More stories

  • in

    Environmental factors shape the epiphytic bacterial communities of Gracilariopsis lemaneiformis

    1.Roth-Schulze, A. J. et al. Functional biogeography and host specificity of bacterial communities associated with the Marine Green Alga Ulva spp. Mol. Ecol. 27, 1952–1965 (2018).PubMed 
    Article 

    Google Scholar 
    2.Teagle, H., Hawkins, S. J., Moore, P. J. & Smale, D. A. The role of kelp species as biogenic habitat formers in coastal marine ecosystems. J. Exp. Mar. Biol. Ecol. 492, 81–98 (2017).Article 

    Google Scholar 
    3.Goecke, F., Labes, A., Wiese, J. & Imhoff, J. F. Chemical interactions between marine macroalgae and bacteria. Mar. Ecol. Prog. Ser. 409, 267–300 (2010).ADS 
    CAS 
    Article 

    Google Scholar 
    4.Singh, R. P. & Reddy, C. R. K. Seaweed-microbial interactions: Key functions of seaweed-associated bacteria. FEMS Microbiol. Ecol. 88, 213–230 (2014).CAS 
    PubMed 
    Article 

    Google Scholar 
    5.Ramanan, R., Kim, B. H., Cho, D. H., Oh, H. M. & Kim, H. S. Algae-bacteria interactions: Evolution, ecology and emerging applications. Biotechnol. Adv. 34, 14–29 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    6.Ismail, A. et al. Antimicrobial activities of bacteria associated with the brown alga padina pavonica. Front. Microbiol. 7, 1–13 (2016).
    Google Scholar 
    7.Sañudo-Wilhelmy, S. A., Gómez-Consarnau, L., Suffridge, C. & Webb, E. A. The role of B vitamins in marine biogeochemistry. Ann. Rev. Mar. Sci. 6, 339–367 (2014).PubMed 
    Article 

    Google Scholar 
    8.Karthick, P. & Mohanraju, R. Antimicrobial potential of epiphytic bacteria associated with seaweeds of little Andaman, India. Front. Microbiol. 9, 1–11 (2018).Article 

    Google Scholar 
    9.El Shafay, S. M., Ali, S. S. & El-Sheekh, M. M. Antimicrobial activity of some seaweeds species from Red sea, against multidrug resistant bacteria. Egypt. J. Aquat. Res. 42, 65–74 (2016).Article 

    Google Scholar 
    10.Dobretsov, S. V. & Qian, P. Y. Effect of bacteria associated with the green alga Ulva reticulata on marine micro- and macrofouling. Biofouling 18, 217–228 (2002).Article 

    Google Scholar 
    11.Mieszkin, S., Callow, M. E. & Callow, J. A. Interactions between microbial biofilms and marine fouling algae: A mini review. Biofouling 29, 1097–1113 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    12.Burke, C., Thomas, T., Lewis, M., Steinberg, P. & Kjelleberg, S. Composition, uniqueness and variability of the epiphytic bacterial community of the green alga Ulva australis. ISME J. 5, 590–600 (2010).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    13.Tujula, N. A. et al. Variability and abundance of the epiphytic bacterial community associated with a green marine Ulvacean alga. ISME J. 4, 301–311 (2010).PubMed 
    Article 

    Google Scholar 
    14.Burke, C., Steinberg, P., Rusch, D., Kjelleberg, S. & Thomas, T. Bacterial community assembly based on functional genes rather than species. Proc. Natl. Acad. Sci. 108, 14288–14293 (2011).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    15.Roth-Schulze, A. J., Zozaya-Valdés, E., Steinberg, P. D. & Thomas, T. Partitioning of functional and taxonomic diversity in surface-associated microbial communities. Environ. Microbiol. 18, 4391–4402 (2016).PubMed 
    Article 

    Google Scholar 
    16.Selvarajan, R. et al. Distribution, interaction and functional profiles of epiphytic bacterial communities from the rocky intertidal seaweeds, South Africa. Sci. Rep. 9, 1–13 (2019).ADS 
    Article 
    CAS 

    Google Scholar 
    17.Aires, T., Serrão, E. A. & Engelen, A. H. Host and environmental specificity in bacterial communities associated to two highly invasive marine species (genus Asparagopsis). Front. Microbiol. 7, 1–14 (2016).Article 

    Google Scholar 
    18.Lachnit, T., Fischer, M., Künzel, S., Baines, J. F. & Harder, T. Compounds associated with algal surfaces mediate epiphytic colonization of the marine macroalga Fucus vesiculosus. FEMS Microbiol. Ecol. 84, 411–420 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    19.Nylund, G. M. et al. The red alga Bonnemaisonia asparagoides regulates epiphytic bacterial abundance and community composition by chemical defence. FEMS Microbiol. Ecol. 71, 84–93 (2010).CAS 
    PubMed 
    Article 

    Google Scholar 
    20.Campbell, A. H., Marzinelli, E. M., Gelber, J. & Steinberg, P. D. Spatial variability of microbial assemblages associated with a dominant habitat-forming seaweed. Front. Microbiol. 6, 1–10 (2015).Article 

    Google Scholar 
    21.Munday, P. L. Competitive coexistence of coral-dwelling fishes: The lottery hypothesis revisited. Ecology 85, 623–628 (2004).Article 

    Google Scholar 
    22.Geange, S. W., Poulos, D. E., Stier, A. C. & McCormick, M. I. The relative influence of abundance and priority effects on colonization success in a coral-reef fish. Coral Reefs 36, 151–155 (2017).ADS 
    Article 

    Google Scholar 
    23.Stratil, S. B., Neulinger, S. C., Knecht, H., Friedrichs, A. K. & Wahl, M. Temperature-driven shifts in the epibiotic bacterial community composition of the brown macroalga Fucus vesiculosus. Microbiologyopen 2, 338–349 (2013).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    24.Stratil, S. B., Neulinger, S. C., Knecht, H., Friedrichs, A. K. & Wahl, M. Salinity affects compositional traits of epibacterial communities on the brown macroalga Fucus vesiculosus. FEMS Microbiol. Ecol. 88, 272–279 (2014).CAS 
    PubMed 
    Article 

    Google Scholar 
    25.Zhang, Y. et al. Effect of salinity on the microbial community and performance on anaerobic digestion of marine macroalgae. J. Chem. Technol. Biotechnol. 92, 2392–2399 (2017).CAS 
    Article 

    Google Scholar 
    26.Liao, L. & Xu, Y. Effects of nitrogen nutrients on growth and epiphytic bacterial composition in sea weed Gracilaria lemaneiformis. Fish. Sci. 28, 130–135 (2009).ADS 
    CAS 

    Google Scholar 
    27.Zozaya-Valdés, E., Roth-Schulze, A. J. & Thomas, T. Effects of temperature stress and aquarium conditions on the red macroalga Delisea pulchra and its associated microbial community. Front. Microbiol. 7, 1–10 (2016).Article 

    Google Scholar 
    28.Nemergut, D. R. et al. Patterns and processes of microbial community assembly. Microbiol. Mol. Biol. Rev. 77, 342–356 (2013).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    29.Liu, X. et al. Isolation and pathogenicity identification of bacterial pathogens in bleached disease and their physiological effects on the red macroalga Gracilaria lemaneiformis. Aquat. Bot. 153, 1–7 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    30.Xie, X. et al. Large-scale seaweed cultivation diverges water and sediment microbial communities in the coast of Nan’ao Island, South China Sea. Sci. Total Environ. 598, 97–108 (2017).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    31.Yang, Y. et al. Cultivation of seaweed Gracilaria in Chinese coastal waters and its contribution to environmental improvements. Algal Res. 9, 236–244 (2015).Article 

    Google Scholar 
    32.Lindström, E. S. & Langenheder, S. Local and regional factors influencing bacterial community assembly. Environ. Microbiol. Rep. 4, 1–9 (2012).PubMed 
    Article 

    Google Scholar 
    33.Hellweger, F. L., Van Sebille, E. & Fredrick, N. D. Biogeographic patterns in ocean microbes emerge in a neutral agent-based model. Science (80-. ). 345, 1346–1349 (2014).34.Longford, S. R. et al. Comparisons of diversity of bacterial communities associated with three sessile marine eukaryotes. Aquat. Microb. Ecol. 48, 217–229 (2007).Article 

    Google Scholar 
    35.Lachnit, T., Meske, D., Wahl, M., Harder, T. & Schmitz, R. Epibacterial community patterns on marine macroalgae are host-specific but temporally variable. Environ. Microbiol. 13, 655–665 (2010).PubMed 
    Article 

    Google Scholar 
    36.Pei, P. et al. Effects of biological water purification grid on microbial community of culture environment and intestine of the shrimp Litopenaeus vannamei. Aquac. Res. 50, 1300–1312 (2019).CAS 
    Article 

    Google Scholar 
    37.Shade, A. & Handelsman, J. Beyond the Venn diagram: The hunt for a core microbiome. Environ. Microbiol. 14, 4–12 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    38.Spoerner, M., Wichard, T., Bachhuber, T., Stratmann, J. & Oertel, W. Growth and thallus morphogenesis of Ulva mutabilis (chlorophyta) depends on a combination of two bacterial species excreting regulatory factors. J. Phycol. 48, 1433–1447 (2012).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    39.Kessler, R. W., Weiss, A., Kuegler, S., Hermes, C. & Wichard, T. Macroalgal–bacterial interactions: Role of dimethylsulfoniopropionate in microbial gardening by Ulva (Chlorophyta). Mol. Ecol. 27, 1808–1819 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    40.Malmstrom, R. R., Kiene, R. P. & Kirchman, D. L. Identification and enumeration of bacteria assimilating dimethylsulfoniopropionate (DMSP) in the North Atlantic and Gulf of Mexico. Limnol. Oceanogr. 49, 597–606 (2004).ADS 
    CAS 
    Article 

    Google Scholar 
    41.Holmström, C., Egan, S., Franks, A., McCloy, S. & Kjelleberg, S. Antifouling activities expressed by marine surface associated Pseudoalteromonas species. FEMS Microbiol. Ecol. 41, 47–58 (2002).PubMed 
    Article 

    Google Scholar 
    42.Holmström, C. & Kjelleberg, S. The effect of external biological factors on settlement of marine invertebrate and new antifouling technology. Biofouling 8, 147–160 (1994).Article 

    Google Scholar 
    43.Lachnit, T., Blümel, M., Imhoff, J. F. & Wahl, M. Specific epibacterial communities on macroalgae : Phylogeny matters more than habitat. Aquat. Biol. 5, 181–186 (2009).Article 

    Google Scholar 
    44.Fan, X. et al. The effect of nutrient concentrations, nutrient ratios and temperature on photosynthesis and nutrient uptake by Ulva prolifera : Implications for the explosion in green tides. J. Appl. Phycol. 26, 537–544 (2014).CAS 
    Article 

    Google Scholar 
    45.Van Alstyne, K. L. Seawater nitrogen concentration and light independently alter performance, growth, and resource allocation in the bloom-forming seaweeds Ulva lactuca and Ulvaria obscura ( Chlorophyta ). Harmful Algae 78, 27–35 (2018).PubMed 
    Article 
    CAS 

    Google Scholar 
    46.Lachnit, T., Wahl, M. & Harder, T. Isolated thallus-associated compounds from the macroalga Fucus vesiculosus mediate bacterial surface colonization in the field similar to that on the natural alga. Biofouling 26, 247–255 (2010).CAS 
    PubMed 
    Article 

    Google Scholar 
    47.Su, H. et al. Persistence and spatial variation of antibiotic resistance genes and bacterial populations change in reared shrimp in South China. Environ. Int. 119, 327–333 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    48.Ekwanzala, M. D., Dewar, J. B. & Momba, M. N. B. Environmental resistome risks of wastewaters and aquatic environments deciphered by shotgun metagenomic assembly. Ecotoxicol. Environ. Saf. 197, 110612 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    49.Numberger, D. et al. Characterization of bacterial communities in wastewater with enhanced taxonomic resolution by full-length 16S rRNA sequencing. Sci. Rep. 9, 1–14 (2019).CAS 
    Article 

    Google Scholar 
    50.Teklehaimanot, G. Z., Genthe, B., Kamika, I. & Momba, M. N. B. Prevalence of enteropathogenic bacteria in treated effluents and receiving water bodies and their potential health risks. Sci. Total Environ. 518–519, 441–449 (2015).ADS 
    PubMed 
    Article 
    CAS 

