More stories

  • in

    A pilot study of eDNA metabarcoding to estimate plant biodiversity by an alpine glacier core (Adamello glacier, North Italy)

    1.
    Millennium Ecosystem Assessment. Ecosystems and human well-being: Biodiversity synthesis (World Resources Institute, Washington, DC, 2005). http://www.millenniumassessment.org/documents/document.354.aspx.pdf (accessed 22 April 2020).
    2.
    Willis, K. & Birks, H. What is natural? The need for a long-term perspective. Science 314(5803), 1261–1266. https://doi.org/10.1126/science.1122667 (2006).
    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

    3.
    Birks, H. J. B. et al. Does pollen-assemblage richness reflect floristic richness? A review of recent developments and future challenges. Rev. Palaeobot. Palynol. 228, 1–25. https://doi.org/10.1016/j.revpalbo.2015.12.011 (2016).
    Article  Google Scholar 

    4.
    Li, K., Liao, M., Ni, J., Liu, X. & Wang, Y. Treeline composition and biodiversity change on the southeastern Tibetan Plateau during the past millennium, inferred from a high-resolution alpine pollen record. Quat. Sci. Rev. 206, 44–55. https://doi.org/10.1016/j.quascirev.2018.12.029 (2019).
    ADS  Article  Google Scholar 

    5.
    Bálint, M. et al. Environmental DNA time series in ecology. Trends Ecol. Evol. 33, 945–957. https://doi.org/10.1016/j.tree.2018.09.003 (2018).
    Article  PubMed  Google Scholar 

    6.
    Garlapati, D., Charankumar, B., Ramu, K., Madeswaran, P. & Ramana Murthy, M. V. A review on the applications and recent advances in environmental DNA (eDNA) metagenomics. Rev. Environ. Sci. Biotechnol. 18, 389–411. https://doi.org/10.1007/s11157-019-09501-4 (2019).
    CAS  Article  Google Scholar 

    7.
    Hebert, P. D. N., Cywinska, A., Ball, S. L. & DeWaard, J. R. Biological identifications through DNA barcodes. Proc. R. Soc. B Biol. Sci. 270, 313–321. https://doi.org/10.1098/rspb.2002.2218 (2003).
    CAS  Article  Google Scholar 

    8.
    Kress, W. J. & Erickson, D. L. DNA barcodes: Genes, genomics, and bioinformatics. Proc. Natl. Acad. Sci. USA 105, 2761–2762. https://doi.org/10.1073/pnas.0800476105 (2008).
    ADS  Article  PubMed  Google Scholar 

    9.
    CBOL Plant Working Group. A DNA barcode for land plants. Proc. Natl. Acad. Sci. USA 106, 12794–12797. https://doi.org/10.1073/pnas.0905845106 (2009).
    Article  Google Scholar 

    10.
    China Plant BOL Group. Comparative analysis of a large dataset indicates that internal transcribed spacer (ITS) should be incorporated into the core barcode for seed plants. Proc. Natl. Acad. Sci. USA 108, 19641–19646. https://doi.org/10.1073/pnas.1104551108 (2011).
    ADS  Article  Google Scholar 

    11.
    Li, X. W. et al. Plant DNA barcoding: From gene to genome. Biol. Rev. Camb. Philos. 90, 157–166. https://doi.org/10.1111/brv.12104 (2015).
    Article  Google Scholar 

    12.
    Fior, S. et al. Spatiotemporal reconstruction of the Aquilegia rapid radiation through next-generation sequencing of rapidly evolving cpDNA regions. New Phytol. 198, 579–592. https://doi.org/10.1111/nph.12163 (2013).
    Article  PubMed  Google Scholar 

    13.
    Staats, M. et al. Advances in DNA metabarcoding for food and wildlife forensic species identification. Anal. Bioanal. Chem. 408, 4615–4630. https://doi.org/10.1007/s00216-016-9595-8 (2016).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    14.
    Taberlet, P. et al. Power and limitations of the chloroplast trnL (UAA) intron for plant DNA barcoding. Nucleic Acids Res. 35, e14. https://doi.org/10.1093/nar/gkl938 (2007).
    CAS  Article  Google Scholar 

    15.
    Kraaijeveld, K. et al. Efficient and sensitive identification and quantification of airborne pollen using next-generation DNA sequencing. Mol. Ecol. Resour. 15, 8–16. https://doi.org/10.1111/1755-0998.12288 (2015).
    CAS  Article  PubMed  Google Scholar 

    16.
    Leontidou, K. et al. DNA metabarcoding of airborne pollen: New protocols for improved taxonomic identification of environmental samples. Aerobiologia 34, 63–74. https://doi.org/10.1007/s10453-017-9497-z (2018).
    Article  Google Scholar 

    17.
    Parducci, L. et al. Ancient plant DNA in lake sediments. New Phytol. 214, 924–942 (2017).
    CAS  Article  Google Scholar 

    18.
    Giguet-Covex, C. et al. New insights on lake sediment DNA from the catchment: Importance of taphonomic and analytical issues on the record quality. Sci. Rep. 9, 1–21 (2019).
    CAS  Article  Google Scholar 

    19.
    Bovo, S. et al. Shotgun metagenomics of honey DNA: Evaluation of a methodological approach to describe a multi-kingdom honey bee derived environmental DNA signature. PLoS ONE 13, 1–19. https://doi.org/10.1371/journal.pone.0205575 (2018).
    CAS  Article  Google Scholar 

    20.
    Yoccoz, N. G. et al. DNA from soil mirrors plant taxonomic and growth form diversity. Mol. Ecol. 21, 3647–3655 (2012).
    CAS  Article  Google Scholar 

    21.
    Parducci, L. et al. Shotgun environmental DNA, pollen, and macrofossil analysis of lateglacial lake sediments from southern Sweden. Front. Ecol. Evol. https://doi.org/10.3389/fevo.2019.00189 (2019).
    Article  Google Scholar 

    22.
    Alsos, I. G. et al. Plant DNA metabarcoding of lake sediments: How does it represent the contemporary vegetation. PLoS ONE 13, 1–23. https://doi.org/10.1371/journal.pone.0195403 (2018).
    CAS  Article  Google Scholar 

    23.
    Willerslev, E. et al. Ancient biomolecules from deep ice cores reveal a forested southern Greenland. Science 317, 111–114. https://doi.org/10.1126/science.1141758 (2007).
    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

    24.
    Willerslev, E. et al. Diverse plant and animal genetic records from holocene and pleistocene sediments. Science 300, 791–795 (2003).
    ADS  CAS  Article  Google Scholar 

    25.
    Willerslev, E. et al. Fifty thousand years of Arctic vegetation and megafaunal diet. Nature 506, 47–51. https://doi.org/10.1038/nature12921 (2014).
    ADS  CAS  Article  PubMed  Google Scholar 

    26.
    Zimmermann, H. et al. Sedimentary ancient DNA and pollen reveal the composition of plant organic matter in Late Quaternary permafrost sediments of the Buor Khaya Peninsula (north-eastern Siberia). Biogeosciences 14, 575–596. https://doi.org/10.5194/bg-14-575-2017 (2017).
    ADS  CAS  Article  Google Scholar 

    27.
    Alaeddini, R. Forensic implications of PCR inhibition—A review. Forensic Sci. Int. Genet. 6, 297–305. https://doi.org/10.1016/j.fsigen.2011.08.006 (2012).
    CAS  Article  PubMed  Google Scholar 

    28.
    Haeberli, W. & Alean, J. Temperature and accumulation of high altitude firn in the alps. Ann. Glaciol. 6, 161–163. https://doi.org/10.3189/1985AoG6-1-161-163 (1985).
    ADS  Article  Google Scholar 

    29.
    Bennett, K. D. & Buck, C. E. Interpretation of lake sediment accumulation rates. Holocene 26, 1092–1102. https://doi.org/10.1177/0959683616632880 (2016).
    ADS  Article  Google Scholar 

    30.
    Festi, D. et al. A novel pollen-based method to detect seasonality in ice cores: A case study from the Ortles glacier, South Tyrol, Italy. J. Glaciol. 61, 815–824. https://doi.org/10.3189/2015JoG14J236 (2015).
    ADS  Article  Google Scholar 

    31.
    Nakazawa, F. Application of pollen analysis to dating of ice cores from lower-latitude glaciers. J. Geophys. Res. 109, 168–170. https://doi.org/10.1029/2004JF000125 (2004).
    Article  Google Scholar 

    32.
    Nakazawa, F. et al. Dating of seasonal snow/firn accumulation layers using pollen analysis. J. Glaciol. 51, 483–490. https://doi.org/10.3189/172756505781829179 (2005).
    ADS  Article  Google Scholar 

    33.
    Nakazawa, F. et al. Establishing the timing of chemical deposition events on Belukha Glacier, Altai Mountains, Russia, using Pollen analysis. Arctic Antarct. Alp. Res. 43, 66–72. https://doi.org/10.1657/1938-4246-43.1.66 (2011).
    Article  Google Scholar 

    34.
    Nakazawa, F., Konya, K., Kadota, T. & Ohata, T. Reconstruction of the depositional environment upstream of Potanin Glacier, Mongolian Altai, from pollen analysis. Environ. Res. Lett. 7, 035402. https://doi.org/10.1088/1748-9326/7/3/035402 (2012).
    ADS  Article  Google Scholar 

    35.
    Santibañez, P. et al. Glacier mass balance interpreted from biological analysis of firn cores in the Chilean lake district. J. Glaciol. 54, 452–462. https://doi.org/10.3189/002214308785837101 (2008).
    ADS  Article  Google Scholar 

    36.
    Uetake, J. et al. Biological ice-core analysis of Sofiyskiy glacier in the Russian Altai. Ann. Glaciol. 43, 70–78. https://doi.org/10.3189/172756406781811925 (2006).
    ADS  CAS  Article  Google Scholar 

    37.
    Andreev, A. A., Nikolaev, V. I., Boi’sheiyanov, D. Y. & Petrov, V. N. Pollen and isotope investigations of an ice core from Vavilov ice cap, October revolution island, Severnaya Zemlya archipelago, Russia. Geogr. Phys. Quat. 51, 379–389. https://doi.org/10.7202/033137ar (1997).
    Article  Google Scholar 

    38.
    Liu, K. B., Reese, C. A. & Thompson, L. G. A potential pollen proxy for ENSO derived from the Sajama ice core. Geophys. Res. Lett. 34, 1–5. https://doi.org/10.1029/2006GL029018 (2007).
    Article  Google Scholar 

    39.
    Reese, C. A., Liu, K. B. & Thompson, L. G. An ice-core pollen record showing vegetation response to Late-glacial and Holocene climate changes at Nevado Sajama, Bolivia. Ann. Glaciol. 54, 183–190. https://doi.org/10.3189/2013AoG63A375 (2013).
    ADS  CAS  Article  Google Scholar 

    40.
    Papina, T. et al. Biological proxies recorded in a Belukha ice core, Russian Altai. Clim. Past 9, 2399–2411. https://doi.org/10.5194/cp-9-2399-2013 (2013).
    Article  Google Scholar 

    41.
    Winkler, S. et al. An introduction to mountain glaciers as climate indicators with spatial and temporal diversity. Erdkunde 64, 97–118. https://doi.org/10.3112/erdkunde.2010.02.01 (2010).
    Article  Google Scholar 

    42.
    Citterio, M. et al. The fluctuations of Italian glaciers during the last century: A contribution to knowledge about alpine glacier changes. Geogr. Ann. Ser. A Phys. Geogr. 89, 167–184. https://doi.org/10.1111/j.1468-0459.2007.00316.x (2007).
    Article  Google Scholar 

    43.
    Knoll, C. & Kerschner, H. A glacier inventory for South Tyrol, Italy, based on airborne laser-scanner data. Ann. Glaciol. 50, 46–52. https://doi.org/10.3189/172756410790595903 (2009).
    ADS  Article  Google Scholar 

    44.
    Diolaiuti, G., Bocchiola, D., D’agata, C. & Smiraglia, C. Evidence of climate change impact upon glaciers’ recession within the Italian Alps: The case of Lombardy glaciers. Theor. Appl. Climatol. 109, 429–445. https://doi.org/10.1007/s00704-012-0589-y (2012).
    ADS  Article  Google Scholar 

    45.
    IPCC. Climate Change 2014: Synthesis Report. In Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (eds Core Writing Team, R.K. Pachauri and L.A. Meyer) 151 (IPCC, Geneva, 2014).

