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    Asynchronous recovery of predators and prey conditions resilience to drought in a neotropical ecosystem

    Dai, A. Drought under global warming: A review. Vo Lu Me 21, 2 (2011).
    Google Scholar 
    Sirdaş, S. & Sen, Z. Spatio-temporal drought analysis in the Trakya region Turkey. Hydrol. Sci. J. 48, 809–820 (2003).Article 

    Google Scholar 
    Marengo, J. A. et al. The drought of Amazonia in 2005. J. Clim. 21, 495–516 (2008).ADS 
    Article 

    Google Scholar 
    Zhang, L., Jiao, W., Zhang, H., Huang, C. & Tong, Q. Studying drought phenomena in the Continental United States in 2011 and 2012 using various drought indices. Remote Sens. Environ. 190, 96–106 (2017).ADS 
    Article 

    Google Scholar 
    Humphries, P. & Baldwin, D. S. Drought and aquatic ecosystems: An introduction: Drought and aquatic ecosystems. Freshw. Biol. 48, 1141–1146 (2003).Article 

    Google Scholar 
    Lake, P. S. Ecological effects of perturbation by drought in flowing waters: Effects of drought in streams. Freshw. Biol. 48, 1161–1172 (2003).Article 

    Google Scholar 
    Wang, W., Peng, C., Kneeshaw, D. D., Larocque, G. R. & Luo, Z. Drought-induced tree mortality: Ecological consequences, causes, and modeling. Environ. Rev. 20, 109–121 (2012).Article 

    Google Scholar 
    Rolls, R. J., Leigh, C. & Sheldon, F. Mechanistic effects of low-flow hydrology on riverine ecosystems: Ecological principles and consequences of alteration. Freshw. Sci. 31, 1163–1186 (2012).Article 

    Google Scholar 
    Trzcinski, M. K., Srivastava, D. S., Corbara, B. & De, O. The effects of food web structure on ecosystem function exceeds those of precipitation. J. Anim. Ecol. 14, 2 (2016).
    Google Scholar 
    Díaz-Paniagua, C. & Aragonés, D. Permanent and temporary ponds in Doñana National Park (SW Spain) are threatened by desiccation. Limnetica 34, 407–424 (2015).
    Google Scholar 
    Downing, J. A. et al. The global abundance and size distribution of lakes, ponds, and impoundments. Limnol. Oceanogr. 51, 2388–2397 (2006).ADS 
    Article 

    Google Scholar 
    Bartout, P. & Touchart, L. A New Approach to Inventorying Bodies of Water, from Local to Global Scale (Gesellschaft für Erdkunde zu, 2015).
    Google Scholar 
    Williams, P. et al. Comparative biodiversity of rivers, streams, ditches and ponds in an agricultural landscape in Southern England. Biol. Conserv. 115, 329–341 (2004).Article 

    Google Scholar 
    Biggs, J., von Fumetti, S. & Kelly-Quinn, M. The importance of small waterbodies for biodiversity and ecosystem services: Implications for policy makers. Hydrobiologia 793, 3–39 (2017).Article 

    Google Scholar 
    Bonhomme, C. et al. In situ resistance, not immigration, supports invertebrate community resilience to drought intensification in a Neotropical ecosystem. J. Anim. Ecol. https://doi.org/10.1111/1365-2656.13392 (2020).Article 
    PubMed 

    Google Scholar 
    Dewson, Z. S., James, A. B. W. & Death, R. G. Invertebrate responses to short-term water abstraction in small New Zealand streams. Freshw. Biol. 52, 357–369 (2007).CAS 
    Article 

    Google Scholar 
    Dézerald, O., Céréghino, R., Corbara, B., Dejean, A. & Leroy, C. Functional trait responses of aquatic macroinvertebrates to simulated drought in a Neotropical bromeliad ecosystem. Freshw. Biol. 60, 1917–1929 (2015).Article 

    Google Scholar 
    Wang, Y., Yu, S. & Wang, J. Biomass-dependent susceptibility to drought in experimental grassland communities. Ecol. Lett. 10, 401–410 (2007).PubMed 
    Article 

    Google Scholar 
    Pallarés, S., Velasco, J., Millán, A., Bilton, D. T. & Arribas, P. Aquatic insects dealing with dehydration: Do desiccation resistance traits differ in species with contrasting habitat preferences?. PeerJ 4, e2382 (2016).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Céréghino, R. et al. Desiccation resistance traits predict freshwater invertebrate survival and community response to drought scenarios in a Neotropical ecosystem. Ecol. Indic. 119, 106839 (2020).Article 

    Google Scholar 
    Atkinson, C. L., Julian, J. P. & Vaughn, C. C. Species and function lost: Role of drought in structuring stream communities. Biol. Conserv. 176, 30–38 (2014).Article 

    Google Scholar 
    Bogan, M. T., Boersma, K. S. & Lytle, D. A. Resistance and resilience of invertebrate communities to seasonal and supraseasonal drought in arid-land headwater streams. Freshw. Biol. 60, 2547–2558 (2015).Article 

    Google Scholar 
    Srivastava, D. S. et al. Ecological response to altered rainfall differs across the Neotropics. Ecology 101, 15 (2020).Article 

    Google Scholar 
    Amundrud, S. L. & Srivastava, D. S. Trophic interactions determine the effects of drought on an aquatic ecosystem. Ecology 97, 1475–1483 (2016).PubMed 
    Article 

    Google Scholar 
    Luo, Y., Keenan, T. F. & Smith, M. Predictability of the terrestrial carbon cycle. Glob. Change Biol. 21, 1737–1751 (2014).ADS 
    Article 

    Google Scholar 
    Givnish, T. J. et al. Adaptive radiation, correlated and contingent evolution, and net species diversification in Bromeliaceae. Mol. Phylogenet. Evol. 71, 55–78 (2014).PubMed 
    Article 

    Google Scholar 
    Brouard, O. et al. Understorey environments influence functional diversity in tank-bromeliad ecosystems: Functional diversity in bromeliad ecosystems. Freshw. Biol. 57, 815–823 (2012).Article 

    Google Scholar 
    Petermann, J. S. et al. Dominant predators mediate the impact of habitat size on trophic structure in bromeliad invertebrate communities. Ecology 96, 428–439 (2015).PubMed 
    Article 

    Google Scholar 
    Romero, G. Q., Piccoli, G. C. O., de Omena, P. M. & Gonçalves-Souza, T. Food web structure shaped by habitat size and climate across a latitudinal gradient. Ecology 97, 2705–2715 (2016).PubMed 
    Article 

    Google Scholar 
    Srivastava, D. S. & Bell, T. Reducing horizontal and vertical diversity in a foodweb triggers extinctions and impacts functions. Ecol. Lett. 12, 1016–1028 (2009).PubMed 
    Article 

    Google Scholar 
    Carrias, J.-F. et al. Resource availability drives bacterial succession during leaf-litter decomposition in a bromeliad ecosystem. FEMS Microbiol. Ecol. 96, 45 (2020).Article 
    CAS 

    Google Scholar 
    Romero, G. Q. et al. Extreme rainfall events alter the trophic structure in bromeliad tanks across the Neotropics. Nat. Commun. 11, 3215 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Hairston, N. G. & Hairston, N. G. Cause-effect relationships in energy flow, trophic structure, and interspecific interactions. Am. Nat. 142, 379–411 (1993).Article 

    Google Scholar 
    Dézerald, O. et al. Environmental drivers of invertebrate population dynamics in neotropical tank bromeliads. Freshw. Biol. 62, 229–242 (2017).Article 

    Google Scholar 
    Dézerald, O. et al. Tank bromeliads sustain high secondary production in neotropical forests. Aquat. Sci. 80, 14 (2018).Article 

    Google Scholar 
    Holt, R. D. & Hoopes, M. F. Food web dynamics in a metacommunity context: modules and beyond. In Metacommunities: Spatial Dynamics and Ecological Communities 68–83 (University of Chicago Press, 2005).
    Google Scholar 
    Srivastava, D. S., Trzcinski, M. K., Richardson, B. A. & Gilbert, B. Why are predators more sensitive to habitat size than their prey? Insights from bromeliad insect food webs. Am. Nat. 172, 761–771 (2008).CAS 
    PubMed 
    Article 

    Google Scholar 
    Amundrud, S. L. et al. Drought alters the trophic role of an opportunistic generalist in an aquatic ecosystem. Oecologia 189, 733–744 (2019).ADS 
    PubMed 
    Article 

    Google Scholar 
    Adler, P. B. & Drake, J. M. Environmental variation, stochastic extinction, and competitive coexistence. Am. Nat. 172, E186–E195 (2008).Article 

    Google Scholar 
    Anisiu, M.-C. Lotka Volterra and their model. Didact. Math. 32, 9–17 (2014).
    Google Scholar 
    Harris, R. M. B. et al. Biological responses to the press and pulse of climate trends and extreme events. Nat. Clim. Change 8, 579–587 (2018).ADS 
    Article 

    Google Scholar 
    Bengtsson, J. Disturbance and resilience in soil animal communities. Eur. J. Soil Biol. 38, 119–125 (2002).Article 

    Google Scholar 
    Parkyn, S. M. & Collier, K. J. Interaction of press and pulse disturbance on crayfish populations: Flood impacts in pasture and forest streams. Hydrobiologia 527, 113–124 (2004).Article 

    Google Scholar 
    Rowe, L. & Richardson, J. S. Community responses to experimental food depletion: Resource tracking by stream invertebrates. Oecologia 129, 473–480 (2001).ADS 
    PubMed 
    Article 

    Google Scholar 
    McPeek, M. A. The growth/predation risk trade-off: So what is the mechanism?. Am. Nat. 163, E88–E111 (2004).PubMed 
    Article 

    Google Scholar 
    Benbow, M. E. et al. Necrobiome framework for bridging decomposition ecology of autotrophically and heterotrophically derived organic matter. Ecol. Monogr. 89, 2 (2019).Article 

    Google Scholar 
    Powers, J. S. et al. Decomposition in tropical forests: A pan-tropical study of the effects of litter type, litter placement and mesofaunal exclusion across a precipitation gradient. J. Ecol. 97, 801–811 (2009).CAS 
    Article 

    Google Scholar 
    Pires, A. P. F. et al. Interactive effects of climate change and biodiversity loss on ecosystem functioning. Ecology 99, 1203–1213 (2018).PubMed 
    Article 

    Google Scholar 
    Rodríguez Pérez, H. et al. Simulated drought regimes reveal community resilience and hydrological thresholds for altered decomposition. Oecologia 187, 267–279 (2018).ADS 
    PubMed 
    Article 

    Google Scholar 
    Brennan, K. E. C., Christie, F. J. & York, A. Global climate change and litter decomposition: More frequent fire slows decomposition and increases the functional importance of invertebrates. Glob. Change Biol. 15, 2958–2971 (2009).ADS 
    Article 

    Google Scholar 
    Marino, N. A. C. et al. Rainfall and hydrological stability alter the impact of top predators on food web structure and function. Glob. Change Biol. 23, 673–685 (2017).ADS 
    Article 

    Google Scholar 
    Hättenschwiler, S., Coq, S., Barantal, S. & Handa, I. T. Leaf traits and decomposition in tropical rainforests: Revisiting some commonly held views and towards a new hypothesis. New Phytol. 189, 950–965 (2011).PubMed 
    Article 

    Google Scholar 
    Céréghino, R. et al. Constraints on the functional trait space of aquatic invertebrates in bromeliads. Funct. Ecol. 32, 2435–2447 (2018).Article 

    Google Scholar 
    Lefcheck, J. S. piecewiseSEM: Piecewise structural equation modelling in r for ecology, evolution, and systematics. Methods Ecol. Evol. 7, 573–579 (2016).Article 

    Google Scholar  More

  • in

    Climate mediates color morph turnover in a species exhibiting alternative reproductive strategies

    Gray, S. M. & McKinnon, J. S. Linking color polymorphism maintenance and speciation. Trends Ecol. Evol. 22, 71–79 (2007).PubMed 

    Google Scholar 
    Forsman, A., Ahnesjö, J., Caesar, S. & Karlsson, M. A model of ecological and evolutionary consequences of color polymorphism. Ecology 89, 34–40 (2008).PubMed 

    Google Scholar 
    O’Neill, K. M. & Evans, H. E. Alternative male mating tactics in Bembecinus quinquespinosus (Hymenoptera: Sphecidae): correlations with size and color variation. Behav. Ecol. Sociobiol. 14, 39–46 (1983).
    Google Scholar 
    Roulin, A. The evolution, maintenance and adaptive function of genetic colour polymorphism in birds. Biol. Rev. 79, 815–848 (2004).PubMed 

    Google Scholar 
    Dijkstra, P. D., Hemelrijk, C., Seehausen, O. & Groothuis, T. G. Color polymorphism and intrasexual competition in assemblages of cichlid fish. Behav. Ecol. 20, 138–144 (2009).
    Google Scholar 
    Brown, D. M. & Lattanzio, M. S. Resource variability and the collapse of a dominance hierarchy in a colour polymorphic species. Behaviour 155, 443–463 (2018).
    Google Scholar 
    Sacchi, R. et al. Morph-specific assortative mating in common wall lizard females. Curr. Zool. 64, 449–453 (2018).PubMed 

    Google Scholar 
    Alonzo, S. H. & Sinervo, B. Mate choice games, context-dependent good genes, and genetic cycles in the side-blotched lizard, Uta stansburiana. Behav. Ecol. Sociobiol. 49, 176–186 (2001).
    Google Scholar 
    Lancaster, L. T., Hipsley, C. A. & Sinervo, B. Female choice for optimal combinations of multiple male display traits increases offspring survival. Behav. Ecol. 20, 993–999 (2009).
    Google Scholar 
    Colborne, S. F., Garner, S. R., Longstaffe, F. J. & Neff, B. D. Assortative mating but no evidence of genetic divergence in a species characterized by a trophic polymorphism. J. Evol. Biol. 29, 633–644 (2016).CAS 
    PubMed 

    Google Scholar 
    Huyghe, K. et al. Relationships between hormones, physiological performance and immunocompetence in a color-polymorphic lizard species, Podarcis melisellensis. Horm. Behav. 55, 488–494 (2009).CAS 
    PubMed 

    Google Scholar 
    Sinervo, B., Miles, D. B., Frankino, W. A., Klukowski, M. & DeNardo, D. F. Testosterone, endurance, and Darwinian fitness: natural and sexual selection on the physiological bases of alternative male behaviors in side-blotched lizards. Horm. Behav. 38, 222–233 (2000).CAS 
    PubMed 

    Google Scholar 
    Mills, S. C. et al. Gonadotropin hormone modulation of testosterone, immune function, performance, and behavioral trade-offs among male morphs of the lizard Uta stansburiana. Am. Nat. 171, 339–357 (2008).PubMed 

    Google Scholar 
    Kusche, H., Elmer, K. R. & Meyer, A. Sympatric ecological divergence associated with a color polymorphism. BMC Biol. 13, 1–11 (2015).
    Google Scholar 
    Lattanzio, M. S. & Miles, D. B. Trophic niche divergence among colour morphs that exhibit alternative mating tactics. R. Soc. Open Sci. 3, 150531 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Scali, S. et al. Does a polymorphic species have a ‘polymorphic’diet? A case study from a lacertid lizard. Biol. J. Linn. Soc. 117, 492–502 (2016).
    Google Scholar 
    Pérez i de Lanuza, G. & Carretero, M. Á. Partial divergence in microhabitat use suggests environmental-dependent selection on a colour polymorphic lizard. Behav. Ecol. Sociobiol. 72, 1–7 (2018).
    Google Scholar 
    Pryke, S. R., Astheimer, L. B., Griffith, S. C. & Buttemer, W. A. Covariation in life-history traits: differential effects of diet on condition, hormones, behavior, and reproduction in genetic finch morphs. Am. Nat. 179, 375–390 (2012).PubMed 