    Google Scholar 
    51.Kelley, S. E. Experimental studies of the evolutionary significance of sexual reproduction. V. A field test of the sib-competition hypotheses. Evolution (N. Y). 43, 1066 (1989).52.Browne, L. & Karubian, J. Rare genotype advantage promotes survival and genetic diversity of a tropical palm. New Phytol. 218, 1658–1667 (2018).PubMed 
    Article 

    Google Scholar 
    53.Gressler, V. et al. Lipid, fatty acid, protein, amino acid and ash contents in four Brazilian red algae species. Food Chem. 120, 585–590 (2010).CAS 
    Article 

    Google Scholar 
    54.Gu, D. et al. Purification of R-phycoerythrin from Gracilaria lemaneiformis by centrifugal precipitation chromatography. J. Chromatogr. B Anal. Technol. Biomed. Life Sci. 1087–1088, 138–141 (2018).55.Su, Y. bin et al. Pyruvate cycle increases aminoglycoside efficacy and provides respiratory energy in bacteria. Proc. Natl. Acad. Sci. U. S. A. 115, E1578–E1587 (2018).56.Hollants, J., Leliaert, F., De Clerck, O. & Willems, A. What we can learn from sushi: A review on seaweed-bacterial associations. FEMS Microbiol. Ecol. 83, 1–16 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    57.AQSIQ. Specifications for Oceanographic Survey. Part 4: Survey of Chemical Parameters in Sea Water. 16–26 (Standards Press of China, 2007).58.Burke, C., Kjelleberg, S. & Thomas, T. Selective extraction of bacterial DNA from the surfaces of macroalgae. Appl. Environ. Microbiol. 75, 252–256 (2009).CAS 
    PubMed 
    Article 

    Google Scholar 
    59.Xu, Y., Le, G. & Zhang, Y. Comparison with several methods to isolate epiphytic bacteria from Gracilaria lemaneiformis (Rhodophyta). Microbiol. China 34, 123–126 (2007).
    Google Scholar 
    60.Pei, P. et al. Analysis of the bacterial community composition of the epiphytes on diseased Gracilaria lemaneiformis using PCR-DGGE fingerprinting technology. J. Fish. Sci. China 25 (2018).61.Takahashi, S., Tomita, J., Nishioka, K., Hisada, T. & Nishijima, M. Development of a prokaryotic universal primer for simultaneous analysis of bacteria and archaea using next-generation sequencing. PLoS One 9 (2014).62.Bokulich, N. A. et al. Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing. Nat. Methods 10, 57–59 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    63.Liu, T. et al. Joining Illumina paired-end reads for classifying phylogenetic marker sequences. BMC Bioinform. 21, 1–13 (2020).Article 

    Google Scholar 
    64.Edgar, R. C., Haas, B. J., Clemente, J. C., Quince, C. & Knight, R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–2200 (2011).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    65.Edgar, R. C. UPARSE: Highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 10, 996–998 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    66.Cole, J. R. et al. Ribosomal database project: Data and tools for high throughput rRNA analysis. Nucleic Acids Res. 42, 633–642 (2014).Article 
    CAS 

    Google Scholar 
    67.Quast, C. et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 41, 590–596 (2013).Article 
    CAS 

    Google Scholar 
    68.Wang, Y. et al. Comparison of the levels of bacterial diversity in freshwater, intertidal wetland, and marine sediments by using millions of illumina tags. Appl. Environ. Microbiol. 78, 8264–8271 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    69.Somerfield, P. J. Identification of the Bray-Curtis similarity index: Comment on Yoshioka (2008). Mar. Ecol. Prog. Ser. 372, 303–306 (2008).ADS 
    Article 

    Google Scholar 
    70.Higgins, M. A., Robbins, G. A., Maas, K. R. & Binkhorst, G. K. Use of bacteria community analysis to distinguish groundwater recharge sources to shallow wells. J. Environ. Qual. 49, 1530–1540 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    71.Yang, J., Ma, L., Jiang, H., Wu, G. & Dong, H. Salinity shapes microbial diversity and community structure in surface sediments of the Qinghai-Tibetan Lakes. Sci. Rep. 6, 6–11 (2016).ADS 
    Article 
    CAS 

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

    Google Scholar  More

  • in

    Distance to native climatic niche margins explains establishment success of alien mammals

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

    Google Scholar 
    2.Guisan, A. et al. Predicting species distributions for conservation decisions. Ecol. Lett. 16, 1424–1435 (2013).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    3.Richardson, D. M. Fifty Years of Invasion Ecology: The Legacy of Charles Elton. (John Wiley & Sons, 2011).4.Soberón, J. Grinnellian and Eltonian niches and geographic distributions of species. Ecol. Lett. 10, 1115–1123 (2007).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    5.Brown, J. H. Patterns, modes and extents of invasions by vertebrates. Biological Invasions: A Global Perspective. 85–110 (John Wiley & Sons, 1989).6.Holt, R. D., Barfield, M. & Gomulkiewicz, R. Theories of niche conservatism and evolution: could exotic species be potential tests. in: Species Invasions: Insights into Ecology, Evolution and Biogeography (eds. Sax, Stachowicz & Gaines) 259–290 (Sinauer Associates, Mass, 2005).7.Brown, J. H., Stevens, G. C. & Kaufman, D. M. The geographic range: size, shape, boundaries, and internal structure. Annu. Rev. Ecol. Syst. 27, 597–623 (1996).Article 

    Google Scholar 
    8.Sagarin, R. D., Gaines, S. D. & Gaylord, B. Moving beyond assumptions to understand abundance distributions across the ranges of species. Trends Ecol. Evol. 21, 524–530 (2006).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    9.Guisan, A., Petitpierre, B., Broennimann, O., Daehler, C. & Kueffer, C. Unifying niche shift studies: insights from biological invasions. Trends Ecol. Evol. 29, 260–269 (2014).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    10.Forsyth, D. M., Duncan, R. P., Bomford, M. & Moore, G. Climatic suitability, life-history traits, introduction effort, and the establishment and spread of introduced mammals in Australia. Conserv. Biol. 18, 557–569 (2004).Article 

    Google Scholar 
    11.Bomford, M., Kraus, F., Barry, S. C. & Lawrence, E. Predicting establishment success for alien reptiles and amphibians: a role for climate matching. Biol. Invasions 11, 713–724 (2009).Article 

    Google Scholar 
    12.Petitpierre, B. et al. Climatic niche shifts are rare among terrestrial plant invaders. Science 335, 1344–1348 (2012).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    13.Liu, C., Wolter, C., Xian, W. & Jeschke, J. M. Most invasive species largely conserve their climatic niche. Proc. Natl Acad. Sci. U.S.A. 117, 23643–23651 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    14.Pearman, P. B., Guisan, A., Broennimann, O. & Randin, C. F. Niche dynamics in space and time. Trends Ecol. Evol. 23, 149–158 (2008).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    15.González-Suárez, M., Bacher, S. & Jeschke, J. M. Intraspecific trait variation is correlated with establishment success of alien mammals. Am. Nat. 185, 737–746 (2015).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    16.Redding, D. W. et al. Location-level processes drive the establishment of alien bird populations worldwide. Nature https://doi.org/10.1038/s41586-019-1292-2 (2019).17.Titeux, N. et al. The need for large-scale distribution data to estimate regional changes in species richness under future climate change. Divers. Distrib. 23, 1393–1407 (2017).Article 

    Google Scholar 
    18.Chevalier, M., Broennimann, O., Cornuault, J., & Guisan, A. Data integration methods to account for spatial niche truncation effects in regional projections of species distribution. Ecol. Appl. (in press).19.Blackburn, T. M. & Duncan, R. P. Determinants of establishment success in introduced birds. Nature 414, 195–197 (2001).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    20.Bacon, S. J., Aebi, A., Calanca, P. & Bacher, S. Quarantine arthropod invasions in Europe: the role of climate, hosts and propagule pressure. Divers. Distrib. 20, 84–94 (2014).Article 

    Google Scholar 
    21.Abellán, P., Tella, J. L., Carrete, M., Cardador, L. & Anadón, J. D. Climate matching drives spread rate but not establishment success in recent unintentional bird introductions. Proc. Natl Acad. Sci. 114, 9385–9390 (2017).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    22.Long, J. L. Introduced Mammals of the World: Their History, Distribution and Influence. (CSIRO PUBLISHING, 2003).23.Pulliam, H. R. On the relationship between niche and distribution. Ecol. Lett. 3, 349–361 (2000).Article 

    Google Scholar 
    24.Godsoe, W., Jankowski, J., Holt, R. D. & Gravel, D. Integrating biogeography with contemporary niche theory. Trends Ecol. Evol. 32, 488–499 (2017).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    25.Sax, D. F., Early, R. & Bellemare, J. Niche syndromes, species extinction risks, and management under climate change. Trends Ecol. Evol. 28, 517–523 (2013).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    26.Csergő, A. M. et al. Less favourable climates constrain demographic strategies in plants. Ecol. Lett. 20, 969–980 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    27.Capellini, I., Baker, J., Allen, W. L., Street, S. E. & Venditti, C. The role of life history traits in mammalian invasion success. Ecol. Lett. 18, 1099–1107 (2015).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    28.Sol, D., Bacher, S., Reader, S. M., & Lefebvre, L. Brain size predicts the success of mammal species introduced into novel environments. American Naturalist 172(S1), S63–S71 (2008).Article 

    Google Scholar 
    29.Duncan, R. P., Blackburn, T. M., Rossinelli, S. & Bacher, S. Quantifying invasion risk: the relationship between establishment probability and founding population size. Methods Ecol. Evol. 5, 1255–1263 (2014).Article 

    Google Scholar 
    30.Allen, C. R. et al. Predictors of regional establishment success and spread of introduced non-indigenous vertebrates. Glob. Ecol. Biogeogr. 22, 889–899 (2013).Article 

    Google Scholar 
    31.Cassey, P., Delean, S., Lockwood, J. L., Sadowski, J. S. & Blackburn, T. M. Dissecting the null model for biological invasions: A meta-analysis of the propagule pressure effect. PLoS Biol. 16, e2005987 (2018).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    32.Buswell, J. M., Moles, A. T. & Hartley, S. Is rapid evolution common in introduced plant species? J. Ecol. 99, 214–224 (2011).Article 

    Google Scholar 
    33.Broennimann, O., Mráz, P., Petitpierre, B., Guisan, A. & Müller-Schärer, H. Contrasting spatio-temporal climatic niche dynamics during the eastern and western invasions of spotted knapweed in North America. J. Biogeogr. 41, 1126–1136 (2014).Article 

    Google Scholar 
    34.Shea, K. & Chesson, P. Community ecology theory as a framework for biological invasions. Trends Ecol. Evol. 17, 170–176 (2002).Article 

    Google Scholar 
    35.Facon, B. et al. A general eco-evolutionary framework for understanding bioinvasions. Trends Ecol. Evol. 21, 130–135 (2006).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    36.Escobar, L. E., Qiao, H., Cabello, J. & Townsend Peterson, A. Ecological niche modeling re-examined: a case study with the Darwin’s fox. Ecol. Evolut. 8, 4757–4770 (2018).Article 

    Google Scholar 
    37.Petitpierre, B. et al. Will climate change increase the risk of plant invasions into mountains? Ecol. Appl. 26, 530–544 (2016).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    38.Pheloung, P. C., Williams, P. A. & Halloy, S. R. A weed risk assessment model for use as a biosecurity tool evaluating plant introductions. J. Environ. Manag. 57, 239–251 (1999).Article 

    Google Scholar 
    39.Pluess, T. et al. Which factors affect the success or failure of eradication campaigns against alien species? PLoS One 7, e48157 (2012).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    40.Pyšek, P. et al. MAcroecological Framework for Invasive Aliens (MAFIA): disentangling large-scale context dependence in biological invasions. NeoBiota 62, 407–461 (2020).Article 

    Google Scholar 
    41.Lonsdale, W. M. Global patterns of plant invasions and the concept of invasibility. Ecology 80, 1522 (1999).Article 

