More stories

  • in

    Genotyping-in-Thousands by sequencing panel development and application for high-resolution monitoring of introgressive hybridization within sockeye salmon

    Winston, M. R. & Taylor, C. M. Upstream extirpation of four minnow species due to damming of a prairie stream. Trans. Am. Fish. Soc. 120, 8 (1991).
    Google Scholar 
    Graham, K. Contemporary status of the North American paddlefish, Polyodon spathula. Environ. Biol. Fishes 48, 279–289 (1997).
    Google Scholar 
    Kaushal, S. S. et al. Rising stream and river temperatures in the United States. Front. Ecol. Environ. 8, 461–466 (2010).
    Google Scholar 
    Vörösmarty, C. J. et al. Global threats to human water security and river biodiversity. Nature 467, 555–561 (2010).PubMed 
    ADS 

    Google Scholar 
    Galbreath, P. F., Bisbee, M. A., Dompier, D. W., Kamphaus, C. M. & Newsome, T. H. Extirpation and tribal reintroduction of coho salmon to the interior columbia river basin. Fisheries 39, 77–87 (2014).
    Google Scholar 
    Schmidt, B. A. et al. Determining habitat limitations of Maumee River walleye production to western Lake Erie fish stocks: Documenting a spawning ground barrier. J. Gt. Lakes Res. 46, 1661–1673 (2020).
    Google Scholar 
    Kendall, N. W., Marston, G. W. & Klungle, M. M. Declining patterns of Pacific Northwest steelhead trout (Oncorhynchus mykiss) adult abundance and smolt survival in the ocean. Can. J. Fish. Aquat. Sci. 74, 1275–1290 (2017).
    Google Scholar 
    Myers, J., Bryant, G. & Lynch, J. Factors Contributing to the Decline of Chinook Salmon: An Addendum to the 1996 West Coast Steelhead Factors for Decline Report (Springer, 1998).
    Google Scholar 
    Molony, B. W., Lenanton, R., Jackson, G. & Norriss, J. Stock enhancement as a fisheries management tool. Rev. Fish Biol. Fish. 13, 409–432 (2005).
    Google Scholar 
    Merz, J. E. & Setka, J. D. Evaluation of a spawning habitat enhancement site for Chinook salmon in a regulated California river. N. Am. J. Fish. Manag. 24, 397–407 (2004).
    Google Scholar 
    Ostberg, C. O., Chase, D. M. & Hauser, L. Hybridization between yellowstone cutthroat trout and rainbow trout alters the expression of muscle growth-related genes and their relationships with growth patterns. PLoS ONE 10, e0141373 (2015).PubMed 
    PubMed Central 

    Google Scholar 
    Veale, A. J. & Russello, M. A. Sockeye salmon repatriation leads to population re-establishment and rapid introgression with native kokanee. Evol. Appl. 9, 1301–1311 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Fraser, D. J., Cook, A. M., Eddington, J. D., Bentzen, P. & Hutchings, J. A. Mixed evidence for reduced local adaptation in wild salmon resulting from interbreeding with escaped farmed salmon: Complexities in hybrid fitness. Evol. Appl. 1, 501–512 (2008).PubMed 
    PubMed Central 

    Google Scholar 
    Stewart, G. S. et al. The power of evolutionary rescue is constrained by genetic load. Evol. Appl. 10, 731–741 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Weeks, A. R. et al. Genetic rescue increases fitness and aids rapid recovery of an endangered marsupial population. Nat. Commun. 8, 1071 (2017).PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    Chan, W. Y., Hoffmann, A. A. & van Oppen, M. J. H. Hybridization as a conservation management tool. Conserv. Lett. 12, e12652 (2019).
    Google Scholar 
    Bekkevold, D., Hansen, M. M. & Nielsen, E. E. Genetic impact of gadoid culture on wild fish populations: Predictions, lessons from salmonids, and possibilities for minimizing adverse effects. ICES J. Mar. Sci. 63, 198–208 (2006).
    Google Scholar 
    Muhlfeld, C. C. et al. Hybridization rapidly reduces fitness of a native trout in the wild. Biol. Lett. 5, 328–331 (2009).PubMed 
    PubMed Central 

    Google Scholar 
    Harvey, A. C., Glover, K. A., Taylor, M. I., Creer, S. & Carvalho, G. R. A common garden design reveals population-specific variability in potential impacts of hybridization between populations of farmed and wild Atlantic salmon, Salmo salar L. Evol. Appl. 9, 435–449 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Edmands, S. Does parental divergence predict reproductive compatibility?. Trends Ecol. Evol. 17, 520–527 (2002).
    Google Scholar 
    Johnson, B. M., Johnson, M. S. & Thorgaard, G. H. Salmon genetics and management in the Columbia river basin. Northwest Sci. 92, 346–363 (2019).
    Google Scholar 
    Hanson, A. J. & Smith, H. D. Mate selection in a population of sockeye salmon (Oncorhynchus nerka) of mixed age-groups. J. Fish. Board Can. 24, 23 (1967).
    Google Scholar 
    Wood, C. C. & Foote, C. J. Evidence for sympatric genetic divergence of anadromous and nonanadromous morphs of sockeye salmon (Oncorhynchus nerka). Evolution 50, 1265–1279 (1996).PubMed 

    Google Scholar 
    Foote, C. J. Male mate choice dependent on male size in salmon. Behaviour 106, 63–80 (1988).
    Google Scholar 
    Craig, J. K., Foote, C. J. & Wood, C. C. Countergradient variation in carotenoid use between sympatric morphs of sockeye salmon (Oncorhynchus nerka) exposes nonanadromous hybrids in the wild by their mismatched spawning colour. Biol. J. Linn. Soc. 84, 287–305 (2005).
    Google Scholar 
    Taylor, E. B. & Foote, C. J. Critical swimming velocities of juvenile sockeye salmon and kokanee, the anadromous and non-anadromous forms of Oncorhynchus nerka (Walbaum). J. Fish Biol. 38, 407–419 (1991).
    Google Scholar 
    Foote, C. J., Wood, C. C., Clarke, W. C. & Blackburn, J. Circannual cycle of seawater adaptability in Oncorhynchus nerka: Genetic differences between sympatric sockeye salmon and kokanee. Can. J. Fish. Aquat. Sci. 49, 99–109 (1992).
    Google Scholar 
    Wood, C. C. & Foote, C. J. Genetic differences in the early development and growth of sympatric sockeye salmon and kokanee (Oncorhynchus nerka), and their hybrids. Can. J. Fish. Aquat. Sci. 47, 2250–2260 (1990).
    Google Scholar 
    Elliott, L. D., Ward, H. G. M. & Russello, M. A. Kokanee–sockeye salmon hybridization leads to intermediate morphology and resident life history: Implications for fisheries management. Can. J. Fish. Aquat. Sci. 77, 355–364 (2020).
    Google Scholar 
    Hendry, A. P., Quinn, T. P. & Utter, F. M. Genetic evidence for the persistence and divergence of native and introduced sockeye salmon (Oncorhynchus nerka) within Lake Washington, Washington. Can. J. Fish. Aquat. Sci. 53, 823–832 (1996).
    Google Scholar 
    Praebel, K. et al. A diagnostic tool for efficient analysis of the population structure, hybridization and conservation status of European whitefish (Coregonus lavaretus (L.)) and vendace (C. albula (L.)). Adv. Limnol. 64, 247–255 (2013).
    Google Scholar 
    Sanz, N., Araguas, R. M., Fernández, R., Vera, M. & García-Marín, J.-L. Efficiency of markers and methods for detecting hybrids and introgression in stocked populations. Conserv. Genet. 10, 225–236 (2009).CAS 

    Google Scholar 
    Mcfarlane, S. & Pemberton, J. Detecting the true extent of introgression during anthropogenic hybridization. Trends Ecol. Evol. 34, 315–326 (2019).PubMed 

    Google Scholar 
    Vähä, J.-P. & Primmer, C. R. Efficiency of model-based Bayesian methods for detecting hybrid individuals under different hybridization scenarios and with different numbers of loci. Mol. Ecol. 15, 63–72 (2006).PubMed 

    Google Scholar 
    Boecklen, W. J. & Howard, D. J. Genetic analysis of hybrid zones: Numbers of markers and power of resolution. Ecology 78, 2611–2616 (1997).
    Google Scholar 
    Elliott, L. & Russello, M. A. SNP panels for differentiating advanced-generation hybrid classes in recently diverged stocks: A sensitivity analysis to inform monitoring of sockeye salmon re-stocking programs. Fish. Res. 208, 339–345 (2018).
    Google Scholar 
    Twyford, A. D. & Ennos, R. A. Next-generation hybridization and introgression. Heredity 108, 179–189 (2012).CAS 
    PubMed 

    Google Scholar 
    Campbell, N. R., Harmon, S. A. & Narum, S. R. Genotyping-in-Thousands by sequencing (GT-seq): A cost effective SNP genotyping method based on custom amplicon sequencing. Mol. Ecol. Resour. 15, 855–867 (2015).CAS 
    PubMed 

    Google Scholar 
    Alexander, C. A. & Pickard, D. Skaha Lake Experimental Sockeye Reintroduction: Synthesis of First 4 of 12 Years (2004–2007 Brood Years) (Springer, 2009).
    Google Scholar 
    McQueen, D. et al. Evaluation of the Experimental Introduction of Sockeye Salmon (Oncorhynchus nerka) into Skaha Lake and Assessment of Sockeye Rearing in Osoyoos Lake (Springer, 2013).
    Google Scholar 
    Hegg, J. C., Kennedy, B. P. & Chittaro, P. What did you say about my mother? The complexities of maternally derived chemical signatures in otoliths. Can. J. Fish. Aquat. Sci. 76, 81–94 (2019).CAS 

    Google Scholar 
    Veale, A. J. & Russello, M. A. Genomic changes associated with reproductive and migratory ecotypes in sockeye salmon (Oncorhynchus nerka). Genome Biol. Evol. 9, 2921–2939 (2017).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Catchen, J., Hohenlohe, P. A., Bassham, S., Amores, A. & Cresko, W. A. Stacks: An analysis tool set for population genomics. Mol. Ecol. 22, 3124–3140 (2013).PubMed 
    PubMed Central 

    Google Scholar 
    Hohenlohe, P. A., Amish, S. J., Catchen, J. M., Allendorf, F. W. & Luikart, G. Next-generation RAD sequencing identifies thousands of SNPs for assessing hybridization between rainbow and westslope cutthroat trout. Mol. Ecol. Resour. 11, 117–122 (2011).PubMed 

    Google Scholar 
    Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156–2158 (2011).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Weir, B. S. & Cockerham, C. C. Estimating F-statistics for the analysis of population structure. Evolution 38, 1358–1370 (1984).CAS 
    PubMed 

    Google Scholar 
    Rousset, F. genepop’007: A complete re-implementation of the genepop software for Windows and Linux. Mol. Ecol. Resour. 8, 103–106 (2008).PubMed 

    Google Scholar 
    Anderson, E. C. & Thompson, E. A. A model-based method for identifying species hybrids using multilocus genetic data. Genetics 160, 1217–1229 (2002).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Schmidt, D. A., Campbell, N. R., Govindarajulu, P., Larsen, K. W. & Russello, M. A. Genotyping-in-Thousands by sequencing (GT-seq) panel development and application to minimally invasive DNA samples to support studies in molecular ecology. Mol. Ecol. Resour. 20, 114–124 (2020).CAS 
    PubMed 

    Google Scholar 
    Purcell, S. et al. PLINK: A tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Reeves, P. A., Bowker, C. L., Fettig, C. E., Tembrock, L. R. & Richards, C. M. Effect of Error and Missing Data on Population Structure Inference Using Microsatellite Data. (2016) https://doi.org/10.1101/080630.Wringe, B. F., Stanley, R. R. E., Jeffery, N. W., Anderson, E. C. & Bradbury, I. R. hybriddetective: A workflow and package to facilitate the detection of hybridization using genomic data in r. Mol. Ecol. Resour. 17, e275–e284 (2017).CAS 
    PubMed 

    Google Scholar 
    Walsh, P. S., Metzger, D. A. & Higuchi, R. Chelex 100 as a medium for simple extraction of DNA for PCR-based typing from forensic material. Biotechniques 10, 506–513 (1991).CAS 
    PubMed 

    Google Scholar 
    Russell, T. et al. Development of a novel mule deer genomic assembly and species-diagnostic SNP panel for assessing introgression in mule deer, white-tailed deer, and their interspecific hybrids. Genes Genomes Genet. 9, 911–919 (2019).CAS 

    Google Scholar 
    Thongda, W. et al. Species-diagnostic SNP markers for the black basses (Micropterus spp.): A new tool for black bass conservation and management. Conserv. Genet. Resour. 12, 319–328 (2020).
    Google Scholar 
    Ricker, W. E. ‘Residual’ and kokanee salmon in Cultus lake. J. Fish. Board Can. 27, 192–218 (1938).
    Google Scholar 
    Crossin, G. T. et al. Exposure to high temperature influences the behaviour, physiology, and survival of sockeye salmon during spawning migration. Can. J. Zool. 86, 127–140 (2008).CAS 

    Google Scholar 
    Moore, M. E. et al. Early marine migration patterns of wild coastal cutthroat trout (Oncorhynchus clarkii clarkii), steelhead trout (Oncorhynchus mykiss), and their hybrids. PLoS ONE 5, e12881 (2010).PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    McCutcheon, C. S., Prentice, E. F. & Park, D. L. Passive monitoring of migrating adult steelhead with PIT tags. N. Am. J. Fish. Manag. 14, 220–223 (1994).
    Google Scholar 
    Scribner, K. T., Page, K. S. & Bartron, M. L. Hybridization in freshwater fishes: A review of case studies and cytonuclear methods of biological inference. Rev. Fish Biol. Fish. 10, 293–323 (2001).
    Google Scholar  More

