More stories

  • in

    Impacts on tourism demand

    Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard
    Provided by the Springer Nature SharedIt content-sharing initiative More

  • in

    Selection on offspring size and contemporary evolution under ocean acidification

    Sunday, J. M., Crim, R. N., Harley, C. D. G. & Hart, M. W. Quantifying rates of evolutionary adaptation in response to ocean acidification. PLoS ONE 6, e22881 (2011).CAS 
    Article 

    Google Scholar 
    Kelly, M. W. & Hofmann, G. E. Adaptation and the physiology of ocean acidification. Funct. Ecol. 27, 980–990 (2013).Article 

    Google Scholar 
    Munday, P. L., Warner, R. R., Monro, K., Pandolfi, J. M. & Marshall, D. J. Predicting evolutionary responses to climate change in the sea. Ecol. Lett. 16, 1488–1500 (2013).Article 

    Google Scholar 
    Reusch, T. B. H. Climate change in the oceans: evolutionary versus phenotypically plastic responses of marine animals and plants. Evol. Appl. 7, 104–122 (2014).Article 

    Google Scholar 
    Sunday, J. M. et al. Evolution in an acidifying ocean. Trends Ecol. Evol. 29, 117–125 (2014).Article 

    Google Scholar 
    Kroeker, K. J., Kordas, R. L., Crim, R. N. & Singh, G. G. Meta-analysis reveals negative yet variable effects of ocean acidification on marine organisms. Ecol. Lett. 13, 1419–1434 (2010).Article 

    Google Scholar 
    Przeslawski, R., Byrne, M. & Mellin, C. A review and meta-analysis of the effects of multiple abiotic stressors on marine embryos and larvae. Glob. Change Biol. 21, 2122–2140 (2015).Article 

    Google Scholar 
    Cattano, C., Claudet, J., Domenici, P. & Milazzo, M. Living in a high CO2 world: a global meta-analysis shows multiple trait-mediated fish responses to ocean acidification. Ecol. Monogr. 88, 320–335 (2018).Article 

    Google Scholar 
    Lohbeck, K., Riebesell, U. & Reusch, T. Adaptive evolution of a key phytoplankton species to ocean acidification. Nat. Geosci. 5, 346–351 (2012).CAS 
    Article 

    Google Scholar 
    Dam, H. G. et al. Rapid, but limited, zooplankton adaptation to simultaneous warming and acidification. Nat. Clim. Change 11, 780–786 (2021).Article 

    Google Scholar 
    Kelly, M. W., Padilla-Gamiño, J. L. & Hofmann, G. E. Natural variation and the capacity to adapt to ocean acidification in the keystone sea urchin Strongylocentrotus purpuratus. Glob. Change Biol. 19, 2536–2546 (2013).Article 

    Google Scholar 
    Pespeni, M. H. et al. Evolutionary change during experimental ocean acidification. Proc. Natl Acad. Sci. USA 110, 6937–6942 (2013).CAS 
    Article 

    Google Scholar 
    Foo, S. A., Dworjanyn, S. A., Poore, A. G. B., Harianto, J. & Byrne, M. Adaptive capacity of the sea urchin Heliocidaris erythrogramma to ocean change stressors: responses from gamete performance to the juvenile. Mar. Ecol. Prog. Ser. 556, 161–172 (2016).CAS 
    Article 

    Google Scholar 
    Malvezzi, A. J. et al. A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification. Evol. Appl. 8, 352–362 (2015).CAS 
    Article 

    Google Scholar 
    Bitter, M. C., Kapsenberg, L., Gattuso, J.-P. & Pfister, C. A. Standing genetic variation fuels rapid adaptation to ocean acidification. Nat. Commun. 10, 5821 (2019).CAS 
    Article 

    Google Scholar 
    Falconer, D. S. & Mackay, T. F. C. Introduction to Quantitative Genetics 4th edn (Pearson Prentice Hall, 1996).Lynch, M. & Walsh, B. Genetics and Analysis of Quantitative Traits (Oxford Univ. Press, 1998).Ishimatsu, A., Hayashi, M. & Kikkawa, T. Fishes in high-CO2, acidified oceans. Mar. Ecol. Prog. Ser. 373, 295–302 (2008).CAS 
    Article 

    Google Scholar 
    Melzner, F. et al. Physiological basis for high CO2 tolerance in marine ectothermic animals: pre-adaptation through lifestyle and ontogeny? Biogeosciences 6, 2313–2331 (2009).CAS 
    Article 

    Google Scholar 
    Timothy A. Mousseau and Charles W. Fox. Maternal Effects as Adaptations 178–201 (Oxford Univ. Press, 1998).Marshall, D., Allen, R. & Crean, A. The ecological and evolutionary importance of maternal effects in the sea. Oceanogr. Mar. Biol. 46, 203–250 (2008).
    Google Scholar 
    Tasoff, A. J. & Johnson, D. W. Can larvae of a marine fish adapt to ocean acidification? Evaluating the evolutionary potential of California grunion (Leuresthes tenuis). Evol. Appl. 12, 560–571 (2019).CAS 
    Article 

    Google Scholar 
    Smith, C. C. & Fretwell, S. D. The optimal balance between size and number of offspring. Am. Nat. 108, 499–506 (1974).Article 

    Google Scholar 
    Shimada, Y., Shikano, T., Murakami, N., Tsuzaki, T. & Seikai, T. Maternal and genetic effects on individual variation during early development in Japanese flounder Paralichthys olivaceus. Fish. Sci. 73, 244–249 (2007).CAS 
    Article 

    Google Scholar 
    Johnson, D. W., Christie, M. R. & Moye, J. Quantifying evolutionary potential of marine fish larvae: heritability, selection, and evolutionary constraints. Evolution 64, 2614–2628 (2010).Article 

    Google Scholar 
    Miles, C. M., Hadfield, M. G. & Wayne, M. L. Heritability for egg size in the serpulid polychaete Hydroides elegans. Mar. Ecol. Prog. Ser. 340, 155–162 (2007).Article 

    Google Scholar 
    Iguchi, K. & Yamaguchi, M. Adaptive significance of inter- and intrapopulational egg size variation in ayu Plecoglossus altivelis (osmeridae). Copeia 1994, 184–190 (1994).Article 

    Google Scholar 
    Marshall, D. J. & Keough, M. J. Effects of settler size and density on early post-settlement survival of Ciona intestinalis in the field. Mar. Ecol. Prog. Ser. 259, 139–144 (2003).Article 

    Google Scholar 
    González-Ortegón, E. & Giménez, L. Environmentally mediated phenotypic links and performance in larvae of a marine invertebrate. Mar. Ecol. Prog. Ser. 502, 185–195 (2014).Article 

    Google Scholar 
    Pan, T.-C. F., Applebaum, S. L. & Manahan, D. T. Experimental ocean acidification alters the allocation of metabolic energy. Proc. Natl Acad. Sci. USA 112, 4696–4701 (2015).CAS 
    Article 

    Google Scholar 
    Rollinson, N. & Hutchings, J. A. Environmental quality predicts optimal egg size in the wild. Am. Nat. 181, 76–90 (2013).Article 

    Google Scholar 
    Lynch, M. & Walsh, B. Genetics and Analysis of Quantitative Traits (Oxford Univ. Press, 1998).Munday, P. L. Transgenerational acclimation of fishes to climate change and ocean acidification. F1000Prime Rep. 6, 99 (2014).Article 

    Google Scholar 
    Murray, C. S., Malvezzi, A., Gobler, C. J. & Baumann, H. Offspring sensitivity to ocean acidification changes seasonally in a coastal marine fish. Mar. Ecol. Prog. Ser. 504, 1–11 (2014).Article 

    Google Scholar 
    Baumann, H. Experimental assessments of marine species sensitivities to ocean acidification and co-stressors: how far have we come? Can. J. Zool. 97, 399–408 (2019).Article 

    Google Scholar 
    Chevin, L.-M., Lande, R. & Mace, G. M. Adaptation, plasticity, and extinction in a changing environment: towards a predictive theory. PLoS Biol. 8, e1000357 (2010).Article 
    CAS 

    Google Scholar 
    Bell, G. Evolutionary rescue and the limits of adaptation. Phil. Trans. R. Soc. B 368, p20120080 (2013).Article 

    Google Scholar 
    Carlson, S. M., Cunningham, C. J. & Westley, P. A. H. Evolutionary rescue in a changing world. Trends Ecol. Evol. 29, 521–530 (2014).Article 

    Google Scholar 
    Smyder, E. A., Martin, K. L. M. & Gatten, R. E. Jr Temperature effects on egg survival and hatching during the extended incubation period of California grunion, Leuresthes tenuis. Copeia 2002, 313–320 (2002).Article 

    Google Scholar 
    Barneche, D. R., Robertson, D. R., White, C. R. & Marshall, D. J. Fish reproductive-energy output increases disproportionately with body size. Science 360, 642–645 (2018).CAS 
    Article 

    Google Scholar 
    Van Noordwijk, A. J. & de Jong, G. Acquisition and allocation of resources: their influence on variation in life history tactics. Am. Nat. 128, 137–142 (1986).Article 

    Google Scholar 
    Davidson, C. Spatial and Temporal Variability of Coastal Carbonate Chemistry in the Southern California Region. MSc thesis, Univ. California, San Diego (2015).Jones, J. M., Sweet, J., Brzezinski, M. A., McNair, H. M. & Passow, U. Evaluating carbonate system algorithms in a nearshore system: does total alkalinity matter? PLoS ONE 11, e0165191 (2016).Article 
    CAS 

    Google Scholar 
    Gruber, N. et al. Rapid progression of ocean acidification in the California current system. Science 337, 220–223 (2012).CAS 
    Article 

    Google Scholar 
    Turi, G., Lachkar, Z., Gruber, N. & Münnich, M. Climatic modulation of recent trends in ocean acidification in the California current system. Environ. Res. Lett. 11, 014007 (2016).Article 

    Google Scholar 
    Northcott, D. et al. Impacts of urban carbon dioxide emissions on sea-air flux and ocean acidification in nearshore waters. PLoS ONE 14, e0214403 (2019).CAS 
    Article 

    Google Scholar 
    Rausher, M. D. The measurement of selection on quantitative traits: biases due to environmental covariances between traits and fitness. Evolution 46, 616–626 (1992).Article 

    Google Scholar 
    Venables, W. N. & Ripley, B. D. Modern Applied Statistics with S (Springer, 2002).R Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2021).Kruuk, L. E. B. Estimating genetic parameters in natural populations using the animal model. Phil. Trans. R. Soc. B 359, 873–890 (2004).Article 

    Google Scholar 
    Wilson, A. J. et al. An ecologist’s guide to the animal model. J. Anim. Ecol. 79, 13–26 (2010).Article 

