More stories

  • in

    Planting period is the main factor for controlling maize rough dwarf disease

    1.
    Rockström, J. et al. Sustainable intensification of agriculture for human prosperity and global sustainability. Ambio 46, 4–17 (2017).
    PubMed  Article  Google Scholar 
    2.
    García-Arenal, F. & McDonald, B. A. An analysis of the durability of resistance to plant viruses. Phytopathology 93, 941–952 (2003).
    PubMed  Article  Google Scholar 

    3.
    Anderson, P. K. et al. Emerging infectious diseases of plants: pathogen pollution, climate change and agrotechnology drivers. Trends Ecol. Evol. 19, 535–544 (2004).
    PubMed  Article  Google Scholar 

    4.
    Landis, D. A., Wratten, S. D. & Gurr, G. M. Habitat management to conserve natural enemies of arthropod pests in agriculture. Annu. Rev. Entomol. 45, 175–201 (2000).
    CAS  PubMed  Article  Google Scholar 

    5.
    Stukenbrock, E. H. & McDonald, B. A. The origins of plant pathogens in agro-ecosystems. Annu. Rev. Phytopathol. 46, 75–100 (2008).
    CAS  PubMed  Article  Google Scholar 

    6.
    Biek, R. & Real, L. A. The landscape genetics of infectious disease emergence and spread. Mol. Ecol. 19, 3515–3531 (2010).
    PubMed  PubMed Central  Article  Google Scholar 

    7.
    Meentemeyer, R. K., Haas, S. E. & Václavík, T. Landscape epidemiology of emerging infectious diseases in natural and human-altered ecosystems. Annu. Rev. Phytopathol. 50, 379–402 (2012).
    CAS  PubMed  Article  Google Scholar 

    8.
    Boccardo, G. & Milne, R.G. Plant Reovirus Group. Description of Plant Viruses. No. 294. CM/AAB (1984).

    9.
    Dovas, C. I., Eythymiou, K. & Katis, N. I. First report of maize rough dwarf virus (MRDV) on maize crops in Greece. Plant Pathol. 53, 238–238 (2004).
    Article  Google Scholar 

    10.
    Lenardon, S. L., March, G. J., Nome, S. F. & Ornaghi, J. A. Recent outbreak of “Mal de Rio Cuarto” virus on corn in Argentina. Plant Dis. 82, 448 (1998).
    CAS  PubMed  Article  Google Scholar 

    11.
    Zhang, H., Chen, J., Lei, J. & Adams, M. J. Sequence analysis shows that a dwarfing disease on rice, wheat and maize in China is caused by rice black-streaked dwarf virus. Eur. J. Plant Pathol. 107, 563–567 (2001).
    CAS  Article  Google Scholar 

    12.
    Hoang, A. T. et al. Identification, characterization, and distribution of southern rice black-streaked dwarf virus in Vietnam. Plant Dis. 95, 1063–1069 (2011).
    PubMed  Article  PubMed Central  Google Scholar 

    13.
    Achon, M. A., Serrano, L., Clemente-Orta, G. & Barcelo, A. The virome of maize rough dwarf disease: molecular genome diversification, phylogeny and selection. Ann Appl Biol. 176, 192–202 (2020).
    CAS  Article  Google Scholar 

    14.
    Lovisolo, O. Maize Rough Dwarf Virus. Descriptions of Plant Viruses No. 72. Commonw. Mycol. Inst. Asso. Appl. Biol. (1971).

    15.
    Achon, M. A. & Sobrepere, M. Incidence of potyviruses in commercial maize fields and their seasonal cycles in Spain. JPDP 108, 399–406 (2001).
    CAS  Google Scholar 

    16.
    Achon, M. A. & Alonso-Dueñas, N. Impact of 9 years of Bt-maize cultivation on the distribution of maize viruses. Transgenic Res. 18, 387–397 (2009).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    17.
    Achon, M. A., Subira, J. & Sin, E. Seasonal occurrence of Laodelphax striatellus in Spain: effect on the incidence of Maize rough dwarf virus. Crop Prot. 47, 1–5 (2013).
    Article  Google Scholar 

    18.
    Achon, M. A., Serrano, L., Sabate, J. & Porta, C. Understanding the epidemiological factors that intensify the incidence of maize rough dwarf disease in Spain. Ann. Appl. Biol. 166, 311–320 (2015).
    CAS  Article  Google Scholar 

    19.
    CABI, 2017. Laodelphax striatellus. Crop protection compendium, Wallingford, UK: CAB International. https://www.cabi.org/isc/datasheet/10935 (2017).

    20.
    Milne, R. G. & Lovisolo, O. Maize rough dwarf and related viruses. Adv. Virus. Res. 21, 267–341 (1977).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    21.
    Häni, A., Günthart, H. & Brunetti, R. Identifikation des Rauhverzwergungsvirus an Mais im Tessin. Landwirtschaft Schweiz 2, 131–136 (1989).
    Google Scholar 

    22.
    Hibino, H. Biology and epidemiology of rice viruses. Annu. Rev. Phytopathol. 34, 249–274 (1996).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    23.
    Bar-Tsur, A., Saadi, H. & Antignu, Y. Resistance of corn genotypes to maize rough darf virus. Maydica 33, 189–200 (1988).
    Google Scholar 

    24.
    Rodriguez-Pardina, P. E., Gimenez-Pecci, M. P. & Laguna, I. G. Wheat: a new natural host for the Mal de rio cuarto virus in the endemic disease area, Rio Cuarto, Cordoba province, Argentina. Plant Dis. 82, 149–152 (1998).
    Article  Google Scholar 

    25.
    Wang, H. D. et al. Recent rice stripe virus epidemics in Zhejiang province, China, and experiments on sowing date, disease–yield loss relationships, and seedling susceptibility. Plant Dis. 92, 1190–1196 (2008).
    PubMed  Article  PubMed Central  Google Scholar 

    26.
    Wang, H. D. et al. Studies on the epidemiology and yield losses from rice black-streaked dwarf disease in a recent epidemic in Zhejiang province, China. Plant Pathol. 58, 815–825 (2009).
    Article  Google Scholar 

    27.
    Cirilo, A. G. & Andrade, F. Sowing date and maize productivity: I. Crop growth and dry matter partitioning. Crop Sci. 34, 1039–1043 (1994).
    Article  Google Scholar 

    28.
    Farnham, D. E. Row spacing, plant density, and hybrid effects on corn grain yield and moisture. Agron. J. 93, 1049–1053 (2001).
    Article  Google Scholar 

    29.
    Kucharik, C. J. A multidecadal trend of earlier corn planting in the central USA. Agron. J. 98, 1544–1550 (2006).
    Article  Google Scholar 

    30.
    Bruns, H. A. & Abbas, H. K. Planting date effects on Bt and non-Bt corn in the mid-south USA. Agron. J. 98, 100–106 (2006).
    Article  Google Scholar 

    31.
    Achon, M. A. & Clemente, G. Nuevos retos en el control de las enfermedades virales del maíz. Vida rural 424, 44–50 (2017).
    Google Scholar 

    32.
    Maresma, A., Ballesta, A., Santiveri, F. & Lloveras, J. Sowing date affects maize development and yield in irrigated Mediterranean Environments. Agriculture 9, 67 (2019).
    Article  Google Scholar 

    33.
    Chaplin-Kramer, R. et al. A meta-analysis of crop pest and natural enemy response to landscape complexity. Ecol. Lett. 14, 922–932 (2011).
    PubMed  Article  PubMed Central  Google Scholar 

    34.
    Harpaz, I. Maize Rough Dwarf (Israel Universities Press, Jerusalem, 1972).
    Google Scholar 

    35.
    Conti, M. Investigations on the epidemiology of maize rough dwarf virus. I. Overwintering of virus in its planthopper vector, Acta HI Congr. Un. Fitopat. Medit., Oeiras 22–28 Outubro 1972, 11. (1972).  

    36.
    Thresh, J. M. The origins and epidemiology of some important plant virus diseases. Appl. Biol. 5, 1–65 (1980).
    Google Scholar 

    37.
    Grilli, M. P. The role of landscape structure on the abundance of a disease vector planthopper: a quantitative approach. Landsc. Ecol. 25, 383–394 (2010).
    Article  Google Scholar 

    38.
    Conti, M. Investigations on the epidemiology of maize rough dwarf virus III. Field symptoms, incidence and control. Maydica 21, 165–175 (1976).
    Google Scholar 

    39.
    Syobu, S. I., Otuka, A. & Matsumura, M. Trap catches of the small brown planthopper, Laodelphax striatellus (Fallén) (Hemiptera: Delphacidae), in northern Kyushu district, Japan in relation to weather conditions. Appl. Entomol. Zool. 46, 41–50 (2011).
    Article  Google Scholar 

    40.
    Clemente-Orta, G., Albajes, R. & Achon, M. A. Early planting, management of edges and non-crop habitats reduce potyvirus infection in maize. Agron. Sustain. Dev. 40, 21 (2020).
    Article  Google Scholar 

    41.
    Clemente-Orta, G. et al. Changes in landscape composition influence the abundance of insects on maize: the role of fruit orchards and alfalfa crops. Agric. Ecosyst. Environ. 291, 106805 (2020).
    CAS  Article  Google Scholar 

    42.
    Grilli, M. P. & Bruno, M. Regional abundance of a planthopper pest: the effect of host match area and configuration. Entomol. Exp. Appl. 122, 133–143 (2007).
    Article  Google Scholar 

    43.
    Grilli, M. P. & Gorla, D. E. The effect of agroecosystem management on the abundance of Delphacodes kuscheli (Homopteran: Delphacidae), vector of the maize rough dwarf virus, in central Argentina. Maydica 43, 77–82 (1998).
    Google Scholar 

    44.
    MacArthur, R. H. & Wilson, E. O. Island Biogeography (Princeton University Press, Princeton, 1967).
    Google Scholar 

    45.
    Root, R. B. Organization of a plant-arthropod association in simple and diverse habitats: the fauna of collards (Brassica oleraceae). Ecol. Monogr. 43, 95–124 (1973).
    Article  Google Scholar 

    46.
    Tscharntke, T. et al. Landscape moderation of biodiversity patterns and processes-eight hypotheses. Biol. Rev. 87, 661–685 (2012).
    PubMed  Article  PubMed Central  Google Scholar 

    47.
    Trumper, E.V. Modelos de epidemiologia matemática aplicados al estudio de1 sistema Virus MRC-maiz-Delphacidae (“Ma1 de Rio Cuarto”). Tesis doctoral. Universidad National de Cordoba (1996).

    48.
    Cheng, J. A. Rice Planthoppers in the Past Half Century in China. Rice Planthoppers: Ecology, Management Social Economics and Policy 1–32 (Springer, Dordrecht, 2015).
    Google Scholar 

    49.
    Liu, Z. et al. (2016) The effect of landscape composition on the abundance of Laodelphax striatellus Fallén in fragmented agricultural landscapes. Land 5, 36 (2016).
    Article  Google Scholar 

    50.
    Clemente-Orta, G. & Álvarez, H. A. L. influencia del paisaje agrícola en el control biológico desde una perspectiva espacial. Revista Ecosistemas 28, 13–25 (2019).
    Article  Google Scholar 

    51.
    Madeira, F. et al. Stable carbon and nitrogen isotope signatures to determine predator dispersal between alfalfa and maize. Biol. Control. 77, 66–75 (2014).
    Article  Google Scholar 

    52.
    Cantero-Martínez, C. & Moncunill, J. Sistemas agrícolas de la Plana de Lleida: Descripción y evaluación de los sistemas de producción en el área del canal Segarra-Garrigues antes de su puesta en funcionamiento. (2012).

    53.
    Braun-Blanquet, J. Fitosociología. Bases para el estudio de las comunidades vegetales (Blume, Madrid, 1979).
    Google Scholar 

    54.
    DePaulo, J. J. & Powell, C. A. Extraction of double-stranded RNA from plant tissues without the use of organic solvents. Plant Dis. 79, 246–248 (1995).
    CAS  Article  Google Scholar 

    55.
    Albajes, R., Lumbierres, B., Pons, X. & Comas, J. Representative taxa in field trials for environmental risk assessment of genetically modified maize. Bull. Entomol. Res. 103, 724–733 (2013).
    CAS  PubMed  Article  Google Scholar 

    56.
    Ardanuy, A., Lee, M. S. & Albajes, R. Landscape context influences leafhopper and predatory Orius spp. abundances in maize fields. Agric. Forest. Entomol. 20, 81–92 (2018).
    Article  Google Scholar 

    57.
    Holzinger, W. E., Kammerlander, I. & Nickel, H. The Auchenorrhyncha of Central Europe. In Fulgoromorpha, Cicadomorpha Excl-Cicadellidae Vol. 1 (ed. Brill) (Brill, Leiden-Boston, 2003).
    Google Scholar 

    58.
    ESRI. ArcGIS Desktop Version 10.3.1 (Environmental Systems Research Institute, Redlands, 2015).
    Google Scholar 

    59.
    Bartoń, K. (2018). Package “MuMIn” Title Multi-Model Inference. In: CRAN-R. https://cran.r-project.org/web/packages/MuMIn/MuMIn.pdf

    60.
    Burnham, K. P. & Anderson, D. R. Multimodel inference: understanding AIC and BIC in model selection. Sociol. Methods Res. 33, 261–304 (2004).
    MathSciNet  Article  Google Scholar 

    61.
    Paradis, E. Package “ape” Title Analyses of Phylogenetics and Evolution Depends R. https://cran.r-project.org/web/packages/ape/ape.pdf (2019).

    62.
    Max, K. et al. Caret: Title Classification and Regression Training. R package version: 6.0-84. https://cran.r-project.org/web/packages/caret/caret.pdf (2018).

    63.
    Bates, D. et al. Lme4: Linear Mixed-Effects Models using ‘Eigen’ and S4. R package version 1.1-21. https://cran.r-project.org/web/packages/lme4/lme4.pdf (2019).

    64.
    Zuur, A. F., Ieno, E. N. & Elphick, C. S. A protocol for data exploration to avoid common statistical problems. Methods Ecol. Evol. 1, 3–14 (2010).
    Article  Google Scholar 

    65.
    R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/ R version 3.6.2. (2019). More

  • in

    Genome-wide macroevolutionary signatures of key innovations in butterflies colonizing new host plants

    1.
    Becerra, J. X. On the factors that promote the diversity of herbivorous insects and plants in tropical forests. Proc. Natl Acad. Sci. USA 112, 6098–6103 (2015).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 
    2.
    Stork, N. E. How many species of insects and other terrestrial arthropods are there on earth? Annu. Rev. Entomol. 63, 31–45 (2018).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    3.
    Grimaldi, D. A. & Engel, M. S. Evolution of the Insects (Cambridge University Press, 2005).

    4.
    Strong, D. R., Lawton, J. H. & Southwood, R. Insects on Plants: Community Patterns and Mechanisms (Harvard University Press, 1984).

    5.
    Ehrlich, P. R. & Raven, P. H. Butterflies and plants: a study in coevolution. Evolution 18, 586–608 (1964).
    Article  Google Scholar 

    6.
    Thompson, J. N. Concepts of coevolution. Trends Ecol. Evol. 4, 179–183 (1989).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    7.
    Mitter, C., Farrell, B. & Wiegmann, B. The phylogenetic study of adaptive zones: has phytophagy promoted insect diversification? Am. Nat. 132, 107–128 (1988).
    Article  Google Scholar 

    8.
    Farrell, B. D. ‘Inordinate fondness’ explained: why are there so many beetles? Science 281, 555–559 (1998).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    9.
    Berenbaum, M. & Specialization, P. F. Chemical Mediation of Host-plant Specialization: The Papilionid Paradigm. Specialization, Speciation, and Radiation: The Evolutionary Biology of Herbivorous Insects (University of California Press, 2008).

