More stories

  • in

    Different increase rate in body mass of two marten species due to climate warming potentially reinforces interspecific competition

    1.Schmidt-Nielsen, K. Scaling: Why is Animal Size So Important? (Cambrige University Press, 1984).Book 

    Google Scholar 
    2.Sheridan, J. A. & Bickford, D. Shrinking body size as an ecological response to climate change. Nat. Clim. Change 1, 401–406. https://doi.org/10.1038/nclimate1259 (2011).ADS 
    Article 

    Google Scholar 
    3.Yom-Tov, Y., Heggberget, T. M., Wiig, O. & Yom-Tov, S. Body size changes among otters, Lutra lutra, in Norway: The possible effects of food availability and global warming. Oecologia 150, 155–160. https://doi.org/10.1007/s00442-006-0499-8 (2006).ADS 
    Article 
    PubMed 

    Google Scholar 
    4.Bergmann, C. Ueber die Verhältnisse der Wärmeökonomie der Tiere zu ihrer Grösse. Gött Stud. 3, 595–708 (1847).
    Google Scholar 
    5.Dehnel, A. Studies on the genus Sorex L.. Ann. Univ. Mariae Curie Sklodowska 5, 17–102 (1949).
    Google Scholar 
    6.Foster, J. B. Evolution of mammals on islands. Nature 202, 234–235. https://doi.org/10.1038/202234a0 (1964).ADS 
    Article 

    Google Scholar 
    7.Mayr, E. Geographical character gradients and climatic adaptation. Evolution 10, 105–108. https://doi.org/10.1111/j.1558-5646.1956.tb02836.x (1956).Article 

    Google Scholar 
    8.Allen, J. A. The Influence of physical conditions in the genesis of species. Radic. Rev. 1, 108–140 (1877).
    Google Scholar 
    9.Blackburn, T. M., Gaston, K. J. & Loder, N. Geographic gradients in body size: A clarification of Bergmann’s rule. Divers. Distrib. 5, 165–174. https://doi.org/10.1046/j.1472-4642.1999.00046.x (1999).Article 

    Google Scholar 
    10.Riemer, K., Guralnick, R. P. & White, E. P. No general relationship between mass and temperature in endothermic species. Elife 7, 16. https://doi.org/10.7554/eLife.27166 (2018).Article 

    Google Scholar 
    11.Ashton, K. G. Patterns of within-species body size variation of birds: Strong evidence for Bergmann’s rule. Glob. Ecol. Biogeogr. 11, 505–523. https://doi.org/10.1046/j.1466-822X.2002.00313.x (2002).Article 

    Google Scholar 
    12.Meiri, S. & Dayan, T. On the validity of Bergmann’s rule. J. Biogeogr. 30, 331–351. https://doi.org/10.1046/j.1365-2699.2003.00837.x (2003).Article 

    Google Scholar 
    13.Reig, S. Geographic variation in pine marten (Martes martes) and beech marten (M. foina) in Europe. J. Mammal. 73, 744–769. https://doi.org/10.2307/1382193 (1992).Article 

    Google Scholar 
    14.Blackburn, T. M. & Hawkins, B. A. Bergmann’s rule and the mammal fauna of northern North America. Ecography 27, 715–724. https://doi.org/10.1111/j.0906-7590.2004.03999.x (2004).Article 

    Google Scholar 
    15.Diniz, J. A. F., Bini, L. M., Rodriguez, M. A., Rangel, T. & Hawkins, B. A. Seeing the forest for the trees: Partitioning ecological and phylogenetic components of Bergmann’s rule in European Carnivora. Ecography 30, 598–608. https://doi.org/10.1111/j.2007.0906-7590.04988.x (2007).Article 

    Google Scholar 
    16.Hoy, S. R., Peterson, R. O. & Vucetich, J. A. Climate warming is associated with smaller body size and shorter lifespans in moose near their southern range limit. Glob. Change Biol. 24, 2488–2497. https://doi.org/10.1111/gcb.14015 (2018).ADS 
    Article 

    Google Scholar 
    17.Martin, J. M., Mead, J. I. & Barboza, P. S. Bison body size and climate change. Ecol. Evol. 8, 4564–4574. https://doi.org/10.1002/ece3.4019 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    18.Ozgul, A. et al. The dynamics of phenotypic change and the shrinking sheep of St. Kilda. Science 325, 464–467. https://doi.org/10.1126/science.1173668 (2009).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    19.Prokosch, J., Bernitz, Z., Bernitz, H., Erni, B. & Altwegg, R. Are animals shrinking due to climate change? Temperature-mediated selection on body mass in mountain wagtails. Oecologia 189, 841–849. https://doi.org/10.1007/s00442-019-04368-2 (2019).ADS 
    Article 
    PubMed 

    Google Scholar 
    20.Loarie, S. R. et al. The velocity of climate change. Nature 462, 1052–1055. https://doi.org/10.1038/nature08649 (2009).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    21.Schloss, C. A., Nunez, T. A. & Lawler, J. J. Dispersal will limit ability of mammals to track climate change in the Western Hemisphere. Proc. Natl. Acad. Sci. U.S.A. 109, 8606–8611. https://doi.org/10.1073/pnas.1116791109 (2012).ADS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    22.Williams, J. E. & Blois, J. L. Range shifts in response to past and future climate change: Can climate velocities and species’ dispersal capabilities explain variation in mammalian range shifts? J. Biogeogr. 45, 2175–2189. https://doi.org/10.1111/jbi.13395 (2018).Article 

    Google Scholar 
    23.Gordon, C. J. Effects of ambient temperature and exposure to 2450-MHz microwave radiation of evaporative heat loss in the mouse. J. Microw. Power Electromagn. Energy 17, 145–150 (1982).CAS 

    Google Scholar 
    24.Zub, K., Piertney, S., Szafranska, P. A. & Konarzewski, M. Environmental and genetic influences on body mass and resting metabolic rates (RMR) in a natural population of weasel Mustela nivalis. Mol. Ecol. 21, 1283–1293. https://doi.org/10.1111/j.1365-294X.2011.05436.x (2012).Article 
    PubMed 

    Google Scholar 
    25.Leyequien, E., de Boer, W. F. & Cleef, A. Influence of body size on coexistence of bird species. Ecol. Res. 22, 735–741. https://doi.org/10.1007/s11284-006-0311-6 (2007).Article 

    Google Scholar 
    26.Briscoe, N. J., Krockenberger, A., Handasyde, K. A. & Kearney, M. R. Bergmann meets Scholander: Geographical variation in body size and insulation in the koala is related to climate. J. Biogeogr. 42, 791–802. https://doi.org/10.1111/JBI.12445 (2015).Article 

    Google Scholar 
    27.Gardner, J. L., Peters, A., Kearney, M. R., Joseph, L. & Heinsohn, R. Declining body size: A third universal response to warming? Trends Ecol. Evol. 26, 285–291. https://doi.org/10.1016/J.TREE.2011.03.005 (2011).Article 
    PubMed 

    Google Scholar 
    28.Reyer, C. et al. Projections of regional changes in forest net primary productivity for different tree species in Europe driven by climate change and carbon dioxide. Ann. For. Sci. 71, 211–225. https://doi.org/10.1007/s13595-013-0306-8 (2014).Article 

    Google Scholar 
    29.Laidre, K. L. et al. Transient benefits of climate change for a high-Arctic polar bear (Ursus maritimus) subpopulation. Glob. Change Biol. 26, 6251–6265. https://doi.org/10.1111/gcb.15286 (2020).ADS 
    Article 

    Google Scholar 
    30.Yunger, J. A. Response of two low-density populations of Peromyscus leucopus to increased food availability. J. Mammal. 83, 267–279. https://doi.org/10.1644/1545-1542(2002)083%3c0267:rotldp%3e2.0.co;2 (2002).Article 

    Google Scholar 
    31.Monterroso, P., Francisco, D. R., Lukacs, P. M., Alves, P. C. & Ferreras, P. Ecological traits and the spatial structure of competitive coexistence among carnivores. Ecology. https://doi.org/10.1002/ecy.3059 (2020).Article 
    PubMed 

    Google Scholar 
    32.Dayan, T. & Simberloff, D. Ecological and community-wide character displacement: The next generation. Ecol. Lett. 8, 875–894. https://doi.org/10.1111/j.1461-0248.2005.00791.x (2005).Article 

    Google Scholar 
    33.Creel, S. & Creel, N. M. Limitation of African wild dogs by competition with larger carnivores. Conserv. Biol. 10, 526–538. https://doi.org/10.1046/j.1523-1739.1996.10020526.x (1996).Article 

    Google Scholar 
    34.Wereszczuk, A. & Zalewski, A. Spatial niche segregation of sympatric stone marten and pine marten—Avoidance of competition or selection of optimal habitat? PLoS ONE 10, e0139852. https://doi.org/10.1371/journal.pone.0139852 (2015).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    35.Pereboom, V. et al. Movement patterns, habitat selection, and corridor use of a typical woodland-dweller species, the European pine marten (Martes martes), in fragmented landscape. Can. J. Zool. 86, 983–991. https://doi.org/10.1139/Z08-076 (2008).Article 

    Google Scholar 
    36.Virgos, E., Zalewski, A., Rosalino, L. M. & Mergey, M. Habitat ecology of Martens species in Europe. A review of the evidence. In Biology and Conservation of Martens, Sables and Fishers: A New Synthesis (eds Aubry, K. B. et al.) 255–266 (Cornell University Press, 2012).
    Google Scholar 
    37.Goszczyński, J., Posłuszny, M., Pilot, M. & Gralak, B. Patterns of winter locomotion and foraging in two sympatric marten species: Martes martes and Martes foina. Can. J. Zool. 85, 239–249. https://doi.org/10.1139/Z06-212 (2007).ADS 
    Article 

    Google Scholar 
    38.Larroque, J., Ruette, S., Vandel, J. M. & Devillard, S. Where to sleep in a rural landscape? A comparative study of resting sites pattern in two syntopic Martes species. Ecography 38, 1129–1140. https://doi.org/10.1111/ecog.01133 (2015).Article 

    Google Scholar 
    39.Monakhov, V. G. & Hamilton, M. J. Spatial trends in the size structure of pine Marten Martes martes Linnaeus, 1756 (Mammalia: Mustelidae) within the species range. Russ. J. Ecol. 51, 250–259. https://doi.org/10.1134/s1067413620030108 (2020).CAS 
    Article 

    Google Scholar 
    40.Meiri, S., Dayan, T. & Simberloff, D. Carnivores, biases and Bergmann’s rule. Biol. J. Linn. Soc. 81, 579–588. https://doi.org/10.1111/j.1095-8312.2004.00310.x (2004).Article 

    Google Scholar 
    41.Keinath, D. A. et al. A global analysis of traits predicting species sensitivity to habitat fragmentation. Glob. Ecol. Biogeogr. 26, 115–127. https://doi.org/10.1111/geb.12509 (2017).Article 

    Google Scholar 
    42.Bailey, L. D. et al. Using different body size measures can lead to different conclusions about the effects of climate change. J. Biogeogr. 47, 1687–1697. https://doi.org/10.1111/jbi.13850 (2020).Article 

    Google Scholar 
    43.Buskirk, S. W. & Harlow, H. J. Body-fat dynamics of the American marten (Martes americana) in winter. J. Mammal. 70, 191–193. https://doi.org/10.2307/1381687 (1989).Article 

    Google Scholar 
    44.Wereszczuk, A.et al. Various responses of pine marten
    morphology and demography to temporal climate changes and primary productivity. PREPRINT (Version 1) available at
    Research Square https://doi.org/10.21203/rs.3.rs-1021314/v1 (2021)45.Desy, E. A. & Batzli, G. O. Effects of food availability and predation on prairie vole demography—A field experiment. Ecology 70, 411–421. https://doi.org/10.2307/1937546 (1989).Article 

    Google Scholar 
    46.Geist, V. Bergmann rule is invalid. Can. J. Zool. 65, 1035–1038. https://doi.org/10.1139/z87-164 (1987).Article 

    Google Scholar 
    47.Nemani, R. R. et al. Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science 300, 1560–1563. https://doi.org/10.1126/science.1082750 (2003).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    48.Svensson, B. M., Carlsson, B. A. & Melillo, J. M. Changes in species abundance after seven years of elevated atmospheric CO2 and warming in a Subarctic birch forest understorey, as modified by rodent and moth outbreaks. PeerJ 6, e4843. https://doi.org/10.7717/peerj.4843 (2018).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    49.Zalewski, A., Jedrzejewski, W. & Jedrzejewska, B. Mobility and home range use by pine martens (Martes martes) in a Polish primeval forest. Ecoscience 11, 113–122. https://doi.org/10.1080/11956860.2004.11682815 (2004).Article 

    Google Scholar 
    50.Krebs, C. J., Cowcill, K., Boonstra, R. & Kenney, A. J. Do changes in berry crops drive population fluctuations in small rodents in the southwestern Yukon? J. Mammal. 91, 500–509. https://doi.org/10.1644/09-mamm-a-005.1 (2010).Article 

    Google Scholar 
    51.Selas, V., Kobro, S. & Sonerud, G. A. Population fluctuations of moths and small rodents in relation to plant reproduction indices in southern Norway. Ecosphere 4, 1–11. https://doi.org/10.1890/es13-00228.1 (2013).Article 