    Google Scholar 
    Hadfield, J. D. MCMC methods for multi-response generalized linear mixed models: the MCMCglmm R package. J. Stat. Softw. 33, (2010).Heidelberger, P. & Welch, P. D. Simulation run length control in the presence of an initial transient. Oper. Res. 31, 1109–1144 (1983).Article 

    Google Scholar 
    Clark, F. N. The Life History of Leuresthes Tenuis, an Atherine Fish with Tide Controlled Spawning Habits Fish Bulletin No. 10 (California Department of Fish and Game, 1925).Johnson, D.W. Data from: Selection on offspring size and contemporary evolution under ocean acidification. Dryad https://doi.org/10.5061/dryad.0gb5mkm3w (2022) More

  • in

    Last glacial loess dynamics in the Southern Caucasus (NE-Armenia) and the phenomenon of missing loess deposition during MIS-2

    Lehmkuhl, F. et al. Loess landscapes of Europe-mapping, geomorphology, and zonal differentiation. Earth-Sci. Rev. 215, 103496 (2021).Article 

    Google Scholar 
    Li, Y., Shi, W., Aydin, A., Beroya-Eitner, M. A. & Gao, G. Loess genesis and worldwide distribution. Earth Sci. Rev. 201, 102947 (2020).Article 

    Google Scholar 
    Moine, O. et al. The impact of last Glacial climate variability in west-European loess revealed by radiocarbon dating of fossil earthworm granules. PNAS 114, 6209–6214 (2017).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Újvári, G. et al. Coupled European and Greenland last glacial dust activity driven by North Atlantic climate. PNAS 114, E10632–E10638 (2017).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Rousseau, D.-D. et al. Link between European and North Atlantic abrupt climate changes over the last glaciation. Geophys. Res. Lett. 34, L22713 (2007).ADS 
    Article 

    Google Scholar 
    Rousseau, D.-D. et al. Eurasian contribution to the last glacial dust cycle: how are loess sequences built?. Clim. Past. 13, 1181–1197 (2017).Article 

    Google Scholar 
    Fischer, P. et al. Millennial-scale terrestrial ecosystem responses to Upper Pleistocene climatic changes: 4D-reconstruction of the Schwalbenberg Loess-Palaeosol-Sequence (Middle Rhine Valley, Germany). CATENA 196, 104913 (2021).Article 

    Google Scholar 
    Wolf, D. et al. Evidence for strong relations between the Upper Tagus Loess Formation (Central Iberia) and the marine atmosphere off the Iberian Margin during the Last Glacial Period. Quat. Res. 101, 84–113 (2021).Article 

    Google Scholar 
    Porter, S. & An, Z. Correlation between climate events in the North Atlantic and China during the last glaciation. Nature 375, 305–308 (1995).ADS 
    CAS 
    Article 

    Google Scholar 
    Sun, Y. et al. Influence of Atlantic meridional overturning circulation on the East Asian winter monsoon. Nat. Geosci. 5, 46–49 (2012).ADS 
    CAS 
    Article 

    Google Scholar 
    Zeeden, C. et al. Patterns and timing of loess-palaeosol transitions in Eurasia: Constraints for palaeoclimate studies. Glob. Planet. Change 162, 1–7 (2018).ADS 
    Article 

    Google Scholar 
    Cheng, H. et al. The climatic cyclicity in semiarid-arid central Asia over the past 500,000 years. Geophys. Res. Lett. 39, L01705 (2012).ADS 
    Article 

    Google Scholar 
    Cheng, H. et al. The Asian monsoon over the past 640,000 years and ice age terminations. Nature 534, 640–646 (2016).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Chiang, J. C. H. et al. Role of seasonal transitions and westerly jets in East Asian paleoclimate. Quat. Sci. Rev. 108, 111–129 (2015).ADS 
    Article 

    Google Scholar 
    Youn, J. H., Seong, Y. B., Choi, J. H., Abdrakhmatov, K. & Ormukov, C. Loess deposits in the northern Kyrgyz Tien Shan: Implications for the paleoclimate reconstruction during the Late Quaternary. CATENA 117, 81–93 (2014).Article 

    Google Scholar 
    Li, Y. et al. Eolian dust dispersal patterns since the last glacial period in eastern Central Asia: Insights from a loess-paleosol sequence in the Ili Basin. Clim. Past 14, 271–286 (2018).Article 

    Google Scholar 
    Frechen, M., Oches, E. A. & Kohfeld, K. E. Loess in Europe—Mass accumulation rates during the Last Glacial Period. Quat. Sci. Rev. 22, 1835–1857 (2003).ADS 
    Article 

    Google Scholar 
    Antoine, P. et al. High resolution record of the last climatic cycle in the southern carpathian basin at Surduk (vojvodina, Serbia). Quat. Int. 198, 19–36 (2009).MathSciNet 
    Article 

    Google Scholar 
    Antoine, P. et al. Upper Pleistocene loess-palaeosols records from Northern France in the European context: Environmental background and dating of the Middle Palaeolithic. Quat. Int. 411, 4–24 (2016).Article 

    Google Scholar 
    Kang, S., Roberts, H. M., Wang, X., An, Z. S. & Wang, M. Mass accumulation rate changes in Chinese loess during MIS 2, and asynchrony with records from Greenland ice cores and North Pacific Ocean sediments during the last glacial maximum. Aeol. Res. 19, 251–258 (2015).Article 

    Google Scholar 
    Fitzsimmons, K. E. et al. Loess accumulation in the Tian Shan piedmont: Implications for palaeoenvironmental change in arid Central Asia. Quat. Int. 469, 30–43 (2018).Article 

    Google Scholar 
    Li, Y., Song, Y., Qiang, M., Miao, Y. & Zeng, M. Atmospheric dust variations in the Ili Basin, northwest China, during the last glacial period as revealed by a high mountain loess-paleosol sequence. J. Geophys. Res. Atmos. 124, 8449–8466 (2019).ADS 
    Article 

    Google Scholar 
    Pinto, J. G. & Ludwig, P. Extratropical cyclones over the North Atlantic and western Europe during the last glacial maximum and implications for proxy interpretation. Clim. Past 16, 611–626 (2020).Article 

    Google Scholar 
    Cheng, L. et al. Drivers for asynchronous patterns of dust accumulation in central and eastern Asia and in Greenland during the Last Glacial Maximum. Geophys. Res. Lett. 48, e2020GL01194 (2021).
    Google Scholar 
    Fenn, K. et al. A tale of two signals: Global and local influences on the Late Pleistocene loess sequences in Bulgarian Lower Danube. Quat. Sci. Rev. 274, 107264 (2021).Article 

    Google Scholar 
    Song, Y. et al. Spatio-temporal distribution of Quaternary loess across Central Asia. Palaeogeogr. Palaeoclim. Palaeoecol. 567, 110279 (2021).ADS 
    Article 

    Google Scholar 
    Hughes, P. D. & Gibbard, P. L. A stratigraphical basis for the Last Glacial Maximum (LGM). Quat. Int. 383, 174–185 (2015).Article 

    Google Scholar 
    Baykal, Y. et al. Detrital zircon U-Pb age analysis of last glacial loess sources and proglacial sediment dynamics in the Northern European Plain. Quat. Sci. Rev. 274, 107265 (2021).Article 

    Google Scholar 
    Pötter, S. et al. Disentangling sedimentary pathways for the Pleniglacial Lower Danube loess based on geochemical signatures. Front. Earth Sci. 9, 150 (2021).ADS 
    Article 

    Google Scholar 
    Prud’homme, C. et al. δ13C signal of earthworm calcite granules: A new proxy for palaeoprecipitation reconstructions during the Last Glacial in western Europe. Quat. Sci. Rev. 179, 158–166 (2018).ADS 
    Article 

    Google Scholar 
    Obreht, I. et al. A critical reevaluation of palaeoclimate proxy records from loess in the Carpathian Basin. Earth-Sci. Rev. 190, 498–520 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    Joannin, S. et al. Vegetation, fire and climate history of the Lesser Caucasus: A new Holocene record from Zarishat fen (Armenia). J. Quat. Sci. 29, 70–82 (2014).Article 

    Google Scholar 
    Brittingham, A. et al. Influence of the north atlantic oscillation on δD and δ18O in meteoric water in the Armenian highland. J. Hydrol. 575, 513–522 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    Bohn, U., Zazanashvili, N. & Nakhutsrishvili, G. The map of the natural vegetation of Europe and its application in the caucasus ecoregion. Bull. Georgian Natl. Acad. Sci. 175, 112–121 (2007).
    Google Scholar 
    Trigui, Y. et al. First calibration and application of leaf wax n-alkane biomarkers in Loess-Paleosol sequences and modern plants and soils in Armenia. Geosciences 9, 263 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    Richter, C. et al. New insights into southern Caucasian glacial-interglacial climate conditions inferred from Quaternary Gastropod Fauna. J. Quat. Sci. 35, 634–649 (2020).Article 

    Google Scholar 
    Kharzyan, E. Geological Map of Republic of Armenia (Ministry of Nature Protection of Republic of Armenia, 2005).
    Google Scholar 
    Sosson, M. et al. Subductions, obduction and collision in the Lesser Caucasus (Armenia, Azerbaijan, Georgia), new insights. Geol. Soc. Spec. Publ. 340, 329–352 (2010).ADS 
    Article 

    Google Scholar 
    Lomax, J. et al. Testing post-IR-IRSL dating on Armenian loess palaeosol sections against independent age control. Quat. Geochron. 69, 101265 (2021).Article 

    Google Scholar 
    Újvári, G., Kovács, J., Varga, G., Raucsik, B. & Markovic, S. B. Dust flux estimates for the Last Glacial Period in East Central Europe based on terrestrial records of loess deposits: A review. Quat. Sci. Rev. 29, 3157–3166 (2010).ADS 
    Article 

    Google Scholar 
    Rudnick, R. L. & Gao, S. Composition of the continental crust. In The Crust (ed. Rudnick, R. L.) 1–64 (Elsevier-Pergamon, 2003).
    Google Scholar 
    Újvári, G., Varga, A. & Balogh-Brunstad, Z. Origin, weathering, and geochemical composition of loess in southwestern Hungary. Quat. Res. 69, 421–437 (2008).Article 
    CAS 

    Google Scholar 
    Galoyan, G. et al. Geology, geochemistry and 40Ar/39Ar dating of Sevan ophiolites (Lesser Caucasus, Armenia): Evidence for Jurassic Back-arc opening and hot spot event between the South Armenian Block and Eurasia. J. Asian Earth Sci. 34, 135–153 (2009).ADS 
    Article 

    Google Scholar 
    Hässig, M. et al. New structural and petrological data on the Amasia ophiolites (NW Sevan-Akera suture zone, Lesser Caucasus): Insights for a large-scale obduction in Armenia and NE Turkey. Tectonophysics 588, 135–153 (2013).ADS 
    Article 
    CAS 