    10.
    Winter, S., Friedman, A. L. L., Astrin, J. J., Gottsberger, B. & Letsch, H. Timing and host plant associations in the evolution of the weevil tribe Apionini (Apioninae, Brentidae, Curculionoidea, Coleoptera) indicate an ancient co-diversification pattern of beetles and flowering plants. Mol. Phylogenet. Evol. 107, 179–190 (2017).
    PubMed  Article  PubMed Central  Google Scholar 

    11.
    Kergoat, G. J. et al. Opposite macroevolutionary responses to environmental changes in grasses and insects during the Neogene grassland expansion. Nat. Commun. 9, 5089 (2018).
    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

    12.
    Wheat, C. W. et al. The genetic basis of a plant–insect coevolutionary key innovation. Proc. Natl Acad. Sci. USA 104, 20427–20431 (2007).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    13.
    Edger, P. P. et al. The butterfly plant arms-race escalated by gene and genome duplications. Proc. Natl Acad. Sci. USA 112, 8362–8366 (2015).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    14.
    Calla, B. et al. Cytochrome P450 diversification and hostplant utilization patterns in specialist and generalist moths: Birth, death and adaptation. Mol. Ecol. 26, 6021–6035 (2017).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    15.
    Nallu, S. et al. The molecular genetic basis of herbivory between butterflies and their host plants. Nat. Ecol. Evol. 2, 1418–1427 (2018).
    PubMed  PubMed Central  Article  Google Scholar 

    16.
    Karageorgi, M. et al. Genome editing retraces the evolution of toxin resistance in the monarch butterfly. Nature 574, 409–412 (2019).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    17.
    Sahoo, R. K., Warren, A. D., Collins, S. C. & Kodandaramaiah, U. Hostplant change and paleoclimatic events explain diversification shifts in skipper butterflies (Family: Hesperiidae). BMC Evol. Biol. 17, 174 (2017).
    PubMed  PubMed Central  Article  Google Scholar 

    18.
    Condamine, F. L., Rolland, J., Höhna, S., Sperling, F. A. H. & Sanmartín, I. Testing the role of the red queen and court jester as drivers of the macroevolution of apollo butterflies. Syst. Biol. 67, 940–964 (2018).
    PubMed  Article  PubMed Central  Google Scholar 

    19.
    Letsch, H. et al. Climate and host-plant associations shaped the evolution of ceutorhynch weevils throughout the Cenozoic. Evolution 72, 1815–1828 (2018).
    PubMed  PubMed Central  Article  Google Scholar 

    20.
    Forister, M. L. et al. The global distribution of diet breadth in insect herbivores. Proc. Natl Acad. Sci. USA 112, 442–447 (2015).
    ADS  CAS  PubMed  Article  Google Scholar 

    21.
    Winkler, I. S., Mitter, C. & Scheffer, S. J. Repeated climate-linked host shifts have promoted diversification in a temperate clade of leaf-mining flies. Proc. Natl Acad. Sci. USA 106, 18103–18108 (2009).
    ADS  CAS  PubMed  Article  Google Scholar 

    22.
    Chomicki, G., Weber, M., Antonelli, A., Bascompte, J. & Kiers, E. T. The impact of mutualisms on species richness. Trends Ecol. Evol. 34, 698–711 (2019).
    PubMed  Article  Google Scholar 

    23.
    Janz, N. Ehrlich and Raven revisited: mechanisms underlying codiversification of plants and enemies. Annu. Rev. Ecol. Evol. Syst. 42, 71–89 (2011).
    Article  Google Scholar 

    24.
    Suchan, T. & Alvarez, N. Fifty years after Ehrlich and Raven, is there support for plant–insect coevolution as a major driver of species diversification? Entomol. Exp. Appl. 157, 98–112 (2015).
    Article  Google Scholar 

    25.
    Endara, M.-J. et al. Coevolutionary arms race versus host defense chase in a tropical herbivore-plant system. Proc. Natl Acad. Sci. USA 114, E7499–E7505 (2017).
    CAS  PubMed  Article  Google Scholar 

    26.
    Simon, J.-C. et al. Genomics of adaptation to host-plants in herbivorous insects. Brief. Funct. Genomics 14, 413–423 (2015).
    CAS  PubMed  Article  Google Scholar 

    27.
    Hammer, T. J., Janzen, D. H., Hallwachs, W., Jaffe, S. P. & Fierer, N. Caterpillars lack a resident gut microbiome. Proc. Natl Acad. Sci. USA 114, 9641–9646 (2017).
    CAS  PubMed  Article  Google Scholar 

    28.
    Hua, X. & Bromham, L. Darwinism for the genomic age: connecting mutation to diversification. Front. Genet. 8, 12 (2017).
    PubMed  PubMed Central  Article  Google Scholar 

    29.
    Hembry, D. H. & Weber, M. G. Ecological interactions and macroevolution: a new field with old roots. Annu. Rev. Ecol. Evol. Syst. 51, (2020).

    30.
    Scriber, J. M., Tsubaki, Y. & Lederhouse, R. C. Swallowtail Butterflies: Their Ecology and Evolutionary Biology (Scientific Publishers, 1995).

    31.
    Nishida, R. Sequestration of defensive substances from plants by Lepidoptera. Annu. Rev. Entomol. 47, 57–92 (2002).
    CAS  PubMed  Article  Google Scholar 

    32.
    Schmeiser, H. H., Stiborovà, M. & Arlt, V. M. Chemical and molecular basis of the carcinogenicity of Aristolochia plants. Curr. Opin. Drug Discov. Dev. 12, 141–148 (2009).
    CAS  Google Scholar 

    33.
    Poon, S. L. et al. Genome-wide mutational signatures of aristolochic acid and its application as a screening tool. Sci. Transl. Med. 5, 197ra101 (2013).
    PubMed  Article  CAS  Google Scholar 

    34.
    Condamine, F. L., Sperling, F. A. H., Wahlberg, N., Rasplus, J.-Y. & Kergoat, G. J. What causes latitudinal gradients in species diversity? Evolutionary processes and ecological constraints on swallowtail biodiversity. Ecol. Lett. 15, 267–277 (2012).
    PubMed  Article  Google Scholar 

    35.
    Simonsen, T. J. et al. Phylogenetics and divergence times of Papilioninae (Lepidoptera) with special reference to the enigmatic genera Teinopalpus and Meandrusa. Cladistics 27, 113–137 (2011).
    Article  Google Scholar 

    36.
    Berenbaum, M. R., Favret, C. & Schuler, M. A. On defining ‘Key Innovations’ in an adaptive radiation: cytochrome P450s and Papilionidae. Am. Nat. 148, S139–S155 (1996).
    Article  Google Scholar 

    37.
    Cohen, M. B., Schuler, M. A. & Berenbaum, M. R. A host-inducible cytochrome P-450 from a host-specific caterpillar: molecular cloning and evolution. Proc. Natl Acad. Sci. USA 89, 10920–10924 (1992).
    ADS  CAS  PubMed  Article  Google Scholar 

    38.
    Li, W., Schuler, M. A. & Berenbaum, M. R. Diversification of furanocoumarin-metabolizing cytochrome P450 monooxygenases in two papilionids: specificity and substrate encounter rate. Proc. Natl Acad. Sci. USA 100(Suppl.), 14593–14598 (2003).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    39.
    Thompson, J. N. Variation in preference and specificity in monophagous and oligophagous swallowtail butterflies. Evolution 42, 118–128 (1988).
    PubMed  Article  PubMed Central  Google Scholar 

    40.
    Thompson, J. N., Wehling, W. & Podolsky, R. Evolutionary genetics of host use in swallowtail butterflies. Nature 344, 148–150 (1990).
    ADS  Article  Google Scholar 

    41.
    Berenbaum, M. R. & Feeny, P. P. in Specialization, Speciation, and Radiation: The Evolutionary Biology of Herbivorous Insects (ed. Tilmon, K.) 2–19 (University of California Press, 2008).

    42.
    Zakharov, E. V., Caterino, M. S. & Sperling, F. A. H. Molecular phylogeny, historical biogeography, and divergence time estimates for swallowtail butterflies of the genus Papilio (Lepidoptera: Papilionidae). Syst. Biol. 53, 193–215 (2004).
    PubMed  Article  Google Scholar 

    43.
    Braby, M., Trueman, J. & Eastwood, R. When and where did troidine butterflies (Lepidoptera: Papilionidae) evolve? Phylogenetic and biogeographic evidence suggests an origin in remnant Gondwana in the Late Cretaceous. Invertebr. Syst. 19, 113–143 (2005).
    Article  Google Scholar 

    44.
    Condamine, F. L., Silva-Brandão, K. L., Kergoat, G. J. & Sperling, F. A. Biogeographic and diversification patterns of Neotropical Troidini butterflies (Papilionidae) support a museum model of diversity dynamics for Amazonia. BMC Evol. Biol. 12, 82 (2012).
    PubMed  PubMed Central  Article  Google Scholar 

    45.
    Condamine, F. L. et al. Deciphering the evolution of birdwing butterflies 150 years after Alfred Russel Wallace. Sci. Rep. 5, 11860 (2015).
    ADS  PubMed  PubMed Central  Article  Google Scholar 

    46.
    Allio, R. et al. Whole genome shotgun phylogenomics resolves the pattern and timing of swallowtail butterfly evolution. Syst. Biol. 69, 38–60 (2020).
    CAS  PubMed  Article  Google Scholar 

    47.
    McKenna, D. D., Sequeira, A. S., Marvaldi, A. E. & Farrell, B. D. Temporal lags and overlap in the diversification of weevils and flowering plants. Proc. Natl Acad. Sci. USA.106, 7083–7088 (2009).
    ADS  CAS  PubMed  Article  Google Scholar 

    48.
    Takahashi, D. & Setoguchi, H. Molecular phylogeny and taxonomic implications of Asarum (Aristolochiaceae) based on ITS and matK sequences. Plant Species Biol. 33, 28–41 (2018).
    Article  Google Scholar 

    49.
    Wanke, S. et al. Evolution of Piperales—matK gene and trnK intron sequence data reveal lineage specific resolution contrast. Mol. Phylogenet. Evol. 42, 477–497 (2007).
    CAS  PubMed  Article  Google Scholar 

    50.
    Neinhuis, C., Wanke, S., Hilu, K. W., Müller, K. & Borsch, T. Phylogeny of Aristolochiaceae based on parsimony, likelihood, and Bayesian analyses of trnL-trnF sequences. Plant Syst. Evol. 250, 7–26 (2005).
    Article  Google Scholar 

    51.
    Wanke, S., González, F. & Neinhuis, C. Systematics of pipevines: combining morphological and fast‐evolving molecular characters to investigate the relationships within subfamily Aristolochioideae. Int. J. Plant Sci. 167, 1215–1227 (2006).
    CAS  Article  Google Scholar 

    52.
    González, F. et al. Present trans-Pacific disjunct distribution of Aristolochia subgenus Isotrema (Aristolochiaceae) was shaped by dispersal, vicariance and extinction. J. Biogeogr. 41, 380–391 (2014).
    Article  Google Scholar 

    53.
    Durden, C. J. & Rose, H. Butterflies from the Middle Eocene: The Earliest Occurrence of Fossil Papilionoidea (Lepidoptera) (Prarce-Sellards Ser. Tax. Mem. Mus., 1978).

    54.
    Sohn, J., Labandeira, C., Davis, D. & Mitter, C. An annotated catalog of fossil and subfossil Lepidoptera (Insecta: Holometabola) of the world. Zootaxa 3286, 1–132 (2012).
    Article  Google Scholar 

    55.
    de Jong, R. Estimating time and space in the evolution of the Lepidoptera. Tijdschr. voor Entomol. 150, 319–346 (2007).
    Article  Google Scholar 

    56.
    Hofmann, C.-C. & Zetter, R. Upper Cretaceous sulcate pollen from the Timerdyakh formation, Vilui Basin (Siberia). Grana 49, 170–193 (2010).
    Article  Google Scholar 

    57.
    Meller, B. The first fossil Aristolochia (Aristolochiaceae, Piperales) leaves from Austria. Palaeontol. Electron 17, 1–17 (2014).
    Google Scholar 

    58.
    Nee, S., May, R. M. & Harvey, P. H. The reconstructed evolutionary process. Philos. Trans. R. Soc. Lond. Ser. B 344, 305–311 (1994).
    ADS  CAS  Article  Google Scholar 

    59.
    Nee, S. Birth-death models in macroevolution. Annu. Rev. Ecol. Evol. Syst. 37, 1–17 (2006).
    Article  Google Scholar 

    60.
    Rabosky, D. L. & Lovette, I. J. Explosive evolutionary radiations: Decreasing speciation or increasing extinction through time? Evolution 62, 1866–1875 (2008).
    PubMed  Article  PubMed Central  Google Scholar 

    61.
    Crisp, M. D. & Cook, L. G. Explosive radiation or cryptic mass extinction? Interpreting signatures in molecular phylogenies. Evolution 63, 2257–2265 (2009).
    PubMed  Article  PubMed Central  Google Scholar 

    62.
    Quental, T. B. & Marshall, C. R. Diversity dynamics: molecular phylogenies need the fossil record. Trends Ecol. Evol. 25, 434–441 (2010).
    PubMed  Article  PubMed Central  Google Scholar 

    63.
    Morlon, H. Phylogenetic approaches for studying diversification. Ecol. Lett. 17, 508–525 (2014).
    PubMed  Article  PubMed Central  Google Scholar 

    64.
    Xue, B. et al. Accelerated diversification correlated with functional traits shapes extant diversity of the early divergent angiosperm family Annonaceae. Mol. Phylogenet. Evol. 142, 106659 (2020).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    65.
    Folk, R. A. et al. Rates of niche and phenotype evolution lag behind diversification in a temperate radiation. Proc. Natl Acad. Sci. USA 116, 10874–10882 (2019).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    66.
    Sun, M. et al. Recent accelerated diversification in rosids occurred outside the tropics. Nat. Commun. 11, 3333 (2020).
    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

    67.
    Losos, J. B. Adaptive radiation, ecological opportunity, and evolutionary determinism. Am. Nat. 175, 623–639 (2010).
    PubMed  Article  PubMed Central  Google Scholar 

    68.
    Cheng, T. et al. Genomic adaptation to polyphagy and insecticides in a major East Asian noctuid pest. Nat. Ecol. Evol. 1, 1747–1756 (2017).
    PubMed  Article  PubMed Central  Google Scholar 

    69.
    Rane, R. V. et al. Detoxifying enzyme complements and host use phenotypes in 160 insect species. Curr. Opin. Insect Sci. 31, 131–138 (2019).
    MathSciNet  PubMed  Article  PubMed Central  Google Scholar 

    70.
    Cong, Q., Borek, D., Otwinowski, Z. & Grishin, N. V. Tiger swallowtail genome reveals mechanisms for speciation and caterpillar chemical defense. Cell Rep. 10, 910–919 (2015).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    71.
    Li, X. et al. Outbred genome sequencing and CRISPR/Cas9 gene editing in butterflies. Nat. Commun. 6, 8212 (2015).
    ADS  PubMed  PubMed Central  Article  Google Scholar 

    72.
    Nishikawa, H. et al. A genetic mechanism for female-limited Batesian mimicry in Papilio butterfly. Nat. Genet. 47, 405–409 (2015).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    73.
    Thomas, G. W. C. & Hahn, M. W. Determining the null model for detecting adaptive convergence from genomic data: a case study using echolocating mammals. Mol. Biol. Evol. 32, 1232–1236 (2015).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    74.
    Zou, Z. & Zhang, J. No genome-wide protein sequence convergence for echolocation. Mol. Biol. Evol. 32, 1237–1241 (2015).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    75.
    Kimura, M. The Neutral Theory of Molecular Evolution (Cambridge University Press, 1983).