    Google Scholar 
    52.Yom-Tov, Y., Yom-Tov, S. & Jarrell, G. Recent increase in body size of the American marten Martes americana in Alaska. Biol. J. Linn. Soc. 93, 701–707. https://doi.org/10.1111/j.1095-8312.2007.00950.x (2008).Article 

    Google Scholar 
    53.Caryl, F. M., Quine, C. P. & Park, K. J. Martens in the matrix: the importance of nonforested habitats for forest carnivores in fragmented landscapes. J. Mammal. 93, 464–474. https://doi.org/10.1644/11-mamm-a-149.1 (2012).Article 

    Google Scholar 
    54.Zalewski, A. Factors affecting the duration of activity by pine martens (Martes martes) in the Bialowieza National Park, Poland. J. Zool. 251, 439–447. https://doi.org/10.1111/j.1469-7998.2000.tb00799.x (2000).Article 

    Google Scholar 
    55.Zalewski, A. Factors affecting selection of resting site type by pine marten in primeval deciduous forests (Bialowieza National Park, Poland). Acta Theriol. 42, 271–288. https://doi.org/10.4098/AT.arch.97-29 (1997).Article 

    Google Scholar 
    56.Gilbert, J. H., Zollner, P. A., Green, A. K., Wright, J. L. & Karasov, W. H. Seasonal field metabolic rates of American martens in Wisconsin. Am. Midl. Nat. 162, 327–334. https://doi.org/10.1674/0003-0031-162.2.327 (2009).Article 

    Google Scholar 
    57.Zub, K., Szafranska, P. A., Konarzewski, M. & Speakman, J. R. Effect of energetic constraints on distribution and winter survival of weasel males. J. Anim. Ecol. 80, 259–269. https://doi.org/10.1111/j.1365-2656.2010.01762.x (2011).Article 
    PubMed 

    Google Scholar 
    58.Hantak, M. M., McLean, B. S., Li, D. & Guralnick, R. P. Mammalian body size is determined by interactions between climate, urbanization, and ecological traits. Commun. Biol. https://doi.org/10.1038/s42003-021-02505-3 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    59.Yom-Tov, Y., Yom-Tov, S. & Baagoe, H. Increase of skull size in the red fox (Vulpes vulpes) and Eurasian badger (Meles meles) in Denmark during the twentieth century: An effect of improved diet? Evol. Ecol. Res. 5, 1037–1048 (2003).
    Google Scholar 
    60.Wereszczuk, A., Leblois, R. & Zalewski, A. Genetic diversity and structure related to expansion history and habitat isolation: Stone marten populating rural-urban habitats. BMC Ecol. 17, 46. https://doi.org/10.1186/s12898-017-0156-6 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    61.Phillips, B. L., Brown, G. P., Webb, J. K. & Shine, R. Invasion and the evolution of speed in toads. Nature 439, 803. https://doi.org/10.1038/439803a (2006).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    62.Sidorovich, V., Kruuk, H. & Macdonald, D. W. Body size, and interactions between European and American mink (Mustela lutreola and M. vison) in Eastern Europe. J. Zool. 248, 521–527. https://doi.org/10.1017/s0952836999008110 (1999).Article 

    Google Scholar 
    63.Pagh, S., Hansen, M. S., Jensen, B., Pertoldi, C. & Chriel, M. Variability in body mass and sexual dimorphism in Danish red foxes (Vulpes vulpes) in relation to population density. Zool. Ecol. 28, 1–9. https://doi.org/10.1080/21658005.2017.1409997 (2018).Article 

    Google Scholar 
    64.Zalewski, A. & Bartoszewicz, M. Phenotypic variation of an alien species in a new environment: The body size and diet of American mink over time and at local and continental scales. Biol. J. Linn. Soc. 105, 681–693. https://doi.org/10.1111/j.1095-8312.2011.01811.x (2012).Article 

    Google Scholar 
    65.Balestrieri, A. et al. Range expansion of the pine marten (Martes martes) in an agricultural landscape matrix (NW Italy). Mamm. Biol. 75, 412–419. https://doi.org/10.1016/j.mambio.2009.05.003 (2010).Article 

    Google Scholar 
    66.Rosellini, S., Osorio, E., Ruiz-Gonzalez, A., Isabel, A. P. & Barja, I. Monitoring the small-scale distribution of sympatric European pine martens (Martes martes) and stone martens (Martes foina): A multievidence approach using faecal DNA analysis and camera-traps. Wildl. Res. 35, 434–440. https://doi.org/10.1071/wr07030 (2008).Article 

    Google Scholar 
    67.Delibes, M. Interspecific competition and the habitat of the stone marten Martes foina (Erxleben 1777) in Europe. Acta Zool. Fennica 174, 229–231 (1983).
    Google Scholar 
    68.Zabala, J., Zuberogoitia, I. & Antonio Martinez-Climent, J. Testing for niche segregation between two abundant carnivores using presence-only data. Folia Zool. 58, 385–395 (2009).
    Google Scholar 
    69.Jacob, D. et al. Climate impacts in Europe under +1.5 degrees C global warming. Earths Fut. 6, 264–285. https://doi.org/10.1002/2017ef000710 (2018).ADS 
    Article 

    Google Scholar 
    70.Fewster, R. M., Buckland, S. T., Siriwardena, G. M., Baillie, S. R. & Wilson, J. D. Analysis of population trends for farmland birds using generalized additive models. Ecology 81, 1970–1984. https://doi.org/10.2307/177286 (2000).Article 

    Google Scholar 
    71.Wood, S. N. Generalized Additive Models: An Introduction with R 2nd edn. (Chapman and Hall/CRC, 2017).Book 

    Google Scholar 
    72.R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020).73.Lenssen, N. J. L. et al. Improvements in the GISTEMP uncertainty model. J. Geophys. Res. Atmos. 124, 6307–6326. https://doi.org/10.1029/2018jd029522 (2019).ADS 
    Article 

    Google Scholar  More

  • in

    Great tits feed their nestlings with more but smaller prey items and fewer caterpillars in cities than in forests

    1.Mckinney, M. L. Effects of urbanization on species richness : a review of plants and animals. Urban Ecosyst. 11, 161–176 (2008).
    Google Scholar 
    2.Anderson, P. M. L., Okereke, C., Rudd, A. & Parnell, S. Urbanization, biodiversity and ecosystem services: challenges and opportunities a global assessment (Springer, Berlin, 2013). https://doi.org/10.1007/978-94-007-7088-1.Book 

    Google Scholar 
    3.Newhouse, M. J., Marra, P. P. & Johnson, L. S. Reproductive success of house wrens in suburban and rural landscapes. Wilson J. Ornithol. 120, 99–104 (2008).
    Google Scholar 
    4.Biard, C. et al. Growing in Cities: An Urban Penalty for Wild Birds? A Study of Phenotypic Differences between Urban and Rural Great Tit Chicks (Parus major). Front. Ecol. Evol. 5, (2017). https://doi.org/10.3389/fevo.2017.000795.Seress, G. et al. Urbanization, nestling growth and reproductive success in a moderately declining house sparrow population. J. Avian Biol. 43, 403–414 (2012).
    Google Scholar 
    6.Glądalski, M. et al. Differences in the breeding success of Blue Tits Cyanistes caeruleus between a forest and an urban area : a long-term study. Acta Ornithol. 52, 59–68 (2017).
    Google Scholar 
    7.Teglhøj, P. G. A comparative study of insect abundance and reproductive success of barn swallows Hirundo rustica in two urban habitats. J. Avian Biol. 48, 846–853 (2017).
    Google Scholar 
    8.Chamberlain, D. E. et al. Avian productivity in urban landscapes: A review and meta-analysis. Ibis (Lond. 1859). 151, 1–18 (2009).
    Google Scholar 
    9.Chatelain, M. et al. Urban metal pollution explains variation in reproductive outputs in great tits and blue tits. Sci. Total Environ. 776, 145966 (2021).ADS 
    CAS 

    Google Scholar 
    10.Capilla-Lasheras, P. et al. A global meta-analysis reveals more variable life histories in urban birds compared to their non-urban neighbours. Preprint (2021). https://doi.org/10.1101/2021.09.24.461498.11.Caizergues, A. et al. An avian urban morphotype: how the city environment shapes greattit morphology at different life stages. Urban Ecosyst. 24, 929–941 (2021).
    Google Scholar 
    12.Corsini, M. et al. Growing in the city: Urban evolutionary ecology of avian growth rates. Evol. Appl. 14, 69–84 (2021).PubMed 

    Google Scholar 
    13.Seress, G. & Liker, A. Habitat urbanization and its effects on birds. Acta Zool. Acad. Sci. Hungaricae 61, 373–408 (2015).
    Google Scholar 
    14.Bailly, J. et al. From eggs to fledging: negative impact of urban habitat on reproduction in two tit species. J. Ornithol. 157, 377–392 (2016).
    Google Scholar 
    15.Seress, G. et al. Impact of urbanization on abundance and phenology of caterpillars and consequences for breeding in an insectivorous bird. Ecol. Appl. 28, 1143–1156 (2018).PubMed 

    Google Scholar 
    16.Seress, G., Sándor, K., Evans, K. L. & Liker, A. Food availability limits avian reproduction in the city: an experimental study on great tits Parus major. J. Anim. Ecol. 89, 1570–1580 (2020).PubMed 

    Google Scholar 
    17.Krištín, A. & Patočka, J. Birds as predators of Lepidoptera: Selected examples. Biologia (Bratisl). 52, 319–326 (1997).
    Google Scholar 
    18.Perrins, C. M. Tits and their caterpillar food supply. Ibis (Lond. 1859). 133, 49–54 (1991).
    Google Scholar 
    19.Ramsay, S. L. & Houston, D. C. Amino acid composition of some woodland arthropods and its implications for breeding tits and other passerines. Ibis (Lond. 1859). 145, 227–232 (2003).
    Google Scholar 
    20.Partali, V., Liaaen-Jensen, S., Slagsvold, T. & Lifjeld, J. T. Carotenoids in food chain studies—II. The food chain of Parus SPP. Monitored by carotenoid analysis. Comp. Biochem. Physiol. Part B Comp. Biochem. 87, 885–888 (1987).
    Google Scholar 
    21.Isaksson, C., Johansson, A. & Andersson, S. Egg yolk carotenoids in relation to habitat and reproductive investment in the great Tit Parus major. Physiol. Biochem. Zool. 81, 112–118 (2008).CAS 
    PubMed 

    Google Scholar 
    22.Isaksson, C., Örnborg, J., Stephensen, E. & Andersson, S. Plasma glutathione and carotenoid coloration as potential biomarkers of environmental stress in great tits. EcoHealth 2, 138–146 (2005).
    Google Scholar 
    23.Arnold, K. E., Ramsay, S. L., Henderson, L. & Larcombe, S. D. Seasonal variation in diet quality: antioxidants, invertebrates and blue tits Cyanistes caeruleus. Biol. J. Linn. Soc. 99, 708–717 (2010).
    Google Scholar 
    24.Fenoglio, M. S., Rossetti, M. R. & Videla, M. Negative effects of urbanization on terrestrial arthropod communities: a meta-analysis. Glob. Ecol. Biogeogr. 29, 1412–1429 (2020).
    Google Scholar 
    25.Piano, E. et al. Urbanization drives cross-taxon declines in abundance and diversity at multiple spatial scales. Glob. Chang. Biol. 26, 1196–1211 (2020).ADS 
    PubMed 

    Google Scholar 
    26.Nadolski, J., Marciniak, B., Loga, B., Michalski, M. & Bańbura, J. Long-term variation in the timing and height of annual peak abundance of caterpillars in tree canopies: Some effects on a breeding songbird. Ecol. Indic. 121, 107120 (2021).
    Google Scholar 
    27.Sepp, T., McGraw, K. J., Kaasik, A. & Giraudeau, M. A review of urban impacts on avian life-history evolution: does city living lead to slower pace of life?. Glob. Chang. Biol. 24, 1452–1469 (2018).ADS 
    PubMed 

    Google Scholar 
    28.Miyashita, T., Shinkai, A. & Chida, T. The effects of forest fragmentation on web spider communities in urban areas. Biol. Conserv. 86, 357–364 (1998).
    Google Scholar 
    29.Merckx, T. et al. Body-size shifts in aquatic and terrestrial urban communities. Nature 558, 113–116 (2018).ADS 
    CAS 
    PubMed 

    Google Scholar 
    30.Ishitani, M., Kotze, D. J. & Niemelä, J. Changes in carabid beetle assemblages across an urban-rural gradient in Japan. Ecography (Cop.) 26, 481–489 (2003).
    Google Scholar 
    31.Pollock, C. J., Capilla-Lasheras, P., McGill, R. A. R., Helm, B. & Dominoni, D. M. Integrated behavioural and stable isotope data reveal altered diet linked to low breeding success in urban-dwelling blue tits (Cyanistes caeruleus). Sci. Rep. 7, 5014 (2017).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    32.Jarrett, C., Powell, L. L., McDevitt, H., Helm, B. & Welch, A. J. Bitter fruits of hard labour: diet metabarcoding and telemetry reveal that urban songbirds travel further for lower-quality food. Oecologia 193, 377–388 (2020).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    33.Isaksson, C. & Andersson, S. Carotenoid diet and nestling provisioning in urban and rural great tits Parus major. J. Avian Biol. 38, 564–572 (2007).
    Google Scholar 
    34.Sinkovics, C. A fiókatáplálék mennyisége , minősége és szezonalitása városi és erdei széncinege (Parus major) populációkban. (Szent István University, 2014).35.Tremblay, I., Thomas, D., Blondel, J., Perret, P. & Lambrechts, M. M. The effect of habitat quality on foraging patterns, provisioning rate and nestling growth in Corsican Blue Tits Parus caeruleus. Ibis (Lond. 1859). 147, 17–24 (2005).
    Google Scholar 
    36.Schwagmeyer, P. L. & Mock, D. W. Parental provisioning and offspring fitness: size matters. Anim. Behav. 75, 291–298 (2008).
    Google Scholar 
    37.Lease, H. M. & Wolf, B. O. Lipid content of terrestrial arthropods in relation to body size, phylogeny, ontogeny and sex. Physiol. Entomol. 36, 29–38 (2011).CAS 