    Google Scholar 
    Jaworski, K. E. & Lattanzio, M. S. Physiological consequences of food limitation for a color polymorphic lizard: are coping responses morph-specific?. Copeia 2017, 689–695 (2017).
    Google Scholar 
    Lattanzio, M. S. & Miles, D. B. Ecological divergence among colour morphs mediated by changes in spatial network structure associated with disturbance. J. Anim. Ecol. 83, 1490–1500 (2014).PubMed 

    Google Scholar 
    Paterson, J. E. & Blouin-Demers, G. Male throat colour polymorphism is related to differences in space use and in habitat selection in tree lizards. J. Zool. 306, 101–109 (2018).
    Google Scholar 
    McLean, C. A., Stuart-Fox, D. & Moussalli, A. Environment, but not genetic divergence, influences geographic variation in colour morph frequencies in a lizard. BMC Evol. Biol. 15, 1–10 (2015).
    Google Scholar 
    Friedman, D., Magnani, J., Paranjpe, D. & Sinervo, B. Evolutionary games, climate and the generation of diversity. PLoS ONE 12, e0184052 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Pérez i de Lanuza, G., Sillero, N. & Carretero, M. Á. Climate suggests environment-dependent selection on lizard colour morphs. J. Biogeogr. 45, 2791–2802 (2018).
    Google Scholar 
    Miñano, M. R. et al. Climate shapes the geographic distribution and introgressive spread of color ornamentation in common wall lizards. Am. Nat. 198, 379–393 (2021).PubMed 

    Google Scholar 
    Sinervo, B. & Lively, C. M. The rock–paper–scissors game and the evolution of alternative male strategies. Nature 380, 240–243 (1996).CAS 

    Google Scholar 
    Amar, A., Koeslag, A., Malan, G., Brown, M. & Wrefordm, E. Clinal variation in the morph ratio of Black Sparrowhawks Accipiter melanoleucus in South Africa and its correlation with environmental variables. Ibis 156, 627–638 (2014).
    Google Scholar 
    Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).
    Google Scholar 
    Li, W. et al. Identifying climate refugia and its potential impact on small population of Asian elephant (Elephas maximus) in China. Global Ecol. Conserv. 19, e00664 (2019).
    Google Scholar 
    Hillman, S. S. & Gorman, G. C. Water loss, desiccation tolerance, and survival under desiccating conditions in 11 species of Caribbean Anolis. Oecologia 29, 105–116 (1977).CAS 
    PubMed 

    Google Scholar 
    Le Galliard, J. F. et al. A worldwide and annotated database of evaporative water loss rates in squamate reptiles. Global Ecol. Biogeogr. 30, 1938–1950 (2021).
    Google Scholar 
    Winters, A. & Gifford, M. E. Geographic variation in the water economy of a lungless salamander. Herpetol. Conserv. Biol. 8, 741–747 (2013).
    Google Scholar 
    Gilbert, A. L. & Lattanzio, M. S. Ontogenetic variation in the thermal biology of yarrow’s spiny lizard, Sceloporus jarrovii. Plos One 11, e0146904 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Cox, R. M. & John-Alder, H. B. Growing apart together: The development of contrasting sexual size dimorphisms in sympatric Sceloporus lizards. Herpetologica 63, 245–257 (2007).
    Google Scholar 
    Takahashi, Y., Morita, S., Yoshimura, J. & Watanabe, M. A geographic cline induced by negative frequency-dependent selection. BMC Evol. Biol. 11, 1–11 (2011).
    Google Scholar 
    Bogert, C. M. Thermoregulation in reptiles, a factor in evolution. Evolution 3, 195–211 (1949).CAS 
    PubMed 

    Google Scholar 
    Huey, R. B. Physiological consequences of habitat selection. Am. Nat. 137, S91–S115 (1991).
    Google Scholar 
    Kopáček, J. et al. Changes in microclimate and hydrology in an unmanaged mountain forest catchment after insect-induced tree dieback. Sci. Total Environ. 720, 137518 (2020).PubMed 

    Google Scholar 
    Haworth, K. & McPherson, G. R. Effects of Quercus emoryi trees on precipitation distribution and microclimate in a semi-arid savanna. J. Arid Environ. 31, 153–170 (1995).
    Google Scholar 
    Moore, M. C., Hews, D. K. & Knapp, R. Hormonal control and evolution of alternative male phenotypes: generalizations of models for sexual differentiation. Am. Zool. 38, 133–151 (1998).CAS 

    Google Scholar 
    Tinkle, D. W. & Dunham, A. E. Demography of the tree lizard, Urosaurus ornatus, in central Arizona. Copeia 1983, 585–598 (1983).
    Google Scholar 
    Seager, R. et al. Model projections of an imminent transition to a more arid climate in southwestern North America. Science 316, 1181–1184 (2007).CAS 
    PubMed 

    Google Scholar 
    Zucker, N. A dual status-signalling system: a matter of redundancy or differing roles?. Anim. Behav. 47, 15–22 (1994).
    Google Scholar 
    Haenel, G. J. Phylogeography of the tree lizard, Urosaurus ornatus: responses of populations to past climate change. Mol. Ecol. 16, 4321–4334 (2007).CAS 
    PubMed 

    Google Scholar 
    Hammerson, G. A., Frost, D. R. & Santos-Barrera, G. Urosaurus ornatus. The IUCN Red List of Threatened Species 2007, e.T64174A12750887 (2007).Hover, E. L. Differences in aggressive behavior between two throat color morphs in a lizard, Urosaurus ornatus. Copeia 1985, 933–940 (1985).
    Google Scholar 
    Thompson, C. W., Moore, I. T. & Moore, C. W. Social, environmental and genetic factors in the ontogeny of phenotypic differentiation in a lizard with alternative male reproductive strategies. Behav. Ecol. Sociobiol. 33, 137–146 (1993).
    Google Scholar 
    Corl, A., Davis, A. R., Kuchta, S. R. & Sinervo, B. Selective loss of polymorphic mating types is associated with rapid phenotypic evolution during morphic speciation. Proc. Natl. Acad. Sci. 107, 4254–4259 (2010).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hews, D. K., Thompson, C. W., Moore, I. T. & Moore, M. C. Population frequencies of alternative male phenotypes in tree lizards: geographic variation and common-garden rearing studies. Behav. Ecol. Sociobiol. 41, 371–380 (1997).
    Google Scholar 
    Feldman, C. R., Flores-Villela, O. & Papenfuss, T. J. Phylogeny, biogeography, and display evolution in the tree and brush lizard genus Urosaurus (Squamata: Phrynosomatidae). Mol. Phylogenet. Evol. 61, 714–725 (2011).PubMed 

    Google Scholar 
    Haisten, D. C., Paranjpe, D., Loveridge, S. & Sinervo, B. The cellular basis of polymorphic coloration in common side-blotched lizards, Uta stansburiana. Herpetologica 71, 125–135 (2015).
    Google Scholar 
    Morrison, R. L., Rand, M. S. & Frost-Mason, S. K. Cellular basis of color differences in three morphs of the lizard Sceloporus undulatus erythrocheilus. Copeia 1995, 397–408 (1995).
    Google Scholar 
    Reclamation. Downscaled CMIP3 and CMIP5 Climate and Hydrology Projections: Release of Downscaled CMIP5 Climate Projections, Comparison with preceding Information, and Summary of User Needs. Prepared by the U.S. Department of the Interior, Bureau of Reclamation, Technical Services Center, Denver, Colorado (2013).Keefer, T. O., Moran, M. S. & Paige, G. B. Long-term meteorological and soil hydrology database, Walnut Gulch Experimental Watershed, Arizona, United States. Water Resour. Res. 44, W05S07 (2008).
    Google Scholar 
    Rankin, K. & Stuart-Fox, D. Testosterone-induced expression of male colour morphs in females of the polymorphic tawny dragon lizard, Ctenophorus decresii. Plos One 10, e0140458 (2015).PubMed 
    PubMed Central 

    Google Scholar 
    Meyers, J. J., Irschick, D. J., Vanhooydonck, B. & Herrel, A. Divergent roles for multiple sexual signals in a polygynous lizard. Funct. Ecol. 20, 709–716 (2006).
    Google Scholar 
    Wood, S. N. Generalized Additive Models: An Introduction with R 2nd edn. (Chapman and Hall, 2017).MATH 

    Google Scholar 
    Zeileis, A. & Hothorn, T. Diagnostic checking in regression relationships. R News 2, 7–10 (2002).
    Google Scholar 
    Bartón, K. MuMIn: Multi-Model Inference. R package version 1.42.1. https://CRAN.R-project.org/package=MuMIn (2018).Burnham, K. P., Anderson, D. R. & Huyvaert, K. P. AIC model selection and multimodel inference in behavioral ecology: some background, observations, and comparisons. Behav. Ecol. Sociobiol. 65, 23–35 (2011).
    Google Scholar 
    Nagelkerke, N. A note on a general definition of the coefficient of determination. Biometrika 78, 691–692 (1991).MathSciNet 
    MATH 

    Google Scholar  More

  • in

    Integrated strategic planning and multi-criteria decision-making framework with its application to agricultural water management

    Abbasi, N., Bahramloo, R. & Movahedan, M. Strategic planning for remediation and optimization of irrigation and drainage networks: a case study of Iran. J. Agric. Agric. Sci. Proc. 4, 211–221 (2015).
    Google Scholar 
    Abdelhaleem, F., Basiouny, M. & Mahmoud, A. Application of remote sensing and geographic information systems in irrigation water management under water scarcity conditions in Fayoum, Egypt. J. Environ. Manag. 299, 113683 (2021).Article 

    Google Scholar 
    Akbari-Alashti, H., Bozorg-Haddad, O., Fallah-Mehdipour, E. & Mariño, M. A. Multi-reservoir real-time operation rules: a new genetic programming approach. Proc. Instit. Civil Eng. Water Manag. 167(10), 561–576 (2014).Article 

    Google Scholar 
    Akhmouch, A. & Correia, F. N. The 12 OECD principles on water governance: when science meets policy. J. Utilities Policy. 43, 14–20 (2016).Article 

    Google Scholar 
    Amblard, L. & Mann, C. Understanding collective action for the achievement of EU water policy objectives in agricultural landscapes: insights from the institutional design principles and integrated landscape management approaches. J. Environ. Sci. Policy. 125, 76–86 (2021).Article 

    Google Scholar 
    Babaeian, F., Delavar, M., Morid, S. & Srinivasan, R. Robust climate change adaptation pathways in agricultural water management. J. Agric. Water Manag. 252, 106904 (2021).Article 

    Google Scholar 
    Barbosa, M. C., Alam, K. & Mushtaq, S. Water policy implementation in the state of São Paulo, Brazil: key challenges and opportunities. J. Environ. Sci. Policy. 60, 11–18 (2016).Article 

    Google Scholar 
    Barrett, S. M. Implementation studies: time for a revival? Personal reflections on 20 years of implementation studies. J. Public Admin. 82(2), 249–269 (2004).MathSciNet 
    Article 

    Google Scholar 
    Baumgartner, R. J. & Korhonen, J. Strategic thinking for sustainable development. J. Sustain. Dev. 18(2), 71–75 (2010).Article 

    Google Scholar 
    Biswas, S. Measuring performance of healthcare supply chains in India: a comparative analysis of multi-criteria decision making methods. J. Decis. Making Appl. Manag. Eng. 3(2), 162–189 (2020).Article 

    Google Scholar 
    Biswas, S., Majumder, S., Pamucar, D. & Suman, D. An extended LBWA framework in picture fuzzy environment using actual score measures application in social enterprise systems. J. Enterp. Inform. Syst. (IJEIS) 17(4), 37–68 (2021).Article 

    Google Scholar 
    Biswas, S., Pamucar, D., Chowdhury, P. & Kar, S. A new decision support framework with picture fuzzy information: comparison of video conferencing platforms for higher education in India. J. Disc. Dyn. Nat. Soc. (2021).Bozorg-Haddad, O., Moradi-Jalal, M., Mirmomeni, M., Kholghi, M. K. H. & Mariño, M. A. Optimal cultivation rules in multi-crop irrigation areas. J. Irrig. Drain. 58(1), 38–49 (2009).Article 

    Google Scholar 
    Bozorg-Haddad, O., Loáiciga, H. A. & Zolghadr-Asli, B. A handbook on multi-attribute decision-making methods chapter (Wiley, 2021).MATH 
    Book 

    Google Scholar 
    Buckley, J. J. Fuzzy hierarchical analysis. J. Fuzzy Sets Syst. 17(3), 233–247 (1985).MathSciNet 
    MATH 
    Article 

    Google Scholar 
    Chang, H. H. & Huang, W. C. Application of a quantification SWOT analytical method. J. Math. Comput. Model. 43, 158–169 (2006).MathSciNet 
    MATH 
    Article 

    Google Scholar 
    Chen, C. T. Extension of the TOPSIS for group decision-making under fuzzy environment. J. Fuzzy Sets Syst. 114(1), 1–9 (2000).MATH 
    Article 

    Google Scholar 
    Conrad, C., Usman, M., Morper-Bush, L. & Schönbrodt-Stitt, S. Remote sensing-based assessments of land use, soil and vegetation status, crop production and water use in irrigation systems of the Aral Sea Basin. J. Water Sec. 11, 100078 (2020).Article 

    Google Scholar 
    David, F. R. Strategic management: concepts and cases (Prentice Hall, 2011).
    Google Scholar 
    Fallah-Mehdipour, E., Bozorg-Haddad, O., Beygi, S. & Mariño, M. A. Effect of utility function curvature of Young’s bargaining method on the design of WDNs. J. Water Resour. Manag. 25(9), 2197–2218 (2011).Article 

    Google Scholar 
    Fanghua, H. & Guanchun, C. Fuzzy multi-criteria group decision-making model based on weighted borda scoring method for watershed ecological risk management: a case study of three Gorges reservoir area of China. J. Water Resour. Manag. 24(10), 2139–2165 (2010).Article 

    Google Scholar 
    Gallego-Ayala, J. & Juızo, D. Strategic implementation of integrated water resources management in Mozambique: an A’WOT analysis. J. PhysChem. Earth. 36(14–15), 1103–1111 (2011).ADS 
    Article 

    Google Scholar 
    Gao, C. Y. & Peng, D. H. Consolidating SWOT analysis with nonhomogeneous uncertain preference information. J. Knowl. Based Syst. 24, 796–808 (2011).Article 

    Google Scholar 
    Gosling, S. N. & Arnell, N. W. A global assessment of the impact of climate change on water scarcity. J. Clim. Change. 134, 371–385 (2016).ADS 
    Article 

    Google Scholar 
    Gurel, M. & Tat, M. SWOT analysis: a theoretical review. J. Int. Soc. Res. 10(51), 994–1006 (2017).Article 

    Google Scholar 
    Hamdy, A., & Trisorio-Liuzzi, G. Water management strategies to combat drought in the semiarid regions. Water management for drought mitigation in the Mediterranean at the regional conference on arab water, Cairo, Egypt (2004).Hartmann, T. & Spit, T. Frontiers of land and water governance in urban regions. J. Water Int. 39(6), 791–797 (2014).Article 

    Google Scholar 
    He, L., Bao, J., Daccache, A., Wang, S. & Guo, P. Optimize the spatial distribution of crop water consumption based on a cellular automata model: a case study of the middle Heihe River basin, China. J. Sci. Total Environ. 720, 137569 (2020).ADS 
    CAS 
    Article 

    Google Scholar 
    Hwang, C.L. & Yoon, K. Methods for multiple attribute decision making. In: Multiple attribute decision making: lecture notes in economics and mathematical systems, Springer, Heidelberg, Germany, vol 186 (1981).Hwang, F. P., Chen, S. J. & Hwang, C. L. Fuzzy multiple attribute decision making: methods and applications (Springer, 1992).MATH 