  • in

    An integrated multiple driver mesocosm experiment reveals the effect of global change on planktonic food web structure

    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, Pachauri, R. K. & Meyer L. A.) 151 (IPCC, Geneva, Switzerland, 2014).Grizzetti, B., Bouraoui, F. & Aloe, A. Changes of nitrogen and phosphorus loads to European seas. Glob. Change Biol. 18, 769–782 (2012).
    Google Scholar 
    Hoegh-Guldberg, O. & Bruno, J. F. The impact of climate change on the world’s marine ecosystems. Science 328, 1523–1528 (2010).CAS 
    PubMed 

    Google Scholar 
    Duarte, C. M. Global change and the future ocean: a grand challenge for marine sciences. Front. Mar. Sci. 1, 1–16 (2014).
    Google Scholar 
    Richardson, A. J. & Schoeman, D. S. Climate impact on plankton ecosystems in the Northeast Atlantic. Science 305, 1609–1612 (2004).CAS 
    PubMed 

    Google Scholar 
    Rose, J. M. et al. Effects of increased pCO2 and temperature on the North Atlantic spring bloom. II. Microzooplankton abundance and grazing. Mar. Ecol. Prog. Ser. 388, 27–40 (2009).CAS 

    Google Scholar 
    Sommer, U., Paul, C. & Moustaka-Gouni, M. Warming and ocean acidification effects on phytoplankton—from species shifts to size shifts within species in a mesocosm experiment. PLoS ONE 10, 1–17 (2015).
    Google Scholar 
    Garzke, J., Hansen, T., Ismar, S. M. H. & Sommer, U. Combined effects of ocean warming and acidification on copepod abundance, body size and fatty acid content. PLoS ONE 11, 1–22 (2016).
    Google Scholar 
    Horn, H. G., Boersma, M., Garzke, J., Sommer, U. & Aberle, N. High CO2 and warming affect microzooplankton food web dynamics in a Baltic Sea summer plankton community. Mar. Biol. 167, 1–17 (2020).
    Google Scholar 
    Boyd, P. W. et al. Experimental strategies to assess the biological ramifications of multiple drivers of global ocean change—a review. Glob. Change Biol. 24, 2239–2261 (2018).
    Google Scholar 
    Stewart, R. I. A. et al. Mesocosm experiments as a tool for ecological provided for ecological climate-change research. In Advances in Ecological Research/Guy Woodward (ed. O’Gorman, E. J.) 71–181 (Academic Press, 2013).Rost, B. & Riebesell, U. Coccolithophores and the biological pump: responses to environmental changes. In Coccolithophores: From Molecular Processes to Global Impact (eds Thierstein, H. R. & Young, J. R.) 99–125 (Springer, 2004).Peter, K. H. & Sommer, U. Phytoplankton cell size reduction in response to warming mediated by nutrient limitation. PLoS ONE 8, 1–6 (2013).
    Google Scholar 
    Bermúdez, J. R., Riebesell, U., Larsen, A. & Winder, M. Ocean acidification reduces transfer of essential biomolecules in a natural plankton community. Sci. Rep. 6, 1–8 (2016).
    Google Scholar 
    Peter, K. H. & Sommer, U. Interactive effect of warming, nitrogen and phosphorus limitation on phytoplankton cell size. Ecol. Evolution 5, 1011–1024 (2015).
    Google Scholar 
    Alvarez-Fernandez, S. et al. Plankton responses to ocean acidification: the role of nutrient limitation. Prog. Oceanogr. 165, 11–18 (2018).
    Google Scholar 
    Stramski, D., Sciandra, A. & Claustre, H. Effects of temperature, nitrogen, and light limitation on the optical properties of the marine diatom Thalassiosira pseudonana. Limnol. Oceanogr. 47, 392–403 (2002).CAS 

    Google Scholar 
    Marañón, E. Cell size as a key determinant of phytoplankton metabolism and community structure. Annu. Rev. Mar. Sci. 7, 241–264 (2015).
    Google Scholar 
    Peñuelas, J., Sardans, J., Rivas‐Ubach, A. & Janssens, I. A. The human-induced imbalance between C, N and P in Earth’s life system. Glob. Change Biol. 18, 3–6 (2011).
    Google Scholar 
    Azam, F. et al. The ecological role of water-column microbes in the sea. Mar. Ecol. Prog. Ser. 10, 257–63. (1983).
    Google Scholar 
    Legendre, L. & Le Fèvre, J. Microbial food webs and the export of biogenic carbon in oceans. Aquat. Microb. Ecol. 9, 69–77 (1995).
    Google Scholar 
    Beaufort, L. et al. Sensitivity of coccolithophores to carbonate chemistry and ocean acidification. Nature 476, 80–83 (2011).CAS 
    PubMed 

    Google Scholar 
    Langer, G., Nehrke, G., Probert, I., Ly, J. & Ziveri, P. Strain-specific responses of Emiliania huxleyi to changing seawater carbonate chemistry. Biogeosciences 6, 2637–2646 (2009).CAS 

    Google Scholar 
    Winter, A., Henderiks, J., Beaufort, L., Rickaby, R. E. M. & Brown, C. W. Poleward expansion of the coccolithophore Emiliania huxleyi. J. Plankton Res. 36, 316–325 (2014).CAS 

    Google Scholar 
    Hopkins, J., Henson, S. A., Painter, S. C., Tyrrell, T. & Poulton, A. J. Phenological characteristics of global coccolithophore blooms. Glob. Biogeochemical Cycles 29, 239–253 (2015).CAS 

    Google Scholar 
    León, P. et al. Seasonal variability of the carbonate system and coccolithophore Emiliania huxleyi at a Scottish Coastal Observatory monitoring site. Estuar., Coast. Shelf Sci. 202, 302–314 (2018).
    Google Scholar 
    Rivero-Calle, S., Gnanadesikan, A., Del Castillo, C. E., Balch, W. M. & Guikema, S. D. Multidecadal increase in North Atlantic coccolithophores and the potential role of rising CO2. Science 350, 1533–1537 (2015).CAS 
    PubMed 

    Google Scholar 
    Purdie, D. A. & Finch, M. S. Impact of a coccolithophorid bloom on dissolved carbon dioxide in sea water enclosures in a Norwegian fjord. Sarsia 79, 379–387 (1994).
    Google Scholar 
    Nejstgaard, J. C., Gismervik, I. & Solberg, P. T. Feeding and reproduction by Calanus finmarchicus, and microzooplankton grazing during mesocosm blooms of diatoms and the coccolithophore Emiliania huxleyi. Mar. Ecol. Prog. Ser. 147, 197–217 (1997).
    Google Scholar 
    Leblanc, K. et al. Distribution of calcifying and silicifying phytoplankton in relation to environmental and biogeochemical parameters during the late stages of the 2005 North East Atlantic Spring Bloom. Biogeosciences 6, 2155–2179 (2009).CAS 

    Google Scholar 
    Sett, S. et al. Temperature modulates coccolithophorid sensitivity of growth, photosynthesis and calcification to increasing seawater pCO2. PLoS ONE 9, e88308 (2014).PubMed 
    PubMed Central 

    Google Scholar 
    Benner, I. et al. Emiliania huxleyi increases calcification but not expression of calcification-related genes in long-term exposure to elevated temperature and pCO2. Philos. Trans. R. Soc. B 368, 20130049 (2013).
    Google Scholar 
    Borchard, C., Borges, A. V., Händel, N. & Engel, A. Biogeochemical response of Emiliania huxleyi (PML B92/11) to elevated CO2 and temperature under phosphorous limitation: a chemostat study. J. Exp. Mar. Biol. Ecol. 410, 61–71 (2011).CAS 

    Google Scholar 
    Harrison, P. J. et al. Geographical distribution of red and green Noctiluca scintillans. Chin. J. Oceanol. Limnol. 29, 807–831 (2011).
    Google Scholar 
    Johns, D. G., Edwards, M., Greve, W. & SJohn, A. W. G. Increasing prevelance of the marine cladoceran Penilia avirostris (Dana, 1852) in the North Sea. Helgol. Mar. Res. 59, 215–218 (2005).
    Google Scholar 
    O’Connor, M. I. O., Piehler, M. F., Leech, D. M., Anton, A. & Bruno, J. F. Warming and resource availability shift food web structure and metabolism. PLoS Biol. 7, 1–6 (2009).
    Google Scholar 
    Cross, W. F., Hood, J. M., Benstead, J. P., Huryn, A. D. & Nelson, D. Interactions between temperature and nutrients across levels of ecological organization. Glob. change Biol. 21, 1025–1040 (2015).
    Google Scholar 
    Boersma, M. et al. Temperature driven changes in the diet preference of omnivorous copepods: no more meat when it’s hot? Ecol. Lett. 19, 45–53 (2016).PubMed 

    Google Scholar 
    Anderson, T. R., Hessen, D. O., Boersma, M., Urabe, J. & Mayor, D. J. Will invertebrates require increasingly carbon-rich food in a warming world? Am. Naturalist 190, 725–742 (2017).
    Google Scholar 
    Kirchner, M., Sahling, G., Uhlig, G., Gunkel, W. & Klings, K.-W. Does the red tide-forming dinoflagellate Noctiluca scintillans feed on bacteria? Sarsia 81, 45–55 (2015).
    Google Scholar 
    Elbrächter, M. & Qi, Y. Aspects of Noctiluca (Dinophyceae) population dynamics. In Physiological Ecology of Harmful Algal Blooms (ed. Anderson, M. D.) 315–335 (Springer-Verlag, 1998).Atienza, D., Saiz, E. & Calbet, A. Feeding ecology of the marine cladoceran Penilia avirostris: natural diet, prey selectivity and daily ration. Mar. Ecol. Prog. Ser. 315, 211–220 (2006).
    Google Scholar 
    Zhang, S., Liu, H., Chen, B. & Chih-Jung, W. Effects of diet nutritional quality on the growth and grazing of Noctiluca scintillans. Sci. Rep. 527, 73–85 (2015).CAS 

    Google Scholar 
    Reid, P. C., Borges, M. F. & Svendsen, E. A regime shift in the North Sea circa 1988 linked to changes in the North Sea horse mackerel fishery. Fish. Res. 50, 163–171 (2001).
    Google Scholar 
    Beaugrand, G., Brander, K. M., Lindley, J. A., Souissi, S. & Reid, P. C. Plankton effect on cod recruitment in the North Sea. Nature 426, 661–664 (2003).CAS 
    PubMed 

    Google Scholar 
    Payne, M. R. et al. Recruitment in a changing environment: the 2000s North Sea herring recruitment failure. ICES J. Mar. Sci. 66, 272–277 (2009).
    Google Scholar 
    Perälä, T., Olsen, E. M. & Hutchings, J. A. Disentangling conditional effects of multiple regime shifts on Atlantic cod productivity. PLoS ONE 15, e0237414 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    Behrenfeld, M. J., Boss, E. S. & Halsey, K. H. Phytoplankton community structuring and succession in a competition-neutral resource landscape. ISME COMMUN. 1, 1–8 (2021).Monteiro, F. M. et al. Why marine phytoplankton calcify. Sci. Adv. 2, 1–14 (2016).
    Google Scholar 
    Mayers, K. M. J. et al. The possession of coccoliths fails to deter microzooplankton grazers. Front. Mar. Sci. 7, 976 (2020).
    Google Scholar 
    Zhao, Y. et al. Grazing by microzooplankton and copepods on the microbial food web in spring in the southern Yellow Sea, China. Mar. Life Sci. Technol. 2, 442–455 (2020).
    Google Scholar 
    Aberle, N. et al. High tolerance of microzooplankton to ocean acidification in an Arctic coastal plankton community. Biogeosciences 10, 1471–1481 (2013).
    Google Scholar 
    Horn, H. G. et al. Low CO2 sensitivity of Microzooplankton communities in the Gullmar Fjord, Skagerrak: evidence from a long-term Mesocosm Study. PLoS ONE 11, 1–24 (2016).
    Google Scholar 
    Chen, B., Landry, M. R., Huang, B. & Liu, H. Does warming enhance the effect of microzooplankton grazing on marine phytoplankton in the ocean? Limnol. Oceanogr. 57, 519–526 (2012).CAS 

    Google Scholar 
    Vázquez-Domínguez, E., Vaqué, D. & Gasol, J. M. Temperature effects on the heterotrophic bacteria, heterotrophic nanoflagellates, and microbial top predators of the NW Mediterranean. Aquat. Microb. Ecol. 67, 107–121 (2012).
    Google Scholar 
    Lara, E. et al. Experimental evaluation of the warming effect on viral, bacterial and protistan communities in two contrasting Arctic systems. Aquat. Microb. Ecol. 70, 17–32 (2013).
    Google Scholar 
    Olson, M. B., Solem, K. & Love, B. Microzooplankton grazing responds to simulated ocean acidification indirectly through changes in prey cellular characteristics. Mar. Ecol. Prog. Ser. 604, 83–97 (2018).CAS 

    Google Scholar 
    Sherr, E. B. & Sherr, B. F. Bacterivory and herbivory: key roles of phagotrophic protists in pelagic food webs. Microb. Ecol. 28, 223–235 (1994).CAS 
    PubMed 

    Google Scholar 
    Brander, K. & Kiørboe, T. Decreasing phytoplankton size adversely affects ocean food chains. Glob. Change Biol. 26, 5356–5357 (2020).
    Google Scholar 
    Irigoien, X. et al. A high frequency time series at weathership M, Norwegian Sea, during the 1997 spring bloom: feeding of adult female Calanus finmarchicus. Mar. Ecol. Prog. Ser. 172, 127–137 (1998).
    Google Scholar 
    Fenchel, T. The microbial loop—25 years later. J. Exp. Mar. Biol. Ecol. 366, 99–103 (2008).
    Google Scholar 
    Aberle, N., Malzahn, A. M., Lewandowska, A. M. & Sommer, U. Some like it hot: the protozooplankton— copepod link in a warming ocean. Mar. Ecol. Prog. Ser. 519, 103–113 (2015).
    Google Scholar 
    Berglund, J., Müren, U., Båmstedt, U. & Andersson, A. Efficiency of a phytoplankton-based and a bacteria-based food web in a pelagic marine system. Limnol. Oceanogr. 52, 121–131 (2007).CAS 