    Google Scholar 
    42.Leung, B. et al. TEASIng apart alien species risk assessments: a framework for best practices. Ecol. Lett. 15, 1475–1493 (2012).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    43.Fourcade, Y. Comparing species distributions modelled from occurrence data and from expert-based range maps. Implication for predicting range shifts with climate change. Ecol. Inform. 36, 8–14 (2016).Article 

    Google Scholar 
    44.Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2005).Article 

    Google Scholar 
    45.Zomer, R. J., Trabucco, A., Bossio, D. A. & Verchot, L. V. Climate change mitigation: A spatial analysis of global land suitability for clean development mechanism afforestation and reforestation. Agriculture. Ecosyst. Environ. 126, 67–80 (2008).Article 

    Google Scholar 
    46.Bellard, C. et al. Will climate change promote future invasions? Glob. Chang. Biol. 19, 3740–3748 (2013).ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    47.Broennimann, O. et al. Measuring ecological niche overlap from occurrence and spatial environmental data. Glob. Ecol. Biogeogr. 21, 481–497 (2012).Article 

    Google Scholar 
    48.Cola, V. D. et al. ecospat: an R package to support spatial analyses and modeling of species niches and distributions. Ecography 40, 774–787 (2017).Article 

    Google Scholar 
    49.Hurlbert, A. H. & Jetz, W. Species richness, hotspots, and the scale dependence of range maps in ecology and conservation. Proc. Natl Acad. Sci. U.S.A. 104, 13384–13389 (2007).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    50.Plummer, M. JAGS: a program for analysis of Bayesian graphical models using Gibbs sampling. in Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC 2003), March 20–22, Vienna, Austria. (2003).51.R Core Team. R: a language and environment for statistical computing. (2014).52.Su, Y.-S. & Yajima, M. R2jags: a package for running jags from R. (2013).53.Gelman, A. Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper). Bayesian Anal. 1, 515–534 (2006).MathSciNet 
    MATH 

    Google Scholar 
    54.Little, R. & Rubin, D. Statistical Analysis with Missing Data, Second Edition. (Wiley Series in Probability and Statistics, 2002).55.Gelman, A. & Rubin, D. B. Inference from iterative simulation using multiple sequences. Stat. Sci. 7, 457–472 (1992).MATH 

    Google Scholar 
    56.Gelman, A., Meng, X.-L. & Stern, H. Posterior predictive assessment of model fitness via realized discrepancies. Stat. Sin. 6, 733–760 (1996).MathSciNet 
    MATH 

    Google Scholar 
    57.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 
    58.Guisan, A., Thuiller, W. & Zimmermann, N. E. Habitat Suitability and Distribution Models: With Applications in R. (Cambridge University Press, 2017).59.Broennimann, O., et al. Distance to native climatic niche margins explains establishment success of alien mammals. ecospat/NMI: NMI v1.0. Zenodo. https://doi.org/10.5281/zenodo.4588999. (2021). More

  • in

    SMART targets for meaningful action

    Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain
    the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in
    Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles
    and JavaScript. More

  • in

    Potential of indigenous crop microbiomes for sustainable agriculture

    1.Savci, S. An agricultural pollutant: chemical fertilizer. Int. J. Environ. Sci. Dev. 3, 77–80 (2012).CAS 

    Google Scholar 
    2.Guo, J. H. et al. Significant acidification in major Chinese croplands. Science 327, 1008–1010 (2010).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    3.Raza, S. et al. Dramatic loss of inorganic carbon by nitrogen‐induced soil acidification in Chinese croplands. Glob. Change Biol. 26, 3738–3751 (2020).ADS 
    Article 

    Google Scholar 
    4.Jez, J. M., Lee, S. G. & Sherp, A. M. The next green movement: plant biology for the environment and sustainability. Science 353, 1241–1244 (2016).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    5.Cordovez, V., Dini-Andreote, F., Carrion, V. J. & Raaijmakers, J. M. Ecology and evolution of plant microbiomes. Annu. Rev. Microbiol. 73, 69–88 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    6.Duran, P. et al. Microbial interkingdom interactions in roots promote Arabidopsis survival. Cell 175, 973–983.e914 (2018).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    7.Dini-Andreote, F. & Raaijmakers, J. M. Embracing community ecology in plant microbiome research. Trends Plant Sci. 23, 467–469 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    8.de Vries, F. T., Griffiths, R. I., Knight, C. G., Nicolitch, O. & Williams, A. Harnessing rhizosphere microbiomes for drought-resilient crop production. Science 368, 270–274 (2020).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    9.Hubbard, C. J. et al. The effect of rhizosphere microbes outweighs host plant genetics in reducing insect herbivory. Mol. Ecol. 28, 1801–1811 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    10.Oldroyd, G. E. D. & Leyser, O. A plant’s diet, surviving in a variable nutrient environment. Science 368, eaba0196 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    11.Tedersoo, L., Bahram, M. & Zobel, M. How mycorrhizal associations drive plant population and community biology. Science 367, eaba1223 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    12.Martín‐Robles, N. et al. Impacts of domestication on the arbuscular mycorrhizal symbiosis of 27 crop species. New Phytol. 218, 322–334 (2018).PubMed 
    Article 

    Google Scholar 
    13.Genre, A., Lanfranco, L., Perotto, S. & Bonfante, P. Unique and common traits in mycorrhizal symbioses. Nat. Rev. Microbiol. 18, 649–660 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    14.Liu, X. et al. Partitioning of soil phosphorus among arbuscular and ectomycorrhizal trees in tropical and subtropical forests. Ecol. Lett. 21, 713–723 (2018).PubMed 
    Article 

    Google Scholar 
    15.Varoquaux, N. et al. Transcriptomic analysis of field-droughted sorghum from seedling to maturity reveals biotic and metabolic responses. Proc. Natl Acad. Sci. USA 116, 27124–27132 (2019).CAS 
    Article 

    Google Scholar 
    16.Lazcano, C., Barrios-Masias, F. H. & Jackson, L. E. Arbuscular mycorrhizal effects on plant water relations and soil greenhouse gas emissions under changing moisture regimes. Soil Biol. Biochem. 74, 184–192 (2014).CAS 
    Article 

    Google Scholar 
    17.Sprent, J. I. Evolving ideas of legume evolution and diversity: a taxonomic perspective on the occurrence of nodulation. New Phytol. 174, 11–25 (2007).CAS 
    PubMed 
    Article 

    Google Scholar 
    18.Soltis, D. E. et al. Chloroplast gene sequence data suggest a single origin of the predisposition for symbiotic nitrogen fixation in angiosperms. Proc. Natl Acad. Sci. USA 92, 2647–2651 (1995).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    19.Young, N. D. et al. The Medicago genome provides insight into the evolution of rhizobial symbioses. Nature 480, 520–524 (2011).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    20.van Velzen, R. et al. Comparative genomics of the nonlegume Parasponia reveals insights into evolution of nitrogen-fixing Rhizobium symbioses. Proc. Natl Acad. Sci. USA 115, E4700–E4709 (2018).PubMed 
    Article 
    CAS 

    Google Scholar 
    21.Smil, V. Nitrogen in crop production: an account of global flows. Glob. Biogeochem. Cycles 13, 647–662 (1999).ADS 
    CAS 
    Article 

    Google Scholar 
    22.O’Hara, G. W. The role of nitrogen fixation in crop production. J. Crop Prod. 1, 115–138 (1998).Article 

    Google Scholar 
    23.Remigi, P., Zhu, J., Young, J. P. W. & Masson-Boivin, C. Symbiosis within symbiosis: evolving nitrogen-fixing legume symbionts. Trends Microbiol. 24, 63–75 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    24.Garcia, K., Delaux, P. M., Cope, K. R. & Ané, J. M. Molecular signals required for the establishment and maintenance of ectomycorrhizal symbioses. New Phytol. 208, 79–87 (2015).PubMed 
    Article 

    Google Scholar 
    25.Fisher, R. F. & Long, S. R. Rhizobium–plant signal exchange. Nature 357, 655–660 (1992).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    26.Cao, Y., Halane, M. K., Gassmann, W. & Stacey, G. The role of plant innate immunity in the legume–Rhizobium symbiosis. Annu. Rev. Plant Biol. 68, 535–561 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    27.Ferguson, B. J. et al. Legume nodulation: the host controls the party. Plant Cell Environ. 42, 41–51 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    28.Remans, R. et al. Effect of Rhizobium–Azospirillum coinoculation on nitrogen fixation and yield of two contrasting Phaseolus vulgaris L. genotypes cultivated across different environments in Cuba. Plant Soil 312, 25–37 (2008).CAS 
    Article 

    Google Scholar 
    29.Cassán, F. & Diaz-Zorita, M. Azospirillum sp. in current agriculture: from the laboratory to the field. Soil Biol. Biochem. 103, 117–130 (2016).Article 
    CAS 

    Google Scholar 
    30.Han, Q. et al. Variation in rhizosphere microbial communities and its association with the symbiotic efficiency of rhizobia in soybean. ISME J. 14, 1915–1928 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    31.Saharan, B. S. & Nehra, V. Plant growth promoting rhizobacteria: a critical review. Life Sci. Med. Res. 21, 30 (2011).
    Google Scholar 
    32.Cheng, Y. T., Zhang, L. & He, S. Y. Plant–microbe interactions facing environmental challenge. Cell Host Microbe 26, 183–192 (2019).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    33.Dini-Andreote, F. Endophytes: the second layer of plant defense. Trends Plant Sci. 25, 319–322 (2020).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    34.Carrión, V. J. et al. Pathogen-induced activation of disease-suppressive functions in the endophytic root microbiome. Science 366, 606–612 (2019).ADS 
    Article 
    CAS 

    Google Scholar 
    35.Sieber, M. et al. Neutrality in the metaorganism. PLoS Biol. 17, e3000298 (2019).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    36.Trivedi, P., Leach, J. E., Tringe, S. G., Sa, T. & Singh, B. K. Plant–microbiome interactions: from community assembly to plant health. Nat. Rev. Microbiol. 18, 607–621 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    37.Burns, A. R. et al. Contribution of neutral processes to the assembly of gut microbial communities in the zebrafish over host development. ISME J. 10, 655–664 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    38.Sloan, W. T. et al. Quantifying the roles of immigration and chance in shaping prokaryote community structure. Environ. Microbiol. 8, 732–740 (2006).PubMed 
    Article 

    Google Scholar 
    39.Ning, D., Deng, Y., Tiedje, J. M. & Zhou, J. A general framework for quantitatively assessing ecological stochasticity. Proc. Natl Acad. Sci. USA 116, 16892–16898 (2019).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    40.Carlström, C. I. et al. Synthetic microbiota reveal priority effects and keystone strains in the Arabidopsis phyllosphere. Nat. Ecol. Evol. 3, 1445–1454 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    41.Purugganan, M. D. & Fuller, D. Q. The nature of selection during plant domestication. Nature 457, 843–848 (2009).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    42.Chen, Y. H., Gols, R. & Benrey, B. Crop domestication and its impact on naturally selected trophic interactions. Annu. Rev. Entomol. 60, 35–58 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    43.Szoboszlay, M. et al. Comparison of root system architecture and rhizosphere microbial communities of Balsas teosinte and domesticated corn cultivars. Soil Biol. Biochem. 80, 34–44 (2015).CAS 
    Article 

    Google Scholar 
    44.Perez-Jaramillo, J. E., Mendes, R. & Raaijmakers, J. M. Impact of plant domestication on rhizosphere microbiome assembly and functions. Plant Mol. Biol. 90, 635–644 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    45.Perez-Jaramillo, J. E., Carrion, V. J., de Hollander, M. & Raaijmakers, J. M. The wild side of plant microbiomes. Microbiome 6, 143 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    46.Emmett, B. D., Buckley, D. H., Smith, M. E. & Drinkwater, L. E. Eighty years of maize breeding alters plant nitrogen acquisition but not rhizosphere bacterial community composition. Plant Soil 431, 53–69 (2018).CAS 
    Article 

    Google Scholar 
    47.Mutch, L. A. & Young, J. P. W. Diversity and specificity of Rhizobium leguminosarum biovar viciae on wild and cultivated legumes. Mol. Ecol. 13, 2435–2444 (2004).CAS 
    PubMed 
    Article 

