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    Diversity of rice rhizosphere microorganisms under different fertilization modes of slow-release fertilizer

    Xin, F. et al. Large increases of paddy rice area, gross primary production, and grain production in Northeast China during 2000–2017. Sci. Total Environ. 711, 135–183. https://doi.org/10.1016/j.scitotenv.2019.135183 (2020).CAS 
    Article 

    Google Scholar 
    Du, B. et al. Deep fertilizer placement improves rice growth and yield in zero tillage. Appl. Ecol. Environ. Res. 16, 8045–8054. https://doi.org/10.15666/aeer/1606_80458054 (2018).Article 

    Google Scholar 
    Ni, B., Liu, M., Lü, S., Xie, L. & Wang, Y. Environmentally friendly slow-release nitrogen fertilizer. J. Agric. Food Chem. 59, 10169–10175. https://doi.org/10.1021/jf202131z (2011).CAS 
    Article 
    PubMed 

    Google Scholar 
    Zhu, C. et al. Mechanized transplanting with side deep fertilization increases yield and nitrogen use efficiency of rice in Eastern China. Sci. Rep. 9, 5653. https://doi.org/10.1038/s41598-019-42039-7 (2019).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Tilman, D., Cassman, K. G., Matson, P. A., Naylor, R. & Polasky, S. Agricultural sustainability and intensive production practices. Nature 418, 671–677. https://doi.org/10.1038/nature01014 (2002).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    Sharma, B. et al. Recycling of organic wastes in agriculture: An environmental perspective. Int. J. Environ. Res. 13, 409–429. https://doi.org/10.1007/s41742-019-00175-y (2019).CAS 
    Article 

    Google Scholar 
    Pan, S. et al. Benefits of mechanized deep placement of nitrogen fertilizer in direct-seeded rice in South China. Field Crops Res. 203, 139–149. https://doi.org/10.1016/j.fcr.2016.12.011 (2017).Article 

    Google Scholar 
    Shahena, S., Rajan, M., Chandran, V. & Mathew, L. Conventional methods of fertilizer release. In Controlled Release Fertilizers for Sustainable Agriculture (eds Lewu, F. B. et al.) 1–24 (Academic Press, 2021). https://doi.org/10.1016/B978-0-12-819555-0.00001-7.Chapter 

    Google Scholar 
    Wang, C. et al. Effects of different fertilization methods on ammonia volatilization from rice paddies. J. Clean. Prod. 295, 126299. https://doi.org/10.1016/j.jclepro.2021.126299 (2021).CAS 
    Article 

    Google Scholar 
    Wu, Q. et al. Effects of different types of slow- and controlled-release fertilizers on rice yield. J. Integr. Agric. 20, 1503–1514. https://doi.org/10.1016/S2095-3119(20)63406-2 (2021).CAS 
    Article 

    Google Scholar 
    Mahajan, G., Kumar, V. & Chauhan, B. S. Rice production in India. In Rice production worldwide (eds Chauhan, B. et al.) 53–91 (Springer International Publishing, 2017). https://doi.org/10.1007/978-3-319-47516-5_3.Chapter 

    Google Scholar 
    Opoku-Kwanowaa, Y., Furaha, R. K., Yan, L. & Wei, D. Effects of planting field on groundwater and surface water pollution in China. Clean-Soil Air Water 48, 1900452. https://doi.org/10.1002/clen.201900452 (2020).CAS 
    Article 

    Google Scholar 
    Lin, W. et al. The effects of chemical and organic fertilizer usage on rhizosphere soil in tea orchards. PLoS ONE 14, e0217018. https://doi.org/10.1371/journal.pone.0217018 (2019).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Sempeho, S. I., Kim, H. T., Mubofu, E. & Hilonga, A. Meticulous overview on the controlled release fertilizers. Adv. Chem. 1–16, 2014. https://doi.org/10.1155/2014/363071 (2014).Article 

    Google Scholar 
    Trenkel, M. E. Controlled-Release and Stabilized Fertilizers in Agriculture 1–156 (International Fertilizer Industry Association, 1997).
    Google Scholar 
    Lawrencia, D. et al. Controlled release fertilizers: A review on coating materials and mechanism of release. Plants 10, 238. https://doi.org/10.3390/plants10020238 (2021).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Tang, S. et al. Studies on the mechanism of single basal application of controlled-release fertilizers for increasing yield of rice (Oryza safiva L.). Agric. Sci. China 6, 586–596. https://doi.org/10.1016/S1671-2927(07)60087-X (2007).CAS 
    Article 

    Google Scholar 
    Zheng, Y. et al. Effects of mixed controlled release nitrogen fertilizer with rice straw biochar on rice yield and nitrogen balance in northeast china. Sci. Rep. 10, 9452. https://doi.org/10.1038/s41598-020-66300-6 (2020).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ransom, C. J., Jolley, V. D., Blair, T. A., Sutton, L. E. & Hopkins, B. G. Nitrogen release rates from slow- and controlled-release fertilizers influenced by placement and temperature. PLoS ONE 15, e0234544. https://doi.org/10.1371/journal.pone.0234544 (2020).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Soni, R., Kumar, V., Suyal, D. C., Jain, L. & Goel, R. Metagenomics of plant rhizosphere microbiome. In Understanding host-microbiome interactions—an omics approach (eds Singh, R. et al.) 193–205 (Springer, 2017). https://doi.org/10.1007/978-981-10-5050-3_12.Chapter 

    Google Scholar 
    Kumar, A. Phosphate solubilizing bacteria in agriculture biotechnology: Diversity, mechanism and their role in plant growth and crop yield. Int. J. Adv. Res. 4, 116–124. https://doi.org/10.21474/IJAR01/111 (2016).Article 

    Google Scholar 
    Arjun, J. K. Metagenomic analysis of bacterial diversity in the rice rhizosphere soil microbiome. Biotechnol. Bioinf. Bioeng 1, 361–367 (2011).
    Google Scholar 
    Zhao, J. et al. Responses of bacterial communities in arable soils in a rice-wheat cropping system to different fertilizer regimes and sampling times. PLoS ONE 9, e85301. https://doi.org/10.1371/journal.pone.0085301 (2014).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Huang, M. et al. Soil bacterial communities in three rice-based cropping systems differing in productivity. Sci. Rep. 10, 9867. https://doi.org/10.1038/s41598-020-66924-8 (2020).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hayatsu, M. A novel function of controlled-release nitrogen fertilizers. Microbes Environ. 29, 121–122. https://doi.org/10.1264/jsme2.ME2902rh (2014).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Aslam, Z., Yasir, M., Yoon, H. S., Jeon, C. O. & Chung, Y. R. Diversity of the bacterial community in the rice rhizosphere managed under conventional and no-tillage practices. J. Microbiol. 51, 747–756. https://doi.org/10.1007/s12275-013-2528-8 (2013).Article 
    PubMed 

    Google Scholar 
    Min, J. et al. Mechanical side-deep fertilization mitigates ammonia volatilization and nitrogen runoff and increases profitability in rice production independent of fertilizer type and split ratio. J. Clean. Prod. 316, 128370. https://doi.org/10.1016/j.jclepro.2021.128370 (2021).CAS 
    Article 

    Google Scholar 
    Ke, J. et al. Combined controlled-released nitrogen fertilizers and deep placement effects of N leaching, rice yield and N recovery in machine-transplanted rice. Agr. Ecosyst. Environ. 265, 402–412. https://doi.org/10.1016/j.agee.2018.06.023 (2018).CAS 
    Article 

    Google Scholar 
    Cardinale, B. J. et al. Effects of biodiversity on the functioning of trophic groups and ecosystems. Nature 443, 989–992. https://doi.org/10.1038/nature05202 (2006).ADS 
    CAS 
    Article 
    PubMed 

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

    Google Scholar 
    Li, P. et al. Different regulation of soil structure and resource chemistry under animal- and plant-derived organic fertilizers changed soil bacterial communities. Appl. Soil. Ecol. 165, 104020. https://doi.org/10.1016/j.apsoil.2021.104020 (2021).Article 

    Google Scholar 
    Wang, J. et al. Wheat and rice growth stages and fertilization regimes alter soil bacterial community structure, but not diversity. Front. Microbiol. https://doi.org/10.3389/fmicb.2016.01207 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Gu, Y., Zhang, X., Tu, S. & Lindström, K. Soil microbial biomass, crop yields, and bacterial community structure as affected by long-term fertilizer treatments under wheat-rice cropping. Eur. J. Soil Biol. 45, 239–246. https://doi.org/10.1016/j.ejsobi.2009.02.005 (2009).CAS 
    Article 

    Google Scholar 
    Niu, J. et al. Insight into the effects of different cropping systems on soil bacterial community and tobacco bacterial wilt rate: Effects of different copping systems. J. Basic Microbiol. 57, 3–11. https://doi.org/10.1002/jobm.201600222 (2017).CAS 
    Article 
    PubMed 

    Google Scholar 
    Wu, T., Qin, Y. & Li, M. Intercropping of tea (Camellia sinensis L.) and Chinese chestnut: Variation in the structure of rhizosphere bacterial communities. J. Soil Sci. Plant Nutr. 21, 2178–2190. https://doi.org/10.1007/s42729-021-00513-0 (2021).CAS 
    Article 

    Google Scholar 
    Li, Y. C. et al. Variations of rhizosphere bacterial communities in tea (Camellia sinensis L.) continuous cropping soil by high-throughput pyrosequencing approach. J. Appl. Microbiol. 121, 787–799. https://doi.org/10.1111/jam.13225 (2016).CAS 
    Article 
    PubMed 

    Google Scholar 
    Bei, Q., Moser, G., Müller, C. & Liesack, W. Seasonality affects function and complexity but not diversity of the rhizosphere microbiome in European temperate grassland. Sci. Total Environ. 784, 147036. https://doi.org/10.1016/j.scitotenv.2021.147036 (2021).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    You, J., Das, A., Dolan, E. M. & Hu, Z. Ammonia-oxidizing archaea involved in nitrogen removal. Water Res. 43, 1801–1809. https://doi.org/10.1016/j.watres.2009.01.016 (2009).CAS 
    Article 
    PubMed 

    Google Scholar 
    Chuang, S. et al. Potential effects of Rhodococcus qingshengii strain djl-6 on the bioremediation of carbendazim-contaminated soil and the assembly of its microbiome. J. Hazard. Mater. 414, 125496. https://doi.org/10.1016/j.jhazmat.2021.125496 (2021).CAS 
    Article 
    PubMed 

    Google Scholar 
    Luo, D. et al. The anaerobic oxidation of methane in paddy soil by ferric iron and nitrate, and the microbial communities involved. Sci. Total Environ. 788, 147773. https://doi.org/10.1016/j.scitotenv.2021.147773 (2021).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    Premnath, N. et al. A crucial review on polycyclic aromatic hydrocarbons—Environmental occurrence and strategies for microbial degradation. Chemosphere 280, 130608. https://doi.org/10.1016/j.chemosphere.2021.130608 (2021).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    Makino, A. Photosynthesis, grain yield, and nitrogen utilization in rice and wheat. Plant Physiol. 155, 125–129. https://doi.org/10.1104/pp.110.165076 (2011).CAS 
    Article 
    PubMed 

    Google Scholar 
    Sun, L., Lu, Y., Yu, F., Kronzucker, H. J. & Shi, W. Biological nitrification inhibition by rice root exudates and its relationship with nitrogen-use efficiency. New Phytol. 212, 646–656. https://doi.org/10.1111/nph.14057 (2016).CAS 
    Article 
    PubMed 