    46.
    Maggi, V. et al. Variability of anthropogenic and natural compounds in high altitude-high accumulation alpine glaciers. Hydrobiologia 562, 43–56. https://doi.org/10.1007/s10750-005-1804-y (2006).
    CAS  Article  Google Scholar 

    47.
    Gabrielli, P. et al. Age of the Mt. Ortles ice cores, the Tyrolean Iceman and glaciation of the highest summit of South Tyrol since the Northern Hemisphere Climatic Optimum. Cryosphere 10, 2779–2797. https://doi.org/10.5194/tc-10-2779-2016 (2016).
    ADS  Article  Google Scholar 

    48.
    Bohleber, P. et al. Temperature and mineral dust variability recorded in two low-accumulation Alpine ice cores over the last millennium. Clim. Past 14, 21–37. https://doi.org/10.5194/cp-14-21-2018 (2018).
    Article  Google Scholar 

    49.
    Rizzi, C., Finizio, A., Maggi, V. & Villa, S. Spatial–temporal analysis and risk characterisation of pesticides in Alpine glacial streams. Environ. Pollut. 248, 659–666. https://doi.org/10.1016/j.envpol.2019.02.067 (2019).
    CAS  Article  PubMed  Google Scholar 

    50.
    Garzonio, R. et al. Mapping the suitability for ice-core drilling of glaciers in the European Alps and the Asian High Mountains. J. Glaciol. 64, 12–26. https://doi.org/10.1017/jog.2017.75 (2018).
    ADS  Article  Google Scholar 

    51.
    Bokulich, N. A. et al. Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing. Nat. Methods 10, 57–59. https://doi.org/10.1038/nmeth.2276 (2013).
    CAS  Article  PubMed  Google Scholar 

    52.
    Olds, B. P. et al. Estimating species richness using environmental DNA. Ecol. Evol. 6, 4214–4226. https://doi.org/10.1002/ece3.2186 (2016).
    Article  PubMed  PubMed Central  Google Scholar 

    53.
    Deiner, K. et al. Environmental DNA metabarcoding: Transforming how we survey animal and plant communities. Mol. Ecol. 26, 5872–5895. https://doi.org/10.1111/mec.14350 (2017).
    Article  PubMed  Google Scholar 

    54.
    Soons, M. B. & Ozinga, W. A. How important is long-distance seed dispersal for the regional survival of plant species?. Divers. Distrib. 11, 165–172. https://doi.org/10.1111/j.1366-9516.2005.00148.x (2005).
    Article  Google Scholar 

    55.
    Lyscov, V. N. & Moshkovsky, Y. S. DNA cryolysis. Biochim. Biophys. Acta 190, 101–110 (1969).
    CAS  Article  Google Scholar 

    56.
    Pietramellara, G. et al. Extracellular DNA in soil and sediment: Fate and ecological relevance. Biol. Fertil. Soils 45, 219–235 (2009).
    CAS  Article  Google Scholar 

    57.
    Lindahl, T. & Nyberg, B. Rate of depurination of native deoxyribonucleic acid. Biochemistry 11, 3610–3618 (1972).
    CAS  Article  Google Scholar 

    58.
    Strickler, K. M., Fremier, A. K. & Goldberg, C. S. Quantifying effects of UV-B, temperature, and pH on eDNA degradation in aquatic microcosms. Biol. Conserv. 183, 85–92 (2015).
    Article  Google Scholar 

    59.
    Bortenschlager, S. Aspects of pollen morphology in the Cupressaceae. Grana 29, 129–137 (1990).
    Article  Google Scholar 

    60.
    Kurmann, M. H. Pollen morphology and ultrastructure in the Cupressaceae. Acta Bot. Gall. 141, 141–147 (1994).
    Article  Google Scholar 

    61.
    Chichiriccò, G. & Pacini, E. Cupressus arizonica pollen wall zonation and in vitro hydration. Plant Syst. Evol. 270, 231–242 (2008).
    Article  Google Scholar 

    62.
    Moran, T., Marshall, S. J. & Sharp, M. J. Isotope thermometry in melt-affected ice cores. J. Geophys. Res. Earth Surf. 116, 1–10. https://doi.org/10.1029/2010JF001738 (2011).
    CAS  Article  Google Scholar 

    63.
    Baroni, C., Armiraglio, S., Gentili, R. & Carton, A. Landform-vegetation units for investigating the dynamics and geomorphologic evolution of alpine composite debris cones (Valle dell’Avio, Adamello Group, Italy). Geomorphology 84, 59–79 (2007).
    ADS  Article  Google Scholar 

    64.
    Coissac, E., Riaz, T. & Puillandre, N. Bioinformatic challenges for DNA metabarcoding of plants and animals. Mol. Ecol. 21, 1834–1847. https://doi.org/10.1111/j.1365-294X.2012.05550.x (2012).
    CAS  Article  PubMed  Google Scholar 

    65.
    Celesti-Grapow, L. et al. (eds) Flora vascolare alloctona e invasiva delle regioni d’Italia (Casa Editrice Università La Sapienza, Roma, 2010).
    Google Scholar 

    66.
    Wu, P.-C., Su, H.-J., Lung, S.-C.C., Chen, M.-J. & Lin, W.-P. Pollen of Broussonetia papyrifera: An emerging aeroallergen associated with allergic illness in Taiwan. Sci. Total Environ. 657, 804–810. https://doi.org/10.1016/j.scitotenv.2018.11.324 (2019).
    ADS  CAS  Article  PubMed  Google Scholar 

    67.
    Kelly, R. P. et al. Genetic and manual survey methods yield different and complementary views of an ecosystem. Front. Mar. Sci. 3, 1–11. https://doi.org/10.3389/fmars.2016.00283 (2017).
    Article  Google Scholar 

    68.
    Baksay, S. et al. Experimental quantification of pollen with DNA metabarcoding using ITS1 and trnL. Sci. Rep. 10, 4202. https://doi.org/10.1038/s41598-020-61198-6 (2020).
    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

    69.
    Picotti, S., Francese, R., Giorgi, M., Pettenati, F. & Carcione, J. M. Estimation of glacier thicknesses and basal properties using the horizontal-to-vertical component spectral ratio (HVSR) technique from passive seismic data. J. Glaciol. 63, 229–248. https://doi.org/10.1017/jog.2016.135 (2017).
    ADS  Article  Google Scholar 

    70.
    Smiraglia, C. et al. The evolution of the Italian glaciers from the previous data base to the new Italian inventory. Preliminary considerations and results. Geogr. Fis. e Din. Quat. 38, 79–87. https://doi.org/10.4461/GFDQ.2015.38.08 (2015).
    Article  Google Scholar 

    71.
    Comitato Glaciologico Italiano & Consiglio Nazionale delle Ricerche. Catasto dei ghiacciai italiani. Anno geofisico 1957–1958. Volume III—Ghiacciai della Lombardia e dell’Ortles-Cevedale. (Comitato Glaciologico Italiano, Torino, 1961).

    72.
    Marson, L. Sui ghiacciai dell’Adamello – Presanella (alto bacino del Sarca – Mincio). Boll. Soc. Geogr. It. 7, 546–568 (1906).
    Google Scholar 

    73.
    Servizio Glaciologico Lombardo. Ghiacciai in Lombardia (Edizioni Bolis, Bergamo, 1992).
    Google Scholar 

    74.
    Payer, J. Originalkarte der Adamello-Presanella Alpen, scala di 1:56.000. In Pajer J. – Die Adamello-Presanella Alpen nach den Forschungen und Aufnahmen, Petermanns Geogr. Mitt. Erganzungs-Hefte, 11 (17) (Gotha, 1865).

    75.
    Bombarda, R. Il cuore Bianco. Guida ai ghiacciai del Trentino (Edizioni Arca, 1996).

    76.
    Baroni, C., Carton, A. & Casarotto, C. I ghiacciai dell’Adamello. In: Itinerari Glaciologici sulle montagne italiane (ed. Comitato Glaciologico Italiano) Vol. 3 (Società Geologica Italiana, Roma, 2017).

    77.
    Bertoni, E. & Casarotto, C. Estensione dei ghiacciai trentini dalla fine della Piccola Età glaciale a oggi. Rilevamento sul terreno, digitalizzazione GIS e analisi. (2015). Progetto finanziato dal Servizio sviluppo sostenibile e aree protette della PAT (rif. prot. n. P001/0640691/29-2014-16 dd. 2/12/2014) (accessed on 27 April 2020). http://www.climatrentino.it/binary/pat_climaticamente/osservatorio_trentino_clima/2014_Estensione_dei_ghiacciai_dalla_fine_della_Piccola_Et_Glaciale_a_oggi_MUSE_.1462456788.pdf.

    78.
    Abeni, F. et al. Hydrogen and oxygen stable isotope fractionation in body fluid compartments of dairy cattle according to season, farm, breed, and reproductive stage. PLoS ONE 10(5), e0127391. https://doi.org/10.1371/journal.pone.0127391 (2015).
    CAS  Article  PubMed  PubMed Central  Google Scholar 

    79.
    Bocchiola, D., Bombelli, G. M., Camin, F. & Ossi, P. M. Field study of mass balance, and hydrology of the West Khangri Nup Glacier (Khumbu, Everest). Water 12(2), 433. https://doi.org/10.3390/w12020433 (2020).
    Article  Google Scholar 

    80.
    Erdtman, G. The acetolysis method, A revised description. Svensk Bot. Tidskr. 54, 561–569 (1960).
    Google Scholar 

    81.
    Faegri, K. & Iversen, J. Textbook of Pollen Analysis (Wiley, London, 1989).
    Google Scholar 

    82.
    Bucher, E., Kofler, V., Vorwohl, G. & Zieger, E. Lo spettro pollinico dei mieli dell’Alto Adige (Laboratorio Biologico, Agenzia Provinciale per l’Ambiente, Laives, Bolzano. 2004).

