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    10 years of Nature Climate Change

    Which individuals will survive?Observing and recording the devastating impacts of climate change on natural lifeforms has long been a keystone of the climate change ecology field. As a result of years of quality research, we now understand that climate change can reduce species numbers and fitness, cause local extinctions and generally alter where, when, how and with whom organisms live.From the point of view of biodiversity conservation, things look pretty bad. And modelling predictions suggest that they are likely to remain bad or worsen in the near future, even if we do manage to rapidly rein in our global emissions.For this reason — although there is still much more to understand about how the various aspects of climate change can impact different organisms and ecosystems — some of the most vital questions arising now relate to if, and how, natural species can persist.Biological persistence in a changing world relies on an ability to fit or adapt to new conditions, and/or an ability to move to ‘greener pastures’. I was pleased to see work from Andrew Gougherty and colleagues address both climate-change-induced maladaptation and the potential for migration to minimize this maladaptation, in work that focused on a wide-ranging North American tree species, balsam poplar (Populus balsamifera)9.Importantly, the authors did not assess the adaptive capacity of the species as a whole, but instead investigated vulnerability in the context of 81 balsam polar populations spanning North America, thus incorporating intraspecific (within species) variation that may play an important role in persistence potential. In the study, maladaptation was defined based on gene–environment associations, in this case centred on flowering-time genes, which are crucial in regulating plant seasonal growth, dormancy and reproduction. Understanding the genetic variations that underlie fitness under given environmental conditions may help understand and rapidly identify individuals with the best chances of survival under climate change.The Gougherty study uses modern methods to go beyond species-level modelling and, to understand population risks in the context of maladaptation and migration, under climate change. This, in turn, can be utilized to prioritize conservation efforts. Ultimately, we hope that climate change science cannot just observe and understand the human-caused alterations to our planet, but lead us to prevent, manage and save.Tegan Armarego-Marriott has been an editor at Nature Climate Change since 2019. More

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    High insecticide resistance mediated by different mechanisms in Culex quinquefasciatus populations from the city of Yaoundé, Cameroon

    1.Kauffman, E. B. & Kramer, L. D. Zika virus mosquito vectors: competence, biology, and vector control. J. Infect. Dis. 216, S976–S990 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    2.Antonio-Nkondjio, C. et al. High mosquito burden and malaria transmission in a district of the city of Douala Cameroon. BMC Infect. Dis. 12, 275 (2012).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    3.Turell, M. J. et al. Vector competence of selected African mosquito (Diptera: Culicidae) Species for Rift Valley fever virus. J. Med. Entomol. 45, 102–108 (2008).PubMed 
    Article 

    Google Scholar 
    4.Mbida, A. M. et al. Preliminary investigation on aggressive culicidae fauna and malaria transmission in two wetlands of the Wouri river estuary Littoral-Cameroon. J. Entomol. Zool. Stud. 4, 105–110 (2016).
    Google Scholar 
    5.Farajollahi, A., Fonseca, D. M., Kramer, L. D. & Kilpatrick, A. M. “Bird biting” mosquitoes and human disease: a review of the role of Culex pipiens complex mosquitoes in epidemiology. Infect. Genet. Evol. 11, 1577–1585 (2011).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    6.Weissenböck, H., Hubálek, Z., Bakonyi, T. & Nowotny, N. Zoonotic mosquito-borne flaviviruses: worldwide presence of agents with proven pathogenicity and potential candidates of future emerging diseases. Vet. Microbiol. 140, 271–280 (2010).PubMed 
    Article 

    Google Scholar 
    7.Antonio-Nkondjio, C., Sandjo, N. N., Awono-Ambene, P. & Wondji, C. S. Implementing a larviciding efficacy or effectiveness control intervention against malaria vectors: key parameters for success. Parasit. Vectors 11, 57 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    8.Nchoutpouen, E. et al. Culex species diversity, susceptibility to insecticides and role as potential vector of Lymphatic filariasis in the city of Yaoundé Cameroon. PLoS Negl. Trop. Dis. 13, e0007229 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    9.Mourou, J.-R. et al. Malaria transmission in Libreville: results of a one year survey. Malar. J. 11, 40 (2012).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    10.Talipouo, A. et al. Comparative study of Culicidae biodiversity of Manoka island and Youpwe mainland area, Littoral Cameroon. Int. J. Biosci. 10, 9–18 (2017).Article 

    Google Scholar 
    11.PNLP. Plan Stratégique National 2019–2023. (2019).12.Antonio-Nkondjio, C. et al. Review of the evolution of insecticide resistance in main malaria vectors in Cameroon from 1990 to 2017. Parasit. Vectors 10, 472 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    13.Bamou, R. et al. Status of insecticide resistance and its mechanisms in Anopheles gambiae and Anopheles coluzzii populations from forest settings in south Cameroon. Genes 10, 741 (2019).CAS 
    PubMed Central 
    Article 
    PubMed 

    Google Scholar 
    14.Chouaïbou, M. et al. Dynamics of insecticide resistance in the malaria vector Anopheles gambiae sl from an area of extensive cotton cultivation in Northern Cameroon. Trop. Med. Int. Health 13, 476–486 (2008).PubMed 
    Article 

    Google Scholar 
    15.Nwane, P. et al. Trends in DDT and pyrethroid resistance in Anopheles gambiaes. s. populations from urban and agro-industrial settings in southern Cameroon. BMC Infect. Dis. 9, 163 (2009).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    16.Antonio-Nkondjio, C. et al. Rapid evolution of pyrethroid resistance prevalence in Anopheles gambiae populations from the cities of Douala and Yaoundé (Cameroon). Malar. J. 14, 155 (2015).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    17.Fossog, B. T. et al. Physiological correlates of ecological divergence along an urbanization gradient: differential tolerance to ammonia among molecular forms of the malaria mosquito Anopheles gambiae. BMC Ecol. 13, 1–12 (2013).Article 

    Google Scholar 
    18.Antonio-Nkondjio, C. et al. Review of malaria situation in Cameroon: technical viewpoint on challenges and prospects for disease elimination. Parasit. Vectors 12, 501 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    19.Hemingway, J., Hawkes, N. J., McCarroll, L. & Ranson, H. The molecular basis of insecticide resistance in mosquitoes. Insect Biochem. Mol. Biol. 34, 653–665 (2004).CAS 
    PubMed 
    Article 

    Google Scholar 
    20.Pocquet, N. et al. Multiple insecticide resistances in the disease vector Culex p. quinquefasciatus from Western Indian Ocean. PLoS ONE 8, 77855 (2013).ADS 
    Article 
    CAS 

    Google Scholar 
    21.Samantsidis, G.-R. et al. ‘What I cannot create, I do not understand’: functionally validated synergism of metabolic and target site insecticide resistance. Proc. R. Soc. B Biol. Sci. 287, 20200838 (2020).CAS 
    Article 

    Google Scholar 
    22.Corbel, V. et al. Multiple insecticide resistance mechanisms in Anopheles gambiae and Culex quinquefasciatus from Benin West Africa. Acta Trop. 101, 207–216 (2007).CAS 
    PubMed 
    Article 

    Google Scholar 
    23.Yadouléton, A. et al. Insecticide resistance status in Culex quinquefasciatus in Benin. Parasit. Vectors 8, 17 (2015).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    24.Xu, Q., Wang, H., Zhang, L. & Liu, N. Sodium channel gene expression associated with pyrethroid resistant house flies and German cockroaches. Gene 379, 62–67 (2006).CAS 
    PubMed 
    Article 

    Google Scholar 
    25.Martinez-Torres, D. et al. Voltage-dependent Na+ channels in pyrethroid-resistant Culex pipiens L. mosquitoes. Pestic. Sci. 55, 1012–1020 (1999).CAS 
    Article 

    Google Scholar 
    26.Weill, M. et al. The unique mutation in ace-1 giving high insecticide resistance is easily detectable in mosquito vectors. Insect Mol. Biol. 13, 1–7 (2004).CAS 
    PubMed 
    Article 

    Google Scholar 
    27.Djogbénou, L., Akogbéto, M. & Chandre, F. Presence of insensitive acetylcholinesterase in wild populations of Culex pipiens quinquefasciatus from Benin. Acta Trop. 107, 272–274 (2008).PubMed 
    Article 
    CAS 

    Google Scholar 
    28.Jones, C. M. et al. Insecticide resistance in Culex quinquefasciatus from Zanzibar: implications for vector control programmes. Parasit. Vectors 5, 78 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    29.Tmimi, F.-Z. et al. Insecticide resistance and target site mutations (G119S ace-1 and L1014F kdr) of Culex pipiens in Morocco. Parasit. Vectors 11, 51 (2018).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    30.Kothera, L. et al. Using targeted next-generation sequencing to characterize genetic differences associated with insecticide resistance in Culex quinquefasciatus populations from the southern U.S. PLoS ONE 14, (2019).31.Matowo, N. S. et al. Fine-scale spatial and temporal variations in insecticide resistance in Culex pipiens complex mosquitoes in rural south-eastern Tanzania. Parasit. Vectors 12, 413 (2019).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    32.Balabanidou, V. et al. Cytochrome P450 associated with insecticide resistance catalyzes cuticular hydrocarbon production in Anopheles gambiae. Proc. Natl. Acad. Sci. 113, 9268–9273 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    33.Huang, Y. et al. Culex pipiens pallens cuticular protein CPLCG5 participates in pyrethroid resistance by forming a rigid matrix. Parasit. Vectors 11, 6 (2018).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    34.Cameroun fiche pays populationData.net 2020. https://www.populationdata.net/pays/cameroun/.35.Djamouko-Djonkam, L. et al. Implication of Anopheles funestus in malaria transmission in the city of Yaoundé Cameroon. Parasite 27, 91 (2011).
    Google Scholar 
    36.Edwards, F. W. Mosquitoes of the Ethiopian Region. III.-Culicine adults and pupae. Mosquitoes Ethiop. Reg. III-Culicine Adults Pupae (1941).37.Jupp, P. G. Mosquitoes of Southern Africa: culicinae and toxorhynchitinae. (Ekogilde Publishers, 1996).38.Organization, W. H. Test procedures for insecticide resistance monitoring in malaria vector mosquitoes. (2016).39.Feyereisen, R. Insect P450 inhibitors and insecticides: challenges and opportunities. Pest Manag. Sci. 71, 793–800 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    40.Smith, J. L. & Fonseca, D. M. Rapid assays for identification of members of the Culex (Culex) pipiens complex, their hybrids, and other sibling species (Diptera: Culicidae). Am. J. Trop. Med. Hyg. 70, 339–345 (2004).CAS 
    PubMed 
    Article 

    Google Scholar 
    41.Scott, J. G., Yoshimizu, M. H. & Kasai, S. Pyrethroid resistance in Culex pipiens mosquitoes. Pestic. Biochem. Physiol. 120, 68–76 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    42.Bisset, J., Rodríguez, M. M. & Fernández, D. Selection of insensitive acetylcholinesterase as a resistance mechanism in Aedes aegypti (Diptera: Culicidae) from Santiago de Cuba. J. Med. Entomol. 43, 1185–1189 (2006).CAS 
    PubMed 
    Article 

    Google Scholar 
    43.Low, V. L. et al. Current susceptibility status of Malaysian Culex quinquefasciatus (Diptera: Culicidae) against DDT, propoxur, malathion, and permethrin. J. Med. Entomol. 50, 103–111 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    44.Djogbénou, L., Noel, V. & Agnew, P. Costs of insensitive acetylcholinesterase insecticide resistance for the malaria vector Anopheles gambiae homozygous for the G119S mutation. Malar. J. 9, 12 (2010).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    45.Labbé, P. et al. Independent duplications of the acetylcholinesterase gene conferring insecticide resistance in the mosquito Culex pipiens. Mol. Biol. Evol. 24, 1056–1067 (2007).PubMed 
    Article 
    CAS 