    Google Scholar 
    Sherr, E. B. & Sherr, B. F. Heterotrophic dinoflagellates: a significant component of microzooplankton biomass and major grazers of diatoms in the sea. Mar. Ecol. Prog. Ser. 352, 187–197 (2007).
    Google Scholar 
    Gifford, D. J. The protozoan-metazoan trophic link in pelagic ecosystems. J. Protozool. 38, 81–86 (1991).
    Google Scholar 
    Rollwagen-Bollens, G. & Gifford, S. The role of protistan microzooplankton in the upper San Francisco estuary planktonic food web: source or sink? Estuaries Coasts 34, 1026–1038 (2011).CAS 

    Google Scholar 
    Anjusha, A. et al. Trophic efficiency of plankton food webs: observations from the Gulf of Mannar and the Palk Bay, Southeast Coast of India. J. Mar. Syst. 115, 40–61 (2013).
    Google Scholar 
    IPCC. Global Warming of 1.5 °C. An IPCC Special Report on the impacts of global warming of 1.5 °C above pre-industrial levels and related global greenhouse gas emission pathways. In The Context of Strengthening the Global Response to The Threat of Climate Change, Sustainable Development, and Efforts to Eradicate Poverty (Masson-Delmotte, V. et al (eds.) 616 (IPCC, Geneva, Switzerland, 2018).Pansch, A., Winde, V., Asmus, R. & Asmus, H. Tidal benthic mesocosms simulating future climate change scenarios in the field of marine ecology. Limnol. Oceanogr.: Methods 14, 257–267 (2016).
    Google Scholar 
    van Leeuwen, S., Tett, P., Mills, D. & van der Molen, J. Stratified and nonstratified areas in the North Sea: long-term variability and biological and policy implications. J. Geophys. Res.: Oceans 120, 4670–4686 (2015).
    Google Scholar 
    Grasshoff, K., Kremling, K. & Ehrhardt, M. (eds). Methods of Seawater Analysis, 3rd edn. (Wiley-VCH, Weinheim, 1999).Dickson, A. G. An exact definition of total alkalinity and a procedure for the estimation of alkalinity and total inorganic carbon from titration data. Deep-Sea Res. 28, 609–623 (1981).CAS 

    Google Scholar 
    Pierrot, D. E., Lewis, E. & Wallace, D. W. R. MS Excel program developed for CO2 system calculations. ORNL/CDIAC-105a. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee https://doi.org/10.3334/CDIAC/otg.CO2SYS_XLS_CDIAC105a (2006).Dickson, A. G. & Millero, F. J. A comparison of the equilibrium constants for the dissociation of carbonic acid in seawater media. Deep-Sea Res. 34, 1733–1743 (1987).CAS 

    Google Scholar 
    Arrigo, K. R. et al. Phytoplankton community structure and the drawdown of nutrients and CO2 in the Southern Ocean. Science 283, 365–368 (1999).CAS 
    PubMed 

    Google Scholar 
    Utermöhl, H. Zur Vervollkommnung der quantitativen Phytoplankton- Methodik. Int. Ver. für. Theoretische und Angew. Limnologie: Mitteilungen 9, 1–38 (1958).
    Google Scholar 
    McEwen, G. F., Johnson, M. W. & Folsom, T. R. A statistical analysis of the performance of the Folsom plankton sample splitter, based upon test observations. Archiv für. Archiv Meteorologie, Geophysik und Bioklimatologie, Ser. A 7, 502–527 (1954).
    Google Scholar 
    Sell, D. W. & Evans, M. S. A statistical analysis of subsampling and an evaluation of the Folsom plankton splitter. Hydrobiologia 94, 223–230 (1982).
    Google Scholar 
    Boersma, M., Wiltshire, K. H., Kong, S., Greve, W. & Renz, J. Long-term change in the copepod community in the southern German Bight. J. Sea Res. 101, 41–50 (2015).
    Google Scholar 
    Marie, D., Simon, N. & Vaulot, D. Phytoplankton cell counting by flow cytometry. Algal Culturing Tech. 1, 253–267 (2005).
    Google Scholar 
    Hillebrand, H., Dürselen, C., Kirschtel, D., Pollingher, U. & Zohary, T. Biovolume calculation for pelagic and benthic microalgae. J. Phycol. 35, 403–424 (1999).
    Google Scholar 
    Menden-Deuer, S. & Lessard, E. J. Carbon to volume relationships for dinoflagellates, diatoms, and other protist plankton. Limnol. Oceanogr. 45, 569–579 (2000).CAS 

    Google Scholar 
    Putt, M. & Stoecker, D. K. An experimentally determined carbon: volume ratio for marine “oligotrichous” ciliates from estuarine and coastal waters. Limnol. Oceanogr. 34, 1097–1103 (1989).
    Google Scholar 
    Beran, A. et al. Carbon content and biovolume of the heterotrophic dinoflagellate Noctiluca scintillans from the Northern Adriatic Sea. In Proceedings of the CESUM-BS 2003, Varna. 28 (Book of Abstracts, UNESCO, Paris, 2003).Lee, S. & Fuhrman, J. A. Relationships between biovolume and biomass of naturally derived marine bacterioplankton. Appl. Environ. Microbiol. 53, 1298–1303 (1987).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kraberg, A., Baumann, M. & Dürselen, C. Coastal Phytoplankton: Photo Guide for Northern European Seas (Dr. Friedrich Pfeil, München, 2010).R Core Team. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/ (2021). More

  • in

    Leucistic plumage as a result of progressive greying in a cryptic nocturnal bird

    Rutz, C. Predator fitness increases with selectivity for odd prey. Curr. Biol. 22, 820–824 (2012).CAS 
    PubMed 

    Google Scholar 
    Santos, C. D. et al. Personality and morphological traits affect pigeon survival from raptor attacks. Sci. Rep. 5, 1–8 (2015).
    Google Scholar 
    Brown, M. B. & Wells, E. Skeletal dysplasia-like syndromes in wild giraffe. BMC Res. Notes 13, 569 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    van Grouw, H. What colour is that bird? The causes and recognition of common colour aberrations in birds. Br. Birds 106, 17–29 (2013).
    Google Scholar 
    Slagsvold, T., Rofstad, G. & Sandvik, J. Partial albinism and natural selection in the hooded crow Corvus corone cornix. J. Zool. 214, 157–166 (1988).
    Google Scholar 
    Stevens, M. et al. Revealed by conspicuousness: distractive markings reduce camouflage. Behav. Ecol. 24, 213–222 (2013).
    Google Scholar 
    van Grouw, H. What’s in a name? Nomenclature for colour aberrations in birds reviewed. Bull. Br. Ornithol. Club 141, 276–299 (2021).
    Google Scholar 
    Parsons, G. J. & Bonderup-Nielsen, S. Partial albinism in an island population of Meadow Voles, Microtus pennsylvanicus, from Nova Scotia. Can. Field-Nat. 109, 263–264 (1995).
    Google Scholar 
    Reis, A. da S., Zampaulo, R. de A. & Talamoni, S. A. Frequency of leucism in a colony of Anoura geoffroyi (Chiroptera: Phyllostomidae) roosting in a ferruginous cave in Brazil. Biota Neotropica 19(3): e20180676. https://doi.org/10.1590/1676-0611-BN-2018-0676 (2019).Jehl, J. R. Leucism in Eared Grebes in western north America. Condor 87, 439–441 (1985).
    Google Scholar 
    Forrest, S. & Naveen, R. Prevalence of leucism in Pygoscelid penguins of the Antarctic peninsula. Waterbirds 23, 283–285 (2000).
    Google Scholar 
    González-Ortegón, E., Drake, P., Quigley, D. T. G. & Cuesta, J. A. Leucism in the European sardine Sardina pilchardus (Clupeidae). Ecol. Indic. 117, 106544 (2020).
    Google Scholar 
    David, B. Z. First report of partial leucism in the poison frog Epipedobates anthonyi (Anura: Dendrobatidae) in El Oro, Ecuador. Neotrop. Biodivers. 7, 1–4 (2021).
    Google Scholar 
    Krecsák, L. Albinism and leucism among European Viperinae: a review. Russ. J. Herpetol. 15, 97–102 (2008).
    Google Scholar 
    Ritland, K., Newton, C. & Marshall, H. D. Inheritance and population structure of the white-phased “Kermode” black bear. Curr. Biol. 11, 1468–1472 (2001).CAS 
    PubMed 

    Google Scholar 
    Galván, I., Bijlsma, R. G., Negro, J. J., Jarén, M. & Garrido-Fernández, J. Environmental constraints for plumage melanization in the northern goshawk Accipiter gentilis. J. Avian Biol. 41, 523–531 (2010).
    Google Scholar 
    Pijpe, A., Gardien, K. L. M., Meijeren-Hoogendoorn, R. E. van, Middelkoop, E. & Zuijlen, P. P. M. van. Scar Symptoms: Pigmentation Disorders in Textbook On Scar Management (eds. Téot, L., Mustoe, T. A., Middelkoop, E. & Gauglitz, G. G.) 109–115 (Springer, 2020).Edelaar, P. et al. Apparent selective advantage of leucism in a coastal population of Southern caracaras (Falconidae). Evol. Ecol. Res. 13, 187–196 (2011).
    Google Scholar 
    Ellegren, H., Lindgren, G., Primmer, C. R. & Møller, A. P. Fitness loss and germline mutations in barn swallows breeding in Chernobyl. Nature 389, 593–596 (1997).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Benítez-López, A. & García-Egea, I. First record of an aberrantly colored Pin-tailed Sandgrouse (Pterocles alchata). Wilson J. Ornithol. 127, 755–759 (2015).
    Google Scholar 
    Zbyryt, A., Mikula, P., Ciach, M., Morelli, F. & Tryjanowski, P. A large-scale survey of bird plumage colour aberrations reveals a collection bias in Internet-mined photographs. Ibis 163, 566–578 (2020).
    Google Scholar 
    Bensch, S., Hansson, B., Hasselquist, D. & Nielsen, B. Partial albinism in a semi-isolated population of Great Reed Warblers. Hereditas 133, 167–170 (2000).CAS 
    PubMed 

    Google Scholar 
    Izquierdo, L. et al. Factors associated with leucism in the common blackbird Turdus merula. J. Avian Biol. 49, e01778 (2018).
    Google Scholar 
    Møller, A. P. & Mousseau, T. A. Albinism and phenotype of barn swallows (Hirundo rustica) from Chernobyl. Evolution 55, 2097–2104 (2001).PubMed 

    Google Scholar 
    Troscianko, J., Wilson-Aggarwal, J., Stevens, M. & Spottiswoode, C. N. Camouflage predicts survival in ground-nesting birds. Sci. Rep. 6, 1–8 (2016).
    Google Scholar 
    Aragonés, J., Arias de Reyna, L. & Recuerda, P. Visual communication and sexual selection in a nocturnal bird species, Caprimulgus ruficollis, a balance between crypsis and conspicuousness. Wilson Bull. 111, 340–345 (1999).
    Google Scholar 
    Negro, J. J., Bortolotti, G. R. & Sarasola, J. H. Deceptive plumage signals in birds: manipulation of predators or prey? Biol. J. Linn. Soc. 90, 467–477 (2007).
    Google Scholar 
    Brooke, M. de L. Unexplained recurrent features of the plumage of birds. Ibis 152, 845–847 (2010).Forero, M. G., Tella, J. L. & García, L. Age related evolution of sexual dimorphism in the Red-necked Nightjar Caprimulgus ruficollis. J. Ornithol. 136, 447–451 (1995).
    Google Scholar 
    Camacho, C. Early age at first breeding and high natal philopatry in the Red-necked Nightjar Caprimulgus ruficollis. Ibis 156, 442–445 (2014).
    Google Scholar 
    Camacho, C. et al. The road to opportunities: landscape change promotes body-size divergence in a highly mobile species. Curr. Zool. 62, 7–14 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Forero, M. G., Tella, J. L. & Oro, D. Annual survival rates of adult Red-necked Nightjars Caprimulgus ruficollis. Ibis 143, 273–277 (2001).
    Google Scholar 
    Henner, J. et al. Genetic mapping of the (G)-locus responsible for the coat color phenotype “Progressive Greying with Age” in horses (Equus caballus). Mamm. Genome 13, 535–537 (2002).CAS 
    PubMed 

    Google Scholar 
    Edson, J. M. An epidemic of albinism. Auk 45, 377–378 (1928).
    Google Scholar 
    Camacho, C., Palacios, S., Sáez, P., Sánchez, S. & Potti, J. Human-induced changes in landscape configuration influence individual movement routines: lessons from a versatile, highly mobile species. PLoS ONE 9, e104974 (2014).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Enders, F. & Post, W. White-spotting in the genus Ammospiza and other grassland sparrows. Bird-Band. 42, 210–219 (1971).
    Google Scholar 
    Sage, B. L. Albinism and melanism in birds. Br. Birds 55, 201–225 (1962).
    Google Scholar 
    O’Sullivan, J. D. B. et al. The biology of human hair greying. Biol. Rev. 96, 107–128 (2021).PubMed 