    83.
    Albanese, D. et al. MICCA: Aa complete and accurate software for taxonomic profiling of metagenomic data. Sci. Rep. 5, 9743 (2015).
    CAS  Article  Google Scholar  More

  • in

    Group size and aquatic vegetation modulates male preferences for female shoals in wild zebrafish, Danio rerio

    Ethics statement
    The study complied with the existing rules and guidelines outlined by the Committee for the Purpose of Control and Supervision of Experiments on Animals (CPCSEA), Government of India, the Institutional Animal Ethics Committee’s (IAEC) and guidelines of Indian Institute of Science Education and Research (IISER) Kolkata. All experimental protocols followed here have been approved by the Institutional Animal Ethics Committee’s (IAEC) and guidelines of Indian Institute of Science Education and Research (IISER) Kolkata, Government of India. No animals were euthanized or sacrificed during any part of the study, and behavioral observations were conducted without any chemical treatment on the individuals. At the end of the experiments, all fish were returned to stock tanks and continued to be maintained in the laboratory.
    Procuring subject animals and maintenance
    We used wild-caught zebrafish (from Howrah district, West Bengal, India), bought from a commercial supplier. The fish were maintained in the laboratory in mixed-sex groups of approximately 60 individuals in well-aerated holding tanks (60 × 30 × 30 cm) filled with filtered water. The lighting in the laboratory was maintained at 14 hL:10 hD to mimic the natural LD cycle in zebrafish. They were fed commercially purchased freeze-dried blood worms once a day alternating with brine shrimp Artemia. The holding tanks were provided with standard corner filters for circulation. They were maintained in the laboratory for six months before experiments were conducted to ensure they were all adults and were reproductively mature. Holding room temperature was maintained between 23 and 25 °C.
    Experimental setup
    The experiments were conducted in a square glass arena (83 × 83 cm), with a half-diagonal of the square from the center that approximated ten fish standard body lengths (i.e. 40 cm, assuming one body length of adult zebrafish to be about 4 cm) (Fig. 1). Each corner of the arena was provided with a square chamber (of sides 10 cm) built from transparent mesh (using synthetic fish nets) for housing the females. This design allowed for the stimuli females to be localized in the patches and not escape into the arena while simultaneously ensuring that the test males can have visuo-chemical communication with the females. The center of the arena was provided with a removable chamber (with holes) for acclimation of the males prior to the trial.
    Figure 1

    Diagrammatic representation of the arena for the density experimental set-up. The central chamber (indicated by a circle) represents the area where the test males were released and the corner square chamber (separated by transparent mesh) contained females of varying density. The distance of each patch from the central chamber was 40 cm.

    Full size image

    Three sets of experiments were performed to test their association preferences under (1) only varying female densities (2) increasing female and vegetation densities and (3) increasing female densities with decreasing vegetation.
    Association preference experiment with varying female densities
    For this experiment, each small chamber within the arena housed two (low number), four (medium number), eight (high number) or no (blank) females. These chambers represented patches of varying female numbers. The position of the female-containing chambers, as well as the composition of females within each patch, was randomized between trials. A total of 20 males were tested for their association preferences. Details on the data collected are provided in Supplementary File S1.
    Association preference experiment with vegetation
    For this experiment, the female-housing chambers (patches) were provided with vegetation (using artificial plants) of varying density (Fig. 2). Each subject fish was tested under two experimental settings. In E1, the number of females was proportional to the density of associated vegetation cover. We used four different densities of females, each associated with different densities of plants
    1.
    one female + no plants (no vegetation—N)

    2.
    two females + two plants (low vegetation—L)

    3.
    four females + three plants (moderate vegetation—M) and

    4.
    eight females + five plants (high vegetation—H).

    Figure 2

    Diagrammatic representation of the arena the vegetation experimental set-up. The central chamber (indicated by a circle) represents the area where the test males were released and the corner square chambers (separated by transparent mesh) contained females of varying density and each patch was associated with variable number of plastic plants representing vegetation cover.

    Full size image

    For E2, we interchanged in the vegetation cover for the two and eight female patches. The patch composition in E2 set were as follows
    1.
    one female + no plants (no vegetation—N)

    2.
    two females + eight plants (high vegetation—H)

    3.
    four females + three plants (moderate vegetation—M) and

    4.
    eight females + two plants (low vegetation—L).

    All test males were tested in E1 and E2 on consecutive days in no particular order. Details on the data collected are provided in Supplementary Files S2 and S3.
    Experimental protocol
    For the experiment involving association preferences with only varying female numbers a total of 20 males were tested, while 24 males were tested for experiments on the association preferences in varying female numbers combined with vegetation density gradients (E1 and E2 experiments). The experiments were performed two months’ apart to ensure the fish do not retain any memory from the first experiment, and thus they could be treated as two independent sets. We isolated subject males of comparable sizes and kept them in individual isolation in 500 ml jars for four days prior to experiments as that allowed us to keep track of individual fish and also stimulated mate-seeking behavior21,22. They were fed freeze-dried blood worms every day at constantly maintained feeding times. The gravid females that were used for the experiment as stimuli for association were isolated (about 22 females) in a small holding tank (30 × 20 × 20 cm) with a feeding regimen similar to the test males. Before the start of each trial, we introduced the females into each chamber (patch) randomly (according to the experimental setup described above) and left them there for 15 min. for acclimation. A single male individual was then gently introduced into the central cylindrical chamber (with a hand-net), open at both ends (made of transparent plastic and provided with holes). After a five-minute acclimation period, the chamber was slowly removed to allow the male to swim freely in the arena and video recording was commenced. Video recordings were done using a camera (Sony DCR-PJ5, Sony DCR-SX22) placed perpendicularly above the arena. The test fish (males and females) were fed only after the end of experimental trials, on each day of experiments. At the end of the trials, the fish were returned to their holding tanks. No subject male fish were tested more than once per experimental setup and trial. The females used for the patches, were housed together (but separate from their male counterparts) in a smaller tank. Before the trials the females were picked randomly and assigned into each patch. During the experiment, the position of females being used was randomized between trials from patch to patch, to avoid the possibility of bias among the subject males for any particular females in the patches.
    We recorded the behavior of each test fish for 10 min. All videos were analyzed using the software BORIS23. A single visit to any of the patch was denoted when the male approaches within 6 cm (1.5 times their average body length) of the patch. We collected data on three parameters: total number of visits to each patch, the total amount of time spent in each patch and the mean time spent per visit within each patch. The same overall protocol was followed for all sets of experiments.
    Statistical analyses
    We noted the total number of visits to each patch, the total duration of time spent in each patch and mean time spent per visit per patch for the entire ten minutes duration of video recording for each test male. We calculated preference index (I) the total number of visits (I_visit) and total time spent (I_time) for each patch as proportion of the total visits made to all four patches24.

    I_visit for patch A = No. of visit to patch A/(visit to patch A + visit to patch B + visit to patch C + visit to patch D).

    I_time for patch A = time spent in patch A/(time spent in patch A + time spent in patch B + time spent in patch C + time spent in patch D).

    All statistical analyses were performed in R studio (version 1.1.463)25. We developed generalized linear mixed models (GLMMs) using package glmmTMB (version 0.2.3)26 with ‘fish’ as the random factor and ‘Patches’ as the fixed factor, with four levels representing the four choices for the test (male) fish. Preference for total number of visits (I_visit) as well as total time spent (I_time) were found to fit beta distribution with values ranging between 0 and 1. For data fitting, we added 0.0001 to every value, to remove zeroes. Relevelled models were used to compare the parameters between the four patches. Link = logit was used under beta family to construct the GLMM models.
    For analyzing the data for the second and third experiments involving varying female densities along with vegetation densities (E1 and E2), we followed a similar procedure of constructing a GLMM followed by post hoc tests. GLMM models were constructed with a single independent variable, “patch”, that had four levels, designated as H (high vegetation density), M (moderate vegetation density), L (low vegetation density) and N (no vegetation). More

  • in

    Silicon alleviates salinity stress in licorice (Glycyrrhiza uralensis) by regulating carbon and nitrogen metabolism

    1.
    Aslam, M., Ahmad, K., Arslan, A. M. & Amir, M. M. Salinity stress in crop plants: Effects of stress, tolerance mechanisms and breeding strategies for improvement. J. Agric. Basic Sci. 2(1), 2518–4210 (2017).
    Google Scholar 
    2.
    Kirsten, B., Abbey, F. W., Thomas, D., Amitava, C. & Jason, H. Soil salinity: A threat to global food security. Agron. J. 108(6), 2189–2200 (2016).
    Article  CAS  Google Scholar 

    3.
    Shakeel, A. A. et al. Drought induced changes in growth, osmolyte accumulation and antioxidant metabolism of three maize hybrids. Front. Plant Sci. 8(69), 1–12 (2017).
    Google Scholar 

    4.
    Abd-ElBaki, G. K. et al. Nitrate reductase in Zea mays L. under salinity. Plant Cell Environ. 23, 515–521 (2000).
    CAS  Article  Google Scholar 

    5.
    Flores, P., Botella, M. Á., Martínez, V. & Cerdá, A. C. Ionic and osmotic effects of nitrate reductase activity in tomato seedlings. J. Plant Physiol. 156, 552–557 (2000).
    CAS  Article  Google Scholar 

    6.
    Petronia, C., Gabriella, M., Francesco, N. & Amodio, F. Nitrate reductase in durum wheat seedlings as affected by nitrate nutrition and salinity. Funct. Plant Biol. 32(3), 209–219 (2005).
    Article  Google Scholar 

    7.
    Flowers, T. J. et al. Salt sensitivity in chickpea. Plant Cell Environ. 3(4), 490–509 (2010).
    MathSciNet  Article  CAS  Google Scholar 

    8.
    Husen, A., Iqbal, M., Sohrab, S. S. & Ansari, M. K. A. Salicylic acid alleviates salinity-caused damage to foliar functions, plant growth and antioxidant system in Ethiopian mustard (Brassica carinata A. Br.). Agric. Food Secur. 7(1), 44 (2018).
    Article  Google Scholar 

    9.
    Farhangi-Abriz, S. & Torabian, S. Biochar improved nodulation and nitrogen metabolism of soybean under salt stress. Symbiosis. 74(3), 215–223 (2018).
    CAS  Article  Google Scholar 

    10.
    Gupta, B. & Huan, B. Mechanism of salinity tolerance in plants: Physiological, biochemical, and molecular characterization. Int. J. Genomics. 1, 701596. https://doi.org/10.1155/2014/701596 (2014).
    CAS  Article  Google Scholar 

    11.
    Zhang, W. J. et al. Silicon promotes growth and root yield of Glycyrrhiza uralensis, under salt and drought stresses through enhancing osmotic adjustment and regulating antioxidant metabolism. Crop Prot. 107, 1–11 (2018).
    Article  CAS  Google Scholar 

    12.
    Saqib, M., Zörb, C. & Schubert, S. Salt resistant and salt-sensitive wheat genotypes show similar biochemical reaction at protein level in the first phase of salt stress. J. Plant Nutr. Soil Sci. 169(4), 542–548 (2006).
    CAS  Article  Google Scholar 

    13.
    Turan, M. A., Katkat, V. & Taban, S. Salinity-induced stomatal resistance, proline, chlorophyll and ion concentrations of bean. Int. J. Agric. Res. 2(5), 483–488 (2007).
    CAS  Article  Google Scholar 

    14.
    Memon, S. A., Hou, X. L. & Wang, L. J. Morphological analysis of salt stress response of pak Choi. Electron. J. Environ. Agric. Food Chem. 9(1), 248–254 (2010).
    CAS  Google Scholar 

    15.
    Keyvan, A. & Setsuko, K. Crop and medicinal plants proteomics in response to salt stress. Front. Plant Sci. 4(8), 8 (2013).
    Google Scholar 

    16.
    Dadkhah, A. R. Effect of salt stress on growth and essential oil of Matricaria chamomilla. Planta Med. 5(10), 643–646 (2010).
    Google Scholar 

    17.
    Aziz, E. E., Al-Amier, H. & Craker, L. E. Influence of salt stress on growth and essential oil production in peppermint, pennyroyal, and apple mint. J. Herbs Spices Med. Plants. 14(1–2), 77–87 (2008).
    CAS  Article  Google Scholar 

    18.
    Leithy, S., Gaballah, M. S. & Gomaa, A. M. Associative impact of bio-and organic fertilizers on geranium plants grown under saline conditions. Electron. J. Environ. Agric. Food Chem. 1(3), 617–626 (2009).
    Google Scholar 