    Google Scholar 
    48.Kiers, E. T., Hutton, M. G. & Denison, R. F. Human selection and the relaxation of legume defences against ineffective rhizobia. Proc. R. Soc. B 274, 3119–3126 (2007).CAS 
    PubMed 
    Article 

    Google Scholar 
    49.Pérez-Jaramillo, J. E. et al. Linking rhizosphere microbiome composition of wild and domesticated Phaseolus vulgaris to genotypic and root phenotypic traits. ISME J. 11, 2244–2257 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    50.Zachow, C., Müller, H., Tilcher, R. & Berg, G. Differences between the rhizosphere microbiome of Beta vulgaris ssp. maritima—ancestor of all beet crops—and modern sugar beets. Front. Microbiol. 5, 415 (2014).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    51.Coleman‐Derr, D. et al. Plant compartment and biogeography affect microbiome composition in cultivated and native Agave species. New Phytol. 209, 798–811 (2016).PubMed 
    Article 
    CAS 

    Google Scholar 
    52.Warschefsky, E., Penmetsa, R. V., Cook, D. R. & von Wettberg, E. J. Back to the wilds: tapping evolutionary adaptations for resilient crops through systematic hybridization with crop wild relatives. Am. J. Bot. 101, 1791–1800 (2014).PubMed 
    Article 

    Google Scholar 
    53.Brozynska, M., Furtado, A. & Henry, R. J. Genomics of crop wild relatives: expanding the gene pool for crop improvement. Plant Biotechnol. J. 14, 1070–1085 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    54.Zhang, H., Mittal, N., Leamy, L. J., Barazani, O. & Song, B. H. Back into the wild—apply untapped genetic diversity of wild relatives for crop improvement. Evol. Appl. 10, 5–24 (2017).PubMed 
    Article 

    Google Scholar 
    55.Maxted, N. & Kell, S. P. Establishment of a Global Network for the In Situ Conservation of Crop Wild Relatives: Status and Needs (FAO Commission on Genetic Resources for Food and Agriculture, 2009).56.Stenberg, J. A., Heil, M., Åhman, I. & Björkman, C. Optimizing crops for biocontrol of pests and disease. Trends Plant Sci. 20, 698–712 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    57.Heil, M. & Baldwin, I. T. Fitness costs of induced resistance: emerging experimental support for a slippery concept. Trends Plant Sci. 7, 61–67 (2002).CAS 
    PubMed 
    Article 

    Google Scholar 
    58.Liu, H. & Brettell, L. E. Plant defense by VOC-induced microbial priming. Trends Plant Sci. 24, 187–189 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    59.Schulz-Bohm, K. et al. Calling from distance: attraction of soil bacteria by plant root volatiles. ISME J. 12, 1252–1262 (2018).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    60.Ehlers, B. K. et al. Plant secondary compounds in soil and their role in belowground species interactions. Trends Ecol. Evol. 35, 716–730 (2020).PubMed 
    Article 

    Google Scholar 
    61.Preece, C. & Penuelas, J. A return to the wild: root exudates and food security. Trends Plant Sci. 25, 14–21 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    62.Rasmann, S. et al. Recruitment of entomopathogenic nematodes by insect-damaged maize roots. Nature 434, 732–737 (2005).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    63.Köllner, T. G. et al. A maize (E)-β-caryophyllene synthase implicated in indirect defense responses against herbivores is not expressed in most American maize varieties. Plant Cell 20, 482–494 (2008).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    64.Lebeis, S. L. et al. Salicylic acid modulates colonization of the root microbiome by specific bacterial taxa. Science 349, 860–864 (2015).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    65.Vorholt, J. A., Vogel, C., Carlstrom, C. I. & Muller, D. B. Establishing causality: opportunities of synthetic communities for plant microbiome research. Cell Host Microbe 22, 142–155 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    66.Zhang, J. et al. NRT1.1B is associated with root microbiota composition and nitrogen use in field-grown rice. Nat. Biotechnol. 37, 676–684 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    67.Hatzenpichler, R., Krukenberg, V., Spietz, R. L. & Jay, Z. J. Next-generation physiology approaches to study microbiome function at single cell level. Nat. Rev. Microbiol. 18, 241–256 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    68.Cui, L., Zhang, D., Yang, K., Zhang, X. & Zhu, Y. G. Perspective on surface-enhanced Raman spectroscopic investigation of microbial world. Anal. Chem. 91, 15345–15354 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    69.Wang, Y., Huang, W. E., Cui, L. & Wagner, M. Single cell stable isotope probing in microbiology using Raman microspectroscopy. Curr. Opin. Biotechnol. 41, 34–42 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    70.Cui, L. et al. Functional single-cell approach to probing nitrogen-fixing bacteria in soil communities by resonance Raman spectroscopy with 15N2 labeling. Anal. Chem. 90, 5082–5089 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    71.Yang, K. et al. Rapid antibiotic susceptibility testing of pathogenic bacteria using heavy-water-labeled single-cell Raman spectroscopy in clinical samples. Anal. Chem. 91, 6296–6303 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    72.Li, H. Z. et al. D2O-isotope-labeling approach to probing phosphate-solubilizing bacteria in complex soil communities by single-cell Raman spectroscopy. Anal. Chem. 91, 2239–2246 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    73.Moutia, J.-F. Y., Saumtally, S., Spaepen, S. & Vanderleyden, J. Plant growth promotion by Azospirillum sp. in sugarcane is influenced by genotype and drought stress. Plant Soil 337, 233–242 (2010).CAS 
    Article 

    Google Scholar 
    74.Bashan, Y. & De-Bashan, L. E. How the plant growth-promoting bacterium Azospirillum promotes plant growth—a critical assessment. Adv. Agron. 108, 77–136 (2010).CAS 
    Article 

    Google Scholar 
    75.Figueiredo, M. V. B., Burity, H. A., Martínez, C. R. & Chanway, C. P. Alleviation of drought stress in the common bean (Phaseolus vulgaris L.) by co-inoculation with Paenibacillus polymyxa and Rhizobium tropici. Appl. Soil Ecol. 40, 182–188 (2008).Article 

    Google Scholar 
    76.Uma, C., Sivagurunathan, P. & Sangeetha, D. Performance of bradyrhizobial isolates under drought conditions. Int. J. Curr. Microbiol. App. Sci. 2, 228–232 (2013).
    Google Scholar 
    77.Tank, N. & Saraf, M. Salinity-resistant plant growth promoting rhizobacteria ameliorates sodium chloride stress on tomato plants. J. Plant Interact. 5, 51–58 (2010).CAS 
    Article 

    Google Scholar 
    78.Tahir, H. A. et al. Plant growth promotion by volatile organic compounds produced by Bacillus subtilis SYST2. Front. Microbiol. 8, 171 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    79.Vardharajula, S., Zulfikar Ali, S., Grover, M., Reddy, G. & Bandi, V. Drought-tolerant plant growth promoting Bacillus spp.: effect on growth, osmolytes, and antioxidant status of maize under drought stress. J. Plant Interact. 6, 1–14 (2011).CAS 
    Article 

    Google Scholar 
    80.Santoyo, G., Orozco-Mosqueda, M. D. C. & Govindappa, M. Mechanisms of biocontrol and plant growth-promoting activity in soil bacterial species of Bacillus and Pseudomonas: a review. Biocontrol Sci. Technol. 22, 855–872 (2012).Article 

    Google Scholar 
    81.Leclere, V. et al. Mycosubtilin overproduction by Bacillus subtilis BBG100 enhances the organism’s antagonistic and biocontrol activities. Appl. Environ. Microbiol. 71, 4577–4584 (2005).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    82.Hu, J. et al. Probiotic Pseudomonas communities enhance plant growth and nutrient assimilation via diversity-mediated ecosystem functioning. Soil Biol. Biochem. 113, 122–129 (2017).CAS 
    Article 

    Google Scholar 
    83.Kohler, J., Hernández, J. A., Caravaca, F. & Roldán, A. Plant-growth-promoting rhizobacteria and arbuscular mycorrhizal fungi modify alleviation biochemical mechanisms in water-stressed plants. Funct. Plant Biol. 35, 141–151 (2008).CAS 
    PubMed 
    Article 

    Google Scholar 
    84.Nassar, A. H., El-Tarabily, K. A. & Sivasithamparam, K. Growth promotion of bean (Phaseolus vulgaris L.) by a polyamine-producing isolate of Streptomyces griseoluteus. Plant Growth Reg. 40, 97–106 (2003).CAS 
    Article 

    Google Scholar 
    85.Gopalakrishnan, S. et al. Evaluation of Streptomyces strains isolated from herbal vermicompost for their plant growth-promotion traits in rice. Microbiol. Res. 169, 40–48 (2014).CAS 
    PubMed 
    Article 

    Google Scholar 
    86.Kwak, M.-J. et al. Rhizosphere microbiome structure alters to enable wilt resistance in tomato. Nat. Biotechnol. 36, 1100–1109 (2018).CAS 
    Article 

    Google Scholar 
    87.Sang, M. K. & Kim, K. D. The volatile‐producing Flavobacterium johnsoniae strain GSE09 shows biocontrol activity against Phytophthora capsici in pepper. J. Appl. Microbiol. 113, 383–398 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    88.Naznin, H. A. et al. Systemic resistance induced by volatile organic compounds emitted by plant growth-promoting fungi in Arabidopsis thaliana. PLoS ONE 9, e86882 (2014).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    89.Kiss, L., Russell, J. C., Szentiványi, O., Xu, X. & Jeffries, P. Biology and biocontrol potential of Ampelomyces mycoparasites, natural antagonists of powdery mildew fungi. Biocontrol Sci. Technol. 14, 635–651 (2004).Article 

    Google Scholar 
    90.Lee, S., Yap, M., Behringer, G., Hung, R. & Bennett, J. W. Volatile organic compounds emitted by Trichoderma species mediate plant growth. Fungal Biol. Biotechnol. 3, 1–14 (2016).CAS 
    Article 

    Google Scholar 
    91.Zhang, S., Gan, Y. & Xu, B. Application of plant-growth-promoting fungi Trichoderma longibrachiatum t6 enhances tolerance of wheat to salt stress through improvement of antioxidative defense system and gene expression. Front. Plant Sci. 7, 1405 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    92.van der Meij, A., Worsley, S. F., Hutchings, M. I. & van Wezel, G. P. Chemical ecology of antibiotic production by Actinomycetes. FEMS Microbiol. Rev. 41, 392–416 (2017).PubMed 
    Article 
    CAS 

    Google Scholar 
    93.Bhatti, A. A., Haq, S. & Bhat, R. A. Actinomycetes benefaction role in soil and plant health. Microb. Pathog. 111, 458–467 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    94.Chaurasia, A. et al. Actinomycetes: an unexplored microorganisms for plant growth promotion and biocontrol in vegetable crops. World J. Microbiol. Biotechnol. 34, 1–16 (2018).Article 

    Google Scholar 
    95.Ercoli, L., Schüßler, A., Arduini, I. & Pellegrino, E. Strong increase of durum wheat iron and zinc content by field-inoculation with arbuscular mycorrhizal fungi at different soil nitrogen availabilities. Plant Soil 419, 153–167 (2017).CAS 
    Article 

    Google Scholar 
    96.Xu, L. et al. Arbuscular mycorrhiza enhances drought tolerance of tomato plants by regulating the 14-3-3 genes in the ABA signaling pathway. Appl. Soil Ecol. 125, 213–221 (2018).Article 

    Google Scholar 
    97.Ghorchiani, M., Etesami, H. & Alikhani, H. A. Improvement of growth and yield of maize under water stress by co-inoculating an arbuscular mycorrhizal fungus and a plant growth promoting rhizobacterium together with phosphate fertilizers. Agric. Ecosyst. Environ. 258, 59–70 (2018).CAS 
    Article 

    Google Scholar 
    98.Meeds, J. A. et al. Phosphorus deficiencies invoke optimal allocation of exoenzymes by ectomycorrhizas. ISME J. https://doi.org/10.1038/s41396-020-00864-z (2021). More

  • in

    An integrative approach reveals a new species of flightless leaf beetle (Chrysomelidae: Suinzona) from South Korea