    Google Scholar 
    Nichols, J. D., Hines, J. E. & Blums, P. Tests for senescent decline in annual survival probabilities of common pochards, Aythya ferina. Ecology 78, 1009–1018 (1997).
    Google Scholar 
    Owen, M. & Skimmings, P. The occurrence and performance of leucistic Barnacle Geese Branta leucopsis. Ibis 134, 22–26 (1992).
    Google Scholar 
    Mulder, T., Campbell, C. J. & Ruxton, G. D. Evaluation of disruptive camouflage of avian cup-nests. Ibis 163, 150–158 (2021).
    Google Scholar 
    Holyoak, D. Variable albinism of the flight feathers as an adaptation for recognition of individual birds in some Polynesian populations of Acrocephalus warblers. Ardea 66, 112–117 (1978).
    Google Scholar 
    Griffith, S. C., Parker, T. H. & Olson, V. A. Melanin- versus carotenoid-based sexual signals: is the difference really so black and red? Anim. Behav. 71, 749–763 (2006).
    Google Scholar 
    Galván, I., Jorge, A., Nielsen, J. T. & Møller, A. P. Pheomelanin synthesis varies with protein food abundance in developing goshawks. J. Comp. Physiol. B 189, 441–450 (2019).PubMed 

    Google Scholar 
    Zaragoza-Trello, C., Vilà, M., Botías, C. & Bartomeus, I. Interactions among global change pressures act in a non-additive way on bumblebee individuals and colonies. Funct. Ecol. 35, 420–434 (2021).
    Google Scholar 
    Rollin, N. A note on abnormally marked Song Thrushes and Blackbirds. Trans. Nat. Hist. Soc. Northumberl. Durh. Newctle upon Tyne 10, 183–184 (1953).Guerrero-Bosagna, C. et al. Transgenerational epigenetic inheritance in birds. Environ. Epigenet. 4, dvy008 (2018).Camacho, C., Negro, J. J., Redondo, I., Palacios, S. & Sáez-Gómez, P. Correlates of individual variation in the porphyrin-based fluorescence of red-necked nightjars (Caprimulgus ruficollis). Sci. Rep. 9, 1–9 (2019).
    Google Scholar 
    Camacho, C. Tropical phenology in temperate regions: extended breeding season in a long-distance migrant. Condor 115, 830–837 (2013).
    Google Scholar 
    Cleere, N. Nightjars: a guide to nightjars and related birds (A&C Black, London, 2010).
    Google Scholar 
    Gargallo, G. Flight feather moult in the red-necked nightjar Caprimulgus ruficollis. J. Avian Biol. 25, 119–124 (1994).
    Google Scholar 
    Jackson, H. D. A field survey to investigate why nightjars frequent roads at night. Ostrich 74, 97–101 (2003).
    Google Scholar 
    Jackson, H. D. Finding and trapping nightjars. Bokmakierie 36, 86–89 (1984).
    Google Scholar 
    Sénar, J. C. & Pascual, J. Keel and tarsus length may provide a good predictor of avian body size. Ardea 85, 269–274 (1997).
    Google Scholar 
    Svensson, L. Identification Guide To European Passerines (Lars Svensson, Cleveland, 1992).
    Google Scholar 
    van de Pol, M. & Wright, J. A simple method for distinguishing within-versus between-subject effects using mixed models. Anim. Behav. 77, 753–758 (2009).
    Google Scholar 
    Schielzeth, H. & Forstmeier, W. Conclusions beyond support: overconfident estimates in mixed models. Behav. Ecol. 20, 416–420 (2009).PubMed 

    Google Scholar 
    Rising, J. D. & Somers, K. M. The measurement of overall body size in birds. Auk 106, 666–674 (1989).
    Google Scholar 
    Magnusson, A. et al. Package “glmmTMB”. R Package Version 0.2.0. (2017).Hartig, F. DHARMa: residual diagnostics for hierarchical (multi-level/mixed) regression models. R package version 0.2, 4. (2019).Nakagawa, S. & Schielzeth, H. A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol. Evol. 4, 133–142 (2013).
    Google Scholar 
    Barton, K. MuMIn: Multi-Model inference. Model selection and model averaging based on information criteria (AICc and alike). R package version 1.43.17. (2020). More

  • in

    Diversity of prokaryotic microorganisms in alkaline saline soil of the Qarhan Salt Lake area in the Qinghai–Tibet Plateau

    Boutaiba, S., Hacene, H., Bidle, K. A. & Maupin-Furlow, J. A. Microbial diversity of the hypersaline Sidi Ameur and Himalatt Salt Lakes of the Algerian Sahara. J. Arid Environ. 75, 909–916. https://doi.org/10.1016/j.jaridenv.2011.04.010 (2011).ADS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ventosa, A. Unusual micro-organisms from unusual habitats: hypersaline environments. Symposia Society for General Microbiology (2006).Fukuchi, S., Yoshimune, K., Wakayama, M., Moriguchi, M. & Nishikawa, K. Unique amino acid composition of proteins in halophilic bacteria. J. Mol. Biol. 327, 347–357 (2003).CAS 
    Article 

    Google Scholar 
    Pillai, S. D., Nakatsu, C. H., Miller, R. V. & Yates, M. V. Manual of environmental microbiology. Life High-Salinity Environ. https://doi.org/10.1128/9781555818821 (2015).Article 

    Google Scholar 
    Poli, A. et al. Microbial diversity in extreme marine habitats and their biomolecules. Microorganisms 5, 25. https://doi.org/10.3390/microorganisms5020025 (2017).CAS 
    Article 
    PubMed Central 

    Google Scholar 
    Azpiazu-Muniozguren, M., Martinez-Ballesteros, I., Gamboa, J., Seoane, S. & Bikandi, J. Altererythrobacter muriae sp. nov., isolated from hypersaline Aana Salt Valley spring water, a continental thalassohaline-type solar saltern. Int. J. Syst. Evol. Microbiol. 71, 3 (2021).
    Google Scholar 
    Zhang, J. et al. Bacterial diversity in Bohai Bay Solar Saltworks, China. Curr. Microbiol. 72, 55–63 (2016).CAS 
    Article 

    Google Scholar 
    Highfield, A., Ward, A., Pipe, R. & Schroeder, D. C. Molecular and phylogenetic analysis reveals new diversity of Dunaliella salina from hypersaline environments. J. Mar. Biol. Assoc. UK 101, 27–37. https://doi.org/10.1017/s0025315420001319 (2021).CAS 
    Article 

    Google Scholar 
    Cycil, L. M. et al. Metagenomic insights into the diversity of halophilic microorganisms indigenous to the Karak Salt Mine, Pakistan. Front. Microbiol. https://doi.org/10.3389/fmicb.2020.01567 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Jacob, J. H., Hussein, E. I., Shakhatreh, M. A. K. & Cornelison, C. T. Microbial community analysis of the hypersaline water of the Dead Sea using high-throughput amplicon sequencing. Microbiol. Open 6, e00500. https://doi.org/10.1002/mbo3.500 (2017).CAS 
    Article 

    Google Scholar 
    Ben Abdallah, M. et al. Abundance and diversity of prokaryotes in ephemeral hypersaline lake Chott El Jerid using Illumina Miseq sequencing, DGGE and qPCR assay. Extremophiles 22, 811–823. https://doi.org/10.1007/s00792-018-1040-9 (2018).CAS 
    Article 
    PubMed 

    Google Scholar 
    Tazi, L., Breakwell, D. P., Harker, A. R. & Crandall, K. A. Life in extreme environments: Microbial diversity in Great Salt Lake, Utah. Extremophiles 18, 525–535. https://doi.org/10.1007/s00792-014-0637-x (2014).Article 
    PubMed 

    Google Scholar 
    Kashi, F. J., Owlia, P., Amoozegar, M. A. & Kazemi, B. Halophilic prokaryotes in Urmia Salt Lake, a hypersaline environment in Iran. Curr. Microbiol. 78(8), 3230–3238 (2021).Article 

    Google Scholar 
    Sorokin, D. Y., Roman, P. & Kolganova, T. V. Halo(natrono)archaea from hypersaline lakes can utilize sulfoxides other than DMSO as electron acceptors for anaerobic respiration. Extremophiles 25, 173–180 (2021).CAS 
    Article 

    Google Scholar 
    Hwang, K., Choe, H. & Kim, K. M. Complete genome of Nocardioides aquaticus KCTC 9944T isolated from meromictic and hypersaline Ekho Lake, Antarctica. Mar. Genom. 1, 100889 (2021).Article 

    Google Scholar 
    Didari, M. et al. Diversity of halophilic and halotolerant bacteria in the largest seasonal hypersaline lake (Aran-Bidgol-Iran). J. Environ. Health Sci. Eng. 18, 961–971. https://doi.org/10.1007/s40201-020-00519-3 (2020).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Oren, A. Diversity of halophilic microorganisms: Environments, phylogeny, physiology, and applications. J. Ind. Microbiol. Biotechnol. 28, 56–63 (2002).CAS 
    Article 

    Google Scholar 
    Mutlu, M. B. et al. Prokaryotic diversity in Tuz Lake, a hypersaline environment in Inland Turkey. FEMS Microbiol. Ecol. 65, 474–483. https://doi.org/10.1111/j.1574-6941.2008.00510.x (2008).CAS 
    Article 
    PubMed 

    Google Scholar 
    Antón, J. et al. Distribution, abundance and diversity of the extremely halophilic bacterium Salinibacter ruber. Saline Syst. 4, 15. https://doi.org/10.1186/1746-1448-4-15 (2008).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Oren, A. Microbial life at high salt concentrations: phylogenetic and metabolic diversity. Saline Syst. 4, 2. https://doi.org/10.1186/1746-1448-4-2 (2008).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Abdeljabbar, H., Badiaa, E., Jean-Luc, C., Marie-Laure, F. & Najla, S. Prokaryotic biodiversity of halophilic microorganisms isolated from Sehline Sebkha Salt Lake (Tunisia). Afr. J. Microbiol. Res. 8, 355–367. https://doi.org/10.5897/ajmr12.1087 (2014).Article 

    Google Scholar 
    Najjari, A., Elshahed, M. S., Cherif, A., Youssef, N. H. & Löffler, F. E. Patterns and determinants of halophilic archaea (Class Halobacteria) diversity in Tunisian endorheic salt lakes and Sebkhet systems. Appl. Environ. Microbiol. 81, 4432–4441. https://doi.org/10.1128/aem.01097-15 (2015).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Aharon, O. The ecology of the extremely halophilic archaea. FEMS Microbiol. Rev. 1, 415–440 (1994).
    Google Scholar 
    Oren, A. Halophilic Archaea. FEMS Microbiol. Rev. https://doi.org/10.1016/b978-0-12-809633-8.20800-5 (2019).Article 

    Google Scholar 
    Feng, Y. et al. The evolutionary origins of extreme halophilic archaeal lineages. Genome Biol. Evol. 13, 8. https://doi.org/10.1093/gbe/evab166 (2021).CAS 
    Article 

    Google Scholar 
    Ventosa, A., Nieto, J. J. & Oren, A. Biology of moderately halophilic aerobic bacteria. Microbiol. Mol. Biol. Rev. 62, 504–544 (1998).CAS 
    Article 

    Google Scholar 
    Kushner, D. J. Halophilic bacteria. Adv. Appl. Microbiol. 10, 73–99 (1968).CAS 
    Article 

    Google Scholar 
    Ghozlan, H., Deif, H., Kandil, R. A. & Sabry, S. Biodiversity of moderately halophilic bacteria in hypersaline habitats in Egypt. J. Gen. Appl. Microbiol. 52, 63–72 (2006).CAS 
    Article 

    Google Scholar 
    Ali, I., Prasongsuk, S., Akbar, A., Aslam, M. & Rakshit, S. K. Hypersaline habitats and halophilic microorganisms. Maejo Int. J. Sci. Technol. 10, 330–345 (2016).CAS 

    Google Scholar 
    Margesin, R. & Schinner, F. Biodegradation and bioremediation of hydrocarbons in extreme environments. Appl. Microbiol. Biotechnol. 56, 650–663. https://doi.org/10.1007/s002530100701 (2001).CAS 
    Article 
    PubMed 

    Google Scholar 
    Poosarla, V. G. & Ts, C. Xylanase production by halophilic bacterium Gracilibacillus sp. TSCPVG under solid state fermentation. Res. J. Biotechnol. 16, 92–100 (2021).Article 

    Google Scholar 
    Foti, M. et al. Diversity, activity, and abundance of sulfate-reducing bacteria in saline and hypersaline soda lakes. Appl. Environ. Microbiol. 73, 2093–2100. https://doi.org/10.1128/aem.02622-06 (2007).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Boujelben, I. et al. Spatial and seasonal prokaryotic community dynamics in ponds of increasing salinity of Sfax solar saltern in Tunisia. Antonie Van Leeuwenhoek 101, 845–857. https://doi.org/10.1007/s10482-012-9701-7 (2012).CAS 
    Article 
    PubMed 

    Google Scholar 
    García-Maldonado, J. Q., Bebout, B. M., Everroad, R. C. & López-Cortés, A. Evidence of novel phylogenetic lineages of methanogenic archaea from hypersaline microbial mats. Microb. Ecol. 69, 106–117. https://doi.org/10.1007/s00248-014-0473-7 (2014).CAS 
    Article 
    PubMed 

    Google Scholar 
    Abed, R. M. M., de Beer, D. & Stief, P. Functional-structural analysis of nitrogen-cycle bacteria in a hypersaline mat from the omani desert. Geomicrobiol. J. 32, 119–129. https://doi.org/10.1080/01490451.2014.932033 (2014).CAS 
    Article 

    Google Scholar 
    Coban, O., Rasigraf, O., Jong, A., Spott, O. & Bebout, B. M. Quantifying potential N turnover rates in hypersaline microbial mats by 15 N tracer techniques. Appl. Environ. Microbiol. 87, 8 (2021).Article 

    Google Scholar 
    Rodriguez-Valera, F. Introduction to Saline Environments (Springer, 1993).
    Google Scholar 
    Wei, H. C., Qi-Shun, F., Fu-Yuan, A., Fa-Shou, S. & Qin, Z. J. Chemical elements in core sediments of the qarhan salt lake and palaeoclimate evolution during 94–9 ka. Acta Geosci. Sin. (2016).Yu, S., Liu, X., Tan, H. & Cao, G. Sustainable Utilization of Qarhan Salt Lake Resources 27–265 (Science Press, 2009).
    Google Scholar 
    Zhu, D. et al. An evaluation of the core bacterial communities associated with hypersaline environments in the Qaidam Basin, China. Arch. Microbiol. 202, 2093–2103. https://doi.org/10.1007/s00203-020-01927-7 (2020).CAS 
    Article 
    PubMed 

