2586–2593 (2011) (in Chinese).
    CAS  Google Scholar 

    5.
    Liang, X. et al. The distribution and partitioning of common antibiotics in water and sediment of the Pearl River Estuary, South China. Chemosphere 92(11), 1410–1416 (2013).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    6.
    Shi, H. The Analysis Method of Twenty Antibiotics in the Sediment and its Application (East China Normal University, Shanghai, 2014) (in Chinese).
    Google Scholar 

    7.
    Zhang, W. R. The Distribution of Typical Antibiotics Strains in the Sediment Environments of Dalian (Dalian University, Dalian, 2014) (in Chinese).
    Google Scholar 

    8.
    Xu C. Contamination of Antibiotics and antibiotics resistance genes in water, soil and sediment of the Three Gorges Reservoir. 2017. Wuhan: the Wuhan Botanical Garden of the Chinese Academy of Sciences (in Chinese).

    9.
    Yang, Y. T. et al. Preliminary investigation of three quinolones in the muscle tissues of four fishes collected from the markets in Guangzhou City. J. Environ. Health 26(2), 109–111 (2009).
    CAS  Google Scholar 

    10.
    Wang, H. et al. Antibiotic residues in meat, milk and aquatic products in Shanghai and human exposure assessment. Food Control 80, 217–225 (2017).
    CAS  Article  Google Scholar 

    11.
    Naik, O. A. et al. Characterization of multiple antibiotic resistance of culturable microorganisms and metagenomic analysis of total microbial diversity of marine fish sold in retail shops in Mumbai, India. Environ. Sci. Pollut. Res. Int. 25(7), 6228–6239 (2017).
    PubMed  Article  CAS  PubMed Central  Google Scholar 

    12.
    Uchida, K. et al. Monitoring of antibiotic residues in aquatic products in urban and rural areas of Vietnam. J. Agric. Food Chem. 64(31), 6133–6138 (2016).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    13.
    Bakeraustin, C. et al. Antibiotic resistance in the shellfish pathogen Vibrio parahaemolyticus isolated from the coastal water and sediment of Georgia and South Carolina, USA. J. Food Prot. 71(12), 2552–2558 (2008).
    CAS  Article  Google Scholar 

    14.
    Richardson, B. J., Lam, P. K. S. & Martin, M. Emerging chemicals of concern: Pharmaceuticals and personal care products (PPCPs) in Asia, with particular reference to Southern China. Mar. Pollut. Bull. 50(9), 913–920 (2005).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    15.
    Liu, X. Pollution Level, Source and Ecological Risk of Typical Antibiotics in the Dongting Lake, China (Shandong Normal University, Jinan, 2017) (in Chinese).
    Google Scholar 

    16.
    Turiel, E., Bordin, G. & Rodrı́guez, A. R. Trace enrichment of (fluoro)quinolone antibiotics in surface waters by solid-phase extraction and their determination by liquid chromatography-ultraviolet detection. J. Chromatogr. A 1008(2), 145–155 (2003).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    17.
    Ying G G. Antibiotic use and pollution in the river basins of China. The 30th Academic Annual Meeting of China Chemical Society. 2016 (in Chinese).

    18.
    Sun, K. Contamination Characteristics and Ecological Risk Assessment of Typical Antibiotics in the Water of the Hongze Lake (Nanjing Agricultural University, Nanjing, 2015) (in Chinese).
    Google Scholar 

    19.
    Wang J W. Distribution characteristics and ecological risk assessment of antibiotics in surface water of Xi’an section of Weihe river. 2018. Xi’an: Xi’an University of Technology (in Chinese).