    Google Scholar 
    Sahakyan, L. et al. Geochemistry of the Eocene magmatic rocks from the Lesser Caucasus area (Armenia): Evidence of a subduction geodynamic environment. in Tectonic Evolution of the Eastern Black Sea and Caucasus (eds. Sosson, M., Stephenson, R. A., Adamia, S. A.). Geological Society Special Publication. Vol. 428. (2016).Obreht, I. et al. Tracing the influence of Mediterranean climate on Southeastern Europe during the past 350,000 years. Sci. Rep. 6, 36334 (2016).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Profe, J., Wacha, L., Frechen, M., Ohlendorf, C. & Zolitschka, B. XRF scanning of discrete samples—A chemostratigraphic approach exemplified for loess-paleosol sequences from the Island of Susak, Croatia. Quat. Int. 494, 34–51 (2018).Article 

    Google Scholar 
    Profe, J., Zolitschka, B., Schirmer, W., Frechen, M. & Ohlendorf, C. Geochemistry unravels MIS3/2 paleoenvironmental dynamics at the loess-paleosol sequence Schwalbenberg II, Germany. Palaeogeogr. Palaeoclim. Palaeoecol. 459, 537–551 (2016).ADS 
    Article 

    Google Scholar 
    Zeeden, C. et al. Three climatic cycles recorded in a loess-palaeosol sequence at Semlac (Romania)—Implications for dust accumulation in south-eastern Europe. Quat. Sci. Rev. 154, 130–142 (2016).ADS 
    Article 

    Google Scholar 
    Song, Y. et al. Magnetic stratigraphy of the Danube loess: A composite Titel-Stari Slankamen loess section over the last one million years in Vojvodina, Serbia. J. Asian Earth Sci. 155, 68–80 (2018).ADS 
    Article 

    Google Scholar 
    Rouzaut, S. & Orgeira, M. J. Influence of volcanic glass on the magnetic signal of different paleosols in Córdoba, Argentina. Stud. Geophys. Geod. 61, 361–384 (2017).ADS 
    Article 

    Google Scholar 
    Campodonico, V. A., Rouzaut, S. & Pasquini, A. I. Geochemistry of a Late Quaternary loess-paleosol sequence in central Argentina: Implications for weathering, sedimentary recycling and provenance. Geoderma 351, 235–249 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    Wolf, D. et al. Loess in Armenia—Stratigraphic findings and palaeoenvironmental indications. Proc. Geol. Assoc. 127, 29–39 (2016).Article 

    Google Scholar 
    Buggle, B. et al. Iron mineralogical proxies and Quaternary climate change in SE-European Loess–Paleosol sequences. CATENA 117, 4–22 (2014).CAS 
    Article 

    Google Scholar 
    Bradák, B. et al. Magnetic susceptibility in the European Loess Belt: New and existing models of magnetic enhancement in Loess. Palaeogeogr. Palaeoclim. Palaeoecol. 569, 110329 (2021).ADS 
    Article 

    Google Scholar 
    Laag, C. et al. A detailed paleoclimate proxy record for the Middle Danube Basin over the Last 430 kyr: A rock magnetic and colorimetric study of the Zemun loess-paleosol sequence. Front. Earth Sci. 9, 600086 (2021).ADS 
    Article 

    Google Scholar 
    Baumgart, P., Hambach, U., Meszner, S. & Faust, D. An environmental magnetic fingerprint of periglacial loess: Records of Late Pleistocene loess–palaeosol sequences from eastern Germany. Quat. Int. 296, 82–93 (2013).Article 

    Google Scholar 
    Boers, N., Ghil, M. & Rousseau, D.-D. Ocean circulation, ice shelf, and sea ice interactions explain Dansgaard-Oeschger cycles. PNAS 115, E11005–E11014 (2018).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Menviel, L. C., Skinner, L. C., Tarasov, L. & Tzedakis, P. C. An ice–climate oscillatory framework for Dansgaard-Oeschger cycles. Nat. Rev. Earth Environ. 1, 677–693 (2020).ADS 
    Article 

    Google Scholar 
    Rasmussen, S. O. et al. A stratigraphic framework for abrupt climatic changes during the Last Glacial period based on three synchronized Greenland ice-core records: refining and extending the INTIMATE event stratigraphy. Quat. Sci. Rev. 106, 14–28 (2014).ADS 
    Article 

    Google Scholar 
    Martrat, B. et al. Four climate cycles ofrecurring deep and surface water destabilizations on the Iberian margin. Science 317, 502–507 (2007).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Broecker, W. S. Massive iceberg discharges as triggers for global climate change. Nature 372, 421–424 (1994).ADS 
    CAS 
    Article 

    Google Scholar 
    Jin, L., Chen, F., Ganopolski, A. & Claussen, M. Response of East Asian climate to Dansgaard/Oeschger and Heinrich events in a coupled model of intermediate complexity. J. Geophys. Res. 112, D06117 (2007).ADS 

    Google Scholar 
    Sun, Y., Wang, X., Liu, Q. & Clemens, S. C. Impacts of post-depositional processes on rapid monsoon signals recorded by the last glacial loess deposits of northern China. Earth Planet. Sci. Lett. 289, 171–179 (2010).ADS 
    CAS 
    Article 

    Google Scholar 
    Yang, S. & Ding, Z. A 249 kyr stack of eight loess grain size records from northern China documenting millennial-scale climate variability. Geochem. Geophys. Geosyst. 15, 798–814 (2014).ADS 
    Article 

    Google Scholar 
    Obreht, I. et al. Shift of large-scale atmospheric systems over Europe during late MIS 3 and implications for modern human dispersal. Sci. Rep. 7, 5848 (2017).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Antoine, P. et al. Evidence of rapid and cyclic eolian deposition during the Last Glacial in European loess series (Loess events): The high-resolution records from Nussloch (Germany). Quat. Sci. Rev. 28, 2955–2973 (2009).ADS 
    Article 

    Google Scholar 
    Rousseau, D. D. et al. North Atlantic abrupt climatic events of the last glacial period recorded in Ukrainian loess deposits. Clim. Past 7, 221–234 (2011).Article 

    Google Scholar 
    Machalett, B. et al. Aeolian dust dynamics in Central Asia during the Pleistocene: driven by the long-term migration, seasonality and permanency of the Asiatic polar front. Geophys. Geochem. Geosyst. 9, Q08Q09 (2008).Article 
    CAS 

    Google Scholar 
    Berger, A. & Loutre, M. F. Insolation values for the climate of the last 10 million years. Quat. Sci. Rev. 10, 297–317 (1991).ADS 
    Article 

    Google Scholar 
    Kutzbach, J., Chen, G., Cheng, H., Edwards, R. & Liu, Z. Potential role of winter rainfall in explaining increased moisture in the Mediterranean and Middle East during periods of maximum orbitally-forced insolation seasonality. Clim. Dynam. 42, 1079–1095 (2014).ADS 
    Article 

    Google Scholar 
    Marković, S. B. et al. Danube loess stratigraphy—Towards a pan-European loess stratigraphic model. Earth Sci. Rev. 148, 228–258 (2015).ADS 
    Article 

    Google Scholar 
    Li, G. et al. Paleoenvironmental changes recorded in a luminescence dated loess/paleosol sequence from the Tianshan Mountains, arid central Asia, since the penultimate glaciation. Earth Planet. Sci. Lett. 448, 1–12 (2016).ADS 
    CAS 
    Article 

    Google Scholar 
    Lomax, J. et al. A luminescence-based chronology for the Harletz Loess sequence, Bulgaria. Boreas 48, 179–194 (2019).Article 

    Google Scholar 
    Kehl, M. et al. Pleistocene dynamics of dust accumulation and soil formation in the southern Caspian Lowlands—New insights from the loess-paleosol sequence at Neka-Abelou, northern Iran. Quat. Sci. Rev. 253, 106774 (2021).Article 

    Google Scholar 
    Ganopolski, A., Calov, R. & Claussen, M. Simulation of the last glacial cycle with a coupled climate ice-sheet model of intermediate complexity. Clim. Past 6, 229–244 (2010).Article 

    Google Scholar 
    Malinsky-Buller, A. et al. Evidence for Middle Palaeolithic occupation and landscape change in central Armenia at the open-air site of Alapars-1. Quat. Res. 99, 223–247 (2021).Article 

    Google Scholar 
    Rao, Z. et al. High-resolution summer precipitation variations in the western Chinese Loess Plateau during the last glacial. Sci. Rep. 3, 2785 (2013).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Stevens, T., Marković, S. B., Zech, M., Hambach, U. & Sümegi, P. Dust deposition and climate in the Carpathian Basin over an independently dated last glacial-interglacial cycle. Quat. Sci. Rev. 30, 662–681 (2011).ADS 
    Article 

    Google Scholar 
    Torfstein, A., Goldstein, S. L., Stein, M. & Enzel, Y. Impacts of abrupt climate changes in the Levant from Last Glacial Dead Sea levels. Quat. Sci. Rev. 69, 1–7 (2013).ADS 
    Article 

    Google Scholar 
    Pickarski, N., Kwiecien, O., Langgut, D. & Litt, T. Abrupt climate and vegetation variability of eastern Anatolia during the last glacial. Clim. Past 11, 1491–1505 (2015).Article 

    Google Scholar 
    Wegwerth, A. et al. Northern hemisphere climate control on the environmental dynamics in the glacial Black Sea “Lake”. Quat. Sci. Rev. 135, 41–53 (2016).ADS 
    Article 

    Google Scholar 
    Ollivier, V., Fontugne, M. & Lyonnet, B. Geomorphic response and 14C chronology of base-level changes induced by Late Quaternary Caspian Sea mobility (middle Kura Valley, Azerbaijan). Geomorphology 230, 109–124 (2015).ADS 
    Article 

    Google Scholar 
    Egeland, C. P. et al. Bagratashen 1, a stratified open-air Middle Paleolithic site in the Debed river valley of northeastern Armenia: A preliminary report. Archaeol. Res. Asia 8, 1–20 (2016).Article 

    Google Scholar 
    von Suchodoletz, H., Gärtner, A., Zielhofer, C. & Faust, D. Eemian and post-Eemian fluvial dynamics in the Lesser Caucasus. Quat. Sci. Rev. 191, 189–203 (2018).ADS 
    Article 

    Google Scholar 
    Langbein, W. B. & Schumm, S. A. Yield of sediment in relation to mean annual precipitation. Trans. Am. Geophys. Union 39, 1076–1084 (1958).ADS 
    Article 

    Google Scholar 
    Wolman, M. G. & Miller, J. P. Magnitude and frequency of forces in geomorphic processes. J. Geol. 68, 54–74 (1960).ADS 
    Article 

    Google Scholar 
    Svirčev, Z. et al. Importance of biological loess crusts for loess formation in semi-arid environments. Quat. Int. 296, 206–215 (2013).Article 