    Google Scholar 
    Liu, W., Jiang, H., Yang, J. & Wu, G. Gammaproteobacterial diversity and carbon utilization in response to salinity in the lakes on the qinghai-tibetan plateau. Geomicrobiol. J. 35, 392–403. https://doi.org/10.1080/01490451.2017.1378951 (2018).CAS 
    Article 

    Google Scholar 
    Zhong, Z.-P. et al. Prokaryotic community structure driven by salinity and ionic concentrations in plateau lakes of the tibetan plateau. Appl. Environ. Microbiol. 82, 1846–1858. https://doi.org/10.1128/aem.03332-15 (2016).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    He, C. et al. Synergistic effect of magnetite and zero-valent iron on anaerobic degradation and methanogenesis of phenol. Biores. Technol. 291, 121874. https://doi.org/10.1016/j.biortech.2019.121874 (2019).CAS 
    Article 

    Google Scholar 
    Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335–336. https://doi.org/10.1038/nmeth.f.303 (2010).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. Embnet J. 17, 10–12 (2011).Article 

    Google Scholar 
    Zhang, J., Kassian, K., Tomáš, F. & Alexandros, S. PEAR: a fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics 30, 614 (2014).CAS 
    Article 

    Google Scholar 
    Schmieder, R. & Edwards, R. Quality control and preprocessing of metagenomic datasets. Bioinformatics 27, 863–864 (2011).CAS 
    Article 

    Google Scholar 
    Edgar, R. C. UPARSE: Highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 10, 996–1000 (2013).CAS 
    Article 

    Google Scholar 
    Schloss, P. D. et al. Introducing mothur: Open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microbiol. 75, 7537 (2009).ADS 
    CAS 
    Article 

    Google Scholar 
    Chen, H. & Boutros, P. C. VennDiagram: A package for the generation of highly-customizable Venn and Euler diagrams in R. BMC Bioinform. 12, 35. https://doi.org/10.1186/1471-2105-12-35 (2011).Article 

    Google Scholar 
    McArdle, B. H. et al. Fitting multivariate models to community data: A comment on distance-based redundancy analysis. Ecology 82, 290–290 (2001).Article 

    Google Scholar 
    Langille, M. G. I. et al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat. Biotechnol. 31, 814–821. https://doi.org/10.1038/nbt.2676 (2013).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Louca, S. & Doebeli, M. Efficient comparative phylogenetics on large trees. Bioinformatics 34, 1–3 (2017).
    Google Scholar 
    Louca, S., Parfrey, L. W. & Doebeli, M. Decoupling function and taxonomy in the global ocean microbiome. Science 353, 1272 (2016).ADS 
    CAS 
    Article 

    Google Scholar 
    Junker, B. H. & Schreiber, F. Analysis of Biological Networks 283–304 (Analysis of biological networks, 2008).Book 

    Google Scholar 
    Faust, K. & Raes, J. Microbial interactions: From networks to models. Nat. Rev. Microbiol. 10, 538–550. https://doi.org/10.1038/nrmicro2832 (2012).CAS 
    Article 
    PubMed 

    Google Scholar 
    Behzad, H., Ibarra, M. A., Mineta, K. & Gojobori, T. Metagenomic studies of the Red Sea. Gene 576, 717–723. https://doi.org/10.1016/j.gene.2015.10.034 (2016).CAS 
    Article 
    PubMed 

    Google Scholar 
    Naghoni, A. et al. Microbial diversity in the hypersaline Lake Meyghan, Iran. Sci. Rep. https://doi.org/10.1038/s41598-017-11585-3 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kambura, A. K. et al. Bacteria and Archaea diversity within the hot springs of Lake Magadi and Little Magadi in Kenya. BMC Microbiol. https://doi.org/10.1186/s12866-016-0748-x (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Paul, D. et al. Exploration of microbial diversity and community structure of Lonar lake: The only hypersaline meteorite crater lake within basalt rock. Front. Microbiol. https://doi.org/10.3389/fmicb.2015.01553 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ventosa, A., de la Haba, R. R., Sánchez-Porro, C. & Papke, R. T. Microbial diversity of hypersaline environments: A metagenomic approach. Curr. Opin. Microbiol. 25, 80–87. https://doi.org/10.1016/j.mib.2015.05.002 (2015).CAS 
    Article 
    PubMed 

    Google Scholar 
    Liu, F. H. et al. Bacterial and archaeal assemblages in sediments of a large shallow freshwater lake, Lake Taihu, as revealed by denaturing gradient gel electrophoresis. J. Appl. Microbiol. 106, 1022–1032. https://doi.org/10.1111/j.1365-2672.2008.04069.x (2009).CAS 
    Article 
    PubMed 

    Google Scholar 
    Song, H., Li, Z., Du, B., Wang, G. & Ding, Y. Bacterial communities in sediments of the shallow Lake Dongping in China. J. Appl. Microbiol. 112, 79–89. https://doi.org/10.1111/j.1365-2672.2011.05187.x (2012).CAS 
    Article 
    PubMed 

    Google Scholar 
    Wu, Q. L., Zwart, G., Schauer, M., Agterveld, K. V. & Hahn, M. W. Bacterioplankton community composition along a salinity gradient of sixteen high-mountain lakes located on the Tibetan Plateau, China. Appl. Environ. Microbiol. 72, 5478–5485 (2006).ADS 
    CAS 
    Article 

    Google Scholar 
    Xing, P., Hahn, M. W. & Wu, Q. L. Low taxon richness of bacterioplankton in high-altitude lakes of the Eastern Tibetan Plateau, with a predominance of bacteroidetes and Synechococcus spp. Appl. Environ. Microbiol. 75, 7017–7025. https://doi.org/10.1128/aem.01544-09 (2009).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Liu, Y. et al. Bacterial diversity of freshwater Alpine Lake Puma Yumco on the Tibetan Plateau. Geomicrobiol. J. 26, 131–145. https://doi.org/10.1080/01490450802660201 (2009).CAS 
    Article 

    Google Scholar 
    MounÃc, S., Caumette, P., Matheron, R. & Willison, J. C. Molecular sequence analysis of prokaryotic diversity in the anoxic sediments underlying cyanobacterial mats of two hypersaline ponds in Mediterranean salterns. FEMS Microbiol. Ecol. 44, 117–130. https://doi.org/10.1016/s0168-6496(03)00017-5 (2003).Article 

    Google Scholar 
    Valenzuela-Encinas, C. et al. Changes in the bacterial populations of the highly alkaline saline soil of the former lake Texcoco (Mexico) following flooding. Extremophiles 13, 609–621. https://doi.org/10.1007/s00792-009-0244-4 (2009).Article 
    PubMed 

    Google Scholar 
    Kim, T. J., Lee, E. Y., Kim, Y. J., Cho, K.-S. & Ryu, H. W. Degradation of polyaromatic hydrocarbons by Burkholderia cepacia 2A–12. World J. Microbiol. Biotechnol. 19, 411–417. https://doi.org/10.1023/A:1023998719787 (2003).CAS 
    Article 

    Google Scholar 
    Gales, G. et al. Preservation of ancestral Cretaceous microflora recovered from a hypersaline oil reservoir. Sci. Rep. https://doi.org/10.1038/srep22960 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kleinsteuber, S., Riis, V., Fetzer, I., Harms, H. & Müller, S. Population dynamics within a microbial consortium during growth on diesel fuel in saline environments. Appl. Environ. Microbiol. 72, 3531–3542. https://doi.org/10.1128/aem.72.5.3531-3542.2006 (2006).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Valenzuela-Encinas, C. et al. The archaeal diversity and population in a drained alkaline saline soil of the former lake Texcoco (Mexico). Geomicrobiol. J. 29, 18–22. https://doi.org/10.1080/01490451.2010.520075 (2012).Article 

    Google Scholar 
    He, S., Tan, J., Hu, W. & Mo, C. Diversity of archaea and its correlation with environmental factors in the Ebinur Lake Wetland. Curr. Microbiol. 76, 1417–1424. https://doi.org/10.1007/s00284-019-01768-8 (2019).CAS 
    Article 
    PubMed 

    Google Scholar 
    Sandaa, R. A., Enger, O. & Torsvik, V. Abundance and diversity of Archaea in heavy-metal-contaminated soils. Appl. Environ. Microbiol. 65, 3293–3297 (1999).ADS 
    CAS 
    Article 

    Google Scholar 
    Dave, B. P. & Soni, A. Diversity of halophilic archaea at salt pans around Bhavnagar Coast, Gujarat. Proc. Natl. Acad. Sci. India B 83, 225–232. https://doi.org/10.1007/s40011-012-0124-z (2012).Article 

    Google Scholar 
    Zafrilla, B., Martínez-Espinosa, R., Alonso, M. A. & Bonete, M. J. Biodiversity of Archaea and floral of two inland saltern ecosystems in the Alto Vinalopó Valley, Spain. Saline Syst. 6, 10 (2010).Article 

    Google Scholar 
    Costa, M., Santos, H. & Galinski, E. A. An overview of the role and diversity of compatible solutes in Bacteria and Archaea. Adv. Biochem. Eng. Biotechnol. 61, 117 (1998).PubMed 

    Google Scholar 
    Williams, R. J., Howe, A. & Hofmockel, K. S. Demonstrating microbial co-occurrence pattern analyses within and between ecosystems. Front. Microbiol. https://doi.org/10.3389/fmicb.2014.00358 (2014).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Schmidt, T. S. B., MatiasRodrigues, J. F. & von Mering, C. A family of interaction-adjusted indices of community similarity. ISME J. 11, 791–807. https://doi.org/10.1038/ismej.2016.139 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Oyewusi, H. A. et al. Functional profiling of bacterial communities in Lake Tuz using 16S rRNA gene sequences. Biotechnol. Biotechnol. Equip. 35, 1–10. https://doi.org/10.1080/13102818.2020.1840437 (2020).CAS 
    Article 

    Google Scholar  More

  • in

    Oceanographic setting influences the prokaryotic community and metabolome in deep-sea sponges

    Taylor, M. W., Radax, R., Steger, D. & Wagner, M. Sponge-associated microorganisms: Evolution, ecology, and biotechnological potential. Microbiol. Mol. Biol. Rev. 71, 295–347 (2007).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Thomas, T. et al. Diversity, structure and convergent evolution of the global sponge microbiome. Nat. Commun. 7, 11870 (2016).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Webster, N. S. et al. Deep sequencing reveals exceptional diversity and modes of transmission for bacterial sponge symbionts. Environ. Microbiol. 12, 2070–2082 (2010).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Sipkema, D. et al. Similar sponge-associated bacteria can be acquired via both vertical and horizontal transmission: Microbial transmission in Petrosia ficiformis. Environ. Microbiol. 17, 3807–3821 (2015).CAS 
    PubMed 

    Google Scholar 
    Cleary, D. F. R. et al. The sponge microbiome within the greater coral reef microbial metacommunity. Nat. Commun. 10, 1644 (2019).Björk, J. R., Díez-Vives, C., Astudillo-García, C., Archie, E. A. & Montoya, J. M. Vertical transmission of sponge microbiota is inconsistent and unfaithful. Nat. Ecol. Evol. 3, 1172–1183 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Webster, N. S. & Taylor, M. W. Marine sponges and their microbial symbionts: Love and other relationships. Environ. Microbiol. 14, 335–346 (2012).CAS 
    PubMed 

    Google Scholar 
    Kennedy, J. et al. Evidence of a putative deep sea specific microbiome in marine sponges. PLoS ONE 9, e91092 (2014).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Steinert, G. et al. Compositional and quantitative insights into bacterial and archaeal communities of south pacific deep-sea sponges (Demospongiae and Hexactinellida). Front. Microbiol. 11, 716 (2020).Busch, K. et al. On giant shoulders: How a seamount affects the microbial community composition of seawater and sponges. Biogeosciences 17, 3471–3486 (2020).ADS 
    CAS 

    Google Scholar 
    Olson, J. B. & Gao, X. Characterizing the bacterial associates of three Caribbean sponges along a gradient from shallow to mesophotic depths. FEMS Microbiol. Ecol. 85, 74–84 (2013).PubMed 

    Google Scholar 
    Steinert, G. et al. In four shallow and mesophotic tropical reef sponges from Guam the microbial community largely depends on host identity. PeerJ 4, e1936 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Morrow, K. M., Fiore, C. L. & Lesser, M. P. Environmental drivers of microbial community shifts in the giant barrel sponge, Xestospongia muta, over a shallow to mesophotic depth gradient. Environ. Microbiol. 18, 2025–2038 (2016).CAS 
    PubMed 

    Google Scholar 
    Ebada, S. S. & Proksch, P. The chemistry of marine sponges. In Handbook of Marine Natural Products (eds Fattorusso, E. et al.) 191–293 (Springer, 2012). https://doi.org/10.1007/978-90-481-3834-0_4.Chapter 

    Google Scholar 
    Kornprobst, J.-M. Porifera (Sponges). Encyclopedia of Marine Natural Products (Wiley, 2014).
    Google Scholar 
    Leal, M. C., Puga, J., Serôdio, J., Gomes, N. C. M. & Calado, R. Trends in the discovery of new marine natural products from invertebrates over the last two decades—Where and what are we bioprospecting?. PLoS ONE 7, e30580 (2012).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Blunt, J. W., Copp, B. R., Keyzers, R. A., Munro, M. H. G. & Prinsep, M. R. Marine natural products. Nat. Prod. Rep. 34, 235–294 (2017).CAS 
    PubMed 