    20.
    Chen, L. et al. Investigation and evaluation of water quality of Qingshtan reservoir in Guilin city. Guangdong Agric. Sci. 40(5), 160–164 (2013) (in Chinese).
    CAS  Google Scholar 

    21.
    Zheng, Y. L. et al. Change of Inflow Runoff into the Qingshitan Reservoir in Guilin City. Water Conserv. Sci. Technol. Econ. 18(8), 46–48 (2012) (in Chinese).
    Google Scholar 

    22.
    Liang, Y. et al. Characteristics and risk assessment of organochlorine pesticide residues in surface sediments collected at the Qingshitan Reservoir. Toxicol. Environ. Chem. Rev. 98(5–6), 658–668 (2016).
    CAS  Article  Google Scholar 

    23.
    Cheng, Y. P. et al. Pollution characteristics and potential ecological risk assessment of heavy metals in sediments of Qingshitan reservoir. Yangtze River 48(10), 24–29 (2017) (in Chinese).
    Google Scholar 

    24.
    Kall, J. Limnology: Inland Water Ecosystem (Higher Education Press, Beijing, 2011).
    Google Scholar 

    25.
    Miu, Z. L., Zong, F. S. & Jiang, Y. P. Study on Hydrographic Karst and Tourism Resources in Guilin (China University of Geosciences Press, Wuhan, 2004) (in Chinese).
    Google Scholar 

    26.
    Qi, S. S. & Yang, X. Study on ecological restoration mode of reservoir eutrophication by fish cage culture. Environ. Sci. Manag. 37(11), 151–154 (2012) (in Chinese).
    CAS  Google Scholar 

    27.
    Xu, W. H. et al. Determination of selected antibiotics in the Victoria Harbour and the Pearl River, South China using highperformance liquid chromatography-electrospray ionization tandem mass spectrometry. Environ. Pollut. 145, 672–679 (2007).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    28.
    Liang, X. M. et al. Occurrence of antibiotics in typical aquaculture of the Pearl River Estuary. Ecol. Environ. Sci. 22(2), 304–310 (2013) (in Chinese).
    Google Scholar 

    29.
    Zhou, L. J. et al. Trends in the occurrence of human and veterinary antibiotics in the sediments of the Yellow River, Hai River and Liao River in northern China. Environ. Pollut. 159(7), 1877–1885 (2011).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    30.
    He, X. T. et al. Residues and health risk assessment of sulfonamides in sediment and fish from typical marine aquaculture regions of Guangdong province, China. Environ. Sci. 35(7), 2728–2735 (2014) (in Chinese).
    Google Scholar 

    31.
    Lu, R. K. Soil Argrochemistry Analysis Protocoes (Agriculture Science Press, Beijing, 1999) (in Chinese).
    Google Scholar 

    32.
    Xu, J. Application of High Performance Liquid Chromatography in Analysis of Antibiotics in Seafood (Harbin, Harbin Institute of Technology, 2016) (in Chinese).
    Google Scholar 

    33.
    European Commission. Technical Guidance Document on Risk Assessment in support of Commission Directive 93/67/EEC on risk assessment for new notified substances. 2003.

    34.
    Vryzas, Z. et al. Determination and aquatic risk assessment of pesticide residues in riparian drainage canals in northeastern Greece. Ecotoxicol. Environ. Saf. 74(2), 174–181 (2011).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    35.
    Backhaus, T., Scholze, M. & Grimme, L. H. The single substance and mixture toxicity of quinolones to the bioluminescent bacterium Vibrio fischeri. Aquat. Toxicol. 49(1), 49–61 (2000).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    36.
    Ma, Y. et al. Occurrences and regional distributions of 20 antibiotics in water bodies during groundwater recharge. Sci. Total Environ. 518–519, 498–506 (2015).
    ADS  PubMed  Article  CAS  PubMed Central  Google Scholar 

    37.
    Zhang, P. W. et al. Spatial, temporal distribution characteristics and potential risk of PPCPs in surface sediments from Taihu Lake. Environ. Sci. 37(9), 3348–3355 (2016) (in Chinese).
    Google Scholar 

