More stories

  • in

    Occurrence of bioluminescent and nonbioluminescent species in the littoral earthworm genus Pontodrilus

    In this study, we confirmed that P. longissimus is nonbioluminescent, despite its close relationship to the luminous species P. litoralis (Supplementary Fig. S2)8. The presence of both luminous and nonluminous species in a single genus is likely widespread, but only a few examples have been confirmed; for example, the genera Vibrio and Photobacterium (marine bacteria)9, Epigonus (deep-sea fishes)10, Mycena (bonnet mushrooms)11 and Eisenia (terrestrial earthworms)12 have been reported to contain both luminous and nonluminous species. P. litoralis and P. longissimus can easily be collected at the same beach8 and reared in a laboratory; thus, they are suitable for studying the ecology and evolution of bioluminescence.In vitro luciferin-luciferase cross-reaction tests of P. longissimus and P. litoralis confirmed that the luminescence ability of P. litoralis is due to the presence of multiple bioluminescent components in coelomic fluid, i.e., luciferin, luciferase and the light emitter. Cross-reaction tests have previously indicated that luminous earthworms in the genera Pontodrilus (Megascolecidae), Microscolex and Diplocardia (Acanthodrilidae) share the same basic bioluminescence mechanisms5,7,13,14, despite their distant relationships to each other15,16. It is expected that the ancestral state of Pontodrilus is nonbioluminescent because the nearest extant relatives of Pontodrilus belong to the genus Plutellus Perrier, 1873, and all members of this group are nonbioluminescent6,17. These findings suggested that P. litoralis secondarily acquired bioluminescent properties through parallel evolution, similar to the case of bioluminescence in lampyrid and elaterid beetles18. We detected a clear difference in the protein composition of the secreted fluid between P. litoralis and P. longissimus (Supplementary Fig. S1). Luciferase and other bioluminescent components of luminous earthworms were not identified, and further comparative analyses of the protein bands, which appear only in the secreted fluid of luminous species, will be useful to understand the mechanisms of bioluminescence and its parallel evolution.In Thailand, P. longissimus was found sympatrically with P. litoralis at the beaches along the coast, but the microhabitats of the two congeners are different; P. litoralis was collected on the beach surface (under trash or leaf litter on sandy beaches), whereas P. longissimus was found at a greater depth than P. litoralis, i.e., a depth of more than 10 cm, where trash and leaves are scarce8 (Fig. 4A–D). It has been hypothesized that the biological function of bioluminescence in Annelida, including P. litoralis, is to stun or divert attention as an anti-predator defense19,20,21,22,23,24,25, but experiments and observations of the prey are limited. Sivinski & Forrest25 reported that the luminescence of Microscolex phosphoreus deterred predation by the mole cricket Scapteriscus acletus under laboratory conditions, although the specimen was ultimately consumed. A British television program26 presented by David Attenborough showed that the French luminous earthworm Avelona ligra glowed when attacked by the carabid beetle, but the beetle consumed the luminescent worm without any hesitation. We suggest that the absence of bioluminescence in P. longissimus may be associated with its presence in habitats with low predation pressure, whereas P. litoralis acquired a bioluminescent property during evolution that enabled it live on the surface of the beach, which is rich in nutrition and food sources3,27 as well as potential predators.Figure 4(A) The microhabitat of Pontodrilus litoralis from Aichi Prefecture, Japan. (B) The microhabitat of P. longissimus in Ranong, Thailand; sympatric Pontodrilus specimens were collected from this location8. (C) P. longissimus was found at a depth of 10–30 cm in muddy sand; the earthworm is shown by an arrow. (D) Bright field image of the Pontodrilus species included in this study. (E) An earwig (Anisolabis maritima) (a potential Pontodrilus predator) grooming its forelegs after attacking P. litoralis. (F) A. maritima (arrowhead) was found in the same microhabitat as P. litoralis in Aichi Prefecture, Japan.Full size imageIndeed, while we observed some burrowing bivalves, no potential predators were observed in the deep sand inhabited by P. longissimus. In contrast, various carnivorous invertebrates, such as earwigs, rove beetles and carabid beetles, were observed on the surface of beaches in Thailand and Japan, where P. litoralis live (Seesamut pers. obs.). We therefore performed a feeding experiment using maritime earwigs sympatrically distributed in a P. litoralis habitat. The maritime earwig Anisolabis maritima (Dermaptera, Anisolabididae) is a cosmopolitan species that can be found in Japan. It has well-developed compound eyes (Fig. 4E) and is considered a carnivorous animal that forages for prey at night28, 29. A. maritima (body length ≤ 30 mm) was the predominant predator at the beach where P. litoralis was collected (Fig. 4F). Some rove beetles (Coleoptera, Staphylinidae) were found in the same habitat, but they seemed to be too small ( More

  • in

    Flowers adapt to welcome the birds — but not the bees

    In Europe, bumblebees pollinate the flowers called foxgloves, but foxgloves that spread to the Americas are also pollinated by hummingbirds and have evolved as a result. Credit: Getty

    Ecology
    16 April 2021
    Flowers adapt to welcome the birds — but not the bees

    Once in the Americas, foxgloves swiftly evolved under pressure by pollinating hummingbirds.

    Share on Twitter
    Share on Twitter

    Share on Facebook
    Share on Facebook

    Share via E-Mail
    Share via E-Mail

    Evolution can forge new relationships between plants and pollinators in fewer than 85 generations.The showy purple flowers called common foxgloves (Digitalis purpurea) are native to Europe, where they are pollinated by bumblebees. When admiring humans took the foxglove to the Americas, it was enthusiastically embraced by a new guild of nectar-drinkers — the hummingbirds.Maria Clara Castellanos at the University of Sussex in Brighton, UK, and her colleagues tallied visitors to foxgloves in the United Kingdom, Colombia and Costa Rica during more than 2,000 3-minute study periods. They found that hummingbirds pollinate up to 27% of foxgloves in Colombia and Costa Rica, where the flowers’ corollas — the long purple tubes that gardeners love so much — are 13% and 26% longer, respectively, than those of UK foxgloves.So why would foxgloves with longer corollas do better? Plants with corollas too long for bumblebees to reach their nectar are guaranteed to be pollinated by hummingbirds, which are more effective than bees at depositing pollen on the next flower. The longer corolla also creates a more comfortable fit for a hovering hummingbird, perhaps improving pollination rates.Hummingbirds can travel further between flowers than can bees, which might reduce plant inbreeding.

    J. Ecol. (2021)

    Ecology More

  • in

    A decadal perspective on north water microbial eukaryotes as Arctic Ocean sentinels

    1.Lovejoy, C., Massana, R. & Pedros-Alio, C. Diversity and distribution of marine microbial eukaryotes in the Arctic Ocean and adjacent seas. Appl. Environ. Microb. 72, 3085–3095. https://doi.org/10.1128/aem.72.5.3085-3095.2006 (2006).CAS 
    Article 

    Google Scholar 
    2.Chamnansinp, A., Li, Y., Lundholm, N. & Moestrup, Ø. Global diversity of two widespread, colony-forming diatoms of the marine plankton, Chaetoceros socialis (syn. C. radians) and Chaetoceros gelidus sp. nov.. J. Phycol. 49, 1128–1141. https://doi.org/10.1111/jpy.12121 (2013).CAS 
    Article 
    PubMed 

    Google Scholar 
    3.Bluhm, B. A. & Gradinger, R. Regional variability in food availability for Arctic marine mammals. Ecol. Appl. 18, S77-96. https://doi.org/10.1890/06-0562.1 (2008).Article 
    PubMed 

    Google Scholar 
    4.Bâcle, J., Carmack, E. C. & Ingram, R. G. Water column structure and circulation under the North Water during spring transition: April–July 1998. Deep Sea Res. Part II Top. Stud. Oceanogr. 49, 4907–4925. https://doi.org/10.1016/S0967-0645(02)00170-4 (2002).ADS 
    Article 

    Google Scholar 
    5.Dumont, D., Gratton, Y. & Arbetter, T. E. Modeling wind-driven circulation and landfast ice-edge processes during polynya events in Northern Baffin Bay. J. Phys. Oceanogr. 40, 1356–1372. https://doi.org/10.1175/2010JPO4292.1 (2010).ADS 
    Article 

    Google Scholar 
    6.Tremblay, J. -É., Gratton, Y., Fauchot, J. & Price, N. M. Climatic and oceanic forcing of new, net, and diatom production in the North Water. Deep Sea Res. Part II Top. Stud. Oceanogr. 49, 4927–4946. https://doi.org/10.1016/S0967-0645(02)00171-6 (2002).ADS 
    CAS 
    Article 

    Google Scholar 
    7.Michel, C. et al. Arctic Ocean outflow shelves in the changing Arctic: A review and perspectives. Progr. Oceanogr. 139, 66–88. https://doi.org/10.1016/j.pocean.2015.08.007 (2015).ADS 
    Article 

    Google Scholar 
    8.Møller, E. F. et al. Zooplankton phenology may explain the North Water polynya’s importance as a breeding area for little auks. Mar. Ecol. Progr. Ser. 605, 207–223. https://doi.org/10.3354/meps12745 (2018).ADS 
    Article 

    Google Scholar 
    9.Mei, Z.-P. et al. Physical control of spring–summer phytoplankton dynamics in the North Water, April–July 1998. Deep Sea Res. Part II Top. Stud. Oceanogr. 49, 4959–4982. https://doi.org/10.1016/S0967-0645(02)00173-X (2002).ADS 
    Article 

    Google Scholar 
    10.Marchese, C. et al. Changes in phytoplankton bloom phenology over the North Water (NOW) polynya: a response to changing environmental conditions. Polar Biol. 40, 1721–1737. https://doi.org/10.1007/s00300-017-2095-2 (2017).Article 

    Google Scholar 
    11.Martin, J. et al. Prevalence, structure and properties of subsurface chlorophyll maxima in Canadian Arctic waters. Mar. Ecol. Progr. Ser. 412, 69–84. https://doi.org/10.3354/meps08666 (2010).ADS 
    CAS 
    Article 

    Google Scholar 
    12.Joli, N. et al. Need for focus on microbial species following ice melt and changing freshwater regimes in a Janus Arctic Gateway. Sci. Rep. 8, 9405. https://doi.org/10.1038/s41598-018-27705-6 (2018).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    13.Lehmann, N. et al. Remote western Arctic nutrients fuel remineralization in deep Baffin Bay. Global Biogeochem. Cycles 33, 649–667. https://doi.org/10.1029/2018GB006134 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    14.Blais, M. et al. Contrasting interannual changes in phytoplankton productivity and community structure in the coastal Canadian Arctic Ocean. Limnol. Oceanogr. 62, 2480–2497. https://doi.org/10.1002/lno.10581 (2017).ADS 
    Article 

    Google Scholar 
    15.Ardyna, M., Gosselin, M., Michel, C., Poulin, M. & Tremblay, J. -É. Environmental forcing of phytoplankton community structure and function in the Canadian High Arctic: Contrasting oligotrophic and eutrophic regions. Mar. Ecol. Progr. Ser. 442, 37–57. https://doi.org/10.3354/meps09378 (2011).ADS 
    CAS 
    Article 

    Google Scholar 
    16.Ardyna, M. et al. Recent Arctic Ocean sea ice loss triggers novel fall phytoplankton blooms. Geophys. Res. Lett. 41, 6207–6212. https://doi.org/10.1002/2014GL061047 (2014).ADS 
    Article 