    Google Scholar 
    38.Riddington, R. & Gosler, A. G. Differences in reproductive success and parental qualities between habitats in the Great Tit Parus major. Ibis (Lond. 1859) 137, 371–378 (1995).
    Google Scholar 
    39.Mennechez, G. & Clergeau, P. Effect of urbanisation on habitat generalists: starlings not so flexible?. Acta Oecologica 30, 182–191 (2006).ADS 

    Google Scholar 
    40.Shawkey, M. D., Bowman, R. & Woolfenden, G. E. Why is brood reduction in Florida Scrub-Jays higher in suburban than in wildland habitats?. Can. J. Zool. 82, 1427–1435 (2004).
    Google Scholar 
    41.Robb, G. N., McDonald, R. A., Chamberlain, D. E. & Bearhop, S. Food for thought: supplementary feeding as a driver of ecological change in avian populations. Front. Ecol. Environ. 6, 476–484 (2008).
    Google Scholar 
    42.Sauter, A., Bowman, R., Schoech, S. J. & Pasinelli, G. Does optimal foraging theory explain why suburban Florida scrub-jays (Aphelocoma coerulescens) feed their young human-provided food ?. Behav. Ecol. Sociobiol. 60, 465–474 (2006).
    Google Scholar 
    43.Heiss, R. S., Clark, A. B. & McGowan, K. J. Growth and nutritional state of American Crow nestlings vary between urban and rural habitats. Ecol. Appl. 19, 829–839 (2009).PubMed 

    Google Scholar 
    44.Graveland, J. & van Gijzen, T. Arthropods and seeds are not sufficient as calcium sources for shell formation and skeletal growth in passerines. Ardea 82, 299–314 (1994).
    Google Scholar 
    45.Ricklefs, R. In Avian Biology (eds. Farner, D., King, J. & Parkes, K.) 1–83 (Academic Press, 1983).46.Peach, W. J., Vincent, K. E., Fowler, J. A. & Grice, P. V. Reproductive success of house sparrows along an urban gradient. Anim. Conserv. 11, 493–503 (2008).
    Google Scholar 
    47.Johnston, R. D. Effects of diet quality on the nestling growth of a wild insectivorous passerine, the house martin Delichon urbica. Funct. Ecol. 7, 255–266 (1993).
    Google Scholar 
    48.Marciniak, B., Nadolski, J., Nowakowska, M., Loga, B. & Bańbura, J. Habitat and annual variation in arthropod abundance affects Blue Tit Cyanistes caeruleus reproduction. Acta Ornithol. 42, 53–62 (2007).
    Google Scholar 
    49.Pagani-Núñez, E. & Senar, J. C. One hour of sampling is enough: great tit Parus major parents feed their nestlings consistently across time. Acta Ornithol. 48, 194–200 (2013).
    Google Scholar 
    50.Betts, M. M. The behaviour of a pair of great tits at the nest. Br. Birds 48, 77–82 (1955).
    Google Scholar 
    51.Van Balen, J. H. A comparative study of the breeding ecology of the great tit Parus major in different habitats. Ardea 61, 1–93 (1973).
    Google Scholar 
    52.Seress, G. et al. Effects of capture and video-recording on the behavior and breeding success of Great Tits in urban and forest habitats. J. F. Ornithol. 88, 299–312 (2017).
    Google Scholar 
    53.Free Software Foundation. vlc. (1991).54.Sinkovics, C., Seress, G., Fábián, V., Sándor, K. & Liker, A. Obtaining accurate measurements of the size and volume of insects fed to nestlings from video recordings. J. F. Ornithol. 89, 165–172 (2018).
    Google Scholar 
    55.R Core Team. R: A language and environment for statistical computing. (2017). Available at: https://www.r-project.org/.56.Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D. & R Core Team. nlme: Linear and Nonlinear Mixed Effects Models. (2021). R package version 3.1-153, https://CRAN.R-project.org/package=nlme.57.Lenth, R. emmeans: Estimated Marginal Means, aka Least-Squares Means. (2018). R package version 1.3.1. https://CRAN.R-project.org/package=emmeans58.Venables, W. N. & Ripley, B. D. Modern applied statistics with S (Springer, Berlin, 2002).MATH 

    Google Scholar 
    59.Fox, J. & Weisberg, S. An R Companion to Applied Regression (Sage, Thousand Oaks, 2011).
    Google Scholar 
    60.Hothorn, T., Bretz, F. & Westfall, P. Simultaneous inference in general parametric models. Biometrical J. 3, 346–363 (2008).MathSciNet 
    MATH 

    Google Scholar 
    61.Ruxton, G. D. & Beauchamp, G. Time for some a priori thinking about post hoc testing. Behav. Ecol. 19, 690–693 (2008).
    Google Scholar 
    62.Bolker, B. M. et al. Generalized linear mixed models :a practical guide for ecology and evolution. Trends Ecol. Evol. 24, 127–135 (2009).PubMed 

    Google Scholar 
    63.Vincze, E. et al. Great tits take greater risk toward humans and sparrowhawks in urban habitats than in forests. Ethology 125, 686–701 (2019).
    Google Scholar 
    64.Zuur, A. F., Ieno, E. N., Walker, N. J., Saveliev, A. A. & Smith, G. M. Mixed effects models and extensions in ecology with R (Springer, New York, 2009).MATH 

    Google Scholar 
    65.Serrano-Davies, E. & Sanz, J. J. Habitat structure modulates nestling diet composition and fitness of Blue Tits Cyanistes caeruleus in the Mediterranean region. Bird Study 64, 295–305 (2017).
    Google Scholar 
    66.Senar, J. C., Manzanilla, A. & Mazzoni, D. A comparison of the diet of urban and forest great tits in a Mediterranean habitat. Anim. Biodivers. Conserv. 44(2), 321–327 (2021).
    Google Scholar 
    67.Narango, D. L., Tallamy, D. W. & Marra, P. P. Nonnative plants reduce population growth of an insectivorous bird. Proc. Natl. Acad. Sci. 115, 201809259 (2018).
    Google Scholar 
    68.de Satgé, J. et al. Urbanisation lowers great tit Parus major breeding success at multiple spatial scales. J. Avian Biol. 50, (2019). https://doi.org/10.1111/jav.0210869.Baldan, D. & Ouyang, J. Q. Urban resources limit pair coordination over offspring provisioning. Sci. Rep. 10, 15888 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    70.Mennechez, G. & Clergeau, P. In Avian Ecology and Conservation in an Urbanizing World (ed. Marzluff, J. M.) 275–287 (Springer, 2001). https://doi.org/10.1007/978-1-4615-1531-9_1371.Meyrier, E. et al. Happy to breed in the city? Urban food resources limit reproductive output in Western Jackdaws. Ecol. Evol. 7, 1363–1374 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    72.Kingsolver, J. G. & Woods, H. A. Thermal sensitivity of growth and feeding in Manduca sexta caterpillars. Physiol. Zool. 70, 631–638 (1997).CAS 
    PubMed 

    Google Scholar 
    73.Warren, M. S. et al. The decline of butterflies in Europe: Problems, significance, and possible solutions. Proc. Natl. Acad. Sci. 118, e2002551117 (2021).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    74.Burghardt, K. T., Tallamy, D. W., Philips, C. & Shropshire, K. J. Non-native plants reduce abundance, richness, and host specialization in lepidopteran communities. Ecosphere 1, 1–22 (2010).
    Google Scholar 
    75.Tallamy, D. W. & Shriver, W. G. Are declines in insects and insectivorous birds related?. Condor 123, 1–8 (2021).
    Google Scholar 
    76.Mackenzie, J. A., Hinsley, S. A. & Harrison, N. M. Parid foraging choices in urban habitat and the consequences for fitness. Ibis (Lond. 1859) 156, 591–605 (2014).
    Google Scholar 
    77.Narango, D. L., Tallamy, D. W. & Marra, P. P. Native plants improve breeding and foraging habitat for an insectivorous bird. Biol. Conserv. 213, 42–50 (2017).
    Google Scholar 
    78.Cholewa, M. & Wesołowski, T. Nestling food of European hole-nesting passerines: do we know enough to test the adaptive hypotheses on breeding seasons?. Acta Ornithol. 46, 105–116 (2011).
    Google Scholar  More

  • in

    Air temperature drives the evolution of mid-infrared optical properties of butterfly wings

    1.Kinoshita, S., Structural Colors in the Realm of Nature (World Scientific, 2008).2.Sun, J., Bhushan, B. & Tong, J. Structural coloration in nature. RSC Adv. 3, 14862–14889 (2013).CAS 
    ADS 

    Google Scholar 
    3.Whitney, H. M. et al. Floral iridescence, produced by diffractive optics, acts as a cue for animal pollinators. Science 323, 130–133 (2009).CAS 
    PubMed 
    ADS 

    Google Scholar 
    4.Whitney, H. M., Kolle, M., Alvarez-Fernandez, R., Steiner, U. & Glover, B. J. Contributions of iridescence to floral patterning. Commun. Integr. Biol. 2, 230–232 (2009).PubMed 
    PubMed Central 

    Google Scholar 
    5.Moyroud, E. et al. Disorder in convergent floral nanostructures enhances signalling to bees. Nature 550, 469–474 (2017).CAS 
    PubMed 
    ADS 

    Google Scholar 
    6.Mason, C. W. Structural colors in feathers. II. J. Phys. Chem. 27, 401–448 (2005).
    Google Scholar 
    7.Mason, C. W. Structural colors in insects. III. J. Phys. Chem. 31, 1856–1872 (2005).
    Google Scholar 
    8.Roberts, N. W., Marshall, N. J. & Cronin, T. W. High levels of reflectivity and pointillist structural color in fish, cephalopods, and beetles. Proc. Natl. Acad. Sci. 109, E3387–E3387 (2012).CAS 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    9.Zi, J. et al. Coloration strategies in peacock feathers. Proc. Natl. Acad. Sci. 100, 12576–12578 (2003).CAS 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    10.McCoy, D. E., Feo, T., Harvey, T. A. & Prum, R. O. Structural absorption by barbule microstructures of super black bird of paradise feathers. Nat. Commun. 9, 1–8 (2018).CAS 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    11.Teyssier, J., Saenko, S. V., Van Der Marel, D. & Milinkovitch, M. C. Photonic crystals cause active colour change in chameleons. Nat. Commun. 6, 1–7 (2015).
    Google Scholar 
    12.Cooper, K. M., Hanlon, R. T. & Budelmann, B. U. Physiological color change in squid iridophores. Cell Tissue Res. 259, 15–24 (1990).CAS 
    PubMed 

    Google Scholar 
    13.Glover, B. J. & Whitney, H. M. Structural colour and iridescence in plants: The poorly studied relations of pigment colour. Ann. Bot. 105, 505–511 (2010).PubMed 
    PubMed Central 

    Google Scholar 
    14.Shi, N. N. et al. Keeping cool: Enhanced optical reflection and radiative heat dissipation in Saharan silver ants. Science 349, 298–301 (2015).CAS 
    PubMed 
    ADS 

    Google Scholar 
    15.Preciado, J. A. et al. Radiative properties of polar bear hair. Am. Soc. Mech. Eng. Bioeng. Div. 54, 57–58 (2002).
    Google Scholar 
    16.Bosi, S. G., Hayes, J., Large, M. C. J. & Poladian, L. Color, iridescence, and thermoregulation in Lepidoptera. Appl. Opt. 47, 5235–5241 (2008).PubMed 
    ADS 

    Google Scholar 
    17.Kinoshita, S., Yoshioka, S., Fujii, Y. & Okamoto, N. Photophysics of structural color in the Morpho butterflies. Forma-Tokyo 17, 103–121 (2002).
    Google Scholar 
    18.Tabata, H., Kumazawa, K., Funakawa, M., Takimoto, J. I. & Akimoto, M. Microstructures and optical properties of scales of butterfly wings. Opt. Rev. 3, 139–145 (1996).
    Google Scholar 
    19.Krishna, A. et al. Infrared optical and thermal properties of microstructures in butterfly wings. Proc. Natl. Acad. Sci. USA 117, 1566–1572 (2020).CAS 
    PubMed 
    PubMed Central 
    ADS 

    Google Scholar 
    20.Tsai, C. C. et al. Physical and behavioral adaptations to prevent overheating of the living wings of butterflies. Nat. Commun. 11, 1–14 (2020).ADS 

    Google Scholar 
    21.Wilts, B. D., Vey, A. J. M., Briscoe, A. D. & Stavenga, D. G. Longwing (Heliconius) butterflies combine a restricted set of pigmentary and structural coloration mechanisms. BMC Evol. Biol. 17, 1–12 (2017).
    Google Scholar 
    22.Berthier, S. Thermoregulation and spectral selectivity of the tropical butterfly Prepona meander: A remarkable example of temperature auto-regulation. Appl. Phys. A Mater. Sci. Process. 80, 1397–1400 (2005).CAS 
    ADS 