    38.
    Piao, H. S. et al. Estimation of sorption coefficients of organic compounds with KOW. Environ. Sci. Technol. 4, 8–13 (1999) (in Chinese).
    Google Scholar 

    39.
    Guérit, I. et al. Environmental risk assessment: a critical approach of the European TGD in an insitu application. Ecotoxicol. Environ. Saf. 71(1), 291–300 (2008).
    PubMed  Article  CAS  Google Scholar 

    40.
    Ren, K. J. et al. Residues characteristics of fluoroquinolones (FQs) in the river sediments and fish tissues in a drinking water protection area of Guangdong Province. Acta Sci. Circum. 36(3), 760–766 (2016) (in Chinese).
    CAS  Google Scholar 

    41.
    Wang, L. et al. Incorporating fish habitat requirements of the complete life cycle into ecological flow regime estimation of rivers. Ecohydrology 13(4), e2204 (2020).
    Article  Google Scholar 

    42.
    Brown, K. D. et al. Occurrence of antibiotics in hospital, residential, and dairy effluent, municipal wastewater, and the Rio Grande in New Mexico. Sci. Total Environ. 366(2), 772–783 (2006).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    43.
    Chang, X. et al. Determination of antibiotics in sewage from hospitals, nursery and slaughter house, wastewater treatment plant and source water in Chongqing region of Three Gorge Reservoir in China. Environ. Pollut. 158(5), 1444–1450 (2010).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    44.
    Hirsch, R. et al. Occurrence of antibiotics in the aquatic environment. Sci. Total Environ. 225(1/2), 109–111 (1999).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    45.
    Guo, X. et al. Research progress on environmental exposure levels and environmental fate of veterinary antibiotics. Environ. Sci. Technol. 37(09), 76–86 (2014) (in Chinese).
    Google Scholar 

    46.
    Jiang, L. et al. Occurrence, distribution and seasonal variation of antibiotics in the Huangpu River, Shanghai. China. Chemosphere 82(6), 822–828 (2011).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    47.
    Li, J. et al. Distribution characteristics and ecological risk assessment of antibiotic pollution in Xiaoqing River watershed. J. Agro-Environ. Sci. 35(7), 1384–1391 (2016) (in Chinese).
    Google Scholar 

    48.
    Wu, X. et al. Occurrence, distribution and ecological risk of aantibiotics in surface water of the Gonghu Bay, Taihu Lake. Environ. Sci. 37(12), 4596–4604 (2016) (in Chinese).
    Google Scholar 

    49.
    Zhu, T. et al. Research on pollution and health risk by antibiotics in source water of Shiyan Reservoir in Shenzhen. J. Environ. Health 30(11), 1003–1006 (2013) (in Chinese).
    Google Scholar 

    50.
    Gao, L. et al. Research on pollution characteristics of antibiotics in Qinghe River in Beijing. Ecol. Sci. 33(1), 83–92 (2014) (in Chinese).
    Google Scholar 

    51.
    Nowara, A., Burhenne, J. & Spiteller, M. Binding of fluoroquinolone carboxylic acid derivatives to clay minerals. J. Agric. Food Chem. 45(4), 1459–1463 (1997).
    CAS  Article  Google Scholar 

    52.
    Li, B. Y. Study on Adsorption and Biodegradation of Norfloxacin in Soil (Zhengzhou University, Zhengzhou, 2010) (in Chinese).
    Google Scholar 

    53.
    Liu C, Li Y. Research Progress of Adsorption and Degradation of Ciprofloxacin in Soil. Beijing Agriculture. 2016, (4) (in Chinese).