    Description of Suinzona borowieci sp. nov. (Figs. 1, 2 and 3)Figure 1Morphology of Suinzona borowieci sp. nov. and related species: (a,b) Holotype of S. borowieci sp. nov. (a) Dorsal habitus, (b) lateral habitus; (c–e) exposed hind wing, (c) S. borowieci sp. nov., (d) S. cyrtonoides, (e) Potaninia assamensis; (f–g) aedeagus with everted internal sac (left) and flagellum (right); (f) S. borowieci sp. nov., (g) S. cyrtonoides.Full size imageFigure 2Genitalia of Suinzona borowieci sp. nov. and related species: (a–d) S. borowieci sp. nov. (a) Aedeagus, dorsal view; (b) aedeagus, lateral view; (c) aedeagus, apical view; (d) spermatheca. (e) Aedeagus of Suinzona cyrtonoides, apical view.Full size imageFigure 3Distribution map of Suinzona and sampling sites: (a) Distribution of Suinzona species in China, South Korea and Japan, (b) type locality and collection sites of Suinzona borowieci sp. nov. in South Korea. Records of distribution are taken from Ge et al.3, Suzuki et al.21 and the results of this work. The map is redrawn and modified from National Geographic Information Institute of Korea (https://www.ngii.go.kr).Full size imageFamily Chrysomelidae Latreille, 1802Subfamily Chrysomelinae Latreille, 1802Genus Suinzona Chen, 1931Type localitySouth Korea: Gyeongbuk Province, Yeongyang County, Irwolsan Mountain, 36° 48′ 30.42″ N, 129° 5′ 23.56″ E, ca. 1135 m.Type materialHolotype: male (NMPC), South Korea: Gyeongbuk Prov., Yeongyang, Mt. Irwolsan, 36° 48′ 30.42″ N, 129° 5′ 23.56″ E, ca. 1135 m, 12.VI.2011, H.W. Cho // HOLOTYPUS Suinzona borowieci sp. n. Cho & Kim 2020. Paratype: SOUTH KOREA – Gyeongbuk Prov.: 1 female (NMPC), same data as holotype plus PARATYPUS Suinzona borowieci sp. n. Cho & Kim 2020; 1 female (HCC), same data as holotype except 31.VII.2004; 1 female (HCC), same data as holotype except 31.VII.2004; 4 males 2 females (HCC), same data as holotype except 22.V.2009; 8 males 2 females (HCC), same data as holotype except 25.VI.2010; 4 males 2 females (HCC), same data as holotype except 10.VI.2017; 1 male 1 female (HCC), same data as holotype except 17.VI.2017; 1 male (HCC), same data as holotype except 36° 48′ 11.74″ N, 129° 6′ 10.01″ E, ca. 1190 m, 17.V.2020; 3 males 1 female (HCC), same data as holotype except 7.VI.2020; 2 males (KNAE), Yeongyang, Irwol-myeon, Mt. Irwolsan, 7.VI.2014, J.K. Park // I14_KNAE483613 // I14_KNAE483649; 1 male 1 female (HCC), Bongwha, Myeongho-myeon, Bukgok-ri, Mt. Cheongnyangsan, 36° 47′ 47″ N, 128° 54′ 30″ E, 21–22.V.2015, J.S. Lee; 1 female (HCC), Daegu, Dong-gu, Mt. Palgongsan, 21.V.1998; 2 males 1 female (HCC), Gunwi, Bugye-myeon, Dongsan-ri, Mt. Palgongsan, 9.V.2009, S.S. Jung; 1 male 1 female (HCC), Yecheon, Bomun-myeon, Urae-ri, Mt. Hakgasan, 26.V.2010, Y.J. You; 1 male (HCC), Yecheon, Bomun-myeon, Mt. Hakgasan, 36° 40′ 32.16″ N, 128° 35′ 38.24″ E, ca. 330 m, 3.VI.2020, H.W. Cho; 1 female (HCC), Cheongsong, Hyeonseo-myeon, Galcheon-ri, 26.V.2004, H.W. Cho; Gangwon Prov.: 2 females (HCC), Taebaek, Hwangji-dong, Mt. Hambaeksan, 37° 9′ 53.22″ N, 128° 55′ 1.35″ E, ca. 1470 m, 6.VI.2005, H.W. Cho; 2 males 3 females (HCC), same data as preceding one except 6.VI.2006; 1 female (HCC), same data as preceding one except 29.V.2009; 1 female (HCC), same data as preceding one except 10.VI.2017; 1 female (HCC), same data as preceding one except 5.VI.2020; Chungnam Prov.: 1 male (HCC), Buyeo, Gyuam-myeon, Sumok-ri, 1–15.VI.2005, J.W. Lee.Other materialSix mature larvae (HCC), same data as holotype except 29.VI.2017; 5 mature larvae (HCC), Gangwon Prov., Taebaek, Hwangji-dong, Mt. Hambaeksan, 19.VI.2006, H.W. Cho; 8 mature larvae (HCC), Gyeongbuk Prov., Yecheon, Bomun-myeon, Mt. Hakgasan, 31.V.2020, H.W. Cho; 7 mature larvae (HCC), same data as preceding one except 3.VI.2020.DiagnosisSuinzona borowieci sp. nov. is almost identical to S. cyrtonoides in the shape of the flagellum of the aedeagus. However, it can be distinguished by its larger body size (5.5–7.0 mm vs. 4.8–6.0 mm), denser punctures on elytra (less dense punctures in S. cyrtonoides), larger and broader aedeagus with the distal tips of the flagellum quadrifurcated and slightly curved, arising from two sclerotized tubes (with a smaller and narrower aedeagus with distal tips of the flagellum quadrifurcated and almost straight, arising from a sclerotized tube in S. cyrtonoides).DescriptionMeasurements in mm (n = 5): length of body: 5.50–7.00 (mean 6.18); width of body: 3.50–4.50 (mean 3.97); height of body: 2.60–3.40 (mean 2.94); width of head: 1.65–1.95 (mean 1.81); interocular distance: 1.15–1.50 (mean 1.33); width of apex of pronotum: 1.90–2.20 (mean 2.02); width of base of pronotum: 2.70–3.25 (mean 2.94); length of pronotum along midline: 1.75–2.05 (mean 1.90); length of elytra along suture: 3.75–5.20 (mean 4.41). Body: oval and strongly convex (Fig. 1a,b). Body dark bluish-black with weak metallic lustre, rarely with a dark brass dorsum. Antenna, mouthparts and tarsus partially dark reddish-brown. Head. Vertex weakly convex, covered with sparse punctures, becoming coarser and denser towards sides, with convex area above antennal insertion. Eyes strongly transverse-oblong and protuberant. Frontal suture V-shaped, forming obtuse angle, arms bent at middle, reaching anterior margin. Frons flat, strongly depressed at anterior margin, covered with dense punctures. Clypeus narrow and trapezoidal. Anterior margin of labrum weakly concave. Mandibles with 2 blunt apical teeth and dense punctures bearing setae on outer side. Maxillary palp 4-segmented with apical palpomere fusiform, truncate apically. Antennae in males much longer than half the length of the body; antennomere 1 robust; antennomere 2 shorter than 3; antennomere 3 longer than 4; antennomeres 7–10 each moderately widened, much longer than wide; antennomere 11 longest, approximately 2.4 times as long as wide. Antennae in females less than half the length of the body. Pronotum. 1.50–1.63 times as wide as long. Lateral sides widest at or near base, roundly narrowed anteriorly, anterior angles strongly produced. Anterior and lateral margins bordered, lateral margins barely visible in dorsal view. Trichobothria present on posterior angles. Disc glabrous, covered with moderately dense punctures, becoming coarser along basal margin; interspaces covered with fine and moderately dense punctures. Scutellum much wider than long, widely rounded apically, with a few fine punctures. Elytra. 1.07–1.16 times as long as wide. Lateral sides widest near middle, roundly narrowed posteriorly. Humeral calli not developed. Disc glabrous and finely rugose, covered with rather irregular punctures arranged in longitudinal rows near suture and lateral margin, more irregular in median region; interspaces covered with fine and sparse punctures. Epipleura wholly visible in lateral view. Hind wings steno- and brachypterous (Fig. 1c). Venter. Hypomera weakly rugose, with a few punctures near anterolateral corners of prosternum. Prosternum covered with coarse and dense punctures bearing long setae; prosternal process broad and strongly expanded apicolaterally, closing procoxal cavities posteriorly. Metasternum covered with punctures bearing long setae, dense medially, sparse laterally. Abdominal ventrites covered with moderately dense punctures bearing long or short setae; apex of last visible abdominal ventrite deeply emarginate in males while rounded in females. Legs. Moderately robust. Tibiae simple without preapical tooth. Tarsomere 1 subequal in width to tarsomere 3 in males but distinctly narrower than tarsomere 3 in females. Tarsal claws simple. Genitalia. Aedeagus broad, lateral margins shallowly concave, with apex moderately produced and truncate in dorsal view (Fig. 2a,c); regularly curved, tapering from middle to apex, with apex pointed and slightly bent upward in lateral view (Fig. 2b); flagellum club-shaped with sharp, sclerotized and quadrifid tips (Fig. 1f). Spermatheca U-shaped, long and rounded at apex (Fig. 2d).EtymologyDedicated to the first author’s mentor Prof. dr hab. Lech Borowiec (University of Wrocław, Poland), the world’s leading specialist in tortoise beetles.DistributionSouth Korea: Chungnam, Gangwon, Gyeongbuk, Daegu (Fig. 3a,b).RemarksThe shape of the apical part of the male genitalia exhibits a certain degree of variation even within the same population. It is difficult to recognize a significant difference in the shape of the male genitalia between populations, but individuals from Yeongyang have a relatively large aedeagus. All specimens that we examined had a dark bluish-black dorsum with a weak metallic lustre, but a single specimen with a dark brass dorsum was found in Yecheon.Mature larva and biology of Suinzona borowieci sp. nov. (Figs. 4, 5 and 6)DiagnosisThe fourth (last) instar larva of S. borowieci sp. nov. is very similar to that of S. cyrtonoides comb. nov. in body shape, colouration and tubercular pattern. However, this species can be distinguished by the 4–5 small secondary tubercles between Dae and DLai on the meso- and metathorax and more densely setose bodies (1 large tubercle between Dae and DLai on the meso- and metathorax and less densely setose body in S. cyrtonoides).Figure 4Mature larva of Suinzona borowieci sp. nov.: (a) Dorsal habitus, (b) lateral habitus, (c) ventral habitus.Full size imageFigure 5Larval morphology of Suinzona borowieci sp. nov.: (a) Head, (b) maxillae and labium, (c) tibiotarsus and pretarsus, (d) mandible, (e) labrum and epipharynx, (f) Schematic presentation of tubercular patterns (top: prothorax; middle: mesothorax; bottom: 2nd abdominal segment).Full size imageFigure 6Host plants of Suinzona borowieci sp. nov.: (a) Arabis pendula L. from Yeongyang, (b) Urtica angustifolia Fisch. ex Hornem. from Yeongyang, (c) Aconitum pseudolaeve Nakai from Taebaek, (d) Isodon inflexus (Thunb.) Kudo from Yecheon; (e–f) A. pseudolaeve Nakai and U. angustifolia Fisch. ex Hornem. for laboratory tests (e) Adult from Yeongyang feeding on leaves, (f) larvae from Yecheon feeding on leaves.Full size imageDescriptionBody length 8.1–8.8 mm, width 2.9–3.2 mm, head width 1.75–1.80 mm (n = 3). Body elongate, rather broad, widest at abdominal segments III–IV, thence moderately narrowed posteriorly and slightly convex dorsally (Fig. 4a). Head pale yellowish-brown, densely setose, with a blackish-brown V-shaped mark along frontal arms; lateral regions of epicrania largely blackish-brown; posterior half of clypeus brown to dark brown; apex of labrum and mandibles blackish-brown. General colouration of integument yellowish-white, but dorsal integument densely covered with minute brown spinules (Fig. 4b); dorsal tubercles dark brown and ventral ones unpigmented (Fig. 4c), both densely setose; spiracles blackish-brown. Legs pale yellow with apex of tibiotarsus and pretarsus brown. Eversible glands absent. Pseudopods present on abdominal segments VI–VII. Head. Hypognathous, rounded, strongly sclerotized (Fig. 5a). Epicranium with 72–77 pairs of setae of varying length; epicranial stem distinct; frontal arms V-shaped, slightly sinuate, not extending to antennal insertions; median endocarina distinct, extending to frontoclypeal suture. Frons slightly depressed medially with 25–29 pairs of setae of varying length. Clypeus almost straight at anterior margin with 3 pairs of setae. Labrum deeply concave anteriorly with 2 pairs of setae and 2 pairs of campaniform sensilla (Fig. 5e, left); epipharynx with 6–7 pairs of setae at anterior margin (Fig. 5e, right). Mandible robust, palmate and 5-toothed, with 4–5 setae and 3 campaniform sensilla; penicillus present (Fig. 5d). Maxillary palp 3-segmented; palpomere I rectangular with 2 setae and 2 campaniform sensilla; II swollen cylindrical with 3 setae and 1 campaniform sensillum; III subconical