    Google Scholar 
    46.Delannay, C. et al. Multiple insecticide resistance in Culex quinquefasciatus populations from Guadeloupe (French West Indies) and associated mechanisms. PLoS ONE 13, e0199615 (2018).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    47.Georghiou, G. P. & Pasteur, N. Organophosphate Resistance and Esterase Pattern in a Natural Population of the Southern House Mosquito from California. J. Econ. Entomol. 73, 489–492 (1980).CAS 
    Article 

    Google Scholar 
    48.Xu, W. et al. Cypermethrin resistance conferred by increased target insensitivity and metabolic detoxification in Culex pipiens pallens Coq. Pestic. Biochem. Physiol. 142, 77–82 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    49.Gong, Y., Li, T., Feng, Y. & Liu, N. The function of two P450s, CYP9M10 and CYP6AA7, in the permethrin resistance of Culex quinquefasciatus. Sci. Rep. 7, 1–12 (2017).Article 
    CAS 

    Google Scholar 
    50.Komagata, O., Kasai, S. & Tomita, T. Overexpression of cytochrome P450 genes in pyrethroid-resistant Culex quinquefasciatus. Insect Biochem. Mol. Biol. 40, 146–152 (2010).CAS 
    PubMed 
    Article 

    Google Scholar 
    51.Liu, N., Li, T., Reid, W. R., Yang, T. & Zhang, L. Multiple Cytochrome P450 Genes: their constitutive overexpression and permethrin induction in insecticide resistant mosquitoes culex quinquefasciatus. PLoS ONE 6, e23403 (2011).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    52.Gordon, J. R. & Ottea, J. Association of esterases with insecticide resistance in Culex quinquefasciatus (Diptera: Culicidae). J. Econ. Entomol. 105, 971–978 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    53.Mouches, C. et al. Characterization of amplification core and esterase B1 gene responsible for insecticide resistance in Culex. Proc. Natl. Acad. Sci. 87, 2574–2578 (1990).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    54.Pasteur, N., Nancé, E. & Bons, N. Tissue localization of overproduced esterases in the mosquito Culex pipiens (Diptera: Culicidae). J. Med. Entomol. 38, 791–801 (2001).CAS 
    PubMed 
    Article 

    Google Scholar 
    55.Achaleke, J., Martin, T., Ghogomu, R. T., Vaissayre, M. & Brévault, T. Esterase-mediated resistance to pyrethroids in field populations of Helicoverpa armigera (Lepidoptera: Noctuidae) from Central Africa. Pest Manag. Sci. Former. Pestic. Sci. 65, 1147–1154 (2009).CAS 
    Article 

    Google Scholar 
    56.Simma, E. A. et al. Genome-wide gene expression profiling reveals that cuticle alterations and P450 detoxification are associated with deltamethrin and DDT resistance in Anopheles arabiensis populations from Ethiopia. PEST Manag. Sci. 75, 1808–1818 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    57.Subra, R. Biology and control of Culex pipiens quinquefasciatus Say, 1823 (Diptera, Culicidae) with special reference to Africa. Int. J. Trop. Insect Sci. 1, 319–338 (1981).CAS 
    Article 

    Google Scholar  More

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    Comparing sterile male releases and other methods for integrated control of the tiger mosquito in temperate and tropical climates

    1.Smith, C. E. G. The history of dengue in tropical asia and its probable relationship to the mosquito aedes aegypti. J. Trop. Med. Hyg. 59, 243–51 (1956).CAS 
    PubMed 

    Google Scholar 
    2.Reiter, P. Aedes albopictus and the world trade in used tires, 1988–1995: The shape of things to come?. J. Am. Mosquito Control Assoc. 14, 83–94 (1998).CAS 

    Google Scholar 
    3.Lounibos, L. P. Invasions by insect vectors of human disease. Ann. Rev. Entomol. 47, 233–266. https://doi.org/10.1146/annurev.ento.47.091201.145206 (2002).CAS 
    Article 

    Google Scholar 
    4.Medley, K. A., Jenkins, D. G. & Hoffman, E. A. Human-aided and natural dispersal drive gene flow across the range of an invasive mosquito. Mol. Ecol. 24, 284–295. https://doi.org/10.1111/mec.12925 (2015).Article 
    PubMed 

    Google Scholar 
    5.Sota, T. & Mogi, M. Survival time and resistance to desiccation of diapause and non-diapause eggs of temperate Aedes (Stegomyia) mosquitoes. Entomologia Experimentalis et Applicata 63, 155–161. https://doi.org/10.1111/j.1570-7458.1992.tb01570.x (1992).Article 

    Google Scholar 
    6.Poelchau, M. F., Reynolds, J. A., Denlinger, D. L., Elsik, C. G. & Armbruster, P. A. A de novo transcriptome of the Asian tiger mosquito, Aedes albopictus, to identify candidate transcripts for diapause preparation. BMC Genom. 12, 619. https://doi.org/10.1186/1471-2164-12-619 (2011).CAS 
    Article 

    Google Scholar 
    7.Bonizzoni, M., Gasperi, G., Chen, X. & James, A. A. The invasive mosquito species Aedes albopictus: current knowledge and future perspectives. Trends Parasitol. 29, 460–468. https://doi.org/10.1016/j.pt.2013.07.003 (2013).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    8.Paupy, C., Delatte, H., Bagny, L., Corbel, V. & Fontenille, D. Aedes albopictus, an arbovirus vector: from the darkness to the light. Microbes Infect. 11, 1177–1185. https://doi.org/10.1016/j.micinf.2009.05.005 (2009).CAS 
    Article 
    PubMed 

    Google Scholar 
    9.Wu, J.-Y., Lun, Z.-R., James, A. A. & Chen, X.-G. Dengue fever in Mainland China. Am. J. Trop. Med. Hyg. 83, 664–671. https://doi.org/10.4269/ajtmh.2010.09-0755 (2010).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    10.Gasperi, G. et al. A new threat looming over the mediterranean basin: emergence of viral diseases transmitted by aedes albopictus mosquitoes. PLOS Negl. Trop. Dis. 6, e1836. https://doi.org/10.1371/journal.pntd.0001836 (2012).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    11.Rezza, G. Aedes albopictus and the reemergence of Dengue. BMC Publ. Health 12, 72. https://doi.org/10.1186/1471-2458-12-72 (2012).Article 

    Google Scholar 
    12.Higgs, S. The 2005–2006 chikungunya epidemic in the Indian Ocean. Vector-Borne Zoo. Dis. 6, 115–116. https://doi.org/10.1089/vbz.2006.6.115 (2006).Article 

    Google Scholar 
    13.Ratsitorahina, M. et al. Outbreak of Dengue and Chikungunya Fevers, Toamasina, Madagascar, 2006. Emerg. Infect. Dis. 14, 1135–1137. https://doi.org/10.3201/eid1407.071521 (2008).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    14.Grard, G. et al. Zika virus in gabon (Central Africa): 2007—A new threat from aedes albopictus?. PLOS Negl. Trop. Dis. 8, e2681. https://doi.org/10.1371/journal.pntd.0002681 (2014).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    15.Vincent, M. et al. From the threat to the large outbreak: dengue on Reunion Island, 2015 to 2018. Eurosurveillhttps://doi.org/10.2807/1560-7917.ES.2019.24.47.1900346 (2019).Article 

    Google Scholar 
    16.Rezza, G. et al. Infection with chikungunya virus in Italy: an outbreak in a temperate region. Lancet 370, 1840–1846. https://doi.org/10.1016/S0140-6736(07)61779-6 (2007).CAS 
    Article 
    PubMed 

    Google Scholar 
    17.Lindh, E. et al. The Italian 2017 outbreak chikungunya virus belongs to an emerging aedes albopictus-adapted virus cluster introduced from the Indian subcontinent. Open Forum Infect. Dis.https://doi.org/10.1093/ofid/ofy321 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    18.Ruche, G. L. et al. First two autochthonous dengue virus infections in metropolitan France, September 2010. Eurosurveillance 15, 19676. https://doi.org/10.2807/ese.15.39.19676-en (2010).Article 
    PubMed 

    Google Scholar 
    19.Gjenero-Margan, I. et al. Autochthonous dengue fever in Croatia, August–September 2010. Eurosurveillance 16, 19805. https://doi.org/10.2807/ese.16.09.19805-en (2011).Article 
    PubMed 

    Google Scholar 
    20.Rovida, F. et al. Viremic Dengue virus infections in travellers: potential for local outbreak in Northern Italy. J. Clin. Virol. 50, 76–79. https://doi.org/10.1016/j.jcv.2010.09.015 (2011).Article 
    PubMed 

    Google Scholar 
    21.WHO. Dengue vaccine: WHO position paper—September 2018. Weekly epidemiological record 457–476 (2018).22.World Health Organization and others. Dengue and severe dengue. Tech. Rep., World Health Organization. Regional Office for the Eastern Mediterranean (2019).23.Organization, W. H. Dengue : Guidelines for Diagnosis, Treatment, Prevention and Control (WHO, 2009). Google-Books-ID: dlc0YSIyGYwC.24.Connelly, C., Florida, C. & Control, M. The State of the Mission as Defined by Mosquito Controllers, Regulators, and Environmental Managers 2009 2009 (University of Florida, Vero Beach, 2009).
    Google Scholar 
    25.Achee, N. L. et al. Alternative strategies for mosquito-borne arbovirus control. PLOS Negl. Trop. Dis. 13, e0006822. https://doi.org/10.1371/journal.pntd.0006822 (2019).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    26.Faraji, A. & Unlu, I. The eye of the tiger, the thrill of the fight: effective larval and adult control measures against the asian tiger mosquito, aedes albopictus (diptera: culicidae). North Am. J. Med. Entomol. 53, 1029–1047. https://doi.org/10.1093/jme/tjw096 (2016).Article 

    Google Scholar 
    27.Mackay, A. J., Amador, M. & Barrera, R. An improved autocidal gravid ovitrap for the control and surveillance of Aedes aegypti. Parasites & Vectors 6, 225. https://doi.org/10.1186/1756-3305-6-225 (2013).CAS 
    Article 

    Google Scholar 
    28.Barrera, R. et al. Impact of autocidal gravid ovitraps on chikungunya virus incidence in aedes aegypti (diptera: culicidae) in areas with and without traps. J. Med. Entomol. 54, 387–395. https://doi.org/10.1093/jme/tjw187 (2017).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    29.Barrera, R., Amador, M., Munoz, J. & Acevedo, V. Integrated vector control of Aedes aegypti mosquitoes around target houses. Parasites & Vectors 11, 88. https://doi.org/10.1186/s13071-017-2596-4 (2018).Article 

    Google Scholar 
    30.Jawara, M. et al. Optimizing odor-baited trap methods for collecting mosquitoes during the malaria season in the gambia. PLOS ONE 4, e8167. https://doi.org/10.1371/journal.pone.0008167 (2009).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    31.Englbrecht, C., Gordon, S., Venturelli, C., Rose, A. & Geier, M. Evaluation of BG-sentinel trap as a management tool to reduce aedes albopictus nuisance in an urban environment in Italy. Moco 31, 16–25. https://doi.org/10.2987/14-6444.1 (2015).Article 

    Google Scholar 
    32.Lacroix, R., Delatte, H., Hue, T., Dehecq, J. S. & Reiter, P. Adaptation of the BG-Sentinel trap to capture male and female Aedes albopictus mosquitoes. Med. Vet. Entomol. 23, 160–162. https://doi.org/10.1111/j.1365-2915.2009.00806.x (2009).CAS 
    Article 
    PubMed 

    Google Scholar 
    33.Suman, D. S. et al. Point-source and area-wide field studies of pyriproxyfen autodissemination against urban container-inhabiting mosquitoes. Acta Trop. 135, 96–103. https://doi.org/10.1016/j.actatropica.2014.03.026 (2014).CAS 
    Article 
    PubMed 