    Google Scholar 
    Coskun, D., Britto, D. T., Shi, W. & Kronzucker, H. J. How plant root exudates shape the nitrogen cycle. Trends Plant Sci. 22, 661–673. https://doi.org/10.1016/j.tplants.2017.05.004 (2017).CAS 
    Article 
    PubMed 

    Google Scholar 
    Qiang, S. et al. Deep placement of mixed controlled-release and conventional urea improves grain yield, nitrogen use efficiency of rainfed spring maize. Arch. Agronomy Soil Sci. 67, 1848–1858. https://doi.org/10.1080/03650340.2020.1817396 (2021).CAS 
    Article 

    Google Scholar 
    Hou, P. et al. Deep fertilization with controlled-release fertilizer for higher cereal yield and N utilization in paddies: The optimal fertilization depth. Agronomy J. https://doi.org/10.1002/agj2.20772 (2021).Article 

    Google Scholar 
    Zhu, S., Vivanco, J. M. & Manter, D. K. Nitrogen fertilizer rate affects root exudation, the rhizosphere microbiome and nitrogen-use-efficiency of maize. Appl. Soil. Ecol. 107, 324–333. https://doi.org/10.1016/j.apsoil.2016.07.009 (2016).Article 

    Google Scholar  More

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    Quantifying fish otolith mineralogy for trace-element chemistry studies

    Morrongiello, J. R., Thresher, R. E. & Smith, D. C. Aquatic biochronologies and climate change. Nat. Clim. Change 2, 849 (2012).ADS 
    Article 

    Google Scholar 
    Pracheil, B. M., Hogan, J. D., Lyons, J. & McIntyre, P. B. Using hard-part microchemistry to advance conservation and management of North American freshwater fishes. Fisheries 39, 451–465 (2014).Article 

    Google Scholar 
    Starrs, D., Ebner, B. C. & Fulton, C. J. All in the ears: Unlocking the early life history biology and spatial ecology of fishes. Biol. Rev. 91, 86–105 (2016).Article 

    Google Scholar 
    Limburg, K. E. Otolith strontium traces environmental history of subyearling American shad Alosa sapidissima. Mar. Ecol. Progr. Ser. 119, 25–35 (1995).ADS 
    Article 

    Google Scholar 
    Kennedy, B. P., Klaue, A., Blum, J. D., Folt, C. L. & Nislow, K. H. Reconstructing the lives of fish using Sr isotopes in otoliths. Can. J. Fish. Aquat. Sci. 59, 925–929 (2002).Article 

    Google Scholar 
    Hogan, J. D., Blum, M. J., Gilliam, J. F., Bickford, N. & McIntyre, P. B. Consequences of alternative dispersal strategies in a putatively amphidromous fish. Ecology 95, 2397–2408 (2014).Article 

    Google Scholar 
    Carlson, A. K., Phelps, Q. E. & Graeb, B. D. S. Chemistry to conservation: using otoliths to advance recreational and commercial fisheries management. J. Fish Biol. 90, 505–527 (2017).CAS 
    Article 

    Google Scholar 
    Campana, S. E. Chemistry and composition of fish otoliths: pathways, mechanisms and applications. Mar. Ecol. Prog. Ser. 188, 263–297 (1999).ADS 
    CAS 
    Article 

    Google Scholar 
    Pracheil, B. M. et al. Sturgeon and paddlefish (Acipenseridae) sagittal otoliths are composed of the calcium carbonate polymorphs vaterite and calcite. J. Fish Biol. 90, 549–558 (2017).CAS 
    Article 

    Google Scholar 
    Pracheil, B. M., George, R. & Chakoumakos, B. C. Significance of otolith calcium carbonate crystal structure diversity to microchemistry studies. Rev. Fish Biol. Fish. 29, 569–588 (2019).Article 

    Google Scholar 
    Nehrke, G., Poigner, H., Wilhelms-Dick, D., Brey, T. & Abele, D. Coexistence of three calcium carbonate polymorphs in the shell of the Antarctic clam Laternula elliptica. Geochem. Geophys. Geosyst. 13(5), 15. https://doi.org/10.1029/2011GC003996 (2012).CAS 
    Article 

    Google Scholar 
    Wassenburg, J. A. et al. Determination of aragonite trace element distribution coefficients from speleothem calcite–aragonite transitions. Geochim. Cosmochim. Acta 190, 347–367 (2016).ADS 
    CAS 
    Article 

    Google Scholar 
    Tzeng, W. N. et al. Misidentification of the migratory history of anguillid eels by Sr/Ca ratios of vaterite otoliths. Mar. Ecol. Prog. Ser. 348, 285–295 (2007).ADS 
    CAS 
    Article 

    Google Scholar 
    Gauldie, R. W. Effects of temperature and vaterite replacement on the chemistry of metal ions in the otoliths of Oncorhynchus tshawytscha. Can. J. Fish. Aquat. Sci. 53, 2015–2026 (1996).CAS 
    Article 

    Google Scholar 
    Reimer, T. et al. Rapid growth causes abnormal vaterite formation in farmed fish otoliths. J. Exp. Biol. 220, 2965–2969 (2017).PubMed 

    Google Scholar 
    Coll-Lladó, C., Giebichenstein, J., Webb, P. B. & Bridges, C. R. Ocean acidification promotes otolith growth and calcite deposition in gilthead sea bream (Sparus aurata) larvae. Sci. Rep. 8, 8384 (2018).ADS 
    Article 

    Google Scholar 
    Loeppky, A. R. et al. Influence of ontogenetic development, temperature, and pCO2 on otolith calcium carbonate polymorph composition in sturgeons. Sci. Rep. 11(1), 1–10 (2021).Article 

    Google Scholar 
    Melancon, S., Fryer, B. J., Ludsin, S. A., Gagnon, J. E. & Yang, Z. Effects of crystal structure on the uptake of metals by lake trout (Salvelinus namaycush) otoliths. Can. J. Fish. Aquat. Sci. 62, 2609–2619 (2005).CAS 
    Article 

    Google Scholar 
    Veinott, G. I., Porter, T. R. & Nasdala, L. Using Mg as a proxy for crystal structure and Sr as an indicator of marine growth in vaterite and aragonite otoliths of aquaculture rainbow trout. Trans. Am. Fish. Soc. 138, 1157–1165 (2009).CAS 
    Article 

    Google Scholar 
    Loeppky, A. R., Chakoumakos, B. C., Pracheil, B. M. & Anderson, W. G. Otoliths of sub-adult Lake Sturgeon Acipenser fulvescens contain aragonite and vaterite calcium carbonate polymorphs. J. Fish Biol. 94, 810–814 (2019).CAS 
    Article 

    Google Scholar 
    Vignon, M. When the presence of a vateritic otolith has morphological effect on its aragonitic partner: Trans-lateral compensation induces bias in microecological patterns in one-side-only vateritic otolith. Can. J. Fish. Aquat. Sci. 77, 285–294 (2020).Article 

    Google Scholar 
    Clarke, A. D., Telmer, K. H. & Mark Shrimpton, J. Elemental analysis of otoliths, fin rays and scales: A comparison of bony structures to provide population and life-history information for the Arctic grayling (Thymallus arcticus). Ecol. Freshw. Fish 16, 354–361 (2007).Article 

    Google Scholar 
    Campana, S. E., Chouinard, G. A., Hanson, J. M., Frechet, A. & Brattey, J. Otolith elemental fingerprints as biological tracers of fish stocks. Fish. Res. 46, 343–357 (2000).Article 

    Google Scholar 
    Gauldie, R. W. Continuous and discontinuous growth in the otolith of Macruronus novaezelandiae (Merlucciidae: Teleostei). J. Morphol. 216(3), 271–294 (1993).CAS 
    Article 

    Google Scholar 
    Long, J. M., Snow, R. A., Pracheil, B. M. & Chakoumakos, B. C. Morphology and composition of Goldeye (Hiodontidae; Hiodon alosoides) otoliths. J. Morphol. 282(4), 511–519 (2021).CAS 
    Article 

    Google Scholar 
    Chakoumakos, B. C., Pracheil, B. M., Koenigs, R. P., Bruch, R. M. & Feygenson, M. Empirically testing vaterite structural models using neutron diffraction and thermal analysis. Sci. Rep. 6, 36799 (2016).ADS 
    CAS 
    Article 

    Google Scholar 
    David, A. W., Grimes, C. B. & Isely, J. J. Vaterite sagittal otoliths in hatchery-reared juvenile red drums. Progres. Fish-Cult. 56(4), 301–303 (1994).Article 

    Google Scholar 
    Tomás, J. & Geffen, A. J. Morphometry and composition of aragonite and vaterite otoliths of deformed laboratory reared juvenile herring from two populations. J. Fish Biol. 63(6), 1383–1401 (2003).Article 

    Google Scholar 
    Kamhi, S. R. On the structure of vaterite CaCO3. Acta Crystallogr. A 16(8), 770–772 (1963).CAS 
    Article 

    Google Scholar 
    Kartnaller, V., Ribeiro, E. M., Venancio, F., Rosariob, F. & Cajaiba, J. Preferential incorporation of sulfate into calcite polymorphs during calcium carbonate precipitation: an experimental approach. CrystEngComm 20, 2241–2244 (2018).CAS 
    Article 

    Google Scholar 
    Paquette, J. & Reeder, R. J. Relationship between surface structure, growth mechanism, and trace element incorporation in calcite. Geochim. Cosmochim. Acta 59(4), 735–749 (1995).ADS 
    CAS 
    Article 

    Google Scholar 
    Hüssy, K. & Mosegaard, H. Atlantic cod (Gadus morhua) growth and otolith accretion characteristics modelled in a bioenergetics context. Can. J. Fish. Aquat. Sci. 61(6), 1021–1031 (2004).Article 

    Google Scholar 
    Fablet, R. et al. Shedding light on fish otolith biomineralization using a bioenergetic approach. PLoS ONE 6(11), e27055 (2011).ADS 
    CAS 
    Article 

    Google Scholar 
    Naslund, A. W., Davis, B. E., Hobbs, J. A., Fangue, N. A. & Todgham, A. E. Warming, not CO2-acidified seawater, alters otolith development of juvenile Antarctic emerald rockcod (Trematomus bernacchii). Polar Biol. 44(9), 1917–1923 (2021).Article 

    Google Scholar 
    Coll-Lladó, C. et al. Pilot study to investigate the effect of long-term exposure to high pCO2 on adult cod (Gadus morhua) otolith morphology and calcium carbonate deposition. Fish Physiol. Biochem. 48, 1879–1891 (2021).Article 

    Google Scholar 
    Söllner, C. et al. Control of crystal size and lattice formation by starmaker in otolith biomineralization. Science 302(5643), 282–286 (2003).ADS 
    Article 

    Google Scholar 
    Rodriguez-Carvajal, J. FULLPROF: A program for Rietveld refinement and pattern matching analysis. In Satellite Meeting on Powder Diffraction of the XV Congress of the IUCr (Vol. 127) (1990).Roisnel, T. & Rodríquez-Carvajal, J. WinPLOTR: A windows tool for powder diffraction pattern analysis. Mater. Sci. 378(1), 118–123 (2001).
    Google Scholar 
    Momma, K. & Izumi, F. VESTA: A three-dimensional visualization system for electronic and structural analysis. J. Appl. Crystallogr. 41(3), 653–658 (2008).CAS 
    Article 

    Google Scholar 
    Slater, J. C. Atomic radii in crystals. J. Chem. Phys. 41(10), 3199–3205 (1964).ADS 
    CAS 
    Article 