    76.
    Yang, Z. Computational Molecular Evolution (Oxford University Press, 2006).

    77.
    Venkat, A., Hahn, M. W. & Thornton, J. W. Multinucleotide mutations cause false inferences of lineage-specific positive selection. Nat. Ecol. Evol. 2, 1280–1288 (2018).
    PubMed  PubMed Central  Article  Google Scholar 

    78.
    Mendes, F. K. & Hahn, M. W. Gene tree discordance causes apparent substitution rate variation. Syst. Biol. 65, 711–721 (2016).
    PubMed  Article  PubMed Central  Google Scholar 

    79.
    Dasmahapatra, K. K. et al. Butterfly genome reveals promiscuous exchange of mimicry adaptations among species. Nature 487, 94–98 (2012).
    ADS  CAS  PubMed Central  Article  Google Scholar 

    80.
    Walden, N. et al. Nested whole-genome duplications coincide with diversification and high morphological disparity in Brassicaceae. Nat. Commun. 11, 3795 (2020).
    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

    81.
    McGee, M. D. et al. The ecological and genomic basis of explosive adaptive radiation. Nature 586, 75–79 (2020).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    82.
    Thomas, G. W. C. et al. Gene content evolution in the arthropods. Genome Biol. 21, 15 (2020).
    PubMed  PubMed Central  Article  Google Scholar 

    83.
    de Medeiros, B. A. S. & Farrell, B. D. Evaluating species interactions as a driver of phytophagous insect divergence. bioRxiv https://doi.org/10.1101/842153 (2019).

    84.
    Katoh, K. & Standley, D. M. MAFFT multiple sequence alignment software version 7: Improvements in performance and usability. Mol. Biol. Evol. 30, 772–780 (2013).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    85.
    Lanfear, R., Frandsen, P. B., Wright, A. M., Senfeld, T. & Calcott, B. PartitionFinder 2: new methods for selecting partitioned models of evolution for molecular and morphological phylogenetic analyses. Mol. Biol. Evol. 34, 772–773 (2016).
    Google Scholar 

    86.
    Nguyen, L.-T., Schmidt, H. A., von Haeseler, A. & Minh, B. Q. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 32, 268–274 (2015).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    87.
    Kalyaanamoorthy, S., Minh, B. Q., Wong, T. K. F., von Haeseler, A. & Jermiin, L. S. ModelFinder: fast model selection for accurate phylogenetic estimates. Nat. Methods 14, 587–589 (2017).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    88.
    Chernomor, O., von Haeseler, A. & Minh, B. Q. Terrace aware data structure for phylogenomic inference from supermatrices. Syst. Biol. 65, 997–1008 (2016).
    PubMed  PubMed Central  Article  Google Scholar 

    89.
    Minh, B. Q., Nguyen, M. A. T. & von Haeseler, A. Ultrafast approximation for phylogenetic bootstrap. Mol. Biol. Evol. 30, 1188–1195 (2013).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    90.
    Ronquist, F. et al. MrBayes 3.2: efficient bayesian phylogenetic inference and model choice across a large model space. Syst. Biol. 61, 539–542 (2012).
    PubMed  PubMed Central  Article  Google Scholar 

    91.
    Huelsenbeck, J. P., Larget, B. & Alfaro, M. E. Bayesian phylogenetic model selection using reversible jump Markov Chain Monte Carlo. Mol. Biol. Evol. 21, 1123–1133 (2004).
    CAS  PubMed  Article  Google Scholar 

    92.
    Rambaut, A., Drummond, A. J., Xie, D., Baele, G. & Suchard, M. A. Posterior summarization in bayesian phylogenetics using Tracer 1.7. Syst. Biol. 67, 901–904 (2018).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    93.
    Douady, C. J., Delsuc, F., Boucher, Y., Doolittle, W. F. & Douzery, E. J. P. Comparison of bayesian and maximum likelihood bootstrap measures of phylogenetic reliability. Mol. Biol. Evol. 20, 248–254 (2003).
    CAS  PubMed  Article  Google Scholar 

    94.
    Miller, M. A. et al. A RESTful API for access to phylogenetic tools via the CIPRES Science Gateway. Evol. Bioinforma. 11, EBO.S21501 (2015).
    Article  Google Scholar 

    95.
    Ayres, D. L. et al. BEAGLE: an application programming interface and high-performance computing library for statistical phylogenetics. Syst. Biol. 61, 170–173 (2012).
    PubMed  Article  Google Scholar 

    96.
    Drummond, A. J., Ho, S. Y. W., Phillips, M. J. & Rambaut, A. Relaxed phylogenetics and dating with confidence. PLoS Biol. 4, e88 (2006).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    97.
    Drummond, A. J., Suchard, M. A., Xie, D. & Rambaut, A. Bayesian phylogenetics with BEAUti and the BEAST 1.7. Mol. Biol. Evol. 29, 1969–1973 (2012).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    98.
    Smith, M. E., Singer, B. & Carroll, A. 40Ar/39Ar geochronology of the Eocene Green River Formation, Wyoming. Geol. Soc. Am. Bull. 115, 549–565 (2003).
    ADS  CAS  Article  Google Scholar 

    99.
    de Jong, R. Fossil butterflies, calibration points and the molecular clock (Lepidoptera: Papilionoidea). Zootaxa 4270, 1–63 (2017).
    PubMed  Article  PubMed Central  Google Scholar 

    100.
    Scudder, S. H. Fossil butterflies. Mem. Am. Assoc. Adv. Sci. 1, 1–99 (1875).
    Google Scholar 

    101.
    Rasnitsyn, A. P. & Zherikhin, V. V. in History of Insects 437–446 (Kluwer Academic Publishers, 2002).

    102.
    Rebel, H. Doritites bosniaskii. Sitzungsberichte der akademie der wissenschaften. Mathematischen-Naturwissenschaftliche classe. Abt. 1 Mineral. Biol. Erdkd. 1, 734–741 (1898).
    Google Scholar 

    103.
    Carpenter, F. Treatise on Invertebrate Paleontology: Arthropoda 4. Superclass Hexapoda (Geological Society of America, 1992).

    104.
    Magallón, S., Gómez-Acevedo, S., Sánchez-Reyes, L. L. & Hernández-Hernández, T. A metacalibrated time‐tree documents the early rise of flowering plant phylogenetic diversity. N. Phytol. 207, 437–453 (2015).
    Article  Google Scholar 

    105.
    Sohn, J.-C., Labandeira, C. C. & Davis, D. R. The fossil record and taphonomy of butterflies and moths (Insecta, Lepidoptera): implications for evolutionary diversity and divergence-time estimates. BMC Evol. Biol. 15, 12 (2015).
    PubMed  PubMed Central  Article  Google Scholar 

    106.
    Toussaint, E. F. A. & Condamine, F. L. To what extent do new fossil discoveries change our understanding of clade evolution? A cautionary tale from burying beetles (Coleoptera: Nicrophorus). Biol. J. Linn. Soc. 117, 686–704 (2016).
    Article  Google Scholar 

    107.
    Gernhard, T. The conditioned reconstructed process. J. Theor. Biol. 253, 769–778 (2008).
    MathSciNet  PubMed  MATH  Article  Google Scholar 

    108.
    Lewis, P. O. A likelihood approach to estimating phylogeny from discrete morphological character data. Syst. Biol. 50, 913–925 (2001).
    CAS  PubMed  Article  Google Scholar 

    109.
    Ree, R. H. & Smith, S. A. Maximum likelihood inference of geographic range evolution by dispersal, local extinction, and cladogenesis. Syst. Biol. 57, 4–14 (2008).
    PubMed  Article  Google Scholar 

    110.
    Pagel, M. & Meade, A. Bayesian analysis of correlated evolution of discrete characters by reversible-jump Markov chain Monte Carlo. Am. Nat. 167, 808–825 (2006).
    PubMed  Article  PubMed Central  Google Scholar 

    111.
    Igarashi, S. The classification of the Papilionidae mainly based on the morphology of their immature stages. Lepid. Sci. 34, 41–96 (1984).
    Google Scholar 

    112.
    Collins, N. M. & Morris, M. Threatened Swallowtail Butterflies of the World: the IUCN Red Data Book (IUCN, 1985).

    113.
    Tyler, H. A., Brown, K. S. & Wilson, K. H. Swallowtail Butterflies of the Americas: A Study in Biological Dynamics, Ecological Diversity, Biosystematics, and Conservation (Scientific Publishers, 1994).

    114.
    Ree, R. H., Moore, B. R., Webb, C. O. & Donoghue, M. J. A likelihood framework for inferring the evolution of geographic range on phylogenetic trees. Evolution 59, 2299–2311 (2005).
    PubMed  Article  PubMed Central  Google Scholar 

    115.
    Massoni, J., Couvreur, T. L. & Sauquet, H. Five major shifts of diversification through the long evolutionary history of Magnoliidae (Angiosperms). BMC Evol. Biol. 15, 49 (2015).
    PubMed  PubMed Central  Article  Google Scholar 

    116.
    Kyalangalilwa, B., Boatwright, J. S., Daru, B. H., Maurin, O. & van der Bank, M. Phylogenetic position and revised classification of Acacia s.l. (Fabaceae: Mimosoideae) in Africa, including new combinations in Vachellia and Senegalia. Bot. J. Linn. Soc. 172, 500–523 (2013).
    Article  Google Scholar 

    117.
    Miller, J. T., Murphy, D. J., Ho, S. Y. W., Cantrill, D. J. & Seigler, D. Comparative dating of Acacia: combining fossils and multiple phylogenies to infer ages of clades with poor fossil records. Aust. J. Bot. 61, 436–445 (2013).
    Article  Google Scholar 

    118.
    Michalak, I., Zhang, L.-B. & Renner, S. S. Trans-Atlantic, trans-Pacific and trans-Indian Ocean dispersal in the small Gondwanan Laurales family Hernandiaceae. J. Biogeogr. 37, 1214–1226 (2010).
    Article  Google Scholar 

    119.
    Wu, S.-D. et al. Evolution of asian interior arid-zone biota: Evidence from the diversification of asian Zygophyllum (Zygophyllaceae). PLoS ONE 10, e0138697 (2015).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    120.
    Chase, M. W. et al. An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG IV. Bot. J. Linn. Soc. 181, 1–20 (2016).
    Article  Google Scholar 

    121.
    Christenhusz, M. J. M., Vorontsova, M. S., Fay, M. F. & Chase, M. W. Results from an online survey of family delimitation in angiosperms and ferns: recommendations to the Angiosperm Phylogeny Group for thorny problems in plant classification. Bot. J. Linn. Soc. 178, 501–528 (2015).
    Article  Google Scholar 

    122.
    Gonzáles, F., Rudall, P. J. & Furness, C. A. Microsporogenesis and systematics of Aristolochiaceae. Bot. J. Linn. Soc. 137, 221–242 (2001).
    Article  Google Scholar 

    123.
    González, F. & Rudall, P. The questionable affinities of Lactoris: evidence from branching pattern, inflorescence morphology, and stipule development. Am. J. Bot. 88, 2143–2150 (2001).
    PubMed  Article  PubMed Central  Google Scholar 

    124.
    Isnard, S. et al. Growth form evolution in Piperales and its relevance for understanding angiosperm diversification: An integrative approach combining plant architecture, anatomy, and biomechanics. Int. J. Plant Sci. 173, 610–639 (2012).
    Article  Google Scholar 

    125.
    Wagner, S. T. et al. Major trends in stem anatomy and growth forms in the perianth-bearing Piperales, with special focus on Aristolochia. Ann. Bot. 113, 1139–1154 (2014).
    PubMed  PubMed Central  Article  Google Scholar 

    126.
    Nickrent, D. L. et al. Molecular data place Hydnoraceae with Aristolochiaceae. Am. J. Bot. 89, 1809–1817 (2002).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    127.
    Kelly, L. M. & González, F. Phylogenetic relationships in Aristolochiaceae. Syst. Bot. 28, 236–249 (2003).
    Google Scholar 

    128.
    Naumann, J. et al. Single-copy nuclear genes place haustorial Hydnoraceae within piperales and reveal a cretaceous origin of multiple parasitic angiosperm lineages. PLoS ONE 8, e79204 (2013).
    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

    129.
    Salomo, K. et al. The emergence of earliest angiosperms may be earlier than fossil evidence indicates. Syst. Bot. 42, 607–619 (2017).
    PubMed  PubMed Central  Article  Google Scholar 

    130.
    Christenhusz, M. J. M. & Byng, J. W. The number of known plants species in the world and its annual increase. Phytotaxa 261, 201–217 (2016).
    Article  Google Scholar 

    131.
    Naumann, J. et al. Detecting and characterizing the highly divergent plastid genome of the nonphotosynthetic parasitic plant Hydnora visseri (Hydnoraceae). Genome Biol. Evol. 8, 345–363 (2016).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    132.
    Jost, M., Naumann, J., Rocamundi, N., Cocucci, A. A. & Wanke, S. The first plastid genome of the Holoparasitic genus Prosopanche (Hydnoraceae). Plants 9, 306 (2020).
    CAS  PubMed Central  Article  PubMed  Google Scholar 

    133.
    Zavada, M. S. & Benson, J. M. First fossil evidence for the primitive angiosperm family Lactoricidae. Am. J. Bot. 74, 1590–1594 (1987).
    Article  Google Scholar 

    134.
    Gamerro, J. C. & Barreda, V. New fossil record of Lactoridaceae in southern South America: a palaeobiogeographical approach. Bot. J. Linn. Soc. 158, 41–50 (2008).
    Article  Google Scholar 

    135.
    Smith, S. Y. & Stockey, R. A. Establishing a fossil record for the perianthless Piperales: Saururus tuckerae sp. nov. (Saururaceae) from the Middle Eocene Princeton Chert. Am. J. Bot. 94, 1642–1657 (2007).
    PubMed  Article  Google Scholar 

    136.
    Massoni, J., Doyle, J. & Sauquet, H. Fossil calibration of Magnoliidae, an ancient lineage of angiosperms. Palaeontol. Electron. 18, 1–25 (2015).
    Google Scholar 

    137.
    Smith, S. A. Taking into account phylogenetic and divergence-time uncertainty in a parametric biogeographical analysis of the Northern Hemisphere plant clade Caprifolieae. J. Biogeogr. 36, 2324–2337 (2009).
    Article  Google Scholar 

    138.
    Beeravolu, C. R. & Condamine, F. L. An extended maximum likelihood inference of geographic range evolution by dispersal, local extinction and cladogenesis. bioRxiv https://doi.org/10.1101/038695 (2016).

    139.
    Scotese, C. R. A continental drift flipbook. J. Geol. 112, 729–741 (2004).
    ADS  Article  Google Scholar 

    140.
    Blakey, R. C. Gondwana paleogeography from assembly to breakup—a 500 m.y. odyssey. Geol. Soc. Am. Spec. Pap. 441, 1–28 (2008).
    Google Scholar 

    141.
    Seton, M. et al. Global continental and ocean basin reconstructions since 200 Ma. Earth Sci. Rev. 113, 212–270 (2012).
    ADS  Article  Google Scholar 

    142.
    Chacón, J. & Renner, S. S. Assessing model sensitivity in ancestral area reconstruction using Lagrange: a case study using the Colchicaceae family. J. Biogeogr. 41, 1414–1427 (2014).
    Article  Google Scholar 

    143.
    Maddison, W. P., Midford, P. E. & Otto, S. P. Estimating a binary character’s effect on speciation and extinction. Syst. Biol. 56, 701–710 (2007).
    PubMed  Article  PubMed Central  Google Scholar 

    144.
    FitzJohn, R. G., Maddison, W. P. & Otto, S. P. Estimating trait-dependent speciation and extinction rates from incompletely resolved phylogenies. Syst. Biol. 58, 595–611 (2009).
    PubMed  Article  PubMed Central  Google Scholar 

    145.
    Morlon, H., Parsons, T. L. & Plotkin, J. B. Reconciling molecular phylogenies with the fossil record. Proc. Natl Acad. Sci. USA 108, 16327–16332 (2011).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    146.
    Rabosky, D. L. et al. Rates of speciation and morphological evolution are correlated across the largest vertebrate radiation. Nat. Commun. 4, 1958 (2013).
    ADS  PubMed  Article  CAS  PubMed Central  Google Scholar 

    147.
    Höhna, S. et al. A Bayesian approach for estimating branch-specific speciation and extinction rates. bioRxiv https://doi.org/10.1101/555805 (2019).