    Google Scholar 
    34.Devine, G. Auto-dissemination of pyriproxyfen for the control of container-inhabiting mosquitoes: a progress review. Outlooks Pest Manag. 27, 164–167 (2016).ADS 
    Article 

    Google Scholar 
    35.Devine, G. J. et al. Using adult mosquitoes to transfer insecticides to Aedes aegypti larval habitats., Using adult mosquitoes to transfer insecticides to Aedes aegypti larval habitats. Proc. Natl. Acad. Sci. USA 106, 11530–11534. https://doi.org/10.1073/pnas.0901369106 (2009).ADS 
    Article 
    PubMed 

    Google Scholar 
    36.Caputo, B. et al. The auto-dissemination approach: a novel concept to fight aedes albopictus in urban areas. PLOS Negl. Trop. Dis. 6, e1793. https://doi.org/10.1371/journal.pntd.0001793 (2012).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    37.Gaugler, R., Suman, D. & Wang, Y. An autodissemination station for the transfer of an insect growth regulator to mosquito oviposition sites. Med. Vet. Entomol. 26, 37–45. https://doi.org/10.1111/j.1365-2915.2011.00970.x (2012).CAS 
    Article 
    PubMed 

    Google Scholar 
    38.El-Sayed, A. M., Suckling, D. M., Wearing, C. H. & Byers, J. A. Potential of mass trapping for long-term pest management and eradication of invasive species. J. Econ. Entomol. 99, 1550–1564. https://doi.org/10.1093/jee/99.5.1550 (2006).CAS 
    Article 
    PubMed 

    Google Scholar 
    39.Dunn, D. W. & Follett, P. A. The sterile insect technique (SIT): an introduction. Entomol. Exp. Appl. 164, 151–154. https://doi.org/10.1111/eea.12619 (2017).Article 

    Google Scholar 
    40.Flores, H. A. & O’Neill, S. L. Controlling vector-borne diseases by releasing modified mosquitoes. Nat. Rev. Microbiol.https://doi.org/10.1038/s41579-018-0025-0 (2018).Article 
    PubMed 

    Google Scholar 
    41.Bellini, R., Medici, A., Puggioli, A., Balestrino, F. & Carrieri, M. Pilot field trials with Aedes albopictus irradiated sterile males in Italian urban areas. J. Med. Entomol. 50, 317–325 (2013).CAS 
    Article 

    Google Scholar 
    42.Zheng, X. et al. Incompatible and sterile insect techniques combined eliminate mosquitoes. Nature 572, 56–61. https://doi.org/10.1038/s41586-019-1407-9 (2019).CAS 
    Article 
    PubMed 

    Google Scholar 
    43.Bouyer, J. & Vreysen, M. Yes, irradiated sterile male mosquitoes can be sexually competitive!. Trends in Parasitology (2020) (in press).44.Alphey, L. et al. Sterile-insect methods for control of mosquito-borne diseases: an analysis. Vector Borne Zoo. Dis. 10, 295–311. https://doi.org/10.1089/vbz.2009.0014 (2010).Article 

    Google Scholar 
    45.Baldacchino, F. C. et al. Pest management science: wiley online library. Pest Manag. Sci.https://doi.org/10.1002/ps.4044 (2015).46.Lees, R., Gilles, J., Hendrichs, J., Vreysen, M. & Bourtzis, K. Back to the future: the sterile insect technique against mosquito disease vectors. Curr. Opin. Insect Sci. 10, 156–162. https://doi.org/10.1016/j.cois.2015.05.011 (2015).Article 
    PubMed 

    Google Scholar 
    47.Pleydell, D. R. J. & Bouyer, J. Biopesticides improve efficiency of the sterile insect technique for controlling mosquito-driven dengue epidemics. Commun. Biol. 2, 201. https://doi.org/10.1038/s42003-019-0451-1 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    48.Bouyer, J. & Lefrançois, T. Boosting the sterile insect technique to control mosquitoes. Trends Parasitol. 30, 271–273. https://doi.org/10.1016/j.pt.2014.04.002 (2014).Article 
    PubMed 

    Google Scholar 
    49.Bouyer, J., Chandre, F., Gilles, J. & Baldet, T. Alternative vector control methods to manage the Zika virus outbreak: more haste, less speed. Lancet Glob. Health 4, e364. https://doi.org/10.1016/S2214-109X(16)00082-6 (2016).Article 
    PubMed 

    Google Scholar 
    50.Invest, J. & Lucas, J. Pyriproxyfen as a mosquito larvicide. Proceedings of the Sixth International Conference on Urban Pests 239–245, (2008).51.Maoz, D. et al. Community effectiveness of pyriproxyfen as a dengue vector control method: a systematic review. PLOS Negl. Trop. Dis. 11, e0005651. https://doi.org/10.1371/journal.pntd.0005651 (2017).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    52.White, M. T. et al. Modelling the impact of vector control interventions on Anopheles gambiae population dynamics. Parasites Vectors 4, 153. https://doi.org/10.1186/1756-3305-4-153 (2011).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    53.Cailly, P. et al. Climate-driven abundance model to assess mosquito control strategies. Ecol. Model. ECOL MODEL 227, 7–17. https://doi.org/10.1016/j.ecolmodel.2011.10.027 (2012).ADS 
    Article 

    Google Scholar 
    54.Arifin, S. N., Madey, G. R. & Collins, F. H. Examining the impact of larval source management and insecticide-treated nets using a spatial agent-based model of Anopheles gambiae and a landscape generator tool. Malar J. 12, 290. https://doi.org/10.1186/1475-2875-12-290 (2013).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    55.Lee, S. S., Baker, R. E., Gaffney, E. A. & White, S. M. Optimal barrier zones for stopping the invasion of Aedes aegypti mosquitoes via transgenic or sterile insect techniques. Theor. Ecol. 6, 427–442. https://doi.org/10.1007/s12080-013-0178-4 (2013).Article 

    Google Scholar 
    56.Yakob, L. & Yan, G. Modeling the effects of integrating larval habitat source reduction and insecticide treated nets for malaria control. PLOS ONE 4, e6921. https://doi.org/10.1371/journal.pone.0006921 (2009).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    57.Almeida, L., Duprez, M., Privat, Y. & Vauchelet, N. Control strategies on mosquitos population for the fight against arboviruses. arXiv:1901.05688 [math] (2019).58.North, A. R., Burt, A. & Godfray, H. C. J. Modelling the potential of genetic control of malaria mosquitoes at national scale. BMC Biol. 17, 26. https://doi.org/10.1186/s12915-019-0645-5 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    59.Strugarek, M., Bossin, H. & Dumont, Y. On the use of the sterile insect release technique to reduce or eliminate mosquito populations. Appl. Math. Model. 68, 443–470. https://doi.org/10.1016/j.apm.2018.11.026 (2019).MathSciNet 
    Article 
    MATH 

    Google Scholar 
    60.Maiti, A., Patra, B. & Samanta, G. P. Sterile insect release method as a control measure of insect pests: a mathematical model. J. Appl. Math. Comput. 22, 71–86. https://doi.org/10.1007/BF02832038 (2006).MathSciNet 
    Article 
    MATH 

    Google Scholar 
    61.White, S. M., Rohani, P. & Sait, S. M. Modelling pulsed releases for sterile insect techniques: fitness costs of sterile and transgenic males and the effects on mosquito dynamics. J. Appl. Ecol. 47, 1329–1339. https://doi.org/10.1111/j.1365-2664.2010.01880.x (2010) (WOS:000283983200020).Article 

    Google Scholar 
    62.Dufourd, C. & Dumont, Y. Impact of environmental factors on mosquito dispersal in the prospect of sterile insect technique control. Comput. Math. Appl. 66, 1695–1715. https://doi.org/10.1016/j.camwa.2013.03.024 (2013).MathSciNet 
    Article 
    MATH 

    Google Scholar 
    63.Fister, K. R., McCarthy, M. L., Oppenheimer, S. F. & Collins, C. Optimal control of insects through sterile insect release and habitat modification. Math. Biosci. 244, 201–212. https://doi.org/10.1016/j.mbs.2013.05.008 (2013) (WOS:000322805400014).MathSciNet 
    Article 
    MATH 

    Google Scholar 
    64.Cai, L., Ai, S. & Li, J. Dynamics of mosquitoes populations with different strategies for releasing sterile mosquitoes. SIAM J. Appl. Math. 74, 1786–1809. https://doi.org/10.1137/13094102X (2014) (WOS:000346845900004).MathSciNet 
    Article 
    MATH 

    Google Scholar 
    65.Evans, T. P. & Bishop, S. R. A spatial model with pulsed releases to compare strategies for the sterile insect technique applied to the mosquito Aedes aegypti. Math. Biosci. 254, 6–27. https://doi.org/10.1016/j.mbs.2014.06.001 (2014).MathSciNet 
    Article 
    MATH 

    Google Scholar 
    66.Li, J. & Yuan, Z. Modelling releases of sterile mosquitoes with different strategies. J. Biol. Dyn. 9, 1–14. https://doi.org/10.1080/17513758.2014.977971 (2015).MathSciNet 
    Article 
    PubMed 
    MATH 

    Google Scholar 
    67.Hendron, R.-W.S. & Bonsall, M. B. The interplay of vaccination and vector control on small dengue networks. J. Theor. Biol. 407, 349–361. https://doi.org/10.1016/j.jtbi.2016.07.034 (2016).MathSciNet 
    Article 
    PubMed 
    PubMed Central 
    MATH 

    Google Scholar 
    68.Huang, M., Song, X. & Li, J. Modelling and analysis of impulsive releases of sterile mosquitoes. J. Biol. Dyn. 11, 147–171. https://doi.org/10.1080/17513758.2016.1254286 (2017) (WOS:000389042600004).MathSciNet 
    Article 
    PubMed 
    MATH 

    Google Scholar 
    69.Mishra, A., Ambrosio, B., Gakkhar, S. & Aziz-Alaoui, M. A. A network model for control of dengue epidemic using sterile insect technique. Math. Biosci. Eng. 15, 441–460. https://doi.org/10.3934/mbe.2018020 (2018) (WOS:000412001800006).MathSciNet 
    Article 
    PubMed 
    MATH 

    Google Scholar 
    70.Multerer, L., Smith, T. & Chitnis, N. Modeling the impact of sterile males on an Aedes aegypti population with optimal control. Math. Biosci. 311, 91–102. https://doi.org/10.1016/j.mbs.2019.03.003 (2019).MathSciNet 
    Article 
    PubMed 
    MATH 

    Google Scholar 
    71.Haramboure, M. et al. Modelling the control of Aedes albopictus mosquitoes based on sterile males release techniques in a tropical environment. Ecol. Model. 424, 109002. https://doi.org/10.1016/j.ecolmodel.2020.109002 (2020).Article 

    Google Scholar 
    72.ANSES. Portail de signalement du moustique tigre.73.Delisle, E. et al. Chikungunya outbreak in Montpellier, France, September to October 2014. Eurosurveillance 20, 21108. https://doi.org/10.2807/1560-7917.ES2015.20.17.21108 (2015) (Publisher: European Centre for Disease Prevention and Control).Article 
    PubMed 

    Google Scholar 
    74.Tran, A. et al. A rainfall- and temperature-driven abundance model for aedes albopictus populations. Int. J. Environ. Res. Publ. Health 10, 1698–1719. https://doi.org/10.3390/ijerph10051698 (2013).Article 

    Google Scholar 
    75.WHO & others. WHO position statement on integrated vector management. Weekly Epidemiological Record= Relevé épidémiologique hebdomadaire83, 177–181 (2008).76.Johnson, B. J., Ritchie, S. A. & Fonseca, D. M. The state of the art of lethal oviposition trap-based mass interventions for arboviral control. Insects 8, 5. https://doi.org/10.3390/insects8010005 (2017).Article 
    PubMed Central 