    Google Scholar 
    23.Vukusic, P. & Sambles, J. R. Photonic structures in biology. Nature 424, 852–855 (2003).CAS 
    PubMed 
    ADS 

    Google Scholar 
    24.Siddique, R. H., Diewald, S., Leuthold, J. & Hölscher, H. Theoretical and experimental analysis of the structural pattern responsible for the iridescence of Morpho butterflies. Opt. Express 21, 14351–14361 (2013).PubMed 
    ADS 

    Google Scholar 
    25.Steindorfer, M. A., Schmidt, V., Belegratis, M., Stadlober, B. & Krenn, J. R. Detailed simulation of structural color generation inspired by the Morpho butterfly. Opt. Express 20, 21485–21494 (2012).PubMed 
    ADS 

    Google Scholar 
    26.Munro, J. T. et al. Climate is a strong predictor of near-infrared reflectance but a poor predictor of colour in butterflies. Proc. R. Soc. B Biol. Sci. 286, 20190234 (2019).
    Google Scholar 
    27.Incropera, F. P., DeWitt, D. P., Bergman, T. L. & Lavine, A. S. Fundamentals of Heat and Mass Transfer (Wiley, 2006).28.DeWitt, D. P., Incropera, F. P. “Physics of thermal radiation” in Theory and Practice of Radiation Thermometry, (1988), pp. 19–89.29.Howell, J. R., Menguc, M. P., Siegel, R. Thermal Radiation Heat Transfer (CRC Press, 2016).30.Lord, S. D. A new software tool for computing earth’s atmospheric transmission of near- and far-infrared radiation. NASA Tech. Memo. 103957 (1992).31.Raman, A. P., Anoma, M. A., Zhu, L., Rephaeli, E. & Fan, S. Passive radiative cooling below ambient air temperature under direct sunlight. Nature 515, 540–544 (2014).CAS 
    PubMed 
    ADS 

    Google Scholar 
    32.Krishna, A. & Lee, J. Morphology-driven emissivity of microscale tree-like structures for radiative thermal management. Nanoscale Microscale Thermophys. Eng. 22, 124–136 (2018).CAS 
    ADS 

    Google Scholar 
    33.Zhai, Y. et al. Scalable-manufactured randomized glass-polymer hybrid metamaterial for daytime radiative cooling. Science 355, 1062–1066 (2017).CAS 
    PubMed 
    ADS 

    Google Scholar 
    34.Zhang, X. A. et al. Dynamic gating of infrared radiation in a textile. Science 623, 1–15 (2019).
    Google Scholar 
    35.Xu, C., Stiubianu, G. T. & Gorodetsky, A. A. Adaptive infrared-reflecting systems inspired by cephalopods. Science 359, 1495–1500 (2018).CAS 
    PubMed 
    ADS 

    Google Scholar 
    36.Xie, D. et al. Broadband omnidirectional light reflection and radiative heat dissipation in white beetles: Goliathus goliatus. Soft Matter 15, 4294–4300 (2019).CAS 
    PubMed 
    ADS 

    Google Scholar 
    37.Heinrich, B. Thermoregulation in endothermic insects. Science 185, 747–756 (1974).CAS 
    PubMed 
    ADS 

    Google Scholar 
    38.Kingsolver, J. G. Thermoregulation and flight in Colias butterflies: elevational patterns and mechanistic limitations. Ecology 64, 534–545 (1983).
    Google Scholar 
    39.Rawlins, J. E. Thermoregulation by the black swallowtail butterfly, Papilio polyxenes (Lepidoptera: Papilionidae). Ecology 61, 345–357 (1980).
    Google Scholar 
    40.Clench, H. K. Behavioral thermoregulation in butterflies. Ecology 47, 1021–1034 (1966).
    Google Scholar 
    41.Bonebrake, T. C., Boggs, C. L., Stamberger, J. A., Deutsch, C. A. & Ehrlich, P. R. From global change to a butterfly flapping: Biophysics and behaviour affect tropical climate change impacts. Proc. R. Soc. B Biol. Sci. 281, 20141264 (2014).
    Google Scholar 
    42.Nève, G. & Hall, C. Variation of thorax flight temperature among twenty Australian butterflies (Lepidoptera: Papilionidae, Nymphalidae, Pieridae, Hesperiidae, Lycaenidae). Eur. J. Entomol. 113, 571–578 (2016).
    Google Scholar 
    43.MacLean, H. J., Higgins, J. K., Buckley, L. B. & Kingsolver, J. G. Morphological and physiological determinants of local adaptation to climate in Rocky Mountain butterflies. Conserv. Physiol. 4, 1 (2016).
    Google Scholar 
    44.Tsai, C. C., et al., Butterflies regulate wing temperatures using radiative cooling in 2017 Conference on Lasers and Electro-Optics (CLEO), (IEEE, 2017), p. 9.45.Watanabe, K., Hoshino, T., Kanda, K., Haruyama, Y. & Matsui, S. Brilliant blue observation from a Morpho-butterfly-scale quasi-structure. Jpn. J. Appl. Phys. 44, L48–L50 (2005).CAS 
    ADS 

    Google Scholar 
    46.Wilts, B. D., Giraldo, M. A. & Stavenga, D. G. Unique wing scale photonics of male Rajah Brooke’s birdwing butterflies. Front. Zool. 13, 1–12 (2016).
    Google Scholar 
    47.De Keyser, R., Breuker, C. J., Hails, R. S., Dennis, R. L. H. & Shreeve, T. G. Why small is beautiful: Wing colour is free from thermoregulatory constraint in the small lycaenid butterfly, Polyommatus icarus. PLoS One 10, e0122663 (2015).
    Google Scholar 
    48.Biró, L. P. et al., Role of photonic-crystal-type structures in the thermal regulation of a lycaenid butterfly sister species pair. Phys. Rev. E Stat. Physics, Plasmas, Fluids, Relat. Interdiscip. Top. 67, 7 (2003).49.Sala-Casanovas, M., Krishna, A., Yu, Z. & Lee, J. Bio-inspired stretchable selective emitters based on corrugated nickel for personal thermal management. Nanoscale Microscale Thermophys. Eng. 23, 173–187 (2019).CAS 
    ADS 

    Google Scholar 
    50.Phan, L. et al. Reconfigurable infrared camouflage coatings from a cephalopod protein. Adv. Mater. 25, 5621–5625 (2013).CAS 
    PubMed 

    Google Scholar 
    51.Pris, A. D. et al. Towards high-speed imaging of infrared photons with bio-inspired nanoarchitectures. Nat. Photonics 6, 564–564 (2012).CAS 
    ADS 

    Google Scholar 
    52.Krishna, A. et al. Ultraviolet to mid-infrared emissivity control by mechanically reconfigurable graphene. Nano Lett. 19, 5086–5092 (2019).CAS 
    PubMed 
    ADS 

    Google Scholar 
    53.Moharam, M. G. & Gaylord, T. K. Rigorous coupled-wave analysis of planar-grating diffraction. J. Opt. Soc. Am. 71, 811 (1981).ADS 

    Google Scholar 
    54.Moharam, M. G. Coupled-wave analysis of two-dimensional dielectric gratings in Holographic Optics: Design and Applications, (1988), p. 8.55.Peng, S. & Morris, G. M. Efficient implementation of rigorous coupled-wave analysis for surface-relief gratings. J. Opt. Soc. Am. A 12, 1087 (1995).ADS 

    Google Scholar 
    56.Moharam, M. G., Gaylord, T. K., Grann, E. B. & Pommet, D. A. Formulation for stable and efficient implementation of the rigorous coupled-wave analysis of binary gratings. J. Opt. Soc. Am. A 12, 1068 (1995).ADS 

    Google Scholar 
    57.Taflove, A., Hagness, S. C. Computational Electrodynamics: The Finite-Difference Time-Domain Method (Artech House, 2005).58.Fang, J. et al. Enhanced photocatalytic hydrogen production on three-dimensional gold butterfly wing scales/CdS nanoparticles. Appl. Surf. Sci. 427, 807–812 (2018).CAS 
    ADS 

    Google Scholar 
    59.Wilts, B. D., Leertouwer, H. L. & Stavenga, D. G. Imaging scatterometry and microspectrophotometry of lycaenid butterfly wing scales with perforated multilayers. J. R. Soc. Interface 6, S185–S192 (2009).PubMed 

    Google Scholar 
    60.Aideo, S. N., Mohanta, D. Investigation of manifestation of optical properties of butterfly wings with nanoscale zinc oxide incorporation. J. Phys: Confer. Ser. 765, 012019 (2016).61.Guan, Y. et al. Ordering of hollow Ag-Au nanospheres with butterfly wings as a biotemplate. Sci. Rep. 8, 1–7 (2018).
    Google Scholar 
    62.Simonsen, T. J. et al. Phylogenetics and divergence times of Papilioninae (Lepidoptera) with special reference to the enigmatic genera Teinopalpus and Meandrusa. Cladistics 27, 113–137 (2011).PubMed 

    Google Scholar 
    63.Wilts, B. D., Pirih, P., Arikawa, K. & Stavenga, D. G. Shiny wing scales cause spec(tac)ular camouflage of the angled sunbeam butterfly, Curetis acuta. Biol. J. Linn. Soc. 109, 279–289 (2013).
    Google Scholar 
    64.Wu, L., Han, Z., Qiu, Z., Guan, H. & Ren, L. The microstructures of butterfly wing scales in northeast of China. J. Bionic Eng. 4, 47–52 (2007).CAS 

    Google Scholar 
    65.Azofeifa, D. E., Arguedas, H. J. & Vargas, W. E. Optical properties of chitin and chitosan biopolymers with application to structural color analysis. Opt. Mater. (Amst) 35, 175–183 (2012).CAS 
    ADS 

    Google Scholar 
    66.Vargas, W. E., Azofeifa, D. E. & Arguedas, H. J. Índices de refracción de la quitina, el quitosano y el ácido úrico con aplicación en análisis de color estructural. Opt. Pura y Apl. 46, 55–72 (2013).
    Google Scholar 
    67.Herman, A., Vandenbem, C., Deparis, O., Simonis, P. & Vigneron, J. P. Nanoarchitecture in the black wings of Troides magellanus : A natural case of absorption enhancement in photonic materials. Nanophotonic Mater. VIII 8094, 80940H (2011).
    Google Scholar 
    68.Yoshioka, S. & Kinoshita, S. Wavelength-selective and anisotropic light-diffusing scale on the wing of the Morpho butterfly. Proc. Biol. Sci. 271, 581–587 (2004).PubMed 
    PubMed Central 

    Google Scholar 
    69.Catalanotti, S. et al. The radiative cooling of selective surfaces. Sol. Energy 17, 83–89 (1975).ADS 

    Google Scholar 
    70.Long Kou, J., Jurado, Z., Chen, Z., Fan, S. & Minnich, A. J. Daytime radiative cooling using near-black infrared emitters. ACS Photonics 4, 626–630 (2017).
    Google Scholar 
    71.Wasserthal, L. T. The role of butterfly wings in regulation of body temperature. J. Insect Physiol. 21, 1921–1930 (1975).
    Google Scholar 
    72.Peel, M. C., Finlayson, B. L. & McMahon, T. A. Updated world map of the Köppen-Geiger climate classification. Hydrol. Earth Syst. Sci. 11, 1633–1644 (2007).ADS 

    Google Scholar 
    73.New, M., Lister, D., Hulme, M. & Makin, I. A high-resolution data set of surface climate over global land areas. Clim. Res. 21, 1–25 (2002).
    Google Scholar 
    74.Weather Spark Weather Data. https://weatherspark.com (July 10, 2019).75.Weather Underground Historical Weather. https://www.wunderground.com/history/ (August 2, 2018).76.Liu, F. et al. Replication of homologous optical and hydrophobic features by templating wings of butterflies Morpho menelaus. Opt. Commun. 284, 2376–2381 (2011).CAS 
    ADS 

    Google Scholar 
    77.Chen, T., Cong, Q., Qi, Y., Jin, J. & Choy, K. L. Hydrophobic durability characteristics of butterfly wing surface after freezing cycles towards the design of nature inspired anti-icing surfaces. PLoS ONE 13, e0188775 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    78.Fang, Y., Sun, G., Wang, T. Q., Cong, Q. & Ren, L. Q. Hydrophobicity mechanism of non-smooth pattern on surface of butterfly wing. Chin. Sci. Bull. 52, 711–716 (2007).
    Google Scholar 
    79.Garland, T., Harvey, P. H. & Ives, A. R. Procedures for the analysis of comparative data using phylogenetically independent contrasts. Syst. Biol. 41, 18–32 (1992).
    Google Scholar 
    80.Felsenstein, J. Phylogenies and the comparative method. Am. Nat. 125, 1–15 (1985).
    Google Scholar 
    81.Felsenstein, J. Phylogenies and quantitative characters. Annu. Rev. Ecol. Syst. 19, 445–471 (1988).
    Google Scholar 
    82.Espeland, M. et al. A comprehensive and dated phylogenomic analysis of butterflies. Curr. Biol. 28, 770–778.e5 (2018).CAS 
    PubMed 