    Google Scholar 
    Unson, M. D., Holland, N. D. & Faulkner, D. J. A brominated secondary metabolite synthesized by the cyanobacterial symbiont of a marine sponge and accumulation of the crystalline metabolite in the sponge tissue. Mar. Biol. 119, 1–11 (1994).CAS 

    Google Scholar 
    Bewley, C. A., Holland, N. D. & Faulkner, D. J. Two classes of metabolites from Theonella swinhoei are localized in distinct populations of bacterial symbionts. Experientia 52, 716–722 (1996).CAS 
    PubMed 

    Google Scholar 
    Wilson, M. C. et al. An environmental bacterial taxon with a large and distinct metabolic repertoire. Nature 506, 58–62 (2014).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Tianero, M. D., Balaich, J. N. & Donia, M. S. Localized production of defence chemicals by intracellular symbionts of Haliclona sponges. Nat. Microbiol. 4, 1149–1159 (2019).CAS 
    PubMed 

    Google Scholar 
    Ivanišević, J., Thomas, O. P., Lejeusne, C., Chevaldonné, P. & Pérez, T. Metabolic fingerprinting as an indicator of biodiversity: Towards understanding inter-specific relationships among Homoscleromorpha sponges. Metabolomics 7, 289–304 (2011).
    Google Scholar 
    Pérez, T. et al. Oscarella balibaloi, a new sponge species (Homoscleromorpha: Plakinidae) from the Western Mediterranean Sea: Cytological description, reproductive cycle and ecology: O. balibaloi: Description, reproductive cycle and ecology. Mar. Ecol. (Berl.) 32, 174–187 (2011).ADS 

    Google Scholar 
    Reveillaud, J. et al. Relevance of an integrative approach for taxonomic revision in sponge taxa: Case study of the shallow-water Atlanto-Mediterranean Hexadella species (Porifera: Ianthellidae: Verongida). Invertebr. Syst. 26, 230–248 (2012).
    Google Scholar 
    Olsen, E. K. et al. Marine AChE inhibitors isolated from Geodia barretti: Natural compounds and their synthetic analogs. Org. Biomol. Chem. 14, 1629–1640 (2016).CAS 
    PubMed 

    Google Scholar 
    Reverter, M., Perez, T., Ereskovsky, A. V. & Banaigs, B. Secondary metabolome variability and inducible chemical defenses in the Mediterranean Sponge Aplysina cavernicola. J. Chem. Ecol. 42, 60–70 (2016).CAS 
    PubMed 

    Google Scholar 
    Reverter, M., Tribalat, M.-A., Pérez, T. & Thomas, O. P. Metabolome variability for two Mediterranean sponge species of the genus Haliclona: Specificity, time, and space. Metabolomics 14, 114 (2018).Villegas-Plazas, M. et al. Variations in microbial diversity and metabolite profiles of the tropical marine sponge Xestospongia muta with season and depth. Microb. Ecol. 78, 243–256 (2019).CAS 
    PubMed 

    Google Scholar 
    Mohanty, I. et al. Multi-omic profiling of Melophlus sponges reveals diverse metabolomic and microbiome architectures that are non-overlapping with ecological neighbors. Mar. Drugs 18, 124 (2020).CAS 
    PubMed Central 

    Google Scholar 
    Bowerbank, J. S. On the anatomy and physiology of the Spongiadae. Part I. On the spicula. Philos. Trans. R. Soc. Lond. 148, 279–332 (1858).ADS 

    Google Scholar 
    Vosmaer, G. C. J. The sponges of the ‘Willem Barents’ expedition 1880 and 1881. Bijdragen tot de Dierkunde 12, 1–47 (1885).
    Google Scholar 
    Radax, R. et al. Metatranscriptomics of the marine sponge Geodia barretti: Tackling phylogeny and function of its microbial community. Environ. Microbiol. 14, 1308–1324 (2012).CAS 
    PubMed 

    Google Scholar 
    Topsent, E. Spongiaires provenant des campagnes scientifiques de la ‘Princesse Alice’ dans les Mers du Nord (1898–1899—1906–1907). Résultats des campagnes scientifiques accomplies par le Prince Albert I. Monaco 45, 1–67 (1913).
    Google Scholar 
    Yashayaev, I. & Loder, J. W. Further intensification of deep convection in the Labrador Sea in 2016. Geophys. Res. Lett. 44, 1429–1438 (2017).ADS 

    Google Scholar 
    Gutleben, J. et al. Diversity of tryptophan halogenases in sponges of the genus Aplysina. FEMS Microbiol. Ecol. 95, fiz108 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Indraningrat, A. et al. Cultivation of sponge-associated bacteria from Agelas sventres and Xestospongia muta collected from different depths. Mar. Drugs 17, 578 (2019).CAS 
    PubMed Central 

    Google Scholar 
    Ramiro-Garcia, J. et al. NG-Tax, a highly accurate and validated pipeline for analysis of 16S rRNA amplicons from complex biomes. F1000 Res. 5, 1791 (2018).
    Google Scholar 
    Yilmaz, P. et al. The SILVA and “All-species Living Tree Project (LTP)” taxonomic frameworks. Nucl. Acids Res. 42, D643–D648 (2014).CAS 
    PubMed 

    Google Scholar 
    Erngren, I., Smit, E., Pettersson, C., Cárdenas, P. & Hedeland, M. The effects of sampling and storage conditions on the metabolite profile of the marine sponge Geodia barretti. Front. Chem. 9:662659 (2021)Smith, C. A., Want, E. J., O’Maille, G., Abagyan, R. & Siuzdak, G. XCMS: Processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Anal. Chem. 78, 779–787 (2006).CAS 
    PubMed 

    Google Scholar 
    Kuhl, C., Tautenhahn, R., Böttcher, C., Larson, T. R. & Neumann, S. CAMERA: An integrated strategy for compound spectra extraction and annotation of liquid chromatography/mass spectrometry data sets. Anal. Chem. 84, 283–289 (2012).CAS 
    PubMed 

    Google Scholar 
    Oksanen, J. et al. vegan: Community Ecology Package (2017).Dat, T. T. H., Steinert, G., Thi Kim Cuc, N., Smidt, H. & Sipkema, D. Archaeal and bacterial diversity and community composition from 18 phylogenetically divergent sponge species in Vietnam. PeerJ 6, e4970 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Miller, M. A., Pfeiffer, W. & Schwartz, T. Creating the CIPRES science gateway for inference of large phylogenetic trees. In 2010 Gateway Computing Environments Workshop (GCE) 1–8 (IEEE, 2010). https://doi.org/10.1109/GCE.2010.5676129.Letunic, I. & Bork, P. Interactive Tree Of Life (iTOL) v4: Recent updates and new developments. Nucl. Acids Res. 47, W256–W259 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Thévenot, E. A., Roux, A., Xu, Y., Ezan, E. & Junot, C. Analysis of the human adult urinary metabolome variations with age, body mass index, and gender by implementing a comprehensive workflow for univariate and OPLS statistical analyses. J. Proteome Res. 14, 3322–3335 (2015).PubMed 

    Google Scholar 
    Weiss, S. et al. Correlation detection strategies in microbial data sets vary widely in sensitivity and precision. ISME J. 10, 1669–1681 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Deng, Y. et al. Molecular ecological network analyses. BMC Bioinform. 13, 113 (2012).
    Google Scholar 
    Friedman, J. & Alm, E. J. Inferring correlation networks from genomic survey data. PLoS Comput. Biol. 8, e1002687 (2012).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Durno, W. E., Hanson, N. W., Konwar, K. M. & Hallam, S. J. Expanding the boundaries of local similarity analysis. BMC Genom. 14, S3 (2013).
    Google Scholar 
    Reshef, D. N. et al. Detecting novel associations in large data sets. Science 334, 1518–1524 (2011).ADS 
    CAS 
    PubMed 
    PubMed Central 
    MATH 

    Google Scholar 
    Hall, M. M., Torres, D. J. & Yashayaev, I. Absolute velocity along the AR7W section in the Labrador Sea. Deep Sea Res. Part 1 Oceanogr. Res. Pap. 72, 72–87 (2013).
    Google Scholar 
    Reveillaud, J. et al. Host-specificity among abundant and rare taxa in the sponge microbiome. ISME J. 8, 1198–1209 (2014).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Moitinho-Silva, L. et al. Predicting the HMA-LMA status in marine sponges by machine learning. Front. Microbiol. 8, 752 (2017).Lidgren, G., Bohlin, L. & Bergman, J. Studies of Swedish marine organisms VII. A novel biologically active indole alkaloid from the sponge Geodia barretti. Tetrahedron Lett. 27, 3283–3284 (1986).CAS 

    Google Scholar 
    Sjögren, M. et al. Antifouling activity of brominated cyclopeptides from the marine sponge Geodia barretti. J. Nat. Prod. 67, 368–372 (2004).PubMed 

    Google Scholar 
    Sölter, S. Identifizierung und Synthese von Naturstoffen aus Borealen Schwämmen (Universität Hamburg, 2004).
    Google Scholar 
    Di, X. et al. 6-Bromoindole derivatives from the Icelandic marine sponge Geodia barretti: Isolation and anti-inflammatory activity. Mar. Drugs 16, 437 (2018).CAS 
    PubMed Central 

    Google Scholar 
    Carstens, B. B. et al. Isolation, characterization, and synthesis of the barrettides: Disulfide-containing peptides from the marine sponge Geodia barretti. J. Nat. Prod. 78, 1886–1893 (2015).CAS 
    PubMed 

    Google Scholar 
    Hedner, E. et al. Brominated cyclodipeptides from the marine sponge Geodia barretti as selective 5-HT ligands. J. Nat. Prod. 69, 1421–1424 (2006).CAS 
    PubMed 

    Google Scholar 
    Hedner, E. et al. Antifouling activity of a dibrominated cyclopeptide from the marine sponge Geodia barretti. J. Nat. Prod. 71, 330–333 (2008).CAS 
    PubMed 

    Google Scholar 
    Erwin, P. M., Pita, L., López-Legentil, S. & Turon, X. Stability of sponge-associated bacteria over large seasonal shifts in temperature and irradiance. Appl. Environ. Microbiol. 78, 7358–7368 (2012).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Cárdenas, C. A., Bell, J. J., Davy, S. K., Hoggard, M. & Taylor, M. W. Influence of environmental variation on symbiotic bacterial communities of two temperate sponges. FEMS Microbiol. Ecol. 88, 516–527 (2014).PubMed 

    Google Scholar 
    Glasl, B., Smith, C. E., Bourne, D. G. & Webster, N. S. Exploring the diversity-stability paradigm using sponge microbial communities. Sci. Rep. 8, 8425 (2018).Schöttner, S. et al. Relationships between host phylogeny, host type and bacterial community diversity in cold-water coral reef sponges. PLoS ONE 8, e55505 (2013).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lurgi, M., Thomas, T., Wemheuer, B., Webster, N. S. & Montoya, J. M. Modularity and predicted functions of the global sponge-microbiome network. Nat. Commun. 10, 992 (2019).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Luter, H. M. et al. Microbiome analysis of a disease affecting the deep-sea sponge Geodia barretti. FEMS Microbiol. Ecol. 93, fix074 (2017).Thistle, D. Ecosystems of the Deep Oceans (Elsevier, 2003).
    Google Scholar 
    Pita, L., Erwin, P. M., Turon, X. & López-Legentil, S. Till death do us part: Stable sponge-bacteria associations under thermal and food shortage stresses. PLoS ONE 8, e80307 (2013).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Webster, N. S., Cobb, R. E. & Negri, A. P. Temperature thresholds for bacterial symbiosis with a sponge. ISME J. 2, 830–842 (2008).CAS 
    PubMed 

    Google Scholar 
    Gerringer, M. E., Drazen, J. C. & Yancey, P. H. Metabolic enzyme activities of abyssal and hadal fishes: Pressure effects and a re-evaluation of depth-related changes. Deep Sea Res. Part 1 Oceanogr. Res. Pap. 125, 135–146 (2017).CAS 

    Google Scholar 
    Yashayaev, I. Hydrographic changes in the Labrador Sea, 1960–2005. Prog. Oceanogr. 73, 242–276 (2007).ADS 

    Google Scholar 
    Rhein, M., Steinfeldt, R., Kieke, D., Stendardo, I. & Yashayaev, I. Ventilation variability of Labrador Sea Water and its impact on oxygen and anthropogenic carbon: A review. Philos. Trans. A Math. Phys. Eng. Sci. 375, 20160321 (2017).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Galand, P. E., Potvin, M., Casamayor, E. O. & Lovejoy, C. Hydrography shapes bacterial biogeography of the deep Arctic Ocean. ISME J. 4, 564–576 (2010).PubMed 

    Google Scholar 
    Frank, A. H., Garcia, J. A. L., Herndl, G. J. & Reinthaler, T. Connectivity between surface and deep waters determines prokaryotic diversity in the North Atlantic Deep Water: North Atlantic dark ocean prokaryotic biogeography. Environ. Microbiol. 18, 2052–2063 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Agogué, H., Lamy, D., Neal, P. R., Sogin, M. L. & Herndl, G. J. Water mass-specificity of bacterial communities in the North Atlantic revealed by massively parallel sequencing. Mol. Ecol. 20, 258–274 (2011).PubMed 

    Google Scholar 
    Djurhuus, A., Boersch-Supan, P. H., Mikalsen, S.-O. & Rogers, A. D. Microbe biogeography tracks water masses in a dynamic oceanic frontal system. R. Soc. Open Sci. 4, 170033 (2017).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Müller, O. et al. Spatiotemporal dynamics of ammonia-oxidizing Thaumarchaeota in distinct Arctic water masses. Front. Microbiol. 9, 1–13 (2018).ADS 