    148.
    May, M. R., Höhna, S. & Moore, B. R. A Bayesian approach for detecting the impact of mass-extinction events on molecular phylogenies when rates of lineage diversification may vary. Methods Ecol. Evol. 7, 947–959 (2016).
    Article  Google Scholar 

    149.
    Magallon, S. & Sanderson, M. J. Absolute diversification rates in angiosperm clades. Evolution 55, 1762–1780 (2001).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    150.
    Rabosky, D. L. Likelihood methods for detecting temporal shifts in diversification rates. Evolution 60, 1152–1164 (2006).
    PubMed  Article  PubMed Central  Google Scholar 

    151.
    FitzJohn, R. G. Diversitree: comparative phylogenetic analyses of diversification in R. Methods Ecol. Evol. 3, 1084–1092 (2012).
    Article  Google Scholar 

    152.
    Scriber, J. M. in Chemical Ecology of Insects (eds Bell, W. J. & Cardé, R. T.) 159–202 (Springer US, 1984).

    153.
    Davis, M. P., Midford, P. E. & Maddison, W. Exploring power and parameter estimation of the BiSSE method for analyzing species diversification. BMC Evol. Biol. 13, 38 (2013).
    PubMed  PubMed Central  Article  Google Scholar 

    154.
    Maddison, W. P. & FitzJohn, R. G. The unsolved challenge to phylogenetic correlation tests for categorical characters. Syst. Biol. 64, 127–136 (2015).
    PubMed  Article  PubMed Central  Google Scholar 

    155.
    Rabosky, D. L. & Goldberg, E. E. Model inadequacy and mistaken inferences of trait-dependent speciation. Syst. Biol. 64, 340–355 (2015).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    156.
    Morlon, H. et al. RPANDA: an R package for macroevolutionary analyses on phylogenetic trees. Methods Ecol. Evol. 7, 589–597 (2016).
    Article  Google Scholar 

    157.
    Rabosky, D. L. Automatic detection of key innovations, rate shifts, and diversity-dependence on phylogenetic trees. PLoS ONE 9, e89543 (2014).
    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

    158.
    Moore, B. R., Höhna, S., May, M. R., Rannala, B. & Huelsenbeck, J. P. Critically evaluating the theory and performance of Bayesian analysis of macroevolutionary mixtures. Proc. Natl Acad. Sci. USA 113, 9569–9574 (2016).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    159.
    Rabosky, D. L. et al. BAMMtools: an R package for the analysis of evolutionary dynamics on phylogenetic trees. Methods Ecol. Evol. 5, 701–707 (2014).
    Article  Google Scholar 

    160.
    Rabosky, D. L., Mitchell, J. S. & Chang, J. Is BAMM flawed? Theoretical and practical concerns in the analysis of multi-rate diversification models. Syst. Biol. 66, 477–498 (2017).
    PubMed  PubMed Central  Article  Google Scholar 

    161.
    Höhna, S. et al. RevBayes: Bayesian phylogenetic inference using graphical models and an interactive model-specification language. Syst. Biol. 65, 726–736 (2016).
    PubMed  PubMed Central  Article  Google Scholar 

    162.
    Höhna, S., May, M. R. & Moore, B. R. TESS: an R package for efficiently simulating phylogenetic trees and performing Bayesian inference of lineage diversification rates. Bioinformatics 32, 789–791 (2016).
    PubMed  Article  CAS  PubMed Central  Google Scholar 

    163.
    Stadler, T. Mammalian phylogeny reveals recent diversification rate shifts. Proc. Natl Acad. Sci. USA 108, 6187–6192 (2011).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    164.
    Partha, R. et al. Subterranean mammals show convergent regression in ocular genes and enhancers, along with adaptation to tunneling. eLife 6, e25884 (2017).
    PubMed  PubMed Central  Article  Google Scholar 

    165.
    Wu, J., Yonezawa, T. & Kishino, H. Rates of molecular evolution suggest natural history of life history traits and a Post-K-Pg nocturnal bottleneck of placentals. Curr. Biol. 27, 3025–3033 (2017).
    CAS  PubMed  Article  Google Scholar 

    166.
    Zhang, G. et al. Comparative genomics reveals insights into avian genome evolution and adaptation. Science 346, 1311–1320 (2014).
    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

    167.
    Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    168.
    Luo, R. et al. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. Gigascience 1, 18 (2012).
    PubMed  PubMed Central  Article  Google Scholar 

    169.
    Abascal, F., Zardoya, R. & Telford, M. J. TranslatorX: multiple alignment of nucleotide sequences guided by amino acid translations. Nucleic Acids Res. 38, W7–W13 (2010).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    170.
    Simion, P. et al. A software tool ‘CroCo’ detects pervasive cross-species contamination in next generation sequencing data. BMC Biol. 16, 28 (2018).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    171.
    Emms, D. M. & Kelly, S. OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol. 20, 238 (2019).
    PubMed  PubMed Central  Article  Google Scholar 

    172.
    Di Franco, A., Poujol, R., Baurain, D. & Philippe, H. Evaluating the usefulness of alignment filtering methods to reduce the impact of errors on evolutionary inferences. BMC Evol. Biol. 19, 21 (2019).
    PubMed  PubMed Central  Article  Google Scholar 

    173.
    Capella-Gutierrez, S., Silla-Martinez, J. M. & Gabaldon, T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25, 1972–1973 (2009).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    174.
    Yang, Z. & Nielsen, R. Estimating synonymous and nonsynonymous substitution rates under realistic evolutionary models. Mol. Biol. Evol. 17, 32–43 (2000).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    175.
    Zhang, J., Nielsen, R. & Yang, Z. Evaluation of an improved branch-site likelihood method for detecting positive selection at the molecular level. Mol. Biol. Evol. 22, 2472–2479 (2005).
    CAS  PubMed  Article  Google Scholar 

    176.
    Yang, Z. Likelihood ratio tests for detecting positive selection and application to primate lysozyme evolution. Mol. Biol. Evol. 15, 568–573 (1998).
    CAS  PubMed  Article  Google Scholar 

    177.
    Yang, Z. PAML 4: phylogenetic analysis by maximum likelihood. Mol. Biol. Evol. 24, 1586–1591 (2007).
    CAS  Article  PubMed  Google Scholar 

    178.
    Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. 57, 289–300 (1995).
    MathSciNet  MATH  Google Scholar 

    179.
    Bauer, D. F. Constructing confidence sets using rank statistics. J. Am. Stat. Assoc. 67, 687–690 (1972).
    MATH  Article  Google Scholar 

    180.
    Diekmann, Y. & Pereira-Leal, J. B. Gene tree affects inference of sites under selection by the branch-site test of positive selection. Evol. Bioinforma. 11, 11–17 (2015).
    Article  Google Scholar 

    181.
    Mallick, S., Gnerre, S., Muller, P. & Reich, D. The difficulty of avoiding false positives in genome scans for natural selection. Genome Res. 19, 922–933 (2009).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    182.
    Fletcher, W. & Yang, Z. The effect of insertions, deletions, and alignment errors on the branch-site test of positive selection. Mol. Biol. Evol. 27, 2257–2267 (2010).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    183.
    Jordan, G. & Goldman, N. The effects of alignment error and alignment filtering on the sitewise detection of positive selection. Mol. Biol. Evol. 29, 1125–1139 (2012).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    184.
    Duret, L. & Galtier, N. Biased gene conversion and the evolution of mammalian genomic landscapes. Annu. Rev. Genomics Hum. Genet. 10, 285–311 (2009).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    185.
    Galtier, N. & Duret, L. Adaptation or biased gene conversion? Extending the null hypothesis of molecular evolution. Trends Genet. 23, 273–277 (2007).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    186.
    Ratnakumar, A. et al. Detecting positive selection within genomes: the problem of biased gene conversion. Philos. Trans. R. Soc. Ser. B 365, 2571–2580 (2010).
    CAS  Article  Google Scholar 

    187.
    Guéguen, L. et al. Bio++: efficient extensible libraries and tools for computational molecular evolution. Mol. Biol. Evol. 30, 1745–1750 (2013).
    PubMed  Article  CAS  Google Scholar 

    188.
    Wickham, H. & Grolemund, G. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data (O’Reilly Media, Inc., Canada, 2016).

    189.
    Wilke, C. O. cowplot: streamlined plot theme and plot annotations for ‘ggplot2.’ CRAN Repos. 2, R2 (2016).

    190.
    Gouy, M., Guindon, S. & Gascuel, O. SeaView version 4: a multiplatform graphical user interface for sequence alignment and phylogenetic tree building. Mol. Biol. Evol. 27, 221–224 (2010).
    CAS  PubMed  Article  Google Scholar 

    191.
    Redelings, B. Erasing errors due to alignment ambiguity when estimating positive selection. Mol. Biol. Evol. 31, 1979–1993 (2014).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    192.
    Mi, H., Muruganujan, A., Ebert, D., Huang, X. & Thomas, P. D. PANTHER version 14: More genomes, a new PANTHER GO-slim and improvements in enrichment analysis tools. Nucleic Acids Res. 47, D419–D426 (2019).
    CAS  Article  PubMed  Google Scholar 

    193.
    Huerta-Cepas, J. et al. Fast genome-wide functional annotation through orthology assignment by eggNOG-mapper. Mol. Biol. Evol. 34, 2115–2122 (2017).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    194.
    Huerta-Cepas, J. et al. eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses. Nucleic Acids Res. 47, D309–D314 (2019).
    CAS  PubMed  Article  Google Scholar  More

  • in

    Variation in size and shape of toxin glands among cane toads from native-range and invasive populations

    1.
    Caro, T. M. Antipredator Defenses in Birds and Mammals (University of Chicago Press, 2005).
    2.
    Emlen, D. J. The evolution of animal weapons. Annu. Rev. Ecol. Evol. Syst. 39, 387–413 (2008).
    Article  Google Scholar 

    3.
    Toledo, L. F., Sazima, I. & Haddad, C. F. Behavioural defences of anurans: An overview. Ethol. Ecol. Evol. 23, 1–25 (2011).
    Article  Google Scholar 

    4.
    Lima, S. L. & Dill, L. M. Behavioral decisions made under the risk of predation: A review and prospectus. Can. J. Zool. 68, 619–640 (1990).
    Article  Google Scholar 

    5.
    Pettorelli, N., Coulson, T., Durant, S. M. & Gaillard, J. Predation, individual variability and vertebrate population dynamics. Oecologia 167, 305–314 (2011).
    ADS  PubMed  Article  Google Scholar 

    6.
    Stankowich, T. Armed and dangerous: predicting the presence and function of defensive weaponry in mammals. Adapt. Behav. 20, 32–43 (2011).
    Article  Google Scholar 

    7.
    Longson, C. G. & Joss, J. M. P. Optimal toxicity in animals: Predicting the optimal level of chemical defences. Funct. Ecol. 20, 731–735 (2006).
    Article  Google Scholar 

    8.
    Relyea, R. A. Predators come and predators go: The reversibility of predator-induced traits. Ecology 84, 1840–1848 (2003).
    Article  Google Scholar 

    9.
    Tollrian, R. & Harvell, D. The Ecology and Evolution of Inducible Defenses (Princeton University Press, 1999).

    10.
    Daly, D., Higginson, A. D., Chen, D., Ruxton, G. D. & Speed, M. P. Density-dependent investment in costly anti-predator defenses: An explanation for the weak survival benefit of group living. Ecol. Lett. 15, 576–583 (2012).
    PubMed  Article  Google Scholar 

    11.
    Kosmala, G., Brown, G. P. & Shine, R. Thin-skinned invaders: Geographic variation in the structure of the skin among populations of cane toads (Rhinella marina). Biol. J. Linn. Soc. 131, 611–621 (2020).
    Article  Google Scholar 

    12.
    Duellman, W. E. & Trueb, L. Biology of Amphibians (McGraw-Hill, 1994).

    13.
    Wells, K. The Ecology and Behavior of Amphibians (University of Chicago Press, 2007).

    14.
    König, E., Bininda-Emonds, O. R. P. & Shaw, C. The diversity and evolution of anuran skin peptides. Peptides 63, 96–117 (2014).
    PubMed  Article  CAS  Google Scholar 

    15.
    Hettyey, A., Tóth, Z. & Van Buskirk, J. Inducible chemical defences in animals. Oikos 123, 1025–1028 (2014).
    Article  Google Scholar 

    16.
    Blennerhasset, R., Bell-Anderson, K., Shine, R. & Brown, G. P. The cost of chemical defence: The impact of toxin depletion on growth and behaviour of cane toads (Rhinella marina). Proc. R. Soc. B. 286, 20190867 (2019).
    Article  CAS  Google Scholar 

    17.
    Chen, W., Hudson, C. M., DeVore, J. L. & Shine, R. Sex and weaponry: The distribution of toxin-storage glands on the bodies of male and female cane toads (Rhinella marina). Ecol. Evol. 7, 8950–8957 (2017).
    PubMed  PubMed Central  Article  Google Scholar 

    18.
    O’Donohoe, M. A. et al. Diversity and evolution of the parotoid macrogland in true toads (Anura: Bufonidae). Zool. J. Linn. Soc. 187, 453–478 (2019).
    Article  Google Scholar 

    19.
    Shine, R. The ecological impact of invasive cane toads (Bufo marinus) in Australia. Q. Rev. Biol. 85, 253–291 (2010).
    PubMed  Article  Google Scholar 

    20.
    Ujvari, B. et al. Isolation breeds naivety: island living robs Australian varanid lizards of toad-toxin immunity via four-base-pair mutation. Evolution 67, 289–294 (2013).
    PubMed  Article  Google Scholar 

    21.
    Pearcy, A. Selective feeding in Keelback snakes Tropidonophis mairii in an Australian wetland. Aust. Zool. 35, 843–845 (2011).
    Article  Google Scholar 

    22.
    Llewelyn, J. et al. Behavioural responses of an Australian colubrid snake (Dendrelaphis punctulatus) to a novel toxic prey item (the Cane Toad Rhinella marina). Biol. Invasions 20, 2507–2516 (2018).
    Article  Google Scholar 

    23.
    van Bocxlaer, I. et al. Gradual adaptation toward a range-expansion phenotype initiated the global radiation of toads. Science 327, 679–682 (2010).
    ADS  PubMed  Article  CAS  Google Scholar 

    24.
    Hudson, C. M., Vidal-García, M., Murray, T. G. & Shine, R. The accelerating anuran: evolution of locomotor performance in cane toads (Rhinella marina, Bufonidae) at an invasion front. Proc. R. Soc. B 287, 20201964 (2020).
    PubMed  Article  Google Scholar 

    25.
    Ward-Fear, G., Greenlees, M. J. & Shine, R. Toads on lava: spatial ecology and habitat use of invasive cane toads (Rhinella marina) in Hawai’i. PLoS ONE 11, e0151700 (2016).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    26.
    Ward-Fear, G., Pearson, D. J., Brown, G. P. & Shine, R. Ecological immunization: in situ training of free-ranging predatory lizards reduces their vulnerability to invasive toxic prey. Biol. Lett. 12, 20150863 (2016).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    27.
    Crossland, M. R., Brown, G. P., Anstis, M., Shilton, C. & Shine, R. Mass mortality of native anuran tadpoles in tropical Australia due to the invasive cane toad (Bufo marinus). Biol. Conserv. 141, 2387–2394 (2008).
    Article  Google Scholar 

    28.
    Hayes, R. A., Crossland, M. R., Hagman, M., Capon, R. J. & Shine, R. Ontogenetic variation in the chemical defences of cane toads (Bufo marinus): Toxin profiles and effects on predators. J. Chem. Ecol. 35, 391–399 (2009).
    CAS  PubMed  Article  Google Scholar 

    29.
    Hagman, M., Hayes, R. A., Capon, R. J. & Shine, R. Alarm cues experienced by cane toad tadpoles affect post-metamorphic morphology and chemical defences. Funct. Ecol. 23, 126–132 (2009).
    Article  Google Scholar 

    30.
    Üveges, B. et al. Age-and environment-dependent changes in chemical defences of larval and post-metamorphic toads. BMC Evol. Biol. 17, 137 (2017).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    31.
    Üveges, B. et al. Chemical defense of toad tadpoles under risk by four predator species. Ecol. Evol. 9, 6287–6299 (2019).
    PubMed  PubMed Central  Article  Google Scholar 

    32.
    Bókony, V., Üveges, B., Verebélyi, V., Ujhegyi, N. & Móricz, Á. M. Toads phenotypically adjust their chemical defences to anthropogenic habitat change. Sci. Rep. 9, 3163 (2019).
    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

    33.
    Hettyey, A. et al. Predator-induced changes in the chemical defence of a vertebrate. J. Anim. Ecol. 88, 1925–1935 (2019).
    PubMed  Article  Google Scholar 

    34.
    Hudson, C. M, Brown, G. P., Stuart, K. & Shine, R. Sexual and geographic divergence in head widths of invasive cane toads, Rhinella marina (Anura: Bufonidae) is driven by both rapid evolution and plasticity. Biol. J. Linn. Soc. 124, 188–199 (2018).