    Google Scholar  More

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    Crop–livestock integration enhanced soil aggregate-associated carbon and nitrogen, and phospholipid fatty acid

    Aggregate size distributionAs hypothesized, the improved soil aggregation was observed under ICL, which is attributed to the presence of animals resulting in higher organic matter contents of total C and N fractions that can significantly enhance soil health over time32. Moreover, well-aggregated soils as observed under ICL ( > 4 mm) at site 1 and NE (2–4 mm) at site 2 have a greater potential of retaining their structure and may have higher macropores, which facilitate sustained root growth than soils with low aggregation such as under CNT (corn–soybean without grazing or CC) in this study. It also explains the significance of ICL systems with no-tillage and undisturbed grassland, where the formation of stable macroaggregates may occur as a result of incorporation of plant residues, stimulation of root exudates and increased biological activity. Furthermore, it was noticed that ICL system not only enhanced the macroaggregates but accentuated the presence of microaggregates due to persistent binding agents, which are critical in SOC protection against microbial decomposition. When integrating grazing livestock into crop rotation, soil aggregation is typically improved under moderate and controlled grazing than the high intensity grazing systems33. Compared to the long-term sites ( > 30 years), short-term site 4 did not result in discernible effects of grazing or CC on soil aggregation. However, within this short-term study, grazed pasture mix was able to enhance aggregation of 1–2 and 2–4 mm sized aggregates compared with oats, oats with CC, oats with CC and grazing. To observe the influence of CC and grazing on  > 4 mm or  4 mm) under ICL at site 1 resulted in 1.3–1.5 times significantly higher SOC concentration than NE and CNT. The greater concentration of SOC and N in ICL and NE is attributed to the lack of soil disturbance, crop residue retention, and rhizodeposition, which reduces macroaggregate turnover rate14. At site 3, NE enhanced aggregate-associated C and N concentrations and performed significantly better than both ICL and CNT treatments. The higher C and N accrual in the NE than ICL and CNT, especially at site 3, can be due to massive root systems, long-term establishment and absence of cultivation, which contributes to enhanced soil quality, while reducing nutrient vulnerability to loss by oxidation18,36. For short-term study at site 4, insignificant differences in aggregate-associated SOC suggested that longer study period of at least  > 5 years is required for SOC to respond to grazing and cover crop management. The higher total N under ICL and NE can also be due to the presence of legumes, and brassicas in CC, which are effective at recycling N and may have helped in scavenging N.An overall increase in C and N cycling under ICL and NE systems has been attributed to ingested pasture being converted into urine and manure. Under these systems, livestock catalyze nutrient cycling by breakdown of complex plant molecules, greater soil incorporation and decomposition of plant residues and soil organic matter, which can maintain or even improve soil fertility by production of organic acids such as fulvic and humic acids6,8,19. Moreover, grazing stimulates the carbohydrate exudation from grass roots, which is mostly composed of polysaccharides, a C-O alkyl source37. The enhanced C concentration under ICL and NE can also be associated with higher MWD. Integrated system cool-season pasture and winter CC had significantly higher total C and N than the non-integrated continuous corn in previous study6. The results from another integrated system study7 showed that soybean and oat-Italian ryegrass CC increased total C (1.16 Mg ha−1 yr−1) and N stocks (0.12 Mg ha−1 yr−1) under 7 year study period. It is previously reported that ICL system contains labile organic matter pools10,38, subsequently showing higher C stocks and greater root densities near soil-surface, which promotes aggregate-associated C stabilization18,39,40, higher infiltration rates, thus providing likely benefits to soil function linked to erosion control and soil water relations41.Soil microbial community compositionTotal bacterial biomass, AM fungi, and PLFA were enhanced under NE, which can be result of accumulation of organic residues and higher pasture root mass7,32, pasture being grazed can promote exudation of organic compounds by roots, serving as energy sources for microorganisms. The consistent increase in microbial population under NE can also be result of increased SOC and N, however, the same does not hold true for ICL system, where despite observing greater SOC and N, a significant decrease in the microbial population at site 2 was noticed. The enhanced total PLFA under NE system at site 2 is due to concomitant increase in AM fungi, gram (−), fungal/bacterial ratio, and total bacterial biomass compared to ICL. The fungal to bacterial ratio was reduced under ICL compared to NE at sites 1 and 2, pertaining to relatively low abundance of the fungal fatty acid 18:2ɷ6 in grazed system as compared to unmanaged grassland. This finding corroborates the notion that livestock-grazing systems contain bacterial-based decomposition channels and are mostly dominated by gram (+) bacteria and that the fungal population is comparatively more important in decomposer food-webs of native grasslands. These results coincide with previous studies42,43. Moreover, the increase in fungal to bacterial ratios under NE system in contrast to ICL at sites 1 and 2 can relate to modifications in soil health with C sequestration, as fungal populations incline towards higher C assimilation proficiencies and greater storage of metabolized C than bacterial populations9,44. The grazing intensity also plays a significant role in bacterial and fungal presence. It is previously reported that high grazing intensity had greater bacterial PLFA concentration than the low grazing counterparts in grassland systems45. It is considered that under heavily grazed sites in grasslands, bacteria-based energy channels of decomposition dominate other microbial communities, while fungi can successfully enable decomposition in both slightly grazed and non-grazed systems43. Grazed pasture mix at short-term study site 4 showed 12–21% higher total PLFA than the oats, oats with CC, oats with CC + grazing systems. It is also possible that this increased total PLFA at site 4 under grazed pasture mix contributed to enhancing the 1–2 and 2–4 mm sized aggregates compared to other treatments. It indicated that though physicochemical properties can take longer ( > 8–15 years) in significantly responding to changes in management systems, soil microbial community and structure may show a rapid response (~ 3 years), thus it can be used as an early indicator while assessing the variations in soil health18,46.Overall, NE exemplified the undisturbed grazed mixture with a greater microbial population at sites 1, 2, and 3, when compared to other agricultural systems. Our findings coincide with previous studies where pasture systems performed better than the agricultural soil, in terms of, showing greater microbial biomass and fatty acid signatures related to bacterial and fungal populations, which is mostly attributed to greater surface coverage and absence of tillage practices in pasture systems9,47,48. Lower soil microbial communities under ICL system than native Cerrado pasture have been found previously because of reduced soil porosity and macropore continuity resulting in restricted gas diffusion and water movement18.Although the AM fungi abundance was not significant for sites 3 and 4, and significantly lower for ICL system than NE at sites 1 and 2, it should be taken into consideration that FAME analysis cannot reflect species-level changes for fungi and/or bacteria and the variations in microbial community structure for ICL system can be due to changes in abundance and distribution among microbial groups. For example, in a previous study9, while increased bacterial population was observed for continuous cotton compared to the ICL system, however, pyrosequencing for bacterial diversity assessment demonstrated disparities between both systems, where greater Proteobacteria was seen under ICL system than continuous cotton. Numerous factors such as degree of disturbance, pH level, bulk density, porosity, soil water content, C and N distribution, and residue positioning regulate the amount of bacterial and fungal biomass in agroecosystems18,49. Arbuscular mycorrhizal fungi are responsible for formation of macroaggregates ( > 0.25 mm) by producing a glycoprotein called glomalin, which is present abundantly in natural and agricultural systems. However, increased grazing intensity, use of excess fertilizers and fungicides can directly or indirectly reduce mycorrhizal population by influencing soil organisms accountable for converting soil organic matter into plant nutrients38. Animals may also cause moderate soil compaction affecting the fungal biodiversity and soil pore space6,38.Relationship among measured soil propertiesBased on PCA, it is derived that integrated crop–livestock and natural ecosystem of native grassland can provide substrate for the microbial composition and enhance aggregate-associated C and N fractions. A positive correlation between SOC and microbial communities suggested the inclination of microbes to affect SOC and N turnover and vice-versa through interaction with crop–livestock grazing, vegetation, and soil properties. Fungi exhibited insignificant responses to changes in soil pH and bulk density than bacteria because chitinous cell walls make fungi more resistant and resilient to variations in soil conditions50,51. A reduction in gram (−) bacteria may indicate the presence of stressed soil conditions due to pH and increased bulk density, which has previously been observed in other studies52,53. A significant negative correlation between bulk density and SOC, N, gram (−), actinomycetes, total bacteria, and total PLFA indicated that the microorganisms influenced the soil compaction and related SOC and N. Moreover, positive correlation between SOC and microbial composition suggested that microbes can influence C sequestration in the soil via a shift in community structure. Microbial composition is influenced by soil C, whereas N is a critical biogenic element that improves microbial growth and their ability to utilize soil C54. More

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    Morpho-physiological adaptations of Leptocylindrus aporus and L. hargravesii to phosphate limitation in the northern Adriatic

    Nanjappa, D., Kooistra, W. H. & Zingone, A. A reappraisal of the genus Leptocylindrus (B acillariophyta), with the addition of three species and the erection of Tenuicylindrus gen. nov. J. Phycol. 49, 917–936 (2013).Article 

    Google Scholar 
    Hasle, G. & Syvertsen, E. (Academic Press, 1997).Gómez, F., Simão, T. L., Utz, L. R. & Lopes, R. M. The nature of the diatom Leptocylindrus mediterraneus (Bacillariophyceae), host of the enigmatic symbiosis with the stramenopile Solenicola setigera. Phycologia 55, 265–273 (2016).Article 

    Google Scholar 
    Ivančić, I. et al. Survival mechanisms of phytoplankton in conditions of stratification-induced deprivation of orthophosphate: Northern Adriatic case study. Limnol. Oceanogr. https://doi.org/10.4319/lo.2012.57.6.0000 (2012).Article 

    Google Scholar 
    Ivančić, I. et al. Alkaline phosphatase activity related to phosphorus stress of microphytoplankton in different trophic conditions. Prog. Oceanogr. 146, 175–186. https://doi.org/10.1016/j.pocean.2016.07.003 (2016).ADS 
    Article 

    Google Scholar 
    Smodlaka, N. Primary production of the organic matter as an indicator of the eutrophication in the northern Adriatic sea. Sci. Total Environ. 56, 211–220. https://doi.org/10.1016/0048-9697(86)90325-6 (1986).ADS 
    CAS 
    Article 

    Google Scholar 
    Degobbis, D. & Gilmartin, M. Nitrogen, phosphorus, and biogenic silicon budgets for the northern Adriatic Sea. Oceanol. Acta 13, 31–45 (1990).CAS 

    Google Scholar 
    Zavatarelli, M., Raicich, F., Bregant, D., Russo, A. & Artegiani, A. Climatological biogeochemical characteristics of the Adriatic Sea. J. Mar. Syst. 18, 227–263 (1998).Article 

    Google Scholar 
    Socal, G. et al. Hydrological and biogeochemical features of the Northern Adriatic Sea in the period 2003–2006. Mar. Ecol. 29, 449–468. https://doi.org/10.1111/J.1439-0485.2008.00266.X (2008).ADS 
    CAS 
    Article 

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

    Google Scholar 
    Marić, D. et al. Phytoplankton response to climatic and anthropogenic influences in the north-eastern Adriatic during the last four decades. Estuar. Coast. Shelf Sci. 115, 98–112. https://doi.org/10.1016/J.Ecss.2012.02.003 (2012).ADS 
    Article 

    Google Scholar 
    Smodlaka Tanković, M. et al. Insights into the life strategy of the common marine diatom Chaetoceros peruvianus Brightwell. PLoS ONE 13, e0203634 (2018).Article 