    Google Scholar 
    83.Maddison, W. P. & Maddison, D. R. Mesquite: a modular system for evolutionary analysis. 2010. Version 2, 73 (2008).
    Google Scholar 
    84.Cai, W., Shalaev, V. M. Optical Metamaterials, 10th Ed. (Springer, 2010).85.Zheludev, N. I. & Kivshar, Y. S. From metamaterials to metadevices. Nat. Mater. 11, 917–924 (2012).CAS 
    PubMed 
    ADS 

    Google Scholar 
    86.Chen, Z., Zhu, L., Raman, A. & Fan, S. Radiative cooling to deep sub-freezing temperatures through a 24-h day-night cycle. Nat. Commun. 7, 1–5 (2016).
    Google Scholar 
    87.Mandal, J. et al. Hierarchically porous polymer coatings for highly efficient passive daytime radiative cooling. Science 362, 315–319 (2018).CAS 
    PubMed 
    ADS 

    Google Scholar 
    88.Lenert, A. et al. A nanophotonic solar thermophotovoltaic device. Nat. Nanotechnol. 9, 126–130 (2014).CAS 
    PubMed 
    ADS 

    Google Scholar 
    89.Quintiere, J. Radiative characteristics of fire fighters’ coat fabrics. Fire Technol. 10, 153–161 (1974).CAS 

    Google Scholar 
    90.Energy Sector Management Assistance Program (ESMAP). Global Solar Atlas 2.1: Technical Report. https://globalsolaratlas.info (World Bank, December 2019).91.Yoshioka, S. & Kinoshita, S. Direct determination of the refractive index of natural multilayer systems. Phys. Rev. E 83, 051917 (2011).ADS 

    Google Scholar 
    92.Leertouwer, H. L., Wilts, B. D. & Stavenga, D. G. Refractive index and dispersion of butterfly chitin and bird keratin measured by polarizing interference microscopy. Opt. Express 19, 24061–24066 (2011).CAS 
    PubMed 
    ADS 

    Google Scholar  More

  • in

    Longitudinal monitoring in Cambodia suggests higher circulation of alpha and betacoronaviruses in juvenile and immature bats of three species

    1.Wang, C., Horby, P. W., Hayden, F. G. & Gao, G. F. A novel coronavirus outbreak of global health concern. Lancet 395, 470–473 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    2.Andersen, K. G., Rambaut, A., Lipkin, W. I., Holmes, E. C. & Garry, R. F. The proximal origin of SARS-CoV-2. Nat. Med. 26, 450–452 (2020).CAS 

    Google Scholar 
    3.Zhou, P. et al. A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature 579, 270–273 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    4.Woo, P. C. Y. et al. Discovery of seven novel mammalian and avian coronaviruses in the genus deltacoronavirus supports bat coronaviruses as the gene source of alphacoronavirus and betacoronavirus and avian coronaviruses as the gene source of gammacoronavirus and deltacoronavirus. J. Virol. 86, 3995–4008 (2012).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    5.Wong, A. C. P., Li, X., Lau, S. K. P. & Woo, P. C. Y. Global epidemiology of bat coronaviruses. Viruses 11, 174 (2019).CAS 
    PubMed Central 

    Google Scholar 
    6.Lacroix, A. et al. Genetic diversity of coronaviruses in bats in Lao PDR and Cambodia. Infect. Genet. Evol. 48, 10–18 (2017).CAS 
    PubMed 

    Google Scholar 
    7.Tsuda, S. et al. Genomic and serological detection of bat coronavirus from bats in the Philippines. Arch. Virol. 157, 2349–2355 (2012).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    8.Han, Y. et al. Identification of diverse bat alphacoronaviruses and betacoronaviruses in China provides new insights into the evolution and origin of coronavirus-related diseases. Front. Microbiol. 10, 20 (2019).
    Google Scholar 
    9.Xu, L. et al. Detection and characterization of diverse alpha- and betacoronaviruses from bats in China. Virol. Sin. 31, 69–77 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    10.Chen, Y.-N. et al. Detection of the severe acute respiratory syndrome-related coronavirus and alphacoronavirus in the bat population of Taiwan. Zoonoses Public Health 63, 608–615 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    11.Wacharapluesadee, S. et al. Group C betacoronavirus in bat guano fertilizer, Thailand. Emerg. Infect. Dis. 19, 1349–1351 (2013).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    12.Latinne, A. et al. Origin and cross-species transmission of bat coronaviruses in China. Nat. Commun. 11, 4235 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    13.Drexler, J. F. et al. Amplification of emerging viruses in a bat colony. Emerg. Infect. Dis. 17, 449–456 (2011).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    14.Amman, B. R. et al. Seasonal pulses of marburg virus circulation in Juvenile Rousettus aegyptiacus bats coincide with periods of increased risk of human infection. PLoS Pathog. 8, 25 (2012).
    Google Scholar 
    15.Peel, A. J. et al. The effect of seasonal birth pulses on pathogen persistence in wild mammal populations. Proc. R. Soc. Lond. B Biol. Sci. 281, 20132962 (2014).
    Google Scholar 
    16.Hayman, D. T. S. Biannual birth pulses allow filoviruses to persist in bat populations. Proc. R. Soc. Lond. B Biol. Sci. 282, 20142591 (2015).
    Google Scholar 
    17.Gloza-Rausch, F. et al. Detection and prevalence patterns of Group I Coronaviruses in Bats, Northern Germany. Emerg. Infect. Dis. 14, 626–631 (2008).PubMed 
    PubMed Central 

    Google Scholar 
    18.Annan, A. et al. Human betacoronavirus 2c EMC/2012-related viruses in bats, Ghana and Europe. Emerg. Infect. Dis. 19, 456–459 (2013).PubMed 
    PubMed Central 

    Google Scholar 
    19.Anthony, S. J. et al. Global patterns in coronavirus diversity. Virus Evol. 3, 25 (2017).
    Google Scholar 
    20.Montecino-Latorre, D. et al. Reproduction of East-African bats may guide risk mitigation for coronavirus spillover. One Health Outlook 2, 2 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    21.Maganga, G. D. et al. Genetic diversity and ecology of coronaviruses hosted by cave-dwelling bats in Gabon. Sci. Rep. 10, 7314 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    22.Hu, B. et al. Discovery of a rich gene pool of bat SARS-related coronaviruses provides new insights into the origin of SARS coronavirus. PLoS Pathog. 13, e1006698 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    23.Wacharapluesadee, S. et al. A longitudinal study of the prevalence of Nipah virus in Pteropus lylei bats in Thailand: Evidence for seasonal preference in disease transmission. Vector-Borne Zoonot. Dis. 10, 183–190 (2010).
    Google Scholar 
    24.Cappelle, J. et al. Nipah virus circulation at human-bat interfaces, Cambodia. Bull. World Health Organ. 98, 539–547 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    25.Thavry, H., Cappelle, J., Bumrungsri, S., Thona, L. & Furey, N. M. The diet of the cave nectar bat (#Eonycteris spelaea# Dobson) suggests it pollinates economically and ecologically significant plants in Southern Cambodia. Zool. Stud. 56, 25 (2017).
    Google Scholar 
    26.Lim, T., Cappelle, J., Hoem, T. & Furey, N. Insectivorous bat reproduction and human cave visitation in Cambodia: A perfect conservation storm?. PLoS One 13, e0196554 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    27.Sikes, R. S. 2016 Guidelines of the American Society of Mammalogists for the use of wild mammals in research and education. J. Mammal. 97, 663–688 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    28.Anthony, E. L. P. Age determination in bats. In Ecological and Behavioral Methods for the Study of Bats 47–58 (Smithsonian Press, 1988).
    Google Scholar 
    29.Racey, P. A. Reproductive assessment. In Behavioural and Ecological Methods for the Study of Bats 249–264 (Johns Hopkins University Press, 2009).
    Google Scholar 
    30.Watanabe, S. et al. Bat coronaviruses and experimental infection of bats, the Philippines. Emerg. Infect. Dis. 16, 1217–1223 (2010).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    31.Quan, P.-L. et al. Identification of a severe acute respiratory syndrome coronavirus-like virus in a leaf-nosed bat in Nigeria. MBio 1, 25 (2010).
    Google Scholar 
    32.Tamura, K., Stecher, G., Peterson, D., Filipski, A. & Kumar, S. MEGA6: Molecular evolutionary genetics analysis version 6.0. Mol. Biol. Evol. 30, 2725–2729 (2013).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    33.Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).
    Google Scholar 
    34.Burgin, C. Family Rhinolophidae, horseshoe bats. In Handbook of the Mammals of the World Vol. 9 260–332 (Lynx Edicions, 2019).
    Google Scholar 
    35.Martín-Martín, A., Orduna-Malea, E., Thelwall, M. & Delgado López-Cózar, E. Google Scholar, Web of Science, and Scopus: A systematic comparison of citations in 252 subject categories. J. Informetr. 12, 1160–1177 (2018).
    Google Scholar 
    36.Racey, P. A. & Entwistle, E. Life history and reproductive strategies of bats. Reprod. Biol. Bats 20, 363–468 (2000).
    Google Scholar 
    37.Furey, N. M., Mackie, I. J. & Racey, P. A. Reproductive phenology of bat assemblages in Vietnamese karst and its conservation implications. Acta Chiropterol. 13, 341–354 (2011).
    Google Scholar 
    38.Sterling, E. J., Hurley, M. M. & Le, D. M. Vietnam: A Natural History (Yale University Press, 2006).
    Google Scholar 
    39.Van, N. K., Hzien, N. T., Loc, P. K. & Hiep, N. T. Bioclimatic Diagrams of Vietnam (Vietnam National University Publishing House, 2000).
    Google Scholar 
    40.Plowright, R. K. et al. Transmission or within-host dynamics driving pulses of zoonotic viruses in reservoir-host populations. PLoS Negl. Trop. Dis. 10, 0004796 (2016).
    Google Scholar 
    41.Peel, A. J. et al. Support for viral persistence in bats from age-specific serology and models of maternal immunity. Sci. Rep. 8, 3859 (2018).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    42.Wanger, T. C., Darras, K., Bumrungsri, S., Tscharntke, T. & Klein, A.-M. Bat pest control contributes to food security in Thailand. Biol. Conserv. 171, 220–223 (2014).
    Google Scholar 
    43.Furey, N. M., Racey, P. A., Ith, S., Touch, V. & Cappelle, J. Reproductive ecology of wrinkle-lipped free-tailed bats Chaerephon plicatus (Buchannan, 1800) in relation to Guano production in Cambodia. Diversity 10, 91 (2018).
    Google Scholar 
    44.Ades, G. W. J. & Dudgeon, D. Insect seasonality in Hong Kong: A monsoonal environment in the northern tropics (1999).45.Kai, K. H. & Corlett, R. T. Seasonality of forest invertebrates in Hong Kong, South China. J. Trop. Ecol. 18, 637–644 (2002).
    Google Scholar 
    46.Kingston, T., Lim, B. L. & Zubaid, A. Bats of Krau Wildlife Reserve (Universiti Kebangsaan Malaysia, 2006).
    Google Scholar 
    47.Nurul-Ain, E., Rosli, H. & Kingston, T. Resource availability and roosting ecology shape reproductive phenology of rain forest insectivorous bats. Biotropica 49, 382–394 (2017).
    Google Scholar 
    48.Fleming, T. H., Hooper, E. T. & Wilson, D. E. Three Central American Bat Communities: Structure, reproductive cycles, and movement patterns. Ecology 53, 555–569 (1972).
    Google Scholar 
    49.Bernard, R. T. & Cumming, G. S. African bats: Evolution of reproductive patterns and delays. Q. Rev. Biol. 72, 253–274 (1997).CAS 
    PubMed 

    Google Scholar 
    50.Nguyen, S. T. et al. Bats (Chiroptera) of Bidoup Nui Ba National Park, Dalat Plateau, Vietnam. Mammal Stud. 46, 53–68 (2021).
    Google Scholar 
    51.Plowright, R. K. et al. Urban habituation, ecological connectivity and epidemic dampening: The emergence of Hendra virus from flying foxes (Pteropus spp.). Proc. R. Soc. B Biol. Sci. 278, 3703–3712 (2011).
    Google Scholar 
    52.Peel, A. J. et al. Synchronous shedding of multiple bat paramyxoviruses coincides with peak periods of Hendra virus spillover. Emerg. Microbes Infect. 8, 1314–1323 (2019).PubMed 
    PubMed Central 

    Google Scholar  More

  • in

    Conserving evolutionarily distinct species is critical to safeguard human well-being