    Google Scholar 
    Reber, R. et al. Glacier advances in northeastern Turkey before and during the global Last Glacial Maximum. Quat. Sci. Rev. 101, 177–192 (2014).ADS 
    Article 

    Google Scholar 
    Ammann, C., Jenny, B., Kammer, K. & Messerli, B. Late Quaternary glacier response to humidity changes in the arid Andes of Chile (18–29 °S). Palaeogeogr. Palaeoclim. Palaeoecol. 172, 313–326 (2001).ADS 
    Article 

    Google Scholar 
    Domínguez-Villar, D. et al. Early maximum extent of paleoglaciers from Mediterranean mountains during the last glaciation. Sci. Rep. 3, 2034 (2013).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Spötl, C. et al. Increased autumn and winter precipitation during the Last Glacial Maximum in the European Alps. Nat. Commun. 12, 1839 (2021).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Shumilovskikh, L. S. et al. Orbital and millennial-scale environmental changes between 64 and 20 ka BP recorded in Black Sea sediments. Clim. Past 10, 939–954 (2014).Article 

    Google Scholar 
    Wegwerth, A. et al. Black Sea temperature response to glacial millennial-scale climate variability. Geophys. Res. Lett. 42, 8147–8154 (2015).ADS 
    Article 

    Google Scholar 
    Sarıkaya, M. A., Zreda, M., Çiner, A. & Zweck, C. Cold and wet Last Glacial Maximum on Mount Sandıras, SW Turkey, inferred from cosmogenic dating and glacier modeling. Quat. Sci. Rev. 27, 769–780 (2008).ADS 
    Article 

    Google Scholar 
    Lézine, A.-M. et al. Lake Ohrid, Albania, provides an exceptional multi-proxy record of environmental changes during the last glacial–interglacial cycle. Palaeogeogr. Palaeoclim. Palaeoecol. 287, 116–127 (2010).ADS 
    Article 

    Google Scholar 
    Tecsa, V. et al. Revisiting the chronostratigraphy of late Pleistocene loess-paleosol sequences in southwestern Ukraine: OSL dating of Kurortne section. Quat. Int. 542, 65–79 (2020).Article 

    Google Scholar 
    Luetscher, M. et al. North Atlantic storm track changes during the Last Glacial Maximum recorded by Alpine speleothems. Nat. Commun. 6, 6344 (2015).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Ludwig, P., Schaffernicht, E. J., Shao, Y. & Pinto, J. G. Regional atmospheric circulation over Europe during the Last Glacial Maximum and its links to precipitation. J. Geophys. Res.-Atmos. 121, 2130–2145 (2016).ADS 
    Article 

    Google Scholar 
    Schaffernicht, E. J., Ludwig, P. & Shao, Y. Linkage between dust cycle and loess of the last glacial maximum in Europe. Atmos. Chem. Phys. 20, 4969–4986 (2020).ADS 
    CAS 
    Article 

    Google Scholar 
    Beghin, P. et al. What drives LGM precipitation over the western Mediterranean? A study focused on the Iberian Peninsula and northern Morocco. Clim. Dyn. 46, 2611–2631 (2016).Article 

    Google Scholar 
    Sümegi, P. et al. Vegetation and land snail-based reconstruction of the palaeocological changes in the forest steppe eco-region of the Carpathian Basin during last glacial warming. Glob. Ecol. Conserv. 33, e01976 (2022).Article 

    Google Scholar 
    Chen, J. et al. Revisiting Late Pleistocene Loess-Paleosol sequences in the Azov Sea Region of Russia: Chronostratigraphy and paleoenvironmental record. Front. Earth Sci. 9, 808157 (2022).Article 

    Google Scholar 
    Xepos, S. Analysis of trace elements in geological materials, soils and sludges. Spectro XRF Rep. 193, 1–5 (2007).
    Google Scholar 
    Buggle, B. et al. Geochemical characterization and origin of Southeastern and Eastern European loesses (Serbia, Romania, Ukraine). Quat. Sci. Rev. 27, 1058–1075 (2008).ADS 
    Article 

    Google Scholar 
    Weltje, G. J. & Tjallingii, R. Calibration of XRF core scanners for quantitative geochemical logging of sediment cores: Theory and application. Earth Planet. Sci. Lett. 274, 423–438 (2008).ADS 
    CAS 
    Article 

    Google Scholar 
    Dearing, J. Environmental Magnetic Susceptibility: Using the Bartington MS2 System (Chi Publishing, 1999).
    Google Scholar 
    Buylaert, J., Murray, A. S., Thomsen, K. J. & Jain, M. Testing the potential of an elevated temperature IRSL signal from K-feldspar. Radiat. Meas. 44, 560–565 (2009).CAS 
    Article 

    Google Scholar 
    Lomax, J. et al. Establishing a luminescence-based chronostratigraphy for the Last Glacial-interglacial cycle of the Loess-Palaeosol sequence Achajur (Armenia). Front. Earth Sci. 9, 755084 (2021).Article 

    Google Scholar 
    Lamothe, M., Auclair, M., Hamzaoui, C. & Huot, S. Towards a prediction of long-term anomalous fading of feldspar IRSL. Radiat. Meas. 37, 493–498 (2003).CAS 
    Article 

    Google Scholar 
    Tudyka, K. et al. Increased dose rate precision in combined α and β counting in the μDose system—A probabilistic approach to data analysis. Radiat. Meas. 134, 106310 (2020).CAS 
    Article 

    Google Scholar 
    Kolb, T. et al. The µDose-system: Determination of environmental dose rates by combined alpha and beta counting—Performance tests and practical experiences. GChron 4, 1–31 (2021).ADS 

    Google Scholar 
    Durcan, J. A., King, G. & Duller, G. DRAC: Dose rate and age calculator for trapped charge dating. Quat. Geochron. 28, 54–61 (2015).Article 

    Google Scholar 
    von Suchodoletz, H. & Faust, D. Late Quaternary fluvial dynamics and landscape evolution at the lower Shulaveris Ghele River (southern Caucasus). Quat. Res. 89, 254–269 (2018).Article 

    Google Scholar 
    von Suchodoletz, H. et al. Late Pleistocene river migrations in response to thrust belt advance and sediment-flux steering e the Kura River (southern Caucasus). Geomorphology 266, 53–65 (2016).ADS 
    Article 

    Google Scholar 
    Ryan, W. B. F. et al. Global multi-resolution topography (GMRT) synthesis data set. Geochem. Geophys. Geosyst. 10, Q03014 (2009).ADS 
    Article 

    Google Scholar 
    Nalivkin, D. V. et al. Geologicheskaya Karta Kavkaza, Mashtav 1:500.000 (Geological Map of the Caucasus, Scale 1:500,000). (Ministry of Geology of the USSR, 1976). More

  • in

    Closing the energetics gap

    Stanier, R. Y. & Van Niel, C. B. Arch. Mikrobiol. 42, 17–35 (1962).CAS 
    Article 

    Google Scholar 
    Schavemaker, P. E. & Muñoz-Gómez, S. A. Nat. Ecol. Evol. https://doi.org/10.1038/s41559-022-01833-9 (2022).Article 

    Google Scholar 
    Lane, N. & Martin, W. F. Nature 467, 929–934 (2010).CAS 
    Article 

    Google Scholar 
    Lynch, M. & Marinov, G. K. PNAS 112, 15690–15695 (2015).CAS 
    Article 

    Google Scholar 
    Cavalier-Smith, T. & Chao, E. E. Protoplasma 257, 621–753 (2020).CAS 
    Article 

    Google Scholar 
    Zachar, I. & Szathmáry, E. Biol. Direct 12, 19 (2017).Article 

    Google Scholar 
    Cavalier-Smith, T. Cold Spring Harb. Perspect. Biol. 6, 1–31 (2014).Article 

    Google Scholar 
    de Duve, C. Nat. Rev. Genet. 8, 395–403 (2007).Article 

    Google Scholar 
    Shiratori, T., Suzuki, S., Kakizawa, Y. & Ishida, K. Nat. Commun. 10, 5529 (2019).Article 

    Google Scholar 
    Martin, W. F., Tielens, A. G. M., Mentel, M., Garg, S. G. & Gould, S. B. Microbiol. Mol. Biol. Rev. 81, 8–17 (2017).Article 

    Google Scholar 
    Jékely, G. Biol. Direct 2, 3 (2007).Article 

    Google Scholar 
    Stanier, R. Y. Some aspects of the biology of cells and their possible evolutionary significance. Organization and Control in Prokaryotic and Eukaryotic Cells. In Proc. 20th Symposium of the Society for General Microbiology (eds Charles, H. P. & Knight, B. C. J. G) 20, 1–38 (Cambridge University Press, Cambridge, 1970).Zachar, I., Szilágyi, A., Számadó, S. & Szathmáry, E. PNAS USA 115, E1504–E1510 (2018).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Burns, J. A., Pittis, A. A. & Kim, E. Nat. Ecol. Evol. 2, 697–704 (2018).Article 

    Google Scholar 
    Bremer, N., Tria, F. D. K., Skejo, J., Garg, S. G. & Martin, W. F. Genome Biol. Evol. 14, evac079 (2022).Article 

    Google Scholar 
    Imachi, H. et al. Nature 577, 519–525 (2020).CAS 
    Article 

    Google Scholar 
    Zachar, I. & Boza, G. Cell. Mol. Life Sci. 77, 3503–3523 (2020).CAS 
    Article 

    Google Scholar 
    Devos, D. P. Mol. Biol. Evol. 38, 3531–3542 (2021).CAS 
    Article 

    Google Scholar  More

  • in

    An experimental study: effects of boulder placement on hydraulic metrics of instream habitat complexity