    Google Scholar 
    Marić Pfannkuchen, D. et al. The ecology of one cosmopolitan, one newly introduced and one occasionally advected species from the genus Skeletonema in a highly structured ecosystem, the northern Adriatic. Microb. Ecol. 75, 674–687 (2018).Article 

    Google Scholar 
    Benitez-Nelson, C. R. The biogeochemical cycling of phosphorus in marine systems. Earth Sci. Rev. 51, 109–135 (2000).ADS 
    CAS 
    Article 

    Google Scholar 
    Paytan, A. & McLaughlin, K. The oceanic phosphorus cycle. Chem. Rev. 107, 563–576 (2007).CAS 
    Article 

    Google Scholar 
    Price, N. M. & Morel, F. M. Role of extracellular enzymatic reactions in natural waters. (1990).Hoppe, H.-G. Phosphatase activity in the sea. Hydrobiologia 493, 187–200 (2003).CAS 
    Article 

    Google Scholar 
    Fields, M. W. et al. Sources and resources: Importance of nutrients, resource allocation, and ecology in microalgal cultivation for lipid accumulation. Appl. Microbiol. Biotechnol. 98, 4805–4816 (2014).CAS 
    Article 

    Google Scholar 
    Van Mooy, B. A. S. et al. Phytoplankton in the ocean use non-phosphorus lipids in response to phosphorus scarcity. Nature 458, 69–72 (2009).ADS 
    Article 

    Google Scholar 
    Gašparović, B. et al. Adaptation of marine plankton to environmental stress by glycolipid accumulation. Mar. Environ. Res. 92, 120–132. https://doi.org/10.1016/J.Marenvres.2013.09.009 (2013).Article 
    PubMed 

    Google Scholar 
    Gašparović, B. et al. Factors influencing particulate lipid production in the East Atlantic Ocean. Deep Sea Res. Part 1 Oceanogr. Res. Pap. 89, 56–67. https://doi.org/10.1016/j.dsr.2014.04.005 (2014).CAS 
    Article 

    Google Scholar 
    Finenko, Z. & Krupatkina-Akinina, D. Effect of inorganic phosphorus on the growth rate of diatoms. Mar. Biol. 26, 193–201 (1974).CAS 
    Article 

    Google Scholar 
    Lombardi, A. & Wangersky, P. Influence of phosphorus and silicon on lipid class production by the marine diatom Chaetoceros gracilis grown in turbidostat cage cultures. Mar. Ecol. Prog. Ser. Oldendorf 77, 39–47 (1991).ADS 
    CAS 
    Article 

    Google Scholar 
    Pan, Y., Subba Rao, D. V. & Mann, K. H. Changes in domoic acid production and cellular chemical composition of the toxigenic diatom Pseudo-nitzschia miltiseries under phosphate limitation. J. Phycol. 32, 371–381 (1996).CAS 
    Article 

    Google Scholar 
    Liu, S., Guo, Z., Li, T., Huang, H. & Lin, S. Photosynthetic efficiency, cell volume, and elemental stoichiometric ratios in Thalassirosira weissflogii under phosphorus limitation. Chin. J. Oceanol. Limnol. 29, 1048 (2011).CAS 
    Article 

    Google Scholar 
    Alipanah, L. et al. Molecular adaptations to phosphorus deprivation and comparison with nitrogen deprivation responses in the diatom Phaeodactylum tricornutum. PLoS ONE 13, e0193335 (2018).Article 

    Google Scholar 
    Guillard, R. R. L. in Culture of Marine Invertebrate Animals (eds W.L. Smith & M.H. Chanley) 29–60 (Plenum Press, New York, USA, 1975).Utermöhl, H. Zur Vervollkommnung der quantitativen Phytoplankton-Methodik. Mitteilungen des Internationale Vereinigung für theoretische und angewandte Limnologie 9, 1–38 (1958).
    Google Scholar 
    Keller, M. D., Bellows, W. K. & Guillard, R. R. L. Microwave treatment for sterilization of phytoplankton culture media. J. Exp. Mar. Biol. Ecol. 117, 279–283. https://doi.org/10.1016/0022-0981(88)90063-9 (1988).Article 

    Google Scholar 
    Gračan, R., Mladineo, I., Kučinić, M., Lazar, B. & Lacković, G. Gastrointestinal helminth community of loggerhead sea turtle Caretta caretta in the Adriatic Sea. Dis. Aquat. Org. 99, 227–236 (2012).Article 

    Google Scholar 
    Anonymous, X. Proposals for a standardization of diatom terminology and diagnoses. Nova Hedwig. Beih. 53, 323–354 (1975).
    Google Scholar 
    Ross, R. et al. An amended terminology for the siliceous components of the diatom cell. (1979).Hillebrand, H., Dürselen, C. D., Kirschtel, D., Pollingher, U. & Zohary, T. Biovolume calculation for pelagic and benthic microalgae. J. Phycol. 35, 403–424 (1999).Article 

    Google Scholar 
    Alverson, A. J. Molecular systematics and the diatom species. Protist 159, 339 (2008).Article 

    Google Scholar 
    Macgillivary, M. & Kaczmarska, I. Survey of the Efficacy of a Short Fragment of the rbcL Gene as a Supplemental DNA Barcode for Diatoms. Vol. 58 (2011).Zimmermann, J., Jahn, R. & Gemeinholzer, B. Barcoding diatoms: Evaluation of the V4 subregion on the 18S rRNA gene, including new primers and protocols. Org. Divers. Evol. 11, 173–192 (2011).Article 

    Google Scholar 
    Kearse, M. et al. Geneious basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics (Oxford, England) 28, 1647–1649. https://doi.org/10.1093/bioinformatics/bts199 (2012).Article 

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

    Google Scholar 
    Clark, K., Karsch-Mizrachi, I., Lipman, D. J., Ostell, J. & Sayers, E. W. GenBank. Nucleic Acids Res. 44, D67–D72 (2016).CAS 
    Article 

    Google Scholar 
    Guindon, S. et al. New algorithms and methods to estimate maximum-likelihood phylogenies: Assessing the performance of PhyML 3.0. Syst. Biol. 59, 307–321 (2010).CAS 
    Article 

    Google Scholar 
    Ritz, C., Baty, F., Streibig, J. C. & Gerhard, D. Dose-response analysis using R. PLoS ONE 10, e0146021. https://doi.org/10.1371/journal.pone.0146021 (2016).CAS 
    Article 

    Google Scholar 
    Lomas, M. W., Swain, A., Shelton, R. & Ammerman, J. W. Taxonomic variability of phosphorus stress in Sargasso Sea phytoplankton. Limnol. Oceanogr. 49, 2303–2310 (2004).ADS 
    Article 

    Google Scholar 
    Yamaguchi, H., Yamaguchi, M. & Adachi, M. Specific-detection of alkaline phosphatase activity in individual species of marine phytoplankton. Plankon Benthos Res. 1, 2014–2217 (2006).Article 

    Google Scholar 
    Strickland, J. D. H. & Parsons, T. R. A Practical Handbook of Seawater Snalysis. (Fisheries Resrach Board of Canada, 1972).Bligh, E. G. & Dyer, W. J. A rapid method of total lipid extraction and purification. Can. J. Biochem. Phys. 37, 911–917 (1959).CAS 
    Article 

    Google Scholar 
    Gašparović, B., Kazazić, S. P., Cvitešić, A., Penezić, A. & Frka, S. Improved separation and analysis of glycolipids by Iatroscan thin-layer chromatography–flame ionization detection. J. Chromatogr. A 1409, 259–267 (2015).Article 

    Google Scholar 
    Gašparović, B., Kazazić, S. P., Cvitešić, A., Penezić, A. & Frka, S. Corrigendum to “Improved separation and analysis of glycolipids by Iatroscan thin-layer chromatography–flame ionization detection”[J. Chromatogr. A 1409 (2015) 259–267]. (2017).Fonda Umani, S. et al. Inter-annual variations of planktonic food webs in the northern Adriatic Sea. Sci. Total Environ. 353, 218–231. https://doi.org/10.1016/j.scitotenv.2005.09.016 (2005).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    R: A language and environment for statistical computing (R Foundation for Statistical Computing, 2015).Sprouffske, K. & Wagner, A. Growthcurver: An R package for obtaining interpretable metrics from microbial growth curves. BMC Bioinform. 17, 172. https://doi.org/10.1186/s12859-016-1016-7 (2016).Article 

    Google Scholar 
    Schlitzer, R. Ocean Data View. http://odv.awi.de (2018).Smodlaka Tanković, M. et al. Experimental evidence for shaping and bloom inducing effects of decapod larvae of Xantho poressa (Olivi, 1792) on marine phytoplankton. J. Mar. Biol. Assoc. United Kingdom 98, 1881–1887 (2018).Article 

    Google Scholar 
    Dyhrman, S. T. et al. The transcriptome and proteome of the diatom Thalassiosira pseudonana reveal a diverse phosphorus stress response. PLoS ONE 7, e33768 (2012).ADS 
    CAS 
    Article 

    Google Scholar 
    Novak, T. et al. Global warming and oligotrophication lead to increased lipid production in marine phytoplankton. Sci Total Environ 668, 171–183 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    Martin, P., Van Mooy, B. A., Heithoff, A. & Dyhrman, S. T. Phosphorus supply drives rapid turnover of membrane phospholipids in the diatom Thalassiosira pseudonana. ISME J. 5, 1057–1060 (2011).CAS 
    Article 

    Google Scholar 
    Abida, H. et al. Membrane glycerolipid remodeling triggered by nitrogen and phosphorus starvation in Phaeodactylum tricornutum. Plant Physiol. 167, 118–136 (2015).CAS 
    Article 

    Google Scholar 
    Ivančić, I. & Degobbis, D. Mechanisms of production and fate of organic phosphorus in the northern Adriatic Sea. Mar. Biol. 94, 117–125 (1987).
    Article 

    Google Scholar 
    Hardin, G. The competitive exclusion principle. Science 131, 1292–1297 (1960).ADS 
    CAS 
    Article 

    Google Scholar 
    Hutchinson, G. E. The paradox of the plankton. Am Nat 95, 137–145 (1961).Article 

    Google Scholar  More

  • in

    Host-trailing satellite flight behaviour is associated with greater investment in peripheral visual sensory system in miltogrammine flies

    Chapman, R. F. Chemoreception: The significance of receptor numbers. Adv. Insect Physiol. 16, 247–356 (1982).CAS 

    Google Scholar 
    Greenfield, M. D. Signalers and Receivers: Mechanisms and Evolution of Arthropod Communication (Oxford University Press, 2002).
    Google Scholar 
    Wyatt, T. D. Pheromones and Animal Behavior: Chemical Signals and Signatures (Cambridge University Press, 2014).
    Google Scholar 
    Elgar, A. et al. Insect antennal morphology: The evolution of diverse solutions to odorant perception. Yale J. Biol. Med. 91, 457–469 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Dötterl, S. & Vereecken, N. J. The chemical ecology and evolution of bee-flower interactions: a review and perspectives. Can. J. Zool. 88, 668–697 (2010).
    Google Scholar 
    Leonard, A. S., Dornhaus, A. & Papaj, D. R. Why are floral signals complex, an outline of functional hypotheses. In Evolution of Plant-Pollinator Relationships (ed. Patiny, S.) (Cambridge University Press, USA, 2012).
    Google Scholar 
    Colazza, S., Peri, E., Salerno, G. & Conti, E. Host Searching by Egg Parasitoids: Exploitation of Host Chemical Cues. In Egg Parasitoids in Agroecosystems with Emphasis on Trichogramma (eds Consoli, F. L. et al.) 97–147 (Springer, 2010).
    Google Scholar 
    Kelber, A. et al. Light intensity limits the foraging activity in nocturnal and crepuscular bees. Behav. Ecol. 17, 63–72 (2006).
    Google Scholar 
    Polidori, C., Jorge, A. & Ornosa, C. Antennal morphology and sensillar equipment vary with pollen diet specialization in Andrena bees. Arthropod Struct. Develop. 57, 100950 (2020).
    Google Scholar 
    Spaethe, J., Brockmann, A., Halbig, C. & Tautz, J. Size determines antennal sensitivity and behavioral threshold to odors in bumblebee workers. Naturwissenschaften. 94, 733–739 (2007).CAS 
    PubMed 
    ADS 