    Dataset of beneficial plantsI collated a species-level dataset of plant benefits (presence/absence data) starting from the information gathered by Kleunen et al.32. These authors extracted data from the WEP database (National Plant Germplasm System GRIN-GLOBAL; https://npgsweb.ars-grin.gov/gringlobal/taxon/taxonomysearcheco.aspx, Accessed 7 Jan 2016), which is based on the book by Wiersema and León20. Their dataset included 84 categories and subcategories of plant benefits pertaining human and animal nutrition, materials, fuels, medicine, useful poisons, social and environmental benefits. Subcategories of benefits, which often included very few records, were merged here into 25 standard and major categories following the guidelines in the Economic Botany Data Collection Standard33 as in Molina-Venegas et al.13, namely ornamental plants, soil improvers, hedging/shelter, human food, human-food additives, vertebrate food, invertebrate food, fuelwood, charcoal, other biofuels, timber, cane/stems, fibres, tannins/dyestuffs, beads, gums/resins, lipids, waxes, essential oils/scents, latex/rubber, medicines, invertebrate poison, vertebrate poison, smoking materials/drugs and symbolic/inspirational plants (Fig. 1). A few records (n = 93) that could not be assigned to any of the above categories were disregarded, and so was the category ‘gene source’ because unlike other benefits, any species is intrinsically a potential gene donor and hence there is not a clear link between the benefit and species features. Note that this is not to say that preserving genetic diversity, which indeed is the underlying message of this research, is a meaningless goal. Infraspecific taxa were collapsed at the species level, and the very few fern taxa in the original database32 were excluded. In total, I gathered 15,834 plant-benefit records sorted in a matrix of 25 types of benefits and 9521 species of seed plants. Most species (83.74%) provided only one or two benefits representing 62.83% of the records in the dataset, and the maximum number of benefits per species was 10 (only three species). Although the WEP database is the largest species-level database on plant benefits32, it does not claim to be comprehensive20. Yet, the size of the dataset I gathered here represented 76.19% of the total seed-plant genus-level records collated for the same types of benefits in a more comprehensive survey by Molina-Venegas et al.13 that based on Mabberley’s Plant-book34. Moreover, the total number of records per category (at the genus-level) strongly correlated between the datasets (Pearson r = 0.94, p  More

  • in

    Plasticity in organic composition maintains biomechanical performance in shells of juvenile scallops exposed to altered temperature and pH conditions

    1.Feely, R. A., Sabine, C. L., Hernandez-Ayon, J. M., Ianson, D. & Hales, B. Evidence for upwelling of corrosive “acidified” water onto the continental shelf. Science 320, 1490–1492 (2008).ADS 
    CAS 
    PubMed 

    Google Scholar 
    2.Hofmann, G. E. et al. High-frequency dynamics of ocean ph: A multi-ecosystem comparison. PLoS ONE 6(12), e28983 (2011).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    3.Kroeker, K. J. et al. Interacting environmental mosaics drive geographic variation in mussel performance and predation vulnerability. Ecol. Lett. 19, 771–779 (2016).PubMed 

    Google Scholar 
    4.Gutiérrez, D. et al. Coastal cooling and increased productivity in the main upwelling zone off Peru since the mid-twentieth century. Geophys. Res. Lett. 38, L07603. https://doi.org/10.1029/2010GL046324 (2011).ADS 
    Article 

    Google Scholar 
    5.Aiken, C. M., Navarrete, S. A. & Pelegrí, J. L. Potential changes in larval dispersal and alongshore connectivity on the central Chilean coast due to an altered wind climate. J. Geophys. Res. 116, G04026. https://doi.org/10.1029/2011JG001731 (2011).ADS 
    Article 

    Google Scholar 
    6.Lagos, N. A., Castilla, J. C. & Broitman, B. Spatial Environmental correlates of intertidal recruitment: A test using barnacles in northern Chile. Ecol. Monogr. 78, 245–261 (2008).
    Google Scholar 
    7.Vargas, C. A. et al. Species-specific responses to ocean acidification should account for local adaptation and adaptive plasticity. Nat. Ecol. Evol. 1, 84. https://doi.org/10.1038/s41559-017-0084 (2017).Article 
    PubMed 

    Google Scholar 
    8.Broitman, B. R. et al. Phenotypic plasticity is not a cline: Thermal physiology of an intertidal barnacle over 20° of latitude. J. Anim. Ecol. 00, 1–12. https://doi.org/10.1111/1365-2656.13514 (2021).Article 

    Google Scholar 
    9.Ramajo, L. et al. Physiological responses of juvenile Chilean scallops (Argopecten purpuratus) to isolated and combined environmental drivers of coastal upwelling. ICES J. Mar. Sci. 76, 1836e1849 (2019).
    Google Scholar 
    10.Saavedra, L. M., Saldías, G., Broitman, B. & Vargas, C. Carbonate chemistry dynamics in shellfish farming areas along the Chilean coast: Natural ranges and biological implications. ICES J. Mar. Sci. 78, 323–339 (2021).
    Google Scholar 
    11.Lardies, M. A. et al. Physiological and histopathological impacts of increased carbon dioxide and temperature on the scallops Argopecten purpuratus cultured under upwelling influences in northern Chile. Aquaculture 479, 455–466 (2017).
    Google Scholar 
    12.Ramajo, L. et al. Upwelling intensity modulates the fitness and physiological performance of coastal species: Implications for the aquaculture of the scallop Argopecten purpuratus in the Humboldt Current System. Sci. Total Environ. 745, 140949 (2020).ADS 
    CAS 
    PubMed 

    Google Scholar 
    13.Bakun, A. Global climate change and intensification of coastal ocean upwelling. Science 247, 198–201 (1990).ADS 
    CAS 
    PubMed 

    Google Scholar 
    14.Wang, D. et al. Intensification and spatial homogenization of coastal upwelling under climate change. Nature 518, 390–394 (2015).ADS 
    CAS 
    PubMed 

    Google Scholar 
    15.Kim, T. W., Barry, J. P. & Micheli, F. The effects of intermittent exposure to low-pH and low-oxygen conditions on survival and growth of juvenile red abalone. Biogeosciences 10, 7255–7262 (2013).ADS 

    Google Scholar 
    16.Ramajo, L. et al. Plasticity and trade-offs in physiological traits of intertidal mussels subjected to freshwater-induced environmental variation. Mar. Ecol. Prog. Ser. 553, 93–109 (2016).ADS 

    Google Scholar 
    17.Leung, J. Y., Connell, S. D., Nagelkerken, I. & Russell, B. D. Impacts of near-future ocean acidification and warming on the shell mechanical and geochemical properties of gastropods from intertidal to subtidal zones. Environ. Sci. Technol. 51, 12097–12103 (2017).ADS 
    CAS 
    PubMed 

    Google Scholar 
    18.Findlay, H. et al. Calcification, a physiological process to be considered in the context of the whole organism. Biogeosciences Discuss. 6, 2267–2284 (2009).ADS 

    Google Scholar 
    19.Waldbusser, G. et al. Saturation-state sensitivity of marine bivalves larvae to ocean acidification. Nat. Clim. Change 5, 273–280 (2015).ADS 
    CAS 

    Google Scholar 
    20.Tunnicliffe, V. et al. Survival of mussels in extremely acidic waters on a submarine volcano. Nat. Geosci. 2, 344–348 (2009).ADS 
    CAS 

    Google Scholar 
    21.Ries, J. B., Cohen, A. L. & McCorkle, D. C. Marine calcifiers exhibit mixed responses to CO2-induced ocean acidification. Geology 37, 1131–1134 (2009).ADS 
    CAS 

    Google Scholar 
    22.Leung, J. Y., Russell, B. D. & Connell, S. D. Mineralogical plasticity acts as a compensatory mechanism to the impacts of ocean acidification. Environ. Sci. Technol. 51, 2652–2659 (2017).ADS 
    CAS 
    PubMed 

    Google Scholar 
    23.Duarte, C. et al. The energetic physiology of juvenile mussels, Mytilus chilensis (Hupe): The prevalent role of salinity under current and predicted pCO2 scenarios. Environ. Pollut. 242, 156–163 (2018).CAS 
    PubMed 

    Google Scholar 
    24.Rodolfo-Metalpa, R. et al. Coral and mollusc resistance to ocean acidification adversely affected by warming. Nat. Clim. Change. 1, 308–312 (2011).ADS 
    CAS 

    Google Scholar 
    25.Waldbusser, G. et al. Slow shell building, a possible trait for resistance to the effects of acute ocean acidification. Limnol. Oceanogr. 61, 1969–1983 (2016).ADS 

    Google Scholar 
    26.Fitzer, S. C. et al. Ocean acidification and temperature increase impact mussel shell shape and thickness: Problematic for protection?. Ecol. Evol. 5, 4875–4884 (2015).PubMed 
    PubMed Central 

    Google Scholar 
    27.Fitzer, S. C., Phoenix, V. R., Cusack, M. & Kamenos, N. A. Ocean acidification impacts mussel control on biomineralization. Sci. Rep. 28, 6218 (2014).
    Google Scholar 
    28.Fitzer, S. C., Cusack, M., Phoenix, V. R. & Kamenos, N. A. Ocean acidification reduces the crystallographic control in juvenile mussel shells. J. Struct. Biol. 188, 39–45 (2014).CAS 
    PubMed 

    Google Scholar 
    29.Fitzer, S. C. et al. Biomineral shell formation under ocean acidification: A shift from order to chaos. Sci. Rep. 6, 21076 (2016).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    30.Lagos, N. A. et al. Effects of temperature and ocean acidification on shell characteristics of Argopecten purpuratus: Implications for scallop aquaculture in an upwelling-influenced area. Aquac. Environ. Interact. 8, 357–370 (2016).
    Google Scholar 
    31.Ramajo, L. et al. Biomineralization changes with food supply confer juvenile scallops (Argopecten purpuratus) resistance to ocean acidification. Glob. Chang. Biol. 22, 2025–2203 (2016).ADS 
    PubMed 

    Google Scholar 
    32.Osores, S. J. et al. Plasticity and inter-population variability in physiological and life-history traits of the mussel Mytilus chilensis: A reciprocal transplant experiment. J. Exp. Mar. Biol. Ecol. 490, 1–12 (2017).
    Google Scholar 
    33.Telesca, L. et al. Plasticity and environmental heterogeneity predict geographic resilience patterns of foundation species to future change. Glob. Chang. Biol. https://doi.org/10.1111/gcb.14758 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    34.Grenier, C. et al. The combined effects of salinity and pH on shell biomineralization of the edible mussel Mytilus chilensis. Environ. Pollut. 263, 114555 (2020).CAS 
    PubMed 

    Google Scholar 
    35.Kroeker, K. J. et al. Impacts of ocean acidification on marine organisms: Quantifying sensitivities and interaction with warming. Glob. Change Biol. 19, 1884–1896 (2013).ADS 

    Google Scholar 
    36.Mackenzie, C. L. et al. Ocean warming, more than acidification, reduces shell strength in a commercial shellfish species during food limitation. PLoS ONE 9(1), e86764 (2014).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    37.Rykaczewski, R. R. et al. Poleward displacement of coastal upwelling-favorable winds in the ocean’s eastern boundary currents through the 21st century. Geophys. Res. Lett. 42, 6424–6431 (2015).ADS 

    Google Scholar 
    38.Rodríguez-Navarro, A. B. Rapid quantification of avian eggshell microstructure and crystallographic-texture using two-dimensional X-ray diffraction. Br. Poult. Sci. 48, 133–144 (2007).PubMed 

    Google Scholar 
    39.Rodríguez-Navarro, A. B. XRD2DScan: New software for polycrystalline materials characterization using two-dimensional X-ray diffraction. J. Appl. Cryst. 39, 905–909 (2006).
    Google Scholar 
    40.Li, S. et al. Interactive effects of seawater acidification and elevated temperature on biomineralization and amino acid metabolism in the mussel Mytilus edulis. J. Exp. Biol. 218, 3623–3631 (2015).PubMed 

    Google Scholar 
    41.Li, S. et al. Interactive effects of seawater acidification and elevated temperature on the transcriptome and biomineralization in the pearl oyster Pinctada fucata. Environ. Sci. Technol. 50, 1157–1165 (2016).ADS 
    CAS 
    PubMed 

    Google Scholar 
    42.Gestoso, I., Arenas, F. & Olabarria, C. Ecological interactions modulate responses of two intertidal mussel species to changes in temperature and pH. J. Exp. Mar. Biol. 474, 116–125 (2016).
    Google Scholar 
    43.Babarro, J. M., Abad, M. J., Gestoso, I., Silva, E. & Olabarria, C. Susceptibility of two co-existing mytilid species to simulated predation under projected climate change conditions. Hydrobiologia 807, 247–261 (2018).
    Google Scholar 
    44.Barthelat, F., Rim, J. E. & Espinosa, H. D. A review on the structure and mechanical properties of mollusk shells: Perspectives on synthetic biomimetic materials. In Applied Scanning Probe Methods XIII (eds Bhushan, B. & Fuchs, H.) 17–44 (Springer, 2009).
    Google Scholar 
    45.Leung, J. Y. et al. Calcifiers can adjust shell building at the nanoscale to resist ocean acidification. Small 16, 2003186 (2020).CAS 

    Google Scholar 
    46.Chatzinikolaou, E., Grigoriou, P., Keklikoglou, K., Faulwetter, S. & Papageorgiou, N. The combined effects of reduced pH and elevated temperature on the shell density of two gastropod species measured using micro-CT imaging. ICES J. Mar. Sci. 74, 1135–1149 (2017).
    Google Scholar 
    47.Nienhuis, S., Palmer, R. & Harley, C. Elevated CO2 affects shell dissolution rate but not calcification rate in a marine snail. Proc. R. Soc. Lond. B Biol. Sci. 277, 2553–2558 (2010).CAS 

    Google Scholar 
    48.Bourdeau, P. E. Prioritized phenotypic responses to combined predators in a marine snail. Ecology 90, 1659–1669 (2009).PubMed 

    Google Scholar 
    49.Weiner, S. & Addadi, L. Crystallization pathways in biomineralization. Annu. Rev. Mater. Sci. 41, 21–40 (2011).ADS 
    CAS 