    Google Scholar 
    77.Delatte, H. et al. Aedes albopictus, vecteur des virus du chikungunya et de la dengue à la Réunion?: biologie et contrôle. Parasite 15, 3–13. https://doi.org/10.1051/parasite/2008151003 (2008).CAS 
    Article 
    PubMed 

    Google Scholar 
    78.Dufourd, C. & Dumont, Y. Modeling and simulations of mosquito dispersal: the case of aedes albopictus. BIOMATH 1, 1209262. https://doi.org/10.11145/j.biomath.2012.09.262 (2012).MathSciNet 
    Article 
    MATH 

    Google Scholar 
    79.Bouyer, J., Yamada, H., Pereira, R., Bourtzis, K. & Vreysen, M. J. B. Phased conditional approach for mosquito management using sterile insect technique. Trends Parasitol. 36, 325–336. https://doi.org/10.1016/j.pt.2020.01.004 (2020).Article 
    PubMed 

    Google Scholar 
    80.McIntire, K. M. & Juliano, S. A. How can mortality increase population size? A test of two mechanistic hypotheses. Ecology 99, 1660–1670. https://doi.org/10.1002/ecy.2375 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    81.Neale, J. T. & Juliano, S. A. Finding the sweet spot: What levels of larval mortality lead to compensation or overcompensation in adult production?. Ecosphere 10, e02855. https://doi.org/10.1002/ecs2.2855 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    82.Seixas, G. et al. An evaluation of efficacy of the auto-dissemination technique as a tool for Aedes aegypti control in Madeira, Portugal. Parasites Vectors 12, 202. https://doi.org/10.1186/s13071-019-3454-3 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    83.Mains, J. W., Brelsfoard, C. L. & Dobson, S. L. Male mosquitoes as vehicles for insecticide. PLOS Negl. Trop. Dis. 9, e0003406. https://doi.org/10.1371/journal.pntd.0003406 (2015).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    84.Ritchie, S. A., Long, S., Hart, A., Webb, C. E. & Russell, R. C. An adulticidal sticky ovitrap for sampling container-breeding mosquitoes. J. Am. Mosq. Control Assoc. 19, 235–242 (2003).PubMed 

    Google Scholar 
    85.Lacroix, R., Delatte, H., Hue, T. & Reiter, P. Dispersal and Survival of Male and Female Aedes albopictus (Diptera: Culicidae) on Réunion Island. Ment 46, 1117–1124. https://doi.org/10.1603/033.046.0519 (2009).CAS 
    Article 

    Google Scholar 
    86.Marini, F., Caputo, B., Pombi, M., Tarsitani, G. & Torre, A. D. Study of Aedes albopictus dispersal in Rome, Italy, using sticky traps in mark-release-recapture experiments. Med. Vet. Entomol. 24, 361–368. https://doi.org/10.1111/j.1365-2915.2010.00898.x (2010).CAS 
    Article 
    PubMed 

    Google Scholar 
    87.Garziera, L. et al. Effect of interruption of over-flooding releases of transgenic mosquitoes over wild population of Aedes aegypti: two case studies in Brazil. Entomol. Exp. Appl. 164, 327–339. https://doi.org/10.1111/eea.12618 (2017) (WOS:000413403700015).Article 

    Google Scholar 
    88.Tran, A. et al. Complementarity of empirical and process-based approaches to modelling mosquito population dynamics with Aedes albopictus as an example-Application to the development of an operational mapping tool of vector populations. PLOS ONE 15, e0227407. https://doi.org/10.1371/journal.pone.0227407 (2020).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    89.Baldacchino, F. et al. An integrated pest control strategy against the Asian tiger mosquito in northern Italy: a case study. Pest Manag. Sci. 73, 87–93. https://doi.org/10.1002/ps.4417 (2017).CAS 
    Article 
    PubMed 

    Google Scholar 
    90.Gentile, J. E., Rund, S. S. C. & Madey, G. R. Modelling sterile insect technique to control the population of Anopheles gambiae. Malar. J. 14, 92. https://doi.org/10.1186/s12936-015-0587-5 (2015) (WOS:000350605300001).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    91.Perrin, A. et al. Mosquito densoviruses: the revival of a biological control agent against urban Aedes vectors of arboviruses. bioRxiv 2020.04.23.055830, https://doi.org/10.1101/2020.04.23.055830 (2020). Publisher: Cold Spring Harbor Laboratory Section: New Results.92.Burattini, M. N. et al. Modelling the control strategies against dengue in Singapore. Epidemiol. Infect. 136, 309–319. https://doi.org/10.1017/S0950268807008667 (2008).CAS 
    Article 
    PubMed 

    Google Scholar 
    93.Yang, H. M. & Ferreira, C. P. Assessing the effects of vector control on dengue transmission. Appl. Math. Comput. 198, 401–413. https://doi.org/10.1016/j.amc.2007.08.046 (2008).MathSciNet 
    Article 
    MATH 

    Google Scholar 
    94.Dumont, Y. & Chiroleu, F. Vector control for the Chikungunya disease. Math. Biosci. Eng. 7, 313–345 (2010).MathSciNet 
    Article 

    Google Scholar 
    95.Hladish, T. J. et al. Designing effective control of dengue with combined interventions. Proc. Natl. Acad. Sci. 117, 3319–3325 (2020).CAS 
    Article 

    Google Scholar 
    96.Tang, B. et al. The effectiveness of quarantine and isolation determine the trend of the COVID-19 epidemics in the final phase of the current outbreak in China. Int. J. Infect. Dis. 95, 288–293. https://doi.org/10.1016/j.ijid.2020.03.018 (2020).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    97.Jr, R. C. R. et al. Estimating the impact of city-wide Aedes aegypti population control: an observational study in Iquitos, Peru. PLOS Negl. Trop. Dis. 13, e0007255. https://doi.org/10.1371/journal.pntd.0007255 (2019).98.Wahid, I. et al. Integrated vector management with additional pre-transmission season thermal fogging is associated with a reduction in dengue incidence in Makassar, Indonesia: Results of an 8-year observational study. PLOS Negl. Trop. Dis. 13, e0007606. https://doi.org/10.1371/journal.pntd.0007606 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    99.Castro, M. et al. A community empowerment strategy embedded in a routine dengue vector control programme: a cluster randomised controlled trial. Trans. R. Soc. Trop. Med. Hyg. 106, 315–321. https://doi.org/10.1016/j.trstmh.2012.01.013 (2012).Article 
    PubMed 

    Google Scholar 
    100.Andersson, N. et al. Evidence based community mobilization for dengue prevention in Nicaragua and Mexico (Camino Verde, the Green Way): cluster randomized controlled trial. BMJ 351, h3267. https://doi.org/10.1136/bmj.h3267 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    101.Gubler, D. J. & Clark, G. G. Community involvement in the control of Aedes aegypti. Acta Trop. 61, 169–179. https://doi.org/10.1016/0001-706X(95)00103-L (1996).CAS 
    Article 
    PubMed 

    Google Scholar 
    102.Baly, A. et al. Cost effectiveness of Aedes aegypti control programmes: participatory versus vertical. Trans. R. Soc. Trop. Med. Hyg. 101, 578–586. https://doi.org/10.1016/j.trstmh.2007.01.002 (2007).CAS 
    Article 
    PubMed 

    Google Scholar 
    103.Alphey, N., Alphey, L. & Bonsall, M. B. A model framework to estimate impact and cost of genetics-based sterile insect methods for dengue vector control. PLoS One 6, e25384. https://doi.org/10.1371/journal.pone.0025384 (2011) (WOS:000295966900023).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    104.Fontenille, D. et al.La lutte antivectorielle en France. IRD Éditions (2009).105.Oliva, C. F. et al. The sterile insect technique for controlling populations of aedes albopictus (diptera: culicidae) on reunion island: mating vigour of sterilized males. PLOS ONE 7, e49414. https://doi.org/10.1371/journal.pone.0049414 (2012).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    106.Madakacherry, O., Lees, R. S. & Gilles, J. R. L. Aedes albopictus (Skuse) males in laboratory and semi-field cages: release ratios and mating competitiveness. Acta Trop. 132(Suppl), S124-129. https://doi.org/10.1016/j.actatropica.2013.11.020 (2014).Article 
    PubMed 

    Google Scholar 
    107.Abad-Franch, F., Zamora-Perea, E., Ferraz, G., Padilla-Torres, S. D. & Luz, S. L. B. Mosquito-disseminated pyriproxyfen yields high breeding-site coverage and boosts juvenile mosquito mortality at the neighborhood scale. PLoS Negl. Trop. Dis.https://doi.org/10.1371/journal.pntd.0003702 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    108.Unlu, I. et al. Large-scale operational pyriproxyfen autodissemination deployment to suppress the immature asian tiger mosquito (diptera: culicidae) populations. J. Med. Entomol.https://doi.org/10.1093/jme/tjaa011 (2020).Article 
    PubMed 

    Google Scholar 
    109.Degener, C. M. et al. Mass trapping with MosquiTRAPs does not reduce Aedes aegypti abundance. Memórias do Instituto Oswaldo Cruz 110, 517–527. https://doi.org/10.1590/0074-02760140374 (2015).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    110.Boubidi, S. C. Surveillance et contrôle du moustique tigre, Aedes albopictus (Skuse, 1894) à Nice, sud de la France (2016).111.Kröckel, U., Rose, A., Eiras, Á. E. & Geier, M. New tools for surveillance of adult yellow fever mosquitoes: comparison of trap catches with human landing rates in an urban environment. Moco 22, 229–238. https://doi.org/10.2987/8756-971X(2006)22[229:NTFSOA]2.0.CO;2 (2006).Article 

    Google Scholar  More

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    Submicron polymer particles may mask the presence of toxicants in wastewater effluents probed by reporter gene containing bacteria

    1.Pivokonsky, M. et al. Occurrence of microplastics in raw and treated drinking water. Sci. Total. Environ. 643, 1644–1651 (2018).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    2.Geyer, R., Jambeck, J. R. & Law, K. L. Production, use, and fate of all plastics ever made. Sci. Adv. 3, e1700782 (2017).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    3.Courtene-Jones, W., Quinn, B., Gary, S. F., Mogg, A. O. & Narayanaswamy, B. E. Microplastic pollution identified in deep-sea water and ingested by benthic invertebrates in the rockall trough, North Atlantic Ocean. Environ. Pollut. 231, 271–280 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    4.Koongolla, J. B. et al. Occurrence of microplastics in gastrointestinal tracts and gills of fish from Beibu Gulf, South China Sea. Environ. Pollut. 258, 113734 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    5.Qu, M. et al. Nanopolystyrene at predicted environmental concentration enhances microcystin-LR toxicity by inducing intestinal damage in Caenorhabditis elegans. Ecotoxicol. Environ. Saf. 183, 109568 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    6.Li, Y. et al. Low level of polystyrene microplastics decreases early developmental toxicity of phenanthrene on marine medaka (Oryzias melastigma). J. Hazard. Mater. 385, 121586 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    7.Shao, H. & Wang, D. Long-term and low-dose exposure to nanopolystyrene induces a protective strategy to maintain functional state of intestine barrier in nematode Caenorhabditis elegans. Environ. Pollut. 258, 113649 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    8.Sørensen, L., Rogers, E., Altin, D., Salaberria, I. & Booth, A. M. Sorption of PAHs to microplastic and their bioavailability and toxicity to marine copepods under co-exposure conditions. Environ. Pollut. 258, 113844 (2020).PubMed 
    Article 
    CAS 