    Google Scholar 
    Warrant, E. J., Kelber, A., Wallén, R. & Wcislo, W. The physiological optics of ocelli in nocturnal and diurnal bees and wasps. Arthropod Struct. Dev. 35, 293–305 (2006).PubMed 

    Google Scholar 
    Keesey, I. W. et al. Inverse resource allocation between vision and olfaction across the genus Drosophila. Nat. Commun. 10, 1162. https://doi.org/10.1038/s41467-019-09087-z (2019).CAS 
    Article 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    Keil, T. A. Morphology and Development of the Peripheral Olfactory Organs. In Insect Olfaction (ed. Hansson, B. S.) 5–47 (Springer, 1999).
    Google Scholar 
    Stöckl, A. et al. Differential investment in visual and olfactory brain areas reflects behavioural choices in hawk moths. Sci. Rep. 6, 26041. https://doi.org/10.1038/srep26041 (2016).CAS 
    Article 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    Bulova, S., Purce, K., Khodak, P., Sulger, E. & O’Donnell, S. Into the black and back: The ecology of brain investment in Neotropical army ants (Formicidae: Dorylinae). Sci. Nat. 103, 31. https://doi.org/10.1007/s00114-016-1353-4 (2016).CAS 
    Article 

    Google Scholar 
    Freelance, C. B. et al. The eyes have it: Dim-light activity is associated with the morphology of eyes but not antennae across insect orders. Biol. J. Linn. Soc. 134, 303–315 (2021).
    Google Scholar 
    Barrett, M. et al. Neuroanatomical differentiation associated with alternative reproductive tactics in male arid land bees, Centris pallida and Amegilla dawsoni. J. Comp. Physiol. A Neuroethol. Sens. Neural. Behav. Physiol. 207, 497–504 (2021).PubMed 

    Google Scholar 
    Newland, P. Physiological properties of afferents from tactile hairs on the hindlegs of the locust. J. Exp. Biol. 155, 487–503 (1991).CAS 
    PubMed 

    Google Scholar 
    Dahake, A., Stöckl, A., Foster, J., Sane, S. P. & Kelber, A. The roles of vision and antennal mechanoreception in hawkmoth flight control. eLife e37606 (2018).Sane, S. P., Dieudonné, A., Willis, M. A. & Daniel, T. L. Antennal mechanosensors mediate flight control in moths. Science 315, 863–866 (2007).CAS 
    PubMed 
    ADS 

    Google Scholar 
    Land, M. F. Compound Eye Structure: Matching Eye to Environment. In Adaptive Mechanisms in the Ecology of Vision (eds Archer, S. et al.) 51–72 (Kluwer Academic Publishers, 1998).
    Google Scholar 
    Land, M. F. Visual acuity in insects. Ann. Rev. Entomol. 42, 147–177 (1997).CAS 

    Google Scholar 
    Land, M. F. & Nilsson, D. E. Animal Eyes (Oxford University Press, 2003).
    Google Scholar 
    Jander, U. & Jander, R. Allometry and resolution of bee eyes (Apoidea). Arthropod Struct. Dev. 30, 179–193 (2002).PubMed 

    Google Scholar 
    Berry, R., van Kleef, J. & Stange, G. The mapping of visual space by dragonfly lateral ocelli. J. Comp. Physiol. A 193, 495–513 (2007).
    Google Scholar 
    Hung, Y. S. & Ibbotson, M. R. Ocellar structure and neural innervation in the honeybee. Front. Neuroanat. https://doi.org/10.3389/fnana.2014.00006 (2014).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Greiner, B. Visual adaptations in the night-active wasp Apoica pallens. J. Comp. Neurol. 495, 255–262 (2006).PubMed 

    Google Scholar 
    Klotz, J. H., Reid, B. L. & Gordon, W. C. Variation of ommatidia number as a function of worker size in Camponotus pennsylvanicus (DeGeer) (Hymenoptera, Formicidae). Insect Soc. 39, 233–236 (1992).
    Google Scholar 
    Narendra, A. et al. Caste-specific visual adaptations to distinct daily activity schedules in Australian Myrmecia ants. Proc. R. Soc. B 278, 1141–1149 (2011).PubMed 

    Google Scholar 
    Piwczyński, M. et al. Molecular phylogeny of Miltogramminae (Diptera: Sarcophagidae): Implications for classification, systematics and evolution of larval feeding strategies. Mol. Phyl. Evol. 116, 49–60 (2017).
    Google Scholar 
    Spofford, M. G. & Kurczewski, F. E. Comparative larvipositional behaviors and cleptoparasitic frequencies of Nearctic species of Miltogrammini (Diptera, Sarcophagidae). J. Nat. Hist. 24, 731–755 (1990).
    Google Scholar 
    Alcock, J. The natural history of a miltogrammine fly, Miltogramma rectangularis (Diptera: Sarcophagidae). J. Kansas Entomol. Soc. 73, 208–219 (2000).
    Google Scholar 
    Newcomer, E. J. Notes on the habits of a digger wasp and its inquiline flies. Ann. Entomol. Soc. Am. 23, 552–563 (1930).
    Google Scholar 
    Ristich, S. S. The host relationship of a miltogrammid fly Senotainia trilineata (VDW). Ohio J. Sci. 56, 271–274 (1956).
    Google Scholar 
    Giordani, G. Contributo alla conoscenza della Senotainia tricuspis Meig, dittero sarcofagide, endoparassita dell’ape domestica. Boll. Istit. Entomol. Univ. Bologna 21, 61–84 (1955).
    Google Scholar 
    Povolný, D. & Verves, Yu. G. The flesh-flies of Central Europe (Insecta, Diptera, Sarcophagidae). Spixiana (Supplement) 24, 1–260 (1997).
    Google Scholar 
    Evans, H. E. & O’Neill, K. M. The sand wasps: Natural history and behavior (Harvard University Press, 2007).
    Google Scholar 
    O’Neill, K. M. Solitary Wasps: Natural History and Behavior (Cornell University Press, 2001).
    Google Scholar 
    Pape, T. The Sarcophagidae (Diptera) of Fennoscandia and Denmark. Fauna Entomol. Scand. 19, 1–203 (1987).
    Google Scholar 
    Polidori, C., Ouadragou, M., Gadallah, N. & Andrietti, F. Potential role of evasive flights and nest closures in an African sand wasp, Bembix sp. near capensis Lepeletier 1845 (Hymenoptera Crabronidae), against a parasitic satellite fly. Trop. Zool. 22, 1–14 (2009).
    Google Scholar 
    Polidori, C. Interactions between the social digger wasp, Cerceris rubida, and its brood parasitic flies at a Mediterranean nest aggregation. J. Insect Behav. 30, 86–102 (2017).
    Google Scholar 
    Pape, T. A new species of Hoplacephala Macquart (Diptera: Sarcophagidae) from Namibia, with a discussion of generic monophyly. Zootaxa 1183, 57–68 (2006).
    Google Scholar 
    Haynie, J. L. & Bryant, P. J. Development of the eye-antenna imaginal disc and morphogenesis of the adult head in Drosophila melanogaster. J. Exp. Zool. 237, 293–308 (1986).CAS 
    PubMed 

    Google Scholar 
    Hódar, J. A. The use of regression equations for estimation of arthropod biomass in ecological studies. Acta Oecol. 17, 421–433 (1996).
    Google Scholar 
    Hogue, J. N. & Hawkins, C. P. Morphological variation in adult aquatic insects: Associations with developmental temperature and seasonal growth patterns. J. N. Am. Benthol. Soc. 10, 309–321 (1991).
    Google Scholar 
    Seidl, R. & Kaiser, W. Visual field size, binocular domain and the ommatidial array of the compound eyes in worker honey bees. J. Comp. Physiol. A 143, 17–26 (1981).
    Google Scholar 
    Stuckenberg, B. R. Antennal evolution in the Brachycera (Diptera), with a reassessment of terminology relating to the flagellum. Stud. Dipterol. 6, 33–48 (1999).
    Google Scholar 
    Lemmon, A. R., Emme, S. A. & Lemmon, E. M. Anchored hybrid enrichment for massively high-throughput phylogenomics. Syst. Biol. 61, 727–744 (2012).CAS 
    PubMed 

    Google Scholar 
    Young, A. D. et al. Anchored enrichment dataset for true flies (order Diptera) reveals insights into the phylogeny of flower flies (family Syrphidae). BMC Evol. Biol. 16, 1–13 (2016).
    Google Scholar 
    Gillung, J. P. et al. Anchored phylogenomics unravels the evolution of spider flies (Diptera, Acroceridae) and reveals discordance between nucleotides and amino acids. Mol. Phyl. Evol. 128, 233–245 (2018).CAS 

    Google Scholar 
    Buenaventura, E., Szpila, K., Cassel, B. K., Wiegmann, M. & Pape, T. An anchored hybrid enrichment-based dataset challenges the traditional classification of flesh flies (Diptera: Sarcophagidae). Syst. Entomol. 45, 281–301 (2020).
    Google Scholar 
    Grzywacz, A. et al. Towards a new classification of Muscidae (Diptera): A comparison of hypotheses based on multiple molecular phylogenetic approaches. Syst. Entomol. 46, 508–525 (2021).
    Google Scholar 
    Misof, B. et al. Phylogenomics resolves the timing and pattern of insect evolution. Science 346, 763–767 (2014).CAS 
    PubMed 
    ADS 

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

    Google Scholar 
    Yan, L. et al. A phylotranscriptomic framework for flesh fly evolution (Diptera, Calyptratae, Sarcophagidae). Cladistics https://doi.org/10.1111/cla.12449 (2020).Article 
    PubMed 

    Google Scholar 
    Paradis, E. & Schliep, K. ape 5.0: An environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics. 35, 526–528 (2019).CAS 
    PubMed 

    Google Scholar 
    Maddison, W. P. & Maddison, D. R. Mesquite: A Modular System for Evolutionary analysis. Version 3.61. http://www.mesquiteproject.org (2019).Hansen, T. F. Stabilizing selection and the comparative analysis of adaptation. Evolution 51, 1341–1351 (1997).PubMed 

    Google Scholar 
    Hansen, T. F., Pienaar, J. & Orzack, S. H. A comparative method for studying adaptation to a randomly evolving environment. Evolution 62, 1965–1977 (2008).PubMed 

    Google Scholar 
    Labra, A., Pienaar, J. & Hansen, T. F. Evolution of thermal physiology in Liolaemus lizards: Adaptation, phylogenetic inertia and niche tracking. Am. Nat. 174, 204–220 (2009).PubMed 

    Google Scholar 
    Hansen, T. F. Use and Misuse of Comparative Methods in the Study of Adaptation. In Modern Phylogenetic Comparative Methods and Their Application in Evolutionary Biology: Concepts and Practice (ed. Garamszegi, L. Z.) 351–379 (Springer, 2014).
    Google Scholar 
    Greiner, B., Ribi, W. A. & Warrant, E. J. Retinal and optical adaptations for nocturnal vision in the halictid bee Megalopta genalis. Cell Tissue Res. 316, 377–390 (2004).PubMed 