with 1 seta, 1 digitiform sensillum and 1 campaniform sensillum on sides and a group of peg-like sensilla at the apex; palpifer well developed with 2 setae (Fig. 5b). Mala rounded with 13–14 setae and 1 campaniform sensillum; stipes distinctly longer than wide with 12–14 setae; cardo with 2–3 setae. Labial palp 2-segmented; palpomere I rectangular with 1 campaniform sensillum; II subconical with 1 seta, 1 campaniform sensillum and a group of peg-like sensilla at the apex. Hypopharynx bilobed, densely covered with minute spinules; prementum with four pairs of setae and three pairs of campaniform sensilla; postmentum basolaterally covered with minute spinules, with 8–9 pairs of setae. Six stemmata present on each side, 4 of them located above the antenna and 2 behind the antenna. Antenna 3-segmented; antenomere I wider than long with 2 campaniform sensilla; II approximately as wide as long, with a conical sensorium and 3–4 min setae; III subconical with 5–6 min setae. Thorax. Prothorax with D-DL-EP (dorsal, dorsolateral and epipleural tubercles fused together, 164–179) largest; P (pleural tubercle, 9–11) and ES-SS (eusternal and sternellar tubercles fused, 6–7) unpigmented (Fig. 5f). Meso- and metathorax with dorsal tubercles more or less arranged in 3 transverse rows; Dai (dorsal anterior interior, 6–10) on both sides separated, smaller than Dae (dorsal anterior exterior, 11–15); DLai (dorsolateral anterior interior, 4–5); Dpi (dorsal posterior interior, 12–15); Dpe (dorsal posterior exterior, 10–13) smaller than Dpi; DLpi (dorsolateral posterior interior, 17–19); DLe (dorsolateral exterior, 40–47) large; dorsal region with 8–9 secondary tubercles, 3 of them located anterior to Dai and Dae, 4–5 between Dae and DLai and 1 anterior to DLe; EPa (epipleural anterior, 17–22) larger than EPp (epipleural posterior, 8–11), both unpigmented; P (9–13), SS (1) and ES (3–4) unpigmented; sternal region with 4–5 additional setae arising from weakly sclerotized base. Mesothoracic spiracles annuliform and largest. Legs moderately long, 5-segmented; tibiotarsus with 23–25 setae; pretarsus large, strongly curved, basal tooth well developed, with 1 short seta (Fig. 5c). Abdomen. Segments I–VI with dorsal tubercles arranged in 3 transverse rows; Dai (5–8) on both sides separated, smaller than Dae (13–14); DLae (12–14) larger than DLai (7); Dpi (16–19), Dpe (15–19) and DLp (24–29) transverse, subequal in size; dorsal region with 5–10 small secondary tubercles; EP (23–27), P (12–13), PS-SS (parasternal and sternellar tubercles fused, 5–7) and ES (5–7) unpigmented; as1 (secondary tubercle on antero-exterior part of ES, 1) and as2 (secondary tubercle between P and PS, 1); sternal region with 3–4 additional setae arising from weakly sclerotized base. Segment VII with Dai and Dae fused and Dpi and Dpe fused. Segments VIII with dorsal and dorso-lateral tubercles completely fused (30–37). Segment IX with dorsal to epipleural tubercles completely fused (34–36). Segment X not visible from above, with paired pygopods. Spiracles annuliform, present on segments I–VIII.Host plantsBrassicaceae: Arabis pendula L.; Lamiaceae: Isodon inflexus (Thunb.) Kudo; Ranunculaceae: Aconitum pseudolaeve Nakai; Urticaceae: Urtica angustifolia Fisch. ex Hornem.Biological notesSuinzona borowieci sp. nov. is univoltine. Overwintered adults appear in late May. They mate and lay 15–18 eggs per cluster on the leaves of host plants in early June. Eggs are pale yellow to yellowish-orange and hatch after 8–9 days. The larvae are solitary during the instar stages and feed on the leaves. There are four larval instars, and pupation occurs in soil. The larvae take 14–16 days to pupate and then take 7–8 days to emerge as adults. Newly emerged adults are found during July. We observed larvae or adults of this species in nearby localities (~ 62 km), feeding on A. pendula L. (Fig. 6a) and U. angustifolia Fisch. ex Hornem. (Fig. 6b) from Yeongyang (at 1135 ~ 1190 m a.s.l.), A. pseudolaeve Nakai (Fig. 6c) from Taebaek (at 1,470 m a.s.l.), and I. inflexus (Thunb.) Kudo (Fig. 6d) from Yecheon (at 330 m a.s.l.). Each population showed a preference for its natural host plant but fed on other host plants and completed its life cycle in laboratory tests (Fig. 6e,f).
    Suinzona cyrtonoides (Jacoby, 1885) comb. nov. (Figs. 1, 2 and 3)Type localityJapan: Kyushu, Kumamoto Prefecture, Konose.Type materialSyntypes: 1 female (BMNH), Lectotype [mislabelled, not lectotype] // Type // DATA under card // Japan, G. Lewis, 1910–320. // Chrysomela crytonoides Jac. // Lectotype, Chrysomela crytonoides Jacoby, Designated. S. GE 2004 // Potaninia cyrtonoides Jacoby, Det. S. GE 2004 // Suinzona cyrtonoides (Jacoby, 1885) det. H.W. Cho 2014; 1 female (BMNH), Japan, G. Lewis, 1910–320. // Paralectotype // Paralectotype, Chrysomela crytonoides Jacoby, Designated. S. GE 2004 // Potaninia cyrtonoides Jacoby, Det. S. GE 2004 // Suinzona cyrtonoides (Jacoby, 1885) det. H.W. Cho 2014; 1 male (MCZC), Japan Lewis // 1st Jacoby Coll. // cyrtonoides Jac. // Type 17,474; 1 female (MCZC), Japan Lewis // 1st Jacoby Coll.Other materialJAPAN – Kyushu: 1 male (BMNH), Yuyama 1883 // Japan, G. Lewis, 1910–320. // Paralectotype [mislabelled, not type series] // Paralectotype, Chrysomela crytonoides Jacoby, Designated. S. GE 2004 // Potaninia cyrtonoides Jacoby, Det. S. GE 2004 // Suinzona cyrtonoides (Jacoby, 1885) det. H.W. Cho 2014; Honshu: 3 males 2 females (KMNH), Nippara, Okutama, Tokyo, 5.VI.1955, Y. Tominaga; 2 males 3 females (BMNH), Mt. Mitake, Ome-shi, Tokyo, 15.VII.2005, Y. Komiya; 1 male (HSC), Chichibu, Saitama Pref., 18.VI.1984, M. Minami; 1 male (HSC), Tochigi, Sano-shi, Tanuma, 4.VI.2008, H. Ohkawa; 1 male (HSC), Gumma, Fujioka-shi, Mikabo-yama rindo, 8.VI.2009, H. Ohkawa; 1 male 2 females (HSC), same data as preceding one except 21.VII.2009; 1 male 1 female (HSC), same data as preceding one except 1.V.2010; Shikoku: 1 female (HSC), Tokushima, Yoshinokawa-shi, Mt. Kotsu-zan, 18.V.1987, S. Mano; 2 females (EUMJ), Tokushima, Mt. Tsurugi, 15.VII.1984, M. Miyatake; 1 male 1 female (EUMJ), Ehime: Omogo-Sibukusa, Kamiukena-gun, 5.VI.2005, Y. Satoh; 7 males (HCC), Ehime, Kamiukena, Kumakogen, Wakayama, 33° 43′ 59.4″ N, 133° 08′ 06.5″ E, 5.VI.2019, H.W. Cho & Y. Hiroyuki; 1 male (HSC), Ehime, Saijo-shi, Mt. Ishizuchizan, 30.V.2009, H. Suenaga; 2 males (HSC), Ehime, Saijo-shi, Nishinokawa, 16.V.2010, H. Suenaga; 1 male 1 female (HSC), Ehime, Saijo-shi, Nishinokawa, 5.VI.2010, H. Suenaga; 1 female (EUMJ), Jiyoshi-toge, Ehime Pref., 26.IV.1976, A. Oda; 1 male (EUMJ), Mt. Ishizuchi, Ehime pref., 1.VI.1975, H. Kan; 1 female (EUMJ), Iwayaji, Ehime Pref., 1.VI.1969, M. Miyatake; 1 male (EUMJ), Ehime: Yokono, 750 m alt. Yanadani-mura, 7.V.1994, M. Sakai; 1 male (EUMJ), Ehime: Yokono, 660 m alt. Yanadani-mura, 6.V.1994, M. Sakai; 1 female (EUMJ), Ehime: Yokono, 700 m alt. Yanadani-mura, 15.VII.1994, M. Sakai.DistributionJapan: Honshu, Shikoku, Kyushu (Fig. 3a).Host plantsUrticaceae: Boehmeria spicata (Thunb.) Thunb., Boehmeria tricuspis (Hance) Makino.Biological notesDetailed descriptions of larvae and pupae and the life cycle have been published by Kimoto16 and Kimoto and Takizawa11. Its life cycle is similar to that of S. borowieci sp. nov., but they feed on different host plants.RemarksThe apical part of the aedeagus is highly variable, narrow to broad, apex narrowly to widely rounded or weakly truncate, mainly with two weak or strong denticles on the apicolateral margin. The aedeagus of the type specimen is narrowly rounded without apicolateral denticles (Fig. 2e). However, we were not able to find an obvious tendency in the morphological variation of the aedeagus at the intrapopulation or interpopulation level. Chrysomela cyrtonoides Jacoby, 1885 was described from Japan. Later, it was transferred to the genus Potaninia by Chûjô and Kimoto17 and then accepted by various authors until now. However, we found that all materials of P. cyrtonoides have reduced hind wings (Fig. 1d), which are the key diagnostic features of the genus Suinzona, and molecular analysis also suggests its placement in Suinzona. Therefore, Suinzona cyrtonoides (Jacoby, 1885) comb. nov. is proposed. Jacoby18 gave ‘Konose’ as the type locality and used at least two specimens collected by G. Lewis for the description. A male specimen (BMNH) from ‘Yuyama’, designated by Ge et al.3 as a lectotype, did not belong to the type series of S. cyrtonoides and thus lost its lectotype status (ICZN: Article 74.2). Indeed, a female specimen (BMNH) was mislabelled as a lectotype. We were able to find four specimens collected from Japan that might belong to the type series of S. cyrtonoides in the G. Lewis collection (BMNH, MCZC), but more precise locality data were not available. Therefore, we regard them as syntypes and defer selection of a lectotype.Molecular phylogenetic analysesIt is evident from the clarified phylogenetic inference based on mitogenomes that the genus Suinzona differs from the genus Potaninia, S. borowieci sp. nov. as the sister species of S. cyrtonoides (Fig. 7a). The phylogenetic inferences included a total of 20 mitogenomes of Chrysomelinae and outgroups of Galerucinae (Supplementary Table S1). The complete mitogenomes of the four Suinzona species and one Potaninia species (incomplete) were newly sequenced in the present study. Each mitogenome contains a typical set of mitochondrial genes (13 PCGs, 22 tRNAs and two rRNAs) and a control region. Phylogenetic trees based on ML and BI inferences revealed the presence of two well-supported clades (Chrysomelini and Doryphorini + Entomoscelini + Gonioctenini), placing the genus Suinzona as the sister group of the genus Potaninia. This result matched the morphological character of the hind wing. The COI haplotype network of the genus Suinzona complex (Fig. 7b) confirms the previous results and shows that the currently known single species is well distinguished as a species. Two independent networks were completely separated without any connection due to the existence of the mutation (62 steps) exceeding the 95% parsimony limits between them.Figure 7Phylogenetic tree and parsimonious network: (a) Bayesian consensus tree inferred from the combined mitochondrial 13 PCGs + 2 rRNA gene. Bayesian inference (left) and maximum likelihood (right) support values are shown on the branch nodes. Only the values over 70% are reported, (b) Parsimonious network of COI haplotypes. Circles correspond to haplotypes, the frequency and geographic origin of which are indicated by circle size. The geographical origins of the haplotypes are noted at the bottom right of the figure.Full size imageKey to Suinzona borowieci sp. nov. and related species1. Hind wings well developed (Fig. 1e); humeral calli present; trichobothria present on anterior angles of pronotum; lateral margins of pronotum distinctly visible from above. China, India, Laos, Myanmar, Thailand and Vietnam……………………………………………………………… Potaninia assamensis (Baly, 1879)– Hind wings reduced (Fig. 1c,d); humeral calli absent; trichobothria absent on anterior angles of pronotum; lateral margins of pronotum not or barely visible from above. China, Korea and Japan……………………… 22. Aedeagus with apex of flagellum quadrifid (Fig. 1f,g). South Korea, Japan……………. 3– Aedeagus with apex of flagellum varied in shape, but not quadrifid (see Ge et al.3 for key to 23 species). China (Sichuan, Yunnan)……………………………………………… Suinzona spp.3. Larger, body length 5.5–7.0 mm; elytra more densely punctate (Fig. 1a); aedeagus larger and broader (Fig. 2c). South Korea…………………………………. Suinzona borowieci sp. nov.– Smaller, body length 4.8–6.0 mm; elytra less densely punctate (Fig. 1d); aedeagus smaller and narrower (Fig. 2e). Japan…………………………….. Suinzona cyrtonoides (Jacoby, 1885) More