    Google Scholar 
    9.Lee, K.-W., Shim, W. J., Kwon, O. Y. & Kang, J.-H. Size-dependent effects of micro polystyrene particles in the marine copepod Tigriopus japonicus. Environ. Sci. Technol. 47, 11278–11283 (2013).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    10.Sun, X. et al. Toxicities of polystyrene nano-and microplastics toward marine bacterium Halomonas alkaliphila. Sci. Total. Environ. 642, 1378–1385 (2018).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    11.Ivask, A. et al. Genome-wide bacterial toxicity screening uncovers the mechanisms of toxicity of a cationic polystyrene nanomaterial. Environ. Sci. Technol. 46, 2398–2405 (2012).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    12.Heinlaan, M. et al. Hazard evaluation of polystyrene nanoplastic with nine bioassays did not show particle-specific acute toxicity. Sci. Total. Environ. 707, 136073 (2020).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    13.Miyazaki, J. et al. Bacterial toxicity of functionalized polystyrene latex nanoparticles toward Escherichia coli. Adv. Mat. Res. 699, 672–677 (2013).CAS 

    Google Scholar 
    14.Kwon, Y.-N. & Leckie, J. O. Hypochlorite degradation of crosslinked polyamide membranes: II. Changes in hydrogen bonding behavior and performance. J. Membr. Sci. 282, 456–464 (2006).CAS 
    Article 

    Google Scholar 
    15.Ateia, M., Kanan, A. & Karanfil, T. Microplastics release precursors of chlorinated and brominated disinfection byproducts in water. Chemosphere 251, 126452 (2020).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    16.Andrady, A. L. Microplastics in the marine environment. Mar. Pollut. Bull. 62, 1596–1605 (2011).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    17.Mammo, F., Amoah, I., Gani, K., Pillay, L., Ratha, S., Bux, F. & Kumari, S. Microplastics in the environment: Interactions with microbes and chemical contaminants. Sci. Total. Environ. 743, 140518 (2020).18.Engler, R. E. The complex interaction between marine debris and toxic chemicals in the ocean. Environ. Sci. Technol. 46, 12302–12315 (2012).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    19.Mattsson, K., Jocic, S., Doverbratt, I. & Hansson, L.-A. An emerging matter of environmental urgency. In Microplastic contamination in aquatic environments (ed. Zeng, E.) 379–399 (Elsevier, 2018).
    Google Scholar 
    20.Sumampouw, O. J. & Risjani, Y. Bacteria as indicators of environmental pollution. Environment 51, 52 (2014).
    Google Scholar 
    21.Hassan, S. H. et al. Real-time monitoring of water quality of stream water using sulfur-oxidizing bacteria as bio-indicator. Chemosphere 223, 58–63 (2019).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    22.Bowdre, J. H. & Krieg, N. R. Water quality monitoring: bacteria as indicators (Virginia Water Resources Research Center, 1974).
    Google Scholar 
    23.Leusch, F. D. et al. Assessment of wastewater and recycled water quality: a comparison of lines of evidence from in vitro, in vivo and chemical analyses. Water Res. 50, 420–431 (2014).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    24.Federation, Water Environmental and American Public Health Association (APHA). Standard methods for the examination of water and wastewater, Vol. 2 , Washington, DC, USA, (1915).25.Belkin, S. et al. A panel of stress-responsive luminous bacteria for the detection of selected classes of toxicants. Water Res. 31, 3009–3016 (1997).CAS 
    Article 

    Google Scholar 
    26.Bhuvaneshwari, M. et al. Toxicity of chlorinated and ozonated wastewater effluents probed by genetically modified bioluminescent bacteria and cyanobacteria Spirulina sp. Water Res. 164, 114910 (2019).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    27.Bianchi, E. et al. Evaluation of genotoxicity and cytotoxicity of water samples from the Sinos River Basin, southern Brazil. Braz. J. Biol. 75, 68–74 (2015).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    28.Melamed, S. et al. A printed nanolitre-scale bacterial sensor array. Lab Chip 11, 139–146 (2011).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    29.Jia, K., Eltzov, E., Toury, T., Marks, R. S. & Ionescu, R. E, A lower limit of detection for atrazine was obtained using bioluminescent reporter bacteria via a lower incubation temperature. Ecotoxicol. Environ. Saf. 84, 221–226 (2012).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    30.Kim, B. C. & Gu, M. B, A bioluminescent sensor for high throughput toxicity classification. Biosens. Bioelectron 18, 1015–1021 (2003).CAS 
    PubMed 
    Article 

    Google Scholar 
    31.Gu, M. B., Min, J. & Kim, E. J, Toxicity monitoring and classification of endocrine disrupting chemicals (EDCs) using recombinant bioluminescent bacteria. Chemosphere 46, 289–294 (2002).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    32.Woutersen, M., Belkin, S., Brouwer, B., van Wezel, A. P. & Heringa, M. B, Are luminescent bacteria suitable for online detection and monitoring of toxic compounds in drinking water and its sources?. Anal Bioanal Chem 4, 915–929 (2011).Article 
    CAS 

    Google Scholar 
    33.Manivannan, B. et al. Water toxicity evaluations: comparing genetically modified bioluminescent bacteria and CHO cells as biomonitoring tools. Ecotoxicol. Environ. Saf. 203, 110984 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    34.Gambardella, C. et al. Microplastics do not affect standard ecotoxicological endpoints in marine unicellular organisms. Mar. Pollut. Bull. 143, 140–143 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    35.Magnusson, K. & Norén, F. Screening of microplastic particles in and down-stream a wastewater treatment plant (IVL Swedish Environmental Research Institute, 2014).
    Google Scholar 
    36.Talvitie, J. et al. Do wastewater treatment plants act as a potential point source of microplastics? Preliminary study in the coastal Gulf of Finland, Baltic Sea. Water Sci. Technol. 72, 1495–1504 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    37.Carr, S. A., Liu, J. & Tesoro, A. G. Transport and fate of microplastic particles in wastewater treatment plants. Water Res. 91, 174–182 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    38.Dris, R. et al. Microplastic contamination in an urban area: a case study in Greater Paris. Environ. Chem. 5, 592–599 (2015).Article 
    CAS 

    Google Scholar 
    39.HELCOM, 2014. Baltic Marine Environment Protection Commission, Preliminary study on Synthetic microfibers and particles at a municipal waste water treatment plant, BASE project 2012–2014.40.Lares, M., Ncibi, M. C., Sillanpää, M. & Sillanpää, M. Occurrence, identification and removal of microplastic particles and fibers in conventional activated sludge process and advanced MBR technology. Water Res 133, 236–246 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    41.Murphy, F., Ewins, C., Carbonnier, F. & Quinn, B. Wastewater treatment works (WwTW) as a source of microplastics in the aquatic environment. Environ. Sci. Technol. 50, 5800–5808 (2016).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    42.Garside, M. Global plastic production from 1950 to 2018. Statista. Available online at: https://www.statista.com/statistics/282732/global-production-ofplastics-since-1950 (2019).43.Jang, M. et al. H, Widespread detection of a brominated flame retardant, hexabromocyclododecane, in expanded polystyrene marine debris and microplastics from South Korea and the Asia-Pacific coastal region. Environ Pollut. 231, 785–794 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    44.De-la-Torre, G. E., Dioses-Salinas, D. C., Pizarro-Ortega, C. I. & Saldaña-Serran, M. Global distribution of two polystyrene-derived contaminants in the marine environment: A review. Mar. Pollut. Bull. 161, 111729 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    45.Zitko, V. Expanded polystyrene as a source of contaminants. Mar. Pollut. Bull 10, 584–585 (1993).Article 

    Google Scholar 
    46.Hoerter, J. & Eisenstark, A. Synergistic killing of bacteria and phage by polystyrene and ultraviolet radiation. Environ. Mutagen. 12, 261–264 (1988).CAS 
    Article 

    Google Scholar 
    47.Miao, L. et al. Acute effects of nanoplastics and microplastics on periphytic biofilms depending on particle size, concentration and surface modification. Environ. Pollut. 255, 113300 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    48.Rupe, L. A., Tuthill, L. B. & Leikhim, J. W. Thickened bleach compositions for treating hard-to-remove soils. U.S. Patent No. 4116851. (1978).49.Merritt, K., Hitchins, V. M. & Brown, S. A. Safety and cleaning of medical materials and devices. J. Biomed. Mater. Res. 53, 131–136 (2000).CAS 
    PubMed 
    Article 

    Google Scholar 
    50.https://www.dutscher.com/data/pdf_guides/en/CCTPPA.pdf Material Pour Laboratories ET Industries, Dominique Dutscher.51.Messing, A. & Sela, Y. SHAFDAN (Greater Tel Aviv Wastewater Treatment Plant): recent upgrade and expansion. Water Pract. Technol 2, 288–297 (2016).Article 

    Google Scholar 
    52.Eldad Spivak, Engineering Firm LTD., Raanana wastewater facility, Israel. http://www.spivak.co.il/en/projects/raanana-wastewater-facility.53.Balasha Jalon, Infrastructure systems LTD., Karmiel wastewater treatment plant- First stage- Israel. http://bj-is.com/karmiel-wwtp.54.Heinlaan, M. et al. & Kahru, A, Hazard evaluation of polystyrene nanoplastic with nine bioassays did not show particle-specific acute toxicity. Sci. Total Environ. 707, 136073 (2020).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    55.Snead, M. C. Benefits of maintaining a chlorine residual in water supply systems, 600/2-80-0100 (US Environmental Protection Agency, 1980).56.Harp, D.L. Current technology for chlorine analysis in water and wastewater. Technical Information Series—Booklet No.17. Hach Company (2002).57.4500-Cl CHLORINE (RESIDUAL). Standard Methods For the Examination of Water and Wastewater, 23rd (2018).58.Engelhardt, T. & Malkov, V. B. Chlorination, chloramination and chlorine measurement 18–20 (HACH, 2015).
    Google Scholar 
    59.https://www.polyfluor.nl/en/chemical-resistance/ptfe/. Specialist in PTFE, Engineering and Manufacturing Service, Polyfluor.60.Vollmer, A. C., Belkin, S., Smulski, D. R., Van Dyk, T. K. & LaRossa, R. A. Detection of DNA damage by use of Escherichia coli carrying recA’: lux, uvrA’: lux, or alkA’: lux reporter plasmids. Appl. Environ. Microbiol. 63, 2566–2571 (1997).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    61.Van Dyk, T. K. et al. Rapid and sensitive pollutant detection by induction of heat shock gene-bioluminescence gene fusions. Appl. Environ. Microbiol. 60, 1414–1420 (1994).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    62.Eltzov, E., Marks, R. S., Voost, S., Wullings, B. A. & Heringa, M. B. Flow-through real time bacterial biosensor for toxic compounds in water. Sensors Actuators B: Chem. 142, 11–18 (2009).CAS 
    Article 

    Google Scholar 
    63.Harpaz, D. et al. Measuring artificial sweeteners toxicity using a bioluminescent bacterial panel. Molecules 23, 2454 (2018).PubMed Central 
    Article 
    CAS 

    Google Scholar 
    64.Thiagarajan, V., Iswarya, V., Seenivasan, R., Chandrasekaran, N. & Mukherjee, A. Influence of differently functionalized polystyrene microplastics on the toxic effects of P25 TiO2 NPs towards marine algae Chlorella sp. Aquat. Toxicol. 207, 208–216 (2019).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    65.Kelkar, V. P. et al. Chemical and physical changes of microplastics during sterilization by chlorination. Water Res. 163, 114871 (2019).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    66.Zhang, X. et al. Formation and interdependence of disinfection byproducts during chlorination of natural organic matter in a conventional drinking water treatment plant. Chemosphere 242, 125227 (2020).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    67.Yan, M., Roccaro, P., Fabbricino, M. & Korshin, G. V. Comparison of the effects of chloramine and chlorine on the aromaticity of dissolved organic matter and yields of disinfection by-products. Chemosphere 191, 477–484 (2018).ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    68.Hüffer, T. & Hofmann, T. Sorption of non-polar organic compounds by micro-sized plastic particles in aqueous solution. Environ. Pollut. 214, 194–201 (2016).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar  More