    Google Scholar 
    Islam, M. S., Sadiq, R. & Rodriguez, M. J. Evaluating water quality failure potential in water distribution systems: a fuzzy-TOPSIS-OWA-based methodology. J. Water Resour. Manag. 27(7), 2195–2216 (2013).Article 

    Google Scholar 
    Karabasevic, D., Zavadskas, E. K., Turskis, Z. & Stanujkic, D. The framework for the selection of personnel based on the SWARA and ARAS methods under uncertainties. J. Inform. 27(1), 49–65 (2016).Article 

    Google Scholar 
    Keršuliene, V., Zavadskas, E. K. & Turskis, Z. Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (Swara). J. Bus. Econ. Manag. 11(2), 243–258 (2010).Article 

    Google Scholar 
    Kim, S. et al. Developing spatial agricultural drought risk index with controllable geo-spatial indicators: a case study for South Korea and Kazakhstan. J. Disast. Risk Reduct. 54, 102056 (2021).Article 

    Google Scholar 
    Kousar, S., Zafar, A., Kausar, N., Pamucar, D. & Kattel, P. Fruit production planning in semiarid zones: a novel triangular intuitionistic fuzzy linear programming approach. J. Math. Prob. Eng. (2022).Lautze, J., de Silva, S., Giordano, M. & Sanford, L. Putting the cart before the horse: Water governance and IWRM. J. Nat. Resour. Forum Unit. Nat. Develop. 35(1), 1–8 (2011).Lee, K. L. & Lin, S. C. A fuzzy quantified SWOT procedure for environmental evaluation of an international distribution center. J. Inform. Sci. 178, 531–549 (2008).Article 

    Google Scholar 
    Loucks, D. P. Sustainable water resources management. Water International. Taylor & Francis, Milton Park (2000).Malczeweski, J. GIS and multicriteria decision analysis (Wiley, 1999).
    Google Scholar 
    Meza, I. et al. Drought risk for agricultural systems in South Africa: drivers, spatial patterns, and implications for drought risk management. J. Sci. Total Environ. 799, 149505 (2021).ADS 
    CAS 
    Article 

    Google Scholar 
    OECD. OECD principles on water governance. OECD Publishing (2015).Pahl-Wostl, C., Holtz, G., Kastens, B. & Knieper, C. Analyzing complex water governance regimes: the management and transition framework. J. Environ. Sci. Policy. 13(7), 571–581 (2010).Article 

    Google Scholar 
    Pahl-Wostl, C. et al. Environmental flows and water governance: managing sustainable water uses. J. Curr. Opin. Environm. Sustain. 5(3), 341–351 (2013).Article 

    Google Scholar 
    Pamucar, D., Torkayesh, A.E. & Biswas, S. Supplier selection in healthcare supply chain management during the COVID-19 pandemic: a novel fuzzy rough decision-making approach. J. Ann. Oper. Res. doi:https://doi.org/10.1007/s10479-022-04529-2(2022).Panchal, D., Chatterjee, P., Pamucar, D. & Yazdani, M. A novel fuzzy-based structured framework for sustainable operation and environmental friendly production in coal-fired power industry. J. Intell. Syst. doi: https://doi.org/10.1002/int.22507(2021).Peldschus, F., Zavadskas, E. K., Turskis, Z. & Tamosaitiene, J. Sustainable assessment of construction site by applying game theory. J. Eng. Econ. 21(3), 223–237 (2010).
    Google Scholar 
    Pérez-Blanco, C. & Gómez, C. Drought management plans and water availability in agriculture: a risk assessment model for a Southern European basin. J. Weather Clim. Extrem. 4, 11–18 (2014).Article 

    Google Scholar 
    Portoghese, I., Giannoccaro, G., Giordano, R. & Pagano, A. Modeling the impact of volumetric water pricing in irrigation districts with conjunctive use of water of surface and groundwater resources. J. Agric. Water Manag. 244, 106561 (2020).Article 

    Google Scholar 
    Rani, P., Mishra, A. R., Saha, A., Hezam, I. M. & Pamucar, D. Fermatean fuzzy Heronian mean operators and MEREC-based additive ratio assessment method: an application to food waste treatment technology selection. J. Intell. Syst. 37(3), 2612–2647 (2021).Article 

    Google Scholar 
    Rogers, P., & Hall, A.W. Effective water governance. J. Tech. Comm. Background Papers.7, Global Water Partnership (GWP) (2003).Rouillard, J. & Rinaudo, J. From State to user-based water allocations: an empirical analysis of institutions developed by agricultural user associations in France. J. Agric. Water Manag. 239, 106269 (2020).Article 

    Google Scholar 
    Ruzgys, A., Volvačiovas, R., Ignatavičius, Č & Turskis, Z. Integrated evaluation of external wall insulation in residential buildings using SWARA-TODIM MCDM method. J. Civil Eng. Manag. 20(1), 103–110 (2014).Article 

    Google Scholar 
    Saaty, T. L. A scaling method for priorities in hierarchical structures. J. Math. Psychol. 15, 234–281 (1977).MathSciNet 
    MATH 
    Article 

    Google Scholar 
    Saaty, T. L. The analytic hierarchy process (McGraw-Hill, 1980).MATH 

    Google Scholar 
    Saaty, T. L. The analytic hierarchy process: planning, priority setting, resource allocation (RWS Publication, 1996).MATH 

    Google Scholar 
    Saaty, T. L. Decision making with the analytic hierarchy process. Int. J. Serv. Sci. 1(1), 83–98 (2008).
    Google Scholar 
    Soltanjalili, M., Bozorg-Haddad, O. & Mariño, M. A. Effect of breakage level one in design of water distribution networks. J. Water Resour. Manag. 25(1), 311–337 (2011).Article 

    Google Scholar 
    Srdjevic, Z., Bajcetic, R. & Srdjevic, B. Identifying the criteria set for multi criteria decision making based on SWOT/PESTLE analysis: a case study of reconstructing a water intake structure. J. Water Resour. Manag. 26(12), 3379–3393 (2012).Article 

    Google Scholar 
    Stewart, R. A., Mohamed, S. & Daet, R. Strategic implementation of IT/IS projects in construction: a case study. J. Autom. Const. 11, 681–694 (2002).Article 

    Google Scholar 
    Thaler, T., Nordbeck, R. & Seher, W. Cooperation in flood risk management: understanding the role of strategic planning in two Austrian policy instruments. J. Environ. Sci. Policy. 114, 170–177 (2020).Article 

    Google Scholar 
    Thomson, J. et al. Spatial conservation action planning in heterogeneous landscapes. J. Biol. Conser. 250, 108735 (2020).Article 

    Google Scholar 
    Tortajada, C. Water governance: some critical issues. J. Water Resour. Develop. 26(2), 297–307 (2010).Article 

    Google Scholar 
    Tropp, H. Water governance: trends and needs for new capacity development. J. Water Policy. 9(2), 19–30 (2007).Article 

    Google Scholar 
    Van Laarhoven, P. J. & Pedrycz, W. A fuzzy extension of Saaty’s priority theory. J. Fuzzy Sets Syst. 11(1–3), 229–241 (1983).MathSciNet 
    MATH 
    Article 

    Google Scholar 
    Venot, J., Reddy, V. R. & Umapathy, D. Coping with drought in irrigated South India: Farmers’ adjustments in Nagarjuna Sagar. J. Agric. Water Manag. 97(10), 1434–1442 (2010).Article 

    Google Scholar 
    Vermillion, D.L. Irrigation sector reform in Asia: from patronage under participation to empowerment with partnership. In Asian Irrigation in Transition. New Delhi: Sage publications. https://www.cabdirect.org/cabdirect/abstract/20073076323(2003).Yazdani, M., Wen, Z., Liao, H., Banaitis, A. & Turskis, Z. A grey combined compromise solution (CoCoSo-G) method for supplier selection in construction management. J. Civil Eng. Manag. 25(8), 858–874 (2019).Article 

    Google Scholar 
    Yuksel, I. & Dagdeviren, M. Using the analytic network process (ANP) in a SWOT analysis: a case study for a textile firm. J. Inform. Sci. 177, 3364–3382 (2007).MATH 
    Article 

    Google Scholar 
    Zadeh, L. A. Fuzzy sets. J. Inform. Control. 8(3), 338–353 (1965).MATH 
    Article 

    Google Scholar 
    Zavadskas, E. K., Mardani, A., Turskis, Z., Jusoh, A. & Nor, K. M. Development of TOPSIS method to solve complicated decision-making problems: an overview on developments from 2000 to 2015. J. Inform. Technol. Dec. Making. 15(03), 645–682 (2016).Article 

    Google Scholar 
    Zuo, Q., Wu, Q., Yu, L., Li, Y. & Fan, Y. Optimization of uncertain agricultural management considering the framework of water, energy and food. J. Agric. Water Manag. 253, 106907 (2021).Article 

    Google Scholar  More

  • in

    Plant growth-promoting rhizobacteria Burkholderia vietnamiensis B418 inhibits root-knot nematode on watermelon by modifying the rhizosphere microbial community

    Jones, J. T. et al. Top 10 plant-parasitic nematodes in molecular plant pathology. Mol. Plant Pathol. 14, 946–961. https://doi.org/10.1111/mpp.12057 (2013).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Collange, B., Navarrete, M., Peyre, G., Mateille, T. & Tchamitchian, M. Root-knot nematode (Meloidogyne) management in vegetable crop production: The challenge of an agronomic system analysis. Crop Prot. 30, 1251–1262. https://doi.org/10.1016/j.cropro.2011.04.016 (2011).Article 

    Google Scholar 
    Nyaku, S. T., Affokpon, A., Danquah, A. & Brentu, F. C. in Nematology–concepts, diagnosis and control (eds Mohammad Manjur Shah & Mohammad Mahamood) 153–182 (IntechOpen, 2017).Desaeger, J., Wram, C. & Zasada, I. New reduced-risk agricultural nematicides-rationale and review. J. Nematol. 52, 1 (2020).Article 

    Google Scholar 
    Dong, L. & Zhang, K. Microbial control of plant-parasitic nematodes: a five-party interaction. Plant Soil 288, 31–45. https://doi.org/10.1007/s11104-006-9009-3 (2006).CAS 
    Article 

    Google Scholar 
    Singh, S., Singh, B. & Singh, A. Nematodes: A threat to sustainability of agriculture. Procedia Environ. Sci. 29, 215–216. https://doi.org/10.1016/j.proenv.2015.07.270 (2015).Article 

    Google Scholar 
    Oka, Y. Mechanisms of nematode suppression by organic soil amendments—A review. Appl. Soil Ecol. 44, 101–115. https://doi.org/10.1016/j.apsoil.2009.11.003 (2010).Article 

    Google Scholar 
    Yue, X., Li, F. & Wang, B. Activity of four nematicides against Meloidogyne incognita race 2 on tomato plants. J. Phytopathol. 168, 399–404. https://doi.org/10.1111/jph.12904 (2020).CAS 
    Article 

    Google Scholar 
    Huang, W.-K. et al. Mutations in Acetylcholinesterase2 (ace 2) increase the insensitivity of acetylcholinesterase to fosthiazate in the root-knot nematode Meloidogyne incognita. Sci. Rep. 6, 1–9. https://doi.org/10.1038/srep38102 (2016).CAS 
    Article 

    Google Scholar 
    Yoon, Y., Kim, E.-S., Hwang, Y.-S. & Choi, C.-Y. Avermectin: Biochemical and molecular basis of its biosynthesis and regulation. Appl. Microbiol. Biotechnol. 63, 626–634. https://doi.org/10.1007/s00253-003-1491-4 (2004).CAS 
    Article 
    PubMed 

    Google Scholar 
    Wolstenholme, A. J. & Rogers, A. Glutamate-gated chloride channels and the mode of action of the avermectin/milbemycin anthelmintics. Parasitology 131, S85–S95. https://doi.org/10.1017/S0031182005008218 (2005).CAS 
    Article 
    PubMed 

    Google Scholar 
    Haydock, P., Woods, S., Grove, I. & Hare, M. in Plant nematology (eds Roland N Perry & Maurice Moens) 459–479 (CABI, 2013).Forghani, F. & Hajihassani, A. Recent advances in the development of environmentally benign treatments to control root-knot nematodes. Front. Plant Sci. 11, 1. https://doi.org/10.3389/fpls.2020.01125 (2020).Article 

    Google Scholar 
    Lugtenberg, B. & Kamilova, F. Plant-growth-promoting rhizobacteria. Annu. Rev. Microbiol. 63, 541–556. https://doi.org/10.1146/annurev.micro.62.081307.162918 (2009).CAS 
    Article 
    PubMed 

    Google Scholar 
    Mhatre, P. H. et al. Plant growth promoting rhizobacteria (PGPR): a potential alternative tool for nematodes bio-control. Biocatal. Agr. Biotechnol. 17, 119–128. https://doi.org/10.1016/j.bcab.2018.11.009 (2019).Article 

    Google Scholar 
    Eissa, M. F. & Abd-Elgawad, M. M. in Biocontrol agents of phytonematodes (eds Tarique Hassan Askary & Paulo Roberto Martinelli) 217–243 (CABI, 2015).Luo, T., Hou, S., Yang, L., Qi, G. & Zhao, X. Nematodes avoid and are killed by Bacillus mycoides-produced styrene. J. Invertebr. Pathol. 159, 129–136. https://doi.org/10.1016/j.jip.2018.09.006 (2018).CAS 
    Article 
    PubMed 

    Google Scholar 
    Siddiqui, I. & Shaukat, S. Systemic resistance in tomato induced by biocontrol bacteria against the root-knot nematode, Meloidogyne javanica is independent of salicylic acid production. J. Phytopathol. 152, 48–54. https://doi.org/10.1046/j.1439-0434.2003.00800.x (2004).Article 

    Google Scholar 
    Li, W. et al. Broad spectrum anti-biotic activity and disease suppression by the potential biocontrol agent Burkholderia ambifaria BC-F. Crop Protect. 21, 129–135. https://doi.org/10.1016/S0261-2194(01)00074-6 (2002).Article 

    Google Scholar 
    Khanna, K. et al. Role of plant growth promoting Bacteria (PGPRs) as biocontrol agents of Meloidogyne incognita through improved plant defense of Lycopersicon esculentum. Plant. Soil 436, 325–345. https://doi.org/10.1007/s11104-019-03932-2 (2019).CAS 
    Article 

    Google Scholar 
    Subedi, P., Gattoni, K., Liu, W., Lawrence, K. S. & Park, S.-W. Current utility of plant growth-promoting rhizobacteria as biological control agents towards plant-parasitic nematodes. Plants 9, 1167. https://doi.org/10.3390/plants9091167 (2020).CAS 
    Article 
    PubMed Central 

    Google Scholar 
    Oka, Y. et al. New strategies for the control of plant-parasitic nematodes. Pest Manag. Sci. 56, 983–988. https://doi.org/10.1002/1526-4998(200011)56:11%3c983::AID-PS233%3e3.0.CO;2-X (2000).CAS 
    Article 

    Google Scholar 
    Ralmi, N. H. A. A., Khandaker, M. M. & Mat, N. Occurrence and control of root knot nematode in crops: A review. Aust. J. Crop Sci. 11, 1649 (2016).Article 

    Google Scholar 
    Topalović, O. & Heuer, H. Plant-nematode interactions assisted by microbes in the rhizosphere. Curr. Issues Mol. Biol. 30, 75–88 (2019).Article 

    Google Scholar 
    Olanrewaju, O. S., Ayangbenro, A. S., Glick, B. R. & Babalola, O. O. Plant health: Feedback effect of root exudates-rhizobiome interactions. Appl. Microbiol. Biotechnol. 103, 1155–1166. https://doi.org/10.1007/s00253-018-9556-6 (2019).CAS 
    Article 
    PubMed 

    Google Scholar 
    Handley, K. M. et al. Biostimulation induces syntrophic interactions that impact C, S and N cycling in a sediment microbial community. ISME J. 7, 800–816. https://doi.org/10.1038/ismej.2012.148 (2013).CAS 
    Article 
    PubMed 