    54.
    Wang, L. P., Zhang, M. K. & Zheng, S. A. Adsorption–desorption characteristics and biological effects of enrofloxacin in agricultural soils. Chin. J. Soil Sci. 39(2), 393–397 (2008) (in Chinese).
    CAS  Google Scholar 

    55.
    Jing, L. D. et al. Study on degradation kinetics of Ofloxacin at sediment–water interface. J. Southwest Univ. Nation. (Natural Science Edition). 42(4), 409–413 (2016) (in Chinese).
    CAS  Google Scholar 

    56.
    Dai, J. F. et al. Water quality analysis and segmentation of the pollution loads in different spatial scales of the upstream of Lijiang River. China Rural Water Hydropower 4, 67–71 (2017) (in Chinese).
    Google Scholar 

    57.
    Huang, J. et al. Residual levels of fluoroquinolones in freshwater fish from aquatic products markets in Guiyang. J. Environ. Health 34(2), 139–141 (2017) (in Chinese).
    Google Scholar 

    58.
    Sun, Y. C. Analysis and Distribution Characteristics of FQs in Environmental Water and Aquatic Product and its Effect on Environmental Stress (Harbin, Harbin Institute of Technology, 2014) (in Chinese).
    Google Scholar 

    59.
    Zhang, L. Y. Optimization of Quinolone Antibiotics Detection Method and in Water Photolysis and Hydrolysis Characteristics Research (Jilin Agricultural University, Jilin, 2016) (in Chinese).
    Google Scholar 

    60.
    Carrasquillo, A. J. et al. Sorption of ciprofloxacin and oxytetracycline zwitterions to soils and soil minerals: influence of compound structure. Environ. Sci. Technol. 42(20), 7634–7642 (2008).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    61.
    Zou, S. et al. Occurrence and distribution of antibiotics in coastal water of the Bohai Bay, China: impacts of river discharge and aquaculture activities. Environ. Pollut. 159(10), 2913–2920 (2011).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    62.
    Fu, H. et al. Impacts of p H on adsorption of quinolones by PAC. China Water Wastewater 33(17), 64–67 (2017) (in Chinese).
    Google Scholar 

    63.
    Huang, S. et al. Study on the relationships among pH, dissolved oxygen and chlorophyll a I: aquaculture water. Chin. J. Environ. Eng. 5(6), 1201–1208 (2011) (in Chinese).
    CAS  Google Scholar 

    64.
    Chen, S. et al. Formation, harmfulness, prevention, control and treatment of waters eutrophication. Environ. Sci. Technol. 22(2), 11–15 (1999) (in Chinese).
    Google Scholar 

    65.
    Pang, H. L. Studies on the Sorption Behavior of two Fluoroquinolones on Marine Sediments (Ocean University of China, Qingdao, 2012) (in Chinese).
    Google Scholar 

    66.
    Qin, Y. et al. Pollution characteristics and ecological risk assessment of typical antibiotics in the surface water of Hunhe River. Res. Environ. Sci. 28(3), 361–368 (2015) (in Chinese).
    CAS  Google Scholar 

    67.
    Syberg, K. et al. On the use of mixture toxicity assessment in REACH and the water framework directive: a review. Hum. Ecol. Risk Assess. 15(6), 1257–1272 (2009).
    CAS  Article  Google Scholar 

    68.
    Liu, K. et al. Investigation on the typical quinolone antibiotics in the surface sediments of Jiaozhou bay China. Mar. Environ. Sci. 36(05), 655–661 (2017) (in Chinese).
    Google Scholar 

    69.
    Zhang, J. et al. Health risk assessment of antibiotics in the centralized drinking water source in the three gorges reservoir area. Environ. Sci. Technol. 41(8), 192–198 (2018) (in Chinese).
    Google Scholar 

    70.
    No. 235 Announcement of the Ministry of Agriculture. Maximum residue limits of veterinary drugs in animal foods. China Swine Industry 2010(8), 10–12 (2002) (in Chinese).
    Google Scholar 

    71.
    National Health and Family Planning Commission of PRC. Outline of China’s food and nutrition development (2014–2020). Chron. Pathematol. J. 36(2), 111–113 (2014) (in Chinese).
    Google Scholar 