    35.
    Phillips, B. L., Brown, G. P., Webb, J. K. & Shine, R. Invasion and the evolution of speed in toads. Nature 439, 803 (2006).
    ADS  CAS  PubMed  Article  Google Scholar 

    36.
    Hudson, C. M., McCurry, M. R., Lundgren, P., McHenry, C. R. & Shine, R. Constructing an invasion machine: The rapid evolution of a dispersal-enhancing phenotype during the cane toad invasion of Australia. PLoS ONE 11, e0156950 (2016).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    37.
    Hudson, C. M., Brown, G. P. & Shine, R. It is lonely at the front: Contrasting evolutionary trajectories in male and female invaders. R. Soc. Open Sci. 3, 160687 (2016).
    ADS  PubMed  PubMed Central  Article  Google Scholar 

    38.
    Brown, G., Kelehear, C. & Shine, R. The early toad gets the worm: Cane toads at an invasion front benefit from higher prey availability. J. Anim. Ecol. 82, 854–862 (2013).
    PubMed  Article  Google Scholar 

    39.
    Shine, R., Brown, G. P. & Phillips, B. L. An evolutionary process that assembles phenotypes through space rather than time. Proc. Natl Acad. Sci. USA 108, 5708–5711 (2011).
    ADS  CAS  PubMed  Article  Google Scholar 

    40.
    Phillips, B. & Shine, R. The morphology, and hence impact, of an invasive species (the cane toad, Bufo marinus) changes with time since colonization. Anim. Conserv. 8, 407–413 (2005).
    Article  Google Scholar 

    41.
    Roff, D. A. Comparing sire and dam estimates of heritability: Jackknife and likelihood approaches. Heredity 100, 32–38 (2008).
    CAS  PubMed  Article  Google Scholar 

    42.
    Kliber, A. & Eckert, C. G. Interaction between founder effect and selection during biological invasion in an aquatic plant. Evolution 59, 1900–1913 (2005).
    CAS  PubMed  Google Scholar 

    43.
    Shine, R. Cane Toad Wars (University of California Press, 2018).

    44.
    Toledo, R. C. & Jared, C. Cutaneous adaptations to water balance in amphibians. Comp. Biochem. Physiol. A 105, 593–608 (1993).
    Article  Google Scholar 

    45.
    Kosmala, G., Brown, G. P., Shine, R. & Christian, K. Skin resistance to water gain and loss has changed in cane toads (Rhinella marina) during their Australian invasion. Ecol. Evol. 10, 13071–13079 (2020).
    PubMed  PubMed Central  Article  Google Scholar 

    46.
    Crossland, M. R. & Shine, R. Cues for cannibalism: Cane toad tadpoles use chemical signals to locate and consume conspecific eggs. Oikos 120, 327–332 (2011).
    Article  Google Scholar 

    47.
    DeVore, J. L., Crossland, M. & Shine, R. Tradeoffs affect the adaptive value of plasticity: Stronger cannibal-induced defenses incur greater costs in toad larvae. Ecol. Monogr. https://doi.org/10.1002/ecm.1426 (2020).
    Article  Google Scholar 

    48.
    Greenlees, M. J. & Shine, R. Impacts of eggs and tadpoles of the invasive cane toad (Bufo marinus) on aquatic predators in tropical Australia. Austral Ecol. 36, 53–58 (2011).
    Article  Google Scholar 

    49.
    Somaweera, R., Crossland, M. R. & Shine, R. Assessing the potential impact of invasive cane toads on a commercial freshwater fishery in tropical Australia. Wildl. Res. 38, 380–385 (2011).
    Article  Google Scholar 

    50.
    Cao, Y., Cui, K., Pan, H., Wu, J. & Wang, L. The impact of multiple climatic and geographic factors on the chemical defences of Asian toads (Bufo gargarizans Cantor). Sci. Rep. 9, 17236 (2019).
    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

    51.
    Hague, M. T. J., Stokes, A. N., Feldman, C. R., Brodie, E. D. Jr. & Brodie, E. D. III. The geographic mosaic of arms race coevolution is closely matched to prey population structure. Evol. Lett. 4, 317–332 (2020).

    52.
    Jared, C. et al. Parotoid macroglands in toad (Rhinella jimi): Their structure and functioning in passive defence. Toxicon 54, 197–207 (2009).
    CAS  PubMed  Article  Google Scholar 

    53.
    Toledo, R. C. & Jared, C. Cutaneous granular glands and amphibian venoms. Comp. Biochem. Physiol. A 111, 1–29 (1995).
    ADS  Article  Google Scholar 

    54.
    Maciel, N. M. et al. Composition of indolealkylamines of Bufo rubescens cutaneous secretions compared to six other Brazilian bufonids with phylogenetic implications. Comp. Biochem. Physiol. B 134, 641–649 (2003).
    PubMed  Article  CAS  Google Scholar 

    55.
    Sciani, J. M., Angeli, C. B., Antoniazzi, M. M., Jared, C. & Pimenta, D. C. Differences and similarities among parotoid macrogland secretions in South American toads: A preliminary biochemical delineation. Sci. World J. 2013, 937407 (2013).
    Article  CAS  Google Scholar 

    56.
    Habermehl, G. Venomous Animals and Their Toxins (Springer-Verlag, 1981).

    57.
    Garrett, C. M. & Boyer, D. M. Bufo marinus (cane toad) predation. Herpetol. Rev. 24, 148 (1993).
    Google Scholar 

    58.
    Pineau, X. & Romanoff, C. Envenomation of domestic carnivores. Rec. Méd. Vét. 171, 182–192 (1995).
    Google Scholar 

    59.
    Sakate, M. & Lucas de Oliveira, P. C. Toad envenoming in dogs: effects and treatment. J. Venom. Anim. Toxins 6, 52–62 (2000).

    60.
    Slade, R. W. & Moritz, C. Phylogeography of Bufo marinus from its natural and introduced ranges. Proc. R. Soc. B 265, 769–777 (1998).
    CAS  PubMed  Article  Google Scholar 

    61.
    Urban, M. C., Phillips, B. L., Skelly, D. K. & Shine, R. The cane toad’s (Chaunus [Bufo] marinus) increasing ability to invade Australia is revealed by a dynamically updated range model. Proc. R. Soc. B 274, 1413–1419 (2007).
    PubMed  Article  Google Scholar 

    62.
    Urban, M., Phillips, B. L., Skelly, D. K. & Shine, R. A toad more traveled: The heterogeneous invasion dynamics of cane toads in Australia. Am. Nat. 171, 134–148 (2008).
    Article  Google Scholar 

    63.
    Nullet, D., Juvik, J. O. & Wall, A. A Hawaiian mountain climate cross-section. Clim. Res. 5, 131–137 (1995).
    Article  Google Scholar 

    64.
    Kelehear, C. & Shine, R. Non-reproductive male cane toads (Rhinella marina) withhold sex-identifying information from their rivals. Biol. Lett. 15, 2019046 (2019).
    Article  Google Scholar 

    65.
    Shine, R., Everitt, C., Woods, D. & Pearson, D. J. An evaluation of methods used to cull invasive cane toads in tropical Australia. J. Pest Sci. 91, 1081–1091 (2018).
    Article  Google Scholar 

    66.
    Phillips, B. L. et al. Parasites and pathogens lag behind their host during periods of host range-advance. Ecology 91, 872–881 (2010).
    PubMed  Article  Google Scholar 

    67.
    Hudson, C. M., Brown, G. P. & Shine, R. Effects of toe-clipping on growth, body condition, and locomotion of cane toads (Rhinella marina). Copeia 105, 257–260 (2017).
    Article  Google Scholar 

    68.
    Wilson, A. J. et al. An ecologist’s guide to the animal model. J. Anim. Ecol. 79, 13–26 (2010).
    PubMed  Article  Google Scholar  More

  • in

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

  • in

    Biological performance and oviposition preference of tomato pinworm Tuta absoluta when offered a range of Solanaceous host plants

    1.
    di Castri, F. History of biological invasions with emphasis on the Old World. In Biological invasions: a global perspective, (ed. Drake J., di Castri, F., Groves, R., Kruger, F., Mooney, H. A., Rejmanek, M., Williamson, M.) 1–30 (Wiley, New York, 1989).
    2.
    Reeve, E. Domestication of Plants in the Old World: The origin and spread of cultivated plants in West Asia, Europe, and the Nile Valley (ed. Zohary, D. & Hopf, M.) (Clarendon Press, Oxford, 1994).

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

    4.
    Worner, S. P. & Gevrey, M. Modelling global insect pest species assemblages to determine risk of invasion. J. Appl. Ecol. 43, 858–867 (2006).
    Article  Google Scholar 

    5.
    Desneux, N., Luna, M. G., Guillemaud, T. & Urbaneja, A. The invasive South American tomato pinworm, Tuta absoluta, continues to spread in Afro-Eurasia and beyond: the new threat to tomato world production. J. Pest Sci. 84, 403–408 (2011).
    Article  Google Scholar 

    6.
    Desneux, N. et al. Biological invasion of European tomato crops by Tuta absoluta: ecology, geographic expansion and prospects for biological control. J. Pest Sci. 83, 197–215 (2010).
    Article  Google Scholar 

    7.
    Sridhar, V., Chakravarthy, A. K. & Asokan, R. New record of the invasive South American tomato leaf miner, Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) in India. Pest. Manag. Hort. 20, 148–154 (2014).
    Google Scholar 

    8.
    Galdino, T. V. S. et al. Is the performance of a specialist herbivore affected by female choices and the adaptability of the offspring?. PLoS ONE 10, 1–18 (2015).
    Article  CAS  Google Scholar 

    9.
    Campos, M. R., Biondi, A., Adiga, A., Guedes, R. N. C. & Desneux, N. From the Western Palaearctic region to beyond: Tuta absoluta 10 years after invading Europe. J. Pest Sci. 90, 787–796 (2017).
    Article  Google Scholar 

    10.
    Cherif, A. & François, V. A review of Tuta absoluta (Lepidoptera: Gelechiidae) host plants and their impact on management strategies. Biotechnol. Agron. Soc. Environ. 23 (4) (2019).

    11.
    Picanço, M. C., Bacci, L., Crespo, A. L. B., Miranda, M. M. M. & Martins, J. C. Effect of integrated pest management practices on tomato production and conservation of natural enemies. Agric. For. Entomol. 9, 327–335 (2007).
    Article  Google Scholar 

    12.
    Biondi, A., Guedes, R. N. C., Wan, F. H. & Desneux, N. Ecology, worldwide spread, and Management of the Invasive South American Tomato Pinworm, Tuta absoluta: past, present, and future. Annu. Rev. Entomol. 63, 239–258 (2018).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    13.
    Guedes, R. N. C. et al. Insecticide resistance in the tomato pinworm Tuta absoluta: patterns, spread, mechanisms, management and outlook. J. Pest Sci. https://doi.org/10.1007/s10340-019-01086-9 (2019).
    Article  Google Scholar 

    14.
    Santana, P. A., Kumar, L., Da Silva, R. S. & Picanço, M. C. Global geographic distribution of Tuta absoluta as affected by climate change. J. Pest Sci. 92, 1373–1385 (2019).
    Article  Google Scholar 

    15.
    Luna, M. G. et al. Biological control of Tuta absoluta in Argentina and Italy: evaluation of indigenous insects as natural enemies. EPPO Bulletin 42, 260–267 (2012).
    ADS  Article  Google Scholar 

    16.
    Bacci, L. et al. Natural mortality factors influencing the tomato leafminer Tuta absoluta in open-field tomato crops in South America. Pest Manage. Sci. https://doi.org/10.1002/ps.5173 (2019).
    Article  Google Scholar 

    17.
    Megido, R. C., Brostaux, Y., Haubruge, E. & Verheggen, F. J. Propensity of the tomato leafminer, Tuta absoluta (Lepidoptera: Gelechiidae), to develop on four potato plant varieties. Am. Potato J. 90, 255–260 (2013).
    Article  Google Scholar 

    18.
    Sylla, S., Brévault, T., Monticelli, L. S., Diarra, K. & Desneux, N. Geographic variation of host preference by the invasive tomato leaf miner Tuta absoluta: implications for host range expansion. J. Pest Sci. https://doi.org/10.1007/s10340-019-01094-9 (2019).
    Article  Google Scholar 

    19.
    Vargas, H. C. Observaciones sobre la biologıa y enemigos naturales de la polilla del tomate, Gnorimoschema absoluta (Meyrick) (Lepidoptera: Gelechiidae). Idesia 1, 75–110 (1970).
    Google Scholar 

    20.
    Gilardón, E., Pocovi, M., Hernández, C., Collavino, G. & Olsen, A. Papel da 2-tridecanona e dos tricomas glandulares tipo VI na resistência do tomateiro a Tuta absoluta. Pesqui. Agropecu. Bras. 36, 929–933 (2001).
    Article  Google Scholar 

    21.
    Pereyra, P. C. & Sánchez, N. E. Effect of two solanaceous plants on developmental and population parameters of the tomato leaf miner, Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae). Neotrop. Entomol. 35, 671–676 (2006).
    PubMed  Article  PubMed Central  Google Scholar 

    22.
    Moreira, L. A. et al. Antibiosis of eight Lycopersicon genotypes to Tuta absoluta (Lepidoptera: Gelechiidae). Rer. Ceres 56, 283–287 (2009).
    Google Scholar 

    23.
    Negi, S., Sharma, P. L., Sharma, K. C. & Verma, S. C. Effect of host plants on developmental and population parameters of invasive leafminer, Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae). Phytoparasitica 46, 213–221 (2018).
    Article  Google Scholar 

    24.
    Satishchandra, K. N., Chakravarthy, A. K., Özgökçe, M. S. & Atlihan, R. Population growth potential of Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) on tomato, potato, and eggplant. J. Appl. Entomol. 143, 518–526 (2019).
    Article  Google Scholar 

    25.
    Younes, A. A., Zohdy, N. Z. M., Abulfadl, H. A. & Fathy, R. Life table parameters of the tomato leafminer, Tuta absoluta (Lepidoptera: Gelechiidae), on three solanaceous host plants. Afr. Entomol. 27, 461–467 (2019).
    Article  Google Scholar 

    26.
    Cherif, A., Attia-Barhoumi, S., Mansour, R., Zappalà, L. & Grissa-Lebdi, K. Elucidating key biological parameters of Tuta absoluta on different host plants and under various temperature and relative humidity regimes. Entomol. Gen. https://doi.org/10.1127/entomologia/2019/0685 (2019).
    Article  Google Scholar 

    27.
    Knapp, S. Tobacco to tomatoes: a phylogenetic perspective on fruit diversity in the Solanaceae. J. Exp. Bot. 53, 2001–2022 (2002).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    28.
    Silva, G. A. et al. Control failure likelihood and spatial dependence of insecticide resistance in the tomato pinworm, Tuta absoluta. Pest Manage. Sci. 67, 913–920 (2011).
    ADS  CAS  Article  Google Scholar 

    29.
    Southwood, T. R. E. & Hendersen, P. A. Ecological Methods (ed. Southwood, T. R. E. & Hendersen, P. A.) (Blackwell Science, 2000).