    Google Scholar 
    Warrant, E. J. et al. Nocturnal vision and landmark orientation in a tropical halictid bee. Curr. Biol. 14, 1309–1318 (2004).CAS 
    PubMed 

    Google Scholar 
    Somanathan, H., Kelber, A., Wallén, R., Borges, R. M. & Warrant, E. J. Visual ecology of Indian carpenter bees II: Visual adaptations to nocturnal and diurnal lifestyles. J. Comp. Physiol. A 195, 571–583 (2009).
    Google Scholar 
    Menzi, U. Visual adaptation in nocturnal and diurnal ants. J. Comp. Physiol. 160, 11–21 (1987).
    Google Scholar 
    Moser, J. C. et al. Eye size and behaviour of day and night-flying leafcutting ant alates. J. Zool. 264, 69–75 (2004).
    Google Scholar 
    Greiner, B. et al. Eye structure correlates with distinct foraging-bout timing in primitive ants. Curr. Biol. 17, R879–R880 (2007).CAS 
    PubMed 

    Google Scholar 
    Warrant, E. J. Seeing in the dark: Vision and visual behaviour in nocturnal bees and wasps. J. Exp. Biol. 211, 1737–1746 (2008).PubMed 

    Google Scholar 
    Leys, R. & Hogendoorn, K. Correlated evolution of mating behaviour and morphology in large carpenter bees (Xylocopa). Apidologie 39, 119–132 (2008).
    Google Scholar 
    Snyder, A. W. Physics of Vision in Compound Eyes. In Handbook of Sensory Physiology: Vision in Invertebrates (ed. Autrum, H. J.) (Springer, 1979).
    Google Scholar 
    McCorquodale, D. B. Digger wasp provisioning flights as a defense against a nest parasite, Senotainia trilineata. Can. J. Zool. 64, 1620–1627 (1986).
    Google Scholar 
    Gilbert, C. & Strausfeld, N. J. The functional organization of male-specific visual neurons in flies. J. Comp. Physiol. A 169, 395–411 (1991).CAS 
    PubMed 

    Google Scholar 
    Trischler, C., Boeddeker, N. & Egelhaaf, M. Characterisation of a blowfly male-specific neuron using behaviourally generated visual stimuli. J. Comp. Physiol. A 193, 559–572 (2007).
    Google Scholar 
    Taylor, G. J. et al. The dual function of orchidbee ocelli as revealed by X-Ray microtomography. Curr. Biol. 26, 1319–1324 (2016).CAS 
    PubMed 

    Google Scholar 
    Hengstenberg, R. Multisensory Control in Insect Oculomotor Systems. In Visual Motion and Its Role in the Stabilization of Gaze (eds Miles, F. A. & Wallmann, J.) (Elsevier, 1993).
    Google Scholar 
    Schuppe, H. & Hengstenberg, R. Optical properties of the ocelli of Calliphora erythrocephala and their role in the dorsal light response. J. Comp. Physiol. A 173, 143–149 (1993).
    Google Scholar 
    Crosskey, R. W. & Lane, R. P. Introduction to Diptera. In Medical Insects and Arachnids (eds Lane, R. P. & Crosskey, R. W.) (Chapman and Hall, 1993).
    Google Scholar 
    Abouzied, E. M. Antennal and maxillary palp sensillae of male and female Liosarcophaga babiyari Lehrer (Diptera: Sarcophagidae). Bull. Ent. Soc. Egypt 85, 29–48 (2008).
    Google Scholar 
    Wasserman, S. L. & Itagaki, H. The olfactory responses of the antenna and maxillary palp of the fleshfly, Neobellieria bullata (Diptera: Sarcophagidae), and their sensitivity to blockage of nitric oxide synthase. J. Insect Physiol. 49, 271–280 (2003).CAS 
    PubMed 

    Google Scholar 
    Khedre, A. M. Olfactory sensilla on the antennae and maxillary palps of the fleshfly Wohlfahrtia nuba (Wied.) (Diptera: Sarcophagidae). J. Egypt Ger. Soc. Zool. 24, 171–193 (1997).
    Google Scholar 
    Pezzi, M. et al. Ultrastructural morphology of the antenna and maxillary palp of Sarcophaga tibialis (Diptera: Sarcophagidae). J. Med. Entomol. 53, 807–814 (2016).CAS 
    PubMed 

    Google Scholar 
    Smallegange, R. C., Kelling, F. J. & Den Otter, C. J. Types and numbers of sensilla on antennae and maxillary palps of small and large houseflies, Musca domestica (Diptera, Muscidae). Microsc. Res. Tech. 71, 880–886 (2008).PubMed 

    Google Scholar 
    Zhang, D., Wang, Q. K., Yang, Y. Z., Chen, Y. O. & Li, K. Sensory organs of the antenna of two Fannia species (Diptera: Fanniidae). Parasitol. Res. 112, 2177–2185 (2013).CAS 
    PubMed 

    Google Scholar 
    Been, T. H., Schomaker, C. H. & Thomas, G. Olfactory sensilla on the antenna and maxillary palp of the sheep head fly, Hydrotaea irritans (Fallen) (Diptera: Muscidae). Int. J. Insect Morphol. Embryol. 17, 121–133 (1998).
    Google Scholar 
    Zacharuk, R. Y. & Antennal, S. Comparative Insect Physiology, Biochemistry and Pharmacology. In Pergamon Press (eds Kerkut, G. A. & Gilbert, L. I.) (1985).
    Google Scholar 
    Sukontason, K. et al. Antennal sensilla of some forensically important flies in families Calliphoridae Sarcophagidae and Muscidae. Micron 35, 671–679 (2004).PubMed 

    Google Scholar 
    Mamiya, A., Straw, A. D., Tómasson, E. & Dickinson, M. H. Active and passive antennal movements during visually guided steering in flying Drosophila. J Neurosci 31, 6900–6914 (2011).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Fuller, S. B., Straw, A. D., Peek, M. Y., Murray, R. M. & Dickinson, M. H. Flying Drosophila stabilize their vision-based velocity controller by sensing wind with their antennae. Proc. Nat. Acad. Sci. 111, E1182–E1191 (2014).CAS 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    Nalbach, G. Extremely non-orthogonal axes in a sense organ for rotation: Behavioural analysis of the dipteran haltere system. Neuroscience 61, 149–163 (1994).CAS 
    PubMed 

    Google Scholar 
    Rozanski, A. N. et al. Differential investment in visual and olfactory brain regions is linked to the sensory needs of a wasp social parasite and its host. J. Comp. Neurol. https://doi.org/10.1002/cne.25242 (2021).Article 
    PubMed 

    Google Scholar  More

  • in

    Tropical forest restoration under future climate change

    Tropical forest restoration areaTo determine the geographic distribution of land available for tropical forest restoration, we used a widely applied global forest restoration map2. This dataset limits potential restoration area to regions that are biogeophysically suitable for forest, and excludes croplands. To define the tropics, we masked the potential restoration map with the following three ecoregions from the Ecoregions2017 vegetation map34: ‘Tropical and Subtropical Moist Broadleaf Forests’, ‘Tropical and Subtropical Dry Broadleaf Forests’, and ‘Tropical and Subtropical Coniferous Forests’. The resulting restoration mask includes all tropical and subtropical forest ecoregions with some that are outside the tropical latitudes, but excludes wetlands and high mountain areas (Extended Data Fig. 4). The restoration mask was converted from a presence–absence raster at its native ~350 m resolution to a 0.5° geographical grid by aggregating to the fraction of each 0.5° grid cell available for restoration. Any uncertainties in the allocation of restorable area, distinguishing crop and pasture, and forest to non-forest classification from the original forest restoration map were also implicitly included in our restoration extent. While the resulting restoration area is relatively small, its spatial distribution is representative for most of the humid tropics.To prioritize for carbon uptake capacity, we selected all grid cells with restoration area greater than 1 ha and ranked these by carbon storage density (above ground and below ground; g m−2) at 2100 under the default scenario. We then selected the top n grid cells with greatest carbon density until cumulatively 64 Mha of restored area was reached. Similarly, for cost we calculated the restoration cost for each grid cell following ref. 27 and sorted the grid cells by their cost, beginning with the lowest value, until 64 Mha were reached. To consider the combined impact of carbon uptake and restoration costs, we divided our restoration cost layer by the total carbon uptake per grid cell from restoration and ranked the cost per carbon uptake from cheapest to most expensive, selecting the n grid cells with the lowest values until 64 Mha were reached. We then used the selected grid cells to mask carbon uptake under the various climate change and CO2 fertilization scenarios. To factor in climate change in the prioritization process, we used the same restoration cost layer but used the carbon density and total carbon uptake layers with climate change impacts in CO22014 for the year 2100.Vegetation modelWe used the LPJ-LMfire DGVM19, a version of the Lund-Potsdam-Jena DGVM (LPJ)35. LPJ-LMfire is driven by gridded fields of climate, soil texture and topography at 0.5° resolution, and with a time series of atmospheric CO2 concentrations (see Supplementary Information). To simulate land use, LPJ-LMfire separates grid cells into fractional tiles of ‘unmanaged’ land that has never been under land use, ‘managed’ land, and areas ‘recovering’ from land use36. Restoration removes land from the ‘managed’ tile and transfers it to the ‘recovering’ tile; land is never reallocated to the ‘unmanaged’ tile. The tiles are treated differently with respect to wildfire: on the ‘unmanaged’ and ‘recovering’ tiles, lightning-ignited wildfires are not suppressed, while fire is excluded from ‘managed’ tiles. For our analysis of total carbon (above and below ground), we only used the ‘recovering’ tile.Climate dataClimate forcing used to drive LPJ-LMfire comes from the output of 13 GCMs in simulations produced for the CMIP6 Supplementary Table 2 (refs. 37,38). For each GCM, we obtained simulations for the historical period (1850–2014) and four future SSPs (SSP1-26, SSP2-45, SSP3-70 and SSP5-85 covering 2015–2100). We used only GCMs that archived all seven climate variables needed to run LPJ-LMfire: 2 m temperature (tas, K), precipitation (pr, kg m−2 s−1), convective precipitation (prc, kg m−2 s−1), cloud cover (clt, %), minimum and maximum daily temperature (tmin, tmax, K), and 10 m surface wind speed (sfcWind, m s−1) (Supplementary Fig. 2). For each model, we concatenated the historical simulation with a future scenario, calculated anomalies with respect to 1971–1990 and added those to observed 30 year climatologies to create bias-corrected monthly climate time series covering 1850–2100 (see Supplementary Information). Where multiple ensemble members were available from a GCM, we chose the first simulation.Simulation protocolWe drove LPJ-LMfire with the GCM simulations described in the previous section, and the same atmospheric CO2 concentrations and land use boundary conditions as those used in the CMIP6 simulations. All forcings cover the historical period (1850–2014) and the individual future SSPs (2015–2100). Each LPJ-LMfire simulation was initialized for 1,020 years with 1850 atmospheric CO2 and land use, and the 1850s climatology of each CMIP6 GCM. This was followed by simulations with transient climate from 1850 to 2100 for each CMIP6 GCM under each of the four SSPs. For each the 13 CMIP6 GCMs running each of the SSP scenarios, we conducted two CO2 experiments (CO22014 and CO2free) and two fire experiments. In total, we ran 221 vegetation model simulations covering the range of future climate, CO2 and fire scenarios.Atmospheric CO2 in these simulations either followed the CMIP6 historical and SSP trajectory for the entire 1850–2100 run (CO2free), or followed the historical CMIP6 trajectory until 2014, and was then fixed at 2014 concentrations for the remainder of the simulation (CO22014). This allowed us to test the vegetation response to future climate change in the absence of additional CO2 fertilization of photosynthesis. Our simulations ended with the standard SSP projections in 2100, 80 years after restoration begins. We therefore could not assess the fate of restored carbon beyond that point. On the basis of the trends in the multi-model mean carbon uptake rates, we estimated that only under severe climate change will carbon storage be reduced shortly after 2100 in CO22014.In control simulations, land use followed the historical CMIP6 trajectory until 2014, after which it was fixed under 2014 conditions until 2100. Land use after 2014 was fixed at 2014 levels because it is the last year with common land use between all scenarios, which allowed us to identify future climate change impacts on restoration permanence and avoid influences from land abandonment and expansion prescribed in the different SSP scenarios.In the restoration experiments, land use also followed the historical CMIP6 trajectory until 2014, but then diverged: cropland extent remained at 2014 levels until 2100, while pasture (or non-cropland land use) remained constant from 2014 to 2020 and was then linearly reduced by the restoration area from 2020 to 2030. From 2030, land use remained constant at that lower level until 2100. The amount of restoration in a grid cell was limited by the pasture area, that is, once all of the available pasture area had been restored, no additional restoration took place. Because it is highly unlikely to be practical to restore the entire target area of tropical forest at once, we linearly increased the restoration area from 2020 to 2030, which caused an expansion-driven increase in carbon uptake over the 11 year period (Extended Data Fig. 1). This means that two factors controlled carbon uptake over time in our experimental design: first the expansion of the restoration area, accounting for approximately 19.7 Pg C, and second the long-term effect of carbon accumulation (Extended Data Fig. 5).Primary climate change impacts, such as drought and heat stress that reduce carbon uptake, were implicitly included in the climate forcing data, while secondary climate change impacts from wildfire were simulated by LPJ-LMfire on the basis of climate. To quantify the contribution of wildfire on the carbon storage from restoration, we repeated the simulations described above with fires turned off in LPJ-LMfire.Restoration opportunity indexWe created a restoration opportunity index to evaluate the suitability of locations for restoration on the basis of the ability for restoration to result in net carbon uptake over 2020–2100 and to store this carbon without episodes of major loss. For each of the 13 realizations of the four SSPs in the CO22014 experiment, we identified all restoration grid cells (1) that had a net carbon uptake by 2100 relative to 2030, and (2) where temporal reductions in total carbon storage over 2030–2100 were More