  • in

    Reflections and projections on a decade of climate science

    When I began my PhD a decade ago, climate change economics was an extremely niche area. Just a few topics dominated — especially discounting and the relative merits of different climate policy instruments — and the number of researchers was small, incommensurate with the scale of the environmental, economic or policy challenges that climate change presents. However, since then, the field has broadened, deepened and strengthened links to climate science.Notably, there has been an explosion of studies documenting the sensitivity of social and economic systems to temperature. This literature, using statistical approaches designed to identify causal relationships in non-experimental data, has uncovered the effects of temperature across a wide range of outcomes: conflict risk, pre-term birth, classroom learning as well as overall economic productivity across many sectors. This discovery of pervasive and, in some cases, large temperature impacts, even in wealthy countries, is a sharp break with previous work, which understood effects to be mostly limited to a few highly exposed sectors, such as agriculture and coastal infrastructure.Important advances have come from questioning assumptions underlying the cost–benefit assessment of climate policy. Ten years ago, conventional wisdom held that substantial emissions reductions by 2050, required to limit warming to less than 2 °C, could not be justified on a cost–benefit basis. Many studies now show that this finding is overturned under alternate but justifiable models of how climate change affects the economy and human welfare. Two prominent examples are the question of whether climate change affects the underlying growth rate of the economy, and disentangling risk and time preferences in the utility function.A welcome development has been growing interest across the entire economics discipline, with scholars from labour, development, macro, health and financial economics working on questions of weather and climate. Even more important has been recognition of systemic climate risk within major financial institutions. Central banks, institutional investors and credit rating agencies direct capital investment flows and manage economic risks, and will play a critical role in structuring future adaptive transitions. Markets, communities, households and businesses will have to adapt both to a continuously changing climate, and to a low-carbon economy. Forward-looking regulations and investments that anticipate these changes will lower the costs of these transitions.I see several important areas still in need of substantive work. Firstly, an assessment of alternative policy instruments that better incorporates the political and technological feedbacks that will accompany major climate policy. Economists tend to favour carbon pricing because of its cost-effectiveness. But how do pricing policies perform given a richer representation of other relevant market failures or real political constraints? Examples include subsidy-driven declines in technology costs or strategic interest group dynamics, where policies themselves create or undermine powerful interest groups and therefore alter the space of political possibility. Collaboration with engineers and political scientists can help address these questions. An expanded focus on desirable policies for low- and middle-income countries, essential to meet ambitious decarbonization goals and which present distinct challenges, is also critical.More work is needed on understanding climate damages, particularly those that fall outside of traditional market measures, such as losses of cultural heritage, conflict risk or biodiversity loss. These are extremely difficult to value and are not adequately incorporated into current estimates of aggregate climate damages, such as the social cost of carbon. Also critical is understanding the transition and adjustment costs associated with a continuously changing climate. Too many studies estimate equilibrium damages or assume costless adjustment. But infrastructure is long-lived, and natural hazards are already under-priced in many property markets. In this context, climate change risks creating stranded assets, price bubbles and unsustainable liabilities for local or even national governments, all of which could add substantially to climate change cost estimates.
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    Impaired viral infection and reduced mortality of diatoms in iron-limited oceanic regions