    Google Scholar 
    Tang, Y. et al. Changes in nitrogen-cycling microbial communities with depth in temperate and subtropical forest soils. Appl. Soil Ecol. 124, 218–228. https://doi.org/10.1016/j.apsoil.2017.10.029 (2018).ADS 
    Article 

    Google Scholar 
    Babić, K. H. et al. Influence of different Sinorhizobium meliloti inocula on abundance of genes involved in nitrogen transformations in the rhizosphere of alfalfa (Medicago sativa L.). Environ. Microbiol. 10, 2922–2930 (2008).Article 

    Google Scholar 
    Ke, X. et al. Effect of inoculation with nitrogen-fixing bacterium Pseudomonas stutzeri A1501 on maize plant growth and the microbiome indigenous to the rhizosphere. Syst. Appl. Microbiol. 42, 248–260. https://doi.org/10.1016/j.syapm.2018.10.010 (2019).CAS 
    Article 
    PubMed 

    Google Scholar 
    Hogan, G. et al. Microbiome analysis as a platform R&D tool for parasitic nematode disease management. ISME J. 13, 2664–2680. https://doi.org/10.1038/s41396-019-0462-4 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wu, Y. et al. Draft genome sequence of Stenotrophomonas maltophilia strain B418, a promising agent for biocontrol of plant pathogens and root-knot nematode. Genome Announc. 3, e00015-00015. https://doi.org/10.1128/genomeA.00015-15 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wang, Y. et al. Isolation and identification of nematicidal active substance from Burkholderia vietnamiensis B418. Plant Prot. 40, 65–69 (2014).
    Google Scholar 
    Li, S., Li, J., Xu, W., Chen, K. & Yang, H. Field efficacy test of biocontrol agent YKT41 and B418 against eggplant root-knot nematode disease. Shandong Sci. 24, 10–13 (2011).CAS 

    Google Scholar 
    Wang, Y., Wang, Z., Liu, B., Pan, M. & Li, J. Field trial of Burkholderia vietnamiensis and its composite microbial flora on cucumber root-knot nematode. Shandong Sci. 31, 39. https://doi.org/10.3976/j.issn.1002-4026.2018.01.007 (2018).Article 

    Google Scholar 
    Saad, A.-F.S., Massoud, M. A., Ibrahim, H. S. & Khalil, M. S. Management study for the root-knot nematodes, Meloidogyne incognita on tomatoes using fosthiazate and arbiscular mycorrhiza fungus. J. Adv. Agric. Res. 16, 137–147 (2011).
    Google Scholar 
    Huang, W.-K. et al. Efficacy evaluation of fungus Syncephalastrum racemosum and nematicide avermectin against the root-knot nematode Meloidogyne incognita on cucumber. PLoS ONE 9, e89717. https://doi.org/10.1371/journal.pone.0089717 (2014).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Jayakumar, J. & Ramakrishnan, S. Evaluation of avermectin and its combination with nematicide and bioagents against root knot nematode, Meloidogyne incognita in tomato. J. Biol. Control 23, 317–319 (2009).
    Google Scholar 
    Moosavi, M. & Zare, R. in Biocontrol Agents of Phytonematodes (eds Tarique Hassan Askary & Paulo Roberto Martinelli) 423–445 (CABI, 2015).Berendsen, R. L., Pieterse, C. M. & Bakker, P. A. The rhizosphere microbiome and plant health. Trends Plant Sci. 17, 478–486. https://doi.org/10.1016/j.tplants.2012.04.001 (2012).CAS 
    Article 
    PubMed 

    Google Scholar 
    Reinhold-Hurek, B., Bünger, W., Burbano, C. S., Sabale, M. & Hurek, T. Roots shaping their microbiome: Global hotspots for microbial activity. Annu. Rev. Phytopathol. 53, 403–424. https://doi.org/10.1146/annurev-phyto-082712-102342 (2015).CAS 
    Article 
    PubMed 

    Google Scholar 
    Ahemad, M. & Kibret, M. Mechanisms and applications of plant growth promoting rhizobacteria: Current perspective. J. King Saud Univ.-Sci. 26, 1–20. https://doi.org/10.1016/j.jksus.2013.05.001 (2014).Article 

    Google Scholar 
    Ciccillo, F. et al. Effects of two different application methods of Burkholderia ambifaria MCI 7 on plant growth and rhizospheric bacterial diversity. Environ. Microbiol. 4, 238–245. https://doi.org/10.1046/j.1462-2920.2002.00291.x (2002).Article 
    PubMed 

    Google Scholar 
    Jo, H. et al. Response of soil bacterial community and pepper plant growth to application of Bacillus thuringiensis KNU-07. Agronomy 10, 551. https://doi.org/10.3390/agronomy10040551 (2020).CAS 
    Article 

    Google Scholar 
    Wang, J. et al. Traits-based integration of multi-species inoculants facilitates shifts of indigenous soil bacterial community. Front. Microbiol. 9, 1692. https://doi.org/10.3389/fmicb.2018.01692 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Welbaum, G. E., Sturz, A. V., Dong, Z. & Nowak, J. Managing soil microorganisms to improve productivity of agro-ecosystems. Crit. Rev. Plant Sci. 23, 175–193. https://doi.org/10.1080/07352680490433295 (2004).CAS 
    Article 

    Google Scholar 
    Mendes, R., Garbeva, P. & Raaijmakers, J. M. The rhizosphere microbiome: Significance of plant beneficial, plant pathogenic, and human pathogenic microorganisms. FEMS Microbiol. Rev. 37, 634–663. https://doi.org/10.1111/1574-6976.12028 (2013).CAS 
    Article 
    PubMed 

    Google Scholar 
    Li, J. et al. Trichoderma harzianum inoculation reduces the incidence of clubroot disease in Chinese cabbage by regulating the rhizosphere microbial community. Microorganisms 8, 1325. https://doi.org/10.3390/microorganisms8091325 (2020).CAS 
    Article 
    PubMed Central 

    Google Scholar 
    Song, L. et al. Regular biochar and bacteria-inoculated biochar alter the composition of the microbial community in the soil of a Chinese fir plantation. Forests 11, 951. https://doi.org/10.3390/f11090951 (2020).Article 

    Google Scholar 
    Mendes, R. et al. Deciphering the rhizosphere microbiome for disease-suppressive bacteria. Science 332, 1097–1100. https://doi.org/10.1126/science.1203980 (2011).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    Palaniyandi, S. A., Yang, S. H., Zhang, L. & Suh, J.-W. Effects of actinobacteria on plant disease suppression and growth promotion. Appl. Microbiol. Biotechnol. 97, 9621–9636. https://doi.org/10.1007/s00253-013-5206-1 (2013).CAS 
    Article 
    PubMed 

    Google Scholar 
    Zhou, D. et al. Rhizosphere microbiomes from root knot nematode non-infested plants suppress nematode infection. Microbial Ecol. 78, 470–481. https://doi.org/10.1007/s00248-019-01319-5 (2019).CAS 
    Article 

    Google Scholar 
    Zou, Y. et al. Metagenomic insights into the effect of oxytetracycline on microbial structures, functions and functional genes in sediment denitrification. Ecotox. Environ. Safe. 161, 85–91. https://doi.org/10.1016/j.ecoenv.2018.05.045 (2018).CAS 
    Article 

    Google Scholar 
    Kong, Z. et al. Seasonal dynamics of the bacterioplankton community in a large, shallow, highly dynamic freshwater lake. Can. J. Microbiol. 64, 786–797. https://doi.org/10.1139/cjm-2018-0126 (2018).CAS 
    Article 
    PubMed 

    Google Scholar 
    Bach, E. M., Williams, R. J., Hargreaves, S. K., Yang, F. & Hofmockel, K. S. Greatest soil microbial diversity found in micro-habitats. Soil Biol. Biochem. 118, 217–226. https://doi.org/10.1016/j.soilbio.2017.12.018 (2018).CAS 
    Article 

    Google Scholar 
    Wang, W. et al. Predatory Myxococcales are widely distributed in and closely correlated with the bacterial community structure of agricultural land. Appl. Soil Ecol. 146, 103365. https://doi.org/10.1016/j.apsoil.2019.103365 (2020).Article 

    Google Scholar 
    Schmidt, J. E., Kent, A. D., Brisson, V. L. & Gaudin, A. C. Agricultural management and plant selection interactively affect rhizosphere microbial community structure and nitrogen cycling. Microbiome 7, 1–18. https://doi.org/10.1186/s40168-019-0756-9 (2019).Article 

    Google Scholar 
    Hu, W., Strom, N., Haarith, D., Chen, S. & Bushley, K. E. Mycobiome of cysts of the soybean cyst nematode under long term crop rotation. Front. Microbiol. 9, 386. https://doi.org/10.3389/fmicb.2018.00386 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Li, W.-H. & Liu, Q.-Z. Changes in fungal community and diversity in strawberry rhizosphere soil after 12 years in the greenhouse. J. Integ. Agric. 18, 677–687. https://doi.org/10.1016/S2095-3119(18)62003-9 (2019).Article 

    Google Scholar 
    Qiu, W. et al. Organic fertilization assembles fungal communities of wheat rhizosphere soil and suppresses the population growth of Heterodera avenae in the field. Front. Plant Sci. 11, 1225. https://doi.org/10.3389/fpls.2020.01225 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Schardl, C. L., Leuchtmann, A. & Spiering, M. J. Symbioses of grasses with seedborne fungal endophytes. Annu. Rev. Plant Biol. 55, 315–340. https://doi.org/10.1146/annurev.arplant.55.031903.141735 (2004).CAS 
    Article 
    PubMed 

    Google Scholar 
    Edgington, S., Thompson, E., Moore, D., Hughes, K. A. & Bridge, P. Investigating the insecticidal potential of Geomyces (Myxotrichaceae: Helotiales) and Mortierella (Mortierellacea: Mortierellales) isolated from Antarctica. Springerplus 3, 1–8. https://doi.org/10.1186/2193-1801-3-289 (2014).Article 

    Google Scholar 
    Yi, X. et al. Comparison of the abundance and community structure of N-Cycling bacteria in paddy rhizosphere soil under different rice cultivation patterns. Int. J. Mol. Sci. 19, 3772. https://doi.org/10.3390/ijms19123772 (2018).CAS 
    Article 
    PubMed Central 

    Google Scholar 
    Duval, S. et al. Electron transfer precedes ATP hydrolysis during nitrogenase catalysis. Proc. Natl. Acad. Sci. USA 110, 16414–16419. https://doi.org/10.1073/pnas.1311218110 (2013).ADS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pham, V. T. et al. The plant growth-promoting effect of the nitrogen-fixing endophyte Pseudomonas stutzeri A15. Arch. Microbiol. 199, 513–517. https://doi.org/10.1007/s00203-016-1332-3 (2017).CAS 
    Article 
    PubMed 

    Google Scholar 
    Ouyang, Y., Evans, S. E., Friesen, M. L. & Tiemann, L. K. Effect of nitrogen fertilization on the abundance of nitrogen cycling genes in agricultural soils: a meta-analysis of field studies. Soil Biol. Biochem. 127, 71–78. https://doi.org/10.1016/j.soilbio.2018.08.024 (2018).CAS 
    Article 

    Google Scholar 
    Dynarski, K. A. & Houlton, B. Z. Nutrient limitation of terrestrial free-living nitrogen fixation. New Phytol. 217, 1050–1061. https://doi.org/10.1111/nph.14905 (2018).CAS 
    Article 
    PubMed 

    Google Scholar 
    Kastl, E.-M., Schloter-Hai, B., Buegger, F. & Schloter, M. Impact of fertilization on the abundance of nitrifiers and denitrifiers at the root–soil interface of plants with different uptake strategies for nitrogen. Biol. Fert. Soils 51, 57–64. https://doi.org/10.1007/s00374-014-0948-1 (2015).CAS 
    Article 

    Google Scholar 
    Bulgarelli, D. et al. Revealing structure and assembly cues for Arabidopsis root-inhabiting bacterial microbiota. Nature 488, 91–95. https://doi.org/10.1038/nature11336 (2012).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    Southey, J. in Laboratory methods for work with plants and soil nematodes (ed JF Southey) 42–44 (HMSO, 1986).Ladner, D. C., Tchounwou, P. B. & Lawrence, G. W. Evaluation of the effect of ecologic on root knot nematode, Meloidogyne incognita, and tomato plant, Lycopersicon esculenum. Int. J. Environ. Res. Public Health 5, 104–110. https://doi.org/10.3390/ijerph5020104 (2008).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Niu, D.-D. et al. Application of PSX biocontrol preparation confers root-knot nematode management and increased fruit quality in tomato under field conditions. Biocontrol Sci. Technol. 26, 174–180. https://doi.org/10.1080/09583157.2015.1085489.18 (2016).Article 

    Google Scholar 
    Klindworth, A. et al. Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucl. Acids Res. 41, e1–e1. https://doi.org/10.1093/nar/gks808 (2013).CAS 
    Article 
    PubMed 

    Google Scholar 
    Buee, M. et al. 454 Pyrosequencing analyses of forest soils reveal an unexpectedly high fungal diversity. New Phytol. 184, 449–456. https://doi.org/10.1111/j.1469-8137.2009.03003.x (2009).CAS 
    Article 
    PubMed 

    Google Scholar 
    Rösch, C., Mergel, A. & Bothe, H. Biodiversity of denitrifying and dinitrogen-fixing bacteria in an acid forest soil. Appl. Environ. Microbiol. 68, 3818–3829. https://doi.org/10.1128/AEM.68.8.3818-3829.2002 (2002).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Throbäck, I. N., Enwall, K., Jarvis, Å. & Hallin, S. Reassessing PCR primers targeting nirS, nirK and nosZ genes for community surveys of denitrifying bacteria with DGGE. FEMS Microbiol. Ecol. 49, 401–417. https://doi.org/10.1016/j.femsec.2004.04.011 (2004).CAS 
    Article 
    PubMed 

    Google Scholar 
    Edgar, R. C., Haas, B. J., Clemente, J. C., Quince, C. & Knight, R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–2200. https://doi.org/10.1093/bioinformatics/btr381 (2011).CAS 
    Article 
    PubMed 
    PubMed Central 

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

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

    Google Scholar 
    Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 1–21. https://doi.org/10.1186/s13059-014-0550-8 (2014).CAS 
    Article 

    Google Scholar 
    Lozupone, C. & Knight, R. UniFrac: A new phylogenetic method for comparing microbial communities. Appl. Environ. Microbiol. 71, 8228–8235. https://doi.org/10.1128/AEM.71.12.8228-8235.2005 (2005).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Parks, D. H., Tyson, G. W., Hugenholtz, P. & Beiko, R. G. STAMP: statistical analysis of taxonomic and functional profiles. Bioinformatics 30, 3123–3124. https://doi.org/10.1093/bioinformatics/btu494 (2014).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar  More

  • in

    Consuming fresh macroalgae induces specific catabolic pathways, stress reactions and Type IX secretion in marine flavobacterial pioneer degraders

    Duarte C, Middelburg JJ, Caraco N. Major role of marine vegetation on the oceanic carbon cycle. Biogeosciences. 2005;2:1–8.CAS 
    Article 

    Google Scholar 
    Kloareg B, Quatrano RS. Structure of the cell walls of marine algae and ecophysiological functions of the matrix polysaccharides. Ocean Mar Biol Annu Rev. 1988;26:259–315.
    Google Scholar 
    Fletcher HR, Biller P, Ross AB, Adams JMM. The seasonal variation of fucoidan within three species of brown macroalgae. Algal Res. 2017;22:79–86.Article 

    Google Scholar 
    Deniaud-Bouët E, Hardouin K, Potin P, Kloareg B, Hervé C. A review about brown algal cell walls and fucose-containing sulfated polysaccharides: Cell wall context, biomedical properties and key research challenges. Carbohydr Polym. 2017;175:395–408.PubMed 
    Article 
    CAS 