  • in

    Bacteria living on tree bark consume methane

    Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain
    the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in
    Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles
    and JavaScript. More

  • in

    Unveiling African rainforest composition and vulnerability to global change

    1.Diffenbaugh, N. S. & Giorgi, F. Climate change hotspots in the CMIP5 global climate model ensemble. Clim. Change 114, 813–822 (2012).ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    2.United Nations, Department of Economic and Social Affairs, Population Division. World Population Prospects: The 2017 Revision, Key Findings and Advance Tables. Working Paper No. ESA/P/WP/248 (2017).3.Malhi, Y., Adu-Bredu, S., Asare, R. A., Lewis, S. L. & Mayaux, P. African rainforests: past, present and future. Phil. Trans. R. Soc. B 368, 20120312 (2013).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    4.James, R., Washington, R. & Rowell, D. P. Implications of global warming for the climate of African rainforests. Phil. Trans. R. Soc. B 368, 20120298 (2013).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    5.Abernethy, K., Maisels, F. & White, L. J. Environmental issues in Central Africa. Annu. Rev. Environ. Resour. 41, 1–33 (2016).Article 

    Google Scholar 
    6.Hubau, W. et al. Asynchronous carbon sink saturation in African and Amazonian tropical forests. Nature 579, 80–87 (2020).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    7.De Wasseige, C., Tadoum, M., Atyi, E. & Doumenge, C. The Forests of the Congo Basin: Forests and Climate Change (Weyrich, 2015).8.Stévart, T. et al. A third of the tropical African flora is potentially threatened with extinction. Sci. Adv. 5, eaax9444 (2019).ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    9.Parmentier, I. et al. The odd man out? Might climate explain the lower tree α-diversity of African rain forests relative to Amazonian rain forests? J. Ecol. 95, 1058–1071 (2007).Article 

    Google Scholar 
    10.Réjou-Méchain, M. et al. Regional variation in tropical forest tree species composition in the Central African Republic: an assessment based on inventories by forest companies. J. Trop. Ecol. 24, 663–674 (2008).Article 

    Google Scholar 
    11.Réjou-Méchain, M. et al. Tropical tree assembly depends on the interactions between successional and soil filtering processes. Glob. Ecol. Biogeogr. 23, 1440–1449 (2014).Article 

    Google Scholar 
    12.Fayolle, A. et al. Geological substrates shape tree species and trait distributions in African moist forests. PLoS One 7, e42381 (2012).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    13.Fayolle, A. et al. Patterns of tree species composition across tropical African forests. J. Biogeogr. 41, 2320–2331 (2014).Article 

    Google Scholar 
    14.Droissart, V. et al. Beyond trees: biogeographical regionalization of tropical Africa. J. Biogeogr. 45, 1153–1167 (2018).Article 

    Google Scholar 
    15.Sosef, M. S. et al. Exploring the floristic diversity of tropical Africa. BMC Biol. 15, 15 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    16.Parmentier, I. et al. Predicting alpha diversity of African rain forests: models based on climate and satellite-derived data do not perform better than a purely spatial model. J. Biogeogr. 38, 1164–1176 (2011).Article 

    Google Scholar 
    17.Bry, X., Trottier, C., Verron, T. & Mortier, F. Supervised component generalized linear regression using a PLS-extension of the fisher scoring algorithm. J. Multivariate Anal. 119, 47–60 (2013).MathSciNet 
    MATH 
    Article 

    Google Scholar 
    18.ter Steege, H. et al. Continental-scale patterns of canopy tree composition and function across Amazonia. Nature 443, 444–447 (2006).ADS 
    Article 
    CAS 

    Google Scholar 
    19.Slik, J. W. et al. Soils on exposed Sunda shelf shaped biogeographic patterns in the equatorial forests of Southeast Asia. Proc. Natl Acad. Sci. USA 108, 12343–12347 (2011).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    20.Philippon, N. et al. The light-deficient climates of western Central African evergreen forests. Environ. Res. Lett. 14, 034007 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    21.Sullivan, M. J. P. et al. Long-term thermal sensitivity of Earth’s tropical forests. Science 368, 869–874 (2020).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    22.Beale, C. M., Lennon, J. J. & Gimona, A. Opening the climate envelope reveals no macroscale associations with climate in European birds. Proc. Natl Acad. Sci. USA 105, 14908–14912 (2008).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    23.Deblauwe, V. et al. Remotely sensed temperature and precipitation data improve species distribution modelling in the tropics. Glob. Ecol. Biogeogr. 25, 443–454 (2016).Article 

    Google Scholar 
    24.Maguire, K. C. et al. Controlled comparison of species- and community-level models across novel climates and communities. Proc. R. Soc. B 283, 20152817 (2016).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    25.Morin-Rivat, J. et al. Present-day central African forest is a legacy of the 19th century human history. eLife 6, e20343 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    26.Ricklefs, R. E. Intrinsic dynamics of the regional community. Ecol. Lett. 18, 497–503 (2015).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    27.Violle, C. et al. Let the concept of trait be functional! Oikos 116, 882–892 (2007).Article 

    Google Scholar 
    28.Díaz, S. et al. The global spectrum of plant form and function. Nature 529, 167–171 (2016).ADS 
    PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    29.Rüger, N. et al. Demographic trade-offs predict tropical forest dynamics. Science 368, 165–168 (2020).ADS 
    PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    30.Ouédraogo, D.-Y. et al. The determinants of tropical forest deciduousness: disentangling the effects of rainfall and geology in central Africa. J. Ecol. 104, 924–935 (2016).Article 
    CAS 

    Google Scholar 
    31.Shipley, B. From Plant Traits to Vegetation Structure: Chance and Selection in the Assembly of Ecological Communities (Cambridge University Press, 2010).32.Feeley, K. J. & Silman, M. R. Biotic attrition from tropical forests correcting for truncated temperature niches. Glob. Change Biol. 16, 1830–1836 (2010).ADS 
    Article 

    Google Scholar 
    33.Parry, M. et al. Climate Change 2007 – Impacts, Adaptation, and Vulnerability: Contribution of Working Group II to the Fourth Assessment Report of the IPCC (Cambridge University Press, 2007).34.Foden, W. B. et al. Identifying the world’s most climate change vulnerable species: a systematic trait-based assessment of all birds, amphibians and corals. PLoS One 8, e65427 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    35.Lachenaud, O., Stévart, T., Ikabanga, D., Ndjabounda, E. C. N. & Walters, G. The littoral forests of the Libreville area (Gabon) and their importance for conservation: description of a new endemic species (Rubiaceae). Plant Ecol. Evol. 146, 68–74 (2013).Article 

    Google Scholar 
    36.Aguirre-Gutiérrez, J. et al. Drier tropical forests are susceptible to functional changes in response to a long-term drought. Ecol. Lett. 22, 855–865 (2019).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    37.Claeys, F. et al. Climate change would lead to a sharp acceleration of Central African forests dynamics by the end of the century. Environ. Res. Lett. 14, 044002 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    38.McDowell, N. G. et al. Pervasive shifts in forest dynamics in a changing world. Science 368, eaaz9463 (2020).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    39.Zhou, L. et al. Widespread decline of Congo rainforest greenness in the past decade. Nature 509, 86–90 (2014).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    40.Purvis, A. Phylogenetic approaches to the study of extinction. Annu. Rev. Ecol. Evol. Syst. 39, 301–319 (2008).Article 

    Google Scholar 
    41.Yachi, S. & Loreau, M. Biodiversity and ecosystem productivity in a fluctuating environment: the insurance hypothesis. Proc. Natl Acad. Sci. USA 96, 1463–1468 (1999).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    42.Neves, D. M. et al. Evolutionary diversity in tropical tree communities peaks at intermediate precipitation. Sci. Rep. 10, 1188 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    43.Letcher, S. G. Phylogenetic structure of angiosperm communities during tropical forest succession. Proc. R. Soc. B 277, 97–104 (2010).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    44.Letouzey, R. Notice de la carte phytogéographique du Cameroun au 1:500000 (Institut de la Carte Internationale de la végétation Toulouse-France et Institut de la recherche agronomique (Herbier National) Yaoundé-Cameroun, 1985).45.Boulvert, Y. Carte phytogéographique de la République Centrafricaine (feuille oust–feuille est) à 1 000 000 (Editions de l’ORSTOM, 1986).46.Fyllas, N. M., Quesada, C. A. & Lloyd, J. Deriving plant functional types for Amazonian forests for use in vegetation dynamics models. Perspect. Plant Ecol. Evol. Syst. 14, 97–110 (2012).Article 

    Google Scholar 
    47.Mitchard, E. T. A. et al. Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites. Glob. Ecol. Biogeogr. 23, 935–946 (2014).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    48.Visconti, P., Pressey, R. L., Bode, M. & Segan, D. B. Habitat vulnerability in conservation planning—when it matters and how much. Conserv. Lett. 3, 404–414 (2010).Article 

    Google Scholar 
    49.Putz, F. E. et al. Sustaining conservation values in selectively logged tropical forests: the attained and the attainable. Conserv. Lett. 5, 296–303 (2012).Article 

    Google Scholar 
    50.Gourlet-Fleury, S. et al. Tropical forest recovery from logging: a 24 year silvicultural experiment from Central Africa. Phil. Trans. R. Soc. B 368, 20120302 (2013).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    51.Clark, C. J., Poulsen, J. R., Malonga, R. & Elkan, P. W. Jr. Logging concessions can extend the conservation estate for Central African tropical forests. Conserv. Biol. 23, 1281–1293 (2009).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    52.Curtis, P. G., Slay, C. M., Harris, N. L., Tyukavina, A. & Hansen, M. C. Classifying drivers of global forest loss. Science 361, 1108–1111 (2018).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    53.Réjou-Méchain, M. et al. Detecting large-scale diversity patterns in tropical trees: can we trust commercial forest inventories? For. Ecol. Manage. 261, 187–194 (2011).Article 

    Google Scholar 
    54.African Plant Database v.3.4.0 (Conservatoire et Jardin Botaniques de la Ville de Genève and South African National Biodiversity Institute, Pretoria, accessed 10 February 2017).55.The Angiosperm Phylogeny Group. An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG III. Bot. J. Linn. Soc. 161, 105–121 (2009).Article 

    Google Scholar 
    56.Dauby, G. et al. RAINBIO: a mega-database of tropical African vascular plants distributions. PhytoKeys 74, 1–18 (2016).Article 