    72.
    Zhang, Q. P., Li, J. & Wang, C. M. Residual level and safety assessment of quinolone antibiotics in aquatic products in Suzhou. Chin. J. Health Lab. Technol. 22(10), 2417–2418 (2012) (in Chinese).
    CAS  Google Scholar 

    73.
    Wu, X. L. Pollution Characteristics and Health Risk of Quinolones in Vegetables in the Pearl River Delta Region (Jinan University, Guangzhou, 2011) (in Chinese).
    Google Scholar 

    74.
    Li, W., Shi, Y., Gao, L., Liu, J. & Cai, Y. Occurrence of antibiotics in water, sediments, aquatic plants, and animals from Baiyangdian Lake in North China. Chemosphere 89(11), 1307–1315 (2012).

    75.
    Minh, T. B. et al. Antibiotics in the Hong Kong metropolitan area: Ubiquitous distribution and fate in Victoria Harbour. Mar. Pollut. Bull. 58(7), 1052–1062 (2009).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    76.
    Riva, F., Zuccato, E., Davoli, E., Fattore, E. & Castiglioni, S. Risk assessment of a mixture of emerging contaminants in surface water in a highly urbanized area in Italy. J. Hazard. Mater. 361, 103–110 (2019).

    77.
    Watkinson, A. J., Murby, E. J., Kolpin, D. W. & Costanzo, S. D. The occurrence of antibiotics in an urban watershed: From wastewater to drinking water. Sci. Total Environ. 407(8), 2711–2723 (2009).

    78.
    Batt, A. L., Bruce, I. B. & Aga, D. S. Evaluating the vulnerability of surface waters to antibiotic contamination from varying wastewater treatment plant discharges. Environ. Pollut. 142(2), 295–302 (2006).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    79.
    Golet, E. M., Strehler, A., Alder, A. C. & Giger, W. Determination of fluoroquinolone antibacterial agents in sewage sludge and sludge-treated soil using accelerated solvent extraction followed by solid-phase extraction. Anal. Chem. 74(21), 5455–5462 (2002).

    80.
    Gibs, J. et al. Occurrence and partitioning of antibiotic compounds found in the water column and bottom sediments from a stream receiving two wastewater treatment plant effluents in Northern New Jersey, 2008. Sci. Total Environ. 458–460, 107–116 (2013).
    ADS  PubMed  Article  CAS  PubMed Central  Google Scholar 

    81.
    Wang, G. Q. & Sun, T. Antibiotic residues in aquatic products of Hongze lake investigation and research. Guangdong Chem. 38(1), 151–153 (2011) (in Chinese).
    CAS  Google Scholar 

    82.
    Yang, Y. T. & Luan, L. J. Residues and health risk assessment of Quinolones in fishes from the markets in Jining City. J. Anhui Agric. Sci. 43(26), 141–143 (2015) (in Chinese).
    CAS  Google Scholar  More

  • in

    Unchartered waters: the unintended impacts of residual chlorine on water quality and biofilms

    Chlorine residual impacted discolouration
    Unexpectedly, flushing of the High-chlorine system (by incrementally increasing the flow rate) produced a significantly greater discolouration response (assessed via turbidity) than the Medium- or Low-chlorine systems across all stages of flushing, of both tests (Fig. 2). Compared to the other regimes, the High-chlorine system also had a greater final concentration of iron (known to be associated with discolouration) at the end of Flush 1 and a greater rate of iron mobilisation during Flush 2 (Fig. 2). Conversely, the Low-chlorine regime consistently resulted in the lowest impact on water quality with the lowest discolouration and metal concentrations. Even after just 28 days of growth, material was mobilised from the High-chlorine regime at sufficient volumes to approach or breach the water quality standards for discolouration and iron concentrations (Fig. 2 and Supplementary Table 1). This contradicts the common perception of residual chlorine impacts on water quality and also studies of cast iron pipes, which suggest increasing oxidant concentration (disinfectant or dissolved oxygen) in drinking water decreases iron release26,27. Although surprising, High-chlorine repeatedly resulted in the greatest discolouration and Low-chlorine the least; as observed during the flushing of test 1, test 2 (Fig. 2) and preliminary tests (Supplementary Fig. 2).
    Fig. 2: Discolouration responses to elevated shear stress during the flushing of the chlorine regimes.