    Google Scholar 
    Haug A, Larsen B, Smidsrød O. Uronic acid sequence in alginate from different sources. Carbohydr Res. 1974;32:217–225.CAS 
    Article 

    Google Scholar 
    Bruhn A, Janicek T, Manns D, Nielsen MM, Balsby TJS, Meyer AS, et al. Crude fucoidan content in two North Atlantic kelp species, Saccharina latissima and Laminaria digitata—seasonal variation and impact of environmental factors. J Appl Phycol. 2017;29:3121–3137.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Ponce NMA, Stortz CA. A comprehensive and comparative analysis of the fucoidan compositional data across the Phaeophyceae. Front Plant Sci. 2020;11:556312.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Fleurence J. The enzymatic degradation of algal cell walls: A useful approach for improving protein accessibility? J Appl Phycol. 1999;11:313–314.CAS 
    Article 

    Google Scholar 
    Verhaeghe EF, Fraysse A, Guerquin-Kern JL, Wu TD, Devès G, Mioskowski C, et al. Microchemical imaging of iodine distribution in the brown alga Laminaria digitata suggests a new mechanism for its accumulation. J Biol Inorg Chem. 2008;13:257–269.CAS 
    PubMed 
    Article 

    Google Scholar 
    Schiener P, Black KD, Stanley MS, Green DH. The seasonal variation in the chemical composition of the kelp species Laminaria digitata, Laminaria hyperborea, Saccharina latissima and Alaria esculenta. J Appl Phycol. 2015;27:363–373.CAS 
    Article 

    Google Scholar 
    Deniaud-Bouët E, Kervarec N, Michel G, Tonon T, Kloareg B, Hervé C. Chemical and enzymatic fractionation of cell walls from Fucales: Insights into the structure of the extracellular matrix of brown algae. Ann Bot. 2014;114:1203–1216.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Michel G, Tonon T, Scornet D, Cock JM, Kloareg B. Central and storage carbon metabolism of the brown alga Ectocarpus siliculosus: Insights into the origin and evolution of storage carbohydrates in Eukaryotes. N. Phytol. 2010;188:67–81.CAS 
    Article 

    Google Scholar 
    Mann K. Ecology of coastal waters—A systems approach, Berkeley: University of California Press; 1982.Egan S, Harder T, Burke C, Steinberg P, Kjelleberg S, Thomas T. The seaweed holobiont: Understanding seaweed-bacteria interactions. FEMS Microbiol Rev. 2013;37:462–476.CAS 
    PubMed 
    Article 

    Google Scholar 
    Kirchman DL. The ecology of Cytophaga-Flavobacteria in aquatic environments. FEMS Microbiol Ecol. 2002;39:91–100.CAS 
    PubMed 

    Google Scholar 
    Thomas F, Hehemann JH, Rebuffet E, Czjzek M, Michel G. Environmental and gut Bacteroidetes: The food connection. Front Microbiol. 2011;2:93.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Teeling H, Fuchs BM, Becher D, Klockow C, Gardebrecht A, Bennke CM, et al. Substrate-controlled succession of marine bacterioplankton populations induced by a phytoplankton bloom. Science. 2012;336:608–611.CAS 
    PubMed 
    Article 

    Google Scholar 
    Wietz M, Wemheuer B, Simon H, Giebel HA, Seibt MA, Daniel R, et al. Bacterial community dynamics during polysaccharide degradation at contrasting sites in the Southern and Atlantic Oceans. Environ Microbiol. 2015;17:3822–3831.CAS 
    PubMed 
    Article 

    Google Scholar 
    Arnosti C, Wietz M, Brinkhoff T, Hehemann J-H, Probant D, Zeugner L, et al. The biogeochemistry of marine polysaccharides: sources, inventories, and bacterial drivers of the carbohydrate cycle. Ann Rev Mar Sci. 2020;13:9.1–9.28.
    Google Scholar 
    Lombard V, Golaconda Ramulu H, Drula E, Coutinho PM, Henrissat B. The carbohydrate-active enzymes database (CAZy) in 2013. Nucleic Acids Res. 2014;42:490–495.Article 
    CAS 

    Google Scholar 
    Barbeyron T, Brillet-Guéguen L, Carré W, Carrière C, Caron C, Czjzek M, et al. Matching the diversity of sulfated biomolecules: Creation of a classification database for sulfatases reflecting their substrate specificity. PLoS One. 2016;11:1–33.Article 
    CAS 

    Google Scholar 
    Tang K, Lin Y, Han Y, Jiao N. Characterization of potential polysaccharide utilization systems in the marine Bacteroidetes Gramella flava JLT2011 using a multi-omics approach. Front Microbiol. 2017;8:220.PubMed 
    PubMed Central 

    Google Scholar 
    Zhu Y, Chen P, Bao Y, Men Y, Zeng Y, Yang J, et al. Complete genome sequence and transcriptomic analysis of a novel marine strain Bacillus weihaiensis reveals the mechanism of brown algae degradation. Sci Rep. 2016;6:38248.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Thomas F, Bordron P, Eveillard D, Michel G. Gene expression analysis of Zobellia galactanivorans during the degradation of algal polysaccharides reveals both substrate-specific and shared transcriptome-wide responses. Front Microbiol. 2017;8:1808.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Ficko-Blean E, Préchoux A, Thomas F, Rochat T, Larocque R, Zhu Y, et al. Carrageenan catabolism is encoded by a complex regulon in marine heterotrophic bacteria. Nat Commun. 2017;8:1685.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Koch H, Dürwald A, Schweder T, Noriega-Ortega B, Vidal-Melgosa S, Hehemann JH, et al. Biphasic cellular adaptations and ecological implications of Alteromonas macleodii degrading a mixture of algal polysaccharides. ISME J. 2019;13:92–103.CAS 
    PubMed 
    Article 

    Google Scholar 
    Bunse C, Koch H, Breider S, Simon M, Wietz M. Sweet spheres: succession and CAZyme expression of marine bacterial communities colonizing a mix of alginate and pectin particles. Environ Microbiol. 2021;23:3130–3148.CAS 
    PubMed 
    Article 

    Google Scholar 
    Hehemann JH, Arevalo P, Datta MS, Yu X, Corzett CH, Henschel A, et al. Adaptive radiation by waves of gene transfer leads to fine-scale resource partitioning in marine microbes. Nat Commun. 2016;7:12860.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Gralka M, Szabo R, Stocker R, Cordero OX. Trophic interactions and the drivers of microbial community assembly. Curr Biol. 2020;30:R1176–R1188.CAS 
    PubMed 
    Article 

    Google Scholar 
    Jiménez DJ, Dini-Andreote F, DeAngelis KM, Singer SW, Salles JF, van Elsas JD. Ecological insights into the dynamics of plant biomass-degrading microbial consortia. Trends Microbiol. 2017;25:788–796.PubMed 
    Article 
    CAS 

    Google Scholar 
    Kang S, Kim JK. Reuse of red seaweed waste by a novel bacterium, Bacillus sp. SYR4 isolated from a sandbar. World J Microbiol Biotechnol. 2015;31:209–217.PubMed 
    Article 

    Google Scholar 
    Jonnadula R, Verma P, Shouche YS, Ghadi SC. Characterization of Microbulbifer strain CMC-5, a new biochemical variant of Microbulbifer elongatus type strain DSM6810T isolated from decomposing seaweeds. Curr Microbiol. 2009;59:600–607.CAS 
    PubMed 
    Article 

    Google Scholar 
    Martin M, Barbeyron T, Martin R, Portetelle D, Michel G, Vandenbol M. The cultivable surface microbiota of the brown alga Ascophyllum nodosum is enriched in macroalgal-polysaccharide-degrading bacteria. Front Microbiol. 2015;6:1487.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Dogs M, Wemheuer B, Wolter L, Bergen N, Daniel R, Simon M, et al. Rhodobacteraceae on the marine brown alga Fucus spiralis are abundant and show physiological adaptation to an epiphytic lifestyle. Syst Appl Microbiol. 2017;40:370–382.CAS 
    PubMed 
    Article 

    Google Scholar 
    Brunet M, le Duff N, Fuchs B, Amann R, Barbeyron T, Thomas F. Specific detection and quantification of the marine flavobacterial genus Zobellia on macroalgae using novel qPCR and CARD-FISH assays. Syst Appl Microbiol. 2021;44:126269.CAS 
    PubMed 
    Article 

    Google Scholar 
    Barbeyron T, L’Haridon S, Corre E, Kloareg B, Potin P. Zobellia galactanovorans gen. nov., sp. nov., a marine species of Flavobacteriaceae isolated from a red alga, and classification of [Cytophaga] uliginosa (ZoBell and Upham 1944) Reichenbach 1989 as Zobellia uliginosa gen. nov., comb. nov. Int J Syst Evol Microbiol. 2001;51:985–997.CAS 
    PubMed 
    Article 

    Google Scholar 
    Barbeyron T, Thiébaud M, Le Duff N, Martin M, Corre E, Tanguy G, et al. Zobellia roscoffensis sp. nov. and Zobellia nedashkovskayae sp. nov., two flavobacteria from the epiphytic microbiota of the brown alga Ascophyllum nodosum, and emended description of the genus Zobellia. Int J Syst Evol Microbiol. 2021;71:004913.Nedashkovskaya OI, Suzuki M, Vancanneyt M, Cleenwerck I, Lysenko AM, Mikhailov VV, et al. Zobellia amurskyensis sp. nov., Zobellia laminariae sp. nov. and Zobellia russellii sp. nov., novel marine bacteria of the family Flavobacteriaceae. Int J Syst Evol Microbiol. 2004;54:1643–1648.CAS 
    PubMed 
    Article 

    Google Scholar 
    Nedashkovskaya O, Otstavnykh N, Zhukova N, Guzev K, Chausova V, Tekutyeva L, et al. Zobellia barbeyronii sp. nov., a new member of the family Flavobacteriaceae, isolated from seaweed, and emended description of the species Z. amurskyensis, Z. laminariae, Z. russellii and Z. uliginosa. Diversity. 2021;13:520.CAS 
    Article 

    Google Scholar 
    Chernysheva N, Bystritskaya E, Stenkova A, Golovkin I. Comparative genomics and CAZyme genome repertoires of marine Zobellia amurskyensis KMM 3526T and Zobellia laminariae KMM 3676T. Mar Drugs. 2019;17:661.CAS 
    PubMed Central 
    Article 

    Google Scholar 
    Chernysheva N, Bystritskaya E, Likhatskaya G, Nedashkovskaya O, Isaeva M. Genome-wide analysis of PL7 alginate lyases in the genus Zobellia. Molecules. 2021;26:2387.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Barbeyron T, Thomas F, Barbe V, Teeling H, Schenowitz C, Dossat C, et al. Habitat and taxon as driving forces of carbohydrate catabolism in marine heterotrophic bacteria: Example of the model algae-associated bacterium Zobellia galactanivorans DsijT. Environ Microbiol. 2016;18:4610–4627.CAS 
    PubMed 
    Article 

    Google Scholar 
    Potin P, Sanseau A, Le Gall Y, Rochas C, Kloareg B. Purification and characterization of a new k‐carrageenase from a marine Cytophaga‐like bacterium. Eur J Biochem. 1991;201:241–247.CAS 
    PubMed 
    Article 

    Google Scholar 
    Lami R, Grimaud R, Sanchez-Brosseau S, Six C, Thomas F, West NJ, et al. Marine bacterial models for experimental biology. In: Boutet A, Schierwater B, editors. Handbook of Marine Model Organisms in Experimental Biology. London: Taylor & Francis Ltd; 2021.Dudek M, Dieudonné A, Jouanneau D, Rochat T, Michel G, Sarels B, et al. Regulation of alginate catabolism involves a GntR family repressor in the marine flavobacterium Zobellia galactanivorans DsijT. Nucleic Acids Res. 2020;48:7786–7800.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Thomas F, Lundqvist LCE, Jam M, Jeudy A, Barbeyron T, Sandström C, et al. Comparative characterization of two marine alginate lyases from Zobellia galactanivorans reveals distinct modes of action and exquisite adaptation to their natural substrate. J Biol Chem. 2013;288:23021–23037.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Thomas F, Barbeyron T, Tonon T, Génicot S, Czjzek M, Michel G. Characterization of the first alginolytic operons in a marine bacterium: from their emergence in marine Flavobacteriia to their independent transfers to marine Proteobacteria and human gut Bacteroides. Environ Microbiol. 2012;14:2379–94.CAS 
    PubMed 
    Article 

    Google Scholar 
    Jam M, Flament D, Allouch J, Potin P, Thion L, Kloareg B, et al. The endo-β-agarases AgaA and AgaB from the marine bacterium Zobellia galactanivorans: Two paralogue enzymes with different molecular organizations and catalytic behaviours. Biochem J. 2005;385:703–713.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Hehemann JH, Correc G, Thomas F, Bernard T, Barbeyron T, Jam M, et al. Biochemical and structural characterization of the complex agarolytic enzyme system from the marine bacterium Zobellia galactanivorans. J Biol Chem. 2012;287:30571–30584.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Labourel A, Jam M, Jeudy A, Hehemann JH, Czjzek M, Michel G. The β-glucanase ZgLamA from Zobellia galactanivorans evolved a bent active site adapted for efficient degradation of algal laminarin. J Biol Chem. 2014;289:2027–2042.CAS 
    PubMed 
    Article 

    Google Scholar 
    Labourel A, Jam M, Legentil L, Sylla B, Hehemann JH, Ferrières V, et al. Structural and biochemical characterization of the laminarinase ZgLamCGH16 from Zobellia galactanivorans suggests preferred recognition of branched laminarin. Acta Crystallogr. 2015;D71:173–184.
    Google Scholar 
    Dorival J, Ruppert S, Gunnoo M, Orłowski A, Chapelais-Baron M, Dabin J, et al. The laterally-acquired GH5 ZgEngAGH5_4 from the marine bacterium Zobellia galactanivorans is dedicated to hemicellulose hydrolysis. Biochem J. 2018;475:3609–3628.PubMed 
    Article 

    Google Scholar 
    Groisillier A, Labourel A, Michel G, Tonon T. The mannitol utilization system of the marine bacterium Zobellia galactanivorans. Appl Environ Microbiol. 2015;81:1799–1812.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Fournier JB, Rebuffet E, Delage L, Grijol R, Meslet-Cladière L, Rzonca J, et al. The vanadium iodoperoxidase from the marine Flavobacteriaceae species Zobellia galactanivorans reveals novel molecular and evolutionary features of halide specificity in the vanadium haloperoxidase enzyme family. Appl Environ Microbiol. 2014;80:7561–7573.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Grigorian E, Groisillier A, Thomas F, Leblanc C, Delage L. Functional characterization of a L-2-haloacid dehalogenase from Zobellia galactanivorans DsijT suggests a role in haloacetic acid catabolism and a wide distribution in marine environments. Front Microbiol. 2021;12:725997.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Zhu Y, Thomas F, Larocque R, Li N, Duffieux D, Cladière L, et al. Genetic analyses unravel the crucial role of a horizontally acquired alginate lyase for brown algal biomass degradation by Zobellia galactanivorans. Environ Microbiol. 2017;19:2164–2181.CAS 
    PubMed 
    Article 

    Google Scholar 
    Zablackis E, Perez J. A partially pyruvated carrageenan from hawaiian Grateloupia filicina (Cryptonemiales, Rhodophyta). Bot Mar. 1990;33:273–276.CAS 
    Article 

    Google Scholar 
    Filisetti-Cozzi T, Carpita N. Measurement of uronic acids without interference from neutral sugars. Anal Biochem. 1991;197:15162.Article 

    Google Scholar 
    Blumenkrantz N, Asboe-Hansen G. New method for quantitative determination of uronic acids. Anal Biochem. 1973;54:484–489.CAS 
    PubMed 
    Article 