    Google Scholar 
    57.Chave, J. et al. Towards a worldwide wood economics spectrum. Ecol. Lett. 12, 351–366 (2009).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    58.Zanne, A. E. et al. Data from: towards a worldwide wood economic spectrum. Dryad https://doi.org/10.5061/dryad.234 (2009).59.Gourlet-Fleury, S. et al. Environmental filtering of dense‐wooded species controls above‐ground biomass stored in African moist forests. J. Ecol. 99, 981–990 (2011).Article 

    Google Scholar 
    60.Westoby, M. & Wright, I. J. Land-plant ecology on the basis of functional traits. Trends Ecol. Evol. 21, 261–268 (2006).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    61.Chave, J. et al. Improved allometric models to estimate the aboveground biomass of tropical trees. Glob. Change Biol. 20, 3177–3190 (2014).ADS 
    Article 

    Google Scholar 
    62.Bénédet, F. et al. CoForTraits, African plant traits information database v.1.0, https://doi.org/10.18167/DVN1/Y2BIZK (2013).63.Davies, T. J. et al. Phylogenetic conservatism in plant phenology. J. Ecol. 101, 1520–1530 (2013).Article 

    Google Scholar 
    64.Cramer, W. et al. Global response of terrestrial ecosystem structure and function to CO2 and climate change: Results from six dynamic global vegetation models. Glob. Change Biol. 7, 357–373 (2001).ADS 
    Article 

    Google Scholar 
    65.Menzel, A. Phenology: its importance to the global change community. Clim. Change 54, 379 (2002).Article 

    Google Scholar 
    66.Borchert, R., Rivera, G. & Hagnauer, W. Modification of vegetative phenology in a tropical semi-deciduous forest by abnormal drought and rain. Biotropica 34, 27–39 (2002).Article 

    Google Scholar 
    67.Kraft, N. J. B., Valencia, R. & Ackerly, D. D. Functional traits and niche-based tree community assembly in an Amazonian forest. Science 322, 580–582 (2008).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    68.Schamp, B. S. & Aarssen, L. W. The assembly of forest communities according to maximum species height along resource and disturbance gradients. Oikos 118, 564–572 (2009).Article 

    Google Scholar 
    69.New, M., Lister, D., Hulme, M. & Makin, I. A high-resolution data set of surface climate over global land areas. Clim. Res. 21, 1–25 (2002).Article 

    Google Scholar 
    70.Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surface for global land areas. Int. J. Climatol. 25, 1965–1978 (2005).Article 

    Google Scholar 
    71.Funk, C. et al. The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. Sci. Data 2, 150066 (2015).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    72.Nachtergaele, F. et al. The harmonized world soil database. In Proc. 19th World Congress of Soil Science, Soil Solutions for a Changing World (eds Gilkes, R. & Prakongkep, N.) 34–37 (International Union of Soil Sciences, 2010).73.Woolmer, G. et al. Rescaling the human footprint: a tool for conservation planning at an ecoregional scale. Landsc. Urban Plan. 87, 42–53 (2008).Article 

    Google Scholar 
    74.Venter, O. et al. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nat. Commun. 7, 12558 (2016).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    75.Geldmann, J., Joppa, L. N. & Burgess, N. D. Mapping change in human pressure globally on land and within protected areas. Conserv. Biol. 28, 1604–1616 (2014).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    76.Linard, C., Gilbert, M., Snow, R. W., Noor, A. M. & Tatem, A. J. Population distribution, settlement patterns and accessibility across Africa in 2010. PLoS One 7, e31743 (2012).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    77.Lloyd, C. T. et al. Global spatio-temporally harmonised datasets for producing high-resolution gridded population distribution datasets. Big Earth Data 3, 108–139 (2019).
    Google Scholar 
    78.Boulesteix, A.-L. & Strimmer, K. Partial least squares: a versatile tool for the analysis of high-dimensional genomic data. Brief. Bioinform. 8, 32–44 (2007).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    79.Carrascal, L. M., Galván, I. & Gordo, O. Partial least squares regression as an alternative to current regression methods used in ecology. Oikos 118, 681–690 (2009).Article 

    Google Scholar 
    80.Tenenhaus, M. La Régression PLS: Théorie et Pratique (Editions Technip, 1998).81.Sabatier, R., Lebreton, J. D. & Chessel, D. in Multiway Data Analysis (eds Coppi, R. & Bolasco, S.) 341–352 (1989).82.Ter Braak, C. J. F. in Theory and Models In Vegetation Science (eds Prentice, I. C. & van der Maarel, E.) 69–77 (Springer, 1987).83.Bry, X. & Verron, T. THEME: THEmatic model exploration through multiple co-structure maximization. J. Chemometr. 29, 637–647 (2015).CAS 
    Article 

    Google Scholar 
    84.Cornu, G., Mortier, F., Trottier, C. & Bry, X. SCGLR: supervised component generalized linear regression. R version 3.0 https://cran.r-project.org/web/packages/SCGLR/index.html (2016).85.Ward, J. H. Jr. Hierarchical grouping to optimize an objective function. J. Am. Stat. Assoc. 58, 236–244 (1963).MathSciNet 
    Article 

    Google Scholar 
    86.Ploton, P. et al. Spatial validation reveals poor predictive performance of large-scale ecological mapping models. Nat. Commun. 11, 4540 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    87.Scrucca, L., Fop, M., Murphy, T. B. & Raftery, A. E. mclust 5: clustering, classification and density estimation using gGussian finite mixture models. R J. 8, 289–317 (2016).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    88.Dormann, C. F. et al. Methods to account for spatial autocorrelation in the analysis of species distributional data: A review. Ecography 30, 609–628 (2007).Article 

    Google Scholar 
    89.Renard, D. et al. RGeostats: the geostatistical package v.11.0. 1 http://rgeostats.free.fr/ (MINES ParisTech, 2014).90.Platts, P. J., Omeny, P. A. & Marchant, R. AFRICLIM: high-resolution climate projections for ecological applications in Africa. Afr. J. Ecol. 53, 103–108 (2015).Article 

    Google Scholar 
    91.Janssens, S. B. et al. A large-scale species level dated angiosperm phylogeny for evolutionary and ecological analyses. Biodivers. Data J. 8, e39677 (2020).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    92.Abouheif, E. A method for testing the assumption of phylogenetic independence in comparative data. Evol. Ecol. Res. 1, 895–909 (1999).
    Google Scholar 
    93.Chao, A., Chiu, C.-H. & Jost, L. Phylogenetic diversity measures based on Hill numbers. Phil. Trans. R. Soc. B 365, 3599–3609 (2010).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    94.R Core Team. R: a language and environment for statistical computing. (R Foundation for Statistical Computing, 2017).95.Chessel, D., Dufour, A. B. & Thioulouse, J. The ade4 package – I: one-table methods. R News 4, 5–10 (2004).
    Google Scholar 
    96.Lafarge, T. & Pateiro-Lopez, B. alphashape3d: implementation of the 3D alpha-shape for the reconstruction of 3D sets from a point cloud. R version 1.3.1 https://cran.r-project.org/web/packages/alphashape3d/index.html (2017).97.Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag, 2016).98.Hijmans, R. J. raster: geographic data analysis and modelling. R version 3.4-5 https://cran.r-project.org/web/packages/raster/index.html (2017).99.Marcon, E. & Hérault, B. entropart: An R package to measure and partition diversity. J. Stat. Softw. 67, 1–26 (2015).
    Google Scholar 
    100.Dufrêne, M. & Legendre, P. Species assemblages and indicator species: the need for a flexible asymmetrical approach. Ecol. Monogr. 67, 345–366 (1997).
    Google Scholar  More

  • in

    Different quantification approaches for nitrogen use efficiency lead to divergent estimates with varying advantages

    1.Zhang, X. et al. Managing nitrogen for sustainable development. Nature 528, 51–59 (2015).ADS 
    CAS 
    Article 

    Google Scholar 
    2.Erisman, J. W. et al. Nitrogen: Too Much of a Vital Resource. WWF Science Brief (WWF Netherlands, 2015); http://www.louisbolk.org/downloads/3005.pdf3.European Union Nitrogen Expert Panel. Nitrogen Use Efficiency (NUE)—An Indicator for the Utilization of Nitrogen in Agriculture and Food Systems (Wageningen University, 2015); http://wedocs.unep.org/handle/20.500.11822/12087
    Google Scholar 
    4.Cassman, K. G., Dobermann, A. & Walters, D. T. Agroecosystems, nitrogen-use efficiency, and nitrogen management. Ambio 31, 132–140 (2002).Article 

    Google Scholar 
    5.Harmsen, K. A comparison of the isotope-dilution and the difference method for estimating fertilizer nitrogen recovery fractions in crops. I. Plant uptake and loss of nitrogen. NJAS: Wageningen J. Life Sci. 50, 321–347 (2003).CAS 

    Google Scholar 
    6.Krupnik, T. J., Six, J., Ladha, J. K., Paine, M. J. & van Kessel, C. An Assessment of Fertilizer Nitrogen Recovery Efficiency by Grain Crops (Island Press, 2004).7.Jin, J. Changes in the efficiency of fertiliser use in China. J. Sci. Food Agric. 92, 1006–1009 (2012).CAS 
    Article 

    Google Scholar 
    8.Zhang, F. et al. Nutrient use efficiencies of major cereal crops in china and measures for improvement. Acta Pedol. Sin. 45, 915–924 (2008) (in Chinese with English abstract).
    Google Scholar 
    9.Yu, F. & Shi, W. Nitrogen use efficiencies of major grain crops in China in recent 10 years. Acta Pedol. Sin. 52, 1311–1324 (2015) (in Chinese with English abstract).
    Google Scholar 
    10.Ju, X. & Christie, P. Calculation of theoretical nitrogen rate for simple nitrogen recommendations in intensive cropping systems: a case study on the North China Plain. Field Crops Res. 124, 450–458 (2011).Article 

    Google Scholar 
    11.Zhang, C., Ju, X., Powlson, D., Oenema, O. & Smith, P. Nitrogen surplus benchmarks for controlling N pollution in the main cropping systems of China. Environ. Sci. Technol. 53, 6678–6687 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    12.Powlson, D. S. et al. Comments on ‘Synthetic nitrogen fertilizers deplete soil nitrogen: a global dilemma for sustainable cereal production,’ by R.L. Mulvaney, S.A. Khan, and T.R. Ellsworth in the Journal of Environmental Quality, 2009 38: 2295–2314. J. Environ. Qual. 39, 749–752 (2010).CAS 
    Article 

    Google Scholar 
    13.Yan, X. et al. Fertilizer nitrogen recovery efficiencies in crop production systems of China with and without consideration of the residual effect of nitrogen. Environ. Res. Lett. 9, 095002 (2014).ADS 
    CAS 
    Article 

    Google Scholar 
    14.Smith, C. J. & Chalk, P. M. The residual value of fertiliser N in crop sequences: an appraisal of 60 years of research using 15N tracer. Field Crops Res. 217, 66–74 (2018).Article 

    Google Scholar 
    15.Ju, X. et al. Reducing environmental risk by improving N management in intensive Chinese agricultural systems. Proc. Natl Acad. Sci. USA 106, 3041–3046 (2009).ADS 
    CAS 
    Article 

    Google Scholar 
    16.Wang, L. et al. Plastic mulching reduces nitrogen footprint of food crops in China: a meta-analysis. Sci. Total Environ. 748, 141479 (2020).ADS 
    CAS 
    Article 

    Google Scholar 
    17.Storkey, J. et al. Grassland biodiversity bounces back from long-term nitrogen addition. Nature 528, 401–404 (2015).ADS 
    CAS 
    Article 

    Google Scholar 
    18.Sebilo, M., Mayer, B., Nicolardot, B., Pinay, G. & Mariotti, A. Long-term fate of nitrate fertilizer in agricultural soils. Proc. Natl Acad. Sci. USA 110, 18185–18189 (2013).ADS 
    CAS 
    Article 

    Google Scholar 
    19.Raun, W. R. & Johnson, G. V. Improving nitrogen use efficiency for cereal production. Agron. J. 91, 357–363 (1999).Article 

    Google Scholar 
    20.Yan, M., Pan, G., Lavallee, J. M. & Conant, R. T. Rethinking sources of nitrogen to cereal crops. Glob. Change Biol. 26, 191–199 (2020).ADS 
    Article 

    Google Scholar  More