    Discolouration was determined primarily by a Turbidity (506 ≤ n ≤ 1091) with consideration of b Iron (n = 3) and c Manganese (n = 3) concentrations. Flush1 refers to the flushing phase of test 1, Flush2 indicates data from the flushing phase of test 2. Data normalised to well-mixed concentrations (0.09 Pa) of each system, mean ± standard deviation plotted. Linear regressions in each plot had R2 values of a 0.82 ≤ R2 ≤ 0.99, b 0.89 ≤ R2 ≤ 1.00 and c 0.76 ≤ R2 ≤ 0.98. High-chlorine: metal concentrations only available for final flushing step for Flush1. Chlorine regimes differed in their turbidity (ANCOVA on raw data: F ≥ 2869, p  More

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    Lactobacillus spp. attenuate antibiotic-induced immune and microbiota dysregulation in honey bees

    LX3 enhances larval pathogen eradication by antibiotics
    Prophylactic administration of OTC to honey bees is a common practice in beekeeping for the prevention of AFB. To evaluate the efficacy of this long-standing apiculture management strategy, we monitored a 2-week treatment regimen with OTC under natural field conditions in honey bee hives experiencing low-grade chronic infection with P. larvae (Fig. 1a). Using a qPCR-based approach to enumerate pathogen load, P. larvae abundance was found to be significantly lower in honey bee larvae (primary target of AFB) at week 1 and week 2 of OTC treatment (Kruskal–Wallis with Dunn’s multiple comparisons, P = 0.0071 and P = 0.0005, respectively) compared to baseline levels at day 0 (Fig. 1b). In contrast, no observable differences in P. larvae abundance were found in adult honey bees (active vector of AFB) at any time point during this treatment (Kruskal–Wallis with Dunn’s multiple comparisons, P = 0.9999, P = 0.6367, respectively; Fig. 1c).
    Fig. 1: LX3 enhances larval pathogen eradication by antibiotics.

    Experimental hives were subjected to standard antibiotic treatment with oxytetracycline (OTC) for 2 weeks and then supplemented for 4 weeks with either pollen patties containing LX3 (LX3) or pollen patties containing vehicle (VEH). No treatment control (NTC) hives received no further treatment after OTC. a Schematic diagram outlining the experimental design. b, c Molecular-based quantification of P. larvae in honey bee larvae (whole body) and adults (dissected abdomen) collected just prior to the start of OTC exposure (A.0), and then after 1 (A.1) and 2 (A.2) weeks of exposure. Data are depicted as median ± 95% confidence intervals (Kruskal–Wallis with Dunn’s multiple comparisons) at different time points. Each data point represents either one individual (adults) or three pooled individuals (larvae) sampled equally from a total of n = 6 hives. d, e Molecular-based quantification of P. larvae in larvae (whole body) and adults (dissected whole abdomens) at the start of the supplementation period (S.0; corresponding to 3 days post A.2 time point), and then after 2 (S.2) and 4 (S.4) weeks. Data are depicted as mean ± standard deviation (two-way ANOVA with Sidak’s multiple comparisons) at different time points with each data point representing either one individual (adults) or three pooled individuals (larvae) sampled equally from n = 4 hives per treatment group. f, g Capped brood counts during OTC treatment (n = 6 hives) and subsequent supplementation period (n = 4 hives per treatment group). Data represents the median (line in box), IQR (box), and minimum/maximum (whiskers) of relative change in brood counts normalized by hive. Statistics shown for one-way and two-way ANOVA, respectively, with Sidak’s multiple comparisons for both. **P  More