    Effects of grid spacing on habitat hydraulic complexity metricsThe sensitivity of the habitat hydraulic complexity metrics to Δs was examined by calculating the metrics for Δs = 0.06, 0.12, 0.18, and 0.24 m (for M4, Δs = Δx = Δy). Figure 3 shows the variation of the metrics with grid spacing for scenarios with boulders. A preliminary assessment of no-boulder scenarios (S1-L and S1-H) showed that all the metrics decreased by increasing the grid spacing. However, because the metrics are mostly used in complex rather than non-obstructed and 1-D flows, the plots only include scenarios with boulder placement to highlight the effects of grid spacing on the metrics in complex flows. All the metrics generally decreased as Δs increased. At the low flow rate, by changing the Δs from the smallest to largest, i.e., 0.06 m to 0.024, the mean decreases in the M1, M2, and M4 metrics (averaged over all the scenarios with boulders) were 45.1, 9.9, and 74.7%, respectively. At the high flow rate, these reductions were 34.8, 14.7, and 82.5% for M1, M2, and M4, respectively. Table 2 shows the p-values associated with the changes in the metrics due to increasing Δs from 0.06 to 0.24 m for all scenarios. The table indicates that changes in M1 and M4 were statistically significant while for M2 they were not (p-values  > 0.05 for all scenarios except for S2-H). This result indicated the considerable influence of grid spacing on M1 and M4 metrics in the reaches with boulder placement. Additionally, the differences in the reported average reductions due to changing the flow rate were less than 10%, indicating an insubstantial effect of flow rate on the habitat hydraulic complexity metrics’ sensitivity to the grid spacing. The significant sensitivity of the metrics M1 and M4 to the grid spacing in this study is contrary to the findings of a previous study in which an insignificant correlation was found between the habitat hydraulic complexity metrics and Δs29. This difference can be attributed to different topographic features in the studied reaches. In the previous findings, measurements were mainly taken around the bends and reaches with no significant obstruction29, in which a more uniform flow with smaller velocity gradients is expected. However, in this study, the systematic boulder placement generated more complex flow patterns with noticeable velocity gradients. Therefore, due to the variations of flow velocities in the zone studied, substantially different values for the metrics are anticipated by computing the metrics over different spatial scales.Figure 3Variation of the habitat hydraulic complexity metrics with grid spacing (Δs) for scenarios with boulder placement. (a) kinetic energy gradient metric, M1, (b) normalized kinetic energy gradient metric, M2, (c) modified recirculation metric M4.Full size imageTable 2 p-values associated with changing the grid spacing from 0.06 to 0.24 m.Full size tableStatistical distribution of habitat hydraulic complexity metricsTable 3 lists the mean, minimum, maximum, and standard deviations of the habitat hydraulic complexity metrics (Δs = 0.06 m) for all the scenarios. To complement the results from Table 3 and assess whether the influences of solely changing the boulder concentration or flow rate on the metrics were statistically significant, Table 4 shows p-values associated with changing flow rate from low to high for a given boulder concentration, and Table 5 shows p-values associated with gradually increasing the boulder concentration for a given flow rate.Table 3 The statistical parameters of the habitat hydraulic complexity metrics in the detailed measurement zone.Full size tableTable 4 p-values from a t-test associated with changes in flow rate for a given boulder concentration.Full size tableTable 5 p-values from a t-test associated with changes in boulder concertation for a given flow rate.Full size tableFor metric M1, the mean M1 values for scenarios incorporating boulders showed the same order of magnitude as values from previous studies for reaches with single and multiple boulders27 but they were about one order of magnitude larger than calculated values in the confluence of two rivers11. Using a larger grid spacing in the study in the confluence of two rivers11 can be the reason for this difference. For a scenario at the higher flow rate, the mean M1 was on average (averaged for all the scenarios) 36% greater than its counterpart at the lower flow rate and this change in M1 values was statistically significant with p  More

  • in

    Clay and climatic variability explain the global potential distribution of Juniperus phoenicea toward restoration planning

    Pecl, G. T. et al. Biodiversity redistribution under climate change: Impacts on ecosystems and human well-being. Science (80-) https://doi.org/10.1126/science.aai9214 (2017).Article 

    Google Scholar 
    Walther, G. R. et al. Ecological responses to recent climate change. Nature 416, 389–395 (2002).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Thuiller, W. et al. Consequences of climate change on the tree of life in Europe. Nature 470, 531–534 (2011).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Zimmermann, N. E., Edwards, T. C. Jr., Graham, C. H., Pearman, P. B. & Svenning, J. New trends in species distribution modelling. Ecography (Cop.) 33, 985–989 (2010).Article 

    Google Scholar 
    Norberg, A. et al. A comprehensive evaluation of predictive performance of 33 species distribution models at species and community levels. Ecol. Monogr. 89, e01370 (2019).Article 

    Google Scholar 
    Smeraldo, S. et al. Generalists yet different: Distributional responses to climate change may vary in opportunistic bat species sharing similar ecological traits. Mamm. Rev. 51, 571–584 (2021).Article 

    Google Scholar 
    Sohlström, E. H. et al. Future climate and land-use intensification modify arthropod community structure. Agric. Ecosyst. Environ. 327, 107830 (2022).Article 
    CAS 

    Google Scholar 
    Araújo, M. B. & New, M. Ensemble forecasting of species distributions. Trends Ecol. Evol. 22, 42–47 (2007).PubMed 
    Article 

    Google Scholar 
    Stohlgren, T. J. et al. Ensemble habitat mapping of invasive plant species. Risk Anal. Int. J. 30, 224–235 (2010).Article 

    Google Scholar 
    Meller, L. et al. Ensemble distribution models in conservation prioritization: from consensus predictions to consensus reserve networks. Divers. Distrib. 20, 309–321 (2014).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Dubuis, A. et al. Improving the prediction of plant species distribution and community composition by adding edaphic to topo-climatic variables. J. Veg. Sci. 24, 593–606 (2013).Article 

    Google Scholar 
    Walthert, L. & Meier, E. S. Tree species distribution in temperate forests is more influenced by soil than by climate. Ecol. Evol. 7, 9473–9484 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Figueiredo, F. O. G. et al. Beyond climate control on species range: The importance of soil data to predict distribution of Amazonian plant species. J. Biogeogr. 45, 190–200 (2018).Article 

    Google Scholar 
    Arar, A., Nouidjem, Y., Bounar, R., Tabet, S. & Kouba, Y. Potential future changes of the geographic range size of Juniperus phoenicea in Algeria based on present and future climate change projections. Contemp. Probl. Ecol. 13, 429–441 (2020).Article 

    Google Scholar 
    Coudun, C., Gégout, J., Piedallu, C. & Rameau, J. Soil nutritional factors improve models of plant species distribution: An illustration with Acer campestre (L.) in France. J. Biogeogr. 33, 1750–1763 (2006).Article 

    Google Scholar 
    Buri, A. et al. What are the most crucial soil variables for predicting the distribution of mountain plant species? A comprehensive study in the Swiss Alps. J. Biogeogr. 47, 1143–1153 (2020).Article 

    Google Scholar 
    Buri, A. et al. Soil factors improve predictions of plant species distribution in a mountain environment. Prog. Phys. Geogr. 41, 703–722 (2017).Article 

    Google Scholar 
    Mod, H. K., Scherrer, D., Luoto, M. & Guisan, A. What we use is not what we know: environmental predictors in plant distribution models. J. Veg. Sci. 27, 1308–1322 (2016).Article 

    Google Scholar 
    Scherrer, D. & Guisan, A. Ecological indicator values reveal missing predictors of species distributions. Sci. Rep. 9, 1–8 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    Boulos, L. Flora of Egypt, Vol. 1. vol. 1 (Al Hadara Publishing, 1999).Farjon, A. & Filer, D. An atlas of the world’s conifers: An analysis of their distribution, biogeography, diversity and conservation status. (Brill, 2013).Allen, DJ. Juniperus phoenicea. The IUCN red list of threatened species 2017: e.T16348983A99965052. https://doi.org/10.2305/IUCN.UK.2017-2.RLTS. T16348983A99965052.en. Downloaded on 19 May 2020El-Bana, M., Shaltout, K., Khalafallah, A. & Mosallam, H. Ecological status of the Mediterranean Juniperus phoenicea L. relicts in the desert mountains of North Sinai Egypt. Flora-Morphol. Distrib. Funct. Ecol. Plants 205, 171–178 (2010).Article 

    Google Scholar 
    Moustafa, A. et al. Ecological Prominence of Juniperus phoenicea L. Growing in Gebel Halal, North Sinai Egypt. Catrina Int. J. Environ. Sci. 15, 11–23 (2016).
    Google Scholar 
    Farahat, E. A. Age structure and static life tables of the endangered Juniperus phoenicea L. in North Sinai Mountains, Egypt. J. Mt. Sci. 17, 2170–2178 (2020).Article 

    Google Scholar 
    El-Wahab, A. Condition assessment of plant diversity of Gebel Maghara, North Sinai, Egypt. Catrina Int. J. Environ. Sci. 3, 21–40 (2008).
    Google Scholar 
    Youssef, A. M., Morsy, A. A., Mosallam, H. A. & Hashim, A. M. Vegetation and soil relationships in some wadis from the North-Central part of Sinai Peninsula Egypt. Minia Sci. Bull. 25, 1–28 (2014).
    Google Scholar 
    Fisher, M. Decline in the juniper woodlands of Raydah Reserve in southwestern Saudi Arabia: A response to climate changes?. Glob. Ecol. Biogeogr. Lett. 6, 379–386 (1997).Article 

    Google Scholar 
    Salvà-Catarineu, M. et al. Past, present, and future geographic range of the relict Mediterranean and Macaronesian Juniperus phoenicea complex. Ecol. Evol. 11, 5075–5095 (2021).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Quevedo, L., Rodrigo, A. & Espelta, J. M. Post-fire resprouting ability of 15 non-dominant shrub and tree species in Mediterranean areas of NE Spain. Ann. For. Sci. 64(8), 883–890 (2007).Article 

    Google Scholar 
    Trabucco, A. & Zomer, R. J. Global aridity index (global-aridity) and global potential evapo-transpiration (global-PET) geospatial database. CGIAR Consort. Spat. Inf. 89, 1–2 (2009).
    Google Scholar 
    Hengl, T. et al. SoilGrids1km—Global soil information based on automated mapping. PLoS One 9, e105992 (2014).ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Kennedy, C. M., Oakleaf, J. R., Theobald, D. M., Baruch-Mordo, S. & Kiesecker, J. Documentation for the global human modification of terrestrial systems (2020).Naimi, B. & Araújo, M. B. sdm: a reproducible and extensible R platform for species distribution modelling. Ecography (Cop.) 39, 368–375 (2016).Article 

    Google Scholar 
    Naimi, B. usdm: Uncertainty analysis for species distribution models. R Packag. Version 1, 1–12 (2015).
    Google Scholar 
    Guisan, A., Thuiller, W. & Zimmermann, N. E. In Habitat Suitability and Distribution Models: With Applications in R. (Cambridge University Press, 2017).Dakhil, M. A. et al. Global invasion risk assessment of Prosopis juliflora at biome level : Does soil matter?. Biology 10, 203 (2021).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Iturbide, M., Bedia, J. & Gutiérrez, J. M. Background sampling and transferability of species distribution model ensembles under climate change. Glob. Planet. Change 166, 19–29 (2018).ADS 
    Article 

    Google Scholar 
    Barbet-Massin, M., Jiguet, F., Albert, C. H. & Thuiller, W. Selecting pseudo-absences for species distribution models: How, where and how many?. Methods Ecol. Evol. 3, 327–338 (2012).Article 

    Google Scholar 
    Zhang, Z., Mammola, S., Xian, W. & Zhang, H. Modelling the potential impacts of climate change on the distribution of ichthyoplankton in the Yangtze Estuary, China. Divers. Distrib. 26, 126–137 (2020).Article 