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    Photosynthetic performance of symbiont-bearing foraminifera Heterostegina depressa affected by sunscreens

    Pawlowski, J. et al. The evolution of early Foraminifera. Proc. Natl. Acad. Sci. 100(20), 11494–11498 (2003).ADS 
    CAS 
    Article 

    Google Scholar 
    Gupta, S. Modern Foraminifera (Springer-Verlag, 1999).
    Google Scholar 
    Narayan, G. R. et al. Response of large benthic foraminifera to climate and local changes: Implications for future carbonate production. Sedimentology 2, 2 (2021).
    Google Scholar 
    Doo, S. S., Fujita, K., Byrne, M. & Uthicke, S. Fate of calcifying tropical symbiont-bearing large benthic foraminifera: Living sands in a changing ocean. Biol. Bull. 226(3), 169–186 (2014).CAS 
    Article 

    Google Scholar 
    Fujita, K. et al. Effects of ocean acidification on calcification of symbiont-bearing reef foraminifers. Biogeosciences 8(8), 2089–2098 (2011).ADS 
    Article 

    Google Scholar 
    Raja, R., Saraswati, P. K., Rogers, K. & Iwao, K. Magnesium and strontium compositions of recent symbiont-bearing benthic foraminifera. Mar. Micropaleontol. 58(1), 31–44 (2005).ADS 
    Article 

    Google Scholar 
    Murray, J. Ecological experiments on Foraminiferida. J. Mar. Biol. Assoc. U.K. 43(3), 621–642 (1963).Article 

    Google Scholar 
    Wukovits, J., Enge, A. J., Wanek, W., Watzka, M. & Heinz, P. Increased temperature causes different carbon and nitrogen processing patterns in two common intertidal foraminifera. Biogeosciences 14, 2815–2829 (2017).ADS 
    CAS 
    Article 

    Google Scholar 
    Lintner, M., Biedrawa, B., Wukovits, J., Wanek, W., and Heinz, P. Salinity-depending algae uptake and subsequent carbon and nitrogen metabolisms of two intertidal foraminifera (Ammonia tepida and Haynesina germanica). BG, 17, 3723–3732 (2020).Hoegh-Guldberg, O. & Bruno, J. F. The impact of climate change on the world’s marine ecosystems. Science 328, 1523–1528 (2010).ADS 
    CAS 
    Article 

    Google Scholar 
    Occhipinti-Ambrogi, A. Global change and marine communities: Alien species and climate change. Mar. Pollut. Bull. 55, 342–352 (2007).CAS 
    Article 

    Google Scholar 
    Hallock, P. Symbiont-bearing foraminifera. In Modern Foraminifera 123–139 (Springer, 1999).Chapter 

    Google Scholar 
    Renema, W. Large benthic foraminifera in low-light environments. In Mesophotic coral ecosystems 553–561 (Springer, 2019).Chapter 

    Google Scholar 
    Hallock, P. & Peebles, M. W. Foraminifera with chlorophyte endosymbionts—habitats of 6 species in the Florida Keys. Mar. Micropaleontol. 20, 277–292 (1993).ADS 
    Article 

    Google Scholar 
    Stulpinaite, R., Hyams-Kaphzan, O. & Langer, M. R. Alien and cryptogenic Foraminifera in the Mediterranean Sea: A revision of taxa as part of the EU 2020 marine strategy framework directive. Mediterr. Mar. Sci. 21(3), 719–758 (2020).
    Google Scholar 
    McCoshum, S., Schlarb, M. A. & Baum, A. K. Direct and indirect effects of sunscreen exposure for reef biota. Rev. Hydrobiology 776, 139–146 (2016).CAS 
    Article 

    Google Scholar 
    Singh, S., Jha, B., Tiwary, N. K. & Agrawal, N. K. Does using a high sun protection factor sunscreen on face, along with physical photoprotection advice, in patients with melasma, change serum vitamin D concentration in Indian conditions? A pragmatic pretest-posttest study. Indian J. Dermatol. Venereol. Leprol. 85, 282–286 (2019).Article 

    Google Scholar 
    Harjung, A. et al. High anthropogenic organic matter inputs during a festival increase river heterotrophy and refractory carbon load. Environ. Sci. Technol. 54(16), 10039–10048. https://doi.org/10.1021/acs.est.0c02259 (2020).ADS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rai, R., Shanmuga, S. C. & Srinivas, C. Update on photoprotection. Indian J. Dermatol. 57, 335–342 (2012).Article 

    Google Scholar 
    Schiavo, S., Oliviero, M., Phillipe, A. & Manzo, S. Nanoparticles based sunscreens provoke adverse effects on marine microalgae Dunaliella tertiolecta. Environ. Sci. Nano. 12, 2 (2018).
    Google Scholar 
    Parkhill, J., Mailett, G. & Cullen, J. Fluorescence-based maximal quantim yield fpr PSII as a diagnostic of nutrient stress. J. Phycol. 37, 517–529 (2001).Article 

    Google Scholar 
    Butler, W. L. Energy distribution in the photochemical apparatus of photosynthesis. Ann. Rev. Plant. Physiol. 29, 345–378 (1978).CAS 
    Article 

    Google Scholar 
    Kroon, B., Prezelin, B. B. & Schonfield, O. Chromatic regulation of quantum yields for photosystem II charge separation, oxygen evolution and carbon fixation in Heterocapsa pygmaea. J. Phycol 29, 453–462 (1993).CAS 
    Article 

    Google Scholar 
    Casas-Beltran, D. A., Hernandez-Pedraza, M. & Alvarado-Flores, J. Estimation of the discharge of sunscreens in aquatic environments of the Mexican caribbean. Environments 7, 15 (2020).Article 

    Google Scholar 
    Danovaro, R. et al. Sunscreens cause coral bleaching by promoting viral infections. Environ. Health Perspect. 116, 441–447 (2008).CAS 
    Article 

    Google Scholar 
    Brausch, J. M. & Rand, G. M. A review of personal care products in the aquatic environment: Environmental concentrations and toxicity. Chemosphere 82, 1518–1532 (2011).ADS 
    CAS 
    Article 

    Google Scholar 
    Balmer, M. E., Buser, H. R., Muller, M. D. & Poiger, T. Occurrence of the organic UV-filter compounds BP-3, 4-MBC, EHMC, and OC in wastewater, surface waters, and in fish from Swiss lakes. Environ. Sci. Technol. 39, 953–962 (2004).ADS 
    Article 

    Google Scholar 
    Godejohann, M., Berset, J. & Muff, D. Non-targeted analysis of wastewater treatment plant effluents by high-performance liquid chromatography–time slice-solid phase extraction-nuclear magnetic resonance/time-of-flight-mass spectrometry. J. Chromatogr. A 1218, 9202–9209 (2011).CAS 
    Article 

    Google Scholar 
    Hallock, P., Lidz, B. H., Cockey-Burkhard, E. M. & Donnelly, K. B. Foraminifera as bioindicators in coral reef assessment and monitoring: The FORAM index. Environ. Monit. Assess. 81(1), 221–238 (2003).Article 

    Google Scholar 
    Sharma, V. K. Aggregation and toxicity of titanium dioxide nanoparticles in aquatic environment—A Review. J. Environ. Sci. Health Part A. 44(14), 1485–2495 (2009).CAS 
    Article 

    Google Scholar 
    Hutchison, J. E. Greener nanoscience: A proactive approach to advancing applications and reducing implications of nanotechnology. ACSNano. 2(3), 395–402 (2008).CAS 

    Google Scholar 
    Soto, K., Garza, K. M. & Murr, L. E. Cytosis effects of aggregated nanomaterials. Acta Biomater. 3, 351–358 (2007).CAS 
    Article 

    Google Scholar 
    Deer, W. A., Howie, R. A. & Zussmann, J. An Introduction to the Rock Forming Minerals (Longman Group Limited, 1992).
    Google Scholar 
    Kaegi, R. et al. Synthetic TiO2 nanoparticle emission from exterior facades into the aquatic environment. Environ. Pollut. 156, 233–239 (2008).CAS 
    Article 

    Google Scholar 
    Mio, A. J. et al. Zinc oxide–engineered nanoparticles: Dissolution and toxicity to marine phytoplankton. Environ. Toxicol. Chem. 29(12), 2814–2822 (2010).Article 

    Google Scholar 
    Herzog, B. et al. In vivo and in vitro assessment of UVA protection by sunscreen formulations containing either butyl methoxy dibenzoyl methane, methylene bis-benzotriazolyl tetramethylbutylphenol, or microfine ZnO. Int. J. Cosmet. Sci. 24, 170–185 (2002).CAS 
    Article 

    Google Scholar 
    Dhas, S. P., Shiny, P. J., Mukherjee, A. & Chandrasekran, N. Toxic behavior of silver and zinc oxide nanoparticles on environmental microorganisms. J. Basic Microbiol. 53, 1–12 (2013).Article 

    Google Scholar 
    Lee, J.J. Algal symbiosis in larger foraminifera. Symbiosis. (2006). More