    19.
    Najafian, S., Khoshkhui, M. & Tavallali, V. Effect of salicylic acid and salinity in rosemary (Rosmarinus officinalis L): Investigation on changes in gas exchange, water relations, and membrane stabilization. Aust. J. Basic. Appl. Sci. 3(3), 322–328 (2009).
    CAS  Google Scholar 

    20.
    Taarit, M. B. et al. Plant growth, essential oil yield and composition of sage (Salvia officinalis L.) fruits cultivated under salt stress conditions. Ind. Crops Prod. 30(3), 333–337 (2009).
    Article  CAS  Google Scholar 

    21.
    Queslati, S. et al. Physiological and antioxidant responses of Mentha pulegium (Pennyroyal) to salt stress. Acta Physiol. Plant. 32(2), 289–296 (2010).
    Article  CAS  Google Scholar 

    22.
    Seyed, M. Z., Faezeh, M., Saadat, S. & Mohsen, P. Selenium and silica nanostructure-based recovery of strawberry plants subjected to drought stress. Sci. Rep. 10, 17672. https://doi.org/10.1038/s41598-020-74273-9 (2020).
    CAS  Article  Google Scholar 

    23.
    Yan, et al. Silicon improves rice salinity resistance by alleviating ionic toxicity and osmotic constraint in an organ-specific pattern. Front. Plant Sci. 11, 260. https://doi.org/10.3389/fpls.2020.00260 (2020).
    ADS  Article  PubMed  PubMed Central  Google Scholar 

    24.
    Mateos-Naranjo, E., Andrades-Moreno, L. & Davy, A. J. Silicon alleviates deleterious effects of high salinity on the halophytic grass Spartina densiflora. Plant Physiol. Biochem. 63, 115–121 (2013).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    25.
    Chen, D. Q., Yin, L., Deng, X. P. & Wang, S. W. Silicon increases salt tolerance by influencing the two-phase growth response to salinity in wheat (Triticum aestivum L). Acta Physiol. Plant. 36(9), 2531–2535 (2014).
    CAS  Article  Google Scholar 

    26.
    Khattab, H. I., Emam, M. A., Emam, M. M., Helal, N. M. & Mohamed, R. M. Effect of selenium and silicon on transcription factors NAC5 and DREB2A involved in drought-responsive gene expression in rice. Biol. Plant. 58(2), 265–273 (2014).
    CAS  Article  Google Scholar 

    27.
    Zhu, Y. X. & Gong, H. G. Beneficial effects of silicon on salt and drought tolerance in plants. Agron. Sustain. Dev. 34(2), 455–472 (2013).
    Article  CAS  Google Scholar 

    28.
    Zhang, X. H. et al. Effect of silicon on seed germination and the physiological characteristics of Glycyrrhiza uralensis under different levels of salinity. J. Hortic. Sci. Biotechnol. 90(4), 439–443 (2015).
    CAS  Article  Google Scholar 

    29.
    Marcin, R. N. & Maria, S. The relationship between carbon and nitrogen metabolism in cucumber leaves acclimated to salt stress. Peer J. 6(3), e6043 (2018).
    Google Scholar 

    30.
    Zhang, D. D. et al. Enhanced of α-ketoglutarate production in Torulopsis glabrata: Redistribution of carbon flux from pyruvate to α-ketoglutarate. Biotechnol. Bioprocess Eng. 14(2), 134–139 (2009).
    ADS  CAS  Article  Google Scholar 

    31.
    Nunes-Nesi, A., Fernie, A. R. & Stitt, M. Metabolic and signaling aspects underpinning the regulation of plant carbon nitrogen interactions. Mol. Plant. 3(6), 973–996 (2010).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    32.
    Miller, A. J., Fan, X. R., Shen, Q. R. & Smith, S. J. Amino acids and nitrate as signals for the regulation of nitrogen acquisition. J. Exp. Bot. 59(1), 111–119 (2008).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    33.
    Reynolds, M. P. Raising yield potential of wheat. III. Optimizing partitioning to grain while maintaining lodging resistance. J. Exp. Bot. 62(2), 469–486 (2010).
    PubMed  PubMed Central  Google Scholar 

    34.
    Yan, B. B. et al. The effects of endogenous hormones on the flowering and fruiting of Glycyrrhiza uralensis. Plants Basel. 8(11), 519 (2019).
    CAS  PubMed Central  Article  Google Scholar 

    35.
    Mochida, K. et al. Draft genome assembly and annotation of Glycyrrhiza uralensis, a medicinal legume. Plant J. 89(2), 181–194 (2016).
    PubMed  Article  CAS  PubMed Central  Google Scholar 

    36.
    An, C.-G. et al. Effect of KCl or K2SO4 supplement to nutrient solution on yield and fruit quality in sweet peppers (Capsicum annuum “Special” and ’Fiesta’). Hortic. Sci. Technol. 24(2), 181–189 (2006).
    Google Scholar 

    37.
    Lang, D. Y., Yu, X. X., Jia, X. X., Li, Z. X. & Zhang, X. H. Methyl jasmonate improves metabolism and growth of NaCl-stressed Glycyrrhiza uralensis seedlings. Sci. Hortic. 266, 109287. https://doi.org/10.1016/j.scienta (2020).
    CAS  Article  Google Scholar 

    38.
    Verma, A. K., Upadhyay, S. K., Verma, P. C., Solomon, S. & Singh, S. B. Functional analysis of sucrose phosphate synthase (SPS) and sucrose synthase (SS) in sugarcane (Saccharum) cultivars. Plant Biol. 13(2), 325–332 (2010).
    PubMed  Article  CAS  PubMed Central  Google Scholar 

    39.
    Orathai, W., Lih, S. K. & Liang, Y. S. The changes in physical, bio-chemical, physiological characteristics and enzyme activities of mango cv. Jinhwang during fruit growth and development. NJAS-Wagen. J. Life Sc. 72–73, 7–12 (2015).
    Google Scholar 

    40.
    Charles, J. B., Christine, H. F., Janice, T., Stephen, A. R. & Quick, W. P. Elevated sucrose-phosphate synthase activity in transgenic tobacco sustains photosynthesis in older leaves and alters development. J. Exp. Bot. 54(389), 1813–1820 (2003).
    Article  Google Scholar 

    41.
    Wang, X. W. et al. In vitro evaluation of the hypoglycemic properties of lactic acid bacteria and its fermentation adaptability in apple juice. LWT-Food Sci. Technol. 136, 110363. https://doi.org/10.1016/j.lwt.2020.110363 (2020).
    CAS  Article  Google Scholar 

    42.
    Ali, A., Jha, P., Sandhu, K. S. & Raghuram, N. Spirulina nitrate-assimilating enzymes (NR, NiR, GS) have higher specific activities and are more stable than those of rice. Physiol. Mol. Biol. Plant. 14(3), 179–182 (2008).
    CAS  Article  Google Scholar 

    43.
    Patel, J. G., Kumar, N. J. I., Kumar, R. N. & Khan, S. R. Evaluation of nitrogen fixing enzyme activities in response to pyrene bioremediation efficacy by defined artificial microalgal-bacterial consortium of Gujarat, India. Polycycl. Aromat. Compd. 38(3), 282–293 (2018).
    CAS  Article  Google Scholar 

    44.
    Liu, C. G. et al. Carbon and nitrogen metabolism in leaves and roots of dwarf bamboo (Fargesia denudata Yi) subjected to drought for two consecutive years during sprouting period. J. Plant Growth Regul. 33, 243–255 (2014).
    CAS  Article  Google Scholar 

    45.
    Magomya, A. M., Kubmarawa, D., Ndahi, J. A. & Yebpella, G. G. Determination of plant proteins via the Kjeldahl method and amino acid analysis: A comparative study. Int. J. Sci. Technol. Res. 3(4), 68–72 (2014).
    Google Scholar 

    46.
    Yang, H. L. et al. Molybdenum blue photometry method for the determination of colloidal silica and soluble silica in leaching solution. Anal. Methods. https://doi.org/10.1039/C5AY01306B (2015).
    Article  Google Scholar 

    47.
    Marino, D., González, E. M. & Arrese-Igor, C. Drought effects on carbon and nitrogen metabolism of pea nodules can be mimicked by paraquat: Evidence for the occurrence of two regulation pathways under oxidative stresses. J. Exp. Bot. 57(3), 665–673 (2006).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    48.
    Shao, Q. S. et al. Effects of NaCl stress on nitrogen metabolism of cucumber seedlings. Russ. J. Plant Physiol. 62(5), 595–603 (2015).
    CAS  Article  Google Scholar 

    49.
    Irani, S. & Todd, C. D. Ureide metabolism under abiotic stress in Arabidopsis thaliana. J. Plant Physiol. 199, 87–95 (2016).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    50.
    Ahmad, P. et al. Silicon (Si) supplementation alleviates NaCl toxicity in Mung Bean [Vigna radiata, (L.) Wilczek] through the modifications of physio-biochemical attributes and key antioxidant enzymes. J. Plant Growth Regul. 38, 70–82 (2018).
    Article  CAS  Google Scholar 

    51.
    Liang, Y. C., Chen, Q., Liu, Q., Zhang, W. H. & Ding, R. X. Exogenous silicon (Si) increases antioxidant enzyme activity and reduces lipid peroxidation in roots of salt-stressed barley (Hordeum vulgare L.). J. Plant Physiol. 160(10), 1157–1164 (2003).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    52.
    Kim, Y. H. et al. Silicon application to rice root zone influenced the phytohormonal and antioxidant responses under salinity stress. J. Plant Growth Regul. 33(2), 137–149 (2013).
    Article  CAS  Google Scholar 

    53.
    Haghighi, M. & Pessarakli, M. Influence of silicon and nano-silicon on salinity tolerance of cherry tomatoes (Solanum lycopersicum L.) at early growth stage. Sci. Hortic. 161(24), 111–117 (2013).
    CAS  Article  Google Scholar 

    54.
    Zhu, Y. X. et al. Silicon improves salt tolerance by increasing root water uptake in Cucumis sativus, L. Plant Cell Rep. 34(9), 1629–1646 (2015).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    55.
    Fernandes, F. M., Arrabaca, M. C. & Carvalho, L. M. M. Sucrose metabolism in Lupinus albus L. under salt stress. Biol. Plant. 48(2), 317–319 (2004).
    CAS  Article  Google Scholar 

    56.
    Miyako, K. et al. Cytosolic GLUTAMINE SYNTHETASE1;1 modulates metabolism and chloroplast development in roots. Plant Physiol. 182(4), 1894–1909 (2020).
    Article  CAS  Google Scholar 

    57.
    Joaquim, A. G. S. et al. Proline accumulation and glutamine synthetase activity are increased by salt-induced proteolysis in cashew leaves. J. Plant Physiol. 160(2), 115–123 (2003).
    Article  Google Scholar 

    58.
    Dresler, S., Wójcik, M., Bednarek, W., Hanaka, A. & Tukiendorf, A. The effect of silicon on maize growth under cadmium stress. Russ. J. Plant Physiol. 62(1), 86–92 (2015).
    CAS  Article  Google Scholar 

    59.
    Muneer, S. & Jeong, B. R. Proteomic analysis of salt-stress responsive proteins in roots of tomato (Lycopersicon esculentum L.) plants towards silicon efficiency. Plant Growth Regul. 77(2), 133–146 (2015).
    ADS  CAS  Article  Google Scholar 

    60.
    Dorairaj, D., Ismail, M. R., Sinniah, U. R. & Ban, T. K. Influence of silicon on growth, yield, and lodging resistance of MR219, a lowland rice of Malaysia. J. Plant Nutr. 40(8), 1111–1124 (2017).
    CAS  Article  Google Scholar 