    1.Nelson, D. M., Tréguer, P., Brzezinski, M. A., Leynaert, A. & Quéguiner, B. Production and dissolution of biogenic silica in the ocean: revised global estimates, comparison with regional data and relationship to biogenic sedimentation. Glob. Biogeochem. Cycles 9, 359–372 (1995).
    Google Scholar 
    2.Smetacek, V. et al. Deep carbon export from a Southern Ocean iron-fertilized diatom bloom. Nature 487, 313–319 (2012).
    Google Scholar 
    3.Hutchins, D. A., DiTullio, G. R., Zhang, Y. & Bruland, K. W. An iron limitation mosaic in the California upwelling regime. Limnol. Oceanogr. 43, 1037–1054 (1998).
    Google Scholar 
    4.Bruland, K. W., Rue, E. L. & Smith, G. J. Iron and macronutrients in California coastal upwelling regimes: implications for diatom blooms. Limnol. Oceanogr. 46, 1661–1674 (2001).
    Google Scholar 
    5.Boyd, P. W. et al. Mesoscale iron enrichment experiments 1993–2005: synthesis and future directions. Science 315, 612–617 (2007).
    Google Scholar 
    6.Brzezinski, M. A. et al. Enhanced silica ballasting from iron stress sustains carbon export in a frontal zone within the California Current. J. Geophys. Res. Oceans 120, 4654–4669 (2015).
    Google Scholar 
    7.Arteaga, L. A., Pahlow, M., Bushinsky, S. M. & Sarmiento, J. L. Nutrient controls on export production in the Southern Ocean. Glob. Biogeochem. Cycles 33, 942–956 (2019).
    Google Scholar 
    8.Stukel, M. R. & Barbeau, K. A. Investigating the nutrient landscape in a coastal upwelling region and its relationship to the biological carbon pump. Geophys. Res. Lett. 47, e2020GL087351 (2020).
    Google Scholar 
    9.Hutchins, D. A. & Bruland, K. W. Iron-limited diatom growth and Si:N uptake ratios in a coastal upwelling regime. Nature 393, 561–564 (1998).
    Google Scholar 
    10.Takeda, S. Influence of iron availability on nutrient consumption ratio of diatoms in oceanic waters. Nature 393, 774–777 (1998).
    Google Scholar 
    11.Pichevin, L. E., Ganeshram, R. S., Geibert, W., Thunell, R. & Hinton, R. Silica burial enhanced by iron limitation in oceanic upwelling margins. Nat. Geosci. 7, 541–546 (2014).
    Google Scholar 
    12.Brzezinski, M. A. et al. A switch from Si(OH)4 to NO3− depletion in the glacial Southern Ocean. Geophys. Res. Lett. 29, 1564 (2002).13.Matsumoto, K., Sarmiento, J. L. & Brzezinski, M. A. Silicic acid leakage from the Southern Ocean: a possible explanation for glacial atmospheric pCO2. Glob. Biogeochem. Cycles 16, 1031 (2002).
    Google Scholar 
    14.Sarmiento, J. L., Gruber, N., Brzezinski, M. A. & Dunne, J. P. High-latitude controls of thermocline nutrients and low latitude biological productivity. Nature 427, 56–60 (2004).
    Google Scholar 
    15.Fuhrman, J. A. Marine viruses and their biogeochemical and ecological effects. Nature 399, 541–548 (1999).
    Google Scholar 
    16.Suttle, C. A. Marine viruses—major players in the global ecosystem. Nat. Rev. Microbiol. 5, 801–812 (2007).
    Google Scholar 
    17.Wilhelm, S. W. & Suttle, C. A. Viruses and nutrient cycles in the sea: viruses play critical roles in the structure and function of aquatic food webs. Bioscience 49, 781–788 (1999).
    Google Scholar 
    18.Kranzler, C. F. et al. Silicon limitation facilitates virus infection and mortality of marine diatoms. Nat. Microbiol. 4, 1790–1797 (2019).19.Laber, C. P. et al. Coccolithovirus facilitation of carbon export in the North Atlantic. Nat. Microbiol. 3, 537–547 (2018).
    Google Scholar 
    20.Yamada, Y., Tomaru, Y., Fukuda, H. & Nagata, T. Aggregate formation during the viral lysis of a marine diatom. Front. Mar. Sci. 5, 167 (2018).
    Google Scholar 
    21.Pelusi, A. et al. Virus-induced spore formation as a defense mechanism in marine diatoms. New Phytol. 229, 2251–2259 (2020).
    Google Scholar 
    22.Johnson, K. S., Chavez, F. P. & Friederich, G. E. Continental-shelf sediment as a primary source of iron for coastal phytoplankton. Nature 398, 697–700 (1999).
    Google Scholar 
    23.Harrison, P. J. Station Papa time series: insights into ecosystem dynamics. J. Oceanogr. 58, 259–264 (2002).
    Google Scholar 
    24.Marchetti, A. et al. Development of a molecular-based index for assessing iron status in bloom-forming pennate diatoms. J. Phycol. 53, 820–832 (2017).
    Google Scholar 
    25.Cohen, N. R. et al. Diatom transcriptional and physiological responses to changes in iron bioavailability across ocean provinces. Front. Mar. Sci. 4, 360 (2017).
    Google Scholar 
    26.Lampe, R. H. et al. Different iron storage strategies among bloom-forming diatoms. Proc. Natl Acad. Sci. USA 115, E12275–E12284 (2018).
    Google Scholar 
    27.King, A. L. & Barbeau, K. Evidence for phytoplankton iron limitation in the southern California Current System. Mar. Ecol. Prog. Ser. 342, 91–103 (2007).
    Google Scholar 
    28.Boyd, P. & Harrison, P. J. Phytoplankton dynamics in the NE subarctic Pacific. Deep Sea Res. II 46, 2405–2432 (1999).
    Google Scholar 
    29.Till, C. P. et al. The iron limitation mosaic in the California Current System: factors governing Fe availability in the shelf/near-shelf region. Limnol. Oceanogr. 64, 109–123 (2019).
    Google Scholar 
    30.Gozzelino, R., Jeney, V. & Soares, M. P. Mechanisms of cell protection by heme oxygenase-1. Annu. Rev. Pharmacol. Toxicol. 50, 323–354 (2010).
    Google Scholar 
    31.Richaud, C. & Zabulon, G. The heme oxygenase gene (pbsA) in the red alga Rhodella violacea is discontinuous and transcriptionally activated during iron limitation. Proc. Natl Acad. Sci. USA 94, 11736–11741 (1997).
    Google Scholar 
    32.Allen, A. E. et al. Whole-cell response of the pennate diatom Phaeodactylum tricornutum to iron starvation. Proc. Natl Acad. Sci. USA 105, 10438–10443 (2008).
    Google Scholar 
    33.Thamatrakoln, K., Korenovska, O., Niheu, A. K. & Bidle, K. D. Whole-genome expression analysis reveals a role for death-related genes in stress acclimation of the diatom Thalassiosira pseudonana. Environ. Microbiol. 14, 67–81 (2012).
    Google Scholar 
    34.Marchetti, A. et al. Comparative metatranscriptomics identifies molecular bases for the physiological responses of phytoplankton to varying iron availability. Proc. Natl Acad. Sci. USA 109, E317–E325 (2012).
    Google Scholar 
    35.De La Rocha, C. L., Hutchins, D. A., Brzezinski, M. A. & Zhang, Y. Effects of iron and zinc deficiency on elemental composition and silica production by diatoms. Mar. Ecol. Prog. Ser. 195, 71–79 (2000).
    Google Scholar 
    36.Leynaert, A. et al. Effect of iron deficiency on diatom cell size and silicic acid uptake kinetics. Limnol. Oceanogr. 49, 1134–1143 (2004).
    Google Scholar 
    37.van Creveld, S. G., Rosenwasser, S., Levin, Y. & Vardi, A. Chronic iron limitation confers transient resistance to oxidative stress in marine diatoms. Plant Physiol. 172, 968–979 (2016).
    Google Scholar 
    38.Slagter, H. A., Gerringa, L. J. A. & Brussaard, C. P. D. Phytoplankton virus production negatively affected by iron limitation. Front. Mar. Sci. 3, 156 (2016).
    Google Scholar 
    39.Drakesmith, H. & Prentice, A. Viral infection and iron metabolism. Nat. Rev. Microbiol. 6, 541–552 (2008).
    Google Scholar 
    40.Weinbauer, M. G., Arrieta, J. M., Griebler, C. & Herndlb, G. J. Enhanced viral production and infection of bacterioplankton during an iron-induced phytoplankton bloom in the Southern Ocean. Limnol. Oceanogr. 54, 774–784 (2009).
    Google Scholar 
    41.Torres, M. A., Jones, J. D. G. & Dangl, J. L. Reactive oxygen species signaling in response to pathogens. Plant Physiol. 141, 373–378 (2006).
    Google Scholar 
    42.Sheyn, U., Rosenwasser, S., Ben-Dor, S., Porat, Z. & Vardi, A. Modulation of host ROS metabolism is essential for viral infection of a bloom-forming coccolithophore in the ocean. ISME J. 10, 1742–1754 (2016).
    Google Scholar 
    43.Hyodo, K., Hashimoto, K., Kuchitsu, K., Suzuki, N. & Okuno, T. Harnessing host ROS-generating machinery for the robust genome replication of a plant RNA virus. Proc. Natl Acad. Sci. USA 114, E1282–E1290 (2017).
    Google Scholar 
    44.Espinoza, J. A., Gonzalez, P. A. & Kalergis, A. M. Modulation of antiviral immunity by heme oxygenase-1. Am. J. Pathol. 187, 487–493 (2017).
    Google Scholar 
    45.Durkin, C. A. et al. Frustule-related gene transcription and the influence of diatom community composition on silica precipitation in an iron-limited environment. Limnol. Oceanogr. 57, 1619–1633 (2012).
    Google Scholar 
    46.Assmy, P. et al. Thick-shelled, grazer-protected diatoms decouple ocean carbon and silicon cycles in the iron-limited Antarctic Circumpolar Current. Proc. Natl Acad. Sci. USA 110, 20633–20638 (2013).
    Google Scholar 
    47.Kimura, K. & Tomaru, Y. Effects of temperature and salinity on diatom cell lysis by DNA and RNA viruses. Aquat. Microb. Ecol. 79, 79–83 (2017).
    Google Scholar 
    48.Thamatrakoln, K. et al. Light regulation of coccolithophore host–virus interactions. New Phytol. 221, 1289–1302 (2019).
    Google Scholar 
    49.Zimmerman, A. E. et al. Metabolic and biogeochemical consequences of viral infection in aquatic ecosystems. Nat. Rev. Microbiol. 18, 21–34 (2020).
    Google Scholar 
    50.Brzezinski, M. A. et al. Co-limitation of diatoms by iron and silicic acid in the equatorial Pacific. Deep Sea Res. II 58, 493–511 (2011).
    Google Scholar 
    51.Boyer, T. P. et al. World Ocean Database 2013 (NOAA Atlas, 2013).52.Krause, J. W. et al. The interaction of physical and biological factors drives phytoplankton spatial distribution in the northern California Current. Limnol. Oceanogr. 65, 1974–1989 (2020).
    Google Scholar 
    53.Krause, J. W., Nelson, D. M. & Brzezinski, M. A. Biogenic silica production and the diatom contribution to primary production and nitrate uptake in the eastern equatorial Pacific Ocean. Deep Sea Res. II 58, 434–448 (2011).
    Google Scholar 
    54.Brzezinski, M. A. & Phillips, D. R. Evaluation of 32Si as a tracer for measuring silica production rates in marine waters. Limnol. Oceanogr. 42, 856–865 (1997).
    Google Scholar 
    55.Nelson, D. M., Brzezinski, M. A., Sigmon, D. E. & Franck, V. M. A seasonal progression of Si limitation in the Pacific sector of the Southern Ocean. Deep Sea Res. II 48, 3973–3995 (2001).
    Google Scholar 
    56.Krause, J. W., Brzezinski, M. A., Villareal, T. A. & Wilson, C. Increased kinetic efficiency for silicic acid uptake as a driver of summer diatom blooms in the North Pacific subtropical gyre. Limnol. Oceanogr. 57, 1084–1098 (2012).
    Google Scholar 
    57.Birol, I. et al. De novo transcriptome assembly with ABySS. Bioinformatics 25, 2872–2877 (2009).
    Google Scholar 
    58.Robertson, G. et al. De novo assembly and analysis of RNA-seq data. Nat. Methods 7, 909–912 (2010).
    Google Scholar 
    59.Gremme, G., Steinbiss, S. & Kurtz, S. GenomeTools: a comprehensive software library for efficient processing of structured genome annotations. IEEE/ACM Trans. Comput. Biol. Bioinform. 10, 645–656 (2013).
    Google Scholar 
    60.Kanehisa, M., Furumichi, M., Tanabe, M., Sato, Y. & Morishima, K. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res. 45, D353–D361 (2017).
    Google Scholar 
    61.Keeling, P. J. et al. The Marine Microbial Eukaryote Transcriptome Sequencing Project (MMETSP): illuminating the functional diversity of eukaryotic life in the oceans through transcriptome sequencing. PLoS Biol. 12, e1001889 (2014).
    Google Scholar 
    62.Patro, R., Duggal, G., Love, M. I., Irizarry, R. A. & Kingsford, C. Salmon provides fast and bias-aware quantification of transcript expression. Nat. Methods 14, 417–419 (2017).
    Google Scholar 
    63.R Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2013).64.Robinson, M. D., McCarthy, D. J. & Smyth, G. K. EdgeR: a bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2010).
    Google Scholar 
    65.Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B 57, 289–300 (1995).
    Google Scholar 
    66.Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer, 2016).67.Wagner, G. P., Kin, K. & Lynch, V. J. Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples. Theory Biosci. 131, 281–285 (2012).
    Google Scholar 
    68.Alexander, H., Jenkins, B. D., Rynearson, T. A. & Dyhrman, S. T. Metatranscriptome analyses indicate resource partitioning between diatoms in the field. Proc. Natl Acad. Sci. USA 112, E2182–E2190 (2015).
    Google Scholar 
    69.Lampe, R. H. et al. Divergent gene expression among phytoplankton taxa in response to upwelling. Environ. Microbiol. 20, 3069–3082 (2018).
    Google Scholar 
    70.Warnes, G. R. et al. gplots: Various R Programming Tools for Plotting Data https://cran.r-project.org/web/packages/gplots/index.html (2019).71.Oksanen, J. et al. vegan: Community Ecology Package https://cran.r-project.org/web/packages/vegan/index.html (2019).72.Thompson, J. D., Higgins, D. G. & Gibson, T. J. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 22, 4673–4680 (1994).
    Google Scholar 
    73.Kumar, S., Stecher, G. & Tamura, K. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol. Biol. Evol. 33, 1870–1874 (2016).
    Google Scholar 
    74.Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).
    Google Scholar 
    75.Matsen, F. A., Kodner, R. B. & Armbrust, E. V. pplacer: linear time maximum-likelihood and Bayesian phylogenetic placement of sequences onto a fixed reference tree. BMC Bioinform. 11, 538 (2010).
    Google Scholar 
    76.Shirai, Y. et al. Isolation and characterization of a single-stranded RNA virus infecting the marine planktonic diatom Chaetoceros tenuissimus Meunier. Appl. Environ. Microbiol. 74, 4022–4027 (2008).
    Google Scholar 
    77.Chen, L.-M., Edelstein, T. & McLachlan, J. Bonnemaisonia hamifera Hariot in nature and in culture. J. Phycol. 5, 211–220 (1969).
    Google Scholar 
    78.Harrison, P. J., Waters, R. E. & Taylor, F. J. R. A broad spectrum artificial sea water medium for coastal and open ocean phytoplankton. J. Phycol. 16, 28–35 (1980).
    Google Scholar 
    79.Berges, J. A., Franklin, D. J. & Harrison, P. J. Evolution of an artificial seawater medium: improvements in enriched seawater, artificial water over the last two decades. J. Phycol. 37, 1138–1145 (2001).
    Google Scholar 
    80.Sunda, W. G., Price, N. M. & Morel, F. M. M. Trace metal ion buffers and their use in culture studies. Algal Cult. Tech. 4, 35–63 (2005).
    Google Scholar 
    81.Tomaru, Y., Shirai, Y., Toyoda, K. & Nagasaki, K. Isolation and characterization of a single-stranded DNA virus infecting the marine planktonic diatom Chaetoceros tenuissimus. Aquat. Microb. Ecol. 64, 175–184 (2011).
    Google Scholar 
    82.Parsons, T. R. A Manual of Chemical & Biological Methods for Seawater Analysis (Elsevier, 2013).83.Krause, J. W., Lomas, M. W. & Nelson, D. M. Biogenic silica at the Bermuda Atlantic time-series study site in the Sargasso Sea: temporal changes and their inferred controls based on a 15-year record. Glob. Biogeochem. Cycles 23, GB3004 (2009).84.Gorbunov, M. Y. & Falkowski, P. G. Fluorescence induction and relaxation (FIRe) technique and instrumentation for monitoring photosynthetic processes and primary production in aquatic ecosystems. In Photosynthesis: Fundamental Aspects to Global Perspectives—Proc. 13th International Congress of Photosynthesis (eds Van der Est, A. & Bruce, D.) 1029–1031 (Allen and Unwin, 2004).85.Suttle, C. A. in Handbook of Methods in Aquatic Microbial Ecology (eds Kemp, P. F. et al.) 121–134 (CRC Press, 1993).86.Klee, A. J. A computer program for the determination of most probable number and its confidence limits. J. Microbiol. Methods 18, 91–98 (1993).
    Google Scholar  More

  • in

    Pollinator interaction flexibility across scales affects patch colonization and occupancy

    1.Kaiser-Bunbury, C. N. et al. Ecosystem restoration strengthens pollination network resilience and function. Nature 542, 223–227 (2017).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    2.Newbold, T. et al. Global effects of land use on local terrestrial biodiversity. Nature 520, 45–50 (2015).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    3.Memmott, J., Waser, N. M. & Price, M. V. Tolerance of pollination networks to species extinctions. Proc. R. Soc. B 271, 2605–2611 (2004).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    4.Kaiser-Bunbury, C. N., Muff, S., Memmott, J., Müller, C. B. & Caflisch, A. The robustness of pollination networks to the loss of species and interactions: a quantitative approach incorporating pollinator behaviour. Ecol. Lett. 13, 442–452 (2010).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    5.Ponisio, L. C., Gaiarsa, M. P. & Kremen, C. Opportunistic attachment assembles plant–pollinator networks. Ecol. Lett. 20, 1261–1272 (2017).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    6.Spiesman, B. J. & Gratton, C. Flexible foraging shapes the topology of plant–pollinator interaction networks. Ecology 97, 1431–1441 (2016).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    7.CaraDonna, P. J. et al. Interaction rewiring and the rapid turnover of plant–pollinator networks. Ecol. Lett. 20, 385–394 (2017).8.Tylianakis, J. M., Martínez-García, L. B., Richardson, S. J., Peltzer, D. A. & Dickie, I. A. Symmetric assembly and disassembly processes in an ecological network. Ecol. Lett. 21, 896–904 (2018).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    9.Yeakel, J. D. et al. Collapse of an ecological network in Ancient Egypt. Proc. Natl Acad. Sci. USA 111, 14472–14477 (2014).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    10.Burkle, L. A. & Alarcón, R. The future of plant–pollinator diversity: understanding interaction networks across time, space, and global change. Am. J. Bot. 98, 528–538 (2011).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    11.Cardinale, B. J. et al. Biodiversity loss and its impact on humanity. Nature 486, 59–67 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    12.Tylianakis, J. M. & Morris, R. J. Ecological networks across environmental gradients. Annu. Rev. Ecol. Syst. 48, 24–48 (2017).13.Bascompte, J. & Jordano, P. Mutualistic Networks (Princeton Univ. Press, 2013).14.MacLeod, M., Genung, M. A., Ascher, J. S. & Winfree, R. Measuring partner choice in plant–pollinator networks: using null models to separate rewiring and fidelity from chance. Ecology 97, 2925–2931 (2016).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    15.Fortuna, M. A., Nagavci, A., Barbour, M. A. & Bascompte, J. Partner fidelity and asymmetric specialization in ecological networks. Am. Nat. 196, 382–389 (2020).16.Bascompte, J. & Stouffer, D. B. The assembly and disassembly of ecological networks. Philos. Trans. R. Soc. B 364, 1781 (2009).Article 