    Google Scholar 
    Kraemer, S., Ramachandran, A., Colatriano, D., Lovejoy, C. & Walsh, D. A. Diversity and biogeography of SAR11 bacteria from the Arctic Ocean. ISME J. https://doi.org/10.1038/s41396-019-0499-4 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Monier, A. et al. Upper Arctic Ocean water masses harbor distinct communities of heterotrophic flagellates. Biogeosciences 10, 4273–4286 (2013).ADS 

    Google Scholar 
    Monier, A. et al. Oceanographic structure drives the assembly processes of microbial eukaryotic communities. ISME J. 9, 990–1002 (2015).CAS 
    PubMed 

    Google Scholar 
    Corrège, T. The relationship between water masses and benthic ostracod assemblages in the western Coral Sea, Southwest Pacific. Palaeogeogr. Palaeoclimatol. Palaeoecol. 105, 245–266 (1993).
    Google Scholar 
    Muhling, B. A., Beckley, L. E., Koslow, J. A. & Pearce, A. F. Larval fish assemblages and water mass structure off the oligotrophic south-western Australian coast: SW Australian larval fish assemblages. Fish. Oceanogr. 17, 16–31 (2007).
    Google Scholar 
    Eerkes-Medrano, D. et al. A community assessment of the demersal fish and benthic invertebrates of the Rosemary Bank Seamount Marine Protected Area (NE Atlantic). Deep Sea Res. Part 1 Oceanogr. Res. Pap. https://doi.org/10.1016/j.dsr.2019.103180 (2019).Article 

    Google Scholar 
    Puerta, P. et al. Influence of water masses on the biodiversity and biogeography of deep-sea benthic ecosystems in the North Atlantic. Front. Mar. Sci. 7, 239 (2020).Roberts, E. et al. Water masses constrain the distribution of deep-sea sponges in the North Atlantic Ocean and Nordic Seas. Mar. Ecol. Prog. Ser. 659, 75–96 (2021).ADS 

    Google Scholar 
    Kenchington, E. et al. Connectivity modelling of areas closed to protect vulnerable marine ecosystems in the northwest Atlantic. Deep Sea Res. Part 1 Oceanogr. Res. Pap. 143, 85–103 (2019).
    Google Scholar 
    Louca, S. et al. Function and functional redundancy in microbial systems. Nat. Ecol. Evol. 2, 936–943 (2018).PubMed 

    Google Scholar 
    McCauley, M., Chiarello, M., Atkinson, C. L. & Jackson, C. R. Gut microbiomes of freshwater mussels (Unionidae) are taxonomically and phylogenetically variable across years but remain functionally stable. Microorganisms 9, 411 (2021).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Page, M., West, L., Northcote, P., Battershill, C. & Kelly, M. Spatial and temporal variability of cytotoxic metabolites in populations of the New Zealand Sponge Mycale hentscheli. J. Chem. Ecol. 31, 1161–1174 (2005).CAS 
    PubMed 

    Google Scholar 
    Ternon, E., Perino, E., Manconi, R., Pronzato, R. & Thomas, O. P. How environmental factors affect the production of guanidine alkaloids by the Mediterranean sponge Crambe crambe. Mar. Drugs 15, 181 (2017).PubMed Central 

    Google Scholar 
    Sacristán-Soriano, O., Banaigs, B. & Becerro, M. A. Temporal trends in the secondary metabolite production of the sponge Aplysina aerophoba. Mar. Drugs 10, 677–693 (2012).PubMed 
    PubMed Central 

    Google Scholar 
    Ivanisevic, J. et al. Biochemical trade-offs: Evidence for ecologically linked secondary metabolism of the sponge Oscarella balibaloi. PLoS ONE 6, e28059 (2011).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Burg, M. B. & Ferraris, J. D. Intracellular organic osmolytes: Function and regulation. J. Biol. Chem. 283, 7309–7313 (2008).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Nau-Wagner, G., Boch, J., Le Good, J. A. & Bremer, E. High-affinity transport of choline-O-sulfate and its use as a compatible solute in Bacillus subtilis. Appl. Environ. Microbiol. 65, 560–568 (1999).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Popowich, A., Zhang, Q. & Le, X. C. Arsenobetaine: The ongoing mystery. Natl. Sci. Rev. 3, 451–458 (2016).CAS 

    Google Scholar 
    Connor, K. M. & Gracey, A. Y. High-resolution analysis of metabolic cycles in the intertidal mussel Mytilus californianus. Am. J. Physiol. Regul. Integr. Comp. Physiol. 302, R103–R111 (2012).CAS 
    PubMed 

    Google Scholar 
    Cárdenas, P. Who produces Ianthelline? The Arctic sponge Stryphnus fortis or its sponge Epibiont Hexadella dedritifera: A probable case of sponge–sponge contamination. J. Chem. Ecol. 42, 339–347 (2016).PubMed 

    Google Scholar 
    Steffen, K. et al. Barrettides: A peptide family specifically produced by the deep-sea sponge Geodia barretti. J. Nat. Prod. 84, 3138–3146 (2021).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Abbamondi, G. R., De Rosa, S., Iodice, C. & Tommonaro, G. Cyclic dipeptides produced by marine sponge-associated bacteria as quorum sensing signals. Nat. Prod. Commun. 9, 229–232 (2014).CAS 
    PubMed 

    Google Scholar 
    Kasheverov, I. et al. 6-Bromohypaphorine from Marine Nudibranch Mollusk Hermissenda crassicornis is an agonist of human α7 nicotinic acetylcholine receptor. Mar. Drugs 13, 1255–1266 (2015).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Moitinho-Silva, L. et al. The sponge microbiome project. Gigascience 6, 1–7 (2017).CAS 
    PubMed 

    Google Scholar 
    Kielak, A. M., Barreto, C. C., Kowalchuk, G. A., van Veen, J. A. & Kuramae, E. E. The ecology of acidobacteria: Moving beyond genes and genomes. Front. Microbiol. 7, 744 (2016).Crits-Christoph, A., Diamond, S., Butterfield, C. N., Thomas, B. C. & Banfield, J. F. Novel soil bacteria possess diverse genes for secondary metabolite biosynthesis. Nature 558, 440–444 (2018).ADS 
    CAS 
    PubMed 

    Google Scholar  More

  • in

    Active swimming and transphort by currents observed in Japanese eels (Anguilla japonica) acoustically tracked in the western North Pacific

    To our knowledge, this study provides the first recorded information on the active swimming of Japanese eels and on their transport by currents in the open ocean. Specifically, the strong flow of the KC largely dominated the movements of the eels and transported them northeastward while they swam mainly southward, and active swimming contributed a little to their travel trajectories. In contrast, the swimming of eels made a relatively higher contribution to their travel trajectories in the TS area.Our in situ estimates of the mean swimming speeds of Japanese eels (26–41 cm/s) were similar or slightly lower than those of European eels. In the acoustic tracking experiment of European eels considering environmental current vectors, their swimming speeds were 35–58 cm/s in the coastal midwater26. In a laboratory experiment using stamina tunnels with stable temperatures, the optimal swimming speeds of European eels were estimated to be 61–68 cm/s (0.74–1.02 BL/s)56, which were higher than the in situ estimates. The minimum swimming speed of European eels is considered to be 40 cm/s if they will arrive at their spawning area in the Sargasso Sea (distance of 5500 km) in 6 months, and their optimal swimming speeds were sufficient to migrate over the long distance in time for the near-spawning period after escape from their growth habitats56. However, field studies using PSAT tagging also reported that in situ migration speeds (including transport by currents) were less than the optimal swimming speeds and suggested that some European eels could reach their spawning area within the near-spawning periods and that others only arrive in time for the following spawning season19.Our estimated effective swimming speed of Japanese eels, all day and all night over the tracking periods, ranged from 3 to 30 cm/s with individual variations. These estimates were consistent with the swimming speeds (excluding transport by currents) of 2.2–15.1 km/day (2–18 cm/s) estimated in the PSAT study of Japanese eels14. Silver-phase Japanese eels start migrating from their coastal growth habitats in Japan primarily in October to December57, 58, and spawning near the West Mariana Ridge occurs in April to August33, 35. Numerical models assuming that migrating eels use true navigation (readjusted compass) or a constant compass heading (fixed compass from the departure place to the spawning site) indicate that the minimal swimming speed required to arrive at the spawning area within 8 months is 10–12 cm/s37. Our estimated effective swimming speeds of five out of ten eels during the day and eight out of ten eels during the night were similar or higher than these minimal speeds. The low effective swimming speeds frequently observed during the day might be due to the relatively low values observed in the swimming speed at 10 min intervals and the swimming directions often varying during the day. When eels swim with stable orientation, as observed in three of the eels (WE2999_TS, WE3001_TS, and WE3002_TS) during the night, the effective swimming speeds exceeded 25 cm/s. If such a stable orientation is maintained and compensate the low speeds during the day, the eels that leave during autumn and winter will be able to arrive at the spawning area during the next spring to summer.It should also be noted that the swimming speeds in body length per second were significantly higher in shallow water during the night than in deep water during the day. In the open ocean, anguillid species exhibit DVMs during oceanic migration, swimming at depth during the day and in the shallows during the night9,10,11,12,13,14,15,16,17,18,19,20,21,22. These DVMs are likely related to the possible avoidance from visual predators under light conditions19 or maturation control59. Essentially, through the DVMs, the eels encounter low temperatures ( 20 °C) during the same day. Generally, the swimming speeds of fishes are restricted by the ambient water temperature60, and the water temperature encountered through DVMs might influence the horizontal-swimming speeds of Japanese eels.Other factors besides swimming speed are important for the success of eel migrations, such as adapting to mesopelagic zones that silver eels undergo during their spawning migrations. The most important and obvious morphological adaptation in mesopelagic fish is their well-developed eyes, and migrating eels also seem to use this strategy. These fish often have relatively large pupils61, high photosensitive structures, such as tubular eyes62, a pure rod multibank retina63, and maximum rhodopsin absorption to adapt to the blue-green light in the deep sea64. The eyes of catadromous eels displayed enlargement during their transformation into migrating silver-phase eels65, 66 and potentially increase their retinal surface area, which results in the possibility of increased photon capture. In addition, the rhodopsins in the eyes change from a freshwater type with a maximum absorption of ~ 500 nm to a deep-sea type with a maximum absorption of ~ 480 nm67,68,69. Their extreme sensitivity to light is evident through their DVM in mesopelagic water, where the timing of a large descent and ascent in the DVM demonstrated by migrating catadromous eels is precisely synchronized with sunrise and sunset. Furthermore, eels alter their swimming depth in response to the phase of the Moon9, 15, 20, 21, appearing to be capable of perceiving extremely low-intensity moonlight.This study showed that three eels released in the TS area (mainly 300–400-m depth) and one eel in the KC area (near surface) were found to change their swimming direction around the time of the solar culmination when the Sun’s bearing changed. The clockwise and counterclockwise trajectories of these eels corresponded to whether the Sun moved from the east to west in the southern and northern sky, suggesting that they demonstrated horizontal negative phototaxis swimming to avoid sunlight. They might move to avoid high-intensity sunlight horizontally, not vertically, as they gradually increase the swimming depths possibly due to acclimation to cold deep water after release. The daytime swimming depths of the eels became deeper day-by-day after their release (Fig. 4); a similar phenomenon was observed in European eels12, American eels17, and long fin eels13. Recently, Higuchi et al.20 observed that the daytime swimming depths of Japanese eels released in the TS area gradually became deeper until 13 days after their release. These facts indicate that they gradually acclimate to the cold water at the deep depths after release. Since this tracking study was conducted 2–8 days after their release, the daytime swimming depth of eels would not have reached a steady state yet. The relatively high intensity from sunlight at the shallow depths where eels swam immediately after release in the TS area might cause horizontal avoidance behavior from the light.In other cases, many eels, especially those released in the KC area, did not demonstrate the rotational behavior. The eels in the KC area mostly stayed deeper (500–800 m) during the day than the eels in the TS area (stayed at depths of 300–600 m) even during the periods shortly after their release. This is possibly due to higher water temperatures even at the deeper depths in the KC area (Fig. 4). The eels in the TS area did not demonstrate clear rotational behavior at depths of more than 400 m. The PSAT studies have reported that the steady swimming depths during the day were 500–800 m14, 20. Therefore, it was assumed that the rotational behavior observed in some eels was not a regular behavior during their migration. However, the rotational behavior observed in this study suggests that they surely perceive the horizontal direction of Sun’s bearing at 400 m depths at least. Generally, they exhibit DVM precisely synchronizing with sunrise and sunset and surely perceive the change in sunlight intensity at deeper depths9,10,11,12,13,14,15,16,17,18,19,20,21,22. Even though the rotational behavior were not observed below 400 m, it remains unknown whether the eels could not perceive the Sun’s bearing from the light penetrated at depth; thus, further investigation of response to underwater light is required in future.While possible negative phototaxis behaviors were observed in some eels after release around the time of solar culmination, the trajectories of ten eels during the entire period of tracking experiments implied that each eel tended to swim meridionally toward the bearing of the Sun at culmination. We observed that eels released at middle (20°–34° N) and low (12°–13°N) latitudes tended to swim southward and northward in the meridional direction, respectively (Fig. 6A, B). The tendency to move in a north–south swimming direction corresponded to whether the Sun culminated to the north or south: eels swam southward if the culmination occurred in the southern sky, but they swam northward if it occurred in the northern sky (Fig. 6). In the KC area (33°–35° N), the Sun rose in the southeast, passed celestial meridian in the southern sky, and set in the southwest (Fig. 6C). At 20° N in the summer time when the tracking study was conducted, the Sun also passed a celestial meridian in the southern sky, but rose in the northeast and set in the northwest (Fig. 6C). When Sun culmination occurred in the southern sky, the meridional swimming directions tended to be southward (Fig. 6A). However, at 12° to 13° N in the summer time, the Sun rose in the northeast, passed the celestial meridian in the northern sky, and set in the northwest (Fig. 6D). When the Sun at culmination appeared in the northern sky, the meridional swimming directions tended to be northward (Fig. 6B). Furthermore, the swimming behavior by one eel (WE4264_TS) that was released slightly south (14° 15′ N) from the latitude with the Sun passing through the zenith was also indicative of the meridional swimming traits. This eel moved in a northerly direction on the first day, but then it lost its north–south bias in swimming around 14° 30′ N, where the Sun nearly passed through the zenith (Figs. 1 and 6D). These observations imply that the eels might move toward the latitude with the Sun passing through the zenith.Figure 6Swimming trajectories of eels and solar paths in the celestial sphere viewed from east during each tracking period. Swimming trajectories of eels released at (A) 20°N in the tropical–subtropical area and the Kuroshio Current area, and (B) 12°–14°15′N in the tropical–subtropical area. Solar paths through the north (N)–south (S) axis and the zenith at the time of tracking in (C) 20°N in the tropical–subtropical area and the Kuroshio Current area, and (D) 12°–14°15′N in the tropical–subtropical area.Full size imageTheoretically, it is possible for mesopelagic animals to use solar cues for navigation at depths shallower than the asymptotic depth, below which penetrating light rays are symmetrical around the vertical axis and the polarization plane becomes horizontal. For example, the Sargasso Sea, where the two Atlantic catadromous eels spawn1, 3, has extremely transparent water70, and the major axis of radiance distribution still remains tilted in the mesopelagic zone. The angle of maximum radiance of sunlight at 475 nm was 13° at depths of 400 m when the Sun’s elevation was 60° (Fig. 7)52, 53. In highly transparent water, the asymptotic depth could be as high as 1000–1200 m, and the depths below this cannot be utilized for compass use53. Currently, it is not possible to verify whether the Sun culminating to north or south caused the meridional swimming tendencies of eels in this study. Potentially, these meridional swimming tendencies could be due to other orientation clues, such as the geomagnetic field, as discussed for temperate anguillid eels17, 45. Nevertheless, in future studies, it would be worthwhile considering solar cues as a possible candidate factor in the orientation of eels, even when under faint underwater light conditions.Figure 7Optical features of underwater sunlight. (A) Schematic diagram of sunlight penetrating the deep ocean at 90° to the solar bearing. The line of arrows indicates the major axis of the incident beam in a vertical plane perpendicular to the Sun’s bearing. Blue light (around 475 nm) reaches the lowest depths. With increasing depth, the light field alters its character into a less directed distribution and a lower energetic level through scattering and absorption processes. Penetrating light rays are symmetrical around the region below the asymptotic depth. (B) An example of spectral radiance distribution (e. g. 475 nm) at a certain depth. The radiance distribution is shown by an ellipsoid and the major axis is drawn by a line with arrow. The refracted angular deviation (a) of the major axis of underwater radiance distribution from the vertical axis equals the tilt of the electric vector (ee bar) from the horizontal axis53. When the Sun’ s elevation was 60° in the Sargasso Sea, the radiance distributions were measured at three different depths and the tilt of the electric vector were estimated to be 24° at depths of 100 m and 200 m and 13° at depth of 400 m52, 53.Full size imageGiven that eels might be able to use the Sun’s bearing at culmination to orient their meridional swimming direction, this orientation scheme could support a clockwise eel migration route following a partial subtropical gyre2, 37. Japanese eels that departed from the nursery area first transported northeastward via the strong KC. Maintaining southward swimming in the current, they eventually crossed the current and shifted to the southward migration course. When they enter the KC, movement to the left of the bearing of the Sun at culmination (i.e., south) is the typical pattern for the early migration of eels from Japan. The movements of eels observed in the KC were consistent with the expected route; however, eels released at low latitudes of the TS area often swam northward but also westward, which resulted in their traveling an unreasonable distance from the spawning area. This might be due to their behavior during early migration. In this study, eels were transported from Japan and released into the open ocean at low latitudes. They might have swum toward the expected bearing of the Sun at culmination as if they were in the north and moved to the left of the Sun’s bearing along with the North Equatorial Current, which would mimic the early migration of eels leaving Japan and moving along the KC.Among the eels tracked in this study were individuals with impaired swim bladders, yellow-phase eels in the process of hormone-treatment maturation, and silver-phase eels collected from different rivers in different years. Despite these variations, the swimming characteristics of the eels did not differ in terms of their DVM behavior16 and swimming speed. Nevertheless, confirmation of our results using samples with a uniform status in future research would be highly desirable. In this study, the tracked eel position was assumed to be identical to that of the tracking ship and the errors between these two positions could not be evaluated; thus, the positioning of tracked fish also may need to be improved in future studies. Experimental studies, such as tracking of blind, magnetically disturbed, or olfactory-blocked eels, could help obtain or eliminate alternative candidate clues and enhance our understanding of the navigational system of anguillid eels. Controlled laboratory experiments are required to directly quantify the ability of eels to perceive radiance distribution or polarization, along with any associated behaviors. In addition, the internal clock of eels required to perform celestial navigation should be investigated. Meanwhile, the results obtained from this study can enhance our knowledge of the mechanisms underlying the migratory behaviors of eels in the open ocean. More