    61.
    Garg, N. & Singh, S. Arbuscular mycorrhiza Rhizophagus irregularis and silicon modulate growth, proline biosynthesis and yield in Cajanus cajan L. Millsp. (pigeonpea) genotypes under cadmium and zinc stress. J. Plant Growth Regul. 37(6), 46–63 (2018).
    CAS  Article  Google Scholar  More

  • in

    Deep-sea bacteria trigger settlement and metamorphosis of the mussel Mytilus coruscus larvae

    1.
    Liang, X., Liu, Y. Z., Chen, K., Li, Y. F. & Yang, J. L. Identification of MyD88-4 in Mytilus coruscus and expression changes in response to Vibrio chagasii challenge (in Chinese with English abstract). J. Fish. China. 43, 2347–2358 (2019).
    Google Scholar 
    2.
    Li, T. W. Marine Biology (in Chinese) (China Ocean Press, Beijing, 2013).
    Google Scholar 

    3.
    Liang, X. et al. Effects of dynamic succession of Vibrio biofilms on settlement of the mussel Mytilus coruscus (in Chinese with English abstract). J. Fish. China. 44, 118–129 (2020).
    Google Scholar 

    4.
    Whalan, S. & Webster, N. S. Sponge larval settlement cues: the role of microbial biofilms in a warming ocean. Sci. Rep. 4, 4072 (2014).
    ADS  CAS  Article  Google Scholar 

    5.
    Satuito, C. G., Natoyama, K., Yamazaki, M. & Fusetani, N. Induction of attachment and metamorphosis of laboratory cultured mussel Mytilus edulis galloprovincialis larvae by microbial film. Fish. Sci. 61, 223–227 (1995).
    CAS  Article  Google Scholar 

    6.
    Zhao, B., Zhang, S. & Qian, P. Y. Larval settlement of the silver-or goldlip pearl oyster Pinctada maxima (Jameson) in response to natural biofilms and chemical cues. Aquaculture 220, 883–901 (2003).
    Article  Google Scholar 

    7.
    Rahim, S. A. K. A., Li, J. Y. & Kitamura, H. Larval metamorphosis of the sea urchins, Pseudocentrotus depressus and Anthocidaris crassispina in response to microbial film. Mar. Biol. 144, 71–78 (2004).
    Article  Google Scholar 

    8.
    Bao, W. Y., Satuito, C. G., Yang, J. L. & Kitamura, H. Larval settlement and metamorphosis of the mussel Mytilus galloprovincialis in response to biofilms. Mar. Biol. 150, 565–574 (2007).
    Article  Google Scholar 

    9.
    Huang, Y., Callahan, S. & Hadfield, M. G. Recruitment in the sea: bacterial genes required for inducing larval settlement in a polychaete worm. Sci. Rep. 2, 228 (2012).
    ADS  Article  Google Scholar 

    10.
    Wang, C. et al. Larval settlement and metamorphosis of the mussel Mytilus coruscus in response to natural biofilms. Biofouling 28, 249–256 (2012).
    Article  Google Scholar 

    11.
    Yang, J. L. et al. Larval settlement and metamorphosis of the mussel Mytilus coruscus in response to monospecific bacterial biofilms. Biofouling 29, 247–259 (2013).
    CAS  Article  Google Scholar 

    12.
    Liang, X. et al. The flagellar gene regulates biofilm formation and mussel larval settlement and metamorphosis. Int. J. Mol. Sci. 21, 710 (2020).
    CAS  Article  Google Scholar 

    13.
    Peng, L. H., Liang, X., Xu, J. K., Dobretsov, S. & Yang, J. L. Monospecific biofilms of Pseudoalteromonas promote larval settlement and metamorphosis of Mytilus coruscus. Sci. Rep. 10, 2577 (2020).
    ADS  CAS  Article  Google Scholar 

    14.
    Schippers, A. et al. Prokaryotic cells of the deep sub-seafloor biosphere identified as living bacteria. Nature 433, 861–864 (2005).
    ADS  CAS  Article  Google Scholar 

    15.
    Orcutt, B. N., Sylvan, J. B., Knab, N. J. & Edwards, K. J. Microbial ecology of the dark ocean above, at, and below the seafloor. Microbiol. Mol. Biol. Rev. 75, 361–422 (2011).
    CAS  Article  Google Scholar 

    16.
    Woodall, L. C. et al. Deep-sea anthropogenic macrodebris harbours rich and diverse communities of bacteria and archaea. PLoS ONE 13, e0206220 (2018).
    Article  Google Scholar 

    17.
    Wieczorek, S. K. & Todd, C. D. Inhibition and facilitation of settlement of epifaunal marine invertebrate larvae by microbial biofilm cues. Biofouling 12, 81–118 (1998).
    Article  Google Scholar 

    18.
    Qian, P. Y., Lau, S. C. K., Dahms, H. U., Dobretsov, S. & Harder, T. Marine biofilms as mediators of colonization by marine macroorganisms: implications for antifouling and aquaculture. Mar. Biotechnol. 9, 399–410 (2007).
    CAS  Article  Google Scholar 

    19.
    Dobretsov, S. in Marine and Industrial Biofouling (eds Flemming, H. C. et al.) 293–313 (Springer, 2009).

    20.
    Huang, S. & Hadfield, M. G. Composition and density of bacterial biofilms determine larval settlement of the polychaete Hydroides elegans. Mar. Ecol. Prog. Ser. 260, 161–172 (2003).
    ADS  CAS  Article  Google Scholar 

    21.
    Tran, C. & Hadfield, M. G. Larvae of Pocillopora damicornis (Anthozoa) settle and metamorphose in response to surface-biofilm bacteria. Mar. Ecol. Prog. Ser. 433, 85–96 (2011).
    ADS  Article  Google Scholar 

    22.
    Dahms, H. U., Dobretsov, S. & Qian, P. Y. The effect of bacterial and diatom biofilms on the settlement of the bryozoan Bugula neritina. J. Exp. Mar. Biol. Ecol. 313, 191–209 (2004).
    Article  Google Scholar 

    23.
    Lau, S. C. K., Thiyagarajan, V. & Qian, P. Y. The bioactivity of bacterial isolates in Hong Kong waters for the inhibition of barnacle (Balanus amphitrite Darwin) settlement. J. Exp. Mar. Biol. Ecol. 282, 43–60 (2003).
    Article  Google Scholar 

    24.
    Lau, S. C. K. & Qian, P. Y. Larval settlement in the serpulid polychaete Hydroides elegans in response to bacterial films: an investigation of the nature of putative larval settlement cue. Mar. Biol. 138, 321–328 (2001).
    Article  Google Scholar 

    25.
    Bao, W. Y., Yang, J. L., Satuito, C. G. & Kitamura, H. Larval metamorphosis of the mussel Mytilus galloprovincialis in response to Alteromonas sp. 1: evidence for two chemical cues?. Mar. Biol. 152, 657–666 (2007).
    Article  Google Scholar 

    26.
    Unabia, C. R. C. & Hadfield, M. G. Role of bacteria in larval settlement and metamorphosis of the polychaete Hydroides elegans. Mar. Biol. 133, 55–64 (1999).
    Article  Google Scholar 

    27.
    Hadfield, M. G. Biofilms and marine invertebrate larvae: what bacteria produce that larvae use to choose settlement sites. Annu. Rev. Mar. Sci. 3, 453–470 (2011).
    ADS  Article  Google Scholar 

    28.
    Flemming, H. C. & Wingender, J. The biofilm matrix. Nat. Rev. Microbiol. 8, 623–633 (2010).
    CAS  Article  Google Scholar 

    29.
    Flemming, H. C. & Wuertz, S. Bacteria and archaea on Earth and their abundance in biofilms. Nat. Rev. Microbiol. 17, 247–260 (2019).
    CAS  Article  Google Scholar 

    30.
    Karygianni, L., Ren, Z., Koo, H. & Thurnheer, T. Biofilm matrixome: extracellular components in structured microbial communities. Trends Microbiol. 28, 668–681 (2020).
    CAS  Article  Google Scholar 

    31.
    Fulaz, S., Vitale, S., Quinn, L. & Casey, E. Nanoparticle–biofilm interactions: the role of the EPS matrix. Trends Microbiol. 27, 915–926 (2019).
    CAS  Article  Google Scholar 

    32.
    Dragoš, A. & Kovács, Á. T. The peculiar functions of the bacterial extracellular matrix. Trends Microbiol. 25, 257–266 (2017).
    Article  Google Scholar 

    33.
    Mayer, C. et al. The role of intermolecular interactions: studies on model systems for bacterial biofilms. Int. J. Biol. Macromol. 26, 3–16 (1999).
    CAS  Article  Google Scholar 

    34.
    Liang, X. et al. Effects of biofilms of deep-sea bacteria under varying temperatures on larval metamorphosis of Mytilus coruscus (in Chinese with English abstract). J. Fish. China. 44, 131–144 (2020).
    Google Scholar 

    35.
    Huggett, M. J., Williamson, J. E., de Nys, R., Kjelleberg, S. & Steinberg, P. D. Larval settlement of the common Australian sea urchin Heliocidaris erythrogramma in response to bacteria from the surface of coralline algae. Oecologia 149, 604–619 (2006).
    ADS  Article  Google Scholar 

    36.
    Yang, J. L., Satuito, C. G., Bao, W. Y. & Kitamura, H. Induction of metamorphosis of pediveliger larvae of the mussel Mytilus galloprovincialis Lamarck, 1819 using neuroactive compounds, KCl, NH4Cl and organic solvents. Biofouling 24, 461–470 (2008).
    CAS  Article  Google Scholar 

    37.
    Yang, J. L., Li, Y. F., Bao, W. Y., Satuito, C. G. & Kitamura, H. Larval metamorphosis of the mussel Mytilus galloprovincialis Lamarck, 1819 in response to neurotransmitter blockers and tetraethylammonium. Biofouling 27, 193–199 (2011).
    CAS  Article  Google Scholar 

    38.
    Yang, J. L., Satuito, C. G., Bao, W. Y. & Kitamura, H. Larval settlement and metamorphosis of the mussel Mytilus galloprovincialis on different macroalgae. Mar. Biol. 152, 1121–1132 (2007).
    Article  Google Scholar 

    39.
    Bao, W. Y., Lee, O. O., Chung, H. C., Li, M. & Qian, P. Y. Copper affects biofilm inductiveness to larval settlement of the serpulid polychaete Hydroides elegans (Haswell). Biofouling 26, 119–128 (2009).
    Article  Google Scholar 

    40.
    Peng, L. H. et al. A bacterial polysaccharide biosynthesis-related gene inversely regulates larval settlement and metamorphosis of Mytilus coruscus. Biofouling 36, 753–765 (2020).
    CAS  Article  Google Scholar  More

  • in

    Effect of temperature on the unimodal size scaling of phytoplankton growth

    1.
    Finkel, Z. V. et al. Phytoplankton in a changing world: cell size and elemental stoichiometry. J. Plankton Res. 32, 119–137 (2010).
    CAS  Article  Google Scholar 
    2.
    Marañón, E. Cell size as a key determinant of phytoplankton metabolism and community structure. Ann. Rev. Mar. Sci. 7, 241–264 (2015).
    PubMed  Article  PubMed Central  Google Scholar 

    3.
    Chavez, F. P., Messié, M. & Pennington, J. T. marine primary production in relation to climate variability and change. Ann. Rev. Mar. Sci. 3, 227–260 (2011).
    PubMed  Article  PubMed Central  Google Scholar 

    4.
    Kleiber, M. Body size and metabolism. Hilgardia J. Agric. Sci. 6, 315–353 (1932).
    CAS  Article  Google Scholar 