    30.
    Maia, H. N., Luiz, A. A. J. & Campanhola, C. Statistical inference on associated fertility life table parameters using jackknife technique: computational aspects. J. Econ. Entomol. 93, 511–518 (2000).
    Article  Google Scholar 

    31.
    Paré, P. W. & Tumlinson, J. H. Plant volatiles as a defense against insect herbivores. Plant Physiol. 121, 325–332 (1999).
    PubMed  PubMed Central  Article  Google Scholar 

    32.
    Feeny, P., Stadler, E., Ahman, I. & Carter, M. Effects of plant odor on oviposition by the black swallowtail butterfly, Papilio polyxenes (Lepidoptera: Papilionidae). J. Insect. Behav. 2, 803–827 (1989).
    Article  Google Scholar 

    33.
    Proffit, M. et al. Attraction and oviposition of Tuta absoluta females in response to tomato leaf volatiles. J. Chem. Ecol. 37, 565–574 (2011).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    34.
    Friedman, M. Analysis of biologically active compounds in potatoes (Solanum tuberosum), tomatoes (Lycopersicon esculentum), and jimson weed (Datura stramonium) seeds. J. Chromatogr. A 1054, 143–155 (2004).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    35.
    Antônio, A. D. C., Silva, D. J. H. D., Picanço, M. C., Santos, N. T. & Fernandes, M. E. S. Tomato plant inheritance of antixenotic resistance to tomato leafminer. Pesqui. Agropecu. Bras. 46, 74–80 (2011).
    Article  Google Scholar 

    36.
    Miranda, M. M. M., Picanço, M., Zanuncio, J. C. & Guedes, R. N. C. Ecological life table of Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae). Biocontrol Sci. Technol. 8, 597–606 (1998).
    Article  Google Scholar 

    37.
    Zalucki, M. P., Clarke, A. R. & Malcolm, S. B. Ecology and behavior of first instar larval lepidoptera. Annu. Rev. Entomol. 47, 361–393 (2002).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    38.
    Krainacker, D. A., Carey, J. R. & Vargas, R. I. Effect of larval host on life history traits on the Mediterranean fruit fly Ceratitis capitata. Oecologia 73, 583–590 (1987).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    39.
    Razmjou, J., Naseri, B. & Hemati, S. A. Comparative performance of the cotton bollworm, Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) on various host plants. J. Pest. Sci. 87, 29–37 (2014).
    Article  Google Scholar 

    40.
    Calvo, D. & Molina, J. M. Fecundity-body size relationship and other reproductive aspects of Streblote panda (Lepidoptera: Lasiocampidae). Ann. Entomol. Soc. Am. 98, 191–196 (2005).
    Article  Google Scholar 

    41.
    Awmack, C. S. & Leather, S. R. Host plant quality and fecundity in herbivorous insects. Annu. Rev. Entomol. 47, 817–844 (2000).
    Article  Google Scholar 

    42.
    Boggs, C. L. & Freeman, K. D. Larval food limitation in butterflies: effects on adult resource allocation and fitness. Oecologia 144, 353–361 (2005).
    ADS  PubMed  Article  Google Scholar 

    43.
    Tammaru, T., Esperk, T. & Castellanos, I. No evidence for costs of being large in females of Orgyia spp. (Lepidoptera, Lymantriidae): larger is always better. Oecologia 133, 430–438 (2002).
    ADS  PubMed  Article  Google Scholar 

    44.
    Calvo, D. & Molina, J. M. Utilization of blueberry by the lappet moth Streblote panda Hübner (Lepidoptera: Lasiocampidae): survival, development and larval performance. J. Econ. Entomol. 97, 957–963 (2004).
    CAS  PubMed  Article  Google Scholar 

    45.
    Kanle Satishchandra, N., Chakravarthy, A. K., Özgökçe, M. S. & Atlihan, R. Population growth potential of Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) on tomato, potato, and eggplant. J. Appl. Entomol. 143, 518–526 (2019).
    Article  Google Scholar 

    46.
    Gotelli, N. J. A primer of ecology (ed. Gotelli, N. J.) (Sinauer Associates Incorporated Press, 1995).

    47.
    Birch, L. The intrinsic rate of natural increase of an insect population. J. Econ. Entomol. 17, 15–26 (1948).
    Google Scholar 

    48.
    Lage, J., Skovmand, B. & Andersen, S. B. Characterization of greenbug (Homoptera: Aphididae) resistance in synthetic hexaploid wheats. J. Econ. Entomol. 96, 1922–1928 (2003).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    49.
    Smith, C. M. Plant Resistance to Arthropods: Molecular and Conventional Approaches (ed. Smith, C. M.) (Springer, Berlin, 2005).

    50.
    Fathi, S. A. A., Bozorg-Amirkalaee, M. & Sarfaraz, R. M. Preference and performance of Plutella xylostella (L.) (Lepidoptera: Plutellidae) on canola cultivars. J. Pest Sci. 84, 41–47 (2011).
    Article  Google Scholar 

    51.
    Thomazini, A. P. B. W., Vendramim, J. D., Brunherotto, R. & Lopes, M. T. Efeito de genótipos de tomateiro sobre a biologia e oviposição de Tuta absoluta (Meyrick) (Lep.: Gelechiidae). Neotrop. Entomol. 30, 283–288 (2001).
    Article  Google Scholar 

    52.
    Boiça Junior, A. L., Bottega, D. B., Lourenção, A. L. & Rodrigues, N. E. L. Não preferência para oviposição e alimentação por Tuta absoluta (Meyrick) em genótipos de tomateiro. Arq. Inst. Biol. 79, 541–548 (2012).
    Article  Google Scholar 

    53.
    Erdogan, P. & Babaroglu, N. E. Life table of the tomato leaf miner, Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae). J. Agric. Facul. Gaziosmanpasa Univ. 31, 80–89 (2014).
    Google Scholar 

    54.
    Malakar, R. & Tingey, W. M. Glandular trichomes of Solanum berthaultii and its hybrids with potato deter oviposition and impair growth of potato tuber moth. Entomol. Exp. Appl. 94, 249–257 (2000).
    Article  Google Scholar 

    55.
    Horgan, F. G., Quiring, D. T., Lagnaoui, A., Salas, A. R. & Pelletier, Y. Periderm and cortex based resistance to tuber feeding Phthorimaea operculella in two wild potato species. Entomol. Exp. Appl. 125, 249–258 (2007).
    Article  Google Scholar 

    56.
    Mackauer, M. Genetic problems in the production of biological control agents. Annu. Rev. Entomol. 21, 369–385 (1976).
    Article  Google Scholar 

    57.
    Spielman, D. & Brook, B. W. Frankham R (2004) Most species are not driven to extinction before genetic factors impact them. Proc. Natl. Acad. Sci. USA 101, 15261–15264 (2000).
    ADS  Article  CAS  Google Scholar 

    58.
    Urbaneja, A., Vercher, R., Navarro, V., García Marí, F. & Porcuna, J. L. La polilla del tomate, Tuta absoluta. Phytoma 194, 16–23 (2007).
    Google Scholar 

    59.
    Campos, R. G. Control químico del “minador de hojas y tallos de la papa” (Scrobipalpula absoluta Meyrick) en el valle del Cañete. Rev. Peru Entomol. 19, 102–106 (1976).
    Google Scholar 

    60.
    Garzia, T. G. Physalis peruviana L. (Solanaceae), a host plant of Tuta absoluta in Italy. IOBC/WPRS Bull 49, 231–232 (2009).

    61.
    Bawin, T., Dujeu, D., De Backer, L., Francis, F. & Verheggen, F. J. Ability of Tuta absoluta (Lepidoptera: Gelechiidae) to develop on alternative host plant species. Can. Entomol. 148, 434–442 (2016).
    Article  Google Scholar  More

  • in

    A record of vapour pressure deficit preserved in wood and soil across biomes

    1.
    Almeida, A. C. & Landsberg, J. J. Evaluating methods of estimating global radiation and vapor pressure deficit using a dense network of automatic weather stations in coastal Brazil. Agric. For. Meteorol. 118, 237–250 (2003).
    ADS  Article  Google Scholar 
    2.
    Hashimoto, H. et al. Satellite-based estimation of surface vapor pressure deficits using MODIS land surface temperature data. Remote Sens. Environ. 112, 142–155 (2008).
    ADS  Article  Google Scholar 

    3.
    Silva, L. C. R. & Lambers, H. Soil-plant-atmosphere interactions : structure, function, and predictive scaling for climate change mitigation. Plant Soil https://doi.org/10.1007/s11104-020-04427-1 (2020).
    Article  Google Scholar 

    4.
    Maxwell, T. M. & Silva, L. C. R. A state factor model for ecosystem carbon: water relations. Trends Plant Sci. 25, 652–660 (2020).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    5.
    Penuelas, J. & Sardans, J. Developing holistic models of the structure and function of the soil/plant/atmosphere continuum. Plant Soil https://doi.org/10.1007/s11104-020-04641-x (2020).
    Article  PubMed  PubMed Central  Google Scholar 

    6.
    Seager, R. et al. Climatology, variability, and trends in the U.S. vapor pressure deficit, an important fire-related meteorological quantity. J. Appl. Meteorol. Climatol. 54, 1121–1141 (2015).
    ADS  Article  Google Scholar 

    7.
    Retallack, G. J. Greenhouse crises of the past 300 million years. Bull. Geol. Soc. Am. 121, 1441–1455 (2009).
    CAS  Article  Google Scholar 

    8.
    Barbour, M. M., Walcroft, A. S. & Farquhar, G. D. Seasonal variation in δ13C and δ18O of cellulose from growth rings of Pinus radiata. Plant. Cell Environ. 25, 1483–1499 (2002).
    Article  Google Scholar 

    9.
    Breecker, D. O., Sharp, Z. D. & McFadden, L. D. Seasonal bias in the formation and stable isotopic composition of pedogenic carbonate in modern soils from central New Mexico, USA. Bull. Geol. Soc. Am. 121, 630–640 (2009).
    CAS  Article  Google Scholar 

    10.
    Farquhar, G. D., Ehleringer, J. R. & Hubick, K. T. Carbon isotope discrimination and photosynthesis. Annu. Rev. Plant Physiol. Plant Mol. Biol. 40, 503–537 (1989).
    CAS  Article  Google Scholar 

    11.
    Cerling, T. E. Use of carbon isotopes in paleosols as an indicator of the P(CO2) of the paleoatmosphere. Global Biogeochem. Cycles 6, 307–314 (1992).
    ADS  CAS  Article  Google Scholar 

    12.
    Scheidegger, Y., Saurer, M., Bahn, M. & Siegwolf, R. Linking stable oxygen and carbon isotopes with stomatal conductance and photosynthetic capacity: a conceptual model. Oecologia 125, 350–357 (2000).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    13.
    Maxwell, T. M., Silva, L. C. R. & Horwath, W. R. Using multielement isotopic analysis to decipher drought impacts and adaptive management in ancient agricultural systems: Fig. 1. Proc. Natl. Acad. Sci. 111, E4807–E4808 (2014).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    14.
    Barbour, M. M. & Farquhar, A. Relative humidity- and ABA-induced variation in carbon and oxygen isotope ratios of cotton leaves. Plant Cell Environ. https://doi.org/10.1046/j.1365-3040.2000.00575.x (2000).
    Article  Google Scholar 

    15.
    Roden, J. S., Lin, G. & Ehleringer, J. R. A mechanistic model for interpretation of hydrogen and oxygen isotope ratios in tree-ring cellulose. Geochim. Cosmochim. Acta 64, 21–35 (2000).
    ADS  CAS  Article  Google Scholar 

    16.
    Roden, J. S. & Farquhar, G. D. A controlled test of the dual-isotope approach for the interpretation of stable carbon and oxygen isotope ratio variation in tree rings. Tree Physiol. 32, 490–503 (2012).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    17.
    Saurer, M., Aellen, K. & Siegwolf, R. Correlating δ13C and δ18O in cellulose of trees. Plant Cell Environ. 20, 1543–1550 (1997).
    Article  Google Scholar 

    18.
    Johnstone, J. A., Roden, J. S. & Dawson, T. E. Oxygen and carbon stable isotopes in coast redwood tree rings respond to spring and summer climate signals. J. Geophys. Res. Biogeosciences 118, 1438–1450 (2013).
    ADS  CAS  Article  Google Scholar 

    19.
    Sidorova, O. V. et al. Do centennial tree-ring and stable isotope trends of Larix gmelinii (Rupr.) Rupr. indicate increasing water shortage in the Siberian north?. Oecologia 161, 825–835 (2009).
    ADS  PubMed  Article  PubMed Central  Google Scholar 

    20.
    Yakir, D. & Sternberg, L. D. S. L. The use of stable isotopes to study ecosystem gas exchange. Oecologia 123, 297–311 (2000).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    21.
    McCarroll, D. & Loader, N. J. Stable isotopes in tree rings. Quat. Sci. Rev. 23, 771–801 (2004).
    ADS  Article  Google Scholar 

    22.
    Koch, P. L. Isotopic reconstruction of past continental environments. Annu. Rev. Earth Planet. Sci. 26, 573–613 (1998).
    ADS  CAS  Article  Google Scholar 

    23.
    Hook, B. A., Halfar, J., Gedalof, Z., Bollmann, J. & Schulze, D. J. Stable isotope paleoclimatology of the earliest Eocene using kimberlite-hosted mummified wood from the Canadian Subarctic. Biogeosciences 12, 5899–5914 (2015).
    ADS  Article  Google Scholar 

    24.
    Zhang, H. & Nobel, P. S. Dependency of cI/ca and leaf transpiration efficiency on the vapour pressure deficit. Funct. Plant Biol. 23, 561–568 (1996).
    Article  Google Scholar 

    25.
    Silva, L. C. R., Pedroso, G., Doane, T. A., Mukome, F. N. D. & Horwath, W. R. Beyond the cellulose: oxygen isotope composition of plant lipids as a proxy for terrestrial water balance. Geochemical Perspect. Lett. https://doi.org/10.7185/geochemlet.1504 (2015).
    Article  Google Scholar 

    26.
    Breecker, D. O., Sharp, Z. D. & McFadden, L. D. Atmospheric CO2 concentrations during ancient greenhouse climates were similar to those predicted for A.D. 2100. Proc. Natl. Acad. Sci. 107, 576–580 (2010).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    27.
    Breecker, D. O., McFadden, L. D., Sharp, Z. D., Martinez, M. & Litvak, M. E. Deep autotrophic soil respiration in shrubland and woodland ecosystems in central New Mexico. Ecosystems 15, 83–96 (2012).
    CAS  Article  Google Scholar 

    28.
    Abels, H. A. et al. Carbon isotope excursions in paleosol carbonate marking five early Eocene hyperthermals in the Bighorn Basin, Wyoming. Clim. Past Discuss. 11, 1857–1885 (2015).
    Article  Google Scholar 

    29.
    Leary, R. J., Quade, J., DeCelles, P. G. & Reynolds, A. Evidence from paleosols for low to moderate elevation of the India-Asia suture zone during mid-Cenozoic time. Geology 45, 399–402 (2017).
    ADS  Article  Google Scholar 

    30.
    Silva, L. C. R. et al. Expansion of gallery forests into central Brazilian savannas. Glob. Chang. Biol. 14, 2108–2118 (2008).
    ADS  Article  Google Scholar 

    31.
    Oerter, E. J. & Amundson, R. Climate controls on spatial temporal variations in the formation of pedogenic carbonate in the western Great Basin of North Americ. Bull. Geol. Soc. Am. 128, 1095–1104 (2016).
    Article  Google Scholar 