    Google Scholar 
    17.Lovejoy, C., Legendre, L., Martineau, M.-J., Bâcle, J. & Von Quillfeldt, C. H. Distribution of phytoplankton and other protists in the North Water. Deep Sea Res. Part II Top. Stud. Oceanogr. 49, 5027–5047. https://doi.org/10.1016/S0967-0645(02)00176-5 (2002).ADS 
    Article 

    Google Scholar 
    18.Tremblay, J. -É., Michel, C., Hobson, K. A., Gosselin, M. & Price, N. M. Bloom dynamics in early opening waters of the Arctic Ocean. Limnol. Oceanogr. 51, 900–912. https://doi.org/10.4319/lo.2006.51.2.0900 (2006).ADS 
    CAS 
    Article 

    Google Scholar 
    19.Mayzaud, P., Boutoute, M., Noyon, M., Narcy, F. & Gasparini, S. Lipid and fatty acids in naturally occurring particulate matter during spring and summer in a high arctic fjord (Kongsfjorden, Svalbard). Mar. Biol. 160, 383–398. https://doi.org/10.1007/s00227-012-2095-2 (2013).CAS 
    Article 

    Google Scholar 
    20.Dumont, D., Gratton, Y. & Arbetter, T. E. Modeling the dynamics of the North Water Polynya Ice Bridge. J. Phys. Oceanogr. 39, 1448–1461. https://doi.org/10.1175/2008jpo3965.1 (2009).ADS 
    Article 

    Google Scholar 
    21.Simo-Matchim, A.-G., Gosselin, M., Poulin, M., Ardyna, M. & Lessard, S. Summer and fall distribution of phytoplankton in relation to environmental variables in Labrador fjords, with special emphasis on Phaeocystis pouchetii. Mar. Ecol. Progr. Ser. 572, 19–42. https://doi.org/10.3354/meps12125 (2017).ADS 
    CAS 
    Article 

    Google Scholar 
    22.Flynn, K. J. et al. Mixotrophic protists and a new paradigm for marine ecology: where does plankton research go now?. J. Plankton Res. 41, 375–391. https://doi.org/10.1093/plankt/fbz026 (2019).Article 

    Google Scholar 
    23.Levinsen, H. & Nielsen, T. G. The trophic role of marine pelagic ciliates and heterotrophic dinoflagellates in arctic and temperate coastal ecosystems: A cross-latitude comparison. Limnol. Oceanogr. 47, 427–439. https://doi.org/10.4319/lo.2002.47.2.0427 (2002).ADS 
    Article 

    Google Scholar 
    24.Marquardt, M., Vader, A., Stübner, E. I., Reigstad, M. & Gabrielsen, T. M. Strong seasonality of marine microbial eukaryotes in a high-Arctic fjord (Isfjorden, in West Spitsbergen, Norway). Appl. Environ. Microb. 82, 1868–1880. https://doi.org/10.1128/AEM.03208-15 (2016).CAS 
    Article 

    Google Scholar 
    25.Terrado, R., Vincent, W. F. & Lovejoy, C. Mesopelagic protists: diversity and succession in a coastal Arctic ecosystem. Aquat. Microb. Ecol. 56, 25–39. https://doi.org/10.3354/ame01327 (2009).Article 

    Google Scholar 
    26.Johnson, M. D. & Beaudoin, D. J. The genetic diversity of plastids associated with mixotrophic oligotrich ciliates. Limnol. Oceanogr. 64, 2187–2201. https://doi.org/10.1002/lno.11178 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    27.Onda, D. F. et al. Seasonal and interannual changes in ciliate and dinoflagellate species assemblages in the Arctic Ocean (Amundsen Gulf, Beaufort Sea, Canada). Front. Mar. Sci. 4, 16. https://doi.org/10.3389/fmars.2017.00016 (2017).ADS 
    Article 

    Google Scholar 
    28.Olsen, L. M. et al. A red tide in the pack ice of the Arctic Ocean. Sci. Rep. 9, 9536. https://doi.org/10.1038/s41598-019-45935-0 (2019).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    29.Lovejoy, C. et al. Distribution, phylogeny, and growth of cold-adapted Picoprasinophytes in Arctic seas 1. J. Phycol. 43, 78–89. https://doi.org/10.1111/j.1529-8817.2006.00310.x (2007).CAS 
    Article 

    Google Scholar 
    30.Metfies, K., von Appen, W.-J., Kilias, E., Nicolaus, A. & Nöthig, E.-M. Biogeography and photosynthetic biomass of arctic marine pico-eukaroytes during summer of the record sea ice minimum 2012. PLoS ONE 11, e0148512. https://doi.org/10.1371/journal.pone.0148512 (2016).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    31.Joli, N., Monier, A., Logares, R. & Lovejoy, C. Seasonal patterns in Arctic prasinophytes and inferred ecology of Bathycoccus unveiled in an Arctic winter metagenome. ISME J. 11, 1372. https://doi.org/10.1038/ismej.2017.7 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    32.Piedade, G. J., Wesdorp, E. M., Montenegro-Borbolla, E., Maat, D. S. & Brussaard, C. P. D. Influence of irradiance and temperature on the virus MpoV-45T infecting the Arctic picophytoplankter Micromonas polaris. Viruses 10, 676. https://doi.org/10.3390/v10120676 (2018).CAS 
    Article 
    PubMed Central 

    Google Scholar 
    33.Maat, D. S. et al. Characterization and temperature dependence of Arctic Micromonas polaris viruses. Viruses 9, 134. https://doi.org/10.3390/v9060134 (2017).CAS 
    Article 
    PubMed Central 

    Google Scholar 
    34.Demory, D. et al. Picoeukaryotes of the Micromonas genus: sentinels of a warming ocean. ISME J. 13, 132–146. https://doi.org/10.1038/s41396-018-0248-0 (2019).Article 
    PubMed 

    Google Scholar 
    35.Ardyna, M. et al. Shelf-basin gradients shape ecological phytoplankton niches and community composition in the coastal Arctic Ocean (Beaufort Sea). Limnol. Oceanogr. 62, 2113–2132. https://doi.org/10.1002/lno.10554 (2017).ADS 
    Article 

    Google Scholar 
    36.Luddington, I. A., Lovejoy, C. & Kaczmarska, I. Species-rich meta-communities of the diatom order Thalassiosirales in the Arctic and northern Atlantic Ocean. J. Plankton Res. 38, 781–797. https://doi.org/10.1093/plankt/fbw030 (2016).CAS 
    Article 

    Google Scholar 
    37.Booth, B. C. et al. Dynamics of Chaetoceros socialis blooms in the North Water. Deep Sea Res. Part II Top. Stud. Oceanogr. 49, 5003–5025. https://doi.org/10.1016/S0967-0645(02)00175-3 (2002).ADS 
    CAS 
    Article 

    Google Scholar 
    38.Oziel, L. et al. Faster Atlantic currents drive poleward expansion of temperate phytoplankton in the Arctic Ocean. Nat. Commun. 11, 1–8. https://doi.org/10.1038/s41467-020-15485-5 (2020).ADS 
    CAS 
    Article 

    Google Scholar 
    39.Dı́ez, B., Pedrós-Alió, C. & Massana, R. Study of genetic diversity of eukaryotic picoplankton in different oceanic regions by small-subunit rRNA Gene cloning and sequencing. Appl. Environ. Microb. 67, 2932. https://doi.org/10.1128/AEM.67.7.2932-2941.2001 (2001).Article 

    Google Scholar 
    40.Crawford, D. W., Cefarelli, A. O., Wrohan, I. A., Wyatt, S. N. & Varela, D. E. Spatial patterns in abundance, taxonomic composition and carbon biomass of nano-and microphytoplankton in subarctic and Arctic Seas. Prog. Oceanogr. 162, 132–159. https://doi.org/10.1016/j.pocean.2018.01.006 (2018).ADS 
    Article 

    Google Scholar 
    41.Fu, R. & Gong, J. Single cell analysis linking ribosomal (r) DNA and r RNA copy numbers to cell size and growth rate provides insights into molecular protistan ecology. J. Eukaryot. Microbiol. 64, 885–896. https://doi.org/10.1111/jeu.12425 (2017).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    42.Lewis, K., Van Dijken, G. & Arrigo, K. R. Changes in phytoplankton concentration now drive increased Arctic Ocean primary production. Science 369, 198–202. https://doi.org/10.1126/science.aay8380 (2020).CAS 
    Article 
    PubMed 

    Google Scholar 
    43.Fetterer, F., Knowles, K., Meier, W. N., Savoie, M. & Windnagel, A. K. Updated daily Sea Ice Index, Version 3 (NSIDC: National Snow and Ice Data Center, Boulder, CO USA). https://doi.org/10.7265/N5K072F8 (2017).44.Ryan, P. A. & Münchow, A. Sea ice draft observations in Nares Strait from 2003 to 2012. J. Geophys. Res. Oceans 122, 3057–3080. https://doi.org/10.1002/2016JC011966 (2017).ADS 
    Article 

    Google Scholar 
    45.Grasshoff, K. et al. (eds). Methods of seawater analysis 3rd edn (John Wiley & Sons). https://doi.org/10.1002/9783527613984 (2009).46.Terrado, R. et al. Protist community composition during spring in an Arctic flaw lead polynya. Polar Biol. 34, 1901–1914. https://doi.org/10.1007/s00300-011-1039-5 (2011).Article 

    Google Scholar 
    47.Dasilva, C. R., Li, W. K. W. & Lovejoy, C. Phylogenetic diversity of eukaryotic marine microbial plankton on the Scotian Shelf Northwestern Atlantic Ocean. J. Plankton Res. 36, 344–363. https://doi.org/10.1093/plankt/fbt123 (2014).CAS 
    Article 

    Google Scholar 
    48.Comeau, A. M., Li, W. K., Tremblay, J. -É., Carmack, E. C. & Lovejoy, C. Arctic Ocean microbial community structure before and after the 2007 record sea ice minimum. PLoS ONE 6, e27492. https://doi.org/10.1371/journal.pone.0027492 (2011).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    49.Bushnell, B., Rood, J. & Singer, E. BBMerge–accurate paired shotgun read merging via overlap. PLoS ONE 12, e0185056. https://doi.org/10.1371/journal.pone.0185056 (2017).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    50.Rognes, T., Flouri, T., Nichols, B., Quince, C. & Mahé, F. VSEARCH: A versatile open source tool for metagenomics. PeerJ 4, e2584. https://doi.org/10.7717/peerj.2584 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    51.Edgar, R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460–2461. https://doi.org/10.1093/bioinformatics/btq461 (2010).CAS 
    Article 
    PubMed 

    Google Scholar 
    52.Schloss, P. D. et al. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microb. 75, 7537–7541. https://doi.org/10.1128/AEM.01541-09 (2009).CAS 
    Article 

    Google Scholar 
    53.Comeau, A. M. et al. Protists in Arctic drift and land-fast sea ice. J. Phycol. 49, 229–240. https://doi.org/10.1111/jpy.12026 (2013).Article 
    PubMed 