    5.
    Gillooly, J. F. Effects of size and temperature on metabolic rate. Science 293, 2248–2251 (2001).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    6.
    Brown, J. H., Gillooly, J. F., Allen, A. P., Savage, V. M. & West, G. B. Toward a metabolic theory of ecology. Ecology 85, 1771–1789 (2004).
    Article  Google Scholar 

    7.
    Raven, J. A. Why are there no picoplanktonic O2 evolvers with volumes less than 10–19 m3?. J. Plankton Res. 16, 565–580 (1994).
    Article  Google Scholar 

    8.
    Bec, B., Collos, Y., Vaquer, A., Mouillot, D. & Souchu, P. Growth rate peaks at intermediate cell size in marine photosynthetic picoeukaryotes. Limnol. Oceanogr. 53, 863–867 (2008).
    ADS  Article  Google Scholar 

    9.
    Chen, B. & Liu, H. Relationships between phytoplankton growth and cell size in surface oceans: interactive effects of temperature, nutrients, and grazing. Limnol. Oceanogr. 55, 965–972 (2010).
    ADS  CAS  Article  Google Scholar 

    10.
    Marañón, E. et al. Unimodal size scaling of phytoplankton growth and the size dependence of nutrient uptake and use. Ecol. Lett. 16, 371–379 (2013).
    PubMed  Article  PubMed Central  Google Scholar 

    11.
    Ward, B. A., Marañón, E., Sauterey, B., Rault, J. & Claessen, D. The size dependence of phytoplankton growth rates: a trade-off between nutrient uptake and metabolism. Am. Nat. 189, 170–177 (2016).
    PubMed  Article  PubMed Central  Google Scholar 

    12.
    Chen, B., Liu, H., Huang, B. & Wang, J. Temperature effects on the growth rate of marine picoplankton. Mar. Ecol. Prog. Ser. 505, 37–47 (2014).
    ADS  Article  Google Scholar 

    13.
    Sal, S., Alonso-Saez, L., Bueno, J., Garcıa, F. C. & Lopez-Urrutia, A. Thermal adaptation, phylogeny, and the unimodal size scaling of marine phytoplankton growth. Limnol. Oceanogr. 60, 1212–1221 (2015).
    ADS  Article  Google Scholar 

    14.
    Bissinger, J. E., Montagnes, D. J. S., Sharples, J. & Atkinson, D. Predicting marine phytoplankton maximum growth rates from temperature: improving on the Eppley curve using quantile regression. Limnol. Oceanogr. 53, 487–493 (2008).
    ADS  Article  Google Scholar 

    15.
    Chen, B. Patterns of thermal limits of phytoplankton. J. Plankton Res. 37, 285–292 (2015).
    Article  Google Scholar 

    16.
    Thomas, M. K., Kremer, C. T. & Litchman, E. Environment and evolutionary history determine the global biogeography of phytoplankton temperature traits. Glob. Ecol. Biogeogr. 25, 75–86 (2016).
    Article  Google Scholar 

    17.
    Heinle, M. The effects of light, temperature and nutrients on coccolithophores and implications for biogeochemical models (Doctoral dissertation, University of East Anglia, Norwich, United Kingdom). (2013).

    18.
    Kruskopf, M. & Flynn, K. J. Chlorophyll content and fluorescence responses cannot be used to gauge reliably phytoplankton biomass, nutrient status or growth rate. New Phytol. 169, 841–842 (2006).
    Article  CAS  Google Scholar 

    19.
    Flynn, K. J. & Raven, J. A. What is the limit for photoautotrophic plankton growth rates?. J. Plankton Res. 39, 13–22 (2016).
    Article  CAS  Google Scholar 

    20.
    Prakash, A., Skoglund, L., Rystad, B. & Jensen, A. Growth and cell-size distribution of marine planktonic algae in batch and dialysis cultures. J. Fish. Res. Board Canada 30, 143–155 (1973).
    Article  Google Scholar 

    21.
    Xia, L., Huang, R., Li, Y. & Song, S. The effect of growth phase on the surface properties of three oleaginous microalgae (Botryococcus sp. FACGB-762, Chlorella sp. XJ-445 and Desmodesmus bijugatus XJ-231). PLoS ONE 12, e0186434 (2017).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    22.
    Verdy, A., Follows, M. & Flierl, G. Optimal phytoplankton cell size in an allometric model. Mar. Ecol. Prog. Ser. 379, 1–12 (2009).
    ADS  Article  Google Scholar 

    23.
    Kempes, C. P., Dutkiewicz, S. & Follows, M. J. Growth, metabolic partitioning, and the size of microorganisms. Proc. Natl. Acad. Sci. U.S.A. 109, 495–500 (2012).
    ADS  CAS  PubMed  Article  Google Scholar 

    24.
    Stawiarski, B., Buitenhuis, E. T. & Quéré, C. L. The physiological response of picophytoplankton to temperature and its model representation. Front. Mar. Sci. 3, 1–13 (2016).
    Article  Google Scholar 

    25.
    Martiny, A. C., Ma, L., Mouginot, C., Chandler, J. W. & Zinser, E. R. Interactions between thermal acclimation, growth rate, and phylogeny influence prochlorococcus elemental stoichiometry. PLoS ONE 11, 1–12 (2016).
    Article  CAS  Google Scholar 

    26.
    Mackey, K. R. M. et al. Effect of temperature on photosynthesis and growth in marine Synechococcus spp. Plant Physiol. 163, 815–829 (2013).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    27.
    Demory, D. et al. Picoeukaryotes of the Micromonas genus: sentinels of a warming ocean. ISME J. 13, 132–146 (2018).
    PubMed  PubMed Central  Article  Google Scholar 

    28.
    Pittera, J. et al. Connecting thermal physiology and latitudinal niche partitioning in marine Synechococcus. ISME J. 8, 1221–1236 (2014).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    29.
    Barton, S. & Yvon-Durocher, G. Quantifying the temperature dependence of growth rate in marine phytoplankton within and across species. Limnol. Oceanogr. 64, 2081–2091 (2019).
    ADS  Article  Google Scholar 

    30.
    Kremer, C. T., Thomas, M. K. & Litchman, E. Temperature- and size-scaling of phytoplankton population growth rates: reconciling the Eppley curve and the metabolic theory of ecology. Limnol. Oceanogr. 62, 1658–1670 (2017).
    ADS  Article  Google Scholar 

    31.
    Berthelot, H. et al. NanoSIMS single cell analyses reveal the contrasting nitrogen sources for small phytoplankton. ISME J. 13, 651–662 (2019).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    32.
    Duhamel, S., Kim, E., Sprung, B. & Anderson, O. R. Small pigmented eukaryotes play a major role in carbon cycling in the P-depleted western subtropical North Atlantic, which may be supported by mixotrophy. Limnol. Oceanogr. 64, 2424–2440 (2019).
    ADS  CAS  Article  Google Scholar 

    33.
    Worden, A. Z., Nolan, J. K. & Palenik, B. Assessing the dynamics and ecology of marine picophytoplankton: the importance of the eukaryotic component. Limnol. Oceanogr. 49, 168–179 (2004).
    ADS  CAS  Article  Google Scholar 

    34.
    Gutierrez-Rodríguez, A., Selph, K. E. & Landry, M. R. Phytoplankton growth and microzooplankton grazing dynamics across vertical environmental gradients determined by transplant in situ dilution experiments. J. Plankton Res. 38, 271–289 (2015).
    PubMed  PubMed Central  Article  Google Scholar 

    35.
    Worden, A. Z. & Binder, B. J. Application of dilution experiments for measuring growth and mortality rates among Prochlorococcus and Synechococcus populations in oligotrophic environments. Aquat. Microb. Ecol. 30, 159–174 (2003).
    Article  Google Scholar 

    36.
    DeLong, J. P., Okie, J. G., Moses, M. E., Sibly, R. M. & Brown, J. H. Shifts in metabolic scaling, production, and efficiency across major evolutionary transitions of life. Proc. Natl. Acad. Sci. U.S. A. 107, 12941–12945 (2010).
    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

    37.
    García, F. C. et al. The allometry of the smallest: superlinear scaling of microbial metabolic rates in the Atlantic Ocean. ISME J. 10, 1029–1036 (2016).
    PubMed  Article  CAS  Google Scholar 

    38.
    Kiørboe, T. Turbulence, phytoplankton cell size, and the structure of pelagic food webs. Adv. Mar. Biol. 29, 1–72 (1993).
    Article  Google Scholar 

    39.
    Marãnón, E. et al. Resource supply overrides temperature as a controlling factor of marine phytoplankton growth. PLoS ONE 9, 20–23 (2014).
    Article  CAS  Google Scholar 

    40.
    Behrenfeld, M. J., Boss, E., Siegel, D. A. & Shea, D. M. Carbon-based ocean productivity and phytoplankton physiology from space. Global Biogeochem. Cycles 19, 1–14 (2005).
    Article  CAS  Google Scholar 

    41.
    Tsuda, A. et al. A mesoscale iron enrichment in the Western subarctic Pacific induces a large centric diatom bloom. Science 300, 958–961 (2003).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    42.
    Latasa, M., Landry, M. R., Schlüter, L. & Bidigare, R. R. Pigment-specific growth and grazing rates of phytoplankton in the central equatorial pacific. Limnol. Oceanogr. 42, 289–298 (1997).
    ADS  CAS  Article  Google Scholar 

    43.
    Cavender-Bares, K. K., Mann, E. L., Chisholm, S. W., Ondrusek, M. E. & Bidigare, R. R. Differential response of equatorial Pacific phytoplankton to iron fertilization. Limnol. Oceanogr. 44, 237–246 (1999).
    ADS  CAS  Article  Google Scholar 

    44.
    Mouriño-Carballido, B. et al. Nutrient supply controls picoplankton community structure during three contrasting seasons in the northwestern Mediterranean Sea. Mar. Ecol. Prog. Ser. 543, 1–19 (2016).
    ADS  Article  CAS  Google Scholar 

    45.
    Schmidt, K. et al. Increasing picocyanobacteria success in shelf waters contributes to long-term food web degradation. Glob. Chang. Biol. https://doi.org/10.1111/gcb.15161 (2020).
    Article  PubMed  PubMed Central  Google Scholar 

    46.
    Tarran, G. A., Heywood, J. L. & Zubkov, M. V. Latitudinal changes in the standing stocks of nano- and picoeukaryotic phytoplankton in the Atlantic Ocean. Deep Res. Part II Top. Stud. Oceanogr. 53, 1516–1529 (2006).
    ADS  Article  Google Scholar 

    47.
    Marañón, E., Cermeño, P., Latasa, M. & Tadonléké, R. D. Temperature, resources, and phytoplankton size structure in the ocean. Limnol. Oceanogr. 57, 1266–1278 (2012).
    ADS  Article  Google Scholar 

    48.
    Chisholm, S. W. Phytoplankton Size. Prim. Product. Biogeochem. Cycles Sea 02139, 213–237 (1992).
    Article  Google Scholar 

    49.
    Montes-Pérez, J. J. et al. Intermediate-size cell dominance in the phytoplankton community of an eutrophic, estuarine ecosystem (Guadalhorce River, Southern Spain). Hydrobiologia 847, 2241–2254 (2020).
    Article  CAS  Google Scholar 

    50.
    Chen, B. & Laws, E. A. Is there a difference of temperature sensitivity between marine phytoplankton and heterotrophs?. Limnol. Oceanogr. 62, 806–817 (2016).
    ADS  Article  Google Scholar 

    51.
    Eppley, R. W. Temperature and phytoplankton growth in the sea. Fish. Bull. 70, 1063–1085 (1972).
    Google Scholar 