    32.
    Quade, J., Cerling, T. E. & Bowman, J. R. Systematic variations in the carbon and oxygen isotopic composition of pedogenic carbonate along elevation trasects in the southern Great Basin, United States. Geol. Soc. Am. Bull. 101, 464–475 (1989).
    ADS  CAS  Article  Google Scholar 

    33.
    Zamanian, K., Pustovoytov, K. & Kuzyakov, Y. Pedogenic carbonates : forms and formation processes. Earth Sci. Rev. 157, 1–17 (2016).
    ADS  CAS  Article  Google Scholar 

    34.
    Botsyun, S. et al. Revised paleoaltimetry data show low Tibetan Plateau elevation during the Eocene. Science 80, 363 (2019).
    Google Scholar 

    35.
    Maxwell, T. M., Silva, L. C. R. & Horwath, W. R. Predictable oxygen isotope exchange between plant lipids and environmental water: implications for ecosystem water balance reconstruction. J. Geophys. Res. Biogeosciences https://doi.org/10.1029/2018JG004553 (2018).
    Article  Google Scholar 

    36.
    Nyachoti, S., Jin, L., Tweedie, C. E. & Ma, L. Insight into factors controlling formation rates of pedogenic carbonates: a combined geochemical and isotopic approach in dryland soils of the US Southwest. Chem. Geol. https://doi.org/10.1016/j.chemgeo.2017.10.014 (2017).
    Article  Google Scholar 

    37.
    Sanyal, P., Bhattacharya, S. K., Kumar, R., Ghosh, S. K. & Sangode, S. J. Mio-Pliocene monsoonal record from Himalayan foreland basin (Indian Siwalik) and its relation to vegetational change. Palaeogeogr. Palaeoclimatol. Palaeoecol. 205, 23–41 (2004).
    Article  Google Scholar 

    38.
    Ufnar, D. F., Gröcke, D. R. & Beddows, P. A. Assessing pedogenic calcite stable-isotope values: Can positive linear covariant trends be used to quantify palaeo-evaporation rates?. Chem. Geol. 256, 46–51 (2008).
    ADS  CAS  Article  Google Scholar 

    39.
    Jahren, A. H. & Sternberg, L. S. L. Annual patterns within tree rings of the Arctic middle Eocene (ca. 45 Ma): isotopic signatures of precipitation, relative humidity, and deciduousness. Geology 36, 99–102 (2008).
    ADS  CAS  Article  Google Scholar 

    40.
    Retallack, G. J., Wynn, J. G. & Fremd, T. J. Glacial-interglacial-scale paleoclimatic change without large ice sheets in the Oligocene of central Oregon. Geology 32, 297–300 (2004).
    ADS  Article  Google Scholar 

    41.
    Howell, T. A. & Dusek, D. Comparison of vapor-pressure-deficit calculation methods: Southern high plains. J. Irrig. Drain. Eng. 121, 191–198 (1995).
    Article  Google Scholar 

    42.
    Castellvi, F., Perez, P. J., Villar, J. M. & Rose, J. I. Analysis of methods for estimating vapor pressure deficits and relative humidity. Agric. For. Meteorol. 82, 29–45 (1996).
    ADS  Article  Google Scholar 

    43.
    Jahren, A. H. & Sternberg, L. S. L. Humidity estimate for the middle Eocene Arctic rain forest. Geology 31, 463–466 (2003).
    ADS  Article  Google Scholar 

    44.
    Schubert, B. A. & Jahren, A. H. The effect of atmospheric CO2 concentration on carbon isotope fractionation in C3 land plants. Geochim. Cosmochim. Acta 96, 29–43 (2012).
    ADS  CAS  Article  Google Scholar 

    45.
    Sheldon, N. D., Retallack, G. J. & Tanaka, S. Geochemical climofunctions from North American soils and application to paleosols across the eocene: oligocene boundary in oregon geochemical climofunctions from North American soils and application to paleosols across the eocene-oligocene boundary in Or. J. Geol. 110, 687–696 (2015).
    ADS  Article  Google Scholar 

    46.
    Retallack, G. J., Bestland, E. & Fremd, T. Eocene and oligocene paleosols of central oregon. Geol. Soc. Am. Spec. Pap. 344, 1–192 (2000).
    Google Scholar 

    47.
    White, P. D. & Schiebout, J. A. Paleogene paleosols of Big Bend National Park, Texas. Spec. Pap. Geol. Soc. Am. 369, 537–550 (2003).
    Google Scholar 

    48.
    Fischer-Femal, B. J. & Bowen, G. J. Coupled carbon and oxygen isotope model for pedogenic carbonates. Geochim. Cosmochim. Acta https://doi.org/10.1016/j.gca.2020.10.022 (2020).
    Article  Google Scholar 

    49.
    Cerling, T. E. & Quade, J. Stable carbon and oxygen isotopes in soil carbonates. Clim. Chang. Cont. Isot. Rec. 78, 78 (1993).
    Google Scholar 

    50.
    Sarangi, V., Agrawal, S. & Sanyal, P. The disparity in the abundance of C4 plants estimated using the carbon isotopic composition of paleosol components. Palaeogeogr. Palaeoclimatol. Palaeoecol. 561, 110068 (2021).
    Article  Google Scholar 

    51.
    Huang, C. M., Wang, C. S. & Tang, Y. Stable carbon and oxygen isotopes of pedogenic carbonates in Ustic Vertisols: Implications for paleoenvironmental change. Pedosphere 15, 539–544 (2005).
    CAS  Google Scholar 

    52.
    Werner, C. et al. Progress and challenges in using stable isotopes to trace plant carbon and water relations across scales. Biogeosciences 9, 3083–3111 (2012).
    ADS  CAS  Article  Google Scholar 

    53.
    Wynn, J. G. & Bird, M. I. C4-derived soil organic carbon decomposes faster than its C3 counterpart in mixed C3/C4 soils. Glob. Chang. Biol. 13, 2206–2217 (2007).
    ADS  Article  Google Scholar 

    54.
    Garzione, C. N., Dettman, D. L. & Horton, B. K. Carbonate oxygen isotope paleoaltimetry: evaluating the effect of diagenesis on paleoelevation estimates for the Tibetan plateau. Palaeogeogr. Palaeoclimatol. Palaeoecol. 212, 119–140 (2004).
    Article  Google Scholar 

    55.
    Rice, C. M. et al. A Devonian auriferous hot spring system, Rhynie, Scotland. J. Geol. Soc. Lond. 152, 229–250 (1995).
    CAS  Article  Google Scholar 

    56.
    Bera, M. K., Sarkar, A., Tandon, S. K., Samanta, A. & Sanyal, P. Does burial diagenesis reset pristine isotopic compositions in paleosol carbonates?. Earth Planet. Sci. Lett. 300, 85–100 (2010).
    ADS  CAS  Article  Google Scholar 

    57.
    Cernusak, L. A. et al. Environmental and physiological determinants of carbon isotope discrimination in terrestrial plants. New Phytol. 200, 950–965 (2013).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    58.
    Vargas, A. I., Schaffer, B., Yuhong, L. & Lobo, S. Testing plant use of mobile vs immobile soil water sources using stable isotope experiments. New Phytol. https://doi.org/10.1111/nph.14616 (2017).
    Article  PubMed  PubMed Central  Google Scholar 

    59.
    Flanagan, L. B. & Farquhar, G. D. Variation in the carbon and oxygen isotope composition of plant biomass and its relationship to water-use efficiency at the leaf- and ecosystem-scales in a northern Great Plains grassland. Plant Cell Environ. 37, 425–438 (2014).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    60.
    Sheshshayee, M. S. et al. Oxygen isotope enrichment (Δ18O) as a measure of time-averaged transpiration rate. J. Exp. Bot. 56, 3033–3039 (2005).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    61.
    Sternberg, L., Fernandes, P. & Ellsworth, V. Divergent biochemical fractionation, not convergent temperature , explains cellulose oxygen isotope enrichment across latitudes. 6, (2011).

    62.
    Retallack, G. J. Field and laboratory tests for recognition of Ediacaran paleosols. Gondwana Res. 36, 94–110 (2016).
    Article  CAS  Google Scholar 

    63.
    Farquhar, G. D. & Cernusak, L. A. Ternary effects on the gas exchange of isotopologues of carbon dioxide. Plant Cell Environ. 35, 1221–1231 (2012).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    64.
    Maxwell, T. M., Silva, L. C. R. & Horwath, W. R. Integrating effects of species composition and soil properties to predict shifts in montane forest carbon–water relations. Proc. Natl. Acad. Sci. 201718864 (2018). https://doi.org/10.1073/pnas.1718864115

    65.
    Locatelli, E. R. The exceptional preservation of plant fossils: a review of taphonomic pathways and biases in the fossil record. Paleontol. Soc. Pap. 20, 237–258 (2014).
    Article  Google Scholar 

    66.
    Castruita-Esparza, L. U. et al. Coping with extreme events: growth and water-use efficiency of trees in Western Mexico during the driest and wettest periods of the past one hundred sixty years. J. Geophys. Res. Biogeosci. 124, 3419–3431 (2019).
    Article  Google Scholar 

    67.
    Jahren, A. H. The arctic forest of the middle eocene. Annu. Rev. Earth Planet. Sci. 35, 509–540 (2007).
    ADS  CAS  Article  Google Scholar 

    68.
    Falini, F. On the formation of coal deposits of lacustrine origin. Bull. Geol. Soc. Am. 76, 1317–1346 (1965).
    Article  Google Scholar  More

  • in

    Multiple life-stage inbreeding depression impacts demography and extinction risk in an extinct-in-the-wild species

    1.
    Keller, L. F. & Waller, D. M. Inbreeding effects in wild populations. Trends Ecol. Evol. 17, 230–241 (2002).
    Article  Google Scholar 
    2.
    Boakes, E. H., Wang, J. & Amos, W. An investigation of inbreeding depression and purging in captive pedigreed populations. Heredity (Edinb). 98, 172–182 (2007).
    CAS  PubMed  Article  Google Scholar 

    3.
    Bozzuto, C., Biebach, I., Muff, S., Ives, A. R. & Keller, L. F. Inbreeding reduces long-term growth of Alpine ibex populations. Nat. Ecol. Evol. 3, 1359–1364 (2019).
    PubMed  Article  Google Scholar 

    4.
    Saccheri, I., Kuussaari, M., Kankare, M., Vikman, P. & Hanski, I. Inbreeding and extinction in a butterfly metapopulation. Nature 392, 491–494 (1998).
    ADS  CAS  Article  Google Scholar 

    5.
    Kardos, M., Taylor, H. R., Ellegren, H., Luikart, G. & Allendorf, F. W. Genomics advances the study of inbreeding depression in the wild. Evol. Appl. 9, 1205–1218 (2016).
    PubMed  PubMed Central  Article  Google Scholar 

    6.
    Allendorf, F. W., Luikart, G. & Aitken, S. N. Conservation and the genetics of populations. (Wiley-Blackwell, 2013).

    7.
    Johnson, H. E., Mills, L. S., Wehausen, J. D., Stephenson, T. R. & Luikart, G. Translating effects of inbreeding depression on component vital rates to overall population growth in endangered bighorn sheep. Conserv. Biol. 25, 1240–1249 (2011).
    PubMed  Article  Google Scholar 

    8.
    Frankham, R. Where are we in conservation genetics and where do we need to go?. Conserv. Genet. 11, 661–663 (2010).
    Article  Google Scholar 

    9.
    Pierson, J. C. et al. Incorporating evolutionary processes into population viability models. Conserv. Biol. 29, 755–764 (2015).
    PubMed  Article  Google Scholar 

    10.
    Huisman, J., Kruuk, L. E. B., Ellisa, P. A., Clutton-Brock, T. & Pemberton, J. M. Inbreeding depression across the lifespan in a wild mammal population. Proc. Natl. Acad. Sci. U. S. A. 113, 3585–3590 (2016).
    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

    11.
    Grueber, C. E., Laws, R. J., Nakagawa, S. & Jamieson, I. G. Inbreeding depression accumulation across life-history stages of the endangered takahe. Conserv. Biol. 24, 1617–1625 (2010).
    PubMed  Article  Google Scholar 

    12.
    Harrisson, K. A. et al. Lifetime fitness costs of inbreeding and being inbred in a critically endangered bird. Curr. Biol. 29, 2711-2717.e4 (2019).
    CAS  PubMed  Article  Google Scholar 

    13.
    Ralls, K., Ballou, J. D. & Templeton, A. Estimates of lethal equivalents and the cost of inbreeding in mammals. Conserv. Biol. 2, 185–192 (1988).
    Article  Google Scholar 

    14.
    Hoeck, P. E. A., Wolak, M. E., Switzer, R. A., Kuehler, C. M. & Lieberman, A. A. Effects of inbreeding and parental incubation on captive breeding success in Hawaiian crows. Biol. Conserv. 184, 357–364 (2015).
    Article  Google Scholar 

    15.
    Jimenez, J. A., Hughes, K. A., Alaks, G., Graham, L. & Lacy, R. C. An experimental study of inbreeding depression in a natural habitat. Science (80-. ). 266, 271–273 (1994).

    16.
    Van Oosterhout, C., Zijlstra, W. G., Van Heuven, M. K. & Brakefield, P. M. Inbreeding depression and genetic load in laboratory metapopulations of the butterfly Bicyclus anynana. Evolution (N. Y). 54, 218–225 (2000).

    17.
    Szulkin, M., Garant, D., Mccleery, R. H. & Sheldon, B. C. Inbreeding depression along a life-history continuum in the great tit. J. Evol. Biol. 20, 1531–1543 (2007).
    CAS  PubMed  Article  Google Scholar 

    18.
    Wolak, M. E., Arcese, P., Keller, L. F., Nietlisbach, P. & Reid, J. M. Sex-specific additive genetic variances and correlations for fitness in a song sparrow (Melospiza melodia) population subject to natural immigration and inbreeding. Evolution (N. Y). 72, 2057–2075 (2018).

    19.
    Kennedy, E. S., Grueber, C. E., Duncan, R. P. & Jamieson, I. G. Severe inbreeding depression and no evidence of purging in an extremely inbred wild species-the chatham island black robin. Evolution (N. Y). 68, 987–995 (2014).

    20.
    Jamieson, I. G., Tracy, L. N., Fletcher, D. & Armstrong, D. P. Moderate inbreeding depression in a reintroduced population of North Island robins. Anim. Conserv. 10, 95–102 (2007).
    Article  Google Scholar 

    21.
    Norén, K., Godoy, E., Dalén, L., Meijer, T. & Angerbjörn, A. Inbreeding depression in a critically endangered carnivore. Mol. Ecol. https://doi.org/10.1111/mec.13674 (2016).
    Article  PubMed  Google Scholar 

    22.
    Sæther, B. E. & Bakke, Ø. Avian life history variation and contribution of demographic traits to the population growth rate. Ecology 81, 642–653 (2000).
    Article  Google Scholar 

    23.
    Beissinger, S. R. & McCullough, D. R. Population viability analysis. (University of Chicago Press, 2002).

    24.
    Lacy, R. C. Lessons from 30 years of population viability analysis of wildlife populations. Zoo Biol. 38, 67–77 (2019).
    PubMed  Article  Google Scholar 

    25.
    Traill, L. W., Bradshaw, C. J. A. & Brook, B. W. Minimum viable population size: A meta-analysis of 30 years of published estimates. Biol. Conserv. 139, 159–166 (2007).
    Article  Google Scholar 

    26.
    O’Grady, J. J. et al. Realistic levels of inbreeding depression strongly affect extinction risk in wild populations. Biol. Conserv. 133, 42–51 (2006).
    Article  Google Scholar 

    27.
    Lacy, R. C., Miller, P. S. & Traylor-Holzer, K. Vortex 10 user’s manual. (2017).

    28.
    Ballou, J. D. & Lacy, R. C. in Population management for survival and recovery (eds. Ballou, J. D., Gilpin, M. & Foose, T. J.) 76–111 (Columbia University Press, 1995).