    Google Scholar 
    54.Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596. https://doi.org/10.1093/nar/gks1219 (2012).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    55.Guillou, L. et al. The protist ribosomal reference database (PR2): A catalog of unicellular eukaryote Small Sub-Unit rRNA sequences with curated taxonomy. Nucleic Acids Res. 41, D597–D604. https://doi.org/10.1093/nar/gks1160 (2012).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    56.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 
    57.Berger, S. A., Krompass, D. & Stamatakis, A. Performance, accuracy, and web server for evolutionary placement of short sequence reads under Maximum Likelihood. Syst. Biol. 60, 291–302. https://doi.org/10.1093/sysbio/syr010 (2011).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    58.Edgar, R. C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32, 1792–1797. https://doi.org/10.1093/nar/gkh340 (2004).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    59.Stamatakis, A. RAxML version 8: A tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313. https://doi.org/10.1093/bioinformatics/btu033 (2014).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    60.Thomson, R. E. & Fine, I. V. Estimating mixed layer depth from oceanic profile data. J. Atmos. Ocean. Technol. 20, 319–329. https://doi.org/10.1175/1520-0426(2003)020%3c0319:EMLDFO%3e2.0.CO;2 (2003).ADS 
    Article 

    Google Scholar 
    61.Chazdon, R. L. et al. A novel statistical method for classifying habitat generalists and specialists. Ecology 92, 1332–1343. https://doi.org/10.1890/10-1345.1 (2011).Article 
    PubMed 

    Google Scholar 
    62.Melling, H., Gratton, Y. & Ingram, G. Ocean circulation within the North Water polynya of Baffin Bay. Atmos. Ocean 39, 301–325. https://doi.org/10.1080/07055900.2001.9649683 (2001).Article 

    Google Scholar  More

  • in

    The non-indigenous Oithona davisae in a Mediterranean transitional environment: coexistence patterns with competing species

    1.Carlton, J. T. & Geller, J. B. Ecological roulette: The global transport of non-indigenous marine organisms. Sciences 261, 78–82 (1993).Article 

    Google Scholar 
    2.Ruiz, G. M., Fofonov, P. & Hines, A. H. Non-indigenous species as stressors in estuarine and marine communities: Assessing invasion impacts and interactions. Limnol. Oceanogr. 44, 950–972 (1999).ADS 
    Article 

    Google Scholar 
    3.Mack, R. N. et al. Biotic invasions: Causes, epidemiology, global consequences, and control. Ecol. Appl. 10, 689–710 (2000).Article 

    Google Scholar 
    4.Tsiamis, K. et al. Non-indigenous species refined national baseline inventories: A synthesis in the context of the European Union’s Marine Strategy Framework Directive. Mar. Pollut. Bull. 145, 429–435 (2019).CAS 
    Article 

    Google Scholar 
    5.Gollasch, S. Overview on introduced aquatic species in European navigational and adjacent waters. Helgol. Mar. Res. 60(2), 84–89 (2006).ADS 
    Article 

    Google Scholar 
    6.Zenetos, A. et al. Alien species in the Mediterranean Sea by 2010 A contribution to the application of European Union’ Marine Strategy Framework Directive (MSFD) Part I. Spatial distribution. Mediterr. Mar. Sci. 11, 381–493 (2010).Article 

    Google Scholar 
    7.Zenetos, A. et al. Uncertainties and validation of alien species catalogues: The Mediterranean as an example. Est. Coast. Shelf. Sci. 191, 171–187 (2017).ADS 
    Article 

    Google Scholar 
    8.Uttieri, M. et al. Towards a EURopean OBservatory of the non-indigenous calanoid copepod Pseudodiaptomus marinUS. Biol. Invasions 22(3), 885–906. https://doi.org/10.1007/s10530-019-02174-8 (2020).Article 

    Google Scholar 
    9.Vidjak, O. et al. Zooplankton in Adriatic port environments: Indigenous communities and non-indigenous species. Mar. Pollut. Bull. 147, 133–149. https://doi.org/10.1016/j.marpolbul.2018.06.055 (2019).CAS 
    Article 
    PubMed 

    Google Scholar 
    10.Malej, A. et al. Mnemiopsis leidyi in the northern Adriatic: Here to stay?. J. Sea Res. 124, 10–16. https://doi.org/10.1016/j.seares.2017.04.010 (2017).ADS 
    Article 

    Google Scholar 
    11.Marchini, A., Ferrario, J., Sfriso, A. & Occhipinti-Ambrogi, A. Current status and trends of biological invasions in the Lagoon of Venice, a hotspot of marine NIS introductions in the Mediterranean Sea. Biol. Invasions 17, 2943–2962. https://doi.org/10.1007/s10530-015-0922-3 (2015).Article 

    Google Scholar 
    12.Galliene, C. P. & Robins, D. B. Is Oithona the most important copepod in the world’s oceans?. J. Plankton Res. 23(12), 1421–1432 (2001).Article 

    Google Scholar 
    13.Saiz, E., Calbet, A. & Broglio, E. Effects of small-scale turbolence on copepods: The case of Oithona davisae. Limnol. Oceanogr. 48, 1304–1311. https://doi.org/10.4319/lo.2003.48.3.1304 (2003).ADS 
    Article 

    Google Scholar 
    14.Turner, T. The importance of small planktonic copepods and their roles in pelagic marine food webs. Zool. Stud. 43(2), 255–266 (2004).
    Google Scholar 
    15.Hwang, I. S., Kumar, R., Dahms, H. U., Tseng, L. C. & Chen, Q. C. Mesh size affects abundance estimates of Oithona spp. (Copepoda, Cyclopoida). Crustaceana 80(7), 827–837 (2007).Article 

    Google Scholar 
    16.Nishida, S., Tanaka, O. & Omori, M. Cyclopoid copepods of the family Oithonidae in Suruga bay and adjacent waters. Bull. Plankton Soc. Japan 24, 120–157 (1977).
    Google Scholar 
    17.Uye, S. I. & Sano, K. Seasonal reproductive biology of the small cyclopoid copepod Oithona davisae in a temperate eutrophic inlet. Mar. Ecol. Prog. Ser. 118, 121–128 (1995).ADS 
    Article 

    Google Scholar 
    18.Zagami, G. et al. Biogeographical distribution and ecology of the planktonic copepod Oithona davisae: Rapid invasion in Lakes Faro and Ganzirri (Central Mediterranean Sea). In Trends in Copepod Studies-Distribution, Biology and Ecology (ed. Uttieri, M.) 59–82 (Nova Science Publisher, New York, 2018).
    Google Scholar 
    19.Cornils, A. & Wend-Heckmann, B. First report of the planktonic copepod Oithona davisae in the northern Wadden Sea (North Sea): Evidence for recent invasion?. Helgol. Mar. Res. 69, 243–248. https://doi.org/10.1007/s10152-015-0426-7 (2015).ADS 
    Article 

    Google Scholar 
    20.Uye, S. I. & Sano, K. Seasonal variations in biomass, growth rate and production rate of the small cyclopoid copepod Oithona davisae in a temperate eutrophic inlet. Mar. Ecol. Progr. Ser. 163, 37–44 (1998).ADS 
    Article 

    Google Scholar 
    21.Ferrari, F. D. & Orsi, J. Oithona davisae, new species, and Limnoithona sinensis (Burckhardt, 1912) (Copepoda, Oithonidae) from the Sacramento San-Joaquin Estuary, California. J. Crustac. Biol. 4, 106–126. https://doi.org/10.2307/1547900 (1984).Article 

    Google Scholar 
    22.Cordell, J. R. et al. Factors influencing densities of non-indigenous species in the ballast water of ships arriving at ports in Puget Sound, Washington, United States. Aquat. Conserv. Mar. Freshw. Ecosyst. 19, 322–343. https://doi.org/10.1002/aqc.986 (2009).Article 

    Google Scholar 
    23.Dexter, E., Bollens, S. M., Cordell, J. & Rollwagen-Bollenseric, G. Zooplankton invasion on a grand scale: Insights from a 20-yr time series across 38 Northeast Pacific estuaries. Ecosphere 11(5), e03040 (2020).Article 

    Google Scholar 
    24.Temnykh, A. & Nishida, S. New record of the planktonic copepod Oithona davisae Ferrari and Orsi in the Black Sea with notes on the identity of Oithona brevicornis. Aquat. Invasions 7, 425–431 (2012).Article 

    Google Scholar 
    25.Uriarte, I., Villate, F. & Iriarte, A. Zooplankton recolonization of the inner estuary of Bilbao: Influence of pollution abatement, climate and non-indigenous species. J. Plankton Res. 38, 718–731. https://doi.org/10.1093/plankt/fbv060 (2015).Article 

    Google Scholar 
    26.Isinibilir, M., Svetlichny, L. & Hubareva, E. Competitive advantage of the invasive copepod Oithona davisae over the indigenous copepod Oithona nana in the Marmara Sea and Golden Horn Estuary. Mar. Freshw. Behav. Physiol. 49(6), 391–405. https://doi.org/10.1080/10236244.2016.1236528 (2016).CAS 
    Article 

    Google Scholar 
    27.Terbıyık Kurt, T. & Beşiktepe, Ş. First distribution record of the invasive copepod Oithona davisae Ferrari and Orsi, 1984, in the coastal waters of the Aegean Sea. Mar. Ecol. 40(3), e12548. https://doi.org/10.1111/maec.12548 (2019).Article 

    Google Scholar 
    28.Cucco, A. & Umgiesser, G. Modeling the Venice Lagoon residence time. Ecol. Model. 193, 34–51 (2006).Article 

    Google Scholar 
    29.Gačić, M. et al. Temporal variations of water flow between the Venetian lagoon and the open sea. J. Mar. Syst. 51, 33–47. https://doi.org/10.1016/j.jmarsys.2004.05.025 (2004).Article 

    Google Scholar 
    30.Zuliani, A., Zaggia, L., Collavini, F. & Zonta, R. Freshwater discharge from the drainage basin to the Venice Lagoon (Italy). Environ. Int. 31, 929–938 (2005).Article 

    Google Scholar 
    31.Sigovini, M. Multiscale dynamics of zoobenthic communities and relationships with environmental factors in the Lagoon of Venice. 207 pp (2011).32.Zirino, A. et al. Salinity and its variability in the Lagoon of Venice, 2000–2009. Adv. Oceanogr. Limnol. 5, 41–59. https://doi.org/10.1080/19475721.2014.900113 (2014).Article 

    Google Scholar 
    33.Amos, C. L., Umgiesser, G., Ghezzo, M., Kassem, H. & Ferrarin, C. Sea Surface Temperature Trends in Venice Lagoon and the Adjacent Waters. J. Coast. Res. 33(2), 385–395. https://doi.org/10.2112/JCOASTRES-D-16-00017.1 (2016).Article 

    Google Scholar 
    34.Ravera, O. The Lagoon of Venice: The result of both natural factors and human influence. J. Limnol. 59, 19–30 (2000).Article 

    Google Scholar 
    35.Solidoro, C. et al. Response of the Venice Lagoon ecosystem to natural and anthropogenic pressures over the last 50 years. In Coastal lagoons: Critical habitats of environmental change (eds Kennish, M. J. & Paerl, H. W.) 483–511 (CRC Press, New York, 2010).
    Google Scholar 
    36.Camatti, E., Pansera, M. & Bergamasco, A. The copepod Acartia tonsa Dana in a microtidal Mediterranean lagoon: History of a successful invasion. Water 11(6), 1200. https://doi.org/10.3390/w11061200 (2019).CAS 
    Article 