    52.
    Johnson, F. & Lewin, I. The growth rate of E. coli in relation to temperature, Quinine and Coenzyme. J. Cell Physiol. 28, 47–75 (1946).
    CAS  Article  Google Scholar 

    53.
    Dell, A. I., Pawar, S. & Savage, V. M. Systematic variation in the temperature dependence of physiological and ecological traits. Proc. Natl. Acad. Sci. U.S.A. 108, 10591–10596 (2011).
    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar  More

  • in

    Temporal division of labor in an aphid social system

    1.
    Wilson, E. O. The Insect Societies (Harvard University Press, Cambridge, 1971).
    Google Scholar 
    2.
    Wilson, E. O. Sociobiology: The New Synthesis (Harvard University Press, Cambridge, 1975).
    Google Scholar 

    3.
    Oster, G. F. & Wilson, E. O. Caste and Ecology in the Social Insects (Princeton University Press, Princeton, 1978).
    Google Scholar 

    4.
    Seeley, T. D. Honeybee Ecology: A Study of Adaptation in Social Life (Princeton University Press, Princeton, 1985).
    Google Scholar 

    5.
    Seeley, T. D. Adaptive significance of the age polyethism schedule in honeybee colonies. Behav. Ecol. Sociobiol. 11, 287–293 (1982).
    Article  Google Scholar 

    6.
    Robinson, G. E. Regulation of division of labor in insect societies. Annu. Rev. Entomol. 37, 637–665 (1992).
    CAS  PubMed  Article  Google Scholar 

    7.
    Beshers, S. N. & Fewell, J. H. Models of division of labor in social insects. Annu. Rev. Entomol. 46, 413–440 (2001).
    CAS  PubMed  Article  Google Scholar 

    8.
    Johnson, B. R. Within-nest temporal polyethism in the honey bee. Behav. Ecol. Sociobiol. 62, 777–784 (2008).
    Article  Google Scholar 

    9.
    Hölldobler, B. & Wilson, E. O. The Ants (Harvard University Press, Cambridge, 1990).
    Google Scholar 

    10.
    Crosland, M. W. J., Lok, C. M., Wong, T. C., Shakarad, M. & Traniello, J. F. A. Division of labour in a lower termite: The majority of tasks are performed by older workers. Anim. Behav. 54, 999–1012 (1997).
    CAS  PubMed  Article  Google Scholar 

    11.
    Hinze, B. & Leuthold, R. H. Age related polyethism and activity rhythms in the nest of the termite Macrotermes bellicosus (Isoptera, Termitidae). Insect. Soc. 46, 392–397 (1999).
    Article  Google Scholar 

    12.
    Cameron, S. A. Temporal patterns of division of labor among workers in the primitively eusocial bumble bee, Bombus griseocoffis (Hymenoptera: Apidae). Ethology 80, 137–151 (1989).
    Article  Google Scholar 

    13.
    Naug, D. & Gadagkar, R. The role of age in temporal polyethism in a primitively eusocial wasp. Behav. Ecol. Sociobiol. 42, 37–47 (1998).
    Article  Google Scholar 

    14.
    Biedermann, P. H. W. & Taborsky, M. Larval helpers and age polyethism in ambrosia beetles. Proc. Natl. Acad. Sci. USA 108, 17064–17069 (2011).
    ADS  CAS  PubMed  Article  Google Scholar 

    15.
    Wakano, J. N., Nakata, K. & Yamamura, N. Dynamic model of optimal age polyethism in social insects under stable and fluctuating environments. J. Theor. Biol. 193, 153–165 (1998).
    Article  Google Scholar 

    16.
    Duarte, A., Weissing, F. J., Pen, I. & Keller, L. An evolutionary perspective on self-organized division of labor in social insects. Annu. Rev. Ecol. Evol. Syst. 42, 91–110 (2011).
    Article  Google Scholar 

    17.
    Stern, D. L. & Foster, W. A. The evolution of soldiers in aphids. Biol. Rev. 71, 27–79 (1996).
    CAS  PubMed  Article  Google Scholar 

    18.
    Aoki, S. & Kurosu, U. A review of the biology of Cerataphidini (Hemiptera, Aphididae, Hormaphidinae), focusing mainly on their life cycles, gall formation, and soldiers. Psyche 2010, 380351 (2010).
    Google Scholar 

    19.
    Abbot, P., Tooker, J. & Lawson, S. P. Chemical ecology and sociality in aphids: Opportunities and directions. J. Chem. Ecol. 44, 770–784 (2018).
    CAS  PubMed  Article  Google Scholar 

    20.
    Aoki, S. Colophina clematis (Homoptera, Pemphigidae), an aphid species with” soldiers”. Kontyu 5, 276–282 (1977).
    Google Scholar 

    21.
    Aoki, S. & Kurosu, U. Gall cleaning by the aphid Hormaphis betulae. J. Ethol. 9, 51–55 (1989).
    Google Scholar 

    22.
    Benton, T. G. & Foster, W. A. Altruistic housekeeping in a social aphid. Proc. R. Soc. B 247, 199–202 (1992).
    ADS  Article  Google Scholar 

    23.
    Aoki, S. & Kurosu, U. Soldiers of Astegopteryx styraci (Homoptera, Aphidoidea) clean their gall. Jpn. J. Entomol. 57, 407–416 (1989).
    Google Scholar 

    24.
    Aoki, S., Kurosu, U. & Stern, D. L. Aphid soldiers discriminate between soldiers and non-soldiers, rather than between kin and non-kin Ceratoglyphina bambusae. Anim. Behav. 42, 865–866 (1991).
    Article  Google Scholar 

    25.
    Kurosu, U., Narukawa, J., Buranapanichpan, S. & Aoki, S. Head-plug defense in a gall aphid. Insect. Soc. 53, 86–91 (2006).
    Article  Google Scholar 

    26.
    Kurosu, U., Aoki, S. & Fukatsu, T. Self-sacrificing gall repair by aphid nymphs. Proc. R. Soc. B 270, S12–S14 (2003).
    PubMed  Article  Google Scholar 

    27.
    Pike, N. & Foster, W. Fortress repair in the social aphid species Pemphigus spyrothecae. Anim. Behav. 67, 909–914 (2004).
    Article  Google Scholar 

    28.
    Kutsukake, M., Shibao, H., Uematsu, K. & Fukatsu, T. Scab formation and wound healing of plant tissue by soldier aphid. Proc. R. Soc. B 276, 1555–1563 (2009).
    PubMed  Article  Google Scholar 

    29.
    Kutsukake, M. et al. Exaggeration and cooption of innate immunity for social defense. Proc. Natl. Acad. Sci. USA 116, 8950–8959 (2019).
    CAS  PubMed  Article  Google Scholar 

    30.
    Aoki, S. Evolution of sterile soldiers in aphids. In Animal Societies: Theories andFacts (eds Ito, Y. et al.) 53–65 (Japan Scientific Societies Press, Tokyo, 1987).
    Google Scholar 

    31.
    Aoki, S. & Kurosu, U. Social aphids. In Encyclopedia of Social Insects (ed. Starr, C. K.) (Springer, New York, 2020). https://doi.org/10.1007/978-3-319-90306-4_107-1.
    Google Scholar 

    32.
    Aoki, S. & Kurosu, U. Biennial galls of the aphid Astegopteryx styraci on a temperate deciduous tree Styrax obassia. Acta Phytopathol. Entomol. Hung. 25, 57–65 (1990).
    Google Scholar 

    33.
    Shibao, H., Kutsukake, M., Lee, J. & Fukatsu, T. Maintenance of soldier-producing aphids on an artificial diet. J. Insect Physiol. 48, 495–505 (2002).
    CAS  PubMed  Article  Google Scholar 

    34.
    Shibao, H., Lee, J. M., Kutsukake, M. & Fukatsu, T. Aphid soldier differentiation: density acts on both embryos and newborn nymphs. Naturwissenschaften 90, 501–504 (2003).
    ADS  CAS  PubMed  Article  Google Scholar 

    35.
    Shibao, H., Kutsukake, M. & Fukatsu, T. Density triggers soldier production in a social aphid. Proc. R. Soc. B 271, S71–S74 (2004).
    PubMed  Article  Google Scholar 

    36.
    Shibao, H., Kutsukake, M. & Fukatsu, T. The proximate cue of density-dependent soldier production in a social aphid. J. Insect Physiol. 50, 143–147 (2004).
    CAS  PubMed  Article  Google Scholar 

    37.
    Shibao, H., Kutsukake, M. & Fukatsu, T. Density-dependent induction and suppression of soldier differentiation in an aphid social system. J. Insect Physiol. 50, 995–1000 (2004).
    CAS  PubMed  Article  Google Scholar 

    38.
    Shibao, H., Kutsukake, M., Matsuyama, S., Fukatsu, T. & Shimada, M. Mechanisms regulating caste differentiation in an aphid social system. Commun. Integr. Biol. 3, 1–5 (2010).
    PubMed  PubMed Central  Article  Google Scholar 

    39.
    Kutsukake, M. et al. Venomous protease of aphid soldier for colony defense. Proc. Natl. Acad. Sci. USA 101, 11338–11343 (2004).
    ADS  CAS  PubMed  Article  Google Scholar 

    40.
    Stern, D. L., Aoki, S. & Kurosu, U. A test of geometric hypotheses for soldier investment patterns in the gall producing tropical aphid Cerataphis fransseni (Homoptera, Hormaphididae). Insect. Soc. 41, 457–460 (1994).
    Article  Google Scholar 

    41.
    Pike, N., Braendle, C. & Foster, W. A. Seasonal extension of the soldier instar as a route to increased defence investment in the social aphid Pemphigus spyrothecae. Ecol. Entomol. 29, 89–95 (2004).
    Article  Google Scholar 

    42.
    Pike, N. Specialised placement of morphs within the gall of the social aphid Pemphigus spyrothecae. BMC Evol. Biol. 7, 18 (2007).
    PubMed  PubMed Central  Article  Google Scholar 

    43.
    Uematsu, K., Kutsukake, M., Fukatsu, T., Shimada, M. & Shibao, H. Altruistic colony defense by menopausal female insects. Curr. Biol. 20, 1182–1186 (2010).
    CAS  PubMed  Article  Google Scholar 

    44.
    Uematsu, K., Shimada, M. & Shibao, H. Juveniles and the elderly defend, the middle-aged escape: division of labour in a social aphid. Biol. Let. 9, 20121053 (2013).
    Article  Google Scholar 

    45.
    Abe, T., Bignell, D. E., Higashi, M. & Abe, Y. Termites: Evolution, Sociality, Symbioses, Ecology (Springer, Berlin, 2000).
    Google Scholar 

    46.
    Shibao, H. Lack of kin discrimination in the eusocial aphid Pseudoregma bambucicola (Homoptera: Aphididae). J. Ethol. 17, 17–24 (1999).
    Article  Google Scholar 

    47.
    Abbot, P., Withgott, J. H. & Moran, N. A. Genetic conflict and conditional altruism in social aphid colonies. Proc. Natl. Acad. Sci. USA 98, 12068–12071 (2001).
    ADS  CAS  PubMed  Article  Google Scholar 

    48.
    Abbot, P. & Chhatre, V. Kin structure provides no explanation for intruders in social aphids. Mol. Ecol. 16, 3659–3670 (2007).
    CAS  PubMed  Article  Google Scholar 

    49.
    Kutsukake, M. et al. An insect-induced novel plant phenotype for sustaining social life in a closed system. Nat. Commun. 3, 1187 (2012).
    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

    50.
    Kutsukake, M. et al. Evolution of soldier-specific venomous protease in social aphids. Mol. Biol. Evol. 25, 2627–2641 (2008).
    CAS  PubMed  Article  Google Scholar  More