    Google Scholar 
    Thuiller, W., Guéguen, M., Renaud, J., Karger, D. N. & Zimmermann, N. E. Uncertainty in ensembles of global biodiversity scenarios. Nat. Commun. 10, 1–9 (2019).CAS 
    Article 

    Google Scholar 
    Breiner, F. T., Nobis, M. P., Bergamini, A. & Guisan, A. Optimizing ensembles of small models for predicting the distribution of species with few occurrences. Methods Ecol. Evol. 9, 802–808 (2018).Article 

    Google Scholar 
    Liu, C., Newell, G. & White, M. On the selection of thresholds for predicting species occurrence with presence-only data. Ecol. Evol. 6, 337–348 (2016).PubMed 
    Article 

    Google Scholar 
    Haider, S. M., Benscoter, A. M., Pearlstine, L., D’Acunto, L. E. & Romañach, S. S. Landscape-scale drivers of endangered Cape Sable Seaside Sparrow (Ammospiza maritima mirabilis) presence using an ensemble modeling approach. Ecol. Modell. 461, 109774 (2021).Article 

    Google Scholar 
    Allouche, O., Tsoar, A. & Kadmon, R. Assessing the accuracy of species distribution models: Prevalence, kappa and the true skill statistic (TSS). J. Appl. Ecol. 43, 1223–1232 (2006).Article 

    Google Scholar 
    Franklin, J. Mapping Species Distributions: Spatial Inference and Prediction (Cambridge University Press, 2010).Book 

    Google Scholar 
    Kabiel, H. F., Hegazy, A. K., Lovett-Doust, L., Al-Rowaily, S. L. & Al Borki, A. E. N. S. Ecological assessment of populations of Juniperus phoenicea L. in the Al-Akhdar mountainous landscape of Libya. Arid L. Res. Manag. 30, 269–289 (2016).Article 

    Google Scholar 
    Camarero, J. J. et al. Dieback and mortality of junipers caused by drought: Dissimilar growth and wood isotope patterns preceding shrub death. Agric. For. Meteorol. 291, 108078 (2020).ADS 
    Article 

    Google Scholar 
    Sánchez-Salguero, R. & Camarero, J. J. Greater sensitivity to hotter droughts underlies juniper dieback and mortality in Mediterranean shrublands. Sci. Total Environ. 721, 137599 (2020).ADS 
    PubMed 
    Article 
    CAS 

    Google Scholar 
    Cramer, W. et al. Climate change and interconnected risks to sustainable development in the Mediterranean. Nat. Clim. Chang. 8, 972–980 (2018).ADS 
    Article 

    Google Scholar 
    Forzieri, G. et al. Ensemble projections of future streamflow droughts in Europe. Hydrol. Earth Syst. Sci. 18, 85–108 (2014).ADS 
    Article 

    Google Scholar 
    González-Hidalgo, J. C. et al. High-resolution spatio-temporal analyses of drought episodes in the western Mediterranean basin (Spanish mainland, Iberian Peninsula). Acta Geophys. 66, 381–392 (2018).ADS 
    Article 

    Google Scholar 
    Stockhecke, M. et al. Millennial to orbital-scale variations of drought intensity in the Eastern Mediterranean. Quat. Sci. Rev. 133, 77–95 (2016).ADS 
    Article 

    Google Scholar 
    Navarro Cerrillo, R. M. et al. Can habitat prediction models contribute to the restoration and conservation of the threatened tree Abies pinsapo Boiss. in Southern Spain?. New For. 52, 89–112 (2021).Article 

    Google Scholar  More

  • in

    Development of microsatellites markers for the deep coral Madracis myriaster (Pocilloporidae: Anthozoa)

    Brooke, S. & Young, C. M. In situ measurement of survival and growth of Lophelia pertusa in the northern Gulf of Mexico. Mar. Ecol. Prog. Ser. 397, 153–161 (2009).ADS 

    Google Scholar 
    Reyes, J., Santodomingo, N. & Florez, P. Corales Escleractinios de Colombia. (Invemar Serie de Publicaciones Especiales, 2010).Alonso, D. et al. Behind the scenes for the designation of the Corales de Profundidad national natural park of Colombia. Front. Mar. Sci. 8, 1147 (2021).
    Google Scholar 
    Hughes, J. A., Menot, L. & Levin, L. Habitat classification and mapping on deep continental margins. Research and Consultancy Report, No 54. COMARGE Workshop (2008).Rogers, A. The biology, ecology and vulnerability of deep-water coral reefs. International Union for Conservation of Nature and Natural Resources (2004).Maier, C., Hegeman, J., Weinbauer, M. G. & Burg, D. Calcification of the cold-water coral Lophelia pertusa under ambient and reduced pH. Biogeosciences 1, 1671–1680 (2009).ADS 

    Google Scholar 
    DeLeo, D. M., Glazier, A., Herrera, S., Barkman, A. & Cordes, E. E. Transcriptomic responses of deep-sea corals experimentally exposed to crude oil and dispersant. Front. Mar. Sci. 8, 1–17 (2021).
    Google Scholar 
    Buddemeier, R., Kleypas, J. A. & Aronson, R. B. Potential contributions of climate change to stresses on coral reef ecosystems. Coral Reefs Global Clim. Change 15, 17789 (2004).
    Google Scholar 
    Schmidt, C. A. et al. Faster crystallization during coral skeleton formation correlates with resilience to ocean acidification. J. Am. Chem. Soc. 144, 1332–1341 (2022).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bors, E. K. et al. Patterns of deep-sea genetic connectivity in the New Zealand Region: Implications for management of benthic ecosystems. PLoS One 7, 11047 (2012).
    Google Scholar 
    Hernández-Ávila, I. Patterns of deep-water coral diversity in the Caribbean basin and adjacent southern waters: An approach based on records from the R/V Pillsbury Expeditions. PLoS ONE 9, 11 (2014).
    Google Scholar 
    Alonso, D. et al. Corales de Profundidad: descripción de comunidades coralinas y fauna asociada. (Serie de Publicaciones Generales del Invemar, 2015).Frade, P. R. et al. Semi-permeable species boundaries in the coral genus Madracis: the role of introgression in a brooding coral system. Mol. Phylogenet. Evol. 57, 1072–1090 (2010).CAS 
    PubMed 

    Google Scholar 
    Locke, J. M. & Coates, K. A. What are the costs of bad taxonomic practices: and what is Madracis mirabilis? Proc. 11th Int. Coral Reef Symp. 7, 1348–1351 (2008).
    Google Scholar 
    Palumbi, S. R. The Ecology of Marine Protected Areas. in Marine Community Ecology (eds. Bertness, M., Gaines, S. & Hay, M.) 509–530 (Sinauer Press, Inc, 2001).Jones, G. P., Srinivasan, M. & Almany, G. R. Population connecivity and conservation of marine biodiversity. Oceanography 20, 100 (2007).
    Google Scholar 
    Fogarty, M. J. & Botsford, L. W. Population connectivity and spatial management of marine fisheries. Oceanography 20, 112–123 (2007).
    Google Scholar 
    Gillis, L. G. et al. Potential for landscape-scale positive interactions among tropical marine ecosystems. Mar. Ecol. Prog. Ser. 503, 289–303 (2014).ADS 

    Google Scholar 
    Griffiths, S. M. et al. A Galaxy-based bioinformatics pipeline for optimised, streamlined microsatellite development from Illumina next-generation sequencing data. Conserv. Genet. Resour. 8, 481–486 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Botsford, L. W. et al. Connectivity and resilience of coral reef metapopulations in marine protected areas: Matching empirical efforts to predictive needs. Coral Reefs 28, 327–337 (2009).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Palumbi, S. R. Population genetics, demographic connectivity, and the desing of marine reserves. Ecol. Appl. 13, 146–158 (2003).
    Google Scholar 
    Ridgway, T., Riginos, C., Davis, J. & Hoegh-Guldberg, O. Genetic connectivity patterns of Pocillopora verrucosa in southern African Marine Protected Areas. Mar. Ecol. Prog. Ser. 354, 161–168 (2008).ADS 

    Google Scholar 
    Hemond, E. M. & Vollmer, S. V. Genetic diversity and connectivity in the threatened staghorn coral (Acropora cervicornis) in Florida. PLoS One 5, 1140 (2010).
    Google Scholar 
    Goodbody-Gringley, G., Woollacott, R. M. & Giribet, G. Population structure and connectivity in the Atlantic scleractinian coral Montastraea cavernosa (Linnaeus, 1767). Mar. Ecol. 33, 32–48 (2012).ADS 
    CAS 

    Google Scholar 
    Montoya-Maya, P. H., Macdonald, A. H. H. & Schleyer, M. H. Cross-amplification and characterization of microsatellite loci in Acropora austera from the south-western Indian Ocean. Genet. Mol. Res. 13, 1244–1250 (2014).CAS 
    PubMed 

    Google Scholar 
    Le Goff-Vitry, M., Pybus, O. G. & Roger, N. Genetic structure of the deep-sea coral. Mol. Ecol. 13, 537–549 (2004).CAS 
    PubMed 

    Google Scholar 
    Zeng, C., Rowden, A. A., Clark, M. R. & Gardner, J. P. A. Population genetic structure and connectivity of deep-sea stony corals (Order Scleractinia) in the New Zealand region: Implications for the conservation and management of vulnerable marine ecosystems. Evol. Appl. 10, 1040–1054 (2017).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Addamo, A. M., García-Jiménez, R., Taviani, M. & Machordom, A. Development of microsatellite markers in the deep-sea cup coral desmophyllum dianthus by 454 sequencing and cross-species amplifications in scleractinia order. J. Hered. 106, 322–330 (2015).CAS 
    PubMed 

    Google Scholar 
    Morrison, C. L., Springmann, M. J., Shroades, K. M. & Stone, R. P. Development of twelve microsatellite loci in the red tree corals Primnoa resedaeformis and Primnoa pacifica. Conserv. Genet. Resour. 7, 763–765 (2015).
    Google Scholar 
    Baranets, V., Forsman, Z. H. & Karl, S. A. Microsatellite loci for the plate-and-pillar coral, Porities rus. Conserv. Genet. Resour. 3, 519–521 (2011).
    Google Scholar 
    Gang, H. et al. Evaluating the reliability of microsatellite genotyping from low-quality DNA templates with a polynomial distribution model. Chin. Sci. Bull. 56, 2523–2530 (2011).
    Google Scholar 
    Taberlet, P. et al. Reliable genotyping of samples with very low DNA quantities using PCR. Nucleic Acids Res. 24, 3189–3194 (1996).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Casado-Amezúa, P. et al. Development of microsatellite markers as a molecular tool for conservation studies of the Mediterranean reef builder coral cladocora caespitosa (Anthozoa, Scleractinia). J. Hered. 102, 622–626 (2011).PubMed 