    Google Scholar 
    37.Schroeder, A. et al. DNA metabarcoding and morphological analysis-Assessment of zooplankton biodiversity in transitional waters. Mar. Environ. Res. https://doi.org/10.1016/j.marenvres.2020.104946 (2020).Article 
    PubMed 

    Google Scholar 
    38.Camatti, E. et al. Analisi dei popolamenti zooplanctonici nella laguna di Venezia dal 1975 al 2004. Biol. Mar. Mediterr. 13, 46–53 (2006).
    Google Scholar 
    39.Riccardi, N. Selectivity of plankton nets over mesozooplankton taxa: Implications for abundance, biomass and diversity estimation. J. Limnol. 69(2), 287–296. https://doi.org/10.3274/JL10-69-2-10 (2010).Article 

    Google Scholar 
    40.Pansera, M. et al. How does mesh-size selection reshape the description of zooplankton community structure in coastal lakes?. Est. Coast. Shelf. Sci. 151, 221–235 (2014).ADS 
    Article 

    Google Scholar 
    41.Harris, R., Wiebe, P., Lenz, J., Skjoldal, H. R. & Huntley, M. ICES Zooplankton methodology manual (Elsevier, New York, 2000).
    Google Scholar 
    42.Clarke, K.R. & Gorley, R.N. PRIMERv6: User Manual/Tutorial. PRIMER-E, Plymouth, 192 pp (2006).43.Legendre, L. & Legendre, P. Ecologie numerique, Tome 2: La structure de données écologiques. Québec, Canada Masson, Paris, France and Presses de l’Univ. du (1984).44.Tokeshi, M. Niche apportionment or random assortment e species abundance patterns revisited. J. Anim. Ecol. 59, 1129–1146 (1990).Article 

    Google Scholar 
    45.Tokeshi, M. Species abundance patterns and community structure. Adv. Ecol. Res. 24, 111–186 (1993).Article 

    Google Scholar 
    46.Fesl, C. Niche-oriented species-abundance models: Different approaches of their application to larval chironomid (Diptera) assemblages in a large river. J. Anim. Ecol. 71, 1085–1094 (2002).Article 

    Google Scholar 
    47.Spatharis, S., Orfanidis, S., Panayotidis, P. & Tsirtsis, G. Assembly processes in upper subtidal macroalgae: The effect of wave exposure. Est. Coast. Shelf. Sci. 91(2), 298–305. https://doi.org/10.1016/j.ecss.2010.10.032 (2011).ADS 
    Article 

    Google Scholar 
    48.Ferreira, F. C. & Petrere, J. M. Comments about some species abundance patterns: Classic, neutral, and niche partitioning models. Braz. J. Biol. 68(4), 1003–1012. https://doi.org/10.1590/S1519-69842008000500008 (2008).CAS 
    Article 
    PubMed 

    Google Scholar 
    49.Spatharis, S., Mouillot, D., Do Chi, T., Danielidis, D. B. & Tsirtsis, G. A niche-based modeling approach to phytoplankton community assembly rules. Oecol. 159(1), 171–180. https://doi.org/10.1007/s00442-008-1178-8 (2009).ADS 
    Article 

    Google Scholar 
    50.Johansson, F., Englund, G., Brodin, T. & Gardfjell, H. Species abundance models and patterns in dragonfly communities: Effects of fish predators. Oikos 114(1), 27–36 (2006).Article 

    Google Scholar 
    51.Anderson, B. J. & Mouillot, D. Influence of scale and resolution on niche apportionment rules in saltmeadow vegetation. Aquat. Biol. 1(2), 195–204. https://doi.org/10.3354/ab00017 (2007).Article 

    Google Scholar 
    52.Tokeshi, M. Power fraction: A new explanation of relative abundance patterns in species-rich assemblages. Oikos 75, 543–550 (1996).Article 

    Google Scholar 
    53.Seebens, H., Gastner, M. T., Blasius, B. & Courchamp, F. The risk of marine bioinvasion caused by global shipping. Ecol. Lett. 16(6), 782–790. https://doi.org/10.1111/ele.12111 (2013).CAS 
    Article 
    PubMed 

    Google Scholar 
    54.Casal, C. M. V. Global documentation of fish introductions: The growing crisis and recommendations for actions. Biol. Invasions 8, 3–11 (2006).Article 

    Google Scholar 
    55.Giani, M. et al. Recent changes in the marine ecosystems of the northern Adriatic Sea. Estuar. Coast. Shelf. Sci. 115, 1–13. https://doi.org/10.1016/j.ecss.2012.08.023 (2012).ADS 
    Article 

    Google Scholar 
    56.Schroeder, K. et al. Rapid response to climate change in a marginal sea. Sci. Rep. 7(1), 1–7. https://doi.org/10.1038/s41598-017-04455-5 (2017).CAS 
    Article 

    Google Scholar 
    57.Elliott, M. Biological pollutants and biological pollution — an increasing cause for concern. Mar. Pollut. Bull. 46, 275–280 (2003).CAS 
    Article 

    Google Scholar 
    58.Elton, C. S. The Ecology of Invasions by Animals and Plants (Methuen, London, 1958).
    Google Scholar 
    59.Gubanova, A., Garbazey, O. A., Popova, E. V., Altukhov, D. A. & Mukhanov, V. S. Oithona davisae: Naturalization in the Black Sea, interannual and seasonal dynamics, and effect on the structure of the planktonic copepod community. Oceanol. 59(6), 912–919. https://doi.org/10.31857/S0030-15745961008-1015 (2019).ADS 
    Article 

    Google Scholar 
    60.Altukhov, D. A., Gubanova, A. D. & Mukhanov, V. S. New invasive copepod Oithona davisae, Ferrari and Orsi, 1984: Seasonal dynamics in Sevastopol Bay and expansion along the Black Sea coasts. Mar. Ecol. 35, 28–34 (2014).ADS 
    Article 

    Google Scholar 
    61.Svetlichny, L. et al. Adaptive strategy of thermophilic Oithona davisae in the cold Black Sea environment. Turk. J. Fish. Aquat. Sci. 16(1), 077–090. https://doi.org/10.4194/1303-2712-v16_1_09 (2016).Article 

    Google Scholar 
    62.Hubareva, E. & Svetlichny, L. Salinity and temperature tolerance of alien copepods Acartia tonsa and Oithona davisae in the Black Sea. Rapp. Comm. Int. Mer. Mediterr. 40, 742. https://doi.org/10.13140/2.1.1145.3445 (2013).Article 

    Google Scholar 
    63.Svetlichny, L., Hubareva, E. & İşi̇ni̇bi̇li̇r, M. ,. Population dynamics of the copepod invader Oithona davisae in the Black Sea. Turk. J. Zool. 42(6), 684–693. https://doi.org/10.3906/zoo-1804-48 (2018).Article 

    Google Scholar 
    64.Uye, S. I. Replacement of large copepods by small ones with eutrophication of embayments: Cause and consequence. Hydrobiol. 292(293), 513–519. https://doi.org/10.1007/BF00229979 (1994).Article 

    Google Scholar 
    65.Saiz, E., Griffell, K., Calbet, A. & Isari, S. Feeding rates and prey: Predator size ratios of the nauplii and adult females of the marine cyclopoid copepod Oithona davisae. Limnol. Oceanography 59(6), 2077–2088 (2014).ADS 
    Article 

    Google Scholar 
    66.Cheng, W., Akiba, T., Omura, T. & Tanaka, Y. On the foraging and feeding ability of Oithona davisae (Crustacea, Copepoda). Hydrobiol. 741(1), 167–176. https://doi.org/10.1007/s10750-014-1867-8 (2014).Article 

    Google Scholar 
    67.Khanaychenko, A., Mukhanov, V., Aganesova, L., Besiktepe, S. & Gavrilova, N. Grazing and feeding selectivity of Oithona davisae in the Black Sea: Importance of cryptophytes. Turk. J. Fish. Aquat. Sci. 18(8), 937–949. https://doi.org/10.4194/1303-2712-v18_8_02 (2018).Article 

    Google Scholar 
    68.Uchima, M. Gut content analysis of neritic copepods Acartia omorii and Oithona davisae by a new method. Mar. Ecol. Prog. Ser. 48(1), 93–97 (1988).ADS 
    Article 

    Google Scholar 
    69.Uchima, M. & Hirano, R. Swimming behavior of the marine copepod Oithona davisae: Internal control and search for environment. Mar. Biol. 99(1), 47–56 (1988).Article 

    Google Scholar 
    70.Bernardi Aubry, F., Acri, F., Bianchi, F. & Pugnetti, A. Looking for patterns in the phytoplankton community of the Mediterranean microtidal Venice Lagoon: Evidence from ten years of observations. Sci. Mar. 77(1), 47–60. https://doi.org/10.3989/scimar.03638.21A (2013).CAS 
    Article 

    Google Scholar 
    71.Facca, C. et al. Description of a Multimetric Phytoplankton Index (MPI) for the assessment of transitional waters. Mar. Pollut. Bull. 79(1–2), 145–154. https://doi.org/10.1016/j.marpolbul.2013.12.025 (2014).CAS 
    Article 
    PubMed 

    Google Scholar 
    72.Acri, F., Braga, F. & Bernardi Aubry, F. Long-term dynamics in nutrients, chlorophyll a and water quality parameters in the Lagoon of Venice. Sci. Mar. https://doi.org/10.3989/scimar.05022.30A (2020).Article 

    Google Scholar 
    73.Bandelj, V. et al. Analysis of multitrophic plankton assemblages in the Lagoon of Venice. Mar. Ecol. Prog. Ser. 368, 23–40. https://doi.org/10.3354/meps07565 (2008).ADS 
    Article 

    Google Scholar 
    74.Gubanova, A. et al. Species composition of Black Sea marine planktonic copepods. J. Mar. Syst. 135, 44–52. https://doi.org/10.1016/j.jmarsys.2013.12.004 (2014).Article 

    Google Scholar 
    75.Sacca, A., Guglielmo, L. & Bruni, V. Vertical and temporal microbial community patterns in a meromictic coastal lake influenced by the Straits of Messina upwelling system. Hydrobiology 600(1), 89–104 (2008).Article 

    Google Scholar 
    76.Tagliapietra, D., Zanon, V., Frangipane, G., Umgiesser, G. & Sigovini, M. Physiographic zoning of the Venetian Lagoon. In Scientific Research and Safeguarding of Venice (ed. Campostrini, P.) 161–164 (2010). More

  • in

    A global occurrence database of the Atlantic blue crab Callinectes sapidus

    1.Anton, A. et al. Global ecological impacts of marine exotic species. Nature Ecology & Evolution 3, 787–800, https://doi.org/10.1038/s41559-019-0851-0 (2019).Article 

    Google Scholar 
    2.Solgaard Thomsen, M. Indiscriminate data aggregation in ecological meta-analysis underestimates impacts of invasive species. Nat. Ecol. Evol. 4, 312–314, https://doi.org/10.1038/s41559-020-1117-6 (2020).Article 
    PubMed 

    Google Scholar 
    3.Tsiamis, K., Zenetos, A., Deriu, I., Gervasini, E. & Cardoso, A. C. The native distribution range of the European marine non-indigenous species. Aquat. Invasions 13, https://doi.org/10.3391/ai.2018.13.2.01 (2018).4.Korpinen, S. et al. Multiple pressures and their combined effects in Europe’s seas. ETC/ICM Technical Report 4/2019. Report No. 3944280652, 164 (European Topic Centre Inland, Coastal and Marine waters (ETC/ICM) 2020).5.Ojaveer, H. et al. Ten recommendations for advancing the assessment and management of non-indigenous species in marine ecosystems. Mar. Policy 44, 160–165, https://doi.org/10.1016/j.marpol.2013.08.019 (2014).Article 