  • in

    Water constraints drive allometric patterns in the body shape of tree frogs

    1.
    Adams, D. C. & Nistri, A. Ontogenetic convergence and evolution of foot morphology in european cave salamanders (Family: Plethodontidae). BMC Evol. Biol. 10, 216 (2010).
    PubMed  PubMed Central  Article  Google Scholar 
    2.
    Baken, E. K., Mellenthin, L. E. & Adams, D. C. Macroevolution of desiccation-related morphology in plethodontid salamanders as inferred from a novel surface area to volume ratio estimation approach. Evolution 74, 476–486 (2020).
    PubMed  Article  Google Scholar 

    3.
    Martinez, P. A. et al. The contribution of neutral evolution and adaptive processes in driving phenotypic divergence in a model mammalian species, the andean fox Lycalopex culpaeus. J. Biogeogr. 45, 1114–1125 (2018).
    Article  Google Scholar 

    4.
    Vidal-García, M., Byrne, P. G., Roberts, J. D. & Keogh, J. S. The role of phylogeny and ecology in shaping morphology in 21 genera and 127 species of australo-papuan myobatrachid frogs. J. Evol. Biol. 27, 181–192 (2014).
    PubMed  Article  Google Scholar 

    5.
    Adams, D. C. Parallel evolution of character displacement driven by competitive selection in terrestrial salamanders. BMC Evol. Biol. 10, 72 (2010).
    PubMed  PubMed Central  Article  Google Scholar 

    6.
    Losos, J. B. Ecological character displacement and the study of adaptation. Proc. Natl. Acad. Sci. 97, 5693–5695 (2000).
    ADS  CAS  PubMed  Article  Google Scholar 

    7.
    Moen, D. S., Irschick, D. J. & Wiens, J. J. Evolutionary conservatism and convergence both lead to striking similarity in ecology, morphology and performance across continents in frogs. Proc. R. Soc. B. 280, 20132156 (2013).
    PubMed  Article  Google Scholar 

    8.
    Amado, T. F., Bidau, C. J. & Olalla-Tárraga, M. Á. Geographic variation of body size in new world anurans: energy and water in a balance. Ecography 42, 456–466 (2019).
    Article  Google Scholar 

    9.
    Gouveia, S. F. et al. Biophysical modeling of water economy can explain geographic gradient of body size in anurans. Am. Nat. 193, 51–58 (2019).
    PubMed  Article  PubMed Central  Google Scholar 

    10.
    Olalla-Tárraga, M. Á., Diniz-Filho, J. A. F., Bastos, R. P. & Rodríguez, M. Á. Geographic body size gradients in tropical regions: water deficit and anuran body size in the brazilian cerrado. Ecography 32, 581–590 (2009).
    Article  Google Scholar 

    11.
    Cooney, C. R. et al. Ecology and allometry predict the evolution of avian developmental durations. Nat. Commun. 11, 1–9 (2020).
    Article  CAS  Google Scholar 

    12.
    Kriegman, S., Cheney, N. & Bongard, J. How morphological development can guide evolution. Sci. Rep. 8, 1–10 (2018).
    Article  CAS  Google Scholar 

    13.
    Moczek, A. P. Re-evaluating the environment in developmental evolution. Front. Ecol. Evol. 3, 1–8 (2015).
    Article  Google Scholar 

    14.
    Richter-Boix, A., Tejedo, M. & Rezende, E. L. Evolution and plasticity of anuran larval development in response to desiccation. a comparative analysis. Ecol. Evol. 1, 15–25 (2011).
    PubMed  PubMed Central  Article  Google Scholar 

    15.
    Castro, K. M. S. A., do Santos, M. P., Brito, M. F. G., Bidau, C. J. & Martinez, P. A. Ontogenetic allometry conservatism across five teleost orders. J. Fish Biol. 93, 745–749 (2018).
    Article  Google Scholar 

    16.
    Skúlason, S. et al. A way forward with eco evo devo: an extended theory of resource polymorphism with postglacial fishes as model systems. Biol. Rev. 94, 1786–1808 (2019).
    PubMed  Article  Google Scholar 

    17.
    Porter, W. P. & Gates, D. M. Thermodynamic equilibria of animals with environment. Ecol. Monogr. 39, 227–244 (1969).
    Article  Google Scholar 

    18.
    Thompson, D. A. On Growth and Form (Cambridge University Press, Cambridge, 1917).
    Google Scholar 

    19.
    Schmidt-Nielsen, K. Scaling: Why is Animal Size so Important? (Cambridge University Press, Cambridge, 1984).
    Google Scholar 

    20.
    Amado, T. F., Pinto, M. G. M. & Olalla-Tárraga, M. Á. Anuran 3d models reveal the relationship between surface area-to-volume ratio and climate. J. Biogeogr. 46, 1429–1437 (2019).
    Google Scholar 

    21.
    Ashton, K. G. Do amphibians follow bergmann’s rule?. Can. J. Zool. 80, 708–716 (2002).
    Article  Google Scholar 

    22.
    Glazier, D. Effects of contingency versus constraints on the body-mass scaling of metabolic rate. Challenges 9, 4 (2018).
    Article  Google Scholar 

    23.
    Gouveia, S. F. & Correia, I. Geographical clines of body size in terrestrial amphibians: water conservation hypothesis revisited. J. Biogeogr. 43, 2075–2084 (2016).
    Article  Google Scholar 

    24.
    Lindsey, C. C. Body sizes of poikilotherm vertebrates at different latitudes. Evolution 20, 456–465 (1966).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    25.
    Bergmannn, C. Über die verhältnisse der wärmeökonomie der thiere zu ihrer grösse. Göttinger Stud. 1, 595–708 (1847).
    Google Scholar 

    26.
    Nevo, E. Adaptive variation in size of cricket frogs. Ecology 54, 1271–1281 (1973).
    Article  Google Scholar 

    27.
    Tracy, C. R., Christian, K. A. & Tracy, C. R. Not just small, wet, and cold : effects of body size and skin resistance on thermoregulation and arboreality of frogs. Ecology 91, 1477–1484 (2010).
    PubMed  Article  PubMed Central  Google Scholar 

    28.
    Wells, K. D. The Ecology and Behavior of Amphibians (The University of Chicago Press, Chicago, 2007).
    Google Scholar 

    29.
    Perez, D., Sheehy, C. M. & Lillywhite, H. B. Variation of organ position in snakes. J. Morphol. 280, 1798–1807 (2019).
    PubMed  Article  PubMed Central  Google Scholar 

    30.
    Amiel, J. J., Chua, B., Wassersug, R. J. & Jones, D. R. Temperature-dependent regulation of blood distribution in snakes. J. Exp. Biol. 214, 1458–1462 (2011).
    PubMed  Article  PubMed Central  Google Scholar 

    31.
    Canals, M. Thermal ecology of small animals. Biol Res 31, 367–374 (1998).
    Google Scholar 

    32.
    Tracy, C. R. A model of the dynamic exchanges of water and energy between a terrestrial amphibian and its environment. Ecol. Monogr. 46, 293–326 (1976).
    Article  Google Scholar 

    33.
    Gould, S. J. Allometry and size in ontogeny and phylogeny. Biol. Rev. 41, 587–640 (1966).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    34.
    Klingenberg, C. P. Heterochrony and allometry: the analysis of evolutionary change in ontogeny. Biol. Rev. 73, 79–123 (1998).
    CAS  PubMed  Article  Google Scholar 

    35.
    Klingenberg, C. P. Size, shape, and form: concepts of allometry in geometric morphometrics. Dev. Genes Evol. 226, 113–137 (2016).
    PubMed  PubMed Central  Article  Google Scholar 

    36.
    Voje, K. L., Hansen, T. F., Egset, C. K., Bolstad, G. H. & Pélabon, C. Allometric constraints and the evolution of allometry. Evolution 68, 866–885 (2014).
    PubMed  Article  Google Scholar 

    37.
    Pélabon, C. et al. Evolution of morphological allometry. Ann. N. Y. Acad. Sci. 1320, 58–75 (2014).
    ADS  PubMed  Article  Google Scholar 

    38.
    Duellman, W. E., Marion, A. B. & Hedges, S. B. Phylogenetics, classification, and biogeography of the treefrogs (amphibia: anura: arboranae). Zootaxa 4104, 001–109 (2016).
    Article  Google Scholar 

    39.
    Kamilar, J. M. & Cooper, N. Phylogenetic signal in primate behaviour, ecology and life history. Phil. Trans. R. Soc. B. 368, 20120341 (2013).
    PubMed  Article  Google Scholar 

    40.
    Landis, M. J. & Schraiber, J. G. Pulsed evolution shaped modern vertebrate body sizes. Proc. Natl. Acad. Sci. U. S. A. 114, 13224–13229 (2017).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    41.
    Levy, D. L. & Heald, R. Biological scaling problems and solutions in amphibians. Cold Spring Harb. Perspect. Biol. 8, a019166 (2015).
    PubMed  Article  PubMed Central  Google Scholar 

    42.
    Boutilier, R. G., Stiffler, D. F. & Toews, D. Exchange of respiratory gases, ions, and water in amphibious and aquatic amphibians. In Environmental Physiology of Amphibians (eds Feder, M. E. & Burggren, W. W.) 81–124 (University of Chicago Press, Chicago, 1992).
    Google Scholar 

    43.
    Spotila, J. R., O’connor, M. P. & Bakken, G. S. Biophysics of heat and mass transfer. In Environmental Physiology of the Amphibians (eds Feder, M. E. & Burggren, W. W.) 59–80 (University of Chicago Press, Chicago, 1992).
    Google Scholar 

    44.
    Sanger, T. J. et al. Convergent evolution of sexual dimorphism in skull shape using distinct developmental strategies. Evolution 67, 2180–2193 (2013).
    PubMed  Article  PubMed Central  Google Scholar 

    45.
    Navas, C. A., Antoniazzi, M. M. & Jared, C. A preliminary assessment of anuran physiological and morphological adaptation to the caatinga, a brazilian semi-arid environment. Int. Congr. Ser. 1275, 298–305 (2004).
    Article  Google Scholar 

    46.
    Wiley, D. F. et al. Evolutionary Morphing Minneapolis, MN, USA Minneapolis, MN, USA (IEEE Computer Society, Minneapolis, 2005).
    Google Scholar 

    47.
    Klingenberg, C. P. & Gidaszewski, N. A. Testing and quantifying phylogenetic signals and homoplasy in morphometric data. Syst. Biol. 59, 245–261 (2010).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    48.
    Dryden, I. L. & Mardia, K. V. Statistical Shape Analysis (Wiley, Hoboken, 1998).
    Google Scholar 

    49.
    Adams, D. C. A generalized k statistic for estimating phylogenetic signal from shape and other high-dimenstional multivariate data. Syst. Biol. 63(5), 685–697 (2014).
    PubMed  Article  PubMed Central  Google Scholar 

    50.
    Jetz, W. & Pyron, R. A. The interplay of past diversification and evolutionary isolation with present imperilment across the amphibian tree of life. Nat. Ecol. Evol. 2, 850–858 (2018).
    PubMed  Article  Google Scholar 

    51.
    Adams, D. C. & Otárola-Castillo, E. Geomorph: an r package for the collection and analysis of geometric morphometric shape data. Methods Ecol. Evol. 4, 393–399 (2013).
    Article  Google Scholar 

    52.
    Fox, J. & Hong, J. Effect displays in r for multinomial and proportional-odds logit models: extensions to the effects package. J. Stat. Softw. 32, 1–24 (2009).
    Article  Google Scholar 

    53.
    R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna, Austria, 2016). More