    Google Scholar 
    Nakajima, Y. et al. Microsatellite markers for multiple Pocillopora genetic lineages offer new insights about coral populations. Sci. Rep. 7, 1–8 (2017).ADS 

    Google Scholar 
    Jenkins, T. L. & Stevens, J. R. Assessing connectivity between MPAs: Selecting taxa and translating genetic data to inform policy. Mar. Policy 94, 165–173 (2018).
    Google Scholar 
    Flot, J. F., Magalon, H., Cruaud, C., Couloux, A. & Tillier, S. Patterns of genetic structure among Hawaiian corals of the genus Pocillopora yield clusters of individuals that are compatible with morphology. Comptes Rendus Biol. 331, 239–247 (2008).
    Google Scholar 
    Benzoni, F. et al. Morphological and genetic divergence between Mediterranean and Caribbean populations of Madracis pharensis (Heller 1868) (Scleractinia, Pocilloporidae): Too much for one species? Zootaxa 4471, 473–492 (2018).PubMed 

    Google Scholar 
    Filatov, M. V., Frade, P. R., Bak, R. P. M., Vermeij, M. J. A. & Kaandorp, J. A. Comparison between colony morphology and molecular phylogeny in the Caribbean Scleractinian Coral Genus Madracis. PLoS One 8, 1104 (2013).
    Google Scholar 
    Althaus, F. et al. Impacts of bottom trawling on deep-coral ecosystems of seamounts are long-lasting. Mar. Ecol. Prog. Ser. 397, 279–294 (2009).ADS 

    Google Scholar 
    Alonso, D. et al. Caracterización de las comunidades coralinas del Parque Nacional Natural Corales de Profundidad en el Caribe colombiano: una aproximación a la conservación de su biodiversidad. (2014).Cairns, S. D., Jaap, W. C. & Lang, J. Scleractinia (Cnidaria) of the Gulf of Mexico. (2009).Werding, B. & Erhardt, H. Un encuentro de Madracis Myriaster (Milne-Edwards & Haime) (Scleractinia) en la Bahia de Santa Marta. Colombia. Bull. Mar. Coast. Res. 9, 415 (1977).
    Google Scholar 
    Blacket, M. J., Robin, C., Good, R. T., Lee, S. F. & Miller, A. D. Universal primers for fluorescent labelling of PCR fragments-an efficient and cost-effective approach to genotyping by fluorescence. Mol. Ecol. Resour. 12, 456–463 (2012).CAS 
    PubMed 

    Google Scholar 
    Culley, T. M. et al. An efficient technique for primer development and application that integrates fluorescent labeling and multiplex PCR. Appl. Plant Sci. 1, 1300027 (2013).
    Google Scholar 
    Holleley, C. E. & Geerts, P. G. Multiplex Manager 1.0: A cross-platform computer program that plans and optimizes multiplex PCR. Biotechniques 46, 511–517 (2009).CAS 
    PubMed 

    Google Scholar 
    Covarrubias-pazaran, A. G., Diaz-Garcia, L., Schlautman, B., Salazar, W. & Zalapa, J. Fragman: An R package for fragment analysis. BMC Genet. 17, 1–8 (2016).
    Google Scholar 
    Alberto, F. MsatAllele_1.0: An R package to visualize the binning of microsatellite alleles. J. Hered. 100, 394–397 (2013).
    Google Scholar 
    Kamvar, Z. N., Tabima, J. F. & Grunwald, N. J. Poppr: An R package for genetic analysis of populations with clonal, partially clonal, and/or sexual reproduction. PeerJ 2014, 1–14 (2014).
    Google Scholar  More

  • in

    Chemotaxis may assist marine heterotrophic bacterial diazotrophs to find microzones suitable for N2 fixation in the pelagic ocean

    Karl D, Michaels A, Bergman B, Capone D, Carpenter E, Letelier R, et al. Dinitrogen fixation in the world’s oceans. In: Boyer EW, Howarth RW, editors. The nitrogen cycle at regional to global scales. Dordrecht: Springer; 2002. p. 47–98.Berthelot H, Benavides M, Moisander PH, Grosso O, Bonnet S. High-nitrogen fixation rates in the particulate and dissolved pools in the Western Tropical Pacific (Solomon and Bismarck Seas): N2 fixation in the Western Pacific. Geophys Res Lett. 2017;44:8414–23.CAS 
    Article 

    Google Scholar 
    Rahav E, Bar-Zeev E, Ohayion S, Elifantz H, Belkin N, Herut B, et al. Dinitrogen fixation in aphotic oxygenated marine environments. Front Microbiol. 2013;4:227.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Bentzon-Tilia M, Traving SJ, Mantikci M, Knudsen-Leerbeck H, Hansen JL, Markager S, et al. Significant N2 fixation by heterotrophs, photoheterotrophs and heterocystous cyanobacteria in two temperate estuaries. ISME J. 2015;9:273–85.CAS 
    PubMed 
    Article 

    Google Scholar 
    Messer LF, Doubell M, Jeffries TC, Brown MV, Seymour JR. Prokaryotic and diazotrophic population dynamics within a large oligotrophic inverse estuary. Aquat Micro Ecol. 2015;74:1–15.Article 

    Google Scholar 
    Sipler RE, Gong D, Baer SE, Sanderson MP, Roberts QN, Mulholland MR, et al. Preliminary estimates of the contribution of Arctic nitrogen fixation to the global nitrogen budget. Limnol Oceanogr Lett. 2017;2:159–66.Article 

    Google Scholar 
    Benavides M, Bonnet S, Berman-Frank I, Riemann L. Deep into oceanic N2 fixation. Front Mar Sci. 2018;5:1–4.Article 

    Google Scholar 
    Mulholland MR, Bernhardt PW, Widner BN, Selden CR, Chappell PD, Clayton S, et al. High rates of N2 fixation in temperate, Western North Atlantic coastal waters expand the realm of marine diazotrophy. Glob Biogeochem Cycles. 2019;33:826–40.CAS 
    Article 

    Google Scholar 
    Zehr JP. Nitrogen fixation by marine cyanobacteria. Trends Microbiol. 2011;19:162–73.CAS 
    PubMed 
    Article 

    Google Scholar 
    Riemann L, Farnelid H, Steward G. Nitrogenase genes in non-cyanobacterial plankton: prevalence, diversity and regulation in marine waters. Aquat Micro Ecol. 2010;61:235–47.Article 

    Google Scholar 
    Farnelid H, Andersson AF, Bertilsson S, Al-Soud WA, Hansen LH, Sørensen S, et al. Nitrogenase gene amplicons from global marine surface waters are dominated by genes of non-cyanobacteria. PLoS ONE. 2011;6:e19223.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Delmont TO, Quince C, Shaiber A, Esen ÖC, Lee ST, Rappé MS, et al. Nitrogen-fixing populations of Planctomycetes and Proteobacteria are abundant in surface ocean metagenomes. Nat Microbiol. 2018;3:804–13.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Salazar G, Paoli L, Alberti A, Huerta-Cepas J, Ruscheweyh H-J, Cuenca M, et al. Gene expression changes and community turnover differentially shape the global ocean metatranscriptome. Cell. 2019;179:1068–1083.e21.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Bombar D, Paerl RW, Riemann L. Marine non-cyanobacterial diazotrophs: moving beyond molecular detection. Trends Microbiol. 2016;24:916–27.CAS 
    PubMed 
    Article 

    Google Scholar 
    Moisander PH, Benavides M, Bonnet S, Berman-Frank I, White AE, Riemann L. Chasing after non-cyanobacterial nitrogen fixation in marine pelagic environments. Front Microbiol. 2017;8:1736.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Eady RR, Postgate JR. Nitrogenase. Nature. 1974;249:805–10.CAS 
    PubMed 
    Article 

    Google Scholar 
    Wong PP, Burris RH. Nature of oxygen inhibition of nitrogenase from azotobacter vinelandii. Proc Natl Acad Sci USA 1972;69:672–5.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Berman-Frank I, Quigg A, Finkel ZV, Irwin AJ, Haramaty L. Nitrogen-fixation strategies and Fe requirements in cyanobacteria. Limnol Oceanogr. 2007;52:2260–9.Article 

    Google Scholar 
    Inomura K, Bragg J, Follows MJ. A quantitative analysis of the direct and indirect costs of nitrogen fixation: a model based on Azotobacter vinelandii. ISME J. 2017;11:166–75.CAS 
    PubMed 
    Article 

    Google Scholar 
    Paerl HW. Microzone formation: its role in the enhancement of aquatic N2 fixation. Limnol Oceanogr. 1985;30:1246–52.CAS 
    Article 

    Google Scholar 
    Paerl HW, Prufert LE. Oxygen-poor microzones as potential sites of microbial N2 fixation in nitrogen-depleted aerobic marine waters. Appl Env Microbiol. 1987;53:1078–87.CAS 
    Article 

    Google Scholar 
    Riemann L, Rahav E, Passow U, Grossart H-P, de Beer D, Klawonn I, et al. Planktonic aggregates as hotspots for heterotrophic diazotrophy: the plot thickens. Front Microbiol. 2022;13:1092.Article 

    Google Scholar 
    Braun ST, Proctor LM, Zani S, Mellon MT, Zehr JP. Molecular evidence for zooplankton-associated nitrogen-fixing anaerobes based on amplification of the nifH gene. FEMS Microbiol Ecol. 1999;28:273–9.CAS 
    Article 

    Google Scholar 
    Farnelid H, Tarangkoon W, Hansen G, Hansen PJ, Riemann L. Putative N2-fixing heterotrophic bacteria associated with dinoflagellate–Cyanobacteria consortia in the low-nitrogen Indian Ocean. Aquat Micro Ecol. 2010;61:105–17.Article 

    Google Scholar 
    Scavotto RE, Dziallas C, Bentzon-Tilia M, Riemann L, Moisander PH. Nitrogen-fixing bacteria associated with copepods in coastal waters of the North Atlantic Ocean: diazotroph community in association with copepods. Environ Microbiol. 2015;17:3754–65.CAS 
    PubMed 
    Article 

    Google Scholar 
    Farnelid H, Turk-Kubo K, Ploug H, Ossolinski JE, Collins JR, Van Mooy BAS, et al. Diverse diazotrophs are present on sinking particles in the North Pacific Subtropical Gyre. ISME J. 2019;13:170–82.PubMed 
    Article 

    Google Scholar 
    Geisler E, Bogler A, Rahav E, Bar-Zeev E. Direct detection of heterotrophic diazotrophs associated with planktonic aggregates. Sci Rep. 2019;9:1–9.CAS 
    Article 

    Google Scholar 
    Pedersen JN, Bombar D, Paerl RW, Riemann L. Diazotrophs and N2-fixation associated with particles in coastal estuarine waters. Front Microbiol. 2018;9:2759.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Paerl RW, Hansen TNG, Henriksen NNSE, Olesen AK, Riemann L. N2-fixation and related O2 constraints on model marine diazotroph Pseudomonas stutzeri BAL361. Aquat Micro Ecol. 2018;81:125–36.Article 