    Google Scholar 
    6.Trebitz, A. S. et al. Early detection monitoring for aquatic non-indigenous species: optimizing surveillance, incorporating advanced technologies, and identifying research needs. J. Environ. Manage. 202, 299–310, https://doi.org/10.1016/j.jenvman.2017.07.045 (2017).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    7.Cardeccia, A. et al. Assessing biological invasions in European Seas: biological traits of the most widespread non-indigenous species. Estuar. Coast. Shelf Sci. 201, 17–28, https://doi.org/10.1016/j.ecss.2016.02.014 (2018).ADS 
    Article 

    Google Scholar 
    8.Carboneras, C. et al. A prioritised list of invasive alien species to assist the effective implementation of EU legislation. J. Appl. Ecol. 55, 539–547, https://doi.org/10.1111/1365-2664.12997 (2018).Article 

    Google Scholar 
    9.Köck, W. & Magsig, B.-O. In Handbook on Marine Environment Protection: Science, Impacts and Sustainable Management (eds Markus Salomon & Till Markus) 905-918 (Springer International Publishing, 2018).10.Tsiamis, K. et al. Prioritizing marine invasive alien species in the European Union through horizon scanning. Aquat. Conserv. 30, 794–845, https://doi.org/10.1002/aqc.3267 (2020).Article 

    Google Scholar 
    11.Witman, J. D. & Roy, K. Marine Macroecology (University of Chicago Press, 2009).12.Peterson, A. T. et al. Ecological Niches and Geographic Distributions (Princeton University Press, 2011).13.Culham, A. & Yesson, C. in Climate Change, Ecology and Systematics (eds T. Hodkinson, M. Jones, S. Waldren, & J. Parnell) 131-242 (Cambridge University Press, 2011).14.Lockwood, J. L., Hoopes, M. F. & Marchetti, M. P. Invasion Ecology (John Wiley & Sons, 2013).15.Katsanevakis, S. et al. Unpublished Mediterranean records of marine alien and cryptogenic species. Bioinvasions Rec. 9, 165–182, https://doi.org/10.3391/bir.2020.9.2.01 (2020).Article 

    Google Scholar 
    16.Meyer, C., Weigelt, P. & Kreft, H. Multidimensional biases, gaps and uncertainties in global plant occurrence information. Ecol. Lett. 19, 992–1006, https://doi.org/10.1111/ele.12624 (2016).Article 
    PubMed 

    Google Scholar 
    17.Moudrý, V. & Devillers, R. Quality and usability challenges of global marine biodiversity databases: an example for marine mammal data. Ecol. Inform. 56, 101051, https://doi.org/10.1016/j.ecoinf.2020.101051 (2020).Article 

    Google Scholar 
    18.Assis, J. et al. A fine-tuned global distribution dataset of marine forests. Sci. Data 7, 119, https://doi.org/10.1038/s41597-020-0459-x (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    19.Millikin, M. R. & Williams, A. B. Synopsis of biological data on blue crab, Callinectes sapidus Rathbun (FAO Fisheries Synopsis 38, 1984).20.Johnson, D. S. The savory swimmer swims north: a northern range extension of the blue crab Callinectes sapidus? J. Crust. Biol. 35, 105–110, https://doi.org/10.1163/1937240X-00002293 (2015).Article 

    Google Scholar 
    21.Mancinelli, G. et al. On the Atlantic blue crab (Callinectes sapidus Rathbun 1896) in southern European coastal waters: Time to turn a threat into a resource? Fish. Res. 194, 1–8, https://doi.org/10.1016/j.fishres.2017.05.002 (2017).Article 

    Google Scholar 
    22.Hines, A. H. in The Blue Crab: Callinectes sapidus (eds V. S. Kennedy & L. E. Cronin) 565-654 (Maryland Sea Grant College, 2007).23.Mancinelli, G. et al. The trophic position of the Atlantic blue crab Callinectes sapidus Rathbun 1896 in the food web of Parila Lagoon (South Eastern Adriatic, Croatia): a first assessment using stable isotopes. Mediterr. Mar. Sci. 17, 634–643, https://doi.org/10.12681/mms.1724 (2016).Article 

    Google Scholar 
    24.Mancinelli, G. et al. Trophic flexibility of the Atlantic blue crab Callinectes sapidus in invaded coastal systems of the Apulia region (SE Italy): A stable isotope analysis. Estuar. Coast. Shelf Sci. 198, 421–431, https://doi.org/10.1016/j.ecss.2017.03.013 (2017).ADS 
    CAS 
    Article 

    Google Scholar 
    25.Baird, D. & Ulanowicz, R. E. The seasonal dynamics of the Chesapeake Bay ecosystem. Ecol Monogr 59, 329–364, https://doi.org/10.2307/1943071 (1989).Article 

    Google Scholar 
    26.Silliman, B. R. & Bertness, M. D. A trophic cascade regulates salt marsh primary production. Proc. Natl. Acad. Sci. USA 99, 10500–10505, https://doi.org/10.1073/pnas.162366599 (2002).CAS 
    Article 
    PubMed 

    Google Scholar 
    27.Boudreau, S. A. & Worm, B. Ecological role of large benthic decapods in marine ecosystems: a review. Mar. Ecol. Prog. Ser. 469, 195–213, https://doi.org/10.3354/meps09862 (2012).ADS 
    Article 

    Google Scholar 
    28.Bouvier, E. L. Sur un Callinectes sapidus M. Rathbun trouvé à Rocheford. Bull. Mus. Hist. Nat. (Paris) 7, 16–17 (1901).
    Google Scholar 
    29.Giordani Soika, A. Il Neptunus pelagicus (L.) nell’alto Adriatico. Natura 42, 18–20 (1951).
    Google Scholar 
    30.Nehring, S. In In the Wrong Place – Alien Marine Crustaceans: Distribution, Biology and Impacts Vol. 6 Invading Nature – Springer Series in Invasion Ecology (eds Bella S. Galil, Paul F. Clark, & James T. Carlton) 607–624 (Springer Netherlands, 2011).31.Enzenroß, R., Enzenroß, L. & Bingel, F. Occurrence of blue crab, Callinectes sapidus (Rathbun, 1896) (Crustacea, Brachyura) on the Turkish Mediterranean and the adjacent Aegean coast and its size distribution in the bay of Iskenderun. Turk. J. Zool. 21, 113–122, https://doi.org/10.1163/001121610X538859 (1997).Article 

    Google Scholar 
    32.Mancinelli, G. et al. The Atlantic blue crab Callinectes sapidus in southern European coastal waters: distribution, impact and prospective invasion management strategies. Mar. Pollut. Bull. 119, 5–11, https://doi.org/10.1016/j.marpolbul.2017.02.050 (2017).CAS 
    Article 
    PubMed 

    Google Scholar 
    33.Labrune, C. et al. The arrival of the American blue crab, Callinectes sapidus Rathbun, 1896 (Decapoda: Brachyura: Portunidae), in the Gulf of Lions (Mediterranean Sea). Bioinvasions Rec. 8, 876–881, https://doi.org/10.3391/bir.2019.8.4.16 (2019).Article 

    Google Scholar 
    34.Cerri, J. et al. Using online questionnaires to assess marine bio-invasions: a demonstration with recreational fishers and the Atlantic blue crab Callinectes sapidus (Rathbun, 1986) along three Mediterranean countries. Mar. Pollut. Bull. 156, 111209, https://doi.org/10.1016/j.marpolbul.2020.111209 (2020).CAS 
    Article 
    PubMed 

    Google Scholar 
    35.Katsanevakis, S. et al. Impacts of invasive alien marine species on ecosystem services and biodiversity: a pan-European review. Aquat. Invasions 9, 391–423, https://doi.org/10.3391/ai.2014.9.4.01 (2014).Article 

    Google Scholar 
    36.Zenetos, A. et al. Annotated list of marine alien species in the Mediterranean with records of the worst invasive species. Mediterr. Mar. Sci. 6, 63–118, https://doi.org/10.12681/mms.186 (2005).Article 

    Google Scholar 
    37.Vilà, M. & Hulme, P. E. Impact of Biological Invasions on Ecosystem Services (Springer, 2017).38.Morais, P. et al. The Atlantic blue crab Callinectes sapidus Rathbun, 1896 expands its non-native distribution into the Ria Formosa lagoon and the Guadiana estuary (SW-Iberian Peninsula, Europe). Bioinvasions Rec. 8, 123–133, https://doi.org/10.3391/bir.2019.8.1.14 (2019).Article 

    Google Scholar 
    39.Vasconcelos, P. et al. Recent and consecutive records of the Atlantic blue crab (Callinectes sapidus Rathbun, 1896): rapid westward expansion and confirmed establishment along the Southern Coast of Portugal. Thalassas 35, 485–494, https://doi.org/10.1007/s41208-019-00163-1 (2019).Article 

    Google Scholar 
    40.Pezy, J. P., Raoux, A., Baffreau, A. & Dauvin, J. C. A well established population of the Atlantic blue crab Callinectes sapidus (Rathbun, 1896) in the English Channel? Cah. Biol. Mar. 60, 205–209 (2019).
    Google Scholar 
    41.Zenetos, A., Koutsogiannopoulos, D., Ovalis, P. & Poursanidis, D. The role played by citizen scientists in monitoring marine alien species in Greece. Cah. Biol. Mar. 54, 419–426 (2013).
    Google Scholar 
    42.Chandler, M. et al. Contribution of citizen science towards international biodiversity monitoring. Biol. Conserv. 213, 280–294, https://doi.org/10.1016/j.biocon.2016.09.004 (2017).Article 

    Google Scholar 
    43.Latombe, G. et al. A vision for global monitoring of biological invasions. Biol. Conserv. 213, 295–308, https://doi.org/10.1016/j.biocon.2016.06.013 (2017).Article 

    Google Scholar 
    44.Lucy, F. E. et al. INVASIVESNET towards an international association for open knowledge on invasive alien species. Manag. Biol. Invasion 7, 131–139, https://doi.org/10.3391/mbi.2016.7.2.01 (2016).Article 

    Google Scholar 
    45.Cardoso, A. C. et al. Citizen science and open data: A model for invasive alien species in Europe. RIO 3, e14811, https://doi.org/10.3897/rio.3.e14811 (2017).Article 

    Google Scholar 
    46.R Development Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/ (2020).47.Chamberlain, S., Ram, K. & Hart, T. spocc: Interface to Species Occurrence Data Sources. R package version 1.0.8. http://cran.r-project.org/web/packages/spocc (2020).48.Zizka, A. et al. CoordinateCleaner: Standardized cleaning of occurrence records from biological collection databases. Methods Ecol. Evol. 10, 744–751, https://doi.org/10.1111/2041-210x.13152 (2019).Article 

    Google Scholar 
    49.Freitag, A., Meyer, R. & Whiteman, L. Strategies employed by citizen science programs to increase the credibility of their data. Citiz. Sci. Theory Pr. 1, 1–11, https://doi.org/10.5334/cstp.6 (2016).Article 