    29.
    Armbruster, P. & Reed, D. H. Inbreeding depression in benign and stressful environments. Heredity (Edinb). 95, 235–242 (2005).
    CAS  PubMed  Article  Google Scholar 

    30.
    Fox, C. W. & Reed, D. H. Inbreeding depression increases with environmental stress: an experimental study and meta-analysis. Evolution (N. Y). 65, 246–258 (2011).

    31.
    Baker, R. H. The avifauna of Micronesia, its origin, evolution and distribution. (University of Kansas Publications, 1951).

    32.
    Marshall, J. T. The endemic avifauna of Sapan, Tinian Guam and Palau. Condor 51, 200–221 (1949).
    Article  Google Scholar 

    33.
    Wiles, G. J., Bart, J., Beck, R. E. & Aguon, C. F. Impacts of the brown tree snake: patterns of decline and species persistence in Guam’s avifauna. Conserv. Biol. 17, 1350–1360 (2003).
    Article  Google Scholar 

    34.
    Savidge, J. A. Extinction of an island forest avifauna by an introduced snake. Ecology 68, 660–668 (1987).
    Article  Google Scholar 

    35.
    Haig, S. M., Ballou, J. D. & Casna, N. J. Genetic identification of kin in Micronesian kingfishers. J. Hered. 86, 423–431 (1995).
    Article  Google Scholar 

    36.
    Lacy, R. C., Ballou, J. D. & Pollak, J. P. PMx: Software package for demographic and genetic analysis and management of pedigreed populations. Methods Ecol. Evol. 3, 433–437 (2012).
    Article  Google Scholar 

    37.
    Ferrie, G. Using molecular genetic and demographic tools to improve management of ex situ avian populations. (University of Central Florida, 2017). http://stars.library.ucf.edu/etd/5709

    38.
    Zuur, A. F., Ieno, E. N. & Elphick, C. S. A protocol for data exploration to avoid common statistical problems. Methods Ecol. Evol. 1, 3–14 (2010).
    Article  Google Scholar 

    39.
    Burnham, K. . & Anderson, D. R. Model selection and multimodel inference: a practical information-theoretic approach. (Springer, 2002).

    40.
    Whittingham, M. J., Stephens, P. A., Bradbury, R. B. & Freckleton, R. P. Why do we still use stepwise modelling in ecology and behaviour?. J. Anim. Ecol. 75, 1182–1189 (2006).
    PubMed  Article  Google Scholar 

    41.
    Nietlisbach, P., Muff, S., Reid, J. M., Whitlock, M. C. & Keller, L. F. Nonequivalent lethal equivalents: Models and inbreeding metrics for unbiased estimation of inbreeding load. Evol. Appl. 12, 266–279 (2018).
    PubMed  PubMed Central  Article  Google Scholar 

    42.
    Zou, G. A modified poisson regression approach to prospective studies with binary data. Am. J. Epidemiol. 159, 702–706 (2004).
    PubMed  Article  Google Scholar 

    43.
    Bates, D., Mächler, M., Bolker, B. M. & Walker, S. C. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).
    Article  Google Scholar 

    44.
    R Development Core Team. R: A language and environment for statistical computing. (2019).

    45.
    Lacy, R. C. & Pollak, J. P. Vortex: A stochastic simulation of the extinction process. (2017).

    46.
    Hemmings, N. L., Slate, J. & Birkhead, T. R. Inbreeding causes early death in a passerine bird. Nat. Commun. 3, 1–4 (2012).
    Article  CAS  Google Scholar 

    47.
    Tiira, K., Piironen, J. & Primmer, C. R. Evidence for reduced genetic variation in severely deformed juvenile salmonids. Can. J. Fish. Aquat. Sci. 63, 2700–2707 (2006).
    Article  Google Scholar 

    48.
    Wang, J., Hill, W. G., Charlesworth, D. & Charlesworth, B. Dynamics of inbreeding depression due to deleterious mutations in small populations: mutation parameters and inbreeding rate. Genet. Res. 74, 165–178 (1999).
    CAS  PubMed  Article  Google Scholar 

    49.
    Husband, B. C. & Schemske, D. W. Evolution of the magnitude and timing of inbreeding depression in plants. Evolution (N. Y). 50, 54–70 (1996).

    50.
    de Boer, R. A., Eens, M. & Müller, W. Sex-specific effects of inbreeding on reproductive senescence. Proc. R. Soc. B Biol. Sci. 285, (2018).

    51.
    Keller, L. F., Reid, J. M. & Arcese, P. Testing evolutionary models of senescence in a natural population: Age and inbreeding effects on fitness components in song sparrows. Proc. R. Soc. B Biol. Sci. 275, 597–604 (2008).
    CAS  Article  Google Scholar 

    52.
    Partridge, L. & Mangel, M. Messages from mortality: The evolution of death rates in the old. Trends Ecol. Evol. 14, 438–442 (1999).
    CAS  PubMed  Article  Google Scholar 

    53.
    Charlesworth, B. & Hughes, K. A. Age-specific inbreeding depression and components of genetic variance in relation to the evolution of senescence. Proc. Natl. Acad. Sci. U. S. A. 93, 6140–6145 (1996).
    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

    54.
    Kristensen, T. N., Loeschcke, V. & Hoffmann, A. A. Linking inbreeding effects in captive populations with fitness in the wild: Release of replicated Drosophila melanogaster lines under different temperatures. Conserv. Biol. 22, 189–199 (2008).
    PubMed  Article  Google Scholar 

    55.
    Ryman, N. & Laikre, L. Effects of supportive breeding on the genetically effective population size. Conserv. Biol. 5, 325–329 (1991).
    Article  Google Scholar 

    56.
    Hedrick, P. W. & Garcia-Dorado, A. Understanding inbreeding depression, purging, and genetic rescue. Trends Ecol. Evol. 31, 940–952 (2016).
    PubMed  Article  Google Scholar 

    57.
    Kalinowski, S. T., Hedrick, P. W. & Miller, P. S. Inbreeding Depression in the Speke’s Gazelle Captive Breeding Program. Conserv. Biol. 14, 1375–1384 (2000).
    Article  Google Scholar 

    58.
    Gilligan, D. M. & Frankham, R. Dynamics of individual adaptation processes. Conserv. Genet. 4, 189–197 (2003).
    Article  Google Scholar 

    59.
    Christie, M. R., Marine, M. L., French, R. A. & Blouin, M. S. Genetic adaptation to captivity can occur in a single generation. Proc. Natl. Acad. Sci. U. S. A. 109, 238–242 (2012).
    ADS  CAS  PubMed  Article  Google Scholar 

    60.
    Grueber, C. E., Waters, J. M. & Jamieson, I. G. The imprecision of heterozygosity-fitness correlations hinders the detection of inbreeding and inbreeding depression in a threatened species. Mol. Ecol. 20, 67–79 (2011).
    PubMed  Article  Google Scholar 

    61.
    Milligan, M. C., Wells, S. L. & McNew, L. B. A population viability analysis for sharp-tailed grouse to inform reintroductions. J. Fish Wildl. Manag. 9, 565–581 (2018).
    Article  Google Scholar 

    62.
    Research needs & implications for population management. Moßbrucker, A. M., Imron, M. A., Pudtatmoko, S., Pratje, P. & Sumardi. Modelling the fate of Sumatran elephants in Bukit Tigapuluh, Indonesia. J. For. Sci. 10, 5–18 (2016).
    Google Scholar 

    63.
    Sharpe, M. & Berggren, P. Indian Ocean humpback dolphin in the Menai Bay off the south coast of Zanzibar, East Africa is Critically Endangered. Aquat. Conserv. Mar. Freshw. Ecosyst. 29, 2133–2146 (2019).
    Article  Google Scholar 

    64.
    McQuillan, R. et al. Runs of homozygosity in European populations. Am. J. Hum. Genet. 83, 359–372 (2008).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    65.
    Caballero, A., Bravo, I. & Wang, J. Inbreeding load and purging: Implications for the short-term survival and the conservation management of small populations. Heredity (Edinb). 118, 177–185 (2017).
    CAS  PubMed  Article  Google Scholar 

    66.
    Liao, W. & Reed, D. H. Inbreeding-environment interactions increase extinction risk. Anim. Conserv. 12, 54–61 (2009).
    CAS  Article  Google Scholar 

    67.
    Melbourne, B. A. & Hastings, A. Extinction risk depends strongly on factors contributing to stochasticity. Nature 454, 100–103 (2008).
    ADS  CAS  PubMed  Article  Google Scholar  More

  • in

    Carbon storage and sequestration potential in aboveground biomass of bamboos in North East India

    1.
    International Network for Bamboo and Rattan. Annual Report. www.Inbar.int. (2005).
    2.
    Sharma, M. L. & Nirmala, C. Bamboo diversity of India: An Update. Conference Paper. 10th World Bamboo Congress, Korea (2015).

    3.
    Environment and Forest Department, Government of Mizoram. Bamboos of Mizoram (2010).

    4.
    Jha, L. K. Bamboo based agroforestry systems to reclaim degraded hilly tracts (jhum) land in North Eastern India: Study on uses, species diversity, distribution, and growth performance of Melocanna baccifera, Dendrocalamus hamiltonii, D. longispathus and Bambusa tulda in natural stands and in stands managed on a sustainable basis. Bamboo Science and Culture. J. Am. Bamboo Soc. 23(1), 1–28 (2010).
    Google Scholar 

    5.
    Nigatu, A., Wondei, M., Alemu, A., Gebeyehu, D. & Workagegnehu, H. Productivity of highland bamboo (Yushania alpina) across different plantation niches in West Amhara, Ethiopia. Forest Sci. Tech. 16, 116–122 (2020).
    Article  Google Scholar 

    6.
    Quiroga, R. A. R., Li, T., Lora, G. & Anderson L. E. A measurement of the carbon sequestration potential of Guadua angustifolia in the Carrasco National Park Bolivia. Development Research Working Paper Series 04/2013. Institute for Advanced Development Studies. Bolivia (2013).

    7.
    Nath, A. J., Lal, R. & Das, A. K. Managing woody bamboos for carbon farming and carbon trading. Glob. Ecol. Conserv. 3, 654–663 (2015).
    Article  Google Scholar 

    8.
    Wu, W., Liu, Q., Zhu, Z. & Shen, Y. Managing bamboo for carbon sequestration, bamboo stem and bamboo shoots. Small Scale Forest. 14, 233–243 (2015).
    Article  Google Scholar 

    9.
    Yen, T. M., Ji, Y. J. & Lee, J. S. Estimating biomass production and carbon storage for a fast-growing makino bamboo (Phyllosatchys makinoi) plant based on the diameter distribution model. For. Ecol. Manag. 260, 339–344 (2010).
    Article  Google Scholar 

    10.
    Singnar, P., Das, M. C., Sileshi, G. W., Brahma, B. & Nath, A. J. Allometric scalling, biomass accumulation and carbon stocks in different aged stands of thin-walled bamboos Schiostachyum dullooa, Pseudostachyum polymorphum and Melocanna baccifera. For. Ecol. Manag. 395, 81–91 (2017).
    Article  Google Scholar 

    11.
    Directorate of Science and Technology. Climate profile of Mizoram. A publication by Mizoram State Climate Change Cell, 23 (2018).

    12.
    Soil Survey Staff. Soil taxonomy A basic system of soil classification for making and interpreting soil surveys. U. S. Department of Agriculture Handbook p 436 (1999).

    13.
    Houba, V., VanderLee, J., Novozamsky, I. & Wallinga, I. Soil and plant analysis. A series of Syllabi Part 5. Soil Analysis Procedures Fourth Edition Wageningen, Netherlands (1989).

    14.
    Banik, R. L. Silviculture and Field-Guide to Priority Bamboos of Bangladesh and South Asia. Government of the people’s Republic of Bangladesh. Forest Research Institute, Chittagong, 187. (2000).

    15.
    FAO. Guidelines on Destructive Measurement for Forest Biomass Estimation (FAO, Rome, 2012).
    Google Scholar 

    16.
    IPCC Good Practice Guidance for LULUCF Sector. Intergovernmental Panel on Climate Change (Cambridge University Press, Cambridge, 2003).
    Google Scholar 

    17.
    Yuming, Y., Chaomao, H., Jiarong, X. & Fan, D. Techniques of cultivation and integrated development of sympodial bamboo species. In Sustainable Development of Bamboo and Rattan Sectors in Tropical China 48–66 (China Forestry Publishing House, Beijing, 2001).
    Google Scholar 

    18.
    Embaye, K., Weih, M., Ledin, S. & Christersson, L. Biomass and nutrient distribution in a highland bamboo forest in southwest Ethiopia: Implications for management. For. Ecol. Manag. 204, 159–169 (2005).
    Article  Google Scholar 

    19.
    Nath, A. J. & Das, A. K. Carbon pool and sequestration potential of village bamboos in the agroforestry system of northeastern India. Trop. Ecol. 53, 287–293 (2012).
    CAS  Google Scholar 

    20.
    Amoah, M., Assan, F. & Dadzie, K. P. Aboveground biomass, carbon storage and fuel values of Bambusa vulgaris, Oxynanteria abbyssinica and Bambusa vulgaris Var. vitata plantations in the Bobiri forest reserve of Ghana. J. Sustain. For. 38, 1–24 (2019).
    Article  Google Scholar 

    21.
    Xu, M., Ji, H. & Zhuang, S. Carbon stock of Moso bamboo (Phyllostachys pubescens) forests along a latitude gradient in the subtropical region of China. PLoS One 13, 2,e0193024 (2018).
    Google Scholar 

    22.
    Majumdar, K., Choudhary, B. K. & Datta, B. K. Aboveground woody biomass carbon stocks potential in selected tropical forest patches of Tripura, Northeast India. Open J. Ecol. 6, 598–612 (2016).
    Article  Google Scholar 

    23.
    Pathak, P. K., Kumar, H., Kumari, G. & Bilyaminu, H. Biomass production potential in different species of hemicelluloses from bamboo in central Utter Pradesh. Ecoscan 10, 41–43 (2016).
    Google Scholar 

    24.
    Sohel, M. S. I., Alamgir, M., Akhter, S. & Rahman, M. Carbon storage in a bamboo (Bambusa vulgaris) plantation in the degraded tropical forest: Implications for policy development. Land Use Policy 49, 142–151 (2015).
    Article  Google Scholar 

    25.
    Thokchom, A. & Yadava, P. S. Comparing aboveground  carbon sequestration between bamboo forest and Dipterocarpus forests of Manipur, Northeast India. Int. J. Ecol. Environ. Sci. 41, 33–42 (2015).
    Google Scholar 

    26.
    Xu, L. et al. Structural development and carbon dynamics of Moso bamboo forests in Zhejiang Province, China. For. Ecol. Manag. 409, 479–488 (2017).
    Article  Google Scholar 

    27.
    Nath, A. J., Das, G. & Das, A. K. Aboveground standing biomass and carbon storage in village bamboos in North East India. Biom. Bioeng. 33, 1188–1196 (2009).
    Article  Google Scholar 

    28.
    Wang, Y. C. Estimates of biomass and carbon sequestration in Dendrocalamus latiflorus culms. J. For. Prod. Ind. 23(1), 13–22 (2004).
    Google Scholar 

    29.
    Wang, J. et al. The structures, aboveground biomass, carbon storage of Phyllostachys pubescens stands in Huisun Experimental Forest Station and Shi-Zhuo. Q. For. Res. 31, 17–26 (2009).
    CAS  Google Scholar 

    30.
    Sujarwo, W. Stand biomass and carbon storage of bamboo forest in Penglipuram traditional village, Bali (Indonesia). J. For. Res. 27, 913–917 (2016).
    CAS  Article  Google Scholar 

    31.
    Nfornkah, B. N. et al. Culm allometry and carbon storage capacity of Bambusa vulgaris Schrad. ex J. C. WendL. in the tropical evergreen rain forest of Cameroon. J Sustain For. https://doi.org/10.1080/10549811.2020.1795688 (2020).
    Article  Google Scholar  More