    Google Scholar 
    Cumashi A, Ushakova NA, Preobrazhenskaya ME, D’Incecco A, Piccoli A, Totani L, et al. A comparative study of the anti-inflammatory, anticoagulant, antiangiogenic, and antiadhesive activities of nine different fucoidans from brown seaweeds. Glycobiology. 2007;17:541–552.CAS 
    PubMed 
    Article 

    Google Scholar 
    Jung SY, Oh TK, Yoon JH. Tenacibaculum aestuarii sp. nov., isolated from a tidal flat sediment in Korea. Int J Syst Evol Microbiol. 2006;56:1577–1581.CAS 
    PubMed 
    Article 

    Google Scholar 
    ZoBell C. Studies on marine bacteria. I. The cultural requirements of heterotrophic aerobes. J Mar Res. 1941;4:75.
    Google Scholar 
    Klindworth A, Pruesse E, Schweer T, Peplies J, Quast C, Horn M, et al. Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res. 2013;41:e1.CAS 
    PubMed 
    Article 

    Google Scholar 
    Patro R, Duggal G, Love MI, Irizarry RA, Kingsford C. Salmon provides fast and bias-aware quantification of transcript expression. Nat Methods. 2017;14:417–419.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Vallenet D, Calteau A, Dubois M, Amours P, Bazin A, Beuvin M, et al. MicroScope: An integrated platform for the annotation and exploration of microbial gene functions through genomic, pangenomic and metabolic comparative analysis. Nucleic Acids Res. 2020;48:D579–D589.CAS 
    PubMed 

    Google Scholar 
    Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9:357–359.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25:2078–2079.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Thomas F, Barbeyron T, Michel G. Evaluation of reference genes for real-time quantitative PCR in the marine flavobacterium Zobellia galactanivorans. J Microbiol Methods. 2011;84:61–6.CAS 
    PubMed 
    Article 

    Google Scholar 
    Robinson JT, Thorvaldsdóttir H, Winckler W, Guttman M, Lander ES, Getz G, et al. Integrative genomics viewer. Nat Biotechnol. 2011;29:24–26.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:1–21.Article 
    CAS 

    Google Scholar 
    R Core Team. R: A language and environment for statistical computing. 2018. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.Lex A, Gehlenborg N, Strobelt H. UpSet: Visualization of intersecting sets. IEEE Trans Vis Comput Graph. 2014;20:1983–1992.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Krassowski M. krassowski/complex-upset. 2020. https://doi.org/10.5281/zenodo.3700590.Murtagh F, Legendre P. Ward’s hierarchical clustering method: clustering criterion and agglomerative algorithm. J Classif. 2014;31:274–295.Article 

    Google Scholar 
    Wickham H Use R! ggplot2: Elegant graphics for data analysis. 2nd ed. London: Springer; 2016.Kidby DK, Davidson DJ. Ferricyanide estimation of sugars in the nanomole range. Anal Biochem. 1973;55:321–325.CAS 
    PubMed 
    Article 

    Google Scholar 
    Zhang H, Yohe T, Huang L, Entwistle S, Wu P, Yang Z, et al. DbCAN2: A meta server for automated carbohydrate-active enzyme annotation. Nucleic Acids Res. 2018;46:W95–W101.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Chen X, Hu Y, Yang B, Gong X, Zhang N, Niu L, et al. Structure of lpg0406, a carboxymuconolactone decarboxylase family protein possibly involved in antioxidative response from Legionella pneumophila. Protein Sci. 2015;24:2070–2075.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Enke TN, Datta MS, Schwartzman J, Cermak N, Schmitz D, Barrere J, et al. Modular assembly of polysaccharide-degrading marine microbial communities. Curr Biol. 2019;29:1528–1535.e6.CAS 
    PubMed 
    Article 

    Google Scholar 
    Pollak S, Gralka M, Sato Y, Schwartzman J, Lu L, Cordero OX. Public good exploitation in natural bacterioplankton communities. Sci Adv. 2021;7:eabi4717.Pontrelli S, Szabo R, Pollak S, Schwartzman J, Ledezma D, Cordero OX, et al. Metabolic cross-feeding structures the assembly of polysaccharide degrading communities. Sci Adv. 2022;8:eabk3076.Holdt SL, Kraan S. Bioactive compounds in seaweed: Functional food applications and legislation. J Appl Phycol. 2011;23:543–597.CAS 
    Article 

    Google Scholar 
    Kawamura-Konishi Y, Watanabe N, Saito M, Nakajima N, Sakaki T, Katayama T, et al. Isolation of a new phlorotannin, a potent inhibitor of carbohydrate-hydrolyzing enzymes, from the brown alga Sargassum patens. J Agric Food Chem. 2012;60:5565–5570.CAS 
    PubMed 
    Article 

    Google Scholar 
    Garbary DJ, Brown NE, MacDonell HJ, Toxopeux J. Ascophyllum and its symbionts — A complex symbiotic community on North Atlantic shores. Algal and Cyanobacteria Symbioses. 2017:547–572.Pluvinage B, Grondin JM, Amundsen C, Klassen L, Moote PE, Xiao Y, et al. Molecular basis of an agarose metabolic pathway acquired by a human intestinal symbiont. Nat Commun. 2018;9:1043.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Reintjes G, Arnosti C, Fuchs BM, Amann R. An alternative polysaccharide uptake mechanism of marine bacteria. ISME J. 2017;11:1640–1650.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Hollants J, Leliaert F, de Clerck O, Willems A. What we can learn from sushi: A review on seaweed-bacterial associations. FEMS Microbiol Ecol. 2013;83:1–16.CAS 
    PubMed 
    Article 

    Google Scholar 
    Thomas F, Le Duff N, Wu TD, Cébron A, Uroz S, Riera P, et al. Isotopic tracing reveals single-cell assimilation of a macroalgal polysaccharide by a few marine Flavobacteria and Gammaproteobacteria. ISME J. 2021;15:3062–3075.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Datta MS, Sliwerska E, Gore J, Polz MF, Cordero OX. Microbial interactions lead to rapid micro-scale successions on model marine particles. Nat Commun. 2016;7:11965.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Enke TN, Leventhal GE, Metzger M, Saavedra JT, Cordero OX. Microscale ecology regulates particulate organic matter turnover in model marine microbial communities. Nat Commun. 2018;9:2743.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Sichert A, Cordero OX. Polysaccharide-bacteria Interactions from the lens of evolutionary ecology. Front Microbiol. 2021;12:705082.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Sichert A, Corzett CH, Schechter M, Unfried F, Markert S, Becher D, et al. Verrucomicrobia use hundreds of enzymes to digest the algal polysaccharide fucoidan. Nat Microbiol. 2020;5:1026–1039.CAS 
    PubMed 
    Article 

    Google Scholar 
    Reisky L, Préchoux A, Zühlke MK, Bäumgen M, Robb CS, Gerlach N, et al. A marine bacterial enzymatic cascade degrades the algal polysaccharide ulvan. Nat Chem Biol. 2019;15:803–812.CAS 
    PubMed 
    Article 

    Google Scholar 
    Mabeau S, Kloareg B, Joseleau J-P. Fractionation and analysis of fucans from brown algae. Phytochemistry. 1990;29:2441–2445.CAS 
    Article 

    Google Scholar 
    Küpper FC, Kloareg B, Guern J, Potin P. Oligoguluronates elicit an oxidative burst in the brown algal kelp Laminaria digitata. Plant Physiol. 2001;125:278–291.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Küpper FC, Müller DG, Peters AF, Kloareg B, Potin P. Oligoalginate recognition and oxidative burst play a key role in natural and induced resistance of sporophytes of Laminariales. J Chem Ecol. 2002;28:2057–2081.PubMed 
    Article 

    Google Scholar 
    Leonard S, Hommais F, Nasser W, Reverchon S. Plant–phytopathogen interactions: bacterial responses to environmental and plant stimuli. Environ Microbiol. 2017;19:1689–1716.PubMed 
    Article 

    Google Scholar 
    Sato K, Naito M, Yukitake H, Hirakawa H, Shoji M, McBride MJ, et al. A protein secretion system linked to bacteroidete gliding motility and pathogenesis. PNAS. 2010;107:276–281.CAS 
    PubMed 
    Article 

    Google Scholar 
    Eckroat TJ, Greguske C, Hunnicutt DW. The type 9 secretion system is required for Flavobacterium johnsoniae biofilm formation. Front Microbiol. 2021;12:660887.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Xie S, Tan Y, Song W, Zhang W, Qi Q, Lu X. N-glycosylation of a cargo protein C-terminal domain recognized by the type IX secretion system in Cytophaga hutchinsonii affects protein secretion and localization. Appl Environ Microbiol. 2022;88:e0160621.PubMed 
    Article 

    Google Scholar  More

  • in

    Insect vector manipulation by a plant virus and simulation modeling of its potential impact on crop infection

    Whitfield, A. E., Falk, B. W. & Rotenberg, D. Insect vector-mediated transmission of plant viruses. Virology 479–480, 278–289. https://doi.org/10.1016/j.virol.2015.03.026 (2015).CAS 
    Article 
    PubMed 

    Google Scholar 
    Nault, L. R. Arthropod transmission of plant viruses: A new synthesis. Ann. Entomol. Soc. Am. 90, 521–541. https://doi.org/10.1093/aesa/90.5.521 (1997).Article 

    Google Scholar 
    Maluta, N., Fereres, A. & Lopes, J. R. S. Plant-mediated indirect effects of two viruses with different transmission modes on Bemisia tabaci feeding behavior and fitness. J. Pest Sci. 92, 405–416. https://doi.org/10.1007/s10340-018-1039-0 (2019).Article 

    Google Scholar 
    Scheirs, J. & De Bruyn, L. Integrating optimal foraging and optimal oviposition theory in plant–insect research. Oikos 96, 187–191. https://doi.org/10.1034/j.1600-0706.2002.960121.x (2002).Article 

    Google Scholar 
    Pyke, G. H. Optimal foraging theory: A critical review. Annu. Rev. Ecol. Syst. 15, 523–575. https://doi.org/10.1146/annurev.es.15.110184.002515 (1984).Article 

    Google Scholar 
    Hurd, H. Manipulation of medically important insect vectors by their parasites. Annu. Rev. Entomol. 48, 141–161. https://doi.org/10.1146/annurev.ento.48.091801.112722 (2003).CAS 
    Article 
    PubMed 

    Google Scholar 
    Moore, J. Parasites and the Behavior of Animals (Oxford University Press, 2002).
    Google Scholar 
    Eigenbrode, S. D., Bosque-Pérez, N. A. & Davis, T. S. Insect-borne plant pathogens and their vectors: Ecology, evolution, and complex interactions. Annu. Rev. Entomol. 63, 169–191. https://doi.org/10.1146/annurev-ento-020117-043119 (2018).CAS 
    Article 
    PubMed 

    Google Scholar 
    Mauck, K., Bosque-Pérez, N. A., Eigenbrode, S. D., De Moraes, C. M. & Mescher, M. C. Transmission mechanisms shape pathogen effects on host–vector interactions: Evidence from plant viruses. Funct. Ecol. 26, 1162–1175. https://doi.org/10.1111/j.1365-2435.2012.02026.x (2012).Article 

    Google Scholar 
    Blanc, S. & Michalakis, Y. Manipulation of hosts and vectors by plant viruses and impact of the environment. Curr. Opin. Insect. Sci. 16, 36–43. https://doi.org/10.1016/j.cois.2016.05.007 (2016).Article 
    PubMed 

    Google Scholar 
    Moreno-Delafuente, A., Garzo, E., Moreno, A. & Fereres, A. A plant virus manipulates the behavior of its whitefly vector to enhance its transmission efficiency and spread. PLoS ONE 8, e61543. https://doi.org/10.1371/journal.pone.0061543 (2013).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ng, J. C. K. & Falk, B. W. Virus-vector interactions mediating nonpersistent and semipersistent transmission of plant viruses. Annu. Rev. Phytopathol. 44, 183–212. https://doi.org/10.1146/annurev.phyto.44.070505.143325 (2006).CAS 
    Article 
    PubMed 

    Google Scholar 
    Stafford, C. A., Walker, G. P. & Ullman, D. E. Infection with a plant virus modifies vector feeding behavior. Proc. Natl. Acad. Sci. 108, 9350–9355. https://doi.org/10.1073/pnas.1100773108 (2011).ADS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rajabaskar, D., Bosque-Pérez, N. A. & Eigenbrode, S. D. Preference by a virus vector for infected plants is reversed after virus acquisition. Virus Res. 186, 32–37. https://doi.org/10.1016/j.virusres.2013.11.005 (2014).CAS 
    Article 
    PubMed 

    Google Scholar 
    Su, Q. et al. Manipulation of host quality and defense by a plant virus improves performance of whitefly vectors. J. Econ. Entomol. 108, 11–19. https://doi.org/10.1093/jee/tou012 (2015).Article 
    PubMed 

    Google Scholar 
    Chen, G. et al. Virus infection of a weed increases vector attraction to and vector fitness on the weed. Sci. Rep. 3, 2253. https://doi.org/10.1038/srep02253 (2013).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wei, J. et al. Vector development and vitellogenin determine the transovarial transmission of begomoviruses. Proc. Natl. Acad. Sci. 114, 6746–6751. https://doi.org/10.1073/pnas.1701720114 (2017).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ogada, P. A., Moualeu, D. P. & Poehling, H.-M. Predictive models for tomato spotted wilt virus spread dynamics, considering Frankliniella occidentalis specific life processes as influenced by the virus. PLoS ONE 11, e0154533. https://doi.org/10.1371/journal.pone.0154533 (2016).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Shoemaker, L. G. et al. Pathogens manipulate the preference of vectors, slowing disease spread in a multi-host system. Ecol. Lett. 22, 1115–1125. https://doi.org/10.1111/ele.13268 (2019).Article 
    PubMed 

    Google Scholar 
    Shelton, A. M. & Badenes-Perez, F. R. Concepts and applications of trap cropping in pest management. Annu. Rev. Entomol. 51, 285–308. https://doi.org/10.1146/annurev.ento.51.110104.150959 (2006).CAS 
    Article 
    PubMed 

    Google Scholar 
    Bennett, C. W. The Curly Top Disease of Sugarbeet and Other Plants (The American Phytopathological Society, 1971).Book 

    Google Scholar 
    Chen, L.-F. & Gilbertson, R. L. Chapter 17: Transmission of curtoviruses (beet curly top virus) by the beet leafhopper (Circulifer tenellus). In Vector-Mediated Transmission of Plant Pathogens (ed. Brown, J. K.) 243–262 (The American Phytopathological Society of America, 2016).Chapter 

    Google Scholar 
    Creamer, R. Chapter 37: Beet curly top virus transmission, epidemiology, and management. In Applied Plant Virology (ed. Awasthi, L. P.) 521–527 (Academic Press, 2020).Chapter 

    Google Scholar 
    Gilbertson, R. L., Melgarejo, T. A., Rojas, M. R., Wintermantel, W. M. & Stanley, J. Beet curly top virus (Geminiviridae). In Encyclopedia of Virology 4th edn (eds Bamford, D. H. & Zuckerman, M.) 200–212 (Academic Press, 2021).Chapter 

    Google Scholar 
    Hudson, A., Richman, D. B., Escobar, I. & Creamer, R. Comparison of the feeding behavior and genetics of beet leafhopper, Circulifer tenellus, populations from California and New Mexico. Southwest. Entomol. 35, 241–250, 210 (2010).Article 

    Google Scholar 
    Soto, M. J. & Gilbertson, R. L. Distribution and rate of movement of the curtovirus Beet mild curly top virus (Family Geminiviridae) in the beet leafhopper. Phytopathology 93, 478–484. https://doi.org/10.1094/phyto.2003.93.4.478 (2003).Article 
    PubMed 