    Google Scholar 
    50.Zenetos, A. et al. ELNAIS: A collaborative network on Aquatic Alien Species in Hellas (Greece). Manag. Biol. Invasion 6, 185–196, https://doi.org/10.3391/mbi.2015.6.2.09 (2015).Article 

    Google Scholar 
    51.Williams, A. B. The swimming crabs of the genus Callinectes (Decapoda: Portunidae). Fish. Bull. 72, 685–798 (1974).
    Google Scholar 
    52.Aydin, M. First record of Blue Crab Callinectes sapidus (Rathbun 1896) from the Middle Black Sea Coast. Turk. J. Marit. Mar. Sci. 3, 121–124 (2017).
    Google Scholar 
    53.Harzing, A. W. Publish or Perish, available from https://harzing.com/resources/publish-or-perish (2007).54.Mancinelli, G., Bardelli, R. & Zenetos, A. An updated dataset of the global occurrence of the Atlantic blue crab Callinectes sapidus Rathbun, 1896 (Brachyura: Portunidae). figshare https://doi.org/10.6084/m9.figshare.12896309 (2020).55.Buckley, M. W., DelSole, T., Lozier, M. S. & Li, L. Predictability of North Atlantic sea surface temperature and upper-ocean heat content. J. Clim. 32, 3005–3023, https://doi.org/10.1175/JCLI-D-18-0509.1 (2019).ADS 
    Article 

    Google Scholar 
    56.Dizdarević, S., Gajić, A., Kahrić, A. & Tomanić, J. Prvi nalaz plavog raka, Callinectes sapidus Rathbun, 1896 (Malacostraca: Portunidae), u Bosni I Hercegovini. Uzaz 12, 5–9 (2016).
    Google Scholar 
    57.Pebesma, E. et al. Sf: Simple Features for R. R package version 0.7-7. https://cran.r-project.org/web/packages/sf (2019).58.Tyberghein, L. et al. Bio-ORACLE: a global environmental dataset for marine species distribution modelling. Global Ecol. Biogeogr. 21, 272–281 (2012).Article 

    Google Scholar 
    59.McLusky, D. S. & Elliott, M. Transitional waters: a new approach, semantics or just muddying the waters? Estuar. Coast. Shelf Sci. 71, 359–363, https://doi.org/10.1016/j.ecss.2006.08.025 (2007).ADS 
    Article 

    Google Scholar 
    60.Sbrocco, E. J. & Barber, P. H. MARSPEC: ocean climate layers for marine spatial. ecology. Ecology 94, 979–979, https://doi.org/10.1890/12-1358.1 (2013).Article 

    Google Scholar 
    61.Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Clim. 37, 4302–4315, https://doi.org/10.1002/joc.5086 (2017).Article 

    Google Scholar 
    62.Domisch, S., Amatulli, G. & Jetz, W. Near-global freshwater-specific environmental variables for biodiversity analyses in 1 km resolution. Sci. Data 2, 150073, https://doi.org/10.1038/sdata.2015.73 (2015).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    63.Venter, O. et al. Global terrestrial Human Footprint maps for 1993 and 2009. Sci. Data 3, 160067, https://doi.org/10.1038/sdata.2016.67 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    64.Aiello-Lammens, M. E., Boria, R. A., Radosavljevic, A., Vilela, B. & Anderson, R. P. spThin: an R package for spatial thinning of species occurrence records for use in ecological niche models. Ecography 38, 541–545, https://doi.org/10.1111/ecog.01132 (2015).Article 

    Google Scholar 
    65.Aiello-Lammens, M. E. et al. spThin: Functions for Spatial Thinning of Species Occurrence Records forUse in Ecological Models. R package version 0.2.0. http://cran.r-project.org/web/packages/spThin (2019). More

  • in

    Agricultural land use curbs exotic invasion but sustains native plant diversity at intermediate levels

    1.Simberloff, D. et al. Impacts of biological invasions: what’s what and the way forward. Trends Ecol. Evol. 28, 58–66 (2013).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    2.Vilà, M. & Hulme, P. (eds) Impact of Biological Invasions on Ecosystem Services (Springer International Publishing, Berlin, 2017).
    Google Scholar 
    3.Gaertner, M., Den Breeyen, A., Hui, C. & Richardson, D. M. Impacts of alien plant invasions on species richness in Mediterranean-type ecosystems: a meta-analysis. Prog. Phys. Geogr. Earth Environ. 33, 319–338 (2009).Article 

    Google Scholar 
    4.Belnap, J., Phillips, S. L., Sherrod, S. K. & Moldenke, A. Soil biota can change after exotic plant invasion: does this affect ecosystem processes?. Ecology 86, 3007–3017 (2005).Article 

    Google Scholar 
    5.Liao, C. et al. Altered ecosystem carbon and nitrogen cycles by plant invasion: a meta-analysis. New Phytol. 177, 706–714 (2008).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    6.Boscutti, F. et al. Cascading effects from plant to soil elucidate how the invasive Amorpha fruticosa L. impacts dry grasslands. J. Veg. Sci. 31(4), 667–677 (2020).Article 

    Google Scholar 
    7.Pejchar, L. & Mooney, H. A. Invasive species, ecosystem services and human well-being. Trends Ecol. Evol. 24, 497–504 (2009).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    8.Vilà, M. & Ibáñez, I. Plant invasions in the landscape. Landsc. Ecol. 26, 461–472 (2011).Article 

    Google Scholar 
    9.Blackburn, T. M. et al. A proposed unified framework for biological invasions. Trends Ecol. Evol. 26(7), 333–339 (2011).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    10.Kowarik, I. On the role of alien species in urban flora and vegetation. Plant invasions: general aspects and special problems. In SPB (eds Pysek, P. et al.) 85–103 (Academic Publishing, Amsterdam, 1995).
    Google Scholar 
    11.Hulme, P. E. Climate change and biological invasions: evidence, expectations, and response options. Biol. Rev. 92(3), 1297–1313 (2017).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    12.Richardson, D. M. & Pyšek, P. Naturalization of introduced plants: ecological drivers of biogeographical patterns. New Phytol. 196(2), 383–396 (2012).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    13.Alexander, J. M. et al. Assembly of nonnative floras along elevational gradients explained by directional ecological filtering. Proc. Natl. Acad. Sci. 108, 656–661 (2011).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    14.Hulme, P. E. Relative roles of life-form, land use and climate in recent dynamics of alien plant distributions in the British Isles. Weed Res. 49(1), 19–28 (2009).Article 

    Google Scholar 
    15.Milbau, A., Stout, J. C., Graae, B. J. & Nijs, I. A hierarchical framework for integrating invasibility experiments incorporating different factors and spatial scales. Biol. Invasions 11(4), 941–950 (2009).Article 

    Google Scholar 
    16.González-Moreno, P., Diez, J. M., Ibáñez, I., Font, X. & Vilà, M. Plant invasions are context-dependent: multiscale effects of climate, human activity and habitat. Divers. Distrib. 20(6), 720–731 (2014).Article 

    Google Scholar 
    17.Bradley, B. A., Wilcove, D. S. & Oppenheimer, M. Climate change increases risk of plant invasion in the Eastern United States. Biol. Invasions 12(6), 1855–1872 (2010).Article 

    Google Scholar 
    18.Cao, Y., Zhang, S. & Hu, W. Simulated warming enhances biological invasion of Solidago canadensis and Bidens frondosa by increasing reproductive investment and altering flowering phenology pattern. Sci. Rep. 8(1), 1–8 (2018).ADS 

    Google Scholar 
    19.Molina-Montenegro, M. A. & Naya, D. E. Latitudinal patterns in phenotypic plasticity and fitness-related traits: assessing the climatic variability hypothesis (CVH) with an invasive plant species. PLoS ONE 7(10), e47620 (2012).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    20.Gritti, E. S., Smith, B. & Sykes, M. T. Vulnerability of Mediterranean Basin ecosystems to climate change and invasion by exotic plant species. J. Biogeogr. 33(1), 145–157 (2006).Article 

    Google Scholar 
    21.Colautti, R. I. & Barrett, S. C. Rapid adaptation to climate facilitates range expansion of an invasive plant. Science 342(6156), 364–366 (2013).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    22.Vitti, S., Pellegrini, E., Casolo, V., Trotta, G. & Boscutti, F. Contrasting responses of native and alien plant species to soil properties shed new light on the invasion of dune systems. J. Plant Ecol. 13, 667–675 (2020).Article 

    Google Scholar 
    23.Vilà, M., Pino, J. & Font, X. Regional assessment of plant invasions across different habitat types. J. Veg. Sci. 18, 35–42 (2007).Article 

    Google Scholar 
    24.Lambdon, P. W. et al. Alien flora of Europe: species diversity, temporal trends, geographical patterns and research needs. Preslia 80, 101–149 (2008).
    Google Scholar 
    25.Botham, M. S. et al. Do urban areas act as foci for the spread of alien plant species? An assessment of temporal trends in the UK. Divers. Distrib. 15, 338–345 (2009).Article 

    Google Scholar 
    26.Boscutti, F., Sigura, M., De Simone, S. & Marini, L. Exotic plant invasion in agricultural landscapes: A matter of dispersal mode and disturbance intensity. Appl. Veget. Sci. 21(2), 250–257 (2018).Article 

    Google Scholar 
    27.González-Moreno, P. et al. Quantifying the landscape influence on plant invasions in Mediterranean coastal habitats. Landsc. Ecol. 28(5), 891–903 (2013).Article 

    Google Scholar 
    28.Catford, J. A., Vesk, P. A., White, M. D. & Wintle, B. A. Hotspots of plant invasion predicted by propagule pressure and ecosystem characteristics. Divers. Distrib. 17(6), 1099–1110 (2011).Article 

    Google Scholar 
    29.McKinney, M. L. Urbanization, biodiversity, and conservation. The impacts of urbanization on native species are poorly studied, but educating a highly urbanized human population about these impacts can greatly improve species conservation in all ecosystems. Bio. Sci. 52, 883–890 (2002).
    Google Scholar 
    30.Mattingly, W. B. & Orrock, J. L. Historic land use influences contemporary establishment of invasive plant species. Oecologia 172(4), 1147–1157 (2013).ADS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    31.Chytrý, M. et al. Separating Habitat Invasibility by Alien Plants from the Actual Level of Invasion. Ecology 89, 1541–1553 (2008).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    32.Jauni, M. & Hyvönen, T. TInvasion level of alien plants in semi-natural agricultural habitats in boreal region. Agric. Ecosyst. Environ. 138, 109–115 (2010).Article 

    Google Scholar 
    33.Carboni, M., Thuiller, W., Izzi, F. & Acosta, A. Disentangling the relative effects of environmental versus human factors on the abundance of native and alien plant species in Mediterranean sandy shores. Divers. Distrib. 16(4), 537–546 (2010).Article 

    Google Scholar 
    34.O’Reilly-Nugent, A. et al. Landscape effects on the spread of invasive species. Curr. Landsc. Ecol. Rep. 1, 107–114 (2016).Article 

    Google Scholar 
    35.Stohlgren, T. J. et al. Species richness and patterns of invasions in plants, birds and fishes in the United States. Biol. Invasions 8, 427–444 (2006).Article 

    Google Scholar 
    36.Chytrý, M. et al. Habitat invasions by alien plants: a quantitative comparison among Mediterranean, subcontinental and oceanic regions of Europe. J. Appl. Ecol. 45, 448–458 (2008).Article 