  • in

    Tree functional traits, forest biomass, and tree species diversity interact with site properties to drive forest soil carbon

    Data collection: soil organic carbonThe process of data acquisition, selection and harmonisation is illustrated in the Supplementary Fig. S15 and in the Supplementary Tables S4–6. We conducted a systematic review for peer-reviewed journal articles, published before December 2018, from Web of Science, and Google Scholar with the search terms “(tree species OR forest) AND (soil organic carbon OR soil organic matter)”. We also used studies listed in two previously published meta-analyses16,17, or cited in already retained references (including references in English, French, Spanish, Portuguese, or Russian). For inclusion in the analysis we chose studies based on the following criteria: (1) the study reported soil organic carbon (SOC) or soil organic matter (SOM) concentrations or pools, at least in the topsoil layer and under at least two single-species forest stands; (2) the stands had to be older than 10 years81; (3) the stands had not experienced a major disturbance that differed between tree species, for at least 30 years (e.g., we rejected studies that compared natural forests with planted forests that were less than 30 years old); (4) The SOC concentration was More

  • in

    Effect of climate on strategies of nest and body temperature regulation in paper wasps, Polistes biglumis and Polistes gallicus

    Both in Polistes biglumis and P. gallicus in most of the inhabited nests all types of brood were present: eggs, larvae and pupae (Table S1), with the exception of one foundress nest of P. biglumis with only one egg. The size of thermographed nests was quite variable in both species, the number of cells ranging from 18 to 99 in P. biglumis (mean: 61.6 cells), and from 19 to 381 in P. gallicus (mean: 101.7 cells) (Table S1). The mean number of wasps on the thermographed nests was higher in P. gallicus (12.6 wasps) than in P. biglumis (7.1 wasps). All nests of Polistes biglumis we observed in this study were built on stone substrate or walls (Figs. 1c, 2a). Only recently we found one nest built on a pile of wood. The choice of the nest substrate was more diverse in P. gallicus (Figs. 1d, 2b). They chose stone, concrete, walls, window grilles, and metal of fences or doorframes.Figure 2Examples of nests and fieldwork set-up in Obergail (a) and Sesto Fiorentino (b). 1 = thermocouple wire; 2 = global radiation sensor, 3 = Peltier-element IR reference source.Full size imageDaily nest temperature coursePolistes biglumisFigure 3 shows a sequence of thermograms of a P. biglumis nest taken from dawn to dusk. Before sunrise the temperatures of the nest and of the wasps on it were quite low (mean ~ 15 °C) and uniform (~ 12 to 17.5 °C; Fig. 3a). The temperature of the stone substrate where the nest was built on was considerably higher (~ 20 °C). After sunrise (Fig. 3b,c) the nest temperature began to rise quickly. It only needed 13 min of sunshine (radiation) to heat the nest from ~ 17 to ~ 25 °C. Within one hour, temperature differences of almost 20 °C were measured within the nest. At 6:50, when the highest temperature on the nest was already at 36.2 °C, fast movements of the adults with inspections of the cells were observed (Fig. 3c). Soon afterwards the increasing temperature induced the wasps to start fanning (arrow in Fig. 3d). The wasps also began to gather water and spread it on and inside cells to cool the nest by evaporation (Fig. 3d,e). Towards late morning, some parts of the nest reached temperatures as high as 46 °C (Fig. 3e)! As soon as the nest was shaded by the substrate (~ 13:00) the nest temperature decreased according to the decrease in ambient temperature (Fig. 3f,g), reaching ~ 21 °C on average after dusk (Fig. 3h). At that time the substrate temperature (~ 25 °C) was still about 4 °C higher than the nest temperature.Figure 3Thermograms of a P. biglumis nest during a whole day (19.07.2017). (a) Before sunrise at 6:20; (b) during sunrise (06:33); (c) nest temperature increasing fast in sunshine; (d) with a fanner for convective nest cooling (arrow; see also Fig. S4); (e) with water drops for evaporative cooling when sunshine increased part of the nest to temperatures  > 45 °C; (f,g) after sunset (nest now in shade) in the afternoon; (h) at dusk with wasps sitting motionless on the nest. Time = CEST = UTC + 2 h.Full size imageThe nest and body temperatures of a complete 24 h cycle of a different nest are shown in Fig. 4a. At night the nest temperature and the wasps’ thorax temperature decreased slowly according to the decrease of the air temperature. The substrate temperature was always higher than the mean nest temperature, which surely helped to keep the nest temperature higher than the temperature of the surrounding air (Tanest). Variation of within-nest temperature (max–min) was low at night. As soon as solar radiation increased in early morning, the nest temperature and the body temperature of the wasps on it increased rapidly, and the variation of nest temperature (max–min) increased (see also Fig. 3b). Though the maximum nest temperature reached values as high as 46.9 °C, cooling measures of the wasps (fanning and spreading of water drops, see below) kept the mean nest temperature always below 38.5 °C. Cooling of the nest after sunset (at the nest) was much slower than the increase in the morning, following the decrease of ambient and substrate temperature (Fig. 4a,b).Figure 4Examples of daily temperature changes of nests and wasps of P. biglumis (a,b) and P. gallicus (c,d). Tthorax = mean thorax surface temperature of up to five adult individuals per time of measurement; gray ribbon: total range of nest temperatures (Tmax:Tmin) with mean; Tsubstrate = temperature beside the nest (see Fig. S1c,d); Tanest = ambient air temperature directly at the nest. Ta = ambient air temperature in shade 1–3 m away from nest; Radiation = global radiation hitting the nest; black bars = fanning events at the time of thermographic measurements: actually, many more fanning events were observed. (c) Fanning was never observed! See also Fig. S2 for another example of a P. gallicus nest in shade. Time = CEST = UTC + 2 h.Full size imagePolistes gallicusMost P. gallicus nests were built in locations with no or only little direct sunshine (Figs. 2b, 4c, Fig. S2). In their habitats temperatures in midsummer are often already quite high in the morning, and may increase to values higher than 40 °C during the day (Fig. 4d). Mean temperatures of the nest and of the imagines on it were usually higher than the air temperature close to the nest (Tanest). In most nests variation of within-nest temperature (max–min) remained small throughout the day. On hot days (Tanest  > 40 °C), however, maximum temperatures of empty cells in the nest margin sometimes reached values as high as 49.9 °C even in shade. Body temperature of the adults was mostly similar to the mean nest temperature (Fig. 4c, Fig. S2). At night, the nest temperature decreased according to the decrease of Tanest, similar to P. biglumis but at a higher level (Fig. 4d).The situation was different in one large nest which had been built in a location exposed to the morning sun (Figs. 4d, 5). On a hot day when Tanest increased to values higher than 42 °C, the body temperature of the adults increased to values up to 5 °C higher than the mean nest temperature. Nevertheless, though the combined effects of high air temperature and intense insolation increased part of the nest to a temperature of ~ 58 °C (Fig. 4d), mean nest temperature was kept below 41 °C. This was accomplished by cooling with many water droplets in the cells (dark spots in Fig. 5), and by the occurrence of fanning during the period when the sun was shining on the nest (Fig. 4d; see arrows in Fig. 5c). Fanning, however, was quite rare in all the other observed nests, even during the hottest time of the day! Water droplets were carried onto this nest until evening (Fig. 5h), as at that time the nest temperature was still at about 35–38 °C.Figure 5Thermograms of a large P. gallicus nest during a whole day (01.08.2017). Thermograms are rotated 90° clockwise (the upper part is on the right). (a) Before sunrise (6:36); (b) during sunrise (06:46) with the first water drops visible (dark spots); (c) with two fanners for convective nest cooling (arrows, see also Fig. 4d); (d) with more cooling drops; (e) after sunset at the nest site (nest now in shade); (f–h) after sunset in the afternoon and evening. Time = CEST = UTC + 2 h. For temperature evaluation see Fig. 4d.Full size imageBody and nest temperaturesFigure 6 shows a comparison of the dependence of body and nest temperatures on ambient air temperature and insolation between the two species. In the lower ranges of air temperature, usually at night, body temperature followed Tanest closely in both species. The exposition of the P. biglumis nests to the morning sun at ESE (Fig. 7) increased the wasp body temperature to values of often more than 15 °C higher than the surrounding air. However, body temperatures remained always below 40 °C (Fig. 6a). In P. gallicus, by contrast, the body temperature of the wasps increased considerably above 40 °C, to maximum values of about 46 °C, especially (but not exclusively) during intense insolation in the nest exposed to the morning sun (Fig. 6b).Figure 6Surface temperature of the thorax of adult wasps, of different stages of brood and of water drops of P. biglumis (left) and P. gallicus (right), in dependence on ambient air temperature close to the nest (Tanest) and global radiation (color scale). Egg f.n. = single egg on a foundress nest; diagonal lines = isolines. Regressions were calculated for shaded conditions (Radiation = 0–100 W/m2; black or gray solid lines) and sunshine (Radiation  > 100 W/m2; pink broken lines); P  More