    Google Scholar 
    50.Nudelman, F. Nacre biomineralisation: A review on the mechanisms of crystal nucleation (In Seminars in cell & developmental biology), 2–10 (Academic Press, 2015).51.Harper, E. M., Checa, A. G. & Rodríguez-Navarro, A. B. Organization and mode of secretion of the granular prismatic microstructure of Entodesma navicular (Bivalvia: Mollusca). Acta Zool. 90, 132e141 (2009).
    Google Scholar 
    52.Pennington, B. J. & Currey, J. D. A mathematical model for the mechanical properties of scallop shells. J. Zool. 202, 239–263 (1984).
    Google Scholar 
    53.Yevenes, M. A., Lagos, N. A., Farías, L. & Vargas, C. A. Greenhouse gases, nutrients and the carbonate system in the Reloncaví Fjord (Northern Chilean Patagonia): Implications on aquaculture of the mussel, Mytilus chilensis, during an episodic volcanic eruption. Sci. Total Environ. 669, 49–61 (2019).ADS 
    CAS 
    PubMed 

    Google Scholar 
    54.Dickinson, G. H. et al. Interactive effects of salinity and elevated CO2 levels on juvenile eastern oysters, Crassostrea virginica. J. Exp. Biol. 215, 29–43 (2012).CAS 
    PubMed 

    Google Scholar 
    55.Gaylord, B. et al. Functional impacts of ocean acidification in an ecologically critical foundation species. J. Exp. Biol. 214, 2586–2594 (2011).CAS 
    PubMed 

    Google Scholar 
    56.O’Toole-Howes, M. et al. Deconvolution of the elastic properties of bivalve shell nanocomposites from direct measurement and finite element analysis. J. Mater. Res. 34, 2869–2880 (2019).ADS 

    Google Scholar 
    57.Auzoux-Bordenave, S. et al. Ocean acidification impacts growth and shell mineralization in juvenile abalone (Haliotis tuberculata). Mar. Biol. 167, 11 (2020).CAS 

    Google Scholar 
    58.Torres, R. et al. Evaluation of a semiautomatic system for long-term seawater carbonate chemistry manipulation. Rev. Chil. Hist. Nat. 86, 443–451 (2013).
    Google Scholar 
    59.IPCC. Climate Change 2021. The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (Eds. Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou). Cambridge University Press. In Press. (2021).60.DOE. Handbook of methods for the analysis of the various parameters of the carbon dioxide system in seawater; version 2 (eds. Dickson, A.G. & Goyet, C.), (ORNL/CDIAC, 74, 1994).61.Meinshausen, M. et al. The RPC greenhouse gas concentrations and their extensions from 1765 to 2300. Clim. Change. 109, 213–241 (2011).ADS 
    CAS 

    Google Scholar 
    62.Rahn, D. A., Rosenblüth, B. & Rutllant, J. A. Detecting subtle seasonal transitions of upwelling in North-Central Chile. J. Phys. Oceanogr. 45, 854–867 (2015).ADS 

    Google Scholar 
    63.Meng, Y., Guo, Z., Yao, H., Yeung, K. W. & Thiyagarajan, V. Calcium carbonate unit realignment under acidification: A potential compensatory mechanism in an edible estuarine oyster. Mar. Pollut. Bull. 139, 141–149 (2019).CAS 
    PubMed 

    Google Scholar 
    64.Rasband, W. S. ImageJ U.S. National Institute of Health, Maryland, USA (1997–2020). More

  • in

    Direct pesticide exposure of insects in nature conservation areas in Germany

    Pesticide residuesInsects were collected in Malaise traps during two-week intervals, where pesticide residues from insect bodies were dissolved in the ethanol that was used to preserve the collected samples. Additionally, particles of plants, pollen, nectar or honeydew adhering to the insect bodies can be carriers of chemical pollution. Detected pesticide residues can therefore come from the insects and potentially attached particles. Under natural conditions of sunlight and warm temperatures, chemical stability of pesticide residues in the ethanol solution may have been affected by hydrolysis, for example, which could have caused the degradation of residues during the two-week collection intervals. Only flying insects that are alive can get into the Malaise traps, and therefore pesticide residues in the collected samples are assumed to represent sublethal levels to all trapped species. Additionally, insect collection was performed over an entire season and did not consider explicit spraying events. Therefore, the sampling we performed did not necessarily record maximum exposure levels that could represent lethal levels for individual species and substances. Hence, the quantification of pesticide amounts cannot be used for risk calculations. Instead we evaluate the presence of residues of CUPs on insects. Since detection is possible at low concentrations (see SOM Table A2) we obtained information on trace concentrations of the pesticide residues that insects were exposed to. It is safe to assume that the pesticide loads of insects were especially high following spraying events, and for individuals that were affected and consequently unable to fly. These insects were then not sampled in the Malaise traps.Of the 92 target common CUPs, 47 were detected in the insect samples from 21 nature conservation areas from two sampling dates in May and August 2020: 13 herbicides, 28 fungicides and 6 insecticides. Additionally, metabolites of fipronil, an insecticide registered for biocidal use in the EU, were recorded at three locations. At the 21 sites, insects in the conservation areas were exposed to 16.7 pesticides on average, ranging from 7 to 27 substances. More fungicides than herbicides were recorded and, on average, insects were exposed to less than two insecticides (Table 1). This may in part reflect the application in arable crops where more fungicides than herbicides are applied and insecticides are used less frequently. On the other hand, as insecticides affect insects directly due to their high acute toxicity, exposure to insecticides results in mortality or sublethal effects that impair mobility, leading to an underestimation of insecticide residues in our samples.Table 1 Number of CUP residues detected at 21 nature conservation areas across Germany and the resulting minimal, maximal and mean number of pesticide substances.Full size tableInsects at all 21 sites were exposed to residues of the herbicides metolachlor-S, prosulfocarb and terbuthylazine, and the fungicides azoxystrobin and fluopyram (Table 2). The presence of the six frequently detected herbicides can be explained by the high volume sold in 2019 (see SOM Table A3). They are among the 25 highest-ranking pesticides in terms of selling volume in Germany34. The same is true for the fungicide azoxystrobin. All other seven regularly detected fungicides were sold at lower volumes and their presence in the insect samples could be related to the high persistence of these fungicides, with soil half-lives reaching 500 d (bixafen), 484 d (boscalid) and 309 d (fluopyram). Only kresoxim-methyl, present in 10 sites, is not highly persistent in soil but has an affinity for the waxy plant cuticle, where it binds and accumulates35,36.Table 2 CUP residues frequently recorded at the 21 sites. Only substances that were recorded in ≥ 10 sites are listed.Full size tableThe neonicotinoid insecticide thiacloprid was recorded on insects in 16 of the 21 nature conservation areas. Thiacloprid was banned in the EU for use in field applications from August 2020 onwards, however, the end of use (grace period) was set to 3rd February, 202137. The high incidence of thiacloprid in our samples at many sites across Germany may therefore also reflect the last opportunity for farmers to use their remaining stocks. A ban could thus result in a greater impact to the ecosystem if parallel applications take place on a large scale. Hence, for potent pesticides which are banned from the market, it seems advisable to stop granting grace periods and instead destroy remaining stock rather than dispersing them into the environment despite knowledge of their high environmental risks.On average, in spring (May) residues of 9.6 and in summer (August) 9.3 CUPs were recorded in individual ethanol samples of the three trapping locations in the conservation areas. The minimum number of pesticide residues of 3 (May, site Mülhauser Halde) and 2 (August, Mittelberg) and the maximum of 16 (May, Bottendorfer Hügel) and 18 (August, Wisseler Dünen) were all from samples closer to the centre of the nature protection area, furthest away from adjacent agricultural fields.Seasonality of CUP exposureThe total number of CUP residues recorded on insects was similar for the two sampling intervals with 32 substances in May and 35 in August. However, a higher number of herbicide residues was recorded in May (13) compared to August (9), whereas for fungicides the reverse was the case [August (23), May (14)]. The number of detected insecticide residues was similar, with three and five substances recorded in May and August, respectively. This resulted in a different set of pesticide residue mixtures, driven by seasonality (Fig. 1). Mixtures in May, dominated by herbicides, were more similar to each other than the August mixtures, which contained more fungicides. The extreme positions of the NMDS analysis in August with Brauselay and Mittelberg are driven by the number of fungicide residues recorded. Brauselay is the only site where vineyards bordered the study area. Wine growing in Germany requires frequent fungicide applications.Figure 1CUP mixtures in May (green) and August (red) analysed with NMDS. The position of each location was determined by the composition of pesticide residues found in the ethanol samples. The closer data points are located in the ordination space, the more similar are their composition of pesticides. For abbreviations see Table 1.Full size imageOn the substance level, residues of the herbicides prosulfocarb, metolachlor-S, dimethenamid-P were recorded in more than half of the sites at both sampling intervals, whereas terbuthylazine was frequently present in May but not in August, and flufenacet was detected more frequently later in the year. Fungicide residues of fluopyram, azoxystrobin and boscalid were common in both sampling intervals, but pyraclostrobin, bixafen and dimoxystrobin were characteristic for May samples and fluazinam and kresoxim-methyl for the August samples (SOM Table A4). Although more residues of fungicides were recorded in August, this did not result in an increase in the number of fungicides that are found at many sites. Thirteen out of the 23 fungicides that were recorded in August were detected comparatively sporadic in samples from one to three sites. For insecticides, only thiacloprid was frequently noted, and the remaining substances acetamiprid, dimethoate, tebufenozide, and indoxacarb were found in May, whereas chlorantraniliprole and indoxacarb were recorded in August. The observed patterns reflect the agricultural practice of using herbicides in spring and early summer to establish crops such as cereals, oilseed rape and maize, and fungicides later in the year to control fungal diseases that increase with warmer temperatures.In addition to pesticide applications, seasonality has a direct effect on insect communities that change in composition from spring to autumn38,39,40. Because of shifts in insect community composition and pesticide application schemes, the mixture of pesticide residues present in insect samples changes throughout the year. Thus, it is likely that a finer time resolution than the selected two sampling intervals could reveal additional pesticide residues for the exposure of insects in conservation areas in the agricultural landscape.Influence of surrounding agricultural production areaOur data demonstrate that insects collected with Malaise traps in the nature conservation areas are exposed to pesticides applied in the surrounding agricultural landscape, where various crops are grown and are treated with a variety of pesticides. As the flight range of aerial insects fluctuates from less than one hundred meters to kilometres (for examples from the literature see SOM Table A5), it is not only the neighbouring arable field that may act as a source of contamination. A correlation analysis of the area of arable fields in the surrounding landscape (buffered from 500 to 3500 m) and number of pesticide residues recorded in the insect-trapping ethanol revealed a best fit for a radius of 2000 m around the center of the trapping positions in the conservation area (Fig. 2, all 21 sites, Pearson correlation coefficient = 0.48, p = 0.029). The site Brauselay differed from all nature conservation areas as vineyards were bordering the nature conservation area. Wine growing is a permanent crop characterised by high fungicide use on a comparable small area. When removing Brauselay from the analysis significance increased further (Pearson correlation coefficient = 0.60, p = 0.005; for further details, see SOM Fig. A2 and Table A6). Hence, pesticide residues on insects collected in the nature conservation areas are not only a result of applications on crops in the direct vicinity, but also from pesticide use in a larger area within the agricultural landscape around the conservation areas.Figure 2The number of CUP residues per site detected in insect/ethanol samples increased with the area of agriculture in a radius of 2000 m around the trapping positions (Pearson correlation coefficient = 0.48, p = 0.029).Full size imageBased on the correlation between pesticides and surrounding arable land, a generalized linear mixed model (GLMM) was applied to model the number of detected pesticide residues as a function of landscape factors (amount of agricultural production area, amount of nature conservation area and amount of FFH area in a 2000 m radius) and biomass of insects collected by the Malaise traps, with the study sites included as random effects (Table 3). Neither the area of the nature conservation area nor the FFH area nor biomass of collected insects was related to the number of pesticides recorded in ethanol samples. Only the agricultural production area in a 2000 m vicinity had a significant (p  More

  • in

    Spatial and temporal patterns in the sex ratio of American lobsters (Homarus americanus) in southwestern Nova Scotia, Canada

    1.Hanson, J. M. Predator-prey interactions of American lobster (Homarus americanus) in the southern Gulf of St. Lawrence, Canada. New Zeal. J. Mar. Freshw. Res. 43, 69–88 (2009).
    Google Scholar 
    2.DFO. Canada’s Fisheries Fast Facts 2019. (2020).3.Fisheries and Oceans Canada. Integrated Fishery Management Plan (Summary). Lobster fishing area 27–38. Scotia-Fundy Sector Maritimes Region 2011. DFO Report (2009).4.Howell, W. H., Watson, W. H. & Jury, S. H. Skewed sex ratio in an estuarine lobster (Homarus americanus) population. J. Shellfish Res. 18, 193–201 (1999).
    Google Scholar 
    5.Jury, S. H., Pugh, T. L., Henninger, H., Carloni, J. T. & Watson, W. H. Patterns and possible causes of skewed sex ratios in American lobster (Homarus americanus) populations. Invertebr. Reprod. Dev. https://doi.org/10.1080/07924259.2019.1595184 (2019).Article 