    Google Scholar 
    37.Pyšek, P. et al. Disentangling the role of environmental and human pressures on biological invasions across Europe. Proc. Natl. Acad. Sci. 107(27), 12157–12162 (2010).ADS 
    PubMed 
    Article 

    Google Scholar 
    38.Szymura, T. H., Szymura, M., Zając, M. & Zając, A. Effect of anthropogenic factors, landscape structure, land relief, soil and climate on risk of alien plant invasion at regional scale. Sci. Total Environ. 626, 1373–1381 (2018).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    39.Marini, L. et al. Alien and native plant life-forms respond differently to human and climate pressures. Global Ecol. Biogeogr. 21, 534–544 (2012).Article 

    Google Scholar 
    40.Buccheri, M., Boscutti, F., Pellegrini, E. & Martini, F. Alien flora in Friuli Venezia Giulia. Gortania 40, 7–78 (2019) (in Italian).
    Google Scholar 
    41.Barros, A. & Pickering, C. M. Non-native plant invasion in relation to tourism use of Aconcagua Park, Argentina, the highest protected area in the Southern Hemisphere. Mt. Res. Dev. 34(1), 13–26 (2014).Article 

    Google Scholar 
    42.Boscutti, F. et al. Conservation tillage affects species composition but not species diversity: a comparative study in northern Italy. Environ. Manag. 55(2), 443–452 (2015).ADS 
    Article 

    Google Scholar 
    43.Galasso, G. et al. An updated checklist of the vascular flora alien to Italy . Plant Biosyst Int. J. Deal. Asp. Plant Biol. 152, 556–592 (2018).
    Google Scholar 
    44.Gao, T. et al. Evaluating the feasibility of using candidate DNA barcodes in discriminating species of the large Asteraceae family. BMC Evol. Biol. 10(1), 324 (2010).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    45.Gallagher, R. V., Randall, R. P. & Leishman, M. R. Trait differences between naturalized and invasive plant species independent of residence time and phylogeny. Conserv. Biol. 29(2), 360–369 (2015).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    46.Hamilton, M. A. et al. Life-history correlates of plant invasiveness at regional and continental scales. Ecol. Lett. 8, 1066–1074 (2005).Article 

    Google Scholar 
    47.Ahern, R. G., Landis, D. A., Reznicek, A. A. & Schemske, D. W. Spread of exotic plants in the landscape: the role of time, growth habit, and history of invasiveness. Biol. Invasions 12(9), 3157–3169 (2010).Article 

    Google Scholar 
    48.Ohlemüller, R., Walker, S. & Bastow Wilson, J. Local vs regional factors as determinants of the invasibility of indigenous forest fragments by alien plant species. Oikos 112, 493–501 (2006).Article 

    Google Scholar 
    49.Zhu, L., Sun, O. J., Sang, W., Li, Z. & Ma, K. Predicting the spatial distribution of an invasive plant species (Eupatorium adenophorum) in China. Landsc. Ecol. 22(8), 1143–1154 (2007).Article 

    Google Scholar 
    50.Timsina, B., Shrestha, B. B., Rokaya, M. B. & Münzbergová, Z. Impact of Parthenium hysterophorus L. invasion on plant species composition and soil properties of grassland communities in Nepal. Flora-Morphol. Distrib. Funct. Ecol. Plants 206(3), 233–240 (2011).Article 

    Google Scholar 
    51.Francis, A. P. & Currie, D. J. A globally consistent richness-climate relationship for angiosperms. Am. Nat. 161, 523–536 (2003).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    52.Currie, D. J. et al. Predictions and tests of climate-based hypotheses of broad-scale variation in taxonomic richness. Ecol. Lett. 7, 1121–1134 (2004).Article 

    Google Scholar 
    53.Tordoni, E. et al. Climate and landscape heterogeneity drive spatial pattern of endemic plant diversity within local hotspots in South-Eastern Alps. Perspect. Plant. Ecol. 43, 125512 (2020).Article 

    Google Scholar 
    54.Alpert, P., Bone, E. & Holzapfel, C. Invasiveness, invisibility and the role of environmental stress in the spread of non-native plants. Perspect. Plant Ecol. Evol. Syst. 3, 52–66 (2000).Article 

    Google Scholar 
    55.Richardson, D. & Pyšek, P. Plant invasions: merging the concepts of species invasiveness and community invasibility. Prog. Phys. Geogr. 30, 409 (2006).Article 

    Google Scholar 
    56.Marini, L. et al. Beta diversity and alien plant invasion. Global Ecol. Biogeogr. 22, 450–460 (2013).Article 

    Google Scholar 
    57.Haider, S. et al. Mountain roads and non-native species modify elevational patterns of plant diversity. Global Ecol. Biogeogr. 27, 667–678 (2018).Article 

    Google Scholar 
    58.Qian, H. & Ricklefs, R. E. The role of exotic species in homogenizing the North American flora. Ecol. Lett. 9(12), 1293–1298 (2006).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    59.Roy, D. B., Hill, M. O. & Rothery, P. Effects of urban land cover on the local species pool in Britain. Ecography 22, 507–515 (1999).Article 

    Google Scholar 
    60.McIntyre, S. & Lavorel, S. Predicting richness of native, rare, and exotic plants in response to habitat and disturbance variables across a variegated landscape. Conserv. Biol. 8(2), 521–531 (1994).Article 

    Google Scholar 
    61.Aikio, S., Duncan, R. P. & Hulme, P. E. The vulnerability of habitats to plant invasion: disentangling the roles of propagule pressure, time and sampling effort. Glob. Ecol. Biogeogr. 21, 778–786 (2012).Article 

    Google Scholar 
    62.Cilliers, S. S., Williams, N. S. G. & Barnard, F. J. Patterns of exotic plant invasions in fragmented urban and rural grasslands across continents. Landsc. Ecol. 23, 1243–1256 (2008).Article 

    Google Scholar 
    63.Pyšek, P. Alien and native species in Central European urban floras: a quantitative comparison. J. Biogeogr. 25, 155–163 (1998).Article 

    Google Scholar 
    64.Hulme, P.E. Nursery crimes: agriculture as victim and perpetrator in the spread of invasive species. Crop Sci. Technol. 733–740 (2005).65.McDougall, K. L. et al. Running off the road: roadside non-native plants invading mountain vegetation. Biol. Invasions 20, 3461–3473 (2018).Article 

    Google Scholar 
    66.Groves, R. H., Austin, M. P. & Kaye, P. E. Competition between Australian native and introduced grasses along a nutrient gradient. Austral. Ecol. 28, 491–498 (2003).Article 

    Google Scholar 
    67.Dupouey, J. L., Dambrine, E., Laffite, J. D. & Moares, C. Irreversible impact of past land use on forest soils and biodiversity. Ecology 83(11), 2978–2984 (2002).Article 

    Google Scholar 
    68.Foster, D. et al. The importance of land-use legacies to ecology and conservation. Bioscience 53(1), 77–88 (2003).Article 

    Google Scholar 
    69.Spooner, P. G. & Lunt, I. D. The influence of land-use history on roadside conservation values in an Australian agricultural landscape. Aust. J. Bot. 52, 445–458 (2004).Article 

    Google Scholar 
    70.Lindborg, R., Plue, J., Andersson, K. & Cousins, S. A. O. Function of small habitat elements for enhancing plant diversity in different agricultural landscapes. Biol. Conserv. 169, 206–213 (2014).Article 

    Google Scholar 
    71.Dorrough, J. & Scroggie, M. P. Plant responses to agricultural intensification. J. Appl. Ecol. 45(4), 1274–1283 (2008).Article 

    Google Scholar 
    72.Stoate, C. et al. Ecological impacts of arable intensification in Europe. J. Environ. Manag. 63, 337–365 (2001).CAS 
    Article 

    Google Scholar 
    73.Deutschewitz, K., Lausch, A., Kühn, I. & Klotz, S. Native and alien plant species richness in relation to spatial heterogeneity on a regional scale in Germany. Glob. Ecol. Biogeogr. 12(4), 299–311 (2003).Article 

    Google Scholar 
    74.Grime, J. P. Plant Strategies and Vegetation Processes (Wiley, Chichester, 1979).
    Google Scholar 
    75.Molino, J. F. & Sabatier, D. Tree diversity in tropical rain forests: a validation of the intermediate disturbance hypothesis. Science 294(5547), 1702–1704 (2001).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    76.Tscharntke, T., Klein, A. M., Kruess, A., Steffan-Dewenter, I. & Thies, C. Landscape perspectives on agricultural intensification and biodiversity-ecosystem service management. Ecol. Lett. 8, 857–874 (2005).Article 

    Google Scholar 
    77.Carulli, G.B. Carta geologica del Friuli Venezia Giulia (scale 1:150000) (Geological Map of Friuli Venezia Giulia, scale 1:150000). Ed. S.E.L.C.A. Firenze (2006).78.Gortani, L. & Gortani, M. Flora friulana con particolare riguardo alla Carnia. Udine: ed. Tipografia Doretti (in Italian) (1906).79.Bonfanti, P., Fregonese, A. & Sigura, M. Landscape analysis in areas affected by land consolidation. Landsc. Urban Plan. 37(1–2), 91–98 (1997).Article 

    Google Scholar 
    80.Ehrendorfer, F. & Hamann, U. Vorschläge zu einer floristischen Kartierung von Mitteleuropa. Berichte der Deutschen Botanischen Gesellschaft (in German) (1965).81.Bartolucci, F. et al. An updated checklist of the vascular flora native to Italy . Plant Biosyst. Int. J. Deal. Asp. Plant Biol. 152, 179–303 (2018).
    Google Scholar 
    82.Engelen, G., Lavalle, C., Barredo, J. I., Van der Meulen, M. & White, R. The moland modelling framework for urban and regional land-use dynamics. In Modelling Land-Use Change: Progress and Applications (eds Koomen, E. et al.) 297–320 (Springer , Berlin, 2007).
    Google Scholar 
    83.Quantum GIS Development Team. QGIS Geographic Information System. Open Source Geospatial Foundation Project (2017).84.Dormann, C. F. et al. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36, 27–46 (2013).Article 

    Google Scholar 
    85.Fox, J. & Weisberg, S. An R Companion to Applied Regression (Sage Publications , Thousand Oaks, 2011).
    Google Scholar 
    86.Dormann, C. F. et al. Effects of landscape structure and land-use intensity on similarity of plant and animal communities. Glob. Ecol. Biogeogr. 16, 774–787 (2007).Article 

    Google Scholar 
    87.Pinheiro, J. C. & Bates, D. M. Mixed-Effects Models in S and S-Plus (Springer , Berlin, 2000).
    Google Scholar 
    88.R Core Team R. A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna, 2019).
    Google Scholar 
    89.Barton, K. MuMIn: Multi-model inference. R package version 1.15.6 (2016).90.Pinheiro, J., Bates, D., Debroy, S., Sarkar, D. & R core team nlme: Linear and Nonlinear Mixed Effects Models. R package version 3.1–131 (2017).91.Burham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference—A Pratical Information-Theoretic Approach (Springer , Berlin, 2002).
    Google Scholar  More

  • in

    Subgenomic flavivirus RNA (sfRNA) associated with Asian lineage Zika virus identified in three species of Ugandan bats (family Pteropodidae)