    Google Scholar 
    Rahav E, Giannetto MJ, Bar-Zeev E. Contribution of mono and polysaccharides to heterotrophic N2 fixation at the eastern Mediterranean coastline. Sci Rep. 2016;6:27858.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Chakraborty S, Andersen KH, Visser AW, Inomura K, Follows MJ, Riemann L. Quantifying nitrogen fixation by heterotrophic bacteria in sinking marine particles. Nat Commun. 2021;12:4085.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Stocker R, Seymour JR, Samadani A, Hunt DE, Polz MF. Rapid chemotactic response enables marine bacteria to exploit ephemeral microscale nutrient patches. Proc Natl Acad Sci USA 2008;105:4209–14.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Stocker R, Seymour JR. Ecology and physics of bacterial chemotaxis in the ocean. Microbiol Mol Biol Rev. 2012;76:792–812.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Garren M, Son K, Raina J-B, Rusconi R, Menolascina F, Shapiro OH, et al. A bacterial pathogen uses dimethylsulfoniopropionate as a cue to target heat-stressed corals. ISME J. 2014;8:999–1007.CAS 
    PubMed 
    Article 

    Google Scholar 
    Son K, Menolascina F, Stocker R. Speed-dependent chemotactic precision in marine bacteria. Proc Natl Acad Sci USA 2016;113:8624–9.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Brumley DR, Carrara F, Hein AM, Yawata Y, Levin SA, Stocker R. Bacteria push the limits of chemotactic precision to navigate dynamic chemical gradients. Proc Natl Acad Sci USA 2019;116:10792–7.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Müller‐Niklas G, Stefan S, Kaltenböok E, Herndl GJ. Organic content and bacterial metabolism in amorphous aggregations of the northern Adriatic Sea. Limnol Oceanogr. 1994;39:58–68.Article 

    Google Scholar 
    Grossart H-P, Czub G, Simon M. Algae–bacteria interactions and their effects on aggregation and organic matter flux in the sea. Environ Microbiol. 2006;8:1074–84.PubMed 
    Article 

    Google Scholar 
    Smith DC, Simon M, Alldredge AL, Azam F. Intense hydrolytic enzyme activity on marine aggregates and implications for rapid particle dissolution. Nature. 1992;359:139–42.CAS 
    Article 

    Google Scholar 
    Kiørboe T, Ploug H, Thygesen UH. Fluid motion and solute distribution around sinking aggregates. I. Small-scale fluxes and heterogeneity of nutrients in the pelagic environment. Mar Ecol Prog Ser. 2001;211:1–13.Article 

    Google Scholar 
    Kiørboe T, Jackson GA. Marine snow, organic solute plumes, and optimal chemosensory behavior of bacteria. Limnol Oceanogr. 2001;46:1309–18.Article 

    Google Scholar 
    Raina J-B, Lambert BS, Parks DH, Rinke C, Siboni N, Bramucci A, et al. Chemotaxis shapes the microscale organisation of the ocean’s microbiome. Nature. 2022;605:132–8.CAS 
    PubMed 
    Article 

    Google Scholar 
    Lambert BS, Raina J-B, Fernandez VI, Rinke C, Siboni N, Rubino F, et al. A microfluidics-based in situ chemotaxis assay to study the behaviour of aquatic microbial communities. Nat Microbiol. 2017;2:1344–9.CAS 
    PubMed 
    Article 

    Google Scholar 
    Clerc EE, Raina J-B, Lambert BS, Seymour J, Stocker R. In situ chemotaxis assay to examine microbial behavior in aquatic ecosystems. J Vis Exp. 2020;159:e61062.
    Google Scholar 
    Boström KH, Riemann L, Kühl M, Hagström Å. Isolation and gene quantification of heterotrophic N2-fixing bacterioplankton in the Baltic Sea. Environ Microbiol. 2007;9:152–64.PubMed 
    Article 
    CAS 

    Google Scholar 
    Farnelid H, Harder J, Bentzon-Tilia M, Riemann L. Isolation of heterotrophic diazotrophic bacteria from estuarine surface waters: heterotrophic diazotrophs in the Baltic Sea. Environ Microbiol. 2014;16:3072–82.CAS 
    PubMed 
    Article 

    Google Scholar 
    ZoBell CE. Studies on Marine Bacteria I. The cultural requirements of heterotrophic aerobes. J Mar Res. 1941;4:41–75.Alldredge AL, Gotschalk C, Passow U, Riebesell U. Mass aggregation of diatom blooms: Insights from a mesocosm study. Deep Sea Res Part II Top Stud Oceanogr. 1995;42:9–27.CAS 
    Article 

    Google Scholar 
    Thornton DCO. Diatom aggregation in the sea: mechanisms and ecological implications. Eur J Phycol. 2002;37:149–61.Article 

    Google Scholar 
    Turner J. Zooplankton fecal pellets, marine snow and sinking phytoplankton blooms. Aquat Micro Ecol. 2002;27:57–102.Article 

    Google Scholar 
    Schnetzer A, Lampe RH, Benitez-Nelson CR, Marchetti A, Osburn CL, Tatters AO. Marine snow formation by the toxin-producing diatom, Pseudo-nitzschia australis. Harmful Algae. 2017;61:23–30.CAS 
    Article 

    Google Scholar 
    Dittmar T, Koch B, Hertkorn N, Kattner G. A simple and efficient method for the solid-phase extraction of dissolved organic matter (SPE-DOM) from seawater. Limnol Oceanogr Methods. 2008;6:230–5.CAS 
    Article 

    Google Scholar 
    Marie D, Partensky F, Jacquet S, Vaulot D. Enumeration and cell cycle analysis of natural populations of marine picoplankton by flow cytometry using the nucleic acid stain SYBR green. Appl Environ Microbiol. 1997;63:186–93.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Bramucci AR, Focardi A, Rinke C, Hugenholtz P, Tyson GW, Seymour JR, et al. Microvolume DNA extraction methods for microscale amplicon and metagenomic studies. ISME Commun. 2021;1:1–5.Article 

    Google Scholar 
    Rinke C, Low S, Woodcroft BJ, Raina J-B, Skarshewski A, Le XH, et al. Validation of picogram- and femtogram-input DNA libraries for microscale metagenomics. PeerJ. 2016;4:e2486.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–20.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Li H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. ArXiv13033997 Q-Bio. 2013.Suzek BE, Huang H, McGarvey P, Mazumder R, Wu CH. UniRef: comprehensive and non-redundant UniProt reference clusters. Bioinformatics. 2007;23:1282–8.CAS 
    PubMed 
    Article 

    Google Scholar 
    Kanehisa M, Goto S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000;28:27–30.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Buchfink B, Xie C, Huson DH. Fast and sensitive protein alignment using DIAMOND. Nat Methods. 2015;12:59–60.CAS 
    PubMed 
    Article 

    Google Scholar 
    Clarke KR, Gorley RN, Somerfield PJ, Warwick RM. Change in marine communities: an approach to statistical analysis and interpretation. 3rd ed. Plymouth: Primer-E Ltd; 2014.Katoh K, Rozewicki J, Yamada KD. MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization. Brief Bioinform. 2019;20:1160–6.CAS 
    PubMed 
    Article 

    Google Scholar 
    Kozlov AM, Darriba D, Flouri T, Morel B, Stamatakis A. RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference. Bioinformatics. 2019;35:4453–5.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Edler D, Klein J, Antonelli A, Silvestro D. raxmlGUI 2.0 beta: a graphical interface and toolkit for phylogenetic analyses using RAxML. bioRxiv. 2019. https://doi.org/10.1101/800912.Barbera P, Kozlov AM, Czech L, Morel B, Darriba D, Flouri T, et al. EPA-ng: massively parallel evolutionary placement of genetic sequences. Syst Biol. 2019;68:365–9.PubMed 
    Article 

    Google Scholar 
    Czech L, Barbera P, Stamatakis A. Genesis and Gappa: processing, analyzing and visualizing phylogenetic (placement) data. Bioinformatics. 2020;36:3263–5.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Chaumeil P-A, Mussig AJ, Hugenholtz P, Parks DH. GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics. 2020;36:1925–7.CAS 

    Google Scholar 
    Bentzon-Tilia M, Severin I, Hansen LH, Riemann L. Genomics and ecophysiology of heterotrophic nitrogen-fixing bacteria isolated from estuarine surface water. mBio. 2015;6:e00929–15.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Martínez-Pérez C, Mohr W, Schwedt A, Dürschlag J, Callbeck CM, Schunck H, et al. Metabolic versatility of a novel N2-fixing Alphaproteobacterium isolated from a marine oxygen minimum zone: novel N2-fixer from oxygen minimum zone off Peru. Environ Microbiol. 2018;20:755–68.PubMed 
    Article 
    CAS 

    Google Scholar 
    Hyatt D, Chen G-L, LoCascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinforma. 2010;11:119.Article 
    CAS 

    Google Scholar 
    Eschemann A, Kühl M, Cypionka H. Aerotaxis in Desulfovibrio. Environ Microbiol. 1999;1:489–94.CAS 
    PubMed 
    Article 

    Google Scholar 
    Zhu S, Kojima S, Homma M. Structure, gene regulation and environmental response of flagella in Vibrio. Front Microbiol. 2013;4:410.Silva MA, Salgueiro CA. Multistep signaling in nature: a close-up of Geobacter chemotaxis sensing. Int J Mol Sci. 2021;22:9034.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Taylor BL, Zhulin IB, Johnson MS. Aerotaxis and other energy-sensing behavior in bacteria. Annu Rev Microbiol. 1999;53:103–28.CAS 
    PubMed 
    Article 

    Google Scholar 
    Colin R, Sourjik V. Emergent properties of bacterial chemotaxis pathway. Curr Opin Microbiol. 2017;39:24–33.CAS 
    PubMed 
    Article 

    Google Scholar 
    Stocker R. Marine microbes see a sea of gradients. Science. 2012;338:628–33.CAS 
    PubMed 
    Article 

    Google Scholar 
    Turk‐Kubo KA, Karamchandani M, Capone DG, Zehr JP. The paradox of marine heterotrophic nitrogen fixation: abundances of heterotrophic diazotrophs do not account for nitrogen fixation rates in the Eastern Tropical South Pacific. Environ Microbiol. 2014;16:3095–114.PubMed 
    Article 
    CAS 

    Google Scholar 
    Bentzon-Tilia M, Farnelid H, Jürgens K, Riemann L. Cultivation and isolation of N2-fixing bacteria from suboxic waters in the Baltic Sea. FEMS Microbiol Ecol. 2014;88:358–71.CAS 
    PubMed 
    Article 

    Google Scholar  More