    Google Scholar 
    17.Cirtwill, A. R., Roslin, T., Rasmussen, C., Olesen, J. M. & Stouffer, D. B. Between-year changes in community composition shape species’ roles in an Arctic plant–pollinator network. Oikos 127, 1163–1176 (2018).18.Mora, B. B., Shin, E., CaraDonna, P. J. & Stouffer, D. B. Untangling the seasonal dynamics of plant–pollinator communities. Nat. Commun. 11, 4086 (2020).19.Saavedra, S., Stouffer, D. B., Uzzi, B. & Bascompte, J. Strong contributors to network persistence are the most vulnerable to extinction. Nature 478, 233–235 (2011).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    20.Sebastián-González, E. Drivers of species role in avian seed-dispersal mutualistic networks. J. Anim. Ecol. 86, 878–887 (2017).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    21.Oliver, T. H. et al. Biodiversity and resilience of ecosystem functions. Trends Ecol. Evol. 30, 673–684 (2015).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    22.CaraDonna, P. J. et al. Seeing through the static: the temporal dimension of plant–animal mutualistic interactions. Ecol. Lett. 24, 149–161 (2020).23.Vázquez, D. P., Chacoff, N. P. & Cagnolo, L. Evaluating multiple determinants of the structure of plant–animal mutualistic networks. Ecology 90, 2039–2046 (2009).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    24.Vázquez, D. P., Blüthgen, N., Cagnolo, L. & Chacoff, N. P. Uniting pattern and process in plant–animal mutualistic networks: a review. Ann. Bot. 103, 1445–1457 (2009).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    25.Olesen, J. M., Bascompte, J., Dupont, Y. & Jordano, P. The modularity of pollination networks. Proc. Natl Acad. Sci. USA 104, 19891–19896 (2007).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    26.Brosi, B. J. & Briggs, H. M. Single pollinator species losses reduce floral fidelity and plant reproductive function. Proc. Natl Acad. Sci. USA 110, 13044–13048 (2013).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    27.Valdovinos, F. S. et al. Niche partitioning due to adaptive foraging reverses effects of nestedness and connectance on pollination network stability. Ecol. Lett. 19, 1277–1286 (2016).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    28.Rafferty, N. E., CaraDonna, P. J. & Bronstein, J. L. Phenological shifts and the fate of mutualisms. Oikos 124, 14–21 (2015).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    29.Winfree, R., Williams, N. M., Dushoff, J. & Kremen, C. Species abundance, not diet breadth, drives the persistence of the most linked pollinators as plant–pollinator networks disassemble. Am. Nat. 183, 600–611 (2014).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    30.Benjamin, F. E., Reilly, J. R. & Winfree, R. Pollinator body size mediates the scale at which land use drives crop pollination services. J. Appl. Ecol. 51, 440–449 (2014).Article 

    Google Scholar 
    31.Grab, H. et al. Habitat enhancements rescue bee body size from the negative effects of landscape simplification. J. Appl. Ecol. 56, 2144–2154 (2019).Article 

    Google Scholar 
    32.Fontaine, C., Collin, C. L. & Dajoz, I. Generalist foraging of pollinators: diet expansion at high density. J. Ecol. 96, 1002–1010 (2008).Article 

    Google Scholar 
    33.Stouffer, D. B., Sales-Pardo, M., Sirer, M. I. & Bascompte, J. Evolutionary conservation of species’ roles in food webs. Science 335, 1489–1492 (2012).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    34.Simmons, B. I. et al. Motifs in bipartite ecological networks: uncovering indirect interactions. Oikos 128, 154–170 (2019).Article 

    Google Scholar 
    35.Ponisio, L. C. Pyrodiversity promotes interaction complementarity and population resistance. Ecol. Evol. 10, 4431–4447 (2020).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    36.Grab, H., Blitzer, E. J., Danforth, B., Loeb, G. & Poveda, K. Temporally dependent pollinator competition and facilitation with mass flowering crops affects yield in co-blooming crops. Sci. Rep. 7, 45296 (2017).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    37.MacArthur, R. H. & Pianka, E. R. On optimal use of a patchy environment. Am. Nat. 100, 603–609 (1966).Article 

    Google Scholar 
    38.Mitchell, W. A. An optimal control theory of diet selection: the effects of resource depletion and exploitative competition. Oikos 58, 16–24 (1990).39.Robinson, B. W. & Wilson, D. S. Optimal foraging, specialization, and a solution to Liem’s paradox. Am. Nat. 151, 223–235 (1998).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    40.Valdovinos, F. S., Moisset de Espanés, P., Flores, J. D. & Ramos-Jiliberto, R. Adaptive foraging allows the maintenance of biodiversity of pollination networks. Oikos 122, 907–917 (2013).Article 

    Google Scholar 
    41.Ponisio, L. C. et al. A network perspective for community assembly. Front. Ecol. Environ. 7, 103 (2019).Article 

    Google Scholar 
    42.Benadi, G. & Gegear, R. J. Adaptive foraging of pollinators can promote pollination of a rare plant species. Am. Nat. 192, E81–E92 (2018).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    43.Vaudo, A. D., Patch, H. M., Mortensen, D. A., Tooker, J. F. & Grozinger, C. M. Macronutrient ratios in pollen shape bumble bee (Bombus impatiens) foraging strategies and floral preferences. Proc. Natl Acad. Sci. USA 113, E4035–E4042 (2016).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    44.Poisot, T., Stouffer, D. B. & Gravel, D. Beyond species: why ecological interaction networks vary through space and time. Oikos 124, 243–251 (2015).Article 

    Google Scholar 
    45.Fort, H., Vázquez, D. P. & Lan, B. L. Abundance and generalisation in mutualistic networks: solving the chicken-and-egg dilemma. Ecol. Lett. 19, 4–11 (2016).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    46.Bascompte, J., Jordano, P., Melián, C. J. & Olesen, J. M. The nested assembly of plant–animal mutualistic networks. Proc. Natl Acad. Sci. USA 100, 9383–9387 (2003).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    47.Lever, J. J., van Nes, E. H., Scheffer, M. & Bascompte, J. The sudden collapse of pollinator communities. Ecol. Lett. 17, 350–359 (2014).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    48.Bascompte, J. & Ferrera, A. in Theoretical Ecology: Concepts and Applications (eds McCann, A. S. & Gellner, G.) 93–115 (Oxford Univ. Press, 2020).49.Allesina, S. & Tang, S. Stability criteria for complex ecosystems. Nature 483, 205–208 (2012).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    50.Suweis, S., Simini, F., Banavar, J. R. & Maritan, A. Emergence of structural and dynamical properties of ecological mutualistic networks. Nature 500, 449–452 (2013).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    51.Naeem, S. & Li, S. Biodiversity enhances ecosystem reliability. Nature 390, 507–509 (1997).CAS 
    Article 

    Google Scholar 
    52.Winfree, R. et al. Species turnover promotes the importance of bee diversity for crop pollination at regional scales. Science 359, 791–793 (2018).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    53.Kremen, C. & M’Gonigle, L. K. Small-scale restoration in intensive agricultural landscapes supports more specialized and less mobile pollinator species. J. Appl. Ecol. 52, 602–610 (2015).Article 

    Google Scholar 
    54.Kremen, C., Williams, N. & Thorp, R. Crop pollination from native bees at risk from agricultural intensification. Proc. Natl Acad. Sci. USA 99, 16812–16816 (2002).55.Morandin, L., Long, R. & Kremen, C. Pest control and pollination cost–benefit analysis of hedgerow restoration in a simplified agricultural landscape. J. Econ. Entomol. 109, 1020–1027 (2016).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    56.Brittain, C., Williams, N., Kremen, C. & Klein, A. Synergistic effects of non-Apis bees and honey bees for pollination services. Proc. R. Soc. B 280, 1471–2954 (2013).Article 

    Google Scholar 
    57.Chao, A., Chazdon, R. L., Colwell, R. K. & Shen, T.-J. A new statistical approach for assessing similarity of species composition with incidence and abundance data. Ecol. Lett. 8, 148–159 (2005).Article 

    Google Scholar 
    58.Oksanen, J. et al. vegan: Community Ecology Package (2019); https://CRAN.R-project.org/package=vegan59.Anderson, M. J. et al. Navigating the multiple meanings of β diversity: a roadmap for the practicing ecologist. Ecol. Lett. 14, 19–28 (2011).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    60.Anderson, M. J., Ellingsen, K. E. & McArdle, B. H. Multivariate dispersion as a measure of beta diversity. Ecol. Lett. 9, 683–693 (2006).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    61.Mora, B. B., Cirtwill, A. R. & Stouffer, D. B. pymfinder: a tool for the motif analysis of binary and quantitative complex networks (2018); https://doi.org/10.1101/36470362.Simmons, B. I. et al. bmotif: a package for motif analyses of bipartite networks. Methods Ecol. Evol. 10, 695–701 (2019).Article 

    Google Scholar 
    63.Anderson, M. J. A new method for non-parametric multivariate analysis of variance. Austral Ecol. 26, 32–46 (2001).
    Google Scholar 
    64.Baker, N. J., Kaartinen, R., Roslin, T. & Stouffer, D. B. Species’ roles in food webs show fidelity across a highly variable oak forest. Ecography 38, 130–139 (2015).Article 

    Google Scholar 
    65.Bastolla, U. et al. The architecture of mutualistic networks minimizes competition and increases biodiversity. Nature 458, 1018–1020 (2009).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    66.Dormann, C., Gruber, B. & Fründ, J. Introducing the bipartite package: analysing ecological networks. R News 8, 8 (2008).
    Google Scholar 
    67.Dorazio, R. M., Kery, M., Royle, J. A. & Plattner, M. Models for inference in dynamic metacommunity systems. Ecology 91, 2466–2475 (2010).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    68.Ponisio, L. C., de Valpine, P., M’Gonigle, L. K. & Kremen, C. Proximity of restored hedgerows interacts with local floral diversity and species’ traits to shape long-term pollinator metacommunity dynamics. Ecol. Lett. 22, 1048–1060 (2019).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    69.Royle, J. A. & Kéry, M. A Bayesian state–space formulation of dynamic occupancy models. Ecology 88, 1813–1823 (2007).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    70.Ponisio, L. C., de Valpine, P., Michaud, N. & Turek, D. One size does not fit all: customizing MCMC methods for hierarchical models using NIMBLE. Ecol. Evol. 10, 2385–2416 (2020).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    71.de Valpine, P. et al. Programming with models: writing statistical algorithms for general model structures with NIMBLE. J. Comput. Graph. Stat. 26, 403–413 (2017).Article 

    Google Scholar 
    72.Shipley, B. Cause and Correlation in Biology: A User’s Guide to Path Analysis, Structural Equations and Causal Inference (Cambridge Univ. Press, 2004).73.Kremen, C., M’Gonigle, L. K. & Ponisio, L. C. Pollinator community assembly tracks changes in floral resources as restored hedgerows mature in agricultural landscapes. Front. Ecol. Evol. 6, 170 (2018).Article 

    Google Scholar 
    74.Ponisio, L. C., M’gonigle, L. K. & Kremen, C. On-farm habitat restoration counters biotic homogenization in intensively managed agriculture. Glob. Change Biol. 22, 704–715 (2016).Article 

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

    Google Scholar 
    76.R Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020); https://www.R-project.org/ More