    Preparation of positive controls for molecular testingZIKV strains MR766, PRVABC59, and DakAR41525 were separately propagated on Vero cells (ATCC CCL-81). Cell supernatant was harvested 72 hpi, and RNA extraction was performed using Trizol. Due to undetectable RNA concentration, the maximum input volume of 11 µL was used for cDNA generation using the SuperScript IV First-Strand Synthesis System with random hexamers (Thermo Fisher Scientific, Waltham, MA, United States). A ten-fold dilution series of RNA was generated for each strain to validate detection of phylogenetically divergent strains of ZIKV using our primer set. For all molecular assays, 3 µL of 10−3 of MR766 was used experimentally as the positive control. Propagation of ZIKV was conducted under CSU biosafety protocol 17-059B.Infection protocol, RNA Extraction, and cDNA synthesis for A129 mice and Jamaican fruit batsAll animal studies were carried out in accordance with ARRIVE guidelines and all procedures approved by and carried out under the Colorado State University Institutional Animal Care and Use Committee (protocol 15-6677AA). Three sub-adult male A129 mice and three female Jamaican fruit bats (Artibeus jamaicensis) were obtained from their respective breeding colonies at Colorado State University. Mice were subcutaneously inoculated with 1 × 103 PFU supernatant from PRVABC59-infected Vero cells, and bats were subcutaneously inoculated with 7.5 × 105 PFU supernatant from Vero cells infected with one of three strains (either PRVABC59, MR766, or DakAR41525; one strain per individual). Mice were euthanized at 7 days post-infection (dpi). The bat infected with ZIKV strain MR766 was euthanized at 28 dpi, while the two bats infected with strains PRVABC59 and DakAR41525 were euthanized at 45 dpi to provide a broader of time window in which to characterize sfRNA persistence. Organs and blood were harvested and placed into DMEM supplemented with 1% penicillin/streptomycin (Thermo Fisher Scientific, Waltham, MA, United States) and 10% FBS (Atlas Biologicals, Fort Collins, CO, United States) and stored at − 80 °C until RNA extraction using the Mag-Bind Viral DNA/RNA 96 kit (Omega Bio-Tek Inc., Norcross, GA, United States) on the KingFisher Flex Magnetic Particle Processor (Thermo Fisher Scientific, Waltham, MA, United States). RNA was eluted in 30 µL nuclease-free water.Droplet digital PCR (ddPCR) to detect ZIKV sfRNATo detect ZIKV sfRNA, primers were designed to target the 3′ UTR of multiple strains of ZIKV according to recommended ddPCR primer design guidelines, resulting in an amplicon 123 bp in length (F: TTCCCCACCCTTYAATCTGG and R: TGGTCTTTCCCAGCGTCAAT). Each reaction consisted of 50 ng cDNA, 125 nM foward primer, 125 nM reverse primer, and 10 µL QX200 ddPCR EvaGreen Supermix (Bio-Rad Laboratories, Hercules, CA, United States). Following reaction preparation, 20 µL of reaction and 60 µL of QX200 Droplet Generation Oil for EvaGreen (Bio-Rad Laboratories, Hercules, CA, United States) were loaded into a DG8 Cartridge for droplet generation in the QX200 Droplet Generator (Bio-Rad Laboratories, Hercules, CA, United States). Following droplet generation, plates were sealed in the PX1 PCR Plate Sealer (Bio-Rad Laboratories, Hercules, CA, United States). PCR was performed on a T100 Thermal Cycler (Bio-Rad Laboratories, Hercules, CA, United States), using the following cycling parameters: 95 °C for 5 min, 40 cycles of 95 °C for 30 s followed by 57.5 °C for 1 min, 4 °C for 5 min, 90 °C for 5 min, and held at 4 °C until reading the plate. Plates were read on the QX200 Droplet Reader (Bio-Rad Laboratories, Hercules, CA, United States). Analysis was performed by two individuals using QuantaSoft Software (Bio-Rad Laboratories, Hercules, CA, United States) to determine results.Gradient PCR was performed to identify the optimal annealing temperature, resulting in selection of 57.5 °C (Fig. S1). At this annealing temperature, the ddPCR reaction using the 3′ UTR primers successfully amplified ZIKV strains MR766, DakAR41525, and PRVABC59 (Fig. S2). As an additional and more biologically relevant sample type, 50 ng cDNA from the organs of A129 mice experimentally infected with ZIKV PRVABC59 were tested using this same assay; successful ZIKV sfRNA amplification was obtained from mouse kidney and spleen (Fig. S2). Blood and tissue samples from the three female Jamaican fruit bats were tested in duplicate on the QX200 Droplet Digital (ddPCR) System (Bio-Rad Laboratories, Hercules, CA, United States) using the ZIKV sfRNA primers as described above.Testing of archived samples from free-ranging Ugandan batsThis study utilized archived tissue samples from bats previously captured in Uganda from 2009 to 201318,26 (Table 1). Bats were captured using harp traps or mist nets, identified using a field guide specific to East African bats, and placed in holding bags prior to anesthesia via halothane and euthanasia by cervical dislocation27. This study used historic archived samples from a previous study, in which all bat captures and sampling were conducted under the approval of CDC IACUC protocols 1731AMMULX and 010-015 and carried out according to ARRIVE guidelines. RNA was extracted from frozen tissue homogenates (spleen, and in some cases both spleen and liver separately) using the MagMax 96 total RNA isolation kit (Applied Biosystems, Foster City, CA, United States), and cDNA generation was performed as above. To confirm RNA integrity via amplification of a housekeeping gene, we used previously published primers demonstrated to amplify GAPDH from two Old World bat species (black flying fox and Egyptian rousette bat) and one New World bat species (common vampire bat) (F: GTCGCCATCAATGACCCCTTC and R: TTCAAGTGAGCCCCAGCC)31. For samples with undetectable RNA concentration on the Qubit RNA HS assay, 6 µL cDNA was used as input. ddPCR was performed as above, except that an annealing temperature of 60˚C was used. Plates were read as above, and only samples deemed ‘suspect’ or ‘positive’ for GAPDH amplification were subjected to ddPCR testing with ZIKV sfRNA (3′ UTR). For these samples, the same volume of input cDNA was used to test for the presence of ZIKV sfRNA in duplicate; results were analyzed by two individuals.Table 1 All bat species and trap sites collected from 2009 to 201318,26.Full size tableSequence confirmationTo confirm specific amplification of GAPDH sequence for each of the 8 Old World species, the same primers were used in a conventional PCR assay using GoTaq HotStart Polymerase (Promega corporation, Madison, WI, United States). Cycling parameters were as follows: 95 °C for 2 min; 35 cycles of 95 °C for 1 min, 57.5 °C for 1 min, and 72 °C for 30 s; followed by 72 °C for 5 min and samples were held at 4 °C until being analyzed for the presence of a 248-bp amplicon via gel electrophoresis. Amplicons were verified by Sanger sequencing (GENEWIZ, Inc., South Plainfield NJ, United States). Results obtained from Sanger sequencing were subjected to quality analysis prior to aligning forward and reverse reads, and the consensus read was subjected to a BLAST search.Confirmation of ZIKV sfRNA ddPCR results in Ugandan bat samples using conventional PCR and sequencingSamples deemed ‘suspect’ via screening on the ddPCR system with ZIKV 3′ UTR primers were subjected to additional PCR and Sanger sequencing using the same primer set targeting the 3′ UTR of ZIKV. ZIKV strain MR766 was used as a positive control in these assays. Samples were considered ‘suspect’ if (1) the automatically-defined threshold yielded ≥ 1 positive droplet in the same 1D amplitude as the positive control cDNA (ZIKV MR766) or (2) the negative droplet populations existed in the same 1D amplitude region of positive control droplets and thus, precluded the ability to differentiate positive and negative populations. The cDNA from these samples was amplified using the GoTaq HotStart system (Promega corporation, Madison, WI, United States), with each reaction consisting of 50 ng cDNA, 25 µL GoTaq HotStart Master Mix, 400 nM forward primer, 400 nM reverse primer, and 1 M Betaine. Cycling parameters were as follows: 95 °C for 2 min; 35 cycles of 95 °C for 1 min, 57.5 °C for 1 min, and 72 °C for 30 s; followed by 72 °C for 5 min and samples were held at 4 °C until being analyzed for the presence of a 123-bp amplicon via gel electrophoresis. Positive samples were verified by Sanger sequencing (GENEWIZ, Inc., South Plainfield NJ, United States). Results obtained from Sanger sequencing were subjected to quality analysis prior to BLAST search and subsequent alignment of forward and reverse reads with the 3′ UTR of ZIKV MR766 in Geneious v11.1.5 (www.geneious.com).Comparison of detection sensitivity between sfRNA and NS5 in field-caught samplesThe four samples from which ZIKV sfRNA was amplified were subjected to cPCR amplification with GoTaq HotStart MasterMix as described above and primers designed for this study targeting NS5 from MR766, PRVABC59, and DakAR41525 in order to compare detection sensitivity (F: TGC CGC CAC CAA GAT GAA CT, R: CAT TCT CCC TTT CCA TGG ATT GAC C). Cycling parameters were as follows: 95 °C for 2 min; 35 cycles of 95 °C for 1 min, 57.5 °C for 1 min, and 72 °C for 30 s; followed by 72 °C for 5 min and samples were held at 4 °C. cDNA from ZIKV MR766 was used as a positive control. Results were sent for Sanger sequencing if a band was present. All methods in this study were carried out in accordance with relevant guidelines and regulations. More

  • in

    Author Correction: Rebuilding marine life

    Red Sea Research Center (RSRC), King Abdullah University of Science and Technology, Thuwal, Saudi ArabiaCarlos M. Duarte, Susana Agusti & Milica PredragovicArctic Research Centre, Department of Biology, Aarhus University, Aarhus, DenmarkCarlos M. DuarteComputational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, Thuwal, Saudi ArabiaCarlos M. DuarteDepartment of Economics, Colorado State University, Fort Collins, CO, USAEdward BarbierDepartment of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, USAGregory L. BrittenDepartamento de Ecología, Facultad de Ciencias Biológicas and Centro Interdisciplinario de Cambio Global, Pontificia Universidad Católica de Chile, Santiago, ChileJuan Carlos CastillaLaboratoire d’Océanographie de Villefranche, Sorbonne Université, CNRS, Villefranche-sur-Mer, FranceJean-Pierre GattusoInstitute for Sustainable Development and International Relations, Sciences Po, Paris, FranceJean-Pierre GattusoMonegasque Association on Ocean Acidification, Prince Albert II of Monaco Foundation, Monaco, MonacoJean-Pierre GattusoDepartment of Earth & Environment, Boston University, Boston, MA, USARobinson W. FulweilerDepartment of Biology, Boston University, Boston, MA, USARobinson W. FulweilerAustralian Research Council Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Queensland, AustraliaTerry P. HughesNational Museum of Natural History, Smithsonian Institution, Washington, DC, USANancy KnowltonSchool of Biological Sciences, The University of Queensland, St Lucia, Queensland, AustraliaCatherine E. LovelockDepartment of Biology, Dalhousie University, Halifax, Nova Scotia, CanadaHeike K. Lotze & Boris WormAlfred Wegener Institute, Integrative Ecophysiology, Bremerhaven, GermanyElvira PoloczanskaDepartment of Environment and Geography, University of York, York, UKCallum Roberts More