  • in

    Standardised bioassays reveal that mosquitoes learn to avoid compounds used in chemical vector control after a single sub-lethal exposure

    Webb, B. Cognition in insects. Philos. Trans. R. Soc B 367, 2715–2722 (2012).
    Google Scholar 
    Lorenz, K. The Foundations of Ethology 347–352 (Springer, 1981).
    Google Scholar 
    Davis, R. L. Olfactory memory formation in Drosophila: From molecular to systems neuroscience. Annu. Rev. Neurosci. 28, 275–302 (2005).CAS 
    PubMed 

    Google Scholar 
    Prokopy, R. J., Averill, A. L., Cooley, S. S. & Roitberg, C. A. Associative learning in egglaying site selection by apple maggot flies. Science 218, 76–77 (1982).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Tempel, B. L., Bonini, N., Dawson, D. R. & Quinn, W. G. Reward learning in normal and mutant Drosophila. Proc. Natl Acad. Sci. 80, 1482–1486 (1983).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Cook, D. F. Influence of previous mating experience on future mating success in maleLucilia cuprina (Diptera: Calliphoridae). J. Insect Behav. 8, 207–217 (1994).
    Google Scholar 
    Raubenheimer, D. & Tucker, D. Associative learning by locusts: Pairing of visual cues with consumption of protein and carbohydrate. Anim. Behav. 54, 1449–1459 (1997).CAS 
    PubMed 

    Google Scholar 
    Harari, A. R. & Landolt, P. J. Feeding experience enhances attraction of female Diaprepes abbreviatus (L.) (Coleoptera: Curculionidae) to food plant odors. 8. J. Insect Behav. 12, 415–422 (1999).
    Google Scholar 
    Menzel, R. Memory dynamics in the honeybee. J. Comp. Physiol. A 185, 323–340 (1999).ADS 

    Google Scholar 
    McCall, P. J. & Kelly, D. W. Learning and memory in disease vectors. Trends Parasitol. 18, 429–433 (2002).CAS 
    PubMed 

    Google Scholar 
    Alonso, W. J. & Schuck-Paim, C. The ‘ghosts’ that pester studies on learning in mosquitoes: Guidelines to chase them off. Med. Vet. Entomol. 20, 157–165 (2006).CAS 
    PubMed 

    Google Scholar 
    WHO. Global Vector Control Response 20217–22030 (World Health Organization, 2017).
    Google Scholar 
    Rocklöv, J. & Dubrow, R. Climate change: An enduring challenge for vector-borne disease prevention and control. Nat. Immunol. 21, 479–483 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    Bhatt, S. et al. The effect of malaria control on Plasmodium falciparum in Africa between 2000 and 2015. Nature 526, 207–211 (2015).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hemingway, J. et al. Averting a malaria disaster: Will insecticide resistance derail malaria control?. The Lancet 387, 1785–1788 (2016).
    Google Scholar 
    Martinez-Torres, D. et al. Molecular characterization of pyrethroid knockdown resistance (kdr) in the major malaria vector Anopheles gambiae ss. Insect Mol. Biol. 7, 179–184 (1998).CAS 
    PubMed 

    Google Scholar 
    Chandre, F. et al. Current distribution of a pyrethroid resistance gene (kdr) in Anopheles gambiae complex from West Africa and further evidence for reproductive isolation of the Mopti form. Parassitologia 41, 319–322 (1999).CAS 
    PubMed 

    Google Scholar 
    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).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Du, W. et al. Independent mutations in the Rdl locus confer dieldrin resistance to Anopheles gambiae and An. arabiensis. Insect Mol. Biol. 14, 179–183 (2005).CAS 
    PubMed 

    Google Scholar 
    Hemingway, J. & Ranson, H. Insecticide resistance in insect vectors of human disease. Annu. Rev. Entomol. 45, 371–391 (2000).CAS 
    PubMed 

    Google Scholar 
    Ranson, H. et al. Pyrethroid resistance in African anopheline mosquitoes: What are the implications for malaria control?. Trends Parasitol. 27, 91–98 (2011).CAS 
    PubMed 

    Google Scholar 
    Liu, N. Insecticide resistance in mosquitoes: Impact, mechanisms, and research directions. Annu. Rev. Entomol. 60, 537–559 (2015).CAS 
    PubMed 

    Google Scholar 
    Wood, O., Hanrahan, S., Coetzee, M., Koekemoer, L. & Brooke, B. Cuticle thickening associated with pyrethroid resistance in the major malaria vector Anopheles funestus. Parasit Vectors 3, 67 (2010).PubMed 
    PubMed Central 

    Google Scholar 
    Balabanidou, V. et al. Cytochrome P450 associated with insecticide resistance catalyzes cuticular hydrocarbon production in Anopheles gambiae. PNAS 113, 9268–9273 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Balabanidou, V. et al. Mosquitoes cloak their legs to resist insecticides. Proc Biol. Sci. 286, 20191091 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Muirhead-Thomson, R. C. The significance of irritability, behaviouristic avoidance and allied phenomena in malaria eradication. Bull. World Health Organ. 22, 721–734 (1960).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Georghiou, G. P. The evolution of resistance to pesticides. Annu. Rev. Ecol. Syst. 3, 133–168 (1972).CAS 

    Google Scholar 
    Grieco, J. P. et al. A new classification system for the actions of IRS chemicals traditionally used for malaria control. PLoS ONE 2, e716 (2007).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Chareonviriyaphap, T. et al. Review of insecticide resistance and behavioral avoidance of vectors of human diseases in Thailand. Parasit Vectors 6, 280 (2013).PubMed 
    PubMed Central 

    Google Scholar 
    Chilaka, N., Perkins, E. & Tripet, F. Visual and olfactory associative learning in the malaria vector Anopheles gambiae sensu stricto. Malar. J. 11, 27 (2012).PubMed 
    PubMed Central 

    Google Scholar 
    Vinauger, C., Lahondère, C., Cohuet, A., Lazzari, C. R. & Riffell, J. A. Learning and memory in disease vector insects. Trends Parasitol. 32, 761–771 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Carrasco, D. et al. Behavioural adaptations of mosquito vectors to insecticide control. Curr. Opin. Insect Sci. 34, 48–54 (2019).PubMed 

    Google Scholar 
    Tomberlin, J. K., Rains, G. C., Allan, S. A., Sanford, M. R. & Lewis, W. J. Associative learning of odor with food- or blood-meal by Culex quinquefasciatus Say (Diptera: Culicidae). Naturwissenschaften 93, 551–556 (2006).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Menda, G. et al. Associative learning in the dengue vector mosquito, Aedes aegypti: Avoidance of a previously attractive odor or surface color that is paired with an aversive stimulus. J. Exp. Biol. 216, 218–223 (2013).PubMed 
    PubMed Central 

    Google Scholar 
    Vinauger, C., Lutz, E. K. & Riffell, J. A. Olfactory learning and memory in the disease vector mosquito Aedes aegypti. J. Exp. Biol. 217, 2321–2330 (2014).PubMed 
    PubMed Central 

    Google Scholar 
    WHO. Guidelines for laboratory and field-testing of long-lasting insecticidal nets (World Health Organization, 2013).
    Google Scholar 
    WHO. Test procedures for insecticide resistance monitoring in malaria vector mosquitoes 2nd edn. (World Health Organization, 2016).
    Google Scholar 
    Rivero, A., Vézilier, J., Weill, M., Read, A. F. & Gandon, S. Insecticide control of vector-borne diseases: When is insecticide resistance a problem?. PLoS Pathog. 6, e1001000 (2010).PubMed 
    PubMed Central 

    Google Scholar 
    Maciel-de-Freitas, R. et al. Undesirable consequences of insecticide resistance following Aedes aegypti control activities due to a dengue outbreak. PLoS ONE 9, e92424 (2014).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Sherrard-Smith, E. et al. Systematic review of indoor residual spray efficacy and effectiveness against Plasmodium falciparum in Africa. Nat. Commun. 9, 4982 (2018).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Dusfour, I. et al. Management of insecticide resistance in the major Aedes vectors of arboviruses: Advances and challenges. PLoS Negl. Trop. Dis. 13, e0007615 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Perrin, A. et al. Variation in the susceptibility of urban Aedes mosquitoes infected with a densovirus. Sci. Rep. 10, 18654 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wilson, A. L. et al. The importance of vector control for the control and elimination of vector-borne diseases. PLoS Negl. Trop. Dis. 14, e0007831 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wills, A. B. et al. Physical durability of PermaNet 2.0 long-lasting insecticidal nets over three to 32 months of use in Ethiopia. Malar. J. 12, 242 (2013).PubMed 
    PubMed Central 

    Google Scholar 
    Gnanguenon, V., Azondekon, R., Oke-Agbo, F., Beach, R. & Akogbeto, M. Durability assessment results suggest a serviceable life of two, rather than three, years for the current long-lasting insecticidal (mosquito) net (LLIN) intervention in Benin. BMC Infect. Dis. 14, 69 (2014).PubMed 
    PubMed Central 

    Google Scholar 
    Boussougou-Sambe, S. T. et al. Physical integrity and residual bio-efficacy of used LLINs in three cities of the South-West region of Cameroon 4 years after the first national mass-distribution campaign. Malar. J. 16, 31 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Janko, M. M., Churcher, T. S., Emch, M. E. & Meshnick, S. R. Strengthening long-lasting insecticidal nets effectiveness monitoring using retrospective analysis of cross-sectional, population-based surveys across sub-Saharan Africa. Sci. Rep. 8, 17110 (2018).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Djènontin, A. et al. The residual life of bendiocarb on different substrates under laboratory and field conditions in Benin, Western Africa. BMC Res Notes 6, 458 (2013).PubMed 
    PubMed Central 

    Google Scholar 
    Mugenyi, L. et al. Estimating the optimal interval between rounds of indoor residual spraying of insecticide using malaria incidence data from cohort studies. PLoS ONE 15, e0241033 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kreppel, K. S. et al. Emergence of behavioural avoidance strategies of malaria vectors in areas of high LLIN coverage in Tanzania. Sci. Rep. 10, 14527 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Parker, J. E. A. et al. Infrared video tracking of Anopheles gambiae at insecticide-treated bed nets reveals rapid decisive impact after brief localised net contact. Sci. Rep. 5, 13392 (2015).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Spitzen, J., Koelewijn, T., Mukabana, W. R. & Takken, W. Visualization of house-entry behaviour of malaria mosquitoes. Malar. J. 15, 233 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Spitzen, J. & Takken, W. Keeping track of mosquitoes: A review of tools to track, record and analyse mosquito flight. Parasit. Vectors https://doi.org/10.1186/s13071-018-2735-6 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Jones, J., Murray, G. & McCall, P. J. A minimal 3D model of mosquito flight behavior around the human baited bed net. Malar. J. 20, (2021)Sougoufara, S., Ottih, E. C. & Tripet, F. The need for new vector control approaches targeting outdoor biting anopheline malaria vector communities. Parasit. Vectors 13, 295 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    Okumu, F. O. & Moore, S. J. Combining indoor residual spraying and insecticide-treated nets for malaria control in Africa: A review of possible outcomes and an outline of suggestions for the future. Malar. J. 10, 208 (2011).PubMed 
    PubMed Central 

    Google Scholar 
    Deletre, E. et al. Repellent, irritant and toxic effects of 20 plant extracts on adults of the malaria vector Anopheles gambiae Mosquito. PLoS One 8, e82103 (2013).ADS 
    PubMed 
    PubMed Central 

    Google Scholar  More