    Google Scholar 
    6.Ogburn, B. M. The effects of sex-biased fisheries on crustacean sex ratios and reproductive output. Invertebr. Reprod. Dev. 63, 200–207 (2019).
    Google Scholar 
    7.Cooper, R., Clifford, R. & Newelll, C. Seasonal abundance of the American lobster, Homarus americanus, in the Boothbay region of Maine. Trans. Am. Fish. Soc. 104, 669–674 (1975).
    Google Scholar 
    8.Pitnick, S. Operational sex ratios and sperm limitation in populations of Drosophila pachea. Behav. Ecol. Sociobiol. 33, 383–391 (1993).
    Google Scholar 
    9.MacDiarmid, A. B. & Butler, M. J. IV. Sperm economy and limitation in spiny lobsters. Behav. Ecol. Sociobiol. 46, 14–24 (1999).
    Google Scholar 
    10.Sato, T. Plausible causes for sperm-store variations in the coconut crab Birgus latro under large male-selective harvesting. Aquat. Biol. 13, 11–19 (2011).
    Google Scholar 
    11.Ogburn, M., Roberts, P., Richie, K., Johnson, E. & Hines, A. Temporal and spatial variation in sperm stores in mature female blue crabs Callinectes sapidus and potential effects on brood production in Chesapeake Bay. Mar. Ecol. Prog. Ser. 507, 249–262 (2014).ADS 

    Google Scholar 
    12.Pardo, L. M., Rosas, Y., Fuentes, J. P., Riveros, M. P. & Chaparro, O. R. Fishery induces sperm depletion and reduction in male reproductive potential for crab species under male-biased harvest strategy. PLoS ONE 10, e0115525 (2015).PubMed 
    PubMed Central 

    Google Scholar 
    13.Pardo, L. M. et al. High fishing intensity reduces females’ sperm reserve and brood fecundity in a eubrachyuran crab subject to sex-and size-biased harvest. ICES J. Mar. Sci. 74, 2459–2469 (2017).
    Google Scholar 
    14.Tremblay, J. M. & Smith, S. J. Lobster (Homarus americanus) catchability in different habitats in late spring and early fall. Mar. Freshw. Res. 52, 1321–1331 (2001).
    Google Scholar 
    15.Karnofsky, E., Atema, J. & RH, E. Field observations of social behavior, shelter use, and foraging in the lobster, Homarus americanus. Biol. Bull. 176, 239–246 (1989).PubMed 

    Google Scholar 
    16.Cowan, D. F., Watson, W., Solow, A. & Mountcastle, A. Thermal histories of brooding lobsters, Homarus americanus, in the Gulf of Maine. Springer 150, 463–470 (2007).
    Google Scholar 
    17.Chang, J., Chen, Y., Holland, D. & Grabowski, J. Estimating spatial distribution of American lobster Homarus americanus using habitat variables. Mar. Ecol. Prog. Ser. 420, 145–156 (2010).ADS 

    Google Scholar 
    18.Anderson, J., Olsen, Z., Wagner Glen Sutton, T., Gelpi, C. & Topping, D. Environmental drivers of the spatial and temporal distribution of spawning blue crabs Callinectes sapidus in the Western Gulf of Mexico. N. Am. J. Fish. Manag. 37, 920–934 (2017).
    Google Scholar 
    19.Crossin, G. T., Al-Ayoub, S. A., Jury, S. H., Howell, W. H. & Watson, W. H. Behavioral thermoregulation in the American lobster Homarus americanus. J. Exp. Biol. 201, 365–374 (1998).PubMed 
    CAS 

    Google Scholar 
    20.Powers, J., Lopez, G., Cerrato, R. & Dove, A. Effects of thermal stress on Long Island Sound lobsters, H. americanus. in Long Island Sound Lobster Research Initiative Working Meeting. University of Connecticut at Avery Point, Groton. (2004).21.Comeau, M. & Savoie, F. Maturity and reproductive cycle of the female American lobster, Homarus americanus, in the southern Gulf of St. Lawrence, Canada. J. Crustac. Biol. https://doi.org/10.1163/20021975-99990290 (2002).Article 

    Google Scholar 
    22.Quinn, B. K. Threshold temperatures for performance and survival of American lobster larvae: A review of current knowledge and implications to modeling impacts of climate change. Fish. Res. 186, 383–396 (2017).
    Google Scholar 
    23.Campbell, A. & Stasko, A. Movement of lobsters (Homarus americanus) tagged in the Bay of Fundy, Canada. Mar. Biol. 92, 393–404 (1986).
    Google Scholar 
    24.Campbell, A. Aggregations of berried lobsters (Homarus americanus) in shallow waters off Grand Manan, eastern Canada. Can. J. Fish. Aquat. Sci. 47, 520–523 (1990).
    Google Scholar 
    25.Watson, W. & Jury, S. H. The relationship between American lobster catch, entry rate into traps and density. Taylor Fr. 9, 59–68 (2013).
    Google Scholar 
    26.Hoegh-Guldberg, O. & Bruno, J. F. The impact of climate change on the world’s marine ecosystems. Science 328, 1523–1528 (2010).ADS 
    PubMed 
    CAS 

    Google Scholar 
    27.Cheng, L. et al. Improved estimates of ocean heat content from 1960 to 2015. Sci. Adv. 3, 10 (2017).
    Google Scholar 
    28.Aiken, D. E. & Waddy, S. L. Environmental influence on recruitment of the American lobster, Homarus americanus: A perspective. Can. J. Fish. Aquat. Sci. 43, 2258–2270 (1986).
    Google Scholar 
    29.Greenan, B. J. W. et al. Climate change vulnerability of American lobster fishing communities in Atlantic Canada. Front. Mar. Sci. 6, 579 (2019).
    Google Scholar 
    30.QGIS Geographic Information System. QGIS Association. http://www.qgis.org/ (2021).31.Tveite, H. NNJoin. http://arken.nmbu.no/~havatv/gis/qgisplugins/NNJoin (2014).32.Hosmer, D. J., Lemeshow, S. & Sturdivant, R. Applied Logistic Regression (John Wiley & Sons, 2013).MATH 

    Google Scholar 
    33.Thakur, K. K. et al. Risk factors associated with soft-shelled lobsters (Homarus americanus) in southwestern Nova Scotia, Canada. FACETS 2, 15–33 (2017).
    Google Scholar 
    34.Dohoo, I., Martin, W. & Stryhn, H. Veterinary Epidemiologic Research (VER Inc., 2009).
    Google Scholar 
    35.Pezzack, D. S. et al. The American lobster Homarus americanus fishery off of south-western Nova Scotia (Lobster Fishing Area 34). Canadian Stock Assessment Secretariat Research Document 99/32 (1999).36.Watson, W. H. & Little, S. A. Differences in the size at maturity of female American lobsters, Homarus americanus, captured throughout the range of the offshore fishery. J. Crustac. Biol. 25, 585–592 (2005).
    Google Scholar 
    37.Pezzack, D., Tremblay, J., Claytor, R., Frail, C. & Smith, S. Stock status and indicators for the lobster fishery in Lobster Fishing Area 34. Canadian Stock Assessment Secretariat Research Document 2006/101 (2006).38.Wu, Y. & Tang, C. Atlas of ocean currents in eastern Canadian waters. Canadian Technical Report of Hydrography and Ocean Sciences. 271 (2011).39.Brickman, D. Could ocean currents be responsible for the west to east spread of aquatic invasive species in Maritime Canadian waters?. Mar. Pollut. Bull. 85, 235–243 (2014).PubMed 
    CAS 

    Google Scholar 
    40.Cowan, D. F., Solow, A. & Beet, A. R. Patterns in abundance and growth of juvenile lobster Homarus americanus. CSIRO https://doi.org/10.1071/MF01191 (2001).Article 

    Google Scholar 
    41.Morse, B. L., Quinn, B. K., Comeau, M. & Rochette, R. Stock structure and connectivity of the American lobster (Homarus americanus) in the southern Gulf of St. Lawrence: Do benthic movements matter?. Can. J. Fish. Aquat. Sci. 75, 2096–2108 (2018).
    Google Scholar 
    42.Staples, K. W., Chen, Y., Townsend, D. W. & Brady, D. C. Spatiotemporal variability in the phenology of the initial intra-annual molt of American lobster (Homarus americanus Milne Edwards, 1837) and its relationship with bottom temperatures in a changing Gulf of Maine. Fish. Oceanogr. 28, 468–485 (2019).
    Google Scholar 
    43.Goñi, R., Quetglas, A. & Reñones, O. Differential catchability of male and female European spiny lobster Palinurus elephas (Fabricius, 1787) in traps and trammelnets. Fish. Res. 65, 295–307 (2003).
    Google Scholar 
    44.Audet, D., Miron, G. & Moriyasu, M. Biological characteristics of a newly established green crab (Carcinus maenas) population in the southern gulf of St. Lawrence, Canada. J. Shellfish Res. 27, 427–441 (2008).
    Google Scholar 
    45.Laurans, M., Fifas, S., Demaneche, S., Brérette, S. & Debec, O. Modelling seasonal and annual variation in size at functional maturity in the European lobster (Homarus gammarus) from self-sampling data. ICES J. Mar. Sci. 66, 1892–1898 (2009).
    Google Scholar 
    46.Cooper, R. & Uzmann, J. Migrations and growth of deep-sea lobsters, Homarus americanus. Science 171, 288–290 (1971).ADS 
    PubMed 
    CAS 

    Google Scholar 
    47.Robichaud, D. A. & Campbell, A. Annual and seasonal size-frequency changes of trap-caught lobsters (Homarus americanus) in the Bay of Fundy. J. Northw. Atl. Fish. Sci 11, 2 (1991).
    Google Scholar 
    48.Waddy, S. L. & Aiken, D. E. Seasonal variation in spawning by preovigerous American lobster (Homarus americanus) in response to temperature and photoperiod manipulation. Can. J. Fish. Aquat. Sci. 49, 1114–1117 (1992).
    Google Scholar 
    49.Campbell, A. & Stasko, A. B. Movements of lobsters (Homarus americanus) tagged in the Bay of Fundy, Canada. Mar. Biol. Int. J. Life Ocean. Coast. Waters 92, 393–404 (1986).
    Google Scholar 
    50.Haakonsen, H. & Anoruo, A. Tagging and migration of the American lobster Homarus americanus. Rev. Fish. Sci. 2, 79–93 (1994).
    Google Scholar 
    51.Lawton, P. & Lavalli, K. Postlarval, juvenile, adolescent and adult ecology. In Biology of the lobster Homarus americanus (ed. Jd, F.) 47–81 (Academic, 1995).
    Google Scholar 
    52.Attard, J. & Hudon, C. Embryonic development and energetic investment in egg production in relation to size of female lobster (Homarus americanus). Can. J. Fish. Aquat. Sci. 44, 1157–1164 (1987).
    Google Scholar 
    53.Krouse, J. Maturity, sex ratio, and size composition of the natural population of American lobster, Homarus americanus, along the Maine coast. Fish. Bull. 71, 165–173 (1973).
    Google Scholar 
    54.Sato, T. Impacts of large male-selective harvesting on reproduction: Illustration with large decapod crustacean resources. Aqua-BioSci. Monogr. 5, 67–102 (2012).CAS 

    Google Scholar 
    55.Raymond, S. M. C. & Todd, C. R. Assessing risks to threatened crayfish populations from sex-based harvesting and differential encounter rates: A new indicator for reproductive state. Ecol. Indic. 118, 106661 (2020).
    Google Scholar 
    56.Estrella, B. & McKiernan, D. Catch-Per-Unit-Effort and Biological Parameters from the Massachusetts Coastal Lobster (Homarus americanus) Resource: Description and Trends (NOAA Technical Report, 1989).
    Google Scholar 
    57.Smolowitz, R., Chistoserdov, A. Y. & Hsu, A. A description of the pathology epizootic shell disease in the American lobster (Homarus americanus) H. Milne Edwards 1837. J. Shellfish Res. 24, 749–756 (2005).
    Google Scholar 
    58.Glenn, R. & Pugh, T. Epizootic shell disease in American lobster (Homarus americanus) in Massachusetts coastal waters: Interactions of temperature, maturity, and intermolt duration. J. Crustac. Biol. 26, 639–645 (2006).
    Google Scholar 
    59.Chistoserdov, A., Quinn, R., Gubbala, S. & Smolowitz, R. Bacterial communities associated with lesions of shell disease in the American lobster Homarus americanus. J. Shellfish Res. 31, 449–462 (2012).
    Google Scholar 
    60.Meres, N. et al. Dysbiosis in epizootic shell disease of the American lobster (Homarus americanus). J. Shellfish Res. 31, 463–472 (2012).
    Google Scholar 
    61.Shields, J. D., Wheeler, K. N. & Moss, J. A. Histological assessment of the lobster (Homarus americanus) in the ‘100 Lobsters’ project. J. Shellfish Res. 31, 439–447 (2012).
    Google Scholar 
    62.Hoenig, J. M. et al. Impact of disease on the survival of three commercially fished species. Ecol. Appl. 27, 2116–2127 (2017).PubMed 

    Google Scholar 
    63.Stevens, B. Effects of epizootic shell disease in American lobster Homarus americanus determined using a quantitative disease index. Dis. Aquat. Organ. 88, 25–34 (2009).PubMed 

    Google Scholar 
    64.Clark, A. S., Jury, S. H., Goldstein, J. S., Langley, T. G. & Watson, W. H. A comparison of American lobster size structure and abundance using standard and ventless traps. Fish. Res. 167, 243–251 (2015).
    Google Scholar 
    65.Jury, S., Kinnison, M., Howell, W., Winsor, H. & Watson, I. The behavior of lobsters in response to reduced salinity. J. Exp. Mar. Biol. Ecol. 180, 23–37 (1994).
    Google Scholar  More