    Google Scholar 
    Prager, S. M., Lewis, O. M., Michels, J. & Nansen, C. The influence of maturity and variety of potato plants on oviposition and probing of Bactericera cockerelli (Hemiptera: Triozidae). Environ. Entomol. 43, 402–409. https://doi.org/10.1603/en13278 (2014).Article 
    PubMed 

    Google Scholar 
    Prager, S. M., Vaughn, K., Lewis, M. & Nansen, C. Oviposition and leaf probing by Bactericera cockerelli (Homoptera: Psyllidae) in response to a limestone particle film or a plant growth regulator applied to potato plants. Crop Prot. 45, 57–62 (2013).CAS 
    Article 

    Google Scholar 
    McBryde, M. C. A method of demonstrating rust hyphae and Haustoria in unsectioned leaf tissue. Am. J. Bot. 23, 686–688 (1936).Article 

    Google Scholar 
    Backus, E. A., Hunter, W. B. & Arne, C. N. Technique for staining leafhopper (Homoptera: Cicadellidae) salivary sheaths and eggs within unsectioned plant tissue. J. Econ. Entomol. 81, 1819–1823. https://doi.org/10.1093/jee/81.6.1819 (1988).Article 

    Google Scholar 
    R Core Team. R: A language and environment for statistical computing (R Foundation for Statistical computing, Vienna, Austria, 2019).Stafford, C. A., Walker, G. P. & Creamer, R. Stylet penetration behavior resulting in inoculation of beet severe curly top virus by beet leafhopper, Circulifer tenellus. Entomol. Exp. Appl. 130, 130–137. https://doi.org/10.1111/j.1570-7458.2008.00813.x (2009).Article 

    Google Scholar 
    Chen, L.-F., Brannigan, K., Clark, R. & Gilbertson, R. L. Characterization of curtoviruses associated with curly top disease of tomato in California and monitoring for these viruses in beet leafhoppers. Plant Dis. 94, 99–108. https://doi.org/10.1094/pdis-94-1-0099 (2010).CAS 
    Article 
    PubMed 

    Google Scholar 
    Rojas, M. R. et al. World management of geminiviruses. Annu. Rev. Phytopathol. 56, 637–677. https://doi.org/10.1146/annurev-phyto-080615-100327 (2018).CAS 
    Article 
    PubMed 

    Google Scholar 
    Schoonhoven, L. M., Van Loon, B., van Loon, J. J. & Dicke, M. Insect-plant biology (Oxford University Press, 2005).
    Google Scholar 
    Mauck, K. E., Kenney, J. & Chesnais, Q. Progress and challenges in identifying molecular mechanisms underlying host and vector manipulation by plant viruses. Curr. Opin. Insect. Sci. 33, 7–18. https://doi.org/10.1016/j.cois.2019.01.001 (2019).Article 
    PubMed 

    Google Scholar 
    Pelosi, P., Iovinella, I., Felicioli, A. & Dani, F. R. Soluble proteins of chemical communication: An overview across arthropods. Front. Physiol 5, 320. https://doi.org/10.3389/fphys.2014.00320 (2014).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pelosi, P., Zhou, J. J., Ban, L. P. & Calvello, M. Soluble proteins in insect chemical communication. Cell. Mol. Life Sci. 63, 1658–1676. https://doi.org/10.1007/s00018-005-5607-0 (2006).CAS 
    Article 
    PubMed 

    Google Scholar 
    Matsuo, T., Sugaya, S., Yasukawa, J., Aigaki, T. & Fuyama, Y. Odorant-binding proteins OBP57d and OBP57e affect taste perception and host-plant preference in Drosophila sechellia. PLoS Biol. 5, e118. https://doi.org/10.1371/journal.pbio.0050118 (2007).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Li, Z. et al. Mouthparts enriched odorant binding protein AfasOBP11 plays a role in the gustatory perception of Adelphocoris fasciaticollis. J. Insect Physiol. 117, 103915. https://doi.org/10.1016/j.jinsphys.2019.103915 (2019).CAS 
    Article 
    PubMed 

    Google Scholar 
    Waris, M. I. et al. Silencing of chemosensory protein gene NlugCSP8 by RNAi induces declining behavioral responses of Nilaparvata lugens. Front. Physiol. 9, 379. https://doi.org/10.3389/fphys.2018.00379 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hu, K. et al. Odorant-binding protein 2 is involved in the preference of Sogatella furcifera (Hemiptera: Delphacidae) for rice plants infected with the Southern rice black-streaked dwarf virus. Fla. Entomol. 102, 353–358. https://doi.org/10.1653/024.102.0210 (2019).CAS 
    Article 

    Google Scholar 
    Brentassi, M. E., Machado-Assefh, C. R. & Alvarez, A. E. The probing behaviour of the planthopper Delphacodes kuscheli (Hemiptera: Delphacidae) on two alternating hosts, maize and oat. Aust. Entomol. 58, 666–674. https://doi.org/10.1111/aen.12383 (2019).Article 

    Google Scholar 
    Milenovic, M., Wosula, E. N., Rapisarda, C. & Legg, J. P. Impact of host plant species and whitefly species on feeding behavior of Bemisia tabaci. Front. Plant Sci. 10, 1. https://doi.org/10.3389/fpls.2019.00001 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Stafford, C. A. & Walker, G. P. Characterization and correlation of DC electrical penetration graph waveforms with feeding behavior of beet leafhopper, Circulifer tenellus. Entomol. Exp. Appl. 130, 113–129. https://doi.org/10.1111/j.1570-7458.2008.00812.x (2009).Article 

    Google Scholar 
    Mauck, K. E., Chesnais, Q. & Shapiro, L. R. Evolutionary determinants of host and vector manipulation by plant viruses. In Advances in Virus Research (ed. Malmstrom, C. M.) 189–250 (Academic Press, 2018).
    Google Scholar 
    Chesnais, Q. et al. Virus effects on plant quality and vector behavior are species specific and do not depend on host physiological phenotype. J. Pest Sci. 92, 791–804 (2019).Article 

    Google Scholar  More

  • in

    Plant beta-diversity across biomes captured by imaging spectroscopy

    Díaz, S. et al. Summary for policymakers of the global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. https://doi.org/10.5281/zenodo.3553579 (2019).Fei, S. et al. Divergence of species responses to climate change. Sci. Adv. 3, e1603055 (2017).ADS 
    Article 

    Google Scholar 
    Jetz, W. et al. Monitoring plant functional diversity from space. Nat. Plants 2, 16024 (2016).Article 

    Google Scholar 
    HyspIRI Mission Concept Team. HyspIRI Final Report. https://hyspiri.jpl.nasa.gov/downloads/reports_whitepapers/HyspIRI_FINAL_Report_1October2018_20181005a.pdf. Jet Propulsion Laboratories, California Institute of Technology, Pasadena, CA, USA (2018).Turner, W. Sensing biodiversity. Science 346, 301–302 (2014).ADS 
    CAS 
    Article 

    Google Scholar 
    Ustin, S. L. & Middleton, E. M. Current and near-term advances in Earth observation for ecological applications. Ecol. Process. 10, 1 (2021).Article 

    Google Scholar 
    Cawse-Nicholson, K. et al. NASA’s surface biology and geology designated observable: a perspective on surface imaging algorithms. Remote Sens. Environ. 257, 112349 (2021).ADS 
    Article 

    Google Scholar 
    Stavros, E. N. et al. ISS Observations Offer Insights Into Plant Function. Nature Ecology and Evolution 1, https://doi.org/10.1038/s41559-017-0194 (2017).Rast, M., Nieke, J., Adams, J., Isola, C. & Gascon, F. Copernicus Hyperspectral Imaging Mission for the Environment (Chime). IEEE International Geoscience and Remote Sensing Symposium IGARSS, 108–111, https://doi.org/10.1109/IGARSS47720.2021.9553319 (2021).Cogliati, S. et al. The PRISMA imaging spectroscopy mission: overview and first performance analysis. Remote Sens. Environ. 262, 112499 (2021).ADS 
    Article 

    Google Scholar 
    Asner, G. P. et al. Airborne laser-guided imaging spectroscopy to map forest trait diversity and guide conservation. Science 355, 385–389 (2017).ADS 
    CAS 
    Article 

    Google Scholar 
    Meireles, J. E. et al. Leaf reflectance spectra capture the evolutionary history of seed plants. N. Phytologist 228, 485–493 (2020).Article 

    Google Scholar 
    Schweiger, A. K. et al. Plant spectral diversity integrates functional and phylogenetic components of biodiversity and predicts ecosystem function. Nat. Ecol. Evolution https://doi.org/10.1038/s41559-018-0551-1 (2018).Article 

    Google Scholar 
    Cavender-Bares, J. et al. Harnessing plant spectra to integrate the biodiversity sciences across biological and spatial scales. Am. J. Bot. 104, 966–969 (2017).Article 

    Google Scholar 
    Laliberté, E., Schweiger, A. K. & Legendre, P. Partitioning plant spectral diversity into alpha and beta components. Ecol. Lett. 23, 370–380 (2020).Article 

    Google Scholar 
    Rocchini, D. et al. Remotely sensed spectral heterogeneity as a proxy of species diversity: recent advances and open challenges. Ecol. Inform. 5, 318–329 (2010).Article 

    Google Scholar 
    Gholizadeh, H. et al. Detecting prairie biodiversity with airborne remote sensing. Remote Sens. Environ. 221, 38–49 (2019).ADS 
    Article 

    Google Scholar 
    Wang, R. et al. Influence of species richness, evenness, and composition on optical diversity: a simulation study. Remote Sens. Environ. 211, 218–228 (2018).ADS 
    Article 

    Google Scholar 
    Féret, J.-B. & Asner, G. P. Mapping tropical forest canopy diversity using high‐fidelity imaging spectroscopy. Ecol. Appl. 24, 1289–1296 (2014).Article 

    Google Scholar 
    Draper, F. C. et al. Imaging spectroscopy predicts variable distance decay across contrasting Amazonian tree communities. J. Ecol. 107, 696–710 (2019).Article 

    Google Scholar 
    Wang, R., Gamon, J. A., Cavender‐Bares, J., Townsend, P. A. & Zygielbaum, A. I. The spatial sensitivity of the spectral diversity–biodiversity relationship: an experimental test in a prairie grassland. Ecol. Appl. 28, 541–556 (2018).Article 

    Google Scholar 
    Rossi, C. et al. Spatial resolution, spectral metrics and biomass are key aspects in estimating plant species richness from spectral diversity in species-rich grasslands. Remote Sens. Ecol. Conserv. https://doi.org/10.1002/rse2.244 (2021).Article 

    Google Scholar 
    Finderup Nielsen, T., Sand-Jensen, K., Dornelas, M. & Bruun, H. H. More is less: net gain in species richness, but biotic homogenization over 140 years. Ecol. Lett. 22, 1650–1657 (2019).Article 

    Google Scholar 
    McKinney, M. L. & Lockwood, J. L. Biotic homogenization: a few winners replacing many losers in the next mass extinction. Trends Ecol. Evolution 14, 450–453 (1999).CAS 
    Article 

    Google Scholar 
    Anderson, M. J. et al. Navigating the multiple meanings of β diversity: a roadmap for the practicing ecologist. Ecol. Lett. 14, 19–28 (2011).ADS 
    Article 

    Google Scholar 
    Rocchini, D. et al. Measuring β‐diversity by remote sensing: a challenge for biodiversity monitoring. Methods Ecol. Evolution 9, 1787–1798 (2018).Article 

    Google Scholar 
    Chadwick, K. D. & Asner, G. P. Landscape evolution and nutrient rejuvenation reflected in Amazon forest canopy chemistry. Ecol. Lett. 21, 978–988 (2018).Article 

    Google Scholar 
    Felsenstein, J. Phylogenies and the comparative method. American Naturalist, 1-15, https://doi.org/10.1086/284325 (1985).Wang, R. & Gamon, J. A. Remote sensing of terrestrial plant biodiversity. Remote Sens. Environ. 231, 111218 (2019).ADS 
    Article 

    Google Scholar 
    Schimel, D. S., Asner, G. P. & Moorcroft, P. Observing changing ecological diversity in the Anthropocene. Front. Ecol. Environ. 11, 129–137 (2013).Article 

    Google Scholar 
    NEON (National Ecological Observatory Network). Spectrometer orthorectified surface directional reflectance—mosaic, RELEASE-2021 (DP3.30006.001). https://doi.org/10.48443/qeae-3×15. Dataset accessed from https://data.neonscience.org on March (2021).Richter, R. & Schläpfer, D. Geo-atmospheric processing of airborne imaging spectrometry data. Part 2: Atmospheric/topographic correction. Int. J. Remote Sens. 23, 2631–2649 (2002).Article 

    Google Scholar 
    Asner, G. P. & Martin, R. E. Airborne spectranomics: mapping canopy chemical and taxonomic diversity in tropical forests. Front. Ecol. Environ. 7, 269–276 (2009).Article 

    Google Scholar 
    Rüfenacht, D., Fredembach, C. & Süsstrunk, S. Automatic and accurate shadow detection using near-infrared information. IEEE Trans. pattern Anal. Mach. Intell. 36, 1672–1678 (2013).Article 

    Google Scholar 
    NEON (National Ecological Observatory Network). High-resolution orthorectified camera imagery mosaic, RELEASE-2021 (DP3.30010.001). https://doi.org/10.48443/4e85-cr14. Dataset accessed from https://data.neonscience.org on March 3 (2021).Feilhauer, H., Asner, G. P., Martin, R. E. & Schmidtlein, S. Brightness-normalized partial least squares regression for hyperspectral data. J. Quant. Spectrosc. Radiat. Transf. 111, 1947–1957 (2010).ADS 
    CAS 
    Article 

    Google Scholar 
    NEON (National Ecological Observatory Network). Plant presence and percent cover, RELEASE-2021 (DP1.10058.001). https://doi.org/10.48443/abge-r811. Dataset accessed from https://data.neonscience.org on March 3 (2021).NEON (National Ecological Observatory Network). Woody plant vegetation structure, RELEASE-2021 (DP1.10098.001). https://doi.org/10.48443/e3qn-xw47. Dataset accessed from https://data.neonscience.org on March 3 (2021).Schweiger, A. K. NEON_crown_area (1.0.0). https://doi.org/10.5281/zenodo.6383923 (2022).R Foundation for Statistical Computing. R: A language and environment for statistical computing (R Foundation for Statistical Computing, 2019).Oksanen, J. et al. vegan: Community Ecology Package. R package version 2.5-7 (2020).Jin, Y. & Qian, H. V. PhyloMaker: an R package that can generate very large phylogenies for vascular plants. Ecography 42, 1353–1359 (2019).Article 

    Google Scholar 
    Smith, S. A. & Brown, J. W. Constructing a broadly inclusive seed plant phylogeny. Am. J. Bot. 105, 302–314 (2018).Article 

    Google Scholar 
    Kembel, S. W. et al. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26, 1463–1464 (2010).CAS 
    Article 

    Google Scholar 
    NEON (National Ecological Observatory Network). Plant foliar traits, RELEASE-2021 (DP1.10026.001). https://doi.org/10.48443/za0d-wn97. Dataset accessed from https://data.neonscience.org on March 3 (2021).Legendre, P. & De Cáceres, M. Beta diversity as the variance of community data: dissimilarity coefficients and partitioning. Ecol. Lett. 16, 951–963 (2013).Article 

    Google Scholar 
    Dray, S. & Dufour, A.-B. The ade4 package: implementing the duality diagram for ecologists. J. Stat. Softw. 22, 1–20 (2007).Article 

    Google Scholar 
    Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D. & Team, R. C. nlme: Linear and nonlinear mixed effects models. R package version 3.1-152 (2021).NEON (National Ecological Observatory Network). LAI—spectrometer—mosaic, RELEASE-2021 (DP3.30012.001). https://doi.org/10.48443/h2rb-pj34. Dataset accessed from https://data.neonscience.org on March 3 (2021). More

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    Behavioural and electrophysiological responses of Philaenus spumarius to odours from conspecifics

    Saponari, M., Boscia, D., Nigro, F. & Martelli, G. P. Identification of DNA sequences related to Xylella fastidiosa in oleander, almond and olive trees exhibiting leaf scorch symptoms in Apulia (Southern Italy). J. Plant Pathol. 95, 668 (2013).
    Google Scholar 
    Janse, J. D. & Obradovic, A. Xylella fastidiosa: Its biology, diagnosis, control and risks. J. Plant Pathol. 92, 35–48 (2010).
    Google Scholar 
    EPPO EPPO Global Database (available online). https://gd.eppo.int (2022)Article 

    Google Scholar 
    Bragard, C. et al. Update of the scientific opinion on the risks to plant health posed by Xylella fastidiosa in the EU territory. EFSA J. 17, 5665 (2019).
    Google Scholar 
    Nunney, L., Ortiz, B., Russell, S. A., Sánchez, R. R. & Stouthamer, R. The complex biogeography of the plant pathogen Xylella fastidiosa: Genetic evidence of introductions and subspecific introgression in central America. PLoS ONE 9, e112463 (2014).PubMed 
    PubMed Central 
    Article 
    ADS 
    CAS 

    Google Scholar 
    Sicard, A. et al. Introduction and adaptation of an emerging pathogen to olive trees in Italy. Microb. Genom. 7, 000735 (2021).CAS 
    PubMed Central 

    Google Scholar 
    Cornara, D. et al. Transmission of Xylella fastidiosa by naturally infected Philaenus spumarius (Hemiptera, Aphrophoridae) to different host plants. J. Appl. Entomol. 141, 80–87 (2017).Article 

    Google Scholar 
    Cornara, D. et al. Spittlebugs as vectors of Xylella fastidiosa in olive orchards in Italy. J. Pest Sci. 2004, 521–530 (2017).Article 

    Google Scholar 
    Bodino, N. et al. Phenology, seasonal abundance and stage-structure of spittlebug (Hemiptera: Aphrophoridae) populations in olive groves in Italy. Sci. Rep. 9, 17725 (2019).PubMed 
    PubMed Central 
    Article 
    ADS 
    CAS 

    Google Scholar 
    Di Serio, F. et al. Collection of data and information on biology and control of vectors of Xylella fastidiosa. EFSA Support. Publ. 16, 2 (2019).
    Google Scholar 
    Bayram, A., Salerno, G., Onofri, A. & Conti, E. Lethal and sublethal effects of preimaginal treatments with two pyrethroids on the life history of the egg parasitoid Telenomus busseolae. Biocontrol 55, 697–710 (2010).CAS 
    Article 

    Google Scholar 
    Saponari, M., Giampetruzzi, A., Loconsole, G., Boscia, D. & Saldarelli, P. Xylella fastidiosa in olive in Apulia: Where we stand. Phytopathology 109, 175–186 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Virant-Doberlet, M. & Cokl, A. Vibrational communication in insects. Neotrop. Entomol. 33, 121–134 (2004).Article 

    Google Scholar 
    Avosani, S. et al. Vibrational communication and mating behavior of the meadow spittlebug Philaenus spumarius. Entomol. Gen. 40, 307–321 (2020).Article 

    Google Scholar 
    Polajnar, J., Eriksson, A., Virant-Doberlet, M. & Mazzoni, V. Mating disruption of a grapevine pest using mechanical vibrations: From laboratory to the field. J. Pest Sci. 2004(89), 909–921 (2016).Article 

    Google Scholar 
    Boullis, A. & Verheggen, F. J. Chemical ecology of aphids (Hemiptera: Aphididae). In Biology and Ecology of Aphids (ed. Vilcinskas, A.) 181–208 (CRC Press, 2016). https://doi.org/10.1201/b19967-11.Chapter 

    Google Scholar 
    Ganassi, S. et al. Evidence of a female-produced sex pheromone in the European pear psylla Cacopsylla pyri. Bull. Insectol. 71, 57–64 (2018).
    Google Scholar 
    Tabata, J. & Ichiki, R. T. Sex pheromone of the cotton mealybug, Phenacoccus solenopsis, with an unusual cyclobutane structure. J. Chem. Ecol. 42, 1193–1200 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Millar, J. G. Pheromones of true bugs. Top. Curr. Chem. 240, 37–84 (2000).Article 
    CAS 

    Google Scholar 
    Khrimian, A. et al. Discovery of the aggregation pheromone of the brown marmorated stink bug (Halyomorpha halys) through the creation of stereoisomeric libraries of 1-Bisabolen-3-ols. J. Nat. Prod. 77, 1708–1717 (2014).CAS 
    PubMed 
    Article 

    Google Scholar 
    Borges, M., Blassioli-Moraes, M. C., Laumann, R. A. & Čokl, A. Suggestions for neotropic stink bug pest status and control. In Stink Bugs: Biorational Control Based on Communication Processes (eds Cokl, A. & Borges, M.) 246–254 (CRC Press, 2017). https://doi.org/10.1201/9781315120713.Chapter 

    Google Scholar 
    Ranieri, E., Ruschioni, S., Riolo, P., Isidoro, N. & Romani, R. Fine structure of antennal sensilla of the spittlebug Philaenus spumarius L. (Insecta: Hemiptera: Aphrophoridae). I. Chemoreceptors and thermo-/hygroreceptors. Arthropod Struct. Dev. 45, 432–439 (2016).PubMed 
    Article 

    Google Scholar 
    Germinara, G. S. et al. Antennal olfactory responses of adult meadow spittlebug, Philaenus spumarius, to volatile organic compounds (VOCs). PLoS ONE 12, e0190454 (2017).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Ganassi, S. et al. Electrophysiological and behavioural response of Philaenus spumarius to essential oils and aromatic plants. Sci. Rep. 10, 3114 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    Nault, L. R., Wood, T. K. & Goff, A. M. Treehopper (Membracidae) alarm pheromones. Nature 249, 387–388 (1974).CAS 
    PubMed 
    Article 
    ADS 

    Google Scholar 
    Chen, X. & Liang, A. P. Identification of a self-regulatory pheromone system that controls nymph aggregation behavior of rice spittlebug Callitettix versicolor. Front. Zool. 12, 10 (2015).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Liang, A. P. A new structure on the frons of male adults of the Asian rice spittlebug Callitettix versicolor (Hemiptera: Auchenorrhyncha: Cercopidae). Zootaxa 4801, 591–599 (2020).Article 

    Google Scholar 
    Cocroft, R. B. & Rodríguez, R. L. The behavioral ecology of insect vibrational communication. Bioscience 55, 323–334 (2005).Article 

    Google Scholar 
    Mazzoni, V. et al. Mating disruption by vibrational signals: state of the field and perspectives. In Biotremology: Studying Vibrational Behavior (eds Hill, P. S. M. et al.) 331–354 (Springer, Cham, 2019). https://doi.org/10.1007/978-3-030-22293-2_17.Chapter 

    Google Scholar 
    Bachmann, G. E. et al. Male sexual behavior and pheromone emission is enhanced by exposure to guava fruit volatiles in Anastrepha fraterculus. PLoS ONE 10, e0124250 (2015).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Frati, F., Salerno, G., Conti, E. & Bin, F. Role of the plant–conspecific complex in host location and intra-specific communication of Lygus rugulipennis. Physiol. Entomol. 33, 129–137 (2008).Article 

    Google Scholar 
    Frati, F. et al. Vicia faba–Lygus rugulipennis interactions: Induced plant volatiles and sex pheromone enhancement. J. Chem. Ecol. 35, 201–208 (2009).CAS 
    PubMed 
    Article 

    Google Scholar 
    Lubanga, U. K., Guédot, C., Percy, D. M. & Steinbauer, M. J. Semiochemical and vibrational cues and signals mediating mate finding and courtship in Psylloidea (Hemiptera): A synthesis. Insects 5, 577–595 (2014).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Borges, M. & Blassioli-Moraes, M. C. The semiochemistry of Pentatomidae. In Stink Bugs: Biorational Control Based on Communication Processes 95–124 (CRC Press, 2017). https://doi.org/10.1201/9781315120713.Chapter 

    Google Scholar 
    Yin, L. & Maschwitz, U. Sexual pheromone in the green house whitefly Trialeurodes vaporariorum Westw. Zeitschrift für Angew. Entomol. 95, 439–446 (1983).Article 

    Google Scholar 
    Dawson, G. W. et al. Identification of an aphid sex pheromone. Nature 325, 614–616 (1987).CAS 
    Article 
    ADS 

    Google Scholar 
    Zanardi, O. Z. et al. Putative sex pheromone of the Asian citrus psyllid, Diaphorina citri, breaks down into an attractant. Sci. Rep. 8, 455 (2018).PubMed 
    PubMed Central 
    Article 
    ADS 
    CAS 

    Google Scholar 
    Sevarika, M., di Giulio, A., Rondoni, G., Conti, E. & Romani, R. Morpho-functional analysis of the head glands in three Auchenorrhynca species and their possible biological significance. bioRxiv 03.03.482260 (2022).Mazzoni, V. et al. Use of substrate-borne vibrational signals to attract the brown marmorated stink bug Halyomorpha halys. J. Pest Sci. 2004, 1219–1229 (2017).Article 

    Google Scholar 
    Avosani, S., Franceschi, P., Ciolli, M., Verrastro, V. & Mazzoni, V. Vibrational playbacks and microscopy to study the signalling behaviour and female physiology of Philaenus spumarius. J. Appl. Entomol. https://doi.org/10.1111/jen.12874 (2021).Article 

    Google Scholar 
    Stewart, A. J. A. & Lees, D. R. Genetic control of colour polymorphism in spittlebugs (Philaenus spumarius) differs between isolated populations. Heredity (Edinb). 59, 445–448 (1987).Article 

    Google Scholar 
    Stewart, A. J. A. The colour/pattern polymorphism of Philaenus spumarius (L.) (Homoptera: Cercopidae) in England and Wales. Philos. Trans. R. Soc. B Biol. Sci. 351, 69–89 (1996).Article 
    ADS 

    Google Scholar 
    Moyal, P. et al. Origin and taxonomic status of the Palearctic population of the stem borer Sesamia nonagrioides (Lefèbvre) (Lepidoptera: Noctuidae). Biol. J. Linn. Soc. 103, 904–922 (2011).Article 

    Google Scholar 
    Glaser, N. et al. Differential expression of the chemosensory transcriptome in two populations of the stemborer Sesamia nonagrioides. Insect Biochem. Mol. Biol. 65, 28–34 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    Bodino, N. et al. Spittlebugs of mediterranean olive groves: host-plant exploitation throughout the year. Insects 11, 130 (2020).PubMed Central 
    Article 

    Google Scholar 
    Cook, S. M., Khan, Z. R. & Pickett, J. A. The use of push-pull strategies in integrated pest management. Annu. Rev. Entomol. 52, 375–400 (2007).CAS 
    PubMed 
    Article 

    Google Scholar 
    Molinatto, G. et al. Biology and prevalence in Northern Italy of Verrallia aucta (Diptera, Pipunculidae), a parasitoid of Philaenus spumarius (Hemiptera, Aphrophoridae), the main vector of Xylella fastidiosa in Europe. Insects 11, 607 (2020).PubMed Central 
    Article 

    Google Scholar 
    Mesmin, X. et al. Ooctonus vulgatus (Hymenoptera, Mymaridae), a potential biocontrol agent to reduce populations of Philaenus spumarius (Hemiptera, Aphrophoridae) the main vector of Xylella fastidiosa in Europe. PeerJ 2020, e8591 (2020).Article 

    Google Scholar 
    Conti, E., Jones, W. A., Bin, F. & Vinson, S. B. Physical and chemical factors involved in host recognition behavior of Anaphes iole Girault, an egg parasitoid of Lygus hesperus knight (Hymenoptera: Mymaridae; Heteroptera: Miridae). Biol. Control 7, 10–16 (1996).Article 

    Google Scholar 
    Conti, E., Jones, W. A., Bin, F. & Vinson, S. B. Oviposition behavior of Anaphes iole, an egg parasitoid of Lygus hesperus (Hymenoptera: Mymaridae; Heteroptera: Miridae). Ann. Entomol. Soc. Am. 90, 91–101 (1997).Article 

    Google Scholar 
    Chiappini, E. et al. Role of volatile semiochemicals in host location by the egg parasitoid Anagrus breviphragma. Entomol. Exp. Appl. 144, 311–316 (2012).CAS 
    Article 

    Google Scholar 
    Conti, E. et al. Biological control of invasive stink bugs: review of global state and future prospects. Entomol. Exp. Appl. 169, 28–51 (2021).Article 

    Google Scholar 
    Rondoni, G. et al. Native egg parasitoids recorded from the invasive Halyomorpha halys successfully exploit volatiles emitted by the plant–herbivore complex. J. Pest Sci. 2004, 1087–1095 (2017).Article 

    Google Scholar 
    Rondoni, G., Ielo, F., Ricci, C. & Conti, E. Behavioural and physiological responses to prey-related cues reflect higher competitiveness of invasive vs native ladybirds. Sci. Rep. 7, 3716 (2017).PubMed 
    PubMed Central 
    Article 
    ADS 
    CAS 

    Google Scholar 
    Colazza, S. et al. Xbug, a video tracking and motion analysis system for LINUX. in XII International Entomophagous Insects Workshop. Pacific Grove, California (1999).De Cristofaro, A. et al. Electrophysiological responses of Cydia pomonella to codlemone and pear ester ethyl (E, Z)-2,4-decadienoate: Peripheral interactions in their perception and evidences for cells responding to both compounds. Bull. Insectol. 57, 137–144 (2004).
    Google Scholar 
    Raguso, R. A. & Light, D. M. Electroantennogram responses of male Sphinx perelegans hawkmoths to floral and ‘green-leaf volatiles’. Entomol. Exp. Appl. 86, 287–293 (1998).CAS 
    Article 

    Google Scholar 
    Pinheiro, J. C. & Bates, D. M. Mixed-Effects Models in S and S-PLUS (Springer, 2000). https://doi.org/10.1007/b98882.Book 
    MATH 

    Google Scholar 
    Rondoni, G., Onofri, A. & Ricci, C. Differential susceptibility in a specialised aphidophagous ladybird, Platynaspis luteorubra (Coleoptera: Coccinellidae), facing intraguild predation by exotic and native generalist predators. Biocontrol Sci. Technol. 22, 1334–1350 (2012).Article 

    Google Scholar 
    Zuur, A. F., Ieno, E. N., Walker, N. J., Saveliev, A. A. & Smith, G. M. Mixed Effects Models and Extensions in Ecology with R (Springer Verlag, 2009). https://doi.org/10.18637/jss.v032.b01.Book 
    MATH 

    Google Scholar 
    Bertoldi, V., Rondoni, G., Brodeur, J. & Conti, E. An egg parasitoid efficiently exploits cues from a coevolved host but not those from a novel host. Front. Physiol. 10, 746 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Suh, E., Choe, D.-H., Saveer, A. M. & Zwiebel, L. J. Suboptimal larval habitats modulate oviposition of the malaria vector mosquito Anopheles coluzzii. PLoS ONE 11, e0149800 (2016).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org (2020).Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D., R Core Team. nlme: Linear and Nonlinear Mixed Effects Models (2020). R package version 3.1–148, https://CRAN.R-project.org/package=nlme.Venables, W. N. & Ripley, B. D. Modern Applied Statistics with S 4th edn. (Springer, 2002). https://doi.org/10.1007/978-0-387-21706-2.Book 
    MATH 

    Google Scholar 
    Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag, 2016).MATH 
    Book 

    Google Scholar 
    Lenth, R. emmeans: Estimated Marginal Means, aka Least-Squares Means (2019). R package version 1.3.2. Available online at: https://CRAN.R-project.org/package=emmeans. More